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

Ambient dust pollution with all-cause, cardiovascular and respiratory mortality: A systematic review and meta-analysis

A severe health crisis has been well-documented regarding dust particle exposure. We aimed to present the risk of all-cause, cardiovascular, and respiratory mortality due to particulate matter (PM) exposure during non-dust and dust storm events by performing a meta-analysis. A systematic review of the literature was conducted by an online search of the databases (Google Scholar, Web of Science, Scopus, and PubMed) with no restrictions according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines until December 2022. We performed a random-effects model to compute the pooled rate ratio (RR) of mortality with 95 % confidence intervals (CI). The Office of Health Assessment and Translation (OHAT) risk of bias rating tool was prepared to assess the quality of the individual study. The registration number in PROSPERO was CRD42023423212. We found a 16 % (95 % CI: 0.7 %, 24 %) increase in all-cause, 25 % (95 % CI: 14 %, 37 %) increase in cardiovascular, and 18 % (95 % CI: 13 %, 22 %) increase in respiratory mortality per 10 μg/m3 increment in dust exposure. Furthermore, the RRs per 10 μg/m3 increment in PM10-2.5 were 1.046 (95 % CI: 1.019, 1.072)¸ 1.085 (95 % CI: 1.045, 1.0124), and 1.089 (95 % CI: 0.939, 1.24) for all-cause, cardiovascular, and respiratory mortality, respectively. PM10 during dust days significantly increased the all-cause (1.013, 95 % CI: 1.007, 1.018) cardiovascular mortality risk (1.014, 95 % CI: 1.009, 1.02). We also found significant evidence for all-cause, cardiovascular, and respiratory mortality among females and the elderly age group due to dust particle (PM10-2.5 and PM10) exposure. Our results provided significant evidence about high concentrations of PM10-2.5 and PM10 during dust storm events related to mortality risk.

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.

Short-term exposure to PM10 and cardiovascular hospitalization in persons with and without disabilities: Invisible population in air pollution epidemiology

Persons with disabilities (PwD), the world's largest minority, can be more susceptible to particulate matter (PM) than persons without disabilities. Although numerous studies have addressed population susceptibility to PM, PwD have not been studied in air pollution epidemiology. This study investigated the association between short-term exposure to PM with an aerodynamic diameter smaller than 10 μm (PM₁₀) and cardiovascular hospital admissions by the existence of a disability, while also considering intersections of disability and other socio-demographic characteristics in South Korea. We used the National Health Insurance Service-National Sample Cohort (NHIS-NSC) to investigate the association between short-term exposure to PM₁₀ and cardiovascular hospital admissions in seven metropolitan cities from 2002 to 2015. We conducted a time-stratified case-crossover analysis using conditional logistic regression and adjusted for daily temperature, relative humidity, air pressure, and national holidays. We conducted stratified analyses according to the existence of a disability, disability type and severity, and socio-demographic characteristics. The results showed that a 10 μg/m³ increase in the 0-3 moving average level of PM₁₀ was associated with 1.9 % (95 % confidence interval [CI]: 0.7 %, 3.2 %) and 0.0 % (95 % CI: -0.5 %, 0.5 %) increase in cardiovascular admissions in persons with and without disabilities, respectively. Among PwD, the associations were pronounced in people with brain lesion disorders (percent change [PC]: 2.7 %, 95 % CI: 0.5 %, 5.0 %), people with visual impairment (PC: 3.0 %, 95 % CI: -1.0 %, 7.1 %), and people with severe disability (PC: 3.0 %, 95 % CI: 0.9 %, 5.0 %). We found that PwD may be more adversely affected by PM₁₀ than their non-disabled counterparts. This suggests that PwD is a social identity reflecting the socially marginalized and disadvantaged population in air pollution epidemiology.

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.

Effect modification by sex for associations of fine particulate matter (PM2.5) with cardiovascular mortality, hospitalization, and emergency room visits: systematic review and meta-analysis

Particulate matter with aerodynamic diameter no larger than 2.5 μm (PM2.5) has been linked to cardiovascular diseases (CVDs) but evidence for vulnerability by sex remains unclear. We performed systematic review and meta-analysis to synthesize the state of scientific evidence on whether cardiovascular risks from PM2.5 differ for men compared to women. The databases Pubmed, Scopus, Embase, and GreenFILE were searched for studies published Jan. 1995 to Feb. 2020. Observational studies conducting subgroup analysis by sex for impacts of short-term or long-term exposure to PM2.5 on target CVDs were included. Data were independently extracted in duplicate and pooled with random-effects meta-regression. Risk ratios (RRs) for long-term exposure and percent changes in outcomes for short-term exposure were calculated per 10 μg/m3 PM2.5 increase. Quality of evidence of risk differences by sex was rated following Grading of Recommendations Assessment, Development and Evaluation (GRADE). A total of 12,502 articles were screened, with 61 meeting inclusion criteria. An additional 32 studies were added from citation chaining. RRs of all CVD mortality for long-term PM2.5 for men and women were the same (1.14; 95% CI: 1.09, 1.22) indicating no statistically different risks. Men and women did not have statistically different risks of daily CVD mortality, hospitalizations from all CVD, ischemic heart disease, cardiac arrest, acute myocardial infarction, and heart failure from short-term PM2.5 exposure (difference in % change in risk per 10 μg/m3 PM2.5: 0.04 (95% CI, -0.42 to 0.51); -0.05 (-0.47 to 0.38); 0.17 (-0.90, 1.24); 1.42 (-1.06, 3.97); 1.33 (-0.05, 2.73); and -0.48 (-1.94, 1.01), respectively). Analysis using GRADE found low or very low quality of evidence for sex differences for PM2.5-CVD risks. In conclusion, this meta-analysis and quality of evidence assessment of current observational studies found very limited evidence of the effect modification by sex for effects of PM2.5 on CVD outcomes in adults, which can inform clinical approaches and policies.

Accurate real-time monitoring of fine dust using a densely connected convolutional networks with measured plasma emissions

Accurate identification and monitoring of fine dust are emerging as a primary global issue for addressing the harmful effects of fine dust on public health. Identifying the source of fine dust is indispensable for ensuring the human lifespan as well as preventing environmental disasters. Here a simple yet effective spark-induced plasma spectroscopy (SIPS) unit combined with deep learning for real-time classification is verified as a fast and precise PM (particulate matter) source identification technique. SIPS promises portable use, label-free detection, source identification, and chemical susceptibility in a single step with acceptable speed and accuracy. In particular, the densely connected convolutional networks (DenseNet) are used with measured spark-induced plasma emission datasets to identify PM sources at above 98%. The identification performance was compared with other common classification methods, and DenseNet with dropouts (30%), optimized batch size (16), and cyclic learning rate training emerged as the most promising source identification method.

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.