Prevalence and risk factors of gestational diabetes mellitus: findings from a universal screening feasibility program in Lima, Peru

Characterization of hair cortisol concentration pre-conception and during pregnancy

BACKGROUND

The hypothalamic pituitary adrenal (HPA) axis is a system involved in stress and pregnancy regulation, and hair cortisol concentration (HCC) is a promising biomarker of its activity. Assessing factors that influence HCC in the prenatal period is critical to understand whether and how HPA axis (dys-)regulation influences maternal health and child development, particularly in high-risk populations from low- and middle-income countries (LMICs).

AIMS

This study aimed at characterizing preconception and pregnancy HCC with respect to multiple sociodemographic, pregnancy-related, and hair-related factors.

METHODS

In a sample of N = 2581 pregnant women in Perú, participants from two cohort studies provided a 6 cm scalp hair sample at three prenatal timepoints. Each hair sample was cut into two segments of 3 cm that represent cortisol secretion at four times: preconception, first-, second- and third trimester of pregnancy. Hair cortisol was extracted using liquid chromatography tandem mass spectrometry (LC-MS/MS). Spearman correlations, paired t-tests, and ANOVA were used to assess differences in log-transformed values of HCC (logHCC) across maternal sociodemographic, pregnancy-related, and hair-related factors. Multivariable linear regressions were used to examine independent associations of HCCs with selected correlates.

RESULTS

Mean logHCC values showed an increase across the four prenatal periods. Preconception BMI was consistently associated with HCC in all three trimesters, while difficulty accessing basic foods, education, hair dyeing, and infant sex showed time-specific associations with HCCs. In sensitivity analyses, we detected no substantial segment effects in the associations of HCCs with maternal characteristics.

CONCLUSION

This study is the largest to characterize HCC in pregnant women from a LMIC. Our findings provide a foundation for the use of HCC as a biomarker of prenatal HPA axis activity for future studies. This foundation may contribute to finding valid biomarkers of stress-response systems to promote maternal and child health.

Epidemiology of hyperglycemia during pregnancy in Ethiopia: prevalence, associated factors, and feto-maternal outcomes: systematic review and meta-analysis

BACKGROUND

Hyperglycemia in pregnancy (HIP) is a significant medical complication affecting pregnant women globally and is considered a public health burden due to the negative outcomes it can cause for both mother and infant. The aim of this systematic review and meta-analysis was to examine the prevalence, risk factors, and feto-maternal outcomes of HIP in Ethiopia.

METHODS

To gather relevant information for this study, both published and unpublished studies were searched for in several major databases, including PubMed, Embase, HINARI, Web of Science direct, and Google Scholar, as well as other sources. The Joanna Briggs Institute (JBI) tool was used to evaluate the methodological quality of the findings from these studies. Data was then extracted and summarized using a template in Microsoft Excel software, and the extracted data was analyzed using Stata software version 16.0. If significant heterogeneity was found between studies, subgroup analyses were conducted to further examine the data.

RESULT

Eighteen studies were included in this systematic review and meta-analysis, involving a total sample size of 50,816 pregnant women in Ethiopia. The prevalence of HIP among pregnant women varied considerably across the primary studies, ranging from 0.4 to 26.2%. The pooled prevalence of HIP among pregnant women in Ethiopia was found to be 6.9% (95% C 2.2-11.6). Pregnant women with a family history of diabetes had 2.5 times higher odds of developing HIP compared to those without a family history of diabetes (OR = 2.49; 95% CI = 2.02, 2.96). However, there was no significant association found between HIP and maternal obesity (OR 2.31, 95% CI = 0.85, 3.78) or previous history of abortion (OR 3.89; 95% CI 0.85, 6.94). The common fetal outcomes associated with HIP were admission to the intensive care unit (46.2; 95% CI 27.4, 65.1), macrosomia (27.3%; 95% CI 9.4%, 45.1%), and preterm birth (16.9; 95% CI 12.5, 21.3). Additionally, hypertensive disorders of pregnancy (28.0%; 95% CI 15.2, 40.8) and operative delivery (51.4%; 95% CI 35.9, 66.8) were more common among women with HIP in Ethiopia.

CONCLUSION

Although there was some variation between studies, the meta-analysis revealed that approximately seven out of 100 pregnant women in Ethiopia had HIP. A family history of diabetes was found to be a significant predictor of HIP in Ethiopia. Additionally, HIP was associated with various serious adverse outcomes for both mothers and infants in Ethiopia. These findings highlight the need for national guidelines to ensure that pregnant women are uniformly screened for HIP.

Gestational diabetes and risk of perinatal depression in low- and middle-income countries: a meta-analysis

Background

The relationship between gestational diabetes (GDM) and the risk of depression has been thoroughly investigated in high-income countries on their financial basis, while it is largely unexplored in low- and middle- income countries. This meta-analysis aims to assess how GDM influences the risk of perinatal depression by searching multiple electronic databases for studies measuring the odds ratios between them in low- and middle-income countries.

Methods

Two independent reviewers searched multiple electronic databases for studies that investigated GDM and perinatal mental disorders on August 31, 2023. Pooled odds ratios (ORs) and confidence intervals (CIs) were calculated using the random effect model. Subgroup analyses were further conducted based on the type of study design and country income level.

Results

In total, 16 observational studies met the inclusion criteria. Only the number of studies on depression (n=10) satisfied the conditions to conduct a meta-analysis, showing the relationship between mental illness and GDM has been overlooked in low- and middle-income countries. Evidence shows an elevated risk of perinatal depression in women with GDM (pooled OR 1.92; 95% CI 1.24, 2.97; 10 studies). The increased risk of perinatal depression in patients with GDM was not significantly different between cross-sectional and prospective design. Country income level is a significant factor that adversely influences the risk of perinatal depression in GDM patients.

Conclusion

Our findings suggested that women with GDM are vulnerable to perinatal depressive symptoms, and a deeper understanding of potential risk factors and mechanisms may help inform strategies aimed at prevention of exposure to these complications during pregnancy.

Psychometric properties of the Persian version of the Fleishman Job Analysis Survey (FJAS)

BACKGROUND

Job analysis is one of the most important and widely used processes to determine job duties, identify and reduce potential risks, and specify the skills and facilities required for each job at the highest level of occupational safety and health.

OBJECTIVE

This study aimed to perform psychometric analyses of the Persian version of the Fleishman Job Analysis Survey (FJAS).

