Resources in women's social networks for food shopping are more strongly associated with better dietary quality than people: A cross-sectional study.

When healthy people are part of an individual's social network, those individuals will have better dietary quality. Little, however, is known about whether social networks for food shopping, including both people and resources (e.g. recipes, weight loss programmes and food advertisements) are associated with dietary quality. The aim of this study was to explore the relationship between social networks for food shopping and dietary quality, and whether this differs for people and resources, among women aged 18-45 years. A total of 129 participants completed a cross-sectional questionnaire including an ego-centric Social Network Exposure tool and short Food Frequency Questionnaire. Associations between dietary quality and type of network member, perceived healthiness and support for healthy shopping choices were explored using linear regression models. Analyses revealed that participants who nominated people in their food shopping social network that eat healthily or support healthy food shopping had better dietary quality (β = 0.16 SD per 1-point change on a 4-point scale, 95%CI -0.06, 0.39; β = 0.20, 95%CI -0.07, 0.46, respectively). Resources in participants' food shopping social networks which promote healthy eating or support healthy shopping were associated with better dietary quality. These associations remained robust after adjustment for confounding variables identified using a directed acyclic graph (β = 0.31 SD per 1-point change on a 4-point scale, 95%CI 0.03, 0.58; β = 0.44, 95%CI 0.09, 0.79 respectively). The results were strengthened when the outcome was multiplied by frequency of contact (β = 0.33, 95%CI 0.05, 0.61; β = 0.47, 95%CI 0.11, 0.83 respectively). This study suggests that resources which promote healthy eating and healthy food shopping have a stronger association with dietary quality than social support from people. Further research is required in a larger sample, including multiple time-points, to confirm these findings.

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