Association of maternal risk factors with infant maltreatment: an administrative data cohort study

Objective: We aimed to evaluate the risk of infant maltreatment associated with commonly used criteria for home visiting programmes: young maternal age, maternal adversity (homelessness, substance abuse, intimate partner violence), newcomer status and mental health concerns in Ontario, Canada. Design: This retrospective cohort study included infants born in hospital in Ontario from 1 April 2005 to 31 March 2017 captured in linked health administrative and demographic databases. Infants were followed from newborn hospitalisation until 1 year of age for child maltreatment captured in healthcare or death records. The association between type and number of maternal risk factors, and maltreatment, was analysed using multivariable logistic regression modelling, controlling for infant characteristics and material deprivation. Further modelling explored the association of each year of maternal age with maltreatment. Results: Of 989 586 infants, 434 (0.04%) had recorded maltreatment. Maternal age <22 years conferred higher risk of infant maltreatment (adjusted OR (aOR) 5.5, 95% CI 4.5 to 6.8) compared with age ≥22 years. Maternal mental health diagnoses (aOR 2.0, 95% CI 1.6 to 2.5) were also associated with maltreatment, while refugee status appeared protective (aOR 0.6, 95% CI 0.4 to 1.0). The odds of maltreatment increased with higher numbers of maternal risk factors. Maternal age was associated with maltreatment until age 28 years. Conclusion: Infants born to young mothers are at greater risk of infant maltreatment, and this association remained until age 28 years. These findings are important for ensuring public health interventions are supporting populations experiencing structural vulnerabilities with the aim of preventing maltreatment

Reductions in hospital care among clinically vulnerable children aged 0-4 years during the COVID-19 pandemic

OBJECTIVE: To quantify reductions in hospital care for clinically vulnerable children during the COVID-19 pandemic. DESIGN: Birth cohort. SETTING: National Health Service hospitals in England. STUDY POPULATION: All children aged <5 years with a birth recorded in hospital administrative data (January 2010-March 2021). MAIN EXPOSURE: Clinical vulnerability defined by a chronic health condition, preterm birth (<37 weeks' gestation) or low birth weight (<2500 g). MAIN OUTCOMES: Reductions in care defined by predicted hospital contact rates for 2020, estimated from 2015 to 2019, minus observed rates per 1000 child years during the first year of the pandemic (March 2020-2021). RESULTS: Of 3 813 465 children, 17.7% (one in six) were clinically vulnerable (9.5% born preterm or low birth weight, 10.3% had a chronic condition). Reductions in hospital care during the pandemic were much higher for clinically vulnerable children than peers: respectively, outpatient attendances (314 vs 73 per 1000 child years), planned admissions (55 vs 10) and unplanned admissions (105 vs 79). Clinically vulnerable children accounted for 50.1% of the reduction in outpatient attendances, 55.0% in planned admissions and 32.8% in unplanned hospital admissions. During the pandemic, weekly rates of planned care returned to prepandemic levels for infants with chronic conditions but not older children. Reductions in care differed by ethnic group and level of deprivation. Virtual outpatient attendances increased from 3.2% to 24.8% during the pandemic. CONCLUSION: One in six clinically vulnerable children accounted for one-third to one half of the reduction in hospital care during the pandemic

Changes in adolescents' planned hospital care during the COVID-19 pandemic: analysis of linked administrative data

OBJECTIVE: To describe changes in planned hospital care during the pandemic for vulnerable adolescents receiving children's social care (CSC) services or special educational needs (SEN) support, relative to their peers. DESIGN: Observational cohort in the Education and Child Health Insights from Linked Data database (linked de-identified administrative health, education and social care records of all children in England). STUDY POPULATION: All secondary school pupils in years 7-11 in academic year 2019/2020 (N=3 030 235). MAIN EXPOSURE: Receiving SEN support or CSC services. MAIN OUTCOMES: Changes in outpatient attendances and planned hospital admissions during the first 9 months of the pandemic (23 March-31 December 2020), estimated by comparing predicted with observed numbers and rates per 1000 child-years. RESULTS: A fifth of pupils (20.5%) received some form of statutory support: 14.2% received SEN support only, 3.6% received CSC services only and 2.7% received both. Decreases in planned hospital care were greater for these vulnerable adolescents than their peers: -290 vs -225 per 1000 child-years for outpatient attendances and -36 vs -16 per 1000 child-years for planned admissions. Overall, 21% of adolescents who were vulnerable disproportionately bore 25% of the decrease in outpatient attendances and 37% of the decrease in planned hospital admissions. Vulnerable adolescents were less likely than their peers to have face-to-face outpatient care. CONCLUSION: These findings indicate that socially vulnerable groups of children have high health needs, which may need to be prioritised to ensure equitable provision, including for catch-up of planned care postpandemic

