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Wang S, Lei Y, Wang X, Ma K, Wang C, Sun C, Han T. Association between temperatures and type 2 diabetes: A prospective study in UK Biobank. Diabetes Res Clin Pract 2024; 215:111817. [PMID: 39128563 DOI: 10.1016/j.diabres.2024.111817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Revised: 08/04/2024] [Accepted: 08/08/2024] [Indexed: 08/13/2024]
Abstract
OBJECTIVE This study aims to prospectively examine the association between temperatures and the occurrence of type 2 diabetes (T2D). METHODS We used the CPH models to analyze 103,215 non-diabetic participants in the UK Biobank cohort who answered questions about workplace temperature, to evaluate the survival relationship, and the interaction effects of working environmental temperature and T2D-related genetic risk scores (GRS) on the occurrence of T2D. The occurrence of T2D was assessed by hospital inpatient records. The weighted T2D-related GRS were calculated. RESULTS During 1,355,200.6 person-years follow-up, a total of 2436 participants were documented as having diagnosed T2D. After adjustment, compared to the comfortable group, the participants working in non-comfortable environmental temperature had greater risk of T2D (HR: 1.27, 95 %CI: 1.04 to 1.55, for cold; HR: 1.32, 95 %CI: 1.17 to 1.48 for hot; HR: 1.51, 95 %CI: 1.38 to 1.65 for alternate). Similarly, individuals exposed to different levels of genetic risk scores in alternating hot and cold work environments had a higher risk of developing type 2 diabetes. CONCLUSIONS This study found working in single non-comfortable environmental temperatures was associated with greater risk of T2D occurrence, and exposure to alternating environmental temperatures had the highest risk of range and severity.
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Affiliation(s)
- ShengYuan Wang
- Department of Occupational Health, School of Public Health, Harbin Medical University, Harbin, PR China
| | - YaTing Lei
- Department of Occupational Health, School of Public Health, Harbin Medical University, Harbin, PR China
| | - XiaoLi Wang
- Department of Occupational Health, School of Public Health, Harbin Medical University, Harbin, PR China
| | - Kun Ma
- Department of Hygiene Toxicology, School of Public Health, Harbin Medical University, Harbin, PR China
| | - Cheng Wang
- Department of Environmental Health, School of Public Health, Harbin Medical University, Harbin, PR China
| | - ChangHao Sun
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province 150081, PR China.
| | - TianShu Han
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province 150081, PR China.
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Niedermayer F, Wolf K, Zhang S, Dallavalle M, Nikolaou N, Schwettmann L, Selsam P, Hoffmann B, Schneider A, Peters A. Sex-specific associations of environmental exposures with prevalent diabetes and obesity - Results from the KORA Fit study. ENVIRONMENTAL RESEARCH 2024; 252:118965. [PMID: 38642640 DOI: 10.1016/j.envres.2024.118965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 03/25/2024] [Accepted: 04/16/2024] [Indexed: 04/22/2024]
Abstract
Promising evidence suggests a link between environmental factors, particularly air pollution, and diabetes and obesity. However, it is still unclear whether men and women are equally susceptible to environmental exposures. Therefore, we aimed to assess sex-specific long-term effects of environmental exposures on metabolic diseases. We analyzed cross-sectional data from 3,034 participants (53.7% female, aged 53-74 years) from the KORA Fit study (2018/19), a German population-based cohort. Environmental exposures, including annual averages of air pollutants [nitrogen oxides (NO2, NOx), ozone, particulate matter of different diameters (PM10, PMcoarse, PM2.5), PM2.5abs, particle number concentration], air temperature and surrounding greenness, were assessed at participants' residences. We evaluated sex-specific associations of environmental exposures with prevalent diabetes, obesity, body-mass-index (BMI) and waist circumference using logistic or linear regression models with an interaction term for sex, adjusted for age, lifestyle factors and education. Further effect modification, in particular by urbanization, was assessed in sex-stratified analyses. Higher annual averages of air pollution, air temperature and greenness at residence were associated with diabetes prevalence in men (NO2: Odds Ratio (OR) per interquartile range increase in exposure: 1.49 [95% confidence interval (CI): 1.13, 1.95], air temperature: OR: 1.48 [95%-CI: 1.15, 1.90]; greenness: OR: 0.78 [95%-CI: 0.59, 1.01]) but not in women. Conversely, higher levels of air pollution, temperature and lack of greenness were associated with lower obesity prevalence and BMI in women. After including an interaction term for urbanization, only higher greenness was associated with higher BMI in rural women, whereas higher air pollution was associated with higher BMI in urban men. To conclude, we observed sex-specific associations of environmental exposures with metabolic diseases. An additional interaction between environmental exposures and urbanization on obesity suggests a higher susceptibility to air pollution among urban men, and higher susceptibility to greenness among rural women, which needs corroboration in future studies.
