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Lee EY, Park S, Kim YB, Lee M, Lim H, Ross-White A, Janssen I, Spence JC, Tremblay MS. Exploring the Interplay Between Climate Change, 24-Hour Movement Behavior, and Health: A Systematic Review. J Phys Act Health 2024; 21:1227-1245. [PMID: 39187251 DOI: 10.1123/jpah.2023-0637] [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: 10/23/2023] [Revised: 07/03/2024] [Accepted: 07/03/2024] [Indexed: 08/28/2024]
Abstract
BACKGROUND Given the emergence of climate change and health risks, this review examined potential relationships between varying indicators of climate change, movement behaviors (ie, physical activity [PA], sedentary behavior, and sleep), and health. METHODS Seven databases were searched in March 2020, April 2023, and April 2024. To be included, studies must have examined indicators of climate change and at least one of the movement behaviors as either an exposure or a third variable (ie, mediator/moderator), and a measure of health as outcome. Evidence was summarized by the role (mediator/moderator) that either climate change or movement behavior(s) has with health measures. Relationships and directionality of each association, as well as the strength and certainty of evidence were synthesized. RESULTS A total of 79 studies were eligible, representing 6,671,791 participants and 3137 counties from 25 countries (40% low- and middle-income countries). Of 98 observations from 17 studies that examined PA as a mediator, 34.7% indicated that PA mediated the relationship between climate change and health measure such that indicators of adverse climate change were associated with lower PA, and worse health outcome. Of 274 observations made from 46 studies, 28% showed that PA favorably modified the negative association between climate change and health outcome. Evidence was largely lacking and inconclusive for sedentary behavior and sleep, as well as climate change indicators as an intermediatory variable. CONCLUSIONS PA may mitigate the adverse impact of climate change on health. Further evidence is needed to integrate PA into climate change mitigation, adaptation, and resilience strategies.
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Affiliation(s)
- Eun-Young Lee
- School of Kinesiology and Health Studies, Queen's University, Kingston, ON, Canada
- Department of Gender Studies, Queen's University, Kingston, ON, Canada
- Children's Hospital of Eastern Ontario Research Institute, Ottawa,ON, Canada
- Institute of Sport Science, Seoul National University, Seoul, South Korea
| | - Seiyeong Park
- School of Kinesiology and Health Studies, Queen's University, Kingston, ON, Canada
- Institute of Sport Science, Seoul National University, Seoul, South Korea
| | - Yeong-Bae Kim
- Faculty of Kinesiology, Sport, and Recreation, University of Alberta, Edmonton, AB, Canada
| | - Mikyung Lee
- School of Kinesiology and Health Studies, Queen's University, Kingston, ON, Canada
| | - Heejun Lim
- School of Kinesiology and Health Studies, Queen's University, Kingston, ON, Canada
| | - Amanda Ross-White
- Bracken Health Sciences Library, Queen's University, Kingston, ON, Canada
| | - Ian Janssen
- School of Kinesiology and Health Studies, Queen's University, Kingston, ON, Canada
- Department of Health Sciences, Queen's University, Kingston, ON, Canada
| | - John C Spence
- Faculty of Kinesiology, Sport, and Recreation, University of Alberta, Edmonton, AB, Canada
| | - Mark S Tremblay
- Children's Hospital of Eastern Ontario Research Institute, Ottawa,ON, Canada
- Department of Pediatrics, University of Ottawa, Ottawa, ON, Canada
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Park H, Kim SY, Jang H, Ha YW, Yun YM, Kim KJ, Rhee Y, Kim HC, Kim CO, Cho J. Impact of physical activity levels on the association between air pollution exposures and glycemic indicators in older individuals. Environ Health 2024; 23:87. [PMID: 39425159 PMCID: PMC11488365 DOI: 10.1186/s12940-024-01125-8] [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: 06/10/2024] [Accepted: 09/30/2024] [Indexed: 10/21/2024]
Abstract
BACKGROUND Air pollution may exacerbate diabetes-related indicators; however, the longitudinal associations between air pollutant concentrations and glycemic markers remain unclear. In this prospective cohort study, we examined the longitudinal associations between air pollution and glycemic indicators among older individuals with normoglycemia at baseline and determined whether these associations differed according to changes in physical activity levels. METHODS Overall, 1,856 participants (mean age, 70.9 years) underwent baseline and 4-year follow-up surveys. We used linear mixed-effect models to examine the associations between previous 1-year exposures to air pollutants and glycemic indicators. We further investigated associations between previous 5-year exposures to air pollutants and glycemic indicators after the inverse probability of treatment weighting (IPTW). We explored effect modifications by the level of physical activity maintenance and changes in metabolic equivalent of task (METs) for physical activity. RESULTS Levels of particulate matter with aerodynamic diameters ≤ 10 μm (PM10) and ≤ 2.5 μm, and nitrogen dioxide (NO2) were significantly associated with increased fasting blood glucose, Hemoglobin A1c, insulin, and homeostatic model assessment for insulin resistance (HOMA-IR) values. After IPTW, the associations remained significant for PM10 and NO2. The positive associations of NO2 with insulin and HOMA-IR remained significant in the maintained inactive group, but not in the maintained moderate-to-vigorous active group. The positive associations of PM10 or NO2 with insulin and HOMA-IR remained significant in the group with increased METs, but not in those with decreased METs. In the post-hoc analysis of non-linear relationships between an increase in METs and glycemic indicators, insulin and HOMA-IR remarkably increased in the higher PM10 and NO2 exposure group from the point of 12,000 and 13,500 METs-min/week increase, respectively. CONCLUSIONS We demonstrated longitudinal associations between air pollution exposures and increased insulin resistance in older individuals. Maintaining moderate-to-vigorous physical activity may mitigate the adverse effects of air pollution on insulin resistance. In older individuals dwelling in highly polluted areas, an increase of less than 12,000 METs-min/week may be beneficial for insulin resistance.
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Affiliation(s)
- Hyunji Park
- Department of Public Health, Graduate School, Yonsei University, Seoul, Republic of Korea
| | - Sun Young Kim
- Department of Cancer Control and Population Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Republic of Korea
| | - Heeseon Jang
- Department of Preventive Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea
| | - Yae Won Ha
- Department of Public Health, Graduate School, Yonsei University, Seoul, Republic of Korea
| | - Young Mi Yun
- Division of Geriatrics, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Kwang Joon Kim
- Division of Geriatrics, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yumie Rhee
- Endocrine Research Institute, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hyeon Chang Kim
- Department of Preventive Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea
| | - Chang Oh Kim
- Division of Geriatrics, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Jaelim Cho
- Department of Preventive Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.
- Institute for Environmental Research, Yonsei University College of Medicine, Seoul, Republic of Korea.
- Institute of Human Complexity and Systems Science, Yonsei University, Incheon, Republic of Korea.
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Li Q, Liu F, Huang K, Liang F, Shen C, Liao J, Li J, Yuan C, Yang X, Cao J, Chen S, Hu D, Huang J, Liu Y, Lu X, Gu D. Physical activity, long-term fine particulate matter exposure and type 2 diabetes incidence: A prospective cohort study. Chronic Dis Transl Med 2024; 10:205-215. [PMID: 39027196 PMCID: PMC11252432 DOI: 10.1002/cdt3.128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 05/14/2024] [Accepted: 05/14/2024] [Indexed: 07/20/2024] Open
Abstract
Background Despite the adverse effects of ambient fine particulate matter (PM2.5) on type 2 diabetes and the beneficial role of physical activity (PA), the influence of PM2.5 on the relationship between PA and type 2 diabetes remains unclear. Methods In this prospective study with 71,689 participants, PA was assessed by a questionnaire and was categorized into quartiles for volume and three groups for intensity. Long-term PM2.5 exposure was calculated using 1-km resolution satellite-based PM2.5 estimates. PM2.5 exposure and PA's effect on type 2 diabetes were assessed by cohort-stratified Cox proportional hazards models, individually and in combination. Results In 488,166 person-years of follow-up, 5487 incident type 2 diabetes cases were observed. The association between PA and type 2 diabetes was modified by PM2.5. Compared with the lowest quartile of PA volume, the highest quartile was associated with reduced type 2 diabetes risk in low PM2.5 stratification (≤65.02 µg/m3) other than in high PM2.5 stratification (>65.02 µg/m3), with the hazard ratio (HR) of 0.75 (95% confidence interval [CI]: 0.66-0.85) and 1.10 (95% CI: 0.99-1.22), respectively. Similar results were observed for PA intensity. High PM2.5 exposure combined with the highest PA levels increased the risk of type 2 diabetes the most (HR = 1.79, 95% CI: 1.59-2.01 for PA volume; HR = 1.82, 95% CI: 1.64-2.02 for PA intensity). Conclusion PA could reduce type 2 diabetes risk in low-pollution areas, but high PM2.5 exposure may weaken or even reverse the protective effects of PA. Safety and health benefits of PA should be thoroughly assessed for long-term polluted residents.
