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Zhou H, Liang X, Zhang X, Wu J, Jiang Y, Guo B, Wang J, Meng Q, Ding X, Baima Y, Li J, Wei J, Zhang J, Zhao X. Associations of Long-Term Exposure to Fine Particulate Constituents With Cardiovascular Diseases and Underlying Metabolic Mediations: A Prospective Population-Based Cohort in Southwest China. J Am Heart Assoc 2024; 13:e033455. [PMID: 38761074 PMCID: PMC11179805 DOI: 10.1161/jaha.123.033455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 04/01/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome. METHODS AND RESULTS A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1-km2 grid were derived based on satellite- and ground-based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P<0.05). Quantile g-computation showed positive associations with 4 types of CVD risks (HRs ranging from 1.48 to 2.25, all P<0.05). OM and chloride had maximum weights for CVD risks. Causal mediation analysis showed that the positive association of OM with total CVD was mediated by metabolic syndrome, with a mediation proportion of 1.3% (all P<0.05). CONCLUSIONS Long-term exposure to PM2.5 chemical constituents is positively associated with CVD risks. OM and chloride appear to play the most responsible role in the positive associations between PM2.5 and CVD. OM is probably associated with CVD through metabolic-related pathways.
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Affiliation(s)
- Hanwen Zhou
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Xian Liang
- Chengdu Center for Disease Control and Prevention Chengdu Sichuan China
| | - Xueli Zhang
- Health Information Center of Sichuan Province Chengdu Sichuan China
| | - Jialong Wu
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Ye Jiang
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Junhua Wang
- School of Public Health, The key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education Guizhou Medical University Guiyang China
| | - Qiong Meng
- Department of Epidemiology and Health Statistics, School of Public Health Kunming Medical University Kunming Yunnan China
| | - Xianbin Ding
- Chongqing Municipal Center for Disease Control and Prevention Chongqing China
| | | | - Jingzhong Li
- Tibet Center for Disease Control and Prevention Lhasa Tibet China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center University of Maryland College Park MD USA
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
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Shi W, Schooling CM, Leung GM, Zhao JV. Early-life exposure to ambient air pollution with cardiovascular risk factors in adolescents: Findings from the "Children of 1997" Hong Kong birth cohort. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 921:171119. [PMID: 38382602 DOI: 10.1016/j.scitotenv.2024.171119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/27/2024] [Accepted: 02/18/2024] [Indexed: 02/23/2024]
Abstract
BACKGROUND Long-term exposure to ambient air pollution is associated with cardiovascular disease (CVD) risk. Little is known about the impact of early-life exposure to air pollutants on CVD risk factors in late adolescence, which may track into adulthood. To clarify, we examined this question in a unique setting with high air pollution and a high level of economic development. METHODS This study leveraged the "Children of 1997" Hong Kong birth cohort (N = 8327), including here 3350 participants. We estimated ambient air pollutant exposure including inhalable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and nitrogen monoxide (NO) by growth phase (in utero, infancy, childhood) and overall based on residential address. Generalized linear regression was used to assess the associations of air pollutants exposure by growth phase and sex with CVD risk factors (fasting blood glucose, glycosylated hemoglobin, lipid profile, blood pressure, and body mass index) at 17.6 years. We also assessed whether associations varied by sex. RESULTS Early life exposed had little association with glucose metabolism, blood pressure or body mass index, but after considering multiple comparisons early exposure to PM10 was associated with low density lipoprotein (LDL) in boys, with β and 95 % confidence intervals (95 % CI) of 0.184 (0.069 to 0.298) mmol/l, 0.151 (0.056 to 0.248) mmol/l, and 0.157 (0.063 to 0.252) mmol/l by per interquartile range (IQR) increment of PM10 for in utero, infancy, and overall, respectively. No such associations were evident for girls, differences by sex were evident. CONCLUSIONS Our study suggested sex-specific associations of early-life PM10 exposure with elevated LDL in adolescence, especially exposure in utero and infancy.
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Affiliation(s)
- Wenming Shi
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong; School of Public Health and Health Policy, City University of New York, New York, NY, USA
| | - Gabriel M Leung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Jie V Zhao
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong.
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Shan Q, Liu J, Qu F, Chen A, He W. Polychlorinated biphenyls exposure and type 2 diabetes: Molecular mechanism that causes insulin resistance and islet damage. ENVIRONMENTAL TOXICOLOGY 2024; 39:2466-2476. [PMID: 38305644 DOI: 10.1002/tox.24094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 10/18/2023] [Accepted: 12/01/2023] [Indexed: 02/03/2024]
Abstract
Polychlorinated biphenyls (PCBs) are typical persistent organic pollutants that have been associated with type 2 diabetes (T2DM) in cohort studies. This review aims to comprehensively assess the molecular mechanisms of PCBs-induced T2DM. Recent progress has been made in the research of PCBs in liver tissue, adipose tissue, and other tissues. By influencing the function of nuclear receptors, such as the aryl hydrocarbon receptor (AhR), pregnancy X receptor (PXR), and peroxisome proliferator activated receptor γ (PPARγ), as well as the inflammatory response, PCBs disrupt the balance of hepatic glucose and lipid metabolism. This is associated with insulin resistance (IR) in the target organ of insulin. Through androgen receptor (AR), estrogen receptor α/β (ERα/β), and pancreato-duodenal-homeobox gene-1 (PDX-1), PCBs affect the secretion of insulin and increase blood glucose. Thus, this review is a discussion on the relationship between PCBs exposure and the pathogenesis of T2DM. It is hoped to provide basic concepts for diabetes research and disease treatment.
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Affiliation(s)
- Qiuli Shan
- College of Biological Science and Technology, University of Jinan, Jinan, China
| | - Jingyu Liu
- College of Biological Science and Technology, University of Jinan, Jinan, China
| | - Fan Qu
- College of Biological Science and Technology, University of Jinan, Jinan, China
| | - Anhui Chen
- Jiangsu Key Laboratory of Food Resource Development and Quality Safe, Xuzhou University of Technology, Xuzhou, China
| | - Wenxing He
- College of Biological Science and Technology, University of Jinan, Jinan, China
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Wang M, He Y, Zhao Y, Zhang L, Liu J, Zheng S, Bai Y. Exposure to PM 2.5 and its five constituents is associated with the incidence of type 2 diabetes mellitus: a prospective cohort study in northwest China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:34. [PMID: 38227152 DOI: 10.1007/s10653-023-01794-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 10/31/2023] [Indexed: 01/17/2024]
Abstract
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.
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Affiliation(s)
- Minzhen Wang
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Yingqian He
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Yanan Zhao
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Lulu Zhang
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Jing Liu
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Shan Zheng
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China.
| | - Yana Bai
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
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Jiang W, Chen H, Li H, Zhou Y, Xie M, Zhou C, Yang L. The Short-Term Effects and Burden of Ambient Air Pollution on Hospitalization for Type 2 Diabetes: Time-Stratified Case-Crossover Evidence From Sichuan, China. GEOHEALTH 2023; 7:e2023GH000846. [PMID: 38023385 PMCID: PMC10680437 DOI: 10.1029/2023gh000846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 10/22/2023] [Accepted: 11/02/2023] [Indexed: 12/01/2023]
Abstract
Type 2 diabetes mellitus (T2DM), a complicated metabolic disease, might be developed or exacerbated by air pollution, resulting in economic and health burden to patients. So far, limited studies have estimated associations between short-term exposure to air pollution and disease burden of T2DM in China. Hence, we aimed to estimate the associations and burden of ambient air pollutants (NO2, PM10, PM2.5, SO2, and CO) on hospital admissions (HAs) for T2DM using a time-stratified case-crossover design. Data on HAs for T2DM during 2017-2019 were collected from hospital electronic health records in nine cities in Sichuan Province using conditional poisson regression. Totally, 92,381 T2DM hospitalizations were recorded. There were significant short-term effects of NO2, PM10, PM2.5, SO2 and CO on HAs for T2DM. A 10 μg/m3 increment of NO2, PM10, PM2.5, SO2 and CO as linked with a 3.39% (95% CI: 2.26%, 4.54%), 0.33% (95% CI: 0.04%, 0.62%), 0.76% (95% CI: 0.35%, 1.16%), 12.68% (95% CI: 8.14%, 17.42%) and 79.00% (95% CI: 39.81%, 129.18%) increase in HAs for T2DM at lag 6. Stratified analyses modified by age, sex, and season showed old (≥65 years) and female patients linked with higher impacts. Using WHO's air quality guidelines of NO2, PM10, PM2.5, and CO as the reference, the attributable number of T2DM HAs exceeding these pollutants exposures were 786, 323, 793, and 2,127 during 2017-2019. Besides, the total medical costs of 25.83, 10.54, 30.74, and 67.78 million China Yuan were attributed to NO2, PM10, PM2.5, and CO. In conclusion, short-term exposures to air pollutants were associated with higher risks of HAs for T2DM.
