A Clinic-Integrated Behavioral Intervention for Families of Youth with Type 1 Diabetes Is Equally Effective Across Income Levels

Introduction: Consistent with general trends in health disparities research, adolescents with type 1 diabetes who experience lower family income have poorer metabolic control. However, the impact of socioeconomic factors on the effectiveness of behavioral interventions is rarely examined.  This study examines whether a behavioral intervention for youth with type 1 diabetes is differentially effective across income levels.

 Methods: “WE*CAN  manage diabetes” is a clinic-integrated behavioral intervention designed to help families of youth with type 1 diabetes improve diabetes management by facilitating problem-solving skills, communication skills, and appropriate responsibility sharing. This behavioral intervention targets families of preadolescents and adolescents, as glycemic control is known to deteriorate during this developmental period. The intervention has previously demonstrated efficacy in improving glycemic control relative to standard care. In this post hoc analysis, we examined the intervention effect across income levels. Families of children ages 9 to 15 with type 1 diabetes (n=390, 49.2% female, age 12.4±1.7, A1c 8.4±1.2, 33.8% pump) at four pediatric endocrinology clinics in diverse U.S. geographic locations participated in a two-year randomized clinical trial. The primary outcome was HbA1c (a biomarker of glycemic control; lower values indicate better control), analyzed centrally at a reference laboratory. Family income was categorized as <$50,000 (low), $50,000- <$100,000 (middle), and ≥$100,000 (high). Treatment effect was defined as the change in HbA1c from baseline to two-year follow-up. A generalized linear model analysis was used to test the interaction on treatment effect of the intervention with family income group.

 Results: Baseline HbA1c was significantly poorer (p=.007) in the low income group (8.7 low, 8.3 middle, 8.2 high). Analysis of change in HbA1c from baseline to follow-up indicated a significant overall effect for treatment group (p=.03). The interaction term for treatment by income group was not significant (p=.74). Within each income category, a smaller deterioration in glycemic control was observed for the treatment group relative to the control group (change in HbA1c of 0.54 vs. 1.13 for low income, 0.39 vs. 0.66 for middle income, and 0.41 vs. 0.71 for high income). Thus, this clinic-integrated behavioral intervention was similarly effective in improving glycemic control among youth with type 1 diabetes across income levels.

 Conclusions: The use of a problem-solving approach applied to diabetes management issues selected by the family offers considerable flexibility in addressing individual family circumstances and needs. Such an approach may optimize impact on health outcomes across income groups.