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Affiliation(s)
- Qian Li
- Department of Epidemiology, Center for Global Health, School of Public HealthNanjing Medical UniversityNanjingJiangsuChina
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Fangchao Liu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
| | - Keyong Huang
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
| | - Fengchao Liang
- School of Public Health and Emergency ManagementSouthern University of Science and TechnologyShenzhenGuangdongChina
| | - Chong Shen
- Department of Epidemiology, Center for Global Health, School of Public HealthNanjing Medical UniversityNanjingJiangsuChina
- Research Units of Cohort Study on Cardiovascular Diseases and CancersChinese Academy of Medical SciencesBeijingChina
| | - Jian Liao
- School of Public Health and Emergency ManagementSouthern University of Science and TechnologyShenzhenGuangdongChina
| | - Jianxin Li
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
| | - Chenxi Yuan
- Department of Epidemiology, Center for Global Health, School of Public HealthNanjing Medical UniversityNanjingJiangsuChina
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Xueli Yang
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Department of Occupational and Environmental Health, School of Public HealthTianjin Medical UniversityTianjinChina
| | - Jie Cao
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
| | - Shufeng Chen
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public HealthZhengzhou UniversityZhengzhouHenanChina
- Department of Epidemiology and Health Statistics, School of Public HealthShenzhen University Health Science CenterShenzhenGuangdongChina
| | - Jianfeng Huang
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
| | - Yang Liu
- Gangarosa Department of Environmental Health, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
| | - Xiangfeng Lu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
| | - Dongfeng Gu
- Department of Epidemiology, Center for Global Health, School of Public HealthNanjing Medical UniversityNanjingJiangsuChina
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
- School of Public Health and Emergency ManagementSouthern University of Science and TechnologyShenzhenGuangdongChina
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Wang H, Li J, Liu Q, Zhang Y, Wang Y, Li H, Sun L, Hu B, Zhang D, Liang C, Lei J, Wang P, Sheng J, Tao F, Chen G, Yang L. Physical activity attenuates the association of long-term exposure to nitrogen dioxide with sleep quality and its dimensions in Chinese rural older adults. J Affect Disord 2024; 349:187-196. [PMID: 38199389 DOI: 10.1016/j.jad.2024.01.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 12/05/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
BACKGROUND Joint impacts of air pollution and physical activity (PA) on sleep quality remain unaddressed. We aimed to investigate whether PA attenuates the association of long-term exposure to nitrogen dioxide (NO2) with sleep quality and its dimensions in older adults. METHODS This study included 3408 Chinese rural older adults. Annual NO2 was estimated using the Space-Time Extra-Trees model. PA was assessed by International Physical Activity Questionnaire. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI) scale. Linear regression models were used to assess the associations of long-term NO2 exposure and PA with sleep quality and its dimensions, and interaction plots were used to depict the attenuating effect of PA on associations of NO2 with sleep quality and its dimensions. RESULTS Three-year (3-y) average NO2 (per 0.64-μg/m3 increment) was positively associated with global PSQI (β = 0.41, 95 % CI: 0.23, 0.59), sleep duration (β = 0.16, 95 % CI: 0.11, 0.21), and habitual sleep efficiency (β = 0.22, 95 % CI: 0.17, 0.27), while PA was negatively associated with global PSQI (β = -0.33, 95 % CI: -0.46, -0.20) and five domains of PSQI other than sleep duration and sleep disturbances. The associations of NO2 with global PSQI, sleep duration, and habitual sleep efficiency were attenuated with increased PA (Pinteraction were 0.037, 0.020, and 0.079, respectively). CONCLUSIONS PA attenuates the adverse impacts of long-term NO2 exposure on sleep quality, especially on sleep duration, and habitual sleep efficiency, in Chinese rural elderly people. Participating in PA should be encouraged in this population, and continued efforts are still needed to reduce air pollution.
