diet research paper

• - Google Chrome

Intended for healthcare professionals

• Access provided by Google Indexer
• My email alerts
• BMA member login
• Username * Password * Forgot your log in details? Need to activate BMA Member Log In Log in via OpenAthens Log in via your institution

Search form

• Advanced search
• Search responses
• Search blogs
• News & Views
• Dietary and...

Dietary and nutritional approaches for prevention and management of type 2 diabetes

Food for thought, click here to read other articles in this collection.

• Related content
• Peer review
• Nita G Forouhi , professor 1 ,
• Anoop Misra , professor 2 ,
• Viswanathan Mohan , professor 3 ,
• Roy Taylor , professor 4 ,
• William Yancy , director 5 6 7
• 1 MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
• 2 Fortis-C-DOC Centre of Excellence for Diabetes, Metabolic Diseases and Endocrinology, and National Diabetes, Obesity and Cholesterol Foundation, New Delhi, India
• 3 Dr Mohan’s Diabetes Specialities Centre and Madras Diabetes Research Foundation, Chennai, India
• 4 Magnetic Resonance Centre, Institute of Cellular Medicine, Newcastle University, Newcastle, UK
• 5 Duke University Diet and Fitness Center, Durham, North Carolina, USA
• 6 Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
• 7 Center for Health Services Research in Primary Care, Department of Veterans Affairs, Durham, North Carolina, USA
• Correspondence to: N G Forouhi nita.forouhi{at}mrc-epid.cam.ac.uk

Common ground on dietary approaches for the prevention, management, and potential remission of type 2 diabetes can be found, argue Nita G Forouhi and colleagues

Dietary factors are of paramount importance in the management and prevention of type 2 diabetes. Despite progress in formulating evidence based dietary guidance, controversy and confusion remain. In this article, we examine the evidence for areas of consensus as well as ongoing uncertainty or controversy about dietary guidelines for type 2 diabetes. What is the best dietary approach? Is it possible to achieve remission of type 2 diabetes with lifestyle behaviour changes or is it inevitably a condition causing progressive health decline? We also examine the influence of nutrition transition and population specific factors in the global context and discuss future directions for effective dietary and nutritional approaches to manage type 2 diabetes and their implementation.

Why dietary management matters but is difficult to implement

Diabetes is one of the biggest global public health problems: the prevalence is estimated to increase from 425 million people in 2017 to 629 million by 2045, with linked health, social, and economic costs. 1 Urgent solutions for slowing, or even reversing, this trend are needed, especially from investment in modifiable factors including diet, physical activity, and weight. Diet is a leading contributor to morbidity and mortality worldwide according to the Global Burden of Disease Study carried out in 188 countries. 2 The importance of nutrition in the management and prevention of type 2 diabetes through its effect on weight and metabolic control is clear. However, nutrition is also one of the most controversial and difficult aspects of the management of type 2 diabetes.

The idea of being on a “diet” for a chronic lifelong condition like diabetes is enough to put many people off as knowing what to eat and maintaining an optimal eating pattern are challenging. Medical nutrition therapy was introduced to guide a systematic and evidence based approach to the management of diabetes through diet, and its effectiveness has been demonstrated, 3 but difficulties remain. Although most diabetes guidelines recommend starting pharmacotherapy only after first making nutritional and physical activity lifestyle changes, this is not always followed in practice globally. Most physicians are not trained in nutrition interventions and this is a barrier to counselling patients. 4 5 Moreover, talking to patients about nutrition is time consuming. In many settings, outside of specialised diabetes centres where trained nutritionists/educators are available, advice on nutrition for diabetes is, at best, a printed menu given to the patient. In resource poor settings, when type 2 diabetes is diagnosed, often the patient leaves the clinic with a list of new medications and little else. There is wide variation in the use of dietary modification alone to manage type 2 diabetes: for instance, estimates of fewer than 5-10% of patients with type 2 diabetes in India 6 and 31% in the UK are reported, although patients treated by lifestyle measures may be less closely managed than patients on medication for type 2 diabetes. 7 Although systems are usually in place to record and monitor process measures for diabetes care in medical records, dietary information is often neglected, even though at least modest attention to diet is needed to achieve adequate glycaemic control. Family doctors and hospital clinics should collect this information routinely but how to do this is a challenge. 5 8

Progress has been made in understanding the best dietary advice for diabetes but broader problems exist. For instance, increasing vegetable and fruit intake is recommended by most dietary guidelines but their cost is prohibitively high in many settings: the cost of two servings of fruits and three servings of vegetables a day per individual (to fulfil the “5-a-day” guidance) accounted for 52%, 18%, 16%, and 2% of household income in low, low to middle, upper to middle, and high income countries, respectively. 9 An expensive market of foods labelled for use by people with diabetes also exists, with products often being no healthier, and sometimes less healthy, than regular foods. After new European Union legislation, food regulations in some countries, including the UK, were updated as recently as July 2016 to ban such misleading labels. This is not the case elsewhere, however, and what will happen to such regulation after the UK leaves the European Union is unclear, which highlights the importance of the political environment.

Evidence for current dietary guidelines

In some, mostly developed, countries, dietary guidelines for the management of diabetes have evolved from a focus on a low fat diet to the recognition that more important considerations are macronutrient quality (that is, the type versus the quantity of macronutrient), avoidance of processed foods (particularly processed starches and sugars), and overall dietary patterns. Many systematic reviews and national dietary guidelines have evaluated the evidence for optimal dietary advice, and we will not repeat the evidence review. 10 11 12 13 14 15 16 17 18 We focus instead in the following sections on some important principles where broad consensus exists in the scientific and clinical community and highlight areas of uncertainty, but we begin by outlining three underpinning features.

Firstly, an understanding of healthy eating for the prevention and management of type 2 diabetes has largely been derived from long term prospective studies and limited evidence from randomised controlled trials in general populations, supplemented by evidence from people with type 2 diabetes. Many published guidelines and reviews have applied grading criteria and this evidence is often of moderate quality in the hierarchy of evidence that places randomised controlled trials at the top. Elsewhere, it is argued that different forms of evidence evaluating consistency across multiple study designs including large population based prospective studies of clinical endpoints, controlled trials of intermediate pathways, and where feasible randomised trials of clinical endpoints should be used collectively for evidence based nutritional guidance. 19

Secondly, it is now recognised that dietary advice for both the prevention and management of type 2 diabetes should converge, and they should not be treated as different entities ( fig 1 ). However, in those with type 2 diabetes, the degree of glycaemic control and type and dose of diabetes medication should be coordinated with dietary intake. 12 With some dietary interventions, such as very low calorie or low carbohydrate diets, people with diabetes would usually stop or reduce their diabetes medication and be monitored closely, as reviewed in a later section.

Dietary advice for different populations for the prevention and management of type 2 diabetes

• Download figure
• Open in new tab
• Download powerpoint

Thirdly, while recognising the importance of diet for weight management, there is now greater understanding 10 of the multiple pathways through which dietary factors exert health effects through both obesity dependent and obesity independent mechanisms. The influence of diet on weight, glycaemia, and glucose-insulin homeostasis is directly relevant to glycaemic control in diabetes, while other outcomes such as cardiovascular complications are further influenced by the effect of diet on blood lipids, apolipoproteins, blood pressure, endothelial function, thrombosis, coagulation, systemic inflammation, and vascular adhesion. The effect of food and nutrients on the gut microbiome may also be relevant to the pathogenesis of diabetes but further research is needed. Therefore, diet quality and quantity over the longer term are relevant to the prevention and management of diabetes and its complications through a wide range of metabolic and physiological processes.

Areas of consensus in guidelines

Weight management.

Type 2 diabetes is most commonly associated with overweight or obesity and insulin resistance. Therefore, reducing weight and maintaining a healthy weight is a core part of clinical management. Weight loss is also linked to improvements in glycaemia, blood pressure, and lipids and hence can delay or prevent complications, particularly cardiovascular events.

Energy balance

Most guidelines recommend promoting weight loss among overweight or obese individuals by reducing energy intake. Portion control is one strategy to limit energy intake together with a healthy eating pattern that focuses on a diet composed of whole or unprocessed foods combined with physical activity and ongoing support.

Dietary patterns

The evidence points to promoting patterns of food intake that are high in vegetables, fruit, whole grains, legumes, nuts, and dairy products such as yoghurt but with some cautions. Firstly, some dietary approaches (eg, low carbohydrate diets) recommend restricting the intake of fruits, whole grains, and legumes because of their sugar or starch content. For fruit intake, particularly among those with diabetes, opinion is divided among scientists and clinicians (see appendix on bmj.com). Many guidelines continue to recommend fruit, however, on the basis that fructose intake from fruits is preferable to isocaloric intake of sucrose or starch because of the additional micronutrient, phytochemical, and fibre content of fruit. Secondly, despite evidence from randomised controlled trials and prospective studies 10 that nuts may help prevent type 2 diabetes, some (potentially misplaced) concern exists about their high energy content. Further research in people with type 2 diabetes should help to clarify this.

There is also consensus on the benefits of certain named dietary patterns such as the Mediterranean diet for prevention and management of type 2 diabetes. Expert guidelines also support other healthy eating patterns that take account of local sociocultural factors and personal preferences.

Foods to avoid

Consensus exists on reducing or avoiding the intake of processed red meats, refined grains and sugars (especially sugar sweetened drinks) both for prevention and management of type 2 diabetes, again with some cautions. Firstly, for unprocessed red meat, the evidence of possible harm because of the development of type 2 diabetes is less consistent and of a smaller magnitude. More research is needed on specific benefits or harms in people with type 2 diabetes. Secondly, evidence is increasing on the relevance of carbohydrate quality: that is that whole grains and fibre are better choices than refined grains and that fibre intake should be at least as high in people with type 2 diabetes as recommended for the general population, that diets that have a higher glycaemic index and load are associated with an increased risk of type 2 diabetes, and that there is a modest glycaemic benefit in replacing foods with higher glycaemic load with foods with low glycaemic load. However, debate continues about the independence of these effects from the intake of dietary fibre. Some evidence exists that consumption of potato and white rice may increase the risk of type 2 diabetes but this is limited and further research is needed.

Moreover, many guidelines also highlight the importance of reducing the intake of in foods high in sodium and trans fat because of the relevance of these specifically for cardiovascular health.

Areas of uncertainty in guidelines

Optimal macronutrient composition.

One of the most contentious issues about the management of type 2 diabetes has been on the best macronutrient composition of the diet. Some guidelines continue to advise macronutrient quantity goals, such as the European or Canadian recommendation of 45–60% of total energy as carbohydrate, 10–20% as protein, and less than 35% as fat, 13 20 or the Indian guidelines that recommend 50-60% energy from carbohydrates, 10-15% from protein, and less than 30% from fat. 21 In contrast, the most recent nutritional guideline from the American Diabetes Association concluded that there is no ideal mix of macronutrients for all people with diabetes and recommended individually tailored goals. 12 Alternatively, a low carbohydrate diet for weight and glycaemic control has gained popularity among some experts, clinicians, and the public (reviewed in a later section). Others conclude that a low carbohydrate diet combined with low saturated fat intake is best. 22

For weight loss, three points are noteworthy when comparing dietary macronutrient composition. Firstly, evidence from trials points to potentially greater benefits from a low carbohydrate than a low fat diet but the difference in weight loss between diets is modest. 23 Secondly, a comparison of named diet programmes with different macronutrient composition highlighted that the critical factor in effectiveness for weight loss was the level of adherence to the diet over time. 24 Thirdly, the quality of the diet in low carbohydrate or low fat diets is important. 25 26

Research to date on weight or metabolic outcomes in diabetes is complicated by the use of different definitions for the different macronutrient approaches. For instance, the definition of a low carbohydrate diet has ranged from 4% of daily energy intake from carbohydrates (promoting nutritional ketosis) to 40%. 15 Similarly, low fat diets have been defined as fat intake less than 30% of daily energy intake or substantially lower. Given these limitations, the best current approach may be an emphasis on the use of individual assessment for dietary advice and a focus on the pattern of eating that most readily allows the individual to limit calorie intake and improve macronutrient quality (such as avoiding refined carbohydrates).

Regular fish intake of at least two servings a week, including one serving of oily fish (eg, salmon, mackerel, and trout) is recommended for cardiovascular risk prevention but fish intake has different associations with the risk of developing type 2 diabetes across the world—an inverse association, no association, and a positive association. 27 It is thought that the type of fish consumed, preparation or cooking practices, and possible contaminants (eg, methyl mercury and polychlorinated biphenyls) vary by geographical location and contributed to this heterogeneity. More research is needed to resolve whether fish intake should be recommended for the prevention of diabetes. However, the current evidence supports an increase in consumption of oily fish for individuals with diabetes because of its beneficial effects on lipoproteins and prevention of coronary heart disease. Most guidelines agree that omega 3 polyunsaturated fatty acid (fish oil) supplementation for cardiovascular prevention in people with diabetes should not be recommended but more research is needed and the results of the ASCEND (A Study of Cardiovascular Events in Diabetes) trial should help to clarify this. 28

Dairy foods are encouraged for the prevention of type 2 diabetes, with more consistent evidence of the benefits of fermented dairy products, such as yoghurt. Similar to population level recommendations about limiting the intake of foods high in saturated fats and replacing them with foods rich in polyunsaturated fat, the current advice for diabetes also favours low fat dairy products but this is debated. More research is needed to resolve this question.

Uncertainty continues about certain plant oils and tropical oils such as coconut or palm oil as evidence from prospective studies or randomised controlled trials on clinical events is sparse or non-existent. However, olive oil, particularly extra virgin olive oil, has been studied in greater detail with evidence of potential benefits for the prevention and management of type 2 diabetes 29 and the prevention of cardiovascular disease within the context of a Mediterranean diet 30 (see article in this series on dietary fats). 31

Difficulties in setting guidelines

Where dietary guidelines exist (in many settings there are none, or they are adapted from those in developed countries and therefore may not be applicable to the local situation), they vary substantially in whether they are evidence based or opinion pieces, and updated in line with scientific progress or outdated. Their accessibility—both physical availability (eg, through a website or clinic) and comprehensibility— for patients and healthcare professionals varies. They vary also in scope, content, detail, and emphasis on the importance of individualised dietary advice, areas of controversy, and further research needs. The quality of research that informs dietary guidelines also needs greater investment from the scientific community and funders. Moreover, lack of transparency in the development of guidelines and bias in the primary nutritional studies can undermine the development of reliable dietary guidelines; recommendations for their improvement must be heeded. 32

Reversing type 2 diabetes through diet

Type 2 diabetes was once thought to be irreversible and progressive after diagnosis, but much interest has arisen about the potential for remission. Consensus on the definition of remission is a sign of progress: glucose levels lower than the diagnostic level for diabetes in the absence of medications for hyperglycaemia for a period of time (often proposed to be at least one year). 33 34 However, the predominant role of energy deficit versus macronutrient composition of the diet in achieving remission is still controversial.

Remission through a low calorie energy deficit diet

Although the clinical observation of the lifelong, steadily progressive nature of type 2 diabetes was confirmed by the UK Prospective Diabetes Study, 35 rapid normalisation of fasting plasma glucose after bariatric surgery suggested that deterioration was not inevitable. 36 As the main change was one of sudden calorie restriction, a low calorie diet was used as a tool to study the mechanisms involved. In one study of patients with type 2 diabetes, fasting plasma glucose normalised within seven days of following a low calorie diet. 37 This normalisation through diet occurred despite simultaneous withdrawal of metformin therapy. Gradually over eight weeks, glucose stimulated insulin secretion returned to normal. 37 Was this a consequence of calorie restriction or composition of the diet? To achieve the degree of weight loss obtained (15 kg), about 610 kcal a day was provided—510 kcal as a liquid formula diet and about 100 kcal as non-starchy vegetables. The formula diet consisted of 59 g of carbohydrate (30 g as sugars), 11.4 g of fat, and 41 g of protein, including required vitamins and minerals. This high “sugar” approach to controlling blood glucose may be surprising but the critical aspect is not what is eaten but the gap between energy required and taken in. Because of this deficit, the body must use previously stored energy. Intrahepatic fat is used first, and the 30% decrease in hepatic fat in the first seven days appears sufficient to normalise the insulin sensitivity of the liver. 37 In addition, pancreatic fat content fell over eight weeks and beta cell function improved. This is because insulin secretory function was regained by re-differentiation after fat removal. 38

The permanence of these changes was tested by a nutritional and behavioural approach to achieve long term isocaloric eating after the acute weight loss phase. 39 It was successful in keeping weight steady over the next six months of the study. Calorie restriction was associated with both hepatic and pancreatic fat content remaining at the low levels achieved. The initial remission of type 2 diabetes was closely associated with duration of diabetes, and the individuals with type 2 diabetes of shorter duration who achieved normal levels of blood glucose maintained normal physiology during the six month follow-up period. Recently, 46% of a UK primary care cohort remained free of diabetes at one year during a structured low calorie weight loss programme (the DiRECT trial). 40 These results are convincing, and four years of follow-up are planned.

A common criticism of the energy deficit research has been that very low calorie diets may not be achievable or sustainable. Indeed, adherence to most diets in the longer term is an important challenge. 24 However, Look-AHEAD, the largest randomised study of lifestyle interventions in type 2 diabetes (n=5145), randomised individuals to intensive lifestyle management, including the goal to reduce total calorie intake to 1200-1800 kcal/d through a low fat diet assisted by liquid meal replacements, and this approach achieved greater weight loss and non-diabetic blood glucose levels at year 1 and year 4 in the intervention than the control group. 41

Considerable interest has arisen about whether low calorie diets associated with diabetes remission can also help to prevent diabetic complications. Evidence is sparse because of the lack of long term follow-up studies but the existing research is promising. A return to the non-diabetic state brings an improvement in cardiovascular risk (Q risk decreasing from 19.8% to 5.4%) 39 ; case reports of individuals facing foot amputation record a return to a low risk state over 2-4 years with resolution of painful neuropathy 42 43 ; and retinal complications are unlikely to occur or progress. 44 However, other evidence highlights that worsening of treatable maculopathy or proliferative retinopathy may occur following a sudden fall in plasma glucose levels, 45 46 so retinal imaging in 4-6 months is recommended for individuals with more than minimal retinopathy if following a low calorie remission diet. Annual review is recommended for all those in the post-diabetic state, and a “diabetes in remission” code (C10P) is now available in the UK. 34

Management or remission through a low carbohydrate diet

Before insulin was developed as a therapy, reducing carbohydrate intake was the main treatment for diabetes. 47 48 Carbohydrate restriction for the treatment of type 2 diabetes has been an area of intense interest because, of all the macronutrients, carbohydrates have the greatest effect on blood glucose and insulin levels. 49

In a review by the American Diabetes Association, interventions of low carbohydrate (less than 40% of calories) diets published from 2001 to 2010 were identified. 15 Of 11 trials, eight were randomised and about half reported greater improvement in HbA1c on the low carbohydrate diet than the comparison diet (usually a low fat diet), and a greater reduction in the use of medicines to lower glucose. Notably, calorie reduction coincided with carbohydrate restriction in many of the studies, even though it was not often specified in the dietary counselling. One of the more highly controlled studies was an inpatient feeding study, 50 which reported a decline in mean HbA1c from 7.3% to 6.8% (P=0.006) over just 14 days on a low carbohydrate diet.

For glycaemia, other reviews of evidence from randomised trials on people with type 2 diabetes have varying conclusions. 51 52 53 54 55 56 Some concluded that low carbohydrate diets were superior to other diets for glycaemic control, or that a dose response relationship existed, with stricter low carbohydrate restriction resulting in greater reductions in glycaemia. Others cautioned about short term beneficial effects not being sustained in the longer term, or found no overall advantage over the comparison diet. Narrative reviews have generally been more emphatic on the benefits of low carbohydrate diets, including increased satiety, and highlight the advantages for weight loss and metabolic parameters. 57 58 More recently, a one year clinic based study of the low carbohydrate diet designed to induce nutritional ketosis (usually with carbohydrate intake less than 30 g/d) was effective for weight loss, and for glycaemic control and medication reduction. 59 However, the study was not randomised, treatment intensity differed substantially in the intervention versus usual care groups, and participants were able to select their group.

Concerns about potential detrimental effects on cardiovascular health have been raised as low carbohydrate diets are usually high in dietary fat, including saturated fat. For lipid markers as predictors of future cardiovascular events, several studies found greater improvements in high density lipoprotein cholesterol and triglycerides with no relative worsening of low density lipoprotein cholesterol in patients with type 2 diabetes following carbohydrate restriction, 15 with similar conclusions in non-diabetic populations. 57 60 61 62 Low density lipoprotein cholesterol tends to decline more, however, in a low fat comparison diet 61 63 and although low density lipoprotein cholesterol may not worsen with a low carbohydrate diet 63 in the short term, the longer term effects are unclear. Evidence shows that low carbohydrate intake can lower the more atherogenic small, dense low density lipoprotein particles. 57 64 Because some individuals may experience an increase in serum low density lipoprotein cholesterol when following a low carbohydrate diet high in saturated fat, monitoring is important.

Another concern is the effect of the potentially higher protein content of low carbohydrate diets on renal function. Evidence from patients with type 2 diabetes with normal baseline renal function and from individuals without diabetes and with normal or mildly impaired renal function has not shown worsening renal function at one or up to two years of follow-up, respectively. 22 65 66 67 Research in patients with more severely impaired renal function, with or without diabetes, has not been reported to our knowledge. Other potential side effects of a very low carbohydrate diet include headache, fatigue, and muscle cramping but these side effects can be avoided by adequate fluid and sodium intake, particularly in the first week or two after starting the diet when diuresis is greatest. Concern about urinary calcium loss and a possible contribution to increased future risk of kidney stones or osteoporosis 68 have not been verified 69 but evidence is sparse and warrants further investigation. The long term effects on cardiovascular disease and chronic kidney disease in patients with diabetes need further evaluation.

Given the hypoglycaemic effect of carbohydrate restriction, patients with diabetes who adopt low carbohydrate diets and their clinicians must understand how to avoid hypoglycaemia by appropriately reducing glucose lowering medications. Finally, low carbohydrate diets can restrict whole grain intake and although some low carbohydrate foods can provide the fibre and micronutrients contained in grains, it may require greater effort to incorporate such foods. This has led some experts to emphasise restricting refined starches and sugars but retaining whole grains.

Nutrition transition and population specific factors

Several countries in sub-Saharan Africa, South America, and Asia (eg, India and China) have undergone rapid nutrition transition in the past two decades. These changes have paralleled economic growth, foreign investment in the fast food industry, urbanisation, direct-to-consumer marketing of foods high in calories, sale of ultraprocessed foods, and as a result, lower consumption of traditional diets. The effect of these factors on nutrition have led to obesity and type 2 diabetes on the one hand, and co-existing undernutrition and micronutrient deficiencies on the other.

Dietary shifts in low and middle income countries have been stark: in India, these include a substantial increase in fat intake in the setting of an already high carbohydrate intake, with a slight increase in total energy and protein, 70 and a decreasing intake of coarse cereals, pulses, fruits, and vegetables 71 ; in China, animal protein and fat as a percentage of energy has also increased, while cereal intake has decreased. 72 An almost universal increase in the intake of caloric beverages has also occurred, with sugar sweetened soda drinks being the main beverage contributing to energy intake, for example among adults and children in Mexico, 73 or the substantial rise in China in sales of sugar sweetened drinks from 10.2 L per capita in 1998 to 55.0 L per capita in 2012. 74 The movement of populations from rural to urban areas within a country may also be linked with shifts in diets to more unhealthy patterns, 75 while acculturation of immigrant populations into their host countries also results in dietary shifts. 76

In some populations, such as South Asians, rice and wheat flour bread are staple foods, with a related high carbohydrate intake (60-70% of calories). 77 Although time trends show that intake of carbohydrate has decreased among South Asian Indians, the quality of carbohydrates has shifted towards use of refined carbohydrates. 71 The use of oils and traditional cooking practices also have specific patterns in different populations. For instance, in India, the import and consumption of palm oil, often incorporated in the popular oil vanaspati (partially hydrogenated vegetable oil, high in trans fats), is high. 78 Moreover, the traditional Indian cooking practice of frying at high temperatures and re-heating increases trans fatty acids in oils. 79 Such oils are low cost, readily available, and have a long shelf life, and thus are more attractive to people from the middle and low socioeconomic strata but their long term effects on type 2 diabetes are unknown.

Despite the nutrition transition being linked to an increasing prevalence of type 2 diabetes, obesity and other non-communicable diseases, strong measures to limit harmful foods are not in place in many countries. Regulatory frameworks including fiscal policies such as taxation for sugar sweetened beverages need to be strengthened to be effective and other preventive interventions need to be properly implemented. Efforts to control trans fatty acids in foods have gained momentum but are largely confined to developed countries. To reduce consumption in low and middle income countries will require both stringent regulations and the availability and development of alternative choices of healthy and low cost oils, ready made food products, and consumer education. 80 The need for nutritional labelling is important but understanding nutrition labels is a problem in populations with low literacy or nutrition awareness, which highlights the need for educational activities and simpler forms of labelling. The role of dietary/nutritional factors in the predisposition of some ethnic groups to developing type 2 diabetes at substantially lower levels of obesity than European populations 81 is poorly researched and needs investigation.

Despite the challenges of nutritional research, considerable progress has been made in formulating evidence based dietary guidance and some common principles can be agreed that should be helpful to clinicians, patients, and the public. Several areas of uncertainty and controversy remain and further research is needed to resolve these. While adherence to dietary advice is an important challenge, weight management is still a cornerstone in diabetes management, supplemented with new developments, including the potential for the remission of type 2 diabetes through diet.

Future directions

Nutritional research is difficult. Although much progress has been made to improve evidence based dietary guidelines, more investment is needed in good quality research with a greater focus on overcoming the limitations of existing research. Experts should also strive to build consensus using research evidence based on a combination of different study designs, including randomised experiments and prospective observational studies

High quality research is needed that compares calorie restriction and carbohydrate restriction to assess effectiveness and feasibility in the long term. Consensus is needed on definitions of low carbohydrate nutrition. Use of the findings must take account of individual preferences, whole diets, and eating patterns

Further research is needed to resolve areas of uncertainty about dietary advice in diabetes, including the role of nuts, fruits, legumes, fish, plant oils, low fat versus high fat dairy, and diet quantity and quality

Given recent widespread recommendations (such as from the World Health Organization 82 and the UK Scientific Advisory Committee on Nutrition 83 ) to reduce free sugars to under 10% or even 5% of total energy intake in the general population and to avoid sugar sweetened drinks, we need targeted research on the effect of non-nutritive sweeteners on health outcomes in people with diabetes and in the whole population

Most dietary guidelines are derived from evidence from Western countries. Research is needed to better understand the specific aetiological factors that link diet/nutrition and diabetes and its complications in different regions and different ethnic groups. This requires investment in developing prospective cohorts and building capacity to undertake research in low and middle income settings and in immigrant ethnic groups. Up-to-date, evidence based dietary guidelines are needed that are locally relevant and readily accessible to healthcare professionals, patients, and the public in different regions of the world. Greater understanding is also needed about the dietary determinants of type 2 diabetes and its complications at younger ages and in those with lower body mass index in some ethnic groups

We need investment in medical education to train medical students and physicians in lifestyle interventions, including incorporating nutrition education in medical curricula

Individual, collective, and upstream factors are important. Issuing dietary guidance does not ensure its adoption or implementation. Research is needed to understand the individual and societal drivers of and barriers to healthy eating. Educating and empowering individuals to make better dietary choices is an important strategy; in particular, the social aspects of eating need attention as most people eat in family or social groups and counselling needs to take this into account. Equally important is tackling the wider determinants of individual behaviour—the “foodscape”, sociocultural and political factors, globalisation, and nutrition transition

Key messages

Considerable evidence supports a common set of dietary approaches for the prevention and management of type 2 diabetes, but uncertainties remain

Weight management is a cornerstone of metabolic health but diet quality is also important

Low carbohydrate diets as the preferred choice in type 2 diabetes is controversial. Some guidelines maintain that no single ideal percentage distribution of calories from different macronutrients (carbohydrates, fat, or protein) exists, but there are calls to review this in light of emerging evidence on the potential benefits of low carbohydrate diets for weight management and glycaemic control

The quality of carbohydrates such as refined versus whole grain sources is important and should not get lost in the debate on quantity

Recognition is increasing that the focus of dietary advice should be on foods and healthy eating patterns rather than on nutrients. Evidence supports avoiding processed foods, refined grains, processed red meats, and sugar sweetened drinks and promoting the intake of fibre, vegetables, and yoghurt. Dietary advice should be individually tailored and take into account personal, cultural, and social factors

An exciting recent development is the understanding that type 2 diabetes does not have to be a progressive condition but instead there is potential for remission with dietary intervention

Acknowledgments

We thank Sue Brown as a patient representative of Diabetes UK for her helpful comments and insight into this article.