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Affiliation(s)
- Fiona Niedermayer
- Chair of Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Siqi Zhang
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Environmental Health Sciences, Yale School of Public Health, New Haven, United States
| | - Marco Dallavalle
- Chair of Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Nikolaos Nikolaou
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lars Schwettmann
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Health Services Research, School of Medicine and Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
| | - Peter Selsam
- Department Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research GmbH-UFZ, Leipzig, Germany
| | - Barbara Hoffmann
- Institute of Occupational, Social and Environmental Medicine, Centre for Health and Society, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Chair of Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Neuherberg, Germany
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Badpa M, Schneider A, Schwettmann L, Thorand B, Wolf K, Peters A. Air pollution, traffic noise, greenness, and temperature and the risk of incident type 2 diabetes: Results from the KORA cohort study. Environ Epidemiol 2024; 8:e302. [PMID: 38617422 PMCID: PMC11008658 DOI: 10.1097/ee9.0000000000000302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 02/12/2024] [Indexed: 04/16/2024] Open
Abstract
Introduction Type 2 diabetes (T2D) is a major public health concern, and various environmental factors have been associated with the development of this disease. This study aimed to investigate the longitudinal effects of multiple environmental exposures on the risk of incident T2D in a German population-based cohort. Methods We used data from the KORA cohort study (Augsburg, Germany) and assessed exposure to air pollutants, traffic noise, greenness, and temperature at the participants' residencies. Cox proportional hazard models were used to analyze the associations with incident T2D, adjusting for potential confounders. Results Of 7736 participants included in the analyses, 10.5% developed T2D during follow-up (mean: 15.0 years). We found weak or no association between environmental factors and the risk of T2D, with sex and education level significantly modifying the effects of air pollutants. Conclusion Our study contributes to the growing body of literature investigating the impact of environmental factors on T2D risks and suggests that the impact of environmental factors may be small.
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Affiliation(s)
- Mahnaz Badpa
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Lars Schwettmann
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, Munich, Germany
- Department of Health Services Research, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany
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Oliveras-Cañellas N, Moreno-Navarrete JM, Lorenzo PM, Garrido-Sánchez L, Becerril S, Rangel O, Latorre J, de la Calle Vargas E, Pardo M, Valentí V, Romero-Cabrera JL, Oliva-Olivera W, Silva C, Diéguez C, Villarroya F, López M, Crujeiras AB, Seoane LM, López-Miranda J, Frühbeck G, Tinahones FJ, Fernández-Real JM. Downregulated Adipose Tissue Expression of Browning Genes With Increased Environmental Temperatures. J Clin Endocrinol Metab 2023; 109:e145-e154. [PMID: 37560997 DOI: 10.1210/clinem/dgad469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/28/2023] [Accepted: 08/08/2023] [Indexed: 08/11/2023]
Abstract
CONTEXT Climate change and global warming have been hypothesized to influence the increased prevalence of obesity worldwide. However, the evidence is scarce. OBJECTIVE We aimed to investigate how outside temperature might affect adipose tissue physiology and metabolic traits. METHODS The expression of genes involved in thermogenesis/browning and adipogenesis were evaluated (through quantitative polymerase chain reaction) in the subcutaneous adipose tissue (SAT) from 1083 individuals recruited in 5 different regions of Spain (3 in the North and 2 in the South). Plasma biochemical variables and adiponectin (enzyme-linked immunosorbent assay) were collected through standardized protocols. Mean environmental outdoor temperatures were obtained from the National Agency of Meteorology. Univariate, multivariate, and artificial intelligence analyses (Boruta algorithm) were performed. RESULTS The SAT expression of genes associated with browning (UCP1, PRDM16, and CIDEA) and ADIPOQ were significantly and negatively associated with minimum, average, and maximum temperatures. The latter temperatures were also negatively associated with the expression of genes involved in adipogenesis (FASN, SLC2A4, and PLIN1). Decreased SAT expression of UCP1 and ADIPOQ messenger RNA and circulating adiponectin were observed with increasing temperatures in all individuals as a whole and within participants with obesity in univariate, multivariate, and artificial intelligence analyses. The differences remained statistically significant in individuals without type 2 diabetes and in samples collected during winter. CONCLUSION Decreased adipose tissue expression of genes involved in browning and adiponectin with increased environmental temperatures were observed. Given the North-South gradient of obesity prevalence in these same regions, the present observations could have implications for the relationship of the obesity pandemic with global warming.
