Vitamin D status of pregnant women with obesity in the UK and its association with pregnancy outcomes: a secondary analysis of the UK Pregnancies Better Eating and Activity Trial (UPBEAT) study.

Prenatal vitamin D deficiency is widely reported and may affect perinatal outcomes. In this secondary analysis of the UK Pregnancies Better Eating and Activity Trial, we examined vitamin D status and its relationship with selected pregnancy outcomes in women with obesity (BMI ≥ 30 kg/m2) from multi-ethnic inner-city settings in the UK. Determinants of vitamin D status at a mean of 17 ± 1 weeks' gestation were assessed using multivariable linear regression and reported as percent differences in serum 25-hydroxyvitamin D (25(OH)D). Associations between 25(OH)D and clinical outcomes were examined using logistic regression. Among 1089 participants, 67 % had 25(OH)D < 50 nmol/l and 26 % had concentrations < 25 nmol/l. In fully adjusted models accounting for socio-demographic and anthropometric characteristics, 25(OH)D was lower among women of Black (% difference = -33; 95 % CI: -39, -27), Asian (% difference = -43; 95 % CI: -51, -35) and other non-White (% difference = -26; 95 % CI: -35, -14) ethnicity compared with women of White ethnicity (n 1086; P < 0·001 for all). In unadjusted analysis, risk of gestational diabetes was greater in women with 25(OH)D < 25 nmol/l compared with ≥ 50 nmol/l (OR = 1·58; 95 % CI: 1·09, 2·31), but the magnitude of effect estimates was attenuated in the multivariable model (OR = 1·33; 95 % CI: 0·88, 2·00). There were no associations between 25(OH)D and risk of preeclampsia, preterm birth or small for gestational age or large-for-gestational-age delivery. These findings demonstrate low 25(OH)D among pregnant women with obesity and highlight ethnic disparities in vitamin D status in the UK. However, evidence for a greater risk of adverse perinatal outcomes among women with vitamin D deficiency was limited.

Impact of COVID-19 on gestational diabetes pregnancy outcomes in the UK: A multicentre retrospective cohort study.

OBJECTIVE: To determine the impact of implementing emergency care pathway(s) for screening, diagnosing and managing women with gestational diabetes (GDM) during COVID-19. DESIGN: Retrospective multicentre cohort. SETTING: Nine National Health Service (NHS) Hospital Trusts/Health boards in England and Scotland. POPULATION: 4915 women with GDM pre-pandemic (1 April 2018 to 31 March 2020), and 3467 women with GDM during the pandemic (1 May 2020 to 31 March 2021). METHODS: We examined clinical outcomes for women with GDM prior to and during the pandemic following changes in screening methods, diagnostic testing, glucose thresholds and introduction of virtual care for monitoring of antenatal glycaemia. MAIN OUTCOME MEASURES: Intervention at birth, perinatal mortality, large-for-gestational-age infants and neonatal unit admission. RESULTS: The new diagnostic criteria more often identified GDM women who were multiparous, had higher body mass index (BMI) and greater deprivation, and less frequently had previous GDM (all p < 0.05). During COVID, these women had no differences in the key outcome measures. Of the women, 3% were identified with pre-existing diabetes at antenatal booking. Where OGTT continued during COVID, but virtual care was introduced, outcomes were also similar pre- and during the pandemic. CONCLUSIONS: Using HbA1c and fasting glucose identified a higher risk GDM population during the pandemic but this had minimal impact on pregnancy outcomes. The high prevalence of undiagnosed pre-existing diabetes suggests that women with GDM risk factors should be offered HbA1c screening in early pregnancy.

Pre-pregnancy health of women with pre-existing diabetes or previous gestational diabetes: Analysis of pregnancy risk factors and behavioural data from a digital tool.

AIMS: To examine health behaviours and risk factors in women with pre-existing diabetes or previous gestational diabetes mellitus who are planning pregnancy. METHODS: Health behaviour, risk factor and demographic data obtained from a digital pregnancy planning advisory tool (Tommy's charity UK) were analysed. Descriptive statistical analysis was performed, stratified by diabetes type. RESULTS: Data from 84,359 women, including 668 with type 1 diabetes, 707 with type 2 diabetes and 1785 with previous gestational diabetes obtained over a 12-month period (September 2019-September 2020) were analysed. 65%, 95%CI (61,68%) of women with type 2 diabetes and 46%, 95%CI (43,48%) with previous gestational diabetes were obese (BMI ≥30 kg/m2 ), compared with 26%, 95%CI (26,26%) without diabetes. Use of folic acid supplements was low; 41%, 95%CI (40,41%) of women without diabetes and 42%, 95%CI (40,45%) with previous gestational diabetes reported taking folic acid (any dose) while 47%, 95%CI (43.50%) women with type 1 diabetes and 44%, 95%CI (40,47%) women with type 2 diabetes respectively reported taking the recommended dose (5 mg). More women with type 1 diabetes and type 2 diabetes reported smoking (20%, 95%CI [17,23%] and 23%, 95%CI [20,26%] respectively) and taking illicit/recreational drugs (7%, 95%CI [6,10%] and 9%, 95% CI [7,11%]) compared to women without diabetes (smoking 17%, 95% CI [16,17%], drug use 5%, 95%CI [5,5%]). Alcohol consumption, low levels of physical activity and of fruit and vegetable intake were also evident. CONCLUSIONS: This study highlights the potential of online pregnancy planning advisory tools to reach high-risk women and emphasises the need to improve pre-pregnancy care for women with pre-existing diabetes and previous gestational diabetes, many of whom are actively seeking advice. It is also the first to describe pre-pregnancy health behaviours in women with previous gestational diabetes.

