Multiple imputation using auxiliary imputation variables that only predict missingness can increase bias due to data missing not at random.

BACKGROUND: Epidemiological and clinical studies often have missing data, frequently analysed using multiple imputation (MI). In general, MI estimates will be biased if data are missing not at random (MNAR). Bias due to data MNAR can be reduced by including other variables ("auxiliary variables") in imputation models, in addition to those required for the substantive analysis. Common advice is to take an inclusive approach to auxiliary variable selection (i.e. include all variables thought to be predictive of missingness and/or the missing values). There are no clear guidelines about the impact of this strategy when data may be MNAR. METHODS: We explore the impact of including an auxiliary variable predictive of missingness but, in truth, unrelated to the partially observed variable, when data are MNAR. We quantify, algebraically and by simulation, the magnitude of the additional bias of the MI estimator for the exposure coefficient (fitting either a linear or logistic regression model), when the (continuous or binary) partially observed variable is either the analysis outcome or the exposure. Here, "additional bias" refers to the difference in magnitude of the MI estimator when the imputation model includes (i) the auxiliary variable and the other analysis model variables; (ii) just the other analysis model variables, noting that both will be biased due to data MNAR. We illustrate the extent of this additional bias by re-analysing data from a birth cohort study. RESULTS: The additional bias can be relatively large when the outcome is partially observed and missingness is caused by the outcome itself, and even larger if missingness is caused by both the outcome and the exposure (when either the outcome or exposure is partially observed). CONCLUSIONS: When using MI, the naïve and commonly used strategy of including all available auxiliary variables should be avoided. We recommend including the variables most predictive of the partially observed variable as auxiliary variables, where these can be identified through consideration of the plausible casual diagrams and missingness mechanisms, as well as data exploration (noting that associations with the partially observed variable in the complete records may be distorted due to selection bias).

Systematic Review of Clinical Prediction Models for the Risk of Emergency Caesarean Births.

BACKGROUND: Globally, caesarean births (CB), including emergency caesareans births (EmCB), are rising. It is estimated that nearly a third of all births will be CB by 2030. OBJECTIVES: Identify and summarise the results from studies developing and validating prognostic multivariable models predicting the risk of EmCBs. Ultimately understanding the accuracy of their development, and whether they are operationalised for use in routine clinical practice. SEARCH STRATEGY: Studies were identified using databases: MEDLINE, CINAHL, Cochrane Central and Scopus with a search strategy tailored to models predicting EmCBs. SELECTION CRITERIA: Prospective studies developing and validating clinical prediction models, with two or more covariates, to predict risk of EmCB. DATA COLLECTION AND ANALYSIS: Data were extracted onto a proforma using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). RESULTS: In total, 8083 studies resulted in 56 unique prediction modelling studies and seven validating studies, with a total of 121 different predictors. Frequently occurring predictors included maternal height, maternal age, parity, BMI and gestational age. PROBAST highlighted 33 studies with low overall bias, and these all internally validated their model. Thirteen studies externally validated; only eight of these were graded an overall low risk of bias. Six models offered applications that could be readily used, but only one provided enough time to offer a planned caesarean birth (pCB). These well-refined models have not been recalibrated since development. Only one model, developed in a relatively low-risk population, with data collected a decade ago, remains useful at 36 weeks for arranging a pCB. CONCLUSION: To improve personalised clinical conversations, there is a pressing need for a model that accurately predicts the timely risk of an EmCB for women across diverse clinical backgrounds. TRIAL REGISTRATION: PROSPERO registration number: CRD42023384439.

Evaluation and comparison of nine growth and development-based measures of pubertal timing.

