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Gu W, Xie D, Li Q, Feng H, Xue Y, Chen Y, Tang J, Zhou Y, Wang D, Tong S, Liu S. Association of humidity and precipitation with asthma: a systematic review and meta-analysis. FRONTIERS IN ALLERGY 2024; 5:1483430. [PMID: 39713043 PMCID: PMC11659254 DOI: 10.3389/falgy.2024.1483430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Accepted: 11/25/2024] [Indexed: 12/24/2024] Open
Abstract
Introduction The relationship of asthma with humidity and precipitation remains controversial. The objective of this study was to investigate the association of increased humidity and precipitation with asthma risk. Methods A comprehensive systematic search was conducted across various databases, including PubMed, Embase, Cochrane Library, Web of Science, Chinese Wanfang, CQVIP, and CNKI. A total of 21 studies with 1,052,960 participants from 9 countries or regions were included. The fixed and random effect model were used to analyze the data. Results The study revealed a pooled odds ratio (OR) of 1.0489 [95% confidence interval (CI): 1.0061, 1.0935] for the association between humidity and asthma risk. Specifically, among individuals under 18 years of age, the OR (95% CI) was 1.0898 (1.0290, 1.1541). Furthermore, the OR (95% CI) for developing countries or regions was 1.0927 (1.0220, 1.1684), while it was 1.1298 (0.9502, 1.3433) for regions with a high latitude (41°-51°). The pooled OR for precipitation and asthma risk was 0.9991 (0.9987, 0.9995). The OR (95%CI) values were 0.9991 (0.9987, 0.9995), 0.9991 (0.9987, 0.9995) and 0.9990 (0.9986, 0.9994) in people above the age of 18, developing countries or regions, and middle latitudes (31°-41°), respectively. Discussion The impact of humidity on asthma risk is particularly pronounced among individuals below 18 years of age, people living in developing countries or regions and in regions located in high latitudes. And the influence of precipitation on asthma persons over the age of 18, developing countries or regions, and middle latitudes significantly. Increased humidity appears to elevate asthma risk, and increased precipitation may reduce the risk. In addition, there appears to be a combined effect of humidity and precipitation on asthma. Systematic Review Registration PROSPERO, identifier, CRD42023482446.
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Affiliation(s)
- Wangyang Gu
- Department of Big Data Center, Sanya Women and Children's Hospital Affiliated to Hainan Medical University, Sanya, China
- Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya, China
| | - Dan Xie
- Department of Big Data Center, Sanya Women and Children's Hospital Affiliated to Hainan Medical University, Sanya, China
- Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya, China
| | - Qinpeng Li
- Department of Big Data Center, Sanya Women and Children's Hospital Affiliated to Hainan Medical University, Sanya, China
- Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya, China
| | - Huike Feng
- Department of Big Data Center, Sanya Women and Children's Hospital Affiliated to Hainan Medical University, Sanya, China
- Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya, China
| | - Yihao Xue
- Department of Big Data Center, Sanya Women and Children's Hospital Affiliated to Hainan Medical University, Sanya, China
- Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya, China
| | - Yang Chen
- Department of Epidemiology and Statistics, School of Public Health, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jingyi Tang
- Department of Epidemiology and Statistics, School of Public Health, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yushi Zhou
- Department of Big Data Center, Sanya Women and Children's Hospital Affiliated to Hainan Medical University, Sanya, China
- Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya, China
| | - Dan Wang
- Department of Big Data Center, Sanya Women and Children's Hospital Affiliated to Hainan Medical University, Sanya, China
- Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya, China
| | - Shilu Tong
- Department of Epidemiology and Statistics, School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia
- Chinese Centers for Disease Control and Prevention, National Institute of Environmental Health, Beijing, China
| | - Shijian Liu
- Department of Big Data Center, Sanya Women and Children's Hospital Affiliated to Hainan Medical University, Sanya, China
- Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya, China
- Department of Epidemiology and Statistics, School of Public Health, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Sanya, China
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Rida J, Bouchriti Y, Ait Haddou M, Achbani A, Sine H, Serhane H. Meteorological factors and climate change impact on asthma: a systematic review of epidemiological evidence. J Asthma 2024; 61:1601-1610. [PMID: 38953539 DOI: 10.1080/02770903.2024.2375272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Revised: 06/19/2024] [Accepted: 06/28/2024] [Indexed: 07/04/2024]
Abstract
OBJECTIVE This systematic review aimed to investigate the epidemiological data about meteorological factors and climate change (CC) impact on asthma. DATA SOURCES A search was performed using three databases (Web of Science, Science Direct, and MEDLINE) for all relevant studies published from January 1, 2018, to December 31, 2022. STUDY SELECTIONS This systematic review complied with the PRISMA document's requirements, including studies related to meteorological factors and CC impact on asthma. The search included studies published in English or French language, and was based on title, abstract, and complete text. Documents not meeting inclusion requirements were excluded. RESULTS We identified 18 studies published in the last five years that were eligible for inclusion in this review. We found that these studies concerned European, Asian, American, and Oceanic cities. Extreme variations in temperature, humidity, wind speed, exceptional incidents like hurricanes, cold and heat waves, and seasonal shifts were strongly correlated with the worsening of asthmatic symptoms, particularly in childhood. In addition, excessive concentrations of air pollutants and aeroallergens were linked to pediatric asthma emergency hospital admissions. CONCLUSIONS A significant association between the consequences of CC and asthma in adults particularly in children has been demonstrated. Future research should quantify the impact of global change in climate regarding the aeroallergens' distribution in terms of geography and time. It is also necessary to research the impact of air pollution on asthmatic health, like sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and particles having an aerodynamic diameter lower than 2.5 µm (PM2.5).
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Affiliation(s)
- Jamila Rida
- Research Laboratory of Innovation in Health Sciences, Faculty of Medicine and Pharmacy, Ibn Zohr University, Agadir, Morocco
- High Institute of Nursing Professions and Health Techniques, Health Sciences and Environment Laboratory, Health Sciences, Epidemiology and Human Pathologies Research Team, Agadir, Morocco
| | - Youssef Bouchriti
- High Institute of Nursing Professions and Health Techniques, Health Sciences and Environment Laboratory, Health Sciences, Epidemiology and Human Pathologies Research Team, Agadir, Morocco
- Geosciences, Environment and Geomatic Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
| | - Mohamed Ait Haddou
- Geosciences, Environment and Geomatic Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
- Department of Geography, Faculty of Humanities and Social Sciences, Ibn Tofail University, Kenitra, Morocco
| | - Abderrahmane Achbani
- Laboratory of Cell Biology and Molecular Genetics, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
- High Institute of Nursing Professions and Health Techniques, Marrakesh, Morocco
| | - Hasnaa Sine
- Laboratory of Cell Biology and Molecular Genetics, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
- High Institute of Nursing Professions and Health Techniques, Marrakesh, Morocco
| | - Hind Serhane
- Research Laboratory of Innovation in Health Sciences, Faculty of Medicine and Pharmacy, Ibn Zohr University, Agadir, Morocco
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Qin P, Ma Y, Zhao Y, Liu Z, Wang W, Feng F, Cheng B. Temperature modification of air pollutants and their synergistic effects on respiratory diseases in a semi-arid city in Northwest China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:284. [PMID: 38963443 DOI: 10.1007/s10653-024-02044-w] [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: 11/25/2023] [Accepted: 05/21/2024] [Indexed: 07/05/2024]
Abstract
Air pollutants and temperature are significant threats to public health, and the complex linkages between the environmental factors and their interactions harm respiratory diseases. This study is aimed to analyze the impact of air pollutants and meteorological factors on respiratory diseases and their synergistic effects in Dingxi, a city in northwestern China, from 2018 to 2020 using a generalized additive model (GAM). Relative risk (RR) was employed to quantitatively evaluate the temperature modification on the short-term effects of PM2.5 and O3 and the synergistic effects of air pollutants (PM2.5 and O3) and meteorological elements (temperature and relative humidity) on respiratory diseases. The results indicated that the RRs per inter-quatile range (IQR) rise in PM2.5 and O3 concentrations were (1.066, 95% CI: 1.009-1.127, lag2) and (1.037, 95% CI: 0.975-1.102, lag4) for respiratory diseases, respectively. Temperature stratification suggests that the influence of PM2.5 on respiratory diseases was significantly enhanced at low and moderate temperatures, and the risk of respiratory diseases caused by O3 was significantly increased at high temperatures. The synergy analysis demonstrated significant a synergistic effect of PM2.5 with low temperature and high relative humidity and an antagonistic effect of high relative humidity and O3 on respiratory diseases. The findings would provide a scientific basis for the impact of pollutants on respiratory diseases in Northwest China.
