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Smith PJ, Whitson HE, Merwin RM, O’Hayer CV, Strauman TJ. Engineering Virtuous health habits using Emotion and Neurocognition: Flexibility for Lifestyle Optimization and Weight management (EVEN FLOW). Front Aging Neurosci 2023; 15:1256430. [PMID: 38076541 PMCID: PMC10702760 DOI: 10.3389/fnagi.2023.1256430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/20/2023] [Indexed: 02/12/2024] Open
Abstract
Interventions to preserve functional independence in older adults are critically needed to optimize 'successful aging' among the large and increasing population of older adults in the United States. For most aging adults, the management of chronic diseases is the most common and impactful risk factor for loss of functional independence. Chronic disease management inherently involves the learning and adaptation of new behaviors, such as adopting or modifying physical activity habits and managing weight. Despite the importance of chronic disease management in older adults, vanishingly few individuals optimally manage their health behavior in the service of chronic disease stabilization to preserve functional independence. Contemporary conceptual models of chronic disease management and health habit theory suggest that this lack of optimal management may result from an underappreciated distinction within the health behavior literature: the behavioral domains critical for initiation of new behaviors (Initiation Phase) are largely distinct from those that facilitate their maintenance (Maintenance Phase). Psychological factors, particularly experiential acceptance and trait levels of openness are critical to engagement with new health behaviors, willingness to make difficult lifestyle changes, and the ability to tolerate aversive affective responses in the process. Cognitive factors, particularly executive function, are critical to learning new skills, using them effectively across different areas of life and contextual demands, and updating of skills to facilitate behavioral maintenance. Emerging data therefore suggests that individuals with greater executive function are better able to sustain behavior changes, which in turn protects against cognitive decline. In addition, social and structural supports of behavior change serve a critical buffering role across phases of behavior change. The present review attempts to address these gaps by proposing a novel biobehavioral intervention framework that incorporates both individual-level and social support system-level variables for the purpose of treatment tailoring. Our intervention framework triangulates on the central importance of self-regulatory functioning, proposing that both cognitive and psychological mechanisms ultimately influence an individuals' ability to engage in different aspects of self-management (individual level) in the service of maintaining independence. Importantly, the proposed linkages of cognitive and affective functioning align with emerging individual difference frameworks, suggesting that lower levels of cognitive and/or psychological flexibility represent an intermediate phenotype of risk. Individuals exhibiting self-regulatory lapses either due to the inability to regulate their emotional responses or due to the presence of executive functioning impairments are therefore the most likely to require assistance to preserve functional independence. In addition, these vulnerabilities will be more easily observable for individuals requiring greater complexity of self-management behavioral demands (e.g. complexity of medication regimen) and/or with lesser social support. Our proposed framework also intuits several distinct intervention pathways based on the profile of self-regulatory behaviors: we propose that individuals with intact affect regulation and impaired executive function will preferentially respond to 'top-down' training approaches (e.g., strategy and process work). Individuals with intact executive function and impaired affect regulation will respond to 'bottom-up' approaches (e.g., graded exposure). And individuals with impairments in both may require treatments targeting caregiving or structural supports, particularly in the context of elevated behavioral demands.
