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Goudarzi G, Hopke PK, Yazdani M. Forecasting PM 2.5 concentration using artificial neural network and its health effects in Ahvaz, Iran. CHEMOSPHERE 2021; 283:131285. [PMID: 34182649 DOI: 10.1016/j.chemosphere.2021.131285] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 06/13/2021] [Accepted: 06/17/2021] [Indexed: 05/28/2023]
Abstract
The main objective of the present study was to predict the associated health endpoint of PM2.5 using an artificial neural network (ANN). The neural network used in this work contains a hidden layer with 27 neurons, an input layer with 8 parameters, and an output layer. First, the artificial neural network was implemented with 80% of data for training then with 90% of data for training. The value of R for the data validation of these two networks was 0.80 and 0.83 respectively. The World Health Organization AirQ + software was utilized for assessing Health effects of PM2.5 levels. The mean PM2.5 over the 9-year study period was 63.27(μg/m3), about six times higher than the WHO guideline. However, the PM2.5 concentration in the last year decreased by about 25% compared to the first year, which is statistically significant (P-value = 0.0048). This reduced pollutant concentration led to a decrease in the number of deaths from 1785 in 2008 to 1059 in 2016. Moreover, a positive correlation was found between PM2.5 concentration and temperature and wind speed. Considering the importance of predicting PM2.5 concentration for accurate and timely decisions as well as the accuracy of the artificial neural network used in this study, the artificial neural network can be utilized as an effective instrument to reduce health and economic effects.
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Affiliation(s)
- Gholamreza Goudarzi
- Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Environmental Technologies Research Center (ETRC), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Philip K Hopke
- Center for Air Resources Engineering and Science, Clarkson University, Potsdam, NY, USA; Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Mohsen Yazdani
- Department of Environmental Health Engineering, School of Public Health, Student Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
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52
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Zang ST, Luan J, Li L, Wu QJ, Chang Q, Dai HX, Zhao YH. Air pollution and metabolic syndrome risk: Evidence from nine observational studies. ENVIRONMENTAL RESEARCH 2021; 202:111546. [PMID: 34265350 DOI: 10.1016/j.envres.2021.111546] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 06/05/2021] [Accepted: 06/15/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND AIMS Globally, the number of metabolic syndrome (MetS) cases has increased substantially over time. However, the association between air pollution (AP) and MetS risk has been contradictory in observational studies. This is the first reported meta-analysis quantitatively exploring the aforementioned association. METHODS We searched PubMed, Embase, and Web of Science database entries up to September 14, 2020, and searches were updated up to December 6, 2020 to identify eligible articles on the AP-MetS risk association. No language restriction was imposed. Random-effects models were applied to estimate summary and subgroup effect sizes with 95% confidence intervals (CIs). PROSPERO registration number: CRD42020210431. RESULTS Eight articles (nine studies) were eligible for the meta-analysis. Increased MetS prevalence was not found to be associated with particulate matter less than 1 μm (PM1), 2.5 μm (PM2.5), and 10 μm (PM10) in diameter or nitrogen dioxide (NO2), and the summary effect sizes were 1.33 (95% CI: 0.95-1.85), 1.34 (95% CI: 0.96-1.89), 1.18 (95% CI: 0.98-1.19), and 1.28 (95% CI: 0.89-1.82), respectively, based on cross-sectional studies. The summary results indicated no association between each 10 μg/m3 increase in PM2.5 and MetS incidence (effect size 2.78 [95% CI: 0.70-11.02]), based on cohort studies. Subgroup analysis demonstrated that MetS incidence in older men increased dramatically by 992% with each 10 μg/m3 increase in PM2.5. CONCLUSIONS The evidence presented here suggests that although exposure to PM1, PM2.5, PM10, or NO2 was not found to have a significant association with the occurrence of MetS, the statistical significance of the relationship between exposure to PM1, PM2.5, or PM10 and MetS prevalence was approximately borderline. More studies on AP-MetS risk association in low-/middle-income countries, as well as on the association between other air pollutants and MetS risk, are warranted. A sufficient number of high-quality studies is required to perform a meaningful meta-analysis of the relationship between air pollutants and MetS.
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Affiliation(s)
- Si-Tian Zang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China; Clinical Research Center, Shengjing Hospital of China Medical University, No. 39 Huaxiang Road, Tiexi District, Shenyang, Liaoning, 110022, China.
| | - Jie Luan
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China; Clinical Research Center, Shengjing Hospital of China Medical University, No. 39 Huaxiang Road, Tiexi District, Shenyang, Liaoning, 110022, China.
| | - Ling Li
- Center for Precision Medicine Research and Training, University of Macau, Avenida da Universidade Taipa, Macau, 999078, China.
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China; Clinical Research Center, Shengjing Hospital of China Medical University, No. 39 Huaxiang Road, Tiexi District, Shenyang, Liaoning, 110022, China.
| | - Qing Chang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China; Clinical Research Center, Shengjing Hospital of China Medical University, No. 39 Huaxiang Road, Tiexi District, Shenyang, Liaoning, 110022, China.
| | - Hui-Xu Dai
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China; Clinical Research Center, Shengjing Hospital of China Medical University, No. 39 Huaxiang Road, Tiexi District, Shenyang, Liaoning, 110022, China.
| | - Yu-Hong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China.
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LaKind JS, Burns CJ, Pottenger LH, Naiman DQ, Goodman JE, Marchitti SA. Does ozone inhalation cause adverse metabolic effects in humans? A systematic review. Crit Rev Toxicol 2021; 51:467-508. [PMID: 34569909 DOI: 10.1080/10408444.2021.1965086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
We utilized a practical, transparent approach for systematically reviewing a chemical-specific evidence base. This approach was used for a case study of ozone inhalation exposure and adverse metabolic effects (overweight/obesity, Type 1 diabetes [T1D], Type 2 diabetes [T2D], and metabolic syndrome). We followed the basic principles of systematic review. Studies were defined as "Suitable" or "Supplemental." The evidence for Suitable studies was characterized as strong or weak. An overall causality judgment for each outcome was then determined as either causal, suggestive, insufficient, or not likely. Fifteen epidemiologic and 33 toxicologic studies were Suitable for evidence synthesis. The strength of the human evidence was weak for all outcomes. The toxicologic evidence was weak for all outcomes except two: body weight, and impaired glucose tolerance/homeostasis and fasting/baseline hyperglycemia. The combined epidemiologic and toxicologic evidence was categorized as weak for overweight/obesity, T1D, and metabolic syndrome,. The association between ozone exposure and T2D was determined to be insufficient or suggestive. The streamlined approach described in this paper is transparent and focuses on key elements. As systematic review guidelines are becoming increasingly complex, it is worth exploring the extent to which related health outcomes should be combined or kept distinct, and the merits of focusing on critical elements to select studies suitable for causal inference. We recommend that systematic review results be used to target discussions around specific research needs for advancing causal determinations.
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Affiliation(s)
- Judy S LaKind
- LaKind Associates, LLC, Catonsville, MD, USA.,Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Carol J Burns
- Burns Epidemiology Consulting, LLC, Sanford, MI, USA
| | | | - Daniel Q Naiman
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
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Xiao X, Wang R, Knibbs LD, Jalaludin B, Heinrich J, Markevych I, Gao M, Xu SL, Wu QZ, Zeng XW, Chen GB, Hu LW, Yang BY, Yu Y, Dong GH. Street view greenness is associated with lower risk of obesity in adults: Findings from the 33 Chinese community health study. ENVIRONMENTAL RESEARCH 2021; 200:111434. [PMID: 34087194 DOI: 10.1016/j.envres.2021.111434] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 05/25/2021] [Accepted: 05/26/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Urban greenness may protect against obesity, but very few studies have assessed 'street view' (SV) greenness metrics, which may better capture people's actual exposure to greenness compared to commonly-used satellite-derived metrics. We aimed to investigate these associations further in a Chinese adult study. METHODS Our analysis included 24,845 adults in the 33 Chinese Community Health Study in 2009. SV images from Tencent Map, segmented by machine learning algorithms, were used to determine the average proportion of green vegetation in SV images at community level in 800m road network buffer. Sensitivity analyses were performed with an alternative buffer size. Overall greenness was assessed as normalized difference vegetation index (NDVI) in 800 m buffer. We used predicted PM2.5 and monitored NO2 as proxies of air pollution. Body mass index (BMI), waist circumference (WC) and hip circumference (HC) were regressed on SV greenness by generalized linear mixed models, with adjustment for covariates. Mediation analyses were performed to assess the mediation effects of air pollution. RESULTS Each interquartile range (IQR = 3.6%) increase in street view greenness was associated with a 0.15 kg/m2 (95% CI: -0.22, -0.09) decrease in BMI and 0.23 cm (95% CI: -0.35, -0.11) reduction in HC, and was associated with 7% lower odds of overweight (OR = 0.93, 95% CI:0.90, 0.96) and 18% lower odds of obesity (OR = 0.82, 95% CI:0.76, 0.89). Similar effect estimation was observed compared with commonly-used NDVI measures. PM2.5 and NO2 mediated 15.5% and 6.1% of the effects of SV greenness with BMI, respectively. CONCLUSIONS Our findings suggest beneficial associations between community-level SV greenness and lower body weight in Chinese adults. The effects were observed in women but not in men. Air pollution may partially mediate the association. These findings may have implications to support efforts to promote greening in urban areas.
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Affiliation(s)
- Xiang Xiao
- Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China; Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Ruoyu Wang
- School of GeoSciences, University of Edinburgh, Edinburgh, UK
| | - Luke D Knibbs
- School of Public Health, The University of Queensland, Herston, Queensland, 4006, Australia; Centre for Air Pollution, Energy and Health Research, Glebe, NSW, 2037, Australia
| | - Bin Jalaludin
- Centre for Air Pollution, Energy and Health Research, Glebe, NSW, 2037, Australia; IIngham Institute for Applied Medial Research, University of New South Wales, Sydney, Australia
| | - Joachim Heinrich
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, Ludwig Maximilian University, Munich, 80336, Germany
| | - Iana Markevych
- Institute of Psychology, Jagiellonian University, Krakow, 30060, Poland
| | - Meng Gao
- Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China
| | - Shu-Li Xu
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Qi-Zhen Wu
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiao-Wen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Gong-Bo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Li-Wen Hu
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Bo-Yi Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yunjiang Yu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou, 510655, China.
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
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Ning J, Zhang Y, Hu H, Hu W, Li L, Pang Y, Ma S, Niu Y, Zhang R. Association between ambient particulate matter exposure and metabolic syndrome risk: A systematic review and meta-analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 782:146855. [PMID: 33839664 DOI: 10.1016/j.scitotenv.2021.146855] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 05/22/2023]
Abstract
Although the association between ambient particulate matter and metabolic syndrome (MetS) has been investigated, the effect of particulate matter (PM) on MetS is inconclusive. We conducted a systematic review and meta-analysis to study the association between long-term ambient PM exposure and MetS risk. The data from five databases were extracted to analyze the association between ambient PM exposure and MetS risk. A random-effects model was performed to estimate the overall risk effect. The present systematic review and meta-analysis illustrated that an increase of 5 μg/m3 in annual PM2.5 or PM10 concentration was associated with 14% or 9% increases of MetS risk, respectively (PM2.5, RR = 1.14, 95%CI [1.03, 1.25]; PM10, RR = 1.09, 95%CI [1.00, 1.19]). The population-attributable risk (PAR) was 12.28% for PM2.5 exposure or 8.26% for PM10 exposure, respectively. There was statistical association between PM2.5 exposure and risk of MetS in male proportion ≥50%, Asia, related disease or medication non-adjustment subgroup as well as cohort study subgroups, respectively. The significant association between PM10 exposure and risk of MetS was observed in male proportion ≥50% and calories intake adjustment subgroups, respectively. Sensitivity analyses showed the robustness of our results. No publication bias was detected. In conclusion, there was positive association between long-term PM exposure and MetS risk. 12.28% of MetS risk could be attributable to PM2.5 exposure.
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Affiliation(s)
- Jie Ning
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Yaling Zhang
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Huaifang Hu
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Wentao Hu
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Lipeng Li
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Yaxian Pang
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Shitao Ma
- Department of Occupation Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Yujie Niu
- Department of Occupation Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, PR China; Hebei Key Laboratory of Environment and Human Health, Shijiazhuang 050017, PR China
| | - Rong Zhang
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, PR China; Hebei Key Laboratory of Environment and Human Health, Shijiazhuang 050017, PR China.
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Matasović B, Pehnec G, Bešlić I, Davila S, Babić D. Assessment of ozone concentration data from the northern Zagreb area, Croatia, for the period from 2003 to 2016. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:36640-36650. [PMID: 33704644 DOI: 10.1007/s11356-021-13295-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Accepted: 03/01/2021] [Indexed: 06/12/2023]
Abstract
A measurement station located in an urban area on the southern slope of the Medvednica Mountain (120 m a.s.l.), close to the Croatian capital Zagreb, provided data for an analysis of the photosmog in the city of Zagreb. Data for the period 2003-2016 obtained from this station and analysed in this work can also be compared with the nearby Puntijarka station (980 m a.s.l.) for which a similar analysis has already been carried out. In Puntijarka station analysis, it has been shown that there is most probably no significant change in ozone concentrations during the observed period. In this study the mean value of the annual ozone volume fractions showed a linear trend of 0.23 ppb yr-1, a growth that is in the worst case scenario among the lowest global prediction, while the seasonal (April-to-September) mean values had a trend of 0.32 ppb yr-1, which is a certain clearly observable growth. The 95-percentile values had trends of 0.009 ppb yr-1 (annual data) and -0.072 ppb yr-1 (seasonal data), respectively. Both of these values show very small changes if any at all. By using FT analysis, with the calculation of uncertainties, we have observed three prominent cycles of 169 ± 4 h (weekly cycle), 24 ± 1 h and 12 ± 1 h (diurnal cycles). Uncertainties were low which strongly indicate that the cycles are present. However, since high concentrations of ozone were observed only sporadically, ozone pollution in the northern part of Zagreb is at the present rather low. A Fourier transformation was used to analyse the data for periodic behaviour, which revealed the existence of diurnal and weekly modulations. Nevertheless, constant monitoring is important and will continue in the future as part of continuous monitoring of the ozone levels in the area.
