Decreased muscle mass and increased central adiposity are independently related to mortality in older men

Body composition analysis techniques in the aged adult: indications and limitations

PURPOSE OF REVIEW

Body composition analysis allows division of the body into different compartments on the basis of differing physical properties. A variety of techniques are available for measuring body composition. This review describes the changes that occur with increasing age, their significance and also the limitations of available body composition analysis techniques when applied to the elderly.

RECENT FINDINGS

Studies have shown the development of changes in body composition with ageing that have important consequences for health. Alterations in body fat content and particularly body fat distribution are associated with adverse metabolic effects and increased cardiovascular risk. Reduced skeletal muscle mass and strength (sarcopenia) are common in the elderly with important effects on function and outcome. A range of techniques are available for measuring body composition. However, changes in body composition with ageing, particularly altered composition of the constituents of fat-free mass, and changes in fat distribution, may lead to measurement errors with standard body composition assessment methodology.

SUMMARY

Measurement of body composition provides information of importance to health and function. Techniques used for assessment should be those unaffected by age-related changes in body composition, or those that have been adapted or validated in this age group. Particular roles of these techniques in the elderly include screening or surveillance of those at risk of malnutrition, and monitoring a range of chronic illnesses that are prevalent in older individuals.

Nutritional risk and health care use before and after an acute hospitalization among the elderly

OBJECTIVE

Our objective was to assess the nutritional status and health care use of community-dwelling elderly before hospitalization and determine risk factors for longer hospitalizations during 3 mo of follow-up.

METHODS

During a 1-y period, we recruited patients 65 y and older admitted to an internal medicine ward at Soroka Medical Center (Beer-Sheva, Israel). Data were obtained regarding health and nutritional status and demographic and social characteristics. We assessed the utilization of health care services during a follow-up period of 3 mo.

RESULTS

Seventy-nine of 204 patients (38.7%) were at nutritional risk. Patients at nutritional risk were older (P < 0.001) and less educated (P = 0.03) than the well-nourished group. Nutritional risk was associated with more diagnosed diseases, days of hospital stay, and physician visits before admission. Participants hospitalized for more than 6 d were significantly less educated, with lower cognitive, functional, Mini Nutritional Assessment, and Nutritional Risk Index scores and a significantly higher depressive symptoms score. Functional status and sum of nutritional problems were significant predictors of length of hospitalization in the following 3 mo.

CONCLUSION

Nutritional risk is a source of concern for health care providers and services, because it significantly increases risk of hospital admission and length of stay. It is important to increase the awareness of primary care providers to the impact of nutrition on health care use and provide appropriate tools to screen and treat nutritional problems.

Influence of central and extremity circumferences on all-cause mortality in men and women

For a given level of adiposity, greater lower body circumferences appear to exert a protective effect on several disease outcomes including cardiovascular disease and diabetes; however, the independent associations between extremity circumferences and mortality have not been widely investigated. The purpose of this study was to determine the independent and shared influences of upper- and lower-body circumferences on the risk of mortality in a population-based sample of adults. The sample included 10,638 adults 20-69 years of age (5,012 men; 5,626 women) from the nationally representative 1981 Canada Fitness Survey (CFS), who were monitored for over 12 years for mortality. BMI was calculated from measured height and weight. Waist, hip, thigh, calf, and upper arm circumferences were measured using a flexible, nonelastic anthropometric tape. Sex-specific proportional hazards regression models were used to evaluate the relationship between standardized values (Z-scores) of extremity circumference measures, waist circumference (WC) and mortality. Age, smoking status, alcohol consumption, and leisure-time physical activity were collected by questionnaire and were included as covariates. During 131,563 person-years of follow-up, there were 340 deaths in men and 231 in women. After mutual adjustment, WC was positively associated with mortality whereas arm, thigh, and calf circumferences were significantly protective in men, and arm and thigh circumferences were protective in women. In conclusion, waist and extremity circumferences appear to have opposite, independent effects on mortality in this sample of Canadians. Independent of BMI and WC, men and women with larger extremity circumferences had a lower risk of mortality.

