Comparison of accelerometer cut points to estimate physical activity in US adults

Objectively Measured Physical Activity and Sedentary Behaviors Among Older Adults in Assisted Living Facilities: A Scoping Review

Older adults in assisted living facilities (ALF) are at risk for low physical activity (PA) and high sedentary behavior (SB), both of which place them at risk for negative health outcomes. The purpose of this scoping review was to synthesize evidence describing the volume of device-measured PA/SB, factors associated with PA/SB, and interventions designed to change PA/SB in older adults living in ALF. Twenty articles representing 15 unique studies were identified from eight electronic databases and grey literature. Residents in ALF spent 96-201 min/day in light PA (n = 2 studies), 1-9.74 min/day in moderate to vigorous PA (n = 2 studies), and 8.5-11.01 hr/day of SB during waking hours (n = 3 studies). Factors associated with PA included 16 personal factors (n = 6 articles), one social factor (n = 2 articles), and two environmental factors (n = 2 articles). Factors associated with SB included 14 personal factors (n = 4 articles) and one social factor (n = 1 article). No intervention successfully changed PA/SB.

A comparative analysis of 24-hour movement behaviors features using different accelerometer metrics in adults: Implications for guideline compliance and associations with cardiometabolic health

BACKGROUND

Movement behavior features such as time use estimates, average acceleration and intensity gradient are crucial in understanding associations with cardiometabolic health. The aim of this study was to 1) compare movement behavior features processed by commonly used accelerometer metrics among adults (i.e. Euclidian Norm Minus One (ENMO), Mean Amplitude Deviation (MAD) and counts per minute (CPM)), 2) investigate the impact of accelerometer metrics on compliance with movement behavior guidelines, and 3) explore potential variations in the association between movement behavior features and cardiometabolic variables depending on the chosen metric.

METHODS

This cross-sectional study collected movement behavior features (Actigraph GT3X+) and cardiometabolic variables. Accelerometer data were analyzed by four metrics, i.e. ENMO, MAD, and CPM vertical axis and CPM vector magnitude (GGIR). Intraclass correlations and Bland‒Altman plots identified metric differences for time use in single movement behaviors (physical activity, sedentary behavior), average acceleration and intensity gradient. Regression models across the four metrics were used to explore differences in 24-hour movement behaviors (24h-MBs; compositional variable) as for exploration of associations with cardiometabolic variables.

RESULTS

Movement behavior data from 213 Belgian adults (mean age 45.8±10.8 years, 68.5% female) differed according to the metric used, with ENMO representing the most sedentary movement behavior profile and CPM vector magnitude representing the most active profile. Compliance rates for meeting integrated 24h-MBs guidelines varied from 0-25% depending on the metric used. Furthermore, the strength and direction of associations between movement behavior features and cardiometabolic variables (body mass index, waist circumference, fat% and HbA1c) differed by the choice of metric.

CONCLUSION

The metric used during data processing markedly influenced cut-point dependent time use estimates and cut-point independent average acceleration and intensity gradient, impacting guideline compliance and associations with cardiometabolic variables. Consideration is necessary when comparing findings from accelerometry studies to inform public health guidelines.

Physical Activity and Public Health for Adults: Is the Glass Mostly Empty or Half Full?

ABSTRACT

Early observations that only a small proportion of U.S. adults were engaging in enough aerobic physical activity to provide substantial health benefit helped shape our public health messaging for physical activity. This messaging has consistently indicated that most adults should increase their activity levels. However, it has been difficult to accurately estimate the proportion of adults who engage in sufficient levels of aerobic activity in the population, with survey-based estimates ranging from 22% in 1994 to 54% in 2018 and widely differing estimates from device-based measures. Recent accelerometer-based studies of physical activity and mortality risk provide new evidence that at least 50% of U.S. adults engage in enough aerobic physical activity to be at low risk for premature mortality. We argue that this observation should lend greater confidence to our current survey-based surveillance estimates, which indicate that a large proportion of adults is physically active. This new insight may also provide clues that could further strengthen our public health messaging for physical activity by placing more emphasis on the maintenance of healthy activity levels throughout life and possibly by using descriptive social norms as an additional intervention element-while continuing current efforts to encourage the adoption of healthy activity levels for less active adults in the population.

Foundations of Exercise and Physical Activity Research

While recognition of the link between physical activity and mental health dates back nearly two millennia, the academic study of physical activity is a relatively young discipline emerging over the last 50 years. This chapter provides an overview of key terms and measurement techniques in physical activity, exercise, and mental health research. The most common study designs in physical activity research include cross-sectional, cohort, randomized controlled trials, systematic reviews, and meta-analytic studies. Examples from the literature as well as the advantages and disadvantages of various methodological approaches are discussed throughout the chapter in the context of mental health research.

Equating NHANES Monitor-Based Physical Activity to Self-Reported Methods to Enhance Ongoing Surveillance Efforts

PURPOSE

Harmonization of assessment methods represents an ongoing challenge in physical activity research. Previous research has demonstrated the utility of calibration approaches to enhance agreement between measures of physical activity. The present study utilizes a calibration methodology to add behavioral context from the Global Physical Activity Questionnaire (GPAQ), an established report-based measure, to enhance interpretations of monitor-based data scored using the novel Monitor Independent Movement Summary (MIMS) methodology.

METHODS

Matching data from the GPAQ and MIMS were obtained from adults (20-80 yr of age) assessed in the 2011-2014 National Health and Nutrition Examination Survey. After developing percentile curves for self-reported activity, a zero-inflated quantile regression model was developed to link MIMS to estimates of moderate to vigorous physical activity (MVPA) from the GPAQ.

RESULTS

Cross-validation of the model showed that it closely approximated the probability of reporting MVPA across age and activity-level segments, supporting the accuracy of the zero-inflated model component. Validation of the quantile regression component directly corresponded to the 25%, 50%, and 75% values for both men and women, further supporting the model fit.

CONCLUSIONS

This study offers a method of improving activity surveillance by translating accelerometer signals into interpretable behavioral measures using nationally representative data. The model provides accurate estimates of minutes of MVPA at a population level but, because of the bias and error inherent in report-based measures of physical activity, is not suitable for converting or interpreting individual-level data. This study provides an important preliminary step in utilizing information from both device- and report-based methods to triangulate activity related outcomes; however additional measurement error modeling is needed to improve precision.

The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review

Low levels of physical activity (PA) and sleep disruption are commonly seen in older adult inpatients and are associated with poor health outcomes. Wearable sensors allow for objective continuous monitoring; however, there is no consensus as to how wearable sensors should be implemented. This review aimed to provide an overview of the use of wearable sensors in older adult inpatient populations, including models used, body placement and outcome measures. Five databases were searched; 89 articles met inclusion criteria. We found that studies used heterogenous methods, including a variety of sensor models, placement and outcome measures. Most studies reported the use of only one sensor, with either the wrist or thigh being the preferred location in PA studies and the wrist for sleep outcomes. The reported PA measures can be mostly characterised as the frequency and duration of PA (Volume) with fewer measures relating to intensity (rate of magnitude) and pattern of activity (distribution per day/week). Sleep and circadian rhythm measures were reported less frequently with a limited number of studies providing both physical activity and sleep/circadian rhythm outcomes concurrently. This review provides recommendations for future research in older adult inpatient populations. With protocols of best practice, wearable sensors could facilitate the monitoring of inpatient recovery and provide measures to inform participant stratification and establish common objective endpoints across clinical trials.

Examining the Associations of and Interactions Between Intrapersonal and Perceived Environmental Factors With Objectively Assessed Physical Activity Among Rural Midwestern Adults, USA

PURPOSE

We investigated associations of intrapersonal and environmental factors with objectively assessed weekly moderate to vigorous physical activity (MVPA) minutes, and their interactions in rural adults.

DESIGN

Cross-sectional.

SETTING

14 rural towns participating in a multilevel intervention to promote physical activity.

SAMPLE

Baseline data from 241 rural community members (19% losses due to missing data).

MEASURES

Self-reported demographics, behavioral factors, and neighborhood environment perceptions. Weekly MVPA minutes were assessed using accelerometry data.

ANALYSIS

Generalized linear models using a negative binomial distribution examined associations of and interactions between intrapersonal and environmental correlates with weekly MVPA.

RESULTS

Older age (β = -1.37; P= .025) and identifying as a woman (β = -.71; p= <.001) were inversely associated with MVPA. Self-efficacy (β = .34; p = <.001) and trail use (β = .44; P-value = .003) were directly associated with MVPA. Further, among women, perceived safety from traffic was inversely associated with MVPA (β = -.37; P = .003), while indoor recreational facility access was directly associated with MVPA (β = .24; P = .045).

CONCLUSIONS

Rural residents, especially women, face disproportionately lower MVPA levels. Improving recreational access and self-efficacy may be effective strategies for increasing MVPA.

