Skip to main content
HHS Author Manuscripts logoLink to HHS Author Manuscripts
. Author manuscript; available in PMC: 2026 Feb 25.
Published in final edited form as: Child Abuse Negl. 2023 Aug 15;145:106399. doi: 10.1016/j.chiabu.2023.106399

State expansion of Supplemental Nutrition Assistance Program eligibility and rates of foster care entries

Anna E Austin a,b,*, Rebecca B Naumann b,c, Meghan E Shanahan a,b, Madeline Frank a,b,d
PMCID: PMC12930766  NIHMSID: NIHMS2141304  PMID: 37591049

Abstract

Background:

State expansion of Supplemental Nutrition Assistance Program (SNAP) eligibility under broad-based categorical eligibility (BBCE) is associated with decreases in household poverty and food insecurity, child protective services investigations, and mental health and substance use disorders among adults, key contributors to foster care entry.

Objective:

To examine the association of state expansion of SNAP eligibility under BBCE with rates of foster care entries.

Participants:

Foster care entries among children ages <18 years.

Methods:

We used 2005–2019 data from the SNAP Policy Database and the Adoption and Foster Care Analysis and Reporting System (AFCARS). We conducted difference-in-differences analyses and generated event study plots adjusting for state economic conditions (percent population unemployed, median household income) and policies (minimum wage, refundable Earned Income Tax Credits, maximum Temporary Assistance for Needy Families benefit for a family of 3).

Results:

On average, there were 1.8 fewer foster care entries (95 % confidence interval (CI) −2.8, −0.8) per 1000 children per year in states that expanded SNAP eligibility than there would have been if they had not expanded eligibility. Average decreases in foster care entries were similar among young (−1.7 per 1000 children per year, 95 % −3.1, −0.3) and school-age (−1.8 per 1000 children per year, 95 % CI −2.7, −0.8) children and larger among Black non-Hispanic (−5.6 per 1000 children per year, 95 % CI −9.1, −2.0) than among White non-Hispanic (−1.4 per 1000 children per year, 95 % CI −2.2, −0.6) children. The magnitude of these decreases increased with greater time since policy adoption.

Conclusions:

Results add to growing evidence that programs and policies that support and stabilize household economic and material conditions may contribute to reductions in foster care entries at the population-level.

Keywords: Foster care, Food insecurity, Supplemental Nutrition Assistance Program, Broad-based categorical eligibility

1. Introduction

By age 18 years, approximately 1 in 20 U.S. children will be removed from their home and placed in foster care by child protective services (CPS) agencies (Yi et al., 2020). Foster care placement is associated with an increased likelihood of adverse health, social, and economic outcomes across the life course, including mental health and substance use disorders (Gypen et al., 2017; Seker et al., 2022; Vasileva & Petermann, 2018), lower education, employment, and income (Clemens et al., 2017; Clemens & Tis, 2016; Gypen et al., 2017), and experiences of homelessness (Dworsky et al., 2013; Gypen et al., 2017). Because one of the most commonly reported reasons for child removal from the home and placement in foster care is neglect, which is highly correlated with poverty (Hunter & Flores, 2021), population-level programs and policies that support the economic and material needs of families may be one strategy to reduce the number of children in foster care (Maguire-Jack et al., 2021; Pac et al., 2023; Paxson & Waldfogel, 2002, 2003; Rostad et al., 2020).

The Supplemental Nutrition Assistance Program (SNAP) is the largest program addressing food insecurity in the U.S., providing a monthly benefit to nearly 21 million low-income households to assist with the cost of food (United States Department of Agriculture, 2023b). Each year, >40 % of SNAP participants are children, and 65 % of SNAP participants live in a household with a child (Hales & Alisha., 2022; United States Department of Agriculture, 2023b). At the federal level, households are eligible for SNAP if household income is ≤130 % of the federal poverty level (FPL) and household assets are ≤$2750, with some modifications for households with an elderly person or person with a disability (Center on Budget and Policy Priorities, January 6, 2022). Under broad-based categorical eligibility (BBCE), states have the option to expand baseline SNAP eligibility by increasing the income limit to up to 200 % of the FPL and/or eliminating the asset test (Rosenbaum, 2019).

