Effects of ambient air particles on mortality in Seoul: Have the effects changed over time?

The temporal trend and disparity in short-term health impacts of fine particulate matter in California (2006-2019)

Most epidemiological studies assume that the relationship between short-term air pollution exposure and health outcomes is constant over time, which ignores potential changes in population composition and particulate matter emission sources. Limited studies have assessed changes in the relationship between fine particulate matter (PM2.5) and adverse health outcomes over time, with mixed results. Additionally, there is a need to identify which subgroups are disproportionately impacted over time by PM2.5-related health consequences. Therefore, we aimed to examine whether temporal trends exist in the relationships between daily PM2.5 exposure and circulatory and respiratory acute care utilization in California from 2006 to 2019. We further assessed whether certain subpopulations are more susceptible to PM2.5 exposure by demographic characteristics and extreme wildfire frequency. Daily PM2.5 concentrations estimated from a stacked ensemble model and daily cause-specific acute care utilization and demographic data from the California Department of Health Care Access and Information. We analyzed this relationship using modified two-stage Bayesian hierarchical models, where we first did not consider temporal trends, then stratified by two periods, and finally flexibly considered non-linear changes over time. Increases in circulatory (0.56 %; 95 % credible interval (CI): 0.17 %, 0.96 %) and respiratory acute care utilization risk (2.61 %; 95%CI: 2.29 %, 2.94 %) were found with every 10 μg/m3 increase in PM2.5 on the same day and previous two days. These risks were found to increase over time, where 0.13 % (95%CI: 0.02 %, 0.22 %) and 1.40 % (95%CI: 1.24 %, 1.54 %) increases were identified for circulatory and respiratory acute care utilizations, respectively, from the first (2006-2012) to second period (2013-2019). Differences by age, sex, race/ethnicity, and extreme wildfire frequency were noted. These findings confirm that air pollution guidelines should consider the dynamic nature of epidemiological dose-response and can provide insight for targeted air pollution control and adaptation policies designed to reduce PM2.5 exposure, particularly for the most susceptible subpopulations.

Temporal variations in the short-term effects of ambient air pollution on cardiovascular and respiratory mortality: a pooled analysis of 380 urban areas over a 22-year period

BACKGROUND

Ambient air pollution, including particulate matter (such as PM10 and PM2·5) and nitrogen dioxide (NO2), has been linked to increases in mortality. Whether populations' vulnerability to these pollutants has changed over time is unclear, and studies on this topic do not include multicountry analysis. We evaluated whether changes in exposure to air pollutants were associated with changes in mortality effect estimates over time.

METHODS

We extracted cause-specific mortality and air pollution data collected between 1995 and 2016 from the Multi-Country Multi-City (MCC) Collaborative Research Network database. We applied a two-stage approach to analyse the short-term effects of NO2, PM10, and PM2·5 on cause-specific mortality using city-specific time series regression analyses and multilevel random-effects meta-analysis. We assessed changes over time using a longitudinal meta-regression with time as a linear fixed term and explored potential sources of heterogeneity and two-pollutant models.

FINDINGS

Over 21·6 million cardiovascular and 7·7 million respiratory deaths in 380 cities across 24 countries over the study period were included in the analysis. All three air pollutants showed decreasing concentrations over time. The pooled results suggested no significant temporal change in the effect estimates per unit exposure of PM10, PM2·5, or NO2 and mortality. However, the risk of cardiovascular mortality increased from 0·37% (95% CI -0·05 to 0·80) in 1998 to 0·85% (0·55 to 1·16) in 2012 with a 10 μg/m3 increase in PM2·5. Two-pollutant models generally showed similar results to single-pollutant models for PM fractions and indicated temporal differences for NO2.

INTERPRETATION

Although air pollution levels decreased during the study period, the effect sizes per unit increase in air pollution concentration have not changed. This observation might be due to the composition, toxicity, and sources of air pollution, as well as other factors, such as socioeconomic determinants or changes in population distribution and susceptibility.

FUNDING

None.