BACKGROUND: Pubertal timing is heritable, varies between individuals, and has implications for life-course health. There are many different indicators of pubertal timing, and how they relate to each other is unclear. Our aim was to quantitatively compare nine indicators of pubertal timing. METHODS: We used data from questionnaires and height, weight, and bone measurements from ages 7-17 y in a population-based cohort of 4267 females and 4251 males to compare nine growth and development-based indicators of pubertal timing. We summarise age of each indicator, their phenotypic and genetic correlations, and how they relate to established genetic risk score (GRS) for puberty timing, and phenotypic childhood body composition measures. RESULTS: We show that pubic hair in males (mean: 12.6 y) and breasts in females (11.5 y) are early indicators of puberty, and voice breaking (14.2 y) and menarche (12.7 y) are late indicators however, there is substantial variation between individuals in pubertal age. All indicators show evidence of positive phenotypic intercorrelations (e.g., r = 0.49: male genitalia and pubic hair ages), and positive genetic intercorrelations. An age at menarche GRS positively associates with all other pubertal age indicators (e.g., difference in female age at peak height velocity per SD higher GRS: 0.24 y, 95%CI: 0.21 to 0.26), as does an age at voice breaking GRS (e.g., difference in age at male axillary hair: 0.11 y, 0.07 to 0.15). Higher childhood fat mass and lean mass associated with earlier puberty timing. CONCLUSIONS: Our findings provide insights into the measurements of the timing of pubertal growth and development and illustrate value of various pubertal timing indicators in life-course research.

Age of puberty varies between individuals and can affect a person's future health. We obtained information from 8500 British children as they progressed through puberty. We compared nine measures of pubertal timing. We found that the appearance of pubic hair in boys and breasts in girls are early indicators of puberty, and that voice change and onset of menstruation are late indicators. However, there was also substantial variability between individuals in age of puberty. All puberty measures were correlated with each other and related to an individual's adult body mass index, as well as to their childhood muscle and fat mass. Our findings are useful information for health care workers and researchers who are interested in assessing and studying puberty.

The role of body image dissatisfaction in the relationship between body size and disordered eating and self-harm: complimentary Mendelian randomization and mediation analyses.

Disordered eating and self-harm commonly co-occur in young people suggesting potential for shared underlying causes. Body image dissatisfaction (BID) has been recognised as a psychological correlate of body size, associated with both disordered eating and self-harm. However, the investigation into etiological pathways early in the lifecourse to provide detail on how body size and BID may foster disordered eating and self-harm remains largely unexplored. Employing data from two large population-based cohorts, the UK Biobank and the Avon Longitudinal Study of Parents And Children (ALSPAC), we conducted bidirectional Mendelian randomization (MR) to determine the causal direction of effect between genetically predicted prepubertal body size and two measures of BID indicating (i) desire to be smaller, and (ii) desire to be larger. We then used multivariable regression followed by counterfactual mediation analyses. Bidirectional MR indicated robust evidence that increased genetically predicted prepubertal body size increased desire to be smaller and decreased desire to be larger. Evidence for the reverse causal direction was negligible. These findings remained very similar across sensitivity analyses. In females and males, multivariable regression analyses demonstrated that being overweight increased the risk of disordered eating (risk ratio (RR), 95% confidence interval (CI): 1.19, 1.01 to 1.40 and 1.98, 1.28 to 3.05, respectively) and self-harm (RR, 95% CI: 1.35, 1.04 to 1.77 and 1.55, 0.86 to 2.81, respectively), while being underweight was protective against disordered eating (RR, 95% CI: 0.57, 0.40 to 0.81 and 0.81, 0.38 to 1.73, respectively). There was weak evidence of an increase in the risk of self-harm among underweight individuals. Mediation analyses indicated that the relationship between being overweight and subsequent disordered eating was largely mediated by the desire to be smaller. Our research carries important public health implications, suggesting distinct risk profiles for self-harm and disordered eating in relation to weight and body image. In addition, a better understanding of genetically predicted prepubertal BID may be valuable in the prevention and treatment of disordered eating and self-harm in adolescence.

Life-course influences of poverty on violence and homicide: 30-year Brazilian birth cohort study.

