|Title||Step-based Physical Activity Metrics and Cardiometabolic Risk: NHANES 2005-06.|
|Publication Type||Journal Article|
|Year of Publication||2016|
|Authors||Tudor-Locke, C, Schuna, Jr, JM, Han, H, Aguiar, EJ, Green, MA, Busa, MA, Larrivee, S, Johnson, WD|
|Journal||Med Sci Sports Exerc|
|Date Published||2016 Sep 23|
PURPOSE: To catalog the relationships between step-based accelerometer metrics indicative of physical activity volume (steps/day, adjusted to a pedometer scale), intensity (mean steps/min from the highest, not necessarily consecutive, minutes in a day; peak 30-min cadence) and sedentary behavior (percent time at zero cadence relative to wear time; %TZC) and cardiometabolic risk factors.
METHODS: We analyzed data from 3388 20+ year-old participants in the 2005-2006 National Health and Nutrition Examination Survey with ≥1 valid day of accelerometer data and at least some data on weight, BMI, waist circumference, systolic and diastolic blood pressure, glucose, insulin, HDL-cholesterol, triglycerides, and/or glycohemoglobin. Linear trends were evaluated for cardiometabolic variables, adjusted for age and race, across quintiles of steps/day, peak 30 min-cadence, and %TZC.
RESULTS: Median steps/day ranged from 2247-12334 for men and 1755-9824 steps/day for women, and median peak 30-min cadence ranged from 48.1-96.0 for men and 40.8-96.2 steps/min for women, for the 1st and 5th quintiles, respectively. Linear trends were statistically significant (all p<0.001), with increasing quintiles of steps/day and peak 30-min cadence inversely associated with waist-circumference, weight, BMI and insulin, for both men and women. Median %TZC ranged from 17.6-51.0% for men and 19.9-47.6% for women, for the 1st and 5th quintiles, respectively. Linear trends were statistically significant (all p<0.05), with increasing quintiles of %TZC associated with increased waist circumference, weight and insulin for men, and insulin for women.
CONCLUSIONS: This analysis identified strong linear relationships between step-based movement/non-movement dimensions and cardiometabolic risk factors. These data offer a set of quantified access points for studying the potential dose-response effects of each of these dimensions separately or collectively in longitudinal observational or intervention study designs.This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
|Alternate Journal||Med Sci Sports Exerc|