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Li X, Wang Q, Feng C, Yu B, Lin X, Fu Y, Dong S, Qiu G, Jin Aik DH, Yin Y, Xia P, Huang S, Liu N, Lin X, Zhang Y, Fang X, Zhong W, Jia P, Yang S. Associations and pathways between residential greenness and metabolic syndromes in Fujian Province. Front Public Health 2022; 10:1014380. [PMID: 36620251 PMCID: PMC9815145 DOI: 10.3389/fpubh.2022.1014380] [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: 08/08/2022] [Accepted: 11/22/2022] [Indexed: 12/24/2022] Open
Abstract
Background Greenness exposure is beneficial to human health, but its potential mechanisms through which the risk for metabolic syndrome (MetS) could be reduced have been poorly studied. We aimed to estimate the greenness-MetS association in southeast China and investigate the independent and joint mediation effects of physical activity (PA), body mass index (BMI), and air pollutants on the association. Methods A cross-sectional study was conducted among the 38,288 adults based on the Fujian Behavior and Disease Surveillance (FBDS), established in 2018. MetS was defined as the presence of three or more of the five components: abdominal obesity, elevated triglyceride, reduced high-density lipoprotein cholesterol (HDL-C), high blood pressure, and elevated fasting glucose. The residential greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 250, 500, and 1,000 meters (m) buffer zones around the residential address of each participant. Logistic regression models were used to estimate the greenness-MetS association. The causal mediation analysis was used to estimate the independent and joint mediation effects of PA, BMI, particulate matter with an aerodynamic diameter of 2.5 μm (PM2.5), particulate matter with an aerodynamic diameter ≤ 10 μm (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2). Results Each interquartile range (IQR) increase in greenness was associated with a decrease of 13% (OR = 0.87 [95%CI: 0.83, 0.92] for NDVI500m and OR = 0.87 [95%CI: 0.82, 0.91] for EVI500m) in MetS risk after adjusting for covariates. This association was stronger in those aged < 60 years (e.g., OR = 0.86 [95%CI: 0.81, 0.92] for NDVI500m), males (e.g., OR = 0.73 [95%CI: 0.67, 0.80] for NDVI500m), having an educational level of primary school or above (OR = 0.81 [95%CI: 0.74, 0.89] for NDVI500m), married/cohabitation (OR = 0.86 [95%CI: 0.81, 0.91] for NDVI500m), businessman (OR = 0.82 [95%CI: 0.68, 0.99] for NDVI500m), other laborers (OR = 0.77 [95%CI: 0.68, 0.88] for NDVI500m), and non-smokers (OR = 0.77 [95%CI: 0.70, 0.85] for NDVI500m). The joint effect of all six mediators mediated about 48.1% and 44.6% of the total effect of NDVI500m and EVI500m on the MetS risk, respectively. Among them, BMI showed the strongest independent mediation effect (25.0% for NDVI500m), followed by NO2 and PM10. Conclusion Exposure to residential greenness was associated with a decreased risk for MetS. PA, BMI, and the four air pollutants jointly interpreted nearly half of the mediation effects on the greenness-MetS association.
