Dataset Information

Association between ambient air pollution and diabetes mellitus in Europe and North America: systematic review and meta-analysis.

ABSTRACT:

Background

Air pollution is hypothesized to be a risk factor for diabetes. Epidemiological evidence is inconsistent and has not been systematically evaluated.

Objectives

We systematically reviewed epidemiological evidence on the association between air pollution and diabetes, and synthesized results of studies on type 2 diabetes mellitus (T2DM).

Methods

We systematically searched electronic literature databases (last search, 29 April 2014) for studies reporting the association between air pollution (particle concentration or traffic exposure) and diabetes (type 1, type 2, or gestational). We systematically evaluated risk of bias and role of potential confounders in all studies. We synthesized reported associations with T2DM in meta-analyses using random-effects models and conducted various sensitivity analyses.

Results

We included 13 studies (8 on T2DM, 2 on type 1, 3 on gestational diabetes), all conducted in Europe or North America. Five studies were longitudinal, 5 cross-sectional, 2 case-control, and 1 ecologic. Risk of bias, air pollution assessment, and confounder control varied across studies. Dose-response effects were not reported. Meta-analyses of 3 studies on PM2.5 (particulate matter ? 2.5 ?m in diameter) and 4 studies on NO2 (nitrogen dioxide) showed increased risk of T2DM by 8-10% per 10-?g/m3 increase in exposure [PM2.5: 1.10 (95% CI: 1.02, 1.18); NO2: 1.08 (95% CI: 1.00, 1.17)]. Associations were stronger in females. Sensitivity analyses showed similar results.

Conclusion

Existing evidence indicates a positive association of air pollution and T2DM risk, albeit there is high risk of bias. High-quality studies assessing dose-response effects are needed. Research should be expanded to developing countries where outdoor and indoor air pollution are high.

SUBMITTER: Eze IC

PROVIDER: S-EPMC4421762 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Publications

Association between ambient air pollution and diabetes mellitus in Europe and North America: systematic review and meta-analysis.

Eze Ikenna C IC Hemkens Lars G LG Bucher Heiner C HC Hoffmann Barbara B Schindler Christian C Künzli Nino N Schikowski Tamara T Probst-Hensch Nicole M NM

Environmental health perspectives 20150127 5

<h4>Background</h4>Air pollution is hypothesized to be a risk factor for diabetes. Epidemiological evidence is inconsistent and has not been systematically evaluated.<h4>Objectives</h4>We systematically reviewed epidemiological evidence on the association between air pollution and diabetes, and synthesized results of studies on type 2 diabetes mellitus (T2DM).<h4>Methods</h4>We systematically searched electronic literature databases (last search, 29 April 2014) for studies reporting the associat ...[more]

PMID: 25625876

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Project description:BACKGROUND:Malaysia has the highest rate of diabetes mellitus (DM) in the Southeast Asian region, and has ongoing air pollution and periodic haze exposure. METHODS:Diabetes data were derived from the Malaysian National Health and Morbidity Surveys conducted in 2006, 2011 and 2015. The air pollution data (NOx, NO2, SO2, O3 and PM10) were obtained from the Department of Environment Malaysia. Using multiple logistic and linear regression models, the association between long-term exposure to these pollutants and prevalence of diabetes among Malaysian adults was evaluated. RESULTS:The PM10 concentration decreased from 2006 to 2014, followed by an increase in 2015. Levels of NOx decreased while O3 increased annually. The air pollutant levels based on individual modelled air pollution exposure as measured by the nearest monitoring station were higher than the annual averages of the five pollutants present in the ambient air. The prevalence of overall diabetes increased from 11.4% in 2006 to 21.2% in 2015. The prevalence of known diabetes, underdiagnosed diabetes, overweight and obesity also increased over these years. There were significant positive effect estimates of known diabetes at 1.125 (95% CI, 1.042, 1.213) for PM10, 1.553 (95% CI, 1.328, 1.816) for O3, 1.271 (95% CI, 1.088, 1.486) for SO2, 1.124 (95% CI, 1.048, 1.207) for NO2, and 1.087 (95% CI, 1.024, 1.153) for NOx for NHMS 2006. The adjusted annual average levels of PM10 [1.187 (95% CI, 1.088, 1.294)], O3 [1.701 (95% CI, 1.387, 2.086)], NO2 [1.120 (95% CI, 1.026, 1.222)] and NOx [1.110 (95% CI, 1.028, 1.199)] increased significantly from NHMS 2006 to NHMS 2011 for overall diabetes. This was followed by a significant decreasing trend from NHMS 2011 to 2015 [0.911 for NO2, and 0.910 for NOx]. CONCLUSION:The findings of this study suggest that long-term exposure to O3 is an important associated factor of underdiagnosed DM risk in Malaysia. PM10, NO2 and NOx may have mixed effect estimates towards the risk of DM, and their roles should be further investigated with other interaction models. Policy and intervention measures should be taken to reduce air pollution in Malaysia.