BACKGROUND: Homicide is the leading cause of death among young people in Latin America, one of the world's most violent regions. Poverty is widely considered a key cause of violence, but theories suggest different effects of poverty, depending on when it is experienced in the life-course. Longitudinal studies of violence are scarce in Latin America, and very few prospective data are available worldwide to test different life-course influences on homicide. METHODS: In a prospective birth cohort study following 5914 children born in southern Brazil, we examined the role of poverty at birth, in early childhood, and in early adulthood on violence and homicide perpetration, in criminal records up to age 30 years. A novel Structured Life Course Modelling Approach was used to test competing life-course hypotheses about 'sensitive periods', 'accumulation of risk', and 'downward mobility' regarding the influence of poverty on violence and homicide. RESULTS: Cumulative poverty and poverty in early adulthood were the most important influences on violence and homicide perpetration. This supports the hypothesis that early adulthood is a sensitive period for the influence of poverty on lethal and non-lethal violence. Results were replicable using different definitions of poverty and an alternative outcome of self-reported fights. CONCLUSION: Cumulative poverty from childhood to adulthood was an important driver of violence and homicide in this population. However, poverty experienced in early adulthood was especially influential, suggesting the importance of proximal mechanisms for violence in this context, such as unemployment, organized crime, drug trafficking, and ineffective policing and justice systems.

Analyses Using Multiple Imputation Need to Consider Missing Data in Auxiliary Variables.

Auxiliary variables are used in multiple imputation (MI) to reduce bias and increase efficiency. These variables may often themselves be incomplete. We explored how missing data in auxiliary variables influenced estimates obtained from MI. We implemented a simulation study with three different missing data mechanisms for the outcome. We then examined the impact of increasing proportions of missing data and different missingness mechanisms for the auxiliary variable on bias of an unadjusted linear regression coefficient and the fraction of missing information. We illustrate our findings with an applied example in the Avon Longitudinal Study of Parents and Children. We found that where complete records analyses were biased, increasing proportions of missing data in auxiliary variables, under any missing data mechanism, reduced the ability of MI including the auxiliary variable to mitigate this bias. Where there was no bias in the complete records analysis, inclusion of a missing not at random auxiliary variable in MI introduced bias of potentially important magnitude (up to 17% of the effect size in our simulation). Careful consideration of the quantity and nature of missing data in auxiliary variables needs to be made when selecting them for use in MI models.

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.

Using instruments for selection to adjust for selection bias in Mendelian randomization.

Selection bias is a common concern in epidemiologic studies. In the literature, selection bias is often viewed as a missing data problem. Popular approaches to adjust for bias due to missing data, such as inverse probability weighting, rely on the assumption that data are missing at random and can yield biased results if this assumption is violated. In observational studies with outcome data missing not at random, Heckman's sample selection model can be used to adjust for bias due to missing data. In this paper, we review Heckman's method and a similar approach proposed by Tchetgen Tchetgen and Wirth (2017). We then discuss how to apply these methods to Mendelian randomization analyses using individual-level data, with missing data for either the exposure or outcome or both. We explore whether genetic variants associated with participation can be used as instruments for selection. We then describe how to obtain missingness-adjusted Wald ratio, two-stage least squares and inverse variance weighted estimates. The two methods are evaluated and compared in simulations, with results suggesting that they can both mitigate selection bias but may yield parameter estimates with large standard errors in some settings. In an illustrative real-data application, we investigate the effects of body mass index on smoking using data from the Avon Longitudinal Study of Parents and Children.

Sleep duration, sleep problems and developmental trajectories of urinary incontinence: a prospective cohort study.