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Affiliation(s)
- Pengpeng Qin
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Yuxia Ma
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
| | - Yuhan Zhao
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Zongrui Liu
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Wanci Wang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Fengliu Feng
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Bowen Cheng
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
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Yan M, Li T. A Review of the Interactive Effects of Climate and Air Pollution on Human Health in China. Curr Environ Health Rep 2024; 11:102-108. [PMID: 38351403 DOI: 10.1007/s40572-024-00432-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/27/2024] [Indexed: 05/12/2024]
Abstract
PURPOSE OF REVIEW Through a systematic search of peer-reviewed epidemiologic studies, we reviewed the literature on the human health impacts of climate and ambient air pollution, focusing on recently published studies in China. Selected previous literature is discussed where relevant in tracing the origins. RECENT FINDINGS Climate variables and air pollution have a complex interplay in affecting human health. The bulk of the literature we reviewed focuses on the air pollutants ozone and fine particulate matter and temperatures (including hot and cold extremes). The interaction between temperature and ozone presented substantial interaction, but evidence about the interactive effects of temperature with other air pollutants is inconsistent. Most included studies used a time-series design, usually with daily mean temperature and air pollutant concentration as independent variables. Still, more needs to be studied about the co-occurrence of climate and air pollution. The co-occurrence of extreme climate and air pollution events is likely to become an increasing health risk in China and many parts of the world as climate changes. Climate change can interact with air pollution exposure to amplify risks to human health. Challenges and opportunities to assess the combined effect of climate variables and air pollution on human health are discussed in this review. Implications from epidemiological studies for implementing coordinated measures and policies for addressing climate change and air pollution will be critical areas of future work.
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Affiliation(s)
- Meilin Yan
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, China
| | - Tiantian Li
- CDC Key Laboratory of Environment and Population Health, Chinese Center for Disease Control and Prevention, National Institute of Environmental Health, Beijing, China.
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5
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Cheng C, Liu Y, Han C, Fang Q, Cui F, Li X. Effects of extreme temperature events on deaths and its interaction with air pollution. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 915:170212. [PMID: 38246371 DOI: 10.1016/j.scitotenv.2024.170212] [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: 09/27/2023] [Revised: 12/17/2023] [Accepted: 01/14/2024] [Indexed: 01/23/2024]
Abstract
BACKGROUND Both extreme temperature events (ETEs) and air pollution affected human health, and their effects were often not independent. Previous studies have provided limited information on the interactions between ETEs and air pollution. METHODS We collected data on deaths (non-accidental, cardiovascular, and respiratory) in Zibo City along with daily air pollution and meteorological data from January 2015 to December 2019. Distributed lag non-linear model was used to explore the health effects of ETEs on deaths. Non-parametric binary response model, hierarchical model and joint effect model were used to further explore the interaction between ETEs and air pollution in different seasons. Meanwhile, subgroup analysis by gender and age (≥ 65 years old and < 65 years old) was conducted to identify the vulnerable population. RESULTS ETEs increased death risk, especially for cardiovascular and respiratory deaths. Heat waves had a stronger impact than cold spells. Cold spells had a longer lag and fluctuating trend. Heat waves had a short-term impact, followed by a decrease. Females and those aged ≥ 65 were more affected, but subgroup differences were not significant. During ETEs and non-ETEs, there were different effects on deaths with per IQR increase in air pollutant concentrations. Joint effect models revealed that there was a significant interaction between ETEs and air pollution on non-accidental deaths. The interaction between PM2.5 and cold spells was antagonistic in the cold season. In the warm season, the health effects of heat waves and high O3 concentration were enhanced. The relative excess risk due to interaction (RERI) of cold spells and PM2.5 in total population was -0.09 (95 % CI: -0.17, -0.01), and 9 % (95 % CI: 1 %, 17 %) of the total effect was attributable to interaction. Subgroup analysis confirmed the interactions in females and those aged ≥ 65. CONCLUSIONS Significant association observed between ETEs and deaths. Females and ≥ 65 age groups were vulnerable. There were interactions between ETEs and air pollution. The effect of PM2.5 on deaths decreased during cold spells, while the effect of O3 increased during heat waves. In addition to improving air quality, it is necessary to further strengthen the prevention and control of ETEs.
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Affiliation(s)
- Chuanlong Cheng
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Ying Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Ma'anshan Center for Disease Control and Prevention, Ma'anshan 243000, Anhui, China
| | - Chuang Han
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Qidi Fang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Feng Cui
- Zibo Center for Disease Control and Prevention, Zibo, Shandong, China
| | - Xiujun Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
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Ji JS, Xia Y, Liu L, Zhou W, Chen R, Dong G, Hu Q, Jiang J, Kan H, Li T, Li Y, Liu Q, Liu Y, Long Y, Lv Y, Ma J, Ma Y, Pelin K, Shi X, Tong S, Xie Y, Xu L, Yuan C, Zeng H, Zhao B, Zheng G, Liang W, Chan M, Huang C. China's public health initiatives for climate change adaptation. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 40:100965. [PMID: 38116500 PMCID: PMC10730322 DOI: 10.1016/j.lanwpc.2023.100965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 10/01/2023] [Accepted: 11/01/2023] [Indexed: 12/21/2023]
Abstract
China's health gains over the past decades face potential reversals if climate change adaptation is not prioritized. China's temperature rise surpasses the global average due to urban heat islands and ecological changes, and demands urgent actions to safeguard public health. Effective adaptation need to consider China's urbanization trends, underlying non-communicable diseases, an aging population, and future pandemic threats. Climate change adaptation initiatives and strategies include urban green space, healthy indoor environments, spatial planning for cities, advance location-specific early warning systems for extreme weather events, and a holistic approach for linking carbon neutrality to health co-benefits. Innovation and technology uptake is a crucial opportunity. China's successful climate adaptation can foster international collaboration regionally and beyond.
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Affiliation(s)
- John S. Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Yanjie Xia
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Linxin Liu
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Weiju Zhou
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National School of Public Health, Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Guanghui Dong
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Qinghua Hu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Jingkun Jiang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National School of Public Health, Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Tiantian Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yi Li
- Public Meteorological Service Centre, China Meteorological Administration, Beijing, China
| | - Qiyong Liu
- National Institute of Infectious Diseases at China, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yanxiang Liu
- Public Meteorological Service Centre, China Meteorological Administration, Beijing, China
| | - Ying Long
- School of Architecture, Tsinghua University, Beijing, China
| | - Yuebin Lv
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jian Ma
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Yue Ma
- School of Architecture, Tsinghua University, Beijing, China
| | - Kinay Pelin
- School of Climate Change and Adaptation, University of Prince Edward Island, Prince Edward Island, Canada
| | - Xiaoming Shi
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Shilu Tong
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Queensland University of Technology, Brisbane, Australia
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, China
| | - Lei Xu
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Changzheng Yuan
- School of Public Health, Zhejiang University, Hangzhou, China
| | - Huatang Zeng
- Shenzhen Health Development Research and Data Management Center, Shenzhen, China
| | - Bin Zhao
- Department of Building Science, School of Architecture, Tsinghua University, Beijing, China
| | - Guangjie Zheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Wannian Liang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Margaret Chan
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
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Huang K, Feng LF, Liu ZY, Li ZH, Mao YC, Wang XQ, Zhao JW, Zhang KD, Li YQ, Wang J, Yu WJ, Cheng X, Yang XY, Li J, Zhang XJ. The modification of meteorological factors on the relationship between air pollution and periodontal diseases: an exploration based on different interaction strategies. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023; 45:8187-8202. [PMID: 37552412 DOI: 10.1007/s10653-023-01705-6] [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: 02/07/2023] [Accepted: 07/18/2023] [Indexed: 08/09/2023]
Abstract
We aimed to characterize the association between air pollutants exposure and periodontal diseases outpatient visits and to explore the interactions between ambient air pollutants and meteorological factors. The outpatient visits data of several large stomatological and general hospitals in Hefei during 2015-2020 were collected to explore the relationship between daily air pollutants exposure and periodontal diseases by combining Poisson's generalized linear model (GLMs) and distributed lag nonlinear model (DLNMs). Subgroup analysis was performed to identify the vulnerability of different populations to air pollutants exposure. The interaction between air pollutants and meteorological factors was verified in both multiplicative and additive interaction models. An interquartile range (IQR) increased in nitrogen dioxide (NO2) concentration was associated with the greatest lag-specific relative risk (RR) of gingivitis at lag 3 days (RR = 1.087, 95% CI 1.008-1.173). Fine particulate matter (PM2.5) exposure also increased the risk of periodontitis at the day of exposure (RR = 1.049, 95% CI 1.004-1.096). Elderly patients with gingivitis and periodontitis were both vulnerable to PM2.5 exposure. The interaction analyses showed that exposure to high levels of NO2 at low temperatures was related to an increased risk of gingivitis, while exposure to high levels of NO2 and PM2.5 may also increase the risk of gingivitis and periodontitis in the high-humidity environment, respectively. This study supported that NO2 and PM2.5 exposure increased the risk of gingivitis and periodontitis outpatient visits, respectively. Besides, the adverse effects of air pollutants exposure on periodontal diseases may vary depending on ambient temperature and humidity.
