Frequency of Self-Weighing and Weight Change: Cohort Study With 10,000 Smart Scale Users

A Novel Web App for Dietary Weight Management: Development, Implementation, and Usability Study

BACKGROUND

Online weight loss programs have ambiguous efficacy. There is a growing body of evidence that weight loss programs when combined with apps have better outcomes; however, many apps lack an evidence-based approach to dietary changes for weight loss and do not rely on a theoretical framework for behavior change.

OBJECTIVE

This study aimed to describe the development and the preliminary usability and acceptability testing of a web app that uses behavior change techniques (BCTs) to support users of a comprehensive online weight loss program.

METHODS

The weight loss program intervention components were nutrient and weight tracking charts that needed a remotely accessible and online format. The app was designed by nutrition researchers and developers in a collaborative effort. A review of BCTs in weight loss and web apps was performed as well as an assessment of user needs to inform the initial prototype. A preliminary app prototype, version 1.0, was provided to participants of a weight loss trial (N=30) to assess for feasibility of its use. A full app prototype, version 2.0, was feasibility and acceptability tested by trial participants (n=11) with formal feedback by Likert-scale survey and open-ended questions. In the final round of testing, a user group of scientists and developers (n=11) was selected to provide a structured 3-month review through which the group met weekly for collective feedback sessions.

RESULTS

The process resulted in a fully developed web app, MealPlot, by the Applied Research Institute, for meal planning and weight tracking that can be used by weight loss users and health professionals to track their patients. MealPlot includes a weight chart, a protein-fiber chart, and a chat feature. In addition, MealPlot has 2 distinct platforms, 1 for weight loss users and 1 for health professionals. Selected BCTs for incorporation into the app were goal setting, feedback, problem-solving, self-monitoring, and social support. Version 1.0 was used successfully to provide a functioning, online weight chart over the course of a 1-year trial. Version 2.0 provided a functional weight chart and meal planning page, but 8 out of 11 participants indicated MealPlot was difficult to use. Version 3.0 was developed based on feedback and strategies provided from user group testing.

CONCLUSIONS

The web app, MealPlot, was developed to improve outcomes and functionality of an online weight loss program by providing a remote method of tracking weight, food intake, and connecting users to health professionals for consistent guidance that is not otherwise available in a traditional in-person health care setting. The final version 3.0 of the web app will be refined based on findings of a review study gathering feedback from health professionals and from actual weight loss users who are part of a clinical weight loss trial.

Coach access to digital self-monitoring data: an experimental test of short-term effects in behavioral weight-loss treatment

OBJECTIVE

This study experimentally tested whether coach access to participants' digital self-monitoring data improved behavioral weight-loss outcomes.

METHODS

Participants (N = 322) received 12 weeks of group-based behavioral weight-loss sessions via videoconference and were instructed to engage in daily self-monitoring of weight, physical activity (PA), and dietary intake. For participants who were randomly assigned to Coach Share ON (n = 161), coaches regularly accessed a web-based portal that displayed data from the participants' scale, PA sensor, and food record.

RESULTS

Weight loss at 12 weeks was significantly greater in Coach Share ON versus OFF (6.2% vs. 5.3%; p = 0.04). Self-monitoring of PA (98.70% vs. 97.40% of days; p = 0.006) and eating (98.05% vs. 93.51% of days; p = 0.007) was more frequent in Coach Share ON versus OFF. There were no significant differences by condition in PA (p = 0.57), attendance (p = 0.42), working alliance (p = 0.62), or self-monitoring of weight (p = 0.12). Perceived supportive accountability was significantly greater in Coach Share ON versus OFF (p < 0.001).

CONCLUSIONS

The short-term efficacy of behavioral weight loss was greater when coaches had direct access to self-monitoring device data. Notably, there also was no evidence of iatrogenic effects of data sharing.

