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Clinical Trial Summary

The aim of this pilot randomized controlled trial LI-PAD is to identify whether a 6-month intervention approach to individually optimize lifestyle behavior, physical activity, and diet, is feasible and leads to larger improvements in body weight, cardiovascular disease risk factors, and health-related quality of life compared to simple written lifestyle advice, in individuals with overweight or obesity. The intervention group will be offered individual support for lifestyle behavioral change (precision health) and the control group will be offered written lifestyle advice, following national recommendations. In total, 60 population-based participants and 60 controls from the Gothenburg area, aged 45-65 years, will be recruited.


Clinical Trial Description

Individualized lifestyle Intervention with Physical Activity and Diet as precision health in individuals with overweight: a 6-month pilot randomized controlled trial (LI-PAD) BACKGROUND Individuals with obesity and type 2 diabetes have an increased risk of cardiovascular disease (CVD). Lifestyle changes with physical activity (PA) and diet have been associated with temporary improvements in these risk factors. However, sustained behavior changes are difficult to achieve. In Sweden and globally, the built environment promotes overweight and obesity through high availability of cheap ultra-processed energy-dense foods and drinks and low possibility of physical activity. Although the recommendation is to apply an individualized approach, few studies have applied this in clinical practice. PA on prescription, using an individualized approach, has been partly implemented into Swedish health care, resulting in short- and long-term favorable effects of PA. However, an individualized approach to modifying diet has not yet been incorporated, despite evidence showing that interventions targeting PA and diet together have a greater effect on obesity. Another crucial limitation is that PA and diet recommendations are not developed for individual application. Previous research has shown that it is important to consider individual adaption to medical conditions (e.g. risk profile, symptoms, comorbidities) and to psychosocial factors (e.g. preferences, barriers-facilitators, readiness-to-change). It is also know that individuals require support for behavioral change (e.g., counseling/coaching, group activities, education, nudging). Furthermore, there is a link between unhealthy food environments, unhealthy food consumptions, and food-related diseases, but results vary. Previous intervention studies have shown that an unhealthy food environment is a barrier of adherence to intended behavioral changes. However, it is unclear which components are particularly important, how much of each of them should be included, and whether freedom of choice is a more efficient option compared to offering a more standardized solution as in most randomized controlled trials (RCTs). To prescribe optimal PA for the underlying disease, the investigators are currently developing accelerometer-based PA measures and recommendations adapted to individual fitness. The optimal diet prescription targets weight reduction, primarily as body fat, by restriction energy intake below the energy need. Although rapid early weight loss is important for sustained effects, too great energy restriction (due to unrealistic goals or applying a standard treatment) results in increased hunger and reduced metabolism, not leading to larger weight reduction when clinically applied. Research supports up to 10% weight loss at 6 months by applying a ~500 kcal/d reduction of energy intake below energy need. Energy need is most accurately determined with the doubly labeled water method but is too expensive for clinical use. An alternative method commonly used is to determine resting energy expenditure (REE), calculated from individual characteristics such as body weight, and multiplied with a factor for the PA level. However, REE determined using body weight is not accurate in obesity, and the most optimal equation considering body composition is too imprecise at an individual level. REE based on measured oxygen (O2) and carbon dioxide (CO2) exchange is preferred and can also be used to monitor the respiratory quotient (RQ=CO2/O2), which is an indicator of fat metabolism. Measured O2 and CO2 are inexpensive and can be used together with measured food intake for more individualized diet prescription and to track the effects of the intervention on metabolism and use of body fat. The present study represents a unique progress of lifestyle intervention programs away from the more standardized randomized controlled trials to approach precision health:1) adaption to medical conditions and psychosocial factors, 2) individualized PA and diet advice based on individual and environmental measurement, 3) aids for achieving goals using education, skills training and supports (Figure 1). Although individual adaptions to medical conditions and psychosocial factors are already performed in health care, individualization of PA, diet, and support for behavioral change has rarely been implemented and evaluated. This individualization requires additional resources in health care. Therefore, it is important to determine the benefits of this approach and in future studies also follow up with cost-benefit analyses. Previous received funding from the Swedish Heart-Lung Foundation for two successive research projects, "Aerobic fitness for cardiovascular health - a Swedish CArdioPulmonary bioimage study (SCAPIS)" targeting improved physical activity recommendations (20180379) and "Individualized physical activity recommendations for cardiovascular health: a SCAPIS program in precision health" (20210270),is the foundation for refined individualized exercise prescriptions, using the individual fitness levels. Knowledge from this research forms an important part of our current individualized lifestyle intervention program. OBJECTIVES - PARADIGM AND HYPOTHESES This pilot study aims to identify whether an approach to optimize lifestyle behavior interventions with PA and diet at an individual