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Yang L, Chen H, Gao H, Wang Y, Chen T, Svartengren M, Norbäck D, Wei J, Zheng X, Zhang L, Lu C, Yu W, Wang T, Ji JS, Meng X, Zhao Z, Zhang X. Prenatal and postnatal early life exposure to greenness and particulate matter of different size fractions in relation to childhood rhinitis - A multi-center study in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 938:173402. [PMID: 38797418 DOI: 10.1016/j.scitotenv.2024.173402] [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: 12/20/2023] [Revised: 05/18/2024] [Accepted: 05/19/2024] [Indexed: 05/29/2024]
Abstract
The impact of early life exposure to residential greenness on childhood rhinitis and its interaction with particulate matter (PM) of different size fractions remain inconsistent. Herein, we recruited 40,486 preschool children from randomly selected daycare centers in 7 cities in China from 2019 to 2020, and estimated exposure to residential greenness by the normalized difference vegetation index (NDVI) with a 500 m buffer. Exposure to ambient PM (PM1, PM2.5, and PM10) was evaluated using a satellite-based prediction model (daily, at a resolution of 1 km × 1 km). By mixed-effect logistic regression, NDVI values during pregnancy, in the first (0-1 year old) and the second (1-2 years old) year of life were negatively associated with lifetime rhinitis (LR) and current rhinitis (CR) (P < 0.001). PM in the same time windows was associated with increased risks of LR and CR in children, with smaller size fraction of PM showing greater associations. The negative associations between prenatal and postnatal NDVI and LR and CR in preschool children remained robust after adjusting for concomitant exposure to PM, whereas the associations of postnatal NDVI and rhinitis showed significant interactions with PM. At lower levels of PM, postnatal NDVI remained negatively associated with rhinitis and was partly mediated by PM (10.0-40.9 %), while at higher levels of PM, the negative associations disappeared or even turned positive. The cut-off levels of PM were identified for each size fraction of PM. In conclusion, prenatal exposure to greenness had robust impacts in lowering the risk of childhood rhinitis, while postnatal exposure to greenness depended on the co-exposure levels to PM. This study revealed the complex interplay of greenness and PM on rhinitis in children. The exposure time window in prenatal or postnatal period and postnatal concomitant PM levels played important roles in influencing the associations between greenness, PM and rhinitis.
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Affiliation(s)
- Liu Yang
- Institute of Environmental Science, Shanxi University, Taiyuan, 030006, China
| | - Han Chen
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment (Fudan University), Fudan University, Shanghai 200032, China
| | - Huiyu Gao
- Institute of Environmental Science, Shanxi University, Taiyuan, 030006, China
| | - Ying Wang
- Institute of Environmental Science, Shanxi University, Taiyuan, 030006, China
| | - Tianyi Chen
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment (Fudan University), Fudan University, Shanghai 200032, China
| | - Magnus Svartengren
- Department of Occupational and Environmental Medicine, Uppsala University Hospital, 751 85 Uppsala, Sweden
| | - Dan Norbäck
- Department of Occupational and Environmental Medicine, Uppsala University Hospital, 751 85 Uppsala, Sweden
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | - Xiaohong Zheng
- School of Energy & Environment, Southeast University, Nanjing 210096, China
| | - Ling Zhang
- Department of Environmental Hygiene and Occupational Medicine, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Chan Lu
- Department of Occupational and Environmental Health, School of Public Health, Xiangya Medical College, Central South University, Changsha 410078, China
| | - Wei Yu
- Key Laboratory of Three Gorges Reservoir Region's Eco-Environment, Chongqing University, Chongqing 400030, China
| | - Tingting Wang
- School of Nursing & Health Management, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | - John S Ji
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China
| | - Xia Meng
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment (Fudan University), Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of the Ministry of Education, 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.
| | - Zhuohui Zhao
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment (Fudan University), Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of the Ministry of Education, 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.
| | - Xin Zhang
- Institute of Environmental Science, Shanxi University, Taiyuan, 030006, China.
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Chen Z, Wu F, Shi Y, Guo Y, Xu J, Liang S, Huang Z, He G, Hu J, Zhu Q, Yu S, Yang S, Wu C, Tang W, Dong X, Ma W, Liu T. Association of Residential Greenness Exposure with Depression Incidence in Adults 50 Years of Age and Older: Findings from the Cohort Study on Global AGEing and Adult Health (SAGE) in China. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:67004. [PMID: 38885140 PMCID: PMC11218708 DOI: 10.1289/ehp13947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 04/07/2024] [Accepted: 05/20/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND Depression is a social and public health problem of great concern globally. Identifying and managing the factors influencing depression are crucial for preventing and decreasing the burden of depression. OBJECTIVES Our objectives are to explore the association between residential greenness and the incidence of depression in an older Chinese population and to calculate the disease burden of depression prevented by greenness exposure. METHODS This study was the Chinese part of the World Health Organization Study on Global AGEing and Adult Health (WHO SAGE). We collected the data of 8,481 residents ≥ 50 years of age in China for the period 2007-2018. Average follow-up duration was 7.00 (± 2.51 ) years. Each participant was matched to the yearly maximum normalized difference vegetation index (NDVI) at their residential address. Incidence of depression was assessed using the Composite International Diagnostic Interview (CIDI), self-reports of depression, and/or taking depression medication. Association between greenness and depression was examined using the time-dependent Cox regression model with stratified analysis by sex, age, urbanicity, annual family income, region, smoking, drinking, and household cooking fuels. Furthermore, the prevented fraction (PF) and attributable number (AN) of depression prevented by exposure to greenness were estimated. RESULTS Residential greenness was negatively associated with depression. Each interquartile range (IQR) increase in NDVI 500 -m buffer was associated with a 40% decrease [hazard ratio ( HR ) = 0.60 ; 95% confidence interval (CI): 0.37, 0.97] in the risk of depression incidence among the total participants. Subgroup analyses showed negative associations in urban residents (HR = 0.32 ; 95% CI: 0.12, 0.86) vs. rural residents, in high-income residents (HR = 0.28 ; 95% CI: 0.11, 0.71) vs. low-income residents, and in southern China (HR = 0.50 ; 95% CI: 0.26, 0.95) vs. northern China. Over 8.0% (PF = 8.69 % ; 95% CI: 1.38%, 15.40%) and 1,955,199 (95% CI: 310,492; 3,464,909) new cases of depression may be avoided by increasing greenness exposures annually across China. DISCUSSION The findings suggest protective effects of residential greenness exposure on depression incidence in the older population, particularly among urban residents, high-income residents, and participants living in southern China. The construction of residential greenness should be included in community planning. https://doi.org/10.1289/EHP13947.