Comparison of different software for processing physical activity measurements with accelerometry

Several raw-data processing software for accelerometer-measured physical activity (PA) exist, but whether results agree has not been assessed. We examined the agreement between three different software for raw accelerometer data, and associated their results with cardiovascular risk. A cross-sectional analysis conducted between 2014 and 2017 in 2693 adults (53.4% female, 45-86 years) living in Lausanne, Switzerland was used. Participants wore the wrist-worn GENEActive accelerometer for 14 days. Data was processed with the GENEActiv manufacturer software, the Pampro package in Python and the GGIR package in R. For the latter, two sets of thresholds "White" and "MRC" defining levels of PA and two versions (1.5-9 and 1.11-1) for the "MRC" threshold were used. Cardiovascular risk was assessed using the SCORE risk score. Time spent (mins/day) in stationary, light, moderate and vigorous PA ranged from 633 (GGIR-MRC) to 1147 (Pampro); 93 (GGIR-White) to 196 (GGIR-MRC); 19 (GGIR-White) to 161 (GENEActiv) and 1 (GENEActiv) to 26 (Pampro), respectively. Spearman correlations between results ranged between 0.317 and 0.995, while concordance coefficients ranged between 0.035 and 0.968. With some exceptions, the line of perfect agreement was not in the 95% confidence interval of the Bland-Altman plots. Compliance to PA guidelines varied considerably: 99.8%, 98.7%, 76.3%, 72.6% and 50.2% for Pampro, GENEActiv, GGIR-MRC v.1.11-1, GGIR-MRC v.1.4-9 and GGIR-White, respectively. Cardiovascular risk decreased with increasing time spent in PA across most software packages. We found large differences in PA estimation between software and thresholds used, which makes comparability between studies challenging.

Physical activity and cognitive function: A comparison of rural and urban breast cancer survivors

PURPOSE

Increasing evidence suggests rural breast cancer survivors (BCS) may experience greater burden in symptoms known to be associated with cancer-associated cognitive decline (CACD). Yet, little is known about CACD in rural BCS. This study (1) examined differences in cognitive function, moderate-to-vigorous physical activity (MVPA), and other CACD correlates and (2) tested the effects of MVPA on cognitive function in rural versus urban BCS.

METHODS

Rural and urban BCS (N = 80), matched on age, education, and time since diagnosis from a larger study, completed cognitive tasks assessing processing speed (Trails-B, Mazes, Task-Switch) and working memory (spatial working memory) and questionnaires assessing subjective memory impairment (SMI), MVPA, and CACD correlates (i.e., sleep quality, fatigue, anxiety/depression). Some participants (n = 62) wore an accelerometer to objectively estimate MVPA. Multiple linear regression and multivariate analysis of covariance were used to test study aims.

RESULTS

Rural BCS (n = 40, M = 61.1±8.4 years-old) performed significantly slower on Trails-B (p<0.01) compared with urban BCS (n = 40, M = 61.0±8.2 years-old) and engaged in less objectively-estimated daily MVPA (mean difference = 13.83±4.73 minutes; p = 0.01). No significant differences in SMI, self-reported MVPA, or CACD correlates were observed (all p>0.28). Regression models did not reveal a significant interaction between MVPA and cognitive performance (all p>0.1); however, estimated marginal means models indicated that the effect of MVPA on processing speed was evident only among rural BCS (Trails-B, p = 0.04; Mazes, p = 0.03).

CONCLUSIONS

Findings suggest rural BCS may suffer greater CACD and engage in less MVPA. Additional research is warranted to further examine CACD and more effectively promote MVPA in rural BCS.

A consensus method for estimating physical activity levels in adults using accelerometry

Identifying the best analytical approach for capturing moderate-to-vigorous physical activity (MVPA) using accelerometry is complex but inconsistent approaches employed in research and surveillance limits comparability. We illustrate the use of a consensus method that pools estimates from multiple approaches for characterising MVPA using accelerometry. Participants (n = 30) wore an accelerometer on their right hip during two laboratory visits. Ten individual classification methods estimated minutes of MVPA, including cut-point, two-regression, and machine learning approaches, using open-source count and raw inputs and several epoch lengths. Results were averaged to derive the consensus estimate. Mean MVPA ranged from 33.9-50.4 min across individual methods, but only one (38.9 min) was statistically equivalent to the criterion of direct observation (38.2 min). The consensus estimate (39.2 min) was equivalent to the criterion (even after removal of the one individual method that was equivalent to the criterion), had a smaller mean absolute error (4.2 min) compared to individual methods (4.9-12.3 min), and enabled the estimation of participant-level variance (mean standard deviation: 7.7 min). The consensus method allows for addition/removal of methods depending on data availability or field progression and may improve accuracy and comparability of device-based MVPA estimates while limiting variability due to convergence between estimates.

Agreement and relationship between measures of absolute and relative intensity during walking: A systematic review with meta-regression

INTRODUCTION

A metabolic equivalent (MET) is one of the most common methods used to objectively quantify physical activity intensity. Although the MET provides an 'objective' measure, it does not account for inter-individual differences in cardiorespiratory fitness. In contrast, 'relative' measures of physical activity intensity, such as heart rate reserve (HRR), do account for cardiorespiratory fitness. The purpose of this systematic review with meta-regression was to compare measures of absolute and relative physical activity intensity collected during walking.

METHODS

A systematic search of four databases (SPORTDiscus, Medline, Academic Search Premier and CINAHL) was completed. Keyword searches were: (i) step* OR walk* OR strid* OR "physical activity"; (ii) absolute OR "absolute intensity" OR mets OR metabolic equivalent OR actigraph* OR acceleromet*; (iii) relative OR "relative intensity" OR "heart rate" OR "heart rate reserve" OR "VO2 reserve" OR VO2* OR "VO2 uptake" OR HRmax* OR metmax. Categories (i) to (iii) were combined using 'AND;' with studies related to running excluded. A Bayesian regression was conducted to quantify the relationship between METs and %HRR, with Bayesian logistic regression conducted to examine the classification agreement between methods. A modified Downs and Black scale incorporating 13 questions relative to cross-sectional study design was used to assess quality and risk of bias in all included studies.

RESULTS

A total of 15 papers were included in the systematic review. A comparison of means between absolute (METs) and relative (%HRR, %HRmax, %VO2R, %VO2max, HRindex) values in 8 studies identified agreement in how intensity was classified (light, moderate or vigorous) in 60% of the trials. We received raw data from three authors, incorporating 3 studies and 290 participants. A Bayesian random intercept logistic regression was conducted to examine the agreement between relative and absolute intensity, showing agreement in 43% of all trials. Two studies had identical relative variables (%HRR) totalling 240 participants included in the Bayesian random intercept regression. The best performing model was a log-log regression, which showed that for every 1% increase in METs, %HRR increased by 1.12% (95% CI: 1.10-1.14). Specifically, the model predicts at the lower bound of absolute moderate intensity (3 METs), %HRR was estimated to be 33% (95%CI: 18-57) and at vigorous intensity (6 METs) %HRR was estimated to be 71% (38-100).

CONCLUSION

This study highlights the discrepancies between absolute and relative measures of physical activity intensity during walking with large disagreement observed between methods and large variation in %HRR at a given MET. Consequently, health professionals should be aware of this lack of agreement between absolute and relative measures. Moreover, if we are to move towards a more individualised approach to exercise prescription and monitoring as advocated, relative intensity could be more highly prioritised.

How adherence to the updated physical activity guidelines should be assessed with accelerometer?

Background

The aerobic part of the recently updated physical activity (PA) guidelines for adults recommends at least 150 min of moderate or at least 75 of vigorous-intensity PA or an equivalent combination of both. PA can be accumulated of any bout duration. On an absolute scale, moderate-intensity threshold is 3 metabolic equivalents (METs) and vigorous 6 METs. On a scale relative to individual’s personal capacity, moderate-intensity threshold is 40% and vigorous 60% of the oxygen uptake reserve. In this study, the adherence to the new guidelines was evaluated using both absolute and relative thresholds.

Methods

Totally, 1645 adults aged 20–64 years, participated in this population-based study and their cardiorespiratory fitness (CRF) was estimated with 6-min walking test. The participants with estimated maximal oxygen uptake <7.9 MET were categorized as low CRF group and the others as adequate CRF group. The participants were instructed to wear a triaxial hip-worn accelerometer for 1 week and their adherence to PA guidelines was assessed from the accelerometer data.

Results

The adequate CRF group had higher adherence to PA guidelines with the absolute thresholds, but the use of relative thresholds inverted the results. The adherence varied from 20% to 99% in the total sample depending on the analysis parameters of accelerometer data.

Conclusions

The absolute thresholds provide a more appropriate basis to assess the adherence to PA guidelines in population-based samples and interventions. The use of individually determined relative thresholds may be more useful for individual exercise prescriptions in PA counseling.

Higher 24-h Total Movement Activity Percentile Is Associated with Better Cognitive Performance in U.S. Older Adults

PURPOSE

This study aimed to assess the association of a wrist-worn, device-based metric of 24-h movement with cognitive function and subjective cognitive complaints among older adults, 60 yr and older.

