A Smartphone-Based Shopping Mall Walking Program and Daily Walking Steps

Yoko Matsuoka; Hiroaki Yoshida; Masamichi Hanazato

doi:10.1001/jamanetworkopen.2023.53957

. 2024 Jan 30;7(1):e2353957. doi: 10.1001/jamanetworkopen.2023.53957

A Smartphone-Based Shopping Mall Walking Program and Daily Walking Steps

Yoko Matsuoka ¹, Hiroaki Yoshida ¹, Masamichi Hanazato ^1,^2,^✉

¹Center for Preventive Medical Sciences, Chiba University, Chiba-shi, Chiba, Japan

²Design Research Institute, Chiba University, Sumida-ku, Tokyo, Japan

Accepted for Publication: December 2, 2023.

Published: January 30, 2024. doi:10.1001/jamanetworkopen.2023.53957

^✉

Corresponding Author: Masamichi Hanazato, PhD, Center for Preventive Medical Sciences, Chiba University, 1-33, Yayoicho, Inage-ku, Chiba-shi, Chiba, Japan (hanazato@chiba-u.jp).

Author Contributions: Dr Hanazato had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Matsuoka.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Matsuoka, Yoshida.

Obtained funding: All authors.

Administrative, technical, or material support: Yoshida, Hanazato.

Supervision: Hanazato.

Conflict of Interest Disclosures: Mr Yoshida and Dr Hanazato reported receiving research funding from Takenaka Corporation outside the submitted work. No other disclosures were reported.

Funding/Support: This work was supported by grants KAKENHI 19K04785, 20H00557, 22K04450, 22K21138, and 23K16349 from the Japan Society for the Promotion of Science; Open Innovation Platform with Enterprises, Research Institute, and Academia (OPERA, JPMJOP183) from Japan Science and Technology; and from AEON MALL Co Ltd.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.

Additional Contributions: We appreciate AEON MALL Co Ltd and Aeon Co Ltd for cooperating in the independent research and providing the AEON MALL smartphone application data set.

^✉

Corresponding author.

PMCID: PMC10828906 PMID: 38289599

Key Points

Question

Can participating in a smartphone-based shopping mall walking program increase individuals’ daily step count?

Findings

In this nationwide cohort study of 217 344 shopping mall app users with 23 638 110 daily step records, participating in the app’s walking program was associated with 1219 additional daily walking steps compared with nonparticipation days. Specifically, being participants in urban, suburban, and large shopping malls; women; and older adults were factors associated with taking more daily steps on walking program participation days.

Meaning

These findings suggest that smartphone-based mall walking programs may motivate individuals to walk more.

Abstract

Importance

Because shopping malls are considered safe places for walking, several mall walking programs have been developed. Research on the association between the use of walking programs and the number of daily steps taken is limited.

Objective

To evaluate the association between use of a smartphone-based shopping mall walking program and daily steps taken after the COVID-19 pandemic.

Design, Setting, and Participants

This cohort study evaluated a nationwide longitudinal data set of 217 344 registered smartphone app users at least 18 years of age residing in Japan. Daily step counts were collected from January 1 to December 31, 2021.

Exposures

The mall walking program Mall Challenge integrated a global positioning system with a smartphone app’s incentive system to reward achieving a goal of 1000 daily steps with lottery-based coupons to win from 0 to 500 shopping points (1 point equaled 1 yen or approximately US $0.01).

Main Outcomes and Measures

Daily step records were collected from the smartphone app’s walking program and adjusted for gender and age. Multilevel analyses using mixed-effect linear regression models were used to estimate the coefficients for the association between daily participation in the walking program and daily step counts. Cross-level interaction terms of age and gender by walking program participation were included in one model.