The Effects of Particulate Matter Alert on Urban Park Visitation in Seoul, Korea: Using Segmented Regression

To reduce the health burden from particulate matter (PM), the Korean government implemented a nationwide PM₁₀ (particles less than 10 µg/m³ in diameter) alert system in 2015. The policy was intended to reduce PM exposure by advising people to refrain from outdoor activities on highly polluted days. The present study aimed to estimate the effect of the PM₁₀ alert system on people's daily outdoor activity patterns using urban park (specifically, Children's Grand Park) visitation data from Seoul, South Korea, from 2014-2019. Segmented regression was fitted to estimate whether the number of visitors to the park decreased on the days with PM₁₀ alerts. PM₁₀ concentration of 80 µg/m³, the cut-off point for a "Bad" alert, was set as a threshold, and discontinuity at the threshold and change in the relative risk after the threshold was tested. Time series regression was used to estimate the dose-response line between the ambient PM₁₀ concentration and the daily number of park visitors. The number of park visitors decreased by 11.8% (relative risk: 0.881, 95% confidence interval: 0.808, 0.960) when a "Bad" alert was issued (PM₁₀ level above 80 µg/m³) compared to when the alert level was "Normal" (PM₁₀ level less than 80 µg/m³). The present study found evidence that the PM₁₀ alert influenced people's daily outdoor activities in Seoul, Korea. As the main purpose of the PM alert is to encourage people to refrain from outdoor activities, evaluating the relationship between PM alerts and behavior patterns can help to grasp the effectiveness of the policy. Further efforts should be made to investigate whether the observed behavioral change leads to reductions in health outcomes caused by PM.

Temporal Heterogeneity of Short-Term Effects of Particulate Matter on Stroke Outpatients in Seven Major Cities of the Republic of Korea

Although particulate matter (PM) is a major risk factor for stroke, its effects on hospital outpatients admitted for stroke have not been documented in Korea. In addition, recent studies have reported that the effects of PM₁₀ on circulatory mortality changed over time. We aimed to estimate the effects of PM₁₀ on stroke and their temporal heterogeneity in seven major cities of Korea during the period 2002-2015. The study period was divided into five years of moving time windows, and city-specific PM₁₀ effects on ischemic and hemorrhagic stroke outpatients were calculated. We pooled the estimates using meta-analysis and plotted them into a sequence to identify their temporal trends. A 10 µg/m³ increase of PM₁₀ was significantly associated with increments in hospital outpatients admitted for ischemic stroke (0.24%, 95% CI: 0.04%, 0.44%), but not for hemorrhagic stroke (0.33%, 95% CI: -0.06%, 0.73%). Effect estimates for strokes increased during the period 2003-2013 but decreased after. For the first time, we have estimated the effects of PM₁₀ on hospital outpatients admitted for stroke in Korea. The observed temporal trend in PM₁₀ effects was similar to patterns of circulatory mortality, suggesting that the temporal heterogeneity in PM₁₀ effects might be due to systematic causes rather than random fluctuations.

Do temporal trends of associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalizations differ by sub-populations and urbanicity-a study of 968 U.S. counties and the Medicare population

While associations between short-term exposure to fine particulate matter (PM_2.5) and risk of hospitalization are well documented and evidence suggests that such associations change over time, it is unclear whether these temporal changes exist in understudied less-urban areas or differ by sub-population. We analyzed daily time-series data of 968 continental U.S. counties for 2000-2016, with cause-specific hospitalization from Medicare claims and population-weighted PM_2.5 concentrations originally estimated at 1km × 1 km from a hybrid model. Circulatory and respiratory hospitalizations were categorized based on primary diagnosis codes at discharge. Using modified Bayesian hierarchical modelling, we evaluated the temporal trend in association between PM_2.5 and hospitalizations and whether disparities in this trend exist across individual-level characteristics (e.g., sex, age, race, and Medicaid eligibility as a proxy for socio-economic status) and urbanicity. Urbanicity was categorized into three levels by county-specific percentage of urban population based on urban rural delineation from the U.S. Census. In this cohort with understudied less-urban areas without regulatory monitors, we still found positive association between circulatory and respiratory hospitalization and short-term exposure to PM_2.5, with higher effect estimates towards the end of study period. Consistent with current literature, we identified significant disparity in associations by race, socioeconomic status and urbanicity. We found that the percentage change in circulatory hospitalization rate per 10 μg/m³ increase in PM_2.5 was higher in the 2008-2016 time period compared to the 2000-2007 period by 0.33% (95% posterior credible interval 0.22, 0.44%), 0.52% (0.33, 0.69%), and 0.67% (0.53, 0.83%) for low, medium and high tertiles of urban areas, respectively. We also observed significant differences in temporal trends of associations across socioeconomic status, sex, and age, indicating a possible widening in disparity of PM_2.5-related health burden. This study raises the importance of considering environmental justice issues in PM_2.5-related health impacts with respect to how associations may change over time.

