Impact of participation in Home-Delivered Meals on nutrient intake, dietary patterns, and food insecurity of older persons in New York state. 2010

Edward A Frongillo, and Wendy S Wolfe
Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, South Carolina 29208, USA. efrongillo@sc.edu

The aim of this study was to determine if (1) participation in Home-Delivered Meals (HDM) results in improved dietary patterns and nutrient intake, lower food insecurity, and reduced loss of weight; (2) subgroups of older persons are more likely to benefit; and (3) nutritional indicators of impact other than nutrient intake may be useful. The design used was quasi-experimental, with longitudinal assessment of individuals on HDM at baseline (before receipt of services), 6, and 12 months, and comparison to non-randomized group receiving other services. Outcomes included measured weight and height, 24-hour dietary recall, and food insecurity. Paired t test, multiple linear regression, and selection models using multiple logistic regression were performed. All older persons in three New York State counties referred for aging services over a 5-month period were asked to participate (n = 456), and 212 agreed (171 on HDM). At 6 months, the sample size was 101 (34 discharged, 42 hospital/died/moved, 26 chose not to continue), and at 12 months it was 68 (similar reasons). After receiving meals for 6 and 12 months, participants showed greater improvement in most dietary intake variables than either a non-HDM comparison group or HDM participants who ate no HDM meal on the day of assessment. Compared to initial values, participants improved significantly in some variables for dietary patterns, nutrient intake, and nutrient density, and were less likely to be food insecure. Furthermore, HDM was more likely to impact those living alone and those with poorer initial status. This study provides strong evidence that HDM has a positive impact on the nutritional well-being of older persons. Food insecurity and dietary patterns are useful nutritional indicators of impact.

UI MeSH Term Description Entries
D008137 Longitudinal Studies Studies in which variables relating to an individual or group of individuals are assessed over a period of time. Bogalusa Heart Study,California Teachers Study,Framingham Heart Study,Jackson Heart Study,Longitudinal Survey,Tuskegee Syphilis Study,Bogalusa Heart Studies,California Teachers Studies,Framingham Heart Studies,Heart Studies, Bogalusa,Heart Studies, Framingham,Heart Studies, Jackson,Heart Study, Bogalusa,Heart Study, Framingham,Heart Study, Jackson,Jackson Heart Studies,Longitudinal Study,Longitudinal Surveys,Studies, Bogalusa Heart,Studies, California Teachers,Studies, Jackson Heart,Studies, Longitudinal,Study, Bogalusa Heart,Study, California Teachers,Study, Longitudinal,Survey, Longitudinal,Surveys, Longitudinal,Syphilis Studies, Tuskegee,Syphilis Study, Tuskegee,Teachers Studies, California,Teachers Study, California,Tuskegee Syphilis Studies
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009518 New York State bounded on the north by Lake Ontario and Canada, on the east by Vermont, Massachusetts, and Connecticut, on the south by the Atlantic Ocean, New Jersey, and Pennsylvania, and on the west by Pennsylvania, Lake Erie, and Canada.
D009749 Nutrition Surveys A systematic collection of factual data pertaining to the nutritional status of a human population within a given geographic area. Data from these surveys are used in preparing NUTRITION ASSESSMENTS. NHANES,National Health and Nutrition Examination Survey,Nutritional Surveys,Nutrition Survey,Nutritional Survey,Survey, Nutrition,Survey, Nutritional,Surveys, Nutrition,Surveys, Nutritional
D009752 Nutritional Status State of the body in relation to the consumption and utilization of nutrients. Nutrition Status,Status, Nutrition,Status, Nutritional
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002149 Energy Intake Total number of calories taken in daily whether ingested or by parenteral routes. Caloric Intake,Calorie Intake,Intake, Calorie,Intake, Energy
D004032 Diet Regular course of eating and drinking adopted by a person or animal. Diets
D005260 Female Females

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