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Affiliation(s)
- Núria Oliveras-Cañellas
- Department of Diabetes, Endocrinology and Nutrition, Dr. Josep Trueta University Hospital, Girona 17007, Spain
- Nutrition, Eumetabolism and Health Group, Girona Biomedical Research Institute (IDIBGI), Girona 17190, Spain
- Department of Medical Sciences, School of Medicine, University of Girona, Girona 17003, Spain
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
| | - José María Moreno-Navarrete
- Department of Diabetes, Endocrinology and Nutrition, Dr. Josep Trueta University Hospital, Girona 17007, Spain
- Nutrition, Eumetabolism and Health Group, Girona Biomedical Research Institute (IDIBGI), Girona 17190, Spain
- Department of Medical Sciences, School of Medicine, University of Girona, Girona 17003, Spain
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
| | - Paula M Lorenzo
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Epigenomics in Endocinology and Nutrition Group, Epigenomics Unit, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago de Compostela (CHUS/SERGAS), Santiago de Compostela 15706, Spain
| | - Lourdes Garrido-Sánchez
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Servicio de Endocrinología y Nutrición, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Virgen de la Victoria, Universidad de Málaga, Málaga 29590, Spain
| | - Sara Becerril
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Obesity Area, Clínica Universidad de Navarra, University of Navarra, Pamplona 31009, Spain
| | - Oriol Rangel
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Nutrigenomics, Metabolic Syndrome Department, Servicio de Medicina Interna, Hospital Universitario Reina Sofía, Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Universidad de Córdoba, Córdoba 14004, Spain
| | - Jèssica Latorre
- Department of Diabetes, Endocrinology and Nutrition, Dr. Josep Trueta University Hospital, Girona 17007, Spain
- Nutrition, Eumetabolism and Health Group, Girona Biomedical Research Institute (IDIBGI), Girona 17190, Spain
- Department of Medical Sciences, School of Medicine, University of Girona, Girona 17003, Spain
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
| | - Elena de la Calle Vargas
- Department of Diabetes, Endocrinology and Nutrition, Dr. Josep Trueta University Hospital, Girona 17007, Spain
- Nutrition, Eumetabolism and Health Group, Girona Biomedical Research Institute (IDIBGI), Girona 17190, Spain
- Department of Medical Sciences, School of Medicine, University of Girona, Girona 17003, Spain
| | - Maria Pardo
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Grupo Obesidómica, Área de Endocrinología, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Xerencia de Xestión Integrada de Santiago (IDIS/SERGAS), Santiago de Compostela 15706, Spain
| | - Victor Valentí
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Obesity Area, Clínica Universidad de Navarra, University of Navarra, Pamplona 31009, Spain
| | - Juan L Romero-Cabrera
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Nutrigenomics, Metabolic Syndrome Department, Servicio de Medicina Interna, Hospital Universitario Reina Sofía, Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Universidad de Córdoba, Córdoba 14004, Spain
| | - Wilfredo Oliva-Olivera
- Servicio de Endocrinología y Nutrición, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Virgen de la Victoria, Universidad de Málaga, Málaga 29590, Spain
| | - Camilo Silva
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Obesity Area, Clínica Universidad de Navarra, University of Navarra, Pamplona 31009, Spain
| | - Carlos Diéguez
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Department of Physiology, CIMUS, University of Santiago de Compostela-Instituto de Investigación Sanitaria, Santiago de Compostela 15782, Spain
| | - Francesc Villarroya
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Department of Biochemistry and Molecular Biomedicine, Insitut de Biomedicina (IBUB), University of Barcelona, Barcelona 08028, Spain
| | - Miguel López
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Department of Physiology, CIMUS, University of Santiago de Compostela-Instituto de Investigación Sanitaria, Santiago de Compostela 15782, Spain
| | - Ana B Crujeiras
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Epigenomics in Endocinology and Nutrition Group, Epigenomics Unit, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago de Compostela (CHUS/SERGAS), Santiago de Compostela 15706, Spain
| | - Luisa-Maria Seoane
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Endocrine Physiopathology Group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago (CHUS/SERGAS), Santiago de Compostela 15706, Spain
| | - José López-Miranda
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Nutrigenomics, Metabolic Syndrome Department, Servicio de Medicina Interna, Hospital Universitario Reina Sofía, Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Universidad de Córdoba, Córdoba 14004, Spain
| | - Gema Frühbeck
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Obesity Area, Clínica Universidad de Navarra, University of Navarra, Pamplona 31009, Spain
| | - Francisco José Tinahones
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
- Servicio de Endocrinología y Nutrición, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Virgen de la Victoria, Universidad de Málaga, Málaga 29590, Spain
| | - José-Manuel Fernández-Real
- Department of Diabetes, Endocrinology and Nutrition, Dr. Josep Trueta University Hospital, Girona 17007, Spain
- Nutrition, Eumetabolism and Health Group, Girona Biomedical Research Institute (IDIBGI), Girona 17190, Spain
- Department of Medical Sciences, School of Medicine, University of Girona, Girona 17003, Spain