Results

Among the 217 344 registered mall app users (23 638 110 daily step records; 154 616 [71.1%] women; 18 014 [8.3%] participants 65 years or older, and 199 330 [91.7%] adults younger than 65 years), the mean (SD) daily steps were 7415 (4686) on walking program participation days and 5281 (4339) on days without participation in the program. Walking program participation days were associated with 1219 additional daily steps (95% CI, 1205-1232) compared with nonparticipation days after adjusting for gender and age. By geographic region, participation in the walking program was associated with 1130 (95% CI, 1113-1146) more steps in rural malls, 1403 (95% CI, 1379-1428) more steps in suburban malls, and 1433 (95% CI, 1408-1457) more steps in urban malls than nonparticipation. Moreover, participation in the walking program was associated with 1422 (95% CI, 1405-1439) more steps in large malls and 1059 (95% CI, 1041-1077) more steps in small malls compared with nonparticipation. Regarding cross-level interactions, women were associated with walking 728 (95% CI, 698-758) more steps than men, and older adults were associated with walking 228 (95% CI, 183-273) more steps than younger adults on walking program participation days.

Conclusions and Relevance

This cohort study found that the use of a smartphone-based mall walking program combined with physical shopping mall facilities and lottery-based digital incentive coupons may motivate people to increase their daily number of walking steps.

This nationwide cohort study assesses the association between the use of a smartphone-based shopping mall walking app and daily steps taken in and around shopping malls after the COVID-19 pandemic by residents of Japan.

Introduction

Physical activity is essential for preventing diseases^1,2 such as cardiovascular disease (CVD), type 2 diabetes,^3,4,5,6 and depression.⁷ International guidelines recommend at least 150 minutes of moderate-intensity physical activity weekly, 75 minutes or more of vigorous intensity, or any equivalent combination of them.¹ Globally, 27.5% of adults do not reach those levels.⁸ Walking is a feasible and effective way of enhancing physical activity.² Increasing daily steps reduces all-cause mortality and CVD risks among adults.^{9,10,11,12,13} However, after the COVID-19 pandemic, the number of walking steps decreased worldwide.¹⁴ The negative effects of the pandemic may differ across regions and neighborhood environments. After the COVID-19 pandemic, the US experienced regional disparities in walking by neighborhood socioeconomic status.¹⁵ Urban-rural differences in walking are also possible,¹⁶ although they were not thoroughly investigated after the pandemic. In addition, some neighborhood features may mitigate a reduction in steps. For instance, closeness to parks reduced the decrease in steps among older women after the pandemic.¹⁷ Therefore, spacious, walkable environments may contribute to restoring the number of steps that were decreased after the pandemic.

To encourage walking, several shopping malls have offered walking programs inside the malls.¹⁸ Shopping malls have been popular places for walking as they can provide safe, spacious, and accessible walking environments for everyone without the challenges of bad weather or traffic.¹⁸ However, few large-scale quantitative studies have been conducted to determine the benefits of shopping mall walking programs. Introducing digital recording systems and interventions using smartphone applications or activity trackers could be promising, as a meta-analysis has shown that the use of such technology is associated with an increase of approximately 1850 daily steps among adults without chronic disease.¹⁹

AEON MALL Co Ltd, a nationwide shopping mall operator in Japan,²⁰ developed a smartphone application (AEON MALL app) and a smartphone-based shopping mall walking program called Mall Challenge. This program uniquely integrates a global positioning system (GPS) with a lottery-based digital incentive system. When users enter an Aeon Mall, they can declare walking program participation once a day by pressing a start button on the app. After the GPS confirms that they are inside a mall, the app starts counting their steps and keeps counting for the whole day, including steps outside the mall. If users walk more than 1000 steps in a day, the app rewards them with a lottery-based digital coupon. Using the coupon, they can enter a lottery to win from 0 to 500 shopping points (1 point equaled 1 yen or approximately US $0.01). Installation of the app and participation in the mall walking program were free.

