Social inequalities in pregnancy metabolic profile: findings from the multi-ethnic Born in Bradford cohort study.

BACKGROUND: Lower socioeconomic position (SEP) associates with adverse pregnancy and perinatal outcomes and with less favourable metabolic profile in nonpregnant adults. Socioeconomic differences in pregnancy metabolic profile are unknown. We investigated association between a composite measure of SEP and pregnancy metabolic profile in White European (WE) and South Asian (SA) women. METHODS: We included 3,905 WE and 4,404 SA pregnant women from a population-based UK cohort. Latent class analysis was applied to nineteen individual, household, and area-based SEP indicators (collected by questionnaires or linkage to residential address) to derive a composite SEP latent variable. Targeted nuclear magnetic resonance spectroscopy was used to determine 148 metabolic traits from mid-pregnancy serum samples. Associations between SEP and metabolic traits were examined using linear regressions adjusted for gestational age and weighted by latent class probabilities. RESULTS: Five SEP sub-groups were identified and labelled 'Highest SEP' (48% WE and 52% SA), 'High-Medium SEP' (77% and 23%), 'Medium SEP' (56% and 44%) 'Low-Medium SEP' (21% and 79%), and 'Lowest SEP' (52% and 48%). Lower SEP was associated with more adverse levels of 113 metabolic traits, including lower high-density lipoprotein (HDL) and higher triglycerides and very low-density lipoprotein (VLDL) traits. For example, mean standardized difference (95%CI) in concentration of small VLDL particles (vs. Highest SEP) was 0.12 standard deviation (SD) units (0.05 to 0.20) for 'Medium SEP' and 0.25SD (0.18 to 0.32) for 'Lowest SEP'. There was statistical evidence of ethnic differences in associations of SEP with 31 traits, primarily characterised by stronger associations in WE women e.g., mean difference in HDL cholesterol in WE and SA women respectively (vs. Highest-SEP) was -0.30SD (-0.41 to -0.20) and -0.16SD (-0.27 to -0.05) for 'Medium SEP', and -0.62SD (-0.72 to -0.52) and -0.29SD (-0.40 to -0.20) for 'Lowest SEP'. CONCLUSIONS: We found widespread socioeconomic differences in metabolic traits in pregnant WE and SA women residing in the UK. Further research is needed to understand whether the socioeconomic differences we observe here reflect pre-conception differences or differences in the metabolic pregnancy response. If replicated, it would be important to explore if these differences contribute to socioeconomic differences in pregnancy outcomes.

How do schools influence the emotional and behavioural health of their pupils? A multi-level analysis of 135 schools in the Born in Bradford inner city multi-ethnic birth cohort.

PURPOSE: To estimate variation in emotional and behavioural problems between primary schools in Bradford, an ethnically diverse and relatively deprived city in the UK. METHODS: We did a cross-sectional analysis of data collected from 2017 to 2021 as part of the 'Born In Bradford' birth cohort study. We used multilevel linear regression in which the dependent variable was the Strengths and Difficulties Questionnaire (SDQ) total score, with a random intercept for schools. We adjusted for pupil-level characteristics including age, ethnicity, socioeconomic status, and parental mental health. RESULTS: The study included 5,036 participants from 135 schools. Participants were aged 7-11 years and 56% were of Pakistani heritage. The mean SDQ score was 8.84 out of a maximum 40. We estimated that the standard deviation in school-level scores was 1.41 (95% CI 1.11-1.74) and 5.49% (95% CI 3.19-9.37%) of variation was explained at school level. After adjusting for pupil characteristics, the standard deviation of school-level scores was 1.04 (95% CI 0.76-1.32) and 3.51% (95% CI 1.75-6.18%) of variation was explained at school level. Simulation suggested that a primary school with 396 pupils at the middle of the distribution has 63 pupils (95% CI 49-78) with a 'raised' SDQ score of 15 + /40; and shifting a school from the lower to the upper quartile would prevent 26 cases (95% CI 5-46). CONCLUSION: The prevalence of emotional and behavioural problems varies between schools. This is partially explained by pupil characteristics; though residual variation in adjusted scores may suggest that schools have a differential impact on mental wellbeing.

Effectiveness of a midwife-led continuity of care model on birth outcomes and maternal mental health in vulnerable women: study protocol for a randomised controlled trial with an internal pilot, process evaluation and economic analysis.

