Table 4. Regression models of physical activity, screen-based sedentary behavior, and diet variables to show contrasts for short versus long sleep and early versus late chronotype (N= 439,933).

Dependent variable	Physical activity (minutes/week)			Screen-based sedentary behavior (hours/day)		Diet variables		Tobacco use
	Walking	Moderate	Vigorous	Computer use	Television viewing	Fruit Servings/day	Vegetables Servings/day
Comparisona	β (SE) 95 % CI	β (SE) 95 % CI	β (SE) 95 % CI	β (SE) 95 % CI	β (SE) 95 % CI	β (SE) 95 % CI	β (SE) 95 % CI	OR (SE) 95 % CI
Short sleep duration	0.077 (0.012) 0.054–0.010	0.007 (0.013) −0.019–0.032 (NS)	0.061 (0.018) 0.026–0.096	0.129(0.012) 0.107–0.152	−0.374 (0.020) −0.412 to −0.336	0.051 (0.012) 0.028–0.073	0.001 (0.012) −0.022–0.024 (NS)	1.082 (0.034) 0.013–0.145
Early chronotype	0.178(0.011) 0.157–0.200	0.172 (0.012) 0.148–0.196	0.172 (0.017) 0.139–0.204	−0.313(0.011) −0.334 to −0.291	−0.141 (0.018) −0.176 to −0.105	0.246(0.011) 0.225–0.267	0.133 (0.011) 0.112–0.155	0.407(0.11) 0.385–0.430

Regression models of the health behaviors include the sleep duration and chronotype variables as well as the controlling variables of sex, race, college attendance, and employment. General linear regression models were used for continuous outcomes (physical activity, screen-based sedentary behavior, fruit intake, and vegetable intake) while logistic regression was used for the outcome of tobacco use)

NS non-signficant at the 0.05 level

^aThe reference category for sleep duration is long sleep duration (nine or more hours). The reference category for chronotype is late chronotype