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Injury and Mortality Among Children Identified as at High Risk of Maltreatment
Rhema Vaithianathan1,2, Bénédicte Rouland3,4, Emily Putnam-Hornstein5,6
1Centre for Social Data Analytics, Auckland University of Technology, Auckland, New Zealand.
Insights
Predictive models for child maltreatment risk also identify children at higher risk of injury and mortality. Early identification can help connect vulnerable families with essential support services.
Area of Science:
- Child welfare
- Pediatric health
- Public health
Background:
- Predictive risk modeling is increasingly used in child protective services.
- Identifying children at high risk of maltreatment is crucial for early intervention.
- Existing models focus on maltreatment substantiation, but their link to injury and mortality is less understood.
Purpose of the Study:
- To assess if children identified as high-risk for maltreatment by a predictive model face elevated risks of injury and mortality in early childhood.
Main Methods:
- A predictive model for maltreatment risk was developed using New Zealand birth data from 2010.
- The model's risk scores were applied to the 2011 birth cohort.
- Children in the top 10% (very high risk) and top 20% (high risk) were compared to the general cohort for injury and mortality rates.
Main Results:
- Children in the top 10% and 20% risk groups exhibited significantly higher postneonatal mortality rates (4.8x and 4.2x greater, respectively).
- These high-risk groups also showed a substantially increased relative risk of hospitalization (2x and 1.8x higher, respectively).
Conclusions:
- Predictive models for child protective services substantiation can effectively identify children at heightened risk of injury and mortality.
- Deploying these models at birth could enable healthcare providers to offer targeted support to at-risk families.
Objectives:
To determine if children identified by a predictive risk model as at "high risk" of maltreatment are also at elevated risk of injury and mortality in early childhood.
Methods:
We built a model that predicted a child's risk of a substantiated finding of maltreatment by child protective services for children born in New Zealand in 2010. We assigned risk scores to the 2011 birth cohort, and flagged children as "very high risk" if they were in the top 10% of the score distribution for maltreatment. We also set a less conservative threshold for defining "high risk" and examined children in the top 20%. We then compared the incidence of injury and mortality rates between very high-risk and high-risk children and the remainder of the birth cohort.
Results:
Children flagged at both 10% and 20% risk thresholds had much higher postneonatal mortality rates than other children (4.8 times and 4.2 times greater, respectively), as well as a greater relative risk of hospitalization (2 times higher and 1.8 times higher, respectively).
Conclusions:
Models that predict risk of maltreatment as defined by child protective services substantiation also identify children who are at heightened risk of injury and mortality outcomes. If deployed at birth, these models could help medical providers identify children in families who would benefit from more intensive supports.
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