The purpose of this analysis was to compare the strength of associations between three measures of PA in adolescents and biological markers, including blood pressure, HDL-C, %BF and BMI percentile, all of which are physiological markers associated with a variety of chronic diseases. In this study, the choice of PA measurement instrument did not appear to substantially impact the observed relationship between PA and several biological variables regardless of statistical approach. The three measures of PA have relatively low correlations with each other, although statistically significant and in the hypothesized direction with each other and biological markers. Consistently, higher PA was associated with lower %BF. The relationship with BMI percentile is less consistent and may be at least partly attributable to over reporting of PA (3DPAR) and cut-points in dichotomous comparisons (MAQ). No association was found between blood pressure, HDL and PA in this sample. This is an important finding for researchers deciding which instrument to use to measure biological associations with PA.
These findings of the association between PA and biological measures are consistent with previous research.[5
] Evidence suggests that high levels of PA compared to low levels of PA are associated with less adiposity among adolescents.[33
] While Rowlands et al. found a similar association, the authors also reported that the relationship differed by measurement instrument, specifically direct observation versus survey-based instruments,[5
] but no difference was found between the effect of PA on %BF between survey-based instruments and accelerometers. Intervention research suggests that increasing PA will decrease %BF among the treatment group,[35
] consistent with the negative association we observed. To our knowledge, there is no evidence that PA reduces resting blood pressure in normotensive adolescents.[36
] Lipids were another potential biomarker associated with PA, although there was no consistent effect of PA on total cholesterol and LDL-C.[8
] PA does however appear to have a positive effect on HDL-C levels, but the results are somewhat mixed.[8
The average number of daily minutes engaged in MVPA in our sample (accelerometer mean=30.7, SD=16.7) are lower than those found by Troiano (accelerometer mean 12–15 years=45.3, sd=3.4) in a national study, although the variation in our sample is substantially larger and the accelerometer data reduction differed somewhat between studies.[9
] Treating accelerometer data as the criterion measure of PA,[39
] we found that participants over-reported PA on the 3DPAR. When comparing prevalence estimates, ten times as many adolescents were classified as having met recommendations when using the 3DPAR compared to the accelerometer data. Therefore, when estimating the prevalence of PA, the choice of PA instrument is vitally important as all instruments are not equivalent.
The fact that we were able to demonstrate this association regardless of the instrument is useful information for researchers planning studies where the focus is on PA and biological markers. While accelerometers require the most expensive initial financial outlay and ongoing technical and data processing expertise, they can be re-used many times by multiple subjects across numerous studies. On the other hand, the 3DPAR requires only paper and pencils but there is additional cost associated with administering, entering and cleaning the data that also requires personnel and financial resources. The 3DPAR has the added benefit of being able to determine what the participant was doing, which may be important information for interventions focused on increasing PA and decreasing sedentary behavior. Lastly, the two PA questions from the MAQ are the least expensive option since they too require only paper and pencils. Since there are only two questions, data entry and processing requirements are minimal. However, data from these selected MAQ questions are difficult to translate into public health recommendations about meeting PA recommendations of at least 60 minutes of MVPA per day. Yet, despite these limitations, the results indicate that compared to the 3DPAR, the MAQ was closer to the accelerometer for the percentage of adolescents meeting the MVPA recommendations.
The strengths of this analysis included the large sample size, the three measures of PA collected during the same time period for each participant, and the ability to combine two sets of data for a more diverse sample. This study does have limitations. This study is a cross-sectional observational study which prevents causal inference. There are inherent challenges in accelerometer data as well, including the use of different criteria for coding, cut points for hours and days of data required for valid measures, and the conversion to appropriate activity levels. And, accelerometry only captures some types of physical activity. Additionally, we did not measure other aspects of cardiorespiratory fitness, abdominal circumference and other plasma variables. Data currently available through the IDEA and ECHO studies limits our research to cross-sectional analysis; the study designs will allow us to examine the relationships longitudinally once the data is available.
In conclusion, the findings from this analysis suggest that researchers who aim to compare biological markers, specifically %BF, with levels of PA have a range of measurement options as the association remained consistent regardless of instrument. This is useful as the participant burden and cost vary substantially by instrument. However, prevalence estimates of those adolescents meeting the daily recommended levels of PA varied substantially between instruments. Current national prevalence estimates collected via survey may represent an overestimation of PA among adolescents, indicating an even more pressing public health concern. Ongoing research is needed to understand declines in PA among adolescents, strategies to increase PA and further testing of measurement approaches.