Maternal smoking during pregnancy and offspring risk of intellectual disability: a UK-based cohort study.

Background: Observational studies have described associations of maternal smoking during pregnancy with intellectual disability (ID) in the exposed offspring. Whether these results reflect a causal effect or unmeasured confounding is still unclear. Methods: Using a UK-based prospectively collected birth cohort (the Avon Longitudinal Study of Parents and Children) of 13,479 children born between 1991 and 1992, we assessed the relationship between maternal smoking at 18 weeks' gestation and offspring risk of ID, ascertained through multiple sources of linked information including primary care diagnoses and education records. Using confounder-adjusted logistic regression, we performed observational analyses and a negative control analysis that compared maternal with partner smoking in pregnancy under the assumption that if a causal effect were to exist, maternal effect estimates would be of greater magnitude than estimates for partner smoking if the two exposures suffer from comparable biases. Results: In observational analysis, we found an adjusted odds ratio for ID of 0.75 (95% CI = 0.49-1.13) for any maternal smoking and 0.97 (95% CI = 0.71-1.33) per 10-cigarette increase in number of cigarettes smoked per day. In negative control analysis, comparable effect estimates were found for any partner smoking (OR = 0.94; 95% CI = 0.63-1.40) and number of cigarettes smoked per day (OR = 0.94; 95% CI = 0.74-1.20). Conclusions: The results are not consistent with a causal effect of maternal smoking during pregnancy on offspring ID.

ENERGY EXPENDITURE OF INTERNATIONAL FEMALE RUGBY UNION PLAYERS DURING A MAJOR INTERNATIONAL TOURNAMENT: A DOUBLY LABELLED WATER STUDY.

The purpose of this study was to quantify the total energy expenditure (TEE) of international female rugby union players. Fifteen players were assessed over 14-days throughout an international multi-game tournament, which represented two consecutive one-match microcycles. Resting metabolic rate (RMR) and TEE were assessed by indirect calorimetry and doubly labelled water, respectively. Physical activity level (PAL) was estimated (TEE:RMR). Mean RMR, TEE, and PAL were 6.60 ± 0.93 MJ.day-1, 13.51 ± 2.28 MJ.day-1 and 2.0 ± 0.3 AU, respectively. There was no difference in TEE (13.74 ± 2.31 vs. 13.92 ± 2.10 MJ.day-1; p = 0.754), or PAL (2.06 ± 0.26 AU vs. 2.09 ± 0.23 AU; p = 0.735) across microcycles, despite substantial decreases in training load (total distance: -8088 m, collisions: -20 n, training duration: -252 min). After correcting for body composition, there was no difference in TEE (13.80 ± 1.74 vs. 13.16 ± 1.97 adj. MJ.day-1, p = 0.190), RMR (6.49 ± 0.81 vs. 6.73 ± 0.83 adj. MJ.day-1, p = 0.633) or PAL (2.15 ± 0.14 vs 1.87 ± 0.26 AU, p = 0.090) between forwards and backs. For an injured participant (n = 1), TEE reduced by 1.7 MJ.day-1 from pre-injury. For participants with illness (n = 3), TEE was similar to pre-illness (+0.49 MJ.day-1). The energy requirements of international female rugby players were consistent across one-match microcycles. Forwards and backs had similar adjusted energy requirements. These findings are critical to inform the dietary guidance provided to female rugby players.

Air and Noise Pollution Exposure in Early Life and Mental Health From Adolescence to Young Adulthood.

