• Jared W Parrish, Julia M Fleckman, John J Prindle, Andrea L Eastman, and Lindsey E G Weil.
• Division of Public Health, Department of Health and Social Services, State of Alaska, Anchorage, Alaska.
• Am J Prev Med. 2020 Apr 1; 58 (4): e133e140e133-e140.

IntroductionMeasuring and comparing the incidence of child maltreatment is challenging. Linkage of statewide birth cohorts with Child Protective Services reports to study incident child maltreatment over the life course are becoming more common. This study compares the reported incidence between 2 states derived from population-based administrative data linkages.MethodsLinked births (2009-2011) with Child Protective Services records (2009-2015) and deaths in each state were used to compare the cumulative incidence of a Child Protective Services report before age 7 years. Given differences in population race structure and documented disparities of race groups in Child Protective Services data, variation was adjusted for using direct standardization. Unadjusted cumulative incidence, race cumulative incidence, and race-adjusted cumulative incidence were compared. Analyses were completed in 2018.ResultsBefore age 7 years, 26.0% of Alaskan children and 19.0% of Californian children were reported to Child Protective Services (RR=1.37, p<0.001). Aside from Asian/Pacific Islanders, the cumulative incidence between states was similar for each race. The race-adjusted cumulative incidence indicated that children born in Alaska were 1.10 times as likely to experience a report before age 7 years compared with children in California.ConclusionsMuch of the difference in risk for child maltreatment observed between Alaska and California is most likely due to variation in the population structure by race as opposed to modifiable factors. Standardization is a simple method to adjust for population structure differences. This study contributes to the growing body of knowledge regarding the use of linked administrative data to study maltreatment and provides insights into considerations for making comparisons or conducting cross-jurisdictional analyses based on commonly aligned data sets.Copyright © 2020 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

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