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Affiliation(s)
- Brunislav Matasović
- Josip Juraj Strossmayer University of Osijek, Ulica cara Hadrijana 8a, HR-31000, Osijek, Croatia.
| | - Gordana Pehnec
- Institute for Medical Research and Occupational Health, Ksaverska cesta 2, HR-10000, Zagreb, Croatia
| | - Ivan Bešlić
- Institute for Medical Research and Occupational Health, Ksaverska cesta 2, HR-10000, Zagreb, Croatia
| | - Silvije Davila
- Institute for Medical Research and Occupational Health, Ksaverska cesta 2, HR-10000, Zagreb, Croatia
| | - Dinko Babić
- Institute for Medical Research and Occupational Health, Ksaverska cesta 2, HR-10000, Zagreb, Croatia
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Wang X, Xu Z, Su H, Ho HC, Song Y, Zheng H, Hossain MZ, Khan MA, Bogale D, Zhang H, Wei J, Cheng J. Ambient particulate matter (PM 1, PM 2.5, PM 10) and childhood pneumonia: The smaller particle, the greater short-term impact? THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 772:145509. [PMID: 33571778 DOI: 10.1016/j.scitotenv.2021.145509] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 01/25/2021] [Accepted: 01/25/2021] [Indexed: 05/06/2023]
Abstract
BACKGROUND Smaller sizes of ambient particulate matter (PM) can be more toxic and can be breathed into lower lobes of a lung. Children are particularly vulnerable to PM air pollution because of their adverse effects on both lung functions and lung development. However, it remains unknown whether a smaller PM has a greater short-term impact on childhood pneumonia. AIMS We compared the short-term effects on childhood pneumonia from PM with aerodynamic diameters ≤1 μm (PM1), ≤2.5 μm (PM2.5), and ≤10 μm (PM10), respectively. METHODS Daily time-series data (2016-2018) on pneumonia hospitalizations in children aged 0-17 years, records of air pollution (PM1, PM2.5, PM10, and gaseous pollutants), and weather conditions were obtained for Hefei, China. Effects of different PM were quantified using a quasi-Poisson generalized additive model after controlling for day of the week, holiday, seasonality and long-term time trend, and weather variables. Stratified analyses (gender, age, and season) were also performed. RESULTS For each 10 μg/m3 increase in PM1, PM2.5, and PM10 concentrations over the past three days (lag 0-2), the risk of pneumonia hospitalizations increased by 10.28% (95%CI: 5.88%-14.87%), 1.21% (95%CI: 0.34%-2.09%), and 1.10% (95%CI: 0.44%-1.76%), respectively. Additionally, both boys and girls were at risk of PM1 effects, while PM2.5 and PM10 effects were only seen in boys. Children aged ≤12 months and 1-4 years were affected by PM1, but PM2.5 and PM10 were only associated with children aged 1-4 years. Furthermore, PM1 effects were greater in autumn and winter, while greater PM2.5 and PM10 effects were evident only in autumn. CONCLUSION This study suggests a greater short-term impact on childhood pneumonia from PM1 in comparison to PM2.5 and PM10. Given the serious PM pollution in China and other rapid developing countries due to various combustions and emissions, more investigations are needed to determine the impact of different PM on childhood respiratory health.
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Affiliation(s)
- Xu Wang
- Department of Science and Education, Children's Hospital of Anhui Medical University (Anhui Provincial Children's Hospital), Hefei, Anhui, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Hong Su
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Hung Chak Ho
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, China
| | - Yimeng Song
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China; Smart Cities Research Institute, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | | | - Daniel Bogale
- College of Health Sciences, Arsi University, Asela, Ethiopia
| | - Heng Zhang
- Sir Run Run Shaw Hospital (SRRSH), affiliated with the Zhejiang University School of Medicine, Zhejiang, China
| | - Jing Wei
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China; Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA.
| | - Jian Cheng
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China.
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Ran Z, An Y, Zhou J, Yang J, Zhang Y, Yang J, Wang L, Li X, Lu D, Zhong J, Song H, Qin X, Li R. Subchronic exposure to concentrated ambient PM2.5 perturbs gut and lung microbiota as well as metabolic profiles in mice. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 272:115987. [PMID: 33213950 DOI: 10.1016/j.envpol.2020.115987] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 10/12/2020] [Accepted: 11/01/2020] [Indexed: 05/21/2023]
Abstract
Exposure to ambient fine particular matter (PM2.5) are linked to an increased risk of metabolic disorders, leading to enhanced rate of many diseases, such as inflammatory bowel disease (IBD), cardiovascular diseases, and pulmonary diseases; nevertheless, the underlying mechanisms remain poorly understood. In this study, BALB/c mice were exposed to filtered air (FA) or concentrated ambient PM2.5 (CPM) for 2 months using a versatile aerosol concentration enrichment system(VACES). We found subchronic CPM exposure caused significant lung and intestinal damage, as well as systemic inflammatory reactions. In addition, serum and BALFs (bronchoalveolar lavage fluids) metabolites involved in many metabolic pathways in the CPM exposed mice were markedly disrupted upon PM2.5 exposure. Five metabolites (glutamate, glutamine, formate, pyruvate and lactate) with excellent discriminatory power (AUC = 1, p < 0.001) were identified to predict PM2.5 exposure related toxicities. Furthermore, subchronic exposure to CPM not only significantly decreased the richness and composition of the gut microbiota, but also the lung microbiota. Strong associations were found between several gut and lung bacterial flora changes and systemic metabolic abnormalities. Our study showed exposure to ambient PM2.5 not only caused dysbiosis in the gut and lung, but also significant systemic and local metabolic alterations. Alterations in gut and lung microbiota were strongly correlated with metabolic abnormalities. Our study suggests potential roles of gut and lung microbiota in PM2.5 caused metabolic disorders.
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Affiliation(s)
- Zihan Ran
- Department of Research, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, 1500 Zhouyuan Road, 201318, Shanghai, China; Inspection and Quarantine Department, The College of Medical Technology, Shanghai University of Medicine & Health Sciences, 279 Zhouzhu Road, 201318, Shanghai, China
| | - Yanpeng An
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Fudan University, Shanghai, 200438, China
| | - Ji Zhou
- Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai, China
| | - Jingmin Yang
- Key Laboratory of Birth Defects and Reproductive Health of National Health and Family Planning Commission (Chongqing Key Laboratory of Birth Defects and Reproductive Health, Chongqing Population and Family Planning, Science and Technology Research Institute), Chongqing, 400020, China; State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Youyi Zhang
- Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai, 200438, China
| | - Jingcheng Yang
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, China
| | - Lei Wang
- Department of Oral & Maxillofacial - Head & Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Stomatology, 639 Zhi Zao Ju Road, Shanghai, 200011, China
| | - Xin Li
- Department of Oral & Maxillofacial - Head & Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Stomatology, 639 Zhi Zao Ju Road, Shanghai, 200011, China
| | - Daru Lu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, 200438, China; Key Laboratory of Birth Defects and Reproductive Health of National Health and Family Planning Commission (Chongqing Key Laboratory of Birth Defects and Reproductive Health, Chongqing Population and Family Planning, Science and Technology Research Institute), Chongqing, 400020, China
| | - Jiang Zhong
- Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai, 200438, China
| | - Huaidong Song
- The Core Laboratory in Medical Center of Clinical Research, Department of Molecular Diagnostic & Endocrinology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University (SJTU) School of Medicine, Shanghai, 200011, China
| | - Xingjun Qin
- Department of Oral & Maxillofacial - Head & Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Stomatology, 639 Zhi Zao Ju Road, Shanghai, 200011, China
| | - Rui Li
- The Core Laboratory in Medical Center of Clinical Research, Department of Molecular Diagnostic & Endocrinology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University (SJTU) School of Medicine, Shanghai, 200011, China.
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Zhang JS, Gui ZH, Zou ZY, Yang BY, Ma J, Jing J, Wang HJ, Luo JY, Zhang X, Luo CY, Wang H, Zhao HP, Pan DH, Bao WW, Guo YM, Ma YH, Dong GH, Chen YJ. Long-term exposure to ambient air pollution and metabolic syndrome in children and adolescents: A national cross-sectional study in China. ENVIRONMENT INTERNATIONAL 2021; 148:106383. [PMID: 33465664 DOI: 10.1016/j.envint.2021.106383] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 12/28/2020] [Accepted: 01/05/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND The prevalence of metabolic syndrome (MetS) rapidly increased over the past decades. However, little evidence exists about the effects of long-term exposure to ambient air pollution on MetS in children and adolescents. OBJECTIVE This study aims to assess the association between long-term ambient air pollution and the prevalence of MetS in a large population of Chinese children and adolescents. METHODS In 2013, a total of 9,897 children and adolescents aged 10 to 18 years were recruited from seven provinces/municipalities in China. MetS was defined based on the recommendation by the International Diabetes Federation (IDF). Satellite based spatio-temporal models were used to estimate exposure to ambient air pollution (including particles with diameters ≤1.0 µm (PM1), ≤2.5 µm (PM2.5), and ≤10 µm (PM10), and nitrogen dioxide (NO2)). Individual exposure was calculated according to 94 schools addresses. After adjustment for a range of covariates, generalized linear mixed-effects models were utilized to evaluate the associations between air pollutants and the prevalence of MetS and its components. In addition, several stratified analyses were examined according to sex, weight status, outdoor physical activity time, and sugar-sweetened beverages (SSBs) intake. RESULTS The prevalence of MetS was 2.8%. The odds ratio of MetS associated with a 10 μg/m3 increase in PM1, PM2.5, PM10 and NO2 was 1.20 (95%CI: 0.99, 1.46), 1.31 (95%CI: 1.05, 1.64), 1.32 (95%CI: 1.08, 1.62), and 1.33 (95%CI: 1.03, 1.72), respectively. Regarding the MetS components, we observed associations between all pollutants and abdominal obesity. In addition, long-term PM1 and NO2 exposures were associated with the prevalence of elevated fasting blood glucose. Stratified analyses detected that the associations between air pollutants and the prevalence of MetS were stronger in boys (Pinteraction < 0.05). CONCLUSIONS We found that long-term exposure to PM2.5, PM10, and NO2 were positively associated with the prevalence of MetS in children and adolescents. Our findings may have certain public health implications for some comprehensive strategy of environment improvement and lifestyles changes in order to reduce the burden of non-communicable disease.
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Affiliation(s)
- Jing-Shu Zhang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Zhao-Huan Gui
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Zhi-Yong Zou
- Institute of Child and Adolescent Health, Peking University, School of Public Health, National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Bo-Yi Yang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Jun Ma
- Institute of Child and Adolescent Health, Peking University, School of Public Health, National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Jin Jing
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Hai-Jun Wang
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing 100191, China
| | - Jia-You Luo
- Department of Maternal and Child Health, School of Public Health, Central South University, Changsha 410078, China
| | - Xin Zhang
- School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Chun-Yan Luo
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai Institutes of Preventive Medicine, Shanghai 200336, China
| | - Hong Wang
- Department of Maternal and Child Health, School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
| | - Hai-Ping Zhao
- School of Public Health and Management, Ningxia Medical University, Ningxia, 750004, China
| | - De-Hong Pan
- Liaoning Health Supervision Bureau, Shenyang 110005, China
| | - Wen-Wen Bao
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Yu-Ming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Ying-Hua Ma
- Institute of Child and Adolescent Health, Peking University, School of Public Health, National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China.
| | - Guang-Hui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Ya-Jun Chen
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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Voss S, Schneider A, Huth C, Wolf K, Markevych I, Schwettmann L, Rathmann W, Peters A, Breitner S. ENVINT-D-20-01309: Long-term exposure to air pollution, road traffic noise, residential greenness, and prevalent and incident metabolic syndrome: Results from the population-based KORA F4/FF4 cohort in Augsburg, Germany. ENVIRONMENT INTERNATIONAL 2021; 147:106364. [PMID: 33421766 DOI: 10.1016/j.envint.2020.106364] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 11/12/2020] [Accepted: 12/21/2020] [Indexed: 05/28/2023]
Abstract
BACKGROUND A growing number of epidemiological studies show associations between environmental factors and impaired cardiometabolic health. However, evidence is scarce concerning these risk factors and their impact on metabolic syndrome (MetS). This analysis aims to investigate associations between long-term exposure to air pollution, road traffic noise, residential greenness, and MetS. METHODS We used data of the first (F4, 2006-2008) and second (FF4, 2013-2014) follow-up of the population-based KORA S4 survey in the region of Augsburg, Germany, to investigate associations between exposures and MetS prevalence at F4 (N = 2883) and MetS incidence at FF4 (N = 1192; average follow-up: 6.5 years). Residential long-term exposures to air pollution - including particulate matter (PM) with a diameter < 10 µm (PM10), PM < 2.5 µm (PM2.5), PM between 2.5 and 10 µm (PMcoarse), absorbance of PM2.5 (PM2.5abs), particle number concentration (PNC), nitrogen dioxide (NO2), ozone (O3) - and road traffic noise were modeled by land-use regression models and noise maps. For greenness, the Normalized Difference Vegetation Index (NDVI) was obtained. We estimated Odds Ratios (OR) for single and multi-exposure models using logistic regression and generalized estimating equations adjusted for confounders. Joint Odds Ratios were calculated based on the Cumulative Risk Index. Effect modifiers were examined with interaction terms. RESULTS We found positive associations between prevalent MetS and interquartile range (IQR) increases in PM10 (OR: 1.15; 95% confidence interval [95% CI]: 1.02, 1.29), PM2.5 (OR: 1.14; 95% CI: 1.02, 1.28), PMcoarse (OR: 1.14; 95% CI: 1.02, 1.27), and PM2.5abs (OR: 1.17; 95% CI: 1.03, 1.32). Results further showed negative, but non-significant associations between exposure to greenness and prevalent and incident MetS. No effects were seen for exposure to road traffic noise. Joint Odds Ratios from multi-exposure models were higher than ORs from models with only one exposure.
