1
|
Valente B, Araújo B, Pereira R, Isabel Ribeiro A, Barros H, Santos S. Residential exposure to green and blue spaces over childhood and cardiometabolic health outcomes: The generation XXI birth cohort. ENVIRONMENT INTERNATIONAL 2025; 198:109452. [PMID: 40239565 DOI: 10.1016/j.envint.2025.109452] [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: 01/08/2025] [Revised: 03/13/2025] [Accepted: 04/09/2025] [Indexed: 04/18/2025]
Abstract
Evidence on the effects of green and blue spaces on childhood cardiometabolic health is inconsistent and mostly cross-sectional. We assessed the associations of green and blue spaces exposure at birth 4, 7, and 10 years (to identify vulnerable periods of exposure) and as longitudinal trajectories (to identify the longitudinal effect over time) with cardiometabolic outcomes at 10 years. Among 4669 participants from a population-based birth cohort, we assessed the residential normalized difference vegetation index (NDVI) and distance to urban green and blue spaces at each time point using geographic information systems and standardized by dividing the observed value by the standard deviation. Longitudinal exposure trajectories were derived using latent class mixed models. At 10 years, we measured body mass index, fat mass index, android-to-gynoid fat ratio, blood pressure, and metabolic outcomes. We defined overweight/obesity (World Health Organization), high blood pressure (American Academy of Pediatrics), and metabolic syndrome (IDEFICS). No significant associations were observed between natural spaces exposure and adiposity outcomes. We found an inverse association between distance to nearest blue space at birth and systolic blood pressure z-scores, and a positive association between distance to nearest green space at 7 and 10 years and metabolic syndrome score (p < 0.05). Children in the descending NDVI500m trajectory, compared to those in the high stable trajectory, showed lower diastolic blood pressure z-scores and metabolic syndrome scores (p < 0.05). However, after multiple testing corrections, all associations lost statistical significance. This study did not find robust associations between natural spaces during key developmental periods and cardiometabolic health.
Collapse
Affiliation(s)
- Berta Valente
- EPIUnit ITR, Instituto de Saúde Pública da Universidade do Porto, Universidade do Porto, Rua das Taipas, n° 135, 4050-600 Porto, Portugal
| | - Berna Araújo
- EPIUnit ITR, Instituto de Saúde Pública da Universidade do Porto, Universidade do Porto, Rua das Taipas, n° 135, 4050-600 Porto, Portugal
| | - Rita Pereira
- EPIUnit ITR, Instituto de Saúde Pública da Universidade do Porto, Universidade do Porto, Rua das Taipas, n° 135, 4050-600 Porto, Portugal
| | - Ana Isabel Ribeiro
- EPIUnit ITR, Instituto de Saúde Pública da Universidade do Porto, Universidade do Porto, Rua das Taipas, n° 135, 4050-600 Porto, Portugal; Departamento de Saúde Pública e Ciências Forenses e Educação Médica, Faculdade de Medicina, Universidade do Porto, Alameda Prof. Hernâni Monteiro, 4200-319 Porto, Portugal
| | - Henrique Barros
- EPIUnit ITR, Instituto de Saúde Pública da Universidade do Porto, Universidade do Porto, Rua das Taipas, n° 135, 4050-600 Porto, Portugal; Departamento de Saúde Pública e Ciências Forenses e Educação Médica, Faculdade de Medicina, Universidade do Porto, Alameda Prof. Hernâni Monteiro, 4200-319 Porto, Portugal
| | - Susana Santos
- EPIUnit ITR, Instituto de Saúde Pública da Universidade do Porto, Universidade do Porto, Rua das Taipas, n° 135, 4050-600 Porto, Portugal.
| |
Collapse
|
2
|
Yang HM, Wang JY, Li C, Zhang YQ, Wang R, Yang Q, Yao Y, Wang Z, Xu SL, Huang HH, Hu QS, Liu RQ, Dong GH. Is there an association between eye-level greenness and childhood hypertension using street view? Findings from the Seven Northeastern Cities study in China. ENVIRONMENTAL RESEARCH 2025; 268:120768. [PMID: 39761782 DOI: 10.1016/j.envres.2025.120768] [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: 11/07/2024] [Revised: 12/17/2024] [Accepted: 01/03/2025] [Indexed: 01/13/2025]
Abstract
There is a lack of evidence regarding associations of eye-level greenness exposure with blood pressure among children. We aimed to investigate the associations between different types of eye-level greenness and pediatric blood pressure in China. From 2012 to 2013, we recruited 9354 children aged between 5 and 17 years in northeast China. Eye-level of greenness was assessed with Street View Greenness (SVG), derived from Tencent Street View images surrounding participants' schools, utilizing a deep machine learning model. Hypertension was defined as blood pressure above the 95th percentile based on the fourth report's guidelines for children and adolescents. Generalized linear mixed-effects regression models were conducted to estimate adjusted odds ratio (aOR) and estimates of childhood hypertension and pediatric blood pressure per interquartile range (IQR) increase of SVG. Mediation analyses including air pollution and exercise time were also performed. We found the significant association of SVG-total with decreased odds of hypertension in Chinese children (aOR = 0.83, 95%CI: 0.75,0.91), especially with the decrease of SBP (β = -0.76, 95%CI: 1.09,-0.43). Interestingly, per IQR increase in SVG-tree 800m for trees was associated with lower adjusted odds of pediatric hypertension (aOR = 0.84; 95%CI: 0.76, 0.92), also with the decrease of systolic blood pressure. Mediation analyses showed that hypertension was significantly mitigated by lower levels of air pollutants, including PM2.5, PM10, SO2 and NO2. Results of this study suggested that eye-level greenness, especially trees, were associated with lower prevalence of hypertension in children, with air pollution exhibiting mediating effects. These findings emphasized the importance of incorporating more greenness, especially trees in both urban planning and public health interventions.