Data Collection and Management of mHealth, Wearables, and Internet of Things in Digital Behavioral Health Interventions With the Awesome Data Acquisition Method (ADAM): Development of a Novel Informatics Architecture

Unlabelled

The integration of health and activity data from various wearable devices into research studies presents technical and operational challenges. The Awesome Data Acquisition Method (ADAM) is a versatile, web-based system that was designed for integrating data from various sources and managing a large-scale multiphase research study. As a data collecting system, ADAM allows real-time data collection from wearable devices through the device's application programmable interface and the mobile app's adaptive real-time questionnaires. As a clinical trial management system, ADAM integrates clinical trial management processes and efficiently supports recruitment, screening, randomization, data tracking, data reporting, and data analysis during the entire research study process. We used a behavioral weight-loss intervention study (SMARTER trial) as a test case to evaluate the ADAM system. SMARTER was a randomized controlled trial that screened 1741 participants and enrolled 502 adults. As a result, the ADAM system was efficiently and successfully deployed to organize and manage the SMARTER trial. Moreover, with its versatile integration capability, the ADAM system made the necessary switch to fully remote assessments and tracking that are performed seamlessly and promptly when the COVID-19 pandemic ceased in-person contact. The remote-native features afforded by the ADAM system minimized the effects of the COVID-19 lockdown on the SMARTER trial. The success of SMARTER proved the comprehensiveness and efficiency of the ADAM system. Moreover, ADAM was designed to be generalizable and scalable to fit other studies with minimal editing, redevelopment, and customization. The ADAM system can benefit various behavioral interventions and different populations.

Psychological and behavioral responses to daily weight gain during behavioral weight loss treatment

Self-weighing is consistently associated with more effective weight control. However, patterns show that participants disengage from their weight control behaviors following weight gain. Women with BMIs in the overweight/obese range (N = 50) enrolled in a long-term behavioral weight loss program completed ecological momentary assessment (EMA) surveys immediately after their daily weigh-ins. Nightly EMA surveys and self-monitoring data through Fitbit measured their weight control behavior that day. On days when participants gained weight (vs. lost or maintained), they reported more negative mood, more guilt/shame, and lower confidence in weight control. Motivation following daily weight gain depended on participants' overall satisfaction with their weight loss so far: more satisfied participants had marginally higher, but less satisfied participants had marginally lower motivation in response to daily weight gain. Greater guilt/shame and lower motivation after the weigh-in predicted less effective weight control behavior that day (e.g., lower likelihood of calorie tracking, fewer minutes of physical activity). Results demonstrate that even small weight gain is distressing and demoralizing for women in BWL programs, which can lead to goal disengagement. These findings have implications for future BWL interventions, including the potential utility of just-in-time adaptive interventions to promote more adaptive responses in the moments after weigh-ins.

Association of Obesity With Health Literacy and Weight Perception Among Women Merchants in Abidjan, Côte d'Ivoire: A Cross-Sectional Study

BACKGROUND

In Abidjan, Côte d'Ivoire's largest city, obesity rates among women are increasing, posing a major health challenge, especially for the working generation. Merchants represent 64.3% of working women and are a typical occupation for women with low- and middle-income. Health literacy is used to prevent and overcome chronic diseases and can be used as anti-obesity measures.

OBJECTIVE

The aim of this study was to examine the relationship between obesity, health literacy, and weight perception among women merchants in Abidjan.

METHODS

In this cross-sectional study, we conducted a complete enumeration survey among women merchants in a market in Abidjan from December 2020 to December 2021. In addition to anthropometric measurements, structured face-to-face interviews were conducted. The participants were asked about their weight perception, weight management behaviors, and sociodemographic attributes. They also responded to the Health Literacy Questionnaire (HLQ). Data were tabulated using descriptive statistics, and multiple logistic regression analysis was performed to examine obesity's association with HLQ scales, weight perception, and weight management behaviors.