INTRODUCTION: Women from social disadvantage are at greater risk of poor birth outcomes. The midwife-led continuity of care (MCC) model, which offers flexible and relational care from a small team of midwives, has demonstrated improved birth outcomes. In the general population, the impact of MCC on socially disadvantaged women and on birth outcomes is still unclear. This protocol describes a pragmatic evaluation of the MCC model in a socially disadvantaged population. METHODS AND ANALYSIS: An open-labelled individual prospective randomised controlled trial with an internal pilot, process evaluation and economic analysis, from 1 April 2022 to 31 March 2024.Women will be randomly allocated to MCC or standard care as part of usual midwifery practice. Participants and midwives will not be blinded, but researchers will be. An internal pilot will test the feasibility of this process.Participants are those randomised into MCC or standard care, who consent to participate in one of two Born in Bradford (BiB) birth cohort studies. Outcomes are taken from routinely linked health data, supplemented by additional data capture. The sample size is fixed by the capacity of MCC teams, commissioning duration and numbers recruited into the cohort. The estimated maximum fixed sample size is 1,410 pregnancies (minimum 734).Intention to treat (ITT) analysis will be undertaken to assess the impact of MCC on two independent primary outcomes. An economic evaluation will explore the impact on health resource use and a process evaluation will explore fidelity to the MCC model, and barriers/facilitators to implementation from midwives' and women's perspectives. ETHICS AND DISSEMINATION: Ethical approval has been obtained for the randomisation in midwifery practice, use of the cohort data for evaluation and for the process evaluation. Findings will be published in peer-reviewed journals, presented at conferences and translated into policy briefings. TRIAL REGISTRATION NUMBER: IsRCTNhttps://doi.org/10.1186/ISRCTN31836167.

Child educational progress in Born in Bradford pregnancies affected by gestational diabetes and also exposed to maternal common mental disorders.

Gestational diabetes and the maternal mental disorders of anxiety and depression have been implicated in adverse offspring neuro-behavioural outcomes but these exposures have only been studied in isolation. 1051 children whose mothers were diagnosed with gestational diabetes in UK's Born in Bradford cohort had linkage to maternal primary care records, providing diagnostic and treatment codes for depression and anxiety. Education record linkage provided results of the Early Years Foundation Stage Profile from the first year of school, aged five. Risk of not attaining a 'Good level of development' was analysed using multivariable Poisson regression within a generalised estimating equation framework. Multiple imputation was implemented for missing data. There was limited evidence of increased risk of failure to attain a 'good level of development' in those additionally exposed to maternal mental disorders (adjusted RR 1.21; 95% CI 0.94, 1.55). However, there was more evidence in children of Pakistani maternal ethnicity (adjusted RR 1.36; 95% CI 1.04, 1.77) than White British; this may have been driven by English not being the primary language spoken in the home. Therefore there may be groups with GDM in whom it is particularly important to optimise both maternal physical and mental health to improve child outcomes.

Detection and evaluation of signals associated with exposure to individual and combination of medications in pregnancy: a signal detection study protocol.

INTRODUCTION: Considering the high prevalence of polypharmacy in pregnant women and the knowledge gap in the risk-benefit safety profile of their often-complex treatment plan, more research is needed to optimise prescribing. In this study, we aim to detect adverse and protective effect signals of exposure to individual and pairwise combinations of medications during pregnancy. METHODS AND ANALYSIS: Using a range of real-world data sources from the UK, we aim to conduct a pharmacovigilance study to assess the safety of medications prescribed during the preconception period (3 months prior to conception) and first trimester of pregnancy. Women aged between 15 and 49 years with a record of pregnancy within the Clinical Practice Research Datalink (CPRD) Pregnancy Register, the Welsh Secure Anonymised Information Linkage (SAIL), the Scottish Morbidity Record (SMR) data sets and the Northern Ireland Maternity System (NIMATS) will be included. A series of case control studies will be conducted to estimate measures of disproportionality, detecting signals of association between a range of pregnancy outcomes and exposure to individual and combinations of medications. A multidisciplinary expert team will be invited to a signal detection workshop. By employing a structured framework, signals will be transparently assessed by each member of the team using a questionnaire appraising the signals on aspects of temporality, selection, time and measurement-related biases and confounding by underlying disease or comedications. Through group discussion, the expert team will reach consensus on each of the medication exposure-outcome signal, thereby excluding spurious signals, leaving signals suggestive of causal associations for further evaluation. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Independent Scientific Advisory Committee, SAIL Information Governance Review Panel, University of St. Andrews Teaching and Research Ethics Committee and Office for Research Ethics Committees Northern Ireland (ORECNI) for access and use of CPRD, SAIL, SMR and NIMATS data, respectively.

