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Non-response to surveys is a common problem; even more so during the COVID-19 pandemic with social distancing measures challenging data collection. As respondents often differ from non-respondents, this can introduce bias. The goal of the current study was to see if we can reduce bias and restore sample representativeness in a series of COVID-19 surveys embedded within five UK cohort studies by using the rich data available from previous waves of data collection. Three surveys were conducted during the pandemic across five UK cohorts: National Survey of Health and Development (NSHD, born 1946), 1958 National Child Development Study (NCDS), 1970 British Cohort Study (BCS70), Next Steps (born 1989-90) and Millennium Cohort Study (MCS, born 2000-02). Response rates in the COVID-19 surveys were lower compared to previous waves, especially in the younger cohorts. We identified bias due to systematic non-response in several variables, with more respondents in the most advantaged social class and among those with higher childhood cognitive ability. Making use of the rich data available pre-pandemic in these longitudinal studies, the application of non-response weights and multiple imputation was successful in reducing bias in parental social class and childhood cognitive ability, nearly eliminating it for the former. Surveys embedded within existing cohort studies offer a clear advantage over cross-sectional samples collected during the pandemic in terms of their ability to mitigate selection bias. This will enhance the quality and reliability of future research studying the medium and long-term effects of the pandemic., Competing Interests: Declarations. Ethics approval: All relevant ethical guidelines have been followed, and ethics committee approvals have been obtained. NCDS, BCS, Next Steps and MCS are publicly available on UK Data Service. NSHD data are available on request to the NSHD Data Sharing Committee. Interested researchers can apply to access the NSHD data via a standard application procedure. As part of a joint COVID-19 survey project between NSHD, NCDS, BCS, Next Steps and MCS we were provided with a basic set of NSHD variables which can be used for COVID-19 survey related research (such as the present paper). Informed consent: Informed written consent was obtained from all individual participants and their parents included in the study. Competing interests: The authors have no relevant financial or non-financial interests to disclose., (© 2024. The Author(s).)

The frequency of, and risk factors for, long COVID are unclear among community-based individuals with a history of COVID-19. To elucidate the burden and possible causes of long COVID in the community, we coordinated analyses of survey data from 6907 individuals with self-reported COVID-19 from 10 UK longitudinal study (LS) samples and 1.1 million individuals with COVID-19 diagnostic codes in electronic healthcare records (EHR) collected by spring 2021. Proportions of presumed COVID-19 cases in LS reporting any symptoms for 12+ weeks ranged from 7.8% and 17% (with 1.2 to 4.8% reporting debilitating symptoms). Increasing age, female sex, white ethnicity, poor pre-pandemic general and mental health, overweight/obesity, and asthma were associated with prolonged symptoms in both LS and EHR data, but findings for other factors, such as cardio-metabolic parameters, were inconclusive., (© 2022. The Author(s).)