To examine if preschool sleep duration and sleep problems are associated with urinary incontinence (UI) at primary school-age. We used multinomial logistic regression to examine the association of child sleep duration/problems (3½ years) with UI trajectories (4-9 years) in 8751 (4507 boys, 4244 girls) from the Avon Longitudinal Study of Parents and Children. We adjusted for sex, socioeconomic indicators, mothers' emotional/practical/financial support, developmental delay, stressful life events, temperament, and emotional/behaviour problems. Preschool children who slept more than 8½ hours per night had a decreased probability of UI at school-age. There was a 33% reduction in odds of daytime wetting per additional hour of sleep (odds ratio [OR] = 0.67, 95% confidence interval [CI] 0.52-0.86). Sleep problems were associated with increased odds of UI e.g., getting up after being put to bed was associated with daytime wetting (OR = 2.20, 95% CI 1.43-3.39); breathing problems whilst sleeping were associated with delayed bladder control (OR = 1.68, 95% CI 1.12-2.52), and night-time waking was associated with persistent (day and night) wetting (OR = 1.53, 95% CI 1.16-2.00). Waking during the night and waking up early in the morning were associated with reduced odds of bedwetting at school-age (OR = 0.76, 95% CI 0.61-0.96 and OR = 0.80, 95% CI 0.64-0.99 respectively). Preschool children who sleep for longer have a lower likelihood of UI at school-age, whilst those with sleep problems are more likely to experience daytime wetting and combined (day and night) wetting, but not bedwetting alone. Short sleep duration and sleep problems in early childhood could be indicators of future problems attaining and maintaining bladder control.

Exposure to Violence and Mental Health Outcomes Among Pre-schoolers in a South African Birth Cohort.

Little is known about the relationship between violence exposure and mental health in preschoolers living in low- and middle-income countries (LMICs). Multiple regression analyses investigated associations between violence exposure and mental health in the Drakenstein Child Health Study (N = 978), a South African birth cohort. Lifetime violence exposure was assessed at age 4.5 years using the parent-report Child Exposure to Community Violence Checklist (CECV). Mental health was assessed at age 5 years using the Child Behaviour Checklist (CBCL 1.5-5). Eighty-three percent of the children were exposed to some form of violence. Internalising and externalising behaviours were positively associated with overall violence exposure (ß per one unit change in the overall score = 0.55 [0.16, 0.94] and ß = 0.53 [0.23, 0.84], respectively), domestic victimisation (ß per one unit change in the subscore = 1.28 [0.28, 2.27]; ß = 1.14 [0.37, 1.90]) and witnessing community violence (ß = 0.77 [0.15, 1.39]; ß = 0.68 [0.19, 1.18]). There was a positive association between polyvictimisation and externalising (ß = 1.02 [0.30, 1.73]) but not internalising (ß = 0.87 [-0.06, 1.80]) behaviour problems. Evidence for an association of witnessing domestic violence with internalising (ß = 0.63 [-0.97, 2.24]) or externalising (ß = 1.23 [-0.04, 2.50]) behaviours was less robust. There was no association between community victimisation and internalising or externalising behaviours (ß = 0.72 [-1.52, 2.97; ß = 0.68 [ -1.06, 2.41]). Observations highlight the risk for mental health problems among preschoolers living in high-violence contexts and emphasize the need for early interventions.

Prenatal Urban Environment and Blood Pressure Trajectories From Childhood to Early Adulthood.