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Affiliation(s)
- Stephan Voss
- Institute for Medical Information Processing, Biometry and Epidemiology - IBE, LMU Munich, Munich, Germany; Pettenkofer School of Public Health, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München GmbH - German Research Center for Environmental Health, Neuherberg, Germany.
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München GmbH - German Research Center for Environmental Health, Neuherberg, Germany
| | - Cornelia Huth
- Institute of Epidemiology, Helmholtz Zentrum München GmbH - German Research Center for Environmental Health, Neuherberg, Germany
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München GmbH - German Research Center for Environmental Health, Neuherberg, Germany
| | - Iana Markevych
- Institute of Epidemiology, Helmholtz Zentrum München GmbH - German Research Center for Environmental Health, Neuherberg, Germany; Institute and Clinic for Occupational, Social and Environmental Medicine, LMU Munich, Munich, Germany; Institute of Psychology, Jagiellonian University, Cracow, Poland
| | - Lars Schwettmann
- Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Institute of Health Economics and Health Care Management, Neuherberg, Germany
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Duesseldorf, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München GmbH - German Research Center for Environmental Health, Neuherberg, Germany
| | - Susanne Breitner
- Institute for Medical Information Processing, Biometry and Epidemiology - IBE, LMU Munich, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München GmbH - German Research Center for Environmental Health, Neuherberg, Germany
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Nowicki GJ, Ślusarska B, Naylor K, Prystupa A, Rudnicka-Drożak E, Halyuk U, Pokotylo P. The Relationship Between the Metabolic Syndrome and the Place of Residence in the Local Community on the Example of the Janów Lubelski District in Eastern Poland: A Population-Based Study. Diabetes Metab Syndr Obes 2021; 14:2041-2056. [PMID: 33986605 PMCID: PMC8110259 DOI: 10.2147/dmso.s301639] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 03/20/2021] [Indexed: 12/15/2022] Open
Abstract
PURPOSE The aim of this study was to estimate the incidence concerning metabolic syndrome (MetS) in a local community with a low socioeconomic status and a medium and high cardiovascular risk on the example of residents of Janów Lubelski district, eastern Poland. The second goal of the research was to analyze the relationship between residence and the occurrence of MetS. METHODS We conducted a cross-sectional study of 4040 people living in eastern Poland. A group of 3046 people with medium and high cardiovascular risk was selected among the respondents and included in further analyzes. The research adopted the definition criteria proposed by the National Cholesterol Education Program - Third Adult Treatment Panel (NCEP ATP III) to implement diagnostic evaluation of MetS. RESULTS It was observed that metabolic syndrome was significantly more frequent among the inhabitants of rural areas (40.56%; n=810) compared to those living in the city (35.27%; n=370) p=0.005. Among the inhabitants of rural areas, the percentage of people with elevated glucose levels was significantly higher, fasting blood glucose (FGB) p<0.001, elevated blood pressure (HBP) p<0.001, elevated serum triglycerides (TGs) p=0.01, and abnormal waist circumference (WC) p=0.003 compared to urban inhabitants. After adjusting for potential confounding variables (age, education, smoking, marital status, and level of physical activity), in both women and men, the odds of developing metabolic syndrome were approximately 30% higher in rural areas compared to urban residents (women: odds ratio (OR)=1.25, 95% confidence intervals (CI)=1.01-1.56; men: OR=1.30, 95% CI=1.01-1.67). CONCLUSION AND RECOMMENDATIONS A higher incidence of metabolic syndrome was observed among respondents living in rural areas than those living in cities. Similarly, across the gender strata, metabolic syndrome is more commonly diagnosed among men and women living in rural areas. Healthcare workers, especially in rural areas, should engage in education, prevention, and the promotion of a healthy lifestyle.
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Affiliation(s)
- Grzegorz Józef Nowicki
- Department of Family Medicine and Community Nursing, Medical University of Lublin, Lublin, Poland
- Correspondence: Grzegorz Józef Nowicki Department of Family Medicine and Community Nursing, Medical University of Lublin, Staszica 6 Street, PL-20-081, Lublin, PolandTel +48 81448 6810Fax +48 81448 6811 Email
| | - Barbara Ślusarska
- Department of Family Medicine and Community Nursing, Medical University of Lublin, Lublin, Poland
| | - Katarzyna Naylor
- Department of Didactics and Medical Simulation, Medical University of Lublin, Lublin, Poland
| | - Andrzej Prystupa
- Department of Internal Medicine, Medical University of Lublin, Lublin, Poland
| | | | - Ulyana Halyuk
- Department of Normal Anatomy, Lviv National Medical University, Lviv, Ukraine
| | - Petro Pokotylo
- Department of Normal Anatomy, Lviv National Medical University, Lviv, Ukraine
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Najafi ML, Zarei M, Gohari A, Haghighi L, Heydari H, Miri M. Preconception air pollution exposure and glucose tolerance in healthy pregnant women in a middle-income country. Environ Health 2020; 19:131. [PMID: 33298083 PMCID: PMC7727159 DOI: 10.1186/s12940-020-00682-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 12/01/2020] [Indexed: 05/11/2023]
Abstract
BACKGROUND Preconception exposure to air pollution has been associated with glucose tolerance during pregnancy. However, the evidence in low and middle-income countries (LMICs) is under debate yet. Therefore, this study aimed to assess the relationship between exposure to ambient particulate matter (PM) and traffic indicators with glucose tolerance in healthy pregnant women in Sabzevar, Iran (2019). METHODS Two-hundred and fifty healthy pregnant women with singleton pregnancies and 24-26 weeks of gestations participated in our study. Land use regression (LUR) models were applied to estimate the annual mean of PM1, PM2.5 and PM10 at the residential address. Traffic indicators, including proximity of women to major roads as well as total streets length in 100, 300 and 500 m buffers around the home were calculated using the street map of Sabzevar. The oral glucose tolerance test (OGTT) was used to assess glucose tolerance during pregnancy. Multiple linear regression adjusted for relevant covariates was used to estimate the association of fasting blood glucose (FBG), 1-h and 2-h post-load glucose with PMs and traffic indicators. RESULTS Exposure to PM1, PM2.5 and PM10 was significantly associated with higher FBG concentration. Higher total streets length in a 100 m buffer was associated with higher FBG and 1-h glucose concentrations. An interquartile range (IQR) increase in proximity to major roads was associated with a decrease of - 3.29 mg/dL (95% confidence interval (CI): - 4.35, - 2.23, P-value < 0.01) in FBG level and - 3.65 mg/dL (95% CI, - 7.01, - 0.28, P-value = 0.03) decrease in 1-h post-load glucose. CONCLUSION We found that higher preconception exposure to air pollution was associated with higher FBG and 1-h glucose concentrations during pregnancy.
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Affiliation(s)
- Moslem Lari Najafi
- Pharmaceutical Sciences and Cosmetic Products Research Center, Kerman University of Medical Sciences, Kerman, Iran
| | - Mehdi Zarei
- Department of Physical Education and Sport Science, Faculty of Human Science, University of Neyshabur, Neyshabur, Iran
| | - Ali Gohari
- Cellular and Molecular Research Center, Sabzevar University of Medical Sciences, Sabzevar, Iran
| | - Leyla Haghighi
- Cellular and Molecular Research Center, Sabzevar University of Medical Sciences, Sabzevar, Iran
| | - Hafez Heydari
- Cellular and Molecular Research Center, Sabzevar University of Medical Sciences, Sabzevar, Iran.
| | - Mohammad Miri
- Non-Communicable Diseases Research Center, Department of Environmental Health, School of Health, Sabzevar University of Medical Sciences, PO Box 319, Sabzevar, Iran.
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Qiu H, Wang L, Zhou L, Pan J. Coarse particles (PM 2.5-10) and cause-specific hospitalizations in southwestern China: Association, attributable risk and economic costs. ENVIRONMENTAL RESEARCH 2020; 190:110004. [PMID: 32745536 DOI: 10.1016/j.envres.2020.110004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 07/21/2020] [Accepted: 07/26/2020] [Indexed: 06/11/2023]
Abstract
The short-term morbidity effects of the coarse particle (diameter in 2.5-10 μm, PM2.5-10), as well as the corresponding morbidity burden and economic costs, remain understudied, especially in developing countries. This study aimed to examine the associations of PM2.5-10 with cause-specific hospitalizations in a multi-city setting in southwestern China and assess the attributable risk and economic costs. City-specific associations were firstly estimated using generalized additive models with quasi-poisson distribution to handle over-dispersion, and then combined to obtain the regional average association. City-specific and pooled concentration-response (C-R) associations of PM2.5-10 with cause-specific hospitalizations were also modeled. Subgroup analyses were performed by age, sex, season and region. The health and economic burden of hospitalizations for multiple outcomes due to PM2.5-10 were further evaluated. A total of 4,407,601 non-accidental hospitalizations were collected from 678 hospitals. The estimates of percentage change in hospitalizations per 10 μg/m³ increase in PM2.5-10 at lag01 was 0.68% (95%CI: 0.33%-1.03%) for non-accidental causes, 0.86% (95% CI: 0.36%-1.37%) for circulatory diseases, 1.52% (95% CI: 1.00%-2.05%) for respiratory diseases, 1.08% (95% CI: 0.47%-1.69%) for endocrine diseases, 0.66% (95% CI: 0.12%-1.21%) for nervous system diseases, and 0.84% (95% CI: 0.42%-1.25%) for genitourinary diseases, respectively. The C-R associations of PM2.5-10 with cause-specific hospitalizations suggested some evidence of nonlinearity, except for endocrine diseases. Meanwhile, the adverse effects were modified by age and season. Overall, about 0.70% (95% CI: 0.35%-1.06%) of non-accidental hospitalizations and 0.78% (95% CI: 0.38%-1.17%) of total hospitalization expenses could be attributed to PM2.5-10. The largest morbidity burden and economic costs were observed in respiratory diseases. Our findings indicate that PM2.5-10 exposure may increase the risk of hospitalizations for multiple outcomes, and account for considerable morbidity and economic burden.
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Affiliation(s)
- Hang Qiu
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
| | - Liya Wang
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
| | - Li Zhou
- Health Information Center of Sichuan Province, Chengdu, China
| | - Jingping Pan
- Health Information Center of Sichuan Province, Chengdu, China
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Deng X, Wang P, Yuan H. Epidemiology, risk factors across the spectrum of age-related metabolic diseases. J Trace Elem Med Biol 2020; 61:126497. [PMID: 32247247 DOI: 10.1016/j.jtemb.2020.126497] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 02/13/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Population aging is dynamic process of increasing proportion of older adults in the total population, which is an inescapable result of decline in fertility rate and extension in life expectancy. Inevitably, age-related metabolic diseases, for example obesity, type 2 diabetes, metabolic syndrome, dyslipidemia, and nonalcoholic fatty liver disease, are becoming epidemic globally along with the demographic transition. CONTENT The review examines the literatures related to: 1) the epidemiology of age related metabolic diseases including obesity, type 2 diabetes, metabolic syndrome, dyslipidemia, and nonalcoholic fatty liver disease; and 2) the risk factors of age related metabolic diseases including genetic factors, diet, smoking, Physical activity, intestinal microbiota and environmental factors. CONCLUSION Population aging is becoming epidemic worldwide, resulting in increasing incidence and prevalence of a serious of age-related metabolic diseases. Both genetic and environmental factors contribute to the diseases, thus interventions targeting on these factors may have beneficial effect on the development of age-related metabolic diseases.
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Affiliation(s)
- Xinru Deng
- Department of Endocrinology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, 450003, China
| | - Pengxu Wang
- Department of Endocrinology, Henan University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, 450003, China
| | - Huijuan Yuan
- Department of Endocrinology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, 450003, China.
