Motion sensor accuracy under controlled and free-living conditions

Who Are We Excluding From Physical Activity Research? Examining the Potential for Exclusion Bias in Pedometer Data Processing

BACKGROUND

Pedometers are a useful measure of physical activity (PA) but whether systematic bias exists when using differing inclusion criterion for pedometer-derived PA data is unknown. We undertake an exploration of previously published criteria for pedometer data cleaning and examine the impact of different inclusion criteria on sample size retention and participant exclusion by key sociodemographic characteristics.

METHODS

Data were drawn from a community survey in Aotearoa/New Zealand. Sociodemographic information and self-reported PA were collected via face-to-face surveys; participants were asked to wear a Yamax CW300 pedometer for 7 days. Analyses involved removing extreme outliers and determining minimum steps per day for inclusion, determining whether day 1 removal was required, examining risk of bias using different inclusion criteria, and examining convergent and concurrent validity of criteria with the lowest bias potential.

RESULTS

Pedometer data were available for 895 participants. A threshold of 100 steps/day was deemed appropriate to define a valid day. All days were correlated with each other; intraclass correlation coefficients were low and did not change meaningfully with removal of the first day of data. Participant retention reduced, and bias in participant inclusion increased, with increasing stringency of data inclusion criterion applied. Evidence for convergent and concurrent validity in the 2 models with the lowest risk of exclusion bias was demonstrated.

CONCLUSION

Increasing stringency in pedometer data inclusion criteria can result in significant and biased loss of sample size. Clear reporting of data cleaning methods and rationale (including consideration of potential for bias) is needed in pedometer-based PA research.

Reliability, validity and minimal detectable change of the Chinese Version of the Assessment of Physical Activity in Frail Older People (APAFOP-C)

BACKGROUND

Physical activity (PA) is essential in mitigating frailty syndrome, and it is necessary to measure PA in older adults with frailty. Assessment of Physical Activity in Frail Older People (APAFOP) is a suitable patient-reported outcome measure (PROM) for assessing PA among older adults with frailty. This study aimed to determine the reliability, validity and minimal detectable change of the Chinese version of the APAFOP (APAFOP-C).

METHODS

This cross-sectional validation study was designed to measure the reliability and criterion validity of the APAFOP-C with 124 frail community-residing older adults. APAFOP-C was completed twice within an interval of 7-17 days to determine test-retest reliability. The investigator triangulation method was used to investigate inter-rater reliability, and a pedometer was used as the reference measurement to assess the criterion validity. Reliability and criterion validity were assessed using the intraclass correlation coefficient (ICC2,1), Pearson correlation coefficient for normally distributed variables, Spearman correlation coefficient, Wilcoxon signed-rank test for skewed variables, and the minimal detectable change at 95% level of confidence (MDC95). Agreement assessment was conducted using Bland-Altman plots for inter-rater reliability and criterion validity. Kendall's W test assessed absolute agreement among three raters in inter-rater reliability. The Mann-Whitney U test was used to evaluate whether any particular day was more representative of certain daily activities.

RESULTS

Total PA on any arbitrarily chosen day illustrates daily activity (Z= -0.84, p = 0.40). The APAFOP-C exhibited strong-to-very strong test-retest reliability (ICC2,1=0.73-0.97; Spearman ρ = 0.67-0.89), and the total PA score demonstrated MDC95 < 10%. Inter-rater reliability was also strong-to-very strong (ICC2,1=0.96-0.98; Spearman ρ = 0.88-1.00), and moderate criterion validity when compared with total PA score on pedometer readings (Spearman ρ = 0.61). Limits of agreement among different raters regarding the APAFOP-C and the pedometer were narrow.

CONCLUSION

The APAFOP-C was found to have limited but acceptable psychometric properties for measuring PA among community-dwelling older adults with frailty in China. It was a feasible comparative PROM for assessing PA worldwide. Practitioners can develop individualized exercise programs for frail older adults and efficiently track changes in PA utilizing the APAFOP-C.

Impact of Treatable Traits on Asthma Control and Quality of Life

BACKGROUND

Many adult patients with asthma have uncontrolled disease and impaired quality of life, despite current asthma-specific drug therapies.

OBJECTIVE

This study aimed to investigate the prevalence of 9 traits in patients with asthma, their associations with disease control and quality of life, and referral rates to nonmedical health care professionals.

METHODS

Retrospectively, data from patients with asthma were collected in 2 Dutch hospitals (Amphia Breda and RadboudUMC Nijmegen). Adult patients without exacerbation <3 months who were referred for a first-ever elective, outpatient, hospital-based diagnostic pathway were deemed eligible. Nine traits were assessed: dyspnea, fatigue, depression, overweight, exercise intolerance, physical inactivity, smoking, hyperventilation, and frequent exacerbations. To assess the likelihood of having poor disease control or decreased quality of life, the odds ratio (OR) was calculated per trait. Referral rates were assessed by checking patients' files.

RESULTS

A total of 444 adults with asthma were studied (57% women, age: 48 ± 16 years, forced expiratory volume in 1 second: 88% ± 17% predicted). Most patients (53%) were found to have uncontrolled asthma (Asthma Control Questionnaire ≥1.5 points) and decreased quality of life (Asthma Quality of Life Questionnaire <6 points). Generally, patients had 3.0 ± 1.8 traits. Severe fatigue was most prevalent (60%) and significantly increased the likelihood of having uncontrolled asthma (OR: 3.0, 95% confidence interval [CI]: 1.9-4.7) and decreased quality of life (OR: 4.6, 95% CI: 2.7-7.9). Referrals to nonmedical health care professionals were low; most referrals were to a respiratory-specialized nurse (33%).

CONCLUSION

Adult patients with asthma with a first-ever referral to a pulmonologist frequently exhibit traits justifying the deployment of nonpharmacological interventions, especially in those with uncontrolled asthma. However, referrals to appropriate interventions appeared infrequent.

Ambulatory Activity and Risk of Premature Mortality Among Young and Middle-aged American Indian Individuals

Importance

To our knowledge, no published studies have investigated the association of ambulatory activity with risk of death among young and middle-aged American Indian individuals. The burden of chronic disease and risk of premature death is higher among American Indian individuals than among the general US population, so better understanding of the association of ambulatory activity with risk of death is needed to inform public health messaging in tribal communities.

Objective

To examine the association of objectively measured ambulatory activity (ie, steps per day) with risk of death among young and middle-aged American Indian individuals.

Design, Setting, and Participants

The ongoing longitudinal Strong Heart Family Study (SHFS) is being conducted with participants aged 14 to 65 years in 12 rural American Indian communities in Arizona, North Dakota, South Dakota, and Oklahoma and includes up to 20 years of follow-up (February 26, 2001, to December 31, 2020). This cohort study included SHFS participants who had available pedometer data at baseline. Data analysis was performed on June 9, 2022.

Exposures

Objectively measured ambulatory activity at baseline.

Main Outcomes and Measures

Outcomes of interest were total and cardiovascular-related mortality. Mixed-effects Cox proportional hazards regression was used to estimate hazard ratios for risk of death, with entry at the time of the pedometer assessment and time at risk until death or the latest adjudicated date of follow-up.

Results

A total of 2204 participants were included in this study. Their mean (SD) age was 41.0 (16.8) years; 1321 (59.9%) were female and 883 (40.1%) were male. During a mean follow-up of 17.0 years (range, 0-19.9 years), 449 deaths occurred. Compared with participants in the lowest quartile of steps per day (<3126 steps), individuals in the upper 3 quartiles of steps per day had lower risk of mortality, with hazard ratios of0.72 (95% CI, 0.54-0.95) for the first quartile, 0.66 (95% CI, 0.47-0.93) for the second quartile, and 0.65 (95% CI, 0.44-0.95) for the third quartile after adjustment for age, sex, study site, education, smoking status, alcohol use, diet quality, body mass index, systolic blood pressure, prevalent diabetes, prevalent cardiovascular disease, biomarker levels (fibrinogen, low-density lipoprotein cholesterol, and triglycerides), medication use (hypertensive or lipid-lowering agents), and self-reported health status. The magnitude of the hazard ratios was similar for cardiovascular mortality.

Conclusions and Relevance

In this cohort study, American Indian individuals who took at least 3126 steps/d had a lower risk of death compared with participants who accumulated fewer steps per day. These findings suggest that step counters are an inexpensive tool that offers an opportunity to encourage activity and improve long-term health outcomes.

Smartphone Pedometer Sensor Application for Evaluating Disease Activity and Predicting Comorbidities in Patients with Rheumatoid Arthritis: A Validation Study

Smartphone-based pedometer sensor telemedicine applications could be useful for measuring disease activity and predicting the risk of developing comorbidities, such as pulmonary or cardiovascular disease, in patients with rheumatoid arthritis (RA), but the sensors have not been validated in this patient population. The aim of this study was to validate step counting with an activity-tracking application running the inbuilt Android smartphone pedometer virtual sensor in patients with RA. Two Android-based smartphones were tested in a treadmill test-bed setup at six walking speeds and compared to manual step counting as the gold standard. Guided by a facilitator, the participants walked 100 steps at each test speed, from 2.5 km/h to 5 km/h, wearing both devices simultaneously in a stomach pouch. A computer automatically recorded both the manually observed and the sensor step count. The overall difference in device step counts versus the observed was 5.9% mean absolute percentage error. Highest mean error was at the 2.5 km/h speed tests, where the mean error of the two devices was 18.5%. Both speed and cadence were negatively correlated to the absolute percentage error, which indicates that the greater the speed and cadence, the lower the resulting step counting error rate. There was no correlation between clinical parameters and absolute percentage error. In conclusion, the activity-tracking application using the inbuilt Android smartphone pedometer virtual sensor is valid for step counting in patients with RA. However, walking at very low speed and cadence may represent a challenge.

Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review

Background

Wearable technology is a leading fitness trend in the growing commercial industry and an established method for collecting 24-hour physical behavior data in research studies. High-quality free-living validation studies are required to enable both researchers and consumers to make guided decisions on which study to rely on and which device to use. However, reviews focusing on the quality of free-living validation studies in adults are lacking.

Objective

This study aimed to raise researchers’ and consumers’ attention to the quality of published validation protocols while aiming to identify and compare specific consistencies or inconsistencies between protocols. We aimed to provide a comprehensive and historical overview of which wearable devices have been validated for which purpose and whether they show promise for use in further studies.

Methods

Peer-reviewed validation studies from electronic databases, as well as backward and forward citation searches (1970 to July 2021), with the following, required indicators were included: protocol must include real-life conditions, outcome must belong to one dimension of the 24-hour physical behavior construct (intensity, posture or activity type, and biological state), the protocol must include a criterion measure, and study results must be published in English-language journals. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool with 9 questions separated into 4 domains (patient selection or study design, index measure, criterion measure, and flow and time).

Results

Of the 13,285 unique search results, 222 (1.67%) articles were included. Most studies (153/237, 64.6%) validated an intensity measure outcome such as energy expenditure. However, only 19.8% (47/237) validated biological state and 15.6% (37/237) validated posture or activity-type outcomes. Across all studies, 163 different wearables were identified. Of these, 58.9% (96/163) were validated only once. ActiGraph GT3X/GT3X+ (36/163, 22.1%), Fitbit Flex (20/163, 12.3%), and ActivPAL (12/163, 7.4%) were used most often in the included studies. The percentage of participants meeting the quality criteria ranged from 38.8% (92/237) to 92.4% (219/237). On the basis of our classification tree to evaluate the overall study quality, 4.6% (11/237) of studies were classified as low risk. Furthermore, 16% (38/237) of studies were classified as having some concerns, and 72.9% (173/237) of studies were classified as high risk.

Conclusions

Overall, free-living validation studies of wearables are characterized by low methodological quality, large variability in design, and focus on intensity. Future research should strongly aim at biological state and posture or activity outcomes and strive for standardized protocols embedded in a validation framework. Standardized protocols for free-living validation embedded in a framework are urgently needed to inform and guide stakeholders (eg, manufacturers, scientists, and consumers) in selecting wearables for self-tracking purposes, applying wearables in health studies, and fostering innovation to achieve improved validity.

Concurrent Validity of the Garmin Vivofit®4 to Accurately Record Step Count in Older Adults in Challenging Environments

There is little evidence of the concurrent validity of commercially available wrist-worn long battery life activity monitors to measure steps in older adults at slow speeds and with real-world challenges. Forty adults aged over 60 years performed a treadmill protocol at four speeds, a 50-m indoor circuit, and a 200-m outdoor circuit with environmental challenges while wearing a Garmin Vivofit®4, the activPAL3™, and a chest-worn camera angled at the feet. The Garmin Vivofit®4 showed high intraclass correlation coefficients2,1 (.98-.99) and low absolute percentage error rates (<2%) at the fastest treadmill speeds and the outdoor circuit. Step counts were underestimated at the slowest treadmill speed and the indoor circuit. The Garmin Vivofit®4 is accurate for older adults at higher walking speeds and during outdoor walking. However, it underestimates steps at slow speeds and when walking indoors with postural transitions.

Accuracy of the ActivPAL and Fitbit Charge 2 in measuring step count in Cystic Fibrosis

BACKGROUND

Physical activity (PA) is important in Cystic Fibrosis (CF) management. Fitness wearables are becoming increasingly popular as measurement tools of PA; however, the accuracy of these devices should first be evaluated.

OBJECTIVE

The purpose of this study was to assess the accuracy of the ActivPAL and Fitbit Charge 2 as a measure of step count in Cystic Fibrosis.

METHODS

Twenty-one participants were recruited from an adult CF Center in Ireland for a single session of testing. Participants walked for 5 min at five pre-determined speeds in a controlled testing environment (2, 2.5, 3, 3.5 and 4 miles per hour on a treadmill) and at three self-selected speeds in a corridor (slow, medium, and fast). They concurrently wore an accelerometer (ActivPAL) and fitness wearable (Fitbit Charge 2), and both were compared to visual observations. Step count is the outcome being assessed.

RESULTS

The ActivPAL under-estimated step count by 0.63% across treadmill speeds and 1.1% across self-selected walking speeds. The Fitbit Charge 2 underestimated the step count by 2.97% across treadmill speeds and by 6.3% across self-selected walking speeds. Very strong correlations were found between the ActivPAL and visual observations (r: 0.93 to 0.99), while the Fitbit Charge 2 ranged from weak to very strong correlations when compared to visual observations (r: 0.34 to 0.84).

CONCLUSION

The ActivPAL and Fitbit Charge 2 demonstrated acceptable validity for step count measurement in CF. These devices can be used for tracking PA during interventions in people with CF.

Evaluating Pedometer Algorithms on Semi-Regular and Unstructured Gaits

Pedometers are popular for counting steps as a daily measure of physical activity, however, errors as high as 96% have been reported in previous work. Many reasons for pedometer error have been studied, including walking speed, sensor position on the body and pedometer algorithm, demonstrating some differences in error. However, we hypothesize that the largest source of error may be due to differences in the regularity of gait during different activities. During some activities, gait tends to be regular and the repetitiveness of individual steps makes them easy to identify in an accelerometer signal. During other activities of everyday life, gait is frequently semi-regular or unstructured, which we hypothesize makes it difficult to identify and count individual steps. In this work, we test this hypothesis by evaluating the three most common types of pedometer algorithm on a new data set that varies the regularity of gait. A total of 30 participants were video recorded performing three different activities: walking a path (regular gait), conducting a within-building activity (semi-regular gait), and conducting a within-room activity (unstructured gait). Participants were instrumented with accelerometers on the wrist, hip and ankle. Collectively, 60,805 steps were manually annotated for ground truth using synchronized video. The main contribution of this paper is to evaluate pedometer algorithms when the consistency of gait changes to simulate everyday life activities other than exercise. In our study, we found that semi-regular and unstructured gaits resulted in 5-466% error. This demonstrates the need to evaluate pedometer algorithms on activities that vary the regularity of gait. Our dataset is publicly available with links provided in the introduction and Data Availability Statement.

Evaluation of a Low-Cost Commercial Actigraph and Its Potential Use in Detecting Cultural Variations in Physical Activity and Sleep

The purpose of the present study was to evaluate the performance of a low-cost commercial smartwatch, the Xiaomi Mi Band (MB), in extracting physical activity and sleep-related measures and show its potential use in addressing questions that require large-scale real-time data and/or intercultural data including low-income countries. We evaluated physical activity and sleep-related measures and discussed the potential application of such devices for large-scale step and sleep data acquisition. To that end, we conducted two separate studies. In Study 1, we evaluated the performance of MB by comparing it to the GT3X (ActiGraph, wGT3X-BT), a scientific actigraph used in research, as well as subjective sleep reports. In Study 2, we distributed the MB across four countries (Austria, Germany, Cuba, and Ukraine) and investigated physical activity and sleep among these countries. The results of Study 1 indicated that MB step counts correlated highly with the scientific GT3X device, but did display biases. In addition, the MB-derived wake-up and total-sleep-times showed high agreement with subjective reports, but partly deviated from GT3X predictions. Study 2 revealed similar MB step counts across countries, but significant later wake-up and bedtimes for Ukraine than the other countries. We hope that our studies will stimulate future large-scale sensor-based physical activity and sleep research studies, including various cultures.

"Can Do" Versus "Do Do" in Patients with Asthma at First Referral to a Pulmonologist

BACKGROUND

Pharmacotherapy is key in asthma control, including preventing lung function decline, in primary care. However, patients' physical functioning (eg, physical capacity [PC] [=can do] and physical activity [PA] [=do do]) correlates poorly with lung function. Therefore, a better insight into the physical function of patients with asthma is needed, using the "can do, do do" concept.

OBJECTIVE

To explore the "can do, do do" concept in adult patients with asthma at referral for the first time to an outpatient consultation of a pulmonologist.

METHODS

PC was measured using the six-minute walk test and PA by using an accelerometer. Patients were classified into quadrants: low PC (6-minute walking distance <70% predicted), low PA (<7000 steps/d, "'can't do, don't do"); preserved PC, low PA ("can do, don't do"); low PC, preserved PA ("'can't do, do do"); or preserved PC, preserved PA ("can do, do do").

RESULTS

A total of 479 patients with asthma had a median (interquartile range) 6-minute walking distance of 74% (66%-82%) predicted, and walked 6829 (4593-9075) steps/d. Only 29% were classified as "can do, do do," whereas 30% were classified as "can't do, don't do." The Asthma Control Questionnaire and the Asthma Quality of Life Questionnaire scores were worst in the "can't do" groups.

CONCLUSIONS

Low PC and/or PA was found in most patients with asthma at the index referral to a pulmonologist. An impaired PC is accompanied by a significantly reduced asthma control and disease-specific quality of life. This justifies further studies on safety and efficacy of nonpharmacological interventions, such as physiotherapy.

