Purchase Quality Research Articles

Pengaruh Lokasi dan Kualitas Produk Terhadap Keputusan Pembelian (Survei Pada Konsumen Toko Santi Collection Cikatomas Tasikmalaya)

This study aims to determine the simultaneous and partial influence of location and purchase quality on clothing purchasing decisions at the Sati Collection Store. The method used in this study is a survey method with a quantitative approach. The population studied was 100 respondents. The data collected were primary and secondary data. Data analysis in this study used multiple linear regression analysis using SPSS version 26. The results showed that location and product quality simultaneously had a significant effect on purchasing decisions at the Santi Collection Cikatomas Store. Location partially had a significant effect on purchasing decisions at the Santi Collection Cikatomas Store. Product quality partially had a significant effect on purchasing decisions at the Santi Collection Cikatomas Store.

Feasibility and acceptability of a personalized, pre-filled online grocery cart to improve benefit redemption and diet quality of grocery purchases among participants of the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC)

Most participants in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) do not fully redeem their benefits due to barriers like transportation, confusing product eligibility, and unclear labeling. Online food shopping enables choice architecture to promote benefit redemption and maximize diet quality. We conducted a mixed-methods pilot randomized-controlled trial to assess the feasibility and acceptability of a pre-filled online grocery shopping cart to improve WIC benefit redemption and diet quality of grocery purchases. Rhode Island WIC participants (n = 24, mean age 29.4 ± 1.1 years, 75% Hispanic, 54% had never grocery shopped online) completed a baseline questionnaire and a simulated shopping episode (SSE), buying WIC and non-WIC items. After a week, we randomized participants into the intervention (personalized, modifiable carts pre-filled with 100% of the 2022 proposed WIC packages) or control (selected their items individually) groups before the second SSE. Both groups had WIC labels. We assessed feasibility using process data and percent agreement to feasibility questions, and acceptability via percent agreement to acceptability questions and post-intervention qualitative interviews. We conducted exploratory analyses to examine differences within and between groups at each timepoint for percent WIC benefit redemption and diet quality of grocery purchases, evaluated using the Grocery Purchase Quality Index-2016 (GPQI-2016) scores. Quantitative study measures suggest that the intervention was feasible and that the personalized, modifiable pre-filled cart was acceptable. These findings were supported during qualitative interviews, where participants highlighted time-savings, flexibility, and WIC labels as facilitators of WIC online shopping. Exploratory results showed significant increases in mean percent redemption of most WIC food categories and non-significant moderate increases in most GPQI-2016 scores. These measures are vital for the future adaptation of a full-scale efficacy trial in real-life settings.

Improving quality standards of purchase policy and sustainable staple food safety

IntroductionFood quality is closely related to food safety. Improving food quality, especially staple foods quality, is crucial to ensuring sustainable food safety. China's government is making efforts to improve the quality of staple foods and has improved quality standards of purchase policy for staple food. However, the actual effects of the new quality standards of purchase policy in implementation have not been verified.MethodsBased on this background, applying difference-in-differences models, this paper examines whether the new quality standards of purchase policy can improve the quality of staple food supply based on the wheat market transaction data.Results and discussionThe results show that the new quality standard of purchase policy has a significant positive impact on the quality of staple food supply. The conclusion remains robust through several alternative tests. Further research shows that the new quality standards of purchase policy significantly expand the degree of quality premiums in the market, thereby improving the staple food supply quality. Our research provides an insight for policy or standard makers to change relevant purchase quality limits following consumer demand to ensure sustainable food security.

Perceived Health and Diet Quality Among Hispanics in South Florida.

There is limited information if perceived health is associated with diet quality in Hispanics. A cross-sectional study was conducted to evaluate is health perception is associated with diet quality among 109 adults in South Florida. Individuals conducting a primary grocery shopping event were asked to complete a survey about their perceived health and to provide a picture of their grocery receipt to estimate diet quality using the Grocery Purchase Quality Index 2016 (GPQI-2016). Data was analyzed using analysis of covariance, adjusting for age, gender, ethnicity, and household size. Mean age was 45.1 ± 13.5 years, 74% were female, 79% were Hispanics, and 36.7% perceived themselves as having 'Good' health. The total average GPQI-2016 score was 40.9 ± 1.0. Perceived health was not significantly associated with total average GPQI-2016 score (p > 0.05). There was no association between perceived health and total diet quality in this sample of Hispanic adults.

