Development of a predictive risk model for school readiness at age 3 years using the UK Millennium Cohort Study

Financial-related discrimination and socioeconomic inequalities in psychological well-being related measures: a longitudinal study

BACKGROUND

This study examined the prospective association between financial-related discrimination and psychological well-being related measures and assessed the role of financial-related discrimination in explaining socioeconomic inequalities in psychological well-being related measures.

METHODS

Data of UK older adults (≥ 50 years) from the English Longitudinal Study of Ageing were used (baseline: Wave 5, 2010/2011; n = 8,988). The baseline total non-pension wealth (in tertiles: poorest, middle, richest) was used as a socioeconomic status (SES) measure. Financial-related discrimination at baseline was defined as participants who reported they had been discriminated against due to their financial status. Five psychological well-being related measures (depressive symptoms, enjoyment of life, eudemonic well-being, life satisfaction and loneliness) were examined prospectively across different follow-up periods (Waves 6, 2012/2013, 2-year follow-up; and 7, 2014/2015, 4-year follow-up). Regression models assessed associations between wealth, financial-related discrimination, and follow-up psychological measures, controlling for sociodemographic covariates and baseline psychological measures (for longitudinal associations). Mediation analysis informed how much (%) the association between wealth and psychological well-being related measures was explained by financial-related discrimination.

RESULTS

Participants from the poorest, but not middle, (vs. richest) wealth groups were more likely to experience financial-related discrimination (OR = 1.97; 95%CI = 1.49, 2.59). The poorest (vs. richest) wealth was also longitudinally associated with increased depressive symptoms and decreased enjoyment of life, eudemonic well-being and life satisfaction in both 2-year and 4-year follow-ups, and increased loneliness at 4-year follow-up. Experiencing financial-related discrimination was longitudinally associated with greater depressive symptoms and loneliness, and lower enjoyment of life across follow-up periods. Findings from mediation analysis indicated that financial-related discrimination explained 3-8% of the longitudinal associations between wealth (poorest vs. richest) and psychological well-being related measures.

CONCLUSIONS

Financial-related discrimination is associated with worse psychological well-being and explains a small proportion of socioeconomic inequalities in psychological well-being.

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.

andomised to early neuroprotection and neurorehabilitation: protocol for a follow-up study of participants from four randomised clinical trials

INTRODUCTION

School readiness includes cognitive, socio-emotional, language and physical growth and development domains which share strong associations with life-course opportunities. Children with cerebral palsy (CP) are at increased risk of poor school readiness compared with their typically developing peers. Recently, earlier diagnosis of CP has allowed interventions to commence sooner, harnessing neuroplasticity. First, we hypothesise that early referral to intervention for children at-risk of CP will lead to improved school readiness at 4-6 years relative to placebo or care as usual. Second, we hypothesise that receipt of early diagnosis and early intervention will lead to cost-savings in the form of reduced healthcare utilisation.

METHODS AND ANALYSIS

Infants identified as at-risk of CP ≤6 months corrected age (n=425) recruited to four randomised trials of neuroprotectants (n=1), early neurorehabilitation (n=2) or early parenting support (n=1) will be re-recruited to one overarching follow-up study at age 4-6 years 3 months. A comprehensive battery of standardised assessments and questionnaires will be administered to assess all domains of school readiness and associated risk factors. Participants will be compared with a historical control group of children (n=245) who were diagnosed with CP in their second year of life. Mixed-effects regression models will be used to compare school readiness outcomes between those referred for early intervention versus placebo/care-as-usual. We will also compare health-resource use associated with early diagnosis and intervention versus later diagnosis and intervention.

ETHICS AND DISSEMINATION

The Children's Health Queensland Hospital and Health Service, The University of Queensland, University of Sydney, Monash University and Curtin University Human Research Ethics Committees have approved this study. Informed consent will be sought from the parent or legal guardian of every child invited to participate. Results will be disseminated in peer-reviewed journals, scientific conferences and professional organisations, and to people with lived experience of CP and their families.

TRIAL REGISTRATION NUMBER

ACTRN12621001253897.

