Archives: Publications

Background
There are few prospective studies of factors that mediate the association between exposure to adverse childhood experiences (ACEs) and obesity in adolescence. Our aim was to address this limitation.

Methods
We used prospective data from the Growing up in Ireland cohort study, with measurements at 9, 13, and 18 years old. The exposures were 14 adverse experiences before age 9. The main outcome was body mass index (BMI) at 18 years. Mediators were daily activity, diet quality, self-image and behavioural difficulties at 13 years.

Results
Among the 4561 adolescents in the final cohort, 77.2% experienced any adversity, 50.5% were female and 26.7% were overweight/obese at 18 years. BMI Z was higher at ages 9 (0.54 vs 0.43, p < 0.05, 95% CI of difference: −0.22, −0.01) and 13 years (0.50 vs 0.35, p < 0.05, 95% CI of difference: −0.25, −0.06), in those exposed to an ACE, compared to those unexposed. Structural equation models revealed that behavioural difficulties (β = 0.01; 95% CI: 0.007–0.018, p < 0.001) and self-concept (β = 0.0027; 95% CI: 0.0004–0.0050, p = 0.026) indirectly mediate the association between exposure to ACEs and BMI at 18 years.

Conclusions
The association between ACEs and BMI in adolescence is mediated by behavioural difficulties and self-concept.

Impact

• In a previous study, we found modest associations between exposure to a range of adverse childhood experiences and weight gain at 13 years of age.
• The strength of the association between adverse childhood experiences and weight gain was lower at 18 years of age compared to the association observed at 13 years and was no longer significant after controlling for confounding and including possible mediators.
• The association between adverse childhood experiences and BMI in adolescence is indirectly mediated by behavioural difficulties and self-concept.

Background
There are no early, accurate, scalable methods for identifying infants at high risk of poor cognitive outcomes in childhood. We aim to develop an explainable predictive model, using machine learning and population-based cohort data, for this purpose.

Methods
Data were from 8858 participants in the Growing Up in Ireland cohort, a nationally representative study of infants and their primary caregivers (PCGs). Maternal, infant, and socioeconomic characteristics were collected at 9-months and cognitive ability measured at age 5 years. Data preprocessing, synthetic minority oversampling, and feature selection were performed prior to training a variety of machine learning models using ten-fold cross validated grid search to tune hyperparameters. Final models were tested on an unseen test set.

Results
A random forest (RF) model containing 15 participant-reported features in the first year of infant life, achieved an area under the receiver operating characteristic curve (AUROC) of 0.77 for predicting low cognitive ability at age 5. This model could detect 72% of infants with low cognitive ability, with a specificity of 66%.

Conclusions
Model performance would need to be improved before consideration as a population-level screening tool. However, this is a first step towards early, individual, risk stratification to allow targeted childhood screening.

Impact
• This study is among the first to investigate whether machine learning methods can be used at a population-level to predict which infants are at high risk of low cognitive ability in childhood.
• A random forest model using 15 features which could be easily collected in the perinatal period achieved an AUROC of 0.77 for predicting low cognitive ability.
• Improved predictive performance would be required to implement this model at a population level but this may be a first step towards early, individual, risk stratification.

This study examines how the presence of outdoor areas such as parks and playgrounds affects children’s well-being and how this effect is moderated by families’ socioeconomic status. Specifically, I aim to answer two research questions. First, does the presence of outdoor areas in children’s neighborhoods affect their well-being? Second, is there a differential effect depending on children’s socioeconomic status? The main part of the study uses data from the International Survey of Children’s Well-Being. The results suggest that the presence of outdoor areas in children’s neighborhoods has a positive effect on their well-being. In addition, the estimated effect of outdoor areas is larger for children from families with low socioeconomic status. Finally, findings from the Growing Up in Ireland data set suggest that children’s mental problems are a plausible mechanism through which outdoor areas affect children’s well-being. These findings have meaningful policy implications. Efforts to provide access to appropriate outdoor areas may be more likely to benefit disadvantaged children and thus reduce inequality in children’s well-being.

The quality of the interparental relationship bears important implications for children’s socioemotional development. Given evidence that relationship satisfaction among parents tends to decline over time this study examined how change in parents’ relationship satisfaction from nine-months-old until nine-years-old related to children’s socioemotional difficulties at nine-years-old. Participants were 2074 mothers, fathers, and their child (55.1% male) recruited through random sampling of the Child Benefit Registrar by Growing Up in Ireland cohort study. Mothers ranged in age from 18 to 40 years (M = 31.06, SD = 4.70) and fathers ranged in age from 18 to 60 years (M = 33.50, SD = 5.54). Mothers and fathers completed the Dyadic Adjustment Scale at nine-months-old and at nine-years-old whereas child socioemotional development was assessed via teacher report on the Strengths and Difficulties Questionnaire at nine-years-old. Residualised change analysis indicated that both parents experienced declines in relationship satisfaction from nine-months-old until nine- years-old. However, in families where initial levels of relationship satisfaction were high, there was no significant association between decline in satisfaction and child socioemotional difficulties. Conversely, in couples where initial levels of satisfaction were low, mothers, but not fathers, who experienced further declines had female, but not male, children with more socioemotional difficulties at nine years (β = −0.22, p = 0.01; R2 = 0.15, F = 2.31, p = 0.02). These findings highlight the need for carefully tailored interventions aimed at promoting couple relationship satisfaction during transition to parenthood such that the negative impact on children of any decline experienced over time can be mitigated.