METHODS

A cross-sectional study was conducted among 31 drivers. Participants were selected by random sampling. Ten occupational health and ergonomics experts confirmed the validity of the survey. First, we calculated the survey's CVR and CVI. Then, we used ICC and Cronbach's alpha coefficients to evaluate the survey's reliability. Data analysis utilized SPSS 21.

RESULTS

78% of the participants were male and 22% were female. The mean age±SD of the participants was 39.1±11.82 years. The reliability and validity of the short version survey showed that the value of ICC and Cronbach's alpha coefficient was 0.96, and CVR was 0.75. Moreover, the values of CVI for simplicity, clarity, and relevance were 0.87, 1, and 0.73, respectively. The long version's ICC and CVR were 0.96 and 0.97, respectively. Simplicity, clarity, and relevance CVI scores were 0.9, 0.94, and 0.95.

CONCLUSION

The results of this study showed that the Persian version of the Fleischman Job Analysis Survey has the necessary validity and reliability for job analysis, so it can be used for driving professional or research purposes. Moreover, this survey is an effective tool for obtaining accurate and complete knowledge of job tasks and requirements.

Prevalence of gestational diabetes mellitus and associated factors among women receiving antenatal care at a tertiary hospital in South-Western Uganda

INTRODUCTION

gestational diabetes mellitus is one of the major causes of morbidity and mortality among pregnant women worldwide. We aimed to determine the prevalence and factors associated with gestational diabetes mellitus among women attending the antenatal care clinic at a tertiary care hospital in South-Western Uganda.

METHODS

this was a hospital-based cross-sectional study conducted among women at ≥24 weeks of amenorrhea attending the antenatal care clinic at Mbarara Regional Referral Hospital between December 2020 and March 2021. We screened all women for gestational diabetes mellitus using the World Health Organization 2013 diagnostic criteria. We obtained socio-demographic, medical, and obstetric data. Multivariable logistic regression was used to determine the factors independently associated with gestational diabetes mellitus.

RESULTS

we enrolled 343 pregnant women with a mean age of 27.3 (SD ±12.3) years. Of the 343 participants, 35 (10.2%) had gestational diabetes mellitus (GDM) (95% C.I: 7.4%-13.9%) and 7 (2%) had diabetes in pregnancy. The factors significantly associated with gestational diabetes mellitus were; previous history of foetal macrosomia in any of the previous pregnancies (aOR: 5.53, 95% C.I: 1.29-23.65) and family history of diabetes mellitus in the first-degree relatives (aOR: 4.45, 95% C.I:1.48-13.34).

CONCLUSION

one in every ten pregnant women attending the antenatal care clinic at Mbarara Regional Referral Hospital is likely to have gestational diabetes mellitus in pregnancy. There is a need to strengthen routine testing for gestational diabetes mellitus among women attending the antenatal care clinic, especially pregnant women with a prior history of foetal macrosomia and a family history of diabetes mellitus in first-degree relatives.

Correlates of preconception and pregnancy hair cortisol concentrations

Assessing factors that influence chronic stress biomarkers like hair cortisol concentrations (HCCs) in pregnancy is critical to prevent adverse pregnancy outcomes. Thus, we aimed to identify correlates of HCC preconception and during pregnancy. 2,581 pregnant women participated in the study. HCC was available at four time periods: pre-pregnancy (0-3 months preconception, n = 1,023), and in the first (1-12 weeks, n = 1,734), second (13-24 weeks, n = 1,534), and third (25-36 weeks, n = 835) trimesters. HCC was assessed using liquid chromatography tandem mass spectrometry (LC-MS/MS). Sociodemographic, pregnancy- and hair-related characteristics, and measures of psychosocial stress, were interrogated as potential correlates of HCC. Spearman correlations, paired t-tests, and ANOVA were used to assess differences in log-transformed values of HCC (logHCC) across maternal characteristics. Multivariable linear regressions were used to identify the correlates of HCCs after adjusting for confounders. Mean logHCC values increased across the four prenatal periods (P < 0.001). In multivariable analyses, pre-pregnancy BMI was consistently associated with all HCCs, while gestational age, economic hardship, hair dyeing, and depression, showed time-specific associations with HCC. In conclusion, this study showed evidence of factors influencing HCC levels before and during pregnancy. The most consistent association was seen with pre-pregnancy BMI. Depression was also associated with HCC concentrations.

Pre-pregnancy weight, the rate of gestational weight gain, and the risk of early gestational diabetes mellitus among women registered in a tertiary care hospital in India

BACKGROUND

The impact of pre-pregnancy weight and the rate of gestational weight gain (GWG) together on the risk of early GDM (< 24 weeks gestation; eGDM) has not been studied in the Indian context. We aimed to study the influence of (1) pre-pregnancy weight on the risk of eGDM diagnosed in two time intervals; and (2) in addition, the rate of GWG by 12 weeks on the risk of eGDM diagnosed in 19-24 weeks.

METHOD

Our study utilized real-world clinical data on pregnant women routinely collected at an antenatal care clinic at a private tertiary hospital, in Pune, India. Women registering before 12 weeks of gestation (v1), with a singleton pregnancy, and having a follow-up visit between 19-24 weeks (v2) were included (n = 600). The oral glucose tolerance test was conducted universally as per Indian guidelines (DIPSI) at v1 and v2 for diagnosing eGDM. The data on the onset time of eGDM were interval censored; hence, we modeled the risk of eGDM using binomial regression to assess the influence of pre-pregnancy weight on the risk of eGDM in the two intervals. The rate of GWG by 12 weeks was added to assess its impact on the risk of eGDM diagnosed in v2.

RESULT

Overall, 89 (14.8%) women (age 32 ± 4 years) were diagnosed with eGDM by 24 weeks, of which 59 (9.8%) were diagnosed before 12 weeks and 30 of 541 (5.5%) women were diagnosed between 19-24 weeks. Two-thirds (66%) of eGDM were diagnosed before 12 weeks of gestation. Women's pre-pregnancy weight was positively associated with the risk of GDM in both time intervals though the lower confidence limit was below zero in v1. The rate of GWG by 12 weeks was not observed to be associated with the risk of eGDM diagnosed between 19-24 weeks of gestation. These associations were independent of age, height, and parity.

CONCLUSION

Health workers may focus on pre-pregnancy weight, a modifiable risk factor for eGDM. A larger community-based study measuring weight and GDM status more frequently may be warranted to deepen the understanding of the role of GWG as a risk factor for GDM.

Maternal hair cortisol concentrations and its association with increased insulin resistance in midpregnancy

PURPOSE

Stress and elevated maternal glycemia have negative effects on pregnancy. We evaluated the association of hair cortisol concentrations (HCC), a marker of chronic stress, with insulin resistance and gestational diabetes (GDM).

