Publications by authors named "Michelle L Bell"

202 Publications

Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study.

Lancet Planet Health 2021 Jul;5(7):e415-e425

Department of Earth Sciences, University of Turin, Turin, Italy.

Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures.

Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature-mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature-mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division.

Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967-5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58-11·07) of all deaths (8·52% [6·19-10·47] were cold-related and 0·91% [0·56-1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60-87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000-03 to 2016-19, the global cold-related excess death ratio changed by -0·51 percentage points (95% eCI -0·61 to -0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13-0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe.

Interpretation: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios.

Funding: Australian Research Council and the Australian National Health and Medical Research Council.
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http://dx.doi.org/10.1016/S2542-5196(21)00081-4DOI Listing
July 2021

Temporal changes in associations between high temperature and hospitalizations by greenspace: Analysis in the Medicare population in 40 U.S. northeast counties.

Environ Int 2021 Jul 2;156:106737. Epub 2021 Jul 2.

School of the Environment, Yale University, New Haven, CT, USA. Electronic address:

Although research indicates health and well-being benefits of greenspace, little is known regarding how greenspace may influence adaptation to health risks from heat, particularly how these risks change over time. Using daily hospitalization rates of Medicare beneficiaries ≥65 years for 2000-2016 in 40 U.S. Northeastern urban counties, we assessed how temperature-related hospitalizations from cardiovascular causes (CVD) and heat stroke (HS) changed over time. We analyzed effect modification of those temporal changes by Enhanced Vegetation Index (EVI), approximating greenspace. We used a two-stage analysis including a generalized additive model and meta-analysis. Results showed that relative risk (RR) (per 1 °C increase in lag0-3 temperature) for temperature-HS hospitalization was higher in counties with the lowest quartile EVI (RR = 2.7, 95% CI: 2.0, 3.4) compared to counties with the highest quartile EVI (RR = 0.40, 95% CI: 0.14, 1.13) in the early part of the study period (2000-2004). RR of HS decreased to 0.88 (95% CI: 0.31, 2.53) in 2013-2016 in counties with the lowest quartile EVI. RR for HS changed over time in counties in the highest quartile EVI, with RRs of 0.4 (95% CI: -0.7, 1.4) in 2000-2004 and 2.4 (95% CI: 1.6, 3.2) in 2013-2016. Findings suggest that adaptation to heat-health associations vary by greenness. Greenspace may help lower risks from heat but such health risks warrant continuous local efforts such as heat-health plans.
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http://dx.doi.org/10.1016/j.envint.2021.106737DOI Listing
July 2021

Community concern and government response: Identifying socio-economic and demographic predictors of oil and gas complaints and drinking water impairments in Pennsylvania.

Energy Res Soc Sci 2021 Jun 24;76. Epub 2021 Apr 24.

Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven CT, 06510, United States.

Oil and gas development has led to environmental hazards and community concerns, particularly in relation to water supply issues. Filing complaints with state agencies enables citizens to register concerns and seek investigations. We evaluated associations between county-level socio-economic and demographic factors, oil and gas drilling, and three outcomes in Pennsylvania between 2004-2016: number of oil and gas complaints filed, and both the number and proportion of state investigations of water supply complaints yielding a confirmed water supply impairment (i.e., "positive determination"). We used hierarchical Bayesian Poisson and binomial regression analyses. From 2004-2016, 9,404 oil and gas-related complaints were filed, of which 4,099 were water supply complaints. Of those, 3,906 received investigations, and 215 yielded positive determinations. We observed a 47% increase in complaints filed per $10,000 increase in annual median household income (MHI) (Rate Ratio [RR]: 1.47, 95% credible interval [CI]: 1.09-1.96) and an 18% increase per 1% increase in educational attainment (RR: 1.18, 95% CI: 1.11-1.26). While the number of complaints filed did not vary by race/ethnicity, the odds of a complaint yielding a positive determination were 0.81 times lower in counties with a higher proportion of marginalized populations (Odds Ratio [OR]: 0.81 per 1% increase in percent Black, Asian, and Native American populations combined, 95% CI: 0.64-0.99). The odds of positive determinations were also lower in areas with higher income (OR per $10,000 increase in MHI: 0.35, 95% CI: 0.09-0.96). Our results suggest these relationships are complex and may indicate potential environmental and procedural inequities, warranting further investigation.
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http://dx.doi.org/10.1016/j.erss.2021.102070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192069PMC
June 2021

Temporal transition of racial/ethnic disparities in COVID-19 outcomes in 3108 counties of the United States: Three phases from January to December 2020.

Sci Total Environ 2021 Jun 1;791:148167. Epub 2021 Jun 1.

School of the Environment, Yale University, New Haven, CT, United States of America.

Early studies reported higher risk of COVID-19 outcomes for racial/ethnic minorities in the early phase of the pandemic in the United States. While the initial surge of COVID-19 was concentrated in some areas, COVID-19 became pervasive across the entire continent with high impacts in the northern region and central region in the end of 2020. With this geographical transition, we aim to investigate patterns of these racial/ethnic disparities over time. We assessed associations of percentage of race/ethnic minorities and racial segregation indexes with COVID-19 case and mortality rates in 3108 counties of the continental United States during the pandemic's early phase, second, and third phase (January 21-June 15, June 16-August 31, and September 1-December 18, 2020, respectively). We adjusted for population density, age, and sex. We tested whether time-varying associations were consistent across climate regions and explained by socioeconomic variables. In the early phase, counties with higher percentage of Black/African Americans and higher Black-White segregation had higher COVID-19 case and mortality rates. These associations decreased over time and reversed in the third phase. Associations between Hispanic and COVID-19 outcomes were positive in all periods, but more so early in the pandemic. Higher COVID-19 case rates for counties with higher non-Hispanic White population emerged in the third phase. These trends were similar across climate regions, and socioeconomic variables did not explain these trends. In summary, county-level racial/ethnic disparities of COVID-19 are not stationary but change over the course of the pandemic, suggesting complex social, cultural, and political influences.
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http://dx.doi.org/10.1016/j.scitotenv.2021.148167DOI Listing
June 2021

SPATIAL DISTRIBUTED LAG DATA FUSION FOR ESTIMATING AMBIENT AIR POLLUTION.