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Madrid 28029, Spain
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McAlexander TP, Ryan V, Uddin J, Kanchi R, Thorpe L, Schwartz BS, Carson A, Rolka DB, Adhikari S, Pollak J, Lopez P, Smith M, Meeker M, McClure LA. Associations between PM 2.5 and O 3 exposures and new onset type 2 diabetes in regional and national samples in the United States. ENVIRONMENTAL RESEARCH 2023; 239:117248. [PMID: 37827369 DOI: 10.1016/j.envres.2023.117248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 09/07/2023] [Accepted: 09/09/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND Exposure to particulate matter ≤2.5 μm in diameter (PM2.5) and ozone (O3) has been linked to numerous harmful health outcomes. While epidemiologic evidence has suggested a positive association with type 2 diabetes (T2D), there is heterogeneity in findings. We evaluated exposures to PM2.5 and O3 across three large samples in the US using a harmonized approach for exposure assignment and covariate adjustment. METHODS Data were obtained from the Veterans Administration Diabetes Risk (VADR) cohort (electronic health records [EHRs]), the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort (primary data collection), and the Geisinger health system (EHRs), and reflect the years 2003-2016 (REGARDS) and 2008-2016 (VADR and Geisinger). New onset T2D was ascertained using EHR information on medication orders, laboratory results, and T2D diagnoses (VADR and Geisinger) or report of T2D medication or diagnosis and/or elevated blood glucose levels (REGARDS). Exposure was assigned using pollutant annual averages from the Downscaler model. Models stratified by community type (higher density urban, lower density urban, suburban/small town, or rural census tracts) evaluated likelihood of new onset T2D in each study sample in single- and two-pollutant models of PM2.5 and O3. RESULTS In two pollutant models, associations of PM2.5, and new onset T2D were null in the REGARDS cohort except for in suburban/small town community types in models that also adjusted for NSEE, with an odds ratio (95% CI) of 1.51 (1.01, 2.25) per 5 μg/m3 of PM2.5. Results in the Geisinger sample were null. VADR sample results evidenced nonlinear associations for both pollutants; the shape of the association was dependent on community type. CONCLUSIONS Associations between PM2.5, O3 and new onset T2D differed across three large study samples in the US. None of the results from any of the three study populations found strong and clear positive associations.
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Affiliation(s)
- Tara P McAlexander
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA.
| | - Victoria Ryan
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA
| | - Jalal Uddin
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Rania Kanchi
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Lorna Thorpe
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Brian S Schwartz
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - April Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 39213, USA
| | - Deborah B Rolka
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Samrachana Adhikari
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Jonathan Pollak
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Priscilla Lopez
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Megan Smith
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA
| | - Melissa Meeker
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA
| | - Leslie A McClure
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA
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Zhang T, Ni M, Jia J, Deng Y, Sun X, Wang X, Chen Y, Fang L, Zhao H, Xu S, Ma Y, Zhu J, Pan F. Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China. BMC Public Health 2023; 23:2363. [PMID: 38031031 PMCID: PMC10685562 DOI: 10.1186/s12889-023-17299-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 11/22/2023] [Indexed: 12/01/2023] Open
Abstract
As climate conditions deteriorate, human health faces a broader range of threats. This study aimed to determine the risk of death from metabolic syndrome (MetS) due to meteorological factors. We collected daily data from 2014 to 2020 in Wuhu City, including meteorological factors, environmental pollutants and death data of common MetS (hypertension, hyperlipidemia and diabetes), as well as a total number of 15,272 MetS deaths. To examine the relationship between meteorological factors, air pollutants, and MetS mortality, we used a generalized additive model (GAM) combined with a distributed delay nonlinear model (DLNM) for time series analysis. The relationship between the above factors and death outcomes was preliminarily evaluated using Spearman analysis and structural equation modeling (SEM). As per out discovery, diurnal temperature range (DTR) and daily mean temperature (T mean) increased the MetS mortality risk notably. The ultra low DTR raised the MetS mortality risk upon the general people, with the highest RR value of 1.033 (95% CI: 1.002, 1.065) at lag day 14. In addition, T mean was also significantly associated with MetS death. The highest risk of ultra low and ultra high T mean occured on the same day (lag 14), RR values were 1.043 (95% CI: 1.010, 1.077) and 1.032 (95% CI: 1.003, 1.061) respectively. Stratified analysis's result showed lower DTR had a more pronounced effect on women and the elderly, and ultra low and high T mean was a risk factor for MetS mortality in women and men. The elderly need to take extra note of temperature changes, and different levels of T mean will increase the risk of death. In warm seasons, ultra high RH and T mean can increase the mortality rate of MetS patients.
