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Biomedical subjects

David R Bassett

Publications and source records attributed to David R Bassett.

At least 19 recordsLinked to original sources
PubMed2006

Estimating energy expenditure using accelerometers.

The purpose of this study was to examine the validity of published regression equations designed to predict energy expenditure (EE) from accelerometers (Actigraph, Actical, and AMP-331) compared to indirect calorimetry, over a wide range of activities. Forty-eight participants (age: 35 +/- 11.4 years) performed various activities that ranged from sedentary behaviors (lying, sitting) to vigorous exercise. The activities were split into three routines of six activities, and each participant performed at least one routine. The participants wore three devices (Actigraph, Actical, and AMP-331) and simultaneously, EE was measured with a portable metabolic system. For the Actigraph, 15 previously published equations were used to estimate EE from the accelerometer counts. For the Actical, two published equations were used to estimate EE from the accelerometer counts. For the AMP-331 we used the manufacturer's equation to estimate EE. The Actigraph and Actical regressions tended to overestimate walking and sedentary activities and underestimate most other activities. The AMP-331 gave a close estimate of EE during walking, but overestimated sedentary/light activities and underestimated all other activities. The only equation not significantly different from actual time spent in both light and moderate physical activity was the Actigraph Freedson kcal equation. All equations significantly underestimated time spent in vigorous physical activity (P < 0.05). In conclusion, no single regression equation works well across a wide range of activities for the prediction of EE or time spent in light, moderate, and vigorous physical activity.

Acceleration↗
PubMed2005

A novel method for using accelerometer data to predict energy expenditure.

The purpose of this study was to develop a new two-regression model relating Actigraph activity counts to energy expenditure over a wide range of physical activities. Forty-eight participants [age 35 yr (11.4)] performed various activities chosen to represent sedentary, light, moderate, and vigorous intensities. Eighteen activities were split into three routines with each routine being performed by 20 individuals, for a total of 60 tests. Forty-five tests were randomly selected for the development of the new equation, and 15 tests were used to cross-validate the new equation and compare it against already existing equations. During each routine, the participant wore an Actigraph accelerometer on the hip, and oxygen consumption was simultaneously measured by a portable metabolic system. For each activity, the coefficient of variation (CV) for the counts per 10 s was calculated to determine whether the activity was walking/running or some other activity. If the CV was 10, a lifestyle/leisure time physical activity regression was used. In the cross-validation group, the mean estimates using the new algorithm (2-regression model with an inactivity threshold) were within 0.75 metabolic equivalents (METs) of measured METs for each of the activities performed (P >or= 0.05), which was a substantial improvement over the single-regression models. The new algorithm is more accurate for the prediction of energy expenditure than currently published regression equations using the Actigraph accelerometer.

Activities of Daily Living↗
PubMed2005

Comparison of two waist-mounted and two ankle-mounted electronic pedometers.

This study compared two ankle-mounted pedometers [StepWatch 3 (SW-3(Ankle)) and Activity Monitoring Pod 331 (AMP(Ankle))] and two waist-mounted pedometers [New Lifestyles NL-2000 (NL(Waist)) and Digiwalker SW-701 (SW-701(Waist))] under controlled and free-living conditions. In part I, 20 participants walked on a treadmill at speeds of 27-107 m min(-1). Actual steps were counted with a hand counter. In part II, participants performed leg swinging, heel tapping, stationary cycling, and car driving. In part III, 15 participants wore all pedometers for a 24 h period. The SW-3(Ankle) displayed values that were within 1% of actual steps during treadmill walking at all speeds. The other devices underestimated steps at slow speeds but all gave mean values that were within +/-3% of actual steps at 80 m min(-1) and above. The SW-3(Ankle) registered some steps during heel tapping, leg swinging, and cycling, while the AMP(Ankle) was only responsive to leg swinging. During car driving no devices recorded more than eight steps, on average. Over 24 h, the AMP(Ankle) recorded 18% fewer steps than the SW-3(Ankle) (P<0.05), while the SW-701(Waist) and the NL(Waist) recorded 15 and 11% less than the SW-3(Ankle), respectively (NSD). The SW-3(Ankle) has superior accuracy at slow treadmill walking speeds (although it was also more likely to detect "fidgeting" activities). Over 24 h, the SW-3(Ankle) tended to give higher estimates of steps per day than the other ankle- and waist-mounted pedometers.