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Affiliation(s)
- Hongli Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Center for Big Data and Population Health of IHM, Hefei 230032, Anhui, China
| | - Junzhe Li
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Center for Big Data and Population Health of IHM, Hefei 230032, Anhui, China
| | - Qiang Liu
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Center for Big Data and Population Health of IHM, Hefei 230032, Anhui, China
| | - Yan Zhang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China
| | - Yuan Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China
| | - Huaibiao Li
- Fuyang Center for Diseases Prevention and Control, Fuyang 236069, Anhui, China
| | - Liang Sun
- Fuyang Center for Diseases Prevention and Control, Fuyang 236069, Anhui, China
| | - Bing Hu
- Fuyang Center for Diseases Prevention and Control, Fuyang 236069, Anhui, China
| | - Dongmei Zhang
- School of Health Services Management, Anhui Medical University, Hefei 230032, Anhui, China
| | - Chunmei Liang
- School of Public Health, Department of Hygiene Inspection and Quarantine, Anhui Medical University, Hefei 230032, Anhui, China
| | - Jingyuan Lei
- School of Public Health, Department of Hygiene Inspection and Quarantine, Anhui Medical University, Hefei 230032, Anhui, China
| | - Panpan Wang
- School of Public Health, Department of Hygiene Inspection and Quarantine, Anhui Medical University, Hefei 230032, Anhui, China
| | - Jie Sheng
- Scientific Research Center in Preventive Medicine, School of Public Health, Anhui Medical University, Hefei 230032, Anhui, China
| | - Fangbiao Tao
- Anhui Provincial Key Laboratory of Population Health and Aristogenics, Hefei 230032, Anhui, China
| | - Guimei Chen
- School of Health Services Management, Anhui Medical University, Hefei 230032, Anhui, China
| | - Linsheng Yang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Center for Big Data and Population Health of IHM, Hefei 230032, Anhui, China.
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Guo T, Cheng X, Wei J, Chen S, Zhang Y, Lin S, Deng X, Qu Y, Lin Z, Chen S, Li Z, Sun J, Chen X, Chen Z, Sun X, Chen D, Ruan X, Tuohetasen S, Li X, Zhang M, Sun Y, Zhu S, Deng X, Hao Y, Jing Q, Zhang W. Unveiling causal connections: Long-term particulate matter exposure and type 2 diabetes mellitus mortality in Southern China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 274:116212. [PMID: 38489900 DOI: 10.1016/j.ecoenv.2024.116212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 03/09/2024] [Accepted: 03/11/2024] [Indexed: 03/17/2024]
Abstract
Evidence of the potential causal links between long-term exposure to particulate matters (PM, i.e., PM1, PM2.5, and PM1-2.5) and T2DM mortality based on large cohorts is limited. In contrast, the existing evidence usually suffers from inherent bias with the traditional association assessment. A prospective cohort of 580,757 participants in the southern region of China were recruited during 2009 and 2015 and followed up through December 2020. PM exposure at each residential address was estimated by linking to the well-established high-resolution simulation dataset. Hazard ratios (HRs) were calculated using time-varying marginal structural Cox models, an established causal inference approach, after adjusting for potential confounders. During follow-up, a total of 717 subjects died from T2DM. For every 1 μg/m3 increase in PM2.5, the adjusted HRs and 95% confidence interval (CI) for T2DM mortality was 1.036 (1.019-1.053). Similarly, for every 1 μg/m3 increase in PM1 and PM1-2.5, the adjusted HRs and 95% CIs were 1.032 (1.003-1.062) and 1.085 (1.054-1.116), respectively. Additionally, we observed a generally more pronounced impact among individuals with lower levels of education or lower residential greenness which as measured by the Normalized Difference Vegetation Index (NDVI). We identified substantial interactions between NDVI and PM1 (P-interaction = 0.003), NDVI and PM2.5 (P-interaction = 0.019), as well as education levels and PM1 (P-interaction = 0.049). The study emphasizes the need to consider environmental and socio-economic factors in strategies to reduce T2DM mortality. We found that PM1, PM2.5, and PM1-2.5 heighten the peril of T2DM mortality, with education and green space exposure roles in modifying it.
