Air pollution exposure in early life may be associated with an increased risk of bronchiolitis in children, but evidence for long-term exposures (over weeks or months) is limited. We estimated associations between fine particulate matter (PM2.5) and nitrogen dioxide (NO2) exposure during pregnancy and in the first year of life and bronchiolitis-related hospital admissions in a London birth cohort. We used a national birth cohort to identify London-resident mothers whose children were born in London from 2010 to 2013 and extracted information from birth and death registrations and maternal and child longitudinal Hospital Episode Statistics. We linked modeled PM2.5 and NO2 data to residential postcode histories during pregnancy and infancy. We applied a landmark approach with Cox proportional hazard models, adjusted for sociodemographic characteristics and housing energy efficiency, to estimate associations between time-varying monthly PM2.5 or NO2 exposure and first bronchiolitis admission. Among 415,311 children, we found inconclusive evidence overall, with suggestive signals of increased risk associated with pregnancy and exposures in the final month of infancy to PM2.5 and NO2 and time to first bronchiolitis-related hospital admission. There were modest increases in risk in the first month after birth, corresponding to prenatal exposures, for PM2.5 (adjusted Hazard ratio [HRa] = 1.07, 95% confidence interval [CI]: 0.70, 1.61 per 5 ug/m(3)) and NO2 (HRa = 1.15, 95% CI: 0.98, 1.35 per 10 ug/m(3)). We found a similar estimated increased risk in the last month of follow-up (PM2.5 HRa = 1.12, 95% CI: 0.94, 1.34; NO2 HRa = 1.31, 95% CI: 1.00, 1.71), corresponding to late infancy exposures. These findings highlight the uncertainty about critical windows of susceptibility during infancy. Future studies should examine the association between air pollution and bronchiolitis in emergency departments and primary care settings.

In the UK, administrative data alone under-ascertain pregnancy-associated deaths. The confidential enquiries into maternal deaths use a notification system, supplemented by administrative data and other sources, for the surveillance of pregnancy-associated death. The confidential enquiry method - the gold standard for ascertainment - does not routinely include population-based adjusted epidemiology to explore differences between social groups. Linkage of health and vital statistics data offers a cost-effective option for population-based analyses, including regarding inequalities, if ascertainment is adequate to minimise bias. This study compared numbers of deaths during or within one year of the end of pregnancy, in the confidential enquiries, administrative records from the Office for National Statistics in England and Wales and National Records of Scotland, and the City Birth Cohort of linked administrative and health data. There is structural non-ascertainment in England and Wales of deaths associated with pregnancies for which no birth was registered. We estimated numbers of deaths in the confidential enquiries excluding those associated with pregnancies that ended before 24 weeks' gestation. Against this more comparable denominator, administrative ascertainment was around 90%, meaning administrative under-ascertainment was not generalised across the dataset. The City Birth Cohort ascertained 80% of all-cause pregnancy-associated deaths within a year of a registerable live/stillbirth, and 60% of maternal deaths. Confidential enquiries will always be the gold standard for detailed case review and surveillance of pregnancy-associated and maternal deaths. Supplementary to this, linkage of administrative and health datasets may allow robust population-based adjusted epidemiology, to enable further insight into health inequalities.

Aim To create longitudinal postcode history datasets that allocate mothers to one postcode for each week of pregnancy and children to one postcode for each week of infancy for a study of air pollution and respiratory infections in infants. Datasets We used linked birth registrations and NHS birth notifications for all children born in London between 2010 and 2014, which constituted the spine for the Air Pollution, housing and respiratory tract Infections in Children: National Birth Cohort Study (PICNIC) study. The birth data were linked by NHS England to the Personal Demographics Service (PDS) in order to derive maternal and child postcode histories for each week of pregnancy and infancy. Challenges While the research team had extensive experience working with administrative data, including birth registrations and notifications, the postcode history data was a new resource and lacked meta-data, papers or reports from previous users. A substantial number of records were missing a move-in date, or both a move-in date and postcode, adding complexities when ascertaining an address history for study participants. Further, we encountered instances of incorrectly recorded postcodes and implausible numbers of postcodes recorded in a week. Lessons learned One half of children in this London-based cohort moved during infancy, and one third of their mothers moved during pregnancy. This highlights the importance of taking into account changes in residential address in studies examining the association between environmental exposures and health outcomes. Cleaned and validated longitudinal national address records are crucial for environmental health studies. However, they are also resource intensive, with implications for researchers and research funders.

OBJECTIVE:To estimate socio-economic (SES) inequalities in stillbirth and preterm birth rates across European countries using population-based routine data. DESIGN:Cross-sectional study of national-level perinatal health and SES indicators (mother's education/occupation or area-level deprivation). SETTING:Twenty-four countries in the Euro-Peristat network. POPULATION:Seventeen million births in 2015-2019. METHODS:Rates of stillbirth, singleton very preterm birth (VPB) and singleton moderate/late preterm birth (MLPB) were derived from routine national birth data collected with a common protocol. MAIN OUTCOME MEASURE:Percentage of excess adverse outcomes associated with SES and concentration indices. RESULTS:Median rates of adverse outcomes were higher in the lowest versus highest SES groups [Stillbirth: 4.9 (interquartile range (IQR):4.30-5.80)] versus 2.7 (IQR:2.25-3.14) per 1000 births; VPB: 1.0 (IQR: 0.87-1.12) versus 0.6 (IQR: 0.59-0.66) per 100 live births; MLPB: 5.8 (IQR: 5.27-6.40) versus 4.4 (IQR:4.13-4.65) per 100 live births. Excess adverse outcomes associated with lower SES varied greatly, particularly for stillbirth (range-3%, 51%) versus VPB (7%, 27%) and MLPB (5%, 20%). Concentration indices further highlighted varying socio-economic inequalities across countries. Median concentration indices were similar for countries with both lower and higher levels of adverse events, with median CIs of -0.12 for countries with both high and low levels of stillbirth. CONCLUSION:We identified widespread but varying inequalities between countries. These seemed to be unrelated to the rate of adverse outcomes. This suggests the need for policy strategies directly targeted to the prevention of stillbirth and preterm birth in low SES populations. Our findings demonstrate the feasibility of monitoring inequalities internationally using routine data to identify effective action.

