Echogenic intracardiac foci detection and location in the second-trimester ultrasound and association with fetal outcomes: A systematic literature review.

BACKGROUND: Echogenic Intracardiac Foci (EIF) are non-structural markers identified during the routine 18-20-week foetal anomaly ultrasound scan yet their clinical significance on future outcomes for the infant is unclear. OBJECTIVE: To examine the association between EIF and risk of preterm birth, chromosomal abnormalities, and cardiac abnormalities. DESIGN: A review across four databases to identify English language journal articles of EIF using a cohort study design. All studies were reviewed for quality using the Critical Appraisal Skills Programme (CASP) checklist and data extracted for comparison and analysis. RESULTS: 19 papers from 9 different countries were included. Combining these studies showed 4.6% (95% CI = 4.55-4.65%) of all pregnancies had EIF which was on the left in 86% of cases, on the right in 3% of cases and bilaterally in 10%. There was no evidence that EIF was associated with higher rates of preterm birth. However, it is possible that infants with EIF were more likely to be terminated rather than be born preterm as there was a 2.1% (range 0.3-4.2%) rate of termination or death of the foetus after week 20 among those with EIF. There was no evidence that EIF alone is highly predictive of chromosomal abnormalities. There was evidence that EIF is associated with higher rates of minor cardiac abnormalities (e.g. ventricular septal defect, tricuspid regurgitation or mitral regurgitation)) with 5.1% (224 of 4385) of those with EIF showing cardiac abnormalities (3.08% in retrospective studies and 17.85% in prospective studies). However, the risk of cardiac defects was only higher with right-sided EIF and where the EIF persisted into the third trimester. However, this is a rare event and would be seen in an estimated 4 per 10,000 pregnancies. CONCLUSION: EIF alone was not associated with adverse outcomes for the infant. Only persistent EIF on the right side showed evidence of carrying a higher risk of cardiac abnormality and would warrant further follow-up.

Changes in self-reported health and wellbeing outcomes in 36,951 primary school children from 2014 to 2022 in Wales: an analysis using annual survey data.

Introduction: This study examines the changes in childhood self-reported health and wellbeing between 2014 and 2022. Methods: An annual survey delivered by HAPPEN-Wales, in collaboration with 500 primary schools, captured self-reported data on physical health, dietary habits, mental health, and overall wellbeing for children aged 8-11 years. Results: The findings reveal a decline in physical health between 2014 and 2022, as evidenced by reduced abilities in swimming and cycling. For example, 68% of children (95%CI: 67%-69%) reported being able to swim 25m in 2022, compared to 85% (95% CI: 83%-87%) in 2018. Additionally, unhealthy eating habits, such as decreased fruit and vegetable consumption and increased consumption of sugary snacks, have become more prevalent. Mental health issues, including emotional and behavioural difficulties, have also increased, with emotional difficulties affecting 13%-15% of children in 2017-2018 and now impacting 29% of children in 2021-2022. Moreover, indicators of wellbeing, autonomy, and competence have declined. Discussion: Importantly, this trend of declining health and wellbeing predates the onset of the Covid-19 pandemic, suggesting that it is not solely attributed to the pandemic's effects. The health of primary school children has been on a declining trajectory since 2018/2019 and has continued to decline through the COVID recovery period. The study suggests that these trends are unlikely to improve without targeted intervention and policy focus.

Cohort profile: Born in Wales-a birth cohort with maternity, parental and child data linkage for life course research in Wales, UK.

