Comparison of Sales From Vending Machines With 4 Different Food and Beverage Messages: A Randomized Trial.

Importance: Point-of-sale food messaging can encourage healthier purchases, but no studies have directly compared multiple interventions in the field. Objective: To examine which of 4 food and beverage messages would increase healthier vending machine purchases. Design, Setting, and Participants: This randomized trial assessed 13 months (February 1, 2019, to February 29, 2020) of vending sales data from 267 machines and 1065 customer purchase assessments from vending machines on government property in Philadelphia, Pennsylvania. Data analysis was performed from March 5, 2020, to November 8, 2022. Interventions: Study interventions were 4 food and beverage messaging systems: (1) beverage tax posters encouraging healthy choices because of the Philadelphia tax on sweetened drinks; (2) green labels for healthy products; (3) traffic light labels: green (healthy), yellow (moderately healthy), or red (unhealthy); or (4) physical activity equivalent labels (minutes of activity to metabolize product calories). Main Outcomes and Measures: Sales data were analyzed separately for beverages and snacks. The main outcomes analyzed at the transaction level were calories sold and the health status (using traffic light criteria) of each item sold. Additional outcomes were analyzed at the monthly machine level: total units sold, calories sold, and units of each health status sold. The customer purchase assessment outcome was calories purchased per vending trip. Results: Monthly sales data came from 150 beverage and 117 snack vending machines, whereas 1065 customers (558 [52%] male) contributed purchase assessment data. Traffic light labels led to a 30% decrease in the mean monthly number of unhealthy beverages sold (mean ratio [MR], 0.70; 95% CI, 0.55-0.88) compared with beverage tax posters. Physical activity labels led to a 34% (MR, 0.66; 95% CI, 0.51-0.87) reduction in the number of unhealthy beverages sold at the machine level and 35% (MR, 0.65; 95% CI, 0.50-0.86) reduction in mean calories sold. Traffic light labels also led to a 30-calorie reduction (b = -30.46; 95% CI, -49.36 to -11.56) per customer trip in the customer purchase analyses compared to physical activity labels. There were very few significant differences for snack machines. Conclusions and Relevance: In this 13-month randomized trial of 267 vending machines, the traffic light and physical activity labels encouraged healthier beverage purchases, but no change in snack sales, compared with a beverage tax poster. Corporations and governments should consider such labeling approaches to promote healthier beverage choices. Trial Registration: ClinicalTrials.gov Identifier: NCT06260176.

Predicted impact of banning nonessential, energy-dense food and beverages in schools in Mexico: A microsimulation study.

BACKGROUND: Childhood obesity is a growing concern worldwide. School-based interventions have been proposed as effective means to improve nutritional knowledge and prevent obesity. In 2023, Mexico approved a reform to the General Education Law to strengthen the ban of sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools and surroundings. We aimed to predict the expected one-year change in total caloric intake and obesity prevalence by introducing the ban of NEDFBs sales in schools, among school-aged children and adolescents (6 to 17 years old) in Mexico. METHODS AND FINDINGS: We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and then estimated total energy intake (TEI) per day. The TEI after the intervention was estimated under 4 scenarios: (1) using national data to inform the intervention effect; (2) varying law compliance; (3) using meta-analytic data to inform the intervention effect size on calories; and (4) using national data to inform the intervention effect by sex and socioeconomic status (SES). We used Hall's microsimulation model to estimate the potential impact on body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools. We found that children could reduce their daily energy intake by 33 kcal/day/person (uncertainty interval, UI, [25, 42] kcal/day/person), reducing on average 0.8 kg/person (UI [0.6, 1.0] kg/person) and 1.5 percentage points (pp) in obesity (UI [1.1, 1.9] pp) 1 year after implementing the law. We showed that compliance will be key to the success of this intervention: considering a 50% compliance the intervention effect could reduce 0.4 kg/person (UI [0.3, 0.5] kg/person). Our sensitivity analysis showed that the ban could reduce body weight by 1.3 kg/person (UI [0.8, 1.8] kg/person) and up to 5.4 kg/person (UI [3.4, 7.5] kg/person) in the best-case scenario. Study limitations include assuming that obesity and the contribution of NEDFBs consumed at school remain constant over time, assuming full compliance, and not considering the potential effect of banning NEDFBs in stores near schools. CONCLUSIONS: Even in the most conservative scenario, banning sales of NEDFBs in schools is expected to significantly reduce obesity, but achieving high compliance will be key to its success. WHY WAS THIS STUDY DONE?: - School-based interventions have been recognized as effective means to improve nutritional knowledge and prevent obesity-related diseases.- In December 2023, the Chamber of Representatives of Mexico approved an amendment that strengthens and updates the General Education Law (Article 75) and nutritional guidelines to ban the sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools. WHAT DID THE RESEARCHERS DO AND FIND?: - We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and total energy intake (TEI) per day.- We used microsimulation modeling to predict body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools.- Our modeling study suggests that an important impact on obesity prevalence can be expected if the law is implemented and enforced as intended. WHAT DO THESE FINDINGS MEAN?: - If successful, this law could serve as an example beyond Mexico on how to achieve changes in body weight through school food regulation.- An important limitation of our main scenario is that we assumed full compliance of schools with the law, yet lower compliance will reduce its impact. We also did not consider historical trends on obesity or NEDFBs consumed in schools during our 1 year simulation, and we considered only the ban impact inside schools, excluding effects near and outside schools.

