Environmental Predictors of US County Mortality Patterns on a National Basis

Abstract

A growing body of evidence has found that mortality rates are positively correlated with social inequalities, air pollution, elevated ambient temperature, availability of medical care and other factors. This study develops a model to predict the mortality rates for different diseases by county across the US. The model is applied to predict changes in mortality caused by changing environmental factors. A total of 3,110 counties in the US, excluding Alaska and Hawaii, were studied. A subset of 519 counties from the 3,110 counties was chosen by using systematic random sampling and these samples were used to validate the model. Step-wise and linear regression analyses were used to estimate the ability of environmental pollutants, socio-economic factors and other factors to explain variations in county-specific mortality rates for cardiovascular diseases, cancers, chronic obstructive pulmonary disease (COPD), all causes combined and lifespan across five population density groups. The estimated models fit adequately for all mortality outcomes for all population density groups and, adequately predicted risks for the 519 validation counties. This study suggests that, at local county levels, average ozone (0.07 ppm) is the most important environmental predictor of mortality. The analysis also illustrates the complex inter-relationships of multiple factors that influence mortality and lifespan, and suggests the need for a better understanding of the pathways through which these factors, mortality, and lifespan are related at the community level.

Racial Residential Segregation, Perceived Neighborhood Conditions, and Self‐Rated Health: The Case of Houston, Texas

“…This provides support for our second hypothesis and the second pathway (Path B) in our conceptual model. Again, this is in keeping with past work that has linked neighborhood disorder and environmental quality to a variety of poor health outcomes (Augustin et al ; Barber et al ; Bowling et al ; Brewer et al ; Chan et al ; Chang ; Chang et al ; Payne‐Sturges and Gee ; Robinette et al ; Surratt et al ; Wen et al ).…”

“…Prior research has established a link between several measures of neighborhood disorder—including perceptions of trash, vandalism, noise, and crime in a neighborhood—and poor health outcomes—including cardiovascular disease (Augustin et al ; Barber et al ), cardiometabolic risk (Robinette, Charles, and Gruenewald ), medication nonadherence (Surratt et al ), high body mass index (BMI) (Chang ; Chang et al ), overall self‐rated health (Bowling et al ), and mortality among older adults (Wen et al ). Similarly, environmental quality has been linked to a wide array of poor health outcomes, including greater mortality rates (Chan et al ; Payne‐Sturges and Gee ), preterm birth (Lorch and Enlow ), cancer risk (Chakraborty, Collins, and Grineski ; Rice et al ), and both juvenile and adult asthma (Brewer et al ; Clark, Millet, and Marshall ; Payne‐Sturges and Gee ). The mechanisms behind these relationships include aesthetic appeal of an environment, perceived safety of a neighborhood, and chronic stress––all of which may influence individual health behaviors and processes.…”

Exploring the Nexus of Energy Burden, Social Capital, and Environmental Quality in Shaping Health in US Counties

“…Decades of research have firmly established that environmental quality is a consistent determinant of health and that environmental quality is a major concern for both public health officials and the general public in the US. [ 44 , 45 , 46 ]. An extensive body of research has demonstrated the adverse health outcomes associated with poor environmental quality (in particular, air pollution exposure, specifically PM 2.5 or particulate matter ≤ 2.5 in aerodynamic diameter) is an important predictor of health levels [ 47 , 48 , 49 , 50 , 51 , 52 ].…”

Two Mechanisms: The Role of Social Capital and Industrial Pollution Exposure in Explaining Racial Disparities in Self-Rated Health

“…Furthermore, while Hispanics have on average less exposure to industrial air pollutants at a national-level, as they tend to live in areas with lower than the national average, they do face higher exposure than Whites within the cities in which they live [19]. Studies examining the health effects of neighborhood-level pollution have shown being in these areas is associated with worse cognitive outcomes [20], greater rates of diabetes [21], greater rate of hospital admissions [22], and higher mortality and morbidity generally [23]. However, only a small number of these studies have examined the role these exposures have on the racial-gap in health, with very few to none controlling for individual-level covariates in a nationally representative sample in the U.S. [24].…”