Association between perinatal mortality and morbidity and customised and non-customised birthweight centiles in Denmark, Finland, Norway, Wales, and England: comparative, population based, record linkage study.

Objectives: To compare the risk of adverse perinatal outcomes according to infants who are born small for gestational age (SGA; <10th centile) or large for gestational age (LGA; >90th centile), as defined by birthweight centiles that are non-customised (ie, standardised by sex and gestational age only) and customised (by sex, gestational age, maternal weight, height, parity, and ethnic group). Design: Comparative, population based, record linkage study with meta-analysis of results. Setting: Denmark, Finland, Norway, Wales, and England (city of Bradford), 1986-2019. Participants: 2 129 782 infants born at term in birth registries. Main outcome measures: Stillbirth, neonatal death, infant death, admission to neonatal intensive care unit, and low Apgar score (<7) at 5 minutes. Results: Relative to those infants born average for gestational age (AGA), both SGA and LGA births were at increased risk of all five outcomes, but observed relative risks were similar irrespective of whether non-customised or customised charts were used. For example, for SGA versus AGA births, when non-customised and customised charts were used, relative risks pooled over countries were 3.60 (95% confidence interval 3.29 to 3.93) versus 3.58 (3.02 to 4.24) for stillbirth, 2.83 (2.18 to 3.67) versus 3.32 (2.05 to 5.36) for neonatal death, 2.82 (2.07 to 3.83) versus 3.17 (2.20 to 4.56) for infant death, 1.66 (1.49 to 1.86) versus 1.54 (1.30 to 1.81) for low Apgar score at 5 minutes, and (based on Bradford data only) 1.97 (1.74 to 2.22) versus 1.94 (1.70 to 2.21) for admission to the neonatal intensive care unit. The estimated sensitivity of combined SGA or LGA births to identify the three mortality outcomes ranged from 31% to 34% for non-customised charts and from 34% to 38% for customised charts, with a specificity of 82% and 80% with non-customised and customised charts, respectively. Conclusions: These results suggest an increased risk of adverse perinatal outcomes of a similar magnitude among SGA or LGA term infants when customised and non-customised centiles are used. Use of customised charts for SGA/LGA births-over and above use of non-customised charts for SGA/LGA births-is unlikely to provide benefits in terms of identifying term births at risk of these outcomes.

Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude.

BACKGROUND: Seasonal variations in environmental exposures at birth or during gestation are associated with numerous adult traits and health outcomes later in life. Whether DNA methylation (DNAm) plays a role in the molecular mechanisms underlying the associations between birth season and lifelong phenotypes remains unclear. METHODS: We carried out epigenome-wide meta-analyses within the Pregnancy And Childhood Epigenetic Consortium to identify associations of DNAm with birth season, both at differentially methylated probes (DMPs) and regions (DMRs). Associations were examined at two time points: at birth (21 cohorts, N = 9358) and in children aged 1-11 years (12 cohorts, N = 3610). We conducted meta-analyses to assess the impact of latitude on birth season-specific associations at both time points. RESULTS: We identified associations between birth season and DNAm (False Discovery Rate-adjusted p values < 0.05) at two CpGs at birth (winter-born) and four in the childhood (summer-born) analyses when compared to children born in autumn. Furthermore, we identified twenty-six differentially methylated regions (DMR) at birth (winter-born: 8, spring-born: 15, summer-born: 3) and thirty-two in childhood (winter-born: 12, spring and summer: 10 each) meta-analyses with few overlapping DMRs between the birth seasons or the two time points. The DMRs were associated with genes of known functions in tumorigenesis, psychiatric/neurological disorders, inflammation, or immunity, amongst others. Latitude-stratified meta-analyses [higher (≥ 50°N), lower (< 50°N, northern hemisphere only)] revealed differences in associations between birth season and DNAm by birth latitude. DMR analysis implicated genes with previously reported links to schizophrenia (LAX1), skin disorders (PSORS1C, LTB4R), and airway inflammation including asthma (LTB4R), present only at birth in the higher latitudes (≥ 50°N). CONCLUSIONS: In this large epigenome-wide meta-analysis study, we provide evidence for (i) associations between DNAm and season of birth that are unique for the seasons of the year (temporal effect) and (ii) latitude-dependent variations in the seasonal associations (spatial effect). DNAm could play a role in the molecular mechanisms underlying the effect of birth season on adult health outcomes.