Association between ozone exposure and prevalence of mumps: a time-series study in a Megacity of Southwest China

In the present study, we aim to evaluate the delayed and cumulative effect of ozone (O₃) exposure on mumps in a megacity with high population density and high humidity. We took Chongqing, a megacity in Southwest China, as the research area and 2013-2017 as the research period. A total of 49,258 confirmed mumps cases were collected from 122 hospitals of Chongqing. We employed the distributed lag nonlinear models with quasi-Poisson link to investigate the relationship between prevalence of mumps and O₃ exposure after adjusting for the effects of meteorological conditions. The results show that the effect of O₃ exposure on mumps was mainly manifested in the lag of 0-7 days. The single-day ;lag effect was the most obvious on the 4th day, with the relative risk (RR) of mumps occurs of 1.006 (95% CI: 1.003-1.007) per 10 μg/m³ in the O₃ exposure. The cumulative RR within 7 days was 1.025 (95% CI: 1.013-1.038). Our results suggest that O₃ exposure can increase the risk of mumps infection, which fills the gap of relevant research in mountainous areas with high population density and high humidity.

Temporal variation in association between short-term exposure to fine particulate matter and hospitalisations in older adults in the USA: a long-term time-series analysis of the US Medicare dataset

BACKGROUND

Short-term exposure to fine particulate matter (PM_2·5) is associated with increased risk of hospital admissions and mortality, and health risks differ by the chemical composition of PM_2·5. Policies to control PM_2·5 could change its chemical composition and total mass concentration, leading to change in the subsequent health impact. However, there is little ence on whether associations between PM_2·5 and health exhibit temporal variation. We investigated whether risks of hospitalisations from short-term exposure to PM_2·5 varied over time in the USA.

METHODS

We did a time-series analysis using a national dataset comprising daily circulatory and respiratory hospitalisation rates of Medicare beneficiaries (age ≥65 years) and PM_2·5 in 173 US counties from 1999 to 2016. We fitted modified quasi-Poisson models to estimate temporal trends of associations within a county, and pooled county-level estimates using Bayesian hierarchical modelling to generate an overall estimate.

FINDINGS

The study included 10 559 654 circulatory and 3 027 281 respiratory hospitalisations. We identified changes in the national average association between previous-day PM_2·5 and respiratory hospitalisation over time, with a U-shape that is robust under stratification, linear, and non-linear models. The change in risk of respiratory hospitalisation per 10 μg/m³ increase in previous-day PM_2·5 decreased from 0·75% (95% posterior credible interval 0·05 to 1·46) in 1999 to -0·28% (-0·79 to 0·23) in 2008, and then increased to 1·44% (0·00 to 2·91) in 2016. No statistically significant temporal change was observed for associations between same-day PM_2·5 and circulatory hospitalisation.

INTERPRETATION

Hospitalisation risk from PM_2·5 changes over time and has increased over the past 7 years in study, especially in northeastern USA. The temporal trend differs by cause of hospitalisation. This study emphasises the necessity of evaluating temporal heterogeneity in health impacts of PM_2·5 and suggests caution in applying association estimates to a different time period.

FUNDING

US Environmental Protection Agency and Yale Institute for Biospheric Studies.

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.

Temporal variations of short-term effects of particulate matter on hospital admissions in the most densely populated city in Thailand

Short-term effects of ambient particulate matter (PM) on daily hospital admissions have been comprehensively elucidated, but very few studies evaluated the temporal variations of ambient PM associated with hospital admissions, especially in developing countries. This study aimed to explore the temporal changes of the short-term effects of PM₁₀ on hospital admissions in Bangkok, Thailand from 2006 to 2014. The overdispersed Poisson regression model was applied to related daily PM₁₀ concentrations to daily cardiovascular and respiratory hospital admissions by adjusting for temperature, humidity, long-term trend and seasonality, day of the week, public holiday, and population dynamics. The temporal variations of the effects of PM₁₀ on hospital admissions were assessed by adding an interaction term between PM₁₀ concentration and predefined time periods into the model. The relative risks per 10 μg/m³ increase in PM₁₀ were 1.0092 (95% CI: 1.0046, 1.0138) for cardiovascular admissions at lag 0-3 day and 1.0209 (95% CI: 1.0145, 1.0273) for respiratory admissions at lag 0-7 day over the entire study period. Despite non-homogenous decreasing trends in annual PM₁₀ concentrations during the study period, the effects of PM₁₀ on cardiovascular and respiratory admissions remained significant and even showed an increasing trend for cardiovascular admissions. Specifically, the relative risks of cardiovascular admission per 10 μg/m³ increase in PM₁₀ were 1.0050 (95% CI: 0.9965, 1.0135), 1.0086 (95% CI: 1.0000, 1.0174), and 1.0103 (95% CI: 1.0041, 1.0165) for the period of 2006-2008, 2009-2011, and 2012-2014, respectively (p-value for interaction <0.01). This finding indicated that estimated effects of PM₁₀ on cardiovascular admissions significantly changed over time, speculating that the composition of PM₁₀ might have changed and introduced the alterations of overall toxicity of PM₁₀. Therefore, the efforts on air pollution control need to be continued to reduce health effects of PM₁₀ in the future.

