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.
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 Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Enrollment
120
Precision health
Centre for lifestyle intervention
Gothenburg, Sweden
Change in body weight 1
Reduction in body weight (kg) in percent will be identified by using Lidén weighing scale.
Time frame: From baseline to 6 months
Change in body weight 2
Reduction in body weight (kg) in percent will be identified by using Lidén weighing scale. Less weight at the 1-month follow-up than at baseline is a better outcome than vice versa.
Time frame: From baseline to 1 month (intervention group)
Change in body weight 3
Reduction in body weight (kg) in percent will be identified by using Lidén weighing scale. Less weight at the 3-month follow-up than at the 1-month follow-up is a better outcome than vice versa.
Time frame: From 1 month to 3 months (intervention group)
Change in body weight 4
Reduction in body weight (kg) in percent will be identified by using Lidén weighing scale. Less weight at the 6-month follow-up than at the 3-month follow-up is a better outcome than vice versa.
Time frame: From 3 months to 6 months (intervention group)
Length in cm
Length will be combined with height to report body mass index (BMI) in kg/m\^2.
Time frame: From baseline to 6 months
Weight in kilograms
Weight will be combined with height to report body mass index (BMI) in kg/m\^2.
Time frame: From baseline to 6 months
Cardiovascular disease risk factor change - Body Mass Index (BMI)
Reduction in BMI will be identified by using Lidén weighing scale and seca length gauge and the formula: BMI = kg/m2 where kg is a person's weight in kilograms and m2 is their height in metres squared. BMI \<18.5: underweight. BMI 18.5-24.9: normal weight. BMI ≥25.0: overweight. BMI ≥30.0: obesity (World Health Organization).
Time frame: From baseline to 6 months
Cardiovascular disease risk factor change - Waist-to-hip ratio 1
Waist-hip-ratio will be identified by using a measure and by dividing waist circumference (cm) at its narrowest point by hip circumference at the widest point (cm). A reduction in waist-hip ratio is a better outcome than vice versa.
Time frame: From baseline to 6 months
Cardiovascular disease risk factor change - Waist-to-hip ratio 2
Waist-to-hip ratio will be identified by using a measure and by dividing waist circumference (cm) at its narrowest point by hip circumference at the widest point (cm). A reduction in waist-hip ratio is a better outcome than vice versa.
Time frame: From baseline to 1 month (intervention group)
Cardiovascular disease risk factor change - Waist-to-hip-ratio 3
Waist-to-hip ratio will be identified by using a measure and by dividing waist circumference (cm) at its narrowest point by hip circumference at the widest point (cm). A reduction in waist-hip ratio is a better outcome than vice versa.
Time frame: From 1 month to 3 months (intervention group)
Cardiovascular disease risk factor change - Waist-hip-ratio 4
Waist-to-hip ratio will be identified by using a measure and by dividing waist circumference (cm) at its narrowest point by hip circumference at the widest point (cm). A reduction in waist-hip ratio is a better outcome than vice versa.
Time frame: From 3 months to 6 months (intervention group)
Cardiovascular disease risk factor change - Blood pressure 1
Systolic and diastolic blood pressure (mm Hg) will be identified by using Welch Allyn Blood Pressure Monitors. A reduction i blood pressure levels is a better outcome than vice versa.
Time frame: From baseline to 6 months
Cardiovascular disease risk factor change - Blood pressure 2
Systolic and diastolic blood pressure (mm Hg) will be identified by using Welch Allyn Blood Pressure Monitors. A reduction i blood pressure levels is a better outcome than vice versa.
Time frame: From baseline to 1 month (intervention group)
Cardiovascular disease risk factor change - Blood pressure 3
Systolic and diastolic blood pressure (mm Hg) will be identified by using Welch Allyn Blood Pressure Monitors. A reduction i blood pressure levels is a better outcome than vice versa.
Time frame: From 1 month to 3 months (intervention group)
Cardiovascular disease risk factor change - Blood pressure 4
Systolic and diastolic blood pressure (mm Hg) will be identified by using Welch Allyn Blood Pressure Monitors. A reduction i blood pressure levels is a better outcome than vice versa.
Time frame: From 3 month to 6 months (intervention group)
Cardiovascular disease risk factor change - Long-term blood glucose control using glycated haemoglobin (HbA1c)
Reduction of HbA1C values will be identified by blood samples. A normal HbA1C will be below 42 mmol/mol (below 6%). Prediabetes will be referred to 42-47 mmol/mol and 6.0 to 6.4%. Diabetes will be identified as a HbA1C of 48 mmol/mol or over and 6.5%.