Empirical research into the relationship between economic well-being and child outcomes has been limited by its cross-sectional nature, or its narrow focus on predominantly financial aspects of economic well-being. This article attempts to overcome these shortcomings by using data from the Growing Up in Ireland Cohort98 (age: 9–17; N = 5,748; female: 51.4%) and Cohort08 studies (age: 3–9 years; N = 7,208; female: 49.8%), which cover a period of large macroeconomic fluctuation (2007–2017). This fluctuation makes a robust fixed effects analysis feasible, allowing for economic well-being effects to be isolated by controlling for all time-invariant confounders. The article uses three different measures of economic well-being (subjective financial strain, material deprivation, income) to explore how distinct forms of economic well-being affect child behavior. The results suggest that household income is not related to behavioral difficulties, whereas subjective financial strain is predictive of externalized behavioral difficulties in adolescent boys. Material deprivation is predictive of externalized behavioral difficulties in adolescent boys and internalized behavioral difficulties in younger boys, but has no effect on girls’ behavioral outcomes. The findings indicate that the relationship between economic well-being and child behavioral outcomes is complex, and requires multi-dimensional measures of economic well-being to accurately ascertain the different effects.

Identifying the clustering and correlates of physical activity (PA) and sedentary behavior (SB) is very important for developing appropriate lifestyle interventions for children and adolescents. This systematic review (Prospero CRD42018094826) aimed to identify PA and SB cluster patterns and their correlates among boys and girls (0-19 years). The search was carried out in five electronic databases. Cluster characteristics were extracted in accordance with authors’ descriptions by two independent reviewers and a third resolved any disagreements. Seventeen studies met the inclusion criteria and the population age ranged from six to 18 years old. Nine, twelve, and ten cluster types were identified for mixed-sex samples, boys, and girls, respectively. While girls were in clusters characterized by “Low PA Low SB” and “Low PA High SB”, the majority of boys were in clusters defined by “High PA High SB” and “High PA Low SB”. Few associations were found between sociodemographic variables and all cluster types. Boys and girls in “High PA High SB” clusters had higher BMI and obesity in most of the tested associations. In contrast, those in the “High PA Low SB” clusters presented lower BMI, waist circumference, and overweight and obesity. Different cluster patterns of PA and SB were observed in boys and girls. However, in both sexes, a better adiposity profile was found among children and adolescents in “High PA Low SB” clusters. Our results suggest that it is not enough to increase PA to manage the adiposity correlates, it is also necessary to reduce SB in this population.

This chapters addresses digital inequalities in young people’s daily lives and well-being. The chapter examines how adolescents’ digital engagement differs across family socioeconomic status (SES) and gender, and how it relates to their mental health outcomes. Analyses use longitudinal data from the Growing Up in Ireland study from age 9 to 18, combined with cross-national data from the Health Behaviour in School-Aged survey on adolescents aged 11-15 across 35 industrialised countries. Longitudinal analyses reveal that low-SES adolescents and girls experience higher mental health problems as they increase their time using digital devices, compared to high-SES adolescents and boys. Cross-national analyses indicate that, while boys spend more time in digital activities, girls are at higher risks of experiencing mental health problems from engaging with digital activities. However, the magnitude of these gendered patterns differs markedly across national contexts. Cross-country comparisons on SES yield mixed results: in some countries low-SES adolescents are mentally more harmed by their digital engagement (i.e., Switzerland, Austria, Norway), but in other countries high-SES adolescents are those at higher mental health risks from using digital devices (i.e., Portugal, Czech Republic, Bulgaria). The chapter findings are discussed within the existing literature on digital inequalities and young people’s well-being.

Background
Physical activity (PA) can reduce young peoples’ risk of depressive symptoms. Associations between PA and depressive symptoms are often investigated over timeframes spanning minutes to weeks. Less is known about whether childhood/adolescent PA can predict depressive symptoms in early adulthood.

Methods
Using a nationally representative sample from Ireland, latent growth mixture modelling was performed to investigate the extent to which different PA trajectories existed from ages 9–17, whether gender, weight status, and socio-economic deprivation at age 9, predicted PA trajectories from ages 9–17, and whether trajectory class membership predicted depressive symptoms at age 20.

Results
A 4-class solution was the best fit to the data (AIC = 52 175.69; BIC = 52 302.69; ssaBIC = 52 245.49; entropy = 1.00). Classes were labelled according to their baseline PA and slope of their trajectory: ‘High-Decreasers’; ‘Moderate-Decreasers’; ‘Moderate-Stable’; and ‘Low-Increasers’. A negative linear association existed between activity trajectory and the likelihood class members were female, overweight or socioeconomically deprived at age 9. The most active class (High-Decreasers) were significantly less likely to report depressive symptoms at age 20 than other classes.

Conclusions
Multiple PA trajectories exist throughout childhood and adolescence although differences in PA levels reduced over time. The most/least active children continued to be the most/least active throughout adolescence. Those most active were least at risk of depressive symptoms in early adulthood. Being female, overweight or experiencing deprivation at age 9 were all risk factors for inactivity throughout adolescence. Findings have implications for public health and PA promotion in young people

Despite the right of disabled people to full social and economic inclusion, many face multiple day-to-day and systemic challenges. These include but are not limited to additional expenses, access to housing, and everyday accessibility difficulties. Surveys show the general public hold positive attitudes towards policies that seek to enable disabled people to overcome these challenges, but standard survey methods are susceptible to response biases that may overestimate this support. This study aimed to test whether two such biases influence support for disability policy in Ireland: social desirability bias (i.e. the tendency for survey respondents to alter their responses in order to present themselves in a positive light); and inattention to the implications of policy support (e.g. that welfare policies require funding). Together the survey experiments covered a range of policy issues and types of disability, as identified in previous research and in consultation with the disability advisory group for the project.