The Grocery Purchase Quality Index-2016 Performs Similarly to the Healthy Eating Index-2015 in a National Survey of Household Food Purchases.

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.

An Innovative Method for Monitoring Food Quality and the Healthfulness of Consumers' Grocery Purchases.

This study presents a method laying the groundwork for systematically monitoring food quality and the healthfulness of consumers' point-of-sale grocery purchases. The method automates the process of identifying United States Department of Agriculture (USDA) Food Patterns Equivalent Database (FPED) components of grocery food items. The input to the process is the compact abbreviated descriptions of food items that are similar to those appearing on the point-of-sale sales receipts of most food retailers. The FPED components of grocery food items are identified using Natural Language Processing techniques combined with a collection of food concept maps and relationships that are manually built using the USDA Food and Nutrient Database for Dietary Studies, the USDA National Nutrient Database for Standard Reference, the What We Eat In America food categories, and the hierarchical organization of food items used by many grocery stores. We have established the construct validity of the method using data from the National Health and Nutrition Examination Survey, but further evaluation of validity and reliability will require a large-scale reference standard with known grocery food quality measures. Here we evaluate the method's utility in identifying the FPED components of grocery food items available in a large sample of retail grocery sales data (~190 million transaction records).

The Relationship between Social Support and Diet Quality in Middle-Aged and Older Adults in the United States.

BACKGROUND: Social support has been associated with physical and mental health; however, the relationship between social support and diet quality is not well understood. OBJECTIVE: The purpose of this research was to assess the relationship between social support and overall diet quality among US adults. DESIGN/PARTICIPANTS: This study was a secondary analysis of data from adults aged 40 years and older who participated in the cross-sectional 2007-2008 National Health and Nutrition Examination Survey (N=3,243). MAIN OUTCOME MEASURES: Social support was determined by a modification of the Rees Social Support Index (SSI), which is the sum of five dichotomized variables addressing emotional support, financial support, marital status, close friends, and religious service attendance. Overall diet quality was measured by the Healthy Eating Index-2010 (HEI-2010) and calculated from the mean of two 24-hour dietary recalls. STATISTICAL ANALYSES PERFORMED: SAS survey procedures were used to incorporate the appropriate sample design weights. Unweighted frequencies are reported along with weighted means and standard errors (SE). Multivariable linear regression was used to compare the total HEI-2010 scores among the six SSI groups with additional models controlling for sex, age, race/ethnicity, income level, and education level, and stratifying by sex. RESULTS: In an unadjusted model, the mean total HEI-2010 score for those with an SSI score of 0 (n=37) was 50.0 (SE=2.83) compared to 57.1 (SE=0.89) for those with SSI score of 5 (n=676) (P<0.0001). The results were no longer statistically significant when adjusted for age, sex, race/ethnicity, income, and education level (P=0.14). However, when stratified by sex and adjusted for other demographics, higher SSI scores were associated with higher HEI-2010 scores compared to lower SSI scores in men (P=0.02), but there was no significant difference among SSI scores and HEI-2010 scores in women (P=0.43). CONCLUSIONS: This study suggests a positive relationship between social support and overall diet quality among middle-aged and older men, but not women, in the United States.

Towards Measuring the Food Quality of Grocery Purchases: an Estimation Model of the Healthy Eating Index-2010 Using only Food Item Counts.

Measuring the quality of food consumed by individuals or groups in the U.S. is essential to informed public health surveillance efforts and sound nutrition policymaking. For example, the Healthy Eating Index-2010 (HEI) is an ideal metric to assess the food quality of households, but the traditional methods of collecting the data required to calculate the HEI are expensive and burdensome. We evaluated an alternative source: rather than measuring the quality of the foods consumers eat, we want to estimate the quality of the foods consumers buy. To accomplish that we need a way of estimating the HEI based solely on the count of food items. We developed an estimation model of the HEI, using an augmented set of the What We Eat In America (WWEIA) food categories. Then we mapped ~92,000 grocery food items to it. The model uses an inverse Cumulative Distribution Function sampling technique. Here we describe the model and report reliability metrics based on NHANES data from 2003-2010.

qDIET: toward an automated, self-sustaining knowledge base to facilitate linking point-of-sale grocery items to nutritional content.

The United States, indeed the world, struggles with a serious obesity epidemic. The costs of this epidemic in terms of healthcare dollar expenditures and human morbidity/mortality are staggering. Surprisingly, clinicians are ill-equipped in general to advise patients on effective, longitudinal weight loss strategies. We argue that one factor hindering clinicians and patients in effective shared decision-making about weight loss is the absence of a metric that can be reasoned about and monitored over time, as clinicians do routinely with, say, serum lipid levels or HgA1C. We propose that a dietary quality measure championed by the USDA and NCI, the HEI-2005/2010, is an ideal metric for this purpose. We describe a new tool, the quality Dietary Information Extraction Tool (qDIET), which is a step toward an automated, self-sustaining process that can link retail grocery purchase data to the appropriate USDA databases to permit the calculation of the HEI-2005/2010.

Linking supermarket sales data to nutritional information: an informatics feasibility study.

Grocery sales are a data source of potential value to dietary assessment programs in public health informatics. However, the lack of a computable method for mapping between nutrient and food item information represents a major obstacle. We studied the feasibility of linking point-of-sale data to USDA-SR nutrient database information in a sustainable way. We analyzed 2,009,533 de-identified sales items purchased by 32,785 customers over a two-week period. We developed a method using the item category hierarchy in the supermarket's database to link purchased items to records from the USDA-SR. We describe our methodology and its rationale and limitations. Approximately 70% of all items were mapped and linked to the SR; approximately 90% of all items could be mapped with an equivalent expenditure of additional effort. 100% of all items were mapped to USDA standard food groups. We conclude that mapping grocery sales data to nutritional information is feasible.

Philosophical approaches to the nursing informatics data-information-knowledge-wisdom framework.

Although informatics is an important area of nursing inquiry and practice, few scholars have articulated the philosophical foundations of the field or how these translate into practice including the often-cited data, information, knowledge, and wisdom (DIKW) framework. Data, information, and knowledge, often approached through postpositivism, can be exhibited in computer systems. Wisdom aligns with constructivist epistemological perspectives such as Gadamerian hermeneutics. Computer systems can support wisdom development. Wisdom is an important element of the DIKW framework and adds value to the role of nursing informaticists and nursing science.