Collapse
Affiliation(s)
- Huang-Min Yang
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Jing-Yao Wang
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Cheng Li
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Ya-Qin Zhang
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Ruoyu Wang
- Institute of Public Health and Wellbeing, University of Essex, Essex, UK
| | - Qi Yang
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yao Yao
- School of Geography and Information Engineering, China University of Geosciences, Wuhan, 430078, China
| | - Zilong Wang
- School of Geography and Information Engineering, China University of Geosciences, Wuhan, 430078, China
| | - Shu-Li Xu
- Department of Environmental and School Hygiene Supervision, Public Health Service Center, Bao'an District, Shenzhen, 518126, China.
| | - He-Hai Huang
- Department of Environmental and School Hygiene Supervision, Public Health Service Center, Bao'an District, Shenzhen, 518126, China
| | - Qian-Sheng Hu
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Ru-Qing Liu
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Guang-Hui Dong
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
| |
Collapse
|
3
|
Peng Y, He H, Lv B, Wang J, Qin Q, Song J, Liu Y, Su W, Song H, Chen Q. Chronic impacts of natural infrastructure on the physical and psychological health of university students during and after COVID-19: a case study of Chengdu, China. Front Public Health 2024; 12:1508539. [PMID: 39735753 PMCID: PMC11671516 DOI: 10.3389/fpubh.2024.1508539] [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: 10/11/2024] [Accepted: 11/25/2024] [Indexed: 12/31/2024] Open
Abstract
Introduction The COVID-19 pandemic has underscored the health benefits of green spaces, yet research on how specific elements of natural infrastructure affect well-being during the pandemic has been limited. Methods This study, conducted at Sichuan Agricultural University with 300 students in 2022, investigated how urban natural infrastructure impacts physical and psychological well-being during the pandemic. Different aspects of natural infrastructure, such as thermal comfort, air quality (negative ion concentration), and noise and light levels, varied in their positive effects on students' health. Results The findings revealed that 65.6% of university students felt reduced stress when engaging with outdoor spaces, and 72.8% of them renewed recognized the therapeutic value of nature. Discussion The study emphasizes the importance of incorporating natural elements into urban planning to enhance outdoor activity and well-being, especially in post-pandemic settings. Recommendations are provided for future urban design to address the therapeutic needs of specific populations.
Collapse
Affiliation(s)
- Yi Peng
- Landscape Architecture College, Sichuan Agricultural University, Chengdu, China
| | - Haoxing He
- Landscape Architecture College, Sichuan Agricultural University, Chengdu, China
| | - Bingyang Lv
- Landscape Architecture College, Sichuan Agricultural University, Chengdu, China
| | - Jiali Wang
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
| | - Qiao Qin
- China Construction Third Bureau First Construction Engineering Company, Wuhan, China
| | - Jialu Song
- Landscape Architecture College, Sichuan Agricultural University, Chengdu, China
| | - Yuzhou Liu
- Landscape Architecture College, Sichuan Agricultural University, Chengdu, China
| | - Wenjun Su
- Sichuan Province Forestry Central Hospital, Chengdu, China
| | - Huixing Song
- Landscape Architecture College, Sichuan Agricultural University, Chengdu, China
| | - Qibing Chen
- Landscape Architecture College, Sichuan Agricultural University, Chengdu, China
| |
Collapse
|
4
|
Gong Y, Wang Y, Nong Q, Hu P, Li Z, Huang X, Zhong M, Li X, Wu S, Zeng F, Zhao N, Qin Y, Liu S, Hong J, Hu L, Zhang W, Huang Y. The Impact of Blood Lead and Its Interaction with Occupational Factors and Air Pollution on Hypertension Prevalence. TOXICS 2024; 12:861. [PMID: 39771076 PMCID: PMC11679143 DOI: 10.3390/toxics12120861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2024] [Revised: 11/22/2024] [Accepted: 11/26/2024] [Indexed: 01/11/2025]
Abstract
Large-scale epidemiological studies on the association of blood lead levels with blood pressure and hypertension prevalence are still limited, particularly among lead-exposed workers. The evidence is even more scarce on the interaction of blood lead levels with occupational variables and ambient air pollution levels. We developed mixed-effect models based on a large group of lead-exposed workers (N = 22,002). The results were also stratified by multiple groupings. Compared to participants with blood lead < 20 μg/L, those with levels > 20 μg/L had a 26-37% higher prevalence of hypertension, as well as a 0.65-13.7 mmHg higher systolic and diastolic blood pressure. Workers exposed to high PM10 levels had a 21-28% higher risk. Workers exposed to high temperatures had a 0.41-2.46 mmHg greater increase in blood pressure, and those not exposed to dust had a 1.29-1.65 mmHg greater blood pressure increase. Our findings suggested the negative impact of blood lead on blood pressure and the prevalence of hypertension, with workers exposed to high PM10 concentrations, those exposed to occupational high temperature, and those without dust exposure being more vulnerable.
Collapse
Affiliation(s)
- Yajun Gong
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Ying Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou 510080, China; (Y.W.); (S.W.); (F.Z.)
| | - Qiying Nong
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
| | - Peixia Hu
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
- School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Zhiqiang Li
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou 510080, China; (Y.W.); (S.W.); (F.Z.)
| | - Xiangyuan Huang
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
- School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Meimei Zhong
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
- School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Xinyue Li
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou 510080, China; (Y.W.); (S.W.); (F.Z.)
| | - Shaomin Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou 510080, China; (Y.W.); (S.W.); (F.Z.)
| | - Fangfang Zeng
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou 510080, China; (Y.W.); (S.W.); (F.Z.)
| | - Na Zhao
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
- School of Public Health, Southern Medical University, Guangzhou 510515, China
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou 510080, China; (Y.W.); (S.W.); (F.Z.)
- School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Yiru Qin
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
| | - Suhui Liu
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou 510080, China; (Y.W.); (S.W.); (F.Z.)
| | - Jiaying Hong
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
| | - Ligang Hu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou 510080, China; (Y.W.); (S.W.); (F.Z.)
| | - Yongshun Huang
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou 510300, China; (Y.G.); (Q.N.); (P.H.); (Z.L.); (X.H.); (M.Z.); (X.L.); (N.Z.); (Y.Q.); (S.L.); (J.H.)
- School of Public Health, Southern Medical University, Guangzhou 510515, China
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-Sen Global Health Institute, Sun Yat-Sen University, Guangzhou 510080, China; (Y.W.); (S.W.); (F.Z.)
- School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| |
Collapse
|
5
|
Cui Z, Pan R, Liu J, Yi W, Huang Y, Li M, Zhang Z, Kuang L, Liu L, Wei N, Song R, Yuan J, Li X, Yi X, Song J, Su H. Green space and its types can attenuate the associations of PM 2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China. ENVIRONMENTAL RESEARCH 2024; 245:117997. [PMID: 38157960 DOI: 10.1016/j.envres.2023.117997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 12/12/2023] [Accepted: 12/19/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces. METHODS A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations. RESULTS Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups. CONCLUSION Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.