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Tu R, Hou J, Liu X, Li R, Dong X, Pan M, Mao Z, Huo W, Chen G, Guo Y, Li S, Wang C. Physical activity attenuated association of air pollution with estimated 10-year atherosclerotic cardiovascular disease risk in a large rural Chinese adult population: A cross-sectional study. ENVIRONMENT INTERNATIONAL 2020; 140:105819. [PMID: 32480112 DOI: 10.1016/j.envint.2020.105819] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 04/26/2020] [Accepted: 05/16/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Although long-term exposure to air pollution and physical inactivity are linked to increased risk for atherosclerotic cardiovascular diseases (ASCVD), however, the interactive effect of air pollution and physical activity (PA) on high 10-year ASCVD risk is largely unknown. METHODS A total of 31,162 individuals aged 35-74 years were derived from the Henan Rural Cohort Study, after individuals with personal histories of ASCVD or missing data on predictors of high 10-year ASCVD risk were excluded. Concentrations of air pollutants (nitrogen dioxide (NO2), particulate matter with an aerodynamics diameters ≤ 1.0 µm (PM1), ≤2.5 µm (PM2.5) or ≤10 µm (PM10)) of individuals were estimated using a spatiotemporal model based on satellites data. The metabolic equivalent (MET) of PA of each individual was evaluated using the formula: duration (hour/time) × frequency/week × MET coefficient of each type of activity. Logistic regression models were used to analyze associations between air pollutants, PA and high 10-year ASCVD risk. Interaction plots were used to describe interactive effects of air pollutants and PA on high 10-year ASCVD risk. RESULTS Each 1 µg/m3 increase in PM1, PM2.5, PM10 and NO2 were related to a 4.4% (odds ratio (OR): 1.044, 95% confidence interval (CI): 1.034, 1.056), 9.1% (OR: 1.091, 95% CI: 1.079, 1.104), 4.6% (OR: 1.046, 95% CI: 1.040, 1.051) or 6.4% (OR: 1.064, 95% CI: 1.055, 1.072) increase in high 10-year ASCVD risk (all p < 0.001), respectively; each one unit-increase in PA MET (hour/day) value was related to a 1.8% (OR: 0.982, 95% CI: 0.980, 0.985) decrease in high 10-year ASCVD risk. Negative interactive effects of PA and PM1, PM2.5, PM10 and NO2 on high 10-year ASCVD risk were observed (all p < 0.001). CONCLUSION Exposure to high levels of air pollutants were related to increase high 10-year ASCVD risk and these associations were attenuated by PA, implying that PA may be an effective method to the prevention of high 10-year ASCVD risk in highly polluted rural regions.
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Affiliation(s)
- Runqi Tu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Ruiying Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xiaokang Dong
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Mingming Pan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Gongbo Chen
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, China
| | - Yuming Guo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China.
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Liao Q, Jin W, Tao Y, Qu J, Li Y, Niu Y. Health and Economic Loss Assessment of PM 2.5 Pollution during 2015-2017 in Gansu Province, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E3253. [PMID: 32392731 PMCID: PMC7246598 DOI: 10.3390/ijerph17093253] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Revised: 04/29/2020] [Accepted: 05/04/2020] [Indexed: 12/07/2022]
Abstract
Many studies have reported that air pollution, especially fine particulate matter (PM2.5), has a significant impact on health and causes economic loss. Gansu Province is in the northwest of China, which is a typical economically underdeveloped area. However, few studies have evaluated the economic loss of PM2.5 related to health effects in this province. In this study, a log-linear exposure-response function was used to estimate the health impact of PM2.5 in 14 cities in Gansu Province from 2015 to 2017, and the amended human capital (AHC) and cost of illness (COI) method were used to evaluate the related economic loss caused by the health impact from PM2.5. The results show that the estimated total number of health endpoints attributed to PM2.5 pollution were 1,644,870 (95%CI: 978,484-2,215,921), 1,551,447 (95%CI: 917,025-2,099,182) and 1,531,372 (95%CI: 899,769-2,077,772) in Gansu Province from 2015 to 2017, respectively. Correspondingly, the economic losses related to health damage caused by PM2.5 pollution were 42,699 (95%CI: 32,380-50,768) million Chinese Yuan (CNY), 43,982 (95%CI: 33,305-52,386) million CNY and 44,261 (95%CI: 33,306-52,954) million CNY, which were equivalent to 6.45% (95%CI: 4.89%-7.67%), 6.28% (95%CI: 4.75%-7.48%), and 5.93% (95%CI: 4.64%-7.10%) of the region Gross Domestic Product (GDP) from 2015 to 2017, respectively. It could be seen that the proportions of health economic loss to GDP were generally high, although the proportion had a slight downward trend. The economic loss from chronic bronchitis and all-cause mortality accounted for more than 94% of the total economic loss. The health impact, economic loss and per capita economic loss in Lanzhou, the provincial capital city of Gansu, were obviously higher than other cities from the same province. The economic loss in Linxia accounted for the highest proportion of GDP. The health impacts in the Hexi region, including the cities of Jiuquan, Jiayuguan, Zhangye, Jinchang and Wuwei, were generally lower, but the economic loss and per capita economic loss were still higher. We also found that urbanization and industrialization were highly correlated with health economic loss caused by PM2.5 pollution. In conclusion, the PM2.5-related health economic burden in Gansu Province was serious. As an economically underdeveloped region, it was very important to further adopt rigid and effective pollution control policies.
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Affiliation(s)
- Qin Liao
- Key Laboratory of Western China’s Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; (Q.L.); (Y.L.)
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China; (J.Q.); (Y.N.)
- Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Wangqiang Jin
- Institute for Environmental Strategy, Gansu Academy of Eco-environmental Sciences, Lanzhou 730020, China;
| | - Yan Tao
- Key Laboratory of Western China’s Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; (Q.L.); (Y.L.)
- Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Jiansheng Qu
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China; (J.Q.); (Y.N.)
| | - Yong Li
- Key Laboratory of Western China’s Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; (Q.L.); (Y.L.)
- Key Laboratory for Environmental Pollution Prediction and Control, Gansu Province, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
| | - Yibo Niu
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China; (J.Q.); (Y.N.)
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Chen L, Zhang Y, Zhang W, Chen G, Lu P, Guo Y, Li S. Short-term effect of PM 1 on hospital admission for ischemic stroke: A multi-city case-crossover study in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 260:113776. [PMID: 31962264 DOI: 10.1016/j.envpol.2019.113776] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 11/12/2019] [Accepted: 12/08/2019] [Indexed: 06/10/2023]
Abstract
This study aims to examine the association between short-term exposures to PM1, PM2.5 and PM10 (particulate matter with aerodynamic diameters ≤1 μm, ≤2.5 μm and ≤10 μm, respectively) and hospital admission for ischemic stroke in China. Daily counts of hospital admission for ischemic stroke were collected in 5 hospitals in China during November 2013 to October 2015. Daily concentrations of PM1, PM2.5 and PM10 were collected in 5 cities where the hospitals were located. A time-stratified case-crossover design was used to examine the hospital-specific PM-ischemic stroke association after controlling for potential confounders. Then the effect estimates were pooled using a random-effect meta-analysis. A total of 68,122 hospital admissions for ischemic stroke were identified from 5 hospitals during the study period. The pooled results showed that exposures to PM1, PM2.5 and PM10 were significantly associated with increased hospital admission for ischemic stroke on the current day and previous 1 day. The RRs (relative risk associated with per 10 μg/m3 increase in each pollutant) and 95%CIs (confidence intervals) for the cumulative effects of PM1, PM2.5 and PM10 on ischemic stroke during lag 0-1 days were 1.014 (1.005, 1.0023), 1.007 (1.000, 1.014) and 1.005 (1.001, 1.009), respectively. In total, 3.5%, 3.6% and 4.1% of hospital admissions for ischemic stroke could be attributable to PM1, PM2.5 and PM10, respectively. Exposures to ambient PM1, PM2.5 and PM10 pollution showed acute adverse effects on hospital admission for ischemic stroke. The health effects of PM1 should be considered by policy-makers.
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Affiliation(s)
- Lijun Chen
- Information Engineering College, Hubei University of Chinese Medicine, Wuhan, Hubei, China
| | - Yongming Zhang
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, National Clinical Research Center for Respiratory Diseases, Beijing, China.
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Gongbo Chen
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, Hubei, China
| | - Peng Lu
- Department of Epidemiology, School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
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Liu X, Tu R, Qiao D, Niu M, Li R, Mao Z, Huo W, Chen G, Xiang H, Guo Y, Li S, Wang C. Association between long-term exposure to ambient air pollution and obesity in a Chinese rural population: The Henan Rural Cohort Study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 260:114077. [PMID: 32041030 DOI: 10.1016/j.envpol.2020.114077] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 01/23/2020] [Accepted: 01/23/2020] [Indexed: 05/17/2023]
Abstract
Association between long-term exposure to ambient air pollution and obesity remains inconclusive, and the evidence from rural areas was limited. Thus, this study aimed to assess the association between ambient air pollution and obesity based on different anthropometric indices in Chinese rural adults, and further to compare the effect sizes of different air pollution types. A total of 38,824 participants (aged 18-79 years) were recruited from the Henan Rural Cohort Study. Logistic and multivariable linear regression model were used to examine the association between ambient air pollution exposure (including particulate matter with aerodynamic diameters ≤ 1.0 μm (PM1), ≤2.5 μm (PM2.5), and ≤10 μm (PM10), and nitrogen dioxide (NO2)) and obesity as well as obese anthropometric indices (including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI)). The potential effect modifications were also examined. Positive associations were found between long-term exposure to PM1, PM2.5, PM10 and NO2 and obesity regardless of how obesity was defined (false discovery rate (FDR) < 0.05). Moreover, BMI, WC, WHR, WHtR, BFP, and VFI displayed increased trends with PM1, PM2.5, PM10 and NO2 concentrations increasing (all FDR<0.05). PM10 had the largest effects on obesity among the four types of air pollution. The elderly, women, individuals with low level of education and income, and those who had high fat diet were more vulnerable to the adverse effects of air pollution. In addition, the results of the sensitivity analysis showed that those associations between ambient air pollution and obesity remained robust. These findings suggest that long-term exposure to ambient air pollutant (particularly PM10) may be positively associated with obesity in Chinese rural adults, especially among the elderly, women, individuals with low education and income, as well as unhealthy lifestyles.
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Affiliation(s)
- Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Runqi Tu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Dou Qiao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Miaomiao Niu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Ruiying Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Gongbo Chen
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, PR China
| | - Hao Xiang
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, PR China
| | - Yuming Guo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China.
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Mao S, Li S, Wang C, Liu Y, Li N, Liu F, Huang S, Liu S, Lu Y, Mao Z, Huo W, Chen G, Xiang H, Guo Y. Is long-term PM 1 exposure associated with blood lipids and dyslipidemias in a Chinese rural population? ENVIRONMENT INTERNATIONAL 2020; 138:105637. [PMID: 32155508 PMCID: PMC7152799 DOI: 10.1016/j.envint.2020.105637] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 03/02/2020] [Accepted: 03/04/2020] [Indexed: 05/09/2023]
Abstract
BACKGROUND Air pollution has been shown to be associated with blood lipid levels. However, studies on long-term ambient particulate matter with aerodynamic diameter ≤1 μm (PM1) exposure in high-exposure areas are still limited. This study aimed to explore the associations among long-term PM1 exposure, blood lipids and dyslipidemias. METHODS Baseline data of The Henan Rural Cohort study was used in present study, including a total of 39,259 participants aged from 18 to 79 years. Daily levels of PM1 were estimated by a spatiotemporal model using ground-level measurements of PM1, satellite remote sensing data and other predictors, according to participants' home addresses. Individual exposure to PM1 was the 3-year average before baseline investigation. Linear regression and logistic regression models were applied to examine the associations among PM1, blood lipids ((total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C)), and prevalence of dyslipidemias. RESULTS The 3-year concentration of PM1 was 55.7 ± 2.1 μg/m3. Each 1 μg/m3 increment of PM1 was associated with an increase of 0.21% (95% confidence interval (CI): 0.11%-0.31%) in TC and 0.75% (95% CI: 0.61%-0.90%) in LDL-C, while decrease of 2.68% (95% CI: 2.43%-2.93%) in TG and 0.47% (95% CI: 0.35%-0.59%) in HDL-C. Each 1 μg/m3 increase in PM1 was associated with 6% (95% CI: 4%-8%), 3% (95% CI: 2%-5%) and 5% (95% CI: 3%-7%) higher risks of hypercholesterolemia, hyperbetalipoproteinemia and hypoalphalipoproteinemia. Sex, age and BMI statistically modified the associations between PM1 with blood lipid levels and dyslipidemias. CONCLUSIONS Higher PM1 exposure was associated with adverse changes of blood lipid levels and dyslipidemias. Males, older and overweight participants were susceptive to the adverse effects of PM1.
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Affiliation(s)
- Shuyuan Mao
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China; Global Health Institute, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Yisi Liu
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98105, USA
| | - Na Li
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China; Global Health Institute, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Feifei Liu
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China; Global Health Institute, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Shuqiong Huang
- Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, Hubei Province, China
| | - Suyang Liu
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China; Global Health Institute, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Yuanan Lu
- Environmental Health Laboratory, Department of Public Health Sciences, University of Hawaii at Manoa, Honolulu, HI 96822, USA
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Gongbo Chen
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China; Global Health Institute, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China.
| | - Hao Xiang
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China; Global Health Institute, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China; Hubei Biomass-Resource Chemistry and Environmental Biotechnology Key Laboratory, Wuhan University, 115# Donghu Road, Wuhan, China.
