NCMJ vol. 82, no. 4 ncmedicaljournal.com ORIGINAL ARTICLE 229 N early 69,000 North Carolina children were identi- fied as experiencing maltreatment in the 2018 fiscal year, a decline of only 12% since peaking in 2012 [1, 2]. Over 19,000 families consequently received services or were rec- ommended for treatment [1]. Children who experience mal- treatment are at increased risk for poor outcomes including increased substance abuse, lower educational performance, increased mental health diagnoses such as post-traumatic stress disorder (PTSD) and depression, and further trauma such as domestic violence [3, 4]. Interventions to prevent child maltreatment can target a range of risk factors [5, 6] at the child, parent or family, and neighborhood or county level [7]. Child-level risk factors include those such as child demographics, school attendance, and medical insurance coverage [8]. Parent and family fac- tors include parent mental health; family structure, such as single-parent households; and substance misuse [9-11]. For example, foster care entry rates have significantly increased in states where high levels of parental opioid misuse are observed [12]. Neighborhood factors include economic distress indicators, such as unemployment and household income, housing and food insecurity, and rurality [8, 13]. Local decision makers have more data available than ever but fewer resources to allocate to maltreatment prevention. Policy makers are accustomed to examining single indica- tors, such as child poverty, to understand the relative risk of one county compared to the state average. However, how do policy makers make meaning of information from dozens of variables? They could benefit from guidance on translating multiple risk factors into intervention priorities [14]. While previous studies have primarily looked at how sin- gular risk factors relate to child maltreatment through fam- ily or child-level data, gaps remain in our understanding of how multiple factors concurrently relate at more aggregate levels, such as the county level. This gap limits risk moni- toring at the county level, where intervention often occurs [15]. The ecological theory of child development posits that understanding maltreatment risk requires a holistic view- point, acknowledging how risk factors interrelate [16]. In other words, looking at singular risk factors may not provide the full story. Recent studies determined that county-level data is not only readily and routinely accessible to decision makers, but can be a useful indicator of individual risk and support policy makers when determining how to prioritize resource allocation [17-19]. Indeed, these studies suggest that models of county-level or similar geographic levels of risk are robust. Methodological choices have impacted the gap in under- standing of how risk factors interrelate. Previous studies to understand the influence of risk and protective factors at the Exploring Clusters of Risk and Association With Child Maltreatment in North Carolina Counties Gracelyn Cruden, C. Hendricks Brown, Paul Lanier, Adam Zolotor, Leah Frerichs, Kristen Hassmiller Lich background Decision makers face challenges in estimating local risk for child maltreatment and how best to prioritize which factors to intervene upon. methods Using US Census and survey data for all US counties (N = 3141), we derived US county profiles characterized by the severity of child maltreatment risk factors observed at the county level, such as parental health, health care access, and economic distress. We estimated how five child maltreatment outcomes would vary across the profiles for North Carolina counties (n = 100): total maltreatment reports (including unsubstantiated and substantiated), substantiated neglect, substantiated abuse, whether services were received, and reported child’s race/ethnicity. results We derived three profiles of county-level child maltreatment risk: high, moderate, and low risk, denoting that predicted risk factors means within profiles were all high, moderate, or low levels compared to counties in other profiles. One risk factor did not follow this pat- tern: the drug overdose death rate. It was highest in the moderate-risk profile instead of the high-risk profile, as would have been consistent with other factor levels. Moderate-risk counties had the highest predicted rate of child maltreatment reports, with over 20 more reports per 10,000 residents compared to low-risk counties (95% CI, 1.38, 38.86). limitations We included only factors for which aggregate, county-level estimates were available, thus limiting inclusion of all relevant factors. conclusions Results suggest the need for increased family-based services and interventions that reduce risk factors such as economic distress and drug overdose deaths. We discuss the implications for tailoring county efforts to prevent child maltreatment. Electronically published July 6, 2021. Address correspondence to Gracelyn Cruden, 10 Shelton McMurphey Blvd, Eugene, OR 97401 (gracelync@oslc.org). N C Med J. 2021;82(4):229-236. ©2021 by the North Carolina Institute of Medicine and The Duke Endowment. All rights reserved. 0029-2559/2021/82401