Recipients of PSC Small Grant Awards

The Effects of Community-Level Violence on Individual-Level Violent Experiences

Yasamin Kusunoki, Jennifer S. Barber, Justin Heinze, Marc Zimmerman, Tom Reischl

Yasamin Kusunoki, Jennifer Barber, Justin Henize, Marc Zimmerman, Tom Reichl

Our overarching goal for this pilot project is to solidify a preliminary collaboration between current Population Studies Center faculty (Yasamin Kusunoki and Jennifer Barber) and the School of Public Health/Michigan Youth Violence Prevention Center (Justin Heinze, Marc Zimmerman, and Tom Reischl). We have three specific aims for this pilot project, which will form the basis for an NICHD R01 proposal.

1) Merge Crime Incident Data (CID) with the Relationship Dynamics and Social Life (RDSL) individual-level dataset.

This dataset is exported from the City of Flint Police Department records, and researchers at the Prevention Research Center of Michigan (PRC/MI), funded by the CDC, have exclusive access to it. The CID includes date, time, and location (geocode) of crimes. All RDSL respondents’ live within Genesee County, and their residential location has been geocoded for each weekly observation in the dataset. Merging these datasets will result in a variable indicating presence/absence of each type of crime (or combinations), and distance to the crime, for each day each respondent was in the RDSL study.

2) Identify the crimes in the CID that were committed by intimate partners and/or family members.

The CID data include the relationship between the suspect and the victim. There are 35 categories, ranging from spouse, common-law spouse, parent, sibling, child, ex-spouse, child, employer, formerly dating, stranger, “otherwise known to victim,” etc. For example, in 2009, the most common code for the suspect was acquaintance (26%) followed by “otherwise known” (12%), boyfriend/girlfriend (10%), formerly dating (8%), cohabiting partner (5%), spouse (4.1%), and a variety of other, less frequent categories. Thus, more than 25% of the crimes were committed by current or prior intimate partners.

3) Estimate models of how proximity to violence – particularly intimate partner violence – is related to individual experiences with violence.

Proximity to violence is likely to affect many outcomes measured in the RDSL dataset, including violence, but also other aspects of intimate relationships, sexual behavior, contraceptive use, pregnancy, and attitudes related to pregnancy. Understanding the effect of community violence on individual behavior requires detailed dynamic measures of behavior that can be linked to time- and location-specific measures of community violence. Merging the RDSL dataset with the CID presents a unique opportunity to explore this multilevel relationship. (We explicate our specific hypotheses about these effects below.)

4) Write an R01 proposal to use the newly merged data to study the influence of proximity to violence on intimate relationships, sexual behavior, contraceptive use, and pregnancy.

Funding: PSC Pilot Funds

Funding Period: 12/1/2014 to 11/30/2015