The development of a core outcome set for studies of pregnant women with multimorbidity.

BACKGROUND: Heterogeneity in reported outcomes can limit the synthesis of research evidence. A core outcome set informs what outcomes are important and should be measured as a minimum in all future studies. We report the development of a core outcome set applicable to observational and interventional studies of pregnant women with multimorbidity. METHODS: We developed the core outcome set in four stages: (i) a systematic literature search, (ii) three focus groups with UK stakeholders, (iii) two rounds of Delphi surveys with international stakeholders and (iv) two international virtual consensus meetings. Stakeholders included women with multimorbidity and experience of pregnancy in the last 5 years, or are planning a pregnancy, their partners, health or social care professionals and researchers. Study adverts were shared through stakeholder charities and organisations. RESULTS: Twenty-six studies were included in the systematic literature search (2017 to 2021) reporting 185 outcomes. Thematic analysis of the focus groups added a further 28 outcomes. Two hundred and nine stakeholders completed the first Delphi survey. One hundred and sixteen stakeholders completed the second Delphi survey where 45 outcomes reached Consensus In (≥70% of all participants rating an outcome as Critically Important). Thirteen stakeholders reviewed 15 Borderline outcomes in the first consensus meeting and included seven additional outcomes. Seventeen stakeholders reviewed these 52 outcomes in a second consensus meeting, the threshold was ≥80% of all participants voting for inclusion. The final core outcome set included 11 outcomes. The five maternal outcomes were as follows: maternal death, severe maternal morbidity, change in existing long-term conditions (physical and mental), quality and experience of care and development of new mental health conditions. The six child outcomes were as follows: survival of baby, gestational age at birth, neurodevelopmental conditions/impairment, quality of life, birth weight and separation of baby from mother for health care needs. CONCLUSIONS: Multimorbidity in pregnancy is a new and complex clinical research area. Following a rigorous process, this complexity was meaningfully reduced to a core outcome set that balances the views of a diverse stakeholder group.

Prediction of childhood overweight and obesity at age 10-11: findings from the Studying Lifecourse Obesity PrEdictors and the Born in Bradford cohorts.

BACKGROUND: In England, 41% of children aged 10-11 years live with overweight or obesity. Identifying children at risk of developing overweight or obesity may help target early prevention interventions. We aimed to develop and externally validate prediction models of childhood overweight and obesity at age 10-11 years using routinely collected weight and height measurements at age 4-5 years and maternal and early-life health data. METHODS: We used an anonymised linked cohort of maternal pregnancy and birth health records in Hampshire, UK between 2003 and 2008 and child health records. Childhood body mass index (BMI), adjusted for age and sex, at 10-11 years was used to define the outcome of overweight and obesity (BMI ≥ 91st centile) in the models. Logistic regression models and multivariable fractional polynomials were used to select model predictors and to identify transformations of continuous predictors that best predict the outcome. Models were externally validated using data from the Born in Bradford birth cohort. Model performance was assessed using discrimination and calibration. RESULTS: Childhood BMI was available for 6566 children at 4-5 (14.6% overweight) and 10-11 years (26.1% overweight) with 10.8% overweight at both timepoints. The area under the curve (AUC) was 0.82 at development and 0.83 on external validation for the model only incorporating two predictors: BMI at 4-5 years and child sex. AUC increased to 0.84 on development and 0.85 on external validation on additionally incorporating maternal predictors in early pregnancy (BMI, smoking, age, educational attainment, ethnicity, parity, employment status). Models were well calibrated. CONCLUSIONS: This prediction modelling can be applied at 4-5 years to identify the risk for childhood overweight at 10-11 years, with slightly improved prediction with the inclusion of maternal data. These prediction models demonstrate that routinely collected data can be used to target early preventive interventions to reduce the prevalence of childhood obesity.

The effects of exposure to NO2, PM2.5 and PM10 on health service attendances with respiratory illnesses: A time-series analysis.