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Affiliation(s)
- Patrick J. Smith
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Heather E. Whitson
- Department of Medicine, Duke University Medical Center, Durham, NC, United States
- Department of Medicine, Durham Veterans Affairs Medical Center, Durham, NC, United States
| | - Rhonda M. Merwin
- Department of Psychiatry, Duke University Medical Center, Durham, NC, United States
| | - C. Virginia O’Hayer
- Department of Psychiatry and Human Behavior, Thomas Jefferson University, Philadelphia, PA, United States
| | - Timothy J. Strauman
- Department of Psychiatry, Duke University Medical Center, Durham, NC, United States
- Department of Psychology and Neuroscience, Duke University, Durham, NC, United States
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Lee YJ, Loh WQ, Dang TK, Teng CWC, Pan WC, Wu CD, Chia SE, Seow WJ. Determinants of residential greenness and its association with prostate cancer risk: A case-control study in Singapore. ENVIRONMENTAL RESEARCH 2023; 237:116903. [PMID: 37598842 DOI: 10.1016/j.envres.2023.116903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 07/31/2023] [Accepted: 08/15/2023] [Indexed: 08/22/2023]
Abstract
BACKGROUND Exposure to greenness has been shown to be beneficial to health, but few studies have examined the association between residential greenness and prostate cancer (PCa) risk. Our main objectives were to identify the determinants of residential greenness, and to investigate if residential greenness was associated with PCa risk in Singapore. METHODS The hospital-based case-control study was conducted between April 2007 and May 2009. The Singapore Prostate Cancer Study (SPCS) comprised 240 prostate cancer cases and 268 controls, whose demographics and residential address were collected using questionnaires. Residential greenness was measured by normalized difference vegetation index (NDVI) around the participants' homes using a buffer size of 1 km. Determinants of NDVI were identified using a multivariable linear regression model. Logistic regression models were used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) of associations between NDVI and PCa risk, adjusting for potential confounders. RESULTS Having a BMI within the second quartile, as compared to the lowest quartile, was associated with higher levels of NDVI (β-coefficient = 0.263; 95% CI = 0.040-0.485) after adjusting for covariates. Additionally, being widowed or separated, as compared to being married, was associated with lower levels of NDVI (β-coefficient = -0.393; 95% CI = -0.723, -0.063). An interquartile range (IQR) increase in NDVI was positively associated with prostate cancer risk OR = 1.45; 95% CI = 1.02-2.07). Stratified analysis by tumour grade and stage showed that higher NDVI was associated with higher risk of low grade PCa. CONCLUSION Our findings suggested that residential greenness was associated with higher risk of PCa in Singapore. Future studies on the quality and type of green spaces, as well as other factors of residential greenness, in association with PCa risk should be conducted to better understand this relationship.
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Affiliation(s)
- Yueh Jia Lee
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Singapore, 117549
| | - Wei Qi Loh
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Singapore, 117549
| | - Trung Kien Dang
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Singapore, 117549
| | - Cecilia Woon Chien Teng
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Singapore, 117549
| | - Wen-Chi Pan
- Institute of Environmental and Occupational Health Sciences, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chih-Da Wu
- Department of Geomatics, National Cheng Kung University, Tainan, Taiwan; National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli, Taiwan; Innovation and Development Center of Sustainable Agriculture, National Chung-Hsing University, Tainan, Taiwan
| | - Sin Eng Chia
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Singapore, 117549; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, 10 Medical Dr, Singapore, 117597
| | - Wei Jie Seow
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Singapore, 117549; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, 10 Medical Dr, Singapore, 117597.
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Ye L, Zhou J, Tian Y, Cui J, Chen C, Wang J, Wang Y, Wei Y, Ye J, Li C, Chai X, Sun C, Li F, Wang J, Guo Y, Jaakkola JJK, Lv Y, Zhang J, Shi X. Associations of residential greenness and ambient air pollution with overweight and obesity in older adults. Obesity (Silver Spring) 2023; 31:2627-2637. [PMID: 37649157 DOI: 10.1002/oby.23856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 05/28/2023] [Accepted: 05/31/2023] [Indexed: 09/01/2023]
Abstract
OBJECTIVE This study aimed to examine the impact of greenness and fine particulate matter <2.5 μm (PM2.5 ) on overweight/obesity among older adults in China. METHODS A total of 21,355 participants aged ≥65 years were included from the Chinese Longitudinal Healthy Longevity Survey between 2000 and 2018. Normalized difference vegetation index (NDVI) with a radius of 250 m and PM2.5 in a 1 × 1-km grid resolution were calculated around each participant's residence. Cox proportional hazards models were used to estimate the effects of NDVI and PM2.5 on overweight/obesity. Interaction and mediation analyses were conducted to explore combined effects. RESULTS The study observed 1895 incident cases of overweight/obesity over 109,566 person-years. For every 0.1-unit increase in NDVI the hazard ratio of overweight/obesity was 0.91 (95% CI: 0.88-0.95), and for every 10-μg/m3 increase in PM2.5 the hazard ratio was 1.11 (95% CI: 1.07-1.14). The effect of NDVI on overweight/obesity was partially mediated by PM2.5 , with a relative mediation proportion of 20.10% (95% CI: 1.63%-38.57%). CONCLUSIONS Greenness exposure appears to lower the risk of overweight/obesity in older adults in China, whereas PM2.5 , acting as a mediator, partly mediated this protective effect.
