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Li H, Zhao Y, Wang L, Liu H, Shi Y, Liu J, Chen H, Yang B, Shan H, Yuan S, Gao W, Wang G, Han C. Association between PM 2.5 and hypertension among the floating population in China: a cross-sectional study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024; 34:943-955. [PMID: 36919640 DOI: 10.1080/09603123.2023.2190959] [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: 12/01/2022] [Accepted: 03/09/2023] [Indexed: 06/18/2023]
Abstract
Few studies have investigated the association between PM2.5 and hypertension among floating populations. We therefore examined the relationship using binary logistic regression. Each grade of increment in the annual average PM2.5 (grade one: ≤15 µg/m3; grade two: 15-25 µg/m3; grade three: 25-35 µg/m3 [Excluding 25]; grade four: ≥35 µg/m3) was associated with an increased risk of hypertension (odds ratio [OR] = 1.081, 95% confidence interval (CI): 1.034-1.129). Among the female floating population (OR = 1.114, 95% CI: 1.030-1.204), those with education level of primary school and below (OR = 1.140, 95% CI: 1.058-1.229), construction workers (OR = 1.228, 95% CI: 1.058-1.426), and those living in the eastern region of China (OR = 1.241, 95% CI: 1.145-1.346) were more vulnerable to PM2.5. These results indicate that PM2.5 is positively associated with hypertension in floating populations. Floating populations who are female, less educated, construction workers, and living in the eastern region of China are more vulnerable to the adverse impacts of PM2.5.
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Affiliation(s)
- Hongyu Li
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Yang Zhao
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
- Digital Health and Stroke Program, The George Institute for Global Health, Beijing, China
| | - Luyang Wang
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Haiyun Liu
- Department of Medicine, Shandong College of Traditional Chinese Medicine, Yantai, Shandong, China
| | - Yukun Shi
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Junyan Liu
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Haotian Chen
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Baoshun Yang
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Haifeng Shan
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
- Science and Education Department, Zibo Mental Health Center, Zibo, Shandong, China
| | - Shijia Yuan
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Wenhui Gao
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Guangcheng Wang
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Chunlei Han
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
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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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Clarke K, Rivas AC, Milletich S, Sabo-Attwood T, Coker ES. Prenatal Exposure to Ambient PM 2.5 and Early Childhood Growth Impairment Risk in East Africa. TOXICS 2022; 10:705. [PMID: 36422914 PMCID: PMC9699051 DOI: 10.3390/toxics10110705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 11/08/2022] [Accepted: 11/16/2022] [Indexed: 06/16/2023]
Abstract
Height for age is an important and widely used population-level indicator of children's health. Morbidity trends show that stunting in young children is a significant public health concern. Recent studies point to environmental factors as an understudied area of child growth failure in Africa. Data on child measurements of height-for-age and confounders were obtained from fifteen waves of the Demographic and Health Surveys (DHS) for six countries in East Africa. Monthly ambient PM2.5 concentration data was retrieved from the Atmospheric Composition Analysis Group (ACAG) global surface PM2.5 estimates and spatially integrated with DHS data. Generalized additive models with linear and logistic regression were used to estimate the exposure-response relationship between prenatal PM2.5 and height-for-age and stunting among children under five in East Africa (EA). Fully adjusted models showed that for each 10 µg/m3 increase in PM2.5 concentration there is a 0.069 (CI: 0.097, 0.041) standard deviation decrease in height-for-age and 9% higher odds of being stunted. Our study identified ambient PM2.5 as an environmental risk factor for lower height-for-age among young children in EA. This underscores the need to address emissions of harmful air pollutants in EA as adverse health effects are attributable to ambient PM2.5 air pollution.
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Zhou W, Wang W, Fan C, Zhou F, Ling L. Residential elevation and its effects on hypertension incidence among older adults living at low altitudes: a prospective cohort study. Environ Health Prev Med 2022; 27:19. [PMID: 35527011 PMCID: PMC9251620 DOI: 10.1265/ehpm.22-00001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background Research on the relationship between residential altitude and hypertension incidence has been inconclusive. Evidence at low altitudes (i.e., <1,500 m) is scarce, let alone in older adults, a population segment with the highest hypertension prevalence. Thus, the objective of this study is to determine whether hypertension risk may be affected by altitude in older adults living at low altitudes. Methods This prospective cohort study collected data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We selected 6,548 older adults (≥65 years) without hypertension at baseline (2008) and assessed events by the follow-up surveys done in 2011, 2014, and 2018 waves. The mean altitude of 613 residential units (county or district) in which the participants resided was extracted from the Digital Elevation Model (DEM) of the National Aeronautics and Space Administration (NASA) and was accurate to within 30 m. The Cox regression model with penalized splines examined the linear or nonlinear link between altitude and hypertension. A random-effects Cox regression model was used to explore the linear association between altitude and hypertension. Results The overall rate of incident hypertension was 8.6 per 100-person years. The median altitude was 130.0 m (interquartile range [IQR] = 315.5 m). We observed that the exposure–response association between altitude and hypertension incidence was not linear. The shape of the exposure–response curve showed that three change points existed. Hypertension risk increased from the lowest to the first change point (247.1 m) and slightly fluctuated until the last change point (633.9 m). The risk decreased above the last change point. According to the categories stratified by the change points, altitude was only significantly associated with hypertension risk (hazard ratio [HR] = 1.003; 95% confidence interval [CI] = 1.002–1.005) under the first change point (247.1 m) after adjusting for related covariates. Conclusion Our study found that the association between altitude and hypertension risk might not be linear. We hope the further study can be conducted to confirm the generality of our findings. Supplementary information The online version contains supplementary material available at https://doi.org/10.1265/ehpm.22-00001.
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Affiliation(s)
- Wensu Zhou
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University
| | - Wenjuan Wang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University
| | - Chaonan Fan
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University
| | - Fenfen Zhou
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University
| | - Li Ling
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University
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