Association between short-term exposure to ambient air pollution and daily mortality: a time-series study in Eastern China

Assessing the short-term effects of PM2.5 and O3 on cardiovascular mortality using high-resolution exposure: a time-stratified case cross-over study in Southwestern China

Air pollution is a major risk factor of cardiovascular disease (CVD). To date, limited studies have estimated the effects of ambient air pollution on CVD mortality using high-resolution exposure assessment, which might fail to capture the spatial variation in exposure and introduce bias in results. Besides, the three-year action plan (TYAP, 2018-2020) was released; thus, the constitution and health effect of air pollutants may have changed. In this study, we estimated the short-term effect exposed to particulate matters with parameter less than 2.5 µm (PM2.5) and ozone (O3) with 0.05° × 0.05° resolution on CVD mortality and measured the influence of TYAP in the associations. We used random forest models with spatial weight matrices to attain high-resolution pollutant concentrations and conditional Poisson regression to assess the relationship between air pollution and cardiovascular mortality. With an increase of 10 µg/m3 in PM2.5 and O3 during 2018-2021 in the Sichuan Basin (SCB), CVD mortality increased 1.0134 (95% CI 1.0102, 1.0166) and 1.0083 (95% CI 1.0060, 1.0107), respectively, using high-resolution air pollutant concentration, comparing to 1.0070 (95% CI 1.0052, 1.0087) and 1.0057 (95% CI 1.0037, 1.0078) using data from air quality monitoring stations (AQMs). After TYAP, the relative risk (RR) due to PM2.5 rose up to 1.0149 (95% CI 1.0054, 1.0243), and the RR due to O3 rose up to 1.0089 (95% CI 1.0030, 1.0148) in Sichuan Province. We found significantly positive association of cardiovascular mortality and air pollution in Sichuan Province. And using high-resolution exposure would be more accurate to estimate the effect of air pollution on CVD. After TYAP, the cardiovascular mortality risk estimation due to PM2.5 decreased in elderly in SCB, and the risk due to O3 increased in Sichuan Province.

Short-term exposure to six air pollutants and cause-specific cardiovascular mortality of nine counties or districts in Anhui Province, China

Recently, the burden of cardiovascular disease (CVD) has attracted global attention. Meanwhile, CVD has become the leading cause of death in China. Some epidemiological studies have indicated that ambient air pollution may contribute to increased mortality from CVD diseases. Many studies have found a strong association between air pollutants and the risk of CVD deaths in some big cities, but few have focused on the effects of six pollutants in rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO₂, O₃, PM_2.5, PM₁₀, and SO₂) on CVD deaths of rural areas in Anhui Province and to further clarify which populations were susceptible to air pollution. First, the generalized additive models were combined with the distributed lag nonlinear models to evaluate the individual effects of air pollution on CVD deaths in each area. Then, random-effects models were used to aggregate the associations between air pollutants and CVD mortality risk in nine regions. Overall, all six pollutants had a statistically significant effect on the risk of CVD deaths on the lag 07 days. The associations between PM_2.5, PM₁₀, and SO₂ and daily CVD deaths were strongest, with maximum cumulative RR (lag 07) of 1.91 (1.64-2.18), 2.27 (1.50-3.05), and 2.13 (1.44-2.82). In general, we found that six air pollutants were the important risk factors for CVD and specific CVD deaths in Anhui Province. The elderly were susceptible to PM_2.5, PM₁₀, and SO₂.

Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution

Chiang Mai is one of the most known cities of Northern Thailand, representative for various cities in the East and South-East Asian region exhibiting seasonal smog crises. While a few studies have attempted to address smog crises effects on human health in that geographic region, research in this regard is still in its infancy. We exploited a unique situation based on two factors: large pollutant concentration variations due to the Chiang Mai smog crises and a relatively large sample of out-patient visits. About 216,000 out-patient visits in the area of Chiang Mai during the period of 2011 to 2014 for upper (J30-J39) and lower (J44) respiratory tract diseases were evaluated with respect to associations with particulate matter (PM10), ozone (O3), and nitrogen dioxide (NO2) concentrations using single-pollutant and multiple-pollutants Poisson regression models. All three pollutants were found to be associated with visits due to upper respiratory tract diseases (with relative risks RR = 1.023 at cumulative lag 05, 95% CI: 1.021–1.025, per 10 μg/m3 PM10 increase, RR = 1.123 at lag 05, 95% CI: 1.118–1.129, per 10 ppb O3 increase, and RR = 1.110 at lag 05, 95% CI: 1.102–1.119, per 10 ppb NO2 increase). Likewise, all three pollutants were found to be associated with visits due to lower respiratory tract diseases (with RR = 1.016 at lag 06, 95% CI: 1.015–1.017, per 10 μg/m3 PM10 increase, RR = 1.073 at lag 06, 95% CI: 1.070–1.076, per 10 ppb O3 increase, and RR = 1.046 at lag 06, 95% CI: 1.040–1.051, per 10 ppb NO2 increase). Multi-pollutants modeling analysis identified O3 as a relatively independent risk factor and PM10-NO2 pollutants models as promising two-pollutants models. Overall, these results demonstrate the adverse effects of all three air pollutants on respiratory morbidity and call for air pollution reduction and control.

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.

Time series analysis of short-term effects of particulate matter pollution on the circulatory system disease mortality risk in Lishui District, China

Epidemiological evidence has shown a significant association between short-term exposure to air pollution and mortality risk for circulatory system diseases (CSD). However, informative insights on the significance and magnitude of its relationship in the process of government interventions on abating air pollution are still lacking, particularly in a burgeoning Chinese city. In this study, we conducted a time series study in Lishui District, Nanjing, to examine the effect of ambient particulate matter (PM), e.g., PM_2.5 and PM₁₀, on daily death counts of CSD which included cardiovascular disease (CVD), cerebrovascular disease (CEVD), and arteriosclerotic heart disease (ASHD) mortality from January 1, 2015, to December 31, 2019. The results revealed that each 10 μg/m³ increase in PM_2.5 and PM₁₀ concentration at lag0 day was associated with an increase of 1.33% (95% confidence interval, 0.08%, 2.60%) and 1.12% (0.43%, 1.82%) in CSD mortality; 2.42% (0.44%, 4.43%) and 1.43% (0.32%, 2.55%) in CVD mortality; 1.20% (- 0.31%, 2.73%) and 1.21% (0.38%, 2.05%) in CEVD mortality; and 2.78% (0.00%, 5.62%) and 1.66% (0.14%, 3.21%) in ASHD mortality, respectively. For cumulative risk, the corresponding increase in daily mortality for the same change in PM_2.5 concentration at lag03 day was significantly associated with 1.94% (0.23%, 3.68%), 3.17% (0.58%, 5.84%), 2.38% (0.17%, 4.63%), and 4.92% (1.18%, 8.81%) for CSD, CVD, CEVD, and ASHD, respectively. The exposure-response curves were approximately nonlinear over the entire exposure range of the PM concentrations. We also analyzed the effect modifications by season (warm or cold), age group (0-64 years, 65-74 years, or ≥ 75 years), and sex (male or female). Although not statistically significant, stratified analysis showed greater vulnerability to PM exposure for cold season, population over 65 years of age, and female group.

Six air pollutants and cause-specific mortality: a multi-area study in nine counties or districts of Anhui Province, China