Importance: Growing evidence associates air pollution exposure with various psychiatric disorders. However, the importance of early-life (eg, prenatal) air pollution exposure to mental health during youth is poorly understood, and few longitudinal studies have investigated the association of noise pollution with youth mental health. Objectives: To examine the longitudinal associations of air and noise pollution exposure in pregnancy, childhood, and adolescence with psychotic experiences, depression, and anxiety in youths from ages 13 to 24 years. Design, Setting, and Participants: This cohort study used data from the Avon Longitudinal Study of Parents and Children, an ongoing longitudinal birth cohort founded in 1991 through 1993 in Southwest England, United Kingdom. The cohort includes over 14 000 infants with due dates between April 1, 1991, and December 31, 1992, who were subsequently followed up into adulthood. Data were analyzed October 29, 2021, to March 11, 2024. Exposures: A novel linkage (completed in 2020) was performed to link high-resolution (100 m2) estimates of nitrogen dioxide (NO2), fine particulate matter under 2.5 µm (PM2.5), and noise pollution to home addresses from pregnancy to 12 years of age. Main outcomes and measures: Psychotic experiences, depression, and anxiety were measured at ages 13, 18, and 24 years. Logistic regression models controlled for key individual-, family-, and area-level confounders. Results: This cohort study included 9065 participants who had any mental health data, of whom (with sample size varying by parameter) 51.4% (4657 of 9051) were female, 19.5% (1544 of 7910) reported psychotic experiences, 11.4% (947 of 8344) reported depression, and 9.7% (811 of 8398) reported anxiety. Mean (SD) age at follow-up was 24.5 (0.8) years. After covariate adjustment, IQR increases (0.72 µg/m3) in PM2.5 levels during pregnancy (adjusted odds ratio [AOR], 1.11 [95% CI, 1.04-1.19]; P = .002) and during childhood (AOR, 1.09 [95% CI, 1.00-1.10]; P = .04) were associated with elevated odds for psychotic experiences. Pregnancy PM2.5 exposure was also associated with depression (AOR, 1.10 [95% CI, 1.02-1.18]; P = .01). Higher noise pollution exposure in childhood (AOR, 1.19 [95% CI, 1.03-1.38]; P = .02) and adolescence (AOR, 1.22 [95% CI, 1.02-1.45]; P = .03) was associated with elevated odds for anxiety. Conclusions and Relevance: In this longitudinal cohort study, early-life air and noise pollution exposure were prospectively associated with 3 common mental health problems from adolescence to young adulthood. There was a degree of specificity in terms of pollutant-timing-outcome associations. Interventions to reduce air and noise pollution exposure (eg, clean air zones) could potentially improve population mental health. Replication using quasi-experimental designs is now needed to shed further light on the underlying causes of these associations.

The mediating role of health behaviors in the association between depression, anxiety and cancer incidence: an individual participant data meta-analysis.

BACKGROUND: Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers). METHODS: Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs). RESULTS: Smoking (HRs range 1.04-1.10) and physical inactivity (HRs range 1.01-1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03-1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01). CONCLUSIONS: Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.

Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis.

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.

Deriving and validating an asthma diagnosis prediction model for children and young people in primary care.

Introduction: Accurately diagnosing asthma can be challenging. We aimed to derive and validate a prediction model to support primary care clinicians assess the probability of an asthma diagnosis in children and young people. Methods: The derivation dataset was created from the Avon Longitudinal Study of Parents and Children (ALSPAC) linked to electronic health records. Participants with at least three inhaled corticosteroid prescriptions in 12-months and a coded asthma diagnosis were designated as having asthma. Demographics, symptoms, past medical/family history, exposures, investigations, and prescriptions were considered as candidate predictors. Potential candidate predictors were included if data were available in ≥60% of participants. Multiple imputation was used to handle remaining missing data. The prediction model was derived using logistic regression. Internal validation was completed using bootstrap re-sampling. External validation was conducted using health records from the Optimum Patient Care Research Database (OPCRD). Results: Predictors included in the final model were wheeze, cough, breathlessness, hay-fever, eczema, food allergy, social class, maternal asthma, childhood exposure to cigarette smoke, prescription of a short acting beta agonist and the past recording of lung function/reversibility testing. In the derivation dataset, which comprised 11,972 participants aged <25 years (49% female, 8% asthma), model performance as indicated by the C-statistic and calibration slope was 0.86, 95% confidence interval (CI) 0.85-0.87 and 1.00, 95% CI 0.95-1.05 respectively. In the external validation dataset, which included 2,670 participants aged <25 years (50% female, 10% asthma), the C-statistic was 0.85, 95% CI 0.83-0.88, and calibration slope 1.22, 95% CI 1.09-1.35. Conclusions: We derived and validated a prediction model for clinicians to calculate the probability of asthma diagnosis for a child or young person up to 25 years of age presenting to primary care. Following further evaluation of clinical effectiveness, the prediction model could be implemented as a decision support software.

Associations between SARS-CoV-2 infection and subsequent economic inactivity and employment status: pooled analyses of five linked longitudinal surveys.

