Neighborhood context and the causes and consequences of street use

Life course (LC) theories posit that the probability of criminological outcomes such as drug use, drug dealing, property, and violent crime increase over time as life circumstances change for the worse.  Many LC models place substantial emphasis on neighborhood-level disadvantage such as poverty and unemployment, arguing  that disadvantage influences outcomes above and beyond the effect of individual-level process and that it exacerbates (i.e., conditions) the impact of individual-level process.  Despite the prominence of neighborhood disadvantage in many LC perspectives, hypotheses asserting the causal import of neighborhood disadvantage are rarely subjected to empirical verification.

A fundamental reason for the chasm between theory and research is a serious

shortage of appropriate longitudinal data.  First, in most longitudinal data sets children, adolescents, or young adults are randomly selected from the general population, and interviews take place in schools, at home, or by phone. This is a serious limitation  because the prevalence  of serious drug  use (ie, cocaine, heroin) in general population samples is low, and because heavy users often leave school prematurely, are rarely home, and avoid talking about drugs on the phone.  Second, when subjects with serious drug problems enter population studies they are more likely to attrite because they frequently  move and are difficult to locate (Thornberry 1989). Third, the lives of serious drug abusers change rapidly from month to month because of changing life circumstances but most prospective, longitudinal data sets employ a six month or one year reference period and thus fail to capture short term change (Horney et. al. 1996). Finally, as we discussed above, many life course theories emphasize the deleterious consequences of neighborhood-level disadvantage yet most longitudinal data are collected in a single city or locality.  This means that there is less variability in local conditions measured at the neighborhood-level and, all else equal, that the chance of linking neighborhood conditions to outcomes is reduced.