Contributors and sources: The authors have experience and research interests in the prevention and management of type 2 diabetes (NGF, AM, VM, RT, WY), in guideline development (NGF, AM, VM, WY), and in nutritional epidemiology (NGF, VM). Sources of information for this article included published dietary guidelines or medical nutrition therapy guidelines for diabetes, and systematic reviews and primary research articles based on randomised clinical trials or prospective observational studies. All authors contributed to drafting this manuscript, with NGF taking a lead role and she is also the guarantor of the manuscript. All authors gave intellectual input to improve the manuscript and have read and approved the final version.

Competing interests: We have read and understood BMJ policy on declaration of interests and declare the following: NGF receives funding from the Medical Research Council Epidemiology Unit (MC_UU_12015/5). NGF is a member (unpaid) of the Joint SACN/NHS-England/Diabetes-UK Working Group to review the evidence on lower carbohydrate diets compared with current government advice for adults with type 2 diabetes and is a member (unpaid) of ILSI-Europe Qualitative Fat Intake Task Force Expert Group on update on health effects of different saturated fats. AM received honorarium and research funding from Herbalife and Almond Board of California. VM has received funding from Abbott Health Care for meal replacement studies, the Cashew Export Promotion Council of India, and the Almond Board of California for studies on nuts. RT has received funding from Diabetes UK for the Diabetes Remission Clinical Trial and he is a member (unpaid) of the Joint SACN/NHS-England/Diabetes-UK Working Group to review the evidence on lower carbohydrate diets compared to current government advice for adults with type 2 diabetes. WY has received funding from the Veterans Affairs for research projects examining a low carbohydrate diet in patients with diabetes.

Provenance and peer review: Commissioned, externally peer reviewed

This article is one of a series commissioned by The BMJ . Open access fees for the series were funded by Swiss Re, which had no input in to the commissioning or peer review of the articles. The BMJ thanks the series advisers, Nita Forouhi and Dariush Mozaffarian, for valuable advice and guiding selection of topics in the series.

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .

• International Diabetes Federation
• Forouzanfar MH ,
• Alexander L ,
• Anderson HR ,
• GBD 2013 Risk Factors Collaborators
• Pastors JG ,
• Warshaw H ,
• DiabCare India 2011 Study Group
• Hippisley-Cox J ,
• England CY ,
• Andrews RC ,
• Thompson JL
• Mozaffarian D
• Boucher JL ,
• Cypress M ,
• American Diabetes Association
• Dworatzek PD ,
• Gougeon R ,
• Sievenpiper JL ,
• Williams SL ,
• Canadian Diabetes Association Clinical Practice Guidelines Expert Committee
• English P ,
• Wheeler ML ,
• Dunbar SA ,
• Jaacks LM ,
• Diabetes UK Nutrition Working Group
• MacLeod J ,
• Schwingshackl L ,
• Hoffmann G ,
• Lampousi AM ,
• Mozaffarian D ,
• De Leeuw I ,
• Hermansen K ,
• Diabetes and Nutrition Study Group (DNSG) of the European Association
• National Dietary Guidelines Consensus Group
• Luscombe-Marsh ND ,
• Thompson CH ,
• Tobias DK ,
• Manson JE ,
• Ludwig DS ,
• Willett W ,
• Johnston BC ,
• Kanters S ,
• Bandayrel K ,
• Gardner CD ,
• Bersamin A ,
• Trepanowski JF ,
• Del Gobbo LC ,
• Di Giuseppe D ,
• Forouhi NG ,
• ASCEND Study Collaborative Group
• Portillo MP ,
• Romaguera D ,
• Estruch R ,
• Salas-Salvadó J ,
• PREDIMED Study Investigators
• Krauss RM ,
• Cefalu WT ,
• McCombie L ,
• Turner RC ,
• Holman RR ,
• UK Prospective Diabetes Study (UKPDS) Group
• Guidone C ,
• Valera-Mora E ,
• Hollingsworth KG ,
• Aribisala BS ,
• Mathers JC ,
• Al-Mrabeh A ,
• Leslie WS ,
• Barnes AC ,
• Wagenknecht LE ,
• Look AHEAD Research Group
• Whittington J
• Pearce IA ,
• The Kroc Collaborative Study Group
• Westman EC ,
• Yancy WS Jr . ,
• Humphreys M
• Bisschop PH ,
• De Sain-Van Der Velden MG ,
• Stellaard F ,
• Sargrad K ,
• Mozzoli M ,
• van Wyk HJ ,
• Snorgaard O ,
• Poulsen GM ,
• Andersen HK ,
• Graves DE ,
• Craven TE ,
• Lipkin EW ,
• Margolis KL
• Chaimani A ,
• Schwedhelm C ,
• Noakes TD ,
• Feinman RD ,
• Pogozelski WK ,
• Hallberg SJ ,
• McKenzie AL ,
• Williams PT ,
• de Melo IS ,
• de Oliveira SL ,
• da Rocha Ataide T
• Mansoor N ,
• Vinknes KJ ,
• Veierød MB ,
• Retterstøl K
• Santos FL ,
• Esteves SS ,
• da Costa Pereira A ,
• Sharman MJ ,
• Forsythe CE
• Friedman AN ,
• Foster GD ,
• Jesudason DR ,
• Pedersen E ,
• Brinkworth GD ,
• Buckley JD ,
• Sakhaee K ,
• Brinkley L ,
• Wycherley TP ,
• Singhal N ,
• Sivakumar B ,
• Jaiswal A ,
• Piernas C ,
• Barquera S ,
• Rivera JA ,
• Ebrahim S ,
• De Stavola B ,
• Holmboe-Ottesen G ,
• Dehghan M ,
• Rangarajan S ,
• Prospective Urban Rural Epidemiology (PURE) study investigators
• Bhardwaj S ,
• Ghosh-Jerath S
• Godsland IF ,
• Hughes AD ,
• Chaturvedi N ,
• ↵ World Health Organization. Sugars intake for adults and children. Guideline. WHO, 2015. http://www.who.int/nutrition/publications/guidelines/sugars_intake/en/
• ↵ Scientific Advisory Committee on Nutrition. SACN Carbohydrates and Health Report. Public Health England. London, 2015. https://www.gov.uk/government/publications/sacn-carbohydrates-and-health-report

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Balanced diet and daily calorie consumption: Consumer attitude during the COVID-19 pandemic from an emerging economy

Roles Conceptualization, Investigation, Methodology, Resources, Writing – review & editing

Affiliation Department of Management Sciences, Savitribai Phule Pune University, Pune, India

Roles Data curation, Formal analysis, Investigation, Validation, Visualization, Writing – original draft

Affiliation Symbiosis Centre for Management and Human Resource Development, Symbiosis International University, Pune, India

Roles Conceptualization, Funding acquisition, Supervision, Validation, Writing – review & editing

* E-mail: [email protected] , [email protected]

Affiliation Széchenyi István University, Győr, Hungary

• Ashutosh Kolte, 
• Yogesh Mahajan, 
• László Vasa

• Published: August 4, 2022
• https://doi.org/10.1371/journal.pone.0270843
• Reader Comments

This article tries to explore consumer attitudes regarding a balanced diet and daily calorie intake monitoring during the COVID-19 pandemic in India. It has become vital to boost people’s immunity because of reoccurring diseases such as COVID-19, Ebola, and other chronic diseases such as diabetes, thyroid disease, etc. Healthy diets are important for supporting immune systems and keeping track of daily calorie consumption is an accompaniment to this. The research on attitudes toward a balanced diet is reviewed in this empirical study. Researchers employed a tri-component attitude model to assess consumer attitudes about a balanced diet and to track daily calorie consumption. A sample of 400 respondents was surveyed and data were collected with a structured questionnaire. The data were analysed using the structural equation modelling technique. The majority of respondents were found to lack declarative knowledge of both a balanced diet and daily calorie consumption. The effects of the COVID-19 pandemic on consumer attitudes about a healthy diet and daily calorie intake were effectively evaluated using beliefs, affection, and intentions. The repercussions for the government and business community were discussed. This study also evaluates the usefulness of the tri-component attitude model in the Indian context.

Citation: Kolte A, Mahajan Y, Vasa L (2022) Balanced diet and daily calorie consumption: Consumer attitude during the COVID-19 pandemic from an emerging economy. PLoS ONE 17(8): e0270843. https://doi.org/10.1371/journal.pone.0270843

Editor: Petri Böckerman, University of Jyvaskyla, FINLAND

Received: December 5, 2021; Accepted: June 20, 2022; Published: August 4, 2022

Copyright: © 2022 Kolte et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

Consuming a balanced diet is an ardent task for most people in the world. Due to recurring diseases like COVID-19, Ebola, Swine flu, and chronic diseases like diabetes, hypertension, thyroid, etc., it has been increasingly necessary to improve people’s immunity. Immunity helps to fight these diseases and other ailments such as blood pressure, diabetes, thyroid, etc. Immunity can be increased by consuming a balanced diet and monitoring daily calorie consumption [ 1 ].

The impact of COVID-19 has shaken the world to its roots—globally, more than 165 million people have been infected, and there have been more than 3 million deaths as of this time [ 2 ]. More than 43 million people have been infected in India with over 521,000 deaths reported [ 2 ]. The everyday lives of people are disturbed through, for example, closure of public places like malls, gardens, cinema theatres, etc., in order to curb the spread of COVID-19. In this challenging situation, it is necessary to maintain health and improve immunity. In order to boost immunity in quarantined patients in India, properly balanced diets are provided to aid in fighting COVID-19 in addition to treatments and vaccines. Such is the effect of this pandemic that the economic growth rate of many countries has declined, and many people, globally, have lost their jobs and enterprises have ceased trading.

58 percent of the 57 million annual deaths in the world are estimated to be due to Non-Communicable Diseases (NCD); mostly related to the heart, chronic pulmonary disease, cancer, and diabetes [ 3 ]. A poor intake of fruit and vegetables, high blood pressure, high blood cholesterol levels, overweight or obesity, physical inactivity, and nicotine use are the most significant risk factors for NCD. In the next few decades, population growth and aging are expected to significantly increase in conjunction with economic transformation and resulting shifts in jobs, and environmental risk factors [ 4 ]. People suffering from the aforementioned diseases and older people are among the most vulnerable to recurring diseases like COVID-19, Ebola, etc. COVID-19 was declared a global pandemic by the World Health Organization (WHO) in 2020.

The likelihood of death due to COVID-19 is high if people already have non-communicable diseases [ 5 ]. In a developing country such as India, the risk of COVID-19 is very high. However proper consumption of a balanced diet and monitoring daily calorie intake [ 6 ] are a necessity in times of a pandemic. According to Lancet, the average Indian (urban or rural) consumes a higher amount of carbohydrates in the form of cereals ( Fig 1 ) than The Lancet commission [ 7 ] recommends. Whereas the protein consumed is significantly less than recommended by the average Indian, the daily calorie intake in both rural (2214 kcal) and urban (2169 kcal) India is less than the reference diet (2,503 kcal/capita/day), except for the wealthiest 5 percent of the population [ 8 ].

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

Source: [ 7 ]. *Quantities not mentioned for some categories as data for some individual components was in terms of number of packets/cups etc.

https://doi.org/10.1371/journal.pone.0270843.g001

In addition, there is less fruit and vegetable intake by Indians and too little unsaturated oil consumption ( Fig 2 ). With an emphasis on natural products over packaged food, a diverse diet was recommended by the EAT-Lancet committee [ 7 ].

(Source: EAT-Lancet commission) (*olive, soybean, rapeseed, sunflower, and peanut oil) Note: Whole grains refer to rice, wheat and wheat products, millet and their products, cereal products refer to maida and other refined products from cereals, palm oil refers to vanaspati, unsaturated oils refer to sunflower, groundnut and refined vegetable oils, dairy fats refer to ghee and butter.

https://doi.org/10.1371/journal.pone.0270843.g002

A population must have sound knowledge and a positive attitude towards a balanced diet and daily calorie consumption [ 9 ]. This study investigated the declarative knowledge and consumer attitude towards a balanced diet and monitoring daily calorie intake among the working population in India by using a tri-component attitude model during the COVID-19 pandemic.

2. Review of literature

Nutritional guidelines were announced during the COVID-19 epidemic emphasizing the importance of a balanced diet to sustain a well-functioning immune system and prevent or reduce chronic diseases and infections. Dietary guidelines from WHO during the COVID-19 pandemic are comparatively higher than the standard dietary recommendations by the WHO [ 10 ]. Literature shows clear evidence of an inadequate diet and the risk to health thereof [ 11 ]. Research from Boylan that linked a poor diet and a lack of physical activities together with the risk of obesity has helped create and promote recommendations to increase public health [ 11 ]. Over-consumption, lifestyle, accessibility to food and strong pressure exerted by the foodstuff industry have disrupted all elements of food consumers’ behaviour which have caused them to lose out on nutritious milestones that have been achieved by family education [ 12 , 13 ]. Consumers are not initially looking for seasonal foods, but for what seems to be the most favourable value for money. In this sense, more than ever, the need for knowledge to connect nutrition and wellbeing, to avoid nutritional and metabolic disorders, and the need for the fundamental values of a healthy diet to mainly be adopted by a new generation of customers. They have positive expectations towards quality of life and a special perception of well-being factors. Limitations brought about by pandemic, particularly, voluntary and involuntary online studying, have an essential impact on the lifestyle and health condition and became an important feature of well-being. Health is understood to depend on the diet to a large extent [ 14 ]. Many authors have stressed the importance of a balanced diet and daily calorie consumption in daily life [ 15 ]. Also, experiments have shown that a balanced diet helps to reduce weight among obese people [ 16 ]. Nutritional education among consumers helps increase awareness about a balanced diet and daily calorie intake [ 17 ].

Knowledge does not consist of a single structure but different components. JR Anderson first identified two elements of knowledge. One representing ‘to know’ and the other representing ‘to know how’. These principles are applied to the concepts of procedural and declarative knowledge in cognitive psychology. Knowledge of facts and objects is called declarative knowledge, while knowledge of performing actions is procedural knowledge [ 18 ]. Procedural knowledge is also closer to behaviour. These differences in declarative and procedural knowledge are extended in the nutrition domain [ 19 ]. Few studies have evaluated declarative knowledge [ 20 , 21 ]. In contrast, some have included concerns about procedural knowledge, typically in the form of food options or by posing a query [ 22 – 24 ]. Declarative knowledge among the population can be ascertained through the study of consumer attitudes towards a balanced diet and daily calorie consumption. Consumer attitudes and perception play an important part in the dietary behavior of an individual. Attitude plays a key role in forecasting behavior, and persuasive communications are undertaken to help people partake in healthy behaviour. Most diet awareness initiatives for subpopulations such as cardiac patients [ 22 ], adolescents [ 23 ], or young men [ 25 ] are planned and applied.

2.1 Tri-Component attitude model

Psychologists have come up with models and theories that help understand consumer attitudes; these assist in understanding consumer buying behavior [ 26 , 27 ]. Important models or theories of consumer attitudes discussed in the literature include the theory of planned behavior, tri-component attitude model, the hierarchy of effects model, theory of reasoned action, and attitude toward behaviour model. This model, regarding components of attitude and their relationships, provides varying perspectives. The tri-component attitude model is the fundamental model to study the attitude of consumers developed by [ 27 ]. The tri-component attitude model ( Fig 3 ) has three constructs: viz, cognition, affect, and conation [ 28 ] as shown in Fig 1 . Arnould [ 29 ] proposed that this model is labeled as the ABC model, with affection, beliefs, and conation as rearranged components. Cognition (understanding) of a person is the consumer’s perceptions and knowledge through understanding the related item and facts from several sources [ 28 , 30 ].

(Source: [ 28 ]).

https://doi.org/10.1371/journal.pone.0270843.g003

The conative component, the way the attitude we have influences how we act or behave, describes the intention to buy or follow, which is also known as behavioural intention. Some explanations consider conation as the behaviour itself [ 28 ]. However, Assael [ 30 ] conflicts with this view. He asserts that the beliefs and assessments of a specific item sometimes need not change the intention of consumers to purchase or follow, especially if economic incentives are sufficient; such as a sharp price decrease. In developing a marketing strategy [ 31 ], it is essential to measure behavioral intention. Studies have been carried out regarding dietary behavior during normal times but such studies during the COVID-19 pandemic have not been carried out. For instance, Popescu and co-authors undertook exploratory research based on the methodology of the food diary by evaluating the features of Romanian food consumption for the next decade. Investigators analyzed the respondent’s diet’s medium energy use and macronutrients to identify possible dietary imbalances [ 13 ]. Consumers’ healthy eating choices are strongly linked to epistemic and emotional values [ 32 ].

In Mexico, Carrete researched the perception of drivers and inhibitors of sound dietary behaviors, with attention paid to serious problems with obesity [ 33 ]. The theoretical basis for this research was the theory of planned behavior (TPB) and protection motivation theory (PMT). Results show that poor self-efficacy and high costs inhibit behavioral change [ 33 ]. Sanusi studied the dietary behavior of university students and noticed that attitudes toward behavior was found to be the more influential predictor of intention to use dietary guidelines in Malaysia [ 34 ]. Worsley concluded that nutritional knowledge is a necessary factor in improving customer behavior, but it is not adequate. For nutritional promoters, the interplay of motivational and information processing factors and the distinction between declaratory and procedural knowledge is essential [ 19 , 35 ]. Additionally, research on monitoring daily calorie intake has shown positive results. Alamer found that customers who checked the daily calorie intake were more likely to change their attitude towards eating behavior [ 36 ]. Researchers have used cognitive, affective, and conative components of consumer attitudes to study dietary behavior in the literature in normal times. For example, Sijtsema [ 37 ] examined the nature, structure, and use of projective approaches in cognitive and affective terms (expressive and associative) to discover consumers’ health perceptions. They observed that participants associated healthy living with feeling comfortable and satisfied and found an equilibrium between being active and passive [ 37 ]. Dietary education is related to maximum scores for food knowledge in developed countries [ 38 ].

The consumer’s attitude was not assessed coherently despite its significance in marketing. For evaluating the dimensionality, reliability, and validity of customer attitudes to imported poultry products, Makanyeza measured the assessment of consumer attitudes based on a tri-component attitude model [ 39 ]. The study showed that the customer approach to poultry products has 3 constructs: viz., cognition, emotions, and purchase intentions [ 39 ]. In consumer health habits, Makarem studied emotion and cognition. He found that wellness programs aimed at improving treatment compliance should consider alternatives to messages demanding control over patients’ health [ 40 ]. In national surveys of a member state of the European Union, Authors studied the attitudes of adult individuals to nutrition, food, and health. Most EU customers do not think they need to change their diets because they believe they are safe enough (Erdeiné Késmárki-Gally and Fenyvesi, 2012). For certain classes of the population, prices may play a large part in choosing food in Europe as in other developed and developing regions. Therefore, the issue with nutritious food proponents in the EU may not be a lack of awareness, but rather of the nature of diet recommendations [ 41 ].

On the other hand, in Asia, dietary behavior is influenced by Western culture. Authors observed that Koreans preferred Westernized and unbalanced foods, providing fewer nutrients [ 42 ]. It was underlined that the growing demand for Western-type foodstuffs can be the implication of the general popularity of the American lifestyle in South Korea. Moreover, the increasing income of family households—especially in the younger generation—generated a demand for food products that used to be almost unknown in the traditional Korean diet. The Korean Medical Association issued 3 top methods for a safe and healthy diet in 2017 to reverse this unfavorable cycle. These recommendations were intended to enable the population to consume a healthy diet that matches the prescribed intake of calories and reduces the threat of obesity as well as diseases associated with an unhealthy diet. Avoiding over-eating and being physically active at a young age can help reduce these conditions [ 42 ]. Whilst a balanced diet should be followed by consuming a range of foods, the ideal is different from what people consume. Food rich in nutrients, including food supplements and fortified foods, may be used as a powerful means to guarantee micronutrient satisfaction in persons at all phases of life and with shifting lifestyles, where food selection can incorporate an optimal diet [ 43 ].

Thomas examined the connection between food preferences and the understanding of a balanced diet of primary school students. There was so significant connection between the pupils’ diet selection and their knowledge of a balanced diet. The findings revealed that children make ’good decisions’ but need the awareness behind these healthy choices to change their approach to a balanced diet [ 44 ]. Casini and co-authors analyzed the development of dietary habits in Generation X. The findings indicate that dietary lifestyles with high animal protein content are strengthened, especially for consumers with poor educational levels. Convenience foods become essential, particularly for couples and for families with children. The significance of consumption at home, mainly among individual men, is increasing [ 45 ]. The food industry should ensure that the messages it has created are inspiring and meaningful for consumers’ lives by ongoing dialog with its consumers and studies on consumer knowledge and dietary attitudes [ 46 ].

For urban American youth, Fila studied their healthy eating behaviour. He found no association between healthy eating and intentions. A balanced food supply and taste were the most predictive obstacles. The behaviour of boys was predetermined by subjective norms, while the behavior of girls by obstacles is more expected. Results show that healthier eating activities should concentrate on working with families to make healthy food attractive for young people [ 47 ]. Song classified products that consumers think are safe and harmful and examined how these products affect consumers’ attitudes [ 48 ].

Research findings demonstrate there is a difference between product appeal dependent on outstanding sensory properties shown by young customers and the actual dietary content of products, transforming into unbalanced nutrient profiles in packed food. Research results show that young customers need to be reassured that delicious food is not always nutritious and to have proper nutrition and a healthy way of life is of value. Young people should be better trained in dietary methods, weight control and fitness [ 49 ]. It is found that consumers perceive functional foods help them follow a balanced diet but are anxious about labels communicating the health benefits [ 50 ].

3. Research methodology

Various methodologies such as projective techniques, questionnaires, focus groups, and images of food are used by researchers to study the attitude and perception of respondents for a healthy diet and daily calorie intake in the literature [ 44 ]. Focus groups and questionnaires are also used for pilot studies in the literature. This study is empirical. As this study was conducted during the COVID-19 pandemic, physical data collection was not possible due to lockdown. However, using an online questionnaire prepared for the sole purpose of measuring consumer attitudes towards a balanced diet and monitoring daily calorie intake, we were able to collect data in India between March, 2020 and May, 2021. The pilot study involved sending the questionnaire to 20 people to refine the constructs for the study. A structured questionnaire [ 25 ] was then prepared and used to collect data from respondents. Researchers explained through a write-up to each respondent that the purpose of the survey was to find out how they feel about a balanced diet and monitor daily calorie intake. Consent was obtained from each respondent before asking him or her to fill out the questionnaire. The convenience sampling method was used to collect the data from respondents.

The questions were structured on the tri-component attitude model to take into account attitudes such as cognition, affection, and conation [ 30 ]. The scales used by various authors like [ 28 , 51 , 52 ] were considered to develop a holistic scale to understand the attitude towards a balanced diet and daily calorie intake. Measurement of 3 components (constructs) was carried out by 12 items (see Table 1 ). The 5-point ordinal Likert scale was used to measure the 3 components with: Strongly agree (1) to Strongly disagree (5). The items F1-F4 were used to measure cognition (beliefs), items F5-F8 were used to measure affection (feelings), and items F9-F12 were used to measure conation (intentions) of the consumer.

https://doi.org/10.1371/journal.pone.0270843.t001

The terminology adopted is based on work done to quantify customer beliefs in a balanced diet and daily calorie consumption [ 52 ]. Consumer emotion measurement is based on the work of Bruner and his co-authors [ 51 ]. To measure consumer intentions, the recommendations of [ 52 ] were followed. An online questionnaire using Google Forms was sent to more than 2,000 respondents via E-Mail and WhatsApp, out of which 412 responded to the questionnaire. 12 responses were not considered due to inadequate data from the respondents. A sample of 400 was considered for this study as per the statistical formula for calculating sample sizes for online surveys. Only respondents above the age of 25 years were selected for this survey. The purpose of this selection was to investigate the attitude of the working population towards a balanced diet and daily calorie intake. The study uses the tri-component attitude model to study the attitude and perception of respondents towards a balanced diet and monitoring daily calorie intake.

Based on the above comprehensive literature review, the following hypothesis was formulated. The hypothesis was developed for both a balanced diet and daily calorie consumption. The hypothesis in the case of balanced diet and monitoring daily calorie intake is:

• H1: Consuming a balanced diet is positively associated with the benefits of good health
• H2: Monitoring daily calorie intake is positively associated with the benefits of good health
• H3: Monitoring daily calorie intake is positively associated with reducing the threat of infection of COVID-19
• H4: Consumption of a balanced diet is positively associated with happiness
• H5: Monitoring daily calorie intake is positively associated with happiness
• H6: Consuming a balanced diet is positively associated with a stronger self in the COVID-19 pandemic
• H7: Monitoring daily calorie intake is positively associated with stronger self in the COVID-19 pandemic
• H8: Consuming a balanced diet is positively associated with intentions due to the threat of COVID-19 has become a necessity
• H9: Recommendation to others to consume a balanced diet is positively associated with intentions due to the threat of COVID-19 pandemic
• H10: Recommendation to others to monitor daily calorie intake is positively associated with intentions due to the threat of COVID-19 pandemic

4. Data analysis and results

Data cleaning was executed and then coded in JASP software [ 53 ] and entered. Exploratory factor analyses were conducted in JASP software to confirm the elements underlying the customer attitude construct. The reliability of the three components’ measurement scales was checked using Cronbach’s alpha. Finally, the JASP program conducted a confirmatory factor analysis and structural equation modelling.

4.1 Sample profile

Collected data illustrates consumer attitudes towards a balanced diet and daily consumption of calories among the working-class population in India. The data was collected in Pune, India. It also studies the use of health apps in India and their impact on following a balanced diet and daily calorie intake. The data were analyzed using MS Excel and JASP software. The demographic profile of respondents is as follows: the number of males and females in the survey were 264 and 136, respectively. All respondents were graduates and above. The income level of respondents was as follows: 130 respondents were recorded in Indian Rupees (1 Lakh = 100,000), Rs. 1–5 Lakhs, 161 respondents in the income group of Rs. 5–10 Lakhs and the remaining 109 were in the income group above Rs. 10 Lakhs per annum. The age group of respondents was as follows: 266 respondents were in the age group of 25–40 years, 79 respondents in the age group of 41–55 years, and the remaining 55 were above 55 years of age.

4.2 Declarative knowledge

To check declarative knowledge, we used a trichotomous scale [ 28 ]. 239 respondents do not know their daily calorie consumption, 88 are not sure and only 73 are aware of their calorie intake. 285 are not aware of their recommended daily calorie intake. This shows that the majority working population lacks declarative knowledge about the calorie intake of food consumed daily. Regarding a balanced diet, 221 are aware of a balanced diet, 103 know something about a balanced diet, and 76 are not aware of a balanced diet. This shows that people have a declarative knowledge about a balanced diet but, when digging deeper into a balanced diet’s five food groups, the results were different. 195 do not know five food groups.74 know something and only 131 were aware of 5 food groups in a balanced diet. Again, in the case of nutrients in a balanced diet, 128 know the nutrients in a balanced diet, 94 know something and 182 do not know anything about nutrients. 157 were able to able to write the name of nutrients. 243 did not know anything about nutrients in a balanced diet. This shows people in India lack declarative knowledge about a balanced diet and daily calorie intake.

