Comparison between smartphone pedometer applications and traditional
pedometers for improving physical activity and body mass index in community-dwelling older
adults

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Abstract

[Purpose] The effectiveness of a smartphone pedometer application was compared with that of a traditional pedometer for improving the physical activity and weight status of community-dwelling older adults. [Subjects and Methods] This study had a nonequivalent pretest-posttest control group design. Ninety-seven older adults (mean age ± SD, 60.1 ± 5.5 years) joined the smartphone pedometer group and underwent a 2-week walking intervention based on a smartphone pedometer application. Fifty-four older adults (mean age ± SD, 65.3 ± 8.7 years) joined the traditional pedometer group and underwent a 2-week walking intervention based on a traditional pedometer. The participants’ physical activity was evaluated using the International Physical Activity Questionnaire–Short Form, and their weight status was quantified by calculating the body mass index. The daily pedometer count was also documented. [Results] No significant time, group, or time-by-group interaction effects were found for any of the outcome variables. However, trends of improvement in physical activity and body mass index were seen only in the smartphone pedometer group. [Conclusion] A smartphone pedometer application might be more favorable than a traditional pedometer in improving physical activity and body mass index in community-dwelling older adults. However, further experimental studies are necessary to confirm the results.

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Increasing Physical Activity With Mobile Devices: A Meta-Analysis

Jason Fanning, Sean P Mullen, Edward McAuley (2012)

Background Regular physical activity has established physical and mental health benefits; however, merely one quarter of the U.S. adult population meets national physical activity recommendations. In an effort to engage individuals who do not meet these guidelines, researchers have utilized popular emerging technologies, including mobile devices (ie, personal digital assistants [PDAs], mobile phones). This study is the first to synthesize current research focused on the use of mobile devices for increasing physical activity. Objective To conduct a meta-analysis of research utilizing mobile devices to influence physical activity behavior. The aims of this review were to: (1) examine the efficacy of mobile devices in the physical activity setting, (2) explore and discuss implementation of device features across studies, and (3) make recommendations for future intervention development. Methods We searched electronic databases (PubMed, PsychINFO, SCOPUS) and identified publications through reference lists and requests to experts in the field of mobile health. Studies were included that provided original data and aimed to influence physical activity through dissemination or collection of intervention materials with a mobile device. Data were extracted to calculate effect sizes for individual studies, as were study descriptives. A random effects meta-analysis was conducted using the Comprehensive Meta-Analysis software suite. Study quality was assessed using the quality of execution portion of the Guide to Community Preventative Services data extraction form. Results Four studies were of “good” quality and seven of “fair” quality. In total, 1351 individuals participated in 11 unique studies from which 18 effects were extracted and synthesized, yielding an overall weight mean effect size of g = 0.54 (95% CI = 0.17 to 0.91, P = .01). Conclusions Research utilizing mobile devices is gaining in popularity, and this study suggests that this platform is an effective means for influencing physical activity behavior. Our focus must be on the best possible use of these tools to measure and understand behavior. Therefore, theoretically grounded behavior change interventions that recognize and act on the potential of smartphone technology could provide investigators with an effective tool for increasing physical activity.

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A comparison of body mass index, waist-hip ratio and waist circumference as predictors of all-cause mortality among the elderly: the Rotterdam study.

A Molarius, D Gey, Michel Hofman … (2001)

To compare body mass index (BMI), waist-hip ratio (WHR) and waist circumference as predictors of all-cause mortality among the elderly. Population-based cohort study; mean follow-up was 5.4 y. The Rotterdam Study. A total of 6296 men and women; baseline age 55-102 y. Sex-specific all-cause mortality was compared between quintiles of BMI, WHR and waist circumference and between predefined categories of BMI and waist circumference, stratified for smoking category. High quintiles of waist circumference, but not high quintiles of BMI and WHR were related to increased mortality among never smoking men, without reaching statistical significance. Only the highest category of BMI (BMI>30 kg/m2) among never smoking men was related to increased mortality, compared to normal BMI (hazard ratio 2.6 (95% confidence interval: 1.3-5.3)). Waist circumference between 94 and 102 cm and waist circumference 102 cm and larger were related to increased mortality, compared to normal waist circumference (hazard ratios 1.7 (95% confidence interval 1.1-2.8) and 1.6 (95% confidence interval 1.0-2.8), respectively). The proportion of mortality attributable to large waist circumference among never smoking men was three-fold the proportion attributable to high BMI. Among never smoking women and ex- and current smokers, categories of large body fatness did not predict increased mortality. Among never smoking elderly men waist circumference may have more potential for detecting overweight than the BMI.