Prior research indicates that state expansion of SNAP eligibility under BBCE is associated with increases in SNAP enrollment (Dickert-Conlin et al., 2021; Jones et al., 2021; Pinard et al., 2017) and decreases in household poverty, food insecurity, and other material hardships (Ettinger de Cuba et al., 2019; Han, 2016; Tiehen et al., 2012). Additional research shows decreases in rates of CPS-investigated reports (Austin, Shanahan, et al., 2023; Johnson-Motoyama et al., 2022) and mental health and substance use disorders among adults in the context of state adoption of BBCE (Austin, Frank, et al., 2023; Naumann et al., under review). Thus, state expansion of SNAP eligibility is associated with decreases in several key contributors to foster care entries (Berger & Waldfogel, 2004; Fong, 2017). While a recent study found that state expansion of SNAP eligibility under BBCE was associated with a non-significant decrease in the rate foster care entries (Johnson-Motoyama et al., 2022), this study did not examine whether the magnitude of this decrease changed over time or differed for specific populations. Because it may take time for families to learn about new SNAP eligibility rules and enroll in the program and then additional time for the food purchasing assistance received through SNAP to affect household conditions, it is possible that it may take time to observe any decreases and that the magnitude of any observed decreases may increase over time. In addition, given racial disproportionality in CPS involvement and foster care placement (Kim et al., 2017; Yi et al., 2020), understanding whether potential changes in rates of foster care entries differ for Black and White non-Hispanic children is critical to understanding whether expanded SNAP eligibility can help address racial inequities. Last, as there are differences in other food assistance programs available for young children (Special Supplemental Nutrition Program for Women, Infants, and Children, or WIC (United States Department of Agriculture, 2022a, 2022b)) and school-age children (National School Lunch and School Breakfast Programs (United States Department of Agriculture, 2023c, 2023d)), it is possible that potential changes differ for younger and older children.

The aim of this study was to examine the association of state expansion of SNAP eligibility under BBCE with rates of foster care entries over time, overall and specifically for White and Black non-Hispanic children and for young (ages 0–4 years) and school-age children (age 5–17 years).

2. Methods

To examine the association of state expansion of SNAP eligibility under BBCE with rates of foster care entries, we used 2005–2019 data and a quasi-experimental study design with a difference-in-differences approach (Callaway & Sant'Anna, 2021).

2.1. Data sources

We used data from the SNAP Policy Database (United States Department of Agriculture, June 10, 2022a) and the Adoption and Foster Care Analysis and Reporting System (AFCARS). The SNAP Policy Database is available online from the United States Department of Agriculture (USDA) and provides data on state adoption of various SNAP policies from 1996 to 2016. We updated data on state adoption of BBCE policies for 2017–2019 using SNAP State Options Reports (United States Department of Agriculture, June 27, 2019) and communication with USDA and state SNAP agencies. The AFCARS files include data on children in foster care who have been placed, cared for, or supervised by state CPS agencies. Since 1995, all 50 states and D.C. have been mandated to submit these data to the Administration on Children and Families. We used the 2005–2019 AFCARS files to capture foster care entries in 2005–2019.

2.2. Measures

Our exposure was state expansion of SNAP eligibility under BBCE through increases in the income limit and/or elimination of the asset test. We determined the year states first expanded SNAP eligibility under BBCE from our updated SNAP Policy Database (Supplemental Table 1).

Our outcome was the number of foster care entries among children ages <18 years per 1000 child population by state and year. To determine the number of foster care entries among Black and White non-Hispanic children, we examined the race and ethnicity of the child. In AFCARS, multiple variables indicate whether the child or the child's caregiver identifies the child as a member of various races and ethnicities. For each child entering foster care, we examined their recorded race and ethnicity and assigned race and ethnicity as American Indian or Alaska Native, Hispanic, Black non-Hispanic, White non-Hispanic, other non-Hispanic races, multiple non-Hispanic races, or missing. For 2005–2019 in the states included in analyses, 45.0 % of foster care entries were among White non-Hispanic children and 24.9 % were among Black non-Hispanic children (Supplemental Table 2). A total of 2.2 % were missing information on child race and ethnicity. To determine the number of foster care entries among young children (ages 0–4 years) and school-age children (ages 5–17 years), we examined the child's age at foster care entry as recorded in AFCARS. Given high rates of foster care entry for infants, we conducted sensitivity analyses among children age <1 year. For all analyses, we did not examine the reason the child was removed from the home and entered foster care given state variation in reporting specific reasons for removal in AFCARS (Sankaran et al., 2018).

We created a conceptual diagram of variables operative in the association of state expansion of SNAP eligibility under BBCE with foster care entries using existing empirical evidence and our subject matter expertise (Supplemental Fig. 1). Based on our conceptual diagram, to account for potential bias due to confounding, we adjusted analyses for measures of the underlying state policy context (state minimum wage, refundable Earned Income Tax Credit, maximum Temporary Assistance for Needy Families benefit for a family of 3) and state economic conditions (percent population unemployed, median household income). We obtained data on these variables from the University of Kentucky National Welfare Database (University of Kentucky Center for Poverty Research, 2020) and the U.S. Census Bureau Small Area Income and Poverty Estimates (United States Census Bureau, 2020).

2.3. Statistical analysis

To examine the association of state expansion of SNAP eligibility under BBCE with rates of foster care entries, we used a difference-in-differences approach developed by Callaway and Sant'Anna (Callaway & Sant'Anna, 2021). Recent research indicates that the traditional two-way fixed effects approach (e.g., fixed effects for state and year) can result in biased estimates of association when there is heterogeneity in associations by time since policy adoption (e.g., differences in associations at 1 vs. 2 years post-policy adoption) or time of policy adoption (e.g., differences in associations for states that adopt the policy in 2009 vs. states that adopt the policy in 2011) (Callaway & Sant'Anna, 2021; Roth, Sant'Anna, Bilinski, & Poe, 2023). We hypothesized that there would be heterogeneity in associations by time since policy adoption, with the magnitude of associations increasing with greater time since policy adoption.

