Associations between social loneliness trajectories and chronotype among adolescents.

Late chronotype during adolescence is a critical risk factor for poor physical and mental health among adolescents. While social loneliness is confirmed to negatively influence sleep behaviors, the long-term effect of social loneliness on chronotype remains unknown. This study aims to investigate whether social loneliness trajectories from middle childhood to adolescence are associated with chronotype in late adolescence and examine the potential sex differences in these associations. Data were obtained from 2398 adolescents who participated in the Child and Adolescent Behaviors in Long-Term Evolution project. Chronotype was calculated as the midpoint of sleep on free days adjusted for sleep debt. Group-based trajectory modeling and multiple linear regression were employed to establish social loneliness trajectories and determine their associations with chronotype. Social loneliness trajectories were significantly associated with chronotype and varied by sex. Specifically, boys following a high-decreasing trajectory had earlier chronotype during late adolescence than did those following a low-decreasing trajectory (B = - 0.07; p < 0.05). By contrast, girls following a low-to-moderate-increasing trajectory exhibited later chronotype than did those following a low-stable trajectory (B = 0.07; p < 0.01). Social loneliness trajectories, especially those displaying significant fluctuations over time, are critical indicators influencing chronotype among adolescents. Furthermore, these trajectories and their associations with chronotype display sex differences. These findings highlight the need for early interventions for psychological factors such as social loneliness to ensure that the late chronotype can be prevented. In addition, sex variations must be considered.

Associations between social jetlag trajectories and body mass index among young adults.

STUDY OBJECTIVES: This study employed longitudinal data collected repeatedly from individuals over the course of several years to examine the trajectories of social jetlag from ages 11 to 22 years and their associations with subsequent body mass index (BMI). Potential sex differences were also investigated. METHODS: Data were obtained from two longitudinal studies conducted in Taiwan (N = 4287). Social jetlag was defined as ≥ 2 hours of absolute difference in sleep midpoint between weekdays and weekends. BMI was calculated using weight (kg)/height(m)2 and categorized as underweight (<18 kg/m2), normal weight (18 kg/m2 ≤ BMI < 24 kg/m2), overweight (24 kg/m2 ≤ BMI < 27 kg/m2), and obese (≥27 kg/m2). Group-based trajectory modeling and multinomial logistic regression were applied to investigate study objectives. RESULTS: Four distinct trajectories of social jetlag throughout the adolescent years were identified, with corresponding proportions as follows: low-stable (42%), moderate-decreasing (19%), low-increasing (22%), and chronic (17%) trajectories. Among males, the risk of being underweight (aOR, 1.96; 95% CI: 1.35 to 2.84) or obese (aOR, 1.40; 95% CI: 1.02 to 1.92) was higher in individuals with a low-increasing trajectory than in those with a low-stable trajectory. Among females, those with a low-increasing (aOR, 1.61; 95% CI: 1.02 to 2.54) or chronic (aOR, 2.04; 95% CI: 1.27 to 3.25) trajectory were at a higher risk of being obese relative to those with a low-stable trajectory. CONCLUSIONS: Addressing the development of increasing or chronic social jetlag during adolescence can help prevent abnormal BMI in young adulthood. Practitioners should consider sex differences in treatment or consultation.

Is Sleep Timing Related to Objectively Measured Physical Activity and Sedentary Behavior in Older Women?

PURPOSE: Sleep, sedentary behavior, and physical activity are the components of the 24-hour model, while the timing of sleep may play a critical role to impact waking behaviors. Therefore, the present study aimed to examine the relationship of sleep timing with sedentary behavior, light-intensity, moderate-to-vigorous-intensity physical activity, and daily steps in older women. PATIENTS AND METHODS: A total of 90 community-dwelling older women (70.5 ± 5.4 years) were included in our sample. Multiple linear regression models were used to estimate the associations of accelerometer-measured sedentary behavior and physical activity metrics with the three sleep timing indicators (bedtime and wake time, and mid-sleep time). Bedtime and wake time were recorded by the participants, and mid-sleep time was estimated based on the two sleep indicators. RESULTS: Most indicators of sleep timing were negatively associated with moderate-to-vigorous-intensity physical activity (unstandardized coefficient [B]-0.07 for bedtime and mid-sleep time, p<0.05) and daily steps (B ranged from -15.51 for bedtime to -13.73 for wake time, p<0.05). No associations of sleep timing were found in sedentary behavior and light-intensity physical activity. CONCLUSION: The findings suggest that sleep timing should be considered when designing promising strategies or interventions for older women to be physically active.