History Of Gestational Diabetes Mellitus Research Articles

FACTORS ASSOCIATED WITH THE INCIDENCE OF TYPE 2 DIABETES MELLITUS IN WOMEN AT THE PEJUANG HEALTH CENTER BEKASI CITY IN 2023

Background: The 2018 Riskesdas results show that the proportion of diabetes mellitus cases in women (1.8%) is higher than the 2013 Riskesdas results (1.7%). Data obtained from the Pejuang Health Center also shows that type 2 DM cases in women are higher in 2022 with 1,661 cases compared to 2021 with 1,454 cases. Purpose: The purpose of this research was to determine factors associated with incidence of type 2 diabetes mellitus in women at the Pejuang Health Center Bekasi City in 2023. Methods: Research design used quantitative analysis with a case control approach. This research was from February to July 2023. Population in this study were women who came for screening non-communicable disease at the Pejuang Health Center. Number of samples based on the formula is 94 respondents with a sampling technique using purposive sampling. Data source from secondary data thats monthly report data Pejuang Health Center and primary data. The analysis used was univariate and bivariate analysis with Chi-Square test. Results: The results showed that there was a relationship between hypertension (p=0.007), physical activity (p=0.039), and obesity (p=0.011) with the incidence of type 2 DM in women. There was no relationship between a history of gestational diabetes mellitus (GDM) (p=0.410) and a history of giving birth to babies ≥ 4000 grams (p=1.000) with the incidence of type 2 DM in women. Conclusion: Therefore, people who are obese can start doing weekly physical activity, such as taking part in gymnastics activities held by the Pejuang Community Health Center.

Gestasyonel Diyabetes Mellitus Hastalarında Doğum Sonrası Tip 2 Diyabet Sıklığı

Aim: This study aims to examine the frequency of type 2 diabetes mellitus (DM) in the postpartum period and its relationship with other risk factors. Materials and Methods: Patients who were diagnosed, followed up and treated for gestational diabetes in Malatya Turgut Özal University, Malatya Training and Research Hospital Endocrinology outpatient clinic and who underwent Oral Glucose Tolerance Test (OGTT) in the postpartum period were included. Results: In our retrospective study, 157 patients were included. The mean age was 31.8±5.6 years. After being followed up with her follow-up and treatment throughout the pregnancy, OGTT administered with 75 grams of glucose was performed at the postpartum 8th week. Impaired glucose tolerance (IGT) was detected in 23 patients (14.64%), impaired fasting glucose (IFG) in 18 patients (11.46%), and type 2 DM in 17 patients (10.8%). When evaluated in terms of the presence of DM in the postpartum period, no difference was found regarding the history of gestational DM in the anamnesis (p=0.305) and the presence or absence of family history (p=0.095). In terms of the presence of DM, there was a significant difference between the patients receiving insulin therapy and those receiving diet therapy (p=0.001). Conclusion: We can say that type 2 DM development in the postpartum period is associated with high maternal age and an increase in body mass index (BMI). Being pregnant with the ideal weight to be achieved by lifestyle changes may decrease the risk of type 2 DM and diabetes-related complications in the long term.

Association of a history of gestational diabetes mellitus with osteoporosis, bone mineral density, and trabecular bone score in postmenopausal women

