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Jimenez MP, Oken E, Gold DR, Luttmann-Gibson H, Requia WJ, Rifas-Shiman SL, Gingras V, Hivert MF, Rimm EB, James P. Early life exposure to green space and insulin resistance: An assessment from infancy to early adolescence. ENVIRONMENT INTERNATIONAL 2020; 142:105849. [PMID: 32593049 PMCID: PMC7784302 DOI: 10.1016/j.envint.2020.105849] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 05/29/2020] [Accepted: 06/01/2020] [Indexed: 05/13/2023]
Abstract
BACKGROUND Recent studies suggest that greater exposure to natural vegetation, or "green space" is associated with lower diabetes risk, possibly through increasing physical activity. However, there is limited research on green space and insulin resistance in youth. We hypothesized greater green space at early-life sensitive time periods would be associated with lower insulin resistance in youth. METHODS We used data from Project Viva (N = 460), a pre-birth cohort study that recruited pregnant women in eastern Massachusetts, 1999-2002, and followed offspring into adolescence. We defined residential green space exposure at infancy (median age - 1.1 years), early childhood (3.2 years), mid-childhood (7.7 years), and early adolescence (12.8 years), using 30 m resolution Landsat satellite imagery to estimate the Normalized Difference Vegetation Index [NDVI]. Our main outcome was early adolescence estimated insulin resistance (HOMA-IR). We used multiple imputation to account for missing data and multiple linear regression models adjusted for age, sex, race/ethnicity, parental education, household income, and neighborhood median household income. RESULTS The highest green space tertile had the highest percentage of white participants (85%), college-educated mothers (87%) and fathers (85%), and households with income higher than US$70,000 (86%). Unadjusted models showed that participants living in the highest green space tertile at infancy had a 0.15 unit lower HOMA-IR (95% CI: -0.23, -0.06) in early adolescence, than those living in the lowest tertile. However, in adjusted models, we did not observe evidence of associations between green space from infancy to early adolescence and HOMA-IR in early adolescence, although some point estimates were in the hypothesized direction. For example, participants in the highest green space tertile in infancy had 0.03 units lower HOMA-IR (95%CI: -0.14, 0.08) than those living in the lowest tertile. CONCLUSIONS Exposure to green space at early life sensitive time periods was not associated with HOMA-IR in youth. Early-life longitudinal studies across diverse populations are needed to confirm or refute our results.
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Affiliation(s)
- Marcia P Jimenez
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Diane R Gold
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Heike Luttmann-Gibson
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Weeberb J Requia
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Sheryl L Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Veronique Gingras
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Eric B Rimm
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Peter James
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, USA
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Dzhambov AM, Browning MHEM, Markevych I, Hartig T, Lercher P. Analytical approaches to testing pathways linking greenspace to health: A scoping review of the empirical literature. ENVIRONMENTAL RESEARCH 2020; 186:109613. [PMID: 32668553 DOI: 10.1016/j.envres.2020.109613] [Citation(s) in RCA: 105] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 04/26/2020] [Accepted: 04/26/2020] [Indexed: 05/04/2023]
Abstract
BACKGROUND Inadequate translation from theoretical to statistical models of the greenspace - health relationship may lead to incorrect conclusions about the importance of some pathways, which in turn may reduce the effectiveness of public health interventions involving urban greening. In this scoping review we aimed to: (1) summarize the general characteristics of approaches to intervening variable inference (mediation analysis) employed in epidemiological research in the field; (2) identify potential threats to the validity of findings; and (3) propose recommendations for planning, conducting, and reporting mediation analyses. METHODS We conducted a scoping review, searching PubMed, Scopus, and Web of Science for peer-reviewed epidemiological studies published by December 31, 2019. The list of potential studies was continuously updated through other sources until March 2020. Narrative presentation of the results was coupled with descriptive summary of study characteristics. RESULTS We found 106 studies, most of which were cross-sectional in design. Most studies only had a spatial measure of greenspace. Mental health/well-being was the most commonly studied outcome, and physical activity and air pollution were the most commonly tested intervening variables. Most studies only conducted single mediation analysis, even when multiple potentially intertwined mediators were measured. The analytical approaches used were causal steps, difference-of-coefficients, product-of-coefficients, counterfactual framework, and structural equation modelling (SEM). Bootstrapping was the most commonly used method to construct the 95% CI of the indirect effect. The product-of-coefficients method and SEM as used to investigate serial mediation components were more likely to yield findings of indirect effect. In some cases, the causal steps approach thwarted tests of indirect effect, even though both links in an indirect effect were supported. In most studies, sensitivity analyses and proper methodological discussion of the modelling approach were missing. CONCLUSIONS We found a persistent pattern of suboptimal conduct and reporting of mediation analysis in epidemiological studies investigating pathways linking greenspace to health; however, recent years have seen improvements in these respects. Better planning, conduct, and reporting of mediation analyses are warranted.