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, Henan, China
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Fossati S, Valvi D, Martinez D, Cirach M, Estarlich M, Fernández-Somoano A, Guxens M, Iñiguez C, Irizar A, Lertxundi A, Nieuwenhuijsen M, Tamayo I, Vioque J, Tardón A, Sunyer J, Vrijheid M. Prenatal air pollution exposure and growth and cardio-metabolic risk in preschoolers. ENVIRONMENT INTERNATIONAL 2020; 138:105619. [PMID: 32193046 DOI: 10.1016/j.envint.2020.105619] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 01/26/2020] [Accepted: 02/27/2020] [Indexed: 05/06/2023]
Abstract
OBJECTIVES We investigated the association between outdoor air pollutants exposure in the first trimester of pregnancy, and growth and cardio-metabolic risk at four years of age, and evaluated the mediating role of birth weight. METHODS We included mother-child pairs (N = 1,724) from the Spanish INMA birth cohort established in 2003-2008. First trimester of pregnancy nitrogen dioxide (NO2) and fine particles (PM2.5) exposure levels were estimated. Height, weight, waist circumference, blood pressure, and lipids were measured at four years of age. Body mass index (BMI) trajectories from birth to four years were identified. RESULTS Increased PM2.5 exposure in the first trimester of pregnancy was associated with decreased z-scores of weight (zWeight) and BMI (zBMI) (zWeight change per interquartile range increase in PM2.5 exposure = -0.12; 95% CI: -0.23, -0.01; zBMI change = -0.12; 95% CI: -0.23, -0.01). Higher NO2 and PM2.5 exposure was associated to a reduced risk of being in a trajectory with accelerated BMI gain, compared to children with the average trajectory. Birth weight partially mediated the association between PM2.5 and zWeight and zBMI. PM2.5 and NO2 were not associated with the other cardio-metabolic risk factors. CONCLUSIONS This comprehensive study of many growth and cardio-metabolic risk related outcomes suggests that air pollution exposure during pregnancy may be associated with delays in physical growth in the early years after birth. These findings imply that pregnancy exposure to air pollutants has a lasting effect on growth after birth and require follow-up at later child ages.
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Affiliation(s)
- Serena Fossati
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.
| | - Damaskini Valvi
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - David Martinez
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Marta Cirach
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Marisa Estarlich
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Department of Nursing, Faculty of Nursing and Chiropody, University of Valencia; Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, 46020, Spain
| | - Ana Fernández-Somoano
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain; IUOPA-Departamento de Medicina, University of Oviedo, Oviedo, Spain; Institute of Health Research of the Principality of Asturias - Foundation for Biosanitary Research of Asturias (ISPA-FINBA), Oviedo, Spain
| | - Mònica Guxens
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre-Sophia Children's Hospital, Rotterdam, the Netherlands
| | - Carmen Iñiguez
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Department of Statistics and Computational Research, Universitat de València, Valencia, Spain
| | - Amaia Irizar
- Biodonostia Health Research Institute, Donostia, Spain
| | - Aitana Lertxundi
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Biodonostia Health Research Institute, Donostia, Spain; Faculty of Medicine and Nursing of the University of the Basque Country, Bilbao, Spain
| | - Mark Nieuwenhuijsen
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Ibon Tamayo
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Division of Immunology and Immunotherapy, Cima, Universidad de Navarra, Pamplona, Spain; Instituto de Investigación Sanitaria de Navarra (IdISNA), Pamplona, Spain
| | - Jesus Vioque
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Universidad Miguel Hernandez, ISABIAL-FISABIO, Alicante, Spain
| | - Adonina Tardón
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain; IUOPA-Departamento de Medicina, University of Oviedo, Oviedo, Spain; Institute of Health Research of the Principality of Asturias - Foundation for Biosanitary Research of Asturias (ISPA-FINBA), Oviedo, Spain
| | - Jordi Sunyer
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain
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Khosravipour M, Abdollahzad H, Khosravi F, Rezaei M, Mohammadi Sarableh H, Moradi Z. The Association of Occupational Noises and the Prevalence of Metabolic Syndrome. Ann Work Expo Health 2020; 64:514-521. [DOI: 10.1093/annweh/wxaa030] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 01/27/2020] [Accepted: 03/03/2020] [Indexed: 12/19/2022] Open
Abstract
AbstractObjectivesPrevious studies have shown the association of exposure to noise with cardiovascular diseases such as hypertension, however, it is not well known whether the exposure has any effect on metabolic syndrome (MetS). This study aimed to quantify and clarify the association between noise exposure and the prevalence of MetS.MethodsThis cross-sectional study was conducted in 2017 among 518 workers in a thermal power plant industry. According to types of work and 8-h equivalent A-weighted sound pressure level (8-h LAeq), the participants were divided into the following groups: office workers and line-production workers exposed to < 85, 90 to <95, 95 to <100, and ≥100 dBA. We used the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) criteria to identify subjects with MetS. The logistic regression was used to determine the odds of MetS among study groups.ResultsWe observed the significant differences in the number (%) of subjects with high blood pressure in line-production workers who exposed to noise ≥100 (12 [19.7%]) versus <85 dBA (7 [7.1%]) and office (10 [4.7%]) groups. For the waist circumference (>102 cm), there was a significant difference in the ≥100 dBA group (12 [19.7%]) compared with office group (21 [9.8%]). Obtained results indicated only the significant difference in the prevalence of MetS in ≥100 versus <85 dBA groups (10 [16.4%] versus 6 [6.1%]). The unadjusted and adjusted odds ratios and 95% confidence intervals of MetS in ≥100 versus <85 dBA groups were estimated 3.01 (1.03, 8.75) and 3.24 (1.01, 10.42), respectively.ConclusionsThis study indicated the significant association between noise exposure and MetS in line-production workers. However, more studies are needed to confirm our results.
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Affiliation(s)
- Masoud Khosravipour
- Research Center for Environmental Determinants of Health (RCEDH), Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
- Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Hadi Abdollahzad
- Research Center for Environmental Determinants of Health (RCEDH), Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
- Nutritional Sciences Department, School of Nutritional Sciences and Food Technology, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Farid Khosravi
- Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Mansour Rezaei
- Department of Statistics and Epidemiology, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | | | - Zahra Moradi
- Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran
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Wang M, Gong L, Zou Z, Jiang A, Wang H, Luo J, Zhang X, Luo C, Wang H, Zhao H, Pan D, Jing J, Wu Y, Wang R, Ma J, Ma Y, Chen Y. The relationship between long-term exposure to PM 2.5 and fasting plasma glucose levels in Chinese children and adolescents aged 6-17 years: A national cross-sectional study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 710:136211. [PMID: 32050359 DOI: 10.1016/j.scitotenv.2019.136211] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Revised: 12/17/2019] [Accepted: 12/17/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Previous studies investigating the association between PM2.5 exposure and fasting plasma glucose levels (FPGLs) are mostly limited to short- and mid-term PM2.5 exposure and lack adjustments for key confounders in adult research. OBJECTIVES Exploring the relationship between seven years long-term PM2.5 exposure and FPGLs in Chinese children and adolescents aged 6-17 years. METHODS Between September 2013 and December 2013, 16,489 participants aged 6-17 years were recruited using a four-staged, stratified, cluster sampling strategy from 7 provinces, autonomous regions and municipalities of mainland China. A generalized linear mixed model (GLMM) was used to estimate the relationship between annual PM2.5 exposure (2007-2013) and FPGLs stratified by sex and one-year age increments. Sociodemographic characteristics, living with both parents, early-life factors, behaviours, and infection symptoms were gradually adjusted from the crude model to regression model 6, and BMI was adjusted for in model 7. RESULTS The annual concentration of PM2.5 was 56.23 (±12.99) μg/m3. The mean FPGLs in the 8551 boys (4.75 mmol/L ± 0.52) was significantly higher than that in the 8194 girls (4.63 mmol/L ± 0.48) (P < 0.0001). In model 6, for every 10 μg/m3 increase in PM2.5 exposure, the FPGLs in boys and girls increased by 0.048 (95% CIs 0.031 to 0.065) mmol/L (P < 0.0001) and 0.054 (95% CIs 0.039 to 0.069) mmol/L (P < 0.0001), respectively. The FPGLs were significantly positively associated with long-term PM2.5 exposure at the ages of 12, 15 and 16 years in both the boys and girls and exhibited age differences in model 7. The prevalence of impaired fasting plasma glucose (IFP) and diabetes decreased by 0.8% when the exposure concentration of PM2.5 was reduced by 10 μg/m3 in model 6, which assessed the negative effects of PM2.5 exposure and revealed that 1,298,920 children and adolescents could have been protected from IFP and diabetes in 2013 in China. CONCLUSIONS Long-term PM2.5 exposure may be an independent risk factor of elevated FPGLs. The adverse effect of PM2.5 exposure on FPGLs in children and adolescents could appear after 10 years of cumulative exposure. The precise intervention time was revealed as approximately 12 and 11 years in boys and girls, respectively. There are great public health implications associated with early prevention strategies for the eradication of the negative effects of long-term exposure to PM2.5 on FPGLs.
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Affiliation(s)
- Mao Wang
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Lijuan Gong
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zhiyong Zou
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Aili Jiang
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Haijun Wang
- School of Public Health, Peking University, Beijing, China
| | - Jiayou Luo
- Department of Maternal and Child Health, School of Public Health, Central South University, Changsha, China
| | - Xin Zhang
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Chunyan Luo
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai Institutes of Preventive Medicine, Shanghai, China
| | - Hong Wang
- Chongqing Medical University, Chongqing, China
| | | | - Dehong Pan
- Liaoning Health Supervision Bureau, Shenyang, China
| | - Jin Jing
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yinglin Wu
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Ruijie Wang
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Yinghua Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China.
| | - Yajun Chen
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, China.
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Hou J, Liu X, Tu R, Dong X, Zhai Z, Mao Z, Huo W, Chen G, Xiang H, Guo Y, Li S, Wang C. Long-term exposure to ambient air pollution attenuated the association of physical activity with metabolic syndrome in rural Chinese adults: A cross-sectional study. ENVIRONMENT INTERNATIONAL 2020; 136:105459. [PMID: 31931348 DOI: 10.1016/j.envint.2020.105459] [Citation(s) in RCA: 74] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 11/27/2019] [Accepted: 01/02/2020] [Indexed: 06/10/2023]
Abstract
BACKGROUND Long-term exposure to ambient air pollution and physical activity are linked to metabolic syndrome (MetS). However, the joint effect of physical activity and ambient air pollution on MetS remains largely unknown in rural Chinese adult population. METHODS In this study, 39 089 individuals were included from the Henan Rural Cohort study that recruited 39 259 individuals at the baseline. Participants' exposure to air pollutants (including particulate matter with an aerodynamic diameter ≤ 1.0 µm (PM1), ≤2.5 µm (PM2.5), or ≤ 10 µm (PM10) and nitrogen dioxide (NO2)) were evaluated by using a spatiotemporal model based on satellites data. Individuals were defined as MetS according to the recommendation of the Joint Interim Societies. Physical activity-metabolic equivalent (MET) was calculated based on the formula of MET coefficient of activity × duration (hour per time) × frequency (times per week). Generalized linear models were used to analyze the individual air pollutant or physical activity and their interaction on MetS. Interaction effects of individual air pollutant and physical activity on MetS were assessed by using Interaction plots which exhibited the estimated effect of physical activity on MetS as a function of individual air pollutant. RESULTS The prevalence of MetS was 30.8%. The adjusted odd ratio of MetS with a per 5 µg/m3 increase in PM1, PM2.5, PM10, NO2 or a 10 MET (hour/day) of physical activity increment was 1.251(1.199, 1.306), 1.424(1.360, 1.491), 1.228(1.203, 1.254), 1.408(1.363, 1.455) or 0.814(0.796, 0.833). The protective effect of physical activity on MetS was decreased with accompanying air pollutant concentrations increased. CONCLUSIONS The results indicated that long-term exposure to ambient air pollutants related to increased risk of MetS and physical activity attenuated the effects of ambient air pollutants on increased risk for MetS.
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Affiliation(s)
- Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Runqi Tu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xiaokang Dong
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Zhihan Zhai
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Gongbo Chen
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, PR China
| | - Hao Xiang
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, PR China
| | - Yuming Guo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China.
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74
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Yang BY, Liu KK, Markevych I, Knibbs LD, Bloom MS, Dharmage SC, Lin S, Morawska L, Heinrich J, Jalaludin B, Gao M, Guo Y, Zhou Y, Huang WZ, Yu HY, Zeng XW, Hu LW, Hu Q, Dong GH. Association between residential greenness and metabolic syndrome in Chinese adults. ENVIRONMENT INTERNATIONAL 2020; 135:105388. [PMID: 31837524 DOI: 10.1016/j.envint.2019.105388] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 11/28/2019] [Accepted: 12/02/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Residing in greener areas has several health benefits, but no study to date has examined the effects of greenness on metabolic syndrome (MetS). We aimed to assess associations between residential greenness and MetS prevalence in China, and to explore whether air pollution and physical activity mediated any observed associations. METHODS We analyzed data from 15,477 adults who participated in the 33 Communities Chinese Health Study during 2009. We defined MetS according to standard guidelines for Chinese populations. Residential greenness was estimated using the Normalized Difference Vegetation Index (NDVI), the Soil Adjusted Vegetation Index (SAVI), and the Vegetation Continuous Field (VCF). We used generalized linear mixed models to assess the associations between greenness and MetS, and mediation analyses to explore potential mechanisms underlying the associations. RESULTS Higher greenness levels were associated with lower odds of MetS [e.g., for every interquartile range increase of NDVI500-m, SAVI500-m, and VCF500-m, the adjusted odds ratio of MetS was 0.81 (95% confidence interval: 0.70-0.93), 0.80 (95% confidence interval: 0.69-0.93), and 0.91 (95% confidence interval: 0.83-1.00), respectively]. The direction and the magnitude of the associations persisted in several sensitivity analyses. Stratified analyses showed that age and household income modified the associations, with greater effect estimates observed in participants younger than 65 years old or those with higher household income. Particulate matter with an aerodynamic diameter ≤10 μm, nitrogen dioxide, and ozone mediated 2.1-20.3% of the associations between greenness and MetS; no evidence of mediation was observed for physical activity. CONCLUSIONS Our findings suggest a beneficial association for residential greenness and MetS in Chinese urban dwellers, especially for participants younger than 65 years old and those with higher household income. Particulate matter with an aerodynamic diameter ≤10 μm, nitrogen dioxide and ozone, but not physical activity, may only partially mediate the association.