Assessment of PM2.5-bound nitrogen-containing organic compounds (NOCs) during winter at urban sites in China and Korea

In this study, ambient fine particles (PM_2.5) were collected in two urban cities in China and Korea (Beijing and Gwangju, respectively) simultaneously in January 2018. Analysis of the nonpolar and semipolar organic matter (OM) using atmospheric pressure photoionization (APPI) Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) revealed that compounds containing only C, H, and O (CHO) and those containing C, H, O, and N (CHON) accounted for more than 90% of the total intensity of the OM peaks. Higher proportions of CHON compounds were observed during days with abnormally high PM_2.5 concentrations at both sites than on regular or non-event days. The proportion of CHON species at the Beijing site was not correlated with secondary ionic species (i.e., NO₃^-, SO₄^2-, and NH₄⁺) or gaseous components (i.e., O₃, NO₂, and SO₂). In contrast, the proportion of CHON species at the Gwangju site was positively correlated with the concentrations of particulate nitrate and ammonium ions, assuming that ambient ammonium nitrate plays a role in the atmospheric formation of nitrogen-containing organic compounds (NOCs) at the Gwangju site and that Gwangju is more strongly influenced by secondary aerosols than Beijing is. In particular, a significant proportion of the compounds observed at the Beijing site contained only C, H and N (CHN), while negligible amounts of CHN were detected at the Gwangju site. The CHN species in Beijing were identified as quinoline compounds and the corresponding -CH₂ homologous series using complementary GC × GC-TOF MS analysis. These results suggest that NOCs and their -CH₂ homologous series from primary emissions may be significant contributors to nonpolar and semipolar OM during winter in Beijing, while NOCs with high oxidation states, likely formed via ambient-phase nitrate-mediated reactions, may be the dominant OM constituents in Gwangju.

The difference in effect of ambient particles on mortality between days with and without yellow dust events: Using a larger dataset in Seoul, Korea from 1998 to 2015

BACKGROUND

Yellow Dust (YD) is a natural source of particulate matter (PM) in Korea. It remarkably increases the concentration of PM. However, characteristics of PM in YD period are different from those of PM in non-YD period.

OBJECTIVES

To investigate whether the association of PM with mortality is different between all days and non-YD days in Seoul, Korea, 1998-2015.

METHODS

We applied time-stratified case-crossover design to estimate effects of PM₁₀ and PM_2.5 on non-accidental cardiovascular and respiratory mortality. Effect estimates of PM were compared for all days in the study period and days without YD events. To identify whether different effect estimates between all days and non-YD days were not merely caused by the exclusion of high PM concentrations but rather by YD itself, we estimated effects of PM by randomly excluding the same number of days as days of YD.

RESULTS

A total of 4,509,392 deaths were observed during the study period. A 10 μg/m³ increase in PM₁₀ or PM_2.5 was associated with a 0.15% (95% CI: 0.06% to 0.24%) or 0.27% (95% CI: 0.07% to 0.47%) increase in risk of non-accidental mortality for all days, respectively. These associations were changed to 0.30% (95% CI: 0.18% to 0.42%) and 0.33% (95% CI: 0.10% to 0.55%) when YD days were excluded from analyses. We also found that effect estimates of PM were larger when YD days were excluded than those when high PM concentrations were randomly excluded.

CONCLUSIONS

The effect estimates of PM differed between all days and non-YD days. Our study suggests that including YD days in the analyses is likely to attenuate the effect of PM in a usual urban environment.

Effect of air pollutant emission reduction policies on hospital visits for asthma in Seoul, Korea; Quasi-experimental study

To improve air quality and reduce adverse health effects due to air pollutants, Seoul metropolitan government has introduced emission reduction policies in Seoul metropolitan area since 2007. As a result, air quality in Seoul has improved. However, no study has reported whether emission reduction policies have affected respiratory morbidities in Korea. Thus, we aimed to assess an association between air pollutant emissions and ambient concentrations, and the effect of implemented emission reduction policies on asthma. The population of Daejeon, one of the metropolitan cities in Korea other than Seoul was used as a reference population to adjust for possible long-term background trend. Trends of air pollutant emissions, ambient concentrations, and hospital visit rates in Seoul and Daejeon were evaluated using descriptive statistics. To evaluate the possible beneficial effect of air pollutant emission reduction policies implemented since 2007 on hospital visits for asthma in Seoul, we conducted interrupted time-series analysis. As a result, we found evidence for the association between emission reductions and reduced ambient concentrations. Trends in hospital visit rates for asthma, which were previously increasing in Seoul, have decreased since the implementation of the policies. Prevented hospital visits cases for asthma in the total population and younger population (0-18 years) were estimated as 500,000 (11.3% of hospital visit cases if there was no intervention) cases and 320,000 (15.5% of hospital visit cases if there was no intervention) cases, respectively in Seoul. Our study provides evidence for the possible beneficial effect of emission reduction policies on hospital visits for asthma.