The relationship between the price and demand of alcohol, tobacco, unhealthy food, sugar-sweetened beverages, and gambling: an umbrella review of systematic reviews.

BACKGROUND: The WHO highlight alcohol, tobacco, unhealthy food, and sugar-sweetened beverage (SSB) taxes as one of the most effective policies for preventing and reducing the burden of non-communicable diseases. This umbrella review aimed to identify and summarise evidence from systematic reviews that report the relationship between price and demand or price and disease/death for alcohol, tobacco, unhealthy food, and SSBs. Given the recent recognition as gambling as a public health problem, we also included gambling. METHODS: The protocol for this umbrella review was pre-registered (PROSPERO CRD42023447429). Seven electronic databases were searched between 2000-2023. Eligible systematic reviews were those published in any country, including adults or children, and which quantitatively examined the relationship between alcohol, tobacco, gambling, unhealthy food, or SSB price/tax and demand (sales/consumption) or disease/death. Two researchers undertook screening, eligibility, data extraction, and risk of bias assessment using the ROBIS tool. RESULTS: We identified 50 reviews from 5,185 records, of which 31 reported on unhealthy food or SSBs, nine reported on tobacco, nine on alcohol, and one on multiple outcomes (alcohol, tobacco, unhealthy food, and SSBs). We did not identify any reviews on gambling. Higher prices were consistently associated with lower demand, notwithstanding variation in the size of effect across commodities or populations. Reductions in demand were large enough to be considered meaningful for policy. CONCLUSIONS: Increases in the price of alcohol, tobacco, unhealthy food, and SSBs are consistently associated with decreases in demand. Moreover, increasing taxes can be expected to increase tax revenue. There may be potential in joining up approaches to taxation across the harm-causing commodities.

Wild capuchin monkeys use stones and sticks to access underground food.

Primates employ different tools and techniques to overcome the challenges of obtaining underground food resources. Humans and chimpanzees are known to tackle this problem with stick tools and one population of capuchin monkeys habitually uses stone tools. Although early hominids could have used stones as digging tools, we know little about when and how these could be useful. Here, we report a second primate population observed using stone tools and the first capuchin monkey population to habitually use the 'stick-probing' technique for obtaining underground resources. The bearded capuchin monkeys (Sapajus libidinosus) from Ubajara National Park, Brazil, use 'hands-only' and 'stone-digging' techniques for extracting underground storage organs and trapdoor spiders. Males also use 'stick-probing' and 'stone-stick' techniques for capturing trapdoor spiders. Tool use does not increase success in obtaining these resources. Stone-digging is less frequent in this population than in the only other known population that uses this technique. Females use stones in a lower proportion of their digging episodes than males in both populations. Ecological and cultural factors potentially influence technique choice and sex differences within and between populations. This population has a different pattern of underground food exploration using tools. Comparing this population with others and exploring the ecological and cultural factors under which capuchin monkeys employ different tools and techniques will allow us to better understand the pressures that may have shaped the evolution of those behaviors in primates.

Effects of sleep deprivation on food-related Pavlovian-instrumental transfer: a randomized crossover experiment.