BackgroundStudies on the association of gestational diabetes mellitus (GDM) with osteoporosis, and bone mineral density (BMD) have been inconsistent. The aim of this study was to investigate the association of a history of GDM with osteoporosis, BMD, and trabecular bone score (TBS) in postmenopausal women.MethodsPostmenopausal women from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2010, between 2013 and 2014, and between 2017 and 2018 were retrospectively included in this cross-sectional study. The logistic regression model was used to explore the relationship between GDM and osteoporosis, and a weighted linear regression model was applied to investigate the association between GDM and total femoral BMD, femoral neck BMD, and total TBS. Subgroup analysis of the association between GDM and osteoporosis was performed according to age, body mass index (BMI), and DM (yes or no).ResultsOf the 6732 women included, 253 women (3.76%) had GDM. No significant differences in total femoral BMD, femoral neck BMD, and total TBS were observed between postmenopausal women with and without a history of GDM. However, a history of GDM was associated with a higher risk of osteoporosis in postmenopausal women [odds ratio (OR): 11.18, 95% confidence intervals (CI): 3.64 to 34.27, P < 0.001]. There was no significant difference between a history of GDM and osteoporosis in postmenopausal women whom BMI is normal and overweight women. However, there was an association between a history of GDM and osteoporosis in postmenopausal obese women (OR: 26.57, 95% CI 10.23 to 68.98, P < 0.001).ConclusionA history of GDM was associated with a higher risk of osteoporosis in postmenopausal women, particularly in postmenopausal obese women.

Risk prediction models for postpartum glucose intolerance in women with a history of gestational diabetes mellitus: a scoping review.

The objective of this scoping review was to investigate the effectiveness and limitations of risk prediction models for postpartum glucose intolerance in women with gestational diabetes mellitus (GDM). The aim was to provide valuable insights for healthcare professionals in the development of robust risk prediction models. A comprehensive literature search was conducted across multiple databases, including PubMed, EBSCO, Web of Science Core Collection, Ovid Full-Text Medical Journal Database, ProQuest, Elsevier ClinicalKey, China National Knowledge Infrastructure, China Biology Medicine, and WanFang Database, spanning from January 1990 to July 2023. To assess the quality of the included models, the Predictive Model Risk of Bias Assessment Tool (PROBAST) was employed. Fourteen relevant studies were identified and included in the final review, all focusing on model development. The discrimination ability of the included models ranged from 0.725 to 0.940, indicating satisfactory prediction accuracy. However, a notable limitation was that nine of these models (64.3%) did not provide clear guidelines on the selection of potential predictors. Furthermore, only six models (42.86%) underwent internal validation, with none undergoing external validation. A high risk of bias was observed across the included models. Logistic regression, Cox regression, and machine learning were the primary methods employed in the construction of these models. The risk prediction models included in this review demonstrated favorable prediction accuracy. However, due to variations in construction methodologies, direct comparison of their performance is challenging. These models exhibited certain shortcomings, such as inadequate handling of missing data and a lack of internal and external validation, resulting in a high risk of bias. Therefore, it is recommended that these models be updated and externally validated. The development of prospective, multi-center studies is encouraged to construct predictive models with low risk of bias and high clinical applicability, ultimately guiding evidence-based clinical practice. The online version contains supplementary material available at 10.1007/s40200-023-01330-1.

Does diabetes mellitus affect the development of fetal brain structures and spaces including corpus callosum, subarachnoid space, insula, and parieto-occipital fissure?

We investigated the impact of pregestational and gestational diabetes mellitus (PGDM and GDM) on the development of fetal intracranial structures and spaces. This prospective cross-sectional study involved singleton pregnancies between 20 and 32 weeks of gestation. The study comprised a control group (n = 65) of healthy pregnant women without diabetes mellitus (DM); a PGDM group (n = 43) of pregnant women having type 2 DM in a controlled diabetic state; and a GDM group (n = 26) of pregnant women with GDM diagnosed with 2-h 75-g oral glucose tolerance test and received intervention to reduce the diabetic impact on fetus. During neurosonographic evaluation, the simultaneous measurements of corpus callosum (CC) width and depth in the midsagittal image; and lateral craniocortical and posterior craniocortical widths of the subarachnoid space and insular and parieto-occipital fissure depths in the axial image were performed. Before statistical analysis, these values were carefully adjusted for the occipitofrontal diameter. The DM groups displayed substantially higher frequencies of family history of DM and obstetric history of GDM compared to the control group (p < 0.05). Regarding the neurosonographic parameters, the CC length and insular and parieto-occipital fissure depths were significantly increased in the GDM group but not in the PGDM group (p < 0.05). No significant difference was found among the study groups regarding other neurosonographic parameters (p > 0.05). The results of neurosonographical evaluation of fetal brain structures and spaces reveal that diabetic impact may not be seen in the presence of PGDM, especially in pregnant women receiving prenatal interventions to reduce or avoid diabetic adverse effects on fetal brain development. The effect of GDM on neurosonographically assessed fetal brain development should be evaluated in further studies with subjects matched for gestational weeks and antenatal care conditions.

