Lanningham‐Foster, Lorraine

AbstractBackgroundCompelling evidence supports multiple benefits of physical activity (PA) even in small bursts. Less than 50% of Americans achieve recommended PA levels, lower still for individuals living with chronic illness or disease.PurposeThe purpose of this study was to develop and evaluate the feasibility and preliminary effects of 3‐min follow‐along video scenarios to promote brief episodes of low–moderate levels of PA among individuals with chronic diseases.MethodsGuided by our previous studies and self‐efficacy theory, the program (WellMe in 3© for Patients) was modeled after another program developed for healthcare staff. An advisory panel and a health and fitness expert guided the creation of twelve 3‐min video scenarios that included two individuals living with chronic illness and a fitness leader who guided the PA scenarios and how to adapt them based on limitations. The 12 scenarios included 3 min of aerobic activities, stretching, or balance. Preliminary pilot effects were measured among 39 patients living with chronic conditions for one month. Standardized instruments were used to measure PA levels, PA self‐efficacy (SE), and quality of life (QoL); usability and satisfaction were assessed using researcher‐developed tools. Descriptive and inferential statistics were used to evaluate change over time.ResultsTwelve video scenarios were created tailored to persons with chronic illness. Thirty‐nine participants piloted the program, reporting an average of two chronic conditions. Baseline QoL scores were lower than normative data, self‐efficacy scores were low‐to‐moderate, and PA levels were very low. Participants averaged using one video per day. 62% of participants provided complete self‐reported pre‐ and post‐QoL and SE data and 41% provided pre‐ and post‐PA (accelerometer) data. Significant improvements were found for general health and energy scores, and trends were found for self‐efficacy scores. PA levels were highly variable with nonsignificant increases from baseline. Effect sizes were low–moderate for several measures. About 79% of participants rated program “Very good”; all recommended the program.Linking Evidence to ActionPhysical activity has multiple health benefits for all people including those living with chronic conditions. Even short bouts of physical activity have health benefits. A program of 3‐min follow‐along PA videoclips for individuals living with chronic disease holds promise for clinicians and researchers.

OBJECTIVE. In this study, we investigated the accuracy of measuring walking steps with commercially available pedometers and an accelerometer-based step-counter in normal and overweight children. Our primary hypothesis was that commercially available pedometers are not an accurate measure of walking steps in normal and overweight children while walking. Our secondary hypothesis was that the accelerometer-based step-counter provides an accurate measure of walking steps in normal and overweight children. METHODS. Thirteen boys (11 ± 1 years) and 14 girls (11 ± 1 years) who ranged in BMI from 15 to 27 kg/m2 (16 normal and 11 overweight or obese) were recruited. Each child wore 4 pedometers at the waist and 1 accelerometer-based step-counter on each ankle. Steps were manually counted and energy expenditure was measured while the child walked on the treadmill at 0.5, 1.0, 1.5, and 2.0 mph, each for 5 minutes. The step-counting devices were also validated while children walked on level ground at a self-selected pace. RESULTS. For the commercially available pedometers at the lowest speed of 0.5 mph, the percentage error approximated 100% for both of the pedometers. At the fastest speed of 2.0 mph, the percentage error approximated 60%. Conversely the accelerometer-based step-counter showed a percentage error of 24% ± 22% (mean ± SD) at 0.5 mph; however, as walking speed increased, the error declined to 5% ± 8% at 1.0 mph, 4% ± 5% at 1.5 mph, and 2% ± 2% at 2.0 mph. The relationship between steps counted and walking energy expenditure showed good linear correlation. CONCLUSIONS. Commercially available pedometers are less accurate for measuring walking and require discretion in their use for children. The accuracy of the accelerometer-based step-counter enables it to be used as a tool to assess and potentially promote physical activity in normal and overweight children.

