This project has two research aims.
Aim 1 aimed to investigate the associations between community conditions and Child Maltreatment Report (CMR) rates. Specifically, Aim 1 addressed the following research questions (RQs):
RQ1. Examining whether there was a relationship between food insecurity rates and CMR rates among US counties from 2009 to 2018.
RQ2. Investigating whether child poverty rates were associated with CMR rates among US counties from 2009 to 2018 and whether the strength of this relationship underwent changes over this period.
RQ3. Analyzing whether opioid prescription rates were linked to CMR rates among US counties from 2009 to 2018 and whether the strength of this relationship changed over this period.
RQ4. Exploring whether rates of mental distress, mental health professionals, physical distress, and physical health professionals were correlated with CMR rates among US counties from 2014 to 2017.
RQ5. Investigating whether home visiting services were related to CMR rates among US counties from 2016 to 2018.
RQ6. Examining whether percentages of Latino residents, percentages of foreign-born residents, and Immigration and Customs Enforcement (ICE) arrest rates were related to CMR rates among US counties from 2015 to 2018 and whether these relationships changed over this period.
RQ7. Analyzing whether food insecurity rates were associated with CMR rates among Illinois zip codes from 2011 to 2018.
RQ8. Investigating whether home visiting services were related to CMR rates among Illinois zip codes from 2011 to 2018.
RQ9. Examining whether child care availability was associated with CMR rates among Illinois zip codes from 2011 to 2018.
These relationships were explored across overall CMR rates, encompassing all children, as well as within specific subgroups based on race/ethnicity (e.g., CMR rates among Black children), sex (e.g., CMR rates among female children), age (e.g., CMR rates among children aged 0-5 years), and maltreatment type (e.g., neglect report rates). To address the first six questions, this project compiled national longitudinal data covering the period from 2009 to 2018 and employed a multilevel approach at the county/state level by integrating data from various national databases. The last three questions were tackled by assembling Illinois zip code-level longitudinal data spanning from 2011 to 2018, connecting multiple statewide databases in Illinois. The examination period for some questions, such as home visiting, was shorter than others due to constraints in data availability for the independent variable. The outcomes of Aim 1 investigations resulted in eight published peer-reviewed journal articles and one working paper.
Aim 2 centered on reviewing existing literature to uncover the impact of policies on community conditions and predict changes in CMR rates resulting from alterations in these policies. In particular, this investigation concentrated on community poverty and policies designed to alleviate child poverty, given that poverty has consistently been recognized as one of the strongest risk factors for occurrences and reporting of child maltreatment. Building on the recent comprehensive study report from the National Academies of Sciences, which presented policy packages targeting a 50% reduction in child poverty over the next decade,85 this investigation centered on six crucial policies: Earned Income Tax Credit (EITC), Child and Dependent Care Tax Credit (CDCTC), Child Tax Credit (CTC), child allowance, Supplemental Nutrition Assistance Program (SNAP), and housing voucher. This study sought to promptly offer preliminary estimates for the potential impact of alterations in these policies on CMR rates, with mediation through community child poverty rates. In other words, this study investigated whether a reduction in child poverty rates resulting from a policy change would subsequently lead to a decrease in CMR rates. This study focused on evaluating the impact of policy adjustments, prioritizing the influence of policy changes over the mere existence of policies, in order to provide insights for the improvement of existing policies.
