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Objectively Measured Total Accelerometer Counts and MVPA: The Relationship with Biomarkers Using 2003 – 2006 NHANES
- Presented on June 17, 2013
Purpose To contrast the associations of objectively measured moderate-to-vigorous physical activity (MVPA) and total accelerometer counts with biomarkers in a representative sample of U.S. adults.
Methods Data from the 2003 – 2006 NHANES were used for this analysis. The sample included adults ≥ 20 y, not pregnant or lactating, who had self-reported PA and ≥ 4 d of accelerometer data with ≥ 10 h wear time (N = 5668). MVPA was defined as the mean minutes with counts ≥ 2020 using a 10-min bout criterion on valid days. Total accelerometer counts represented the mean total counts acquired on valid days. Biomarkers included: blood pressure, body mass index (BMI), waist circumference, triceps and subscapular skinfolds, cholesterol, triglyceride, glycohemoglobin, plasma glucose, C-peptide, insulin, C-reactive protein, and homocysteine. Simultaneous regressions were conducted in which each biomarker was regressed on MVPA and total accelerometer counts per day independently while adjusting for relevant covariates.
Results When compared to MVPA, total accelerometer counts per day displayed stronger associations with the following biomarkers: BMI, waist circumference, triceps skinfolds, subscapular skinfolds, HDL, triglycerides, plasma glucose, C-peptide, insulin, C-reactive protein, and homocysteine (adj. Wald F = 9.04 – 97.41, P < 0.05 – 0.0001). Only one biomarker, glycohemoglobin, had stronger associations with MVPA (F = 6.67, P ≤ 0.05) than total accelerometer counts (F= 0.87, P > 0.05). After adjusting for BMI and other relevant covariates, total accelerometer counts remained more strongly associated with cardiometabolic biomarkers than MVPA, with glycohemoglobin found to have no relationship with either PA variable.
Conclusions Total accelerometer counts per day were more robustly associated with various cardiobiomarkers than MVPA. Thus, using total accelerometer counts per day may provide a better estimate of the strength of the relationship between PA and biomarkers.