Interventions to enhance pre-pregnancy care for women with type 2 diabetes: A systematic review of the literature.

AIMS: The aim of the study was to examine the content and impact of interventions that have been used to increase the uptake of pre-pregnancy care for women with type 2 diabetes, and their impact on maternal and fetal outcomes. METHODS: A systematic search of multiple databases was conducted in November 2021, and updated July 2022, to identify studies assessing interventions to enhance pre-pregnancy care for women with type 2 diabetes. Over 10% of articles were screened by two reviewers at title and abstract phase, after which all selected full-text articles were screened by two reviewers. Quality assessment was conducted using the Critical Appraisal Skills Programme checklist for cohort studies. Meta-analysis was not possible due to study heterogeneity; therefore, narrative synthesis was conducted. RESULTS: Four eligible cohort studies were identified. The conclusions able to be drawn by this review were limited as women with type 2 diabetes (n = 800) were in the minority in all four studies (35%-40%) and none of the interventions were exclusively tailored for them. The uptake of pre-pregnancy care was lower in women with type 2 diabetes (8%-10%) compared with other participant groups in the studies. Pregnancy preparation indicators generally improved among all groups exposed to pre-pregnancy care, with varying impact on pregnancy outcomes. CONCLUSIONS: This review demonstrates that previous interventions have had a limited impact on pre-pregnancy care uptake in women with type 2 diabetes. Future studies should focus on tailored interventions for improving pre-pregnancy care for women with type 2 diabetes, particularly those from ethnic minorities and living in poorer communities.

The physical-mental health interface in the preconception period: analysis of 131 182 women planning pregnancy in the UK.

OBJECTIVE: The physical and mental health of women prior to conception can have a significant impact on pregnancy and child outcomes. Given the rising burden of non-communicable diseases, the aim was to explore the relation between mental health, physical health and health behaviour in women planning a pregnancy. METHODS: Cross-sectional analysis of responses from 131 182 women to a preconception health digital education tool, providing data on physical and mental health and health behaviour. Logistic regression was used to explore associations between mental health and physical health variables. RESULTS: Physical health conditions were reported by 13.1% and mental health conditions by 17.8%. There was evidence for an association between self-reported physical and mental health conditions (odds ratio [OR] 2.22, 95% CI 2.14-2.3). Those with a mental health condition were less likely to engage with healthy behaviour at preconception such as folate supplementation (OR 0.89, 95% CI 0.86-0.92) and consumption of the recommended amount of fruit and vegetables (OR 0.77, 95% CI 0.74-0.79). They were more likely to be physically inactive (OR 1.14, 95% CI 1.11-1.18), smoke tobacco (OR 1.72, 95% CI 1.66-1.78) and use illicit substances (OR 2.4, 95% CI 2.25-2.55). CONCLUSIONS: Greater recognition of mental and physical comorbidities is needed and closer integration of physical and mental healthcare in the preconception period, which could support people to optimise their health during this time and improve long-term outcomes.

Health behaviours in 131,182 UK women planning pregnancy.

BACKGROUND: A woman's health at the time of conception lays the foundation for a healthy pregnancy and the lifelong health of her child. We investigated the health behaviours of UK women planning pregnancy. METHODS: We analysed survey data from the 'Planning for Pregnancy' online tool (Tommy's, UK). We described all women planning pregnancy and compared the frequency of non-adherence to preconception recommendations in women who had already stopped contraception (active planners) and those who had not (non-active planners). RESULTS: One hundred thirty-one thousand one hundred eighty-two women from across the UK were included, of whom 64.8% were actively planning pregnancy. Of the whole cohort, twenty percent were smokers and less than one third took folic acid supplements (31.5%). Forty two percent engaged in less than the recommended 150 min of weekly physical activity and only 53.3% consumed five portions of fruit or vegetables 4 days a week. Smokers were 1.87 times more likely to be active planners than non-smokers (95% CI 1.79-1.94), and women who took folic acid were 7 times more likely to be active planners (95% CI 6.97-7.59) compared to women who did not. Smoking, drug use and lack of folic acid supplementation were common in younger women and those who were underweight. CONCLUSIONS: This unique survey of UK women has identified poor adherence to preconception recommendations in those planning pregnancies and supports the need for a greater public health focus on preconception health. This study provides a contemporary basis from which to inform preconception health advice and a benchmark to measure changes over time.

