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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: 3
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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: 3
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Abstract: Experts worldwide have constantly been calling for high-quality open-access epidemiological data, given the fast-evolving nature of the COVID-19 pandemic. Disaggregated high-level granularity records are still scant despite being essential to corroborate the effectiveness of virus containment measures and even vaccination strategies. We provide a complete dataset containing disaggregated epidemiological information about all the COVID-19 patients officially reported during the first 250 days of the COVID-19 pandemic in Bucharest (Romania). We give the sex, age, and the COVID-19 infection confirmation date for 46.440 individual cases, between March 7th and November 11th, 2020. Additionally, we provide context-wise information such as the stringency levels of the measures taken by the Romanian authorities. We procured the data from the local public health authorities and systemized it to respond to the urgent international need of comparing observational data collected from various populations. Our dataset may help understand COVID-19 transmission in highly dense urban communities, perform virus spreading simulations, ascertain the effects of non-pharmaceutical interventions, and craft better vaccination strategies.
Keywords: disaggregated data, age, sex, COVID-19, pandemic, Romania
Published in DKUM: 15.07.2024; Views: 92; Downloads: 8
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Abstract: We describe the early spread of the novel coronavirus (COVID-19) and the first human-to-human transmission networks, in Romania. We profiled the first 147 cases referring to sex, age, place of residence, probable country of infection, return day to Romania, COVID-19 confirmation date and the probable modes of COVID-19 transmissions. Also, we analysed human-to-human transmission networks and explored their structural features and time dynamics. In Romania, local cycles of transmission were preceded by imported cases, predominantly from Italy. We observed an average of 4.8 days (s.d. = 4.0) between the arrival to a Romanian county and COVID-19 confirmation. Furthermore, among the first 147 COVID-19 patients, 88 were imported cases (64 carriers from Italy), 54 were domestic cases, while for five cases the source of infection was unknown. The early human-to-human transmission networks illustrated a limited geographical dispersion, the presence of super-spreaders and the risk of COVID-19 nosocomial infections. COVID-19 occurred in Romania through case importation from Italy. The largest share of the Romanian diaspora is concentrated especially in the northern parts of Italy, heavily affected by COVID-19. Human mobility (including migration) accounts for the COVID-19 transmission and it should be given consideration while tailoring prevention measures.
Keywords: coronavirus, COVID-19, transmission networks, human mobility, migration, nosocomial infections
Published in DKUM: 16.12.2020; Views: 903; Downloads: 215
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