KEY RESULTS

Of the 873 participants, 259 (29.7%) were obese; 82% of them underestimated their weight. Obesity was associated with a higher rate of HLQ1 (Feeling understood and supported by health care providers) (odds ratio [OR] = 2.926, confidence interval [CI]:1.450-5.901, p = .03), a lower score of HLQ3 (Actively managing my health) (OR = 0.343, CI:0.165-0.716, p = 0.004), a lower rate of accurate weight perception (OR = 0.145, CI: 0.093-0.224, p < .001), and a lower rate of eating at least three meals per day (OR = 0.401, CI:0.260-0.617, p < .001).

CONCLUSIONS

Findings from this study of Abidjan women merchants include obese participants' lack of a proactive attitude toward personal health management, and the association of factors such as inaccurate weight perception and eating fewer than three meals per day with obesity. These finding have important implications for future anti-obesity measures. [HLRP: Health Literacy Research and Practice. 2024;8(2):e102-e112.].

Patient perceptions of three-dimensional (3D) surface imaging technology and traditional methods used to assess anthropometry

Background

Obesity and overweight are commonplace, yet attrition rates in weight management clinics are high. Traditional methods of body measurement may be a deterrent due to invasive and time-consuming measurements and negative experiences of how data are presented back to individuals. Emerging new technologies, such as three-dimensional (3D) surface imaging technology, might provide a suitable alternative. This study aimed to understand acceptability of traditional and 3D surface imaging-based body measures, and whether perceptions differ between population groups.

Methods

This study used a questionnaire to explore body image, body measurement and shape, followed by a qualitative semi-structured interview and first-hand experience of traditional and 3D surface imaging-based body measures.

Results

49 participants responded to the questionnaire and 26 participants attended for the body measurements and interview over a 2-month period. There were 3 main themes from the qualitative data 1) Use of technology, 2) Participant experience, expectations and perceptions and 3) Perceived benefits and uses.

Conclusion

From this study, 3D-surface imaging appeared to be acceptable to patients as a method for anthropometric measurements, which may reduce anxiety and improve attrition rates in some populations. Further work is required to understand the scalability, and the role and implications of these technologies in weight management practice. (University Research Ethics Committee reference number ER41719941).

Day-to-day variability in euvolemic body mass

Short-term variability in body mass is a common, everyday phenomenon; however, data on body mass variability are scarce. While the physiological variability of body mass is negligible in healthy individuals, it could have implications for therapy in patients with impaired volume homeostasis, for example, patients with kidney failure undergoing kidney replacement therapy. We analyzed a long-term dataset comprising 9521 days of standardized body mass measurements from one healthy male individual and assessed the variability in body mass as a positive or negative relative difference in body mass measured on subsequent days. The average and median relative differences were zero, with a standard deviation (SD) of 0.53% for the one-day interval, increasing to 0.69% for the 7-day interval, and this variability was constant throughout the observation period. A body mass variability of approximately 0.6% (±450 mL in a 75-kg patient) should be taken into consideration when weight-dependent treatment prescriptions, e.g. the ultrafiltration rates in patients on hemodialysis, are being set. Consequently, a "soft target weight", considering the longitudinal variation of volume markers, such as body mass, might improve treatment quality.

The BREAK study protocol: Effects of intermittent energy restriction on adaptive thermogenesis during weight loss and its maintenance

BACKGROUND

Adaptive thermogenesis, defined as the decrease in the energy expenditure components beyond what can be predicted by changes in body mass stores, has been studied as a possible barrier to weight loss and weight maintenance. Intermittent energy restriction (IER), using energy balance refeeds, has been pointed out as a viable strategy to reduce adaptive thermogenesis and improve weight loss efficiency (greater weight loss per unit of energy deficit), as an alternative to a continuous energy restriction (CER). Following a randomized clinical trial design, the BREAK Study aims to compare the effects of IER versus CER on body composition and in adaptive thermogenesis, and understand whether participants will successfully maintain their weight loss after 12 months.

METHODS

Seventy-four women with obesity and inactive (20-45 y) will be randomized to 16 weeks of CER or IER (8x2 weeks of energy restriction interspersed with 7x1 week in energy balance). Both groups will start with 2 weeks in energy balance before energy restriction, followed by 16 weeks in energy restriction, then 8 weeks in energy balance and finally a 12-month weight maintenance phase. Primary outcomes are changes in fat-mass and adaptive thermogenesis after weight loss and weight maintenance. Secondary outcomes include weight loss, fat-free mass preservation, alterations in energy expenditure components, and changes in hormones (thyroid function, insulin, leptin, and cortisol).

