Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multisource Data Fusion

Impact of fine particulate matter on latent tuberculosis infection and active tuberculosis in older adults: a population-based multicentre cohort study

Evidence showed that air pollution was associated with an increased risk of tuberculosis (TB). This study aimed to study the impact of long-term exposure to ambient particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) on the acquisition of LTBI and on the risk of subsequent active disease development among rural older adults from a multicentre cohort, which have not yet been investigated to date. A total of 4790 older adults were included in a population-based, multicentre, prospective cohort study (LATENTTB-NSTM) from 2013 to 2018. The level of long-term exposure to PM2.5 for each participant was assessed by aggregating satellite-based estimates. Logistic regression and time-varying Cox proportional hazards models with province-level random intercepts were employed to assess associations of long-term exposures to PM2.5 with the risk of LTBI and subsequent development of active TB, respectively. Out of 4790 participants, 3284 were LTBI-free at baseline, among whom 2806 completed the one-year follow-up and 127 developed newly identified LTBI. No significant associations were identified between PM2.5 and the risk of LTBI. And among 1506 participants with LTBI at baseline, 30 active TB cases were recorded during the 5-year follow-up. Particularly, an increment of 5 μg/m3 in 2-year moving averaged PM2.5 was associated with a 50.6% increased risk of active TB (HR = 1.506, 95% CI: 1.161-1.955). Long-term air pollution might be a neglected risk factor for active TB development from LTBI, especially for those living in developing or less-developed areas where the air quality is poor.

Impaired thyroid hormone sensitivity exacerbates the effect of PM2.5 and its components on dyslipidemia in schizophrenia

BACKGROUND

Dyslipidemia in schizophrenia causes a serious loss of healthy life expectancy, making it imperative to explore key environmental risk factors. We aimed to assess the effect of PM2.5 and its constituents on dyslipidemia in schizophrenia, identify the critical hazardous components, and investigate the role of impaired thyroid hormones (THs) sensitivity in this association.

METHODS

We collected disease data on schizophrenia from the Anhui Mental Health Center from 2019 to 2022. Logistic regression was constructed to explore the effect of average annual exposure to PM2.5 and its components [black carbon (BC), organic matter (OM), sulfate (SO42-), ammonium (NH4+), and nitrate (NO3-)] on dyslipidemia, with subgroup analyses for age and gender. The degree of impaired THs sensitivity in participants was reflected by the Thyroid Feedback Quantile-based Index (TFQI), and its role in the association of PM2.5 components with dyslipidemia was explored.

RESULTS

A total of 5125 patients with schizophrenia were included in this study. Exposure to PM2.5 and its components (BC, OM, SO42-, NH4+, and NO3-) were associated with dyslipidemia with the odds ratios and 95 % confidence interval of 1.13 (1.04, 1.23), 1.16 (1.07, 1.26), 1.15 (1.06, 1.25), 1.11 (1.03, 1.20), 1.09 (1.00, 1.18), 1.12 (1.04, 1.20), respectively. Mixed exposure modeling indicated that BC played a major role in the effects of the mixture. More significant associations were observed in males and groups <45 years. In addition, we found that the effect of PM2.5 and its components on dyslipidemia was exacerbated as impaired THs sensitivity in the patients.

CONCLUSIONS

Exposure to PM2.5 and its components is associated with an increased risk of dyslipidemia in schizophrenia, which may be exacerbated by impaired THs sensitivity. Our results suggest a new perspective for the management of ambient particulate pollution and the protection of thyroid function in schizophrenia.

A super sandstorm altered the abundance and composition of airborne bacteria in Beijing

Sandstorm, which injects generous newly emerging microbes into the atmosphere covering cities, adversely affects the air quality in built environments. However, few studies have examined the change of airborne bacteria during severe sandstorm events. In this work, we analyzed the airborne bacteria during one of the strongest sandstorms in East Asia on March 15th, 2021, which affected large areas of China and Mongolia. The characteristics of the sandstorm were compared with those of the subsequent clean and haze days. The composition of the bacterial community of air samples was investigated using quantitative polymerase chain reaction (qPCR) and high-throughput sequencing technology. During the sandstorm, the particulate matter (PM) concentration and bacterial richness were extremely high (PM2.5: 207 µg/m3; PM10: 1630 µg/m3; 5700 amplicon sequence variants/m3). In addition, the sandstorm brought 10 pathogenic bacterial genera to the atmosphere, posing a grave hazard to human health. As the sandstorm subsided, small bioaerosols (0.65-1.1 µm) with a similar bacterial community remained suspended in the atmosphere, bringing possible long-lasting health risks.

Associations and attributable burdens in late-life exposure to PM2.5 and its major components and depressive symptoms in middle-aged and older adults: A nationwide cohort study

BACKGROUND

Depression in late life has been associated with reduced quality of life and increased mortality. Whether the chronic fine particular matter (PM2.5) and its components exposure are contributed to the older depression symptoms remains unclear.

METHOD

Middle-aged and older adults (>45 years) were selected from the China Health and Retirement Longitudinal Study during the four waves of interviews. The concentrations of PM2.5 and its major constituents were calculated using near real-time data at a spatial resolution of 10 km during the study period. The depressive symptom was evaluated by the Depression Center for Epidemiologic Studies Depression (CES-D)-10 score. The fix-effect model was applied to evaluate the association between PM2.5 and its major constituents with depressive symptoms. Three three-step methods were used to explore the modification role of sleep duration against the depressive symptoms caused by PM2.5 exposure.

RESULTS

In our study, a total of 52,683 observations of 16,681 middle-aged and older adults were assessed. Each interquartile range (IQR) level of PM2.5 concentration exposure was longitudinally associated with a 2.6 % (95 % confidence interval [CI]: 1.3 %, 4.0 %) increase in the depression CES-D-10 score. Regarding the major components of PM2.5, OM, NO3-, and NH4+ showed the leading toxicity effects, which could increase the depression CES-D-10 score by 2.2 % (95 %CI: 1.0 %, 3.4 %), 2.2 % (0.6 %, 3.9 %), and 2.0 % (95 %CI: 0.6 %, 3.4 %) correspondingly. Besides, males were more susceptible to the worse depressive symptoms caused by PM2.5 and its major components exposure than female subpopulations. Shortened sleep duration might be the mediator of PM2.5-associated depressive symptoms.

CONCLUSION

Our results suggest that long-term exposure to PM2.5 and its major components were associated with an increased risk for depressive symptoms in middle-aged and older adults. Reducing the leading components of PM2.5 may cost-effectively alleviate the disease burden of depression and promote healthy longevity in heavy pollutant countries.

Insulin resistance and its relationship with long-term exposure to ozone: Data based on a national population cohort

The relationship of ozone (O3), particularly the long-term exposure, with impacting metabolic homeostasis in population was understudied and under-recognised. Here, we used data from ChinaHEART, a nationwide, population-based cohort study, combined with O3 and PM2.5 concentration data with high spatiotemporal resolution, to explore the independent association of exposure to O3 with the prevalence of insulin resistance (IR). Among the 271 540 participants included, the crude prevalence of IR was 39.1%, while the age and sex standardized prevalence stood at 33.0%. Higher IR prevalence was observed with each increase of 10.0 μg/m3 in long-term O3 exposure, yielding adjusted odds ratios (OR) of 1.084 (95% CI: 1.079-1.089) in the one-pollutant model and 1.073 (95% CI: 1.067-1.079) in the two-pollutant model. Notably, a significant additive interaction between O3 and PM2.5 on the prevalence of IR was observed (P for additive interaction < 0.001). Our main findings remained consistent and robust in the sensitivity analyses. Our study suggests long-term exposure to O3 was independently and positively associated with prevalence of IR. It emphasized the benefits of policy interventions to reduce O3 and PM2.5 exposure jointly, which could ultimately alleviate the health and economic burden related to DM.

Interaction between Extreme Temperature Events and Fine Particulate Matter on Cardiometabolic Multimorbidity: Evidence from Four National Cohort Studies

Accumulating evidence linked extreme temperature events (ETEs) and fine particulate matter (PM2.5) to cardiometabolic multimorbidity (CMM); however, it remained unknown if and how ETEs and PM2.5 interact to trigger CMM occurrence. Merging four Chinese national cohorts with 64,140 free-CMM adults, we provided strong evidence among ETEs, PM2.5 exposure, and CMM occurrence. Performing Cox hazards regression models along with additive interaction analyses, we found that the hazards ratio (HRs) of CMM occurrence associated with heatwave and cold spell were 1.006-1.019 and 1.063-1.091, respectively. Each 10 μg/m3 increment of PM2.5 concentration was associated with 17.9% (95% confidence interval: 13.9-22.0%) increased risk of CMM. Similar adverse effects were also found among PM2.5 constituents of nitrate, organic matter, sulfate, ammonium, and black carbon. We observed a synergetic interaction of heatwave and PM2.5 pollution on CMM occurrence with relative excess risk due to the interaction of 0.999 (0.663-1.334). Our study provides novel evidence that both ETEs and PM2.5 exposure were positively associated with CMM occurrence, and the heatwave interacts synergistically with PM2.5 to trigger CMM.