The associations of exposure to air-pollutants and respiratory illness remains inconsistent and studies have not adequately addressed the non-linearity and delayed effects of exposure. This is a retrospective cohort study using linked routine health and pollution data collected between January 2018 and December 2021. Participants were patients who visited General Practice (GP) or accident and emergency (A&E) services for respiratory illness. Time-series analysis, distributed lagged models, was used to address the potential non-linearity and delayed effects of exposure. There were 114,930 GP and 9878 A&E respiratory visits. For every 10 µg/m3 increase in NO2 and PM2.5 above the WHO recommended 24-hr thresholds, the immediate relative risk of GP respiratory visits was 1.09 (95% CI: 1.07 to 1.05) and 1.06 (95% CI: 1.01 to 1.10), respectively. The respective relative risk of A&E visit was 1.10 (95% CI: 1.07 to 1.14) and 1.07 (95% CI: 1.00 to 1.14). Exposure to 10-unit increases in NO2, PM2.5 and PM10 above the WHO recommended 24-hr thresholds, was associated with lagged relative risks of 1.49 (95% CI: 1.42 to 1.56), 5.26 (95% CI: 4.18 to 6.61) and 2.32 (95% CI: 1.66 to 3.26), respectively, for GP respiratory attendances. The lagged relative risk of A&E respiratory visits for same units of exposure in NO2, PM2.5, and PM10 at the peak lag days were 1.98 (95% CI: 1.82 to 2.15), 4.52 (95% CI: 3.37 to 6.07) and 3.55 (95% CI: 1.85 to 6.84). A third of GP and half of A&E respiratory visits were attributable to exposure to NO2 beyond the WHO threshold. The combined cost of these visits over the study period was 1.95 million (95% CI: 1.82 to 2.09). High pollution events are related to increased health service use for respiratory illness, with impacts persisting up to 100 days post exposure. The burden of respiratory illness related to air-pollution may be considerably higher than previously reported.

Evaluating causal associations of chronotype with pregnancy and perinatal outcomes and its interactions with insomnia and sleep duration: a Mendelian randomization study.

IMPORTANCE: Observational studies suggest that chronotype is associated with pregnancy and perinatal outcomes. Whether these associations are causal is unclear. OBJECTIVE: To explore associations of a lifetime genetic predisposition to an evening preference chronotype with pregnancy and perinatal outcomes, and explore differences in associations of insomnia and sleep duration with those outcomes between chronotype. DESIGN SETTING AND PARTICIPANTS: We conducted two-sample Mendelian randomization (MR) using 105 genetic variants reported in a genome-wide association study (N=248 100) to instrument for lifelong predisposition to evening-versus morning-preference chronotypes. We generated variant-outcome associations in European ancestry women from UK Biobank (UKB, N=176 897), Avon Longitudinal Study of Parents and Children (ALSPAC, N=6826), Born in Bradford (BiB, N=2940) and Norwegian Mother, Father and Child Cohort Study (MoBa, with linked data from the Medical Birth Registry of Norway (MBRN), N=57 430), and extracted equivalent associations from FinnGen (N=190 879). We used inverse variance weighted (IVW) as main analysis, with weighted median and MR-Egger as sensitivity analyses. We also conducted IVW analyses of insomnia and sleep duration on the outcomes stratified by genetically predicted chronotype. EXPOSURES: Self-reported and genetically predicted chronotype, insomnia and sleep duration. MAIN OUTCOMES AND MEASURES: Stillbirth, miscarriage, preterm birth, gestational diabetes, hypertensive disorders of pregnancy, perinatal depression, low birthweight and macrosomia. RESULTS: In IVW and sensitivity analyses we did not find robust evidence of effects of chronotype on the outcomes. Insomnia was associated with a higher risk of preterm birth among evening preference women (odds ratio 1.61, 95% confidence interval: 1.17, 2.21), but not among morning preference women (odds ratio 0.87, 95% confidence interval: 0.64, 1.18), with an interaction P-value=0.01. There was no evidence of interactions between insomnia and chronotype on other outcomes, or between sleep duration and chronotype on any outcomes. CONCLUSIONS AND RELEVANCE: This study raises the possibility of a higher risk of preterm birth among women with insomnia who also have an evening preference chronotype. Our findings warrant replications due to imprecision of the estimates. Key points: Question: Does an evening preference chronotype adversely affect pregnancy and perinatal outcomes? Is there an interaction between chronotype and either insomnia or sleep duration in relation to those outcomes?Findings: There was no evidence that evening preference was associated with pregnancy or perinatal outcomes. Women with a genetically predicted insomnia had a higher risk of preterm birth, if they also had a genetically predicted preference for evening chronotype.Meaning: The suggestive interaction between insomnia and evening preference on preterm birth, if replicated, supports targeting insomnia prevention in women of reproductive age with an evening chronotype.

Home working and social and mental wellbeing at different stages of the COVID-19 pandemic in the UK: Evidence from 7 longitudinal population surveys.

