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Nutrition and healthy ageing: the key ingredients

Published online by Cambridge University Press:  06 February 2014

Jessica C. Kiefte-de Jong*
Affiliation:
Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
John C. Mathers
Affiliation:
Human Nutrition Research Centre, Centre for Brain Ageing and Vitality, Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, UK
Oscar H. Franco
Affiliation:
Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
*
* Corresponding author: J. C. Kiefte-de Jong, fax +31 10 7044657, email j.c.kiefte-dejong@erasmusmc.nl
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Abstract

Healthy longevity is a tangible possibility for many individuals and populations, with nutritional and other lifestyle factors playing a key role in modulating the likelihood of healthy ageing. Nevertheless, studies of effects of nutrients or single foods on ageing often show inconsistent results and ignore the overall framework of dietary habits. Therefore, the use of dietary patterns (e.g. a Mediterranean dietary pattern) and the specific dietary recommendations (e.g. dietary approaches to stop hypertension, Polymeal and the American Healthy Eating Index) are becoming more widespread in promoting lifelong health. A posteriori defined dietary patterns are described frequently in relation to age-related diseases but their generalisability is often a challenge since these are developed specifically for the population under study. Conversely, the dietary guidelines are often developed based on prevention of disease or nutrient deficiency, but often less attention is paid to how well these dietary guidelines promote health outcomes. In the present paper, we provide an overview of the state of the art of dietary patterns and dietary recommendations in relation to life expectancy and the risk of age-related disorders (with emphasis on cardiometabolic diseases and cognitive outcomes). According to both a posteriori and a priori dietary patterns, some key ‘ingredients’ can be identified that are associated consistently with longevity and better cardiometabolic and cognitive health. These include high intake of fruit, vegetables, fish, (whole) grains and legumes/pulses and potatoes, whereas dietary patterns rich in red meat and sugar-rich foods have been associated with an increased risk of mortality and cardiometabolic outcomes.

Type
Conference on ‘Nutrition and healthy ageing’
Copyright
Copyright © The Authors 2014 

Abbreviations:
DASH

dietary approaches to stop hypertension

HDI

healthy diet indicator

HEI

healthy eating index

MD

Mediterranean diet

PNNSG

Programme National Nutrition Santé Guideline Score

Nutrition and healthy ageing: a matter of reciprocity?

Those over age 65 years constitute the fastest growing segment of populations worldwide. This change in the world's age distribution and consequent demographic shift can be attributed to a large extent to reduced birth rate, greater economic development, more effective medical interventions (hence reductions in mortality), and to improvements in hygiene, nutrition, lifestyle and in general preventive care( Reference Salomon, Wang and Freeman 1 ).

Ageing is often defined as a continuous process that includes loss of functional capability and the increase in risk of morbidity and mortality( Reference Franco, Karnik and Osborne 2 ). Although ageing is a risk factor for chronic diseases, ageing is not necessarily defined by the presence of morbidities but is a process that starts early in life and which is modulated by the accumulation of experiences and exposures throughout the life-course( Reference Franco, Karnik and Osborne 2 ). As suggested earlier, a ‘healthy ageing phenotype’ can be defined as ‘the condition of being alive, while having highly preserved functioning metabolic, hormonal and neuro-endocrine control systems at the organ, tissue and molecular levels‘( Reference Franco, Karnik and Osborne 2 ). This phenotype represents a state of adequate resilience that minimises the risk of major chronic conditions such as CVD and dementia, but also represents the maintenance of cognitive and physical functioning( Reference Franco, Karnik and Osborne 2 ). Although life expectancy has increased in the past decade, following improved care and diagnosis, the years lived with disabilities and diseases are increasing( Reference Salomon, Wang and Freeman 1 ), emphasising that the maintenance of a healthy phenotype in later life has become a major public health challenge. Dietary habits are one of the important modifiable factors that can affect the maintenance of a healthy ageing phenotype( Reference Mathers 3 ). For example, high intake of both n-6 and n-3 PUFA have been found to reduce the risk of CHD( Reference Willett 4 ), whereas trans-fatty acids intake is considered to increase CVD risk( Reference Willett 4 , Reference Aronis, Khan and Mantzoros 5 ).

One for all and all for one

Although nutrition has long been among the main areas of interest for scientists trying to identify the lifestyle factors that exacerbate or reduce the risk of age-related disorders, studies of the specific nutrients, single foods or food groups have multiple challenges( Reference Hu 6 ). A major difficulty in interpreting the outcomes of such studies in relation to health and disease is the high degree of correlation among dietary components. Moreover, the assumption that single foods or nutrients have isolated effects may not be valid when it comes to maintaining a healthy ageing phenotype since this may cover a combination of different pathways. In addition, foods and nutrients interact, or act in synergy, when influencing numerous metabolic processes. As a result, the focus of nutritional research in the last two decades has shifted to the analyses of whole diets or dietary patterns( Reference Hu 6 ). A dietary pattern approach could better capture the totality of diet, and may be a more appropriate approach for investigating diet–disease associations than focusing on single foods or nutrients( Reference Hu 6 Reference Jones-McLean, Shatenstein and Whiting 8 ).

A posteriori approaches to dietary pattern analysis are driven by the dietary data per se of the population under study and patterns are derived on the basis of correlations or clustering of various dietary factors (e.g. using principal component analysis or k-means clustering)( Reference Ocke 9 ). Conversely, in a priori approaches, researchers define scores or indices of the overall dietary quality on the basis of foods or diets associated with health or according to the specific dietary guidelines( Reference Ocke 9 ). While such dietary guidelines can play important roles in health promotion policies and in individual dietary counselling, they are often based on evidence of decreased risk of chronic diseases and/or prevention of nutrient deficiencies( Reference Ocke 9 ) and their utility in promoting healthy ageing is uncertain. In several countries, adherence of these dietary guidelines is monitored regularly through national food surveys, but less is known about how well adherence to these dietary guidelines predicts health and development of age-related diseases. In recent years, several indices have been developed to assess adherence to these specific dietary guidelines in relation to health outcomes( Reference Ocke 9 ). In this review, we describe the existing evidence of several dietary patterns and dietary guidelines in relation to aspects of healthy ageing and we attempt to identify the key characteristics, which they have in common. Emphasis has been placed on life expectancy, cardiometabolic diseases and cognitive outcomes, but not on cancer because of its heterogeneity in the relationship between diet and different cancer sites.

A Posteriori defined regional dietary patterns

A posteriori defined dietary patterns have frequently been used in epidemiological studies. One advantage of this approach is that it is data-driven, and, thus, independent of previous hypotheses and not limited by the current knowledge in nutrition( Reference Ocke 9 ). However, due to the different populations that are studied, the specific dietary patterns that are associated with health outcomes can be cultural-specific( Reference Tucker 10 ) and thus difficult to translate to other settings.