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Affiliation(s)
- Angel M Dzhambov
- Department of Hygiene and Ecomedicine, Faculty of Public Health, Medical University of Plovdiv, Plovdiv, Bulgaria.
| | - Matthew H E M Browning
- Department of Park, Recreation, and Tourism Management, Clemson University, Clemson, USA
| | - Iana Markevych
- Institute of Psychology, Jagiellonian University, Krakow, Poland
| | - Terry Hartig
- Institute for Housing and Urban Research, Uppsala University, Uppsala, Sweden
| | - Peter Lercher
- Institute for Highway Engineering and Transport Planning, Graz University of Technology, Graz, Austria
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Rugel EJ, Brauer M. Quiet, clean, green, and active: A Navigation Guide systematic review of the impacts of spatially correlated urban exposures on a range of physical health outcomes. ENVIRONMENTAL RESEARCH 2020; 185:109388. [PMID: 32244108 DOI: 10.1016/j.envres.2020.109388] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 02/23/2020] [Accepted: 03/12/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Recent epidemiologic analyses have considered impacts of multiple spatially correlated urban exposures, but this literature has not been systematically evaluated. OBJECTIVES To characterize the long-term impacts of four distinct spatially correlated urban environmental exposures - traffic-related air pollution (TRAP), noise, natural spaces, and neighborhood walkability - by evaluating studies including measures of at least two such exposures in relationship to mortality, cardiovascular disease, chronic respiratory disease, allergy, type 2 diabetes, or reproductive outcomes. METHODS Following the Navigation Guide framework, the literature was searched for studies published since 2003 and meeting predefined inclusion criteria. Identified studies were scored individually for risk of bias and all studies related to an exposure-group set were appraised for overall quality and strength of evidence. RESULTS A total of 51 individual studies (TRAP and noise: n = 29; TRAP and natural spaces: n = 10; noise and natural spaces: n = 2; TRAP, noise, and natural spaces: n = 7; TRAP, noise, natural spaces, and walkability: n = 3) were included. When TRAP and noise were considered jointly, evidence was sufficient for increased cardiovascular morbidity with higher noise exposures; sufficient for no effect of TRAP on CVD morbidity; sufficient for increased mortality with higher TRAP exposures, but limited for noise; and limited for increased adverse reproductive outcomes with higher TRAP exposures and no effect of noise. Looking at natural spaces and TRAP, there was limited evidence for lower risk of chronic respiratory disease and small increases in birthweight with greater natural space; this relationship with birthweight persisted after adjustment for noise as well. Evidence was inadequate for all other exposure groups and outcomes. DISCUSSION Studies that properly account for the complexity of relationships between urban form and physical health are limited but suggest that even highly correlated exposures may have distinct effects. REVIEW REGISTRATION PROSPERO 2018 CRD42018106050.
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Affiliation(s)
- Emily Jessica Rugel
- School of Population and Public Health, University of British Columbia, 3rd Floor - 2206 East Mall, Vancouver, BC V6T1Z3, Canada
| | - Michael Brauer
- School of Population and Public Health, University of British Columbia, 3rd Floor - 2206 East Mall, Vancouver, BC V6T1Z3, Canada; Institute for Health Metrics and Evaluation, University of Washington, 2301 5th Ave, Suite 600, Seattle, WA 98121, USA.
