A life course perspective on diet quality and healthy ageing
Vinke, Petra
DOI:
10.33612/diss.135998182
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from
it. Please check the document version below.
Document Version
Publisher's PDF, also known as Version of record
Publication date:
2020
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
Vinke, P. (2020). A life course perspective on diet quality and healthy ageing. University of Groningen.
https://doi.org/10.33612/diss.135998182
Copyright
Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).
Take-down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum.
10
GENERAL INTRODUCTION
The ongoing worldwide increase in life expectancy comes with challenges, as the goal is to not only live longer, but also in good health. In 2018, non-communicable chronic diseases like cardiovascular diseases, cancer and diabetes accounted for 71% of all deaths globally 1. Many risk factors for chronic diseases and associated mortality
can be identified, covering the genetic, environmental and lifestyle domain 1,2, of
which the latter receives lots of scientific attention due to its modifiable character. Of all lifestyle risk factors, suboptimal dietary factors account for most deaths globally
3,4. Furthermore, nutrition provides the building blocks and fuel for our cells and
is therefore essential for growth, development and survival. This makes nutrition different from other behavioral risk factors such as smoking or alcohol consumption: it is not a matter of elimination, but a matter of optimization of both quantity and quality in order to maximize its beneficial effects on health and diseases. For these reasons, diet quality is the lifestyle risk factor of primary interest in this thesis.
Nutritional science progressed over the past decades and high quality, evidence-based dietary guidelines that aimed at a reduction of diet-related chronic disease risk have been developed. Such guidelines are often intended to serve heterogeneous populations. A remaining question is how such guidelines and their underlying scientific evidence can be translated into tools to assess diet quality in scientific research. Furthermore, while the importance of diet quality in healthy ageing is well established, it is unclear whether the benefits of a healthy diet differ over the life course. The aims of this thesis are therefore to develop a state-of-the-art diet quality assessment tool, and to investigate the association of diet quality and healthy ageing across the life course, during which diet and health are influenced by contextual factors like age, gender, socio-economic status and cardiometabolic diseases.
ORIGINS OF NUTRITIONAL SCIENCES AND DIETARY
ASSESSMENT
The history of nutritional sciences
Medicinal qualities have been ascribed to food products in many cultures for centuries, but the discovery of the vitamins was the start of modern nutritional science. Vitamins were described for the first time in 1912 by Casimir Funk. As he observed that outbreaks of a group of diseases were primarily found in countries with monotonous diets consumed over a longer period of time, he hypothesized that the
135558_Petra_Vinke_BNW-def.indd 10
1
diseases were caused by a deficiency of an essential substance in the food. Early analyses indicated these substances were likely to be amines, which were vital to life, and were therefore called “vitamines” 5.
In the following decades, nutritional science was focused on the identification of vitamins and their role in single nutrient deficiency diseases like scurvy (vitamin C deficiency), beriberi (vitamin B1 deficiency) and rickets (vitamin D deficiency) 6,7.
These discoveries, among others, led to fortification of several food products and the issuance of the first recommended dietary allowances. Shortly after the second World War, these developments, together with economic progress, led to steep decreases in single nutrient deficiencies in high income countries 6. At the same
time, however, the incidence of other diet-related diseases such as obesity, Type 2 Diabetes, cardiovascular diseases and specific types of cancer started to increase. In response to the increase of chronic diseases related to diet, the first dietary guidelines aiming to reduce chronic disease risk were issued in the United States in 1980 8. At that time, nutritional sciences mainly focused on the influence of isolated
nutrients on health. Therefore, these guidelines solely provided nutrient-based recommendations, such as to limit the intake of saturated and total fat, cholesterol, sugar and salt, and to eat foods with adequate starch and fiber.
At the end of the 20th century, the first epidemiological studies investigated food products and dietary patterns, and their associations with varying health outcomes 6.
