Oxidative stress is correlated with sleep quality. A common tool for evaluating dietary and lifestyle exposures to oxidative stress is the Oxidative Balance Score (OBS), with higher OBS suggesting more substantial antioxidant exposures. The relationship between OBS and sleep quality is unclear. Investigating the association between OBS and sleep quality was the purpose of this study. To figure out the relationship between OBS and sleep quality, we utilized weighted linear models and weighted logistic regression. Adjusted models were also examined. 6300 participants who took part in the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2014 were recruited. OBS was negatively associated with sleep disorder (OR: 0.97; 95 % CI: 0.94-0.99), and positively associated with sleep duration (MD: 0.02; 95%CI: 0.01-0.03). Within the range of OBS > 24, each unit increase in OBS will result in a 40 % reduction in sleep disorder, and a 26 % increasement in sleep duration after adjustment (all P for trend <0.05). Dietary and lifestyle components were closely related to sleep quality independently. The relationship between OBS and sleep quality was prominent in the female population under 50 years of age. After stratification by education level, this relationship persisted. This research was cross-sectional design, and it was not possible to deduce causality. Diet and lifestyle might influence sleep quality by modulating oxidative balance. Antioxidant diets and lifestyles were important in reducing sleep problems and our study also provided new ideas for improving sleep quality.

Background: Oxidative Balance Score (OBS) is a tool for assessing the oxidative stress-related exposures of diet and lifestyle. The study aimed to investigate the association between OBS and low muscle mass.Methods: Overall, 6,307 individuals over the age of 18 were assessed using data from the 2011 to 2018 National Health and Nutrition Examination Survey (NHANES). Weighted logistic regression and models were used, together with adjusted models.Results: There was a negative relationship between OBS and low muscle mass [odds ratio (OR): 0.96, 95% confidence interval (CI): 0.94–0.97, p&lt; 0.0001] using the first OBS level as reference. The values (all 95% CI) were 0.745 (0.527–1.054) for the second level, 0.650 (0.456–0.927) for the third level, and 0.326 (0.206–0.514) for the fourth level (P for trend <0.0001). Independent links with low muscle mass were found for diet and lifestyle factors. A restricted cubic spline model indicated a non-linear association between OBS and low muscle mass risk (P for non-linearity<0.05). In addition, the inflection points of the nonlinear curves for the relationship between OBS and risk of low muscle mass were 20.Conclusion: OBS and low muscle mass were found to be significantly negatively correlated. By modulating oxidative balance, a healthy lifestyle and antioxidant rich diet could be a preventive strategy for low muscle mass.