BACKGROUND: Household food purchases are potential indicators of the quality of the home food environment, and grocery purchase behavior is a main focus of US Department of Agriculture (USDA) nutrition education programs; therefore, objective measures of grocery purchases are needed. OBJECTIVE: The objective of the study was to evaluate the Grocery Purchase Quality Index-2016 (GPQI-2016) as a tool for assessing grocery food purchase quality by using the Healthy Eating Index-2015 (HEI-2015) as the reference standard. DESIGN: In 2012, the USDA Economic Research Service conducted the National Household Food Acquisition and Purchase Survey. Members of participating households recorded all foods acquired for a week. Foods purchased at stores were mapped to the 29 food categories used in USDA Food Plans, expenditure shares were estimated, and GPQI-2016 scores were calculated. USDA food codes, provided in the survey database, were used to calculate the HEI-2015. PARTICIPANTS/ SETTING: All households in the 48 coterminous states were eligible for the survey. The analytic sample size was 4,276 households. MAIN OUTCOME MEASURES: GPQI-2016 and HEI-2015 scores were compared. STATISTICAL ANALYSES PERFORMED: Correlation of scores was assessed using Spearman's correlation coefficient. Linear regression models with fixed effects were used to determine differences among various subgroups of households. RESULTS: The correlation coefficient for the total GPQI-2016 score and the total HEI-2015 score was 0.70. For the component scores, the strongest correlations were for Total and Whole Fruit (0.89 to 0.90); the weakest were for Dairy (0.67), Refined Grains (0.66), and Sweets and Sodas/Added Sugars (0.65) (all, P<0.01). Both the GPQI-2016 and HEI-2015 were significantly different among subgroups in expected directions. CONCLUSIONS: Overall, the GPQI-2016, estimated from a national survey of households, performed similarly to the HEI-2015. The tool has potential for evaluating nutrition education programs and retail-oriented interventions when the nutrient content and gram weights of foods purchased are not available.
BACKGROUND: Household food purchases are potential indicators of the quality of the home food environment, and grocery purchase behavior is a main focus of US Department of Agriculture (USDA) nutrition education programs; therefore, objective measures of grocery purchases are needed. OBJECTIVE: The objective of the study was to evaluate the Grocery Purchase Quality Index-2016 (GPQI-2016) as a tool for assessing grocery food purchase quality by using the Healthy Eating Index-2015 (HEI-2015) as the reference standard. DESIGN: In 2012, the USDA Economic Research Service conducted the National Household Food Acquisition and Purchase Survey. Members of participating households recorded all foods acquired for a week. Foods purchased at stores were mapped to the 29 food categories used in USDA Food Plans, expenditure shares were estimated, and GPQI-2016 scores were calculated. USDA food codes, provided in the survey database, were used to calculate the HEI-2015. PARTICIPANTS/ SETTING: All households in the 48 coterminous states were eligible for the survey. The analytic sample size was 4,276 households. MAIN OUTCOME MEASURES: GPQI-2016 and HEI-2015 scores were compared. STATISTICAL ANALYSES PERFORMED: Correlation of scores was assessed using Spearman's correlation coefficient. Linear regression models with fixed effects were used to determine differences among various subgroups of households. RESULTS: The correlation coefficient for the total GPQI-2016 score and the total HEI-2015 score was 0.70. For the component scores, the strongest correlations were for Total and Whole Fruit (0.89 to 0.90); the weakest were for Dairy (0.67), Refined Grains (0.66), and Sweets and Sodas/Added Sugars (0.65) (all, P<0.01). Both the GPQI-2016 and HEI-2015 were significantly different among subgroups in expected directions. CONCLUSIONS: Overall, the GPQI-2016, estimated from a national survey of households, performed similarly to the HEI-2015. The tool has potential for evaluating nutrition education programs and retail-oriented interventions when the nutrient content and gram weights of foods purchased are not available.
Authors: Lisa Harnack; Joseph Redden; Simone French; Nancy E Sherwood; Gabrielle Rivera; Sruthi Valluri; Muna Tahir Journal: Public Health Nutr Date: 2021-02-26 Impact factor: 4.539
Authors: Katja A Schönenberger; Luca Cossu; Francesco Prendin; Giacomo Cappon; Jing Wu; Klaus L Fuchs; Simon Mayer; David Herzig; Andrea Facchinetti; Lia Bally Journal: Front Nutr Date: 2022-04-07
Authors: Maya Vadiveloo; Xintong Guan; Haley W Parker; Elie Perraud; Ashley Buchanan; Stephen Atlas; Anne N Thorndike Journal: JAMA Netw Open Date: 2021-02-01