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Zheng J, Zhang H, Shi J, Li X, Zhang J, Zhang K, Gao Y, He J, Dai J, Wang J. Association of air pollution exposure with overweight or obesity in children and adolescents: A systematic review and meta-analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 910:168589. [PMID: 37984657 DOI: 10.1016/j.scitotenv.2023.168589] [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: 06/13/2023] [Revised: 11/12/2023] [Accepted: 11/13/2023] [Indexed: 11/22/2023]
Abstract
Childhood overweight and obesity is a global problem. 38 million children under five years old were reported as being overweight/obese in 2019. However, current evidence regarding the effects of air pollution on children weight status remains scarce and inconsistent. This study aimed to determine the association between air pollutants and the weight status of children and adolescents. Four databases were searched up to August 9, 2023. Adjusted merged odds ratios (ORs), regression coefficients (β), and their 95 % confidence intervals (95 % CIs) were calculated and pooled. A total of 27 studies were included. The results showed that air pollutants had adverse effects on the body weight of children and adolescents. Exposure to PM1, PM2.5, PMcoarse, and PM10 were associated with increased risk of overweight/obesity, with pooled ORs (95 % CI) of 1.23 (1.09, 1.40), 1.18 (1.10, 1.28), 1.04 (1.03, 1.05) and 1.11 (1.06, 1.17) per 10 μg/m3 increment, respectively. Individuals with higher exposure levels to NOX, O3, SO2 and CO (per 10 μg/m3 increment) were associated with 12 %, 6 %, 28 % and 1 % increased odds of being overweight/obese, respectively. With respect to the level of body mass index, the pooled β (95 % CIs) for each 10 μg/m3 increase in PM1, PM2.5, PM10, and NOX exposure were 0.15 (0.12, 0.18), 0.11 (0.06, 0.16), 0.07 (0.03, 0.10), and 0.03 (0.01, 0.04), respectively. PM1 has relatively strong adverse effects on body weight status. The subgroup analysis revealed a significantly increase in the risk of overweight/obesity when the concentrations of PM2.5, PM10, and NO2 exceeded 35 μg/m3, 50 μg/m3, and 40 μg/m3, respectively. Exposure to PM2.5, PM10 and NOX increased the risk of overweight/obesity, especially in Asia. This study provides evidence of the association between air pollution and being overweight/obese in children and adolescents.
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Affiliation(s)
- Jingying Zheng
- School of Public Health, Jilin University, Changchun 130021, China
| | - Huiling Zhang
- School of Public Health, Jilin University, Changchun 130021, China
| | - Jianyang Shi
- School of Public Health, Jilin University, Changchun 130021, China
| | - Xin Li
- School of Public Health, Jilin University, Changchun 130021, China
| | - Jing Zhang
- School of Public Health, Jilin University, Changchun 130021, China
| | - Kunlun Zhang
- School of Public Health, Jilin University, Changchun 130021, China
| | - Yameng Gao
- School of Public Health, Jilin University, Changchun 130021, China
| | - Jingtong He
- School of Public Health, Jilin University, Changchun 130021, China
| | - Jianghong Dai
- School of Public Health, Xinjiang Medical University, Xinjiang 834000, China
| | - Juan Wang
- School of Public Health, Jilin University, Changchun 130021, China.
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Tong Z, Zhang H, Yu J, Jia X, Hou X, Kong Z. Spatial-temporal evolution of overweight and obesity among Chinese adolescents from 2016 to 2020. iScience 2024; 27:108742. [PMID: 38230263 PMCID: PMC10790006 DOI: 10.1016/j.isci.2023.108742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 11/19/2023] [Accepted: 12/12/2023] [Indexed: 01/18/2024] Open
Abstract
This study examines the spatial-temporal evolution of overweight and obesity among Chinese adolescents aged 14-17. Data from five national surveys conducted between 2016 and 2020 were analyzed to determine distribution patterns and trends. Results showed that overweight and obesity exhibit spatial clustering, with greater severity in the north and less severity in the south. The issue has spread from the northeast to the southwest of Mainland China. Using a local autocorrelation model, the regions were divided into a northern disease cold spot area (Inner Mongolia) and a southern disease hot spot area (Guangxi). Over the past five years, overweight rates among Chinese adolescents have not been effectively curbed, but obesity has shown some success in control and reversal until 2019. Future efforts should focus on the spatial-temporal pattern of disease spread, targeting hotspot areas and abnormal values for regional synergy and precise prevention and control.
