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J Am Geriatr Soc ; 66(5): 1017-1024, 2018 05.
Article in English | MEDLINE | ID: mdl-29492953

ABSTRACT

OBJECTIVES: To estimate food insecurity prevalence and develop a statistical prediction model for food insecurity. DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente Colorado. PARTICIPANTS: Adult members who completed a pre-Medicare Annual Wellness Visit survey. MEASUREMENTS: Food insecurity was assessed using a single screening question. Sociodemographic and clinical characteristics from electronic health records and self-reported characteristics from the survey were used to develop the prediction model. RESULTS: Of 130,208 older adult members between January 2012 and December 2015, 50,097 (38.5%) completed food insecurity screening, 2,859 of whom (5.7% of respondents) reported food insecurity. The prevalence of food insecurity was 10.0% or greater among individuals who were black or Hispanic, had less than high school education, had Medicaid insurance, were extremely obese, had poor health status or quality of life, had depression or anxiety, had impairments in specific activities of daily living, had other nutritional risk factors, or were socially isolated (all p<.001). A multivariable model based on these and other characteristics showed moderate discrimination (c-statistic = 0.74) between individuals with food insecurity and those without and 14.3% of individuals in the highest quintile of risk reported food insecurity. CONCLUSION: Food insecurity is prevalent even in older adults with private-sector healthcare coverage. Specific individual characteristics, and a model based on those characteristics, can identify older adults at higher risk of food insecurity. System-level interventions will be necessary to connect older adults with community-based food resources.


Subject(s)
Delivery of Health Care, Integrated , Food Supply/statistics & numerical data , Social Determinants of Health , Aged , Colorado , Female , Health Status , Humans , Male , Medicare , Prevalence , Quality of Life , Retrospective Studies , Risk Factors , Surveys and Questionnaires , United States
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