Helfgott Research Institute, National University of Natural Medicine, Portland, Oregon, USA; NIA‐Layton Aging and Alzheimer’s Disease Center, Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
This chapter was originally written by Wija A. van Staveren and Lisette C.P.G.M. de Grooth and has been updated by Gene L. Bowman.
Introduction
The population reaching oldest‐old age (>80 years) is expanding more rapidly than any other segment around the globe, with current estimates predicted at a three‐fold increase from 143 to 426 million by 2050.1 This ‘population ageing’ is partially attributable to the post‐WWII expansion of successful births combined with declining fertility in the modern day. Ageing is associated with a decline in gustatory, olfactory, digestive, and absorptive capacities and the assimilation and delivery of nutrients to target tissues (i.e. the brain, muscle, and bone). These demographic and biological shifts and the lack of a full understanding of the most appropriate diet to promote healthy ageing have led to a variety of potentially modifiable nutrition‐related conditions worldwide. This chapter reviews body weight and composition, hydration, energy intake, and modifiers of food preference and summarizes nutrition literature associated with healthy brain, bone, and muscle ageing from a clinical and public health perspective.
Body weight and composition
The prevalence of obesity (body mass index [BMI] >30 kg−2) increases with age until approximately 60 years of age, remains stable until about 70, and then declines.2,3 Studies indicate that flux in both weight loss and gain in older adults is associated with adverse health outcomes, such as decreased functional status, institutionalization, and increased mortality. Changes in body composition with ageing are also an important consideration. A decline in lean body mass occurs in the third decade of life. This loss in lean body mass, much of which may be due to a more sedentary lifestyle, is offset by gains in fat mass that continue until age 65–70. Older people have a higher proportion of fat to lean body mass than younger adults of similar body weight. It has been estimated that fat‐free mass diminishes by as much as 70% between the ages of 30 and 70. Studies in exceptionally healthy elders indicate that very small weight decreases (e.g. 0.1–0.2 kg per year) are normal with ageing; therefore, weight loss should never be dismissed as part of the ageing process but rather as a shift in the proportion of fat to lean muscle mass.2
Most studies of BMI in ageing have been conducted in the United States (e.g. the Baltimore Longevity Study, the New Mexico Study, and the older age group of NHANES III [National Health and Nutrition Examination Survey]) and in Europe (e.g. SENECA [Survey in Europe on Nutrition and the Elderly – a Concerted Action] and the elderly part of EPIC [European Prospective Investigation into Cancer and Nutrition]). One study including diverse geographic and ethno‐racial groups was the International Union of Nutrition Societies (IUNS) cross‐cultural study ‘Food Habits in Later Life’. This study of elders 70 and older from communities in Australia, Greece, China, Japan, the Philippines, and Sweden showed that on average, BMI for Caucasian men and women is about 25 kg−2, with the highest for Greek women (30 kg−2). Filipino and Chinese had average BMIs between 20 and 22 kg−2. The estimated fat‐mass gender differences were apparent with women averaging 43–50% and men 25–35%, but differences in fat mass between ethno‐racial groups were less striking.
Body mass index, weight loss, and ageing
Many studies have documented that the relative risks for chronic disease related to BMI become less pronounced with ageing. One review examined the effect of an elevated BMI on all‐cause mortality risk in men and women age 65, concluding that overweight (25–29 kg−2) elders do not have an increased risk of mortality. Obesity (BMI ≥30 kg−2) carries only a modest increase in mortality risk regardless of gender, disease status, and smoking status in older adults.4 Several explanations for this phenomenon include selective survival, cohort effects, and/or a ceiling effect of mortality rates. However, another explanation may be the limitation of BMI as an indicator of body composition. The U‐shaped relation between BMI and mortality in younger adults may result from a positive association between body fat mass and mortality and an inverse linear association between fat‐free mass and mortality. As stated above, the ratio between the two compartments (fat and fat‐free mass) changes with ageing. Further, kyphosis in old age makes it difficult to measure height and, therefore, may result in unreliable estimates of BMI. For this reason, changes in weight (rather than changes in BMI) are a preferable measure with consideration of oedema in the overall interpretation.5 As a final reason for the less pronounced relative risk of a high BMI, it is suggested that an excess fat mass is less detrimental in old age. However, recent views on pro‐inflammatory factors related to adiposity indicate that fat loss ameliorates some catabolic conditions of ageing since some cytokines may directly affect muscle protein synthesis and breakdown. A voluntary decrease in weight may also ease the mechanical burden on ageing joints and muscles, thus improving mobility. Therefore, only weight‐loss therapy that minimizes muscle and bone mineral density loss is recommended for older obese people. Especially in the case of sarcopenic obesity, prevention of further loss of muscle mass is necessary. Sarcopenic obesity is defined as the coexistence of diminished lean mass and increased fat mass.6
Prospective studies have shown that weight loss and decline in BMI can both be markers of and independent contributors to adverse health outcomes. Involuntary weight loss in elderly subjects is likely to reflect sarcopenia, a loss of lean body mass and particularly muscle mass. Cachexia is a disease‐related weight loss, and starvation or undereating reflects a loss of fat mass predominantly. Weight loss may contribute to increased mortality, especially if the initial body weight is relatively low. Prevalence of involuntary weight loss in community‐dwelling elders is 5–15%, 8% of all adult outpatient visits, and 27% of frail people ≥65 years old.7‐9 Clinically, the observation of weight loss is considered the most important indicator of under‐nutrition. A loss of 10% in six months, 7.5% in three months, or 5% in one month is considered serious, owing to the direct relationship with morbidity and mortality. The reduction in total caloric intake is associated with nutritional depletion that may in part contribute to the mortality risk.10
Central adiposity and healthy ageing
Redistribution of body fat with ageing further limits the applicability of BMI as a risk indicator in older adults. There is evidence in younger adults that those who have the majority of their adipose tissue around their waist (high waist‐to‐hip ratio) have a higher prevalence of diabetes mellitus, hypertension, and coronary artery disease than those who have predominantly hip adiposity. Folsom et al.11 examined the role of body fatness on mortality in a random sample of 31,702 Iowan women age 55–69, followed for 11–12 years. A higher waist‐to‐hip ratio was associated with increased mortality independent of smoking, alcohol, and oestrogen use. The waist‐to‐hip ratio is difficult to interpret with ageing. Whereas the waist measures abdominal fatness, hip circumference may also reflect variations in pelvic width and gluteal musculature. In elders, narrow hips may reflect peripheral muscle wasting, which may correlate with chronic conditions.
The current literature on the utility of BMI, waist‐to‐hip ratio, or waist circumference is inconsistent. So far, except for the oldest age group, the conclusion of Canoy12 based on current epidemiology states, ‘adipose tissue distribution assessment ideally should provide a single risk estimate that captures the separate effects of abdominal and peripheral adiposity’. Although far from perfect, waist‐hip ratio or just waist circumference is a simple and inexpensive measure that captures these effects and can help to improve other chronic disease risk assessments. Further research and development are needed for an appropriate protocol for the diagnosis of adipose tissue distribution, including the search into cut‐off points for specific ethnic, age, and other population groups.