Time frame: From baseline to 6 months
Cardiovascular disease risk factor change - Serum (total) Cholesterol (S-Cholesterol)
Reduction of S-Cholesterol will be identified by blood samples. A S-cholesterol below 200 mg/dL is ideal, from 200 to 239 mg/dL is borderline high and 240 mg/dL and over is high.
Time frame: From baseline to 6 months
Cardiovascular disease risk factor change - High density lipoprotein (HDL)
Rise of HDL levels will be identified by blood samples. A value of 50+ mg/dL indicates less risk
Time frame: From baseline to 6 months.
Cardiovascular disease risk factor change - Low densitiy lipoprotein (LDL)
A reduction in LDL levels will be identified by blood samples. LDL should be below 130 mg/dL.
Time frame: From baseline to 6 months.
Cardiovascular disease risk factor change - Triglycerides
A decrease in mg/dL will be identified by blood samples. A healthy level for adult is below 150 mg/dL.
Time frame: From baseline to 6 months.
Cardiovascular disease risk factor change - Aerobic fitness (predicted V02 max)
An increase in predicted maximal oxygen uptake capacity will be identified by using the Ekblom-Bak test.
Time frame: From baseline to 6 months.
Cardiovascular disease risk factor change - Physical activity level
An increase in physical activity time spent at a higher intensity level will be identified using accelerometry data.
Time frame: From baseline to 6 months
Change in functional lower extremity muscle strength
Number of sit-to-stand test during 30 s. A higher number means a better outcome.
Time frame: From baseline to 6 months
Change in upper extremity muscle strength - Hand grip strength
The mean hand grip strength in kg for the right and left hands will be registered using the Jamar hand dynamometer. Participants will be asked to perform three attempts per hand (alternating between left and right hand). The participants will be seated, and the performance will be completed with the elbow in 90° flexion and with a straight wrist. The more kg, the better the outcome.
Time frame: From baseline to 6 months
Change in muscle strength - Shoulder flexion
Shoulder flexion -The participants will be asked to move a dumbbell (3 kg for men, 2 kg for women) up and down with a straight arm between 0 and 90 degrees of shoulder flexion. A metronome set at 40 beats/minute, i.e., 20 contractions/minute, will keep everyone at the same pace. The test will be interrupted if the participant does not reach 90 degrees of shoulder flexion, performs the movement with a flexed elbow, or cannot keep up the pace. The maximal number of repetitions will be recorded. The more repetitions, the better the outcome.
Time frame: From baseline to 6 months
Change in muscle strength - Ankle Plantar
Standing Heel-Rise Test for Ankle Plantar - The number of maximal heel lifts for each leg with the participant standing on a 10° wedge will be recorded, with one lift every other second (i.e., 30 heel rises/min) using a metronome. The participants will be allowed to contact the wall for balance, and on each rise, the head must touch a marking on a calibrated measuring stick. The opposing foot will be elevated slightly above the floor. The test will be terminated if the knee on the tested leg is bent or if the research subject is unable to perform the test.The higher number of heel lifts, the better the outcome.
Time frame: From baseline to 6 months
Cardiovascular disease risk factor change - Healthy food intake
Healthy food intake will be measured using the Meal-Q web-based food frequency questionnaire. Healthy food intake is determined with a Healthy Food Index (HFI) as an aggregated composite score. The selected food items are important indicators of a healthy food intake behavior (vegetables, fruits and berries, nuts, vegetable oils, fatty fish). The higher the score of HFI, the better the outcome.
Time frame: From baseline to 6 months
Change in resting energy expenditure 1
Resting energy expenditure (REE) will be determined from measured oxygen uptake and the carbon dioxide during 20 minutes at rest in a lying position. The first 5 minutes of data will be excluded from the analysis. The 2-5 minutes with the lowest data and the lowest data variation, with a variation \<10%, will be used in the analysis. Energy expenditure will be calculated as: REE (kcal/) = 3.9 x O2 (L) + 1.1 x CO2 (L). REE is connected to energy intake. A too restrictive intake with the aim of reducing body weight may lower REE and counteract metabolism of body fat and weight reduction. Physical activity may increase muscle mass and consequently increase REE. Unchanged or increased REE is a positive outcome.
