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BACKGROUND: Cervical cancer disparities exist in the United States with the highest incidence in Hispanic women and the highest mortality in Black women. Effective control of cervical cancer in the population requires targeted interventions tailored to community composition in terms of race, ethnicity, and social determinants of health (SDOH). METHODS: Using cancer registry and SDOH data, geospatial hot spot analyses were carried out to identify statistically significant neighborhood clusters with high numbers of cervical cancer cases within the catchment area of an NCI-Designated Cancer Center. The locations, racial and ethnic composition, and SDOH resources of these hot spots were used by the center's community outreach and engagement office to deploy mobile screening units (MSU) for intervention in communities with women facing heightened risk for cervical cancer. RESULTS: Neighborhood hot spots with high numbers of cervical cancer cases in south Florida largely overlap with locations of poverty. Cervical cancer hot spots are associated with a high percentage of Hispanic cases and low SDOH status, including low income, housing tenure, and education attainment. CONCLUSIONS: A geospatially referenced cancer surveillance platform integrating cancer registry, SDOH, and cervical screening data can effectively identify targets for cervical cancer intervention in neighborhoods experiencing disparities. IMPACT: Guided with a data-driven surveillance system, MSUs proactively bringing prevention education and cervical screening to communities with more unscreened, at-risk women are an effective means for addressing disparities associated with cervical cancer control.
RESUMEN
Abstract The objective of this study was to assess the impact of local health department (LHD) expenditures on population health measures using counties as the unit of analysis. An observational research design is used to examine whether public health benefits are associated with higher levels of public health funding. Linear probability multivariate regression models with the use of local level cross-sectional and panel data are employed. A 1-year and a 2-year lag structure are also used to quantify the longer term public health effects of changes in LHD expenditures. Analyses were performed at the county level using local data representing 2120 LHDs, covering 48 US states. Expenditure data from the National Association of County and City Health Officials Profile Surveys and public health measures from County Health Rankings Annual Reports are used. Four public health measures are examined-obesity prevalence, sexually transmitted diseases, diabetes prevalence, and human immunodeficiency virus prevalence. Results from cross-sectional, pooled ordinary least squares, and panel data with fixed effects reveal that increased LHD expenditures per capita were not associated with any of the population health outcomes studied. Multivariate linear regression results using a 1- and 2-year lag structure reveal similar results: funding was not significantly predictive of better public health outcomes. The study design did not control for the potential endogeneity of public health funding. More detailed data and robust research approaches are needed to disentangle the effect and effectively answer whether increased public funding translates to improved population health.