Collapse
Affiliation(s)
- Zhiqian Cui
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Yuxin Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Ming Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Zichen Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Lingmei Kuang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Li Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Ning Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Jiajun Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Xuanxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Xingxu Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China.
| |
Collapse
|
6
|
Bao WW, Jiang N, Zhao Y, Yang B, Chen G, Pu Y, Ma H, Liang J, Xiao X, Guo Y, Dong G, Chen Y. Urban greenspaces and child blood pressure in China: Evidence from a large population-based cohort study. ENVIRONMENTAL RESEARCH 2024; 244:117943. [PMID: 38104917 DOI: 10.1016/j.envres.2023.117943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 11/22/2023] [Accepted: 12/11/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND With the world's population steadily shifting toward urban living, children's engagement with the natural environment seems to be diminishing. This raises significant concerns about the influence of urban greenspaces on the cardiovascular health of children. OBJECTIVE To assess the association between urban greenspaces exposure and blood pressure (BP) in Chinese primary schoolchildren. METHODS This prospective cohort study used data from the Children's growth environment, lifestyle, physical, and mental health development (COHERENCE) project in Guangzhou, China. Participants included 164,853 primary schoolchildren starting from 2016/17 to 2019/20 academic year. We assessed the surrounding greenspaces at home and school by using Sentinel-2 satellite data on the normalized difference vegetation index. Prehypertension and hypertension status were defined with BP above 90th to less than the 95th percentile, at or above the 95th percentile, respectively. The association of surrounding greenness with children's BP levels and risk of prehypertension/hypertension were examined using linear mixed-effects models and Cox proportional hazards model. RESULTS Among 164,853 eligible children aged 7.21 (0.74) years, 89,190 (54.1%) were boys. Our results showed that average systolic and diastolic BP increased by 0.48 and 0.42 standard deviations, respectively, over the 3-year follow-up. We identified 23,225 new cases of prehypertension and 35,067 of hypertension status. An interquartile range increase both in home-, school- and home-school NDVI100m was significantly associated with a reduction of 0.018-0.037 in BP z-scores and a 2.7%-7.6% lower risk of hypertension. Additionally, family socioeconomic status modified the impact of home-school greenness on BP levels. Air pollution exhibited mediating effects solely in school-greenness-BP associations, while physical activity and children's BMI mainly mediated the relationships between home-greenness and BP. CONCLUSION The findings of this large cohort study suggest that surrounding greenspaces are associated with lower BP levels and a decreased risk of prehypertension and hypertension in Chinese schoolchildren.
Collapse
Affiliation(s)
- Wen-Wen Bao
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Nan Jiang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yu Zhao
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Boyi Yang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Gongbo Chen
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yinqi Pu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Hanping Ma
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinghong Liang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiang Xiao
- Department of Geography, Hong Kong Baptist University, Hong Kong Special Administrative Region, China; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Guanghui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yajun Chen
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
| |
Collapse
|
7
|
Guo X, Su W, Wang X, Hu W, Meng J, Ahmed MA, Qu G, Sun Y. Assessing the effects of air pollution and residential greenness on frailty in older adults: a prospective cohort study from China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:9091-9105. [PMID: 38183550 DOI: 10.1007/s11356-023-31741-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 12/22/2023] [Indexed: 01/08/2024]
Abstract
Many studies have established a correlation between air pollution and green space with age-related diseases, yet the relationship between air pollution, green space, and frailty among older adults is not fully understood. The primary objective of this investigation is to examine the longitudinal association among air pollution, green space, and frailty in older adults, as well as the potential interaction and mediating effect. Analyzed data were obtained from the multi-wave CLHLS investigation (2008-2018). The participants' environmental exposure was evaluated using six air pollutants (PM1, PM2.5, PM10, PM10-2.5, O3, and NO2), and normalized difference vegetation index (NDVI). Annual ambient air pollutants were estimated using satellite-based spatiotemporal models. Time-varying Cox proportional risk models were employed to investigate the longitudinal relationships between air pollutants, greenness, and the onset of frailty in the elderly population. We conducted a variety of subgroup analyses, sensitivity analyses, and assessed potential interaction and causal mediating effects. A total of 6953 eligible elderly individuals were enrolled in our study. In the fully adjusted model, per IQR uptick in levels of PM1, PM2.5, PM10, PM10-2.5, O3, and NO2 corresponded to a 17% (95% CI 1.10-1.24), 25% (95% CI 1.17-1.34), 29% (95% CI 1.20-1.39), 35% (95% CI 1.24-1.47), 12% (95% CI 1.04-1.20), and 11% (95% CI 1.05-1.18) increase in frailty risk, respectively. For NDVI, increased IQR was significantly negatively associated with the risk of frailty (aHR 0.82, 95% CI 0.77-0.87). Our results revealed a significant interaction effect among O3, NO2, and residential greenness. PM1, PM2.5, PM10, and PM10-2.5 play a mediating role in the estimated relationship between residential greenness and frailty. In summary, our study reveals that PM1, PM2.5, PM10, PM10-2.5, O3, and NO2 correspond to elevated risks of frailty in the elderly. Residential greenness is associated with a lower risk of frailty in the elderly. Residential greenness can exert a positive impact on frailty by reducing particulate matter concentrations.
Collapse
Affiliation(s)
- Xianwei Guo
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Wenqi Su
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Xingyue Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Wenjing Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Jia Meng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Mubashir Ayaz Ahmed
- Division of Pulmonary Critical Care and Sleep Medicine, Albert Einstein Medical Center, Philadelphia, PA, USA
| | - Guangbo Qu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Yehuan Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China.
| |
Collapse
|
8
|
Wu W, Wu G, Wei J, Lawrence WR, Deng X, Zhang Y, Chen S, Wang Y, Lin X, Chen D, Ruan X, Lin Q, Li Z, Lin Z, Hao C, Du Z, Zhang W, Hao Y. Potential causal links and mediation pathway between urban greenness and lung cancer mortality: Result from a large cohort (2009 to 2020). SUSTAINABLE CITIES AND SOCIETY 2024; 101:105079. [PMID: 38222851 PMCID: PMC10783447 DOI: 10.1016/j.scs.2023.105079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
Urban greenness, as a vital component of the urban environment, plays a critical role in mitigating the adverse effects of rapid urbanization and supporting urban sustainability. However, the causal links between urban greenness and lung cancer mortality and its potential causal pathway remain poorly understood. Based on a prospective community-based cohort with 581,785 adult participants in southern China, we applied a doubly robust Cox proportional hazard model to estimate the causal associations between urban greenness exposure and lung cancer mortality. A general multiple mediation analysis method was utilized to further assess the potential mediating roles of various factors including particulate matter (PM1, PM2.5-1, and PM10-2.5), temperature, physical activity, and body mass index (BMI). We observed that each interquartile range (IQR: 0.06) increment in greenness exposure was inversely associated with lung cancer mortality, with a hazard ratio (HR) of 0.89 (95 % CI: 0.83, 0.96). The relationship between greenness and lung cancer mortality might be partially mediated by particulate matter, temperature, and physical activity, yielding a total indirect effect of 0.826 (95 % CI: 0.769, 0.887) for each IQR increase in greenness exposure. Notably, the protective effect of greenness against lung cancer mortality could be achieved primarily by reducing the particulate matter concentration.
