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. 2022 Sep 14;6(9):e40739.
doi: 10.2196/40739.

Agreement Between Clinically Measured Weight and Self-reported Weight Among Patients With Type 2 Diabetes Through an mHealth Lifestyle Coaching Program in Denmark: Secondary Analysis of a Randomized Controlled Trial

Albi Imeraj  1 , Thomas Bastholm Olesen  2 , Ditte Hjorth Laursen  3 , Jens Søndergaard  1 , Carl Joakim Brandt  1
Affiliations

Agreement Between Clinically Measured Weight and Self-reported Weight Among Patients With Type 2 Diabetes Through an mHealth Lifestyle Coaching Program in Denmark: Secondary Analysis of a Randomized Controlled Trial

Albi Imeraj et al. JMIR Form Res. .

Abstract

Background: Digital health interventions are increasingly used to handle and promote positive health behaviors. Clinical measures are often used, and a certain precision is essential for digital health interventions to have an effect. Only few studies have compared clinically measured weights with self-reported weights. No study has examined the validity of self-reported weight from a mobile app used in a tailored weight loss intervention.

Objective: The aim of this study was to analyze the agreement between clinically measured weight and self-reported weight collected from a mobile health lifestyle coaching program during a 12-month weight loss intervention for obese patients with and without type 2 diabetes. The secondary aim was to investigate the determinants for possible discrepancies between clinically measured and self-reported weights of these patients with different demographic and lifestyle characteristics and achievements of weight loss goals.

Methods: Weight registrations were collected from participants (N=104) in a Danish randomized controlled trial examining the effect of a digital lifestyle intervention on weight loss among obese patients with and without type 2 diabetes. Data were collected at baseline and after 6 and 12 months. Self-reported weight was measured at home and registered in the app.

Results: Self-reported body weight was lower than the weight measured in the clinic after 6 months by 1.03 kg (95% CI 1.01-1.05; P<.001) and after 12 months also by 1.03 kg (95% CI 0.99-1.04; P<.001). After 6 months, baseline weight and BMI were associated with a discrepancy of 0.03 kg (95% CI 0.01-0.04; P=.01) and 0.09 kg (95% CI 0.02-0.17; P=.02) per increment of 1 kg and 1 kg/m2, respectively, between clinically measured weight and self-reported weight. Weight change during the first 6 months was also associated with a difference of 0.1 kg (95% CI 0.04-0.01; P<.001) per kilogram of difference in weight between clinically measured weight and self-reported weight. Participants who did not achieve the 5% weight loss goal underestimated their weight by 0.79 kg (95% CI 0.34-1.23) at 6 months. After 12 months, only baseline weight was associated with a discrepancy of 0.03 kg (95% CI 0.01-0.05; P=.02) per increment of kilogram between clinically measured weight and self-reported weight. None of the other factors showed any significant discrepancy after 12 months.

Conclusions: Self-reported weight obtained from mobile health is a valid method for collecting anthropometric measurements.

Trial registration: ClinicalTrials.gov NCT03788915; https://clinicaltrials.gov/ct2/show/NCT03788915.

Keywords: body weight; diabetes; digital behavioral coaching; lifestyle change; mobile intervention; obesity; patient engagement; self-report; telemedicine; validation.

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Conflict of interest statement

Conflicts of Interest: CJB owns stock in Liva Healthcare A/S and originally cofounded Liva Healthcare A/S, the company that developed parts of the technical platform. CJB works currently at the Research Unit for General Practice at University of Southern Denmark. DHL is employed at Liva Healthcare A/S. DHL, TBO, JS, and AI have no financial interests in Liva Healthcare A/S or any other aspects of this study.

Figures

Figure 1
Figure 1
Screenshots of the Liva Healthcare app showing certain features, including weight measurement, tracking, and weight goals.
Figure 2
Figure 2
Participant flow during the study.
Figure 3
Figure 3
(A-B) Linear regression (95% CI) of measured and self-reported weights after 6 and 12 months of clinical follow-up. (C-D) Bland-Altman plot of difference between measured and self-reported weights (y-axis) in relation to the average of measured weight (x-axis) after 6 and 12 months of clinical follow-up. The solid area shows mean difference (2 SD) and the dashed line shows differences equal to zero. A negative sign in difference indicates overestimation. A positive sign indicates underestimation of self-reported weight.
Figure 4
Figure 4
Scatter plots with fitted lines at 6 and 12 months of clinical follow-up grouped by baseline weight.
Figure 5
Figure 5
Scatter plots with fitted lines at 6 and 12 months of clinical follow-up grouped by baseline BMI.
Figure 6
Figure 6
Scatter plots with fitted lines at 6 and 12 months of clinical follow-up grouped by weight changes during the intervention.
See this image and copyright information in PMC

References

    1. World Health Organization‎. Geneva: World Health Organization‎; 2014. Global status report on noncommunicable diseases.
    1. Afshin A, Babalola D, Mclean M, Yu Z, Ma W, Chen C, Arabi M, Mozaffarian D. Information Technology and Lifestyle: A Systematic Evaluation of Internet and Mobile Interventions for Improving Diet, Physical Activity, Obesity, Tobacco, and Alcohol Use. J Am Heart Assoc. 2016 Aug 31;5(9):e003058. doi: 10.1161/JAHA.115.003058. http://jaha.ahajournals.org/cgi/pmidlookup?view=long&pmid=27581172 JAHA.115.003058 - DOI - PMC - PubMed
    1. Ried-Larsen M, Christensen R, Hansen KB, Johansen MY, Pedersen M, Zacho M, Hansen LS, Kofoed K, Thomsen K, Jensen MS, Nielsen RO, MacDonald C, Langberg H, Vaag AA, Pedersen BK, Karstoft K. Head-to-head comparison of intensive lifestyle intervention (U-TURN) versus conventional multifactorial care in patients with type 2 diabetes: protocol and rationale for an assessor-blinded, parallel group and randomised trial. BMJ Open. 2015 Dec 09;5(12):e009764. doi: 10.1136/bmjopen-2015-009764. https://bmjopen.bmj.com/lookup/pmidlookup?view=long&pmid=26656025 bmjopen-2015-009764 - DOI - PMC - PubMed
    1. Johansen MY, MacDonald CS, Hansen KB, Karstoft K, Christensen R, Pedersen M, Hansen LS, Zacho M, Wedell-Neergaard A, Nielsen ST, Iepsen UW, Langberg H, Vaag AA, Pedersen BK, Ried-Larsen M. Effect of an Intensive Lifestyle Intervention on Glycemic Control in Patients With Type 2 Diabetes: A Randomized Clinical Trial. JAMA. 2017 Aug 15;318(7):637–646. doi: 10.1001/jama.2017.10169. https://europepmc.org/abstract/MED/28810024 2648632 - DOI - PMC - PubMed
    1. Diabetes Prevention Program (DPP) Research Group. Hamman RF, Horton E, Barrett-Connor E, Bray GA, Christophi CA, Crandall J, Florez JC, Fowler S, Goldberg R, Kahn SE, Knowler WC, Lachin JM, Murphy MB, Venditti E. Factors affecting the decline in incidence of diabetes in the Diabetes Prevention Program Outcomes Study (DPPOS) Diabetes. 2015 Mar;64(3):989–98. doi: 10.2337/db14-0333. https://europepmc.org/abstract/MED/25277389 db14-0333 - DOI - PMC - PubMed

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