The impact of diabetes on employment and work productivity.
OBJECTIVE
The purpose of this study was to longitudinally examine the effect of diabetes on labor market outcomes.


METHODS
Using secondary data from the first two waves (1992 and 1994) of the Health and Retirement Study, we identified 7,055 employed respondents (51-61 years of age), 490 of whom reported having diabetes in wave 1. We estimated the effect of diabetes in wave 1 on the probability of working in wave 2 using probit regression. For those working in wave 2, we modeled the relationships between diabetic status in wave 1 and the change in hours worked and work-loss days using ordinary least-squares regressions and modeled the presence of health-related work limitations using probit regression. All models control for health status and job characteristics and are estimated separately by sex.


RESULTS
Among individuals with diabetes, the absolute probability of working was 4.4 percentage points less for women and 7.1 percentage points less for men relative to that of their counterparts without diabetes. Change in weekly hours worked was not statistically significantly associated with diabetes. Women with diabetes had 2 more work-loss days per year compared with women without diabetes. Compared with individuals without diabetes, men and women with diabetes were 5.4 and 6 percentage points (absolute increase), respectively, more likely to have work limitations.


CONCLUSIONS
This article provides evidence that diabetes affects patients, employers, and society not only by reducing employment but also by contributing to work loss and health-related work limitations for those who remain employed.
Tunceli
Kaan
K
Center for Health Services Research, Henry Ford Health System, Detroit, MI 48202, USA. ktuncel1@hfhs.org
Bradley
Cathy J
CJ
Nerenz
David
D
Williams
L Keoki
LK
Pladevall
Manel
M
Elston Lafata
Jennifer
J
D003920:Diabetes Mellitus / Q000191:economics* / Q000453:epidemiology / Q000523:psychology; D004526:Efficiency; D004651:Employment / Q000191:economics / Q000706:statistics & numerical data*; D005260:Female; D006304:Health Status; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D014481:United States / Q000453:epidemiology; D014937:Work / Q000191:economics* / Q000523:psychology