Toward Harmonized Treadmill-Based Validation of Step-Counting Wearable Technologies: A Scoping Review

BACKGROUND

The authors conducted a scoping review as a first step toward establishing harmonized (ie, consistent and compatible), empirically based best practices for validating step-counting wearable technologies.

PURPOSE

To catalog studies validating step-counting wearable technologies during treadmill ambulation.

METHODS

The authors searched PubMed and SPORTDiscus in August 2019 to identify treadmill-based validation studies that employed the criterion of directly observed (including video recorded) steps and cataloged study sample characteristics, protocol details, and analytical procedures. Where reported, speed- and wear location-specific mean absolute percentage error (MAPE) values were tabulated. Weighted median MAPE values were calculated by wear location and a 0.2-m/s speed increment.

RESULTS

Seventy-seven eligible studies were identified: most had samples averaging 54% (SD = 5%) female and 27 (5) years of age, treadmill protocols consisting of 3 to 5 bouts at speeds of 0.8 (0.1) to 1.6 (0.2) m/s, and reported measures of bias. Eleven studies provided MAPE values at treadmill speeds of 1.1 to 1.8 m/s; their weighted median MAPE values were 7% to 11% for wrist-worn, 1% to 4% for waist-worn, and ≤1% for thigh-worn devices.

CONCLUSIONS

Despite divergent study methodologies, the authors identified common practices and summarized MAPE values representing device step-count accuracy during treadmill walking. These initial empirical findings should be further refined to ultimately establish harmonized best practices for validating wearable technologies.

Low-Cost Consumer-Based Trackers to Measure Physical Activity and Sleep Duration Among Adults in Free-Living Conditions: Validation Study

Background

Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption.

Objective

This study aimed to investigate the concurrent validity of 6 low-cost activity trackers for measuring steps, moderate-to-vigorous physical activity (MVPA), and TST: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0, and Xiaomi MiBand 2.

Methods

A free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore a low-cost tracker and a high-cost tracker (Fitbit Charge HR) on the nondominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+ and BodyMedia SenseWear using mean absolute percentage error scores, correlations, and Bland-Altman plots in IBM SPSS 24.0.

Results

Large variations were shown between trackers. Low-cost trackers showed moderate-to-strong correlations (Spearman r=0.53-0.91) and low-to-good agreement (intraclass correlation coefficient [ICC]=0.51-0.90) for measuring steps. Weak-to-moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed weak-to-strong correlations (Spearman r=0.04-0.73) and low agreement (ICC=0.05-0.52). The Bland-Altman plot revealed a variation between overcounting and undercounting for measuring steps, MVPA, and TST, depending on the used low-cost tracker. None of the trackers, including Fitbit (a high-cost tracker), showed high validity to measure MVPA.

Conclusions

This study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for the measurement of steps; there was evidence of validity for measurement of sleep in some trackers, and validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with Xiaomi having the highest validity for measurement of steps and VeryFit performing relatively strong across both sleep and steps domains. Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers.

Use of Activity Trackers in Orthopaedics

Activity trackers are relatively inexpensive, easily available, and widely used by consumers. There has been increased interest in healthcare practice and research to use activity tracker data. Continuous collection of health variables including step count, heart rate, and calorimetry provides researchers and clinicians data to monitor patients after an intervention and/or encourage physical activity. The purpose of this article is to review the current use of activity trackers in orthopaedics and discuss potential applications in clinical research.

Full-Fat Dairy Food Intake is Associated with a Lower Risk of Incident Diabetes Among American Indians with Low Total Dairy Food Intake

BACKGROUND

Diet plays a key role in development of diabetes, and there has been recent interest in better understanding the association of dairy food intake with diabetes.

OBJECTIVE

This study examined the associations of full-fat and low-fat dairy food intake with incident diabetes among American Indians-a population with a high burden of diabetes.

METHODS

The study included participants from the Strong Heart Family Study (SHFS), a family-based study of cardiovascular disease in American Indians, free of diabetes at baseline (2001-2003) (n = 1623). Participants were 14-86-y-old at baseline and 60.8% were female. Dairy food intake was assessed using a Block food frequency questionnaire. Incident diabetes was defined using American Diabetes Association criteria. Parametric survival models with a Weibull distribution were used to evaluate the associations of full-fat and low-fat dairy food intake with incident diabetes. Serving sizes were defined as 250 mL for milk and 42.5 g for cheese.

RESULTS

We identified 277 cases of diabetes during a mean follow-up of 11 y. Reported intake of dairy foods was low [median full-fat dairy food intake: 0.11 serving/1000 kcal; median low-fat dairy food intake: 0.03 serving/1000 kcal]. Participants who reported the highest full-fat dairy food intake had a lower risk of diabetes compared to those who reported the lowest full-fat food dairy intake [HR (95% CI): 0.79 (0.59, 1.06); P-trend = 0.03, comparing extreme tertiles, after adjustment for age, sex, site, physical activity, education, smoking, diet quality, and low-fat dairy food intake]. Low-fat dairy food intake was not associated with diabetes.

CONCLUSIONS

American Indians who participated in the SHFS reported low dairy food intake. Participants who reported higher full-fat dairy food intake had a lower risk of diabetes than participants who reported lower intake. These findings may be of interest to populations with low dairy food intake.

IPSCL: An Accurate Indoor Positioning Algorithm Using Sensors and Crowdsourced Landmarks

Indoor positioning technology has attracted the attention of researchers due to the increasing pervasiveness of smartphones and the development of sensor technology, along with the increase of indoor time. Sensor technology, which is one of the most commonly used data sources for indoor positioning, has the advantage that sensors can receive data from a smartphone without installing any additional device. However, the readings of built-in sensors are easily affected by the surrounding environment and are even occasionally different from each other which adversely influence the accuracy of indoor positioning. Moreover, once an error occurs, it can accumulate because there is not any reference point in the sensor, only in indoor positioning. In this paper, we present an accurate indoor positioning technology, which uses smartphone built-in sensors and Bluetooth beacon-based landmarks. Our proposed algorithm chooses proper one between values of sensors alternately based on their characteristics. It exploits landmarks as the reference points of indoor positioning. It also allows individuals to add the location where they repeatedly detect the same and special beacon received signal strength indicator values as a crowdsourced landmark. Extensive experimental results show that our proposed algorithm facilitates the acquisition of accurate heading direction and coordinates of the user.

An observational study investigating the use of patient-owned technology to quantify physical activity in survivors of critical illness

BACKGROUND

Physical activity after intensive care unit (ICU) discharge is challenging to measure but could inform research and practice. A patient's smartphone may provide a novel method to quantify physical activity.

OBJECTIVES

We aimed to evaluate the feasibility and accuracy of using smartphone step counts among survivors of critical illness.

METHODS

We performed a prospective observational cohort study in 50 patients who had an ICU length of stay>48 h, owned a smartphone, were ambulatory before admission, and were likely to attend follow-up at 3 and 6 months after discharge. At follow-up, daily step counts were extracted from participants' smartphones and two FitBit pedometers, and exercise capacity (6-min walk test) and quality of life (European Quality of Life-5 Dimensions) were measured.

RESULTS

Thirty-nine (78%) patients returned at 3 months and 33 (66%) at 6 months, the median [interquartile range] smartphone step counts being 3372 [1688-5899] and 2716 [1717-5994], respectively. There was a strong linear relationship, with smartphone approximating 0.71 (0.58, 0.84) of FitBit step counts, P < 0.0001, R-squared = 0.87. There were weak relationships between step counts and the 6-min walk test distance.

CONCLUSION

Although smartphone ownership and data acquisition limit the viability of using extracted smartphone steps at this time, mean daily step counts recorded using a smartphone may act as a surrogate for a dedicated pedometer; however, the relationship between step counts and other measures of physical recovery remains unclear.

"Can do" versus "do do": A Novel Concept to Better Understand Physical Functioning in Patients with Chronic Obstructive Pulmonary Disease

BACKGROUND

Physical capacity (PC) and physical activity (PA) represent associated but separate domains of physical function. It remains unknown whether this framework may support a better understanding of the impaired physical function in patients with chronic obstructive pulmonary disease (COPD). The current study had two aims: (1) to determine the distribution of patients with COPD over the PC-PA quadrants, and (2) to explore whether differences exist in clinical characteristics between these quadrants.

METHODS

In this retrospective study, PC was measured using the six-minute walk distance (6MWD), and PA was assessed with an accelerometer. Moreover, patients' clinical characteristics were obtained. Patients were divided into the following quadrants: (I) low PC (6MWD <70% predicted), low PA, using a step-defined inactivity index (<5000 steps/day, "can't do, don't do" quadrant); (II) preserved PC, low PA ("can do, don't do" quadrant); (III) low PC, preserved PA ("can't do, do do" quadrant); and (IV) preserved PC, preserved PA ("can do, do do" quadrant).

RESULTS

The distribution of the 662 COPD patients over the quadrants was as follows: "can't do, don't do": 34%; "can do, don't do": 14%; "can't do, do do": 21%; and "can do, do do": 31%. Statistically significant differences between quadrants were found for all clinical characteristics, except for educational levels.

CONCLUSIONS

This study proves the applicability of the PC-PA quadrant concept in COPD. This concept serves as a pragmatic clinical tool, that may be useful in the understanding of the impaired physical functioning in COPD patients and therefore, may improve the selection of appropriate interventions to improve physical function.