Adult↗
PubMed2005

Spring-levered versus piezo-electric pedometer accuracy in overweight and obese adults.

PURPOSE: The purpose of this study was to examine the effects of BMI, waist circumference, and pedometer tilt on the accuracy of a spring-levered pedometer (Yamax Digiwalker SW-200 (SW)) and a piezo-electric pedometer (New Lifestyles NL-2000 (NL)) during treadmill walking and over a 24-h period in overweight and obese adults. METHODS: Forty participants (40 +/- 13.0 yr, 32.6 +/- 4.8 kg.m) walked on a treadmill at various speeds (54, 67, 80, 94, and 107 m.min) for 3-min stages. Simultaneously, an investigator determined actual steps by a hand counter. For all walking trials the SW and NL were positioned on the right and left waistband, respectively. Height, weight, pedometer tilt angle and circumference measures of the hip and waist were also measured. Thirty-six participants wore the pedometers for a 24-h period in the same position as during the treadmill walking trials. RESULTS: : In general, the SW became less accurate with increasing BMI, increasing waist circumference, and greater pedometer tilt, whereas the NL was not affected by these variables. The SW error scores were significantly correlated with the absolute pedometer tilt angle at all walking speeds (P < 0.05), but the NL error scores were not. On average the NL recorded 1030 +/- 1414 (16.5 +/- 22.7%) more steps that the SW during the 24-h trial. CONCLUSION: In overweight and obese individuals, a piezo-electric pedometer (NL) is more accurate than a spring-levered pedometer (SW), especially at slower walking speeds. In addition, it appears that pedometer tilt; more so than waist circumference and BMI, was the most important factor influencing the accuracy of the SW. The NL accuracy was not affected by pedometer tilt, waist circumference, or BMI.

Adolescent↗
PubMed2005

The technology of accelerometry-based activity monitors: current and future.

PURPOSE: This paper reviews accelerometry-based activity monitors, including single-site first-generation devices, emerging technologies, and analytical approaches to predict energy expenditure, with suggestions for further research and development. METHODS: The physics and measurement principles of the accelerometer are described, including the sensor properties, data collections, filtering, and integration analyses. The paper also compares these properties in several commonly used single-site accelerometers. The emerging accelerometry technologies introduced include the multisensor arrays and the combination of accelerometers with physiological sensors. The outputs of accelerometers are compared with criterion measures of energy expenditure (indirect calorimeters and double-labeled water) to develop mathematical models (linear, nonlinear, and variability approaches). RESULTS: The technologies of the sensor and data processing directly influence the results of the outcome measurement (activity counts and energy expenditure predictions). Multisite assessment and combining accelerometers with physiological measures may offer additional advantages. Nonlinear approaches to predict energy expenditure using accelerometer outputs from multiple sites and orientation can enhance accuracy. CONCLUSIONS: The development of portable accelerometers has made objective assessments of physical activity possible. Future technological improvements will include examining raw acceleration signals and developing advanced models for accurate energy expenditure predictions.

Acceleration↗
PubMed2005

Pedometer-determined walking and body composition variables in African-American women.

PURPOSE: This study evaluated the relationship between pedometer-determined physical activity and body composition variables in middle-aged, African-American women. METHODS: Height, weight, waist circumference, hip circumference, and percent body fat were measured in 69 African-American females (mean age 51.4 +/- 5.4 yr). Subjects wore a pedometer for seven consecutive days, and average steps per day (i.e, walking volume) were compared with each anthropometric variable. Caloric intake was assessed by a 3-d diet record. The subjects were categorized into three different groups based on their physical activity level: <5000, 5000-7499, and > or =7500 steps per day. A one-way analysis of variance (ANOVA) was performed to examine the body composition variables among the three groups. Partial correlation coefficients controlling for age and caloric intake were calculated for walking volume and body composition variables (BMI, percent body fat, waist and hip circumferences, and WHR). Significance was set at P < 0.05 for all tests. RESULTS: There were significant differences between the least active and most active group for age (P = 0.013), BMI (P = 0.005), percent body fat (P < 0.001), waist circumference (P = 0.004), and hip circumference (P = 0.043). When a partial correlation controlling for age and caloric intake was used to compare steps per day with body composition variables, significant negative correlations still existed for each variable except WHR. These correlations were significant for BMI (P < 0.001), percent body fat (P < 0.001), waist circumference (P = 0.002), and hip circumference (P = 0.017). CONCLUSIONS: Middle-aged, African-American women who accumulate more ambulatory activity have significantly lower body fat percentages, BMI values, waist circumferences, and hip circumferences.

