Search Results (9)

Phosphate pollution caused by human activities has become a pressing environmental issue, leading to eutrophication and severe ecological risks. In this study, artificial humic acid (HA) and fulvic acid (FA) were synthesized from tung fruit and glucose, respectively, and further composited with ferrihydrite (Fh) to prepare HA/Fh and FA/Fh adsorbents for phosphate removal. The structural and morphological characteristics of the composites were confirmed by SEM, XRD, FTIR, and XPS analyses, which indicated successful complexation of HA or FA with Fh through ligand exchange and surface interactions. Batch adsorption experiments revealed that HA/Fh and FA/Fh exhibited significantly enhanced adsorption capacities compared to pristine Fh, with maximum Langmuir adsorption capacities of 33.67 mg g⁻¹ and 37.06 mg g⁻¹, respectively. The adsorption behavior was well described by the pseudo-second-order kinetic model and the Langmuir isotherm, suggesting a chemisorption-dominated process involving ligand exchange between surface –OH groups of Fh and phosphate ions, supplemented by electrostatic attraction. Coexisting ion studies demonstrated that Cl⁻ and SO₄²⁻ slightly promoted phosphate adsorption, while NO₃⁻ and CO₃²⁻ strongly inhibited it, highlighting the competition of multivalent anions with phosphate for Fe³⁺ active sites. Importantly, the phosphate-enriched adsorbents can be directly recycled as phosphorus fertilizers, providing a sustainable pathway for both environmental remediation and phosphorus resource recovery. Full article

(1) Background: Independently owned restaurants (IORs) are prevalent in under-resourced racial and ethnic minority communities in the US and present a unique setting for public health nutrition interventions. (2) Methods: We conducted 14 in-depth interviews with IOR owners in Baltimore about their perceptions of healthy food, and customers’ acceptance of healthier menus and cooking methods and concurrent observations of the availability of healthy options on their menus. Qualitative data were coded and analyzed using ATLAS.ti. Observations were analyzed with statistical analysis performed in R. (3) Results: Owners perceived non-fried options, lean proteins, and plant-based meals as healthy. While open to using healthier cooking fats, they had mixed feelings about reducing salt, adopting non-frying methods for cooking, and adding vegetables and whole grains to the menu, and were reluctant to reduce sugar in recipes and beverages. Only 17.5% of 1019 foods and 27.6% of 174 beverages in these IORs were healthy, with no significant differences in the healthfulness of restaurant offerings within low-healthy-food-access/low-income neighborhoods and those outside. (4) Conclusion: Healthy options are generally scarce in Baltimore’s IORs. Insights from owners inform future interventions to tailor healthy menu offerings that are well-received by customers and feasible for implementation. Full article

Crowdsourced online food images, when combined with food image recognition technologies, have the potential to offer a cost-effective and scalable solution for the assessment of the restaurant nutrition environment. While previous research has explored this approach and validated the accuracy of food image recognition technologies, much remains unknown about the validity of crowdsourced food images as the primary data source for large-scale assessments. In this paper, we collect data from multiple sources and comprehensively examine the validity of using crowdsourced food images for assessing the restaurant nutrition environment in the Greater Hartford region. Our results indicate that while crowdsourced food images are useful in terms of the initial assessment of restaurant nutrition quality and the identification of popular food items, they are subject to selection bias on multiple levels and do not fully represent the restaurant nutrition quality or customers’ dietary behaviors. If employed, the food image data must be supplemented with alternative data sources, such as field surveys, store audits, and commercial data, to offer a more representative assessment of the restaurant nutrition environment. Full article

Background: High intake of food away from home is associated with poor diet quality. This study examines how the COVID-19 pandemic period and Food Away from Home (FAFH) inflation rate fluctuations influenced dining out behaviors. Methods: Approximately 2800 individuals in Texas reported household weekly dining out frequency and spending. Responses completed prior to the COVID-19 pandemic (2019 to early 2020) were compared to the post-COVID-19 period (2021 through mid-2022). Multivariate analysis with interaction terms was used to test study hypotheses. Results and Conclusion: From the COVID-19 period (before vs. after), the unadjusted frequency of dining out increased from 3.4 times per week to 3.5 times per week, while the amount spent on dining out increased from $63.90 to $82.20. Once the relationship between dining out (frequency and spending) was adjusted for FAFH interest rate and sociodemographic factors, an increase in dining out frequency post-COVID-19 remained significant. However, the unadjusted increase in dining out spending did not remain significant. Further research to understand the demand for dining out post-pandemic is warranted. Full article