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Affiliation(s)
- Tong Guo
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xi Cheng
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland 20740, USA
| | - Shirui Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Shao Lin
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA
| | - Xinlei Deng
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Yanji Qu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangdong, China
| | - Ziqiang Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China
| | - Shimin Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Jie Sun
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xudan Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Zhibing Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xurui Sun
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Dan Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xingling Ruan
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Shaniduhaxi Tuohetasen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xinyue Li
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Man Zhang
- Department of nosocomial infection management, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Yongqing Sun
- Department of Ultrasound, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Shuming Zhu
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xueqing Deng
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China.
| | - Qinlong Jing
- Guangzhou Municipal Health Commission, Guangzhou, China.
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.
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6
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Chen S, Zhang Y, Wang Y, Lawrence WR, Rhee J, Guo T, Chen S, Du Z, Wu W, Li Z, Wei J, Hao Y, Zhang W. Long-term particulate matter exposure and the risk of neurological hospitalization: Evidence from causal inference of a large longitudinal cohort in South China. CHEMOSPHERE 2023; 345:140397. [PMID: 37838030 PMCID: PMC10841469 DOI: 10.1016/j.chemosphere.2023.140397] [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: 06/29/2023] [Revised: 09/12/2023] [Accepted: 10/08/2023] [Indexed: 10/16/2023]
Abstract
With limited evidence on the neurological impact of particulate matter (PM) exposure in China, particularly for PM1 which is smaller but more toxic, we conducted a large Chinese cohort study using causal inference approaches to comprehensively clarify such impact. A total of 36,271 participants in southern China were recruited in 2015 and followed up through 2020. We obtained the neurological hospitalizations records by linking the cohort data to the electronic reports from 418 medical institutions across the study area. By using high-resolution PM concentrations from satellite-based spatiotemporal models and the cohort data, we performed marginal structural Cox models under causal assumptions to assess the potential causal links between time-varying PM exposure and neurological hospitalizations. Our findings indicated that increasing PM1, PM2.5, and PM10 concentrations by 1 μg/m³ were associated with higher overall neurological hospitalization risks, with hazard ratios (HRs) of 1.10 (95% confidence interval (CI) 1.04-1.16), 1.09 (95% CI 1.04-1.14), and 1.03 (95% CI 1.00-1.06), respectively. PM1 appeared to have a stronger effect on neurological hospitalization, with a 1% and 7% higher impact compared to PM2.5 and PM10, respectively. Additionally, each 1-μg/m3 increase in the annual PM1 concentration was associated with an elevated risk of hospitalizations for ischemic stroke (HR: 1.15; 95% CI, 1.06-1.26), which tended to be larger than the estimates for PM2.5 (HR: 1.13, 95% CI, 1.04-1.23) and PM10 (HR: 1.05, 95% CI, 1.00-1.09). Furthermore, never-married or female individuals tended be at a greater risk compared with their counterparts. Our study provides important insights into the health impact of particles, particularly smaller particles, on neurological hospitalization risk and highlights the need for clean-air policies that specifically target these particles.
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Affiliation(s)
- Shimin Chen
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Ying Wang
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wayne R Lawrence
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States
| | - Jongeun Rhee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States
| | - Tong Guo
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Shirui Chen
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wenjing Wu
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, China.
| | - Wangjian Zhang
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China.
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Peng H, Wang M, Wang S, Wang X, Fan M, Qin X, Wu Y, Chen D, Li J, Hu Y, Wu T. KCNQ1 rs2237892 polymorphism modify the association between short-term ambient particulate matter exposure and fasting blood glucose: A family-based study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 876:162820. [PMID: 36921852 DOI: 10.1016/j.scitotenv.2023.162820] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 03/08/2023] [Accepted: 03/08/2023] [Indexed: 05/10/2023]
Abstract
BACKGROUND The association between particulate matter and fasting blood glucose (FBG) has shown conflicting results. Genome-wide association studies have shown that KCNQ1 rs2237892 polymorphism is associated with the risk of diabetes. Whether KCNQ1 rs2237892 polymorphism might modify the association between particulate matter and FBG is still uncertain. METHODS Data collected from a family-based cohort study in Northern China, were used to perform the analysis. A generalized additive Gaussian model was used to examine the short-term effects of air pollutants on FBG. We further conducted interaction analyses by including a cross-product term of air pollutants by rs2237892 within KCNQ1 gene. RESULTS A total of 4418 participants were included in the study. In the single pollutant model, the FBG level increased 0.0031 mmol/L with per 10 μg/m3 elevation in fine particular matter (PM2.5) for lag 0 day. After additional adjustments for nitrogen dioxide (NO2) and sulfur dioxide (SO2), similar results were observed for lag 0-2 days. As for particulate matter with particle size below 10 μm (PM10), the significant association between the daily average concentration of the pollutant and FBG level was observed for lag 0-3 days. Additionally, rs2237892 in KCNQ1 gene modified the association between PM and FBG level. The higher risk of FBG levels associated with elevations in PM10 and PM2.5 were more evident as the number of risk allele C increased. Individuals with a CC genotype had the highest risk of elevation in FBG levels. CONCLUSION Short-term exposures to PM2.5 and PM10 were associated with higher FBG levels. Additionally, rs2237892 in KCNQ1 gene might modify the association between the air pollutants and FBG levels.