Short-Term Exposure to Fine Particulate Matter and Ozone: Source Impacts and Attributable Mortalities

Short-term exposure to particles with aerodynamic diameters less than 2.5 μm (PM2.5) and ozone (O3) are important risk factors for human health. Despite the awareness of reducing attributable health burden, region-specific and source-specific strategies remain less explored due to the gap between precursor emissions and health effects. In this study, we isolate the health burden of individual sector sources of PM2.5 and O3 precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), across the globe. Specifically, we estimate mortalities attributable to short-term exposure using machine-learning-based daily exposure estimates and quantify sectoral impacts using chemical transport model simulations. Globally, short-term exposure to PM2.5 and O3 result in 713.5 (95% Confidence Interval: 598.8-843.3) thousand and 496.3 (371.3-646.1) thousand mortalities in 2019, respectively, of which 12.5% are contributed by fuel-related NOx emissions from transportation, energy, and industry. Sectoral impacts from anthropogenic NOx and VOC emissions on health burden vary significantly among seasons and regions, requiring a target shift from transportation in winter to industry in summer for East Asia, for instance. Emission control and health management are additionally complicated by unregulated natural influences during climatic events. Fire-sourced NOx and VOC emissions, respectively, contribute to 8.5 (95% CI: 6.2-11.7) thousand and 4.8 (3.6-5.9) thousand PM2.5 and O3 mortalities, particularly for tropics with high vulnerability to climate change. Additionally, biogenic VOC emissions during heatwaves contribute to 1.8 (95% CI: 1.5-2.2) thousand O3-introduced mortalities, posing challenges in urban planning for high-income regions, where biogenic contributions to health burden during heatwaves are 13% of anthropogenic contributions annually. Our study provides important implications for temporally dynamic and sector-targeted emission control and health management strategies, which are of urgency under the projection of continuously increasing energy consumption and changing climate.

Effects of socioeconomic status and regional inequality on the association between PM2.5 and its components and cardiometabolic multimorbidity: A multicenter population-based survey in eastern China

BACKGROUND

Despite evidence linking fine particulate matter (PM2.5) to cardiometabolic multimorbidity (CMM), the impact of its components remains unclear. Socioeconomic status (SES) and regional disparities may confound their association. We aim to evaluate the associations between PM2.5 components and CMM and explore how socioeconomic status and regional disparities affect these relationships.

METHODS

We recruited 108,941 participants aged 35-76 years from ten cities in eastern China. Individual exposure was assessed using Tracking Air Pollution in China (TAP) data, including PM2.5 and five components: ammonium (NH4+), black carbon (BC), nitrates (NO3-), organic matter (OM), and sulfates (SO42-). Generalized linear models and quantile g-computation models were employed to quantify the effects of PM2.5 components on CMM and to identify key components. Stratified analyses were performed to investigate the modifying effect of SES and regional disparities.

RESULTS

For each increase in interquartile range (IQR), BC (odds ratio [OR] 1.37, 95 % CI 1.29-1.47), OM (1.38, 1.29-1.48), NH4+ (1.31, 1.21-1.40), NO3- (1.34, 1.25-1.44), and SO42- (1.28, 1.20-1.38) were positively associated with CMM. Joint exposure to five components was significantly positively associated with CMM (OR: 1.27, 95 % CI: 1.21-1.33), with SO42- having the highest estimated weight, followed by NO3- and BC. These associations were stronger for participants from low socio-economic status and poor regions.

CONCLUSION

In summary, we found a stronger hazard effect of PM2.5 and its components on CMM, compared to those suffering from CMDs, particularly among participants with low socioeconomic status and in poor regions. SO42- may be a primary contributor to the association between PM2.5 components and CMM. These findings underscore the importance of prioritizing CMM and targeting SO42-related pollution sources in health policies, particularly amid China's aging population, reducing environmental health inequalities is critical.

Association between PM2.5 constituents and cardiometabolic risk factors: Exploring individual and combined effects, and mediating inflammation

BACKGROUND

The individual and combined effects of PM2.5 constituents on cardiometabolic risk factors are sparsely investigated. Besides, the key cardiometabolic risk factor that PM2.5 constituents targeted and the biological mechanisms remain unclear.

METHOD

A multistage, stratified cluster sampling survey was conducted in two typically air-polluted Chinese cities. The PM2.5 and its constituents including sulfate, nitrate, ammonium, organic matter, and black carbon were predicted using a machine learning model. Twenty biomarkers in three category were simultaneously adopted as cardiometabolic risk factors. We explored the individual and mixture association of long-term PM2.5 constituents with these markers using generalized additive model and quantile-based g-computation, respectively. To minimize potential confounding effects, we accounted for covariates including demographic, lifestyle, meteorological, temporal trends, and disease-related information. We further used ROC curve and mediation analysis to identify the key subclinical indicators and explore whether inflammatory mediators mediate such association, respectively.

RESULT

PM2.5 constituents was positively correlated with HOMA-B, TC, TG, LDL-C and LCI, and negatively correlated with PP and RC. Further, PM2.5 constituent mixture was positive associated with DBP, MAP, HbA1c, HOMA-B, AC, CRI-1 and CRI-2, and negative associated with PP and HDL-C. The ROC analysis further reveals that multiple cardiometabolic risk factors can collectively discriminate exposure to PM2.5 constituents (AUC>0.9), among which PP and CRI-2 as individual indicators exhibit better identifiable performance for nitrate and ammonium (AUC>0.75). We also found that multiple blood lipid indicators may be affected by PM2.5 and its constituents, possibly mediated through complement C3 or hsCRP.

CONCLUSION

Our study suggested associations of individual and combined PM2.5 constituents exposure with cardiometabolic risk factors. PP and CRI-2 were the targeted markers of long-term exposure to nitrate and ammonium. Inflammation may serve as a mediating factor between PM2.5 constituents and dyslipidemia, which enhance current understanding of potential pathways for PM2.5-induced preclinical cardiovascular responses.

High-Resolution Spatiotemporal Modeling for PM2.5 Major Components in the Pearl River Delta and Its Implications for Epidemiological Studies

Distinguishing the effects of different fine particulate matter components (PMCs) is crucial for mitigating their effects on human health. However, the sparse distribution of locations where PM is collected for component analysis makes it challenging to investigate the relevant health effects. This study aimed to investigate the agreement between data-fusion-enhanced exposure assessment and site monitoring data in estimating the effects of PMCs on gestational diabetes mellitus (GDM). We first improved the spatial resolution and accuracy of exposure assessment for five major PMCs (EC, OM, NO3-, NH4+, and SO42-) in the Pearl River Delta region by a data fusion model that combined inputs from multiple sources using a random forest model (10-fold cross-validation R2: 0.52 to 0.61; root mean square error: 0.55 to 2.26 μg/m3). Next, we compared the associations between exposures to PMCs during pregnancy and GDM in a hospital-based cohort of 1148 pregnant women in Heshan, China, using both site monitoring data and data-fusion model estimates. The comparative analysis showed that the data-fusion-based exposure generated stronger estimates of identifying statistical disparities. This study suggests that data-fusion-enhanced estimates can improve exposure assessment and potentially mitigate the misclassification of population exposure arising from the utilization of site monitoring data.

Unequal Health Risks and Attributable Mortality Burden of Source-Specific PM2.5 in China

Anthropogenic emissions, originating from human activities, stand as the primary contributors to PM2.5, which is recognized as a global health threat. The disease burden associated with PM2.5 has been extensively documented. However, the prevailing estimations have predominantly relied on PM2.5 exposure-response functions, neglecting the distinct risks posed by PM2.5 from various sources. China has experienced a significant reduction in the PM2.5 concentration due to stringent emission controls. With diverse sources and abundant mortality data, this situation provides a unique opportunity to estimate short-term source-specific attributable mortality. Our approach involves an integrated unequal health risk-oriented modeling in China, incorporating a source-oriented Community Multiscale Air Quality model, an adjustment and downscaling method for exposure measurement, a generalized linear model with random-effects meta-analysis, and premature mortality estimation. Adhering to the unequal health risk concept, we calculated the attributable mortality of multiple PM2.5 sources by determining the source risk-adjusted factor. In this study, we observed varying excess risks associated with multiple PM2.5 sources, with transportation-related PM2.5 exhibiting the most substantial association. An interquartile range increase (7.65 μg/m3) was linked to a 1.98% higher daily nonaccidental mortality. Residential use- and transportation-related PM2.5 emerged as the two principal sources of premature mortality. In 2018, a remarkable 53,381 avoiding deaths were estimated compared to 2013, and over 67% of these were attributed to reductions in coal-dependent sources. Notably, transportation-related PM2.5 emerged as the largest contributor to premature mortality in 2018. This study underscores the significance of a new source-oriented health risk assessment to support actions aimed at reducing air pollution. It strongly advocates for heightened attention to PM2.5 reductions in the transportation sector in China.

Combined short-term and long-term emission controls improve air quality sustainably in China

The effectiveness of national policies for air pollution control has been demonstrated, but the relative effectiveness of short-term emission reduction measures in comparison with national policies has not. Here we show that short-term abatement measures during important international events substantially reduced PM2.5 concentrations, but air quality rebounded to pre-event levels after the measures ceased. Long-term adherence to strict emission reduction policies led to successful decreases of 54% in PM2.5 concentrations in Beijing, and 23% in atmospheric nitrogen deposition in China from 2012 to 2020. Incentivized by "blue skies" type campaigns, economic development and reactive nitrogen pollution are quickly decoupled, showing that a combination of inspiring but aggressive short-term measures and effective but durable long-term policies delivers sustainable air quality improvement. However, increased ammonia concentrations, transboundary pollutant flows, and the complexity to achieving reduction targets under climate change scenarios, underscore the need for the synergistic control of multiple pollutants and inter-regional action.

Association between long-term exposure to fine particulate matter and its chemical constituents and premature death in individuals living with HIV/AIDS

Long-term exposure to fine particulate matter (PM2.5) is associated with an increased total mortality. However, the association of PM2.5 with mortality in people living with human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS, PLWHA) and the relationship between its constituents and adverse outcomes remain unknown. In this cohort study, 28,140 PLWHA were recruited from the HIV/AIDS Comprehensive Response Information Management System of the Hubei Provincial Centre for Disease Control and Prevention in China between 2001 and 2020. The annual PM2.5 chemical composition data, including sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), black carbon (BC), and organic matter (OM), was extracted from the Tracking Air Pollution (TAP) dataset in China. A Cox proportional hazard model with time-varying exposure and time-to-event quantile-based generalized (g) computation was used to assess the associations between PM2.5 chemical constituents, and mortality in PLWHA. A multivariate Cox proportional hazard model estimated an excess hazard ratio (eHR) of 0.32% [95% confidence interval (CI): (0.01%, 0.64%)] for AIDS-related death (ARD), associated with 1 μg/m3 rise in PM2.5 exposure. An increase of 1 μg/m3 in NH4+ was associated with 5.13% [95% CI: (2.89%, 7.43%)] and 2.97% [95% CI: (1.52%, 4.44%)] increase in the risk of ARD and all-cause deaths (ACD), respectively. When estimated using survival-based quantile g-computation, the eHR for ARD with a joint change in a decile increase in all five components was 6.10% [95% CI: 3.77%, 8.48%)]. Long-term exposure to PM2.5 chemical composition, particularly NH4+ increased the risk of death in PLWHA. This study provides epidemiological evidence that SO42- and NH4+ increased the risk of ARD and that NH4+ increased the risk of ACD in PLWHA. Multi-constituent analyses further suggested that NH4+ may be a key component in increasing the risk of premature death in patients with HIV/AIDS. Individuals aged ≥65 with HIV/AIDS are more vulnerable to SO42-, and consequent ACD.