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Affiliation(s)
- Zhiqing Chen
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
- Key Laboratory of Viral Pathogenesis & Infection Prevention and Control (Jinan University), Ministry of Education, Guangzhou, China
| | - Fan Wu
- Shanghai Medical College, Fudan University, Shanghai, China
| | - Yan Shi
- Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, China
| | - Yanfei Guo
- Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, China
| | - Jiahong Xu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
| | - Shuru Liang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
| | - Zhongguo Huang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
| | - Jianxiong Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
| | - Qijiong Zhu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
| | - Siwen Yu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
| | - Shangfeng Yang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
| | - Cuiling Wu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
| | - Weiling Tang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
| | - Xiaomei Dong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
- Key Laboratory of Viral Pathogenesis & Infection Prevention and Control (Jinan University), Ministry of Education, Guangzhou, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou, China
- Key Laboratory of Viral Pathogenesis & Infection Prevention and Control (Jinan University), Ministry of Education, Guangzhou, China
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Lamichhane DK, Ha E, Hong YC, Lee DW, Park MS, Song S, Kim S, Kim WJ, Bae J, Kim HC. Ambient particulate matter and surrounding greenness in relation to sleep quality among pregnant women: A nationwide cohort study. Heliyon 2024; 10:e26742. [PMID: 38434397 PMCID: PMC10904245 DOI: 10.1016/j.heliyon.2024.e26742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 02/08/2024] [Accepted: 02/19/2024] [Indexed: 03/05/2024] Open
Abstract
Background Particulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed. Objective This cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women. Methods Pregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM. Results After adjusting for confounders, each 10 μg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%-56% of the association between residential greenness and poor sleep quality. Conclusions This study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health.
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Affiliation(s)
- Dirga Kumar Lamichhane
- Department of Occupational and Environmental Medicine, Inha University School of Medicine, Incheon, Republic of Korea
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Eunhee Ha
- Department of Occupational and Environmental Medicine, Ewha Womans University School of Medicine, Seoul, Republic of Korea
| | - Yun-Chul Hong
- Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Dong-Wook Lee
- Department of Occupational and Environmental Medicine, Inha University School of Medicine, Incheon, Republic of Korea
| | - Myung-Sook Park
- Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Sanghwan Song
- Environmental Health Research Division, Department of Environmental Health Research, National Institute of Environmental Research, Ministry of Environment, Incheon, Republic of Korea
| | - Suejin Kim
- Environmental Health Research Division, Department of Environmental Health Research, National Institute of Environmental Research, Ministry of Environment, Incheon, Republic of Korea
| | - Woo Jin Kim
- Department of Internal Medicine and Environmental Health Center, Kangwon National University, Chuncheon, Republic of Korea
| | - Jisuk Bae
- Department of Preventive Medicine, Daegu Catholic University School of Medicine, Daegu, Republic of Korea
| | - Hwan-Cheol Kim
- Department of Occupational and Environmental Medicine, Inha University School of Medicine, Incheon, Republic of Korea
| | - Ko-CHENS Study Group
- Department of Occupational and Environmental Medicine, Inha University School of Medicine, Incheon, Republic of Korea
- Department of Psychiatry, Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
- Department of Occupational and Environmental Medicine, Ewha Womans University School of Medicine, Seoul, Republic of Korea
- Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
- Environmental Health Research Division, Department of Environmental Health Research, National Institute of Environmental Research, Ministry of Environment, Incheon, Republic of Korea
- Department of Internal Medicine and Environmental Health Center, Kangwon National University, Chuncheon, Republic of Korea
- Department of Preventive Medicine, Daegu Catholic University School of Medicine, Daegu, Republic of Korea
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Zhang Y, Wu T, Yu H, Fu J, Xu J, Liu L, Tang C, Li Z. Green spaces exposure and the risk of common psychiatric disorders: A meta-analysis. SSM Popul Health 2024; 25:101630. [PMID: 38405164 PMCID: PMC10885792 DOI: 10.1016/j.ssmph.2024.101630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 02/07/2024] [Accepted: 02/13/2024] [Indexed: 02/27/2024] Open
Abstract
Objective To explore the effects of green spaces exposure on common psychiatric disorders. Methods PubMed, Embase, Web of Science and MEDLINE were screened and articles published prior to November 15, 2023 were included. Analyses were performed on common psychiatric disorders, categorized into depression, anxiety, dementia, schizophrenia, and attention deficit hyperactivity disorder (ADHD). And the subgroup analyses were conducted for depression, anxiety, dementia, and schizophrenia. Results In total, 2,0064 studies were retrieved, 59 of which were included in our study; 37 for depression, 14 for anxiety, 8 for dementia, 7 for schizophrenia and 5 for ADHD. Green spaces were found to benefit the moderation of psychiatric disorders (OR = 0.91, 95% CI: 0.89 to 0.92). Green spaces positively influence depression (OR = 0.89, 95% CI: 0.86 to 0.93), regardless of the cross-sectional or cohort studies. Green spaces can also help mitigate the risk of anxiety (OR = 0.94, 95%CI:0.92 to 0.96). As an important index for measuring green spaces, a higher normalized difference vegetation index (NDVI) level related to a lower level of depression (OR = 0.95, 95%CI:0.91 to 0.98) and anxiety (OR = 0.95, 95%:0.92 to 0.98). The protection was also found in dementia (OR = 0.95, 95% CI: 0.93 to 0.96), schizophrenia (OR = 0.74, 95% CI: 0.67 to 0.82), and ADHD (OR = 0.89, 95% CI: 0.86 to 0.92) results. Conclusion Green spaces decrease the risk of psychiatric disorders, including depression, anxiety, dementia, schizophrenia, and ADHD. Further studies on green spaces and psychiatric disorders are needed, and more green spaces should be considered in city planning.
