Food waste contributes to adverse environmental and economic outcomes, and substantial food waste occurs at the household level in the US. This study explored perceived household food waste changes during the COVID-19 pandemic and related factors. A total of 946 survey responses from primary household food purchasers were analyzed. Demographic, COVID-19-related household change, and household food waste data were collected in October 2020. Wilcoxon signed-rank was used to assess differences in perceived food waste. A hierarchical binomial logistic regression analysis was conducted to examine whether COVID-19-related lifestyle disruptions and food-related behavior changes increased the likelihood of household food waste. A binomial logistic regression was conducted to explore the contribution of different food groups to the likelihood of increased food waste. Perceived food waste, assessed as the estimated percent of food wasted, decreased significantly during the pandemic (z = −7.47, p < 0.001). Food stockpiling was identified as a predictor of increased overall food waste during the pandemic, and wasting fresh vegetables and frozen foods increased the odds of increased food waste. The results indicate the need to provide education and resources related to food stockpiling and the management of specific food groups during periods of disruption to reduce food waste.

BackgroundScreen time among adults represents a continuing and growing problem in relation to health behaviors and health outcomes. However, no instrument currently exists in the literature that quantifies the use of modern screen-based devices. The primary purpose of this study was to develop and assess the reliability of a new screen time questionnaire, an instrument designed to quantify use of multiple popular screen-based devices among the US population.MethodsAn 18-item screen-time questionnaire was created to quantify use of commonly used screen devices (e.g. television, smartphone, tablet) across different time points during the week (e.g. weekday, weeknight, weekend). Test-retest reliability was assessed through intra-class correlation coefficients (ICCs) and standard error of measurement (SEM). The questionnaire was delivered online using Qualtrics and administered through Amazon Mechanical Turk (MTurk).ResultsEighty MTurk workers completed full study participation and were included in the final analyses. All items in the screen time questionnaire showed fair to excellent relative reliability (ICCs = 0.50–0.90; all < 0.000), except for the item inquiring about the use of smartphone during an average weekend day (ICC = 0.16, p = 0.069). The SEM values were large for all screen types across the different periods under study.ConclusionsResults from this study suggest this self-administered questionnaire may be used to successfully classify individuals into different categories of screen time use (e.g. high vs. low); however, it is likely that objective measures are needed to increase precision of screen time assessment.

No abstract

Life cycle assessment (LCA) evaluates environmental impacts of a product from material extraction through disposal. Applications of LCA in evaluating diets and foods indicate that plant-based foods have lower environmental impacts than animal-based foods, whether on the basis of total weight or weight of the protein content. However, LCA comparisons do not differentiate the true biological value of protein bioavailability. This paper presents a methodology to incorporate protein quality and quantity using the digestible indispensable amino acid score (DIAAS) when making comparisons using LCA data. The methodology also incorporates the Food and Drug Administration’s (FDA) reference amounts customarily consumed (RACCs) to best represent actual consumption patterns. Integration of these measures into LCA provides a mechanism to identify foods that offer balance between the true value of their protein and environmental impacts. To demonstrate, this approach is applied to LCA data regarding common protein foods’ global warming potential (GWP). The end result is a ratio-based score representing the biological value of protein on a GWP basis. Principal findings show that protein powders provide the best efficiency while cheeses, grains, and beef are the least efficient. This study demonstrates a new way to evaluate foods in terms of nutrition and sustainability.

Background: The purpose of this study was to examine whether extended use of a variety of screen-based devices, in addition to television, was associated with poor dietary habits and other health-related characteristics and behaviors among US adults. The recent phenomenon of binge-watching was also explored. Methods: A survey to assess screen time across multiple devices, dietary habits, sleep duration and quality, perceived stress, self-rated health, physical activity, and body mass index, was administered to a sample of US adults using the Qualtrics platform and distributed via Amazon Mechanical Turk (MTurk). Participants were adults 18 years of age and older, English speakers, current US residents, and owners of a television and at least one other device with a screen. Three different screen time categories (heavy, moderate, and light) were created for total screen time, and separately for screen time by type of screen, based on distribution tertiles. Kruskal-Wallis tests were conducted to examine differences in dietary habits and health-related characteristics between screen time categories. Results: Aggregate screen time across all devices totaled 17.5 h per day for heavy users. Heavy users reported the least healthful dietary patterns and the poorest health-related characteristicsincluding self-rated healthcompared to moderate and light users. Moreover, unique dietary habits emerged when examining dietary patterns by type of screen separately, such that heavy users of TV and smartphone displayed the least healthful dietary patterns compared to heavy users of TV-connected devices, laptop, and tablet. Binge-watching was also significantly associated with less healthy dietary patterns, including frequency of fast-food consumption as well as eating family meals in front of a television, and perceived stress. Conclusions: The present study found that poorer dietary choices, as well as other negative health-related impacts, occurred more often as the viewing time of a variety of different screen-based devices increased in a sample of US adults. Future research is needed to better understand what factors among different screen-based devices might affect health behaviors and in turn health-related outcomes. Research is also required to better understand how binge-watching behavior contributes impacts health-related behaviors and characteristics.