Effect of financial strain on mortality in community-dwelling older women.
OBJECTIVE
Although it is well established that low socioeconomic status is related to mortality, little research has focused on whether financial strain predicts mortality. Still less research has examined this question by race, despite the evidence that African Americans suffer earlier mortality and more financial strain at the same levels of socioeconomic status than their Caucasian counterparts. We examined the extent to which financial strain was associated with increased mortality risk in older women and whether the relationship differed by race.


METHODS
The sample was the Women's Health and Aging Studies I and II of community-dwelling older women aged 70 to 79. We used Cox proportional hazards models to estimate the effect of financial strain on 5-year mortality rates.


RESULTS
Women who reported financial strain were almost 60% more likely to die within 5 years independent of race, age, education, absolute income, health insurance status, and comorbidities (p <.001) than their counterparts who did not. Although race was not a predictor of mortality, the association between financial strain and mortality was stronger for African Americans than for Caucasians (p <.01).


CONCLUSIONS
For older women, financial strain may be a better predictor of mortality than annual income, particularly in the case of older African American women.
Szanton
Sarah L
SL
Johns Hopkins University School of Nursing, 525 N. Wolfe street #424, Baltimore, MD 21205, USA. sszanton@son.jhmi.edu
Allen
Jerilyn K
JK
Thorpe
Roland J
RJ
Seeman
Teresa
T
Bandeen-Roche
Karen
K
Fried
Linda P
LP
D001741:Black or African American / Q000706:statistics & numerical data; D000368:Aged; D015142:Baltimore / Q000453:epidemiology; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D008137:Longitudinal Studies; D008396:Maryland / Q000453:epidemiology; D009026:Mortality / Q000208:ethnology*; D015999:Multivariate Analysis; D011203:Poverty / Q000208:ethnology*; D016016:Proportional Hazards Models; D044465:White People / Q000706:statistics & numerical data; D016387:Women's Health / Q000208:ethnology*