Maternal dysglycaemia, changes in the infant's epigenome modified with a diet and physical activity intervention in pregnancy: Secondary analysis of a randomised control trial.

BACKGROUND: Higher maternal plasma glucose (PG) concentrations, even below gestational diabetes mellitus (GDM) thresholds, are associated with adverse offspring outcomes, with DNA methylation proposed as a mediating mechanism. Here, we examined the relationships between maternal dysglycaemia at 24 to 28 weeks' gestation and DNA methylation in neonates and whether a dietary and physical activity intervention in pregnant women with obesity modified the methylation signatures associated with maternal dysglycaemia. METHODS AND FINDINGS: We investigated 557 women, recruited between 2009 and 2014 from the UK Pregnancies Better Eating and Activity Trial (UPBEAT), a randomised controlled trial (RCT), of a lifestyle intervention (low glycaemic index (GI) diet plus physical activity) in pregnant women with obesity (294 contol, 263 intervention). Between 27 and 28 weeks of pregnancy, participants had an oral glucose (75 g) tolerance test (OGTT), and GDM diagnosis was based on diagnostic criteria recommended by the International Association of Diabetes and Pregnancy Study Groups (IADPSG), with 159 women having a diagnosis of GDM. Cord blood DNA samples from the infants were interrogated for genome-wide DNA methylation levels using the Infinium Human MethylationEPIC BeadChip array. Robust regression was carried out, adjusting for maternal age, smoking, parity, ethnicity, neonate sex, and predicted cell-type composition. Maternal GDM, fasting glucose, 1-h, and 2-h glucose concentrations following an OGTT were associated with 242, 1, 592, and 17 differentially methylated cytosine-phosphate-guanine (dmCpG) sites (false discovery rate (FDR) ≤ 0.05), respectively, in the infant's cord blood DNA. The most significantly GDM-associated CpG was cg03566881 located within the leucine-rich repeat-containing G-protein coupled receptor 6 (LGR6) (FDR = 0.0002). Moreover, we show that the GDM and 1-h glucose-associated methylation signatures in the cord blood of the infant appeared to be attenuated by the dietary and physical activity intervention during pregnancy; in the intervention arm, there were no GDM and two 1-h glucose-associated dmCpGs, whereas in the standard care arm, there were 41 GDM and 160 1-h glucose-associated dmCpGs. A total of 87% of the GDM and 77% of the 1-h glucose-associated dmCpGs had smaller effect sizes in the intervention compared to the standard care arm; the adjusted r2 for the association of LGR6 cg03566881 with GDM was 0.317 (95% confidence interval (CI) 0.012, 0.022) in the standard care and 0.240 (95% CI 0.001, 0.015) in the intervention arm. Limitations included measurement of DNA methylation in cord blood, where the functional significance of such changes are unclear, and because of the strong collinearity between treatment modality and severity of hyperglycaemia, we cannot exclude that treatment-related differences are potential confounders. CONCLUSIONS: Maternal dysglycaemia was associated with significant changes in the epigenome of the infants. Moreover, we found that the epigenetic impact of a dysglycaemic prenatal maternal environment appeared to be modified by a lifestyle intervention in pregnancy. Further research will be needed to investigate possible medical implications of the findings. TRIAL REGISTRATION: ISRCTN89971375.

Do nuclear magnetic resonance (NMR)-based metabolomics improve the prediction of pregnancy-related disorders? Findings from a UK birth cohort with independent validation.