Interventions to reduce ambient particulate matter air pollution and their effect on health

BACKGROUND

Ambient air pollution is associated with a large burden of disease in both high-income countries (HICs) and low- and middle-income countries (LMICs). To date, no systematic review has assessed the effectiveness of interventions aiming to reduce ambient air pollution.

OBJECTIVES

To assess the effectiveness of interventions to reduce ambient particulate matter air pollution in reducing pollutant concentrations and improving associated health outcomes.

SEARCH METHODS

We searched a range of electronic databases with diverse focuses, including health and biomedical research (CENTRAL, Cochrane Public Health Group Specialised Register, MEDLINE, Embase, PsycINFO), multidisciplinary research (Scopus, Science Citation Index), social sciences (Social Science Citation Index), urban planning and environment (Greenfile), and LMICs (Global Health Library regional indexes, WHOLIS). Additionally, we searched grey literature databases, multiple online trial registries, references of included studies and the contents of relevant journals in an attempt to identify unpublished and ongoing studies, and studies not identified by our search strategy. The final search date for all databases was 31 August 2016.

SELECTION CRITERIA

Eligible for inclusion were randomized and cluster randomized controlled trials, as well as several non-randomized study designs, including controlled interrupted time-series studies (cITS-EPOC), interrupted time-series studies adhering to EPOC standards (ITS-EPOC), interrupted time-series studies not adhering to EPOC standards (ITS), controlled before-after studies adhering to EPOC standards (CBA-EPOC), and controlled before-after studies not adhering to EPOC standards (CBA); these were classified as main studies. Additionally, we included uncontrolled before-after studies (UBA) as supporting studies. We included studies that evaluated interventions to reduce ambient air pollution from industrial, residential, vehicular and multiple sources, with respect to their effect on mortality, morbidity and several air pollutant concentrations. We did not restrict studies based on the population, setting or comparison.

DATA COLLECTION AND ANALYSIS

After a calibration exercise among the author team, two authors independently assessed studies for inclusion, extracted data and assessed risk of bias. We conducted data extraction, risk of bias assessment and evidence synthesis only for main studies; we mapped supporting studies with regard to the types of intervention and setting. To assess risk of bias, we used the Graphic Appraisal Tool for Epidemiological studies (GATE) for correlation studies, as modified and employed by the Centre for Public Health Excellence at the UK National Institute for Health and Care Excellence (NICE). For each intervention category, i.e. those targeting industrial, residential, vehicular and multiple sources, we synthesized evidence narratively, as well as graphically using harvest plots.

MAIN RESULTS

We included 42 main studies assessing 38 unique interventions. These were heterogeneous with respect to setting; interventions were implemented in countries across the world, but most (79%) were implemented in HICs, with the remaining scattered across LMICs. Most interventions (76%) were implemented in urban or community settings.We identified a heterogeneous mix of interventions, including those aiming to address industrial (n = 5), residential (n = 7), vehicular (n = 22), and multiple sources (n = 4). Some specific interventions, such as low emission zones and stove exchanges, were assessed by several studies, whereas others, such as a wood burning ban, were only assessed by a single study.Most studies assessing health and air quality outcomes used routine monitoring data. Studies assessing health outcomes mostly investigated effects in the general population, while few studies assessed specific subgroups such as infants, children and the elderly. No identified studies assessed unintended or adverse effects.The judgements regarding the risk of bias of studies were mixed. Regarding health outcomes, we appraised eight studies (47%) as having no substantial risk of bias concerns, five studies (29%) as having some risk of bias concerns, and four studies (24%) as having serious risk of bias concerns. Regarding air quality outcomes, we judged 11 studies (31%) as having no substantial risk of bias concerns, 16 studies (46%) as having some risk of bias concerns, and eight studies (23%) as having serious risk of bias concerns.The evidence base, comprising non-randomized studies only, was of low or very low certainty for all intervention categories and primary outcomes. The narrative and graphical synthesis showed that evidence for effectiveness was mixed across the four intervention categories. For interventions targeting industrial, residential and multiple sources, a similar pattern emerged for both health and air quality outcomes, with essentially all studies observing either no clear association in either direction or a significant association favouring the intervention. The evidence base for interventions targeting vehicular sources was more heterogeneous, as a small number of studies did observe a significant association favouring the control. Overall, however, the evidence suggests that the assessed interventions do not worsen air quality or health.