How Digital Economy affect Innovation? Evidence from Commodity Quality and Green Economy

The concept of digital economy is spreading quickly as human has entered the information age. Digital economy contains a wide range of things for anything relating to using digital data either directly or indirectly to lead the production of aggregation effects of resources, which starts a whole profound revolution of society and economy. This paper will discuss about the innovation in the development of digital economy, focusing on innovation effect, purchase quality and green development. Some limitations might be found in the process of research due to some non-linear linkages in certain economic relationships and some difficulties in the technology of model designs. For the policy used in the whole digital economy and digital reform, it is necessary for it to better analyze the local economic model, activate the consumer market, and drive the growth of the entire consumer.

Promosi dan Harga terhadap Keputusan Pembelian

The purpose of this study is to analyze the influence of promotions and prices on buying decisions at Traveloka Agents. This research method is descriptive quantitative. Interpretation of the data is processed using SPSS 25 statistics. The research model uses Multiple Regression Analysis to test the effect value of promotion (X1) and price (X2) on purchasing decisions. The analysis technique used is validity test, reliability test, and t-test and F-test. The results show that simultaneously there is an influence between promotion and price according to the correlation test with an R value of 0.440 or 44% in the medium category. This implies that the effect of variables X1 and X2 simultaneously on variable Y is 44%. Based on the T test, the results obtained are: a) the sig value of the promotion variable on purchasing decisions has a significant value of 0.499 > 0.05, and the value of t count < t table is 0.679 < 1.9916; b) the price variable on purchasing decisions has a significant value of 0.000 <0.05, and the t count > t table is 4.332 > 1.9916. Conclusion, a) there is no relationship between promotion variable and buying decision; b) there is an influence between price and purchase quality; c) Simultaneously, there is an influence between promotion and price with purchasing decisions, so it indicates the promotion given and the price is affordable and accepted by consumers.
 Keywords: Price, Purchase Decision, Promotion

Factor Affecting Purchase of Quality Wood: Understanding Perceptions of Wood Workers Using Logistic Regression Model

Woodworkers purchase wood from farmlands as well as from the timber markets, transport them and later convert them into usable products keeping in mind their profitability and customer relationship. Wood with problems not only devoid woodworkers with profit, in turn, affect customers with low quality products. This research is, therefore, formulated to understand factor affecting wood workers ‘choice of quality wood in Multan timber market, Pakistan. A total of 60 respondents were interviewed by administering questionnaire using snow-ball sampling technique. The wealth of information obtained thus analyzed using logistic regression technique to draw meaningful inferences. The results revealed that wood problem related to Insect’s pests and diseases (B= .234, Wald 3.687, sig .05), wood defects (B=-.294, Wald 3.833, Sig -.050) and perception of safe transportation (B= 3.833, Wald= 5.479, sig =.019) positively affect wood workers’ choice of quality wood purchase. The research concluded that woods available in timber markets should be free from insect pests and defects damage to save woodworkers and customers premiums. This might entail trainings organized by government for consumers and wood workers to identify wood problems and purchase quality woods.

Participant Characteristics Associated with High Responsiveness to Personalized Healthy Food Incentives: a Secondary Analysis of the Randomized Controlled Crossover Smart Cart Study

