Systematic review and meta-analysis on the association between seasonal variation and gestational diabetes mellitus

Abstract

Recently, there is growing evidence that ambient temperature and seasonal changes are related to the incidence of gestational diabetes mellitus (GDM). Thereby, this study was conducted to evaluate the association between seasonal changes and ambient temperature and GDM. We conducted a systematic search in PubMed, ISI Web of Science, Scopus, Google Scholar, and Cochrane Collaboration for human studies available until the end of 2020. We used the following keywords to identify relevant articles: "Diabetes, Gestational" (MeSH), "Glucose Tolerance Test" (MeSH), "Glucose intolerance" (MeSH), "Pregnancy outcome" (MeSH), "Birth outcome", "Seasons" (MeSH), "Weather" (MeSH), "Ambient Temperature," "Climate Change" (MeSH). Meta-analyses by using STATA software were conducted for analyzing data. Due to the high heterogeneity between included studies, a random-effects model was used. Subgroup analysis, meta-regression, and sensitivity analysis were used to define a source of heterogeneity. We found 13 studies related to the association between ambient temperature and season changes and GDM, which 11 of them were included in meta-analyses. Despite inconsistencies in outcome assessment across studies, we found a significant positive association between seasons of GDM screening and risk of GDM (pooled OR=1.12; 95 CI (1.03, 1.21)). The funnel plot and Egger's test showed that there was no significant publication bias among these studies (p=0.51). In general, season changes showed a significant positive relationship with prevalence of GDM. However, due to the unknown exact mechanism on this association, further studies should be conducted.