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Affiliation(s)
- Xiaoqing Li
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Qinjian Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chuanteng Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China,Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China
| | - Bin Yu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China,Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, China
| | - Xi Lin
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Yao Fu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Shu Dong
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ge Qiu
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China,International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Darren How Jin Aik
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China,International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Yanrong Yin
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Pincang Xia
- Department for HIV/AIDS and STDs Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Shaofen Huang
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Nian Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xiuquan Lin
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Yefa Zhang
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Xin Fang
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Wenling Zhong
- Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China,*Correspondence: Wenling Zhong
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China,International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China,Peng Jia
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China,International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China,Shujuan Yang
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Coelho PRS, Ker FTO, Araújo AD, Guimarães RJPS, Negrão-Corrêa DA, Caldeira RL, Geiger SM. Identification of Risk Areas for Intestinal Schistosomiasis, Based on Malacological and Environmental Data and on Reported Human Cases. Front Med (Lausanne) 2021; 8:642348. [PMID: 34422845 PMCID: PMC8377395 DOI: 10.3389/fmed.2021.642348] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 07/14/2021] [Indexed: 11/13/2022] Open
Abstract
The aim of the present study was to use an integrated approach for the identification of risk areas for Schistosoma mansoni transmission in an area of low endemicity in Minas Gerais, Brazil. For that, areas of distribution of Biomphalaria glabrata were identified and were related to environmental variables and communities with reported schistosomiasis cases, in order to determine the risk of infection by spatial analyses with predictive models. The research was carried out in the municipality of Alvorada de Minas, with data obtained between the years 2017 and 2019 inclusive. The Google Earth Engine was used to obtain geo-climatic variables (temperature, precipitation, vegetation index and digital elevation model), R software to determine Pearson's correlation and MaxEnt software to obtain an ecological model. ArcGis Software was used to create maps with data spatialization and risk maps, using buffer models (diameters: 500, 1,000 and 1,500 m) and CoKriging. Throughout the municipality, 46 collection points were evaluated. Of these, 14 presented snails of the genus Biomphalaria. Molecular analyses identified the presence of different species of Biomphalaria, including B. glabrata. None of the snails eliminated S. mansoni cercariae. The distribution of B. glabrata was more abundant in areas of natural vegetation (forest and cerrado) and, for spatial analysis (Buffer), the main risk areas were identified especially in the main urban area and toward the northern and eastern extensions of the municipality. The distribution of snails correlated with temperature and precipitation, with the latter being the main variable for the ecological model. In addition, the integration of data from malacological surveys, environmental characterization, fecal contamination, and data from communities with confirmed human cases, revealed areas of potential risk for infection in the northern and eastern regions of the municipality. In the present study, information was integrated on epidemiological aspects, transmission and risk areas for schistosomiasis in a small, rural municipality with low endemicity. Such integrated methods have been proposed as important tools for the creation of schistosomiasis transmission risk maps, serve as an example for other communities and can be used for control actions by local health authorities, e.g., indicate priority sectors for sanitation measures.
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Affiliation(s)
- Paulo R S Coelho
- Department for Parasitology, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Fabrício T O Ker
- Department for Parasitology, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Amanda D Araújo
- Oswaldo Cruz Foundation (Fiocruz), Research Group on Helminthology and Medical Malacology, René Rachou Institute, Belo Horizonte, Brazil
| | | | | | - Roberta L Caldeira
- Oswaldo Cruz Foundation (Fiocruz), Research Group on Helminthology and Medical Malacology, René Rachou Institute, Belo Horizonte, Brazil
| | - Stefan M Geiger
- Department for Parasitology, Federal University of Minas Gerais, Belo Horizonte, Brazil
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Di N, Li S, Xiang H, Xie Y, Mao Z, Hou J, Liu X, Huo W, Yang B, Dong G, Wang C, Chen G, Guo Y. Associations of Residential Greenness with Depression and Anxiety in Rural Chinese Adults. Innovation (N Y) 2020; 1:100054. [PMID: 34557719 PMCID: PMC8454668 DOI: 10.1016/j.xinn.2020.100054] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 10/29/2020] [Indexed: 12/27/2022] Open
Abstract
Background Depression and anxiety are top contributors to non-fatal health loss globally. Several studies have indicated the association between residential greenness and mental health. Method The participants (n = 27,366) were recruited from four counties in Henan Province, China during 2015–2017. Symptoms of depression and anxiety were evaluated using the Patient Health Questionnaire-2 (PHQ-2) and the Generalized Anxiety Disorder-2 (GAD-2) in the baseline survey. The level of residential greenness during the 3-year period before the baseline survey was assessed using the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The mixed-effect linear regression model was applied to examine the associations of residential greenness with depression and anxiety. Results The results of adjusted models showed that the score of PHQ-2 (Δscore and 95% confidence interval [CI]) decreased by −0.024 (−0.041, −0.006) and −0.022 (−0.038, −0.004) with an interquartile range (IQR) increase in NDVI and EVI within a 1,000-m buffer radius, respectively. The score of GAD-2 (Δscore and 95% CI) decreased by −0.024 (−0.040, −0.006) and −0.028 (−0.044, −0.011), in relation to an IQR increase in NDVI and EVI within a 1,000-m buffer radius, respectively. Conclusions A higher level of residential greenness was significantly associated with lower risk of depression and anxiety in rural areas of Henan Province. Improving residential greenness accessibility may help to promote the mental health of rural populations. Mental disorders, particularly depression and anxiety, have become one of the most serious public health issues globally. Symptoms of depression and anxiety and level of residential greenness were investigated for 27,366 participants from the Henan Rural Cohort. The mixed effect linear regression model was used to examine the associations between level of residential greenness and depression and anxiety in rural areas of Henan Province, China. Higher residential greenness was significantly associated with lower risks of depression and anxiety. Stronger effects of residential greenness were observed in males and in those with higher income and education level.
