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Dong S, Yu B, Yin C, Li Y, Zhong W, Feng C, Lin X, Qiao X, Yin Y, Wang Z, Chen T, Liu H, Jia P, Li X, Yang S. Associations between PM 2.5 and its chemical constituents and blood pressure: a cross-sectional study. J Hypertens 2024; 42:1897-1905. [PMID: 39248113 DOI: 10.1097/hjh.0000000000003795] [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: 07/11/2023] [Accepted: 05/31/2024] [Indexed: 09/10/2024]
Abstract
OBJECTIVES To investigate the associations between PM 2.5 and its chemical constituents with blood pressure (BP), assess effects across BP quantiles, and identify the key constituent elevating BP. METHODS A total of 36 792 adults were included in the cross-sectional study, representing 25 districts/counties of southeast China. Quantile regression models were applied to estimate the associations of PM 2.5 and its chemical constituents (ammonium [NH 4+ ], nitrate [NO 3- ], sulfate [SO 42- ], black carbon [BC], organic matter [OM]) with systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean artery pressure (MAP). A weighted quantile sum (WQS) index was used to estimate the relative importance of each PM 2.5 chemical constituent to the joint effect on BP. RESULTS The adverse effects of each interquartile range (IQR) increase in PM 2.5 , NH 4+ , NO 3- , SO 42- , and BC on BP were found to be greater with elevated BP, especially when SBP exceeded 133 mmHg and DBP exceeded 82 mmHg. Each IQR increase in all five PM 2.5 chemical constituents was associated with elevated SBP ( β [95% CI]: 0.90 [0.75, 1.05]), DBP ( β : 0.44 [0.34, 0.53]), and MAP ( β : 0.57 [0.45, 0.69]), NH 4+ (for SBP: weight = 99.43%; for DBP: 12.78%; for MAP: 60.73%) and BC (for DBP: 87.06%; for MAP: 39.07%) predominantly influencing these effects. The joint effect of PM 2.5 chemical constituents on risks for elevated SBP and DBP exhibited an upward trend from the 70 th quantile (SBP exceeded 133 mmHg, DBP exceeded 82 mmHg). CONCLUSION Long-term exposure to PM 2.5 and its chemical constituents was associated with increased risk for elevated BP, with NH 4+ and BC being the main contributors, and such associations were significantly stronger at 70th to 90th quantiles (SBP exceeded 133 mmHg, DBP exceeded 82 mmHg).
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Affiliation(s)
- Shu Dong
- West China School of Public Health and West China Fourth Hospital, Sichuan University
| | - Bin Yu
- West China School of Public Health and West China Fourth Hospital, Sichuan University
- Institute for Disaster Management and Reconstruction, Sichuan University - The Hong Kong Polytechnic University, Chengdu
| | - Chun Yin
- School of Resource and Environmental Sciences
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Yuchen Li
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Wenling Zhong
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou
| | - Chuanteng Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University
- Institute for Disaster Management and Reconstruction, Sichuan University - The Hong Kong Polytechnic University, Chengdu
| | - Xi Lin
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou
| | - Xu Qiao
- West China School of Public Health and West China Fourth Hospital, Sichuan University
- Institute for Disaster Management and Reconstruction, Sichuan University - The Hong Kong Polytechnic University, Chengdu
| | - Yanrong Yin
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou
| | - Zihang Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University
| | - Tiehui Chen
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou
| | - Hongyun Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University
| | - Peng Jia
- School of Resource and Environmental Sciences
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- Hubei Luojia Laboratory
- School of Public Health, Wuhan University, Wuhan, China
| | - Xiaoqing Li
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
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Wang D, Liu Z, Liu Y, Zhao L, Xu L, He S, Duan B. Knowledge, attitudes, and practices among patients with diabetes mellitus and hyperuricemia toward disease self-management. Front Public Health 2024; 12:1426259. [PMID: 39399698 PMCID: PMC11466750 DOI: 10.3389/fpubh.2024.1426259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Accepted: 09/10/2024] [Indexed: 10/15/2024] Open
Abstract
