Biomedical subjects

Scott J Strath

Publications and source records attributed to Scott J Strath.

8 recordsLinked to original sources

PubMed2007

Discrepancies between methods of identifying objectively determined physical activity.

UNLABELLED: Current methods for validating physical activity (PA) questionnaires typically use accelerometers as objective measures for comparison with questionnaire responses and obtain low correlations or agreement. PURPOSE: We examined possible reasons for weak associations in validation studies by comparing published ActiGraph accelerometer intensity cut points with cut points based on intensity thresholds for heart rate response to PA. METHODS: Twelve adults (five men, seven women; age 31.0 +/- 14.3 yr) wore an ActiGraph accelerometer and a Polar Vantage NV heart watch simultaneously for seven consecutive days during their waking hours. We identified PA bouts from the minute-by-minute ActiGraph data using published accelerometer thresholds for defining moderate- and vigorous-intensity PA. We then compared PA bout intensities identified with these criteria with intensity classifications of the PA bouts using mean percent heart rate reserve (HRR). RESULTS: Most of the moderate-intensity PA bouts identified by the Freedson (78.3%), Swartz (88.0%), and Hendelman (94.7%) ActiGraph cut points were associated with a mean %HRR < 45% (very light and light intensities). The estimated mean frequency with which study participants engaged in moderate-intensity PA varied with the cut points and type of bouts used and ranged from 1.1 d.wk(-1) (45-60%HRR) to 7.0 d.wk(-1) (Hendelman cut points). The mean total duration on active days ranged from 17.9 min.d(-1)(45-60%HRR) to 139.2 min.d(-1) (Hendelman cut points). Fewer bouts of vigorous PA were found in the accelerometer data, and most were in the vigorous-intensity category of > or = 60%HRR. CONCLUSIONS: The method used for analyzing ActiGraph activity data can result in large differences in the summary measure of minutes of moderate- to vigorous-intensity activity.

Adult↗

PubMed2005

Integration of physiological and accelerometer data to improve physical activity assessment.

PURPOSE: Accurate measurement of physical activity (PA) is a prerequisite to determine dose-response relationships between activity and health. The combination of HR and accelerometers (ACC) holds promise for improving the accuracy of PA assessment, but it is unclear how currently proposed modeling techniques compare and to what extent different levels of individual calibration (IC) of HR influence monitoring accuracy. METHODS: A total of 10 men and women (25.8 +/- 3.4 yr, 1.70 +/- 0.1 m, 71.7 +/- 11.8 kg, 24.4 +/- 5.0 kg.m-2) were recruited for this study, in which IC of HR to PA energy expenditure (PAEE) during both arm crank and treadmill activity were available. Participants completed 6 h of free-living activity, during which PAEE (obtained with indirect calorimetry), HR, hip ACC, arm ACC, and leg ACC were collected. PAEE was then modeled from two different methods of combining HR and ACC (arm-leg HR+M and branched model), both with IC and group-level calibration (GC) of HR, and also from hip ACC estimates alone. Estimates of PAEE were compared with criterion values for PAEE. RESULTS: Combined estimates of PAEE from the arm-leg HR+M and the branched model were similar when IC was used (R2 = 0.81, SEE = 0.55 METs and R2 = 0.75, SEE = 0.61 METs, respectively). When using GC, all estimates of PAEE had larger error, but the performance of the branched model suffered less than the arm-leg HR+M model (R2 = 0.75, SEE = 0.67 METs and R2 = 0.67, SEE = 0.88 METs, respectively). Both combination modeling techniques were more precise than single-measure hip ACC estimates (R2 = 0.41, SEE = 0.96 METs). CONCLUSION: The combination of HR and ACC improves the accuracy of PAEE estimates and could be applied in large-scale epidemiological studies.

Acceleration↗

PubMed2004

Comparison of the college alumnus questionnaire physical activity index with objective monitoring.