Postpartum lifestyle behaviour among women with prior gestational diabetes mellitus: evidence from the HUNT study

IntroductionWomen with a history of gestational diabetes mellitus (GDM) are at increased risk of type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). Recommendations for postpartum follow-up include targeted lifestyle...

Participant characteristics in the prevention of gestational diabetes as evidence for precision medicine: a systematic review and meta-analysis

BackgroundPrecision prevention involves using the unique characteristics of a particular group to determine their responses to preventive interventions. This study aimed to systematically evaluate the participant characteristics associated with responses to interventions in gestational diabetes mellitus (GDM) prevention.MethodsWe searched MEDLINE, EMBASE, and Pubmed to identify lifestyle (diet, physical activity, or both), metformin, myoinositol/inositol and probiotics interventions of GDM prevention published up to May 24, 2022.ResultsFrom 10347 studies, 116 studies (n = 40940 women) are included. Physical activity results in greater GDM reduction in participants with a normal body mass index (BMI) at baseline compared to obese BMI (risk ratio, 95% confidence interval: 0.06 [0.03, 0.14] vs 0.68 [0.26, 1.60]). Combined diet and physical activity interventions result in greater GDM reduction in participants without polycystic ovary syndrome (PCOS) than those with PCOS (0.62 [0.47, 0.82] vs 1.12 [0.78–1.61]) and in those without a history of GDM than those with unspecified GDM history (0.62 [0.47, 0.81] vs 0.85 [0.76, 0.95]). Metformin interventions are more effective in participants with PCOS than those with unspecified status (0.38 [0.19, 0.74] vs 0.59 [0.25, 1.43]), or when commenced preconception than during pregnancy (0.21 [0.11, 0.40] vs 1.15 [0.86–1.55]). Parity, history of having a large-for-gestational-age infant or family history of diabetes have no effect on intervention responses.ConclusionsGDM prevention through metformin or lifestyle differs according to some individual characteristics. Future research should include trials commencing preconception and provide results disaggregated by a priori defined participant characteristics including social and environmental factors, clinical traits, and other novel risk factors to predict GDM prevention through interventions.

PROFILING OF CLINICAL DYNAMICS OF TYPE 2 DIABETES MELLITUS IN PATIENTS: A PERSPECTIVE REVIEW

Type 2 diabetes mellitus (T2DM), also known as Non-Insulin Dependent Diabetes Mellitus (NIDDM) is one of the common metabolic disorders in the world. T2DM accounts for around 90% of all cases of diabetes mellitus, afflicting millions worldwide. It is a significant global health burden with a steadily increasing prevalence. In T2DM, the response to insulin is diminished, and this is defined as insulin resistance. Risk factors for T2DM are diverse. Some are modifiable, and others are not. Modifiable risk factors include overweight/obesity, lack of exercise or physical inactivity, poor nutrition, etc. Non-modifiable risk factors include age, ethnicity/race, family history, history of gestational diabetes mellitus, etc. The starting points and mainstays of treatment for T2DM are diet and lifestyle modifications such as increased physical activity and stoppage of smoking. In addition to the diet and lifestyle modifications, drugs are also used in the management of T2DM. This study aimed to profile the clinical dynamics of type 2 diabetes mellitus in patients. Current literatures from different databases including MEDLINE, PubMed, EMBASE, CINAHL, Google Scholar, etc. on the topic were searched online and reviewed.