4.3 Exploratory factor analysis (EFA)

An exploratory factor analysis was executed to verify the factors underlying the consumer’s attitude. The adequacy of the sample was tested and also tested was whether the data permitted factor analysis. A Kaiser-Meyer-Olkin (KMO) Sample Adequacy Measurement was used to test the adequacy of the sample. The figure for the KMO was 0.73. This shows that the sample was appropriate [ 58 ]. The Bartlett-Sphericity test was used to determine whether the data should be used for factor analysis or not. The data (Chi-square = 886.77; df = 33; significant at p ޒ 0.001) enabled the study of exploratory factor analysis, as recommended by [ 58 ]. EFA results are presented in Table 2 .

https://doi.org/10.1371/journal.pone.0270843.t002

Three factors extracted from the results are shown in Table 2 . Items F1-F2 are associated with customer beliefs for a balanced diet and daily consumption of calories. This element was then referred to as ’beliefs.’ Items F3-F8 clarified the feelings that customers maintained balanced nutrition and an intake of calories every day; thus the element was known as ‘emotions’. Except for F9, the points F10-F12 demonstrated the consumer’s intentions about the balanced diet, hence the factors were referred to as ‘intentions’. Item F9 was removed since only one of the three variables was able to load it. Instead of a belief, items F3 and F4 were translated as emotions. Cronbach’s alpha was 0.857 as indicated in Table 2 [ 54 , 55 ].

4.4 Confirmatory factor analysis (CFA)

Validity of the dimensions of customer attitude was assessed after extraction of three variables by CFA; namely beliefs, intentions, and feelings. JASP software conducted confirmatory factor analysis. The results are shown in Table 3 .

https://doi.org/10.1371/journal.pone.0270843.t003

The model fit indices were acceptable as per Table 3 (Tukey-Lewis index (TLI)) = 0.992). F3 and F9 were perfectly correlated, F4 and F10 respectively. So were deleted by confirmatory factor analysis (CFA). The choice to agree on these indices is grounded on the references of [ 56 , 57 ] that GFI and TLI should be close to 1 and CMIN/df should be less than 3.

A structural model was developed, and the estimates of the model were measured to calculate their significance. The items loaded (p<0.001) with latent variables were sufficient to be greater than 0.4, as shown in Fig 4 [ 58 ]. There were positive correlations between latent variables. It was determined that the association between beliefs and emotions is 0.18; p is significant (p < 0.001). The association between feelings and intentions is found at 0.89. It was determined that 0.20 is the association between beliefs and intentions (p < 0.001). These results show that latent variables are convergent. From Table 4 , all hypotheses are accepted. Hypothesis H1 and H2 show that a balanced diet and monitoring daily calorie consumption are positively associated with the benefit of good health. Hypothesis H3 shows that monitoring daily calorie intake is positively associated with reducing the threat of infection of COVID-19. Hypothesis H4 and H5 show that consumption of a balanced diet and monitoring calorie consumption is related to happiness. Hypothesis H6 and H7 show that consuming a balanced diet and monitoring calorie consumption is related to a stronger self in the COVID-19 pandemic. Hypothesis H8 shows that following a balanced diet, as a necessity, is positively associated with intentions due to the threat of COVID-19. Hypothesis H9 and H10 show that recommendation to others to follow a balanced diet and monitor daily calorie intake is positively associated with intentions due to the threat of the COVID-19 pandemic.

(Source: own calculation).

https://doi.org/10.1371/journal.pone.0270843.g004

https://doi.org/10.1371/journal.pone.0270843.t004

5. Discussion of results

The consumer attitude of people during the COVID-19 pandemic was studied using the tri-component attitude model. The purpose of the research was to evaluate the validity, reliability, and dimensionality of consumers’ attitudes to a balanced diet and daily consumption of calories during the COVID-19 pandemic in a developing country. As several authors have indicated (28,30), the tri-component attitude model of behavior; which studies belief (cognition), emotions (affect), and intention to follow (conation), have been proven as true and reliable customer attitude measures in an emerging economy. This means that consumer emotions, beliefs, and intent are key considerations in the COVID-19 pandemic that affects consumer decisions.

The vital association of consumer feelings and buying intentions reveal that consumers are more prepared to adopt a balanced diet when their emotions are favored. Consumer belief is also positively linked to follow-up intentions. This means that customer decisions to maintain a balanced diet and control the daily intake of calories will also be affected by consumer beliefs of a balanced diet. The connections between customer beliefs, emotions, and purchasing intentions show convergence; i.e., these components converge on the mindset of the consumer but, since the correlations are not high, Indian consumers still see these components as distinctive.

The cognitive component studied the declarative knowledge of a balanced diet and daily calorie consumption among people. While most people were aware of a balanced diet, the majority were not aware of their daily calorie consumption. The knowledge of a balanced diet is limited to name only as a majority were not able to name the five foods in a balanced diet. In addition, the majority were unaware of the nutrients in a balanced diet. As people are not aware of their daily calorie consumption, it may result in an intake of more calories, which may be harmful to their health. It may increase chronic and non-chronic diseases. From the data collected, people in the age group of 25–40 hardly have any health issues but people above age the age of 40 suffer from various health issues like diabetes, blood pressure, thyroid problems, arthritis, etc. Therefore, it is the responsibility of the government and corporate world to create awareness about a balanced diet and daily calorie intake through social awareness campaigns. Food companies can develop innovative campaigns [ 59 , 60 ] and products through corporate social responsibility that help change people’s attitudes towards a balanced diet and daily calorie intake.

5.1 Implications for industry and government

Companies in food production need to be more research-oriented for products with components that are not suitable from a balanced diet point-of-view. For example, wheat flour-based items can be substituted with whole wheat-based items, and wheat can also be complemented or substituted by other grains like millets in packaged food products. Companies can have their products listed in diet apps for consumer awareness about the composition of food items. Consumers have an average awareness about a balanced diet but are not exposed to any appropriate measuring method. They need to be made aware of the measurements. A mobile app can play a significant role here. The Indian consumer is a food-loving consumer. Traditional or modern foods that are calorie-rich can be substituted without changing the palate significantly. For example, the introduction by food brand Maggi of multi-grain products or oats has been very well received by Indian consumers. Packaged food products have a high amount of preservatives that can be substituted with natural preservatives. Consumers can demand these if they are aware of such substitutes. The change can be introduced from a production perspective if the change is demanded from the consumption side. Therefore, consumers have to demand healthy changes in their foods; especially packaged food, and that requires knowledge about a balanced diet and monitoring daily calorie intake.

Results from the experiment to increase awareness of a balanced diet have been fruitful. A. Alam found that the balanced plate intervention helped women through practical demonstration to learn about a balanced meal by highlighting appropriate portion sizes and food diversity [ 61 ]. Innovative solutions [ 62 , 63 ] can be developed to create awareness about a balanced diet and daily calorie intake. Social media can be used by corporate organizations and local governments to promote a balanced diet and to monitor daily calorie consumption [ 64 ]. Governments should undertake social marketing to promote the importance of consuming a balanced diet and monitoring daily calorie intake, which is rarely seen in a developing country like India. Governments should take the initiative for a public-private partnership to promote healthy eating behaviors through social advertising.

6. Conclusion

The conative, cognitive, and affective components explain the respondents’ attitudes towards a balanced diet and monitoring daily calorie consumption. The model helps to understand declarative knowledge about a balanced diet and daily calorie consumption. People are found lacking declarative knowledge about a balanced diet and daily calorie consumption. Relatively, females are much more aware and have the intention to follow balanced diet. Nutrition professionals and government agencies should work with local leaders and retired people to provide complete dietary knowledge to the working population. Encouraging parents and caretakers to purchase and make healthy foods regularly will go a long way to imbibe the culture of a balanced diet and daily calorie consumption among the working population. The working population and community at large are a valuable component of any economy and children seem keen to receive and follow nutritional recommendation from their parents. Males who are less aware but seem receptive to subjective norms would benefit more from family and peers’ activities to increase healthy eating behaviors. Because of the alarming increase in recurring diseases like COVID-19 in India and abroad, it is prudent to promote healthy dietary behavior through knowledge dissemination about the importance of a balanced diet and daily calorie consumption. This will help to play down the fears about recurring diseases and push people’s intention to follow a balanced diet and monitor daily calorie consumption. This will help reduce the prevalence of obesity and other chronic diseases among the working population in India and further help to reduce the threat of COVID-19-like pandemics.

7. Limitations and future scope for research

Data was collected through an online questionnaire using Google Forms. Other options normally available for data collection (such as interviews) were not available due to the COVID-19 pandemic and subsequent lockdown in India. The convenience sampling method used may not be entirely representative of the population. The authors have used the tri-component attitude model, utilized to study dietary behaviour. The paper only studies the consumer attitude of the working population towards a balanced diet and daily calorie consumption. The research cannot be generalized to a larger population. Further studies can be carried out to study consumer attitudes of children, females, senior citizens towards a balanced diet and daily calorie consumption, separately. The efficacy of the tri-component attitude model can be tested on different age groups in India and other countries in this sector. Future researchers can study procedural knowledge about a balanced diet and daily calorie consumption. Longitudinal studies and experimental interventions can be undertaken to study such phenomena. To provide a robust understanding of estimation and dimensionality, future investigations can also be undertaken in other emerging economies.

Supporting information

https://doi.org/10.1371/journal.pone.0270843.s001

• View Article
• PubMed/NCBI
• Google Scholar
• 2. Worldometer. https://www.worldometers.info/coronavirus/#countries [Internet]. Worldometer. 2021. p. 1. https://www.worldometers.info/coronavirus/
• 12. Faris MAIE, Al-Bakheit A, Hasan H, Cheikh Ismail L, Jahrami H, Rajab D, et al. Assessment of nutritional quality of snacks and beverages sold in university vending machines: a qualitative assessment. Br Food J. 2021;
• 14. Giazitzi K, Boskou G. Developing a methodology to create nutritionally balanced meals. Br Food J. 2021.
• 18. Anderson JR. Cognitive psychology and its implications. 4th ed. New York: W. H. Freeman and Company; 1995.
• 27. Rosenberg, M.J., Hovland CI. Cognitive, affective, and behavioral components of attitude. New Haven; 1960.
• 28. Ramesh Kumar S., Leon Schiffman LLK. Consumer Behaviour. 11th ed. New Delhi: Pearson; 2017.
• 29. Arnould L.L, Price E.J, & Zinkhan GM. Consumers. New York: Mcgraw Hill; 2004.
• 30. Assael H. Consumer behaviour: A strategic approach. Boston: Houghton Mifflin Company; 2004.
• 51. Bruner G.C II, Hensel P.J, & James KE. Marketing scales handbook, Volume IV: A combination of multi-item measures for consumer behaviour and advertising. Ohio, USA: Thompson Higher Education.; 2005.
• 53. Wagenmakers Eric-Jan. JASP Software [Internet]. Amsterdam: University of Amsterdam; 2020. https://jasp-stats.org/download/
• 54. William G. Zikmund; Barry J. Babin; Jon C. Carr; Mitch Griffin. Business Research Methods. 10th ed. Cengage Learning; 2010.
• 55. Bryman A. Social research methods. 3rd ed. New York: Oxford University Press Inc.; 2008.
• 58. Field A. Discovering statistics using SPSS. 2nd ed. London: Sage Publication; 2005.

Assessing the Cost of Healthy and Unhealthy Diets: A Systematic Review of Methods

• Public Health Nutrition (KE Charlton, Section Editor)
• Open access
• Published: 09 September 2022
• Volume 11 , pages 600–617, ( 2022 )

Cite this article

You have full access to this open access article

• Cherie Russell   ORCID: orcid.org/0000-0003-1251-4810 1 ,
• Jillian Whelan   ORCID: orcid.org/0000-0001-9434-109X 2 &
• Penelope Love   ORCID: orcid.org/0000-0002-1244-3947 1 , 3  

6242 Accesses

3 Citations

2 Altmetric

Explore all metrics

Purpose of Review

Poor diets are a leading risk factor for chronic disease globally. Research suggests healthy foods are often harder to access, more expensive, and of a lower quality in rural/remote or low-income/high minority areas. Food pricing studies are frequently undertaken to explore food affordability. We aimed to capture and summarise food environment costing methodologies used in both urban and rural settings.

Recent Findings

Our systematic review of high-income countries between 2006 and 2021 found 100 relevant food pricing studies. Most were conducted in the USA ( n  = 47) and Australia ( n  = 24), predominantly in urban areas ( n  = 74) and cross-sectional in design ( n  = 76). All described a data collection methodology, with just over half ( n  = 57) using a named instrument. The main purpose for studies was to monitor food pricing, predominantly using the ‘food basket’, followed by the Nutrition Environment Measures Survey for Stores (NEMS-S). Comparatively, the Healthy Diets Australian Standardised Affordability and Price (ASAP) instrument supplied data on relative affordability to household incomes.

Future research would benefit from a universal instrument reflecting geographic and socio-cultural context and collecting longitudinal data to inform and evaluate initiatives targeting food affordability, availability, and accessibility.

Similar content being viewed by others

Evidence-based European recommendations for the dietary management of diabetes

Food Insecurity and Hypoglycemia among Older Patients with Type 2 Diabetes Treated with Insulin or Sulfonylureas: The Diabetes & Aging Study

The role of food banks in addressing food insecurity: a systematic review.

Avoid common mistakes on your manuscript.

Introduction

Poor diets, described as those low in fruits, vegetables, and whole grains, and high in red and processed meats and ultra-processed foods, are a leading risk factor for chronic disease globally [ 1 ]. In most high-income countries (HIC), poor diets disproportionally affect lower socioeconomic populations, Indigenous Peoples, and those living in rural and/or remote areas [ 2 , 3 , 4 , 5 ]. Rather than solely a consequence of individual behaviours, poor diets are critically informed by broad contextual factors, including social, commercial, environmental, and cultural influences [ 6 , 7 ]. Crucially, the consumption of a healthy diet is constrained by the range, affordability, and acceptability of foods available for sale [ 8 ]. Research suggests that healthy foods are often harder to access, more expensive, and often of a lower quality in rural, remote, or low-income/high minority areas, than in metropolitan or high-income areas [ 9 , 10 , 11 , 12 ]. Such food environments contribute to higher rates of diet-related non-communicable diseases and food insecurity [ 13 , 14 ]. In order to improve population diets, all aspects of the food environment must be addressed to ensure healthy foods are affordable, available, and of adequate nutritional quality [ 15 ].

Price is a primary factor impacting food choice, diet quality, and food security, therefore having affordable, acceptable, healthy food should be a political and social priority [ 8 , 15 , 16 ]. Some research suggests that healthy diets are associated with greater total spending [ 17 , 18 , 19 ], while other studies report that adherence to a healthy diet is less expensive than current or ‘unhealthy’ diets [ 9 , 20 , 21 ]. Regardless, the cost of a healthy diet is a proportionately large household expense (> 30% of household income) and may therefore be considered ‘unaffordable’ [ 22 ]. Additionally, public perception that healthy diets are expensive is high, which itself may be a barrier to the purchase of healthy foods [ 23 ]. Therefore, improving the affordability of healthy food could improve population diets, regardless of context [ 24 ].

To address the issue of food affordability and inform appropriate attenuating policy and intervention strategies, food pricing studies are frequently undertaken. Food pricing, however, is not a universal construct and is highly influenced by country and context. Numerous methods have been developed to measure food pricing, with data therefore not always comparable or replicable, and of limited value to inform appropriate policy [ 25 ]. Most studies that collect food pricing data conclude that food prices are rising, making healthy eating unaffordable for many populations. However, few studies to date have used this data to suggest strategies to improve affordability. Our systematic review aims to capture and summarise food environment costing methodologies used in HIC, in both urban and rural settings, between 2006 and 2021. In addressing this aim, we answer the following questions: (i) What is the stated purpose of collecting data on food prices, including whether the data is used to inform or advocate for interventions? (ii) Which instruments are being used to measure food pricing? (iii) What are the strengths and limitations of each instrument as reported by study authors?

To address the research aim, we undertook a systematic review of the literature, following the Preferred Reported Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 26 ]. We followed four steps: (i) systematic search for relevant literature; (ii) selection of studies, (iii) data extraction, and (iv) analysis and synthesis of results.

Systematic Search Strategy

After consultation with a research liaison librarian, databases used included EBSCOHOST (Academic Search Complete, CINAHL Complete, GlobalHealth, Medline Complete, and PsychINFO) and Informit. We chose these databases for their comprehensiveness and conventional use in the public health nutrition discipline. We identified search terms using a scoping review and key words used in previous food pricing reviews [ 15 , 23 , 27 , 28 ]. We searched both article abstracts and titles using the following search string: ‘food affordability’ OR ‘food cost’ OR ‘food price*’ OR ‘food promotion*’. We completed an initial search for studies published 2016–2021 in October 2021, followed by a search for studies published 2006–2015 in December 2021.

Selection of Studies

Studies were included if they were English, peer-reviewed journal articles presenting original research, monitored food prices in a high-income country/s, and were published between 2006 and 2021. The article by Glanz (2006) [ 15 ] is considered a seminal paper in food pricing research and was therefore chosen as the starting date for our search. Studies prior to this date were considered unlikely to be relevant to the research question and were thus excluded. Review articles, opinion pieces, posters, perspectives, study protocols, viewpoints, editorials, and commentaries were excluded, as well as those assessing middle- or low-income countries.

Study screening involved an initial review of all titles and removal of duplicates by A1 using online Covidence software [ 29 ], followed by abstract screening (A1), and then full text screening of remaining studies (A1). A second reviewer independently screened all articles by abstract and full text to minimise bias (A2 and A3). Disagreements were resolved through discussion between researchers; where no agreement was reached, a third party acted as an arbiter (A2 and A3). Limited hand searching was conducted given the volume of papers identified. Online Resource 1 presents a PRISMA flow chart of the study selection process.

Data Extraction

Included studies were uploaded to an Endnote (V. X9) [ 30 ] library. We systematically extracted details of each study to Microsoft Excel (V. 2112), including the author/s, year published, article title, aim, pricing instrument used (if specified), country and geographical context (e.g. urban or rural), type of data collected, number and type of locations assessed, number and type of food items captured, population (if the study used sales receipts to estimate food prices), time period of study, strengths, limitations, and conclusions.

Data Analysis and Synthesis

The coded data were used to identify major themes that were then synthesised in the results. We used an inductive thematic approach for our analysis, with the results discussed between the research team to limit researcher subjectivity [ 31 ]. We used Microsoft Excel to calculate descriptive statistics and graphical outputs.

Overview of Studies

Database searching identified 2737 studies, with 1882 studies remaining after removal of duplicates. After abstract screening, a total of 287 were identified for full-text screening, with 187 excluded, and a total of 100 studies included in this systematic review (Online Resource 1).

We observed an increasing number of studies each year, with peaks in 2013, 2014, and 2018 (Fig.  1 ).

Frequency of studies published assessing food prices between 2006 and 2021

Most studies measured food prices in the USA ( n  = 47), followed by Australia ( n  = 25). Urban food environments were assessed more frequently ( n  = 74) than rural ( n  = 33). Most studies were cross-sectional ( n  = 77). Most studies included instore price audits ( n  = 59), followed by online price audits (supermarket websites, n  = 13), or electronic point of sale data (consumer receipts, register sales, or electronic scanning of food prices in the home, n  = 12), and a combination of these ( n  = 17). Most studies collected food price data from more than 20 food retail outlets ( n  = 34) (Table 1 ).

Details of all included studies, grouped according to data source used (instore price audits, online price audits, electronic point of sale, and combinations of these), are shown in Tables 2 , 3 , and 4 . Details include instrument used (if applicable), purpose of data collection, country, context, study type (e.g. cross-sectional, longitudinal), healthiness comparisons (between healthy and unhealthy products or diets), study author, and year. The use of a named instrument was captured to identify commonalities in usage of instruments, and not as an indication of study quality. When assessing differentials in ‘healthiness’, studies either presented a comparison of a ‘healthy diet’ with an ‘unhealthy or currently consumed diet’ or a comparison of the cost of ‘healthy’ and ‘unhealthy’ foods or product categories.

Study Purpose for Collecting Data on Food Prices

The studies included in this review had a multitude of aims (Tables 2 , 3 , and 4 ). While most studies were conducted solely to monitor food prices in a specific location/s [ 33 , 39 , 42 , 46 , 47 , 52 , 54 , 56 , 57 , 59 , 64 , 67 , 71 , 75 , 80 , 81 , 88 , 89 , 104 , 106 , 108 , 109 , 114 ], others aimed to monitor food price changes over time [ 53 , 63 , 74 , 83 , 93 , 97 , 111 , 127 ], assess food prices as a function of income, socioeconomic status, or welfare assistance [ 9 , 19 , 20 , 33 , 36 , 37 , 38 , 40 , 41 , 66 , 69 , 70 , 77 , 84 , 85 , 86 , 90 , 91 , 92 , 94 , 100 , 110 , 115 , 116 , 117 , 122 ]; assess food price in relation to geographic distance [ 19 , 77 , 91 , 92 , 94 , 98 ]; compare perceptions of food price with actual food prices [ 68 , 101 , 107 ]; and relate food price with a health outcome [ 34 , 35 , 37 , 40 , 47 , 58 , 70 , 72 , 78 , 105 , 116 , 117 , 124 , 125 ], compare the price of healthy or unhealthy foods/diets [ 9 , 20 , 34 , 43 , 50 , 51 , 55 , 60 , 61 , 62 , 63 , 64 , 65 , 76 , 85 , 86 , 93 , 94 , 95 , 96 , 99 , 102 , 110 , 111 , 112 , 120 , 121 , 123 , 124 , 126 ], assess diet costs for a specific population [ 82 , 118 ], compare food prices between brands [ 79 ], compare approaches for estimating dietary costs [ 32 ], or understand how prices impact consumption [ 44 ]. Only seven studies specifically aimed to collect data to inform policy strategies and/or community interventions to improve population health [ 10 , 11 , 49 , 80 , 87 , 103 , 113 ]. However, 26 studies did discuss their study findings on food price in relation to potential further action to improve food environments [ 9 , 19 , 20 , 33 , 36 , 37 , 40 , 43 , 47 , 49 , 50 , 54 , 55 , 59 , 63 , 64 , 81 , 85 , 86 , 87 , 88 , 103 , 104 , 105 , 110 ]. Specific suggested strategies included those targeting individuals, such as education campaigns to promote healthy and more affordable food choices [ 9 , 36 , 43 , 45 , 49 , 50 , 55 ], and those targeting environmental changes, such as taxes on ‘unhealthy’ foods [ 33 , 49 , 85 , 104 , 110 ], subsidies and exemptions for ‘healthy’ foods [ 9 , 20 , 45 , 62 , 63 , 85 , 104 , 110 ], vouchers for farmer’s markets [ 43 ], establishing more food stores [ 33 , 45 , 48 , 104 ], better public transportation for consumers to access food stores [ 59 ], generating savings at the manufacturer/wholesaler level that can be passed on to customers [ 81 ], establishing community-led food supply options [ 9 ], and increasing welfare support proportionate to food prices and geographic distances to food stores [ 37 , 40 , 50 , 73 , 85 ].

Overview of Instruments Used to Measure Food Prices

Of the 100 included studies, 57 used a named instrument to measure food prices, as described below. The remaining 43 studies did not name a pre-existing data collection instrument; instead, the authors described the data collection methodology used, for example, in store, online, or via electronic sales data.

Food Basket Instruments

The majority ( n  = 30) of studies used a variation of a ‘food basket’ to estimate food prices. Food baskets capture the prices of a pre-defined list of foods, often in quantities representative of the total diet of reference families over a defined timeframe [ 9 ], and is a longstanding methodology used to investigate the availability and affordability of food. Food basket studies were mainly conducted in the USA ( n  = 14) and Australia ( n  = 12) [ 19 , 20 , 80 , 81 , 83 , 87 , 88 , 89 , 90 , 91 , 92 ]. Food basket studies using named instruments were conducted in the USA—using the Thrifty Food Plan Market Basket ( n  = 5), the Fred Hutchinson Cancer Research Center Market Basket ( n  = 3), the University of Washington’s Center for Public Health Nutrition Market Basket ( n  = 3), and the USDA Market Basket ( n  = 2); in Australia—using the Victorian Healthy Food Basket ( n  = 4), the Food Basket informed by the INFORMAS framework ( n  = 2), the Adelaide Healthy Food Basket ( n  = 2), the Illawarra Healthy Food Basket ( n  = 2), the Queensland Healthy Food Access Basket Survey ( n  = 1), and the Northern Territory Market Basket ( n  = 1); and in Canada—using the Ontario Nutritious food basket ( n  = 1), the Revised Northern Food Basket ( n  = 1), and an unspecified market basket ( n  = 1). Food basket studies were conducted in both rural ( n  = 13) [ 19 , 37 , 49 , 50 , 52 , 81 , 83 , 87 , 88 , 90 , 91 , 103 , 110 ] and urban contexts ( n  = 25) [ 19 , 20 , 37 , 38 , 40 , 46 , 49 , 50 , 51 , 52 , 62 , 63 , 64 , 66 , 67 , 70 , 80 , 81 , 83 , 88 , 89 , 92 , 104 , 105 , 111 ].

All but two [ 37 , 40 ] food basket studies collected prices from physical instore locations [ 19 , 20 , 38 , 43 , 46 , 49 , 50 , 51 , 52 , 55 , 62 , 63 , 64 , 66 , 67 , 70 , 73 , 80 , 81 , 83 , 87 , 88 , 89 , 90 , 91 , 92 , 103 , 104 , 105 , 110 ], with four of these studies supplementing the data with online supermarket prices [ 62 , 63 , 64 , 81 ]. Additionally, three instruments compared the cost of a ‘healthy diet’ to either an ‘unhealthy or currently consumed diet’ [ 20 , 88 , 110 ], 13 instruments compared the cost of ‘healthy’ and ‘unhealthy’ individual foods or product categories [ 19 , 38 , 51 , 62 , 63 , 66 , 83 , 87 , 89 , 90 , 103 ], and 14 instruments did not present a comparison [ 37 , 40 , 46 , 49 , 50 , 52 , 64 , 67 , 70 , 80 , 81 , 91 , 92 , 104 , 105 ]. ‘Current’ diets were defined using national survey data [ 20 , 110 ]. Level of healthiness was defined using various benchmarks, namely the NOVA food processing classification system [ 38 ], nutrient composition and energy density [ 38 , 51 , 62 , 63 , 66 , 80 , 83 , 90 ], national Dietary Guidelines [ 19 , 43 , 70 , 87 , 88 , 89 , 90 ], and the Dietary Approaches to Stop Hypertension (DASH) dietary pattern [ 43 ]. Food affordability was benchmarked using household income [ 20 , 49 , 50 , 90 , 91 , 92 , 103 , 105 , 110 ], government subsidies [ 37 , 40 , 87 , 89 , 91 ], and minimum wage [ 38 , 66 , 70 ]; however, most studies ( n  = 13) did not determine relative affordability in their analysis [ 43 , 51 , 52 , 55 , 62 , 63 , 64 , 67 , 73 , 80 , 81 , 83 , 88 ].

Healthy Diets Australian Standardised Affordability and Price (ASAP) Instrument

Following critiques of existing food baskets, the previously described INFORMAS instrument was refined to assess and compare the price and affordability of healthy and current diets in Australia, leading to the development of the Healthy Diets Australian Standardised Affordability and Price (ASAP). This instrument assesses the cost of a ‘recommended’ Australian diet (defined by the Australian Dietary Guidelines and Australian Guide to Healthy Eating) and the cost of the ‘current’ Australian diet (as reported in the 2011–12 Australian Health Survey) using the reference household of two parents and two children (boy aged 14 years; girl aged 8 years) [ 128 ]. Thus, all studies using this instrument present a comparison of the cost of a ‘healthy’ and ‘unhealthy’ diet in their analysis. Intrinsic to the instrument, the relative affordability of a healthy diet is measured against household incomes. The ASAP instrument was used by four studies to collect food price data in physical instore locations [ 9 , 85 , 86 ] or from online supermarkets [ 94 ]. Studies were conducted in both rural ( n  = 2) [ 9 , 85 , 94 ] and urban ( n  = 2) [ 85 , 86 , 94 ] contexts.