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Affiliation(s)
- Hexiang Peng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Mengying Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Siyue Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Xueheng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Meng Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Xueying Qin
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Yiqun Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Dafang Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Jing Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Yonghua Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Tao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
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Jiang H, Zhang S, Yao X, Meng L, Lin Y, Guo F, Yang D, Jin M, Wang J, Tang M, Chen K. Does physical activity attenuate the association between ambient PM 2.5 and physical function? THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 874:162501. [PMID: 36863583 DOI: 10.1016/j.scitotenv.2023.162501] [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: 12/21/2022] [Revised: 02/21/2023] [Accepted: 02/23/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Physical function (PF), such as muscle strength, performing daily activities, has gradually declined with the increase of age, causing the occurrence of disability and diseases burden. Air pollution exposure and physical activity (PA) were both linked to PF. We aimed to explore the individual and joint effects of particulate matter <2.5 μm (PM2.5) and PA on PF. METHODS A total of 4537 participants and 12,011 observations aged ≥45 years old from the China Health and Retirement Longitudinal Study (CHARLS) cohort from 2011 to 2015 were included into the study. PF was assessed by a combined score of four tests, including grip strength, walking speed, sense of balance, and chair standing tests. Air pollution exposure data was from The ChinaHighAirPollutants (CHAP) dataset. The annual PM2.5 exposure for each individual was estimated based on county-level resident addresses. We estimated the volume of moderate-to-vigorous physical activity (MVPA) by quoting metabolic equivalent (MET). Multivariate linear model was conducted for baseline analysis, and linear mixed model with random participant intercepts was constructed for cohort longitudinal analysis. RESULTS PM2.5 was negatively associated with PF, while PA was positively associated with PF in baseline analysis. In cohort longitudinal analysis, a 10 μg/m3 increase in PM2.5 was associated to a 0.025 point (95 % CI: -0.047, -0.003) decrease in PF score, and a 10-MET-h/week increase in PA was related to a 0.004 point (95 % CI: 0.001, 0.008) increase in PF score. The association between PM2.5 and PF decreased by increased PA intensity, and PA reversed the detrimental effects between PM2.5 and PF. CONCLUSION PA attenuated the association of air pollution with PF at both high and low levels of air pollution, implying that PA may be an effective behavior to reduce the adverse effects of poor air quality on PF.
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Affiliation(s)
- Haiyan Jiang
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Simei Zhang
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Xuecheng Yao
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Lin Meng
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Yaoyao Lin
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Fanjia Guo
- Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Dandan Yang
- Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Mingjuan Jin
- Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Jianbing Wang
- Department of Public Health, National Clinical Research Center for Child Health of Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Mengling Tang
- Department of Public Health, Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China.
| | - Kun Chen
- Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China.