Background This study aimed to assess the knowledge, attitudes and practices (KAP) among patients with diabetes mellitus and hyperuricemia toward disease self-management. Methods This web-based cross-sectional study was conducted between June 2023 and January 2024 at Heilongjiang Provincial Hospital. A self-designed questionnaire was developed to collect demographic information of patients with diabetes mellitus and hyperuricemia, and assess their knowledge, attitudes and practices toward disease self-management. Results A total of 482 participants were enrolled in this study, among them, 364 (75.52%) were male, 235 (48.76%) were aged between 40 and 59 years, 226 (46.89%) had a body mass index (BMI) ranging from 24 to 28 kg/m2, 337 (69.92%) had received a diagnosis of diabetes for a duration of 2 years or more, while 245 (50.83%) had been diagnosed with hyperuricemia for a similar duration. Their median (range) knowledge, attitude and practice scores were 10.00 (9.00, 11.00) (possible range: 0-12), 38.00 (36.00, 40.00) (possible range: 9-45), and 30.00 (26.00, 34.75) (possible range: 10-50), respectively. The path analysis demonstrated that knowledge had direct effects on attitude (β = 0.508, p < 0.001), and attitude had direct effects on practice (β = 0.448, p < 0.001). Additionally, there was an indirect effect of knowledge on practice mediated through attitude, with a path coefficient of 0.228 (p < 0.001). Conclusion This study demonstrates that patients with diabetes mellitus and hyperuricemia exhibit relatively proficient responses to certain items within the KAP dimensions. However, it also exposes a certain degree of inadequacy in the KAP level toward disease management. Interventions should focus on improving patients' understanding of their conditions while fostering positive attitudes, ultimately translating into better self-management practices.
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Affiliation(s)
- Dan Wang
- Department of Endocrinology, Heilongjiang Provincial Hospital, Harbin, China
| | - Zhixin Liu
- The First Clinical College of Medicine, Mudanjiang Medical University, Mudanjiang, China
| | - Yu Liu
- Department of Endocrinology, Heilongjiang Provincial Hospital, Harbin, China
| | - Lingfei Zhao
- Department of Endocrinology, Heilongjiang Provincial Hospital, Harbin, China
| | - Lijuan Xu
- Department of Endocrinology, Heilongjiang Provincial Hospital, Harbin, China
| | - Shanshan He
- Department of Endocrinology, Heilongjiang Provincial Hospital, Harbin, China
| | - Binhong Duan
- Department of Endocrinology, Heilongjiang Provincial Hospital, Harbin, China
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Lin L, Hu X, Liu X, Hu G. Key influences on dysglycemia across Fujian's urban-rural divide. PLoS One 2024; 19:e0308073. [PMID: 39083543 PMCID: PMC11290630 DOI: 10.1371/journal.pone.0308073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 07/17/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND Screening and treatment of dysglycemia (prediabetes and diabetes) represent significant challenges in advancing the Healthy China initiative. Identifying the crucial factors contributing to dysglycemia in urban-rural areas is essential for the implementation of targeted, precise interventions. METHODS Data for 26,157 adults in Fujian Province, China, were collected using the Social Factors Special Survey Form through a multi-stage random sampling method, wherein 18 variables contributing to dysglycemia were analyzed with logistic regression and the random forest model. OBJECTIVE Investigating urban-rural differences and critical factors in dysglycemia prevalence in Fujian, China, with the simultaneous development of separate predictive models for urban and rural areas. RESULT The detection rate of dysglycemia among adults was 35.26%, with rates of 34.1% in urban areas and 35.8% in rural areas. Common factors influencing dysglycemia included education, age, BMI, hypertension, and dyslipidemia. For rural residents, higher income (OR = 0.80, 95% CI [0.74, 0.87]), average sleep quality (OR = 0.89, 95% CI [0.80, 0.99]), good sleep quality (OR = 0.89, 95% CI [0.80, 1.00]), and high physical activity (PA) (OR = 0.87, 95% CI [0.79, 0.96]) emerged as protective factors. Conversely, a daily sleep duration over 8 hours (OR = 1.46, 95% CI [1.03, 1.28]) and middle income (OR = 1.12, 95% CI [1.03, 1.22]) were specific risk factors. In urban areas, being male (OR = 1.14, 95% CI [1.02, 1.26]), cohabitation (OR = 1.18, 95% CI [1.02, 1.37]), and central obesity (OR = 1.35, 95% CI [1.19, 1.53]) were identified as unique risk factors. Using logistic regression outcomes, a random forest model was developed to predict dysglycemia, achieving accuracies of 75.35% (rural) and 76.95% (urban) with ROC areas of 0.77 (rural) and 0.75 (urban). CONCLUSION This study identifies key factors affecting dysglycemia in urban and rural Fujian residents, including common factors such as education, age, BMI, hypertension, and dyslipidemia. Notably, rural-specific protective factors are higher income and good sleep quality, while urban-specific risk factors include being male and central obesity. These findings support the development of targeted prevention and intervention strategies for dysglycemia, tailored to the unique characteristics of urban and rural populations.