Earlier regional dietary patterns have already been described to explain some of the cross-cultural variation in the prevalence of age-related chronic diseases. For example, the original Eskimo diet and Japanese diet are both characterised by relatively high intakes of fish, which is thought to explain the low rate of CHD in these populations( Reference Kromhout 11 , Reference Feskens and Kromhout 12 ). Later cross-cultural studies, such as the Seven Countries Study initiated in the late 1950s, suggested that fish intake per se may not be that important (fish consumption was not consistently associated with mortality patterns across countries), whereas low intakes of saturated fats may explain reduced mortality risk( Reference Keys, Menotti and Karvonen 13 ). The Mediterranean diet (MD), which can be characterised by high intake of vegetables, fruit, grains, fish and olive oil( Reference Haber 14 ), has received most attention in relation to mortality because of intriguing differences in chronic disease prevalence and mortality statistics in Mediterranean populations relative to other parts of the world( 15 ), and its potential health effects have been acknowledged since Renaissance( Reference Haber 14 ).

More recently, the importance of diet has been further recognised in other parts of the world where populations exhibit greater healthy ageing, i.e. living longer without disabilities and being more physically active even when aged over 90 years. Population groups in Sardinia (Italy), Nicoya Peninsula (Costa Rica), Loma Linda (California) and Okinawa (Japan), have reputedly longer life expectancy and lower rates of age-related diseases (including CVD and dementia) compared with other countries( Reference Buettner 16 ). These areas have been designated as the ‘Blue Zones’ and are part of a large research project to discover lifestyle factors that explain healthy longevity( Reference Buettner 16 ). Despite their different ethnic and socioeconomic backgrounds, those living in these ‘Blue Zones’ share some common lifestyle characteristics including diets rich in plant-based foods (notably vegetables, beans, soyabean and lentils) and low in meat( Reference Buettner 16 ) . These findings are consistent with most of the studies using the a posteriori dietary patterns approach within populations where lower risks of mortality and also of cardiometabolic disease and of poor cognitive outcomes are associated with higher intakes of plant-based foods and relatively low meat consumption( Reference Fung, Schulze and Manson 17 Reference Ozawa, Ninomiya and Ohara 22 ).

Mortality and life expectancy

Several independent studies have shown that a dietary pattern rich in plant-based foods, fish and olive oil, but low in whole-fat dairy products was associated with a lower cardiovascular or all-cause mortality in Italy( Reference Menotti, Alberti-Fidanza and Fidanza 23 ), Spain( Reference Guallar-Castillon, Rodriguez-Artalejo and Tormo 24 , Reference Anderson, Harris and Tylavsky 25 ), UK( Reference Hamer, McNaughton and Bates 26 ), Japan( Reference Maruyama, Iso and Date 27 ) and USA( Reference Heidemann, Schulze and Franco 28 ). Results from the European Prospective Investigation into Cancer and Nutrition suggested that the relationship between a plant-based diet and mortality in those aged 60+ years may be country-specific since there were relatively strong associations in Greece, Spain, Denmark and the Netherlands, but no associations in the UK and Germany( Reference Bamia, Trichopoulos and Ferrari 29 ). The consequences of dietary patterns rich in dairy products for mortality seem to be inconsistent. Studies from Japan and the Netherlands found that a dietary pattern rich in dairy products was associated with decreased risk of mortality( Reference Maruyama, Iso and Date 27 , Reference Waijers, Ocke and van Rossum 30 ), whereas a study in USA found that a pattern characterised by intake of particularly high-fat dairy products was associated with higher all-cause mortality in middle-aged and older people( Reference Anderson, Harris and Tylavsky 25 ). In addition, studies have linked dietary patterns characterised by high intakes of meat and sugar-containing foods to increased risk of overall mortality in several countries including Germany( Reference Meyer, Doring and Herder 31 ), USA( Reference Heidemann, Schulze and Franco 28 ), Canada( Reference Heroux, Janssen and Lam 32 ) and Spain( Reference Anderson, Harris and Tylavsky 25 ). Nevertheless, most of these studies have been conducted in adult populations below age 75 years and evidence of the dietary patterns associated with healthy ageing among those aged >75 years is scarce. To our knowledge, there is only one such study, which found no link between mortality risk and any of three dietary patterns namely those rich in dairy and sweets, a health-conscious pattern, and a Western dietary pattern, which suggests that the effects of dietary patterns may differ between age-groups( Reference Hsiao, Mitchell and Coffman 33 ).

Cardiometabolic disorders

Several dietary patterns have been found to be associated with cardiometabolic disorders. For example, a ‘prudent diet’ characterised by high intake of vegetables, fruit, legumes, whole grains, fish and poultry, has been associated with almost 30% decrease in the risk of CVD among men and women in the USA, Germany, Spain and the Netherlands( Reference Fung, Stampfer and Manson 18 Reference Stricker, Onland-Moret and Boer 21 , Reference Guallar-Castillon, Rodriguez-Artalejo and Tormo 24 , Reference Weikert, Hoffmann and Dierkes 34 ). In contrast, a ‘Western’ dietary pattern characterised by high intake of red meat, processed meat, refined grains and sweets was associated with increased risk of CHD in the USA and Sweden( Reference Fung, Stampfer and Manson 18 Reference Hu, Rimm and Stampfer 20 , Reference Hlebowicz, Persson and Gullberg 35 ), but this relationship was not observed in Spain( Reference Guallar-Castillon, Rodriguez-Artalejo and Tormo 24 ). An Italian study found that a dietary pattern featuring high consumption of bread, cereals (pasta), potatoes, vegetables, fish and oil and low consumption of milk, sugar, fruit and alcoholic beverages was associated with a reduced risk of CHD ( Reference Menotti, Alberti-Fidanza and Fidanza 23 ), whereas in Chinese adults, a pattern characterised by refined cereals, salted vegetables and potatoes was associated with an increased risk of stroke( Reference Li, He and Lai 36 ). In addition, several studies confirmed an association between dietary patterns and the risk of type 2 diabetes mellitus. For example, both a ‘Western’ dietary pattern during both adolescence and adulthood was found to be associated with an increased risk of type 2 diabetes in US middle-aged and older people( Reference Fung, Schulze and Manson 17 , Reference Malik, Fung and van Dam 37 , Reference van Dam, Rimm and Willett 38 ) as well as in Chinese men and women( Reference Odegaard, Koh and Butler 39 ).