Introduction: Following the acute phase of the COVID-19 pandemic, record numbers of people became economically inactive (i.e., neither working nor looking for work), or non-employed (including unemployed job seekers and economically inactive people). A possible explanation is people leaving the workforce after contracting COVID-19. We investigated whether testing positive for SARS-CoV-2 is related to subsequent economic inactivity and non-employment, among people employed pre-pandemic. Methods: The data came from five UK longitudinal population studies held by both the UK Longitudinal Linkage Collaboration (UK LLC; primary analyses) and the UK Data Service (UKDS; secondary analyses). We pooled data from five long established studies (1970 British Cohort Study, English Longitudinal Study of Ageing, 1958 National Child Development Study, Next Steps, and Understanding Society). The study population were aged 25-65 years between March 2020 to March 2021 and employed pre-pandemic. Outcomes were economic inactivity and non-employment measured at the time of the last follow-up survey (November 2020 to March 2021, depending on study). For the UK LLC sample (n=8,174), COVID-19 infection was indicated by a positive SARS-CoV-2 test in NHS England records. For the UKDS sample we used self-reported measures of COVID-19 infection (n=13,881). Logistic regression models estimated odds ratios (ORs) with 95% confidence intervals (95%CIs) adjusting for potential confounders including sociodemographic variables, pre-pandemic health and occupational class. Results: Testing positive for SARS-CoV-2 was very weakly associated with economic inactivity (OR 1.08 95%CI 0.68-1.73) and non-employment status (OR 1.09. 95%CI 0.77-1.55) in the primary analyses. In secondary analyses, self-reported test-confirmed COVID-19 was not associated with either economic inactivity (OR 1.01 95%CI 0.70-1.44) or non-employment status (OR 1.03 95%CI 0.79-1.35). Conclusions: Among people employed pre-pandemic, testing positive for SARS-CoV-2 was either weakly or not associated with increased economic inactivity or non-employment. Research on the recent increases in economic inactivity should focus on other potential causes.

A protocol for linking participants' retailer 'loyalty card' records into the Avon Longitudinal Study of Parents and Children (ALSPAC).

Longitudinal population studies (LPS) have a long history of providing insights into how individual consumption patterns and other lifestyle choices affect health and socio-economic outcomes. LPS typically operate as research databanks, integrating rich and deep phenotypic data - covering diverse aspects of individual, family and household status - with genomic data and linked records on health and socio-economic outcomes. However, individual consumption and behavioural choices are traditionally studied solely using self-report methods which are prone to known biases. We propose to enrich LPS databanks with a new form of digital footprint data - individual shopping history records. These are collected by supermarkets through "loyalty" card schemes and can provide a new perspective on real world behaviours and history of consumption. However, as a novel class of data in the context of longitudinal research, our ability to assess the quality and completeness of the data is unknown, as is our ability to effectively triangulate between self-reported and linked data. This paper describes a protocol for linking individual level shopping history data into a LPS using Avon Longitudinal Study of Parents and Children (ALSPAC) as a testbed. The protocol covers the process of establishing participant fair processing, an ethical and legal basis for the linkage framework itself, and how these data will be integrated into the ALSPAC databank. It does not cover the subsequent research use of these data. The protocol was built on an extensive participant engagement and acceptability work and has been approved by the ALSPAC Law and Ethics committee.

Twins Early Development Study (TEDS): A genetically sensitive investigation of mental health outcomes in the mid-twenties.

The Twins Early Development Study (TEDS) is a longitudinal study following a cohort of twins born 1994-1996 in England and Wales. Of the 13,759 families who originally consented to take part, over 10,000 families remain enrolled in the study. The current focus of TEDS is on mental health in the mid-twenties. Making use of over 25 years of genetically sensitive data, TEDS is uniquely placed to explore the longitudinal genetic and environmental influences on common mental health disorders in early adulthood. This paper outlines recent data collection efforts supporting this work, including a cohort-wide mental health assessment at age 26 and a multi-phase Covid-19 study. It will also provide an update on data linkage efforts and the Children of TEDS (CoTEDS) project.

Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis.

BACKGROUND: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. METHODS: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). RESULTS: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06-1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04-1.23). CONCLUSIONS: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. PREREGISTRATION NUMBER: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677.

Linkage of the Avon Longitudinal Study of Parents and Children (ALSPAC) to Avon & Somerset Police regional police records.

