A double-blinded, randomized, parallel intervention to evaluate biomarker-based nutrition plans for weight loss: The PREVENTOMICS study.

BACKGROUND & AIMS: Growing evidence suggests that biomarker-guided dietary interventions can optimize response to treatment. In this study, we evaluated the efficacy of the PREVENTOMCIS platform-which uses metabolomic and genetic information to classify individuals into different 'metabolic clusters' and create personalized dietary plans-for improving health outcomes in subjects with overweight or obesity. METHODS: A 10-week parallel, double-blinded, randomized intervention was conducted in 100 adults (82 completers) aged 18-65 years, with body mass index ≥27 but <40 kg/m2, who were allocated into either a personalized diet group (n = 49) or a control diet group (n = 51). About 60% of all food was provided free-of-charge. No specific instruction to restrict energy intake was given. The primary outcome was change in fat mass from baseline, evaluated by dual energy X-ray absorptiometry. Other endpoints included body weight, waist circumference, lipid profile, glucose homeostasis markers, inflammatory markers, blood pressure, physical activity, stress and eating behavior. RESULTS: There were significant main effects of time (P < 0.01), but no group main effects, or time-by-group interactions, for the change in fat mass (personalized: -2.1 [95% CI -2.9, -1.4] kg; control: -2.0 [95% CI -2.7, -1.3] kg) and body weight (personalized: -3.1 [95% CI -4.1, -2.1] kg; control: -3.3 [95% CI -4.2, -2.4] kg). The difference between groups in fat mass change was -0.1 kg (95% CI -1.2, 0.9 kg, P = 0.77). Both diets resulted in significant improvements in insulin resistance and lipid profile, but there were no significant differences between groups. CONCLUSION: Personalized dietary plans did not result in greater benefits over a generic, but generally healthy diet, in this 10-week clinical trial. Further studies are required to establish the soundness of different precision nutrition approaches, and translate this science into clinically relevant dietary advice to reduce the burden of obesity and its comorbidities. CLINICAL TRIAL REGISTRY: ClinicalTrials.gov registry (NCT04590989).

Associations between behavioral flexibility and health behavior in cardiac patients in the Do CHANGE trials.

OBJECTIVE: Health behaviors (e.g., physical inactivity, poor diet) are associated with poor prognosis and mortality in cardiac patients. Changing these behaviors is challenging and only a minority of patients succeeds in this endeavor. Studies show that behavioral flexibility (defined as responding less habitually to stimuli and having a large behavioral repertoire) is a potentially important facilitator of health behaviors. The current study examines the association between behavioral flexibility and health behaviors (health responsibility, physical activity, nutrition, spiritual growth, interpersonal relations, stress management) in patients with cardiac disease. METHOD: A total of 387 patients with stable cardiac disease were recruited as part of the Do Cardiac Health: Advanced New Generation Ecosystem Trials. Behavioral flexibility (via the Do Something Different Questionnaire) was assessed at baseline and health behaviors including the above described six domains (HPLP-II at baseline, at 3 months, and at 6 months. Linear mixed models were used to answer the research question. RESULTS: The sample consisted of predominantly male patients (n = 274/71%) with a mean age of 62 (SD = 10), diagnosed with hypertension (n = 198/51%), coronary artery disease (n = 114/30%), and/or heart failure (n = 75/19%). The analyses revealed a positive but small (r = .106-.270, B = .00-.31) association between behavioral flexibility and all self-reported health behaviors over time. CONCLUSIONS: This is the first study to examine the association between behavioral flexibility and health behaviors in cardiac patients. Current results showed a positive association between behavioral flexibility and health behaviors over time. More research is needed to further examine causal effects of behavioral flexibility on health behaviors. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Empowering consumers to PREVENT diet-related diseases through OMICS sciences (PREVENTOMICS): protocol for a parallel double-blinded randomised intervention trial to investigate biomarker-based nutrition plans for weight loss.

