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通过智能手机应用程序测量的常量营养素、饮食成分与客观睡眠变量之间的关系:真实世界横断面研究。

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

作者信息

Seol Jaehoon, Iwagami Masao, Kayamare Megane Christiane Tawylum, Yanagisawa Masashi

机构信息

International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Ibaraki, Japan.

Institute of Health and Sport Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan.

出版信息

J Med Internet Res. 2025 Jan 30;27:e64749. doi: 10.2196/64749.

DOI:10.2196/64749
PMID:39883933
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11826953/
Abstract

BACKGROUND

Few studies have explored the relationship between macronutrient intake and sleep outcomes using daily data from mobile apps.

OBJECTIVE

This cross-sectional study aimed to examine the associations between macronutrients, dietary components, and sleep parameters, considering their interdependencies.

METHODS

We analyzed data from 4825 users of the Pokémon Sleep and Asken smartphone apps, each used for at least 7 days to record objective sleep parameters and dietary components, respectively. Multivariable regression explored the 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 percentage of wakefulness after sleep onset [%WASO]). The lowest intake group was the reference. Compositional data analysis accounted for macronutrient interdependencies. Models were adjusted for age, sex, and BMI.

RESULTS

Greater protein intake was associated with longer TST in the third (+0.17, 95% CI 0.09-0.26 h) and fourth (+0.18, 95% CI 0.09-0.27 h) quartiles. In contrast, greater fat intake was linked to shorter TST in the third (-0.11, 95% CI -0.20 to -0.27 h) and fourth (-0.16, 95% CI -0.25 to -0.07 h) quartiles. Greater carbohydrate intake was associated with shorter %WASO in the third (-0.82%, 95% CI -1.37% to -0.26%) and fourth (-0.57%, 95% CI -1.13% to -0.01%) quartiles, while greater fat intake was linked to longer %WASO in the fourth quartile (+0.62%, 95% CI 0.06%-1.18%). Dietary fiber intake correlated with longer TST and shorter SL. A greater sodium-to-potassium ratio was associated with shorter TST in the third (-0.11, 95% CI -0.20 to -0.02 h) and fourth (-0.19, 95% CI -0.28 to -0.10 h) quartiles; longer SL in the second (+1.03, 95% CI 0.08-1.98 min) and fourth (+1.50, 95% CI 0.53-2.47 min) quartiles; and longer %WASO in the fourth quartile (0.71%, 95% CI 0.15%-1.28%). Compositional data analysis, involving 6% changes in macronutrient proportions, showed that greater protein intake was associated with an elevated TST (+0.27, 95% CI 0.18-0.35 h), while greater monounsaturated fat intake was associated with a longer SL (+4.6, 95% CI 1.93-7.34 min) and a larger %WASO (+2.2%, 95% CI 0.63%-3.78%). In contrast, greater polyunsaturated fat intake was associated with a reduced TST (-0.22, 95% CI -0.39 to -0.05 h), a shorter SL (-4.7, 95% CI to 6.58 to -2.86 min), and a shorter %WASO (+2.0%, 95% CI -3.08% to -0.92%).

CONCLUSIONS

Greater protein and fiber intake were associated with longer TST, while greater fat intake and sodium-to-potassium ratios were linked to shorter TST and longer WASO. Increasing protein intake in place of other nutrients was associated with longer TST, while higher polyunsaturated fat intake improved SL and reduced WASO.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/2de9d15b4bc5/jmir_v27i1e64749_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/12226dd18891/jmir_v27i1e64749_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/2e29fc5ee185/jmir_v27i1e64749_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/50f500acf43a/jmir_v27i1e64749_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/02eedf4c0e3c/jmir_v27i1e64749_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/2de9d15b4bc5/jmir_v27i1e64749_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/12226dd18891/jmir_v27i1e64749_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/2e29fc5ee185/jmir_v27i1e64749_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/50f500acf43a/jmir_v27i1e64749_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/02eedf4c0e3c/jmir_v27i1e64749_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/818a/11826953/2de9d15b4bc5/jmir_v27i1e64749_fig5.jpg
摘要

背景

很少有研究使用移动应用程序的每日数据来探究常量营养素摄入与睡眠结果之间的关系。

目的

这项横断面研究旨在考察常量营养素、饮食成分与睡眠参数之间的关联,并考虑它们之间的相互依存关系。

方法

我们分析了4825名使用《宝可梦睡眠》和Asken智能手机应用程序的用户的数据,每个应用程序分别用于记录客观睡眠参数和饮食成分,且使用时间至少为7天。多变量回归探究了常量营养素(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)四分位数、饮食成分(钠、钾、膳食纤维和钠钾比)与睡眠变量(总睡眠时间[TST]、睡眠潜伏期[SL]和睡眠开始后清醒时间百分比[%WASO])之间的关联。摄入量最低的组作为参照。成分数据分析考虑了常量营养素的相互依存关系。模型对年龄、性别和BMI进行了调整。

结果

蛋白质摄入量增加与第三四分位数(+0.17,95%CI 0.09 - 0.26小时)和第四四分位数(+0.18,95%CI 0.09 - 0.27小时)的总睡眠时间延长相关。相比之下,脂肪摄入量增加与第三四分位数(-0.11,95%CI -0.20至-0.27小时)和第四四分位数(-0.16,95%CI -0.25至-0.07小时)的总睡眠时间缩短相关。碳水化合物摄入量增加与第三四分位数(-0.82%,95%CI -1.37%至-0.26%)和第四四分位数(-0.57%,95%CI -1.13%至-0.01%)的%WASO缩短相关,而脂肪摄入量增加与第四四分位数的%WASO延长相关(+0.62%,95%CI 0.06% - 1.18%)。膳食纤维摄入量与总睡眠时间延长和睡眠潜伏期缩短相关。钠钾比增加与第三四分位数(-0.11,95%CI -0.20至-0.02小时)和第四四分位数(-0.19,95%CI -0.28至-0.10小时)的总睡眠时间缩短相关;与第二四分位数(+1.03,95%CI 0.08 - 1.98分钟)和第四四分位数(+1.50,95%CI 0.53 - 2.47分钟)的睡眠潜伏期延长相关;与第四四分位数的%WASO延长相关(0.71%,95%CI 0.15% - 1.28%)。成分数据分析涉及常量营养素比例6%的变化,结果显示蛋白质摄入量增加与总睡眠时间延长相关(+0.27,95%CI 0.18 - 0.35小时),而单不饱和脂肪摄入量增加与睡眠潜伏期延长(+4.6,95%CI 1.93 - 7.34分钟)和%WASO增加(+2.2%,95%CI 0.63% - 3.78%)相关。相比之下,多不饱和脂肪摄入量增加与总睡眠时间缩短(-0.22,95%CI -0.39至-0.05小时)、睡眠潜伏期缩短(-4.7,95%CI -6.58至-2.86分钟)和%WASO缩短(+2.0%,95%CI -3.08%至-0.92%)相关。

结论

蛋白质和膳食纤维摄入量增加与总睡眠时间延长相关,而脂肪摄入量增加和钠钾比与总睡眠时间缩短和WASO延长相关。用蛋白质替代其他营养素增加摄入量与总睡眠时间延长相关,而多不饱和脂肪摄入量增加可改善睡眠潜伏期并减少WASO。

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