PURPOSE: Two methods of measuring physical activity (PA) were compared over a consecutive 7-day period among 25 adults (12 men and 13 women). METHODS: Each day estimates of energy expended in light, moderate, vigorous, and total PA were derived from the simultaneous heart-rate motion sensor (HR+M) technique. At the end of the 7-day period participants completed the College Alumnus Questionnaire Physical Activity Index (CAQ-PAI) and results were compared with HR+M technique estimates. RESULTS: Correlations between the two methods in the four activity categories ranged from r=0.20 to r=0.47, with vigorous and total PA showing higher associations than light and moderate PA. Mean levels of PA (MET-minxwk(-1)) obtained using the two methods were similar in the moderate and vigorous categories, but individual differences were large. Energy expended in light PA was significantly underestimated on the CAQ-PAI, resulting in lower total activity scores on this questionnaire as compared with the HR+M. CONCLUSIONS: The CAQ-PAI accurately reflected mean moderate and vigorous activity in comparison with the HR+M technique. The results are consistent with other studies which have shown that physical activity questionnaires are better at assessing vigorous PA than ubiquitous light-moderate activities.

Adult↗

PubMed2004

A preliminary study of one year of pedometer self-monitoring.

BACKGROUND: Long-term pedometer monitoring has not been attempted. PURPOSE: The purpose of this project was to collect 365 days of continuous self-monitored pedometer data to explore the natural variability of physical activity. METHODS: Twenty-three participants (7 men, 16 women; M age = 38 +- 9.9 years; M body mass index = 27.7 +- 6.2 kg/m2) were recruited by word of mouth at two southern U.S. universities. Participants were asked to wear pedometers at their waist during waking hours and record steps per day and daily behaviors (e.g., sport/exercise, work or not) on a simple calendar. In total, participants wore pedometers and recorded 8,197 person-days of data (of a possible 8,395 person-days, or 98%) for a mean of 10,090 +- 3,389 steps/day. Missing values were estimated using the Missing Values Analysis EM function in SPSS, Version 11.0.1. RESULTS: A mean of 10,082 +- 3,319 steps/day was computed. Using the corrected data, differences in steps/day were significant for season (summer > winter, F = 7.57, p = .001), day of the week (weekday > weekend, F = 3.97, p = .011), type of day (workday vs. nonworkday, F = 9.467, p = .008), and participation in sport/exercise (day with sport/exercise > day without sport/exercise, F = 102.5, p < .0001). CONCLUSIONS: These data suggest that surveillance should be conducted in the spring/fall or that an appropriate correction factor should be considered if the intent is to capture values resembling the year-round average.

Adult↗

PubMed2003

Validity of uniaxial accelerometry during activities of daily living in children.

The purpose of this study was to examine the validity of treadmill-based equations of two commonly used uniaxial accelerometers to estimate energy expenditure (EE) during activities of daily living in children. Twelve subjects with mean (SD) age11.4 (0.4) years engaged in a choreographed routine consisting of three activities (sweeping, bowling, and basketball) of 4min duration while wearing a Manufacturing Technology, Inc. (MTI) accelerometer, Caltrac accelerometer, and a portable gas analyzer (Cosmed K4b(2)). The equations of Trost et al. and Sallis et al. were used to convert activity counts to estimations of EE for the MTI and Caltrac, respectively. Correlation coefficients between Caltrac predictions of EE and measured EE from indirect calorimetry ranged from r=0.22 to 0.72 for individual activities. Correlations between MTI EE predictions and indirect calorimetry ranged from r=0.50 to 0.68 for individual activities. When the activities were pooled the correlations between EE from uniaxial accelerometers and EE from indirect calorimetry were moderately strong (MTI, r=0.78 and Caltrac, r=0.82). Inter-accelerometer (counts min(-1)) correlations were 0.08, -0.54, 0.63, and 0.79 for sweeping, bowling, basketball, and pooled data, respectively. The overall mean difference, or bias, and 95% confidence intervals (CI) for each uniaxial accelerometer compared to indirect calorimetry were as follows: Caltrac, bias = 2.80 (2.36, 3.24) kcal min(-1); MTI, bias = 0.88 (0.23, 1.53) kcal min(-1). Both accelerometers significantly underestimated measured EE ( P<0.05). Uniaxial accelerometers provide potential for the measurement of physical activity (PA) and EE in children. Future studies refining accelerometry predictions of PA and EE are warranted.

Acceleration↗

PubMed2003

Increasing daily walking improves glucose tolerance in overweight women.

