Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies

BACKGROUND: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. METHODS: This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5-40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. RESULTS: Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. CONCLUSIONS: LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software

Gene-environment correlations and causal effects of childhood maltreatment on physical and mental health: a genetically informed approach.

BACKGROUND: Childhood maltreatment is associated with poor mental and physical health. However, the mechanisms of gene-environment correlations and the potential causal effects of childhood maltreatment on health are unknown. Using genetics, we aimed to delineate the sources of gene-environment correlation for childhood maltreatment and the causal relationship between childhood maltreatment and health. METHODS: We did a genome-wide association study meta-analysis of childhood maltreatment using data from the UK Biobank (n=143 473), Psychiatric Genomics Consortium (n=26 290), Avon Longitudinal Study of Parents and Children (n=8346), Adolescent Brain Cognitive Development Study (n=5400), and Generation R (n=1905). We included individuals who had phenotypic and genetic data available. We investigated single nucleotide polymorphism heritability and genetic correlations among different subtypes, operationalisations, and reports of childhood maltreatment. Family-based and population-based polygenic score analyses were done to elucidate gene-environment correlation mechanisms. We used genetic correlation and Mendelian randomisation analyses to identify shared genetics and test causal relationships between childhood maltreatment and mental and physical health conditions. FINDINGS: Our meta-analysis of genome-wide association studies (N=185 414) identified 14 independent loci associated with childhood maltreatment (13 novel). We identified high genetic overlap (genetic correlations 0·24-1·00) among different maltreatment operationalisations, subtypes, and reporting methods. Within-family analyses provided some support for active and reactive gene-environment correlation but did not show the absence of passive gene-environment correlation. Robust Mendelian randomisation suggested a potential causal role of childhood maltreatment in depression (unidirectional), as well as both schizophrenia and ADHD (bidirectional), but not in physical health conditions (coronary artery disease, type 2 diabetes) or inflammation (C-reactive protein concentration). INTERPRETATION: Childhood maltreatment has a heritable component, with substantial genetic correlations among different operationalisations, subtypes, and retrospective and prospective reports of childhood maltreatment. Family-based analyses point to a role of active and reactive gene-environment correlation, with equivocal support for passive correlation. Mendelian randomisation supports a (primarily bidirectional) causal role of childhood maltreatment on mental health, but not on physical health conditions. Our study identifies research avenues to inform the prevention of childhood maltreatment and its long-term effects. FUNDING: Wellcome Trust, UK Medical Research Council, Horizon 2020, National Institute of Mental Health, and National Institute for Health Research Biomedical Research Centre.This work was supported by the Wellcome Trust (Grant refs: 214322/Z/18/Z, 104036/Z/14/Z, 204623/Z/16/Z, and 217065/Z/19/Z). VW was funded by the Bowring Research Fellowship from St. Catharine’s College, Cambridge and Wellcome Trust Collaborative Award (Grant Ref: 214322/Z/18/Z). ASFK and AM are supported by Wellcome Trust Grant 104036/Z/14/Z. ASFK is also supported by an ESRC Postdoctoral Fellowship (Grant ref: ES/V011650/1). ML is supported by the scholarship from the China Scholarship Council (No. 201706990036). The work of CC has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement No 707404 and grant agreement No 848158 (EarlyCause Project). MHvIJ is supported by the Dutch Ministry of Education, Culture, and Science and the Netherlands Organization for Scientific Research (NWO grant No. 024.001.003, Consortium on Individual Development) and by a Spinoza Prize of the Netherlands Organization for Scientific Research. HMS and MRM are supported by the Medical Research Council and the University of Bristol (MC_UU_00011/7) and by the National Institute for Health Research (NIHR) Biomedical Research Centre at the University Hospitals Bristol National Health Service Foundation Trust and the University of Bristol. HMS is also supported by the European Research Council (Grant ref: 758813 MHINT). CMN is supported by the National Institute for Mental Health NIMH R01MH106595 and the Center of Excellence for Stress and Mental Health (CESAMH), Veterans Affairs San Diego. AJG and SB are supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant number 204623/Z/16/Z). TMM and RB are supported by the NIMH (R01MH117014, TMM; K23MH120437, RB).The research was conducted in association with the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, and the NIHR Collaboration for Leadership in Applied Health Research and Care East of England at Cambridgeshire and Peterborough NHS Foundation Trust. The views expressed are those of the author(s) and not necessarily those of the National Health Service, the NIHR, or the Department of Health and Social Care. This research was possible due to two applications to the UK Biobank: Projects 20904 and 23787. This research was co-funded by the NIHR Cambridge Biomedical Research Centre and a Marmaduke Sheild grant. The UK Medical Research Council and Wellcome (Grant Ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf). We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The study website contains details of all data available through a fully searchable data dictionary (http://www.bristol.ac.uk/alspac/researchers/our-data/). Part of this data was collected using REDCap, see the REDCap website for details https://projectredcap.org/resources/citations/). The first phase of the Generation R Study is made possible by financial support from the Erasmus Medical Centre, Rotterdam; the Erasmus University Rotterdam; ZonMw; the Netherlands Organization for Scientific Research (NWO); and the Ministry of Health, Welfare and Sport. The authors gratefully acknowledge the contribution of all children and parents, general practitioners, hospitals, midwives and pharmacies involved in the Generation R Study. The Generation R Study is conducted by the Erasmus Medical Center in close collaboration with the School of Law and Erasmus School of Social and Behavioural Sciences at Erasmus University Rotterdam; the Municipal Health Service Rotterdam area, Rotterdam; the Rotterdam Homecare Foundation, Rotterdam; and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR-MDC), Rotterdam

