The Ability of Various Measures of Fatness to Predict Application for Disability Insurance

Richard Burkhauser, John Cawley and Maximilian Schmeiser

Working Papers from University of Michigan, Michigan Retirement Research Center

Abstract: This paper compares a variety of measures of fatness (e.g. BMI, waist circumference, waist-tohip ratio, percent body fat) in terms of their ability to predict application for Social Security Disability Insurance (DI). This is possible through a recent linkage of the National Health and Nutrition Examination Survey (NHANES) III to Social Security Administration (SSA) administrative records. Our results indicate that the measure of fatness that best predicts application for DI varies by race and gender. For white men, BMI consistently predicts future application for DI. For white women, almost all are consistently predictive. For black men, none predict application. For black women, waist circumference and waist-to-hip ratio are the only significant predictors of DI application. This variation across race and gender suggests that the inclusion of alternative measures of fatness in social science datasets should be considered, and that researchers examining the impact of fatness on social science outcomes should examine the robustness of their findings to alternative measures of fatness.

Pages: 31 pages
Date: 2008-09
New Economics Papers: this item is included in nep-ias
References: Add references at CitEc
Citations:

Downloads: (external link)
http://mrdrc.isr.umich.edu/publications/Papers/pdf/wp185.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 403 Forbidden (http://mrdrc.isr.umich.edu/publications/Papers/pdf/wp185.pdf [301 Moved Permanently]--> https://mrdrc.isr.umich.edu/publications/Papers/pdf/wp185.pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mrr:papers:wp185

Access Statistics for this paper

More papers in Working Papers from University of Michigan, Michigan Retirement Research Center P.O. Box 1248, Ann Arbor, MI 48104. Contact information at EDIRC.
Bibliographic data for series maintained by MRRC Administrator ().