Mental health and social difficulties of late-diagnosed autistic children, across childhood and adolescence

BACKGROUND: Autism can be diagnosed from 2 years of age, although most autistic people receive their diagnosis later than this after they have started education. Research is required to understand why some autistic children are diagnosed late, and the level and nature of unmet need prior to diagnosis for late-diagnosed children. METHODS: We examined trajectories of emotional, behavioural and social difficulties (EBSDs) across childhood and adolescence, comparing 'earlier-diagnosed' (diagnosed 7 years or younger) with 'late-diagnosed' (diagnosed between 8 and 14 years) autistic children. Data were from the Millennium Cohort Study, a population-based UK birth cohort. EBSDs were measured using the parent-report Strengths and Difficulties Questionnaire, at 3, 5, 7, 11 and 14 years. We used Growth Curve Modelling to investigate levels and rates of change in these difficulties, and to compare earlier- (n = 146) and late-diagnosed (n = 284) autistic children. RESULTS: Aged 5, earlier-diagnosed autistic children had more emotional (i.e., internalising), conduct, hyperactivity and social difficulties; although clinical difficulties in these areas were nevertheless common in late-diagnosed children. There was a faster annual increase in scores for all domains for late-diagnosed children, and by age 14 years, they had higher levels of EBSDs. These results persisted when we ran adjusted models, to account for the late-diagnosed group having higher rates of late-diagnosed attention deficit/hyperactivity disorder, higher IQ, a higher proportion of females and older and more educated mothers. CONCLUSIONS: Emotional, behavioural and social difficulties are associated with, and may influence, the timing of autism diagnosis. Late-diagnosed autistic children often have high levels of mental health and social difficulties prior to their autism diagnosis, and tend to develop even more severe problems as they enter adolescence

What influences 11-year-olds to drink? Findings from the Millennium Cohort Study

Background Drinking in youth is linked to other risky behaviours, educational failure and premature death. Prior research has examined drinking in mid and late teenagers, but little is known about the factors that influence drinking at the beginning of adolescence. Objectives were: 1. to assess associations of parental and friends’ drinking with reported drinking among 11 year olds; 2. to investigate the roles of perceptions of harm, expectancies towards alcohol, parental supervision and family relationships on reported drinking among 11 year olds. Methods Analysis of data from the UK Millennium Cohort Study on 10498 11-year-olds. The outcome measure was having drank an alcoholic drink, self-reported by cohort members. Results 13.6 % of 11 year olds reported having drank. Estimates reported are odds ratios and 95 % confidence intervals. Cohort members whose mothers drank were more likely to drink (light/moderate = 1.6, 1.3 to 2.0, heavy/binge = 1.8, 1.4 to 2.3). Cohort members whose fathers drank were also more likely to drink but these estimates lost statistical significance when covariates were adjusted for (light/moderate = 1.3, 0.9 to 1.9, heavy/binge = 1.3, 0.9 to 1.9). Having friends who drank was strongly associated with cohort member drinking (4.8, 3.9 to 5.9). Associated with reduced odds of cohort member drinking were: heightened perception of harm from 1–2 drinks daily (some = 0.9, 0.7 to 1.1, great = 0.6, 0.5 to 0.7); and negative expectancies towards alcohol (0.5, 0.4 to 0.7). Associated with increased odds of cohort member drinking were: positive expectancies towards alcohol (1.9, 1.4 to 2.5); not being supervised on weekends and weekdays (often = 1.2, 1.0 to 1.4); frequent battles of will (1.3, 1.1 to 1.5); and not being happy with family (1.2, 1.0 to 1.5). Conclusions Examining drinking at this point in the lifecourse has potentially important public health implications as around one in seven 11 year olds have drank, although the vast majority are yet to explore alcohol. Findings support interventions working at multiple levels that incorporate family and peer factors to help shape choices around risky behaviours including drinking

Country specific associations between social contact and mental health : evidence from civil servant studies across Great Britain, Japan and Finland

Peer reviewe

Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory

Abstract: Background/objectives: The mediating role of eating behaviors in genetic susceptibility to weight gain during mid-adult life is not fully understood. This longitudinal study aims to help us understand contributions of genetic susceptibility and appetite to weight gain. Subjects/methods: We followed the body-mass index (BMI) trajectories of 2464 adults from 45 to 65 years of age by measuring weight and height on four occasions at 5-year intervals. Genetic risk of obesity (gene risk score: GRS) was ascertained, comprising 92 BMI-associated single-nucleotide polymorphisms and split at a median (=high and low risk). At the baseline, the Eating Inventory was used to assess appetite-related traits of ‘disinhibition’, indicative of opportunistic eating or overeating and ‘hunger’ which is susceptibility to/ability to cope with the sensation of hunger. Roles of the GRS and two appetite-related scores for BMI trajectories were examined using a mixed model adjusted for the cohort effect and sex. Results: Disinhibition was associated with higher BMI (β = 2.96; 95% CI: 2.66–3.25 kg/m2), and accounted for 34% of the genetically-linked BMI difference at age 45. Hunger was also associated with higher BMI (β = 1.20; 0.82–1.59 kg/m2) during mid-life and slightly steeper weight gain, but did not attenuate the effect of disinhibition. Conclusions: Appetite disinhibition is most likely to be a defining characteristic of genetic susceptibility to obesity. High levels of appetite disinhibition, rather than hunger, may underlie genetic vulnerability to obesogenic environments in two-thirds of the population of European ancestry

Correction: Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory.