Maternal postnatal depression and offspring depression at age 24 years in a UK-birth cohort: the mediating role of maternal nurturing behaviours concerning feeding, crying and sleeping

Background: Maternal postnatal depression (PND) is a risk factor for offspring depression in adulthood. However, few longitudinal studies have examined the role of maternal nurturing parenting behaviours in the association between maternal PND and offspring depression in adulthood. Methods: We examined pathways from maternal PND measured using self-reported Edinburgh Postnatal Depression Scale at 8 weeks to offspring ICD-10 depression diagnosed using the Clinical Interview Schedule-Revised computerised assessment at 24 years through maternal-reported nurturing behaviours concerning feeding, sleeping and crying measured from pregnancy to age 3 years 6 months in 5,881 members of the UK-based birth cohort study, the Avon Longitudinal Study of Parents and Children. Results: The fully adjusted model revealed an indirect effect from PND to adult offspring depression through the combination of all parenting factors (probit regression coefficient [B]=0.038, 95% confidence interval [CI] 0.005, 0.071); however, there was no evidence of a direct effect from early maternal PND to offspring depression once the indirect effect via parenting factors was accounted for (B=0.009, 95%CI -0.075, 0.093). Specificity analyses revealed indirect effects through maternal worries about feeding (B=0.019, 95%CI 0.003, 0.035, p=0.010) and maternal perceptions and responses to crying (B=0.018, 95%CI 0.004, 0.032, p=0.012). Conclusions: The adverse impact of maternal PND on offspring depression in early adulthood was explained by maternal nurturing behaviours concerning feeding, crying and sleeping in early childhood. Residual confounding and measurement error likely limit reliable conclusions. If found causal, interventions providing support to reduce worries around maternal nurturing behaviours and treating depression could reduce adverse outcomes in adult offspring of depressed mothers

Psychological Distress Before and During the COVID-19 Pandemic Among Adults in the United Kingdom Based on Coordinated Analyses of 11 Longitudinal Studies

