Seasonal variations in incidence and maternal-fetal outcomes of gestational diabetes

Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM.

METHODS

Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA).

RESULTS

A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers.

CONCLUSIONS

Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

Seasonal Pattern in Gestational Diabetes Mellitus in Poland: A Retrospective Cohort Study

The existing literature does not address the question of the seasonal impact on pregnancy in Central-Eastern Europe; therefore, this study was designed to investigate the seasonal variation in gestational diabetes mellitus (GDM) based on a recent Polish sample. The data of 30,205 newborns from singleton pregnancies and their mothers, including the date and gestational age of birth, neonatal sex and weight, maternal age and parity, mode of delivery, ethnicity, and a detailed list of comorbidities (including GDM), were retrospectively analysed. The prevalence of GDM was significantly (p < 0.0001) lower in spring (14.71%) than in the other seasons (16.78%). A higher incidence of GDM was observed for mothers who underwent an oral glucose tolerance test from June to August compared to those who were tested from December to February (17.34% vs. 14.75%, p < 0.0001). Similarly, there were significant differences between seasons with higher and lower insolation. The regression analysis revealed that seasonal patterns were significantly associated with the prevalence of GDM. In conclusion, this large retrospective cohort study demonstrated seasonal changes in GDM risk. The observed seasonal patterns may equally refer to mothers of babies born at term and prematurely. Further research concerning GDM risk and other seasonal and gender associations is warranted.

Examining the Relationship Between Extreme Temperature, Microclimate Indicators, and Gestational Diabetes Mellitus in Pregnant Women Living in Southern California

Few studies have assessed extreme temperatures' impact on gestational diabetes mellitus (GDM). We examined the relation between GDM risk with weekly exposure to extreme high and low temperatures during the first 24 weeks of gestation and assessed potential effect modification by microclimate indicators.

Methods

We utilized 2008-2018 data for pregnant women from Kaiser Permanente Southern California electronic health records. GDM screening occurred between 24 and 28 gestational weeks for most women using the Carpenter-Coustan criteria or the International Association of Diabetes and Pregnancy Study Groups criteria. Daily maximum, minimum, and mean temperature data were linked to participants' residential address. We utilized distributed lag models, which assessed the lag from the first to the corresponding week, with logistic regression models to examine the exposure-lag-response associations between the 12 weekly extreme temperature exposures and GDM risk. We used the relative risk due to interaction (RERI) to estimate the additive modification of microclimate indicators on the relation between extreme temperature and GDM risk.

Results

GDM risks increased with extreme low temperature during gestational weeks 20--24 and with extreme high temperature at weeks 11-16. Microclimate indicators modified the influence of extreme temperatures on GDM risk. For example, there were positive RERIs for high-temperature extremes and less greenness, and a negative RERI for low-temperature extremes and increased impervious surface percentage.

Discussion

Susceptibility windows to extreme temperatures during pregnancy were observed. Modifiable microclimate indicators were identified that may attenuate temperature exposures during these windows, which could in turn reduce the health burden from GDM.

Seasonal variation in gestational diabetes mellitus among women in Norway: a national population-based study

OBJECTIVES

Previous research on seasonal variation in the incidence of gestational diabetes mellitus (GDM) has shown inconclusive results. Furthermore, little is known about whether a seasonal variation in GDM might be associated with the maternal country of birth. We examined whether there was seasonal variation in GDM incidence by the maternal country background.

DESIGN

National population-based registry study.

SETTING AND PARTICIPANTS

We used national population-based data from the Medical Birth Registry of Norway (MBRN), n=1 443 857 (1990-2016) and data from four merged community-based studies (4GDM) with universal screening for GDM, n=2 978 (2002-2013).

OUTCOME MEASURES

The association between season of pregnancy onset with incidence of GDM was examined separately in both datasets using logistic regression analyses, stratified by the mother's country background using two broad geographical categories (MBRN: Norwegian and immigrant; 4GDM: European and African/Asian ethnicity). Winter season was used as reference category.