PURPOSE: Using Wales's national dataset for maternity and births as a core dataset, we have linked related datasets to create a more complete and comprehensive entire country birth cohort. Data of anonymised identified persons are linked on the individual level to data from health, social care and education data within the Secure Anonymised Information Linkage (SAIL) Databank. Each individual is assigned an encrypted Anonymised Linking Field; this field is used to link anonymised individuals across datasets. We present the descriptive data available in the core dataset, and the future expansion plans for the database beyond its initial development stage. PARTICIPANTS: Descriptive information from 2011 to 2023 has been gathered from the National Community Child Health Database (NCCHD) in SAIL. This comprehensive dataset comprises over 400 000 child electronic records. Additionally, survey responses about health and well-being from a cross-section of the population including 2500 parents and 30 000 primary school children have been collected for enriched personal responses and linkage to the data spine. FINDINGS TO DATE: The electronic cohort comprises all children born in Wales since 2011, with follow-up conducted until they finish primary school at age 11. The child cohort is 51%: 49% female: male, and 7.8% are from ethnic minority backgrounds. When considering age distribution, 26.8% of children are under the age of 5, while 63.2% fall within the age range of 5-11. FUTURE PLANS: Born in Wales will expand by 30 000 new births annually in Wales (in NCCHD), while including follow-up data of children and parents already in the database. Supplementary datasets complement the existing linkage, including primary care, hospital data, educational attainment and social care. Future research includes exploring the long-term implications of COVID-19 on child health and development, and examining the impact of parental work environment on child health and development.

Factors associated with low school readiness, a linked health and education data study in Wales, UK.

BACKGROUND: School readiness is a measure of a child's cognitive, social, and emotional readiness to begin formal schooling. Children with low school readiness need additional support from schools for learning, developing required social and academic skills, and catching-up with their school-ready peers. This study aims to identify the most significant risk factors associated with low school readiness using linked routine data for children in Wales. METHOD: This was a longitudinal cohort study using linked data. The cohort comprises of children who completed the Foundation Phase assessment between 2012 and 2018. Individuals were identified by linking Welsh Demographic Service and Pre16 Education Attainment datasets. School readiness was assessed via the binary outcome of the Foundation Phase assessment (achieved/not achieved). This study used multivariable logistic regression model and a decision tree to identify and weight the most important risk factors associated with low school readiness. RESULTS: In order of importance, logistic regression identified maternal learning difficulties (adjusted odds ratio 5.35(95% confidence interval 3.97-7.22)), childhood epilepsy (2.95(2.39-3.66)), very low birth weight (2.24(1.86-2.70), being a boy (2.11(2.04-2.19)), being on free school meals (1.85(1.78-1.93)), living in the most deprived areas (1.67(1.57-1.77)), maternal death (1.47(1.09-1.98)), and maternal diabetes (1.46(1.23-1.78)) as factors associated with low school readiness. Using a decision tree, eligibility for free school meals, being a boy, absence/low attendance at school, being born late in the academic year, being a low birthweight child, and not being breastfed were factors which were associated with low school readiness. CONCLUSION: This work suggests that public health interventions focusing on children who are: boys, living in deprived areas, have poor early years attendance, have parents with learning difficulties, have parents with an illness or have illnesses themselves, would make the most difference to school readiness in the population.

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.

COVID-19 vaccination in pregnancy: the impact of multimorbidity and smoking status on vaccine hesitancy, a cohort study of 25,111 women in Wales, UK.