Cognitive function and dementia

In contrast to the relative wealth of studies of cardiometabolic outcomes and mortality, less attention has been paid to the relationship between a posteriori defined dietary patterns and cognitive outcomes in middle-aged and older people. The Supplémentation en Vitamines et Minéraux Antioxydant study studied the association between a posteriori dietary patterns in relation to cognitive performance among French participants aged 45 years and older. Adherence to a ‘prudent’ dietary pattern (characterised by high intake of fruit, whole grains, dairy, vegetable fat, nuts and fish) was associated with better global cognitive function and verbal memory whereas no association with cognitive outcomes was found for adherence to a pattern characterised by intake of vegetable fat, meat and poultry( Reference Kesse-Guyot, Andreeva and Jeandel 40 ). Conversely, in a study group of 249 people aged 65–90 years with mild cognitive impairment, there was no association between a ‘prudent’ diet and cognitive function but participants adhering to a dietary pattern characterised by high intake of potatoes, fried foods, confectionery, red meat and sugar-containing beverages, were more likely to have poor executive functioning( Reference Torres, Lautenschlager and Wattanapenpaiboon 41 ). Gu et al. found that a dietary pattern characterised by high intake of nuts, tomatoes, poultry, vegetables, fruit, and a low intake of high-fat dairy, red meat, organ meat and butter was associated with lower risk of dementia( Reference Gu, Nieves and Stern 42 ). Also, in the Hisayama study of Japanese people, adherence to a dietary pattern characterised by a high intake of soyabeans and soyabean products, vegetables and dairy products was associated with a reduced risk of dementia( Reference Ozawa, Ninomiya and Ohara 22 ).

A priori defined dietary patterns: dietary guidelines and dietary scores

A priori defined dietary patterns are generally based on evidence showing that the dietary patterns are important to health. In practical terms, diets are assessed for the presence or absence of a certain amount of foods or nutrients and the resulting score is then operationalised as a dietary index. Generally, three groups of a priori defined dietary patterns can be distinguished: (a) dietary scores based on the national or international dietary guidelines, (b) scores derived from assessment of concordance with nutrients or foods associated with the specific health outcomes and (c) scores based on characteristics of regional diets, e.g. an MD pattern (Table 1)( Reference Ocke 9 ).

Table 1. Examples of a priori developed dietary patterns

HEI, healthy eating index; MD, Mediterranean diet; HDI, healthy diet indicator.

* With emphasis on mortality, cardiometabolic disease and cognitive outcomes.

Mortality and life expectancy

The American Healthy Eating Index (HEI) is a measure of diet quality based on the Dietary Guidelines for Americans. The original HEI was developed in 1995( Reference Kennedy, Ohls and Carlson 43 ) and was revised in 2005( Reference Guenther, Reedy and Krebs-Smith 44 ) to include whole grains, beans and oils (Table 1). Subsequently, in 2010 the HEI-2005 was updated according to the revised Dietary Guidelines for Americans, which resulted in the inclusion of seafood in the current index. In several studies, adherence to the HEI has been associated with lower chronic disease risk( Reference Ye, Scott and Gao 45 Reference Agnoli, Krogh and Grioni 47 ), and whereas adherence to the HEI-1995 was associated with a 30% reduction in mortality risk in males, this relationship was not apparent in females( Reference Kappeler, Eichholzer and Rohrmann 48 ). For those aged 65+ years, a higher HEI-1995 score was associated with lower overall and cardiovascular mortality irrespective of gender( Reference Rathod, Bharadwaj and Badheka 49 ).

The Recommended Food Score developed by Kant et al.( Reference Kant, Schatzkin and Graubard 50 ) is a composite measure based on the sum of the number of foods recommended by the current dietary guidelines (fruit, vegetables, whole grains, low-fat dairy and lean meats and poultry) that were reported to be consumed at least once weekly and higher scores were associated with lower risk of all-cause mortality (28 and 18% lower risk in men and women, respectively)( Reference Kant, Schatzkin and Graubard 50 , Reference Kant, Graubard and Schatzkin 51 ).

Adherence to a modified version of the HEI-1995 for an Australian population (Australian dietary guidelines index)( Reference McNaughton, Ball and Crawford 52 ) was associated with a 21% reduction in all-cause mortality( Reference Russell, Flood and Rochtchina 53 ). The HEI-1995 was further adapted by McCullough et al.( Reference McCullough, Feskanich and Stampfer 54 ) by adding fish/poultry to red meat ratio as a component and excluding milk. Adherence to this alternative HEI was associated with a reduced risk of mortality and of cause-specific mortality (CVD, cancer and inflammatory-related diseases) in the Iowa Women's Health Study( Reference Mursu, Steffen and Meyer 55 ) and in the Whitehall II cohort study( Reference Akbaraly, Sabia and Hagger-Johnson 56 ).

The healthy diet indicator (HDI) was developed according to the dietary recommendations of the WHO and includes components of saturated fat, mono- and disaccharides as well as fruit and vegetables, and pulses, nuts and seeds (Table 1)( 57 ). The main focus of the HDI has been the prevention of chronic diseases (i.e. obesity, diabetes mellitus and CVD), but higher HDI scores have been associated with decreased mortality risk in Finland, the Netherlands and Italy( Reference Huijbregts, Feskens and Rasanen 58 ) but not in older Swedish men( Reference Sjogren, Becker and Warensjo 59 ).

Several indices based on the MD have been developed (Table 1). The original MD score developed by Trichopoulou et al.( Reference Trichopoulou, Kouris-Blazos and Wahlqvist 60 ) was further adapted by including fish as component of the score since this food was consumed widely in the Mediterranean countries( Reference Trichopoulou, Costacou and Bamia 61 ). Even though questions have been raised about the generalisability of MD scores to non-Mediterranean countries, adherence to the original MD score has been associated with survival not only in Greece( Reference Trichopoulou, Costacou and Bamia 61 ) but also in Northern Europe( Reference Osler and Schroll 62 ), Australia( Reference Kouris-Blazos, Gnardellis and Wahlqvist 63 ), Spain( Reference Lasheras, Fernandez and Patterson 64 ) and the USA( Reference Mitrou, Kipnis and Thiebaut 65 , Reference Behrens, Fischer and Kohler 66 ). When adapted for the European Prospective Investigation into Cancer and Nutrition study, which studied the mortality across several European countries (including Denmark, France, Germany, Greece, Italy, the Netherlands, Spain, Sweden and UK), higher scores in this MD were associated with an overall 8% reduction in mortality risk per 2 point change in score (10 point scale). There was no evidence of statistically significant heterogeneity among countries although the association was less evident in the Netherlands and Germany( Reference Trichopoulou, Orfanos and Norat 67 ).

Cardiometabolic disease

The dietary approaches to stop hypertension (DASH) diet (rich in fruits, vegetables, low-fat dairy products, grains, poultry, fish and nuts, and low in saturated fat, red meat, sweets and sugar-containing beverages) was originally designed to decrease hypertension( Reference Appel, Moore and Obarzanek 68 ). Later it was shown that adherence to the DASH dietary pattern may also be successful in decreasing the risk of CVD, CHD, stroke and heart failure in several studies among middle-aged and older people( Reference Salehi-Abargouei, Maghsoudi and Shirani 69 ).

Earlier studies using the HEI-1995 found that a high score was associated with moderately reduced risk of CVD in men but not in women( Reference McCullough, Feskanich and Rimm 70 , Reference McCullough, Feskanich and Stampfer 71 ). Also, adherence to HEI-2005, DASH and the Greek and Italian Mediterranean Index was linked with a lower risk of stroke in an Italian population aged 35–74 years( Reference Agnoli, Krogh and Grioni 47 ). Even in secondary prevention cohorts, there were protective relations between adherence to the alternative HEI and secondary CVD events( Reference Dehghan, Mente and Teo 72 ). Adherence to the HEI-2005, the alternative HEI, the Recommended Food score, the alternative MD score, and the DASH diet has been associated with lower risk of type 2 diabetes mellitus in both men and women( Reference de Koning, Chiuve and Fung 73 ).