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Affiliation(s)
- LiHan Lin
- College of Physical Education, Huaqiao University, Quanzhou, China
| | - XiangJu Hu
- School of Public Health, Fujian Medical University, Fuzhou, China
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, Fujian, China
| | - XiaoYang Liu
- College of Physical Education, Huaqiao University, Quanzhou, China
| | - GuoPeng Hu
- College of Physical Education, Huaqiao University, Quanzhou, China
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Niu Z, Duan Z, He W, Chen T, Tang H, Du S, Sun J, Chen H, Hu Y, Iijima Y, Han S, Li J, Zhao Z. Kidney function decline mediates the adverse effects of per- and poly-fluoroalkyl substances (PFAS) on uric acid levels and hyperuricemia risk. JOURNAL OF HAZARDOUS MATERIALS 2024; 471:134312. [PMID: 38640681 DOI: 10.1016/j.jhazmat.2024.134312] [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: 01/06/2024] [Revised: 03/30/2024] [Accepted: 04/14/2024] [Indexed: 04/21/2024]
Abstract
Previous studies indicated per- and poly-fluoroalkyl substances (PFAS) were related to uric acid and hyperuricemia risk, but evidence for the exposure-response (E-R) curves and combined effect of PFAS mixture is limited. Moreover, the potential mediation effect of kidney function was not assessed. Hence, we conducted a national cross-sectional study involving 13,979 US adults in NHANES 2003-2018 to examine the associations of serum PFAS with uric acid and hyperuricemia risk, and the mediation effects of kidney function. Generalized linear models and E-R curves showed positive associations of individual PFAS with uric acid and hyperuricemia risk, and nearly linear E-R curves indicated no safe threshold for PFAS. Weighted quantile sum regression found positive associations of PFAS mixture with uric acid and hyperuricemia risk, and PFOA was the dominant contributor to the adverse effect of PFAS on uric acid and hyperuricemia risk. Causal mediation analysis indicated significant mediation effects of kidney function decline in the associations of PFAS with uric acid and hyperuricemia risk, with the mediated proportion ranging from 19 % to 57 %. Our findings suggested that PFAS, especially PFOA, may cause increased uric acid and hyperuricemia risk increase even at low levels, and kidney function decline plays a crucial mediation effect.
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Affiliation(s)
- Zhiping Niu
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Zhizhou Duan
- Preventive Health Service, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, 152 Aiguo Road, Nanchang, Jiangxi, China
| | - Weixiang He
- Department of Urology, Xijing Hospital, The Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, China
| | - Tianyi Chen
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Hao Tang
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Shuang Du
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Jin Sun
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Han Chen
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Yuanzhuo Hu
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Yuka Iijima
- Department of Clinical Medicine, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Shichao Han
- Department of Urology, Xijing Hospital, The Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, China.
| | - Jiufeng Li
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China.
| | - Zhuohui Zhao
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China; Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China; WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai 200438, China.