Air pollution and its negative effects on health of people have been a global concern. Many studies had found a strong association between air pollutants and risk of death, but few had focused on the effects of six pollutants and rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO₂, O₃, PM_2.5, PM₁₀, and SO₂) on non-accidental and respiratory deaths in rural areas of Anhui Province by adjusting for confounding factors, and to further clarify which populations were susceptible to death associated with air pollution. In the first phase of the analysis, the generalized additive models were combined with the distributed lag non-linear models to evaluate the individual effects of air pollution on death in each area. In the second stage, random-effects models were used to aggregate the associations between air pollutants and mortality risk in nine areas. Overall, six pollutants had the strongest effects on the risk of death on the lag 07 days. The associations between PM_2.5 and NO₂ and daily non-accidental deaths were strongest, with maximum RR (lag 07): 1.63 (1.37-1.88) and 1.67 (1.37-1.96). The maximum pooled effects of association between six air pollutants and RD were PM_2.5, with RR (lag 07): 1.89 (1.45-2.34). PM_2.5 and PM₁₀ had significant differences between the elderly and the non-elderly with respectively, RRR: 1.22 (1.04-1.41) and 1.26 (1.11-1.42). In general, we found that six air pollutants were the important risk factors for deaths (deaths from respiratory disease and non-accidental) in rural areas of Anhui Province. PM₁₀ and PM_2.5 had a considerable impact on the elderly.

Short-term exposure to nitrogen dioxide and mortality: A systematic review and meta-analysis

BACKGROUND

Ambient air pollution has been characterized as a leading cause of mortality worldwide and has been associated with cardiovascular and respiratory diseases. There is increasing evidence that short-term exposure to nitrogen dioxide (NO₂), is related to adverse health effects and mortality.

METHODS

We conducted a systematic review of short-term NO₂ and daily mortality, which were indexed in PubMed and Embase up to June 2021. We calculated random-effects estimates by different continents and globally, and tested for heterogeneity and publication bias.

RESULTS

We included 87 articles in our quantitative analysis. NO₂ and all-cause as well as cause-specific mortality were positively associated in the main analysis. For all-cause mortality, a 10 ppb increase in NO₂ was associated with a 1.58% (95%CI 1.28%-1.88%, I² = 96.3%, Eggers' test p < 0.01, N = 57) increase in the risk of death. For cause-specific mortality, a 10 ppb increase in NO₂ was associated with a 1.72% (95%CI 1.41%-2.04%, I² = 87.4%, Eggers' test p < 0.01, N = 42) increase in cardiovascular mortality and a 2.05% (95%CI 1.52%-2.59%, I² = 78.5%, Eggers' test p < 0.01, N = 38) increase in respiratory mortality. In the sensitivity analysis, the meta-estimates for all-cause mortality, cardiovascular and respiratory mortality were nearly identical. The heterogeneity would decline to varying degrees through regional and study-design stratification.

CONCLUSIONS

This study provides evidence of an association between short-term exposure to NO₂, a proxy for traffic-sourced air pollutants, and all-cause, cardiovascular and respiratory mortality.

Association between ambient air pollution and cause-specific mortality in Cape Town, Durban, and Johannesburg, South Africa: any susceptible groups?

Studies have confirmed that adverse human health effects that are associated with exposure to air pollution may differ depending on other factors such as age, gender, environmental conditions, and socio-economic factors. This study was conducted to assess the association between ambient air pollution and cause-specific mortality in the three big cities in South Africa and to determine the susceptible groups thereof. Cause-specific mortality data for all ages and PM10, NO2, and SO2 in Cape Town, Durban, and Johannesburg for the period from 1 January 2006 to 31 December 2010 were obtained. Statistical analyses were done to estimate the associations between air pollutants and cause-specific mortality. Susceptibility was therefore investigated in stratified analyses by sex and age (≥60 years) and environmental conditions (heat and cold) followed by models with interaction terms. Our estimates showed independent associations between these air pollutants, environmental conditions, and susceptible groups.

The construction of the air quality health index (AQHI) and a validity comparison based on three different methods

The most common currently used air quality risk communication tool, the Air Quality Index (AQI), has been criticized. As a result, Canada proposed the Air Quality Health Index (AQHI) to communicate the health risks of multiple pollutants. However, the AQHI is calculated by directly summing the excess risks from single-pollutant models, which may overestimate the effects of the pollutants. To solve this problem, we introduced two methods for estimating the joint effects of multiple pollutants: the cumulative risk index (CRI) and supervised principal component analysis (SPCA). Based on three methods, i.e., the standard, CRI and SPCA methods, we constructed three types of AQHIs and compared their validity to select the best communication tool. Our results showed that compared with the AQI, all three AQHIs had a linear relationship with mortality. In addition, the CRI-AQHI had the best goodness of fit and captured the overall health risk of pollution mixtures most robustly among various cause-specific mortalities when identifying health risks. Our study indicated that the CRI-AQHI may have the potential to be a better alternative to the standard AQHI in communicating air pollution-related health risks to the public.

