Long-term exposure to particulate matter has been increasingly implicated in the progression of chronic kidney disease (CKD). However, its impact on IgA nephropathy (IgAN), a leading cause of end-stage renal disease (ESRD), remains unclear. A total of 1768 IgAN patients, confirmed by renal biopsy were included in this cohort study. Long-term exposure to PM_2.5 and PM₁₀ was assessed using high-resolution satellite-based data from the China High Air Pollutants (CHAP) dataset. Cox proportional hazards models were used to estimate the associations between PM_2.5 or PM₁₀ and ESRD risk, adjusting for demographic, clinical, and biochemical covariates. Over a median follow-up of 3.63 years, 209 participants progressed to ESRD. Higher exposure to both PM_2.5 and PM₁₀ was significantly associated with an increased risk, with hazard ratios of 1.62 and 1.36 per 10 µg/m³ increase, respectively. A nonlinear dose-response relationship was observed, with risk increasing markedly beyond threshold levels. Trajectory modeling of prebaseline exposure identified a subgroup with persistently high and fluctuating particulate matter exposure that showed the highest risk. This study provides strong evidence that prolonged exposure to ambient particulate matter contributes to renal disease progression in individuals with IgAN.
Humans ; Glomerulonephritis, IGA/pathology* ; Particulate Matter/adverse effects* ; Male ; Female ; Kidney Failure, Chronic/epidemiology* ; Adult ; China/epidemiology* ; Disease Progression ; Environmental Exposure/adverse effects* ; Middle Aged ; Proportional Hazards Models ; Risk Factors ; Air Pollutants/adverse effects* ; Cohort Studies

OBJECTIVE: To examine the mechanistic of organochlorine-associated changes in lung function. METHODS: This study investigated 76 healthy older adults in Jinan, Shandong Province, over a five-month period. Personal exposure to organochlorines was quantified using wearable passive samplers, while inflammatory factors and thyroid hormones were analyzed from blood samples. Participants' lung function was evaluated. After stratifying participants according to their thyroid hormone levels, we analyzed the differential effects of organochlorine exposure on lung function and inflammatory factors across the low and high thyroid hormone groups. Mediation analysis was further conducted to elucidate the relationships among organochlorine exposures, inflammatory factors, and lung function. RESULTS: Bis (2-chloro-1-methylethyl) ether (BCIE), was negatively associated with forced vital capacity (FVC, -2.05%, 95% CI: -3.11% to -0.97%), and associated with changes in inflammatory factors such as interleukin (IL)-2, IL-7, IL-8, and IL-13 in the low thyroid hormone group. The mediation analysis indicated a mediating effect of IL-2 (15.63%, 95% CI: 0.91% to 44.64%) and IL-13 (13.94%, 95% CI: 0.52% to 41.07%) in the association between BCIE exposure and FVC. CONCLUSION Lung function and inflammatory factors exhibited an increased sensitivity to organochlorine exposure at lower thyroid hormone levels, with inflammatory factors potentially mediating the adverse effects of organochlorines on lung function.
Environmental Exposure ; Hydrocarbons, Chlorinated/metabolism* ; China ; Ethyl Ethers/metabolism* ; Environmental Monitoring ; Thyroid Hormones/blood* ; Lung/physiology* ; Inhalation Exposure/statistics & numerical data* ; Air Pollution/statistics & numerical data* ; Air Pollutants/metabolism* ; Humans ; Male ; Female ; Middle Aged ; Aged