Personalized dietary behavioral interventions could be enhanced by understanding factors accounting for individual variability in dietary decisions. This study was a secondary analysis of the Smart Cart randomized controlled trial to determine whether participant characteristics predicted high responsiveness to personalized grocery incentives for purchasing healthy food. This secondary analysis of a 9-mo crossover study included 192 regular shoppers (86%) from a Rhode Island supermarket. To analyze whether health, behavioral, and/or sociodemographic characteristics predicted responsiveness to a personalized grocery incentive intervention, participants were divided into 3 categories [high (n=47), moderate (n=50), and unresponsive (n=95)] based on percentage changes in their Grocery Purchase Quality Index scores during the intervention versus control period calculated from sales data. We tested whether participant characteristics, including individual, household, and intervention-related factors, differed across responsiveness groups using ANOVA and whether they predicted the likelihood of being high responsive versus unresponsive or moderate responsive using logistic regression. Participants had a mean (SD) age of 56.0 (13.8) y and were 89% female. Education, self-reported BMI, income, diet-related medical condition, food insecurity, cooking adequacy, and value consciousness differed across responsiveness categories (P<0.1). High versus moderate and unresponsive participants increased their percentage of spending on targeted foods (P<0.0001) and purchased fewer unique items (P=0.01). In multinomial adjusted models, the odds of being high versus unresponsive or moderate responsive were lower for participants with a BMI (in kg/m2) <25 versus ≥25 (OR: 0.41; 95% CI: 0.19, 0.90) and higher with a diet-related medical condition present (OR: 3.75; 95% CI: 1.20, 11.8). Other characteristics were not associated with responsiveness. Findings demonstrated that a BMI ≥25 and having a diet-related medical condition within the household predicted high responsiveness to a personalized grocery purchasing intervention, suggesting that personalized dietary interventions may be particularly effective for households with higher health risk. This trial is registered at www.clinicaltrials.gov as NCT03748056.

Implementasi Metode Lean Startup dalam Pengembangan Ide Bisnis Aplikasi Golek Kost Berbasis Mobile

The need for housing (boarding houses) for students is a basic need and becomes a significant consideration when deciding to study in a particular city. So far, students have obtained information related to boarding houses manually to meet the needs associated with the necessary furniture and in carrying out the moving process. With everything still manual, it takes longer and is more difficult to find a boarding house that fits the student’s needs. To help solve existing problems, a mobile-based application called GOLEK KOST was made. The application is a form of digital innovation to make it easier for students to obtain information related to boarding houses, including prices, locations and boarding facilities, buying, and selling furniture, transportation services, or moving services in the Yogyakarta area. Developing this application business idea applies the Lean Startup method, which consists of three stages: Market Validation, Product Validation, and Business Validation. This method focuses on developing applications based on feedback obtained from potential users so that later the resulting application will meet the needs of potential users. In the product validation, the results obtained are 37% for the boarding information feature, 33.3% for the transportation service feature, and 29.6% for the furniture sale and purchase quality.

온라인 신선식품 구매 시 품질 인식과 태도가 만족도에 미치는 영향 연구

This study was undertaken to analyze the relationship between quality perception, attitude, and satisfaction of consumers related to the online purchase of fresh foods. An online, self-administered survey was distributed for data collection. The sample subjects of the study comprised consumers experienced in buying fresh food through online shopping. The findings from this study showed that the three factors of online fresh food purchase quality perception (viz., product, website, and delivery) all have a significant impact on attitude toward online fresh food shopping. Furthermore, all three factors have a significant impact on purchase satisfaction. In addition, examining the mediating effect of the attitude toward online fresh food shopping confirmed that quality perception had a significant impact on satisfaction, and attitude toward online fresh food shopping partially mediated this relationship. The results of this study will provide marketing implications for companies selling fresh food online.

Estimating Dietary Intake from Grocery Shopping Data-A Comparative Validation of Relevant Indicators in Switzerland.