Objective: Non-response is unavoidable in longitudinal surveys. The consequences are lower statistical power and the potential for bias. We implemented a systematic data-driven approach to identify predictors of non-response in the National Child Development Study (NCDS; 1958 British birth cohort). Such variables can help make the missing at random assumption more plausible, which has implications for the handling of missing data STUDY DESIGN AND SETTING: We identified predictors of non-response using data from the 11 sweeps (birth to age 55) of the NCDS (n = 17,415), employing parametric regressions and the LASSO for variable selection., Results: Disadvantaged socio-economic background in childhood, worse mental health and lower cognitive ability in early life, and lack of civic and social participation in adulthood were consistently associated with non-response. Using this information, along with other data from NCDS, we were able to replicate the "population distribution" of educational attainment and marital status (derived from external data), and the original distributions of key early life characteristics., Conclusion: The identified predictors of non-response have the potential to improve the plausibility of the missing at random assumption. They can be straightforwardly used as "auxiliary variables" in analyses with principled methods to reduce bias due to missing data., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objectives: We aim to examine the relative contributions of pathways from middle childhood/adolescence to mid-life well-being, health and cognition, in the context of family socio-economic status (SES) at birth, educational achievement and early-adulthood SES. Our approach is largely exploratory, suspecting that the strongest mediators between childhood circumstances and mid-life physical and emotional well-being may be cognitive performance during school years, material and behavioural difficulties, and educational achievement. We also explore whether the effects of childhood circumstances on mid-life physical and emotional well-being differ between men and women., Setting/participants: Data were from the National Child Development Study, a fully-representative British birth cohort sample of 17 415 people born in 1 week in 1958., Primary/secondary Outcome Measures: Our four primary mid-life outcome measures are: cognitive performance, physical and emotional well-being and quality of life. Our intermediate adult outcomes are early-adulthood social class and educational/vocational qualifications., Results: Using structural equation modelling, we explore numerous pathways through childhood and early adulthood which are significantly linked to our outcomes. We specifically examine the mediating effects of the following: cognitive ability at ages 7, 11 and 16 years; childhood psychological issues; family material difficulties at age 7 years: housing, unemployment, finance; educational/vocational qualifications and social class position at age 42 years.We find that social class at birth has a strong indirect effect on the age 50 outcomes via its influence on cognitive performance in childhood and adolescence, educational attainment and mid-life social class position, together with small direct effects on qualifications and social class position at age 42 years. Teenage cognitive performance has a strong positive effect on later physical health for women, while educational/vocational qualifications have a stronger positive effect on emotional well-being for men., Conclusion: Our findings provide an understanding of the legacy of early life on multiple aspects of mid-life health, well-being, cognition and quality of life, showing stronger mediated links for men from childhood social class position to early adult social class position. The observed effect of qualifications supports those arguing that education is positively associated with subsequent cognitive functioning., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Introduction: There is increasing interest in the clustering of risk behaviours in adolescence. However, few studies have examined what clusters of risk behaviours exist among adolescents, their early-life predictors, and their associations with later health., Methods: We analysed data derived from 8754 participants (women 53.3%) in the 1970 British Cohort Study. Latent class analysis was used to identify clusters of risk behaviours at age 16. Regression modelling was then used to examine predictors of clusters and their consequences of risk behaviours and health outcomes at age 42., Results: We identified two latent classes: a risky-behaviour (men: 20.0%, women: 23.6%) and less-risky-behaviour class. Among men, those in the risky-behaviour class were more likely to report smoking, multiple binge drinking, sexual debut before 16, involvement in fights and delinquency than were women. Membership in risky-behaviour class was mainly predicted by sociodemographic and parental risk behaviours and monitoring. The risky-behaviour class at age 16 was associated with the following outcome age 42: smoking status (more strongly among women), excessive alcohol consumption (more strongly among men), worse self-rated health (more strongly among men), and psychological distress (only among women)., Conclusions: Engagement in multiple risk behaviours in adolescence is an important driver of health inequalities later in life. Early life intervention, for example via school-based interventions, may be warranted for favourable lifelong health., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Some studies have indicated that social engagement is associated with better cognitive outcomes. This study aimed to investigate associations between life-course social engagement (civic participation) and cognitive status at age 50, adjusting for social networks and support, behavioural, health, social and socio-economic characteristics., Methods: The vehicle for the study was the National Child Development Study (1958 Birth Cohort Study), which is a general population sample in England, Scotland and Wales (9119: 4497 men and 4622 women) participating in nationally representative, prospective birth cohort surveys. The primary outcome variable was cognitive status at age 50, measured by memory test (immediate and delayed word recall test) and executive functioning test (word fluency and letter cancelation tests). The influence of hypothesised predictor variables was analysed using linear multiple regression analysis., Results: Cognitive ability at age 11 (β = 0.19;95% CI = 0.17 to 0.21), participation in civic activities at ages 33 (0.12; 0.02 to 0.22) and 50 (0.13; 0.07 to 0.20), frequent engagement in physical activity (sport) (β from 0.15 to 0.18), achieving higher level qualifications (β from 0.23 to 1.08), and female gender (β = 0.49;95% CI = 0.38 to 0.60) were positively, significantly and independently associated with cognitive status at age 50. Having low socio-economic status at ages 11 (β from -0.22 to -0.27) and 42 (β from -0.28 to -0.38), and manifesting worse mental well-being at age 42 (β = -0.18; 95% CI = -0.33 to -0.02) were inversely associated with cognitive status at age 50. The proportion of explained variance in the multiple regression model (18%), while modest, is impressive given the multi-faceted causal nature of cognitive status., Conclusions: The results indicate that modest associations between adult social engagement and cognitive function at age 50 persist after adjusting for covariates which included health, socio-economic status and gender, supporting theories of neuroplasticity. In addition to the continuing emphasis on physical activity, the encouragement of civic participation, at least as early as mid-life, should be a targeted policy to potentially promote and protect cognitive function in later mid-life.