This study aimed to evaluate the association between the use of the walking program and the number of daily walking steps of adults after the COVID-19 pandemic. Additionally, we examined whether that association differed by environmental (region or shopping mall size) or individual (gender or age) factors. In Japan, there was a decrease in the number of walking steps, specifically among women and younger adults, before vs after the soft lockdown in April 2020.^17,21 We hypothesized that the association between participation in the walking program and daily steps would be particularly evident in car-dependent areas, in rural areas with low baseline steps, in spacious environments (eg, large malls), and among people with decreased steps after the soft lockdown (women or younger adults). Examining whether the program can reduce urban-rural disparities and help reverse the reduction in walking steps after the COVID-19 pandemic in Japan is important.

Methods

Study Design and Setting

This cohort study used nationwide records of smartphone application users registered on the mall app in Japan. This study used only deidentified data sets and was approved by the Research Ethics Committee of the Graduate School of Medicine, Chiba University. Informed consent was obtained from all participants with their agreement with the terms and conditions of the use of the mall app. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.²²

The app was downloadable on iPhone operating system (iOS) and Android OS and promoted both inside the malls and online. The app mainly targeted shoppers at Aeon Malls in Japan. Many app users activated the app’s mall walking program features after initial registration. People agreeing to the terms and conditions of use, including for academic purposes, were registered for the use of the app’s walking program and permitted the app to collect their daily step records. Those records were collected from the Health app (Apple Inc) on iOS or Google Fit (Google LLC) on the Android OS. Recording devices included iPhones, Android smartphones, and other wearable devices. During registration, participants provided information on birth year, month, and gender (men, women, others, prefer not to declare) through the app. Optionally, they could add their height (in centimeters), weight (in kilograms), prefecture of residence, and favorite malls. The users could modify their profile at any time, but we used the information provided at their initial registration. Whenever the users opened the app, it collected the records of the previous 7 days’ daily steps regardless of walking program participation. However, if they did not open the app for more than 1 week, their records from the prior 8 days were no longer reflected in the app. The app provided 4 features for the registered users of the mall walking program; details and reasoning based on gamification²³ and behavioral techniques^24,25 are described in eFigure 1 in Supplement 1. This study assessed data collected for the first feature of the walking program.

The app collected the daily step records of individuals who registered for the mall walking program regardless of location. The app users could participate in the walking program when visiting any of 163 malls in Japan (as of February 2021).²⁰ The enrollment period was from January 1 to December 31, 2021. We used the available daily step records and profile data of individuals who registered for the walking program before or during this period. A total of 277 061 users with 30 294 159 daily step records registered their profiles and agreed to have their step records collected (Figure). We excluded users whose age information was missing, who were younger than 18 years or provided an unrealistic age (≥120 years) as of January 1, 2021, or who had missing or an unspecified gender. We also excluded individuals with invalid daily step records: missing, fewer than 500 or more than 30 000 steps per day,²⁶ or walking program participation days at unspecified malls (opened during the period but not described in the 2021 Corporate Social Responsibility reports of AEON MALL Co Ltd).²⁰ In addition, we excluded users whose remaining valid step records were for fewer than 4 days.

Figure. — ^aRegistered users with age missing or age younger than 18 years or older than 120 years.

^bRegistered users with unspecified gender (missing or other or preferred not to declare).

^cRegistered users with empty records after excluding daily step records with step counts missing or with fewer than 500 or more than 30 000 steps.

^dRegistered users with empty records after excluding daily step records on days of walking program participation at malls not specified in the 2021 Corporate Social Responsibility reports of AEON MALL Co Ltd.

^eRegistered users with fewer than 4 days of valid step records.

The study outcome was daily step counts collected on the app. The exposure was a binary variable to indicate a day when users participated in the walking program program. The names of the malls where users started the walking program on the same day were also available. Therefore, we could further divide a walking program into subcategories by region and mall size according to the attributes of specified malls. For each region, we specified the prefectures of the malls and collected the prefectural population data on January 1, 2020.²⁷ We then classified the region by population in accordance with the Organisation for Economic Cooperation and Development Functional Urban Areas²⁸ as follows: metropolitan (≥500 000), suburban (200 000-499 999), and rural areas (<200 000). Therefore, we created a 3-part categorical variable for the walking program by region—walking program participation in urban (metropolitan), suburban, and rural malls—in addition to the variable for no program participation. Regarding mall size, we collected information on the total commercial areas of the malls from the 2021 Corporate Social Responsibility reports.²⁰ We divided this by the median value to define small (<60 000 m²) and large (≥60 000 m²) malls. Accordingly, we created a 2-category variable of the walking program by mall size—walking program participation at large and small malls—in addition to the variable for no program participation. The covariates were binary variables for older adults (≥65 years old at retirement age) or younger adults and for women or men. The possibility of temporal bias was presumably low because the participants started the walking program while the mall was operating, and the daily steps were counted at the end of the day (midnight).

