Associations of physical activity, sedentary behavior, and sleep patterns with cognitive function among middle-aged and older adults.

Background: Despite the established evidence that physical activity, sedentary behavior, and sleep affect cognitive function individually, less is known about the combined effects of these movement behaviors. The study aimed to identify movement patterns of physical activity, sitting time, and sleep and to examine the association of movement patterns with cognitive function.

Methods: This cross-sectional study included 1,240 participants aged ≥ 55 years participating in the Cooper Center Longitudinal Study who visited the Cooper Clinic, Dallas (2016-2019) for preventive health care. Four movement behaviors were self-reported, including leisure-time aerobic activity, muscle-strengthening activity, sitting time, sleep, and other characteristics. Cognitive function was assessed by the Montreal Cognitive Assessment (MoCA). Four categorical indicators were created for each movement behavior and used to identify latent classes. Information criterion, scaled relative entropy and model interpretability were used to determine the optimal number of classes. Participants were assigned to the predicted classes based on their highest posterior probabilities. Multinomial regressions examined the association between movement patterns and each covariate. Linear and logistic regression models examined the association of movement patterns and cognitive function. A sensitivity analysis accounted for misclassification errors.

Results: Participants were predominantly White (95%), male (71%), with an average age of 62 years. A 3-class model was selected, comprising class 1: active long sleepers, class 2: very active short sleepers, and class 3: moderately active short sleepers, representing 11%, 62%, and 27% of the sample. Compared to class 2, class 1 was more likely to be older and female, while class 3 was more likely to be female, have less education, be overweight and obese, and have chronic conditions. Compared to class 2, class 3 was associated with a lower MoCA total score, adjusting for sociodemographic factors. There were no differences in MoCA total score between class 2 and class 3 when further controlling for health behaviors and indicators. Sensitivity analysis accounting for misclassification suggested that class 3 had a significantly lower average MoCA total score than class 2.

Conclusions: The current study identified three distinct movement classes that exhibited different sociodemographic, health characteristics and cognitive functions. Findings highlight that less active, more sedentary, and shorter sleep individuals had worse cognitive function.