Nutrition Environment Measures Survey for Stores (NEMS-S) Instrument

The Nutrition Environment Measures Survey for Stores (NEMS-S) and its variants were also frequently used throughout food pricing studies ( n  = 15). These included NEMS-S-Rev (Nutrition Environment Measures Survey for Stores Revised), TxNEAS (Texas Nutrition Environment Assessment), NEMS-S-NL (Nutrition Environment Measures Survey for Stores Newfoundland and Labrador), and The Bridging the Gap Food Store Observation Form. This instrument was used mostly in the USA ( n  = 11) [ 11 , 33 , 36 , 44 , 47 , 48 , 54 , 57 , 68 , 71 , 107 ]. Studies were conducted in both rural ( n  = 4) [ 10 , 11 , 56 , 106 ] and urban ( n  = 11) [ 33 , 36 , 44 , 47 , 48 , 54 , 57 , 68 , 71 , 107 , 108 ] contexts. Compared to the food basket methodology, the NEMS-S instrument compares products in the same category that are considered ‘healthy’ or ‘unhealthy’ based on American Dietetic Association (ADA) recommended dietary guidelines, focusing on availability, price, and quality. All studies using the NEMS-S instrument collected food price data in physical instore locations. While the instrument itself does not include a calculation of relative affordability, approximately half the NEMS-S studies included this step in their methods [ 33 , 36 , 44 , 47 , 48 , 54 , 57 ], while all others did not [ 10 , 11 , 56 , 68 , 71 , 106 , 107 , 108 ].

Other Instruments

Several other named instruments were identified, used in single studies. These included the Diet and Nutrition Tool for Evaluation (DANTE) [ 101 ], the Flint Store Food Assessment Instrument [ 60 ], the Food Label Trial registry tool [ 76 ], the New Zealand Food Price Index [ 111 ], the USDA Food Store Survey Instrument [ 73 ], USDA Low-cost food plan [ 55 ] and audit forms developed by the Yale Rudd Center [ 39 ], the Hartford Advisory Commission on Food Policy [ 59 ], and the USDA Authorized Food Retailers’ Characteristics and Access Study [ 43 ]. Only three instruments compared healthy and unhealthy products [ 43 , 76 , 111 ] and none analysed the relative affordability of food.

Instrument Strengths and Limitations

The strengths and limitations of instruments commonly used across studies, as identified by study authors, are presented in Online Resource 2 . Commonly cited limitations, regardless of instrument used, included that actual purchasing behaviours were not captured (unless electronic point of sales data was utilised); culturally important and region-specific products were often not captured; tools were cross-sectional in nature, thus seasonality or changes overtime were not considered; and out-shopping, described as food purchases undertaken outside the local residential geography, including internet orders or foods purchased during travel to other communities, could not be accounted for. While some food basket studies and those using the ASAP instrument did contextualise the relative affordability of healthy foods and/or diets, this was not a part of the methodology for NEMS-S. Other limitations specific to NEMS-S included the length of the survey, and a low convergence between NEMS-S results and consumer perceptions of affordability. Specific limitations for food basket studies included results being constrained by the reference family used and the assumption that food is shared equally among household members. Additionally, most instruments did not capture geographical information regarding access to food retail outlets or availability of foods within food retail outlets.

Authors less commonly described instrument strengths. For NEMS-S, cited strengths included the ability to compare food prices between healthy and unhealthy options, that it has strong inter-rater and test-re-test reliability, and that it has been validated in multiple countries. ASAP studies, and some food basket studies, included a comparison between healthy and current (‘unhealthy’) diets (based on actual consumption) and included alcohol in the survey.

Our systematic review details the key purposes, and methodologies used, for measuring food prices in HIC between 2006 and 2021. While most studies were conducted solely to monitor food prices in specific locations, some sought to report price changes over time, and others collected data to assess comparability of food costs to healthier alternatives, average earnings, welfare payments, rurality, and socioeconomic position. Most studies measured food prices in urban areas, using instore food price audits, with an emerging use of online data collection evident. The most frequently used instruments were ‘food baskets’, used predominantly to monitor food prices; the NEMS-S instrument, used to provide data on relative cost and availability; and the ASAP instrument, use to provide data on relative affordability.

Our review differs from previous reviews of food price and affordability instruments [ 23 , 28 ] by taking a broadened focus on food pricing measures used in HIC globally and including new technology that is affording opportunities for electronic food pricing data collection. While a previous review critiqued food pricing measures for relevance specific to a rural context, our review includes both rural and urban contexts [ 28 ]. Another review [ 23 ] also describes the components of individual instruments, such as the identification of differently sized ‘food baskets’, ranging between 30 and 200 food items. Such critique was beyond the scope of our research questions.

Despite emerging options for electronic methodologies, the predominance of in person, instore data collection continues, notwithstanding the time-consuming and resource-intensive nature of this method. Studies indicate that these instore instruments can be targeted and applied within multiple contexts, such as rural [ 9 , 10 , 11 , 12 ], Indigenous [ 129 , 130 ], and low socioeconomic areas [ 85 ]. Perhaps researchers consider instore data collection as providing real-world insights at a community and population health level. Our review identified that food pricing instruments were mostly used to monitor food prices at a single point in time (cross-sectional) rather than changes at different time points (longitudinal). Instruments that enable the comparison of food prices in terms of a healthy diet (as recommended by dietary guidelines) compared with current dietary patterns (as reported through population health surveys) [ 128 ], and relative affordability for families, appear to provide data of greater practice and policy relevance with regard to community strategies, taxes, and subsidies that have potential to enhance food affordability, availability, and accessibility.

Technological innovations are an emerging alternative to in person data collection, facilitating the acquisition of online supermarket prices, a less labour-intensive method for capturing food prices [ 131 ]. To date, this method has been used within major chain-supermarkets, with a recent study reporting similar results when comparing pricing data obtained instore versus online [ 94 ]. This method therefore holds potential where an online supermarket presence exists, which was increasingly the case during the COVID-19 pandemic [ 53 ], providing rapid feedback to inform price promotions. However, for smaller and/or independent food retail outlets, frequently located in rural areas, online data collection does not appear to capture the contextual nuances of instore price promotions.

Our review found an over-representation of food pricing studies within urban areas. This is consistent with multiple studies that reflect inequities experienced within rural environments [ 132 ], and rural food environments are no exception [ 133 ]. The predominance of research within urban areas may also reflect a pragmatic researcher response to the physical proximity of stores (ease of measurement) and larger population reach (potential for greater population impact). Previous research shows significant differences in income-based variables, food environments, and the affordability of healthy food between urban and rural settings [ 134 ]. There is therefore a need for rural-specific food pricing studies, using appropriate instruments, to evaluate and inform rural-specific food environment initiatives [ 28 ].

During the period covered by this review, high level experts from the World Health Organization [ 135 ], the Lancet Commission [ 136 ], and the Food and Agricultural Organisation of the United Nations [ 137 ] have identified the potential benefits that initiatives located within food retail environments can provide in nudging dietary choices towards healthier options through instore food pricing and promotion, with the overall aim of improving population level diets [ 14 ]. Measures of food pricing, and the relative affordability of a healthy diet, are important to both inform and measure the effectiveness of such initiatives. However, few studies in our review explicitly aimed to inform initiatives or strategies, either at the community or policy level. Assessment of author-reported strengths and limitations of food pricing instruments and methodologies also identified a need for a universal instrument that reflects contextual geographic and socio-cultural information; is intended to be used repeatedly over time; and is adaptable to different country/cultural/contextual settings [ 17 , 23 ]. Future research would benefit from linking the purpose of undertaking food pricing data collection more explicitly to potential initiatives. Our review supports this call and suggests that the instrument selected should suit the context and collect longitudinal data to provide greater insights into the design and effectiveness of initiatives that make healthy food not only affordable but also available and accessible.

Strengths and Limitations

This systematic review provides a current and comprehensive overview of international food pricing studies across HIC. We acknowledge that while food prices are an important factor influencing food choice, it is only one component of the food environment; however, analysing instruments that assess food acceptability, availability, and accessibility was beyond the scope of this review. This review focused on HIC and a similar review on food pricing studies in low- and middle-income countries would be informative. This review may have missed additional relevant data as it only included English language studies and did not include grey literature or hand searching of reference lists.

Food security has come under heightened scrutiny given the food supply interruptions experienced worldwide during the COVID-19 pandemic. While studies providing a snapshot of food prices can be useful to identify areas impacted by rising food prices, much of this cross-sectional data is known. This review raises questions regarding the purpose of collecting food price data, and how this data can best be used to inform change through practice and policy strategies. We suggest that longitudinal studies using a consistent methodology, which acknowledges contextual nuances and demonstrates temporal changes in food pricing, are needed to inform and to evaluate community-based or legislative strategies to improve the relative affordability of a healthy diet.

Murray CJL, Aravkin AY, Zheng P, Abbafati C, Abbas KM, Abbasi-Kangevari M, Abd-Allah F, Abdelalim A, Abdollahi M, Abdollahpour I, et al. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396:1223–49.

Article   Google Scholar  

Australian Institute of Health and Welfare. Australia’s Health 2022: Burden of Disease. Canberra: AIHW; 2020.

Google Scholar  

Sloane DC, Diamant AL, Lewis LB, Yancey AK, Flynn G, Nascimento LM, Mc Carthy WJ, Guinyard JJ, Cousineau MR. Improving the nutritional resource environment for healthy living through community-based participatory research. J Gen Intern Med. 2003;18:568–75.

Swinburn BA, Sacks G, Hall KD, McPherson K, Finegood DT, Moodie ML, Gortmaker SL. The global obesity pandemic: shaped by global drivers and local environments. Lancet. 2011;378:804–14.

Darmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr. 2008;87:1107–17.

Article   CAS   Google Scholar  

Kickbusch I, Allen L, Franz C. The commercial determinants of health. Lancet Glob Health. 2016;4:e895–6.

Wilkinson RG, Marmot M. Social determinants of health: the solid facts, (World Health Organization). 2003.

Lee JH, Ralston RA, Truby H. Influence of food cost on diet quality and risk factors for chronic disease: a systematic review. Nutr Diet. 2011;68:248–61.

Love P, Whelan J, Bell C, Grainger F, Russell C, Lewis M, Lee A. Healthy diets in rural Victoria-cheaper than unhealthy alternatives, yet unaffordable. Int J Environ Res Public Health. 2018;15.

Whelan J, Millar L, Bell C, Russell C, Grainger F, Allender S, Love P. You can’t find healthy food in the bush: poor accessibility, availability and adequacy of food in rural Australia. Int J Environ Res Public Health. 2018;15:2316.

Pereira RF, Sidebottom AC, Boucher JL, Lindberg R, Werner R. Peer Reviewed: Assessing the Food Environment of a Rural Community: Baseline Findings From the Heart of New Ulm Project, Minnesota, 2010–2011. Prev Chronic Dis. 2014;11.

Vilaro MJ, Barnett TE. The rural food environment: a survey of food price, availability, and quality in a rural Florida community. Food Public Health. 2013;3:111–8.

Garasky S, Morton LW, Greder KA. The effects of the local food environment and social support on rural food insecurity. J Hunger Environ Nutr. 2006;1:83–103.

Swinburn B, Sacks G, Vandevijvere S, Kumanyika S, Lobstein T, Neal B, Barquera S, Friel S, Hawkes C, Kelly B. INFORMAS (I nternational N etwork for F ood and O besity/non-communicable diseases R esearch, M onitoring and A ction S upport): overview and key principles. Obes Rev. 2013;14:1–12.

Glanz K, Johnson L, Yaroch AL, Phillips M, Ayala GX, Davis EL. Measures of retail food store environments and sales: review and implications for healthy eating initiatives. J Nutr Educ Behav. 2016;48(280–288): e281.

Begemann F. Ecogeographic differentiation of bambarra groundnut (Vigna subterranea) in the collection of the International Institute of Tropical Agriculture (IITA, (Wissenschaftlicher Fachverlag). 1988.

Lee A, Mhurchu CN, Sacks G, Swinburn B, Snowdon W, Vandevijvere S, Hawkes C, L’Abbé M, Rayner M, Sanders D. Monitoring the price and affordability of foods and diets globally. Obes Rev. 2013;14:82–95.

Rao M, Afshin A, Singh G, Mozaffarian D. Do healthier foods and diet patterns cost more than less healthy options? A systematic review and meta-analysis. BMJ Open. 2013;3: e004277.

Palermo C, McCartan J, Kleve S, Sinha K, Shiell A. A longitudinal study of the cost of food in Victoria influenced by geography and nutritional quality. Aust N Z J Public Health. 2016;40:270–3.

Lee AJ, Kane S, Ramsey R, Good E, Dick M. Testing the price and affordability of healthy and current (unhealthy) diets and the potential impacts of policy change in Australia. BMC Public Health. 2016;16:1–22.

Clark P, Mendoza-Gutiérrez CF, Montiel-Ojeda D, Denova-Gutiérrez E, López-González D, Moreno-Altamirano L, Reyes A. A healthy diet is not more expensive than less healthy options: cost-analysis of different dietary patterns in Mexican children and adolescents. Nutrients. 2021;13:3871.

Burns C, Friel S. It’s time to determine the cost of a healthy diet in Australia. Aust N Z J Public Health. 2007;31:363–5.

Lewis M, Lee A. Costing ‘healthy’food baskets in Australia–a systematic review of food price and affordability monitoring tools, protocols and methods. Public Health Nutr. 2016;19:2872–86.

Moayyed H, Kelly B, Feng X, Flood V. Is living near healthier food stores associated with better food intake in regional Australia? Int J Environ Res Public Health. 2017;14:884.

Seal J. Monitoring the price and availability of healthy food–time for a national approach? Nutr Diet. 2004;61:197–200.

Moher D, Liberati A, Tetzlaff J, Altman D. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151:264–9.

Caspi CE, Sorensen G, Subramanian S, Kawachi I. The local food environment and diet: a systematic review. Health Place. 2012;18:1172–87.

Love P, Whelan J, Bell C, McCracken J. Measuring rural food environments for local action in Australia: a systematic critical synthesis review. Int J Environ Res Public Health. 2019;16:2416.

Covidence systematic review software. Volume 2022. (Melbourne, Australia: Veritas Health Innovation).

The Endnote Team. Endnote. Endnote. X9 ed. Philadelphia, PA: Clarivate; 2013.

Braun V, Clarke V. Reflecting on reflexive thematic analysis. Qual Res Sport Exerc Health. 2019;11:589–97.

Aaron GJ, Keim NL, Drewnowski A, Townsend MS. Estimating dietary costs of low-income women in California: a comparison of 2 approaches. Am J Clin Nutr. 2013;97:835–41.

Andreyeva T, Blumenthal DM, Schwartz MB, Long MW, Brownell KD. Availability and prices of foods across stores and neighborhoods: the case of New Haven, Connecticut. Health affairs (Project Hope). 2008;27:1381–8.

Anekwe TD, Rahkovsky I. The association between food prices and the blood glucose level of US adults with type 2 diabetes. Am J Public Health. 2014;104:678–85.

Bernstein AM, Bloom DE, Rosner BA, Franz M, Willett WC. Relation of food cost to healthfulness of diet among US women. Am J Clin Nutr. 2010;92:1197–203.

Borja K, Dieringer S. Availability of affordable healthy food in Hillsborough County, Florida. J Public Aff (14723891). 2019;19. N.PAG-N.PAG.

Bronchetti ET, Christensen G, Hoynes HW. Local food prices, SNAP purchasing power, and child health. J Health Econ. 2019;68: 102231.

Buszkiewicz J, House C, Anju A, Long M, Drewnowski A, Otten JJ. The impact of a city-level minimum wage policy on supermarket food prices by food quality metrics: a two-year follow up study. Int J Environ Res Public Health. 2019;16:102.

Caspi CE, Pelletier JE, Harnack LJ, Erickson DJ, Lenk K, Laska MN. Pricing of staple foods at supermarkets versus small food stores. Int J Environ Res Public Health. 2017;14.

Christensen G, Bronchetti ET. Local food prices and the purchasing power of SNAP benefits. Food Policy. 2020;95. N.PAG-N.PAG.

Colabianchi N, Antonakos CL, Coulton CJ, Kaestner R, Lauria M, Porter DE. The role of the built environment, food prices and neighborhood poverty in fruit and vegetable consumption: an instrumental variable analysis of the moving to opportunity experiment. Health Place. 2021;67: 102491.

Cole S, Filomena S, Morland K. Analysis of fruit and vegetable cost and quality among racially segregated neighborhoods in Brooklyn. New York J Hunger Environ Nutr. 2010;5:202–15.

Connell CL, Zoellner JM, Yadrick MK, Chekuri SC, Crook LB, Bogle ML. Energy density, nutrient adequacy, and cost per serving can provide insight into food choices in the lower Mississippi Delta. J Nutr Educ Behav. 2012;44:148–53.

DiSantis KI, Grier SA, Oakes JM, Kumanyika SK. Food prices and food shopping decisions of black women. Appetite. 2014;77:106–14.

Fan L, Canales E, Fountain B, Buys D. An assessment of the food retail environment in counties with high obesity rates in Mississippi. J Hunger Environ Nutr. 2021;16:571–93.

Franzen L, Smith C. Food system access, shopping behavior, and influences on purchasing groceries in adult Hmong living in Minnesota. Am J Health Promot. 2010;24:396–409.

Ghosh-Dastidar B, Cohen D, Hunter G, Zenk SN, Huang C, Beckman R, Dubowitz T. Distance to store, food prices, and obesity in urban food deserts. Am J Prev Med. 2014;47:587–95.

Ghosh-Dastidar M, Hunter G, Collins RL, Zenk SN, Cummins S, Beckman R, Nugroho AK, Sloan JC, Wagner LV, Dubowitz T, et al. Does opening a supermarket in a food desert change the food environment? Health Place. 2017;46:249–56.

Greenberg JA, Luick B, Alfred JM, Barber LR Jr, Bersamin A, Coleman P, Esquivel M, Fleming T, Guerrero RTL, Hollyer J, et al. The affordability of a thrifty food plan-based market basket in the United States-affiliated Pacific Region. Hawaii J Med Public Health. 2020;79:217–23.

Hardin-Fanning F, Rayens MK. Food cost disparities in rural communities. Health Promot Pract. 2015;16:383–91.

Hardin-Fanning F, Wiggins AT. Food costs are higher in counties with poor health rankings. J Cardiovasc Nurs. 2017;32:93–8.

Hilbert N, Evans-Cowley J, Reece J, Rogers C, Ake W, Hoy C. Mapping the cost of a balanced diet, as a function of travel time and food price. Journal of Agriculture, Food Systems and Community Development. 2014;5:105–27.

Hillen J. Online food prices during the COVID-19 pandemic. Agribusiness (New York). 2021;37:91–107.

Jin H, Lu Y. Evaluating consumer nutrition environment in food deserts and food swamps. Int J Environ Res Public Health. 2021;18.

Karp RJ, Wong G, Orsi M. Demonstrating nutrient cost gradients: a Brooklyn case study. Int J Vitam Nutr Res. 2014;84:244–51.

Ko LK, Enzler C, Perry CK, Rodriguez E, Mariscal N, Linde S, Duggan C. Food availability and food access in rural agricultural communities: use of mixed methods. BMC Public Health. 2018;18. N.PAG-N.PAG.

Lee Smith M, Sunil TS, Salazar CI, Rafique S, Ory MG. Disparities of food availability and affordability within convenience stores in Bexar County. Texas J Environ Public Health. 2013;2013:1–7.

Lipsky LM. Are energy-dense foods really cheaper? Reexamining the relation between food price and energy density. Am J Clin Nutr. 2009;90:1397–401.

Martin KS, Ghosh D, Page M, Wolff M, McMinimee K, Zhang M. What role do local grocery stores play in urban food environments? A case study of Hartford-Connecticut. PLoS ONE. 2014;9: e94033.

Mayfield KE, Hession SL, Weatherspoon L, Hoerr SL. A cross-sectional analysis exploring differences between food availability, food price, food quality and store size and store location in Flint Michigan. J Hunger Environ Nutr. 2020;15:643–57.

Meyerhoefer CD, Leibtag ES. A spoonful of sugar helps the medicine go down: the relationship between food prices and medical expenditures on diabetes. Am J Agr Econ. 2010;92:1271–82.

Monsivais P, Drewnowski A. The rising cost of low-energy-density foods. J Am Diet Assoc. 2007;107:2071–6.

Monsivais P, McLain J, Drewnowski A. The rising disparity in the price of healthful foods: 2004–2008. Food Policy. 2010;35:514–20.

Monsivais P, Perrigue MM, Adams SL, Drewnowski A. Measuring diet cost at the individual level: a comparison of three methods. Eur J Clin Nutr. 2013;67:1220–5.

Nansel TR, Lipsky LM, Eisenberg MH, Liu A, Mehta SN, Laffel LMB. Can families eat better without spending more? Improving diet quality does not increase diet cost in a randomized clinical trial among youth with type 1 diabetes and their parents. J Acad Nutr Diet. 2016;116:1751.

Otten JJ, Buszkiewicz J, Tang W, Anju A, Long M, Vigdor J, Drewnowski A. The impact of a city-level minimum-wage policy on supermarket food prices in Seattle-King County. Int J Environ Res Public Health. 2017;14:1039.

Richards R, Smith C. Shelter environment and placement in community affects lifestyle factors among homeless families in Minnesota. Am J Health Promot. 2006;21:36–44.

Shen Y, Clarke P, Gomez-Lopez IN, Hill AB, Romero DM, Goodspeed R, Berrocal VJ, Vydiswaran VV, Veinot TC. Using social media to assess the consumer nutrition environment: comparing Yelp reviews with a direct observation audit instrument for grocery stores. Public Health Nutr. 2019;22:257–64.

Smith C, Butterfass J, Richards R. Environment influences food access and resulting shopping and dietary behaviors among homeless Minnesotans living in food deserts. Agric Hum Values. 2010;27:141–61.

Spoden AL, Buszkiewicz JH, Drewnowski A, Long MC, Otten JJ. Seattle’s minimum wage ordinance did not affect supermarket food prices by food processing category. Public Health Nutr. 2018;21:1762–70.

Stroebele-Benschop N, Wolf K, Palmer K, Kelley CJ, Jilcott Pitts SB. Comparison of food and beverage products’ availability, variety, price and quality in German and US supermarkets. Public Health Nutr. 2020;23:3387–93.

Townsend MS, Aaron GJ, Monsivais P, Keim NL, Drewnowski A. Less-energy-dense diets of low-income women in California are associated with higher energy-adjusted diet costs. Am J Clin Nutr. 2009;89:1220–6.

Wright L, Palak G, Yoshihara K. Accessibility and affordability of healthy foods in food deserts in Florida: policy and practice implications. Florida Public Health Review. 2018;15:98–103.

Yang Y, Leung P. Price premium or price discount for locally produced food products? A temporal analysis for Hawaii. J Asian Pac Econ. 2020;25:591–610.

Zenk SN, Grigsby-Toussaint DS, Curry SJ, Berbaum M, Schneider L. Short-term temporal stability in observed retail food characteristics. J Nutr Educ Behav. 2010;42:26–32.

Abreu MD, Charlton K, Probst Y, Li N, Crino M, Wu JHY. Nutrient profiling and food prices: what is the cost of choosing healthier products? J Hum Nutr Diet. 2019;32:432–42.

Ball K, Timperio A, Crawford D. Neighbourhood socioeconomic inequalities in food access and affordability. Health Place. 2009;15:578–85.

Brimblecombe J, Ferguson M, Liberato SC, O’Dea K, Riley M. Optimisation modelling to assess cost of dietary improvement in remote aboriginal Australia. PLoS ONE. 2013;8: e83587.

Chapman K, Innes-Hughes C, Goldsbury D, Kelly B, Bauman A, Allman-Farinelli M. A comparison of the cost of generic and branded food products in Australian supermarkets. Public Health Nutr. 2013;16:894–900.

Cuttler R, Evans R, McClusky E, Purser L, Klassen KM, Palermo C. An investigation of the cost of food in the Geelong region of rural Victoria: essential data to support planning to improve access to nutritious food. Health Promot J Austr. 2019;30:124–7.

Ferguson M, O’Dea K, Chatfield M, Moodie M, Altman J, Brimblecombe J. The comparative cost of food and beverages at remote Indigenous communities, Northern Territory, Australia. Aust N Z J Public Health. 2016;40(Suppl 1):S21–6.

Ferguson M, O’Dea K, Holden S, Miles E, Brimblecombe J. Food and beverage price discounts to improve health in remote Aboriginal communities: mixed method evaluation of a natural experiment. Aust N Z J Public Health. 2017;41:32–7.

Harrison MS, Coyne T, Lee AJ, Leonard D, Lowson S, Groos A, Ashton BA. The increasing cost of the basic foods required to promote health in Queensland. Med J Aust. 2007;186:9–14.

Kettings C, Sinclair AJ, Voevodin M. A healthy diet consistent with Australian health recommendations is too expensive for welfare-dependent families. Aust N Z J Public Health. 2009;33:566–72.

Lee A, Patay D, Herron L-M, Parnell Harrison E, Lewis M. Affordability of current, and healthy, more equitable, sustainable diets by area of socioeconomic disadvantage and remoteness in Queensland: insights into food choice. Int J Equity Health. 2021;20:1–17.

Lee AJ, Kane S, Herron L-M, Matsuyama M, Lewis M. A tale of two cities: the cost, price-differential and affordability of current and healthy diets in Sydney and Canberra, Australia. Int J Behav Nutr Phys Act. 2020;17:1–13.

Palermo CE, Walker KZ, Hill P, McDonald J. The cost of healthy food in rural Victoria. Rural Remote Health. 2008;8. (1 December 2008).

Pollard CM, Landrigan TJ, Ellies PL, Kerr DA, Lester MLU, Goodchild SE. Geographic factors as determinants of food security: a Western Australian food pricing and quality study. Asia Pac J Clin Nutr. 2014;23:703–13.

Tsang A, Ndung’u MW, Coveney J, O’Dwyer L. Adelaide Healthy Food Basket: a survey on food cost, availability and affordability in five local government areas in metropolitan Adelaide, South Australia. Nutr Diet. 2007;64:241–7.

Walton K, do Rosario V, Kucherik M, Frean P, Richardson K, Turner M, Mahoney J, Charlton K, Andre do Rosario V. Identifying trends over time in food affordability: the Illawarra Healthy Food Basket survey, 2011–2019. Health Promot J Austr. 2021;1–1.

Ward PR, Coveney J, Verity F, Carter P, Schilling M. Cost and affordability of healthy food in rural South Australia. Rural Remote Health 2012;12. Article No. 1938.

Wong K, Coveney J, Ward P, Muller R, Carter P, Verity F, Tsourtos G. Availability, affordability and quality of a healthy food basket in Adelaide, South Australia. Nutr Diet. 2011;68:8–14.

Burns C, Sacks G, Gold L. Longitudinal study of Consumer Price Index (CPI) trends in core and non-core foods in Australia. Aust N Z J Public Health. 2008;32:450–3.

Zorbas C, Lee A, Peeters A, Lewis M, Landrigan T, Backholer K. Streamlined data-gathering techniques to estimate the price and affordability of healthy and unhealthy diets under different pricing scenarios. Public Health Nutr. 2021;24:1–11.

Conklin AI, Monsivais P, Khaw K, Wareham NJ, Forouhi NG. Dietary diversity, diet cost, and incidence of type 2 diabetes in the United Kingdom: a prospective cohort study. PLoS Med. 2016;13: e1002085.

Jones NRV, Tong TYN, Monsivais P. Meeting UK dietary recommendations is associated with higher estimated consumer food costs: an analysis using the National Diet and Nutrition Survey and consumer expenditure data, 2008–2012. Public Health Nutr. 2018;21:948–56.

Lan H, Lloyd T, Morgan W, Dobson PW. Are food price promotions predictable? The hazard function of supermarket discounts. J Agric Econ. 2021;1.

Mackenbach JD, Burgoine T, Lakerveld J, Forouhi NG, Griffin SJ, Wareham NJ, Monsivais P. Accessibility and affordability of supermarkets: associations with the DASH diet. Am J Prev Med. 2017;53:55–62.