Statistical Analysis

We conducted multilevel analyses using mixed-effect linear regression models to estimate the coefficients for the association between daily participation in the walking program and daily step counts. The estimation was conducted by iterative generalized least squares.²⁹ After testing a null model (model 1) with a constant and random effects of days (level 1) and individuals (level 2) only, we tested a random slope model with walking program use, age, and gender as fixed effects (model 2). We conducted additional analyses by replacing the walking program variable with program participation by region (model 3) and mall size (model 4). We included the cross-level interaction terms of age and gender by program participation in model 5. We adjusted only gender and age because no other reliable sociodemographic information was available. Moreover, gender or age disparities in walking have been previously reported.^17,21 We did not use prefecture of residence because people did not always go to malls within their prefectures. Considering possible recall or reporting bias of weight and height variables, we conducted sensitivity analyses using the same procedure but adjusted for a self-reported body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) category and its cross-level interaction term by walking program participation after excluding 33 194 persons (27 727 with missing data on BMI, 3491 persons with BMI lower than 18, and 1976 persons with BMI higher than 35).³⁰ The BMI category was coded as overweight (>25), underweight (<18.5), or otherwise healthy (18.5-25). We also confirmed models 1 through 5 after limiting them to 106 714 iOS users because iOS measurements had lower variability than Android OS measurements.^31,32 All analyses were complete case analyses. Statistical significance was set as 2-tailed P < .05. Analyses were conducted with MLwiN, version 3.06 (Centre for Multilevel Modeling),³³ and STATA, version 17.0 (StataCorp LLC),³⁴ using the runmlwin command.³⁵

Results

Among 217 344 users with a combined total of 23 638 110 daily step records included in this study, 62 728 (28.9%) were men, 154 616 (71.1%) were women, 18 014 (8.3%) were older adults (≥65 years), and 199 330 (91.7%) were younger adults (<65 years) (Table 1). The mean (SD) ages were 44.0 (11.3) years for younger adults and 69.9 (4.5) years for older adults. The mean (SD) daily steps were 7415 (4686) on walking program participation days and 5281 (4339) on days without participation in the program. We identified 136 malls where participants in this study took part in the walking program (eFigure 2 in Supplement 1), and the mean (SD) mall size was 53 908 (20 019) m². We observed no clear differences in distribution of mall sizes across regions (eTable 1 in Supplement 1). We describe the distributions of walking program participation days and participants across the year and months in eFigures 3, 4, and 5 in Supplement 1. Although some seasonal fluctuations were observed by month, the median (IQR) days of walking program participation per year was 2 (0-15).

Table 1. Demographic Characteristics of 217 344 App Users With 23 638 110 Daily Step Records by Walking Program Participation Status.