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Affiliation(s)
- Kai Huang
- The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, 230032, China
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Lin-Fei Feng
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230032, China
| | - Zhe-Ye Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Zhen-Hua Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Yi-Cheng Mao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Xin-Qiang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Jia-Wen Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Kang-Di Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Ying-Qing Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Jie Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Wen-Jie Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Xin Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Xi-Yao Yang
- The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, 230032, China
| | - Jiong Li
- College and Hospital of Stomatology, Key Laboratory of Oral Diseases Research of Anhui Province, Anhui Medical University, Hefei, 230032, China
| | - Xiu-Jun Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China.
- College and Hospital of Stomatology, Key Laboratory of Oral Diseases Research of Anhui Province, Anhui Medical University, Hefei, 230032, China.
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8
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Squires E. Effects of climate change on patients with respiratory and cardiovascular conditions. Nurs Stand 2023; 38:57-61. [PMID: 37259785 DOI: 10.7748/ns.2023.e12087] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/23/2023] [Indexed: 06/02/2023]
Abstract
Climate change is one of the most significant global challenges and is already having detrimental effects on people's health. Pollution levels and ambient temperatures continue to increase, resulting in higher levels of humidity and pollen production. These environmental threats can affect many vulnerable patients, particularly those with respiratory and cardiovascular conditions, and nurses have a crucial role in raising awareness of the health implications of climate change. This article explores the pathophysiological effects of climate change on patients with asthma, chronic obstructive pulmonary disease and cardiovascular disease, and aims to enhance nurses' understanding of the health challenges of climate change.
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Affiliation(s)
- Eleanor Squires
- School of Health and Social Work, University of Hertfordshire, Hatfield, England
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9
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McDermott-Levy R, Pennea E, Moore C. Protecting Children's Health: Asthma and Climate Change. MCN Am J Matern Child Nurs 2023; 48:188-194. [PMID: 36943899 DOI: 10.1097/nmc.0000000000000927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
ABSTRACT Children are particularly vulnerable to the impacts of climate change. Their lungs are developing, making children with asthma especially susceptible to temperature extremes, variations in precipitation, poor air quality, and changes in pollen and flora. Structural and social determinants of health, such as racism and poverty, that disproportionately affect children of color are linked to higher rates of asthma and negative effects of climate change. These factors lead to increased absences from school and social activities, loss of work for caregivers, and increased health care costs, thus negatively affecting children, their families, and the greater community. Nurses must support caregivers and children to link climate change to asthma care, be involved in health education; climate change mitigation and adaptation strategies and policies; and develop the evidence to address climate change and asthma strategies. We address the impacts of climate change on children with asthma and nursing adaptation responses.
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10
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Zhou L, Wang Y, Wang Q, Ding Z, Jin H, Zhang T, Zhu B. The interactive effects of extreme temperatures and PM 2.5 pollution on mortalities in Jiangsu Province, China. Sci Rep 2023; 13:9479. [PMID: 37301905 PMCID: PMC10257702 DOI: 10.1038/s41598-023-36635-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 06/07/2023] [Indexed: 06/12/2023] Open
Abstract
Exposure to extreme temperatures or fine particles is associated with adverse health outcomes but their interactive effects remain unclear. We aimed to explore the interactions of extreme temperatures and PM2.5 pollution on mortalities. Based on the daily mortality data collected during 2015-2019 in Jiangsu Province, China, we conducted generalized linear models with distributed lag non-linear model to estimate the regional-level effects of cold/hot extremes and PM2.5 pollution. The relative excess risk due to interaction (RERI) was evaluated to represent the interaction. The relative risks (RRs) and cumulative relative risks (CRRs) of total and cause-specific mortalities associated with hot extremes were significantly stronger (p < 0.05) than those related to cold extremes across Jiangsu. We identified significantly higher interactions between hot extremes and PM2.5 pollution, with the RERI range of 0.00-1.15. The interactions peaked on ischaemic heart disease (RERI = 1.13 [95%CI: 0.85, 1.41]) in middle Jiangsu. For respiratory mortality, RERIs were higher in females and the less educated. The interaction pattern remained consistent when defining the extremes/pollution with different thresholds. This study provides a comprehensive picture of the interactions between extreme temperatures and PM2.5 pollution on total and cause-specific mortalities. The projected interactions call for public health actions to face the twin challenges, especially the co-appearance of hot extremes and PM pollution.
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Affiliation(s)
- Lian Zhou
- Center for Disease Control and Prevention of Jiangsu Province, Nanjing, 210009, China
| | - Yuning Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 Dingjia Bridge, Gulou District, Nanjing, 210009, China.
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, 210009, China.
| | - Qingqing Wang
- Center for Disease Control and Prevention of Jiangsu Province, Nanjing, 210009, China
| | - Zhen Ding
- Center for Disease Control and Prevention of Jiangsu Province, Nanjing, 210009, China
| | - Hui Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 Dingjia Bridge, Gulou District, Nanjing, 210009, China
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, 210009, China
| | - Ting Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China.
- Department of Civil, Environmental, and Infrastructure Engineering, George Mason University, Fairfax, VA, 22030, USA.
| | - Baoli Zhu
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
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Wang S, Wu G, Du Z, Wu W, Ju X, Yimaer W, Chen S, Zhang Y, Li J, Zhang W, Hao Y. The causal links between long-term exposure to major PM 2.5 components and the burden of tuberculosis in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 870:161745. [PMID: 36690108 DOI: 10.1016/j.scitotenv.2023.161745] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 01/09/2023] [Accepted: 01/17/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND We aimed to estimate the causal impacts of long-term exposure to major PM2.5 components - including black carbon, organic matter, sulfate, nitrate, and ammonium - on the incidence and mortality of tuberculosis in China. METHODS We collected annual and provincial-level tuberculosis incidence and mortality, concentrations of PM2.5 components, and socioeconomic indicators from between 2004 and 2018 in mainland China. We used the difference-in-differences (DID) causal inference approach with a generalized weighted quantile sum (gWQS) regression model to estimate the long-term effects and relative contributions of PM2.5 components' exposure on tuberculosis incidence and mortality. RESULTS We found that long-term multi-components exposure was significantly associated with tuberculosis incidence (WQS index IR%:8.34 %, 95 % CI:4.54 %-12.27 %) and mortality (WQS index IR%:19.49 %, 95 % CI: 9.72 %-30.13 %). Primary pollutants, black carbon and organic matter, contributed most of the overall mixture effect (over 85 %). Nitrate showed a critical role in tuberculosis burden in not-aging provinces and in regions at the Q3 stratum (i.e., the 3rd quartile) of GDP per capita and urbanization rate. Meanwhile the contribution of sulfate to tuberculosis burden in regions at the Q1 stratum of GDP per capita and urbanization rate was the largest among the effect of secondary pollutants (i.e., sulfate, nitrate, and ammonium). CONCLUSION The mitigation of black carbon and organic matter pollution may significantly reduce the tuberculosis burden in China. Controlling nitrate emissions and increasing clean energy (i.e., energy sources with limited pollution emissions, such as natural gas and clean coal) may also be effective in certain regions.
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Affiliation(s)
- Shenghao Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Gonghua Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wenjing Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xu Ju
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wumitijiang Yimaer
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Shirui Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jinghua Li
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China.
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China.
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12
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Yuan J, Chang W, Yao Z, Wen L, Liu J, Pan R, Yi W, Song J, Yan S, Li X, Liu L, Wei N, Song R, Jin X, Wu Y, Li Y, Liang Y, Sun X, Mei L, Cheng J, Su H. The impact of hazes on schizophrenia admissions and the synergistic effect with the combined atmospheric oxidation capacity in Hefei, China. ENVIRONMENTAL RESEARCH 2023; 220:115203. [PMID: 36592807 DOI: 10.1016/j.envres.2022.115203] [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: 11/01/2022] [Revised: 12/15/2022] [Accepted: 12/30/2022] [Indexed: 06/17/2023]
Abstract
OBJECTIVES Currently, most epidemiological studies on haze focus on respiratory diseases, cardiovascular diseases, etc. However, the relationship between haze and mental health has not been adequately explored. The purpose of this study was to investigate the influence of hazes on schizophrenia admissions and to further explore the potential interaction effect with the combined atmospheric oxidative indices (Ox and Oxwt). METHODS We collected 5328 cases during the cold season from 2013 to 2015 in Hefei, China. By integrating the Poisson Generalized Linear Models with the Distributed Lag Non-linear Models, the association between haze and schizophrenia admissions was evaluated. The interaction between hazes and two combined oxidation indexes was tested by stratifying hazes and Ox, and Oxwt. RESULTS Haze was found to be significantly linked to an increased risk of hospitalization for schizophrenia, and a 9-day lag effect on schizophrenia (lag 3-lag 11), with the largest effect on lag 6 (RR = 1.080, 95% confidence interval (CI): 1.046-1.116). Males, females, and <40 y (people under 40 years old) were sensitive to hazes. Furthermore, in the stratified analysis, we found synergies between two combined oxidation indexes and hazes. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) between Ox and hazes were 1.170 (95% CI: 1.071-1.277) and 0.149 (95% CI: 0.045-0.253), respectively. For Oxwt, the IRR and RERI were 1.179 (95% CI: 1.087-1.281) and 0.159 (95% CI: 0.056-0.263), respectively. It is noteworthy that this synergistic effect was significant in males and <40 y when examining the various subgroups in the interaction analysis. CONCLUSIONS Our findings suggest that exposure to haze significantly increases the risk of hospitalization for schizophrenia. More significant public health benefits can be obtained by prioritizing haze periods with high combined atmospheric oxidation capacity.