The Accuracy of Smart Devices for Measuring Physical Activity in Daily Life: Validation Study

Background

Wearables for monitoring physical activity (PA) are increasingly popular. These devices are not only used by consumers to monitor their own levels of PA but also by researchers to track the behavior of large samples. Consequently, it is important to explore how accurately PA can be tracked via these devices.

Objectives

The aim of this study was, therefore, to investigate convergent validity of 3 Android Wear smartwatches—Polar M600 (Polar Electro Oy, Kempele, Finland), Huawei Watch (Huawei Technologies Co, Ltd, Shenzhen, Guangdong, China), Asus Zenwatch3 (AsusTek Computer Inc, Taipei, Taiwan)—and Fitbit Charge with an ActiGraph accelerometer for measuring steps and moderate to vigorous physical activity (MVPA) on both a day level and 15-min level.

Methods

A free-living protocol was used in which 36 adults engaged in usual daily activities over 2 days while wearing 2 different wearables on the nondominant wrist and an ActiGraph GT3X+ accelerometer on the hip. Validity was evaluated on both levels by comparing each wearable with the ActiGraph GT3X+ accelerometer using correlations and Bland-Altman plots in IBM SPSS 24.0.

Results

On a day level, all devices showed strong correlations (Spearman r=.757-.892) and good agreement (interclass correlation coefficient, ICC=.695-.885) for measuring steps, whereas moderate correlations (Spearman r=.557-.577) and low agreement (ICC=.377-.660) for measuring MVPA. Bland-Altman revealed a systematic overestimation of the wearables for measuring steps but a variation between over- and undercounting of MVPA. On a 15-min level, all devices showed strong correlations (Spearman r=.752-.917) and good agreement (ICC=.792-.887) for measuring steps, whereas weak correlations (Spearman r=.116-.208) and low agreement (ICC=.461-.577) for measuring MVPA. Bland-Altman revealed a systematic overestimation of the wearables for steps but under- or overestimation for MVPA depending on the device.

Conclusions

In sum, all 4 consumer-level devices can be considered accurate step counters in free-living conditions. This study, however, provides evidence of systematic bias for all devices in measurement of MVPA. The results on a 15-min level also indicate that these devices are not sufficiently accurate to provide correct real-time feedback.

Feedback From Activity Trackers Improves Daily Step Count After Knee and Hip Arthroplasty: A Randomized Controlled Trial

BACKGROUND

Commercial wrist-worn activity monitors have the potential to accurately assess activity levels and are being increasingly adopted in the general population. The aim of this study was to determine if feedback from a commercial activity monitor improves activity levels over the first 6 weeks after total hip arthroplasty (THA) or total knee arthroplasty (TKA).

METHODS

One hundred sixty-three consecutive subjects undergoing primary TKA or THA were randomized into 2 groups. Subjects received an activity tracker with the step display obscured 2 weeks before surgery and completed patient-reported outcome measures (PROMs). On day 1 after surgery, participants were randomized to either the "feedback (FB) group" or the "no feedback (NFB) group." The FB group was able to view their daily step count and was given a daily step goal. Participants in the NFB group wore the device with the display obscured for 2 weeks after surgery, after which time they were also able to see their daily step count but did not receive a formal step goal. The mean daily steps at 1, 2, 6 weeks, and 6 months were monitored. At 6 months after surgery, subjects repeated PROMs and daily step count collection.

RESULTS

Of the 163 subjects, 95 underwent THA and 68 underwent TKA. FB subjects had a significantly higher (P < .03) mean daily step count by 43% in week 1, 33% in week 2, 21% in week 6, and 17% at 6 months, compared with NFB. The FB subjects were 1.7 times more likely to achieve a mean 7000 steps per day than the NFB subjects at 6 weeks after surgery (P = .02). There was no significant difference between the groups in PROMs at 6 months. Ninety percent of FB and 83% of NFB participants reported that they were satisfied with the results of the surgery (P = .08). At 6 months after surgery, 70% of subjects had a greater mean daily step count compared with their preoperative level.

CONCLUSION

Subjects who received feedback from a commercial activity tracker with a daily step goal had significantly higher activity levels after hip and knee arthroplasty over 6 weeks and 6 months, compared with subjects who did not receive feedback in a randomized controlled trial. Commercial activity trackers may be a useful and effective adjunct after arthroplasty.

Dietary Intake and Physical Activity Assessment: Current Tools, Techniques, and Technologies for Use in Adult Populations

Accurate assessment of dietary intake and physical activity is a vital component for quality research in public health, nutrition, and exercise science. However, accurate and consistent methodology for the assessment of these components remains a major challenge. Classic methods use self-report to capture dietary intake and physical activity in healthy adult populations. However, these tools, such as questionnaires or food and activity records and recalls, have been shown to underestimate energy intake and expenditure as compared with direct measures like doubly labeled water. This paper summarizes recent technological advancements, such as remote sensing devices, digital photography, and multisensor devices, which have the potential to improve the assessment of dietary intake and physical activity in free-living adults. This review will provide researchers with emerging evidence in support of these technologies, as well as a quick reference for selecting the "right-sized" assessment method based on study design, target population, outcome variables of interest, and economic and time considerations.

THEME INFORMATION

This article is part of a theme issue entitled Innovative Tools for Assessing Diet and Physical Activity for Health Promotion, which is sponsored by the North American branch of the International Life Sciences Institute.

Accuracy of a smartphone pedometer application according to different speeds and mobile phone locations in a laboratory context

BACKGROUND

The purpose of this study was to compare the accuracy of a smartphone application and a mechanical pedometer for step counting at different walking speeds and mobile phone locations in a laboratory context.

METHODS

Seventeen adults wore an iPphone6© with Runtastic Pedometer© application (RUN), at 3 different locations (belt, arm, jacket) and a pedometer (YAM) at the waist. They were asked to walk on an instrumented treadmill (reference) at various speeds (2, 4 and 6 km/h).

RESULTS

RUN was more accurate than YAM at 2 km/h (p < 0.05) and at 4 km/h (p = 0.03). At 6 km/h the two devices were equally accurate. The precision of YAM increased with speed (p < 0.05), while for RUN, the results were not significant but showed a trend (p = 0.051). Surprisingly, YAM underestimates the number of step by 60.5% at 2 km/h. The best accurate step counting (0.7% mean error) was observed when RUN is attached to the arm and at the highest speed.

CONCLUSIONS

RUN pedometer application could be recommended mainly for walking sessions even for low walking speed. Moreover, our results confirm that the smartphone should be strapped close to the body to discriminate steps from noise by the accelerometers (particularly at low speed).

Controlled before-after intervention study of suburb-wide street changes to increase walking and cycling: Te Ara Mua-Future Streets study design

BACKGROUND

Achieving a shift from car use to walking, cycling and public transport in cities is a crucial part of healthier, more environmentally sustainable human habitats. Creating supportive active travel environments is an important precursor to this shift. The longevity of urban infrastructure necessitates retrofitting existing suburban neighbourhoods. Previous studies of the effects of street changes have generally relied on natural experiments, have included few outcomes, and have seldom attempted to understand the equity impacts of such interventions.

METHODS

In this paper we describe the design of Te Ara Mua - Future Streets, a mixed-methods, controlled before-after intervention study to assess the effect of retrofitting street changes at the suburb scale on multiple health, social and environmental outcomes. The study has a particular focus on identifying factors that improve walking and cycling to local destinations in low-income neighbourhoods and on reducing social and health inequities experienced by Māori (Indigenous New Zealanders) and Pacific people. Qualitative system dynamics modelling was used to develop a causal theory for the relationships between active travel, and walking and cycling infrastructure. On this basis we selected outcomes of interest. Together with the transport funder, we triangulated best evidence from the literature, transport policy makers, urban design professionals and community knowledge to develop interventions that were contextually and culturally appropriate. Using a combination of direct observation and random sample face to face surveys, we are measuring outcomes in these domains of wellbeing: road-user behaviour, changes to travel mode for short trips, physical activity, air quality, road traffic injuries, greenhouse gas emissions, and perceptions of neighbourhood social connection, safety, and walking and cycling infrastructure .

DISCUSSION

While building on previous natural experiments, Te Ara Mua - Future Streets is unique in testing an intervention designed by the research team, community and transport investors together; including a wide range of objective outcome measures; and having an equity focus. When undertaking integrated intervention studies of this kind, a careful balance is needed between epidemiological imperatives, the constraints of transport funding and implementation and community priorities, while retaining the ability to contribute new evidence for healthy, equitable transport policy. The study was retrospectively registered as a clinical trial on 21 June 2018 in the ISCRTN registry: ISRCTN89845334 http://www.isrctn.com/ISRCTN89845334.

A systematic literature review of reviews on techniques for physical activity measurement in adults: a DEDIPAC study

The links between increased participation in Physical Activity (PA) and improvements in health are well established. As this body of evidence has grown, so too has the search for measures of PA with high levels of methodological effectiveness (i.e. validity, reliability and responsiveness to change). The aim of this “review of reviews” was to provide a comprehensive overview of the methodological effectiveness of currently employed measures of PA, to aid researchers in their selection of an appropriate tool. A total of 63 review articles were included in this review, and the original articles cited by these reviews were included in order to extract detailed information on methodological effectiveness.

Self-report measures of PA have been most frequently examined for methodological effectiveness, with highly variable findings identified across a broad range of behaviours. The evidence-base for the methodological effectiveness of objective monitors, particularly accelerometers/activity monitors, is increasing, with lower levels of variability observed for validity and reliability when compared to subjective measures. Unfortunately, responsiveness to change across all measures and behaviours remains under-researched, with limited information available.