THU321 Indirect Effects Of COVID-19 On The Risk Of Gestational Diabetes And Factors Mediating Increased Risk

Abstract Disclosure: Y.J. Rhou: None. J. Elhindi: None. S.J. Melov: None. N. Cheung: None. D. Pasupathy: None. Aim: COVID-19 has had indirect effects on pregnancy outcomes. This study aimed to assess the risk of gestational diabetes (GDM) in distinct COVID-19 exposure periods and determine the potential factors contributing to increased risk of GDM in a multiethnic population. Methods: Multicentre, retrospective cohort study of singleton pregnancies at three hospitals two years pre-COVID-19 (January 2018 - January 2020), 1st year of COVID-19 with low COVID-19 pandemic burden and limited restrictions (February 2020 - January 2021), and 2nd year of COVID-19 with increased pandemic burden and stringent restrictions (February 2021 - January 2022). Baseline maternal characteristics, gestational weight gain (GWG) and pregnancy outcome data were compared between time periods. The primary outcome of GDM was assessed using univariate and multivariate generalized estimating equations models. Results: Of 28,207 pregnancies, 14,663 occurred in the two years pre-COVID-19, 6,890 in COVID-19 Year 1 and 6,654 in COVID-19 Year 2. The study population was diverse, comprising 82.5% of non-Caucasian ethnicity and 22.7% in the quintile of greatest socioeconomic disadvantage. Maternal age increased across exposure periods (30.7 ± 5.0 years pre-COVID-19 vs 31.0 ± 5.0 years COVID-19 Year 1 vs 31.3 ± 5 years COVID-19 Year 2; p&amp;lt;0.001). There were increases in prepregnancy BMI (25.5 ± 5.7 kg/m2 vs 25.7 ± 5.6 kg/m2 vs 26.1 ± 5.7 kg/m2; p&amp;lt;0.001), proportion who were obese (17.5% vs 18.1% vs 20.7%; p&amp;lt;0.001) and proportion with other traditional risk factors for GDM including South Asian ethnicity and prior history of GDM. Weekly rate of GWG and proportion exceeding recommended GWG increased across pandemic exposure periods (64.3% vs 66.0% vs 66.6%; p=0.009). GDM diagnosis increased across exposure periods (21.2% vs 22.9% vs 24.8%; p&amp;lt;0.001). Both COVID-19 Year 1 and Year 2 were associated with increased risk of GDM on univariate analysis, only COVID-19 Year 2 remaining significantly associated after adjusting for maternal baseline characteristics and GWG (OR 1.17 [1.06, 1.28], p=0.01). Conclusion: Diagnosis of GDM increased with pandemic exposure. Progressive sociodemographic changes and greater GWG may have contributed to increased risk. However, exposure to the 2nd year of COVID-19 remained independently associated with GDM after adjusting for shifts in baseline maternal characteristics and GWG. Presentation: Thursday, June 15, 2023

Precision gestational diabetes treatment: a systematic review and meta-analyses

BackgroundGestational Diabetes Mellitus (GDM) affects approximately 1 in 7 pregnancies globally. It is associated with short- and long-term risks for both mother and baby. Therefore, optimizing treatment to effectively treat the condition has wide-ranging beneficial effects. However, despite the known heterogeneity in GDM, treatment guidelines and approaches are generally standardized. We hypothesized that a precision medicine approach could be a tool for risk-stratification of women to streamline successful GDM management. With the relatively short timeframe available to treat GDM, commencing effective therapy earlier, with more rapid normalization of hyperglycaemia, could have benefits for both mother and fetus.MethodsWe conducted two systematic reviews, to identify precision markers that may predict effective lifestyle and pharmacological interventions.ResultsThere was a paucity of studies examining precision lifestyle-based interventions for GDM highlighting the pressing need for further research in this area. We found a number of precision markers identified from routine clinical measures that may enable earlier identification of those requiring escalation of pharmacological therapy (to metformin, sulphonylureas or insulin). This included previous history of GDM, Body Mass Index and blood glucose concentrations at diagnosis.ConclusionsClinical measurements at diagnosis could potentially be used as precision markers in the treatment of GDM. Whether there are other sensitive markers that could be identified using more complex individual-level data, such as omics, and if these can feasibly be implemented in clinical practice remains unknown. These will be important to consider in future studies.

