Social clustering of health behaviors in rural Romania: a personal network analysis
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Abstract
Background. Romanian sociology has lacked systematic personal network analysis (PNA) methods for rural research. Social clustering patterns in health behaviors indicate whether interventions should target individuals or social groups, yet detecting these patterns requires network-level data. We develop and test a PNA design for Romanian rural contexts, using health behaviors to demonstrate the method’s capacity to detect social clustering. Methods. We conducted tablet-assisted interviews with 83 adult residents in Lerești (Argeș County). Respondents listed social contacts and provided demographic and behavioral data for themselves and their contacts. We tested the protocol across three health topics: vaccination and media use (61 ego networks), smoking (76 egos), and processed food high in salt intake (83 ego networks). Mixed-effects models analyzed clustering patterns with alters nested within egos. Results. We detected social clustering in all three topics of interest. Vaccination showed assortative patterns (OR = 3.75, 95% CI 1.79-7.85) and media effects: online-only health information use associated with lower alter vaccination (OR = 0.37, 95% CI 0.15-0.92). Smoking clustered in family-dense networks with demographic variations. Food intake displayed local assortativity beyond composition effects (OR = 1.17, p = 0.01). Network context explained 11-67% of behavioral variance across health topics. Conclusions. PNA can be systematically applied in Romanian rural communities to detect social mechanisms across behavioral domains. Our design generates reproducible data suitable for mixed-effects analysis and reveals network effects that individual-level analysis would miss. This method contributes to Romanian rural sociology’s empirical tradition and provides tools for network-informed public health interventions.
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