■随着肥胖患病率的增加,在中国,减肥已经成为一个关键问题。通过移动健康(mHealth)应用程序进行自我管理的减肥可能是一种前瞻性方法。然而,它在中国不同经济区域的实用性是未知的。
本研究旨在评估通过mHealth应用程序在中国不同经济地区肥胖人群中进行自我管理减肥的有效性,并证明在线自我管理减肥的可行性。
■共有165,635名报名参加mHealthapp的中国成年人被纳入,通过χ2分析分析来自不同经济地区的个体的身体成分特征。此外,使用mHealth监测的2种类型的肥胖参与者,包括74,611名BMI≥24.0kg/m2的参与者和22,903名BMI正常但体内脂肪百分比(PBF)过多的参与者,随访6个月,以探索中国不同经济地区的减肥和减脂效应,并通过双尾t检验和多变量logistic回归分析找到与减肥成功相关的独立预测因素。
■有来自低收入地区的32,129个用户和来自高收入地区的133,506个用户。低收入地区肥胖使用者比例高于高收入地区,两者均基于BMI(15,378/32,129,47.9%vs59,233/133,506,44.4%;P<.001)和PBF分类(19,146/32,129,59.6%vs72,033/133,506,54%;P<.001)。随访分析显示,低收入地区超重或肥胖参与者的减肥效果大于高收入地区(平均值-4.93,SD6.41vs平均值-4.71,SD6.14kg;P<.001)。而脂肪损失没有显著差异(平均-2.06%,SD3.14%与平均值-2.04%,SD3.19%;P=.54)。在体重正常的肥胖人群中,体重减轻(平均值-2.42,SD4.07与平均值-2.23,SD4.21kg;P=.004)和脂肪损失效应(平均值-1.43%,SD2.73%与平均值-1.27%,SD2.63%;P<.001)高收入地区强于低收入地区。此外,多变量Logistic回归分析表明,年龄,基线PBF,骨骼肌率,测量频率与体重减轻有关,而性别和基线身体代谢率仅显示与高收入地区人群的体重减轻相关.
■这项研究发现,在低收入地区,患有肥胖症的mHealthapp用户比例很高。在中国不同经济地区,超重和肥胖的人使用mHealth应用程序经历了显着的体重减轻和脂肪减少。此外,高收入地区的个体更重视体脂,减脂效果更好。因此,通过mHealth应用程序促进体重和PBF的自我监测可能是一项重要的干预措施,可以在中国所有地区实施。
UNASSIGNED: With the increasing prevalence of obesity, weight loss has become a critical issue in China. Self-managed weight loss through a mobile health (mHealth) app may be a prospective method. However, its practicability in different economic regions of China is unknown.
UNASSIGNED: This study aims to evaluate the effectiveness of self-managed weight loss through an mHealth app among individuals with obesity in different economic regions of China and to demonstrate the feasibility of online self-management for weight loss.
UNASSIGNED: A total of 165,635 Chinese adults who signed up for the mHealth app were included to analyze the body composition characteristics of individuals from different economic regions by χ2 analyses. Furthermore, 2 types of participants with obesity using mHealth monitoring, including 74,611 participants with a BMI ≥24.0 kg/m2 and 22,903 participants with a normal BMI but an excessive percentage of body fat (PBF), were followed for 6 months to explore the weight loss and fat loss effects in different economic regions of China and to find independent predictors associated with weight loss success by 2-tailed Student t test and multivariable logistic regression analysis.
UNASSIGNED: There were 32,129 users from low-income regions and 133,506 users from high-income regions. The proportion of users with obesity in low-income regions was higher than in high-income regions, both based on BMI (15,378/32,129, 47.9% vs 59,233/133,506, 44.4%; P<.001) and PBF classification (19,146/32,129, 59.6% vs 72,033/133,506, 54%; P<.001). Follow-up analyses showed that the weight loss effect among participants with overweight or obesity in low-income regions was greater than in high-income regions (mean -4.93, SD 6.41 vs mean -4.71, SD 6.14 kg; P<.001), while there was no significant difference in fat loss (mean -2.06%, SD 3.14% vs mean -2.04%, SD 3.19%; P=.54). In the population with normal-weight obesity, the weight loss (mean -2.42, SD 4.07 vs mean -2.23, SD 4.21 kg; P=.004) and fat loss effects (mean -1.43%, SD 2.73% vs mean -1.27%, SD 2.63%; P<.001) were stronger in high-income regions than in low-income regions. In addition, multivariable logistic regression analyses showed that age, baseline PBF, skeletal muscle rate, and measurement frequency were related to weight loss, whereas gender and baseline body metabolic rate only showed a correlation with weight loss in the population in high-income regions.
UNASSIGNED: This study found a high proportion of mHealth app users with obesity in low-income regions. Individuals with overweight and obesity in different economic regions of China experienced significant weight loss and fat loss using an mHealth app. Moreover, individuals in high-income regions paid more attention to body fat and had better fat reduction effects. Therefore, promoting self-monitoring of weight and PBF through an mHealth app could be an important intervention that could be implemented across all regions of China.