A holistic approach to preventing type 2 diabetes in Asian women with a history of gestational diabetes mellitus: a feasibility study and pilot randomized controlled trial.

Gestational Diabetes Mellitus (GDM) exposes women to future risk of Type 2 Diabetes. Previous studies focused on diet and physical activity, less emphasis was given to tackle intertwined risk factors such as sleep and stress. Knowledge remains scarce in multi-ethnic Asian communities. This study explored the: (1) feasibility of a holistic digital intervention on improving diet, physical activity (PA), sleep and stress of Asian women with a history of GDM, and (2) preliminary efficacy of the holistic intervention on women's physical and mental well-being via a pilot randomized controlled trial. Female volunteers with a history of GDM but without pre-existing diabetes were recruited from multi-ethnic Singaporean community. Each eligible woman was given a self-monitoring opportunity using Oura Ring that provided daily feedback on step counts, PA, sleep and bedtime heart rate. Intervention group additionally received personalized recommendations aimed to reinforce healthy behaviors holistically (diet, PA, sleep and stress). Dietary intake was evaluated by a research dietitian, while step counts, PA, sleep and bedtime heart rate were evaluated by health coaches based on Oura Ring data. Perceived physical and mental health and well-being were self-reported. Clinical outcomes included glycemic status determined by HbA1c and OGTT tests, body mass index, blood pressures and lipid profile. Of 196 women from the community, 72 women completed diabetes screening, 61 women were eligible and 56 women completed the study. The 56 completers had mean age of 35.8 ± 3.7 years, predominantly Chinese, majority had their first GDM diagnosed at least 2 years ago and had two GDM-affected pregnancies. After intervention period, more women in the Intervention group achieved at least 8,000 steps/day and had at least 6 hours of sleep per night. Noticeable reduction of added sugar in their food and beverages were observed after the dietary intervention. Changes in body weight and mental well-being were observed but group differences were not statistically significant. The holistic approach appeared feasible for personalizing lifestyle recommendations to promote physical and mental well-being among women with a history of GDM. Larger studies with sufficient assessment timepoints and follow-up duration are warranted to improve the evaluation of intervention effects on clinical outcomes. https://clinicaltrials.gov/show/NCT05512871, NCT05512871.

A-316 Suboptimal Compliance to Postpartum Glucose Monitoring in a High-risk Pregnancy Population - A Single Center Study