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Affiliation(s)
- Jiajun Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Weiwei Chang
- Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, 241002, Wuhu, Anhui, China
| | - Zhenhai Yao
- Anhui Public Meteorological Service Center, Hefei, Anhui, China
| | - Liying Wen
- Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, 241002, Wuhu, Anhui, China
| | - Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Shuangshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Xuanxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Li Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Ning Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Yudong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Yuxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Yunfeng Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Xiaoni Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Lu Mei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China.
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Chen Y, Li D, Karimian H, Wang S, Fang S. The relationship between air quality and MODIS aerosol optical depth in major cities of the Yangtze River Delta. CHEMOSPHERE 2022; 308:136301. [PMID: 36064028 DOI: 10.1016/j.chemosphere.2022.136301] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 08/18/2022] [Accepted: 08/29/2022] [Indexed: 06/15/2023]
Abstract
The AOD derived from the MODIS deep blue(DB) algorithm and AQI were used to investigate the correlation between AOD and AQI in seven major cities of Yangtze River Delta (YRD) from January to December 2019. The accuracy of MODIS AOD was validated by AERONET. Moreover, the AOD and AQI were studied to explore the annual and seasonal distribution characteristics, and the correlation analysis was carried out using five regression models. It was found: Ⅰ) There was a significant correlation between AOD and AERONET data (R2 ˃ 0.80, RMSE = 0.106, and MAE = 0.089). Ⅱ) The highest AQI was observed in winter (83), followed by spring (76), autumn (74), and summer (72). Ⅲ) The monthly average AOD showed noticeable seasonal variations, which reached the highest in summer (0.91) and the lowest in winter (0.69), followed by spring and autumn. Ⅳ) Among the five models, the cubic model obtained the best results with R2 ˃ 0.55. In the sub-seasonal regression model, the cubic model outperformed other models in spring (R2 ˃ 0.57), summer (R2 ˃ 0.76) and autumn (R2 ˃ 0.38). However, in winter the composite model outperformed others (R2 ˃ 0.68). Ⅴ) Considering annual data, the AOD can predict over 70% of the variations in AQI (0.41<R2 <0.81). These results demonstrate the feasibility of AOD derived from the MODIS DB algorithm in AQI prediction. The method used in this study can be applied as an aid for air pollution control programs in different regions.
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Affiliation(s)
- Youliang Chen
- Department of Geo-informatics, Central South University, Changsha, 410000, China; School of Civil and Surveying Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China
| | - Dan Li
- School of Civil and Surveying Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China
| | - Hamed Karimian
- School of Civil and Surveying Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China.
| | - Shiteng Wang
- School of Civil and Surveying Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China
| | - Shuwei Fang
- Institute of Remote Sensing and Geographic Information System, Peking University, Beijing, 100871, China
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Huang J, Ma Y, Lv Q, Liu Y, Zhang T, Yin F, Shui T. Interactive effects of meteorological factors and air pollutants on hand, foot, and mouth disease in Chengdu, China: a time-series study. BMJ Open 2022; 12:e067127. [PMID: 36450433 PMCID: PMC9716848 DOI: 10.1136/bmjopen-2022-067127] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 11/15/2022] [Indexed: 12/03/2022] Open
Abstract
OBJECTIVES Hand, foot, and mouth disease (HFMD) is a viral infectious disease that poses a substantial threat in the Asia-Pacific region. It is widely reported that meteorological factors are associated with HFMD. However, the relationships between air pollutants and HFMD are still controversial. In addition, the interactive effects between meteorological factors and air pollutants on HFMD remain unknown. To fill this research gap, we conducted a time-series study. DESIGN A time-series study. SETTING AND PARTICIPANTS Daily cases of HFMD as well as meteorological and air pollution data were collected in Chengdu from 2011 to 2017. A total of 184 610 HFMD cases under the age of 15 were included in our study. OUTCOME MEASURES Distributed lag nonlinear models were used to investigate the relationships between HFMD and environmental factors, including mean temperature, relative humidity, SO2, NO2, and PM10. Then, the relative excess risk due to interaction (RERI) and the proportion attributable to interaction were calculated to quantitatively evaluate the interactions between meteorological factors and air pollutants on HFMD. Bivariate response surface models were used to visually display the interactive effects. RESULTS The cumulative exposure-response curves of SO2 and NO2 were inverted 'V'-shaped and 'M'-shaped, respectively, and the risk of HFMD gradually decreased with increasing PM10 concentrations. We found that there were synergistic interactions between mean temperature and SO2, relative humidity and SO2, as well as relative humidity and PM10 on HFMD, with individual RERIs of 0.334 (95% CI 0.119 to 0.548), 0.428 (95% CI 0.214 to 0.642) and 0.501 (95% CI 0.262 to 0.741), respectively, indicating that the effects of SO2 and PM10 on HFMD were stronger under high temperature (>17.3°C) or high humidity (>80.0%) conditions. CONCLUSIONS There were interactive effects between meteorological factors and air pollutants on HFMD. Our findings could provide guidance for targeted and timely preventive and control measures for HFMD.
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Affiliation(s)
- Jiaqi Huang
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
| | - Yue Ma
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
| | - Qiang Lv
- Department of Acute Infectious Disease Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Yaqiong Liu
- Department of Acute Infectious Disease Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Tao Zhang
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
| | - Fei Yin
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, China
| | - Tiejun Shui
- Department of Leprosy Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
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15
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Chen P, Yuan Z, Miao L, Yang L, Wang H, Xu D, Lin Z. Acute cardiorespiratory response to air quality index in healthy young adults. ENVIRONMENTAL RESEARCH 2022; 214:113983. [PMID: 35948148 DOI: 10.1016/j.envres.2022.113983] [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: 02/01/2022] [Revised: 06/27/2022] [Accepted: 07/22/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Little is known about the acute health impacts of air quality index (AQI) on cardiorespiratory risk factors. OBJECTIVES To assess the short-term links of AQI with cardiorespiratory risk factors in young healthy adults. METHODS We performed a longitudinal panel study with 4 repeated visits in 40 healthy young adults in Hefei, Anhui Province, China from August to October 2021. Cardiorespiratory factors included systolic blood pressure (BP), diastolic BP (DBP), mean arterial pressure (MAP) and fractional exhaled nitric oxide (FeNO). We collected hourly AQI data from a nearby air quality monitoring site. Linear mixed-effects model was applied to assess the effects of AQI on BP and FeNO. RESULTS The study participants (75.0% females) provided 160 pairs of valid health measurements with average age of 24 years. The mean AQI level was 44.43 during the study period. There were significant positive associations of AQI with three BP parameters and FeNO at different lag periods. For example, an interquartile range increase in AQI (26.54 unit) over lag 0-24 h was associated with increments of 6.69 mmHg (95%CI: 2.95-10.44), 5.71 mmHg (95%CI: 3.30-8.13), 6.04 mmHg (95%CI: 3.46-8.62) and 5.67% (95%CI: 1.05%-16.05%) in SBP, DBP, MAP and FeNO, respectively. The results were robust after controlling for PM1. We did not find effect modifications by gender, BMI, physical activity, or AQI category level on the associations. CONCLUSIONS The current findings on associations of AQI with cardiorespiratory factors might add evidence of the acute adverse cardiorespiratory consequences following air pollution.
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Affiliation(s)
- Ping Chen
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, 230032, China
| | - Zhi Yuan
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, 230032, China
| | - Lin Miao
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, 230032, China
| | - Liyan Yang
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, 230032, China
| | - Hua Wang
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, 230032, China; Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei, 230032, China
| | - Dexiang Xu
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, 230032, China; Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei, 230032, China.
| | - Zhijing Lin
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei, 230032, China; Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei, 230032, China.