Characterizing the emission trends and pollution evolution patterns during the transition period following COVID-19 at an industrial megacity of central China

After the resumption of work and production following the COVID-19 pandemic, many cities entered a "transition phase", characterized by the gradual recovery of emission levels from various sources. Although the overall PM2.5 emission trends have recovered, the specific changes in different sources of PM2.5 remain unclear. Here, we investigated the changes in source contributions and the evolution pattern of pollution episodes (PE) in Wuhan during the "transition period" and compared them with the same period during the COVID-19 lockdown. We found that vehicle emissions, industrial processes, and road dust exhibited significant recoveries during the transition period, increasing by 5.4%, 4.8%, and 3.9%, respectively, during the PE. As primary emissions increased, secondary formation slightly declined, but it still played a predominant role (accounting for 39.1∼ 43.0% of secondary nitrate). The reduction in industrial activities was partially offset by residential burning. The evolution characteristics of PE exhibited significant differences between the two periods, with PM2.5 concentration persisting at a high level during the transition period. The differences in the evolution patterns of the two periods were also reflected in their change rates at each stage, which mostly depend on the pre-PE concentration level. The transition period shows a significantly higher value (8.4 μg m-3 h-1) compared with the lockdown period, almost double the amount. In addition to local emissions, regional transport should be a key consideration in pollution mitigation strategies, especially in areas adjacent to Wuhan. Our study quantifies the variations in sources between the two periods, providing valuable insights for optimizing environmental planning to achieve established goals.

Exploring the nexus of urban form, transport, environment and health in large-scale urban studies: A state-of-the-art scoping review

BACKGROUND

As the world becomes increasingly urbanised, there is recognition that public and planetary health relies upon a ubiquitous transition to sustainable cities. Disentanglement of the complex pathways of urban design, environmental exposures, and health, and the magnitude of these associations, remains a challenge. A state-of-the-art account of large-scale urban health studies is required to shape future research priorities and equity- and evidence-informed policies.

OBJECTIVES

The purpose of this review was to synthesise evidence from large-scale urban studies focused on the interaction between urban form, transport, environmental exposures, and health. This review sought to determine common methodologies applied, limitations, and future opportunities for improved research practice.

METHODS

Based on a literature search, 2958 articles were reviewed that covered three themes of: urban form; urban environmental health; and urban indicators. Studies were prioritised for inclusion that analysed at least 90 cities to ensure broad geographic representation and generalisability. Of the initially identified studies, following expert consultation and exclusion criteria, 66 were included.

RESULTS

The complexity of the urban ecosystem on health was evidenced from the context dependent effects of urban form variables on environmental exposures and health. Compact city designs were generally advantageous for reducing harmful environmental exposure and promoting health, with some exceptions. Methodological heterogeneity was indicative of key urban research challenges; notable limitations included exposure and health data at varied spatial scales and resolutions, limited availability of local-level sociodemographic data, and the lack of consensus on robust methodologies that encompass best research practice.

CONCLUSION

Future urban environmental health research for evidence-informed urban planning and policies requires a multi-faceted approach. Advances in geospatial and AI-driven techniques and urban indicators offer promising developments; however, there remains a wider call for increased data availability at local-levels, transparent and robust methodologies of large-scale urban studies, and greater exploration of urban health vulnerabilities and inequities.

Long-term exposure to PM2.5 chemical constituents and diabesity: evidence from a multi-center cohort study in China

Background

Long-term exposure to PM2.5 is known to increase the risks for diabetes and obesity, but its effects on their coexistence, termed diabesity, remain uncertain. This study aimed to investigate the associations of long-term exposure to PM2.5 and its chemical constituents with the risks for diabesity, diabetes, and obesity.

Methods

This cross-sectional study used the baseline data of a multi-center cohort, consisting of three provincially representative cohorts comprising a total of 134,403 participants from the eastern (Fujian Province), central (Hubei Province), and western (Yunnan Province) regions of China. Obesity and diabetes, and diabesity were identified by a body mass index (BMI) ≥28 kg/m2 and fasting plasma glucose (FPG) ≥126 mg/dL. The average concentrations of PM2.5 and five chemical constituents (NO3 -, SO4 2-, NH4 +, organic matter, and black carbon) over participants' residence during the past three years were estimated using machine learning models. Logistic regression models with double robust estimators, Bayesian kernel machine regression, and weighted quantile sum regression were employed to estimate independent and joint effects of PM2.5 chemical constituents on the risks for diabesity, diabetes, and obesity, as well as the differences from the effects on obesity. Stratified analyses were performed to examine effect modification of sociodemographic and lifestyle factors.

Findings

There were 129,244 participants with a mean age of 54.1 ± 13.8 years included in the study. Each interquartile range increase in PM2.5 concentration (8.53 μg/m3) was associated with an increased risk for diabesity (OR = 1.23 [1.17, 1.30]), diabetes only (OR = 1.16 [1.13, 1.19]), and obesity only (OR = 1.03 [1.00, 1.05]). Long-term exposure to each PM2.5 chemical constituent was associated with an increased risk for diabesity, where organic matter exposure, with maximum weight (48%), was associated with a higher risk for diabesity (OR = 1.21 [1.16, 1.27]). Among those with obesity, black carbon contributed most (68%) to the joint effect of PM2.5 chemical constituents on diabesity (OR = 1.16 [1.11, 1.22]). Physical activity reduced adverse effects of PM2.5 on diabesity. Also, additive rather than multiplicative effects of obesity on the PM2.5-diabetes association were observed.

Interpretation

Long-term exposure to PM2.5 and its chemical constituents was associated with an increased risk for diabesity, stronger than associations for diabetes and obesity alone. The main constituents associated with diabesity and obesity were black carbon and organic matter.

Funding

National Natural Science Foundation of China (42271433, 723B2017), National Key R&D Program of China (2023YFC3604702), Fundamental Research Funds for the Central Universities (2042023kfyq04, 2042024kf1024), the Science and Technology Major Project of Tibetan Autonomous Region of China (XZ202201ZD0001G), Science and technology project of Tibet Autonomous Region（XZ202303ZY0007G), Key R&D Project of Sichuan Province (2023YFS0251), Renmin Hospital of Wuhan University (JCRCYG-2022-003), Jiangxi Provincial 03 Special Foundation and 5G Program (20224ABC03A05), Wuhan University Specific Fund for Major School-level Internationalization Initiatives (WHU-GJZDZX-PT07).

A new ChatGPT-empowered, easy-to-use machine learning paradigm for environmental science

The quantity and complexity of environmental data show exponential growth in recent years. High-quality big data analysis is critical for performing a sophisticated characterization of the complex network of environmental pollution. Machine learning (ML) has been employed as a powerful tool for decoupling the complexities of environmental big data based on its remarkable fitting ability. Yet, due to the knowledge gap across different subjects, ML concepts and algorithms have not been well-popularized among researchers in environmental sustainability. In this context, we introduce a new research paradigm-"ChatGPT + ML + Environment", providing an unprecedented chance for environmental researchers to reduce the difficulty of using ML models. For instance, each step involved in applying ML models to environmental sustainability, including data preparation, model selection and construction, model training and evaluation, and hyper-parameter optimization, can be easily performed with guidance from ChatGPT. We also discuss the challenges and limitations of using this research paradigm in the field of environmental sustainability. Furthermore, we highlight the importance of "secondary training" for future application of "ChatGPT + ML + Environment".

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.

Changes in PM2.5-related diabetes risk under the implementation of the clean air act in Shanghai

OBJECTIVES

We examined the associations between PM2.5 exposure and Type 2 diabetes mellitus risk under the implementation of the Clean Air Act (CAA) among high-risk population for diabetes in Shanghai.

METHODS

A total of 10,499 subjects from the Shanghai High-Risk Diabetic Screen (SHiDS) project between 2002 and 2018, linked with remotely sensed PM2.5 concentrations, were enrolled in this study. Ordinary least squares and logistic regression were applied to explore associations between PM2.5 and diabetes risk in various exposure periods.

RESULTS

In year 2002-2013 (before CAA), the diabetes risk increased 7.5 % (95 % CI: 1.018-1.137), 8.0 % (95 % CI: 1.022-1.142) and 7.9 % (95 % CI: 1.021-1.141) under each 10 μg/m3 increase of long-term (1, 2 and 3 years) PM2.5 exposure, respectively. Elevated PM2.5 exposure were also associated with a significant increase in glycemic parameters before CAA implementation. However, in the year 2014-2018 (after CAA), the associations between PM2.5 exposure and diabetes risk were not significant after controlling for potential confounders.

CONCLUSION

Our findings suggest that long-term and high-level exposure to PM2.5 was associated with increased prevalence of diabetes. Moreover, the implementation of CAA might ameliorate PM2.5-related diabetes risk.

Does the morphology of residential greenspaces contribute to the development of a cardiovascular-healthy city?

BACKGROUNDS

Greenspaces are indispensable for the construction of a healthy city. Research has shown that greenspaces contribute to the reduction of cardiovascular risks. However, the role of greenspace morphology in the development of a healthy city is not well understood.