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Affiliation(s)
- Bo-Yi Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Kang-Kang Liu
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Iana Markevych
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336 Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
| | - Luke D Knibbs
- School of Public Health, The University of Queensland, Herston, Queensland 4006, Australia
| | - Michael S Bloom
- Departments of Environmental Health Sciences and Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, NY 12144, USA
| | - Shaymali C Dharmage
- Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population & Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; Murdoch Children Research Institute, Melbourne, VIC 3010, Australia
| | - Shao Lin
- Departments of Environmental Health Sciences and Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, NY 12144, USA
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology (QUT), GPO Box 2434, Brisbane, Queensland 4001, Australia
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336 Munich, Germany; Comprehensive Pneumology Center Munich, German Center for Lung Research, Ziemssenstraße 1, 80336 Munich, Germany
| | - Bin Jalaludin
- Centre for Air Quality and Health Research and Evaluation, Glebe, NSW 2037, Australia; Population Health, South Western Sydney Local Health District, Liverpool, NSW 2170, Australia; Ingham Institute for Applied Medical Research, Liverpool, NSW 2170, Australia; School of Public Health and Community Medicine, The University of New South Wales, Kensington, NSW 2052, Australia
| | - Meng Gao
- Department of Geography, Hong Kong Baptist University, Hong Kong Special Administrative Region
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Yang Zhou
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Wen-Zhong Huang
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Hong-Yao Yu
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiao-Wen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Li-Wen Hu
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Qiang Hu
- Department of Pediatric Surgery, Weifang People's Hospital, Weifang 261041, China.
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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Association of urinary polycyclic aromatic hydrocarbons and obesity in children aged 3-18: Canadian Health Measures Survey 2009-2015. J Dev Orig Health Dis 2019; 11:623-631. [PMID: 31806062 DOI: 10.1017/s2040174419000825] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Polycyclic aromatic hydrocarbons (PAHs) may contribute to obesity. Childhood obesity is a strong predictor of adult obesity and morbidity; however, the relationship between PAHs and obesity in young children (e.g., aged 3-5) has not been studied. We examined the association between urinary PAH metabolites and measures of obesity in children. We analyzed data from 3667 children aged 3-18 years who participated in the Canadian Health Measures Survey (CHMS, 2009-2015). We ran separate multivariable linear models to estimate the association between quartiles of PAH metabolites and each of body mass index (BMI) percentile, waist circumference (WC), and waist-to-height ratio (WHtR) in the total population, as well as in the age subgroups 3-5, 6-11, and 12-18, adjusting for age, sex, ethnicity, education, income quintile, diet, creatinine, and exposure to environmental tobacco smoke. A multinomial logistic regression model estimated adjusted odds ratios for risk of central obesity. BMI, WC, and WHtR were positively associated with total PAH and naphthalene metabolites in the total population aged 3-18 and in age groups 6-11 and 12-18. In 3-5 year olds, WHtR, but not BMI, was significantly associated with total PAH, naphthalene, and phenanthrene metabolites. Overall, those in the highest quartile for naphthalene or total PAH metabolites had three times greater odds of having central obesity compared with those in the lowest quartile. Urinary PAH metabolites are associated with WHtR, an indicator of central obesity and predictor of health risks associated with obesity, in children as young as 3-5.
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76
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Li A, Pei L, Zhao M, Xu J, Mei Y, Li R, Xu Q. Investigating potential associations between O3 exposure and lipid profiles: A longitudinal study of older adults in Beijing. ENVIRONMENT INTERNATIONAL 2019; 133:105135. [PMID: 31491592 DOI: 10.1016/j.envint.2019.105135] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2019] [Revised: 08/23/2019] [Accepted: 08/26/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Little information exists on the lipidemic effects of ozone exposure. Few studies have focused on the different patterns of the association among older adults population, and little attention has been given to comprehensive lipid indices when evaluating the effect of O3 exposure on the metabolism. METHODS We conducted a longitudinal study involving 201 older adults in Beijing, China between 2016 and 2018. A mixed regression model was applied with random effects to investigate the relationship between O3 and lipid profiles. RESULTS O3 exposure positively correlated with TC, LDL-C, CRI-I, CRI-II and AC at short-term and medium-term exposure periods. The largest increases in TC, LDL-C, CRI-I and CRI-II were found in the 28-days moving average indicating accumulative effects over prolonged exposure period. A 10 μg/m3 increase of O3 at the 28-days moving average was associated with a significant increase of 3.9% (95% CI: 1.0, 6.9) in TC, 8.2% (95% CI: 4.2, 12.4) in LDL-C, 4.8% (95% CI: 1.1, 8.5) in CRI-I and 7.0% (95% CI: 2.7, 11.5) in CRI-II. Stratification by health status and characteristics revealed different patterns of lipid changes among older adults, lipid status, age, sex and BMI may modify the relationship between O3 exposure and lipid profiles. CONCLUSIONS Our findings suggest that short-term and medium-term O3 exposure is associated with lipid profiles abnormalities among the older adults. Evidence also suggests there are patterns within population which differ according to both health status and demographic characteristics.
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Affiliation(s)
- Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Lu Pei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Runkui Li
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China.
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77
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Liu F, Guo Y, Liu Y, Chen G, Wang Y, Xue X, Liu S, Huo W, Mao Z, Hou Y, Lu Y, Wang C, Xiang H, Li S. Associations of long-term exposure to PM 1, PM 2.5, NO 2 with type 2 diabetes mellitus prevalence and fasting blood glucose levels in Chinese rural populations. ENVIRONMENT INTERNATIONAL 2019; 133:105213. [PMID: 31654916 PMCID: PMC6853163 DOI: 10.1016/j.envint.2019.105213] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 09/19/2019] [Accepted: 09/22/2019] [Indexed: 05/07/2023]
Abstract
OBJECTIVES To evaluate the associations between long-term exposure to particulate matter with an aerodynamic diameter ≤1.0 μm and ≤2.5 μm (PM1 and PM2.5), nitrogen dioxide (NO2) and type 2 diabetes prevalence and fasting blood glucose levels in Chinese rural populations. MATERIAL AND METHODS A total of 39, 259 participants were enrolled in The Henan Rural Cohort study. Questionnaires and medical examination were conducted from July 2015 to September 2017 in rural areas of Henan province, China. Three-year average residential exposure levels of PM1, PM2.5, NO2 for each subject were estimated by a spatiotemporal model. Logistic regression and linear regression models were applied to estimate the associations between PM1, PM2.5, NO2 exposure and type 2 diabetes prevalence and fasting blood glucose levels. RESULTS The mean 3-year residential exposure concentrations of PM1, PM2.5 and NO2 was 57.4 μg/m3, 73.4 μg/m3 and 39.9 μg/m3, respectively. Higher exposure concentrations of PM1, PM2.5, NO2 by 1 μg/m3 was positively related to a 4.0% (95%CIs: 1.026, 1.054), 6.8% (1.052, 1.084) and 5.0% (1.039, 1.061) increase in odds of type 2 diabetes in the final adjusted models. Besides, a 1 μg/m3 increase of PM1, PM2.5 and NO2 was related to a 0.020 mmol/L (95%CIs: 0.014, 0.026), 0.036 mmol/L (95%CIs: 0.030, 0.042) and 0.030 mmol/L (95%CIs: 0.026, 0.034) mmol/L higher fasting blood glucose levels. CONCLUSIONS Higher exposure concentrations of air pollutants were positively related to the increased odds of type 2 diabetes, as well as higher fasting blood glucose levels in Chinese rural populations.
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Affiliation(s)
- Feifei Liu
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Yisi Liu
- Department of Environmental and Occupational Health Sciences, University of Washington, 1959 NE Pacific Street, Seattle, USA
| | - Gongbo Chen
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Yuxin Wang
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Xiaowei Xue
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Suyang Liu
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Yitan Hou
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Yuanan Lu
- Environmental Health Laboratory, Department of Public Health Sciences, University Hawaii at Manoa, 1960 East West Rd, Biomed Bldg, D105 Honolulu, USA
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
| | - Hao Xiang
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China.
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
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Karimi A, Shirmardi M, Hadei M, Birgani YT, Neisi A, Takdastan A, Goudarzi G. Concentrations and health effects of short- and long-term exposure to PM 2.5, NO 2, and O 3 in ambient air of Ahvaz city, Iran (2014-2017). ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2019; 180:542-548. [PMID: 31128552 DOI: 10.1016/j.ecoenv.2019.05.026] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 03/08/2019] [Accepted: 05/09/2019] [Indexed: 06/09/2023]
Abstract
The primary objective of the present study was to evaluate the concentrations and short and long-term excess mortality attributed to PM2.5, NO2, and O3 observed in ambient air of Ahvaz during March 2014 to March 2017 period using the AirQ + software developed by the World Health Organization (WHO), which is updated in 2016 by WHO European Centre for Environment and Health. The hourly concentrations of PM2.5, O3, and NO2 measured at different regulatory monitoring network stations in Ahvaz city were obtained from the Department of Environment (DOE) of the city. Then, for various air quality monitoring stations, the 24-h average concentration of PM2.5, 1-h average of NO2 concentration, and maximum daily 8-h O3 concentrations were calculated using Excel 2010 software. When the maximum daily 8-h ozone means exceeding the value of 35, it was subtracted from 35 to calculate SOMO35 indicator for modeling. Validation of air quality data was performed according to the Aphekom and WHO's methodologies for health impact assessment of air pollution. Year-specific city population and baseline incidence of the health outcomes were obtained. The three-year averages of PM2.5, NO2, and O3 concentrations were 68.95 (±39.86) μg/m3, 135.90 (±47.82) μg/m3, and 38.63 (±12.83) parts-per-billion-volume (ppbv), respectively. SOMO35 values of ozone were 6596.66, 3411.78, and 470.88 ppbv in 2014-2015, 2015-2016, and 2016-2017 years, respectively. The AP and number of natural deaths due to NO2 were higher than PM2.5 except the last year (2016-2017), causing about 39.18%, 40.73%, and 14.39% of deaths within the first, the second, and the third year, respectively. However, for the last year, the natural mortality for PM2.5 was higher than NO2 (34.46% versus 14.39%). The total number of natural mortality caused by PM2.5 and NO2 in all years was 4061 and 4391, respectively. A significant number of deaths was estimated to be attributed to the given air pollutants. It can be concluded that by designing and implementing air pollution control strategies and actions, both health effects and economic losses will be prevented.
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Affiliation(s)
- Afsaneh Karimi
- Department of Environmental Health Engineering, Health Faculty, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Mohammad Shirmardi
- Social Determinants of Health Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran; Environmental Health Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran; Department of Environmental Health Engineering, School of Public Health, Babol University of Medical Sciences, Babol, Iran
| | - Mostafa Hadei
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Yaser Tahmasebi Birgani
- Environmental Technologies Research Center (ETRC), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Abdolkazem Neisi
- Environmental Technologies Research Center (ETRC), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Afshin Takdastan
- Environmental Technologies Research Center (ETRC), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Gholamreza Goudarzi
- Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
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Kwon S, Crowley G, Caraher EJ, Haider SH, Lam R, Veerappan A, Yang L, Liu M, Zeig-Owens R, Schwartz TM, Prezant DJ, Nolan A. Validation of Predictive Metabolic Syndrome Biomarkers of World Trade Center Lung Injury: A 16-Year Longitudinal Study. Chest 2019; 156:486-496. [PMID: 30836056 PMCID: PMC6717118 DOI: 10.1016/j.chest.2019.02.019] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 01/07/2019] [Accepted: 02/13/2019] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Metabolic syndrome (MetSyn) predicted future development of World Trade Center lung injury (WTC-LI) in a subgroup of firefighters who never smoked and were male. An intracohort validation of MetSyn as a predictor of WTC-LI is examined in the cohort exposed to the World Trade Center (WTC) that has been followed longitudinally for 16 years. METHODS Results of pulmonary function tests (n = 98,221) in workers exposed to the WTC (n = 9,566) were evaluated. A baseline cohort of firefighters who had normal FEV1 before 9/11 and who had had serum drawn before site closure on July 24, 2002 (n = 7,487) was investigated. Case subjects with WTC-LI (n = 1,208) were identified if they had at least two measured instances of FEV1 less than the lower limit of normal (LLN). Cox proportional hazards modeled early MetSyn biomarker ability to predict development of FEV1 less than the LLN. RESULTS Case subjects were more likely to smoke, be highly exposed, and have MetSyn. There was a significant exposure dose response; the individuals most highly exposed had a 30.1% increased risk of developing WTC-LI, having MetSyn increased risk of developing WTC-LI by 55.7%, and smoking increased risk by 15.2%. There was significant interaction between smoking and exposure. CONCLUSIONS We validated the usefulness of MetSyn to predict future WTC-LI in a larger population of individuals who were exposed. MetSyn defined by dyslipidemia, insulin resistance, and cardiovascular disease suggests that systemic inflammation can contribute to future lung function loss.
