1. Processed food intake assortativity in the personal networks of older adultsMarian-Gabriel Hâncean, Jürgen Lerner, Matjaž Perc, José Luis Molina González, Marius Geanta, Iulian Oană, Bianca-Elena Mihǎilǎ, 2025, original scientific article Abstract: Existing research indicates that dietary habits spread through social networks, yet the impact on populations in Eastern Europe, particularly in rural areas, is less understood. We examine the influence of personal networks on the consumption of high-salt processed foods among individuals in rural Romania, with a specific focus on older adults. Using a personal network analysis, we analyze data from 83 participants of varying ages and their social contacts through multi-level regression models. The inclusion of participants across a wider age range allows us to capture the broader dynamics of social networks, reflecting the intergenerational nature of rural communities. Our findings reveal assortativity in dietary habits, indicating that individuals cluster with others who share similar food consumption patterns. Our results underscore the need for public health interventions that account for the influence of social networks on dietary behavior, as addressing high salt intake and its associated health risks may require considering the broader social context beyond older adults. The study contributes to understanding the social determinants of dietary behaviors and highlights the role of personal networks in shaping food choices in vulnerable populations.
Keywords: processed food, older adults, social networks, assortativity, Romania, Eastern Europe
Published in DKUM: 31.03.2025; Views: 0; Downloads: 10
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2. Online media use and COVID-19 vaccination in real-world personal networks : quantitative studyIulian Oană, Marian-Gabriel Hâncean, Matjaž Perc, Jürgen Lerner, Bianca-Elena Mihǎilǎ, Marius Geanta, José Luis Molina González, Isabela Tincă, Carolina Espina, 2024, original scientific article Keywords: vaccine hesitancy, online media, assortative mixing, personal network analysis, social network analysis, vaccination, health information
Published in DKUM: 21.03.2025; Views: 0; Downloads: 4
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3. Cross-sectional personal network analysis of adult smoking in rural areasBianca-Elena Mihǎilǎ, Marian-Gabriel Hâncean, Matjaž Perc, Jürgen Lerner, Iulian Oană, Marius Geanta, José Luis Molina González, Cosmina Cioroboiu, 2024, original scientific article Abstract: Research on smoking behaviour has primarily focused on adolescents, with less attention given to middle-aged and older adults in rural settings. This study examines the influence of personal networks and sociodemographic factors on smoking behaviour in a rural Romanian community. We analysed data from 76 participants, collected through face-to-face interviews, including smoking status (non-smokers, current and former smokers), social ties and demographic details. Multilevel regression models were used to predict smoking status. The results indicate that social networks are essential in shaping smoking habits. Current smokers were more likely to have smoking family members, reinforcing smoking within familial networks, while non-smokers were typically embedded in non-smoking environments. Gender and age patterns show that women were less likely to smoke, and older adults were more likely to have quit smoking. These findings suggest that targeted interventions should focus not only on individuals but also on their social networks. In rural areas, family-based approaches may be particularly effective due to the strong influence of familial ties. Additionally, encouraging connections with non-smokers and former smokers could help disrupt smoking clusters, supporting smoking cessation efforts.
Keywords: network science, human behaviour, data science, smoking, social physics
Published in DKUM: 03.12.2024; Views: 0; Downloads: 4
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4. Assortative mixing of opinions about COVID‑19 vaccination in personal networksMarian-Gabriel Hâncean, Jürgen Lerner, Matjaž Perc, José Luis Molina González, Marius Geanta, 2024, original scientific article Abstract: Many countries worldwide had difculties reaching a sufciently high vaccination uptake during the COVID-19 pandemic. Given this context, we collected data from a panel of 30,000 individuals, which were representative of the population of Romania (a country in Eastern Europe with a low 42.6% vaccination rate) to determine whether people are more likely to be connected to peers displaying similar opinions about COVID-19 vaccination. We extracted 443 personal networks, amounting to 4430 alters. We estimated multilevel logistic regression models with random-ego-level intercepts to predict individual opinions about COVID-19 vaccination. Our evidence indicates positive opinions about the COVID-19 vaccination cluster. Namely, the likelihood of having a positive opinion about COVID-19 vaccination increases when peers have, on average, a more positive attitude than the rest of the nodes in the network (OR 1.31, p < 0.001). We also found that individuals with higher education and age are more likely to hold a positive opinion about COVID-19 vaccination. With the given empirical data, our study cannot reveal whether this assortative mixing of opinions is due to social infuence or social selection. However, it may nevertheless have implications for public health interventions, especially in countries that strive to reach higher uptake rates. Understanding opinions about vaccination can act as an early warning system for potential outbreaks, inform predictions about vaccination uptake, or help supply chain management for vaccine distribution.
Keywords: assortative mixing, opinions, vaccination, personal network, social physics
Published in DKUM: 27.11.2024; Views: 0; Downloads: 14
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