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Affiliation(s)
- Lihong Ye
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jinhui Zhou
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yanlin Tian
- Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Jia Cui
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chen Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jun Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yueqing Wang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuan Wei
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Jiaming Ye
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Chenfeng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Anhui Medical University, Hefei, China
| | - Xin Chai
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chris Sun
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Fangyu Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Anhui Medical University, Hefei, China
| | - Jiaonan Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yanbo Guo
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Jouni J K Jaakkola
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
- Finnish Meteorological Institute, Helsinki, Finland
| | - Yuebin Lv
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Juan Zhang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
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Song Y, Li H, Yu H. Effects of green space on physical activity and body weight status among Chinese adults: a systematic review. Front Public Health 2023; 11:1198439. [PMID: 37546310 PMCID: PMC10399589 DOI: 10.3389/fpubh.2023.1198439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 06/29/2023] [Indexed: 08/08/2023] Open
Abstract
Background Green space may provide many benefits to residents' health behaviors and body weight status, but the evidence is still relatively scattered among Chinese adults. The purpose of this study was to review the scientific evidence on the effects of green space on physical activity (PA) and body weight status among Chinese adults. Methods A keyword and reference search was conducted in Pubmed, Web of Science, MEDLINE, and PsycINFO. Studies examining the associations between green space and PA, body mass index (BMI) among Chinese adults were included. The quality of the included literature was evaluated using the National Institutes of Health's Observational Cohort and Cross-Sectional Study Quality Assessment Tool. Results A total of 31 studies were included that met the inclusion criteria, including 25 studies with a cross-sectional design, 3 studies with a longitudinal design, and 3 studies with an experimental design. Street-level green view index and green space accessibility were found to be positively associated with PA, but negatively associated with BMI. In most studies, there was a correlation between green space ratio in local areas and BMI. In addition, green space interventions were effective in increasing PA and decreasing BMI among Chinese adults. In contrast, further evidence is needed to support the association between the design characteristics of green space and PA and BMI. Conclusion Preliminary evidence suggests that green space has a positive effect on PA and BMI among Chinese adults. However, there are contradictory findings, and future studies adopting longitudinal and quasi-experimental studies are needed to further explore the causal relationship between green space and PA and BMI to provide a relevant theoretical basis for policymakers.
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Affiliation(s)
| | | | - Hongjun Yu
- Department of Physical Education, Tsinghua University, Beijing, China
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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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Zhao H, Wu M, Du Y, Zhang F, Li J. Relationship between Built-Up Environment, Air Pollution, Activity Frequency and Prevalence of Hypertension-An Empirical Analysis from the Main City of Lanzhou. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:743. [PMID: 36613066 PMCID: PMC9819356 DOI: 10.3390/ijerph20010743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/23/2022] [Accepted: 12/27/2022] [Indexed: 06/17/2023]
Abstract
In the process of promoting the strategy of a healthy China, the built environment, as a carrier of human activities, can effectively influence the health level of residents in the light of its functional types. Based on the POI data of four main urban areas in Lanzhou, this paper classifies the built environment in terms of function into four types. The association between different types of built environments and the prevalence of hypertension was investigated by using the community as the study scale, and activity frequency, air pollution and green space were used as mediating variables to investigate whether they could mediate the relationship between built environments and hypertension. The results indicate that communities with a high concentration of commercial service facilities, road and traffic facilities and industrial facilities have a relatively high prevalence of hypertension. By determining the direct, indirect and overall effects of different functional types of built environment on the prevalence of hypertension, it was learned that the construction of public management and service facilities can effectively mitigate the negative effects of hypertension in the surrounding residents. The results of the study contribute to the rational planning of the structure of the built environment, which is beneficial for optimizing the urban structure and preventing and controlling chronic diseases such as hypertension.