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Liu L, Zhu A, Shu C, Zeng Y, Ji JS. Gene-Environment Interaction of FOXO and Residential Greenness on Mortality Among Older Adults. Rejuvenation Res 2020; 24:49-61. [PMID: 32364002 DOI: 10.1089/rej.2019.2301] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Residential greenness is an important environmental factor that is strongly associated with mortality. To our knowledge, there was no previous study on the gene-environment interaction analysis between residential greenness and forkhead box O (FOXO) gene, a candidate longevity gene. Our sample consisted of 3179 participants aged 65 and older from the Chinese Longitudinal Healthy Longevity Survey. Residential greenness was measured by satellite-derived normalized difference vegetation index (NDVI) using a 500-m radius around each residential location. Contemporaneous NDVI, cumulative NDVI, and changes in NDVI over time were calculated. We used Cox-proportional hazard regression models to assess the main effect and gene-environment interaction effect of FOXO single nucleotide polymorphism (SNP) and residential greenness on mortality. We found that participants carrying two minor alleles of the three studied FOXO3A SNPs had lower mortality risk than those without minor allele (hazard ratio [HR]: 0.803 95% confidence interval [CI]: 0.654-0.987 for rs4946936, HR: 0.807 95% CI: 0.669-0.974 for rs2802292, HR: 0.803 95% CI: 0.666-0.968 for rs2253310). We found no difference in mortality among the genotypes of the other three FOXO1A SNPs (rs17630266, rs2755213, or rs2755209). Higher contemporaneous NDVI was associated with lower mortality risk (HR: 0.887 95% CI: 0.863-0.911 for 0.1-U of NDVI). The protective effect of both contemporaneous NDVI and cumulative NDVI was stronger for two minor allele carriers compared with zero minor allele carriers of the three FOXO3A SNPs. Compared with the zero minor allele genotype of the three FOXO3A SNPs, the protective effect on the mortality risk of minor allele homozygotes also increased with the increasing NDVI level at percentile 25, 50, and 75 (interaction term coefficient p < 0.05). We found gene-environment interaction between FOXO and residential greenness on mortality in this population study. A higher level of greenness may interact with FOXO pathways.
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Affiliation(s)
- Linxin Liu
- Environmental Research Center, Duke Kunshan University, Kunshan, China
| | - Anna Zhu
- Environmental Research Center, Duke Kunshan University, Kunshan, China
| | - Chang Shu
- School of Medicine, Yale University, New Haven, Connecticut, USA
| | - Yi Zeng
- Center for the Study of Aging and Human Development, Duke Medical School, Durham, North Carolina, USA.,Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China
| | - John S Ji
- Environmental Research Center, Duke Kunshan University, Kunshan, China.,Nicholas School of the Environment, Duke University, Durham, North Carolina, USA
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Yang BY, Liu KK, Markevych I, Knibbs LD, Bloom MS, Dharmage SC, Lin S, Morawska L, Heinrich J, Jalaludin B, Gao M, Guo Y, Zhou Y, Huang WZ, Yu HY, Zeng XW, Hu LW, Hu Q, Dong GH. Association between residential greenness and metabolic syndrome in Chinese adults. ENVIRONMENT INTERNATIONAL 2020; 135:105388. [PMID: 31837524 DOI: 10.1016/j.envint.2019.105388] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 11/28/2019] [Accepted: 12/02/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Residing in greener areas has several health benefits, but no study to date has examined the effects of greenness on metabolic syndrome (MetS). We aimed to assess associations between residential greenness and MetS prevalence in China, and to explore whether air pollution and physical activity mediated any observed associations. METHODS We analyzed data from 15,477 adults who participated in the 33 Communities Chinese Health Study during 2009. We defined MetS according to standard guidelines for Chinese populations. Residential greenness was estimated using the Normalized Difference Vegetation Index (NDVI), the Soil Adjusted Vegetation Index (SAVI), and the Vegetation Continuous Field (VCF). We used generalized linear mixed models to assess the associations between greenness and MetS, and mediation analyses to explore potential mechanisms underlying the associations. RESULTS Higher greenness levels were associated with lower odds of MetS [e.g., for every interquartile range increase of NDVI500-m, SAVI500-m, and VCF500-m, the adjusted odds ratio of MetS was 0.81 (95% confidence interval: 0.70-0.93), 0.80 (95% confidence interval: 0.69-0.93), and 0.91 (95% confidence interval: 0.83-1.00), respectively]. The direction and the magnitude of the associations persisted in several sensitivity analyses. Stratified analyses showed that age and household income modified the associations, with greater effect estimates observed in participants younger than 65 years old or those with higher household income. Particulate matter with an aerodynamic diameter ≤10 μm, nitrogen dioxide, and ozone mediated 2.1-20.3% of the associations between greenness and MetS; no evidence of mediation was observed for physical activity. CONCLUSIONS Our findings suggest a beneficial association for residential greenness and MetS in Chinese urban dwellers, especially for participants younger than 65 years old and those with higher household income. Particulate matter with an aerodynamic diameter ≤10 μm, nitrogen dioxide and ozone, but not physical activity, may only partially mediate the association.
