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Zhang J, Tao Y, Wang Y, Ji X, Wu Y, Zhang F, Wang Z. Independent and interaction effects of prenatal exposure to high AQI and extreme Humidex on the risk of preterm birth: A large sample population study in northern China. Reprod Toxicol 2024; 124:108544. [PMID: 38246475 DOI: 10.1016/j.reprotox.2024.108544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 12/29/2023] [Accepted: 01/17/2024] [Indexed: 01/23/2024]
Abstract
The combined effects of air pollution and extreme temperature on PTB remain unclear. To evaluate the independent effect and interaction effect of prenatal extreme exposure to air quality index (AQI) and Humidex, on PTB. Based on the National Health Care Data Platform of Shandong University, women who gave birth in 2019-2020 were selected for the study. First, the independent effects of AQI and Humidex on PTB were assessed by logistic regression model. Subsequently, the interaction effects of AQI and Humidex on PTB were estimated separately by calculation of the relative excess risk of interaction (RERI). A total of 34365 pregnant women were included and 1975 subjects were diagnosed with PTB. We observed a significant increase in the odds of PTB associated with maternal high AQI exposure, with an OR of 1.70 (95% CI: 1.59, 1.81). Similarly, extreme exposure to Humidex also demonstrated an elevated PTB odds, with a low Humidex OR of 2.48 (95% CI: 2.23, 2.76) and a high Humidex OR of 1.48 (95% CI: 1.31, 1.67). Finally, we observed an interaction between high AQI and extreme Humidex during the 1st trimester. Interaction effects were noted between high AQI and low Humidex throughout the entire trimester and the 2nd trimester. This study suggests that prenatal exposure to high AQI and extreme Humidex could increase the odds of PTB, with effects exhibiting the sensitivity window and a cumulative trend. Additionally, there is an interaction between AQI and Humidex.
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Affiliation(s)
- Jiatao Zhang
- Department of Occupational and Environmental Health, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, PR China
| | - Yu Tao
- Department of Occupational and Environmental Health, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, PR China
| | - Yongchao Wang
- Institute for Medical Dataology, Shandong University, Shandong, PR China
| | - Xiaokang Ji
- Institute for Medical Dataology, Shandong University, Shandong, PR China
| | - Yanling Wu
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, PR China
| | - Fengmei Zhang
- Department of Occupational and Environmental Health, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, PR China.
| | - Zhiping Wang
- Department of Occupational and Environmental Health, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, PR China; Institute for Medical Dataology, Shandong University, Shandong, PR China.
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Xue T, Wang R, Wang M, Wang Y, Tong D, Meng X, Huang C, Ai S, Li F, Cao J, Tong M, Ni X, Liu H, Deng J, Lu H, Wan W, Gong J, Zhang S, Zhu T. Health benefits from the rapid reduction in ambient exposure to air pollutants after China's clean air actions: progress in efficacy and geographic equality. Natl Sci Rev 2024; 11:nwad263. [PMID: 38213522 PMCID: PMC10776362 DOI: 10.1093/nsr/nwad263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 09/13/2023] [Accepted: 10/08/2023] [Indexed: 01/13/2024] Open
Abstract
Clean air actions (CAAs) in China have been linked to considerable benefits in public health. However, whether the beneficial effects of CAAs are equally distributed geographically is unknown. Using high-resolution maps of the distributions of major air pollutants (fine particulate matter [PM2.5] and ozone [O3]) and population, we aimed to track spatiotemporal changes in health impacts from, and geographic inequality embedded in, the reduced exposures to PM2.5 and O3 from 2013 to 2020. We used a method established by the Global Burden of Diseases Study. By analyzing the changes in loss of life expectancy (LLE) attributable to PM2.5 and O3, we calculated the gain of life expectancy (GLE) to quantify the health benefits of the air-quality improvement. Finally, we assessed the geographic inequality embedded in the GLE using the Gini index (GI). Based on risk assessments of PM2.5 and O3, during the first stage of CAAs (2013 to 2017), the mean GLE was 1.87 months. Half of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed (GI 0.44). During the second stage of CAAs (2017 to 2020), the mean GLE increased to 3.94 months and geographic inequality decreased (GI 0.18). According to our assessments, CAAs were enhanced, from the first to second stages, in terms of not only preventing premature mortality but also ameliorating health inequalities. The enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM2.5 and O3 levels. Our findings will contribute to optimizing future CAAs.