OBJECTIVE: Several epidemiological observational studies have related particulate matter (PM) exposure to Inflammatory bowel disease (IBD), but many confounding factors make it difficult to draw causal links from observational studies. The objective of this study was to explore the causal association between PM _2.5 exposure, its absorbance, and IBD. METHODS: We assessed the association of PM _2.5 and PM _2.5 absorbance with the two primary forms of IBD (Crohn's disease [CD] and ulcerative colitis [UC]) using Mendelian randomization (MR) to explore the causal relationship. We conducted two-sample MR analyses with aggregated data from the UK Biobank genome-wide association study. Single-nucleotide polymorphisms linked with PM _2.5 concentrations or their absorbance were used as instrumental variables (IVs). We used inverse variance weighting (IVW) as the primary analytical approach and four other standard methods as supplementary analyses for quality control. RESULTS: The results of MR demonstrated that PM _2.5 had an adverse influence on UC risk (odds ratio [ OR] = 1.010; 95% confidence interval [ CI] = 1.001-1.019, P = 0.020). Meanwhile, the results of IVW showed that PM _2.5 absorbance was also causally associated with UC ( OR = 1.012; 95% CI = 1.004-1.019, P = 0.002). We observed no causal relationship between PM _2.5, PM _2.5 absorbance, and CD. The results of sensitivity analysis indicated the absence of heterogeneity or pleiotropy, ensuring the reliability of MR results. CONCLUSION Based on two-sample MR analyses, there are potential positive causal relationships between PM _2.5, PM _2.5 absorbance, and UC.
Humans ; Mendelian Randomization Analysis ; Particulate Matter/analysis* ; Polymorphism, Single Nucleotide ; Inflammatory Bowel Diseases/genetics* ; Air Pollutants/analysis* ; Crohn Disease/genetics* ; Colitis, Ulcerative/genetics* ; Genome-Wide Association Study ; Risk Factors ; Environmental Exposure

OBJECTIVE: The results of limited studies on the relationship between environmental pollution and dementia have been contradictory. We analyzed the combined effects of PM _2.5 and smoking on the prevalence of dementia and cognitive impairment in an elderly community-dwelling Chinese population. METHODS: We assessed 24,117 individuals along with the annual average PM _2.5 concentrations from 2012 to 2016. Dementia was confirmed in the baseline survey at a qualified clinical facility, and newly suspected dementia was assessed in 2017, after excluding cases of suspected dementia in 2015. National census data were used to weight the sample data to reflect the entire population in China, with multiple logistic regression performed to analyze the combined effects of PM _2.5 and smoking frequency on dementia and cognitive impairment. RESULTS: Individuals exposed to the highest PM _2.5 concentration and smoked daily were at higher risk of dementia than those in the lowest PM _2.5 concentration group ( OR, 1.603; 95% CI [1.626-1.635], P < 0.0001) and in the nonsmoking group ( OR, 1.248; 95% CI [1.244-1.252]; P < 0.0001). Moderate PM _2.5 exposure and occasional smoking together increased the short-term risk of cognitive impairment. High-level PM _2.5 exposure and smoking were associated with an increased risk of dementia, so more efforts are needed to reduce this risk through environmental protection and antismoking campaigns. CONCLUSION High-level PM _2.5 exposure and smoking were associated with an increased risk of dementia. Lowering the ambient PM _2.5, and smoking cessation are recommended to promote health.
Humans ; Dementia/etiology* ; Male ; Aged ; Female ; Cognitive Dysfunction/etiology* ; China/epidemiology* ; Particulate Matter/analysis* ; Smoking/epidemiology* ; Air Pollutants/analysis* ; Aged, 80 and over ; Environmental Exposure/adverse effects* ; Prevalence ; Middle Aged

OBJECTIVE: This study aimed to identify high-risk areas for type 2 diabetes mellitus (T2DM) mortality to provide relevant evidence for interventions in emerging economies. METHODS: Empirical Bayesian Kriging and a discrete Poisson space-time scan statistic were applied to identify the spatiotemporal clusters of T2DM mortality. The relationships between economic factors, air pollutants, and the mortality risk of T2DM were assessed using regression analysis and the Poisson Log-linear Model. RESULTS: A coastal district in East Guangdong, China, had the highest risk (Relative Risk [RR] = 4.58, P < 0.01), followed by the 10 coastal districts/counties in West Guangdong, China (RR = 2.88, P < 0.01). The coastal county in the Pearl River Delta, China (RR = 2.24, P < 0.01), had the third-highest risk. The remaining risk areas were two coastal counties in East Guangdong, 16 districts/counties in the Pearl River Delta, and two counties in North Guangdong, China. Mortality due to T2DM was associated with gross domestic product per capita (GDP per capita). In pilot assessments, T2DM mortality was significantly associated with carbon monoxide. CONCLUSION High mortality from T2DM occurred in the coastal areas of East and West Guangdong, especially where the economy was progressing towards the upper middle-income level.
Diabetes Mellitus, Type 2/epidemiology* ; China/epidemiology* ; Humans ; Risk Factors ; Spatio-Temporal Analysis ; Air Pollutants/analysis* ; Socioeconomic Factors ; Bayes Theorem ; Female ; Male ; Middle Aged

