Patterns of physical activity in free-living adults in the Southern United States

Abstract

Objective: To examine the relationship between the amount and patterns of physical activity (PA), body fatness, and age in a heterogeneous adult population in the free living. Design: Cross-sectional study of the amount of PA over a 1-week period. The amount of body movements during PA (PA counts * 10 3 ) and time spent on various PA intensity categories were calculated from a triaxial accelerometer and compared with subject characteristics, including body fat from hydrodensitometry. Participants: Adult healthy men (n ¼ 48) and women (n ¼ 72) were recruited from the Nashville, Tennessee area and their PA was monitored in their free-living environment. Results: The average weekday PA counts (176.5760.3, P ¼ 0.002, r 2 ¼ 0.294), PA counts day-to-day variability (47.3732.7, P ¼ 0.002, r 2 ¼ 0.286), daily maximum PA counts (241.9789.2, P ¼ 0.001, r 2 ¼ 0.327), minute-to-minute variability on weekdays (0.28170.091, P ¼ 0.001, r 2 ¼ 0.362), and the difference between maximum and minimum daily PA counts (130.6778.3, P ¼ 0.008, r 2 ¼ 0.243) were significantly and negatively correlated with body fatness. During awake time, both men and women spent 10-12 h on low intensity (1.0-2.9 metabolic equivalents (METs)) PA, approximately 1 h on moderate (3.0-5.9 MET), and less than 10 min on vigorous (46.0 MET) PA each day. On weekends, men and women spent more time at rest (1 MET), less time on low-intensity PA, and men spent more time on moderate PA than on weekdays. Conclusions: In adults living in the Southern US the amount of free-living PA was negatively correlated with body fatness. Both men and women spent the majority of active time on low and moderate PA. PA patterns on weekends were different than on weekdays and were related to sex and age, but not to body fatness.

Within- and between-individual variability in estimated energy expenditure and habitual physical activity among young adults

“…Since few studies have specifically addressed the CV for AEE using the Bouchard diary direct comparisons are difficult to make. Using a more objective assessment tool, Buchowski et al (2004) examined patterns of PA among adults using an accelerometer and determined the CV for accelerometer counts over a 7-day-period approximated 27%, ranging from B2 to 85%. The slightly higher mean CV obtained in the current study is most likely the result of fewer assessment days with a less objective instrument.…”

Evaluation of a Questionnaire to Assess Sedentary and Active Behaviors in the Southern Community Cohort Study

“…The values from the Compendium of Physical Activities used in the conversion algorithm relies on group averages to estimate activity intensity, and these estimates may be imprecise for certain individuals. 18 The RT3 counts cut points used for the PA activity levels categorization 23 were obtained in young men and therefore, could lead to miscategorization of some activities in this study and affect the relative validity of the PAQ. There is also a possibility PAQ missed some modes of activity such as transportation and child or elderly care.…”

“…23 The epoch interval was set at 1-min and output was expressed as the vector magnitude in counts per minute. Wearing time was estimated using established algorithms 24 adapted for the RT3.…”

Energy balance and obesity: a UK perspective on the gluttonyv.sloth debate

“…Direct measurements of PAEE by tri-axial accelerometry during 1 week in free-living overweight men and women in the Southern USA show that 95 % of their active time is spent in low-intensity PAEE, suggesting a sedentary lifestyle. Importantly, the amount of free-living PAEE negatively correlated with body fatness to the extent that in ageand sex-adjusted multiple regressions, average and maximum weekday PAEE explained 29-32 % of the variation in body fat (70) . Such information and that shown in Table 2 clearly indicate that physical activity behaviour is markedly reduced in the obese in line with common experience, with the latter study showing that such changes can contribute to obesity.…”