Effects of state anxiety on gait:a 7.5% carbon dioxide challenge study

We used the 7.5% carbon dioxide (CO(2)) model of anxiety induction to investigate the effects of state anxiety on normal gait and gait when navigating an obstacle. Healthy volunteers (n = 22) completed a walking task during inhalations of 7.5% CO(2) and medical air (placebo) in a within-subjects design. The order of inhalation was counterbalanced across participants and the gas was administered double-blind. Over a series of trials, participants walked the length of the laboratory, with each trial requiring participants to navigate through an aperture (width adjusted to participant size), with gait parameters measured via a motion capture system. The main findings were that walking speed was slower, but the adjustment in body orientation was greater, during 7.5% CO(2) inhalation compared to air. These findings indicate changes in locomotor behaviour during heightened state anxiety that may reflect greater caution when moving in an agitated state. Advances in sensing technology offer the opportunity to monitor locomotor behaviour, and these findings suggest that in doing so, we may be able to infer emotional states from movement in naturalistic settings. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00426-020-01393-2) contains supplementary material, which is available to authorized users

Father absence and trajectories of offspring mental health across adolescence and young adulthood:Findings from a UK-birth cohort

Background High prevalence of parental separation and resulting biological father absence raises important questions regarding its impact on offspring mental health across the life course. We specifically examined whether these relationships vary by sex and the timing of exposure to father absence (early or middle childhood). Methods This study is based on up to 8409 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). Participants provided self-reports of depression (Clinical Interview Schedule-Revised) at age 24 years and depressive symptoms (Short Mood and Feelings Questionnaire) between the ages of 10 and 24 years. Biological father absence in childhood was assessed through maternal questionnaires at regular intervals from birth to 10 years. We estimated the association between biological father absence and trajectories of depressive symptoms using multilevel growth-curve modelling. Results Early but not middle childhood father absence was strongly associated with increased odds of offspring depression and greater depressive symptoms at age 24 years. Early childhood father absence was associated with higher trajectories of depressive symptoms during adolescence and early adulthood compared with father presence. Differences in the level of depressive symptoms between middle childhood father absent and father present groups narrowed into adulthood. Limitations This study could be biased by attrition and residual confounding. Conclusions We found evidence that father absence in childhood is persistently associated with offspring depression in adolescence and early adulthood. This relationship varies by sex and timing of father's departure, with early childhood father absence emerging as the strongest risk factor for adverse offspring mental health trajectories Further research is needed to identify mechanisms that could inform preventative interventions to reduce the risk of depression in children who experience father absence

Locus of Control and Negative Cognitive Styles in Adolescence as Risk Factors for Depression Onset in Young Adulthood:Findings From a Prospective Birth Cohort Study

Whilst previous observational studies have linked negative thought processes such as an external locus of control and holding negative cognitive styles with depression, the directionality of these associations and the potential role that these factors play in the transition to adulthood and parenthood has not yet been investigated. This study examined the association between locus of control and negative cognitive styles in adolescence and probable depression in young adulthood and whether parenthood moderated these associations. Using a UK prospective population-based birth cohort study: the Avon Longitudinal Study of Parents and Children (ALSPAC), we examined the association between external locus of control and negative cognitive styles in adolescence with odds of depression in 4,301 young adults using logistic regression models unadjusted and adjusted for potential confounding factors. Interaction terms were employed to examine whether parenthood (i.e., having become a parent or not) moderated these associations. Over 20% of young adults in our sample were at or above the clinical threshold indicating probable depression. For each standard deviation (SD) increase in external locus of control in adolescence, there was a 19% (95% CI: 8–32%) higher odds of having probable depression in young adulthood, after adjusting for various confounding factors including baseline mood and different demographic and life events variables. Similarly, for each SD increase in negative cognitive styles in adolescence, there was a 29% (95% CI: 16–44%) higher odds of having probable depression in the adjusted model. We found little evidence that parenthood status moderated the relationship between external locus of control or negative cognitive styles in adolescence and probable depression following adjustment for confounding factors. Effect estimates were comparable when performed in the complete case dataset. These findings suggest that having an external locus of control and holding negative cognitive styles in mid- to late adolescence is associated with an increased likelihood of probable depression in young adulthood

Trajectories of depressive symptoms and adult educational and employment outcomes

Background Depressive symptoms show different trajectories throughout childhood and adolescence that may have different consequences for adult outcomes. Aims To examine trajectories of childhood depressive symptoms and their association with education and employment outcomes in early adulthood. Method We estimated latent trajectory classes from participants with repeated measures of self-reported depressive symptoms between 11 and 24 years of age and examined their association with two distal outcomes: university degree and those not in employment, education or training at age 24. Results Our main analyses (n = 9399) yielded five heterogenous trajectories of depressive symptoms. The largest group found (70.5% of participants) had a stable trajectory of low depressive symptoms (stable–low). The other four groups had symptom profiles that reached full-threshold levels at different developmental stages and for different durations. We identified the following groups: childhood–limited (5.1% of participants) with full-threshold symptoms at ages 11–13; childhood–persistent (3.5%) with full-threshold symptoms at ages 13–24; adolescent onset (9.4%) with full-threshold symptoms at ages 17–19; and early-adult onset (11.6%) with full-threshold symptoms at ages 22–24. Relative to the majority ‘stable–low’ group, the other four groups all exhibited higher risks of one or both adult outcomes. Conclusions Accurate identification of depressive symptom trajectories requires data spanning the period from early adolescence to early adulthood. Consideration of changes in, as well as levels of, depressive symptoms could improve the targeting of preventative interventions in early-to-mid adolescence. </jats:sec

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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01542-8