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Affiliation(s)
- Haili Zhao
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
- Key Laboratory of Resource Environment and Sustainable Development of Oasis, Lanzhou 730070, China
| | - Minghui Wu
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
- Key Laboratory of Resource Environment and Sustainable Development of Oasis, Lanzhou 730070, China
| | - Yuhan Du
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
- Key Laboratory of Resource Environment and Sustainable Development of Oasis, Lanzhou 730070, China
| | - Fang Zhang
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
- Key Laboratory of Resource Environment and Sustainable Development of Oasis, Lanzhou 730070, China
| | - Jialiang Li
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
- Key Laboratory of Resource Environment and Sustainable Development of Oasis, Lanzhou 730070, China
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Liang X, Liu F, Liang F, Ren Y, Tang X, Luo S, Huang D, Feng W. Association of decreases in PM2.5 levels due to the implementation of environmental protection policies with the incidence of obesity in adolescents: A prospective cohort study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 247:114211. [PMID: 36306623 DOI: 10.1016/j.ecoenv.2022.114211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 10/16/2022] [Accepted: 10/18/2022] [Indexed: 06/16/2023]
Abstract
AIMS To explore the association between decreased levels of particulate matter (≤2.5 µm; PM2.5) due to the implementation of environmental protection policies and the incidence of obesity in adolescents in Chongqing, China through a prospective cohort study. METHODS A total of 2105 children (52.02% male; aged 7.33 ± 0.60 years at baseline) were enrolled from the Chongqing Children's Health Cohort. A mixed linear regression model was used to analyse the relationships of PM2.5 levels with obesity indicators after adjusting for covariates. Additionally, a Poisson regression model was used to determine the relationship between PM2.5 exposure and the incidence of overweight/obesity. RESULTS The average PM2.5 exposure levels from participant conception to 2014, from 2015 to 2017, and from 2018 to 2019 were 66.64 ± 5.33 μg/m3, 55.49 ± 3.78 μg/m3, and 42.50 ± 1.87 μg/m3, respectively; these levels significantly decreased over time (P < 0.001). Throughout the entire follow-up period, the incidence of overweight/obesity after a ≥ 25 μg/m3 decrease in the PM2.5 level was 4.57% among females; this incidence was the lowest among females who experienced remarkable decreases in PM2.5 exposure. A 1-µg/m3 decrease in the PM2.5 level significantly decreased the body mass index (BMI), BMI z score (BMIz), and weight of adolescents (all P < 0.001). Compared with a < 20-μg/m3 decrease in the PM2.5 level, a ≥ 25-μg/m3 decrease protected against increased BMI (net difference= -0.93; 95% confidence interval [CI]: (-1.23,-0.63) kg/m2), BMIz (-0.28 (-0.39, -0.17)), weight (-1.59 (-2.44, -0.74) kg), and incidence of overweight/obesity (0.48 (0.37, 0.62), P < 0.001). Moreover, compared with a < 20-μg/m3 decrease in the PM2.5 level, a ≥ 25-μg/m3 decrease resulted in significant absolute differences in BMI (-1.26 (-1.56, -0.96) kg/m2), BMIz (-0.53 (-0.65, -0.40)) and weight (-3.01 (-3.8, -2.19) kg) (all P < 0.001). CONCLUSIONS This study showed the etiological relevance of declining PM2.5 concentrations for the incidence of obesity in children and adolescents, suggesting that controlling ambient air pollutants may prevent the development of obesity in this age group. Continuous implementation of environmental protection policies in China has led to substantial health benefits.
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Affiliation(s)
- Xiaohua Liang
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing 400016, China.
| | - Fangchao Liu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Fengchao Liang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yanling Ren
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing 400016, China
| | - Xian Tang
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing 400016, China
| | - Shunqing Luo
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing 400016, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China; School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen 518055, China
| | - Daochao Huang
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing 400016, China
| | - Wei Feng
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing 400016, China
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Jiang J, Xiang Z, Liu F, Li N, Mao S, Xie B, Xiang H. Associations of residential greenness with obesity and BMI level among Chinese rural population: findings from the Henan Rural Cohort Study. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:74294-74305. [PMID: 35635662 DOI: 10.1007/s11356-022-20268-0] [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: 12/19/2021] [Accepted: 04/11/2022] [Indexed: 06/15/2023]
Abstract
In recent years, increasing evidence supports the notion that obesity risk is affected by residential greenness. However, limited studies have been established in low- and middle-income countries, especially in China. The study aimed to evaluate the associations of residential greenness with obesity and body mass index (BMI) level in Chinese rural-dwelling adults. A total of 39,259 adults from the Henan Rural Cohort Study (HRCS) were included in the analyses. According to the guideline for prevention and control of overweight and obesity in Chinese adults, obesity was defined as BMI ≥ 28 kg/m2. Residential greenness was measured by satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Generalized linear mixed models were used to study the associations between exposure to residential greenness with obesity and BMI level. Higher residential greenness was significantly correlated with lower odds of obesity and BMI level. For example, in the full-adjusted analyses, an interquartile range (IQR) increase in EVI500-m was linked with reduced odds of obesity (OR = 0.77, 95%CI 0.72-0.82) and BMI level (β = - 0.41 kg/m2, 95%CI - 0.48 to - 0.33 kg/m2). Mediation analyses showed air pollution and physical activity could be potential mediators in these associations. Besides, we found that the association of NDVI500-m with BMI was stronger in females and low-income populations. Higher residential greenness was associated with a lower prevalence of obesity and BMI level, particularly among females and the low-income population. These relationships were partially mediated by reducing air pollution and increasing physical activity.
