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Yan T, Song Q, Yao M, Zhang X, He Y. Diurnal temperature range and hypertension: cross-sectional and longitudinal findings from the China Health and Retirement Longitudinal Study (CHARLS). BMC Public Health 2024; 24:2665. [PMID: 39350136 PMCID: PMC11440652 DOI: 10.1186/s12889-024-20148-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 09/20/2024] [Indexed: 10/04/2024] Open
Abstract
BACKGROUND Research indicates a positive association between short-term diurnal temperature range (DTR) exposure and hypertension. However, the impact of long-term DTR exposure has not been thoroughly studied in population-based cohort research. METHODS This study conducted cross-sectional (including 16,690 participants) and longitudinal analyses (including 9,650 participants) based on the China Health and Retirement Longitudinal Study (CHARLS). Daily temperature data was sourced from the National Scientific Data of the Qinghai-Tibet Plateau. We calculated the moving average of DTR exposure of all the participants in CHARLS with exposure windows of 30-day, 60-day, 180-day, 1-year, and 2-year before the interview month of CHARLS Wave1 (2011). Logistic regression and age-stratified Cox proportional hazards models were employed in our analysis. RESULTS In the cross-sectional study, 6,572 (39.4%) participants had hypertension. We found higher DTR is associated with a higher prevalence of hypertension across different exposure windows. The effect was strongest when the exposure window of DTR was 180-day, with an adjusted odds ratio (OR) of 1.261 (95% confidence interval (CI): 1.124-1.416 [highest tertile DTR vs. lowest tertile DTR]). In the cohort study, 3,020 (31.3%) participants developed hypertension during 83 months of follow-up. A higher level of DTR (hazard ratio (HR): 1.224, 95% CI: 1.077-1.391) was associated with a higher risk of incident hypertension. We found significant interactions between DTR and age (P interaction: <0.001) and residence (P interaction: 0.045). CONCLUSION We found significant positive associations between DTR and prevalent and incident hypertension. Individuals younger than 65 and those living in rural areas are at an elevated risk of developing hypertension due to DTR.
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Affiliation(s)
- Tiange Yan
- Department of Cardiology, Renmin Hospital of Xiangzhou District, Xiangyang City, China
- State Key Laboratory of New Drug Discovery and Development for Major Diseases, Gannan Medical University, Ganzhou, China
- Gannan Innovation and Translational Medicine Research Institute, Gannan Medical University, Ganzhou, China
| | - Qilin Song
- Department of Cardiology, Renmin Hospital of Xiangzhou District, Xiangyang City, China
- State Key Laboratory of New Drug Discovery and Development for Major Diseases, Gannan Medical University, Ganzhou, China
- Gannan Innovation and Translational Medicine Research Institute, Gannan Medical University, Ganzhou, China
| | - Ming Yao
- State Key Laboratory of New Drug Discovery and Development for Major Diseases, Gannan Medical University, Ganzhou, China
- Gannan Innovation and Translational Medicine Research Institute, Gannan Medical University, Ganzhou, China
| | - Xingyuan Zhang
- School of Basic Medical Sciences, Wuhan University, 115 Donghu Road, Wuhan, 430060, China.
| | - Yaxiong He
- Department of Cardiology, Renmin Hospital of Xiangzhou District, Xiangyang City, China.
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Ning Z, Ma Y, He S, Li G, Hua X, Ma C, Wu J. Effects of combined exposure to fine particulate matter and cold waves and on IHD hospitalizations at low and high altitudes. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 283:116977. [PMID: 39216221 DOI: 10.1016/j.ecoenv.2024.116977] [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: 06/14/2024] [Revised: 07/30/2024] [Accepted: 08/27/2024] [Indexed: 09/04/2024]
Abstract
Climate change and air pollution are major challenges facing the world today. Cold waves and air pollution significantly impact ischemic heart disease (IHD), but the extent of these effects at different altitudes remains unclear, especially their interactions. We collected daily meteorological, pollutant, and IHD hospitalization data from Xining and Xinxiang from 2016 to 2021. Using a time-stratified case-crossover approach, we fitted conditional Poisson regression models to assess the association between cold waves, PM2.5, and IHD hospitalizations and quantified their interactions. Additionally, we calculated the attributable fraction (AF) and attributable number (AN) of hospitalizations due to exposure to cold waves and medium to high-level PM2.5. We also performed stratified analyses by altitude, gender, and age. Both cold waves and PM2.5 were positively associated with IHD hospitalization rates in Xining and Xinxiang, but the differences between the two regions were not significant. The relative risk of cold waves was 1.15 (1.07, 1.24) in Xining and 1.16 (1.11, 1.21) in Xinxiang. In Xining, there was an interaction between cold waves and different levels of PM2.5. We estimated the attributable fraction due to the joint exposure of cold waves and PM2.5 to be 0.14-0.49 in Xining and 0.26-0.36 in Xinxiang. Older adults and males faced higher risks. This study highlights the importance of reducing PM2.5 exposure and optimizing extreme weather warning systems and suggests further exploration of the impacts of individual behaviors and regional characteristics on IHD.
