SummaryBackgroundDiagnosis of gestational diabetes predicts risk of infants who are large for gestational age (LGA) and with high adiposity, which in turn aims to predict a future risk of obesity in the offspring. South Asian women have higher risk of gestational diabetes, lower risk of LGA, and on average give birth to infants with greater adiposity than do white European women. Whether the same diagnostic criteria for gestational diabetes should apply to both groups of women is unclear. We aimed to assess the association between maternal glucose and adverse perinatal outcomes to ascertain whether thresholds used to diagnose gestational diabetes should differ between south Asian and white British women. We also aimed to assess whether ethnic origin affected prevalence of gestational diabetes irrespective of criteria used.MethodsWe used data (including results of a 26–28 week gestation oral glucose tolerance test) of women from the Born in Bradford study, a prospective study that recruited women attending the antenatal clinic at the Bradford Royal Infirmary, UK, between 2007 and 2011 and who intended to give birth to their infant in that hospital. We studied the association between fasting and 2 h post-load glucose and three primary outcomes (LGA [defined as birthweight >90th percentile for gestational age], high infant adiposity [sum of skinfolds >90th percentile for gestational age], and caesarean section). We calculated adjusted odds ratios (ORs) and their 95% confidence intervals (CIs) for a 1 SD increase in fasting and post-load glucose. We established fasting and post-load glucose thresholds that equated to an OR of 1·75 for LGA and high infant adiposity in each group of women to identify ethnic-specific criteria for diagnosis of gestational diabetes.FindingsOf 13 773 pregnancies, 3420 were excluded from analyses. Of 10 353 eligible pregnancies, 4088 women were white British, 5408 were south Asian, and 857 were of other ethnic origin. The adjusted ORs of LGA per 1 SD fasting glucose were 1·22 (95% CI 1·08–1·38) in white British women and 1·43 (1·23–1·67) in south Asian women (pinteraction with ethnicity = 0·39). Results for high infant adiposity were 1·35 (1·23–1·49) and 1·35 (1·18–1·54; pinteraction with ethnicity=0·98), and for caesarean section they were 1·06 (0·97–1·16) and 1·11 (1·02–1·20; pinteraction with ethnicity=0·47). Associations between post-load glucose and the three primary outcomes were weaker than for fasting glucose. A fasting glucose concentration of 5·4 mmol/L or a 2 h post-load level of 7·5 mmol/L identified white British women with 75% or higher relative risk of LGA or high infant adiposity; in south Asian women, the cutoffs were 5·2 mmol/L or 7·2 mml/L; in the whole cohort, the cutoffs were 5·3 mmol/L or 7·5 mml/L. The prevalence of gestational diabetes in our cohort ranged from 1·2% to 8·7% in white British women and 4% to 24% in south Asian women using six different criteria. Compared with the application of our whole-cohort criteria, use of our ethnic-specific criteria increased th...

BackgroundAdvancements in knowledge of obesity aetiology and mobile phone technology have created the opportunity to develop an electronic tool to predict an infant’s risk of childhood obesity. The study aims were to develop and validate equations for the prediction of childhood obesity and integrate them into a mobile phone application (App).Methods and FindingsAnthropometry and childhood obesity risk data were obtained for 1868 UK-born White or South Asian infants in the Born in Bradford cohort. Logistic regression was used to develop prediction equations (at 6±1.5, 9±1.5 and 12±1.5 months) for risk of childhood obesity (BMI at 2 years >91st centile and weight gain from 0–2 years >1 centile band) incorporating sex, birth weight, and weight gain as predictors. The discrimination accuracy of the equations was assessed by the area under the curve (AUC); internal validity by comparing area under the curve to those obtained in bootstrapped samples; and external validity by applying the equations to an external sample. An App was built to incorporate six final equations (two at each age, one of which included maternal BMI). The equations had good discrimination (AUCs 86–91%), with the addition of maternal BMI marginally improving prediction. The AUCs in the bootstrapped and external validation samples were similar to those obtained in the development sample. The App is user-friendly, requires a minimum amount of information, and provides a risk assessment of low, medium, or high accompanied by advice and website links to government recommendations.ConclusionsPrediction equations for risk of childhood obesity have been developed and incorporated into a novel App, thereby providing proof of concept that childhood obesity prediction research can be integrated with advancements in technology.