METHODS

In total, 527 women from Lima, Peru, provided a hair sample in the second trimester of their pregnancy to measure HCC using liquid chromatography-tandem mass spectrometry. Each 6 cm of hair captured HCC in early (T1=1-12 weeks) and midpregnancy (T2 = 13-24 weeks). GDM diagnosis was conducted in midpregnancy. Multivariable regression models adjusted for putative risk factorsincluding maternal sociodemographic factors, diabetes history, and hair characteristics, were used to estimate the association of HCC with GDM and various glycemic traits.

RESULTS

GDM was diagnosed in 122 (23%) women. Mean HCC across pregnancy was T1 = 3.7 (±3.4) pg/mg and T2 = 4.8 (±3.4) pg/mg. HCC was associated with increased log-transformed units of fasting insulin (T1 = 0.15 [0.03, 0.27], T2 = 0.17 [0.04, 0.30]), homeostasis model assessment for insulin resistance (T1 = 0.14 [0.01, 0.26], T2 = 0.17 [0.03, 0.30]), and homeostasis model assessment for β-cell function (T1 = 0.20 [0.05, 0.34], T2 = 0.20 [0.04, 0.36]), but not with GDM (T1 = 0.95 [0.63, 1.40], T2 = 1.11 [0.74, 1.67]).

CONCLUSIONS

Elevated maternal HCC was associated with abnormal insulin homeostasis in pregnancy. Dysregulation of the hypothalamic-pituitary-adrenal axis, as reflected by high HCC, may also contribute to insulin resistance syndrome in pregnancy.

Screening and nursing management of gestational diabetes in Ghana: Evidence-based recommendations

Objective

To describe the development of evidence-based recommendations for screening and nursing management of gestational diabetes mellitus (GDM) in Ghana and present the recommendations.

Design

A qualitative study.

Setting

Military Health Institutions in Ghana.

Measurements

Data from qualitative interviews with 7 women with GDM and 8 midwives, and an integrative literature review including available clinical practice guidelines on screening and nursing management of GDM, was used to develop the recommendations. The National Institute for Health and Care Excellence' steps guided the recommendations' development. Methodological quality of the recommendations was assessed based on an adapted version of the Appraisal of Guidelines for Research and Evaluation (AGREE II) tool. Six experts reviewed the recommendations and an infographic in support of the recommendations.

Findings

Two main recommendations and an infographic were developed, including: 1. Early screening and diagnosis of GDM, and 2. Involvement of women with GDM and their significant others during pregnancy, intrapartum and postpartum management, in a culturally and socio-economically appropriate manner.

Key conclusions

The recommendations and infographic, once reviewed and pilot tested, may assist midwives managing GDM in Ghana, with support of health institution management.

Implications for practice

The study highlights the need for recommendations which can be used by midwives to manage GDM in Ghana. The recommendations are the first to be contextualized for the Ghanaian setting.

Gestational diabetes mellitus and its associated factors in Ethiopia: a systematic review and meta-analysis

BACKGROUND

In Ethiopia, gestational diabetes mellitus (GDM) is a significant public health issue and a risk to maternal and child health. Understanding the prevalence and factors of GDM in Ethiopia may also help determine the best interventions. Therefore, we tried to review gestational diabetes and its factors in Ethiopia.AQ: Please check and confirm the edit made to the article title.yes i have checked and confirm METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) instrument was used to conduct the review. In order to report on the prevalence and contributing factors of gestational diabetes mellitus, the following databases were used: Google Scholar, PubMed, EMBASE, Scopus, Web of Sciences, and Grey literature. Pilo-tests were conducted using a standardized data gathering form in research using a random sample. All statistical analyses were performed using STATA version 16 software for Windows and the random-effects meta-analysis method. The results are presented using texts, tables, and forest plots, along with measure of effect and a 95% confidence interval.Affiliations: Please confirm if the author names are presented accurately and in the correct sequence (given name, middle name/initial, family name). Author Given name: [Fentahun Yenealem], Last name [Beyene], Given name: [Bekalu Getnet], Last name [Kassa], Given name: [Gedefaye Nibret], Last name [Mihretie], Given name: [Alemu Degu], Last name [Ayele].yes checked and corrected AQ: Is this word Pilo-tests spelled correctly throughout the article?Thank you the correction Affiliations: Please check and confirm whether the city name is correctly identified for the affiliation 2.yes checked and corrected  RESULTS: Out of 1755 records, 10 studies with 6525 participants that fully satisfy the inclusion criteria were included for the meta-analysis. The pooled prevalence of gestational diabetes mellitus in Ethiopia was 12.04% [95% CI (8.17%, 15.90%)]. Inadequate dietary diversity, high body mass index, having a family history of DM, history of having macrosomic neonate, low physical activity, and previous history of GDM were statistically significant.AQ: Please note that the sentence Inadequate dietary diversity, high body mass index… is repeated under the below heading Conclusion.yes checked and corrected  CONCLUSION: The pooled prevalence of gestational diabetes mellitus is high in Ethiopia. Inadequate dietary diversity, high body mass index, having a family history of DM, history of having macrosomic neonate, low physical activity and previous history of GDM were statically significant variables. Emphasize on early screening, prenatal care and all women having risk factors and trying to get pregnant should get screens for diabetes to improve the maternal and child health at large.AQ: Please check the clarity of the sentence Emphasize on early screening, prenatal…it is clear and easly understand the readers.

Biochemical and molecular biomarkers: unraveling their role in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is the most prevalent metabolic disorder during pregnancy, causing short- and long-term complications for both mother and baby. GDM is a multifactorial disease, and it may be affected by interactions between genetic, epigenetic, and environmental factors. However, the exact etiology is poorly understood. Despite the high prevalence of GDM, there is still debate regarding the optimal time for screening, the diagnostic threshold to apply, and the best strategies for treatment. Identifying effective strategies for therapeutic purposes as well as accurate biomarkers for prognostic and diagnostic purposes will reduce the GDM incidence and improve its management. In recent years, new biochemical and molecular biomarkers such as microRNAs, single-nucleotide polymorphisms, and DNA methylation have received great interest in the diagnosis of GDM. In this review, we discuss current and future diagnostic approaches for the detection of GDM and evaluate lifestyle and pharmacological strategies for GDM prevention.

Longer physical exercise duration prevents abnormal fasting plasma glucose occurrences in the third trimester: Findings from a cohort of women with gestational diabetes mellitus in Shanghai

OBJECTIVE

This study aims to investigate the relationship between daily physical exercise (PE) duration and frequency of abnormal plasma glucose (PG) times both during fasting and 2 h after a standard diet in women with gestational diabetes mellitus (GDM).

