[Infant sleep patterns based on latent class analysis and their influencing factors]

To identify infant sleep patterns and explore their influencing factors, providing scientific evidence for the formation and intervention of healthy sleep patterns.

A total of 1 483 12-month-old infants from the Shanghai Birth Cohort were included. Sleep status was assessed using the Brief Infant Sleep Questionnaire. Latent class analysis was performed to integrate sleep behavior and sleep problem variables and to identify typical sleep patterns. A binary logistic regression model was employed to examine influencing factors.

Two sleep patterns were identified: a good sleep pattern characterized by healthier sleep habits and fewer sleep problems, and a poor sleep pattern characterized by poorer sleep habits and more sleep problems. Logistic regression analysis showed that, compared with infants who had stopped breastfeeding, infants still being breastfed at 12 months were more likely to develop poor sleep patterns (OR=1.725, P<0.001). Compared with infants from families with better economic status, those from families with economic hardship were more likely to develop poor sleep patterns (OR=1.638, P=0.003). Outdoor activity for more than one hour per day was associated with better sleep patterns (OR=0.633, P<0.001), while screen exposure increased the risk of poor sleep patterns (OR=1.887, P<0.001).

Infant sleep patterns are influenced by multiple factors; increasing outdoor activity and limiting screen exposure help infants form good sleep patterns.