In this period studies consistently showed a beneficial health effect of Mediterranean-like diets 9,10, after Ancel Keys first observed that general health in Mediterranean
regions was beyond expectations 11. These advances contributed to a transition in
nutrition sciences, as it became clear that modern diet-related chronic diseases could not be explained by single nutrients only, but also by complex biological effects of foods and dietary patterns 12,13. This asked for a revision of dietary guidelines, to inform
the public on how to adapt their diet in accordance to the scientific developments.
Food-based dietary guidelines
Along with the transition towards a scientific focus on food products and dietary patterns, rather than nutrients alone, the World Health Organization (WHO) and Food and Agriculture Organization of the United Nations (FAO) first advocated the preparation and use of food-based dietary guidelines in 1998 14. An additional benefit
12
of food-based guidelines is that they can be more easily adopted by the public, as people tend to think in terms of foods, rather than nutrients. To date, more than 100 countries have issued food-based dietary guidelines. Differences in guidelines may exist since guidelines are accommodated to a countries’ food availability and culinary habits, but most guidelines agree with regard to recommendations such as to increase the intake of fruits, vegetables, whole-grain products and fish 15.
The Health Council of The Netherlands issued their first fully food-based dietary guidelines in 2015. In the development of these guidelines, the Health Council performed 29 systematic reviews of international peer-reviewed meta-analyses of prospective cohort studies and randomized controlled trials on relations of foods, dietary patterns and nutrients with intermediate risk factors or chronic diseases. This process led to 15 fully evidence-based guidelines, which recommend to increase the consumption of vegetables, fruit, whole-grain products, legumes, unsalted nuts, fish and tea, to maintain the consumption of dairy, and to limit the consumption of red and processed meat, sugar-containing beverages and alcoholic beverages. Furthermore, it is advised to replace refined cereal products by whole-grain products, to replace butter and hard margarines by soft margarines, liquid cooking fats and vegetable oils, and to replace unfiltered coffee by filtered coffee 16. Adhering to these
guidelines will naturally also result in a diet rich in nutrients such as unsaturated fats, fiber, antioxidants and minerals, which were often considered positive, and low in sodium, trans fat, saturated fat and sucrose, which are considered to be negative for health. Thus, a focus on intake of healthy food products will likely result in a nutrient-rich dietary pattern. This is not necessarily true the other way around, i.e. a focus on nutrients does not necessarily result in intake of healthy foods, since healthy nutrients can be part of food products of which healthfulness is debatable. For example, in earlier days, potato chips were often fried in fats with a high content of saturated fatty acids. After dietary guidelines advised to limit the intake of saturated fat intake, manufacturers have changed the production process. Nowadays, potato chips are mostly fried in plant-based oils high in unsaturated fatty acids. Therefore, this food product can be a dietary source of these healthy fatty acids, although it is not necessarily part of a healthy food-based dietary pattern. This is an example which further underlines the benefit of a focus on foods rather than nutrients 13. However,
while the issuance of food-based dietary guidelines already serves a public health purpose, additional steps are needed to enable the integration of such guidelines and their underlying evidence in scientific research.
135558_Petra_Vinke_BNW-def.indd 12
1
Measuring dietary intake and dietary quality
In order to investigate the association of nutrition and health in scientific research, methods to assess individual’s dietary quality are required. A first challenge before being able to assess the quality of the diet, is to measure an individual’s dietary intake. Several dietary assessment methods exist, all with specific benefits and disadvantages. Food frequency questionnaires (FFQs) are among the most commonly used methods, and are used to estimate long-term, habitual food intake. They consist of pre-specified questions regarding the habitual frequency of consuming common food products over a specified time period in the past, usually a month. Questions on the frequency of consumption of an item are sometimes supplemented with a question on portion size. Although such questionnaires only provide a rough estimate of dietary intake, they can easily be self-administered and processing can be automated, what makes it an inexpensive and efficient dietary assessment method that is preferred in large-scale observational studies 17.
