Social Ecological Factors as Predictors of Sexual Crimes

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Predicting crime trends via individual and community level-factors associated with crime is common across criminology, public health, and psychology. From social disorganization theory, crime rates are linked to neighborhood ecological characteristics that may shape the occurrence of illegal activities. Expanding this view, Shaw and McKay (1969) and Sampson (1993) emphasized the role of appropriate parental supervision and stable familial homes in reducing crime. Bursik and Grasmick (1993) further highlighted the influence of structural factors such as poverty and divorce.

Social disorganization theory includes a discussion of systems within the social ecological model, three of which will be discussed. The micro system (immediate environment) involves factors like family. The mesosystem is where microsystems link, such as between family and community. Lastly, the exosystem (indirect environment) captures larger structures (e.g., economic influences) which help create the built environment comprised of the neighborhood and social services. These levels overlap and may provide information related to specific factors predictive of crime.

Health-related quality of life (HRQOL) is a multi-dimensional concept that encapsulates physical, mental, emotional, and social functioning and has been used for risk factor identification (Yin, Njai, Barker, Siegel, & Liao, 2016). In the social ecological model, HRQOL exists in the micro (e.g., child abuse, intimate partner violence), meso (e.g., prenatal care), and exosystems (e.g., neighborhood poverty). For example, a host of research has discussed the contribution of neighborhood disadvantages to increased intimate partner violence rates (Miller-Graff & Graham Bermann, 2014), while other studies have found economic disadvantage and violent crime to negatively impact birthweight (Masi, Hawkley, Piotrowski, & Pickett, 2007).

Although these factors, along with others like drug use and various health factors, have been linked to violent crime, the exploration of social ecological predictors for sexual crimes has been comparatively neglected. In a systematic review of risk factors for sexual crime perpetration, Tharp and colleagues (2014) examined 191 empirical studies and identified two societal and community factors (gender-based factors like female education level and environmental factors like homicide rates), 23 relationship factors, and 42 individual-level risk factors for sexual crime perpetration.

To attain a better understanding of the potential range of predictors of sexual crime, the current study will utilize data extracted from two publicly available data bases. The first is the Tennessee Bureau of Investigations (TBI) database, which includes crime statistics for each of the 95 counties in Tennessee. Reported number of crimes against persons in 2018 will be examined in the current analysis with variables categorized as either sexual (n=7 offense categories) or violent, non-sexual (n=11 offense categories) crimes. Violent non-sexual crimes will be collapsed into one variable to serve as the comparison group. The second data base, County Health Rankings and Roadmaps, provides data on health factors contributing to quality of life. For all Tennessee counties, 11 community variables will be included. These factors were selected because they reach across the social ecological levels of micro (e.g., single-parent households, teen births, low birthweight), meso (e.g., substance use factors, health factors including mortality and insurance), and exosystems (e.g., children in poverty, disconnected youth). A multinomial logistical regression will be conducted to investigate whether specific community level factors predict the rate of sexual crime beyond the prediction of violent, non-sexual crime. The overall model significance will be examined by the collective effect of the community level predictors.

A key factor in promoting community safety while simultaneously preventing sexual violence involves comprehensive strategies that stretch the range of social ecology. Less is known about predictors of sexual violence than those of other crimes. Further, more research has examined individual-level factors related to sexual crime perpetration. A more nuanced understanding of predictors of sexual violence at social ecological levels can assist in the development of more comprehensive prevention and intervention programs that target multiple levels of risk.


San Antonio, TX

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