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Affiliation(s)
- Zhenxu Ning
- Department of Public Health, Qinghai University Medical College, Xining, Qinghai 810016, China
| | - Yanjun Ma
- Qinghai Institute of Health Sciences, Xining, Qinghai 810016, China.
| | - Shuzhen He
- Xining Centre for Disease Control and Prevention, Xining, Qinghai 810000, China.
| | - Genshan Li
- Department of Public Health, Qinghai University Medical College, Xining, Qinghai 810016, China
| | - Xiaojuan Hua
- Department of Public Health, Qinghai University Medical College, Xining, Qinghai 810016, China
| | - Chunguang Ma
- Xining Centre for Disease Control and Prevention, Xining, Qinghai 810000, China
| | - Jing Wu
- Xining Centre for Disease Control and Prevention, Xining, Qinghai 810000, China
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Zhang X, Zhang T, Chen X, Ni J, Xu S, Peng Y, Wang G, Sun W, Liu X, Pan F. The impact of short-term exposure to meteorological factors on the risk of death from hypertension and its major complications: a time series analysis based on Hefei, China. Int Arch Occup Environ Health 2024; 97:313-329. [PMID: 38403848 DOI: 10.1007/s00420-024-02046-2] [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: 09/23/2023] [Accepted: 01/16/2024] [Indexed: 02/27/2024]
Abstract
OBJECTIVES This study aimed to reveal the short-term impact of meteorological factors on the mortality risk in hypertensive patients, providing a scientific foundation for formulating pertinent prevention and control policies. METHODS In this research, meteorological factor data and daily death data of hypertensive patients in Hefei City from 2015 to 2018 were integrated. Time series analysis was performed using distributed lag nonlinear model (DLNM) and generalized additive model (GAM). Furthermore, we conducted stratified analysis based on gender and age. Relative risk (RR) combined with 95% confidence interval (95% CI) was used to represent the mortality risk of single day and cumulative day in hypertensive patients. RESULTS Single-day lag results indicated that high daily mean temperature (T mean) (75th percentile, 24.9 °C) and low diurnal temperature range (DTR) (25th percentile, 4.20 °C) levels were identified as risk factors for death in hypertensive patients (maximum effective RR values were 1.144 and 1.122, respectively). Extremely high levels of relative humidity (RH) (95th percentile, 94.29%) reduced the risk of death (RR value was 0.893). The stratified results showed that the elderly and female populations are more susceptible to low DTR levels, whereas extremely high levels of RH have a more significant protective effect on both populations. CONCLUSION Overall, we found that exposure to low DTR and high T mean environments increases the risk of death for hypertensive patients, while exposure to extremely high RH environments significantly reduces the risk of death for hypertensive patients. These findings contribute valuable insights for shaping targeted prevention and control strategies.
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Affiliation(s)
- Xu Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- The Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Tao Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- The Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Xuyang Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China
| | - Jianping Ni
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China
| | - Siwen Xu
- School of Medicine, Tongji University, 500 Zhennan Road, Shanghai, 200333, China
| | - Yongzhen Peng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China
| | - Guosheng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China
| | - Wanqi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China
| | - Xuxiang Liu
- Hefei Center for Disease Control and Prevention, 86 Luan Road, Hefei, 230032, Anhui, China
| | - Faming Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China.
- The Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China.
