State Variations in the Association between Race-Specific Poverty and Racial Disparities in Child Neglect Reports

Background: Inequitable socioeconomic conditions (e.g., poverty) have been documented as contributors to heightened rates of child neglect and the overrepresentation of racially minoritized families in the child welfare system (Drake et al., 2021). While the prevalence of both poverty and neglect reports varies greatly across geographic contexts (e.g., states) and social groups (e.g., racial/ethnic groups) (Luken et al., 2021), limited research systematically examined how these associations differ across states for each racial/ethnic group. This study explores how the associations between race-specific poverty (RSP) and racial disparities (RD) in child neglect reports vary by state.

Methods: We used two primary data sources to examine associations between RSP and RD across states. RSP data were drawn from the 2018 American Community Survey. RD was assessed based on the Disparity Index (DI) (Shaw et al., 2008) using the 2018 Child File (N=2,688,684) from the National Child Abuse and Neglect Data System. Correlation analyses examined the relationships between poverty rates and DI values for six racial/ethnic groups compared to White children: 1) Asian, 2) Black, 3) Latinx, 4) multiracial, 5) Native American/Alaskan Native (NAAN), and 6) Native Hawaiian/Pacific Islander (NHPI). Next, geo-mapping techniques (Brewer & Pickle, 2002) were used to visualize variations across 49 states.

Results: At the national level, NAAN children had the highest poverty rates (23.3%), followed by Black (22.9%), Latinx (20.0%), NHPI (19.0%), multiracial (17.8%), and Asian (11.8%) children. Analysis of racial/ethnic disparities showed that Black children had the highest overrepresentation (DI=2.00) in neglect cases, followed by NAAN (DI=1.80), NHPI (DI=1.54), multiracial (DI=1.31), Latinx (DI=0.90), and Asian (DI=0.20) children. NAAN children ranked first in poverty and second in overrepresentation, while Black children ranked second in poverty and first in overrepresentation. Notably, disaggregated analysis of Asian and NHPI children—often combined in previous research—revealed that NHPI children had the third highest DI and were overrepresented in 28 states. Correlation results showed a significant association between poverty and DI only among NAAN children (r=0.336; p< 0.05). Additionally, analyses of geo-mapping showed substantial variations in RD-RSP patterns across states. While RSP and RD levels were mismatched in most states (e.g., low RSP with overrepresentation), they aligned in several states where both were high (e.g., Michigan, Wisconsin).

Conclusions/Implications: Findings have key implications for policies aimed at preventing child neglect. First, universal, nationwide prevention approaches may be insufficient, given the substantial variation in neglect disparities across racial/ethnic groups and states. This highlights the need for context-specific intervention strategies at the state or local level. Second, the distinct outcomes for Asian and NHPI children when analyzed separately underscore the necessity of disaggregated data in developing equitable interventions. Lastly, although poverty was significantly associated with disparities only among NAAN children in this study, the broader link between poverty and neglect remains evident. Research (Kovski, 2021) on macro-level policies providing family support (e.g., Earned Income Tax Credit) has shown declines in neglect reports, underscoring the importance of socioeconomic supports in child neglect prevention.