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Affiliation(s)
- Wanyanhan Jiang
- School of Public HealthChengdu University of Traditional Chinese MedicineChengduSichuanChina
| | - Han Chen
- Sichuan Wanhao Consulting Co., LtdChengduSichuanChina
| | - Hongwei Li
- School of Public HealthChengdu University of Traditional Chinese MedicineChengduSichuanChina
| | - Yuelin Zhou
- School of Public HealthChengdu University of Traditional Chinese MedicineChengduSichuanChina
| | - Mengxue Xie
- School of Public HealthChengdu University of Traditional Chinese MedicineChengduSichuanChina
| | - Chengchao Zhou
- Centre for Health Management and Policy ResearchSchool of Public HealthCollege of MedicineShandong UniversityJinanChina
| | - Lian Yang
- School of Public HealthChengdu University of Traditional Chinese MedicineChengduSichuanChina
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Yang S, Hong F, Li S, Han X, Li J, Wang X, Chen L, Zhang X, Tan X, Xu J, Duoji Z, Ciren Z, Guo B, Zhang J, Zhao X. The association between chemical constituents of ambient fine particulate matter and obesity in adults: A large population-based cohort study. ENVIRONMENTAL RESEARCH 2023; 231:116228. [PMID: 37230219 DOI: 10.1016/j.envres.2023.116228] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 05/09/2023] [Accepted: 05/22/2023] [Indexed: 05/27/2023]
Abstract
OBJECTIVES Current evidence demonstrated that ambient fine particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) and its constituents may be obesogenic in children, but evidence from adults is lacking. Our aim was to characterize the association between PM2.5 and its constituents and obesity in adults. METHODS We included 68,914 participants from the China Multi-Ethnic Cohort (CMEC) baseline survey. Three-year average concentrations of PM2.5 and its constituents were evaluated by linking pollutant estimates to the geocoded residential addresses. Obesity was defined as body mass index (BMI) ≥ 28 kg/m2. Logistic regression was used to examine the relationship between PM2.5 and its constituents and obesity. We performed weighed quantile sum (WQS) regression to get the overall effect of PM2.5 and its constituents and the relative contribution of each constituent. RESULTS Per-SD increase in PM2.5 (odds ratio [OR] = 1.43, 95% confidence interval [CI]: 1.37-1.49), black carbon (BC) (1.42, 1.36-1.48), ammonium (1.43, 1.37-1.49), nitrate (1.44, 1.38-1.50), organic matter (OM) (1.45, 1.39-1.51), sulfate (1.42, 1.35-1.48), and soil particles (SOIL) (1.31, 1.27-1.36) were positively associated with obesity, and SS (0.60, 0.55-0.65) was negatively associated with obesity. The overall effect (OR = 1.34, 95% CI: 1.29-1.41) of the PM2.5 and its constituents was positively associated with obesity, and ammonium made the most contribution to this relationship. Participants who were older, female, never smoked, lived in urban areas, had lower income or higher levels of physical activity were more significantly adversely affected by PM2.5, BC, ammonium, nitrate, OM, sulfate and SOIL compared to other individuals. CONCLUSION Our study revealed that PM2.5 constituents except SS were positively associated with obesity, and ammonium played the most important role. These findings provided new evidence for public health interventions, especially the precise prevention and control of obesity.
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Affiliation(s)
- Shaokun Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Feng Hong
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Sicheng Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xinyu Han
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiawei Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xing Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Lin Chen
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xuehui Zhang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Xi Tan
- Wuhou District Center for Disease Control and Prevention, Chengdu, China
| | - Jingru Xu
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Zhuoma Duoji
- School of Medicine, Tibet University, Lhasa, China
| | - Zhuoga Ciren
- School of Medicine, Tibet University, Lhasa, China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
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Zhang Y, Wei J, Liu C, Cao W, Zhang Z, Li Y, Zeng Q, Sun S. Association between ambient PM 1 and semen quality: A cross-sectional study of 27,854 men in China. ENVIRONMENT INTERNATIONAL 2023; 175:107919. [PMID: 37104984 DOI: 10.1016/j.envint.2023.107919] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 03/17/2023] [Accepted: 04/03/2023] [Indexed: 05/22/2023]
Abstract
BACKGROUND Exposure to ambient fine and respirable particulate matter is associated with poor sperm quality, but evidence for particulate matter with an aerodynamic diameter ≤ 1 μm (PM1) is scarce. We aimed to estimate the association between PM1 exposure and sperm concentration, sperm count, sperm total motility, and sperm progressive motility in Chinese men. METHODS We conducted a cross-sectional study of 33,221 men attending an infertility clinic in Hubei, China, between 2014 and 2020. Daily concentrations of PM1 data were estimated from a validated spatiotemporal artificial intelligence model. We used multivariate linear regression to estimate the association between PM1 exposure and sperm parameters during the spermatogenesis period after adjusting for age, body mass index (BMI), education, ever having fathered a child, and season of semen collection. In addition, we performed stratified analysis to assess whether the association was varied by age, BMI, and educational attainment. RESULTS A total of 27,854 participants were included in the final analysis. An interquartile range (17.2 μg/m3) increase in PM1 during the entire period of semen development was associated with declined semen concentration [-4.39% (95% CI: -7.67%, -1.12%)] and sperm count [-23.56% (95% CI: -28.95%, -18.18%)], reduced total motility [-0.86% (95% CI: -1.66%, -0.06%)] and progressive motility [-2.22% (95% CI: -3.00%, -1.43%)]. The associations were homogeneous across subgroups defined by age and education, but were more pronounced among men with underweight for sperm concentration and sperm count. We identified a critical exposure window of 0-9 lag days, 10-14 lag days, and 70-90 lag days before semen collection for sperm count and progressive motility. CONCLUSIONS Among men attending an infertility clinic in China, exposure to PM1 was associated with poor semen quality, especially during the 70-90 days before ejaculation. These results suggest that exposure to PM1 might be a novel risk factor for impaired semen quality.
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Affiliation(s)
- Yangchang Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA
| | - Chong Liu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wangnan Cao
- Department of Social Medicine and Health Education, School of Public Health, Peking University, Beijing 100191, China
| | - Zhenyu Zhang
- Department of Global Health, Peking University School of Public Health, Beijing, China; Institute for Global Health and Development, Peking University, Beijing 100191, China
| | - Yufeng Li
- Reproductive Medicine Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095, Jiefang Avenue, Wuhan, Hubei, China.
| | - Qiang Zeng
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Shengzhi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China; School of Public Health, Guizhou Medical University, Guiyang 550025, China.