BACKGROUND: Home working has increased since the Coronavirus Disease 2019 (COVID-19) pandemic's onset with concerns that it may have adverse health implications. We assessed the association between home working and social and mental wellbeing among the employed population aged 16 to 66 through harmonised analyses of 7 UK longitudinal studies. METHODS AND FINDINGS: We estimated associations between home working and measures of psychological distress, low life satisfaction, poor self-rated health, low social contact, and loneliness across 3 different stages of the pandemic (T1 = April to June 2020 -first lockdown, T2 = July to October 2020 -eased restrictions, T3 = November 2020 to March 2021 -second lockdown) using modified Poisson regression and meta-analyses to pool results across studies. We successively adjusted the model for sociodemographic characteristics (e.g., age, sex), job characteristics (e.g., sector of activity, pre-pandemic home working propensities), and pre-pandemic health. Among respectively 10,367, 11,585, and 12,179 participants at T1, T2, and T3, we found higher rates of home working at T1 and T3 compared with T2, reflecting lockdown periods. Home working was not associated with psychological distress at T1 (RR = 0.92, 95% CI = 0.79 to 1.08) or T2 (RR = 0.99, 95% CI = 0.88 to 1.11), but a detrimental association was found with psychological distress at T3 (RR = 1.17, 95% CI = 1.05 to 1.30). Study limitations include the fact that pre-pandemic home working propensities were derived from external sources, no information was collected on home working dosage and possible reverse association between change in wellbeing and home working likelihood. CONCLUSIONS: No clear evidence of an association between home working and mental wellbeing was found, apart from greater risk of psychological distress during the second lockdown, but differences across subgroups (e.g., by sex or level of education) may exist. Longer term shifts to home working might not have adverse impacts on population wellbeing in the absence of pandemic restrictions but further monitoring of health inequalities is required.

Defining cases of asthma, eczema and allergic rhinitis using electronic health records in the Born in Bradford birth cohort.

Key Messages • In electronic health records, the accuracy of diagnostic codes to define outcomes can be uncertain • The accuracy can vary in different settings, doctors and practices, even with validated codes • We recommend definitions combining codes previously described and other codes available in the records.

Maternal and child outcomes for pregnant women with pre-existing multiple long-term conditions: protocol for an observational study in the UK.

INTRODUCTION: One in five pregnant women has multiple pre-existing long-term conditions in the UK. Studies have shown that maternal multiple long-term conditions are associated with adverse outcomes. This observational study aims to compare maternal and child outcomes for pregnant women with multiple long-term conditions to those without multiple long-term conditions (0 or 1 long-term conditions). METHODS AND ANALYSIS: Pregnant women aged 15-49 years old with a conception date between 2000 and 2019 in the UK will be included with follow-up till 2019. The data source will be routine health records from all four UK nations (Clinical Practice Research Datalink (England), Secure Anonymised Information Linkage (Wales), Scotland routine health records and Northern Ireland Maternity System) and the Born in Bradford birth cohort. The exposure of two or more pre-existing, long-term physical or mental health conditions will be defined from a list of health conditions predetermined by women and clinicians. The association of maternal multiple long-term conditions with (a) antenatal, (b) peripartum, (c) postnatal and long-term and (d) mental health outcomes, for both women and their children will be examined. Outcomes of interest will be guided by a core outcome set. Comparisons will be made between pregnant women with and without multiple long-term conditions using modified Poisson and Cox regression. Generalised estimating equation will account for the clustering effect of women who had more than one pregnancy episode. Where appropriate, multiple imputation with chained equation will be used for missing data. Federated analysis will be conducted for each dataset and results will be pooled using random-effects meta-analyses. ETHICS AND DISSEMINATION: Approval has been obtained from the respective data sources in each UK nation. Study findings will be submitted for publications in peer-reviewed journals and presented at key conferences.

Polypharmacy during pregnancy and associated risk factors: a retrospective analysis of 577 medication exposures among 1.5 million pregnancies in the UK, 2000-2019.