BACKGROUND: Multimorbidity, smoking status, and pregnancy are identified as three risk factors associated with more severe outcomes following a SARS-CoV-2 infection, thus vaccination uptake is crucial for pregnant women living with multimorbidity and a history of smoking. This study aimed to examine the impact of multimorbidity, smoking status, and demographics (age, ethnic group, area of deprivation) on vaccine hesitancy among pregnant women in Wales using electronic health records (EHR) linkage. METHODS: This cohort study utilised routinely collected, individual-level, anonymised population-scale linked data within the Secure Anonymised Information Linkage (SAIL) Databank. Pregnant women were identified from 13th April 2021 to 31st December 2021. Survival analysis was employed to examine and compare the length of time to vaccination uptake in pregnancy by considering multimorbidity, smoking status, as well as depression, diabetes, asthma, and cardiovascular conditions independently. The study also assessed the variation in uptake by multimorbidity, smoking status, and demographics, both jointly and separately for the independent conditions, using hazard ratios (HR) derived from the Cox regression model. RESULTS: Within the population cohort, 8,203 (32.7%) received at least one dose of the COVID-19 vaccine during pregnancy, with 8,572 (34.1%) remaining unvaccinated throughout the follow-up period, and 8,336 (33.2%) receiving the vaccine postpartum. Women aged 30 years or older were more likely to have the vaccine in pregnancy. Those who had depression were slightly but significantly more likely to have the vaccine compared to those without depression (HR = 1.08, 95% CI 1.03 to 1.14, p = 0.002). Women living with multimorbidity were 1.12 times more likely to have the vaccine compared to those living without multimorbidity (HR = 1.12, 95% CI 1.04 to 1.19, p = 0.001). Vaccine uptakes were significantly lower among both current smokers and former smokers compared to never smokers (HR = 0.87, 95% CI 0.81 to 0.94, p < 0.001 and HR = 0.92, 95% CI 0.85 to 0.98, p = 0.015 respectively). Uptake was also lower among those living in the most deprived areas compared to those living in the most affluent areas (HR = 0.89, 95% CI 0.83 to 0.96, p = 0.002). CONCLUSION: Younger women, living without multimorbidity, current and former smokers, and those living in the more deprived areas are less likely to have the vaccine, thus, a targeted approach to vaccinations may be required for these groups. Pregnant individuals living with multimorbidity exhibit a slight but statistically significant reduction in vaccine hesitancy towards COVID-19 during pregnancy.

Maternal multimorbidity and preterm birth in Scotland: an observational record-linkage study.

BACKGROUND: Multimorbidity is common in women across the life course. Preterm birth is the single biggest cause of neonatal mortality and morbidity. We aim to estimate the prevalence of multimorbidity in pregnant women and to examine the association between maternal multimorbidity and PTB. METHODS: This is a retrospective cohort study using electronic health records from the Scottish Morbidity Records. All pregnancies among women aged 15 to 49 with a conception date between 1 January 2014 and 31 December 2018 were included. Multimorbidity was defined as the presence of two or more pre-existing long-term physical or mental health conditions, and complex multimorbidity as the presence of four or more. It was calculated at the time of conception using a predefined list of 79 conditions published by the MuM-PreDiCT consortium. PTB was defined as babies born alive between 24 and less than 37 completed weeks of gestation. We used Generalised Estimating Equations adjusted for maternal age, socioeconomic status, number of previous pregnancies, BMI, and smoking history to estimate the effect of maternal pre-existing multimorbidity. Absolut rates are reported in the results and tables, whilst Odds Ratios (ORs) are adjusted (aOR). RESULTS: Thirty thousand five hundred fifty-seven singleton births from 27,711 pregnant women were included in the analysis. The prevalence of pre-existing multimorbidity and complex multimorbidity was 16.8% (95% CI: 16.4-17.2) and 3.6% (95% CI: 3.3-3.8), respectively. The prevalence of multimorbidity in the youngest age group was 10.2%(95% CI: 8.8-11.6), while in those 40 to 44, it was 21.4% (95% CI: 18.4-24.4), and in the 45 to 49 age group, it was 20% (95% CI: 8.9-31.1). In women without multimorbidity, the prevalence of PTB was 6.7%; it was 11.6% in women with multimorbidity and 15.6% in women with complex multimorbidity. After adjusting for maternal age, socioeconomic status, number of previous pregnancies, Body Mass Index (BMI), and smoking, multimorbidity was associated with higher odds of PTB (aOR = 1.64, 95% CI: 1.48-1.82). CONCLUSIONS: Multimorbidity at the time of conception was present in one in six women and was associated with an increased risk of preterm birth. Multimorbidity presents a significant health burden to women and their offspring. Routine and comprehensive evaluation of women with multimorbidity before and during pregnancy is urgently needed.

Key outcomes for reporting in studies of pregnant women with multiple long-term conditions: a qualitative study.