BACKGROUND: Prediction of pregnancy-related disorders is usually done based on established and easily measured risk factors. Recent advances in metabolomics may provide earlier and more accurate prediction of women at risk of pregnancy-related disorders. METHODS: We used data collected from women in the Born in Bradford (BiB; n = 8212) and UK Pregnancies Better Eating and Activity Trial (UPBEAT; n = 859) studies to create and validate prediction models for pregnancy-related disorders. These were gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), small for gestational age (SGA), large for gestational age (LGA) and preterm birth (PTB). We used ten-fold cross-validation and penalised regression to create prediction models. We compared the predictive performance of (1) risk factors (maternal age, pregnancy smoking, body mass index (BMI), ethnicity and parity) to (2) nuclear magnetic resonance-derived metabolites (N = 156 quantified metabolites, collected at 24-28 weeks gestation) and (3) combined risk factors and metabolites. The multi-ethnic BiB cohort was used for training and testing the models, with independent validation conducted in UPBEAT, a multi-ethnic study of obese pregnant women. RESULTS: Maternal age, pregnancy smoking, BMI, ethnicity and parity were retained in the combined risk factor and metabolite models for all outcomes apart from PTB, which did not include maternal age. In addition, 147, 33, 96, 51 and 14 of the 156 metabolite traits were retained in the combined risk factor and metabolite model for GDM, HDP, SGA, LGA and PTB, respectively. These include cholesterol and triglycerides in very low-density lipoproteins (VLDL) in the models predicting GDM, HDP, SGA and LGA, and monounsaturated fatty acids (MUFA), ratios of MUFA to omega 3 fatty acids and total fatty acids, and a ratio of apolipoprotein B to apolipoprotein A-1 (APOA:APOB1) were retained predictors for GDM and LGA. In BiB, discrimination for GDM, HDP, LGA and SGA was improved in the combined risk factors and metabolites models. Risk factor area under the curve (AUC 95% confidence interval (CI)): GDM (0.69 (0.64, 0.73)), HDP (0.74 (0.70, 0.78)) and LGA (0.71 (0.66, 0.75)), and SGA (0.59 (0.56, 0.63)). Combined risk factor and metabolite models AUC 95% (CI): GDM (0.78 (0.74, 0.81)), HDP (0.76 (0.73, 0.79)) and LGA (0.75 (0.70, 0.79)), and SGA (0.66 (0.63, 0.70)). For GDM, HDP and LGA, but not SGA, calibration was good for a combined risk factor and metabolite model. Prediction of PTB was poor for all models. Independent validation in UPBEAT at 24-28 weeks and 15-18 weeks gestation confirmed similar patterns of results, but AUCs were attenuated. CONCLUSIONS: Our results suggest a combined risk factor and metabolite model improves prediction of GDM, HDP and LGA, and SGA, when compared to risk factors alone. They also highlight the difficulty of predicting PTB, with all models performing poorly.

Smartphone applications available to pregnant women in the United Kingdom: An assessment of nutritional information.

The importance of diet during pregnancy is critically important for the short- and long-term health of both mother and child. The number of apps targeting pregnant women is rapidly increasing, yet the nutritional content of these tools remains largely unexplored. This review aimed to evaluate the coverage and content of nutrition information in smartphone apps available to U.K. pregnant women. Keyword searches were conducted in iTunes and Google Play stores in November 2018. Candidate apps were included if they targeted pregnant women, provided pregnancy-specific nutritional information, had a user rating of at least 4+ based on at least 20 ratings, and were available in English. Nutritional content was assessed for accuracy against U.K. recommendations. Behaviour change techniques (BCTs) were also evaluated. Twenty-nine apps were included, seven of which originated in the United Kingdom. There was a large variability in the quality of smartphone app nutritional information. The accuracy of nutrition information varied, and several apps conveyed inappropriate information for pregnancy. On average, 10 BCTs were identified per app (range 2-15). Overall, smartphone apps do not consistently provide accurate and useful nutritional information to pregnant women. This study highlights the need for the integration of evidence-based nutritional information during app development and for increased regulatory oversight. App developers should also make it clear that nutritional content is intended for a specific geographical region or population or modify for the intended audience. These are important considerations for the design of future apps, which are increasingly used to complement existing maternity services.

The effect of a lifestyle intervention in obese pregnant women on gestational metabolic profiles: findings from the UK Pregnancies Better Eating and Activity Trial (UPBEAT) randomised controlled trial.

BACKGROUND: Pregnancy is associated with widespread change in metabolism, which may be more marked in obese women. Whether lifestyle interventions in obese pregnant women improve pregnancy metabolic profiles remains unknown. Our objectives were to determine the magnitude of change in metabolic measures during obese pregnancy, to indirectly compare these to similar profiles in a general pregnant population, and to determine the impact of a lifestyle intervention on change in metabolic measures in obese pregnant women. METHODS: Data from a randomised controlled trial of 1158 obese (BMI ≥ 30 kg/m2) pregnant women recruited from six UK inner-city obstetric departments were used. Women were randomised to either the UPBEAT intervention, a tailored complex lifestyle intervention focused on improving diet and physical activity, or standard antenatal care (control group). UPBEAT has been shown to improve diet and physical activity during pregnancy and up to 6-months postnatally in obese women and to reduce offspring adiposity at 6-months; it did not affect risk of gestational diabetes (the primary outcome). Change in the concentrations of 158 metabolic measures (129 lipids, 9 glycerides and phospholipids, and 20 low-molecular weight metabolites), quantified three times during pregnancy, were compared using multilevel models. The role of chance was assessed with a false discovery rate of 5% adjusted p values. RESULTS: All very low-density lipoprotein (VLDL) particles increased by 1.5-3 standard deviation units (SD) whereas intermediate density lipoprotein and specific (large, medium and small) LDL particles increased by 1-2 SD, between 16 and 36 weeks' gestation. Triglycerides increased by 2-3 SD, with more modest changes in other metabolites. Indirect comparisons suggest that the magnitudes of change across pregnancy in these obese women were 2- to 3-fold larger than in unselected women (n = 4260 in cross-sectional and 583 in longitudinal analyses) from an independent, previously published, study. The intervention reduced the rate of increase in extremely large, very large, large and medium VLDL particles, particularly those containing triglycerides. CONCLUSION: There are marked changes in lipids and lipoproteins and more modest changes in other metabolites across pregnancy in obese women, with some evidence that this is more marked than in unselected pregnant women. The UPBEAT lifestyle intervention may contribute to a healthier metabolic profile in obese pregnant women, but our results require replication. TRIAL REGISTRATION: UPBEAT was registered with Current Controlled Trials, ISRCTN89971375 , on July 23, 2008 (prior to recruitment).