AUTHORS' CONCLUSIONS

Given the heterogeneity across interventions, outcomes, and methods, it was difficult to derive overall conclusions regarding the effectiveness of interventions in terms of improved air quality or health. Most included studies observed either no significant association in either direction or an association favouring the intervention, with little evidence that the assessed interventions might be harmful. The evidence base highlights the challenges related to establishing a causal relationship between specific air pollution interventions and outcomes. In light of these challenges, the results on effectiveness should be interpreted with caution; it is important to emphasize that lack of evidence of an association is not equivalent to evidence of no association.We identified limited evidence for several world regions, notably Africa, the Middle East, Eastern Europe, Central Asia and Southeast Asia; decision-makers should prioritize the development and implementation of interventions in these settings. In the future, as new policies are introduced, decision-makers should consider a built-in evaluation component, which could facilitate more systematic and comprehensive evaluations. These could assess effectiveness, but also aspects of feasibility, fidelity and acceptability.The production of higher quality and more uniform evidence would be helpful in informing decisions. Researchers should strive to sufficiently account for confounding, assess the impact of methodological decisions through the conduct and communication of sensitivity analyses, and improve the reporting of methods, and other aspects of the study, most importantly the description of the intervention and the context in which it is implemented.

On inferences about lag effects using lag models in air pollution time-series studies

The choice of lag length is a matter of uncertainty in air pollution time-series studies. Lag models and model selections are widely used for inferences about lag effects, but there is lack of discussion on the integration of the two. We aimed to provide theoretical discussion on the performance of lag models, and the impact of model selections on inferences about lag effects. Bias and model selections based upon information criteria, statistical significance, effect size, and model averaging were discussed in the context of lag analysis. A simulation with eight of PM_2.5-mortality relation scenarios was also conducted in order to explore the performances of lag models and to compare the model selections. The application of lag models with an insufficient lag interval taken into account (i.e. insufficient lag models) provides biased estimates. We provided features of the model selections and showed their pitfalls in lag analysis of air pollution time-series studies. We also discussed limitations of meta-analysis which fails to consider the application of different lag models in individual studies. To foster exploration on air pollution-lag-response relations with relevant tools, we encourage researchers to compare different lag models in terms of effect estimates and variance estimates, and to report their favored models and competing models together based upon scientific knowledge supporting lag-response relations.

Temporal variations in ambient particulate matter reduction associated short-term mortality risks in Guangzhou, China: A time-series analysis (2006-2016)

Numerous studies have reported associations between ambient particulate matter (PM) and daily mortality; however, little is known about temporal variations in ambient air pollution associated mortality risks, particularly in developing countries with limited long time-series air monitoring data. In present study, we assessed the associations and temporal relationships between ambient PM and daily mortality in Guangzhou, China, during 2006-2016. With this unique 11-year dataset, we related daily concentrations of PM with aerodynamic diameter < 2.5 μm (PM_2.5), between 2.5 and 10 μm (PM_10-2.5) and <10 μm (PM₁₀) to daily mortality in Guangzhou. We applied overdispersed Poisson regression with adjustment for time trend and potential confounding factors. Multiple level sensitivity analyses were conducted to examine the robustness of main results. Between 2006 and 2016, annual concentrations of PM_2.5 decreased by 50.8% to 27.0 μg/m³, of PM_10-2.5 by 27.6% to 16.2 μg/m³, and of PM₁₀ by 44.1% to 43.3 μg/m³ in Guangzhou. In this study, per 10 μg/m³ increases in mean concentrations at current day and 6 prior days of death (lag06), we observed increases in total mortality risks of 0.55% (95% Confidence Interval (CI): 0.24%, 0.86%) for PM_2.5, 0.99% (95%CI: 0.48%, 1.50%) for PM_10-2.5, and 0.44% (95%CI: 0.22%, 0.65%) for PM₁₀. Stronger associations were observed for ambient PM on cardio-respiratory mortality and people at age ≥ 65 years. Despite drastic reductions in annual PM levels, PM_2.5 associated cardiovascular and respiratory mortality risks remained significant at 1.26% (95%CI: 0.19%, 2.35%) and 1.91% (95%CI: 0.25%, 3.60%) during 2014-2016. Further, PM_2.5 and PM₁₀ associated respiratory mortality risks showed increasing trend over time (p-value = 0.03 for PM_2.5). In summary, though ambient PM levels decreased substantially in Guangzhou in recent years, PM_2.5 and PM₁₀ associated cardio-respiratory mortality risks remained significant and respiratory mortality risks even increased. Our findings provide strong rationale for continuation of ambient air pollution control effort for public health protection in the future.