Background: Prenatal urban environmental exposures have been associated with blood pressure in children. The dynamic of these associations across childhood and later ages is unknown. Objectives: The purpose of this study was to assess associations of prenatal urban environmental exposures with blood pressure trajectories from childhood to early adulthood. Methods: Repeated measures of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were collected in up to 7,454 participants from a UK birth cohort. Prenatal urban exposures (n = 43) covered measures of noise, air pollution, built environment, natural spaces, traffic, meteorology, and food environment. An exposome-wide association study approach was used. Linear spline mixed-effects models were used to model associations of each exposure with trajectories of blood pressure. Replication was sought in 4 independent European cohorts (up to 9,261). Results: In discovery analyses, higher humidity was associated with a faster increase (mean yearly change in SBP for an interquartile range increase in humidity: 0.29 mm Hg/y, 95% CI: 0.20-0.39) and higher temperature with a slower increase (mean yearly change in SBP per interquartile range increase in temperature: -0.17 mm Hg/y, 95% CI: -0.28 to -0.07) in SBP in childhood. Higher levels of humidity and air pollution were associated with faster increase in DBP in childhood and slower increase in adolescence. There was little evidence of an association of other exposures with change in SBP or DBP. Results for humidity and temperature, but not for air pollution, were replicated in other cohorts. Conclusions: Replicated findings suggest that higher prenatal humidity and temperature could modulate blood pressure changes across childhood.

Emotional problems across development: examining measurement invariance across childhood, adolescence and early adulthood.

Emotional problems (anxiety, depression) are prevalent in children, adolescents and young adults with varying ages at onset. Studying developmental changes in emotional problems requires repeated assessments using the same or equivalent measures. The parent-rated Strengths and Difficulties Questionnaire is commonly used to assess emotional problems in childhood and adolescence, but there is limited research about whether it captures a similar construct across these developmental periods. Our study addressed this by investigating measurement invariance in the scales' emotional problems subscale (SDQ-EP) across childhood, adolescence and early adulthood. Data from two UK population cohorts were utilised: the Millennium Cohort Study (ages 3-17 years) and the Avon Longitudinal Study of Parents and Children (4-25 years). In both samples we observed weak (metric) measurement invariance by age, suggesting that the parent-rated SDQ-EP items contribute to the underlying construct of emotional problems similarly across age. This supports the validity of using the subscale to rank participants on their levels of emotional problems in childhood, adolescence and early adulthood. However strong (scalar) measurement invariance was not observed, suggesting that the same score may correspond to different levels of emotional problems across developmental periods. Comparisons of mean parent-rated SDQ-EP scores across age may therefore not be valid.

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.

Incident psychotic experiences following self-reported use of high-potency cannabis: Results from a longitudinal cohort study.

BACKGROUND AND AIMS: High-potency cannabis has been associated with increased risk of psychosis, but a lack of prospective data hinders understanding of causality in this relationship. This study aimed to combine prospective report of cannabis use with retrospective report of potency to infer the potency of cannabis used in adolescence and explore whether use of cannabis, and the use of high-potency cannabis, in adolescence is associated with incident psychotic experiences. DESIGN: Population-based birth cohort study. SETTING: United Kingdom. PARTICIPANTS: n = 5570 participants who reported on any cannabis use (yes/no) age 16 and 18 years, and n = 1560 participants from this group who also retrospectively reported on cannabis potency. MEASUREMENTS: In questionnaires at ages 16 and 18, individuals self-reported lifetime cannabis use, and at age 24, participants reported the type of cannabis they most commonly used in the whole time since first using cannabis. Psychotic experiences were assessed at age 24 years using the semi-structured Psychosis-Like Symptom Interview, with incident defined as new-onset occurring between ages 19 and 24 years. FINDINGS: Use of high-potency cannabis at age 16 or 18 was associated with twice the likelihood of experiencing incident psychotic experiences from age 19-24 (Odds Ratio 2.15, 95% Confidence Intervals 1.13-4.06). There was less evidence for an effect of any cannabis use on incident psychotic experiences (Odds Ratio 1.45, 95% Confidence Intervals 0.94-2.12). CONCLUSIONS: Use of high-potency cannabis appears to be associated with increased likelihood of psychotic experiences.

Counterfactual Mediation Analysis with a Latent Class Exposure.

