A digital health weight-loss intervention in severe obesity

App Engagement as a Predictor of Weight Loss in Blended-Care Interventions: Retrospective Observational Study Using Large-Scale Real-World Data

BACKGROUND

Early weight loss is an established predictor for treatment outcomes in weight management interventions for people with obesity. However, there is a paucity of additional, reliable, and clinically actionable early predictors in weight management interventions. Novel blended-care weight management interventions combine coach and app support and afford new means of structured, continuous data collection, informing research on treatment adherence and outcome prediction.

OBJECTIVE

Against this backdrop, this study analyzes app engagement as a predictor for weight loss in large-scale, real-world, blended-care interventions. We hypothesize that patients who engage more frequently in app usage in blended-care treatment (eg, higher logging activity) lose more weight than patients who engage comparably less frequently at 3 and 6 months of intervention.

METHODS

Real-world data from 19,211 patients in obesity treatment were analyzed retrospectively. Patients were treated with 3 different blended-care weight management interventions, offered in Switzerland, the United Kingdom, and Germany by a digital behavior change provider. The principal component analysis identified an overarching metric for app engagement based on app usage. A median split informed a distinction in higher and lower engagers among the patients. Both groups were matched through optimal propensity score matching for relevant characteristics (eg, gender, age, and start weight). A linear regression model, combining patient characteristics and app-derived data, was applied to identify predictors for weight loss outcomes.

RESULTS

For the entire sample (N=19,211), mean weight loss was -3.24% (SD 4.58%) at 3 months and -5.22% (SD 6.29%) at 6 months. Across countries, higher app engagement yielded more weight loss than lower engagement after 3 but not after 6 months of intervention (P3 months<.001 and P6 months=.59). Early app engagement within the first 3 months predicted percentage weight loss in Switzerland and Germany, but not in the United Kingdom (PSwitzerland<.001, PUnited Kingdom=.12, and PGermany=.005). Higher age was associated with stronger weight loss in the 3-month period (PSwitzerland=.001, PUnited Kingdom=.002, and PGermany<.001) and, for Germany, also in the 6-month period (PSwitzerland=.09, PUnited Kingdom=.46, and PGermany=.03). In Switzerland, higher numbers of patients' messages to coaches were associated with higher weight loss (P3 months<.001 and P6 months<.001). Messages from coaches were not significantly associated with weight loss (all P>.05).

CONCLUSIONS

Early app engagement is a predictor of weight loss, with higher engagement yielding more weight loss than lower engagement in this analysis. This new predictor lends itself to automated monitoring and as a digital indicator for needed or adapted clinical action. Further research needs to establish the reliability of early app engagement as a predictor for treatment adherence and outcomes. In general, the obtained results testify to the potential of app-derived data to inform clinical monitoring practices and intervention design.

Baseline Serum BCAAs are Related to the Improvement in Insulin Resistance in Obese People After a Weight Loss Intervention

BACKGROUND

Branched chain amino acids (BCAAs) have been revealed to be closely related to insulin resistance and obesity. This study aimed to investigate if BCAA levels at baseline are related to an improvement in insulin resistance after implementing a weight loss program intervention.

METHODS

Stored blood samples from participants in previous trials were used for BCAA evaluation. Linear regression was used to analyze the relationship between baseline amino acid levels and changes in the insulin resistance index (HOMA-IR) and blood glucose.

RESULTS

A total of 48 participants were enrolled. After the intervention, the body weight (78.29± 12.68 vs 72.06 ± 13.30 kg, p=0.020), fasting glucose (4.76 ± 0.43 vs 4.48 ± 0.39 mmol/L, p=0.001), fasting insulin (18.41±13.58 vs 12.87±10.88, p=0.028), and HOMA-IR (4.01±3.39 vs 2.62± 2.18, p=0.018) were improved significantly. BCAA levels were related to the improvement in HOMA-IR (β=-0.006, p=0.039), and valine was found to be the most closely related to the improvement in HOMA-IR (β=-0.013, p=0.017).

CONCLUSION

The baseline BCAA is related to the improvement in insulin resistance among participants after a weight loss intervention.

Führt die Einführung eines DMP Adipositas zur Verbesserung der Behandlung von Adipositaspatient*innen: eine qualitative Analyse

Hintergrund Disease Management Programme (DMP) sind strukturierte Behandlungsprogramme zur koordinierten Behandlung ausgewählter chronischer Krankheiten von der Prävention bis zur Nachsorge 1. Das zunächst 2022 geplante strukturierte Behandlungsprogramm (DMP) Adipositas soll im Rahmen des Gesetzes 2023 auf den Weg gebracht werden 2 11. In Deutschland sind laut Adipositas Gesellschaft (DAG) ein Viertel der rund 66 Millionen erwachsenen Bundesbürger* innen adipös, davon sind 23% Männer und 24% Frauen 3 4. Die Weltgesundheitsorganisation klassifiziert Erwachsene mit einem BMI über 30 als adipös 5. Die Krankheit trägt zu einem erhöhten Risiko für verschiedene Gesundheitsprobleme und Folgeerkrankungen bei. Mit diesen vielfältig assoziierten Folgeerkrankungen entstehen erhebliche Kosten für das Gesundheits- und Sozialsystem 6 7. Obwohl es bereits zahlreiche verschiedene Programme und einen großen Markt für die Abnehmindustrie gibt, ist eine kontinuierliche, strukturierte Versorgung von Menschen mit Adipositas noch nicht gewährleistet 8. Eine Möglichkeit zur Versorgungsunterstützung liegt in den Bereichen Digital Health 9 und Interprofessionelle Zusammenarbeit, die aus Expert*innensicht eingeschätzt werden soll.

