Analysing body composition as compositional data: An exploration of the relationship between body composition, body mass and bone strength.

Human body composition is made up of mutually exclusive and exhaustive parts (e.g. %truncal fat, %non-truncal fat and %fat-free mass) which are constrained to sum to the same total (100%). In statistical analyses, individual parts of body composition (e.g. %truncal fat or %fat-free mass) have traditionally been used as proxies for body composition, and have been linked with a range of health outcomes. But analysis of individual parts omits information about the other parts, which are intrinsically co-dependent because of the constant sum constraint of 100%. Further, body mass may be associated with health outcomes. We describe a statistical approach for body composition based on compositional data analysis. The body composition data are expressed as logratios to allow relative information about all the compositional parts to be explored simultaneously in relation to health outcomes. We describe a recent extension to the logratio approach to compositional data analysis which allows absolute information about the total of the compositional parts (body mass) to be considered alongside relative information about body composition. The statistical approach is illustrated by an example that explores the relationships between adults' body composition, body mass and bone strength.

Relationships between older adults' use of time and cardio-respiratory fitness, obesity and cardio-metabolic risk: A compositional isotemporal substitution analysis.

OBJECTIVE: Older adults' health has been linked with time in moderate-to-vigorous physical activity (MVPA), and recent studies suggest time in sedentary behaviour may also be important. Time-use behaviours (MVPA, light physical activity, sedentary time and sleep) are co-dependent, and therefore their associations with health should be examined in an integrated manner. This is the first study to investigate the relationship between older adults' reallocation of time among these time-use behaviours and markers of cardio-respiratory fitness, obesity and cardio-metabolic risk. STUDY DESIGN: Cross-sectional study of 122 Australians (65 ±â€¯3 y, 61% female). MAIN OUTCOME MEASURES: Daily time use: average daily minutes spent in MVPA, light physical activity, sedentary time and sleep derived from 24-h, 7-day accelerometry, were conceptualised as a time-use composition. Cardio-respiratory fitness: graded submaximal cycle ergometer test. Obesity: objectively measured body mass index (BMI) and waist-to-hip ratio (WHR). Cardio-metabolic risk: sphygmomanometer-measured resting blood pressure and fingertip blood sampling for fasting total cholesterol and glucose. RESULTS: Time-use composition was significantly associated with obesity markers (BMI, p = 0.001; WHR, p < 0.001). The reallocation of 15 min to MVPA from any of the other behaviours was associated with approximately +1.1 (95% confidence interval 0.2; 1.9) ml/kg-1 min-1 VO2max, -0.7 (-1.0; -0.3) BMI units and -1.2 (-1.8; -0.7) WHR percentage points, while the opposite reallocation (15 min from MVPA to other behaviours) was associated with larger difference estimates of -1.8 (-3.2; -0.4) ml/kg-1 min-1 VO2max, +1.2 (0.5; 1.9) BMI units and +2.1 (1.2; 3.1) WHR percentage points. CONCLUSION: These findings reinforce the importance of MVPA for health among older adults. Interventions to maintain MVPA, even without increasing it, may be valuable.