To conduct analyses, we used variation in time (i.e., time pre- and post-expansion of SNAP eligibility) and in state policy adoption status (i.e., states that did and did not expand SNAP eligibility from 2005 to 2019). Thus, we included states that did not expand SNAP eligibility under BBCE during 2005–2019 and states that expanded SNAP eligibility under BBCE at some point during 2005–2019 (Supplemental Table 1). We excluded 10 states that expanded SNAP eligibility under BBCE prior to 2005 given that these states had no pre-policy time. We used the difference-in-differences approach to create event study plots showing the estimated difference in the number of foster care entries per 1000 children for each year pre- and post-policy adoption in states that expanded SNAP eligibility, compared to the counterfactual in which they did not expand SNAP eligibility, to assess for variation over time (Callaway & Sant'Anna, 2021). We also calculated an overall average post-policy estimate by averaging differences for years 0–6 post-policy adoption (Callaway & Sant'Anna, 2021).

In difference-in-differences approaches, the parallel trends assumption holds that in the absence of policy adoption, all states would follow the same trend in the outcome over time (Callaway & Sant'Anna, 2021). For our event study plots, we assessed the parallel trends assumption by examining whether pre-policy estimates were approximately 0 (Callaway & Sant'Anna, 2021) and, consistent with best practice guidance, excluded three states that contributed to violations of this assumption (Supplemental Table 1; Arizona, Nebraska, Indiana). Our final sample included data from 37 states during 2005–2019, for 555 state-years.

To assess the potential for unmeasured confounding to affect results, we conducted a falsification test using the rate of deaths due to flu, pneumonia, and other respiratory infections per 100,000 population as the outcome. We do not expect this outcome to be associated with state expansion of SNAP eligibility under BBCE.

In our difference-in-differences analyses, we used a doubly robust estimator based on stabilized inverse probability of treatment weights and ordinary least squares regression to generate measures of association estimating the difference in the number of foster care entries per 1000 children in the post-policy adoption period for states that adopted policies to expand SNAP eligibility under BBCE compared to the counterfactual scenario in which they did not adopt these policies. To account for repeated measures within states over time, we clustered standard errors at the state level. We conducted analyses in Stata 17 using the csdid package. To interpret results, we relied on the magnitude of the point estimate for measures of association and the width and location of the corresponding 95 % confidence interval (CI) (American Statistical Association, 2016). This study was considered exempt by the Institutional Review Board at the University of North Carolina at Chapel Hill.

3. Results

Two states expanded SNAP eligibility under BBCE in 2008, 10 in 2009, 10 in 2010, and 6 in 2011 (Supplemental Table 1). Rates of foster care entries among children ages <18 years in the 37 states included in analyses decreased from 2005 (4.4 per 1000 children) to 2013 (3.5 per 1000 children) and then remained relatively stable through 2019 (3.4 per 1000 children; Supplemental Figs. 1-2). Rates of foster care entries were consistently higher among Black than among White non-Hispanic children (4.7 vs. 3.0 per 1000 children in 2019, respectively) and among children ages 0–4 years than among children ages 5–17 years (5.5 vs. 2.6 per 1000 children in 2019, respectively).

There was a decrease in foster care entries among all children, White non-Hispanic children, Black non-Hispanic children, children ages 0–4 years, and children ages 5–17 years, beginning the year after states first expanded SNAP eligibility under BBCE, and the magnitude of this decrease increased with greater time since policy adoption (Figs. 1-3; Supplemental Tables 3-7). Among all children, on average 1 year post-policy adoption, there were 1.1 fewer foster care entries per 1000 children (95 % CI −1.6, −0.6), and 6 years post-policy adoption, there were 2.9 fewer foster care entries per 1000 children (95 % CI −4.5, −1.2) in states that expanded SNAP eligibility than there would have been if they had not expanded eligibility.

Fig. 1.

Fig. 1.

Association of state expansion of Supplemental Nutrition Assistance Program (SNAP) eligibility under broad-based categorical eligibility with rates of foster care entries, 2005–2019.a

aAnalyses included states that did not expand SNAP eligibility under broad-based categorical eligibility during 2005–2016 (AK, AR, KS, MO, SD, TN, UT, VA, WY) and states that expanded SNAP eligibility in 2008 (GA, NY), 2009 (ID, MT, NH, NV, OH, OK, PA, RI, VT, WV), 2010 (AL, CA, CT, DC, IL, KY, LA, MS, NJ, NM), and 2011 (CO, FL, HI, IA, MN, NC). Analyses adjusted for state minimum wage, refundable Earned Income Tax Credit, maximum Temporary Assistance for Needy Families benefit for a family of 3, percent population unemployed, and median household income. Outcome modeled as number of foster care entries among children ages <18 years per 1000 child population.

Note: Year 0 is the year the year states first expanded SNAP eligibility under broad-based categorical eligibility by eliminating the asset test or increasing the income limit.

Fig. 3.

Fig. 3.

