Efficacy of an app-based multimodal lifestyle intervention on body weight in persons with obesity: results from a randomized controlled trial.


Journal

International journal of obesity (2005)
ISSN: 1476-5497
Titre abrégé: Int J Obes (Lond)
Pays: England
ID NLM: 101256108

Informations de publication

Date de publication:
28 Nov 2023
Historique:
received: 04 08 2023
accepted: 07 11 2023
revised: 24 10 2023
medline: 29 11 2023
pubmed: 29 11 2023
entrez: 28 11 2023
Statut: aheadofprint

Résumé

Despite an increasing number of smartphone applications (apps) addressing weight management, data on the effect of app-based multimodal obesity treatment approaches on weight loss is limited. This study aimed to examine the effect of a digital multimodal weight loss intervention program delivered by an app on body weight in persons with obesity. For this single-centre randomized controlled study, 168 adults with a body mass index (BMI) between 30.0 and 40.0 kg/m 64.3% of study participants were women, mean age was 46.8 ± 11.0 years, and mean BMI was 34.2 ± 2.8 kg/m Application of a multimodal app-based weight loss program results in moderate weight loss in persons with obesity. This study was registered in the German Clinical Trials Register (Registration number: DRKS00025291).

Sections du résumé

BACKGROUND BACKGROUND
Despite an increasing number of smartphone applications (apps) addressing weight management, data on the effect of app-based multimodal obesity treatment approaches on weight loss is limited. This study aimed to examine the effect of a digital multimodal weight loss intervention program delivered by an app on body weight in persons with obesity.
METHODS METHODS
For this single-centre randomized controlled study, 168 adults with a body mass index (BMI) between 30.0 and 40.0 kg/m
RESULTS RESULTS
64.3% of study participants were women, mean age was 46.8 ± 11.0 years, and mean BMI was 34.2 ± 2.8 kg/m
CONCLUSIONS CONCLUSIONS
Application of a multimodal app-based weight loss program results in moderate weight loss in persons with obesity.
TRIAL REGISTRATION BACKGROUND
This study was registered in the German Clinical Trials Register (Registration number: DRKS00025291).

Identifiants

pubmed: 38017117
doi: 10.1038/s41366-023-01415-0
pii: 10.1038/s41366-023-01415-0
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2023. The Author(s).

