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.
Minigrants can increase local public health capacity to address climate change. Jurisdictions that wish to utilize minigrant mechanisms to promote climate change adaptation and preparedness at the local level may benefit from the experience of the 6 states and 44 local health programs described.
Problem, research strategy, and findings: Florida's 2015 Peril of Flood Act requires that coastal localities incorporate sea level rise (SLR) planning policies into their comprehensive plans. We surveyed planners and reviewed more than 150 plans to determine how communities responded to the state mandate along three domains: planning intelligence, SLR responses, and collaboration. We learned that the mandate spurred SLR planning, but that local SLR planning responses varied widely, ranging from complacent compliance to progressive planning responses. Further research is needed to clarify underlying motivators for these varied responses, as well as connections between policy adoption and implementation.Takeaway for practice: Flexible mandates allow for discretion in how localities respond to complex, ever-changing, long-term, and uncertain phenomena like climate change and SLR. Commitment to addressing these challenges can be bolstered by state mandates that provide political cover and an impetus to move adaptation planning forward. Such flexibility can lead to inconsistent and vague policies. Thus, mandates can spur local policy adoption but cannot ensure substantive responses to climate change. Meaningful responses to climate change adaptation still depend heavily on local commitment, capacity, and competence of planners.
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