Obesity, Physical Activity
Conditions
Keywords
Exercise, Actigraphy, Prevention and Control, Cardiorespiratory Fitness
Brief summary
A high physical fitness can prevent cardiovascular disease. Which form of exercise training is efficient at improving fitness is well known. The challenge is to get people to do it. Personal activity intelligence (PAI) is an algorithm developed for this challenge. It gives a score that tells the users whether they are active enough to achieve the maximum health benefit of exercise based on their heart rate. It has been shown that people who obtain 100 PAI a week have less cardiovascular disease, but intervention studies showing that PAI can improve physical fitness are so far lacking. Step counters have received a lot of attention and 10 000 steps a day is a common recommendation, but little is known about the physiological adaptations to this intervention. This study will compare the effect of physical activity with a value of 100 PAI points a week with 10 000 steps a day in healthy, but overweight (body mass index \> 25) participants between 30 and 50 years of age.
Interventions
BEHAVIORALpersonal activity intelligence
Participants randomized to the PAI intervention will receive a Mio Slice fitness bracelet and asked to install the Mio Pai 2.0 app on their smart phone. This tracks their fitness score based on the PAI algorithm where the goal is to maintain 100 PAI points a week. PAI is earned incrementally based on time spent in three different heart rate zones, low, medium and high intensity. PAI is recorded every day and added to the weekly total and the PAI earned on the same day the previous week is deleted (on Tuesday, the PAI earned the previous Tuesday will disappear). Participants will be encouraged to maintain 100 PAI during the 8 weeks intervention by telephone messages (sms).
BEHAVIORAL10,000 steps daily
Participants randomized to the 10,000 step intervention will receive a fit bit zip step counter and asked to obtain 10.000 steps per day. Participants will be encouraged to obtain 10.000 steps per day by telephone messages (sms).
Sponsors
Norwegian University of Science and Technology
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
30 Years to 50 Years
Healthy volunteers
No
Inclusion criteria
* Body mass index (BMI) \> 25 * Low physical activity (less than 50 PAI points calculated from a questionnaire)
Exclusion criteria
* Cancer diagnosis * Cardiac arrhythmia * Angina * Previous myocardial infarction * lung disease * heart disease * uncontrolled hypertension * kidney disease * orthopedic or neurological limitations * planned surgery during the intervention * participation in other research studies conflicting with the current study
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Maximal oxygen uptake | After the intervention period (8 weeks) | The highest amount of oxygen the body can take up, achieved at maximal exercise at the end of an incremental treadmill test measured through ergospirometry. The difference between the two groups post-intervention will be used, while controlling for a pre-intervention value. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Body composition | After intervention period (8 weeks) | Body mass, fat mass and lean mass will be measured using a bio impedance analysis which weighs the participants and uses bio impedance to also assess fat mass and lean mass. The difference between the two groups post-intervention will be used, while controlling for a pre-intervention value. |
Countries
Norway
Outcome results
None listed