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Li C, Ning G, Xia Y. Does exercise participation promote happiness?: Mediations and heterogeneities. Front Public Health 2023; 11:1033157. [PMID: 36969647 PMCID: PMC10036593 DOI: 10.3389/fpubh.2023.1033157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 02/24/2023] [Indexed: 03/12/2023] Open
Abstract
This paper uses a nationally representative and large-scale dataset from China to empirically examine the relationship between exercise participation and happiness. To address the problem of reverse causality between the two factors, the instrumental variable (IV) approach is used to deal with endogeneity to some extent. It is demonstrated that higher frequencies of exercise participation are positively related to happiness. Findings also demonstrate that physical exercise could significantly decrease depressive disorders, improves self-rated health conditions and reduces the frequency of health problems affecting people's work and life. At the same time, all of above health factors significantly influence subjective wellbeing. When these health variables are included in regressions, the correlation between exercise participation and happiness declines. This confirms that physical activity helps to improve happiness by enhancing mental and overall health conditions. In addition, results show that physical activities are more prominently related to happiness for male, older and unmarried individuals and those living in rural areas, lacking social security and with higher levels of depression as well as lower socioeconomic status. Furthermore, a series of robustness checks are carried out and exercise participation's positive role in improving happiness is further confirmed using different happiness measures and instrumental variables, various IV models, as well as penalized machine learning methods and placebo tests. With the increasing emphasis of improving happiness as an important goal in the global public health policy, findings of this paper have important policy implications for enhancing subjective wellbeing.
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Affiliation(s)
- Chao Li
- Business School, Shandong University, Weihai, China
- Chao Li
| | - Guangjie Ning
- Business School, Shandong University, Weihai, China
- *Correspondence: Guangjie Ning
| | - Yuxin Xia
- HSBC Business School, Peking University, Shenzhen, China
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Eating Spicy Food, Dietary Approaches to Stop Hypertension (DASH) Score, and Their Interaction on Incident Stroke in Southwestern Chinese Aged 30-79: A Prospective Cohort Study. Nutrients 2023; 15:nu15051222. [PMID: 36904221 PMCID: PMC10005455 DOI: 10.3390/nu15051222] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 02/16/2023] [Accepted: 02/20/2023] [Indexed: 03/04/2023] Open
Abstract
Little is known about the association between spicy food intake, dietary approaches to stop hypertension (DASH) score, and incident stroke. This study aimed to explore the association of eating spicy food, DASH score, and their interaction with stroke incidence. We included 22,160 Han residents aged 30-79 in southwest China from the China Multi-Ethnic Cohort. Three hundred and twelve cases were newly diagnosed with stroke by October 8, 2022, during a mean of 45.5 months of follow-up. Cox regression analyses showed that eating spicy food reduced stroke risk by 34% among people with low DASH scores (HR 0.66, 95%CI 0.45-0.97), while individuals with high DASH scores versus low DASH scores had a 46% lower stroke incidence among spicy food nonconsumers (HR 0.54, 95%CI 0.36-0.82). The HR of the multiplicative interactive term was 2.02 (95%CI 1.24-3.30) and the overall estimates of relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and the synergy index (S) were 0.54 (95%CI 0.24-0.83), 0.68 (95%CI 0.23-1.14), and 0.29 (95%CI 0.12-0.70), respectively. Consuming spicy food seems to be associated with lower stroke risk only in people who have a lower DASH score, while the beneficial effect of higher DASH scores seems to be found only among nonconsumers of spicy food, and a negative interaction may exist between them in southwestern Chinese aged 30-79. This study could provide scientific evidence for dietary guidance to reduce stroke risk.
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Andrade A, D’Oliveira A, De Souza LC, Bastos ACRDF, Dominski FH, Stabile L, Buonanno G. Effects of Air Pollution on the Health of Older Adults during Physical Activities: Mapping Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3506. [PMID: 36834200 PMCID: PMC9960154 DOI: 10.3390/ijerph20043506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/12/2023] [Accepted: 02/13/2023] [Indexed: 06/18/2023]
Abstract
Atmospheric pollutants present environmental threats to health and have been investigated in different environments, such as highways, squares, parks, and gyms. These environments are frequented by older adults, who are considered fragile to the harmful impacts of pollution present in the air. The aim was to analyze the state of the art on the effects of air pollution on the health of older adults during physical activities (PAs) through a mapping review. The search was performed in PubMed, Web of Science, Scopus, and Cinahl databases until June 2022. Of the 10,109 studies initially identified, 58 met the inclusion criteria. The most investigated health outcome was cardiovascular disease, followed by respiratory outcomes. Particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3) were the most investigated pollutants. Of the 75 health outcomes investigated, in 29, air pollution had harmful effects on the health of the older adults during the practice of PA, more frequently in cardiovascular diseases. In 25 outcomes, the beneficial effects of PA to the health of the older adults remained, despite exposure to high and low concentrations of pollutants, most often in terms of mental disorders. We conclude that poor air quality is a harmful factor for the health of older adults during the practice of PAs, more frequently in cardiovascular and respiratory diseases. On the other hand, for mental-health-related outcomes (depression and cognition), in most studies, the beneficial effects of PA in older adults were maintained, even after exposure to pollutants.
