Objective: The aim of the present study was to examine to what extent different social network mechanisms are involved in the pathogenesis of obesity and insulin-resistance.
Design: We used nonparametric and parametric regression models to analyse whether individual BMI and HOMA-IR are determined by social network characteristics.
Subjects And Methods: A total of 677 probands (EGO) and 3033 social network partners (ALTER) were included in the study. Data gathered from the probands include anthropometric measures, HOMA-IR index, health attitudes, behavioural and socio-economic variables and social network data.
Results: We found significant treatment effects for ALTERs frequent dieting (p<0.001) and ALTERs health oriented nutritional attitudes (p<0.001) on EGO's BMI, establishing a significant indirect network effect also on EGO's insulin resistance. Most importantly, we also found significant direct social network effects on EGO's insulin resistance, evidenced by an effect of ALTERs frequent dieting (p = 0.033) and ALTERs sport activities (p = 0.041) to decrease EGO's HOMA-IR index independently of EGO's BMI.
Conclusions: Social network phenomena appear not only to be relevant for the spread of obesity, but also for the spread of insulin resistance as the basis for type 2 diabetes. Attitudes and behaviour of peer groups influence EGO's health status not only via social mechanisms, but also via socio-biological mechanisms, i.e. higher brain areas might be influenced not only by biological signals from the own organism, but also by behaviour and knowledge from different human individuals. Our approach allows the identification of peer group influence controlling for potential homophily even when using cross-sectional observational data.
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J Affect Disord
January 2025
Center for Anti-racism, Social Justice & Public Health, New York University School of Global Public Health, New York, NY, USA; Department of Biostatistics, New York University School of Global Public Health, New York, NY, USA. Electronic address:
Background: A knowledge gap exists in understanding the role of social isolation as a determinant of mental health among hybrid employees during the COVID-19 era.
Methods: Using 2024 Household Pulse Survey data, we investigated the relationship between social isolation and mental health among US hybrid employees. We assessed depression symptoms using the Patient Health Questionnaire-2 and anxiety symptoms using the Generalized Anxiety Disorder-2.
Objectives: To characterize the 1) types of material goods (non-medical items) offered in pediatric residency continuity clinics, 2) consistency of good availability, 3) funding sources used to support supply, 4) whether goods are provided in response to social needs screening, and 5) common challenges with provision. To assess the extent to which provision of goods varied by clinic size and proportion of publicly insured patients.
Methods: Faculty and staff members from clinics in the Academic Pediatric Association's Continuity Research Network (APA CORNET) completed an online survey about material goods provided in their clinic in the preceding 12 months.
R Soc Open Sci
January 2025
Mathematics Application Consortium for Science and Industry (MACSI), University of Limerick, Limerick, Ireland.
The analysis of social networks enables the understanding of social interactions, polarization of ideas and the spread of information, and therefore plays an important role in society. We use Twitter data-as it is a popular venue for the expression of opinion and dissemination of information-to identify opposing sides of a debate and, importantly, to observe how information spreads between these groups in our current polarized climate. To achieve this, we collected over 688 000 tweets from the Irish Abortion Referendum of 2018 to build a conversation network from users' mentions with sentiment-based homophily.
View Article and Find Full Text PDFFront Child Adolesc Psychiatry
November 2024
Department of Psychology, Palo Alto University, Palo Alto, CA, United States.
Introduction: Autism Spectrum Disorder (ASD) is characterized by deficits in social cognition, self-referential processing, and restricted repetitive behaviors. Despite the established clinical symptoms and neurofunctional alterations in ASD, definitive biomarkers for ASD features during neurodevelopment remain unknown. In this study, we aimed to explore if activation in brain regions of the default mode network (DMN), specifically the medial prefrontal cortex (MPC), posterior cingulate cortex (PCC), superior temporal sulcus (STS), inferior frontal gyrus (IFG), angular gyrus (AG), and the temporoparietal junction (TPJ), during resting-state functional magnetic resonance imaging (rs-fMRI) is associated with possible phenotypic features of autism (PPFA) in a large, diverse youth cohort.
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