Time frame: From baseline to 6 months
Change in resting energy expenditure 2
Resting energy expenditure (REE) will be determined from measured oxygen uptake and the carbon dioxide during 20 minutes at rest in a lying position. The first 5 minutes of data will be excluded from the analysis. The 2-5 minutes with the lowest data and the lowest data variation, with a variation \<10%, will be used in the analysis. Energy expenditure will be calculated as: REE (kcal/) = 3.9 x O2 (L) + 1.1 x CO2 (L). REE is connected to energy intake. A too restrictive intake with the aim of reducing body weight may lower REE and counteract metabolism of body fat and weight reduction. Physical activity may increase muscle mass and consequently increase REE. Unchanged or increased REE is a positive outcome.
Time frame: From baseline to 1 month (intervention group)
Change in resting energy expenditure 3
Resting energy expenditure (REE) will be determined from measured oxygen uptake and the carbon dioxide during 20 minutes at rest in a lying position. The first 5 minutes of data will be excluded from the analysis. The 2-5 minutes with the lowest data and the lowest data variation, with a variation \<10%, will be used in the analysis. Energy expenditure will be calculated as: REE (kcal/) = 3.9 x O2 (L) + 1.1 x CO2 (L). REE is connected to energy intake. A too restrictive intake with the aim of reducing body weight may lower REE and counteract metabolism of body fat and weight reduction. Physical activity may increase muscle mass and consequently increase REE. Unchanged or increased REE is a positive outcome.
Time frame: From 1 month to 3 months (intervention group)
Change in resting energy expenditure 4
Resting energy expenditure (REE) will be determined from measured oxygen uptake and the carbon dioxide during 20 minutes at rest in a lying position. The first 5 minutes of data will be excluded from the analysis. The 2-5 minutes with the lowest data and the lowest data variation, with a variation \<10%, will be used in the analysis. Energy expenditure will be calculated as: REE (kcal/) = 3.9 x O2 (L) + 1.1 x CO2 (L). REE is connected to energy intake. A too restrictive intake with the aim of reducing body weight may lower REE and counteract metabolism of body fat and weight reduction. Physical activity may increase muscle mass and consequently increase REE. Unchanged or increased REE is a positive outcome.
Time frame: From 3 months to 6 months (intervention group)
Change in respiratory quotient 1
Oxygen uptake (O2) and carbon dioxide production (CO2) will be measured during 20 minutes at rest in a lying position. The first 5 minutes of data will be excluded from the analysis. The 2-5 minutes with the lowest data and the lowest data variation, with a variation \<10%, will be used in the analysis. Respiratory quotient (RQ) is determined as the quotient CO2/O2 and indicates the proportion carbohydrate, fat and protein used as energy substrate. A value of 1.0 indicates only carbohydrate used and a value of 0.7 indicates only fat used. With a mixed food intake, the normal value range between 0.8-0.9. If an increase fat metabolism is induced by energy restriction, the RQ will be reduced. A reduced or maintained lower RQ (below 0.8) is a positive outcome.
Time frame: From baseline to 6 months
Change in respiratory quotient 2
Oxygen uptake (O2) and carbon dioxide production (CO2) will be measured during 20 minutes at rest in a lying position. The first 5 minutes of data will be excluded from the analysis. The 2-5 minutes with the lowest data and the lowest data variation, with a variation \<10%, will be used in the analysis. Respiratory quotient (RQ) is determined as the quotient CO2/O2 and indicates the proportion carbohydrate, fat and protein used as energy substrate. A value of 1.0 indicates only carbohydrate used and a value of 0.7 indicates only fat used. With a mixed food intake, the normal value range between 0.8-0.9. If an increase fat metabolism is induced by energy restriction, the RQ will be reduced. A reduced or maintained lower RQ (below 0.8) is a positive outcome.
Time frame: From baseline to 1 month (intervention group)
Change in respiratory quotient 3
Oxygen uptake (O2) and carbon dioxide production (CO2) will be measured during 20 minutes at rest in a lying position. The first 5 minutes of data will be excluded from the analysis. The 2-5 minutes with the lowest data and the lowest data variation, with a variation \<10%, will be used in the analysis. Respiratory quotient (RQ) is determined as the quotient CO2/O2 and indicates the proportion carbohydrate, fat and protein used as energy substrate. A value of 1.0 indicates only carbohydrate used and a value of 0.7 indicates only fat used. With a mixed food intake, the normal value range between 0.8-0.9. If an increase fat metabolism is induced by energy restriction, the RQ will be reduced. A reduced or maintained lower RQ (below 0.8) is a positive outcome.
