Jul 2026· Frontiers in Public Health· Vol 14· 0 citations· 38 references
Medicine
Abstract
Background Short-term exposure to ambient air pollution has been associated with cardiovascular disease (CVD) mortality, but localized evidence from subtropical cities in southwestern China remains limited. This 11-year time-series study aimed to evaluate the short-term associations between six criteria air pollutants and daily CVD mortality in Nanning, China. Methods We conducted a time-series analysis using daily data on CVD mortality, air pollutant concentrations, and meteorological variables from 2014 to 2024 in Nanning. Generalized additive quasi-Poisson models were used to estimate associations across single-day lags (lag0-lag7) and cumulative lag windows (lag0-1 to lag0-7), adjusting for long-term trends, temperature, relative humidity, and day of the week. Exposure-response relationships were assessed using natural cubic splines. Stratified analyses were conducted by season and age group, and two-pollutant models and sensitivity analyses were performed to evaluate robustness. Results A total of 87,913 CVD deaths were recorded during the study period, of which 57.5% occurred in males and 77.9% occurred among individuals aged ≥65 years. In single-day lag models, PM2.5, PM10, SO2, NO2, and O3-8h showed significant positive associations with CVD mortality at early lag days. At lag0, the RRs were 1.014 (95% CI: 1.008–1.020) for PM2.5, 1.009 (95% CI: 1.006–1.013) for PM10, and 1.018 (95% CI: 1.011–1.026) for NO2, while SO2 showed its largest estimate at lag1 [RR = 1.044 (95% CI: 1.018–1.069)]. In cumulative lag models, PM2.5, PM10, SO2, NO2, and O3-8h showed significant cumulative associations, whereas CO was significant mainly in shorter lag windows. Season-stratified analyses suggested pollutant-specific variation between cold and warm seasons, although formal pollutant-by-season interaction tests were not statistically significant. Age-stratified analyses indicated broader susceptibility among older adults. The main associations were generally robust in sensitivity analyses, distributed lag models, and two-pollutant models, particularly for PM2.5, PM10, and NO2. Conclusion Short-term exposure to ambient air pollution was associated with increased CVD mortality, particularly for PM2.5, PM10, and NO2, with consistent effects across single-day and cumulative lag structures. The results highlight the cardiovascular risks of particulate and traffic-related pollution and support pollutant-specific air quality management and targeted protection for older adults during high-pollution periods.
Introduction: Short-term associations between ambient air pollution and cardiovascular morbidity remain inconsistent across different settings. This study evaluated these associations using Generalized Additive Models (GAMs) and examined the robustness of the findings through lag and sensitivity analyses.
Materials and methods: An ecological time-series analysis was conducted using a publicly available environmental–health dataset comprising 5,811 daily observations of air pollutant concentrations, meteorological variables, and aggregated cardiovascular morbidity indicators. GAMs with penalized smoothing splines were fitted to assess potentially non-linear exposure– response relationships while adjusting for meteorological covariates. Lag structures (Lag 0–3 days), alternative spline dimensions, and multi-pollutant models were evaluated as sensitivity analyses.
Results: The final GAM demonstrated limited explanatory capacity (AIC=25,602.9; AICc=25,604.6; explained deviance=1.04%). Pollutant smooth terms showed shallow non-linear exposure–response patterns (effective degrees of freedom: 8.36-9.40), but none were statistically significant (PM₂.₅: p=0.357; PM₁₀: p=0.950; NO₂: p=0.594; SO₂: p=0.339; O₃: p=0.530). Sensitivity analyses produced consistent results across alternative lag structures and spline dimensions, and model diagnostics indicated satisfactory fit without evidence of substantial over dispersion.
Conclusion: Only shallow, statistically non-significant short-term associations were identified. These findings should be interpreted within the limitations of the ecological design, potential exposure misclassification, and residual confounding.