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Luo H, Liu C, Chen X, Lei J, Zhu Y, Zhou L, Gao Y, Meng X, Kan H, Xuan J, Chen R. Ambient air pollution and hospitalization for type 2 diabetes in China: A nationwide, individual-level case-crossover study. ENVIRONMENTAL RESEARCH 2023; 216:114596. [PMID: 36272593 DOI: 10.1016/j.envres.2022.114596] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 10/09/2022] [Accepted: 10/12/2022] [Indexed: 06/16/2023]
Abstract
Scarce evidence is available on the short-term association between air pollution and type 2 diabetes (T2D). We aimed to evaluate the associations between short-term exposure to six criteria air pollutants and hospitalization for T2D based on a national registry. We conducted an individual-level, time-stratified case-crossover study among inpatients with a primary diagnosis of T2D from 153 hospitals across 20 provincial regions in China (2013-2021). Daily concentrations of fine particulate matter (PM2.5), inhalable particle (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO), and ozone were collected from the nearest monitoring stations. T2D patients were separated into those admission for T2D with and without complications. Distributed lag non-linear models combined with conditional logistic regressions were used to estimate the associations. A total of 88,904 patients were hospitalized for T2D. Short-term exposures to all six air pollutants above except for ozone were significantly associated with the risk of hospitalization for T2D and both subclasses. An interquartile range increase in the concentrations of PM2.5, PM10, NO2, SO2, and CO at lag 0-2 d was associated with higher hospitalization risk of T2D by 1.71% (95%CI: 0.56%, 2.87%), 2.08% (0.88%, 3.29%), 4.85% (3.29%, 6.44%), 2.44% (1.22%, 3.67%) and 2.55% (1.24%, 3.88%), respectively. The associations of T2D hospitalizations were stronger in cold season than in warm season. Air pollutants had more acute and stronger associations with T2D with complications. The exposure-response relationship curves showed no thresholds, and the slopes were larger for T2D with complications. This nationwide individual-level, case-crossover study provides the first comprehensive evidence that short-term exposure to multiple criteria air pollutants may increase the risk of hospitalizations for T2D, especially for T2D with complications.
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Affiliation(s)
- Huihuan Luo
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Cong Liu
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Xiyin Chen
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jian Lei
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Yixiang Zhu
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Lu Zhou
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Ya Gao
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Xia Meng
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Haidong Kan
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Jianwei Xuan
- Health Economic Research Institute, School of Pharmacy, Sun Yat-Shen University, GuangZhou, 510275, China.
| | - Renjie Chen
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China.
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Li S, Guo B, Jiang Y, Wang X, Chen L, Wang X, Chen T, Yang L, Silang Y, Hong F, Yin J, Lin H, Zhao X. Long-term Exposure to Ambient PM2.5 and Its Components Associated With Diabetes: Evidence From a Large Population-Based Cohort From China. Diabetes Care 2023; 46:111-119. [PMID: 36383478 PMCID: PMC9918443 DOI: 10.2337/dc22-1585] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 10/19/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Association between particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5) components and diabetes remains unclear. We therefore aimed to investigate the associations of long-term exposure to PM2.5 components with diabetes. RESEARCH DESIGN AND METHODS This study included 69,210 adults with no history of diabetes from a large-scale epidemiologic survey in Southwest China from 2018 to 2019. The annual average concentrations of PM2.5 and its components were estimated using satellite remote sensing and chemical transport modeling. Diabetes was identified as fasting plasma glucose ≥7.0 mmol/L (126 mg/dL) or hemoglobin A1c ≥48 mmol/mol (6.5%). The logistic regression model and weighted quantile sum method were used to estimate the associations of single and joint exposure to PM2.5 and its components with diabetes, respectively. RESULTS Per-SD increases in the 3-year average concentrations of PM2.5 (odds ratio [OR] 1.08, 95% CI 1.01-1.15), black carbon (BC; 1.07, 1.01-1.15), ammonium (1.07, 1.00-1.14), nitrate (1.08, 1.01-1.16), organic matter (OM; 1.09, 1.02-1.16), and soil particles (SOIL; 1.09, 1.02-1.17) were positively associated with diabetes. The associations were stronger in those ≥65 years. Joint exposure to PM2.5 and its components was positively associated with diabetes (OR 1.04, 95% CI 1.01-1.07). The estimated weight of OM was the largest among PM2.5 and its components. CONCLUSIONS Long-term exposure to BC, nitrate, ammonium, OM, and SOIL is positively associated with diabetes. Moreover, OM might be the most responsible for the relationship between PM2.5 and diabetes. This study adds to the evidence of a PM2.5-diabetes association and suggests controlling sources of OM to curb the burden of PM2.5-related diabetes.
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Affiliation(s)
- Sicheng Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ye Jiang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xing Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lin Chen
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xue Wang
- Chenghua Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Ting Chen
- Chongqing Center for Disease Control and Prevention, Chongqing, China
| | - La Yang
- School of Medicine, Tibet University, Tibet, China
| | - Yangzong Silang
- Tibet Center for Disease Control and Prevention, Tibet, China
| | - Feng Hong
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guizhou, China
| | - Jianzhong Yin
- School of Public Health, Kunming Medical University, Yunnan, China
- Baoshan College of Traditional Chinese Medicine, Yunnan, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
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Chen M, Qin Q, Liu F, Wang Y, Wu C, Yan Y, Xiang H. How long-term air pollution and its metal constituents affect type 2 diabetes mellitus prevalence? Results from Wuhan Chronic Disease Cohort. ENVIRONMENTAL RESEARCH 2022; 212:113158. [PMID: 35351454 PMCID: PMC9227727 DOI: 10.1016/j.envres.2022.113158] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 02/20/2022] [Accepted: 03/18/2022] [Indexed: 05/07/2023]
Abstract
BACKGROUND Epidemiological evidence linking type 2 diabetes mellitus (T2DM) with air pollution is discrepant and most are restricted to the influences of air-pollutant mass concentration. This study aims to explore the effects of long-term exposure to air pollution and its metal constituents on T2DM prevalence in China. METHODS We used data on 10,253 adult residents from the baseline survey of Wuhan Chronic Disease Cohort in 2019. Ambient PM2.5, PM10 and NO2 exposure were estimated at residences based on Chinese Air Quality Reanalysis Dataset. Concentrations of 10 metal constituents were measured by 976 PM2.5 filter samples collected from four monitoring stations. Logistic regression models were employed to examine associations of T2DM prevalence with 3-year mean concentrations of each air pollutant and PM2.5 metal constituents prior to the baseline investigation. RESULTS A total of 673 T2DM cases (6.6%) were identified. The 3-year mean exposures to PM2.5, PM10 and NO2 were 50.89 μg/m3, 82.86 μg/m3, and 39.79 μg/m3, respectively. And interquartile range (IQR) of 10 metals in PM2.5 varied from 0.03 ng/m3 to 78.30 ng/m3. For 1 μg/m3 increment in PM2.5, PM10 and NO2, the odds of T2DM increased by 7.2% (95%CI: 1.026, 1.136), 3.1% (95%CI: 1.013, 1.050), and 2.1% (95%CI: 1.005, 1.038) after adjusting for potential confounders. Cd and Sb in PM2.5 were significant risk factors to T2DM with odds ratios of 1.350 (95%CI: 1.089, 1.673) and 1.389 (95%CI: 1.164, 1.658) for per IQR increase, respectively. Stratification analyses indicated that males and those aged ≥45 years were more susceptive to long-term air pollution. CONCLUSIONS Long-term exposure to PM2.5, PM10 and NO2 increased T2DM prevalence in a Wuhan population, especially for men and middle-aged and elderly people. Moreover, T2DM was significantly associated with Cd and Sb in PM2.5. Further research to validate these results and to clarify the underlying mechanisms is warranted.
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Affiliation(s)
- Meijin Chen
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Qiujun Qin
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Feifei Liu
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Yixuan Wang
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Chuangxin Wu
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Yaqiong Yan
- Wuhan Centers for Disease Control and Prevention, 288#Machang Road, Wuhan, China.
| | - Hao Xiang
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, Wuhan University, 115# Donghu Road, Wuhan, 430071, China.