The ‘Polymeal’, a collection of food ingredients, was developed as a natural alternative to the ‘Polypill’, a multi-pharmaceutical approach intended to reduce CVD risk( Reference Wald and Law 74 ). Components of the ‘Polymeal’ include wine, fish, dark chocolate, fruit and vegetables, almonds and garlic( Reference Franco, Bonneux and de Laet 75 ). Using life tables based on information from the Framingham Heart Study, it was estimated that the combined effects of these dietary components might increase life expectancy free from CVD by 9 years for men and 8 years for women among populations over age 50 years( Reference Franco, Bonneux and de Laet 75 ). However, this theoretical concept has yet to be tested in population and intervention studies.

Cognitive function and dementia

Adherence to some a priori defined dietary patterns has been linked with prevention of some adverse cognitive outcomes. The MD score, the French National Nutrition and Health Programme (Programme National Nutrition Santé) Guideline Score (PNNSG), the Recommended Food Score and the DASH diet have all been associated with lower risks of cognitive impairment, and dementia or Alzheimer's disease( Reference Alles, Samieri and Feart 76 ). In addition, adherence to the HEI, HDI and to the MD have been associated with better cognitive function in middle-aged and older adults( Reference Ye, Scott and Gao 45 , Reference Huijbregts, Feskens and Rasanen 77 Reference Psaltopoulou, Sergentanis and Panagiotakos 79 ).

From observation to intervention?

Although, several indices of MD patterns as well as adherence to the DASH diet and other healthy diet scores are associated with a lower risk of stroke, CHD and CVD in numerous prospective cohort studies in different populations( Reference Salehi-Abargouei, Maghsoudi and Shirani 69 , Reference Sofi, Cesari and Abbate 80 Reference Martinez-Gonzalez, Garcia-Lopez and Bes-Rastrollo 84 ), residual confounding by other lifestyle and socioeconomic factors remains a major challenge in determining causality. While a trial of the DASH diet has demonstrated that adherence to DASH can reduce numerous cardiovascular risk factors( Reference Chen, Maruthur and Appel 85 ) the causal effects on mortality and on other age-related end points are unknown.

The benefit of adherence to an MD pattern on primary prevention of cardiovascular endpoints was confirmed recently in a randomised controlled trial (PREDIMED) conducted in Spain. In this study, an MD supplemented with either extra-virgin olive oil or nuts reduced the risk of major cardiovascular events by almost 30%( Reference Estruch, Ros and Salas-Salvado 86 ). Also, results from the PREDIMED trial showed that this intervention improved cognition (0·6 points increase in score on the Mini-Mental State Examination and Clock Drawing Tests) in participants aged 75+ years with high vascular risk( Reference Martinez-Lapiscina, Clavero and Toledo 87 ). Although whether the PREDIMED trial is a test of an MD per se or of the effects of supplemental extra-virgin olive oil or nuts can be debated, the study provides strong evidence that greater adherence to this dietary pattern can have substantial beneficial effects on health in the older people and reduces the risk of common age-related diseases( Reference Estruch, Ros and Salas-Salvado 86 , Reference Martinez-Lapiscina, Clavero and Toledo 87 ). However, before such findings can be translated to public health-level interventions regionally or nationally, more evidence is needed about the most effective intervention modalities for achieving the necessary changes in eating behaviour and to sustain those behavioural changes in the long term( Reference Curtis, Adamson and Mathers 88 ). In addition, there is a need for an objective panel of outcome measures, which can be used to ascertain whether the interventions have been successful in enhancing healthy ageing. Recently, a preliminary panel of such measures (based on the healthy ageing phenotype concept( Reference Franco, Karnik and Osborne 2 )) which is designed to assess the efficacy of lifestyle-based interventions in promoting healthy ageing in community settings has been proposed( Reference Lara, Godfrey and Evans 89 ).

Nutrition and healthy ageing: agreement on the key ingredients

Dietary patterns define relevant and modifiable risk factors for deviations from a healthy ageing phenotype. Using both a posteriori and a priori dietary patterns, some key ‘ingredients’ (food groups) can be identified that are associated consistently with longevity and with better cardiometabolic and cognitive health. These include: high intakes of fruits, vegetables, fish, (whole) grains and legumes/pulses and potatoes (Fig. 1).

Fruit, vegetables and (whole) grains are components included in the HEI-2005, HEI-1995, Recommended Food score and the WHO HDI, but are also found in indices of the MD (Table 1). All of these indices and also a posteriori defined dietary patterns that include these food groups have been associated with lower risk of mortality, cardiometabolic disease and adverse cognitive outcomes in middle-aged and older people.

Although fish has been included recently in the HEI-2010, we are not aware that this new index has yet been studied in relation to healthy ageing outcomes. However, fish is a component in most Mediterranean diets and has been included in other indices such the DASH diet, the PNNSG score and the Polymeal as well as in a posteriori defined dietary patterns that have been linked with healthy ageing outcomes.

Finally, legumes/pulses and potatoes are not included in all a priori defined dietary patterns but those, which included one or more of these components (e.g. HEI-2005, PNNSG, HDI and MD scores) have found that they are associated with lower mortality rates and decreased risk of cardiometabolic diseases and of poor cognitive outcomes.

In contrast, dietary patterns rich in red meat and sugar-rich foods have been associated with an increased risk of mortality, type 2 diabetes mellitus and CHD in studies that defined these patterns a posteriori ( Reference Fung, Schulze and Manson 17 Reference Hu, Rimm and Stampfer 20 , Reference Anderson, Harris and Tylavsky 25 , Reference Heidemann, Schulze and Franco 28 , Reference Meyer, Doring and Herder 31 , Reference Heroux, Janssen and Lam 32 , Reference Hlebowicz, Persson and Gullberg 35 , Reference Malik, Fung and van Dam 37 Reference Odegaard, Koh and Butler 39 ). There is a general agreement on the potential deleterious effect of higher intakes of these two food items and most of the dietary guidelines and scores designate these foods as unfavourable components (Table 1). However, not all a priori defined dietary patterns include these components (e.g. they are not included in the Recommended Food Score, the Danish Diet quality Index, the PNNSG score and WHO HDI). It can be argued that these guidelines might be improved (made more sensitive) by adding specific recommendations on the intake of red meat and of sugar-rich foods and that such modified guidelines may be better at identifying those with eating behaviours more likely to lead to a healthy ageing phenotype.

Fig. 1. (colour online) Nutrition and healthy ageing: the key ingredients.

