This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.
Some studies on weight loss promotion using smartphone apps have shown a weight loss effect but not an increase in physical activity. However, the long-term effects of smartphone apps on weight loss and increasing physical activity have not been rigorously examined to date.
The aim of this study was to assess whether the use of a smartphone app will increase physical activity and reduce body weight.
In this parallel randomized clinical trial, participants recruited between April 2018 and June 2019 were randomized in equal proportions to a smartphone app group (n=55) or a control group (n=54). The intention-to-treat approach was used to analyze the data from December 2019 through November 2021. Before the intervention, an hour-long lecture on weight loss instruction and increasing physical activity was conducted once for both groups. Participants in both groups were instructed to weigh themselves immediately after waking up at least once daily from the start of the intervention. Monthly emails were sent advising the participants in both groups on how to lose weight and increase physical activity in order to maintain or increase motivation. Participants in the smartphone app group were instructed to open the app at least once a day to check their step count and rank. The primary outcome was daily accelerometer-measured physical activity (step count) and the secondary outcome was body weight. Since there was a significant difference in the wear time of the accelerometer depending on the intervention period (
The mean age of the 109 participants in this study was 47 (SD 8) years. At baseline, the mean daily total steps were 7259 (SD 3256) steps per day for the smartphone app group and 8243 (SD 2815) steps per day for the control group. The difference in the step count per wear time between preintervention and postintervention was significantly different between the app group and the control group (average difference [95% CI], 65 [30 to 101] steps per hour vs –9 [–56 to 39] steps per hour;
In this trial, the group with the smartphone app intervention showed increased physical activity, especially on weekends. However, this increased physical activity did not lead to increased weight loss.
University Hospital Medical Information Network UMIN000033397; https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000037956
Physical inactivity–related deaths contribute to US $13.7 billion in productivity losses, and physical inactivity is responsible for 13.4 million disability-adjusted life-years worldwide [
Recently, the use of mobile apps has led to notable success in increasing physical activity [
The purpose of this study was to determine whether using a mobile app would promote increased physical activity and weight loss after 32 weeks of the intervention. In addition, we aimed to assess the intraweek variability of physical activity during the intervention period and to evaluate the impact of using or not using the app.
The participants in this study were recruited using a web portal for municipal employees according to the following inclusion criteria: (1) age, 30-60 years, (2) gained more weight than the weight at 20 years of age, (3) BMI>20 kg/m2, and (4) possession of a smartphone. Participants with any disease and who could not obtain permission from their physicians were excluded from the study. The calculated sample size of 102 participants was determined based on a previous study [
This study was conducted in accordance with the guidelines of the Consolidated Standards of Reporting Trials (CONSORT). This study followed the guidelines of the Declaration of Helsinki and was approved by the ethics committee for Clinical Research of the Prefectural University of Kumamoto (approval 30-30,01-20) and the ethics committee of the National Institutes of Biomedical Innovation, Health and Nutrition (approval 122-01). Informed consent was obtained from all the participants in this study. The protocol was registered in the University Hospital Medical Information Network (UMIN000033397).
Before the intervention, EY gave both groups 1-hour group-based lectures on weight loss and increasing physical activity. The in-person lecture sessions consisted of 7 domains that focused on the following: (1) the benefits and barriers to engaging in health behaviors, (2) the health benefits of increased physical activity and weight loss, (3) how to calculate energy expenditure by activity intensity, (4) the amount of energy contained in cooked foods and seasonings, (5) how to set a goal of +1000 steps/day (increase walking time by approximately 10 minutes) of increased step count from participants’ current (preintervention period) daily step counts, (6) how to set a weight loss goal of –5% from the participant’s current body weight, and (7) healthy diet and weight maintenance. The participants’ body weight and physical activity were measured for 3 consecutive weeks before and during the intervention (10-12 weeks and 30-32 weeks, respectively). Preintervention evaluations were assessed during the 3 weeks before the intervention began. In addition, dietary intake was assessed during the evaluation period using a questionnaire to assess the average amount of food consumed in the past month. Participants in both groups were instructed to weigh themselves immediately after waking up at least once daily from the start of the intervention. Monthly emails were sent advising the participants in both groups on how to lose weight and to increase physical activity to maintain or increase motivation. In the app group, a smartphone app (present in both Apple and Android smartphones) capable of managing the tracking steps [
Height was measured using digital scales with a stadiometer to the nearest 0.1 cm (BW-306, Yamato scale) before the intervention period. The body weights of the participants were measured with a body composition monitor to the nearest 50 g (BC-308, Tanita). The participants were instructed to weigh themselves at least once a day, and the time of weighing was to be measured every day within an hour of waking up in the morning, wearing as similar clothes as possible and under fasting conditions. The measured weight and time data were recorded on the Secure Digital card built into the body composition monitor. BMI was calculated as weight (kg) divided by height (in m2).