BACKGROUND: Maternal multiple long-term conditions are associated with adverse outcomes for mother and child. We conducted a qualitative study to inform a core outcome set for studies of pregnant women with multiple long-term conditions. METHODS: Women with two or more pre-existing long-term physical or mental health conditions, who had been pregnant in the last five years or planning a pregnancy, their partners and health care professionals were eligible. Recruitment was through social media, patients and health care professionals' organisations and personal contacts. Participants who contacted the study team were purposively sampled for maximum variation. Three virtual focus groups were conducted from December 2021 to March 2022 in the United Kingdom: (i) health care professionals (n = 8), (ii) women with multiple long-term conditions (n = 6), and (iii) women with multiple long-term conditions (n = 6) and partners (n = 2). There was representation from women with 20 different physical health conditions and four mental health conditions; health care professionals from obstetrics, obstetric/maternal medicine, midwifery, neonatology, perinatal psychiatry, and general practice. Participants were asked what outcomes should be reported in all studies of pregnant women with multiple long-term conditions. Inductive thematic analysis was conducted. Outcomes identified in the focus groups were mapped to those identified in a systematic literature search in the core outcome set development. RESULTS: The focus groups identified 63 outcomes, including maternal (n = 43), children's (n = 16) and health care utilisation (n = 4) outcomes. Twenty-eight outcomes were new when mapped to the systematic literature search. Outcomes considered important were generally similar across stakeholder groups. Women emphasised outcomes related to care processes, such as information sharing when transitioning between health care teams and stages of pregnancy (continuity of care). Both women and partners wanted to be involved in care decisions and to feel informed of the risks to the pregnancy and baby. Health care professionals additionally prioritised non-clinical outcomes, including quality of life and financial implications for the women; and longer-term outcomes, such as children's developmental outcomes. CONCLUSIONS: The findings will inform the design of a core outcome set. Participants' experiences provided useful insights of how maternity care for pregnant women with multiple long-term conditions can be improved.

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.

Childhood Outcomes in Children with and without Cardiac Echogenic Foci: An Electronic Birth Cohort Study in Wales, UK.

There is uncertainty about outcomes associated with cardiac echogenic foci (CEF) seen at the midtrimester ultrasound scan because of limited population-based follow-up data. This can lead to unnecessary invasive testing and significant parental anxiety. We analysed data from a cohort study, The Welsh Study of Mothers and Babies, to examine whether children with CEF had more adverse outcomes during childhood compared with children without CEF. Children born between 1 January 2009 and 31 December 2011 were followed until 31 January 2018, migration out of Wales, or death. The primary outcome was cardiac hospital admissions, defined a priori by an expert steering group. Secondary outcomes included congenital cardiac anomalies, and hospital admissions for other causes. There was no evidence of an association between isolated CEF and cardiac hospital admissions (hazard ratio 0.87, 95% confidence interval [CI] 0.33-2.25, p value 0.768), or with congenital cardiac anomalies. There was a small increased risk of a respiratory admission with isolated CEF (hazard ratio 1.27, 95% CI 1.04-1.54, p value 0.020). Further research is needed on features of CEF, such as location or number, to fully understand the clinical significance of these findings.

Insights from linking police domestic abuse data and health data in South Wales, UK: a linked routine data analysis using decision tree classification.