Latent classes are a useful tool in developmental research, however there are challenges associated with embedding them within a counterfactual mediation model. We develop and test a new method "updated pseudo class draws (uPCD)" to examine the association between a latent class exposure and distal outcome that could easily be extended to allow the use of any counterfactual mediation method. UPCD extends an existing group of methods (based on pseudo class draws) that assume that the true values of the latent class variable are missing, and need to be multiply imputed using class membership probabilities. We simulate data based on the Avon Longitudinal Study of Parents and Children, examine performance for existing techniques to relate a latent class exposure to a distal outcome ("one-step," "bias-adjusted three-step," "modal class assignment," "non-inclusive pseudo class draws," and "inclusive pseudo class draws") and compare bias in parameter estimates and their precision to uPCD when estimating counterfactual mediation effects. We found that uPCD shows minimal bias when estimating counterfactual mediation effects across all levels of entropy. UPCD performs similarly to recommended methods (one-step and bias-adjusted three-step), but provides greater flexibility and scope for incorporating the latent grouping within any commonly-used counterfactual mediation approach.

Investigating changes in student mental health and help-seeking behaviour after the introduction of new well-being support services at a UK university.

BACKGROUND: Growing numbers of students now seek mental health support from their higher education providers. In response, a number of universities have invested in non-clinical well-being services, but there have been few evaluations of these. This research addresses a critical gap in the existing literature. AIMS: This study examined the impact of introducing non-clinical well-being advisers on student mental health and help-seeking behaviour at a large UK university. METHOD: Survey data collected pre-post service introduction in 2018 (n = 5562) and 2019 (n = 2637) measured prevalence of depression (Patient Health Questionnaire-9), anxiety (Generalised Anxiety Disorder-7), and low mental well-being (Warwick-Edinburgh Mental Wellbeing Scale), alongside student support-seeking behaviour. Logistic regression models investigated changes in outcome measures. Administrative data (2014-2020) were used to investigate corresponding trends in antidepressant prescribing at the onsite health service, student counselling referrals and course withdrawal rates. RESULTS: Adjusted models suggested reductions in students' levels of anxiety (odds ratio 0.86, 95% CI 0.77-0.96) and low well-being (odds ratio 0.84, 95% CI 0.75-0.94) in 2019, but not depression symptoms (odds ratio 1.05, 95% CI 0.93-1.17). Statistical evidence showed reduced student counselling referrals, with antidepressant prescribing and course withdrawal rates levelling off. Student perception of the availability and accessibility of university support improved. CONCLUSIONS: Our findings suggest a non-clinical well-being service model may improve student perception of support, influence overall levels of anxiety and low well-being, and reduce clinical need. The current study was only able to examine changes over the short term, and a longer follow-up is needed.

Association of early-life exposure to air and noise pollution with youth mental health: findings from the ALSPAC cohort.

BACKGROUND: Increasing evidence suggests that air pollution exposure contributes to the development of mental health problems, including psychosis and depression. However, little is known about the importance of early-life exposure, nor the potential role of noise pollution, a correlate of air pollution. We examined the association of exposure to air and noise pollution from pregnancy to age 12 years with three mental health problems assessed at ages 12, 18, and 24 years. METHODS: Data were from the Avon Longitudinal Study of Parents and Children (ALSPAC), which tracks the development of about 14 000 babies who had expected delivery dates between April 1, 1991, and Dec 31, 1992, in Avon, UK. This was linked with novel data on nitrogen dioxide, PM2·5, and noise pollution in pregnancy, childhood (ages 1-9 years), and adolescence (ages 10-12 years). Psychotic experiences, depression, and anxiety were measured at ages 12, 18, and 24 years. Logistic regression models were controlled for individual-level, family-level, and area-level confounders, and e-values were calculated to estimate residual confounding. FINDINGS: Participants exposed to higher PM2.5, particularly during pregnancy, had greater odds for psychotic experiences (adjusted odds ratio 1·17 [95% CI 1·05-1·30]) and depression (1·11 [1·01-1·22]). There was little evidence associating nitrogen dioxide or noise pollution with psychotic experiences or depression. Conversely, higher nitrogen dioxide (but not PM2·5) exposure in pregnancy (1·16 [1·01-1·33]), and higher noise pollution in childhood (1·20 [1·06-1·37]) and adolescence (1·17 [1·02-1·35]), were associated with greater odds for anxiety. INTERPRETATION: Our study builds on evidence linking air pollution to psychosis and depression and provides rare longitudinal evidence linking noise pollution to anxiety. Our findings indicate that air pollution exposure earlier in development (eg, during pregnancy) might be particularly important, and suggest a degree of specificity in terms of pollutant-outcome associations. If causal, our findings suggest that interventions to reduce air pollution would improve global mental health. FUNDING: Wellcome Trust, UK Medical Research Council-Wellcome, and University of Bristol.

