Precision Lifestyle Medicine Program for IFHAS Participants
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Precision Lifestyle Medicine Program, Standard IFHAS Care.
- Who it may be relevant to
- Registry conditions: Obese Adults, BMI/Body Composition, Cardiometabolic Risk, Cardiovascular Disease Risk. Basic parameters: 25 years — 50 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United Arab Emirates
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
Application of a Precision Lifestyle Medicine Clinical Program for a Sample of IFHAS Screening Cohort
Overview
The goal of this clinical trial is to evaluate whether a precision lifestyle medicine intervention can improve cardiometabolic health in Emirati adults aged 25 to 50 years living in Abu Dhabi with obesity (BMI 30-35 kg/m²) who have previously completed IFHAS screening. The study will also use IFHAS screening data to better understand participants' health profiles and the relationship between lifestyle factors and chronic diseases. The main questions it aims to answer are: * Does a precision lifestyle medicine program improve cardiometabolic biomarkers after an 18-week intervention? * Can IFHAS screening data be used to identify health risk profiles and support personalized lifestyle interventions for the Emirati population? Researchers will compare participants receiving the precision lifestyle medicine intervention with a propensity-matched control group receiving standard IFHAS care to determine whether the intervention leads to greater improvements in cardiometabolic health. Participants will: * Take part in an 18-week personalized lifestyle medicine program tailored to their health profile. * Attend study visits and complete health assessments over a total study period of 24 weeks. * Undergo cardiometabolic biomarker assessments before and after the intervention. * Complete questionnaires or assessments about their adherence to the lifestyle program and their experience with the precision lifestyle medicine clinic. * Provide biological samples to support the establishment of a biomarker repository for future research.
Detailed description
This study is a prospective clinical trial designed to evaluate the effectiveness of a precision lifestyle medicine program in improving cardiometabolic health among Emirati adults with obesity. The study also aims to use data collected through the IFHAS screening program to better understand the current health status, disease risk profiles (pathophenotypes), and associations between lifestyle factors and chronic diseases within the Emirati population.
A total of 150 eligible participants will be enrolled to receive an individualized precision lifestyle medicine intervention. Their outcomes will be compared with those of 150 propensity score-matched individuals selected from the IFHAS database who receive standard IFHAS care. The intervention is designed to provide personalized lifestyle recommendations based on each participant's clinical characteristics and health profile.
Eligible participants are Emirati adults aged 25 to 50 years who reside in the Emirate of Abu Dhabi, have a body mass index (BMI) between 30 and 35 kg/m², are Thiqa cardholders, have completed at least one IFHAS screening, are enrolled in the Emirati Genome Programme, and are able to provide informed consent. Individuals receiving weight-loss medications, those with certain medical conditions or physical limitations that may interfere with participation, pregnant women, and individuals enrolled in other lifestyle intervention programs are excluded.
Recruitment will occur on a rolling basis until the target sample size of 150 participants is reached. Each participant will be involved in the study for approximately 24 weeks, including an 18-week precision lifestyle medicine intervention and follow-up assessments.
The primary objectives of the study are to:
* Use IFHAS screening data to stratify health risks, characterize the current health status and pathophenotypes of the Emirati population, and examine associations between lifestyle factors and chronic diseases. * Design and implement a precision lifestyle medicine program for eligible participants. * Evaluate changes in cardiometabolic biomarkers following completion of the intervention.
The secondary objectives are to:
* Assess participants' adherence to the recommended lifestyle intervention program. * Evaluate participants' experiences with the precision lifestyle medicine clinical program. * Establish a structured biomarker repository to support future exploratory and hypothesis-generating research.
Study assessments will include measurements of cardiometabolic biomarkers before and after the intervention. Participants may also undergo additional clinical assessments and complete questionnaires related to adherence and their experience with the intervention program. Biological samples collected during the study will contribute to the development of a biomarker repository for future research, in accordance with applicable ethical and regulatory requirements.
The study will be conducted in accordance with the Department of Health (DoH)-approved protocol, the Declaration of Helsinki, the International Council for Harmonisation Good Clinical Practice (ICH-GCP) guidelines, and all applicable national laws and regulations
Interventions
- Behavioral Precision Lifestyle Medicine Program
Participants receive an 18-week precision lifestyle medicine intervention based on individual IFHAS screening results and cardiometabolic risk stratification. The program includes personalized lifestyle recommendations and multidisciplinary clinical support focused on improving cardiometabolic health. Participants are followed for 24 weeks, with assessments conducted at baseline and post-intervention. - Other Standard IFHAS Care
Participants receive standard IFHAS care without participation in the precision lifestyle medicine intervention. This group serves as a propensity score-matched comparison cohort.