A second challenge in the assessment of diet quality is the choice for a scoring method. Many diet quality scores have been described in the literature, of which
the Healthy Eating Index (HEI) 18, Dietary Approach to Stop Hypertension (DASH)
19 and Mediterranean Diet Score (MDS) 9 are among those most frequently used.
While all indices score the intake of nutrients, food products and/or food groups, differences exist in their composition. The difference in rationale behind the scores can explain some of the differences in their components. For the HEI, the selection of components was based on the Dietary Guidelines for Americans. The latest update of the HEI, reflecting the guidelines for 2015-2020, therefore scores the intake of fatty acids, added sugars and sodium, in addition to major food groups. The DASH score is based on adherence to the DASH eating plan, an appendix of the Dietary Guidelines for Americans specifically designed to target hypertension, and has many of the same characteristics as the healthy American eating pattern reflected by the HEI 20.
The MDS aimed to reflect adherence to the traditional Mediterranean diet, as local dietary habits were expected to contribute to the regional general health that was beyond expectations. In addition to major food groups, the traditional score rewards higher intake of monounsaturated fatty acids and moderate alcohol consumption. A difference between the traditional MDS and HEI is that the MDS rewards low intake of dairy, while the HEI supports high intake. In addition, the MDS did not score added sugars or sugar-sweetened beverages, of which detrimental effects on obesity and diabetes risk are now well established 21,22. Although studies found associations with
14
various health outcomes for all previously mentioned diet scores 23,24, advances in the
field of nutrition ask for updated scientific tools to assess diet quality. It is therefore that a fully food-based diet quality score, in line with the latest scientific evidence on diet-disease relationships, is needed.
DIET AND HEALTH OVER THE LIFE COURSE
Diet quality and healthy ageing
A healthy diet is important over the whole life course, although it can serve different purposes in different phases of life. In childhood, a healthy diet is essential for growth
and development 25, whereas its importance in the prevention of non-communicable
diseases becomes more pronounced in adulthood 24. Finally, diet can help prevent
frailty and sarcopenia in elderly 26,27. This thesis will mainly focus on the association
of diet with non-communicable diseases and their risk factors in the cardiometabolic domain. Cardiometabolic health covers a broad spectrum of risk factors, such as overweight, insulin resistance, dyslipidemia and hypertension, as well as
non-communicable diseases such as Type 2 Diabetes and cardiovascular diseases 28.
Already in childhood, overweight is a risk factor that can influence cardiometabolic health and disease in later life. Not only can childhood overweight track into
adulthood 29, overweight that was already established during childhood was found
to have a stronger association with Type 2 Diabetes than overweight established in adulthood 30. Type 2 Diabetes, on its turn, is associated with an approximately
twofold-increased risk for cardiovascular diseases 31. In late adulthood, the accumulation
of cardiometabolic risk factors and diseases eventually affects risk of death. When considering diabetes, myocardial infarction and stroke, a history of any combination of two of these conditions is associated with a 12 year lower life expectancy at age 60 32.
Although changes in cardiometabolic health are to some extent inevitably linked to the process of ageing, modifiable lifestyle factors like diet quality can influence how health and disease progress over the life course. With regard to risk factors for cardiometabolic disease, an umbrella review of meta-analyses of randomized controlled trials (RCTs) confirmed that there is consistent evidence for a beneficial effect of adherence to a Mediterranean diet on body weight, BMI, waist circumference, total cholesterol, glucose and C-reactive protein 33. Similarly, an umbrella review
focused on the DASH dietary pattern and cardiometabolic outcomes reported that meta-analyses of RCTs confirmed beneficial effects of the DASH diet on systolic and diastolic blood pressure, total and LDL cholesterol, HbA1c, fasting insulin and
135558_Petra_Vinke_BNW-def.indd 14
1
body weight 34. For more advanced cardiometabolic endpoints, higher scores
on various dietary indices including the (Alternative) Healthy Eating Index, DASH diet and Mediterranean diet, were associated with a lower incidence of Type 2 Diabetes in meta-analyses of prospective observational studies 35. Similar beneficial
associations have, among others, been found for the Healthy Eating Index vs. obesity risk 36 and diabetes, cardiovascular diseases and all-cause mortality 24, DASH diet vs.
cardiovascular disease and diabetes 34 and Mediterranean diet vs. all-cause mortality,
cardiovascular diseases and diabetes 33. Furthermore, adherence to a healthy diet
does not only have the potential to extend life expectancy, but also to extend life expectancy free of major chronic diseases like cancer, cardiovascular diseases and Type 2 Diabetes by approximately 3.5 years 37.