Ann Appl Stat 2021 Mar 18;15(1):323-342. Epub 2021 Mar 18.

School of Forestry and Environmental Studies, Department of Environmental Health Sciences, Yale University.

We introduce spatial (DLfuse) and spatiotemporal (DLfuseST) distributed lag data fusion methods for predicting point-level ambient air pollution concentrations, using, as input, gridded average pollution estimates from a deterministic numerical air quality model. The methods incorporate predictive information from grid cells surrounding the prediction location of interest and are shown to collapse to existing downscaling approaches when this information adds no benefit. The spatial lagged parameters are allowed to vary spatially/spatiotemporally to accommodate the setting where surrounding geographic information is useful in one area/time but not in another. We apply the new methods to predict ambient concentrations of eight-hour maximum ozone and 24-hour average PM at unobserved spatial locations and times, and compare the predictions with those from several state-of-the-art data fusion approaches. Results show that DLfuse and DLfuseST often provide improved model fit and predictive accuracy when the lagged information is shown to be beneficial. Code to apply the methods is available in the R package DLfuse.
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http://dx.doi.org/10.1214/20-aoas1399DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8189329PMC
March 2021

Impact of Changed Use of Greenspace during COVID-19 Pandemic on Depression and Anxiety.

Int J Environ Res Public Health 2021 05 29;18(11). Epub 2021 May 29.

School of the Environment, Yale University, New Haven, CT 06511, USA.

The COVID-19 pandemic has had devastating consequences for health, social, and economic domains, but what has received far less focus is the effect on people's relationship to vital ecological supports, including access to greenspace. We assessed patterns of greenspace use in relation to individual and environmental factors and their relationship with experiencing psychological symptoms under the pandemic. We conducted an online survey recruiting participants from social media for adults in Korea for September-December 2020. The survey collected data on demographics, patterns of using greenspace during the pandemic, and major depression (MD) and generalized anxiety disorder (GAD) symptoms. The Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder 2-item (GAD-2) were applied to identify probable cases of MD and GAD. A logistic regression model assessed the association decreased visits to greenspace after the outbreak compared to 2019 and probable MD and GAD. Among the 322 survey participants, prevalence of probable MD and GAD were 19.3% and 14.9%, respectively. High rates of probable MD (23.3%) and GAD (19.4%) were found among persons currently having job-related and financial issues. Of the total participants, 64.9% reported decreased visits to greenspace after the COVID-19 outbreak. Persons with decreased visits to greenspace had 2.06 higher odds (95% CI: 0.91, 4.67, significant at < 0.10) of probable MD at the time of the survey than persons whose visits to greenspace increased or did not change. Decreased visits to greenspace were not significantly associated with GAD (OR = 1.45, 95% CI: 0.63, 3.34). Findings suggest that barriers to greenspace use could deprive people of mental health benefits and affect mental health during pandemic; an alternative explanation is that those experiencing poor mental health may be less likely to visit greenspaces during pandemic. This implies the need of adequate interventions on greenspace uses under an outbreak especially focusing on how low-income populations may be more adversely affected by a pandemic and its policy responses.
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http://dx.doi.org/10.3390/ijerph18115842DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197797PMC
May 2021

Temperature-mortality relationship in North Carolina, USA: Regional and urban-rural differences.

Sci Total Environ 2021 Sep 11;787:147672. Epub 2021 May 11.

School of the Environment, Yale University, New Haven, CT, USA. Electronic address:

Background: Health disparities exist between urban and rural populations, yet research on rural-urban disparities in temperature-mortality relationships is limited. As inequality in the United States increases, understanding urban-rural and regional differences in the temperature-mortality association is crucial.

Objective: We examined regional and urban-rural differences of the temperature-mortality association in North Carolina (NC), USA, and investigated potential effect modifiers.

Methods: We applied time-series models allowing nonlinear temperature-mortality associations for 17 years (2000-2016) to generate heat and cold county-specific estimates. We used second-stage analysis to quantify the overall effects. We also explored potential effect modifiers (e.g. social associations, greenness) using stratified analysis. The analysis considered relative effects (comparing risks at 99th to 90th temperature percentiles based on county-specific temperature distributions for heat, and 1st to 10th percentiles for cold) and absolute effects (comparing risks at specific temperatures).

Results: We found null effects for heat-related mortality (relative effect: 1.001 (95% CI: 0.995-1.007)). Overall cold-mortality risk for relative effects was 1.019 (1.015-1.023). All three regions had statistically significant cold-related mortality risks for relative and absolute effects (relative effect: 1.019 (1.010-1.027) for Coastal Plains, 1.021 (1.015-1.027) for Piedmont, 1.014 (1.006-1.023) for Mountains). The heat mortality risk was not statistically significant, whereas the cold mortality risk was statistically significant, showing higher cold-mortality risks in urban areas than rural areas (relative effect for heat: 1.006 (0.997-1.016) for urban, 1.002 (0.988-1.017) for rural areas; relative effect for cold: 1.023 (1.017-1.030) for urban, 1.012 (1.001-1.023) for rural areas). Findings are suggestive of higher relative cold risks in counties with the less social association, higher population density, less green-space, higher PM lower education level, higher residential segregation, higher income inequality, and higher income (e.g., Ratio of Relative Risks 1.72 (0.68, 4.35) comparing low to high education).

Conclusion: Results indicate cold-mortality risks in NC, with potential differences by regional, urban-rural areas, and community characteristics.
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http://dx.doi.org/10.1016/j.scitotenv.2021.147672DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8214419PMC
September 2021

Air Pollution and COVID-19 Mortality in New York City.

Am J Respir Crit Care Med 2021 07;204(1):97-99

Yale University School of the Environment New Haven, Connecticut.

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http://dx.doi.org/10.1164/rccm.202010-3844LEDOI Listing
July 2021

Ambient carbon monoxide and daily mortality: a global time-series study in 337 cities.

Lancet Planet Health 2021 04;5(4):e191-e199

Environmental and Occupational Medicine, National Taiwan University and NTU Hospital, Taipei, Taiwan; National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan.