METHODS

Our study utilized data from a cardiovascular disease screening cohort comprising 106,238 residents in Anhui Province, China, aged between 35 and 75 years. We calculated landscape indices of each participant using high-resolution land cover data to measure the greenness, fragmentation, connectivity, aggregation, and shape of greenspaces. We used a multivariate linear regression model to assess the associations between these landscape indices and triglyceride risk, and employed a structural equation model to explore the potential contributions of heatwaves and fine particulate matter (PM2.5) to this association.

RESULTS

Overall, triglyceride was expected to increase by 0.046% (95% CI: 0.040%, 0.052%) with a 1% increase in the percentage of built-up area. Conversely, an increase in the percentage of greenspace was associated with a 0.270% (95% CI: 0.337%, -0.202%) decrease in triglyceride levels. Furthermore, when the total greenspace was held constant, the shape, connectedness, and aggregation of greenspace were inversely correlated with triglyceride levels, with effects of -0.605% (95% CI: 1.012%, -0.198%), -0.031% (95% CI: 0.039%, -0.022%), and -0.049% (95% CI: 0.058%, -0.039%), respectively. Likewise, the protective effect of the area-weighed mean shape index was higher than that of the total amount of greenspace. The stratification results showed that urban residents benefited more from greenspace exposure. Greenspace morphology can minimize triglyceride risk by reducing pollutant and heatwaves, with aggregation having the greatest effect on reducing pollutants whereas fragmentation is more efficient at reducing heatwaves.

CONCLUSION

Exposure to the greenspaces morphology is associated with a reduction in triglyceride risk. The study has important practical and policy implications for early health monitoring and the spatial layout of greenspace and will provide scientific information for healthy urban planning by reducing unfavorable health consequences.

Gestational and Postpartum Exposure to PM2.5 Components and Glucose Metabolism in Chinese Women: A Prospective Cohort Study

Pregnant women are physiologically prone to glucose intolerance, while the puerperium represents a critical phase for recovery. However, how air pollution disrupts glucose homeostasis during the gestational and early postpartum periods remains unclear. This prospective cohort study conducted an oral glucose tolerance test and measured the insulin levels of 834 pregnant women in Guangzhou, with a follow-up for 443 puerperae at 6-8 weeks postpartum. Residential PM2.5 and five chemical components were estimated by an established spatiotemporal model. The adjusted linear model showed that an IQR increase in gestational PM2.5 exposure was associated with an increase of 0.17 mmol/L (95% CI: 0.06, 0.28) in fasting plasma glucose (FPG) and 0.24 (95% CI: 0.05, 0.42) in the insulin resistance index. Postpartum PM2.5 exposure was linked to a 0.17 mmol/L (95% CI: 0.05, 0.28) elevation in FPG per IQR, with a strengthened association found in women with gestational diabetes (Pinteraction = 0.003). In the quantile-based g-computation model, NO3- consistently contributed to the combined effect of PM2.5 components on gestational and postpartum FPG. This study was the first to suggest that PM2.5 components were associated with exacerbated gestational insulin resistance and elevated postpartum FPG. Targeted interventions reducing the emissions of toxic PM2.5 components are essential to improving maternal glucose metabolism.

Association between fine particulate matter and fecundability in Henan, China: A prospective cohort study

OBJECTIVE

To investigate the relationship between ambient fine particulate matter (PM2.5) exposure and fecundability.

METHODS

This study included 751,270 female residents from Henan Province who participated in the National Free Pre-conception Check-up Projects during 2015-2017. Ambient cycle-specific PM2.5 exposure was assessed at the county level for each participant using satellite-based PM2.5 concentration data at 1-km resolution. Cox proportional hazards models with time-varying exposure were used to estimate the association between fecundability and PM2.5 exposure, adjusted for potential individual risk factors.

RESULTS

During the study period, 568,713 participants were pregnant, monthly mean PM2.5 concentrations varied from 25.5 to 114.0 µg/m3 across study areas. For each 10 µg/m3 increase in cycle-specific PM2.5, the hazard ratio for fecundability was 0.951 (95 % confidence interval: 0.950-0.953). The association was more pronounced in women who were older, with urban household registration, history of pregnancy, higher body mass index (BMI), hypertension, without exposure to tobacco, or whose male partners were older, with higher BMI, or hypertension.

CONCLUSION

In this population-based prospective cohort, ambient cycle-specific PM2.5 exposure was associated with reduced fecundability. These findings may support the adverse implications of severe air pollution on reproductive health.

Predicting particulate matter, nitrogen dioxide, and ozone across Great Britain with high spatiotemporal resolution based on random forest models

In Great Britain, limited studies have employed machine learning methods to predict air pollution especially ozone (O3) with high spatiotemporal resolution. This study aimed to address this gap by developing random forest models for four key pollutants (fine and inhalable particulate matter [PM2.5 and PM10], nitrogen dioxide [NO2] and O3) by integrating multiple-source predictors at a daily level and 1-km resolution. The out-of-bag R2 (root mean squared error, RMSE) between predictions from models and measurements from monitoring stations in 2006-2013 was 0.85 (3.63 μg/m3) for PM2.5, 0.77 (6.00 μg/m3) for PM10, 0.85 (9.71 μg/m3) for NO2, and 0.85 (9.39 μg/m3) for maximum daily 8-h average (MDA8) O3 at daily level, and the predicting accuracy was higher at monthly and annual level. The high-resolution predictions captured characterized spatiotemporal patterns of the four pollutants. Higher concentrations of PM2.5, PM10, and NO2 were distributed in densely populated southern regions of Great Britain while O3 showed an inverse spatial pattern in general, which could not be fully depicted by monitoring stations. Therefore, predictions produced in this study could improve exposure assessment with less exposure misclassification and flexible exposure windows for future epidemiological studies to investigate the impact of air pollution across Great Britain.

Long-term exposure to major constituents of fine particulate matter and neurodegenerative diseases: A population-based survey in the Pearl River Delta Region, China

BACKGROUND

Exposure to PM2.5 has been linked to neurodegenerative diseases, with limited understanding of constituent-specific contributions.

OBJECTIVES

To explore the associations between long-term exposure to PM2.5 constituents and neurodegenerative diseases.

METHODS

We recruited 148,274 individuals aged ≥ 60 from four cities in the Pearl River Delta region, China (2020 to 2021). We calculated twenty-year average air pollutant concentrations (PM2.5 mass, black carbon (BC), organic matter (OM), ammonium (NH4+), nitrate (NO3-) and sulfate (SO42-)) at the individuals' home addresses. Neurodegenerative diseases were determined by self-reported doctor-diagnosed Alzheimer's disease (AD) and Parkinson's disease (PD). Generalized linear mixed models were employed to explore associations between pollutants and neurodegenerative disease prevalence.

RESULTS

PM2.5 and all five constituents were significantly associated with a higher prevalence of AD and PD. The observed associations generally exhibited a non-linear pattern. For example, compared with the lowest quartile, higher quartiles of BC were associated with greater odds for AD prevalence (i.e., the adjusted odds ratios were 1.81; 95% CI, 1.45-2.27; 1.78; 95% CI, 1.37-2.32; and 1.99; 95% CI, 1.54-2.57 for the second, third, and fourth quartiles, respectively).

CONCLUSIONS

Long-term exposure to PM2.5 and its constituents, particularly combustion-related BC, OM, and SO42-, was significantly associated with higher prevalence of AD and PD in Chinese individuals.

ENVIRONMENTAL IMPLICATION

PM2.5 is a routinely regulated mixture of multiple hazardous constituents that can lead to diverse adverse health outcomes. However, current evidence on the specific contributions of PM2.5 constituents to health effects is scarce. This study firstly investigated the association between PM2.5 constituents and neurodegenerative diseases in the moderately to highly polluted Pearl River Delta region in China, and identified hazardous constituents within PM2.5 that have significant impacts. This study provides important implications for the development of targeted PM2.5 prevention and control policies to reduce specific hazardous PM2.5 constituents.

The association between humidex and tuberculosis: a two-stage modelling nationwide study in China

BACKGROUND

Under a changing climate, the joint effects of temperature and relative humidity on tuberculosis (TB) are poorly understood. To address this research gap, we conducted a time-series study to explore the joint effects of temperature and relative humidity on TB incidence in China, considering potential modifiers.

METHODS

Weekly data on TB cases and meteorological factors in 22 cities across mainland China between 2011 and 2020 were collected. The proxy indicator for the combined exposure levels of temperature and relative humidity, Humidex, was calculated. First, a quasi-Poisson regression with the distributed lag non-linear model (DLNM) was constructed to examine the city-specific associations between humidex and TB incidence. Second, a multivariate meta-regression model was used to pool the city-specific effect estimates, and to explore the potential effect modifiers.

RESULTS

A total of 849,676 TB cases occurred in the 22 cities between 2011 and 2020. Overall, a conspicuous J-shaped relationship between humidex and TB incidence was discerned. Specifically, a decrease in humidex was positively correlated with an increased risk of TB incidence, with a maximum relative risk (RR) of 1.40 (95% CI: 1.11-1.76). The elevated RR of TB incidence associated with low humidex (5th humidex) appeared on week 3 and could persist until week 13, with a peak at approximately week 5 (RR: 1.03, 95% CI: 1.01-1.05). The effects of low humidex on TB incidence vary by Natural Growth Rate (NGR) levels.

CONCLUSION

A J-shaped exposure-response association existed between humidex and TB incidence in China. Humidex may act as a better predictor to forecast TB incidence compared to temperature and relative humidity alone, especially in regions with higher NGRs.

Relationship of long-term exposure to air pollutant mixture with metabolic-associated fatty liver disease and subtypes: A retrospective cohort study of the employed population of Southwest China

BACKGROUND

While evidence suggests that PM2.5 is associated with overall prevalence of Metabolic (dysfunction)-Associated Fatty Liver Disease (MAFLD), effects of comprehensive air pollutant mixture on MAFLD and its subtypes remain unclear.

OBJECTIVE

To investigate individual and joint effects of long-term exposure to comprehensive air pollutant mixture on MAFLD and its subtypes.

