On adjustment for temperature in heatwave epidemiology: a new method and toward clarification of methods to estimate health effects of heatwaves.

Defining the effect of exposure of interest and selecting an appropriate estimation method are prerequisite for causal inference. Understanding the ways in which association between heatwaves (i.e., consecutive days of extreme high temperature) and an outcome depends on whether adjustment was made for temperature and how such adjustment was conducted, is limited. This paper aims to investigate this dependency, demonstrate that temperature is a confounder in heatwave-outcome associations, and introduce a new modeling approach to estimate a new heatwave-outcome relation: E[R(Y)|HW=1, Z]/E[R(Y)|T=OT, Z], where HW is a daily binary variable to indicate the presence of a heatwave; R(Y) is the risk of an outcome, Y; T is a temperature variable; OT is optimal temperature; and Z is a set of confounders including typical confounders but also some types of T as a confounder. We recommend characterization of heatwave-outcome relations and careful selection of modeling approaches to understand the impacts of heatwaves under climate change. We demonstrate our approach using real-world data for Seoul, which suggests that the total effect of heatwaves may be larger than what may be inferred from the extant literature. An R package, HEAT (Heatwave effect Estimation via Adjustment for Temperature), was developed and made publicly available.

Is residential exposure to oil refineries a novel contextual risk factor for coronary heart disease?

Despite a multi-decade decrease in cardiovascular disease, geographic disparities have widened, with excess mortality concentrated within the United States (U.S.) South. Petroleum production and refining, a major contributor to climate change, is concentrated within the U.S. South and emits multiple classes of atherogenic pollutants. We investigated whether residential exposure to oil refineries could explain variation in self-reported coronary heart disease (CHD) prevalence among adults in southern states for the year 2018, where the majority of oil refinery activity occurs (Alabama, Mississippi, Louisiana, Arkansas, Texas, New Mexico, and Oklahoma). We examined census tract-level association between oil refineries and CHD prevalence. We used a double matching method to adjust for measured and unmeasured spatial confounders: one-to-n distance matching and one-to-one generalized propensity score matching. Exposure metrics were constructed based on proximity to refineries, activities of refineries, and wind speed/direction. For all census tracts within 10 km of refineries, self-reported CHD prevalence ranged from 1.2% to 17.6%. Compared to census tracts located at ≥5 km and <10 km, one standard deviation increase in the exposure within 5 km of refineries was associated with a 0.33 (95% confidence interval: 0.04, 0.63) percentage point increase in the prevalence. A total of 1119.0 (123.5, 2114.2) prevalent cases or 1.6% (0.2, 3.1) of CHD prevalence in areas within 5 km from refineries were potentially explained by exposure to oil refineries. At the census tract-level, the prevalence of CHD explained by exposure to oil refineries ranged from 0.02% (0.00, 0.05) to 47.4% (5.2, 89.5). Thus, although we cannot rule out potential confounding by other personal risk factors, CHD prevalence was found to be higher in populations living nearer to oil refineries, which may suggest that exposure to oil refineries can increase CHD risk, warranting further investigation.

Modeling and Analysis of Air Pollution and Environmental Justice: The Case for North Carolina's Hog Concentrated Animal Feeding Operations.

