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The Effect of Different Types of Monitoring Strategies on Weight Loss: A Randomized Controlled Trial
Obesity
Abstract
Objective:
To determine the effectiveness of various monitoring strategies on weight loss, body composition, blood markers, exercise, and psychosocial indices in adults with overweight and obesity following a 12-month weight loss program.
Methods:
Two hundred fifty adults with BMI ≥ 27 were randomized to brief, monthly, individual consults, daily self-monitoring of weight, self-monitoring of diet using MyFitnessPal, self-monitoring of hunger, or control over 12 months. All groups received diet and exercise advice, and 171 participants (68.4%) remained at 12 months.
Results:
No significant differences in weight, body composition, blood markers, exercise, or eating behavior were apparent between those in the four monitoring groups and the control condition at 12 months (all P ≥ 0.053). Weight differences between groups ranged from -1.1 kg (-3.8 to 1.6) to 2.2 kg (-1.0 to 5.3). However, brief support and hunger training groups reported significantly lower scores for depression (difference [95% CI]: -3.16 [-5.70 to -0.62] and -3.05 [-5.61 to -0.50], respectively) and anxiety (-1.84, [-3.67 to -0.02]) scores than control participants.
Conclusions:
Although adding a monitoring strategy to diet and exercise advice did not further increase weight loss, no adverse effects on eating behavior were observed, and some monitoring strategies may even benefit mental health.
... People following GGE are trained to monitor perceived hunger and glucose levels and to associate symptoms experienced when glucose levels approximate (morning) fasting levels with being physically hungry. Eating according to GGE includes recognizing the symptoms of physical hunger and having preprandial glucose below a personalized threshold, which is computed as the average of 2 consecutive morning preprandial glucose levels [1,5,7,11]. Eating when glucose is below the GGE threshold requires postprandial glucose to return to a fasted state before initiating a subsequent eating event. ...
... In the context of GGE, an optimal glucose threshold would promote glycemic control and weight loss (as needed), and improve insulin sensitivity [8,11]. The future implementation of GGE among people with T2DM will need to take DP into consideration when deriving personalized GGE thresholds. ...
... KMM, ARB, and SMS contributed to the study conceptualization and data collection; NLB, LC, and VV contributed to data processing; MRJ, YL, and SMS contributed to data analysis and interpretation; MFM, DGM, and KMR contributed to data interpretation; MRJ and SMS drafted the manuscript. 11.08.2023. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), ...
Background:
Glucose-guided eating (GGE) improves metabolic markers of chronic disease risk, including insulin resistance, in adults without diabetes. GGE is a timed eating paradigm that relies on experiencing feelings of hunger and having a preprandial glucose level below a personalized threshold computed from 2 consecutive morning fasting glucose levels. The dawn phenomenon (DP), which results in elevated morning preprandial glucose levels, could cause typically derived GGE thresholds to be unacceptable or ineffective among people with type 2 diabetes (T2DM).
Objective:
The aim of this study is to quantify the incidence and day-to-day variability in the magnitude of DP and examine its effect on morning preprandial glucose levels as a preliminary test of the feasibility of GGE in adults with T2DM.
Methods:
Study participants wore a single-blinded Dexcom G6 Pro continuous glucose monitoring (CGM) system for up to 10 days. First and last eating times and any overnight eating were reported using daily surveys over the study duration. DP was expressed as a dichotomous variable at the day level (DP day vs non-DP day) and as a continuous variable reflecting the percent of days DP was experienced on a valid day. A valid day was defined as having no reported overnight eating (between midnight and 6 AM). ∂ Glucose was computed as the difference in nocturnal glucose nadir (between midnight and 6 AM) to morning preprandial glucose levels. ∂ Glucose ≥20 mg/dL constituted a DP day. Using multilevel modeling, we examined the between- and within-person effects of DP on morning preprandial glucose and the effect of evening eating times on DP.
Results:
In total, 21 adults (59% female; 13/21, 62%) with non-insulin-treated T2DM wore a CGM for an average of 10.5 (SD 1.1) days. Twenty out of 21 participants (95%) experienced DP for at least 1 day, with an average of 51% of days (SD 27.2; range 0%-100%). The mean ∂ glucose was 23.7 (SD 13.2) mg/dL. People who experience DP more frequently had a morning preprandial glucose level that was 54.1 (95% CI 17.0-83.9; P<.001) mg/dL higher than those who experienced DP less frequently. For within-person effect, morning preprandial glucose levels were 12.1 (95% CI 6.3-17.8; P=.008) mg/dL higher on a DP day than on a non-DP day. The association between ∂ glucose and preprandial glucose levels was 0.50 (95% CI 0.37-0.60; P<.001). There was no effect of the last eating time on DP.
Conclusions:
DP was experienced by most study participants regardless of last eating times. The magnitude of the within-person effect of DP on morning preprandial glucose levels was meaningful in the context of GGE. Alternative approaches for determining acceptable and effective GGE thresholds for people with T2DM should be explored and evaluated.
... People following GGE are trained to monitor perceived hunger and glucose levels and to associate symptoms experienced when glucose levels approximate (morning) fasting levels with being physically hungry. Eating according to GGE includes recognizing the symptoms of physical hunger and having preprandial glucose below a personalized threshold, which is computed as the average of 2 consecutive morning preprandial glucose levels [1,5,7,11]. Eating when glucose is below the GGE threshold requires postprandial glucose to return to a fasted state before initiating a subsequent eating event. ...
... In the context of GGE, an optimal glucose threshold would promote glycemic control and weight loss (as needed), and improve insulin sensitivity [8,11]. The future implementation of GGE among people with T2DM will need to take DP into consideration when deriving personalized GGE thresholds. ...
... KMM, ARB, and SMS contributed to the study conceptualization and data collection; NLB, LC, and VV contributed to data processing; MRJ, YL, and SMS contributed to data analysis and interpretation; MFM, DGM, and KMR contributed to data interpretation; MRJ and SMS drafted the manuscript. 11.08.2023. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), ...
BACKGROUND
Glucose-guided eating (GGE) improves metabolic markers of chronic disease risk, including insulin resistance, in adults without diabetes. GGE is a timed eating paradigm that relies on experiencing feelings of hunger and having a preprandial glucose level below a personalized threshold computed from 2 consecutive morning fasting glucose levels. The dawn phenomenon (DP), which results in elevated morning preprandial glucose levels, could cause typically derived GGE thresholds to be unacceptable or ineffective among people with type 2 diabetes (T2DM).
OBJECTIVE
The aim of this study is to quantify the incidence and day-to-day variability in the magnitude of DP and examine its effect on morning preprandial glucose levels as a preliminary test of the feasibility of GGE in adults with T2DM.
METHODS
Study participants wore a single-blinded Dexcom G6 Pro continuous glucose monitoring (CGM) system for up to 10 days. First and last eating times and any overnight eating were reported using daily surveys over the study duration. DP was expressed as a dichotomous variable at the day level (DP day vs non-DP day) and as a continuous variable reflecting the percent of days DP was experienced on a valid day. A valid day was defined as having no reported overnight eating (between midnight and 6 AM). ∂ Glucose was computed as the difference in nocturnal glucose nadir (between midnight and 6 AM) to morning preprandial glucose levels. ∂ Glucose ≥20 mg/dL constituted a DP day. Using multilevel modeling, we examined the between- and within-person effects of DP on morning preprandial glucose and the effect of evening eating times on DP.
RESULTS
In total, 21 adults (59% female; 13/21, 62%) with non–insulin-treated T2DM wore a CGM for an average of 10.5 (SD 1.1) days. Twenty out of 21 participants (95%) experienced DP for at least 1 day, with an average of 51% of days (SD 27.2; range 0%-100%). The mean ∂ glucose was 23.7 (SD 13.2) mg/dL. People who experience DP more frequently had a morning preprandial glucose level that was 54.1 (95% CI 17.0-83.9; P <.001) mg/dL higher than those who experienced DP less frequently. For within-person effect, morning preprandial glucose levels were 12.1 (95% CI 6.3-17.8; P =.008) mg/dL higher on a DP day than on a non-DP day. The association between ∂ glucose and preprandial glucose levels was 0.50 (95% CI 0.37-0.60; P <.001). There was no effect of the last eating time on DP.
CONCLUSIONS
DP was experienced by most study participants regardless of last eating times. The magnitude of the within-person effect of DP on morning preprandial glucose levels was meaningful in the context of GGE. Alternative approaches for determining acceptable and effective GGE thresholds for people with T2DM should be explored and evaluated.
... The 30 selected trials were from 2006 ( Byrne et al., 2006 ) to 2020 and undertaken in Australia (number of trials, k = 3) ( Byrne et al., 2006 ;Jospe et al., 2017 ;Vandelanotte et al., 2018 ), Canada ( k = 1) ( Ashe et al., 2015 ), Germany ( k = 1) ( Kempf et al., 2018 ), Japan ( k = 1) ( Nakata et al., 2019 ), Korea ( k = 3) ( Cho et al., 2018 ;Kim et al., 2019 ;Shin et al., 2017 ), Singapore ( k = 1) ( Finkelstein et al., 2016 ), Spain ( k = 1) ( Lugones-Sanchez et al., 2020 ), Sweden ( k = 1) ( Reijonsaari et al., 2012 ), Turkey ( k = 1) ( Gocer et al., 2017 ), the United Kingdom ( k = 2) ( Bentley et al., 2016 ;Biddle et al., 2015 ) and the United States ( k = 15) ( Table 1 ). The trials were two ( k = 15), three ( k = 12), four ( k = 2) ( Finkelstein et al., 2016 ;Shuger et al., 2011 ) and five ( k = 1) ( Jospe et al., 2017 ) armed. ...
... The 30 selected trials were from 2006 ( Byrne et al., 2006 ) to 2020 and undertaken in Australia (number of trials, k = 3) ( Byrne et al., 2006 ;Jospe et al., 2017 ;Vandelanotte et al., 2018 ), Canada ( k = 1) ( Ashe et al., 2015 ), Germany ( k = 1) ( Kempf et al., 2018 ), Japan ( k = 1) ( Nakata et al., 2019 ), Korea ( k = 3) ( Cho et al., 2018 ;Kim et al., 2019 ;Shin et al., 2017 ), Singapore ( k = 1) ( Finkelstein et al., 2016 ), Spain ( k = 1) ( Lugones-Sanchez et al., 2020 ), Sweden ( k = 1) ( Reijonsaari et al., 2012 ), Turkey ( k = 1) ( Gocer et al., 2017 ), the United Kingdom ( k = 2) ( Bentley et al., 2016 ;Biddle et al., 2015 ) and the United States ( k = 15) ( Table 1 ). The trials were two ( k = 15), three ( k = 12), four ( k = 2) ( Finkelstein et al., 2016 ;Shuger et al., 2011 ) and five ( k = 1) ( Jospe et al., 2017 ) armed. Studies were conducted in hospitals ( k = 9) and in the community ( k = 21). ...
... The multivariable meta-regression model revealed that 95% of the variance in effects could be explained by CI = Confidence Interval; I 2 = Heterogeneity; d -Laird = DerSimonian-Laird; m = metre; mmHg = milimeter of mercury; N = sample size; * p < 0.05; * * p < 0.01; * * * p < 0.001; random = random effects model; ref = reference list; MD = mean difference; Z = z -statistics. a ( Cho et al., 2018 ;Gocer et al., 2017 ;Jospe et al., 2017 ;Kempf et al., 2018 ;Kim et al., 2019 ;Pellegrini et al., 2012 ;Rogers et al., 2016 ;Shuger et al., 2011 ). b ( Biddle et al., 2015 ;Chambliss et al., 2011 ;Godino et al., 2019 ;Jakicic et al., 2016 ;Lugones-Sanchez et al., 2020 ;Nakata et al., 2019 ;Shin et al., 2017 ;Shrestha et al., 2013 ;Vandelanotte et al., 2018 ). ...
Background
Globally, overweight and obesity are becoming a growing concern, and wearable technology combined with lifestyle intervention may offer an innovative solution.
Objective
This review aimed to (1) assess the effectiveness of lifestyle interventions delivered by wearable technology in improving weight loss and physical activity among overweight or obese adults and (2) explore the effects of covariates on intervention outcomes.
Design
Systematic review, meta-analysis and meta-regression.
Methods
The criteria for inclusion in the review were that the trial must be a lifestyle modification intervention that utilised wearable technology and had a randomised control design and obese or overweight participants aged 18–64 years. Ten electronic databases were searched from inception to 8 December 2020. The Cochrane Risk of Bias Tool version 1 and Grading of Recommendations, Assessment, Development and Evaluations were adopted to rate risk of bias of individual trials and certainty of evidence, respectively. Stata 16 software was used to conduct the meta-analysis, subgroup analysis and meta-regression analysis.
Results
Thirty trials comprising 5,391 adults from 11 countries were included. Meta-analyses found significant changes in weight (−1.08 kg, 95% confidence interval, CI: −1.88, −0.28), body mass index (−0.36 kg/m², 95% CI: −0.62, −0.09), waist circumference (−1.12 cm, 95% CI: −2.08, −0.16), steps per day (1,243.51 steps, 95% CI: 111.51, 2375.51), steps per day change (456.18 steps, 95% CI: 40.61, 871.76), systolic pressure (−2.57 mmHg, 95% CI: −4.57, −0.56) and diastolic pressure (−2.10 mmHg, 95% CI: −3.43, −0.77). Significant differences were found between subgroups regarding region (Q = 7.35, p = 0.01), lifestyle component (Q = 8.51, p = 0.01) and registration protocol (Q = 20.24, p < 0.01). The multivariable meta-regression model suggested that year of publication (adjusted β = 0.20, 95% CI: 0.07, 0.34, p = 0.003), mean age (adjusted β = −0.94, 95% CI: −0.14, 0.04, p < 0.001) and duration (adjusted β = 0.17, 95% CI: 0.09, 0.25, p < 0.001) had significant effects on the mean difference of weight change.
Discussion
The majority of the certainty of evidence was graded moderate to high, which suggests that interventions utilising wearable technology may improve body mass index, waist circumference and physical activity of participants. These findings may aid in the development of future health interventions. However, the current review was limited to self-selected samples and trials conducted in English.
Registration
PROSPERO Number: CRD42021232871
... Published RCTs of My Fitness Pal are limited and have revealed small, short-term weight loss [30,31]. In one study, My Fitness Pal users achieved weight reductions of 2.2 kg at 12 months, which were not significantly greater than those of control participants [31]. ...
... Published RCTs of My Fitness Pal are limited and have revealed small, short-term weight loss [30,31]. In one study, My Fitness Pal users achieved weight reductions of 2.2 kg at 12 months, which were not significantly greater than those of control participants [31]. Continued engagement with platforms like My Fitness Pal may be an issue, as one study found that application engagement markedly declined after 1 month of follow-up (97% vs 55% participant log-ins at 1 and 2 months, respectively) [30]. ...
... Of the 2 studies reviewed, 1 reported only completers' analyses; attrition ranged from 25 to 32%. When reported, there were no serious adverse events or other harmful effects described with the use of My Fitness Pal [30,31]. ...
Purpose of Review
Comprehensive lifestyle programs are cornerstones of obesity management, but clinician referrals may be limited by program availability. Commercial weight loss programs may be an alternative, but clinicians may be unaware of their efficacy and safety. This review describes the evidence for commercial programs, particularly 12-month weight loss, among individuals with obesity.
Recent Findings
Several programs are concordant with evidence-based recommendations (i.e., lower-calorie diet, increased physical activity, and behavioral strategies). Among the guideline-concordant programs, National Diabetes Prevention Program, WW, Jenny Craig, Medifast, and OPTIFAST have demonstrated 12-month weight loss efficacy and safety. While other programs show promise, more evidence is needed before clinician referral may be recommended.