METHODS

This is a cross-sectional analysis of the 2011-2012 and 2013-2014 National Health and Nutrition Examination Survey (NHANES) cycles. A wrist-worn ActiGraph GT3X+ accelerometer captured total 24-h movement activity, analyzed as Monitor-Independent Movement Summary units (MIMS-units), and quantified into placement based on an age- and sex-standardized percentile. Cognitive tests in the domains of memory, language/verbal fluency, and executive performance were administered. Test-specific cognitive z -scores were generated. Subjective cognitive complaints included perceived difficulty remembering and confusion/memory loss.

RESULTS

The analytical sample included 2708 U.S. older adults (69.5 ± 0.2 yr, 55% female, 20.9% non-White). Multivariable linear regressions revealed those in quartiles 3 (50th-74th percentile) and 4 (≥75th percentile) for their age and sex had higher cognitive function z -scores across all domains compared with those in quartile 1. Logistic regressions demonstrated those in quartiles 3 and 4 also had lower odds of reporting difficulty remembering (adjusted odds ratio [AOR] = 0.52, 95% confidence interval [CI] = 0.31-0.89; AOR = 0.57, 95% CI = 0.37-0.88) and confusion/memory loss (AOR = 0.49, 95% CI = 0.27-0.91; AOR = 0.49, 95% CI = 0.27-0.98), respectively, compared with those in quartile 1.

CONCLUSIONS

In a representative sample of U.S. older adults, higher cognitive functioning occurs among those that perform total 24-h movement activity at or above the 50th percentile for their age and sex. Future studies should consider movement behaviors across a 24-h period on cognitive health outcomes in older adults. More research exploring prospective associations of MIMS-units and time-use behaviors across midlife and older adulthood that may affect cognitive functioning across diverse populations is needed.

A Comparative Study on the Influence of Undersampling and Oversampling Techniques for the Classification of Physical Activities Using an Imbalanced Accelerometer Dataset

Accelerometer data collected from wearable devices have recently been used to monitor physical activities (PAs) in daily life. While the intensity of PAs can be distinguished with a cut-off approach, it is important to discriminate different behaviors with similar accelerometry patterns to estimate energy expenditure. We aim to overcome the data imbalance problem that negatively affects machine learning-based PA classification by extracting well-defined features and applying undersampling and oversampling methods. We extracted various temporal, spectral, and nonlinear features from wrist-, hip-, and ankle-worn accelerometer data. Then, the influences of undersampilng and oversampling were compared using various ML and DL approaches. Among various ML and DL models, ensemble methods including random forest (RF) and adaptive boosting (AdaBoost) exhibited great performance in differentiating sedentary behavior (driving) and three walking types (walking on level ground, ascending stairs, and descending stairs) even in a cross-subject paradigm. The undersampling approach, which has a low computational cost, exhibited classification results unbiased to the majority class. In addition, we found that RF could automatically select relevant features for PA classification depending on the sensor location by examining the importance of each node in multiple decision trees (DTs). This study proposes that ensemble learning using well-defined feature sets combined with the undersampling approach is robust for imbalanced datasets in PA classification. This approach will be useful for PA classification in the free-living situation, where data imbalance problems between classes are common.

Assessing moderate-to-vigorous physical activity in hip and knee osteoarthritis using accelerometers: Implications of different patterns and cut-points for health and well-being

OBJECTIVE

This cross-sectional study explored how using age-specific and non-age-specific cut-points to assess moderate-to-vigorous physical activity (MVPA) measured by GT3X accelerometers affected bouted and total volume MVPA associations with health and well-being.

METHODS

MVPA correlations with physical function, BMI, joint pain, quality of life, anxiety and depression were tested. Steiger's z compared the strength of these correlations for each pair of cut-points.

RESULTS

A total of 109 adults with hip/knee osteoarthritis [M= 63.8 years (±10.58), 63.3% women] participated. Applying age-specific cut-points resulted in significantly more time classified as MVPA (76/9.5min total volume/bouted) compared to non-age-specific (38.8/7min total volume/bouted). Only total volume MVPA correlations differed significantly as a function of cut-points for self-reported function, quality of life, anxiety and depression (p ≤ .05). For age-specific cut-points, more time spent in MVPA was associated with a worse psychological profile.

DISCUSSION

Applying age-specific cut-points for MVPA assessment in older adults with lower limb OA had implications for MVPA associations with health and well-being when total volume, but not bouted, MVPA was considered. Age-specific total volume MVPA needs further understanding regarding patterns and affective responses it comprises. Bouted MVPA is an important pattern for MVPA accrual, but probably not an applicable PA target for many patients.

CARL: a running recognition algorithm for free-living accelerometer data

Wearable accelerometers hold great promise for physical activity epidemiology and sports biomechanics. However, identifying and extracting data from specific physical activities, such as running, remains challenging.Objective. To develop and validate an algorithm to identify bouts of running in raw, free-living accelerometer data from devices worn at the wrist or torso (waist, hip, chest).Approach. The CARL (continuous amplitude running logistic) classifier identifies acceleration data with amplitude and frequency characteristics consistent with running. The CARL classifier was trained on data from 31 adults wearing accelerometers on the waist and wrist, then validated on free-living data from 30 new, unseen subjects plus 166 subjects from previously-published datasets using different devices, wear locations, and sample frequencies.Main results. On free-living data, the CARL classifier achieved mean accuracy (F₁score) of 0.984 (95% confidence interval 0.962-0.996) for data from the waist and 0.994 (95% CI 0.991-0.996) for data from the wrist. In previously-published datasets, the CARL classifier identified running with mean accuracy (F₁score) of 0.861 (95% CI 0.836-0.884) for data from the chest, 0.911 (95% CI 0.884-0.937) for data from the hip, 0.916 (95% CI 0.877-0.948) for data from the waist, and 0.870 (95% CI 0.834-0.903) for data from the wrist. Misclassification primarily occurred during activities with similar torso acceleration profiles to running, such as rope jumping and elliptical machine use.Significance. The CARL classifier can accurately identify bouts of running as short as three seconds in free-living accelerometry data. An open-source implementation of the CARL classifier is available atgithub.com/johnjdavisiv/carl.

Exercise Amounts and Short- to Long-Term Weight Loss: Psychological Implications for Behavioral Treatments of Obesity

Purpose: Although exercise is typically included in behavioral weight-loss programs, the amount associated with meaningful short- to long-term weight reduction required investigation. Indirect paths between exercise-associated psychological changes and weight loss might be more relevant than the direct effect of exercise on energy expenditure-related weight loss in deconditioned/obese individuals. Method: Sedentary women with obesity (N = 97; M_age = 47.2 years) participated in a year-long cognitive-behavioral weight-loss treatment that emphasized building self-regulatory skills to maintain exercise in advance of transferring those skills to controlled eating. Results: There was a significant increase in exercise (metabolic equivalents/week or leisure score index; LSI), and significant improvements in mood, self-regulation for exercise, and self-regulation for eating from baseline to Months 6, 12, and 24. There were 5.9%, 5.8%, and 5.8% reductions in weight, respectively. Completion of 15-20 LSI did not significantly differ from greater amounts on associated weight losses except for the rare occurrence of ≥ 30 LSI over the full 24-month study period. There were significant bivariate relationships between completion of ≥ 15 LSI and weight loss over 6, 12, and 24 months. Within serial mediation analyses assessing changes from baseline-Months 6 and 24, there were significant indirect paths from ≥ 15 LSI→self-regulation for exercise→self-regulation for eating→weight loss, and ≥ 15 LSI→negative mood→self-regulation for exercise→self-regulation for eating→weight loss. Those paths were not significant when baseline-Month 12 changes were entered. Conclusion: Findings suggested the value of even manageable exercise amounts because of their association with psychosocial correlates of weight loss, and informed behavioral obesity treatments.

Physical Activity in De Novo Parkinson Disease: Daily Step Recommendation and Effects of Treadmill Exercise on Physical Activity

OBJECTIVE

People with Parkinson disease (PD) have low physical activity (PA) levels and are at risk for cardiovascular events. The 3 purposes of this study were to determine a step threshold that corresponds to meeting aerobic PA guidelines, determine effects of treadmill exercise on PA, and quantify the relationship between changes in daily steps and fitness.

METHODS

This was a secondary analysis of the Study in Parkinson's Disease of Exercise trial, which randomized participants to high-intensity treadmill exercise, moderate-intensity treadmill exercise, or usual care for 6 months. Daily steps and moderate- to vigorous-intensity PA (MVPA) were assessed at baseline and once each month using an activity monitor. Fitness was assessed via graded exercise test at baseline and at 6 months. A step threshold that corresponds to meeting PA guidelines was determined by receiver operating characteristic curves. The effect of treadmill exercise on PA was examined in those below the step threshold (ie, the least active participants). Pearson r correlations determined the relationship between daily steps and fitness.