Association of state expansion of Supplemental Nutrition Assistance Program (SNAP) eligibility under broad-based categorical eligibility with rates of foster care entries by child age, 2005–2019.a

a. Children ages 0–4 years.

b. Children ages 5–17 years.

aAnalyses included states that did not expand SNAP eligibility under broad-based categorical eligibility during 2005–2016 (AK, AR, KS, MO, SD, TN, UT, VA, WY) and states that expanded SNAP eligibility in 2008 (GA, NY), 2009 (ID, MT, NH, NV, OH, OK, PA, RI, VT, WV), 2010 (AL, CA, CT, DC, IL, KY, LA, MS, NJ, NM), and 2011 (CO, FL, HI, IA, MN, NC). Analyses adjusted for state minimum wage, refundable Earned Income Tax Credit, maximum Temporary Assistance for Needy Families benefit for a family of 3, percent population unemployed, and median household income. Outcome modeled as number of foster care entries among children ages <18 years per 1000 child population.

Note: Year 0 is the year the year states first expanded SNAP eligibility under broad-based categorical eligibility by eliminating the asset test or increasing the income limit.

Over the entire post-policy period, there were on average 1.8 fewer foster care entries (95 % CI −2.8, −0.8) per 1000 children per year in states that expanded SNAP eligibility than there would have been if they had not expanded SNAP eligibility (Table 1). Decreases in foster care entries differed for Black and White non-Hispanic children, with 5.6 fewer foster care entries (95 % CI −9.1, −2.0) per 1000 children per year among Black non-Hispanic children and 1.4 fewer foster care entries (95 % CI −2.2, −0.6) per 1000 children per year among White non-Hispanic children, on average. Decreases in foster care entries were similar for young and school-age children, with 1.7 fewer foster care entries (95 % CI −3.1, −0.3) per 1000 children per year among children ages 0–4 years and 1.8 fewer foster care entries (95 % CI −2.7, −0.8) per 1000 children per year among children ages 5–17 years, on average.

Table 1.

Average post-policy difference in number of foster care entries per 1000 children per year, 2005–2019a

Average post-policy difference in states that expanded SNAP eligibility under BBCE compared to the counterfactual in
which they did not (95 % CI)
All children <18 years −1.8 (−2.8, −0.8)
Black non-Hispanic children ages <18 years −5.6 (−9.1, −2.2)
White non-Hispanic children ages <18 years −1.4 (−2.3, −0.5)
Children 0–4 years −1.6 (−3.2, −0.1)
Children 5–17 years −1.9 (−2.9, −0.9)
a

Analyses included states that did not expand SNAP eligibility under broad-based categorical eligibility during 2005–2016 (AK, AR, KS, MO, SD, TN, UT, VA, WY) and states that expanded SNAP eligibility in 2008 (GA, NY), 2009 (ID, MT, NH, NV, OH, OK, PA, RI, VT, WV), 2010 (AL, CA, CT, DC, IL, KY, LA, MS, NJ, NM), and 2011 (CO, FL, HI, IA, MN, NC). Analyses adjusted for state minimum wage, refundable Earned Income Tax Credit, maximum Temporary Assistance for Needy Families benefit for a family of 3, percent population unemployed, and median household income. Outcome modeled as number of foster care entries among children ages <18 years per 1000 child population.

In sensitivity analyses among infants age <1 year, over the entire post-policy period, there were on average 2.4 fewer foster care entries (95 % CI −5.2, 0.5) per 1000 children per year in states that expanded SNAP eligibility than there would have been if they had not (Supplemental Fig. 4; Supplemental Table 8). Of note, the 95 % CIs for estimated differences by year in the post-policy adoption period were wide, likely due to considerable variation across states in absolute rates of foster care entries among infants.

In the falsification test, there was no association of state expansion of SNAP eligibility under BBCE with rates of deaths due to flu, pneumonia, or other acute respiratory infections (Supplemental Fig. 5).

4. Discussion

Overall, our results demonstrated decreases in foster care entries among children ages <18 years in states that expanded SNAP eligibility by increasing the income limit and/or eliminating the asset test under BBCE. We found similar decreases in foster care entries among younger children and school age-children and larger decreases among Black non-Hispanic children than among White non-Hispanic children. These results add to growing evidence that programs and policies that support and stabilize household economic and material resources may contribute to reductions in the number of children entering foster care at the population-level (Maguire-Jack et al., 2021; Pac et al., 2023; Paxson & Waldfogel, 2002, 2003; Rostad et al., 2020).