OBJECTIVE:To explore term mortality rates in relation to rates of early-term birth (gestational ages 37 + 0 to 38 + 6 weeks), regarded as a proxy indicator of practices of elective birth by induction or caesarean. DESIGN:Ecological study using national birth data. SETTING:28 European countries. POPULATION:Births ≥ 37 weeks between 2015 and 2020. METHODS:Aggregated data on live and stillbirths by completed week of gestation was compiled from routine sources in the Euro-Peristat network. Countries were divided into three groups based on their percentages of early-term births using terciles (high, medium and low) and mortality rates were compared between groups with random-effects meta-analysis of proportions. MAIN OUTCOME MEASURES:Stillbirths (antepartum or intrapartum fetal death) and perinatal death (stillbirth or early neonatal death) per 1000 total births ≥ 37 weeks. RESULTS:Early-term birth rates ranged from 17.8% (Iceland) to 49.1% (Cyprus), with terciles being < 21%, 21%-27%, and > 27%. Post-term birth rates were low in countries with higher early-term birth rates. The pooled stillbirth rate ≥ 37 weeks was 1.28 per 1000 total births (95% CI: 1.13-1.46) in the lowest tercile and 1.05 (95% CI: 0.95-1.16) in the highest (p = 0.05), but prediction intervals were wide reflecting heterogeneity within groups. No evidence of difference was seen between perinatal mortality rates by tercile (p = 0.71). CONCLUSION:On average, the stillbirth rate was lower in countries where early-term birth rates were highest, but no difference was found in perinatal mortality rates. Heterogeneity was high within groups.

Background Exposure to ambient air pollution has been linked to increased risk of respiratory infections in children, which may require antibiotics. However, the impact of prenatal exposure to air pollution on antibiotic use in infancy remains unexplored. Methods We linked maternal postcode at delivery to modelled annual fine particulate matter ambient air pollution (PM2.5) concentration data and national birth and community pharmacy dispensing data for all singleton children born in Scotland from 2009 to 2018. The association between PM2.5 exposure and amoxicillin and phenoxymethylpenicillin dispensing for children under one year old, was estimated using logistic regression (odds ratio (OR) for ever dispensed) and negative binomial regression models (incidence rate ratio (IRR) for total dispensed). Models were adjusted for birth year, season, infant sex, maternal age, and smoking during pregnancy. Results Antenatal PM2.5 concentrations for 421,289 children ranged from 2.9 to 16.5 µg/m3. The amoxicillin dispensing rate was 450/1000 child-years during year 1 (95% CI: 448, 451); 32.4% of children were dispensed at least one dose. A unit and interquartile range (IQR) increase in PM2.5 was associated with a 4% (OR:1.04, 95% CI: 1.03-1.05) and 8% (OR:1.08, 95% CI:1.06-1.10) increase in odds of amoxicillin dispensing and a 4% (IRR: 1.04, 95% CI: 1.03-1.04) and 7% (IRR:1.07, 95% CI:1.06-1.08) increase in dispensing rates. For phenoxymethylpenicillin, the dispensing rate was 343/1000 child-years (95% CI: 384, 396), 3% of children received at least one dose. A unit increase in PM2.5 was associated with a 6% increase in odds of dispensing (OR:1.06, 95% CI:1.04-1.08), and an IQR increase with a 13% increase (OR:1.13, 95% CI:1.08-1.17). Similarly, negative binomial regression showed a 9% (IRR:1.09, 95%CI:1.07-1.11) and 18% (IRR:1.18, 95%CI:1.14-1.23) increase with unit and IQR increases in PM2.5. Conclusion Antenatal exposure to PM2.5 was associated with an increased likelihood and frequency of amoxicillin and phenoxymethylpenicillin dispensing during infancy, reflecting its potential impact on early life respiratory health. Targeted interventions to improve air quality during pregnancy may reduce the burden of antibiotic use.

Introduction:Environmental exposures are known to affect the health and well-being of populations throughout the life course. Children are particularly susceptible to environmental impacts on educational and health outcomes as they spend more time in their local environments compared to adults. In England, no national, longitudinal dataset linking information about the physical and social environment in and around homes and schools to children's health and education outcomes currently exists. This limits our understanding of how environments might impact the health and well-being of children as they grow up. Objective:To establish the Kids' Environment and Health Cohort, a research-ready, de-identified and annually updated national birth cohort of all children born in England from 2006 onwards. Methods:The Kids' Environment and Health Cohort will link birth and mortality records, health and educational attainment datasets, to maternal health (up to 12 months prior to their child's birth), and environmental data for all children born in England from 2006 - approximately 11 million children at first build. A subset of children born between 2010 and 2012, and between 2020 and 2022 will be linked to their mothers' 2011 or 2021 Census records, respectively. The cohort database will be held in, and accessed via, a trusted research environment (TRE) at the Office for National Statistics (ONS). All geographical identifiers in the cohort, allowing for linkage to further environmental data, will be securely held by the ONS, separately to the main cohort, and will be encrypted before being shared with researchers. Conclusion:The Kids' Environment and Health Cohort will, for the first time, link administrative health and education data to longitudinal environmental exposures for children at national level in England. It will serve as a data resource to support research about the health and well-being of children via improved home and school environments.