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Affiliation(s)
- Niu Di
- Global Health Institute; Department of Global Health, School of Health Sciences, Wuhan University, Wuhan 430071, Hubei, China
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Hao Xiang
- Global Health Institute; Department of Global Health, School of Health Sciences, Wuhan University, Wuhan 430071, Hubei, China
| | - Yinyu Xie
- Global Health Institute; Department of Global Health, School of Health Sciences, Wuhan University, Wuhan 430071, Hubei, China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Boyi 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, 74 Zhongshan 2 Road, Yuexiu District, Guangzhou 510080, Guangdong, China
| | - Guanghui 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, 74 Zhongshan 2 Road, Yuexiu District, Guangzhou 510080, Guangdong, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou 450001, Henan, China
| | - Gongbo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment; Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2 Road, Yuexiu District, Guangzhou 510080, Guangdong, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
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Scholte RG, Gosoniu L, Malone JB, Chammartin F, Utzinger J, Vounatsou P. Predictive risk mapping of schistosomiasis in Brazil using Bayesian geostatistical models. Acta Trop 2014; 132:57-63. [PMID: 24361640 DOI: 10.1016/j.actatropica.2013.12.007] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2012] [Revised: 10/16/2013] [Accepted: 12/08/2013] [Indexed: 11/24/2022]
Abstract
Schistosomiasis is one of the most common parasitic diseases in tropical and subtropical areas, including Brazil. A national control programme was initiated in Brazil in the mid-1970s and proved successful in terms of morbidity control, as the number of cases with hepato-splenic involvement was reduced significantly. To consolidate control and move towards elimination, there is a need for reliable maps on the spatial distribution of schistosomiasis, so that interventions can target communities at highest risk. The purpose of this study was to map the distribution of Schistosoma mansoni in Brazil. We utilized readily available prevalence data from the national schistosomiasis control programme for the years 2005-2009, derived remotely sensed climatic and environmental data and obtained socioeconomic data from various sources. Data were collated into a geographical information system and Bayesian geostatistical models were developed. Model-based maps identified important risk factors related to the transmission of S. mansoni and confirmed that environmental variables are closely associated with indices of poverty. Our smoothed predictive risk map, including uncertainty, highlights priority areas for intervention, namely the northern parts of North and Southeast regions and the eastern part of Northeast region. Our predictive risk map provides a useful tool for to strengthen existing surveillance-response mechanisms.
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Scholte RG, Freitas CC, Dutra LV, Guimaraes RJ, Drummond SC, Oliveira G, Carvalho OS. Utilizing environmental, socioeconomic data and GIS techniques to estimate the risk for ascariasis and trichuriasis in Minas Gerais, Brazil. Acta Trop 2012; 121:112-7. [PMID: 22041638 DOI: 10.1016/j.actatropica.2011.10.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2011] [Revised: 10/11/2011] [Accepted: 10/15/2011] [Indexed: 10/16/2022]
Abstract
The impact of intestinal helminths on human health is well known among the population and health authorities because of their wide geographic distribution and the serious problems they cause. Geohelminths are highly prevalent and have a big impact on public health, mainly in underdeveloped and developing countries. Geohelminths are responsible for the high levels of debility found in the younger population and are often related to cases of chronic diarrhea and malnutrition, which put the physical and intellectual development of children at risk. These geohelminths have not been sufficiently studied. One obstacle in implementing a control program is the lack of knowledge of the prevalence and geographical distribution. Geographical information systems (GIS) and remote sensing (RS) have been utilized to improve understanding of infectious disease distribution and climatic patterns. In this study, GIS and RS technologies, as well as meteorological, social, and environmental variables were utilized for the modeling and prediction of ascariasis and trichuriasis. The GIS and RS technologies specifically used were those produced by orbital sensing including the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Shuttle Radar Topography Mission (SRTM). The results of this study demonstrated important factors related to the transmission of ascariasis and trichuriasis and confirmed the key association between environmental variables and the poverty index, which enabled us to identify priority areas for intervention planning in the state of Minas Gerais in Brazil.
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