Collapse
Affiliation(s)
- Wenjing Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Gonghua Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, USA
| | - Wayne R Lawrence
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Xinlei Deng
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, USA
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Shirui Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Ying Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xiao Lin
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Dan Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xinling Ruan
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Qiaoxuan Lin
- Department of Statistics, Guangzhou Health Technology Identification & Human Resources Assessment Center, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Ziqiang Lin
- Department of Preventive Medicine, School of Basic Medicine and Public Health, Jinan University, Guangzhou, China
| | - Chun Hao
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, China
| |
Collapse
|
9
|
Ma Q, Cheng C, Chen Y, Wang Q, Li B, Wang P. Effect and prediction of physical exercise and diet on blood pressure control in patients with hypertension. Medicine (Baltimore) 2023; 102:e36612. [PMID: 38115342 PMCID: PMC10727525 DOI: 10.1097/md.0000000000036612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 08/07/2023] [Accepted: 11/21/2023] [Indexed: 12/21/2023] Open
Abstract
The study aims to explore the current status of hypertension control and its predictors in patients with hypertension in China and provide evidence for preventing and controlling hypertension. A questionnaire survey was conducted among 300 hypertensive patients who visited the Second Affiliated Hospital of Anhui Medical University from February 20, 2023 to March 11, 2023. The patients were divided into a well-controlled group and an untargeted-control group according to their hypertension control status. A total of 294 subjects, including 83 in the well-controlled group and 211 in the untargeted-control group, were included in the analysis. Multivariate logistic regression analysis showed that hypertensive patients with high BMI and family history of hypertension were risk factors for hypertension control. Married status was a protective factor for hypertension control. SVM optimized the model with γ = 0.001 and a penalty factor of C = 0.001. The prediction accuracy of the final model was 80.9%. The findings indicated that BMI, family history of hypertension, and marital status were independent predictors of blood pressure control. Further studies are warranted to illustrate potential mechanisms for improving hypertensive patients' blood pressure control.
Collapse
Affiliation(s)
- Qiang Ma
- Department of Police Physical Skills Training, Anhui Vocational College of Police Officers, Hefei, China
| | - Cheng Cheng
- Department of Cardiovascular Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yuenan Chen
- School of Pharmacy, Anhui Medical University, Hefei, China
| | - Qianya Wang
- School of Clinical Medicine, Anhui Medical University, Hefei, China
| | - Baozhu Li
- School of Public Health, Anhui Medical University, Hefei, China
| | - Ping Wang
- School of Innovation and Entrepreneurship, Anhui Medical University, Hefei, China
| |
Collapse
|
10
|
Sabedotti MES, O'Regan AC, Nyhan MM. Data Insights for Sustainable Cities: Associations between Google Street View-Derived Urban Greenspace and Google Air View-Derived Pollution Levels. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:19637-19648. [PMID: 37972280 DOI: 10.1021/acs.est.3c05000] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
Unprecedented levels of urbanization have escalated urban environmental health issues, including increased air pollution in cities globally. Strategies for mitigating air pollution, including green urban planning, are essential for sustainable and healthy cities. State-of-the-art research investigating urban greenspace and pollution metrics has accelerated through the use of vast digital data sets and new analytical tools. In this study, we examined associations between Google Street View-derived urban greenspace levels and Google Air View-derived air quality, where both have been resolved in extremely high resolution, accuracy, and scale along the entire road network of Dublin City. Particulate matter of size fraction less than 2.5 μm (PM2.5), nitrogen dioxide, nitric oxide, carbon monoxide, and carbon dioxide were quantified using 5,030,143 Google Air View measurements, and greenspace was quantified using 403,409 Google Street View images. Significant (p < 0.001) negative associations between urban greenspace and pollution were observed. For example, an interquartile range increase in the Green View Index was associated with a 7.4% [95% confidence interval: -13.1%, -1.3%] decrease in NO2 at the point location spatial resolution. We provide insights into how large-scale digital data can be harnessed to elucidate urban environmental interactions that will have important planning and policy implications for sustainable future cities.
