III. STATEMENT OF SPECIFIC AIMS
This project examines the association between changes in monthly and quarterly unemployment levels and the risk of homicide within the NVDRS reporting region from 2003-2009. We examine the association between unemployment and homicide in the general population, as well as the association with homicide that occurs at work.
Homicide data were obtained for sixteen states (AK, CO, GA, KY, MA, MD, NC, NJ, NM, OK, OR, RI, SC, UT, VA, WI) from the National Violent Death
Reporting System (NVDRS) for the years 2003-2009. County-level unemployment levels were obtained from the Bureau of Labor Statistics (BLS) and were used as the main exposure variable in the analyses. We examined the association between changes in county-level unemployment level and homicides outside of the workplace that occurred among adult non-institutionalized men and women residing in the sixteen NVDRS states over period of 2003-2009 (Aim 1). We also examined the association between county-level unemployment level and rates of homicide
occurring to employees within workplaces in the 16 NVDRS states from 2003-2009 (Aim 2). Covariates, including victim-level demographic variables, such as age, sex, race/ethnicity, and community-level measures such as median household income
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population density, and poverty within county populations were gathered from the U.S. Census Bureau, BLS, and from victim records within the NVDRS.
The project addresses the following specific aims:
Aim 1: Examine the association between monthly change in county-level unemployment levels and change in homicide rates.
This was done using the NVDRS data for all individual homicide victims, US Census population estimates, and BLS unemployment information to examine the relationship between homicide rates (per 100,000 population) and changes in unemployment among people residing in the states covered by the NVDRS during the period 2003-2009.This analysis was performed using the entire NVDRS victim population, regardless of whether or not the homicide act occurred within or outside of the workplace.
We use Poisson regression to calculate homicide rates and stratified by whether or not the individual killed was at work. Homicide rates were compared using the rate ratio effect measure. Homicide rates were compared among racial and ethnic groups, between sexes, among age groups, across states and years, and among community-level median household income and population density.
We hypothesized that an increase in the unemployment level over a 1-month (or 3-month) period would result in an increase in the homicide rate. We further hypothesized that the changes in the unemployment level will affect some racial,
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age, and population groups differently. We explored effect modification by population density, as has been the case in other studies (55, 57, 134-136).
Aim 2: Estimate the association between unemployment change and homicide at the workplace level
A case-crossover analysis was conducted to investigate whether homicide risk was influenced by change in the county unemployment.
In the case-crossover design control periods are selected at different points in time within a referent window. This is a method for studying the effects of transient exposures on acute events; in this research, it was applied to the study of
unemployment change on workplace homicide (149).
Control periods were defined as time periods close in time to a case event and were used in examining the unemployment change-workplace homicide
association. Time-invariant covariates such as victim-level age, race, and sex, are assumed to be constant within each risk because of the length of the period of observation; therefore, they do not have a confounding effect within their given risk set so far as this assumption is held.
We hypothesized that an increase in the odds of workplace homicide will occur for every 1.0% increase in 1-month unemployment. We further hypothesized that population density will modify the effect of this 1-month unemployment change.
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Aim 3: Assess effect modification of the odds ratio for the unemployment- homicide association among potentially time-varying victim- and county-level covariates for homicide in the workplace.
For this aim, we assessed effect modification by county-level population density and median household income and heterogeneity of the unemployment- homicide association within victim subgroups and event types. Models were compared using the same conditional logistic regression methods that were employed in Aim 2 and the same covariates that were used in Aims 1 and 2. However, this research aim also compared odds ratios among workplace homicide types.
The information we gain through this aim informs as to whether or not there is any exacerbation of the odds ratio due to the presence of one or more county-level effect modifiers and if there is a difference in the unemployment change-workplace homicide association among population subgroups and event types. We hypothesize that there will be modification due to county-level population density. We further hypothesize that the unemployment change-workplace homicide association will differ among workplace homicide types, specifically as it pertains to Type 1 workplace violence. This hypothesis is based on the correlation between
unemployment and crime in the general population. Our expectation is that the odds of experiencing a workplace homicide event will be higher among workplaces that are located within areas that may have experienced exceptionally high rates of unemployment change during the study period.
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Chapter 4: Methods