Change in body mass index is a stronger predictor of change in fat mass than lean mass in elderly black and white women

The aim of this study was to determine the relation between change in body mass index (BMI) and changes in fat mass (FM), lean soft tissue (LST), and percentage body fat (%Fat) in elderly (67.6 +/- 6.0 years) women varying in race (53 black, 144 white) who underwent measurements of BMI, FM, LST, and %Fat at baseline and after 2 years. The group did not markedly change body composition over 2 years (BMI = -0.1 +/- 1.5 kg/m(2), P = 0.53; FM = 0.0 +/- 2.8 kg, P = 0.95; LST = -0.4 +/- 1.7 kg, P < 0.001; %Fat = 0.3 +/- 2.0%, P = 0.06). Change in BMI predicted change in FM (r = 0.90, SEE = 1.19 kg FM, P < 0.001) but was less predictive of change in %Fat (r = 0.64, SEE = 1.54%Fat, P < 0.001). Change in BMI was curvilinearly related to change in LST adjusted for change in height (R = 0.76, SEE = 1.10 kg LST, P < 0.001). Change in BMI more strongly predicts change in FM than LST and could be used to monitor change in FM in community-dwelling women.

Impact of body mass index and waist-to-hip ratio on clinical outcomes in patients with ST-segment elevation acute myocardial infarction (from the Korean Acute Myocardial Infarction Registry)

The relation between body mass index (BMI) and waist-to-hip ratio (WHR) to clinical outcomes in patients with ST-segment elevation acute myocardial infarction (MI) has not been well described. As part of the Korean Acute MI Registry, we enrolled 3,734 eligible patients who were diagnosed with ST-segment elevation acute MI. The study population was categorized by BMI (into 4 groups according to the World Health Organization classification for the Asian population) and WHR (into 2 sets of 4 groups, 1 set for men and another for women, based on the INTERHEART study). Baseline characteristics and clinical outcomes were analyzed and compared among the BMI and WHR categories. Mean follow-up duration was 199 +/- 37 days. In the BMI category, underweight versus obese patients were older, were more likely to present with heart failure, and underwent guideline-based treatments less frequently. In the WHR category, the reverse trends were apparent for the latter factors except treatment-use frequencies. The highest mortality rate was observed in patients with the lowest BMI and the highest WHR. In an adjusted model, the highest WHR (hazard ratio 5.57, 95% confidence interval 1.53 to 12.29, p = 0.009) and the underweight (hazard ratio 2.88, 95% confidence interval 1.17 to 6.08, p = 0.021) categories within the 2 anthropometric indexes remained as mortality risk factors. In conclusion, the relation between obesity and prognosis after ST-segment elevation acute MI appears complex and should be further assessed in larger population-based cohort studies to determine the associations apparent in this study.

Waist-to-hip ratio and body mass index as risk factors for cardiovascular events in CKD

BACKGROUND

The role of obesity as a risk factor for cardiovascular disease in patients with chronic kidney disease (CKD) is poorly understood. Waist-to-hip ratio (WHR) is less influenced by muscle and bone mass than body mass index (BMI). We compared WHR and BMI as risk factors for cardiac events (myocardial infarction and fatal coronary disease) in persons with CKD.

STUDY DESIGN

Cohort study.

SETTING & PARTICIPANTS

Persons with CKD, defined as baseline estimated glomerular filtration rate of 15 to 60 mL/min/1.73 m(2), drawn from 2 community studies: the Atherosclerosis Risk in Communities Study and the Cardiovascular Health Study.

PREDICTOR

WHR, waist circumference, and BMI.

OUTCOMES & MEASUREMENTS

Myocardial infarction and fatal coronary heart disease.

RESULTS

Of 1,669 participants with CKD, mean age was 70.3 years and 56% were women. Mean (SD) WHRs were 0.97 +/- 0.08 in men and 0.90 +/- 0.07 in women; mean (SD) BMI was 27.2 +/- 4.6 kg/m(2). During a mean of 9.3 years of follow-up, there were 334 cardiac events. In multivariable-adjusted Cox models, the highest WHR group (n = 386) was associated with an increased risk of cardiac events compared with the lowest WHR group (hazard ratio, 1.36; 95% confidence interval, 1.01 to 1.83). Obesity, defined as BMI greater than 30 kg/m(2) (n = 381), was not associated with cardiac events (hazard ratio, 0.86; 95% confidence interval, 0.62 to 1.20) in comparison to participants with normal BMI (<25 kg/m(2)). Results with waist circumference were similar to those with BMI.