BACKGROUND: The number of medications prescribed during pregnancy has increased over the past few decades. Few studies have described the prevalence of multiple medication use among pregnant women. This study aims to describe the overall prevalence over the last two decades among all pregnant women and those with multimorbidity and to identify risk factors for polypharmacy in pregnancy. METHODS: A retrospective cohort study was conducted between 2000 and 2019 using the Clinical Practice Research Datalink (CPRD) pregnancy register. Prescription records for 577 medication categories were obtained. Prevalence estimates for polypharmacy (ranging from 2+ to 11+ medications) were presented along with the medications commonly prescribed individually and in pairs during the first trimester and the entire pregnancy period. Logistic regression models were performed to identify risk factors for polypharmacy. RESULTS: During the first trimester (812,354 pregnancies), the prevalence of polypharmacy ranged from 24.6% (2+ medications) to 0.1% (11+ medications). During the entire pregnancy period (774,247 pregnancies), the prevalence ranged from 58.7 to 1.4%. Broad-spectrum penicillin (6.6%), compound analgesics (4.5%) and treatment of candidiasis (4.3%) were commonly prescribed. Pairs of medication prescribed to manage different long-term conditions commonly included selective beta 2 agonists or selective serotonin re-uptake inhibitors (SSRIs). Risk factors for being prescribed 2+ medications during the first trimester of pregnancy include being overweight or obese [aOR: 1.16 (1.14-1.18) and 1.55 (1.53-1.57)], belonging to an ethnic minority group [aOR: 2.40 (2.33-2.47), 1.71 (1.65-1.76), 1.41 (1.35-1.47) and 1.39 (1.30-1.49) among women from South Asian, Black, other and mixed ethnicities compared to white women] and smoking or previously smoking [aOR: 1.19 (1.18-1.20) and 1.05 (1.03-1.06)]. Higher and lower age, higher gravidity, increasing number of comorbidities and increasing level of deprivation were also associated with increased odds of polypharmacy. CONCLUSIONS: The prevalence of polypharmacy during pregnancy has increased over the past two decades and is particularly high in younger and older women; women with high BMI, smokers and ex-smokers; and women with multimorbidity, higher gravidity and higher levels of deprivation. Well-conducted pharmaco-epidemiological research is needed to understand the effects of multiple medication use on the developing foetus.

Study Protocol. Evaluating the life-course health impact of a city-wide system approach to improve air quality in Bradford, UK: A quasi-experimental study with implementation and process evaluation.

BACKGROUND: Air quality is a major public health threat linked to poor birth outcomes, respiratory and cardiovascular disease, and premature mortality. Deprived groups and children are disproportionately affected. Bradford will implement a Clean Air Zone (CAZ) as part of the Bradford Clean Air Plan (B-CAP) in 2022 to reduce pollution, providing a natural experiment. The aim of the current study is to evaluate the impact of the B-CAP on health outcomes and air quality, inequalities and explore value for money. An embedded process and implementation evaluation will also explore barriers and facilitators to implementation, impact on attitudes and behaviours, and any adverse consequences. METHODS: The study is split into 4 work packages (WP). WP1A: 20 interviews with decision makers, 20 interviews with key stakeholders; 10 public focus groups and documentary analysis of key reports will assess implementation barriers, acceptability and adverse or unanticipated consequences at 1 year post-implementation (defined as point at which charging CAZ goes 'live'). WP1B: A population survey (n = 2000) will assess travel behaviour and attitudes at baseline and change at 1 year post-implementation). WP2: Routine air quality measurements will be supplemented with data from mobile pollution sensors in 12 schools collected by N = 240 pupil citizen scientists (4 within, 4 bordering and 4 distal to CAZ boundary). Pupils will carry sensors over four monitoring periods over a 12 month period (two pre, and two post-implementation). We will explore whether reductions in pollution vary by CAZ proximity. WP3A: We will conduct a quasi-experimental interrupted time series analysis using a longitudinal routine health dataset of > 530,000 Bradford residents comparing trends (3 years prior vs 3 years post) in respiratory health (assessed via emergency/GP attendances. WP3B: We will use the richly-characterised Born in Bradford cohort (13,500 children) to explore health inequalities in respiratory health using detailed socio-economic data. WP4: will entail a multi-sectoral health economic evaluation to determine value for money of the B-CAP. DISCUSSION: This will be first comprehensive quasi-experimental evaluation of a city-wide policy intervention to improve air quality. The findings will be of value for other areas implementing this type of approach. TRIAL REGISTRATION: ISRCTN67530835 https://doi.org/10.1186/ISRCTN67530835.

Inequalities in healthcare disruptions during the COVID-19 pandemic: evidence from 12 UK population-based longitudinal studies.

