Childhood exposure to outdoor air pollution in different microenvironments and cognitive and fine motor function in children from six European cohorts.

BACKGROUND: Exposure to air pollution during childhood has been linked with adverse effects on cognitive development and motor function. However, limited research has been done on the associations of air pollution exposure in different microenvironments such as home, school, or while commuting with these outcomes. OBJECTIVE: To analyze the association between childhood air pollution exposure in different microenvironments and cognitive and fine motor function from six European birth cohorts. METHODS: We included 1301 children from six European birth cohorts aged 6-11 years from the HELIX project. Average outdoor air pollutants concentrations (NO2, PM2.5) were estimated using land use regression models for different microenvironments (home, school, and commute), for 1-year before the outcome assessment. Attentional function, cognitive flexibility, non-verbal intelligence, and fine motor function were assessed using the Attention Network Test, Trail Making Test A and B, Raven Colored Progressive Matrices test, and the Finger Tapping test, respectively. Adjusted linear regressions models were run to determine the association between each air pollutant from each microenvironment on each outcome. RESULTS: In pooled analysis we observed high correlation (rs = 0.9) between air pollution exposures levels at home and school. However, the cohort-by-cohort analysis revealed correlations ranging from low to moderate. Air pollution exposure levels while commuting were higher than at home or school. Exposure to air pollution in the different microenvironments was not associated with working memory, attentional function, non-verbal intelligence, and fine motor function. Results remained consistently null in random-effects meta-analysis. CONCLUSIONS: No association was observed between outdoor air pollution exposure in different microenvironments (home, school, commute) and cognitive and fine motor function in children from six European birth cohorts. Future research should include a more detailed exposure assessment, considering personal measurements and time spent in different microenvironments.

Risk of not being in employment, education or training (NEET) in late adolescence is signalled by school readiness measures at 4-5 years.

BACKGROUND: Not being in employment, education, or training (NEET) is associated with poor health (physical and mental) and social exclusion. We investigated whether England's statutory school readiness measure conducted at 4-5 years provides a risk signal for NEET in late adolescence. METHODS: We identified 8,118 individuals with school readiness measures at 4-5 years and NEET records at 16-17 years using Connected Bradford, a bank of linked routinely collected datasets. Children were categorised as 'school ready' if they reached a 'Good Level of Development' on the Early Years Foundation Stage Profile. We used probit regression and structural equation modelling to investigate the relationship between school readiness and NEET status and whether it primarily relates to academic attainment. RESULTS: School readiness was significantly associated with NEET status. A larger proportion of young people who were not school ready were later NEET (11%) compared to those who were school ready (4%). Most of this effect was attributable to shared relationships with academic attainment, but there was also a direct effect. Measures of deprivation and Special Educational Needs were also strong predictors of NEET status. CONCLUSIONS: NEET risk factors occur early in life. School readiness measures could be used as early indicators of risk, with interventions targeted to prevent the long-term physical and mental health problems associated with NEET, especially in disadvantaged areas. Primary schools are therefore well placed to be public health partners in early intervention strategies.

The relationship between 'school readiness' and later persistent absenteeism.

Post-pandemic school absence is an increasing concern for governments worldwide. Absence is associated with poor academic outcomes and long-term illness (physical and mental). Absenteeism increases the risk of financial difficulties in adulthood and involvement in the criminal justice system. We hypothesized that early childhood problems might be an antecedent of absenteeism. We tested this hypothesis by investigating the pre-pandemic association between school readiness and persistent absenteeism using a population-linked dataset. Analyses included 62,598 children aged 5-13 years from the Connected Bradford database (spanning academic years 2012/13 to 2019/20). Special educational needs status, English as an Additional Language status, socioeconomic status, sex and ethnicity were covariates significantly associated with persistent absenteeism. Children who were not 'school ready' had increased odds of being persistently absent later in their education journey after controlling for these covariates. School readiness was associated with even greater odds of being persistently absent over two or more years. These findings show (i) the seeds of absenteeism are sown early in childhood; (ii) absenteeism shows the hallmark of structural inequities; and (iii) the potential of 'school readiness' measures to identify children at risk of long-term disengagement from the education system.