Big data, machine learning, and population health: predicting cognitive outcomes in childhood

The application of machine learning (ML) to address population health challenges has received much less attention than its application in the clinical setting. One such challenge is addressing disparities in early childhood cognitive development-a complex public health issue rooted in the social determinants of health, exacerbated by inequity, characterised by intergenerational transmission, and which will continue unabated without novel approaches to address it. Early life, the period of optimal neuroplasticity, presents a window of opportunity for early intervention to improve cognitive development. Unfortunately for many, this window will be missed, and intervention may never occur or occur only when overt signs of cognitive delay manifest. In this review, we explore the potential value of ML and big data analysis in the early identification of children at risk for poor cognitive outcome, an area where there is an apparent dearth of research. We compare and contrast traditional statistical methods with ML approaches, provide examples of how ML has been used to date in the field of neurodevelopmental disorders, and present a discussion of the opportunities and risks associated with its use at a population level. The review concludes by highlighting potential directions for future research in this area. IMPACT: To date, the application of machine learning to address population health challenges in paediatrics lags behind other clinical applications. This review provides an overview of the public health challenge we face in addressing disparities in childhood cognitive development and focuses on the cornerstone of early intervention. Recent advances in our ability to collect large volumes of data, and in analytic capabilities, provide a potential opportunity to improve current practices in this field. This review explores the potential role of machine learning and big data analysis in the early identification of children at risk for poor cognitive outcomes.

Predicting Low Cognitive Ability at Age 5-Feature Selection Using Machine Learning Methods and Birth Cohort Data

Objectives: In this study, we applied the random forest (RF) algorithm to birth-cohort data to train a model to predict low cognitive ability at 5 years of age and to identify the important predictive features. Methods: Data was from 1,070 participants in the Irish population-based BASELINE cohort. A RF model was trained to predict an intelligence quotient (IQ) score ≤90 at age 5 years using maternal, infant, and sociodemographic features. Feature importance was examined and internal validation performed using 10-fold cross validation repeated 5 times. Results The five most important predictive features were the total years of maternal schooling, infant Apgar score at 1 min, socioeconomic index, maternal BMI, and alcohol consumption in the first trimester. On internal validation a parsimonious RF model based on 11 features showed excellent predictive ability, correctly classifying 95% of participants. This provides a foundation suitable for external validation in an unseen cohort. Conclusion: Machine learning approaches to large existing datasets can provide accurate feature selection to improve risk prediction. Further validation of this model is required in cohorts representative of the general population.

A Systematic Review of School Transition Interventions to Improve Mental Health and Wellbeing Outcomes in Children and Young People

Normative transitions between educational settings can be important life events for young people, having the potential to influence mental health trajectories across the life course. Interventions to target transitions have been used to support children and young people as they transition between school settings, but there is limited synthesis of their effects. Seven databases were searched to identify studies of universal interventions focused on supporting mental health and wellbeing across three main types of educational transition: preschool to elementary school; school to school (including elementary to middle; middle to high and other combinations depending on country); and high school to post-compulsory education. Effect directions for behavioural, psychological/emotional and social measures of mental health were extracted for each study and synthesized using effect direction plot methodology. Searches identified 6494 records for screening. This resulted in 34 papers being included in the review, consisting of 24 different interventions. Social outcomes appeared more amenable to intervention than behavioural outcomes, with mixed findings for psychological measures of mental health. Intervention characteristics shifted based on the age of young person involved in the transition, with greater focus on parenting and school environment during the early transitions, and more focus on social support for the transition to post-compulsory education. A broad range of interventions were identified for supporting mental health and wellbeing across the three types of educational transition with mixed impact and diverse methodologies. More research is needed to identify transferable intervention mechanisms that may hold across different contexts and settings. PROSPERO registration number: CRD42020176336.

Measuring disadvantage in the early years in the UK: A systematic scoping review

Background

The relationship between disadvantage and child health in the early years is well established. For this evidence base to most helpfully inform services, we need to better understand how disadvantage is conceptualised and measured in the literature. We aimed to conceptualise disadvantage measured in child health literature and explore the associations between disadvantage and child health using these measures.

Method

We conducted a scoping review using systematic methods to identify key concepts of disadvantage used in empirical child health literature. We searched MEDLINE, Scopus, and grey literature for studies exploring the association between disadvantage and child health outcomes for children aged 0–5 in the United Kingdom. We extracted and analysed data from 86 studies.

Results

We developed a framework describing two domains, each with two attributes conceptualising disadvantage: level of disadvantage indicator (individual and area) and content of disadvantage indicator (social and economic). Individual-level measures of disadvantage tended to identify stronger associations between disadvantage and child health compared with area-level measures.

Conclusion

The choice of disadvantage indicators, particularly whether individual- or area-level, can affect the inferences made about the relationship between disadvantage and child health. Better access to individual-level disadvantage indicators in administrative data could support development and implementation of interventions aimed at reducing child health inequalities in the early years.

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Measurement of disadvantage in child health is wide-ranging and multi-dimensional.

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Social, economic, individual, and area-level are key concepts of disadvantage.

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Area-level measures underestimate the association between disadvantage and child health.

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Individual-level disadvantage indicators are needed in administrative data.

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Policymakers planning child health interventions should measure disadvantage carefully.

