Race/ethnicity, socioeconomic status, and lifetime morbidity burden in the women's health initiative: a cross-sectional analysis.
OBJECTIVE
We sought to assess the extent to which race/ethnicity and socioeconomic status (SES) are independently and jointly related to lifetime morbidity burden by comparing the impact of SES on lifetime morbidity among women of different racial/ethnic groups: white, black, Hispanic, American Indian/Alaska Native (AIAN), and Asian/Pacific Islander (API).


METHODS
Using baseline data from the Women's Health Initiative (WHI), a national study of 162,000 postmenopausal women, we measured lifetime morbidity burden using a modified version of the Charlson Index, and measured SES with educational attainment and household income. In multivariable simple polytomous logistic regression models, we first assessed the effect of SES on lifetime morbidity burden among women of each racial/ethnic group, then assessed the combined effect of race/ethnicity and SES.


RESULTS
Five percent of all women in the study population had high lifetime morbidity burden. Women with high lifetime morbidity were more likely to be AIAN or black; poor; less educated; divorced, separated, or widowed; past or current smokers; obese; uninsured or publicly insured. Lower SES was associated with higher morbidity among most women. The extent to which morbidity was higher among lower SES compared to higher SES women was about the same among Hispanic women and white women, but was substantially greater among black and AIAN women compared with white women.


CONCLUSIONS
This study demonstrates the importance of considering race/ethnicity and class together in relation to health outcomes.
Gold
Rachel
R
Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon 97227, USA. rachel.gold@kpchr.org
Michael
Yvonne L
YL
Whitlock
Evelyn P
EP
Hubbell
F Allan
FA
Mason
Ellen D
ED
Rodriguez
Beatriz L
BL
Safford
Monika M
MM
Sarto
Gloria E
GE
D001741:Black or African American / Q000706:statistics & numerical data; D000368:Aged; D001213:Asian / Q000706:statistics & numerical data; D002908:Chronic Disease / Q000453:epidemiology; D017281:Cost of Illness; D003430:Cross-Sectional Studies; D005006:Ethnicity / Q000706:statistics & numerical data*; D005260:Female; D015438:Health Behavior / Q000208:ethnology*; D006297:Health Services Accessibility; D006304:Health Status; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D006801:Humans; D007198:Indians, North American / Q000706:statistics & numerical data; D008875:Middle Aged; D011203:Poverty; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data; D016387:Women's Health