Objectives We aim to establish the Kids’ Environment and Health Cohort, a research-ready, de-identified, longitudinal birth cohort of approximately 11 million children born in England (2006-2022), updated annually. The cohort will be used to investigate how environmental factors in and around children’s homes and schools affect their health and educational outcomes. Method The Kids’ Environment and Health Cohort will link vital statistics, census, health, education, and environmental data, via unique property identifiers from longitudinal health service address records for children, and their mothers during pregnancy. Environmental exposure data in/around schools will be linked via education records. The Office for National Statistics (ONS) is developing Phase 1, which includes birth and death registrations (2006-2022), linked deterministically using a combination of NHS numbers and personal information. Cohort children born within two years of the 2011 or 2021 Census will be linked to their mother’s Census record. Environmental data on air pollution, greenspace proximity, temperature, and building characteristics will be linked to all cohort children via birth addresses. The cohort will be held and accessed in a secure research environment at the ONS, with encrypted geographical identifiers stored separately to ensure privacy. Results We have received ethics approval and agreed the legal bases for establishing the Kids’ Environment and Health Cohort. The linkage of death registrations to birth registrations is complete, and the ONS team were able to match >97% of registered deaths to birth records of cohort children with both precision and recall estimated at >99%. Researchers will be able to request access to the Phase 1 data via ONS by March 2026. Conclusion The Kid’s Environment and Health Cohort will support policy-relevant research in exploring associations between environmental factors and children's health and educational outcomes and assessing the effectiveness of policy interventions. It will also support interdisciplinary collaboration, guiding evidence-based decision-making for environmental, planning, and public health policies to promote children’s health and well-being.

BACKGROUND:International comparisons of population birth data provide essential benchmarks for evaluating perinatal health policies. OBJECTIVES:This study aimed to describe routine national data sources in Europe by their ability to provide core perinatal health indicators. METHODS:The Euro-Peristat Network collected routine national data on a recommended set of core indicators from 2015 to 2021 using a federated protocol based on a common data model with 16 data items. Data providers completed an online questionnaire to describe the sources used in each country. We classified countries by the number of data items they provided (all 16, 15-14, < 14). RESULTS:A total of 29 out of the 31 countries that provided data responded to the survey. Routine data sources included birth certificates (15 countries), electronic medical records (EMR) from delivery hospitalisations (16 countries), direct entry by health providers (9 countries), EMR from other care providers (7 countries) and Hospital Discharge Summaries (7 countries). Completeness of population coverage was at least 98%, with 17 countries reporting 100%. These databases most often included mothers giving birth in the national territory, regardless of nationality or place of residence (24 countries), whereas others register births to residents only. In 20 countries, routine sources were linked, including linkage between birth and death certificates (16 countries). Countries providing all 16 items (n = 8) were more likely to use EMRs from delivery hospitalisations (100%) compared to 50% and 11% in countries with 15-14 items (n = 12) and < 14 items (n = 9), respectively. Linkage was also more common in these countries (100%) versus 75% and 56%, respectively. Other data source characteristics did not differ by the ability to provide data on core perinatal indicators. CONCLUSIONS:There are wide differences between countries in the data sources used to construct perinatal health indicators in Europe. Countries using EMR linking to other sources had the best data availability.

Abstract Background A third of children born in England have at least one parent born outside the United Kingdom (UK), yet family migration history is infrequently studied as a social determinant of child health. We describe rates of hospital admissions in children aged up to 5 years by parental migration and socioeconomic group. Methods Birth registrations linked to Hospital Episode Statistics were used to derive a cohort of 4,174,596 children born in state-funded hospitals in England between 2008 and 2014, with follow-up until age 5 years. We looked at eight maternal regions of birth, maternal country of birth for the 6 most populous groups and parental migration status for the mother and second parent (UK-born/non-UK-born). We used Index of Multiple Deprivation (IMD) quintiles to indicate socioeconomic deprivation. We fitted negative binomial/Poisson regression models to model associations between parental migration groups and the risk of hospital admissions, including interactions with IMD group. Results Overall, children whose parents were both born abroad had lower emergency admission rates than children with parents both born in the UK. Children of UK-born (73.6% of the cohort) mothers had the highest rates of emergency admissions (171.6 per 1000 child-years, 95% confidence interval (CI) 171.4–171.9), followed by South Asia-born mothers (155.9 per 1000, 95% CI 155.1–156.7). The high rates estimated in the South Asia group were driven by children of women born in Pakistan (186.8 per 1000, 95% CI 185.4–188.2). A socioeconomic gradient in emergency admissions was present across all maternal regions of birth groups, but most pronounced among children of UK-born mothers (incidence rate ratio 1.43, 95% CI 1.42–1.44, high vs. low IMD group). Patterns of planned admissions followed a similar socioeconomic gradient and were highest among children with mothers born in Middle East and North Africa, and South Asia. Conclusions Overall, we found the highest emergency admission rates among children of UK-born parents from the most deprived backgrounds. However, patterns differed when decomposing maternal place of birth and admission reason, highlighting the importance of a nuanced approach to research on migration and health.

Introduction Environmental exposures are known to affect the health and well-being of populations throughout the life course. Children are particularly susceptible to environmental impacts on educational and health outcomes as they spend more time in their local environments compared to adults. In England, no national, longitudinal dataset linking information about the physical and social environment in and around homes and schools to children's health and education outcomes currently exists. This limits our understanding of how environments might impact the health and well-being of children as they grow up. Objective To establish the Kids' Environment and Health Cohort, a research-ready, de-identified and annually updated national birth cohort of all children born in England from 2006 onwards. Methods The Kids' Environment and Health Cohort will link birth and mortality records, health and educational attainment datasets, to maternal health (up to 12 months prior to their child's birth), and environmental data for all children born in England from 2006 -- approximately 11 million children at first build. A subset of children born between 2010 and 2012, and between 2020 and 2022 will be linked to their mothers' 2011 or 2021 Census records, respectively. The cohort database will be held in, and accessed via, a trusted research environment (TRE) at the Office for National Statistics (ONS). All geographical identifiers in the cohort, allowing for linkage to further environmental data, will be securely held by the ONS, separately to the main cohort, and will be encrypted before being shared with researchers. Conclusion The Kids' Environment and Health Cohort will, for the first time, link administrative health and education data to longitudinal environmental exposures for children at national level in England. It will serve as a data resource to support research about the health and well-being of children via improved home and school environments.