This data note describes a new resource for crime-related research: the Avon Longitudinal Study of Parents and Children (ALSPAC) linked to regional police records. The police data were provided by Avon & Somerset Police (A&SP), whose area of responsibility contains the ALSPAC recruitment area. In total, ALSPAC had permission to link to crime records for 12,662 of the 'study children' (now adults, who were born in the early 1990s).  The linkage took place in two stages: Stage 1 involved the ALSPAC Data Linkage Team establishing the linkage using personal identifiers common to both the ALSPAC participant database and A&SP records using deterministic and probabilistic methods. Stage 2 involved A&SP extracting attribute data on the matched individuals, removing personal identifiers and securely sharing the de-identified records with ALSPAC. The police data extraction took place in July 2021, when the participants were in their late 20s/early 30s. This data note contains details on the resulting linked police records available. In brief, electronic police records were available from 2007 onwards. In total, 1757 participants (14%) linked to at least one police record for a charge, offence 'taken into consideration', caution, or another out of court disposal. Linked participants had a total of 6413 records relating to 6283 offences. Almost three quarters of the linked participants were male. The most common offence types were violence against the person (22% of records), drug offences (19%), theft (17%) and public order offences (11%). This data note also details important issues that researchers using the local police data should be aware of, including the importance of defining an appropriate denominator, completeness, and biases affecting police records.

Associations between self-reported healthcare disruption due to covid-19 and avoidable hospital admission: evidence from seven linked longitudinal studies for England.

OBJECTIVES: To examine whether there is an association between people who experienced disrupted access to healthcare during the covid-19 pandemic and risk of an avoidable hospital admission. DESIGN: Observational analysis using evidence from seven linked longitudinal cohort studies for England. SETTING: Studies linked to electronic health records from NHS Digital from 1 March 2020 to 25 August 2022. Data were accessed using the UK Longitudinal Linkage Collaboration trusted research environment. PARTICIPANTS: Individual level records for 29 276 people. MAIN OUTCOME MEASURES: Avoidable hospital admissions defined as emergency hospital admissions for ambulatory care sensitive and emergency urgent care sensitive conditions. RESULTS: 9742 participants (weighted percentage 35%, adjusted for sample structure of longitudinal cohorts) self-reported some form of disrupted access to healthcare during the covid-19 pandemic. People with disrupted access were at increased risk of any (odds ratio 1.80, 95% confidence interval 1.39 to 2.34), acute (2.01, 1.39 to 2.92), and chronic (1.80, 1.31 to 2.48) ambulatory care sensitive hospital admissions. For people who experienced disrupted access to appointments (eg, visiting their doctor or an outpatient department) and procedures (eg, surgery, cancer treatment), positive associations were found with measures of avoidable hospital admissions. CONCLUSIONS: Evidence from linked individual level data shows that people whose access to healthcare was disrupted were more likely to have a potentially preventable hospital admission. The findings highlight the need to increase healthcare investment to tackle the short and long term implications of the pandemic, and to protect treatments and procedures during future pandemics.

Recreational Marijuana Use, Adolescent Cognitive Development, and Schizophrenia Susceptibility.

Background: We investigated how low marijuana (MJ) use levels, the typical use pattern in most adolescent users, affect cognitive maturation and schizophrenia risk. Methods: In two complementary adolescent samples where the majority reported minimal MJ use, we compared cognitive performances before and after MJ use initiation. The Iowa sample (40 first-degree relatives and 54 second-degree relatives of patients with schizophrenia and 117 control subjects with no schizophrenia family history) underwent a battery of standardized neuropsychological tests at 0, 18, and 36 months. Based on self-administered Timeline Followback interviews, 26.5% of adolescents had emergent MJ use (eMJ) during follow-up. The second sample (n = 3463), derived from a birth cohort, received substance use and sustained attention assessments between ages 10 and 15 years. Mixed linear models and regression analyses tested the effects of eMJ on longitudinal changes in cognitive performance. Results: In the Iowa sample, longitudinal changes in 5 of 8 cognitive domains were significantly associated with eMJ. On sustained attention, visuospatial working memory, and executive sequencing, adolescents with eMJ showed less age-expected improved performance. In addition, first-degree relatives with eMJ were less improved on processing speed and executive reasoning than first-degree relatives without eMJ. In the birth cohort, greater intraindividual variability in reaction times (indicative of poorer sustained attention) was significantly associated with more frequent MJ use and with recreational use levels. Conclusions: Nonheavy MJ use disrupts normal adolescent maturation and compounds aberrant adolescent maturation associated with familial schizophrenia risk. These findings underscore the importance of reducing adolescent MJ access in the context of increased availability to high-potency MJ.