Collapse
Affiliation(s)
- Maria E S Sabedotti
- Discipline of Civil, Structural & Environmental Engineering, School of Engineering & Architecture, University College Cork, Cork T12 K8AF, Ireland
- MaREI, the SFI Research Centre for Energy, Climate & Marine, University College Cork, Ringaskiddy, CorkP43 C573, Ireland
- Environmental Research Institute, University College Cork, Lee Rd, Sundays, Well, Cork T23 XE10, Ireland
| | - Anna C O'Regan
- Discipline of Civil, Structural & Environmental Engineering, School of Engineering & Architecture, University College Cork, Cork T12 K8AF, Ireland
- MaREI, the SFI Research Centre for Energy, Climate & Marine, University College Cork, Ringaskiddy, CorkP43 C573, Ireland
- Environmental Research Institute, University College Cork, Lee Rd, Sundays, Well, Cork T23 XE10, Ireland
| | - Marguerite M Nyhan
- Discipline of Civil, Structural & Environmental Engineering, School of Engineering & Architecture, University College Cork, Cork T12 K8AF, Ireland
- MaREI, the SFI Research Centre for Energy, Climate & Marine, University College Cork, Ringaskiddy, CorkP43 C573, Ireland
- Environmental Research Institute, University College Cork, Lee Rd, Sundays, Well, Cork T23 XE10, Ireland
| |
Collapse
|
11
|
Baheti B, Chen G, Ding Z, Wu R, Zhang C, Zhou L, Liu X, Song X, Wang C. Residential greenness alleviated the adverse associations of long-term exposure to ambient PM 1 with cardiac conduction abnormalities in rural adults. ENVIRONMENTAL RESEARCH 2023; 237:116862. [PMID: 37574100 DOI: 10.1016/j.envres.2023.116862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/27/2023] [Accepted: 08/08/2023] [Indexed: 08/15/2023]
Abstract
BACKGROUND Ambient air pollution was linked to elevated risks of adverse cardiovascular events, and alterations in electrophysiological properties of the heart might be potential pathways. However, there is still lacking research exploring the associations between PM1 exposure and cardiac conduction parameters. Additionally, the interactive effects of PM1 and residential greenness on cardiac conduction parameters in resource-limited areas remain unknown. METHODS A total of 27483 individuals were enrolled from the Henan Rural Cohort study. Cardiac conduction parameters were tested by 12-lead electrocardiograms. Concentrations of PM1 were evaluated by satellite-based spatiotemporal models. Levels of residential greenness were assessed using Enhanced Vegetation Index (EVI) and Normalized difference vegetation index (NDVI). Logistic regression models and restricted cubic splines were fitted to explore the associations of PM1 and residential greenness exposure with cardiac conduction abnormalities risk, and the interaction plot method was performed to visualize their interaction effects. RESULTS The 3-year median concentration of PM1 was 56.47 (2.55) μg/m3, the adjusted odds rate (ORs) and 95% confidence intervals (CIs) for abnormal HR, PR, QRS, and QTc interval risk in response to 1 μg/m3 increase in PM1 were 1.064 (1.044, 1.085), 1.037 (1.002, 1.074), 1.061 (1.044, 1.077) and 1.046 (1.028, 1.065), respectively. Participants exposure to higher levels of PM1 had increased risks of abnormal HR (OR = 1.221, 95%CI: 1.144, 1.303), PR (OR = 1.061, 95%CI: 0.940, 1.196), QRS (OR = 1.225, 95%CI: 1.161, 1.294) and QTc interval (OR = 1.193, 95%CI: 1.121, 1.271) compared with lower levels of PM1. Negative interactive effects of exposure to PM1 and residential greenness on abnormal HR, QRS, and QTc intervals were observed (Pfor interaction < 0.05). CONCLUSION Long-term PM1 exposure was associated with elevated cardiac conduction abnormalities risks, and this adverse association might be mitigated by residential greenness to some extent. These findings emphasize that controlling PM1 pollution and increasing greenness levels might be effective strategies to reduce cardiovascular disease burdens in resource-limited areas.
Collapse
Affiliation(s)
- Bota Baheti
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Gongbo Chen
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Zhongao Ding
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Ruiyu Wu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Caiyun Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Lue Zhou
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, PR China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xiaoqin Song
- Physical Examination Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China; NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, PR China.
| |
Collapse
|
12
|
Pan M, Liu F, Zhang K, Chen Z, Tong J, Wang X, Zhou F, Xiang H. Independent and interactive associations between greenness and ambient pollutants on novel glycolipid metabolism biomarkers: A national repeated measurement study. ENVIRONMENTAL RESEARCH 2023; 233:116393. [PMID: 37308069 DOI: 10.1016/j.envres.2023.116393] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/22/2023] [Accepted: 06/09/2023] [Indexed: 06/14/2023]
Abstract
This study aims to investigate the independent and interactive effects of greenness and ambient pollutants on novel glycolipid metabolism biomarkers. A repeated national cohort study was conducted among 5085 adults from 150 counties/districts across China, with levels of novel glycolipid metabolism biomarkers of TyG index, TG/HDL-c, TC/HDL-c, and non-HDL-c measured. Exposure levels of greenness and ambient pollutants (including PM1, PM2.5, PM10, and NO2) for each participant were determined based on their residential location. Linear mixed-effect and interactive models were used to evaluate the independent and interactive effects between greenness and ambient pollutants on the four novel glycolipid metabolism biomarkers. In the main models, the changes [β (95% CIs)] of TyG index, TG/HDL-c, TC/HDL-c, and non-HDL-c were -0.021 (-0.036, -0.007), -0.120 (-0.175, -0.066), -0.092 (-0.122, -0.062), and -0.445 (-1.370, 0.480) for every 0.1 increase in NDVI, and were 0.004 (0.003, 0.005), 0.014 (0.009, 0.019), 0.009 (0.006, 0.011), and 0.067 (-0.019, 0.154) for every 1 μg/m3 increase in PM1. Results of interactive analyses demonstrated that individuals living in low-polluted areas could get greater benefits from greenness than those living in highly-polluted areas. Additionally, the results of mediation analyses revealed that PM2.5 mediated 14.40% of the association between greenness and the TyG index. Further research is needed to validate our findings.
Collapse
Affiliation(s)
- Mengnan Pan
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Feifei Liu
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Ke Zhang
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Zhongyang Chen
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Jiahui Tong
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Xiangxiang Wang
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Feng Zhou
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Hao Xiang
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China.
| |
Collapse
|
13
|
Wei N, Wang S, Li X, Pan R, Yi W, Song J, Liu L, Liu J, Yuan J, Song R, Cheng J, Su H. The association between greenery type and gut microbiome in schizophrenia: did all greenspaces play the equivalent role? ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:100006-100017. [PMID: 37624502 DOI: 10.1007/s11356-023-29419-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 08/17/2023] [Indexed: 08/26/2023]
Abstract
In recent years, attention has been focused on the benefit of greenspace on mental health, and it is suggested this link may vary with the type of greenspace. More and more studies have emphasized the influence of the gut microbiome on schizophrenia (SCZ). However, the effects of greenspaces on the gut microbiota in SCZ and the effect of different types of greenspaces on the gut microbiota remain unclear. We aim to examine if there were variations in the effects of various greenspace types on the gut microbiome in SCZ. Besides, we sink to explore important taxonomic compositions associated with different greenspace types. We recruited 243 objects with schizophrenia from Anhui Mental Health Center and collected fecal samples for 16Sr RNA gene sequencing. Three types of greenery coverage were calculated with different circular buffers (800, 1500, and 3000 m) corresponding to individual addresses. The association between greenspace and microbiome composition was analyzed with permutational analysis of variance (PERMANOVA). We conducted the linear regression to capture specific gut microbiome taxa associated with greenery coverage. Tree coverage was consistently associated with microbial composition in both 1500 m (R2 = 0.007, P = 0.030) and 3000 m (R2 = 0.007, P = 0.039). In contrast, there was no association with grass cover in any of the buffer zones. In the regression analysis, higher tree coverage was significantly correlated with the relative abundance of several taxa. Among them, tree coverage was positively associated with increased Bifidobacterium longum (β = 1.069, P = 0.004), which was the dominant composition in the gut microbiota. The relationship between greenspace and gut microbiome in SCZ differed by the type of greenspace. Besides, "tree coverage" may present a dominant effect on the important taxonomic composition. Our findings might provide instructive evidence for the design of urban greenspace to optimize health and well-being in SCZ as well as the whole people.
