Associations between sleep duration trajectories and sarcopenia among middle-aged and older Chinese adults.

BACKGROUND

The association between a single time-point measurement of sleep duration and sarcopenia has been extensively explored in existing literature. However, the potential link between sleep duration trajectories and sarcopenia remains largely unexplored. This study aims to assess the relationship between sleep duration trajectories and sarcopenia within a longitudinal cohort of middle-aged and older Chinese individuals.

METHODS

This study analyzed a substantial cohort of participants (n = 6305), aged 45 to 80, drawn from the China Longitudinal Study of Health and Retirement (CHARLS). Sleep duration data, collected at intervals from 2011 to 2015, were employed to plot sleep duration trajectories using group-based trajectory modeling (GBTM). Sarcopenia was assessed utilizing data from 2015. Subsequently, a multivariable logistic regression model was applied to investigate the association between varying sleep duration trajectories and the risk of sarcopenia.

RESULTS

Four distinct trajectories of sleep duration were identified: Class 1, characterized by persistently long sleep duration (n = 1391, 22.06 %); Class 2, characterized by persistently high-normal sleep duration (n = 2129, 33.77 %); Class 3, characterized by persistently low-normal sleep duration (n = 1401, 22.22 %); and Class 4, characterized by persistently short sleep duration (n = 1384, 21.95 %). In the model 0, both persistently long sleep duration (OR: 1.83, 95 % CI: 1.50-2.24; p < 0.001) and persistently short sleep duration (OR: 1.76, 95 % CI: 1.44-2.15; p < 0.001) were notably correlated with a greater risk of sarcopenia when compared to persistently high-normal sleep duration. Furthermore, the stratified analyses generally corroborated the primary findings.

CONCLUSIONS

Both persistently long and short sleep duration trajectories are associated with an elevated risk of sarcopenia, compared to persistently high-normal sleep duration trajectories among middle-aged and older Chinese adults. Furthermore, the findings highlight the essential need to monitor changes in sleep duration over time.