Scott B Going

PMID: 17989943;Abstract:

Differences in bone among racial/ethnic groups may be explained by differences in body size and shape. Previous studies have not completely explained differences among white, Asian, and Hispanic groups during growth. To determine racial/ethnic differences and predictors of bone mass in early pubertal girls, we measured bone mineral content (BMC) in white, Hispanic, and Asian sixth-grade girls across six states in the United States. We developed models for predicting BMC for the total-body, distal radius, total-hip, and lumbar spine for 748 subjects. For each of the bone sites, the corresponding area from dual-energy X-ray absorptiometry (DXA) was a strong predictor of BMC, with correlations ranging 0.78-0.98, confirming that larger subjects have more BMC. Anthropometric measures of bone area were nearly as effective as bone area from DXA at predicting BMC. For total-body, distal radius, lumbar spine, and total-hip BMC, racial/ethnic differences were explained by differences in bone area, sexual maturity, physical activity, and dairy calcium intake. Bone size explained most of the racial/ethnic differences in BMC, although behavioral indicators were also significant predictors of BMC. © 2007 Springer Science+Business Media, LLC.

ABSTRACT:: Global positioning system (GPS) watches have been introduced commercially, converting frequent measurements of time, location, speed (pace), and elevation into energy expenditure (EE) estimates. The purpose of this study was to compare EE estimates of 4 different GPS watches (Forerunner, Suunto, Polar, Adeo) at various walking speeds, to EE estimate from a triaxial accelerometer (RT3), which was used as a reference measure in this study. Sixteen healthy young adults completed the study. Participants wore 4 different GPS watches and an RT3 accelerometer, and walked 6 minute intervals on an outdoor track at 3 speeds (3, 5 and 7 km/hr). EE estimates from each GPS watch were compared to EE estimates from RT3 accelerometer using correlation coefficients and multiple linear regression analysis. The GPS watches demonstrated lower reliability (intra-class correlation coefficient) across trials when compared with the RT3, particularly at the higher speed, 7km/hr. Three GPS watches (Forerunner, Polar, and Suunto) significantly, and consistently, underestimated EE compared to the reference EE given by the RT3 accelerometer (average mean difference: Garmin, -50.5%, Polar, -41.7%, and Suunto, -41.7%, all p 0.001). Results suggested that caution should be exercised when using commercial GPS watches to estimate EE in athletes during field-based testing and training.

PMID: 18716855;PMCID: PMC2613296;Abstract:

Background: Radiographic joint changes are used to diagnose osteoarthritis; however, they alone do not adequately predict who experiences symptoms. Purpose: To examine psychological risk and resilience factors in combination with an objective indicator of disease severity (knee X-rays) to determine what factors best account for pain and physical functioning in an early knee osteoarthritis (KOA) population. Methods: Structural equation modeling was used to analyze data from 275 men and women with early KOA. Results: Structural equation modeling yielded a fair to good fit of the data, suggesting that both risk and resilience were important in predicting pain and physical functioning over and above disease severity in the expected directions. Resilience's effect on pain was mediated through self-efficacy, suggesting that higher self-efficacy was linked to lower pain and better physical functioning. Conclusions: Results provide an integrative model of adjustment to early KOA and may be important to the prevention of disability in this population. © 2008 The Society of Behavioral Medicine.

To examine whether components of body composition (size, fat mass, and fat-free mass) were related to physical activity.

There is no doubt that body composition changes with aging. Some general trends have been described, including an increase in body weight and fat mass in middle age followed by a decrease in stature, weight, FFM, and body cell mass at older ages. Losses in muscle, protein, and bone mineral contribute to the decline in FFM; however, the onset and rates of decline remain controversial. Most data are available for men and women 80 yr and we know relatively little about the normal status and the changes that occur in body composition in elderly men and women. This situation has developed in part because the changes that occur in various body constituents with aging confound the estimation of body composition by traditional techniques. Hence, there is a need for longitudinal reference data in persons 80 yr of age, both to describe the normal status and to develop valid prediction equations for estimating body composition in older men and women in settings outside the laboratory. This should be possible using new technologies and approaches based on multiple component models of body composition. An understanding of the normal changes in body composition with increasing age, the normal variation in these changes, and their health implications is important for the health, nutritional support, and pharmacologic treatment of elderly men and women in the United States. The information is especially important because elderly men and women, in terms of both numbers and health care dollars, represent the most rapidly expanding segment of the U.S. population.