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

OBJECTIVES: To characterize fine particulate matter (PM _2.5)-bound polycyclic aromatic hydrocarbons (PAHs) emitted from different cooking fumes and their exposure routes and assess their health-associated impact to provide a reference for health risk prevention from PAH exposure across different age and sex groups. METHODS: Sixteen PM _2.5-bound PAHs emitted from 11 cooking styles were analyzed using GC-MS/MS. The health hazards of these PAHs in the Handan City population (stratified by age and sex) were predicted using the incremental lifetime cancer risk ( ILCR) model. The respiratory deposition doses ( RDDs) of the PAHs in children and adults were calculated using the PM _2.5 deposition rates in the upper airway, tracheobronchial, and alveolar regions. RESULTS: The total concentrations of PM _2.5-bound PAHs ranged from 61.10 to 403.80 ng/m ³. Regardless of cooking styles, the ILCR _total values for adults (1.23 × 10 ^-6 to 3.70 × 10 ^-6) and older adults (1.28 × 10 ^-6 to 3.88 × 10 ^-6) exceeded the acceptable limit of 1.00 × 10 ^-6. With increasing age, the ILCR _total value first declined and then increased, varying substantially among the population groups. Cancer risk exhibited particularly high sensitivity to short exposure to barbecue-derived PAHs under equivalent body weights. Furthermore, barbecue, Sichuan and Hunan cuisine, Chinese cuisine, and Chinese fast food were associated with higher RDDs for both adults and children. CONCLUSION ILCR _total values exceeded the acceptable limit for both females and males of adults, with all cooking styles showing a potentially high cancer risk. Our findings serve as an important reference for refining regulatory strategies related to catering emissions and mitigating health risks associated with cooking styles.
Humans ; Polycyclic Aromatic Hydrocarbons/analysis* ; Cooking/methods* ; Male ; Female ; Particulate Matter/analysis* ; Adult ; Child ; Middle Aged ; Air Pollutants/analysis* ; Adolescent ; Air Pollution, Indoor/analysis* ; Young Adult ; Child, Preschool ; Aged ; China ; Inhalation Exposure ; Age Factors ; Sex Factors ; Cities ; Infant

OBJECTIVE: To investigate the association between long-term exposure to ambient fine particulate matter (PM _2.5) and its constituents and the risk of incident type 2 diabetes mellitus (T2DM), and to examine the modification roles of overweight status. METHODS: This prospective study included 27,507 adults living in rural China. The annual mean residential exposure to PM _2.5 and its constituents was estimated using a satellite-based statistical model. Cox models were used to estimate the risk of T2DM associated with PM _2.5 and its constituents. Stratified analysis quantified the role of overweight status in the association between PM _2.5 constituents and T2DM. RESULTS: Over a median follow-up of 9.4 years, 3,001 new T2DM cases were identified. The hazard ratio ( HR) for a 10 μg/m ³ increase in ambient PM _2.5 was 1.30 (95% confidence interval [ CI]: 1.17, 1.45). Among the constituents, the strongest association was observed with black carbon. Being overweight significantly modified the association between certain constituents and the risk of T2DM. Participants who were overweight and exposed to the highest quartile of PM _2.5 constituents had the highest risk of T2DM ( HR: 2.46, 95% CI: 2.04, 2.97). CONCLUSIONS Our findings indicate that PM _2.5 was associated with an increased risk of T2DM, with black carbon potentially being the primary contributor. Being overweight appeared to enhance the association between PM _2.5 and T2DM. This suggests that controlling both PM _2.5 exposure and overweight status may reduce the burden of T2DM.
Humans ; Diabetes Mellitus, Type 2/chemically induced* ; China/epidemiology* ; Particulate Matter/analysis* ; Overweight/epidemiology* ; Female ; Male ; Middle Aged ; Rural Population ; Air Pollutants/analysis* ; Adult ; Prospective Studies ; Environmental Exposure/adverse effects* ; Aged ; Risk Factors