Adult↗
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↗
PubMed2004

Physical activity in an Old Order Amish community.

UNLABELLED: One method to assess the impact of modern technology on physical activity is to examine a group whose lifestyle has not changed markedly in the last 150 yr. The Old Order Amish refrain from driving automobiles, using electrical appliances, and employing other modern conveniences. Labor-intensive farming is still the preferred occupation. PURPOSE: The purposes of this study were to characterize the physical activity (PA) levels in an Old Order Amish farming community and to examine measures of adiposity in this group. METHODS: Ninety-eight Amish adults (18-75 yr of age) in southern Ontario were studied. Anthropometric variables included height, weight, body mass index (BMI), and percent body fat (% BF). Participants were asked to wear an electronic pedometer for 7 d and to fill out a log sheet on which they recorded steps per day and physical activities. After 1 wk, they returned the pedometers and log sheets and filled out the International Physical Activity Questionnaire. RESULTS: The average number of steps per day was 18,425 for men versus 14,196 for women (P < 0.05). Men reported 10.0 h.wk-1 of vigorous PA, 42.8 h.wk-1 of moderate PA, and 12.0 h.wk-1 of walking. Women reported 3.4 h.wk-1 of vigorous PA, 39.2 h.wk-1 of moderate PA, and 5.7 h.wk-1 of walking. Men had higher levels of energy expenditure than women (P < 0.001). A total of 25% of the men and 27% of the women were overweight (BMI > or = 25), and 0% of the men and 9% of the women were obese (BMI > or = 30). CONCLUSIONS: The Amish we studied had very high levels of physical activity, which may contribute to their low prevalence of obesity. This group probably represents an upper extreme for "lifestyle PA" in North America today.

Adolescent↗
PubMed2004

Pedometer measures of free-living physical activity: comparison of 13 models.

PURPOSE: The purpose of this study was to compare the step values of multiple brands of pedometers over a 24-h period. The following 13 electronic pedometers were assessed in the study: Accusplit Alliance 1510 (AC), Freestyle Pacer Pro (FR), Colorado on the Move (CO), Kenz Lifecorder (KZ), New-Lifestyles NL-2000 (NL), Omron HJ-105 (OM), Oregon Scientific PE316CA (OR), Sportline 330 (SL330) and 345 (SL345), Walk4Life LS 2525 (WL), Yamax Skeletone EM-180 (SK), Yamax Digi-Walker SW-200 (YX200), and the Yamax Digi-Walker SW-701 (YX701). METHODS: Ten males (39.5 +/- 16.6 yr, mean +/- SD) and 10 females (43.3 +/- 16.6 yr) ranging in BMI from 19.8 to 35.4 kg.m-2 wore two pedometers for a 24-h period. The criterion pedometer (YX200) was worn on the left side of the body, and a comparison pedometer was worn on the right. Steps counted by each device were recorded at the end of the day for each of the thirteen pedometers. RESULTS: Subjects took an average of 9244 steps.d-1. The KZ, YX200, NL, YX701, and SL330 yielded mean values that were not significantly different from the criterion. The FR, AC, SK, CO, and SL345 significantly underestimated steps (P < 0.05) and the WL, OM, and OR significantly overestimated steps (P < 0.05) when compared with the criterion. In addition, some pedometers underestimated by 25% whereas others overestimated by 45%. CONCLUSION: The KZ, YX200, NL, and YX701 appear to be suitable for most research purposes. Given the potential for pedometers in physical activity research, it is necessary that there be consistency across studies in the measurement of "steps per day."

Activities of Daily Living↗
PubMed2004

Accuracy of polar S410 heart rate monitor to estimate energy cost of exercise.