Metabolic profiling of gestational diabetes in obese women during pregnancy.

AIMS/HYPOTHESIS: Antenatal obesity and associated gestational diabetes (GDM) are increasing worldwide. While pre-existing insulin resistance is implicated in GDM in obese women, the responsible metabolic pathways remain poorly described. Our aim was to compare metabolic profiles in blood of obese pregnant women with and without GDM 10 weeks prior to and at the time of diagnosis by OGTT. METHODS: We investigated 646 women, of whom 198 developed GDM, in this prospective cohort study, a secondary analysis of UK Pregnancies Better Eating and Activity Trial (UPBEAT), a multicentre randomised controlled trial of a complex lifestyle intervention in obese pregnant women. Multivariate regression analyses adjusted for multiple testing, and accounting for appropriate confounders including study intervention, were performed to compare obese women with GDM with obese non-GDM women. We measured 163 analytes in serum, plasma or whole blood, including 147 from a targeted NMR metabolome, at time point 1 (mean gestational age 17 weeks 0 days) and time point 2 (mean gestational age 27 weeks 5 days, at time of OGTT) and compared them between groups. RESULTS: Multiple significant differences were observed in women who developed GDM compared with women without GDM (false discovery rate corrected p values <0.05). Most were evident prior to diagnosis. Women with GDM demonstrated raised lipids and lipoprotein constituents in VLDL subclasses, greater triacylglycerol enrichment across lipoprotein particles, higher branched-chain and aromatic amino acids and different fatty acid, ketone body, adipokine, liver and inflammatory marker profiles compared with those without GDM. CONCLUSIONS/INTERPRETATION: Among obese pregnant women, differences in metabolic profile, including exaggerated dyslipidaemia, are evident at least 10 weeks prior to a diagnosis of GDM in the late second trimester.

Prediction of uncomplicated pregnancies in obese women: a prospective multicentre study.

BACKGROUND: All obese pregnant women are considered at equal high risk with respect to complications in pregnancy and birth, and are commonly managed through resource-intensive care pathways. However, the identification of maternal characteristics associated with normal pregnancy outcomes could assist in the management of these pregnancies. The present study aims to identify the factors associated with uncomplicated pregnancy and birth in obese women, and to assess their predictive performance. METHODS: Data form obese women (BMI ≥ 30 kg/m2) with singleton pregnancies included in the UPBEAT trial were used in this analysis. Multivariable logistic regression was used to identify sociodemographic, clinical and biochemical factors at 15+0 to 18+6 weeks' gestation associated with uncomplicated pregnancy and birth, defined as delivery of a term live-born infant without antenatal or labour complications. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC). Internal validation and calibration were also performed. Women were divided into fifths of risk and pregnancy outcomes were compared between groups. Sensitivity, specificity, and positive and negative predictive values were calculated using the upper fifth as the positive screening group. RESULTS: Amongst 1409 participants (BMI 36.4, SD 4.8 kg/m2), the prevalence of uncomplicated pregnancy and birth was 36% (505/1409). Multiparity and increased plasma adiponectin, maternal age, systolic blood pressure and HbA1c were independently associated with uncomplicated pregnancy and birth. These factors achieved an AUROC of 0.72 (0.68-0.76) and the model was well calibrated. Prevalence of gestational diabetes, preeclampsia and other hypertensive disorders, preterm birth, and postpartum haemorrhage decreased whereas spontaneous vaginal delivery increased across the fifths of increasing predicted risk of uncomplicated pregnancy and birth. Sensitivity, specificity, and positive and negative predictive values were 38%, 89%, 63% and 74%, respectively. A simpler model including clinical factors only (no biomarkers) achieved an AUROC of 0.68 (0.65-0.71), with sensitivity, specificity, and positive and negative predictive values of 31%, 86%, 56% and 69%, respectively. CONCLUSION: Clinical factors and biomarkers can be used to help stratify pregnancy and delivery risk amongst obese pregnant women. Further studies are needed to explore alternative pathways of care for obese women demonstrating different risk profiles for uncomplicated pregnancy and birth.

