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Body mass index versus bioelectrical impedance analysis for classifying physical function impairment in a racially diverse cohort of midlife women: the Study of Women’s Health Across the Nation (SWAN)

  • Bradley M. AppelhansEmail author
  • Brittney S. Lange-Maia
  • Kelley Pettee Gabriel
  • Carrie Karvonen-Gutierrez
  • Kelly Karavolos
  • Sheila A. Dugan
  • Gail A. Greendale
  • Elizabeth F. Avery
  • Barbara Sternfeld
  • Imke Janssen
  • Howard M. Kravitz
Original Article
  • 52 Downloads

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.

Keywords

Physical function Body composition Body mass index Skeletal muscle mass 

Notes

Acknowledgements

The Study of Women’s Health Across the Nation (SWAN) has grant support from the National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR), and the NIH Office of Research on Women’s Health (ORWH) (Grants U01NR004061; U01AG012505, U01AG012535, U01AG012531, U01AG012539, U01AG012546, U01AG012553, U01AG012554, U01AG012495). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the NIA, NINR, ORWH, or the NIH.

Clinical centers: University of Michigan, Ann Arbor—Siobán Harlow, PI 2011–present, MaryFran Sowers, PI 1994–2011; Massachusetts General Hospital, Boston, MA—Joel Finkelstein, PI 1999–present; Robert Neer, PI 1994–1999; Rush University, Rush University Medical Center, Chicago, IL—Howard Kravitz, PI 2009–present; Lynda Powell, PI 1994–2009; University of California, Davis/Kaiser—Ellen Gold, PI; University of California, Los Angeles—Gail Greendale, PI; Albert Einstein College of Medicine, Bronx, NY—Carol Derby, PI 2011–present, Rachel Wildman, PI 2010–2011; Nanette Santoro, PI 2004–2010; University of Medicine and Dentistry–New Jersey Medical School, Newark—Gerson Weiss, PI 1994–2004; and the University of Pittsburgh, Pittsburgh, PA: Karen Matthews, PI.

NIH program office: National Institute on Aging, Bethesda, MD—Chhanda Dutta 2016–present; Winifred Rossi 2012–2016; Sherry Sherman 1994–2012; Marcia Ory 1994–2001; National Institute of Nursing Research, Bethesda, MD—Program Officers.

Central laboratory: University of Michigan, Ann Arbor—Daniel McConnell (Central Ligand Assay Satellite Services).

Coordinating center: University of Pittsburgh, Pittsburgh, PA—Maria Mori Brooks, PI 2012–present; Kim Sutton-Tyrrell, PI 2001–2012; New England Research Institutes, Watertown, MA—Sonja McKinlay, PI 1995–2001.

Steering committee: Susan Johnson, Current Chair. Chris Gallagher, Former Chair

We thank the study staff at each site and all the women who participated in SWAN.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Statement of human and animal rights

Study procedures received institutional review board approval from each study site. The study was conducted in accordance with the Declaration of Helsinki.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

40520_2019_1355_MOESM1_ESM.tif (1.2 mb)
Supplementary material 1. Supplemental Fig. 1. Race-specific receiver-operating characteristic curves for each body composition measure in classifying midlife women on their likelihood of moderate–severe physical function impairment (TIFF 1275 kb)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Bradley M. Appelhans
    • 1
    • 2
    Email author
  • Brittney S. Lange-Maia
    • 1
  • Kelley Pettee Gabriel
    • 3
    • 4
    • 5
  • Carrie Karvonen-Gutierrez
    • 6
  • Kelly Karavolos
    • 1
  • Sheila A. Dugan
    • 7
  • Gail A. Greendale
    • 8
  • Elizabeth F. Avery
    • 1
  • Barbara Sternfeld
    • 9
  • Imke Janssen
    • 1
  • Howard M. Kravitz
    • 1
    • 2
  1. 1.Department of Preventive MedicineRush University Medical CenterChicagoUSA
  2. 2.Department of Psychiatry and Behavioral SciencesRush University Medical CenterChicagoUSA
  3. 3.Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health - Austin CampusThe University of Texas Health Science CenterAustinUSA
  4. 4.Department of Women’s Health, Dell Medical SchoolThe University of Texas at AustinAustinUSA
  5. 5.Department of Kinesiology and Health EducationThe University of Texas at AustinAustinUSA
  6. 6.Department of Epidemiology, School of Public HealthUniversity of MichiganAnn ArborUSA
  7. 7.Department of Physical Medicine and RehabilitationRush University Medical CenterChicagoUSA
  8. 8.Department of MedicineDavid Geffen School of Medicine at the University of California, Los AngelesLos AngelesUSA
  9. 9.Division of ResearchKaiser Permanente Northern CaliforniaOaklandUSA

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