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Affiliation(s)
- Alexandro Andrade
- Health and Sports Science Center, Department of Physical Education, CEFID, Santa Catarina State University, Florianópolis 88035-901, Brazil
| | - Anderson D’Oliveira
- Health and Sports Science Center, Department of Physical Education, CEFID, Santa Catarina State University, Florianópolis 88035-901, Brazil
| | - Loiane Cristina De Souza
- Health and Sports Science Center, Department of Physical Education, CEFID, Santa Catarina State University, Florianópolis 88035-901, Brazil
| | | | - Fábio Hech Dominski
- Department of Physical Education, Univille University, Joinville 89219-710, Brazil
| | - Luca Stabile
- Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via Di Biasio 43, 03043 Cassino, Italy
| | - Giorgio Buonanno
- Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via Di Biasio 43, 03043 Cassino, Italy
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane 4001, Australia
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12
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Yu Z, Feng Y, Chen Y, Zhang X, Zhao X, Chang H, Zhang J, Gao Z, Zhang H, Huang C. Green space, air pollution and gestational diabetes mellitus: A retrospective cohort study in central China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 249:114457. [PMID: 38321676 DOI: 10.1016/j.ecoenv.2022.114457] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/08/2022] [Accepted: 12/19/2022] [Indexed: 02/08/2024]
Abstract
Emerging evidence suggests residential surrounding green space is beneficial for human health. The association between green space and GDM showed inconsistent results, and potential effect modification of green space with air pollution is still unclear. This study aims to evaluate the association between green space and GDM, and further explore potential interaction and medication effects. Participants were recruited from a retrospective cohort study between 2015 and 2020 in Henan, China. Residential green space based on normalized difference vegetation index (NDVI) and air pollution exposure were estimated using spatial-statistical models. Multivariate logistic regression was applied to evaluate the association between per 0.1 unit increase in NDVI with 4 buffer sizes (250 m, 500 m, 1000 m, 2000 m) and GDM. We examined potential interaction of green space and air pollutants on GDM. Mediating effects of air pollution associated with green space exposure on GDM were also investigated by causal mediation analyses. A total of 46,665 eligible pregnant women were identified. There were 4092 (8.8 %) women diagnosed with GDM according to the IADPSG criteria. We found that per 0.1-unit increment in NDVI250 m, NDVI500 m, NDVI1000 m and NDVI2000 m in second trimester were associated with the decreased risk of GDM, with adjusted OR of 0.921(95 %CI: 0.890-0.953), 0.922 (95 %CI: 0.891-0.953), 0.921 (95 %CI: 0.892-0.952) and 0.921 (95 %CI: 0.892-0.951), respectively. We identified significant interactions between second trimester PM2.5 and O3 exposure and NDVI for GDM (Pinteraction < 0.001). The causal mediation analysis showed that PM2.5 mediated approximately 2.5-5.5 % of the association between green space and GDM, while the estimated mediating effect of O3 was approximately 30.1-38.5 %. In conclusion, our study indicates that residential green space was associated with a reduced risk of GDM, particularly second trimester. Green space may benefit to GDM partly mediated by a reduction in PM2.5 and O3.
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Affiliation(s)
- Zengli Yu
- School of Public Health, Zhengzhou University, Zhengzhou, China; NHC Key Laboratory of Birth Defects Prevention & Henan Key Laboratory of Population Defects Prevention, Zhengzhou, China
| | - Yang Feng
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yao Chen
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoan Zhang
- The Third Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- The Third Hospital of Zhengzhou University, Zhengzhou, China
| | - Hui Chang
- The Third Hospital of Zhengzhou University, Zhengzhou, China
| | - Junxi Zhang
- NHC Key Laboratory of Birth Defects Prevention & Henan Key Laboratory of Population Defects Prevention, Zhengzhou, China
| | - Zhan Gao
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huanhuan Zhang
- School of Public Health, Zhengzhou University, Zhengzhou, China.
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
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