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Affiliation(s)
- Jie Jiang
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, 430071, Hubei, China
- Global Health Institute, Wuhan University, Wuhan, 430071, Hubei, China
| | - Zixi Xiang
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, 430071, Hubei, China
- Global Health Institute, Wuhan University, Wuhan, 430071, Hubei, China
| | - Feifei Liu
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, 430071, Hubei, China
- Global Health Institute, Wuhan University, Wuhan, 430071, Hubei, China
| | - Na Li
- Department of Global Health, School of Public Health, Peking University, Beijing, 100871, China
| | - Shuyuan Mao
- The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Bo Xie
- School of Urban Design, Wuhan University, Wuhan, 430072, Hubei, China
| | - Hao Xiang
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, 430071, Hubei, China.
- Global Health Institute, Wuhan University, Wuhan, 430071, Hubei, China.
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Jiang Y, Kang Zhuo BM, Guo B, Zeng PB, Guo YM, Chen GB, Wei J, He RF, Li ZF, Zhang XH, Wang ZY, Li X, Wang L, Zeng CM, Chen L, Xiao X, Zhao X. Living near greenness is associated with higher bone strength: A large cross-sectional epidemiological study in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 831:155393. [PMID: 35461937 DOI: 10.1016/j.scitotenv.2022.155393] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 04/15/2022] [Accepted: 04/15/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Living near green spaces may benefit various health outcomes. However, no studies have investigated the greenness-bone linkage in the general population. Moreover, to which extent ambient air pollution (AAP), physical activity (PA), and body mass index (BMI) mediate this relationship remains unclear. We aimed to explore the association between greenness and bone strength and the potential mediating roles of AAP, PA, and BMI in Chinese adults. METHODS This cross-sectional analysis enrolled 66,053 adults from the China Multi-Ethnic Cohort in 2018-2019. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were employed to define residential greenness. The calcaneus quantitative ultrasound index (QUI) was used to indicate bone strength. Multiple linear regression models and mediation analyses were used to estimate the residential greenness-bone strength association and potential pathways operating through AAP (represented by PM2.5 [particulate matter <2.5 μm in diameter]), PA, and BMI. Stratification analyses were performed to identify susceptible populations. RESULTS Higher residential exposure to greenness was significantly associated with an increase in QUI, with changes (95% confidence interval) of 3.28 (3.05, 3.50), 3.57 (3.34, 3.80), 2.68 (2.46, 2.90), and 2.93 (2.71, 3.15) for every interquartile range increase in NDVI500m, NDVI1000m, EVI500m, and EVI1000m, respectively. Sex, urbanicity, annual family income, smoking, and drinking significantly modified the association of greenness-bone strength, with more remarkable associations in males, urban residents, subjects from wealthier families, smokers, and drinkers. For the NDVI500m/EVI500m-QUI relationship, the positive mediating roles of PM2.5 and PA were 6.70%/8.50 and 2.43%/2.69%, respectively, whereas those negative for BMI and PA-BMI were 0.88%/1.06% and 0.05%/0.05%, respectively. CONCLUSION Living in a greener area may predict higher bone strength, particularly among males, urban residents, wealthier people, smokers, and drinkers. AAP, PA, BMI, and other factors may partially mediate the positive association. Our findings underscore the importance of optimizing greenness planning and management policies.
