Accelerometer-determined lifestyle activities in US adults.
ABSTRACT Objective physical activity data analyses focus on moderate-to-vigorous physical activity (MVPA) without considering lower intensity lifestyle-type activities (LA). We describe 1) quantity of LA (minutes and steps per day) across demographic groups, 2) proportion of LA to total physical activity, and 3) relationships between LA and MVPA using NHANES 2005-2006 accelerometer adult data (n = 3744).
LA was defined as 760 to 2019 counts per minute (cpm) and MVPA as ≥2020 cpm. LA was compared within gender, ethnicity, age, and BMI groups. Regression analyses examined independent effects. Correlations were evaluated between LA and MVPA. All analyses incorporated sampling weights to represent national estimates.
Adults spent 110.4 ± 1.6 minutes and took 3476 ± 54 steps per day in LA. Similar to MVPA, LA was highest in men, Mexican Americans, and lowest in adults ≥60 years or obese. When LA was held constant, ethnic differences no longer predicted MVPA minutes, and age no longer predicted MVPA steps. LA and MVPA minutes (r = .84) and steps per day (r = .72) were significantly correlated, but attenuated with MVPA modified bouts (≥10 minutes sustained activity).
LA accumulation differs between demographic subgroups and is related to MVPA: adults who spend more minutes and steps in MVPA also spend them in LA.
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ABSTRACT: PurposeWe performed a study to determine the best appropriate wearing site of a triaxial accelerometer at different exercise speeds.Materials and MethodsWe conducted an observational study with 66 healthy Korean adults (26 men and 40 women). Resting metabolic rate (RMR) before exercise, physical activity-related energy expenditure (PAEE) by cardiorespiratory gas analyzer and Signal Vector Magnitude (SVM) were measured while wearing four triaxial accelerometers on four different sites (wrist, waist, upper arm, and ankle) at exercise speeds from 2-10 km/h.ResultsThe mean RMR was 4.03 mL/kg/min and Actual METs (oxygen consumption at different exercise speeds divided by individual RMR) compared with the calculated METs (oxygen consumption divided by 3.5 mL/kg/min) showed relatively low value. The overall correlation between PAEE and SVM was highest when the accelerometer was worn on the wrist at low exercise speed (r=0.751, p<0.001), waist at a moderate speed (r=0.821, p<0.001), and ankle at a high speed (r=0.559, p<0.001). Using regression analysis, it was shown that the ankle at a low speed (R2=0.564, p<0.001), high speed (R2=0.559, p<0.001), and the waist at a moderate speed (R2=0.821, p<0.001) were the best appropriate sites.ConclusionWhen measuring the PAEE and SVM at different exercise speeds, the ankle in low and high exercise speed, and waist in moderate speed are the most appropriate sites for an accelerometer.Yonsei Medical Journal 07/2014; 55(4):1145-51. DOI:10.3349/ymj.2014.55.4.1145 · 1.26 Impact Factor
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ABSTRACT: Accelerometers objectively monitor physical activity and sedentary patterns and are increasingly used in the research setting. It is important to maintain consistency in data analysis and reporting, therefore, we: (1) systematically identified studies using accelerometry (ActiGraph, Pensacola, FL, USA) to measure moderate-to-vigorous physical activity (MVPA) and sedentary time in older adults, and (2) based on the review findings, we used different cut-points obtained to analyze accelerometry data from a sample of community-dwelling older women. We identified 59 articles with cut-points ranging between 574 and 3,250 counts/min for MVPA and 50 and 500 counts/min for sedentary time. Using these cut-points and data from women (mean age, 70 years), the median MVPA minutes per day ranged between 4 and 80 min while percentage of sedentary time per day ranged between 62 % and 86 %. These data highlight (1) the importance of reporting detailed information on the analysis assumptions and (2) that results can differ greatly depending on analysis parameters.European Review of Aging and Physical Activity 01/2014; 11(1):35-49. DOI:10.1007/s11556-013-0132-x · 0.81 Impact Factor
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ABSTRACT: To compare the extent to which different combinations of objectively measured sedentary behavior (SB) and physical activity contribute to cardiometabolic health. A population representative sample of 5,268 individuals, aged 20-85 years, was included from the combined 2003-2006 NHANES datasets. Activity categories were created on the combined basis of objectively measured SB and moderate-to-vigorous physical activity (MVPA) tertiles. Cardiometabolic abnormalities included elevated blood pressure, levels of triglycerides, fasting plasma glucose, C-reactive protein, homeostasis model assessment (HOMA) of insulin resistance value, and low HDL-cholesterol level. BMI, and DXA-derived percent body fat (% BF) and android adiposity were also compared across groups. Predictors for a metabolically abnormal phenotype (≥3 cardiometabolic abnormalities, or insulin resistance) were determined. Adults with the least SB and greatest MVPA exhibited the healthiest cardiometabolic profiles, whereas adults with the greatest SB and lowest MVPA were older and had elevated risk. Time spent in SB was not a predictor of the metabolically abnormal phenotype when MVPA was accounted for. Adults with the highest MVPA across SB tertiles did not differ markedly in prevalence of obesity, adiposity, and/or serum cardiometabolic risk factors; however, less MVPA was associated with substantial elevations of obesity and cardiometabolic risk. Android adiposity (per kilogram) was independently associated with the metabolically abnormal phenotype in both men (OR: 2.36 [95% CI, 1.76-3.17], p<0.001) and women (OR: 2.00 [95% CI, 1.63-2.45], p<0.001). Among women, greater SB, and less lifestyle moderate activity and MVPA were each independently associated with the metabolically abnormal phenotype, whereas only less MVPA was associated with it in men. MVPA is a strong predictor of cardiometabolic health among adults, independent of time spent in SB.Medicine and science in sports and exercise 01/2014; DOI:10.1249/MSS.0000000000000212 · 4.46 Impact Factor