RESULTS

The incidence of GDM in MBRN was highest when the pregnancy started during the winter (Norwegian-born: 1.21%; immigrants: 3.32%) and lowest when pregnancy started during the summer for both Norwegian and immigrant women (Norwegian-born: 1.03% (OR 0.85, 95% CI 0.81 to 0.98); immigrants: 2.99% (OR 0.90, 95% CI 0.84 to 0.96)). The 4GDM data showed that women with European ancestry had the highest incidence of GDM when pregnancy started during autumn (10.7%, OR 1.01, 95% CI 0.69 to 1.46) and winter (10.6%), while ethnic African and Asian women had the highest incidence when pregnancy onset was during the summer (15.3%, OR 1.17, 95% CI 0.54 to 2.53).

CONCLUSIONS

Based on national population-based data, this study suggests that GDM incidence varies by season in both Norwegian-born and immigrant women. The 4GDM dataset did not show a clear seasonal variation in GDM incidence, possibly due to the relatively small sample. Causes for the seasonal variation in GDM should be explored further.

Environmental health influences in pregnancy and risk of gestational diabetes mellitus: a systematic review

Background

Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications globally. Environmental risk factors may lead to increased glucose levels and GDM, which in turn may affect not only the health of the mother but assuming hypotheses of "fetal programming", also the health of the offspring. In addition to traditional GDM risk factors, the evidence is growing that environmental influences might affect the development of GDM. We conducted a systematic review analyzing the association between several environmental health risk factors in pregnancy, including climate factors, chemicals and metals, and GDM.

Methods

We performed a systematic literature search in Medline (PubMed), EMBASE, CINAHL, Cochrane Library and Web of Science Core Collection databases for research articles published until March 2021. Epidemiological human and animal model studies that examined GDM as an outcome and / or glycemic outcomes and at least one environmental risk factor for GDM were included.

Results

Of n = 91 studies, we classified n = 28 air pollution, n = 18 persistent organic pollutants (POP), n = 11 arsenic, n = 9 phthalate n = 8 bisphenol A (BPA), n = 8 seasonality, n = 6 cadmium and n = 5 ambient temperature studies. In total, we identified two animal model studies. Whilst we found clear evidence for an association between GDM and air pollution, ambient temperature, season, cadmium, arsenic, POPs and phthalates, the findings regarding phenols were rather inconsistent. There were clear associations between adverse glycemic outcomes and air pollution, ambient temperature, season, POPs, phenols, and phthalates. Findings regarding cadmium and arsenic were heterogeneous (n = 2 publications in each case).

Conclusions

Environmental risk factors are important to consider in the management and prevention of GDM. In view of mechanisms of fetal programming, the environmental risk factors investigated may impair the health of mother and offspring in the short and long term. Further research is needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13965-5.

Effect of Elevated Ambient Temperature on Maternal, Foetal, and Neonatal Outcomes: A Scoping Review

This scoping review provides an overview of the published literature, identifies research gaps, and summarises the current evidence of the association between elevated ambient temperature exposure during pregnancy and adverse maternal, foetal, and neonatal outcomes. Following the PRISMA extension for scoping reviews reporting guidelines, a systematic search was conducted on CINAHL, PubMed, and Embase and included original articles published in the English language from 2015 to 2020 with no geographical limitations. A total of seventy-five studies were included, conducted across twenty-four countries, with a majority in the USA (n = 23) and China (n = 13). Study designs, temperature metrics, and exposure windows varied considerably across studies. Of the eighteen heat-associated adverse maternal, foetal, and neonatal outcomes identified, pre-term birth was the most common outcome (n = 30), followed by low birth weight (n = 11), stillbirth (n = 9), and gestational diabetes mellitus (n = 8). Overall, papers reported an increased risk with elevated temperature exposures. Less attention has been paid to relationships between heat and the diverse range of other adverse outcomes such as congenital anomalies and neonatal mortality. Further research on these less-reported outcomes is needed to improve understanding and the effect size of these relationships with elevated temperatures, which we know will be exacerbated by climate change.

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

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.

