The interrelationship between body topology and body composition varies with age among women.
The purpose of this analysis was to evaluate the relationship between age and the size and distribution of the fat and lean tissue compartments in a population-based sample of women. The study population consisted of the 875 women aged 18-94 y in the Iowa Bone Health Study who reported never smoking. Fat mass and lean mass were measured using dual X-ray absorptiometry. Hip and waist circumference and height were measured using standardized protocols. Regression was used to model the associations among age, composition and topology measures. When fat mass was modeled as a function of hip and waist circumference as well as age, age(2) and height, the age x height and age x waist circumference interaction terms remained in the fitted model and collectively accounted for 91% of the variance. In contrast, the quadratic model of age alone accounted for 8% of the observed variance in fat mass. Lean mass was modeled in two segments, with age dichotomized at 58 y. Age alone did not predict lean mass in women <58 y but did predict lean mass in women >/=58 y, with the modeled relationship including interactions with waist circumference and height. These models accounted for 70% of observed variance in lean mass. Age is associated with body composition but explains <10% of variation. When measures of height and circumferences are available, amounts of lean and fat mass are highly predictable. This is particularly important for lean mass because no other surrogate measures exist for lean mass, whereas there are surrogates for fat mass, including body mass index.
Welch
G W
GW
Department of Epidemiology, University of Michigan, Ann Arbor, MI 48109-2029, USA.
Sowers
M R
MR
D015502:Absorptiometry, Photon; D000273:Adipose Tissue; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D001823:Body Composition; D001824:Body Constitution; D001827:Body Height; D015992:Body Mass Index; D001835:Body Weight; D005260:Female; D006801:Humans; D007484:Iowa; D008875:Middle Aged; D012044:Regression Analysis