METHODS

We established a cohort involving 878 GDM women. GDM was confirmed by a diagnostic 75-g oral glucose tolerance test. Information was extracted from the delivery records and antenatal checkup forms. Physical exercise information was collected through a questionnaire.

RESULTS

Over 80% of GDM women were under 35 years old. An abnormal fasting PG with ≥1 occurrence presented in 742/878 (84.51%), and the abnormal PG 2 h after standard diet with ≥1 occurrence presented in 634/878 (72.21%). Compared to GDM women with ≥4 occurrences of abnormal fasting PG, GDM women with 0 occurrences (odds ratio (OR) = 2.56), one occurrence (OR = 1.94), two occurrences (OR = 2.29), and three occurrences (OR = 2.16) had a higher proportion of PE duration being in the 45-60-min/day group than those in the <45-min/day group, and GDM women also had a higher proportion of PE during being in the 61-90- and >90-min/day group than those in the <45-min/day group. However, the duration of PE was not associated to the number of abnormal PG occurrences 2-h after the standard diet.

CONCLUSION

Moderate-intensity PE duration in GDM women was negatively associated with the number of abnormal fasting PG occurrences but not with the number of PG occurrences 2 h after the standard diet.

Evolution of Gestational Diabetes Mellitus across Continents in 21st Century

Over the last few decades, several definitions of gestational diabetes mellitus (GDM) have been described. There is currently not enough research to show which way is the best to diagnose GDM. Opinions differ in terms of the optimal screening and diagnostic measures, in part due to the differences in the population risks, the cost-effectiveness considerations, and the lack of an evidence base to support large national screening programs. The basic method for identifying the disease is the measurement of glucose plasma levels which may be determined when fasting, two hours after a meal, or simply at any random time. The currently increasing incidence of diabetes in the whole population, the altering demographics and the presence of lifestyle changes still require better methods of screening for hyperglycemia, especially during pregnancy. The main aim of this review is to focus on the prevalence and modifications to the screening criteria for GDM across all continents in the 21st century. We would like to show the differences in the above issues and correlate them with the geographical situation. Looking at the history of diabetes, we are sure that more than one evolution in GDM diagnosis will occur, due to the development of medicine, appearance of modern technologies, and the dynamic continuation of research.

Development and Validation of Risk Prediction Models for Gestational Diabetes Mellitus Using Four Different Methods

Gestational diabetes mellitus (GDM), a common perinatal disease, is related to increased risks of maternal and neonatal adverse perinatal outcomes. We aimed to establish GDM risk prediction models that can be widely used in the first trimester using four different methods, including a score-scaled model derived from a meta-analysis using 42 studies, a logistic regression model, and two machine learning models (decision tree and random forest algorithms). The score-scaled model (seven variables) was established via a meta-analysis and a stratified cohort of 1075 Chinese pregnant women from the Northwest Women's and Children's Hospital (NWCH) and showed an area under the curve (AUC) of 0.772. The logistic regression model (seven variables) was established and validated using the above cohort and showed AUCs of 0.799 and 0.834 for the training and validation sets, respectively. Another two models were established using the decision tree (DT) and random forest (RF) algorithms and showed corresponding AUCs of 0.825 and 0.823 for the training set, and 0.816 and 0.827 for the validation set. The validation of the developed models suggested good performance in a cohort derived from another period. The score-scaled GDM prediction model, the logistic regression GDM prediction model, and the two machine learning GDM prediction models could be employed to identify pregnant women with a high risk of GDM using common clinical indicators, and interventions can be sought promptly.

Incidence and risk factors of gestational diabetes mellitus in Goba town, Southeast Ethiopia: a prospective cohort study

OBJECTIVE

Gestational diabetes mellitus (GDM) is becoming a public health concern in low/middle-income countries, and is known to cause severe morbidity and mortality for mothers and newborns. However, evidence reported for the incidence and risk factors of GDM is scant in Ethiopia. We aimed to assess the incidence of, and risk factors for, GDM in Goba town, Southeast Ethiopia.

DESIGN

Prospective cohort study.

SETTING

Goba town, Southeast Ethiopia.

PARTICIPANTS

Four hundred eighty pregnant women on antenatal care follow-up from 30 April to 30 September 2021.

PRIMARY AND SECONDARY OUTCOMES

Incidence and risk factors of GDM using fasting capillary blood glucose. Log-binomial model was used to identify the risk factors of GDM. Adjusted relative risk (aRR), along with 95% CIs, were calculated to estimate the strength of associations.

RESULTS

The cumulative incidence rate of GDM in this study was 15.7% (95% CI: 12.3% to 19.2%). Being unemployed (aRR=2.73; 95% CI: 1.36 to 5.47), having a family history of diabetes mellitus (DM) (3.01; 2.09 to 4.35), low physical activity (2.43; 1.11 to 5.32), inadequate dietary diversity (1.48; 1.29 to 1.92), anaemia (2.51; 1.32 to 3.54) and antenatal depression (4.95; 3.35 to 7.31) were significantly associated with GDM.

CONCLUSION

The cumulative incidence of GDM was relatively high among the study participants. Having antenatal depression symptoms, low physical activity, inadequate dietary diversity, being unemployed, anaemia and a family history of DM were significant risk factors for GDM.

Maternal Early-Life Risk Factors and Later Gestational Diabetes Mellitus: A Cross-Sectional Analysis of the UAE Healthy Future Study (UAEHFS)

Limited studies have focused on maternal early-life risk factors and the later development of gestational diabetes mellitus (GDM). We aimed to estimate the GDM prevalence and examine the associations of maternal early-life risk factors, namely: maternal birthweight, parental smoking at birth, childhood urbanicity, ever-breastfed, parental education attainment, parental history of diabetes, childhood overall health, childhood body size, and childhood height, with later GDM. This was a retrospective cross-sectional study using the UAE Healthy Future Study (UAEHFS) baseline data (February 2016 to April 2022) on 702 ever-married women aged 18 to 67 years. We fitted a Poisson regression to estimate the risk ratio (RR) for later GDM and its 95% confidence interval (CI). The GDM prevalence was 5.1%. In the fully adjusted model, females with low birthweight were four times more likely (RR 4.04, 95% CI 1.36-12.0) and females with a parental history of diabetes were nearly three times more likely (RR 2.86, 95% CI 1.10-7.43) to report later GDM. In conclusion, maternal birthweight and parental history of diabetes were significantly associated with later GDM. Close glucose monitoring during pregnancy among females with either a low birth weight and/or parental history of diabetes might help to prevent GDM among this high-risk group.