The consumption of meals prepared away from home (FAFH) in the U.S. has been commonly linked to overall poorer diet quality; however, less is known about the relationship with health parameters. The aim of this cross-sectional study was to assess the diet quality and health parameters of adults who reported the frequency of obtaining or eating FAFH using a combination of four 2-year cycles of National Health and Nutrition Examination Survey (NHANES, 2011–2018) data. Data from 14,999 adults aged 20 to 65 years were used to examine the associations between diet and health outcomes and the weekly frequency of FAFH. Multivariable regression models were used to compare Healthy Eating Index-2015 (HEI-2015) scores by FAFH frequency, adjusting for sociodemographic variables. Adults with more frequent FAFH meals were more likely to be younger, male, lower-income, and unmarried. Total HEI-2015 scores and component scores for greens and beans, total and whole fruits, whole grains, saturated fats, and added sugars were significantly lower in those consuming >2 FAFH meals/week vs. ≤2 FAFH meals/week. BMI and waist circumference tended to be higher for women having more frequent FAFH meals. More frequent FAFH meals among adults were associated with poorer diet quality and weight outcomes, building on results from earlier studies. Full article

This study examined the factors that determine U.S. household expenditure patterns for food products in the context of exceptional price shocks due to the COVID-19 pandemic. This research relied on the Consumer Expenditure Diary Survey (CEX) for the year 2020, where households or consumer units represent units of observation. With a sample size of 10,453 observations, the empirical estimation of the Heckman two-step model yields interesting results. Consistent with the inelastic nature of food products, we found conditional expenditure elasticities of income were less than one for all kinds of food, including food away from home (FAFH). The results showed both food and FAFH to be highly price elastic in this special period of higher food prices. For instance, a 1% increase in own price implied a 7.78% decrease in the probability to spend on food and a 20.93% decrease in propensity to purchase FAFH. This study provides business managers and marketing experts with insights on the consumer profile and food product price strategy. Full article

Disruptive events such as the coronavirus disease 2019 (COVID-19) pandemic have the potential to reshape even the most basic human systems and behaviors, including those related to food production, acquisition, and consumption. This paper provides an in-depth analysis of how the pandemic has changed the ratio of food-away-from-home (FAFH) expenditure to income in Mexico, as well as participation in this market. In 2020, household participation in FAFH expenditures declined in all income deciles and regions, but the impact on household shares is far from uniform. Using a detailed national database of household income and expenditures (N = 87,274), an Engel curve of the Working-Lesser functional form for FAFH including 19 independent variables was estimated using the Heckman method appropriate for censored response data. The results provide statistically significant estimates for income, which both increases the probability of participation in this expenditure and has a negative relationship with its budget share. The number of older adults and the exposure to food insecurity during the pandemic similarly limit participation and increase the budget share. In addition, remittances encourage participation and decrease the budget share. The corrected conditional income elasticity for FAFH is 0.4609; the sign and magnitude indicate that FAFH behaved as a necessary good in Mexico for the proportion of households that maintained spending during the lockdown conditions (about one-third of the sample). An increase or decrease in income will lead to a corresponding change in FAFH expenditure, but the change will be less than proportional. Full article

Deep learning models can recognize the food item in an image and derive their nutrition information, including calories, macronutrients (carbohydrates, fats, and proteins), and micronutrients (vitamins and minerals). This technology has yet to be implemented for the nutrition assessment of restaurant food. In this paper, we crowdsource 15,908 food images of 470 restaurants in the Greater Hartford region on Tripadvisor and Google Place. These food images are loaded into a proprietary deep learning model (Calorie Mama) for nutrition assessment. We employ manual coding to validate the model accuracy based on the Food and Nutrient Database for Dietary Studies. The derived nutrition information is visualized at both the restaurant level and the census tract level. The deep learning model achieves 75.1% accuracy when compared with manual coding. It has more accurate labels for ethnic foods but cannot identify portion sizes, certain food items (e.g., specialty burgers and salads), and multiple food items in an image. The restaurant nutrition (RN) index is further proposed based on the derived nutrition information. By identifying the nutrition information of restaurant food through crowdsourced food images and a deep learning model, the study provides a pilot approach for large-scale nutrition assessment of the community food environment. Full article

Changes in demographic and socioeconomic characteristics have contributed to an increase in away-from-home food consumption. Although consumers are increasingly demanding higher quality food, unbalanced nutrition intakes and health issues such as obesity remain prominent predicaments. This paper investigates the relationship between the frequency of having Food Away From Home (FAFH), balanced dietary intakes, and obesity (controlling for covariates) among Korean adults aged 19 to 64. Whether there exists a linear relationship between the number of having FAFH and health outcome is investigated and the optimal number of having FAFH that leads to the best health outcome is identified in the study. The results suggest that Food Away From Home generally increases deviations of dietary intakes from the reference intakes and high-frequency FAFH consumers have an elevated chance of being obese (36.22%). However, having FAFH 1–7 times per week is associated with decreased body mass index (BMI) and a lower chance of being obese in comparison to the outcomes of having food at home. The optimal level of consuming FAFH is identified to be 5–7 times per week in terms of BMI and obesity. However, consuming no FAFH is suggested to be the best in terms of balanced nutrition intake. Full article