On average, we found 1.8 fewer foster care entries per 1000 children per year in states that expanded SNAP eligibility under BBCE than we would have observed if these states had not expanded eligibility. Scaled to the 2019 child population in the 28 states that expanded SNAP eligibility under BBCE during the study period (43,979,757 children ages <18 years), this is equivalent to 79,163 fewer foster care entries than expected in 2019 alone. The most commonly reported reasons for child removal from the home and placement in foster care are neglect, which is highly correlated with poverty (Hunter & Flores, 2021), and parental drug use (U.S. Department of Health and Human Services, June 23, 2020). State expansion of SNAP eligibility under BBCE may contribute to decreases in foster care entries by addressing factors shown to increase the likelihood of neglect allegations and foster care entry (Berger & Waldfogel, 2004; Fong, 2017), including household economic and material conditions and parental mental health and substance use disorders (Austin, Frank, et al., 2023; Austin, Shanahan, et al., 2023; Ettinger de Cuba et al., 2019; Han, 2016; Johnson-Motoyama et al., 2022; Naumann et al., under review; Tiehen et al., 2012). Our results showing that there were larger decreases in foster care entries with greater time since state expansion of SNAP eligibility is consistent with a prior study on CPS-investigated reports (Austin, Shanahan, et al., 2023), and suggest that prevention benefits may accumulate over time.

We found larger average decreases in foster care entries among Black non-Hispanic children than among White non-Hispanic children in the context of state expansion of SNAP eligibility under BBCE. By age 18 years, nearly 1 in 10 Black non-Hispanic children, as compared to 1 in 20 White non-Hispanic children, are placed in foster care (Yi et al., 2020). Experiences of food insecurity are also unevenly distributed by race and ethnicity. In 2019–2020, 19 % of Black non-Hispanic compared to 6 % of White non-Hispanic children lived in a household that experienced food insecurity (Ullmann et al., 2022). For population-level programs and policies, including those targeting food insecurity, to effectively address the racial disproportionality in foster care entries, there need to be larger decreases in foster care entries among Black non-Hispanic children than among White non-Hispanic children. Our results suggest that state expansion of SNAP eligibility may be one component of larger strategies to reduce racial inequities in foster care entries.

Healthcare and social service professionals play an essential role in ensuring child safety and wellbeing. The American Academy of Pediatrics recommends that pediatric and primary care clinics screen children and caregivers for food insecurity at healthcare visits, connect families in need to community resources and federal and state food and nutrition programs, and advocate to protect and strengthen federal and state food and nutrition programs, including SNAP (Ashbrook et al., 2021; Council on Community et al., 2015). Suggested advocacy efforts include writing op-eds, meeting with policymakers, and joining state and local food insecurity taskforces (Ashbrook et al., 2021). The Farm Bill, federal legislation governing food and agriculture programs in the U.S., is reauthorized every 5 years (Congressional Research Service, 2023), offering a critical opportunity for health and social service professionals to advocate for SNAP policies, such as BBCE, that are associated with a range of improved child and family outcomes. While ultimately not enacted, the 2018 Farm Bill included restrictions to BBCE as a state policy option, and these restrictions would have resulted in loss of SNAP benefits for millions of households (Congressional Research Service, 2023). BBCE as a state policy option is currently being debated in discussions for the 2023 Farm Bill reauthorization (Bergh, 2023),46 and evidence of multiple positive outcomes associated with state adoption of BBCE policies, including reductions in poverty, food insecurity, CPS-investigated reports, foster care entries, and adult mental health and substance use disorders (Austin, Frank, et al., 2023; Austin, Shanahan, et al., 2023; Ettinger de Cuba et al., 2019; Han, 2016; Johnson-Motoyama et al., 2022; Naumann et al., under review; Tiehen et al., 2012), should be considered as part of these discussions.

4.1. Limitations and directions for future reserach

This study has limitations. First, although we adjusted our difference-in-differences analyses for several potential confounders, there may be unmeasured confounding. To examine the potential for unmeasured confounding to bias results, we conducted a falsification test using rates of deaths due to flu, pneumonia, and other acute respiratory infections as the outcome, finding no association of state expansion of SNAP eligibility under BBCE with this outcome. Second, this study was ecological, with analyses conducted at the state-level. The results are thus subject to ecological fallacy and do not provide information on associations of SNAP eligibility and enrollment with foster care entries at the individual-level. Third, we were unable to examine the association of state expansion of SNAP eligibility with foster care entries among American Indian/Alaska Native children, a racial group with disproportionately high rates of foster care placement (Yi et al., 2020), due to small numbers in many states and years. Similarly, we did not examine the association of state expansion of SNAP eligibility with foster care entries among Hispanic children given small numbers in some states and years. Fourth, our 2005–2019 study period ended before the onset of the COVID-19 pandemic. Future research is needed to examine potential associations of COVID-19-era SNAP policies, including temporary emergency allotments (i.e., additional monthly benefits for participating households) (Rosenbaum & Hall, 2023), on child and family outcomes. Future research is also needed to consider eligibility criteria across multiple programs addressing food insecurity, including SNAP, WIC, and school breakfast and lunch programs, and associations with child and family outcomes. Of note, SNAP participation automatically qualifies school-age children for free school meals (United States Department of Agriculture, 2023a) and pregnant, postpartum, and breastfeeding people, infants, and children up to age 5 years for WIC (Neuberger, 2022), limiting variation in eligibility and enrollment across programs. Last, future research is needed to understand changes in CPS policies specific to family preservation and reducing the number of children in foster care (Child Welfare Information Gateway, 2023) and whether these policies changes affect the associations observed in this study. Importantly, the Families First Prevention Services Act, a key policy change aimed at reducing the number of children in foster care, was passed in 2018 (Child Welfare Information Gateway, 2023) after most states included in the current study had already expanded SNAP eligibility under BBCE.