Previous adverse pregnancy events as a predictor of gestational diabetes mellitus in Southern Ethiopia: a case control study

INTRODUCTION

Gestational diabetes mellitus is a type of glucose intolerance that first manifests itself during pregnancy. A pregnant woman and her unborn child are at an increased risk of pregnancy complications and poor neonatal outcomes. Pregnancy diabetes affects one out of every 200 women. Therefore, this study aims to identify the determinants of gestational diabetes mellitus among pregnant women attending an antenatal care service in Gedeo Zone, Ethiopia.

METHODS

A facility-based case-control study design was employed from 25 January 2020 through 25 April 2020. The study included 80 cases and 240 control groups of pregnant women. Face-to-face interviews with structured questionnaires were used to collect data. For analyses, data was entered into Epidata version 3.1 and exported to the Statistical Package for the Social Sciences (SPSS) version 23.0. Variables with p .25 or lower in bivariate analysis were fitted to multivariable analysis. A multivariable logistic regression model with a 95% confidence interval and a p-Value of .05 was used.

RESULTS

Family history of diabetes mellitus [AOR 1.837; 95% CI (1.06-3.18)], history of spontaneous abortion [AOR 2.39; 95% CI 1.33-4.31), history of still birth [AOR 2.240 (1.222-4.105)], and history of delivery of a macrocosmic baby in the previous pregnancy [AOR 1.99 (1.157-3.43)] were found to be predictors of GDM.

CONCLUSION

Previous adverse pregnancy outcomes were found to be the main predictors of GDM. Women with gestational diabetes mellitus should be followed after delivery in order to monitor hyper-glycemic status.

The Effect of Gestational Diabetes on Depression and Breastfeeding Self-Efficacy in Pregnancy and Postpartum Period

Objective: The purpose of this study was to explore the effect of gestational diabetes mellitus (GDM) on depression and breastfeeding self-efficacy during pregnancy and the postpartum period. Methods: This descriptive study was conducted in Obstetrics and Perinatology clinics of two university hospitals in Turkey between July 2016 and June 2017. Women were followed up two times. The first follow-up was performed face-to-face in the gestational week 34th to 38th and the second one was performed by telephone in the 8th week of the postpartum period. In the first follow-up, 104 pregnant women with GDM and 133 pregnant with non-GDM women were interviewed. In the second follow up, 30 women could not be reached in both groups. Data were collected by the Individual Description Form, Edinburgh Postpartum Depression Scale, and Breastfeeding Self-Efficacy Scale-Short Form. Descriptive statistics, repeated measures analysis of variance and correlation analysis were used in the data analysis. Results: The depression risk of mothers with GDM was found higher compared to non- GDM mothers. No significant difference was found between the depression and breastfeeding self-efficacy mean scores in the antenatal and postpartum period of women by the presence of GDM. There was no significant difference between the depression and breastfeeding self-efficacy mean scores in the antenatal and postpartum period by the presence of GDM and some confounding variables. As the breastfeeding self-efficacy level of mothers with GDM both in the antenatal and postpartum period increased, the depression risk decreased. Conclusion: In the study, it has been concluded that GDM does not have an impact on depression and breastfeeding self-efficacy during pregnancy and in the postpartum period.

Early universal screening of gestational diabetes in a university hospital in Thailand

A total of 1016 pregnant women attending antenatal clinic before 20 weeks of gestation during September 2018 to February 2019 were included in a cohort study with repeated cross-sectional assessments. The study was aimed to determine prevalence and characteristics of gestational diabetes mellitus (GDM) and pregnancy outcomes by early universal screening approach. GDM screening was performed during first visit and repeated during 24-28 weeks of gestation, as necessary, using a 50-g glucose challenge test followed by a 100-g oral glucose tolerance test for GDM diagnosis. Overall prevalence of GDM was 18.6%. A significantly higher prevalence of GDM was observed among high-risk than low-risk women (21.3% vs. 13.1%, p = 0.002). GDM among low-risk women contributed to 23.3% of all GDM cases. The majority of GDM (76.2%) were diagnosed before 20 weeks of gestation, with 74.5% occurring in high-risk women and 81.8% occurring in low-risk women. When initial screening tests were normal, risk of GDM diagnosed during 24-28 weeks was 6.0% (7.5% among high-risk women and 3.1% among low-risk women). Compared to those without GDM, women with GDM significantly had lower gestational weight gain (p < 0.001), higher prevalence of preeclampsia (p = 0.001), large for gestational age (LGA) (p = 0.034) and macrosomia (p = 0.004). These outcomes were more pronounced among high-risk women with GDM. Impact StatementWhat is already known on this subject? Universal GDM screening is recommended during 24-28 weeks of gestation, either by 1- or 2-step approach. Some also recommend early GDM screening among high-risk women. Prevalence of early-onset GDM varies between studies and benefits of early diagnosis and treatment are still controversial.What do the results of this study add? Early universal GDM screening identified more women with GDM and majority could be diagnosed before 20 weeks of gestation. GDM among low-risk women contributed to 23.3% of all cases. Adverse pregnancy outcomes were more common among high-risk women with GDM. This approach could be useful and can be implemented in other settings, especially those that serve high-risk population or with high GDM prevalence.What are the implications of these findings for clinical practice and/or further research? Early universal GDM screening should be considered in settings with high prevalence of GDM and high-risk women. However, benefits of early detection and treatment of GDM should be determined in more details in the future, especially in terms of cost-effectiveness and improvement in pregnancy outcomes.

Adverse pregnancy and perinatal outcomes in Latin America and the Caribbean: systematic review and meta-analysis

Objective.

To estimate the point prevalence and likely ranges of pregnancy-induced hypertension, pre-eclampsia, gestational diabetes, low birth weight and preterm delivery in Latin America and the Caribbean, and evaluate the heterogeneity of the estimates.

Methods.

We conducted a systematic review and meta-analysis of observational studies reporting the prevalence of maternal and perinatal adverse outcomes in populations in Latin American and the Caribbean published between 2000 and 2019 in English, Spanish, or Portuguese. We searched PubMed, Embase, and LILACS. We estimated the point prevalence and evaluated overall heterogeneity and, in sub-group analyses, heterogeneity by study design and level of bias.

Results.

