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Florida Neighborhood Analysis of Societal Determinants and their Relationship to Life Expectancy Rates

Authors: Bertram Melix*, Florida State University, Christopher K. Uejio, Geography Department Florida State University
Topics: Medical and Health Geography, Spatial Analysis & Modeling
Keywords: Health Geography, Life Expectancy, Social Determinants of Health, Social Vulnerability, Spatial Statistics
Session Type: Paper
Presentation File: No File Uploaded

Social determinants (SDOH) of health, or local conditions where people work, live, and age contribute to differences in life expectancy (LE) rates. A small portion of papers have analyzed these relationships at the neighborhood level as opposed to the county level. Both, the social determinants of health and the social vulnerability literature were reviewed to identify relevant risk factors. LE was calculated from mortality records for Florida from 2009-2013. A spatial Durbin error model was used to quantify the direction and magnitude for each of our risk factors. The SDEM contains a spatial error term and provides estimates for both local and neighborhood impacts of risk factors on LE. This methodology controls for remaining spatial auto-correlation between census tracts. Risk factors that were related to an increase in LE, include % of the population who identify as Asian, Black, and Hispanic, % households earning over $200,000/year, % age dependent populations (% population < 5 years old and % population > 65), and population density. Conversely, factors that exhibited significant negative LE associations were % of population who identify as Native American, % population with less than high school education, % with no automobile, % mobile homes, % females, % female headed households, % nursing home residents, and % uninsured. The results shed light on risk factors that contribute to unequal life expectancy rates in Florida. Identifying important risk factors for life expectancy can enable public health researchers to better target health interventions to reduce local health disparities.

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