Background: The COVID-19 pandemic and mitigation measures are likely to have a marked effect on mental health. It is important to use longitudinal data to improve inferences.Aims: To quantify the prevalence of depression, anxiety and mental well-being before and during the COVID-19 pandemic. Also, to identify groups at risk of depression and/or anxiety during the pandemic.Method: Data were from the Avon Longitudinal Study of Parents and Children (ALSPAC) index generation (n = 2850, mean age 28 years) and parent generation (n = 3720, mean age 59 years), and Generation Scotland (n = 4233, mean age 59 years). Depression was measured with the Short Mood and Feelings Questionnaire in ALSPAC and the Patient Health Questionnaire-9 in Generation Scotland. Anxiety and mental well-being were measured with the Generalised Anxiety Disorder Assessment-7 and the Short Warwick Edinburgh Mental Wellbeing Scale.Results: Depression during the pandemic was similar to pre-pandemic levels in the ALSPAC index generation, but those experiencing anxiety had almost doubled, at 24% (95% CI 23–26%) compared with a pre-pandemic level of 13% (95% CI 12–14%). In both studies, anxiety and depression during the pandemic was greater in younger members, women, those with pre-existing mental/physical health conditions and individuals in socioeconomic adversity, even when controlling for pre-pandemic anxiety and depression.Conclusions: These results provide evidence for increased anxiety in young people that is coincident with the pandemic. Specific groups are at elevated risk of depression and anxiety during the COVID-19 pandemic. This is important for planning current mental health provisions and for long-term impact beyond this pandemic.

Individual-level longitudinal data on biological, behavioural, and social dimensions are becoming increasingly available. Typically, these data are analysed using mixed effects models, with the result summarised in terms of an average trajectory plus measures of the individual variations around this average. However, public health investigations would benefit from finer modelling of these individual variations which identify not just one average trajectory, but several typical trajectories. If evidence of heterogeneity in the development of these variables is found, the role played by temporally preceding (explanatory) variables as well as the potential impact of differential trajectories may have on later outcomes is often of interest. A wide choice of methods for uncovering typical trajectories and relating them to precursors and later outcomes exists. However, despite their increasing use, no practical overview of these methods targeted at epidemiological applications exists. Hence we provide: (a) a review of the three most commonly used methods for the identification of latent trajectories (growth mixture models, latent class growth analysis, and longitudinal latent class analysis); and (b) recommendations for the identification and interpretation of these trajectories and of their relationship with other variables. For illustration, we use longitudinal data on childhood body mass index and parental reports of fussy eating, collected in the Avon Longitudinal Study of Parents and Children.

Objectives Few studies have investigated the incidence of eating disorders (EDs). Important questions about changes in the incidence of diagnosed disorders in recent years, disorder and gender-specific onset and case detection remain unanswered. Understanding changes in incidence is important for public health, clinical practice and service provision. The aim of this study was to estimate the annual (age-specific, gender-specific and subtype-specific) incidence of diagnosed ED: anorexia nervosa (AN), bulimia nervosa (BN) and eating disorder not otherwise specified (EDNOS) in primary care over a 10-year period in the UK (2000–2009); to examine the changes within the study period; and to describe peak age at diagnosis. Design Register-based study. Setting Primary care. Data were obtained from a primary care register, the General Practice Research Database, which contains anonymised records representing about 5% of the UK population. Participants All patients with a first-time diagnosis of AN, BN and EDNOS were identified. Primary outcome Annual crude and age-standardised incidence rates were calculated. Results A total of 9072 patients with a first-time diagnosis of an ED were identified. The age-standardised annual incidence rate of all diagnosed ED for ages 10–49 increased from 32.3 (95% CI 31.7 to 32.9) to 37.2 (95% CI 36.6 to 37.9) per 100 000 between 2000 and 2009. The incidence of AN and BN was stable; however, the incidence of EDNOS increased. The incidence of the diagnosed ED was highest for girls aged 15–19 and for boys aged 10–14. Conclusions The age-standardised incidence of ED increased in primary care between 2000 and 2009. New diagnoses of EDNOS increased, and EDNOS is the most common ED in primary care.

ObjectiveTo investigate the association between overeating (without loss of control) and binge eating (overeating with loss of control) and adverse outcomes.DesignProspective cohort study.SettingAdolescents and young adults living throughout the United States.ParticipantsSixteen thousand eight hundred eighty-two males and females participating in the Growing Up Today Study who were 9 to 15 years old at enrollment in 1996.Main ExposureOvereating and binge eating assessed via questionnaire every 12 to 24 months between 1996 and 2005.Main Outcome MeasuresRisk of becoming overweight or obese, starting to binge drink frequently, starting to use marijuana, starting to use other drugs, and developing high levels of depressive symptoms. Generalized estimating equations were used to estimate associations. All models controlled for age and sex; additional covariates varied by outcome.ResultsAmong this large cohort of adolescents and young adults, binge eating was more common among females than males. In fully adjusted models, binge eating, but not overeating, was associated with incident overweight/obesity (odds ratio, 1.73; 95% CI, 1.11-2.69) and the onset of high depressive symptoms (odds ratio, 2.19; 95% CI, 1.40-3.45). Neither overeating nor binge eating was associated with starting to binge drink frequently, while both overeating and binge eating predicted starting to use marijuana and other drugs.ConclusionsAlthough any overeating, with or without loss of control, predicted the onset of marijuana and other drug use, we found that binge eating is uniquely predictive of incident overweight/obesity and the onset of high depressive symptoms. These findings suggest that loss of control is an important indicator of severity of overeating episodes.