OBJECTIVES: We investigated associations between multiple sociodemographic characteristics (sex, age, occupational social class, education and ethnicity) and self-reported healthcare disruptions during the early stages of the COVID-19 pandemic. DESIGN: Coordinated analysis of prospective population surveys. SETTING: Community-dwelling participants in the UK between April 2020 and January 2021. PARTICIPANTS: Over 68 000 participants from 12 longitudinal studies. OUTCOMES: Self-reported healthcare disruption to medication access, procedures and appointments. RESULTS: Prevalence of healthcare disruption varied substantially across studies: between 6% and 32% reported any disruption, with 1%-10% experiencing disruptions in medication, 1%-17% experiencing disruption in procedures and 4%-28% experiencing disruption in clinical appointments. Females (OR 1.27; 95% CI 1.15 to 1.40; I2=54%), older persons (eg, OR 1.39; 95% CI 1.13 to 1.72; I2=77% for 65-75 years vs 45-54 years) and ethnic minorities (excluding white minorities) (OR 1.19; 95% CI 1.05 to 1.35; I2=0% vs white) were more likely to report healthcare disruptions. Those in a more disadvantaged social class were also more likely to report healthcare disruptions (eg, OR 1.17; 95% CI 1.08 to 1.27; I2=0% for manual/routine vs managerial/professional), but no clear differences were observed by education. We did not find evidence that these associations differed by shielding status. CONCLUSIONS: Healthcare disruptions during the COVID-19 pandemic could contribute to the maintenance or widening of existing health inequalities.

Characterisation of ethnic differences in DNA methylation between UK-resident South Asians and Europeans.

Ethnic differences in non-communicable disease risk have been described between individuals of South Asian and European ethnicity that are only partially explained by genetics and other known risk factors. DNA methylation is one underexplored mechanism that may explain differences in disease risk. Currently, there is little knowledge of how DNA methylation varies between South Asian and European ethnicities. This study characterised differences in blood DNA methylation between individuals of self-reported European and South Asian ethnicity from two UK-based cohorts: Southall and Brent Revisited and Born in Bradford. DNA methylation differences between ethnicities were widespread throughout the genome (n = 16,433 CpG sites, 3.4% sites tested). Specifically, 76% of associations were attributable to ethnic differences in cell composition with fewer effects attributable to smoking and genetic variation. Ethnicity-associated CpG sites were enriched for EWAS Catalog phenotypes including metabolites. This work highlights the need to consider ethnic diversity in epigenetic research.

Investigating causal relations between sleep duration and risks of adverse pregnancy and perinatal outcomes: linear and nonlinear Mendelian randomization analyses.

BACKGROUND: Observational studies have reported maternal short/long sleep duration to be associated with adverse pregnancy and perinatal outcomes. However, it remains unclear whether there are nonlinear causal effects. Our aim was to use Mendelian randomization (MR) and multivariable regression to examine nonlinear effects of sleep duration on stillbirth (MR only), miscarriage (MR only), gestational diabetes, hypertensive disorders of pregnancy, perinatal depression, preterm birth and low/high offspring birthweight. METHODS: We used data from European women in UK Biobank (N=176,897), FinnGen (N=~123,579), Avon Longitudinal Study of Parents and Children (N=6826), Born in Bradford (N=2940) and Norwegian Mother, Father and Child Cohort Study (MoBa, N=14,584). We used 78 previously identified genetic variants as instruments for sleep duration and investigated its effects using two-sample, and one-sample nonlinear (UK Biobank only), MR. We compared MR findings with multivariable regression in MoBa (N=76,669), where maternal sleep duration was measured at 30 weeks. RESULTS: In UK Biobank, MR provided evidence of nonlinear effects of sleep duration on stillbirth, perinatal depression and low offspring birthweight. Shorter and longer duration increased stillbirth and low offspring birthweight; shorter duration increased perinatal depression. For example, longer sleep duration was related to lower risk of low offspring birthweight (odds ratio 0.79 per 1 h/day (95% confidence interval: 0.67, 0.93)) in the shortest duration group and higher risk (odds ratio 1.40 (95% confidence interval: 1.06, 1.84)) in the longest duration group, suggesting shorter and longer duration increased the risk. These were supported by the lack of evidence of a linear effect of sleep duration on any outcome using two-sample MR. In multivariable regression, risks of all outcomes were higher in the women reporting <5 and ≥10 h/day sleep compared with the reference category of 8-9 h/day, despite some wide confidence intervals. Nonlinear models fitted the data better than linear models for most outcomes (likelihood ratio P-value=0.02 to 3.2×10-52), except for gestational diabetes. CONCLUSIONS: Our results show shorter and longer sleep duration potentially causing higher risks of stillbirth, perinatal depression and low offspring birthweight. Larger studies with more cases are needed to detect potential nonlinear effects on hypertensive disorders of pregnancy, preterm birth and high offspring birthweight.