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

31 Pages Posted: 5 Feb 2009

See all articles by Richard V. Burkhauser

Richard V. Burkhauser

Cornell University - Department of Policy Analysis & Management (PAM); University of Melbourne, Melbourne Institute

John Cawley

Cornell University - College of Human Ecology, Department of Policy Analysis & Management (PAM); Cornell University - College of Arts & Sciences, Department of Economics; Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE); National University of Ireland, Galway (NUIG) - J.E. Cairnes School of Business & Economics; NBER; IZA

Maximilian D. Schmeiser

Amazon Lending

Date Written: September 1, 2008

Abstract

This paper compares a variety of measures of fatness (e.g. BMI, waist circumference, waist-to-hip 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.

Suggested Citation

Burkhauser, Richard V. and Cawley, John and Schmeiser, Maximilian D., The Ability of Various Measures of Fatness to Predict Application for Disability Insurance (September 1, 2008). Michigan Retirement Research Center Research Paper No. 2008-185, Available at SSRN: https://ssrn.com/abstract=1337648 or http://dx.doi.org/10.2139/ssrn.1337648

Richard V. Burkhauser (Contact Author)

Cornell University - Department of Policy Analysis & Management (PAM) ( email )

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University of Melbourne, Melbourne Institute ( email )

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John Cawley

Cornell University - College of Human Ecology, Department of Policy Analysis & Management (PAM) ( email )

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Cornell University - College of Arts & Sciences, Department of Economics ( email )

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Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE) ( email )

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National University of Ireland, Galway (NUIG) - J.E. Cairnes School of Business & Economics ( email )

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NBER

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IZA ( email )

P.O. Box 7240
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Germany

Maximilian D. Schmeiser

Amazon Lending ( email )

Seattle, WA 98144
United States

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