Explainable Early Prediction of Gestational Diabetes Biomarkers by Combining Medical Background and Wearable Devices: A Pilot Study With a Cohort Group in South Africa.

This study aims to explore the potential of Internet of Things (IoT) devices and explainable Artificial Intelligence (AI) techniques in predicting biomarker values associated with GDM when measured 13-16 weeks prior to diagnosis. We developed a system that forecasts biomarkers such as LDL, HDL, triglycerides, cholesterol, HbA1c, and results from the Oral Glucose Tolerance Test (OGTT) including fasting glucose, 1-hour, and 2-hour post-load glucose values. These biomarker values are predicted based on sensory measurements collected around week 12 of pregnancy, including continuous glucose levels, short physical movement recordings, and medical background information. To the best of our knowledge, this is the first study to forecast GDM-associated biomarker values 13 to 16 weeks prior to the GDM screening test, using continuous glucose monitoring devices, a wristband for activity detection, and medical background data. We applied machine learning models, specifically Decision Tree and Random Forest Regressors, along with Coupled-Matrix Tensor Factorisation (CMTF) and Elastic Net techniques, examining all possible combinations of these methods across different data modalities. The results demonstrated good performance for most biomarkers. On average, the models achieved Mean Squared Error (MSE) between 0.29 and 0.42 and Mean Absolute Error (MAE) between 0.23 and 0.45 for biomarkers like HDL, LDL, cholesterol, and HbA1c. For the OGTT glucose values, the average MSE ranged from 0.95 to 2.44, and the average MAE ranged from 0.72 to 0.91. Additionally, the utilisation of CMTF with Alternating Least Squares technique yielded slightly better results (0.16 MSE and 0.07 MAE on average) compared to the well-known Elastic Net feature selection technique. While our study was conducted with a limited cohort in South Africa, our findings offer promising indications regarding the potential for predicting biomarker values in pregnant women through the integration of wearable devices and medical background data in the analysis. Nevertheless, further validation on a larger, more diverse cohort is imperative to substantiate these encouraging results.

Interventions in preconception and pregnant women at risk of gestational diabetes; a systematic review and meta-analysis of randomised controlled trials.

BACKGROUND: Women at risk of gestational diabetes mellitus (GDM) need preventative interventions. OBJECTIVE: To evaluate targeted interventions before and during pregnancy for women identified as being at risk of developing GDM. METHODS: Systematic review and meta-analysis conducted following PRISMA guidelines. MEDLINE, EMBASE and the Cochrane Library in addition to reference and citation lists were searched to identify eligible randomised controlled trials (RCTs) utilising risk stratification during the preconception period or in the first/early second trimester. Screening and data extraction were carried out by the authors independently. Quality assessment was conducted based on the Cochrane risk-of-bias tool. Random effects meta-analysis and narrative synthesis were performed. RESULTS: Eighty-four RCTs were included: two during preconception and 82 in pregnancy, with a pooled sample of 22,568 women. Interventions were behavioural (n = 54), dietary supplementation (n = 19) and pharmacological (n = 11). Predictive factors for risk assessment varied; only one study utilised a validated prediction model. Gestational diabetes was reduced in diet and physical activity interventions (risk difference - 0.03, 95% CI 0.06, - 0.01; I2 58.69%), inositol (risk difference - 0.19, 95% CI 0.33, - 0.06; I2 92.19%), and vitamin D supplements (risk difference - 0.16, 95% CI 0.25, - 0.06; I2 32.27%). Subgroup analysis showed that diet and physical activity interventions were beneficial in women with ≥ 2 GDM risk factors (risk difference - 0.16, 95% CI 0.25, - 0.07; I2 11.23%) while inositol supplementation was effective in women with overweight or obesity (risk difference - 0.17, 95% CI 0.22, - 0.11; I2 0.01%). Effectiveness of all other interventions were not statistically significant. CONCLUSIONS: This review provides evidence that interventions targeted at women at risk of GDM may be an effective strategy for prevention. Further studies using validated prediction tools or multiple risk factors to target high-risk women for intervention before and during pregnancy are warranted.

Towards Precision Medicine in Gestational Diabetes: Pathophysiology and Glycemic Patterns in Pregnant Women With Obesity.

