Showing papers by "Patty S. Freedson published in 2010"

Accelerometer output and MET values of common physical activities.

Abstract: Purpose: This article 1) provides the calibration procedures and methods for metabolic and activity monitor data collection, 2) compares measured MET values to the MET values from the compendium of physical activities, and 3) examines the relationship between accelerometer output and METs for a range of physical activities. Methods: Participants (N = 277) completed 11 activities for 7 min each from a menu of 23 physical activities. Oxygen consumption (V?O2) was measured using a portable metabolic system, and an accelerometer was worn. MET values were defined as measured METs (V?O2/measured resting metabolic rate) and standard METs (V?O2/3.5 mL·kg-1·min-1). For the total sample and by subgroup (age [young < 40 yr], sex, and body mass index [normal weight < 25 kg·m-2]), measured METs and standard METs were compared with the compendium, using 95% confidence intervals to determine statistical significance (a = 0.05). Average counts per minute for each activity and the linear association between counts per minute and METs are presented. Results: Compendium METs were different than measured METs for 17/21 activities (81%). The number of activities different than the compendium was similar between subgroups or when standard METs were used. The average counts for the activities ranged from 11 counts per minute (dishes) to 7490 counts per minute (treadmill: 2.23 m·s-1, 3%). The r2 between counts and METs was 0.65. Conclusions: This study provides valuable information about data collection, metabolic responses, and accelerometer output for common physical activities in a diverse participant sample. The compendium should be updated with additional empirical data, and linear regression models are inappropriate for accurately predicting METs from accelerometer output.

Comparison of the ActiGraph 7164 and the ActiGraph GT1M during Self-Paced Locomotion

Abstract: Purpose: This study compared the ActiGraph accelerometer model 7164 (AM1) with the ActiGraph GT1M (AM2) during self-paced locomotion. Methods: Participants (n = 116, aged 18-73 yr, mean body mass index = 26.1 kg[middle dot]m-2) walked at self-selected slow, medium, and fast speeds around an indoor circular hallway (0.47 km). Both activity monitors were attached to a belt secured to the hip and simultaneously collected data in 60-s epochs. To compare differences between monitors, the average difference (bias) in count output and steps output was computed at each speed. Time spent in different activity intensities (light, moderate, and vigorous) based on the cut points of Freedson et al. was compared for each minute. Results: The mean +/- SD walking speed was 0.7 +/- 0.22 m[middle dot]s-1 for the slow speed, 1.3 +/- 0.17 m[middle dot]s-1 for medium, and 2.1 +/- 0.61 m[middle dot]s-1 for fast speeds. Ninety-five percent confidence intervals (95% CI) were used to determine significance. Across all speeds, step output was significantly higher for the AM1 (bias = 19.8%, 95% CI = -23.2% to -16.4%) because of the large differences in step output at slow speed. The count output from AM2 was a significantly higher (2.7%, 95% CI = 0.8%-4.7%) than that from AM1. Overall, 96.1% of the minutes were classified into the same MET intensity category by both monitors. Conclusions: The step output between models was not comparable at slow speeds, and comparisons of step data collected with both models should be interpreted with caution. The count output from AM2 was slightly but significantly higher than that from AM1 during the self-paced locomotion, but this difference did not result in meaningful differences in activity intensity classifications. Thus, data collected with AM1 should be comparable to AM2 across studies for estimating habitual activity levels

Errors in MET Estimates of Physical Activities Using 3.5 ml·kg−1·min−1 as the Baseline Oxygen Consumption

Abstract: Purpose:To compare intensity misclassification and activity MET values using measured RMR (measMET) compared with 3.5 ml·kg−1·min−1 (standMET) and corrected METs [corrMET = mean standMET × (3.5 ÷ Harris-Benedict RMR)] in subgroups. Methods:RMR was measured for 252 subjects following a 4-hr fast and before completion of 11 activities. VO2 was measured during activity using indirect calorimetry (n = 2555 activities). Subjects were classified by BMI category (normal-weight or overweight/obese), sex, age (decade 20, 30, 40, or 50 y), and fitness quintiles (low to high). Activities were classified into low, moderate, and vigorous intensity categories. Results:The (mean ± SD) measMET was 6.1 ± 2.64 METs. StandMET [mean (95% CI)] was (0.51(0.42, 0.59) METs) less than measMET. CorrMET was not statistically different from measMET (−0.02 (−0.11, 0.06) METs). 12.2% of the activities were misclassified using standMETs compared with an 8.6% misclassification rate for METs based on predicted RMR (P < .0001). StandMET d...

Medical hazards of prolonged sitting.