Time frame: From 1 month to 3 months (intervention group)
Change in respiratory quotient 4
Oxygen uptake (O2) and carbon dioxide production (CO2) will be measured during 20 minutes at rest in a lying position. The first 5 minutes of data will be excluded from the analysis. The 2-5 minutes with the lowest data and the lowest data variation, with a variation \<10%, will be used in the analysis. Respiratory quotient (RQ) is determined as the quotient CO2/O2 and indicates the proportion carbohydrate, fat and protein used as energy substrate. A value of 1.0 indicates only carbohydrate used and a value of 0.7 indicates only fat used. With a mixed food intake, the normal value range between 0.8-0.9. If an increase fat metabolism is induced by energy restriction, the RQ will be reduced. A reduced or maintained lower RQ (below 0.8) is a positive outcome.
Time frame: From 3 months to 6 months (intervention group)
Change in health-related quality of life - Proportions of problems in five dimensions
HRQoL will be assessed using the EuroQoL five dimensions (5D) and three levels (3L), i.e.,the EQ-5D-3L questionnaire.The proportions of "no problems", "moderate problems" and "extreme problems and the EQ-5D-3L value index for each of the five dimensions will be registered for baseline and the 6-month follow-up. The higher proportion of participants with no problems, the better the outcome. The EuroQol Group Association comprises an international network of multidisciplinary researchers.
Time frame: From baseline to 6 months
Change in health-related quality of life - Index score
The health state of each participant will be converted into the EuroQoL: EQ-5 dimensions and 3 levels (i.e., the EQ-5D-3L) value index, a score between 0 and 1. A higher index score means a better outcome as an index score of 0 means death and an index score of 1 means complete health. Values less than 0 indicate health states worse than death. The EuroQol Group Association comprises an international network of multidisciplinary researchers.
Time frame: From baseline to 6 months
Change in health-related quality of life - Visual analog score of present health status
The participants will also be asked to score their self-perceived present health status using the EuroQoL Visual Analog Scale (i.e. the EQ-VAS). The EQ-VAS is a vertical scale ranging from 0, "The worst health you can imagine" to 100, "The best health you can imagine". That is, a higher score means a better outcome. The EuroQol Group Association comprises an international network of multidisciplinary researchers.
Time frame: From baseline to 6 months
Change in health-related quality of life - Health status categories
The EuroQoL Visual Analog Scale (i.e., the EQ-VAS) scores will also be presented related to health status categories (very poor health, poor health, fair health, good health, and very good health).The higher EQ-VAS score, the better the outcome. The EuroQol Group Association comprises an international network of multidisciplinary researchers.
Time frame: From baseline to 6 months
Change in self-reported physical activity level
Self-reported physical activity level will be assessed using the Saltin-Grimby Physical Activity Level Scale (i.e., the SGPALS). The SGPALS is a self-reporting scale with response categories that ranges from 1 to 4. A higher values refers to a higher level of self-reported physical activity level. A higher value at the 6-month follow-up than at the baseline is a better outcome than vice versa.
Time frame: From baseline to 6 months
Change in exposure pattern to the food environment
Outlet density and quality will be recorded within the individual food environment using Global Positioning System (GPS) and Geographical Information System (GIS). Outlet quality refers to type of outlet, e.g. fast-food restaurants, full-service restaurants, bakeries, coffee shops, supermarkets, convenience stores, department stores, gas stations, fruit- and vegetable stores and markets. The individual food environment will cover 1) neighborhood area, 2) daily path area, and 3) work/school area. The individual will have a movement pattern within the individual food environment connected with a specific exposure to the different outlets. Change in individual exposure pattern will be used as outcome measure. The change in the individual exposure pattern will be related to change in the food pattern determined with the Meal-Q food frequency questionnaire. A change in the exposure pattern that is related to a healthier food pattern is a positive outcome of the study.
Time frame: From baseline to 6 months
Change in exposure pattern to the built environment
The built environment density and quality will be recorded within the individual food environment using Global Positioning System (GPS) and Geographical Information System (GIS). Density and quality refers to number and type of conditions promoting a physical activity, e.g. green areas, in- and outdoor gyms, places for spontaneous sport, walking and bike lanes, and other recreational spaces. The individual built environment will cover 1) neighborhood area, 2) daily path area, and 3) work/school area. The individual will have a movement pattern within the individual built environment connected with a specific exposure to the different conditions. Change in individual exposure pattern will be used as outcome measure. The change in the individual exposure pattern will be related to change in physical activity level. A change in the exposure pattern that is related to a increased physical activity level is a positive outcome of the study.
