A network analysis of depressive symptoms in adults with and without diabetes: findings from the Irish longitudinal study on ageing.

OBJECTIVES: This study aimed to estimate networks of depressive symptoms among Irish adults with and without diabetes at two time points and compare between the two groups at each time point using data from the Irish Longitudinal Study on Ageing (TILDA). METHODS: Participants were from Wave 1 (2009-2011) and Wave 4 (2016) of TILDA, with n = 639 participants with diabetes and n = 7,837 without diabetes at Wave 1, and n = 1,151 with diabetes and n = 4,531 without diabetes at Wave 4. Depressive symptoms were measured using the 8 items of the Center for Epidemiologic Studies Depression Scale. Network psychometric analysis was used to examine symptom centrality, symptom-level associations, and network comparisons at each time point. RESULTS: Stable, strongly connected networks emerged for people with and without diabetes at both time points. The symptoms of feeling depressed, feeling like everything's an effort, not enjoying life, feeling sad, and couldn't get going were the most central nodes in all networks, which did not differ between people with and without diabetes. However, for people with diabetes, the network was more densely connected at Wave 4, when the sample was predominately people with newly diagnosed diabetes. Furthermore, the relationship between 'felt lonely' and 'couldn't get going' and between 'not enjoying life' and 'sad' was significantly stronger for people with diabetes than for those without. CONCLUSIONS: This study provides a more detailed understanding of the structure of depressive symptoms at two time points in older Irish adults with and without type 1 or type 2 diabetes.

Neighbourhood characteristics and socioeconomic inequalities in child mental health: Cross-sectional and longitudinal findings from the Growing Up in Ireland study.

This study examined the role of neighbourhood characteristics in explaining socioeconomic inequalities in child mental health (the total difficulties score from the Strengths and Difficulties Questionnaire) using data from Cohort '08 of Growing Up in Ireland Waves 3 (age 5; baseline) and 5 (age 9; follow-up). Twenty neighbourhood items were grouped into neighbourhood safety, built environments, cohesion, interaction, and disorder. Data were analysed using regression, single and multiple mediation, and network psychometric analyses. We found that neighbourhood safety, cohesion, interaction, and disorder were associated with child mental health. These four domains separately (by up to 18 %) or in concert (by up to 23 %) partially explained socioeconomic inequalities in child mental health. Built environments may explain socioeconomic inequalities in mental health in urban children only. Findings from network analysis indicated that specific concerns over "people being drunk or taking drugs in public" and "this is a safe neighbourhood" had the strongest connections with child mental health. Improving neighbourhood characteristics may be important to reduce socioeconomic inequalities in child mental health in Ireland.

Diabetes Distress, Depressive Symptoms, and Anxiety Symptoms in People With Type 2 Diabetes: A Network Analysis Approach to Understanding Comorbidity.

OBJECTIVE: In this study, we aimed to explore interactions between individual items that assess diabetes distress, depressive symptoms, and anxiety symptoms in a cohort of adults with type 2 diabetes using network analysis. RESEARCH DESIGN AND METHODS: Participants (N = 1,796) were from the Montreal Evaluation of Diabetes Treatment (EDIT) study from Quebec, Canada. A network of diabetes distress was estimated using the 17 items of the Diabetes Distress Scale (DDS-17). A second network was estimated using the DDS-17 items, the nine items of the Patient Health Questionnaire (PHQ-9), and the seven items of the Generalized Anxiety Disorder Assessment (GAD-7). Network analysis was used to identify central items, clusters of items, and items that may act as bridges between diabetes distress, depressive symptoms, and anxiety symptoms. RESULTS: Regimen-related and physician-related problems were among the most central (highly connected) and influential (most positive connections) in the diabetes distress network. The depressive symptom of failure was found to be a potential bridge between depression and diabetes distress, being highly connected to diabetes distress items. The anxiety symptoms of worrying too much, uncontrollable worry, and trouble relaxing were identified as bridges linking both anxiety and depressive items and anxiety and diabetes distress items, respectively. CONCLUSIONS: Regimen-related and physician-related diabetes-specific problems may be important in contributing to the development and maintenance of diabetes distress. Feelings of failure and worry are potentially strong candidates for explaining comorbidity. These individual diabetes-specific problems and mental health symptoms could hold promise for targeted interventions for people with type 2 diabetes.