Other criteria beyond methodological effectiveness often influence tool selection, including cost and feasibility. However, researchers must be aware of the methodological effectiveness of any measure selected for use when examining PA. Although no “perfect” tool for the examination of PA in adults exists, it is suggested that researchers aim to incorporate appropriate objective measures, specific to the behaviours of interests, when examining PA in free-living environments.

Comparison of Different Physical Activity Measurement Methods in Adults Aged 45 to 64 Years Under Free-Living Conditions

OBJECTIVE

To compare physical activity (PA) measured by 4 methods in adults under free-living conditions in relation to selected demographic and anthropometric variables.

DESIGN

Cohort study.

SETTING

Department of Sports Medicine.

PARTICIPANTS

Clinically healthy men (81) and women (69) aged 45 to 64 years.

INTERVENTIONS

Physical activity monitoring for 7 consecutive days under free-living conditions by pedometer (P) and accelerometer (A) simultaneously and PA questionnaires: International Physical Activity Questionnaire (IPAQ) and Seven-Day Physical Activity Questionnaire Recall (SDPAR) completed after the 7-day PA.

MAIN OUTCOME MEASURES

Comparison of PA measured by pedometer, IPAQ, and SDPAR with accelerometer with regard to age, body mass, gender, and obesity type.

RESULTS

Total energy expenditure (EE) by IPAQ was higher than A (P < 0.001) in both groups regardless of age, body mass, or obesity type. Mean EE value by P was greater than A (P < 0.001) in central-obesity males and lower than A (P < 0.001) in central-obesity females. There were differences in step counts in women, unnoticed in men. SDPAR overestimated total EE in gynoid-obesity males and in central-obesity females compared with A. Ninety-five percent CI was the largest around IPAQ compared with P and SDPAR, with SDPAR showing the best agreement with A.

CONCLUSIONS

Body mass and obesity type influenced PA measurements. To monitor PA, it is recommended to use pedometer in normal bodyweight and overweight groups while accelerometer is advisable in obese subjects. A combined approach of objective and subjective PA monitoring tools is preferable.

Relationship between ambulatory physical activity assessed by activity trackers and physical frailty among nursing home residents

BACKGROUNDS

The aim of this study was to assess the relationship between the level of ambulatory physical activity, measured by physical activity tracker, and the clinical components of physical frailty, among nursing home residents.

METHODS

We proceeded in 3 steps: (1) Validation of the physical activity tracker (i.e. the Pebble): 24 volunteer adults walked on a treadmill. The number of steps recorded by the Pebble worn by the subjects was compared with the number of steps counted by the investigators, by means of the Intra-class correlation coefficients (ICC). (2) Measurement of ambulatory physical activity, using the Pebble trackers, over a 7-day period. (3) Relationship between the results obtained with the Pebble trackers (step 2) and subjects' clinical characteristics, linked to physical frailty.

RESULTS

ICC data, showed that the reliability of the Pebble was better when it was worn at the foot level (ICC ranged from 0.60 to 0.93 depending on the tested speed). Gait speed is also an important determinant of the reliability, which is better for low gait speed. On average, the 27 nursing home residents included in the second step of this study walked 1678.4±1621 (median=1300) steps per day. Most physical components of frailty measured in this study were significantly different between subjects who walked less than 1300 steps per day and those who were more active.

CONCLUSION

This study showed that nursing home residents have a poor ambulatory physical activity, assessed using a physical activity tracker, which is associated with poorer physical performances and higher disability.

Comparing accelerometer, pedometer and a questionnaire for measuring physical activity in bronchiectasis: a validity and feasibility study?

Background

There are challenges for researchers and clinicians to select the most appropriate physical activity tool, and a balance between precision and feasibility is needed. Currently it is unclear which physical activity tool should be used to assess physical activity in Bronchiectasis. The aim of this research is to compare assessment methods (pedometer and IPAQ) to our criterion method (ActiGraph) for the measurement of physical activity dimensions in Bronchiectasis (BE), and to assess their feasibility and acceptability.

Methods

Patients in this analysis were enrolled in a cross-sectional study. The ActiGraph and pedometer were worn for seven consecutive days and the IPAQ was completed for the same period. Statistical analyses were performed using SPSS 20 (IBM). Descriptive statistics were used; the percentage agreement between ActiGraph and the other measures were calculated using limits of agreement. Feedback about the feasibility of the activity monitors and the IPAQ was obtained.

Results

There were 55 (22 male) data sets available. For step count there was no significant difference between the ActiGraph and Pedometer, however, total physical activity time (mins) as recorded by the ActiGraph was significantly higher than the pedometer (mean ± SD, 232 (75) vs. 63 (32)). Levels of agreement between the two devices was very good for step count (97% agreement); and variation in the levels of agreement were within accepted limits of ±2 standard deviations from the mean value.

IPAQ reported more bouted- moderate - vigorous physical activity (MVPA) [mean, SD; 167(170) vs 6(9) mins/day], and significantly less sedentary time than ActiGraph [mean, SD; 362(115) vs 634(76) vmins/day]. There were low levels of agreement between the two tools (57% sedentary behaviour; 0% MVPA₁₀₊), with IPAQ under-reporting sedentary behaviour and over-reporting MVPA₁₀₊ compared to ActiGraph. The monitors were found to be feasible and acceptable by participants and researchers; while the IPAQ was accepta ble to use, most patients required assistance to complete it.

Conclusions

Accurate measurement of physical activity is feasible in BE and will be valuable for future trials of therapeutic interventions. ActiGraph or pedometer could be used to measure simple daily step counts, but ActiGraph was superior as it measured intensity of physical activity and was a more precise measure of time spent walking. The IPAQ does not appear to represent an accurate measure of physical activity in this population.

Trial registration

Clinical Trials Registration Number NCT01569009: Physical Activity in Bronchiectasis.

Physical activity and nutrition behaviour outcomes of a cluster-randomized controlled trial for adults with metabolic syndrome in Vietnam

Background

Metabolic syndrome is prevalent among Vietnamese adults, especially those aged 50–65 years. This study evaluated the effectiveness of a 6 month community-based lifestyle intervention to increase physical activity levels and improve dietary behaviours for adults with metabolic syndrome in Vietnam.

Methods

Ten communes, involving participants aged 50–65 years with metabolic syndrome, were recruited from Hanam province in northern Vietnam. The communes were randomly allocated to either the intervention (five communes, n = 214) or the control group (five communes, n = 203). Intervention group participants received a health promotion package, consisting of an information booklet, education sessions, a walking group, and a resistance band. Control group participants received one session of standard advice during the 6 month period. Data were collected at baseline and after the intervention to evaluate programme effectiveness. The International Physical Activity Questionnaire – Short Form and a modified STEPS questionnaire were used to assess physical activity and dietary behaviours, respectively, in both groups. Pedometers were worn by the intervention participants only for 7 consecutive days at baseline and post-intervention testing. To accommodate the repeated measures and the clustering of individuals within communes, multilevel mixed regression models with random effects were fitted to determine the impacts of intervention on changes in outcome variables over time and between groups.

Results

With a retention rate of 80.8%, the final sample comprised 175 intervention and 162 control participants. After controlling for demographic and other confounding factors, the intervention participants showed significant increases in moderate intensity activity (P = 0.018), walking (P < 0.001) and total physical activity (P = 0.001), as well as a decrease in mean sitting time (P < 0.001), relative to their control counterparts. Significant improvements in dietary behaviours were also observed, particularly reductions in intake of animal internal organs (P = 0.001) and in using cooking oil for daily meal preparation (P = 0.001).

Conclusions

The prescribed community-based physical activity and nutrition intervention programme successfully improved physical activity and dietary behaviours for adults with metabolic syndrome in Vietnam.

Trial registration

Australian New Zealand Clinical Trials Registry, ACTRN12614000811606. Registered on 31 July 2014

Electronic supplementary material

The online version of this article (doi:10.1186/s13063-016-1771-9) contains supplementary material, which is available to authorized users.

Assessment of pedometer accuracy in capturing habitual types of physical activities in overweight and obese children

BACKGROUND

Currently, there is a limited amount of research exploring physical activity measurement tools in overweight and obese (OW/OB) children using pedometers. Thus, our objective was to determine the accuracy of one spring-levered (SC-T2) and two piezoelectric pedometers (NL-1000 and Piezo) in OW/OB children.

METHODS

A total of 26 boys and 34 girls (n = 60) participated. Pedometer step-counts were compared to observed step counts for walking (walking, stair ascent and decent) and hopping tests. Pedometer accuracies were compared with Friedman tests while Bland-Altman plots were used to establish the accuracy of each pedometer against direct observations.

RESULTS

Boys (n = 26) and females (n = 34) were 96 and 91% OB, respectively. The two piezoelectric pedometers (NL-1000 and Piezo) were accurate for walking and stair climbing tasks, however all pedometers were inaccurate for hopping tests. Averaged over all three walking activities, the NL-1000 was the most accurate with 6.7% median error (interquartile range (IQR): 0.0-13.3); followed by the Piezo with 10.0% median error (IQR: 3.3-18.1); SC-T2 was the least accurate with -14.7% median error (IQR: -54.8-3.5).

CONCLUSION

These results support the use of the piezoelectric pedometers for walking and stair climbing types of activities, which are typical for OW/OB children in a nonlaboratory setting.