Zielsetzung Das Studienziel ist eine qualitative Analyse der Einschätzungen von ernährungs- und adipositasspezifischen Expert*innen aus verschiedenen Professionen, die sich derzeit mit der Behandlung von Adipositas beschäftigen. Sie sollen zur neuen möglichen Versorgungsform befragt werden, um denkbare Erfolgs- und Misserfolgsfaktoren zu erforschen. Zudem wird eine Einschätzung des potenziellen DMP Adipositas im Zusammenhang mit Digital Health und Interprofessionalität untersucht.

Methode Es wurden halbstrukturierte qualitative Interviews mit zehn Expert*innen aus verschiedenen ernährungs- und adipositasspezifischen Bereichen geführt und unter Einsatz des qualitativen Datenanalyseprogramms MAXQDA auf Basis der Analyse nach Kuckartz inhaltsanalytisch ausgewertet 10.

Ergebnisse Die Ergebnisse zeigen, dass ein Disease Management Programm eine Reihe an Erfolgsaspekten mit sich bringt, jedoch auch gewisse Misserfolge mit sich bringen kann. Dabei stellte sich in diesem Zusammenhang heraus, dass Aspekte wie interprofessionelle Behandlung, festgelegte Finanzierung, gesteigerte Selbstwahrnehmung, Langzeiteffektivität, Frühdiagnostik, gesteigerte Lebensqualität, Wissensvermittlung, Adipositas-Lotsen und die Anerkennung des Krankheitsbild Adipositas als erfolgsversprechend angesehen werden und durch den strukturierten, definierten Behandlungspfades des künftigen Disease Management Programm Adipositas gefördert werden sollten. Der Wunsch nach einem definierten Schweregrad für die spezifischen Behandlungsziele der Expert*innen wurde zusätzlich als Erfolgsfaktor analysiert. Der Umgang mit Digital Health wurde ambivalent, sowohl vorteilig als auch nachteilig, bewertet. So kann eine digitale Gesundheitsanwendung neben der persönlichen Betreuung einen positiven Aspekt im Bereich Prävention und Langzeitbetreuung mit sich bringen. In Bezug auf die interprofessionelle Zusammenarbeit in einem DMP wurde diese als überwiegend förderlich erachtet und nur dann negativ konnotiert, wenn Interessenskonflikte, beispielsweise durch den bereits genannten Aspekt der Finanzierung, entstehen.

Fazit Zusammenfassend hat diese qualitative Forschung gezeigt, dass neben einem DMP weitere Schritte nötig sind und Optimierungsbedarf bei bereits bestehenden Ansätzen in der Adipositasversorgung in Deutschland besteht. Dabei wurde sowohl auf die nötige politische Unterstützung, die Finanzierung auf den verschiedenen Ebenen, als auch den Zeitfaktor für eine ausreichende individuelle Ursachenanalyse, Aufklärung und Wissensvermittlung sowie allgemeine Gesundheitsförderung eingegangen. Diese Forschungsarbeit kann durch die Darlegung der bestehenden Defizite und Optimierungsvorschläge der Expert*innen dazu führen, dass die Gesundheitskompetenz der interprofessionellen Akteur*innen in der Adipositasversorgung, die Förderung von digitalen Gesundheitsanwendungen in Kombination mit einem strukturierten Behandlungsprogramm und die politische Aufmerksamkeit für die Erkrankung Adipositas gestärkt werden und in diesen Bereichen in Zukunft nachjustiert wird.

Weight Reduction Interventions Using Digital Health for Employees with Obesity: A Systematic Review

PURPOSE

This study aimed to systematically review the literature on randomized controlled trials on weight reduction interventions using digital health for employees with obesity.

METHODS

All relevant articles published until September 2021 were systematically identified from six electronic databases: MEDLINE, EMBASE, CINAHL, PsycINFO, RISS, and KISS. Data selection and extraction were independently performed by three researchers. Methodological quality was assessed using the JBI Critical Appraisal Checklist for Randomized Controlled Trials. The results were narratively synthesized.

RESULTS

Eleven studies were included in the systematic review. All studies had a low risk of bias. The settings and sample sizes of the included studies were different. The contents of the interventions included nutrition, physical activity, behavioral change, incentives, and motivation. Four studies were based on social cognitive theory. A total of ten studies delivered web-based intervention, while the other used tele-monitoring device. A wide range of intervention strategies was used including providing online resources, tele-counseling, and patient-tailored advice. As a result of the intervention, a total of seven studies showed a significant weight reduction in both the intervention and comparison groups, with significant differences between groups.