Temporal variations in maternal treatment requirements and early neonatal outcomes in patients with gestational diabetes

AIMS

There is seasonal variation in the incidence of gestational diabetes (GDM) and delivery outcomes of affected patients. We assessed whether there was also evidence of temporal variation in maternal treatment requirements and early neonatal outcomes.

METHODS

We performed a retrospective analysis of women diagnosed with GDM (75 g oral glucose tolerance test, 0 h ≥ 5.1; 1 h ≥ 10.0; 2 h ≥ 8.5 mmol/L) in a UK tertiary obstetric centre (2015-2019) with a singleton infant. Data regarding demographic characteristics, total insulin requirements and neonatal outcomes were extracted from contemporaneous electronic medical records. Linear/logistic regression models using month of the year as a predictor of outcomes were used to assess annual variation.

RESULTS

In all, 791 women (50.6% receiving pharmacological treatment) and 790 neonates were included. The likelihood of requiring insulin treatment was highest in November (p < 0.05). The average total daily insulin dose was higher at peak (January) compared to average by 19 units/day (p < 0.05). There was no temporal variation in neonatal intensive care admission, or neonatal capillary blood glucose. However, rates of neonatal hypoglycaemia (defined as <2.6 mmol/L) were highest in December (40% above average; p < 0.05).

CONCLUSIONS

Women with GDM diagnosed in winter are more likely to require insulin treatment and to require higher insulin doses. Neonates born to winter-diagnosed mothers had a corresponding increased risk of neonatal hypoglycaemia. Maternal treatment requirements and neonatal outcomes of GDM vary significantly throughout the year, even in a relatively temperate climate.

Approaches to screening for hyperglycaemia in pregnant women during and after the COVID-19 pandemic

AIM

To evaluate the diagnostic and prognostic performance of alternative diagnostic strategies to oral glucose tolerance tests, including random plasma glucose, fasting plasma glucose and HbA_1c , during the COVID-19 pandemic.

METHODS

Retrospective service data (Cambridge, UK; 17 736 consecutive singleton pregnancies, 2004-2008; 826 consecutive gestational diabetes pregnancies, 2014-2019) and 361 women with ≥1 gestational diabetes risk factor (OPHELIA prospective observational study, UK) were included. Pregnancy outcomes included gestational diabetes (National Institute of Health and Clinical Excellence or International Association of Diabetes and Pregnancy Study Groups criteria), diabetes in pregnancy (WHO criteria), Caesarean section, large-for-gestational age infant, neonatal hypoglycaemia and neonatal intensive care unit admission. Receiver-operating characteristic curves and unadjusted logistic regression were used to compare random plasma glucose, fasting plasma glucose and HbA_1c performance.

RESULTS

Gestational diabetes diagnosis was significantly associated with random plasma glucose at 12 weeks [area under the receiver-operating characteristic curve for both criteria 0.81 (95% CI 0.79-0.83)], fasting plasma glucose [National Institute of Health and Clinical Excellence: area under the receiver-operating characteristic curve 0.75 (95% CI 0.65-0.85); International Association of Diabetes and Pregnancy Study Groups: area under the receiver-operating characteristic curve 0.92 (95% CI 0.85-0.98)] and HbA_1c at 28 weeks' gestation [National Institute of Health and Clinical Excellence: 0.83 (95% CI 0.75-0.90); International Association of Diabetes and Pregnancy Study Groups: 0.84 (95% CI 0.77-0.91)]. Each measure predicts some, but not all, pregnancy outcomes studied. At 12 weeks, ~5% of women would be identified using random plasma glucose ≥8.5 mmol/l (sensitivity 42%; specificity 96%) and at 28 weeks using HbA_1c ≥39 mmol/mol (sensitivity 26%; specificity 96%) or fasting plasma glucose ≥5.2-5.4 mmol/l (sensitivity 18-41%; specificity 97-98%).

CONCLUSIONS

Random plasma glucose at 12 weeks, and fasting plasma glucose or HbA_1c at 28 weeks identify women with hyperglycaemia at risk of suboptimal pregnancy outcomes. These opportunistic laboratory tests perform adequately for risk stratification when oral glucose tolerance testing is not available.

Climate factors and gestational diabetes mellitus risk - a systematic review

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.