DISCUSSION

We anticipate that The BREAK Study will allow us to better understand adaptive thermogenesis during weight loss and weight maintenance, in women with obesity. These findings will enable evidence-based decisions for obesity treatment.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT05184361.

Examining demographic and psychosocial factors related to self-weighing behavior during pregnancy and postpartum periods

Black childbearing individuals in the US experience a higher risk of postpartum weight retention (PPWR) compared to their White counterparts. Given that PPWR is related to adverse health outcomes, it is important to investigate predictors of weight-related health behaviors, such as self-weighing (i.e., using a scale at home). Regular self-weighing is an evidence-based weight management strategy, but there is minimal insight into sociodemographic factors related to frequency. The Postpartum Mothers Mobile Study (PMOMS) facilitated longitudinal ambulatory weight assessments to investigate racial inequities in PPWR. Our objective for the present study was to describe self-weighing behavior during and after pregnancy in the PMOMS cohort, as well as related demographic and psychosocial factors. Applying tree modeling and multiple regression, we examined self-weighing during and after pregnancy. Participants (N = 236) were 30.2 years old on average (SD = 4.7), with the majority being college-educated (53.8%, n = 127), earning at least $30,000 annually (61.4%, n = 145), and self-identifying as non-Hispanic White (NHW; 68.2%, n = 161). Adherence to regular self-weighing (at least once weekly) was highest among participants during pregnancy, with a considerable decline after giving birth. Low-income Black participants (earning < $30,000) were significantly less likely to reach a completion rate of ≥ 80% during pregnancy (AOR = 0.10) or the postpartum period (AOR = 0.16), compared to NHW participants earning at least $30,000 annually. Increases in perceived stress were associated with decreased odds of sustained self-weighing after delivery (AOR = 0.79). Future research should consider behavioral differences across demographic intersections, such as race and socioeconomic status, and the impact on efficacy of self-weighing.

Collecting health-related research data using consumer-based wireless smart scales

BACKGROUND

Serious public-health concerns such as overweight and obesity are in many cases caused by excess intake of food combined with decreases in physical activity. Smart scales with wireless data transfer can, together with smart watches and trackers, observe changes in the population's health. They can present us with a picture of our metabolism, body health, and disease risks. Combining body composition data with physical activity measurements from devices such as smart watches could contribute to building a human digital twin.

OBJECTIVE

The objectives of this study were to (1) investigate the evolution of smart scales in the last decade, (2) map status and supported sensors of smart scales, (3) get an overview of how smart scales have been used in research, and (4) identify smart scales for current and future research.

METHOD

We searched for devices through web shops and smart scale tests/reviews, extracting data from the manufacturer's official website, user manuals when available, and data from web shops. We also searched scientific literature databases for smart scale usage in scientific papers.

RESULT

We identified 165 smart scales with a wireless connection from 72 different manufacturers, released between 2009 and end of 2021. Of these devices, 49 (28%) had been discontinued by end of 2021. We found that the use of major variables such as fat and muscle mass have been as good as constant over the years, and that minor variables such as visceral fat and protein mass have increased since 2015. The main contribution is a representative overview of consumer grade smart scales between 2009 and 2021.

CONCLUSION

The last six years have seen a distinct increase of these devices in the marketplace, measuring body composition with bone mass, muscle mass, fat mass, and water mass, in addition to weight. Still, the number of research projects featuring connected smart scales are few. One reason could be the lack of professionally accurate measurements, though trend analysis might be a more feasible usage scenario.