Références

Mensink GB, Schienkiewitz A, Haftenberger M, Lampert T, Ziese T, Scheidt-Nave C. Übergewicht und Adipositas in Deutschland: Ergebnisse der Studie zur Gesundheit Erwachsener in Deutschland (DEGS1) [Overweight and obesity in Germany: results of the German Health Interview and Examination Survey for Adults (DEGS1)]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2013;56:786–94.
doi: 10.1007/s00103-012-1656-3 pubmed: 23703499
Abdullah A, Peeters A, de Courten M, Stoelwinder J. The magnitude of association between overweight and obesity and the risk of diabetes: A meta-analysis of prospective cohort studies. Diabetes Res Clin Pract. 2010;89:309–19.
doi: 10.1016/j.diabres.2010.04.012 pubmed: 20493574
Wiseman M. The second World Cancer Research Fund/American Institute for Cancer Research expert report. Food, nutrition, physical activity, and the prevention of cancer: A global perspective. Proc Nutr Soc. 2008;67:253–6.
doi: 10.1017/S002966510800712X pubmed: 18452640
Carmienke S, Freitag MH, Pischon T, Schlattmann P, Fankhaenel T, Goebel H, et al. General and abdominal obesity parameters and their combination in relation to mortality: A systematic review and meta-regression analysis. Eur J Clin Nutr. 2013;67:573–85.
doi: 10.1038/ejcn.2013.61 pubmed: 23511854
Flegal KM, Kit BK, Orpana H, Graubard BI. Association of all-cause mortality with overweight and obesity using standard body mass index categories: A systematic review and meta-analysis. JAMA. 2013;309:71–82.
doi: 10.1001/jama.2012.113905 pubmed: 23280227 pmcid: 4855514
Semlitsch T, Stigler FL, Jeitler K, Horvath K, Siebenhofer A. Management of overweight and obesity in primary care: A systematic overview of international evidence-based guidelines. Obes Rev. 2019;20:1218–30.
doi: 10.1111/obr.12889 pubmed: 31286668 pmcid: 6852048
Villinger K, Wahl DR, Boeing H, Schupp HT, Renner B. The effectiveness of app-based mobile interventions on nutrition behaviours and nutrition-related health outcomes: A systematic review and meta-analysis. Obes Rev. 2019;20:1465–84.
doi: 10.1111/obr.12903 pubmed: 31353783 pmcid: 6852183
Federal Institute for Drugs and Medical Devices. Digital Health Applications (DiGA). Accessed 22 May. https://www.bfarm.de/EN/Medical-devices/Tasks/DiGA-and-DiPA/Digital-Health-Applications/_node.html .
Berman HB. Random Number Generator. Accessed 13 Jan 2023. https://stattrek.com/statistics/random-number-generator .
German Obesity Society (DAG) e. V., German Diabetes Society (DDG), German Society for Nutrition (DGE) e. V., German Society for Nutritional Medicine (DGEM). Interdisciplinary Quality Guideline S3 for “Prevention and Therapy” of Obesity - Long Version. State: 30.04.2014. Valid until: 30.04.2019 (currently undergoing revision).
Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: Building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013;46:81–95.
doi: 10.1007/s12160-013-9486-6 pubmed: 23512568
EuroQol Research Foundation. EQ-5D-5L User Guide. https://euroqol.org/publications/user-guides . 2019.
Fraser M eq5d: Methods for Analysing ‘EQ-5D’ Data and Calculating ‘EQ-5D’ Index Scores. Accessed 26 Apr 2023. https://github.com/fragla/eq5d .
Venkatesh V, Bala H. Technology Acceptance Model 3 and a Research Agenda on Interventions. Decis Sci. 2008;39:273–315.
doi: 10.1111/j.1540-5915.2008.00192.x
Brooke J. SUS - A quick and dirty usability scale. Usability Eval Ind. 1996;189:1–7.
Faul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behav Res Methods. 2009;41:1149–60.
doi: 10.3758/BRM.41.4.1149 pubmed: 19897823
Lugones-Sanchez C, Sanchez-Calavera MA, Repiso-Gento I, Adalia EG, Ramirez-Manent JI, Agudo-Conde C, et al. Effectiveness of an mHealth Intervention Combining a Smartphone App and Smart Band on Body Composition in an Overweight and Obese Population: Randomized Controlled Trial (EVIDENT 3 Study). JMIR Mhealth Uhealth. 2020;8:e21771.
doi: 10.2196/21771 pubmed: 33242020 pmcid: 7728540
Neter JE, Stam BE, Kok FJ, Grobbee DE, Geleijnse JM. Influence of weight reduction on blood pressure: A meta-analysis of randomized controlled trials. Hypertension. 2003;42:878–84.
doi: 10.1161/01.HYP.0000094221.86888.AE pubmed: 12975389
Anderson JW, Konz EC. Obesity and disease management: Effects of weight loss on comorbid conditions. Obes Res. 2001;9:326. https://doi.org/10.1038/oby.2001.138 .
doi: 10.1038/oby.2001.138