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11
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Riches NO, Gouripeddi R, Payan-Medina A, Facelli JC. K-means cluster analysis of cooperative effects of CO, NO 2, O 3, PM 2.5, PM 10, and SO 2 on incidence of type 2 diabetes mellitus in the US. ENVIRONMENTAL RESEARCH 2022; 212:113259. [PMID: 35460634 PMCID: PMC9413686 DOI: 10.1016/j.envres.2022.113259] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 03/08/2022] [Accepted: 04/03/2022] [Indexed: 06/02/2023]
Abstract
Air pollution (AP) has been shown to increase the risk of type 2 diabetes mellitus, as well as other cardiometabolic diseases. AP is characterized by a complex mixture of components for which the composition depends on sources and metrological factors. The US Environmental Protection Agency (EPA) monitors and regulates certain components of air pollution known to have negative consequences for human health. Research assessing the health effects of these components of AP often uses traditional regression models, which might not capture more complex and interdependent relationships. Machine learning has the capability to simultaneously assess multiple components and find complex, non-linear patterns that may not be apparent and could not be modeled by other techniques. Here we use k-means clustering to assess the patterns associating PM2.5, PM10, CO, NO2, O3, and SO2 measurements and changes in annual diabetes incidence at a US county level. The average age adjusted annual decrease in diabetes incidence for the entire US populations is -0.25 per 1000 but the change shows a significant geographic variation (range: -17.2 to 5.30 per 1000). In this paper these variations were compared with the local daily AP concentrations of the pollutants listed above from 2005 to 2015, which were matched to the annual change in diabetes incidence for the following year. A total of 134,925 daily air quality observations were included in the cluster analysis, representing 125 US counties and the District of Columbia. K-means successfully clustered AP components and indicated an association between exposure to certain AP mixtures with lower decreases on T2D incidence.
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Affiliation(s)
- Naomi O Riches
- University of Utah School of Medicine, Department of Biomedical Informatics, 421 Wakara Way #140, Salt Lake City, UT, 84108, USA; University of Utah Center of Excellence in Exposure Health Informatics, 27 S. Mario Capecci Dr. Bldg 379, Salt Lake City, UT, 84133, USA.
| | - Ramkiran Gouripeddi
- University of Utah School of Medicine, Department of Biomedical Informatics, 421 Wakara Way #140, Salt Lake City, UT, 84108, USA; University of Utah Center for Clinical and Translational Science, 27 S. Mario Capecci Dr. Bldg 379, Salt Lake City, UT, 84133, USA; University of Utah Center of Excellence in Exposure Health Informatics, 27 S. Mario Capecci Dr. Bldg 379, Salt Lake City, UT, 84133, USA.
| | - Adriana Payan-Medina
- University of Utah School of Medicine, Department of Biomedical Informatics, 421 Wakara Way #140, Salt Lake City, UT, 84108, USA; University of Utah Center of Excellence in Exposure Health Informatics, 27 S. Mario Capecci Dr. Bldg 379, Salt Lake City, UT, 84133, USA; University of Utah Office of Undergraduate Research, Sill Center 005, Salt Lake City, UT, 84112, USA.
| | - Julio C Facelli
- University of Utah School of Medicine, Department of Biomedical Informatics, 421 Wakara Way #140, Salt Lake City, UT, 84108, USA; University of Utah Center for Clinical and Translational Science, 27 S. Mario Capecci Dr. Bldg 379, Salt Lake City, UT, 84133, USA; University of Utah Center of Excellence in Exposure Health Informatics, 27 S. Mario Capecci Dr. Bldg 379, Salt Lake City, UT, 84133, USA.
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12
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Tian Y, Fang J, Wang F, Luo Z, Zhao F, Zhang Y, Du P, Wang J, Li Y, Shi W, Liu Y, Ding E, Sun Q, Li C, Tang S, Yue X, Shi G, Wang B, Li T, Shen G, Shi X. Linking the Fasting Blood Glucose Level to Short-Term-Exposed Particulate Constituents and Pollution Sources: Results from a Multicenter Cross-Sectional Study in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:10172-10182. [PMID: 35770491 DOI: 10.1021/acs.est.1c08860] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Ambient PM2.5 (fine particulate matter with aerodynamic diameters ≤ 2.5 μm) is thought to be associated with the development of diabetes, but few studies traced the effects of PM2.5 components and pollution sources on the change in the fasting blood glucose (FBG). In the present study, we assessed the associations of PM2.5 constituents and their sources with the FBG in a general Chinese population aged over 40 years. Exposure to PM2.5 was positively associated with the FBG level, and each interquartile range (IQR) increase in a lag period of 30 days (18.4 μg/m3) showed the strongest association with an elevated FBG of 0.16 mmol/L (95% confidence interval: 0.04, 0.28). Among various constituents, increases in exposed elemental carbon, organic matter, arsenic, and heavy metals such as silver, cadmium, lead, and zinc were associated with higher FBG, whereas barium and chromium were associated with lower FBG levels. The elevated FBG level was closely associated with the PM2.5 from coal combustion, industrial sources, and vehicle emissions, while the association with secondary sources was statistically insignificant. Improving air quality by tracing back to the pollution sources would help to develop well-directed policies to protect human health.
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Affiliation(s)
- Yanlin Tian
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Feng Wang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Zhihan Luo
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Feng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Peng Du
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jiaonan Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yawei Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Wanying Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yuanyuan Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Enmin Ding
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Qinghua Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Chengcheng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xu Yue
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Guoliang Shi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Bin Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Guofeng Shen
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
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13
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Liu S, Tian H, Luo L, Bai X, Zhu C, Lin S, Zhao S, Zhang K, Hao J, Guo Z, Lv Y. Health impacts and spatiotemporal variations of fine particulate and its typical toxic constituents in five urban agglomerations of China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 806:151459. [PMID: 34742961 DOI: 10.1016/j.scitotenv.2021.151459] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 10/07/2021] [Accepted: 11/01/2021] [Indexed: 05/22/2023]
Abstract
Fine particulate matter (PM2.5) and its constituents pose great threatens to public health. The spatial-temporal characteristics of some key chemical constituents, such as sulfate, nitrate, and especially toxic trace elements in China has remained unclear, limiting further studies on evaluating the associated public health. Here, we conduct a two-yearlong (2012 and 2015) air quality simulation by coupling localized emission inventory for primary air pollutants and trace elements with a modified CMAQ model in a domain of China and five urban agglomerations. Associated health burdens of PM2.5 and various toxic trace elements are assessed applying exposure assessment models. The model successfully reproduces air pollution situations. Significant spatial-temporal variations of PM2.5 and chemical constituents are observed, with higher concentrations mainly occurred in North China Plain (NCP), Fenwei Plain (FWP) and Sichuan-Chongqing Basin (SCB). All chemical constituents in PM2.5 show higher concentrations in winter except for sulfate. From 2012 to 2015, the annual averaged PM2.5 concentration and its constituents decreased by 3% -20% nationally and regionally. Smaller reductions of nitrate make PM2.5 pollution become nitrate-dominated, especially in winter. Approximately 0.28 million deaths related to PM2.5 in China are avoided, while the population affected by the cancer risks of Cr (VI) and arsenic has slightly increased from 2012 to 2015. Our findings could provide critical insights on the mitigation of air pollution, as well as benefit for epidemiological studies on air pollutants related health effects.
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Affiliation(s)
- Shuhan Liu
- School of Environment, Beijing Normal University, Beijing 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Hezhong Tian
- School of Environment, Beijing Normal University, Beijing 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China.