Recent research suggests that insufficient sleep elevates the risk of obesity. Although the mechanisms underlying the relationship between insufficient sleep and obesity are not fully understood, preliminary evidence suggests that insufficient sleep may intensify habitual control of behavior, leading to greater cue-elicited food-seeking behavior that is insensitive to satiation. The present study tested this hypothesis using a within-individual, randomized, crossover experiment. Ninety-six adults underwent a one-night normal sleep duration (NSD) condition and a one-night total sleep deprivation (TSD) condition. They also completed the Pavlovian-instrumental transfer paradigm in which their instrumental responses for food in the presence and absence of conditioned cues were recorded. The sleep × cue × satiation interaction was significant, indicating that the enhancing effect of conditioned cues on food-seeking responses significantly differed across sleep × satiation conditions. However, this effect was observed in NSD but not TSD, and it disappeared after satiation. This finding contradicted the hypothesis but aligned with previous literature on the effect of sleep disruption on appetitive conditioning in animals-sleep disruption following learning impaired the expression of appetitive behavior. The present finding is the first evidence for the role of sleep in Pavlovian-instrumental transfer effects. Future research is needed to further disentangle how sleep influences motivational mechanisms underlying eating.

Fine-grained food image classification and recipe extraction using a customized deep neural network and NLP.

Global eating habits cause health issues leading people to mindful eating. This has directed attention to applying deep learning to food-related data. The proposed work develops a new framework integrating neural network and natural language processing for classification of food images and automated recipe extraction. It address the challenges of intra-class variability and inter-class similarity in food images that have received shallow attention in the literature. Firstly, a customized lightweight deep convolution neural network model, MResNet-50 for classifying food images is proposed. Secondly, automated ingredient processing and recipe extraction is done using natural language processing algorithms: Word2Vec and Transformers in conjunction. Thirdly, a representational semi-structured domain ontology is built to store the relationship between cuisine, food item, and ingredients. The accuracy of the proposed framework on the Food-101 and UECFOOD256 datasets is increased by 2.4% and 7.5%, respectively, outperforming existing models in literature such as DeepFood, CNN-Food, Wiser, and other pre-trained neural networks.

Valorisation of Agri-Food Waste for Bioactive Compounds: Recent Trends and Future Sustainable Challenges.

Worldwide, a massive amount of agriculture and food waste is a major threat to the environment, the economy and public health. However, these wastes are important sources of phytochemicals (bioactive), such as polyphenols, carotenoids, carnitine, coenzymes, essential oils and tocopherols, which have antioxidant, antimicrobial and anticarcinogenic properties. Hence, it represents a promising opportunity for the food, agriculture, cosmetics, textiles, energy and pharmaceutical industries to develop cost effective strategies. The value of agri-food wastes has been extracted from various valuable bioactive compounds such as polyphenols, dietary fibre, proteins, lipids, vitamins, carotenoids, organic acids, essential oils and minerals, some of which are found in greater quantities in the discarded parts than in the parts accepted by the market used for different industrial sectors. The value of agri-food wastes and by-products could assure food security, maintain sustainability, efficiently reduce environmental pollution and provide an opportunity to earn additional income for industries. Furthermore, sustainable extraction methodologies like ultrasound-assisted extraction, pressurized liquid extraction, supercritical fluid extraction, microwave-assisted extraction, pulse electric field-assisted extraction, ultrasound microwave-assisted extraction and high hydrostatic pressure extraction are extensively used for the isolation, purification and recovery of various bioactive compounds from agri-food waste, according to a circular economy and sustainable approach. This review also includes some of the critical and sustainable challenges in the valorisation of agri-food wastes and explores innovative eco-friendly methods for extracting bioactive compounds from agri-food wastes, particularly for food applications. The highlights of this review are providing information on the valorisation techniques used for the extraction and recovery of different bioactive compounds from agricultural food wastes, innovative and promising approaches. Additionally, the potential use of these products presents an affordable alternative towards a circular economy and, consequently, sustainability. In this context, the encapsulation process considers the integral and sustainable use of agricultural food waste for bioactive compounds that enhance the properties and quality of functional food.

Enzyme modified biodegradable plastic preparation and performance in anaerobic co-digestion with food waste.