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Affiliation(s)
- Ye Jiang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Bai Ma Kang Zhuo
- Division of Pulmonary Diseases, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China; School of Medicine, Tibet University, Lhasa, Tibet, China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Pei-Bin Zeng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yu-Ming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Gong-Bo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | - Rui-Feng He
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet, China
| | - Zhi-Feng Li
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Xue-Hui Zhang
- School of public Health, Kunming Medical University, Kunming, Yunnan, China
| | - Zi-Yun Wang
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou, China
| | - Xuan Li
- Jianyang Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Lei Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chun-Mei Zeng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lin Chen
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiong Xiao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
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Shen J, Li M, Wang Q, Liu R, Ji M, An R. The Influence of Green Space on Obesity in China: A Systematic Review. Obes Facts 2022; 15:463-472. [PMID: 35545010 PMCID: PMC9421664 DOI: 10.1159/000524857] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 04/21/2022] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION This study systematically reviewed scientific evidence concerning the influence of green space on obesity in China. METHODS Keyword and reference search was conducted in PubMed, Web of Science, Scopus, EBSCO, and CNKI. Predetermined selection criteria included study designs: experimental and observational studies; subjects: people of all ages; exposures: green space (i.e., any open land partly or entirely covered with grass, trees, shrubs, or other vegetation); outcomes: body weight status (e.g., body mass index [BMI], overweight, or obesity); and country: China. RESULTS Ten studies met the selection criteria and were included in the review. All studies adopted a cross-sectional design. Overall greenness measures were found to be inversely associated with BMI, overweight, and obesity in most included studies. Street greenness, which measures the perceived greenness at the eye level on streets, was found to be inversely associated with BMI and obesity. By contrast, mixed results were observed for the relationship between green space accessibility and weight outcomes. Air quality was found to mediate the relationship between greenness and obesity. The influence of green space on obesity tended to vary by residents' gender, age, and socioeconomic status. Boys, women, older residents, and those with lower education or household income were more likely to benefit from greenness exposure. CONCLUSION The literature on green space exposure in relation to obesity in China remains limited. Longitudinal and quasi-experimental studies are warranted to assess the causal link between green space and obesity. Future measures should better capture the self-perception, quality, and attractiveness of green space. The underlying pathways through which green space affects residents' weight outcomes should be further elucidated.
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Affiliation(s)
- Jing Shen
- Department of Physical Education, China University of Geosciences (Beijing), Beijing, China,
| | - Mengfei Li
- Department of Physical Education, China University of Geosciences (Beijing), Beijing, China
| | - Qianhui Wang
- Department of Physical Education, China University of Geosciences (Beijing), Beijing, China
| | - Ruidong Liu
- Sports Coaching College, Beijing Sport University, Beijing, China
| | - Mengmeng Ji
- Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Ruopeng An
- Brown School, Washington University, St. Louis, Missouri, USA
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11
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Thorpe LE, Adhikari S, Lopez P, Kanchi R, McClure LA, Hirsch AG, Howell CR, Zhu A, Alemi F, Rummo P, Ogburn EL, Algur Y, Nordberg CM, Poulsen MN, Long L, Carson AP, DeSilva SA, Meeker M, Schwartz BS, Lee DC, Siegel KR, Imperatore G, Elbel B. Neighborhood Socioeconomic Environment and Risk of Type 2 Diabetes: Associations and Mediation Through Food Environment Pathways in Three Independent Study Samples. Diabetes Care 2022; 45:798-810. [PMID: 35104336 PMCID: PMC9016733 DOI: 10.2337/dc21-1693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 01/05/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: 1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); 2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and 3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of 1) fast-food restaurants and 2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural. RESULTS Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways. CONCLUSIONS Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways.
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Affiliation(s)
- Lorna E. Thorpe
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Samrachana Adhikari
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Priscilla Lopez
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Rania Kanchi
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Leslie A. McClure
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | | | - Carrie R. Howell
- Division of Preventive Medicine, University of Alabama at Birmingham School of Medicine, Birmingham, AL
| | - Aowen Zhu
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL
| | - Farrokh Alemi
- Department of Health Administration and Policy, George Mason University, Fairfax, VA
| | - Pasquale Rummo
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Elizabeth L. Ogburn
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD
| | - Yasemin Algur
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | - Cara M. Nordberg
- Department of Population Health Sciences, Geisinger, Danville, PA
| | | | - Leann Long
