Abstract

BackgroundBreast cancer is the leading cause of cancer death in Israeli women. Previous studies found socioeconomic status and other risk factors impact breast cancer outcomes. The ultra-orthodox community is characterized by a longer life expectancy, lower rates of mammography performance, higher fertility rates and other sociodemographic variables that may be related to breast cancer mortality. This study examined disparities in breast cancer mortality between ultra-Orthodox and non-ultra-Orthodox Israeli women. MethodsThis retrospective cohort study for breast cancer mortality included the all Jewish Israeli citizens women born between 1940 and 1960 and lived in communities with over 20,000 residents (n = 628,617). Data was collected from various sources, monitoring a period of 31 years; for each participants, their sociodemographic characteristics were compiled from the population registry, the tax authority, the education registry, and the Central Bureau of Statistics (CBS). Variables included religiosity, age, marital status, children, origin, education, and income. Multivariable Cox models evaluated predictors of mortality. ResultsOf the 628,617 women in the study, 29,611 were ultra-Orthodox. Ultra-Orthodox women had higher marriage rates, more children, and lower secular education and income. Mortality was 108.8/100,000 overall, lower among ultra-Orthodox (83.4/100,000) than non-ultra-Orthodox women (110.1/100,000) despite their risk factors. Using a multivariate model to evaluate the association between ultra-Orthodoxy and breast cancer mortality, the study found higher breast cancer mortality rate among non-ultra-Orthodox women compared to ultra-Orthodox women (HR = 1.491; 99% CI = 1.232, 1.804). Associations with sociodemographic variables were different for each group. ConclusionsAlthough ultra-Orthodox women have socioeconomic risk factors, breast cancer mortality was lower than non-ultra-Orthodox women. Further research on potential cultural and religious factors influencing mortality is warranted. These findings highlight the importance of evaluating predictors within specific populations.

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