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Affiliation(s)
- Bo-Yi Yang
- 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 510080, China
| | - Kang-Kang Liu
- 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 510080, China
| | - Iana Markevych
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336 Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Luke D Knibbs
- School of Public Health, The University of Queensland, Herston, Queensland 4006, Australia
| | - Michael S Bloom
- Departments of Environmental Health Sciences and Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, NY 12144, USA
| | - Shaymali C Dharmage
- Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population & Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; Murdoch Children Research Institute, Melbourne, VIC 3010, Australia
| | - Shao Lin
- Departments of Environmental Health Sciences and Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, NY 12144, USA
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology (QUT), GPO Box 2434, Brisbane, Queensland 4001, Australia
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336 Munich, Germany; Comprehensive Pneumology Center Munich, German Center for Lung Research, Ziemssenstraße 1, 80336 Munich, Germany
| | - Bin Jalaludin
- Centre for Air Quality and Health Research and Evaluation, Glebe, NSW 2037, Australia; Population Health, South Western Sydney Local Health District, Liverpool, NSW 2170, Australia; Ingham Institute for Applied Medical Research, Liverpool, NSW 2170, Australia; School of Public Health and Community Medicine, The University of New South Wales, Kensington, NSW 2052, Australia
| | - Meng Gao
- Department of Geography, Hong Kong Baptist University, Hong Kong Special Administrative Region
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Yang Zhou
- 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 510080, China
| | - Wen-Zhong Huang
- 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 510080, China
| | - Hong-Yao Yu
- 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 510080, China
| | - Xiao-Wen Zeng
- 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 510080, China
| | - Li-Wen Hu
- 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 510080, China
| | - Qiang Hu
- Department of Pediatric Surgery, Weifang People's Hospital, Weifang 261041, China.
| | - Guang-Hui Dong
- 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 510080, China.
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Xiao X, Yang BY, Hu LW, Markevych I, Bloom MS, Dharmage SC, Jalaludin B, Knibbs LD, Heinrich J, Morawska L, Lin S, Roponen M, Guo Y, Lam Yim SH, Leskinen A, Komppula M, Jalava P, Yu HY, Zeeshan M, Zeng XW, Dong GH. Greenness around schools associated with lower risk of hypertension among children: Findings from the Seven Northeastern Cities Study in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 256:113422. [PMID: 31672364 DOI: 10.1016/j.envpol.2019.113422] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 10/12/2019] [Accepted: 10/15/2019] [Indexed: 05/12/2023]
Abstract
Evidence suggests that residential greenness may be protective of high blood pressure, but there is scarcity of evidence on the associations between greenness around schools and blood pressure among children. We aimed to investigate this association in China. Our study included 9354 children from 62 schools in the Seven Northeastern Cities Study. Greenness around each child's school was measured by NDVI (Normalized Difference Vegetation Index) and SAVI (Soil-Adjusted Vegetation Index). Particulate matter ≤ 1 μm (PM1) concentrations were estimated by spatiotemporal models and nitrogen dioxide (NO2) concentrations were collected from air monitoring stations. Associations between greenness and blood pressure were determined by generalized linear and logistic mixed-effect models. Mediation by air pollution was assessed using mediation analysis. Higher greenness was consistently associated with lower blood pressure. An increase of 0.1 in NDVI corresponded to a reduction in SBP of 1.39 mmHg (95% CI: 1.86, -0.93) and lower odds of hypertension (OR = 0.76, 95% CI: 0.69, 0.82). Stronger associations were observed in children with higher BMI. Ambient PM1 and NO2 mediated 33.0% and 10.9% of the association between greenness and SBP, respectively. In summary, greater greenness near schools had a beneficial effect on blood pressure, particularly in overweight or obese children in China. The associations might be partially mediated by air pollution. These results might have implications for policy makers to incorporate more green space for both aesthetic and health benefits.