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Affiliation(s)
- Tao Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Man Ni
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Juan Jia
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Yujie Deng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Xiaoya Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Xinqi Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Yuting Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Lanlan Fang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Hui Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Shanshan Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Yubo Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Jiansheng Zhu
- Wuhu center for disease control and prevention, Wuhu, Anhui, China
| | - Faming Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
- Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
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7
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Fan JF, Xiao YC, Feng YF, Niu LY, Tan X, Sun JC, Leng YQ, Li WY, Wang WZ, Wang YK. A systematic review and meta-analysis of cold exposure and cardiovascular disease outcomes. Front Cardiovasc Med 2023; 10:1084611. [PMID: 37051068 PMCID: PMC10083291 DOI: 10.3389/fcvm.2023.1084611] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 02/22/2023] [Indexed: 03/29/2023] Open
Abstract
BackgroundCold exposure has been considered an essential risk factor for the global disease burden, while its role in cardiovascular diseases is still underappreciated. The increase in frequency and duration of extreme cold weather events like cold spells makes it an urgent task to evaluate the effects of ambient cold on different types of cardiovascular disease and to understand the factors contributing to the population's vulnerability.MethodsIn the present systematic review and meta-analysis, we searched PubMed, Scopus, and Cochrane. We included original research that explored the association between cold exposure (low temperature and cold spell) and cardiovascular disease outcomes (mortality and morbidity). We did a random-effects meta-analysis to pool the relative risk (RR) of the association between a 1°C decrease in temperature or cold spells and cardiovascular disease outcomes.ResultsIn total, we included 159 studies in the meta-analysis. As a result, every 1°C decrease in temperature increased cardiovascular disease-related mortality by 1.6% (RR 1.016; [95% CI 1.015–1.018]) and morbidity by 1.2% (RR 1.012; [95% CI 1.010–1.014]). The most pronounced effects of low temperatures were observed in the mortality of coronary heart disease (RR 1.015; [95% CI 1.011–1.019]) and the morbidity of aortic aneurysm and dissection (RR 1.026; [95% CI 1.021–1.031]), while the effects were not significant in hypertensive disease outcomes. Notably, we identified climate zone, country income level and age as crucial influential factors in the impact of ambient cold exposure on cardiovascular disease. Moreover, the impact of cold spells on cardiovascular disease outcomes is significant, which increased mortality by 32.4% (RR 1.324; [95% CI 1.2341.421]) and morbidity by 13.8% (RR 1.138; [95% CI 1.015–1.276]).ConclusionCold exposure could be a critical risk factor for cardiovascular diseases, and the cold effect varies between disease types and climate zones.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier: CRD42022347247.
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8
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Ratter-Rieck JM, Roden M, Herder C. Diabetes and climate change: current evidence and implications for people with diabetes, clinicians and policy stakeholders. Diabetologia 2023; 66:1003-1015. [PMID: 36964771 PMCID: PMC10039694 DOI: 10.1007/s00125-023-05901-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/15/2023] [Indexed: 03/26/2023]
Abstract
Climate change will be a major challenge for the world's health systems in the coming decades. Elevated temperatures and increasing frequencies of heat waves, wildfires, heavy precipitation and other weather extremes can affect health in many ways, especially if chronic diseases are already present. Impaired responses to heat stress, including compromised vasodilation and sweating, diabetes-related comorbidities, insulin resistance and chronic low-grade inflammation make people with diabetes particularly vulnerable to environmental risk factors, such as extreme weather events and air pollution. Additionally, multiple pathogens show an increased rate of transmission under conditions of climate change and people with diabetes have an altered immune system, which increases the risk for a worse course of infectious diseases. In this review, we summarise recent studies on the impact of climate-change-associated risk for people with diabetes and discuss which individuals may be specifically prone to these risk conditions due to their clinical features. Knowledge of such high-risk groups will help to develop and implement tailored prevention and management strategies to mitigate the detrimental effect of climate change on the health of people with diabetes.
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Affiliation(s)
- Jacqueline M Ratter-Rieck
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
- German Center for Diabetes Research, Partner Düsseldorf, München-Neuherberg, Germany.
