Trends in food insecurity rates at an academic primary care clinic: a retrospective cohort study

Abstract

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.

Social determinants of health screening in pediatric healthcare settings

“…Healthy People 2030 groups SDOH into five domains: economic stability, education access and quality, healthcare access and quality, neighborhood and built environment, and social and community context [1]. Over the past 2 years, pediatric literature has primarily focused on the domains of food insecurity/nutrition [10 ▪ ,22] and housing insecurity/housing conditions [23 ▪ ,24 ▪ ]. This is likely because of concrete social outcomes associated with community referrals (i.e., improving housing conditions/stability, and access to benefits like the Supplemental Nutrition Assistance Program), and prevalence within the pediatric population [22].…”

“…Over the past 2 years, pediatric literature has primarily focused on the domains of food insecurity/nutrition [10 ▪ ,22] and housing insecurity/housing conditions [23 ▪ ,24 ▪ ]. This is likely because of concrete social outcomes associated with community referrals (i.e., improving housing conditions/stability, and access to benefits like the Supplemental Nutrition Assistance Program), and prevalence within the pediatric population [22]. Additional domains, described below, have also emerged as areas of consideration for SDOH screening.…”

Integrating Social Care into Healthcare: A Review on Applying the Social Determinants of Health in Clinical Settings

“…Specifically, Table 2 provides information on patient population demographics and health conditions underpinning SDH clinical assessments, Table 3 lists various SDH screening tools used in clinical settings, Table 4 identifies various reasons for SDH integration, and finally, Supplementary Materials Table S1 lists the study design of the articles included in this review, method of integration, type of healthcare facility and its geographic location. Berkman-Syme Social Network Index, SNI (on social isolation) [56] BRFSS Survey-Behavior Risk Factor Surveillance System (1-3-item food insecurity questions) [26] CLEAR Toolkit-Community Leadership on the Environment, Advocacy, and Resilience (four-step process for assessing patient vulnerability in a contextually appropriate and caring way) [86] Family Needs Screening Tool (28-33-item survey) [87] HARK Tool-Humiliation, Afraid, Rape, Kick (four-item survey) [56] Health Begins Upstream Risks Screening Tool (28-item survey) [87] Health Leads Social Needs Screening Toolkit (seven-item survey) [63,81] HITS Screening Tool-Hurt-Insult-Threaten-Scream (12-item survey) [55] HVS-Hunger Vital Sign (two-item survey) [26,58,68,75] iHELP/iHELLP Social History Tool-Income/Insurance-Hunger/Housing Conditions/Homeless-Education/Ensuring Safety-Legal Status, Literacy-Personal Safety (14-24-item survey) [76] iScreen Social Screening Questionnaire (46-item survey) [87] MST-Malnutrition Screening Tool (two-item survey) [68] NASEM-National Academies of Sciences, Engineering, and Medicine (one-item measure of financial strain) [56] NHIS-National Health Interview Survey, a CDC-NCHS SDH assessments in clinical settings focused primarily on vulnerable, disadvantaged, at-risk, and/or socially isolated patients. These patients came from communities experiencing persistent socio-economic challenges, material deprivation, food insecurity, housing instability, and/or toxic stress.…”

Developing and sustaining a community advisory committee to support, inform, and translate biomedical research

“…The connection and idea led to a Community-Engaged Research Cooperative Agreement project and a Community-Engaged Research Fellowship. The team then received funding from a foundation for the project and ongoing research collaborations [25][26][27]. The linkages have led to new clinical projects, educational opportunities for medical students, and subsequent grant submissions, including a funded NIH R01 award to explore the cardiometabolic consequences of food insecurity among persons with HIV, and a funded foundation grant to support a cooperative grocery located within a food desert.…”