Primary outcome measures
- Change in Body Mass Index (BMI) [Time frame: Baseline and Week 24]
- Change in Cardiometabolic Composite Response [Time frame: 24 weeks]
Secondary outcome measures (9)
- High responder rate [Time frame: 24 weeks]
- Change in body weight [Time frame: baseline to week 24]
- Change in HbA1c [Time frame: Baseline to Week 24]
- Change in ApoB [Time frame: Baseline to Week 24]
- VO₂peak [Time frame: Baseline to Week 24]
- Change in 10-year cardiovascular disease risk [Time frame: Baseline to Week 24]
- Change in 10-year type 2 diabetes risk [Time frame: Baseline to Week 24]
- Participant commitment to the intervention [Time frame: Throughout the intervention (up to Week 24)]
- Participant experience [Time frame: Week 24]
Eligibility criteria
Inclusion criteria
- Emiratis residing in Abu Dhabi emirate
- Aged 25-50 years
- BMI 30-35 kg/m²
- Thiqa cardholder
- Previous participation in IFHAS screening
- Able to provide informed consent
- Participant in the Emirati Genome Programme
- No weight-loss medications (e.g., Ozempic, Saxenda, Wegovy) within 3 months of enrollment.
Exclusion criteria
- Aged under 25 years or over 50 years of age
- BMI range under 30 kg/m2 and over 35 kg/m2
- Taking weight loss medication such as GLP-1 drugs (Ozempic, Saxenda, Wegovy)
- Active treatment for serious medical conditions (cancer, planned surgery, immunomodulation)
- Transplant surgery within 12 months
- Pregnancy
- Surgery within 3 months prior to recruitment
- Physical limitations preventing exercise participation
- Current enrolment in other lifestyle intervention programs
- Active psychiatric conditions, cognitive impairment, or mental health conditions affecting study participation
- Contraindication to MRI or DEXA imaging, including severe claustrophobia or need for sedation.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Non-randomized
- Model
- Parallel assignment
- Masking
- Open label
- Primary purpose
- Treatment
Study locations
United Arab Emirates · 1 center
- Institute for Healthier Living — Abu Dhabi
Publications
- Fitzgerald KN, Hodges R, Hanes D, Stack E, Cheishvili D, Szyf M, Henkel J, Twedt MW, Giannopoulou D, Herdell J, Logan S, Bradley R. Potential reversal of epigenetic age using a diet and lifestyle intervention: a pilot randomized clinical trial. Aging (Albany NY). 2021 Apr 12;13(7):9419-9432. doi: 10.18632/aging.202913. Epub 2021 Apr 12. PMID 33844651
- Reicher L, Bar N, Godneva A, Reisner Y, Zahavi L, Shahaf N, Dhir R, Weinberger A, Segal E. Phenome-wide associations of human aging uncover sex-specific dynamics. Nat Aging. 2024 Nov;4(11):1643-1655. doi: 10.1038/s43587-024-00734-9. Epub 2024 Nov 5. PMID 39501126
- Lee S, Lee S, Kim Y, et al. A deep learning model for biological age prediction using comprehensive health check-up data: A retrospective cohort study. Aging (Albany NY). 2023;15(15):7519-7539.
- Pinu FR, Beale DJ, Zwart P, et al. A random forest-based approach for the identification of diagnostic biomarkers for heart failure from gene expression data. Front Mol Biosci. 2020;7:139.
- Alanazi SA, Kamruzzaman MM, Alruwaili M, et al. A machine learning-based approach for the prediction of cardiometabolic disease risk in students. Int J Environ Res Public Health. 2021;18(11):5649.
- Ambrose M, Mitmesser SH, Sesso HD, et al. Use of reduced rank regression and random forest to identify dietary patterns associated with cardiometabolic risk. Curr Dev Nutr. 2017;1(6):e000782.
- Georga EI, Protopappas VC, Yaluri N, et al. A machine learning approach for predicting non-responders to a lifestyle intervention for prediabetes. Sensors (Basel). 2021;21(6):2082.
- Gárate-Escamila AK, El-Guindy A, Tamez-Peña JG. Machine learning for diabetes and hypertension classification in the Mexican population. J Healthc Eng. 2020;2020:8839074.
Identifiers
NCT: NCT07742917 · DOH/ADHRTC/2026/1867