Characteristic	Users, No. (%)
	Total (N = 217 344)	Walking program participation		Walking program participation by mall region^a			Walking program participation by mall size^a
	Total (N = 217 344)	No (n = 80 177)	Yes (n = 137 167)	Rural (n = 86 797)	Suburban (n = 44 949)	Urban (n = 46 550)	Small (n = 79 564)	Large (n = 90 034)
Gender
Men	62 728 (28.9)	22 048 (27.5)	40 680 (29.7)	26 044 (30.0)	13 600 (30.3)	14 288 (30.7)	24 883 (31.3)	26 173 (29.1)
Women	154 616 (71.1)	58 129 (72.5)	96 487 (70.3)	60 753 (70.0)	31 349 (69.7)	32 262 (69.3)	54 681 (68.7)	63 861 (70.9)
Age
Younger adults (<65 y)	199 330 (91.7)	74 994 (93.5)	124 336 (90.6)	78 755 (90.7)	41 352 (92.0)	42 617 (91.6)	71 842 (90.3)	82 610 (91.8)
Older adults (≥65 y)	18 014 (8.3)	5183 (6.5)	12 831 (9.4)	8042 (9.3)	3597 (8.0)	3933 (8.4)	7722 (9.7)	7424 (8.2)
Daily walking steps during 1 y, median (IQR)^b	4445 (2994-6555)	3887 (2663-5746)	4800 (3237-7013)	4729 (3193-6952)	4881 (3284-7130)	5290 (3649-7523)	5069 (3423-7357)	4750 (3229-6930)

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^{^a}

The sums of numbers of participants by region or mall size are not equal to the number of walking program participants because some users participated in the program at multiple malls in different regions or sizes within the year (2021).

^{^b}

Average daily walking steps during 1 year were calculated per user using all available daily step count records in 2021; median (IQR) was derived from distribution of average daily walking steps of users counted in groups of each column.

According to multilevel analyses using mixed-effect linear regression models (Table 2), the variance component model (model 1) showed an intraclass correlation coefficient of 0.48, meaning that the variance of individuals comprised nearly half of the total variance. Therefore, a nested structure was assumed. After adjusting for gender and age (model 2), participating in the walking program was associated with 1219 (95% CI, 1205-1232) additional daily steps compared with nonparticipation days. Model 3 indicated that participating in the walking program was associated with additional steps of 1130 (95% CI, 1113-1146) in rural malls, 1403 (95% CI, 1379-1428) in suburban malls, and 1433 (95% CI, 1408-1457) in urban malls compared with nonparticipation days. In model 4, participating in the walking program was associated with additional steps of 1422 (95% CI, 1405-1439) in large malls and of 1059 (95% CI, 1041-1077) in small malls compared with nonparticipation days. Regarding the cross-level interactions of model 5, on the days of walking program participation, women were associated with walking 728 (95% CI, 698-758) steps more than men; older adult participants, with 228 (95% CI, 183-273) steps more than younger ones.

Table 2. Mixed-Effect Linear Regression Model Coefficients Showing an Association Between Walking Program Participation and Daily Walking Steps, With Random Slopes and Cross-Level Interaction Terms.

Daily walking steps	Coefficient (95% CI)^a
Daily walking steps	Model 1^b	Model 2	Model 3	Model 4	Model 5
Constant	5213 (5200 to 5226)	6440 (6417 to 6463)	6432 (6409 to 6455)	6436 (6413 to 6459)	6554 (6531 to 6578)
Walking program^c	NA	1219 (1205 to 1232)	NA	NA	682 (656 to 708)
Walking program at rural mall^c	NA	NA	1130 (1113 to 1146)	NA	NA
Walking program at suburban mall^c	NA	NA	1403 (1379 to 1428)	NA	NA
Walking program at urban mall^c	NA	NA	1433 (1408 to 1457)	NA	NA
Walking program at large mall^c	NA	NA	NA	1422 (1405 to 1439)	NA
Walking program at small mall^c	NA	NA	NA	1059 (1041 to 1077)	NA
Walking program × older adults^d	NA	NA	NA	NA	228 (183 to 273)
Walking program × women^d	NA	NA	NA	NA	728 (698 to 758)
Women (reference, men)	NA	−2003 (−2029 to −1977)	−1993 (−2019 to −1966)	−1997 (−2024 to −1971)	−2156 (−2183 to −2130)
Older adults (reference, younger adults)	NA	195 (152 to 238)	196 (153 to 238)	191 (148 to 233)	141 (96 to 185)

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Abbreviation: NA, not applicable.

^{^a}

An explanation of the 5 models appears in the Statistical Analysis subsection of the Methods section.