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Yu B, Tang W, Fan Y, Ma C, Ye T, Cai C, Xie Y, Shi Y, Baima K, Yang T, Wang Y, Jia P, Yang S. Associations between residential greenness and obesity phenotypes among adults in Southwest China. Health Place 2024; 87:103236. [PMID: 38593578 DOI: 10.1016/j.healthplace.2024.103236] [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: 09/01/2023] [Revised: 02/27/2024] [Accepted: 03/21/2024] [Indexed: 04/11/2024]
Abstract
BACKGROUND Although exposure to greenness has generally benefited human metabolic health, the association between greenness exposure and metabolic obesity remains poorly studied. We aimed to investigate the associations between residential greenness and obesity phenotypes and the mediation effects of air pollutants and physical activity (PA) level on the associations. METHODS We used the baseline of the China Multi-Ethnic Cohort (CMEC) study, which enrolled 87,613 adults. Obesity phenotypes were defined based on obesity and metabolic status, including metabolically unhealthy obesity (MUO), non-obesity (MUNO), metabolically healthy obesity (MHO), and non-obesity (MHNO). Greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 500-m buffer zones around the participants' residence. Multivariable logistic regression was used to estimate the associations between greenness and obesity phenotypes. Stratified analyses by age, sex, educational level, and urbanicity were performed to identify how the effect varies across different subgroups. Causal mediation analysis was used to examine the mediation effects of air pollutants and PA level. RESULTS Compared with MHNO, each interquartile range (IQR) increase in greenness exposure was associated with reduced risks of MHO (ORNDVI [95% CI] = 0.87 [0.81, 0.93]; OREVI = 0.91 [0.86, 0.97]), MUO (ORNDVI = 0.83 [0.78, 0.88]; OREVI = 0.86 [0.81, 0.91]), and MUNO (ORNDVI = 0.88 [0.84, 0.91]; OREVI = 0.89 [0.86, 0.92]). For each IQR increase in both NDVI and EVI, the risks of MHO, MUO, and MUNO were reduced more in men, participants over 60 years, those with a higher level of education, and those living in urban areas, compared to their counterparts. Concentrations of particulate matter (PM) and PA level partially mediated the associations between greenness exposure and obesity phenotypes. CONCLUSIONS Exposure to residential greenness was associated with decreased risks of MHO, MUO, and MUNO, which was mediated by concentrations of PM and PA level, and modified by sex, age, educational level, and urbanicity.
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Affiliation(s)
- Bin Yu
- Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China; West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wenge Tang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Yunzhe Fan
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunlan Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Tingting Ye
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Changwei Cai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yiming Xie
- Jianyang Center for Disease Control and Prevention, Jianyang, China
| | - Yuanyuan Shi
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Kangzhuo Baima
- High Altitude Health Science Research Center of Tibet University, Lhasa, Tibet, China
| | - Tingting Yang
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Yanjiao Wang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China; Hubei Luojia Laboratory, Wuhan, China; School of Public Health, Wuhan University, Wuhan, China.
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China.
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Cui Z, Pan R, Liu J, Yi W, Huang Y, Li M, Zhang Z, Kuang L, Liu L, Wei N, Song R, Yuan J, Li X, Yi X, Song J, Su H. Green space and its types can attenuate the associations of PM 2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China. ENVIRONMENTAL RESEARCH 2024; 245:117997. [PMID: 38157960 DOI: 10.1016/j.envres.2023.117997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 12/12/2023] [Accepted: 12/19/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces. METHODS A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations. RESULTS Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups. CONCLUSION Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.
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Affiliation(s)
- Zhiqian Cui
- 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, Hefei, Anhui, 230032, China
| | - 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, Hefei, Anhui, 230032, China
| | - Jintao 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, Hefei, Anhui, 230032, 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, Hefei, Anhui, 230032, China
| | - Yuxin Huang
- 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, Hefei, Anhui, 230032, China
| | - Ming Li
- 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, Hefei, Anhui, 230032, China
| | - Zichen Zhang
- 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, Hefei, Anhui, 230032, China
| | - Lingmei Kuang
- 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, Hefei, Anhui, 230032, China
| | - Li 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, Hefei, Anhui, 230032, China
| | - Ning Wei
- 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, Hefei, Anhui, 230032, China
| | - Rong 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, Hefei, Anhui, 230032, China
| | - Jiajun Yuan
- 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, Hefei, Anhui, 230032, China
| | - Xuanxuan Li
- 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, Hefei, Anhui, 230032, China
| | - Xingxu 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, Hefei, Anhui, 230032, 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, Hefei, Anhui, 230032, 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, Hefei, Anhui, 230032, China.