Collapse
Affiliation(s)
- Ning Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China
| | - Shusi Wang
- Hefei Stomatological Hospital, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Xuanxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China
| | - Li Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China
| | - Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China
| | - Jiajun Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China
| | - Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China.
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, 230032, Anhui, China.
| |
Collapse
|
14
|
Abstract
As the world's population becomes increasingly urbanized, there is growing concern about the impact of urban environments on cardiovascular health. Urban residents are exposed to a variety of adverse environmental exposures throughout their lives, including air pollution, built environment, and lack of green space, which may contribute to the development of early cardiovascular disease and related risk factors. While epidemiological studies have examined the role of a few environmental factors with early cardiovascular disease, the relationship with the broader environment remains poorly defined. In this article, we provide a brief overview of studies that have examined the impact of the environment including the built physical environment, discuss current challenges in the field, and suggest potential directions for future research. Additionally, we highlight the clinical implications of these findings and propose multilevel interventions to promote cardiovascular health among children and young adults.
Collapse
Affiliation(s)
- Kai Zhang
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA
| | - Robert D Brook
- Division of Cardiovascular Diseases, Department of Internal Medicine, Wayne State University, Detroit, MI, USA
| | - Yuanfei Li
- Department of Sociology, University at Albany, State University of New York, Albany, NY, USA
| | - Sanjay Rajagopalan
- Cardiovascular Research Institute, University Hospitals Harrington Heart and Vascular Institute, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Juyong Brian Kim
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA; Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
| |
Collapse
|
15
|
Zhang Y, Chen S, Chen L, Wu Y, Wei J, Ma T, Chen M, Ma Q, Liu J, Wang X, Xing Y, Wu L, Li W, Liu X, Guo X, Ma J, Dong Y, Zhang J. Association of SO 2/CO exposure and greenness with high blood pressure in children and adolescents: A longitudinal study in China. Front Public Health 2023; 11:1097510. [PMID: 37304113 PMCID: PMC10248062 DOI: 10.3389/fpubh.2023.1097510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 02/06/2023] [Indexed: 06/13/2023] Open
Abstract
Introduction We aimed to investigate the association between greenness around schools, long-term gaseous air pollution exposure (SO2 and CO), and blood pressure in children and adolescents. Methods From 2006 to 2018, a total of 219,956 Chinese children and adolescents aged 7-17 years in Beijing and Zhongshan were included in this longitudinal study. Annual average concentrations of SO2 and CO and the mean values of normalized difference vegetation index around schools were calculated. We used the generalized estimation equation model, restricted cubic spline model, and Cox model to analyze the health effects. Results Among all the subjects, 52,515 had the first onset of HBP. During the follow-up, HBP's cumulative incidence and incidence density were 23.88% and 7.72 per 100 person-year respectively. Exposures to SO2 and CO were significantly associated with SBP [β = 1.30, 95% CI: (1.26, 1.34) and 0.78 (0.75, 0.81)], DBP [β = 0.81 (0.79, 0.84) and 0.46 (0.44, 0.48)] and HBP [HR = 1.58 (1.57, 1.60) and 1.42 (1.41, 1.43)]. The risks of HBP attributed to SO2 and CO pollution would be higher in school-aged children in the low greenness group: the attributable fractions (AFs) were 26.31% and 20.04%, but only 13.90% and 17.81% in the higher greenness group. The AFs were also higher for normal-BMI children and adolescents in the low greenness group (AFs = 30.90% and 22.64%, but 14.41% and 18.65% in the high greenness group), while the AFs were not as high as expected for obese children in the low greenness group (AFs = 10.64% and 8.61%), nor was it significantly lower in the high greenness group (AFs = 9.60% and 10.72%). Discussion Greenness could alleviate the damage effects of SO2/CO exposure on the risks of HBP among children and adolescents, and the benefit is BMI sensitivity. It might offer insights for policymakers in making effective official interventions to prevent and control the prevalence of childhood HBP and the future disease burden caused by air pollution.
Collapse
Affiliation(s)
- Yi Zhang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, National Health Commission Key Laboratory of Reproductive Health, Beijing, China
| | - Shuo Chen
- Beijing Physical Examination Center, Beijing, China
| | - Li Chen
- Institute of Child and Adolescent Health, School of Public Health, Peking University, National Health Commission Key Laboratory of Reproductive Health, Beijing, China
| | - Yu Wu
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States
| | - Tao Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, National Health Commission Key Laboratory of Reproductive Health, Beijing, China
| | - Manman Chen
- Institute of Child and Adolescent Health, School of Public Health, Peking University, National Health Commission Key Laboratory of Reproductive Health, Beijing, China
| | - Qi Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, National Health Commission Key Laboratory of Reproductive Health, Beijing, China
| | - Jieyu Liu
- Institute of Child and Adolescent Health, School of Public Health, Peking University, National Health Commission Key Laboratory of Reproductive Health, Beijing, China
| | - Xinxin Wang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, China
| | - Yi Xing
- Institute of Child and Adolescent Health, School of Public Health, Peking University, National Health Commission Key Laboratory of Reproductive Health, Beijing, China
| | - Lijuan Wu
- Department of Epidemiology and Health Statistics, Capital Medical University School of Public Health, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Weiming Li
- Department of Epidemiology and Health Statistics, Capital Medical University School of Public Health, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Xiangtong Liu
- Department of Epidemiology and Health Statistics, Capital Medical University School of Public Health, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Xiuhua Guo
- Department of Epidemiology and Health Statistics, Capital Medical University School of Public Health, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, National Health Commission Key Laboratory of Reproductive Health, Beijing, China
| | - Yanhui Dong