Other food groups/items are the subject of controversy. For example, the role of dairy products in healthy ageing remains unclear. Although, some a priori dietary patterns (e.g. HEI-1995, -2005, -2010, Recommended Food Score, PNNSG and DASH) have included dairy foods as a beneficial component, none of the MD scores includes dairy products as a beneficial component. In addition, a posteriori derived dietary patterns do not show consistent relationships between patterns rich in dairy and beneficial health outcomes( Reference Anderson, Harris and Tylavsky 25 , Reference Maruyama, Iso and Date 27 , Reference Waijers, Ocke and van Rossum 30 , Reference Granic, Andel and Dahl 90 ).

It could be argued that the relationship between dairy-rich dietary patterns and health outcomes are culturally specific and are influenced by the habitual dairy consumption of the population under study and the type of dairy products consumed. For example, the Netherlands and USA are countries with the highest milk consumption worldwide( 91 ), but increased mortality risk was associated with dietary patterns characterised particularly by fat-rich dairy products( Reference Anderson, Harris and Tylavsky 25 ). Future studies in this field need to address the effects of dairy-rich dietary patterns on health outcomes in specific subpopulations.

The totality of available evidence suggests that dietary patterns rich in fruit, vegetables, fish, whole grains and starchy low-fat staple foods are likely to play a key role in promoting aspects of healthy ageing including life expectancy and lower risk of cardiometabolic diseases and adverse cognitive outcomes. However, the current evidence is derived mainly from observational studies and more evidence from intervention studies on the effect of whole diets and on how to achieve the necessary sustained dietary behaviour changes is needed to support the development of soundly based public health interventions to promote healthy ageing at the population level. Furthermore, although regional diets such as the MD may be beneficial in other geographical locations, interventions promoting their use may be influenced by local availability, population-specific effects and by culture-specific acceptability of particular foods and food groups. A more tailored approach is needed.

Personalised nutrition: the next frontier?

Most of the current dietary guidelines adopt a ‘one size fits all’ approach and this needs to change since not all individuals within populations will share the same dietary risks and there is considerable heterogeneity in food preferences. Indeed, a more personalised approach to dietary interventions may be both more acceptable and more efficacious.

Future nutritional research should recognise this challenge and aim to disentangle the complex interactions among genotype, diet, lifestyle and environmental factors to understand the basis for varying vulnerabilities and the different responses to dietary patterns( Reference Joost, Gibney and Cashman 92 ). Addressing these interactions may provide the basis for a more personalised approach to nutritional recommendations and to nutritional counselling to improve eating patterns and to promote healthy ageing.

Acknowledgements

None.

Financial Support

No specific funding was received for this article. J. C. K. and O. H. F. work in ErasmusAge, a centre for ageing research across the life course that receives funding from Nestlé Nutrition (Nestec Ltd.), Metagenics Inc. and AXA Research Fund. None of these funding sources had any role in the design and conduct of the study, and preparation, review or approval of the manuscript. The other author reports no specific funding source.

Conflicts of Interest

Oscar H. Franco has received a grant from Nestlé Nutrition (Nestec Ltd.), Metagenics Inc. and AXA to establish a centre on ageing research. These funding sources had no role in design and conduct of this manuscript; collection, management, analysis and interpretation of the data; and preparation, review or approval of this manuscript. The authors declare no conflicts of interest.

Authorship

J. C. K. d. J. and O. H. F. conducted the literature search. J. C. K. d. J. and O. H. F. drafted the manuscript. J. C. M. provided critical comments during writing of the manuscript.