INTRODUCTION: Personalised nutrition holds immense potential over conventional one-size-fits-all approaches for preventing and treating diet-related diseases, such as obesity. The current study aims to examine whether a personalised nutritional plan produces more favourable health outcomes than a standard approach based on general dietary recommendations in subjects with overweight or obesity and elevated waist circumference. METHODS AND ANALYSIS: This project is a 10-week parallel, double-blinded randomised intervention trial. We plan to include 100 adults aged 18-65 years interested in losing weight, with body mass index ≥27 but<40 kg/m2 and elevated waist circumference (males >94 cm; females >80 cm). Participants will be categorised into one of five predefined 'clusters' based on their individual metabolic biomarker profile and genetic background, and will be randomised in a 1:1 ratio to one of two groups: (1) personalised plan group that will receive cluster-specific meals every day for 6 days a week, in conjunction with a personalised behavioural change programme via electronic push notifications; or (2) control group that will receive meals following the general dietary recommendations in conjunction with generic health behaviour prompts. The primary outcome is the difference between groups (personalised vs control) in the change in fat mass from baseline. Secondary outcomes include changes in weight and body composition, fasting blood glucose and insulin, lipid profile, adipokines, inflammatory biomarkers, and blood pressure. Other outcomes involve measures of physical activity and sleep patterns, health-related quality of life, dietary intake, eating behaviour, and biomarkers of food intake. The effect of the intervention on the primary outcome will be analysed by means of linear mixed models. ETHICS AND DISSEMINATION: The protocol has been approved by the Ethics Committee of the Capital Region, Copenhagen, Denmark. Study findings will be disseminated through peer-reviewed publications, conference presentations and media outlets. TRIAL REGISTRATION NUMBER: NCT04590989.

A Personalized eHealth Intervention for Lifestyle Changes in Patients With Cardiovascular Disease: Randomized Controlled Trial.

BACKGROUND: Behavior change methods involving new ambulatory technologies may improve lifestyle and cardiovascular disease outcomes. OBJECTIVE: This study aimed to provide proof-of-concept analyses of an intervention aiming to increase (1) behavioral flexibility, (2) lifestyle change, and (3) quality of life. The feasibility and patient acceptance of the intervention were also evaluated. METHODS: Patients with cardiovascular disease (N=149; mean age 63.57, SD 8.30 years; 50/149, 33.5% women) were recruited in the Do Cardiac Health Advanced New Generation Ecosystem (Do CHANGE) trial and randomized to the Do CHANGE intervention or care as usual (CAU). The intervention involved a 3-month behavioral program in combination with ecological momentary assessment and intervention technologies. RESULTS: The intervention was perceived to be feasible and useful. A significant increase in lifestyle scores over time was found for both groups (F2,146.6=9.99; P<.001), which was similar for CAU and the intervention group (F1,149.9=0.09; P=.77). Quality of life improved more in the intervention group (mean 1.11, SD 0.11) than CAU (mean -1.47, SD 0.11) immediately following the intervention (3 months), but this benefit was not sustained at the 6-month follow-up (interaction: P=.02). No significant treatment effects were observed for behavioral flexibility (F1,149.0=0.48; P=.07). CONCLUSIONS: The Do CHANGE 1 intervention was perceived as useful and easy to use. However, no long-term treatment effects were found on the outcome measures. More research is warranted to examine which components of behavioral interventions are effective in producing long-term behavior change. TRIAL REGISTRATION: ClinicalTrials.gov NCT02946281; https://www.clinicaltrials.gov/ct2/show/NCT02946281.

Type D personality and global positioning system tracked social behavior in patients with cardiovascular disease.