RESULTS

Individuals with de novo PD (n = 110) were included. Those with ≥4200 steps were 23 times more likely (95% CI = 7.72 to 68) to meet PA guidelines than those with <4200 steps. For those with <4200 steps at baseline (n = 33), only those in the high-intensity exercise group increased daily steps (median of differences = 1250 steps, z = -2.35) and MVPA (median of differences = 12.5 minutes, z = -2.67) at 6 months. For those with <4200 steps, changes in daily steps were not associated with changes in fitness (r = .183).

CONCLUSION

In people with PD and <4200 daily steps at baseline, high-intensity treadmill exercise increased daily steps and MVPA, but these changes were not associated with changes in fitness.

IMPACT

People with PD should be encouraged to take ≥4200 daily steps to meet PA guidelines through walking.

Personalised Accelerometer Cut-point Prediction for Older Adults' Movement Behaviours using a Machine Learning approach

BACKGROUND AND OBJECTIVES

Body-worn accelerometers are the most popular method for objectively assessing physical activity in older adults. Many studies have developed generic accelerometer cut-points for defining activity intensity in metabolic equivalents for older adults. However, methodological diversity in current studies has led to a great deal of variation in the resulting cut-points, even when using data from the same accelerometer. In addition, the generic cut-point approach assumes that 'one size fits all' which is rarely the case in real life. This study proposes a machine learning method for personalising activity intensity cut-points for older adults.

METHODS

Firstly, raw accelerometry data was collected from 33 older adults who performed set activities whilst wearing two accelerometer devices: GENEActive (wrist worn) and ActiGraph (hip worn). ROC analysis was applied to generate personalised cut-point for each data sample based on a device. Four cut-points have been considered: Sensitivity optimised Sedentary Behaviour; Specificity optimised Moderate to Vigorous Physical Activity; Youden optimised Sedentary Behaviour; and Youden optimised Moderate to Vigorous Physical Activity. Then, an additive regression algorithm trained on biodata features, that concern the individual characteristics of participants, was used to predict the cut-points. As the model output is a numeric cut-point value (and not discrete), evaluation was based on two error metrics, Mean Absolute Error and Root Mean Square Error. Standard Error of estimation was also calculated to measure the accuracy of prediction (goodness of fit) and this was used for performance comparison between our approach and the state-of-the-art. Hold-out and 10-Fold cross validation methods were used for performance validation and comparison.

RESULTS

The results show that our personalised approach performed consistently better than the state-of-the-art with 10-Fold cross validation on all four cut-points considered for both devices. For the ActiGraph device, the Standard Error of estimation from our approach was lower by 0.33 (Youden optimised Sedentary Behaviour), 9.50 (Sensitivity optimised Sedentary Behaviour), 0.64 (Youden optimised Moderate to Vigorous Physical Activity) and 22.11 (Specificity optimised Moderate to Vigorous Physical Activity). Likewise, the Standard Error of estimation from our approach was lower for the GENEActiv device by 2.29 (Youden optimised Sedentary Behaviour), 41.65 (Sensitivity optimised Sedentary Behaviour), 4.31 (Youden optimised Moderate to Vigorous Physical Activity) and 347.15 (Specificity optimised Moderate to Vigorous Physical Activity).

CONCLUSIONS

personalised cut-point can be predicted without prior knowledge of accelerometry data. The results are very promising especially when we consider that our method predicts cut-points without prior knowledge of accelerometry data, unlike the state-of-the-art. More data is required to expand the scope of the experiments presented in this paper.

Accelerometer Profile of Physical Activity and Sedentary Behavior in a Multi-Ethnic Urban Asian Population

Purpose: Variability in accelerometry-data processing decisions limited data comparability across studies. We aimed to examine different accelerometry-data processing rules: varying bout lengths and allowance of 0- and 2-min interruptions on the total and bout-accumulated time spent in moderate-to-vigorous physical activity (MVPA) and sedentary behavior estimates, and describe the distribution of activity time based on counts per min (CPM) in granular categories. Method: Using the Singapore Health 2 survey, this study included 746 adults (41.8% women, median age 45.0 years) who provided valid ActiGraph GT3X+ accelerometer-data (≥4 valid days with ≥10-h/day). Quantile regression analysis adjusting for accelerometry daily wear time, age, and gender was performed to calculate the median and interquartile range of accelerometry estimates. Results: Median MVPA time accumulated in bouts of 1-min versus bouts of 10-min was 39.2 min/day and 6.0 min/day, respectively. MVPA time was higher when considering a 2-min interruption (range: 1.8-39.2 min/day) compared to 0-min interruption (range: 0-35.5 min/day) across bout lengths of 1- to 15-min. Participants were sedentary (≤100 CPM) for a daily median of 7.6 h/day. Median activities min/day on the lower-intensity activity spectrum (100-2499 CPM) decreased from 63.4 to 4.6 min/day, while on the higher-intensity activity spectrum (≥2500 CPM) was ≤2.9 min/day. Men generally spent more time in MVPA than women. Conclusions: This study highlights the differences in accelerometry estimates based on data processing decisions, and the importance of quantifying accelerometry-based activity time across the granular intensity spectrum. More studies are warranted to understand the determinants and health impact of these behaviors.

Surveillance of Physical Activity and Sedentary Behavior Among Youth and Adults in the United States: History and Opportunities

BACKGROUND

Surveillance is a core function of public health, and approaches to national surveillance of physical activity and sedentary behavior have evolved over the past 2 decades. The purpose of this paper is to provide an overview of surveillance of physical activity and sedentary behavior in the United States over the past 2 decades, along with related challenges and emerging opportunities.

METHODS

The authors reviewed key national surveillance systems for the assessment of physical activity and sedentary behavior among youth and adults in the United States between 2000 and 2019.

RESULTS

Over the past 20 years, 8 surveillance systems have assessed physical activity, and 5 of those have assessed sedentary behavior. Three of the 8 originated in nonpublic health agencies. Most systems have assessed physical activity and sedentary behavior via surveys. However, survey questions varied over time within and also across systems, resulting in a wide array of available data.

CONCLUSION

The evolving nature of physical activity surveillance in the United States has resulted in both broad challenges (eg, balancing content with survey space; providing data at the national, state, and local level; adapting traditional physical activity measures and survey designs; and addressing variation across surveillance systems) and related opportunities.

Leisure-time aerobic physical activity and the risk of diabetes-related mortality: An analysis of effect modification by race-ethnicity

AIMS

To examine the relationship between aerobic moderate-to-vigorous intensity leisure-time physical activity (LTPA) and the risk of diabetes-related mortality in the NHANES III (1988-1994) while considering potential effect modification by race-ethnicity.

METHODS

The study sample (n = 14,006) included adults, 20-79 years of age, with Mobile Examination Center (MEC) data. An age-standardized physical activity score (PAS) was calculated from the self-reported frequency and intensity of 12 leisure-time aerobic activities. Three categories of PA were examined: inactive (PAS = 0), insufficiently active (PAS >0-<10), and active (PAS ≥10). Diabetes-related mortality was defined as death from diabetes mellitus. Cox Proportional Hazard models were used all analyses.

RESULTS

A statistically significant reduction in risk was found for insufficiently active (HR 0.59, 95% CI 0.40-0.90) and active non-Hispanic black (NHB) (HR 0.54, 95% CI 0.34-0.88). Among active non-Hispanic white (NHW), a similar pattern of risk reduction was found, however, this relationship was borderline significance (HR 0.59, 95% CI 0.35-1.02, p = 0.06).

CONCLUSIONS

Any volume of aerobic LTPA is beneficial in terms of reducing the risk of diabetes-related mortality. However, these benefits may differ by racial-ethnic group, with further research on health disparities in the area of PA being warranted.

Untapping the Health Enhancing Potential of Vigorous Intermittent Lifestyle Physical Activity (VILPA): Rationale, Scoping Review, and a 4-Pillar Research Framework

Recently revised public health guidelines acknowledge the health benefits of regular intermittent bouts of vigorous intensity incidental physical activity done as part of daily living, such as carrying shopping bags, walking uphill, and stair climbing. Despite this recognition and the advantages such lifestyle physical activity has over continuous vigorous intensity structured exercise, a scoping review we conducted revealed that current research in this area is, at best, rudimentary. Key gaps include the absence of an empirically-derived dose specification (e.g., minimum duration of lifestyle physical activity required to achieve absolute or relative vigorous intensity), lack of acceptable measurement standards, limited understanding of acute and chronic (adaptive) effects of intermittent vigorous bouts on health, and paucity of essential information necessary to develop feasible and scalable interventions (e.g., acceptability of this kind of physical activity by the public). To encourage collaboration and research agenda alignment among groups interested in this field, we propose a research framework to further understanding of vigorous intermittent lifestyle physical activity (VILPA). This framework comprises four pillars aimed at the development of: (a) an empirical definition of VILPA, (b) methods to reliably and accurately measure VILPA, (c) approaches to examine the short and long-term dose-response effects of VILPA, and (d) scalable and acceptable behavioural VILPA-promoting interventions.