A novel tool for characterising upper limb function in progressive multiple sclerosis through kinematic assessment.

INTRODUCTION: Current upper limb assessment methods in MS rely on measuring duration in tasks like the nine-hole peg test (9HPT). Kinematic techniques may provide a more useful measure of functional change in clinical and research practice. The aim of this study was to assess upper limb function prospectively in people with progressive MS using a kinematic 3D motion capture system and compare with current measures. METHODS: 42 people with progressive MS (PwPMS) and 15 healthy controls reached-and-grasped different objects whilst recorded by a kinematic assessment system. 9HPT, Expanded Disability Status Scale (EDSS), and patient reported outcome measures (PROs) were collected. All measures were taken at baseline for PwPMS and controls, and again at six months for PwPMS. RESULTS: Relative to controls, PwPMS had significantly longer reaction (0.11 s, p < 0.05) and reach (0.25 s, p < 0.05) times. PwPMS took longer to pick-up (0.34 s, p < 0.05), move (0.14 s, p < 0.05), and place (0.18 s, p < 0.05) objects. PwPMS had lower peak velocities when reaching (7.4 cm/s, p < 0.05) and moving (7.3 cm/s, p < 0.05) objects. Kinematic assessment demonstrated consistent differences between PwPMS with mild and severe upper limb dysfunction as defined by PROs, which were not captured by 9HPT or EDSS in this group. PwPMS demonstrated altered grip apertures profiles, as measured by their ability to complete individual parts of the reach and grasp task, between the baseline and follow-up timepoints. CONCLUSIONS: We have created and tested a novel upper limb function assessment tool which has detected changes and characteristics in hand function, not currently captured by the EDSS and 9HPT.

Getting stuck in a rut as an emergent feature of a dynamic decision-making system.

Human sensorimotor decision making has a tendency to get 'stuck in a rut', being biased towards selecting a previously implemented action structure (hysteresis). Existing explanations propose this is the consequence of an agent efficiently modifying an existing plan, rather than creating a new plan from scratch. Instead, we propose that hysteresis is an emergent property of a system learning from the consequences of its actions. To examine this, 152 participants moved a cursor to a target on a tablet device while avoiding an obstacle. Hysteresis was observed when the obstacle moved sequentially across the screen between trials, whereby the participant continued moving around the same side of the obstacle despite it now requiring a larger movement than the alternative. Two further experiments (n = 20) showed an attenuation when time and resource constraints were eased. We created a simple computational model capturing probabilistic estimate updating that showed the same patterns of results. This provides, to our knowledge, the first computational demonstration of how sensorimotor decision making can get 'stuck in a rut' through the updating of the probability estimates associated with actions.

Early educational attainment in children with major congenital anomaly in the UK.

OBJECTIVE: To describe early educational attainment and special educational needs (SEN) provision in children with major congenital anomaly (CA) compared with peers. DESIGN: Analysis of educational data linked to the ongoing Born in Bradford cohort study. Confounders were identified via causal inference methods and multivariable logistic regression performed. SETTING: Children born in Bradford Royal Infirmary (BRI), West Yorkshire. PATIENTS: All women planning to give birth at BRI and attending antenatal clinic from March 2007 to December 2010 were eligible. 12 453 women with 13 776 pregnancies (>80% of those attending) were recruited. Records of 555 children with major CA and 11 188 without were linked to primary education records. OUTCOMES: Key Stage 1 (KS1) attainment at age 6-7 years in Maths, Reading, Writing and Science. SEN provision from age 4 to 7 years. RESULTS: 41% of children with major CA received SEN provision (compared with 14% without), and 48% performed below expected standards in at least one KS1 domain (compared with 29% without). The adjusted odds of children with CA receiving SEN provision and failing to achieve the expected standard at KS1 were, respectively, 4.30 (95% CI 3.49 to 5.31) and 3.06 (95% CI 2.47 to 3.79) times greater than their peers. Those with genetic, heart, neurological, urinary, gastrointestinal and limb anomalies had significantly poorer academic achievement. CONCLUSIONS: These novel results demonstrate that poor educational attainment extends to children with urinary, limb and gastrointestinal CAs. We demonstrate the need for collaboration between health and education services to assess and support children with major CA, so every CA survivor can maximise their potential.