OBJECTIVE:To assess associations between housing characteristics and risk of hospital admissions related to falls on/from stairs in children, to help inform prevention measures. STUDY DESIGN:An existing dataset of birth records linked to hospital admissions up to age 5 for a cohort of 3 925 737 children born in England between 2008 and 2014, was linked to postcode-level housing data from Energy Performance Certificates. Association between housing construction age, tenure (eg, owner occupied), and built form and risk of stair fall-related hospital admissions was estimated using Poisson regression. We stratified by age (<1 and 1-4 years), and adjusted for geographic region, Index of Multiple Deprivation, and maternal age. RESULTS:The incidence was higher in both age strata for children in neighborhoods with homes built before 1900 compared with homes built in 2003 or later (incidence rate ratio [IRR], 1.40; 95% CI, 1.10-1.77 [age <1 year], 1.20; 95% CI, 1.05-1.36 [age 1-4 years]). For those aged 1-4 years, the incidence was higher for those in neighborhoods with housing built between 1900 and 1929, compared with 2003 or later (IRR, 1.26; 95% CI, 1.13-1.41), or with predominantly social-rented homes compared with owner occupied (IRR, 1.21; 95% CI, 1.13-1.29). Neighborhoods with predominantly houses compared with flats had higher incidence (IRR, 1.24; 95% CI, 1.08-1.42 [<1 year] and IRR 1.16; 95% CI, 1.08-1.25 [1-4 years]). CONCLUSIONS:Changes in building regulations may explain the lower fall incidence in newer homes compared with older homes. Fall prevention campaigns should consider targeting neighborhoods with older or social-rented housing. Future analyses would benefit from data linkage to individual homes, as opposed to local area level.

Objective and ApproachThe environment in and around children’s homes and schools can influence their health and educational outcomes. Better understanding of how these potentially modifiable environmental risk factors can affect children is crucial in enabling the creation of healthier and more equitable places. We aim to establish the Kids’ Environment and Health Cohort, a research-ready, de-identified, national longitudinal birth cohort of approximately 11 million children born in England from 2006 to 2023, updated annually. The cohort will link vital statistics, census, health, education, and environmental data, via unique property identifiers from longitudinal health service address records for children and their mothers during pregnancy. Data on environmental exposures around schools will be linked to the cohort via education records. The cohort will be held and accessed in a secure research environment at the Office for National Statistics (ONS). All geographical identifiers will be encrypted and stored separately from the main cohort by the ONS to ensure privacy and security. ResultsWe have received ethics approval and have agreed the legal bases for establishing the cohort. We are now setting up data sharing agreements with each data provider. Delivery of the cohort is scheduled for late 2025. ConclusionThe Kid’s Environment and Health Cohort will support policy-relevant research in exploring associations between environmental factors and children's health and educational outcomes, and assessing the effectiveness of policy interventions. It will also support interdisciplinary collaboration, guiding evidence-based decision-making for environmental, planning, and public health policies aimed at promoting children’s health and well-being.

Introduction & Background Evidence is mounting that children’s physical environment (e.g. in and around the home, school, and neighbourhood) is critical for their long-term health and education. Early life exposure to factors such as indoor and outdoor air pollution, or a lack of access to greenspaces are associated with the development of long-term health conditions such as asthma or mental health problems. Local and central government in England are implementing numerous policies to improve air quality and housing, and mitigate climate change. Further, England has seen large scale changes to local service provision (including childcare and libraries) due to austerity policies and the COVID-19 pandemic. Currently, there is no national, linked data resource for England that allows research into how the local environment impacts children’s health and education. Objectives & Approach The Kids’ Environment and Health Cohort will be a new, linked national data resource for England currently being developing by researchers from UCL, London School of Hygiene and Tropical Medicine, London School of Economics and Political Science, Brock University, and City, University of London in collaboration with the Office for National Statistics (ONS), and funded by Administrative Data Research-UK (ADR-UK). The Kids’ Environment and Health Cohort will be a de-identified and annually updated national birth cohort of all children born in England from 2006 onwards – around 10.5 million children until 2023. The cohort will be constructed using linked administrative data from vital registration (live and stillbirth, and death registration), Census (housing and socio-economic indicators), health (hospital contacts, mental health referrals, and community dispensing data), and education (key stage results, special educational needs, absenteeism). Environmental exposure data can be securely linked to the Cohort via longitudinal residential unique property reference numbers (UPRNs) and postcodes from the Personal Demographic Service, and school location from education records. Relevance to Digital Footprints The Kids’ Environment and Health Cohort will, for the first time, link health, education, Census and environmental data at national level in England. It will allow researchers to integrate data on local environments, including physical characteristics (such as temperature, building energy efficiency, or greenspace access) or the social environment (including proximity to food outlets, or services like libraries) with individual level data on health and education outcomes in children. This will be done using the ONS’s 5 safes framework, ensuring highest standards of data security and confidentiality. Results The Kids’ Environment and Health Cohort will be constructed using administrative datasets, including national linked vital statistics, health, education and Census data from multiple data providers (ONS, NHS England and Department for Education), combined with small-area level environmental data for England. Together, these datasets allow detailed analyses of the impact of environmental exposures on health and education outcomes in children, with robust confounder adjustment. The Kids’ Environment and Health Cohort will be made available in a de-identified format in the ONS Secure Research Service (SRS). Conclusions & Implications The Kids’ Environment and Health Cohort will provide researchers secure access to a national data resource integrating environmental and administrative health and education data, for child public health research.