METHODS

Data of 27,699 participants of the Chinese Cohort of Working Adults were analyzed. MAFLD and subtypes, including overweight/obesity, lean, and diabetes MAFLD, were diagnosed according to clinical guidelines. Concentrations of NO3-, SO42-, NH4+, organic matter (OM), black carbon (BC), PM2.5, SO2, NO2, O3 and CO were estimated as a weighted average over participants' residential and work addresses for the three years preceding outcome assessment. Logistic regression and weighted quantile sum regression were used to estimate individual and joint effects of air pollutant mixture on presence of MAFLD.

RESULTS

Overall prevalence of MAFLD was 26.6 % with overweight/obesity, lean, and diabetes MAFLD accounting for 92.0 %, 6.4 %, and 1.6 %, respectively. Exposure to SO42-, NO3-, NH4+, BC, PM2.5, NO2, O3and CO was significantly associated with overall MAFLD, overweight/obesity MAFLD, or lean MAFLD in single pollutant models. Joint effects of air pollutant mixture were observed for overall MAFLD (OR = 1.10 [95 % CI: 1.03, 1.17]), overweight/obesity (1.09 [1.02, 1.15]), and lean MAFLD (1.63 [1.28, 2.07]). Contributions of individual air pollutants to joint effects were dominated by CO in overall and overweight/obesity MAFLD (Weights were 42.31 % and 45.87 %, respectively), while SO42- (36.34 %), SO2 (21.00 %) and BC (12.38 %) were more important in lean MAFLD. Being male, aged above 45 years and smoking increased joint effects of air pollutant mixture on overall MAFLD.

CONCLUSIONS

Air pollutant mixture was associated with MAFLD, particularly the lean MAFLD subtype. CO played a pivotal role in both overall and overweight/obesity MAFLD, whereas SO42- were associated with lean MAFLD.

Association between ambient temperature and risk of notifiable infectious diseases in China from 2011 to 2019

Previous studies on temperature and infectious diseases primarily focused on individual disease types, yielding inconsistent conclusions. This study collected monthly data on notifiable infectious disease cases and meteorological variables across 7 provinces in China from 2011 to 2019. A distributed lag nonlinear model was used to evaluate the association between ambient temperature and infectious diseases within each province, and random meta-analysis was applied to evaluate the pooled effect. Extreme hot temperature (the 97.5th percentile) was positively associated with the risk of respiratory infectious diseases with the relative risk (RR) of 1.45 (95%CI: 1.01-2.08). Conversely, extreme cold temperature (the 2.5th percentile) was negatively associated with intestinal infectious diseases and zoonotic diseases and vector-borne diseases, reporting RRs of 0.43 (95%CI: 0.30-0.60) and 0.46 (95%CI: 0.38-0.57), respectively. This study described the nonlinear association between ambient temperature and infectious diseases with different transmission routes, informing comprehensive prevention and control strategies for temperature-related infectious diseases.

Amelioration of metabolic disorders in H9C2 cardiomyocytes induced by PM2.5 treated with vitamin C

OBJECTIVE

Particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) is a public health risk. We investigate PM2.5 on metabolites in cardiomyocytes and the influence of vitamin C on PM2.5 toxicity.

MATERIALS AND METHODS

For 24 hours, H9C2 were exposed to various concentrations of PM2.5 (0, 100, 200, 400, 800 μg/ml), after which the levels of reactive oxygen species (ROS) and cell viability were measured using the cell counting kit-8 (CCK-8) and 2',7'-dichlorofluoresceindiacetate (DCFH2-DA), respectively. H9C2 were treated with PM2.5 (200 μg/ml) in the presence or absence of vitamin C (40 μmol/L). mRNA levels of interleukin 6(IL-6), caspase-3, fatty acid-binding protein 3 (FABP3), and hemeoxygenase-1 (HO-1) were investigated by quantitative reverse-transcription polymerase chain reaction. Non-targeted metabolomics by LC-MS/MS was applied to evaluate the metabolic profile in the cell.

RESULTS

Results revealed a concentration-dependent reduction in cell viability, death, ROS, and increased expression of caspase-3, FABP3, and IL-6. In total, 15 metabolites exhibited significant differential expression (FC > 2, p < 0.05) between the control and PM2.5 group. In the PM2.5 group, lysophosphatidylcholines (LysoPC,3/3) were upregulated, whereas amino acids (5/5), amino acid analogues (3/3), and other acids and derivatives (4/4) were downregulated. PM2.5 toxicity was lessened by vitamin C. It reduced PM2.5-induced elevation of LysoPC (16:0), LysoPC (16:1), and LysoPC (18:1).

DISCUSSION AND CONCLUSIONS

PM2.5 induces metabolic disorders in H9C2 cardiomyocytes that can be ameliorated by treatment with vitamin C.

Relationships between long-term exposure to major PM2.5 constituents and outpatient visits and hospitalizations in Guangdong, China

Ambient fine particulate matter (PM2.5) has attracted considerable attention due to its crucial role in the rising global disease burden. Evidence of health risks associated with exposure to PM2.5 and its major constituents is important for advancing hazard assessments and air pollution emission policies. We investigated the relationship between exposure to major constituents of PM2.5 and outpatient visits as well as hospitalizations in Guangdong Province, China, where 127 million residents live in a severe PM2.5 pollution environment. An approach that integrates the generalized weighted quantile sum (gWQS) regression with the difference-in-differences (DID) approach was used to assess the overall mixture effects and relative contributions of each constituent. We observed significant associations between long-term exposure to the mixture of PM2.5 constituents (WQS index) and outpatient visits (IR%, percentage increases in risk per unit WQS index increase:1.73, 95%CI: 1.72, 1.74) as well as hospitalizations (IR%:5.15, 95%CI: 5.11, 5.20). Black carbon (weight: 0.34) and nitrate (weight: 0.60) respectively exhibited the highest contributions to outpatient visits and hospitalizations. The overall mixture effects on outpatient visits and hospitalizations were higher with increased summer air temperatures (IR%: 7.54, 95%CI: 7.33, 7.74 and IR%: 9.55, 95%CI: 8.36, 10.75, respectively) or decreased winter air temperatures (IR%: 1.88, 95%CI: 1.68, 2.08 and IR%: 4.87, 95%CI: 3.73, 6.02, respectively). Furthermore, the overall mixture effects on outpatient visits and hospitalizations were significantly higher in populations with higher socioeconomic status (P < 0.01). It's crucial to address the primary sources of nitrate precursor substances and black carbon (mainly traffic-related and industrial-related air pollutants) and consider the complex interaction effects between air temperature and PM2.5 in the context of climate change. Of particular concern is the need to prioritize healthcare demands in economically disadvantaged regions and to address the health inequalities stemming from the uneven distribution of healthcare resources and PM2.5 pollution.

Sex differences and dietary patterns in the association of air pollutants and hypertension

BACKGROUND

Hypertension is one of the major public health problems in China. Limited evidence exists regarding sex differences in the association between hypertension and air pollutants, as well as the impact of dietary factors on the relationship between air pollutants and hypertension. The aim of this study was to investigate the sex-specific effects of dietary patterns on the association between fine particulate matter (PM2.5), ozone(O3) and hypertension in adults residing in Jiangsu Province of China.

METHODS

A total of 3189 adults from the 2015 China Adult Chronic Disease and Nutrition Surveillance in Jiangsu Province were included in this study. PM2.5 and O3 concentrations were estimated using satellite space-time models and assigned to each participant. Dietary patterns were determined by reduced rank regression (RRR), and multivariate logistic regression was used to assess the associations of the obtained dietary patterns with air pollutants and hypertension risk.

RESULTS

After adjusting for confounding variables, we found that males were more sensitive to long-term exposure to PM2.5 (Odds ratio (OR) = 1.42 95%CI:1.08,1.87), and females were more sensitive to long-term exposure to O3 (OR = 1.61 95%CI:1.15,2.23). Traditional southern pattern identified through RRR exhibited a protective effect against hypertension in males (OR = 0.73 95%CI: 0.56,1.00). The results of the interaction between dietary pattern score and PM2.5 revealed that adherence to traditional southern pattern was significantly associated with a decreased risk of hypertension in males (P < 0.05), while no significant association was observed among females.

CONCLUSIONS

Our findings suggested that sex differences existed in the association between dietary patterns, air pollutants and hypertension. Furthermore, we found that adherence to traditional southern pattern may mitigate the risk of long-term PM2.5 exposure-induced hypertension in males.

Long-term exposure to fine particulate matter constituents and cognitive impairment among older adults: An 18-year Chinese nationwide cohort study

BACKGROUND

Although growing evidence has shown independent links of long-term exposure to fine particulate matter (PM2.5) with cognitive impairment, the effects of its constituents remain unclear. This study aims to explore the associations of long-term exposure to ambient PM2.5 constituents' mixture with cognitive impairment in Chinese older adults, and to further identify the main contributor.

METHODS

15,274 adults ≥ 65 years old were recruited by the Chinese Longitudinal Healthy Longevity Study (CLHLS) and followed up through 7 waves during 2000-2018. Concentrations of ambient PM2.5 and its constituents (i.e., black carbon [BC], organic matter [OM], ammonium [NH4+], sulfate [SO42-], and nitrate [NO3-]) were estimated by satellite retrievals and machine learning models. Quantile-based g-computation model was employed to assess the joint effects of a mixture of 5 PM2.5 constituents and their relative contributions to cognitive impairment. Analyses stratified by age group, sex, residence (urban vs. rural), and region (north vs. south) were performed to identify vulnerable populations.

RESULTS

During the average 3.03 follow-up visits (89,296.9 person-years), 4294 (28.1%) participants had developed cognitive impairment. The adjusted hazard ratio [HR] (95% confidence interval [CI]) for cognitive impairment for every quartile increase in mixture exposure to 5 PM2.5 constituents was 1.08 (1.05-1.11). BC held the largest index weight (0.69) in the positive direction in the qg-computation model, followed by OM (0.31). Subgroup analyses suggested stronger associations in younger old adults and rural residents.

