Accelerometer- and Pedometer-Based Physical Activity Interventions Among Adults With Cardiometabolic Conditions: A Systematic Review and Meta-analysis.
ABSTRACT: Importance:Accelerometers and pedometers are accessible technologies that could have a role in encouraging physical activity (PA) in line with current recommendations. However, there is no solid evidence of their association with PA in participants with 1 or more cardiometabolic conditions such as diabetes, prediabetes, obesity, and cardiovascular disease. Objectives:To assess the association of accelerometer- and pedometer-based interventions with increased activity and other improved health outcomes in adults with cardiometabolic conditions and to examine characteristics of the studies that could influence the association of both interventions in improving PA. Data Sources:Records from MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the Cumulative Index to Nursing and Allied Health, and PsycINFO were searched from inception until August 2018 with no language restriction. Study Selection:Randomized clinical trials or cluster randomized clinical trials evaluating the use of wearable technology devices such as pedometers and accelerometers as motivating and monitoring tools for increasing PA were included. After removing duplicates, the searches retrieved 5762 references. Following abstract and title screening of 1439 references and full-text screening of 107 studies, 36 studies met inclusion criteria. Data Extraction and Synthesis:Mean difference in PA was assessed by random-effects meta-analysis. Where the scale was different across studies, the standardized mean difference was used instead. Heterogeneity was quantified using the I2 statistic and explored using mixed-effects metaregression. This study was registered with PROSPERO and followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Main Outcomes and Measures:The primary outcome was objectively measured PA in the short to medium term (postintervention to 8 months' follow-up). Results:Thirty-six randomized clinical trials (20 using accelerometers and 16 using pedometers) involving 5208 participants were eligible for review. Meta-analysis involving 32 of these trials (4856 participants) showed medium improvements in PA: accelerometers and pedometers combined vs comparator showed a small significant increase in PA overall (standardized mean difference, 0.39 [95% CI, 0.28-0.51]; I2 = 60% [95% CI, 41%-73%]) in studies of short to medium follow-up over a mean (SD) of 32 (28.6) weeks. Multivariable metaregression showed improved association with PA for complex interventions that involved face-to-face consultation sessions with facilitators (β = 0.36; 95% CI, 0.17-0.55; P < .001) and pedometer-based interventions (β = 0.30; 95% CI, 0.08-0.52; P = .002). Conclusions and Relevance:In this study, complex accelerometer- and pedometer-based interventions led to significant small to medium improvements in PA levels of people with cardiometabolic conditions. However, longer-term trials are needed to assess their performance over time. This study found no evidence that simple self-monitored interventions using either pedometers or accelerometers are associated with improvements in PA.
Project description:BACKGROUND: Because physical activity (PA) provides multiple medical and psychosocial benefits after a cancer diagnosis, greater integration of objective activity monitoring into research and clinical practice is warranted. OBJECTIVES: To review randomized PA trials in cancer survivors after diagnosis using an accelerometer or pedometer and make recommendations for integrating objective monitoring into research and practice. MAJOR FINDINGS: Ten published PA and post-cancer diagnosis randomized trials have used pedometers (n=3), accelerometers (n=3), or both (n=4). Pedometers were primarily used to motivate PA adherence with several studies also using unblinded pedometers to assess the intervention effect on PA adherence. Accelerometers were primarily used to assess PA adherence after a PA intervention with one study using accelerometers to assess PA increase as a benefit of a non-PA intervention. One study used accelerometers to document sufficient ground forces for improving bone density in cancer survivors. Across studies, the reported objective monitoring outcome varied and was not always consistent with the stated intervention goal. CONCLUSIONS: PA and post-cancer diagnosis randomized trials have used objective monitoring primarily for motivation and/or adherence assessment. Investigators and practitioners are encouraged to expand the use of objective monitoring to also include understanding mechanisms of PA benefits and assess non-PA treatment modality effects. Future clinical and research protocols should consider the 1) outcome to be measured and reported, 2) need (or not) for blinding of the instrument outputs to participants, 3) appropriateness of activity intensity cutpoints for interpreting accelerometer data, and 4) logistical issues relevant to cancer survivors after diagnosis.