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Affiliation(s)
- Sophia Kwon
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, New York, NY
| | - George Crowley
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, New York, NY
| | - Erin J Caraher
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, New York, NY
| | - Syed Hissam Haider
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, New York, NY
| | - Rachel Lam
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, New York, NY
| | - Arul Veerappan
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, New York, NY
| | - Lei Yang
- Division of Biostatistics, Department of Population Health, New York University School of Medicine, New York, NY
| | - Mengling Liu
- Division of Biostatistics, Department of Population Health, New York University School of Medicine, New York, NY
| | - Rachel Zeig-Owens
- Bureau of Health Services and Office of Medical Affairs, Fire Department of New York, New York, NY; Pulmonary Medicine Division, Department of Medicine, Montefiore Medical Center and Albert Einstein College of Medicine, New York, NY
| | - Theresa M Schwartz
- Bureau of Health Services and Office of Medical Affairs, Fire Department of New York, New York, NY; Pulmonary Medicine Division, Department of Medicine, Montefiore Medical Center and Albert Einstein College of Medicine, New York, NY
| | - David J Prezant
- Bureau of Health Services and Office of Medical Affairs, Fire Department of New York, New York, NY; Pulmonary Medicine Division, Department of Medicine, Montefiore Medical Center and Albert Einstein College of Medicine, New York, NY
| | - Anna Nolan
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, New York, NY; Department of Environmental Medicine, New York University School of Medicine, New York, NY; Bureau of Health Services and Office of Medical Affairs, Fire Department of New York, New York, NY.
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Li N, Chen G, Liu F, Mao S, Liu Y, Hou Y, Lu Y, Liu S, Wang C, Xiang H, Guo Y, Li S. Associations of long-term exposure to ambient PM 1 with hypertension and blood pressure in rural Chinese population: The Henan rural cohort study. ENVIRONMENT INTERNATIONAL 2019; 128:95-102. [PMID: 31035115 PMCID: PMC7086153 DOI: 10.1016/j.envint.2019.04.037] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 04/16/2019] [Accepted: 04/16/2019] [Indexed: 05/20/2023]
Abstract
BACKGROUND The epidemiological evidence on relationships between long-term exposure to particulate matter and hypertension and blood pressure has been inconclusive. Limited evidence was available for particulate matter with an aerodynamic diameter ≤ 1 μm (PM1) in rural areas of developing countries. OBJECTIVE This study aimed to investigate the associations between long-term exposure to PM1 and hypertension and blood pressure among rural Chinese population. METHODS This study included 39,259 participants who had completed the baseline survey from Henan Rural Cohort. Participants' exposure to PM1 was assessed by a satellite-based spatiotemporal model. The binary logistic regression model was used to examine the association between long-term PM1 exposure and hypertension, and multivariable linear regression model was used to investigate the associations between long-term PM1 exposure and systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP). Moreover, we examined potential effect modifications by demographic, lifestyle and diet factors. RESULTS The mean concentration of PM1 for all participants during the 3-year before baseline survey was 59.98 μg/m3. Each 1 μg/m3 increase in PM1 concentration was significantly associated with an increase of 4.3% [Odds ratio(OR) = 1.043, 95% confidence interval(CI): 1.033, 1.053] in odds for hypertension, an increase of 0.401 mm Hg (95% CI, 0.335, 0.467), 0.328 mm Hg (95% CI, 0.288, 0.369), 0.353 mm Hg (95% CI, 0.307, 0.399) and 0.073 mm Hg (95% CI, 0.030, 0.116) in SBP, DBP, MAP and PP, respectively. Further stratified analyses showed that the effect of PM1 on hypertension and blood pressure could be modified by sex, lifestyle and diet. CONCLUSIONS This study suggests that long-term exposure to ambient PM1 increases the risk of hypertension and is associated with elevations in blood pressure in rural Chinese adults, especially in male and those with unhealthy habits.
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Affiliation(s)
- Na Li
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Gongbo Chen
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Feifei Liu
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Shuyuan Mao
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Yisi Liu
- Department of Environmental and Occupational Health Sciences, University of Washington, 1959 NE Pacific Street, Seattle, USA
| | - Yitan Hou
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Yuanan Lu
- Environmental Health Laboratory, Department of Public Health Sciences, University Hawaii at Manoa, 1960 East West Rd, Biomed Bldg, D105, Honolulu, USA
| | - Suyang Liu
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
| | - Hao Xiang
- Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Road, Wuhan, China.
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
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Yang BY, Markevych I, Heinrich J, Bloom MS, Qian Z, Geiger SD, Vaughn M, Liu S, Guo Y, Dharmage SC, Jalaludin B, Knibbs LD, Chen D, Jalava P, Lin S, Hung-Lam Yim S, Liu KK, Zeng XW, Hu LW, Dong GH. Residential greenness and blood lipids in urban-dwelling adults: The 33 Communities Chinese Health Study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2019; 250:14-22. [PMID: 30981931 DOI: 10.1016/j.envpol.2019.03.128] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 03/29/2019] [Accepted: 03/31/2019] [Indexed: 06/09/2023]
Abstract
While exposure to places with higher greenness shows health benefits, evidence is scarce on its lipidemic effects. We assessed the associations between residential greenness and blood lipids and effect mediations by air pollution, physical activity, and adiposity in China. Our study included 15,477 adults from the population-based 33 Communities Chinese Health Study, conducted between April and December 2009, in Northeastern China. We measured total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). Residential greenness was estimated using two satellite-derived vegetation indices - the Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI). We used both nitrogen dioxide (NO2) and particles ≤2.5 μm in aerodynamic diameter (PM2.5) as proxies of outdoor air pollution. Associations were assessed using linear mixed effects regression models and logistic mixed effects regression models, and mediation analyses were also performed. Living in higher greenness areas was consistently associated with lower TC, TG, and LDL-C levels and higher HDL-C levels (e.g., change in TC, TG, LDL-C, and HDL-C per 0.1-unit increase in NDVI500-m was -1.52%, -3.05%, -1.91%, and 0.52%, respectively). Similar results were obtained for the corresponding dyslipidemias. These associations were generally stronger in women and older adults. While educational levels showed effect modifications, the effect pattern was inconsistent. Both outdoor air pollution and body mass index mediated 9.1-62.3% and 5.6-40.1% of the associations for greenness and blood lipids, respectively, however, physical activity did not. Our results suggest beneficial associations between residing in places with higher greenness and blood lipid levels, especially in women and the elder individuals. The associations were partly mediated by lower air pollution and adiposity.
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Affiliation(s)
- Bo-Yi Yang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Iana Markevych
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336, Munich, Germany; Comprehensive Pneumology Center Munich, German Center for Lung Research, Ziemssenstraße 1, 80336, Munich, Germany
| | - Michael S Bloom
- Department of Environmental Health Sciences and Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, NY, 12144, USA
| | - Zhengmin Qian
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, 63104, USA
| | - Sarah Dee Geiger
- School of Nursing and Health Studies, Northern Illinois University, DeKalb, 60115, USA
| | - Michael Vaughn
- School of Social Work, College for Public Health & Social Justice, Saint Louis University, Saint Louis, 63103, USA
| | - Shan Liu
- NHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment 7 Panjiayuan Nanli, Room 312, Beijing, 100021, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Shyamali C Dharmage
- Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population & Global Health, The University of Melbourne, Melbourne, VIC, 3010, Australia; Murdoch Children Research Institute, Melbourne, VIC, 3010 Australia
| | - Bin Jalaludin
- Centre for Air Quality and Health Research and Evaluation, Glebe, NSW, 2037, Australia; Population Health, South Western Sydney Local Health District, Liverpool, NSW, 2170, Australia; Ingham Institute for Applied Medical Research, Liverpool, NSW, 2170, Australia; School of Public Health and Community Medicine, The University of New South Wales, Kensington, NSW, 2052, Australia
| | - Luke D Knibbs
- School of Public Health, The University of Queensland, Herston, Queensland, 4006, Australia
| | - Da Chen
- School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, 510632, China
| | - Pasi Jalava
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, FI 70211, Finland
| | - Shao Lin
- Department of Environmental Health Sciences and Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, NY, 12144, USA
| | - Steve Hung-Lam Yim
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, Shatin, N.T, Hong Kong, China; Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, N.T, Hong Kong, China; Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, N.T, Hong Kong, China
| | - Kang-Kang Liu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiao-Wen Zeng
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Li-Wen Hu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Guang-Hui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
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Guo X, Yang Q, Zhang W, Chen Y, Ren J, Gao A. Associations of blood levels of trace elements and heavy metals with metabolic syndrome in Chinese male adults with microRNA as mediators involved. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2019; 248:66-73. [PMID: 30771749 DOI: 10.1016/j.envpol.2019.02.015] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Revised: 02/01/2019] [Accepted: 02/04/2019] [Indexed: 06/09/2023]
Abstract
Metabolic syndrome (MetS) is a global health problem with an increasing prevalence. However, effects of trace elements and heavy metals on MetS and the mechanism underlying this effect are poorly understood. A preliminary cross-sectional study was conducted in 2015. Significantly higher blood concentrations of lead (Pb), cadmium (Cd), copper (Cu), and selenium (Se) were observed in the MetS group. With a priori adjustment for age, the concentration of Cu and Se in the blood was associated with a 2.56 - fold [95% confidence interval (CI), 1.11, 5.92] and 3.31 - fold (95% CI, 1.4, 7.82) increased risk of MetS, respectively. Moreover, increased blood Se concentrations were associated with body mass index (BMI) [odds ratio (OR): 2.56; 95% CI, 1.11, 5.93], high blood pressure [for both systolic and diastolic blood pressures (SBP and DBP); OR: 3.82; 95% CI, 1.47, 7.31 for SBP and OR: 2.56; 95% CI, 1.18, 5.59 for DBP], and hypertriglyceridemia (OR: 3.3; 95% CI, 1.51, 7.2). In addition, the expression of miR-21-5p, miR-122-5p, and miR-146a-5p was significantly higher in subjects with MetS than those without MetS. Increased expression of miR-21-5p was significantly associated with increased SBP (β = 5.28; 95% CI, 0.63, 9.94) and DBP (β = 4.17; 95% CI, 0.68, 7.66). Moreover, Cu was positively associated with miR-21-5p (β = 3.02; 95% CI, 0.07, 5.95), whereas Se was positively associated with miR-122-5p (β = 2.7; 95% CI, 0.64, 4.76). The bootstrapping mediation models indicated that miR-21-5p partially mediated the relationships between Cu level and SBP/DBP. This study suggested that Cu and Se were both associated with MetS, and miR-21-5p participated in the development of MetS associated with Cu.
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Affiliation(s)
- Xiaoli Guo
- Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China
| | - Qiaoyun Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, PR China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin, 300070, PR China; National Demonstration Center for Experimental Preventive Medicine Education (Tianjin Medical University), Tianjin, 300070, PR China
| | - Wei Zhang
- Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China
| | - Yujiao Chen
- Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China
| | - Jing Ren
- Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China
| | - Ai Gao
- Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, 100069, PR China.
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83
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Ding S, Yuan C, Si B, Wang M, Da S, Bai L, Wu W. Combined effects of ambient particulate matter exposure and a high-fat diet on oxidative stress and steatohepatitis in mice. PLoS One 2019; 14:e0214680. [PMID: 30921449 PMCID: PMC6438678 DOI: 10.1371/journal.pone.0214680] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Accepted: 03/18/2019] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Chronic exposure to ambient particulate matter with aerodynamic diameters < 2.5 (PM2.5) induces oxidative injury and liver pathogenesis. The present study assessed the effect and mechanism of long-term, real-world airborne particulate matter (PM) exposure on oxidative stress and hepatic steatosis in the context of a standard chow diet (STD) and a high-fat diet (HFD); the study further explored whether a combination of PM exposure and HFD treatment exacerbates the adverse effects in mice. METHODS C57BL/6J mice fed with STD or HFD (41.26% kcal fat) were exposed to PM or filtered air (FA) for 5 months. Lipid metabolism, oxidative stress and liver pathogenesis were evaluated. Real-time PCR and western blotting were performed to determine gene expression and molecular signal transduction in liver. RESULTS Chronic airborne PM exposure impaired oxidative homeostasis, caused inflammation and induced hepatic steatosis in mice. Further investigation found that exposure to real-world PM increased the expression of hepatic Nrf2 and Nrf2-regulated antioxidant enzyme gene. The increased protein expression of the sterol regulatory element binding protein-1c (SREBP-1c) and fatty acid synthase (FAS) in the liver were also observed in PM-exposed groups. Furthermore, the combination of PM exposure and HFD treatment caused a synergistic effect on the changes of lipid accumulation oxidative stress, inflammation in the mouse liver. CONCLUSIONS Through in vivo study, we reveal that the combination of real-world ambient PM exposure and HFD treatment aggravates hepatic lipid metabolism disorders, inflammation and oxidative stress. PM exposure may accelerate the progression to non-alcoholic steatohepatitis by regulating SREBP-1c/FAS regulatory axis.