Abstract Background Gestational diabetes mellitus (GDM) is a predictive factor in developing type 2 diabetes mellitus (T2DM) in affected mothers and their offspring. Its prevalence is increasing proportionally with the obesity epidemic, affecting 10% of pregnant women and 50% of which are likely to develop T2DM. Current guidelines by the American Diabetes Association and the American College of Obstetricians and Gynecologists recommend screening at 4–12 weeks with a 2-hour postpartum glucose tolerance test (OGTT) in patients with a history of GDM. However, several studies have reported suboptimal test ordering and completion rates attributable to the busy postpartum period and provider role confusion between primary care physicians and obstetricians. Due to the complex maternal-fetal cases encountered at our institution, the aim of this study is to evaluate the ordering and test completion rates amongst care providers and patients to ensure compliance with stipulated guidelines. Method We conducted a retrospective audit of women diagnosed with GDM who delivered at our institution from Jan 2019–Oct 2022. We abstracted data from electronic health records. Gestational diabetes was defined by one or more of the following: abnormal 3hr OGTT or 1-hour OGTT of &amp;gt;/=200 mg/dL at &amp;gt;/= 24 weeks. We excluded patients with pre-existing diabetes defined by diagnosis code or by an abnormal 1st trimester 3hr GTT or HbA1C and patients who did not return for a postpartum visit. We compared the proportions of patients with postpartum glucose monitoring orders (glucose tolerance tests or Hemoglobin A1C) to those without orders. Factors such as race, GDM management, provider type and insurance carrier were assessed as potential barriers to non-compliance. Results We identified 356 patients who were diagnosed with GDM during the study period. Of these, 158 patients were excluded who had pre-existing diabetes or did not return for postpartum care. The mean (SD) maternal age was 33.2 (6.0) years. Seventy-four percent (147/198) of patients had a postpartum glucose tolerance test order (Group A), and 26% (51/198) had no laboratory order for glucose monitoring (Group B). The proportion of patients with a completed test order was 24% (35/147), of which four results were abnormal (indicated for diabetes or pre-diabetes). There was no difference in parity, ethnicity, insurance type, diabetes management and provider type between the two groups. Poor compliance was observed in patients with glucose tolerance laboratory orders, while patients with an HbA1c order were 100% compliant. Conclusion Overall, this report demonstrates poor patient compliance with postpartum glucose tolerance testing. Although HbA1C is not recommended for postpartum glucose monitoring, patients were more likely to complete this test.

The Impact of the Association Between Nonalcoholic Fatty Liver Disease and Intrahepatic Cholestasis of Pregnancy on Maternal and Fetal Outcomes.

Backgroundː Intrahepatic cholestasis of pregnancy (ICP), a hepatic condition that causes severe itching in late pregnancy, is linked to nonalcoholic fatty liver disease (NAFLD) due to disrupted bile acid balance. It poses maternal risks such as preterm labor and gestational diabetes and fetal risks such as preterm birth and respiratory distress. The study examined NAFLD's impact on ICP in pregnant women, highlighting management and research implications. Methodsː This retrospective study examined pregnant women (≥18 years) with ICP, assessing fatty liver with follow-up ultrasounds. Participants were divided into ICP only and ICP with fatty liver (FL) groups, excluding heavy alcohol users and incomplete data. Maternal age, medical history, and comorbidities were evaluated alongside abdominal ultrasounds to identify FL. Resultsː In this study of 43 pregnant women, the mean maternal age was 27 years. Patients with ICP and FL had significantly higher bile acid levels than those with ICP alone. However, no significant differences were found between the two groups regarding the history of gestational diabetes mellitus (GDM), dyslipidemia, polycystic ovarian syndrome (PCOS), parity, and hypothyroidism. Among women with ICP and FL, 51.85% underwent lower segment cesarean section (LSCS), while 43.75% with ICP without FL underwent LSCS. Conclusionsː ICP with FL did not show significant adverse effects on maternal and neonatal outcomes, including mode of delivery, gestational age, maternal complications, neonatal intensive care unit (NICU) admissions, and low birth weight (LBW) with asphyxia. However, additional research is required to fully comprehend the relationship between ICP, NAFLD, and their impact on pregnancy outcomes.

Comparison of machine learning and conventional logistic regression-based prediction models for gestational diabetes in an ethnically diverse population; the Monash GDM Machine learning model