A modified biodegradable plastic (PLA/PBAT) was developed by through covalent bonding with proteinase K, porcine pancreatic lipase, or amylase, and was then investigated in anaerobic co-digestion mixed with food waste. Fluorescence microscope validated that enzymes could remain stable in modified the plastic, even after co-digestion. The results of thermophilic anaerobic co-digestion showed that, degradation of the plastic modified with Proteinase K increased from 5.21 ± 0.63 % to 29.70 ± 1.86 % within 30 days compare to blank. Additionally, it was observed that the cumulative methane production increased from 240.9 ± 0.5 to 265.4 ± 1.8 mL/gVS, and the methane production cycle was shortened from 24 to 20 days. Interestingly, the kinetic model suggested that the modified the plastic promoted the overall hydrolysis progression of anaerobic co-digestion, possibly as a result of the enhanced activities of Bacteroidota and Thermotogota. In conclusion, under anaerobic co-digestion, the modified the plastic not only achieved effective degradation but also facilitated the co-digestion process.

#junkfluenced: the marketing of unhealthy food and beverages by social media influencers popular with Canadian children on YouTube, Instagram and TikTok.

BACKGROUND: Marketing of unhealthy foods to children on digital media significantly impacts their dietary preferences and contributes to diet-related noncommunicable diseases. Canadian children spend a significant amount of time on digital devices and are frequently exposed to unhealthy food marketing on social media, including by influencers with celebrity status who endorse products. This study aimed to examine the frequency, healthfulness, and power of unhealthy food marketing in posts by influencers popular with Canadian children on YouTube, Instagram and TikTok. METHODS: The top 9 influencers popular amongst Canadian children aged 10-12 years were identified from the 2021 International Food Policy Study Youth Survey. A total of 2,232 Instagram, YouTube and TikTok posts made by these influencers between June 1st 2021 and May 31st 2022 were examined for instances of food marketing. Food products/brands were identified and frequencies were calculated for the number of posts promoting food products/brands, posts promoting products/brands classified as less healthy according to Health Canada's Nutrient Profile Model (2018) and marketing techniques utilized. RESULTS: YouTube had the highest average rate of food marketing instances per post, at a rate of 1 food marketing instance every 0.7 posts, while TikTok and Instagram had instances every 10.2 posts and 19.3 posts, respectively. Overall, fast food restaurants was the most promoted food category (21%), followed by regular soft drinks (13%), snacks (11%), candy and chocolate (11%) and water (8%). The most frequently used marketing techniques were appeals to fun/cool (37%), the use of songs or music (28%) and the product being consumed (25%). In terms of healthfulness, 83% of the products/brands (87% of brands and 82% of products) promoted were classified as less healthy. CONCLUSIONS: Social media influencers play a substantial role in promoting unhealthy food products to children, primarily fast food items. Given the significant impact of such marketing on children, there is a need for ongoing government-led monitoring, and it is crucial to include social media and influencer marketing in marketing restrictions targeting children in Canada to safeguard this vulnerable demographic.

Comfort food concepts and contexts in which they are used: A scoping review protocol.

OBJECTIVE: The objectives of this study are to clarify the scientific definition of comfort food, identify which methodologies are being used in research on this topic and which factors are associated with the consumption of comfort food. INTRODUCTION: The consumption of comfort foods is subjective and influenced by individual experiences, as they are known and appreciated by the person. However, divergences about the definition of comfort food in the scientific literature reflect the heterogeneity of the methods used in the research, and consequently identification of possible factors associated with the consumption of this type of food, which can influence the knowledge about the consumption of these foods and their potential effects on the health of those who consume them. INCLUSION CRITERIA: Works with a qualitative and quantitative approach published in full in indexed sources or in gray literature, available online in the databases consulted, without restriction on language or year of publication will be included. METHODS: The protocol was built based on the methodological recommendations of the Joanna Briggs Institute (JBI) for scoping reviews and the recommendations of the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The Participants, Concept and Context (PCC) mnemonic strategy was built: general population, comfort food concept and world context. Based on this, search strategies were developed for different databases. Instruments were also developed for recording documents, extracting data, justifying the exclusion of documents and not obtaining access to content. A Pilot Study was conducted to test the developed methodology and instruments. The protocol has been registered with the Open Science Framework (OSF) (https://osf.io/gnza4/). The results will be presented in the review resulting from this protocol in three ways: accounting of the documents will be recorded in a PRISMA Flow Diagram, the main information of the studies and their frequencies will be presented in a table, and the union of these outcomes will be presented visually in a Graphical Abstract.