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Yan X, Li J, Wu J, Lin S, Wang Z, Pei L, Zheng C, Wang X, Cao X, Hu Z, Tian Y. Association between short-term daily temperature variability and blood pressure in the Chinese population: From the China hypertension survey. ENVIRONMENT INTERNATIONAL 2024; 184:108463. [PMID: 38324925 DOI: 10.1016/j.envint.2024.108463] [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: 10/31/2023] [Revised: 01/04/2024] [Accepted: 01/28/2024] [Indexed: 02/09/2024]
Abstract
BACKGROUND We aimed to evaluate the impacts of short-term daily temperature variability (DTV) on blood pressure (BP) among participants with normotension, prehypertension, and hypertension, respectively, and explore the effects in different climate zones and seasons. METHODS A representative population sample (n = 397,173) covering the subtropical, temperate continental, and temperate monsoon zones was obtained from the China Hypertension Survey. DTV was calculated as the standard deviation of daily minimum and maximum temperatures during the exposure days. The linear mixed effect regression model was used to estimate the associations between DTV exposure and BP among normotension, prehypertension, and hypertension, respectively, and further stratified analysis was performed by climate zones and seasons. RESULTS After adjustment for confounders, per interquartile range (IQR) increase in DTV (2.28 °C) at 0-6 days of exposure was associated with an increase of 0.41 mmHg (95 % confidence interval [CI]: 0.07, 0.75) in systolic BP (SBP) and 0.41 mmHg (95 % CI: 0.09, 0.72) in pulse pressure (PP) among hypertensive participants in the subtropical zone. Similarly, DTV exposure was associated with an increase of 0.31 mmHg (95 % CI: 0.06, 0.55) in SBP and 0.59 mmHg (95 % CI: 0.24, 0.94) in PP among prehypertensive participants in the temperate continental zone. Additionally, during the warm season, DTV was positively associated with SBP among populations with prehypertension and hypertension, and with PP among all three populations. CONCLUSION Short-term DTV exposure was associated with an increase in SBP and PP among hypertensive and prehypertensive participants in the subtropical zone and the temperate continental zone. In addition, positive associations of DTV with SBP and PP were observed among participants with prehypertension and hypertension in the warm season. Comprehensive health education and effective intervention strategies should be implemented to mitigate the effects of temperature variations on BP, particularly among prehypertensive and hypertensive populations.
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Affiliation(s)
- Xiaojin Yan
- Institute of Population Research, Peking University, Beijing 100871, China
| | - Jiajia Li
- Institute of Population Research, Peking University, Beijing 100871, China
| | - Jilei Wu
- Institute of Population Research, Peking University, Beijing 100871, China
| | - Shiqi Lin
- Institute of Population Research, Peking University, Beijing 100871, China
| | - Zengwu Wang
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, Peking Union Medical College & Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 102308, China.
| | - Lijun Pei
- Institute of Population Research, Peking University, Beijing 100871, China.
| | - Congyi Zheng
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, Peking Union Medical College & Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 102308, China
| | - Xin Wang
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, Peking Union Medical College & Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 102308, China
| | - Xue Cao
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, Peking Union Medical College & Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 102308, China
| | - Zhen Hu
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, Peking Union Medical College & Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 102308, China
| | - Yixin Tian
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, Peking Union Medical College & Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 102308, China
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Zhang T, Ni M, Jia J, Deng Y, Sun X, Wang X, Chen Y, Fang L, Zhao H, Xu S, Ma Y, Zhu J, Pan F. Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China. BMC Public Health 2023; 23:2363. [PMID: 38031031 PMCID: PMC10685562 DOI: 10.1186/s12889-023-17299-8] [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: 06/25/2023] [Accepted: 11/22/2023] [Indexed: 12/01/2023] Open
Abstract
As climate conditions deteriorate, human health faces a broader range of threats. This study aimed to determine the risk of death from metabolic syndrome (MetS) due to meteorological factors. We collected daily data from 2014 to 2020 in Wuhu City, including meteorological factors, environmental pollutants and death data of common MetS (hypertension, hyperlipidemia and diabetes), as well as a total number of 15,272 MetS deaths. To examine the relationship between meteorological factors, air pollutants, and MetS mortality, we used a generalized additive model (GAM) combined with a distributed delay nonlinear model (DLNM) for time series analysis. The relationship between the above factors and death outcomes was preliminarily evaluated using Spearman analysis and structural equation modeling (SEM). As per out discovery, diurnal temperature range (DTR) and daily mean temperature (T mean) increased the MetS mortality risk notably. The ultra low DTR raised the MetS mortality risk upon the general people, with the highest RR value of 1.033 (95% CI: 1.002, 1.065) at lag day 14. In addition, T mean was also significantly associated with MetS death. The highest risk of ultra low and ultra high T mean occured on the same day (lag 14), RR values were 1.043 (95% CI: 1.010, 1.077) and 1.032 (95% CI: 1.003, 1.061) respectively. Stratified analysis's result showed lower DTR had a more pronounced effect on women and the elderly, and ultra low and high T mean was a risk factor for MetS mortality in women and men. The elderly need to take extra note of temperature changes, and different levels of T mean will increase the risk of death. In warm seasons, ultra high RH and T mean can increase the mortality rate of MetS patients.
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Affiliation(s)
- Tao Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Man Ni
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Juan Jia
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Yujie Deng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Xiaoya Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Xinqi Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Yuting Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Lanlan Fang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Hui Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Shanshan Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Yubo Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Jiansheng Zhu
- Wuhu center for disease control and prevention, Wuhu, Anhui, China
| | - Faming Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
- Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
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