References

1. Salomon, JA, Wang, H, Freeman, MK et al. (2012) Healthy life expectancy for 187 countries, 1990–2010: a systematic analysis for the Global Burden Disease Study. Lancet 380, 21442162.CrossRefGoogle ScholarPubMed
2. Franco, OH, Karnik, K, Osborne, G et al. (2009) Changing course in ageing research: the healthy ageing phenotype. Maturitas 63, 1319.CrossRefGoogle ScholarPubMed
3. Mathers, JC (2013) Nutrition and ageing: knowledge, gaps and research priorities. Proc Nutr Soc 72, 246250.CrossRefGoogle ScholarPubMed
4. Willett, WC (2012) Dietary fats and coronary heart disease. J Intern Med 272, 1324.CrossRefGoogle ScholarPubMed
5. Aronis, KN, Khan, SM & Mantzoros, CS (2012) Effects of trans fatty acids on glucose homeostasis: a meta-analysis of randomized, placebo-controlled clinical trials. Am J Clin Nutr 96, 10931099.CrossRefGoogle ScholarPubMed
6. Hu, FB (2002) Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 13, 39.CrossRefGoogle ScholarPubMed
7. Kant, AK (2010) Dietary patterns: biomarkers and chronic disease risk. Appl Physiol Nutr Metab 35, 199206.CrossRefGoogle ScholarPubMed
8. Jones-McLean, EM, Shatenstein, B & Whiting, SJ (2010) Dietary patterns research and its applications to nutrition policy for the prevention of chronic disease among diverse North American populations. Appl Physiol Nutr Metab 35, 195198.CrossRefGoogle ScholarPubMed
9. Ocke, MC (2013) Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis. Proc Nutr Soc 72, 191199.CrossRefGoogle ScholarPubMed
10. Tucker, KL (2010) Dietary patterns, approaches, and multicultural perspective. Appl Physiol Nutr Metab 35, 211218.CrossRefGoogle ScholarPubMed
11. Kromhout, D (1989) N-3 fatty acids and coronary heart disease: epidemiology from Eskimos to Western populations. J Intern Med Suppl 731, 4751.CrossRefGoogle ScholarPubMed
12. Feskens, EJ & Kromhout, D (1993) Epidemiologic studies on Eskimos and fish intake. Ann N Y Acad Sci 683, 915.CrossRefGoogle ScholarPubMed
13. Keys, A, Menotti, A, Karvonen, MJ et al. (1986) The diet and 15-year death rate in the seven countries study. Am J Epidemiol 124, 903915.CrossRefGoogle ScholarPubMed
14. Haber, B (1997) The Mediterranean diet: a view from history. Am J Clin Nutr 66, 1053S1057S.CrossRefGoogle ScholarPubMed
15. World Health Organization (1993) Health for all – statistical database. WHO, Regional Office for Europe.Google Scholar
16. Buettner, D (2008) The Blue Zone: Lessons for Living Longer From the People Who've Lived the Longest. Washington, DC: National Geographic Society.Google Scholar
17. Fung, TT, Schulze, M, Manson, JE et al. (2004) Dietary patterns, meat intake, and the risk of type 2 diabetes in women. Arch Intern Med 164, 22352240.CrossRefGoogle ScholarPubMed
18. Fung, TT, Stampfer, MJ, Manson, JE et al. (2004) Prospective study of major dietary patterns and stroke risk in women. Stroke 35, 20142019.CrossRefGoogle ScholarPubMed
19. Fung, TT, Willett, WC, Stampfer, MJ et al. (2001) Dietary patterns and the risk of coronary heart disease in women. Arch Intern Med 161, 18571862.CrossRefGoogle ScholarPubMed
20. Hu, FB, Rimm, EB, Stampfer, MJ et al. (2000) Prospective study of major dietary patterns and risk of coronary heart disease in men. Am J Clin Nutr 72, 912921.CrossRefGoogle ScholarPubMed
21. Stricker, MD, Onland-Moret, NC, Boer, JM et al. (2013) Dietary patterns derived from principal component- and k-means cluster analysis: long-term association with coronary heart disease and stroke. Nutr Metab Cardiovasc Dis 23, 250256.CrossRefGoogle ScholarPubMed
22. Ozawa, M, Ninomiya, T, Ohara, T et al. (2013) Dietary patterns and risk of dementia in an elderly Japanese population: the Hisayama Study. Am J Clin Nutr 97, 10761082.CrossRefGoogle Scholar
23. Menotti, A, Alberti-Fidanza, A, Fidanza, F et al. (2012) Factor analysis in the identification of dietary patterns and their predictive role in morbid and fatal events. Public Health Nutr 15, 12321239.CrossRefGoogle ScholarPubMed
24. Guallar-Castillon, P, Rodriguez-Artalejo, F, Tormo, MJ et al. (2012) Major dietary patterns and risk of coronary heart disease in middle-aged persons from a Mediterranean country: the EPIC-Spain cohort study. Nutr Metab Cardiovasc Dis 22, 192199.CrossRefGoogle ScholarPubMed
25. Anderson, AL, Harris, TB, Tylavsky, FA et al. (2011) Dietary patterns and survival of older adults. J Am Diet Assoc 111, 8491.CrossRefGoogle ScholarPubMed
26. Hamer, M, McNaughton, SA, Bates, CJ et al. (2010) Dietary patterns, assessed from a weighed food record, and survival among elderly participants from the United Kingdom. Eur J Clin Nutr 64, 853861.CrossRefGoogle ScholarPubMed
27. Maruyama, K, Iso, H, Date, C et al. (2013) Dietary patterns and risk of cardiovascular deaths among middle-aged Japanese: JACC Study. Nutr Metab Cardiovasc Dis 23, 519527.CrossRefGoogle ScholarPubMed
28. Heidemann, C, Schulze, MB, Franco, OH et al. (2008) Dietary patterns and risk of mortality from cardiovascular disease, cancer, and all causes in a prospective cohort of women. Circulation 118, 230237.CrossRefGoogle Scholar
29. Bamia, C, Trichopoulos, D, Ferrari, P et al. (2007) Dietary patterns and survival of older Europeans: the EPIC-Elderly Study (European Prospective Investigation into Cancer and Nutrition). Public Health Nutr 10, 590598.CrossRefGoogle Scholar
30. Waijers, PM, Ocke, MC, van Rossum, CT et al. (2006) Dietary patterns and survival in older Dutch women. Am J Clin Nutr 83, 11701176.CrossRefGoogle ScholarPubMed
31. Meyer, J, Doring, A, Herder, C et al. (2011) Dietary patterns, subclinical inflammation, incident coronary heart disease and mortality in middle-aged men from the MONICA/KORA Augsburg cohort study. Eur J Clin Nutr 65, 800807.CrossRefGoogle ScholarPubMed
32. Heroux, M, Janssen, I, Lam, M et al. (2010) Dietary patterns and the risk of mortality: impact of cardiorespiratory fitness. Int J Epidemiol 39, 197209.CrossRefGoogle ScholarPubMed
33. Hsiao, PY, Mitchell, DC, Coffman, DL et al. (2013) Dietary patterns and relationship to obesity-related health outcomes and mortality in adults 75 years of age or greater. J Nutr Health Aging 17, 566572.CrossRefGoogle ScholarPubMed
34. Weikert, C, Hoffmann, K, Dierkes, J et al. (2005) A homocysteine metabolism-related dietary pattern and the risk of coronary heart disease in two independent German study populations. J Nutr 135, 19811988.CrossRefGoogle ScholarPubMed
35. Hlebowicz, J, Persson, M, Gullberg, B et al. (2011) Food patterns, inflammation markers and incidence of cardiovascular disease: the Malmo Diet and Cancer study. J Intern Med 270, 365376.CrossRefGoogle Scholar
36. Li, Y, He, Y, Lai, J et al. (2011) Dietary patterns are associated with stroke in Chinese adults. J Nutr 141, 18341839.CrossRefGoogle ScholarPubMed
37. Malik, VS, Fung, TT, van Dam, RM et al. (2012) Dietary patterns during adolescence and risk of type 2 diabetes in middle-aged women. Diabetes Care 35, 1218.CrossRefGoogle ScholarPubMed
