Financial hardship and mortality among older adults using the 1996-2004 Health and Retirement Study

Ann Epidemiol. 2009 Dec;19(12):850-7. doi: 10.1016/j.annepidem.2009.08.003.


Purpose: We investigated the effect of financial hardship on mortality risk in a community-dwelling sample of adults 50 years of age and olderin the United States.

Method: The 1996 Health and Retirement Study cohorts were followed prospectively to 2004 (N = 8,377). Gender-stratified grouped Cox models were used to estimate the difference in the relative risk (RR) of mortality between a specific number of financial hardships (one, two, or three or more) and no hardships; and the predictive utility of each individual financial hardship for mortality during the follow-up period.

Results: Gender-stratified models adjusted for demographics, socioeconomic characteristics, and functional limitations in 1996 showed that women reporting one (hazard ratio [HR] = 1.42; 95% confidence interval [CI]: 1.05-1.92) or three or more (HR = 1.60; 95% CI: 1.05-2.46) and men reporting two (HR = 1.80; 95% CI: 1.21-2.69) financial hardships had a substantially higher probability of mortality compared to those reporting no financial hardships. Individual financial hardships that predicted mortality in fully adjusted models for women included receiving Medicaid (HR = 2.23; 95% CI: 1.68-2.98) and for men receiving Medicaid (HR = 2.11; 95% CI: 1.57-2.84) and receiving food stamps (HR = 1.59; 95% CI: 1.09-2.33).

Conclusions: These findings suggest that over and above the influence of traditional measures of socioeconomic status, financial hardship exerts an influence on the risk of mortality among older adults and that the number and type of hardships important in predicting mortality may differ for men and women.

MeSH terms

  • Aged
  • Female
  • Geriatric Assessment
  • Health Surveys*
  • Humans
  • Male
  • Medicaid
  • Middle Aged
  • Mortality*
  • Poverty*
  • Proportional Hazards Models
  • Prospective Studies
  • Retirement / economics*
  • Retirement / statistics & numerical data
  • Risk
  • Sex Factors
  • United States / epidemiology