Background: Epidemiological evidence on short-term association between ambient carbon monoxide (CO) and mortality is inconclusive and limited to single cities, regions, or countries. Generalisation of results from previous studies is hindered by potential publication bias and different modelling approaches. We therefore assessed the association between short-term exposure to ambient CO and daily mortality in a multicity, multicountry setting.

Methods: We collected daily data on air pollution, meteorology, and total mortality from 337 cities in 18 countries or regions, covering various periods from 1979 to 2016. All included cities had at least 2 years of both CO and mortality data. We estimated city-specific associations using confounder-adjusted generalised additive models with a quasi-Poisson distribution, and then pooled the estimates, accounting for their statistical uncertainty, using a random-effects multilevel meta-analytical model. We also assessed the overall shape of the exposure-response curve and evaluated the possibility of a threshold below which health is not affected.

Findings: Overall, a 1 mg/m increase in the average CO concentration of the previous day was associated with a 0·91% (95% CI 0·32-1·50) increase in daily total mortality. The pooled exposure-response curve showed a continuously elevated mortality risk with increasing CO concentrations, suggesting no threshold. The exposure-response curve was steeper at daily CO levels lower than 1 mg/m, indicating greater risk of mortality per increment in CO exposure, and persisted at daily concentrations as low as 0·6 mg/m or less. The association remained similar after adjustment for ozone but was attenuated after adjustment for particulate matter or sulphur dioxide, or even reduced to null after adjustment for nitrogen dioxide.

Interpretation: This international study is by far the largest epidemiological investigation on short-term CO-related mortality. We found significant associations between ambient CO and daily mortality, even at levels well below current air quality guidelines. Further studies are warranted to disentangle its independent effect from other traffic-related pollutants.

Funding: EU Horizon 2020, UK Medical Research Council, and Natural Environment Research Council.
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http://dx.doi.org/10.1016/S2542-5196(21)00026-7DOI Listing
April 2021

Effect modification of greenness on temperature-mortality relationship among older adults: A case-crossover study in China.

Environ Res 2021 06 8;197:111112. Epub 2021 Apr 8.

School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA.

Background: Climate change exacerbates temperature-related mortality, but effects may vary by geographic characteristics. We hypothesize that higher greenness may mitigate temperature-related mortality, and that the effect may vary in different areas.

Objective: We examined how mortality among older adults in China was associated with temperature for 2000-2014, and how geolocation and residential greenness may modulate this association.

Methods: We used health data from the China Longitudinal Healthy Longevity Survey (CLHLS), and meteorological data from the Global Surface Summary of Day (GSOD) product by National Climate Data Center. We used a case-crossover study design with distributed nonlinear modeling to estimate mortality risks in relation to temperature, and stratified analysis by quartile of greenness. Greenness was estimated by Normalized Difference Vegetation Index (NDVI) from remote-sensed imagery. In addition to the national analysis, we also assessed three provinces (Jiangsu, Guangdong, and Liaoning) to examine differences by climatic regions.

Results: Extreme temperatures had a significant association with higher mortality, with regional differences. Findings from the national analysis suggest that individuals in the lowest quartile of greenness exposure had a ratio of relative risks (RRR) of 1.38 (0.79, 2.42) for mortality risk on extreme hot days at the 95th percentile compared to those at the 50th percentile, compared to those in the highest quartile, which means those residing in the lowest quartile of greenness had a 38% higher RR than those residing in the highest quartile of greenness, where RR refers to the risk of mortality on days at the 95th percentile of temperature compared to days at the 50th percentile. The RRR for the highest to lowest quartiles of greenness for mortality risk on extreme cold days at the 5th percentile compared to the 50th percentile was 2.08 (0.12, 36.2). In Jiangsu and Guangdong provinces, both the heat effects and cold effects were the lowest in the highest greenness quartile, and the results in Liaoning province were not statistically significant, indicating different regional effects of greenness on modulating the temperature-mortality relationship.

Discussion: We elucidated one pathway through which greenness benefits health by decreasing impact from extreme high temperatures. The effects of greenness differed by climatic regions. Policymakers should consider vegetation in the context of climate change and health.
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http://dx.doi.org/10.1016/j.envres.2021.111112DOI Listing
June 2021

Long-term Exposure to PM2.5 and Mortality for the Older Population: Effect Modification by Residential Greenness.

Epidemiology 2021 07;32(4):477-486

From the School of the Environment, Yale University, New Haven, CT.

Background: Although many studies demonstrated reduced mortality risk with higher greenness, few studies examined the modifying effect of greenness on air pollution-health associations. We evaluated residential greenness as an effect modifier of the association between long-term exposure to fine particles (PM2.5) and mortality.

Methods: We used data from all Medicare beneficiaries in North Carolina (NC) and Michigan (MI) (2001-2016). We estimated annual PM2.5 averages using ensemble prediction models. We estimated mortality risk per 1 μg/m3 increase using Cox proportional hazards modeling, controlling for demographics, Medicaid eligibility, and area-level covariates. We investigated health disparities by greenness using the Normalized Difference Vegetation Index with measures of urbanicity and socioeconomic status.

Results: PM2.5 was positively associated with mortality risk. Hazard ratios (HRs) were 1.12 (95% confidence interval (CI) = 1.12 to 1.13) for NC and 1.01 (95% CI = 1.00 to 1.01) for MI. HRs were higher for rural than urban areas. Within each category of urbanicity, HRs were generally higher in less green areas. For combined disparities, HRs were higher in low greenness or low SES areas, regardless of the other factor. HRs were lowest in high-greenness and high-SES areas for both states.

Conclusions: In our study, those in low SES and high-greenness areas had lower associations between PM2.5 and mortality than those in low SES and low greenness areas. Multiple aspects of disparity factors and their interactions may affect health disparities from air pollution exposures. Findings should be considered in light of uncertainties, such as our use of modeled PM2.5 data, and warrant further investigation.
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http://dx.doi.org/10.1097/EDE.0000000000001348DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8159868PMC
July 2021

Short term associations of ambient nitrogen dioxide with daily total, cardiovascular, and respiratory mortality: multilocation analysis in 398 cities.

