Florida neighborhood analysis of social determinants and their relationship to life expectancy

Abstract Background Social determinants of health (SDOH) contribute to unequal life expectancy (LE). Only a handful of papers have analyzed these relationships at the neighborhood level as opposed to the county level. This study draws on both the SDOH and social vulnerability literature to identify...

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Bibliographic Details
Main Authors: Bertram L. Melix, Christopher K. Uejio, Kristina W. Kintziger, Keshia Reid, Chris Duclos, Melissa M. Jordan, Tisha Holmes, Jessica Joiner
Format: Article
Language:English
Published: BMC 2020-05-01
Series:BMC Public Health
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Online Access:http://link.springer.com/article/10.1186/s12889-020-08754-x
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Summary:Abstract Background Social determinants of health (SDOH) contribute to unequal life expectancy (LE). Only a handful of papers have analyzed these relationships at the neighborhood level as opposed to the county level. This study draws on both the SDOH and social vulnerability literature to identify relevant factors affecting LE. Methods LE was calculated from mortality records for Florida from 2009 to 2013 for 3640 census tracts with reliable estimates. A spatial Durbin error model (SDEM) quantified the direction and magnitude of the factors to LE. The SDEM contains a spatial error term and jointly estimates both local and neighborhood associations. This methodology controls for non-independence between census tracts to provide unbiased statistical estimates. Results Factors significantly related to an increase in LE, include percentage (%) of the population who identify as Hispanic (beta coefficient [β]: 0.06, p-value [P] < 0.001) and % of age dependent populations (% population < 5 years old and % population > 65) (β: 0.13, P < 0.001). Conversely, the following factors exhibited significant negative LE associations, % of households with no automobile (β: -0.05, P < 0.001), % of mobile homes (β: -0.02, P < 0.001), and % of female headed households (β: -0.11, P < 0.001). Conclusions Results from the SDEM demonstrate social vulnerability indicators account for additional geographic LE variability beyond commonly studied SDOH. Empirical findings from this analysis can help local health departments identify drivers of spatial health disparities at the local level.
ISSN:1471-2458