BackgroundEarly identification of pregnant women at high risk of developing gestational diabetes (GDM) is desirable as effective lifestyle interventions are available to prevent GDM and to reduce associated adverse outcomes. Personalised probability of developing GDM during pregnancy can be determined using a risk prediction model. These models extend from traditional statistics to machine learning methods; however, accuracy remains sub-optimal. ObjectiveWe aimed to compare multiple machine learning algorithms to develop GDM risk prediction models, then to determine the optimal model for predicting GDM. MethodsA supervised machine learning predictive analysis was performed on data from routine antenatal care at a large health service network from January 2016 to June 2021. Predictor set 1 were sourced from the existing, internationally validated Monash GDM model: GDM history, body mass index, ethnicity, age, family history of diabetes, and past poor obstetric history. New models with different predictors were developed, considering statistical principles with inclusion of more robust continuous and derivative variables. A randomly selected 80% dataset was used for model development, with 20% for validation. Performance measures, including calibration and discrimination metrics, were assessed. Decision curve analysis was performed. ResultsUpon internal validation, the machine learning and logistic regression model’s area under the curve (AUC) ranged from 71% to 93% across the different algorithms, with the best being the CatBoost Classifier (CBC). Based on the default cut-off point of 0.32, the performance of CBC on predictor set 4 was: Accuracy (85%), Precision (90%), Recall (78%), F1-score (84%), Sensitivity (81%), Specificity (90%), positive predictive value (92%), negative predictive value (78%), and Brier Score (0.39). ConclusionsIn this study, machine learning approaches achieved the best predictive performance over traditional statistical methods, increasing from 75 to 93%. The CatBoost classifier method achieved the best with the model including continuous variables.

Longitudinal effects of PFAS exposure on insulin sensitivity and β-cell function among women with gestational diabetes mellitus history

Longitudinal effects of PFAS exposure on insulin sensitivity and β-cell function among women with gestational diabetes mellitus history

Breastfeeding Practices among Postpartum Women with and without a History of Gestational Diabetes Mellitus: A Prospective Study

Objective: To compare breastfeeding (BF) practices, particularly exclusive BF (EBF), among women with and without a history of gestational diabetes mellitus (GDM) during the first six postpartum months and assess the impact of EBF on offspring weight from birth to six months postpartum. Materials and Methods: The present study was a prospective study that included 244 women, with 123 with a history of GDM (GDM group) and 121 without a history of GDM (non-GDM group). All participants were first interviewed on the discharge date and then via telephone at 1, 2, 3, 4, 5, and 6 months postpartum. BF practices were classified as EBF, partial BF (PBF), or no BF. Data on infant weight at six months were evaluated. Results: Upon hospital discharge, women mostly practiced PBF with 53.6% PBF versus 30.1% EBF in the GDM group and 48.8% PBF versus 38.0% EBF in the non-GDM group. However, EBF was more commonly practiced than PBF, during the first six months postpartum. The 6-month EBF rates for the GDM and non-GDM groups were 28.4% and 17.4%, respectively (p=0.039). In a multivariate analysis, only the intended EBF period was a factor that significantly impacted 6-month EBF rates (adjusted odds ratio 3.49 and 95% confidence interval 1.48 to 8.22). EBF for six months resulted in reduced weight gain during the first six months of life among offspring of women in both groups. Conclusion: The GDM group practiced EBF for six months postpartum more frequently than the non-GDM group. However, a history of GDM was not an independent predictor of EBF success over six months. EBF demonstrated lower offspring weight gain from birth to six months postpartum for women with and without a history of GDM. These findings may be used to design targeted educational programs for informed postpartum BF practices. Keywords: Breastfeeding practices; Breastmilk; Exclusive breastfeeding; Gestational diabetes mellitus; Infant weight gain; Postpartum

O.3.3-7 A Socio-ecological approach to overcoming barriers for physical activity promotion after gestational diabetes: a systematic review and thematic synthesis