- Institute of Child and Adolescent Health, School of Public Health, Peking University, National Health Commission Key Laboratory of Reproductive Health, Beijing, China
| | - Jingbo Zhang
- Beijing Physical Examination Center, Beijing, China
| |
Collapse
|
16
|
Liu Y, Li Y, Xu H, Zhao X, Zhu Y, Zhao B, Yao Q, Duan H, Guo C, Li Y. Pre- and postnatal particulate matter exposure and blood pressure in children and adolescents: A systematic review and meta-analysis. ENVIRONMENTAL RESEARCH 2023; 223:115373. [PMID: 36731599 DOI: 10.1016/j.envres.2023.115373] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 01/10/2023] [Accepted: 01/25/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Early life is a susceptible period of air pollution-related adverse health effects. Hypertension in children might be life-threatening without prevention or treatment. Nevertheless, the causative association between environmental factors and childhood hypertension was limited. In the light of particulate matter (PM) as an environmental risk factor for cardiovascular diseases, this study investigated the association of pre- and postnatal PM exposure with blood pressure (BP) and hypertension among children and adolescents. METHOD Four electronic databases were searched for related epidemiological studies published up to September 13, 2022. Stata 14.0 was applied to examine the heterogeneity among the studies and evaluate the combined effect sizes per 10 μg/m3 increase of PM by selecting the corresponding models. Besides, subgroup analysis, sensitivity analysis, and publication bias test were also conducted. RESULTS Prenatal PM2.5 exposure was correlated with increased diastolic blood pressure (DBP) in offspring [1.14 mmHg (95% CI: 0.12, 2.17)]. For short-term postnatal exposure effects, PM2.5 (7-day average) was significantly associated with systolic blood pressure (SBP) [0.20 mmHg (95% CI: 0.16, 0.23)] and DBP [0.49 mmHg (95% CI: 0.45, 0.53)]; and also, PM10 (7-day average) was significantly associated with SBP [0.14 mmHg (95% CI: 0.12, 0.16)]. For long-term postnatal exposure effects, positive associations were manifested in SBP with PM2.5 [β = 0.44, 95% CI: 0.40, 0.48] and PM10 [β = 0.35, 95% CI: 0.19, 0.51]; DBP with PM1 [β = 0.45, 95% CI: 0.42, 0.49], PM2.5 [β = 0.31, 95% CI: 0.27, 0.35] and PM10 [β = 0.32, 95% CI: 0.19, 0.45]; and hypertension with PM1 [OR = 1.43, 95% CI: 1.40, 1.46], PM2.5 [OR = 1.65, 95% CI: 1.29, 2.11] and PM10 [OR = 1.26, 95% CI: 1.09, 1.45]. CONCLUSION Both prenatal and postnatal exposure to PM can increase BP, contributing to a higher prevalence of hypertension in children and adolescents.
Collapse
Affiliation(s)
- Yufan Liu
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, China
| | - Yan Li
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, China; Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
| | - Hailin Xu
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, China
| | - Xinying Zhao
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, China
| | - Yawen Zhu
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, China; Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China
| | - Bosen Zhao
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, China
| | - Qing Yao
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, China
| | - Huawei Duan
- Key Laboratory of Chemical Safety and Health, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Caixia Guo
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, China; Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, China.
| | - Yanbo Li
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, China.
| |
Collapse
|
17
|
Yu Z, Feng Y, Chen Y, Zhang X, Zhao X, Chang H, Zhang J, Gao Z, Zhang H, Huang C. Green space, air pollution and gestational diabetes mellitus: A retrospective cohort study in central China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 249:114457. [PMID: 38321676 DOI: 10.1016/j.ecoenv.2022.114457] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/08/2022] [Accepted: 12/19/2022] [Indexed: 02/08/2024]
Abstract
Emerging evidence suggests residential surrounding green space is beneficial for human health. The association between green space and GDM showed inconsistent results, and potential effect modification of green space with air pollution is still unclear. This study aims to evaluate the association between green space and GDM, and further explore potential interaction and medication effects. Participants were recruited from a retrospective cohort study between 2015 and 2020 in Henan, China. Residential green space based on normalized difference vegetation index (NDVI) and air pollution exposure were estimated using spatial-statistical models. Multivariate logistic regression was applied to evaluate the association between per 0.1 unit increase in NDVI with 4 buffer sizes (250 m, 500 m, 1000 m, 2000 m) and GDM. We examined potential interaction of green space and air pollutants on GDM. Mediating effects of air pollution associated with green space exposure on GDM were also investigated by causal mediation analyses. A total of 46,665 eligible pregnant women were identified. There were 4092 (8.8 %) women diagnosed with GDM according to the IADPSG criteria. We found that per 0.1-unit increment in NDVI250 m, NDVI500 m, NDVI1000 m and NDVI2000 m in second trimester were associated with the decreased risk of GDM, with adjusted OR of 0.921(95 %CI: 0.890-0.953), 0.922 (95 %CI: 0.891-0.953), 0.921 (95 %CI: 0.892-0.952) and 0.921 (95 %CI: 0.892-0.951), respectively. We identified significant interactions between second trimester PM2.5 and O3 exposure and NDVI for GDM (Pinteraction < 0.001). The causal mediation analysis showed that PM2.5 mediated approximately 2.5-5.5 % of the association between green space and GDM, while the estimated mediating effect of O3 was approximately 30.1-38.5 %. In conclusion, our study indicates that residential green space was associated with a reduced risk of GDM, particularly second trimester. Green space may benefit to GDM partly mediated by a reduction in PM2.5 and O3.
Collapse
Affiliation(s)
- Zengli Yu
- School of Public Health, Zhengzhou University, Zhengzhou, China; NHC Key Laboratory of Birth Defects Prevention & Henan Key Laboratory of Population Defects Prevention, Zhengzhou, China
| | - Yang Feng
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yao Chen
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoan Zhang
- The Third Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- The Third Hospital of Zhengzhou University, Zhengzhou, China
| | - Hui Chang
- The Third Hospital of Zhengzhou University, Zhengzhou, China
| | - Junxi Zhang
- NHC Key Laboratory of Birth Defects Prevention & Henan Key Laboratory of Population Defects Prevention, Zhengzhou, China
| | - Zhan Gao
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huanhuan Zhang
- School of Public Health, Zhengzhou University, Zhengzhou, China.