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16
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Jin X, Xu Z, Liang Y, Sun X, Yan S, Wu Y, Li Y, Mei L, Cheng J, Wang X, Song J, Pan R, Yi W, Yang Z, Su H. The modification of air particulate matter on the relationship between temperature and childhood asthma hospitalization: An exploration based on different interaction strategies. ENVIRONMENTAL RESEARCH 2022; 214:113848. [PMID: 35817164 DOI: 10.1016/j.envres.2022.113848] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 06/28/2022] [Accepted: 07/05/2022] [Indexed: 06/15/2023]
Abstract
The influence of temperature on childhood asthma was self-evident, yet the issue of whether the relationship will be synergized by air pollution remains unclear. The study aimed to investigate whether the relationship between short-term temperature exposure and childhood asthma hospitalization was modified by particulate matter (PM). Data on childhood asthma hospitalization, meteorological factors, and air pollutants during 2013-2016 in Hefei, China, were collected. First, a basic Poisson regression model combined with a distributed lag nonlinear model was used to assess the temperature-childhood asthma hospitalization relationship. Then, two interactive strategies were applied to explore the modification effect of PM on the temperature-childhood asthma hospitalization association. We found a greater effect of cold (5th percentile of temperature) on asthma during days with higher PM2.5 (RR: 2.16, 95% CI: 1.38, 3.38) or PM10 (RR: 1.87, 95% CI:1.20, 2.91) than that during days with lower PM2.5 (RR: 1.64, 95% CI: 1.06, 2.54) or PM10 (RR: 1.52, 95% CI: 0.98, 2.36). In addition, we observed a greater modification effect of PM2.5 on the cold-asthma association than did PM10, with a per 10 μg/m3 increase in PM2.5 and PM10 associated with increases of 0.065 and 0.025 for the RR corresponding to the 5th temperature percentile, respectively. For the temperature-related AF, moderate cold showed the largest change magnitude with the PM levels rising compared with other temperature ranges. For the subgroup, Females and those aged 6-18 years were more sensitive to the modification effect of PM2.5 or PM10 on the cold-asthma association. Our findings demonstrated that particulate matter could modify the associations between temperature and childhood asthma hospitalization.
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Affiliation(s)
- Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Yunfeng Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Xiaoni Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Shuangshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Yudong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Yuxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Lu Mei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Xu Wang
- Anhui Provincial Children's Hospital, Hefei, Anhui, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zeyu Yang
- Anhui Provincial Children's Hospital, Hefei, Anhui, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
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Hu Y, Cheng J, Liu S, Tan J, Yan C, Yu G, Yin Y, Tong S. Evaluation of climate change adaptation measures for childhood asthma: A systematic review of epidemiological evidence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 839:156291. [PMID: 35644404 DOI: 10.1016/j.scitotenv.2022.156291] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 05/23/2022] [Accepted: 05/24/2022] [Indexed: 06/15/2023]
Abstract
Global climate change (GCC) is widely accepted as the biggest threat to human health of the 21st century. Children are particularly vulnerable to GCC due to developing organ systems, psychological immaturity, nature of daily activities, and higher level of per-body-unit exposure. There is a rising trend in the disease burden of childhood asthma and allergies in many parts of the world. The associations of CC, air pollution and other environmental exposures with childhood asthma are attracting more research attention, but relatively few studies have focused on CC adaptation measures and childhood asthma. This study aimed to bridge this knowledge gap and conducted the first systematic review on CC adaptation measures and childhood asthma. We searched electronic databases including PubMed, Embase, and Web of Science using a set of MeSH terms and related synonyms, and identified 20 eligible studies included for review. We found that there were a number of adaptation measures proposed for childhood asthma in response to GCC, including vulnerability assessment, improving ventilation and heating, enhancing community education, and developing forecast models and early warning systems. Several randomized controlled trials show that improving ventilation and installing heating in the homes appear to be an effective way to relieve childhood asthma symptoms, especially in winter. However, the effectiveness of most adaptation measures, except for improving ventilation and heating, have not been explored and quantified. Given more extreme weather events (e.g., cold spells and heatwaves) may occur as climate change progresses, this finding may have important implications. Evidently, further research is urgently warranted to evaluate the impacts of CC adaptation measures on childhood asthma. These adaptation measures, if proven to be effective, should be integrated in childhood asthma control and prevention programs as GCC continues.
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Affiliation(s)
- Yabin Hu
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jian Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Shijian Liu
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jianguo Tan
- Shanghai Key Laboratory of Meteorology and Health (Shanghai Meteorological Service), Shanghai, China
| | - Chonghuai Yan
- MOE-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guangjun Yu
- Center for Biomedical Informatics, Shanghai Children's Hospital, Shanghai, China
| | - Yong Yin
- Department of Respiratory Medicine, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
| | - Shilu Tong
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.
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18
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He Y, Zhang X, Gao J, Gao H, Cheng J, Xu Z, Pan R, Yi W, Song J, Liu X, Tang C, Song S, Su H. The impact of cold spells on schizophrenia admissions and the synergistic effect with the air quality index. ENVIRONMENTAL RESEARCH 2022; 212:113243. [PMID: 35398316 DOI: 10.1016/j.envres.2022.113243] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 03/20/2022] [Accepted: 04/01/2022] [Indexed: 06/14/2023]
Abstract
OBJECTIVES Under current global climate conditions, there are insufficient studies on the health influences of cold spells, especially on mental health. This study aimed to examine the effect of cold spells on schizophrenia admissions and to analyze the potential interaction effect with the air quality index (AQI). METHODS Daily data on schizophrenia admissions and climatic variables in Hefei were collected from 2013 to 2019. Based on 20 definitions, the impacts of cold spells were quantified separately to find the most appropriate definition for the region, and meta-regression was used to explore the different effect sizes of the different days in a cold spell event. In addition, the potential interaction effect was tested by introducing a categorical variable, CSH, reflecting the cold spell and AQI level. RESULTS The cold spell defined by temperature below the 6th centile while lasting for at least three days produced the optimum model fit performance. In general, the risk of schizophrenia admissions increased on cold spell days. The largest single-day effect occurred on the 12th day with RR = 1.081 (95% CI: 1.044, 1.118). In a single cold spell event, the effect of the 3rd and subsequent days of a cold spell (RR = 1.082, 95% CI: 1.036, 1.130) was higher than that on the 2nd day (RR = 1.054, 95% CI: 1.024, 1.085). Similarly, the effect of the 2nd day was also higher than that of the 1st day (RR = 1.027, 95% CI: 1.012, 1.042). We found a synergistic effect between cold spells and high AQI in the male group, and the relative excess risk due to interaction (RERI) was 0.018 (95% CI: 0.005-0.030). CONCLUSIONS This study suggested that the impacts of cold spells should be considered based on the definition of the most appropriate for the region when formulating targeted measures of schizophrenia. The discovery of the synergistic effect was referred to help the selection of the timing of precautions for susceptible people.
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Affiliation(s)
- Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Xulai Zhang
- Anhui Mental Health Center, Hefei, Anhui, China
| | - Jiaojiao Gao
- Pudong New Area Center for Disease Control and Prevention, Shanghai, China
| | - Hua Gao
- Anhui Mental Health Center, Hefei, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Shasha Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
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19
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Armero G, Penela-Sánchez D, Belmonte J, Gómez-Barroso D, Larrauri A, Henares D, Vallejo V, Jordan I, Muñoz-Almagro C, Brotons P, Launes C. Concentrations of nitrogen compounds are related to severe rhinovirus infection in infants. A time-series analysis from the reference area of a pediatric university hospital in Barcelona. Pediatr Pulmonol 2022; 57:2180-2188. [PMID: 35652447 PMCID: PMC9543680 DOI: 10.1002/ppul.26021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 05/17/2022] [Accepted: 05/29/2022] [Indexed: 11/14/2022]
Abstract
BACKGROUND There is scarce information focused on the effect of weather conditions and air pollution on specific acute viral respiratory infections, such as rhinovirus (RV), with a wide clinical spectrum of severity. OBJECTIVE The aim of this study was to analyze the association between episodes of severe respiratory tract infection by RV and air pollutant concentrations (NOx and SO2 ) in the reference area of a pediatric university hospital. METHODS An analysis of temporal series of daily values of NOx and SO2 , weather variables, circulating pollen and mold spores, and daily number of admissions in the pediatric intensive care unit (PICU) with severe respiratory RV infection (RVi) in children between 6 months and 18 years was performed. Lagged variables for 0-5 days were considered. The study spanned from 2010 to 2018. Patients with comorbidities were excluded. RESULTS One hundred and fifty patients were admitted to the PICU. Median age was 19 months old (interquartile range [IQR]: 11-47). No relationship between RV-PICU admissions and temperature, relative humidity, cumulative rainfall, or wind speed was found. Several logistic regression models with one pollutant and two pollutants were constructed but the best model was that which included average daily NOx concentrations. Average daily NOx concentrations were related with the presence of PICU admissions 3 days later (odds ratio per IQR-unit increase: 1.64, 95% confidence interval: 1.20-2.25)). CONCLUSIONS This study has shown a positive correlation between NOx concentrations at Lag 3 and children's PICU admissions with severe RV respiratory infection. Air pollutant data should be taken into consideration when we try to understand the severity of RVis.