Project description:There is inconclusive evidence on the association between ambient air pollution and pulmonary tuberculosis (PTB) incidence, tuberculosis-related hospital admission and mortality. This review aimed to assess the extent to which selected air pollutants are associated to PTB incidence, hospital admissions and mortality. This was a systematic review of studies published in English from January 1st, 1946, through May 31st, 2022, that quantitatively assessed the association between PM2.5, PM10, NO2, SO2, CO, O3 and the incidence of, hospital admission or death from PTB. Medline, Embase, Scopus and The Cochrane Library were searched. Extracted data from eligible studies were analysed using STATA software. Random-effect meta-analysis was used to derive pooled adjusted risk and odds ratios. A total of 24 studies (10 time-series, 5 ecologic, 5 cohort, 2 case-control, 1 case cross-over, 1 cross-sectional) mainly from Asian countries were eligible and involved a total of 437,255 tuberculosis cases. For every 10 μg/m3 increment in air pollutant concentration, there was a significant association between exposure to PM2.5 (pooled aRR = 1.12, 95% CI: 1.06-1.19, p < 0.001, N = 6); PM10 (pooled aRR = 1.06, 95% CI: 1.01-1.12, p = 0.022, N = 8); SO2 (pooled aRR = 1.08, 95% CI: 1.04-1.12, p < 0.001, N = 9); and the incidence of PTB. There was no association between exposure to CO (pooled aRR = 1.04, 95% CI: 0.98-1.11, p = 0.211, N = 4); NO2 (pooled aRR = 1.08, 95% CI: 0.99-1.17, p = 0.057, N = 7); O3 (pooled aRR = 1.00, 95% CI: 0.99-1.02, p = 0.910, N = 6) and the incidence of PTB. There was no association between the investigated air pollutants and mortality or hospital admissions due to PTB. Overall quality of evidence was graded as low (GRADE approach). Exposure to PM2.5, PM10 and SO2 air pollutants was found to be associated with an increased incidence of PTB, while exposure to CO, NO2 and O3 was not. There was no observed association between exposure to these air pollutants and hospital admission or mortality due to PTB. The quality of the evidence generated, however, remains low. Addressing the tuberculosis epidemic by 2030 as per the 4th Sustainable Development Goal may require a more rigorous exploration of this association.

