Objectively Measured Physical Activity and Sedentary Behavior in Successful Weight Loss Maintainers

Perceived importance of moderate-to-vigorous physical activity as a weight control strategy in behavioral weight loss

Background

Previous research has established the importance of moderate-to-vigorous physical activity (MVPA) for weight control. One area of unexplored investigation is the relationship between individuals' perceptions of the importance of MVPA for weight control and MVPA engagement. This study examined the associations between the perceived importance of MVPA and MVPA engagement, weight loss, barriers to PA, and exercise enjoyment in adults enrolled in a long-term behavioral weight loss (BWL) intervention.

Methods

Adults (N = 301) with overweight/obesity (BMI = 27-45 kg/m2) completed an 18-month BWL intervention, followed by a no-intervention 18-month follow-up. At baseline, 6 months, 18 months (i.e., post-treatment), and 36 months (i.e., follow-up), participants ranked the importance of six strategies for weight control: keeping a food record, MVPA, light PA, self-weighing, small portions, and low-calorie diet. Observed MVPA (measured by accelerometer), percent weight loss, perceived barriers to PA, and exercise enjoyment were also measured at each assessment.

Results

Results showed that most participants perceived MVPA as a primary weight control strategy (first, second, or third most important) throughout the intervention, regardless of the weight control goal (weight loss vs. maintenance). Individuals who ranked MVPA as a primary strategy for weight control at concurrent time points, compared to those who did not, engaged in significantly more MVPA at post-treatment, had greater weight loss at follow-up, endorsed fewer barriers to PA at post-treatment and follow-up, and reported greater exercise enjoyment at baseline and post-treatment.

Conclusion

Perceived importance of MVPA was related to subjective experiences of MVPA, MVPA adherence, and weight loss in a long-term BWL intervention.

New insights in the mechanisms of weight-loss maintenance: Summary from a Pennington symposium

Obesity is a chronic disease that affects more than 650 million adults worldwide. Obesity not only is a significant health concern on its own, but predisposes to cardiometabolic comorbidities, including coronary heart disease, dyslipidemia, hypertension, type 2 diabetes, and some cancers. Lifestyle interventions effectively promote weight loss of 5% to 10%, and pharmacological and surgical interventions even more, with some novel approved drugs inducing up to an average of 25% weight loss. Yet, maintaining weight loss over the long-term remains extremely challenging, and subsequent weight gain is typical. The mechanisms underlying weight regain remain to be fully elucidated. The purpose of this Pennington Biomedical Scientific Symposium was to review and highlight the complex interplay between the physiological, behavioral, and environmental systems controlling energy intake and expenditure. Each of these contributions were further discussed in the context of weight-loss maintenance, and systems-level viewpoints were highlighted to interpret gaps in current approaches. The invited speakers built upon the science of obesity and weight loss to collectively propose future research directions that will aid in revealing the complicated mechanisms involved in the weight-reduced state.

Behavioral, psychological, and environmental predictors of weight regain in a group of successful weight losers in a widely available weight-management program

OBJECTIVE

The aim of this study was to identify predictors of weight regain and continued weight maintenance among individuals already successful at long-term weight loss in a widely available weight-management program.

METHODS

Participants were 2843 weight-loss maintainers in WeightWatchers who had maintained weight loss ≥9.1 kg for ≥1 year (average 25.5 kg for 3.5 years; BMI = 26.7 kg/m2 ). Validated behavioral, psychosocial, and home environmental questionnaires were administered at study entry and 1 year later. Discriminant analysis identified variables that discriminated gainers (≥2.3-kg gain) from maintainers (±2.3-kg change).

RESULTS

Over the 1 year of follow-up, 43% were gainers (mean [SD], 7.2 [5.4] kg), and 57% were maintainers (0.4 [1.2] kg). Compared with maintainers, gainers were younger and had higher initial weight, more recent weight losses, and larger initial weight losses. Standardized canonical coefficients indicated that the 1-year changes that most discriminated gainers from maintainers were greater decreases in the ability to accept uncomfortable food cravings, urges, and desires to overeat (0.232); self-monitoring (0.166); body image (0.363); and body satisfaction (0.194) and greater increases in disinhibition (0.309) and bodily pain (0.147). The canonical correlation was 0.505 (p < 0.001).

CONCLUSIONS

Future interventions to prevent regain should consider targeting overeating in response to internal and external food cues and declines in self-monitoring and body image.

Does the built environment influence location- and trip-based sedentary behaviors? Evidence from a GPS-based activity space approach of neighborhood effects on older adults

OBJECTIVE

Evidence on the influence of built environments on sedentary behaviors remains unclear and is often contradictory. The main limitations encompass the use of self-reported proxies of sedentary time (ST), the scarce consideration of the plurality of sedentary behaviors, and environmental exposures limited to the residential neighborhood. We investigated the relationships between GPS-based activity space measures of environmental exposures and accelerometer-based ST measured in total, at the place of residence, at all locations, and during trips.

METHODS

This study is part of the CURHA project, based on 471 older adults residing in Luxembourg, who wore a GPS receiver and a tri-axial accelerometer during 7 days. Daily ST was computed in total, at the residence, at all locations and during trips. Environmental exposures included exposure to green spaces, walking, biking, and motorized transportation infrastructures. Associations between environments and ST were examined using linear and negative binomial mixed models, adjusted for demographics, self-rated health, residential self-selection, weather conditions and wear time.

RESULTS

Participants accumulated, on average, 8 h and 14 min of ST per day excluding sleep time. ST spent at locations accounted for 83 % of the total ST. ST spent at the residence accounted for 87 % of the location-based ST and 71 % of the total ST. Trip-based ST represents 13 % of total ST, and 4 % remained unclassified. Higher street connectivity was negatively associated with total ST, while the density of parking areas correlated positively with total and location-based ST. Stronger associations were observed for sedentary bouts (uninterrupted ST over 20 and 30 min).

CONCLUSION

Improving street connectivity and controlling the construction of new parking, while avoiding the spatial segregation of populations with limited access to public transport, may contribute to limit ST. Such urban planning interventions may be especially efficient in limiting the harmful uninterrupted bouts of ST among older adults.

Uncovering Barriers and Facilitators of Weight Loss and Weight Loss Maintenance: Insights from Qualitative Research

Long-term weight loss maintenance is often difficult to achieve. This review analysed qualitative data on self-perceived barriers and facilitators of weight loss and weight loss maintenance among weight loss intervention participants. A literature search was conducted using electronic databases. Qualitative studies written in English and published between 2011-2021 were eligible for inclusion if they explored the perspectives and experiences of individuals who received standardised dietary and behavioural support for weight loss. Studies were excluded if weight loss was achieved through self-directed methods, only increasing physical activity, or surgical or pharmacological interventions. Fourteen studies were included, totaling 501 participants from six countries. Thematic analysis was used to identify four aggregate themes: internal factors (i.e., motivation and self-efficacy), programme-specific factors (i.e., the intervention diet), social factors (i.e., supporters and saboteurs), and environmental factors (i.e., an obesogenic environment). Our findings demonstrate that internal, social, and environmental factors all influence weight loss success, as well as the acceptability of the weight loss intervention. Future interventions may be more successful if they prioritise participant acceptability and engagement by, for example, providing tailored interventions, a structured relapse management plan, strategies to enhance autonomous motivation and emotional self-regulation, and extended contact during weight loss maintenance.