BMJ 2021 03 24;372:n534. Epub 2021 Mar 24.

Department of Environmental Health, Portuguese National Institute of Health, Porto, Portugal.

Objective: To evaluate the short term associations between nitrogen dioxide (NO) and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide, using a uniform analytical protocol.

Design: Two stage, time series approach, with overdispersed generalised linear models and multilevel meta-analysis.

Setting: 398 cities in 22 low to high income countries/regions.

Main Outcome Measures: Daily deaths from total (62.8 million), cardiovascular (19.7 million), and respiratory (5.5 million) causes between 1973 and 2018.

Results: On average, a 10 μg/m increase in NO concentration on lag 1 day (previous day) was associated with 0.46% (95% confidence interval 0.36% to 0.57%), 0.37% (0.22% to 0.51%), and 0.47% (0.21% to 0.72%) increases in total, cardiovascular, and respiratory mortality, respectively. These associations remained robust after adjusting for co-pollutants (particulate matter with aerodynamic diameter ≤10 μm or ≤2.5 μm (PM and PM, respectively), ozone, sulfur dioxide, and carbon monoxide). The pooled concentration-response curves for all three causes were almost linear without discernible thresholds. The proportion of deaths attributable to NO concentration above the counterfactual zero level was 1.23% (95% confidence interval 0.96% to 1.51%) across the 398 cities.

Conclusions: This multilocation study provides key evidence on the independent and linear associations between short term exposure to NO and increased risk of total, cardiovascular, and respiratory mortality, suggesting that health benefits would be achieved by tightening the guidelines and regulatory limits of NO.
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http://dx.doi.org/10.1136/bmj.n534DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988454PMC
March 2021

Urban environments and COVID-19 in three Eastern states of the United States.

Sci Total Environ 2021 Jul 12;779:146334. Epub 2021 Mar 12.

School of the Environment, Yale University, New Haven, CT, USA. Electronic address:

The United States has the highest numbers of confirmed cases and deaths during the novel coronavirus disease 2019 (COVID-19) pandemic. Previous studies reported that urban residents are more vulnerable to the spread and mortality of COVID-19 than rural residents. However, the pathways through which urban environments affect COVID-19 spread and mortality are unclear. We collected daily data on the number of confirmed cases and deaths of COVID-19 from Mar. 01 to Nov. 16, 2020 for all 91 counties in New York, New Jersey, and Connecticut in the United States. We calculated the COVID-19 incidence %, daily reproduction number, and mortality %, then estimated the associations with urban environment indicators using regression models. COVID-19 outcomes were generally highest in areas with high population density, and this pattern was evident in the early period of epidemic. Among the area-level demographic variables, the percentage of Black or Hispanic residents showed the strongest positive association with COVID-19 outcomes. Higher risk of COVID-19 outcomes was also associated with higher percentage of overcrowded households, uninsured people, and income inequality. The percent elderly, sex ratio (the ratio of males to females), and greenness were negatively associated with risk of COVID-19 outcomes. The results of this study could indicate where resources are most needed.
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http://dx.doi.org/10.1016/j.scitotenv.2021.146334DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7952127PMC
July 2021

Multi-dimensional community characteristics in linking particulate matter pollution and cause-specific mortality: 72 communities of South Korea.

Environ Res 2021 05 6;196:110989. Epub 2021 Mar 6.

Interdisciplinary Program in Precision Public Health, Korea University, Seoul, Republic of Korea; Department of Environmental Health, Korea University, Seoul, Republic of Korea; School of Health Policy and Management, College of Health Science, Korea University, Seoul, Republic of Korea. Electronic address:

Concentration-response function for exposure to ambient particulate matter (PM) and mortality (i.e., relative risk, RR) may be inequal across communities by socioeconomic conditions. Investigation on specific mechanisms of this inequality regarding susceptibility to PM, beyond non-specific "socioeconomic conditions", would provide policy-relevant implications for tackling this inequality. However, such investigation via epidemiological studies is challenged by residual confounding by correlated mechanisms and different loss of life expectancy by PM exposures between communities. Here, we aimed to assess community characteristics including different aspects of socioeconomic deprivation, medical resources, health behaviors, air quality, and greenness in their relation to inequal RR for PM and cause-specific mortality in 72 municipalities in South Korea, 2006-2013, considering these challenges. We found that a 10 μg/m increase in PM on average across 46 days was associated with a 1.05% (95% CI: 0.24, 1.88) increase in all-cause mortality (ALL), 1.32% (95% CI: -0.29, 2.95) increase in cardiovascular mortality (CVD), and 6.47% (95% CI: 3.06, 10.00) increase in respiratory mortality (RES). The association between PM and mortality was higher in communities with higher ratio of SO to PM (ALL and RES), higher material deprivation (ALL, CVD, and RES), lower medical resources (CVD), higher prevalence of drinking (ALL and CVD), and lower prevalence of smoking (CVD and RES). Lag-structures showed smaller loss of life expectancy by PM exposures in communities with higher prevalence of smoking. Our findings suggest that PM-related health inequalities are shaped by a variety of mechanisms relating to susceptibility to PM exposures and different loss of life expectancy. Health policies controlling community characteristics may contribute to minimizing PM-related health inequalities in those perspectives.
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http://dx.doi.org/10.1016/j.envres.2021.110989DOI Listing
May 2021

Distribution of environmental justice metrics for exposure to CAFOs in North Carolina, USA.

Environ Res 2021 04 11;195:110862. Epub 2021 Feb 11.

School of the Environment, Yale University, New Haven, CT, USA.

Background: Several studies have reported environmental disparities regarding exposure to concentrated animal feeding operations (CAFOs). Public health implications of environmental justice from the intensive livestock industry are of great concern in North Carolina (NC), USA, a state with a large number and extensive history of CAFOs.

Objectives: We examined disparities by exposure to CAFOs using several environmental justice metrics and considering potentially vulnerable subpopulations.

