Using New Measures of Fatness to Improve Estimates of Early Retirement and Entry onto the OASI Rolls...

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Transcript of Using New Measures of Fatness to Improve Estimates of Early Retirement and Entry onto the OASI Rolls...

  • Slide 1
  • Using New Measures of Fatness to Improve Estimates of Early Retirement and Entry onto the OASI Rolls Richard V. Burkhauser John C. Cawley
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  • Research Question Our research question: Is there a causal relationship between fatness and taking Old-Age benefits at age 62? Fatness is a risk factor for morbidity and mortality in the medical literature Innovations: Utilize alternative measures of fatness to capture health. Test for causal link using method of instrumental variables.
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  • Discrete when health is continuous Error-ridden since individuals scales are different Endogenous to retirement decision. Bond, Steinbricker and Waidmann (2006) Problems with Subjective Measures of Health
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  • Body Mass Index (BMI) BMI = kg/m 2 is most common measure of fatness in social science research NIH, WHO use BMI to define obesity (BMI>=30) Advantage: weight and height found in many social science datasets, easy to calculate Disadvantage: BMI does not distinguish between fat and muscle Overestimates fatness among the muscular (U.S. DHHS, 2001; Prentice and Jebb, 2001) Underestimates fatness among those with small frames
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  • Accurate Measures of Obesity Must Distinguish Body Composition Fatness (not muscle/bone/blood) causes morbidity, mortality Previous studies that define obesity using body mass index (BMI) likely misstate correlation between fatness and economic outcomes Better measure of fatness: Percent Body Fat (PBF) Obesity defined as PBF>25 for men, PBF>30 for women (NIH, 2006)
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  • BMI Poor Measure of Fatness BMI alone accounts for just 25% of between- individual differences in percent body fat (Gallagher et al., 1996) False negatives: BMI correctly identifies only 44.3% of obese men and 55.4% of obese women (judged by measurement of actual body fat); Smalley et al (1990) False positives: 9.9% of non-obese men and 1.8% of non-obese women. Smalley et al. (1990).
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