This study seeks to improve our understanding of neighborhood contextual effects on child maltreatment reports (CMR).
Methods:
This study used secondary data from a longitudinal study based in St. Louis City/County. We used two separate samples. The CAN sample included all children aged ≤3 with a first-time CMR in 1993-1994 (n = 2,111). The AFDC sample included randomly selected children aged ≤3 receiving AFDC in 1993-1994 with no CMR (n = 1,923). We followed up these children from 1995 through 2009 in secondary data including various Missouri administrative records. To trace changes of residential neighborhoods through welfare (AFDC/TANF) records, we selected age-year observations on welfare. This allowed us to correctly measure “current” neighborhood characteristics at any given age. This also fixed family-level economic conditions to a low level, allowing us to examine neighborhood contextual effects independent from family-level economic conditions. We used multilevel growth curve models to estimate the CMR likelihood at each age from 1 to 16 as a function of various risk/protective factors.
Results:
During follow-up, about 90% families moved at least once. While considering residential moves and other variables, no neighborhood characteristics (i.e., poverty rate, mobility rate, child/adult ratio, and moving out of St. Louis) were found to be significant in the CAN sample. Yet, several were significant in the AFDC sample. Each 10-percentage-point increase in neighborhood poverty increased the CMR likelihood by 31% (OR=1.31, 95% CI=1.05-1.64) for Whites. This relationship was not significant for Blacks (1.01, 0.92-1.10). Neighborhood child/adult ratio (1 unit=0.1) decreased the CMR likelihood by 10% (0.90, 0.82-0.99). Making a long-distance move (i.e., moving out of St. Louis) increased the CMR likelihood by 63% (1.63, 1.07-2.48).
Conclusions/Implications:
Among children experiencing CMR in early childhood (CAN sample), neighborhood contexts appear to have no contribution to CMR recurrence. Among children who merely received welfare with no CMR in early childhood (the AFDC sample), neighborhood poverty increased the risk of CMR for Whites, while the risk did not vary by neighborhood poverty for Blacks. Although this interaction between race and neighborhood poverty is theoretically interesting, the practice importance seems to be small as only a few Whites reside in high-poverty neighborhoods and are subject to this interaction. The negative association between neighborhood child/adult ratio and CMR in the AFDC sample are surprising and inconsistent with some prior studies. Both family-level and neighborhood-level mobility were found to have no meaningful contribution to CMR in both samples. Although long-distance mobility (i.e., moving out of St. Louis) increases the risk, the overall impact is small as low-SES families mostly make short-distance moves. This study highlights the importance of tracing residential neighborhoods in a longitudinal study. While doing so, we identify some neighborhood effects. These effects, however, are small in contribution to the overall risk and are less observable among more vulnerable children. The current findings have limited generalizability to low-risk families, which may explain some inconsistencies with prior studies. Nevertheless, the current findings may be practically and theoretically important as they have strong external validity for high-risk populations.