Methods: We obtained data on permitted animal facilities from NC Department of Environmental Quality (DEQ). Using ZIP code level variables from the 2010 Census, we evaluated environmental disparities by eight environmental justice metrics (i.e., percentage of Non-Hispanic White, Non-Hispanic Black, or Hispanic; percentage living below the poverty level; median household income; percentage with education less than high school diploma; racial residential isolation (RI) for Non-Hispanic Black; and educational residential isolation (ERI) for population without college degree). We applied two approaches to assign CAFOs exposure for each ZIP code: (1) a count method based on the number of CAFOs within ZIP code; and (2) a buffer method based on the area-weighted number of CAFOs using a 15 km buffer.

Results: Spatial distributions of CAFOs exposure generally showed similar patterns between the two exposure methods. However, some ZIP codes had different estimated CAFOs exposure for the different approaches, with higher exposure when using the buffer method. Our findings indicate that CAFOs are located disproportionately in communities with higher percentage of minorities and in low-income communities. Distributions of environmental justice metrics generally showed similar patterns for both exposure methods, however starker disparities were observed using a buffer method.

Conclusions: Our findings of the disproportionate location of CAFOs provide evidence of environmental disparities with respect to race and socioeconomic status in NC and have implications for future studies of environmental and health impacts of CAFOs.
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http://dx.doi.org/10.1016/j.envres.2021.110862DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7987827PMC
April 2021

Alternative adjustment for seasonality and long-term time-trend in time-series analysis for long-term environmental exposures and disease counts.

BMC Med Res Methodol 2021 01 4;21(1). Epub 2021 Jan 4.

School of the Environment, Yale University, 195 Prospect Street, New Haven, CT, 06511, USA.

Background: Time-series analysis with case-only data is a prominent method for the effect of environmental determinants on disease events in environmental epidemiology. In this analysis, adjustment for seasonality and long-term time-trend is crucial to obtain valid findings. When applying this analysis for long-term exposure (e.g., months, years) of which effects are usually studied via survival analysis with individual-level longitudinal data, unlike its application for short-term exposure (e.g., days, weeks), a standard adjustment method for seasonality and long-term time-trend can extremely inflate standard error of coefficient estimates of the effects. Given that individual-level longitudinal data are difficult to construct and often available to limited populations, if this inflation of standard error can be solved, rich case-only data over regions and countries would be very useful to test a variety of research hypotheses considering unique local contexts.

Methods: We discuss adjustment methods for seasonality and time-trend used in time-series analysis in environmental epidemiology and explain why standard errors can be inflated. We suggest alternative methods to solve this problem. We conduct simulation analyses based on real data for Seoul, South Korea, 2002-2013, and time-series analysis using real data for seven major South Korean cities, 2006-2013 to identify whether the association between long-term exposure and health outcomes can be estimated via time-series analysis with alternative adjustment methods.

Results: Simulation analyses and real-data analysis confirmed that frequently used adjustment methods such as a spline function of a variable representing time extremely inflate standard errors of estimates for associations between long-term exposure and health outcomes. Instead, alternative methods such as a combination of functions of variables representing time can make sufficient adjustment with efficiency.

Conclusions: Our findings suggest that time-series analysis with case-only data can be applied for estimating long-term exposure effects. Rich case-only data such as death certificates and hospitalization records combined with repeated measurements of environmental determinants across countries would have high potentials for investigating the effects of long-term exposure on health outcomes allowing for unique contexts of local populations.
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http://dx.doi.org/10.1186/s12874-020-01199-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780665PMC
January 2021

Gender Differences in First and Corresponding Authorship in Public Health Research Submissions During the COVID-19 Pandemic.

Am J Public Health 2021 01 19;111(1):159-163. Epub 2020 Nov 19.

Michelle L. Bell and Kelvin C. Fong are with the School of the Environment, Yale University, New Haven, CT.

To investigate the rate of manuscript submission to a major peer-reviewed journal () by gender, comparing periods before and during the pandemic. We used data from January 1 to May 12, 2020, and defined the start of the pandemic period by country as the first date of 50 or more confirmed cases. We used an algorithm to classify gender based on first name and nation of origin. We included authors whose gender could be estimated with a certainty of at least 95%. Submission rates were higher overall during the pandemic compared with before. Increases were higher for submissions from men compared with women (41.9% vs 10.9% for corresponding author). For the United States, submissions increased 23.8% for men but only 7.9% for women. Women authored 29.4% of COVID-19-related articles. Our findings suggest that the pandemic exacerbated gender imbalances in scientific research.
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http://dx.doi.org/10.2105/AJPH.2020.305975DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750581PMC
January 2021

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

Environ Health Perspect 2020 11 10;128(11):115001. Epub 2020 Nov 10.

Department of Epidemiology and Biostatistics, School of Public Health, Seoul National University, Seoul, South Korea.

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.
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http://dx.doi.org/10.1289/EHP6745DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654632PMC
November 2020

Examining PM concentrations and exposure using multiple models.

Environ Res 2021 05 7;196:110432. Epub 2020 Nov 7.

School of the Environment, Yale University, New Haven, CT, USA.

Epidemiologic studies have found associations between fine particulate matter (PM) exposure and adverse health effects using exposure models that incorporate monitoring data and other relevant information. Here, we use nine PM concentration models (i.e., exposure models) that span a wide range of methods to investigate i) PM concentrations in 2011, ii) potential changes in PM concentrations between 2011 and 2028 due to on-the-books regulations, and iii) PM exposure for the U.S. population and four racial/ethnic groups. The exposure models included two geophysical chemical transport models (CTMs), two interpolation methods, a satellite-derived aerosol optical depth-based method, a Bayesian statistical regression model, and three data-rich machine learning methods. We focused on annual predictions that were regridded to 12-km resolution over the conterminous U.S., but also considered 1-km predictions in sensitivity analyses. The exposure models predicted broadly consistent PM concentrations, with relatively high concentrations on average over the eastern U.S. and greater variability in the western U.S. However, differences in national concentration distributions (median standard deviation: 1.00 μg m) and spatial distributions over urban areas were evident. Further exploration of these differences and their implications for specific applications would be valuable. PM concentrations were estimated to decrease by about 1 μg m on average due to modeled emission changes between 2011 and 2028, with decreases of more than 3 μg m in areas with relatively high 2011 concentrations that were projected to experience relatively large emission reductions. Agreement among models was closer for population-weighted than uniformly weighted averages across the domain. About 50% of the population was estimated to experience PM concentrations less than 10 μg m in 2011 and PM improvements of about 2 μg m due to modeled emission changes between 2011 and 2028. Two inequality metrics were used to characterize differences in exposure among the four racial/ethnic groups. The metrics generally yielded consistent information and suggest that the modeled emission reductions between 2011 and 2028 would reduce absolute exposure inequality on average.
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http://dx.doi.org/10.1016/j.envres.2020.110432DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8102649PMC
May 2021

Projections of excess mortality related to diurnal temperature range under climate change scenarios: a multi-country modelling study.

