Geographic and Racial Variation in Premature Mortality in the U.S.: Analyzing the Disparities

Life expectancy at birth, estimated from United States period life tables, has been shown to vary systematically and widely by region and race. We use the same tables to estimate the probability of survival from birth to age 70 (S70), a measure of mortality more sensitive to disparities and more reliably calculated for small populations, to describe the variation and identify its sources in greater detail to assess the patterns of this variation. Examination of the unadjusted probability of S70 for each US county with a sufficient population of whites and blacks reveals large geographic differences for each race-sex group. For example, white males born in the ten percent healthiest counties have a 77 percent probability of survival to age 70, but only a 61 percent chance if born in the ten percent least healthy counties. Similar geographical disparities face white women and blacks of each sex. Moreover, within each county, large differences in S70 prevail between blacks and whites, on average 17 percentage points for men and 12 percentage points for women. In linear regressions for each race-sex group, nearly all of the geographic variation is accounted for by a common set of 22 socio-economic and environmental variables, selected for previously suspected impact on mortality; R2 ranges from 0.86 for white males to 0.72 for black females. Analysis of black-white survival chances within each county reveals that the same variables account for most of the race gap in S70 as well. When actual white male values for each explanatory variable are substituted for black in the black male prediction equation to assess the role explanatory variables play in the black-white survival difference, residual black-white differences at the county level shrink markedly to a mean of −2.4% (+/−2.4); for women the mean difference is −3.7% (+/−2.3)

Integrated assessment of global climate, air pollution, and dietary, malnutrition and obesity health impacts of food production and consumption between 2014 and 2018

Agriculture accounts for approximately 10% of global greenhouse gas emissions and is simultaneously associated with impacts on human health through food consumption, and agricultural air pollutant emissions. These impacts are often quantified separately, and there is a lack of modelling tools to facilitate integrated assessments. This work presents a new model that integrates assessment of agricultural systems on (i) human health indirectly through dietary, obesity and malnutrition health risks from food consumption, (ii) human health directly through exposure to air pollutants from agricultural emissions, and (iii) greenhouse gas emissions. In the model, national food demand is the starting point from which the livestock and crop production systems that meet this are represented. The model is applied for 2014–2018 to assess the robustness of the GHG emissions and health burden results that this integrated modelling framework produces compared to previous studies that have quantified these variables independently. Methane and nitrous oxide emissions globally in 2018 were estimated to be 129 and 4.4 million tonnes, respectively, consistent with previous estimates. Agricultural systems were also estimated to emit 44 million tonnes of ammonia. An estimated 4.1 million deaths were associated with dietary health risks, 6.0 million with overweight/obesity, and 730 thousand infant deaths from malnutrition, consistent with previous studies. Agricultural air pollutant emissions were estimated to be associated with 537 thousand premature deaths attributable to fine particulate matter (PM2.5) exposure, and 184 thousand premature deaths from methane-induced ground-level ozone. These health impacts provide substantial opportunities to design integrated strategies that mitigate climate change, and improve human health, and also highlight possible trade-offs that the expansion of agricultural production could have due to increased emissions. The model presented here provides for the consistent evaluation of the implications of different agricultural strategies to meet food demand while minimising human health and climate change impacts

Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions

Background: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. Objective: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. Methods: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. Results: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. Discussion: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice

Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions.

BACKGROUND: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. OBJECTIVE: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. METHODS: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. RESULTS: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. DISCUSSION: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745

Impacts of 21st century climate change on global air pollution-related premature mortality

Climate change modulates surface concentrations of fine particulate matter (PM2.5) and ozone (O-3), indirectly affecting premature mortality attributed to air pollution. We estimate the change in global premature mortality and years of life lost (YLL) associated with changes in surface O-3 and PM2.5 over the 21st century as a result of climate change. We use a global coupled chemistry-climate model to simulate current and future climate and the effect of changing climate on air quality. Epidemiological concentration-response relationships are applied to estimate resulting changes in premature mortality and YLL. The effect of climate change on air quality is isolated by holding emissions of air pollutants constant while allowing climate to evolve over the 21st century according to a moderate projection of greenhouse gas emissions (A1B scenario). Resulting changes in 21st century climate alone lead to an increase in simulated PM2.5 concentrations globally, and to higher (lower) O-3 concentrations over populated (remote) regions. Global annual premature mortality associated with chronic exposure to PM2.5 increases by approximately 100 thousand deaths (95 % confidence interval, CI, of 66-130 thousand) with corresponding YLL increasing by nearly 900 thousand (95 % CI, 576-1,128 thousand) years. The annual premature mortality due to respiratory disease associated with chronic O-3 exposure increases by +6,300 deaths (95 % CI, 1,600-10,400). This climate penalty indicates that stronger emission controls will be needed in the future to meet current air quality standards and to avoid higher health risks associated with climate change induced worsening of air quality over populated regions.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000326944000011&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Environmental SciencesMeteorology & Atmospheric SciencesSCI(E)EI17ARTICLE2239-25312

Climate change impacts on human health over Europe through its effect on air quality

Abstract This review examines the current literature on the effects of future emissions and climate change on particulate matter (PM) and O3 air quality and on the consequent health impacts, with a focus on Europe. There is considerable literature on the effects of climate change on O3 but fewer studies on the effects of climate change on PM concentrations. Under the latest Intergovernmental Panel on Climate Change (IPCC) 5th assessment report (AR5) Representative Concentration Pathways (RCPs), background O3 entering Europe is expected to decrease under most scenarios due to higher water vapour concentrations in a warmer climate. However, under the extreme pathway RCP8.5 higher (more than double) methane (CH4) abundances lead to increases in background O3 that offset the O3 decrease due to climate change especially for the 2100 period. Regionally, in polluted areas with high levels of nitrogen oxides (NOx), elevated surface temperatures and humidities yield increases in surface O3 – termed the O3 climate penalty – especially in southern Europe. The O3 response is larger for metrics that represent the higher end of the O3 distribution, such as daily maximum O3. Future changes in PM concentrations due to climate change are much less certain, although several recent studies also suggest a PM climate penalty due to high temperatures and humidity and reduced precipitation in northern mid-latitude land regions in 2100. A larger number of studies have examined both future climate and emissions changes under the RCP scenarios. Under these pathways the impact of emission changes on air quality out to the 2050s will be larger than that due to climate change, because of large reductions in emissions of O3 and PM pollutant precursor emissions and the more limited climate change response itself. Climate change will also affect climate extreme events such as heatwaves. Air pollution episodes are associated with stagnation events and sometimes heat waves. Air quality during the 2003 heatwave over Europe has been examined in numerous studies and mechanisms for enhancing O3 have been identified. There are few studies on health effects associated with climate change impacts alone on air quality, but these report higher O3-related health burdens in polluted populated regions and greater PM2.5 health burdens in these emission regions. Studies that examine the combined impacts of climate change and anthropogenic emissions change under the RCP scenarios report reductions in global and European premature O3-respiratory related and PM mortalities arising from the large decreases in precursor emissions. Under RCP 8.5 the large increase in CH4 leads to global and European excess O3-respiratory related mortalities in 2100. For future health effects, besides uncertainty in future O3 and particularly PM concentrations, there is also uncertainty in risk estimates such as effect modification by temperature on pollutant-response relationships and potential future adaptation that would alter exposure risk