Project description:ObjectiveTo investigate the role of air pollutants in risk of dementia, considering differences by study factors that could influence findings.DesignSystematic review and meta-analysis.Data sourcesEMBASE, PubMed, Web of Science, Psycinfo, and OVID Medline from database inception through July 2022.Eligibility criteria for selecting studiesStudies that included adults (≥18 years), a longitudinal follow-up, considered US Environmental Protection Agency criteria air pollutants and proxies of traffic pollution, averaged exposure over a year or more, and reported associations between ambient pollutants and clinical dementia. Two authors independently extracted data using a predefined data extraction form and assessed risk of bias using the Risk of Bias In Non-randomised Studies of Exposures (ROBINS-E) tool. A meta-analysis with Knapp-Hartung standard errors was done when at least three studies for a given pollutant used comparable approaches.Results2080 records identified 51 studies for inclusion. Most studies were at high risk of bias, although in many cases bias was towards the null. 14 studies could be meta-analysed for particulate matter <2.5 µm in diameter (PM2.5). The overall hazard ratio per 2 μg/m3 PM2.5 was 1.04 (95% confidence interval 0.99 to 1.09). The hazard ratio among seven studies that used active case ascertainment was 1.42 (1.00 to 2.02) and among seven studies that used passive case ascertainment was 1.03 (0.98 to 1.07). The overall hazard ratio per 10 μg/m3 nitrogen dioxide was 1.02 ((0.98 to 1.06); nine studies) and per 10 μg/m3 nitrogen oxide was 1.05 ((0.98 to 1.13); five studies). Ozone had no clear association with dementia (hazard ratio per 5 μg/m3 was 1.00 (0.98 to 1.05); four studies).ConclusionPM2.5 might be a risk factor for dementia, as well as nitrogen dioxide and nitrogen oxide, although with more limited data. The meta-analysed hazard ratios are subject to limitations that require interpretation with caution. Outcome ascertainment approaches differ across studies and each exposure assessment approach likely is only a proxy for causally relevant exposure in relation to clinical dementia outcomes. Studies that evaluate critical periods of exposure and pollutants other than PM2.5, and studies that actively assess all participants for outcomes are needed. Nonetheless, our results can provide current best estimates for use in burden of disease and regulatory setting efforts.Systematic review registrationPROSPERO CRD42021277083.

Project description:IntroductionAir pollution is speculated to increase the risk of Coronavirus disease-2019 (COVID-19). Nevertheless, the results remain inconsistent and inconclusive. This study aimed to explore the association between ambient air pollution (AAP) and COVID-19 risks using a meta-analysis with meta-regression modelling.MethodsThe inclusion criteria were: original studies quantifying the association using effect sizes and 95 % confidence intervals (CIs); time-series, cohort, ecological or case-crossover peer-reviewed studies in English. Exclusion criteria encompassed non-original studies, animal studies, and data with common errors. PubMed, Web of Science, Embase and Google Scholar electronic databases were systemically searched for eligible literature, up to 31, March 2023. The risk of bias (ROB) was assessed following the Agency for Healthcare Research and Quality parameters. A random-effects model was used to calculate pooled risk ratios (RRs) and their 95 % CIs.ResultsA total of 58 studies, between 2020 and 2023, met the inclusion criteria. The global representation was skewed, with major contributions from the USA (24.1 %) and China (22.4 %). The distribution included studies on short-term (43.1 %) and long-term (56.9 %) air pollution exposure. Ecological studies constituted 51.7 %, time-series-27.6 %, cohorts-17.2 %, and case crossover-3.4 %. ROB assessment showed low (86.2 %) and moderate (13.8 %) risk. The COVID-19 incidences increased with a 10 μg/m3 increase in PM2.5 [RR = 4.9045; 95 % CI (4.1548-5.7895)], PM10 [RR = 2.9427: (2.2290-3.8850)], NO2 [RR = 3.2750: (3.1420-3.4136)], SO2 [RR = 3.3400: (2.7931-3.9940)], CO [RR = 2.6244: (2.5208-2.7322)] and O3 [RR = 2.4008: (2.1859-2.6368)] concentrations. A 10 μg/m3 increase in concentrations of PM2.5 [RR = 3.0418: (2.7344-3.3838)], PM10 [RR = 2.6202: (2.1602-3.1781)], NO2 [RR = 3.2226: (2.1411-4.8504)], CO [RR = 1.8021 (0.8045-4.0370)] and O3 [RR = 2.3270 (1.5906-3.4045)] was significantly associated with COVID-19 mortality. Stratified analysis showed that study design, exposure period, and country influenced exposure-response associations. Meta-regression model indicated significant predictors for air pollution-COVID-19 incidence associations.ConclusionThe study, while robust, lacks causality demonstration and focuses only on the USA and China, limiting its generalizability. Regardless, the study provides a strong evidence base for air pollution-COVID-19-risks associations, offering valuable insights for intervention measures for COVID-19.

Dataset Information

Association between ambient air pollution and diabetes mellitus in Europe and North America: systematic review and meta-analysis.

Background

Objectives

Methods

Results

Conclusion

Publications

Association between ambient air pollution and diabetes mellitus in Europe and North America: systematic review and meta-analysis.

Similar Datasets

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