BACKGROUND: Healthcare organizations are increasingly screening and addressing food insecurity (FI); yet, limited data exists from clinic-based settings on how FI rates change over time. The objective of this study was to evaluate household FI trends over a two-year period at a clinic that implemented a FI screening and referral program. METHODS: In this retrospective cohort study, data were extracted for all visits at one academic primary care clinic for all children aged 0-18 years whose parents/guardians had been screened for FI at least once between February 1, 2018 to February 28, 2019 (Year 1) and screened at least once between March 1, 2019 to February 28, 2020 (Year 2). Bivariate analyses tested for differences in FI and demographics using chi-square tests. Mixed effects logistic regression was used to assess change in FI between Years 1 and 2 with random intercept for participants controlling for covariates. The interaction between year and all covariates was evaluated to determine differences in FI change by demographics. RESULTS: Of 6182 patients seen in Year 1, 3691 (59.7%) were seen at least once in Year 2 and included in this study. In Year 1, 19.6% of participants reported household FI, compared to 14.1% in Year 2. Of those with FI in Year 1, 40% had FI in Year 2. Of those with food security in Year 1, 92.3% continued with food security in Year 2. Compared to Hispanic/Latinx participants, African American/Black (OR: 3.53, 95% CI: 2.33, 5.34; p < 0.001) and White (OR: 1.88, 95% CI: 1.06, 3.36; p = 0.03) participants had higher odds of reporting FI. African American/Black participants had the largest decrease in FI between Years 1 and 2 (- 7.9, 95% CI: - 11.7, - 4.1%; p < 0.0001). CONCLUSIONS: Because FI is transitional, particularly for racial/ethnic minorities, screening repeatedly can identify families situationally experiencing FI.

Although the intent of community-based participatory research (CBPR) is to include community voices in all phases of a research initiative, community partners appear less frequently engaged in data analysis and interpretation than in other research phases. Using 4 brief case studies, each with a different data collection methodology, we provide examples of how community members participated in data analysis, interpretation, or both, thereby strengthening community capacity and providing unique insight. The roles and skills of the community and academic partners were different from but complementary to each other. We suggest that including community partners in data analysis and interpretation, while lengthening project time, enriches insights and findings and consequently should be a focus of the next generation of CBPR initiatives.