From a biological perspective, there are multiple mechanisms through which diet quality can influence cardiometabolic health. An important and frequently studied intermediate risk factor in the association of diet and cardiometabolic health is body weight. A poor quality diet is often higher in energy as well, potentially resulting in energy imbalance and, subsequently, weight gain. However, many of the reported associations of diet quality with anthropometric outcomes included in a meta-analysis of prospective studies were adjusted for energy intake, and outcomes
were not markedly different from outcomes unadjusted for energy intake36. This
illustrates that aspects of diet quality beyond energy intake may independently influence body weight. Such aspects may include a higher density of bio-active components, fiber and micronutrients, or synergy between the foods consumed, which might in turn influence endocrine and inflammatory processes. Besides body weight, other intermediate risk factors play a role in the association of diet quality and cardiometabolic health. This is also confirmed by previous mediation studies that only reported partial mediation by BMI for several diet-disease relationships 38–41.
Furthermore, a prospective cohort study of initially healthy women of the Women’s Health Study showed that inflammation biomarkers (29.2%), biomarkers of glucose metabolism and insulin resistance (27.9%), BMI (27.3%), blood pressure (26.6%) and traditional lipids including LDL, HDL cholesterol and triglycerides (26.0%) explain approximately similar proportions of the lower risk of cardiovascular disease events associated with higher Mediterranean Diet adherence 41. This emphasizes that diet
quality, beyond quantity, can exert its influence on cardiometabolic health through various risk factors for disease.
16
The role of life course factors in diet and health
During life, several factors can influence diet and/or health, what makes that the association of diet quality and healthy ageing is dynamic over the life course. Some factors that are involved in the life course, such as sex, are determined at birth. Other contextual factors, like socio-economic status, are not necessarily constant, but still exert influence throughout life. Furthermore, life events, e.g. acquiring a chronic disease, will only play a role from a specific moment in time onwards. A schematic overview of the association of life course factors with diet quality and healthy ageing over the life course is presented in Figure 1.
Here, socio-economic status will serve as a first example to explain the rationale behind this figure. Previous research has shown that a gradient in diet quality exists over levels of socio-economic status, with lower quality diets being present in lower socio-economic classes 42. The generally higher cost of a healthful, nutrient dense diet 43 as well as differences in nutrition knowledge and beliefs 44–46 have been identified as
contributors to this economic gradient in diet quality. This influence of socio-economic status on diet quality is reflected in Figure 1 by arrow 2. At the same time, it has long been known that socio-economic inequalities in cardiometabolic health exist 47. Although this disparity may be mediated by differences in lifestyle factors like
diet quality (arrow 2 + 3), socioeconomic differences in exposure to stressful events and the resulting stress reaction (e.g. due to discrimination, financial concerns or poor living conditions) may also contribute to socioeconomic disparities in health
47,48. Socio-economic status may therefore also influence healthy ageing through
mechanisms other than diet quality (arrow 1).