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Affiliation(s)
- Georgina Armero
- Pediatrics Department, Hospital Sant Joan de Déu, Barcelona, Spain.,Pediatrics Intensive Care Unit, Hospital Sant Joan de Déu, Barcelona, Spain
| | | | - Jordina Belmonte
- Botanic Unit of Animal Biology, Vegetal Biology and Ecology Department, Science and Ambiental Technology Institute, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Diana Gómez-Barroso
- Centro Nacional de Epidemiología, Instituto de Salud Carlos III, Madrid, Spain.,Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Amparo Larrauri
- Centro Nacional de Epidemiología, Instituto de Salud Carlos III, Madrid, Spain.,Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Desiree Henares
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.,Grupo de investigación en enfermedades infecciosas pediátricas, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
| | - Violeta Vallejo
- Pediatrics Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Iolanda Jordan
- Pediatrics Intensive Care Unit, Hospital Sant Joan de Déu, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.,Grupo de investigación en enfermedades infecciosas pediátricas, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain.,Departament de Cirurgia i Especialitats Medicoquirúrgiques, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
| | - Carmen Muñoz-Almagro
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.,Grupo de investigación en enfermedades infecciosas pediátricas, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain.,Molecular Microbiology Department, Hospital Sant Joan de Déu, Barcelona, Spain.,Department of Medicine, School of Medicine, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Pedro Brotons
- Grupo de investigación en enfermedades infecciosas pediátricas, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain.,Department of Medicine, School of Medicine, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Cristian Launes
- Pediatrics Department, Hospital Sant Joan de Déu, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.,Grupo de investigación en enfermedades infecciosas pediátricas, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain.,Departament de Cirurgia i Especialitats Medicoquirúrgiques, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
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20
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Lu C, Zhang Y, Li B, Zhao Z, Huang C, Zhang X, Qian H, Wang J, Liu W, Sun Y, Norbäck D, Deng Q. Interaction effect of prenatal and postnatal exposure to ambient air pollution and temperature on childhood asthma. ENVIRONMENT INTERNATIONAL 2022; 167:107456. [PMID: 35952466 DOI: 10.1016/j.envint.2022.107456] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/28/2022] [Accepted: 08/03/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Although mounting evidence has associated air pollution and environmental temperature with children's health problems, it is unclear whether there is an interaction between these factors on childhood asthma. OBJECTIVES To explore the effects of temperature-pollution interactions during pre- and post-natal periods on asthma among pre-schoolers. METHODS A retrospective cohort study of 39,782 pre-schoolers was performed during 2010-2012, in seven cities in China. Exposure to three temperature indicators (TI) and three critical ambient air pollutants, including particulate matter with aerodynamic diameter ≤ 10 μm (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NO2) as proxies of industrial and vehicular air pollution, was estimated by an inverse distance weighted (IDW) method. Two-level logistical regression analysis was used to examine the association between both pre- and post-natal exposure and childhood asthma in terms of odds ratio (OR) and 95 % confidence interval (CI). RESULTS Asthma prevalence in pre-schoolers at age of 3-6 years (6.9 %) was significantly associated with traffic-related air pollutant (NO2) exposure, with ORs (95 % CI) of 1.17 (1.06, 1.28), 1.19 (1.05-1.34) and 1.16 (1.03-1.31) for an IQR increase in NO2 exposure during lifetime, pregnancy, and entire postnatal period respectively. Furthermore, childhood asthma was positively associated with exposure to increased temperature during lifetime, pregnancy, and entire postnatal period with ORs (95 % CI) = 1.89 (1.66, 2.16), 1.47 (1.34, 1.61), and 1.15 (1.11, 1.18) respectively, while was negatively associated with decreased temperatures. Childhood asthma was positively related with exposure to extreme heat days (EHD) during postnatal period particularly in first year of life respectively with ORs (95 % CI) = 1.23 (1.04, 1.46) and 1.26 (1.07, 1.47), but was not related with extreme cold days (ECD) exposure. A combination of high air pollutant levels and high temperatures significantly increased the risk of asthma during both pre- and post-natal periods. Strikingly, we found a significantly positive interaction of temperature and PM10 or SO2 on asthma risk among boys and younger children. CONCLUSIONS Prenatal and postnatal exposure to ambient air pollution and high temperatures are independently and jointly associated with asthma risk in early childhood.
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Affiliation(s)
- Chan Lu
- XiangYa School of Public Health, Central South University, Changsha, Hunan, China
| | - Yinping Zhang
- School of Architecture, Tsinghua University, Beijing, China
| | - Baizhan Li
- Key Laboratory of Three Gorges Reservoir Region's Eco-Environment, Chongqing University, Chongqing, China
| | - Zhuohui Zhao
- Department of Environmental Health, Fudan University, Shanghai, China
| | - Chen Huang
- School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China
| | - Xin Zhang
- Institute of Environmental Science, Shanxi University, Taiyuan, China
| | - Hua Qian
- School of Energy & Environment, Southeast University, Nanjing, China
| | - Juan Wang
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Wei Liu
- Institute for Health and Environment, Chongqing University of Science and Technology, Chongqing, China
| | - Yuexia Sun
- School of Environmental Science and Engineering, Tianjin University, Tianjin, China
| | - Dan Norbäck
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Qihong Deng
- School of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
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21
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Hu X, Han W, Wang Y, Aunan K, Pan X, Huang J, Li G. Does air pollution modify temperature-related mortality? A systematic review and meta-analysis. ENVIRONMENTAL RESEARCH 2022; 210:112898. [PMID: 35181304 DOI: 10.1016/j.envres.2022.112898] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 02/01/2022] [Accepted: 02/03/2022] [Indexed: 06/14/2023]
Abstract
INTRODUCTION There is an increasing interest in understanding whether air pollutants modify the quantitative relationships between temperature and health outcomes. The results of available studies were, however, inconsistent. This study aims to sum up the current evidence and provide a comprehensive understanding of this topic. METHODS We conducted an electronic search in PubMed (MEDLINE), EMBASE, Web of Science Core Collection, and ProQuest Dissertations and Theses. The modified Navigation Guide was applied to evaluate the quality and strength of evidence. We calculated pooled temperature-related mortality at low and high pollutant levels respectively, using the random-effects model. RESULTS We identified 22 eligible studies, eleven of which were included in the meta-analysis. Significant effect modification was observed on heat effects for all-cause and non-accidental mortality by particulate matter with an aerodynamic diameter of <10 μm (PM10) and ozone (O3) (p < 0.05). The excess risks (ERs) for all-cause and non-accidental mortality were 5.4% (4.4%, 6.4%) and 6.3% (4.8%, 7.8%) at the low PM10 level, 8.8% (7.5%, 10.1%) and 11.4% (8.7%, 14.2%) at the high PM10 level, respectively. As for O3, the ERs for all-cause and non-accidental mortality were 5.1% (3.9%, 6.3%) and 3.6% (0.1%, 7.2%) at the low O3 level, 7.6% (6.3%, 9.0%) and 12.5% (4.7%, 20.9%) at the high O3 level, respectively. Surprisingly, the heat effects on cardiovascular mortality were found to be lower at high carbon monoxide (CO) levels [ERs = 5.4% (3.9%, 6.9%)] than that at low levels [ERs = 9.4% (7.0%, 11.9%)]. The heterogeneity varied, but the results of sensitivity analyses were generally robust. Significant effect modification by air pollutants was not observed for heatwave or cold effects. CONCLUSIONS PM10 and O3 modify the heat-related all-cause and non-accidental mortality, indicating that policymakers should consider air pollutants when establishing heat-health warning systems. Future studies with comparable designs and settings are needed.
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Affiliation(s)
- Xin Hu
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, 38 Xueyuan Road, Haidian District, Beijing, 100191, China
| | - Wenxing Han
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, 38 Xueyuan Road, Haidian District, Beijing, 100191, China
| | - Yuxin Wang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, 38 Xueyuan Road, Haidian District, Beijing, 100191, China
| | - Kristin Aunan
- CICERO Center for International Climate Research, N-0318, Oslo, Norway
| | - Xiaochuan Pan
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, 38 Xueyuan Road, Haidian District, Beijing, 100191, China
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, 38 Xueyuan Road, Haidian District, Beijing, 100191, China
| | - Guoxing Li
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, 38 Xueyuan Road, Haidian District, Beijing, 100191, China.
