Bradley M Appelhans1,2, Brittney S Lange-Maia3, Kelley Pettee Gabriel4,5,6, Carrie Karvonen-Gutierrez7, Kelly Karavolos3, Sheila A Dugan8, Gail A Greendale9, Elizabeth F Avery3, Barbara Sternfeld10, Imke Janssen3, Howard M Kravitz3,11. 1. Department of Preventive Medicine, Rush University Medical Center, 1700 W. Van Buren St., Suite 470, Chicago, IL, 60612, USA. brad_appelhans@rush.edu. 2. Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, 2150 W. Harrison St., Room 278, Chicago, IL, 60612, USA. brad_appelhans@rush.edu. 3. Department of Preventive Medicine, Rush University Medical Center, 1700 W. Van Buren St., Suite 470, Chicago, IL, 60612, USA. 4. Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health - Austin Campus, The University of Texas Health Science Center, Austin, USA. 5. Department of Women's Health, Dell Medical School, The University of Texas at Austin, Austin, USA. 6. Department of Kinesiology and Health Education, The University of Texas at Austin, Austin, USA. 7. Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA. 8. Department of Physical Medicine and Rehabilitation, Rush University Medical Center, Chicago, USA. 9. Department of Medicine, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, USA. 10. Division of Research, Kaiser Permanente Northern California, Oakland, USA. 11. Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, 2150 W. Harrison St., Room 278, Chicago, IL, 60612, USA.
Abstract
BACKGROUND: Body composition strongly influences physical function in older adults. Bioelectrical impedance analysis (BIA) differentiates fat mass from skeletal muscle mass, and may be more useful than body mass index (BMI) for classifying women on their likelihood of physical function impairment. AIMS: This study tested whether BIA-derived estimates of percentage body fat (%BF) and height-normalized skeletal muscle mass (skeletal muscle mass index; SMI) enhance classification of physical function impairment relative to BMI. METHOD: Black, White, Chinese, and Japanese midlife women (N = 1482) in the Study of Women's Health Across the Nation (SWAN) completed performance-based measures of physical function. BMI (kg/m2) was calculated. %BF and SMI were derived through BIA. Receiver-operating characteristic (ROC) curve analysis, conducted in the overall sample and stratified by racial group, evaluated optimal cutpoints of BMI, %BF, and SMI for classifying women on moderate-severe physical function impairment. RESULTS: In the overall sample, a BMI cutpoint of ≥ 30.1 kg/m2 correctly classified 71.1% of women on physical function impairment, and optimal cutpoints for %BF (≥ 43.4%) and SMI (≥ 8.1 kg/m2) correctly classified 69% and 62% of women, respectively. SMI did not meaningfully enhanced classification relative to BMI (change in area under the ROC curve = 0.002; net reclassification improvement = 0.021; integrated discrimination improvement = - 0.003). Optimal cutpoints for BMI, %BF, and SMI varied substantially across race. Among Black women, a %BF cutpoint of 43.9% performed somewhat better than BMI (change in area under the ROC curve = 0.017; sensitivity = 0.69, specificity = 0.64). CONCLUSION: Some race-specific BMI and %BF cutpoints have moderate utility for identifying impaired physical function among midlife women.
BACKGROUND: Body composition strongly influences physical function in older adults. Bioelectrical impedance analysis (BIA) differentiates fat mass from skeletal muscle mass, and may be more useful than body mass index (BMI) for classifying women on their likelihood of physical function impairment. AIMS: This study tested whether BIA-derived estimates of percentage body fat (%BF) and height-normalized skeletal muscle mass (skeletal muscle mass index; SMI) enhance classification of physical function impairment relative to BMI. METHOD: Black, White, Chinese, and Japanese midlife women (N = 1482) in the Study of Women's Health Across the Nation (SWAN) completed performance-based measures of physical function. BMI (kg/m2) was calculated. %BF and SMI were derived through BIA. Receiver-operating characteristic (ROC) curve analysis, conducted in the overall sample and stratified by racial group, evaluated optimal cutpoints of BMI, %BF, and SMI for classifying women on moderate-severe physical function impairment. RESULTS: In the overall sample, a BMI cutpoint of ≥ 30.1 kg/m2 correctly classified 71.1% of women on physical function impairment, and optimal cutpoints for %BF (≥ 43.4%) and SMI (≥ 8.1 kg/m2) correctly classified 69% and 62% of women, respectively. SMI did not meaningfully enhanced classification relative to BMI (change in area under the ROC curve = 0.002; net reclassification improvement = 0.021; integrated discrimination improvement = - 0.003). Optimal cutpoints for BMI, %BF, and SMI varied substantially across race. Among Black women, a %BF cutpoint of 43.9% performed somewhat better than BMI (change in area under the ROC curve = 0.017; sensitivity = 0.69, specificity = 0.64). CONCLUSION: Some race-specific BMI and %BF cutpoints have moderate utility for identifying impaired physical function among midlife women.
Entities:
Keywords:
Body composition; Body mass index; Physical function; Skeletal muscle mass
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