Time frame: From baseline to 6 months
Process evaluation measure 1 - Extent to which intervention was implemented as planned
The intervention offers: 1. Start meeting with medical feedback, physical activity and diet advises, and information and planning of intervention components 2. Individual lifestyle counselling meetings of longer duration based on individual measures of physical activity, aerobic fitness, energy requirement and support from a physical activity and food app 3. Individual lifestyle followup meetings of shorter duration 4. Supervised aerobic and strength exercise 5. Lifestyle school with different contents (group sessions) 6. Information about other lifestyle tools and activities available in the region 7. Followup measurement sessions of anthropometry, resting energy expenditure, respiratory quotient and blood pressure The process evaluation measure 1 determines the number of these components implemented as planned.
Time frame: During the 6 months intervention (intervention group)
Process evaluation measure 2 - Number of sessions of each intervention component delivered
1. Start meeting - 1 session 2. Individual lifestyle counselling meeting - 4 longer sessions of 60 minutes each 3. Individual lifestyle followup meeting - up to 8 shorter sessions of up to 30 minutes each 4. Supervised aerobic and strength exercise - twice a week each 5. 5 different lifestyle school sessions for each participant 6. Information about other lifestyle tools and activities at the start meeting 7. Followup measurement of anthropometry, resting energy expenditure, respiratory quotient and blood pressure after 1 month, 3 months and 6 months Process evaluation measure 2 quantifies the number of sessions delivered of each of 7 intervention components.
Time frame: During the 6 months intervention (intervention group)
Process evaluation measure 3 - Number of sessions of each intervention component received
1. Start meeting - 1 session 2. Individual lifestyle counselling meeting - 4 longer sessions of 60 minutes each 3. Individual lifestyle followup meeting - up to 8 shorter sessions of up to 30 minutes each 4. Supervised aerobic and strength exercise - twice a week each 5. 5 different lifestyle school sessions for each participant 6. Information about other lifestyle tools and activities at the start meeting 7. Followup measurement of anthropometry, resting energy expenditure, respiratory quotient and blood pressure after 1 month, 3 months and 6 months Process evaluation measure 3 quantifies the number of sessions delivered of each of 7 intervention components that each participant took part of.
Time frame: During the 6 months intervention (intervention group)
Process evaluation measure 4 - Satisfaction with individual lifestyle counselling
Process evaluation measure 4 attempts to provide an overall view of the participant satisfaction with the individual lifestyle counselling. It combines categorial with open-ended (free text) questions to determine: 1. Support to weight reduction: yes/no 2. In what way: free text 3. Provided tool to behavior change: agree, agree partly, disagree 4. More meetings: yes/no 5. Suggestions of improvement: free text The questions provide together an overall degree of satisfaction with the individual counseling and contribution to behavioral change and weight reduction.
Time frame: After 6 months intervention (intervention group)
Process evaluation measure 5 - Satisfaction with the lifestyle school
Process evaluation measure 5 attempts to provide an overall view of the participant satisfaction with the lifestyle school. It combines categorial with open-ended (free text) questions to determine: 1. Support to weight reduction?: yes/no 2. In what way?: free text 3. Which of the 5 different lifestyle schools have provide most aid?: check one or several of the 5 different lifestyle school 4. Provided tools to behavior change?: agree, agree partly, disagree 5. More sessions?: yes/no 6. Suggestions of improvement?: free text The questions provide together an overall degree of satisfaction with the lifestyle school and contribution to behavioral change and weight reduction.
Time frame: After 6 months intervention (intervention group)
Process evaluation measure 6A - Perceived facilitators
A qualitative interview with open-ended questions will be performed at the end of the intervention to identify facilitators for lifestyle behavior change and weight reduction.
Time frame: After 6 months intervention (intervention group)
Process evaluation measure 6B - Perceived barriers
A qualitative interview with open-ended questions will be performed at the end of the intervention to identify facilitators for lifestyle behavior change and weight reduction.
Time frame: After 6 months intervention (intervention group)
Process evaluation measure 7 - Reach
Process evaluation measure 7 assesses the participation rate at each step of the study: 1) Recruitment; 2) Screening; 3) Baseline; 4) Medical evaluation; 5) Allocation; 6) Intervention period (intervention component and sessions, measurement sessions); 7) 6 months followup measurements. It also assesses characteristics of completers at each step versus non-completers.
Time frame: From start of recruitment to end of 6 months followup measurements
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.