BackgroundThe prevalence of infant obesity is increasing, but there is a lack of evidence-based approaches to prevent obesity at this age. This study tested the acceptability and feasibility of evaluating a theory-based intervention aimed at reducing risk of obesity in infants of overweight/obese women during and after pregnancy: the Healthy and Active Parenting Programme for Early Years (HAPPY).MethodsA feasibility randomised controlled trial was conducted in Bradford, England. One hundred twenty overweight/obese pregnant women (Body Mass Index [BMI] ≥25 kg/m2) were recruited between 10–26 weeks gestation. Consenting women were randomly allocated to HAPPY (6 antenatal, 6 postnatal sessions: N = 59) or usual care (N = 61). Appropriate outcome measures for a full trial were explored, including: infant’s length and weight, woman’s BMI, physical activity and dietary intake of the women and infants. Health economic data were collected. Measurement occurred before randomisation and when the infant was aged 6 months and 12 months. Feasibility outcomes were: recruitment/attrition rates, and acceptability of: randomisation, measurement, and intervention. Intra-class correlations for infant weight were calculated. Fidelity was assessed through observations and facilitator feedback. Focus groups and semi-structured interviews explored acceptability of methods, implementation, and intervention content.ResultsRecruitment targets were met (~20 women/month) with a recruitment rate of 30 % of eligible women (120/396). There was 30 % attrition at 12 months; 66 % of recruited women failed to attend intervention sessions, but those who attended the first session were likely to continue to attend (mean 9.4/12 sessions, range 1–12). Reaction to intervention content was positive, and fidelity was high. Group clustering was minimal; an adjusted effect size of −0.25 standard deviation scores for infant weight at 12 months (95 % CI: −0.16–0.65) favouring the intervention was observed using intention to treat analyses. No adverse events were reported.ConclusionsThe HAPPY intervention appeared feasible and acceptable to participants who attended and those delivering it, however attendance was low; adaptations to increase initial attendance are recommended. Whilst the study was not powered to detect a definitive effect, our results suggest a potential to reduce risk of infant obesity. The evidence reported provides valuable lessons to inform progression to a definitive trial.Trial RegistrationCurrent Controlled Trials ISRCTN56735429Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-2861-z) contains supplementary material, which is available to authorized users.

Background Although maternal death is rare in the United Kingdom, 90% of these women had multiple health/social problems. This study aims to estimate the prevalence of pre-existing multimorbidity (two or more long-term physical or mental health conditions) in pregnant women in the United Kingdom (England, Northern Ireland, Wales and Scotland). Study design Pregnant women aged 15–49 years with a conception date 1/1/2018 to 31/12/2018 were included in this population-based cross-sectional study, using routine healthcare datasets from primary care: Clinical Practice Research Datalink (CPRD, United Kingdom, n = 37,641) and Secure Anonymized Information Linkage databank (SAIL, Wales, n = 27,782), and secondary care: Scottish Morbidity Records with linked community prescribing data (SMR, Tayside and Fife, n = 6099). Pre-existing multimorbidity preconception was defined from 79 long-term health conditions prioritised through a workshop with patient representatives and clinicians. Results The prevalence of multimorbidity was 44.2% (95% CI 43.7–44.7%), 46.2% (45.6–46.8%) and 19.8% (18.8–20.8%) in CPRD, SAIL and SMR respectively. When limited to health conditions that were active in the year before pregnancy, the prevalence of multimorbidity was still high (24.2% [23.8–24.6%], 23.5% [23.0–24.0%] and 17.0% [16.0 to 17.9%] in the respective datasets). Mental health conditions were highly prevalent and involved 70% of multimorbidity CPRD: multimorbidity with ≥one mental health condition/s 31.3% [30.8–31.8%]). After adjusting for age, ethnicity, gravidity, index of multiple deprivation, body mass index and smoking, logistic regression showed that pregnant women with multimorbidity were more likely to be older (CPRD England, adjusted OR 1.81 [95% CI 1.04–3.17] 45–49 years vs 15–19 years), multigravid (1.68 [1.50–1.89] gravidity ≥ five vs one), have raised body mass index (1.59 [1.44–1.76], body mass index 30+ vs body mass index 18.5–24.9) and smoked preconception (1.61 [1.46–1.77) vs non-smoker). Conclusion Multimorbidity is prevalent in pregnant women in the United Kingdom, they are more likely to be older, multigravid, have raised body mass index and smoked preconception. Secondary care and community prescribing dataset may only capture the severe spectrum of health conditions. Research is needed urgently to quantify the consequences of maternal multimorbidity for both mothers and children.