Temporal variability of short term effects of PM10 on mortality in Seoul, Korea

Health effects of PM₁₀ on mortality have been studies worldwide. However, not many studies have questioned possibility that short-term effects of PM₁₀ can be changed over time. Identifying temporal variability of the effects would be of help to getting more valid PM₁₀ effect estimates which are a major basis for public health policies. In this study, temporal variability of short-term effects of PM₁₀ for mortality was investigated from 2001 to 2015 in Seoul, Korea. A time series analysis was used to estimate the effects of PM₁₀ on all-cause, circulatory, and respiratory mortality. Study period was divided into five years of moving time window, and relative risks and its 95% confidence intervals were estimated using distributed lag model for each time window. The annual average of PM₁₀ in Seoul decreased from 52.6 μg/m³ in 2001 to 40.5 μg/m³ in 2015. There were significant temporal trends in PM₁₀ effects regarding each mortality. The effects of PM₁₀ tend to slightly increase in early of the study period and then dropped in recent years. An increase of 2 days of cumulative exposure of PM₁₀ was associated with 0.31% (95% confidence interval: 0.15, 0.46) increase in all-cause mortality for 2001-2005 period, 0.61% (95% confidence interval: 0.34, 0.89) increase in 2005-2009 period, and -0.06% (95% confidence interval: -0.38, 0.25) increase in 2011-2015 period. We found evidence that short-term effects of PM₁₀ on mortality have been changed over time in Seoul, Korea. The observed temporal trend might attributable from two factors which are change of PM₁₀ compositions and population vulnerability. If effects of PM₁₀ vary over time, considering its change would be necessary not only in the estimation of the PM₁₀ effect but also its application for a variety of public health policies.

Impact of air pollution on cause-specific mortality in Korea: Results from Bayesian Model Averaging and Principle Component Regression approaches

Health effects related to air pollution are a major global concern. Related studies based on reliable exposure assessment methods would potentially enable policy makers to propose appropriate environmental management policies. In this study, integrated Bayesian Model Averaging (BMA) and Principle Component Regression (PCR) were adopted to assess the severity of air pollution impacts on mortality related to circulatory, respiratory and skin diseases in 25 districts of Seoul, South Korea for the years 2005-2015. These methods were consistent in determining the best regression models and most important pollutants related to mortality in those highly susceptible to poor air quality. Specifically, the results demonstrated that pneumonia was highly associated with air pollution, with a large determination coefficient (BMA: 0.46, PCR: 0.51) and high model's posterior probability (0.47). The most reliable prediction model for pneumonia was indicated by the lowest Bayesian Information Criterion. Among the pollutants, particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀) was associated with serious health risks on evaluation, with the highest posterior inclusion probabilities (range, 80.20 to 100.00%) and significantly positive correlation coefficients (range, 0.14 to 0.34, p < 0.05). In addition, excessive PM₁₀ concentration (approximately 2.54 times the threshold) and a continuous increase in mortality due to respiratory diseases (approximately 1.50-fold in 10 years) were also exhibited. Overall, the results of this study suggest that currently, socio-environmental policies and international collaboration to mitigate health effects of air pollution is necessary in Seoul, Korea. Moreover, consideration of uncertainty of the regression model, which was verified in this research, will facilitate further application of this approach and enable optimal prediction of interactions between human and environmental factors.

Has the risk of mortality related to short-term exposure to particles changed over the past years in Athens, Greece?

Although the health effects of short-term exposure to ambient particles have been well documented, there is a need to update scientific knowledge due to the continuously changing profile of the air pollution mixture. Furthermore the effect of the severe economic crisis in Greece that started in 2008 on previously reported associations has not been studied. We assessed the change in mortality risk associated with short-term exposure to PM₁₀ in Athens, Greece during 2001-12. Time-series data on the daily concentrations of regulated particles and all cause, cardiovascular and respiratory mortality were analyzed using overdispersed Poisson regression models, controlling for time-varying confounders such as seasonality, meteorology, influenza outbreaks, summer holidays and day of the week. We assessed changes in risk over time by inclusion of an interaction term between particles' levels and time or predefined periods, i.e. 2001-07 and 2008-12. While the related mortality risks increased over the analyzed period, the difference before and after 2008 was significant only for total mortality (p-value for interaction .03) and driven by the difference observed among those ≥75 years. An interquartile increase in PM₁₀ before 2008 was associated with 1.51% increase in deaths among ≥75 years (95% Confidence interval (CI): 0.62%, 2.40%), while after 2008 with a 2.61% increase (95%CI: 1.72%, 3.51%) (p-value for interaction .01). Our results indicate that despite the decline in particles' concentration in Athens, Greece during 2001-12 the associated mortality risk has possibly increased, suggesting that the economic crisis initiated in 2008 may have led to changes in the particles' composition due to the ageing of the vehicular fleet and the increase in the use of biomass fuel for heating.