Project description:This study examined the reliability of two objective measurement tools in assessing children’s physical activity (PA) levels in an exergaming setting.A total of 377 children (190 girls, Mage = 8.39, SD = 1.55) attended the 30-min exergaming class every other day for 18 weeks. Children’s PA levels were concurrently measured by NL-1000 pedometer and ActiGraph GT3X accelerometer, while children’s steps per min and time engaged in sedentary, light, and moderate-to-vigorous PA were estimated, respectively.The results of intraclass correlation coefficient (ICC) indicated a low degree of reliability (single measures ICC = 0.03) in accelerometers. ANOVA did detect a possible learning effect for 27 classes (p < 0.01), and the single measures ICC was 0.20 for pedometers. Moreover, there was no significant positive relationship between steps per min and time spent in moderate-to-vigorous physical activity (MVPA). Finally, only 1.3% variance was explained by pedometer as a predictor using Hierarchical Linear Modeling to further explore the relationship between pedometer and accelerometer data.The NL-1000 pedometers and ActiGraph GT3X accelerometers have low reliability in assessing elementary school children’s PA levels during exergaming. More research is warranted in determining the reliable and accurate measurement information regarding the use of modern devices in exergaming setting.
Project description:BACKGROUND:Self-monitoring using pedometers is an effective behaviour change technique to support increased physical activity (PA). However, the ways in which pedometers operate as motivational tools in adoption and maintenance of PA is not well understood. This paper investigates men's experiences of pedometers as motivational tools both during and after their participation in a 12-week group-based, weight management programme for overweight/obese men, Football Fans in Training (FFIT). METHODS:Semi-structured telephone interviews were conducted with 28 men, purposively sampled to include men who did and did not achieve 5% weight loss during the programme. Data were analysed thematically utilising the framework approach, using Self-Determination Theory (SDT) - namely concepts of behavioural regulation and the basic needs of relatedness, competence and autonomy - as an analytical lens. RESULTS:During the programme, FFIT's context and fellow participants supported relatedness and encouraged use of the pedometer. The pedometer was seen to provide tangible proof of progress, thus increasing competence for change, whilst the ability to monitor one's own progress and take remedial action supported autonomy; these men portrayed the pedometer as an 'ally'. However, a minority found the pedometer 'dispiriting' or controlling when it evidenced their inability to meet their PA targets. After the programme, some men no longer used the device as they had fully internalised their motivations for increased PA. In contrast, others continued to use pedometers or progressed to other self-monitoring technologies because it was enjoyable and facilitated maintenance of their increased PA. However, the minority of men who experienced the pedometer as controlling no longer used it. They were less successful in achieving 5% weight loss and appeared reliant on external factors, including support from coach and group members, to maintain motivation. CONCLUSION:These findings show how self-monitoring using pedometers and associated goal setting supported the development of autonomous motivation for PA, during and after participation in a group-based programme. They also suggest that programmes could focus on early identification of participants who remain motivated by extrinsic factors or express negative experiences of self-monitoring tools, to offer greater support to identify the benefits of PA based on a person's own values.
Project description:Background: Brief counseling and self-monitoring with a pedometer are common practice within primary care for physical activity promotion. It is unknown how high-tech electronic activity monitors compare to pedometers within this setting. This study aimed to investigate the outcomes, through effect size estimation, of an electronic activity monitor-based intervention to increase physical activity and decrease cardiovascular disease risk. Method: The pilot randomized controlled trial was pre-registered online at clinicaltrials.gov (NCT02554435). Forty overweight, sedentary participants 55-74 years of age were randomized to wear a pedometer or an electronic activity monitor for 12 weeks. Physical activity was measured objectively for 7 days at baseline and follow-up by a SenseWear monitor and cardiovascular disease risk was estimated by the Framingham risk calculator. Results: Effect sizes for behavioral and health outcomes ranged from small to medium. While these effect sizes were favorable to the intervention group for physical activity (PA) (d = 0.78) and general health (d = 0.39), they were not favorable for measures. Conclusion: The results of this pilot trial show promise for this low-intensity intervention strategy, but large-scale trials are needed to test its efficacy.