| | - Lining Luo
- School of Environment, Beijing Normal University, Beijing 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Xiaoxuan Bai
- School of Environment, Beijing Normal University, Beijing 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Chuanyong Zhu
- College of Environmental Science and Engineering, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250353, China
| | - Shumin Lin
- School of Environment, Beijing Normal University, Beijing 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Shuang Zhao
- School of Environment, Beijing Normal University, Beijing 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Kai Zhang
- Department of Environmental Health Sciences School of Public Health University at Albany, State University of New York One University Place Rensselaer, NY 12144, United States of America
| | - Jiming Hao
- School of Environment, Tsinghua University, Beijing 100084, China
| | - Zhihui Guo
- School of Environment, Beijing Normal University, Beijing 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Yunqian Lv
- School of Environment, Beijing Normal University, Beijing 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
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14
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Wang Y, Xiao S, Zhang Y, Chang H, Martin RV, Van Donkelaar A, Gaskins A, Liu Y, Liu P, Shi L. Long-term exposure to PM 2.5 major components and mortality in the southeastern United States. ENVIRONMENT INTERNATIONAL 2022; 158:106969. [PMID: 34741960 PMCID: PMC9190768 DOI: 10.1016/j.envint.2021.106969] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 10/19/2021] [Accepted: 11/01/2021] [Indexed: 05/05/2023]
Abstract
BACKGROUND Long-term exposure to fine particulate matter (PM2.5) mass has been associated with adverse health effects. However, the health effects of PM2.5 components have been less studied. There is a pressing need to better understand the relative contribution of components of PM2.5, which can lay the scientific basis for designing effective policies and targeted interventions. METHODS We conducted a population-based cohort study, comprising all Medicare enrollees aged 65 or older in the southeastern United States from 2000 to 2016, to explore the associations between long-term exposure to PM2.5 major components and all-cause mortality among the elderly. Based on well-validated prediction models, we estimated ZIP code-level annual mean concentrations for five major PM2.5 components, including black carbon (BC), nitrate (NIT), organic matter (OM), sulfate (SO4), and soil particles. Data were analyzed using Cox proportional hazards models, adjusting for potential confounders. RESULTS The cohort comprised 13,590,387 Medicare enrollees and a total of 107,191,652 person-years. In single-component models, all five major PM2.5 components were significantly associated with elevated all-cause mortality. The hazard ratios (HR) per interquartile range (IQR) increase in exposure were 1.027 (95% CI: 1.025-1.030), 1.012 (95% CI: 1.010-1.013), 1.018 (95% CI: 1.017-1.020), 1.021 (95% CI: 1.017-1.024), and 1.004 (95% CI: 1.003-1.006) for BC, NIT, OM, SO4, and soil particles, respectively. While the effect estimate of soil component was statistically significant, it is much smaller than those of combustion-related components. CONCLUSION Our study provides epidemiological evidence that long-term exposure to major PM2.5 components is significantly associated with elevated mortality.
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Affiliation(s)
- Yifan Wang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Siyao Xiao
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Yuhan Zhang
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Howard Chang
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Randall V Martin
- Department of Energy, Environmental & Chemical Engineering, Washington University at St. Louis, MO, USA
| | - Aaron Van Donkelaar
- Department of Energy, Environmental & Chemical Engineering, Washington University at St. Louis, MO, USA; Department of Physics and Atmospheric Science, Dalhousie University, Halix, Nova Scotia, Canada
| | - Audrey Gaskins
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Yang Liu
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Pengfei Liu
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Liuhua Shi
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
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15
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Song L, Lei L, Jiang S, Pan K, Zeng X, Zhang J, Zhou J, Xie Y, Zhou L, Dong C, Zhao J. NLRP3 inflammasome is involved in ambient PM 2.5-related metabolic disorders in diabetic model mice but not in wild-type mice. Inhal Toxicol 2021; 33:260-267. [PMID: 34641747 DOI: 10.1080/08958378.2021.1980637] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
AIMS To explore the role of nucleotide-binding domain and leucine-rich repeat protein 3 (NLRP3) inflammasome in ambient fine particulate matter (PM2.5)-related metabolic disorders. METHODS In this study, the C57BL/6 and db/db mice were exposed to concentrated PM2.5 or filtered air (FA) using Shanghai Meteorological and Environmental Animal Exposure System (Shanghai-METAS) for 12 weeks. Indices of lipid metabolism, glucose metabolism, insulin sensitivity, and protein expression of NLRP3 inflammasome in visceral adipose tissue (VAT) were measured, respectively. RESULTS The results showed that PM2.5 exposure increased circulatory insulin, triglycerides (TG), and total cholesterol (TC), and decreased high-density lipoprotein (HDL) in both C57BL/6 and db/db mice. The levels of NLRP3-related circulatory inflammatory cytokines including both interleukin (IL)-18 and IL-1β in serum were increased in the PM2.5-exposed mice and accompanied by the elevation in fasting blood glucose and insulin. The results also showed that exposure to PM2.5 promoted the activation of NLRP3, pro-caspase-1, caspase-1, and apoptosis-associated speck-like protein containing CARD (ASC), simultaneously accompanied by the increase of IL-18 and IL-1β expression in VAT, but the statistically significant difference only found in the db/db mice, not in C57BL/6 mice. CONCLUSION The activation of NLRP3 inflammasome might be not the main mechanism of PM2.5-related metabolic disorders in wide type mice but it partly mediated the exacerbation of metabolic disorders in diabetic model mice.
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Affiliation(s)
- Liying Song
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
| | - Lei Lei
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
| | - Shuo Jiang
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China.,Shanghai Changning Center for Disease Control and Prevention, Shanghai, China
| | - Kun Pan
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
| | - Xuejiao Zeng
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
| | - Jia Zhang
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China
| | - Ji Zhou
- Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai, China
| | - Yuquan Xie
- Department of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Li Zhou
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, China
| | - Chen Dong
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Jinzhuo Zhao
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China.,Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.,IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
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16
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Yu G, Chen Y, Tang J, Lin Z, Zheng F, Zheng C, Zhou J, Su Q, Wu S, Li H. Meta-analyses of maternal exposure to atmospheric particulate matter and risk of congenital anomalies in offspring. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:55869-55887. [PMID: 34491504 DOI: 10.1007/s11356-021-16200-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 08/24/2021] [Indexed: 06/13/2023]
Abstract
Congenital anomalies are the main causes of infant death and disability. Previous studies have suggested that maternal exposure to particulate matter is related to congenital malformation. However, the conclusions of this study remain controversial. Hence, meta-analyses were performed to assess the relationship between maternal exposure to particulate matter and the risk of congenital anomalies. The Medline, Embase, and Web of Science databases were systemically searched from inception until August 2020 to find articles related to birth defects and particulate matter. The pooled risk estimated for the combination of pollution outcomes was calculated for each study by performing fixed effects or random effects models. The existence of heterogeneity and publication bias in relevant studies was also examined. Thirty studies were included in the analysis. A statistically increased summary risk valuation was found. PM10 exposure was associated with an increased risk of congenital heart disease, neural tube defects, and cleft lip with or without cleft palate (OR per 10 μg/m3 = 1.05, 95% CI, 1.03-1.07; OR per 10 μg/m3 = 1.04, 95% CI, 1.01-1.06; OR per 10 μg/m3 = 1.03, 95% CI, 1.01-1.06). Maternal exposure to particulate matter might be associated with an increased risk of congenital anomalies. Our results indicate the dangers of particulate matter exposure on fetal development and the importance of protection against exposure to such particles during pregnancy. The schematic representation of the association between maternal exposure to PM2.5/PM10 and congenital anomalies in offspring, and geographic distribution of the included reports in the meta-analyses.
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Affiliation(s)
- Guangxia Yu
- Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, China
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, 350122, China
- Key Lab of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Yao Chen
- Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, China
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, 350122, China
| | - Jianping Tang
- Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, China
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, 350122, China
| | - Zhifeng Lin
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, 350122, China
| | - Fuli Zheng
- Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, China
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, 350122, China
- Key Lab of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Chunyan Zheng
- Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, China
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, 350122, China
| | - Jinfu Zhou
- Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, China
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, 350122, China
- Key Lab of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qianqian Su
- Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, China
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, 350122, China
| | - Siying Wu
- Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, China.
- Key Lab of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China.
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, 350122, China.
| | - Huangyuan Li
- Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, China.
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou, 350122, China.
- Key Lab of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China.