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Affiliation(s)
- Yimin Zhang
- School of Public Health, Health Science Center, Ningbo University, Ningbo, China
| | - Tongyan Wu
- School of Public Health, Health Science Center, Ningbo University, Ningbo, China
| | - Hao Yu
- Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Department of Urology, The Second Clinical Medical College of Nanjing Medical University, Nanjing, China
| | - Jianfei Fu
- Department of Medical Records and Statistics, Ningbo First Hospital, Ningbo, China
| | - Jin Xu
- School of Public Health, Health Science Center, Ningbo University, Ningbo, China
| | - Liya Liu
- School of Public Health, Health Science Center, Ningbo University, Ningbo, China
| | - Chunlan Tang
- School of Public Health, Health Science Center, Ningbo University, Ningbo, China
| | - Zhen Li
- School of Public Health, Health Science Center, Ningbo University, Ningbo, China
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Fossa AJ, D'Souza J, Bergmans R, Zivin K, Adar SD. Residential greenspace and major depression among older adults living in urban and suburban areas with different climates across the United States. ENVIRONMENTAL RESEARCH 2024; 243:117844. [PMID: 38061587 DOI: 10.1016/j.envres.2023.117844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Revised: 11/04/2023] [Accepted: 11/30/2023] [Indexed: 12/22/2023]
Abstract
BACKGROUND AND AIM Residential greenspace could alleviate depression - a leading cause of disability. Fewer studies of depression and greenspace have considered major depression, and, to our knowledge, none have considered how climate, which determines vegetation abundance and type, may change the impacts of greenspace. Our aim was to investigate whether residential greenspace is associated with major depression among older adults and explore effect modification by climate. METHODS We used biennial interviews between 2008 and 2016 from the Health and Retirement Study. We calculated greenness within walking distance of home addresses as the maximum NDVI for the year of each participant interview averaged within a 1 km buffer. Reflecting clinical criteria, a score of ≥5 on the CIDI-SF indicated major depression in the preceding 12-months. We characterized climate using Köppen-Geiger classifications. To estimate prevalence ratios, we used Poisson regression. Our models adjusted for sociodemographic characteristics, geography, annual sunshine, and bluespace. RESULTS The 21,611 eligible participants were 65 ± 10 years old on average, 55% female, 81% White, 12% Black, 10% Hispanic/Latino, and 31% had at least a 4-year college degree. The 12-month prevalence of a major depression was 8%. In adjusted models, more residential greenspace was associated with a lower prevalence of major depression (prevalence ratio per IQR, 0.91; 95% CI, 0.84 to 0.98). There was evidence of effect modification by climate (P forinteraction, 0.062). We observed stronger associations in tropical (prevalence ratio per IQR 0.69; 95% CI, 0.47 to 1.01) and cold (prevalence ratio per IQR, 0.83; 95% CI, 0.74 to 0.93) climates compared to arid (prevalence ratio per IQR 0.99; 95% CI, 0.90 to 1.09) and temperate (prevalence ratio per IQR 0.98; 95% CI, 0.86 to 1.11) climates. CONCLUSIONS Residential greenspace may help reduce major depression. However, climate may influence how people benefit from greenspace.
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Affiliation(s)
- Alan J Fossa
- University of Michigan School of Public Health, Department of Epidemiology, Ann Arbor, MI, United States.