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Affiliation(s)
- Zihan Tong
- Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing 100084, China
| | - Hanyue Zhang
- Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing 100084, China
- Institute of Physical Education, Northeast Normal University, Changchun 130024, China
| | - Jingjing Yu
- Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing 100084, China
| | - Xiao Jia
- Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing 100084, China
| | - Xiao Hou
- Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing 100084, China
- School of Sport Science, Beijing Sport University, Beijing 100084, China
| | - Zhenxing Kong
- Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing 100084, China
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Guo LH, Zeeshan M, Huang GF, Chen DH, Xie M, Liu J, Dong GH. Influence of Air Pollution Exposures on Cardiometabolic Risk Factors: a Review. Curr Environ Health Rep 2023; 10:501-507. [PMID: 38030873 DOI: 10.1007/s40572-023-00423-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/20/2023] [Indexed: 12/01/2023]
Abstract
PURPOSE OF REVIEW The increasing prevalence of cardiometabolic risk factors (CRFs) contributes to the rise in cardiovascular disease. Previous research has established a connection between air pollution and both the development and severity of CRFs. Given the ongoing impact of air pollution on human health, this review aims to summarize the latest research findings and provide an overview of the relationship between different types of air pollutants and CRFs. RECENT FINDINGS CRFs include health conditions like diabetes, obesity, hypertension etc. Air pollution poses significant health risks and encompasses a wide range of pollutant types, air pollutants, such as particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O2). More and more population epidemiological studies have shown a positive correlation between air pollution and CRFs. Although various pollutants have diverse effects on specific cellular molecular pathways, their main influence is on oxidative stress, inflammation response, and impairment of endothelial function. More and more studies have proved that air pollution can promote the occurrence and development of cardiovascular and metabolic risk factors, and the research on the relationship between air pollution and CRFs has grown intensively. An increasing number of studies are using new biological monitoring indicators to assess the occurrence and development of CRFs resulting from exposure to air pollution. Abnormalities in some important biomarkers in the population (such as homocysteine, uric acid, and C-reactive protein) caused by air pollution deserve more attention. Further research is warranted to more fully understand the link between air pollution and novel CRF biomarkers and to investigate potential prevention and interventions that leverage the mechanistic link between air pollution and CRFs.
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Affiliation(s)
- Li-Hao Guo
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan 2Nd Road, Yuexiu District, Guangzhou, 510080, China
| | - Mohammed Zeeshan
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan 2Nd Road, Yuexiu District, Guangzhou, 510080, China
| | - Guo-Feng Huang
- Guangdong Ecological Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Duo-Hong Chen
- Guangdong Ecological Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Min Xie
- Guangdong Ecological Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Jun Liu
- Guangdong Ecological Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan 2Nd Road, Yuexiu District, Guangzhou, 510080, China.
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Zhang HZ, Wang DS, Wu SH, Huang GF, Chen DH, Ma HM, Zhang YT, Guo LH, Lin LZ, Gui ZH, Liu RQ, Hu LW, Yang JW, Zhang WJ, Dong GH. The association between childhood adiposity in northeast China and anthropogenic heat flux: A new insight into the comprehensive impact of human activities. Int J Hyg Environ Health 2023; 254:114258. [PMID: 37703624 DOI: 10.1016/j.ijheh.2023.114258] [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: 06/12/2023] [Revised: 08/13/2023] [Accepted: 09/06/2023] [Indexed: 09/15/2023]
Abstract
Anthropogenic heat has been reported to have significant health impacts, but research on its association with childhood adiposity is still lacking. In this study, we matched the 2008-2012 average anthropogenic heat flux, as simulated by a grid estimation model using inventory methods, with questionnaire and measurement data of 49,938 children randomly recruited from seven cities in Northeast China in 2012. After adjusting for social demographic and behavioral factors, we used generalized linear mixed-effect models to assess the association between anthropogenic heat flux and adiposity among children. We also examined the effect modification of various social demographic and behavioral confounders. We found that each 10 W/m2 increase in total anthropogenic heat flux and that from the industry source was associated with an increase of 5.82% (95% CI = 0.84%-11.05%) and 6.62% (95% CI = 0.87%-12.70%) in the odds of childhood adiposity. Similarly, the excess rate of adiposity among children were 5.26% (95% CI = -1.33%-12.29%) and 8.51% (95% CI = 2.24%-15.17%) per 1 W/m2 increase in the anthropogenic heat flux from transportation and buildings, and was 7.94% (95% CI = 2.28%-13.91%) per 0.001 W/m2 increase in the anthropogenic heat flux from human metabolism. We also found generally greater effect estimates among female children and children who were exposed to passive smoking during pregnancy, born by caesarean section, non-breastfed/mixed-fed, or lived within 20 m adjacent to the main road. The potential deleterious effect of anthropogenic heat exposure on adiposity among children may make it a new but major threat to be targeted by future mitigation strategies.
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Affiliation(s)
- Hong-Zhi Zhang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Dao-Sen Wang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Si-Han Wu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Guo-Feng Huang
- Department of Air Quality Forecasting and Early Warning, Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Duo-Hong Chen
- Department of Air Quality Forecasting and Early Warning, Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Hui-Min Ma
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China
| | - Yun-Ting Zhang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Li-Hao Guo
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Li-Zi Lin
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Zhao-Huan Gui
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Ru-Qing Liu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Li-Wen Hu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Jie-Wen Yang
- Guangzhou Social Welfare Institution, Guangzhou, 510520, China.
| | - Wang-Jian Zhang
- Department of Biostatistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
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