OBJECTIVE To examine the association between gestational age at birth and hospital admissions to age 10 years and how admission rates change throughout childhood. DESIGN Population based, record linkage, cohort study in England. SETTING NHS hospitals in England, United Kingdom. PARTICIPANTS 1 018 136 live, singleton births in NHS hospitals in England between January 2005 and December 2006. MAIN OUTCOME MEASURES Primary outcome was all inpatient hospital admissions from birth to age 10, death, or study end (March 2015); secondary outcome was the main cause of admission, which was defined as the World Health Organization's first international classification of diseases, version 10 (ICD-10) code within each hospital admission record. RESULTS 1 315 338 admissions occurred between 1 January 2005 and 31 March 2015, and 831 729 (63%) were emergency admissions. 525 039 (52%) of 1 018 136 children were admitted to hospital at least once during the study period. Hospital admissions during childhood were strongly associated with gestational age at birth (<28, 28-29, 30-31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, and 42 weeks). In comparison with children born at full term (40 weeks' gestation), those born extremely preterm (<28 weeks) had the highest rate of hospital admission throughout childhood (adjusted rate ratio 4.92, 95% confidence interval 4.58 to 5.30). Even children born at 38 weeks had a higher rate of hospital admission throughout childhood (1.19, 1.16 to 1.22). The association between gestational age and hospital admission decreased with increasing age (interaction P<0.001). Children born earlier than 28 weeks had an adjusted rate ratio of 6.34 (95% confidence interval 5.80 to 6.85) at age less than 1 year, declining to 3.28 (2.82 to 3.82) at ages 7-10, in comparison with those born full term; whereas in children born at 38 weeks, the adjusted rate ratios were 1.29 (1.27 to 1.31) and 1.16 (1.13 to 1.19), during infancy and ages 7-10, respectively. Infection was the main cause of excess hospital admissions at all ages, but particularly during infancy. Respiratory and gastrointestinal conditions also accounted for a large proportion of admissions during the first two years of life. CONCLUSIONS The association between gestational age and hospital admission rates decreased with age, but an excess risk remained throughout childhood, even among children born at 38 and 39 weeks of gestation. Strategies aimed at the prevention and management of childhood infections should target children born preterm and those born a few weeks early.

ObjectivesTo compare neonatal mortality in English hospitals by time of day and day of the week according to care pathway. DesignRetrospective cohort linking birth registration, birth notification and hospital episode data. SettingNational Health Service (NHS) hospitals in England. Participants6 054 536 liveborn singleton births from 2005 to 2014 in NHS maternity units in England. Main outcome measuresNeonatal mortality. ResultsAfter adjustment for confounders, there was no significant difference in the odds of neonatal mortality attributed to asphyxia, anoxia or trauma outside of working hours compared with working hours for spontaneous births or instrumental births. Stratification of emergency caesareans by onset of labour showed no difference in mortality by birth timing for emergency caesareans with spontaneous or induced onset of labour. Higher odds of neonatal mortality attributed to asphyxia, anoxia or trauma out of hours for emergency caesareans without labour translated to a small absolute difference in mortality risk. ConclusionsThe apparent 'weekend effect' may result from deaths among the relatively small numbers of babies who were coded as born by emergency caesarean section without labour outside normal working hours. Further research should investigate the potential contribution of care-seeking and community-based factors as well as the adequacy of staffing for managing these relatively unusual emergencies.

Preterm birth (<37 weeks' gestation) is a risk factor for poor educational outcomes. A dose-response effect of earlier gestational age at birth on poor primary school attainment has been observed, but evidence for secondary school attainment is limited and focused predominantly on the very preterm (<32 weeks) population. We examined the association between gestational age at birth and academic attainment at the end of primary and secondary schooling in England. Data for children born in England from 2000-2001 were drawn from the population-based UK Millennium Cohort Study. Information about the child's birth, sociodemographic factors and health was collected from parents. Attainment on national tests at the end of primary (age 11) and secondary school (age 16) was derived from linked education records. Data on attainment in primary school was available for 6,950 pupils and that of secondary school was available for 7,131 pupils. Adjusted relative risks (aRRs) for these outcomes were estimated at each stage separately using modified Poisson regression. At the end of primary school, 17.7% of children had not achieved the expected level in both English and Mathematics and this proportion increased with increasing prematurity. Compared to full term (39-41 weeks) children, the strongest associations were among children born moderately (32-33 weeks; aRR = 2.13 (95% CI 1.44-3.13)) and very preterm (aRR = 2.06 (95% CI 1.46-2.92)). Children born late preterm (34-36 weeks) and early term (37-38 weeks) were also at higher risk with aRR = 1.18 (95% CI 0.94-1.49) and aRR = 1.21 (95% CI 1.05-1.38), respectively. At the end of secondary school, 45.2% had not passed at least five General Certificate of Secondary Education examinations including English and Mathematics. Following adjustment, only children born very preterm were at significantly higher risk (aRR = 1.26 (95% CI 1.03-1.54)). All children born before full term are at risk of poorer attainment during primary school compared with term-born children, but only children born very preterm remain at risk at the end of secondary schooling. Children born very preterm may require additional educational support throughout compulsory schooling.