5. Conclusion

Given the magnitude of foster care entries in the U.S. and the increased likelihood of adverse health, social, and economic outcomes following out-of-home placement, large-scale strategies designed to reduce foster care entries are urgently needed. Results from this study provide evidence that state expansion of SNAP eligibility under BBCE is associated with decreases in rates of foster care entries. Results also indicate larger decreases in foster care entries among Black non-Hispanic children than among White non-Hispanic children, signifying that expansion of SNAP eligibility under BBCE may be one component of larger strategies to reduce racial inequities in foster care entries. Current discussions, including the 2023 Farm Bill reauthorization, provide important opportunities to ensure that impactful policy options, like expansion of SNAP eligibility under BBCE, are used by states to promote child and family health and wellbeing.

Supplementary Material

Supplement

Fig. 2.

Fig. 2.

Association of state expansion of Supplemental Nutrition Assistance Program (SNAP) eligibility under broad-based categorical eligibility with rates of foster care entries by race/ethnicity, 2005–2019.a

a. Black non-Hispanic children.

b. White non-Hispanic children.

aAnalyses included states that did not expand SNAP eligibility under broad-based categorical eligibility during 2005–2016 (AK, AR, KS, MO, SD, TN, UT, VA, WY) and states that expanded SNAP eligibility in 2008 (GA, NY), 2009 (ID, MT, NH, NV, OH, OK, PA, RI, VT, WV), 2010 (AL, CA, CT, DC, IL, KY, LA, MS, NJ, NM), and 2011 (CO, FL, HI, IA, MN, NC). Analyses adjusted for state minimum wage, refundable Earned Income Tax Credit, maximum Temporary Assistance for Needy Families benefit for a family of 3, percent population unemployed, and median household income. Outcome modeled as number of foster care entries among children ages <18 years per 1000 child population.

Note: Year 0 is the year the year states first expanded SNAP eligibility under broad-based categorical eligibility by eliminating the asset test or increasing the income limit.

Acknowledgements

The analyses presented in this publication were based on data from the Adoption and Foster Care Analysis and Reporting System (AFCARS), 2005-2019. These data were made available by the National Data Archive on Child Abuse and Neglect, Cornell University, Ithaca, NY, and have been used with permission. Data from the Adoption and Foster Care Analysis and Reporting System (AFCARS) were originally reported to the Children's Bureau. Funding for the project was provided by the Children's Bureau, Administration on Children, Youth and Families, Administration for Children and Families, U.S. Department of Health and Human Services. The receiver of the original data, the funder, the Archive, Cornell University and their agents or employees bear no responsibility for the analyses or interpretations presented here. We would like to thank the study Advisory Board for their feedback and insights into the Supplemental Nutrition Assistance Program and broad-based categorical eligibility as a state policy option.

Funding

This study was funded by an award from the Centers for Disease Control and Prevention, National Center for Injury Prevention and Control (R01CE003334). The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.chiabu.2023.106399.

Footnotes

Declaration of competing interest

None reported.

Data availability

The authors have made data on state adoption of SNAP policies available in the Supplement. The authors cannot provide access to the AFCARS data.

