Self-managed Weight Loss by Smart Body Fat Scales Ameliorates Obesity-related Body Composition During the COVID-19 Pandemic: A Follow-up Study in Chinese Population

Overview

Journal Front Endocrinol (Lausanne)

Specialty Endocrinology

Date 2022 Nov 28

PMID 36440229

Authors

Xinru Huang

Mingjie Li

Yefei Shi

Hongyun Yao

Zhijun Lei

Wenxin Kou

Bo Li

Jiayun Shi

Weiwei Zhang

Weixia Jian

Affiliations

Soon will be listed here.

Abstract

Background: Since 2020, longer stay-at-home time in response to the coronavirus disease 2019 (COVID-19) pandemic has changed the weight-related behaviors of Chinese population.

Objectives: To explore the demographic and basic characteristics of body fat scale users and to investigate the changes in obesity-related body composition of overweight and obese users during COVID-19. Further, we analyzed the factors associated with successful weight loss and improved body composition changes in overweight and obese people.

Methods: The study included 107,419 Chinese adults registered in the smart app connecting to the body fat scale in 2020 to describe the demographic characteristics of body fat scale users by Unpaired Student's t-test and Chi-Square test. Subsequently, overweight and obese participants with body mass index (BMI) of more than 24 kg/m were screened to investigate the independent factors associated with effective weight loss and improved body composition changes by multivariable logistic regression analyses.

Results: During the pandemic, the number of body fat scale users increased markedly compared with pre-pandemic. Over half of the participants were women and with normal baseline BMI. Based on BMI classification, multivariable logistic regressions showed that age, gender, measurement frequency classification, baseline BMI, visceral adipose index and skeletal muscle rate were associated with weight loss and fat loss in the overweight and obese population, with the high-frequency measurement being the most important factor for effective weight and fat loss. In the population with normal BMI obesity, younger age was the most significant factor for effective fat loss.

Conclusion: During the COVID-19 pandemic, participation in self-monitored weight loss increased markedly compared with pre-pandemic, and women accounted for the majority. We found that many overweight and obese participants achieved weight loss goals by smart body fat scales, and the effectiveness of weight and fat loss was greater in obese participants than in overweight participants, both based on BMI and PBF classification. In addition, promoting the usage of smart body fat scales could contribute to more effective weight and fat loss in the overweight and obese population based on BMI classification. However, in the population with normal BMI obesity, young subjects might be easier to successfully lose fat compared with the elder. Digital self-management by smart body fat scales could become a promising approach for the obese population with high BMI to lose weight and keep healthy.

Citing Articles

Weight Loss Using an mHealth App Among Individuals With Obesity in Different Economic Regions of China: Cohort Study.

Huang X, Shi Y, Yao H, Li M, Lei Z, Shi J JMIR Mhealth Uhealth. 2024; 12:e48675.

PMID: 38297510 PMC: 10851113. DOI: 10.2196/48675.

References

Jin M, Du H, Zhang Y, Zhu H, Xu K, Yuan X . Characteristics and reference values of fat mass index and fat free mass index by bioelectrical impedance analysis in an adult population. Clin Nutr. 2018; 38(5):2325-2332. DOI: 10.1016/j.clnu.2018.10.010. View

Lear S, James P, Ko G, Kumanyika S . Appropriateness of waist circumference and waist-to-hip ratio cutoffs for different ethnic groups. Eur J Clin Nutr. 2009; 64(1):42-61. DOI: 10.1038/ejcn.2009.70. View

Sharma S, Batsis J, Coutinho T, Somers V, Hodge D, Carter R . Normal-Weight Central Obesity and Mortality Risk in Older Adults With Coronary Artery Disease. Mayo Clin Proc. 2016; 91(3):343-51. DOI: 10.1016/j.mayocp.2015.12.007. View

Wang Y, Min J, Khuri J, Xue H, Xie B, Kaminsky L . Effectiveness of Mobile Health Interventions on Diabetes and Obesity Treatment and Management: Systematic Review of Systematic Reviews. JMIR Mhealth Uhealth. 2020; 8(4):e15400. PMC: 7218595. DOI: 10.2196/15400. View

Hu Z, Lin X, Kaminga A, Xu H . Impact of the COVID-19 Epidemic on Lifestyle Behaviors and Their Association With Subjective Well-Being Among the General Population in Mainland China: Cross-Sectional Study. J Med Internet Res. 2020; 22(8):e21176. PMC: 7458584. DOI: 10.2196/21176. View