Monsivais P, Scarborough P, Lloyd T, Mizdrak A, Luben R, Mulligan AA, Wareham NJ, Woodcock J. Greater accordance with the Dietary Approaches to Stop Hypertension dietary pattern is associated with lower diet-related greenhouse gas production but higher dietary costs in the United Kingdom. Am J Clin Nutr. 2015;102:138–45.

Timmins KA, Hulme C, Cade JE. The monetary value of diets consumed by British adults: an exploration into sociodemographic differences in individual-level diet costs. Public Health Nutr. 2015;18:151–9.

Timmins KA, Morris MA, Hulme C, Edwards KL, Clarke GP, Cade JE. Comparability of methods assigning monetary costs to diets: derivation from household till receipts versus cost database estimation using 4-day food diaries. Eur J Clin Nutr. 2013;67:1072–6.

Vogel C, Abbott G, Ntani G, Barker M, Cooper C, Moon G, Ball K, Baird J. Examination of how food environment and psychological factors interact in their relationship with dietary behaviours: test of a cross-sectional model. Int J Behav Nutr Phys Act. 2019;16. N.PAG-N.PAG.

Kenny T-A, Fillion M, MacLean J, Wesche SD, Chan HM. Calories are cheap, nutrients are expensive – the challenge of healthy living in Arctic communities. Food Policy. 2018;80:39–54.

Latham J, Moffat T. Determinants of variation in food cost and availability in two socioeconomically contrasting neighbourhoods of Hamilton, Ontario, Canada. Health Place. 2007;13:273–87.

Lear SA, Gasevic D, Schuurman N. Association of supermarket characteristics with the body mass index of their shoppers. Nutr J. 2013;12. (13 August 2013).

Mah CL. Taylor N. Store patterns of availability and price of food and beverage products across a rural region of Newfoundland and Labrador. Canadian journal of public health = Revue canadienne de sante publique. 2020;111:247–256.

Minaker LM, Raine KD, Wild TC, Nykiforuk CIJ, Thompson ME, Frank LD. Objective food environments and health outcomes. Am J Prev Med. 2013;45:289–96.

Minaker LM, Raine KD, Wild TC, Nykiforuk CIJ, Thompson ME, Frank LD. Construct validation of 4 food-environment assessment methods: adapting a multitrait-multimethod matrix approach for environmental measures. Am J Epidemiol. 2014;179:519–28.

Pakseresht M, Lang R, Rittmueller S, Roache C, Sheehy T, Batal M, Corriveau A, Sangita S. Food expenditure patterns in the Canadian Arctic show cause for concern for obesity and chronic disease. Int J Behav Nutr Phys Act. 2014;11. (17 April 2014).

Mackay S, Buch T, Vandevijvere S, Goodwin R, Korohina E, Funaki-Tahifote M, Lee A, Swinburn B. Cost and affordability of diets modelled on current eating patterns and on dietary guidelines, for New Zealand total population, Māori and Pacific households. Int J Environ Res Public Health. 2018;15.

Mackay S, Vandevijvere S, Lee A. Ten-year trends in the price differential between healthier and less healthy foods in New Zealand. Nutrition & dietetics: the journal of the Dietitians Association of Australia. 2019;76:271–6.

Vandevijvere S, Young N, Mackay S, Swinburn B, Gahegan M. Modelling the cost differential between healthy and current diets: the New Zealand case study. Int J Behav Nutr Phys Act. 2018;15:1–1.

Wilson N, Nghiem N, Mhurchu CN, Eyles H, Baker MG, Blakely T. Foods and dietary patterns that are healthy, low-cost, and environmentally sustainable: a case study of optimization modeling for New Zealand. PLoS ONE. 2013;8: e59648.

Alexy U, Bolzenius K, Köpper A, Clausen K, Kersting M. Diet costs and energy density in the diet of German children and adolescents. Eur J Clin Nutr. 2012;66:1362–3.

Stroebele N, Dietze P, Tinnemann P, Willich SN. Assessing the variety and pricing of selected foods in socioeconomically disparate districts of Berlin, Germany. J Public Health. 2011;19:23–8.

Albuquerque G, Moreira P, Rosário R, Araújo A, Teixeira VH, Lopes O, Moreira A, Padrão P. Adherence to the Mediterranean diet in children: Is it associated with economic cost? Porto biomedical journal. 2017;2:115–9.

Alves R, Lopes C, Rodrigues S, Perelman J. Adhering to a Mediterranean diet in a Mediterranean country: an excess cost for families? Br J Nutr. 2021;1–24.

Faria AP, Albuquerque G, Moreira P, Rosário R, Araújo A, Teixeira V, Barros R, Lopes Ó, Moreira A, Padrão P. Association between energy density and diet cost in children. Porto Biomed J. 2016;1:106–11.

Mackenbach JD, Dijkstra SC, Beulens JWJ, Seidell JC, Snijder MB, Stronks K, Monsivais P, Nicolaou M. Socioeconomic and ethnic differences in the relation between dietary costs and dietary quality: the HELIUS study. Nutr J. 2019;18. N.PAG-N.PAG.

Waterlander WE, de Haas WE, van Amstel I, Schuit AJ, Twisk JWR, Visser M, Seidell JC, Steenhuis IHM. Energy density, energy costs and income - how are they related? Public Health Nutr. 2010;13:1599–608.

Rydén P, Mattsson Sydner Y, Hagfors L. Counting the cost of healthy eating: a Swedish comparison of Mediterranean-style and ordinary diets. Int J Consum Stud. 2008;32:138–46.

Rydén PJ, Hagfors L. Diet cost, diet quality and socio-economic position: how are they related and what contributes to differences in diet costs? Public Health Nutr. 2011;14:1680–92.

Keiko S, Kentaro M, Hitomi O, Livingstone MBE, Satomi K, Hitomi S, Satoshi S. Nutritional correlates of monetary diet cost in young, middle-aged and older Japanese women. J Nutr Sci. 2017;6:1–11.

Bolarić M, Šatalić Z. The relation between food price, energy density and diet quality. Croatian Journal of Food Science and Technology. 2013;5:39–45.

Parlesak A, Tetens I, Jensen JD, Smed S, Blenkuš MG, Rayner M, Darmon N, Robertson A. Use of linear programming to develop cost-minimized nutritionally adequate health promoting food baskets. PLoS ONE. 2016;11: e0163411.

Marty L, Dubois C, Gaubard MS, Maidon A, Lesturgeon A, Gaigi H, Darmon N. Higher nutritional quality at no additional cost among low-income households: insights from food purchases of “positive deviants.” Am J Clin Nutr. 2015;102:190–8.

Ng SW, Slining MM, Popkin BM. Turning point for US diets? Recessionary effects or behavioral shifts in foods purchased and consumed. Am J Clin Nutr. 2014;99:609–16.

Lee AJ, Kane S, Lewis M, Good E, Pollard CM, Landrigan TJ, Dick M. Healthy diets ASAP–Australian standardised affordability and pricing methods protocol. Nutr J. 2018;17:1–14.

Lee A, Lewis M. Testing the price of healthy and current diets in remote Aboriginal communities to improve food security: development of the Aboriginal and Torres Strait Islander Healthy Diets ASAP (Australian Standardised Affordability and Pricing) methods. Int J Environ Res Public Health. 2018;15:2912.

Ferguson M, O’Dea K, Chatfield M, Moodie M, Altman J, Brimblecombe J. The comparative cost of food and beverages at remote Indigenous communities, Northern Territory, Australia. Aust N Z J Public Health. 2016;40:S21–6.

Zorbas C, Gilham B, Boelsen-Robinson T, Blake MR, Peeters A, Cameron AJ, Wu JH, Backholer K. The frequency and magnitude of price-promoted beverages available for sale in Australian supermarkets. Aust N Z J Public Health. 2019;43:346–51.

Bourke L, Humphreys JS, Wakerman J, Taylor J. Understanding rural and remote health: a framework for analysis in Australia. Health Place. 2012;18:496–503.

Alston LV, Bolton KA, Whelan J, Reeve E, Shee AW, Browne J, Walker T, Versace VL, Allender S, Nichols M. Retail initiatives to improve the healthiness of food environments in rural, regional and remote communities. Med J Aust. 2020;213:S5.

Cafer AM, Kaiser ML. An analysis of differences in predictors of food affordability between rural and urban counties. J Poverty. 2016;20:34–55.

Drysdale C, Sykes E, Honeysett C. WHO urges governments to promote healthy food in public facilities. 2021;2022.

Willet W. Summary report of the EAT-Lancet Commission on healthy diets from sustainable food systems. E.-L. Commission, ed. (Eat-Lancet Commission ). 2019.

Food and Organization A. The State of Food Security and Nutrition in the World 2021. (Food and Agriculture Organization Rome). 2021.

Download references

Open Access funding enabled and organized by CAUL and its Member Institutions CR is supported by an Australian Government Research Training Scholarship. This funder had no involvement in any aspect of the study. JW is funded by a Deakin University Dean’s Postdoctoral Research Fellowship. JW is also supported by the National Health and Medical Research Council (NHMRC) funded Centre of Research Excellence in Food Retail Environments for Health (RE-FRESH) (APP1152968). The opinions, analysis, and conclusions in this paper are those of the authors and should not be attributed to the NHMRC.

Author information

Authors and affiliations.

School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia

Cherie Russell & Penelope Love

School of Medicine, Institute for Health Transformation, Deakin University, Geelong, Australia

Jillian Whelan

Institute for Physical Activity and Nutrition, Deakin University, Geelong, Australia

Penelope Love

You can also search for this author in PubMed   Google Scholar

Contributions

Conceptualisation: Penelope Love and Jillian Whelan; Methodology: all authors; Data extraction and synthesis: Cherie Russell; Writing—original draft preparation: Cherie Russell; Writing—review and editing: all authors.

Corresponding author

Correspondence to Cherie Russell .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Public Health Nutrition

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 47 kb)

Supplementary file2 (docx 39 kb), rights and permissions.

Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Russell, C., Whelan, J. & Love, P. Assessing the Cost of Healthy and Unhealthy Diets: A Systematic Review of Methods. Curr Nutr Rep 11 , 600–617 (2022). https://doi.org/10.1007/s13668-022-00428-x

Download citation

Accepted : 11 July 2022

Published : 09 September 2022

Issue Date : December 2022

DOI : https://doi.org/10.1007/s13668-022-00428-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Food pricing
• Measurement instruments
• Food environments

Advertisement

• Find a journal
• Publish with us
• Track your research

Link between diet and disease depends on measuring the right data

May 9, 2024 – In the 1970s, researchers first noticed an interesting trend in cancer data: disease rates in countries around the world varied greatly, even when taking into account biological differences between populations. One hypothesis was that the differences in cancer rates occurred due to environmental factors—in particular, variations in diet . Indeed, when researchers compared population-level data about food intake, they found that consuming fats and oils was associated with developing cancer.

“Based on not much more than this evidence, dietary guidelines across the United States and across the world emphasized reducing fat in the diet,” said Walter Willett , professor of epidemiology and nutrition at Harvard T.H. Chan School of Public Health, speaking on May 3 at the 8th Cutter Symposium .

But since then, according to Willett, study after study has found that the association between dietary fat and cancer rates does not hold up. One rigorous study , conducted in the 1990s to early 2000s, involved tens of thousands of individuals and directly compared those who reduced the amount of fat in their diets with those who did not. After collecting data from the individuals for several years, researchers did not find a significant reduction in breast cancer in the low-fat diet group.

“Clearly, if you put the data together, [the link] is very, very null,” said Willett. He noted that subsequent studies investigated specific types of dietary fats, rather than grouping them all into one category. In general, the studies found that trans and saturated fats led to higher disease risks, while unsaturated fats did not. Importantly, the results depended on data analyses that controlled for hidden, so-called confounding factors other than diet that contributed to disease—something that the 1970s research did not address.

The symposium focused on one of the major challenges of obtaining accurate results in nutrition studies—the role of confounding factors in studying the impact of diet on disease.

Organized by the Department of Epidemiology , the Cutter Lectures on Preventive Medicine are held once or twice a year, funded by a bequest from John Clarence Cutter, a graduate of Harvard Medical School.

Need for careful data analysis

In nutrition studies, when researchers analyze data and find a potential connection between diet and disease risk, they need to account for confounding factors that might be responsible instead, according to the symposium speakers, who included Donna Spiegelman, Susan Dwight Bliss Professor of Biostatistics at the Yale University School of Public Health, and Richard Peto, emeritus professor of medical statistics and epidemiology at the University of Oxford.

Spiegelman explained that people who have healthy diets may also follow healthy lifestyles in general, which include aspects like exercising , refraining from smoking or drinking alcohol , and seeing a doctor regularly. She said that if confounding factors such as these are not measured and analyzed accurately during studies, the results may not show the true impact of diet. She has developed statistical methods and software to help address issues of confounding.

Still, Spiegelman concluded that despite the challenges of determining precisely how different diets affect disease risks, the collective body of studies in the nutrition field shows that diet does indeed have an impact.

“For me, the diet-health associations are so strong that I have moved on to implementation research to translate the knowledge already in place to improve public health,” she said.

Photo: Kent Dayton

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Review Article
• Open access
• Published: 12 September 2019

The effects of plant-based diets on the body and the brain: a systematic review

• Evelyn Medawar   ORCID: orcid.org/0000-0001-5011-8275 1 , 2 , 3 ,
• Sebastian Huhn 4 ,
• Arno Villringer 1 , 2 , 3 &
• A. Veronica Witte 1  

Translational Psychiatry volume  9 , Article number:  226 ( 2019 ) Cite this article

311k Accesses

188 Citations

1439 Altmetric

Metrics details

• Human behaviour
• Molecular neuroscience
• Psychiatric disorders

Western societies notice an increasing interest in plant-based eating patterns such as vegetarian and vegan, yet potential effects on the body and brain are a matter of debate. Therefore, we systematically reviewed existing human interventional studies on putative effects of a plant-based diet on the metabolism and cognition, and what is known about the underlying mechanisms. Using the search terms “plant-based OR vegan OR vegetarian AND diet AND intervention” in PubMed filtered for clinical trials in humans retrieved 205 studies out of which 27, plus an additional search extending the selection to another five studies, were eligible for inclusion based on three independent ratings. We found robust evidence for short- to moderate-term beneficial effects of plant-based diets versus conventional diets (duration ≤ 24 months) on weight status, energy metabolism and systemic inflammation in healthy participants, obese and type-2 diabetes patients. Initial experimental studies proposed novel microbiome-related pathways, by which plant-based diets modulate the gut microbiome towards a favorable diversity of bacteria species, yet a functional “bottom up” signaling of plant-based diet-induced microbial changes remains highly speculative. In addition, little is known, based on interventional studies about cognitive effects linked to plant-based diets. Thus, a causal impact of plant-based diets on cognitive functions, mental and neurological health and respective underlying mechanisms has yet to be demonstrated. In sum, the increasing interest for plant-based diets raises the opportunity for developing novel preventive and therapeutic strategies against obesity, eating disorders and related comorbidities. Still, putative effects of plant-based diets on brain health and cognitive functions as well as the underlying mechanisms remain largely unexplored and new studies need to address these questions.

Similar content being viewed by others

Long-term weight loss effects of semaglutide in obesity without diabetes in the SELECT trial

Microdosing with psilocybin mushrooms: a double-blind placebo-controlled study

Investigating nutrient biomarkers of healthy brain aging: a multimodal brain imaging study

Introduction.

Western societies notice an increasing interest in plant-based eating patterns such as avoiding meat or fish or fully excluding animal products (vegetarian or vegan, see Fig.  1 ). In 2015, around 0.4−3.4% US adults, 1−2% British adults, and 5−10% of German adults were reported to eat largely plant-based diets 1 , 2 , 3 , 4 , due to various reasons (reviewed in ref. 5 ). Likewise, the number of scientific publications on PubMed (Fig.  2 ) and the public popularity as depicted by Google Trends (Fig.  3 ) underscore the increased interest in plant-based diets. This increasing awareness calls for a better scientific understanding of how plant-based diets affect human health, in particular with regard to potentially relevant effects on mental health and cognitive functions.

From left to right: including all food items (omnivore), including all except for meat (pesco-vegetarian) or meat and fish (ovo-lacto-vegetarian) to including only plant-based items (vegan)

Frequency of publications on PubMed including the search terms “vegan” (in light green), vegetarian (in orange) and plant-based (dark green)—accessed on 19 April 2019

Note indicates technical improvements implemented by Google Trends. Data source: Google Trends . Search performed on 18 April 2019

A potential effect of plant-based diets on mortality rate remains controversial: large epidemiological studies like the Adventist studies ( n  = 22,000−96,000) show a link between plant-based diets, lower all-cause mortality and cardiovascular diseases 6 , 7 , while other studies like the EPIC-Oxford study and the “45 and Up Study” ( n  = 64,000−267,000) show none 8 , 9 . Yet, many, but not all, epidemiological and interventional human studies in the last decades have suggested that plant-based diets exert beneficial health effects with regard to obesity-related metabolic dysfunction, type 2 diabetes mellitus (T2DM) and chronic low-grade inflammation (e.g. refs. 6 , 7 , 10 , 11 , for reviews, see refs. 12 , 13 , 14 , 15 , 16 , 17 , 18 ). However, while a putative link between such metabolic alterations and brain health through pathways which might include diet-related neurotransmitter precursors, inflammatory pathways and the gut microbiome 19 becomes increasingly recognized, the notion that plant-based diets exert influence on mental health and cognitive functions appears less documented and controversial 20 , 21 , 22 , 23 , 24 . We therefore systematically reviewed the current evidence based on available controlled interventional trials, regarded as the gold standard to assess causality, on potential effects of plant-based diets on (a) metabolic factors including the microbiome and (b) neurological or psychiatric health and brain functions. In addition, we aimed to evaluate potential underlying mechanisms and related implications for cognition.

We performed a systematic PubMed search with the following search terms “plant-based OR vegan OR vegetarian AND diet AND intervention” with the filter “clinical trial” and “humans”, preregistered at PROSPERO (CRD42018111856; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=111856 ) (Suppl. Fig.  1 ). PubMed was used as search engine because it was esteemed to yield the majority of relevant human clinical trials from a medical perspective. Exclusion criteria were insufficient design quality (such as lack of a control group), interventions without a plant-based or vegetarian or vegan diet condition, intervention with multiple factors (such as exercise and diet), and the exclusive report of main outcomes of no interest, such as dietary compliance, nutrient intake (such as vitamins or fiber intake), or nonmetabolic (i.e., not concerning glucose metabolism, lipid profile, gastrointestinal hormones or inflammatory markers) or non-neurological/psychiatric disease outcomes (e.g. cancer, caries).

Studies were independently rated for eligibility into the systematic review by three authors based on reading the abstract and, if needed, methods or other parts of the publication. If opinions differed, a consensus was reached through discussion of the individual study. This yielded 27 eligible out of 205 publications; see Table  1 for details. To increase the search radius for studies dealing with microbial and neurological/psychiatric outcomes, we deleted the search term “intervention”, which increased the number of studies by around one third, and checked for studies with “microbiome/microbiota”, “mental”, “cognitive/cognition” or “psychological/psychology” in the resulting records. Through this, we retrieved another five studies included in Table  1 . Further related studies were reviewed based on additional nonsystematic literature search.

Section I: Effects of plant-based diets on body and brain outcomes

Results based on interventional studies on metabolism, microbiota and brain function.

Overall, the vast majority of studies included in this systematic review reported a short-term beneficial effect of plant-based dietary interventions (study duration 3−24 months) on weight status, glucose, insulin and/or plasma lipids and inflammatory markers, whereas studies investigating whether plant-based diets affect microbial or neurological/psychiatric disease status and other brain functions were scarce and rather inconclusive (Table  1 ).

More specifically, 19 out of 32 studies dealing with T2DM and/or obese subjects and seven out of 32 dealing with healthy subjects observed a more pronounced weight loss and metabolic improvements, such as lowering of glycated hemoglobin (HbA1c)—a long-term marker for glucose levels—decreased serum levels of low-density (LDL) and high-density lipoproteins (HDL) and total cholesterol (TC), after a plant-based diet compared to an omnivore diet. This is largely in line with recent meta-analyses indicating beneficial metabolic changes after a plant-based diet 25 , 26 , 27 .

For example, Lee et al. found a significantly larger reduction of HbA1c and lower waist circumference after vegan compared to conventional dieting 28 . Jenkins et al. found a disease-attenuating effect in hyperlipidemic patients after 6 months adopting a low-carbohydrate plant-based diet compared to a high-carbohydrate lacto-ovo-vegetarian diet 29 , 30 . However, lower energy intake in the vegan dieters might have contributed to these effects. Yet, while a plant-based diet per se might lead to lower caloric intake, other studies observed nonsignificant trends toward higher effect sizes on metabolic parameters after a vegan diet, even when caloric intake was comparable: two studies in T2DM patients 31 , 32 compared calorie-unrestricted vegan or vegetarian to calorie-restricted conventional diets over periods of 6 months and 1.5 years, respectively, in moderate sample sizes ( n  ~ 75−99) with similar caloric intake achieved in both diet groups. Both studies indicated stronger effects of plant-based diets on disease status, such as reduced medication, improved weight status and increased glucose/insulin sensitivity, proposing a diabetes-preventive potential of plant-based diets. Further, a five-arm study comparing four types of plant-based diets (vegan, vegetarian, pesco-vegetarian, semi-vegetarian) to an omnivore diet (total n  = 63) in obese participants found the most pronounced effect on weight loss for a vegan diet (−7.5 ± 4.5% of total body weight) 33 . Here, inflammation markers conceptualized as the dietary inflammatory index were also found to be lower in vegan, vegetarian and pesco-vegetarian compared to semi-vegetarian overweight to obese dieters 33 .

Intriguingly, these results 28 , 29 , 30 , 31 , 32 , 33 cohesively suggest that although caloric intake was similar across groups, participants who had followed a vegan diet showed higher weight loss and improved metabolic status.

As a limitation, all of the reviewed intervention studies were carried out in moderate sample sizes and over a period of less than 2 years, disregarding that long-term success of dietary interventions stabilizes after 2−5 years only 34 . Future studies with larger sample sizes and tight control of dietary intake need to confirm these results.

Through our systematic review we retrieved only one study that added the gut microbiome as novel outcome for clinical trials investigating the effects of animal-based diets compared to plant-based diets. While the sample size was relatively low ( n  = 10, cross-over within subject design), it showed that changing animal- to plant based diet changed gut microbial activity towards a trade-off between carbohydrate and protein fermentation processes within only 5 days 35 . This is in line with another controlled-feeding study where microbial composition changes already occurred 24 h after changing diet (not exclusively plant-based) 36 . However, future studies incorporating larger sample sizes and a uniform analysis approach of microbial features need to further confirm the hypothesis that a plant-based diet ameliorates microbial diversity and health-related bacteria species.

Considering neurological or psychiatric diseases and brain functions, the systematic review yielded in six clinical trials of diverse clinical groups, i.e. migraine, multiple sclerosis, fibromyalgia and rheumatoid arthritis. Here, mild to moderate improvement, e.g. measured by antibody levels, symptom improvement or pain frequency, was reported in five out of six studies, sometimes accompanied by weight loss 37 , 38 , 39 , 40 (Table  1 ). However, given the pilot character of these studies, indicated by small sample sizes ( n  = 32−66), lack of randomization 37 , or that the plant-based diet was additionally free of gluten 40 , the evidence is largely anecdotal. One study in moderately obese women showed no effects on psychological outcomes 41 , two studies with obese and nonobese healthy adults indicated improvements in anxiety, stress and depressive symptom scores 23 , 24 . Taken together, the current evidence based on interventional trials regarding improvements of cognitive and emotional markers and in disease treatment for central nervous system disorders such as multiple sclerosis or fibromyalgia remains considerably fragmentary for plant-based diets.

Among observational studies, a recent large cross-sectional study showed a higher occurrence of depressive symptoms for vegetarian dieters compared to nonvegetarians 20 . Conversely, another observational study with a sample of about 80% women found a beneficial association between a vegan diet and mood disturbance 24 .

Overall, the relationship between mental health (i.e. depression) and restrictive eating patterns has been the focus of recent research 20 , 21 , 22 , 24 , 42 ; however, causal relationships remain uninvestigated due to the observational design.

Underlying mechanisms linking macronutrient intake to metabolic processes

On the one hand, nutrient sources as well as their intake ratios considerably differ between plant-based and omnivore diets (Suppl. Table  1 ), and on the other hand, dietary micro- and macromolecules as well as their metabolic substrates affect a diversity of physiological functions, pointing to complex interdependencies. Thus, it seems difficult to nail down the proposed beneficial effects of a plant-based diet on metabolic status to one specific component or characteristic, and it seems unlikely that the usually low amount of calories in plant-based diets could explain all observed effects. Rather, plant-based diets might act through multiple pathways, including better glycemic control 43 , lower inflammatory activity 44 and altered neurotransmitter metabolism via dietary intake 45 or intestinal activity 46 (Fig.  4 ).

BMI body-mass-index, HbA1c hemoglobin A1c, LDL-cholesterol low-density lipoprotein cholesterol, Trp tryptophan, Tyr tyrosine. Images from commons.wikimedia.org , “Brain human sagittal section” by Lynch 2006 and “Complete GI tract” by Häggström 2008, “Anatomy Figure Vector Clipart” by http://moziru.com

On the macronutrient level, plant-based diets feature different types of fatty acids (mono- and poly-unsaturated versus saturated and trans) and sugars (complex and unrefined versus simple and refined), which might both be important players for mediating beneficial health effects 18 . On the micronutrient level, the EPIC-Oxford study provided the largest sample of vegan dieters worldwide ( n (vegan) = 2396, n (total) = 65,429) and showed on the one hand lower intake of saturated fatty acids (SFA), retinol, vitamin B12 and D, calcium, zinc and protein, and on the other hand higher intake of fiber, magnesium, iron, folic acid, vitamin B1, C and E in vegan compared to omnivore dieters 47 . Other studies confirmed the variance of nutrient intake across dietary groups, i.e. omnivores, vegetarians and vegans, showing the occurrence of critical nutrients for each group 48 , 49 . Not only the amount of SFA but also its source and profile might be important factors regulating metabolic control (reviewed in ref. 14 ), for example through contributing to systemic hyperlipidemia and subsequent cardiovascular risk. Recently, it has been shown in a 4-week intervention trial that short-term dietary changes favoring a diet high in animal-based protein may lead to an increased risk for cardiovascular derangements mediated by higher levels of trimethylamine N-oxide (TMAO), which is a metabolite of gut bacteria-driven metabolic pathways 50 .

Secondly, high fiber intake from legumes, grains, vegetables and fruits is a prominent feature of plant-based diets (Table  1 ), which could induce beneficial metabolic processes like upregulated carbohydrate fermentation and downregulated protein fermentation 35 , improved gut hormonal-driven appetite regulation 51 , 52 , 53 , 54 , 55 , and might prevent chronic diseases such as obesity and T2DM by slowing down digestion and improving lipid control 56 . A comprehensive review including evidence from 185 prospective studies and 58 clinical trials concluded that risk reduction for a myriad of diseases (incl. CVD, T2DM, stroke incidence) was greatest for daily fiber intake between 25 and 29 g 57 . Precise evidence for underlying mechanisms is missing; however, more recently it has been suggested that high fiber intake induces changes on the microbial level leading to lower long-term weight gain 58 , a mechanism discussed below.

The reason for lower systemic inflammation in plant-based dieters could be due to the abundance of antiinflammatory molecule intake and/or avoidance of proinflammatory animal-derived molecules. Assessing systemic inflammation is particularly relevant for medical conditions such as obesity, where it has been proposed to increase the risk for cardiovascular disease 59 , 60 . In addition, higher C-reactive protein (CRP) and interleukin-6 (IL-6) levels have been linked with measures of brain microstructure, such as microstructural integrity and white matter lesions 61 , 62 , 63 and higher risk of dementia 64 , and recent studies point out that a diet-related low inflammatory index might also directly affect healthy brain ageing 65 , 66 .