Effects of a 12-Month Pedometer-Based Walking Intervention in Women of Low Socioeconomic Status

This study examined the effects of a 12-month walking intervention in overweight/obese, low socioeconomic women. Forty-six women (48.2 ± 8.0 years) entered the study. Outcomes included weight, waist and hip circumferences, body mass index (BMI), blood pressure, glycosylated hemoglobin, blood lipids, fibrinogen, and high-sensitivity C-reactive protein (hsCRP). Both intention-to-treat analyses in all participants and group analyses in study completers only (3K group = increased steps/day by ≥3,000; No Δ group = did not increase steps/day by ≥3,000) were conducted. Group × time ANOVA was used. In study completers, 3K significantly increased steps/day (6,903 ± 3,328 to 12,323 ± 5,736) compared to No Δ (4,926 ± 3,374 to 5,174 ± 3,095) from baseline to 12 months. There was a significant time effect for weight (P = 0.030), BMI (P = 0.029), and hsCRP (P = 0.044). Low socioeconomic women who adhere to a long-term, pedometer-based walking intervention significantly increased steps/day and may improve body weight, BMI, and hsCRP. This could help reduce health disparities in this population over time.

Using Pedometers to Increase the Non-Workday Steps of Hospital Nursing and Support Staff: A Pilot Study

Nursing is a physically active profession; however, nurses and nursing support staff may limit their physical activity (PA) on non-workdays. The purpose of this pilot study was to examine the effects of a 12-week pedometer-based PA intervention on daily steps of hospital nursing and support staff from two departments, emergency (ED) and oncology (ONC). The 12-week minimal-contact, self-managed intervention was designed to increase total and non-workday PA. Twenty participants with an average age of 47.6 ± 7.1 years completed the intervention. Significant differences were found between total daily steps at baseline (8,446) and at 12 weeks (10,655; p = .014), and between workday steps at baseline (10,398) and at 12 weeks (13,056; p = 0.005). Oncology unit participants significantly increased their non-workday steps from baseline (5,850) to 12 weeks (9,829; p = .003). As part of a comprehensive intervention, pedometers can promote total and non-workday PA of nursing and support staff.

Measurement of physical activity in obese persons: how and why? A review

[Purpose] Overweight and obesity are major risk factors for poor health, especially in children. Reduced physical activity, prompted by a sedentary lifestyle, is a major contributor. Hence, it is important to assess physical activity using standardized methods in public health to identify the risks associated with obesity. There have been no recent reports comparing such modalities for use by clinicians and researchers. In this article, some of these methods for use in the assessment of physical activity are reviewed, and their advantages and disadvantages are described. [Subjects and Methods] Electronic databases including PubMed, Medline, and Google Scholar were searched for literature, using key words Obesity, Physical activity, and Physical Behavior Monitoring. [Results] With advances in technology, various novel methods have been developed to assess physical behavior, but conventional methods are still relevant and easy to administer. [Conclusion] There are various measurement options available. Researchers may choose devices providing more accurate measurements, while clinicians may prefer portability and affordability for patients.

Effects of a 10,000 Steps per Day Goal in Overweight Adults

Purpose.

This study was designed (1) to examine the effects of a 10,000 steps·d−1 exercise prescription on sedentary, overweight/obese adults, and (2) to examine the effects of adherence on body composition and cardiovascular risk factors.

Methods.

Fifty-six overweight/obese adults participated in the study. Body composition and cardiovascular risk factors were determined at baseline, 20 weeks, and 36 weeks. Adherence was defined as averaging ≥ 9500 steps·d−1 from week 4 to week 36.

Results.

38 participants (68%) wore pedometers daily for 36 weeks and were available for posttesting. Significant improvements were noted in mean values for walking volume (3994 steps·d−1), body weight (–2.4 kg), body mass index (–0.8 kg·m−2), percentage body fat (–1.9%), fat mass (–2.7 kg), waist circumference (–1.8 cm), hip circumference (–1.9 cm) and high-density lipoprotein (3 mg/dl). The adherers had large improvements in body composition measures, whereas the nonadherers showed little or no change in these variables.

Discussion.

A 10,000 steps·d−1 exercise prescription resulted in weight loss over 36 weeks in previously sedentary, overweight/obese adults. Adherence to the step goal had a marked effect on the outcome.

Mobile and Wearable Device Features that Matter in Promoting Physical Activity

BACKGROUND

As wearable sensors/devices become increasingly popular to promote physical activity (PA), research is needed to examine how and which components of these devices people use to increase their PA levels.

AIMS

(1) To assess usability and level of engagement with the Fitbit One and daily SMS-based prompts in a 6-week PA intervention, and (2) to examine whether use/ level of engagement with specific intervention components were associated with PA change.

METHODS

Data were analyzed from a randomized controlled trial that compared (1) a wearable sensor/ device (Fitbit One) plus SMS-based PA prompts, and (2) Fitbit One only, among overweight/ obese adults (N = 67). We calculated average scores from Likert-type response items that assessed usability and level of engagement with device features (e.g., tracker, website, mobile app, and SMS-based prompts), and assessed whether such factors were associated with change in steps/day (using Actigraph GT3X+).

RESULTS

Participants reported the Fitbit One was easy to use and the tracker helped to be more active. Those who used the Fitbit mobile app (36%) vs. those who did not (64%) had an increase in steps at 6-week follow-up, even after adjusting for previous web/app use: +545 steps/ day (SE = 265) vs. -28 steps/ day (SE = 242) (p = .04).

CONCLUSIONS

Level of engagement with the Fitbit One, particularly the mobile app, was associated with increased steps. Mobile apps can instantly display summaries of PA performance and could optimize self-regulation to activate change. More research is needed to determine whether such modalities might be cost-effective in future intervention research and practice.

Impact of Prescribed Exercise on Physical Activity Compensation in Young Adults

Liguori, G, Schuna, JM Jr, Tucker, J, and Fountaine, CM. Impact of prescribed exercise on physical activity compensation in young adults. J Strength Cond Res 31(2): 503-508, 2017-Army Reserve Officers' Training Corps cadets present a unique subpopulation because they are required to participate in regular physical activity (PA). This study describes PA patterns of cadets and attempts to identify evidence of nonexercise PA compensation (activitystat) as a result of prescribed PA (pPA) by comparing differences between training and nontraining days for (a) autonomous PA among cadets and (b) PA between cadets and noncadets. Participants included 84 university students (33 cadets and 51 noncadets) who each wore an accelerometer for 5 consecutive days to estimate moderate and vigorous physical activity (MVPA). A 2×2 mixed model analysis of variance was used to examine within- and between-group differences in MVPA on training and nontraining days. This analysis was repeated after removing the cadet's pPA. Cadets had lower-body fat than noncadets (p = 0.044), but all other characteristics were similar. Overall, moderate PA (MPA) and vigorous PA (VPA) were significantly greater among cadets (p = 0.048 and p < 0.001), because of greater weekend MPA (p = 0.021) and greater weekday VPA (p < 0.001). Cadets accumulated more MVPA on training days than nontraining days (p < 0.001) and accumulated more MVPA than noncadets on training days (p = 0.004). However, after accounting for pPA, cadet MVPA did not differ between training and nontraining days (within 1.2Â ± 18.4 min·d) and was similar between cadets and noncadets (within 1.5Â ± 5.9 min·d). These results suggest that cadets were significantly more active than noncadets due mainly to pPA. When controlling for pPA, cadets were similarly active across all days, and were as active as noncadets, indicating no evidence of activitystat in this population.

How Much Improvement in Patient Activity Can Be Expected After TKA?

Most patients expect an improvement of physical activity after total knee arthroplasty (TKA). The aim of this study was to evaluate improvement in physical activity after TKA. An accelerometer was used to measure activity in 221 patients before and 1 year after TKA. The measurements included the total number of steps and time spent lying, sitting/standing, or walking. Threshold for achievement of health-enhancing physical activity (HEPA) guidelines and step-defined lifestyle were applied to the data. Measured steps per day improved from 5371 to 6587. Only 50 patients (22.6%) met the HEPA guidelines, whereas 31% achieved an active lifestyle. Improvement in daily step number was influenced by age (P<.001), body mass index (P<.001) and preoperative activity (P<.001). After TKA, patients improved in physical activity and one-third achieved an active lifestyle. Patient-specific characteristics and preoperative levels of physical activity had a relevant influence on activity after TKA. [Orthopedics. 2016; 39(3):S18-S23.].

Activity Monitors Step Count Accuracy in Community-Dwelling Older Adults

Objective: To examine the step count accuracy of activity monitors in community-dwelling older adults. Method: Twenty-nine participants aged 67.70 ± 6.07 participated. Three pedometers and the Actical accelerometer step count functions were compared with actual steps taken during a 200-m walk around an indoor track and during treadmill walking at three different speeds. Results: There was no statistical difference between activity monitors step counts and actual steps during self-selected pace walking. During treadmill walking at 0.67 m∙s⁻¹, all activity monitors step counts were significantly different from actual steps. During treadmill walking at 0.894m∙s⁻¹, the Omron HJ-112 pedometer step counts were not significantly different from actual steps. During treadmill walking at 1.12 m∙s⁻¹, the Yamax SW-200 pedometer steps were significantly different from actual steps. Discussion: Activity monitor selection should be deliberate when examining the walking behaviors of community-dwelling older adults, especially for those who walk at a slower pace.

Wearable Sensor/Device (Fitbit One) and SMS Text-Messaging Prompts to Increase Physical Activity in Overweight and Obese Adults: A Randomized Controlled Trial

BACKGROUND

Studies have shown self-monitoring can modify health behaviors, including physical activity (PA). This study tested the utility of a wearable sensor/device (Fitbit(®) One™; Fitbit Inc., San Francisco, CA) and short message service (SMS) text-messaging prompts to increase PA in overweight and obese adults.