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Yu G, Ao J, Cai J, Luo Z, Martin R, Donkelaar AV, Kan H, Zhang J. Fine particular matter and its constituents in air pollution and gestational diabetes mellitus. ENVIRONMENT INTERNATIONAL 2020; 142:105880. [PMID: 32593838 DOI: 10.1016/j.envint.2020.105880] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 06/01/2020] [Accepted: 06/05/2020] [Indexed: 05/06/2023]
Abstract
BACKGROUND Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, previous studies provided inconsistent findings and no study has examined the effects of complex chemical constituents of the particular matter on GDM, especially in developing countries. Therefore, we aim to investigate the associations of exposure to PM2.5 (particular matter ≤ 2.5 μm) and its constituents with GDM, and to identify susceptible exposure window in a large survey in China. METHODS The China Labor and Delivery Survey was a cross-sectional investigation conducted in 24 provinces in China between 2015 and 2016. A random sample of all deliveries in each participating hospital was selected and detailed obstetric and newborn information was extracted from medical records. Average concentrations of PM2.5 and six constituents (organic matter, black carbon, sulfate, nitrate, ammonium and soil dust) were estimated (1 km × 1 km) using a combined geoscience-statistical model. GDM was diagnosed based on an oral glucose tolerance test (OGTT) between 24 to 28 weeks of gestation and according to IADPSG criteria. Generalized linear mixed models were used to adjust for potential confounders. RESULTS A total of 54,517 subjects from 55 hospitals were included. The incidence of GDM was 10.8%. An interquartile range (IQR) increase in PM2.5 exposure in the 2nd trimester of pregnancy was associated with an increased GDM risk in the single pollutant model, [adjusted odds ratio (aOR) = 1.11 and 95% confidence interval (CI): 1.01-1.22]. Exposure to organic matter (aOR = 1.14; 95%CI: 1.05-1.23), black carbon (aOR = 1.15; 95%CI: 1.07-1.25) and nitrate (aOR = 1.13; 95%CI: 1.02-1.24) during 2nd trimester were associated with increased risks of GDM. Associations between constituents and GDM were robust after controlling for total PM2.5 mass and accounting for multi-collinearity. CONCLUSIONS Exposure to PM2.5 in 2nd trimester of pregnancy was associated with an increased risk of GDM. Organic matter, black carbon and nitrate may be the main culprits for the association.
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Affiliation(s)
- Guoqi Yu
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200092, China
| | - Junjie Ao
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200092, China
| | - Jing Cai
- School of Public Health, Fudan University, Shanghai 200032, China
| | - Zhongcheng Luo
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200092, China
| | - Randall Martin
- Department of Physics and Atmospheric Science, Dalhousie University, 6300 Coburg Road, Halifax, Nova Scotia B3H 3J5, Canada
| | - Aaron van Donkelaar
- Department of Physics and Atmospheric Science, Dalhousie University, 6300 Coburg Road, Halifax, Nova Scotia B3H 3J5, Canada
| | - Haidong Kan
- School of Public Health, Fudan University, Shanghai 200032, China.
| | - Jun Zhang
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai 200092, China; School of Public Health, Shanghai Jiao-Tong University School of Medicine, Shanghai 200025, China.
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18
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Viher Hrženjak V, Kukec A, Eržen I, Stanimirović D. Effects of Ultrafine Particles in Ambient Air on Primary Health Care Consultations for Diabetes in Children and Elderly Population in Ljubljana, Slovenia: A 5-Year Time-Trend Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17144970. [PMID: 32664229 PMCID: PMC7400531 DOI: 10.3390/ijerph17144970] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 06/26/2020] [Accepted: 07/08/2020] [Indexed: 11/16/2022]
Abstract
Epidemiological studies indicate that exposure to ultrafine particles (UFP) in ambient air represents an important environmental public health issue. The aim of this study was to determine the association between UFP in ambient air and the daily number of consultations in the primary health care unit due to diabetes mellitus in children and elderly population of the Municipality of Ljubljana. A 5-year time-trend ecological study was carried out for the period between 1 January 2013 and 31 December 2017. The daily number of primary health care consultations due to diabetes mellitus among children and elderly population was observed as the health outcome. Daily mean UFP concentrations (different size from 10 to 100 nm) were measured and calculated. Poisson regression analysis was used to investigate the association between the observed outcome and the daily UFP, particulate matter fine fraction (PM2.5), and particulate matter coarse fraction (PM10) concentrations, adjusted to other covariates. The results show that the daily number of consultations due to diabetes mellitus were highly significantly associated with the daily concentrations of UFP (10 to 20 nm; p ≤ 0.001 and 20 to 30 nm; p ≤ 0.001) in all age groups and in the elderly population. In observed the population of children, we did not confirm the association. Findings indicate that specified environmental challenges should be addressed by comprehensive public health strategies leading to the coordinated cross-sectoral measures for the reduction of UFP in ambient air and the mitigation of adverse health effects.
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Affiliation(s)
- Vesna Viher Hrženjak
- National Laboratory of Health, Environment and Food, Prvomajska 1, 2000 Maribor, Slovenia;
| | - Andreja Kukec
- Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia; (A.K.); (I.E.)
- National Institute of Public Health, Trubarjeva 2, 1000 Ljubljana, Slovenia
| | - Ivan Eržen
- Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia; (A.K.); (I.E.)
- National Institute of Public Health, Trubarjeva 2, 1000 Ljubljana, Slovenia
| | - Dalibor Stanimirović
- National Institute of Public Health, Trubarjeva 2, 1000 Ljubljana, Slovenia
- Correspondence: ; Tel.: +386-1244-1413
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Mason TG, Mary Schooling C, Ran J, Chan KP, Tian L. Does the AQHI reduce cardiovascular hospitalization in Hong Kong's elderly population? ENVIRONMENT INTERNATIONAL 2020; 135:105344. [PMID: 31801101 DOI: 10.1016/j.envint.2019.105344] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 10/31/2019] [Accepted: 11/17/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Air quality alert programs have been introduced around the world to reduce the short term effects of air pollution on health. Hong Kong, a densely populated city in southern China with high levels of air pollution, introduced its first air quality health index (AQHI) on December 30th 2013. However, whether air quality alert program warnings, such as the AQHI, reduces morbidity is uncertain. Using a quasi-experimental design, we conducted the first evaluation of the AQHI in Hong Kong, focusing on cardiovascular morbidity in Hong Kong's elderly population. METHOD Interrupted time series with Poisson segmented regression from 2010 to 2016 was used to detect any sudden or gradual changes in emergency hospital admissions for cardiovascular diseases (CVD), after the AQHI policy was implemented. To account for potential confounders, models were adjusted for air pollutants (NO2, SO2, PM10, O3), temperature and humidity. The findings were validated using a negative control and three false policy periods. We also assessed effects on specific subtypes of CVD (hypertensive disease (HPD), acute myocardial infarction (AMI), heart failure, stroke and other CVD) and by sex. RESULTS From January 1st 2010 to December 31st, 2016, 375,672 hospital admissions for CVD occurred in Hong Kong's elderly population. Immediately after the policy HPD and AMI dropped by16% (relative risk (RR) 0.84, 95% confidence interval (CI): 0.78-0.91) and 15% (RR 0.85, 95% CI: (0.76-0.97)) respectively. There was no significant change for all CVD or other sub-types and no differences by sex. CONCLUSION Hong Kong's AQHI helped reduced hospital admissions in the elderly for HPD and AMI but had no effect on overall emergency hospitalization for CVD. To maximize health benefits of the policy, at risk groups need to be able to follow the behavioral changes recommended by the AQHI warnings.
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Affiliation(s)
- Tonya G Mason
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
| | - JinJun Ran
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region
| | - King-Pan Chan
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region
| | - Linwei Tian
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
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20
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Sun S, Cao W, Pun VC, Qiu H, Ge Y, Tian L. Respirable Particulate Constituents and Risk of Cause-Specific Mortality in the Hong Kong Population. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:9810-9817. [PMID: 31361948 DOI: 10.1021/acs.est.9b01635] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Emerging studies examined the associations of particulate matter constituents with nonaccidental and cardiorespiratory diseases, but few have investigated more specific causes of cardiorespiratory diseases or other system diseases, especially in Asia. We estimated the association between respirable particulate matter (PM10) constituents and a spectrum of deaths using a quasi-Poisson time-series model in Hong Kong. Positive associations were identified between cause-specific deaths and elemental carbon, organic carbon (OC), nitrate, and potassium ion (K+), but only the associations for OC and K+ were robust in the two-constituent models adjusting for other constituents. The estimated effects of OC were strongest on mortality from the respiratory system with cumulative percent excess risk (ER%) of 3.82% (95% CI: 0.96%, 6.92%) per interquartile range (6.7 μg/m3) increase over 7 days prior to death (lag0-7), especially for pneumonia (ER%: 4.32%; 95% CI: 0.70%, 8.26%). The digestive system was most sensitive to K+ with cumulative ER% of 6.74% (95% CI: 0.37%, 14.01%) per interquartile range (0.6 μg/m3) increase. This study indicates that PM10 constituents from biomass burning (OC and K+) were more toxic than other constituents for deaths in Hong Kong, especially for mortalities from respiratory and digestive systems. These findings should have potential biological and pollution control implications.