Associations between mortality and prolonged exposure to elevated particulate matter concentrations in East Asia

Previous epidemiological studies regarding mortality and particulate matter with an aerodynamic diameter of <10μm (PM₁₀) have considered only absolute concentrations of PM₁₀ as a risk factor. However, none have evaluated the durational effect of multi-day periods with high PM₁₀ concentrations. To evaluate the durational effect (i.e., number of days) of high PM₁₀ concentrations on mortality, we collected data regarding 3,662,749 deaths from 28 cities in Japan, South Korea, and China (1993-2009). Exposure was defined as consecutive days with daily PM₁₀ concentrations ≥75μg/m³. A Poisson model was used with duration as the variable of interest, while controlling for daily PM₁₀ concentrations, meteorological variables, seasonal trends, and day of the week. The increase in mortality risk for each additional consecutive day with PM₁₀ concentrations ≥75μg/m³ was 0.68% in Japan (95% confidence interval [CI]: 0.35-1.01%), 0.48% in South Korea (95% CI: 0.30-0.66%), and 0.24% in China (95% CI: 0.14-0.33%). The annual average maximum number of consecutive days with high PM₁₀ in Japan (2.40days), South Korea (6.96days), and China (42.26days) was associated with non-accidental death increases of 1.64% (95% CI: 1.31-1.98%), 3.37% (95% CI: 3.19-3.56%), and 10.43% (95% CI: 10.33-10.54%), respectively. These findings may facilitate the planning of public health interventions to minimize the health burden of air pollution.

Does a lag-structure of temperature confound air pollution-lag-response relation? Simulation and application in 7 major cities, Korea (1998-2013)

BACKGROUND

Temperature must be controlled when estimating the associations of short-term exposure to air pollution and mortality. Given that multi-country studies have implied temperature has lagged effects, we aim to explore confounding by temperature-lag-response and investigate PM₁₀-lag-mortality relation in 7 cities, Korea.

METHODS

In a simulation study, we compared the performance of different methods to control for: the same day temperature, a lagged temperature and distributed lags of temperature. In a real data study, we explored PM₁₀-lag-mortality relation in 7 cities using these different methods.

RESULTS

We confirmed that a model with insufficient control of temperature offers a biased estimate of PM₁₀ risk. The degree of bias was from -82% to 95% in simulation settings. A real data study shows estimates among different models by temperature adjustments and PM₁₀ lag variables ranging from -0.3% to 0.4% increase in the risk of all-cause mortality, with a 10μg/m³ increase in PM₁₀. Controlling for temperature as distributed lags for 21 days provided 0.25% (95% CI: 0.1, 0.4) increase in the risk of all-cause mortality.

CONCLUSIONS

A lag structure of temperature can confound the air pollution-lag-response relation. Temperature-lag-response relation should be evaluated when estimating air pollution-lag-response relation. As a corollary, air pollution and temperature risk in mortality can be estimated using the same regression model.

Assessment of temporal variation for the risk of particulate matters on asthma hospitalization

Increased ambient concentration of particulate matters are considered as one of major causes for increased prevalence or exacerbation of asthma or asthma like symptoms. Recently, possible temporal variation in risks of PM on mortality has been suggested. We investigated short-term effect of both PM₁₀ and PM_2.5 on asthma hospitalization, and assessed temporal variation of PM risks in Seoul, Korea, 2003-2011. Generalized additive model was used to estimate PM risks on asthma hospitalization with consideration by long-term trend, influenza epidemic, day of week, meteorological factors. To assess temporal variation of PM risks, year-round PM risks were estimated. Stratified analysis by season and age-group were also conducted. Estimated RRs of PM on asthma hospitalization by an increase of 10㎍/㎥were 1.0084 (95% CI: 1.0041-1.0127) and 1.0156 (95% CI: 1.0055-1.0259) respectively with 7-days lag periods (lag06). PM_2.5 had stronger effect than PM₁₀ for all age group. Elderly group was most affected by PM. For the analysis of temporal variation of PM risks, we found increasing trend in total population and the elderly group. In the season-specific analysis, we also found increasing trend in winter for PM₁₀, and in spring for PM_2.5. PM₁₀ and PM_2.5 has adverse effect on asthma hospitalization with evidence suggesting temporal variation in PM risks. Further research will be needed to confirm the temporal variation of PM risk on asthma hospitalization, and to identify casual factors affecting this temporal variation. This study results could be evidentiary materials for establishing valid public health policies to reduce health burden or economic burden of asthma.