LAUSR

The occurrence of obstructive sleep apnea (OSA) is strongly associated with obesity. Behavioral, pharmacological, and surgical interventions that promote weight reduction can reduce OSA severity and improve other common obesity related complications and quality of life. While the relationship between weight reduction and apnea-hypopnea index (AHI) improvement has been documented, it does not seem to have been quantified adequately. The objective of this analysis was to quantify the association between percent change in body weight and percent change in AHI using results from the literature. A literature search identified 13 studies with AHI and weight measurements before and after weight intervention in people living with obesity and OSA; 6 studies from bariatric surgery, 4 studies from diet and exercise intervention, and 3 studies from anti-obesity medications (including 2 placebo-controlled randomized clinical trials). A polynomial and a linear meta regression model as well as 95% prediction intervals were used to assess the relationship between % weight change from baseline and % change in AHI from baseline. Both the polynomial and linear models show, on average, weight reduction in patients living with obesity and OSA has a clinical benefit in reducing AHI. The linear meta-regression model that we developed suggests a mean AHI decrease of 2.6% per 1% weight reduction. As the prediction intervals are relatively wide, a precise relationship could not be established. For example, based on the linear model for a patient with 20% weight reduction we expect to see a mean 52.8% reduction in AHI with a 95% prediction interval (89.8%, 15.8%) AHI reduction. Evidence shows that intentional weight reduction in people living with obesity and OSA results in improvements in OSA severity, and this was confirmed by our meta-analysis and modeling. The model shows that the degree of AHI improvement is dependent on the magnitude of weight reduction. However, establishing a precise relationship between percent change in AHI and percent weight reduction is challenging given the sparsity of data, variability in populations studied, and variability in AHI change following weight reduction. Eli Lilly and Company