Environmental Predictors of US County Mortality Patterns on a National Basis

The influence of residential greenness on mortality in the Asia-Pacific region: a systematic review and meta-analysis

AIMS

To critically appraise the evidence of the impact of exposure to salutogenic green environment on mortality, which is an important endpoint in epidemiological and clinical studies.

METHODS

We searched for studies published and indexed in three databases (PubMed, AMED, and CINAHL Plus) from inception until 31 March 2020, complemented with a search of cited literature for articles describing the effects of greenness on mortality in Asia-Pacific region. Eligible articles were screened and data were extracted independently by two reviewers. A random-effects model was utilised to obtain pool hazard ratio (HR) and risk ratio of all-cause mortality outcome.

RESULTS

The search identified 3239 studies, of which 20 studies reporting 133,363 participants from longitudinal cohort studies and 202 million people from population-based prevalence studies were included in the review. The majority of the studies (60%) were conducted in high-income countries in Asia-Pacific. All participants of the longitudinal cohort studies were aged 60 years or older, whereas the prevalence studies involved people of all age groups. A significant protective association of green environment exposure with all-cause mortality was reported in 18 studies. Pooled results from five studies showed increased level of greenness exposure was associated with a significant decrease in all-cause mortality (pooled HR = 0.97; 95% confidence interval (CI) = 0.93 to 1.02; p < 0.01; I²= 87.8%). Meta-analysis of total number of deaths in different quartiles of green spaces noted decreased risks of mortality with all causes of death with increased surrounding greenness.

CONCLUSIONS

Some limited evidence suggests that populations exposed to the greener environment have a lower risk of mortality, implying the potential role of greenness in increasing longevity. Further studies with standardised design and outcome reporting should be conducted in low- and middle-income countries and in populations of low socioeconomic status to glean more generalisable and complete evidence for public health policy implications.

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

The United States spends more on health care than any other OECD country, yet the nation's health is declining. Recent research has identified multiple sources for this decline, including one's position in social and economic structures, environmental quality, and individual and collective social capital. This paper assesses the primary hypotheses that the health effects of household energy burden, social capital and environmental quality on aggregated community health levels remain while controlling for other determinants. The analysis moves beyond prior research by integrating multiple secondary data sources to assess those effects across US counties. Three indicators of public health are analyzed (premature mortality, self-reported health, and life expectancy). The county-level energy burden is measured by the percent of household income spent on housing energy bills for low- and moderate-income households. In addition to energy burden, social capital, environmental quality and other determinants are included in the analysis. The results produced by multivariate regression models support the primary hypotheses, even while a number of control variables also have a significant effect on health. The paper concludes that public health is associated with a complex nexus of factors, including environmental quality and social capital, and that energy burden needs to be among the considerations.

Using Census Data to Understand County-Level Differences in Overall Drug Mortality and Opioid-Related Mortality by Opioid Type

Objectives. To examine associations of county-level demographic, socioeconomic, and labor market characteristics on overall drug mortality rates and specific classes of opioid mortality. Methods. We used National Vital Statistics System mortality data (2002-2004 and 2014-2016) and county-level US Census data. We examined associations between several census variables and drug deaths for 2014 to 2016. We then identified specific classes of counties characterized by different levels and rates of growth in mortality from specific opioid types between 2002 to 2004 and 2014 to 2016. We ran multivariate and multivariable regression models to predict probabilities of membership in each "opioid mortality class" on the basis of county-level census measures. Results. Drug mortality rates overall are higher in counties characterized by more economic disadvantage, more blue-collar and service employment, and higher opioid-prescribing rates. High rates of prescription opioid overdoses and overdoses involving both prescription and synthetic opioids cluster in more economically disadvantaged counties with larger concentrations of service industry workers. High heroin and "syndemic" opioid mortality counties (high rates across all major opioid types) are more urban, have larger concentrations of professional workers, and are less economically disadvantaged. Syndemic opioid counties also have greater concentrations of blue-collar workers. Conclusions. Census data are essential tools for understanding the importance of place-level characteristics on opioid mortality. Public Health Implications. National opioid policy strategies cannot be assumed universally applicable. In addition to national policies to combat the opioid and larger drug crises, emphasis should be on developing locally and regionally tailored interventions, with attention to place-based structural economic and social characteristics.

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

This study provides an empirical test of two mechanisms (social capital and exposure to air pollution) that are theorized to mediate the effect of neighborhood on health and contribute to racial disparities in health outcomes. To this end, we utilize the Social Capital Benchmark Study, a national survey of individuals nested within communities in the United States, to estimate how multiple dimensions of social capital and exposure to air pollution, explain racial disparities in self-rated health. Our main findings show that when controlling for individual-confounders, and nesting within communities, our indicator of cognitive bridging, generalized trust, decreases the gap in self-rated health between African Americans and Whites by 84%, and the gap between Hispanics and Whites by 54%. Our other indicator of cognitive social capital, cognitive linking as represented by engagement in politics, decreases the gap in health between Hispanics and Whites by 32%, but has little impact on African Americans. We also assessed whether the gap in health was explained by respondents' estimated exposure to toxicity-weighted air pollutants from large industrial facilities over the previous year. Our results show that accounting for exposure to these toxins has no effect on the racial gap in self-rated health in these data. This paper contributes to the neighborhood effects literature by examining the impact that estimated annual industrial air pollution, and multiple measures of social capital, have on explaining the racial gap in health in a sample of individuals nested within communities across the United States.