CONCLUSION

Long-term exposure to ambient PM2.5, particularly its constituents BC and OM, is associated with an elevated risk of cognitive impairment onset among Chinese older adults.

Unexpected PM2.5-related emissions and accompanying environmental-economic inequalities driven by "clean" tertiary industry in China

The tertiary industry, led by service sectors, usually have "clean" production processes and thus is ignored by current PM2.5 pollution mitigation strategies in China. Actually, the tertiary industry heavily relies on the supplies from its upstream industries, resulting in pollutant emissions and economic benefits transferring among different regions. With the application of the multiregional input-output (MRIO) model, our study explores the emission contribution from the tertiary industry's consumption activities in China and analyses the accompanying emission-economy relationship. We find that the production process of tertiary industry (with the sector Transportation excluded) contributes only ∼1 % of China's PM2.5-related emissions in 2017. However, its consumption-based emission contributions could increase to 11 %-17 %, among which >95 % are indirectly contributed. More than 40 % of tertiary industry consumption-based emissions, accompanied by 25 % of the consumption-based value added, are transferred via interprovincial trade. The proportion of transferred emissions even exceeds 50 % for the top 10 importers. The spatial pattern of value-added flows is nearly opposite to that of emission flows. Our results also reveal that among the 30 provinces and 870 interprovincial trading pairs, 6 provinces are experiencing environmental-economic win, 7 provinces are experiencing environmental-economic loss, and in detail 326 trading pairs are experiencing environmental-economic win or loss. To reduce the unexpected emissions and inequalities embodied in seemingly "clean" industries, consumption activities should be considered and strengthened in China's new-stage environmental policies.

The Associations of Prenatal Exposure to Fine Particulate Matter and Its Chemical Components with Allergic Rhinitis in Children and the Modification Effect of Polyunsaturated Fatty Acids: A Birth Cohort Study

BACKGROUND

Polyunsaturated fatty acids (PUFAs) have been shown to protect against fine particulate matter < 2.5 μ m in aerodynamic diameter (PM 2.5 )-induced hazards. However, limited evidence is available for respiratory health, particularly in pregnant women and their offspring.

OBJECTIVES

We aimed to investigate the association of prenatal exposure to PM 2.5 and its chemical components with allergic rhinitis (AR) in children and explore effect modification by maternal erythrocyte PUFAs.

METHODS

This prospective birth cohort study involved 657 mother-child pairs from Guangzhou, China. Prenatal exposure to residential PM 2.5 mass and its components [black carbon (BC), organic matter (OM), sulfate (SO 4 2 - ), nitrate (NO 3 - ), and ammonium (NH 4 + )] were estimated by an established spatiotemporal model. Maternal erythrocyte PUFAs during pregnancy were measured using gas chromatography. The diagnosis of AR and report of AR symptoms in children were assessed up to 2 years of age. We used Cox regression with the quantile-based g-computation approach to assess the individual and joint effects of PM 2.5 components and examine the modification effects of maternal PUFA levels.

RESULTS

Approximately 5.33 % and 8.07% of children had AR and related symptoms, respectively. The average concentration of prenatal PM 2.5 was 35.50 ± 5.31   μ g / m 3 . PM 2.5 was positively associated with the risk of developing AR [hazard ratio ( HR ) = 1.85 ; 95% confidence interval (CI): 1.16, 2.96 per 5   μ g / m 3 ] and its symptoms (HR = 1.79 ; 95% CI: 1.22, 2.62 per 5   μ g / m 3 ) after adjustment for confounders. Similar associations were observed between individual PM 2.5 components and AR outcomes. Each quintile change in a mixture of components was associated with an adjusted HR of 3.73 (95% CI: 1.80, 7.73) and 2.69 (95% CI: 1.55, 4.67) for AR and AR symptoms, with BC accounting for the largest contribution. Higher levels of n-3 docosapentaenoic acid and lower levels of n-6 linoleic acid showed alleviating effects on AR symptoms risk associated with exposure to PM 2.5 and its components.

CONCLUSION

Prenatal exposure to PM 2.5 and its chemical components, particularly BC, was associated with AR/symptoms in early childhood. We highlight that PUFA biomarkers could modify the adverse effects of PM 2.5 on respiratory allergy. https://doi.org/10.1289/EHP13524.

Green space and its types can attenuate the associations of PM2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China

BACKGROUND

The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces.

METHODS

A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations.

RESULTS

Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups.

CONCLUSION

Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.

Cohort profile: China undergraduate cohort for environmental health study

The China Undergraduate Cohort (CUC) is an ambispective cohort study with its major purpose to better understand the effects of lifetime environmental exposures on health outcomes. We recruited 5322 college students with an average age of 18.3 ± 0.7 years in China from August 23, 2019 to October 28, 2019. Follow-up surveys were conducted annually. The dataset comprises individual demographic data (e.g. age, sex, height, weight, birth date, race, home address, annual family income, contact information), health-related behavior data (smoking status, smoking cessation, passive smoking exposure, drinking habit, physical activity, dietary status), lifestyle data (physical exercise, dietary habit, length of time spent outdoors), disease history (respiratory disease history, cardiovascular disease history, urinary system disease history, etc.), mental health status data (sleep quality, self-reported stress, anxiety and depression symptoms), lung function and blood samples data. Preliminary results from our cohort have found the association between air pollution, summer heat and mercury exposure and lung function among young adults in China.

Policy implications for synergistic management of PM2.5 and O3 pollution from a pattern-process-sustainability perspective in China

In recent years, the pattern of air pollution in China has changed profoundly, and PM2.5 and surface ozone (O3) have become the main air pollutants affecting the air quality of cities and regions in China. The synergistic control of the two has become the key to the sustainable improvement of air quality in China. In this study, we investigated and analyzed the spatial and temporal distribution patterns, exposure health risks, key drivers, and sustainable characteristics of PM2.5 and O3 concentrations in China from 2013 to 2022 at the national and city cluster scales by combining methodological models such as spatial statistics, trend analysis, exposure-response function, Hurst index, and multi-scale geographically weighted regression (MGWR) model. Ultimately, a synergistic management system for PM2.5 and O3 pollution was proposed. The results showed that: (1) The PM2.5 concentration decreased at a rate of 1.45 μg/m3 per year (p < 0.05), while the O3 concentration increased at a rate of 2.54 μg/m3 per year (p < 0.05). The trends of the two concentrations showed significant differences in spatial distribution. (2) Population exposure risks to pollutants showed an increasing trend, with PM2.5 and O3 increasing by 55.1 % and 42.7 %, respectively. The annual deaths associated with exposure to PM2.5 and O3 demonstrated a decreasing and inverted U-shaped trend, respectively, with annual average deaths of 1.312 million and 98,000. Significant regional disparities in health risks from these pollutants were influenced by socio-economic factors such as industrial activities and population density. In the future, it is expected that more than half of China's regions will be exposed to rising risks of PM2.5 and O3 population exposure. (3) Key drivers of regional exacerbation in PM2.5 and O3 levels include the number of industrial enterprises above designated size (NSIE) and population agglomeration (PA), while the disposable income of urban residents (URDI), technological innovation (TI), and government attention level (GAL) emerged as primary factors in controlling pollution hotspots, ranked in order of influence from greatest to least as TI > GAL > URDI. Overall, this study sheds light on the current status of air pollution and health risk sustainability in China and enhances the understanding of future air pollution dynamics in China. The results of the study may help to develop effective targeted control measures to synergize the management of PM2.5 and O3 in different regions.

Long-term exposure to ambient PM2.5 and its components on menarche timing among Chinese adolescents: evidence from a representative nationwide cohort

BACKGROUND

Ambient air pollutants have been suggested to affect pubertal development. Nevertheless, current studies indicate inconsistent effects of these pollutants, causing precocious or delayed puberty onset. This study aimed to explore the associations between long-term exposure to particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5) along with its components and menarche timing among Chinese girls.

METHOD

Self-reported age at menarche was collected among 855 girls from China Health and Nutrition Survey 2004 to 2015. The pre-menarche annual average concentrations of PM2.5 and its components were calculated on the basis of a long-term (2000-2014) high-resolution PM2.5 components dataset. Generalized linear models (GLM) and logistic regression models were used to analyze the associations of exposure to a single pollutant (PM2.5, sulfate, nitrate, ammonium, black carbon and organic matter) with age at menarche and early menarche (< 12 years), respectively. Weighted quantile sum methods were applied to examine the impacts of joint exposure on menarche timing.

RESULTS

In the adjusted GLM, per 1 µg/m3 increase of annual average concentrations of nitrate and ammonium decreased age at menarche by 0.098 years and 0.127 years, respectively (all P < 0.05). Every 1 µg/m3 increase of annual average concentrations of PM2.5 (OR: 1.04, 95% CI: 1.00-1.08), sulfate (OR: 1.23, 95% CI: 1.01-1.50), nitrate (OR: 1.23, 95% CI: 1.06-1.43) and ammonium (OR: 1.32, 95% CI: 1.06-1.66) were significantly positively associated with early menarche. Higher level of joint exposure to PM2.5 and its components was associated with 11% higher odds of early menarche (P = 0.04). Additionally, the estimated weight of sulfate was the largest among the mixed pollutants.

CONCLUSIONS

Long-term exposure to PM2.5 and its components could increase the risk of early menarche among Chinese girls. Moreover, sulfate might be the most critical components responsible for this relationship. Our study provides foundation for targeted prevention of PM2.5 components.

