Dietary Patterns of Older Adults in the United States and Their Risk of Listeriosis: Characterizing Sociodemographic and Economic Attributes of Consumers by Dietary Patterns (P18-047-19)

Objectives 1) Determine dietary consumption patterns, among older adults in the United States; 2) Evaluate sociodemographic and economic characteristics associated with each pattern; 3) Determine intake of foods associated with larger relative risk of listeriosis within these patterns; and 4) Rank these patterns based on risk. Methods The study included older adults, age 60 and older, from What We Eat in America, National Health and Nutrition Examination Surveys 2009–2010, 2011–2012 and 2013–2014 (n = 4967). Cluster analysis based on day 1 24-hour dietary recalls was used to define dietary patterns. ANOVA with Dunnett's method of adjustment used to evaluate significant differences in mean intake of foods associated with higher risk of listeriosis within each pattern. Patterns were ranked based on relative risk of listeriosis using outbreak illness attribution and risk assessment data. Results Five distinct dietary patterns were identified -Vegetables, Fruits & Oils; Mixed Dishes; RTE (Ready-To-Eat) Cereal, Milk & Yogurt; Meat & Potatoes; and Cured Meats & Cheese. The patterns ranked at highest relative risk of listeriosis, based on 2013 outbreak illness attribution data, were (1) the Vegetables, Fruits & Oils, characterized by relatively higher intakes of fruits, vegetables, and vegetable oils (∼22% respondents), (2) the RTE (Ready-To-Eat) Cereal, Milk & Yogurt, with relatively higher intakes of cereal, milk, and yogurt (16% respondents); and, based on 2003 risk assessment data, (3) the Cured Meats & Cheese with relatively higher intakes of breads, cheese, and cured meats (∼9.6% respondents). Individuals consuming these dietary patterns differed in sex, race/ethnicity, food security, self-rated diet quality, and self-rated health. Conclusions Cluster analysis, despite methodological limitations, provides new information on consumption, sociodemographic, and economic characteristics of subgroups within susceptible populations that can be used to target educational messages. Funding Sources Agricultural Research Service, US Department of Agriculture; Food and Drug Administration.