OBJECTIVE: Social behavior (e.g., loneliness, isolation) has been indicated as an important risk factor for cardiovascular disease. Recent studies show that Type D personality might be an important predictor of social behavior. Hence, the current exploratory study aims to examine, using ecological assessment, whether Type D personality is associated with a lower likelihood to engage in social encounters in patients with cardiovascular disease. METHOD: Cardiac patients who participated in the Do CHANGE (Phase 2) trial were included in current analysis. As part of the Do CHANGE intervention, real-life data were collected in the intervention group using the MOVES app, which was installed on patients' mobile phones. For a period of 6 months, Global Positioning System (GPS) data from the participating patients were collected. From the GPS data, 3 target variables were computed: (a) general activity level, (b) social variety, and (c) social opportunity. RESULTS: A total of 70 patients were included in the analysis. Patients with a Type D personality had lower scores on the "social opportunity" variable compared to non-Type D patients (F = 6.72; p = .01). Type D personality was associated with lower social participation after adjusting for depression and anxiety. No association between Type D personality and general activity or behavioral variety was observed. CONCLUSIONS: This is the first study to use an ecological measure to assess social behavior of cardiac patients with a Type D personality. Results show that Type D personality might be associated with lower social engagement, which could, in turn, partly explain its association with adverse health outcomes. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Personalized eHealth Program for Life-style Change: Results From the "Do Cardiac Health Advanced New Generated Ecosystem (Do CHANGE 2)" Randomized Controlled Trial.

OBJECTIVE: Unhealthy life-style factors have adverse outcomes in cardiac patients. However, only a minority of patients succeed to change unhealthy habits. Personalization of interventions may result in critical improvements. The current randomized controlled trial provides a proof of concept of the personalized Do Cardiac Health Advanced New Generation Ecosystem (Do CHANGE) 2 intervention and evaluates effects on a) life-style and b) quality of life over time. METHODS: Cardiac patients (n = 150; mean age = 61.97 ± 11.61 years; 28.7% women; heart failure, n = 33; coronary artery disease, n = 50; hypertension, n = 67) recruited from Spain and the Netherlands were randomized to either the "Do CHANGE 2" or "care as usual" group. The Do CHANGE 2 group received ambulatory health-behavior assessment technologies for 6 months combined with a 3-month behavioral intervention program. Linear mixed-model analysis was used to evaluate the intervention effects, and latent class analysis was used for secondary subgroup analysis. RESULTS: Linear mixed-model analysis showed significant intervention effects for life-style behavior (Finteraction(2,138.5) = 5.97, p = .003), with improvement of life-style behavior in the intervention group. For quality of life, no significant main effect (F(1,138.18) = .58, p = .447) or interaction effect (F(2,133.1) = 0.41, p = .67) was found. Secondary latent class analysis revealed different subgroups of patients per outcome measure. The intervention was experienced as useful and feasible. CONCLUSIONS: The personalized eHealth intervention resulted in significant improvements in life-style. Cardiac patients and health care providers were also willing to engage in this personalized digital behavioral intervention program. Incorporating eHealth life-style programs as part of secondary prevention would be particularly useful when taking into account which patients are most likely to benefit. TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT03178305.

Usefulness of a Lifestyle Intervention in Patients With Cardiovascular Disease.

The importance of modifying lifestyle factors in order to improve prognosis in cardiac patients is well-known. Current study aims to evaluate the effects of a lifestyle intervention on changes in lifestyle- and health data derived from wearable devices. Cardiac patients from Spain (n = 34) and The Netherlands (n = 36) were included in the current analysis. Data were collected for 210 days, using the Fitbit activity tracker, Beddit sleep tracker, Moves app (GPS tracker), and the Careportal home monitoring system. Locally Weighted Error Sum of Squares regression assessed trajectories of outcome variables. Linear Mixed Effects regression analysis was used to find relevant predictors of improvement deterioration of outcome measures. Analysis showed that Number of Steps and Activity Level significantly changed over time (F = 58.21, p < 0.001; F = 6.33, p = 0.01). No significant changes were observed on blood pressure, weight, and sleep efficiency. Secondary analysis revealed that being male was associated with higher activity levels (F = 12.53, p < 0.001) and higher number of steps (F = 8.44, p < 0.01). Secondary analysis revealed demographic (gender, nationality, marital status), clinical (co-morbidities, heart failure), and psychological (anxiety, depression) profiles that were associated with lifestyle measures. In conclusion results showed that physical activity increased over time and that certain subgroups of patients were more likely to have a better lifestyle behaviors based on their demographic, clinical, and psychological profile. This advocates a personalized approach in future studies in order to change lifestyle in cardiac patients.

Do CHANGE platform: A service-based architecture for secure aggregation and distribution of health and wellbeing data.

