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ABSTRACT
Objectives. This study evaluated the relative gross and net predictive value of multiple socioeconomic status indicators for the likelihood of undergoing hysterectomy.
Methods. Data from a sample of Wisconsin Longitudinal Study women respondents (n = 3326) followed for 35 years were analyzed by means of multivariate logistic regression.
Results. Women's own higher occupational status and greater family net worth were significant net predictors of a lower likelihood of hysterectomy. Women's own education was a significant bivariate predictor. Mental ability did not account for the education effect.
Conclusions. Higher education's association with a lower rate of hysterectomy is not due to ability, but to the opportunities that moreeducated women have for higherstatus employment and its healthrelated benefits. Measures of women's own occupational status should be included in future health surveys. (Am J Public Health. 1997;87:15071514)
Introduction
Women of lower socioeconomic status (SES) are more likely than higherSES women to undergo a hysterectomy.,2 This association is consistent with a substantial accumulation of evidence that lower SES is associated with poorer health-related outcomes overall for both women and men.3-io Hysterectomy brings more than one in three American women into major surgery by age 60. This rate of uterus removal far exceeds that of any other country in the developed world.--l4 Significant regional hysterectomy rate differences have also been noted in the United States" as well as England.ls
Only about 11% of hysterectomies in the United States are performed because of cancer of the uterus. The vast majority of uterine removal takes place for conditions that can also be managed by means of other techniques.**ib*17 This fact, along with marked national and regional rate variation, suggests that social as well as biological processes are important determinants of hysterectomy.
Different measures of SES-for example, income, education, and occupational status-yield a roughly similar picture of health-related inequalities. Yet there is considerable public health debate about which measures of SES show the largest net associations with health and health care utilization and whether it is important to evaluate more than one measure of SES when looking at SES and health-related differentials.'>22 It is also questionable whether the same SES measures are the most important predictors of health-related outcomes for different population groups-for example, women vs men, nonelderly vs...