MATERIALS AND METHODS

Sixty-seven adults wore a Fitbit One tracker for 6 weeks; half were randomized to also receive three daily SMS-based PA prompts. The Fitbit One consisted of a wearable tracker for instant feedback on performance and a Web site/mobile application (app) for detailed summaries. Outcome measures were objectively measured steps and minutes of PA by intensity using two accelerometers: Actigraph™ (Pensacola, FL) GT3X+ (primary measure) at baseline and Week 6 and Fitbit One (secondary measure) at baseline and Weeks 1, 2, 3, 4, 5, and 6.

RESULTS

Mixed-model repeated-measures analysis of primary measures indicated a significant within-group increase of +4.3 (standard error [SE]=2.0) min/week of moderate- to vigorous-intensity PA (MVPA) at 6-week follow-up (p=0.04) in the comparison group (Fitbit only), but no study group differences across PA levels. Secondary measures indicated the SMS text-messaging effect lasted for only 1 week: the intervention group increased by +1,266 steps (SE=491; p=0.01), +17.8 min/week MVPA (SE=8.5; p=0.04), and +38.3 min/week total PA (SE=15.9; p=0.02) compared with no changes in the comparison group, and these between-group differences were significant for steps (p=0.01), fairly/very active minutes (p<0.01), and total active minutes (p=0.02).

CONCLUSIONS

These data suggest that the Fitbit One achieved a small increase in MVPA at follow-up and that the SMS-based PA prompts were insufficient in increasing PA beyond 1 week. Future studies can test this intervention in those requiring less help and/or test strategies to increase participants' engagement levels.

Validity of activity monitors worn at multiple nontraditional locations under controlled and free-living conditions in young adult women

The purpose of this study was to examine the validity of counting steps and computing indices of moderate-to-vigorous physical activity (MVPA) using miniature activity monitors with 3-D technology worn at various locations under controlled (CON) and free-living conditions (FL). Kenz e-style2, Tanita Calorism Smart, and Omron Calori Scan HJA-306 activity monitors were assessed. Nine and 31 young adult women were assigned to the CON and FL studies, respectively. While walking or jogging on a treadmill at 5 different speeds, the subjects simultaneously carried the 3 different monitors in a pants pocket (PP), a chest shirt pocket, and a shoulder bag (B). Under the FL condition, the 3 monitors were placed only at the PP and B locations for practical reasons. Significant effects of monitor location and walking/jogging speed on the step count measured by the 3 monitors were evaluated under the CON condition. Monitors placed at both PP and B tended to underestimate the number of steps; however, there were no significant differences between the values obtained with the Kenz monitor and those obtained with a criterion accelerometer under the FL condition. Moreover, strong correlations were observed between steps measured by monitors placed at PP and steps measured by the criterion accelerometer. The amount of MVPA for the PP location and the non-carrying duration of the bag for the B location were considered to be important determinants of the accuracy of step counting under the FL condition. In conclusion, monitors placed at the PP location, especially the Kenz monitor, showed acceptable accuracy for young adult women in real-life settings. In contrast, MVPA indices assessed using these monitors showed limited validity.

The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study

Background

Technological advances have seen a burgeoning industry for accelerometer-based wearable activity monitors targeted at the consumer market. The purpose of this study was to determine the convergent validity of a selection of consumer-level accelerometer-based activity monitors.

Methods

21 healthy adults wore seven consumer-level activity monitors (Fitbit One, Fitbit Zip, Jawbone UP, Misfit Shine, Nike Fuelband, Striiv Smart Pedometer and Withings Pulse) and two research-grade accelerometers/multi-sensor devices (BodyMedia SenseWear, and ActiGraph GT3X+) for 48-hours. Participants went about their daily life in free-living conditions during data collection. The validity of the consumer-level activity monitors relative to the research devices for step count, moderate to vigorous physical activity (MVPA), sleep and total daily energy expenditure (TDEE) was quantified using Bland-Altman analysis, median absolute difference and Pearson’s correlation.

Results

All consumer-level activity monitors correlated strongly (r > 0.8) with research-grade devices for step count and sleep time, but only moderately-to-strongly for TDEE (r = 0.74-0.81) and MVPA (r = 0.52-0.91). Median absolute differences were generally modest for sleep and steps (<10% of research device mean values for the majority of devices) moderate for TDEE (<30% of research device mean values), and large for MVPA (26-298%). Across the constructs examined, the Fitbit One, Fitbit Zip and Withings Pulse performed most strongly.

Conclusions

In free-living conditions, the consumer-level activity monitors showed strong validity for the measurement of steps and sleep duration, and moderate valid for measurement of TDEE and MVPA. Validity for each construct ranged widely between devices, with the Fitbit One, Fitbit Zip and Withings Pulse being the strongest performers.

Patient activity after TKA depends on patient-specific parameters

BACKGROUND

Most patients expect an improvement of walking ability and an increase in activity levels after TKA. Unfortunately, few studies report qualitative and quantitative activity improvements after TKA.

QUESTIONS/PURPOSES

The aims of this study were (1) to evaluate quantity and quality of physical activity before and after TKA with an accelerometer, and to compare activity level with that of an age-matched control group without lower-extremity disorders. (2) Improvement in measured steps per day after TKA and the ability to meet physical activity guidelines were evaluated. (3) The influence of patient-specific and implant parameters were assessed.

PATIENTS AND METHODS

An accelerometer was used to measure activity in 97 patients who were assessed before TKA and 1 year after TKA. The measurements included the total number of steps, moderate to vigorous activity defined as at least 100 steps per minute, and time spent lying, sitting/standing, or walking. We then calculated the proportion of patients who met the 10,000 steps per day guideline recommendation and determined factors that predicted failure to meet that goal. Thirty-nine age-matched control subjects without lower-extremity disorders were selected and underwent the same assessments using the accelerometer for comparison with patients 1 year after TKA.

RESULTS

Measured steps per day improved from a mean of 5278 (SD, 2999) preoperatively to 6473 (SD, 3654) postoperatively (effect size, 1.23; 95% CI, 1.10-1.35; p < 0.001). Moderate to vigorous steps per day improved from a mean of 1150 (SD, 982) to 1935 (SD, 1728; p < 0.001). Times spent in lying, sitting, or standing position or during walking did not change after TKA. For all measured parameters, activity of the patients after TKA was considerably less than that of the age-matched control subjects, who walked a mean of 13,375 (SD, 4614) steps per day (p < 0.001), performed a mean of 6562 (SD, 3401) vigorous steps per day (p < 0.001), and spent a mean of 2.9 hours (SD, 1.1) per day walking (p < 0.001). Only 16 patients (16.5%) met physical activity guidelines after TKA. BMI (p = 0.017), sex (p = 0.027), and comorbidities (American Society of Anesthesiologists Grade, p = 0.042) were independent factors associated with steps per day after TKA.

CONCLUSIONS

One year after TKA, patients had increased walking and moderate to vigorous steps. However, only 16.5% achieved the guideline recommendations for walking activity. BMI, sex, and comorbidities are patient factors that are associated with activity after TKA. Even with improvements in walking, activity level after TKA remains less than that seen for age-matched control subjects. Surgeons should be aware of this when counseling patients undergoing TKA.

LEVEL OF EVIDENCE

Level III, therapeutic study. See the Instructions for Authors for a complete description of levels of evidence.

Compliance to step count and vegetable serve recommendations mediates weight gain prevention in mid-age, premenopausal women. Findings of the 40-Something RCT

The 40-Something RCT aimed to determine if a 12-month health professional-led intervention could modify diet and physical activity behaviour for obesity prevention, in 44-50 year old, non-obese (BMI = 18.5-29.9 kg/m(2)) premenopausal women. Women were monitored for an additional 12 months to determine if effects could be maintained. This paper aimed to explore dietary and physical activity behavioural mediators hypothesised to be causally associated with weight change. Fifty-four women were randomised to a Motivational Interviewing Intervention (MI) (n = 28; five health professional consultations) or a Self-Directed Intervention (n = 26; written advice). Compliance to 10 study recommendations was measured at three months by a four-day weighed food and physical activity record including pedometer-measured step counts, self-reported exercise minutes and sitting time. The 10 compliance scores were independently assessed in mediation models for 12- and 24-month weight change. The MI effect on step count was an increase of 0.99 points on the 10-point compliance scale (p ≤ 0.01). This MI effect on step count significantly mediated the 12 and 24 month effect on weight (12 months AB = -0.74, 95%CI = -1.95, -0.14; 24 months AB = -1.06, 95% CI = -2.56, -0.36), accounting for 37.23% and 53.79% of the effect, respectively. The MI effect on vegetable serves was an increase of 1.50 points on the compliance scale (p = 0.02). The MI effect on vegetable compliance significantly mediated the effect on weight at 24 months (AB = -0.54, 95% CI = -1.50, -0.04), accounting for 24.92% of the effect. The remaining eight dietary and physical activity compliance scores did not significantly mediate weight loss. Encouraging women to take 10,000 steps and eat five vegetable serves per day may be a promising strategy to achieve long-term weight control at mid-life.