Physical activity was measured for 3 weeks [
Food intake was assessed using a validated brief self-administered diet history questionnaire [
Changes in the body weight during the intervention are shown as raw data and as a moving average over a week. The demographic variables were assessed using independent sample two-sided
The flowchart of the participants included in this study is shown in
Study flow diagram.
Study protocol. Wk: weeks.
The baseline data of the 109 participants by their group are shown in
The effects of the intervention on body weight and physical activity before and after the intervention are shown in
Baseline information of the participants (N=109).
|
Smartphone app group |
Control group |
|||||
|
|||||||
|
Women, n (%) | 26 (47) | 24 (44) | .85 | |||
|
Age (years), mean (SD) | 47 (8) | 47 (8) | .93 | |||
|
Body weight (kg), mean (SD) | 71.0 (13.9) | 70.0 (13.0) | .69 | |||
|
BMI (kg/m2), mean (SD) | 25.9 (4.1) | 25.3 (3.6) | .46 | |||
|
Step counts (steps/day), mean (SD) | 7259 (3256) | 8243 (2815) | .09 | |||
|
Activity time of 1.5 METsa (min/day), mean (SD) | 571.5 (99.6) | 603.5 (109.5) | .11 | |||
|
Activity time of 1.6-2.9 METs (min/day), mean (SD) | 302.2 (79.9) | 289.3 (69.6) | .37 | |||
|
Activity time of over 3.0 METs (min/day), mean (SD) | 55.2 (25.2) | 61.5 (23.8) | .18 | |||
|
Activity time of 1.5 METs (%), mean (SD) | 61.4 (8.7) | 62.9 (6.6) | .31 | |||
|
Activity time of 1.6-2.9 METs (%), mean (SD) | 32.7 (8.0) | 30.5 (6.2) | .13 | |||
|
Activity time of over 3.0 METs (%), mean (SD) | 6.0 (2.7) | 6.6 (2.6) | .25 | |||
|
Energy intake (kcal/day), mean (SD) | 2005 (649) | 1857 (624) | .23 | |||
|
Protein (%), mean (SD) | 14.6 (2.9) | 15.5 (2.6) | .08 | |||
|
Fat (%), mean (SD) | 27.8 (5.1) | 28.9 (5.6) | .29 | |||
|
Carbohydrate (%), mean (SD) | 57.6 (7.1) | 55.5 (7.6) | .16 | |||
|
|||||||
|
Overweight/obeseb | 25 (45) | 22 (41) | .70 | |||
|
Obesec | 8 (15) | 7 (13) | >.99 | |||
|
Hypertension | 5 (9) | 6 (11) | .76 | |||
|
Dyslipidemia | 1 (2) | 4 (7) | .21 | |||
|
Diabetes | 1 (2) | 0 (0) | >.99 | |||
|
Current smoker | 2 (4) | 5 (9) | .27 |
aMET: metabolic equivalent.
bBMI≥25 kg/m2.
cBMI≥30 kg/m2.
Changes in body weight during the intervention period (32 weeks). The change in the body weight of the participants is shown by the solid line for the smartphone app group and the dotted line for the control group. (A) Values are shown as average and (B) as the moving average over 1 week. The change in body weight before and after the intervention (preintervention, 12 weeks, and 32 weeks) was not significantly different between the groups.
Intraweek variation in (A) body weight, (B) step counts, and (C) moderate-to-vigorous physical activity before the intervention. Missing data were taken into account and analyzed using two-way repeated measures mixed analysis of variance to examine the interaction between the groups. Values are presented as means and standard errors. MVPA: moderate-to-vigorous physical activity.
