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. 2020 Jun:104:104467.
doi: 10.1016/j.chiabu.2020.104467. Epub 2020 Apr 1.

Longitudinal Understanding of Child Maltreatment Report Risks

Hyunil Kim  1 , Brett Drake  2 , Melissa Jonson-Reid  2
Affiliations

Longitudinal Understanding of Child Maltreatment Report Risks

Hyunil Kim et al. Child Abuse Negl. 2020 Jun.

Abstract

Background: Child maltreatment reports (CMR) are both common and strongly associated with various negative outcomes.

Objective: To examine CMR risks by child age, early childhood context, current/cumulative economic status (welfare receipt), race, and other risk factors with a longitudinal dataset.

Participants and setting: The CAN sample included 2,111 children having a CMR ≤ age 3, suggestive of a harmful early childhood context. The AFDC sample included 1,923 children having AFDC but no CMR ≤ age 3, suggestive of early childhood protective factors despite poverty.

Methods: We estimated the CMR likelihood at each age from 1-17 years based on various risk factors while following up children from 1995-2009.

Results: During follow-up, CMR likelihoods were substantially higher for the CAN sample than for the AFDC sample. The age-CMR relationship was strongly negative for the CAN sample (OR = 0.87, 95% CI = 0.86-0.88). This relationship was weaker for the AFDC sample (OR = 0.92, 0.89-0.95) and became non-significant for children who exited welfare. Current welfare receipt remained a strong predictor of CMR likelihoods for both CAN (OR = 2.32, 1.98-2.71) and AFDC (OR = 2.08, 1.61-2.68) samples. Prior welfare receipt moderately increased CMR likelihoods among those not currently on welfare. Controlling for other risk factors, White children had the highest likelihood of CMR. Other child and parent level vulnerabilities also increased CMR risk over time.

Conclusions: This study highlights the importance of longitudinal analytic approaches and the utility of cross-sector administrative data in improving our ability to understand and predict CMRs over time.

Keywords: Administrative data analysis; Child abuse; Child maltreatment; Child protective services; Multilevel growth curve model.

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Conflict of interest statement

Declaration of Competing Interest None.

Figures

Figure 1.
Figure 1.. Estimated child maltreatment report likelihoods by child age, current welfare and prior welfare.
Note: Estimates are based on the final models in Table 2. All other variables are fixed to their grand mean. The “Current welfare=yes, Prior welfare=75%” and “Current welfare=yes, Prior welfare=25%” lines for the CAN sample are overlapped since the effect size of prior welfare is practically 0 when currently on welfare.
Figure 2.
Figure 2.. Estimated child maltreatment report likelihoods by child age, current welfare and child race.
Note: Estimates are based on the final models in Table 2. All other variables are fixed to their grand mean. White = non-Hispanic/Latino White only. Black = non-Hispanic/Latino Black only. Other = other minority including Asian, Hispanic/Latino, and other minorities.
See this image and copyright information in PMC

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