Modifiers of the effect of short-term variation in PM2.5 on mortality in Beijing, China

INTRODUCTION

Epidemiologic studies have reported associations between short-term exposure to particulate matter <2.5 μm in aerodynamic diameter (PM_2.5) and mortality, but the role of modifiers remains unclear with studies reporting inconsistent results. We evaluated the impact of individual (age, gender and education) and township (geographic area, socioeconomic status, background air pollution and road density) level factors on the relationship between short-term variation in PM_2.5 with cause-specific mortality in Beijing (population: 21.7 million in 2016), China.

METHODS

Daily PM_2.5 concentrations in each township (n = 327; township population: 2000-359,400; township area: 1-392 km²) within Beijing were estimated by kriging with external drift using measurements from 35 air quality monitoring stations and geographic variables. Time-stratified case-crossover analysis with township-level mortality data from Oct. 1st, 2012 to Dec. 31st, 2013 was then used to examine associations between PM_2.5 exposure estimates and cause-specific mortality, stratified by the potential effect modifiers.

RESULTS

A 10-μg/m³ increase in PM_2.5 concentration was associated with a 0.17% [95% confidence interval (CI): 0.05%-0.29%] and 0.27% (95%CI:0.01%-0.52%) increase in non-accidental and stroke mortality with no lag, a 0.81% (95%CI:0.39%-1.23%) and 0.96% (95%CI:0.35%-1.57%) increase in respiratory disease (RD) and chronic obstructive pulmonary disease (COPD) mortality at a lag of two-day moving average. For individual-level effect modifiers, the elderly showed higher effects for all the specific causes of mortality; those with lower education level showed higher effects for non-accidental, cardiovascular disease and stroke mortality; females showed higher effects for non-accidental and cause-specific cardiovascular diseases. For township-level effect modifiers, effect estimates tended to be larger for suburban areas, areas of lower road density, lower PM_2.5 and lower socioeconomic status.

CONCLUSIONS

Short-term exposure to township-level ambient PM_2.5 was associated with increased mortality in Beijing, with indications of effect modification by both individual and township-level factors.

Modelling rein tension during riding sessions using the generalised additive modelling technique

General additive modelling (GAM-modelling) is an exploratory technique that can be used on longitudinal (time series) data, e.g. rein tension, over a period of time. The aim was to apply GAM-modelling to investigate changes in rein tension during a normal flatwork training session. Six riders each rode two or three of their horses (n=17 horses) during a normal flatwork/dressage training session with video recordings and rein tension measurements (128 Hz). Training sessions were classified according to rider position, stride length and whether horses were straight, bent to the left or bent to the right. The rein tension data were split into strides and for each stride minimal (MIN) and maximal (MAX) rein tension were determined and the area under the rein tension curve (AUC) was calculated. Using data on a contact the three outcome variables MIN, MAX and AUC rein tension were modelled by horse and rein (left/right), and time within the session was modelled as a smooth function. Two additional sets of models were constructed; one set using data within-rein with gait as a fixed effect and one set with rein and gait as fixed effects. Mean ± standard deviation values were MIN: 8.0±7.7 N, AUC: 180±109 Ns, and MAX: 49±31 N. GAM-modelling extracted visually interpretable information from the originally chaotic rein tension signals. Modelled data suggest that MIN, AUC and MAX follow the same pattern within horse. In general, rein tension was lowest in walk, intermediate in trot and highest in canter. Evaluating the entire ride, 12/17 horses systematically showed higher tension in the right rein. It is concluded that GAM-models may be useful for detecting patterns through time in biomechanical data.