Intervention effects on body weight, physical activity, and dietary intake before and after intervention.
|
Smartphone app group | Control group | Group × |
||||||||||||||
|
Preintervention, mean (95% CI) | 12 weeks, mean (95% CI) | 32 weeks, mean (95% CI) | Preintervention, mean (95% CI) | 12 weeks, mean (95% CI) | 32 weeks, mean (95% CI) |
|
||||||||||
|
|||||||||||||||||
|
Body weight (kg) | 70.9 (67.4-74.5) | 68.8 (65.3-72.4) | 68.8 (65.2-72.3) | 70.0 (66.4-73.5) | 68.0 (64.4-71.6) | 67.8 (64.2-71.4) | .94 | |||||||||
|
Step count (steps/day) | 7259 (6335-8183) | 7850 (6921-8779) | 7846 (6910-8782) | 8243 (7465-9021) | 8143 (7346-8940) | 7806 (6998-8615) | .06 | |||||||||
|
Step counts per wear time (steps/h/day) | 473 (408-538) | 527 (462-592) | 538 (473-604) | 525 (472-579) | 528 (4737-583) | 517 (461-572) | .04 | |||||||||
|
MVPAa (min/day) | 55 (48-62) | 58 (51-65) | 62 (55-69) | 62 (55-68) | 60 (54-67) | 59 (52-65) | .05 | |||||||||
|
MVPA per wear time (min/h/day) | 4 (3-4) | 4 (3-4) | 4 (4-5) | 4 (3-4) | 4 (3-4) | 4 (3-4) | .03 | |||||||||
|
Energy |
2005 (1844-2166) | 1783 (1621-1946) | 1836 (1673-2000) | 1857 (1694-2020) | 1718 (1553-1883) | 1758 (1593-1923) | .66 | |||||||||
|
Protein (%) | 14.6 (13.8-15.4) | 15.6 (14.8-16.4) | 15.5 (14.7-16.3) | 15.5 (14.7-16.3) | 16.1 (15.3-16.9) | 16.1 (15.3-16.9) | .65 | |||||||||
|
Fat (%) | 27.8 (26.3-29.4) | 28.7 (27.1-30.2) | 27.5 (25.9-29.1) | 28.9 (27.3-30.5) | 29.5 (27.9-31.1) | 28.3 (26.7-29.9) | .96 | |||||||||
|
Carbohydrate (%) | 57.6 (55.4-59.7) | 55.7 (53.5-57.9) | 57 (54.8-59.2) | 55.5 (53.4-57.7) | 54.4 (52.2-56.6) | 55.7 (53.4-57.9) | .87 | |||||||||
|
|||||||||||||||||
|
Body weight (kg) | 70.6 (67.0-74.2) | 68.4 (64.9-71.9) | 68.4 (64.9-71.9) | 68.3 (64.7-72.0) | 66.4 (62.8-69.9) | 66.2 (62.6-69.7) | .90 | |||||||||
|
Step count (steps/day) | 7130 (6287-7972) | 7833 (6939-8728) | 7779 (6874-8685) | 8231 (7333-9129) | 8149 (7196-9103) | 7826 (6861-8791) | .05 | |||||||||
|
Step counts per wear time (steps/h/day) | 465 (408-522) | 527 (465-588) | 535 (467-602) | 526 (465-587) | 527 (462-592) | 520 (448-592) | .047 | |||||||||
|
MVPA (min/day) | 54 (48-61) | 58 (51-65) | 61 (54-68) | 61 (54-68) | 60 (53-67) | 59 (51-66) | .04 | |||||||||
|
MVPA per wear time (min/h/day) | 4 (3-4) | 4 (3-4) | 4 (4-5) | 4 (3-4) | 4 (3-4) | 4 (3-4) | .03 | |||||||||
|
Energy |
1966 (1800-2133) | 1759 (1600-1919) | 1811 (1677-1945) | 1851 (1680-2022) | 1704 (1539-1870) | 1752 (1576-1927) | .79 | |||||||||
|
Protein (%) | 14.8 (14.0-15.5) | 15.7 (14.9-16.6) | 15.6 (14.8-16.4) | 15.7 (15.0-16.4) | 16.2 (15.4-17.1) | 16.2 (15.3-17.0) | .68 | |||||||||
|
Fat (%) | 27.8 (26.4-29.2) | 28.7 (27.1-30.3) | 27.5 (25.8-29.2) | 28.8 (27.2-30.3) | 29.3 (27.6-30.9) | 28.0 (26.3-29.7) | .90 | |||||||||
|
Carbohydrate (%) | 57.4 (55.4-59.4) | 55.5 (53.2-57.9) | 56.9 (54.5-59.2) | 55.5 (53.4-57.6) | 54.5 (52.2-56.8) | 55.9 (53.5-58.2) | .81 |
aMVPA: moderate-to-vigorous physical activity.