Comparison of Sedentary Time Between Thigh-Worn and Wrist-Worn Accelerometers

Background: The accuracy of wrist-worn accelerometers in identifying sedentary time has been scarcely studied in free-living conditions. The aim of this study was to compare daily sedentary time estimates between a thigh-worn accelerometer, which measured sitting and lying postures, and a wrist-worn accelerometer, which measured low levels of movement. Methods: The study population consisted of 259 participants (Mage = 62.8 years, SD = 0.9) from the Finnish Retirement and Aging Study (FIREA). Participants wore an Axivity AX3 accelerometer on their mid-thigh and an Actigraph wActiSleep-BT accelerometer on their non-dominant wrist simultaneously for a minimum of 4 days in free-living conditions. Two definitions to estimate daily sedentary time were used for data from the wrist-worn accelerometer: 1) the count cutpoint, ≤1853 counts per minute; and 2) the Euclidean Norm Minus One (ENMO) cutpoint, <30 mg. Results: Compared to the thigh-worn accelerometer, daily sedentary time estimate was 63 min (95% confidence interval [CI] = −53 to −73) lower by the count cutpoint and 50 min (95% CI = 34 to 67) lower by the ENMO cutpoint. The limits of agreement in daily sedentary time estimates between the thigh- and cutpoint methods for wrist-worn accelerometers were wide (the count cutpoint: −117 to 243, the ENMO cutpoint: −212 to 313 min). Conclusions: Currently established cutpoint-based methods to estimate sedentary time from wrist-worn accelerometers result in underestimation of daily sedentary time compared to posture-based estimates of thigh-worn accelerometers. Thus, sedentary time estimates obtained from wrist-worn accelerometers using currently available cutpoint-based methods should be interpreted with caution and future work is needed to improve their accuracy.

Differences between accelerometer cut point methods among midlife women with cardiovascular risk markers

OBJECTIVE

Midlife women experience elevated risk for cardiovascular disease and often receive advice to increase physical activity to mitigate this risk. Use of accelerometers to measure ambulatory physical activity requires selection of appropriate thresholds for estimating moderate-to-vigorous physical activity (MVPA), and choice of cut points may lead to meaningfully different conclusions about midlife women's physical activity (PA) engagement. This is particularly important given the recent elimination of 10-minute bout requirements for MVPA. This two-phase study examined differences between four cut point methods among midlife women with cardiovascular disease (CVD) risk. We used findings from Study 1 (exploratory) to generate hypotheses for Study 2 (confirmatory).

METHODS

Across studies, participants (N = 65) were midlife women with an additional CVD risk factor (eg, hypertension). Participants wore waistband accelerometers for seven days. Daily totals were calculated for minutes in light and MVPA using four common quantification methods (Freedson, Matthews, Swartz, and Troiano).

RESULTS

Multilevel models showed meaningful differences between methods (P < 0.0001). For total (non-bouted) minutes of MVPA, Freedson and Troiano methods showed that participants barely met MVPA recommendations (30 min per day), whereas Matthews and Swartz methods showed that participants greatly exceeded this goal. As differences between methods were smaller using MVPA bouts of 10 minutes or more (though remained significant), the observed variation was due in part to small bursts of MVPA dispersed throughout the day.

CONCLUSIONS

Findings demonstrate the need for careful consideration of PA quantification among midlife women with CVD risk, and for further investigation to determine the most appropriate quantification method. : Video Summary:http://links.lww.com/MENO/A545.

Comparing Two Moderate-to-Vigorous Physical Activity Accelerometer Cut Points in Older Adults With Neck and Back Disabilities Undergoing Exercise and Spinal Manipulation Interventions

Different techniques used to analyze and reduce accelerometer data may impact its interpretation. To determine which variables were impacted by changing analysis parameters, the authors performed a secondary analysis of data gained from a clinical trial conducted on older adults (aged ≥65 years; M = 71.1 and SD = 5.3; n = 100) with neck and back disabilities and compared the effects of two different cut- point sets (Matthews and Freedson sets) commonly used to analyze older adult accelerometry data. The Matthews set was found to assign significantly greater moderate-to-vigorous physical activity per day than the Freedson set in all comparisons. This suggests that, if moderate-to-vigorous physical activity per unit time is a primary outcome measure, the choice of which analysis method is used should be carefully considered. Further results from analyses of dependent variables, time in moderate-to-vigorous physical activity bouts of >10 min/day, mean bout length, and number of bouts per day are discussed.

Challenges and opportunities related to the objective assessment of physical activity within U.S. health surveys

Public health surveillance is a vital component in the assessment of health-related behaviors such as physical activity (PA). With multiple active national health surveys in the United States, questions arise about how data are collected, what each data source contributes to the overall knowledge base about PA and health outcomes, and how to interpret PA data from different data sources to gain an understanding about PA at the population level. This article highlights specifically the challenges and opportunities with using wearable devices in population-level PA assessment. A major challenge faced by PA assessment researchers is that of which assessment methods and evaluation tools to use and under what circumstances to use them. This article discusses issues related to (1) what device to use, (2) how to collect data, (3) how to process data, (4) how to analyze the data, and (5) how to report the procedures used. These decisions shape not only the data collection process including collection time and cost but also directly impact data analysis and subsequently the outcomes of interest. This article discusses the implications of using different assessment methods and evaluation tools and how the use of sensor-based tools may impact the future of PA assessment at the population level. There are a number of opportunities emerging for population-level assessment of PA due in part to the technological advances occurring with wearable technology. These opportunities may afford surveillance systems new data streams to bolster what is currently being collected to provide more robust estimates of PA and other health behaviors. The article concludes with some discussion about how the landscape of population-level PA assessment is changing, thanks to increasing opportunities to collect wearable device data. With new data streams becoming available through advanced wearable devices containing multiple sensor types and the opportunity for corporate partnerships, the way PA is being assessed could change considerably in the near future. While acknowledging the limitations of wearable technology, it is an exciting time for PA assessment, given the possibilities on the horizon.

Cardiorespiratory fitness and accelerometer-determined physical activity following one year of free-living high-intensity interval training and moderate-intensity continuous training: a randomized trial

Background

Free-living adherence to high-intensity interval training (HIIT) has not been adequately tested. This randomized trial examined changes in cardiorespiratory fitness (CRF) and accelerometer-measured purposeful physical activity over 12 months of free-living HIIT versus moderate-intensity continuous training (MICT).

Methods

Ninety-nine previously low-active participants with overweight/obesity were randomly assigned to HIIT (n = 47) or MICT (n = 52). Both interventions were combined with evidence-based behaviour change counselling consisting of 7 sessions over 2 weeks. Individuals in HIIT were prescribed 10 X 1-min interval-based exercise 3 times per week (totalling 75 min) whereas individuals in MICT were prescribed 150 min of steady-state exercise per week (50 mins 3 times per week). Using a maximal cycling test to exhaustion with expired gas analyses, CRF was assessed at baseline and after 6 and 12 months of free-living exercise. Moderate-to-vigorous physical activity of 10+ minutes (MVPA10+) was assessed by 7-day accelerometry at baseline, 3, 6, 9, and 12 months. Intention to treat analyses were conducted using linear mixed models.

Results

CRF was improved over the 12 months relative to baseline in both HIIT (+ 0.15 l/min, 95% CI 0.08 to 0.23) and MICT (+ 0.11 l/min, 95% CI 0.05 to 0.18). Both groups improved 12-month MVPA10+ above baseline (HIIT: + 36 min/week, 95% CI 17 to 54; MICT: + 69 min/week, 95% CI 49 to 89) with the increase being greater (by 33 min, 95% CI 6 to 60) in MICT (between group difference, P = 0.018).

Conclusion

Despite being prescribed twice as many minutes of exercise and accumulating significantly more purposeful exercise, CRF improvements were similar across 12 months of free-living HIIT and MICT in previously low-active individuals with overweight/obesity.

[Physical activity in the German National Cohort (NAKO): use of multiple assessment tools and initial results]

BACKGROUND

Physical activity is a complex behavior that is difficult to measure validly and reliably in large, population-based studies. Data on physical activity are available for the initial 100,000 participants of the German National Cohort.

OBJECTIVES

To describe the baseline physical activity assessment in the cohort and to present initial descriptive results.

MATERIAL AND METHODS

Physical activity was assessed using a combination of tools, including two self-administered questionnaires, the Questionnaire on Annual Physical Activity Pattern (QUAP) and the Global Physical Activity Questionnaire (GPAQ); a computer-based 24‑h physical activity recall (cpar24); and 7‑day accelerometry (Actigraph GT3X/+; ActiGraph, Pensacola, FL, USA).