Over the last decade, the adoption of open API standards offers new services meaningful in the domain of health informatics and behavior change. We present our privacy-oriented solution to support personal data collection, distribution, and usage. Given the new General Data Protection Regulations in Europe, the proposed platform is designed with requirements in mind to position citizens as the controllers of their data. The proposed result uses NodeJS servers, OAuth protocol for Authentication and Authorization, a publish-subscribe semantic for real-time data notification and Cron for APIs without a notification strategy. It uses Distributed Data Protocol to control and securely provision data to distributed frameworks utilizing the data and those distributed applications are exemplified. The platform design is transparent and modularized for research projects and small businesses to set-up and manage, and to allow them to focus on the application layer utilizing personal information. This solution can easily be configured to support custom or new data sources with open API and can scale. In our use cases, maintaining the separate ecosystem services was trivial. The adopted distributed protocol was the most challenging to manage due to its high RAM usage. And implementing a fine-grained privacy control by end-users was challenging in an existing clinical enterprise system.

Enhancing Lifestyle Change in Cardiac Patients Through the Do CHANGE System ("Do Cardiac Health: Advanced New Generation Ecosystem"): Randomized Controlled Trial Protocol.

BACKGROUND: Promoting a healthy lifestyle (eg, physical activity, healthy diet) is crucial for the primary and secondary prevention of cardiac disease in order to decrease disease burden and mortality. OBJECTIVE: The current trial aims to evaluate the effectiveness of the Do Cardiac Health: Advanced New Generation Ecosystem (Do CHANGE) service, which is developed to assist cardiac patients in adopting a healthy lifestyle and improving their quality of life. METHODS: Cardiac patients (ie, people who have been diagnosed with heart failure, coronary artery disease, and/or hypertension) will be recruited at three pilot sites (Badalona Serveis Assistencials, Badalona, Spain [N=75]; Buddhist Tzu Chi Dalin General Hospital, Dalin, Taiwan [N=100] and Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands [N=75]). Patients will be assisted by the Do Something Different (DSD) program to change their unhealthy habits and/or lifestyle. DSD has been developed to increase behavioral flexibility and subsequently adopt new (healthier) habits. In addition, patients' progress will be monitored with a number of (newly developed) devices (eg, Fitbit, Beddit, COOKiT, FLUiT), which will be integrated in one application. RESULTS: The Do CHANGE trial will provide us with new insights regarding the effectiveness of the proposed intervention in different cultural settings. In addition, it will give insight into what works for whom and why. CONCLUSIONS: The Do CHANGE service integrates new technologies into a behavior change intervention in order to change the unhealthy lifestyles of cardiac patients. The program is expected to facilitate long-term, sustainable behavioral change. TRIAL REGISTRATION: Clinicaltrials.gov NCT03178305; https://clinicaltrials.gov/ct2/show/NCT03178305 (Archived by WebCite at http://www.webcitation.org/6wfWHvuyU).

Patient Perspectives on Health Data Privacy and Management: "Where Is My Data and Whose Is It?"

New technologies are increasingly evaluated for use within the clinical practice to monitor patients' medical and lifestyle data. This development could contribute to a more personalized approach to patient care and potentially improve health outcomes. To date, patient perspective on this development has mostly been neglected in the literature. Hence, this study aims to shed more light on the patient perspective on health data privacy and management. Focus groups with cardiac patients were done at the Elizabeth TweeSteden Ziekenhuis (ETZ) in the Netherlands as part of the DoCHANGE project. The focus groups were conducted using a semistructured protocol which was organized around three themes: privacy regulations, data storage, and transparency and privacy management. Five focus groups with a total of 23 patients were conducted. The majority of the patients preferred to have access to their medical data; however, the knowledge on who has access to data was limited. Patients indicated that they do not want to share their medical data with health insurance companies or the pharmaceutical industry. Furthermore, most patients do not see the added value of supplementing their medical dossier with lifestyle data. Current findings showed patients prefer access to and control over own data but that the knowledge concerning data privacy and management is limited. Sharing of non-medical health data (e.g.,, physical activity) was considered unnecessary. Future studies should address patient preferences and develop infrastructure which facilitates medical data access for patients.