Intraweek variation in (A) body weight, (B and C) step counts, and (D and E) moderate-to-vigorous physical activity during the intervention. Data were combined from 12 and 32 weeks to analyze the relationship between physical activity and intraweek variability. Missing data were taken into account and analyzed using two-way repeated-measures mixed analysis of variance to examine the interaction between the groups. Values are presented as means and standard errors. MVPA: moderate-to-vigorous physical activity.
The aim of this study was to determine the effects of using a mobile app on increasing physical activity and weight loss by assessing accelerometer data and weight loss data after 32 weeks of the app intervention. Our findings showed that the use of a step count–specific mobile app for the assessment of physical activity for weight loss might be effective in increasing the step count, although it may not affect the amount of weight loss. In addition, we found that the effects of using the mobile app on physical activity differed between weekends and weekdays and that the mobile app showed data of higher physical activity on weekends.
Flores Mateo et al [
Inconsistent with that reported in a meta-analysis [
Notably, we found that the effects of the mobile app on physical activity differed between weekends and weekdays, that is, the mobile app data showed higher physical activity on weekends. In a study on Japanese white-collar workers, the sedentary behavior time was significantly longer on weekdays than on weekends (598 min/day vs 479 min/day, respectively;
The dropout rate in our study was less than 10%, despite the long intervention period of 32 weeks, and there was no difference between the 2 groups. The reasons for this cannot be ascertained; however, intervention content such as monthly emails and feedback on the results may have had an impact. Continued participation in the intervention is an essential factor affecting the validation of intervention effectiveness and should be investigated in future studies.
This study has several limitations. First, all the participants in this study were prefectural employees, which limits the generalizability of the study. Second, although this study calculated the sample size and conducted an intervention, it is possible that sample size estimation was inadequate due to the lack of appropriate studies utilizing apps focused on step count and using physical activity and weight loss as outcomes. Future large-scale intervention studies are needed. Third, although the duration of the intervention in this study was longer compared to that in previous studies, it is necessary to examine the impact of the intervention for more than 1 year, and the influence of the seasons needs to be considered. Further, the use of the app may have affected the motivation for the intervention but could not be assessed in this study. Future studies should also evaluate the motivational impact of app use. Finally, it is necessary to develop support tools to increase not only the amount of physical activity but also the weight loss effect. However, the major strength of our study was the parallel randomized controlled trial design, which indicates that our findings are reliable.
In conclusion, this study shows that the use of a step count–specific mobile app during weight loss support might be effective in increasing the step count, although it might not affect the amount of weight loss. Moreover, we found that the effects of the mobile app on physical activity differed between weekends and weekdays, with the mobile app data showing higher physical activity on weekends. Future studies need to focus on the development of methods for increasing the effectiveness of physical activity and weight loss by using mobile apps.
Changes in body composition and blood glucose levels in physical examination findings. Missing data were considered and analyzed using one-way repeated-measures mixed analysis of variance. Values are presented as means and standard errors.
CONSORT-eHEALTH (V 1.6.1) checklist.
Consolidated Standards of Reporting Trials
metabolic equivalent
moderate-to-vigorous physical activity
This work was supported by the JST-Mirai Program (grant JP0000012) and a grant-in-aid for Scientific Research (C) (KAKENHI 20K02410) and (A) (KAKENHI 16H01877).
EY and ST conceptualized this study and the methodology. EY, ET, RM, NM, and YH performed the formal analysis. EY performed investigation, visualization, supervision, and project administration. EY, RM, and ET performed data curation. EY and YH performed the writing and original draft preparation, EY, ST, RM, NM, and YH reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.
None declared.