Project description:BACKGROUND:Pedometers can increase walking and moderate-to-vigorous physical activity (MVPA) levels, but their effectiveness with or without support has not been rigorously evaluated. We assessed the effectiveness of a pedometer-based walking intervention in predominantly inactive adults, delivered by post or through primary care nurse-supported physical activity (PA) consultations. METHODS AND FINDINGS:A parallel three-arm cluster randomised trial was randomised by household, with 12-mo follow-up, in seven London, United Kingdom, primary care practices. Eleven thousand fifteen randomly selected patients aged 45-75 y without PA contraindications were invited. Five hundred forty-eight self-reporting achieving PA guidelines were excluded. One thousand twenty-three people from 922 households were randomised between 2012-2013 to one of the following groups: usual care (n = 338); postal pedometer intervention (n = 339); and nurse-supported pedometer intervention (n = 346). Of these, 956 participants (93%) provided outcome data (usual care n = 323, postal n = 312, nurse-supported n = 321). Both intervention groups received pedometers, 12-wk walking programmes, and PA diaries. The nurse group was offered three PA consultations. Primary and main secondary outcomes were changes from baseline to 12 mo in average daily step-counts and time in MVPA (in ?10-min bouts), respectively, measured objectively by accelerometry. Only statisticians were masked to group. Analysis was by intention-to-treat. Average baseline daily step-count was 7,479 (standard deviation [s.d.] 2,671), and average time in MVPA bouts was 94 (s.d. 102) min/wk. At 12 mo, mean steps/d, with s.d. in parentheses, were as follows: control 7,246 (2,671); postal 8,010 (2,922); and nurse support 8,131 (3,228). PA increased in both intervention groups compared with the control group; additional steps/d were 642 for postal (95% CI 329-955) and 677 for nurse support (95% CI 365-989); additional MVPA in bouts (min/wk) were 33 for postal (95% CI 17-49) and 35 for nurse support (95% CI 19-51). There were no significant differences between the two interventions at 12 mo. The 10% (1,023/10,467) recruitment rate was a study limitation. CONCLUSIONS:A primary care pedometer-based walking intervention in predominantly inactive 45- to 75-y-olds increased step-counts by about one-tenth and time in MVPA in bouts by about one-third. Nurse and postal delivery achieved similar 12-mo PA outcomes. A primary care pedometer intervention delivered by post or with minimal support could help address the public health physical inactivity challenge. CLINICAL TRIAL REGISTRATION:isrctn.com ISRCTN98538934.
Project description:Valid, reliable, and direct measures of physical activity (PA) are critical to assessing the impact of lifestyle PA interventions. However, little is known about the extent to which objective measures have been used to assess the outcomes of lifestyle PA interventions. This systematic review had two aims: 1) evaluate the extent to which PA is measured objectively in lifestyle PA interventions targeting adults and 2) explore and summarize what objective measures have been used and what PA dimensions and metrics have been reported. Pubmed, Cochrane Central Register, and PsychInfo were searched for lifestyle PA interventions conducted between 2006 and 2016. Of the 342 articles that met the inclusion criteria, 239 studies measured PA via subjective measures and 103 studies measured PA via objective measures. The proportion of studies using objective measures increased from 4.4% to 70.6% from 2006 to 2016. All studies measuring PA objectively utilized wearable devices; half (50.5%) used pedometers only and 40.8% used accelerometers only. A majority of the 103 studies reported steps (73.8%) as their PA metric. Incorporating objective measures of PA should continue to be a priority in PA research. More work is needed to address the challenges of comprehensive and consistent collecting, reporting, and analyzing of PA metrics.
Project description:This study aimed to systematically review previous studies on the reliability and concurrent validity of the Global Physical Activity Questionnaire (GPAQ). A systematic literature search was conducted (n = 26) using the online EBSCOHost databases, PubMed, Web of Science, and Google Scholar up to September 2019. A previously developed coding sheet was used to collect the data. The Modified Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was employed to assess risk of bias and study quality. It was found that GPAQ was primarily revalidated in adult populations in Asian and European countries. The sample size ranged from 43 to 2657 with a wide age range (i.e., 15-79 years old). Different populations yielded inconsistent results concerning the reliability and validity of the GPAQ. Short term (i.e., one- to two-week interval) and long-term (i.e., two- to three-month apart) test-retest reliability was good to very good. The concurrent validity using accelerometers, pedometers, and physical activity (PA) log was poor to fair. The GPAQ data and accelerometer/pedometer/PA log data were not compared using the same measurements in some validation studies. Studies with more rigorous research designs are needed before any conclusions concerning the concurrent validity of GPAQ can be reached.