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Affiliation(s)
- Xiang Xiao
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Bo-Yi Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Li-Wen Hu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Iana Markevych
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Michael S Bloom
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China; Departments of Environmental Health Sciences & Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY, 12144, USA
| | - Shyamali C Dharmage
- Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, 3004, Australia; Murdoch Children Research Institute, Melbourne, VIC, 3010, Australia
| | - Bin Jalaludin
- Centre for Air Quality and Health Research and Evaluation, Glebe, NSW, 2037, Australia; IIngham Institute for Applied Medial Research, University of New South Wales, Sydney, 2170, Australia
| | - Luke D Knibbs
- School of Public Health, The University of Queensland, Herston, Queensland, 4006, Australia
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336, Munich, Germany; Comprehensive Pneumology Center Munich, German Center for Lung Research, Ziemssenstraße 1, 80336, Munich, Germany
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology (QUT), GPO Box 2434, Brisbane, Queensland, 4001, Australia
| | - Shao Lin
- Departments of Environmental Health Sciences & Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY, 12144, USA
| | - Marjut Roponen
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, FI, 70211, Finland
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Steve Hung Lam Yim
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China; Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China
| | - Ari Leskinen
- Finnish Meteorological Institute, Kuopio, 70211, Finland; Department of Applied Physics, University of Eastern Finland, Kuopio, 70211, Finland
| | - Mika Komppula
- Finnish Meteorological Institute, Kuopio, 70211, Finland
| | - Pasi Jalava
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, FI, 70211, Finland
| | - Hong-Yao Yu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Mohammed Zeeshan
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiao-Wen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
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Fan S, Xue Z, Yuan J, Zhou Z, Wang Y, Yang Z, Yang B, Dong G, Zhang Z. Associations of Residential Greenness with Diabetes Mellitus in Chinese Uyghur Adults. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16245131. [PMID: 31888136 PMCID: PMC6950214 DOI: 10.3390/ijerph16245131] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 11/26/2019] [Accepted: 12/10/2019] [Indexed: 12/26/2022]
Abstract
Greenness exposure is nominated as a potential beneficial factor for health, but evidence is limited on its diabetes effects. We conducted a cross-sectional study between May and September 2016 in rural areas of northwestern China, including 4670 Uyghur adults, to explore the associations between residential greenness and fasting glucose levels and diabetes prevalence. Fasting glucose levels were determined, and information on covariates was collected by questionnaire. Normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI) were calculated to assess greenness levels. Generalized linear mixed models were applied to evaluate the associations of greenness with fasting glucose levels and diabetes prevalence. The prevalence of diabetes was 11.6%. We found that living in rural areas characterized by increased amounts of greenness was associated with reduced diabetes prevalence (e.g., NDVI1000m: OR, 0.92; 95% CI, 0.86, 0.99). Stratified analyses showed that the protective effects of greenness on diabetes prevalence were found only in women (NDVI1000m: OR, 0.90; 95% CI, 0.82, 0.99). However, none of the interaction was statistically significant. Our study suggests that greater residential greenness levels were associated with a lower odds ratio of diabetes prevalence in Xinjiang Uyghur adults. Further well-designed longitudinal studies are needed to confirm our findings.
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Affiliation(s)
- Shujun Fan
- Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China; (S.F.); (J.Y.); (Z.Z.); (Z.Y.)
| | - Zhenxiang Xue
- Shufu Center for Disease Control and Prevention, Kashgar 844100, China; (Z.X.); (Y.W.)
| | - Jun Yuan
- Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China; (S.F.); (J.Y.); (Z.Z.); (Z.Y.)
| | - Ziyan Zhou
- Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China; (S.F.); (J.Y.); (Z.Z.); (Z.Y.)
| | - Yuzhong Wang
- Shufu Center for Disease Control and Prevention, Kashgar 844100, China; (Z.X.); (Y.W.)
| | - Zhicong Yang
- Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China; (S.F.); (J.Y.); (Z.Z.); (Z.Y.)
| | - Boyi Yang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, 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 510080, China;
| | - Guanghui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, 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 510080, China;
- Correspondence: (G.D.); (Z.Z.); Tel.: +862087333409 (G.D.); +86-20-36052380 (Z.Z.); Fax: +862087330446 (G.D.); +86-20-36052380 (Z.Z.)
| | - Zhoubin Zhang
- Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China; (S.F.); (J.Y.); (Z.Z.); (Z.Y.)
- Correspondence: (G.D.); (Z.Z.); Tel.: +862087333409 (G.D.); +86-20-36052380 (Z.Z.); Fax: +862087330446 (G.D.); +86-20-36052380 (Z.Z.)