Using linked administrative data to aid the handling of non-response and restore sample representativeness in cohort studies: the 1958 national child development study and hospital episode statistics data

BACKGROUND: There is growing interest in whether linked administrative data have the potential to aid analyses subject to missing data in cohort studies. METHODS: Using linked 1958 National Child Development Study (NCDS; British cohort born in 1958, n = 18,558) and Hospital Episode Statistics (HES) data, we applied a LASSO variable selection approach to identify HES variables which are predictive of non-response at the age 55 sweep of NCDS. We then included these variables as auxiliary variables in multiple imputation (MI) analyses to explore the extent to which they helped restore sample representativeness of the respondents together with the imputed non-respondents in terms of early life variables (father's social class at birth, cognitive ability at age 7) and relative to external population benchmarks (educational qualifications and marital status at age 55). RESULTS: We identified 10 HES variables that were predictive of non-response at age 55 in NCDS. For example, cohort members who had been treated for adult mental illness had more than 70% greater odds of bring non-respondents (odds ratio 1.73; 95% confidence interval 1.17, 2.51). Inclusion of these HES variables in MI analyses only helped to restore sample representativeness to a limited extent. Furthermore, there was essentially no additional gain in sample representativeness relative to analyses using only previously identified survey predictors of non-response (i.e. NCDS rather than HES variables). CONCLUSIONS: Inclusion of HES variables only aided missing data handling in NCDS to a limited extent. However, these findings may not generalise to other analyses, cohorts or linked administrative datasets. This work provides a demonstration of the use of linked administrative data for the handling of missing cohort data which we hope will act as template for others

Evaluating the real-world implementation of the Family Nurse Partnership in England: protocol for a data linkage study.

INTRODUCTION: Almost 20 000 babies are born to teenage mothers each year in England, with poorer outcomes for mothers and babies than among older mothers. A nurse home visitation programme in the USA was found to improve a wide range of outcomes for young mothers and their children. However, a randomised controlled trial in England found no effect on short-term primary outcomes, although cognitive development up to age 2 showed improvement. Our study will use linked routinely collected health, education and social care data to evaluate the real-world effects of the Family Nurse Partnership (FNP) on child outcomes up to age 7, with a focus on identifying whether the FNP works better for particular groups of families, thereby informing programme targeting and resource allocation. METHODS AND ANALYSIS: We will construct a retrospective cohort of all women aged 13-24 years giving birth in English NHS hospitals between 2010 and 2017, linking information on mothers and children from FNP programme data, Hospital Episodes Statistics and the National Pupil Database. To assess the effectiveness of FNP, we will compare outcomes for eligible mothers ever and never enrolled in FNP, and their children, using two analysis strategies to adjust for measured confounding: propensity score matching and analyses adjusting for maternal characteristics up to enrolment/28 weeks gestation. Outcomes of interest include early childhood development, childhood unplanned hospital admissions for injury or maltreatment-related diagnoses and children in care. Subgroup analyses will determine whether the effect of FNP varied according to maternal characteristics (eg, age and education). ETHICS AND DISSEMINATION: The Nottingham Research Ethics Committee approved this study. Mothers participating in FNP were supportive of our planned research. Results will inform policy-makers for targeting home visiting programmes. Methodological findings on the accuracy and reliability of cross-sectoral data linkage will be of interest to researchers

Dengue in pregnancy and maternal mortality: a cohort analysis using routine data.

Dengue is a mosquito-borne disease with major public health importance due to its growing incidence and geographical spread. There is a lack of knowledge on its contribution to maternal death. We conducted a population-based cohort study to investigate the association between symptomatic dengue during pregnancy and deaths in Brazil from 2007 to 2012. We did this by linking routine records of confirmed dengue cases to records of deaths of women who had a live birth. Using the Firth method, we estimated odds ratios for maternal deaths associated with dengue during pregnancy. Dengue increased the risk of maternal death by 3 times (95%CI,1.5-5.8) and dengue haemorrhagic fever increased the risk of maternal death by 450 times (95%CI,186.9-1088.4) when compared to mortality of pregnant women without dengue. The increase in risk occurred mostly during acute dengue 71.5 (95%CI,32.8-155.8), compared with no dengue cases. This study showed an increased risk of adverse outcomes in pregnant women with dengue. Therefore in areas where dengue is circulating, the health of pregnant women should be not only a public health priority, but health professionals attending pregnant women with dengue should more closely observe these patients to be able to intervene in a timely way and avoid deaths

Evaluation of record linkage of two large administrative databases in a middle income country: stillbirths and notifications of dengue during pregnancy in Brazil.

