Purpose:
Produce prescription projects (PPRs) engage multisector partnerships, most often between healthcare organizations (e.g., clinics) and food retailers (e.g., groceries, farmers’ markets), to mitigate food insecurity and reduce diet-related chronic disease. In the United States (US), the largest federal funding source for PPRs is the US Department of Agriculture (USDA) Gus Schumacher Nutrition Incentive Program (GusNIP). GusNIP requires that PPR projects collect healthcare outcomes, utilization, and costs data for evaluation. However, substantial challenges exist. The objective of this study is to understand facilitators, barriers, lessons learned, and emergent best practices for healthcare evaluation processes among PPRs. This work will inform implementation of nutrition-related behavior change programs in the US.  

Methods:
This evaluation, conducted by the GusNIP Nutrition Incentive Program Technical Assistance, Training, and Information Center used an instrumental, multiple methods, case study design. The sample included four PPRs funded in a 1-year pilot grant to measure healthcare outcomes, utilization, and costs. Data includes funded grant applications (n=4), a contextual description of each unique PPR, pre/post qualitative interviews (n=8), and midpoint focus groups (n=2) with program leadership. Researchers employed a thematic qualitative analytic approach to construct themes focused on facilitators, barriers, and opportunities.

Results:
Three salient themes emerged: 1) PPR projects need sufficient time and resources to develop procedures to collect and share healthcare data; 2) healthcare data procedures should be tailored to PPR design (e.g., PPR distribution and redemption method), outcomes of interest, and electronic health record (EHR) capabilities; 3) PPR projects need technical support related to technology, data security, and data sharing.

Conclusions:
EHR data can provide insight on the impact of PPRs and related healthcare interventions on health outcomes and cost-effectiveness in reaching target patient outcomes. To be successful, evaluation efforts must consider project capacity and ensure adequate resources to collect, securely share, and analyze healthcare data. Our findings are based on data collected from diverse health care contexts and models and indicate that there need to be multiple approaches to evaluate the impacts of PPRs and related programs on health outcomes, healthcare utilization, and costs, in the US and possibly other countries with similar health care systems.

Purpose: The UNM Basic Needs Project conducted a statewide survey of basic needs insecurities among students, staff and faculty across public institutions of higher education in New Mexico (NM). This project examined food insecurity (FI) and nutrition insecurity (NI), a distinct but complementary construct, and associations with mental health-related outcomes.
Methods: An anonymous cross-sectional Qualtrics survey was distributed to currently enrolled or employed students, staff, and faculty at 27 NM institutions in February-March 2023. FI was assessed using the U.S. Department of Agriculture (USDA) 18-item household food security survey module (FSSM) and NI was assessed using a new one-item nutrition security screener (NSS; “In the past 12 months, I worried that the food I was able to eat would hurt my health and well-being” where “sometimes”, “often”, and “always” indicated NI). We combined the NSS with the first two items of the FSSM, known as the Hunger Vital Sign (HVS), to examine food/nutrition insecurity (FNI); an affirmative response to any of the three questions indicated FNI. Using logistic regression, associations between FI (FSSM and HVS), NI (NSS), and FNI (HVS+NSS) and mental health-related outcomes [symptoms of anxiety (GAD-2), symptoms of depression (PHQ-2), lack of social support] were examined.
Results/Findings: 12,047 completed both the FSSM and NSS. Of those, 51.6% were FI according to the FSSM, 61.7% were FI according to the HVS, 37.7% were NI according to the NSS, and 67.5% were FNI according to the HVS+NSS. Nearly 39% had symptoms of anxiety (GAD-2 score>3), 30.5% had symptoms of depression (PHQ-2 score>3), and 8.2% lacked social support. All associations between FI, NI. and FNI and outcomes were significant and positive (P<0.0001). Compared to FI measured via the FSSM or HVS, FNI had a stronger association with anxiety (OR=3.36, 95% CI=3.08-3.67), depression (OR=4.33, 95% CI=3.90-4.80) and lack of social support (OR=3.47, 95% CI=2.87-4.20).
Conclusions: As social risk screening is implemented in clinical and community settings across the U.S., measurement and follow-up are critical. Adding a one-item NSS to the widely-used HVS may not improve identification of FI in general, but may alert clinicians to further screen for mental health concerns.

Purpose: Due to lack of age-specific food insecurity (FI) measures, youth-focused research and interventions usually rely on caregiver-reported FI. However, there is growing evidence that many youth report FI differently than their caregivers and may be misclassified using traditional measures. To better understand which groups are at risk of misclassification, we examined how sociodemographic factors pattern across adolescent-caregiver dyads according to adolescent and caregiver report of very low food security (VLFS).

Methods: Data were collected through two coordinated, population-based studies: EAT 2010 and F-EAT 2010. Students from Minneapolis/St. Paul area public schools (USA), along with their primary caregivers, were surveyed in 2009-2010. Adolescents reported past-year VLFS, or hunger because their family could not afford more food, using a single survey item. Caregivers completed the U.S. Household Food Security Survey Module Six-Item Short Form. The analytic sample included 425 adolescent-caregiver dyads with caregiver-reported household FI, where the caregiver and/or adolescent reported any VLFS. Adolescents (mean age=14.8 years) were 54.8% female and 87.4% people of color. Linear and logistic regression models examined cross-sectional associations between alignment of adolescent and caregiver VLFS with sociodemographic factors.

