A systematic review on the association of month and season of birth with future anthropometric measures

BACKGROUND

Prenatal factors might have some health impacts later in life. This study aims to systematically review the current literature on the association between season and month of birth with birth weight as well as with weight status in childhood.

METHODS

The search process was conducted in electronic databases, including papers published until April 2019 in ISI Web of Science, PubMed, Scopus, and Google Scholar. The following search strategy was used with MeSH terms: ("Seasons"[Mesh]) AND ("Obesity"[Mesh] OR "Pediatric Obesity"[Mesh] OR "Obesity, Abdominal"[Mesh] OR "Overweight"[Mesh] OR "Birth Weight"[Mesh] OR "Body Height"[Mesh]). After the selection process, 50 papers were included in this systematic review.

RESULTS

This review showed that individuals who are born in cold season (winter month) have higher body mass index (BMI) and weight in childhood. Birth in March was associated with lower weight and BMI in boys according to most studies. All studies, except one of them, showed that season/month of birth was not associated with birth weight.

CONCLUSIONS

This systematic review confirms a relationship between season and month of birth with birth weight and body size in childhood; however, the impact of confounding factors, for example, vitamin D status, should be considered in the underlying pathway of this association.

IMPACT

The results provide evidence for the effect of season and month of birth on body size in childhood. Our systematic review suggests that there is no pattern between birth weight and season/month of birth, and the occurrence of low birth weight was more frequent among infants who were born in summer than others. Further research should focus on identifying the impact of confounding factors, for example, vitamin D status in the underlying pathway of this association. There was response to the controversial findings about the effect of environment factors, such as season and month of birth, and future anthropometric indices, such as obesity, weight, height, and birth weight. Obesity is a complex and multifactorial disorder; the findings of the current study would be useful in determining the relationship pathway between the season and the month of birth with other underlying factors for childhood obesity.

Systematic review and meta-analysis on the association between phthalates exposure and insulin resistance

This study aims to provide an overview of human studies on the association of exposure to phthalates and insulin resistance. We systematically searched human studies available until 15 January 2018.We conducted a literature search in Scopus, ISI Web of Science, PubMed, Google Scholar, and Cochrane Collaboration. We used the following keywords to identify relevant articles: "phthalate", "phthalate ester", "metabolic syndrome", "insulin resistance", "glucose intolerance", and "diabetes". For analyzing data, we conducted meta-analysis using the Stata software. We appraised each study to examine the sources of heterogeneity, including difference in clinical outcomes and exposure measurements. To determine the robustness and whether some of the factors have the highest impact on the results of the present meta-analysis, several sensitivity analyses were conducted. Sensitivity analysis showed that by removing studies with the highest weight and age groups, no change was observed in heterogeneity. Moreover, with excluding the study conducted in Europe, the results remained unchanged and constant. In addition, the funnel plot and Egger's tests were executed to access publication bias. Both the funnel plots and Egger's test did not show any evidence of publication bias (P = 0.31). In the random effects meta-analysis of all studies (n = 8), the pooled correlation coefficient between phthalate exposure and HOMA-IR was 0.10 (95% CI; 0.07-0.12, P < 0.001), with significant heterogeneity (P < 0.001, I² = 85.5%). Our findings revealed positive association between exposure to phthalate metabolites and increased HOMA-IR; this association remained significant even after adjusting the analysis for multiple confounding variables.