Association of multiple chronic conditions and pain among older black and white adults with diabetes mellitus

Abstract

Background

Aging is often associated with the challenge of navigating daily tasks with a painful chronic medical illness. Yet, there is concern of the number of older adults impacted with more than one chronic condition. Despite the increasing number of adults diagnosed with diabetes and comorbid chronic illnesses, there remains a lack of understanding in how multiple illnesses relate to experiences of pain. To assess the association between multiple chronic conditions and pain, this study aimed to identify clusters of chronic medical conditions and their association with pain among a sample of older Black and White adults diagnosed with diabetes.

Methods

Two hundred and thirty-six participants responded to a series of questions assessing pain frequency and severity, as well as health and social characteristics. A factor analysis was used to categorize clusters of medical conditions, and multiple regression models were used to examine predictors of pain.

Results

Seven of the assessed chronic medical conditions loaded on three factors, and accounted for 57.2% of the total variance, with heart disease (factor 1) accounting for 21.9%, musculoskeletal conditions (factor 2) for another 18.4%, and factor 3 (microvascular diseases) accounting for a final 16.9% of the variability among the chronic medical conditions. Covariate-adjusted models showed that fewer years of education and higher scores on the microvascular and musculoskeletal conditions factors were associated with higher pain frequency, with the musculoskeletal conditions factor being the strongest predictor.

Conclusions

Findings from this study compliment existent literature underscoring the prevalence and importance of comorbid diagnoses in relation to pain. Examining health-related factors beyond a single disease diagnosis also provides an opportunity to explore underlying disease co-occurrences that may persist beyond organ system classifications.