Lifestyle strategies after intentional weight loss: results from the MAINTAIN-pc randomized trial

Introduction/Purpose

Weight maintenance following intentional weight loss is challenging and often unsuccessful. Physical activity and self-monitoring are strategies associated with successful weight loss maintenance. However, less is known about the type and number of lifestyle strategies used following intentional weight loss. The purpose of this study was to determine the types and amounts of strategies associated with successful long-term weight loss maintenance.

Methods

Data from the 24-month Maintaining Activity and Nutrition Through Technology-Assisted Innovation in Primary Care (MAINTAIN-pc) trial were analyzed. MAINTAIN-pc recruited adults (n=194; 53.4±12.2 years of age, body mass index (BMI): 30.4±5.9 kg/m2, 74% female) with recent intentional weight loss of ≥5%, randomized to tracking tools plus coaching (i.e., coaching group) or tracking tools without coaching (i.e., tracking-only group). At baseline, 6, 12, and 24 months, participants reported lifestyle strategies used in the past 6 months, including self-monitoring, group support, behavioral skills, and professional support. General linear models evaluated changes in the number of strategies over time between groups and the consistency of strategies used over the 24-month intervention.

Results

At baseline, 100% used behavioral skills, 73% used group support, 69% used self-monitoring, and 68% used professional support in the past 6 months; at 24 months, these rates were 98%, 60%, 75%, and 61%, respectively. While the number of participants utilizing individual strategies did not change significantly over time, the overall number of strategies participants reported decreased. More strategies were used at baseline and 6 months compared to 12- and 24-month follow-ups. The coaching group used more strategies at months 6 and 12 than the tracking-only group. Consistent use of professional support strategies over the 24-month study period was associated with less weight regain.

Conclusion

Weight loss maintenance interventions that incorporate continued follow-up and support from healthcare professionals are likely to prevent weight regain after intentional weight loss.

The role of physical activity in the regulation of body weight: The overlooked contribution of light physical activity and sedentary behaviors

The role of physical activity (PA) in the regulation of body weight is still a major topic of debate. This may be because studies have essentially focused on the effects of moderate/vigorous PA (MVPA) on body weight while overlooking the other components of PA, namely, light-intensity PA (LPA, daily life activities) and sedentary behaviors (SB, too much sitting). In this review, we will (i) describe the history of changes in PA behaviors that occurred with modernization; (ii) review data from cross-sectional and longitudinal studies that examined the associations between PA, SB, and measures of obesity; (iii) review interventional studies that investigated the effects of changes in PA and SB on body weight and adiposity; and (iv) discuss experimental studies that addressed potential biological mechanisms underlying the effects of PA and SB on weight regulation. Overall recent findings support the importance of considering all components of PA to better understand the regulation of energy balance and suggest an important role for LPA and SB in addition to MVPA on body weight regulation. Longitudinal large-scale rigorous studies are needed to advance our knowledge of the role of PA/SB in combating the obesity epidemic.

Positive and negative psychosocial factors related to healthy and unhealthy weight control among nursing students

BACKGROUND

Although nursing students are educated on the importance of exercising regularly and maintaining a well-balanced diet, many do not practice healthy weight management behaviors, and some even use unhealthy weight loss methods. Yet, little research has examined both positive and negative psychosocial variables related to weight control among nursing students.

PURPOSE

The present study aimed to identify the most salient psychosocial variables related to healthy and unhealthy weight control among nursing students.

METHOD

Using survey data from 241 nursing students, structural equation modeling was conducted to examine the relative contributions of eight interrelated psychosocial variables, including constructs from a strengths perspective (health-specific hope, health self-efficacy, social support, and body satisfaction) and from a deficit perspective (depression, anxiety, weight perception, and barriers to physical activity).

RESULTS

Results showed that the degree to which individuals perceive themselves to be overweight was related to both healthy and unhealthy weight control. Aside from weight perception, health self-efficacy produced the strongest association with healthy weight control, and anxiety produced the strongest association with unhealthy weight control. The structural model explained 23 % of the variance in healthy weight control and 29 % of the variance in unhealthy weight control.

CONCLUSIONS

These findings emphasize the need for tailored, integrated weight management interventions for nursing students that equip them with effective anxiety management skills and build self-efficacy.

The impact of yoga on components of energy balance in adults with overweight or obesity: A systematic review

Background

Yoga may reduce body weight in individuals with overweight or obesity, but whether this occurs through decreased energy intake (EI) or increased energy expenditure (EE)/physical activity (PA) is unclear.

Methods

A systematic search of PubMed, Web of Science, Embase, and PsychINFO was conducted from inception until April 26, 2021. Eligible studies included randomized controlled trials or single‐arm pre‐post studies with any type and duration of yoga intervention in adults with overweight or obesity. Studies with measures related to EI , EE, or PA were eligible. The review initially identified 1,373 articles.

Results

Of the 10 included studies, one used indirect calorimeter measures of resting EE, while nine used self‐reported measures of EI and PA. Of the seven studies measuring parameters related to EI, only one found greater decreases in EI relative to the control group, although three other investigations reported trends toward improved dietary intake. Of the eight studies measuring PA, two reported greater increases in resting EE or PA in the yoga group relative to the control group. Two reported significant within‐group increases in PA from pre‐post intervention, and four studies reported a trend for increased PA with no p‐values reported.

Conclusions

Limited evidence suggests yoga may reduce EI and increase PA in adults with overweight or obesity. Additional studies that investigate the effects of yoga interventions on energy balance parameters using objective techniques are warranted.

