The Correlates of Neighborhood Social Cohesion within the Census Blocks of Making Connections Initiative Neighborhoods

Background and Purpose:  Neighborhood social cohesion (NSC) is a measure of resident relationships, trust, shared values, and willingness to help one another. NSC is theorized to be critical for relational interventions in low to moderate-income neighborhoods. United States (US) Census variables are often used to represent variation in the structural components of neighborhoods, which may have an impact on the success of neighborhood interventions. Previous research indicates that several US Census variables have an impact on NSC, including but not limited to: resident stability/mobility, homeownership, level of education, and concentrations of racial minorities. This study seeks to: (1) determine if neighborhood structural components identified in previous research were significantly correlated with NSC at baseline before community level interventions and (2) whether these neighborhood structural components were related to changes in NSC during a specific place-based initiative.

 

Methods:  The study used data from three waves of the Annie E. Casey Foundation’s Making Connections initiative to provide a thorough description of the variation in NSC across low to moderate-income neighborhoods and across time.  The Making Connections data were collected on a stratified random sample of 7,495 households in 430 US Census block groups in ten cities in the US between 1999 and 2007.  The study aggregates NSC scores at the US Census Block Group level to create a representative and generalizable sample of NSC scores in low and moderate-income neighborhoods. NSC is measured using five survey items measured on a five point Likert scale with 1 representing low neighborhood NSC (strongly disagree) and 5 representing high NSC (strongly agree). Descriptive statistics and growth curve models were used to provide a rich description of the correlates of NSC in low and moderate-income neighborhoods.

Results:  Twenty-four US Census variables were correlated with NSC at baseline. The largest correlations between NSC and US Census variables at baseline were: the percent that own their home (.39), percent that moved (-.30), and percent Latino/Latina (.30).  Three US Census variables were significantly correlated with NSC at wave 1 and were significantly correlated with changes in NSC from wave 1 to wave 3, respectively, including: percent American Indian and Alaska Native (-.10, .11), the percent of people that moved (-.30, .11), and the percent that moved to a different county (-.15, .16). The percent of bachelor’s degrees was also a significant correlate of NSC change scores (.16).

 

Conclusions and Implications:  Many US Census variables were correlates of NSC; however, fewer US Census variables were significant correlates of intervention-targeted changes in NSC. Three US Census variables had both negative correlations with NSC at baseline and positive correlations with NSC change scores. Future research should explore the potential reasons for higher NSC scores when several US Census variables were higher including: homeownership, moves, and educational attainment particularly in neighborhoods with concentration of Latino/Latina and American Indian and Alaska Natives. Longitudinal research can help illuminate the impact of structural features on communities and community change over time.