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Mengue YW, Audate PP, Dubé J, Lebel A. Contribution of environmental determinants to the risk of developing type 2 diabetes mellitus in a life-course perspective: a systematic review protocol. Syst Rev 2024; 13:80. [PMID: 38429833 PMCID: PMC10908215 DOI: 10.1186/s13643-024-02488-2] [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: 04/10/2023] [Accepted: 02/14/2024] [Indexed: 03/03/2024] Open
Abstract
BACKGROUND Prevention policies against type 2 diabetes mellitus (T2DM) focus solely on individual healthy lifestyle behaviours, while an increasing body of research recognises the involvement of environmental determinants (ED) (cultural norms of land management and planning, local foodscape, built environment, pollution, and neighbourhood deprivation). Precise knowledge of this relationship is essential to proposing a prevention strategy integrating public health and spatial planning. Unfortunately, issues related to the consistency and synthesis of methods, and results in this field of research limit the development of preventive strategies. This systematic review aims to improve knowledge about the relationship between the risk of developing T2DM in adulthood and long-term exposure to its ED during childhood or teenage years. METHODS This protocol is presented according to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) tools. PubMed, Embase, CINAHL, Web of Science, EBSCO, and grey literature from the Laval University Libraries databases will be used for data collection on main concepts such as 'type 2 diabetes mellitus', 'zoning' or 'regional, urban, or rural areas land uses', 'local food landscape', 'built environment', 'pollution', and 'deprivation'. The Covidence application will store the collected data for selection and extraction based on the Population Exposure Comparator Outcome and Study design approach (PECOS). Studies published until December 31, 2023, in English or French, used quantitative data about individuals aged 18 and over that report on T2DM, ED (cultural norms of land management and planning, local foodscape, built environment, and neighbourhood deprivation), and their association (involving only risk estimators) will be included. Then, study quality and risk of bias will be conducted according to the combined criteria and ratings from the ROBINS-E (Risk of Bias in Non-randomised Studies-of Exposures) tools and the 'Effective Public Health Practice Project' (EPHPP). Finally, the analytical synthesis will be produced using the 'Synthesis Without Meta-analysis' (SWiM) guidelines. DISCUSSION This systematic review will summarise available evidence on ED associated with T2DM. The results will contribute to improving current knowledge and developing more efficient cross-sectoral interventions in land management and public health in this field of research. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42023392073.
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Affiliation(s)
- Yannick Wilfried Mengue
- Graduate School of Land Management and Regional Planning, Laval University, Quebec, Canada.
- Quebec Heart and Lung Institute, Quebec, Canada.