- Department of Biostatistics, University of Alabama at Birmingham School of Public Health, Birmingham, AL
| | - April P. Carson
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL
| | - Shanika A. DeSilva
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | - Melissa Meeker
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | - Brian S. Schwartz
- Department of Population Health Sciences, Geisinger, Danville, PA
- Department of Environmental Health and Engineering, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD
| | - David C. Lee
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
- Department of Emergency Medicine, New York University Grossman School of Medicine, New York, NY
| | - Karen R. Siegel
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Giuseppina Imperatore
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Brian Elbel
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
- New York University Wagner Graduate School of Public Service, New York, NY
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12
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Zhang L, Chen C, Liu C, Zhang Y, Fang J, Han J, Zhao F, Du P, Wang Q, Wang J, Shi W, Wang W, Shi S, Chen R, Kan H, Meng X, Li T, Shi X. Associations of residential greenness with peripheral and central obesity in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 791:148084. [PMID: 34139501 DOI: 10.1016/j.scitotenv.2021.148084] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 05/21/2021] [Accepted: 05/24/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Obesity is a well-known risk factor for public health. Recent studies found that greenness exposure may protect against obesity. However, the accumulated evidence on associations of greenness-obesity is inconsistent and most of them are from developed countries. OBJECTIVES This study aimed to evaluate the associations of greenness exposure with indicators of peripheral and central obesity. METHODS This cross-sectional study was based on a Chinese national Sub-Clinical Outcomes of Polluted Air (SCOPA) prospective cohort across 15 provinces, and 5849 participants with average age of 64.7 were included. Surrounding greenness was estimated with the Enhanced Vegetation Index (EVI), which was calculated at each participant's residential addresses within a 250 m buffer. Weight, height and waist circumference (WC) were measured, and body mass index (BMI) and the waist-to-height ratio% (WHtR%) were calculated based on those measurements. The relationships between EVI and obese outcomes were explored using multiple linear regression and logistic regression models. RESULTS Non-linear associations were observed between EVI and obese indicators. Participants living in Quartile 3 benefited more than in Quartile 4 compared to the lowest quartile (Quartile 1) of greenness. For peripheral obesity, participants living in Quartile 3 of EVI250m had 0.86 kg/m2 (β -0.86, 95% CI: -1.10, -0.61) lower BMI, and 46% (OR 0.54, 95% CI: 0.44-0.66) lower odds of peripheral obesity than in Quartile 1. For central obesity, participants living in Quartile 3 of EVI250m had 1.85 cm (β -1.85, 95% CI: -2.54, -1.15) lower waist circumference, 1.12% (β -1.12, 95% CI: -1.56, -0.67) lower waist-to-height ratio% (WHtR%), and 33% (OR 0.67, 95% CI: 0.57-0.78) lower odds of central obesity than in Quartile 1 of EVI250m. CONCLUSIONS Higher levels of greenness were statistically significant associated with lower obesity risk.
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Affiliation(s)
- Lina Zhang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200032, China
| | - Chen Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Cong Liu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200032, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jingxiu Han
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Feng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Peng Du
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Qiong Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jiaonan Wang
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Wanying Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Weidong Wang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200032, China
| | - Su Shi
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200032, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200032, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200032, China
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200032, China.
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
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Green Space and Health in Mainland China: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18189937. [PMID: 34574854 PMCID: PMC8472560 DOI: 10.3390/ijerph18189937] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 09/03/2021] [Accepted: 09/13/2021] [Indexed: 12/12/2022]
Abstract
Non-communicable diseases (NCDs) have become a major cause of premature mortality and disabilities in China due to factors concomitant with rapid economic growth and urbanisation over three decades. Promoting green space might be a valuable strategy to help improve population health in China, as well as a range of co-benefits (e.g., increasing resilience to climate change). No systematic review has so far determined the degree of association between green space and health outcomes in China. This review was conducted to address this gap. Five electronic databases were searched using search terms on green space, health, and China. The review of 83 publications that met eligibility criteria reports associations indicative of various health benefits from more green space, including mental health, general health, healthier weight status and anthropometry, and more favorable cardiometabolic and cerebrovascular outcomes. There was insufficient evidence to draw firm conclusions on mortality, birth outcomes, and cognitive function, and findings on respiratory and infectious outcomes were inconsistent and limited. Future work needs to examine the health benefits of particular types and qualities of green spaces, as well as to take advantage of (quasi-)experimental designs to test greening interventions within the context of China's rapid urbanization and economic growth.