Importance: How population mental health has evolved across the COVID-19 pandemic under varied lockdown measures is poorly understood, and the consequences for health inequalities are unclear. Objective: To investigate changes in mental health and sociodemographic inequalities from before and across the first year of the COVID-19 pandemic in 11 longitudinal studies. Design, Setting, and Participants: This cohort study included adult participants from 11 UK longitudinal population-based studies with prepandemic measures of psychological distress. Analyses were coordinated across these studies, and estimates were pooled. Data were collected from 2006 to 2021. Exposures: Trends in the prevalence of poor mental health were assessed in the prepandemic period (time period 0 [TP 0]) and at 3 pandemic TPs: 1, initial lockdown (March to June 2020); 2, easing of restrictions (July to October 2020); and 3, a subsequent lockdown (November 2020 to March 2021). Analyses were stratified by sex, race and ethnicity, education, age, and UK country. Main Outcomes and Measures: Multilevel regression was used to examine changes in psychological distress from the prepandemic period across the first year of the COVID-19 pandemic. Psychological distress was assessed using the 12-item General Health Questionnaire, the Kessler 6, the 9-item Malaise Inventory, the Short Mood and Feelings Questionnaire, the 8-item or 9-item Patient Health Questionnaire, the Hospital Anxiety and Depression Scale, and the Centre for Epidemiological Studies–Depression across different studies. Results: In total, 49 993 adult participants (12 323 [24.6%] aged 55-64 years; 32 741 [61.2%] women; 4960 [8.7%] racial and ethnic minority) were analyzed. Across the 11 studies, mental health deteriorated from prepandemic scores across all 3 pandemic periods, but there was considerable heterogeneity across the study-specific estimated effect sizes (pooled estimate for TP 1: standardized mean difference [SMD], 0.15; 95% CI, 0.06-0.25; TP 2: SMD, 0.18; 95% CI, 0.09-0.27; TP 3: SMD, 0.21; 95% CI, 0.10-0.32). Changes in psychological distress across the pandemic were higher in women (TP 3: SMD, 0.23; 95% CI, 0.11, 0.35) than men (TP 3: SMD, 0.16; 95% CI, 0.06-0.26) and lower in individuals with below–degree level education at TP 3 (SMD, 0.18; 95% CI, 0.06-0.30) compared with those who held degrees (SMD, 0.26; 95% CI, 0.14-0.38). Increased psychological distress was most prominent among adults aged 25 to 34 years (SMD, 0.49; 95% CI, 0.14-0.84) and 35 to 44 years (SMD, 0.35; 95% CI, 0.10-0.60) compared with other age groups. No evidence of changes in distress differing by race and ethnicity or UK country were observed. Conclusions and Relevance: In this study, the substantial deterioration in mental health seen in the UK during the first lockdown did not reverse when lockdown lifted, and a sustained worsening was observed across the pandemic period. Mental health declines have been unequal across the population, with women, those with higher degrees, and those aged 25 to 44 years more affected than other groups

Living alone and mental health: parallel analyses in UK longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic

BACKGROUND: People who live alone experience greater levels of mental illness; however, it is unclear whether the COVID-19 pandemic had a disproportionately negative impact on this demographic. OBJECTIVE: To describe the mental health gap between those who live alone and with others in the UK prior to and during the COVID-19 pandemic. METHODS: Self-reported psychological distress and life satisfaction in 10 prospective longitudinal population surveys (LPSs) assessed in the nearest pre-pandemic sweep and three periods during the pandemic. Recorded diagnosis of common and severe mental illnesses between March 2018 and January 2022 in electronic healthcare records (EHRs) within the OpenSAFELY-TPP. FINDINGS: In 37 544 LPS participants, pooled models showed greater psychological distress (standardised mean difference (SMD): 0.09 (95% CI: 0.04; 0.14); relative risk: 1.25 (95% CI: 1.12; 1.39)) and lower life satisfaction (SMD: −0.22 (95% CI: −0.30; −0.15)) for those living alone pre-pandemic. This gap did not change during the pandemic. In the EHR analysis of c.16 million records, mental health conditions were more common in those who lived alone (eg, depression 26 (95% CI: 18 to 33) and severe mental illness 58 (95% CI: 54 to 62) more cases more per 100 000). For common mental health disorders, the gap in recorded cases in EHRs narrowed during the pandemic. CONCLUSIONS: People living alone have poorer mental health and lower life satisfaction. During the pandemic, this gap in self-reported distress remained; however, there was a narrowing of the gap in service use. CLINICAL IMPLICATIONS: Greater mental health need and potentially greater barriers to mental healthcare access for those who live alone need to be considered in healthcare planning

Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors

SARS-CoV-2 antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. From cross-sectional antibody testing of 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies (jointly in April-May 2021, and TwinsUK only in November 2021-January 2022), we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables. Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had 3-fold greater odds of SARS-CoV-2 infection over the next six to nine months, compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK "Shielded Patient List" had consistently greater odds (2 to 4-fold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations. These findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies

Living alone and mental health: parallel analyses in UK longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic

Background: People who live alone experience greater levels of mental illness; however, it is unclear whether the COVID-19 pandemic had a disproportionately negative impact on this demographic. Objective: To describe the mental health gap between those who live alone and with others in the UK prior to and during the COVID-19 pandemic. Methods: Self-reported psychological distress and life satisfaction in 10 prospective longitudinal population surveys (LPSs) assessed in the nearest pre-pandemic sweep and three periods during the pandemic. Recorded diagnosis of common and severe mental illnesses between March 2018 and January 2022 in electronic healthcare records (EHRs) within the OpenSAFELY-TPP. Findings: In 37 544 LPS participants, pooled models showed greater psychological distress (standardised mean difference (SMD): 0.09 (95% CI: 0.04; 0.14); relative risk: 1.25 (95% CI: 1.12; 1.39)) and lower life satisfaction (SMD: −0.22 (95% CI: −0.30; −0.15)) for those living alone pre-pandemic. This gap did not change during the pandemic. In the EHR analysis of c.16 million records, mental health conditions were more common in those who lived alone (eg, depression 26 (95% CI: 18 to 33) and severe mental illness 58 (95% CI: 54 to 62) more cases more per 100 000). For common mental health disorders, the gap in recorded cases in EHRs narrowed during the pandemic. Conclusions: People living alone have poorer mental health and lower life satisfaction. During the pandemic, this gap in self-reported distress remained; however, there was a narrowing of the gap in service use. Clinical implications: Greater mental health need and potentially greater barriers to mental healthcare access for those who live alone need to be considered in healthcare planning

Genome-wide Association Study of Long COVID

SummaryInfections can lead to persistent or long-term symptoms and diseases such as shingles after varicella zoster, cancers after human papillomavirus, or rheumatic fever after streptococcal infections1, 2. Similarly, infection by SARS-CoV-2 can result in Long COVID, a condition characterized by symptoms of fatigue and pulmonary and cognitive dysfunction3–5. The biological mechanisms that contribute to the development of Long COVID remain to be clarified. We leveraged the COVID-19 Host Genetics Initiative6, 7to perform a genome-wide association study for Long COVID including up to 6,450 Long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We identified the first genome-wide significant association for Long COVID at theFOXP4locus.FOXP4has been previously associated with COVID-19 severity6, lung function8, and cancers9, suggesting a broader role for lung function in the pathophysiology of Long COVID. While we identify COVID-19 severity as a causal risk factor for Long COVID, the impact of the genetic risk factor located in theFOXP4locus could not be solely explained by its association to severe COVID-19. Our findings further support the role of pulmonary dysfunction and COVID-19 severity in the development of Long COVID.</jats:p

Disordered eating and self-harm as risk factors for poorer mental health during the COVID-19 pandemic: a UK-based birth cohort study