References

  1. American Statistical Association. (2016). Statement on statistical signfiicance and p-values. https://www.amstat.org/asa/files/pdfs/P-ValueStatement.pdf.
  2. Ashbrook A, Essel K, Montez K, & Bennett-Tejes D (2021). Screen and intervene: A toolkit for pediatricians to address food insecurity. https://frac.org/wp-content/uploads/FRAC_AAP_Toolkit_2021_032122.pdf. [Google Scholar]
  3. Austin AE, Frank M, Shanahan ME, Reyes HLM, Corbie G, & Naumann RB (2023). Association of State Supplemental Nutrition Assistance Program eligibility policies with adult mental health and suicidality. JAMA Network Open, 6(4), e238415. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Austin AE, Shanahan ME, Frank M, Naumann RB, Reyes HLM, Corbie G, & Ammerman AS (2023). Association of state expansion of Supplemental Nutrition Assistance Program eligibility with rates of child protective services–Investigated reports. JAMA Pediatrics, 177(3), 294–302. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Berger LM, & Waldfogel J (2004). Out-of-home placement of children and economic factors: An empirical analysis. Review of Economics of the Household, 2(4), 387–411. [Google Scholar]
  6. Bergh KRD (2023). House Republicans' proposals could take food away from millions of low-income individuals and families. Retrieved from https://www.cbpp.org/research/food-assistance/house-republicans-proposals-could-take-food-away-from-millions-of-low. [Google Scholar]
  7. Callaway B, & Sant’Anna PHC (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200–230. [Google Scholar]
  8. Center on Budget and Policy Priorities. (2022). A quick guide to SNAP eligibility and benefits. Retrieved from https://www.cbpp.org/research/food-assistance/a-quick-guide-to-snap-eligibility-and-benefits. [Google Scholar]
  9. Child Welfare Information Gateway. (2023). Family First Prevention Services Act. Retrieved from https://www.childwelfare.gov/topics/systemwide/laws-policies/federal/family-first/. [Google Scholar]
  10. Clemens E, & Tis M (2016). Colorado study of students in foster care. Needs assessment data 2008 to 2014. Retrieved from https://www.unco.edu/cebs/foster-care-research/needs-assessment-data/. [Google Scholar]
  11. Clemens EV, Helm HM, Myers K, Thomas C, & Tis M (2017). The voices of youth formerly in foster care: Perspectives on educational attainment gaps. Children and Youth Services Review, 79, 65–77. [Google Scholar]
  12. Congressional Research Service. (2023). Farm Bill Primer: What is the Farm Bill?. Retrieved from https://crsreports.congress.gov/product/pdf/IF/IF12047#:~:text=The%20farm%20bill%20is%20an,address%20agricultural%20and%20food%20issues.
  13. Council on Community P, Committee On N, Gitterman BA, Chilton LA, Cotton WH, Duffee JH, … Kuo AA (2015). Promoting food security for all children. Pediatrics, 136(5), e1431–e1438. [DOI] [PubMed] [Google Scholar]
  14. Dickert-Conlin S, Fitzpatrick K, Stacy B, & Tiehen L (2021). The downs and ups of the SNAP caseload: What matters? Applied Economic Perspectives and Policy, 43 (3), 1026–1050. [Google Scholar]
  15. Dworsky A, Napolitano L, & Courtney M (2013). Homelessness during the transition from foster care to adulthood. American Journal of Public Health, 103(S2), S318–S323. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Ettinger de Cuba S, Chilton M, Bovell-Ammon A, Knowles M, Coleman SM, Black MM, … Heeren TC (2019). Loss of SNAP is associated with food insecurity and poor health in working families with young children. Health Affairs, 38(5), 765–773. [DOI] [PubMed] [Google Scholar]
  17. Fong K. (2017). Child welfare involvement and contexts of poverty: The role of parental adversities, social networks, and social services. Children and Youth Services Review, 72, 5–13. [Google Scholar]
  18. Gypen L, Vanderfaeillie J, De Maeyer S, Belenger L, & Van Holen F (2017). Outcomes of children who grew up in foster care: Systematic-review. Children and Youth Services Review, 76, 74–83. [Google Scholar]
  19. Hales LC-J, & Alisha.. (2022). Food insecurity for households with children rose in 2020, disrupting decade-long decline. Retrieved from https://www.ers.usda.gov/amber-waves/2022/february/food-insecurity-for-households-with-children-rose-in-2020-disrupting-decade-long-decline/. [Google Scholar]
  20. Han J. (2016). The impact of SNAP on material hardships: Evidence from broad-based categorical eligibility expansions. Southern Economic Journal, 83(2), 464–486. [Google Scholar]
  21. Hunter AA, & Flores G (2021). Social determinants of health and child maltreatment: A systematic review. Pediatric Research, 89(2), 269–274. [DOI] [PubMed] [Google Scholar]
  22. Johnson-Motoyama M, Ginther DK, Oslund P, Jorgenson L, Chung Y, Phillips R, … Sattler PL (2022). Association between State Supplemental Nutrition Assistance Program policies, child protective services involvement, and foster care in the US, 2004-2016. JAMA Network Open, 5(7), Article e2221509. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Jones JW, Courtemanche CJ, Denteh A, Marton J, & Tchernis R (2021). Do state snap policies influence program participation among seniors? Applied Economic Perspectives and Policy, 44(2), 591–608. [Google Scholar]
  24. Kim H, Wildeman C, Jonson-Reid M, & Drake B (2017). Lifetime prevalence of investigating child maltreatment among US children. American Journal of Public Health, 107(2), 274–280. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Maguire-Jack K, Johnson-Motoyama M, & Parmenter S (2021). A scoping review of economic supports for working parents: The relationship of TANF, child care subsidy, SNAP, and EITC to child maltreatment. Aggression and Violent Behavior, 65. [Google Scholar]