Gut microbiome resilience of green-lipped mussels, Perna canaliculus, to starvation

Host gut microbiomes play an important role in animal health and resilience to conditions, such as malnutrition and starvation. These host-microbiome relationships are poorly understood in the marine mussel Perna canaliculus, which experiences significant variations in food quantity and quality in coastal areas. Prolonged starvation may be a contributory factor towards incidences of mass mortalities in farmed mussel populations, resulting in highly variable production costs and unreliable market supplies. Here, we examine the gut microbiota of P. canaliculus in response to starvation and subsequent re-feeding using high-throughput amplicon sequencing of the 16S rRNA gene. Mussels showed no change in bacterial species richness when subjected to a 14-day starvation, followed by re-feeding/recovery. However, beta bacteria diversity revealed significant shifts (PERMANOVA p-value < 0.001) in community structure in the starvation group and no differences in the subsequent recovery group (compared to the control group) once they were re-fed, highlighting their recovery capability and resilience. Phylum-level community profiles revealed an elevation in dominance of Proteobacteria (ANCOM-BC p-value <0.001) and Bacteroidota (ANCOM-BC p-value = 0.04) and lower relative abundance of Cyanobacteria (ANCOM-BC p-value = 0.01) in the starvation group compared to control and recovery groups. The most abundant genus-level shifts revealed relative increases of the heterotroph Halioglobus (p-value < 0.05) and lowered abundances of the autotroph Synechococcus CC9902 in the starvation group. Furthermore, a SparCC correlation network identified co-occurrence of a cluster of genera with elevated relative abundance in the starved mussels that were positively correlated with Synechococcus CC9902... (AU)

How conspecific and allospecific eggs and larvae drive oviposition preference in Drosophila.

Where to lay the eggs is a crucial decision for females as it influences the success of their offspring. Female flies prefer to lay eggs on food already occupied and consumed by larvae, which facilitates social feeding, but potentially could also lead to detrimental interactions between species. Whether females can modulate their attraction to cues associated with different species is unknown. Here, we analyzed the chemical profiles of eggs and larvae of 16 Drosophila species, and tested whether Drosophila flies would be attracted to larvae-treated food or food with eggs from 6 different Drosophila species. The chemical analyses revealed that larval profiles from different species are strongly overlapping, while egg profiles exhibit significant species specificity. Correspondingly, female flies preferred to lay eggs where they detected whatever species' larval cues, while we found a significant oviposition preference only for eggs of some species but not others. Our findings suggest that both larval and egg cues present at a given substrate can drive oviposition preference in female flies.

Robust Deep Neural Network for Learning in Noisy Multi-Label Food Images.

Deep networks can facilitate the monitoring of a balanced diet to help prevent various health problems related to eating disorders. Large, diverse, and clean data are essential for learning these types of algorithms. Although data can be collected automatically, the data cleaning process is time-consuming. This study aims to provide the model with the ability to learn even when the data are not completely clean. For this purpose, we extend the Attentive Feature MixUp method to enable its learning on noisy multi-label food data. The extension was based on the hypothesis that during the MixUp phase, when a pair of images are mixed, the resulting soft labels should be different for each ingredient, being larger for ingredients that are mixed with the background because they are better distinguished than when they are mixed with other ingredients. Furthermore, to address data perturbation, the incorporation of the Laplace approximation as a post-hoc method was analyzed. The evaluation of the proposed method was performed on two food datasets, where a notable performance improvement was obtained in terms of Jaccard index and F1 score, which validated the hypothesis raised. With the proposed MixUp, our method reduces the memorization of noisy multi-labels, thereby improving its performance.

Amount Estimation Method for Food Intake Based on Color and Depth Images through Deep Learning.

