Relationship Among Macronutrients, Dietary Components, and Objective Sleep Variables Measured by Smartphone Applications: A Real-World Cross-Sectional Study

medRxiv - Nutrition Pub Date : 2024-07-26 DOI:10.1101/2024.07.25.24311028

Jaehoon Seol, Masao Iwagami, Megane Kayamare, Masashi Yanagisawa

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Abstract

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.

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智能手机应用程序测量的宏量营养素、膳食成分和客观睡眠变量之间的关系：一项真实世界横断面研究

背景：在睡眠和营养研究中，很少有研究使用客观应用的每日数据来探讨宏量营养素之间的相互作用：这项横断面研究考察了宏量营养素、膳食成分和睡眠参数之间的关系，并考虑了它们之间的相互依存关系：方法：分析了4825名使用睡眠与营养应用程序至少7天的用户的数据。多变量回归分析调查了宏量营养素（蛋白质、碳水化合物和总脂肪，包括饱和脂肪、单不饱和脂肪和多不饱和脂肪）、膳食成分（钠、钾、膳食纤维和钠钾比）和睡眠变量（总睡眠时间[TST]、睡眠潜伏期[SL]和入睡后觉醒百分比[%WASO]）的四分位数之间的关联。营养素分为四等分，以最低摄入量组为参照。成分数据分析考虑了宏量营养素之间的相互依存关系。分析根据年龄、性别和体重指数（BMI）进行了调整：蛋白质摄入量越高，第 3 个四分位数（B = 0.17，95% CI = 0.09，0.26）和第 4 个四分位数（B = 0.18，95% CI = 0.09，0.27）的 TST 越长。总脂肪摄入量越高，第 3 个四分位数（B = -0.11，95% CI = -0.20，-0.27）和第 4 个四分位数（B = -0.16，95% CI = -0.25，-0.07）的 TST 越短。较高的碳水化合物摄入量与第 3 个四分位数（B = -0.82，95% CI = -1.37, -0.26）和第 4 个四分位数（B = -0.57，95% CI = -1.13, -0.01）中较短的 WASO 百分比有关，而较高的总脂肪摄入量与第 4 个四分位数中较长的 WASO 百分比有关（B = 0.62，95% CI = 0.06, 1.18）。膳食纤维摄入量越高，第 3 个四分位数（B = 0.11，95% CI = 0.02，0.19）和第 4 个四分位数（B = 0.18，95% CI = 0.09，0.26）的 TST 越长，第 2 个四分位数（B = -1.71，95% CI = -2.66，-0.76）和第 3 个四分位数（B = -2.23，95% CI = -0.76）的 SL 越短。23，95% CI = -3.19，-1.27）和第 4 个四分位数（B =-2.30，95% CI = -3.27，-1.33），第 2 个（B =-1.06，95% CI =-1.61，-0.51）、第 3 个（B =-1.04，95% CI =-1.59，-0.48）和第 4 个四分位数（B =-1.05，95% CI =-1.61，-0.48）的 WASO%较短。钠钾比值越高，第 3 个四分位数（B = -0.11，95% CI = -0.20，-0.02）和第 4 个四分位数（B = -0.19，95% CI = -0.28，-0.10）的 TST 越短，第 2 个四分位数（B = -0.59，95% CI = -0.48）的 SL 越长。10），第 2 个四分位数（B = 1.03，95% CI = 0.08，1.98）和第 4 个四分位数（B = 1.50，95% CI = 0.53，2.47）的 SL 更长，第 4 个四分位数（B = 0.71，95% CI = 0.15，1.28）的 %WASO 更长。成分数据分析涉及 6% 的宏量营养素比例变化，结果显示，蛋白质摄入量越高，TST 越长（B = 0.27，95% CI = 0.18，0.35），而单不饱和脂肪摄入量越高，SL 越长（B = 4.64，95% CI = 1.93，7.34），WASO% 越高（B = 2.21，95% CI = 0.63，3.78）。多不饱和脂肪摄入量越高，TST越短（B = -0.22，95% CI = -0.39，-0.05），SL越短（B = -4.72，95% CI = -6.58，-2.86），WASO%越短（B = -2.00，95% CI = -3.08，-0.92）：这些发现凸显了饮食因素与睡眠结果之间错综复杂的关系。有必要进行前瞻性研究，以确定饮食干预是否会带来积极的睡眠结果。

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medRxiv - Nutrition

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