Lancet Planet Health 2020 11;4(11):e512-e521

Department of Earth Sciences, University of Turin, Turin, Italy.

Background: Various retrospective studies have reported on the increase of mortality risk due to higher diurnal temperature range (DTR). This study projects the effect of DTR on future mortality across 445 communities in 20 countries and regions.

Methods: DTR-related mortality risk was estimated on the basis of the historical daily time-series of mortality and weather factors from Jan 1, 1985, to Dec 31, 2015, with data for 445 communities across 20 countries and regions, from the Multi-Country Multi-City Collaborative Research Network. We obtained daily projected temperature series associated with four climate change scenarios, using the four representative concentration pathways (RCPs) described by the Intergovernmental Panel on Climate Change, from the lowest to the highest emission scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). Excess deaths attributable to the DTR during the current (1985-2015) and future (2020-99) periods were projected using daily DTR series under the four scenarios. Future excess deaths were calculated on the basis of assumptions that warmer long-term average temperatures affect or do not affect the DTR-related mortality risk.

Findings: The time-series analyses results showed that DTR was associated with excess mortality. Under the unmitigated climate change scenario (RCP 8.5), the future average DTR is projected to increase in most countries and regions (by -0·4 to 1·6°C), particularly in the USA, south-central Europe, Mexico, and South Africa. The excess deaths currently attributable to DTR were estimated to be 0·2-7·4%. Furthermore, the DTR-related mortality risk increased as the long-term average temperature increased; in the linear mixed model with the assumption of an interactive effect with long-term average temperature, we estimated 0·05% additional DTR mortality risk per 1°C increase in average temperature. Based on the interaction with long-term average temperature, the DTR-related excess deaths are projected to increase in all countries or regions by 1·4-10·3% in 2090-99.

Interpretation: This study suggests that globally, DTR-related excess mortality might increase under climate change, and this increasing pattern is likely to vary between countries and regions. Considering climatic changes, our findings could contribute to public health interventions aimed at reducing the impact of DTR on human health.

Funding: Korea Ministry of Environment.
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http://dx.doi.org/10.1016/S2542-5196(20)30222-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869581PMC
November 2020

Do fine particulate air pollution (PM) exposure and its attributable premature mortality differ for immigrants compared to those born in the United States?

Environ Res 2021 05 28;196:110387. Epub 2020 Oct 28.

Yale School of the Environment, Yale University, New Haven, CT, USA.

In the United States (US), immigrants constitute a considerable and growing proportion of the general population. Compared to the US-born, immigrants have differential health risks, and it is unclear if environmental exposures contribute. In this work, we estimated disparities between immigrants and the US-born in fine particulate matter (PM) exposure and attributable premature mortality, including by region of origin and time since immigration. With PM estimates from a validated model at ~1 km spatial resolution and residential Census tract population data, we calculated the annual area-weighted average PM exposure for immigrants overall, the US-born, and immigrants separately by geographic region of origin and time since immigration. We then calculated the premature mortality attributed to PM for each population group, assessing disparities by immigrant status in PM exposure and attributable premature mortality in the US as a whole and in each US county to evevaluate spatial heterogeneity. Overall, immigrants were exposed to slightly higher PM (0.36 μg/m, 3.8%) than the US-born. This exposure difference translates to 2.11 more premature deaths attributable to PM per 100,000 in population for immigrants compared to the US-born in 2010. Immigrant - US-born disparities in PM and attributable premature mortality were more severe among immigrants originating from Asia, Africa, and Latin America than those from Europe, Oceania, and North America. Disparities between immigrant groups by time since immigration were comparatively small. Sensitivity analyses using 2000 data and a non-linear set of PM attributable mortality coefficients identified similar patterns. Our findings suggest that environmental exposure disparities, such as in PM, may contribute to immigrant health disparities in the US.
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http://dx.doi.org/10.1016/j.envres.2020.110387DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8079555PMC
May 2021

Wildfires, Global Climate Change, and Human Health.

N Engl J Med 2020 11 9;383(22):2173-2181. Epub 2020 Oct 9.

From the School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC (R.X., P.Y., M.J.A., S.L., Y.G.), and Menzies Institute for Medical Research, University of Tasmania, Hobart (F.H.J.) - both in Australia; the Colorado School of Public Health, University of Colorado, Aurora (J.M.S.); the School of the Environment, Yale University, New Haven, CT (M.L.B.); the Department of Public Health, Environments, and Society and Department of Population Health, Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London (A.H.); and the Center for Health and the Global Environment, University of Washington, Seattle (K.L.E.).

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http://dx.doi.org/10.1056/NEJMsr2028985DOI Listing
November 2020

COVID-19 in South Korea: epidemiological and spatiotemporal patterns of the spread and the role of aggressive diagnostic tests in the early phase.

Int J Epidemiol 2020 08;49(4):1106-1116

Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea.

Background: South Korea experienced the novel coronavirus disease (COVID-19) outbreak in the early period; thus data from this country could provide significant implications for global mitigation strategies. This study reports how COVID-19 has spread in South Korea and examines the effects of rapid widespread diagnostic testing on the spread of the disease in the early epidemic phase.

Methods: We collected daily data on the number of confirmed cases, tests and deaths due to COVID-19 from 20 January to 13 April 2020. We estimated the spread pattern with a logistic growth model, calculated the daily reproduction number (Rt) and examined the fatality pattern of COVID-19.