In light of the globally increasing prevalence of diet-related chronic diseases, new scalable and non-invasive dietary monitoring techniques are urgently needed. Automatically collected digital receipts from loyalty cards hereby promise to serve as an objective and automatically traceable digital marker for individual food choice behavior and do not require users to manually log individual meal items. With the introduction of the General Data Privacy Regulation in the European Union, millions of consumers gained the right to access their shopping data in a machine-readable form, representing a historic chance to leverage shopping data for scalable monitoring of food choices. Multiple quantitative indicators for evaluating the nutritional quality of food shopping have been suggested, but so far, no comparison has validated the potential of these alternative indicators within a comparative setting. This manuscript thus represents the first study to compare the calibration capacity and to validate the discrimination potential of previously suggested food shopping quality indicators for the nutritional quality of shopped groceries, including the Food Standards Agency Nutrient Profiling System Dietary Index (FSA-NPS DI), Grocery Purchase Quality Index-2016 (GPQI), Healthy Eating Index-2015 (HEI-2015), Healthy Trolley Index (HETI) and Healthy Purchase Index (HPI), checking if any of them performs differently from the others. The hypothesis is that some food shopping quality indicators outperform the others in calibrating and discriminating individual actual dietary intake. To assess the indicators’ potentials, 89 eligible participants completed a validated food frequency questionnaire (FFQ) and donated their digital receipts from the loyalty card programs of the two leading Swiss grocery retailers, which represent 70% of the national grocery market. Compared to absolute food and nutrient intake, correlations between density-based relative food and nutrient intake and food shopping data are stronger. The FSA-NPS DI has the best calibration and discrimination performance in classifying participants’ consumption of nutrients and food groups, and seems to be a superior indicator to estimate nutritional quality of a user’s diet based on digital receipts from grocery shopping in Switzerland.

Association between the Nutritional Quality of Household At-Home Food Purchases and Chronic Diseases and Risk Factors in the United States, 2015.

Lower diet quality is a leading preventable risk factor for obesity and chronic diseases. This study assesses differences in the nutritional quality of at-home food purchases, using the Healthy Eating Index (HEI)-2015 and its components, among households with and without a member reporting type 2 diabetes (T2D), cardiovascular disease (CVD), obesity, and/or smoking. We use the 2015 IRI Consumer Network nationally representative household food purchase scanner data, combined with the IRI MedProfiler and the USDA’s Purchase-to-Plate Crosswalk datasets. For each/multiple condition(s), the difference in mean HEI score adjusted for covariates is tested for equivalence with the respective score against households without any member with the condition(s). The HEI score is higher for households without a member with reported T2D (2.4% higher), CVD (3.2%), obesity (3.3%), none of the three conditions (6.1%, vs. all three conditions), and smoking (10.5%) than for those with a member with the respective condition. Households with a member with T2D score better on the added sugar component than those with no member reporting T2D. We found that the average food purchase quality is lower than the recommended levels, especially for households with at least one member reporting a chronic condition(s).

Food Waste and Its Association with Diet Quality of Foods Purchased in South Florida.

The objective of this study was to explore the associations between food waste and the diet quality of foods purchased and with grocery purchasing behaviors. This was a cross-sectional study among 109 primary household food providers conducting primary shopping. Participants were recruited outside of local grocery stores and were asked to complete a survey assessing amounts of avoidable food waste and grocery purchasing behaviors. The diet quality of the foods purchased was assessed from grocery receipts using the Grocery Purchase Quality Index-2016 (GPQI-2016). Variables were associated using linear regression, analysis of covariance, and point biserial correlations. We found that fresh fruits (63%) and leafy greens (70%) were the foods that were the most wasted. The GPQI-2016 total score was significantly inversely associated with the total amount of food wasted (β = −0.63; 95% CI: −1.14,−0.12) after adjusting for important confounders. The reason “food past the date printed on the package” was directly correlated with food wasted (r = 0.40; p < 0.01) but inversely correlated with GPQI-2016 score (r = −0.21; p = 0.04). Food wasted, but not the GPQI-2016 score, was significantly higher among those who grocery shop 2–4 times per week compared to 1 time every 1–2 weeks (p = 0.02). In conclusion, food waste is inversely associated with diet quality and directly associated with grocery purchasing frequency.

