Climatic conditions and human mortality: spatial and regional variation in the United States

Abstract

Previous research on climatic conditions and human mortality in the United States has three gaps: largely ignoring social conditions, lack of nationwide focus, and overlooking potential spatial variations. Our goal is to understand whether climatic conditions contribute to mortality after considering social conditions and to investigate whether spatial non-stationarity exists in these factors. Applying geographically weighted regression to a unique nationwide county-level dataset, we found that (1) net of other factors, average July temperatures are positively (detrimentally) associated with mortality while January temperatures mainly have a curvilinear relationship, (2) the mortality-climatic condition associations are spatially non-stationary, (3) the relationships between social conditions (e.g., social capital) and mortality are stable geographically, and (4) without a spatial approach to understanding the environment-mortality relationship, important spatial variations are overlooked. Our findings suggest that a universal approach to coping with the relationships between rapid climate changes and health may not be appropriate and effective.

The role of homelessness community based organizations during COVID‐19

“…Exposure to severe weather, not presidentially declared disasters, can result in injury or death for the pre‐disaster homeless. Specifically, extreme heat can increase the potential for heat stroke, dehydration, and exacerbate cardiovascular renal and respiratory conditions (Cagle, 2009; Harvey, 2018; Otto et al, 2017; Yang & Jensen, 2017). Gender, health, age, and race also increase vulnerability, mortality and morbidity in the predisaster homeless in extreme heat events (Cagle, 2009; Harvey, 2018).…”

Local modelling of U.S. mortality rates: A multiscale geographically weighted regression approach

“…However, these studies focus on the spatial variation in mortality rates, not the determinants of these rates. More recently, Yang, Noah, and Shoff (2015) and Sparks and Sparks (2010) have examined explicitly spatial components of mortality such as the degree of spatial dependency in such rates or the presence of observed spatial relationships in mortality rates, whereas Yang and Jensen (2017) and Chen, Deng, Yang, and Matthews (2012) applied variants of the GWR model towards U.S. mortality. Though these models provide a preliminary exploration of the spatially varying effect of the determinants of mortality, this study goes further by investigating the presence of spatial nonstationarity causing the determinants of mortality rates to vary across space, placing specific attention to the spatial scale over which these relationships vary.…”

Factors That Influence Climate Change-Related Mortality in the United States: An Integrative Review

“…People living in northeastern U.S., especially Massachusetts, New Jersey, and New York, are also more vulnerable to heat-related mortality as this area is more densely populated and contains more metropolitan areas than the southern regions [14,75]. During a heatwave, an increase in average temperature of 1 • F was associated with a 4.39% increase in the relative risk of mortality in the Northeast and a 3.22% increase in the Midwest, making the Northeast the region with an average of 2.50% greater risk of daily mortality during a heatwave [18].…”

“…While most research has focused on how specific aspects of climate change (heat waves, extreme weather events, flooding, etc.) have affected mortality, few studies give an in-depth analysis of the scope of climate's effect on factors that influence climate changerelated mortality [3,13,14]. It is important to have a comprehensive understanding of the collective factors that influence climate change mortality to understand the impacts on human health, thus we are examining the climate change-related factors that lead to mortality.…”