Tiffany L Thomson1, Valdis Krebs2, Julianna M Nemeth3, Bo Lu4, Juan Peng5, Nathan J Doogan3, Amy K Ferketich6, Douglas M Post7, Christopher R Browning8, Electra D Paskett9, Mary Ellen Wewers3. 1. Division of Health Behavior and Health Promotion, The Ohio State University College of Public Health, Columbus, OH, USA. thomson.46@osu.edu. 2. Orgnet LLC, Cleveland, OH, USA. 3. Division of Health Behavior and Health Promotion, The Ohio State University College of Public Health, Columbus, OH, USA. 4. Division of Biostatistics, The Ohio State University College of Public Health, Columbus, OH, USA. 5. Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA. 6. Division of Epidemiology, The Ohio State University College of Public Health, Columbus, OH, USA. 7. Department of Family Medicine, The Ohio State University College of Medicine, Columbus, OH, USA. 8. Department of Sociology, The Ohio State University College of Arts and Sciences, Columbus, OH, USA. 9. Division of Cancer Prevention and Control, Department of Internal Medicine, The Ohio State University College of Medicine, Columbus, OH, USA.
Abstract
OBJECTIVES: We characterized the social network characteristics of women in Ohio Appalachia according to smoking status. METHODS: Women ≥18 years of age were recruited from 3 Ohio Appalachian counties to complete a cross-sectional survey. Sociodemographic and smoking-related information was collected by face-to-face interview. A description of women's time (ie, spends time with) and advice (ie, gets support and advice) social network ties were obtained. An egocentric social network analysis was completed, according to the woman's smoking status. RESULTS: Of the 408 women enrolled, 20.1% were current smokers. Time networks were larger (p < .001), more dense (p < .001), and more redundant (p < .001) than advice networks. Current smokers had a greater proportion of smoking ties in their networks compared to non-smokers (p < .001). Daily face-to-face contact with non-smoking ties was greater in time compared to advice networks (p < .001). Current smokers in advice networks tended to have less daily contact with non-smoking ties than non-smokers (p = .06). CONCLUSIONS: Differences existed in characteristics of time versus advice egocentric networks. Smoking status was associated with these differences. Results will assist with future development of a network-based smoking cessation intervention.
OBJECTIVES: We characterized the social network characteristics of women in Ohio Appalachia according to smoking status. METHODS:Women ≥18 years of age were recruited from 3 Ohio Appalachian counties to complete a cross-sectional survey. Sociodemographic and smoking-related information was collected by face-to-face interview. A description of women's time (ie, spends time with) and advice (ie, gets support and advice) social network ties were obtained. An egocentric social network analysis was completed, according to the woman's smoking status. RESULTS: Of the 408 women enrolled, 20.1% were current smokers. Time networks were larger (p < .001), more dense (p < .001), and more redundant (p < .001) than advice networks. Current smokers had a greater proportion of smoking ties in their networks compared to non-smokers (p < .001). Daily face-to-face contact with non-smoking ties was greater in time compared to advice networks (p < .001). Current smokers in advice networks tended to have less daily contact with non-smoking ties than non-smokers (p = .06). CONCLUSIONS: Differences existed in characteristics of time versus advice egocentric networks. Smoking status was associated with these differences. Results will assist with future development of a network-based smoking cessation intervention.
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