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Associations between metabolic syndrome and anthropogenic heat emissions in northeastern China.
Cong, Jianping; Wang, Le-Bing; Liu, Fang-Jie; Qian, Zhengmin Min; McMillin, Stephen Edward; Vaughn, Michael G; Song, Yimeng; Wang, Shasha; Chen, ShanShan; Xiong, Shimin; Shen, Xubo; Sun, Xiao; Zhou, Yuanzhong; Ho, Hung Chak; Dong, Guang-Hui.
Afiliação
  • Cong J; Department of Internal Medicine, Shenyang Women's and Children's Hospital, Shenyang, 110011, China; Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat
  • Wang LB; Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China.
  • Liu FJ; Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China.
  • Qian ZM; Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO, 63104, USA.
  • McMillin SE; School of Social Work, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO, 63103, USA.
  • Vaughn MG; School of Social Work, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO, 63103, USA.
  • Song Y; Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China.
  • Wang S; College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China.
  • Chen S; Institute of Remote Sensing and Geographic Information System, School of Earth and Space Science, Peking University, Beijing, 100871, China.
  • Xiong S; Department of Epidemiology, School of Public Health, Zunyi Medical University, Zunyi, 563060, China.
  • Shen X; Department of Epidemiology, School of Public Health, Zunyi Medical University, Zunyi, 563060, China.
  • Sun X; Department of Internal Medicine, Shenyang Women's and Children's Hospital, Shenyang, 110011, China. Electronic address: sunxiao-124@163.com.
  • Zhou Y; Department of Epidemiology, School of Public Health, Zunyi Medical University, Zunyi, 563060, China. Electronic address: zhouyuanzhong@163.com.
  • Ho HC; Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China. Electronic address: hcho21@hku.hk.
  • Dong GH; Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China. Electronic address: donggh5@mail.sysu.edu.cn.
Environ Res ; 204(Pt A): 111974, 2022 03.
Article em En | MEDLINE | ID: mdl-34480945
ABSTRACT

BACKGROUND:

Recent research attention has been paid to anthropogenic heat emissions (AE), temperature increase generated by human activity such as lighting, transportation, manufacturing, construction, and building climate controls. However, there is no epidemiological data available to investigate the association between anthropogenic heat emissions and metabolic syndrome (MetS), a cluster of conditions that increase risk of stroke, heart disease and diabetes.

OBJECTIVE:

To explore the relationships between AE and MetS in China.

METHODS:

We recruited 15,477 adults from the 33 Communities Chinese Health Study, a cross-sectional study in northeastern China. We retrieved anthropogenic heat flux by collecting socio-economic and energy consumption data as well as satellite-based nighttime light and Normalized Difference Vegetation Index datasets, including emissions from buildings, transportation, human metabolism, and industries. We also measured MetS components consisting of triglycerides, high density lipoprotein cholesterol, fasting glucose, systolic blood pressure, and diastolic blood pressure, and waist circumference. Restricted cubic spline models were applied to assess the associations between AE and MetS.

RESULTS:

The median flux of total AE was 30.98 W/m2 and industrial AE was the dominant contributor (87.64%). The adjusted odds ratio and 95% confidence interval (CI) of MetS for the 75th and 95th percentiles of the total AE against the threshold were 1.29 (95% CI 1.21, 1.38) and 1.65 (95% CI 1.47, 1.85). Greater AE was associated with higher odds of MetS in a dose-response pattern, and the lowest point of U-shape curve indicated the threshold effect. Participants who are young and middle-aged exhibited stronger associations between AE and MetS.

CONCLUSIONS:

Our novel findings reveal that AE are positively associated with MetS and that associations are modified by age. Further investigations into the mechanisms of the effects are needed.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Síndrome Metabólica Tipo de estudo: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Humans / Middle aged País/Região como assunto: Asia Idioma: En Revista: Environ Res Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Síndrome Metabólica Tipo de estudo: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Humans / Middle aged País/Região como assunto: Asia Idioma: En Revista: Environ Res Ano de publicação: 2022 Tipo de documento: Article