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Wang X, Zhang Y, Tarik B, Zhang K, Lin S, Deng X, Gu H, Wu W, Lin X, Du Z, Wang Y, Qu Y, Lin Z, Zhang M, Sun Y, Dong GH, Wei Y, Zhang W, Hao Y. The effect of residential greenness on cardiovascular mortality from a large cohort in South China: An in-depth analysis of effect modification by multiple demographic and lifestyle characteristics. ENVIRONMENT INTERNATIONAL 2024; 190:108894. [PMID: 39047544 DOI: 10.1016/j.envint.2024.108894] [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: 03/18/2024] [Revised: 06/24/2024] [Accepted: 07/16/2024] [Indexed: 07/27/2024]
Abstract
BACKGROUND The potential for residential greenness to improve cardiovascular health through both physical and psychological mechanisms is well recognized. However, evidence from rapidly urbanizing developing countries and cohort-based causal inference approaches, remains limited. We aim to examine the effect of residential greenness and time to cardiovascular mortality in South China. METHODS We utilized data from a community-based population survey involving 748,209 participants at baseline from 2009 to 2015, followed up until 2020. Residential greenness exposure was assessed by the annual Normalized Difference Vegetation Index (NDVI) in the 500 m radius of each participant's residence. We used time-varying proportional hazard Cox models coupled with inverse probability weighting to fit marginal structural models and obtain hazard ratios (HRs) for cardiovascular disease (CVD) mortality after adjusting for confounders. Multiple effect modifiers on both additive and multiplicative scales were further explored. RESULTS A total of 15,139 CVD-related deaths were identified during a median of 7.9 years of follow-up. A protective effect was found between higher greenness exposure and reduced CVD mortality, with a 9.3 % lower rate of total CVD mortality (HR 0.907, 95 % CI 0.859-0.957) based on a 0.1 increase in annual average NDVI. Demographic (age, marital status) and lifestyle factors (smoking, drinking status) were found to modify the association between residential greenness and CVD mortality (all P interaction values < 0.05 or 95 %CI for RERI excluded the value 0). Notably, this effect was more pronounced among older adults, married, and individuals having healthier lifestyles, indicating a greater benefit from greenness for these subgroups. CONCLUSIONS Our findings support a causal link between increased residential greenness exposure and a reduced risk of CVD mortality in South China with marked heterogenous effects, which has public health implications for cultivating greener urban environments to mitigate the impact of CVD within the context of rapid urbanization.
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Affiliation(s)
- Xiaowen Wang
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Yuqin Zhang
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China; Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Benmarhnia Tarik
- Scripps Institution of Oceanography, University of California, San Diego, CA, USA; Univ Rennes, Inserm, EHESP, Irset (Institut de Recherche En Santé, Environnement Et Travail) - UMR_S 1085, Rennes, France
| | - Kai Zhang
- Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, Rensselaer, NY, USA
| | - Shao Lin
- Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, Rensselaer, NY, USA
| | - Xinlei Deng
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Haogao Gu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Wenjing Wu
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiao Lin
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Ying Wang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yanji Qu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangdong, China
| | - Ziqiang Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China
| | - Man Zhang
- Department of Nosocomial Infection Management, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Yongqing Sun
- Department of Ultrasound, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Guang-Hui Dong
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yongyue Wei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China.
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China.