^{^b}

Variance component model of only constant and random effects of days (level 1) and individuals (level 2); intraclass correlation coefficient was 0.48.

^{^c}

Reference was no walking program participation.

^{^d}

Cross-level interaction terms indicating contextual effects.

Sensitivity analyses adjusted for BMI (eTable 2 and eTable 3 in Supplement 1) showed similar directionalities for each variable in models 1 through 5 as reported in Table 2. The interaction term of BMI and walking program participation did not show a clear association. Moreover, analyses limited to iOS users (eTable 4 and eTable 5 in Supplement 1) showed similar overall data for models 1 through 5 as reported in Table 2, except that the mixed-effect linear regression model coefficient for walking program use in suburban malls of 1432 (95% CI, 1394-1470) was slightly larger than that in urban malls (1421 [95% CI, 1384-1459]).

Discussion

This cohort study found that a smartphone-based mall walking program with lottery-based incentive coupons was associated with an additional 1219 steps walked per day on program participation days compared with nonparticipation days. Urban, suburban, and large malls were associated with higher numbers of steps than rural or small malls. Use of the program was also associated with taking more steps for women than men and older adults (≥65 years) than younger adults. Although the estimated effect size was smaller than that in a previous meta-analysis (1850 daily step increases),¹⁹ the use of the smartphone app was associated with an increase of more than 1000 steps daily. Walking 1000 steps further may reduce the risk of all-cause mortality by 6% to 36% and of CVD by 5% to 21%.¹⁰ Our findings are consistent with those of prior studies that showed the effectiveness of smartphone apps and gamification in enhancing physical activity.^36,37,38

Supporting our hypothesis, participating in the walking program was specifically associated with more daily steps taken in large malls, suggesting that spacious environments within facilities may influence walking. Contrary to our hypothesis, more daily steps were associated with urban or suburban malls than with rural malls. This finding could be because participants who visited urban and suburban malls had multiple destinations. Compared with rural areas, commercial or leisure facilities are more concentrated near shopping malls in urban and suburban areas, and easy access to destinations can positively influence physical activities and walking behaviors.³⁹ Therefore, participants in urban or suburban areas may have explored other destinations on the days of shopping mall visits. Because we evaluated the total daily step counts, including steps taken outside shopping malls, this difference may be reflected in the regional gap. Regarding individual social characteristics, walking program participation was associated with more daily steps for women than for men, consistent with our hypothesis. As the literature suggests, women may be more responsive than men to nonmonetary incentives (eg, coupons).⁴⁰ In contrast to our hypothesis, walking program participation was associated with more daily steps for older adults than for younger adults. The safe and walkable environments of shopping malls are favorable, especially for older adults.¹⁸

This study is the first, to our knowledge, to show, using big data collected nationwide, that a smartphone-based mall walking program was associated with increased daily walking steps. The advantage of a smartphone-based mall walking program is that each mall can automate program operations. Once a shopping mall company develops a smartphone app to connect GPS and step counts inside a mall, the app can automatically confirm users’ program participation and completion. Therefore, the use of program coordinators to distribute pedometers or rewards to participants is not necessary in malls. This could lower participation fees, which had been a hurdle for individuals with low income to participate in conventional mall walking programs.¹⁸ Although maintaining the app and providing digital rewards may be costly for a shopping mall company, operating the program may still be beneficial if encouraging shoppers to walk additional steps can increase their odds of purchasing additional products. Because visiting a shopping mall is a regular activity, users’ emotional engagement may not be as intense as previous smartphone-based gamification programs targeting fans of a sports team or existing game content.^37,38,41 However, shopping mall apps are accessible to everyone without prior knowledge of certain games. Consequently, these apps have the potential to reach a significant portion of the general population. Although a major barrier to participating in the program is geographic accessibility to shopping malls, combining GPS and digital incentive coupons can be expanded to other avenues, such as other large-scale facilities. Therefore, the program may contribute to population health involving an extensive range of people.