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Yang BY, Guo Y, Markevych I, Qian Z(M, Bloom MS, Heinrich J, Dharmage SC, Rolling CA, Jordan SS, Komppula M, Leskinen A, Bowatte G, Li S, Chen G, Liu KK, Zeng XW, Hu LW, Dong GH. Association of Long-term Exposure to Ambient Air Pollutants With Risk Factors for Cardiovascular Disease in China. JAMA Netw Open 2019; 2:e190318. [PMID: 30848806 PMCID: PMC6484675 DOI: 10.1001/jamanetworkopen.2019.0318] [Citation(s) in RCA: 146] [Impact Index Per Article: 29.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
IMPORTANCE Which cardiometabolic risk factors (eg, hypertension, type 2 diabetes, overweight or obesity, and dyslipidemia) are more sensitive to long-term exposure to ambient air pollution and whether participants with these conditions are more susceptible to the cardiovascular effects of air pollution remain unclear. OBJECTIVES To evaluate the associations among long-term exposure to air pollutants, cardiometabolic risk factors, and cardiovascular disease (CVD) prevalence. DESIGN, SETTING, AND PARTICIPANTS This population-based cross-sectional study was conducted from April 1 through December 31, 2009, in 3 cities in Northeastern China. Participants were adults aged 18 to 74 years who had lived in study area for 5 years or longer. Data analysis was performed from May 1 through December 31, 2018. EXPOSURES Long-term (2006-2008) exposure to air pollutants was measured using a spatiotemporal statistical model (particulate matter with an aerodynamic diameter of ≤2.5 μm [PM2.5] and ≤1.0 μm [PM1.0]) and data from air monitoring stations (particulate matter with an aerodynamic diameter of ≤10.0 μm [PM10.0], sulfur dioxide [SO2], nitrogen dioxide [NO2], and ozone [O3]). MAIN OUTCOMES AND MEASURES Cardiovascular disease was determined by self-report of physician-diagnosed CVD. Blood pressure, body mass index, and levels of triglycerides and low-density lipoprotein cholesterol were measured using standard methods. RESULTS Participants included 15 477 adults (47.3% women) with a mean (SD) age of 45.0 (13.5) years. The prevalence of CVD was 4.8%, and the prevalence of cardiometabolic risk factors ranged from 8.6% (hyperbetalipoproteinemia) to 40.5% (overweight or obesity). Mean (SD) air pollutant concentrations ranged from 35.3 (5.5) μg/m3 (for NO2) to 123.1 (14.6) μg/m3 (for PM10.0). Associations with air pollutants were identified for individuals with hyperbetalipoproteinemia (eg, odds ratio [OR], 1.36 [95% CI, 1.03-1.78] for a 10-μg/m3 increase in PM1.0) and the weakest association for those with for overweight or obesity (eg, OR, 1.06 [95% CI, 1.02-1.09] for a 10-μg/m3 increase in PM1.0). Cardiometabolic risk factors only partially mediated associations between air pollution and CVD. However, they modified the associations such that greater associations were found in participants with these cardiometabolic conditions (eg, ORs for CVD and per 10-μg/m3 increase in PM1.0, 1.22 [95% CI, 1.12-1.33] in participants with hyperbetalipoproteinemia and 1.07 [95% CI, 0.98-1.16] in participants without hyperbetalipoproteinemia). CONCLUSIONS AND RELEVANCE In this population-based study of Chinese adults with CVD, long-term exposure to air pollution was associated with a higher prevalence of cardiometabolic risk factors, and the strongest associations were observed for hyperbetalipoproteinemia. In addition, participants with cardiometabolic risk factors may have been more vulnerable to the effects of air pollution on CVD.
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Affiliation(s)
- Bo-Yi Yang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, 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, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Iana Markevych
- Institute of Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
- Division of Metabolic and Nutritional Medicine, Dr von Hauner Children’s Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital of Munich, Munich, Germany
| | - Zhengmin (Min) Qian
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, St Louis, Missouri
| | - Michael S. Bloom
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, New York
- Department of Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, New York
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital of Munich, Munich, Germany
- Comprehensive Pneumology Center Munich, German Center for Lung Research, Munich, Germany
| | - Shyamali C. Dharmage
- Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia
- Murdoch Children Research Institute, Melbourne, Australia
| | - Craig A. Rolling
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, St Louis, Missouri
| | - Savannah S. Jordan
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, St Louis, Missouri
| | | | - Ari Leskinen
- Finnish Meteorological Institute, Kuopio, Finland
| | - Gayan Bowatte
- The National Institute of Fundamental Studies, Kandy, Sri Lanka
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Gongbo Chen
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Kang-Kang Liu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, 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, China
| | - Xiao-Wen Zeng
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, 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, China
| | - Li-Wen Hu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, 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, China
| | - Guang-Hui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, 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, China
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