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Steven P. Singleton, James T. Fitzgerald and Anne Victoria Neale

This study was conducted to determine the exercise habits and fitness status of healthy older black and white adults, ages 50 to 80 years. The 384 subjects were enrolled in a health promotion project conducted by a midwestern medical school. Self-reported exercise levels were higher for men than for women and were higher for whites compared with blacks. Age had the greatest impact on treadmill performance for both sexes. Activity levels declined with age for men but not for women. Self-reported exercise levels were highly predictive of fitness status for men but not for women. The relationship in older adults between activity levels and both measured fitness and health status needs further investigation.

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MeLisa Creamer, Heather R. Bowles, Belinda von Hofe, Kelley Pettee Gabriel, Harold W. Kohl III and Adrian Bauman

Background:

Computer-assisted techniques may be a useful way to enhance physical activity surveillance and increase accuracy of reported behaviors.

Purpose:

Evaluate the reliability and validity of a physical activity (PA) self-report instrument administered by telephone and internet.

Methods:

The telephone-administered Active Australia Survey was adapted into 2 forms for internet self-administration: survey questions only (internet-text) and with videos demonstrating intensity (internet-video). Data were collected from 158 adults (20–69 years, 61% female) assigned to telephone (telephone-interview) (n = 56), internet-text (n = 51), or internet-video (n = 51). Participants wore an accelerometer and completed a logbook for 7 days. Test-retest reliability was assessed using intraclass correlation coefficients (ICC). Convergent validity was assessed using Spearman correlations.

Results:

Strong test-retest reliability was observed for PA variables in the internet-text (ICC = 0.69 to 0.88), internet-video (ICC = 0.66 to 0.79), and telephone-interview (ICC = 0.69 to 0.92) groups (P-values < 0.001). For total PA, correlations (ρ) between the survey and Actigraph+logbook were ρ = 0.47 for the internet-text group, ρ = 0.57 for the internet-video group, and ρ = 0.65 for the telephone-interview group. For vigorous-intensity activity, the correlations between the survey and Actigraph+logbook were 0.52 for internet-text, 0.57 for internet-video, and 0.65 for telephone-interview (P < .05).

Conclusions:

Internet-video of the survey had similar test-retest reliability and convergent validity when compared with the telephone-interview, and should continue to be developed.

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Barbara B. Brown and Carol M. Werner

Background:

Accelerometer output feedback might enable assessment of recall biases for moderate bouts by obese and nonobese individuals; accelerometry might also help residents recall destinations for moderate-intensity walking bouts.

Methods:

Adult residents’ 1-week accelerometer-measured physical activity and obesity status were measured before and after a new rail stop opened (n = 51 Time 1; n = 47 Time 2). Participants recalled the week’s walking bouts, described them as brisk (moderate) or not, and reported a rail stop destination or not.

Results:

At the end of the week, we provided accelerometry output to residents as a prompt. Recall of activity intensity was accurate for about 60% of bouts. Nonobese participants had more moderate bouts and more “stealth exercise” —moderate bouts recalled as not brisk—than did obese individuals. Obese participants had more overestimates—recalling light bouts as brisk walks—than did nonobese individuals. Compared with unprompted recall, accelerometry-prompted recalls allowed residents to describe where significantly more moderate bouts of activity occurred.

Conclusion:

Coupling accelerometry feedback with self-report improves research by measuring the duration, intensity, and destination of walking bouts. Recall errors and different patterns of errors by obese and nonobese individuals underscore the importance of validation by accelerometry.

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Jeanne F. Nichols, Hilary Aralis, Sonia Garcia Merino, Michelle T. Barrack, Lindsay Stalker-Fader and Mitchell J. Rauh