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Affiliation(s)
- Shengzhi Sun
- School of Public Health , The University of Hong Kong , Hong Kong SAR , P. R. China
- Department of Epidemiology , Brown University School of Public Health , Providence , Rhode Island 02912 , United States
| | - Wangnan Cao
- Center for Evidence Synthesis in Health, School of Public Health , Brown University , Providence , Rhode Island 02912 , United States
| | - Vivian C Pun
- Jockey Club School of Public Health and Primary Care , The Chinese University of Hong Kong , Hong Kong SAR , P. R. China
| | - Hong Qiu
- School of Public Health , The University of Hong Kong , Hong Kong SAR , P. R. China
| | - Yang Ge
- School of Public Health, Department of Epidemiology and Biostatistics , University of Georgia , Athens , Georgia 30606 , United States
| | - Linwei Tian
- School of Public Health , The University of Hong Kong , Hong Kong SAR , P. R. China
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Li H, Duan D, Xu J, Feng X, Astell-Burt T, He T, Xu G, Zhao J, Zhang L, You D, Han L. Ambient air pollution and risk of type 2 diabetes in the Chinese. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2019; 26:16261-16273. [PMID: 30977004 DOI: 10.1007/s11356-019-04971-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2018] [Accepted: 03/22/2019] [Indexed: 06/09/2023]
Abstract
We performed a time series analysis to investigate the potential association between exposure to ambient air pollution and type 2 diabetes (T2D) incidence in the Chinese population. Monthly time series data between 2008 and 2015 on ambient air pollutants and incident T2D (N = 25,130) were obtained from the Environment Monitoring Center of Ningbo and the Chronic Disease Surveillance System of Ningbo. Relative risks (RRs) and 95% confidence intervals (95% CIs) of incident T2D per 10 μg/m3 increases in ambient air pollutants were estimated from Poisson generalized additive models. Exposure to particulate matter < 10 μm (PM10) and sulfur dioxide (SO2) was associated with increased T2D incidence. The relative risks (RRs) of each increment in 10 μg/m3 of PM10 and SO2 were 1.62 (95% CI, 1.16-2.28) and 1.63 (95% CI, 1.12-2.38) for overall participants, whereas for ozone (O3) exposure, the RRs were 0.78 (95% CI, 0.68-0.90) for overall participants, 0.78 (95% CI, 0.69-0.90) for males, and 0.78 (95% CI, 0.67-0.91) for females, respectively. Exposure to PM10 and SO2 is positively associated with T2D incidence, whereas O3 is negatively associated with T2D incidence.
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Affiliation(s)
- Hui Li
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo, 315010, China
| | - Donghui Duan
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo, 315010, China
| | - Jiaying Xu
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Xiaoqi Feng
- Population Wellbeing and Environment Research Lab (Power Lab), Faculty of Social Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
- Early Start, Faculty of Social Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
- Menzies Centre for Health Policy, University of Sydney, Sydney, NSW, 2006, Australia
| | - Thomas Astell-Burt
- Population Wellbeing and Environment Research Lab (Power Lab), Faculty of Social Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
- Early Start, Faculty of Social Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
- Menzies Centre for Health Policy, University of Sydney, Sydney, NSW, 2006, Australia
| | - Tianfeng He
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo, 315010, China
| | - Guodong Xu
- Department of Preventive Medicine, Medical School of Ningbo University, Ningbo, 315211, China
| | - Jinshun Zhao
- Department of Preventive Medicine, Medical School of Ningbo University, Ningbo, 315211, China
| | - Lina Zhang
- Department of Preventive Medicine, Medical School of Ningbo University, Ningbo, 315211, China
| | - Dingyun You
- School of Public Health, Kunming Medical University, Kunming, China.
| | - Liyuan Han
- Department of Preventive Medicine, Medical School of Ningbo University, Ningbo, 315211, China
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22
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Yang Y, Ruan Z, Wang X, Yang Y, Mason TG, Lin H, Tian L. Short-term and long-term exposures to fine particulate matter constituents and health: A systematic review and meta-analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2019; 247:874-882. [PMID: 30731313 DOI: 10.1016/j.envpol.2018.12.060] [Citation(s) in RCA: 182] [Impact Index Per Article: 36.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 12/17/2018] [Accepted: 12/18/2018] [Indexed: 05/04/2023]
Abstract
BACKGROUND Fine particulate matter (Particulate matter with diameter ≤ 2.5 μm) is associated with multiple health outcomes, with varying effects across seasons and locations. It remains largely unknown that which components of PM2.5 are most harmful to human health. METHODS We systematically searched all the relevent studies published before August 1, 2018, on the associations of fine particulate matter constituents with mortality and morbidity, using Web of Science, MEDLINE, PubMed and EMBASE. Studies were included if they explored the associations between short term or long term exposure of fine particulate matter constituents and natural, cardiovascular or respiratory health endpoints. The criteria for the risk of bias was adapted from OHAT and New Castle Ottawa. We applied a random-effects model to derive the risk estimates for each constituent. We performed main analyses restricted to studies which adjusted the PM2.5 mass in their models. RESULTS Significant associations were observed between several PM2.5 constituents and different health endpoints. Among them, black carbon and organic carbon were most robustly and consistently associated with all natural, cardiovascular mortality and morbidity. Other potential toxic constituents including nitrate, sulfate, Zinc, silicon, iron, nickel, vanadium, and potassium were associated with adverse cardiovascular health, while nitrate, sulfate and vanadium were relevant for adverse respiratory health outcomes. CONCLUSIONS Our analysis suggests that black carbon and organic carbon are important detrimental components of PM2.5, while other constituents are probably hazardous to human health. However, more studies are needed to further confirm our results.
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Affiliation(s)
- Yang Yang
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Zengliang Ruan
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xiaojie Wang
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yin Yang
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Tonya G Mason
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Hualiang Lin
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Linwei Tian
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
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Li Y, Xu L, Shan Z, Teng W, Han C. Association between air pollution and type 2 diabetes: an updated review of the literature. Ther Adv Endocrinol Metab 2019; 10:2042018819897046. [PMID: 31903180 PMCID: PMC6931138 DOI: 10.1177/2042018819897046] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Accepted: 12/02/2019] [Indexed: 01/11/2023] Open
Abstract
Air pollution and type 2 diabetes mellitus (T2DM) are critical public health issues worldwide. A large number of epidemiological studies have highlighted the adverse effects of air pollution on diabetes, and include risk profiles for different exposure durations, study design types, subgroup populations, and effects of air pollution components. We researched PubMed, Google Scholar, and Web of Science to identify studies on the association between air pollution and T2DM from January 2009 to January 2019. The aim of this review is to provide a brief overview of epidemiological and experimental studies on air pollution associated with T2DM from the latest research, which may provide practical information about this relationship and possible mechanisms. Current cumulative evidence appears to suggest that T2DM-related biomarkers increase with increasing exposure duration and concentration of air pollutants. The chemical constituents of the air pollutant mixture may affect T2DM to varying degrees. The suggested mechanisms whereby air pollutants induce T2DM include increased inflammation, oxidative stress, and endoplasmic reticulum stress.