The devastating impact of obesity on global health is without question and it is generally agreed that low levels of physical activity, particularly sitting (i.e., sedentariness), are important in its pathogenesis. Therefore, the measure of physical activity such as walking is vital to its use in the research and clinical milieu. This study investigated three accelerometry parameters (sampling rate, range, and data depth) on ten healthy subjects (BMI 18–31 kg/m 2 ) walking on a calibrated treadmill at eight speeds (0, 0.95, 1.74, 2.48, 3.22, 4.04, 4.83, and 5.70 km/h) while wearing a three-axis accelerometer on the thigh (Crossbow Technology, San Jose, CA) in order to find an optimal system for the determination of walking speed, as well as a new data analysis strategy using a differentiation of the acceleration values (jerk). Twenty-four sampling rates (2–25 Hz in 1-Hz intervals) and seven acceleration ranges (± 1 g – ± 2.5 g at 0.25- g intervals) were used to create a 24 × 7 factorial design. Data was also truncated from two to seven digits in the mantissa. This study found that although there is an improvement in walking speed prediction when sampling rate was set above 4 Hz ( P<0.0002), there was no further improvement when the sampling rate is set higher. This study found that there is an increase in walking speed prediction accuracy when the range of acceleration is limited to ± 1 g ( P<0.0024 for ± 2 g versus ± 1 g). This study found that increasing or decreasing data depth has no impact on walking speed prediction accuracy. Further, this study found that a model based on jerk was accurate at predicting walking speeds ( r 2 0.9 for all comparisons). For measuring walking using a sensor on the thigh, there is no significant improvement gained by large sampling rates, data ranges, or data precision. A model based on the time rate of change of acceleration is a valid analysis tool for measuring walking.

OBJECTIVE—Diminished daily physical activity explains, in part, why obesity and diabetes have become worldwide epidemics. In particular, chair use has replaced ambulation, so that obese individuals tend to sit for ∼2.5 h/day more than lean counterparts. Here, we address the hypotheses that free-living daily walking distance is decreased in obesity compared with lean subjects and that experimental weight gain precipitates decreased daily walking. RESEARCH DESIGN AND METHODS—During weight-maintenance feeding, we measured free-living walking using a validated system that captures locomotion and body movement for 10 days in 22 healthy lean and obese sedentary individuals. These measurements were then repeated after the lean and obese subjects were overfed by 1,000 kcal/day for 8 weeks. RESULTS—We found that free-living walking comprises many (∼47) short-duration (&lt;15 min), low-velocity (∼1 mph) walking bouts. Lean subjects walked 3.5 miles/day more than obese subjects (n = 10, 10.3 ± 2.5 vs. n = 12, 6.7 ± 1.8 miles/day; P = 0.0009). With overfeeding, walking distance decreased by 1.5 miles/day compared with baseline values (−1.5 ± 1.7 miles/day; P = 0.0005). The decrease in walking that accompanied overfeeding occurred to a similar degree in the lean (−1.4 ± 1.9 miles/day; P = 0.04) and obese (−1.6 ± 1.7 miles/day; P = 0.008) subjects. CONCLUSIONS—Walking is decreased in obesity and declines with weight gain. This may represent a continuum whereby progressive increases in weight are associated with progressive decreases in walking distance. By identifying walking as pivotal in weight gain and obesity, we hope to add credence to an argument for an ambulatory future.

OBJECTIVE. We examined the effect of activity-enhancing screen devices on children's energy expenditure compared with performing the same activities while seated. Our hypothesis was that energy expenditure would be significantly greater when children played activity-promoting video games, compared with sedentary video games. METHODS. Energy expenditure was measured for 25 children aged 8 to 12 years, 15 of whom were lean, while they were watching television seated, playing a traditional video game seated, watching television while walking on a treadmill at 1.5 miles per hour, and playing activity-promoting video games. RESULTS. Watching television and playing video games while seated increased energy expenditure by 20 ± 13% and 22 ± 12% above resting values, respectively. When subjects were walking on the treadmill and watching television, energy expenditure increased by 138 ± 40% over resting values. For the activity-promoting video games, energy expenditure increased by 108 ± 40% with the EyeToy (Sony Computer Entertainment) and by 172 ± 68% with Dance Dance Revolution Ultramix 2 (Konami Digital Entertainment). CONCLUSIONS. Energy expenditure more than doubles when sedentary screen time is converted to active screen time. Such interventions might be considered for obesity prevention and treatment.

Obesity occurs when energy intake exceeds energy expenditure. Humans expend energy through purposeful exercise and through changes in posture and movement that are associated with the routines of daily life [called nonexercise activity thermogenesis (NEAT)]. To examine NEAT's role in obesity, we recruited 10 lean and 10 mildly obese sedentary volunteers and measured their body postures and movements every half-second for 10 days. Obese individuals were seated, on average, 2 hours longer per day than lean individuals. Posture allocation did not change when the obese individuals lost weight or when lean individuals gained weight, suggesting that it is biologically determined. If obese individuals adopted the NEAT-enhanced behaviors of their lean counterparts, they might expend an additional 350 calories (kcal) per day.