The Influence of Community Violence and Protective Factors on Healthcare Utilization in High-Risk Children with Asthma

Background and Purpose: Asthma is a chronic inflammatory lung disease that disproportionately impacts inner-city minority children (Williams, Sternthal, & Wright, 2009).  Exposure to community violence, which may range from perceived threats to direct victimization, is one stressor that has an especially robust connection to asthma morbidity, as it is proposed to precipitate asthma exacerbations and result in increased healthcare utilization.  Although understanding contextual factors at the level of families and neighborhood has long been regarded as fundamental to reducing asthma disparities (Ford & McCaffrey, 2006), the longitudinal effects of community risk and protective factors are understudied in pediatric asthma populations. 

Methods: Three hundred urban caregivers of children with poorly controlled asthma were enrolled in a randomized controlled trial testing the effectiveness of a behavioral/educational intervention and completed measures of exposure to community violence (ECV), social cohesion (SC), informal social control (ISC), and asthma-related emergency services (e.g., urgent care, emergency room visits, and hospitalizations) at baseline, two-months, six-months, and twelve-months post-enrollment. Latent growth curve modeling (LGCM) was used to test the hypothesis that community protective factors are statistically significant moderators of the relationship between exposure to community violence and healthcare utilization over time.

Results: Caregivers were primarily the biological mother (92%), single (70%), and poor (50% earned less than $10,000). Children were African American (96%) and young (Mean age= 5.5 years, SD=2.2). ECV at baseline was high, with 24.7% of caregivers reporting more than two exposures to violence in the previous six months (M=1.45,SD=1.61). The LGCM analysis of healthcare utilization indicated that the final model including interactions was the best fitting model and demonstrated acceptable overall fit as evidenced by a non-significant chi-square test (x²₍₅₀₎=66.25, p>0.05), RMSEA of 0.05, highest values for CFI (0.89) and TFI (0.82), and smallest AIC of the three models.  Caregiver ECV predicted asthma-related healthcare utilization at baseline (b=0.19, s.e.=0.07, p=0.003) and two-months (b=0.12, s.e.=0.05, p=0.04). Small but statistically significant interactions were detected between informal social control and ECV at baseline (b=-0.005,s.e.=0.002,p=0.005) and two-months (b=-0.003,s.e.=0.002,p=0.049) and between social cohesion and community violence at baseline (b=-0.005,s.e.=0.002,p=0.007) and two-months (b=-0.003,s.e.=0.002,p=0.049).

Conclusions:  Our findings support prior calls to implement programs that address community stressors like crime as a means to reduce asthma morbidity, but interventions solely focusing on violence reduction may not necessarily be sufficient to decrease the use of emergency services.  These results suggest that multi-faceted social work interventions that include strategies to promote healing from violence exposure and foster feelings of cohesion among low-income urban residents may be needed to reduce asthma-related emergency services.

References:

Ford, J. G., & McCaffrey, L (2006).  Understanding disparities in asthma outcomes among African Americans. Clinics in Chest Medicine, 27, 423-430.

Williams, D. R., Sternthal, M., & Wright, R.J. (2009). Social determinants: Taking the social context of asthma seriously. Pediatrics, 123(Suppl. 3), S174-S184.