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14
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Yu J, Ma G, Wang S. Do Age-Friendly Rural Communities Affect Quality of Life? A Comparison of Perceptions from Middle-Aged and Older Adults in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18147283. [PMID: 34299736 PMCID: PMC8306948 DOI: 10.3390/ijerph18147283] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 06/24/2021] [Accepted: 06/30/2021] [Indexed: 01/09/2023]
Abstract
The aging population in rural areas of China faces serious challenges due to urban–rural disparities. In order to improve the active aging of rural older adults, the establishment of age-friendly communities is encouraged. However, globally, the focus is on age-friendly communities in urban areas, not reflecting rural communities. Hence, we addressed the importance of age-friendly rural communities (AFRCs) and aimed to investigate their impact on the quality of life (QoL) of older adults. We examined different perceptions of AFRCs among older adults (aged over 60) and middle-aged people (45–60) in rural communities with questionnaire surveys (n = 470 and 393, respectively). Several statistical methods, such as Chi-squared test, t-test, reliability test, and multiple regression, were adopted to investigate and compare the perceptions of these two. The results indicated that (1) middle-aged people were more satisfied with AFRC components and had a higher QoL than older adults; (2) the QoL of middle-aged people was predicted by housing, accessibility, and outdoor spaces; (3) the QoL of older adults was affected by housing, outdoor spaces, social participation, and public transportation. These findings aid in our understanding of rural communities and the QoL of rural residents. They are helpful for urban planners and policymakers to improve the planning of AFRCs and supplement research on age-friendly communities in rural areas. Practical implementations are proposed for the planning of AFRCs, such as the passive design of residential housing, grouping of community facilities together, and improvement in the hygiene of outdoor spaces in rural areas.
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Affiliation(s)
- Jingyu Yu
- School of Civil Engineering, Hefei University of Technology, Hefei 230009, China;
| | - Guixia Ma
- School of Civil Engineering, Hefei University of Technology, Hefei 230009, China;
- Correspondence:
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15
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Huang B, Xiao T, Grekousis G, Zhao H, He J, Dong G, Liu Y. Greenness-air pollution-physical activity-hypertension association among middle-aged and older adults: Evidence from urban and rural China. ENVIRONMENTAL RESEARCH 2021; 195:110836. [PMID: 33549617 DOI: 10.1016/j.envres.2021.110836] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 01/09/2021] [Accepted: 01/31/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Although some evidence suggests that residential greenness may prevent hypertension in urban areas, limited attention has been paid to urban-rural disparities in the association of greenness with hypertension in rapidly urbanizing developing countries. OBJECTIVES The current study investigated the association between the amount of neighbourhood greenness and hypertension among middle and older aged people in Chinese urban and rural areas. It further examined whether PM2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) concentrations, physical activity, and body mass index (BMI) mediated the association of greenness with hypertension. METHODS We used data from 11 486 adults aged 50 years or above within the first wave of the Study on Global Ageing and Adult Health in China during 2007-2010. Hypertension was assessed by criterion-based measures of blood pressure. Residential greenness was characterized by satellite-derived Normalized Difference Vegetation Index. We employed multilevel generalized structural equation models to estimate the association between neighbourhood greenness and hypertension in urban and rural areas. Serial mediation models have been performed to test potential pathways linking greenness to hypertension. RESULTS In rural areas, a greater amount of residential greenness was directly associated with a decrease in the odds of hypertension (odds ratio = 0.51, 95% confidence interval 0.29-0.89). No direct association was observed in urban areas (odds ratio = 1.33, 95% confidence interval 0.94-1.89). Serial mediation models showed that the association of greenness with hypertension was completely mediated by PM2.5 concentrations in urban areas, while the association of greenness with hypertension was only partially mediated by PM2.5 concentrations and serial PM2.5 concentrations-physical activity path in rural areas. There was no evidence that physical activity, air pollution-BMI path, air pollution-physical activity-BMI path, and physical activity-BMI path mediated the association in both urban and rural areas. CONCLUSIONS Higher neighbourhood greenness was directly associated with a lower prevalence of hypertension among middle and older aged adults in rural China but not in urban areas. The association of greenness with hypertension was completely mediated by air pollution (without any mediation effect of physical activity and BMI) in urban areas. In contrast, the association was partly mediated by air pollution, physical activity, and other unobservables in rural areas. Further longitudinal studies are warranted to prove a cause-and-effect association, which may help policymakers and practitioners to conduce effective interventions to prevent and control the prevalence of hypertension and the attendant disease burden.
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Affiliation(s)
- Baishi Huang
- School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China; Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-Sen University, Guangzhou, China
| | - Tong Xiao
- School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China; Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-Sen University, Guangzhou, China
| | - George Grekousis
- School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China; Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-Sen University, Guangzhou, China.
| | - Hongsheng Zhao
- Department of Land Economy, University of Cambridge, Cambridge, UK
| | - Jiarui He
- School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China; Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-Sen University, Guangzhou, China
| | - Guanghui Dong
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Ye Liu
- School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China; Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-Sen University, Guangzhou, China.
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