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Gina M. McCaskill, Olivio J. Clay, Peng Li, Richard E. Kennedy, Kathryn L. Burgio and Cynthia J. Brown

, contributing to health inequities between Black and White male veterans. Therefore, we examined the influence of kilocalorie expenditure, based on self-report of leisure-time physical activity, on all-cause mortality, in a sample of Black and White male veterans and nonveterans in the University of Alabama at

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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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David Alexander Leaf and Holden MacRae

The purpose of this study was to examine the criterion-related validity of two indirect measures of energy expenditure (EE): American College of Sports Medicine (ACSM) predictive equations, and estimated EE based on the Caltrac accelerometer. These measures were compared in 20 community-dwelling older men and women (mean age 71 years). The strength of the relationships among major determinants of EE during self-selected speeds of treadmill and outdoor walking was also examined. EE measured by respiratory gas analysis during an exercise stress test was highly correlated with ACSM predictive equations and poorly correlated with Caltrac. Multivariate regression equations were established to evaluate the ability of independent variables—body weight and height, age, and preferred treadmill walking speed—to predict EE (dependent variable). It was concluded that the ACSM predictive equations are suitable for use in elderly individuals, and that the apparent differences in the relationships between treadmill and outdoor walking speeds on EE deserve further investigation.

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Mark W. Swanson, Eric Bodner, Patricia Sawyer and Richard M. Allman

Little is known about the effect of reduced vision on physical activity in older adults. This study evaluates the association of visual acuity level, self-reported vision, and ocular disease conditions with leisure-time physical activity and calculated caloric expenditure. A cross-sectional study of 911 subjects 65 yr and older from the University of Alabama at Birmingham Study of Aging (SOA) cohort was conducted evaluating the association of vision-related variables to weekly kilocalorie expenditure calculated from the 17-item Leisure Time Physical Activity Questionnaire. Ordinal logistic regression was used to evaluate possible associations while controlling for potential confounders. In multivariate analyses, each lower step in visual acuity below 20/50 was significantly associated with reduced odds of having a higher level of physical activity, OR 0.81, 95% CI 0.67, 0.97. Reduced visual acuity appears to be independently associated with lower levels of physical activity among community-dwelling adults.

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Faye Prior, Margaret Coffey, Anna Robins and Penny Cook

–960) +660** +636** −24 Kilocalorie expenditure 223 0 (0–289) 1051 (582–1583) 941 (461–1456) +1051** +941** −110 Body weight 224 91.3 (76.75–107.2) 89 (76.8–104.8) 88 (76.1–104) −2.3** −3.3** −1** BMI 222 32.7 (27.82–37.64) 31.68 (27.68–36.91) 31.42 (27.51–35.99) −1.02** −1.28** −0.26** Systolic BP 81 138