  26. Naumann RB, Frank M, Shanahan ME, Reyes HLM, Ammerman AS, Corbie G, & Austin AE (2023). Association of state adoption of Supplemental Nutrition Assistance Program eligibility policies with rates of substance misuse, use disorders, and treatment need. American Journal of Preventive Medicine (under review). [Google Scholar]
  27. Neuberger ZHL (2022). WIC coordination with Medicaid and SNAP. Retrieved from https://www.cbpp.org/research/food-assistance/wic-coordination-with-medicaid-and-snap-0. [Google Scholar]
  28. Pac J, Collyer S, Berger L, O’Brien K, Parker E, Pecora P, … Wimer C (2023). The effects of child poverty reductions on child protective services involvement. Social Service Review, 97(1), 43–91. [Google Scholar]
  29. Paxson C, & Waldfogel J (2002). Work, welfare, and child maltreatment. Journal of Labor Economics, 20(3), 435–474. [Google Scholar]
  30. Paxson C, & Waldfogel J (2003). Welfare reforms, family resources, and child maltreatment. Journal of Policy Analysis and Management, 22(1), 85–113. [Google Scholar]
  31. Pinard CA, Bertmann FMW, Byker Shanks C, Schober DJ, Smith TM, Carpenter LC, & Yaroch AL (2017). What factors influence SNAP participation? Literature reflecting enrollment in food assistance programs from a social and behavioral science perspective. Journal of Hunger & Environmental Nutrition, 12(2), 151–168. [Google Scholar]
  32. Rosenbaum D. (2019). SNAP's “Broad-Based Categorical Eligibility” supports working families and those saving for the future. Retrieved from https://www.cbpp.org/research/food-assistance/snaps-broad-based-categorical-eligibility-supports-working-families-and. [Google Scholar]
  33. Rosenbaum DB, & Hall LK (2023). Temporary pandemic SNAP benefits will end in remaining 35 states in March 2023. Retrieved from https://www.cbpp.org/research/food-assistance/temporary-pandemic-snap-benefits-will-end-in-remaining-35-states-in-march. [Google Scholar]
  34. Rostad WL, Ports KA, Tang S, & Klevens J (2020). Reducing the number of children entering foster care: Effects of state earned income tax credits. Child Maltreatment, 25(4), 393–397. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Roth J, Sant’Anna PHC, Bilinski A, & Poe J (2023). What’s trending in difference-in-differences? A synthesis of the recent econometrics literature. Journal of Econometircs, 235(2), 2218–2244. [Google Scholar]
  36. Sankaran V, Church C, & Mitchell M (2018). A cure worse than the disease: The impact of removal on children and their families. Marquette Law Review, 102, 1161. [Google Scholar]
  37. Seker S, Boonmann C, Gerger H, Jäggi L, d’Huart D, Schmeck K, & Schmid M (2022). Mental disorders among adults formerly in out-of-home care: A systematic review and meta-analysis of longitudinal studies. European Child & Adolescent Psychiatry, 31(12), 1963–1982. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Tiehen L, Jolliffe D, & Gundersen C (2012). How state policies influence the efficacy of the Supplemental Nutrition Assistance Program in reducing poverty. Retrieved from https://ageconsearch.umn.edu/record/124937?ln=en. [Google Scholar]
  39. U.S. Department of Health and Human Services. (2020, June 23). The AFCARS Report. Retrieved from https://www.acf.hhs.gov/sites/default/files/documents/cb/afcarsreport27.pdf. [Google Scholar]
  40. Ullmann HW, Madans JD, & J H. (2022). Children living in households that experienced food insecurity: United States, 2019–2020. NCHS Data Brief, 432. [PubMed] [Google Scholar]
  41. United States Census Bureau. (2020). Small area income and poverty estimates. https://www.census.gov/data-tools/demo/saipe/#/?map_geoSelector=aa_c. [Google Scholar]
  42. United States Department of Agriculture. (2019). State options report. Retrieved from https://www.fns.usda.gov/snap/waivers/state-options-report. [Google Scholar]
  43. United States Department of Agriculture. (2022a). About WIC. Retrieved from https://www.fns.usda.gov/wic/about-wic. [Google Scholar]
  44. United States Department of Agriculture. (2022b). SNAP policy data sets. Retrieved from https://www.ers.usda.gov/data-products/snap-policy-data-sets/. [Google Scholar]
  45. United States Department of Agriculture. (2023a). Applying for free and reduced price school meals. Retrieved from https://www.fns.usda.gov/cn/applying-free-and-reduced-price-school-meals. [Google Scholar]
  46. United States Department of Agriculture. (2023b). Characteristics of Supplemental Nutrition Assistance Program households: Fiscal year 2020. Retrieved from https://fns-prod.azureedge.us/sites/default/files/resource-files/Characteristics2020.pdf. [Google Scholar]
  47. United States Department of Agriculture. (2023c). National School Lunch Program. Retrieved from https://www.fns.usda.gov/nslp. [Google Scholar]
  48. United States Department of Agriculture. (2023d). School Breakfast Program. Retrieved from https://www.fns.usda.gov/sbp/school-breakfast-program. [Google Scholar]
  49. University of Kentucky Center for Poverty Research. (2020). National welfare data, 1980–2018. Retrieved from https://ukcpr.org/resources/national-welfare-data. [Google Scholar]
  50. Vasileva M, & Petermann F (2018). Attachment, development, and mental health in abused and neglected preschool children in foster care: A meta-analysis. Trauma, Violence & Abuse, 19(4), 443–458. [DOI] [PubMed] [Google Scholar]
  51. Yi Y, Edwards FR, & Wildeman C (2020). Cumulative prevalence of confirmed maltreatment and foster care placement for US children by race/ethnicity, 2011–2016. American Journal of Public Health, 110(5), 704–709. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement

Data Availability Statement

The authors have made data on state adoption of SNAP policies available in the Supplement. The authors cannot provide access to the AFCARS data.

RESOURCES