Time-sensitive prediction of NO2 concentration in China using an ensemble machine learning model from multi-source data

Nitrogen dioxide (NO2) poses a critical potential risk to environmental quality and public health. A reliable machine learning (ML) forecasting framework will be useful to provide valuable information to support government decision-making. Based on the data from 1609 air quality monitors across China from 2014-2020, this study designed an ensemble ML model by integrating multiple types of spatial-temporal variables and three sub-models for time-sensitive prediction over a wide range. The ensemble ML model incorporates a residual connection to the gated recurrent unit (GRU) network and adopts the advantage of Transformer, extreme gradient boosting (XGBoost) and GRU with residual connection network, resulting in a 4.1%±1.0% lower root mean square error over XGBoost for the test results. The ensemble model shows great prediction performance, with coefficient of determination of 0.91, 0.86, and 0.77 for 1-hr, 3-hr, and 24-hr averages for the test results, respectively. In particular, this model has achieved excellent performance with low spatial uncertainty in Central, East, and North China, the major site-dense zones. Through the interpretability analysis based on the Shapley value for different temporal resolutions, we found that the contribution of atmospheric chemical processes is more important for hourly predictions compared with the daily scale predictions, while the impact of meteorological conditions would be ever-prominent for the latter. Compared with existing models for different spatiotemporal scales, the present model can be implemented at any air quality monitoring station across China to facilitate achieving rapid and dependable forecast of NO2, which will help developing effective control policies.

The mediation effect of asprosin on the association between ambient air pollution and diabetes mellitus in the elderly population in Taiyuan, China

Evidence around the relationship between air pollution and the development of diabetes mellitus (DM) remains limited and inconsistent. To investigate the potential mediation effect of asprosin on the association between fine particulate matter (PM2.5), tropospheric ozone (O3) and blood glucose homeostasis. A case-control study was conducted on a total of 320 individuals aged over 60 years, including both diabetic and non-diabetic individuals, from six communities in Taiyuan, China, from July to September 2021. Generalized linear models (GLMs) suggested that short-term exposure to PM2.5 was associated with elevated fasting blood glucose (FBG), insulin resistance index (HOMA-IR), as well as reduced pancreatic β-cell function index (HOMA-β), and short-term exposure to O3 was associated with increased FBG and decreased HOMA-β in the total population and elderly diabetic patients. Mediation analysis showed that asprosin played a mediating role in the relationship of PM2.5 and O3 with FBG, with mediating ratios of 10.2% and 18.4%, respectively. Our study provides emerging evidence supporting that asprosin mediates the short-term effects of exposure to PM2.5 and O3 on elevated FBG levels in an elderly population. Additionally, the elderly who are diabetic, over 70 years, and BMI over 24 kg/m2 are more vulnerable to air pollutants and need additional protection to reduce their exposure to air pollution.

Spatiotemporal patterns of surface ozone exposure inequality in China

Rising surface ozone (O3) levels in China are increasingly emphasizing the potential threats to public health, ecological balance, and economic sustainability. Using a 1 km × 1 km dataset of O3 concentrations, this research employs subpopulation demographic data combined with a population-weighted quality model. Its aim is to evaluate quantitatively the differences in O3 exposure among various subpopulations within China, both at a provincial and urban cluster level. Additionally, an exposure disparity indicator was devised to establish unambiguous exposure risks among significant urban agglomerations at varying O3 concentration levels. The findings reveal that as of 2018, the population-weighted average concentration of O3 for all subgroups has experienced a significant uptick, surpassing the average O3 concentration (118 μg/m3). Notably, the middle-aged demographic exhibited the highest O3 exposure level at 135.7 μg/m3, which is significantly elevated compared to other age brackets. Concurrently, there exists a prominent positive correlation between educational attainment and O3 exposure levels, with the medium-income bracket showing the greatest susceptibility to O3 exposure risks. From an industrial vantage point, the secondary sector demographic is the most adversely impacted by O3 exposure. In terms of urban-rural structure, urban groups in all regions had higher levels of exposure to O3 than rural areas, with North and East China having the most significant levels of exposure. These findings not only emphasize the intricate interplay between public health and environmental justice but further highlight the indispensability of segmented subgroup strategies in environmental health risk assessment. Moreover, this research furnishes invaluable scientific groundwork for crafting targeted public health interventions and sustainable air quality management policies.

Short-Term Exposure to PM2.5 Chemical Components and Depression Outpatient Visits: A Case-Crossover Analysis in Three Chinese Cities

BACKGROUND

The association between specific chemical components of PM2.5 and depression remains largely unknown.

METHODS

We conducted a time-stratified case-crossover analysis with a distributed lag nonlinear model (DLNM) to evaluate the relationship of PM2.5 and its chemical components, including black carbon (BC), organic matter (OM), sulfate (SO42-), nitrate (NO3-), and ammonium (NH4+), with the depression incidence. Daily depression outpatients were enrolled from Huizhou, Shenzhen, and Zhaoqing.

RESULTS

Among 247,281 outpatients, we found the strongest cumulative effects of PM2.5 and its chemical components with the odd ratios (ORs) of 1.607 (95% CI: 1.321, 1.956) and 1.417 (95% CI: 1.245, 1.612) at the 50th percentile of PM2.5 and OM at lag 21, respectively. Furthermore, the ORs with SO42- and NH4+ at the 75th percentile on the same lag day were 1.418 (95% CI: 1.247, 1.613) and 1.025 (95% CI: 1.009, 1.140). Relatively stronger associations were observed among females and the elderly.

CONCLUSIONS

Our study suggests that PM2.5 and its chemical components might be important risk factors for depression. Reducing PM2.5 emissions, with a particular focus on the major sources of SO42- and OM, might potentially alleviate the burden of depression in South China.

A Chinese longitudinal maternity cohort study (2013-2021) on intrahepatic cholestasis phenotypes: Risk associations from environmental exposure to adverse pregnancy outcomes

Intrahepatic cholestasis of pregnancy (ICP) is an idiopathic disease that occurs during mid-to-late pregnancy and is associated with various adverse pregnancy outcomes, including intrauterine fetal demise. However, since the underlying cause of ICP remains unclear, there is an ongoing debate on the phenotyping criteria used in the diagnostic process. Here, we identified single- and multi-symptomatic ICP (ICP-S and ICP-M) in 104,221 Chinese females from the ZEBRA maternity cohort, with the objective of exploring the risk implications of the two phenotypes on pregnancy outcomes and from environmental exposures. We employed multivariate binary logistic regression to estimate confounder-adjusted odds ratios and found that ICP-M was more strongly associated with preterm birth and low birth weight compared to ICP-S. Throughout pregnancy, incremental exposure to PM2.5, O3, and greenness could alter ICP risks by 17.3%, 12.5%, and -2.3%, respectively, with more substantial associations observed with ICP-M than with ICP-S. The major scientific advancements lie in the elucidation of synergistic risk interactions between pollutants and the protective antagonistic effects of greenness, as well as highlighting the risk impact of preconceptional environmental exposures. Our study, conducted in the context of the "three-child policy" in China, provides epidemiological evidence for policy-making to safeguard maternal and neonatal health.

Association between PM2.5 and hypertension among the floating population in China: a cross-sectional study

Few studies have investigated the association between PM2.5 and hypertension among floating populations. We therefore examined the relationship using binary logistic regression. Each grade of increment in the annual average PM2.5 (grade one: ≤15 µg/m3; grade two: 15-25 µg/m3; grade three: 25-35 µg/m3 [Excluding 25]; grade four: ≥35 µg/m3) was associated with an increased risk of hypertension (odds ratio [OR] = 1.081, 95% confidence interval (CI): 1.034-1.129). Among the female floating population (OR = 1.114, 95% CI: 1.030-1.204), those with education level of primary school and below (OR = 1.140, 95% CI: 1.058-1.229), construction workers (OR = 1.228, 95% CI: 1.058-1.426), and those living in the eastern region of China (OR = 1.241, 95% CI: 1.145-1.346) were more vulnerable to PM2.5. These results indicate that PM2.5 is positively associated with hypertension in floating populations. Floating populations who are female, less educated, construction workers, and living in the eastern region of China are more vulnerable to the adverse impacts of PM2.5.

Prenatal exposure to PM2.5 components and the risk of different types of preterm birth and the mediating effect of pregnancy complications: a cohort study

OBJECTIVES

This study aims to reveal the single and mixed associations of PM2.5 and its components with very, moderately, and late preterm births and to explore the potential mediating role of pregnancy complications in PM2.5-induced preterm birth.

STUDY DESIGN

This was a retrospective cohort study.

METHODS

We enrolled 168,852 mothers and matched the concentrations of PM2.5 and its five components (OM, SO42-, BC, NO3-, and NH4+) based on their geographical location. Next, we used generalized linear models, quantile g-computation, and mediation analysis to evaluate the associations of PM2.5 and its components with very, moderately, and late preterm births and the mediating role of pregnancy complications.

RESULTS

Prenatal exposure to PM2.5 and its components was associated with preterm birth, and the association was strongest in the third trimester. Preterm birth was associated with co-exposure to a mixture of PM2.5 components in the third trimester, and the contributions of NO3-, NH4+, and BC to the risk of preterm birth were positive. Meanwhile, pregnancy complications mediated PM2.5-induced preterm birth. Moreover, very and moderately preterm births were associated with PM2.5 and its components in the second and third trimesters, and very and late preterm births were associated with co-exposure to a mixture of PM2.5 components in the third trimester.

CONCLUSIONS

Later exposure to PM2.5 during pregnancy will cause earlier preterm birth. Targeted and positive interventions for anthropogenic sources of specific PM2.5 components and pregnancy complications are helpful for preterm birth prevention.

Effects of long-term exposure to ambient fine particulate matter and its specific components on blood pressure and hypertension incidence

BACKGROUND

Epidemiological evidence on the association of PM2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) and its specific components with hypertension and blood pressure is limited.

METHODS

We applied information of participants from the World Health Organization's (WHO) Study on Global Ageing and Adult Health (SAGE) to estimate the associations of long-term PM2.5 mass and its chemical components exposure with blood pressure (BP) and hypertension incidence in Chinese adults ≥ 50 years during 2007-2018. Generalized linear mixed model and Cox proportional hazard model were applied to investigate the effects of PM2.5 mass and its chemical components on the incidence of hypertension and BP, respectively.