Increases in physical activity are associated with a faster rate of weight loss during dietary energy restriction in women with overweight and obesity

This secondary analysis examined the influence of changes in physical activity (PA), sedentary time and energy expenditure (EE) during dietary energy restriction on the rate of weight loss (WL) and 1-year follow-up weight change in women with overweight/obesity.Measurements of body weight and composition (air-displacement plethysmography), resting metabolic rate (indirect calorimetry), total daily (TDEE) and activity EE (AEE), minutes of PA and sedentary time (PA monitor) were taken at baseline, after 2 weeks, after ≥5% WL or 12 weeks of continuous (25% daily energy deficit) or intermittent (75% daily energy deficit alternated with ad libitum day) energy restriction, and at 1-year post-WL. The rate of WL was calculated as total %WL/number of dieting weeks. Data from both groups were combined for analyses.Thirty-seven participants (age=35±10y; BMI=29.1±2.3kg/m2) completed the intervention (WL=-5.9±1.6%) and 18 returned at 1-year post-WL (weight change=+4.5±5.2%). Changes in sedentary time at 2 weeks were associated with the rate of WL during energy restriction (r=-0.38; p=0.03). Changes in total (r=0.54; p<0.01), light (r=0.43; p=0.01) and moderate-to-vigorous PA (r=0.55; p<0.01), sedentary time (r=-0.52; p<0.01), steps per day (r=0.39; p=0.02), TDEE (r=0.46; p<0.01) and AEE (r=0.51; p<0.01) during energy restriction were associated with the rate of WL. Changes in total (r=-0.50; p=0.04) and moderate-to-vigorous PA (r=-0.61; p=0.01) between post-WL and follow-up were associated with 1-year weight change (r=-0.51; p=0.04).These findings highlight that PA and sedentary time could act as modifiable behavioural targets to promote better weight outcomes during dietary energy restriction and/or weight maintenance.

Intervening on exercise and daylong movement for weight loss maintenance in older adults: A randomized, clinical trial

OBJECTIVE

This study aimed to determine the impact of dietary weight loss (WL) plus aerobic exercise (EX) and a "move more, more often" approach to activity promotion (SitLess; SL) on WL and maintenance.

METHODS

Low-active older adults (age 65-86 years) with obesity were randomized to WL+EX, WL+SL, or WL+EX+SL. Participants received a social-cognitive group-mediated behavioral WL program for 6 months, followed by a 12-month maintenance period. EX participants received guided walking exercise with the goal of walking 150 min/wk. SL attempted to achieve a step goal by moving frequently during the day. The primary outcome was body weight at 18 months, with secondary outcomes including weight regain from 6 to 18 months and objectively assessed physical activity and sedentary behavior at each time point.

RESULTS

All groups demonstrated significant WL over 6 months (p < 0.001), with no group differences. Groups that received SL improved total activity time (p ≤ 0.05), and those who received EX improved moderate-to-vigorous activity time (p = 0.003). Over the 12-month follow-up period, those who received WL+EX demonstrated greater weight regain (5.2 kg; 95% CI: 3.5-6.9) relative to WL+SL (2.4 kg; 95% CI: 0.8-4.0).

CONCLUSIONS

Pairing dietary WL with a recommendation to accumulate physical activity contributed to similar WL and less weight regain compared with traditional aerobic exercise.

Physical Activity and Total Daily Energy Expenditure in Older US Adults: Constrained versus Additive Models

PURPOSE

This study aimed to examine the shape of the relationship between physical activity (PA) and total energy expenditure (TEE) and to explore the role of energy balance status (negative, stable, positive) in influencing this association.

METHODS

Cross-sectional. Participants were 584 older adults (50-74 yr) participating in the Interactive Diet and Activity Tracking in AARP study. TEE was assessed by doubly labeled water and PA by accelerometer. The relationship between PA and TEE was assessed visually and using nonlinear methods (restricted cubic splines). Percent weight change (>3%) over a 6-month period was used as a proxy measurement of energy balance status.

RESULTS

TEE generally increased with increasing deciles of PA averaging 2354 (SD, 351) kcal·d-1 in the bottom decile to 2693 (SD, 480) kcal·d-1 in the top decile. Cubic spline models showed an approximate linear association between PA and TEE (linear relation, P < 0.0001; curvature, P = 0.920). Results were similar in subgroup analyses for individuals classified as stable or positive energy balance. For those in negative energy balance, TEE was generally flat with increasing deciles of PA averaging 2428 (SD, 285) kcal·d-1 in the bottom decile to 2372 (SD, 560) kcal·d-1 in the top decile.

CONCLUSIONS

Energy balance status seems to play an important role in the relationship between PA and TEE. When in a positive energy balance, the relationship between TEE and PA was consistent with an additive model; however, when energy balance was negative, TEE seems to be consistent with a constrained model. These findings support PA for weight gain prevention by increasing TEE; however, the effect of PA on TEE during periods of weight loss may be limited. An adequately powered, prospective study is warranted to confirm these exploratory findings.

Examining the Role of Exercise Timing in Weight Management: A Review

Many adults cite exercise as a primary strategy for losing weight, yet exercise alone is modestly effective for weight loss and results in variable weight loss responses. It is possible that some of the variability in weight loss may be explained by the time of day that exercise is performed. Few studies have directly compared the effects of exercise performed at different times of the day (i. e., morning versus evening exercise). Results from these existing studies are mixed with some studies demonstrating superior weight and fat mass loss from morning exercise, while other studies have found that evening exercise may be better for weight management. Exercise timing may alter modifiable lifestyle behaviors involved in weight management, such as non-exercise physical activity, energy intake, and sleep. The purpose of this review is to summarize evidence for and against time-of-day dependent effects of exercise on weight management. Although limited, we also review studies that have examined the effect of exercise timing on other lifestyle behaviors linked to body weight regulation. While exercise at any time of day is beneficial for health, understanding whether there is an optimal time of day to exercise may advance personalized treatment paradigms for weight management.

Temporal patterns of physical activity in successful weight loss maintainers

BACKGROUND/OBJECTIVES

Individuals successful at weight loss maintenance engage in high amounts of physical activity (PA). Understanding how and when weight loss maintainers accumulate PA within a day and across the week may inform PA promotion strategies and recommendations for weight management.

METHODS

We compared patterns of PA in a cohort of weight loss maintainers (WLM, n = 28, maintaining ≥13.6 kg weight loss for ≥1 year, BMI 23.6 ± 2.3 kg/m²), controls without obesity (NC, n = 30, BMI similar to current BMI of WLM, BMI 22.8 ± 1.9 kg/m²), and controls with overweight/obesity (OC, n = 26, BMI similar to pre-weight loss BMI of WLM, 33.6 ± 5.1 kg/m²). PA was assessed during 7 consecutive days using the activPAL^TM activity monitor. The following variables were quantified; sleep duration, sedentary time (SED), light-intensity PA (LPA), moderate-to-vigorous intensity PA (MVPA), and steps. Data were examined to determine differences in patterns of PA across the week and across the day using mixed effect models.

RESULTS

Across the week, WLM engaged in ≥60 min of MVPA on 73% of days, significantly more than OC (36%, p < 0.001) and similar to NC (59%, p = 0.10). Across the day, WLM accumulated more MVPA in the morning (i.e., within 3 h of waking) compared to both NC and OC (p < 0.01). WLM engaged in significantly more MVPA accumulated in bouts ≥10 min compared to NC and OC (p < 0.05). Specifically, WLM engaged in more MVPA accumulated in bouts of ≥60 min compared to NC and OC (p < 0.05).