| | - Michael Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research, Partner Düsseldorf, München-Neuherberg, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research, Partner Düsseldorf, München-Neuherberg, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
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9
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Khraishah H, Alahmad B, Ostergard RL, AlAshqar A, Albaghdadi M, Vellanki N, Chowdhury MM, Al-Kindi SG, Zanobetti A, Gasparrini A, Rajagopalan S. Climate change and cardiovascular disease: implications for global health. Nat Rev Cardiol 2022; 19:798-812. [PMID: 35672485 DOI: 10.1038/s41569-022-00720-x] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/04/2022] [Indexed: 12/15/2022]
Abstract
Climate change is the greatest existential challenge to planetary and human health and is dictated by a shift in the Earth's weather and air conditions owing to anthropogenic activity. Climate change has resulted not only in extreme temperatures, but also in an increase in the frequency of droughts, wildfires, dust storms, coastal flooding, storm surges and hurricanes, as well as multiple compound and cascading events. The interactions between climate change and health outcomes are diverse and complex and include several exposure pathways that might promote the development of non-communicable diseases such as cardiovascular disease. A collaborative approach is needed to solve this climate crisis, whereby medical professionals, scientific researchers, public health officials and policymakers should work together to mitigate and limit the consequences of global warming. In this Review, we aim to provide an overview of the consequences of climate change on cardiovascular health, which result from direct exposure pathways, such as shifts in ambient temperature, air pollution, forest fires, desert (dust and sand) storms and extreme weather events. We also describe the populations that are most susceptible to the health effects caused by climate change and propose potential mitigation strategies, with an emphasis on collaboration at the scientific, governmental and policy levels.
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Affiliation(s)
- Haitham Khraishah
- Division of Cardiovascular Medicine, University of Maryland School of Medicine, Baltimore, MD, USA. .,Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
| | - Barrak Alahmad
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.,Environmental & Occupational Health Department, Faculty of Public Health, Kuwait University, Hawalli, Kuwait
| | | | - Abdelrahman AlAshqar
- Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven, CT, USA
| | - Mazen Albaghdadi
- Division of Cardiology, Peter Munk Cardiac Centre, Toronto General Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Nirupama Vellanki
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Mohammed M Chowdhury
- Department of Vascular and Endovascular Surgery, Department of Surgery, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
| | - Sadeer G Al-Kindi
- University Hospitals, Harrington Heart & Vascular Institute, Department of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Antonio Gasparrini
- Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, UK.,Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK.,Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Sanjay Rajagopalan
- University Hospitals, Harrington Heart & Vascular Institute, Department of Medicine, Case Western Reserve University, Cleveland, OH, USA
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10
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Kharwadkar S, Attanayake V, Duncan J, Navaratne N, Benson J. The impact of climate change on the risk factors for tuberculosis: A systematic review. ENVIRONMENTAL RESEARCH 2022; 212:113436. [PMID: 35550808 DOI: 10.1016/j.envres.2022.113436] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 04/03/2022] [Accepted: 05/04/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Tuberculosis (TB) continues to pose a major public health risk in many countries. The current incidence of disease exceeds guidelines proposed by the World Health Organisation and United Nations. Whilst the relationship between climate change and TB has surfaced in recent literature, it remains neglected in global agendas. There is a need to acknowledge TB as a climate-sensitive disease to facilitate its eradication. OBJECTIVE To review epidemiological and prediction model studies that explore how climate change may affect the risk factors for TB, as outlined in the Global Tuberculosis Report 2021: HIV infection, diabetes mellitus, undernutrition, overcrowding, poverty, and indoor air pollution. METHODS We conducted a systematic literature search of PubMed, Embase, and Scopus databases to identify studies examining the association between climate variables and the risk factors for TB. Each study that satisfied the inclusion criteria was assessed for quality and ethics. Studies then underwent vote-counting and were categorised based on whether an association was found. RESULTS 53 studies met inclusion criteria and were included in our review. Vote-counting revealed that two out of two studies found a positive association between the examined climate change proxy and HIV, nine out of twelve studies for diabetes, eight out of seventeen studies for undernutrition, four out of five studies for overcrowding, twelve out of fifteen studies for poverty and one out of three studies for indoor air pollution. DISCUSSION We found evidence supporting a positive association between climate change and each of the discussed risk factors for TB, excluding indoor air pollution. Our findings suggest that climate change is likely to affect the susceptibility of individuals to TB by increasing the prevalence of its underlying risk factors, particularly in developing countries. This is an evolving field of research that requires further attention in the scientific community.
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Affiliation(s)
- Sahil Kharwadkar
- School of Medicine, The University of Adelaide, Australia; School of Public Health, The University of Adelaide, Australia.
| | | | - John Duncan
- School of Medicine, The University of Adelaide, Australia.
| | | | - Jill Benson
- Discipline of General Practice, School of Medicine, The University of Adelaide, Australia.
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11
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Low glucose metabolizing capacity and not insulin resistance is primary etiology of Type 2 Diabetes Mellitus: A hypothesis. Med Hypotheses 2022. [DOI: 10.1016/j.mehy.2022.110804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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12
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Association between Physical Activity and Seasonal Variations in Metabolic and Vascular Function in Adults. ENDOCRINES 2021. [DOI: 10.3390/endocrines2020015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
This article highlights the association between physical activity (PA) and seasonal variations in metabolic and vascular function in adults. Increasing PA is an important method for preventing cardiovascular disease (CVD) and all-cause mortality by improving blood glucose, blood pressure, blood lipid profiles, body fat, insulin resistance, and vascular function, such as endothelial function. Conversely, various factors, such as seasonal climate conditions, may affect the amount of PA that individuals undertake. Changes in PA often induce seasonal variations in metabolic and vascular function; the deterioration of such functions in winter is the most prominent, and there is clear evidence of an increased risk of CVD in this season. Understanding the influence of PA on seasonal variations observed in metabolic and vascular function is necessary for the management of these physiological functions. In this article summary, few studies have proven that maintaining PA can suppress the variations, and it remains unclear what types, intensities, and durations of regular PA are effective for circumventing seasonal impact. In addition to further studies, there is a need to educate individuals about the strategies to manage PA and other aspects of their lifestyles throughout the year, particularly in winter.