BACKGROUND: Concentrated animal feeding operations (CAFOs) emit pollutants that can cause negative impacts on human health. The concentration of hog production in North Carolina raises concerns regarding the disproportionate exposure of vulnerable communities to air pollution from CAFOs. OBJECTIVES: We investigated whether exposure to gaseous ammonia (NH3) and hydrogen sulfide (H2S) (in 2019) differs between subpopulations by examining demographics, including race/ethnicity, age, educational attainment, language proficiency, and socioeconomic status. METHODS: We used an Air Monitoring Station (AMS)/Environmental Protection Agency (EPA) Regulatory Model (AERMOD)-based Human Exposure Model (version 3) to estimate ambient concentrations of NH3 and H2S from hog farms in Duplin County and its surrounding counties in North Carolina and estimate subsequent exposures of communities within 50km of Duplin County, North Carolina, or the Duplin County Region. We combined estimated exposures with 2016 American Community Summary Census data, at the block group level, using spatial analysis to investigate whether exposures to these pollutants differ by race and ethnicity, age, income, education, and language proficiency. Based on these estimations, we assessed associated exposure risks to the impacted communities and used multivariable regression modeling to evaluate the relationship between average ammonia exposures from Duplin regional hog farms and the presence of vulnerable populations. RESULTS: The average [±standard deviation (SD)] annual estimated concentration of NH3 and H2S in the Duplin County Region is 1.75±2.81 µg/m3 and 0.0087±0.014 µg/m3, respectively. The maximum average annual ambient concentrations are estimated at 54.27±4.12 µg/m3 and 0.54±0.041 µg/m3 for NH3 and H2S, respectively. Our descriptive analysis reveals that people of low income, people of color, people with low educational attainment, and the linguistically isolated in the Duplin Region are disproportionately exposed to higher levels of pollutants than the average exposure for residents. Alternatively, our statistical results suggests that after adjusting for covariates, communities of color are associated with 1.70% (95% CI: -3.79, 0.44) lower NH3 concentrations per 1-SD increase. One-standard deviation increases in the adults with low educational attainment and children <19 years of age is associated with 1.26% (95% CI: -0.77, 3.33) and 1.20% (95% CI: -0.62, 3.05) higher NH3 exposure per 1-SD increase, respectively. DISCUSSION: Exposures to NH3 and H2S differed by race and ethnicity, educational attainment, language proficiency, and socioeconomic status. The observed associations between exposure to CAFO-generated pollutants and sociodemographic indicators differed among demographics. The disproportionate distribution of hog facilities and resulting pollutant exposures among communities may have adverse environmental and human health impacts, raising environmental justice concerns. https://doi.org/10.1289/EHP11344.

Residential exposure to petroleum refining and stroke in the southern United States.

BACKGROUND: The southern United States (U.S.) sustains a disproportionate burden of incident stroke and associated mortality, compared to other parts of the U.S. A large proportion of this risk remains unexplained. Petroleum production and refining (PPR) is concentrated within this region and emits multiple pollutants implicated in stroke pathogenesis. The relationship between residential PPR exposure and stroke has not been studied. OBJECTIVE: We aimed to investigate the census tract-level association between residential PPR exposure and stroke prevalence for adults (≥18 years) in seven southern U.S. states in 2018. METHODS: We conducted spatial distance- and generalized propensity score-matched analysis that adjusts for sociodemographic factors, smoking, and unmeasured spatial confounding. PPR was measured as inverse-distance weighted averages of petroleum production within 2.5km or 5km from refineries, which was strongly correlated with measured levels of sulfur dioxide, a byproduct of PPR. RESULTS: The prevalence of self-reported stroke ranged from 0.4% to 12.7% for all the census tracts of the seven states. People with low socioeconomic status and of Hispanic ethnicity resided closer to petroleum refineries. The non-Hispanic Black population was exposed to higher PPR, while the non-Hispanic White population was exposed to lower PPR. Residential PPR exposure was significantly associated with stroke prevalence. One standard deviation increase in PPR within 5km from refineries was associated with 0.22 (95% confidence interval: 0.09, 0.34) percentage point increase in stroke prevalence. PPR explained 5.6% (2.4, 8.9) of stroke prevalence in the exposed areas. These values differed by states: 1.1% (0.5, 1.7) in Alabama to 11.7% (4.9, 18.6) in Mississippi, and by census tract-level: 0.08% (0.03, 0.13) to 25.3% (10.6, 40.0). CONCLUSIONS: PPR is associated with self-reported stroke prevalence, suggesting possible links between pollutants emitted from refineries and stroke. The increased prevalence due to PPR may differ by sociodemographic factors.

Association between Short-Term Exposure to Air Pollution and COVID-19 Mortality: A Population-Based Case-Crossover Study Using Individual-Level Mortality Registry Confirmed by Medical Examiners.