Results: From the start date of the epidemic in Korea (18 February 2020), the time to peak and plateau were 15.2 and 25 days, respectively. The initial Rt was 3.9 [95% credible interval (CI) 3.7 to 4.2] and declined to <1 after 2 weeks. The initial epidemic doubling time was 3.8 days (3.4 to 4.2 days). The aggressive testing in the early days of the epidemic was associated with reduction in transmission speed of COVID-19. In addition, as of 13 April, the case fatality rate of COVID-19 in Korea was 2.1%, suggesting a positive effect of the targeted treatment policy for severe patients and medical resources.

Conclusions: Our findings provide important information for establishing and revising action plans based on testing strategies and severe patient care systems, needed to address the unprecedented pandemic.
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http://dx.doi.org/10.1093/ije/dyaa119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454567PMC
August 2020

Reductions in mortality resulting from reduced air pollution levels due to COVID-19 mitigation measures.

Sci Total Environ 2020 Nov 17;744:141012. Epub 2020 Jul 17.

Yale School of the Environment, Yale University, New Haven, CT, USA.

To control the novel coronavirus disease (COVID-19) outbreak, state and local governments in the United States have implemented several mitigation efforts that resulted in lower emissions of traffic-related air pollutants. This study examined the impacts of COVID-19 mitigation measures on air pollution levels and the subsequent reductions in mortality for urban areas in 10 US states and the District of Columbia. We calculated changes in levels of particulate matter with aerodynamic diameter no larger than 2.5 μm (PM) during mitigation period versus the baseline period (pre-mitigation measure) using the difference-in-difference approach and the estimated avoided total and cause-specific mortality attributable to these changes in PM by state and district. We found that PM concentration during the mitigation period decreased for most states (except for 3 states) and the capital. Decreases of average PM concentration ranged from 0.25 μg/m (4.3%) in Maryland to 4.20 μg/m (45.1%) in California. On average, PM levels across 7 states and the capital reduced by 12.8%. We estimated that PM reduction during the mitigation period lowered air pollution-related total and cause-specific deaths. An estimated 483 (95% CI: 307, 665) PM-related deaths was avoided in the urban areas of California. Our findings have implications for the effects of mitigation efforts and provide insight into the mortality reductions can be achieved from reduced air pollution levels.
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http://dx.doi.org/10.1016/j.scitotenv.2020.141012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7366090PMC
November 2020

Health and economic impacts of air pollution induced by weather extremes over the continental U.S.

Environ Int 2020 10 2;143:105921. Epub 2020 Jul 2.

School of Forestry & Environmental Studies, Yale University, New Haven, CT 06511, USA.

Extreme weather events may enhance ozone (O) and fine particulate matter (PM) pollution, causing additional adverse health effects. This work aims to evaluate the health and associated economic impacts of changes in air quality induced by heat wave, stagnation, and compound extremes under the Representative Concentration Pathways (RCP) 4.5 and 8.5 climate scenarios. The Environmental Benefits Mapping and Analysis Program-Community Edition is applied to estimate health and related economic impacts of changes in surface O and PM levels due to heat wave, stagnation, and compound extremes over the continental U.S. during past (i.e., 2001-2010) and future (i.e., 2046-2055) decades under the two RCP scenarios. Under the past and future decades, the weather extremes-induced concentration increases may lead to several tens to hundreds O-related deaths and several hundreds to over ten thousands PM-related deaths annually. High mortalities and morbidities are estimated for populated urban areas with strong spatial heterogeneities. The estimated annual costs for these O and PM related health outcomes are $5.5-12.5 and $48.6-140.7 billion U.S. dollar for mortalities, and $8.9-97.8 and $19.5-112.5 million for morbidities, respectively. Of the extreme events, the estimated O- and PM-related mortality and morbidity attributed to stagnation are the highest, followed by heat wave or compound extremes. Large increases in heat wave and compound extreme events in the future decade dominate changes in mortality during these two extreme events, whereas population growth dominates changes in mortality during stagnation that is projected to occur less frequently. Projected reductions of anthropogenic emissions under bothRCP scenarios compensate for the increased mortality due to increasedoccurrence for heat wave and compound extremes in the future. These results suggest a need to further reduce air pollutant emissions during weather extremes to minimize the adverse impacts of weather extremes on air quality and human health.
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http://dx.doi.org/10.1016/j.envint.2020.105921DOI Listing
October 2020

Health Effects of Asian Dust: A Systematic Review and Meta-Analysis.

Environ Health Perspect 2020 06 26;128(6):66001. Epub 2020 Jun 26.

Department of Environmental and Occupational Health, School of Medicine, Toho University, Tokyo, Japan.

Background: Potential adverse health effects of Asian dust exposure have been reported, but systematic reviews and quantitative syntheses are lacking.

Objective: We reviewed epidemiologic studies that assessed the risk of mortality, hospital admissions, and symptoms/dysfunction associated with exposure to Asian dust.

Methods: We performed a systematic search of PubMed and Web of Science to identify studies that reported the association between Asian dust exposure and human health outcomes. We conducted separate meta-analyses using a random-effects model for mortality and hospital admissions for a specific health outcome and assessed pooled estimates for each lag when at least three studies were available for a specific lag.

Results: We identified 89 studies that met our inclusion criteria for the systematic review, and 21 studies were included in the meta-analysis. The pooled estimates (percentage changes) of mortality from circulatory and respiratory causes for Asian dust days vs. non-Asian dust days were 2.33% [95% confidence interval (CI): 0.76, 3.93] increase at lag 0 and 3.99% (95% CI: 0.08, 8.06) increase at lag 3, respectively. The increased risk for hospital admissions for respiratory disease, asthma, and pneumonia peaked at lag 3 by 8.85% (95% CI: 0.80, 17.55), 14.55% (95% CI: 6.74, 22.94), and 8.51% (95% CI: 2.89, 14.44), respectively. Seven of 12 studies reported reduced peak expiratory flow, and 16 of 21 studies reported increased respiratory symptoms associated with Asian dust exposure. There were substantial variations between the studies in definitions of Asian dust, study designs, model specifications, and confounder controls.