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Affiliation(s)
- Tao Xue
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
- Advanced Institute of Information Technology, Peking University, Hangzhou311215, China
| | - Ruohan Wang
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY14214, USA
| | - Yanying Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
| | - Dan Tong
- Department of Earth System Science, Tsinghua University, Beijing100084, China
| | - Xia Meng
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education, and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai200433, China
| | - Conghong Huang
- College of Land Management, Nanjing Agricultural University, Nanjing 210095, China
- National & Local Joint Engineering, Research Center for Rural Land Resources Use and Consolidation, Nanjing 210095, China
| | - Siqi Ai
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
| | - Fangzhou Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
| | - Jingyuan Cao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
| | - Mingkun Tong
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Xueqiu Ni
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Hengyi Liu
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Jianyu Deng
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Hong Lu
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Wei Wan
- Clean Air Asia, Beijing100600, China
| | - Jicheng Gong
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
| | - Shiqiu Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
| | - Tong Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
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Tong M, Wang M, Li P, Gong J, Zhu T, Xue T. The short-term effect of ozone on pregnancy loss modified by temperature: Findings from a nationwide epidemiological study in the contiguous United States. Sci Total Environ 2023; 902:166088. [PMID: 37549698 PMCID: PMC10592165 DOI: 10.1016/j.scitotenv.2023.166088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/18/2023] [Accepted: 08/04/2023] [Indexed: 08/09/2023]
Abstract
BACKGROUND Pregnancy loss, a major health issue that affects human sustainability, has been linked to short-term exposure to ground-surface ozone (O3). However, the association is inconsistent, possibly because of the co-occurrence of O3 and heat episodes, as increased temperature is a risk factor for pregnancy loss. To explain this inconsistency, the effect of O3 on pregnancy loss needs to be examined jointly with that of high temperature. METHODS A total of 247,305 pregnancy losses during the warm season were extracted from fetal death certificates from the 386 counties in contiguous United States from 1989 to 2005. We assessed environmental exposure based on the daily maximum 8 h average of O3 from Air Quality System monitors and the 24 h average temperature from the North American Regional Reanalysis product. We conducted a bidirectional, time-stratified case-crossover study of the association between pregnancy loss and exposures to O3 and temperature and their multiplicative interaction. The main time window for the exposure assessment was the day of case occurrence and the preceding 3 days. To estimate the association, we used conditional logistic regression with adjustment for relative humidity, height of the planetary boundary layer, and holidays. Sensitivity analyses were performed on the lagged structure, nonlinearity, and between-subpopulation heterogeneity of the estimated joint effect. RESULTS The joint effect was first estimated by the regression against categorical exposure by tertile. Compared to the low-low exposure group (O3 ≤ 78 μg/m3 and temperature ≤ 18 °C), the odds of pregnancy loss was significantly higher by 6.0 % (95 % confidence interval [CI] 2.4-9.7 %), 9.8 % (6.1-13.8 %), and 7.5 % (4.7-10.3 %) in the high-low (>104 μg/m3 and ≤18 °C), low-high (≤78 μg/m3 and >23 °C), and high-high (>104 μg/m3 and >23 °C) groups. The model of linear exposure and the multiplicative interaction yielded similar results. Each increment of 10 μg/m3 in O3 and 1 °C in temperature was associated with a 3.0 % (2.0 %-4.0 %) and 3.9 % (3.5 %-4.3 %), respectively, increase in the odds of pregnancy loss. A decrease in odds of 0.2 % (0.1 %-0.2 %) was associated with the temperature × O3 interaction. The finding of an antagonistic interaction between temperature and O3 was confirmed by models parametrizing the joint exposure as alternative nonlinear terms (i.e., a two-dimensional spline term or a varying-coefficient term) and was robust to a variety of exposure lags and stratifications. Therefore, the marginal effect of O3 was estimated to vary by climate zone. A significant association between O3 and pregnancy loss was observed in the northern, but not southern, United States. CONCLUSION Joint exposure to O3 and high temperature can increase the risk for pregnancy loss. The adverse effect of O3 is potentially modified by ambient temperature. In high-latitude cities, controlling for O3 pollution could protect maternal health.
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Affiliation(s)
- Mingkun Tong
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Center, Beijing, China
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY 14214, United States; Research and Education in Energy, Environment and Water Institute, University at Buffalo, Buffalo, NY 14214, United States; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98115, United States
| | - Pengfei Li
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Center, Beijing, China; Advanced Institute of Information Technology, Peking University, Hangzhou, China; National Institute of Health Data Science, Peking University, Beijing, China
| | - Jicheng Gong
- College of Environmental Sciences and Engineering, Peking University, Beijing, China; State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management and Center for Environment and Health, Peking University, Beijing, China
| | - Tong Zhu
- College of Environmental Sciences and Engineering, Peking University, Beijing, China; State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management and Center for Environment and Health, Peking University, Beijing, China
| | - Tao Xue
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Center, Beijing, China; Advanced Institute of Information Technology, Peking University, Hangzhou, China; State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management and Center for Environment and Health, Peking University, Beijing, China.
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