38. van Dam, RM, Rimm, EB, Willett, WC et al. (2002) Dietary patterns and risk for type 2 diabetes mellitus in U.S. men. Ann Intern Med 136, 201209.CrossRefGoogle ScholarPubMed
39. Odegaard, AO, Koh, WP, Butler, LM et al. (2011) Dietary patterns and incident type 2 diabetes in Chinese men and women: the Singapore Chinese health study. Diabetes Care 34, 880885.CrossRefGoogle ScholarPubMed
40. Kesse-Guyot, E, Andreeva, VA, Jeandel, C et al. (2012) A healthy dietary pattern at midlife is associated with subsequent cognitive performance. J Nutr 142, 909915.CrossRefGoogle ScholarPubMed
41. Torres, SJ, Lautenschlager, NT, Wattanapenpaiboon, N et al. (2012) Dietary patterns are associated with cognition among older people with mild cognitive impairment. Nutrients 4, 15421551.CrossRefGoogle ScholarPubMed
42. Gu, Y, Nieves, JW, Stern, Y et al. (2010) Food combination and Alzheimer disease risk: a protective diet. Arch Neurol 67, 699706.CrossRefGoogle ScholarPubMed
43. Kennedy, ET, Ohls, J, Carlson, S et al. (1995) The Healthy Eating Index: design and applications. J Am Diet Assoc 95, 11031108.CrossRefGoogle ScholarPubMed
44. Guenther, PM, Reedy, J & Krebs-Smith, SM (2008) Development of the Healthy Eating Index-2005. J Am Diet Assoc 108, 18961901.CrossRefGoogle ScholarPubMed
45. Ye, X, Scott, T, Gao, X et al. (2013) Mediterranean diet, healthy eating index 2005, and cognitive function in middle-aged and older Puerto Rican adults. J Acad Nutr Diet 113, 276281.CrossRefGoogle ScholarPubMed
46. Tobias, DK, Hu, FB, Chavarro, J et al. (2012) Healthful dietary patterns and type 2 diabetes mellitus risk among women with a history of gestational diabetes mellitus. Arch Intern Med 172, 15661572.CrossRefGoogle ScholarPubMed
47. Agnoli, C, Krogh, V, Grioni, S et al. (2011) A priori-defined dietary patterns are associated with reduced risk of stroke in a large Italian cohort. J Nutr 141, 15521558.CrossRefGoogle Scholar
48. Kappeler, R, Eichholzer, M & Rohrmann, S (2013) Meat consumption and diet quality and mortality in NHANES III. Eur J Clin Nutr 67, 598606.CrossRefGoogle ScholarPubMed
49. Rathod, AD, Bharadwaj, AS, Badheka, AO et al. (2012) Healthy Eating Index and mortality in a nationally representative elderly cohort. Arch Intern Med 172, 275277.CrossRefGoogle Scholar
50. Kant, AK, Schatzkin, A, Graubard, BI et al. (2000) A prospective study of diet quality and mortality in women. JAMA 283, 21092115.CrossRefGoogle ScholarPubMed
51. Kant, AK, Graubard, BI & Schatzkin, A (2004) Dietary patterns predict mortality in a national cohort: the National Health Interview Surveys, 1987 and 1992. J Nutr 134, 17931799.CrossRefGoogle Scholar
52. McNaughton, SA, Ball, K, Crawford, D et al. (2008) An index of diet and eating patterns is a valid measure of diet quality in an Australian population. J Nutr 138, 8693.CrossRefGoogle Scholar
53. Russell, J, Flood, V, Rochtchina, E et al. (2012) Adherence to dietary guidelines and 15-year risk of all-cause mortality. Br J Nutr [Epublication ahead of print].Google ScholarPubMed
54. McCullough, ML, Feskanich, D, Stampfer, MJ et al. (2002) Diet quality and major chronic disease risk in men and women: moving toward improved dietary guidance. Am J Clin Nutr 76, 12611271.CrossRefGoogle ScholarPubMed
55. Mursu, J, Steffen, LM, Meyer, KA et al. (2013) Diet quality indexes and mortality in postmenopausal women: the Iowa Women's Health Study. Am J Clin Nutr 89, 444453.CrossRefGoogle Scholar
56. Akbaraly, T, Sabia, S, Hagger-Johnson, G et al. (2013) Does overall diet in midlife predict future aging phenotypes? A cohort study. Am J Med 126, 411419.CrossRefGoogle ScholarPubMed
57. World Health Organisation (1990) Diet, nutrition, and the prevention of chronic diseases. Report of a WHO Study Group. Geneva: World Health Organisation.Google Scholar
58. Huijbregts, P, Feskens, E, Rasanen, L et al. (1997) Dietary pattern and 20 year mortality in elderly men in Finland, Italy, and The Netherlands: longitudinal cohort study. BMJ 315, 1317.CrossRefGoogle ScholarPubMed
59. Sjogren, P, Becker, W, Warensjo, E et al. (2010) Mediterranean and carbohydrate-restricted diets and mortality among elderly men: a cohort study in Sweden. Am J Clin Nutr 92, 967974.CrossRefGoogle ScholarPubMed
60. Trichopoulou, A, Kouris-Blazos, A, Wahlqvist, ML et al. (1995) Diet and overall survival in elderly people. BMJ 311, 14571460.CrossRefGoogle ScholarPubMed
61. Trichopoulou, A, Costacou, T, Bamia, C et al. (2003) Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med 348, 25992608.CrossRefGoogle Scholar
62. Osler, M & Schroll, M (1997) Diet and mortality in a cohort of elderly people in a north European community. Int J Epidemiol 26, 155159.CrossRefGoogle Scholar
63. Kouris-Blazos, A, Gnardellis, C, Wahlqvist, ML et al. (1999) Are the advantages of the Mediterranean diet transferable to other populations? A cohort study in Melbourne, Australia. Br J Nutr 82, 5761.CrossRefGoogle ScholarPubMed
64. Lasheras, C, Fernandez, S & Patterson, AM (2000) Mediterranean diet and age with respect to overall survival in institutionalized, nonsmoking elderly people. Am J Clin Nutr 71, 987992.CrossRefGoogle ScholarPubMed
65. Mitrou, PN, Kipnis, V, Thiebaut, AC et al. (2007) Mediterranean dietary pattern and prediction of all-cause mortality in a US population: results from the NIH-AARP Diet and Health Study. Arch Intern Med 167, 24612468.CrossRefGoogle Scholar
66. Behrens, G, Fischer, B, Kohler, S et al. (2013) Healthy lifestyle behaviors and decreased risk of mortality in a large prospective study of U.S. women and men. Eur J Epidemiol 28, 361372.CrossRefGoogle Scholar
67. Trichopoulou, A, Orfanos, P, Norat, T et al. (2005) Modified Mediterranean diet and survival: EPIC-elderly prospective cohort study. BMJ 330, 991.CrossRefGoogle ScholarPubMed
68. Appel, LJ, Moore, TJ, Obarzanek, E et al. (1997) A clinical trial of the effects of dietary patterns on blood pressure. DASH Collaborative Research Group. N Engl J Med 336, 11171124.CrossRefGoogle ScholarPubMed
69. Salehi-Abargouei, A, Maghsoudi, Z, Shirani, F et al. (2013) Effects of dietary approaches to stop hypertension (DASH)-style diet on fatal or nonfatal cardiovascular diseases – incidence: a systematic review and meta-analysis on observational prospective studies. Nutrition 29, 611618.CrossRefGoogle ScholarPubMed
70. McCullough, ML, Feskanich, D, Rimm, EB et al. (2000) Adherence to the Dietary Guidelines for Americans and risk of major chronic disease in men. Am J Clin Nutr 72, 12231231.CrossRefGoogle ScholarPubMed
71. McCullough, ML, Feskanich, D, Stampfer, MJ et al. (2000) Adherence to the Dietary Guidelines for Americans and risk of major chronic disease in women. Am J Clin Nutr 72, 12141222.CrossRefGoogle ScholarPubMed
72. Dehghan, M, Mente, A, Teo, KK et al. (2012) Relationship between healthy diet and risk of cardiovascular disease among patients on drug therapies for secondary prevention: a prospective cohort study of 31 546 high-risk individuals from 40 countries. Circulation 126, 27052712.CrossRefGoogle ScholarPubMed
