What does the USDA Characteristics report show about SNAP participants by race and age for fiscal years 2015–2023?
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Executive summary
The USDA Characteristics report (FY2023) shows that SNAP participants are racially and age-wise diverse: in FY2023 the largest racial group was White (about 35%), with substantial shares of Black (about 26%) and Hispanic (about 16%) participants and a sizable “race unknown” category (about 17%) [1] [2]. By age, FY2023 participants were roughly 39% children, 42% adults age 18–59, and 19% adults age 60 and older, and the report includes an age series covering FY2017–2023 [3] [4].
1. What the FY2023 report explicitly reports on race
The USDA’s FY2023 Characteristics report and contemporaneous summaries show the racial composition of SNAP participants in 2023 as White ~35.4%, Black/African American ~25.7%, Hispanic/Latino ~15.6%, Asian ~3.9%, Native American ~1.3%, multiracial ~1%, with roughly 17% of participants recorded as “race unknown,” a caveat that affects interpretation and cross‑year comparability [1] [2]. Advocacy coverage of the report stresses that SNAP serves people across races and that headline percentages can be misconstrued on social media, a point reinforced by fact‑checks noting viral charts that mislead about race and citizenship [2] [1].
2. What the report shows about age in FY2023 and the recent trend window
USDA data for FY2023 place children under 18 at about 39% of participants, adults 18–59 at about 42%, and adults 60+ at about 19%, and the published report contains an age‑group series spanning FY2017–2023 that lets analysts track modest shifts over that seven‑year window [3] [4]. The report also documents that most SNAP households (79%) include either a child, an elderly person, or a nonelderly person with a disability, and those households account for 88% of participants and receive the bulk of benefits, which highlights how the program concentrates resources toward vulnerable age groups [5].
3. What the series (FY2017–2023) enables — and its limits
The FY2017–2023 age series in the report allows inspection of how the caseload’s age composition moved through the pandemic and recovery years, but the public summary materials and linked charts emphasize FY2023 point estimates [4] [3]. For race, readily available reporting and fact‑checks focus on the FY2023 snapshot; the assembled sources do not provide a full, consistent year‑by‑year racial time series from FY2015 through FY2023 in the excerpts provided here, so precise annual racial trend lines between 2015 and 2022 cannot be asserted from these documents alone [4] [1]. Where “race unknown” is large (≈17%), that missingness complicates trend interpretation [1] [2].
4. Context, interpretation, and competing narratives
USDA and researchers frame SNAP as a means‑tested, countercyclical program that serves a cross‑section of low‑income households and concentrates benefits on households with children, older adults, and people with disabilities [6] [5]. Advocacy groups use the report to rebut stigmatizing narratives and to highlight the program’s role in reducing hunger [2]. Conversely, viral social‑media graphics and some political rhetoric have attempted to recast participation as dominated by non‑white or non‑citizen groups; fact‑checkers and the USDA data point to different conclusions and emphasize the importance of administrative definitions (citizenship is not directly equated with race in the QC data) and the sizable “race unknown” category [1] [2].
5. Bottom line and data caveats
The USDA FY2023 Characteristics report shows that SNAP in 2023 served a racially diverse caseload with Whites the largest single racial group but with sizeable Black and Hispanic shares, and that children and working‑age adults together constituted the majority of participants while older adults made up about one‑fifth [1] [3] [5]. The report’s multi‑year age charts cover FY2017–2023 and support trend analysis for age groups, but the sources provided here do not include a complete, year‑by‑year racial series back to FY2015, and the presence of a large “race unknown” category limits precision when comparing races across years [4] [1].