A Conceptual Model for Mobile Health-enabled Slow Eating Strategies

Ingestive behaviors (IBs) (eg, bites, chews, oral processing, swallows, pauses) have meaningful roles in enhancing satiety, promoting fullness, and decreasing food consumption, and thus may be an underused strategy for obesity prevention and treatment. Limited IB monitoring research has been conducted because of a lack of accurate automated measurement capabilities outside laboratory settings. Self-report methods are used, but they have questionable validity and reliability. This paper aimed to present a conceptual model in which IB, specifically slow eating, supported by technological advancements, contributes to controlling hedonic and homeostatic processes, providing an opportunity to reduce energy intake, and improve health outcomes.

Enablers and barriers to implementing obesity assessments in clinical practice: a rapid mixed-methods systematic review

OBJECTIVES

This systematic review aims to improve our knowledge of enablers and barriers to implementing obesity-related anthropometric assessments in clinical practice.

DESIGN

A mixed-methods systematic review.

DATA SOURCES

Medline, Embase and CINAHL to November 2021.

ELIGIBILITY CRITERIA

Quantitative studies that reported patient factors associated with obesity assessments in clinical practice (general practice or primary care); and qualitative studies that reported views of healthcare professionals about enablers and barriers to their implementation.

DATA EXTRACTION AND SYNTHESIS

We used random-effects meta-analysis to pool ratios for categorical predictors reported in ≥3 studies expressed as pooled risk ratio (RR) with 95% CI, applied inverse variance weights, and investigated statistical heterogeneity (I2), publication bias (Egger's test), and sensitivity analyses. We used reflexive thematic analysis for qualitative data and applied a convergent integrated approach to synthesis.

RESULTS

We reviewed 22 quantitative (observational) and 3 qualitative studies published between 2004 and 2020. All had ≥50% of the quality items for risk of bias assessments. Obesity assessment in clinical practice was positively associated with patient factors: female sex (RR 1.28, 95% CI 1.10 to 1.50, I2 99.8%, mostly UK/USA), socioeconomic deprivation (RR 1.21, 95% CI 1.18 to 1.24, I2 73.9%, UK studies), non-white race/ethnicity (RR 1.27, 95% CI 1.03 to 1.57, I2 99.6%) and comorbidities (RR 2.11, 95% CI 1.60 to 2.79, I2 99.6%, consistent across most countries). Obesity assessment was also most common in the heaviest body mass index group (RR 1.55, 95% CI 0.99 to 2.45, I2 99.6%). Views of healthcare professionals were positive about obesity assessments when linked to patient health (convergent with meta-analysis for comorbidities) and if part of routine practice, but negative about their role, training, time, resources and incentives in the healthcare system.

CONCLUSIONS

Our evidence synthesis revealed several important enablers and barriers to obesity assessments that should inform healthcare professionals and relevant stakeholders to encourage adherence to clinical practice guideline recommendations.

Self-Weighing Behaviors of Diverse Community-Dwelling Adults Motivated for a Lifestyle Change

We aimed to understand adults’ self-weighing behaviors and explore significant predictors of body mass index (BMI) accuracy based on self-reported height and weight in a diverse sample of community-dwelling adults. Methods: In this cross-sectional study, 531 adults participating in a physical activity program or a weight loss program were analyzed. Participants’ self-reported and objectively measured weight, height, weight scale ownership, self-weighing behaviors, and medical history were collected. Results: The mean age (standard deviation) was 50.0 (12.0) years with a range of 24 to 78 years. Out of 531 participants, 455 (85.7%) were women. The study population was diverse (58.9% non-White). In total, 409 (77.0%) participants had a weight scale at home, but only 222 (41.8%) weighed themselves at least once a week. The weight and BMI underestimation became much more significant as the participant’s weight increased (p ≤ 0.001). Employment status, high cholesterol, and low objectively measured weight were significant predictors of self-reported BMI accuracy after controlling for potential confounding factors (p < 0.05). Interestingly, ownership of a home weight scale and the frequency of self-weighing behavior were not significantly associated with the accuracy of self-reported BMI (p > 0.05). Conclusion: The accuracy of the participants’ BMI, based on self-reported height and weight, was significantly associated with employment status, high cholesterol, and low objectively measured weight, suggesting that BMI accuracy depends on multi factors.