PURPOSE: The purpose of this study was to examine the accuracy of the Polar S410 for estimating gross energy expenditure (EE) during exercise when using both predicted and measured VO2max and HRmax versus indirect calorimetry (IC). METHODS: Ten males and 10 females initially had their VO2max and HRmax predicted by the S410, and then performed a maximal treadmill test to determine their actual values. The participants then performed three submaximal exercise tests at RPE of 3, 5, and 7 on a treadmill, cycle, and rowing ergometer for a total of nine submaximal bouts. For all submaximal testing, the participant had two S410 heart rate monitors simultaneously collecting data: one heart rate monitor (PHRM) utilized their predicted VO2max and HRmax, and one heart rate monitor (AHRM) used their actual values. Simultaneously, EE was measured by IC. RESULTS: In males, there were no differences in EE among the mean values for the AHRM, PHRM, and IC for any exercise mode (P > 0.05). In females, the PHRM significantly overestimated mean EE on the treadmill (by 2.4 kcal x min(-1)), cycle (by 2.9 kcal x min(-1)), and rower (by 1.9 kcal x min(-1)) (all P < 0.05). The AHRM for females significantly improved the estimation of mean EE for all exercise modes, but it still overestimated mean EE on the treadmill (by 0.6 kcal x min(-1)) and cycle (by 1.2 kcal x min(-1)) (P < 0.05). CONCLUSION: When the predicted values of VO2max and HRmax are used, the Polar S410 HRM provides a rough estimate of EE during running, rowing, and cycling. Using the actual values for VO2max and HRmax reduced the individual error scores for both genders, but in females the mean EE was still overestimated by 12%.

Energy Metabolism↗
PubMed2004

How many steps/day are enough? Preliminary pedometer indices for public health.

Pedometers are simple and inexpensive body-worn motion sensors that are readily being used by researchers and practitioners to assess and motivate physical activity behaviours. Pedometer-determined physical activity indices are needed to guide their efforts. Therefore, the purpose of this article is to review the rationale and evidence for general pedometer-based indices for research and practice purposes. Specifically, we evaluate popular recommendations for steps/day and attempt to translate existing physical activity guidelines into steps/day equivalents. Also, we appraise the fragmented evidence currently available from associations derived from cross-sectional studies and a limited number of interventions that have documented improvements (primarily in body composition and/or blood pressure) with increased steps/day.A value of 10000 steps/day is gaining popularity with the media and in practice and can be traced to Japanese walking clubs and a business slogan 30+ years ago. 10000 steps/day appears to be a reasonable estimate of daily activity for apparently healthy adults and studies are emerging documenting the health benefits of attaining similar levels. Preliminary evidence suggests that a goal of 10000 steps/day may not be sustainable for some groups, including older adults and those living with chronic diseases. Another concern about using 10000 steps/day as a universal step goal is that it is probably too low for children, an important target population in the war against obesity. Other approaches to pedometer-determined physical activity recommendations that are showing promise of health benefit and individual sustainability have been based on incremental improvements relative to baseline values. Based on currently available evidence, we propose the following preliminary indices be used to classify pedometer-determined physical activity in healthy adults: (i). <5000 steps/day may be used as a 'sedentary lifestyle index'; (ii). 5000-7499 steps/day is typical of daily activity excluding sports/exercise and might be considered 'low active'; (iii). 7500-9999 likely includes some volitional activities (and/or elevated occupational activity demands) and might be considered 'somewhat active'; and (iv). >or=10000 steps/day indicates the point that should be used to classify individuals as 'active'. Individuals who take >12500 steps/day are likely to be classified as 'highly active'.

Age Factors↗
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

Effects of resistance versus aerobic training on coronary artery disease risk factors.

Individuals exhibiting "the metabolic syndrome" have multiple coronary artery disease risk factors, including insulin resistance, hyperlipidemia, hypertension, and android obesity. We performed a randomized trial to compare the effects of aerobic and resistance training regimens on coronary risk factors. Twenty-six volunteers who exhibited android obesity and at least one other risk factor for coronary artery disease were randomized to aerobic or resistance training groups. Body mass index, waist-to-hip ratio, glucose, insulin, body composition, 24-hr urinary albumin, fibrinogen, blood pressure, and lipid profile were measured at baseline and after 10 weeks of exercise training. Both groups showed a significant reduction in waist-to-hip ratio and the resistance training group also showed a reduction in total body fat. There was no significant change in mean arterial blood pressure in either group. Fasting plasma glucose, insulin, total cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides were unchanged in both groups. High-density lipoprotein (HDL) cholesterol increased (13%) with aerobic training only. Plasma fibrinogen was increased (28% and 34%, P < 0.02) in both groups and both groups showed a significant decrease (34% and 28%, P < 0.03) in microalbuminuria after their respective training regimen. In conclusion, resistance training was effective in improving body composition of middle-aged obese sedentary males. Only aerobic training was effective in raising HDL cholesterol. More studies are warranted to assess the effects of exercise on plasma fibrinogen and microalbuminuria.