RESULTS

Each interquartile range (IQR = 16.80 μg/m3) increase in the one-year average of PM2.5 mass concentration was associated with a 17 % increase in the risk of hypertension (HR = 1.17, 95 % CI: 1.10, 1.24), and the population attributable fraction (PAF) was 23.44 % (95 % CI: 14.69 %, 31.55 %). Each IQR μg/m3 increase in PM2.5 exposure was also related to increases of systolic blood pressure (SBP) by 2.54 mmHg (95 % CI:1.99, 3.10), and of diastolic blood pressure (DBP) by 1.36 mmHg (95 % CI: 1.04, 1.68). Additionally, the chemical components of SO42-, NO3-, NH4+, OM, and BC were also positively associated with an increased risk of hypertension incidence and elevated blood pressure.

CONCLUSIONS

These results indicate that long-term exposure to PM2.5 mass and its specific components may be major drivers of escalation in hypertension diseases.

Prenatal exposure to fine particulate matter chemical constituents and the risk of stillbirth and the mediating role of pregnancy complications: A cohort study

Evidence on the association of fine particulate matter (PM2.5) exposure with stillbirth is limited and inconsistent, which is largely attributed to differences in PM2.5 constituents. Studies have found that the hazards of certain PM2.5 constituents to the fetus are comparable to or even higher than total PM2.5 mass. However, few studies have linked PM2.5 constituents to stillbirth. Moreover, the mediating role of pregnancy complications in PM2.5-related stillbirth remains unclear. To our knowledge, this study was the first to explore the individual and mixed associations of PM2.5 and its constituents with stillbirth in China. After matching the concentrations of PM2.5 and its constituents (sulfate [SO42-], nitrate [NO3-], ammonium [NH4+], organic matter [OM], and black carbon [BC]) for participants according to their geographical location, there were 170,507 participants included in this study. We found that stillbirth was associated with exposure to PM2.5 and its constituents in the year before pregnancy and during the entire pregnancy, and the associations in trimester 1 were strongest. The risk of stillbirth increased sharply when PM2.5 and its constituents during pregnancy exceeded the median concentrations. Moreover, stillbirth was associated with exposure to the mixtures of SO42-, NO3-, NH4+, OM, and BC before and during pregnancy (trimesters 1 and 2). Meanwhile, two-pollutant models also suggested stillbirth was associated with PM2.5 and its constituents in the year before and during pregnancy. The associations of PM2.5 and its constituents with stillbirth were stronger in mothers with advanced age and without cesarean delivery history. Additionally, hypertensive disorders in pregnancy, gestational diabetes, and placental abruption mediated the association of PM2.5 with stillbirth. Therefore, enhanced protection against PM2.5 for pregnant women before and during pregnancy and targeted interventions for pregnancy complications and anthropogenic sources of PM2.5 constituents are important to reduce stillbirth risk.

Exposure to PM2.5 and its five constituents is associated with the incidence of type 2 diabetes mellitus: a prospective cohort study in northwest China

Studies have demonstrated that fine particulate matter (PM2.5) is an underlying risk factor for type 2 diabetes mellitus (T2DM), but evidence exploring the relationship between PM2.5 chemical components and T2DM was extremely limited, to investigate the effects of long-term exposure to PM2.5 and its five constituents (sulfate [SO42-], nitrate [NO3-], ammonium [NH4+]), organic matter [OM] and black carbon [BC]) on incidence of T2DM. Based on the "Jinchang Cohort" platform, a total of 19,884 participants were selected for analysis. Daily average concentrations of pollutants were gained from Tracking Air Pollution in China (TAP). Cox proportional hazards regression models were utilized to estimate the hazard ratios (HR) and 95% confidence interval (CI) in single-pollutant models, restricted cubic splines functions were used to examine the dose-response relationships, and quantile g-computation (QgC) was applied to evaluate the combined effect of PM2.5 compositions on T2DM. Stratification analysis was also considered. A total of 791 developed new cases of T2DM were observed during a follow-up period of 45254.16 person-years. The concentrations of PM2.5, NO3-, NH4+, OM and BC were significantly associated with incidence of T2DM (P-trend < 0.05), with the HRs in the highest quartiles of 2.16 (95% CI 1.79, 2.62), 1.43 (95% CI 1.16, 1.75), 1.75 (95% CI 1.45, 2.11), 1.31 (95% CI 1.08, 1.59) and 1.79 (95% CI 1.46, 2.21), respectively. Findings of QgC model showed a noticeably positive joint effect of one quartile increase in PM2.5 constituents on increased T2DM morbidity (HR 1.27, 95% CI 1.09, 1.49), and BC (32.7%) contributed the most to the overall effect. The drinkers, workers and subjects with hypertension, obesity, higher physical activity, and lower education and income were generally more susceptible to PM2.5 components hazards. Long-term exposure to PM2.5 and its components (i.e., NO3-, NH4+, OM, BC) was positively correlated with T2DM incidence. Moreover, BC may be the most responsible for the association between PM2.5 constituents and T2DM. In the future, more epidemiological and experimental studies are needed to identify the link and potential biological mechanisms.

Association of PM2.5 mass and its components with ovarian reserve in a northern peninsular province, China: The critical exposure period and components

BACKGROUND

A possible role of PM2.5 components on ovarian reserve has not been adequately unexplored.

OBJECTIVE

To evaluate the association between PM2.5 components and women' ovarian reserve over critical exposure periods in northern China, where the level of air pollution is among the nation's highest.

METHODS

We included 15,102 women with serum anti-Müllerian hormone (AMH) measurements from the Center for Reproductive Medicine of Shandong University during 2015-2019. Concentrations of PM2.5 and its five major components (0.1° × 0.1°), including sulfate, nitrate, ammonium, organic matter, and black carbon, were assigned to each residential address. Multivariable linear mixed effect models combined with constituent-residual models were performed to estimate the effect sizes of essential components over six short- to long-term exposure periods.

RESULTS

The strength of association was stronger during the process from primary to small antral follicle compared with other longer windows. For every interquartile range increase in PM2.5 mass was associated with - 8.7% (95%CI: -12.3%, -4.9%) change in AMH and the effect size was greatest for sulfate. Women with the lower level of attained education and those living inland were more susceptible compared with other population subgroups.

CONCLUSION

Exposure to specific components of air pollution during critical exposure windows is associated with a decline in ovarian reserve. These data add to the growing body of evidence that environmental factors have adverse effects on reproductive health, particularly for vulnerable population subgroups.

Long-term effects of PM2.5 constituents on metabolic syndrome and mediation effects of serum uric acid

Exposure to particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) was associated with the risk for metabolic syndrome (MetS) in the general population, but the contributions of individual PM2.5 constituents to this association and the potential pathway between PM2.5 constituents and MetS risk are not well elaborated. This study aimed to investigate associations between PM2.5 constituents and MetS in general populations, relative importance of PM2.5 constituents to and mediation effects of serum uric acid (SUA) on those associations. The 48,148 participants from a provincially representative cohort established in southwest China were included. The 3-year average concentrations of PM2.5 and its constituents (nitrate [NO3-], sulfate [SO42-], ammonium [NH4+], organic matter [OM], and black carbon [BC]) were estimated using a series of machine-learning models. Multivariate logistic regression and weighted quantile sum regression were used to estimate effects of independent PM2.5 constituents on MetS and their contributions to the joint effect. Mediation analysis examined the potential mediation effects of SUA on the associations between PM2.5 constituents and MetS. Each interquartile range (IQR) increase in the concentration of PM2.5 constituents was all positively associated with the increased MetS odds, including SO42- (OR = 1.15 [1.11, 1.19]]), NO3- (OR = 1.12 [1.08, 1.16]), NH4+ (OR = 1.13 [1.09, 1.17]), OM (OR = 1.09 [1.06, 1.13]), and BC (OR = 1.09 [1.06, 1.13]). Their joint associations on MetS were mainly attributed to SO42- (weight=46.1%) and NH4+ (44.0%). The associations of PM2.5 constituents with abnormal MetS components were mainly attributed to NH4+ for elevated BP (51.6%) and reduced HDL-C (97.0%), SO42- for elevated FG (68.9%), NO3- for elevated TG (51.0%), and OM for elevated WC (63.0%). Percentages mediated by SUA for the associations of PM2.5, SO42-, NO3-, and BC with MetS were 13.6%, 13.1%, 10.6%, and 11.1%, respectively. Long-term exposure to PM2.5 constituents, mainly NH4+ and SO42-, was positively associated with MetS odds, partially mediated by SUA.

A study on identifying synergistic prevention and control regions for PM2.5 and O3 and exploring their spatiotemporal dynamic in China

Air pollutants, notably ozone (O3) and fine particulate matter (PM2.5) give rise to evident adverse impacts on public health and the ecotope, prompting extensive global apprehension. Though PM2.5 has been effectively mitigated in China, O3 has been emerging as a primary pollutant, especially in summer. Currently, alleviating PM2.5 and O3 synergistically faces huge challenges. The synergistic prevention and control (SPC) regions of PM2.5 and O3 and their spatiotemporal patterns were still unclear. To address the above issues, this study utilized ground monitoring station data, meteorological data, and auxiliary data to predict the China High-Resolution O3 Dataset (CHROD) via a two-stage model. Furthermore, SPC regions were identified based on a spatial overlay analysis using a Geographic Information System (GIS). The standard deviation ellipse was employed to investigate the spatiotemporal dynamic characteristics of SPC regions. Some outcomes were obtained. The two-stage model significantly improved the accuracy of O3 concentration prediction with acceptable R2 (0.86), and our CHROD presented higher spatiotemporal resolution compared with existing products. SPC regions exhibited significant spatiotemporal variations during the Blue Sky Protection Campaign (BSPC) in China. SPC regions were dominant in spring and autumn, and O3-controlled and PM2.5-dominated zones were detected in summer and winter, respectively. SPC regions were primarily located in the northwest, north, east, and central regions of China, specifically in the Beijing-Tianjin-Hebei urban agglomeration (BTH), Shanxi, Shaanxi, Shandong, Henan, Jiangsu, Xinjiang, and Anhui provinces. The gravity center of SPC regions was distributed in the BTH in winter, and in Xinjiang during spring, summer, and autumn. This study can supply scientific references for the collaborative management of PM2.5 and O3.