Purpose: To examine the associations between social class at ages 0, 5, 10, 30, and 34 years and physical activity at age 34 years using a novel approach to analysis of life course data., Methods: We used structural equation modeling to compare three competing models in life course epidemiology: the accumulation of risk model with additive effects, the accumulation of risk model with trigger effect, and the critical period model. Data were from a nationally representative prospective cohort of 16,571 British men and women born in 1970. Outcomes were physical activity during leisure time, during transports, and at work., Results: For all three domains of physical activity, for men and women, the accumulation of risk model with additive effects fit the data best. In this model, social class at ages 0, 5, 10, 30, and 34 years were associated with physical activity at age 34 years, although the magnitude and the direction of the associations for social class at each age varied by physical activity outcome and by sex., Conclusions: Structural equation modeling appears to be a helpful tool in selecting among competing models in life course epidemiology., (Crown Copyright © 2014. Published by Elsevier Inc. All rights reserved.)

Background: Geographical variation in mortality is influenced by factors operating in early life and in adulthood. The relative contributions of these factors may be examined by comparing the extent to which adult mortality is related to places of residence in early life and at death. We describe a population-based case-control design, in which all deaths are used as cases and the Office for National Statistics (ONS) Longitudinal Study (LS) survivors are used as controls., Methods: Cases were all deaths from stomach cancer and stroke in England and Wales 1993-1995 amongst people born between January 1930 and September 1939 and for whom place of enumeration in 1939 could be imputed from the first three characters of their National Health Service number. Controls were all LS members born in the same period, enumerated in the 1991 census, resident in England and Wales in mid-1994 and for whom place of enumeration in 1939 could be similarly imputed. Logistic regression was used, adjusting for birth year, sex and social class. A previous mapping exercise by ONS generated comparable geographical units (counties) for 1939 enumeration and area of residence in 1991 or at death. 'Non-migrant' (i.e. 1939 'county' the same as county in 1991 or at death) case:control ratios were calculated to indicate background mortality risk in counties, with adjustment for imprecision using Bayesian smoothing methods. These ratios were then used in modelling risk for inter-county migrants., Results: There were 2590 stomach cancer and 7778 stroke deaths and 28,400 men and 28,180 women as controls. For men, 64%, 61% and 67% of stomach cancer deaths, stroke deaths and controls respectively could be assigned a county of enumeration in 1939. The corresponding percentages for women were 76%, 72% and 75%. For stomach cancer, after adjustment for county of enumeration in 1939, a significant association with the non-migrant case:control ratio for county of residence in 1991 or at death was observed (P= 0.010), indicating an association between current area of residence and stomach cancer mortality. There was no evidence of an independent effect of county of enumeration in 1939. For stroke, there was a highly significant trend in relation to 1939 county (P = 0.0004)and a less significant association with county of residence in 1991 or at death(P = 0.016)., Conclusions: The method described is able to detect the effect of place of residence in early life on geographical variation in adult mortality and will be useful for investigating specific characteristics of areas of enumeration in 1939 in relation to subsequent risk of mortality from a range of diseases.