RESULTS

The availability of data varied between assessment instruments (QUAP: n = 16,372; GPAQ: n = 90,900; cpar24: n = 23,989; accelerometry: n = 35,218). Analyses across measurement tools showed that on average, women spent 75 to 216 min/d, and men spent 73 to 224 min/d in moderate or higher intensity total physical activity. Persons aged 20-39 years spent 66 to 200 min/d, and persons aged 40-69 years spent 78 to 244 min/d in moderate or higher intensity total physical activity.

CONCLUSIONS

Initial baseline analyses of physical activity in this cohort show the value of using a combination of questionnaires, 24‑h recalls, and a movement sensor. The comprehensive data collection represents a valuable resource for future analyses and will improve our understanding of the association between physical activity and disease prevention.

Individualized Relative-Intensity Physical Activity Accelerometer Cut Points

PURPOSE

Physical activity (PA) intensity is expressed as either absolute or relative intensity. Absolute intensity refers to the energy required to perform an activity. Relative intensity refers to a level of effort that takes into account how hard an individual is working relative to their maximum capacity. We sought to develop methods for obtaining individualized relative-intensity accelerometer cut points using data from a maximal graded exercise treadmill test (GXT) so that each individual has their own cut point.

METHODS

A total of 2363 men and women 38 to 50 yr old from the CARDIA fitness study wore ActiGraph 7164 accelerometers during a maximal GXT and for seven consecutive days in 2005-2006. Using mixed-effects regression models, we regressed accelerometer counts on heart rate as a percentage of maximum (%HRmax) and on RPE. Based on these two models, we obtained a moderate-intensity (%HRmax = 64% or RPE = 12) count cut point that is specific to each participant. We applied these subject-specific cut points to the available CARDIA accelerometer data.

RESULTS

Using RPE, the mean moderate-intensity accelerometer cut point was 4004 (SD = 1120) counts per minute. On average, cut points were higher for men (4189 counts per minute) versus women (3865 counts per minute) and were higher for Whites (4088 counts per minute) versus African Americans (3896 counts per minute). Cut points were correlated with body mass index (rho = -0.11) and GXT duration (rho = 0.33). Mean daily minutes of absolute- and relative-intensity moderate to vigorous PA were 34.1 (SD = 31.1) min·d and 9.1 (SD = 18.2) min·d, respectively. RPE cut points were higher than those based on %HRmax. This is likely due to some participants ending the GXT before achieving their HRmax.

CONCLUSIONS

Accelerometer-based relative-intensity PA may be a useful measure of intensity relative to maximal capacity.

Proportion of Adults Meeting the 2018 Physical Activity Guidelines for Americans According to Accelerometers

The new 2018 Physical Activity Guidelines for Americans provides updated recommendations for physical activity behavior. These guidelines remove the requirement for physical activity to be obtained in bouts of at least 10 min. The purpose of the present study was to provide an updated estimate of the proportion of adults meeting the physical activity guidelines, based on nationally representative data using accelerometers. Data from 6,525 adults were included in this study. The proportion of adults meeting the physical activity guidelines according to the Department of Health and Human Services and according to the American College of Sports Medicine were estimated using (a) lifestyle activities and (b) ambulatory activities only. Estimates of the proportion of adults meeting the physical activity guidelines ranged from 3.4 to 95.6%, even when based on the same data. The large range of these estimates suggest that challenges exist when using accelerometer data to estimate the levels of physical activity behavior in the population. Further, the large range indicates that, perhaps, physical activity guidelines should not be used as a reference point for behavior change. Instead, we suggest that efforts should be made to promote physical activity in reference to current behavior.

Dose-response effects of high-intensity interval neuromuscular exercise training on weight loss, performance, health and quality of life in inactive obese adults: Study rationale, design and methods of the DoIT trial

Obesity is associated with high mortality and morbidity rates and low levels of quality of life among adults globally. It is critical to examine evidence-based practices for developing lifestyle behavioral changes such as physical movement and structured exercise training. The DoIT protocol, a high-intensity interval exercise training (HIIT) program, effectively reduces body mass, alters energy balance, and improves performance of obese adults with a high adherence rate. This study aims to determine the dose-response effects of the DoIT protocol on body composition, health, performance and quality of life in sedentary obese adults. This study will recruit 88 sedentary, obese males and females (BMI 25.0–34.9; 30–50 years) who will be randomly assigned to one of four groups: (i) control (n = 22), (ii) one session/week (n = 22), (iii) two sessions/week (n = 22) or (iv) three sessions/week (n = 22). DoIT will use a supervised, circuit-type (1–3 rounds), functional/neuromotor and progressive exercise program for 12 months. DoIT incorporates 8–12 multi-planar, fundamental and complex, whole body movements and uses bodyweight and alternative exercise modes as a resistance. DoIT utilizes prescribed work-to-rest ratios which will be varied every four weeks. Each session will last less than 30 min. DoIT will be implemented for a year and its effects on body mass and body composition, physical fitness, functional capacity, bone health, leptin, adiponectin, blood lipids, glycemic control, inflammation, oxidative stress and quality of life will be assessed. The outcomes of the proposed study will provide insight on optimal exercise prescription guidelines for such HIIT-type exercise protocols for overweight or obese individuals.

Influence of Accelerometer Calibration Approach on Moderate-Vigorous Physical Activity Estimates for Adults

PURPOSE

To compare estimates of moderate-vigorous physical activity (MVPA) duration derived from accelerometers calibrated only to walking and running activities to estimates from calibrations based on a broader range of lifestyle and ambulatory activities.

METHODS

In a study of 932 older (50-74 yr) adults we compared MVPA estimates from accelerometer counts based on three ambulatory calibration methods (Freedson 1952 counts per minute; Sasaki 2690 counts per minute; activPAL 3+ METs) to estimates based on calibrations from lifestyle and ambulatory activities combined (Matthews 760 counts per minute; Crouter 3+ METs; Sojourn3x 3+ METs). We also examined data from up to 6 previous-day recalls describing the MVPA in this population.

RESULTS

The MVPA duration values derived from ambulatory calibration methods were significantly lower than methods designed to capture a broader range of both lifestyle and ambulatory activities (P < 0.05). The MVPA (h·d) estimates in all participants were: Freedson (median, 0.35; interquartile range, 0.17-0.58); Sasaki (median, 0.91; interquartile range, 0.59-1.32); and activPAL (median, 0.97; interquartile range, 0.71-1.26) compared with Matthews (median, 1.82; interquartile range, 1.37-2.34); Crouter (2.28 [1.72-2.82]); and Sojourn3x (median, 1.85; interquartile range, 1.42-2.34). Recall-based estimates in all participants were comparable (median, 1.61; interquartile range, 0.89-2.57) and indicated participation in a broad range of lifestyle and ambulatory MVPA.

CONCLUSIONS

Accelerometer calibration studies that employ only ambulatory activities may produce MVPA duration estimates that are substantially lower than methods calibrated to a broader range of activities. These findings highlight the potential to reduce potentially large differences among device-based measures of MVPA due to variation in calibration study design by including a variety of lifestyle and ambulatory activities.

Physical Activity Questionnaires for Pregnancy: A Systematic Review of Measurement Properties

Background

In order to assess physical activity (PA) during pregnancy, it is important to choose the instrument with the best measurement properties.

Objectives

To systematically summarize, appraise, and compare the measurement properties of all self-administered questionnaires assessing PA in pregnancy.

Methods

We searched PubMed, Embase, and SPORTDiscus with the following inclusion criteria: (i) the study reported at least one measurement property (reliability, criterion validity, construct validity, responsiveness) of a self-administered questionnaire; (ii) the questionnaire intended to measure PA; (iii) the questionnaire was evaluated in healthy pregnant women; and (iv) the study was published in English. We evaluated results, quality of individual studies, and quality of evidence using a standardized checklist (Quality Assessment of Physical Activity Questionnaires [QAPAQ]) and the GRADE (Grading of Recommendation, Assessment, Development, and Evaluation) approach.

Results

Seventeen articles, reporting 18 studies of 11 different PA questionnaires (17 versions), were included. Most questionnaire versions showed insufficient measurement properties. Only the French and Turkish versions of the Pregnancy Physical Activity Questionnaire (PPAQ) showed both sufficient reliability and construct validity. However, all versions of the PPAQ pooled together showed insufficient construct validity. The quality of individual studies was usually high for reliability but varied considerably for construct validity. Overall, the quality of evidence was very low to moderate.

Conclusions

We recommend the PPAQ to assess PA in pregnancy, although the pooled results revealed insufficient construct validity. The lack of appropriate standards in data collection and processing criteria for objective devices in measuring PA during pregnancy attenuates the quality of evidence. Therefore, research on the validity of comparison instruments in pregnancy followed by consensus on validation reference criteria and standards of PA measurement is needed.

Electronic supplementary material

The online version of this article (10.1007/s40279-018-0961-x) contains supplementary material, which is available to authorized users.