S. Admane, Tejas Admane, Aditi Admane et al.· Journal of air pollution and...· 0 citations
A significant association between short-term exposure to air pollutants and CKD mortality in the population of Zhejiang Province is revealed and a need for governmental authorities to enhance the monitoring and control of air pollution to mitigate the health burden on the elderly is suggested.
Pin-Yuan Dai, Xiao-Yan Zhou, Wei-Wei Gong et al.· BMC Nephrology· 0 citations
BACKGROUND
Chronic lung diseases (CLD) pose a substantial public health burden. Although air pollution is a recognized risk factor, atmospheric humidity may influence respiratory health. Evidence evaluating multidimensional humidity indicators together with air pollution in relation to chronic lung disease in China remains limited.
METHODS
Data from 16,204 adults aged ≥45 years from the 2011, 2013, and 2015 waves of the China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Annual exposures to six air pollutants (CO, NO2, O3, PM2.5, PM10, SO2) and six humidity indicators (RH, AVP, VPD, DPT, MR, SH) were estimated at 1-km resolution. Multivariable logistic regression and restricted cubic spline models were applied. Stratified and sensitivity analyses were conducted.
RESULTS
Higher concentrations of CO, NO2, O3, PM2.5, and SO2 were linearly associated with increased self-reported CLD risk, while PM10 showed an approximate U-shaped relationship. Each interquartile-range increase in air pollutant concentrations was associated with an 18-45% higher odds of self-reported CLD. AVP, VPD, DPT, MR, and SH were positively associated with self-reported CLD risk, whereas RH exhibited an inverted U-shaped pattern. Weighted quantile sum analyses showed significant positive associations for both air pollution and humidity mixtures. A significant interaction between RH and sex was observed. Sensitivity analyses across different lag structures confirmed that air pollutants and atmospheric humidity were consistently associated with self-reported CLD risk.
CONCLUSIONS
Long-term exposure to ambient air pollution and multidimensional humidity indicators was independently associated with higher self-reported CLD risk, highlighting the importance of considering meteorological factors in disease prevention.
Zong-Hui Yang, Xiao-Xia Li· Journal of Asthma· 0 citations
The substantial burden of cardiovascular disease (CVD) attributable to air pollution remains a critical public health challenge, yet its combined effect with cardiometabolic factors is not fully understood. This study leveraged data from the Global Burden of Disease Study (GBD) and the China High Air Pollutants (CHAP) database to evaluate the CVD burden attributable to air pollution, which was found to increase progressively with age. We conducted a cross-sectional analysis using baseline (2011) data from 7420 participants aged ≥ 45 years in the China Health and Retirement Longitudinal Study (CHARLS), and a prospective cohort analysis in 8792 participants followed through 2020. In the longitudinal analysis, long-term exposure to PM2.5 (HR = 1.09, 95% CI: 1.03–1.16) and PM10 (HR = 1.07, 95% CI: 1.04–1.10) was significantly associated with an elevated risk of incident CVD, whereas the association for NO2 was nominally significant (HR = 1.12, 95% CI: 1.00–1.24) and that for O3 was not statistically significant (HR = 1.08, 95% CI: 0.93–1.27). Furthermore, prolonged exposure to these pollutants was associated with a higher prevalence of hypertension, diabetes, dyslipidemia, and obesity, and with adverse levels of metabolic indicators, including the TyG, TyG-BMI, and TyG-WC indices. A random forest model showed modest discrimination for incident CVD (AUC = 0.656), identifying PM10 and PM2.5 as the most important predictors. In conclusion, long-term exposure to ambient air pollution, particularly particulate matter, is associated with an increased risk of CVD and cardiometabolic disorders in middle-aged and older Chinese adults.
Xue-Hua Wang, Zhaohui Wang, Yan Wang· Bioengineering· 0 citations
Although long-term exposure to ambient fine particulate matter (PM
2.5
) is an established risk factor for stroke, evidence on the detrimental effects of its specific constituents remains limited. This study aimed to investigate the associations between long-term exposure to PM
2.5
constituents and incident stroke, and to identify the key contributor.