Of 1087 records retrieved, 50 articles were included in the review: two on hypertensive disorders of pregnancy, 14 on pre-eclampsia, six on gestational diabetes, nine on low birth weight and 19 on preterm birth. No meta-analysis for hypertensive disorders of pregnancy could be done because of the small number of studies. Point prevalence estimates and 95% confidence intervals (CIs) for pre-eclampsia, gestational diabetes, low birth weight, and preterm birth were: 6.6% (95% CI: 4.9%, 8.6%), 8.5% (95% CI: 3.9%, 14.7%), 8.5% (95% CI: 7.2%, 9.8%), and 10.0% (95% CI: 8.0%, 12.0%), respectively. We observed substantial heterogeneity overall and by study design. No major differences in estimates were observed by level of bias.

Conclusions.

The results of this study provide updated estimates of some of the most prevalent adverse pregnancy and perinatal outcomes in Latin America and the Caribbean. They highlight that important heterogeneity exists in prevalence estimates, which may reflect the diversity of populations in the region.

Pathophysiological Role of Genetic Factors Associated With Gestational Diabetes Mellitus

Gestational Diabetes Mellitus (GDM) is a highly prevalent maternal pathology characterized by maternal glucose intolerance during pregnancy that is, associated with severe complications for both mother and offspring. Several risk factors have been related to GDM; one of the most important among them is genetic predisposition. Numerous single nucleotide polymorphisms (SNPs) in genes that act at different levels on various tissues, could cause changes in the expression levels and activity of proteins, which result in glucose and insulin metabolism dysfunction. In this review, we describe various SNPs; which according to literature, increase the risk of developing GDM. These SNPs include: (1) those associated with transcription factors that regulate insulin production and excretion, such as rs7903146 (TCF7L2) and rs5015480 (HHEX); (2) others that cause a decrease in protective hormones against insulin resistance such as rs2241766 (ADIPOQ) and rs6257 (SHBG); (3) SNPs that cause modifications in membrane proteins, generating dysfunction in insulin signaling or cell transport in the case of rs5443 (GNB3) and rs2237892 (KCNQ1); (4) those associated with enzymes such as rs225014 (DIO2) and rs9939609 (FTO) which cause an impaired metabolism, resulting in an insulin resistance state; and (5) other polymorphisms, those are associated with growth factors such as rs2146323 (VEGFA) and rs755622 (MIF) which could cause changes in the expression levels of these proteins, producing endothelial dysfunction and an increase of pro-inflammatory cytokines, characteristic on GDM. While the pathophysiological mechanism is unclear, this review describes various potential effects of these polymorphisms on the predisposition to develop GDM.

Association of pre-pregnancy body mass index and rate of weight gain during pregnancy with maternal indicators of cardiometabolic risk

BACKGROUND/OBJECTIVE

Changes in metabolism and extensive hemodynamic adjustments occur during normal pregnancy. The presence of maternal obesity imposes an overload to these physiological adaptations that may result in increased risk for the development of cardiometabolic complications during and after pregnancy. The aim of this study is to describe total cholesterol (TC), triglycerides (TG), glucose, and arterial blood pressure (BP) trajectories and to analyze the association of these cardiometabolic risk indicators during pregnancy with pre-pregnancy body mass index (pBMI) and monthly gestational weight gain (MGWG).

SUBJECTS/METHODS

A prospective cohort study of pregnant women was conducted in Mexico City. Monthly samples of blood were taken during clinical follow-up and biochemical and blood pressure were measured during each visit. Adjusted linear mixed-effect regression models were fit to describe the trajectories of these biomarkers during pregnancy and to analyze the association with pBMI and MGWG.

RESULTS

Seven hundred and twenty women were included of which 16.6% had pre-gestational obesity, 33.2% had pre-gestational overweight, 45.8% had normal pBMI and 4.4% had pre-gestational underweight. Women with pre-gestational obesity had higher lipids concentrations in the beginning of pregnancy (TC: [Formula: see text] = 33.08, p = 0.010; TG: [Formula: see text] = 31.29, p = <0.001) but the concentrations increased less than in women with normal pBMI (TC: [Formula: see text] = -14.18, p = 0.001; TG: [Formula: see text] = -5.42, p < 0.001). By the end of pregnancy, women with pre-gestational obesity had lower concentrations of lipids than women with normal pBMI. By contrast, women with pre-gestational obesity had higher glucose concentrations and higher BP levels than women with normal pBMI over pregnancy.

CONCLUSIONS

pBMI is differentially associated with longitudinal trajectories of maternal biochemical markers of cardiometabolic risk. MGWG did not significantly affect the biochemical indicators or BP trajectories. Our results suggest that pBMI is more relevant to predicting adverse cardiometabolic markers trajectories during pregnancy than MGWG.

A systematic review and meta-analysis of gestational diabetes mellitus and mental health among BAME populations

BACKGROUND

Gestational diabetes mellitus (GDM) is a common complication of pregnancy and is associated with an increased risk of mental health (MH) disorders including antenatal and postnatal depression (PND), anxiety and post-traumatic-stress-disorder (PTSD). We hypothesized GDM and MH disorders will disproportionately affect individuals from Black, Asian and Minority Ethnic backgrounds.

METHODS

A systematic methodology was developed, and a protocol was published in PROSPERO (CRD42020210863) and a systematic review of publications between 1st January 1990 and 30th January 2021 was conducted. Multiple electronic databases were explored using keywords and MeSH terms. The finalised dataset was analysed using statistical methods such as random-effect models, subgroup analysis and sensitivity analysis. These were used to determine odds ratio (OR) and 95% confidence intervals (CI) to establish prevalence using variables of PND, anxiety, PTSD and stress to name a few.

FINDINGS

Sixty studies were finalised from the 20,040 data pool. Forty-six studies were included systematically with 14 used to meta-analyze GDM and MH outcomes. A second meta-analysis was conducted using 7 studies to determine GDM risk among Black, Asian and Minority Ethnic women with pre-existing MH disorders. The results indicate an increased risk with pooled adjusted OR for both reflected at 1.23, 95% CI of 1.00-1.50 and 1.29, 95% CI of 1.11-1.50 respectively.

INTERPRETATION

The available studies suggest a MH sequalae with GDM as well as a sequalae of GDM with MH among Black, Asian and Minority Ethnic populations. Our findings warrant further future exploration to better manage these patients.

FUNDING

Not applicable.

Risk of gestational diabetes mellitus by pre-pregnancy body mass index: A systematic review and meta-analysis

Gestational diabetes mellitus (GDM) is serious health challenges. This study aimed at determining the risk of GDM among pregnant women by pre-pregnancy BMI. Five electronic databases including Medline (PubMed), Scopus, Embase, Web of Science and Google Scholar were searched for literature published form 2015 to January 1, 2021. The pooled estimate risk of GDM among pregnant women was 16.8% (95% CI: 15.3-18.4). The risk of GDM in underweight/normal group and overweight/obese group were 10.7% (95% CI: 9.1-12.4) and 23% (95% CI: 20.2-25.9), respectively. The risk of GDM is high among overweight/obese pregnant women.