Is a universal nurse home visiting program possible? A cross-sectional survey of nurse home visitation service needs among pregnant women and mothers with young children

In 2019, the South Korean government established a plan to develop home visitation services for pregnant women and women with children below the age of 24 months and expand the services nationwide. Therefore, a national survey was needed to provide relevant information for the policy decision of whether to implement universal home visitation services by nurses for families with young children. To determine home visitation service needs in South Korea, 804 women who were pregnant or had children below the age of 24 months were selected as survey participants through stratified random sampling by region reflecting geographical distribution in numbers of births. Of them, 614 responded to survey questionnaires delivered via email. After excluding surveys with too short of a response time, extreme values, and incomplete answers, 500 participants’ responses were analyzed. Participants indicated whether they supported the provision of home visitation services and whether they were willing to utilize home visitation services. The survey also elicited responses regarding the level of needs for individual service items that could be delivered by nurses during home visits. The fieldwork was conducted by a consulting and research firm. The differences in whether respondents supported nurse home visitation services and intended to use nurse home visitation services according to mothers’ characteristics were examined using the chi-square test. In total, 88.0% of survey participants supported nurse home visitation services, and 81.2% indicated that they intended to receive the services. Most pregnant women and women with children below the age of 24 months responded positively to the various prenatal or postpartum services that nurses could provide during home visits. The percentages of support for the services and intention to use services were generally high among subgroups according to mothers’ characteristics. Therefore, universal home visitation services by nurses during pregnancy and in the postnatal period would be received well by Korean women.

Pre-Birth Household Challenges Predict Future Child’s School Readiness and Academic Achievement

Early developmental success and school readiness strongly influence future skill development, occupational opportunities, and health. Therefore, it is critical to identify and address early determinants of school readiness for supporting children’s overall well-being and success. In this retrospective cohort study, we examined the effects of pre-birth household challenges, such as homelessness or experiences of intimate partner violence, on children’s early school readiness. We linked data from the Alaska 2009–2011 Pregnancy Risk Assessment Monitoring System (PRAMS) to administrative and education records through 2019. Education records included kindergarten developmental scores, third grade reading assessments, and attendance records. Generalized linear models with Quasi-Poisson distributions for each outcome of interest examined the predictive value of pre-birth household challenges on the risks of not meeting school readiness expectations. We found that experiencing higher numbers of pre-birth household challenges was related to higher risk of the child not meeting developmental and reading proficiency and having chronic absenteeism. These results suggest that it is imperative support systems for pregnant persons and their families be introduced as soon as possible in pre-natal care routines to address current pre-birth household stressors and prevent future challenges. Such early prevention efforts are needed to ensure the best possible developmental start for children.

Is amblyopia associated with school readiness and cognitive performance during early schooling? Findings from the Millennium Cohort Study

Background

Amblyopia is a neurodevelopmental condition causing reduced vision, for which programmes of whole population child vision screening exist throughout the world. There is an ongoing debate about the value of screening due to the lack of evidence about meaningful functional impacts of amblyopia. Our objective was to determine whether amblyopia is associated with school readiness and early cognitive performance.

Methods and findings

Data from the prospective Millennium Cohort Study of children born in the United Kingdom in 2000–01 and followed-up to age 7 years (n = 13,967). Using parental self-report on eye conditions and treatment coded by clinical reviewers, participants were grouped into no eye conditions, strabismus alone, refractive amblyopia, or strabismic/mixed (refractive plus strabismic) amblyopia. The outcomes were poor school readiness using Bracken School Readiness Assessment <25th percentile (age 3); and cognitive tests and their age-related trajectories using British Ability Scale II Naming Vocabulary (ages 3/5) and Pattern Construction (ages 5/7). Multivariable analyses showed that compared to children without any eye conditions, only those with strabismic/mixed amblyopia had an increased risk of poor school readiness (OR = 2.04, 95%CI 1.09–3.82). Small differences in mean scores for NV and PC of children with amblyopia (all types) compared to those without any eye condition were not clinically significant (>10 points) irrespective of whether treatment had already started. The age-related cognitive trajectories of children with amblyopia did not differ from those without any eye conditions for either NV (p = 0.62) or PC (p = 0.51). These associations are at population rather than individual level, so it might be that some individuals with amblyopia did experience significant adverse outcomes that are not captured by summary statistics.

Conclusions

Amblyopia is not significantly associated with adverse cognitive performance and trajectories in early schooling and there is no evidence that this is due to a mediating effect of treatment. Although amblyopia combined with strabismus is associated with poor school readiness, this is not translated into poor cognitive performance. These novel findings may explain the lack of association reported between amblyopia and educational outcomes in adult life and suggest that the impact of amblyopia on education is not of itself a justification for whole population child vision screening aimed at detecting this disorder.