In this paper, we propose an amount estimation method for food intake based on both color and depth images. Two pairs of color and depth images are captured pre- and post-meals. The pre- and post-meal color images are employed to detect food types and food existence regions using Mask R-CNN. The post-meal color image is spatially transformed to match the food region locations between the pre- and post-meal color images. The same transformation is also performed on the post-meal depth image. The pixel values of the post-meal depth image are compensated to reflect 3D position changes caused by the image transformation. In both the pre- and post-meal depth images, a space volume for each food region is calculated by dividing the space between the food surfaces and the camera into multiple tetrahedra. The food intake amounts are estimated as the difference in space volumes calculated from the pre- and post-meal depth images. From the simulation results, we verify that the proposed method estimates the food intake amount with an error of up to 2.2%.

Characterization of Crude and Processed Pulp Cell Walls of Three Selected Mamey Accessions (Mammea americana L.).

Mamey (Mammea americana L.) is a tropical fleshy fruit native from the West Indies and northern South America. It is very appreciated for its flavor and color but has been little described. The present study investigates the composition and histochemistry of the pulp cell walls of three mamey accessions readily available in Martinique. The impact of pulp processing into puree on cell wall composition is evaluated. The histology and rheology of mamey puree are assessed considering these characterizations. Mamey pulp cell wall composition is dominated by highly methyl-esterified pectins (DM: 66.2-76.7%) of high molecular weight, and show few hemicelluloses, mainly xyloglucans. Processing reduced methyl-esterified uronic acid contents and gave purees with significantly different viscosities. Mamey puree was composed of polydisperse particles (20-2343 µm), which size distributions were different depending on the accession: Ti Jacques was dominated by smaller particles (50% had approximated diameters lower than 160 µm), Sonson's by larger particles (50% had approximated diameters higher than 900 µm), and Galion's had an intermediate profile. This new knowledge on mamey pulp is valuable for future works on mamey processing into new food products, even more so for those including cell wall polysaccharide-degrading enzymes.

The Effect of Essential Oils from Asteraceae Plants on Behavior and Selected Physiological Parameters of the Bird Cherry-Oat Aphid.

Essential oils (EOs), including those from the Asteraceae plants, have been shown to have promising insecticidal activity against a wide range of insect pests. Understanding the mechanism of action of EOs is one of the studied aspects. The present study aimed to evaluate the effect of essential oils from Achillea millefolium, Santolina chamaecyparissus, Tagetes patula and Tanacetum vulgare on the settling and probing behavior of the bird cherry-oat aphid (Rhopalosiphum padi L.). In addition, the effect of the oils on the activity of such enzymes as trypsin, pepsin and α- and ß-glucosidase involved in the metabolism of proteins and sugars of the insects was examined. The leaf-choice bioassays demonstrated that the studied EOs limited aphid settling for at least 24 h after the treatment. The application of EOs also inferred with aphid probing behavior by reducing the total probing time and total duration of phloem sap ingestion. Aphids spent more time in the search phase due to an increase in the number and total duration of pathway phases. Moreover, the activity of the studied proteases and glucosidases significantly decreased in R. padi females exposed to the EOs. The enzyme inhibition varied depending on the applied oil and exposure time. Generally, the EOs with stronger deterrent activity also showed higher inhibitory effects. The results suggest that the tested EOs disrupt key digestive processes in R. padi which may be an important factor determining their aphicidal activity.

Characterizing Food Policy Councils' Network Partnerships and COVID-19 Responses.

The COVID-19 pandemic pushed millions of Americans into food insecurity. Food policy councils (FPCs) across the country played a vital role in organizing coordinated food responses across multiple sectors. We used a social network analysis (SNA) approach to investigate: (1) the network of partnering organizations and agencies within FPCs; (2) how the characteristics of FPCs' network partnerships (i.e., degree, coreness, and density) related to programmatic, policy, and advocacy actions in response to the pandemic; and (3) how FPCs' use of a racial or social equity framework shifted their network partnerships and responses. Local government agencies and food supply chain actors were core in FPCs' network partnerships, while public utilities, correctional facilities, social justice groups, and others were non-core partners. Network density was more likely to be associated with any action by FPCs, and it was especially pronounced for advocacy actions taken by FPCs; trends were similar among FPCs that reported using a racial or social equity framework. The findings begin to uncover core actors in FPCs' partnerships and opportunities to establish new partnerships, particularly with social justice groups. The results also suggest that network density (interconnectedness) may be more important than other network characteristics when responding to food-related needs.