Physical activity and fat-free mass during growth and in later life

Background: Physical activity may be a way to increase and maintain fat-free mass (FFM) in later life, similar to the prevention of fractures by increasing peak bone mass. Objectives: A study is presented of the association between FFM and physical activity in relation to age. Methods: In a cross-sectional study, FFM was analyzed in relation to physical activity in a large participant group as compiled in the International Atomic Energy Agency Doubly Labeled Water database. The database included 2000 participants. age 3-96 y, with measurements of total energy expenditure (TEE) and resting energy expenditure (REE) to allow calculation of physical activity level (PAL = TEE/REE), and calculation of FFM from isotope dilution. Results: PAL was a main determinant of body composition at all ages. Models with age, fat mass (FM), and PAL explained 76% and 85% of the variation in FFM in females and males = 18 y old, respectively. In participants < 18 y old, mean FM-adjusted FFM was 1.7 kg (95% CI: 0.1, 3.2 kg) and 3.4 kg (95% CI: 1.0, 5.6 kg) higher in a very active participant with PAL = 2.0 than in a sedentary participant with PAL = 1.5, for females and males, respectively. At age 18 y. height and FM-adjusted FFM was 3.6 kg (95% CI: 2.8, 4.4 kg) and 4.4 kg (95% Cl: 3.2, 5.7 kg) higher. and at age 80 y 0.7 kg (95% CI: -0.2. 1.7 kg) and 1.0 kg (95% CI: -0.1, 2.1 kg) higher. in a participant with PAL = 2.0 than in a participant with PAL = 1.5, for females and males, respectively. Conclusions: If these associations are causal, they suggest physical activity is a major determinant of body composition as reflected in peak FFM, and that a physically active lifestyle can only partly protect against loss of FFM in aging adults.Peer reviewe

Physical activity and fat-free mass during growth and in later life.

BACKGROUND: Physical activity may be a way to increase and maintain fat-free mass (FFM) in later life, similar to the prevention of fractures by increasing peak bone mass. OBJECTIVES: A study is presented of the association between FFM and physical activity in relation to age. METHODS: In a cross-sectional study, FFM was analyzed in relation to physical activity in a large participant group as compiled in the International Atomic Energy Agency Doubly Labeled Water database. The database included 2000 participants, age 3-96 y, with measurements of total energy expenditure (TEE) and resting energy expenditure (REE) to allow calculation of physical activity level (PAL = TEE/REE), and calculation of FFM from isotope dilution. RESULTS: PAL was a main determinant of body composition at all ages. Models with age, fat mass (FM), and PAL explained 76% and 85% of the variation in FFM in females and males < 18 y old, and 32% and 47% of the variation in FFM in females and males ≥ 18 y old, respectively. In participants < 18 y old, mean FM-adjusted FFM was 1.7 kg (95% CI: 0.1, 3.2 kg) and 3.4 kg (95% CI: 1.0, 5.6 kg) higher in a very active participant with PAL = 2.0 than in a sedentary participant with PAL = 1.5, for females and males, respectively. At age 18 y, height and FM-adjusted FFM was 3.6 kg (95% CI: 2.8, 4.4 kg) and 4.4 kg (95% CI: 3.2, 5.7 kg) higher, and at age 80 y 0.7 kg (95% CI: -0.2, 1.7 kg) and 1.0 kg (95% CI: -0.1, 2.1 kg) higher, in a participant with PAL = 2.0 than in a participant with PAL = 1.5, for females and males, respectively. CONCLUSIONS: If these associations are causal, they suggest physical activity is a major determinant of body composition as reflected in peak FFM, and that a physically active lifestyle can only partly protect against loss of FFM in aging adults

Physical activity and fat-free mass during growth and in later life.

Physical activity may be a way to increase and maintain fat-free mass (FFM) in later life, similar to the prevention of fractures by increasing peak bone mass. A study is presented of the association between FFM and physical activity in relation to age. In a cross-sectional study, FFM was analyzed in relation to physical activity in a large participant group as compiled in the International Atomic Energy Agency Doubly Labeled Water database. The database included 2000 participants, age 3-96 y, with measurements of total energy expenditure (TEE) and resting energy expenditure (REE) to allow calculation of physical activity level (PAL = TEE/REE), and calculation of FFM from isotope dilution. PAL was a main determinant of body composition at all ages. Models with age, fat mass (FM), and PAL explained 76% and 85% of the variation in FFM in females and males &lt; 18 y old, and 32% and 47% of the variation in FFM in females and males ≥ 18 y old, respectively. In participants &lt; 18 y old, mean FM-adjusted FFM was 1.7 kg (95% CI: 0.1, 3.2 kg) and 3.4 kg (95% CI: 1.0, 5.6 kg) higher in a very active participant with PAL = 2.0 than in a sedentary participant with PAL = 1.5, for females and males, respectively. At age 18 y, height and FM-adjusted FFM was 3.6 kg (95% CI: 2.8, 4.4 kg) and 4.4 kg (95% CI: 3.2, 5.7 kg) higher, and at age 80 y 0.7 kg (95% CI: -0.2, 1.7 kg) and 1.0 kg (95% CI: -0.1, 2.1 kg) higher, in a participant with PAL = 2.0 than in a participant with PAL = 1.5, for females and males, respectively. If these associations are causal, they suggest physical activity is a major determinant of body composition as reflected in peak FFM, and that a physically active lifestyle can only partly protect against loss of FFM in aging adults

Variation in human water turnover associated with environmental and lifestyle factors

Water is essential for survival, but one in three individuals worldwide (2.2 billion people) lack access to safe drinking water. Water intake requirements largely reflect water turnover (WT), the water used by the body each day. We investigated the determinants of human WT in 5,604 people from the ages of 8 days to 96 years from 26 countries using isotope tracking ((2)H) methods. Age, body size, and composition were significantly associated with WT as were physical activity, athletic status, pregnancy, socioeconomic status, and environmental characteristics (latitude, altitude, air temperature, and humidity). People in countries with low human development index (HDI) had higher water turnover than people who lived in countries with high HDI. Based on this extensive dataset we provide equations to predict human water requirements in relation to anthropometric, economic, and environmental factors