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B-MOBILE - A Smartphone-Based Intervention to Reduce Sedentary Time in Overweight/Obese Individuals: A Within-Subjects Experimental Trial

Dale Bond, J Graham Thomas, Hollie Raynor … (2014)

Purpose Excessive sedentary time (SED) has been linked to obesity and other adverse health outcomes. However, few sedentary-reducing interventions exist and none have utilized smartphones to automate behavioral strategies to decrease SED. We tested a smartphone-based intervention to monitor and decrease SED in overweight/obese individuals, and compared 3 approaches to prompting physical activity (PA) breaks and delivering feedback on SED. Design and Methods Participants [N = 30; Age = 47.5(13.5) years; 83% female; Body Mass Index (BMI) = 36.2(7.5) kg/m2] wore the SenseWear Mini Armband (SWA) to objectively measure SED for 7 days at baseline. Participants were then presented with 3 smartphone-based PA break conditions in counterbalanced order: (1) 3-min break after 30 SED min; (2) 6-min break after 60 SED min; and (3) 12-min break after 120 SED min. Participants followed each condition for 7 days and wore the SWA throughout. Results All PA break conditions yielded significant decreases in SED and increases in light (LPA) and moderate-to-vigorous PA (MVPA) (p<0.005). Average % SED at baseline (72.2%) decreased by 5.9%, 5.6%, and 3.3% [i.e. by mean (95% CI) −47.2(−66.3, −28.2), −44.5(−65.2, −23.8), and −26.2(−40.7, −11.6) min/d] in the 3-, 6-, and 12-min conditions, respectively. Conversely, % LPA increased from 22.8% to 26.7%, 26.7%, and 24.7% [i.e. by 31.0(15.8, 46.2), 31.0(13.6, 48.4), and 15.3(3.9, 26.8) min/d], and % MVPA increased from 5.0% to 7.0%, 6.7%, and 6.3% (i.e. by 16.2(8.5, 24.0), 13.5(6.3, 20.6), and 10.8(4.2, 17.5) min/d] in the 3-, 6-, and 12-min conditions, respectively. Planned pairwise comparisons revealed the 3-min condition was superior to the 12-min condition in decreasing SED and increasing LPA (p<0.05). Conclusion The smartphone-based intervention significantly reduced SED. Prompting frequent short activity breaks may be the most effective way to decrease SED and increase PA in overweight/obese individuals. Future investigations should determine whether these SED reductions can be maintained long-term. Trial Registration ClinicalTrials.gov NCT01688804

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Author and article information

Journal

Journal ID (nlm-ta): J Phys Ther Sci

Journal ID (iso-abbrev): J Phys Ther Sci

Journal ID (publisher-id): JPTS

Title: Journal of Physical Therapy Science

Publisher: The Society of Physical Therapy Science

ISSN (Print): 0915-5287

ISSN (Electronic): 2187-5626

Publication date (Electronic): 31 May 2016

Publication date (Print): May 2016

Volume: 28

Issue: 5

Pages: 1651-1656

Affiliations

[1) ] Institute of Human Performance, The University of Hong Kong, Hong Kong

[2) ] Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong

[3) ] Department of Health and Physical Education, The Hong Kong Institute of Education, Hong Kong

[4) ] Faculty of Liberal Arts and Social Sciences, The Hong Kong Institute of Education, Hong Kong

[5) ] Elderly Core Business, Hong Kong Christian Service, Hong Kong

[6) ] Bliss District Elderly Community Centre, Active Ageing Service, Hong Kong Christian Service, Hong Kong

Author notes

[* ]Corresponding author. Shirley S.M. Fong, Institute of Human Performance, The University of Hong Kong: Pokfulam, Hong Kong. (E-mail: smfong@ 123456hku.hk )

Article

Publisher ID: jpts-2016-016

DOI: 10.1589/jpts.28.1651

PMC ID: 4905930

PubMed ID: 27313391

SO-VID: fe33770c-80f3-4e3a-9fa3-6259ca1f8725

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (by-nc-nd) License.

Comparison between smartphone pedometer applications and traditional pedometers for improving physical activity and body mass index in community-dwelling older adults

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Most cited references 12

Increasing Physical Activity With Mobile Devices: A Meta-Analysis

A comparison of body mass index, waist-hip ratio and waist circumference as predictors of all-cause mortality among the elderly: the Rotterdam study.

B-MOBILE - A Smartphone-Based Intervention to Reduce Sedentary Time in Overweight/Obese Individuals: A Within-Subjects Experimental Trial

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