A component-specific exposure-mortality model for ambient PM2.5 in China: findings from nationwide epidemiology based on outputs from a chemical transport model

An association between PM2.5 components and respiratory infectious diseases: A China's mainland-based study

The particulate matter with diameter of less than 2.5 µm (PM2.5) is an important risk factor for respiratory infectious diseases, such as scarlet fever, tuberculosis, and similar diseases. However, it is not clear which component of PM2.5 is more important for respiratory infectious diseases. Based on data from 31 provinces in mainland China obtained between 2013 and 2019, this study investigated the effects of different PM2.5 components, i.e., sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and organic matter (OM), and black carbon (BC), on respiratory infectious diseases incidence [pulmonary tuberculosis (PTB), scarlet fever (SF), influenza, hand, foot, and mouth disease (HFMD), and mumps]. Geographical probes and the Bayesian kernel machine regression (BKMR) model were used to investigate correlations, single-component effects, joint effects, and interactions between components, and subgroup analysis was used to assess regional and temporal heterogeneity. The results of geographical probes showed that the chemical components of PM2.5 were associated with the incidence of respiratory infectious diseases. BKMR results showed that the five components of PM2.5 were the main factors affecting the incidence of respiratory infectious diseases (PIP>0.5). The joint effect of influenza and mumps by co-exposure to the components showed a significant positive correlation, and the exposure-response curve for a single component was approximately linear. And single-component modelling revealed that OM and BC may be the most important factors influencing the incidence of respiratory infections. Moreover, respiratory infectious diseases in southern and southwestern China may be less affected by the PM2.5 component. This study is the first to explore the relationship between different components of PM2.5 and the incidence of five common respiratory infectious diseases in 31 provinces of mainland China, which provides a certain theoretical basis for future research.

Combined health effects of PM2.5 components on respiratory mortality in short-term exposure using BKMR: A case study in Sichuan, China

One of the major causes of global mortality is respiratory diseases. Fine particulate matter (PM2.5) increased the risk of respiratory death in short-term exposure. PM2.5 is the chemical mixture of components with different health effects. The combined health effects of PM2.5 are determined by the role of each component and the potential interaction between components, but they have not been studied in short-term exposure. Sichuan Province (SC), with high respiratory mortality and heavy PM2.5 pollution, had distinctive regional differences in four regions in sources and proportions of PM2.5, so it was divided into four regions to explore the combined health effects of PM2.5 components on respiratory mortality in short-term exposure and to identify the main hazardous components. Due to the multicollinear, interactive, and nonlinear characteristics of the associations between PM2.5 components and respiratory mortality, Bayesian kernel machine regression (BKMR) was used to characterize the combined health effects, along with quantile-based g-computation (QGC) as a reference. Positive combined effects of PM2.5 were found in all four regions of Sichuan using BKMR with excess risks (ER) of 0.0101-0.0132 (95 % CI: 0.0093-0.0158) and in the central basin and northwest basin using QGC with relative risks (RR) of 1.0064 (95 % CI: 1.0039, 1.0089) and 1.0044 (95 % CI: 1.0022, 1.0066), respectively. In addition, the adverse health effect was larger in cold seasons than that in warm seasons, so vulnerable people should reduce outdoor activities in heavily polluted days, especially in the cold season. For the components of PM2.5, the BC and OM mainly from traffic, dominated the adverse health effects on respiratory mortality. Furthermore, NO3- might aggravate the adverse health effects of BC/OM. Therefore, BC/OM and NO3- should be focused together in air pollution control.

Air pollution health burden embodied in China's supply chains

Product trade plays an increasing role in relocating production and the associated air pollution impact among sectors and regions. While a comprehensive depiction of atmospheric pollution redistribution through trade chains is missing, which may hinder targeted clean air cooperation among sectors and regions. Here, we combined five state-of-the-art models from physics, economy, and epidemiology to track the anthropogenic fine particle matters (PM_2.5) related premature mortality along the supply chains within China in 2017. Our results highlight the key sectors that affect PM_2.5-related mortality from both production and consumption perspectives. The consumption-based effects from food, light industry, equipment, construction, and services sectors, caused 2-22 times higher deaths than those from a production perspective and totally contributed 63% of the national total. From a cross-boundary perspective, 25.7% of China's PM_2.5-related deaths were caused by interprovincial trade, with the largest transfer occurring from the central and northern regions to well-developed east coast provinces. Capital investment dominated the cross-boundary effect (56% of the total) by involving substantial equipment and construction products, which greatly rely on product exports from regions with specific resources. This supply chain-based analysis provides a comprehensive quantification and may inform more effective joint-control efforts among associated regions and sectors from a health risk perspective.

The causal links between long-term exposure to major PM2.5 components and the burden of tuberculosis in China

BACKGROUND

We aimed to estimate the causal impacts of long-term exposure to major PM_2.5 components - including black carbon, organic matter, sulfate, nitrate, and ammonium - on the incidence and mortality of tuberculosis in China.

METHODS

We collected annual and provincial-level tuberculosis incidence and mortality, concentrations of PM_2.5 components, and socioeconomic indicators from between 2004 and 2018 in mainland China. We used the difference-in-differences (DID) causal inference approach with a generalized weighted quantile sum (gWQS) regression model to estimate the long-term effects and relative contributions of PM_2.5 components' exposure on tuberculosis incidence and mortality.