AIMS: Precision medicine has revolutionized our understanding of type 1 diabetes and neonatal diabetes but has yet to improve insight into gestational diabetes mellitus (GDM), the most common obstetric complication and strongly linked to obesity. Here we explored if patterns of glycaemia (fasting, 1 hour, 2 hours) during the antenatal oral glucose tolerance test (OGTT), reflect distinct pathophysiological subtypes of GDM as defined by insulin secretion/sensitivity or lipid profiles. METHODS: 867 pregnant women with obesity (body mass index ≥ 30 kg/m2) from the UPBEAT trial (ISRCTN 89971375) were assessed for GDM at 28 weeks' gestation (75 g oral glucose tolerance test OGTT; World Health Organization criteria). Lipid profiling of the fasting plasma OGTT sample was undertaken using direct infusion mass spectrometry and analyzed by logistic/linear regression, with and without adjustment for confounders. Insulin secretion and sensitivity were characterized by homeostatic model assessment 2b and 2s, respectively. RESULTS: In women who developed GDM (n = 241), patterns of glycaemia were associated with distinct clinical and biochemical characteristics and changes to lipid abundance in the circulation. Severity of glucose derangement, rather than pattern of postload glycaemia, was most strongly related to insulin action and lipid abundance/profile. Unexpectedly, women with isolated postload hyperglycemia had comparable insulin secretion and sensitivity to euglycemic women, potentially indicative of a novel mechanistic pathway. CONCLUSIONS: Patterns of glycemia during the OGTT may contribute to a precision approach to GDM as assessed by differences in insulin resistance/secretion. Further research is indicated to determine if isolated postload hyperglycemia reflects a different mechanistic pathway for targeted management.

Micronutrient supplementation interventions in preconception and pregnant women at increased risk of developing pre-eclampsia: a systematic review and meta-analysis.

BACKGROUND: Pre-eclampsia can lead to maternal and neonatal complications and is a common cause of maternal mortality worldwide. This review has examined the effect of micronutrient supplementation interventions in women identified as having a greater risk of developing pre-eclampsia. METHODS: A systematic review was performed using the PRISMA guidelines. The electronic databases MEDLINE, EMBASE and the Cochrane Central Register of Controlled trials were searched for relevant literature and eligible studies identified according to a pre-specified criteria. A meta-analysis of randomised controlled trials (RCTs) was conducted to examine the effect of micronutrient supplementation on pre-eclampsia in high-risk women. RESULTS: Twenty RCTs were identified and supplementation included vitamin C and E (n = 7), calcium (n = 5), vitamin D (n = 3), folic acid (n = 2), magnesium (n = 1) and multiple micronutrients (n = 2). Sample size and recruitment time point varied across studies and a variety of predictive factors were used to identify participants, with a previous history of pre-eclampsia being the most common. No studies utilised a validated prediction model. There was a reduction in pre-eclampsia with calcium (risk difference, -0.15 (-0.27, -0.03, I2 = 83.4%)), and vitamin D (risk difference, -0.09 (-0.17, -0.02, I2 = 0.0%)) supplementation. CONCLUSION: Our findings show a lower rate of pre-eclampsia with calcium and vitamin D, however, conclusions were limited by small sample sizes, methodological variability and heterogeneity between studies. Further higher quality, large-scale RCTs of calcium and vitamin D are warranted. Exploration of interventions at different time points before and during pregnancy as well as those which utilise prediction modelling methodology, would provide greater insight into the efficacy of micronutrient supplementation intervention in the prevention of pre-eclampsia in high-risk women.

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

BACKGROUND: Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM. METHODS: Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA). RESULTS: A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers. CONCLUSIONS: Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

Gestational Diabetes (GDM) is high blood sugar that develops during pregnancy and may cause complications. GDM diagnosis is centered on blood sugar levels. Despite everyone receiving standard treatment, the clinical outcomes may vary from one individual to another. This indicates a need to identify factors that may help GDM diagnosis and result in improved classification of those at greatest risk for complications. Here, we systematically analyzed all published evidence for potential markers that could identify those with GDM who have greater risk of complications. We find that high maternal weight is a risk factor for offspring born larger for their gestational age. Other promising markers were identified, but further analysis is needed before they can be applied in the clinic.

Rollout of Closed-Loop Technology to Pregnant Women with Type 1 Diabetes: Healthcare Professionals' Views About Potential Challenges and Solutions.