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| |
Collapse
|
18
|
Ye T, Yu P, Wen B, Yang Z, Huang W, Guo Y, Abramson MJ, Li S. Greenspace and health outcomes in children and adolescents: A systematic review. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 314:120193. [PMID: 36122655 DOI: 10.1016/j.envpol.2022.120193] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 09/04/2022] [Accepted: 09/13/2022] [Indexed: 06/15/2023]
Abstract
An increasing body of evidence has linked greenspace and various health outcomes in children and adolescents, but the conclusions were inconsistent. For this review, we comprehensively summarized the measurement methods of greenspace, resultant health outcomes, and potential mechanisms from epidemiological studies in children and adolescents (aged ≤19 years). We searched for studies published and indexed in MEDLINE and EMBASE (via Ovid) up to April 11, 2022. There were a total of 9,291 studies identified with 140 articles from 28 countries finally assessed and included in this systematic review. Over 70% of the studies were conducted in highly urbanised countries/regions, but very limited research has been done in low-and middle-income countries and none in Africa. Measures of greenspace varied. Various health outcomes were reported, including protective effects of greenspace exposure on aspects of obesity/overweight, myopia, lung health, circulatory health, cognitive function, and general health in children and adolescents. The associations between greenspace exposure and other health outcomes were inconsistent, especially for respiratory health studies. We pooled odds ratios (OR) using random-effects meta-analysis for health outcomes of asthma (OR = 0.94, 95%CI: 0.84 to 1.06), allergic rhinitis (OR = 0.95; 95% CI: 0.73 to 1.25), and obesity/overweight (OR = 0.91, 95%CI: 0.84 to 0.98) with per 0.1 unit increase in normalized difference in vegetation index (NDVI). These associations have important implications for the assessment and management of urban environment and health in children and adolescents.
Collapse
Affiliation(s)
- Tingting Ye
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Pei Yu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Bo Wen
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Zhengyu Yang
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Wenzhong Huang
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Michael J Abramson
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Shanshan Li
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
| |
Collapse
|
19
|
Xu YX, Zhou Y, Huang Y, Yu Y, Li JY, Huang WJ, Wan YH, Tao FB, Sun Y. Physical activity alleviates negative effects of bedroom light pollution on blood pressure and hypertension in Chinese young adults. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 313:120117. [PMID: 36087897 DOI: 10.1016/j.envpol.2022.120117] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 08/08/2022] [Accepted: 09/02/2022] [Indexed: 06/15/2023]
Abstract
Excessive exposure to light at night (LAN) has become a serious public health concern. However, little is known about the impact of indoor LAN exposure on blood pressure, particularly among young adults. We aimed to investigate the effects of bedroom individual-level LAN exposure in real-world environment on blood pressure and hypertension among vulnerable young adults, and to evaluate the possible buffering effect of physical activity. In this cross-sectional study, a total of 400 healthy young adults aged 16-22 years were included. Bedroom LAN exposure was recorded at 1-min intervals for two consecutive nights using a TES-1339 R illuminance meter. Blood pressure was measured three times (8-11 a.m. in the physical examination day) in the seated position using an Omron HEM-7121 digital sphygmomanometer. A wrist-worn triaxial accelerometer (ActiGraph GT3X-BT) was used to assess physical activity for seven consecutive days. Each 1 lx increase of bedroom LAN intensity was associated with 0.55 mmHg-increase in SBP (95% CI: 0.15, 0.95), 0.30 mmHg-increase in DBP (95% CI: 0.06, 0.54), and 0.38 mmHg-increase in MAP (95% CI: 0.12, 0.65). Higher levels of LAN exposure were associated with increased risk of hypertension (LAN ≥ 3lx vs. LAN < 3lx: OR = 3.30, 95%CI = 1.19-9.19; LAN ≥ 5lx vs. LAN < 5lx: OR = 3.87, 95%CI = 1.37-10.98). However, these detrimental effects of bedroom LAN exposure on blood pressure and hypertension were not observed among young adults with high MVPA (≥2 h/day) level. MVPA can alleviate negative effects of bedroom LAN exposure on blood pressure and hypertension. Maintaining bedroom settings darkness at night may be an important strategy for reducing the risk of hypertension. Furthermore, for individuals living with high levels of indoor LAN exposure, regular physical activity may be a good option for preventing cardiovascular disease and hypertension.
Collapse
Affiliation(s)
- Yu-Xiang Xu
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Yi Zhou
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Yan Huang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Yang Yu
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Jing-Ya Li
- School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Wen-Juan Huang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Yu-Hui Wan
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Fang-Biao Tao
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Ying Sun
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
| |
Collapse
|
20
|
Chien JW, Wu C, Chan CC. The association of hypertension and prehypertension with greenness and PM 2.5 in urban environment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 821:153526. [PMID: 35101513 DOI: 10.1016/j.scitotenv.2022.153526] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 01/23/2022] [Accepted: 01/25/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND The interplay of air pollution and urban greenness on hypertension (HTN) is not fully understood. METHODS We conducted a cross-sectional study to explore the role of greenness and PM2.5 on HTN for 40,375 adult residents in the New Taipei City, Taiwan. Normalized Difference Vegetation Index (NDVI) defined greenness and land use regression derived exposures of PM2.5 were used to calculate odds ratios (ORs) of HTN in logistic regression models and common OR of normal to stage 3 HTN in ordinal logistic regression models. Linear regression model was used to evaluate the association between NDVI and blood pressures, including systolic (SBP), diastolic (DBP) and mean (MBP) pressures. The mediation and moderation analysis were used to assess the mediation and moderation effect of PM2.5 on the association between greenness and SBP. RESULTS We found 37.3%, 21.4%, 8.2% and 2.7% of prehypertension and stage 1-3 hypertensions, respectively, for our study participants with annual PM2.5 exposures of 10.96-43.59 μg/m3 living in an urban environment with NDVI within 500 m buffer ranging from -0.22 to 0.26. The ORs of HTN were 0.744 (95% CI: 0.698-0.793) for NDVI (quartile 4 vs. quartile 1) and 1.048 (1.012-1.085) for each IQR (8.69 μg/m3) increase in PM2.5, respectively. The common OR of the higher level of 5 categories of BP was 1.1310 (1.241-1.383). With each IQR increase of NDVI (0.03), we found SBP, DBP and MBP were decreased by 0.78 mm Hg (-0.93-0.64), 0.52 mm Hg (-0.62-0.43) and 0.61 mm Hg (-0.71-0.51), respectively, in linear regression models. Stratified analysis found greenness effect was more prominent for people who are younger, female, never smoking, and without chronic diseases. PM2.5 is moderated rather than mediated the association between greenness and SBP. CONCLUSIONS Greenness was associated with lower prevalence of prehypertension and all stages of HTN and this relationship was moderated by PM2.5.
Collapse
Affiliation(s)
- Jien-Wen Chien
- Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan; Department of Pediatric Nephrology, Changhua Christian Children's Hospital, Changhua, Taiwan; Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taiwan
| | - Charlene Wu
- Global Health Program, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Chang-Chuan Chan
- Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan; Innovation and Policy Center for Population Health and Sustainable Environment (Population Health Research Center, PHRC), College of Public Health, National Taiwan University, Taipei, Taiwan.
| |
Collapse
|