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22
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Wu J, Ye Q, Fang L, Deng L, Liao T, Liu B, Lv X, Zhang J, Tao J, Ye D. Short-term association of NO 2 with hospital visits for chronic kidney disease and effect modification by temperature in Hefei, China: A time series study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 237:113505. [PMID: 35462193 DOI: 10.1016/j.ecoenv.2022.113505] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 04/05/2022] [Accepted: 04/07/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND A large body of evidence has linked air pollution and temperature with chronic kidney disease (CKD) prevalence and hospitalizations. However, most studies have focused on the influence of heat stress on CKD prevalence, and the potential effect modification of temperature on the association between air pollution and CKD has not been well-investigated. In this study, we examined the associations of the whole temperature spectrum and air pollution with CKD-related hospital visits and explored whether temperature modifies the short-term association of air pollution with CKD-related hospital visits. METHODS AND FINDINGS We collected 40 276 CKD-related hospital visits from the first Affiliated Hospital of Anhui Medical University and Anhui Provincial Hospital in Hefei, China, during 2015-2019. A two-stage time-series design was conducted to investigate the associations of air pollution and daily mean temperature with CKD-related hospital visits. First, we estimated the associations between air pollution and CKD-related hospital visits as well as temperature and CKD-related hospital visits. Second, we analyzed the associations of air pollution with CKD hospital visits at different temperatures. We found that NO2 exposure and low temperature were associated with an increased risk of CKD-related hospital visits. Low temperature enhanced the association between NO2 exposure and CKD-related hospital visits, with an increase of 4.30% (95% CI: 2.47-5.92%) per 10 μg/m3 increment in NO2 at low temperature. Effect modification of the association between NO2 and the risk of CKD-related hospital visits was stronger at low temperature across the whole population. CONCLUSIONS Our findings indicate that low temperature-related chronic kidney damage should be of immediate public health concern. Impact of NO2 exposure on the risk of CKD-related hospital visits may increase under the low temperature, which suggests the need for NO2 exposure mitigation strategies in the context of climate change and an enhanced understanding of the mechanisms underlying the temperature variance of air pollution effect to help reduce the magnitude of the CKD burden on the healthcare systems.
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Affiliation(s)
- Jun Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - QianLing Ye
- Department of Oncology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
| | - LanLan Fang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - LiJun Deng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Tao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Bo Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - XiaoJie Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Jie Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - JinHui Tao
- Department of Rheumatology & Immunology, Anhui Provincial Hospital, Hefei, Anhui, China.
| | - DongQing Ye
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China.
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23
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Wu R, Guo Q, Fan J, Guo C, Wang G, Wu W, Xu J. Association between air pollution and outpatient visits for allergic rhinitis: Effect modification by ambient temperature and relative humidity. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 821:152960. [PMID: 35016948 DOI: 10.1016/j.scitotenv.2022.152960] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/02/2022] [Accepted: 01/04/2022] [Indexed: 06/14/2023]
Abstract
Mounting evidence indicated the associations between air pollution and outpatient visits for allergic rhinitis (AR), while few studies assessed the effect modification of these associations by ambient temperature and relative humidity (RH). In this study, dataset of AR outpatients was obtained from Chinese People's Liberation Army Strategic Support Force Characteristic Medical Center in Beijing during 2014 to 2019, and the average concentrations of air pollutants including particulate matter ≤2.5 μm in diameter (PM2.5) and ≤10 μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and meteorological factors (temperature and RH) at the same period were collected from one nearby air monitoring station. We performed a time-series study with Poisson regression model to examine the effects of air pollutants on AR outpatients after adjustment for potential confounders. And the effects modification analysis was further conducted by stratifying temperature and RH by tertiles into three groups of low, middle and high. In total of 33,599 outpatient visits for AR were recorded during the study period. Results found that a 10 μg/m3 increase in PM2.5, PM10, NO2 and SO2 was associated with significant increases in AR outpatients of 1.24% (95% confidence interval (CI): 0.69%, 1.78%), 0.79% (95% CI: 0.43%, 1.15%), 3.05% (95% CI: 1.72%, 4.40%) and 5.01% (95% CI: 1.18%, 8.96%), respectively. Stronger associations were observed in males than those in females, as well as in young adults (18-44 years) than those in other age groups. Air pollution effects on AR outpatients increased markedly at low temperature (<33.3th percentile) and high RH (>66.7th percentile). Findings in this study indicate that air pollution is associated with increased risk of AR outpatients, and the effects of air pollution on AR could be enhanced at low temperature and high RH.
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Affiliation(s)
- Rongshan Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Center for Environmental Health Risk Assessment and Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Qun Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Center for Environmental Health Risk Assessment and Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jingpu Fan
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Center for Environmental Health Risk Assessment and Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Changsheng Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Center for Environmental Health Risk Assessment and Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Gang Wang
- Department of Otolaryngology, Strategic Support Force Medical Center, Beijing 100005, China; State Environmental Protection Key Laboratory of Environmental Sense Organ Stress and Health, Beijing 100005, China
| | - Wei Wu
- Department of Otolaryngology, Strategic Support Force Medical Center, Beijing 100005, China; State Environmental Protection Key Laboratory of Environmental Sense Organ Stress and Health, Beijing 100005, China.
| | - Jian Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Center for Environmental Health Risk Assessment and Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
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Pan R, Zheng H, Ding Z, Xu Z, Ho HC, Hossain MZ, Huang C, Yi W, Song J, Cheng J, Su H. Attributing hypertensive life expectancy loss to ambient heat exposure: A multicenter study in eastern China. ENVIRONMENTAL RESEARCH 2022; 208:112726. [PMID: 35033548 DOI: 10.1016/j.envres.2022.112726] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/03/2022] [Accepted: 01/10/2022] [Indexed: 06/14/2023]
Abstract
Ambient high temperature is a worldwide trigger for hypertension events. However, the effects of heat exposure on hypertension and years of life lost (YLL) due to heat remain largely unknown. We conducted a multicenter study in 13 cities in Jiangsu Province, China, to investigate 9727 individuals who died from hypertension during the summer months (May to September) between 2016 and 2017. Meteorological observation data (temperature and rainfall) and air pollutants (fine particulate matter and ozone) were obtained for each decedent by geocoding the residential addresses. A time-stratified case-crossover design was used to quantify the association between heat and different types of hypertension and further explore the modification effect of individual and hospital characteristics. Meanwhile, the YLL associated with heat exposure was estimated. Our results show that summer heat exposure shortens the YLL of hypertensive patients by a total of 14,74 years per month. Of these, 77.9% of YLL was mainly due to hypertensive heart disease. YLL due to heat was pronounced for essential hypertension (5.1 years (95% empirical confidence intervals (eCI): 4.1-5.8)), hypertensive heart and renal disease with heart failure (4.4 years (95% eCI: 0.9-5.9)), and hypertensive heart and renal disease (unspecified, 3.5 years (95% eCI: 1.8-4.5)). Moderate heat was associated with a larger YLL than extreme heat. The distance between hospitals and patients and the number of local first-class hospitals can significantly mitigate the adverse effect of heat exposure on longevity. Besides, unmarried people and those under 65 years of age were potentially susceptible groups, with average reduced YLL of 3.5 and 3.9 years, respectively. Our study reveals that heat exposure increases the mortality risk from many types of hypertension and YLL. In the context of climate change, if effective measures are not taken, hot weather may bring a greater burden of disease to hypertension due to premature death.
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Affiliation(s)
- Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, 210009, China
| | - Zhen Ding
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, 210009, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, 288 Herston Road, Herston, QLD, 4006, Australia
| | - Hung Chak Ho
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
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Hu Y, Cheng J, Yin Y, Liu S, Tan J, Li S, Wu M, Yan C, Yu G, Hu Y, Tong S. Association of childhood asthma with intra-day and inter-day temperature variability in Shanghai, China. ENVIRONMENTAL RESEARCH 2022; 204:112350. [PMID: 34762926 DOI: 10.1016/j.envres.2021.112350] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 09/28/2021] [Accepted: 11/03/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVES Short-term temperature variability (TV) is associated with the exacerbation of asthma, but little is known about the relative effects of intra- and inter-day TV. We aimed to assess the relative impacts of intra- and inter-day TV on childhood asthma and to explore the modification effects by season. METHODS A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was adopted to evaluate the nonlinear and lagged effects of TV on childhood asthma in Shanghai from 2009 to 2017. Intra- and inter-day TV was measured with diurnal temperature range (DTR) and temperature changes between neighboring days (TCN), respectively. RESULTS Increased DTR was associated with the elevated relative risk (RR) of daily outpatient visits for childhood asthma (DOVCA) in both the whole year (RRlag0-14 for the 99th percentile: 1.264, 95% confidence interval (CI): 1.052, 1.518) and cold season (RRlag0-12 for the 99th percentile: 1.411, 95% CI: 1.053, 1.889). Higher TCN in the warm season was associated with the increased RR of DOVCA (RRlag0-14 for the 99th percentile: 2.964, 95% CI: 1.636, 5.373). The number and fraction of DOVCA attributed to an interquartile range (IQR) increase of TCN were higher than those attributed to DTR in both the whole year period and warm season. However, the number and fraction of DOVCA attributed to an IQR increase of DTR were greater than those attributed to TCN in the cold season. CONCLUSIONS Our results provide novel evidence that both intra- and inter-day TV might be a trigger of childhood asthma. Higher DTR appeared to have greater impacts on childhood asthma in the cold season while an increase in TCN seemed to have bigger effects in the warm season.