| | - Jennifer D'Souza
- University of Michigan School of Public Health, Department of Epidemiology, Ann Arbor, MI, United States
| | - Rachel Bergmans
- University of Michigan, Medical School, Department of Anesthesiology, Ann Arbor, MI, United States
| | - Kara Zivin
- University of Michigan Medical School, Department of Psychiatry, Ann Arbor, MI, United States; VA Ann Arbor Healthcare System, Center for Clinical Management Research, Ann Arbor, MI, United States
| | - Sara D Adar
- University of Michigan School of Public Health, Department of Epidemiology, Ann Arbor, MI, United States
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Wang P, Wang M, Shan J, Liu X, Jing Y, Zhu H, Zheng G, Peng W, Wang Y. Association between residential greenness and depression symptoms in Chinese community-dwelling older adults. ENVIRONMENTAL RESEARCH 2024; 243:117869. [PMID: 38070849 DOI: 10.1016/j.envres.2023.117869] [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: 09/19/2023] [Revised: 11/23/2023] [Accepted: 12/02/2023] [Indexed: 02/06/2024]
Abstract
BACKGROUND Studies of residential greenness and depression symptoms among community-dwelling older adults in China are limited. However, understanding the role of greenness in depression symptoms among older adults can inform depression prevention and interventions. OBJECTIVE This study explored the relationship between residential greenness and depression symptoms among community-dwelling older adults in China. METHODS A cluster random sampling method was used to survey 7512 community-dwelling adults aged 60 and above from three towns in Shanghai. Depression symptoms were assessed using the Geriatric Depression Scale (GDS30). Residential greenness was measured using the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). Long-term greenspace exposure was defined as the mean NDVI and EVI in the three years prior to the baseline survey. Controlling for the covariates, the relationship between greenness and depression symptoms was assessed using binomial logistic regression and mixed-effects linear regression. Interaction analysis was conducted to explore which covariates potentially alter the association. We also assessed the mediating role of physical activity. RESULTS The prevalence of depression symptoms among the participants was 13.72%. Higher residential greenness was associated with lower odds of depression symptoms, after adjusting for covariates. In the logistic regression analysis, the odds of depression symptoms decreased with increasing NDVI and EVI. In linear regression analysis, GDS30 scores decreased with increasing NDVI and EVI. Interaction analyses revealed that higher NDVI and EVI were more protective against depression among male individuals and older adults living with others than among female individuals and older adults living alone. Additionally, physical activity had a masking effect on residential greenness and depression symptoms. CONCLUSION Higher residential greenness is associated with lower odds of depression symptoms in community-dwelling Chinese older adults. Increasing urban and neighborhood green spaces may contribute to the prevention and intervention of depression symptoms in community-dwelling older adults.
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Affiliation(s)
- Pengfei Wang
- School of Public Health, Fudan University, Shanghai, China; NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Meng Wang
- Human Resources Department, Eye & Ent Hospital, Fudan University, Shanghai, China
| | - Jiatong Shan
- Arts and Science Department, New York University Shanghai, Shanghai, China
| | - Xinya Liu
- School of Public Health, Fudan University, Shanghai, China; NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Yurong Jing
- School of Public Health, Fudan University, Shanghai, China; NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Hongfei Zhu
- School of Public Health, Fudan University, Shanghai, China; NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Guang Zheng
- Shanghai Institute of Occupational Disease for Chemical Industry, Shanghai, China.
| | - Wenjia Peng
- School of Public Health, Fudan University, Shanghai, China; NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China.
| | - Ying Wang
- School of Public Health, Fudan University, Shanghai, China; NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China.
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Guo X, Su W, Wang X, Hu W, Meng J, Ahmed MA, Qu G, Sun Y. Assessing the effects of air pollution and residential greenness on frailty in older adults: a prospective cohort study from China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:9091-9105. [PMID: 38183550 DOI: 10.1007/s11356-023-31741-9] [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: 08/08/2023] [Accepted: 12/22/2023] [Indexed: 01/08/2024]
Abstract
Many studies have established a correlation between air pollution and green space with age-related diseases, yet the relationship between air pollution, green space, and frailty among older adults is not fully understood. The primary objective of this investigation is to examine the longitudinal association among air pollution, green space, and frailty in older adults, as well as the potential interaction and mediating effect. Analyzed data were obtained from the multi-wave CLHLS investigation (2008-2018). The participants' environmental exposure was evaluated using six air pollutants (PM1, PM2.5, PM10, PM10-2.5, O3, and NO2), and normalized difference vegetation index (NDVI). Annual ambient air pollutants were estimated using satellite-based spatiotemporal models. Time-varying Cox proportional risk models were employed to investigate the longitudinal relationships between air pollutants, greenness, and the onset of frailty in the elderly population. We conducted a variety of subgroup analyses, sensitivity analyses, and assessed potential interaction and causal mediating effects. A total of 6953 eligible elderly individuals were enrolled in our study. In the fully adjusted model, per IQR uptick in levels of PM1, PM2.5, PM10, PM10-2.5, O3, and NO2 corresponded to a 17% (95% CI 1.10-1.24), 25% (95% CI 1.17-1.34), 29% (95% CI 1.20-1.39), 35% (95% CI 1.24-1.47), 12% (95% CI 1.04-1.20), and 11% (95% CI 1.05-1.18) increase in frailty risk, respectively. For NDVI, increased IQR was significantly negatively associated with the risk of frailty (aHR 0.82, 95% CI 0.77-0.87). Our results revealed a significant interaction effect among O3, NO2, and residential greenness. PM1, PM2.5, PM10, and PM10-2.5 play a mediating role in the estimated relationship between residential greenness and frailty. In summary, our study reveals that PM1, PM2.5, PM10, PM10-2.5, O3, and NO2 correspond to elevated risks of frailty in the elderly. Residential greenness is associated with a lower risk of frailty in the elderly. Residential greenness can exert a positive impact on frailty by reducing particulate matter concentrations.
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Affiliation(s)
- Xianwei Guo
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Wenqi Su
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Xingyue Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Wenjing Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Jia Meng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Mubashir Ayaz Ahmed
- Division of Pulmonary Critical Care and Sleep Medicine, Albert Einstein Medical Center, Philadelphia, PA, USA
| | - Guangbo Qu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Yehuan Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China.