CONCLUSIONS

WLM engage in high amounts of MVPA (≥60 min/d) on more days of the week, accumulate more MVPA in sustained bouts, and accumulate more MVPA in the morning compared to controls. Future research should investigate if these distinct patterns of PA help to promote weight loss maintenance.

Comparison of the Validity and Generalizability of Machine Learning Algorithms for the Prediction of Energy Expenditure: Validation Study

Background

Accurate solutions for the estimation of physical activity and energy expenditure at scale are needed for a range of medical and health research fields. Machine learning techniques show promise in research-grade accelerometers, and some evidence indicates that these techniques can be applied to more scalable commercial devices.

Objective

This study aims to test the validity and out-of-sample generalizability of algorithms for the prediction of energy expenditure in several wearables (ie, Fitbit Charge 2, ActiGraph GT3-x, SenseWear Armband Mini, and Polar H7) using two laboratory data sets comprising different activities.

Methods

Two laboratory studies (study 1: n=59, age 44.4 years, weight 75.7 kg; study 2: n=30, age=31.9 years, weight=70.6 kg), in which adult participants performed a sequential lab-based activity protocol consisting of resting, household, ambulatory, and nonambulatory tasks, were combined in this study. In both studies, accelerometer and physiological data were collected from the wearables alongside energy expenditure using indirect calorimetry. Three regression algorithms were used to predict metabolic equivalents (METs; ie, random forest, gradient boosting, and neural networks), and five classification algorithms (ie, k-nearest neighbor, support vector machine, random forest, gradient boosting, and neural networks) were used for physical activity intensity classification as sedentary, light, or moderate to vigorous. Algorithms were evaluated using leave-one-subject-out cross-validations and out-of-sample validations.

Results

The root mean square error (RMSE) was lowest for gradient boosting applied to SenseWear and Polar H7 data (0.91 METs), and in the classification task, gradient boost applied to SenseWear and Polar H7 was the most accurate (85.5%). Fitbit models achieved an RMSE of 1.36 METs and 78.2% accuracy for classification. Errors tended to increase in out-of-sample validations with the SenseWear neural network achieving RMSE values of 1.22 METs in the regression tasks and the SenseWear gradient boost and random forest achieving an accuracy of 80% in classification tasks.

Conclusions

Algorithms trained on combined data sets demonstrated high predictive accuracy, with a tendency for superior performance of random forests and gradient boosting for most but not all wearable devices. Predictions were poorer in the between-study validations, which creates uncertainty regarding the generalizability of the tested algorithms.

The Long-Term Dietitian and Psychological Support of Obese Patients Who Have Reduced Their Weight Allows Them to Maintain the Effects

The role of post-therapeutic support after weight loss in obesity treatment is not fully understood. Therefore, weight maintenance after a successful weight loss intervention is not very common, especially in obese individuals. This randomized controlled study was conducted to explore the efficacy of following dietary and psychological support in a group of 36 obese individuals. Participants (22 women, 14 men aged 35.58 ± 9.85 years, BMI 35.04 ± 3.80 kg/m²) who completed a 12-month weight loss phase (balanced energy-restricted diet) were randomly allocated to receive 18-month support (SG) or no additional care (CG). The support phase included some elements of Ten Top Tips (TTT), cognitive behavioral therapy (CBT), motivational interviewing (MI) in combination with nutritional education and assessment of the level of physical activity. The primary outcome was the maintenance of anthropometric parameters at an 18-month follow-up. The secondary outcomes included evaluation of biochemical parameters and single nucleotide polymorphisms (SNPs) in genes connected with obesity. A comparison of SG vs. CG after a 30-month period of the study revealed significant differences in weight changes (−3.83 ± 6.09 vs. 2.48 ± 6.24 kg), Body Mass Index (−1.27 ± 2.02 vs. 0.72 ± 2.12 kg/m²), visceral adipose tissue (−0.58 ± 0.63 vs. 0.45 ± 0.74 L), and waist circumference (−4.83 ± 4.05 vs. 1.83 ± 5.97 cm). Analysis of SNPs (rs9939609 FTO, rs987237 TFAP2B, and rs894160 PLIN1) provided further insight into the potential modulating effect of certain genotypes on weight loss and maintenance and extended the knowledge of the potential benefits of personalized medicine. Post-therapeutical support in current clinical practice may increase the chances of long-term weight loss maintenance in obesity treatment even in patients with a genetic predisposition to excessive weight.

Sitting Time, Type, and Context Among Long-Term Weight-Loss Maintainers

OBJECTIVE

This study aimed to investigate sitting time, the home sedentary environment, and physical activity among weight-loss maintainers in WW (formerly Weight Watchers).

METHODS

Participants were 4,305 weight-loss maintainers who had maintained ≥9.1 kg of weight loss (24.7 kg on average) for 3.3 years and had an average current BMI of 27.6 kg/m² . A control group of weight-stable individuals with obesity (n = 619) had an average BMI of 38.9 kg/m² . The Multicontext Sitting Time Questionnaire and Paffenbarger physical activity questionnaire were administered.

RESULTS

Weight-loss maintainers versus controls spent 3 hours less per day sitting during the week (10.9 vs. 13.9; η p 2 = 0.039; P = 0.0001) and weekends (9.7 vs. 12.6; η p 2 = 0.038). Weight-loss maintainers versus controls spent 1 hour less per day in non-work-related sitting using a computer or video games during the week (1.4 vs. 2.3; η p 2 = 0.03; P = 0.0001) and weekends (1.5 vs. 2.5; η p 2 = 0.03; P = 0.0001). Weight-loss maintainers versus controls had similar numbers of sedentary-promoting devices (15.8 vs. 14.8) and expended significantly more calories per week in physical activity (1,835 vs. 785; η p 2 = 0.036; P = 0.0001).

CONCLUSIONS

Weight-loss maintainers reported less time sitting than weight-stable individuals with obesity. Future research should test the efficacy of targeting sitting time to help promote long-term weight-loss maintenance.

Physical Activity, Sleep, and Sedentary Behavior among Successful Long-Term Weight Loss Maintainers: Findings from a U.S. National Study

Despite adults’ desire to reduce body mass (weight) for numerous health benefits, few are able to successfully lose at least 5% of their starting weight. There is evidence on the independent associations of physical activity, sedentary behaviors, and sleep with weight loss; however, this study provided insight on the combined effects of these behaviors on long-term body weight loss success. Hence, the purpose of this cross-sectional study was to evaluate the joint relations of sleep, physical activity, and sedentary behaviors with successful long-term weight loss. Data are from the 2005–2006 wave of the National Health and Examination Survey (NHANES). Physical activity and sedentary behavior were measured with an accelerometer, whereas sleep time was self-reported. Physical activity and sleep were dichotomized into meeting guidelines (active/not active, ideal sleep/short sleep), and sedentary time was categorized into prolonged sedentary time (4th quartile) compared to low sedentary time (1st–3rd quartiles). The dichotomized behaviors were combined to form 12 unique behavioral combinations. Two-step multivariable regression models were used to determine the associations between the behavioral combinations with (1) long-term weight loss success (≥5% body mass reduction for ≥12-months) and (2) the amount of body mass reduction among those who were successful. After adjustment for relevant factors, there were no significant associations between any of the independent body weight loss behaviors (physical activity, sedentary time, and sleep) and successful long-term weight loss. However, after combining the behaviors, those who were active (≥150 min MVPA weekly), regardless of their sedentary time, were significantly (p < 0.05) more likely to have long-term weight loss success compared to the inactive and sedentary referent group. These results should be confirmed in longitudinal analyses, including investigation of characteristics of waking (type, domain, and context) and sleep (quality metrics) behaviors for their association with long-term weight loss success.