RESULTS

We found that long-term multi-components exposure was significantly associated with tuberculosis incidence (WQS index IR%:8.34 %, 95 % CI:4.54 %-12.27 %) and mortality (WQS index IR%:19.49 %, 95 % CI: 9.72 %-30.13 %). Primary pollutants, black carbon and organic matter, contributed most of the overall mixture effect (over 85 %). Nitrate showed a critical role in tuberculosis burden in not-aging provinces and in regions at the Q3 stratum (i.e., the 3rd quartile) of GDP per capita and urbanization rate. Meanwhile the contribution of sulfate to tuberculosis burden in regions at the Q1 stratum of GDP per capita and urbanization rate was the largest among the effect of secondary pollutants (i.e., sulfate, nitrate, and ammonium).

CONCLUSION

The mitigation of black carbon and organic matter pollution may significantly reduce the tuberculosis burden in China. Controlling nitrate emissions and increasing clean energy (i.e., energy sources with limited pollution emissions, such as natural gas and clean coal) may also be effective in certain regions.

Source sectors underlying PM2.5-related deaths among children under 5 years of age in 17 low- and middle-income countries

BACKGROUND

Fine particulate matter (PM_2.5) from different source sectors might differ in toxicity. However, data from large-scale studies on vulnerable children in low- and middle-income countries (LMICs) are insufficient.

OBJECTIVE

To analyze the association of under-five death (U5D) with long-term exposure to PM_2.5 from different sources.

METHOD

We evaluated demographic and health survey data for 79,995 babies born in 2017 in 16 Asian and African LMICs (AA-LMICs) and a Latin America low-income country (i.e., Haiti). Long-term exposure to PM_2.5 was assessed by a well-established product that attributed the annual concentration to 20 source sectors in 2017. The associations of survival during < 5-year periods with each source-specific concentration of PM_2.5 were analyzed by Cox regression with multiple adjustments. We derived a multiple-pollutant ridge regression model to estimate the joint exposure-response function (JERF) between U5D and PM_2.5 mixtures. To evaluate how sources affected PM_2.5 toxicity, we evaluated the number of U5Ds attributable to PM_2.5 based on the source profiles for 88 AA-LMICs.

RESULTS

According to the single-pollutant model, the risk of U5D increased by 7% (95% confidence interval [CI]: 5%, 9%) for each 10 μg/m³ increment in total PM_2.5 concentration. The model performance was lower than that of the multiple-pollutant ridge regression model. For each 10 μg/m³ increment in PM_2.5, the excess risk of U5D ranged from 6% (95% CI: 4%, 9%) in Nepal to 10% (95% CI: 6%, 14%) in Mauritania. Based on the JERF, PM_2.5 contributed to 817,647 (95% CI: 585,729, 1,050,439), i.e., 28.0% (95% CI: 20.1%, 35.8%), of all U5Ds across the 88 AA-LMICs. The PM_2.5-related U5Ds were mostly attributable to PM_2.5 produced by desert dust, followed by solid biofuel combustion and open fires.

CONCLUSION

The average toxicity of PM_2.5 varied by source profile, which should be taken into consideration when planning public health interventions. For some AA LMICs, natural sources of PM_2.5 had the most significant health effects, and should not be ignored to ensure the protection of child health.

Short-term exposure to fine particulate matter constituents and mortality: case-crossover evidence from 32 counties in China

A growing number of studies associated increased mortality with exposures to specific fine particulate (PM_2.5) constituents, while great heterogeneity exists between locations. In China, evidence linking PM_2.5 constituents and mortality was extensively sparse. This study primarily aimed to quantify short-term associations between PM_2.5 constituents and non-accidental mortality among the Chinese population. We collected daily mortality records from 32 counties in China between January 1, 2011, and December 31, 2013. Daily concentrations of main PM_2.5 constituents (organic carbon (OC), elemental carbon (EC), nitrate (NO₃^-), sulfate (SO₄^2-), and ammonium (NH₄⁺)) were estimated using the modified Community Multiscale Air Quality model. Time-stratified case-crossover design with conditional logistic regression models was adopted to estimate mortality risks associated with short-term exposures to PM_2.5 mass and its constituents. Stratification analyses were done by sex, age, and season. A total of 116,959 non-accidental deaths were investigated. PM_2.5 concentrations on the day of death were averaged at 75.7 µg m^-3 (control day: 75.6 µg m^-3), with an interquartile range (IQR) of 65.2 µg m^-3. Per IQR rise in PM_2.5, EC, OC, NO₃^-, SO₄^2-, and NH₄⁺ at lag-04 day was associated with an increase in non-accidental mortality of 2.4% (95% confidence interval, (1.0-3.7), 1.7% (0.8-2.7), 2.9% (1.6-4.3), 2.1% (0.4-3.9), 1.0% (0.2-1.9), and 1.6% (0.3-2.9), respectively. Both PM_2.5 mass and its constituents were strongly associated with elevated cardiovascular mortality risks, but only PM_2.5, EC, and OC were positively associated with respiratory mortality at lag-3 day. PM_2.5 mass and its constituents associated effects on mortality varied among sex- and age-specific subpopulations. Differences in the seasonal pattern of associations exist among PM_2.5 constituents, with stronger effects related to EC and NO₃^- in warm months but SO₄^2- and NH₄⁺ in cold months. Short-term exposures to PM_2.5 compositions were positively associated with increased risks of mortality, particularly those constituents from combustion-related sources.