BACKGROUND: Exposure to domestic abuse can lead to long-term negative impacts on the victim's physical and psychological wellbeing. The 1998 Crime and Disorder Act requires agencies to collaborate on crime reduction strategies, including data sharing. Although data sharing is feasible for individuals, rarely are whole-agency data linked. This study aimed to examine the knowledge obtained by integrating information from police and health-care datasets through data linkage and analyse associated risk factor clusters. METHODS: This retrospective cohort study analyses data from residents of South Wales who were victims of domestic abuse resulting in a Public Protection Notification (PPN) submission between Aug 12, 2015 and March 31, 2020. The study links these data with the victims' health records, collated within the Secure Anonymised Information Linkage databank, to examine factors associated with the outcome of an Emergency Department attendance, emergency hospital admission, or death within 12 months of the PPN submission. To assess the time to outcome for domestic abuse victims after the index PPN submission, we used Kaplan-Meier survival analysis. We used multivariable Cox regression models to identify which factors contributed the highest risk of experiencing an outcome after the index PPN submission. Finally, we created decision trees to describe specific groups of individuals who are at risk of experiencing a domestic abuse incident and subsequent outcome. FINDINGS: After excluding individuals with multiple PPN records, duplicates, and records with a poor matching score or missing fields, the resulting clean dataset consisted of 8709 domestic abuse victims, of whom 6257 (71·8%) were female. Within a year of a domestic abuse incident, 3650 (41·9%) individuals had an outcome. Factors associated with experiencing an outcome within 12 months of the PPN included younger victim age (hazard ratio 1·183 [95% CI 1·053-1·329], p=0·0048), further PPN submissions after the initial referral (1·383 [1·295-1·476]; p<0·0001), injury at the scene (1·484 [1·368-1·609]; p<0·0001), assessed high risk (1·600 [1·444-1·773]; p<0·0001), referral to other agencies (1·518 [1·358-1·697]; p<0·0001), history of violence (1·229 [1·134-1·333]; p<0·0001), attempted strangulation (1·311 [1·148-1·497]; p<0·0001), and pregnancy (1·372 [1·142-1·648]; p=0·0007). Health-care data before the index PPN established that previous Emergency Department and hospital admissions, smoking, smoking cessation advice, obstetric codes, and prescription of antidepressants and antibiotics were associated with having a future outcome following a domestic abuse incident. INTERPRETATION: The results indicate that vulnerable individuals are detectable in multiple datasets before and after involvement of the police. Operationalising these findings could reduce police callouts and future Emergency Department or hospital admissions, and improve outcomes for those who are vulnerable. Strategies include querying previous Emergency Department and hospital admissions, giving a high-risk assessment for a pregnant victim, and facilitating data linkage to identify vulnerable individuals. FUNDING: National Institute for Health Research.

Breastfeeding initiation and duration through the COVID-19 pandemic, a linked population-level routine data study: the Born in Wales Cohort 2018-2021.

OBJECTIVES: The WHO recommends exclusive breastfeeding for the first 6 months of life. This study aimed to examine the impact the pandemic had on breastfeeding uptake and duration, and whether intention to breastfeed is associated with longer duration of exclusive breastfeeding. METHODS: A cohort study using routinely collected, linked healthcare data from the Secure Anonymised Information Linkage databank. All women who gave birth in Wales between 2018 and 2021 recorded in the Maternal Indicators dataset were asked about intention to breastfeed. These data were linked with the National Community Child Health Births and Breastfeeding dataset to examine breastfeeding rates. RESULTS: Intention to breastfeed was associated with being 27.6 times more likely to continue to exclusively breastfeed for 6 months compared with those who did not intend to breastfeed (OR 27.6, 95% CI 24.9 to 30.7). Breastfeeding rates at 6 months were 16.6% prepandemic and 20.5% in 2020. When compared with a survey population, the initial intention to breastfeed/not breastfeed only changes for about 10% of women. CONCLUSION: Women were more likely to exclusively breastfeed for 6 months during the pandemic compared with before or after the pandemic. Arguably, interventions which enable families to spend more time with their baby such as maternal and paternal leave may help improve breastfeeding duration. The biggest predictor of breastfeeding at 6 months was intention to breastfeed. Therefore, targeted interventions during pregnancy to encourage motivation to breastfeed could improve duration of breastfeeding.

Using administrative data to evaluate national policy impacts on child and maternal health: a research framework from the Maternal and Child Health Network (MatCHNet).

Reducing health inequalities by addressing the social circumstances in which children are conceived and raised is a societal priority. Early interventions are key to improving outcomes in childhood and long-term into adulthood. Across the UK nations, there is strong political commitment to invest in the early years. National policy interventions aim to tackle health inequalities and deliver health equity for all children. Evidence to determine the effectiveness of socio-structural policies on child health outcomes is especially pressing given the current social and economic challenges facing policy-makers and families with children. As an alternative to clinical trials or evaluating local interventions, we propose a research framework that supports evaluating the impact of whole country policies on child health outcomes. Three key research challenges must be addressed to enable such evaluations and improve policy for child health: (1) policy prioritisation, (2) identification of comparable data and (3) application of robust methods.