BACKGROUND: Studies have suggested links between ambient air pollution and coronavirus 2019 (COVID-19) mortality, yet confirmation by well-designed epidemiological studies with individual data is needed. OBJECTIVES: We aimed to examine whether short-term exposure to air pollution is associated with risk of mortality from COVID-19 for those infected with COVID-19. METHODS: The Cook County Medical Examiner's Office reports individual-level data for deaths from COVID-19 that occur in its jurisdiction, which includes all confirmed COVID-19 deaths in Cook County, Illinois. Case-crossover analysis was conducted to estimate the associations of estimated short-term exposures to particulate matter (PM) with aerodynamic diameter ≤2.5µm (PM2.5) and ozone (O3) on the day of death and up to 21 d before death at location of death with COVID-19. A total of 7,462 deaths from COVID-19 that occurred up to 28 February 2021 were included in the final analysis. We adjusted for potential confounders by time-stratified case-crossover design and by covariate adjustments (i.e., time-invariant factors, meteorological factors, viral transmission, seasonality, and time trend). RESULTS: Of the 7,462 case and 25,457 self-control days, almost all were days with exposure levels below the PM2.5 24-h National Ambient Air Quality Standard (NAAQS) (35 µg/m3); 98.9% had O3 levels below the maximum 8-h NAAQS (35.7 µg/m3 or 70 parts per billion). An interquartile range (IQR) increase (5.2 µg/m3) in cumulative 3-wk PM2.5 exposure was associated with a 69.6% [95% confidence interval (CI): 34.6, 113.8] increase in risk of COVID-19 mortality. An IQR increase (8.2 µg/m3) in 3-d O3 exposure was associated with a 29.0% (95% CI: 9.9, 51.5) increase in risk of COVID-19 mortality. The associations differed by demographics or race/ethnicity. There was indication of modification of the associations by some comorbid conditions. DISCUSSION: Short-term exposure to air pollution below the NAAQS may increase the mortality burden from COVID-19. https://doi.org/10.1289/EHP10836.

The Intersection of Immigrant and Environmental Health: A Scoping Review of Observational Population Exposure and Epidemiologic Studies.

BACKGROUND: Transnational immigration has increased since the 1950s. In countries such as the United States, immigrants now account for >15% of the population. Although differences in health between immigrants and nonimmigrants are well documented, it is unclear how environmental exposures contribute to these disparities. OBJECTIVES: We summarized current knowledge comparing immigrants' and nonimmigrants' exposure to and health effects of environmental exposures. METHODS: We conducted a title and abstract review on articles identified through PubMed and selected those that assessed environmental exposures or health effects separately for immigrants and nonimmigrants. After a full text review, we extracted the main findings from eligible studies and categorized each article as exposure-focused, health-focused, or both. We also noted each study's exposure of interest, study location, exposure and statistical methods, immigrant and comparison groups, and the intersecting socioeconomic characteristics controlled for. RESULTS: We conducted a title and abstract review on 3,705 articles, a full text review on 84, and extracted findings from 50 studies. There were 43 studies that investigated exposure (e.g., metals, organic compounds, fine particulate matter, hazardous air pollutants) disparities, but only 12 studies that assessed health disparities (e.g., mortality, select morbidities). Multiple studies reported higher exposures in immigrants compared with nonimmigrants. Among immigrants, studies sometimes observed exposure disparities by country of origin and time since immigration. Of the 50 studies, 43 were conducted in North America. DISCUSSION: The environmental health of immigrants remains an understudied area, especially outside of North America. Although most identified studies explored potential exposure disparities, few investigated subsequent differences in health effects. Future research should investigate environmental health disparities of immigrants, especially outside North America. Additional research gaps include the role of immigrants' country of origin and time since immigration, as well as the combined effects of immigrant status with intersecting socioeconomic characteristics, such as race/ethnicity, income, and education attainment. https://doi.org/10.1289/EHP9855.

Heterogeneous effects of COVID-19 control measures on tuberculosis in South Korea: an analysis of case notification data.

Coronavirus disease (COVID-19) responses such as social distancing practices can decrease health care access and tuberculosis (TB) notification, particularly among individuals aged 60 years or older. Conversely, they can increase TB notification among younger individuals. These results may be attributable to household transmission and the similarity of TB respiratory symptoms to COVID-19.

New Insights for Tracking Global and Local Trends in Exposure to Air Pollutants.

Over six million people die prematurely each year from exposure to air pollution. Current air quality metrics insufficiently monitor exposure to air pollutants. This gap hinders the ability of decisionmakers to address the public health impacts of air pollution. To spur new emissions control policies and ensure implemented solutions realize meaningful gains in environmental health, we develop a framework of public-health-focused air quality indicators that quantifies over 200 countries' trends in exposure to particulate matter, ozone, nitrogen oxides, sulfur dioxide, carbon monoxide, and volatile organic compounds. We couple population density to ground-level pollutant concentrations to derive population-weighted exposure metrics that quantify the pollutant levels experienced by the average resident in each country. Our analyses demonstrate that most residents in 171 countries experience pollutant levels exceeding international health guidelines. In addition, we find a negative correlation between temporal trends in ozone and nitrogen oxide concentrations, which─when qualitatively interpreted with a simple atmospheric chemistry box model─can help describe the apparent tradeoff between the mitigation of these two pollutants on local scales. These novel indicators and their applications enable regulators to identify their most critical pollutant exposure trends and allow countries to track the performance of their emission control policies over time.