Underreporting of energy intake in weight loss maintainers

BACKGROUND

Individuals with overweight or obesity commonly underreport energy intake (EI), but it is unknown if the tendency to underreport persists in formerly obese individuals who lose significant weight and maintain their weight loss over long periods of time.

OBJECTIVE

Assess the accuracy of self-reported EI in successful weight loss maintainers (WLM) compared with controls of normal body weight (NC) and controls with overweight/obesity (OC).

METHODS

Participants for this case-controlled study were recruited in 3 groups: WLM [n = 26, BMI (in kg/m2) 24.1 ± 2.3; maintaining ≥13.6 kg weight loss for ≥1 y], NC (n = 33, BMI 22.7 ± 1.9; similar to current BMI of WLM), and OC (n = 32, BMI 34.0 ± 4.6; similar to pre-weight loss BMI of WLM). Total daily energy expenditure (TDEE) was measured over 7 d using the doubly labeled water (DLW) method, and self-reported EI was concurrently measured from 3-d diet diaries. DLW TDEE and self-reported EI were compared to determine accuracy of self-reported EI.

RESULTS

WLM underreported EI (median, interquartile range) (-605, -915 to -314 kcal/d) to a greater degree than NC (-308, -471 to -68 kcal/d; P < 0.01) but not more than OC (-310, -970 to 18 kcal/d; P = 0.21). WLM also showed a greater degree of relative underreporting (-25.3%, -32.9% to -12.5%) compared with NC (-14.3%, -19.6% to -3.1%; P = 0.02) but not OC (-11.2%, -34.1% to -0.7%; P = 0.16). A greater proportion of WLM was classified as underreporters (30.8%) than NC (9.1%; P = 0.05) but not OC (28.1%; P = 1.00).

CONCLUSIONS

WLM underreported EI in both absolute and relative terms to a greater extent than NC but not OC. These findings call into question the accuracy of self-reported EI in WLM published in previous studies and align with recent data suggesting that WLM rely less on chronic EI restriction and more on high levels of physical activity to maintain weight loss. This trial was registered at clinicaltrials.gov as NCT03422380.

A Randomized Trial Evaluating Exercise for the Prevention of Weight Regain

OBJECTIVE

This study aimed to evaluate the effectiveness of three levels of exercise on weight regain subsequent to clinically meaningful weight loss (WL).

METHODS

Adults with overweight or obesity (n = 298) initiated a 3-month behavioral WL intervention, which included reduced energy intake, increased exercise, and weekly behavioral counseling. Participants achieving ≥5% WL (n = 235) began a 12-month behavioral WL maintenance intervention and were randomized to 150 min/wk (n = 76), 225 min/wk (n = 80), or 300 min/wk (n = 79) of partially supervised moderate-to-vigorous-intensity exercise.

RESULTS

Participants randomized to 150, 225, and 300 minutes of exercise completed 129 ± 30, 153 ± 49 and 179 ± 62 min/wk of exercise (supervised + unsupervised), respectively. Mean WL at 3 months (9.5 ± 3.1 kg) was similar across randomized groups (P = 0.68). Weight change across 12 months was 1.1 ± 6.5 kg, 3.2 ± 5.7 kg, and 2.8 ± 6.9 kg in the 150, 225, and 300 min/wk groups, respectively. Intent-to-treat analysis revealed no significant overall trend across the three treatment groups (P = 0.09), effects for group (P = 0.08), or sex (P = 0.21).

CONCLUSIONS

This study found no evidence for an association between the volume of moderate-to-vigorous-intensity exercise and weight regain across 12 months following clinically relevant WL. Further, results suggest that exercise volumes lower than those currently recommended for WL maintenance, when completed in conjunction with a behavioral weight-maintenance intervention, may minimize weight regain over 12 months.

Leisure Sedentary Behavior Levels and Meeting Program Goals in a Community Lifestyle Intervention for Diabetes Prevention

BACKGROUND

The importance of leisure sedentary behavior (LSB) change in diabetes prevention efforts is not well known. This study examines the relationships between changes in self-reported LSB and the primary intervention goals (weight and moderate-intensity to vigorous-intensity physical activity [MVPA]) during a community-based translation of the Diabetes Prevention Program (the Group Lifestyle Balance Program).

METHODS

A total of 322 adults at risk for type 2 diabetes were recruited from 3 community centers, a worksite, and military site. Community and worksite participants were randomized to immediate or delayed-delivery (control) intervention. All military site participants (n = 99) received immediate intervention. Logistic and linear generalized estimating equations were used to determine associations between LSB changes and weight-related outcomes and MVPA.

RESULTS

Results were obtained for 259 (80.4%) participants. The LSB decreased after 6 and 12 months (mean [95% confidence interval]: -25.7 [-38.6 to -12.8] and -16.1 [-28.2 to -3.9] min/d; both P < .05). Each 20-minute reduction in LSB was associated with a 5% increase in odds of meeting the weight-loss goal (6 mo: odds ratio = 1.05 [1.002 to 1.102]; P = .042; adjusted model including MVPA), but LSB was not related to changes in reported MVPA minutes or MVPA goal achievement.

CONCLUSION

Within the context of existing lifestyle intervention programs, reducing sedentary behavior has the potential to contribute to weight loss separately from reported MVPA improvement.

Gender and racial/ethnic differences in physiologic responses in the Stimulant Reduction Intervention using Dosed Exercise Study

Exercise may be beneficial for individuals in substance use disorder (SUD) treatment given the higher rates of both medical and psychiatric comorbidity, namely mood and anxiety disorders, compared to the general population. Gender and/or racial/ethnic differences in health benefits and response to prescribed exercise have been reported and may have implications for designing exercise interventions in SUD programs.

METHOD

Data are from the National Drug Abuse Treatment Clinical Trials Network (NIDA/CTN) Stimulant Reduction Intervention using Dosed Exercise (STRIDE) trial. Gender differences across racial/ethnic groups in physiological responses and stimulant withdrawal severity across time were analyzed using linear mixed effects models.