environmental level leads to larger improvements in body weight, CVD risk factors, and health-related quality of life compared to simple lifestyle advice, and is feasible, in overweight individuals. The hypothesis is that the precision health approach is feasible and superior to simple lifestyle advice. The knowledge gained will be used to design a larger long-term intervention study. The paradigm "one size fits all" is not optimal, why our paradigm shift towards precision health is required. Work plan - Overview LI-PAD is a randomized controlled trial with two arms (Figure 2). The intervention group will be offered individual precision health (Figure 1) and the control group usual care, defined as written lifestyle advice based on the general recommendations for diet and PA. In total, 60 population-based participants and 60 controls from the Gothenburg area will be recruited. LI-PAD includes outcome evaluation on change in body weight (primary outcome), risk factors for CVD, PA, and diet, and quality of life (secondary), process evaluation of feasibility, and identification of barriers and facilitators from qualitative data. PARTICIPANTS Men and women aged 45-65 years will be recruited from the census register in the Gothenburg area and invited by mail. Included are individuals with a body mass index (BMI) of ≥28 and equal to or less than 34. Individuals with known coronary artery disease (clinical symptoms/earlier event) or other contraindications such as inability to understand language or unable to perform lifestyle interventions, will be excluded. OUTCOME MEASURES (Figure 2) PRIMARY OUTCOME (all participants) Weight reduction from 0 to 6 months. SECONDARY OUTCOMES (all participants) 1. CVD risk factor change: weight, BMI, waist and hip circumferences; blood pressure, HbA1c, cholesterol, HDL, LDL; aerobic fitness (VO2max). 2. Physical activity by accelerometry, self-reported physical activity level using the Saltin Grimby Physical Activity Level Scale (SGPALS); muscle strength and endurance; diet pattern by the food frequency questionnaire Meal-Q; and measured REE. 3. Health-related quality of life change using the EuroQol Group's EuroQol Five Dimensions and 3 Levels (EQ5D-3L) index score and EQ-Visual Analogue Scale (VAS). ADDITIONAL OUTCOMES (intervention group) 1. Process evaluation: to determine feasibility of the study by measures of implementation quality, intervention sessions provided, intervention sessions received, satisfaction with intervention components, 2. Qualitative evaluation: perceived barriers and facilitators for behavioral change. INTERVENTION GROUP Figure 1 presents a detailed description of the Lifestyle Intervention with Physical Activity and Diet (LI-PAD) for precision health. CONTROL GROUP - one size fits all (Figure 2) The control group will receive usual care defined as simple lifestyle advice based on the general recommendations for diet and PA, including a healthy and varied diet, at least 300 mins/week of medium-intensity aerobic PA, and resistance training 2 times per week. STATISTICAL ANALYSES Multilevel mixed modeling for repeated measures will be applied, to determine variation both at group and individual levels. Both continuous and categorical variables will be included, therefore both linear and logistic analyses will be employed. Some of the measures may include multiple interrelated categories (e.g., physical activity intensity categories). Therefore, regression models considering multicollinearity will be used (e.g., partial least square modeling). To map interrelationships between intervention components and outcome measures, statistical analyses can be expanded to structural equation modeling with or without partial least square regression for repeated measurement. Peer protocol analyses will be applied. The primary intervention target is the reduction of body weight. The evidence-based and clinically relevant weight change has been determined to be 5-10% at 6 months. In the previous Look Action for Health in Diabetes (AHEAD) study, the mean (SD) % weight change up to one year in the intervention group was 8.5%. The corresponding value in the control group was 0.6 (10)%. Look AHEAD is one of the most comprehensive, and evaluated lifestyle behavior interventions with diet and physical activity. Data from the previous Look AHEAD study were used to estimate the sample size of each group in the present study: To detect a mean (standard deviation, SD) reduction of 5 (10)% in the intervention group relative to the control group (effect size) with 80% power would include at least 60 participants in each group. Our previous extensive research in the field of physical activity and cardiovascular health-epidemiology, measurement, methodology (accelerometry, fitness tests) and clinical aspects are all relevant to the present application. Specifically, the investigators have improved the processing of accelerometer data to useful measures of PA and the statistics to analyze more complex accelerometer data for group differences, individual development over time, and associations with measures of CVD risk. Based on this research, the investigators are currently developing accelerometer-based PA measures and recommendations adapted to individual fitness. COLLABORATORS AND RESEARCH NETWORKS The affiliated research environment offers expertise in methodological, epidemiological, and clinical research. Collaborations and research networks include the SCAPIS, national network for quality and research (SWEDEHEART), and HPI study networks, the Swedish School of Exercise and Sports Science (GIH) as well as the Department of Food and Nutrition, and Sport Science (IKI), with IKI adding knowledge and skills in health promotion and lifestyle behavior change to the project. Group training will be led by physiotherapists at Sahlgrenska University Hospital/Östra. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT06379802
Study type Interventional
Source Vastra Gotaland Region
Contact Mats Börjesson, Professor
Phone +46 31 343 53 98
Email mats.borjesson@gu.se
Status Recruiting
Phase N/A
Start date February 12, 2024
Completion date December 31, 2027

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