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Tondelli M, Chiari A, Vinceti G, Galli C, Salemme S, Filippini T, Carbone C, Minafra C, De Luca C, Prandi R, Tondelli S, Zamboni G. Greenness and neuropsychiatric symptoms in dementia. ENVIRONMENTAL RESEARCH 2024; 242:117652. [PMID: 37980996 DOI: 10.1016/j.envres.2023.117652] [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: 08/28/2023] [Revised: 11/10/2023] [Accepted: 11/11/2023] [Indexed: 11/21/2023]
Abstract
OBJECTIVES It is acknowledged that living in a green environment may help mental well-being and this may be especially true for vulnerable people. However, the relationship between greenness and neuropsychiatric symptoms in dementia has not been explored yet. METHODS We collected clinical, neuropsychiatric, and residential data from subjects with dementia living in the province of Modena, Northern Italy. Neuropsychiatric symptoms were measured with the Neuropsychiatry Inventory, a questionnaire administered to the caregiver who assesses the presence and severity of neuropsychiatric symptoms, including delusions, hallucinations, agitation/aggression, dysphoria/depression, anxiety, euphoria/elation, apathy/indifference, disinhibition, irritability/lability, aberrant motor behaviors, sleep disturbances, and appetite/eating changes. Normalized Difference Vegetation Index (NDVI) was used as a proxy of greenness. Regression models were constructed to study the association between greenness and neuropsychiatric features. RESULTS 155 patients with dementia were recruited. We found that greenness is variably associated with the risk of having neuropsychiatric symptoms. The risk of apathy was lower with lower levels of greenness (OR = 0.42, 95% CI 0.19-0.91 for NDVI below the median value). The risk of psychosis was higher with lower levels of greenness but with more imprecise values (OR = 1.77, 95% CI 0.84-3.73 for NDVI below the median value). CONCLUSION Our results suggest a possible association between greenness and neuropsychiatric symptoms in people with dementia. If replicated in larger samples, these findings will pave the road for identifying innovative greening strategies and interventions that can improve mental health in dementia.
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Affiliation(s)
- Manuela Tondelli
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Unit, Baggiovara Hospital, AOU Modena, Modena, Italy.
| | - Annalisa Chiari
- Neurology Unit, Baggiovara Hospital, AOU Modena, Modena, Italy
| | - Giulia Vinceti
- Neurology Unit, Baggiovara Hospital, AOU Modena, Modena, Italy
| | - Chiara Galli
- Primary Care Department, AUSL Modena, Modena, Italy
| | - Simone Salemme
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Tommaso Filippini
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; School of Public Health, University of California Berkeley, Berkeley, CA, USA
| | - Chiara Carbone
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Claudia Minafra
- Department of Architecture, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Claudia De Luca
- Department of Architecture, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Riccardo Prandi
- Department of Biological, Geological and Environmental Sciences (BiGeA), Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Simona Tondelli
- Department of Architecture, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Giovanna Zamboni
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Unit, Baggiovara Hospital, AOU Modena, Modena, Italy
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Wu W, Wu G, Wei J, Lawrence WR, Deng X, Zhang Y, Chen S, Wang Y, Lin X, Chen D, Ruan X, Lin Q, Li Z, Lin Z, Hao C, Du Z, Zhang W, Hao Y. Potential causal links and mediation pathway between urban greenness and lung cancer mortality: Result from a large cohort (2009 to 2020). SUSTAINABLE CITIES AND SOCIETY 2024; 101:105079. [PMID: 38222851 PMCID: PMC10783447 DOI: 10.1016/j.scs.2023.105079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
Urban greenness, as a vital component of the urban environment, plays a critical role in mitigating the adverse effects of rapid urbanization and supporting urban sustainability. However, the causal links between urban greenness and lung cancer mortality and its potential causal pathway remain poorly understood. Based on a prospective community-based cohort with 581,785 adult participants in southern China, we applied a doubly robust Cox proportional hazard model to estimate the causal associations between urban greenness exposure and lung cancer mortality. A general multiple mediation analysis method was utilized to further assess the potential mediating roles of various factors including particulate matter (PM1, PM2.5-1, and PM10-2.5), temperature, physical activity, and body mass index (BMI). We observed that each interquartile range (IQR: 0.06) increment in greenness exposure was inversely associated with lung cancer mortality, with a hazard ratio (HR) of 0.89 (95 % CI: 0.83, 0.96). The relationship between greenness and lung cancer mortality might be partially mediated by particulate matter, temperature, and physical activity, yielding a total indirect effect of 0.826 (95 % CI: 0.769, 0.887) for each IQR increase in greenness exposure. Notably, the protective effect of greenness against lung cancer mortality could be achieved primarily by reducing the particulate matter concentration.