Assessment of physical activity and energy expenditure: an overview of objective measures

The ability to assess energy expenditure (EE) and estimate physical activity (PA) in free-living individuals is extremely important in the global context of non-communicable diseases including malnutrition, overnutrition (obesity), and diabetes. It is also important to appreciate that PA and EE are different constructs with PA defined as any bodily movement that results in EE and accordingly, energy is expended as a result of PA. However, total energy expenditure, best assessed using the criterion doubly labeled water (DLW) technique, includes components in addition to physical activity energy expenditure, namely resting energy expenditure and the thermic effect of food. Given the large number of assessment techniques currently used to estimate PA in humans, it is imperative to understand the relative merits of each. The goal of this review is to provide information on the utility and limitations of a range of objective measures of PA and their relationship with EE. The measures discussed include those based on EE or oxygen uptake including DLW, activity energy expenditure, physical activity level, and metabolic equivalent; those based on heart rate monitoring and motion sensors; and because of their widespread use, selected subjective measures.

The SHED-IT community trial: a randomized controlled trial of internet- and paper-based weight loss programs tailored for overweight and obese men

BACKGROUND

There is limited evidence for effective obesity treatment programs that engage men.

PURPOSE

This study evaluated the efficacy of two gender-tailored weight loss interventions for men, which required no face-to-face contact.

METHODS

This was a three-arm, randomized controlled trial: (1) Resources (n = 54), gender-tailored weight loss materials (DVD, handbooks, pedometer, tape measure); (2) Online (n = 53), Resources materials plus study website and e-feedback; and (3) Wait-list control (n = 52). The interventions lasted 3 months and were grounded in Social Cognitive Theory.

RESULTS

At 6 months, significantly greater weight loss was observed for the Online (-4.7 kg; 95 % CI -6.1, -3.2) and Resources (-3.7 kg; 95 % CI -4.9, -2.5) groups compared to the control (-0.5 kg; 95 % CI -1.4, 0.4). Additionally, both intervention groups significantly improved body mass index, percent body fat, waist circumference, blood pressure, physical activity, quality of life, alcohol risk, and portion size, compared to controls.

CONCLUSIONS

Men achieved significant weight loss after receiving novel, minimal-contact, gender-tailored programs, which were designed for widespread dissemination.

Placement makes a difference: accuracy of an accelerometer in measuring step number and stair climbing

Accurate and easy-to-use measurement tools are required to evaluate the effect of treatments on patient activity. Comfortable device placement and fixation are important for patient compliance. The aim of this study was the evaluation of the accuracy of an accelerometer at different placements and slow velocities.

METHODS

A total of 43 healthy volunteers were included for a literature-based treadmill protocol using five accelerometer positions; a subset of 18 volunteers performed an extended treadmill protocol with velocities between 0.1 and 2.6m/s and finally stair climbing.

RESULTS

An alternative accelerometer position at the anterolateral aspect of the middle shank did measure steps more accurately than at the manufacturer suggested position, especially during slow velocities. Participants preferred the alternative placement at the shank. The accuracy of different accelerometer positions was excellent at velocities between 1.0 and 2.2m/s. During slow velocities below 1.0m/s steps were recorded less accurately. Accepting an error of five percent, the accelerometer recorded steps accurately from 0.5m/s at the alternative placement and from 0.8m/s at the manufacturer suggested placement. Stair climbing was not recorded accurately by any accelerometer position.

CONCLUSION

For measuring step number during slow velocities, the alternative position should be favoured. Stair climbing was not recorded accurately by any tested placement.

Accuracy of 2 activity monitors in detecting steps in people with stroke and traumatic brain injury

BACKGROUND

Advances in sensor technologies and signal processing techniques provide a method to accurately measure walking activity in the home and community. Activity monitors geared toward consumer or patient use may be an alternative to more expensive monitors designed for research to measure stepping activity.

OBJECTIVE

The objective of this study was to examine the accuracy of 2 consumer/patient activity monitors, the Fitbit Ultra and the Nike+ Fuelband, in identifying stepping activity in people with stroke and traumatic brain injury (TBI). Secondarily, the study sought to compare the accuracy of these 2 activity monitors with that of the StepWatch Activity Monitor (SAM) and a pedometer, the Yamax Digi-Walker SW-701 pedometer (YDWP).

DESIGN

A cross-sectional design was used for this study.

METHOD

People with chronic stroke and TBI wore the 4 activity monitors while they performed the Two-Minute Walk Test (2MWT), during which they were videotaped. Activity monitor estimated steps taken were compared with actual steps taken counted from videotape. Accuracy and agreement between activity monitor estimated steps and actual steps were examined using intraclass correlation coefficients (ICC [2,1]) and the Bland-Altman method.

RESULTS

The SAM demonstrated the greatest accuracy (ICC [2,1]=.97, mean difference between actual steps and SAM estimated steps=4.7 steps) followed by the Fitbit Ultra (ICC [2,1]=.73, mean difference between actual steps and Fitbit Ultra estimated steps=-9.7 steps), the YDWP (ICC [2,1]=.42, mean difference between actual steps and YDWP estimated steps=-28.8 steps), and the Nike+ Fuelband (ICC [2,1]=.20, mean difference between actual steps and Nike+ Fuelband estimated steps=-66.2 steps).

LIMITATIONS

Walking activity was measured over a short distance in a closed environment, and participants were high functioning ambulators, with a mean gait speed of 0.93 m/s.

CONCLUSIONS

The Fitbit Ultra may be a low-cost alternative to measure the stepping activity in level, predictable environments of people with stroke and TBI who can walk at speeds ≥0.58 m/s.

PACE-UP (Pedometer and consultation evaluation--UP)--a pedometer-based walking intervention with and without practice nurse support in primary care patients aged 45-75 years: study protocol for a randomised controlled trial

BACKGROUND

Most adults do not achieve the 150 minutes weekly of at least moderate intensity activity recommended for health. Adults' most common physical activity (PA) is walking, light intensity if strolling, moderate if brisker. Pedometers can increase walking; however, most trials have been short-term, have combined pedometer and support effects, and have not reported PA intensity. This trial will investigate whether pedometers, with or without nurse support, can help less active 45-75 year olds to increase their PA over 12 months.

METHODS/DESIGN

DESIGN

Primary care-based 3-arm randomized controlled trial with 12-month follow-up and health economic and qualitative evaluations.

PARTICIPANTS

Less active 45-75 year olds (n = 993) will be recruited by post from six South West London general practices, maximum of two per household and households randomised into three groups. Step-count and time spent at different PA intensities will be assessed for 7 days at baseline, 3 and 12 months by accelerometer. Questionnaires and anthropometric assessments will be completed.

INTERVENTION

The pedometer-alone group will be posted a pedometer (Yamax Digi-Walker SW-200), handbook and diary detailing a 12-week pedometer-based walking programme, using targets from their baseline assessment. The pedometer-plus-support group will additionally receive three practice nurse PA consultations. The handbook, diary and consultations include behaviour change techniques (e.g., self-monitoring, goal-setting, relapse prevention planning). The control group will receive usual care.

OUTCOMES

Changes in average daily step-count (primary outcome), time spent sedentary and in at least moderate intensity PA weekly at 12 months, measured by accelerometry. Other outcomes include change in body mass index, body fat, self-reported PA, quality of life, mood and adverse events. Cost-effectiveness will be assessed by the incremental cost of the intervention to the National Health Service and incremental cost per change in step-count and per quality adjusted life year. Qualitative evaluations will explore reasons for trial non-participation and the interventions' acceptability.

DISCUSSION

The PACE-UP trial will determine the effectiveness and cost-effectiveness of a pedometer-based walking intervention delivered by post or practice nurse to less active primary care patients aged 45-75 years old. Approaches to minimise bias and challenges anticipated in delivery will be discussed.

TRIAL REGISTRATION

ISRCTN98538934.

The SHED-IT weight loss maintenance trial protocol: A randomised controlled trial of a weight loss maintenance program for overweight and obese men

Despite short-term efficacy, many weight loss studies demonstrate poor long-term results and have difficulty recruiting men. Cost-effective treatments that help men achieve long-term weight loss are required. Using a two-phase, assessor-blinded, parallel-group randomised controlled trial design this study will test the effectiveness and cost-effectiveness of a male-only weight loss maintenance intervention. In Phase I (3 months) 209 men received the SHED-IT Weight Loss Program. In Phase II (12 months) 92 men who lost 4 kg or more were randomised to either (i) a maintenance group who received the 6-month, gender-tailored SHED-IT Weight Loss Maintenance Program, which included no face-to-face contact (n = 47), or (ii) a self-help control group (n = 45). Randomisation was stratified by weight loss (4 kg-7.4 kg, ≥7.5 kg) and BMI (<30 kg/m(2), ≥30 kg/m(2)). Assessments occurred at 'study entry' (start of Phase I), 'baseline' (start of Phase II), '6 months' (post-test) and will occur at '12 months' (follow-up; primary endpoint). The primary outcome is weight change in Phase II (i.e. from 'baseline' at 12 months after randomization). Secondary outcomes include waist circumference (umbilicus and narrowest), blood pressure, body composition, objectively measured physical activity, sedentary time, portion size, dietary intake, quality of life, depressive symptoms, and behavioural cognitions. Costing data will be collected for cost-effectiveness analysis. Generalised linear mixed models (intention-to-treat) will assess outcomes for treatment (maintenance vs. control), time (baseline, 6-month and 12-month) and the treatment-by-time interaction. This will be the first study to evaluate a male-only, gender-targeted weight loss maintenance program. Results will provide evidence regarding feasible and theoretically-driven obesity treatments for men with potential for long-term impact and widespread dissemination.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ACTRN12612000749808).