Study on the Optimal Time-use Composition of 24-hour Movement Behaviors for Obesity Prevention in College Students

doi:10.12114/j.issn.1007-9572.2025.0174

Abstract

Abstract:

Background

Obesity has become an increasingly serious public health challenge in China, with a steadily rising prevalence. Studies have shown that 24-hour movement behaviors are closely associated with obesity. However, most current guidelines only provide separate time recommendations for individual behaviors without fully considering their interdependence and combined effects within a 24-hour framework.

Objective

To explore the associations between 24-hour movement behaviors and obesity-related outcomes among Chinese university students using the compositional data analysis approach, and to develop an optimal time-use composition for obesity prevention.

Methods

A total of 108 university students from Hangzhou were recruited. 24-hour movement behaviors were monitored using accelerometers. Anthropometric indicators including height, weight, and waist circumference (WC) were measured following standardized protocols, and BMI, waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were calculated. Body fat percentage (BFP) and visceral fat area (VFA) were assessed using the InBody 720 bioelectrical impedance analyzer. A compositional multiple regression model was constructed to estimate optimal time allocations and prediction intervals for different movement behaviors.

Results

The composition of 24-hour movement behaviors was significantly associated with obesity-related indicators among college students, including BMI (F=8.25, P<0.01), BFP (F=27.58, P<0.01), WC (F=13.90, P<0.01), WHR (F=13.10, P<0.01), WHtR (F=14.09, P<0.01), and VFA (F=7.04, P<0.01). The optimal 24-hour time-use composition for obesity prevention was identified as: 131 minutes of moderate-to-vigorous physical activity (MVPA)(110-140 min), 208 minutes of light physical activity (LPA) (160-230 min), 663 minutes of sedentary behavior(SB)(620-730 min), and 438 minutes of sleep (360-520 min).

Conclusion

The composition of 24-hour movement behaviors is closely associated with obesity-related indicators among college students. The optimal time-use composition developed in this study aligns with current guidelines for MVPA and sleep, while also providing recommendations for SB and LPA. These findings offer scientific evidence for the optimized allocation of daily activity time and the prevention of obesity in college populations.

Key words: Physical activity, 24-hour movement behaviors, Optimal time-use composition, College students, Obesity management

摘要：

背景

肥胖已成为我国日益严重的公共卫生挑战，患病率持续上升。研究表明，24 h活动行为与肥胖密切相关，但现有指南多对各活动行为分别提出推荐时间，尚未充分考虑其在24 h内的相互制约与协同作用。

目的

基于最佳时间使用成分数据分析方法，探讨24 h活动行为与大学生肥胖相关指标的关系，并构建预防肥胖的活动时间组合。

方法

采用方便抽样法，于2024年4—6月选取杭州师范大学108名大学生为研究对象进行测试调查。使用加速度计测量24 h活动行为；通过标准化工具测量身高、体重、腰围等指标，计算BMI、腰臀比、腰高比，并采用InBody 720分析仪测定体脂百分比和内脏脂肪面积。通过构建成分线性回归模型、生成预测活动行为时间组合、预测肥胖相关指标估计值等步骤确定最佳时间组合时长和区间。

结果

24 h活动行为组合与大学生BMI（F=8.25，P<0.01）、体脂百分比（F=27.58，P<0.01）、腰围（F=13.90，P<0.01）、腰臀比（F=13.10，P<0.01）、腰高比（F=14.09，P<0.01）及内脏脂肪面积（F=7.04，P<0.01）具有相关性。预防大学生肥胖相关指标的24 h活动最佳时间组合为：中高强度身体活动（MVPA）131 min（110~140 min）、低强度身体活动（LPA）208 min（160~230 min）、久坐行为（SB）663 min（620~730 min）和睡眠时间（SLP）438 min（360~520 min）。

结论

24 h活动行为组合与大学生肥胖相关指标关系密切。所构建的最佳时间组合中，MVPA和SLP的最佳时长与现有指南相符，并对SB和LPA时长提出了一定建议，该研究为大学生24 h身体活动行为时间分配的科学优化和肥胖的防控提供了科学依据。

关键词: 身体活动, 24小时活动行为, 最佳时间组合, 大学生, 肥胖管理

CHEN Xiaolong,JIN Jing,HUA Jialu, et al. Study on the Optimal Time-use Composition of 24-hour Movement Behaviors for Obesity Prevention in College Students[J]. Chinese General Practice, 2026, 29(12): 1525-1532. DOI: 10.12114/j.issn.1007-9572.2025.0174.
陈小龙,金晶,华佳禄等. 预防大学生肥胖的24 h活动行为最佳时间组合研究[J]. 中国全科医学, 2026, 29(12): 1525-1532. DOI: 10.12114/j.issn.1007-9572.2025.0174.