The coding of telephone consultations in UK primary care databases: are we picking up all the calls?

OBJECTIVES: To examine the use of two coding systems used in the THIN UK primary care research database for the coding of telephone encounters between patient and healthcare professional in primary care. This is relevant to other research databases built on GP clinical systems. Consideration of telephone consultations was particularly important during the COVID-19 pandemic as remote interactions between patient and GP are more numerous than before and are likely to remain at a higher frequency. RESULTS: Telephone encounters could either be indicated by a consultation-type code or by a Read code. All three possible combinations (coded by one method, the other method and both) were in use. In 2014, 30% were coded by the consultation-type, 55% by Read codes and 15% by both. In contrast, in 2000, 77% were coded by the consultation-type, 21% by Read codes and 2% by both. This has important implications because national and regional consultation rates by GPs are often estimated from these research databases by looking only at the consultation-type codes and consequently many encounters will not be detected.

How does the local area deprivation influence life chances for children in poverty in Wales: A record linkage cohort study.

Objectives: Children growing up in poverty are less likely to achieve in school and more likely to experience mental health problems. This study examined factors in the local area that can help a child overcome the negative impact of poverty. Design: A longitudinal record linkage retrospective cohort study. Participants: This study included 159,131 children who lived in Wales and completed their age 16 exams (Key Stage 4 (KS4)) between 2009 and 2016. Free School Meal (FSM) provision was used as an indicator of household-level deprivation. Area-level deprivation was measured using the Welsh Index of Multiple Deprivation (WIMD) 2011. An encrypted unique Anonymous Linking Field was used to link the children with their health- and educational records. Outcome measures: The outcome variable 'Profile to Leave Poverty' (PLP) was constructed based on successful completion of age 16 exams, no mental health condition, no substance and alcohol misuse records in routine data. Logistic regression with stepwise model selection was used to investigate the association between local area deprivation and the outcome variable. Results: 22% of children on FSM achieved PLP compared to 54.9% of non-FSM children. FSM Children from least deprived areas were significantly more likely to achieve PLP (adjusted odds ratio (aOR) - 2.20 (1.93, 2.51)) than FSM children from most deprived areas. FSM children, living in areas with higher community safety, higher relative income, higher access to services, were more likely to achieve PLP than their peers. Conclusion: The findings indicate that community-level improvements such as increasing safety, connectivity and employment might help in child's education attainment, mental health and reduce risk taking behaviours.

Identifying opportunities for upstream evaluations relevant to child and maternal health: a UK policy-mapping review.

OBJECTIVE: Interventions to tackle the social determinants of health can improve outcomes during pregnancy and early childhood, leading to better health across the life course. Variation in content, timing and implementation of policies across the 4 UK nations allows for evaluation. We conducted a policy-mapping review (1981-2021) to identify relevant UK early years policies across the social determinants of health framework, and determine suitable candidates for evaluation using administrative data. METHODS: We used open keyword and category searches of UK and devolved Government websites, and hand searched policy reviews. Policies were rated and included using five criteria: (1) Potential for policy to affect maternal and child health outcomes; (2) Implementation variation across the UK; (3) Population reach and expected effect size; (4) Ability to identify exposed/eligible group in administrative data; (5) Potential to affect health inequalities. An expert consensus workshop determined a final shortlist. RESULTS: 336 policies and 306 strategy documents were identified. Policies were mainly excluded due to criteria 2-4, leaving 88. The consensus workshop identified three policy areas as suitable candidates for natural experiment evaluation using administrative data: pregnancy grants, early years education and childcare, and Universal Credit. CONCLUSION: Our comprehensive policy review identifies valuable opportunities to evaluate sociostructural impacts on mother and child outcomes. However, many potentially impactful policies were excluded. This may lead to the inverse evidence law, where there is least evidence for policies believed to be most effective. This could be ameliorated by better access to administrative data, staged implementation of future policies or alternative evaluation methods.