Associations between Long-Term Air Pollution Exposure and Risk of Osteoporosis-Related Fracture in a Nationwide Cohort Study in South Korea.

Bone health is a major concern for aging populations globally. Osteoporosis and bone mineral density are associated with air pollution, but less is known about the impacts of air pollution on osteoporotic fracture. We aimed to assess the associations between long-term air pollution exposure and risk of osteoporotic fracture in seven large Korean cities. We used Cox proportional hazard models to estimate hazard rations (HRs) of time-varying moving window of past exposures of particulate matter (PM10), sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3) for osteoporotic fracture in Korean adults (age ≥ 50 years) in the National Health Insurance Service-National Sample Cohort data, followed 2002 to 2015. HRs were calculated for an interquartile range (IQR) increase. Comorbidity and prescription associated with osteoporosis, age, sex, body mass index, health behaviors, and income were adjusted in the models. Effect modification by age, sex, exercise, and income was examined. We assessed 56,467 participants over 535,481 person-years of follow up. Linear and positive exposure-response associations were found for SO2, while PM10 and NO2 showed nonlinear associations. SO2 was associated with osteoporosis-related fracture with marginal significance (HR for an IQR [2 ppb] increase = 1.04, 95% CI: 1.00, 1.09). The SO2 HR estimates were robust in analyses applying various moving windows of exposure (from one to three years of past exposure) and two-pollutant models. The central HR estimate of O3 implied positive associations but was not significant (HR for 0.007 ppm increase = 1.01, 95% CI: 0.97, 1.06). PM10, CO, and NO2 did not show associations. Vulnerable groups by sex, age, exercise, and income varied across air pollutants and there was no evidence of effect modifications. Long-term exposure to SO2, but not PM10, CO, NO2 and O3, was associated with increased osteoporotic fracture risks in Korean adults.

Higher incidence of novel coronavirus (COVID-19) cases in areas with combined sewer systems, heavy precipitation, and high percentages of impervious surfaces.

Combined sewer systems (CSS) are water management systems that collect and transport stormwater and sewer water in the same pipes. During large storm events, stormwater runoff may exceed the capacity of the system and lead to combined sewer overflows (CSOs), where untreated sewer and stormwater are released into the environment. Though current literature reveals inconclusive evidence regarding the infectivity of SARS-CoV-2 in wastewater, detection of infectious SARS-CoV-2 in urine and feces of COVID-19 patients led to concerns that areas contaminated by CSOs may be a reservoir of SARS-CoV-2 and may result in illness after the ingestion and/or inhalation of contaminated splashes, droplets, or aerosols. We investigated the association between COVID-19 incidence and CSSs and whether this association differed by precipitation and percent impervious surfaces as a proxy for possible CSOs. We fitted a quasi-Poisson regression model to estimate the change in percentage of incidence rate of COVID-19 cases in counties with a CSS compared to those without, adjusting for potential confounders (i.e., state, population density, date of first documented COVID-19 case, social vulnerability, and percent vaccinated) and including interaction variables between CSS, precipitation, and impervious surfaces. Our findings suggest that heavy precipitation in combination with high percentages of imperviousness is associated with higher incidences of COVID-19 cases in counties with a CSS compared to in counties without (p-value = 2.5e-9). For example, CSS-counties with precipitation of 10 in/month may observe a higher incidence in COVID-19 cases compared to non-CSS counties if their impervious surfaces exceed 33.5% [95%CI: 23.0%, 60.0%]. We theorize that more COVID-19 cases may be seen in counties with a CSS, heavy precipitation, and high percentages of impervious surfaces because of the possible increase in frequency and severity of CSOs. The results suggest links between climate change, urbanization, and COVID-19.

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

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.

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

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.

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

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.

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

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 PM10 and cause-specific mortality in 72 municipalities in South Korea, 2006-2013, considering these challenges. We found that a 10 µg/m3 increase in PM10 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 PM10 and mortality was higher in communities with higher ratio of SO2 to PM10 (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 PM10-related health inequalities in those perspectives.

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

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.

Effects of long-term exposure to air pollution on all-cause mortality and cause-specific mortality in seven major cities of South Korea: Korean national health and nutritional examination surveys with mortality follow-up.