There is a growing need to accurately assess exercise energy expenditure (EEE) in athletic populations that may be at risk for health disorders because of an imbalance between energy intake and energy expenditure. The Actiheart combines heart rate and uniaxial accelerometry to estimate energy expenditure above rest. The authors’ purpose was to determine the utility of the Actiheart for predicting EEE in female adolescent runners (N = 39, age 15.7 ± 1.1 yr). EEE was measured by indirect calorimetry and predicted by the Actiheart during three 8-min stages of treadmill running at individualized velocities corresponding to each runner’s training, including recovery, tempo, and 5-km-race pace. Repeated-measures ANOVA with Bonferroni post hoc comparisons across the 3 running stages indicated that the Actiheart was sensitive to changes in intensity (p < .01), but accelerometer output tended to plateau at race pace. Pairwise comparisons of the mean difference between Actiheart- and criterion-measured EEE yielded values of 0.0436, 0.0539, and 0.0753 kcal · kg−1 · min−1 during recovery, tempo, and race pace, respectively (p < .0001). Bland–Altman plots indicated that the Actiheart consistently underestimated EEE except in 1 runner’s recovery bout. A linear mixed-model regression analysis with height as a covariate provided an improved EEE prediction model, with the overall standard error of the estimate for the 3 speeds reduced to 0.0101 kcal · kg−1 · min−1. Using the manufacturer’s equation that combines heart rate and uniaxial motion, the Actiheart may have limited use in accurately assessing EEE, and therefore energy availability, in young, female competitive runners.

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Kimberly A. Smith, Michael Gallagher, Anne E. Hays, Fredric L. Goss and Robert Robertson

Background:

Pedometers are most accurate at measuring steps, less accurate at estimating distance, and even less accurate at estimating kilocalorie expenditure. The purpose of this investigation was to create a Physical Activity Index (PAI) using pedometer step counts and rating of perceived exertion (RPE) to enhance the ability to estimate kilocalorie expenditure during walking exercise.

Methods:

Thirty-two females performed 3 counterbalanced walking bouts. During each bout, oxygen consumption, RPE, and step counts were measured. The PAI was calculated as the product of RPE and step count for each of the bouts.

Results:

Concurrent validation of the PAI was established using VO2 as the criterion variable. A multiple regression analysis revealed a strong, positive relation between PAI score and VO2 (r = .91). Data were then used to develop a statistical model to estimate kcal expenditure using the PAI score as the predictor variable.

Conclusion:

The PAI was found to be an accurate method of estimating kcal expenditure and is a simple, unobtrusive and inexpensive tool which may be used in public health settings.

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Joanna Kostka, Tomasz Kostka and Ewa Borowiak

Background:

The goal of this study was to assess the physical activity (PA) and its determinants of older people living in the 3 different environments.

Methods:

Three equal (n = 693 each) groups of individuals aged ≥65 years living in urban, rural and institutional environments took part in this study. PA was measured by the Seven Day Recall PA Questionnaire (energy expenditure—PA-EE) and the Stanford Usual Activity Questionnaire (health-related behaviors—PA-HRB).

Results:

PA-EE was highest in the rural environment and lowest in nursing homes. PA-HRB were most common in urban area. Older age, lower education level, several concomitant diseases and the number of systematically used medications were consistently related to lower PA-EE and PA-HRB. Smoking habit, presence of hypertension, musculoskeletal and gastrointestinal disorders had different association to PA-EE and PA-HRB in the 3 environments.

Conclusions:

Subpopulations of older people differ from the general population with regard to their level of PA and its association with sociodemographic data and concomitant diseases. Concomitant serious diseases significantly decrease the level of PA of older subjects. The relationship between PA and nondebilitating disorders may vary depending on the living environment or PA assessment methodology.

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Melissa Raymond, Adele Winter and Anne E. Holland

Background:

Older adults undergoing rehabilitation may have limited mobility, slow gait speeds and low levels of physical activity. Devices used to quantify activity levels in older adults must be able to detect these characteristics.

Objective:

To investigate the validity of the Positional Activity Logger (PAL2) for monitoring position and measuring physical activity in older inpatients (slow stream rehabilitation).

Methods:

Twelve older inpatients (≥65 years) underwent a 1-hour protocol (set times in supine, sitting, standing; stationary and moving). Participants were video-recorded while wearing the PAL2. Time spent in positions and walking (comfortable and fast speeds) were ascertained through video-recording analysis and compared with PAL2 data.

Results:

There was no difference between the PAL2 and video recording for time spent in any position (P-values 0.055 to 0.646). Walking speed and PAL2 count were strongly correlated (Pearson’s r = .913, P < .01). The PAL2 was responsive to within-person changes in gait speed: activity count increased by an average of 52.47 units (95% CI 3.31, 101.63). There was 100% agreement for transitions between lying to sitting and < 1 transition difference between siting to standing.