For other life course factors, similar associations exist. Evidently, cardiometabolic health problems are associated with ageing. For example, the accumulation of atherosclerosis over the life course can ultimately result in a cardiovascular event
49. In addition to higher prevalence in older age, gender differences also exist in
the prevalence of cardometabolic diseases, for which men generally have a higher risk. For example, Type 2 Diabetes risk is higher in men, which is possibly related to differences in the distribution of adipose tissue between men and women. The capacity to store fat subcutaneously is lower in men, what makes that fat is more rapidly stored as ectopic fat in, among others, intra-abdominal, peri-vascular, liver or even pancreatic cells. A rise in ectopic fat, often accompanied by a rise in waist circumference, has more influence on insulin resistance than subcutaneous
135558_Petra_Vinke_BNW-def.indd 16
1
fat. Therefore, men can develop diabetes at a lower average BMI than women, which contributes to their higher risk 50. While these are examples of physiological
mechanisms through which age and gender can influence healthy ageing (arrow 1), both factors are also known to be associated with diet quality. Higher quality dietary patterns were found among women and older adults 51,52. This means that the
association of age and gender with healthy ageing, may in part rely on differences in diet quality as well (arrow 2 + 3).
Figure 1. Simplistic model of how life course factors and diet quality can influence healthy ageing.
Over the life course (blue bar), different health outcomes can serve as a read-out of healthy ageing (yellow bar). These health outcomes can be influenced by life course factors like age, gender, so-cio-economic status or health status, either independent from diet quality (arrow 1) or indirectly, via their influence on diet quality (arrow 2 + 3). Unclear is whether these life course factors also influence the way in which diet affects the process of healthy ageing over the life course.
The possibility of differential effects of diet over the life course
We have already seen that life course factors can influence both diet and health, either directly or via each other. However, we have limited information on whether the association between diet and healthy ageing is constant over the life course and upon exposure to life course factors (Figure 1: question mark arrow). Will the adherence to a high quality diet elicit a similar health benefit for everyone?
It can easily be understood that differences in cardiometabolic health among subgroups of the population can be due to uneven distributions of risk factors. A previously mentioned example of this is that a poor quality diet is more common
18
among groups with a lower socio-economic status, which can therefore contribute to a higher prevalence of chronic diseases in these groups. A term to describe this mechanism, proposed by Diderichsen et al. is differential exposure 53. The majority
of studies investigating the associations of risk factors with health outcomes across strata of a given contextual variable focus on this differential exposure. The possibility that the effect of a risk factor differs across groups, the concept of differential effect
53, is less often studied, yet not less important. Within the same example, this
would mean that a poor diet quality is more, or less, likely to cause health issues in individuals with a lower economic status than in individuals with higher socio-economic status. In other words, the vulnerability to the risk factor in question differs across strata of socio-economic status. Whether such a differential effect of diet quality on healthy ageing exists for strata of the life course factors mentioned before, is currently unclear.
Differential effects of diet quality across life course factors could have major implications for epidemiological research and subsequent public health policies. In case of differential effects, scientific studies could lead to overall conclusions that are not true for subgroups of the study population, since the overall estimates represent an average of associations in subgroups. It is therefore of major importance to investigate how the association of diet quality and healthy ageing is influenced by life course factors, as this will help to tailor public health strategies to subgroups of the population.
OUTLINE OF THIS THESIS
Aim of this thesis
The aim of this thesis is twofold. First, this thesis aims to establish how diet quality can be measured. The second aim is to investigate the association of diet quality and health outcomes in the cardiometabolic domain over the life course, and across subgroups of the population.
General design
The studies included in this thesis were performed in the population-based Lifelines Cohort, and the GECKO Drenthe birth cohort. The Lifelines Cohort study is a multi-disciplinary prospective population-based cohort study examining in a unique three-generation design, the health and health-related behaviors of 167.729 persons living in the North of the Netherlands. All participants were included in the study between
135558_Petra_Vinke_BNW-def.indd 18
1
2006 and 2013. So far, three follow-up assessments have taken place, covering a great variety of self-reported questionnaires and physical examinations 54. Baseline food
frequency questionnaire data is available for approximately 129.000 adult participants. This data is used for chapter 2, and chapters 5 to 8 (see Figure 2). The GECKO Drenthe birth cohort is a population-based cohort including children born in 2006 and 2007,
designed to study the determinants and development of childhood overweight 55.
