Neighborhood as a predictor of non-aggressive, but not aggressive, antisocial behaviors in adulthood.

There is converging evidence that, although physical aggression (e.g., assaulting others, bullying; AGG) and non-aggressive rule-breaking (e.g., lying, stealing, vandalism; RB) are moderately-to-strongly correlated, they nevertheless constitute meaningfully distinct dimensions of antisocial behavior. As reviewed previously (Burt, 2012; Tackett, Krueger, Iacono, & McGue, 2005; Tremblay, 2010), AGG and RB evidence distinctive developmental trajectories, demographic correlates, personological underpinnings, and perhaps most importantly, etiologic differences. In particular, a meta-analysis of 103 twin and adoption studies (Burt, 2009) revealed that AGG was a highly heritable condition (65% of the variance), with little role for the shared environment (i.e., influences that create similarity regardless of the extent of genetic similarity). By contrast, while genetic influences also contributed to RB (48%), there was an important role for shared environmental effects as well (18%). Although such findings clearly point to substantive etiologic distinctions between AGG and RB, the identification of larger shared environmental influences on RB than on AGG in a classical twin study design does not reveal anything about the specific aspects of the environment that underlie this effect (sometimes referred to as the “black box” problem). The larger environmental contributions to RB could thus be a function of the parent-child relationship, divorce, peers, and/or broader contextual influences, each of which has different ramifications for our understanding of the origins of RB. It is equally unclear what specific genes may comprise and underlie the differential heritability of AGG and RB. Fortunately, a small handful of studies have begun to fill these gaps in the literature (see Breslau et al., 2011; Gorman-Smith, Tolan, Zelli, & Huesmann, 1996; Klahr, Klump, & Burt, in press; Lynam et al., 2000; Raine, Brennan, & Mednick, 1994). For example, Klahr and colleagues (in press) examined whether maternal negativity was differentially associated with AGG and RB in a sample of 1,648 child twins from 824 families. Results revealed that the association with maternal negativity was entirely environmental in origin for RB, but was both genetic and environmental in origin for AGG. Moreover, the shared environmental correlation between maternal negativity and RB was significantly larger than that with AGG (.82 and .62, respectively), indicating that maternal negativity is one source of the etiologic differences between AGG and RB prior to adulthood. For their study, Breslau and colleagues (2011) focused on broader societal effects that may differ across AGG and RB. They specifically examined adults of Mexican ancestry in various stages of migration: a) adults of Mexican ancestry living in the United States but who were raised in Mexico, b) adults of Mexican ancestry who were born in the United States or who came to the United States as children, and c) adults of Mexican ancestry born in the United States to at least one US-born parent. Comparing migrants (i.e., group a) to those born and/or raised in the new country (i.e., groups b and c) allowed researchers to examine the influence of broader societal/environmental conditions on behavior prevalence. Results revealed that, when compared to group a, the odds ratios for AGG (0-2 versus 3+ symptoms) in groups b and c were 1.51 and 3.07, whereas those for RB were 3.45 and 10.50. Such results highlight a likely role for societal or broader contextual influences in adult RB in particular. Although the above studies have begun to narrow in on the specific environmental experiences that underlie the stronger environmental influences on RB, much remains unknown. There is thus a clear need for additional research on the source of environmental differences between AGG and RB. Neighborhood context is an excellent candidate for such work given the vast literature tying neighborhood disadvantage to antisocial behavior across the lifespan (as two representative examples, please see Gorman-Smith, Tolan, & Henry, 2000; Leventhal & Brooks-Gunn, 2000), as well as the focus on (as yet unidentified) contextual environmental influences in Breslau et al. (2011). The current study thus sought to examine neighborhood disadvantage as a unique predictor of RB, evaluating whether unrelated adults residing in the same neighborhood were more similar in their RB (but not their AGG) than would be expected by chance. This design functions in some ways as a conceptual extension of studies using similarity among step-siblings to make inferences regarding the importance of the shared environment (Burt, 2014). It is important to note, however, that neighborhood-level similarity could reflect genetic similarity between neighbors and/or common selection processes rather than an effect of the environment (Burt, 2014). We thus attempted to evaluate the role(s) of neighborhood selection and gene-environment correlation (i.e., rGE; non-random or genetically-influenced exposure to particular environmental experiences, in this case neighborhood residence) in our results. We specifically reasoned that environmentally-mediated similarity among neighbors would not be present in new residents. Instead, similarity should emerge/increase after residing in the neighborhood for some time. We also restricted our analyses to neighborhoods with similar levels of likely selection characteristics, reasoning that the continued presence of neighborhood-level variance in a sub-sample of similar neighborhoods (which should be influenced by similar selection processes) would implicate an environmentally-mediated process. Although conclusions from these analyses will not definitively establish neighborhood as an environmental predictor of RB given the pervasive nature of genetic influences on human behavior and experience, positive results would nevertheless point to neighborhood context as a predictor of RB in particular and begin to clarify whether these neighborhood-level influences on RB function at least in part via the environment.