A Correction to this paper has been published: https://doi.org/10.1038/s41366-021-00770-0</jats:p

Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory

Abstract: Background/objectives: The mediating role of eating behaviors in genetic susceptibility to weight gain during mid-adult life is not fully understood. This longitudinal study aims to help us understand contributions of genetic susceptibility and appetite to weight gain. Subjects/methods: We followed the body-mass index (BMI) trajectories of 2464 adults from 45 to 65 years of age by measuring weight and height on four occasions at 5-year intervals. Genetic risk of obesity (gene risk score: GRS) was ascertained, comprising 92 BMI-associated single-nucleotide polymorphisms and split at a median (=high and low risk). At the baseline, the Eating Inventory was used to assess appetite-related traits of ‘disinhibition’, indicative of opportunistic eating or overeating and ‘hunger’ which is susceptibility to/ability to cope with the sensation of hunger. Roles of the GRS and two appetite-related scores for BMI trajectories were examined using a mixed model adjusted for the cohort effect and sex. Results: Disinhibition was associated with higher BMI (β = 2.96; 95% CI: 2.66–3.25 kg/m2), and accounted for 34% of the genetically-linked BMI difference at age 45. Hunger was also associated with higher BMI (β = 1.20; 0.82–1.59 kg/m2) during mid-life and slightly steeper weight gain, but did not attenuate the effect of disinhibition. Conclusions: Appetite disinhibition is most likely to be a defining characteristic of genetic susceptibility to obesity. High levels of appetite disinhibition, rather than hunger, may underlie genetic vulnerability to obesogenic environments in two-thirds of the population of European ancestry

Investigating the growing trend of non-drinking among young people; analysis of repeated cross-sectional surveys in England 2005–2015

Abstract Background Non-drinking among young people has increased over the past decade in England, yet the underlying factor driving this change is unknown. Traditionally non-drinking has been found to be associated with lower socio-economic status and poorer health. This study explores among which sub-groups non-drinking has increased, and how this correlates with changes in drinking patterns, to identify whether behaviours are becoming more polarised, or reduction is widespread among young people. Methods Among participants aged 16 to 24 years (N = 9699), within the annual cross-sectional nationally-representative Health Survey for England 2005–2015 datasets, the following analyses were conducted: 1) The proportion of non-drinkers among social-demographic and health sub-groups by year, and tests for linear trends among sub-groups, adjusting for age were calculated. In pooled analyses, an interaction between year and each variable was modelled in sex- and age-adjusted logistic regression models on the odds of being a non-drinker versus drinker 2) At the population level, spearman correlation co-efficients were calculated between the proportion non-drinking and the mean alcohol units consumed and binge drinking on the heaviest drinking day, by year. Ordinary least squares regression analyses were used, modelling the proportion non-drinking as the independent variable, and the mean units/binge drinking as the dependent variable. Results Rates of non-drinking increased from 18% (95%CI 16–22%) in 2005 to 29% (25–33%) in 2015 (test for trend; p < 0.001), largely attributable to increases in lifetime abstention. Not drinking in the past week increased from 35% (32–39%) to 50% (45–55%) (p < 0.001). Significant linear increases in non-drinking were found among most sub-groups including healthier sub-groups (non-smokers, those with high physical activity and good mental health), white ethnicity, north and south regions, in full-time education, and employed. No significant increases in non-drinking were found among smokers, ethnic minorities and those with poor mental health. At the population-level, significant negative correlations were found between increases in non-drinking and declines in the mean units consumed (ρ = − 0.85, p < 0.001), and binge drinking (ρ = − 0.87, p < 0.001). Conclusion Increases in non-drinking among young people has coincided with a delayed initiation into alcohol consumption, and are to be welcomed. Future research should explore attitudes towards drinking among young people

Associations between social media usage and alcohol use among youths and young adults: findings from Understanding Society.

Background and Aims: Given the decline in alcohol consumption and rise in technological use among young people, there is a need to investigate whether technology use might influence how young people drink. This study explores how social media use and changes in social media use over time could affect alcohol use among youths. Design: The UK Household Longitudinal Study (Understanding Society). Setting: United Kingdom. Participants: Participants aged 10–15 (n = 4093) and 16–19 (n = 2689) from the youth and main survey interviewed in 2011–13, and followed-up in 2014–16 (aged 10–15 n = 2588, aged 16–19 n = 1057). Measurements: Self-reported social media usage on an average day (no profile/non-daily/less than an hour/1–3/4+ hours use), drinking frequency (never/one to three times/weekly) and binge drinking frequency (never/one to two/three/more than three times) in the past month. Covariates included sex, age, educational status, household income, urban/rural, number of friends and life satisfaction. Findings: Among 10–15-year-olds, compared with those who used social media for less than an hour, those with no profile [odds ratio (OR) = 0.41, 95% confidence interval (CI) = 0.25–0.67] and non-daily users (OR = 0.49, 95% CI = 0.33–0.72) had a lower risk of drinking at least monthly, whereas those with 1–3 hours’ use (OR = 1.44, 95% CI = 1.14–1.81) and 4+ hours’ use (OR = 2.08, 1.47–2.95) had a greater risk. Among participants aged 16–19, a lower risk of binge drinking three or more times per month was found for those with no profile [relative risk ratios (RRR) = 0.29, 95% CI = 0.17–0.48] and a higher risk for those with 4+ hours’ use (RRR = 1.47, 95% CI = 1.03–2.09). Longitudinally, among 10–15-year-olds, those who had increased their social media usage versus no change were more likely to have increased their drinking frequency (OR = 1.89, 95% CI = 1.45–2.46). Some social media use at baseline (rather than none) was predictive of increased drink and binge drinking frequency over time among youths and young adults. Conclusions: Heavier social media use was associated with more frequent alcohol consumption among young people in the United Kingdom