Interventional studies that focus on plant- versus meat-based proteins or micronutrients and potential effects on the body and brain are lacking. A meta-analysis including seven RCTs and one cross-sectional studies on physical performance and dietary habits concluded that a vegetarian diet did not adversely influence physical performance compared to an omnivore diet 67 . An epidemiological study by Song et al. 11 estimated that statistically replacing 3% of animal protein, especially from red meat or eggs, with plant protein would significantly improve mortality rates. This beneficial effect might however not be explained by the protein source itself, but possibly by detrimental components found in meat (e.g. heme-iron or nitrosamines, antibiotics, see below).

Some studies further hypothesized that health benefits observed in a plant-based diet stem from higher levels of fruits and vegetables providing phytochemicals or vitamin C that might boost immune function and eventually prevent certain types of cancer 68 , 69 , 70 . A meta-analysis on the effect of phytochemical intake concluded a beneficial effect on CVD, cancer, overweight, body composition, glucose tolerance, digestion and mental health 71 . Looking further on the impact of micronutrients and single dietary compounds, there is room for speculation that molecules, that are commonly avoided in plant-based diets, might affect metabolic status and overall health, such as opioid-peptides derived from casein 72 , pre- and probiotics 73 , 74 , carry-over antibiotics found in animal products 75 , 76 or food-related carcinogenic toxins, such as dioxin found in eggs or nitrosamines found in red and processed meat 77 , 78 . Although conclusive evidence is missing, these findings propose indirect beneficial effects on health deriving from plant-based compared to animal-based foods, with a potential role for nonprotein substances in mediating those effects 18 . While data regarding chemical contaminant levels (such as crop pesticides, herbicides or heavy metals) in different food items are fragmentary only, certain potentially harmful compounds may be more (or less) frequently consumed in plant-based diets compared to more animal-based diets 79 . Whether these differences lead to systematic health effects need to be explored.

Taken together, the reviewed studies indicating effects of plant-based diets through macro- and micronutrient intake reveal both the potential of single ingredients or food groups (low SFA, high fiber) and the immense complexity of diet-related mechanisms for metabolic health. As proposed by several authors, benefits on health related to diet can probably not be viewed in isolation for the intake (or nonintake) of specific foods, but rather by additive or even synergistic effects between them (reviewed in refs. 12 , 80 ). Even if it remains a challenging task to design long-term RCTs that control macro- and micronutrient levels across dietary intervention groups, technological advancements such as more fine-tuned diagnostic measurements and automated self-monitoring tools, e.g. automatic food recognition systems 81 and urine-related measures of dietary intake 82 , could help to push the field forward.

Nutrients of particular interest in plant-based diets

As described above, plant-based diets have been shown to convey nutritional benefits 48 , 49 , in particular increased fiber, beta carotene, vitamin K and C, folate, magnesium, and potassium intake and an improved dietary health index 83 . However, a major criticism of plant-based diets is the risk of nutrient deficiencies for specific micronutrients, especially vitamin B12, a mainly animal-derived nutrient, which is missing entirely in vegan diets unless supplemented or provided in B12-fortified products, and which seems detrimental for neurological and cognitive health when intake is low. In the EPIC-Oxford study about 50% of the vegan dieters showed serum levels indicating vitamin B12 deficiency 84 . Along other risk factors such as age 85 , diet, and plant-based diets in particular, seem to be the main risk factor for vitamin B12 deficiency (reviewed in ref. 86 ), and therefore supplementing vitamin B12 for these risk groups is highly recommended 87 . Vitamin B12 is a crucial component involved in early brain development, in maintaining normal central nervous system function 88 and suggested to be neuroprotective, particularly for memory performance and hippocampal microstructure 89 . One hypothesis is that high levels of homocysteine, that is associated with vitamin B12 deficiency, might be harmful to the body. Vitamin B12 is the essential cofactor required for the conversion of homocysteine into nonharmful components and serves as a cofactor in different enzymatic reactions. A person suffering from vitamin B12 insufficiency accumulates homocysteine, lastly promoting the formation of plaques in arteries and thereby increasing atherothrombotic risk 90 , possibly facilitating symptoms in patients of Alzheimer’s disease 91 . A meta-analysis found that vitamin B12 deficiency was associated with stroke, Alzheimer’s disease, vascular dementia, Parkinson’s disease and in even lower concentrations with cognitive impairment 92 , supporting the claim of its high potential for disease prevention when avoided or treated 93 . Further investigations and longitudinal studies are needed, possibly measuring holotranscobalamin (the active form of vitamin B12) as a more specific and sensitive marker for vitamin B12 status 94 , to examine in how far nonsupplementing vegan dieters could be at risk for cardiovascular and cognitive impairment.

Similar health dangers can stem from iron deficiency, another commonly assumed risk for plant-based dieters and other risk groups such as young women. A meta-analysis on 24 studies proposes that although serum ferritin levels were lower in vegetarians on average, it is recommended to sustain an optimal ferritin level (neither too low nor too high), calling for well-monitored supplementation strategies 95 . Iron deficiency is not only dependent on iron intake as such but also on complimentary dietary factors influencing its bioavailability (discussed in ref. 95 ). The picture remains complex: on the one hand iron deficiency may lead to detrimental health effects, such as impairments in early brain development and cognitive functions in adults and in children carried by iron-deficient mothers 96 and a possible role for iron overload in the brain on cognitive impairment on the other hand 97 . One study showed that attention, memory and learning were impaired in iron-deficient compared to iron-sufficient women, which could be restored after a 4-month oral iron supplementation ( n  = 118) 98 . Iron deficiency-related impairments could be attributed to anemia as an underlying cause, possibly leading to fatigue, or an undersupply of blood to the brain or alterations in neurobiological and neuronal systems 99 provoking impaired cognitive functioning.

This leads to the general recommendation to monitor health status by frequent blood tests, to consult a dietician to live healthily on a plant-based diet and to consider supplements to avoid nutrient deficiencies or nutrient-overdose-related toxicity. All in all, organizations such as the Academy of Nutrition and Dietetics 100 and the German Nutrition Society do not judge iron as a major risk factor for plant-based dieters 101 .

Section II: Effects of diet on the gut microbiome

The link between diet and microbial diversity.

Another putative mechanistic pathway of how plant-based diets can affect health may involve the gut microbiome which has increasingly received scientific and popular interest, lastly not only through initiatives such as the Human Microbiome Project 102 . A common measure for characterizing the gut community is enterotyping, which is a way to stratify individuals according to their gut bacterial diversity, by calculating the ratio between bacterial genera, such as Prevotella and Bacteroides 103 . While interventional controlled trials are still scarce, this ratio has been shown to be conclusive for differentiating plant-based from animal-based microbial profiles 36 . Specifically, in a sample of 98 individuals, Wu et al. 36 found that a diet high in protein and animal fats was related to more Bacteroides, whereas a diet high in carbohydrates, representing a plant-based one, was associated with more Prevotella. Moreover, the authors showed that a change in diet to high-fat/low-fiber or to low-fat/high-fiber in ten individuals elicited a change in gut microbial enterotype with a time delay of 24 h only and remained stable over 10 days, however not being able to switch completely to another enterotype 36 . Another strictly controlled 30-day cross-over interventional study showed that a change in diet to either an exclusively animal-based or plant-based diet promoted gut microbiota diversity and genetic expression to change within 5 days 35 . Particularly, in response to adopting an animal-based diet, microbial diversity increased rapidly, even overshadowing individual microbial gene expression. Beyond large shifts in overall diet, already modest dietary modifications such as the daily consumption of 43 g of walnuts, were able to promote probiotic- and butyric acid-producing bacterial species in two RCTs, after 3 and 8 weeks respectively 104 , 105 , highlighting the high adaptability of the gut microbiome to dietary components. The Prevotella to Bacteroides ratio (P/B) has been shown to be involved in the success of dietary interventions targeting weight loss, with larger weight loss in high P/B compared to low P/B in a 6-month whole-grain diet compared to a conventional diet 106 . Only recently, other microbial communities, such as the salivary microbiome, have been shown to be different between omnivores and vegan dieters 107 , opening new avenues for research on adaptable mechanisms related to dietary intake.

A continuum in microbial diversity dependent on diet

Plant-based diets are supposed to be linked to a specific microbial profile, with a vegan profile being most different from an omnivore, but not always different from a vegetarian profile (reviewed in ref. 15 ). Some specifically vegan gut microbial characteristics have also been found in a small sample of six obese subjects after 1 month following a vegetarian diet, namely less pathobionts, more protective bacterial species improving lipid metabolism and a reduced level of intestinal inflammation 108 . Investigating long-term dietary patterns a study found a dose-dependent effect for altered gut microbiota in vegetarians and vegans compared to omnivores depending on the quantity of animal products 109 . The authors showed that gut microbial profiles of plant-based diets feature the same total number but lower counts of Bacteroides, Bifidobacterium, E. coli and Enterobacteriaceae compared to omnivores, with the biggest difference to vegans. Still today it remains unclear, what this shift in bacterial composition means in functional terms, prompting the field to develop more functional analyses.

In a 30-day intervention study, David et al. found that fermentation processes linked to fat and carbohydrate decomposition were related to the abundance of certain microbial species 35 . They found a strong correlation between fiber intake and Prevotella abundance in the microbial gut. More recently, Prevotella has been associated with plant-based diets 110 that are comparable to low-fat/high-fiber diets 111 and might be linked to the increased synthesis of short-chain fatty acids (SCFA) 112 . SCFAs are discussed as putative signaling molecules between the gut microbiome and the receptors, i.e. free fatty acid receptor 2 (FFA2) 51 , found in host cells across different tissues 113 and could therefore be one potential mechanism of microbiome−host communication.

The underlying mechanisms of nutrient decomposition by Prevotella and whether abundant Prevotella populations in the gut are beneficial for overall health remain unknown. Yet it seems possible that an increased fiber intake and therefore higher Prevotella abundance such as associated with plant-based diets is beneficial for regulating glycemic control and keeping inflammatory processes within normal levels, possibly due to reduced appetite and lower energy intake mediated by a higher fiber content 114 . Moreover, it has been brought forward that the microbiome might influence bodily homeostatic control, suggesting a role for the gut microbiota in whole-body control mechanisms on the systemic level. Novel strategies aim to develop gut-microbiota-based therapies to improve bodily states, e.g. glycemic control 115 , based on inducing microbial changes and thereby eliciting higher-level changes in homeostasis. While highly speculative, such strategies could in theory also exert changes on the brain level, which will be discussed next in the light of a bi-directional feedback between the gut and the brain.

Effects on cognition and behavior linking diet and cognition via the microbiome−gut−brain axis

While the number of interventional studies focusing on cognitive and mental health outcomes after adopting plant-based diets overall is very limited (see Section I above), one underlying mechanism of how plant-based diets may affect mood could involve signaling pathways on the microbiome−gut−brain axis 116 , 117 , 118 , 119 . A recent 4-week intervention RCT showed that probiotic administration compared to placebo and no intervention modulated brain activity during emotional decision-making and emotional recognition tasks 117 . In chronic depression it has been proposed that immunoglobulin A and M antibodies are synthesized by the host in response to gut commensals and are linked to depressive symptoms 120 . Whether the identified gram-negative bacteria might also play a role in plant-based diets remains to be explored. A meta-analysis on five studies concluded that probiotics may mediate an alleviating effect on depression symptomatic 121 —however, sample sizes remained rather small ( n  < 100) and no long-term effects were tested (up to 8 weeks).

Currently, several studies aim to identify microbial profiles in relation to disease and how microbial data can be used on a multimodal way to improve functional resolution, e.g. characterizing microbial profiles of individuals suffering from type-1 diabetes 122 . Yet, evidence for specific effects of diet on cognitive functions and behavior through changes in the microbiome remains scarce. A recent study indicated the possibility that our food choices determine the quantity and quality of neurotransmitter-precursor levels that we ingest, which in turn might influence behavior, as shown by lower fairness during a money-redistribution task, called the ultimatum game, after a high-carbohydrate/protein ratio breakfast than after a low-ratio breakfast 123 . Strang et al. found that precursor forms of serotonin and dopamine, measured in blood serum, predicted behavior in this task, and precursor concentrations were dependent on the nutrient profile of the consumed meal before the task. Also on a cross-sectional level tryptophan metabolites from fecal samples have been associated with amygdala-reward network functional connectivity 124 . On top of the dietary composition per se, the microbiota largely contributes to neurotransmitter precursor concentrations; thus, in addition to measuring neurotransmitter precursors in the serum, metabolomics on fecal samples would be helpful to further understand the functional role of the gut microbiota in neurotransmitter biosynthesis and regulation 125 .

Indicating the relevance of gut microbiota for cognition, a first human study assessing cognitive tests and brain imaging could distinguish obese from nonobese individuals using a microbial profile 126 . The authors found a specific microbiotic profile, particularly defined by Actinobacteria phylum abundance, that was associated with microstructural properties in the hypothalamus and in the caudate nucleus. Further, a preclinical study tested whether probiotics could enhance cognitive function in healthy subjects, showing small effects on improved memory performance and reduced stress levels 127 .

A recent study could show that microbial composition influences cerebral amyloidogenesis in a mouse model for Alzheimer’s disease 128 . Health status of the donor mouse seemingly mattered: fecal transplants from transgenic mice had a larger impact on amyloid beta proliferation in the brain compared to wild-type feces. Translational interpretations to humans should be done with caution if at all—yet the results remain elucidative for showing a link between the gut microbiome and brain metabolism.

The evidence for effects of strictly plant-based diets on cognition is very limited. For other plant-based diets such as the Mediterranean diet or DASH diet, there are more available studies that indicate protective effects on cardiovascular and brain health in the aging population (reviewed in refs. 129 , 130 ). Several attempts have been made to clarify potential underlying mechanisms, for example using supplementary plant polyphenols, fish/fish-oil consumption or whole dietary pattern change in RCTs 131 , 132 , 133 , 134 , 135 , 136 , 137 , yet results are not always equivocal and large-scale intervention studies have yet to be completed.

The overall findings of this paragraph add to the evidence that microbial diversity may be associated with brain health, although underlying mechanisms and candidate signaling molecules remain unknown.

Based on this systematic review of randomized clinical trials, there is an overall robust support for beneficial effects of a plant-based diet on metabolic measures in health and disease. However, the evidence for cognitive and mental effects of a plant-based diet is still inconclusive. Also, it is not clear whether putative effects are due to the diet per se, certain nutrients of the diet (or the avoidance of certain animal-based nutrients) or other factors associated with vegetarian/vegan diets. Evolving concepts argue that emotional distress and mental illnesses are linked to the role of microbiota in neurological function and can be potentially treated via microbial intervention strategies 19 . Moreover, it has been claimed that certain diseases, such as obesity, are caused by a specific microbial composition 138 , and that a balanced gut microbiome is related to healthy ageing 111 . In this light, it seems possible that a plant-based diet is able to influence brain function by still unclear underlying mechanisms of an altered microbial status and systemic metabolic alterations. However, to our knowledge there are no studies linking plant-based diets and cognitive abilities on a neural level, which are urgently needed, due to the hidden potential as a dietary therapeutic tool. Also, further studies are needed to disentangle motivational beliefs on a psychological level that lead to a change in diet from causal effects on the body and the brain mediated e.g., by metabolic alterations or a change in the gut microbiome.

GOV.UK. National Diet and Nutrition Survey: headline results from years 1, 2 and 3 (combined) of the rolling programme 2008/09–2010/11. https://www.gov.uk/government/statistics/national-diet-and-nutrition-survey-headline-results-from-years-1-2-and-3-combined-of-the-rolling-programme-200809-201011 (2012).

V. E. B. U. Deutschland & Joy, S. Anzahl der Veganer und Vegetarier in Deutschland. Stand 31 , 2016 (2015).

Mensink, G., Barbosa, C. L. & Brettschneider, A.-K. Verbreitung der vegetarischen Ernährungsweise in Deutschland 1 , (2016).

The Vegetarian Resource Group. How many adults in the U.S. are vegetarian and vegan? http://www.vrg.org/nutshell/Polls/2016_adults_veg.htm (2016).

Rosenfeld, D. L. & Burrow, A. L. Vegetarian on purpose: understanding the motivations of plant-based dieters. Appetite 116 , 456–463 (2017).

Article   PubMed   Google Scholar  

Orlich, M. J. et al. Vegetarian dietary patterns and mortality in Adventist Health Study 2. JAMA Intern. Med. 173 , 1230–1238 (2013).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Le, L. T. & Sabaté, J. Beyond meatless, the health effects of vegan diets: findings from the Adventist cohorts. Nutrients 6 , 2131–2147 (2014).

Article   PubMed   PubMed Central   Google Scholar  

Mihrshahi, S. et al. Vegetarian diet and all-cause mortality: evidence from a large population-based Australian cohort-the 45 and up study. Prev. Med. 97 , 1–7 (2017).

Key, T. J. et al. Mortality in British vegetarians: results from the European Prospective Investigation into Cancer and Nutrition (EPIC-Oxford). Am. J. Clin. Nutr. 89 , 1613S–1619S (2009).

Article   CAS   PubMed   Google Scholar  

Fung, T. T. et al. Low-carbohydrate diets and all-cause and cause-specific mortalitytwo cohort studies. Ann. Intern. Med. 153 , 289–298 (2010).

Song, M. et al. Association of animal and plant protein intake with all-cause and cause-specific mortality. JAMA Intern. Med. 176 , 1453–1463 (2016).

Hu, F. B. Plant-based foods and prevention of cardiovascular disease: an overview. Am. J. Clin. Nutr. 78 , 544S–551S (2003).

Tonstad, S., Butler, T., Yan, R. & Fraser, G. E. Type of vegetarian diet, body weight, and prevalence of type 2 diabetes. Diabetes Care 32 , 791–796 (2009).

McEvoy, C. T., Temple, N. & Woodside, J. V. Vegetarian diets, low-meat diets and health: a review. Public Health Nutr. 15 , 2287–2294 (2012).

Glick-Bauer, M. & Yeh, M.-C. The health advantage of a vegan diet: exploring the gut microbiota connection. Nutrients 6 , 4822–4838 (2014).

Appleby, P. N. & Key, T. J. The long-term health of vegetarians and vegans. Proc. Nutr. Soc. 75 , 287–293 (2016).

Eichelmann, F., Schwingshackl, L., Fedirko, V. & Aleksandrova, K. Effect of plant‐based diets on obesity‐related inflammatory profiles: a systematic review and meta‐analysis of intervention trials. Obes. Rev. 17 , 1067–1079 (2016).

McMacken, M. & Shah, S. A plant-based diet for the prevention and treatment of type 2 diabetes. J. Geriatr. Cardiol. 14 , 342 (2017).

CAS   PubMed   PubMed Central   Google Scholar  

Rogers, G. B. et al. From gut dysbiosis to altered brain function and mental illness: mechanisms and pathways. Mol. Psychiatry 21 , 738–748 (2016).

Hibbeln, J. R., Northstone, K., Evans, J. & Golding, J. Vegetarian diets and depressive symptoms among men. J. Affect Disord. 225 , 13–17 (2018).

Forestell, C. A. & Nezlek, J. B. Vegetarianism, depression, and the five factor model of personality. Ecol. Food Nutr. 57 , 246–259 (2018).

Matta, J. et al. Depressive symptoms and vegetarian diets: results from the constances cohort. Nutrients 10 , 1695 (2018).

Article   PubMed Central   Google Scholar  

Agarwal, U. et al. A multicenter randomized controlled trial of a nutrition intervention program in a multiethnic adult population in the corporate setting reduces depression and anxiety and improves quality of life: the GEICO study. Am. J. Health Promot. 29 , 245–254 (2015).

Beezhold, B., Radnitz, C., Rinne, A. & DiMatteo, J. Vegans report less stress and anxiety than omnivores. Nutr. Neurosci. 18 , 289–296 (2015).

Barnard, N. D., Levin, S. M. & Yokoyama, Y. A systematic review and meta-analysis of changes in body weight in clinical trials of vegetarian diets. J. Acad. Nutr. Diet. 115 , 954–969 (2015).

Huang, R.-Y., Huang, C.-C., Hu, F. B. & Chavarro, J. E. Vegetarian diets and weight reduction: a meta-analysis of randomized controlled trials. J. Gen. Intern. Med. 31 , 109–116 (2016).

Benatar, J. R. & Stewart, R. A. H. Cardiometabolic risk factors in vegans: a meta-analysis of observational studies. PLoS ONE 13 , e0209086 (2018).

Lee, Y.-M. et al. Effect of a brown rice based vegan diet and conventional diabetic diet on glycemic control of patients with type 2 diabetes: a 12-week randomized clinical trial. PLoS ONE 11 , e0155918 (2016).

Article   PubMed   PubMed Central   CAS   Google Scholar  

Jenkins, D. J. A. et al. Effect of a 6-month vegan low-carbohydrate (‘Eco-Atkins’) diet on cardiovascular risk factors and body weight in hyperlipidaemic adults: a randomised controlled trial. BMJ Open 4 , e003505 (2014).

Jenkins, D. J. A. et al. The effect of a plant-based low-carbohydrate (“Eco-Atkins”) diet on body weight and blood lipid concentrations in hyperlipidemic subjects. Arch. Intern. Med. 169 , 1046–1054 (2009).

Barnard, N. D. et al. A low-fat vegan diet and a conventional diabetes diet in the treatment of type 2 diabetes: a randomized, controlled, 74-wk clinical trial. Am. J. Clin. Nutr. https://doi.org/10.3945/ajcn.2009.26736H (2009).

Kahleova, H., Hill M. & Pelikánova, T. Vegetarian vs. conventional diabetic diet—a 1-year follow-up. Cor Vasa 56 . https://doi.org/10.1016/j.crvasa.2013.12.004 (2016).

Article   Google Scholar  

Turner-McGrievy, G. M., Davidson, C. R., Wingard, E. E., Wilcox, S. & Frongillo, E. A. Comparative effectiveness of plant-based diets for weight loss: a randomized controlled trial of five different diets. Nutrition 31 , 350–358 (2015).

Wing, R. R. & Phelan, S. Long-term weight loss maintenance. Am. J. Clin. Nutr. 82 , 222S–225S (2005).

David, L. A. et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505 , 559–563 (2014).

Wu, G. D. et al. Linking long-term dietary patterns with gut microbial enterotypes. Science (80-) 334 , 105–108 (2011).

Article   CAS   Google Scholar  

Kaartinen, K. et al. Vegan diet alleviates fibromyalgia symptoms. Scand. J. Rheumatol. 29 , 308–313 (2000).

Yadav, V. et al. Low-fat, plant-based diet in multiple sclerosis: a randomized controlled trial. Mult. Scler. Relat. Disord. 9 , 80–90 (2016).

Rauma, A. L., Nenonen, M., Helve, T. & Hänninen, O. Effect of a strict vegan diet on energy and nutrient intakes by Finnish rheumatoid patients. Eur. J. Clin. Nutr. 47 , 747–749 (1993).

CAS   PubMed   Google Scholar  

Elkan, A.-C. et al. Gluten-free vegan diet induces decreased LDL and oxidized LDL levels and raised atheroprotective natural antibodies against phosphorylcholine in patients with rheumatoid arthritis: a randomized study. Arthritis Res. Ther. 10 , R34 (2008).

Karlsson, J. et al. Predictors and effects of long-term dieting on mental well-being and weight loss in obese women. Appetite 23 , 15–26 (1994).

Beezhold, B. L. & Johnston, C. S. Restriction of meat, fish, and poultry in omnivores improves mood: a pilot randomized controlled trial. Nutr. J. 11 , 9 (2012).

Yokoyama, Y., Barnard, N. D., Levin, S. M. & Watanabe, M. Vegetarian diets and glycemic control in diabetes: a systematic review and meta-analysis. Cardiovasc. Diagn. Ther. 4 , 373–382 (2014).

PubMed   PubMed Central   Google Scholar  

Sutliffe, J. T., Wilson, L. D., de Heer, H. D., Foster, R. L. & Carnot, M. J. C-reactive protein response to a vegan lifestyle intervention. Complement Ther. Med. 23 , 32–37 (2015).

Strasser, B., Gostner, J. M. & Fuchs, D. Mood, food, and cognition: role of tryptophan and serotonin. Curr. Opin. Clin. Nutr. Metab. Care 19 , 55–61 (2016).

O’Mahony, S. M., Clarke, G., Borre, Y. E., Dinan, T. G. & Cryan, J. F. Serotonin, tryptophan metabolism and the brain-gut-microbiome axis. Behav. Brain Res. 277 , 32–48 (2015).

Article   PubMed   CAS   Google Scholar  

Davey, G. K. et al. EPIC–Oxford: lifestyle characteristics and nutrient intakes in a cohort of 33 883 meat-eaters and 31 546 non meat-eaters in the UK. Public Health Nutr. 6 , 259–268 (2003).

Schüpbach, R., Wegmüller, R., Berguerand, C., Bui, M. & Herter-Aeberli, I. Micronutrient status and intake in omnivores, vegetarians and vegans in Switzerland. Eur. J. Nutr. 56 , 283–293 (2017).

Clarys, P. et al. Comparison of nutritional quality of the vegan, vegetarian, semi-vegetarian, pesco-vegetarian and omnivorous diet. Nutrients 6 , 1318–1332 (2014).

Park, J. E., Miller, M., Rhyne, J., Wang, Z. & Hazen, S. L. Differential effect of short-term popular diets on TMAO and other cardio-metabolic risk markers. Nutr. Metab. Cardiovasc. Dis. 29 , 513–517 (2019).

Psichas, A. et al. The short chain fatty acid propionate stimulates GLP-1 and PYY secretion via free fatty acid receptor 2 in rodents. Int J. Obes. 39 , 424 (2015).

Lin, H. V. et al. Butyrate and propionate protect against diet-induced obesity and regulate gut hormones via free fatty acid receptor 3-independent mechanisms. PLoS ONE 7 , e35240 (2012).

Canfora, E. E., Jocken, J. W. & Blaak, E. E. Short-chain fatty acids in control of body weight and insulin sensitivity. Nat. Rev. Endocrinol. 11 , 577 (2015).

Guo, Y. et al. Physiological evidence for the involvement of peptide YY in the regulation of energy homeostasis in humans. Obesity 14 , 1562–1570 (2006).

Holzer, P., Reichmann, F. & Farzi, A. Neuropeptide Y, peptide YY and pancreatic polypeptide in the gut–brain axis. Neuropeptides 46 , 261–274 (2012).

Kendall, C. W. C., Esfahani, A. & Jenkins, D. J. A. The link between dietary fibre and human health. Food Hydrocoll. 24 , 42–48 (2010).

Reynolds, A. et al. Carbohydrate quality and human health: a series of systematic reviews and meta-analyses. Lancet . https://doi.org/10.1016/S0140-6736(18)31809-9 (2019).

Menni, C. et al. Gut microbiome diversity and high-fibre intake are related to lower long-term weight gain. Int. J. Obes. 41 , 1099 (2017).

Van Gaal, L. F., Mertens, I. L. & Christophe, E. Mechanisms linking obesity with cardiovascular disease. Nature 444 , 875 (2006).

Ferreira, C. M. et al. The central role of the gut microbiota in chronic inflammatory diseases. J. Immunol. Res. 2014 , https://doi.org/10.1155/2014/689492 (2014).

Wersching, H. et al. Serum C-reactive protein is linked to cerebral microstructural integrity and cognitive function. Neurology 74 , 1022–1029 (2010).

Gu, Y. et al. Circulating inflammatory biomarkers in relation to brain structural measurements in a non-demented elderly population. Brain Behav. Immun. 65 , 150–160 (2017).

Lampe, L. et al. Visceral obesity relates to deep white matter hyperintensities via inflammation. Ann. Neurol. 85 , 194–203 (2018).

Google Scholar  

Schmidt, R. et al. Early inflammation and dementia: a 25‐year follow‐up of the Honolulu‐Asia Aging Study. Ann. Neurol. 52 , 168–174 (2002).

Rosano, C., Marsland, A. L. & Gianaros, P. J. Maintaining brain health by monitoring inflammatory processes: a mechanism to promote successful aging. Aging Dis. 3 , 16 (2012).

PubMed   Google Scholar  

Tangney, C. C. et al. Relation of DASH-and Mediterranean-like dietary patterns to cognitive decline in older persons. Neurology 83 , 1410–1416 (2014).