A dietary pattern rich in fruits and dairy products is inversely associated to gestational diabetes: a case-control study in Iran

BACKGROUND

Gestational diabetes mellitus (GDM) causes many problems for mother and her neonate. A healthy diet plays an important role in preventing GDM. This study aimed to investigate the relationship between major dietary patterns and the GDM.

METHODS

386 healthy and 306 GDM pregnant women (total 693) completed this case-control study. Basic information and anthropometric indices were recorded, and a food frequency questionnaire was completed. For extracting major dietary patterns, the principal component analysis was performed. Multivariable logistic regression models were used to examine whether specific dietary patterns are associated to the GDM.

RESULTS

Four dietary patterns were identified: "fruits and dairy products", "red meat and plant-based foods", "snacks and high-fat foods" and "carbohydrate-rich foods". Among these major extracted dietary patterns, "fruits and dairy products" showed an inverse association to the GDM (odds ratio adjusted for confounders: 0.50, confidence interval: 0.284-0.882, p-trend = 0.019, for highest vs. lowest quartile).

CONCLUSIONS

It seems using a healthy dietary pattern such as "fruits and dairy products" may decrease GDM risk.

The Effect of Solution-Oriented Counseling on Coping Strategies in Mental Health Issues in Women with Gestational Diabetes

This study aimed to investigate the effectiveness of solution-oriented intervention in patients with gestational diabetes, stress and anxiety on using coping strategies. This study was a randomized clinical trial with a control group. The population consisted of 56 diabetic women under treatment with insulin, who obtained higher score in one of the psychological disorders using DASS-21 (Depression, anxiety, stress scale). The participants were randomly assigned in two interventional (n = 28) and control (n = 28) groups after signing the written informed consent forms. The solution-oriented interventional program was conducted in six 60-min sessions for 6 weeks. Immediately after the final session and 6-8 weeks after the first session of the intervention, both groups completed coping inventory for stressful situations. The analytical statistic of t-test, chi-square, and variance analysis with repeated measurements using SPSS were used to analyze the data. solution-oriented counseling increased the problem-solving coping strategy in the intervention group (P = 0.001); the scores obtained by the subjects in the interventional group after adjusting the score before the intervention increased 2.68 units immediately after the intervention, which was not statistically significant (p-value = 0.44). However, it increased 11.5 scores six weeks after the intervention, which was statistically significant (P = 0.00). But, emotional and avoidance coping strategies were not significantly different between the two groups. This technique can be easily trained to all clients, and since it is focused on finding various solutions for psychological problems by clients, it can be used to reduce stress and anxiety in other chronic diseases as well.IRCT code: The code of this clinical trial study is IRCT20200202046339N1.

Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population

OBJECTIVE

Gestational diabetes mellitus (GDM) is a common metabolic disorder with onset during pregnancy. However, the etiology and pathogenesis of GDM have not been fully elucidated. In this study, we used a metabolomics approach to investigate the relationship between maternal serum metabolites and GDM in early pregnancy.

METHODS

A nested case-control study was performed. To establish an early pregnancy cohort, pregnant women in early pregnancy (10-13⁺⁶ weeks) were recruited. In total, 51 patients with GDM and 51 healthy controls were included. Serum samples were analyzed using an untargeted high-performance liquid chromatography mass spectrometry metabolomics approach. The relationships between metabolites and GDM were analyzed by an orthogonal partial least-squares discriminant analysis. Differential metabolites were evaluated using a KEGG pathway analysis.

RESULTS

A total of 44 differential metabolites were identified between GDM cases and healthy controls during early pregnancy. Of these, 26 significant metabolites were obtained in early pregnancy after false discovery rate (FDR < 0.1) correction. In the GDM group, the levels of L-pyroglutamic acid, L-glutamic acid, phenylacetic acid, pantothenic acid, and xanthine were significantly higher and the levels of 1,5-anhydro-D-glucitol, calcitriol, and 4-oxoproline were significantly lower than those in the control group. These metabolites were involved in multiple metabolic pathways, including those for amino acid, carbohydrate, lipid, energy, nucleotide, cofactor, and vitamin metabolism.

CONCLUSIONS

We identified significant differentially expressed metabolites associated with the risk of GDM, providing insight into the mechanisms underlying GDM in early pregnancy and candidate predictive markers.

Gestational Diabetes Mellitus: A Harbinger of the Vicious Cycle of Diabetes

Gestational diabetes mellitus (GDM), characterized by a transitory form of diabetes induced by insulin resistance and pancreatic β-cell dysfunction during pregnancy, has been identified as one of the major obstacles in achieving improved maternal and child health. Approximately 9-25% of pregnancies worldwide are impacted by the acute, long-term, and transgenerational health complications of this disease. Here, we discuss how GDM affects longstanding maternal and neonatal outcomes, as well as health risks that likely persist into future generations. In addition to the current challenges in the management and diagnosis of and the complications associated with GDM, we discuss current preclinical models of GDM to better understand the underlying pathophysiology of the disease and the timely need to increase our scientific toolbox to identify strategies to prevent and treat GDM, thereby advancing clinical care.

Association between maternal exposure to particulate matter (PM2.5) and adverse pregnancy outcomes in Lima, Peru

The literature shows associations between maternal exposures to PM_2.5 and adverse pregnancy outcomes. There are few data from Latin America. We have examined PM_2.5 and pregnancy outcomes in Lima. The study included 123,034 births from 2012 to 2016, at three public hospitals. We used estimated daily PM_2.5 from a newly created model developed using ground measurements, satellite data, and a chemical transport model. Exposure was assigned based on district of residence (n = 39). Linear and logistic regression analyzes were used to estimate the associations between air pollution exposure and pregnancy outcomes. Increased exposure to PM_2.5 during the entire pregnancy and in the first trimester was inversely associated with birth weight. We found a decrease of 8.13 g (-14.0; -1.84) overall and 18.6 g (-24.4, -12.8) in the first trimester, for an interquartile range (IQR) increase (9.2 µg/m³) in PM_2.5. PM_2.5 exposure was positively associated with low birth weight at term (TLBW) during entire pregnancy (OR: 1.11; 95% CI: 1.03-1.20), and at the first (OR: 1.11; 95% CI: 1.03-1.20), second (OR: 1.09; 95% CI: 1.01-1.17), and third trimester (OR: 1.10; 95% CI: 1.02-1.18) per IQR (9.2 µg/m³) increase. Higher exposure to PM_2.5 was also associated with increased risk of small for gestational age (SGA). There were no statistically significant associations between PM_2.5 exposure and preterm births (PTB). Exposure to higher concentrations of PM_2.5 in Lima may decrease birth weight and increase the frequency of TLBW and SGA. Our study was inconsistent with the literature in finding no associations with preterm birth.

