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Associations of Exposure to Air Pollution with Insulin Resistance: A Systematic Review and Meta-Analysis
In this article, we review the available evidence and explore the association between air pollution and insulin resistance (IR) using meta-analytic techniques. Cohort studies published before January 2018 were selected through English-language literature searches in nine databases. Six cohort studie...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6266153/ https://www.ncbi.nlm.nih.gov/pubmed/30463387 http://dx.doi.org/10.3390/ijerph15112593 |
Sumario: | In this article, we review the available evidence and explore the association between air pollution and insulin resistance (IR) using meta-analytic techniques. Cohort studies published before January 2018 were selected through English-language literature searches in nine databases. Six cohort studies were included in our sample, which assessed air pollutants including PM(2.5) (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm), NO(2)(nitrogen dioxide), and PM(10) (particulate matter with an aerodynamic diameter less than 10 μm). Percentage change in insulin or insulin resistance associated with air pollutants with corresponding 95% confidence interval (CI) was used to evaluate the risk. A pooled effect (percentage change) was observed, with a 1 μg/m(3) increase in NO(2) associated with a significant 1.25% change (95% CI: 0.67, 1.84; I(2) = 0.00%, p = 0.07) in the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) and a 0.60% change (95% CI: 0.17, 1.03; I(2) = 30.94%, p = 0.27) in insulin. Similar to the analysis of NO(2), a 1 μg/m(3) increase in PM(10) was associated with a significant 2.77% change (95% CI: 0.67, 4.87; I(2) = 94.98%, p < 0.0001) in HOMA-IR and a 2.75% change in insulin (95% CI: 0.45, 5.04; I(2) = 58.66%, p = 0.057). No significant associations were found between PM(2.5) and insulin resistance biomarkers. We conclude that increased exposure to air pollution can lead to insulin resistance, further leading to diabetes and cardiometabolic diseases. Clinicians should consider the environmental exposure of patients when making screening and treatment decisions for them. |
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