Figures/Tables 4

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变量	R²	P值	MVPA[B（SE）]	LPA[B（SE）]	SB[B（SE）]	SLP[B（SE）]
BMI	0.32	<0.01	-3.37（0.10）^a	-2.31（1.20）	4.38（2.37）	1.30（2.67）
BFP	0.56	<0.01	-8.63（2.10）^a	-4.43（2.42）	12.01（4.76）^a	0.94（5.39）
WC	0.46	<0.01	-9.49（2.30）^a	-7.20（2.77）^a	14.49（5.45）^a	2.20（6.18）
WHR	0.27	<0.01	-0.05（0.02）^a	-0.03（0.02）	0.06（0.04）	0.02（0.04）
WHtR	0.34	<0.01	-0.06（0.01）^a	-0.04（0.02）^a	0.07（0.03）	0.03（0.04）
VFA	0.23	<0.01	-31.57（8.84）^a	-13.68（20.91）	26.85（20.91）	18.40（23.71）

变量	R²	P值	MVPA[B（SE）]	LPA[B（SE）]	SB[B（SE）]	SLP[B（SE）]
BMI	0.32	<0.01	-3.37（0.10）^a	-2.31（1.20）	4.38（2.37）	1.30（2.67）
BFP	0.56	<0.01	-8.63（2.10）^a	-4.43（2.42）	12.01（4.76）^a	0.94（5.39）
WC	0.46	<0.01	-9.49（2.30）^a	-7.20（2.77）^a	14.49（5.45）^a	2.20（6.18）
WHR	0.27	<0.01	-0.05（0.02）^a	-0.03（0.02）	0.06（0.04）	0.02（0.04）
WHtR	0.34	<0.01	-0.06（0.01）^a	-0.04（0.02）^a	0.07（0.03）	0.03（0.04）
VFA	0.23	<0.01	-31.57（8.84）^a	-13.68（20.91）	26.85（20.91）	18.40（23.71）

变量	ilr模型（最佳时间使用）		最佳时间组合最佳时长（区间）（min/d）
变量	F值	P值	MVPA	LPA	SB	SLP
BMI	8.25	<0.01	129（100~140）	209（160~230）	667（620~740）	435（360~520）
BFP	27.58	<0.01	130（100~140）	207（150~230）	665（620~740）	438（360~530）
WC	13.90	<0.01	130（100~140）	204（140~230）	659（620~730）	448（360~540）
WHR	13.10	<0.01	131（110~140）	208（160~230）	674（620~760）	428（360~520）
WHtR	14.09	<0.01	130（100~140）	205（150~230）	662（620~740）	443（360~530）
VFA	7.04	<0.01	133（110~140）	200（130~230）	665（620~750）	433（360~550）
重叠最佳区域			131（110~140）	208（160~230）	663（620~730）	438（360~520）

变量	ilr模型（最佳时间使用）		最佳时间组合最佳时长（区间）（min/d）
变量	F值	P值	MVPA	LPA	SB	SLP
BMI	8.25	<0.01	129（100~140）	209（160~230）	667（620~740）	435（360~520）
BFP	27.58	<0.01	130（100~140）	207（150~230）	665（620~740）	438（360~530）
WC	13.90	<0.01	130（100~140）	204（140~230）	659（620~730）	448（360~540）
WHR	13.10	<0.01	131（110~140）	208（160~230）	674（620~760）	428（360~520）
WHtR	14.09	<0.01	130（100~140）	205（150~230）	662（620~740）	443（360~530）
VFA	7.04	<0.01	133（110~140）	200（130~230）	665（620~750）	433（360~550）
重叠最佳区域			131（110~140）	208（160~230）	663（620~730）	438（360~520）