Tobacco Induced Diseases (Jan 2019)
The association of neighborhood-level social class and tobacco consumption with adverse lung cancer characteristics in Maryland
Abstract
Introduction Although both active tobacco use and passive tobacco exposure are well-established as being risk factors for lung cancer, it is challenging to measure tobacco-related exposures at the population level, while considering other factors (gender, race, socioeconomic status) that may modify the relationship between tobacco and lung cancer. Moreover, research to date has focused primarily on relationships between tobacco and endpoints of lung cancer incidence or mortality. Tobacco’s role in disease progression, through association with important disease characteristics such as tumor histological type and grade, and stage of disease at diagnosis, has been less well examined. Methods This research examines associations between area-level tobacco use and social class, as well as individual gender, race and age, and three adverse disease characteristics (tumor type, grade and stage) among incident cases of lung cancer reported to the Maryland Cancer Registry in 2000. Cases were geocoded by residential address. Multi-level logistic regression models included Census block group-level estimates of per capita tobacco spending, from Consumer Expenditure Survey data, and a 4-item social class index, from Census estimates of rates of high school graduation, employment, white collar occupation, and per capita income. Results Analyses of 3223 cases found no significant differences by race, however, results differed by gender. Lower block-group social class and higher tobacco spending were associated with squamous and small cell histological types and poorly differentiated or undifferentiated tumor grade. However, for later stage at diagnosis (SEER stages 2–7), both higher social class and greater tobacco spending were protective, especially for women, suggesting women in high tobacco use communities may benefit from early detection. Conclusions Results support using area-level behavioral data as tools for identifying high risk communities suitable for more resource-intensive research or interventions. Findings also suggest that area-level social resources are consistent drivers of lung cancer disparities, and merit continued research attention.
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