RESULTS

Males completed significantly more exercise sessions than females and were more adherent to the prescribed exercise dose of 12 Kcal/Kg/Week. Controlling for age, race/ethnicity, treatment group and stimulant withdrawal severity, there was a significant gender by time interaction for body mass index (BMI) (p < 0.001), waist circumference (p < 0.001) and heart rate measured prior to exercise sessions (p < 0.01). For females, body mass index (BMI) and waist circumference increased over time while for males BMI and waist circumference stayed unchanged or slightly decreased with time. Heart rate over time significantly increased for females at a higher rate than in males. Stimulant withdrawal severity was similar in males and females at baseline but males exhibited a significant decrease over time while females did not. Although baseline differences were observed, there were no time by race/ethnicity differences in physiologic responses.

DISCUSSION

Gender differences in response to exercise may have implications for developing gender specific exercise interventions in SUD programs.

Misguided Opposition to Multiplicity Adjustment Remains a Problem

Fallacious arguments against multiplicity adjustment have been cited with increasing frequency to defend unadjusted tests. These arguments and their enduring impact are discussed in this paper.

Cognitive and behavioural strategies employed to overcome "lapses" and prevent "relapse" among weight-loss maintainers and regainers: A qualitative study

While many behavioural weight management programmes are effective in the short-term, post-programme weight regain is common. Overcoming "lapses" and preventing "relapse" has been highlighted as important in weight-loss maintenance, but little is known on how this is achieved. This study aimed to compare the cognitive and behavioural strategies employed to overcome "lapses" and prevent "relapse" by people who had regained weight or maintained weight-loss after participating in a weight management programme. By investigating differences between groups, we intended to identify strategies associated with better weight-loss maintenance. Semi-structured interviews were conducted with 26 participants (58% female) recruited from the 5-year follow-up of the Weight Loss Referrals for Adults in Primary Care (WRAP) trial (evaluation of a commercial weight-loss programme). Participants who had lost ≥5% baseline weight during the active intervention were purposively sampled according to 5-year weight trajectories (n = 16 'Regainers', n = 10 'Maintainers'). Interviews were audio-recorded, transcribed verbatim, and analysed thematically. Key differences in strategies were that Maintainers continued to pay attention to their dietary intake, anticipated and planned for potential lapses in high-risk situations, and managed impulses using distraction techniques. Regainers did not report making plans, used relaxed dietary monitoring, found distraction techniques to be ineffective and appeared to have difficulty navigating food within interpersonal relationships. This study is one of the longest qualitative follow-ups of a weight loss trial to date, offering unique insights into long-term maintenance. Future programmes should emphasize strategies focusing on self-monitoring, planning and managing interpersonal relationships to help participants successfully maintain weight-loss in the longer-term.

Unravelling the health effects of fasting: a long road from obesity treatment to healthy life span increase and improved cognition

In recent years a revival of interest has emerged in the health benefits of intermittent fasting and long-term fasting, as well as of other related nutritional strategies. In addition to meal size and composition a new focus on time and frequency of meals has gained attention. The present review will investigate the effects of the main forms of fasting, activating the metabolic switch from glucose to fat and ketones (G-to-K), starting 12-16 h after cessation or strong reduction of food intake. During fasting the deactivation of mTOR regulated nutrient signalling pathways and activation of the AMP protein kinase trigger cell repair and inhibit anabolic processes. Clinical and animal studies have clearly indicated that modulating diet and meal frequency, as well as application of fasting patterns, e.g. intermittent fasting, periodic fasting, or long-term fasting are part of a new lifestyle approach leading to increased life and health span, enhanced intrinsic defences against oxidative and metabolic stresses, improved cognition, as well as a decrease in cardiovascular risk in both obese and non-obese subjects. Finally, in order to better understand the mechanisms beyond fasting-related changes, human studies as well as non-human models closer to human physiology may offer useful clues.KEY-MESSAGESBiochemical changes during fasting are characterised by a glucose to ketone switch, leading to a rise of ketones, advantageously used for brain energy, with consequent improved cognition.Ketones reduce appetite and help maintain effective fasting.Application of fasting patterns increases healthy life span and defences against oxidative and metabolic stresses.Today's strategies for the use of therapeutic fasting are based on different protocols, generally relying on intermittent fasting, of different duration and calorie intake.Long-term fasting, with durations between 5 and 21 days can be successfully repeated in the course of a year.

Relationship of objectively measured physical activity and sedentary behaviour with health-related quality of life among breast cancer survivors

Background

Lack of physical activity throughout one’s lifetime has been associated with obesity and it is also an important risk factor of breast cancer. This study aimed to determine the relationship between objectively measured physical activity and sedentary behaviour with health-related quality of life (HRQoL) among breast cancer survivors in the East Coast region of Peninsular Malaysia.

Methods

A cross-sectional study involving 83 breast cancer survivors was carried out in two main government referral hospitals in the region. Participants wore the ActivPAL3™ microdevice physical activity monitor for seven consecutive days. The validated European Organization for Research and Treatment of Cancer Quality of Life Questionnaires (EORTC QLQ–C30) and Breast Cancer Supplementary Measure (EORTC QLQ-BR23) were used to measure their HRQoL. Multiple linear regression analysis was conducted to determine the relationship between objectively measured physical activity and sedentary behaviour with HRQoL.

Results

Longer time spent on moderate to vigorous physical activity (MVPA) was significantly associated with an improvement of HRQoL (p = 0.039) whereas longer time spent on sedentary behaviour significantly reduced the functioning score (p = 0.005). In addition, prolonged sedentary bouts were also significantly associated with better body image that led to improved HRQoL (p = 0.013).

Conclusions

The study findings suggest that an increase in the time spent on MVPA was associated with improved HRQoL while sedentary behaviour was associated with poorer HRQoL among breast cancer survivors. Thus, it is essential to displace sedentary behaviour with MVPA to improve the quality of life of breast cancer survivors.

On computing critical factors based healthy behavior index for behavior assessment

OBJECTIVE

Ubiquitous computing has supported personalized health through a vast variety of wellness and healthcare self-quantification applications over the last decade. These applications provide insights for daily life activities but unable to portray the comprehensive impact of personal habits on human health. Therefore, in order to facilitate the individuals, we have correlated the lifestyle habits in an appropriate proportion to determine the overall impact of influenced behavior on the well-being of humans.

MATERIALS AND METHODS

To study the combined impact of personal behaviors, we have proposed a methodology to derive the comprehensive Healthy Behavior Index (HBI) consisting of two major processes: (1) Behaviors' Weight-age Identification (BWI), and (2) Healthy Behavior Quantification and Index (HBQI) modeling. The BWI process identifies the high ranked contributing behaviors through life-expectancy based weight-age, whereas HBQI derives a mathematical model based on quantification and indexing of behavior using wellness guidelines.