Craddock, J. C., Probst, Y. & Peoples, G. Vegetarian nutrition—comparing physical performance of omnivorous and vegetarian athletes. J. Nutr. Intermed. Metab. 4 , 19 (2016).

Liu, R. H. Health benefits of fruit and vegetables are from additive and synergistic combinations of phytochemicals. Am. J. Clin. Nutr. 78 , 517S–520S (2003).

Boffetta, P. et al. Fruit and vegetable intake and overall cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC). J. Natl. Cancer Inst. 102 , 529–537 (2010).

Reczek, C. R. & Chandel, N. S. Revisiting vitamin C and cancer. Science (80-) 350 , 1317–1318 (2015).

Probst, Y. C., Guan, V. X. & Kent, K. Dietary phytochemical intake from foods and health outcomes: a systematic review protocol and preliminary scoping. BMJ Open 7 , e013337 (2017).

Hartmann, R. & Meisel, H. Food-derived peptides with biological activity: from research to food applications. Curr. Opin. Biotechnol. 18 , 163–169 (2007).

Tillisch, K. et al. Consumption of fermented milk product with probiotic modulates brain activity. Gastroenterology 144 , 1394–1401 (2013).

Gibson, G. R. et al. Expert consensus document: The International Scientific Association for Probiotics and Prebiotics (ISAPP) consensus statement on thedefinition and scope of prebiotics. Nat. Rev. Gastroenterol. Hepatol. 14 , 491 (2017).

Nisha, A. R. Antibiotic residues-a global health hazard. Vet. World 1 , 375–377 (2008).

Wang, H. et al. Antibiotic residues in meat, milk and aquatic products in Shanghai and human exposure assessment. Food Control 80 , 217–225 (2017).

Bertazzi, P. A. et al. Health effects of dioxin exposure: a 20-year mortality study. Am. J. Epidemiol. 153 , 1031–1044 (2001).

Bouvard, V. et al. Carcinogenicity of consumption of red and processed meat. Lancet Oncol. 16 , 1599–1600 (2015).

Van Audenhaege, M. et al. Impact of food consumption habits on the pesticide dietary intake: comparison between a French vegetarian and the general population. Food Addit. Contam . 26 , 1372–1388 (2009).

Jacobs, D. R. & Tapsell, L. C. Food synergy: the key to a healthy diet. Proc. Nutr. Soc. 72 , 200–206 (2013).

Kawano, Y. & Yanai, K. Foodcam: a real-time food recognition system on a smartphone. Multimed. Tools Appl. 74 , 5263–5287 (2015).

Garcia-Perez, I. et al. Objective assessment of dietary patterns by use of metabolic phenotyping: a randomised, controlled, crossover trial. Lancet Diabetes Endocrinol. 5 , 184–195 (2017).

Turner-McGrievy, G. M. et al. Changes in nutrient intake and dietary quality among participants with type 2 diabetes following a low-fat vegan diet or a conventional diabetes diet for 22 weeks. J. Am. Diet. Assoc. 108 , 1636–1645 (2008).

Gilsing, A. M. J. et al. Serum concentrations of vitamin B12 and folate in British male omnivores, vegetarians and vegans: results from a cross-sectional analysis of the EPIC-Oxford cohort study. Eur. J. Clin. Nutr. 64 , 933–939 (2010).

Allen, L. H. How common is vitamin B-12 deficiency? Am. J. Clin. Nutr. 89 , 693S–696S (2008).

Pawlak, R., Parrott, S. J., Raj, S., Cullum-Dugan, D. & Lucus, D. How prevalent is vitamin B12 deficiency among vegetarians? Nutr. Rev. 71 , 110–117 (2013).

Rizzo, G. et al. Vitamin B12 among vegetarians: status, assessment and supplementation. Nutrients 8 , 767 (2016).

Article   PubMed Central   CAS   Google Scholar  

Stabler, S. P. Vitamin B12 deficiency. N. Engl. J. Med . 368 , 149–160 (2013).

Köbe, T. et al. Vitamin B-12 concentration, memory performance, and hippocampal structure in patients with mild cognitive impairment, 2. Am. J. Clin. Nutr. 103 , 1045–1054 (2016).

Ganguly, P. & Alam, S. F. Role of homocysteine in the development of cardiovascular disease. Nutr. J. 14 , 6 (2015).

McCaddon, A., Regland, B., Hudson, P. & Davies, G. Functional vitamin B12 deficiency and Alzheimer disease. Neurology 58 , 1395–1399 (2002).

Moore, E. et al. Cognitive impairment and vitamin B12: a review. Int. Psychogeriatr. 24 , 541–556 (2012).

Spence, J. D. Metabolic vitamin B12 deficiency: a missed opportunity to prevent dementia and stroke. Nutr. Res. 36 , 109–116 (2016).

Nexo, E. & Hoffmann-Lücke, E. Holotranscobalamin, a marker of vitamin B-12 status: analytical aspects and clinical utility. Am. J. Clin. Nutr. 94 , 359S–365S (2011).

Haider, L. M., Schwingshackl, L., Hoffmann, G. & Ekmekcioglu, C. The effect of vegetarian diets on iron status in adults: a systematic review and meta-analysis. Crit. Rev. Food Sci. Nutr. 58 , 1359–1374 (2018).

Lozoff, B. & Georgieff, M. K. et al. Iron deficiency and brain development. Semin. Pediatr. Neurol. 13 , 158–165 (2006).

Ayton, S. et al. Brain iron is associated with accelerated cognitive decline in people with Alzheimer pathology. Mol. Psychiatry 1 , https://doi.org/10.1038/s41380-019-0375-7 (2019).

Murray-Kolb, L. E. & Beard, J. L. Iron treatment normalizes cognitive functioning in young women. Am. J. Clin. Nutr. 85 , 778–787 (2007).

Beard, J. Iron deficiency alters brain development and functioning. J. Nutr. 133 , 1468S–1472S (2003).

Melina, V., Craig, W. & Levin, S. Position of the Academy of Nutrition and Dietetics: vegetarian diets. J. Acad. Nutr. Diet. 116 , 1970–1980 (2016).

Richter, M. et al. For the German Nutrition Society (DGE)(2016) Vegan diet. Position of the German Nutrition Society (DGE). Ernaehrungsumschau 63 , 92–102 (2016).

Peterson, J. et al. The NIH human microbiome project. Genome Res. 19 , 2317–2323 (2009).

Arumugam, M. et al. Enterotypes of the human gut microbiome. Nature 473 , 174–180 (2013).

Bamberger, C. et al. A walnut-enriched diet affects gut microbiome in healthy Caucasian subjects: a randomized, controlled trial. Nutrients 10 , 244 (2018).

Holscher, H. D. et al. Walnut consumption alters the gastrointestinal microbiota, microbially derived secondary bile acids, and health markers in healthy adults: a randomized controlled trial. J. Nutr. 148 , 861–867 (2018).

Hjorth, M. F. et al. Pre-treatment microbial Prevotella-to-Bacteroides ratio, determines body fat loss success during a 6-month randomized controlled diet intervention. Int J. Obes. 42 , 580 (2018).

Hansen, T. H. et al. Impact of a vegan diet on the human salivary microbiota. Sci. Rep. 8 , 5847 (2018).

Kim, M., Hwang, S., Park, E. & Bae, J. Strict vegetarian diet improves the risk factors associated with metabolic diseases by modulating gut microbiota and reducing intestinal inflammation. Environ. Microbiol. Rep. 5 , 765–775 (2013).

Zimmer, J. et al. A vegan or vegetarian diet substantially alters the human colonic faecal microbiota. Eur. J. Clin. Nutr. 66 , 53–60 (2012).

De Filippis, F., Pellegrini, N., Laghi, L., Gobbetti, M. & Ercolini, D. Unusual sub-genus associations of faecal Prevotella and Bacteroides with specific dietary patterns. Microbiome 4 , 57 (2016).

Kumar, M., Babaei, P., Ji, B. & Nielsen, J. Human gut microbiota and healthy aging: Recent developments and future prospective. Nutr. Health Aging 4 , 3–16 (2016).

Wu, G. D. et al. Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production. Gut 65 , 63–72 (2014).

Morrison, D. J. & Preston, T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes 7 , 189–200 (2016).

Wanders, A. J. et al. Effects of dietary fibre on subjective appetite, energy intake and body weight: a systematic review of randomized controlled trials. Obes. Rev. 12 , 724–739 (2011).

Brunkwall, L. & Orho-Melander, M. The gut microbiome as a target for prevention and treatment of hyperglycaemia in type 2 diabetes: from current human evidence to future possibilities. Diabetologia 60 , 943–951 (2017).

Lach, G., Schellekens, H., Dinan, T. G. & Cryan, J. F. Anxiety, depression, and the microbiome: a role for gut peptides. Neurotherapeutics 15 , 36–59 (2018).

Bagga, D. et al. Influence of 4-week multi-strain probiotic administration on resting-state functional connectivity in healthy volunteers. Eur. J. Nutr. 58 , 1821–1827 (2018).

Foster, J. A. & Neufeld, K.-A. M. Gut–brain axis: how the microbiome influences anxiety and depression. Trends Neurosci. 36 , 305–312 (2013).

Saulnier, D. M. et al. The intestinal microbiome, probiotics and prebiotics in neurogastroenterology. Gut Microbes 4 , 17–27 (2013).

Maes, M., Kubera, M., Leunis, J.-C. & Berk, M. Increased IgA and IgM responses against gut commensals in chronic depression: further evidence for increased bacterial translocation or leaky gut. J. Affect Disord. 141 , 55–62 (2012).

Huang, R., Wang, K. & Hu, J. Effect of probiotics on depression: a systematic review and meta-analysis of randomized controlled trials. Nutrients 8 , 483 (2016).

Heintz-Buschart, A. et al. Integrated multi-omics of the human gut microbiome in a case study of familial type 1 diabetes. Nat. Microbiol. 2 , 16180 (2016).

Strang, S. et al. Impact of nutrition on social decision making. Proc. Natl Acad. Sci. 114 , 6510–6514 (2017).

Osadchiy, V. et al. Correlation of tryptophan metabolites with connectivity of extended central reward network in healthy subjects. PLoS ONE 13 , e0201772 (2018).

Franzosa, E. A. et al. Sequencing and beyond: integrating molecular’omics’ for microbial community profiling. Nat. Rev. Microbiol. 13 , 360–372 (2015).

Fernandez-Real, J.-M. et al. Gut microbiota interacts with brain microstructure and function. J. Clin. Endocrinol. Metab. 100 , 4505–4513 (2015).

Allen, A. P. et al. Bifidobacterium longum 1714 as a translational psychobiotic: modulation of stress, electrophysiology and neurocognition in healthy volunteers. Transl. Psychiatry 6 , e939 (2016).

Harach, T. et al. Reduction of Abeta amyloid pathology in APPPS1 transgenic mice in the absence of gut microbiota. Sci. Rep. 7 , 41802 (2017).

Huhn, S., Masouleh, S. K., Stumvoll, M., Villringer, A. & Witte, A. V. Components of a Mediterranean diet and their impact on cognitive functions in aging. Front Aging Neurosci 7 , 132 (2015).

Larsson, S. C., Wallin, A. & Wolk, A. Dietary approaches to stop hypertension diet and incidence of stroke: results from 2 prospective cohorts. Stroke 47 , 986–990 (2016).

van de Rest, O. et al. Effect of fish oil on cognitive performance in older subjects: a randomized, controlled trial. Neurology 71 , 430–438 (2008).

Witte, A. V. et al. Long-chain omega-3 fatty acids improve brain function and structure in older adults. Cereb. Cortex 24 , 3059–3068 (2013).

Witte, A. V., Kerti, L., Margulies, D. S. & Flöel, A. Effects of resveratrol on memory performance, hippocampal functional connectivity, and glucose metabolism in healthy older adults. J. Neurosci. 34 , 7862–7870 (2014).

Brickman, A. M. et al. Enhancing dentate gyrus function with dietary flavanols improves cognition in older adults. Nat. Neurosci. 17 , 1798 (2014).

Martínez-González, M. A. et al. Benefits of the Mediterranean diet: insights from the PREDIMED study. Prog. Cardiovasc. Dis. 58 , 50–60 (2015).

Huhn, S. et al. Effects of resveratrol on memory performance, hippocampus connectivity and microstructure in older adults—a randomized controlled trial. Neuroimage (2018).

Rosenberg, A. et al. Multidomain lifestyle intervention benefits a large elderly population at risk for cognitive decline and dementia regardless of baseline characteristics: The FINGER trial. Alzheimer’s. Dement. 14 , 263–270 (2018).

Turnbaugh, P. J. Microbes and diet-induced obesity: fast, cheap, and out of control. Cell Host Microbe 21 , 278–281 (2017).

Turner-Mc Grievy, G. M., Barnard, N. D. & Scialli, A. R. A two-year randomized weight loss trial comparing a vegan diet to a more moderate low-fat diet*. Obesity 15 , 2276–2281 (2007).

Burke, L. E. et al. A randomized clinical trial of a standard versus vegetarian diet for weight loss: the impact of treatment preference. Int. J. Obes. 32 , 166–176 (2008).

Barnard, N. D. et al. A low-fat vegan diet and a conventional diabetes diet in the treatment of type 2 diabetes: a randomized, controlled, 74-wk clinical trial. Am. J. Clin. Nutr. 89 , 1588S–1596S (2009).

Marniemi, J., Seppänen, A. & Hakala, P. Long-term effects on lipid metabolism of weight reduction on lactovegetarian and mixed diet. Int. J. Obes. 14 , 113–125 (1990).

Acharya, S. D., Brooks, M. M., Evans, R. W., Linkov, F. & Burke, L. E. Weight loss is more important than the diet type in improving adiponectin levels among overweight/obese adults. J. Am. Coll. Nutr. 32 , 264–271 (2013).

Wright, N., Wilson, L., Smith, M., Duncan, B. & McHugh, P. The BROAD study: A randomised controlled trial using a whole food plant-based diet in the community for obesity, ischaemic heart disease or diabetes. Nutr. Diabetes 7 , e256 (2017).

Turner-McGrievy, G. M., Davidson, C. R., Wingard, E. E. & Billings, D. L. Low glycemic index vegan or low-calorie weight loss diets for women with polycystic ovary syndrome: a randomized controlled feasibility study. Nutr. Res. 34 , 552–558 (2014).

Kahleova, H. et al. Vegetarian diet improves insulin resistance and oxidative stress markers more than conventional diet in subjects with Type 2 diabetes. Diabet. Med 28 , 549–559 (2011).

Ferdowsian, H. R. et al. A multicomponent intervention reduces body weight and cardiovascular risk at a GEICO corporate site. Am. J. Heal. Promot 24 , 384–387 (2010).

Mishra, S. et al. A multicenter randomized controlled trial of a plant-based nutrition program to reduce body weight and cardiovascular risk in the corporate setting: the GEICO study. Eur. J. Clin. Nutr. 67 , 718 (2013).

Agarwal, U. et al. A multicenter randomized controlled trial of a nutrition intervention program in a multiethnic adult population in the corporate setting reduces depression and anxiety and improves quality of life: the GEICO study. Am. J. Heal. Promot 29 , 245–254 (2015).

Kahleova, H., Dort, S., Holubkov, R. & Barnard, N. A plant-based high-carbohydrate, low-fat diet in overweight individuals in a 16-week randomized clinical trial: the role of carbohydrates. Nutrients 10 , 1302 (2018).

Barnard, N., Scialli, A. R., Bertron, P., Hurlock, D. & Edmonds, K. Acceptability of a therapeutic low-fat, vegan diet in premenopausal women. J. Nutr. Educ. 32 , 314–319 (2000).

Gardner, C. D. et al. The effect of a plant-based diet on plasma lipids in hypercholesterolemic adults: a randomized trial. Ann. Intern. Med. 142 , 733 (2005).

Macknin, M. et al. Plant-based, no-added-fat or American Heart Association diets: impact on cardiovascular risk in obese children with hypercholesterolemia and their parents. J. Pediatr. 166 , 953–959 (2015).

Sciarrone, S. E. et al. Biochemical and neurohormonal responses to the introduction of a lacto-ovovegetarian diet. J. Hypertens. 11 , 849–860 (1993).

Alleman, R. J., Harvey, I. C., Farney, T. M. & Bloomer, R. J. Both a traditional and modified Daniel Fast improve the cardio-metabolic profile in men and women. Lipids Health Dis. 12 , 114 (2013).

Neacsu, M., Fyfe, C., Horgan, G. & Johnstone, A. M. Appetite control and biomarkers of satiety with vegetarian (soy) and meat-based high-protein diets for weight loss in obese men: a randomized crossover trial–. Am. J. Clin. Nutr. 100 , 548–558 (2014).

Koebnick, C. et al. Double-blind, randomized feedback control fails to improve the hypocholesterolemic effect of a plant-based low-fat diet in patients with moderately elevated total cholesterol levels. Eur. J. Clin. Nutr. 58 , 1402 (2004).

Kjeldsen-Kragh, J., Haugen, M., Førre, Ø., Laache, H. & Malt, U. F. Vegetarian diet for patients with rheumatoid arthritis: can the clinical effects be explained by the psychological characteristics of the patients? Rheumatology 33 , 569–575 (1994).

Bunner, A. E., Agarwal, U., Gonzales, J. F., Valente, F. & Barnard, N. D. Nutrition intervention for migraine: a randomized crossover trial. J. Headache Pain. 15 , 69 (2014).

Kahleova, H., Hrachovinova, T., Hill, M. & Pelikanova, T. Vegetarian diet in type 2 diabetes–improvement in quality of life, mood and eating behaviour. Diabet. Med 30 , 127–129 (2013).

Turner-McGrievy, G. M. et al. Randomization to plant-based dietary approaches leads to larger short-term improvements in Dietary Inflammatory Index scores and macronutrient intake compared with diets that contain meat. Nutr. Res. 35 , 97–106 (2015).

Download references

Acknowledgements

This work was supported by a scholarship (E.M.) by the German Federal Environmental Foundation and by the grants of the German Research Foundation contract grant number CRC 1052 “Obesity mechanisms” Project A1 (AV) and WI 3342/3-1 (A.V.W.).

Author information

Authors and affiliations.

Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

Evelyn Medawar, Arno Villringer & A. Veronica Witte

Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany

Evelyn Medawar & Arno Villringer

Charité—Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, Berlin, Germany

Helmholtz Centre for Environmental Research GmbH—UFZ, Leipzig, Germany

Sebastian Huhn

You can also search for this author in PubMed   Google Scholar

Contributions

E.M., A.V. and A.V.W. designed research; E.M. conducted research; E.M., S.H. and A.V.W. analyzed data; E.M. and A.V.W. wrote the paper; E.M., A.V. and A.V.W. had primary responsibility for final content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Evelyn Medawar .

Ethics declarations

Conflict of interest.

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Suppl. table 1, suppl. figure 1, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Medawar, E., Huhn, S., Villringer, A. et al. The effects of plant-based diets on the body and the brain: a systematic review. Transl Psychiatry 9 , 226 (2019). https://doi.org/10.1038/s41398-019-0552-0

Download citation

Received : 20 February 2019

Revised : 22 June 2019

Accepted : 17 July 2019

Published : 12 September 2019

DOI : https://doi.org/10.1038/s41398-019-0552-0

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Nutrient scoring for the degs1-ffq – from food intake to nutrient intake.

• Ronja Thieleking
• Lennard Schneidewind
• Evelyn Medawar

BMC Nutrition (2023)

Environmental pressures and pesticide exposure associated with an increase in the share of plant-based foods in the diet

• Emmanuelle Kesse-Guyot
• Benjamin Allès
• Julia Baudry

Scientific Reports (2023)

Animal protein intake is directly associated with serum level of pentraxin 3 in hemodialysis patients

• Fatemeh Navab
• Sahar Foshati
• Mohammad Hossein Rouhani

Integrated multiomic wastewater-based epidemiology can elucidate population-level dietary behaviour and inform public health nutrition assessments

• Devin A. Bowes
• Erin M. Driver
• Rolf U. Halden

Nature Food (2023)

Influence of the vegan, vegetarian and omnivore diet on the oral health status in adults: a systematic review and meta-analysis

• Luana Giò Azzola
• Nicolas Fankhauser
• Murali Srinivasan

Evidence-Based Dentistry (2023)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Mediterranean diet tied to one-fifth lower risk of early death in women

Investigators from Brigham and Women's Hospital identified and assessed underlying mechanisms that may explain the Mediterranean diet's 23 percent reduction in all-cause mortality risk for American women

The health benefits of the Mediterranean diet have been reported in multiple studies, but there is limited long-term data of its effects in U.S. women and little understanding about why the diet may reduce risk of death. In a new study that followed more than 25,000 initially healthy U.S. women for up to 25 years, researchers from Brigham and Women's Hospital, a founding member of the Mass General Brigham healthcare system, found that participants who had greater Mediterranean diet intake had up to 23% lower risk of all-cause mortality, with benefits for both cancer mortality and cardiovascular mortality. The researchers found evidence of biological changes that may help explain why: they detected changes in biomarkers of metabolism, inflammation, insulin resistance and more. Results are published in JAMA .

"For women who want to live longer, our study says watch your diet! The good news is that following a Mediterranean dietary pattern could result in about one quarter reduction in risk of death over more than 25 years with benefit for both cancer and cardiovascular mortality, the top causes of death in women (and men) in the US and globally," said senior author Samia Mora, MD, a cardiologist and the director of the Center for Lipid Metabolomics at the Brigham.

The Mediterranean diet is a plant-based diverse diet that is rich in plants (nuts, seeds, fruits, vegetables, whole grains, legumes). The main fat is olive oil (usually extra virgin), and the diet additionally includes moderate intake of fish, poultry, dairy, eggs, and alcohol, and rare consumption of meats, sweets, and processed foods.

The current study investigated the long-term benefit of adherence to a Mediterranean diet in a U.S. population recruited as part of the Women's Health Study, and explored the biological mechanisms that may explain the diet's health benefits. The study investigators evaluated a panel of approximately 40 biomarkers representing various biological pathways and clinical risk factors.

Biomarkers of metabolism and inflammation made the largest contribution, followed by triglyceride-rich lipoproteins, adiposity, insulin resistance. Other biological pathways relate to branched-chain amino acids, high-density lipoproteins, low-density lipoproteins, glycemic measures, and hypertension have smaller contribution.

"Our research provides significant public health insight: even modest changes in established risk factors for metabolic diseases -- particularly those linked to small molecule metabolites, inflammation, triglyceride-rich lipoproteins, obesity, and insulin resistance -- can yield substantial long-term benefits from following a Mediterranean diet. This finding underscores the potential of encouraging healthier dietary habits to reduce the overall risk of mortality," said lead author Shafqat Ahmad, PhD, an associate professor of Epidemiology at Uppsala University Sweden and a researcher in the Center for Lipid Metabolomics and the Division of Preventive Medicine at the Brigham.

The current study identifies important biological pathways that may help explain all-cause mortality risk. However, the authors note some key limitations, including that the study was limited to middle aged and older well-educated female health professionals who were predominantly non-Hispanic and white. The study relied on food-frequency questionnaires and other self-reported measures, such as height, weight and blood pressure. But the study's strengths include its large scale and long follow up period.

The authors also note that as the concept of the Mediterranean diet has gained popularity, the diet has been adapted in different countries and cultures.

"The health benefits of the Mediterranean diet are recognized by medical professionals, and our study offers insights into why the diet may be so beneficial. Public health policies should promote the healthful dietary attributes of the Mediterranean diet and should discourage unhealthy adaptations," said Mora.

• Cholesterol
• Diet and Weight Loss
• Food and Agriculture
• Endangered Plants
• Population dynamics of fisheries
• Mammography
• Head injury
• Cervical cancer
• Appendicitis
• Breast cancer

Story Source:

Materials provided by Brigham and Women's Hospital . Note: Content may be edited for style and length.

Journal Reference :

• Shafqat Ahmad, M. Vinayaga Moorthy, I-Min Lee, Paul M Ridker, JoAnn E. Manson, Julie E. Buring, Olga V. Demler, Samia Mora. Mediterranean Diet Adherence and Risk of All-Cause Mortality in Women . JAMA Network Open , 2024; 7 (5): e2414322 DOI: 10.1001/jamanetworkopen.2024.14322

Cite This Page :

Explore More

• How Statin Therapy May Prevent Cancer
• Origins of 'Welsh Dragons' Exposed
• Resting Brain: Neurons Rehearse for Future
• Observing Single Molecules
• A Greener, More Effective Way to Kill Termites
• One Bright Spot Among Melting Glaciers
• Martian Meteorites Inform Red Planet's Structure
• Volcanic Events On Jupiter's Moon Io: High Res
• What Negative Adjectives Mean to Your Brain
• 'Living Bioelectronics' Can Sense and Heal Skin

Trending Topics

Strange & offbeat.

The 2024 Global Food Policy Report Stresses Urgent Need for Transformative Action to Achieve Sustainable Healthy Diets and Improved Nutrition

• From International Food Policy Research Institute (IFPRI)
• Published on 29.05.24

Share this to :

Washington DC, May 29, 2024:   In the face of growing challenges posed by unhealthy diets, all forms of malnutrition, and environmental constraints, the   2024 Global Food Policy Report   (GFPR) — released today by the International Food Policy Research Institute (IFPRI) — underscores the importance of transforming complex global food systems to ensure sustainable healthy diets for all.

Progress in reducing undernutrition and micronutrient deficiencies has slowed in low- and middle-income countries, while overweight and obesity has rapidly increased worldwide. Many countries are facing a double burden of malnutrition — meaning that undernutrition and micronutrient deficiencies coexist with overweight and obesity, or diet-related noncommunicable diseases (NCDs), within individuals, households, and communities, and across the life course. At the same time, there is a pressing need for food systems to undergo transformation to reduce their considerable environmental impact.

“To meet our ambitious global development goals on diets and nutrition, we need innovative research across the food system that informs and supports large-scale equitable impacts. People and the planet are at the heart of our efforts, and so our priorities for research and action center on understanding how to make sustainable healthy diets aspirational, affordable, and accessible for all,” commented Ismahane Elouafi, Executive Managing Director, CGIAR.

The   2024 Global Food Policy Report: Food Systems for Healthy Diets and Nutrition , co-authored by 41 researchers representing IFPRI and several partner organizations, calls for urgent and concerted efforts to transform global food systems to ensure equitable access to sustainable healthy diets for everyone. Improving diets is a global imperative that will require addressing multiple issues across food systems to achieve meaningful and sustainable changes in diets and, in turn, nutrition and health outcomes.

“Evidence suggests that poor quality diets are the leading cause of disease worldwide and that one in five lives could be saved by improving diets. Thus, it is imperative that we prioritize improving diets as a critical entry point for addressing all forms of malnutrition and diet-related NCDs,” stressed Deanna Olney, Director of IFPRI’s Nutrition, Diets, and Health Unit and a lead author of the report.

The 2024 GFPR emphasizes the need for   sustainable healthy diets   and provides evidence-based recommendations on ways to make the foods that form these diets more desirable, affordable, accessible, and available while considering environmental impacts. This holistic approach recognizes the interplay between dietary patterns, food environments, food production, food-related policies, and broader societal and environmental factors.

“Our research estimates that more than 2 billion people, many of them in Africa and South Asia, cannot afford a healthy diet. According to FAO, more than half of children under the age of five and two-thirds of adult women are affected by micronutrient deficiencies. The 2024 GFPR serves as a clarion call for prioritizing sustainable healthy diets as a cornerstone of public health and sustainable development,” said Johan Swinnen, Director General, IFPRI and Managing Director, Systems Transformation, CGIAR.

The report draws on a comprehensive food systems framework to recommend transformative actions. “By addressing demand-side challenges, such as affordability and consumer preferences, alongside improving food environments and addressing supply-side issues to enhance the availability of nutritious foods, we can make sustainable healthy diets a reality,” said Purnima Menon, Senior Director, Food and Nutrition Policy, CGIAR and IFPRI, a lead contributor to the report.

The report underscores the imperative of collaborative efforts, innovative interventions, food system approaches, and sound policies and governance to overcome the complex challenges facing global food systems. As nations strive to meet the malnutrition targets necessary to achieve the UN’s Sustainable Development Goal 2, the 2024 GFPR underscores the need for accelerated action, robust financing mechanisms, and evidence-based policymaking to accomplish lasting impact.