The validity and reliability of school-based fundamental movement skills screening to identify children with motor difficulties.

AIM: Assess whether school-based teacher-led screening is effective at identifying children with motor difficulties. METHODS: Teachers tested 217 children aged between 5 and 11 years old, after a one hour training session, using a freely available tool (FUNMOVES). Four classes (n = 91) were scored by both researchers and teachers to evaluate inter-rater reliability. Researchers assessed 22 children using the Movement Assessment Battery for Children (MABC-2; considered to be the 'gold standard' in Europe for use as part of the diagnostic process for Developmental Coordination Disorder) to assess concurrent and predictive validity. RESULTS: Inter-rater reliability for all individual activities within FUNMOVES ranged from 0.85-0.97 (unweighted Kappa; with 95%CI ranging from 0.77-1). For total score this was lower (κ = 0.76, 95%CI = 0.68-0.84), however when incorporating linear weighting, this improved (κ = 0.94, 95%CI = 0.89-0.99). When evaluating FUNMOVES total score against the MABC-2 total score, the specificity (1, 95%CI = 0.63-1) and positive predictive value (1; 95%CI = 0.68-1) of FUNMOVES were high, whereas sensitivity (0.57, 95%CI = 0.29-0.82) and negative predictive values (0.57, 95%CI = 0.42-0.71) were moderate. Evaluating only MABC-2 subscales which are directly related to fundamental movement skills (Aiming & Catching, and Balance) improved these values to 0.89 (95%CI = 0.52-1) and 0.93 (95%CI = 0.67-0.99) respectively. INTERPRETATION: Teacher-led screening of fundamental movement skills (via FUNMOVES) is an effective method of identifying children with motor difficulties. Such universal screening in schools has the potential to identify movement difficulties and enable earlier intervention than the current norm.

Born in Bradford's Age of Wonder cohort: protocol for adolescent data collection.

Background: Adolescence and transition into adulthood are periods shaping life-long mental health, cardiometabolic risk, and inequalities. However, they are poorly studied and understood. By extending and expanding the Born in Bradford (BiB) cohort study through this period using innovative, co-produced approaches to collect and analyse data, we aim to understand better the interplay of factors that influence health and wellbeing, and inform/evaluate interventions to improve them and reduce inequalities. Protocol: BiB Age of Wonder (AoW) is a large, whole city cohort that will capture the contemporary lived experience amongst multi-ethnic adolescents progressing into young adulthood. We will collect repeated data from existing BiB participants and their peers (N~30,000 adolescents). The protocol for the first phase of the quantitative methods, involving survey measurements and health assessments in mainstream secondary schools is described here. We describe the co-production behind these methods, and lessons learned from the first year of data collection.

Born in Bradford have been following the health and wellbeing of over 13,000 Bradford children since they were born. This group of children are now in their teenage years ­ a time that is crucial for their future mental and physical health. Age of Wonder aims to capture this journey through adolescence and early adulthood with up to 30,000 young people in Bradford over 7 years. In the first phase of this project, data collection is taking part in secondary schools in Bradford. This protocol describes how this data collection is currently being carried out in the schools. Young people aged 12-15 are being asked to complete questionnaires, covering topics such as mental and physical health. These topics have been designed with groups of young people, schools and other partners, to make sure we are capturing data on the things most important to young people. Those in Year 9 (13-14 years old), are also asked to take part in physical health measurements such as height, weight, blood pressure and a blood sample, as well as computer-based assessments of cognition (memory), movement and language. There have been a number of lessons learned from the first full year of data collection, such as how to make the research as easy as possible for schools to take part in when they have so many competing demands on their time.