Epicosm-a framework for linking online social media in epidemiological cohorts.

MOTIVATION: Social media represent an unrivalled opportunity for epidemiological cohorts to collect large amounts of high-resolution time course data on mental health. Equally, the high-quality data held by epidemiological cohorts could greatly benefit social media research as a source of ground truth for validating digital phenotyping algorithms. However, there is currently a lack of software for doing this in a secure and acceptable manner. We worked with cohort leaders and participants to co-design an open-source, robust and expandable software framework for gathering social media data in epidemiological cohorts. IMPLEMENTATION: Epicosm is implemented as a Python framework that is straightforward to deploy and run inside a cohort's data safe haven. GENERAL FEATURES: The software regularly gathers Tweets from a list of accounts and stores them in a database for linking to existing cohort data. AVAILABILITY: This open-source software is freely available at [https://dynamicgenetics.github.io/Epicosm/].

Linking electronic mental healthcare and benefits records in South London: design, procedure and descriptive outcomes.

OBJECTIVES: To describe the process and outcomes of a data linkage between electronic secondary mental healthcare records from the South London and Maudsley (SLaM) NHS Foundation Trust with benefits records from the Department for Work and Pensions (DWP). We also describe the mental health and benefit profile of patients who were successfully linked. DESIGN: A deterministic linkage of routine records from health and welfare government service providers within a secure environment. SETTING AND PARTICIPANTS: Adults aged≥18 years who were referred to or accessed treatment at SLaM services between January 2007 and June 2019, including those who were treated as part of Improving Access to Psychological Therapies (IAPT) services between January 2008 and June 2019 (n=448 404). Benefits data from the DWP from January 2005 to June 2020. OUTCOME MEASURES: The linkage rate and associated sociodemographic, diagnostic and treatment factors. Recorded primary psychiatric diagnosis based on International Classification of Diseases (ICD)-10 codes and type of benefit receipt. RESULTS: A linkage rate of 92.3% was achieved. Women, younger patients and those from ethnic minority groups were less likely to be successfully linked. Patients who had subsequently died, had a recorded primary psychiatric diagnosis, had also engaged with IAPT and had a higher number of historical postcodes available were more likely to be linked. Overall, 83% of patients received benefits at some point between 2005 and 2020. Benefit receipt across the psychiatric diagnosis spectrum was high, over 80% across most ICD-10 codes. CONCLUSIONS: This data linkage is the first of its kind in the UK demonstrating the use of routinely collected mental health and benefits data. Benefit receipt was high among patients accessing SLaM services and varied by psychiatric diagnosis. Future areas of research are discussed, including exploring the effectiveness of interventions for helping people into work and the impact of benefit reforms.

Towards a standardised cross-sectoral data access agreement template for research: a core set of principles for data access within trusted research environments.

Introduction: Trusted Research Environments (TREs) are secure computing environments that provide access to data for approved researchers to use in studies that can save and improve lives. TREs rely on Data Access Agreements (DAAs) to bind researchers and their organisations to the terms and conditions of accessing the infrastructure and data use. However, DAAs can be overly lengthy, complex, and can contain outdated terms from historical data sharing agreements for physical exchange of data. This is often cited as a cause of significant delays to legal review and research projects starting. Objectives: The aim was to develop a standardised DAA optimised for data science in TREs across the UK and framed around the 'Five Safes framework' for trustworthy data use. The DAA is underpinned by principles of data access in TREs, the development of which is described in this paper. Methods: The Pan-UK Data Governance Steering Group of the UK Health Data Research Alliance led the development of a core set of data access principles. This was informed by a benchmarking exercise of DAAs used by established TREs and consultation with public members and stakeholders. Results: We have defined a core set of principles for TRE data access that can be mapped to a common set of DAA terms for UK-based TREs. Flexibility will be ensured by including terms specific to TREs or specific data/data owners in customisable annexes. Public views obtained through public involvement and engagement (PIE) activities are also reported. Conclusions: These principles provide the foundation for a standardised UK TRE DAA template, designed to support the growing ecosystem of TREs. By providing a familiar structure and terms, this template aims to build trust among data owners and the UK public and to provide clarity to researchers on their obligations to protect the data. Widespread adoption is intended to accelerate health data research by enabling faster approval of projects, ultimately enabling more timely and effective research.

