Murder-suicide occupies a distinct epidemiological domain that overlaps with suicide, domestic homicide, and mass murder. These events may be categorized into one of only several phenomenologic typologies that share similar demographics, motivations, and circumstances. Despite the disruption of families and communities caused by murder-suicide, there are no standardized operational definitions, validated taxonomic systems, or national surveillance networks for these events, all of which are needed to develop prevention strategies.

These data suggest that interventions to prevent accidental overdose mortality should address the use of drugs such as heroin, cocaine and alcohol in combination.

Accidental drug overdose is a substantial cause of mortality for drug users. Neighborhood-level factors, such as income distribution, may be important determinants of overdose death independent of individual-level factors. We used data from the Office of the Chief Medical Examiner to identify all cases of accidental deaths in New York City (NYC) in 1996 and individual-level covariates. We used 1990 US Census data to calculate the neighborhood-level income distribution. This multi-level case-control study included 725 accidental overdose deaths (cases) and 453 accidental deaths due to other causes (controls) in 59 neighborhoods in NYC. Overdose deaths were more likely in neighborhoods with higher levels of drug use and with more unequal income distribution. In multi-level models, income maldistribution was significantly associated with risk of overdose independent of individual-level variables (age, race, and sex) and neighborhood-level variables (income, drug use, and racial composition). The odds of death due to drug overdose were 1.63-1.88 in neighborhoods in the least equitable decile compared with neighborhoods in the most equitable decile. Disinvestment in social and economic resources in unequal neighborhoods may explain this association. Public health interventions related to overdose risk should pay particular attention to highly unequal neighborhoods.

This paper presents an analysis of the relationship between levels of economic inequality and homicide rates for a sample of 26 neighborhoods in Manhattan, New York. It argues that neighborhoods are more appropriate units of analysis for studying inequality and homicide than are larger political and statistical units because neighborhoods are more likely to constitute meaningful frames of reference for social comparisons. The principle hypothesis is that a high degree of economic inequality in a neighborhood will give rise to high levels of relative deprivation and high rates of homicide. The results of a series of multiple regression analyses fail to support this hypothesis. The measure of economic inequality is weakly associated with the observed homicide rates. Similarly, the racial composition of Manhattan neighborhoods exhibits no significant association with levels of homicide, given statistical controls for other sociodemographic variables. Two neighborhood characteristics do emerge as significant predictors of homicide rates: the relative size of the poverty population and the percent divorced or separated. Homicide rates tend to be highest in those neighborhoods characterized by extreme poverty and pervasive marital dissolution.