A Sleep Apnea Prediction Model Developed for African Americans, the Jackson Heart Sleep Study.

STUDY OBJECTIVES: African Americans have a high prevalence of severe sleep apnea which is often undiagnosed. We developed a prediction model for sleep apnea and compared the predictive values of that model to other prediction models among African Americans in the Jackson Heart Sleep Study (JHSS). METHODS: JHSS participants underwent a Type 3 home sleep apnea study and completed standardized measurements and questionnaires. We identified 26 candidate predictors from 17 preselected measures capturing information on demographics, anthropometry, sleep, and comorbidities. To develop the optimal prediction model, we fit logistic regression models using all possible combinations of candidate predictors. We then implemented a series of steps: comparisons of equivalent models based on the C-statistics, bootstrap to evaluate the finite sample properties of the C-statistics between models, and 5-fold cross-validation to prevent overfitting. RESULTS: Of 719 participants, 38% had moderate or severe sleep apnea, 34% were male and 38% reported habitual snoring. The average age and BMI were 63.2 (SD:10.7) years and 32.2 (SD: 7.0) kg/m(2). The final prediction model included: age, sex, BMI, neck circumference, depressive symptoms, snoring, restless sleep, and witnessed apneas. The final model has an equal sensitivity and specificity of 0.72, and better predictive properties than commonly used prediction models. CONCLUSIONS: In comparing a prediction model developed for African Americans in the JHSS to widely used screening tools, we found a model that included measures of demographics, anthropometry, depressive symptoms, and sleep patterns and symptoms better predicted sleep apnea.