Assessment of contact involvements and scrums in international rugby union match-play using video analysis and microsensor technology methods.

This study sought to assess the validity of contact involvement (CI) detection using microsensor technology (MST, Catapult Vector) within the context of a Tier One national rugby union (RU) squad, consisting of 44 players. Sensitivity of MST units to detect CI and scrums was assessed in eight test matches, by comparison with match data obtained by video analysis. This paper is the first to assess the sensitivity of MST to the full range of skilled CI which occur in RU, including evaluating "non-performance" collisions, such as incidental collisions or foul play. Sensitivity to tackles made (52.9-84.9%) and ruck hits (53.3-87.2%) was lower than previous research, although ball carries (71.9-93.5%) showed broadly similar sensitivity to established results. The sensitivity of the MST to detect scrums was substantially lower than previous findings, with large positional variation evident (51.4-91.5%). Further refinement of MST software should be considered in order to facilitate valid monitoring of RU performance and injury risk. An additional finding was that video analysis generally demonstrated satisfactory intrarater reliability. This result supports the use of video analysis as a reliable method of assessing RU performance, including CI.

Intellectual disability in the children of the Avon Longitudinal Study of Parents and Children (ALSPAC).

Background: Intellectual disability (ID) describes a neurodevelopmental condition involving impaired cognitive and functional ability. Here, we describe a multisource variable of ID using data from the Avon Longitudinal Study of Parents and Children (ALSPAC).  Methods: The multisource indicator variable for ID was derived from i) IQ scores less than 70 measured at age 8 and at age 15, ii) free text fields from parent reported questionnaires, iii) school reported provision of educational services for individuals with a statement of special educational needs for cognitive impairments, iv) from relevant READ codes contained in GP records, iv) international classification of disease diagnoses contained in electronic hospital records and hospital episode statistics and v) recorded interactions with mental health services for ID contained within the mental health services data set. A case of ID was identified if two or more sources indicated ID. A second indicator, labelled as "probable ID", was created by relaxing the cut off in IQ scores to be less than 85. An indicator variable for known causes of ID was also created to aid in aetiological studies where ID with a known cause may need to be excluded.  Results: 158 of 14,370 participants (1.10%) were indicated as having ID by two or more sources and 449 (3.12%) were indicated as having probable ID when the criteria for IQ scores was relaxed to less than 85. There were 476 participants (3.31%) with 1 or fewer sources of available information on ID; these participants had their multisource variable set to missing. The number of cases of ID with known cause was 31 (0.22% of the cohort, 19.6% of those with ID).   Conclusions: The multisource variable of ID can be used in future analyses on ID in ALSPAC children.

Does perceived wellness influence technical-tactical match performance? A study in youth international rugby using partial least squares correlation analysis.

The purpose of this study was to determine the relationship between matchday wellness status and a technical-tactical performance construct during rugby match-play. One hundred and thirty-three male rugby union players (73 forwards and 60 backs) from five under-18 national squads who participated in the under-18 Six Nations competition completed a subjective wellness questionnaire on each matchday morning. Players subjectively rated each item (sleep quality, fatigue, muscle soreness, stress and mood) on a five-point Likert scale to calculate their daily wellness status (i.e. difference between matchday and baseline perceived wellness). Technical-tactical performance during match-play was quantified by coding individual key performance indicators (e.g. number of carries, number of tackles). Partial least squares correlation analysis (PLSCA) was employed to compute the latent variables of perceived wellness status (X matrix) and technical-tactical performance (Y matrix) for each player observation (n = 271). The latent variables are a construct of each variable group, enabling higher dimensional data to be visualised more simply. Linear mixed-effect models were later conducted to assess the relationships between the latent variables. The effect of perceived wellness status on technical-tactical performance was statistically significant in forwards (p = .042), not statistically significant in backs (p = .120) and accounted for 4.9% and 1.9% variance in the technical-tactical performance construct, respectively. The findings of this study suggest that perceived wellness status can influence technical-tactical match performance, but the practical significance of these findings should be interpreted with caution given the amount of variance in technical-tactical performance accounted by the models.