BackgroundThere have been no population-based studies of SARS-CoV-2 testing, PCR-confirmed infections and COVID-19-related hospital admissions across the full paediatric age range. We examine the epidemiology of SARS-CoV-2 in children and young people (CYP) aged <23 years.MethodsWe used a birth cohort of all children born in Scotland since 1997, constructed via linkage between vital statistics, hospital records and SARS-CoV-2 surveillance data. We calculated risks of tests and PCR-confirmed infections per 1000 CYP-years between August and December 2020, and COVID-19-related hospital admissions per 100 000 CYP-years between February and December 2020. We used Poisson and Cox proportional hazards regression models to determine risk factors.ResultsAmong the 1 226 855 CYP in the cohort, there were 378 402 tests (a rate of 770.8/1000 CYP-years (95% CI 768.4 to 773.3)), 19 005 PCR-confirmed infections (179.4/1000 CYP-years (176.9 to 182.0)) and 346 admissions (29.4/100 000 CYP-years (26.3 to 32.8)). Infants had the highest COVID-19-related admission rates. The presence of chronic conditions, particularly multiple types of conditions, was strongly associated with COVID-19-related admissions across all ages. Overall, 49% of admitted CYP had at least one chronic condition recorded.ConclusionsInfants and CYP with chronic conditions are at highest risk of admission with COVID-19. Half of admitted CYP had chronic conditions. Studies examining COVID-19 vaccine effectiveness among children with chronic conditions and whether maternal vaccine during pregnancy prevents COVID-19 admissions in infants are urgently needed.