Impact of Prolonged Sitting on Peripheral and Central Vascular Health

Prolonged, uninterrupted sitting negatively impacts markers of peripheral vascular health, particularly, vasodilatory function of leg arteries. Whether sitting can similarly impact measures of central vascular health, as well as overall leg vasoreactivity (i.e., vasodilatory and vasoconstrictor function) remains unknown. To address this, measurements were made in relatively healthy participants (i.e., free of overt disease; n = 20, age = 26 ± 7; body mass index = 30 ± 7 kg/m²; 7 female) pre, during and post 3 hours of uninterrupted sitting. Measures of central vascular health included arterial wave reflection (augmentation index and Reflection Magnitude-RM%) and aortic vascular stiffness (aortic pulse wave velocity). Local vasoreactivity of the distal, posterior tibial artery was measured using flow-mediated dilation-FMD, coupled with low-flow mediated constriction, and microvascular function was assessed through the total hyperemic blood velocity (area-under-curve) response during FMD. After sitting, there was a significant increase in aortic pulse wave velocity (pre sit = 5.7 ± 0.3 vs post sit = 6.1 ± 0.3 m/s; p = 0.009, d = 0.36), whereas, augmentation index decreased (pre sit = 13 ± 3 vs post sit = 3 ± 1%; p < 0.001, d = 0.71). Albeit a moderate effect for decrease, RM% was not significantly altered during sitting (p = 0.13, d = 0.3). Vasodilatory (i.e., FMD pre sit = 0.5 ± 0.04 vs post sit = 0.3 ± 0.04 mm; p = 0.014, d = 0.29) and microvascular function (i.e., Microvascular area-under-curve: pre sit = 2,196 ± 333 vs 1,157±172 AU; p = 0.003, d = 0.31) decreased, but vasoconstrictor function (low-flow mediated constriction; p = 0.85, d = 0.005) was unaffected by sitting. In conclusion, these data demonstrate that a prolonged bout of uninterrupted sitting negatively impacts markers of peripheral and central vascular health in relatively healthy adults.

Estimation of energy balance and training volume during Army Initial Entry Training

BACKGROUND

Adequate dietary intake is important for promoting adaptation and prevention of musculoskeletal injury in response to large volumes of physical training such as Army Initial Entry Training (IET). The purpose of this study was to evaluate training volume and dietary intake and estimate energy balance in Army IET soldiers.

METHODS

Dietary intake was assessed by collecting diet logs for three meals on each of three, non-consecutive days during the first week of IET. Training volume was measured across 13 weeks of training using Actigraph wGT3X accelerometers. Training intensity was classified using Sasaki vector magnitude three cut points. Energy expenditure estimates were calculated during weeks two and three of training using the modified Harris-Benedict equation and by estimation of active energy expenditure using metabolic equivalents for each classification of physical activity. All data is presented as mean ± standard deviation.

RESULTS

A total of 111 male soldiers (ht. = ± 173 ± 5.8 cm, age = 19 ± 2 years, mass = 71.6. ± 12.4 kg) completed diet logs and were monitored with Actigraphs. IET soldiers performed on average 273 ± 62 min low, 107 ± 42 min moderate, 26 ± 22 min vigorous, and 10 ± 21 min of very vigorous intensity physical activity daily across 13 weeks. The estimated total daily energy expenditure was on average 3238 ± 457 kcals/d during weeks two and three of IET. Compared to week one caloric intake, there was a caloric deficit of 595 ± 896 kcals/d on average during weeks two and three of IET. Regression analysis showed that body weight was a significant predictor for negative energy balance (adj. R2 = 0.54, p < 0.001), whereby a 1 kg increase in body mass was associated with a 53 kcal energy deficit.

CONCLUSIONS

Based on week one dietary assessment, IET soldiers did not consume adequate calories and nutrients to meet training needs during red phase (weeks one through three). This may directly affect soldier performance and injury frequency. IET soldiers undergo rigorous training, and these data may help direct future guidelines for adequate nourishment to optimize soldier health and performance.

High intensity, circuit-type integrated neuromuscular training alters energy balance and reduces body mass and fat in obese women: A 10-month training-detraining randomized controlled trial

This randomized controlled trial examined body mass, body composition, energy balance and performance responses of previously sedentary overweight/obese women to a circuit-type integrated neuromuscular training program with alternative modalities. Forty-nine healthy overweight or class I obese females (36.4±4.4 yrs) were randomly assigned to either a control (N = 21), training (N = 14) or training-detraining (N = 14) group. In weeks 1-20, the training groups trained three times/week using 10-12 whole-body exercises of progressively increased intensity/volume, organized in timed interval circuit form. In weeks 21-40, the training group continued training whereas the training-detraining group not. Heart rate, perceived exertion, blood lactate, exertion, oxygen consumption and excess post-exercise oxygen consumption were measured for one session/phase/person and exercise energy expenditure was calculated. Energy intake, habitual physical activity, resting metabolic rate, body composition, body mass, strength and maximal oxygen consumption were measured at baseline, mid-intervention and post-intervention. A two-way repeated measures ANOVA was used to determine differences between three time points and three groups. In C, VO2max declined (p<0.013) and body fat (p<0.008), waist (p<0.059) and hip (p<0.012) circumferences increased after 40 weeks compared to baseline. Training reduced body mass (6%, p<0.001), body fat (~5.5%, p<0.001) and increased fat-free mass (1.2-3.4%, p<0.05), strength (27.2%, p<0.001) and endurance (26.8%, p<0.001) after a 10-month implementation period using a metabolic overload of only 5-12 metabolic equivalents of task-hours per week. Training induced a long-term negative energy balance during an exercise and a non-exercise day due to an elevation of resting metabolic rate (6%-10%, p<0.05) and exercise-related energy expenditure. Training had an 8% and 94% attrition and attendance rates, respectively. Training-induced gains were attenuated but not lost following a 5-month detraining. A 10-month implementation of a high-intensity interval type training program elicited both endurance and musculoskeletal gains and resulted in a long-term negative energy balance that induced a progressive and sustained reduction of body and fat mass.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03134781.

Association between Objectively Measured Physical Activity and Mortality in NHANES

PURPOSE

We examined total activity, light activity, and moderate-to-vigorous physical activity (MVPA) as predictors of mortality in a nationally representative sample of older adults. Then we explored the theoretical consequences of replacing sedentary time with the same duration of light activity or MVPA.

METHODS

Using accelerometer-measured activity, the associations between total activity, light activity (100-2019 counts per minute), and MVPA (>2019 counts per minute) counts and mortality were examined in adults age 50 to 79 yr in the National Health and Nutrition Examination Survey, 2003-2006 (n = 3029), with mortality follow-up through December 2011. Cox proportional hazard models were fitted to estimate mortality risks. An isotemporal substitution model was used to examine the theoretical consequences of replacing sedentary time with light activity or MVPA on mortality.

RESULTS

After adjusting for potential confounders, including age, sex, race/ethnicity, education, BMI, and the presence of comorbid conditions, those in the highest tertile of total activity counts had one fifth the risk of death of those in the lowest tertile (hazard ratio [HR] = 0.21, 95% confidence interval [CI] = 0.12-0.38), and those in the middle tertile had one third the risk of death (HR = 0.36, 95% CI = 0.30-0.44). In addition, replacing 30 min of sedentary time with light activity was associated with significant reduction in mortality risk (after 5 yr of follow-up: HR = 0.80, 95% CI = 0.75-0.85). Replacing 30 min of sedentary time with MVPA was also associated with reduction in mortality risk (HR = 0.49, 95% CI = 0.25-0.97).

CONCLUSIONS

Greater total activity is associated with lower all-cause mortality risk. Replacing sedentary time with light activity or MVPA may reduce mortality risk for older adults.

Associations between neighborhood socioeconomic environment and physical activity in Cuban immigrants

Physical inactivity is a major public health concern because it is a determinant of obesity and obesity-related chronic diseases. Few longitudinal studies have examined the association between neighborhood socioeconomic (SES) environment and change in physical activity behaviors. Additionally, few studies have examined this association in immigrant groups or Hispanic subgroups such as Cubans. This research aimed to determine if neighborhood SES is associated with longitudinal change in moderate-to-vigorous physical activity (MVPA) among Cuban immigrants who participate in the Cuban Health Study in Miami, Florida. Data on 280 participants [mean age: 37.4 (±4.6), 48.9% women, mean body mass index: 25.0 (±2.5)] collected at baseline, 12 months and 24 months were analyzed. Minutes of MVPA were objectively measured during each data collection period using accelerometers. A neighborhood SES score was calculated for each participant’s residential census tract from American Community Survey data on median household income, median housing value, educational attainment and occupation. The neighborhood SES score was grouped into tertiles, reflecting low, moderate and high neighborhood SES environment. Multilevel linear models were used to examine the relationship between neighborhood SES and change in MVPA over 24 months. At baseline, 94 (33.6%), 108 (38.6%) and 78 (27.9%) participants resided in low, moderate, and high SES neighborhoods, respectively. After adjusting for age, sex, and body mass index, no difference in average change in MVPA over time was observed between participants residing in low and moderate SES neighborhoods (p=0.48) or low and high SES neighborhoods (p=0.62). In Cuban immigrants, longitudinal change in MVPA may not vary by neighborhood socioeconomic environment.