Childhood Adversity and Incident Psychotic Experiences in Early Adulthood: Cognitive and Psychopathological Mediators.

BACKGROUND AND HYPOTHESIS: Childhood adversity is often described as a potential cause of incident psychotic experiences, but the underlying mechanisms are not well understood. We aimed to examine the mediating role of cognitive and psychopathological factors in the relation between childhood adversity and incident psychotic experiences in early adulthood. STUDY DESIGN: We analyzed data from the Avon Longitudinal Study of Parents and Children, a large population-based cohort study. Childhood adversity was measured prospectively from birth to age 11 years, mediators (anxiety, depression, external locus of control [LoC], negative symptoms) were assessed at approximately 16 years of age, and incident psychotic experiences were assessed at ages 18 and 24 years. Mediation was examined via the counterfactual g-computation formula. STUDY RESULTS: In total, 7% of participants had incident suspected or definite psychotic experiences in early adulthood. Childhood adversity was related to more incident psychotic experiences (ORadjusted = 1.34, 95% CI = 1.21; 1.49), and this association was partially mediated via all mediators examined (proportion mediated: 19.9%). In separate analyses for each mediator, anxiety, depression, external LoC, and negative symptoms were all found to mediate the link between adversity and incident psychotic experiences. Accounting for potential confounders did not modify our results. CONCLUSIONS: Our study shows that cognitive biases as well as mood symptomatology may be on the causal pathway between early-life adversity and the development of psychotic experiences. Future studies should determine which mediating factors are most easily modifiable and most likely to reduce the risk of developing psychotic experiences.

Childhood adversities characterize the heterogeneity in the brain pattern of individuals during neurodevelopment.

BACKGROUND: Several factors shape the neurodevelopmental trajectory. A key area of focus in neurodevelopmental research is to estimate the factors that have maximal influence on the brain and can tip the balance from typical to atypical development. METHODS: Utilizing a dissimilarity maximization algorithm on the dynamic mode decomposition (DMD) of the resting state functional MRI data, we classified subjects from the cVEDA neurodevelopmental cohort (n = 987, aged 6-23 years) into homogeneously patterned DMD (representing typical development in 809 subjects) and heterogeneously patterned DMD (indicative of atypical development in 178 subjects). RESULTS: Significant DMD differences were primarily identified in the default mode network (DMN) regions across these groups (p < 0.05, Bonferroni corrected). While the groups were comparable in cognitive performance, the atypical group had more frequent exposure to adversities and faced higher abuses (p < 0.05, Bonferroni corrected). Upon evaluating brain-behavior correlations, we found that correlation patterns between adversity and DMN dynamic modes exhibited age-dependent variations for atypical subjects, hinting at differential utilization of the DMN due to chronic adversities. CONCLUSION: Adversities (particularly abuse) maximally influence the DMN during neurodevelopment and lead to the failure in the development of a coherent DMN system. While DMN's integrity is preserved in typical development, the age-dependent variability in atypically developing individuals is contrasting. The flexibility of DMN might be a compensatory mechanism to protect an individual in an abusive environment. However, such adaptability might deprive the neural system of the faculties of normal functioning and may incur long-term effects on the psyche.