Low-carbohydrate versus balanced-carbohydrate diets for reducing weight and cardiovascular risk

BACKGROUND

Debates on effective and safe diets for managing obesity in adults are ongoing. Low-carbohydrate weight-reducing diets (also known as 'low-carb diets') continue to be widely promoted, marketed and commercialised as being more effective for weight loss, and healthier, than 'balanced'-carbohydrate weight-reducing diets.

OBJECTIVES

To compare the effects of low-carbohydrate weight-reducing diets to weight-reducing diets with balanced ranges of carbohydrates, in relation to changes in weight and cardiovascular risk, in overweight and obese adults without and with type 2 diabetes mellitus (T2DM).

SEARCH METHODS

We searched MEDLINE (PubMed), Embase (Ovid), the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science Core Collection (Clarivate Analytics), ClinicalTrials.gov and WHO International Clinical Trials Registry Platform (ICTRP) up to 25 June 2021, and screened reference lists of included trials and relevant systematic reviews. Language or publication restrictions were not applied.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) in adults (18 years+) who were overweight or living with obesity, without or with T2DM, and without or with cardiovascular conditions or risk factors. Trials had to compare low-carbohydrate weight-reducing diets to balanced-carbohydrate (45% to 65% of total energy (TE)) weight-reducing diets, have a weight-reducing phase of 2 weeks or longer and be explicitly implemented for the primary purpose of reducing weight, with or without advice to restrict energy intake.  DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles and abstracts and full-text articles to determine eligibility; and independently extracted data, assessed risk of bias using RoB 2 and assessed the certainty of the evidence using GRADE. We stratified analyses by participants without and with T2DM, and by diets with weight-reducing phases only and those with weight-reducing phases followed by weight-maintenance phases. Primary outcomes were change in body weight (kg) and the number of participants per group with weight loss of at least 5%, assessed at short- (three months to < 12 months) and long-term (≥ 12 months) follow-up.

MAIN RESULTS

We included 61 parallel-arm RCTs that randomised 6925 participants to either low-carbohydrate or balanced-carbohydrate weight-reducing diets. All trials were conducted in high-income countries except for one in China. Most participants (n = 5118 randomised) did not have T2DM. Mean baseline weight across trials was 95 kg (range 66 to 132 kg). Participants with T2DM were older (mean 57 years, range 50 to 65) than those without T2DM (mean 45 years, range 22 to 62). Most trials included men and women (42/61; 3/19 men only; 16/19 women only), and people without baseline cardiovascular conditions, risk factors or events (36/61). Mean baseline diastolic blood pressure (DBP) and low-density lipoprotein (LDL) cholesterol across trials were within normal ranges. The longest weight-reducing phase of diets was two years in participants without and with T2DM. Evidence from studies with weight-reducing phases followed by weight-maintenance phases was limited. Most trials investigated low-carbohydrate diets (> 50 g to 150 g per day or < 45% of TE; n = 42), followed by very low (≤ 50 g per day or < 10% of TE; n = 14), and then incremental increases from very low to low (n = 5). The most common diets compared were low-carbohydrate, balanced-fat (20 to 35% of TE) and high-protein (> 20% of TE) treatment diets versus control diets balanced for the three macronutrients (24/61). In most trials (45/61) the energy prescription or approach used to restrict energy intake was similar in both groups. We assessed the overall risk of bias of outcomes across trials as predominantly high, mostly from bias due to missing outcome data. Using GRADE, we assessed the certainty of evidence as moderate to very low across outcomes.  Participants without and with T2DM lost weight when following weight-reducing phases of both diets at the short (range: 12.2 to 0.33 kg) and long term (range: 13.1 to 1.7 kg).  In overweight and obese participants without T2DM: low-carbohydrate weight-reducing diets compared to balanced-carbohydrate weight-reducing diets (weight-reducing phases only) probably result in little to no difference in change in body weight over three to 8.5 months (mean difference (MD) -1.07 kg, (95% confidence interval (CI) -1.55 to -0.59, I2 = 51%, 3286 participants, 37 RCTs, moderate-certainty evidence) and over one to two years (MD -0.93 kg, 95% CI -1.81 to -0.04, I2 = 40%, 1805 participants, 14 RCTs, moderate-certainty evidence); as well as change in DBP and LDL cholesterol over one to two years. The evidence is very uncertain about whether there is a difference in the number of participants per group with weight loss of at least 5% at one year (risk ratio (RR) 1.11, 95% CI 0.94 to 1.31, I2 = 17%, 137 participants, 2 RCTs, very low-certainty evidence).  In overweight and obese participants with T2DM: low-carbohydrate weight-reducing diets compared to balanced-carbohydrate weight-reducing diets (weight-reducing phases only) probably result in little to no difference in change in body weight over three to six months (MD -1.26 kg, 95% CI -2.44 to -0.09, I2 = 47%, 1114 participants, 14 RCTs, moderate-certainty evidence) and over one to two years (MD -0.33 kg, 95% CI -2.13 to 1.46, I2 = 10%, 813 participants, 7 RCTs, moderate-certainty evidence); as well in change in DBP, HbA1c and LDL cholesterol over 1 to 2 years. The evidence is very uncertain about whether there is a difference in the number of participants per group with weight loss of at least 5% at one to two years (RR 0.90, 95% CI 0.68 to 1.20, I2 = 0%, 106 participants, 2 RCTs, very low-certainty evidence).  Evidence on participant-reported adverse effects was limited, and we could not draw any conclusions about these.  AUTHORS' CONCLUSIONS: There is probably little to no difference in weight reduction and changes in cardiovascular risk factors up to two years' follow-up, when overweight and obese participants without and with T2DM are randomised to either low-carbohydrate or balanced-carbohydrate weight-reducing diets.