Project description:Introduction:Physical activity (PA) may improve cardiometabolic fitness and increase high-molecular-weight adiponectin (HMW-Adip). The pedometer is an effective, user-friendly device to monitor PA with the aim of improving health. This study examined how counting footsteps, using a pedometer, might affect HMW-Adip and MetS components among young females. Methods:Fifty-two females (21.43 ± 4.8 years) were divided into "normal" (BMI = 18-24.9?kg/m2) and "high" (BMI ? 25?kg/m2) BMI groups. Participants wore pedometers throughout the day for nine weeks. Pre-post intervention tests performed on anthropometric, biochemical, and nutrient intake variables were tested at p ? 0.05. Results:Participants walked 7056 ± 1570 footsteps/day without a significant difference between normal (7488.49 ± 1098) and high (6739.18 ± 1793) BMI groups. After week 9, the normal BMI group improved significantly in BMI, body fat mass (BFM), and waist-hip ratio (WHR). Additionally, percent body fat, waist circumference (WC), and visceral fat area also reduced significantly in the high BMI group. A significant decrease in triglycerides (TG) (71.62 ± 29.22 vs. 62.50 ± 29.16?mg/dl, p=0.003) and insulin (21.7 ± 8.33?µU/l vs. 18.64 ± 8.25?µU/l, p=0.046) and increase in HMW-Adip (3.77 ± 0.46 vs. 3.80 ± 0.44??g/ml, p=0.034) were recorded in the high BMI group. All participants exhibited significant inverse correlations between daily footsteps and BMI (r=-0.33, p=0.017), BFM (r=-0.29, p=0.037), WHR (r=-0.401, p=0.003), and MetS score (r=-0.49, p < 0.001) and positive correlation with HMW-Adip (r=0.331, p=0.017). A positive correlation with systolic (r=0.46, p=0.011) and diastolic (r=0.39, p=0.031) blood pressures and inverse correlation with the MetS score (r=-0.5, p=0.005) were evident in the high BMI group. Conclusion:Counting footsteps using a pedometer is effective in improving MetS components (obesity, TG) and increasing HMW-Adip levels.
Project description:Strategies to increase adherence to national dietary and physical activity (PA) guidelines to improve the health in regions such as the Lower Mississippi Delta (LMD) of the United States are needed. Here we explore the cardiometabolic responses to an education and behavior change intervention among overweight and obese adults that adapted the 2010 Dietary Guidelines (DG), with and without a PA component.White and African American overweight and obese adults were randomized to a DG group (n=61) or a DG+PA group (n=60). Both groups received a 12-week dietary education and behavior change intervention, and the DG+PA group also received a PA education and behavior change intervention with a pedometer. Changes in individual risk factors (blood pressure, fasting glucose, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol) and a continuous cardiometabolic risk score were determined. General linear models compared mean changes between groups, adjusting for covariates.No main effect of intervention group was found in completers (n=99) and those who engaged with ≥80% of the intervention (n=83) for individual risk factors or the continuous risk score. Pooling both groups, those with higher baseline risk factor values realized greater improvements in individual risk factors.Adapting DG did not produce any cardiometabolic benefits, even with a PA component. Although the sample was ostensibly healthy, they were all overweight to mildly obese (body mass index of 25-34.9 kg/m(2)) and participants with higher baseline risk factor values showed more improvements. Adherence to longer-term behavior change may elicit changes in risk profile, so this should be explored.
Project description:Worldwide, one third of the adult population is insufficiently physically active. This fact has led to a strong demand for public health initiatives. Given the mixed evidence on the effectiveness of worksite interventions promoting physical activity (PA), a pedometer-based and gamified intervention, Healingo Fit, was developed and evaluated over a period of six weeks.The effectiveness of Healingo Fit was evaluated as part of a randomized controlled trial (RCT) with two measurement points involving employees of an automobile manufacturer. Direct health promotion outcomes were assessed using self-developed items on PA knowledge, the HAPA brief scales and the exercise self-efficacy scale. IPAQ short version was used to assess different forms of PA behavior. Intervention effects were identified using a two-way analysis of variance (ANOVA) with repeated measurements.A total of 144 participants took part in the study (intervention group = 80, control group = 64). The results of the ANOVA show significant interaction effects (group x time) for health promotion outcomes (knowledge, intention, and self-efficacy), with medium to high effect sizes. In the health behavior related outcomes, there were significant improvements, with large effect sizes for low levels of PA, but not for moderate and high PA. Walking time increased by 125 min/week in the intervention group, corresponding to a percentage increase of 30% compared to baseline.Pedometer-based interventions using gamification elements can have positive effects not only on health promotion parameters but can also lead to an increase in PA behavior. The online format of Healingo Fit is suitable for reaching large numbers of people and achieving population effects.German Clinical Trials Register (DRKS): DRKS00006105 , date of registration: 2017-03-24.