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Cardiovascular risk factors in China: a nationwide population-based cohort study. LANCET PUBLIC HEALTH 2020; 5:e672-e681. [PMID: 33271080 DOI: 10.1016/s2468-2667(20)30191-2] [Citation(s) in RCA: 112] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 07/23/2020] [Accepted: 08/17/2020] [Indexed: 11/20/2022]
Abstract
BACKGROUND It is estimated that 4 million deaths are due to cardiovascular diseases each year in China. Comprehensive understanding about modifiable risk factors and how the risk differs across regions is needed to inform public health policies. We aimed to examine the geographical profile of cardiovascular disease risk across China. METHODS In this study, we analysed data from a nationwide, population-based screening project, which covered 152 rural counties and 100 urban districts from 31 provinces in China. Between Sept 1, 2015, and Nov 30, 2019, standardised measurements were taken from participants aged 35-75 years who had lived in the region for at least 6 of the preceding 12 months to collect information on blood pressure, blood lipids, blood glucose, physical activity, tobacco smoking, alcohol use, overweight or obesity, and intake frequencies of fruits, vegetables, whole grains, legumes, and red meat. Individuals with a high risk of cardiovascular disease were identified according to medical history and WHO risk prediction charts. FINDINGS 983 476 individuals were included in this study. Among the participants included, 10·3% (95% CI 10·2-10·3) had a high cardiovascular disease risk after standardising age and sex, with a range of 3·1-24·9% across counties or districts. Among the seven regions in mainland China, the prevalence of high risk of cardiovascular disease was relatively high in northeast China (12·6% [12·4-12·8]) and north China (11·4% [11·3-11·6]), whereas it was low in south China (8·0% [7·8-8·2]). The geographical profiles of the 12 major cardiovascular disease risk factors were different. We found that the regions with high cardiovascular disease risk were facing challenges such as obesity and high blood pressure (north China) and consumption of unhealthy non-staple food (low intake of fruits and vegetables or high intake of red meat; northeast China). By contrast, south China-the region with the lowest cardiovascular disease risk-had the highest prevalence of unhealthy staple food (low intake of whole grains and beans), abnormal metabolism (glucose and lipid), and low physical activity in the country. INTERPRETATION Risk for cardiovascular diseases varies geographically, and the major contributing risk factors are different across regions in China. Hence, geographically targeted interventions are needed to mitigate the risk and reduce the burden in such a vast country. FUNDING Ministry of Science and Technology, Ministry of Finance, and National Health Commission of China.
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14
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Preston EV, Eberle C, Brown FM, James-Todd T. Climate factors and gestational diabetes mellitus risk - a systematic review. Environ Health 2020; 19:112. [PMID: 33168031 PMCID: PMC7653781 DOI: 10.1186/s12940-020-00668-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 10/15/2020] [Indexed: 05/04/2023]
Abstract
BACKGROUND Current and projected increases in global temperatures and extreme climate events have led to heightened interest in the impact of climate factors (i.e. ambient temperature, season/seasonality, and humidity) on human health. There is growing evidence that climate factors may impact metabolic function, including insulin sensitivity. Gestational diabetes mellitus (GDM) is a common pregnancy complication, with an estimated global prevalence of up to 14%. While lifestyle and genetic risk factors for GDM are well established, environmental factors may also contribute to GDM risk. Previous reviews have summarized the growing evidence of environmental risk factors for GDM including endocrine disrupting chemicals and ambient air pollution. However, studies of the effects of climate factors on GDM risk have not been systematically evaluated. Therefore, we conducted a systematic review to summarize and evaluate the current literature on the associations of climate factors with GDM risk. METHODS We conducted systematic searches in PubMed and EMBASE databases for original research articles on associations of climate factors (i.e. ambient temperature, season/seasonality, and humidity) with GDM and/or related glycemic outcomes for all publication dates through September 20th, 2020. RESULTS Our search identified 16 articles on the associations of ambient temperature and/or season with GDM and maternal glycemic outcomes during pregnancy, which were included in this review. Despite inconsistencies in exposure and outcome assessment, we found consistent evidence of a seasonal effect on GDM risk, with higher prevalence of GDM and higher pregnancy glucose levels in summer months. We found suggestive evidence of an association between higher ambient temperature and elevated glucose levels from GDM screening tests. CONCLUSION Climate factors may be associated with GDM risk. However, further research is needed to evaluate these associations and to elucidate the specific mechanisms involved.
