Abstract
DOI: http://dx.doi.org/10.5007/1980-0037.2016v18n4p381 The aim of this study was to compare body adiposity indexes and to identify cutoff values in the prediction of disability in older women. Eighty-seven voluntees (67.27±6.45 years) underwent body composition assessment using dual-energy X-ray absorptiometry (DXA) and had five anthropometric indexes measured (Waist Circumference, WC; Waist-to-Height Ratio, WHtR; Body Mass Index, BMI; Body Adiposity Index, BAI; and conicity index). Functionality was assessed from three Senior Fitness Test Battery protocols: 30-second chair stand, 8-foot up-and-go, and 6-minute walk. Pearson’s correlation was conducted to identify the relationship between body adiposity indexes and functionality results. Cutoff values to predict disability were obtained from ROC curves and odds ratio were calculated for the same outcome. Disability prevalence was 36.8%. Scores in the 30-second chair stand, 8-foot up-and-go, and 6-minute walk tests showed stronger associations with WC (r=-0.345; p<0.01), WHtR (r=-0.417; p<0.01) and BAI (r=0.296; p<0.01), respectively. The cutoff values identified were 89.5cm, 39.2%, 26.93kg/m2, 34.6%, 0.51cm and 1.23 for WC, DXA-derived body fat percentage, BMI, BAI, WHtR and conicity index, respectively. WC showed greater odds ratio for disability outcome (odds ratio: 3.16; CI: 1.3–7.8). WC showed strong relationship with functional tests and its cutoff values exhibited predicting skill for disability in older women.
Highlights
The aging process is associated with important changes in the various physiological systems
Subjects classified with and without the functional disability outcome showed no significant differences in the variables that characterize the sample
By observing participants classified with high adiposity, the odds ratio for the functional disability outcome was increased for both waist circumference (WC) and body mass index (BMI)
Summary
The aging process is associated with important changes in the various physiological systems. Increased body fat has been associated with negative health indicators, such as cardiometabolic diseases in various populations, including in the elderly[2]. There is growing interest in investigating the predictive power of low-cost and easy-application clinical evaluations. In this scenario, some body adiposity indexes have been widely used to predict various risk factors of the population as a whole[2]. In an effort to improve the methods commonly used to estimate body fat percentage, Bergman et al.[5] proposed the body adiposity index (BAI), which was consistently associated (r = 0.85) with fat percentage measured by DXA. Its ability to identify conditions related to excess body fat needs further investigations in specific populations[2]
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