Relationship between macronutrients, dietary components, and objective sleep variables measured by smartphone applications
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Background
Few studies have used daily data from objective applications to explore macronutrient interactions in sleep and nutrition research.
Objective
This cross-sectional study examined the relationships between macronutrients, dietary components, and sleep parameters, considering their interdependencies.
Methods
Data from 4,825 users of sleep and nutrition apps for at least 7 days were analyzed. Multivariable regression analysis investigated associations between quartiles of macronutrients (protein, carbohydrate, and total fat, including saturated, monounsaturated, and polyunsaturated fats), dietary components (sodium, potassium, dietary fiber, and sodium-to-potassium ratio), and sleep variables (total sleep time [TST], sleep latency [SL], and % wakefulness after sleep onset [%WASO]). Nutrients were divided into quartiles, with the lowest intake group as the reference. Compositional data analysis accounted for interdependencies among macronutrients. Analyses were adjusted for age, sex, and body mass index (BMI).
Results
Higher protein intake was associated with longer TST in the 3rd (B = 0.17, 95% CI = 0.09, 0.26) and 4th quartiles (B = 0.18, 95% CI = 0.09, 0.27). Higher total fat intake was linked to shorter TST in the 3rd (B = -0.11, 95% CI = -0.20, -0.27) and 4th quartiles (B = -0.16, 95% CI = -0.25, -0.07). Higher carbohydrate intake was associated with shorter %WASO in the 3rd (B = -0.82, 95% CI = -1.37, -0.26) and 4th quartiles (B = -0.57, 95% CI = -1.13, -0.01), while higher total fat intake was linked to longer %WASO in the 4th quartile (B = 0.62, 95% CI = 0.06, 1.18). Higher dietary fiber intake was consistently associated with longer TST in the 3rd (B = 0.11, 95% CI = 0.02, 0.19) and 4th quartiles (B = 0.18, 95% CI = 0.09, 0.26), shorter SL in the 2nd (B = -1.71, 95% CI = -2.66, -0.76), 3rd (B = -2.23, 95% CI = -3.19, -1.27), and 4th quartiles (B = -2.30, 95% CI = -3.27, -1.33), and shorter %WASO in the 2nd (B = -1.06, 95% CI = -1.61, -0.51), 3rd (B = -1.04, 95% CI = -1.59, -0.48), and 4th quartiles (B = -1.05, 95% CI = -1.61, -0.48). A higher sodium-to-potassium ratio was linked to shorter TST in the 3rd (B = -0.11, 95% CI = -0.20, -0.02) and 4th quartiles (B = -0.19, 95% CI = -0.28, -0.10), longer SL in the 2nd (B = 1.03, 95% CI = 0.08, 1.98) and 4th quartiles (B = 1.50, 95% CI = 0.53, 2.47), and longer %WASO in the 4th quartile (B = 0.71, 95% CI = 0.15, 1.28). Compositional data analysis, involving 6% changes in macronutrient proportions, showed higher protein intake correlated with longer TST (B = 0.27, 95% CI = 0.18, 0.35), while more monounsaturated fats were linked to longer SL (B = 4.64, 95% CI = 1.93, 7.34) and %WASO (B = 2.21, 95% CI = 0.63, 3.78). Higher polyunsaturated fat intake correlated with shorter TST (B = -0.22, 95% CI = -0.39, -0.05), shorter SL (B = -4.72, 95% CI = -6.58, -2.86), and shorter %WASO (B = -2.00, 95% CI = -3.08, -0.92).
Conclusions
These findings highlight the intricate relationships between dietary factors and sleep outcomes. Prospective studies are warranted to determine whether dietary interventions result in positive sleep outcomes.