Aims: To explore healthcare professionals' views about the training and support needed to rollout closed-loop technology to pregnant women with type 1 diabetes. Methods: We interviewed (n = 19) healthcare professionals who supported pregnant women using CamAPS FX closed-loop during the Automated insulin Delivery Amongst Pregnant women with Type 1 diabetes (AiDAPT) trial. Data were analyzed descriptively. An online workshop involving (n = 15) trial team members was used to inform recommendations. Ethics approvals were obtained in conjunction with those for the wider trial. Results: Interviewees expressed enthusiasm for a national rollout of closed-loop, but anticipated various challenges, some specific to use during pregnancy. These included variations in insulin pump and continuous glucose monitoring expertise and difficulties embedding and retaining key skills, due to the relatively small numbers of pregnant women using closed-loop. Inexperienced staff also highlighted difficulties interpreting data downloads. To support rollout, interviewees recommended providing expert initial advice training, delivered by device manufacturers together with online training resources and specific checklists for different systems. They also highlighted a need for 24 h technical support, especially when supporting technology naive women after first transitioning onto closed-loop in early pregnancy. They further recommended providing case-based meetings and mentorship for inexperienced colleagues, including support interpreting data downloads. Interviewees were optimistic that if healthcare professionals received training and support, their long-term workloads could be reduced because closed-loop lessened women's need for glycemic management input, especially in later pregnancy. Conclusions: Interviewees identified challenges and opportunities to rolling-out closed-loop and provided practical suggestions to upskill inexperienced staff supporting pregnant women using closed-loop. A key priority will be to determine how best to develop mentorship services to support inexperienced staff delivering closed-loop. Clinical Trials Registration: NCT04938557.

Metabolic Profiling of Pregnant Women with Obesity: An Exploratory Study in Women at Greater Risk of Gestational Diabetes.

Gestational diabetes mellitus (GDM) is one of the most prevalent obstetric conditions, particularly among women with obesity. Pathways to hyperglycaemia remain obscure and a better understanding of the pathophysiology would facilitate early detection and targeted intervention. Among obese women from the UK Pregnancies Better Eating and Activity Trial (UPBEAT), we aimed to compare metabolic profiles early and mid-pregnancy in women identified as high-risk of developing GDM, stratified by GDM diagnosis. Using a GDM prediction model combining maternal age, mid-arm circumference, systolic blood pressure, glucose, triglycerides and HbA1c, 231 women were identified as being at higher-risk, of whom 119 women developed GDM. Analyte data (nuclear magnetic resonance and conventional) were compared between higher-risk women who developed GDM and those who did not at timepoint 1 (15+0−18+6 weeks) and at timepoint 2 (23+2−30+0 weeks). The adjusted regression analyses revealed some differences in the early second trimester between those who developed GDM and those who did not, including lower adiponectin and glutamine concentrations, and higher C-peptide concentrations (FDR-adjusted p < 0.005, < 0.05, < 0.05 respectively). More differences were evident at the time of GDM diagnosis (timepoint 2) including greater impairment in ß-cell function (as assessed by HOMA2-%B), an increase in the glycolysis-intermediate pyruvate (FDR-adjusted p < 0.001, < 0.05 respectively) and differing lipid profiles. The liver function marker γ-glutamyl transferase was higher at both timepoints (FDR-adjusted p < 0.05). This exploratory study underlines the difficulty in early prediction of GDM development in high-risk women but adds to the evidence that among pregnant women with obesity, insulin secretory dysfunction may be an important discriminator for those who develop GDM.

Altered Lipid Metabolism in Obese Women With Gestational Diabetes and Associations With Offspring Adiposity.

CONTEXT: Gestational diabetes (GDM) affects 20 million women/year worldwide and is associated with childhood obesity. Infants of affected mothers have increased adiposity from birth, which leads to obesity in later life. However, it remains unknown whether the effect of GDM upon neonatal body composition is due to hyperglycemia alone or is mediated by other pathways. OBJECTIVE: To investigate plasma lipid profiles in obese women according to GDM diagnosis, infant birthweight percentiles, and adiposity. DESIGN: Prospective cohort from UPBEAT trial (ISRCTN 89971375). SETTING: Hospital and community. PATIENTS: 867 obese pregnant women recruited in early pregnancy, assessed at 28 weeks for GDM. Offspring anthropometry was assessed at birth. OUTCOME (PRESPECIFIED): Neonatal birth percentile and abdominal circumference. METHODS: Lipidomic profiling in the fasting plasma oral glucose tolerance test sample using direct infusion mass spectrometry. Analysis included logistic/linear regression, unadjusted and adjusted for maternal age, body mass index, parity, ethnicity, UPBEAT trial arm, and fetal sex. The limit of significance was P = 0.05 for offspring anthropometry and P = 0.002 for lipidomic data. RESULTS: GDM in obese women was associated with elevated plasma concentrations of specific diglycerides [DG(32:0)] and triglycerides [TG(48:0), (50:1), (50:2)] containing fatty acids (16:0), (16:1), (18:0), and (18:1), consistent with increased de novo lipogenesis. In the whole cohort, these species were associated with birthweight percentile and neonatal abdominal circumference. Effects upon infant abdominal circumference remained significant after adjustment for maternal glycemia. CONCLUSIONS: Increased de novo lipogenesis-related species in pregnant women with obesity and GDM are associated with measures of offspring adiposity and may be a target for improving lifelong health.