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Affiliation(s)
- Wenjing Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Gonghua Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, USA
| | - Wayne R Lawrence
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Xinlei Deng
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, USA
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Shirui Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Ying Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xiao Lin
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Dan Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xinling Ruan
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Qiaoxuan Lin
- Department of Statistics, Guangzhou Health Technology Identification & Human Resources Assessment Center, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Ziqiang Lin
- Department of Preventive Medicine, School of Basic Medicine and Public Health, Jinan University, Guangzhou, China
| | - Chun Hao
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, China
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10
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Madonsela BS. A meta-analysis of particulate matter and nitrogen dioxide air quality monitoring associated with the burden of disease in sub-Saharan Africa. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2023; 73:737-749. [PMID: 37602776 DOI: 10.1080/10962247.2023.2248928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 08/01/2023] [Accepted: 08/07/2023] [Indexed: 08/22/2023]
Abstract
Exposure to air pollution is a fundamental obstacle that makes it complex to realize the Sustainable Development Goals (SDGs 3) for good health and wellbeing. It is for this reason that air pollution has been characterized as the global environmental health risk facing the current generation. The risks of air pollution on morbidity, and life expectancy are well documented. This feeds directly to the substantial body of the literature that exists regarding the burden of diseases associated with ambient air pollution. However, the bulk of this literature originates from developed countries. Whilst most of the sub-Saharan African studies extrapolate literature from developed countries to contextualize the risks of elevated air pollution exposure levels associated with the burden of disease. However, extrapolation of epidemiological evidence from developed countries is problematic given that it disregards the social vulnerability. Therefore, given this observation, it is ideal to evaluate if the monitoring executions of hazardous particulate matter and nitrogen dioxide do take into consideration the concerted necessary efforts to associate monitored air pollution exposure levels with the burden of disease. Therefore, based on this background, the current meta-analysis evaluated air quality monitoring associated with the burden of disease across sub-Saharan Africa. To this extent, the current meta-analysis strictly included peer-reviewed published journal articles from the sub-Saharan African regions to gain insight on air quality monitoring associated with the burden of disease. The collected meta-analysis data was captured and subsequently analyzed using Microsoft Excel 2019. This program facilitated the presentation of the meta-analysis data in the form of graphs and numerical techniques. Generally, the results indicate that the sub-Saharan Africa is characterized by a substantial gap in the number of regional studies that evaluate the burden of disease in relation with exposure to air quality.Implications: The work presented here is an original contribution and provides a comprehensive yet succinct overview of the monitoring associated with the burden of disease in sub-Saharan Africa. The author explores if the monitoring executions of hazardous particulate matter and nitrogen dioxide do take into considerations the concerted necessary efforts to associate monitored air pollution exposure levels with the burden of disease. The manuscript includes the most relevant and current literature in a field of study that has not received a deserving degree of research attention in recent years. This is especially true in sub-Saharan Africa, characterized by insufficient monitoring of air quality exposure concentrations.
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Affiliation(s)
- Benett Siyabonga Madonsela
- Department of Environmental and Occupational Studies, Faculty of Applied Sciences, Cape Peninsula University of Technology, Cape Town, South Africa
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11
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Zhang T, Huang B, Yan Y, Lin Y, Wong H, Wong SYS, Chung RYN. Street-view and traditional greenness metrics with adults' sitting time in high-density living in Hong Kong: Comparing associations, air pollution and noise roles, and population heterogeneity. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 870:161778. [PMID: 36716875 DOI: 10.1016/j.scitotenv.2023.161778] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 01/08/2023] [Accepted: 01/19/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Emerging evidence suggests neighborhood greenness is associated with physical activity; however, the sitting-specific associations with multi-source greenness metrics remain unclear, especially in high-density cities. OBJECTIVES This cross-sectional study examined: 1) the associations of street-view greenness (SVG) and traditional greenness metrics (i.e., Normalized Difference Vegetable Index (NDVI) and park density) with sitting time; 2) the potential moderating/mediating roles of objective/perceived air pollution and perceived roadside noise; and 3) how the associations vary by demographics and socioeconomic status. METHODS Interview survey data of 1977 adults in Hong Kong from 2014 and 2015 was linked to environmental data. Using an object-based image classification algorithm, SVG was derived from Google Street View images, capturing human-viewed street-level greenery. NDVI was derived from Landsat 8 satellite images using the normalized difference between the near-infrared and red bands. Park density was calculated by point density. In the main analyses including regressions, parallel mediation, interaction, and stratified models, the environmental metrics were measured within a 1000-m Euclidean buffer of residence. RESULTS SVG and park density were negatively associated with sitting time after adjusting for covariates including physical activity while NDVI was not significantly associated with sitting time, and results were robust with 800-1800 m Euclidean and 1400-1800 m network distance. Greenness-sitting associations were not moderated/mediated by perceived air pollution/roadside noise while SVG-sitting associations were moderated by objective NO2, O3, and PM2.5 and mediated by O3. SVG-sitting associations differed by age, having under-school-aged children, birthplace, education, and occupation type while associations between traditional greenness metrics and prolonged sitting showed no significant population heterogeneity. CONCLUSIONS SVG appears to be more accurate in estimating exposure than traditional metrics to reflect greenness-sitting associations, objective air pollution moderating and mediating roles, and population heterogeneity, which emphasizes the importance of street-level greenness planning for health promotion in terms of reducing sitting time.
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Affiliation(s)
- Ting Zhang
- School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai 200030, China; Institute of Space and Earth Information Science, The Chinese University of Hong Kong, 999077, Hong Kong.
| | - Bo Huang
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, 999077, Hong Kong; Department of Geography and Resource Management, The Chinese University of Hong Kong, 999077, Hong Kong; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China.
| | - Yizhen Yan
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, 999077, Hong Kong.
| | - Yinyi Lin
- Department of Geography, The University of Hong Kong, 999077, Hong Kong.
| | - Hung Wong
- Department of Social Work, The Chinese University of Hong Kong, 999077, Hong Kong; Institute of CUHK Institute of Health Equity, The Chinese University of Hong Kong, 999077, Hong Kong.
| | - Samuel Yeung-Shan Wong
- Institute of CUHK Institute of Health Equity, The Chinese University of Hong Kong, 999077, Hong Kong; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, 999077, Hong Kong.
| | - Roger Yat-Nork Chung
- Institute of CUHK Institute of Health Equity, The Chinese University of Hong Kong, 999077, Hong Kong; JC School of Public Health and Primary Care, The Chinese University of Hong Kong, 999077, Hong Kong.