Children are followed by routine anthropometric check-ups at Community Health Services and self-reported questionnaires. For approximately 1000 children, data from food pattern and food frequency questionnaires is available at age three and five. The data from this cohort is used for chapters 3 and 4 (see Figure 2).
20
THESIS OUTLINE
PART 1:
Measuring diet quality
Chapter 2 describes the development of the food-based Lifelines Diet Score, which was based on the scientific evidence underlying the 2015 Dutch Dietary Guidelines. The chapter provides descriptives of its application in adults of the Lifelines cohort. In the other studies included in this thesis, the Lifelines Diet Score is used to express diet quality.
PART 2:
Diet quality and body weight over the life course
Chapter 3 describes the association of diet quality in early childhood (age three), with changes in BMI and overweight incidence in the following seven years. This study was performed in the GECKO Drenthe birth cohort.
Chapter 4 builds on Chapter 3, but additionally investigates the role of sugar-sweetened beverages and their timing of consumption during the day, in BMI changes in early childhood (age five to ten).
Chapter 5 describes the sex- and age-specific association of diet quality and 4-year weight change in adults of the Lifelines Cohort, aged between 18 and 93 years at baseline.
PART 3:
Diet quality and cardiometabolic endpoints in adulthood
Chapter 6 describes the socio-economic disparities in the association of diet quality and Type 2 Diabetes incidence in adults of the Lifelines Cohort.
Chapter 7 builds on Chapter 6, but further investigates the role of ultra-processed foods in the development of Type 2 Diabetes in adults of the Lifelines Cohort. Chapter 8 describes the association of diet quality and all-cause mortality across levels of cardiometabolic health in a 7.6-year prospective analysis including adults of the Lifelines Cohort.
135558_Petra_Vinke_BNW-def.indd 20
1
REFERENCES
1. WHO. Noncommunicable diseases, accessed 2019, available from: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases.
2. Habib SH, Saha S. Burden of non-communicable disease: Global overview. Diabetes Metab Syndr
Clin Res Rev 2010; 4: 41–47.
3. Stanaway JD, Afshin A, Gakidou E, et al. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018; 392: 1923–1994.
4. Afshin A, Sur PJ, Fay KA, et al. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2019; 393: 1958–1972. 5. Funk C. The etiology of the deficiency diseases. J State Med 1912; 20: 341–68.
6. Mozaffarian D, Rosenberg I, Uauy R. History of modern nutrition science—implications for current research, dietary guidelines, and food policy. BMJ 2018; k2392.
7. Rosenfeld L. Vitamine-vitamin. The early years of discovery. Clin Chem 1997; 43: 680–685. 8. U.S. Department of Health and Human Services and U.S. Department of Agriculture. Nutrition
and Your Health: Dietary Guidelines for Americans. 1980.
9. Trichopoulou A, Kouris-Blazos A, Wahlqvist ML, et al. Diet and overall survival in elderly people.
BMJ 1995; 311: 1457–1460.
10. Trichopoulou A, Lagiou P, Trichopoulos D. Traditional Greek diet and coronary heart disease. J
Cardiovasc Risk 1994; 9–15.
11. Keys AB, Keys M. How to Eat Well and Stay Well the Mediterranean Way. Slow Food Editore. 1975. 12. Jacobs DR, Tapsell LC. Food synergy: the key to a healthy diet. Proc Nutr Soc 2013; 72: 200–206. 13. Mozaffarian D, Ludwig DS. Dietary guidelines in the 21st century--a time for food. JAMA 2010; 304:
681–682.
14. Preparation and use of food-based dietary guidelines / report of a joint FAO/WHO consultation. Nicosia, Cyprus, 1998.
15. Food and Agriculture Organization of the United Nations. Background | Food-based dietary guidelines, accessed 2019, available from: http://www.fao.org/nutrition/education/food-dietary-guidelines/background/en/.
16. Kromhout D, Spaaij CJK, de Goede J, et al. The 2015 Dutch food-based dietary guidelines. Eur J
Clin Nutr 2016; 70: 869–78.