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The SARS-CoV-2 pandemic exposed multiple shortcomings in national and international capacity to respond to an outbreak of infectious disease. It is essential to learn from these deficiencies to prepare for future epidemics. One major gap is the limited availability of timely and comprehensive population-based routine data on the impact of COVID-19 on pregnant women and babies. As part of the Horizon 2020 Population Health Information Research Infrastructure (PHIRI) project on the use of population data for COVID-19 surveillance, the Euro-Peristat Research Network investigated the extent to which routine information systems could be used to assess the effects of the pandemic by constructing indicators of maternal and child health and COVID-19 infection. The Euro-Peristat network brings together researchers and statisticians from 31 countries to monitor population indicators of perinatal health in Europe, and periodically compiles data on a set of ten core and 20 recommended indicators.1 At the onset of the pandemic, single-centre hospital studies and rapidly mounted population-based studies provided vital information to guide clinical care and policy by documenting the greater risks of admission to intensive care and of pregnancy complications, such as preterm delivery and pre-eclampsia, among pregnant women with COVID-19.2 They also showed generally good outcomes for most infected pregnant women and babies.2 Systematic reviews of this growing body of work have provided more robust guidance, but are limited in their ability to capture key population outcomes such as stillbirth and neonatal death, which occur too infrequently to be included as outcomes in most single- and even multi-centre studies. The most recent update of a living systematic review, based on 192 studies of pregnant women with COVID-19, with 97 studies investigating perinatal outcomes, included only 72 stillbirths and 41 neonatal deaths.3 Research has also accumulated on the effects of the pandemic on the general population of pregnant women. These indirect effects may result from changes in health care access or quality, through health-system failures, policies to reorganise care, such as moving to telemedicine consultations, or women's reluctance to seek care for fear of infection, as well as from economic adversity and increased stress. A recent systematic review provides a valuable overview of 40 studies on the indirect effects of the pandemic on multiple maternal and perinatal outcomes, but also reveals the lack of research using population birth data.4 For example, some very small studies reported unexpected decreases in preterm birth rates during the first lockdown in March and April 2020.5, 6 Ten further studies on preterm birth in high-income countries were identified by the review, yielding an overall pooled effect in favour of a decrease in preterm birth, but with substantial heterogeneity.4 However, only three studies were population-based regional or national studies. Only one of the eight studies on stillbirth included in the review was population based. As pregnant women and newborns are generally in good health, studies to monitor their health require large population-based samples. Further, trend data from previous years are required for reliable assessments of change because seasonal effects, secular trends in birth rates and pandemic-related changes in fertility, as observed during CoV-SARS-2,7 can impact on perinatal outcomes. A population approach is also essential because single- and multi-centre studies may not detect systemic changes that result from disruption to the organisation of healthcare services. They may also be unreliable if population movements affect their activity levels and patient case mix. For instance, 17% of residents of the Parisian region moved to other parts of France during the first lockdown.8 Finally, comprehensive coverage, including disadvantaged populations, is needed because perinatal outcomes are sensitive to changes in socio-economic circumstances, and social disadvantage increases vulnerability to infection and its consequences.2 To assess the availability of population birth data in Europe, the Euro-Peristat network developed an online survey for participating countries asking about the availability of preliminary and verified finalised birth data for constructing core perinatal health indicators, including stillbirth, neonatal mortality, preterm birth, low birthweight and caesarean rates for births from (i) January–April 2020 and (ii) all of 2020. We also enquired about whether codes had been routinely added to birth data to indicate COVID-19 infection. The initial survey was completed in June–July 2020 and updated in November–December 2020 to include information on linkage and disruptions to reporting systems after a discussion of preliminary results by the country teams. Twenty-seven countries and the constituent nations of the UK provided data (Table S1). Some countries used several data sources, including birth and death certificates, birth notification systems, or stillbirth and abortion registers, to generate the full set of core indicators. In these cases, we asked for information about the availability of data to generate stillbirth, preterm birth, low birthweight and caesarean rates, as they are often available earlier than data on neonatal or infant deaths. Figure 1 presents the estimated timing for accessing preliminary and final population data on births in 2020 and illustrates the considerable heterogeneity between countries. About half of the countries had preliminary data on the first lockdown period by November of 2020, with half having the final data by May 2021. Final data for the year 2020 started to become available in March 2021, with half of the countries having data available by September 2021. Figures distinguishing between sources that rely solely on civil registration data and those using medical registers or hospital discharge databases show that, especially for preliminary data, medical registers provided more rapid access. Some countries reported disruptions or changes of data procedures related to the pandemic that may impact on quality or completeness, particularly for preliminary data. These were mainly as a result of personnel being repurposed for other data or clinical duties, resulting in backlogs in processing, mentioned by eight countries. Several countries mentioned delays to birth registration. For instance, in the UK the civil registration of live births was paused for several months during the first lockdown. It was then continued in Scotland and Northern Ireland, but varied locally in England and Wales, during subsequent lockdowns. Other changes to procedures, such as in France, where the hospital budgets for 2020 and 2021 will not be determined by activity measures from hospital discharge data, may affect the coding of complications or outcomes. Specific codes indicating COVID-19 infection are necessary for monitoring outcomes associated with infection, but also for exploring indirect effects where and when the prevalence of infection is high. Only two of the 11 countries that use civil registration sources have the option of adding COVID-19 codes from the tenth revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) to birth data, as shown in Table 1. In contrast, 17 out of 19 countries that use sources based on clinical or medical databases reported that this code is already or will be added to birth data. In some countries, there is a potential to link COVID-19 codes to birth data, but this is not currently planned. Overall, 23% of the countries cannot add COVID-19 codes to routine birth data. This overview focused on the availability and timeliness of key data items, but other questions remain. For instance, it is important to evaluate whether disruptions to data procedures affected the quality or completeness of the data. Verifying the coding of key variables or trends over time in numbers of births by hospital or region could reveal system dysfunctions; these quantitative assessments could be complemented by qualitative studies. Further research is also needed on the quality and reliability of COVID-19 codes. At the onset of the pandemic, the World Health Organization (WHO) issued guidelines for coding confirmed COVID-19 infection using ICD codes; these were updated to include guidelines for suspected infection and specific guidelines were developed for mothers and babies. Studies are beginning to address the issue of coding quality as applied generally, finding good results overall,9 but this is likely to differ across countries and hospitals and has not been assessed for pregnant women and babies. Unique questions exist for the mother–child dyad: for instance, although it may be easy to identify babies with a symptomatic mother testing positive for COVID-19 at delivery, identifying children born to mothers with a resolved or asymptomatic COVID-19 infection during pregnancy is more challenging. The ability to link hospital testing strategies will be crucial for the interpretation of positivity rates as it is estimated that about three-quarters of infections at delivery are asymptomatic.3 A final question concerns the data in population data sources beyond the core perinatal health outcomes discussed here. The Euro-Peristat indicator set has a limited number of health service measures, in part because of the complexity of defining comparable indicators between health systems. In line with broader WHO initiatives to develop population health indicators in the context of COVID-19,10 countries should assess whether they are able to report on population health service indicators to enable rapid feedback on problems with access or quality of care that can affect women and babies during a pandemic. This overview draws attention