Self-managed weight loss by smart body fat scales ameliorates obesity-related body composition during the COVID-19 pandemic: A follow-up study in Chinese population

BACKGROUND

Since 2020, longer stay-at-home time in response to the coronavirus disease 2019 (COVID-19) pandemic has changed the weight-related behaviors of Chinese population.

OBJECTIVES

To explore the demographic and basic characteristics of body fat scale users and to investigate the changes in obesity-related body composition of overweight and obese users during COVID-19. Further, we analyzed the factors associated with successful weight loss and improved body composition changes in overweight and obese people.

METHODS

The study included 107,419 Chinese adults registered in the smart app connecting to the body fat scale in 2020 to describe the demographic characteristics of body fat scale users by Unpaired Student's t-test and Chi-Square test. Subsequently, overweight and obese participants with body mass index (BMI) of more than 24 kg/m² were screened to investigate the independent factors associated with effective weight loss and improved body composition changes by multivariable logistic regression analyses.

RESULTS

During the pandemic, the number of body fat scale users increased markedly compared with pre-pandemic. Over half of the participants were women and with normal baseline BMI. Based on BMI classification, multivariable logistic regressions showed that age, gender, measurement frequency classification, baseline BMI, visceral adipose index and skeletal muscle rate were associated with weight loss and fat loss in the overweight and obese population, with the high-frequency measurement being the most important factor for effective weight and fat loss. In the population with normal BMI obesity, younger age was the most significant factor for effective fat loss.

CONCLUSION

During the COVID-19 pandemic, participation in self-monitored weight loss increased markedly compared with pre-pandemic, and women accounted for the majority. We found that many overweight and obese participants achieved weight loss goals by smart body fat scales, and the effectiveness of weight and fat loss was greater in obese participants than in overweight participants, both based on BMI and PBF classification. In addition, promoting the usage of smart body fat scales could contribute to more effective weight and fat loss in the overweight and obese population based on BMI classification. However, in the population with normal BMI obesity, young subjects might be easier to successfully lose fat compared with the elder. Digital self-management by smart body fat scales could become a promising approach for the obese population with high BMI to lose weight and keep healthy.