LIMITATIONS

Absence of a gold standard for measurement of visceral fat.

CONCLUSIONS

WHR, but not BMI, is associated with cardiac events in persons with CKD. Relying exclusively on BMI may underestimate the importance of obesity as a cardiovascular disease risk factor in persons with CKD.

Lifestyle factors associated with age-related differences in body composition: the Florey Adelaide Male Aging Study

BACKGROUND

Age-related change in body composition is associated with adverse health outcomes, including functional decline, disability, morbidity, and early mortality. Prevention of age-related changes requires a greater understanding of the associations among age, lifestyle factors, and body composition.

OBJECTIVE

We aimed to comprehensively determine lifestyle factors associated with age-related differences in body composition assessed by using dual-energy X-ray absorptiometry.

DESIGN

We analyzed baseline (cross-sectional) data collected from 2002 to 2005 for approximately 1200 men in the Florey Adelaide Male Aging Study, a regionally representative cohort of Australian men aged 35-81 y.

RESULTS

Mean values for whole-body lean mass (LM) and areal bone mineral density (aBMD) decreased, whereas mean values for abdominal fat mass (FM) and whole-body and abdominal percentage FM (%FM) increased with age. No significant age-related differences were found for whole-body FM. Multiple adjusted odds of being in the highest tertiles for whole-body and abdominal %FM decreased for smokers (63-71%) but increased with age group and for lowest energy (43-50%), carbohydrate (92-107%), and fiber (107%) intake tertiles. Multiple adjusted odds of being in the highest aBMD tertile decreased for lowest body mass (92%) and carbohydrate intake (63%) tertiles and for men aged > or = 75 y (78%) but increased for Australian birth (58%) and for participation in vigorous physical activities (82%).

CONCLUSIONS

Age-related differences in body composition indicate that whole-body FM remains stable but increases viscerally and that whole-body %FM is confounded by LM, whereas aBMD decreases with age. Age-related differences in %FM and aBMD are associated with demographic and lifestyle factors.

Can metabolic syndrome usefully predict cardiovascular disease and diabetes? Outcome data from two prospective studies

BACKGROUND

Clinical use of criteria for metabolic syndrome to simultaneously predict risk of cardiovascular disease and diabetes remains uncertain. We investigated to what extent metabolic syndrome and its individual components were related to risk for these two diseases in elderly populations.

METHODS

We related metabolic syndrome (defined on the basis of criteria from the Third Report of the National Cholesterol Education Program) and its five individual components to the risk of events of incident cardiovascular disease and type 2 diabetes in 4812 non-diabetic individuals aged 70-82 years from the Prospective Study of Pravastatin in the Elderly at Risk (PROSPER). We corroborated these data in a second prospective study (the British Regional Heart Study [BRHS]) of 2737 non-diabetic men aged 60-79 years.

FINDINGS

In PROSPER, 772 cases of incident cardiovascular disease and 287 of diabetes occurred over 3.2 years. Metabolic syndrome was not associated with increased risk of cardiovascular disease in those without baseline disease (hazard ratio 1.07 [95% CI 0.86-1.32]) but was associated with increased risk of diabetes (4.41 [3.33-5.84]) as was each of its components, particularly fasting glucose (18.4 [13.9-24.5]). Results were similar in participants with existing cardiovascular disease. In BRHS, 440 cases of incident cardiovascular disease and 105 of diabetes occurred over 7 years. Metabolic syndrome was modestly associated with incident cardiovascular disease (relative risk 1.27 [1.04-1.56]) despite strong association with diabetes (7.47 [4.90-11.46]). In both studies, body-mass index or waist circumference, triglyceride, and glucose cutoff points were not associated with risk of cardiovascular disease, but all five components were associated with risk of new-onset diabetes.

INTERPRETATION

Metabolic syndrome and its components are associated with type 2 diabetes but have weak or no association with vascular risk in elderly populations, suggesting that attempts to define criteria that simultaneously predict risk for both cardiovascular disease and diabetes are unhelpful. Clinical focus should remain on establishing optimum risk algorithms for each disease.