to the delays in the availability of population birth data; in general, finalised data from the first lockdown period were not available until the spring of the following year. However, there was marked heterogeneity, suggesting that workable solutions to producing more rapid data already exist. Some of the variation was linked to the types of data systems, with a generally longer lag for preliminary information when countries derive birth data from civil registration rather than from clinical databases or hospital discharge systems. This illustrates the importance of using these medical databases for reporting on perinatal indicators at a population level, if this is the case. Many countries relied on linkage to obtain information on COVID-19. Linkage of routine data, underused in many countries, emerges as a central component of a strategy to improve the pandemic readiness of population birth data. It is being exploited in some countries to make further investigations possible,11 and ambitious initiatives to provide longitudinal maternal–newborn databases for routine surveillance could provide a road map for the future.12 Finally, a future plan should include procedures for the rapid international synthesis of data. Compiling data at a European level, a central objective of the PHIRI project, permits insight into the generalisability of national trends and generates knowledge to inform European policy. This overview of information systems in Europe, highlighting the limits of routine birth data, calls for urgent attention to population monitoring capacity to improve preparedness for a future pandemic. The SARS-CoV-2 virus has been most deadly for older people and adults with respiratory and other comorbidities. In contrast, a future pandemic could be more dangerous for pregnant women and newborns who remain uniquely vulnerable to major adverse effects from viral infections and are at risk when health systems are disrupted because of their non-deferrable need for health services during pregnancy, childbirth and the postpartum period. None declared. Completed disclosure of interests form available to view online as supporting information. All members of the Euro-Peristat network, listed as a group author, participated in the design of the study, provided data for their country, assisted with interpretation of the data and revision of the article and approved the final version. Several online meetings were held to discuss this study. From the Institut national de la santé et de la recherche médicale (Inserm) team, MD and MP designed the data collection instrument and carried out the data analyses. JZ drafted the article. Not required. The research leading to these results received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 101018317, the Population Health Information Research Infrastructure (PHIRI). Austria - Gerald Haidinger (The Medical University of Vienna, Department of Epidemiology, Centre of Public Health, Vienna), Jeannette Klimont (Statistics Austria, Vienna); Belgium - Sophie Alexander, Wei-Hong Zhang (Perinatal Epidemiology and Reproductive Health Unit, CR2, School of Public Health, ULB, Brussels), Gisèle Vandervelpen (Statbel, Brussels), Marie Delnord (Sciensano, Belgian Institute for Health, Brussels); Bulgaria - Rumyana Kolarova (Directorate Budget and Finance, Ministry of Health, Sofia), Evelin Yordanova (Statistics of health and justice. National Stastitical Institute, Sofia); Croatia - Urelija Rodin, Željka Draušnik (Croatian National Institute of Public Health, Zagreb), Boris Filipovic-Grcic (Clinical Hospital Center Zagreb, School of Medicine University of Zagreb, Zagreb); Cyprus - Theopisti Kyprianou, Vasos Scoutellas (Health Monitoring Unit, Ministry of Health, Nicosia); Czech Republic - Petr Velebil (Institute for the Care of Mother and Child, Prague); Denmark - Laust Hvas Mortensen (Department of Public Health, University of Copenhagen, Copenhagen and Denmark Statistics, Copenhagen); Estonia - Luule Sakkeus, Liili Abuladze (Estonian Institute for Population Studies, Tallinn University, Tallinn); Finland - Mika Gissler (THL Finnish Institute for Health and Welfare, Information Services Department, Helsinki and Karolinska Institute, Department of Neurobiology, Care Sciences and Society, Stockholm); France - Béatrice Blondel, Catherine Deneux-Tharaux, Mélanie Durox, Marianne Philibert, Jennifer Zeitlin (Université de Paris, CRESS, Obstetrical Perinatal and Pediatric Epidemiology Research Team, EPOPé, INSERM, INREA,Paris), Jeanne Fresson (Population Health Office, Directorate of Research, Study, Evaluation and Statistics (DREES), Health Ministry, Paris); Germany - Guenther Heller (Institute for Quality Assurance and Transparency in Healthcare IQTIG, Berlin), Bjoern Misselwitz (Institute of Quality Assurance Hesse, Eschborn); Greece - Aris Antsaklis (IASO Maternity Hospital, Department of Fetal Maternal and Perinatal Medicine, University of Athens, Athens); Hungary - István Berbik (MedCongress Ltd., Budapest); Iceland - Helga Sól Ólafsdóttir (Department of Obstetrics and Gynaecology, Landspitali University Hospital, Reykjavik); Ireland - Karen Kearns (Healthcare Pricing Office, National Finance Division, HSE, Dublin), Izabela Sikora (The National Perinatal Reporting System, Health Pricing Office, Dublin); Italy - Marina Cuttini (Clinical Care and Management Innovation Research Area, Bambino Gesù Pediatric Hospital, Rome), Marzia Loghi (Directorate for Social Statistics and Welfare, Italian Statistical Institute (ISTAT), Rome), Serena Donati (National Centre for Epidemiology, Surveillance, and Health Promotion, National Institute of Health, Rome), Rosalia Boldrini (General Directorate for the Health Information and Statistical System, Italian Ministry of Health, Rome); Latvia - Janis Misins, Irisa Zile (The Centre for Disease Prevention and Control of Latvia, Riga; Lithuania - Jelena Isakova (Institute of Hygiene, Health Information Centre, Health Statistics Department, Vilnius); Luxembourg - Aline Touvrey-Lecomte, Audrey Billy, Sophie Couffignal (Department of Population Health, Luxembourg Institute of Health, Luxembourg), Guy Weber (Department of Epidemiology and Statistics, Directorate of Health, Luxembourg); Malta - Miriam Gatt (Directorate for Health Information and Research, National Obstetric Information Systems (NOIS) Register, Tal-Pietà); Netherlands - Jan Nijhuis (Department of Obstetrics & Gynaecology, Maastricht University Medical Centre, MUMC+, Maastricht), Lisa Broeders (The Netherlands Perinatal Registry (Perined), Utrecht), PW Achterberg (National Institute for Public Health and the Environment, Bilthoven), Ashna Hindori-Mohangoo (Foundation for Perinatal Interventions and Research in Suriname (PeriSur), Paramaribo, Suriname, Tulane University School of Public Health and Tropical Medicine, New Orleans, USA); Norway - Kari Klungsoyr (Division of Mental and Physical Health, Norwegian Institute of Public Health, Bergen, Norway and Department of Global Public Health and Primary Care, University of Bergen), Rupali Akerkar, Hilde Engjom (Health Registry Research and Development, Norwegian Institute of Public Health, Bergen); Poland - Katarzyna Szamotulska, Ewa Mierzejewska (Department of Epidemiology and Biostatistics, National Research Institute of Mother and Child, Warsaw); Portugal - Henrique Barros (University of Porto Medical School, Department of Public Health, Forensic Sciences and Medical Education, Porto), Carina Rodrigues (Institute of Public Health of the University of Porto, Porto); Romania - Mihai Horga (East European Institute for Reproductive Health, Târgu Mureş), Vlad Tica (East European Institute for Reproductive Health, Faculty of Medicine, University "Ovidius", Constanţa); Lucian Puscasiu (East European Institute for Reproductive Health, University of Medicine, Pharmacy, Science and Technology "George Emil Palade", Târgu Mureş), Mihaela-Alexandra Budianu (Obstetrics and Gynaecology Clinic, University of Medicine and Pharmacy, Târgu Mureş), Alexandra Cucu (National Centre for Health Promotion and Evaluation, National Institute of Public Health, Târgu Mureş), Cristian Calomfirescu (National Center for Statistics and Informatics in Public Health, National Institute of Public Health, Târgu Mureş); Slovakia - Jan Cap (National Health Information Center, Bratislava); Slovenia - Natasa Tul Mandic (Gynaecological and Maternity Hospital Postojna, Postojna), Ivan Verdenik (University Medical Centre, Department of Obstetrics & Gynecology, Ljubljana); Spain - Oscar Zurriaga (Public Health General Directorate, Valencia Regional Public Health Authority and Public Health and Preventive Medicine Department, University of Valencia and Centre for Network Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid), Adela Recio Alcaide (National Institute for Statistics (INE), Madrid), Mireia Jané (Public Health Surveillance Direction, Catalan Public Health Agency Generalitat de Catalunya, Barcelona), Maria José Vidal (Public Health Surveillance Direction, Catalan Public Health Agency Generalitat de Catalunya, Barcelona); Sweden - Karin Källén, Anastasia Nyman (The National Board of Health and Welfare, Department of Evaluation and Analysis, Epidemiology and Methodological Support Unit, Stockholm); Switzerland - Tonia Rihs (Federal Statistical Office FSO, Neuchâtel); United Kingdom - Alison Macfarlane (Centre for Maternal and Child Health Research, School of Health Sciences, City University of London, London), Rachael Wood, Kirsten Monteath (Public Health Scotland, Edinburgh and University of Edinburgh, Edinburgh), Lucy Smith (Department of Health Sciences, College of Life Sciences, University of Leicester, Leicester), Siobhán Morgan, Jennifer Hillen (Hospital Information Branch, Department of Health, Stormont Estate, Belfast). Data are provided in Table S1. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.