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12
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Zhou W, Wang Q, Kadier A, Wang W, Zhou F, Li R, Ling L. The role of residential greenness levels, green land cover types and diversity in overweight/obesity among older adults: A cohort study. ENVIRONMENTAL RESEARCH 2023; 217:114854. [PMID: 36403655 DOI: 10.1016/j.envres.2022.114854] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 10/27/2022] [Accepted: 11/17/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Few studies have investigated the effects of greenness exposure, green land cover types and diversity and their interaction with particulate matter (PM) to adiposity. METHOD Cohort data were collected from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Baseline data on greenness levels, green land cover types and diversity were assessed by the Normalized Difference Vegetation Index (NDVI), three greenery types (trees, shrublands and grassland) and Shannon's diversity index, respectively. Body mass index (BMI) and waist circumference (WC) were separately used as dependent variables and represented for peripheral overweight/obesity and central obesity, respectively. The mixed Cox model with random intercept was used to estimate the effects of greenness levels, types and diversity on overweight/obesity using single and multiple exposure models. We also examined the interaction of PM and the aforementioned indicators on overweight/obesity on both additive and multiplicative scales. RESULTS Single exposure models showed that higher levels of residential greenness, tree coverage and ratio of trees to shrublands/grassland were inversely associated with peripheral overweight/obesity and central obesity. An increase in shrublands, grassland and diversity of green was related to lower odds of peripheral overweight/obesity. Multiple exposure models confirmed the association between greenness levels and peripheral overweight/obesity. Males, educated participants and elderly who lived in southern regions and areas with cleaner air environments acquired more benefits from greenspace exposure. Single and multiple exposure models indicated that an antagonistic effect of increasing PM and decreasing greenness levels on peripheral overweight/obesity and central obesity. Single exposure models showed the potential interaction of tree coverage, ratio of trees to grassland and PM2.5 exposures on the risk of peripheral overweight/obesity. CONCLUSION Increasing residential greenness and diversity of green were associated with healthy weight status. The relationship between greenery and overweight/obesity varied, and the effects of greenspace exposure on overweight/obesity were associated with air pollution.
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Affiliation(s)
- Wensu Zhou
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Qiong Wang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Aimulaguli Kadier
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Wenjuan Wang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Fenfen Zhou
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Rui Li
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Li Ling
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China; Clinical Research Design Division, Clinical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
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13
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Klompmaker JO, Laden F, Browning MHEM, Dominici F, Jimenez MP, Ogletree SS, Rigolon A, Zanobetti A, Hart JE, James P. Associations of Greenness, Parks, and Blue Space With Neurodegenerative Disease Hospitalizations Among Older US Adults. JAMA Netw Open 2022; 5:e2247664. [PMID: 36538329 PMCID: PMC9856892 DOI: 10.1001/jamanetworkopen.2022.47664] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 10/31/2022] [Indexed: 12/24/2022] Open
Abstract
Importance Exposure to natural environments has been associated with health outcomes related to neurological diseases. However, the few studies that have examined associations of natural environments with neurological diseases report mixed findings. Objective To evaluate associations of natural environments with hospital admissions for Alzheimer disease and related dementias (ADRD) and Parkinson disease (PD) among older adults in the US. Design, Setting, and Participants This open cohort study included fee-for-service Medicare beneficiaries aged 65 years or older who lived in the contiguous US from January 1, 2000, to December 31, 2016. Beneficiaries entered the cohort on January 1, 2000, or January 1 of the year after enrollment. Data from US Medicare enrollment and Medicare Provider Analysis and Review files, which contain information about individual-level covariates and all hospital admissions for Medicare fee-for-service beneficiaries, were analyzed between January 2021 and September 2022. Exposures Differences in IQRs for zip code-level greenness (normalized difference vegetation index [NDVI]), percentage park cover, and percentage blue space cover (surface water; ≥1.0% vs <1.0%). Main Outcomes and Measures The main outcome was first hospitalizations with a primary or secondary discharge diagnosis of ADRD or PD. To examine associations of exposures to natural environments with ADRD and PD hospitalization, we used Cox-equivalent Poisson models. Results We included 61 662 472 and 61 673 367 Medicare beneficiaries in the ADRD and PD cohorts, respectively. For both cohorts, 55.2% of beneficiaries were women. Most beneficiaries in both cohorts were White (84.4%), were not eligible for Medicaid (87.6%), and were aged 65 to 74 years (76.6%) at study entry. We observed 7 737 609 and 1 168 940 first ADRD and PD hospitalizations, respectively. After adjustment for potential individual- and area-level confounders (eg, Medicaid eligibility and zip code-level median household income), NDVI was negatively associated with ADRD hospitalization (hazard ratio [HR], 0.95 [95% CI, 0.94-0.96], per IQR increase). We found no evidence of an association of percentage park and blue space cover with ADRD hospitalization. In contrast, NDVI (HR, 0.94 [95% CI, 0.93-0.95], per IQR increase), percentage park cover (HR, 0.97 [95% CI, 0.97-0.98], per IQR increase), and blue space cover (HR, 0.97 [95% CI, 0.96-0.98], ≥1.0% vs <1.0%) were associated with a decrease in PD hospitalizations. Patterns of effect modification by demographics differed between exposures. Conclusions and Relevance The findings of this cohort study suggest that some natural environments are associated with a decreased risk of ADRD and PD hospitalization.