•

Objectively measured time spent in MVPA was calculated among new Cuban immigrant adults.

•

Longitudinal associations between neighborhood SES and MVPA were assessed.

•

Study participants, on average, increased their physical activity over two years.

•

Multilevel modeling indicated that neighborhood SES and change in MVPA were not associated.

The Health and Working Conditions of Women Employed in Child Care

Over one million women are employed in child care and are among the lowest wage workers in the US. The health and working conditions of 674 child care workers (118 administrators and 556 staff) from 74 centers is described using baseline data from a larger intervention trial. Participants were 39.9 (±13.0) years old; 55.4% African American, 37.1% Caucasian, and 5.3% of Hispanic ethnicity. Seventy-six percent reported having an Associate’s degree or less; 42% were classified as at or below poverty (<$20,000); and exhibited many health risks such as excess weight, insufficient activity, poor diet, and inadequate sleep. We investigated potential differences by income and job category. Lower income participants were significantly more likely to be current smokers (19.9% vs. 11.7%), drink more sweetened beverages (1.9 vs. 1.5), and report higher depressive symptoms (15.5 vs. 12.6). Administrators worked more hours weekly compared to staff (46.4 vs. 40.6), are less active (100 vs. 126 min/week), more sedentary (501 vs. 477 min/day), and reported higher job demands (13.3 vs. 12.5). Given the numerous health issues and challenging work conditions, we hope our results serve as a call to action for addressing low wages and the work environment as a means of influencing the health and well-being of child care workers.

Behavior Change with Fitness Technology in Sedentary Adults: A Review of the Evidence for Increasing Physical Activity

Physical activity is closely linked with health and well-being; however, many Americans do not engage in regular exercise. Older adults and those with low socioeconomic status are especially at risk for poor health, largely due to their sedentary lifestyles. Fitness technology, including trackers and smartphone applications (apps), has become increasingly popular for measuring and encouraging physical activity in recent years. However, many questions remain regarding the effectiveness of this technology for promoting behavior change. Behavior change techniques such as goal setting, feedback, rewards, and social factors are often included in fitness technology. However, it is not clear which components are most effective and which are actually being used by consumers. We discuss additional strategies not typically included in fitness technology devices or apps that are promising for engaging inactive, vulnerable populations. These include action planning, restructuring negative attitudes, enhancing environmental conditions, and identifying other barriers to regular physical activity. We consider which strategies are most conducive to motivating behavior change among sedentary adults. Overall, fitness technology has the potential to significantly impact public health, research, and policies. We suggest ways in which app developers and behavior change experts can collaborate to develop successful apps. Advances are still needed to help inactive individuals determine how, when, where, and with whom they can increase their physical activity.

Measuring Physical Activity in Free-Living Conditions-Comparison of Three Accelerometry-Based Methods

We examined the agreement in time spent on different physical activity (PA) levels using (1) mean amplitude deviation (MAD) of raw acceleration from the hip, (2) wrist-worn Polar Active, and (3) hip-worn Actigraph counts using Freedson's cut-points among adults under free-living conditions. PA was measured in 41 volunteers (mean age 47.6 years) for 14 days. Two MET-based threshold sets were used for MAD and Polar Active for sedentary time (ST) and time spent in light (LPA), moderate (MPA), and vigorous (VPA) PA. Actigraph counts were divided into PA classes, ≤100 counts/min for ST and Freedson's cut-points for LPA, MPA, and VPA. Analysis criteria were simultaneous use of devices for at least 4 days of >500 min/d. The between-method differences were analyzed using a repeated measures analysis of variance test. Bland-Altman plots and ROC graphs were also employed. Valid data were available from 27 participants. Polar Active produced the highest amount of VPA with both thresholds (≥5 and ≥6 MET; mean difference 17.9-30.9 min/d, P < 0.001). With the threshold 3-6 MET for MPA, Polar Active indicated 19.2 min/d more than MAD (95% CI 5.8-32.6) and 51.0 min/d more than Actigraph (95% CI 36.7-65.2). The results did not differ with 3.5-5 MET for MPA [F_{(1.44, 37.43)} = 1.92, P = 0.170]. MAD and Actigraph were closest to each other for ST with the threshold < 1.5 MET (mean difference 22.2 min/d, 95% CI 7.1-37.3). With the threshold <2 MET, Polar Active and Actigraph provided similar results (mean difference 7.0 min/d, 95% CI -17.8-31.7). Moderate to high agreement (area under the ROC curve 0.806-0.963) was found between the methods for the fulfillment of the recommendation for daily moderate-to-vigorous PA of 60 min. In free-living conditions the agreement between MAD, Polar Active, and Actigraph for measuring time spent on different activity levels in adults was dependent on the activity thresholds used and PA intensity. ROC analyses showed moderate to high agreement for the fulfillment of the recommendation for daily MVPA. Without additional statistical adjustment, these methods cannot be used interchangeably when measuring daily PA, but any of the methods can be used to identify persons with insufficient daily amount of MVPA.

Strategic Priorities for Physical Activity Surveillance in the United States

PURPOSE

Develop strategic priorities to guide future physical activity surveillance in the United States.

METHODS

The Centers for Disease Control and Prevention and the American College of Sports Medicine convened a scientific roundtable of physical activity and measurement experts. Participants summarized the current state of aerobic physical activity surveillance for adults, focusing on practice and research needs in three areas: 1) behavior, 2) human movement, and 3) community supports. Needs and challenges for each area were identified. At the conclusion of the meeting, experts identified one overarching strategy and five strategic priorities to guide future surveillance.

RESULTS

The identified overarching strategy was to develop a national plan for physical activity surveillance similar to the U.S. National Physical Activity Plan for promotion. The purpose of the plan would be to enhance coordination and collaboration within and between sectors, such as transportation and public health, and to address specific strategic priorities identified at the roundtable. These strategic priorities were used 1) to identify and prioritize physical activity constructs; 2) to assess the psychometric properties of instruments for physical activity surveillance; 3) to provide training and technical assistance for those collecting, analyzing, or interpreting surveillance data; 4) to explore accessing data from alternative sources; and 5) to improve communication, translation, and dissemination about estimates of physical activity from surveillance systems.

CONCLUSION

This roundtable provided strategic priorities for physical activity surveillance in the United States. A first step is to develop a national plan for physical activity surveillance that would provide an operating framework from which to execute these priorities.

Practical considerations in using accelerometers to assess physical activity, sedentary behavior, and sleep

Increasingly, behavioral and epidemiological research uses activity-based measurements (accelerometry) to provide objective estimates of physical activity, sedentary behavior, and sleep in a variety of study designs. As interest in concurrently assessing these domains grows, there are key methodological considerations that influence the choice of monitoring instrument, analysis algorithm, and protocol for measuring these behaviors. The purpose of this review is to summarize evidence-guided information for 7 areas that are of importance in the design and interpretation of studies using actigraphy: (1) choice of cut-points; (2) impact of epoch length; (3) accelerometer placement; (4) duration of monitoring; (5) approaches for distinguishing sleep, nonwear times, and sedentary behavior; (6) role for a sleep and activity diary; and (7) epidemiological applications. Recommendations for future research are outlined and are intended to enhance the appropriate use of accelerometry for assessing physical activity, sedentary behavior, and sleep behaviors in research studies.

Accelerometer-based measures in physical activity surveillance: current practices and issues

OBJECTIVE

Self-reports of physical activity (PA) have been the mainstay of measurement in most non-communicable disease (NCD) surveillance systems. To these, other measures are added to summate to a comprehensive PA surveillance system. Recently, some national NCD surveillance systems have started using accelerometers as a measure of PA. The purpose of this paper was specifically to appraise the suitability and role of accelerometers for population-level PA surveillance.

METHODS

A thorough literature search was conducted to examine aspects of the generalisability, reliability, validity, comprehensiveness and between-study comparability of accelerometer estimates, and to gauge the simplicity, cost-effectiveness, adaptability and sustainability of their use in NCD surveillance.

CONCLUSIONS

Accelerometer data collected in PA surveillance systems may not provide estimates that are generalisable to the target population. Accelerometer-based estimates have adequate reliability for PA surveillance, but there are still several issues associated with their validity. Accelerometer-based prevalence estimates are largely dependent on the investigators' choice of intensity cut-off points. Maintaining standardised accelerometer data collections in long-term PA surveillance systems is difficult, which may cause discontinuity in time-trend data. The use of accelerometers does not necessarily produce useful between-study and international comparisons due to lack of standardisation of data collection and processing methods. To conclude, it appears that accelerometers still have limitations regarding generalisability, validity, comprehensiveness, simplicity, affordability, adaptability, between-study comparability and sustainability. Therefore, given the current evidence, it seems that the widespread adoption of accelerometers specifically for large-scale PA surveillance systems may be premature.