73. de Koning, L, Chiuve, SE, Fung, TT et al. (2011) Diet-quality scores and the risk of type 2 diabetes in men. Diabetes Care 34, 11501156.CrossRefGoogle ScholarPubMed
74. Wald, NJ & Law, MR (2003) A strategy to reduce cardiovascular disease by more than 80%. BMJ 326, 1419.CrossRefGoogle ScholarPubMed
75. Franco, OH, Bonneux, L, de Laet, C et al. (2004) The Polymeal: a more natural, safer, and probably tastier (than the Polypill) strategy to reduce cardiovascular disease by more than 75%. BMJ 329, 14471450.CrossRefGoogle Scholar
76. Alles, B, Samieri, C, Feart, C et al. (2012) Dietary patterns: a novel approach to examine the link between nutrition and cognitive function in older individuals. Nutr Res Rev 25, 207222.CrossRefGoogle ScholarPubMed
77. Huijbregts, PP, Feskens, EJ, Rasanen, L et al. (1998) Dietary patterns and cognitive function in elderly men in Finland, Italy and The Netherlands. Eur J Clin Nutr 52, 826831.CrossRefGoogle ScholarPubMed
78. Correa Leite, ML, Nicolosi, A, Cristina, S et al. (2001) Nutrition and cognitive deficit in the elderly: a population study. Eur J Clin Nutr 55, 10531058.CrossRefGoogle ScholarPubMed
79. Psaltopoulou, T, Sergentanis, TN, Panagiotakos, DB et al. (2013) Mediterranean diet and stroke, cognitive impairment, depression: a meta-analysis. Ann Neurol 74, 580591.CrossRefGoogle ScholarPubMed
80. Sofi, F, Cesari, F, Abbate, R et al. (2008) Adherence to Mediterranean diet and health status: meta-analysis. BMJ 337, a1344.CrossRefGoogle ScholarPubMed
81. Fung, TT, Rexrode, KM, Mantzoros, CS et al. (2009) Mediterranean diet and incidence of and mortality from coronary heart disease and stroke in women. Circulation 119, 10931100.CrossRefGoogle ScholarPubMed
82. Misirli, G, Benetou, V, Lagiou, P et al. (2012) Relation of the traditional Mediterranean diet to cerebrovascular disease in a Mediterranean population. Am J Epidemiol 176, 11851192.CrossRefGoogle Scholar
83. Dilis, V, Katsoulis, M, Lagiou, P et al. (2012) Mediterranean diet and CHD: the Greek European Prospective Investigation into Cancer and Nutrition cohort. Br J Nutr 108, 699709.CrossRefGoogle ScholarPubMed
84. Martinez-Gonzalez, MA, Garcia-Lopez, M, Bes-Rastrollo, M et al. (2011) Mediterranean diet and the incidence of cardiovascular disease: a Spanish cohort. Nutr Metab Cardiovasc Dis 21, 237244.Google ScholarPubMed
85. Chen, ST, Maruthur, NM & Appel, LJ (2010) The effect of dietary patterns on estimated coronary heart disease risk: results from the Dietary Approaches to Stop Hypertension (DASH) trial. Circ Cardiovasc Qual Outcomes 3, 484489.CrossRefGoogle ScholarPubMed
86. Estruch, R, Ros, E, Salas-Salvado, J et al. (2013) Primary prevention of cardiovascular disease with a Mediterranean diet. N Engl J Med 368, 12791290.CrossRefGoogle ScholarPubMed
87. Martinez-Lapiscina, EH, Clavero, P, Toledo, E et al. (2013) Mediterranean diet improves cognition: the PREDIMED-NAVARRA randomised trial. J Neurol Neurosurg Psychiatry 84, 13181325.CrossRefGoogle ScholarPubMed
88. Curtis, PJ, Adamson, AJ & Mathers, JC (2012) Effects on nutrient intake of a family-based intervention to promote increased consumption of low-fat starchy foods through education, cooking skills and personalised goal setting: the Family Food and Health Project. Br J Nutr 107, 18331844.CrossRefGoogle ScholarPubMed
89. Lara, J, Godfrey, A, Evans, E et al. (2013) Towards measurement of the Healthy Ageing Phenotype in lifestyle-based intervention studies. Maturitas 67, 189199.CrossRefGoogle Scholar
90. Granic, A, Andel, R, Dahl, AK et al. (2013) Midlife dietary patterns and mortality in the population-based study of Swedish twins. J Epidemiol Commun Health 67, 578586.CrossRefGoogle ScholarPubMed
91. FAO (2011). Milk Consumption – Excluding Butter (Total) (kg/capita/yr), FAO Statistics Division. http://chartsbin.com/view/1492 Google Scholar
92. Joost, HG, Gibney, MJ, Cashman, KD et al. (2007) Personalised nutrition: status and perspectives. Br J Nutr 98, 2631.CrossRefGoogle Scholar
93. Guenther, PM, Casavale, KO, Reedy, J et al. (2013) Update of the Healthy Eating Index: HEI-2010. J Acad Nutr Diet 113, 569580.CrossRefGoogle ScholarPubMed
94. McCullough, ML, Feskanich, D, Stampfer, MJ et al. (2002) Diet quality and major chronic disease risk in men and women: moving toward improved dietary guidance. Am J Clin Nutr 76, 12611271.CrossRefGoogle ScholarPubMed
95. van Lee, L, Geelen, A, van Huysduynen, EJ et al. (2012) The Dutch Healthy Diet index (DHD-index): an instrument to measure adherence to the Dutch Guidelines for a Healthy Diet. Nutr J 20, 1149.Google Scholar
96. Knudsen, VK, Fagt, S, Trolle, E et al. (2012) Evaluation of dietary intake in Danish adults by means of an index based on food-based dietary guidelines. Food Nutr Res 56, 18.CrossRefGoogle ScholarPubMed
97. Estaquio, C, Kesse-Guyot, E, Deschamps, V et al. (2009) Adherence to the French Programme National Nutrition Santé Guideline Score is associated with better nutrient intake and nutritional status. J Am Diet Assoc 109, 10311041.CrossRefGoogle ScholarPubMed
98. Maynard, M, Ness, AR, Abraham, L et al. (2005) Selecting a healthy diet score: lessons from a study of diet and health in early old age (the Boyd Orr cohort). Public Health Nutr 8, 321326.CrossRefGoogle Scholar
99. Fung, TT, McCullough, ML, Newby, PK et al. (2005) Diet-quality scores and plasma concentrations of markers of inflammation and endothelial dysfunction. Am J Clin Nutr 82, 163173.CrossRefGoogle ScholarPubMed
100. Willett, WC, Sacks, F, Trichopoulou, A et al. (1995) Mediterranean diet pyramid: a cultural model for healthy eating. Am J Clin Nutr 61, 1402S1406S.CrossRefGoogle ScholarPubMed
101. Alberti, A, Fruttini, D, Fidanza, F (2009) The Mediterranean Adequacy Index: further confirming results of validity. Nutr Metab Cardiovasc Dis 19, 6166.CrossRefGoogle ScholarPubMed
102. Alberti-Fidanza, A, Fidanza, F (2004) Mediterranean Adequacy Index of Italian diets. Public Health Nutr 7, 937941.CrossRefGoogle ScholarPubMed
103. Lee, S, Harnack, L, Jacobs, DR Jr et al. (2007) Trends in diet quality for coronary heart disease prevention between 1980–1982 and 2000–2002: The Minnesota Heart Survey. J Am Diet Assoc 107, 213222.CrossRefGoogle ScholarPubMed
104. Appel, LJ, Moore, TJ, Obarzanek, E et al. (1997) A clinical trial of the effects of dietary patterns on blood pressure. DASH Collaborative Research Group. N Engl J Med 336, 11171124.CrossRefGoogle ScholarPubMed
105. Fung, TT, Chiuve, SE, McCullough, ML et al. (2008) Adherence to a DASH-style diet and risk of coronary heart disease and stroke in women. Arch Intern Med 168, 713720.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Examples of a priori developed dietary patterns

Figure 1

Fig. 1. (colour online) Nutrition and healthy ageing: the key ingredients.

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