Evidence from cohort studies on the effects of long-term exposure to air pollution on mortality is limited in South Korea, which has high concentration of particles compared to North America, Western Europe, and Japan, and low exposure compared to China. To reduce knowledge gaps between other countries and South Korea, we investigated the association between all-cause, cardiovascular, and respiratory mortality and long-term exposure to PM10 and, as a surrogate for fine particles from local emission sources, SO2 and NO2. Participants comprised 18,220 subjects (97,114.4 person-years) residing in 73 districts of seven major cities of South Korea who were assigned to measurements of fixed-site monitoring stations and followed up. We applied Cox proportional hazard models with time-varying exposure up to three years average of air pollutants. We adjusted for individual and district-level covariates measured at baseline such as age, sex, socioeconomic positions, and health behaviors. We found that hazard ratios of PM10 and SO2 for all-cause mortality leveled off over approximately 5 ppb of SO2 and 35-50 µg/m3 of PM10. Interquartile range increases of PM10 (5.05 µg/m3), SO2 (2.09 ppb), and NO2 (11.41 ppb) were associated with 14.4% (95% CI: -0.4, 31.4), 18.1% (-4.5, 46.0), and 18.9% (-8.7, 54.7) increases in cardiovascular mortality, respectively. We did not find positive associations for respiratory mortality. The increase in cardiovascular mortality varied by sex (for PM10, in females, 27.4% (5.8, 53.5) increase), smoking (in non-smokers, 35.9% (12.7, 64.0) increase), drinking (in drinkers, 24.5% (2.1, 51.8) increase), marital status (in those not married, 23.1% (1.1, 49.9)), employment status (for SO2, in those employed, 79.4% (16.1, 177.3) increase), body mass index (in those ≥23, 47.6% (10.4, 97.3) increase), and community deprivation (for PM10, in less deprived communities, 21.0% (1.3, 44.4) increase). In summary, long-term exposure to air pollution is associated with mortality risk in South Korea. Our results suggest that the health effect of long-term exposure to air pollution may not be equal by sex, health behaviors and socioeconomic positions.

Inter-mortality displacement hypothesis and short-term effect of ambient air pollution on mortality in seven major cities of South Korea: a time-series analysis.

BACKGROUND: Inter-mortality displacement (IMD) between cause-specific mortalities has not been introduced in air pollution epidemiology. Investigation into IMD would provide insights on the actual health burden of air pollution and interpretation of associations. We aimed to investigate IMD regarding short-term effect of air pollution on mortality. METHODS: We illustrated manifestations and interpretations of lag-mortality associations. If IMD exists, a net increase of one cause-specific death can be offset by a net decrease of other cause-specific deaths. We conducted a time-series analysis to estimate associations of ambient particulate matter smaller than 10 µm (PM10), ozone (O3), sulphur dioxide (SO2), nitrogen dioxide (NO2) and carbon monoxide (CO) with mortality, considering lags up to the previous 45 days, for seven major cities of South Korea from 2006 to 2013. Attributable mortality cases were identified. RESULTS: For O3, respiratory mortality [11 929 cases, 95% empirical confidence interval (eCI), 5358, 17 688 cases] was counterbalanced by cardiovascular mortality (-11 272 cases, 95% eCI: -22 444, -629 cases). All-cause mortality was 37 148 cases (95% eCI: 4448, 68 782 cases). For PM10, respiratory deaths were 9167 cases (95% eCI: 563, 16 521 cases), and cardiovascular deaths were 6929 cases (95% eCI: -11 793, 24 138 cases). Estimates for SO2 were comparable to those for PM10. All-cause mortality attributable to NO2 was explained by short-term mortality displacement. No associations with mortality were found for CO. CONCLUSIONS: IMD may exist in the relationship between air pollution and mortality. The actual relationship between air pollution and cause-specific mortality may be masked by IMD.

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

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.

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

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 (PM2.5) 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 PM2.5 by state and district. We found that PM2.5 concentration during the mitigation period decreased for most states (except for 3 states) and the capital. Decreases of average PM2.5 concentration ranged from 0.25 µg/m3 (4.3%) in Maryland to 4.20 µg/m3 (45.1%) in California. On average, PM2.5 levels across 7 states and the capital reduced by 12.8%. We estimated that PM2.5 reduction during the mitigation period lowered air pollution-related total and cause-specific deaths. An estimated 483 (95% CI: 307, 665) PM2.5-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.