Magkos F, Fraterrigo G, Yoshino J, Luecking C, Kirbach K, Kelly S . Effects of Moderate and Subsequent Progressive Weight Loss on Metabolic Function and Adipose Tissue Biology in Humans with Obesity. Cell Metab. 2016; 23(4):591-601. PMC: 4833627. DOI: 10.1016/j.cmet.2016.02.005. View

Brindal E, Hendrie G, Freyne J, Noakes M . A Mobile Phone App Designed to Support Weight Loss Maintenance and Well-Being (MotiMate): Randomized Controlled Trial. JMIR Mhealth Uhealth. 2019; 7(9):e12882. PMC: 6834303. DOI: 10.2196/12882. View

Gomez-Ambrosi J, Silva C, Galofre J, Escalada J, Santos S, Gil M . Body adiposity and type 2 diabetes: increased risk with a high body fat percentage even having a normal BMI. Obesity (Silver Spring). 2011; 19(7):1439-44. DOI: 10.1038/oby.2011.36. View

Zhang J, Zhao A, Ke Y, Huo S, Ma Y, Zhang Y . Dietary Behaviors in the Post-Lockdown Period and Its Effects on Dietary Diversity: The Second Stage of a Nutrition Survey in a Longitudinal Chinese Study in the COVID-19 Era. Nutrients. 2020; 12(11). PMC: 7693097. DOI: 10.3390/nu12113269. View

10.

Marini S, Merino J, Montgomery B, Malik R, Sudlow C, Dichgans M . Mendelian Randomization Study of Obesity and Cerebrovascular Disease. Ann Neurol. 2020; 87(4):516-524. PMC: 7392199. DOI: 10.1002/ana.25686. View

11.

Avgerinos K, Spyrou N, Mantzoros C, Dalamaga M . Obesity and cancer risk: Emerging biological mechanisms and perspectives. Metabolism. 2018; 92:121-135. DOI: 10.1016/j.metabol.2018.11.001. View

12.

Flores Mateo G, Granado-Font E, Ferre-Grau C, Montana-Carreras X . Mobile Phone Apps to Promote Weight Loss and Increase Physical Activity: A Systematic Review and Meta-Analysis. J Med Internet Res. 2015; 17(11):e253. PMC: 4704965. DOI: 10.2196/jmir.4836. View

13.

Chen W, Jiang H, Yang J, Yang H, Liu J, Zhen X . Body Composition Analysis by Using Bioelectrical Impedance in a Young Healthy Chinese Population: Methodological Considerations. Food Nutr Bull. 2017; 38(2):172-181. DOI: 10.1177/0379572117697534. View

14.

Pan X, Wang L, Pan A . Epidemiology and determinants of obesity in China. Lancet Diabetes Endocrinol. 2021; 9(6):373-392. DOI: 10.1016/S2213-8587(21)00045-0. View

15.

. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004; 363(9403):157-63. DOI: 10.1016/S0140-6736(03)15268-3. View

16.

van Rinsum C, Gerards S, Rutten G, van de Goor I, Kremers S . The coaching on lifestyle (CooL) intervention for obesity, a study protocol for an action-oriented mixed-methods study. BMC Public Health. 2018; 18(1):117. PMC: 5759228. DOI: 10.1186/s12889-017-5010-4. View

17.

Patel M, Wakayama L, Bennett G . Self-Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity. Obesity (Silver Spring). 2021; 29(3):478-499. DOI: 10.1002/oby.23088. View

18.

Manrique-Acevedo C, Chinnakotla B, Padilla J, Martinez-Lemus L, Gozal D . Obesity and cardiovascular disease in women. Int J Obes (Lond). 2020; 44(6):1210-1226. PMC: 7478041. DOI: 10.1038/s41366-020-0548-0. View

19.

Oliveros E, Somers V, Sochor O, Goel K, Lopez-Jimenez F . The concept of normal weight obesity. Prog Cardiovasc Dis. 2014; 56(4):426-33. DOI: 10.1016/j.pcad.2013.10.003. View

20.

Richardson S, Hirsch J, Narasimhan M, Crawford J, McGinn T, Davidson K . Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA. 2020; 323(20):2052-2059. PMC: 7177629. DOI: 10.1001/jama.2020.6775. View