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Silveira IH, Hartwig SV, Moura MN, Cortes TR, Junger WL, Cirino G, Ignotti E, de Oliveira BFA. Heat waves and mortality in the Brazilian Amazon: Effect modification by heat wave characteristics, population subgroup, and cause of death. Int J Hyg Environ Health 2023; 248:114109. [PMID: 36599199 DOI: 10.1016/j.ijheh.2022.114109] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 12/23/2022] [Accepted: 12/30/2022] [Indexed: 01/03/2023]
Abstract
BACKGROUND The Brazilian Amazon faces overlapping socio-environmental, sanitary, and climate challenges, and is a hotspot of concern due to projected increases in temperature and in the frequency of heat waves. Understanding the effects of extreme events on health is a central issue for developing climate policies focused on the population's health. OBJECTIVES We investigated the effects of heat waves on mortality in the Brazilian Amazon, examining effect modification according to various heat wave definitions, population subgroups, and causes of death. METHODS We included all 32 Amazonian municipalities with more than 100,000 inhabitants. The study period was from 2000 to 2018. We obtained mortality data from the Information Technology Department of the Brazilian Public Healthcare System, and meteorological data were derived from the ERA5-Land reanalysis dataset. Heat waves were defined according to their intensity (90th; 92.5th; 95th; 97.5th and 99th temperature percentiles) and duration (≥2, ≥3, and ≥4 days). In each city, we used a time-stratified case-crossover study to estimate the effects of each heat wave definition on mortality, according to population subgroup and cause of death. The lagged effects of heat waves were estimated using conditional Poisson regression combined with distributed lag non-linear models. Models were adjusted for specific humidity and public holidays. Risk ratios were pooled for the Brazilian Amazon using a univariate random-effects meta-analysis. RESULTS The pooled relative risks (RR) for mortality from total non-external causes varied between 1.03 (95% CI: 1.01-1.06), for the less stringent heat wave definition, and 1.18 (95% CI: 1.04-1.33) for the more stringent definition. The mortality risk rose as the heat wave intensity increased, although the increase from 2 to 3, and 3-4 days was small. Although not statistically different, our results suggest a higher mortality risk for the elderly, this was also higher for women than men, and for cardiovascular causes than for non-external or respiratory ones. CONCLUSIONS Heat waves were associated with a higher risk of mortality from non-external causes and cardiovascular diseases. Heat wave intensity played a more important role than duration in determining this risk. Suggestive evidence indicated that the elderly and women were more vulnerable to the effects of heat waves on mortality.
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Affiliation(s)
| | | | - Maurício Nascimento Moura
- Institute of Collective Health, Federal University of Bahia, Salvador, Brazil; Geosciences Institute, Federal University of Pará, Belém, Brazil
| | | | | | - Glauber Cirino
- Geosciences Institute, Federal University of Pará, Belém, Brazil
| | - Eliane Ignotti
- Postgraduate Program in Environmental Sciences, Mato Grosso State University, Cáceres, Brazil
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Zhao Z, Chu J, Xu X, Cao Y, Schikowski T, Geng M, Chen G, Bai G, Hu K, Xia J, Ma W, Liu Q, Lu Z, Guo X, Zhao Q. Association between ambient cold exposure and mortality risk in Shandong Province, China: Modification effect of particulate matter size. Front Public Health 2023; 10:1093588. [PMID: 36684922 PMCID: PMC9850236 DOI: 10.3389/fpubh.2022.1093588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 12/06/2022] [Indexed: 01/06/2023] Open
Abstract
Introduction Numerous studies have reported the modification of particulate matters (PMs) on the association between cold temperature and health. However, it remains uncertain whether the modification effect may vary by size of PMs, especially in Shandong Province, China where the disease burdens associated with cold temperature and PMs are both substantial. This study aimed to examine various interactive effects of cold exposure and ambient PMs with diameters ≤1/2.5 μm (PM1 and PM2.5) on premature deaths in Shandong Province, China. Methods In the 2013-2018 cold seasons, data on daily mortality, PM1 and PM2.5, and weather conditions were collected from the 1822 sub-districts of Shandong Province. A time-stratified case-crossover study design was performed to quantify the cumulative association between ambient cold and mortality over lag 0-12 days, with a linear interactive term between temperature and PM1 and PM2.5 additionally added into the model. Results The mortality risk increased with temperature decline, with the cumulative OR of extreme cold (-16.9°C, the 1st percentile of temperature range) being 1.83 (95% CI: 1.66, 2.02), compared with the minimum mortality temperature. The cold-related mortality risk was 2.20 (95%CI: 1.83, 2.64) and 2.24 (95%CI: 1.78, 2.81) on high PM1 and PM2.5 days, which dropped to 1.60 (95%CI: 1.39, 1.84) and 1.60 (95%CI: 1.37, 1.88) on low PM1 and PM2.5 days. PM1 showed greater modification effect for per unit concentration increase than PM2.5. For example, for each 10?g/m3 increase in PM1 and PM2.5, the mortality risk associated with extreme cold temperature increased by 7.6% (95% CI: 1.3%, 14.2%) and 2.6% (95% CI: -0.7%, 5.9%), respectively. Discussion The increment of smaller PMs' modification effect varied by population subgroups, which was particularly strong in the elderly aged over 75 years and individuals with middle school education and below. Specific health promotion strategies should be developed towards the greater modification effect of smaller PMs on cold effect.