| | | | - Jean Dubé
- Graduate School of Land Management and Regional Planning, Laval University, Quebec, Canada
| | - Alexandre Lebel
- Graduate School of Land Management and Regional Planning, Laval University, Quebec, Canada
- Quebec Heart and Lung Institute, Quebec, Canada
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Yu Y, Lin H, Liu Q, Ma Y, Zhao L, Li W, Zhou Y, Byun HM, Li P, Li C, Sun C, Chen X, Liu Z, Dong W, Chen L, Deng F, Wu S, Hou S, Guo L. Association of residential greenness, air pollution with adverse birth outcomes: Results from 61,762 mother‑neonatal pairs in project ELEFANT (2011-2021). THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169549. [PMID: 38145684 DOI: 10.1016/j.scitotenv.2023.169549] [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: 09/16/2023] [Revised: 11/06/2023] [Accepted: 12/18/2023] [Indexed: 12/27/2023]
Abstract
BACKGROUND Emerging evidence has demonstrated the benefits of greenness exposure on human health, while conflicts remain unsolved in issue of adverse birth outcomes. METHODS Utilizing data from project ELEFANT spanning the years 2011 to 2021, we assessed residential greenness using the NDVI from MODIS data and residential PM2.5 exposure level from CHAP data. Our primary concerns were PTD, LBW, LGA, and SGA. Cox proportional hazard regression model was used to examine the association of residential greenness and air pollution exposure with risk of adverse birth outcomes. We performed mediation and modification effect analyses between greenness and air pollutant. RESULTS We identified 61,762 mother‑neonatal pairs in final analysis. For per 10 μg/m3 increase in PM2.5 concentration during entire pregnancy was associated with 19.8 % and 20.7 % increased risk of PTD and LGA. In contrast, we identified that an 0.1 unit increment in NDVI were associated with 24 %, 43 %, 26.5 %, and 39.5 % lower risk for PTD, LBW, LGA, and SGA, respectively. According to mediation analysis, NDVI mediated 7.70 % and 7.89 % of the associations between PM2.5 and PTD and LGA. Residential greenness could reduce the risk of PTD among mothers under 35 years old, living in rural areas, primigravidae and primiparity.. CONCLUSIONS In summary, our results highlighted the potential of residential greenness to mitigate the risk of adverse birth outcomes, while also pointing to the adverse impact of PM2.5 on increased risk of multiple adverse birth outcomes (PTD and LGA). The significant mediation effect of NDVI emphasizes its potential as an important protective factor of PM2.5 exposure. Additionally, the identification of susceptible subgroups can inform targeted interventions to reduce adverse birth outcomes related to air pollution and lack of green spaces. Further research and understanding of these associations can contribute to better public health strategies aimed at promoting healthier pregnancies and birth outcomes.
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Affiliation(s)
- Yuanyuan Yu
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou 325000, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China
| | - Huishu Lin
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou 325000, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China
| | - Qisijing Liu
- Research Institute of Public Health, School of Medicine, Nankai University, Tianjin, China
| | - Yuxuan Ma
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou 325000, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China
| | - Lei Zhao
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou 325000, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China
| | - Weixia Li
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou 325000, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China
| | - Yan Zhou
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin 300072, China
| | - Hyang-Min Byun
- Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Campus for Ageing and Vitality, Newcastle Upon Tyne NE4 5PL, UK
| | - Penghui Li
- Department of Environmental Science, School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin, China
| | - Chen Li
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Congcong Sun
- Department of Scientific Research Center, The Third Clinical Institute Affiliated of Wenzhou Medical University, The Third Affiliated of Shanghai University, Wenzhou People's Hospital, Wenzhou Maternal and Child Health Care Hospital, Wenzhou, China
| | - Xuemei Chen
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou 325000, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China
| | - Ziquan Liu
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou 325000, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China
| | - Wenlong Dong
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou 325000, China
| | - Liqun Chen
- Academy of Medical Engineering and Translational Medicine, Medical College, Tianjin University, Tianjin 300072, China
| | - Furong Deng
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Shike Hou
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou 325000, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China.
| | - Liqiong Guo
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou 325000, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China.