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Affiliation(s)
- Jochem O. Klompmaker
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - Francine Laden
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | | | - Francesca Dominici
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Marcia P. Jimenez
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | - S. Scott Ogletree
- OPENspace Research Centre, School of Architecture and Landscape Architecture, University of Edinburgh, Edinburgh, United Kingdom
| | - Alessandro Rigolon
- Department of City and Metropolitan Planning, University of Utah, Salt Lake City
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Jaime E. Hart
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - Peter James
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
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Yang C, Wang J, Yang H, Liao J, Wang X, Jiao K, Ma X, Liao J, Liu X, Ma L. Association of NO 2 with daily hospital admissions for mental disorders: Investigation of the modification effects of green spaces and long-term NO 2 exposure. J Psychiatr Res 2022; 156:698-704. [PMID: 36410308 DOI: 10.1016/j.jpsychires.2022.11.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/03/2022] [Accepted: 11/12/2022] [Indexed: 11/16/2022]
Abstract
Air pollution is a risk factor for increased hospital admissions due to mental disorders, while green spaces have been linked with better mental health. We linked daily hospital admission records from Wuhan's 74 municipal hospitals from 2017 to 2019 with modeled annual average NO2 concentrations and added data on the residential surrounding green spaces with 250 m and 500 m buffers based on the normalized difference vegetation index (NDVI) using a land use regression model (LUR). The conditional logistic regression model was used to estimate the acute effect of short-term NO2 exposure, and stratification analyses were applied to explore the modification effect of long-term NO2 exposure and green spaces by estimating the odds ratios in the single- and dual-environmental factor groups. A total of 42,705 hospital admissions for mental disorders were identified. Short-term exposure to NO2 was associated with an increased risk of hospital admission for mental disorders. A 10 μg/m3 increase in NO2 (lag01 day) was associated with an increase in hospital admissions of 2.86% (95% CI, 2.05-3.68) for the total mental disorders. Compared with patients in the "low-NDVI/low-NO2" group (ER = 2.27%, 95% CI, 0.27-4.31), patients in the "high-NDVI/low-NO2" group (ER = 1.93%, -0.10-3.99) showed a lower and insignificant increase in hospitalizations for the total mental disorders, while greenness had a slight moderating effect in the high-level long-term NO2 exposure areas. This study suggested that green spaces may moderate the acute effect of NO2 exposure for mental disorder hospitalizations, especially in low-level long-term NO2 exposure areas.
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Affiliation(s)
- Can Yang
- School of Public Health, Wuhan University, Wuhan, China
| | - Jing Wang
- School of Public Health, Wuhan University, Wuhan, China
| | - Haoming Yang
- School of Public Health, Wuhan University, Wuhan, China
| | - Jianpeng Liao
- School of Public Health, Wuhan University, Wuhan, China
| | - Xiaodie Wang
- School of Public Health, Wuhan University, Wuhan, China
| | | | - Xuxi Ma
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, China
| | - Jingling Liao
- Department of Nutrition and Food Hygiene, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan, China
| | - Xingyuan Liu
- Wuhan Information Control Health & Family Planning, Wuhan, China
| | - Lu Ma
- School of Public Health, Wuhan University, Wuhan, China.
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15
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Associations of greenness surrounding schools and self-reported depressive and anxiety symptoms in Chinese adolescents. J Affect Disord 2022; 318:62-69. [PMID: 36058356 DOI: 10.1016/j.jad.2022.08.095] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 08/24/2022] [Accepted: 08/26/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND The effect of school-based greenness exposure on mental health among adolescents remains unclear. The study aimed to estimate the associations between school-based greenness and depressive and anxiety symptoms among adolescents and explore potential modifier and mediator between the associations. METHODS A cross-sectional survey involving 15,559 adolescents was conducted in China. The Chinese version of the Center for Epidemiologic Studies Depression 9-Item Scale and the Generalized Anxiety Disorder 7-Item Scale were used to assess the depressive and anxiety symptoms among adolescents. The Normalized Difference Vegetation Index within a 400 m and 800 m zone surrounding schools was used to indicate the adolescents' exposure to greenness. We estimated daily concentrations of PM1.0, PM2.5, and NO2 from the China High Air Pollutants dataset. Multiple logistic regression models were used. RESULTS Higher exposure to greenness surrounding schools was negatively associated with depressive (OR: 0.774, 95%CI: 0.685-0.875) and anxiety symptoms (0.740, 0.669-0.818). We observed stronger associations between greenness and depressive and anxiety symptoms among girls, lower age group (11-15 years), and adolescents born to parents with lower education levels. PM1.0 (proportion mediated estimates: 14.3 %; 95 % CI: 4.2 %, 24.5 %) and PM2.5 (10.5 %; 95 % CI: 3.0 %, 17.9 %) mediated the associations between greenness exposure and depressive symptoms. The number of days adolescents attended physical education classes per week mediated -22.8 % (95 % CI: -38.5 %, -7.1 %) and -9.7 % (95 % CI: -15.5 %, -3.8 %) of the effects of greenness on depressive and anxiety symptoms. CONCLUSIONS Increasing the greenness and improving the environment surrounding schools is effective in promoting the mental health of adolescents.
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