An instrumental variables approach to measuring the effect of body weight on employment disability

Health Serv Res. 2000 Dec;35(5 Pt 2):1159-79.

Abstract

Objective: To measure the effect of body weight on employment disability.

Data sources: Female respondents to the National Longitudinal Survey of Youth (NLSY), a nationally representative sample of American youth, surveyed from 1979 to 1998, merged with data from the child sample of the NLSY.

Study design: A series of probit models and probit models with instrumental variables is estimated with the goal of measuring the effect of body weight on employment disability. The two outcomes of interest are whether a woman reports that her health limits the amount of work that she can do for pay, and whether she reports that her health limits the kind of work that she can do for pay. The models control for factors that affect the probability of health limitations on employment, such as education, cognitive ability, income of other family members, and characteristics of children in the household. Self-reports of height and weight are corrected for reporting error.

Principal findings: All else being equal, heavier women are more likely to report employment disability. However, this overall correlation may be due to any or all of the following factors: weight causing disability, disability causing weight gain, or unobserved factors causing both. Instrumental variables estimates provide no evidence that body weight affects the probability of either type of employment disability.

Conclusions: This study finds no evidence that body weight causes employment disability. Instead, the observed correlation between heaviness and disability may be due to disability causing weight gain or unobservable factors causing both disability and weight gain.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Bias
  • Body Mass Index
  • Body Weight*
  • Data Interpretation, Statistical*
  • Disabled Persons / statistics & numerical data*
  • Employment / statistics & numerical data*
  • Female
  • Health Status*
  • Health Surveys
  • Humans
  • Longitudinal Studies
  • Models, Statistical*
  • Obesity / complications*
  • Occupations / statistics & numerical data
  • Regression Analysis*
  • United States
  • Women's Health*
  • Workload / statistics & numerical data