Participant Characteristics Contributed to Variable Responsiveness to Personalized Healthy Food Incentives—A Secondary Analysis of a Randomized Crossover Trial

ObjectivesThe recently completed Smart Cart Study, designed to promote healthier food purchases, found that personalized healthy food incentives modestly improved mean grocery purchase quality, with considerable variation in participant responsiveness. The present study explored participant characteristics associated with variable responsiveness to this healthy food incentives intervention. MethodsA secondary analysis examined the Smart Cart Study, where participants received personalized weekly coupons during in the intervention and occasional generic coupons during the control period (n = 209). The outcome variable was 3-month changes in Grocery Purchase Quality Index (GPQI), a validated score calculated from purchasing data that compares the % spending relative to recommended spending to reflect the dietary quality of grocery purchases, in the intervention minus control periods. Potential exposure variables were selected a priori based on a literature review included age, sex, race/ethnicity, education, income, general health status, food literacy, food neophobia, nutritional self-efficacy and eating perception. Multivariable linear regressions evaluated characteristics that predict changes in GPQI. Stepwise model selection guided variable retention with specification of pr = 0.2. Analyses were conducted in Stata 16.1. ResultsParticipants were predominately female (89.5%), Non-Hispanic white (94.1%), higher income (50.3% ≥$100K/year), higher education (48.4% >bachelor’s degree), with a mean age of 55.3. In the final model, changes in % spending on couponed foods (β = 15.58, P < 0.001) and food neophobia (β = –1.77, P = 0.047) predicted changes in GPQI, while other predictors were not significant. The final model explained 13% of the variation in GPQI changes. ConclusionsGreater % spending on couponed foods was associated with higher GPQI while food neophobia was associated with lower GPQI. Given that food neophobia may prevent participants from increasing their spending on new couponed healthy foods, future personalized couponing interventions should explore strategies to address food neophobia, potentially through free samples of new foods or providing coupons for familiar healthy foods, especially in diverse populations. Funding SourcesThe Smart Cart Study was funded by the Foundation for Food and Agricultural Research.

Effect of Personalized Incentives on Dietary Quality of Groceries Purchased

Many factors are associated with food choice. Personalized interventions could help improve dietary intake by using individual purchasing preferences to promote healthier grocery purchases. To test whether a healthy food incentive intervention using an algorithm incorporating customer preferences, purchase history, and baseline diet quality improves grocery purchase dietary quality and spending on healthy foods. This was a 9-month randomized clinical crossover trial (AB-BA) with a 2- to 4-week washout period between 3-month intervention periods. Participants included 224 loyalty program members at an independent Rhode Island supermarket who completed baseline questionnaires and were randomized from July to September 2018 to group 1 (AB) or group 2 (BA). Data analysis was performed from September 2019 to May 2020. Participants received personalized weekly coupons with nutrition education during the intervention period (A) and occasional generic coupons with nutrition education during the control period (B). An automated study algorithm used customer data to allocate personalized healthy food incentives to participant loyalty cards. All participants received a 5% grocery discount. Grocery Purchase Quality Index-2016 (GPQI-16) scores (range, 0-75, with higher scores denoting healthier purchases) and percentage spending on targeted foods were calculated from cumulative purchasing data. Participants in the top and bottom 1% of spending were excluded. Paired t tests examined between-group differences. The analytical sample included 209 participants (104 in group 1 and 105 in group 2), with a mean (SD) age of 55.4 (14.0) years. They were predominantly non-Hispanic White (193 of 206 participants [94.1%]) and female (187 of 207 participants [90.3%]). Of 161 participants with income data, 81 (50.3%) had annual household incomes greater than or equal to $100 000. Paired t tests showed that the intervention increased GPQI-16 scores (between-group difference, 1.06; 95% CI, 0.27-1.86; P = .01) and percentage spending on targeted foods (between-group difference, 1.38%; 95% CI, 0.08%-2.69%; P = .04). During the initial intervention period, group 1 (AB) and group 2 (BA) had similar mean (SD) GPQI-16 scores (41.2 [6.6] vs 41.0 [7.5]) and mean (SD) percentage spending on targeted healthy foods (32.0% [10.8%] vs 31.0% [10.5%]). During the crossover intervention period, group 2 had a higher mean (SD) GPQI-16 score than group 1 (42.9 [7.7] vs 41.0 [6.8]) and mean (SD) percentage spending on targeted foods (34.0% [12.1%] vs 32.0% [13.1%]). This pilot trial demonstrated preliminary evidence for the effectiveness of a novel personalized healthy food incentive algorithm to improve grocery purchase dietary quality. ClinicalTrials.gov Identifier: NCT03748056.

The utility of household Grocery Purchase Quality Index scores as an individual diet quality metric.

The Grocery Purchase Quality Index (GPQI) reflects concordance between household grocery purchases and US dietary recommendations. However, it is unclear whether GPQI scores calculated from partial purchasing records reflect individual-level diet quality. This secondary analysis of a 9-month randomised controlled trial examined concordance between the GPQI (range 0-75, scaled to 100) calculated from 3 months of loyalty-card linked partial (≥50 %) household grocery purchasing data and individual-level Healthy Eating Index (HEI) scores at baseline and 3 months calculated from FFQ (n 209). Concordance was assessed with overall and demographic-stratified partially adjusted correlations; covariate-adjusted percentage score differences, cross-classification and weighted κ coefficients assessed concordance across GPQI tertiles (T). Participants were middle aged (55·4 (13·9) years), female (90·3 %), from non-smoking households (96·4 %) and without children (70·7 %). Mean GPQI (54·8 (9·1) %) scores were lower than HEI scores (baseline: 73·2 (9·1) %, 3 months: 72·4 (9·4) %) and moderately correlated (baseline r 0·41 v. 3 months r 0·31, P < 0·001). Correlations were stronger among participants with ≤ bachelor's degree, obesity and children. Scores showed moderate agreement (κ = 0·25); concordance was highest in T3. Participants with high (T3) v. low (T1) GPQI scores had 7·3-10·6 higher odds of having HEI scores >80 % at both time points. Household-level GPQI was moderately correlated with self-reported intake, indicating their promise for evaluating diet quality. Partial purchasing data appear to moderately reflect individual diet quality and may be useful in interventions monitoring changes in diet quality.

Sociodemographic Differences in the Dietary Quality of Food-at-Home Acquisitions and Purchases among Participants in the U.S. Nationally Representative Food Acquisition and Purchase Survey (FoodAPS).

Insufficient research has explored whether sociodemographic differences in self-reported, individual-level diet quality are similarly reflected by grocery purchase quality. This cross-sectional analysis of n = 3961 U.S. households from the nationally representative Food Acquisition and Purchase Survey (FoodAPS) compared Healthy Eating Index (HEI)-2015 scores from 1 week of food-at-home acquisitions across self-reported demographic factors (race/ethnicity, Supplemental Nutrition Assistance Program (SNAP) participation, food security, and household-level obesity status). Multivariable-adjusted, survey-weighted regression models compared household HEI-2015 scores across sociodemographic groups. Respondents were primarily White and female, with a mean age of 50.6 years, 14.0% were food insecure, and 12.7% were SNAP-participating. Mean HEI-2015 scores were 54.7; scores differed across all sociodemographic exposures (p < 0.05). Interactions (p < 0.1) were detected between SNAP participation and (1) food insecurity and (2) household-level obesity, and race/ethnicity and (1) household-level obesity. HEI-2015 scores were higher among food secure, non-SNAP households than among food insecure, SNAP-participating households (53.9 ± 0.5 vs. 50.3 ± 0.7, p = 0.007); non-SNAP households without obesity had significantly higher HEI-2015 scores than other households. Household-level obesity was associated with lower HEI-2015 scores in White (50.8 ± 0.5 vs. 52.5 ± 0.7, p = 0.046) and Black (48.8 ± 1.5 vs. 53.1 ± 1.4, p = 0.018) but not Hispanic households (54.4 ± 1.0 vs. 52.2 ± 1.2, p = 0.21). Sociodemographic disparities in household HEI-2015 scores were consistent with previous research on individual-level diet quality.