Abstract: Prolonged sitting is hazardous to one’s health. In 1700 Italy, Ramazini observed that sedentary tailors were not as healthy as active messengers (10). In the 1950s, the first epidemiological study using occupational activity to define sedentary and active behavior was conducted by Morris and colleagues (6). In this study, bus conductors who climbed approximately 600 stairs per day at work had half the number of heart attacks in comparison to bus drivers who spent 90% of their work time sitting. More recently, a wealth of evidence has arisen indicating that postural fixity (either sitting or standing) is undesirable from a health standpoint. A review article by Neville Owen, Ph.D., and colleagues (8) in this issue of Exercise and Sport Sciences Reviews reports on ‘‘Too Much Sitting: The Population-Health Science of Sedentary Behavior.’’ Their article expands on information presented in a lecture by Owen at the 2009 American College of Sports Medicine (ACSM) Annual Meeting and helps to strengthen the link between sedentary behavior and ill health. Their paper draws attention to several new findings: 1) Cross-sectional studies show that TV viewing is associated with obesity, diabetes, impaired glucose uptake, and insulin resistance. 2) These associations remain even after statistically adjusting for moderate-to-vigorous leisure time physical activity and waist circumference. 3) Accelerometer studies indicate that in adults, on average, 60% of waking hours are spent being sedentary (i.e., accelerometer values G100 counts per minute). 4) Individuals who meet the recommended levels of moderateto-vigorous physical activity and spend the majority of their waking hours in sedentary activities may have compromised health, compared with those who are sufficiently active and sit less.

Design of a wearable multi-sensor system for physical activity assessment

Abstract: In-situ measurement of physical activity of human under free-living environment is important for assessing their exposure to the environment. Innovative sensing technology is needed to realize such measurement. This paper presents a wearable, multi-sensor integrated measurement system (IMS) for assessing physical activity. Detailed analysis and simulation were performed for the parametric design of the IMS hardware and embedded software. An adaptive-scheduling method was devised to improve the battery power efficiency, reducing the energy consumption by over 16 times as compared to the conventional technique, enabling continued system operation of up to 54 hours. Experiments on human subjects have shown that the multi-sensor IMS is more effective in recognizing activities of varying intensity than the traditional activity measurement devices that use accelerometers alone. Error analysis of the IMS accelerometer outputs is also presented.

Effects of a Single Exercise Bout on Insulin Sensitivity in Black and White Individuals

Abstract: Background: Previous research suggests non-Hispanic blacks (blacks) are more insulin resistant than non-Hispanic whites (whites). Physical activity can play an important role in reducing insulin resistance. However, it is unknown whether racial differences exist in response to exercise. Therefore, the purpose of this study was to compare metabolic responses to a single bout of exercise in blacks and age-, sex-, and body mass index-matched whites. Methods: Whole-body insulin sensitivity, glucose storage, glucose oxidation, and respiratory exchange ratio (RER) were assessed during a hyperinsulinemic-euglycemic clamp in normoglycemic blacks (n = 11) and whites (n = 10). Outcome measures were evaluated in a sedentary control condition and 12 h after treadmill walking at 75% of maximal heart rate for 75 min. Results: In the control condition, there were no differences in insulin sensitivity between blacks and whites (P = 0.54). During the clamp, glucose oxidation and insulin-stimulated RER values were signific...

Use of continuous glucose monitoring in normoglycemic, insulin-resistant women

Abstract: The purpose of this study was to compare fasting and post-prandial glucose concentrations measured in venous blood with continuous glucose monitoring (CGM)-derived values, with and without prior exercise, in insulin-resistant, normoglycemic women. Interstitial and venous glucose concentrations were assessed in ten sedentary, overweight/obese African-American women following a sedentary condition (75 min of rest) and following an exercise condition (75 min of brisk walking on a treadmill). Ninety minutes after rest or exercise, participants completed an oral glucose tolerance test (OGTT). In response to the OGTT, CGM-derived glucose area under the curves (AUC) were lower than venous values in the exercise condition (−25%, p = 0.03) but this difference was attenuated in the sedentary condition (−10%, p = 0.09). Additionally, CGM-derived absolute glucose values (mMol) were significantly lower compared to venous values during the sedentary (p = 0.007) and exercise conditions (p = 0.006). Overall, there was a moderately strong relationship between venous and CGM-derived glucose AUC (r 2 = 0.68) but the CGM-derived values were consistently lower in this study group. Although CGM provided more information regarding post-prandial glucose responses, these results suggest that CGM may not closely match venous glucose measurements in normoglycemic participants.