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Affiliation(s)
- Yabin Hu
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jian Cheng
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, Hefei, China
| | - Yong Yin
- Department of Respiratory Medicine, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Shijian Liu
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jianguo Tan
- Shanghai Key Laboratory of Meteorology and Health (Shanghai Meteorological Service), Shanghai, China
| | - Shenghui Li
- School of Public Health, Shanghai Jiao Tong University, Shanghai, China
| | - Meiqin Wu
- MOE-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chonghuai Yan
- MOE-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guangjun Yu
- Center for Biomedical Informatics, Shanghai Children's Hospital, Shanghai, China
| | - Yi Hu
- Center for Biomedical Informatics, Shanghai Children's Hospital, Shanghai, China
| | - Shilu Tong
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.
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Huang J, Yang X, Fan F, Hu Y, Wang X, Zhu S, Ren G, Wang G. Outdoor air pollution and the risk of asthma exacerbations in single lag0 and lag1 exposure patterns: a systematic review and meta-analysis. J Asthma 2021; 59:2322-2339. [PMID: 34809505 DOI: 10.1080/02770903.2021.2008429] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Objective: To synthesize evidence regarding the relationship between outdoor air pollution and risk of asthma exacerbations in single lag0 and lag1 exposure patterns.Methods: We performed a systematic literature search using PubMed, Embase, Cochrane Library, Web of Science, ClinicalTrials, China National Knowledge Internet, Chinese BioMedical, and Wanfang databases. Articles published until August 1, 2020 and the reference lists of the relevant articles were reviewed. Two authors independently evaluated the eligible articles and performed structured extraction of the relevant information. Pooled relative risks (RRs) and 95% confidence intervals (CIs) of lag0 and lag1 exposure patterns were estimated using random-effect models.Results: Eighty-four studies met the eligibility criteria and provided sufficient information for meta-analysis. Outdoor air pollutants were associated with increased risk of asthma exacerbations in both single lag0 and lag1 exposure patterns [lag0: RR (95% CI) (pollutants), 1.057(1.011, 1.103) (air quality index, AQI), 1.007 (1.005, 1.010) (particulate matter of diameter ≤ 2.5 μm, PM2.5), 1.009 (1.005, 1.012) (particulate matter of diameter, PM10), 1.010 (1.006, 1.014) (NO2), 1.030 (1.011, 1.048) (CO), 1.005 (1.002, 1.009) (O3); lag1:1.064(1.022, 1.106) (AQI), 1.005 (1.002, 1.008) (PM2.5), 1.007 (1.004, 1.011) (PM10), 1.008 (1.004, 1.012) (NO2), 1.025 (1.007, 1.042) (CO), 1.010 (1.006, 1.013) (O3)], except SO2 [lag0: RR (95% CI), 1.004 (1.000, 1.007); lag1: RR (95% CI), 1.003 (0.999, 1.006)]. Subgroup analyses revealed stronger effects in children and asthma exacerbations associated with other events (including symptoms, lung function changes, and medication use).Conclusion: Outdoor air pollution increases the asthma exacerbation risk in single lag0 and lag1 exposure patterns.Trial registration: PROSPERO, CRD42020204097. https://www.crd.york.ac.uk/.Supplemental data for this article is available online at https://doi.org/10.1080/02770903.2021.2008429 .
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Affiliation(s)
- Junjun Huang
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Xiaoyu Yang
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Fangfang Fan
- Department of Cardiology, Peking University First Hospital, Beijing, China
| | - Yan Hu
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Xi Wang
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Sainan Zhu
- Department of Biostatistics, Peking University First Hospital, Beijing, China
| | - Guanhua Ren
- Department of Library, Peking University First Hospital, Beijing, China
| | - Guangfa Wang
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
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Liu Z, Wang S, Zhang Y, Xiang J, Tong MX, Gao Q, Zhang Y, Sun S, Liu Q, Jiang B, Bi P. Effect of temperature and its interactions with relative humidity and rainfall on malaria in a temperate city Suzhou, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:16830-16842. [PMID: 33394450 DOI: 10.1007/s11356-020-12138-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Accepted: 12/16/2020] [Indexed: 06/12/2023]
Abstract
Malaria is a climate-sensitive infectious disease. Many ecological studies have investigated the independent impacts of ambient temperature on malaria. However, the optimal temperature measures of malaria and its interaction with other meteorological factors on malaria transmission are less understood. This study aims to investigate the effect of ambient temperature and its interactions with relative humidity and rainfall on malaria in Suzhou, a temperate climate city in Anhui Province, China. Weekly malaria and meteorological data from 2005 to 2012 were obtained for Suzhou. A distributed lag nonlinear model was conducted to quantify the effect of different temperature measures on malaria. The best measure was defined as that with the minimum quasi-Akaike information criterion. GeoDetector and Poisson regression models were employed to quantify the interactions of temperature, relative humidity, and rainfall on malaria transmission. A total of 13,382 malaria cases were notified in Suzhou from 2005 to 2012. Each 5 °C rise in average temperature over 10 °C resulted in a 22% (95% CI: 17%, 28%) increase in malaria cases at lag of 4 weeks. In terms of cumulative effects from lag 1 to 8 weeks, each 5 °C increase over 10 °C caused a 175% growth in malaria cases (95% CI: 139%, 216%). Average temperature achieved the best performance in terms of model fitting, followed by minimum temperature, most frequent temperature, and maximum temperature. Temperature had an interactive effect on malaria with relative humidity and rainfall. High temperature together with high relative humidity and high rainfall could accelerate the transmission of malaria. Meteorological factors may affect malaria transmission interactively. The research findings could be helpful in the development of weather-based malaria early warning system, especially in the context of climate change for the prevention of possible malaria resurgence.
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Affiliation(s)
- Zhidong Liu
- Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan City, Shandong Province, People's Republic of China
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
| | - Shuzi Wang
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China
| | - Ying Zhang
- School of Public Health, China Studies Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Jianjun Xiang
- School of Public Health, Fujian Medical University, Fuzhou, People's Republic of China
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Michael Xiaoliang Tong
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Qi Gao
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China
| | - Yiwen Zhang
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China
| | - Shuyue Sun
- National Meteorological Center, China Meteorological Administration, Beijing, People's Republic of China
| | - Qiyong Liu
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People's Republic of China
| | - Baofa Jiang
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China.
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China.
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
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Hu Y, Cheng J, Jiang F, Liu S, Li S, Tan J, Yin Y, Tong S. Season-stratified effects of meteorological factors on childhood asthma in Shanghai, China. ENVIRONMENTAL RESEARCH 2020; 191:110115. [PMID: 32846175 DOI: 10.1016/j.envres.2020.110115] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 07/19/2020] [Accepted: 08/14/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVES There has been increasing interest in identifying the adverse effects of ambient environmental factors on asthma exacerbations (AE), but season-stratified effects of meteorological factors on childhood asthma remain unclear. We explored the season-stratified effects of meteorological factors on childhood AE in Shanghai, China. METHODS Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to examine the lagged and nonlinear effects of meteorological factors on childhood AE after adjustment for putative confounders. We also performed a season-stratified analysis to determine whether the season modified the relationship between meteorological factors and childhood AE. RESULTS There were 23,103 emergency department visits (EDVs) for childhood AE, including 15,466 boys and 7637 girls during 2008-2017. Most meteorological factors (e.g., temperature, diurnal temperature range (DTR), relative humidity (RH) and wind speed (WS)) were significantly associated with EDVs for childhood AE, even after adjustment for the confounding effects of air pollutants. In the whole year, extreme cold, moderate heat, higher DTR, lower RH and WS increased the relative risk (RR) for childhood AE. In the cold season, lower RH and wind speed increased the risks of childhood AE (RRlag0-28 for the 5th percentile (p5) of RH: 9.744, 95% CI: 3.567, 26.616; RRlag0-28 for the p5 of wind speed: 10.671, 95% CI: 1.096, 103.879). In the warm season, higher temperature and DTR, lower RH and WS increased the RR for childhood AE (RRlag0-5 for the p95 of temperature: 1.871, 95% CI: 1.246, 2.810; RRlag0-2 for the p95 of DTR: 1.146, 95% CI: 1.010, 1.300; RRlag0-5 for the p5 of RH: 1.931, 95% CI: 1.191, 3.128; RRlag0-2 for the p5 of WS: 1.311, 95% CI: 1.005, 1.709). CONCLUSIONS Extreme meteorological factors appeared to be triggers of EDVs for childhood AE in Shanghai and the effects modified by season. These findings provide evidence for developing season-specific and tailored strategies to prevent and control childhood AE.
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Affiliation(s)
- Yabin Hu
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jian Cheng
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Fan Jiang
- Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institution, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shijian Liu
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shenghui Li
- School of Public Health, Shanghai Jiaotong University, Shanghai, China
| | - Jianguo Tan
- Shanghai Key Laboratory of Meteorology and Health (Shanghai Meteorological Service), Shanghai, China
| | - Yong Yin
- Department of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
| | - Shilu Tong
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China; School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
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