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Wang W, Yang C, Wang J, Wang F, Liang Z, Wang Y, Zhang F, Liang C, Li C, Lan Y, Li S, Li P, Zhou Y, Zhang L, Ding L. Lower regional urbanicity and socioeconomic status attenuate associations of green spaces with hypertension and diabetes mellitus: a national representative cross-sectional study in China. Environ Health Prev Med 2024; 29:47. [PMID: 39245566 PMCID: PMC11391273 DOI: 10.1265/ehpm.24-00121] [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] [Indexed: 09/10/2024] Open
Abstract
BACKGROUND High blood pressure (HBP) and diabetes mellitus (DM) are two of the most prevalent cardiometabolic disorders globally, especially among individuals with lower socio-economic status (SES). Studies have linked residential greenness to decreased risks of HBP and DM. However, there has been limited evidence on whether SES may modify the associations of residential greenness with HBP and DM. METHODS Based on a national representative cross-sectional study among 44,876 adults, we generated the normalized difference vegetation index (NDVI) at 1 km spatial resolution to characterize individuals' residential greenness level. Administrative classification (urban/rural), nighttime light index (NLI), individual income, and educational levels were used to characterize regional urbanicity and individual SES levels. RESULTS We observed weaker inverse associations of NDVI with HBP and DM in rural regions compared to urban regions. For instance, along with per interquartile range (IQR, 0.26) increment in residential NDVI at 0∼5 year moving averages, the ORs of HBP were 1.04 (95%CI: 0.94, 1.15) in rural regions and 0.85 (95%CI: 0.79, 0.93) in urban regions (P = 0.003). Along with the decrease in NLI levels, there were continuously decreasing inverse associations of NDVI with DM prevalence (P for interaction <0.001). In addition, weaker inverse associations of residential NDVI with HBP and DM prevalence were found among individuals with lower income and lower education levels compared to their counterparts. CONCLUSIONS Lower regional urbanicity and individual SES could attenuate the associations of residential greenness with odds of HBP and DM prevalence.
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Affiliation(s)
- Wanzhou Wang
- National Institute of Health Data Science at Peking University
- Institute of Medical Technology, Peking University Health Science Center
| | - Chao Yang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences
- Advanced Institute of Information Technology, Peking University
| | - Jinwei Wang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of Education of the People's Republic of China
| | - Fulin Wang
- National Institute of Health Data Science at Peking University
- Institute of Medical Technology, Peking University Health Science Center
| | - Ze Liang
- Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University
| | - Yueyao Wang
- Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University
| | - Feifei Zhang
- National Institute of Health Data Science at Peking University
| | - Chenyu Liang
- Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University
| | - Chenshuang Li
- Center for Smart and Healthy Buildings, Huazhong University of Science and Technology
| | - Yiqun Lan
- Center for Smart and Healthy Buildings, Huazhong University of Science and Technology
| | - Shuangcheng Li
- Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University
| | - Pengfei Li
- Advanced Institute of Information Technology, Peking University
| | - Ying Zhou
- Center for Smart and Healthy Buildings, Huazhong University of Science and Technology
| | - Luxia Zhang
- National Institute of Health Data Science at Peking University
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences
- Advanced Institute of Information Technology, Peking University
| | - Lieyun Ding
- Center for Smart and Healthy Buildings, Huazhong University of Science and Technology
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Baheti B, Chen G, Ding Z, Wu R, Zhang C, Zhou L, Liu X, Song X, Wang C. Residential greenness alleviated the adverse associations of long-term exposure to ambient PM 1 with cardiac conduction abnormalities in rural adults. ENVIRONMENTAL RESEARCH 2023; 237:116862. [PMID: 37574100 DOI: 10.1016/j.envres.2023.116862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/27/2023] [Accepted: 08/08/2023] [Indexed: 08/15/2023]
Abstract
BACKGROUND Ambient air pollution was linked to elevated risks of adverse cardiovascular events, and alterations in electrophysiological properties of the heart might be potential pathways. However, there is still lacking research exploring the associations between PM1 exposure and cardiac conduction parameters. Additionally, the interactive effects of PM1 and residential greenness on cardiac conduction parameters in resource-limited areas remain unknown. METHODS A total of 27483 individuals were enrolled from the Henan Rural Cohort study. Cardiac conduction parameters were tested by 12-lead electrocardiograms. Concentrations of PM1 were evaluated by satellite-based spatiotemporal models. Levels of residential greenness were assessed using Enhanced Vegetation Index (EVI) and Normalized difference vegetation index (NDVI). Logistic regression models and restricted cubic splines were fitted to explore the associations of PM1 and residential greenness exposure with cardiac conduction abnormalities risk, and the interaction plot method was performed to visualize their interaction effects. RESULTS The 3-year median concentration of PM1 was 56.47 (2.55) μg/m3, the adjusted odds rate (ORs) and 95% confidence intervals (CIs) for abnormal HR, PR, QRS, and QTc interval risk in response to 1 μg/m3 increase in PM1 were 1.064 (1.044, 1.085), 1.037 (1.002, 1.074), 1.061 (1.044, 1.077) and 1.046 (1.028, 1.065), respectively. Participants exposure to higher levels of PM1 had increased risks of abnormal HR (OR = 1.221, 95%CI: 1.144, 1.303), PR (OR = 1.061, 95%CI: 0.940, 1.196), QRS (OR = 1.225, 95%CI: 1.161, 1.294) and QTc interval (OR = 1.193, 95%CI: 1.121, 1.271) compared with lower levels of PM1. Negative interactive effects of exposure to PM1 and residential greenness on abnormal HR, QRS, and QTc intervals were observed (Pfor interaction < 0.05). CONCLUSION Long-term PM1 exposure was associated with elevated cardiac conduction abnormalities risks, and this adverse association might be mitigated by residential greenness to some extent. These findings emphasize that controlling PM1 pollution and increasing greenness levels might be effective strategies to reduce cardiovascular disease burdens in resource-limited areas.