Morris E, Jebb SA, Oke J, Nickless A, Ahern A, Boyland E, et al. Effect of weight loss on cardiometabolic risk: Observational analysis of two randomised controlled trials of community weight-loss programmes. Br J Gen Pract. 2021;71:e312–e319.
doi: 10.3399/bjgp20X714113 pubmed: 33685923 pmcid: 7959667
Appel LJ, Clark JM, Yeh HC, Wang NY, Coughlin JW, Daumit G, et al. Comparative effectiveness of weight-loss interventions in clinical practice. N Engl J Med. 2011;365:1959–68.
doi: 10.1056/NEJMoa1108660 pubmed: 22085317 pmcid: 4074540
Shai I, Schwarzfuchs D, Henkin Y, Shahar DR, Witkow S, Greenberg I, et al. Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet. N Engl J Med. 2008;359:229–41.
doi: 10.1056/NEJMoa0708681 pubmed: 18635428
Thomas JG, Bond DS, Raynor HA, Papandonatos GD, Wing RR. Comparison of Smartphone-Based Behavioral Obesity Treatment With Gold Standard Group Treatment and Control: A Randomized Trial. Obesity. 2019;27:572–80.
doi: 10.1002/oby.22410 pubmed: 30779333
Roth L, Ordnung M, Forkmann K, Mehl N, Horstmann A. A randomized-controlled trial to evaluate the app-based multimodal weight loss program zanadio for patients with obesity. Obesity. 2023;31:1300–10.
doi: 10.1002/oby.23744 pubmed: 37140392
Svetkey LP, Batch BC, Lin PH, Intille SS, Corsino L, Tyson CC, et al. Cell phone intervention for you (CITY): A randomized, controlled trial of behavioral weight loss intervention for young adults using mobile technology. Obesity. 2015;23:2133–41.
doi: 10.1002/oby.21226 pubmed: 26530929
Wang C, Qi H. Influencing Factors of Acceptance and Use Behavior of Mobile Health Application Users: Systematic Review. Healthcare. 2021;9:357.
doi: 10.3390/healthcare9030357 pubmed: 33809828 pmcid: 8004182
Carter MC, Burley VJ, Nykjaer C, Cade JE. Adherence to a smartphone application for weight loss compared to website and paper diary: Pilot randomized controlled trial. J Med Internet Res. 2013;15:e32.
doi: 10.2196/jmir.2283 pubmed: 23587561 pmcid: 3636323
Lee K, Kwon H, Lee B, Lee G, Lee JH, Park YR, et al. Effect of self-monitoring on long-term patient engagement with mobile health applications. PLoS One. 2018;13:e0201166.
doi: 10.1371/journal.pone.0201166 pubmed: 30048546 pmcid: 6062090
Han M, Rhee SY. Effect of Adherence to Smartphone App Use on the Long-term Effectiveness of Weight Loss in Developing and OECD Countries: Retrospective Cohort Study. JMIR Mhealth Uhealth. 2021;9:e13496.
doi: 10.2196/13496 pubmed: 34255708 pmcid: 8314148
Andersen ES. Satiation in an evolutionary model of structural economic dynamics. J Evol Econ. 2001;11:143–64.
doi: 10.1007/PL00003852
Szinay D, Forbes CC, Busse H, DeSmet A, Smit ES, König LM. Is the uptake, engagement, and effectiveness of exclusively mobile interventions for the promotion of weight-related behaviors equal for all? A systematic review. Obes Rev. 2023;24:e13542.
doi: 10.1111/obr.13542 pubmed: 36625062
Patel ML, Wakayama LN, Bennett GG. Self-Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity. Obesity. 2021;29:478–99.
doi: 10.1002/oby.23088 pubmed: 33624440
Schirmann F, Kanehl P, Jones L. What Intervention Elements Drive Weight Loss in Blended-Care Behavior Change Interventions? A Real-World Data Analysis with 25,706 Patients. Nutrients. 2022;14. https://doi.org/10.3390/nu14142999 .

Auteurs

Kathrin Gemesi (K)

Institute for Nutritional Medicine, School of Medicine & Health, Technical University of Munich, Munich, Germany.

Stefanie Winkler (S)

Institute for Nutritional Medicine, School of Medicine & Health, Technical University of Munich, Munich, Germany.

Susanne Schmidt-Tesch (S)

Institute for Nutritional Medicine, School of Medicine & Health, Technical University of Munich, Munich, Germany.

Florian Schederecker (F)

Chair of Epidemiology, Department of Sport and Health Sciences, School of Medicine & Health, Technical University of Munich, Munich, Germany.

Hans Hauner (H)

Institute for Nutritional Medicine, School of Medicine & Health, Technical University of Munich, Munich, Germany.
Else Kröner Fresenius Center for Nutritional Medicine, ZIEL - Institute for Food and Health, Technical University of Munich, Freising, Germany.

Christina Holzapfel (C)

Institute for Nutritional Medicine, School of Medicine & Health, Technical University of Munich, Munich, Germany. christina.holzapfel@tum.de.
Department of Nutritional, Food and Consumer Sciences, Fulda University of Applied Sciences, Fulda, Germany. christina.holzapfel@tum.de.

Classifications MeSH