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Affiliation(s)
- Emma V. Preston
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Building 1, Room 1411, 677 Huntington Ave, Boston, MA 02118 USA
| | - Claudia Eberle
- Medicine with specialization in Internal Medicine and General Medicine, Hochschule Fulda - University of Applied Sciences, Fulda, Germany
| | | | - Tamarra James-Todd
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Building 1, Room 1411, 677 Huntington Ave, Boston, MA 02118 USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
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15
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Zhou Y, Meng T, Wu L, Duan Y, Li G, Shi C, Zhang H, Peng Z, Fan C, Ma J, Xiong C, Bao W, Liu Y. Association between ambient temperature and semen quality: A longitudinal study of 10 802 men in China. ENVIRONMENT INTERNATIONAL 2020; 135:105364. [PMID: 31841801 DOI: 10.1016/j.envint.2019.105364] [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: 05/06/2019] [Revised: 10/20/2019] [Accepted: 11/25/2019] [Indexed: 05/25/2023]
Abstract
Semen quality is a vital determinant for male fertility. The process of spermatogenesis is highly sensitive to fluctuations in temperature. However, the impact of ambient temperature on semen quality remains unclear. We aimed to quantitatively assess the association between ambient temperature and semen quality. Using data from Hubei provincial human sperm bank in Wuhan, China, we conducted a longitudinal study including 10 802 volunteers who lived in Wuhan and passed the initial physical examination for sperm donation between Mar 27, 2013 and April 9, 2018. Semen quality parameters including sperm concentration, total sperm number, total motility, progressive motility, total motile sperm count and progressively motile sperm count were determined in the sperm bank. We used linear mixed models to identify estimate changes of outcomes in relation to ambient temperature (i.e., air temperature and apparent temperature) exposure measured as the mean daily temperature during the 0-90 days before semen collection. Among 10 802 subjects who underwent 41 689 semen examinations, we observed inverted U-shaped exposure-response associations between air temperature exposure and all semen quality parameters, with an identical threshold exposure of 13 °C. For air temperature exposure <13 °C, each 5 °C lower temperature was significantly associated with 1.94 × 106/ml, 7.12 × 106, 0.77%, 0.81%, 6.48 × 106, and 5.87 × 106 decrease in sperm concentration, total sperm count, total motility, progressive motility, total motile sperm count and progressively motile sperm count, respectively. When air temperature exposure was ≥13 °C, each 5 °C higher temperature was significantly associated with 0.70 × 106/ml, 4.09 × 106, 1.01%, 1.06%, 4.31 × 106, and 4.20 × 106 decrease in sperm concentration, total sperm count, total motility, progressive motility, total motile sperm count and progressively motile sperm count, respectively. Age, BMI and smoking did not significantly modify these associations. Similar results were observed for apparent temperature. This study provides a comprehensive picture of nonlinear association between ambient temperature and semen quality, as well as an optimal temperature for the benefit of semen quality. Both lower and higher ambient temperature exposures compared with the optimal temperature were significantly associated with decreased semen quality. The findings highlight the needs and importance to reduce extreme ambient temperature exposures in maintaining optimal semen quality for men. Further investigation is warranted to determine the causality of the association and the underlying mechanisms.
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Affiliation(s)
- Yun Zhou
- School of Public Health, Guangzhou Medical University, Guangzhou, Guangdong 511436, China
| | - Tianqing Meng
- Center for Reproductive Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Li Wu
- Reproductive Medical Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yonggang Duan
- Shenzhen Key Laboratory of Fertility Regulation, Centre of Assisted Reproduction and Embryology, The University of Hong Kong - Shenzhen Hospital, Shenzhen, Guangdong 518053, China
| | - Guo Li
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Chunxiang Shi
- National Meteorological Information Center, Beijing 100081, China
| | - Hai Zhang
- Institute of Health Surveillance, Analysis and Protection, Hubei Provincial Center for Disease Control and Prevention, Wuhan, Hubei 430079, China
| | - Zhe Peng
- Institute of Health Surveillance, Analysis and Protection, Hubei Provincial Center for Disease Control and Prevention, Wuhan, Hubei 430079, China
| | - Chuangang Fan
- Institute of Health Surveillance, Analysis and Protection, Hubei Provincial Center for Disease Control and Prevention, Wuhan, Hubei 430079, China
| | - Jixuan Ma
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Chengliang Xiong
- Center for Reproductive Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Wei Bao
- Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA 52242, USA.
| | - Yuewei Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.
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