Summary
Clinical practice guidelines support referrals to commercial weight loss programs that have peer-reviewed evidence to support their efficacy and safety. Clinicians should consider the available evidence, patient preference, and cost when considering referrals to these programs for weight management.
... Twenty studies [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] (Figure 1) addressing the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss were identified, which were conducted in six countries: 12 in the United States [21,23,25,28,31,[33][34][35][37][38][39][40], two in the United Kingdom [24,32], three in Australia [22,26,29], one in New Zealand [27], one in South Korea [30] and one in Finland [36]. Reports were published between 2007 and 2019, and they included studies using the following experimental designs: 17 RCTs [21][22][23][24][25][26][27][28][29][31][32][33][34][35][36][37][38] and three non-RCTs [30,39,40]. ...
... Twenty studies [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] (Figure 1) addressing the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss were identified, which were conducted in six countries: 12 in the United States [21,23,25,28,31,[33][34][35][37][38][39][40], two in the United Kingdom [24,32], three in Australia [22,26,29], one in New Zealand [27], one in South Korea [30] and one in Finland [36]. Reports were published between 2007 and 2019, and they included studies using the following experimental designs: 17 RCTs [21][22][23][24][25][26][27][28][29][31][32][33][34][35][36][37][38] and three non-RCTs [30,39,40]. ...
... Twenty studies [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] (Figure 1) addressing the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss were identified, which were conducted in six countries: 12 in the United States [21,23,25,28,31,[33][34][35][37][38][39][40], two in the United Kingdom [24,32], three in Australia [22,26,29], one in New Zealand [27], one in South Korea [30] and one in Finland [36]. Reports were published between 2007 and 2019, and they included studies using the following experimental designs: 17 RCTs [21][22][23][24][25][26][27][28][29][31][32][33][34][35][36][37][38] and three non-RCTs [30,39,40]. Regarding the characteristics of the included populations, participants were aged between 20.5 and 59.8 years, with sample sizes ranging from 11 to 131 participants in the lifestyle mHealth self-monitoring intervention groups and from six to 133 participants in the control groups. ...
Alongside an increase in obesity, society is experiencing the development of substantial technological advances. Interventions that are easily scalable, such as lifestyle (including diet and physical activity) mobile health (mHealth) self-monitoring, may be highly valuable in the prevention and treatment of excess weight. Thus, the aims of this systematic review and meta-analysis were to estimate the following: (i) the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss and (ii) the adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring. MEDLINE via PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and the Web of Science databases were systematically searched. The DerSimonian and Laird method was used to estimate the effect of and adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss. Twenty studies were included in the systematic review and meta-analysis, yielding a moderate decrease in weight and higher adherence to intervention of behavioral weight management interventions using lifestyle mHealth self-monitoring, which was greater than other interventions. Subgroup analyses showed that smartphones were the most effective mHealth approach to achieve weight management and the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring was more pronounced when compared to usual care and in the short-term (less than six months). Furthermore, behavioral weight management interventions using lifestyle mHealth self-monitoring showed a higher adherence than: (i) recording on paper at any time and (ii) any other intervention at six and twelve months.
... Whether IF and Paleo diets result in weight loss and metabolic improvements in overweight adults without intensive dietetic or other clinical support is uncertain (14)(15)(16). We recently reported no differences in weight, body composition, blood markers, exercise, or eating behavior in a randomized controlled trial investigating how different monitoring strategies influenced weight loss over 1 y (17,18). As part of this trial, participants could choose whether to follow a Mediterranean, IF, or Paleo diet. ...
... The different monitoring strategies were brief support visits (monthly individual meetings where the participant was weighed and had the opportunity to discuss ongoing successes and challenges), daily self-monitoring of body weight (with entry to an online database that displayed a graph over time and monthly e-mails that provided personalized feedback and encouragement), self-monitoring of dietary intake [using the MyFitnessPal app (myfitnesspal.com) daily for the first month and for 1 wk per month for months [2][3][4][5][6][7][8][9][10][11][12], or hunger training (where participants are taught to eat only when blood glucose is below a certain level) (18). As part of the study design, participants were able to choose whether to follow a Mediterranean, IF, or Paleo diet, allowing us to examine how being able to choose which diet to follow affected long-term adherence, dietary intake, and health outcomes. ...
... Following baseline assessments, participants chose whether to follow the Mediterranean diet, IF using the 5:2 method (normal intake for 5 d/wk, markedly reduced energy intake for 2 d/wk) (21), or a modified Paleo diet (22) before being randomly assigned to a monitoring strategy (17,18). These diets were chosen due to their popularity, effectiveness for weight loss, and diversity in macronutrient ratios and protocols. ...
Background:
Intermittent fasting (IF) and Paleolithic (Paleo) diets produce weight loss in controlled trials, but minimal evidence exists regarding long-term efficacy under free-living conditions without intense dietetic support.
Objectives:
This exploratory, observational analysis examined adherence, dietary intake, weight loss, and metabolic outcomes in overweight adults who could choose to follow Mediterranean, IF, or Paleo diets, and standard exercise or high-intensity interval training (HIIT) programs, as part of a 12-mo randomized controlled trial investigating how different monitoring strategies influenced weight loss (control, daily self-weighing, hunger training, diet/exercise app, brief support).
Methods:
A total of 250 overweight [BMI (in kg/m2) ≥27] healthy adults attended an individualized dietary education session (30 min) relevant to their self-selected diet. Dietary intake (3-d weighed diet records), weight, body composition, blood pressure, physical activity (0, 6, and 12 mo), and blood indexes (0 and 12 mo) were assessed. Mean (95% CI) changes from baseline were estimated using regression models. No correction was made for multiple tests.
Results:
Although 54.4% chose IF, 27.2% Mediterranean, and 18.4% Paleo diets originally, only 54% (IF), 57% (Mediterranean), and 35% (Paleo) participants were still following their chosen diet at 12 mo (self-reported). At 12 mo, weight loss was -4.0 kg (95% CI: -5.1, -2.8 kg) in IF, -2.8 kg (-4.4, -1.2 kg) in Mediterranean, and -1.8 kg (-4.0, 0.5 kg) in Paleo participants. Sensitivity analyses showed that, due to substantial dropout, these may be overestimated by ≤1.2 kg, whereas diet adherence increased mean weight loss by 1.1, 1.8, and 0.3 kg, respectively. Reduced systolic blood pressure was observed with IF (-4.9 mm Hg; -7.2, -2.6 mm Hg) and Mediterranean (-5.9 mm Hg; -9.0, -2.7 mm Hg) diets, and reduced glycated hemoglobin with the Mediterranean diet (-0.8 mmol/mol; -1.2, -0.4 mmol/mol). However, the between-group differences in most outcomes were not significant and these comparisons may be confounded due to the nonrandomized design.
Conclusions:
Small differences in metabolic outcomes were apparent in participants following self-selected diets without intensive ongoing dietary support, even though dietary adherence declined rapidly. However, results should be interpreted with caution given the exploratory nature of analyses. This trial was registered with the Australian New Zealand Clinical Trials Registry as ACTRN12615000010594 at https://www.anzctr.org.au.
... The Support Strategies for Whole-Food Diets, Intermittent Fasting and Training (SWIFT) study was a 12-month randomized controlled trial investigating whether the addition of monitoring strategies (face to face contact, selfweighing, dietary monitoring, or monitoring of hunger) to dietary and exercise advice increased weight loss over 12 months compared with the provision of advice alone (23). SWIFT is registered with the Australian New Zealand Clinical Trials Registry (ACTRN12615000010594), and ethical approval was obtained from the University of Otago Human Ethics Committee (H14/024). ...
... All participants provided written informed consent. As a protocol paper (24) and main outcome findings (23) have been published, only relevant details are provided here. ...
... Although we observed very few differences in our exercise groups at baseline, it is possible that differences existed in variables we did not measure. Attrition was relatively high at 31.6% (23), although this is not unusual for lifestyle interventions. Small changes in aerobic fitness may not have been detected because of the use of submaximal estimation of V O 2peak , which was the safest and most pragmatic test for this population, but inherently less accurate than maximal oxygen uptake testing (32,40). ...
Purpose:
Although high-intensity interval training (HIIT) and moderate-intensity continuous exercise have comparable health outcomes in the laboratory setting, effectiveness studies in real-world environments are lacking. The aim of this study was to determine the effectiveness of an unsupervised HIIT programme in overweight/obese adults over 12 months.
Methods:
250 overweight/obese adults could choose HIIT or current exercise guidelines of 30 minutes/day moderate-intensity exercise. HIIT participants received a single training session and were advised to independently perform HIIT 3x/week utilizing a variety of protocols. Mixed models, with a random effect for participant, compared differences in weight, body composition, blood pressure, aerobic fitness, physical activity and blood indices at 12 months, adjusting for relevant baseline variables.
Results:
Forty-two percent (n=104) of eligible participants chose HIIT in preference to current guidelines. At 12 months, there were no differences between exercise groups in weight (adjusted difference HIIT vs conventional; 95% CI: -0.44kg; -2.5, 1.6) or visceral fat (-103cm; -256, 49), although HIIT participants reported greater enjoyment of physical activity (p=0.01). Evidence of adherence to ≥2 sessions/week of unsupervised HIIT (from heart rate monitoring) declined from 60.8% at baseline to 19.6% by 12 months. Participants remaining adherent to HIIT over 12 months (23%) were more likely to be male (67% vs 36%, p=0.03), with greater reductions in weight (-2.7kg; -5.2 -0.2) and visceral fat (-292cm; -483, -101) than non-adherent participants.
Conclusions:
HIIT was well-accepted by overweight adults and opting for HIIT as an alternative to standard exercise recommendations led to no difference in health outcomes after 12 months. While regular participation in unsupervised HIIT declined rapidly, those apparently adherent to regular HIIT demonstrated beneficial weight loss and visceral fat reduction.
Trial registration:
Australian New Zealand Clinical Trials Registry (ACTRN12615000010594) Retrospectively registered.
... At 12 months, no significant differences in weight, body composition, blood markers, exercise, or eating behavior were apparent between those in the four monitoring groups and the control condition, although some monitoring groups reported favourable effects on depression and anxiety. In terms of disordered eating, there was no significant difference in global EDE-Q score compared with the control group at 1 year (16). However, given that previous research has linked selfmonitoring with a change in certain subscales (7,9), a detailed analysis of the EDE-Q subscales is warranted. ...
... This was a secondary outcome analysis of the SWIFT study, a five-arm parallel RCT that examined the effect of different monitoring strategies on weight and health over 12 months (16). As a protocol paper and results for the wider study have been published (15,16), only necessary details will be provided here. ...
... This was a secondary outcome analysis of the SWIFT study, a five-arm parallel RCT that examined the effect of different monitoring strategies on weight and health over 12 months (16). As a protocol paper and results for the wider study have been published (15,16), only necessary details will be provided here. The SWIFT study was approved by the University of Otago Human Ethics Committee (H14/024) and is registered with the Australian New Zealand Clinical Trials Registry ACTRN12615000010594. ...
Objectives
Although monitoring is considered a key component of effective behaviour change, the development of apps has allowed consumers to constantly evaluate their own diet, with little examination of what this might mean for eating behavior. The aim of this study was to investigate whether self‐monitoring of diet using the app MyFitnessPal or daily self‐weighing increases the reported occurrence of eating disorders in adults with overweight/obesity following a weight loss program.
Methods
Two hundred and fifty adults with BMI≥27kg/m² received diet and exercise advice and were randomised to one of four monitoring strategies (daily self‐weighing, MyFitnessPal, brief monthly consults, or self‐monitoring hunger) or control for 12 months. The Eating Disorders Examination Questionnaire (EDE‐Q 6.0) was used to assess eating disorder symptoms and behaviours for the previous 28 days at 0 and 12 months.
Results
There were no significant differences in the global EDE‐Q score or the subscales between those in the four monitoring groups and the control at 12 months (all p≥0.164), nor were there differences in binge eating, self‐induced vomiting, laxative misuse or excessive exercise at 12 months (p≥0.202). The overall prevalence of one or more episodes of binge eating was 53.6% at baseline and 50.6% at 12 months, with no change over time (p=0.662).
Conclusions
There was no evidence that self‐monitoring, including using diet apps like MyFitnessPal or daily self‐weighing, increases the reported occurrence of eating disorder behaviours in adults with overweight/obesity who are trying to lose weight.
... As we had concerns regarding the feasibility of participants being able to restrict food intake to only when blood glucose was this low, we undertook a feasibility study, which demonstrated that adherence to the protocol was greater over two weeks if an individualized blood glucose cut-off was used (determined from fasting blood glucose) [19]. In our subsequent randomized controlled trial (RCT), we examined the efficacy of this modified protocol for producing weight loss over 12 months in conjunction with diet and exercise advice [21]. We observed a similar degree of weight loss as that observed in the previous trial (3.9 vs. 3.5 kg, respectively) [20,21], although our difference did not reach statistical significance. ...
... In our subsequent randomized controlled trial (RCT), we examined the efficacy of this modified protocol for producing weight loss over 12 months in conjunction with diet and exercise advice [21]. We observed a similar degree of weight loss as that observed in the previous trial (3.9 vs. 3.5 kg, respectively) [20,21], although our difference did not reach statistical significance. Regardless, hunger training did produce significantly greater weight loss than other types of monitoring strategies (brief support and diet monitoring) and was rated as a very helpful strategy for weight management by our participants [21]. ...
... We observed a similar degree of weight loss as that observed in the previous trial (3.9 vs. 3.5 kg, respectively) [20,21], although our difference did not reach statistical significance. Regardless, hunger training did produce significantly greater weight loss than other types of monitoring strategies (brief support and diet monitoring) and was rated as a very helpful strategy for weight management by our participants [21]. ...
Monitoring blood glucose prior to eating can teach individuals to eat only when truly hungry, but how adherence to ‘hunger training’ influences weight loss and eating behaviour is uncertain. This exploratory, secondary analysis from a larger randomized controlled trial examined five indices of adherence to ‘hunger training’, chosen a priori, to examine which adherence measure best predicted weight loss over 6 months. We subsequently explored how the best measure of adherence influenced eating behavior in terms of intuitive and emotional eating. Retention was 72% (n = 36/50) at 6 months. Frequency of hunger training booklet entry most strongly predicted weight loss, followed by frequency of blood glucose measurements. Participants who completed at least 60 days of booklet entry (of recommended 63 days) lost 6.8 kg (95% CI: 2.6, 11.0; p < 0.001) more weight than those who completed fewer days. They also had significantly higher intuitive eating scores than those who completed 30 days or less of booklet entry; a difference (95% CI) of 0.73 (0.12, 1.35) in body-food choice congruence and 0.79 (0.06, 1.51) for eating for physical rather than emotional reasons. Adherent participants also reported significantly lower scores for emotional eating of −0.70 (−1.13, −0.27). Following hunger training and focusing on simply recording ratings of hunger on a regular basis can produce clinically significant weight loss and clinically relevant improvements in eating behaviour.
... The problem of overweight and obesity appears to be one of the most urgent problems in many western countries, with a profound impact on quality of life and implications for both physical and mental health [23], as well as significant impacts on worldwide healthcare economic expenditure [24]. It is also a risk factor in several pathologies [25][26][27]. ...
... Significant improvements were also achieved using the mDiabetes APP system [69]. Conversely, Jospe [25], after studying the selfmonitoring of weight and diet using APPs, did not find weight loss or changes in dietary habits; nevertheless, an improvement in the patients' depression and anxiety was observed, showing an enhancement in the psychosocial care of the patients [68]. ...
The rapid evolution of technologies is a key innovation in the organisation and management of physical activities (PA) and sports. The increase in benefits and opportunities related to the adoption of technologies for both the promotion of a healthy lifestyle and the management of chronic diseases is evident. In the field of telehealth, these devices provide personalised recommendations, workout monitoring and injury prevention. The study aimed to provide an overview of the landscape of technology application to PA organised to promote active lifestyles and improve chronic disease management. This review identified specific areas of focus for the selection of articles: the utilisation of mobile APPs and technological devices for enhancing weight loss, improving cardiovascular health, managing diabetes and cancer and preventing osteoporosis and cognitive decline. A multifactorial intervention delivered via mobile APPs, which integrates PA while managing diet or promoting social interaction, is unquestionably more effective than a singular intervention. The main finding related to promoting PA and a healthy lifestyle through app usage is associated with “behaviour change techniques”. Even when individuals stop using the APP, they often maintain the structured or suggested lifestyle habits initially provided by the APP. Various concerns regarding the excessive use of APPs need to be addressed.
... 30,49,50,62 Three trials reported no difference between intervention groups but did not report within group change. 32,40,46 No trials reported increased scores within or between groups. ...
... meta-analysis of nine trials,14,30,37,40,46,49,50,62,72 including 20 intervention arms and with a combined sample size of 929 participants, found a reduction in global eating disorder risk between baseline and post-intervention (Hedges' g = À0.27; 95% CI À0.36, À0.17; ...
This systematic review examined change in eating disorder risk during weight management interventions. Four databases and clinical trials registries were searched in March and May 2022, respectively, to identify behavioral weight management intervention trials in adults with overweight/obesity measuring eating disorder symptoms at pre- and post-intervention or follow-up. Random effects meta-analyses were conducted examining within group change in risk. Of 12,023 screened, 49 were eligible (n = 6337, mean age range 22.1 to 59.9 years, mean (SD) 81(20.4)% female). Interventions ranged from 4 weeks to 18 months, with follow-up of 10 weeks to 36 months post-intervention. There was a within group reduction in global eating disorder scores (20 intervention arms; Hedges' g = -0.27; 95% CI -0.36, -0.17; I2 67.1%) and binge eating (49 intervention arms; -0.66; 95% CI -0.76, -0.56; I2 82.7%) post-intervention, both maintained at follow-up. Of 14 studies reporting prevalence or episodes of binge eating, all reported a reduction. Four studies reported eating disorder symptoms, not present at baseline, in a subset of participants (0%-6.5%). Overall, behavioral weight management interventions do not increase eating disorder symptoms for most adults; indeed, a modest reduction is seen post-intervention and follow-up. A small subset of participants may experience disordered eating; therefore, monitoring for the emergence of symptoms is important.
... A smaller proportion (47%, 26/55) of male users recruited from health and fitness websites described it as, at least, somewhat contributing to disordered eating (Linardon & Messer, 2019). However, in contrast to these cross-sectional studies, an experimental study found no evidence for a causal effect of using MyFitnessPal on eating disorder symptomatology (Jospe et al., 2017(Jospe et al., , 2018. Given the inconsistent results, it is important to explore factors that could influence the nature of these relationships. ...
... Similarly, while no causal effect of MyFitnessPal use on eating disorder symptomatology was detected in the experimental study (Jospe et al., 2018), this finding could be due to the duration (or consistency) of engagement being insufficiently manipulated. Specifically, the participants in the "MyFitnessPal" condition used the application daily for the first month, but for only 1 week of each remaining month in the 12-month period (approximately 15 weeks in total; Jospe et al., 2017). ...
Objective:
Using calorie-counting and fitness-tracking technologies is concerning in relation to eating disorders. While studies in this area typically assess one aspect of use (e.g., frequency), engagement with a device or application is more complex. Consequently, important relationships between the use of these technologies and the eating disorder symptomatology might remain undetected. The current study therefore used comments from online eating disorder-related forums to generate comprehensive qualitative insights into engagement with a popular calorie-counting and fitness-tracking application, MyFitnessPal.
Method:
First, we extracted every comment mentioning MyFitnessPal made on three eating disorder-related forums between May 2015 and January 2018 (1,695 comments from 920 commenters). Then, we conducted an inductive thematic analysis using these comments to identify important aspects of engagement with MyFitnessPal.
Results:
The analyses resulted in three themes: Preventing misuse, describing ways in which MyFitnessPal attempts to prevent pathological use and actions taken by users to circumvent its interventions; Accuracy, outlining distrust of MyFitnessPal's accuracy and ways in which perceived inaccuracy is reduced or compensated for; and Psychosocial factors, comprising cognitive, behavioral, and social factors that influence, or are influenced by, engagement with MyFitnessPal.
Discussion:
The qualitative insights provide a detailed overview of how people with high levels of eating disorder symptomatology likely engage with MyFitnessPal. The insights can be used as a basis to develop valid, quantitative assessment of pathological patterns of engagement with calorie-counting and fitness-tracking technologies. The findings can also provide clinicians with insight into how their patients likely engage with, and are affected by, these devices and applications.
... In comparison with other randomized trials of commercial [28,29,32,[55][56][57][58] or researcher-designed [24,59,60] apps for self-monitoring of diet, GoalTracker's Simultaneous arm tended to have greater adherence to diet tracking, whereas the Sequential arm had lower adherence. Given that most weight loss trials of commercial apps are pilot studies and/or were not powered to detect an effect in weight change between treatment arms [26,28,29,38,56,61], more fully powered studies are needed that examine the efficacy of commercial apps for weight loss. ...
... This design may have greater external validity but may make it harder to detect an effect between arms. Another strength was that the trial had little contamination between arms, which has been a problem in past app-based trials where up to 50% of participants in no-treatment control arms were found to have used commercial apps during the study period [44,55,63]. ...
Background:
Self-monitoring of dietary intake is a valuable component of behavioral weight loss treatment; however, it declines quickly, thereby resulting in suboptimal treatment outcomes.
Objective:
This study aimed to examine a novel behavioral weight loss intervention that aims to attenuate the decline in dietary self-monitoring engagement.
Methods:
GoalTracker was an automated randomized controlled trial. Participants were adults with overweight or obesity (n=105; aged 21-65 years; body mass index, BMI, 25-45 kg/m2) and were randomized to a 12-week stand-alone weight loss intervention using the MyFitnessPal smartphone app for daily self-monitoring of either (1) both weight and diet, with weekly lessons, action plans, and feedback (Simultaneous); (2) weight through week 4, then added diet, with the same behavioral components (Sequential); or (3) only diet (App-Only). All groups received a goal to lose 5% of initial weight by 12 weeks, a tailored calorie goal, and automated in-app reminders. Participants were recruited via online and offline methods. Weight was collected in-person at baseline, 1 month, and 3 months using calibrated scales and via self-report at 6 months. We retrieved objective self-monitoring engagement data from MyFitnessPal using an application programming interface. Engagement was defined as the number of days per week in which tracking occurred, with diet entries counted if ≥800 kcal per day. Other assessment data were collected in-person via online self-report questionnaires.
Results:
At baseline, participants (84/100 female) had a mean age (SD) of 42.7 (11.7) years and a BMI of 31.9 (SD 4.5) kg/m2. One-third (33/100) were from racial or ethnic minority groups. During the trial, 5 participants became ineligible. Of the remaining 100 participants, 84% (84/100) and 76% (76/100) completed the 1-month and 3-month visits, respectively. In intent-to-treat analyses, there was no difference in weight change at 3 months between the Sequential arm (mean -2.7 kg, 95% CI -3.9 to -1.5) and either the App-Only arm (-2.4 kg, -3.7 to -1.2; P=.78) or the Simultaneous arm (-2.8 kg, -4.0 to -1.5; P=.72). The median number of days of self-monitoring diet per week was 1.9 (interquartile range [IQR] 0.3-5.5) in Sequential (once began), 5.3 (IQR 1.8-6.7) in Simultaneous, and 2.9 (IQR 1.2-5.2) in App-Only. Weight was tracked 4.8 (IQR 1.9-6.3) days per week in Sequential and 5.1 (IQR 1.8-6.3) days per week in Simultaneous. Engagement in neither diet nor weight tracking differed between arms.
Conclusions:
Regardless of the order in which diet is tracked, using tailored goals and a commercial mobile app can produce clinically significant weight loss. Stand-alone digital health treatments may be a viable option for those looking for a lower intensity approach.
Trial registration:
ClinicalTrials.gov NCT03254953; https://clinicaltrials.gov/ct2/show/NCT03254953 (Archived by WebCite at http://www.webcitation.org/72PyQrFjn).
... mHealth apps are generally designed for chronically ill people (56%), ltness enthusiasts (33%), and physicians (32%) [4], with users downloading them with the aim to monitor their ltness and track foods as well as to manage chronic conditions [5]. A recent study specilcally evaluating the market of weight management apps in 10 different countries [6] identiled 28,905 unique apps that focus on physical activity (34%); diet (31%); and on tracking exercise, calorie intake, and body weight (23%) [6]. ...
... Despite lacking evidence-based content [6,21], health apps can be used as stand-alone delivery modes in self-directed weight loss interventions [22,23] or as supplemental components of complex interventions. Some studies employing researcher-developed apps [24] or popular calorie counting apps (eg, MyFitnessPal [25,26]) in combination with face-to-face delivery modes showed generally larger effects compared with interventions using the apps as standalone [27][28][29]. ...
Background: Evaluating the quality of mobile health apps for weight loss and weight management is important to understand whether these can be used for obesity prevention and treatment. Recent reviews call for more research on multidimensional aspects of app quality, especially involving end users, as there are already many expert reviews on this domain. However, no quantitative study has investigated how laypersons see popular apps for weight management and perceive different dimensions of app quality.
Objective: This study aimed to explore how laypersons evaluate the quality of 6 free weight management apps (My Diet Coach, SparkPeople, Lark, MyFitnessPal, MyPlate, and My Diet Diary), which achieved the highest quality ratings in a related and recent expert review.
Methods: A user-centered study was conducted with 36 employees of a Lebanese university. Participants enrolled in the study on a rolling basis between October 2016 and March 2017. Participants were randomly assigned an app to use for 2 weeks. App quality was evaluated at the end of the trial period using the Mobile App Rating Scale user version (uMARS). uMARS assesses the dimensions of engagement, functionality, aesthetics, information, and subjective quality on 5-point scales. Internal consistency and interrater agreement were examined. The associations between uMARS scores and users’ demographic characteristics were also explored using nonparametric tests. Analyses were completed in November 2017.
Results: Overall, the 6 apps were of moderately good quality (median uMARS score 3.6, interquartile range [IQR] 0.3). The highest total uMARS scores were achieved by Lark (mean 4.0 [SD 0.5]) and MyPlate (mean 3.8 [SD 0.4]), which also achieved the highest subjective quality scores (Lark: mean 3.3 [SD 1.4]; MyPlate: mean 3.3 [SD 0.8]). Functionality was the domain with the highest rating (median 3.9, IQR 0.3), followed by aesthetics (median 3.7, IQR 0.5), information (median 3.7, IQR 0.1), and engagement (median 3.3, IQR 0.2). Subjective quality was judged low (median 2.5, IQR 0.9). Overall, subjective quality was strongly and positively related (P<.001) with total uMARS score (ρ=.75), engagement (ρ=.68), information, and aesthetics (ρ=.60) but not functionality (ρ=.40; P=.02). Higher engagement scores were reported among healthy (P=.003) and obese individuals (P=.03), who also showed higher total uMARS (P=.04) and subjective quality (P=.05) scores.
Conclusions: Although the apps were considered highly functional, they were relatively weak in engagement and subjective quality scores, indicating a low propensity of using the apps in the future. As engagement was the subdomain most strongly associated with subjective quality, app developers and researchers should focus on creating engaging apps, holding constant the functionality, aesthetics, and information quality. The tested apps (in particular Lark and MyPlate) were perceived as more engaging and of higher quality among healthy, obese individuals, making them a promising mode of delivery for self-directed interventions promoting weight control among the sampled population or in similar and comparable settings.
... Mobile apps started to show some suggestive evidence of effectiveness [18,29], with studies reporting positive effects in weight reduction when apps were employed as a supplement to telephone coaching [30]. However, small, nonsigni_cant effects were reported when apps were used as a standalone tool [31,32]. Smartphones are the ideal platform for delivering self-directed, Just-in-Time Adaptive Interventions (JITAIs), which are treatment programs that, as the name suggests, adapt to the patients' progress, eg, when they attain goals or positively respond to treatment [33]. ...
... Lark has recently been used in an observational study, involving 70 diabetic patients who lost 2.4% of their weight at baseline after about 15 weeks [48]. MyFitnessPal has been utilized in a few weight loss trials, showing some positive effects in weight reduction when employed as a supplement to telephone coaching [30], but small, no signi_cant effects when used as a standalone tool [31,32]. We hypothesize that the use of Lark will be associated with larger, more positive changes in cognitions, behaviors, and anthropometric measures than the other apps. ...
Background: Overweight and obesity have become major health problems globally with more than 1.9 billion overweight adults. In Lebanon, the prevalence of obesity and overweight is 65.4% combined. Risk factors of obesity and overweight are preventable and can be addressed by modifications in the environment and in an individual’s lifestyle. Mobile technologies are increasingly used in behavioral, self-directed weight management interventions, providing users with additional opportunities to attain weight control (weight loss, weight gain prevention, etc). Mobile apps may allow for the delivery of Just-in-Time Adaptive Interventions (JITAIs), which provide support through skill building, emotional support, and instrumental support, following the participants’ progress. A few commercially available apps offer JITAI features, but no studies have tested their efficacy.
Objective: The primary objective of this study is to examine the feasibility of a self-directed weight loss intervention, targeting employees of an academic institution, using a virtual coaching app with JITAI features (Lark) and a self-help calorie-counting app (MyFitnessPal). The secondary objective is to estimate the effects of the intervention on main study outcomes.
Methods: This study is a single-center, parallel, randomized controlled trial with 2 study arms (intervention and control). Participants will be randomly allocated in equal proportions to the intervention (Lark) and control groups (MyFitnessPal). To be eligible for this study, participants must be employed full- or part-time at the university or its medical center, able to read English, have a smartphone, and be interested in controlling their weight. Recruitment strategies entail email invitations, printed posters, and social media postings. We will assess quantitative rates of recruitment, adherence, and retention, self-reported app quality using the user version of the Mobile App Rating Scale. We will also assess changes in weight-related outcomes (absolute weight and waist circumference), behavioral outcomes (physical activity and diet), and cognitive factors (motivation to participate in the trial and to manage weight).
Results: WaznApp was funded in June 2017, and recruitment started in March 2018.
Conclusions: This study will provide information as to whether the selected mobile apps offer a feasible solution for promoting weight management in an academic workplace. The results will inform a larger trial whose results might be replicated in similar workplaces in Lebanon and the Middle East and North Africa region, and will be used as a benchmark for further investigations in other settings and similar target groups.
Trial Registration: ClinicalTrials.gov NCT03321331; https://clinicaltrials.gov/ct2/show/NCT03321331 (Archived by WebCite at http://www.webcitation.org/6ys9NOLo5)
Registered Report Identifier: RR1-10.2196/9793
... Examples of varying adherence definitions are dietary SM defined as "a day that any foods or beverages were logged," PA SM defined as "a day that any steps were recorded," and weight SM as "a day on which at least one weight value was captured" [8,19]. Others have defined adherence as percent of days with recording [20,21]. The significant variability in measuring adherence precludes comparing adherence outcomes across studies. ...
Objective
The SMARTER mobile health (mHealth) weight‐loss trial compared adherence to self‐monitoring (SM) of diet, physical activity (PA), and weight and adherence to study‐prescribed diet and PA goals between SM + feedback (SM + FB) and SM‐only arms over 12 months.
Methods
Participants used digital tools to monitor their dietary intake, PA, and weight. We applied generalized linear mixed modeling to compare patterns of monthly adherence to SM and behavioral goals between groups over time and examine the association of adherence to SM and behavioral goals with ≥5% weight loss.
Results
The sample ( N = 502) was 80% female and 82% White, with a mean (SD) BMI of 33.7 (4.0) kg/m ² . Adherence to SM and fat, calorie, and PA goals declined nonlinearly over time, with the SM + FB group displaying less of a decline compared with the SM‐only group. Higher adherence to diet, PA, and weight SM and to calorie and PA goals was associated with greater odds of achieving ≥5% weight loss. A higher monthly probability of achieving ≥5% weight loss was associated with greater adherence to diet, PA, and weight SM and to calorie and PA goals.
Conclusions
These results suggest that future research should examine the mechanisms underlying tailored FB to improve the effect of FB intervention strategies that can lead to improved weight loss.
... In another study, weight loss over 6 and 12 months was not significantly different between selfmonitoring dietary intake via MyFitnessPal and brief monthly individual (face-to-face) consults. 60 Given that diet-tracking apps such as MyFitnessPal are fairly popular (50 million downloads for Android in 2017), 61 the use of such tools either alone or in addition to other intervention components can be a viable option to enhance weight loss success. Of note, results regarding the effectiveness of traditional food records (paper) compared to technology-assisted methods are inconclusive. ...
Intensive lifestyle interventions are the first-line approach to effectively treat obesity, typically relying on in-person contact between patients and interventionists. However, several barriers exist to in-person obesity treatment, including travel time, cost, scheduling conflicts, and the burden of attending in-person sessions. Remotely delivered interventions aim to overcome these barriers, improve cost-effectiveness, and increase accessibility to behavioral weight loss programs. Mobile health (mHealth) technology can aid communication between interventionists and patients via phone calls, email, text messages, and videoconferencing; and facilitate remote and real-time collection of objective data via smartphone apps, fitness trackers, Internet-connected scales, and other devices. Indeed, mHealth approaches facilitate multi-component interventions that may facilitate adherence and enhance long-term weight management, though the current evidence is limited, particularly for entirely remotely delivered interventions. The integrity and continuity of communication between the patient and interventionist, as well as the interventionist's ability to customize intervention delivery based on mHealth data, appear to be important in remotely delivered interventions. In recent years, Just-In-Time Adaptive Interventions (JITAIs) have more systematically integrated mHealth data into personalized multi-component interventions that aim to maximize efficacy while minimizing resource utilization. This approach offers a framework to move the mHealth field forward and is a worthy area of study.
... mHealth adherence in this study followed a trajectory similar to that observed in other intervention studies using a health app to self-monitor diet, weight, and activity in both rural and urban adults [35,36]. Specifically, adherence waned over the course of the study with sharper declines following the end of the intervention. ...
Background
Mobile health (mHealth) technology using apps or devices to self-manage health behaviors is an effective strategy to improve lifestyle-related health problems such as hypertension, obesity, and diabetes. However, few studies have tested an mHealth intervention with Hispanic/Latino adults, and no studies were found testing mHealth with rural Hispanic/Latino adults, the fastest-growing population in rural areas.
Objective
The purpose of this study was to evaluate the feasibility, usability, and acceptability of an mHealth cardiovascular risk self-management intervention with rural Hispanic/Latino adults.
Methods
A descriptive study using quantitative and qualitative methods was used to evaluate the feasibility, usability, and acceptability of delivering a 12-week mHealth self-management intervention to reduce cardiovascular risk with rural Hispanic/Latino adults who were randomized to 1 of 2 groups. Both groups were asked to use MyFitnessPal to self-monitor daily steps, weight, and calories. The intervention group received support to download, initiate, and troubleshoot technology challenges with MyFitnessPal (Under Armour) and a smart scale, while the enhanced usual care group received only a general recommendation to use MyFitnessPal to support healthy behaviors. The usability of MyFitnessPal and the smart scale was measured using an adapted Health Information Technology Usability EvaluationScale (Health-ITUES). Adherence data in the intervention group (daily steps, weight, and calories) were downloaded from MyFitnessPal. Acceptability was evaluated using semistructured interviews in a subsample (n=5) of intervention group participants.
Results
A sample of 70 eligible participants (enhanced usual care group n=34; intervention group n=36) were enrolled between May and December 2019. The overall attrition was 28% at 12 weeks and 54% at 24 weeks. mHealth usability in the intervention group increased at each time point (6, 12, and 24 weeks). Adherence to self-monitoring using mHealth in the intervention group after week 1 was 55% for steps, 39% for calories, and 35% for weights; at the end of the 12-week intervention, the adherence to self-monitoring was 31% for steps, 11% for weight, and 8% for calories. Spikes in adherence coincided with scheduled in-person study visits. Structured interviews identified common technology challenges including scale and steps not syncing with the app and the need for additional technology support for those with limited mHealth experience.
Conclusions
Recruitment of rural Hispanic/Latino adults into the mHealth study was feasible using provider and participant referrals. The use of MyFitnessPal, the smart scale, and SMS text messages to self-monitor daily steps, weights, and calories was acceptable and feasible if technology support was provided. Future research should evaluate and support participants’ baseline technology skill level, provide training if needed, and use a phone call or SMS text message follow-ups as a strategy to minimize attrition. A wearable device, separate from the smartphone app, is recommended for activity tracking.
... В ряде систематических обзоров была продемонстрирована эффективность мобильных приложений для регуляции рациона [249] и контроля МТ [250][251][252]. Некоторые исследования, в которых использовались известные приложения для подсчета калорий (например, MyFitnessPal) [253,254] в сочетании с режимами очных консультаций, показали в целом больший эффект по сравнению с теми формами, где использовались только приложения [255,256]. ...
The methodological guidelines are developed as a practical document for medical specialists working in the field of preventive medicine, in order to expand and improve the provision of this type of medical service to the adult population. The methodological guidelines include an informational and informative part for medical specialists and a practical part for patients, presented in the format of memos, contain the main sections-healthy nutrition, correction of eating habits, issues of modifying the diet for the main alimentary-dependent risk factors for chronic non-communicable diseases, such as arterial hypertension, obesity, disorders of lipid, carbohydrate and purine metabolism, a decrease in bone mineral density. They are intended for medical specialists working in the field of prevention, for doctors and secondary medical personnel of offices and departments of medical prevention, public health and medical prevention centers, healthy lifestyle specialists, teachers of medical educational institutions, for specialists who develop and implement educational programs for patients, as well as for medical specialists of a therapeutic profile.
... Такие приложения могут применяться как самостоятельно [14,15], так и в качестве дополнительных компонентов медицинских вмешательств. Так, установлено, что использование приложений [16], в том числе популярных приложений для подсчета калорий (например, MyFitnessPal) [17,18], в сочетании с режимом очных консультаций дает больший эффект по сравнению с вмешательствами, использующими только приложения [19,20]. С учетом вышесказанного в условиях многообразия мобильных приложений, в том числе и в сфере контроля и снижения избыточной массы тела, актуальным становится не только специальное изучение рынка таких инструментов, но и проведение их независимой экспертизы (оценки), а также определение целесообразности широкого внедрения цифровых профилактических технологий, потребность в которых продолжает расти. ...
The problem of independent examination of mobile health applications including the control and reduction of excess body weight is extremely relevant in the context of their widespread use. The most popular tool for the comprehensive assessment of mobile applications is the Mobile application rating scale (MARS), which has not yet been used in Russia.
Objective. To assess the Russian-language mobile applications used to control and reduce overweight using MARS.
Material and methods. The research was carried out in several stages: searching for mobile applications in the App Store and Google Play using keywords, establishing their compliance with the inclusion and exclusion criteria, assessing the consistency of expert opinions, and statistical data processing. The mean scores for the studied parameters of the scale were calculated for each application, as well as the mean (M) and standard deviation (SD) for all applications. Correlation analysis between the MARS rating of applications and the rating obtained in the app store according to Spearman was carried out in SPSS 23.0.
Results. Of the 513 applications found by keywords, 25 were selected for MARS assessment. The combined average MARS rating of applications was 3.53 (SD=0.32) with a maximum score of 4.20 to 2.88 points. Average scores for individual parameters ranged from 4.26 (SD=0.30) for functionality to 2.47 (SD=0.44) for informativeness. Differences are noted between MARS peer quality scores and application user ratings. The value of the correlation coefficient between the MARS rating and the user rating (r=0.378) indicates that users in their ratings take into account mainly the technical characteristics of applications.
Conclusion. For the first time in Russia, an expert assessment of mobile applications for monitoring and correcting excess body weight has been carried out. Most apps scored highly in terms of technical parameters, while engagement and informativeness were the weakest metrics in the rated mobile apps.
... One wearable selfmonitoring device currently commercially available, which may have potential for monitoring and modifying dietary intake, is a continuous wearable blood glucose monitoring device . These devices can be used to train individuals in a weight loss program to correctly identify hunger states to determine when to eat (Jospe et al., 2017). While numerous approaches are being explored, wearable and sensor-based methods have not been evaluated on a large scale to demonstrate feasibility of use and effectiveness in improving self-regulation of dietary intake and few are currently commercially available. ...
Objective
The goal of this paper is to provide an overview of the emerging lower-burden mobile dietary self-monitoring approaches and provide a case study highlighting the role that habit formation (regularly logging meals) and burden played in two weight loss interventions examining three different methods of dietary self-monitoring: two lower-burden (wearable device and photo-based) and one higher-burden (standard database app).MethodsA review of the literature of current methods for dietary self-monitoring was conducted. In addition, a case study using data from two different remotely delivered weight loss interventions is presented. Participants (n = 100) were randomly assigned to one of the three mobile diet tracking methods. At 6 weeks, participants were asked seven questions on a Likert scale (1 completely disagree; 7 completely agree) assessing factors such as habit formation (e.g., remembering to use the device).ResultsSeveral emerging methods of dietary self-monitoring are presented. For the case study, the wearable device (5.0 ± 1.81) and photo-based app (4.0 ± 2.24) participants found it more difficult to remember to use their device than did the standard database app (2.35 ± 1.79; p < 0.001) participants, indicating that habit formation was stronger in the Standard App condition than the approaches that were aimed to be of lower burden.Conclusions
Gaining a better understanding of the current and innovative approaches to dietary self-monitoring, as well as considering how burden and habit formation may be influencing sustained engagement could help inform future effective dietary interventions.
... lower restrained, emotional and external eating, unhealthy weight-loss practices, eating disorder symptomatology; higher eating self-efficacy, proactive coping, autonomy) (8)(9)(10)(11)(12)(13)(14) . Evidence from intervention studies further corroborates these positive findings (8,10,(15)(16)(17)(18)(19)(20)(21)(22)(23) , although with respect to weight it seems that internally regulated eating mainly results in weight maintenance and to a lesser extent in weight loss (small effect sizes have been reported (24) ). The impact on energy intake, dietary quality and other physical indicators of health (e.g. ...
Internally regulated eating style, the eating style that is driven by internal bodily sensations of hunger and satiation, is a concept that has received increasing attention in the literature and health practice over the last decades. The various attempts that have been made so far to conceptualize internally regulated eating have taken place independently of one another and each sheds light on only parts of the total picture of what defines internally regulated eating. This has resulted in a literature that is rather fragmented. More importantly, it is not yet clear which are the characteristics that comprise this eating style. In this paper, we identify and describe the full spectrum of these characteristics, namely, sensitivity to internal hunger and satiation signals, self-efficacy in using internal hunger and satiation signals, self-trusting attitude for the regulation of eating, relaxed relationship with food, and tendency to savor the food while eating. With this research, we introduce a common language to the field and we present a new theoretical framework that does justice not just to the full breadth of characteristics that are necessary for the internally regulated eating style but also to the associations between them and the potential mechanisms by which they contribute to this eating style.
... lower restrained, emotional and external eating, unhealthy weight-loss practices, eating disorder symptomatology; higher eating self-efficacy, proactive coping, autonomy) (8)(9)(10)(11)(12)(13)(14) . Evidence from intervention studies further corroborates these positive findings (8,10,(15)(16)(17)(18)(19)(20)(21)(22)(23) , although with respect to weight it seems that internally regulated eating mainly results in weight maintenance and to a lesser extent in weight loss (small effect sizes have been reported (24) ). The impact on energy intake, dietary quality and other physical indicators of health (e.g. ...
The concept of internally regulated eating has been explored along several, distinct research lines. The most prominent are those on intuitive eating, eating competence, and mindful eating, but there are also several independent intervention programs that promote eating by internal hunger and satiation cues (i.e., bodily sensations of hunger and satiation). Although these paradigms have certain key elements in common, they also differ in various respects. As a result, there is no consensus regarding the key features that compose the internally regulated eating style. In the present paper, we synthesize the underlying concepts that bind together the various research lines on internally regulated eating. We do this by delineating the individual-difference characteristics that form the tendency towards engaging in internally regulated eating. These include the sensitivity to and self-efficacy in using internal hunger and satiation signals, a self-trusting attitude for the regulation of eating, a relaxed relationship with food, and the tendency to savor the food while eating. Building on earlier work, we propose an inclusive definition for the internally regulated eating style, we embody this eating style in an existing, well-known model of eating behavior (the boundary model of eating), and we present a comprehensive theoretical framework with its key defining features, antecedents, and consequences, which can be used to drive future research.
... This is an important factor for consideration, especially when body weight was the main outcome investigated. We cannot make causal conclusions about the exercise mode or adherence to exercise and changes in body composition or ''health outcomes'' when the participants received only ''diet and exercise advice'' (2). Indeed, diet and conventional training were ignored in the study flow chart and in the limitations list (1). ...
... To demonstrate how the BIT model applies to mHealth, Mohr and colleagues applied the BIT concepts to MyFitnessPal (2014). This popular fitness app tracks calories and exercise to promote weight loss and has been utilized in several weight loss trials (Jospe et al., 2017;Laing, Mangione, & Tseng, 2014). However, Laing and colleagues (2014) aptly noted that although the utilization of smartphone apps by individuals who are primed to engage in dietary self-monitoring may be useful, the mere introduction of the app is "unlikely to produce substantial weight change in most patients" (p. ...
Utilization of mobile applications in collaborative patient-provider monitoring of chronic health conditions: A theoretical framework to guide the use of mobile applications in collaborative patient-provider monitoring of chronic health conditions
While general health and fitness-related self-service technologies, such as health and fitness apps and wearable activity trackers, are steadily increasing in popularity, there are now increasing reports of the potential harm they can cause to consumer well-being. An overview and analysis of the “dark side” of general health and fitness-related self-service technologies is therefore timely and appropriate. In the present work, the authors systematically identify and review the existing literature on this topic across various disciplinary backgrounds. They summarize available knowledge concerning the potential adverse consequences for consumer well-being resulting from the use of health and fitness apps and wearable devices and propose a conceptual framework to explain the relationship between using such technologies and these negative outcomes. Based on these insights, the authors identify current research gaps concerning the dark side of general health and fitness-related self-service technologies and propose corresponding directions for future research. They also discuss the implications of these findings for marketers and public policy makers.
Objectives
Diabetes is a complex condition that often requires the simultaneous employment of diverse approaches for prevention and treatment. Mindful eating may be a beneficial complementary approach. This narrative review analyzes potential mechanisms of action through which mindful eating may regulate blood glucose and thereby aid in diabetes prevention and management. Findings from this review may serve to inform both clinical practice and new research in the field.
Method
We conducted a narrative review focusing on the meditation-independent mechanisms by which mindful eating could improve blood glucose regulation. Specifically, we analyzed the effects of mindful eating practices on eating behavior, calorie intake, weight control, and/or glucose control.
Results
Evidence suggests that mindful eating can improve eating behaviors by decreasing automatic and disordered eating which, in turn, may regulate blood glucose levels. Moreover, by eating slowly, attentively, and according to hunger and satiety cues, mindful eating may help align energy intake to energy needs, thereby improving weight and glycemic management.
Conclusion
Key mindful eating practices that may directly or indirectly improve glycemic management include eating slowly, eating with deliberate attention to the sensory properties of food, cultivating acceptance of thoughts and feelings concerning food and eating, decentering from food-related thoughts, and relying on hunger and satiety cues to guide eating. Future research may improve our knowledge of these interventions and their application to the prevention and treatment of diabetes.
Personal exercise programmes have long been used and prescribed for weight loss and the improvement of quality of life in obese patients. While individualised programmes are usually the preferred option, they can be more costly and challenging to deliver in person. A move to digital programmes with a wider reach has commenced, and demand has increased due to the SARS-CoV-2 pandemic. In this review, we evaluate the current status of digital exercise programme delivery and its evolution over the past decade, with a focus on personalisation. We used specific keywords to search for articles that met our predetermined inclusion and exclusion criteria in order to provide valuable evidence and insights for future research. We identified 55 studies in total in four key areas of focus, from the more recent development of apps and personal digital assistants to web-based programmes and text or phone call interventions. In summary, we observed that apps may be useful for a low-intensity approach and can improve adherence to programmes through self-monitoring, but they are not always developed in an evidence-based manner. Engagement and adherence are important determinants of weight loss and subsequent weight maintenance. Generally, professional support is required to achieve weight loss goals.
Résumé
L’évolution des technologies de santé connectée dans la prise en charge du surpoids et de l’obésité nécessite de mieux connaître les raisons pour lesquelles certains patients adhèrent et d’autre pas. Les objectifs de cette revue des revues systématiques sont d’examiner comment l’adhésion aux interventions de santé connectée dans la gestion du poids est conceptualisée et d’identifier les facteurs qui influencent l’adhésion et comment ils l’influencent. Sept revues systématiques publiées entre 2010 et 2022 ont été incluses. Les définitions et les mesures de l’adhésion ainsi que les conceptions de l’intervention sont très hétérogènes dans la littérature existante, ce qui rend difficiles les conclusions sur les réels niveaux d’adhésion. Quatre composantes ont été identifiées comme favorisant l’adhésion aux interventions de gestion de poids auprès de patients en situation de surpoids ou d’obésité : (1) l’auto-surveillance dont la facilité et la rapidité d’emploi lui confèrent un bon niveau d’adhésion ; (2) l’entretien motivationnel avec une relation soignant-patient via la vidéo ou le téléphone qui favorise l’adhésion ; (3) la thérapie comportementale demandant surtout des échanges fréquents, au mieux hebdomadaires ; (4) et la personnalisation qui doit être effective tout au long de l’intervention pour rester pertinente au regard des objectifs du patient. Cependant, la complexité des phénomènes impliqués dans l’obésité impose une analyse plus fine de l’adhésion qui ne se focalise pas simplement sur l’outil, mais qui importe également de prendre en considération leurs appropriations dans des contextes variés et donc de l’étudier du point de vue des utilisateurs.
Background
The effectiveness of smartphone apps for weight loss is limited by the diversity of interventions that accompany such apps. This research extends the scope of previous systematic reviews by including 2 subgroup analyses based on nonmobile interventions that accompanied smartphone use and human-based versus passive behavioral interventions.
Objective
The primary objective of this study is to systematically review and perform a meta-analysis of studies that evaluated the effectiveness of smartphone apps on weight loss in the context of other interventions combined with app use. The secondary objective is to measure the impact of different mobile app features on weight loss and mobile app adherence.
Methods
We conducted a systematic review and meta-analysis of relevant studies after an extensive search of the PubMed, MEDLINE, and EBSCO databases from inception to January 31, 2022. Gray literature, such as abstracts and conference proceedings, was included. Working independently, 2 investigators extracted the data from the articles, resolving disagreements by consensus. All randomized controlled trials that used smartphone apps in at least 1 arm for weight loss were included. The weight loss outcome was the change in weight from baseline to the 3- and 6-month periods for each arm. Net change estimates were pooled across the studies using random-effects models to compare the intervention group with the control group. The risk of bias was assessed independently by 2 authors using the Cochrane Collaboration tool for assessing the risk of bias in randomized trials.
Results
Overall, 34 studies were included that evaluated the use of a smartphone app in at least 1 arm. Compared with controls, the use of a smartphone app–based intervention showed a significant weight loss of –1.99 kg (95% CI –2.19 to –1.79 kg; I2=81%) at 3 months and –2.80 kg (95% CI –3.03 to –2.56 kg; I2=91%) at 6 months. In the subgroup analysis, based on the various intervention components that were added to the mobile app, the combination of the mobile app, tracker, and behavioral interventions showed a statistically significant weight loss of –2.09 kg (95% CI –2.32 to –1.86 kg; I2=91%) and –3.77 kg (95% CI –4.05 to –3.49 kg; I2=90%) at 3 and 6 months, respectively. When a behavioral intervention was present, only the combination of the mobile app with intensive behavior coaching or feedback by a human coach showed a statistically significant weight loss of –2.03 kg (95% CI –2.80 to –1.26 kg; I2=83%) and –2.63 kg (95% CI –2.97 to –2.29 kg; I2=91%) at 3 and 6 months, respectively. Neither the type nor the number of mobile app features was associated with weight loss.
Conclusions
Smartphone apps have a role in weight loss management. Nevertheless, the human-based behavioral component remained key to higher weight loss results.
Weight losses >10% favorably modulate biomarkers of breast cancer risk but are not typically achieved by comprehensive weight loss programs, including the Diabetes Prevention Program (DPP). Combining the DPP with hunger training (HT), an evidence-based self-regulation strategy that uses self-monitored glucose levels to guide meal timing, has potential to enhance weight losses and cancer-related biomarkers, if proven feasible. This two-arm randomized controlled trial examined the feasibility of adding HT to the DPP and explored effects on weight and metabolic and breast cancer risk biomarkers. Fifty postmenopausal women [body mass index (BMI) >27 kg/m2)] at risk of breast cancer were randomized to the DPP+HT or DPP-only arm. Both arms followed a 16-week version of the DPP delivered weekly by a trained registered dietitian. Those in the DPP+HT also wore a continuous glucose monitor during weeks 4-6 of the program. Feasibility criteria were accrual rates >50%, retention rates >80%, and adherence to the HT protocol >75%. All a priori feasibility criteria were achieved. The accrual rate was 67%, retention rate was 81%, and adherence to HT was 90%. Weight losses and BMI reductions were significant over time as were changes in metabolic and breast cancer risk biomarkers but did not vary by group. This trial demonstrated that HT was feasible to add to comprehensive weight management program targeted toward postmenopausal women at high risk of breast cancer, though upon preliminary examination it does not appear to enhance weight loss or metabolic changes.
Prevention relevance:
This study found that it was feasible to add a short glucose-guided eating intervention to a comprehensive weight management program targeting postmenopausal women at high risk of breast cancer. However, further development of this novel intervention as a cancer prevention strategy is needed.
Objective
To identify dietary self-monitoring implementation strategies in behavioral weight loss interventions.
Design
We conducted a systematic review of eight databases and examined 59 weight loss intervention studies targeting adults with overweight/obesity that used dietary self-monitoring.
Setting
NA
Participants
NA
Results
We identified self-monitoring implementation characteristics, effectiveness of interventions in supporting weight loss, and examined weight loss outcomes among higher and lower intensity dietary self-monitoring protocols. Included studies utilized diverse self-monitoring formats (paper, website, mobile app, phone) and intensity levels (recording all intake or only certain aspects of diet). We found the majority of studies using high and low intensity self-monitoring strategies demonstrated statistically significant weight loss in intervention groups compared to control groups.
Conclusions
Based on our findings, lower and higher intensity dietary self-monitoring may support weight loss, but variability in adherence measures and limited analysis of weight loss relative to self-monitoring usage limits our understanding of how these methods compare to each other.
Sobrepeso e Obesidade em Adultos
Portaria SCTIE nº 53 - 11/11/2020
This study aimed to systematically review the relationship of obesity-depression in the female sex. We carried out a systematic search (PubMed, MEDLINE, Embase) to quantify the articles (controlled trials and randomized controlled trials) regarding obesity and depression on a female population or a mixed sample. Successively, we established whether the sex specificities were studied by the authors and if they reported on collecting data regarding factors that may contribute to the evolution of obesity and depression and that could be responsible for the greater susceptibility of females to those conditions. After applying the inclusion and exclusion criteria, we found a total of 20 articles with a female sample and 54 articles with a mixed sample. More than half of all articles (51.35%, n = 38) evaluated the relationship between depression and obesity, but only 20 (27.03%) evaluated this relationship among females; still, 80% of those (n = 16) presented supporting results. However, few articles considered confounding factors related to female hormones (12.16%, n = 9) and none of the articles focused on factors responsible for the binomial obesity-depression in the female sex. The resulting articles also supported that depression (and related impairments) influencing obesity (and related impairments) is a two-way road. This systematic review supports the concurrency of obesity-depression in females but also shows how sex specificities are ultimately under-investigated. Female sex specificity is not being actively considered when studying the binomial obesity-depression, even within a female sample. Future studies should focus on trying to understand how the female sex and normal hormonal variations influence these conditions.
Objective
Self‐monitoring is a core component of behavioral obesity treatment, but it is unknown how digital health has been used for self‐monitoring, what engagement rates are achieved in these interventions, and how self‐monitoring and weight loss are related.
Methods
This systematic review examined digital self‐monitoring in behavioral weight loss interventions among adults with overweight or obesity. Six databases (PubMed, Embase, Scopus, PsycInfo, CINAHL, and ProQuest Dissertations & Theses) were searched for randomized controlled trials with interventions ≥ 12 weeks, weight outcomes ≥ 6 months, and outcomes on self‐monitoring engagement and their relationship to weight loss.
Results
Thirty‐nine studies from 2009 to 2019 met inclusion criteria. Among the 67 interventions with digital self‐monitoring, weight was tracked in 72% of them, diet in 81%, and physical activity in 82%. Websites were the most common self‐monitoring modality, followed by mobile applications, wearables, electronic scales, and, finally, text messaging. Few interventions had digital self‐monitoring engagement rates ≥ 75% of days. Rates were higher in digital‐ than in paper‐based arms in 21 out of 34 comparisons and lower in just 2. Interventions with counseling had similar rates to standalone interventions. Greater digital self‐monitoring was linked to weight loss in 74% of occurrences.
Conclusions
Self‐monitoring via digital health is consistently associated with weight loss in behavioral obesity treatment.
Recent advancements in continuous glucose monitoring (CGM) represent a novel and untapped resource to optimize behavior change interventions for the prevention and treatment of type 2 diabetes and obesity. In this chapter, we provide a brief history about CGM and evidence supporting its use, including nontraditional indications (people with type 2 diabetes and nondiabetic populations). We then discuss current applications for CGM as a tool for dietary modification, physical activity behavior change, and weight control as well as insights on the theoretical basis for using CGM as biological feedback to motivate lifestyle behavior change. The chapter concludes with a discussion on the future opportunities for CGM as a wearable lifestyle behavior change tool for the treatment of obesity and diabetes.
Background
Hunger training teaches people to eat according to their appetite using pre-prandial glucose measurement. Previous hunger training interventions used fingerprick blood glucose, however continuous glucose monitoring (CGM) offers a painless and convenient form of glucose monitoring. The aim of this randomised feasibility trial was to compare hunger training using CGM with fingerprick glucose monitoring in terms of adherence to the protocol, acceptability, weight, body composition, HbA1c, psychosocial variables, and the relationship between adherence measures and weight loss.
Methods
40 adults with obesity were randomised to either fingerpricking or scanning with a CGM and followed identical interventions for 6 months, which included 1 month of only eating when glucose was under their individualised glucose cut-off. For months 2–6 participants relied on their sensations of hunger to guide their eating and filled in a booklet.
Results
90% of the fingerpricking group and 85% of the scanning group completed the study. Those using the scanner measured their glucose an extra 1.9 times per day (95% CI 0.9, 2.8, p < 0.001) compared with those testing by fingerprick. Both groups lost similar amounts of weight over 6 months (on average 4 kg), were satisfied with the hunger training program and wanted to measure their glucose again within the next year. There were no differences between groups in terms of intervention acceptability, weight, body composition, HbA1c, eating behaviours, or psychological health. Frequency of glucose testing and booklet entry both predicted a clinically meaningful amount of weight loss.
Conclusions
Either method of measuring glucose is effective for learning to eat according to hunger using the hunger training program. As scanning with a CGM encouraged better adherence to the protocol without sacrificing outcome results, future interventions should consider using this new technology in hunger training programs.
Self-monitoring is a strategy that patients use to manage their chronic disease and chronic disease risk factors. Technological advances such as mobile apps, web-based tracking programs, sensing devices, wearable technologies, and insideable devices enable IT-based self-monitoring (ITSM) for chronic disease management. Since ITSM is multidisciplinary in nature and our understanding is fragmented, a systematic examination of the literature is performed to build a holistic understanding of the phenomenon. We review 159 studies published in 108 journals and conferences between 2006 and 2017. By adapting Affordance Actualization Theory, we develop an overarching framework to organize the existing literature on ITSM for chronic disease management. Four themes emerge: key ITSM functionalities that enable affordances; effects on ITSM system use; effects on the achievement of chronic care goals; and the role of intermediary outcomes. For each theme, we identify what is known, what is unknown, and opportunities for future research. We also discuss cross-theme opportunities for future research where more diverse theoretical perspectives can contribute to our understanding of the phenomenon. This work provides research directions for IS researchers studying ITSM for chronic disease self-management.
Introduction:
For women with an increased breast cancer risk, reducing excess weight and increasing physical activity are believed to be important approaches for reducing their risk. This study tested a weight loss intervention that combined commercially available technology-based self-monitoring tools with individualized phone calls.
Design:
Women were randomized to a weight loss intervention arm (n=36) or a usual care arm (n=18).
Setting/participants:
Participants were women with a BMI ≥ 27.5 kg/m(2) and elevated breast cancer risk recruited from the mammography clinic at the Moores Cancer Center at the University of California San Diego.
Intervention:
Intervention participants used the MyFitnessPal website and phone app to monitor diet and a Fitbit to monitor physical activity. Participants received 12 standardized coaching calls with trained counselors over 6 months. Usual care participants received the U.S. Dietary Guidelines for Americans at baseline and two brief calls over the 6 months.
Main outcome measures:
Weight and accelerometer-measured physical activity were assessed at baseline and 6 months. Data were collected in San Diego, CA, from 2012 to 2014 and analyzed in 2015.
Results:
Participants (n=54) had a mean age of 59.5 (SD=5.6) years, BMI of 31.9 (SD=3.5), and a mean Gail Model score of 2.5 (SD=1.4). At 6 months, intervention participants had lost significantly more weight (4.4 kg vs 0.8 kg, p=0.004) and a greater percentage of starting weight (5.3% vs 1.0%, p=0.005) than usual care participants. Across arms, greater increases in moderate-to-vigorous physical activity resulted in greater weight loss (p=0.01).
Conclusions:
Combining technology-based self-monitoring tools with phone counseling supported weight loss over 6 months in women at increased risk for breast cancer.
The dissemination and implementation of evidence-based behavioral medicine interventions into real world practice has been limited. The purpose of this paper is to discuss specific limitations of current behavioral medicine research within the context of the RE-AIM framework, and potential opportunities to increase public health impact by applying novel intervention designs and data collection approaches. The MOST framework has recently emerged as an alternative approach to development and evaluation that aims to optimize multicomponent behavioral and bio-behavioral interventions. SMART designs, imbedded within the MOST framework, are an approach to optimize adaptive interventions. In addition to innovative design strategies, novel data collection approaches that have the potential to improve the public-health dissemination include mHealth approaches and considering environment as a potential data source. Finally, becoming involved in advocacy via policy related work may help to improve the impact of evidence-based behavioral interventions. Innovative methods, if increasingly implemented, may have the ability to increase the public health impact of evidence-based behavioral interventions to prevent disease.
Many people self-weigh and many interventions addressing weight-related problems such as obesity promote self-weighing. However, while self-weighing has been associated with weight loss, there is mixed evidence regarding the psychological impact of this behaviour. The present review aimed to quantify the relationship between self-weighing and: (i) affect (e.g., anxiety, depression), (ii) psychological functioning (e.g., self-esteem), (iii) body-related attitudes, and (iv) disordered eating. A computerized search of scientific databases in September 2014 and subsequent ancestry and citation searches identified twenty-nine independent tests of the relationship between self-weighing on psychological outcomes. Meta-analysis was used to quantify the size of the association across the tests. Results indicated that there was no association between self-weighing and affect, body-related attitudes, or disordered eating. There was, however, a small-sized negative association between self-weighing and psychological functioning. The age of participants, obesity status, the extent of weight loss, duration of self-weighing, and study design (RCT vs. correlational) were found to influence at least some of the psychological outcomes of self-weighing. The findings suggest that, for the most part, self-weighing is not associated with adverse psychological outcomes. However, in some cases the association between self-weighing and psychological outcomes may be more negative than in others.
Background:
Physical activity plays a critical role in health, including for effective weight maintenance, but adherence to guidelines is often poor. Similarly, although debate continues over whether a "best" diet exists for weight control, meta-analyses suggest little difference in outcomes between diets differing markedly in macronutrient composition, particularly over the longer-term. Thus a more important question is how best to encourage adherence to appropriate lifestyle change. While brief support is effective, it has on-going cost implications. While self-monitoring (weight, diet, physical activity) is a cornerstone of effective weight management, little formal evaluation of the role that self-monitoring technology can play in enhancing adherence to change has occurred to date. People who eat in response to hunger have improved weight control, yet how best to train individuals to recognise when true physical hunger occurs and to limit consumption to those times, requires further study.
Methods/design:
SWIFT (Support strategies for Whole-food diets, Intermittent Fasting, and Training) is a two-year randomised controlled trial in 250 overweight (body mass index of 27 or greater) adults that will examine different ways of supporting people to make appropriate changes to diet and exercise habits for long-term weight control. Participants will be randomised to one of five intervention groups: control, brief support (monthly weigh-ins and meeting), app (use of MyFitnessPal with limited support), daily self-weighing (with brief monthly feedback), or hunger training (four-week programme which trains individuals to only eat when physically hungry) for 24 months. Outcome assessments include weight, waist circumference, body composition (dual-energy x-ray absorptiometry), inflammatory markers, blood lipids, adiponectin and ghrelin, blood pressure, diet (3-day diet records), physical activity (accelerometry) and aerobic fitness, and eating behaviour. SWIFT is powered to detect clinically important differences of 4 kg in body weight and 5 cm in waist circumference. Our pragmatic trial also allows participants to choose one of several dietary (Mediterranean, modified Paleo, intermittent fasting) and exercise (current recommendations, high-intensity interval training) approaches before being randomised to a support strategy.
Discussion:
SWIFT will compare four different ways of supporting overweight adults to lose weight while following a diet and exercise plan of their choice, an aspect we believe will enhance adherence and thus success with weight management.
Trial registration:
Australian and New Zealand Clinical Trials Registry ACTRN12615000010594 . Registered 8(th) January 2015.
"Hunger training", which aims to teach people to eat only when blood glucose is below a set target, appears promising as a weight loss strategy. As the ability of participants to adhere to the rigorous protocol has been insufficiently described, we sought to determine the feasibility of hunger training, in terms of retention in the study, adherence to measuring blood glucose, and eating only when blood glucose concentrations are below a set level of 4.7 mmol/L.
We undertook a two-week feasibility study, utilising an adaptive design approach where the specific blood glucose cut-off was the adaptive feature. A blood glucose cut-off of 4.7 mmol/L (protocol A) was used for the first 20 participants. A priori we decided that if interim analysis revealed that this cut-off did not meet our feasibility criteria, the remaining ten participants would use an individualised cut-off based on their fasting glucose concentrations (protocol B).
Retention of the participants in the study was 97 % (28/29 participants), achieving our criterion of 85 %. Participants measured their blood glucose before 94 % (95 % CI 91, 98) of eating occasions (criterion 80 %). However, participants following protocol A, which used a standard blood glucose cut-off of 4.7 mmol/L, were only able to adhere to eating when blood glucose was below the prescribed level 66 % of the time, below our within-person criterion of 75 %. By contrast, those participants following protocol B (individualised cut-off) adhered to the eating protocol 84 % of the time, a significant (p = 0.010) improvement over protocol A.
Hunger training appears to be a feasible method, at least in the short-term, when an individualised fasting blood glucose is used to indicate that a meal can begin.
Background
People who are prescribed self administered medications typically take only about half their prescribed doses. Efforts to assist patients with adherence to medications might improve the benefits of prescribed medications.
Objectives
The primary objective of this review is to assess the effects of interventions intended to enhance patient adherence to prescribed medications for medical conditions, on both medication adherence and clinical outcomes.
Search methods
We updated searches of The Cochrane Library, including CENTRAL (via http://onlinelibrary.wiley.com/cochranelibrary/search/), MEDLINE, EMBASE, PsycINFO (all via Ovid), CINAHL (via EBSCO), and Sociological Abstracts (via ProQuest) on 11 January 2013 with no language restriction. We also reviewed bibliographies in articles on patient adherence, and contacted authors of relevant original and review articles.
Selection criteria
We included unconfounded RCTs of interventions to improve adherence with prescribed medications, measuring both medication adherence and clinical outcome, with at least 80% follow-up of each group studied and, for long-term treatments, at least six months follow-up for studies with positive findings at earlier time points.
Data collection and analysis
Two review authors independently extracted all data and a third author resolved disagreements. The studies differed widely according to medical condition, patient population, intervention, measures of adherence, and clinical outcomes. Pooling results according to one of these characteristics still leaves highly heterogeneous groups, and we could not justify meta-analysis. Instead, we conducted a qualitative analysis with a focus on the RCTs with the lowest risk of bias for study design and the primary clinical outcome.
Main results
The present update included 109 new RCTs published since the previous update in January 2007, bringing the total number of RCTs to 182; we found five RCTs from the previous update to be ineligible and excluded them. Studies were heterogeneous for patients, medical problems, treatment regimens, adherence interventions, and adherence and clinical outcome measurements, and most had high risk of bias. The main changes in comparison with the previous update include that we now: 1) report a lack of convincing evidence also specifically among the studies with the lowest risk of bias; 2) do not try to classify studies according to intervention type any more, due to the large heterogeneity; 3) make our database available for collaboration on sub-analyses, in acknowledgement of the need to make collective advancement in this difficult field of research. Of all 182 RCTs, 17 had the lowest risk of bias for study design features and their primary clinical outcome, 11 from the present update and six from the previous update. The RCTs at lowest risk of bias generally involved complex interventions with multiple components, trying to overcome barriers to adherence by means of tailored ongoing support from allied health professionals such as pharmacists, who often delivered intense education, counseling (including motivational interviewing or cognitive behavioral therapy by professionals) or daily treatment support (or both), and sometimes additional support from family or peers. Only five of these RCTs reported improvements in both adherence and clinical outcomes, and no common intervention characteristics were apparent. Even the most effective interventions did not lead to large improvements in adherence or clinical outcomes.
Authors' conclusions
Across the body of evidence, effects were inconsistent from study to study, and only a minority of lowest risk of bias RCTs improved both adherence and clinical outcomes. Current methods of improving medication adherence for chronic health problems are mostly complex and not very effective, so that the full benefits of treatment cannot be realized. The research in this field needs advances, including improved design of feasible long-term interventions, objective adherence measures, and sufficient study power to detect improvements in patient-important clinical outcomes. By making our comprehensive database available for sharing we hope to contribute to achieving these advances.
Background: There is a need to find simple cost effective weight loss interventions that can be used in primary
care. There is evidence that self-monitoring is an effective intervention for problem drinking and self-weighing
might be an effective intervention for weight loss.
Purpose: To examine the efficacy of daily self-weighing as an intervention for weight loss.
Methods: A randomised controlled trial of 183 obese adults, follow-up three months. The intervention group were given a set of weighing scales and instructed to weigh themselves daily and record their weight. Both groups received two weight loss consultations which were known to be ineffective.
Results: 92 participants were randomised to the intervention group and 91 to the control group. The intervention
group lost 0.5 kg (95% CI 0.3 to 1.3 kg) more than the control group, but this was not significant. There was no
evidence that self-weighing frequency was associated with more weight loss.
Conclusions: As an intervention for weight loss, instruction to weigh daily is ineffective. Unlike other studies, there was no evidence that greater frequency of self-weighing is associated with greater weight loss.
Trial registration: ISRCTN05815264
Keywords: Weight loss, Obesity, Self-weighing, Self-monitoring
Background/objectives:
Short-term studies have suggested beneficial effects of a Palaeolithic-type diet (PD) on body weight and metabolic balance. We now report the long-term effects of a PD on anthropometric measurements and metabolic balance in obese postmenopausal women, in comparison with a diet according to the Nordic Nutrition Recommendations (NNR).
Subjects/methods:
Seventy obese postmenopausal women (mean age 60 years, body mass index 33 kg/m(2)) were assigned to an ad libitum PD or NNR diet in a 2-year randomized controlled trial. The primary outcome was change in fat mass as measured by dual-energy X-ray absorptiometry.
Results:
Both groups significantly decreased total fat mass at 6 months (-6.5 and-2.6 kg) and 24 months (-4.6 and-2.9 kg), with a more pronounced fat loss in the PD group at 6 months (P<0.001) but not at 24 months (P=0.095). Waist circumference and sagittal diameter also decreased in both the groups, with a more pronounced decrease in the PD group at 6 months (-11.1 vs-5.8 cm, P=0.001 and-3.7 vs-2.0 cm, P<0.001, respectively). Triglyceride levels decreased significantly more at 6 and 24 months in the PD group than in the NNR group (P<0.001 and P=0.004). Nitrogen excretion did not differ between the groups.
Conclusions:
A PD has greater beneficial effects vs an NNR diet regarding fat mass, abdominal obesity and triglyceride levels in obese postmenopausal women; effects not sustained for anthropometric measurements at 24 months. Adherence to protein intake was poor in the PD group. The long-term consequences of these changes remain to be studied.
Objective:
To determine whether daily self-weighing (DSW) is associated with disordered eating (DE) symptoms within an adult lifestyle intervention (LI), and to examine changes in DE symptoms during the 18-month trial.
Method:
One-hundred and seventy-eight adults (53% female, 90% White, 52.0 ± 8.6 years, BMI = 35.0 ± 4.4 kg/m2) were enrolled in a randomized trial testing 2 dietary prescriptions within a LI (standard vs. limited dietary variety). Both arms were taught DSW and had the same contact schedule and calorie and activity goals. Frequency of weighing and DE were assessed at 0, 6, 12, and 18 months. Analyses controlled for treatment arm.
Results:
At baseline, 16.3% of participants reported weighing ≥ daily compared with 83.7%, 72.3%, and 68.2% at 6, 12, and 18 months, respectively. There was no relationship between change in frequency of self-weighing and change in DE symptoms at any time point. Further, there were no significant differences between those who weighed ≥ daily versus < daily on DE composite scores at baseline or 6 months; at 12 and 18 months participants who weighed ≥ daily reported lower DE scores compared with those who weighed < daily (p = .008 and .043 at 12 and 18 months, respectively). Participants who weighed ≥ daily achieved better weight losses than those weighing < daily at 12 and 18 months (p = .003 and <.001). There was a significant reduction over time in DE symptoms (p < .0001) and a reduction in odds of meeting criteria for Binge Eating Disorder (BED; ps < .001).
Conclusions:
Daily self-weighing did not appear to be related to increased disordered eating behavior and was associated with better weight loss outcomes.
The 21-item Intuitive Eating Scale (IES; Tylka, 2006) measures individuals' tendency to follow their physical hunger and satiety cues when determining when, what, and how much to eat. While its scores have demonstrated reliability and validity with college women, the IES-2 was developed to improve upon the original version. Specifically, we added 17 positively scored items to the original IES items (which were predominantly negatively scored), integrated an additional component of intuitive eating (Body-Food Choice Congruence), and evaluated its psychometric properties with 1,405 women and 1,195 men across three studies. After we deleted 15 items (due to low item-factor loadings, high cross-loadings, and redundant content), the results supported the psychometric properties of the IES-2 with women and men. The final 23-item IES-2 contained 11 original items and 12 added items. Exploratory and second-order confirmatory factor analyses upheld its hypothesized 4-factor structure (its original 3 factors, plus Body-Food Choice Congruence) and a higher order factor. The IES-2 was largely invariant across sex, although negligible differences on 1 factor loading and 2 item intercepts were detected. Demonstrating validity, the IES-2 total scores and most IES-2 subscale scores were (a) positively related to body appreciation, self-esteem, and satisfaction with life; (b) inversely related to eating disorder symptomatology, poor interoceptive awareness, body surveillance, body shame, body mass index, and internalization of media appearance ideals; and (c) negligibly related to social desirability. IES-2 scores also garnered incremental validity by predicting psychological well-being above and beyond eating disorder symptomatology. The IES-2's applications for empirical research and clinical work are discussed. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
In the US, 34% of adults currently meet the criteria for the metabolic syndrome defined by elevated waist circumference, plasma triglycerides (TG), fasting glucose and/or blood pressure, and decreased high-density lipoprotein cholesterol (HDL-C). While these cardiometabolic risk factors can be treated with medication, lifestyle modification is strongly recommended as a first-line approach. The purpose of this review is to focus on the effect of physical activity interventions and, specifically, on the potential benefits of incorporating higher intensity exercise. Several recent studies have suggested that compared with continuous moderate exercise (CME), high-intensity interval training (HIT) may result in a superior or equal improvement in fitness and cardiovascular health. HIT is comprised of brief periods of high-intensity exercise interposed with recovery periods at a lower intensity. The premise of using HIT in both healthy and clinical populations is that the vigorous activity segments promote greater adaptations via increased cellular stress, yet their short length, and the ensuing recovery intervals, allow even untrained individuals to work harder than would otherwise be possible at steady-state intensity. In this review, we examine the impact of HIT on cardiometabolic risk factors, anthropometric measures of obesity and cardiovascular fitness in both healthy and clinical populations with cardiovascular and metabolic disease. The effects of HIT versus CME on health outcomes were compared in 14 of the 24 studies featuring HIT. Exercise programmes ranged from 2 weeks to 6 months. All 17 studies that measured aerobic fitness and all seven studies that measured insulin sensitivity showed significant improvement in response to HIT, although these changes did not always exceed responses to CME comparison groups. A minimum duration of 12 weeks was necessary to demonstrate improvement in fasting glucose in four of seven studies (57%). A minimum duration of 8 weeks of HIT was necessary to demonstrate improvement in HDL-C in three of ten studies (30%). No studies reported that HIT resulted in improvement of total cholesterol, low-density lipoprotein cholesterol (LDL-C), or TG. At least 12 weeks of HIT was required for reduction in blood pressure to emerge in five studies of participants not already being treated for hypertension. A minimum duration of 12 weeks was necessary to see consistent improvement in the six studies that examined anthropometric measures of obesity in overweight/obese individuals. In the 13 studies with a matched-exercise-volume CME group, improvement in aerobic fitness in response to HIT was equal to (5 studies), or greater than (8 studies) in response to CME. Additionally, HIT has been shown to be safe and effective in patients with a range of cardiac and metabolic dysfunction. In conclusion, HIT appears to promote superior improvements in aerobic fitness and similar improvements in some cardiometabolic risk factors in comparison to CME, when performed by healthy subjects or clinical patients for at least 8-12 weeks. Future studies need to address compliance and efficacy of HIT in the real world with a variety of populations.
Calls for primary care providers (PCPs) to offer obese patients behavioral weight-loss counseling have not been accompanied by adequate guidance on how such care could be delivered. This randomized trial compared weight loss during a 2-year period in response to three lifestyle interventions, all delivered by PCPs in collaboration with auxiliary health professionals (lifestyle coaches) in their practices.
We randomly assigned 390 obese adults in six primary care practices to one of three types of intervention: usual care, consisting of quarterly PCP visits that included education about weight management; brief lifestyle counseling, consisting of quarterly PCP visits combined with brief monthly sessions with lifestyle coaches who instructed participants about behavioral weight control; or enhanced brief lifestyle counseling, which provided the same care as described for the previous intervention but included meal replacements or weight-loss medication (orlistat or sibutramine), chosen by the participants in consultation with the PCPs, to potentially increase weight loss.
Of the 390 participants, 86% completed the 2-year trial, at which time, the mean (±SE) weight loss with usual care, brief lifestyle counseling, and enhanced brief lifestyle counseling was 1.7±0.7, 2.9±0.7, and 4.6±0.7 kg, respectively. Initial weight decreased at least 5% in 21.5%, 26.0%, and 34.9% of the participants in the three groups, respectively. Enhanced lifestyle counseling was superior to usual care on both these measures of success (P=0.003 and P=0.02, respectively), with no other significant differences among the groups. The benefits of enhanced lifestyle counseling remained even after participants given sibutramine were excluded from the analyses. There were no significant differences between the intervention groups in the occurrence of serious adverse events.
Enhanced weight-loss counseling helps about one third of obese patients achieve long-term, clinically meaningful weight loss. (Funded by the National Heart, Lung, and Blood Institute; POWER-UP ClinicalTrials.gov number, NCT00826774.).
Self-monitoring is the centerpiece of behavioral weight loss intervention programs. This article presents a systematic review of the literature on three components of self-monitoring in behavioral weight loss studies: diet, exercise, and self-weighing. This review included articles that were published between 1993 and 2009 that reported on the relationship between weight loss and these self-monitoring strategies. Of the 22 studies identified, 15 focused on dietary self-monitoring, one on self-monitoring exercise, and six on self-weighing. A wide array of methods was used to perform self-monitoring; the paper diary was used most often. Adherence to self-monitoring was reported most frequently as the number of diaries completed or the frequency of log-ins or reported weights. The use of technology, which included the Internet, personal digital assistants, and electronic digital scales were reported in five studies. Descriptive designs were used in the earlier studies whereas more recent reports involved prospective studies and randomized trials that examined the effect of self-monitoring on weight loss. A significant association between self-monitoring and weight loss was consistently found; however, the level of evidence was weak because of methodologic limitations. The most significant limitations of the reviewed studies were the homogenous samples and reliance on self-report. In all but two studies, the samples were predominantly white and women. This review highlights the need for studies in more diverse populations, for objective measures of adherence to self-monitoring, and for studies that establish the required dose of self-monitoring for successful outcomes.
Cognitive behavioral therapy (CBT) is the leading evidence-based treatment for bulimia nervosa. A new "enhanced" version of the treatment appears to be more potent and has the added advantage of being suitable for all eating disorders, including anorexia nervosa and eating disorder not otherwise specified. This article reviews the evidence supporting CBT in the treatment of eating disorders and provides an account of the "transdiagnostic" theory that underpins the enhanced form of the treatment. It ends with an outline of the treatment's main strategies and procedures.
Dietary restraint is largely unsuccessful for controlling obesity. As an alternative, subjects can easily be trained to reliably recognize sensations of initial hunger (IH) a set of physiological sensations which emerge spontaneously, not necessarily at planned mealtimes, and may be the afferent arm of a homeostatic system of food intake regulation. Previously we have reported that IH is associated with blood glucose concentration (BG) below 81.8 mg/dL (4.55 mmol/l), (low blood glucose, LBG), and that a pattern of meals in which IH is present pre-meal (IHMP) improved insulin sensitivity, HbA1c and other cardiovascular risk factors. Here we report the effect upon weight in overweight and normal weight subjects.
To investigate whether the IHMP is associated with sustained loss of weight in overweight subjects over a 5 month period.
Seventy four overweight subjects (OW: BMI > 25) and 107 normal weight (NW) subjects were randomly allocated to either trained (OW: N = 51; NW N = 79) or control (OW: N = 23; NW: N = 28) groups. All subjects were allocated post-randomization into either low or high mean pre-meal BG groups (LBG and HBG groups) using a demarcation point of 81.8 mg/dL.
A significant longitudinal decrease was found in body weight (trained NW: -2.5 ± 4.6 kg; OW -6.7 ± 4.5 kg; controls: NW +3.5 ± 4.0 kg and OW -3.4 ± 4.0 kg; P = 0.006 and 0.029) and in energy intake, mean BG, standard deviation of diary BG (BG as recorded by subjects' 7-day diary), BMI, and arm and leg skin-fold thickness in (OW and NW) HBG subjects. OW LBG subjects significantly decreased body weight (trained: -4.0 ± 2.4 kg; controls: -0.4 ± 3.7 kg; P = 0.037). 26 NW LBG subjects showed no longitudinal difference after training as did 9 control subjects.
Over a 5 month period the IHMP resulted in significant loss of weight in OW subjects compared to controls practicing dietary restraint. NW subjects maintained weight overall, however NW HBG subjects also lost weight compared to controls.
Meta-analyses of behavior change (BC) interventions typically find large heterogeneity in effectiveness and small effects. This study aimed to assess the effectiveness of active BC interventions designed to promote physical activity and healthy eating and investigate whether theoretically specified BC techniques improve outcome.
Interventions, evaluated in experimental or quasi-experimental studies, using behavioral and/or cognitive techniques to increase physical activity and healthy eating in adults, were systematically reviewed. Intervention content was reliably classified into 26 BC techniques and the effects of individual techniques, and of a theoretically derived combination of self-regulation techniques, were assessed using meta-regression.
Valid outcomes of physical activity and healthy eating.
The 122 evaluations (N = 44,747) produced an overall pooled effect size of 0.31 (95% confidence interval = 0.26 to 0.36, I(2) = 69%). The technique, "self-monitoring," explained the greatest amount of among-study heterogeneity (13%). Interventions that combined self-monitoring with at least one other technique derived from control theory were significantly more effective than the other interventions (0.42 vs. 0.26).
Classifying interventions according to component techniques and theoretically derived technique combinations and conducting meta-regression enabled identification of effective components of interventions designed to increase physical activity and healthy eating.
Weight regain often occurs after weight loss in overweight individuals. We aimed to compare the effectiveness of 2 support programs and 2 diets of different macronutrient compositions intended to facilitate long-term weight maintenance.
Using a 2 x 2 factorial design, we randomly assigned 200 women who had lost 5% or more of their initial body weight to an intensive support program (implemented by nutrition and activity specialists) or to an inexpensive nurse-led program (involving "weigh-ins" and encouragement) that included advice about high-carbohydrate diets or relatively high-monounsaturated-fat diets.
In total, 174 (87%) participants were followed-up for 2 years. The average weight loss (about 2 kg) did not differ between those in the support programs (0.1 kg, 95% confidence interval [CI] -1.8 to 1.9, p = 0.95) or diets (0.7 kg, 95% CI -1.1 to 2.4, p = 0.46). Total and low-density lipoprotein (LDL) cholesterol levels were significantly higher among those on the high-monounsaturated-fat diet (total cholesterol: 0.17 mmol/L, 95% CI 0.01 to 0.33; p = 0.040; LDL cholesterol: 0.16 mmol/L, 95% CI 0.01 to 0.31; p = 0.039) than among those on the high-carbohydrate diet. Those on the high-monounsaturated-fat diet also had significantly higher intakes of total fat (5% total energy, 95% CI 3% to 6%, p < 0.001) and saturated fat (2% total energy, 95% CI 1% to 2%, p < 0.001). All of the other clinical and laboratory measures were similar among those in the support programs and diets.
A relatively inexpensive program involving nurse support is as effective as a more resource-intensive program for weight maintenance over a 2-year period. Diets of different macronutrient composition produced comparable beneficial effects in terms of weight loss maintenance.
To determine the feasibility of recruiting and retaining young adults in a brief behavioral weight loss intervention tailored for this age group, and to assess the preliminary efficacy of an intervention that emphasizes daily self-weighing within the context of a self-regulation model.
Forty young adults (29.1 +/- 3.9 years, range 21-35, average BMI of 33.36 +/- 3.4) were randomized to one of two brief behavioral weight loss interventions: behavioral self-regulation (BSR) or adapted standard behavioral treatment (SBT). Assessments were conducted at baseline, post-treatment (10 weeks), and follow-up (20 weeks). Intent to treat analyses were conducted using general linear modeling in SPSS version 14.0.
Participants in both groups attended an average of 8.7 out of 10 group meetings, and retention rates were 93% and 88% for post-treatment and follow-up assessments, respectively. Both groups achieved significant weight losses at post-treatment (BSR = -6.4 kg (4.0); SBT = -6.2 kg (4.5) and follow-up (BSR = -6.6 kg (5.5); SBT = -5.8 kg (5.2), p < .001; but the interaction of group x time was not statistically significant, p = .84. Across groups, there was a positive association between frequency of weighing at follow-up and overall weight change at follow-up (p = .01). Daily weighing was not associated with any adverse changes in psychological symptoms.
Young adults can be recruited and retained in a behavioral weight loss program tailored to their needs, and significant weight losses can be achieved and maintained through this brief intervention. Future research on the longer-term efficacy of a self-regulation approach using daily self-weighing for weight loss in this age group is warranted.
# NCT00488228.
Maximal oxygen uptake (VO2max) is an important indicator of health-risk status, specifically for coronary heart disease (Blair et al., 1989). Direct measurement of VO2max is considered to be the most accurate means of determining cardiovascular fitness level. Typically, this measurement is taken using a progressive exercise test on a treadmill or cycle ergometer. Unfortunately, this test is costly and time consuming and requires a well equipped laboratory, highly trained personnel, and for some populations medical supervision. Therefore, submaximal exercise test protocols that predict VO2max have been developed (Astrand & Rhyming, 1954; Fitchett, 1985). These tests require less equipment, time and are easily administered without highly skilled personnel.
To study the phenomenon that obese subjects show considerable individual variability in their reported relationships between eating and sensations of hunger and fullness.
A laboratory study of the relationship between eating behaviour traits and the episodic oscillations in sensations of hunger and fullness in response to obligatory, fixed energy breakfast (481 kcal) and lunch (675 kcal) meals.
Obese subjects were divided into two groups based on their responses to four 'screening' questions associated with their habitual experience of hunger and fullness sensations before and after eating: those who experienced sensations of hunger and fullness related to eating (Related-R; n=20, body mass index (BMI)=42.4 kg/m(2)) and those for whom eating was not related to hunger or fullness sensations (Unrelated - UR; n=19, BMI=41.3 kg/m(2)). In addition, a control, lean group (Control - C; n=14, BMI=22.6 kg/m(2)) who experienced sensations of hunger and fullness related to eating was studied.
The Three-Factor Eating Questionnaire (TFEQ) was used to measure the eating behaviour traits, disinhibition, restraint and hunger. Profiles of subjective appetite sensations were continuously monitored across the day using visual analogue scales.
All groups displayed clear meal-related oscillations in subjective sensations of hunger, fullness, desire to eat and prospective consumption. In contrast, the TFEQ disinhibition and hunger scores (but not restraint scores) were significantly different (P<0.05) between the groups ((UR; D=13.5+/-0.5, H=10.0+/-0.5), R (D 7.5+/-0.6, H 6.1+/-0.4), C(D 3.7+/-0.5, H 3.7+/-0.5)). In addition, analysis of the intra-meal changes in subjective appetite sensations revealed that the UR group displayed a smaller meal-induced suppression of hunger and elevation of fullness.
These data indicate that the reported relationship between eating and hunger/fullness was associated with obese individuals showing high or low disinhibition scores. In addition, the data suggest that the processes underlying disinhibition may be associated with a modulation of the recognition of meal-related satiety sensations.
To assist health professionals who counsel patients with overweight and obesity, a systematic review was undertaken to determine types of weight-loss interventions that contribute to successful outcomes and to define expected weight-loss outcomes from such interventions.
A search was conducted for weight-loss-focused randomized clinical trials with >or=1-year follow-up. Eighty studies were identified and are included in the evidence table.
The primary outcomes were a measure of weight loss at 6, 12, 24, 36, and 48 months. Eight types of weight-loss interventions-diet alone, diet and exercise, exercise alone, meal replacements, very-low-energy diets, weight-loss medications (orlistat and sibutramine), and advice alone-were identified. By using simple pooling across studies, subjects mean amount of weight loss at each time point for each intervention was determined.
Efficacy outcomes were calculated by meta-analysis and provide support for the pooled data. Hedges' gu was combined across studies to obtain an average effect size (and confidence level).
A mean weight loss of 5 to 8.5 kg (5% to 9%) was observed during the first 6 months from interventions involving a reduced-energy diet and/or weight-loss medications with weight plateaus at approximately 6 months. In studies extending to 48 months, a mean 3 to 6 kg (3% to 6%) of weight loss was maintained with none of the groups experiencing weight regain to baseline. In contrast, advice-only and exercise-alone groups experienced minimal weight loss at any time point.
Weight-loss interventions utilizing a reduced-energy diet and exercise are associated with moderate weight loss at 6 months. Although there is some regain of weight, weight loss can be maintained. The addition of weight-loss medications somewhat enhances weight-loss maintenance.
The development of the Dutch Eating Behaviour Questionnaire (DEBQ) with scales for restrained, emotional, and external eating is described. Factor analyses have shown that all items on restrained and external eating each have high loadings on one factor, but items on emotional eating have two dimensions, one dealing with eating in response to diffuse emotions, and the other with eating in response to clearly labelled emotions. The pattern of corrected item-total correlation coefficients and of the factors was very similar for various subsamples, which indicates a high degree of stability of dimensions on the eating behavior scales. The norms and Cronbach's alpha coefficients of the scales and also the Pearson's correlation coefficients to assess interrelationships between scales indicate that the scales have a high internal consistency and factorial validity. However, their external validity has yet to be investigated.
Background:
Self-weighing increases a person's self-awareness of current weight and weight patterns. Increased self-weighing frequency can help an individual prevent weight gain. Literature, however, is limited in describing variability in self-weighing strategies and how the variability is associated with weight management outcomes.
Aim:
This review analyzed self-weighing in weight management interventions and the effects of self-weighing on weight and other outcomes.
Methods:
Twenty-two articles from PubMed, CINAHL, Medline, PsychInfo, and Academic Search Premier were extracted for review.
Results:
These 22 articles reported findings from 19 intervention trials, mostly on weight loss or weight gain prevention. The majority of the reviewed articles reported interventions that combined self-weighing with other self-monitoring strategies (64%), adopted daily self-weighing frequency (84%), and implemented interventions up to six months (59%). One-half of the articles mentioned that technology-enhanced or regular weight scales were given to study participants. Of the articles that provided efficacy data, 75% of self-weighing-only interventions and 67% of combined interventions demonstrated improved weight outcomes. No negative psychological effects were found.
Conclusions:
Self-weighing is likely to improve weight outcomes, particularly when performed daily or weekly, without causing untoward adverse effects. Weight management interventions could consider including this strategy.
Objectives
To determine associations between use of three different modes of social contact (in person, telephone, written or e-mail), contact with different types of people, and risk of depressive symptoms in a nationally representative, longitudinal sample of older adults.DesignPopulation-based observational cohort.SettingUrban and suburban communities throughout the contiguous United States.ParticipantsIndividuals aged 50 and older who participated in the Health and Retirement Survey between 2004 and 2010 (N = 11,065).MeasurementsFrequency of participant use of the three modes of social contact with children, other family members, and friends at baseline were used to predict depressive symptoms (measured using the eight-item Center for Epidemiologic Studies Depression Scale) 2 years later using multivariable logistic regression models.ResultsProbability of having depressive symptoms steadily increased as frequency of in-person—but not telephone or written or e-mail contact—decreased. After controlling for demographic, clinical, and social variables, individuals with in-person social contact every few months or less with children, other family, and friends had a significantly higher probability of clinically significant depressive symptoms 2 years later (11.5%) than those having in-person contact once or twice per month (8.1%; P < .001) or once or twice per week (7.3%; P < .001). Older age, interpersonal conflict, and depression at baseline moderated some of the effects of social contact on depressive symptoms.Conclusion
Frequency of in-person social contact with friends and family independently predicts risk of subsequent depression in older adults. Clinicians should consider encouraging face-to-face social interactions as a preventive strategy for depression.
Background:
Many smartphone applications (apps) for weight loss are available, but little is known about their effectiveness.
Objective:
To evaluate the effect of introducing primary care patients to a free smartphone app for weight loss.
Design:
Randomized, controlled trial. (ClinicalTrials.gov: NCT01650337).
Setting:
2 academic primary care clinics.
Patients:
212 primary care patients with body mass index of 25 kg/m2 or greater.
Intervention:
6 months of usual care without (n = 107) or with (n = 105) assistance in downloading the MyFitnessPal app (MyFitnessPal).
Measurements:
Weight loss at 6 months (primary outcome) and changes in systolic blood pressure and behaviors, frequency of app use, and satisfaction (secondary outcomes).
Results:
After 6 months, weight change was minimal, with no difference between groups (mean between-group difference, -0.30 kg [95% CI, -1.50 to 0.95 kg]; P = 0.63). Change in systolic blood pressure also did not differ between groups (mean between-group difference, -1.7 mm Hg [CI, -7.1 to 3.8 mm Hg]; P = 0.55). Compared with patients in the control group, those in the intervention group increased use of a personal calorie goal (mean between-group difference, 2.0 d/wk [CI, 1.1 to 2.9 d/wk]; P < 0.001), although other self-reported behaviors did not differ between groups. Most users reported high satisfaction with MyFitnessPal, but logins decreased sharply after the first month.
Limitations:
Despite being blinded to the name of the app, 14 control group participants (13%) used MyFitnessPal. In addition, 32% of intervention group participants and 19% of control group participants were lost to follow-up at 6 months. The app was given to patients by research assistants, not by physicians.
Conclusion:
Smartphone apps for weight loss may be useful for persons who are ready to self-monitor calories, but introducing a smartphone app is unlikely to produce substantial weight change for most patients.
Primary funding source:
Robert Wood Johnson Foundation Clinical Scholars Program, National Institutes of Health/National Center for Advancing Translational Sciences for the UCLA Clinical and Translational Science Institute, and the Resource Centers for Minority Aging Research Center for Health Improvement of Minority Elderly under the National Institutes of Health/National Institute on Aging.
The development of the Dutch Eating Behaviour Questionnaire (DEBQ) with scales for restrained, emotional, and external eating is described. Factor analyses have shown that all items on restrained and external eating each have high loadings on one factor, but items on emotional eating have two dimensions, one dealing with eating in response to diffuse emotions, and the other with eating in response to clearly labelled emotions. The pattern of corrected item-total correlation coefficients and of the factors was very similar for various subsamples, which indicates a high degree of stability of dimensions on the eating behavior scales. The norms and Cronbach's alpha coefficients of the scales and also the Pearson's correlation coefficients to assess interrelationships between scales indicate that the scales have a high internal consistency and factorial validity. However, their external validity has yet to be investigated.
Physicians have limited time for weight-loss counseling, and there is a lack of resources to which they can refer patients for assistance with weight loss. Weight-loss mobile applications (apps) have the potential to be a helpful tool, but the extent to which they include the behavioral strategies included in evidence-based interventions is unknown.
The primary aims of the study were to determine the degree to which commercial weight-loss mobile apps include the behavioral strategies included in evidence-based weight-loss interventions, and to identify features that enhance behavioral strategies via technology.
Thirty weight-loss mobile apps, available on iPhone and/or Android platforms, were coded for whether they included any of 20 behavioral strategies derived from an evidence-based weight-loss program (i.e., Diabetes Prevention Program). Data on available apps were collected in January 2012; data were analyzed in June 2012.
The apps included on average 18.83% (SD=13.24; range=0%-65%) of the 20 strategies. Seven of the strategies were not found in any app. The most common technology-enhanced features were barcode scanners (56.7%) and a social network (46.7%).
Weight-loss mobile apps typically included only a minority of the behavioral strategies found in evidence-based weight-loss interventions. Behavioral strategies that help improve motivation, reduce stress, and assist with problem solving were missing across apps. Inclusion of additional strategies could make apps more helpful to users who have motivational challenges.
Intermittent energy restriction may result in greater improvements in insulin sensitivity and weight control than daily energy restriction (DER). We tested two intermittent energy and carbohydrate restriction (IECR) regimens, including one which allowed ad libitum protein and fat (IECR+PF). Overweight women (n 115) aged 20 and 69 years with a family history of breast cancer were randomised to an overall 25 % energy restriction, either as an IECR (2500-2717 kJ/d, < 40 g carbohydrate/d for 2 d/week) or a 25 % DER (approximately 6000 kJ/d for 7 d/week) or an IECR+PF for a 3-month weight-loss period and 1 month of weight maintenance (IECR or IECR+PF for 1 d/week). Insulin resistance reduced with the IECR diets (mean - 0·34 (95 % CI - 0·66, - 0·02) units) and the IECR+PF diet (mean - 0·38 (95 % CI - 0·75, - 0·01) units). Reductions with the IECR diets were significantly greater compared with the DER diet (mean 0·2 (95 % CI - 0·19, 0·66) μU/unit, P= 0·02). Both IECR groups had greater reductions in body fat compared with the DER group (IECR: mean - 3·7 (95 % CI - 2·5, - 4·9) kg, P= 0·007; IECR+PF: mean - 3·7 (95 % CI - 2·8, - 4·7) kg, P= 0·019; DER: mean - 2·0 (95 % CI - 1·0, 3·0) kg). During the weight maintenance phase, 1 d of IECR or IECR+PF per week maintained the reductions in insulin resistance and weight. In the short term, IECR is superior to DER with respect to improved insulin sensitivity and body fat reduction. Longer-term studies into the safety and effectiveness of IECR diets are warranted.
The construct of attempted eating restriction has been measured in a number of ways in recent years. The Three-Factor Model of Dieting suggests that dieting can be subdivided into three types: (1) frequency of past dieting and overeating (i.e., history of dieting), (2) current dieting to lose weight, and (3) weight suppression, or the difference between an individual's current weight and his or her highest previous weight. The purpose of this paper is to 1) describe the Dieting and Weight History Questionnaire (DWHQ), a measure that we have used for many years to assess these three dimensions of dieting; 2) provide some recent examples of published research on each type of dieting; 3) discuss some of the nuances of assessing these dieting types; and 4) suggest directions for future research.
The Think Health! study evaluated a behavioral weight loss program adapted from the Diabetes Prevention Program (DPP) lifestyle intervention to assist primary care providers (PCPs) and auxiliary staff acting as lifestyle coaches (LCs) in offering weight loss counseling to their patients. In a randomized trial conducted at five clinical sites, study participants were randomly assigned in a 1:1 ratio within each site to either "Basic Plus" (n = 137), which offered PCP counseling every 4 months plus monthly LC visits during the first year of treatment, or "Basic" (n = 124), which offered only PCP counseling every 4 months. Participants were primarily (84%) female, 65% African American, 16% Hispanic American, and 19% white. In the 72% of participants in each treatment group with a 12-month weight measurement, mean (95% CI) 1-year weight changes (kg) were -1.61 (-2.68, -0.53) in Basic Plus and -0.62 (-1.45, 0.20) in Basic (difference: 0.98 (-0.36, 2.33); P = 0.15). Results were similar in model-based estimates using all available weight data for randomized participants, adjusting for potential confounders. More Basic Plus (22.5%) than Basic (10.2%) participants lost ≥ 5% of their baseline weight (P = 0.022). In a descriptive, nonrandomized analysis that also considered incomplete visit attendance, mean weight change was -3.3 kg in Basic Plus participants who attended ≥ 5 LC visits vs. + 0.53 kg in those attending <5 LC visits. We conclude that the Basic Plus approach of moderate-intensity counseling by PCPs and their staff can facilitate modest weight loss, with clinically significant weight loss in high program attenders.
The prevalence of obesity is similar for men (32.2%) and women (35.5%). It has been assumed that lifestyle weight loss interventions have been developed and tested in predominately female samples, but this has not been systematically investigated. The aim of this review was to investigate total and ethnic male inclusion in randomized controlled trials of lifestyle interventions. PUBMED, MEDLINE, and PSYCHINFO were searched for randomized controlled trials of lifestyle weight loss interventions (N = 244 studies with a total of 95,207 participants) published in the last 10 years (1999-2009). A trial must be in English, included weight loss as an outcome, and tested a dietary, exercise, and/or other behavioral intervention for weight loss. Results revealed samples were on average 27% male vs. 73% female (P < 0.001). Trials recruiting a diseased sample included a larger proportion of males than those not targeting a disease (35% vs. 21%; P < 0.001). About 32% of trials used exclusively female samples, whereas only 5% used exclusively male samples (P < 0.001). No studies in the past 10 years specifically targeted minority males. Ethnic males identified composed 1.8% of total participants in US studies. Only 24% of studies that underrepresented males provided a reason. Males, especially ethnic males, are underrepresented in lifestyle weight loss trials.
The epidemiological evidence supporting a causal link between Mediterranean diets and body weight is contrasting. We evaluated the effect of Mediterranean diets on body weight in randomized controlled trials (RCTs) using a meta-analysis.
We searched English and non-English publications in PubMed, Embase, Scopus, and the Cochrane Central Register of Controlled Trials from inception to January, 2010. Two evaluators independently selected and reviewed eligible studies. Sixteen randomized controlled trials, with 19 arms and 3,436 participants (1,848 assigned to a Mediterranean diet and 1,588 assigned to a control diet) were included.
In a random-effects meta-analysis of all 19 arms, the Mediterranean diet group had a significant effect on weight [mean difference between Mediterranean diet and control diet, -1.75 kg; 95% confidence interval (CI), -2.86 to -0.64 kg] and body mass index (mean difference, -0.57 kg/m², -0.93 to -0.21 kg/m²). The effect of Mediterranean diet on body weight was greater in association with energy restriction (mean difference, -3.88 kg, -6.54 to -1.21 kg), increased physical activity (-4.01 kg, -5.79 to -2.23 kg), and follow up longer than 6 months (-2.69 kg, -3.99 to -1.38 kg). No study reported significant weight gain with a Mediterranean diet.
Mediterranean diet may be a useful tool to reduce body weight, especially when the Mediterranean diet is energy-restricted, associated with physical activity, and more than 6 months in length. Mediterranean diet does not cause weight gain, which removes the objection to its relatively high fat content. These results may be useful for helping people to lose weight.
The development of the Dutch Eating Behaviour Questionnaire (DEBQ) with scales for restrained, emotional, and external eating is described. Factor analyses have shown that all items on restrained and external eating each have high loadings on one factor, but items on emotional eating have two dimensions, one dealing with eating in reponse to diffuse emotions, and the other with eating in response to clearly labelled emotions. The pattern of corrected item-total correlation coefficients and of the factors was very similar for various subsamples, which indicates a high degree of stability of dimensions on the eating behavior scales. The norms and Cronbach's alpha coefficients of the scales and also the Pearson's correlation coefficients to assess interrelationships between scales indicate that the scales have a high internal consistency and factorial validity. However, their external validity has yet to be investigated.
A method for estimating the cholesterol content of the serum low-density lipoprotein fraction (Sf- 0.20)is presented. The method involves measure- ments of fasting plasma total cholesterol, tri- glyceride, and high-density lipoprotein cholesterol concentrations, none of which requires the use of the preparative ultracentrifuge. Cornparison of this suggested procedure with the more direct procedure, in which the ultracentrifuge is used, yielded correlation coefficients of .94 to .99, de- pending on the patient population compared. Additional Keyph rases hyperlipoproteinemia classifi- cation #{149} determination of plasma total cholesterol, tri- glyceride, high-density lipoprotein cholesterol #{149} beta lipo proteins
Body size feedback is commonly provided to clients in weight loss programs. The attention focused on one's current, and presumably undesirable, body size can be motivating for those who want to modify a pattern of unhealthful behaviors. For others, this feedback may result in psychological distress and could lead to outcomes that are, in fact, counter to a weight loss strategy, such as attrition from programs, misreporting of dietary intake, and emotional states associated with binge eating. Dietitians and weight loss professionals should provide weight feedback judiciously, especially to vulnerable clients, and perhaps soften the emphasis on body size altogether.
To describe physical activity levels of children (6-11 yr), adolescents (12-19 yr), and adults (20+ yr), using objective data obtained with accelerometers from a representative sample of the U.S. population.
These results were obtained from the 2003-2004 National Health and Nutritional Examination Survey (NHANES), a cross-sectional study of a complex, multistage probability sample of the civilian, noninstitutionalized U.S. population in the United States. Data are described from 6329 participants who provided at least 1 d of accelerometer data and from 4867 participants who provided four or more days of accelerometer data.
Males are more physically active than females. Physical activity declines dramatically across age groups between childhood and adolescence and continues to decline with age. For example, 42% of children ages 6-11 yr obtain the recommended 60 min x d(-1) of physical activity, whereas only 8% of adolescents achieve this goal. Among adults, adherence to the recommendation to obtain 30 min x d(-1) of physical activity is less than 5%.
Objective and subjective measures of physical activity give qualitatively similar results regarding gender and age patterns of activity. However, adherence to physical activity recommendations according to accelerometer-measured activity is substantially lower than according to self-report. Great care must be taken when interpreting self-reported physical activity in clinical practice, public health program design and evaluation, and epidemiological research.
The Fast Diet-The Simple Secret of Intermittent Fasting: Lose Weight, Stay Healthy, Live Longer
- M Mosley
- M Spencer
Mosley M, Spencer M. The Fast Diet-The Simple Secret of Intermittent Fasting:
Lose Weight, Stay Healthy, Live Longer. New York, NY: Atria Books; 2013.
Sustained self-regulation of energy intake. Loss of weight in overweight subjects. Maintenance of weight in normalweight subjects
- M Ciampolini
- D Lovell-Smith
- M Sifone
Ciampolini M, Lovell-Smith D, Sifone M. Sustained self-regulation of energy
intake. Loss of weight in overweight subjects. Maintenance of weight in normalweight subjects. Nutr Metab (Lond) 2010;7:4. doi:10.1186/1743-7075-7-4
Figure 2 Mean monthly adherence to monitoring strategies over 1-year intervention. Obesity Monitoring Strategies for Weight Loss
- Jospe
Figure 2 Mean monthly adherence to monitoring strategies over 1-year intervention.
Obesity
Monitoring Strategies for Weight Loss Jospe et al.
Manual for the Depression Anxiety Stress Scales. Sydney, NSW: Psychology Foundation of Australia
- S H Lovibond
- P F Lovibond
Lovibond SH, Lovibond PF. Manual for the Depression Anxiety Stress Scales.
Sydney, NSW: Psychology Foundation of Australia; 1996.
Interventions for enhancing medication adherence
- R Nieuwlaat
- N Wilczynski
- T Navarro
Nieuwlaat R, Wilczynski N, Navarro T, et al. Interventions for enhancing
medication adherence. Cochrane Database Syst Rev 2014;CD000011. doi:10.1002/
14651858.CD000011.pub4