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Affiliation(s)
- Bota Baheti
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Gongbo Chen
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Zhongao Ding
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Ruiyu Wu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Caiyun Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Lue Zhou
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, PR China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xiaoqin Song
- Physical Examination Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China; NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, PR China.
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11
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Xue Y, Li J, Xu YN, Cui JS, Li Y, Lu YQ, Luo XZ, Liu DZ, Huang F, Zeng ZY, Huang RJ. Mediating effect of body fat percentage in the association between ambient particulate matter exposure and hypertension: a subset analysis of China hypertension survey. BMC Public Health 2023; 23:1897. [PMID: 37784103 PMCID: PMC10544618 DOI: 10.1186/s12889-023-16815-0] [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: 06/12/2023] [Accepted: 09/22/2023] [Indexed: 10/04/2023] Open
Abstract
BACKGROUND Hypertension caused by air pollution exposure is a growing concern in China. The association between air pollutant exposure and hypertension has been found to be potentiated by obesity, however, little is known about the processes mediating this association. This study investigated the association between fine particulate matter (aerodynamic equivalent diameter ≤ 2.5 microns, PM2.5) exposure and the prevalence of hypertension in a representative population in southern China and tested whether obesity mediated this association. METHODS A total of 14,308 adults from 48 communities/villages in southern China were selected from January 2015 to December 2015 using a stratified multistage random sampling method. Hourly PM2.5 measurements were collected from the China National Environmental Monitoring Centre. Restricted cubic splines were used to analyze the nonlinear dose-response relationship between PM2.5 exposure and hypertension risk. The mediating effect mechanism of obesity on PM2.5-associated hypertension was tested in a causal inference framework following the approach proposed by Imai and Keele. RESULTS A total of 20.7% (2966/14,308) of participants in the present study were diagnosed with hypertension. Nonlinear exposure-response analysis revealed that exposure to an annual mean PM2.5 concentration above 41.8 µg/m3 was associated with increased hypertension risk at an incremental gradient. 9.1% of the hypertension burden could be attributed to exposure to elevated annual average concentrations of PM2.5. It is noteworthy that an increased body fat percentage positively mediated 59.3% of the association between PM2.5 exposure and hypertension risk, whereas body mass index mediated 34.3% of this association. CONCLUSIONS This study suggests that a significant portion of the estimated effect of exposure to PM2.5 on the risk of hypertension appears to be attributed to its effect on alterations in body composition and the development of obesity. These findings could inform intersectoral actions in future studies to protect populations with excessive fine particle exposure from developing hypertension.
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Affiliation(s)
- Yan Xue
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Jin Li
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Yu-Nan Xu
- Department of Medical Research, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jia-Sheng Cui
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Yue Li
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Yao-Qiong Lu
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Xiao-Zhi Luo
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - De-Zhao Liu
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Feng Huang
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China.
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China.
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China.
| | - Zhi-Yu Zeng
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China.
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China.
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China.
| | - Rong-Jie Huang
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China.
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China.
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China.
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