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Affiliation(s)
- Yongze Li
- Department of Endocrinology and Metabolism, Key
Laboratory of Thyroid Disease in Liaoning Provinces, The First Hospital of
China Medical University, Shenyang, China
| | - Lu Xu
- Department of Oncology, Affiliated Zhongshan
Hospital of Dalian University, Dalian, China
| | - Zhongyan Shan
- Department of Endocrinology and Metabolism, Key
Laboratory of Thyroid Disease in Liaoning Provinces, The First Hospital of
China Medical University, Shenyang, China
| | - Weiping Teng
- Department of Endocrinology and Metabolism, Key
Laboratory of Thyroid Disease in Liaoning Province, The First Hospital of
China Medical University, Shenyang, Liaoning, 110001, PRC
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Yang Y, Guo Y, Qian ZM, Ruan Z, Zheng Y, Woodward A, Ai S, Howard SW, Vaughn MG, Ma W, Wu F, Lin H. Ambient fine particulate pollution associated with diabetes mellitus among the elderly aged 50 years and older in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2018; 243:815-823. [PMID: 30243190 DOI: 10.1016/j.envpol.2018.09.056] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 08/29/2018] [Accepted: 09/10/2018] [Indexed: 06/08/2023]
Abstract
The linkage between ambient air pollution exposure and occurrence of diabetes mellitus is not well defined. This study examined the association between exposure to fine particles (PM2.5) and the prevalence of diabetes among Chinese elderly people. We surveyed 11,504 adults aged ≥50 years in China, estimated the annual concentrations of ambient PM2.5 using a satellite-based model of aerosol optical depth information. We employed a generalized mixed effects model to examine the association between PM2.5 and the prevalence of diabetes and explored potential effect modifiers. We estimated diabetes burden attributable to ambient PM2.5 if the observed association is indeed causal. The diabetes prevalence among the participants was 6.5% (n = 745). Our analysis found a statistically significant association between PM2.5 and diabetes. The adjusted odds ratio was 1.27 (95% confidence interval (CI), 1.12, 1.43) for each 10 μg/m3 increment in ambient PM2.5. Stratified analyses found a lower association among the participants with higher consumption of fruit. We estimated that 22.02% (95% CI: 8.59%, 43.29%) of the diabetes cases could be ascribable to ambient PM2.5. Our finding suggests that PM2.5 exposures could increase the risk of diabetes, and if causal, could be responsible for substantial burden of diabetes among the Chinese elderly; and higher intakes of fruit might reduce the harmful effects of PM2.5, however, due to the limitation of the cross-sectional study design, more studies are warranted to confirm this observation.
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Affiliation(s)
- Yin Yang
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yanfei Guo
- Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, China
| | - Zhengmin Min Qian
- College for Public Health & Social Justice, Saint Louis University, St. Louis, Missouri, USA
| | - Zengliang Ruan
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yang Zheng
- Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, China
| | - Alistair Woodward
- School of Population Health, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand
| | - Siqi Ai
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Steven W Howard
- College for Public Health & Social Justice, Saint Louis University, St. Louis, Missouri, USA
| | - Michael G Vaughn
- College for Public Health & Social Justice, Saint Louis University, St. Louis, Missouri, USA
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Fan Wu
- Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, China.
| | - Hualiang Lin
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
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Kim H, Kim W, Choi JE, Kim C, Sohn J. Short-term Effect of Ambient Air Pollution on Emergency Department Visits for Diabetic Coma in Seoul, Korea. J Prev Med Public Health 2018; 51:265-274. [PMID: 30514056 PMCID: PMC6283743 DOI: 10.3961/jpmph.18.153] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Accepted: 10/05/2018] [Indexed: 12/23/2022] Open
Abstract
Objectives A positive association between air pollution and both the incidence and prevalence of diabetes mellitus (DM) has been reported in some epidemiologic and animal studies, but little research has evaluated the relationship between air pollution and diabetic coma. Diabetic coma is an acute complication of DM caused by diabetic ketoacidosis or hyperosmolar hyperglycemic state, which is characterized by extreme hyperglycemia accompanied by coma. We conducted a time-series study with a generalized additive model using a distributed-lag non-linear model to assess the association between ambient air pollution (particulate matter less than 10 μm in aerodynamic diameter, nitrogen dioxide [NO2], sulfur dioxide, carbon monoxide, and ozone) and emergency department (ED) visits for DM with coma in Seoul, Korea from 2005 to 2009. Methods The ED data and medical records from the 3 years previous to each diabetic coma event were obtained from the Health Insurance Review and Assessment Service to examine the relationship with air pollutants. Results Overall, the adjusted relative risks (RRs) for an interquartile range (IQR) increment of NO2 was statistically significant at lag 1 (RR, 1.125; 95% confidence interval [CI], 1.039 to 1.219) in a single-lag model and both lag 0-1 (RR, 1.120; 95% CI, 1.028 to 1.219) and lag 0-3 (RR, 1.092; 95% CI, 1.005 to 1.186) in a cumulative-lag model. In a subgroup analysis, significant positive RRs were found for females for per-IQR increments of NO2 at cumulative lag 0-3 (RR, 1.149; 95% CI, 1.022 to 1.291). Conclusions The results of our study suggest that ambient air pollution, specifically NO2, is associated with ED visits for diabetic coma.
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Affiliation(s)
- Hyunmee Kim
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Woojin Kim
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Jee Eun Choi
- Department of Public Health, Yonsei University Graduate School, Seoul, Korea
| | - Changsoo Kim
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea.,Department of Public Health, Yonsei University Graduate School, Seoul, Korea.,Institute of Human Complexity and Systems Science, Yonsei University, Incheon, Korea
| | - Jungwoo Sohn
- Institute of Human Complexity and Systems Science, Yonsei University, Incheon, Korea
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Hu LW, Lawrence WR, Liu Y, Yang BY, Zeng XW, Chen W, Dong GH. Ambient Air Pollution and Morbidity in Chinese. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 1017:123-151. [PMID: 29177961 DOI: 10.1007/978-981-10-5657-4_6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The rapid economic growth in China is coupled with a severe ambient air pollution, which poses a huge threat to human health and the sustainable development of social economy. The rapid urbanization and industrialization over the last three decades have placed China as one of countries with the greatest disease burden in world. Notably, the prevalence rate of chronic noncommunicable diseases (CND), including respiratory diseases, CVD, and stroke, in 2010 reaches 16.9%. The continuous growth of the incidence of CND urgent needs for effective regulatory action for health protection. This study aims to evaluate the impact of rapid urbanization on status of ambient air pollution and associated adverse health effects on the incidence and the burden of CND and risk assessment. Our findings would be greatly significant in the prediction of the risk of ambient air pollution on CND and for evidence-based policy making and risk management in China.
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Affiliation(s)
- Li-Wen Hu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, 510080, Guangdong, China
| | - Wayne R Lawrence
- Department of Epidemiology and Biostatistics, School of Public Health, State University of New York, Albany, NY, 12144-3445, USA
| | - Yimin Liu
- Laboratory of Occupational Environment and Health Effects, Guangzhou Key Medical Discipline of Occupational Health Guardianship, Guangzhou Prevention and Treatment Center for Occupational Diseases, Guangzhou Twelfth People's Hospital, Guangzhou, 510620, China
| | - Bo-Yi Yang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, 510080, Guangdong, China
| | - Xiao-Wen Zeng
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, 510080, Guangdong, China
| | - Wen Chen
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, 510080, Guangdong, China
| | - Guang-Hui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, 510080, Guangdong, China.
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Tian L, Sun S. Comparison of Health Impact of Air Pollution Between China and Other Countries. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 1017:215-232. [PMID: 29177964 DOI: 10.1007/978-981-10-5657-4_9] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Air pollution is the world's largest single environmental risk according to the World Health Organization (WHO), which caused around seven million deaths in 2012. Extensive epidemiological studies have been carried out worldwide to examine the health impacts of ambient air pollution, consistently demonstrating significant health impacts of ambient air pollution. Air pollution problem in China is especially serious; it has become the fourth biggest threat to the health of the Chinese people. In this review, we summarized existing literature, compared health impact of air pollution between China and other countries, and found substantial heterogeneity in the risk estimates of air pollution. The effect heterogeneities may be due to the differences in the characteristics of populations (e.g., the proportion of the elder population and people with preexisting diseases), exposure profile (e.g., air pollution concentrations and composition), and regional climate. Although the magnitude of relative risk estimates of air pollution is generally similar with that in other parts of the world, air pollution is one of China's most serious environmental health problems given the huge number of people exposed to high concentration levels of air pollution in China.
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Affiliation(s)
- Linwei Tian
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
| | - Shengzhi Sun
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
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