17. Willett W. Food Frequency Methods. In: Nutritional Epidemiology. Oxford University Press. 2012. 18. Kennedy ET, Ohls J, Carlson S, et al. The Healthy Eating Index: Design and applications. J Am Diet
Assoc 1995; 95: 1103–1108.
19. Dixon LB, Subar AF, Peters U, et al. Adherence to the USDA Food Guide, DASH Eating Plan, and Mediterranean Dietary Pattern Reduces Risk of Colorectal Adenoma. J Nutr 2007; 137: 2443–2450. 20. U.S. Department of Health and Human Services and U.S. Department of Agriculture. 2015-2020
22
21. Malik VS, Pan A, Willett WC, et al. Sugar-sweetened beverages and weight gain in children and adults : a systematic review and meta-analysis. Am J Clin Nutr 2013; 98: 1084–102.
22. Greenwood DC, Threapleton DE, Evans CEL, et al. Association between sugar-sweetened and artificially sweetened soft drinks and type 2 diabetes: systematic review and dose–response meta-analysis of prospective studies. Br J Nutr 2014; 112: 725–734.
23. Sofi F, Cesari F, Abbate R, et al. Adherence to Mediterranean diet and health status: Meta-analysis.
BMJ 2008; 337: 673–675.
24. Schwingshackl L, Bogensberger B, Hoffmann G. Diet Quality as Assessed by the Healthy Eating Index, Alternate Healthy Eating Index, Dietary Approaches to Stop Hypertension Score, and Health Outcomes: An Updated Systematic Review and Meta-Analysis of Cohort Studies. J Acad
Nutr Diet 2018; 118: 74-100.e11.
25. Smithers LG, Golley RK, Brazionis L, et al. Characterizing whole diets of young children from developed countries and the association between diet and health: A systematic review. Nutr Rev 2011; 69: 449–467.
26. Cruz-Jentoft AJ, Kiesswetter E, Drey M, et al. Nutrition, frailty, and sarcopenia. Aging Clin Exp Res 2017; 29: 43–48.
27. Lorenzo-López L, Maseda A, De Labra C, et al. Nutritional determinants of frailty in older adults: A systematic review. BMC Geriatr 2017; 17: 1–13.
28. Guo F, Moellering DR, Garvey WT. The Progression of Cardiometabolic Disease: Validation of a New Cardiometabolic Disease Staging System Applicable to Obesity. Obesity 2014; 22: 110–118. 29. Singh AS, Mulder C, Twisk JWR, et al. Tracking of childhood overweight into adulthood: A
systematic review of the literature. Obes Rev 2008; 9: 474–488.
30. Park MH, Sovio U, Viner RM, et al. Overweight in Childhood, Adolescence and Adulthood and Cardiovascular Risk in Later Life: Pooled Analysis of Three British Birth Cohorts. PLoS One 2013; 8: 3–8.
31. Saeed A, Ballantyne CM. Assessing Cardiovascular Risk and Testing in Type 2 Diabetes. Curr
Cardiol Rep 2017; 19: 19.
32. Di Angelantonio E, Kaptoge S, Wormser D, et al. Association of Cardiometabolic Multimorbidity With Mortality. JAMA 2015; 314: 52–60.
33. Dinu M, Pagliai G, Casini A, et al. Mediterranean diet and multiple health outcomes: An umbrella review of meta-analyses of observational studies and randomised trials. Eur J Clin Nutr 2018; 72: 30–43.
34. Chiavaroli L, Viguiliouk E, Nishi SK, et al. DASH dietary pattern and cardiometabolic outcomes: An umbrella review of systematic reviews and meta-analyses. Nutrients 2019; 11: 338.
35. Neuenschwander M, Ballon A, Weber KS, et al. Role of diet in type 2 diabetes incidence: umbrella review of meta-analyses of prospective observational studies. BMJ 2019; 3: I2368.
