Developing survey weights to ensure representativeness in a national, matched cohort study: results from the children and young people with Long Covid (CLoCk) study.

BACKGROUND: Findings from studies assessing Long Covid in children and young people (CYP) need to be assessed in light of their methodological limitations. For example, if non-response and/or attrition over time systematically differ by sub-groups of CYP, findings could be biased and any generalisation limited. The present study aimed to (i) construct survey weights for the Children and young people with Long Covid (CLoCk) study, and (ii) apply them to published CLoCk findings showing the prevalence of shortness of breath and tiredness increased over time from baseline to 12-months post-baseline in both SARS-CoV-2 Positive and Negative CYP. METHODS: Logistic regression models were fitted to compute the probability of (i) Responding given envisioned to take part, (ii) Responding timely given responded, and (iii) (Re)infection given timely response. Response, timely response and (re)infection weights were generated as the reciprocal of the corresponding probability, with an overall 'envisioned population' survey weight derived as the product of these weights. Survey weights were trimmed, and an interactive tool developed to re-calibrate target population survey weights to the general population using data from the 2021 UK Census. RESULTS: Flexible survey weights for the CLoCk study were successfully developed. In the illustrative example, re-weighted results (when accounting for selection in response, attrition, and (re)infection) were consistent with published findings. CONCLUSIONS: Flexible survey weights to address potential bias and selection issues were created for and used in the CLoCk study. Previously reported prospective findings from CLoCk are generalisable to the wider population of CYP in England. This study highlights the importance of considering selection into a sample and attrition over time when considering generalisability of findings.

Examining the quality and population representativeness of linked survey and administrative data: guidance and illustration using linked 1958 National Child Development Study and Hospital Episode Statistics data.

Introduction: Recent years have seen an increase in linkages between survey and administrative data. It is important to evaluate the quality of such data linkages to discern the likely reliability of ensuing research. Evaluation of linkage quality and bias can be conducted using different approaches, but many of these are not possible when there is a separation of processes for linkage and analysis to help preserve privacy, as is typically the case in the UK (and elsewhere). Objectives: We aimed to describe a suite of generalisable methods to evaluate linkage quality and population representativeness of linked survey and administrative data which remain tractable when users of the linked data are not party to the linkage process itself. We emphasise issues particular to longitudinal survey data throughout. Methods: Our proposed approaches cover several areas: i) Linkage rates, ii) Selection into response, linkage consent and successful linkage, iii) Linkage quality, and iv) Linked data population representativeness. We illustrate these methods using a recent linkage between the 1958 National Child Development Study (NCDS; a cohort following an initial 17,415 people born in Great Britain in a single week of 1958) and Hospital Episode Statistics (HES) databases (containing important information regarding admissions, accident and emergency attendances and outpatient appointments at NHS hospitals in England). Results: Our illustrative analyses suggest that the linkage quality of the NCDS-HES data is high and that the linked sample maintains an excellent level of population representativeness with respect to the single dimension we assessed. Conclusions: Through this work we hope to encourage providers and users of linked data resources to undertake and publish thorough evaluations. We further hope that providing illustrative analyses using linked NCDS-HES data will improve the quality and transparency of research using this particular linked data resource.

Longitudinal pathways between childhood BMI, body dissatisfaction, and adolescent depression: an observational study using the UK Millenium Cohort Study.

BACKGROUND: Globally, more adolescents are having depressive symptoms than in the past. High BMI is a risk factor for depressive symptoms, potentially acting via increased body dissatisfaction. Robust longitudinal evidence of these associations could help to inform preventive interventions, but such evidence remains scarce. We investigated the longitudinal associations between BMI at age 7 years and depressive symptoms at age 14 years (objective 1), BMI at age 7 years and body dissatisfaction at age 11 years (objective 2), and body dissatisfaction at age 11 years and depression at age 14 years (objective 3). We also investigated the extent to which body dissatisfaction mediated the association between BMI and depressive symptoms (objective 4). METHODS: This study used data from the Millennium Cohort Study, a representative longitudinal general population cohort of UK children born between Sept 1, 2000, and Jan 11, 2002. We used univariable and multivariable linear regression models to investigate the associations in objectives 1-3 adjusting for a range of child-level and family-level confounders. For mediation analyses we used non-parametric g-formula (objective 4). We reported stratified results in presence of sex differences. All analyses were based on participants with complete BMI data and imputed confounders and outcomes. FINDINGS: Our sample included 13 135 participants. Of these, 6624 (50·4%) were male participants and 6511 (49·6%) were female participants; 11 096 (84·4%) were of White ethnicity and 2039 (15·6%) were from a minority ethnic background. At baseline, mean age was 7·2 years (SD 0·25, range 6·3-8·3). In multivariable models, an SD increase in BMI at age 7 years was associated with greater depressive symptoms at age 14 years (estimated regression coefficient [coeff]: 0·30, 95% CI 0·17-0·43) and greater body dissatisfaction at age 11 years (coeff 0·15, 0·12-0·18). Greater body dissatisfaction at age 11 years was associated with higher depressive symptoms at age 14 years (coeff 0·60, 0·52-0·68). All these associations were twice as large in girls as in boys. Body dissatisfaction explained 43% of the association between BMI and depression in girls. INTERPRETATION: Our findings bear relevance for interventions aimed at reducing weight in childhood and reducing body dissatisfaction. Implementation of evidence-based body image interventions and identification of drivers of weight stigma should be key public health priorities. Interventions aiming to reduce weight in childhood need to avoid increasing body dissatisfaction and should target environmental drivers of weight rather than individuals. FUNDING: Wellcome Trust; The Royal Society; Economic and Social Research Council; and the National Institute for Health and Care Research.