CONCLUSION

Until now, use of digital health in weight reduction interventions for employees with obesity has been conducted on a web-based. Various contents such as nutrition, physical activity and theories were explored. Further study is required using more diverse delivery methods such as mobile application, use of wearable devices.

Low Carb Program Health App Within a Hospital-Based Obesity Setting: Observational Service Evaluation

Background

Obesity underlies much chronic disease. Digitalization of obesity management provides an opportunity to innovate our traditional model of health care delivery within this setting, and to transform its scalability potentially to the population level.

Objective

The objective was to assess the feasibility and effectiveness of the Low Carb Program app for weight loss, applied within our hospital-based (tier 3) obesity service. Due to the disrupting effects of the COVID-19 pandemic on our obesity service, we compared the clinical outcomes from the Low Carb Program app applied in the context of remote patient appointments over the telephone with the prepandemic traditional standard of care.

Methods

We invited patients who attended our hospital-based obesity service to engage with the Low Carb Program smartphone app. We combined this approach with remote delivery (over the telephone) of obesity management from medical and psychology members of our obesity team during the COVID-19 pandemic. Outcome variables included changes in body weight and changes in HbA_1c as a marker of glycemic control. We compared data from the Low Carb Program group with a retrospective control group (n=126) that had received traditional face-to-face obesity management from our team without concomitant use of the Low Carb Program app in the pre–COVID-19 era. T test comparisons were employed, with P<.05 considered significant.

Results

The mean weight of participants (n=105) was 130.2 kg, with 59% (n=62) females and a mean age of 48.8 years. Most participants (90/105, 86%) completed the Low Carb Program app registration process and engaged with the Low Carb Program app program; at follow-up, most participants (88/105, 84%) had actively engaged with the Low Carb Program app within the prior 30 days. The majority of participants (58/105, 55%) self-reported outcomes within the app. Mean duration of clinical follow-up for recruited participants who received the app was 7.4 months. Paired data were available for 48 participants for body weight and 41 participants for HbA_1c. Paired sample t test analysis revealed a statistically significant mean loss of body weight of 2.7 kg (P=.001) and improvement in HbA_1c of 3.3 mmol/mol (P=.01). The mean weight of control group patients (n=126) was 137.1 kg, with 74% (93/126) females and a mean age of 44.4 years. The mean follow-up for this group was 6 months. Data comparisons between the app user group and the pre–COVID-19 retrospective control group revealed equivalence for loss of body weight and change in HbA_1c between the two groups.

Conclusions

We provide evidence to support the feasibility of implementing the Low Carb Program app combined with remote management; this is the first proof of concept for digitalized management within a hospital-based (tier 3) obesity service. We demonstrate the potential clinical efficacy of the approach in terms of improvements in body weight and glycemic control.

Weight Reduction Through a Digital Nutrition and Food Purchasing Platform Among Users With Obesity: Longitudinal Study

Background

Digital nutrition apps that monitor or provide recommendations on diet have been found to be effective in behavior change and weight reduction among individuals with obesity. However, there is less evidence on how integration of personalized nutrition recommendations and changing the food purchasing environment through online meal planning and grocery delivery, meal kits, and grocery incentives impacts weight loss among individuals with obesity.

Objective

The objective of this observational longitudinal study was to examine weight loss and predictors of weight loss among individuals with obesity who are users of a digital nutrition platform that integrates tools to provide nutrition recommendations and changes in the food purchasing environment grounded in behavioral theory.

Methods

We included 8977 adults with obesity who used the digital Foodsmart platform, created by Zipongo, Inc, DBA Foodsmart between January 2013 and April 2020. We retrospectively analyzed user characteristics and their associations with weight loss. Participants reported age, gender, height, at least 2 measures of weight, and usual dietary intake. Healthy Diet Score, a score to measure overall diet quality, was calculated based on responses to a food frequency questionnaire. We used paired t tests to compare differences in baseline and final weights and baseline and final Healthy Diet Scores. We used univariate and multivariate logistic regression models to estimate odds ratios and 95% CI of achieving 5% weight loss by gender, age, baseline BMI, Healthy Diet Score, change in Healthy Diet Score, and duration of enrollment. We conducted stratified analyses to examine mean percent weight change by enrollment duration and gender, age, baseline BMI, and change in Healthy Diet Score.

Results

Over a median (IQR) of 9.9 (0.03-54.7) months of enrollment, 59% of participants lost weight. Of the participants who used the Foodsmart platform for at least 24 months, 33.3% achieved 5% weight loss. In the fully adjusted logistic regression model, we found that baseline BMI (OR 1.02, 95% CI 1.02-1.03; P<.001), baseline Healthy Diet Score (OR 1.06, 95% CI 1.05-1.08; P<.001), greater change in Healthy Diet Score (OR 1.12, 95% CI 1.11-1.14; P<.001), and enrollment length (OR 1.28, 95% CI 1.23-1.32; P<.001) were all significantly associated with higher odds of achieving at least 5% weight loss.

Conclusions

This study found that a digital app that provides personalized nutrition recommendations and change in one’s food purchasing environment appears to be successful in meaningfully reducing weight among individuals with obesity.