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Affiliation(s)
- Shibin Ding
- Department of nutrition and food hygiene, school of public health, Xinxiang Medical University, Xinxiang, Henan Province, PR China
- Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, Xinxiang Medical University, Xinxiang, Henan Province, PR China
- * E-mail:
| | - Chunyan Yuan
- Department of nutrition and food hygiene, school of public health, Xinxiang Medical University, Xinxiang, Henan Province, PR China
| | - Bingjie Si
- Department of nutrition and food hygiene, school of public health, Xinxiang Medical University, Xinxiang, Henan Province, PR China
| | - Mengruo Wang
- Department of nutrition and food hygiene, school of public health, Xinxiang Medical University, Xinxiang, Henan Province, PR China
| | - Shuyan Da
- Department of nutrition and food hygiene, school of public health, Xinxiang Medical University, Xinxiang, Henan Province, PR China
| | - Lanxin Bai
- Department of nutrition and food hygiene, school of public health, Xinxiang Medical University, Xinxiang, Henan Province, PR China
| | - Weidong Wu
- Department of nutrition and food hygiene, school of public health, Xinxiang Medical University, Xinxiang, Henan Province, PR China
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84
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Ho HC, Wong MS, Man HY, Shi Y, Abbas S. Neighborhood-based subjective environmental vulnerability index for community health assessment: Development, validation and evaluation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 654:1082-1090. [PMID: 30841383 DOI: 10.1016/j.scitotenv.2018.11.136] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 10/29/2018] [Accepted: 11/09/2018] [Indexed: 06/09/2023]
Abstract
Neighborhood-based environmental vulnerability is significantly associated with long-term community health impacts. Previous studies have quantified environmental vulnerability using objective environmental datasets. However, environmental cognition among a population may influence subjective feelings of environmental vulnerability, and this can be associated with community health risk. In this study, a mixed-methods approach was applied to estimate neighborhood-based environmental vulnerability based on objective environmental measures and subjective environmental understanding from a local population. The synergistic use of both qualitative and quantitative data resulted in a "subjective environmental vulnerability" index which can demonstrate environmental deprivation across Hong Kong. The resultant maps were compared with a mortality dataset between 2007 and 2014, based on a case-series analysis. The case-series analysis indicated that using a subjective environmental vulnerability index as an approach for neighborhood mapping is able to estimate the community health risk across Hong Kong. In particular, the following types of cause-specific mortality have significant association with the subjective environmental vulnerability index: 1) mortality associated with mental and behavioral disorders, 2) cardiovascular mortality, 3) respiratory mortality, and 4) mortality associated with diseases of the digestive system. In conclusion, the use of a subjective environmental vulnerability index can be implemented within a community health planning program, especially to reduce long-term adverse impacts on population with mental impairment.
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Affiliation(s)
- Hung Chak Ho
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong; Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
| | - Man Sing Wong
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong; Research Institute for Sustainable Urban Development, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
| | - Ho Yin Man
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | - Yuan Shi
- School of Architecture, The Chinese University of Hong Kong, Sha Tin, Hong Kong
| | - Sawaid Abbas
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
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85
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Yang M, Chu C, Bloom MS, Li S, Chen G, Heinrich J, Markevych I, Knibbs LD, Bowatte G, Dharmage SC, Komppula M, Leskinen A, Hirvonen MR, Roponen M, Jalava P, Wang SQ, Lin S, Zeng XW, Hu LW, Liu KK, Yang BY, Chen W, Guo Y, Dong GH. Is smaller worse? New insights about associations of PM 1 and respiratory health in children and adolescents. ENVIRONMENT INTERNATIONAL 2018; 120:516-524. [PMID: 30153645 DOI: 10.1016/j.envint.2018.08.027] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 07/27/2018] [Accepted: 08/09/2018] [Indexed: 06/08/2023]
Abstract
BACKGROUND AND OBJECTIVES Little is known about PM1 effects on respiratory health, relative to larger size fractions (PM2.5). To address this literature gap, we assessed associations between PM1 exposure and asthmatic symptoms in Chinese children and adolescents, compared with PM2.5. METHODS A total of 59,754 children, aged 2-17 years, were recruited from 94 kindergartens, elementary and middle schools in the Seven Northeast Cities (SNEC) study, during 2012-2013. We obtained information on asthma and asthma-related symptoms including wheeze, persistent phlegm, and persistent cough using a standardized questionnaire developed by the American Thoracic Society. PM1 and PM2.5 concentrations were estimated using a spatial statistical model matched to the children's geocoded home addresses. To examine the associations, mixed models with school/kindergarten as random intercept were used, controlling for covariates. RESULTS Odds ratios (ORs) of doctor-diagnosed asthma associated with a 10-μg/m3 increase for PM1 and PM2.5 were 1.56 (95% CI: 1.46-1.66) and 1.50 (1.41-1.59), respectively, and similar pattern were observed for other outcomes. Interaction analyses indicated that boys and the individuals with an allergic predisposition may be vulnerable subgroups. For example, among children with allergic predisposition, the ORs for doctor diagnosed asthma per 10 μg/m3 increase in PM1 was 1.71 (95% CI: 1.60-1.83), which was stronger than in their counterparts (1.46; 1.37-1.56) (pfor interaction < 0.05). CONCLUSIONS This study indicated that long-term exposure to PM1 may increase the risk of asthma and asthma-related symptoms, especially among boys and those with allergic predisposition. Furthermore, these positive associations for PM1 were very similar to those for PM2.5.
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Affiliation(s)
- Mo Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, 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
| | - Chu Chu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, 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
| | - Michael S Bloom
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, 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; Department of Environmental Health Sciences and Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY 12144, USA
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Gongbo Chen
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, Ludwig-Maximilian-University, Munich 80336, Germany; Allergy and Lung Health Unit, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC 3052, Australia
| | - Iana Markevych
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, Ludwig-Maximilian-University, Munich 80336, Germany
| | - Luke D Knibbs
- School of Public Health, The University of Queensland, Herston, Queensland 4006, Australia
| | - Gayan Bowatte
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC 3052, Australia
| | - Shyamali C Dharmage
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC 3052, Australia
| | - Mika Komppula
- Finnish Meteorological Institute, Kuopio 70211, Finland
| | - Ari Leskinen
- Finnish Meteorological Institute, Kuopio 70211, Finland; Department of Applied Physics, University of Eastern Finland, Kuopio 70211, Finland
| | - Maija-Riitta Hirvonen
- Department of Environmental and Biological Science, University of Eastern Finland, Kuopio 70211, Finland
| | - Marjut Roponen
- Department of Environmental and Biological Science, University of Eastern Finland, Kuopio 70211, Finland
| | - Pasi Jalava
- Department of Environmental and Biological Science, University of Eastern Finland, Kuopio 70211, Finland
| | - Si-Quan Wang
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Shao Lin
- Department of Environmental Health Sciences and Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY 12144, USA
| | - Xiao-Wen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, 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
| | - Li-Wen Hu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, 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.
| | - Kang-Kang Liu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, 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
| | - Bo-Yi Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, 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
| | - Wen Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, 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
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, 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.
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A New Study on Air Quality Standards: Air Quality Measurement and Evaluation for Jiangsu Province Based on Six Major Air Pollutants. SUSTAINABILITY 2018. [DOI: 10.3390/su10103561] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
China’s current Air Quality Index (AQI) system only considers one air pollutant which has the highest concentration value. In order to comprehensively evaluate the urban air quality of Jiangsu Province, this paper has studied the air quality of 13 cities in that province from April 2015 to March 2018 based on an expanded AQI system that includes six major air pollutants. After expanding the existing air quality evaluation standards of China, this paper has calculated the air quality evaluation scores of cities in Jiangsu Province based on the six major air pollutants by using the improved Fuzzy Comprehensive Evaluation Model. This paper has further analyzed the effectiveness of air pollution control policies in Jiangsu Province and its different cities during the study period. The findings are as follows: there are distinct differences in air quality for different cities in Jiangsu Province; except for coastal cities such as Nantong, Yancheng and Lianyungang, the southern cities of Jiangsu generally have better air quality than the northern cities. The causes of these differences include not only natural factors such as geographical location and wind direction, but also economic factors and energy structure. In addition, air pollution control policies have achieved significant results in Nantong, Changzhou, Wuxi, Yangzhou, Suzhou, Yancheng, Zhenjiang, Tai’an and Lianyungang. Among them, Nantong has seen the biggest improvement, 20.28%; Changzhou and Wuxi have improved their air quality by more than 10%, while Yangzhou, Suzhou, and Yancheng have improved their air quality by more than 5%. However, the air quality of Nanjing, Huai’an, Xuzhou, and Suqian has worsened by different degrees compared that of the last period within the beginning period, during which Suqian’s air quality has declined by 20.07% and Xuzhou’s by 16.32%.
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Abraham E, Rousseaux S, Agier L, Giorgis-Allemand L, Tost J, Galineau J, Hulin A, Siroux V, Vaiman D, Charles MA, Heude B, Forhan A, Schwartz J, Chuffart F, Bourova-Flin E, Khochbin S, Slama R, Lepeule J. Pregnancy exposure to atmospheric pollution and meteorological conditions and placental DNA methylation. ENVIRONMENT INTERNATIONAL 2018; 118:334-347. [PMID: 29935799 DOI: 10.1016/j.envint.2018.05.007] [Citation(s) in RCA: 97] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Revised: 05/02/2018] [Accepted: 05/02/2018] [Indexed: 05/17/2023]
Abstract
BACKGROUND Air pollution exposure represents a major health threat to the developing foetus. DNA methylation is one of the most well-known molecular determinants of the epigenetic status of cells. Blood DNA methylation has been proven sensitive to air pollutants, but the molecular impact of air pollution on new-borns has so far received little attention. OBJECTIVES We investigated whether nitrogen dioxide (NO2), particulate matter (PM10), temperature and humidity during pregnancy are associated with differences in placental DNA methylation levels. METHODS Whole-genome DNA-methylation was measured using the Illumina's Infinium HumanMethylation450 BeadChip in the placenta of 668 newborns from the EDEN cohort. We designed an original strategy using a priori biological information to focus on candidate genes with a specific expression pattern in placenta (active or silent) combined with an agnostic epigenome-wide association study (EWAS). We used robust linear regression to identify CpGs and differentially methylated regions (DMR) associated with each exposure during short- and long-term time-windows. RESULTS The candidate genes approach identified nine CpGs mapping to 9 genes associated with prenatal NO2 and PM10 exposure [false discovery rate (FDR) p < 0.05]. Among these, the methylation level of 2 CpGs located in ADORA2B remained significantly associated with NO2 exposure during the 2nd trimester and whole pregnancy in the EWAS (FDR p < 0.05). EWAS further revealed associations between the environmental exposures under study and variations of DNA methylation of 4 other CpGs. We further identified 27 DMRs significantly (FDR p < 0.05) associated with air pollutants exposure and 13 DMRs with meteorological conditions. CONCLUSIONS The methylation of ADORA2B, a gene whose expression was previously associated with hypoxia and pre-eclampsia, was consistently found here sensitive to atmospheric pollutants. In addition, air pollutants were associated to DMRs pointing towards genes previously implicated in preeclampsia, hypertensive and metabolic disorders. These findings demonstrate that air pollutants exposure at levels commonly experienced in the European population are associated with placental gene methylation and provide some mechanistic insight into some of the reported effects of air pollutants on preeclampsia.
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Affiliation(s)
- Emilie Abraham
- Univ. Grenoble Alpes, Inserm, CNRS, IAB, 38000 Grenoble, France
| | | | - Lydiane Agier
- Univ. Grenoble Alpes, Inserm, CNRS, IAB, 38000 Grenoble, France
| | | | - Jörg Tost
- Laboratory for Epigenetics and Environment, Centre National de Recherche en Génomique Humaine, CEA - Institut de Biologie François Jacob, Evry, France
| | | | | | - Valérie Siroux
- Univ. Grenoble Alpes, Inserm, CNRS, IAB, 38000 Grenoble, France
| | - Daniel Vaiman
- Genomics, Epigenetics and Physiopathology of Reproduction, Institut Cochin, U1016 Inserm - UMR 8104 CNRS - Paris-Descartes University, Paris, France
| | - Marie-Aline Charles
- Inserm U1153, Early Origins of Child Health and Development team, Research Center for Epidemiology and Biostatistics Sorbonne Paris Cité (CRESS), Paris Descartes University, Villejuif, France
| | - Barbara Heude
- Inserm U1153, Early Origins of Child Health and Development team, Research Center for Epidemiology and Biostatistics Sorbonne Paris Cité (CRESS), Paris Descartes University, Villejuif, France
| | - Anne Forhan
- Inserm U1153, Early Origins of Child Health and Development team, Research Center for Epidemiology and Biostatistics Sorbonne Paris Cité (CRESS), Paris Descartes University, Villejuif, France
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | | | - Saadi Khochbin
- Univ. Grenoble Alpes, Inserm, CNRS, IAB, 38000 Grenoble, France
| | - Rémy Slama
- Univ. Grenoble Alpes, Inserm, CNRS, IAB, 38000 Grenoble, France
| | - Johanna Lepeule
- Univ. Grenoble Alpes, Inserm, CNRS, IAB, 38000 Grenoble, France.
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