호텔 경험구매 질이 재구매 의도에 미치는 영향에 대한 이해

호텔 경험구매 질이 재구매 의도에 미치는 영향에 대한 이해

Association Between Health Perception and Diet Quality in a Sample of Hispanics

Abstract Objectives This study was conducted to evaluate how health perception is associated with diet quality among Hispanics living in South Florida. Methods The research design was a cross-sectional study with a total of 109 people recruited at the end of their grocery event in local supermarkets around the Miami-Dade County area. They were asked to complete a questionnaire and to provide a picture of their grocery receipt. We included only adults ≥18 years and the primary food provider of the household conducting a primary shopping event for the week. Health perception was assessed from a question used in NHANES (Would you say your health in general is…with the following options ‘Excellent’, ‘Very Good’, ‘Good’, ‘Fair’ and ‘Poor’). Diet quality was evaluated using the Grocery Purchase Quality Index 2016 (GPQI-2016) from the grocery receipt. The GPQI-2016 is based on the Healthy Eating Index (HEI)– 2010 and has a total of 31 categories, 29 of those coming from the USDA Food Plan Market Baskets and 2 added by the authors of the GPQI-2016. These are mapped into 11 different components, which are re-grouped into ‘Adequacy’ and ‘Moderation’. Each component can have a maximum score of 5 or 10 with a total maximum score of 75 when all 11 components scores are added up. An analysis of covariance was used to compare GPQI-2016 by health perception which was categorized into three groups: Excellent/Very Good, Good, and Fair/Poor, adjusting for age and gender. Results The mean age of individuals was 45.1 ± 13.5 years, 74% were female, 77% were Hispanics, and 36.7% perceived themselves as having ‘Good’ health. The total average GPQI-2016 score was 40.9 ± 1.0, which is below the maximum score of 75 by almost 50%. Green and Beans Scores were lower among those with ‘Good’ perceived health and higher amongst those with ‘Fair/Poor’ perceived health (P &amp;lt; 0.05). The other individual component scores or the total GPQI-2016 score did not differ by health perception. Conclusions The diet quality score could be considered somewhat poor or regular. Only the Greens and Beans score differed by groups, with a higher score amongst those with ‘Fair/Poor’ perceived health group. Because health perception is subjective, other objective markers of health may be needed to detect differences in diet quality by health status. Funding Sources No funding source was acquired for this study.

Association Between Diet Quality and Food Waste in South Florida

Abstract Objectives In 2015, the USDA/EPA set a goal of reducing food waste in 50% by 2030. This goal will not only lower U.S. methane gas emissions but also redirect food to millions of food insecure Americans. Little is known on food waste and its association with diet quality. Therefore, our objective was to explore the associations between diet quality and food waste. Methods This was a cross sectional study among adults ³18 years in south Florida who are the primary household food provider conducting a primary shopping event for the week. Participants were recruited outside of local grocery stores and asked to fill out a quick food waste survey. Pictures of the participants’ grocery receipts were taken to analyze diet quality using the Grocery Purchase Quality Index 2016 (GPQI-2016). The GPQI-2016 is based on the Healthy Eating Index (HEI)– 2010 and has 11 different components (each with a maximum score of 5 or 10) for a total score of 75. Correlations were used to determine the associations between diet quality and amount of food waste (Pearson) or reasons for food waste (Point-biserial). Results A total of 109 participants were recruited but 103 had complete data. Mean age was 44.6 ± 13.6 years, most were females (74%) and Hispanics (79%). Most usually grocery shop in a main event and then go back for smaller items (44%) once (36%) or twice (28%) a week. Mean diet quality score was 40.9 ± 9.64 out of 75 points and mean amount of food waste was 17.7 ± 19.9 handfuls. Most reported throwing away food mainly because it went bad (90%) or it was past it's due date (80%). Handfuls of bread/rice waste were significantly inversely correlated with diet quality (r = −2.60; p = 0.013). Also, we found a significant inverse correlation between diet quality and food thrown away because it had gone past it's use by date (r = −.196; p = 0.049). Conclusions A lower diet quality score was related to higher amount of bread/rice wasted and with throwing away foods that has past it's use date. These results could justify directing reducing food waste efforts in the community by educating individuals on purchasing frozen products or on proper storage to prolong shelf life, as well as on understanding the different dates placed on products by manufacturers. Funding Sources Internal funds from Florida International University.