Abstract Purpose Physical activity is recommended after Gestational Diabetes to reduce risk of subsequent Type 2 Diabetes. However, uptake and maintenance of physical activity is low. Approaching barriers and facilitators to physical activity using a socio-ecological approach could help better direct multi-level interventions in future. The present review therefore aimed to synthesise the postnatal barriers and facilitators to physical activity, and develop and understanding of where, across the socio-ecological model, these factors exist and/or are interrelated. Methods Eligible studies included discussion around physical activity with women with a history of GDM. A systematic search of MEDLINE, CINAHL Complete, Scopus, Web of Science and Cochrane Library was conducted in October 2022. Risk of bias was assessed in included studies using The Critical Appraisal Skills Programmes checklist for qualitative research. A reflexive thematic analysis was employed by 2 authors to analyse the barriers and facilitators to physical activity. Themes were first open coded, and then subsequently organised and interpreted in the context of and according to the socio-ecological model. Results After screening, 29 studies were included in the final review. The present review updated the most recent review in 2019, including 9 new studies since then. All but 4 studies had a CASP study quality rating greater than 6.5. Most themes spanned the intrapersonal, social, and organisational levels of the socio-ecological model. Physical activity barriers discussed pertained to leisure time physical activity, while other modes of activity, including active transport, were often overlooked, despite being routine. Partner and familial support were identified as vital for engagement with activity. This was either due to the emotional support received, or the provision of childcare. However, most women did not want to have to rely on family for childcare and identified that other forms of childcare present could be facilitative of physical activity. Conclusions Most barriers and facilitators at the social and organisational levels were interrelated with those at the individual level. Therefore, future physical activity interventions after Gestational Diabetes should be multi-level.

Prediction of postpartum prediabetes by machine learning methods in women with gestational diabetes mellitus

Early onset of type 2 diabetes and cardiovascular disease are common complications for women diagnosed with gestational diabetes. Prediabetes refers to a condition in which blood glucose levels are higher than normal, but not yet high enough to be diagnosed as type 2 diabetes. Currently, there is no accurate way of knowing which women with gestational diabetes are likely to develop postpartum prediabetes. This study aims to predict the risk of postpartum prediabetes in women diagnosed with gestational diabetes. Our sparse logistic regression approach selects only two variables- antenatal fasting glucose at OGTT and HbA1c soon after the diagnosis of GDM- as relevant, but gives an area under the receiver operating characteristic curve of 0.72, outperforming all other methods. We envision this to be a practical solution, which coupled with a targeted follow-up of high-risk women, could yield better cardiometabolic outcomes in women with a history of GDM.

Universal Screening of Gestational Diabetes Mellitus In Upper Egypt: Prospective Cohort Study of The Prevalence, Risk Factors, and Short-Term Outcomes

Background: Despite the high prevalence of diabetes mellitus in Egypt, the real prevalence and epidemiology of gestational diabetes mellitus (GDM) in Upper Egypt is still lacking. Objective: This study aims to determine the prevalence and risk factors of GDM among pregnant women in Upper Egypt and to evaluate the foetal and maternal outcomes of this disease. Methods: This prospective cohort study was conducted between July 2014 and July 2018. Universal screening for GDM among all pregnant women attending primary health care clinics was done using Diabetes in Pregnancy Study Group of India (DIPSI) criteria. Those with GDM were followed up until the end of purpureum. Maternal and foetal outcomes were recorded. Results: GDM was diagnosed in 956 out of 7141 pregnant women (13.4%). Previous history of GDM, macrosomic babies, and family history of diabetes were all significantly higher in GDM women (P&lt;0.001 each). However, no definite risk factors were observed in about half of the GDM women. 29% of GDM women responded to medical nutrition therapy (MNT) alone. When the oral glucose tolerance test (OGTT) was repeated Postpartum, diagnosis of DM was established in 14.3% of the cohort, while 25.7% had impaired glucose tolerance. Conclusions: The prevalence of GDM is relatively high in Upper Egypt. Half of GDM cases lack risk factors. Universal screening using OGTT should be routinely performed to all attendant pregnant ladies. Discrete MNT is not an enough management in most of GDM cases. Keywords: GDM; Postpartum OGTT; diabetes; MNT; foetal outcome; maternal outcome.

Knowledge on gestational diabetes mellitus and associated factors among pregnant women attending antenatal care clinics of North Shewa zone public hospitals, Oromia region, Central Ethiopia: a cross-sectional study

BackgroundGlobally, the prevalence of gestational diabetes mellitus (GDM) is currently rising. Assessing GDM knowledge and taking various public health actions will help pregnant women know more about the condition, resulting...