| dc.description.abstract | Background
Body composition measures are important because it is known to be associated with the development of several chronic diseases. Describing the distribution of objectively measured body composition in the general population, and if this is related to different physical activity levels, may help to identify subgroups of the population that will benefit from lifestyle interventions.
Purpose
The aim of this study is to describe the variations in body composition measures according to self-reported and device measured physical activity and to assess if adverse body composition levels are associated with physical activity in the population-based HUNT Study.
Method
This study utilized HUNT4 data obtained between 2017-2019. The participants that gave information about self-reported physical activity using HUNT-4 questionnaire 1 were 54527, and 26003 participants had device-measured physical activity up to a week. InBody bioelectrical impedance was used for measuring body composition. Both self-reported and device measured physical activity were divided into three groups: <90 mins, 90-149 mins, and 150+ mins. Linear regression was used to estimate the age and sex adjusted mean difference in body composition measures related to self-reported and device measured physical activity measurements whereas logistic regression was used to estimate the age and sex adjusted odds ratio of adverse body composition levels associated with physical activity. All data were analysed using Stata.
Results
The study found that for device measured physical activity, all the body composition indices were lowest at the highest physical activity level of 150+ mins and highest at the least physical activity level of <90 mins for the linear regression, although the difference in mean was small for skeletal muscle mass, soft lean mass, and fat free mass. For example, the mean difference (with CI) of the body composition from the least to the most active participants decreased by 2.84 (-3.00 to -2.67) for body mass index and 0.33 (-0.56 to -0.09) for soft lean mass. However, for self-report, increased physical activity from <90 mins to 150+ mins was associated with lower body mass index, waist hip ratio, waist circumference, percent body fat, body fat mass, visceral fat level, and visceral fat area and higher soft lean mass, skeletal muscle mass, and fat free mass. In addition, logistic regression showed that for both self-report and device measured physical activity, increased physical activity from the reference group of <90 mins to 150+ mins was associated with a reduced likelihood of adverse body composition levels, body mass index, waist circumference, waist hip ratio, and percent body fat.
Conclusion
There was an association between increased physical activity and lower levels of all body composition variables for device measured physical activity. For self-report, increased physical activity was associated with reduced body mass index, waist hip ratio, waist circumference, percent body fat, body fat mass, visceral fat area, and visceral fat level and increased fat free mass, soft lean mass, and skeletal muscle mass. Moreover, the proportion with adverse body mass index, waist hip ratio, percent body fat, and waist circumference decreased when physical activity increased from <90 mins to 150 mins. | |
