Social Network Characteristics Are Correlated with Dietary Patterns Among Middle Aged and Older South Asians (SA) Living in the United States (US) (P04-124-19). (13th June 2019)

• Record Type: Journal Article
• Authors: Talegawkar, Sameera; Lancki, Nicola; Siddique, Juned; Gadgil, Meghana; Kanaya, Alka; Jin, Yichen; Schneider, John; Horn, Linda Van; Koning, Lawrence de; Kandula, Namratha
• Is Part Of: Current developments in nutrition. Volume 3(2019)Supplement 1
• Publication Date: 2019-06-13
• Subjects: Nutrition -- Periodicals; Nutritional Physiological Phenomena; Nutrition; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 612.3
• DOI: 10.1093/cdn/nzz051.P04-124-19
• Languages: English
• ISSNs: 2475-2991

Abstract

Abstract: Objectives: Social and cultural norms, operating through social networks, may influence an individual's dietary choices. We examined the correlations among social network characteristics and dietary patterns among SA in the US. Methods: Data from the Mediators of Atherosclerosis in South Asians Living in America Social Network study were analyzed among 756 participants (mean age 59 y standard deviation [SD] = 9 y; 44% women). A culturally adapted, validated food frequency questionnaire was used for dietary assessment. Principal component analysis yielded, three dietary patterns named: "Animal protein", "Fried snacks, sweets and high-fat dairy", and "Fruits, vegetables, nuts and legumes", based on contribution of food groups. Social network characteristics were assessed using a standard egocentric approach, where participants (egos) self-reported data on perceived dietary habits of their network members. Partial correlations between social network characteristics and egos' dietary patterns were examined. Results: The mean social network size of egos was 4.2 (SD = 1.1), with high proportion of network members being family (72%), SA ethnicity (89%), and half having daily contact. Higher scores for the "Animal protein" pattern among egos, were negatively correlated with daily fruits and cooked vegetables consumption of their network. This pattern was also positively correlated with the proportion of network who weekly consumed non-South Asian foods, diet drinks, non-vegetarian foods, processed meat and fried foods, and dined out. Scores for the "Fried snacks, sweets and high-fat dairy" pattern were positively correlated with proportion of network who weekly consumed sugar-sweetened beverages, South Asian sweets, fried foods, fast foods and ghee (clarified butter). Higher scores for the "Fruits, vegetables, nuts and legumes" pattern were positively associated with proportion of network who daily consumed both raw and cooked vegetables and fruits, and brown rice/quinoa weekly. Conclusions: Network member characteristics and perceived dietary behaviors of network members were correlated with dietary patterns of SA in the US. Dietary intervention studies among SA should consider social network characteristics as candidate components for dietary intervention. Funding Sources: National Institutes of Health. Supporting Tables, Images and/or Graphs: