EVIDENT 3 Study: A randomized, controlled clinical trial to reduce inactivity and caloric intake in sedentary and overweight or obese people using a smartphone application: Study protocol

Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity

BACKGROUND

Obesity is considered to be a risk factor for various diseases, and its incidence has tripled worldwide since 1975. In addition to potentially being at risk for adverse health outcomes, people with overweight or obesity are often stigmatised. Behaviour change interventions are increasingly delivered as mobile health (m-health) interventions, using smartphone apps and wearables. They are believed to support healthy behaviours at the individual level in a low-threshold manner.

OBJECTIVES

To assess the effects of integrated smartphone applications for adolescents and adults with overweight or obesity.

SEARCH METHODS

We searched CENTRAL, MEDLINE, PsycINFO, CINAHL, and LILACS, as well as the trials registers ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform on 2 October 2023 (date of last search for all databases). We placed no restrictions on the language of publication.

SELECTION CRITERIA

Participants were adolescents and adults with overweight or obesity. Eligible interventions were integrated smartphone apps using at least two behaviour change techniques. The intervention could target physical activity, cardiorespiratory fitness, weight loss, healthy diet, or self-efficacy. Comparators included no or minimal intervention (NMI), a different smartphone app, personal coaching, or usual care. Eligible studies were randomised controlled trials of any duration with a follow-up of at least three months.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methodology and the RoB 2 tool. Important outcomes were physical activity, body mass index (BMI) and weight, health-related quality of life, self-efficacy, well-being, change in dietary behaviour, and adverse events. We focused on presenting studies with medium- (6 to < 12 months) and long-term (≥ 12 months) outcomes in our summary of findings table, following recommendations in the core outcome set for behavioural weight management interventions.

MAIN RESULTS

We included 18 studies with 2703 participants. Interventions lasted from 2 to 24 months. The mean BMI in adults ranged from 27 to 50, and the median BMI z-score in adolescents ranged from 2.2 to 2.5. Smartphone app versus no or minimal intervention Thirteen studies compared a smartphone app versus NMI in adults; no studies were available for adolescents. The comparator comprised minimal health advice, handouts, food diaries, smartphone apps unrelated to weight loss, and waiting list. Measures of physical activity: at 12 months' follow-up, a smartphone app compared to NMI probably reduces moderate to vigorous physical activity (MVPA) slightly (mean difference (MD) -28.9 min/week (95% confidence interval (CI) -85.9 to 28; 1 study, 650 participants; moderate-certainty evidence)). We are very uncertain about the results of estimated energy expenditure and cardiorespiratory fitness at eight months' follow-up. A smartphone app compared with NMI probably results in little to no difference in changes in total activity time at 12 months' follow-up and leisure time physical activity at 24 months' follow-up. Anthropometric measures: a smartphone app compared with NMI may reduce BMI (MD of BMI change -2.6 kg/m2, 95% CI -6 to 0.8; 2 studies, 146 participants; very low-certainty evidence) at six to eight months' follow-up, but the evidence is very uncertain. At 12 months' follow-up, a smartphone app probably resulted in little to no difference in BMI change (MD -0.1 kg/m2, 95% CI -0.4 to 0.3; 1 study; 650 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in body weight change (MD -2.5 kg, 95% CI -6.8 to 1.7; 3 studies, 1044 participants; low-certainty evidence) at 12 months' follow-up. At 24 months' follow-up, a smartphone app probably resulted in little to no difference in body weight change (MD 0.7 kg, 95% CI -1.2 to 2.6; 1 study, 245 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in self-efficacy for a physical activity score at eight months' follow-up, but the results are very uncertain. A smartphone app probably results in little to no difference in quality of life and well-being at 12 months (moderate-certainty evidence) and in little to no difference in various measures used to inform dietary behaviour at 12 and 24 months' follow-up. We are very uncertain about adverse events, which were only reported narratively in two studies (very low-certainty evidence). Smartphone app versus another smartphone app Two studies compared different versions of the same app in adults, showing no or minimal differences in outcomes. One study in adults compared two different apps (calorie counting versus ketogenic diet) and suggested a slight reduction in body weight at six months in favour of the ketogenic diet app. No studies were available for adolescents. Smartphone app versus personal coaching Only one study compared a smartphone app with personal coaching in adults, presenting data at three months. Two studies compared these interventions in adolescents. A smartphone app resulted in little to no difference in BMI z-score compared to personal coaching at six months' follow-up (MD 0, 95% CI -0.2 to 0.2; 1 study; 107 participants). Smartphone app versus usual care Only one study compared an app with usual care in adults but only reported data at three months on participant satisfaction. No studies were available for adolescents. We identified 34 ongoing studies.

AUTHORS' CONCLUSIONS

The available evidence is limited and does not demonstrate a clear benefit of smartphone applications as interventions for adolescents or adults with overweight or obesity. While the number of studies is growing, the evidence remains incomplete due to the high variability of the apps' features, content and components, which complicates direct comparisons and assessment of their effectiveness. Comparisons with either no or minimal intervention or personal coaching show minor effects, which are mostly not clinically significant. Minimal data for adolescents also warrants further research. Evidence is also scarce for low- and middle-income countries as well as for people with different socio-economic and cultural backgrounds. The 34 ongoing studies suggest sustained interest in the topic, with new evidence expected to emerge within the next two years. In practice, clinicians and healthcare practitioners should carefully consider the potential benefits, limitations, and evolving research when recommending smartphone apps to adolescents and adults with overweight or obesity.

Long-Term Effectiveness of a Smartphone App and a Smart Band on Arterial Stiffness and Central Hemodynamic Parameters in a Population with Overweight and Obesity (Evident 3 Study): Randomised Controlled Trial

BACKGROUND

mHealth technologies could help to improve cardiovascular health; however, their effect on arterial stiffness and hemodynamic parameters has not been explored to date.

OBJECTIVE

To evaluate the effect of a mHealth intervention, at 3 and 12 months, on arterial stiffness and central hemodynamic parameters in a sedentary population with overweight and obesity.

METHODS

Randomised controlled clinical trial (Evident 3 study). 253 subjects were included: 127 in the intervention group (IG) and 126 in the control group (CG). The IG subjects were briefed on the use of the Evident 3 app and a smart band (Mi Band 2, Xiaomi) for 3 months to promote healthy lifestyles. All measurements were recorded in the baseline visit and at 3 and 12 months. The carotid-femoral pulse wave velocity (cfPWV) and the central hemodynamic parameters were measured using a SphigmoCor System^® device, whereas the brachial-ankle pulse wave velocity (baPWV) and the Cardio Ankle Vascular Index (CAVI) were measured using a VaSera VS-2000^® device.

RESULTS

Of the 253 subjects who attended the initial visit, 237 (93.7%) completed the visit at 3 months of the intervention, and 217 (85.3%) completed the visit at 12 months of the intervention. At 12 months, IG showed a decrease in peripheral augmentation index (PAIx) (-3.60; 95% CI -7.22 to -0.00) and ejection duration (ED) (-0.82; 95% CI -1.36 to -0.27), and an increase in subendocardial viability ratio (SEVR) (5.31; 95% CI 1.18 to 9.44). In CG, cfPWV decreased at 3 months (-0.28 m/s; 95% CI -0.54 to -0.02) and at 12 months (-0.30 m/s, 95% CI -0.54 to -0.05), central diastolic pressure (cDBP) decreased at 12 months (-1.64 mm/Hg; 95% CI -3.19 to -0.10). When comparing the groups we found no differences between any variables analyzed.

CONCLUSIONS

In sedentary adults with overweight or obesity, the multicomponent intervention (Smartphone app and an activity-tracking band) for 3 months did not modify arterial stiffness or the central hemodynamic parameters, with respect to the control group. However, at 12 months, CG presented a decrease of cfPWV and cDBP, whereas IG showed a decrease of PAIx and ED and an increase of SEVR.

Changes in lifestyles, cognitive impairment, quality of life and activity day living after combined use of smartphone and smartband technology: a randomized clinical trial (EVIDENT-Age study)

Background

The aim of this study was to assess the efficacy of the combined use of smartphone and smartband technology for 3-months alongside brief lifestyle counselling, versus counselling alone, in increasing physical activity. As secondary objectives, the effects of the intervention on dietary habits, body composition, quality of life, level of functionality and cognitive performance were assessed.

Methods

This study employed a randomized clinical trial of two-parallel groups design – control group (CG) and intervention group (IG). The study was conducted in 3 Spanish health-centres between October 2018-February 2020. Eligible participants were people of both sexes and aged between 65–80 years attending the health-centres with a score ≥ 24 points on the Mini-Mental State Examination. Key variables included physical activity, dietary pattern, body composition, cognitive performance, level of functionality and quality of life. All variables were measured at baseline and after 3-months. Both groups received a brief nutritional and physical activity advice. Intervention group participants were instructed to use a smartphone application for a period of 3-months. This application integrates information on physical activity received from a fitness bracelet and self-reported information on the patient’s daily nutritional composition.

Results

The study population comprised 160 participants (IG = 81, CG = 79), with a mean age of 70.8 ± 4.0 years (61.3% women). No difference was found in the primary and secondary outcomes analyzed (physical activity (steps/min -0.4 (-1.0 to 0.2) p = 0.174), and dietary habits (Mediterranean diet score 0.0 (-0.6 to 0.6) p = 0.956) that could be attributed to either group after an ANCOVA test. A difference attributable to the intervention was observed in the total Clock test score (0.7 (0.1 to 1.2) p = 0.018.

Conclusions

In a sample of people over 65 years of age, the combined use of the EVIDENT 3 smartphone app and an activity tracking bracelet for 3-months did not result in lifestyles changes related to the amount and level of physical activity or the eating habits, compared to brief lifestyle advice. Other clinical parameters were not changed either, although at the cognitive level, a slight improvement was observed in the score on the Clock test assessing a variety of cognitive functions such as memory.

Trial registration

The study was registered in ClinicalTrials.gov Identifier: NCT03574480. Date of trial Registration 02/07/2018.

Long-term Effectiveness of a Smartphone App Combined With a Smart Band on Weight Loss, Physical Activity, and Caloric Intake in a Population With Overweight and Obesity (Evident 3 Study): Randomized Controlled Trial

BACKGROUND

Multicomponent mobile health approaches can improve lifestyle intervention results, although little is known about their long-term effectiveness.

OBJECTIVE

This study aims to evaluate the long-term effectiveness (12 months) of a multicomponent mobile health intervention-combining a smartphone app, an activity tracker wristband, and brief counseling, compared with a brief counseling group only-on weight loss and improving body composition, physical activity, and caloric intake in Spanish sedentary adults with overweight or obesity.

METHODS

We conducted a randomized controlled, multicenter clinical trial (Evident 3). A total of 650 participants were recruited from 5 primary care centers, with 318 participants in the intervention group (IG) and 332 in the control group (CG). All participants were briefly counseled about a healthy diet and physical activity at the baseline visit. For the 3-month intervention period, the IG received training to use the app to promote healthy lifestyles and the smart band (Mi Band 2, Xiaomi). All measurements were performed at baseline and at 3 and 12 months. Physical activity was measured using the International Physical Activity Questionnaire-Short Form. Nutritional habits were assessed using the Food Frequency Questionnaire and Adherence to Mediterranean diet questionnaire.

RESULTS

Of the 650 participants included, 563 (86.6%) completed the 3-month visit and 443 (68.2%) completed the 12-month visit. After 12 months, the IG showed net differences in weight (-0.26, 95% CI -1.21 to 0.70 kg; P=.02), BMI (-0.06, 95% CI -0.41 to 0.28 points; P=.01), waist-height ratio (-0.25, 95% CI -0.94 to 0.44; P=.03), body adiposity index (-0.33, 95% CI -0.77 to 0.11; P=.03), waist circumference (-0.48, 95% CI -1.62 to 0.66 cm, P=.04) and hip circumference (-0.69, 95% CI -1.62 to 0.25 cm; P=.03). Both groups lowered daily caloric intake and increased adherence to the Mediterranean diet, with no differences between the groups. The IG increased light physical activity time (32.6, 95% CI -30.3 to 95.04 min/week; P=.02) compared with the CG. Analyses by subgroup showed changes in body composition variables in women, people aged >50 years, and married people.

CONCLUSIONS

The low-intensity intervention of the Evident 3 study showed, in the IG, benefits in weight loss, some body composition variables, and time spent in light physical activity compared with the CG at 3 months, but once the devices were collected, the downward trend was not maintained at the 12-month follow-up. No differences in nutritional outcomes were observed between the groups.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03175614; https://clinicaltrials.gov/ct2/show/NCT03175614.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1097/MD.0000000000009633.

Effect of a Multicomponent mHealth Intervention on the Composition of Diet in a Population with Overweight and Obesity-Randomized Clinical Trial EVIDENT 3

A balanced diet can help in the prevention of chronic diseases. The aim of this study was to evaluate the effect of an mHealth intervention on the distribution of macronutrients and the intake of food groups. A total of 650 participants were included in this multi-center, clinical, randomized, controlled trial (Evident 3 study). All participants were given brief advice about diet and exercise. The intervention group received, in addition, an app (Evident 3) for the self-recording of their diet and an activity tracker wristband for 3 months. Follow-up visits were performed at 3 and 12 months to collect the diet composition using the Food Frequency Questionnaire. There were decreases in the intake of total calories, fat, protein and carbohydrates in both groups throughout the study, without significant differences between them. The intervention group reduced the intake of cholesterol (−30.8; 95% CI −59.9, −1.7) and full-fat dairies (−23.3; 95% CI −42.8, −3.8) and increased the intake of wholemeal bread (3.3; 95% CI −6.7, 13.3) and whole-grain cereals (3.4; 95% CI −6.8, 13.7) with respect to the control group. No differences were found in the rest of the nutritional parameters. The brief advice is useful to promote a healthier diet, and the app can be a support tool to obtain changes in relevant foods, such as integral foods, and the intake of cholesterol. Trial registration: ClinicalTrials.gov with identifier NCT03175614.

Implementation of telerehabilitation in Austrian outpatient physiotherapy – A qualitative study / Implementierung von Telerehabilitation in der ambulanten Physiotherapie in Österreich – Eine qualitative Studie

Background

New technologies, for example, telerehabilitation (TR) tools, can support physiotherapists’ work. Even though studies have demonstrated their potential, TR is not yet fully implemented in Austrian outpatient physiotherapy. As a result of the Coronavirus pandemic and the associated lockdowns, physiotherapists in Austria were confronted with the challenge of offering therapies without physical contact. This study aims to investigate opinions and experiences of physiotherapists in Austria regarding TR and its implementation in different clinical fields.

Methods

A qualitative research design with expert interviews and a focus group discussion were conducted. Data were analysed using content analysis. The categories were formed following a deductive-inductive approach.

Results

The interview partners considered opportunities for using synchronous TR in internal medicine as well as orthopaedics and traumatology, especially in later, exercise-dominated stages. In addition, using TR can be supportive for patient education. In the field of neurology, synchronous TR is viewed with some criticism, especially when used for people with severe neuropsychological disorders. Asynchronous TR is considered useful across all disciplines and could support physical therapy from the first therapy session and throughout the treatment. Important questions regarding liability, billing, or data protection still need to be clarified. Interdisciplinary approaches in TR should also be pursued to improve care.

Conclusion

The use of asynchronous TR in addition to regular physiotherapy is seen as promising in all clinical fields. In general, when implementing TR, the needs and requirements of different fields should be considered. Moreover, various framework conditions still need to be clarified for further implementation of TR.

Establishing the relevance of psychological determinants regarding physical activity in people with overweight and obesity

To identify the most relevant determinants involved in Physical Activity (PA) changes in the EVIDENT 3 study population, measured by the International PA Questionnaire (IPAQ) and the Actigraph GT3X accelerometer.

METHOD

Exploratory study. Data used were collected from EVIDENT 3 study (N = 650). Items to measure psychological determinants were chosen from the baseline questionnaires. PA minutes/week were assessed by an accelerometer and IPAQ. The sample was analyzed by the control group (CG), the intervention group (IG) and Body Mass Index, using Confidence Interval-Based Estimation of Relevance (CIBER) analyses.

RESULTS

486 participants, (IG: n = 251, CG: n = 235) were included. IG shows a positive association between PA assessed by accelerometer and self-efficacy. In IG, the overweight sample shows a positive association between PA assessed by accelerometer and motivation and self-efficacy. PA assessed by accelerometer obtained a higher explained variance (R2 ) in IG, both people with overweight (.10 - .55) and obesity (.03 - .19). In CG, IPAQ reached better results in people with overweight (.12 - .49).

CONCLUSIONS

Motivation and self-efficacy showed as relevant in increasing PA minutes/week, but only in the people with overweight in IG. There might be other factors not analyzed that could improve the low R2 obtained.

Smartphone-Based Interventions for Physical Activity Promotion: Scoping Review of the Evidence Over the Last 10 Years

Background

Several reviews of mobile health (mHealth) physical activity (PA) interventions suggest their beneficial effects on behavior change in adolescents and adults. Owing to the ubiquitous presence of smartphones, their use in mHealth PA interventions seems obvious; nevertheless, there are gaps in the literature on the evaluation reporting processes and best practices of such interventions.

Objective

The primary objective of this review is to analyze the development and evaluation trajectory of smartphone-based mHealth PA interventions and to review systematic theory- and evidence-based practices and methods that are implemented along this trajectory. The secondary objective is to identify the range of evidence (both quantitative and qualitative) available on smartphone-based mHealth PA interventions to provide a comprehensive tabular and narrative review of the available literature in terms of its nature, features, and volume.

Methods

We conducted a scoping review of qualitative and quantitative studies examining smartphone-based PA interventions published between 2008 and 2018. In line with scoping review guidelines, studies were not rejected based on their research design or quality. This review, therefore, includes experimental and descriptive studies, as well as reviews addressing smartphone-based mHealth interventions aimed at promoting PA in all age groups (with a subanalysis conducted for adolescents). Two groups of studies were additionally included: reviews or content analyses of PA trackers and meta-analyses exploring behavior change techniques and their efficacy.

Results

Included articles (N=148) were categorized into 10 groups: commercial smartphone app content analyses, smartphone-based intervention review studies, activity tracker content analyses, activity tracker review studies, meta-analyses of PA intervention studies, smartphone-based intervention studies, qualitative formative studies, app development descriptive studies, qualitative follow-up studies, and other related articles. Only 24 articles targeted children or adolescents (age range: 5-19 years). There is no agreed evaluation framework or taxonomy to code or report smartphone-based PA interventions. Researchers did not state the coding method, used various evaluation frameworks, or used different versions of behavior change technique taxonomies. In addition, there is no consensus on the best behavior change theory or model that should be used in smartphone-based interventions for PA promotion. Commonly reported systematic practices and methods have been successfully identified. They include PA recommendations, trial designs (randomized controlled trials, experimental trials, and rapid design trials), mixed methods data collection (surveys, questionnaires, interviews, and focus group discussions), scales to assess app quality, and industry-recognized reporting guidelines.

Conclusions

Smartphone-based mHealth interventions aimed at promoting PA showed promising results for behavior change. Although there is a plethora of published studies on the adult target group, the number of studies and consequently the evidence base for adolescents is limited. Overall, the efficacy of smartphone-based mHealth PA interventions can be considerably improved through a more systematic approach of developing, reporting, and coding of the interventions.

Gut microbiota composition and arterial stiffness measured by pulse wave velocity: case-control study protocol (MIVAS study)

INTRODUCTION

Intestinal microbiota is arising as a new element in the physiopathology of cardiovascular diseases. A healthy microbiota includes a balanced representation of bacteria with health promotion functions (symbiotes). The aim of this study is to analyse the relationship between intestinal microbiota composition and arterial stiffness.

METHODS AND ANALYSIS

An observational case-control study will be developed. Cases will be defined by the presence of at least one of the following: carotid-femoral pulse wave velocity (cf-PWV), Cardio-Ankle Vascular Index (CAVI), brachial ankle pulse wave velocity (ba or ba-PWV) above the 90^th percentile, for age and sex, of the reference population. Controls will be selected from the same population as cases. The study will be developed in Primary Healthcare Centres. We will select 500 subjects (250 cases and 250 controls), between 45 and 74 years of age. Cases will be selected from a database that combines data from EVA study (Spain) and Guimarães/Vizela study (Portugal).

MEASUREMENTS

cf-PWV will be measured using the SphygmoCor system, CAVI, ba-PWV and Ankle-Brachial Index will be determined using VaSera device. Gut microbiome composition in faecal samples will be determined by 16S ribosomal RNA sequencing. Lifestyle will be assessed by food frequency questionnaire, adherence to the Mediterranean diet and IPAQ (International Physical Activity Questionnaire). Body composition will be evaluated by bioimpedance.

ETHICS AND DISSEMINATION

The study has been approved by 'Committee of ethics of research with medicines of the health area of Salamanca' on 14 December 2018 (cod. 2018-11-136) and the 'Ethics committee for health of Guimaraes' (Portugal) on 15 October 2019 (ref: 67/2019). All study participants will sign an informed consent form agreeing to participate in the study, in compliance with the Declaration of Helsinki and the WHO standards for observational studies. The results of this study will allow a better description of gut microbiota in patients with arterial stiffness.

TRIAL REGISTRATION DETAILS

ClinicalTrials.gov, identifier NCT03900338.

Effectiveness of an mHealth Intervention Combining a Smartphone App and Smart Band on Body Composition in an Overweight and Obese Population: Randomized Controlled Trial (EVIDENT 3 Study)

Background

Mobile health (mHealth) is currently among the supporting elements that may contribute to an improvement in health markers by helping people adopt healthier lifestyles. mHealth interventions have been widely reported to achieve greater weight loss than other approaches, but their effect on body composition remains unclear.

Objective

This study aimed to assess the short-term (3 months) effectiveness of a mobile app and a smart band for losing weight and changing body composition in sedentary Spanish adults who are overweight or obese.

Methods

A randomized controlled, multicenter clinical trial was conducted involving the participation of 440 subjects from primary care centers, with 231 subjects in the intervention group (IG; counselling with smartphone app and smart band) and 209 in the control group (CG; counselling only). Both groups were counselled about healthy diet and physical activity. For the 3-month intervention period, the IG was trained to use a smartphone app that involved self-monitoring and tailored feedback, as well as a smart band that recorded daily physical activity (Mi Band 2, Xiaomi). Body composition was measured using the InBody 230 bioimpedance device (InBody Co., Ltd), and physical activity was measured using the International Physical Activity Questionnaire.

Results

The mHealth intervention produced a greater loss of body weight (–1.97 kg, 95% CI –2.39 to –1.54) relative to standard counselling at 3 months (–1.13 kg, 95% CI –1.56 to –0.69). Comparing groups, the IG achieved a weight loss of 0.84 kg more than the CG at 3 months. The IG showed a decrease in body fat mass (BFM; –1.84 kg, 95% CI –2.48 to –1.20), percentage of body fat (PBF; –1.22%, 95% CI –1.82% to 0.62%), and BMI (–0.77 kg/m², 95% CI –0.96 to 0.57). No significant changes were observed in any of these parameters in men; among women, there was a significant decrease in BMI in the IG compared with the CG. When subjects were grouped according to baseline BMI, the overweight group experienced a change in BFM of –1.18 kg (95% CI –2.30 to –0.06) and BMI of –0.47 kg/m² (95% CI –0.80 to –0.13), whereas the obese group only experienced a change in BMI of –0.53 kg/m² (95% CI –0.86 to –0.19). When the data were analyzed according to physical activity, the moderate-vigorous physical activity group showed significant changes in BFM of –1.03 kg (95% CI –1.74 to –0.33), PBF of –0.76% (95% CI –1.32% to –0.20%), and BMI of –0.5 kg/m² (95% CI –0.83 to –0.19).

Conclusions

The results from this multicenter, randomized controlled clinical trial study show that compared with standard counselling alone, adding a self-reported app and a smart band obtained beneficial results in terms of weight loss and a reduction in BFM and PBF in female subjects with a BMI less than 30 kg/m² and a moderate-vigorous physical activity level. Nevertheless, further studies are needed to ensure that this profile benefits more than others from this intervention and to investigate modifications of this intervention to achieve a global effect.

Trial Registration

Clinicaltrials.gov NCT03175614; https://clinicaltrials.gov/ct2/show/NCT03175614.

International Registered Report Identifier (IRRID)

RR2-10.1097/MD.0000000000009633

Interventions outside the workplace for reducing sedentary behaviour in adults under 60 years of age

BACKGROUND

Adults spend a majority of their time outside the workplace being sedentary. Large amounts of sedentary behaviour increase the risk of type 2 diabetes, cardiovascular disease, and both all-cause and cardiovascular disease mortality.

OBJECTIVES

Primary • To assess effects on sedentary time of non-occupational interventions for reducing sedentary behaviour in adults under 60 years of age Secondary • To describe other health effects and adverse events or unintended consequences of these interventions • To determine whether specific components of interventions are associated with changes in sedentary behaviour • To identify if there are any differential effects of interventions based on health inequalities (e.g. age, sex, income, employment) SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, Cochrane Database of Systematic Reviews, CINAHL, PsycINFO, SportDiscus, and ClinicalTrials.gov on 14 April 2020. We checked references of included studies, conducted forward citation searching, and contacted authors in the field to identify additional studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and cluster RCTs of interventions outside the workplace for community-dwelling adults aged 18 to 59 years. We included studies only when the intervention had a specific aim or component to change sedentary behaviour.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles/abstracts and full-text articles for study eligibility. Two review authors independently extracted data and assessed risk of bias. We contacted trial authors for additional information or data when required. We examined the following primary outcomes: device-measured sedentary time, self-report sitting time, self-report TV viewing time, and breaks in sedentary time.

MAIN RESULTS

We included 13 trials involving 1770 participants, all undertaken in high-income countries. Ten were RCTs and three were cluster RCTs. The mean age of study participants ranged from 20 to 41 years. A majority of participants were female. All interventions were delivered at the individual level. Intervention components included personal monitoring devices, information or education, counselling, and prompts to reduce sedentary behaviour. We judged no study to be at low risk of bias across all domains. Seven studies were at high risk of bias for blinding of outcome assessment due to use of self-report outcomes measures. Primary outcomes Interventions outside the workplace probably show little or no difference in device-measured sedentary time in the short term (mean difference (MD) -8.36 min/d, 95% confidence interval (CI) -27.12 to 10.40; 4 studies; I² = 0%; moderate-certainty evidence). We are uncertain whether interventions reduce device-measured sedentary time in the medium term (MD -51.37 min/d, 95% CI -126.34 to 23.59; 3 studies; I² = 84%; very low-certainty evidence) We are uncertain whether interventions outside the workplace reduce self-report sitting time in the short term (MD -64.12 min/d, 95% CI -260.91 to 132.67; I² = 86%; very low-certainty evidence). Interventions outside the workplace may show little or no difference in self-report TV viewing time in the medium term (MD -12.45 min/d, 95% CI -50.40 to 25.49; 2 studies; I² = 86%; low-certainty evidence) or in the long term (MD 0.30 min/d, 95% CI -0.63 to 1.23; 2 studies; I² = 0%; low-certainty evidence). It was not possible to pool the five studies that reported breaks in sedentary time given the variation in definitions used. Secondary outcomes Interventions outside the workplace probably have little or no difference on body mass index in the medium term (MD -0.25 kg/m², 95% CI -0.48 to -0.01; 3 studies; I² = 0%; moderate-certainty evidence). Interventions may have little or no difference in waist circumference in the medium term (MD -2.04 cm, 95% CI -9.06 to 4.98; 2 studies; I² = 65%; low-certainty evidence). Interventions probably have little or no difference on glucose in the short term (MD -0.18 mmol/L, 95% CI -0.30 to -0.06; 2 studies; I² = 0%; moderate-certainty evidence) and medium term (MD -0.08 mmol/L, 95% CI -0.21 to 0.05; 2 studies, I² = 0%; moderate-certainty evidence) Interventions outside the workplace may have little or no difference in device-measured MVPA in the short term (MD 1.99 min/d, 95% CI -4.27 to 8.25; 4 studies; I² = 23%; low-certainty evidence). We are uncertain whether interventions improve device-measured MVPA in the medium term (MD 6.59 min/d, 95% CI -7.35 to 20.53; 3 studies; I² = 70%; very low-certainty evidence). We are uncertain whether interventions outside the workplace improve self-reported light-intensity PA in the short-term (MD 156.32 min/d, 95% CI 34.34 to 278.31; 2 studies; I² = 79%; very low-certainty evidence). Interventions may have little or no difference on step count in the short-term (MD 226.90 steps/day, 95% CI -519.78 to 973.59; 3 studies; I² = 0%; low-certainty evidence) No data on adverse events or symptoms were reported in the included studies.

AUTHORS' CONCLUSIONS

Interventions outside the workplace to reduce sedentary behaviour probably lead to little or no difference in device-measured sedentary time in the short term, and we are uncertain if they reduce device-measured sedentary time in the medium term. We are uncertain whether interventions outside the workplace reduce self-reported sitting time in the short term. Interventions outside the workplace may result in little or no difference in self-report TV viewing time in the medium or long term. The certainty of evidence is moderate to very low, mainly due to concerns about risk of bias, inconsistent findings, and imprecise results. Future studies should be of longer duration; should recruit participants from varying age, socioeconomic, or ethnic groups; and should gather quality of life, cost-effectiveness, and adverse event data. We strongly recommend that standard methods of data preparation and analysis are adopted to allow comparison of the effects of interventions to reduce sedentary behaviour.

Extensive Review of Persuasive System Design Categories and Principles: Behavioral Obesity Interventions

In this extensive review of behavioral digital obesity interventions, we reviewed randomized control trials aimed at weight loss or maintaining weight loss and identifying persuasive categories and principles that drive these interventions. The following databases were searched for long-term obesity interventions: Medline, PsycINFO, Academic Search Complete, CINAHL and Scopus. The inclusion criteria included the following search terms: obesity, overweight, weight reduction, weight loss, obesity management, and diet control. Additional criteria included randomized control trial, ≥ 6 months intervention, ≥ 100 participants and must include persuasive technology. Forty-six publications were in the final review. Primary task support was the most frequently utilized persuasive system design (PSD) category and self-monitoring was the most utilized PSD principle. Behavioral obesity interventions that utilized PSD with a behavior change theory more frequently produced statistically significant weight loss findings. Persuasive technology and PSD in digital health play a significant role in the management and improvement of obesity especially when aligned with behavior change theories. Understanding which PSD categories and principles work best for behavioral obesity interventions is critical and future interventions might be more effective if they were based on these specific PSD categories and principles.

The Concept of Early Vascular Aging

The age is one of the main non-modified factors which reduces the elasticity of vessels and increases the appearance of atherosclerotic plaques. A number of studies have revealed that in some people, vascular changes occur at a younger age, while the presence of only classical risk factors does not explain the development of cardiovascular events in young people. This phenomenon is described as a syndrome of early, or accelerated, vascular aging (EVA). Aspects of this premature process include endothelial dysfunction, increased arterial stiffness, thickening of the intima-media complex and impaired dilatation of the central arteries, an increase of the reflected wave, hypertrophy of small vessels with a decrease in their lumen. Accelerated aging of the vascular wall increases the frequency of complications, therefore, recently "vascular age” is considered as an important predictor of individual risk of cardiovascular events. The review describes factors and mechanisms that trigger the process of EVA, genetic aspects of vascular damage and the biology of telomeres. Changes in hemodynamics and structural and functional properties of arteries during physiological and accelerated aging are presented. Currently, several indicators have been proposed that indicate arterial wall damaging and progression of vascular aging. The carotid-femoral pulse wave velocity is included in the list of indicators of subclinical target organs damage in ESH-ESC Guidelines for the management of arterial hypertension. The results of studies on the developing the new diagnostic markers for identifying individuals with "normal" or "early" ("accelerated") vascular aging are presented. Therapeutic strategies are aimed at decreasing the influence of factors that provoke EVA and include a non-pharmacological approach and medical intervention. The paper describes methods of therapeutic correction of the EVA syndrome.

Combined use of smartphone and smartband technology in the improvement of lifestyles in the adult population over 65 years: study protocol for a randomized clinical trial (EVIDENT-Age study)

BACKGROUND

The increasing use of smartphones by older adults also increases their potential for improving different aspects of health in this population. Some studies have shown promising results in the improvement of cognitive performance through lifestyle modification. All this may have a broad impact on the quality of life and carrying out daily living activities. The objective of this study is to evaluate the effectiveness of combining the use of smartphone and smartband technology for 3 months with brief counseling on life habits, as opposed to providing counseling only, in increasing physical activity and improving adherence to the Mediterranean diet. Secondary objectives are to assess the effect of the intervention on body composition, quality of life, independence in daily living activities and cognitive performance.

METHODS

This study is a two-arm cluster-randomized trial that will be carried out in urban health centers in Spain. We will recruit 160 people aged between 65 and 80 without cardiovascular disease or cognitive impairment (score in the Mini-mental State Examination ≥24). On a visit to their center, intervention group participants will be instructed to use a smartphone application for a period of 3 months. This application integrates information on physical activity received from a fitness bracelet and self-reported information on the patient's daily nutritional composition. The primary outcome will be the change in the number of steps measured by accelerometer. Secondary variables will be adherence to the Mediterranean diet, sitting time, body composition, quality of life, independence in daily living activities and cognitive performance. All variables will be measured at baseline and on the assessment visit after 3 months. A telephone follow-up will be carried out at 6 months to collect self-reported data regarding physical activity and adherence to the Mediterranean diet.

DISCUSSION

Preventive healthy aging programs should include health education with training in nutrition and lifestyles, while stressing the importance of and enhancing physical activity; the inclusion of new technologies can facilitate these goals. The EVIDENT-AGE study will incorporate a simple, accessible intervention with potential implementation in the care of older adults.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03574480 . Date of trial Registration July 2, 2018.

Targeting Postprandial Hyperglycemia With Physical Activity May Reduce Cardiovascular Disease Risk. But What Should We Do, and When Is the Right Time to Move?

Physical inactivity and excessive postprandial hyperglycemia are two major independent risk factors for type 2 diabetes and cardiovascular-related mortality. Current health policy guidelines recommend at least 150 min of physical activity per week coupled with reduced daily sedentary behavior by interrupting prolonged sitting with bouts of light activity every 30-min. This evidence-based strategy promotes health and quality of life. Since modern lifestyle enforces physical inactivity through motorized transportation and seated office working environments, this review examines the practical strategies (standing, walking, stair climbing, and strength-based circuit exercises) for reducing sitting time and increasing activity during the workday. Furthermore, since postprandial hyperglycemia poses the greatest relative risk for developing type 2 diabetes and its cardiovascular complications, this review examines a novel hypothesis that interrupting sitting time would be best focused on the postprandial period in order to optimize blood glucose control and maximize cardiometabolic health. In doing so, we aim to identify the science gaps which urgently need filling if we are to optimize healthcare policy in this critical area.