Background: Young adults and especially those with pre-existing mental health conditions, such as disordered eating and self-harm, appear to be at greater risk of developing metal health problems during the COVID-19 pandemic. However, it is unclear whether this increased risk is affected by any changes in lockdown restrictions, and whether any lifestyle changes could moderate this increased risk. Methods: In a longitudinal UK-based birth cohort (The Avon Longitudinal Study of Parents and Children, ALSPAC) we assessed the relationship between pre-pandemic measures of disordered eating and self-harm and mental health during the COVID-19 pandemic in 2657 young adults. Regression models examined the relationship between self-reported disordered eating, self-harm, and both disordered eating and self-harm at age 25 years and depressive symptoms, anxiety symptoms and mental wellbeing during a period of eased restrictions in the COVID-19 pandemic (May–July 2020) when participants were aged 27–29 years. Analyses were adjusted for sex, questionnaire completion date, pre-pandemic socioeconomic disadvantage and pre-pandemic mental health and wellbeing. We also examined whether lifestyle changes (sleep, exercise, alcohol, visiting green space, eating, talking with family/friends, hobbies, relaxation) in the initial UK lockdown (April–May 2020) moderated these associations. Results: Pre-existing disordered eating, self-harm and comorbid disordered eating and self-harm were all associated with the reporting of a higher frequency of depressive symptoms and anxiety symptoms, and poorer mental wellbeing during the pandemic compared to individuals without disordered eating and self-harm. Associations remained when adjusting for pre-pandemic mental health measures. There was little evidence that interactions between disordered eating and self-harm exposures and lifestyle change moderators affected pandemic mental health and wellbeing. Conclusions: Young adults with pre-pandemic disordered eating, self-harm and comorbid disordered eating and self-harm were at increased risk for developing symptoms of depression, anxiety and poor mental wellbeing during the COVID-19 pandemic, even when accounting for pre-pandemic mental health. Lifestyle changes during the pandemic do not appear to alter this risk. A greater focus on rapid and responsive service provision is essential to reduce the impact of the pandemic on the mental health of these already vulnerable individuals. Plain English summary: The aim of this project was to explore the mental health of young adults with disordered eating behaviours (such as fasting, vomiting/taking laxatives, binge-eating and excessive exercise) and self-harm during the COVID-19 pandemic. We analysed data from an established study that has followed children from birth (in 1991 and 1992) up to present day, including during the pandemic when participants were 28 years old. We looked at the relationship between disordered eating and/or self-harm behaviours from before the pandemic and mental health problems (symptoms of depression and anxiety) and mental wellbeing during the pandemic. We also explored whether there were any lifestyle changes (such as changes in sleep, exercise, visiting green space) that might be linked to better mental health and wellbeing in young adults with disordered eating and self-harm. We found that young adults with prior disordered eating and/or self-harm had more symptoms of depression and anxiety, and worse mental wellbeing than individuals without prior disordered eating or self-harm. However, lifestyle changes did not appear to affect mental health and wellbeing in these young adults. Our findings suggest that people with a history of disordered eating and/or self-harm were at high risk for developing mental health problems during the pandemic, and they will need help from mental health services

Depressive symptoms and academic achievement in UK adolescents: a cross-lagged analysis with genetic covariates

Background: The relationship between adolescent depressive symptoms and academic achievement remains poorly understood. The aim of this study was to help clarify the nature and directionality of this association. Methods: We used a sample of 13,599 British adolescents (main sample of N=3,809 participants). We fitted cross-lagged panel models using four repeated measures of self-reported depressive symptoms and four measures of academic achievement based on British national records between 11-18 years, separately for male and female adolescents and considering polygenic risk scores (PRS) for educational attainment and depression, alongside other child and parental covariates. Results: We found evidence of an overall negative association that was stronger in boys (R=-0.21, 95% CI -0.31 to -0.11) than in girls (-0.13, -0.31 to 0.05). Higher depressive symptoms were associated with lower academic achievement at a later stage up to the end of compulsory education (16 years), when the direction of the association reversed, although girls with lower achievement also appeared vulnerable to depressive symptoms at previous stages. The genetic variables derived for this study showed stronger associations for academic achievement, but the PRS for depression also showed a negative association with academic achievement in girls. Child intelligence quotient and peer victimization also showed relevant associations. Limitations: Observational design, variation around measurement times, missing data. Conclusions: Depressive symptoms and academic achievement should be considered jointly when designing school-based programmes for children and adolescents, alongside gender, child ability and school experience. Including genetic information in research can help to disentangle average from time-varying effects