OBJECTIVE: To assess the short-term lag effects of climate and air pollution on hospital admissions for cardiovascular and respiratory diseases, and to develop deep learning-based models for daily hospital admission prediction. METHODS: A multi-city study was conducted in Tokyo's 23 wards, Osaka City, and Nagoya City. Random forest models were employed to assess the synergistic short-term lag effects (lag0, lag3, and lag7) of climate and air pollutants on hospitalization for five cardiovascular diseases (CVDs) and two respiratory diseases (RDs). Furthermore, we developed hybrid deep learning models that integrated an autoencoder (AE) with a Long Short-Term Memory network (AE+LSTM) to predict daily hospital admissions. RESULTS: On the day of exposure (lag0), air pollutants, particularly nitrogen oxides (NO x), exhibited the strongest influence on hospital admissions for CVD and RD, with pronounced effects observed for hypertension (I10-I15), ischemic heart disease (I20), arterial and capillary diseases (I70-I79), and lower respiratory infections (J20-J22 and J40-J47). At longer lags (lag3 and lag7), temperature and precipitation were more influential predictors. The AE+LSTM model outperformed the standard LSTM, improving the prediction accuracy by 32.4% for RD in Osaka and 20.94% for CVD in Nagoya. CONCLUSION Our findings reveal the dynamic, time-varying health risks associated with environmental exposure and demonstrate the utility of deep learnings in predicting short-term hospital admissions. This framework can inform early warning systems, enhance healthcare resource allocation, and support climate-adaptive public health strategies.
Humans ; Hospitalization/statistics & numerical data* ; Cardiovascular Diseases/epidemiology* ; Japan/epidemiology* ; Air Pollutants/analysis* ; Air Pollution/adverse effects* ; Cities/epidemiology* ; Climate ; Respiratory Tract Diseases/epidemiology* ; Deep Learning ; Male

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a major health concern in northwest China; however, the impact of particulate matter (PM) exposure during sand-dust storms (SDS) remains poorly understood. Therefore, this study aimed to investigate the association between PM exposure on SDS days and COPD hospitalization risk in arid regions. METHODS: Data on daily COPD hospitalizations were collected from 323 hospitals from 2018 to 2022, along with the corresponding air pollutant and meteorological data for each city in Gansu Province. Employing a space-time-stratified case-crossover design and conditional Poisson regression, we analyzed 265,379 COPD hospitalizations. RESULTS: PM exposure during SDS days significantly increased COPD hospitalization risk [relative risk ( RR) for PM _2.5, lag 3:1.028, 95% confidence interval ( CI): 1.021-1.034], particularly among men and the elderly, and during the cold season. The burden of PM exposure on COPD hospitalization was substantially high in Northwest China, especially in the arid and semi-arid regions. CONCLUSION Our findings revealed a positive correlation between PM exposure during SDS episodes and elevated hospitalization rates for COPD in arid and semi-arid zones in China. This highlights the urgency of developing region-specific public health strategies to address adverse respiratory outcomes associated with SDS-related air quality deterioration.
Humans ; China/epidemiology* ; Pulmonary Disease, Chronic Obstructive/chemically induced* ; Particulate Matter/analysis* ; Hospitalization/statistics & numerical data* ; Male ; Female ; Middle Aged ; Aged ; Air Pollutants/analysis* ; Environmental Exposure/adverse effects* ; Spatio-Temporal Analysis ; Adult ; Sand ; Air Pollution