Discussion: We found evidence of increased mortality and hospital admissions for circulatory and respiratory events. However, the number of studies included in the meta-analysis was not large and further evidences are merited to strengthen our conclusions. Standardized protocols for epidemiological studies would facilitate interstudy comparisons. https://doi.org/10.1289/EHP5312.
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http://dx.doi.org/10.1289/EHP5312DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319773PMC
June 2020

Health disparities attributable to air pollutant exposure in North Carolina: Influence of residential environmental and social factors.

Health Place 2020 03 31;62:102287. Epub 2020 Jan 31.

School of Forestry & Environmental Studies, Yale University, New Haven, CT, USA.

Understanding the environmental justice implications of the mortality impacts of air pollution exposure is a public health priority, as some subpopulations may face a disproportionate health burden. We examined which residential environmental and social factors may affect disparities in the air pollution-mortality relationship in North Carolina, US, using a time-stratified case-crossover design. Results indicate that air pollution poses a higher mortality risk for some persons (e.g., elderly) than others. Our findings have implications for environmental justice regarding protection of those who suffer the most from exposure to air pollution and policies to protect their health.
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http://dx.doi.org/10.1016/j.healthplace.2020.102287DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266831PMC
March 2020

Short term association between ozone and mortality: global two stage time series study in 406 locations in 20 countries.

BMJ 2020 02 10;368:m108. Epub 2020 Feb 10.

Institute of Environmental Assessment and Water Research, Spanish Council for Scientific Research, Barcelona, Spain.

Objective: To assess short term mortality risks and excess mortality associated with exposure to ozone in several cities worldwide.

Design: Two stage time series analysis.

Setting: 406 cities in 20 countries, with overlapping periods between 1985 and 2015, collected from the database of Multi-City Multi-Country Collaborative Research Network.

Population: Deaths for all causes or for external causes only registered in each city within the study period MAIN OUTCOME MEASURES: Daily total mortality (all or non-external causes only).

Results: A total of 45 165 171 deaths were analysed in the 406 cities. On average, a 10 µg/m increase in ozone during the current and previous day was associated with an overall relative risk of mortality of 1.0018 (95% confidence interval 1.0012 to 1.0024). Some heterogeneity was found across countries, with estimates ranging from greater than 1.0020 in the United Kingdom, South Africa, Estonia, and Canada to less than 1.0008 in Mexico and Spain. Short term excess mortality in association with exposure to ozone higher than maximum background levels (70 µg/m) was 0.26% (95% confidence interval 0.24% to 0.28%), corresponding to 8203 annual excess deaths (95% confidence interval 3525 to 12 840) across the 406 cities studied. The excess remained at 0.20% (0.18% to 0.22%) when restricting to days above the WHO guideline (100 µg/m), corresponding to 6262 annual excess deaths (1413 to 11 065). Above more lenient thresholds for air quality standards in Europe, America, and China, excess mortality was 0.14%, 0.09%, and 0.05%, respectively.

Conclusions: Results suggest that ozone related mortality could be potentially reduced under stricter air quality standards. These findings have relevance for the implementation of efficient clean air interventions and mitigation strategies designed within national and international climate policies.
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http://dx.doi.org/10.1136/bmj.m108DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190035PMC
February 2020

Disparities in exposure to surrounding greenness related to proportion of the population that were immigrants to the United States.

Int J Hyg Environ Health 2020 03 18;224:113434. Epub 2019 Dec 18.

School of Forestry & Environmental Studies, Yale University, USA.

The proportion of the United States (US) population who are immigrants (i.e., foreign-born) has been rising. Compared to the US-born, immigrants have different health risks, and prior studies could not fully explain these differences by diet and socioeconomic status. Surrounding greenness, an environmental exposure linked to better health, potentially contributes to differences in health risks between immigrants and the US-born. Using satellite imagery, we assessed exposure to surrounding greenness, as estimated by the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), in US Census tracts in 2000 and 2010. We then investigated the association between the percentage of the population that were immigrants and greenness using spatial error regression. Adjusted for median household income, urbanicity, educational attainment, unemployment, elderly and youth population proportion, and ecozone, Census tracts with ~10% higher overall immigrant percentage points were, on average, ~0.06 NDVI/EVI interquartile range lower, indicating lower greenness. The pattern of negative associations was most consistent when the immigrant country of origin was in Latin America. Conversely, when the immigrant country of origin was in Europe, we found mostly positive associations. Our findings suggest an environmental exposure disparity by immigrant status, motivating future work on environmental contributions to health disparities between immigrants and the US-born.
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http://dx.doi.org/10.1016/j.ijheh.2019.113434DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6992482PMC
March 2020

Risk of particulate matter on birth outcomes in relation to maternal socio-economic factors: a systematic review.

Environ Res Lett 2019 Dec 22;14(12). Epub 2019 Nov 22.

School of Forestry and Environmental Studies, Yale University.

A growing number of studies provide evidence of an association between exposure to maternal air pollution during pregnancy and adverse birth outcomes including low birth weight and preterm birth. Prevention of these health effects of air pollution is critical to reducing the adverse infant outcomes, which can have impacts throughout the life course. However, there is no consensus on whether the association between air pollution exposure and birth outcomes varies by maternal risk factors including demographic characteristics and socio-economic status. Such information is vital to understand potential environmental health disparities. Our search found 859 unique studies, of which 45 studies met our inclusion criteria (Jan. 2000- July. 2019). We systematically reviewed the 45 identified epidemiologic studies and summarized the results on effect modifications by maternal race/ethnicity, educational attainment, income, and area-level socio-economic status. We considered adverse birth outcomes of preterm birth, low birth weight, small for gestational age (SGA), and stillbirth. Suggestive evidence of higher risk of particulate matter in infants of African-American/black mothers than infants of other women was found for preterm birth and low birth weight. We found weak evidence that particulate matter risk was higher for infants of mothers with lower educational attainment for preterm birth and low birth weight. Due to the small study numbers, we were unable to conclude whether effect modification is present for income, occupation, and area-level socio-economic status, and additional research is needed. Furthermore, adverse birth outcomes such as SGA and stillbirth need more study to understand potential environmental justice issues regarding the impact of particulate matter exposure during pregnancy on birth outcomes.
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http://dx.doi.org/10.1088/1748-9326/ab4cd0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8186490PMC
December 2019