156620 Violent death data viewed by municipal socio-economic groupings

Monday, November 5, 2007

Kevin T. Borrup, JD, MPA , Injury Prevention Center, Connecticut Children's Medical Center, Hartford, CT
Garry Lapidus, PA-C MPH , Injury Prevention Center, Connecticut Children's Medical Center, Hartford, CT
Nicole Peretto , Injury Prevention Center, Connecticut Children's Medical Center, Hartford, CT
Objective: Using a system of municipal classification by socio-economic status, violent deaths in the State of Connecticut were charted for years 2001-2004, revealing a more accurate picture of homicide in the most in need communities.

Methods: Of the 1432 deaths charted by socio-economic status, there were 395 homicide deaths and 1037 suicide deaths from 2001-2004 in Connecticut. Connecticut utilizes a system of categorization that identifies school districts by socio-economic status. The nine classifications from “A” to “I” make up socio-economic groupings (SEGs) with SEG I containing the poorest and highest need districts, including Connecticut's five biggest cities.

Results: SEGs A to H have homicide rates ranging from .3, for SEG B, to 2.6, for SEG H. The homicide rate for SEG I, at 9.6, is more than three times the homicide rate of the SEG H which at 2.6 is the second highest homicide rate after SEG I. The homicide rate in SEG I at 9.6 is higher than Connecticut's average annual suicide rate of 7.6. By contrast the suicide rate in SEG I at 7.6 is equal to the state average rate for suicide.

Conclusion: While suicide deaths are a public health concern, it is clear from the use of SEGs that homicide is a greater public health concern than suicide for the poorest and most in need communities. Other geographic models solely using urbanization measures are less accurate in describing communities and fail to take into account important socioeconomic factors leading to an understatement of urban homicide rates.

Learning Objectives:
1. Recognize the benefits of viewing mortality data by municipaity-specific socio-economic groupings. 2. Assess the power of socio-economic groupings in explaining the variance of homicide rates. 3. Discuss the utility of Connecticut's socio-economic grouping system.

Keywords: Data/Surveillance, Homicide

Presenting author's disclosure statement:

Any relevant financial relationships? No
Any institutionally-contracted trials related to this submission?

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.