36. Asghari G, Mirmiran P, Yuzbashian E, et al. A systematic review of diet quality indices in relation to obesity. Br J Nutr 2017; 117: 1055–1065.
37. Li Y, Schoufour J, Wang DD, et al. Healthy lifestyle and life expectancy free of cancer, cardiovascular disease, and type 2 diabetes: prospective cohort study. BMJ 2020; 368: l6669.
135558_Petra_Vinke_BNW-def.indd 22
1
38. Laouali N, Mancini FR, Hajji-Louati M, et al. Dietary inflammatory index and type 2 diabetes risk in a prospective cohort of 70,991 women followed for 20 years: the mediating role of BMI.
Diabetologia 2019; 62: 2222–2232.
39. Park Y-M, Zhang J, Steck SE, et al. Obesity Mediates the Association between Mediterranean Diet Consumption and Insulin Resistance and Inflammation in US Adults. J Nutr 2017; 147: 563–571. 40. Tobias DK, Hu FB, Chavarro J, et al. Healthful dietary patterns and type 2 diabetes mellitus risk
among women with a history of gestational diabetes mellitus. Arch Intern Med 2012; 172: 1566– 1572.
41. Ahmad S, Moorthy MV, Demler O V., et al. Assessment of Risk Factors and Biomarkers Associated With Risk of Cardiovascular Disease Among Women Consuming a Mediterranean Diet. JAMA
Netw Open 2018; 1: e185708.
42. Darmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr 2008; 87: 1107–17. 43. Monsivais P, Aggarwal A, Drewnowski A. Are socio-economic disparities in diet quality explained
by diet cost? J Epidemiol Community Health 2012; 66: 530–535.
44. McLeod ER, Campbell KJ, Hesketh KD. Nutrition Knowledge: A Mediator between Socioeconomic Position and Diet Quality in Australian First-Time Mothers. J Am Diet Assoc 2011; 111: 696–704. 45. McKinnon L, Giskes K, Turrell G. The contribution of three components of nutrition knowledge to
socio-economic differences in food purchasing choices. Public Health Nutr 2014; 17: 1814–1824. 46. Beydoun MA, Wang Y. Do nutrition knowledge and beliefs modify the association of
socio-economic factors and diet quality among US adults? Prev Med 2008; 46: 145–153.
47. Adler NE, Newman K. Socioeconomic disparities in health: Pathways and Policies. Health Aff 2002; 21: 60–76.
48. Lantz P, House J, Mero R, et al. Stress, Life Events and Socioeconomic Disparities in Health. J
Health Soc Behav 2005; 46: 274–288.
49. Hardy R, Lawlor DA, Kuh D. A life course approach to cardiovascular aging. Future Cardiol 2015; 11: 101–113.
50. Sattar N. Gender aspects in type 2 diabetes mellitus and cardiometabolic risk. Best Pract Res Clin
Endocrinol Metab 2013; 27: 501–507.
51. Hiza HAB, Casavale KO, Guenther PM, et al. Diet Quality of Americans Differs by Age, Sex, Race/ Ethnicity, Income, and Education Level. J Acad Nutr Diet 2013; 113: 297–306.
52. Guenther PM, Kirkpatrick SI, Reedy J, et al. The Healthy Eating Index-2010 Is a Valid and Reliable Measure of Diet Quality According to the 2010 Dietary Guidelines for Americans. J Nutr 2014; 144: 399–407.
53. Diderichsen F, Hallqvist J, Whitehead M. Differential vulnerability and susceptibility: How to make use of recent development in our understanding of mediation and interaction to tackle health inequalities. Int J Epidemiol 2018; 48: 268–274.
54. Scholtens S, Smidt N, Swertz MA, et al. Cohort Profile: LifeLines, a three-generation cohort study and biobank. Int J Epidemiol 2015; 44: 1172–1180.
55. L’Abée C, Sauer PJJ, Damen M, et al. Cohort Profile: The GECKO Drenthe study, overweight programming during early childhood. Int J Epidemiol 2008; 37: 486–489.