BACKGROUND: Due to the increasing availability of individual-level information across different electronic datasets, record linkage has become an efficient and important research tool. High quality linkage is essential for producing robust results. The objective of this study was to describe the process of preparing and linking national Brazilian datasets, and to compare the accuracy of different linkage methods for assessing the risk of stillbirth due to dengue in pregnancy. METHODS: We linked mothers and stillbirths in two routinely collected datasets from Brazil for 2009-2010: for dengue in pregnancy, notifications of infectious diseases (SINAN); for stillbirths, mortality (SIM). Since there was no unique identifier, we used probabilistic linkage based on maternal name, age and municipality. We compared two probabilistic approaches, each with two thresholds: 1) a bespoke linkage algorithm; 2) a standard linkage software widely used in Brazil (ReclinkIII), and used manual review to identify further links. Sensitivity and positive predictive value (PPV) were estimated using a subset of gold-standard data created through manual review. We examined the characteristics of false-matches and missed-matches to identify any sources of bias. RESULTS: From records of 678,999 dengue cases and 62,373 stillbirths, the gold-standard linkage identified 191 cases. The bespoke linkage algorithm with a conservative threshold produced 131 links, with sensitivity = 64.4% (68 missed-matches) and PPV = 92.5% (8 false-matches). Manual review of uncertain links identified an additional 37 links, increasing sensitivity to 83.7%. The bespoke algorithm with a relaxed threshold identified 132 true matches (sensitivity = 69.1%), but introduced 61 false-matches (PPV = 68.4%). ReclinkIII produced lower sensitivity and PPV than the bespoke linkage algorithm. Linkage error was not associated with any recorded study variables. CONCLUSION: Despite a lack of unique identifiers for linking mothers and stillbirths, we demonstrate a high standard of linkage of large routine databases from a middle income country. Probabilistic linkage and manual review were essential for accurately identifying cases for a case-control study, but this approach may not be feasible for larger databases or for linkage of more common outcomes

Study protocol: evaluation of the 0–5 public health investment in England – a mixed-methods study integrating analyses of national linked administrative data with in-depth case studies

INTRODUCTION: Health visiting is a long-established, nationally implemented programme that works with other services at a local level to improve the health and well-being of children and families. To maximise the impact and efficiency of the health visiting programme, policy-makers and commissioners need robust evidence on the costs and benefits of different levels and types of health visiting, for different families, in different local contexts. METHODS AND ANALYSIS: This mixed-methods study will analyse individual-level health visiting data for 2018/2019 and 2019/2020 linked with longitudinal data from children's social care, hospitals and schools to estimate the association of number and type of health visiting contacts with a range of children and maternal outcomes. We will also use aggregate local authority data to estimate the association between local models of health visiting and area-level outcomes. Outcomes will include hospitalisations, breast feeding, vaccination, childhood obesity and maternal mental health. Where possible, outcomes will be valued in monetary terms, and we will compare total costs to total benefits of different health visiting service delivery models. Qualitative case studies and extensive stakeholder input will help explain the quantitative analyses and interpret the results in the context of local policy, practice and circumstance

Symptomatic dengue infection during pregnancy and the risk of stillbirth in Brazil, 2006-12: a matched case-control study.

BACKGROUND: Maternal infections during pregnancy can increase the risk of fetal death. Dengue infection is common, but little is known about its role in fetal mortality. We aimed to investigate the association between symptomatic dengue infection during pregnancy and fetal death. METHODS: We did a nested case-control study using obstetrician-collected data from the Brazilian livebirth information system (SINASC), the mortality information system (SIM), and the national reportable disease information system (SINAN). We identified all pregnancies ending in stillbirth and a random sample of livebirths between Jan 1, 2006, and Dec 31, 2012. We did linkage to determine which mothers were diagnosed with dengue infection during pregnancy. By use of stillbirths as cases and a sample of matched livebirths as a control, we calculated matched odds ratios (mORs) using conditional logistic regression adjusted for maternal age and education. FINDINGS: 275 (0·2%) of 162 188 women who had stillbirths and 1507 (0·1%) of 1 586 105 women who had livebirths were diagnosed with dengue infection during pregnancy. Symptomatic dengue infection during pregnancy almost doubled the odds of fetal death (mOR 1·9, 95% CI 1·6-2·2). The increase in risk was similar when analyses were restricted to laboratory-confirmed cases of dengue infection (1·8, 1·4-2·4). Severe dengue infection increased the risk of fetal death by about five times (4·9, 2·3-10·2). INTERPRETATION: Symptomatic dengue infection during pregnancy is associated with an increased risk of fetal death. We recommend further epidemiological and biological studies of the association between dengue and poor birth outcomes to measure the burden of subclinical infections and elucidate pathological mechanisms. FUNDING: Brazilian National Council for Scientific and Technological Development, Horizon 2020