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Affiliation(s)
- Zhonghui Zhao
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, China,Shandong University Climate Change and Health Center, Jinan, China
| | - Jie Chu
- Shandong Center for Disease Control and Prevention, Jinan, China,Academy of Preventive Medicine, Shandong University, Jinan, China
| | - Xiaohui Xu
- Shandong Center for Disease Control and Prevention, Jinan, China,Academy of Preventive Medicine, Shandong University, Jinan, China
| | - Yanwen Cao
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, China,Shandong University Climate Change and Health Center, Jinan, China
| | - Tamara Schikowski
- Department of Epidemiology, Leibniz Institute for Environmental Medicine (IUF)-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Mengjie Geng
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Gongbo Chen
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Guannan Bai
- Department of Child Health Care, The Children's Hospital, National Clinical Research Center for Child Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Kejia Hu
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
| | - Jingjing Xia
- School of Life Sciences, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
| | - Wei Ma
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, China,Shandong University Climate Change and Health Center, Jinan, China
| | - Qiyong Liu
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zilong Lu
- Shandong Center for Disease Control and Prevention, Jinan, China,Academy of Preventive Medicine, Shandong University, Jinan, China
| | - Xiaolei Guo
- Shandong Center for Disease Control and Prevention, Jinan, China,Academy of Preventive Medicine, Shandong University, Jinan, China,Xiaolei Guo ✉
| | - Qi Zhao
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, China,Shandong University Climate Change and Health Center, Jinan, China,Department of Epidemiology, Leibniz Institute for Environmental Medicine (IUF)-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany,*Correspondence: Qi Zhao ✉
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Relationship between Depressive Symptoms and Weather Conditions. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19095069. [PMID: 35564464 PMCID: PMC9101342 DOI: 10.3390/ijerph19095069] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/31/2022] [Accepted: 04/20/2022] [Indexed: 12/10/2022]
Abstract
Background: Weather is a well-known factor worldwide in psychiatric problems such as depression, with the elderly and females being particularly susceptible. The aim of this study was to detect associations between the risk of depressive symptoms (DS) and weather variables. Methods: 6937 participants were assessed in the baseline survey of the Health Alcohol Psychosocial Factors in Eastern Europe (HAPIEE) study during 2006−2008. To assess the risk of DS, a multivariate logistic model was created with predictors such as socio-demographic factors, health behaviors, and weather variables. Results: DS were found in 23.4% of the respondents, in 15.6% of males and in 29.9% in females. A higher risk of DS (by 25%) was associated with November−December, a rising wind speed, and relative humidity (RH) < 94% and snowfall during the cold period occurring 2 days before the survey. A higher air temperature (>14.2 °C) predominant during May−September had a protective impact. A higher risk of DS in males was associated with lower atmospheric pressure (<1009 hPa) 2 days before. Females were more sensitive to the monthly variation, snowfall, and RH. Conclusions: The findings of our study suggest that some levels of weather variables have a statistically significant effect on DS.
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