RESULTS

The contributing behaviors are identified through text mining technique and verified by seven experts with a Kappa agreement level of 0.379. A real-world user-centric statistical evaluation is applied through User Experience Questionnaire (UEQ) method to evaluate the impact of HBI service. This HBI service is developed for the Mining Minds, a wellness management application. This study involves 103 registered participants (curious about the chronic disease) for a Korean wellness management organization. They used the HBI service over 12 weeks, the results for which were evaluated through UEQ and user feedback. The service reliability for the Cronbach's alpha coefficient greater than 0.7 was achieved using HBI service whereas the stimulation coefficient of the value 0.86 revealed significant effect. We observed an overall novelty of the value 0.88 showing the potential interest of participants.

CONCLUSIONS

The comprehensive HBI has demonstrated positive user experience concerning the stimulation for adapting the healthy behaviors. The HBI service is designed independently to work as a service, so any other wellness management service-enabled platform can consume it to evaluate the healthy behavior index of the person for recommendation generation, behavior indication, and behavior adaptation.

Successful weight loss maintenance: A systematic review of weight control registries

Weight loss maintenance is a major challenge for obesity treatment. Weight control registries can be useful in identifying psychological and behavioural factors that could contribute to better long-term success. The objective of this study is to describe the existing weight control registries and their participants and identify correlates of weight loss maintenance. A comprehensive search of peer-reviewed articles published until November 2018 was conducted in PubMed, Web of Science, and Scopus. Studies that reported results from weight control registries were considered. Fifty-two articles, corresponding to five registries (the United States, Portugal, Germany, Finland, and Greece), were included. Registries differed in inclusion criteria and procedures. Of 51 identified weight loss and maintenance strategies, grouped in 14 domains of the Oxford Food and Activity Behaviors taxonomy, the following were the most frequently reported: having healthy foods available at home, regular breakfast intake, increasing vegetable consumption, decreasing sugary and fatty foods, limiting certain foods, and reducing fat in meals. Increased physical activity was the most consistent positive correlate of weight loss maintenance. To our knowledge, this is the first systematic review of information about successful weight loss maintenance obtained from weight control registries. Key common influential characteristics of success were identified, which can inform future prospective studies and weight management initiatives.

Sex-Specific Physical Activity Patterns Differentiate Weight Loss Maintainers From Regainers: The MedWeight Study

BACKGROUND

Although plenty of evidence indicates that weight loss maintainers are highly physically active, studies focusing on the sex-specific differences in activity levels between maintainers and regainers are scarce. The authors aimed to investigate sex-specific differences in activity patterns in a cohort of Mediterranean maintainers and regainers.

METHODS

Sample includes 756 participants of the MedWeight registry (60.5% women), aged 18-65 years, who lost ≥10% of their initial weight, and either maintained their loss for ≥12 months or regained it. Participants completed a series of questionnaires, including demographics and weight history. Activity levels were evaluated with the International Physical Activity Questionnaire-short version.

RESULTS

Maintainers of both sexes were, in total, more active than their same-sex regainers. When specific activities were considered, women maintainers spent more time walking than regainers (Padjusted = .02), whereas men maintainers spent more time in vigorous activities (Padjusted = .001) and walking than regainers (Padjusted = .001). Modest increments in activity of sex-relevant intensity were associated with increased odds for maintenance.

CONCLUSIONS

Maintainers attained a more active lifestyle than their same-sex regainers, involving more walking for both sexes and more vigorous activities for men. The detected differences, according to activity intensity, support that activity patterns associated with successful weight loss are distinguishable between sexes.

Associations of Objectively Measured Physical Activity and Sleep with Weight Loss Maintenance: A Preliminary Study of Japanese Adults

Maintaining weight loss is considerably more challenging than losing weight. Most previous studies on weight loss maintenance have been conducted in Western countries and have assessed physical activity and sleep with the use of questionnaires. This preliminary study investigated the associations of objectively measured physical activity and sleep with weight loss maintenance among 25 Japanese adults who had intentionally lost ≥ 10% of their original weight. Participants wore tri-axial accelerometers on their waists and sleep monitors on their wrists for two weeks to measure their physical activity and sleep, respectively. A linear regression adjusted for sex, age, maximum weight, and time since losing weight was performed to investigate these associations. Participants had a mean body mass index of 23.4 kg/m² and a median weight loss of 12.5%. Compared to those who maintained < 12.5% weight loss, those who maintained ≥ 12.5% weight loss slept longer (adjusted mean difference: 66.1 min/night, 95% confidence interval (CI): −14.0, 146.3 min/night, p = 0.10) and performed less moderate-to-vigorous physical activity (adjusted mean difference: −21.7 min/day, 95% CI: −58.0, 14.5 min/day, p = 0.22). Though statistical power was limited, sleep behavior may be an important modifiable factor that facilitates weight loss maintenance. Our findings can be used to establish a well-designed study to confirm this association.

Behavioral Predictors of Weight Regain in Postmenopausal Women: Exploratory Results From the Breast Cancer and Exercise Trial in Alberta

OBJECTIVE

This secondary analysis assessed associations between changes in energy balance and sleep behaviors and the risk of weight regain following exercise-induced weight loss.

METHODS

Of 400 participants initially randomized in the Breast Cancer and Exercise Trial in Alberta (BETA), 227 lost weight following the moderate- to vigorous-intensity exercise intervention (-4.2 ± 3.6 kg) and were included in this analysis. Self-reported energy intake (EI), sleep duration, quality and timing, and objective measurements of physical activity (PA) and sedentary time were collected at the end of the intervention and the end of follow-up. Linear regression models assessed associations between changes in these behaviors and risk of weight regain during follow-up.

RESULTS

Participants regained 43% of the weight lost during follow-up. Reductions in moderate to vigorous PA (β = -1.00; 95% CI = -1.74 to -0.25 h/d; P = 0.01) and steps per day (β = -0.0003; 95% CI = -0.0005 to -0.0001 steps/d; P = 0.004); increases in sedentary time (β = 0.54; 95% CI = 0.67 to 1.02 h/d; P = 0.03), EI (β = 0.001; 95% CI = 0.0003 to 0.002 kcal; P = 0.01), and fat intake (β = 0.004; 95% CI = 0.001 to 0.006 kcal; P = 0.002); and delayed sleep timing midpoint (β = 0.02; 95% CI = 0.004 to 0.03 min; P = 0.01) were associated with weight regain during follow-up.

CONCLUSIONS

These exploratory results suggest that reductions in moderate to vigorous PA; increases in EI, fat intake, and sedentary time; and delayed sleep timing midpoint were significantly associated with risk of weight regain.