Predicting a diagnosis of ankylosing spondylitis using primary care health records-A machine learning approach.

Ankylosing spondylitis is the second most common cause of inflammatory arthritis. However, a successful diagnosis can take a decade to confirm from symptom onset (via x-rays). The aim of this study was to use machine learning methods to develop a profile of the characteristics of people who are likely to be given a diagnosis of AS in future. The Secure Anonymised Information Linkage databank was used. Patients with ankylosing spondylitis were identified using their routine data and matched with controls who had no record of a diagnosis of ankylosing spondylitis or axial spondyloarthritis. Data was analysed separately for men and women. The model was developed using feature/variable selection and principal component analysis to develop decision trees. The decision tree with the highest average F value was selected and validated with a test dataset. The model for men indicated that lower back pain, uveitis, and NSAID use under age 20 is associated with AS development. The model for women showed an older age of symptom presentation compared to men with back pain and multiple pain relief medications. The models showed good prediction (positive predictive value 70%-80%) in test data but in the general population where prevalence is very low (0.09% of the population in this dataset) the positive predictive value would be very low (0.33%-0.25%). Machine learning can be used to help profile and understand the characteristics of people who will develop AS, and in test datasets with artificially high prevalence, will perform well. However, when applied to a general population with low prevalence rates, such as that in primary care, the positive predictive value for even the best model would be 1.4%. Multiple models may be needed to narrow down the population over time to improve the predictive value and therefore reduce the time to diagnosis of ankylosing spondylitis.

Weighting of risk factors for low birth weight: a linked routine data cohort study in Wales, UK.

OBJECTIVE: Globally, 20 million children are born with a birth weight below 2500 g every year, which is considered as a low birthweight (LBW) baby. This study investigates the contribution of modifiable risk factors in a nationally representative Welsh e-cohort of children and their mothers to inform opportunities to reduce LBW prevalence. DESIGN: A longitudinal cohort study based on anonymously linked, routinely collected multiple administrative data sets. PARTICIPANTS: The cohort, (N=693 377) comprising of children born between 1 January 1998 and 31 December 2018 in Wales, was selected from the National Community Child Health Database. OUTCOME MEASURES: The risk factors associated with a binary LBW (outcome) variable were investigated with multivariable logistic regression (MLR) and decision tree (DT) models. RESULTS: The MLR model showed that non-singleton children had the highest risk of LBW (adjusted OR 21.74 (95% CI 21.09 to 22.40)), followed by pregnancy interval less than 1 year (2.92 (95% CI 2.70 to 3.15)), maternal physical and mental health conditions including diabetes (2.03 (1.81 to 2.28)), anaemia (1.26 (95% CI 1.16 to 1.36)), depression (1.58 (95% CI 1.43 to 1.75)), serious mental illness (1.46 (95% CI 1.04 to 2.05)), anxiety (1.22 (95% CI 1.08 to 1.38)) and use of antidepressant medication during pregnancy (1.92 (95% CI 1.20 to 3.07)). Additional maternal risk factors include smoking (1.80 (95% CI 1.76 to 1.84)), alcohol-related hospital admission (1.60 (95% CI 1.30 to 1.97)), substance misuse (1.35 (95% CI 1.29 to 1.41)) and evidence of domestic abuse (1.98 (95% CI 1.39 to 2.81)). Living in less deprived area has lower risk of LBW (0.70 (95% CI 0.67 to 0.72)). The most important risk factors from the DT models include maternal factors such as smoking, maternal weight, substance misuse record, maternal age along with deprivation-Welsh Index of Multiple Deprivation score, pregnancy interval and birth order of the child. CONCLUSION: Resources to reduce the prevalence of LBW should focus on improving maternal health, reducing preterm births, increasing awareness of what is a sufficient pregnancy interval, and to provide adequate support for mothers' mental health and well-being.

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.