A mid-pregnancy risk prediction model for gestational diabetes mellitus based on the maternal status in combination with ultrasound and serological findings

Although previous studies have proposed predictive models of gestational diabetes mellitus (GDM) based on maternal status, they do not always provide reliable results. The present study aimed to create a novel model that included ultrasound data of maternal fat distribution and serum inflammatory factors. The clinical data of 1,158 pregnant women treated at Tangshan Gongren Hospital and eight other flagship hospitals in Tangshan, including the First Hospital of Tangshan Gongren Hospital group, Ninth Hospital of Tangshan Gongren Hospital group, Tangshan Gongren Hospital group rehabilitation hospital, Tangshan railway central hospital, Tangshan Gongren Hospital group Fengnan hospital, Tangshan Gongren Hospital group Qianan Yanshan hospital, Tangshan Gongren Hospital group Qianxi Kangli hospital and Tangshan Gongren Hospital group Jidong Sub-hospital, were analyzed following the division of subjects into GDM and non-GDM groups according to their diagnostic results at 24-28 weeks of pregnancy. Univariate analysis was performed to investigate the significance of the maternal clinical parameters for GDM diagnosis and a GDM prediction model was established using stepwise regression analysis. The predictive value of the model was evaluated using a Homer-Lemeshow goodness-of-fit test and a receiver operating characteristic curve (ROC). The model demonstrated that age, pre-pregnancy body mass index, a family history of diabetes mellitus, polycystic ovary syndrome, a history of GDM, high systolic pressures, glycosylated hemoglobin levels, triglyceride levels, total cholesterol levels, low-density lipoprotein cholesterol levels, serum hypersensitive C-reactive protein, increased subcutaneous fat thickness and visceral fat thickness were all correlated with an increased GDM risk (all P<0.01). The area under the curve value was 0.911 (95% CI, 0.893-0.930). Overall, the results indicated that the current model, which included ultrasound and serological data, may be a more effective predictor of GDM compared with other single predictor models. In conclusion, the present study developed a tool to determine the risk of GDM in pregnant women during the second trimester. This prediction model, based on various risk factors, demonstrated a high predictive value for the GDM occurrence in pregnant women in China and may prove useful in guiding future clinical practice.

Prevalence and associated factors of gestational diabetes mellitus among rural pregnant women in southern Tanzania

INTRODUCTION

Gestational diabetes mellitus (GDM) is a potential risk factor for both maternal and foetal complications during pregnancy. This study aimed to determine the prevalence and factors associated with GDM among pregnant women in Southern Tanzania.

METHODS

A cross-sectional study was conducted among 612 randomly selected pregnant women attending routine antenatal clinics in Southern Tanzania from September to October 2017. Detailed medical and gynaecological history was taken using pre-tested questionnaires. Blood samples were collected for fasting and oral glucose tolerance tests. We diagnosed GDM using the World Health Organization 2013 diagnostic criteria for diabetes mellitus. We performed statistical analysis using SPSS v24.0. Possible associations and statistical significance were measured using odds ratio at 95% confidence interval, and p-values of <0.05 were considered statistically significant.

RESULTS

The mean age and standard deviation of the study subjects was 24.5±6.9 years. The prevalence of GDM was 4.3%. GDM was significantly associated with: being overweight or obese (p<0.001), past history of pre-term delivery (p<0.001), past history of stillbirths (p<0.001), history of macrosmia (p<0.001), alcohol consumption (p=0.001), and having a first degree relative with diabetes mellitus (p<0.001).

CONCLUSION

Prevalence of Gestational Diabetes Mellitus is low in this study setting. We recommend close attention to at risk women to prevent development of GDM.

FUNDING

None declared.

Trends and predictors of gestational diabetes mellitus in Chile

OBJECTIVE

To examine the temporal trends in gestational diabetes mellitus (GDM) prevalence in Chile, and to determine the main predictors of GDM.

METHODS

A secondary analysis was conducted of all birth records at Hospital Dr. Sótero del Río, Chile, from January 1, 2002, to December 31, 2015. We excluded those women with pre-existing type 2 diabetes, those with missing data, and those with unlikely data. GDM was defined as fasting glucose levels >5.55 mmol/L [>100 mg/dL] or >7.77 mmol/L [>140 mg/dL] 2 hours after glucose load in the oral glucose tolerance test. Potential predictors were selected based on prior research and ease of evaluation.

RESULTS

From the original database of 100 758 records, 86 362 women were included in the final cohort. The mean GDM prevalence was 7.6% (95% CI [confidence interval] 7.5%-7.8%), increasing from 4.4% (95% CI 4.0%-4.9%) in 2002 to 13.0% (95% CI 12.0%-13.9%) in 2015. Age, education, marital status, parity, family history of type 2 diabetes, personal history of GDM, hypertension and pre-eclampsia, alcohol consumption, smoking, and pre-gestational nutritional status performed well in the prediction of GDM.

CONCLUSION

One out of eight Chilean pregnant women of medium- to low socio-economic status were found to develop GDM. We identified a set of easy-to-capture predictors in the primary health care system that may allow for the early identification of women at high-risk for the development of GDM.

Association between maternal education level and gestational diabetes mellitus: a meta-analysis

Aims: The association between maternal education and gestational diabetes mellitus (GDM) has been discussed in considerable studies, yet the inconsistent findings still exist. The aim of this study is to investigate whether maternal education level is associated with GDM risk.Material and methods: PubMed, ScienceDirect, and Cochrane Library databases were searched up to October 2018. Observational studies on the association between maternal education level and GDM risk were included. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) for highest versus lowest level of maternal education were estimated using a random-effects model.Results: As compared to lowest education level, the pooled OR for women with highest education level was 0.75 (95% CI: 0.53-1.05). After adjusting for body mass index (BMI) and family history of diabetes, the estimated effect of maternal education on GDM were 0.68 (95% CI: 0.57-0.80) and 0.75 (95% CI: 0.60-0.92), respectively.Conclusions: Our results indicate that there is no significant association between maternal education level and risk of GDM.