Adult↗
PubMed2003

Validity of 10 electronic pedometers for measuring steps, distance, and energy cost.

PURPOSE: This study examined the effects of walking speed on the accuracy and reliability of 10 pedometers: Yamasa Skeletone (SK), Sportline 330 (SL330) and 345 (SL345), Omron (OM), Yamax Digiwalker SW-701 (DW), Kenz Lifecorder (KZ), New Lifestyles 2000 (NL), Oregon Scientific (OR), Freestyle Pacer Pro (FR), and Walk4Life LS 2525 (WL). METHODS: Ten subjects (33 +/- 12 yr) walked on a treadmill at various speeds (54, 67, 80, 94, and 107 m x min-1) for 5-min stages. Simultaneously, an investigator determined steps by a hand counter and energy expenditure (kcal) by indirect calorimetry. Each brand was measured on the right and left sides. RESULTS: Correlation coefficients between right and left sides exceeded 0.81 for all pedometers except OR (0.76) and SL345 (0.57). Most pedometers underestimated steps at 54 m x min-1, but accuracy for step counting improved at faster speeds. At 80 m x min-1 and above, six models (SK, OM, DW, KZ, NL, and WL) gave mean values that were within +/- 1% of actual steps. Six pedometers displayed the distance traveled. Most of them estimated mean distance to within +/- 10% at 80 m x min-1 but overestimated distance at slower speeds and underestimated distance at faster speeds. Eight pedometers displayed kilocalories, but except for KZ and NL, it is unclear whether this should reflect net or gross kilocalories. If one assumes they display net kilocalories, the general trend was an overestimation of kilocalories at every speed. If one assumes they display gross kilocalorie, then seven of the eight pedometers were accurate to within +/-30% at all speeds. CONCLUSION: In general, pedometers are most accurate for assessing steps, less accurate for assessing distance, and even less accurate for assessing kilocalories.

Adult↗
PubMed2003

Accuracy and reliability of 10 pedometers for measuring steps over a 400-m walk.

PURPOSE: The purpose of this study was to determine the accuracy and reliability of the following electronic pedometers for measuring steps: Freestyle Pacer Pro (FR), Kenz Lifecorder (KZ), New Lifestyles NL-2000 (NL), Omron HJ-105 (OM), Oregon Scientific PE316CA (OR), Sportline 330 (SL330) and 345 (SL345), Walk4Life LS 2525 (WL), Yamax Skeletone EM-180 (SK), and the Yamax Digi-Walker SW-701 (DW). METHODS: Ten males (34.7 +/- 12.6 yr) (mean +/- SD) and 10 females (43.1 +/- 19.9 yr) ranging in BMI from 19.8 to 33.6 kg.m-2 walked 400-m around an outdoor track while wearing two pedometers of the same model (one on the right and left sides of the body) for each of 10 models. Four pedometers of each model were assessed in this fashion. The actual steps taken were tallied by a researcher. RESULTS: The KZ, NL, and DW were the most accurate in counting steps, displaying values that were within +/-3% of the actual steps taken, 95% of the time. The SL330 and OM were the least accurate, displaying values that were within +/-37% of the actual steps, 95% of the time. The reliability within a single model (Cronbach's alpha) was >0.80 for all pedometers with the exception of the SL330. The intramodel reliability was exceptionally high (>0.99) in the KZ, OM, NL, and the DW. CONCLUSION: Due to the variation that exists among models in regard to the internal mechanism and sensitivity, not all pedometers count steps accurately. Thus, it is important for researchers who use pedometers to assess physical activity to be aware of their accuracy and reliability.

Humans↗
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↗