Mechanisms of weight regain after weight loss - the role of adipose tissue

One of the biggest challenges in the management of obesity is the prevention of weight regain after successful weight loss. Weight regain after weight loss has large interindividual variation. Although many factors probably contribute to this variation, we hypothesize that variability in biological responses associated with weight loss-induced shrinking of subcutaneous adipocytes has an important role. In this Review, we show that weight loss-induced variations in cellular stress, extracellular matrix remodelling, inflammatory responses, adipokine secretion and lipolysis seem to be associated with the amount of weight that is regained after successful weight loss. Weight regain could therefore, at least in part, depend on a combination of these factors. Further research on the causality of these associations could aid the development of effective strategies to prevent weight regain after successful weight loss.

Physical Activity Energy Expenditure and Total Daily Energy Expenditure in Successful Weight Loss Maintainers

OBJECTIVE

The objective of this study was to compare physical activity energy expenditure (PAEE) and total daily energy expenditure (TDEE) in successful weight loss maintainers (WLM) with normal weight controls (NC) and controls with overweight/obesity (OC).

METHODS

Participants were recruited in three groups: WLM (n = 25, BMI 24.1 ± 2.3 kg/m² ; maintaining ≥ 13.6-kg weight loss for ≥ 1 year), NC (n = 27, BMI 23.0 ± 2.0 kg/m² ; similar to current BMI of WLM), and OC (n = 28, BMI 34.3 ± 4.8 kg/m² ; similar to pre-weight loss BMI of WLM). TDEE was measured using the doubly labeled water method. Resting energy expenditure (REE) was measured using indirect calorimetry. PAEE was calculated as (TDEE - [0.1 × TDEE] - REE).

RESULTS

PAEE in WLM (812 ± 268 kcal/d, mean ± SD) was significantly higher compared with that in both NC (621 ± 285 kcal/d, P < 0.01) and OC (637 ± 271 kcal/d, P = 0.02). As a result, TDEE in WLM (2,495 ± 366 kcal/d) was higher compared with that in NC (2,195 ± 521 kcal/d, P = 0.01) but was not significantly different from that in OC (2,573 ± 391 kcal/d).

CONCLUSIONS

The high levels of PAEE and TDEE observed in individuals maintaining a substantial weight loss (-26.2 ± 9.8 kg maintained for 9.0 ± 10.2 years) suggest that this group relies on high levels of energy expended in physical activity to remain in energy balance (and avoid weight regain) at a reduced body weight.

ACTonHEALTH study protocol: promoting psychological flexibility with activity tracker and mHealth tools to foster healthful lifestyle for obesity and other chronic health conditions

Background

Obesity and the state of being overweight are increasing steadily and becoming a global epidemic. Recent research reports 64% of the adult population as overweight in Europe and the USA. The social and economic impacts are increasing, and most of the rehabilitation programs, while effective in the short term, do not produce long-lasting results. An explanatory model from a behavioral perspective can describe the phenomena with the lack of sources of reinforcement related to healthful habits in a daily life context.

Methods/design

A randomized clinical trial combining single-subject studies and a four-arm group design will be conducted to compare the effect of the current standard in obesity treatment to Acceptance and Commitment Therapy (ACT) and wearable technology at different times, before starting intervention, at the end, and at follow-up visits of 3, 6, and 12 months measuring changes over time of physical activity and psychological well-being.

Discussion

The goal of this project, combining ACT and wearable technology, is to develop an effective intervention, efficient and sustainable, which even after discharge can provide adequate contingencies of reinforcement in the natural environment, integrating systematic measurements, continuous feedback, and individualized, values-based objectives. The intervention is aimed to provide a contingent reinforcement for healthful behaviors instead of reinforcing only the achievement of a significant weight loss.

The aim of the project, combining Acceptance and Commitment Therapy and Wearable Technology, is to develop an effective, efficient and sustainable intervention able to provide a contingent reinforcement for healthy behaviors. The intervention is aimed to promote adequate healthy behaviors in the natural environment, integrating systematic measurements, continuous feedback and individualized values-based objectives, instead of reinforcing only the achievement of a significant weight loss.

Trial registration

ClinicalTrials.gov, NCT03351712. Registered on 24 November 2017.

Electronic supplementary material

The online version of this article (10.1186/s13063-018-2968-x) contains supplementary material, which is available to authorized users.

A Pilot Randomized Trial of an Intervention to Enhance the Health-Promoting Effects of Older Adults' Activity Portfolios: The Engaged4Life Program

The purpose of this study was to evaluate the feasibility and outcomes of the Engaged4Life program, an intervention to encourage inactive community-dwelling older adults to embed physical activity, cognitive activity, and social interaction into their everyday lives in contexts that are personally meaningful and natural for them. Fifteen participants were randomized to the intervention group (technology-assisted self-monitoring of daily activity via pedometers and daily tablet-based surveys; psychoeducation + goal-setting via a 3-hour workshop; and peer mentoring via phone 2×/week for 2.5 weeks) and 15 to the control (technology-assisted self-monitoring only). Recruitment was shown to be feasible and efficient, but not able to reach the target for men. Retention rate was 83% and participants manifested high adherence and engagement with the intervention. Though this pilot trial was not powered to demonstrate significant differences between groups, daily steps increased by 431 (11% increase) from baseline to Week 4 for the intervention (p < .05), but decreased by 458 for the control, for a net difference of 889 steps (p < .05). Findings were sustained at Week 8 (p < .01). In a future trial, difficulties in recruiting men, barriers due to the technology-intensive design, and the optimization of secondary outcome measures should be addressed.

Device-measured physical activity data for classification of patients with ventricular arrhythmia events: A pilot investigation

Low levels of physical activity are associated with increased mortality risk, especially in cardiac patients, but most studies are based on self-report. Cardiac implantable electronic devices (CIEDs) offer an opportunity to collect data for longer periods of time. However, there is limited agreement on the best approaches for quantification of activity measures due to the time series nature of the data. We examined physical activity time series data from 235 subjects with CIEDs and at least 365 days of uninterrupted measures. Summary statistics for raw daily physical activity (minutes/day), including statistical moments (e.g., mean, standard deviation, skewness, kurtosis), time series regression coefficients, frequency domain components, and forecasted predicted values, were calculated for each individual, and used to predict occurrence of ventricular tachycardia (VT) events as recorded by the device. In unsupervised analyses using principal component analysis, we found that while certain features tended to cluster near each other, most provided a reasonable spread across activity space without a large degree of redundancy. In supervised analyses, we found several features that were associated with the outcome (P < 0.05) in univariable and multivariable approaches, but few were consistent across models. Using a machine-learning approach in which the data was split into training and testing sets, and models ranging in complexity from simple univariable logistic regression to ensemble decision trees were fit, there was no improvement in classification of risk over naïve methods for any approach. Although standard approaches identified summary features of physical activity data that were correlated with risk of VT, machine-learning approaches found that none of these features provided an improvement in classification. Future studies are needed to explore and validate methods for feature extraction and machine learning in classification of VT risk based on device-measured activity.