The 2024 GFPR is an important contribution to the global dialogue on food security, public health, and sustainable development, providing a roadmap for the transformative change required for global food systems to ensure sustainable healthy diets and nutrition for all.

Read report and synopsis

Visit 2024 GFPR website

Recommended citation:   International Food Policy Research Institute. 2024.   2024 Global Food Policy Report: Food Systems for Healthy Diets and Nutrition . Washington, DC: International Food Policy Research Institute.   https://hdl.handle.net/10568/141760

Hybrid global launch event “2024 Global Food Policy Report: Improving Diets and Nutrition through Food Systems: What Will it Take?”

May 29, 2025, 9:30am–11:00 am EDT

More information and register:   https://www.ifpri.org/event/improving-diets-and-nutrition-through-food-systems-what-will-it-take

The International Food Policy Research Institute (IFPRI)   provides research-based policy solutions to sustainably reduce poverty and end hunger and malnutrition. IFPRI’s strategic research aims to identify and analyze alternative international and country-led strategies and policies for meeting food and nutrition needs in low- and middle-income countries, with particular emphasis on poor and vulnerable groups in those countries, gender equity, and sustainability. It is a research center of CGIAR, a worldwide partnership engaged in agricultural research for development.  www.ifpri.org

Media inquiries : Evgeniya Anisimova,   [email protected]

This website uses cookies in order to improve the use experience and provide additional functionality Detail

To revisit this article, visit My Profile, then View saved stories .

New Study Suggests the Keto Diet May Actually Be Harmful to Health

By Margaux Anbouba

The ketogenic diet rose to popularity in the early 2000s with the mantra “fat is not the enemy.” But a study covered in the March 2024 issue of Current Problems in Cardiology suggests that the diet—which focuses on foods high in fats and deemed very low in carbohydrates—is perhaps something of a Trojan horse.

The paper, published by Joanna Popiolek-Kalisz, MD and PhD, found a few issues with the diet’s parameters. The first was weight-loss related: While many people who followed it experienced rapid weight loss (typical of making any significant diet change), it was likely mostly water weight and failed to yield any permanent positive health changes within the body. “The ketogenic diet does not fulfill the criteria of a healthy diet,” Popiolek-Kalisz states in the paper. Quite the contrary, in fact: When it comes to overall heart health, “the low-carb pattern is more beneficial than very low-carbohydrate (including the ketogenic diet).” Because of the keto diet’s emphasis on fats, those adhering to it typically have a higher rate of LDL cholesterol , which is associated with a higher risk of heart disease, clogged arteries, and death.

Low-carb dietary plans include the Atkins diet, the paleo diet, and the South Beach diet. Other studies have noted that the keto diet can also lead to major vitamin and mineral deficiencies (as well as a surplus of fat-soluble vitamin K, which is also unhealthy for the heart) and increased kidney stones .

According to the International Food Information Council’s annual study, more than half of Americans follow a diet or a specific eating pattern—but the high-fat keto diet dropped in popularity by 4% compared to 2023. That trend will likely continue downward.

The ketogenic diet: Pros and cons

Affiliations.

• 1 Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, AB, Canada; Department of Medicine, University of Alberta, Edmonton, AB, Canada; Division of Cardiology, University of Alberta, Edmonton, AB, Canada.
• 2 Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, AB, Canada; Department of Medicine, University of Alberta, Edmonton, AB, Canada; Division of Cardiology, University of Alberta, Edmonton, AB, Canada. Electronic address: [email protected].
• PMID: 31805451
• DOI: 10.1016/j.atherosclerosis.2019.11.021

Diets have been at the center of animated debates for decades and many claims have been made in one direction or the other by supporters of opposite camps, often with limited evidence. At times emphasis has been put on a single new aspect that the previous diets had overlooked and the new one was to embrace in order to improve weight loss and well-being. Unfortunately, very few randomized clinical trials involving diets have addressed the combined question of weight loss and cardiovascular outcomes. The recently introduced ketogenic diet requires a rigorous limitation of carbohydrates while allowing a liberal ingestion of fats (including saturated fats) and has generated a flurry of interest with many taking the pro position and as many taking the cons position. The ketogenic diet causes a rapid and sensible weight loss along with favourable biomarker changes, such as a reduction in serum hemoglobin A1c in patients with diabetes mellitus type 2. However, it also causes a substantial rise in low density lipoprotein cholesterol levels and many physicians are therefore hesitant to endorse it. In view of the popular uptake of the keto diet even among subjects not in need of weight loss, there is some preoccupation with the potential long-term consequences of a wide embrace of this diet by large segments of the population. On the contrary, numerous lines of evidence show that plant-based diets are associated with reduction in oncological and cardiovascular diseases and a prolonged life span. The debate reproduced in this article took place during a continuous medical education program between two cardiologists with largely differing views on the matter of effectiveness, sustainability, and safety of the ketogenic diet compared to alternative options.

Copyright © 2019 Elsevier B.V. All rights reserved.

Publication types

• Diet, Ketogenic* / adverse effects
• Diet, Reducing* / adverse effects

• Weird But True
• Sex & Relationships
• Viral Trends
• Human Interest
• Fashion & Beauty
• Food & Drink
• Health Care
• Men’s Health
• Women’s Health
• Mental Health
• Health & Wellness Products
• Personal Care Products

trending now in Lifestyle

I thought a Florida alligator was walking near me and my daughter...

I lost 110 pounds in 15 months — thanks to a quick...

Sex has unique health benefits for chronically stressed moms,...

Here's the real reason why flight attendants greet passengers...

Best vacation spots if you’re trying to avoid hurricanes in the...

Wealthy people 'at greater risk of cancer' than the rest of us:...

Plane passenger slammed for refusing to switch seats mid-flight...

Men keep hitting on me at the gym, then I turn around and they...

How intermittent fasting, protein pacing can lead to weight loss, better gut health.

• View Author Archive
• Follow on X
• Get author RSS feed

Thanks for contacting us. We've received your submission.

Start the clock!

Practicing protein pacing — evenly spacing protein consumption throughout the day — and intermittent fasting — limiting eating to certain times — is better for gut health, weight loss, and metabolic responses than just restricting calories, a new Arizona State University study finds .

27 women and 14 men who were overweight or obese were divided into two groups: one ate a heart-healthy, calorie-restricted diet, while the other followed a calorie-restricted plan incorporating intermittent fasting and protein pacing.

Both groups were monitored over eight weeks for changes in their weight, body composition, gut bacteria, and metabolic health.

Participants following the intermittent fasting and protein-pacing diet significantly reduced their gut symptoms, increased their beneficial gut bacteria, lost more weight, and shed more body fat.

The fasting/pacing group dropped an average of 8.81% of their initial body weight while those on the calorie-restricted diet lost just 5.4% on average. The calorie-restricted group also received worse news about their metabolic health.

As part of the findings, published last week in the journal Nature Communications , the researchers determined that the intermittent fasting protocol increases beneficial gut microbes tied to a lean body type and better health while raising the levels of proteins in the blood linked to weight loss.

“A healthy gut microbiome is essential for overall health, particularly in managing obesity and metabolic diseases,” said Karen Sweazea, the ASU principal study investigator.

“The gut bacteria influence how we store fat, balance glucose levels and respond to hormones that make us feel hungry or full,” she continued. “Disruptions in the gut microbiota can lead to increased inflammation, insulin resistance and weight gain, underscoring the critical role of gut health in preventing and managing metabolic disorders.”

Get the latest breakthroughs in medicine, diet & nutrition tips and more.

Subscribe to our weekly Post Care newsletter!

Thanks for signing up!

Please provide a valid email address.

By clicking above you agree to the Terms of Use and Privacy Policy .

Never miss a story.

Intermittent fasting has been associated with weight loss, a lower risk of Type 2 diabetes and heart disease, less inflammation , and improved immune function. But research has also cast doubt on its purported benefits.

One recent major study found that those who limit their eating to a window less than eight hours a day are more likely to die from cardiovascular disease than people who eat over 12-16 hours a day. Medical experts also warn that intermittent fasting is not for everyone.

Consult your doctor if you have diabetes, kidney stones, gastroesophageal reflux, or other medical conditions before beginning an intermittent fasting plan.

Share this article:

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• v.12(8); 2020 Aug

Advantages and Disadvantages of the Ketogenic Diet: A Review Article

Jennifer t batch.

1 Internal Medicine, Orange Park Medical Center, Orange Park, USA

Sanjay P Lamsal

2 Radiology, University of Florida Health Jacksonville, Jacksonville, USA

Michelle Adkins

3 Pharmacy, University of Florida, Gainesville, USA

Senan Sultan

4 Endocrinology, Orange Park Medical Center, Orange Park, USA

Monica N Ramirez

5 Pharmacy, University of Florida Health Jacksonville, Jacksonville, USA

The ketogenic diet (KD) has gained immense popularity during the last decade, primarily because of its successful short-term effect on weight loss. In the United States, KD is utilized in a variety of patient populations for weight management, despite limited evidence regarding its efficacy and risks. This literature review provides an evaluation of data on the benefits and risks associated with the chronic use of KD, including its metabolic, endocrinological, and cardiovascular effects.

Introduction and background

Obesity is classified based on the body mass index (BMI) of the individual. A BMI of 18.5-24.9 kg/m 2 is considered to be the normal range, while a BMI of 25.0-29.9 is considered overweight and a BMI ≥30 is classified as obese (further classified as obesity class I if BMI is between 30.0-34.9, class II if BMI is between 35.0-39.9, and class III if BMI is ≥40.0). In 2016, the World Health Organization (WHO) reported that more than 1.9 billion (39%) adults were overweight globally and of these, over 650 million (13%) were obese [ 1 ]. Obesity is associated with multiple comorbidities including type 2 diabetes, hypertension, cardiovascular disease (CVD), cancer, sleep apnea, and obesity-hypoventilation syndrome (OHS). The effectiveness of different types of diets based on different macronutrient restrictions has been a topic of debate for the past few years. Some researchers support restriction in carbohydrate (CHO), while others endorse cutting down protein or fats [ 2 ].

This review article will focus on the ketogenic diet KD, which is defined as a low-carbohydrate diet (LCD) with a moderate amount of protein restriction to induce ketosis without restricting fat intake [ 3 ]. The concept of KD was initially developed in 1921 by Dr. Russel Wilder for the management of refractory seizures in pediatric patients [ 4 ]. Originally, the diet consisted of a 4:1 ratio of fat-to-CHO and protein. Fat provides upwards of 90% the caloric intake [ 5 ]. All variations of this diet, whether involving animal- or plant-based derivatives, are based on severely restricting overall intake of CHO with a goal of bringing it down to less than 50 g/day. A well-formulated KD limits protein intake moderately to less than 1 g/lb body weight, or 1.5 g/lb body weight for individuals performing heavy exercises. Additionally, the diet does not restrict fat intake while decreasing appetite and caloric intake, resulting in weight loss observed after the initiation of the diet [ 6 ].

Following CHO deprivation and depletion of glycogen stores, the body undergoes metabolic changes to provide an energy source for the body through gluconeogenesis and ketogenesis. Gluconeogenesis can be sustained for three days with adherence to an LCD, and subsequently, additional energy sources are necessary to meet the metabolic requirements of the body and brain. This is where the process of ketogenesis becomes indispensable, and the formation of ketone bodies is then used as the primary energy source by cells with mitochondria and, most importantly, the brain [ 6 ].

KD has been shown to effectively lead to weight loss, reduction in hyperinsulinemia, and improvement in insulin sensitivity. However, patients diagnosed with diabetes on insulin or oral hypoglycemic agents may suffer severe hypoglycemia if their medication regimen is not properly managed during the initiation of KD. Furthermore, the diet is limited and/or contraindicated in patients with liver failure, pancreatitis, inborn disorders of fat metabolism, primary carnitine deficiency, carnitine palmitoyltransferase deficiency, carnitine translocase deficiency, porphyria, and pyruvate kinase deficiency [ 6 ]. Common short-term side effects resulting from the initiation of KD have been referred to as “keto flu,” which encompasses symptoms including fatigue, headache, dizziness, nausea, vomiting, constipation, and low exercise tolerance [ 6 ]. Symptoms typically resolve after a few days to weeks as the body adjusts to the low CHO, ketogenic state. Long-term side effects include hepatic steatosis, kidney stones, hypoproteinemia, and vitamin deficiency. While the benefits of following KD have been extensively reported, long-term compliance with KD is a limiting factor. The sustainability of the diet has been called into question, and the prognosis of the diet’s effects after discontinuation must be examined.

1. Ketogenic diet and cardiovascular risk factors

Dyslipidemia

In a systematic review and meta-analysis of clinical trials performed by Santos et al., a total of 23 randomized controlled trials corresponding to 17 clinical investigations were analyzed. The authors concluded that LCD has positive effects on body weight, BMI, abdominal circumference, blood pressure, high-density lipoprotein cholesterol (HDL-C), triglycerides, glycemia, hemoglobin A1c (HbA1c), insulin, and C-reactive protein (CRP) [ 2 ]. However, despite the positive impact on cardiovascular risk factors, there is insufficient data to support KD in the long term as the studies were of relatively shorter duration, ranging from three to 36 months only.

In another meta-analysis performed by Bueno et al., a total of 13 randomized controlled trials were examined. The authors reported statistically significant results in the first six months of intervention, but at longer periods of 12-24 months, the statistical significance of outcomes decreased. In a majority of the studies analyzed, CHO intake was higher than the protocol allowed, which was less than 50 g of CHO per day. These similarities found during the follow-up period were likely a contributing factor to the observed decrease in statistical significance [ 7 ]. Also, participants following a very-low-carbohydrate ketogenic diet (VLCKD) had a significantly greater increase in low-density lipoprotein cholesterol (LDL-C) levels when compared to participants following a low-fat diet (LFD) (95% CI: 0.04 to 0.2; p=0.002). This increase in LDL-C may subsequently lead to the development of accelerated atherosclerosis and increases the risks associated with CVD.

The lack of evidence regarding long-term cardiovascular implications indicates that making recommendations against or in favor of KD should be a topic of further discussion. In a randomized controlled trial performed at the outpatient care of the Philadelphia Veterans Affairs Medical Center among adults of ≥18 years old with a BMI of ≥35 kg/m 2 , 64 participants were assigned to an LCD and 68 participants were assigned to a conventional diet. Analysis at one year of initiating the study found favorable metabolic effects on atherogenic dyslipidemia and glycemic control with participants on an LCD compared to participants on a conventional diet [ 8 ]. The mean weight change for participants assigned to the LCD group was -5.1 ±8.7 kg, while it was -3.1 ±8.4 kg for the conventional diet group. However, the differences in weight change were not significant [-1.9 kg (95% CI: -4.9 to 1.0 kg), p=0.20]. This reinforces the low sustainability of a long-term LCD and the high likelihood of regaining the weight lost. 

Interestingly, multiple studies mention a “favorable” lipid profile associated with KD because it increases HDL-C and decreases triglyceride levels. Distinguishably, increases are observed with LDL-C and total cholesterol. A review article analyzing five randomized controlled trials concluded that, after six months, individuals assigned to an LCD lost more weight than individuals assigned to an LFD with a weight difference of -3.3 kg (95% CI: -5.3 to -1.4 kg). Nevertheless, this significant difference was not identified after one year of intervention (95% CI: -3.5 to 1.5 kg). Triglyceride levels had a significant decrease [-22.1 mg/dl (95% CI: -38.1 to -5.3 mg/dl)], and HDL-C levels underwent a significant increase [4.6 mg/dl (95% CI: 1.5 to -8.1 mg/dl)] in the LCD group when compared to the LFD group. Conversely, LDL-C and total cholesterol changed more favorably in the LFD group after six months of the intervention [ 9 ]. The mechanism postulated for this is mediated through lower CHO intake, inducing suppressed insulin production. Concomitantly, decreased insulin production inhibits 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase activation and stimulates HMG-CoA lyase involved in ketone production. Thus, following a low CHO diet inadvertently leads to increased production of LDL-C and hypothetically promotes atherosclerotic properties.

Differentiation in Fat Sources

As reported by Seidelmann et al. in a prospective cohort study and meta-analysis, it is not only a matter of CHO restriction but also the quality of food ingested. The study’s primary outcome measure was all-cause mortality. After multivariable adjustment and a median follow-up period of 25 years, a U-shape association was observed between the percentage of energy consumed from CHO and mortality [pooled hazard ratio (HR): 1.20 (95% CI: 1.09 to 1.32 for low CHO consumption); pooled HR: 1.23 (95% CI: 1.11 to 1.36 for high CHO consumption)] in the Atherosclerosis Risk in Communities (ARIC) cohort. The authors emphasized that both low (<40%) and high CHO consumption (>70%) conferred higher mortality when compared with moderate CHO intake. Further analysis of the results demonstrated that mortality was worse when fat and protein sources were animal-derived instead of plant-derived. A relationship may exist between decreasing mortality rates and long-term approach considerations in the replacement of CHO with plant-based fats and proteins such as vegetables, nuts, and whole grains [ 10 ].

Hypertension

A meta-analysis that included 13 studies aimed to examine whether participants assigned to a VLCKD (diet restriction to ≤50 g CHO/day) would achieve better long-term body weight and cardiovascular risk factor management when compared with participants assigned to a conventional LFD (diet restriction to <30% energy from fat). In the overall analysis, those assigned to the VLCKD group showed a statistically significant decrease in their primary outcome: body weight: -0.91 kg (95% CI: -2.49 to -0.37). Additionally, of the 13 studies, 11 were included in the systolic blood pressure (SBP) and diastolic blood pressure (DBP) subgroup analyses. A statistically greater reduction in DBP [-1.43 mmHg (95% CI: -2.49 to -0.37)] was reported in participants assigned to a VLCKD compared to participants assigned to an LFD. Furthermore, an increase was reported in secondary endpoints: HDL-C: 0.09 mmol/l (95% CI: 0.06 to 0.12), LDL-C: 0.12 mmol/l (95% CI: 0·04 to 0·2), and triacylglycerol (TAG): -0.18 mmol/l (95% CI: -0.27 to -0.08) [ 7 ].

In contrast, a meta-analysis of 11 randomized controlled trials proposed to assess the effects of LCD vs LFD on weight loss and risk factors of CVD reported that cardiovascular risk factors such as SBP and DBP were not found to be statistically significant among both groups. A dietary intervention of six months or longer was implemented, and participants assigned to the LCD group had greater reductions in body weight [-2.17 kg (95% CI: -3.36 to -0.99)] and TAG [-0.26 mmol/l, (95% CI: -0.37 to -0.15)]. On the other hand, increases in LDL-C [0.16 mmol/l (95% CI: 0.003 to 0.33)] and HDL-C [0.14 mmol/l, (95% CI: 0.09 to 0.19)] were observed [ 11 ].

2. Effects of the ketogenic diet on endocrinology and metabolism

Polycystic Ovarian Syndrome

KD has been postulated to positively impact women diagnosed with polycystic ovarian syndrome (PCOS). Women with PCOS experience symptoms of irregular/absent menses, infertility, obesity, and other phenotypical effects of hyperandrogenism such as hirsutism. PCOS is closely associated with other metabolic and endocrinological irregularities, which include insulin resistance, hyperinsulinemia, type 2 diabetes mellitus, dyslipidemia, and hyperandrogenism [ 12 ]. PCOS is accompanied by key features such as insulin resistance, androgen excess, and abnormal gonadotropin dynamics. In turn, treatment is targeted towards improving insulin resistance, weight loss, decreasing luteinizing hormone (LH) and follicular stimulating hormone (FSH) ratios, and excess androgens. A study by Mavropoulos et al. implemented KD for women between the ages of 18-45 years diagnosed with PCOS, with a BMI greater than 27 kg/m2, and no other serious medical conditions. Participants adhered to a six-month period of strict KD consisting of less than 20 g of CHO per day with unlimited consumption of animal-based foods. After 24 weeks, the results of the study (pre- and post-design) showed a statistically significant decrease in fasting serum insulin (23.5 to 8.2, p=0.002), LH-to-FSH ratio (2.23 to 1.21, p≤0.05), and free testosterone (2.19 to 1.70, p≤0.05). Furthermore, the study subjects had an overall mean body weight change from baseline of -12.1% and a mean decrease in BMI of 4.0 kg/m2 (p=0.0006) [ 12 ]. Despite the results of the pilot study demonstrating a positive impact, there are limitations in generalization due to the small sample sizes of the study.

A crossover study by Gower et al. included participants with PCOS who were randomly assigned to either a standard diet or an LCD. The results demonstrated that LCD can lead to decreases in glycemia, fasting insulin, testosterone, and insulin sensitivity. However, the study had limitations due to the broad age range of participants and the small sample size, thereby rendering it inadequate in terms of generalizability [ 13 ]. Similar results were reported by Paoli et al., with significant reductions in BMI, glycemia, insulin, LDL-C, HDL-C, triglycerides, LH, testosterone, and dehydroepiandrosterone sulfate (DHEAS). Even though a reversal of the LH-to-FSH ratio was observed initially, it was not reported after 12 weeks. Limitations of this study include small sample size, single-arm design, lack of infertility measurements, and a short intervention time interval [ 14 ].

Diabetes Mellitus and Insulin

The term “Ketogenic Diet” may lead to apprehension in diabetic patients given its association with the well-known, life-threatening condition of ketoacidosis. It is important to note that during nutritional ketosis, the concentrations of beta-hydroxybutyrate and acetone are of low levels and do not cause any alterations in the pH of blood [ 6 ]. Management of type 1 and type 2 diabetes generally consists of medication adjustments targeted toward glycemic control and an HbA1c level of <7%. As mentioned previously with regard to patients with PCOS, the same benefits of following a VLCKD apply to patients with diabetes as well. They include decreased glycemia, lower levels of fasting insulin, decreased insulin resistance, and potentiating decreased requirements of insulin and/or oral glycemic medications. Thus, VLCKD has become popular among patients suffering from diabetes and obesity; nevertheless, the appropriateness of this diet is still debated.

In an outpatient clinic study by Yancy et al., overweight patients diagnosed with type 2 diabetes were made to follow a VLCKD throughout 16 weeks with the primary outcome measure of monitoring blood glucose control through HbA1c levels. The 28 participants enrolled were restricted to less than 20 g of CHO per day. At the end of the 16-week timeframe, HbA1c decreased from 7.5 ±1.4% to 6.3 ±1.0% (p<0.001). The absolute decrease in HgA1c was approximately 1.0% in 11 participants (52%). The relative decrease in HgA1c from baseline was >10% in 14 participants, and >20% in six participants. Furthermore, seven participants had their baseline diabetic medications discontinued, 10 participants had their baseline medications decreased, while four participants had unchanged requirements regarding baseline medications [ 15 ]. 

A similar observational study was performed by Leow et al. to evaluate the glycemic benefits of a VLCKD in patients diagnosed with type 1 diabetes. The study had a total of 11 eligible participants based on the study inclusion criteria, which included type 1 diabetes of ≥2 years, not taking any medications other than insulin, fasting blood beta-hydroxybutyrate levels of ≥0.4 mmol/l, and C-peptide levels of <0.05. Participants were required to follow a VLCKD with ingestion of less than 55 g of CHO a day for more than six months. The median duration of intervention was 1.5 years (range: 0.6-3 years). All participants had their HbA1c, C-peptide, beta-hydroxybutyrate levels, lipoprotein profile, markers of liver and kidney function, height, body mass, and blood pressure measurements taken after overnight fasting. The participants were found to have a mean HbA1c of 5.3% ±0.4%; mean and median blood glucose levels determined from continuous glucose monitoring were 5.8 ±1.2 and 5.5 (3.1-8.4) mmol/l, respectively. Daily blood glucose variability, expressed as standard deviation (SD) and coefficient of variation, was 1.5 ±0.7 mmol/l and 26.4% ±8.0%, respectively. The mean and median magnitude of postprandial blood glucose excursions were 0.8 ±1.5 and 0.5 (0-2.2) mmol/l, respectively. Hypoglycemic events were detected with continuous glucose monitoring; patients experienced 0.9 (0.0-2.0) episodes of hypoglycemia per day, defined as blood glucose levels of <3.0 mmol/l [ 5 ]. The results of this study indicate that adherence to KD in type 1 diabetics is associated with well-controlled HbA1c levels and minimal glycemic variability. Although this shows some evidence regarding the normalization of HbA1c, the diet comes with increased risks of hypoglycemic episodes. Hence, it is important to emphasize that insulin regimens, as well as oral hypoglycemic agents, must be closely monitored and adjusted in any diabetic patient following a VLCKD regimen. 

Long-term adherence to KD is a major challenge and that is why this type of diet is considered non-sustainable. A comparison of different meta-analyses, review articles, and interventional studies revealed that no uniformity was established in the reported results. The limitations of most studies are attributed to small sample sizes, short duration of interventions, and high participant dropout rates. Due to the above-mentioned issues, even though some studies show positive results, we cannot consider them applicable to the general population; especially given that patients with diabetes or obesity often have other comorbid conditions such as dyslipidemia and CVD.

In a controlled study involving 20 participants receiving a nutritional intervention with VLCKD, a significant improvement in anthropometric and biochemical parameters was observed after eight weeks of therapy. This included a reduction in BMI, LDL-C, triglycerides, insulinemia, and liver transaminases. Additionally, it was reported that VLCKD also reduced inflammation [ 16 ]. Limitations once again include small sample size and a short period of intervention. In a meta-analysis of 11 studies, significant weight reductions were reported in the LCD groups when compared to LFD groups. Interestingly, the authors mentioned that this was attributed to lower energy intake rather than the macronutrient composition [ 11 ].

The aim of The Diet Intervention Examining the Factors Interacting with Treatment Success (DIETFITS) randomized clinical trial was to determine the effect of healthy low-fat (HLF) diet vs a healthy low-carbohydrate (HLC) diet on weight change and if genotype pattern or insulin secretion were related to the dietary effects on weight loss. The clinical trial, involving 609 overweight adults, did not demonstrate any results of statistical significance regarding its primary outcome measure, which was weight change with an HLF diet or HLC diet over 12 months. Similarly, neither type of diet showed outcomes of statistical significance in genotype pattern interaction or baseline insulin secretion interaction with 12-month weight loss. It can be assumed that it would be difficult to identify which type of diet is better for any individual. Thus, this leads us to conclude that dietary modifications remain key to successful weight loss [ 17 ].

Lastly, a multicenter randomized controlled trial by Ebbeling et al. randomly assigned participants who achieved target weight loss to either a low CHO, moderate CHO, or high CHO diet. This 20-week interventional study found that independent of body weight, total energy expenditure was significantly greater in participants assigned to low CHO diets compared to high CHO diets of similar protein content. Moreover, a significant decrease in metabolic hormonal response with both ghrelin and leptin was reported in the participants assigned to the low CHO diet compared with those assigned to the high CHO diet. These results led the authors to conclude that these metabolic effects and the correlation of dietary quality with energy expenditure may be helpful in the treatment of obesity [ 18 ].

Conclusions

Based on our review, within the first 6-12 months of initiating KD, transient decreases in blood pressure, triglycerides, and glycosylated hemoglobin, as well as increases in HDL and weight loss may be observed. However, the aforementioned effects are generally not seen after 12 months of therapy, as the changes reported in the studies we reviewed are not statistically significant. Further research is warranted to evaluate the long-term implications of KD. Despite the diet's favorable effect on HDL-C, the concomitant increases in LDL-C and very-low-density lipoproteins (VLDL) may lead to increased cardiovascular risks. Additionally, the dietary restrictions required to sustain ketosis may actually lead to its low sustainability. Unfortunately, most available studies lack generalizability and validity due to their small sample sizes and short study durations. Due to the limited amount of robust studies and lack of strong evidence evaluating the diet’s potential risks, recommendations supporting VLCKD in patients with no comorbidities, or cardiometabolic and endocrinologic diseases should be made at the provider’s discretion.

Funding Statement

This research was supported (in whole or in part) by HCA and/or an HCA-affiliated entity. The views expressed in this publication represent those of the author(s) and do not necessarily represent the official views of HCA or any of its affiliated entities.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.