BACKGROUND: Physical activity (PA) has been shown to benefit glucose tolerance. Walking is a convenient low-impact mode of PA and is reported to be the most commonly performed activity for those with diabetes. The purpose of this study was to determine whether a recommendation to accumulate 10,000 steps/day for 8 weeks was effective at improving glucose tolerance in overweight, inactive women. METHODS: Eighteen women (53.3 +/- 7.0 years old, 35.0 +/- 5.1 kg/m(2)) with a family history of type 2 diabetes completed a 4-week control period followed by an 8-week walking program with no changes in diet. The walking program provided a goal of accumulating at least 10,000 steps/day, monitored by a pedometer. RESULTS: During the control period, participants walked 4972 steps/day. During the intervention period, the participants increased their accumulated steps/day by 85% to 9213, which resulted in beneficial changes in 2-h postload glucose levels (P < 0.001), AUC(glucose) (P = 0.025), systolic blood pressure (P < 0.001), and diastolic blood pressure (P = 0.002). There were no changes in body mass, body fat percentage, and waist circumference during the walking intervention. CONCLUSIONS: The 10,000 steps/day recommendation resulted in improved glucose tolerance and a reduction in systolic and diastolic blood pressure in overweight women at risk for type 2 diabetes. This demonstrates that activity can be accumulated throughout the day and does not have to result in weight loss to benefit this population.

Diabetes Mellitus↗

PubMed2003

Assessment of physical activity by telephone interview versus objective monitoring.

PURPOSE: To compare different methods of quantifying time in physical activity (PA). METHODS: Twenty-five participants (12 male, 13 female) volunteered to be monitored for seven consecutive days, during which different PA patterns were measured by the simultaneous heart-rate motion sensor technique (HR+M). At the end of the 7th day, participants completed questions taken from the 2001 Behavioral Risk Factor Surveillance System (BRFSS) PA module telephone survey, in which they recalled the amount of time spent walking, and in moderate and vigorous activities. The results of the BRFSS PA module were then compared with those of the HR+M. RESULTS: No significant group differences were found in the amount of time spent in moderate and vigorous activities between methods. However, individual differences were greater for time spent in moderate activities (SE +/- 7.36 min x d(-1); range -70 to 77 min x d(-1)) than for time spent in vigorous activities (SE +/- 3.57 min x d(-1); range -39 to 33 min x d(-1). Spearman correlation coefficients between the HR+M and the BRFSS were significant for vigorous activities (r = 0.54, P < 0.01). There was 80% agreement between the two methods of classifying individuals who either: (a) met the recommendations (through moderate and/or vigorous PA) or (b) did not meet the recommendations. CONCLUSION: The BRFSS and HR+M methods yielded similar group estimates of PA, but individual assessments of moderate activity differed more than those of vigorous activity. BRFSS estimations of group compliance with national PA recommendations were similar to those of the HR+M.

Adult↗

PubMed2002

Validity of the simultaneous heart rate-motion sensor technique for measuring energy expenditure.

PURPOSE: To determine the validity of the simultaneous heart rate-motion sensor (HR+M) technique for estimating energy expenditure (EE) by comparing it with indirect calorimetry. In addition, we examined the validity of the flex heart rate (FlexHR) method to estimate EE. METHODS: Ten participants (4 men: 26.7 yr +/- 1.5, and 6 women: 26.5 yr +/-3.3) performed arm and leg work in the laboratory for the purpose of developing individualized HR-oxygen uptake (VO2) regression equations. Participants completed physical tasks in a field setting while HR, VO2, and motion sensor data were collected on a near-continuous basis for 6 h. Accelerometers, one on the arm and one on the leg, were used to discriminate between upper- and lower-body movement. HR was used to predict EE (METs) from the corresponding laboratory regression equation. Predicted values (METs) were compared with measured values (METs) obtained via a portable metabolic measurement system. RESULTS: The simultaneous HR+M technique showed a significantly stronger relationship with VO2 (R2 = 0.81, SEE = 0.55 METs) in comparison with the FlexHR method (R2 = 0.63, SEE = 0.76 METs) (P < 0.001). The FlexHR method significantly overestimated measured minute-by-minute EE (P < 0.001), whereas the simultaneous HR+M technique did not. The simultaneous HR+M technique accurately reflected time spent in resting/light, moderate, and hard activity, whereas the FlexHR method underpredicted time spent in resting/light activity (P = 0.02) and overpredicted time spent in moderate activity (P = 0.02). The simultaneous HR+M technique also accurately estimated total 6-h EE. CONCLUSION: The simultaneous HR+M technique is an accurate predictor of EE during free-living activity and provides a valid measure of the time spent in various intensity categories.

Adult↗