Limitations

This study has limitations. First, residual confounding is possible owing to unadjusted or unmeasured confounders, such as socioeconomic status and residential location. Because the available information from users’ profile data was limited, we adjusted only for age and gender (Table 2) in the main analyses. We excluded BMI because height and weight to calculate BMI were optional self-reported items and were missing or invalid for 33 194 (15.3%) of 217 344 users, and existing values may contain recall or reporting bias. Although we tested the models with BMI, the results may contain these biases (eTable 3 in Supplement 1). Second, daily step records obtained with the use of various measuring devices, such as iPhones, Android smartphones, and other wearable devices, may include measurement errors. However, bias owing to measurement errors may be minor because according to the literature, the size of the errors does not exceed 1000 steps.³¹ Additionally, during the sensitivity analyses limited to iOS, a similar trend was confirmed (eTable 5 in Supplement 1). Nevertheless, iPhones may underestimate actual steps owing to noncarrying time and carrying locations.³² Third, the association between the walking program participation days and daily steps may be overestimated given the possible underestimation of step counts on nonparticipation days. Although we excluded daily step records with fewer than 500 steps, records on nonparticipation days may have still included days of not going out or carrying smartphones. Moreover, going to shopping malls may involve more steps than usual, as people may walk in malls for leisure or essential grocery shopping. Finally, there may be potential selection bias, as this study included only individuals who agreed to register for shopping mall walking programs and tended to incorporate records from frequent app users. If these individuals were more health conscious and motivated to walk on walking program participation days compared with those who did not register or open the app frequently, the association between walking program participation and daily steps could be overestimated. Therefore, generalizability is limited to adults who register for shopping mall walking programs in Japan.

Conclusions

This cohort study of nationwide users in Japan found that the use of a smartphone-based shopping mall walking program was associated with increased daily steps taken on participation days. Gamification systems combined with physical shopping mall facilities and digital lottery-based incentive coupons may motivate people to walk more. The use of the mall walking program was specifically associated with increased daily steps in urban, suburban, or large malls and for women and older adults. Although generalizability needs to be tested, smartphone-based shopping mall walking programs may contribute to population health by reversing the decrease in walking steps after the COVID-19 pandemic.

Supplement 1.

eFigure 1. Features and Behavioral Techniques of AEON MALL Application

eFigure 2. Maps of Total Numbers of Mall Challenge Days and Participants at the Included Aeon Malls in 2021 (N = 136)

eFigure 3. Histograms of Number of Days With Step Records and Mall Challenge Days in 2021 (All Users, N = 217,344)

eFigure 4. Graphs of Monthly Numbers of Mall Challenge Days and Participants in 2021 (All Users Who Registered for the AEON MALL App by 2020 or in 2021)

eFigure 5. Graphs of Monthly Numbers of Mall Challenge Days and Participants in 2021 (Users Who Registered for the AEON MALL App by 2020)

eTable 1. Cross-Table of Mall Size by Region of the Included Aeon Malls in 2021 (N = 136)

eTable 2. Demographic Characteristics of 184,150 App Users With 20,108,120 Daily Step Records by Walking Program Participation Status, Excluding Registered Users With Invalid Body Mass Indices

eTable 3. Mixed-Effect Linear Regression Model Coefficients Showing an Association Between Walking Program Participation and Daily Walking Steps, With Random Slopes and Cross-Level Interaction Terms After Excluding Registered Users With Invalid Body Mass Indices (184,150 App Users With 20,108,120 Daily Step Records)

eTable 4. Demographic Characteristics of 106,714 App Users With 9,841,531 Daily Step Records (iOS only) by Walking Program Participation Status

eTable 5. Mixed-Effect Linear Regression Model Coefficients Showing an Association Between Walking Program Participation and Daily Walking Steps, With Random Slopes and Cross-Level Interaction Terms (iOS Only, 106,714 App Users With 9,841,531 Daily Step Records)

Click here for additional data file.^{(773.4KB, pdf)}

Supplement 2.

Data Sharing Statement

Click here for additional data file.^{(14.7KB, pdf)}

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