Results: In 78 dyads, both adolescent and caregiver reported VLFS; in 122 dyads, only the adolescent reported VLFS; and in 225 dyads, only the caregiver reported VLFS. Compared to dyads with adolescent and caregiver VLFS, dyads with adolescent-only VLFS had more children per household (Beta=1.13, p<.0001); they were also more likely to include adolescents of color (Odds Ratio [OR]=2.84, p=0.02) and/or caregivers of color (OR=2.51, p=0.008). Findings for individual racial/ethnic identities will be shared in the presentation. There were no significant differences by adolescent age or gender, caregiver gender, whether the adolescent lived in multiple households, or household receipt of public assistance.

Conclusions: These results suggest that caregiver-reported FI might mask some experiences of adolescent hunger, with certain sociodemographic groups being disproportionately affected. These findings should inform further investigation into the reasons for adolescent-caregiver reporting differences (e.g., potential differences in adolescent and caregiver experience of VLFS, unintentional or intentional misreporting, etc.). Finally, these results also underscore the need for accurate, age-specific methods for measuring FI in diverse populations.

Purpose:
We present the overall design and lessons learned from implementation of the Houston Food Bank (HFB) comprehensive food prescription (Food Rx) program on gestational weight gain, pregnancy and birth outcomes, and food/nutrition security in low-income, ethnically diverse, at-risk women in Houston, TX.

Methods:
Utilizing a quasi-experimental design, the study involves high-risk pregnant women served by Community Health Choice (CHC) Clinics over a 24-month period. The Food Rx program provides bi-weekly produce prescription box deliveries from the Houston Food Bank (HFB). The primary outcome of interest is excess gestational weight gain (EGWG), while secondary outcomes encompass adverse pregnancy events, birth outcomes, food/nutrition security, and diet quality. Data collection includes pregnancy outcomes (gestational weight gain as the primary outcome, blood pressure, HbA1c), and birth outcomes (pre-term birth, gestational week of delivery), mental health outcomes, food security, nutrition security and diet quality at enrollment, 3 and 6 months post-enrollment, and a post-partum survey at 2 months. Self-reported data is matched with claims data from CHC. Data on the number of successful Food Rx deliveries will be collected by the Houston Food Bank.

Results:
A sample size of 620 women, considering a minimum detectable effect size for EGWG of 2.7 lbs, provides 80% power for detecting effects, with a 20% overage for potential study dropouts. Mixed effects models with linear, logit, or non-linear links will be utilized to account for missing data, repeated measures, and different specifications of outcomes. Regression-based methods, mixed effects models, and dose-response analyses will examine Food Rx's impact on weight gain and secondary outcomes. As part of the dose-response analyses, mediation models will be utilized to examine the role of food insecurity and diet quality in weight change.

Conclusion:
This study contributes insights into the effectiveness of produce prescriptions on maternal health outcomes and lessons learned in the implementation process of a produce prescription program.

Purpose
Improving physical activity (PA) research in Africa is key to action on developing PA promotion strategies to address the rising epidemic of non-communicable diseases in the region countries. Yet, there is a paucity of country-level PA indicators for research, surveillance and monitoring, and policy across the African region. We aim to describe the evolution of PA research in Africa, examine income and gender inequalities, and discuss future possibilities.
Methods
This was a secondary analysis of the Global Observatory for Physical Activity (GoPA!) data on PA research in Africa (1950 to 2019). The GoPA team conducted a systematic review of PA and health articles indexed in PubMed, SCOPUS, and ISI Web of Knowledge for all world countries in 2020. In 2023, we further analyzed the systematic review dataset to (1) determine sex disparities in authorships, and (2) explore relationships between PA research characteristics and country-level human and public health indicators for African countries.
Results/Findings
We identified 514 PA articles from 47 African countries in the past 70 years. Majority (83.1%) of the articles were published between 2012 and 2019. Fifteen countries had no publications. Six countries (South Africa [n=156], Nigeria [n=85], Ethiopia [n=44], Ghana [n=41], Kenya [n=39], and Cameroon [n=20]) accounted for about 75% of the publications. Most articles were observational (92.4%), single-country studies (78.4%), with male first (58.4%) and last authors (68%), and were classified as surveillance studies (45.1%). Few studies addressed interventions (5.8%) and policy (3.5%) or used device-based PA measurement (14.0%). The number of articles per country was positively related to human population level (r=0.552, P= 0.000) and GDP % spent on Research and Development (r=0.301, P=0.040). The publication rate per 100.000 people was positively related with Human Development Index (r=0.349, P=0.016), and negatively with Gender Inequality Index (r= -0.360, P=0.019).
Conclusions
Our results provide an overview and status of PA research in Africa, highlighting country differences and gender inequalities in authorship. The findings may be used to benchmark the evolution of research in the region and to inform areas for improvement. There is an urgent need for more PA interventions and policy studies in Africa.