Conclusion:

The PAL2 is a valid tool for quantifying activity levels, position transitions, and within-person changes in gait speed in older inpatients.

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Daniel P. Hatfield, Virginia R. Chomitz, Kenneth Chui, Jennifer M. Sacheck and Christina D. Economo

Background:

Associations between physical activity (PA) intensity and volume and adolescents’ cardiometabolic health have research, policy, and practice implications. This study compares associations between cardiometabolic risk factors and 1) moderate-to-vigorous PA (MVPA) minutes versus total PA volume (accelerometer-derived total activity counts, TAC) and 2) light PA volume (counts at light intensity, L-TAC) versus moderate-to-vigorous PA volume (counts at moderate-to-vigorous intensity, MV-TAC).

Methods:

2105 adolescents from 2003– 2006 NHANES were included. Independent variables were MVPA minutes, TAC, L-TAC, and MV-TAC. Regression models tested associations between PA variables and continuous metabolic risk index (CMRI), waist circumference, systolic and diastolic blood pressure, HDL, insulin, and triglycerides.

Results:

TAC demonstrated a slightly stronger inverse association with CMRI (P = .004) than did MVPA (P = .013). TAC and MVPA were both associated with systolic and diastolic pressure, HDL, and insulin; associations were similar or slightly stronger for TAC. L-TAC and MV-TAC were both associated with CMRI and HDL. Only L-TAC was associated with diastolic pressure. Only MV-TAC was associated with waist circumference, systolic pressure, and insulin.

Conclusions:

Compared with MVPA minutes, TAC demonstrates similar or slightly stronger associations with cardiometabolic risk factors. L-TAC and MV-TAC appear similarly associated with adolescents’ clustered risk but differently associated with individual risk factors.

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Holiday A. Durham, Miriam C. Morey, Cheryl A. Lovelady, Rebecca J. Namenek Brouwer, Katrina M. Krause and Truls Østbye

Background:

Low physical activity (PA) during the postpartum period is associated with weight retention. While patterns of PA have been examined in normal weight women during this period, little is known about PA among overweight and obese women. The aim of this cross-sectional study was to investigate PA and determine the proportion of women meeting recommendations for PA.

Methods:

Women (n = 491), with a body mass index (BMI) ≥ 25 kg/m2 were enrolled in a behavioral intervention. PA was assessed at six weeks postpartum using the Seven-Day PA Recall.

Results:

Women averaged 923 ± 100 minutes/day of sedentary/ light and 33 ± 56 minutes/day of combined moderate, hard, and very hard daily activity. Women with a BMI ≥ 40 kg/m2 reported more time in sedentary/light activities and less hours of sleep than those with a lower BMI. Only 34% met national PA guidelines; this proportion was significantly lower among blacks (OR 0.5, CI 0.3−0.9).

Conclusions:

These overweight and obese postpartum women reported a large percentage of time spent in sedentary/light activity, and a high proportion failed to meet minimal guidelines for PA. Promotion of PA in the postpartum period should focus on reducing sedentary behaviors and increasing moderate PA.

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Nicolas Aguilar-Farias, Wendy J. Brown, Tina L. Skinner and G.M.E.E. (Geeske) Peeters

Background: The purpose was to assess metabolic equivalent (MET) values of common daily activities in middle-age and older adults in free-living environments and compare these with MET values listed in the compendium of physical activities (CPA). Methods: Sixty participants (mean age = 71.5, SD = 10.8) completed a semistructured protocol of sitting, lying, self-paced walking, and 4 self-selected activities in their residences. Oxygen consumption was measured using portable indirect calorimetry, to assess METs for each activity relative to VO2 at rest (VO2 during activity/VO2 at rest). Measured MET values for 20 different activities were compared with those in the CPA, for the total sample and for participants aged 55–64, 65–74, and 75–99 years. Results: Measured METs for sitting, walking, sweeping, trimming, and laundry were significantly different from the CPA values. Measured MET values for sedentary activities were lower in all age groups, and those for walking and household activities were higher in the youngest age group, than the CPA values. For gardening activities, there was a significant decline in measured METs with age. Conclusions: Some measured MET values in older people differed from those in the CPA. The values reported here may be useful for future research with younger, middle-age, and older-old people.