Neural Processing of Health Information and Hypertension Self-Management in African Americans

Uncontrolled blood pressure (BP) rates are persistently high among African Americans with hypertension. Although self-management is critical to controlling BP, little is known about the brain-behavior connections underlying the processing of health information and the performance of self-management activities.

In this pilot study, we explored the associations among neural processing of two types of health information and a set of self-management cognitive processes (self-efficacy, activation, decision-making, and hypertension knowledge) and behaviors (physical activity, dietary intake, and medication taking) and health status indicators (BP, health-related quality of life, anxiety, and depression).

Using a descriptive cross-sectional design, 16 African Americans with uncontrolled hypertension (mean age = 57.5 years, 68.8% women) underwent functional magnetic resonance imaging to assess activation of two neural networks, the task-positive network and the default mode network, and a region in the ventromedial prefrontal cortex associated with emotion-focused and analytic-focused health information. Participants completed self-reports and clinical assessments of self-management processes, behaviors, and health status indicators.

Our hypothesis that neural processing associated with different types of health information would correlate with self-management cognitive processes and behaviors and health status indicators was only partially supported. Home diastolic BP was positively associated with ventromedial prefrontal cortex activation ( r = .536, p = .09); no other associations were found among the neural markers and self-management or health status variables. Expected relationships were found among the self-management processes and behaviors and health status indicators.

To advance our understanding of the neural processes underlying health information processing and chronic illness self-management, future studies are needed that use larger samples with more heterogeneous populations and additional neuroimaging techniques.