We conducted a nationwide prospective cohort study using data from the China Health and Retirement Longitudinal Study (CHARLS) between 2013 and 2018. Incident stroke cases were identified from CHARLS self-reported physician diagnoses during follow-up interviews. PM
2.5
constituent concentration data were derived from the Tracking Air Pollution in China (TAP) dataset, while temperature and relative humidity data were obtained from the European Center for Medium-Range Weather Forecasts Reanalysis v5 (ERA5). Individual records were matched with environmental exposure data to quantify the associations between specific PM
2.5
constituents (sulfate, nitrate, ammonium, organic matter, and black carbon) and the incident stroke. Multivariate Cox models and quantile-based g-computation were applied to assess the associations of PM
2.5
constituents with incident stroke and to identify the key contributor.
Over a median follow-up of 5.0 years, 610 incident stroke cases occurred among 8,724 participants. All five constituents were significantly associated with stroke onset, the adjusted hazard ratios (95% confidence interval [CI]) for each interquartile range increase were 1.55 (95% CI: 1.35–1.79) for PM
2.5
, 1.55 (95% CI: 1.34–1.79) for sulfate, 1.37 (95% CI: 1.18–1.59) for nitrate, 1.42 (95% CI: 1.24–1.63) for ammonium, 1.59 (95% CI: 1.40–1.80) for organic matter, and 1.77 (95% CI: 1.54–2.03) for black carbon, respectively. In the joint effect analysis, black carbon (28.6%) exhibited the largest weight within the mixture. Stratified analyses revealed that individuals aged over 65 years and residents of southern China were more susceptible.
Long-term exposure to PM
2.5
constituents is associated with an elevated risk of incident stroke, with black carbon showing the strongest association among the five constituents. Older adults and residents of southern China were found to exhibit heightened susceptibility. These findings highlight the importance of mitigating the growing stroke burden through tailored clinical approaches and targeted regulation of carbonaceous emissions, accounting for demographic and regional vulnerabilities.
Hao Wang, Miao-Miao Wei, Tai-Kun Lu et al.· Frontiers in Public Health· 0 citations
Long-term exposure to ambient air pollution perturbs white blood cell (WBC) homeostasis through inflammatory pathways. However, its pollutant- and time-window-specific, mixture-related associations with WBC counts, and whether metabolic dysfunction mediates them, remain uncertain. We conducted a retrospective cohort study of 29,603 adults who underwent routine health examinations at Liangshan General Hospital between 2016 and 2024. Daily concentrations of six air pollutants were assigned to geocoded residential addresses and aggregated into one-month, six-month, one-year, and two-year average exposures before examination. Exposure-response associations were examined using single-pollutant mixed-effect models. Quantile g-computation and Bayesian kernel machine regression were applied to assess mixture effects and each pollutant's direction and contribution, while exploratory mediation analysis quantified the extent to which fasting blood glucose (FBG) accounted for pollutant-WBC associations. Associations were strongest for six-month average exposures. Per IQR increase in CO, NO2, PM10, PM2.5 and SO2, WBC counts changed by -0.206×109/L (95% CI: -0.237, -0.174), -0.231×109/L (-0.270, -0.192), -0.349×109/L (-0.391, -0.307), -0.503×109/L (-0.552, -0.454) and -0.216×109/L (-0.242, -0.191), respectively, whereas O3 was positively associated with WBC counts. Mixture analyses indicated a time-window-dependent signal, with particulate matter dominant in the negative association in the six-month window, whereas the dominant negative contributor shifted to SO2 in the two-year window. Exploratory analyses suggested that FBG accounted for part of the associations between several pollutants and WBC counts (4.97%-10.98%). The subgroups identified as most vulnerable were overweight, urban, and after-COVID-19 participants. These findings suggest pollutant- and exposure-window-specific changes in WBC homeostasis, with glycaemic regulation contributing modestly to pollution-related immune alterations.
Tong-Yang Wu, S. Nyadanu, Gavin Pereira et al.· Environmental Pollution· 0 citations
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