829 resultados para anthropometric data
Resumo:
Objective The purpose of this study was to quantify physical activity levels and determine the barriers to physical activity for women with ovarian cancer. Materials and Methods Women with ovarian cancer from 3 oncology clinics enrolled in the cross-sectional study. Physical activity and barriers to physical activity were measured using the International Physical Activity Questionnaire and Perceived Physical Activity Barriers scale, respectively. Demographic, medical, and anthropometric data were obtained from medical records. Results Ninety-five women (response rate, 41%), with a mean (SD) age of 61 (10.6) years, a body mass index of 26.5 (6.8) kg/m2, and 36.6 (28.2) months since diagnosis, participated in the study. The majority of the participants had stage III (32%) or IV (32%) ovarian cancer, were undergoing chemotherapy (41%), and had a history of chemotherapy (93%). The majority of the participants reduced their physical activity after diagnosis, with 19% meeting recommended physical activity guidelines. The participants undergoing treatment reported lower moderate-vigorous physical activity compared with those not undergoing active treatment (mean [SD], 42 [57] vs 104 [119] min/wk; P < 0.001) and less total physical activity barriers (mean [SD], 49 vs 47; P > 0.4). The greatest barriers to physical activity included fatigue (37.8%), exercise not in routine (34.7%), lack of self-discipline (32.6%), and procrastination (27.4%). Conclusions Women with ovarian cancer have low levels of physical activity. There are disease-specific general barriers to physical activity participation. The majority of the participants reduced their physical activity after diagnosis, with these patients reporting a higher number of total barriers. Behavioral strategies are required to increase physical activity adherence in this population to ensure that recommended guidelines are met to achieve the emerging known benefits of exercise oncology.
Resumo:
Virtual prototyping emerges as a new technology to replace existing physical prototypes for product evaluation, which are costly and time consuming to manufacture. Virtualization technology allows engineers and ergonomists to perform virtual builds and different ergonomic analyses on a product. Digital Human Modelling (DHM) software packages such as Siemens Jack, often integrate with CAD systems to provide a virtual environment which allows investigation of operator and product compatibility. Although the integration between DHM and CAD systems allows for the ergonomic analysis of anthropometric design, human musculoskeletal, multi-body modelling software packages such as the AnyBody Modelling System (AMS) are required to support physiologic design. They provide muscular force analysis, estimate human musculoskeletal strain and help address human comfort assessment. However, the independent characteristics of the modelling systems Jack and AMS constrain engineers and ergonomists in conducting a complete ergonomic analysis. AMS is a stand alone programming system without a capability to integrate into CAD environments. Jack is providing CAD integrated human-in-the-loop capability, but without considering musculoskeletal activity. Consequently, engineers and ergonomists need to perform many redundant tasks during product and process design. Besides, the existing biomechanical model in AMS uses a simplified estimation of body proportions, based on a segment mass ratio derived scaling approach. This is insufficient to represent user populations anthropometrically correct in AMS. In addition, sub-models are derived from different sources of morphologic data and are therefore anthropometrically inconsistent. Therefore, an interface between the biomechanical AMS and the virtual human model Jack was developed to integrate a musculoskeletal simulation with Jack posture modeling. This interface provides direct data exchange between the two man-models, based on a consistent data structure and common body model. The study assesses kinematic and biomechanical model characteristics of Jack and AMS, and defines an appropriate biomechanical model. The information content for interfacing the two systems is defined and a protocol is identified. The interface program is developed and implemented through Tcl and Jack-script(Python), and interacts with the AMS console application to operate AMS procedures.
Resumo:
Background: Body mass index (BMI) is widely used as a measure of adiposity. However, currently used cut-off values are not sensitive in diagnosing obesity in South Asian populations. Aim: To define BMI and waist circumference (WC), cut-off values representing percentage fat mass (%FM) associated with adverse health outcomes. Subjects and methods: A cross-sectional descriptive study of 285 5–14 year old Sri Lankan children (56% boys) was carried out. Fat mass (FM) was assessed using the isotope (D2O) dilution technique based on 2C body composition model. BMI and WC cut-off values were defined based on %FM associated with adverse health outcomes. Results: Sri Lankan children had a low fat free mass index (FFMI) and a high fat mass index (FMI). Individuals with the same BMI had %FM distributed over a wide range. Lean body tissue grew very little with advancing age and weight gain was mainly due to increases in body fat. BMI corresponding to 25% in males and 35% in females at 18 years was 19.2 kg/m2 and 19.7 kg/m2, respectively. WC cut-off values for males and females were 68.4 cm and 70.4 cm, respectively. Conclusion: This chart analysis clearly confirms that Sri Lankan children have a high %FM from a young age. With age, more changes occur in FM than in fat free mass (FFM). Although the newly defined BMI and WC cut-off values appear to be quite low, they are comparable to some recent data obtained in similar populations.
Resumo:
Objective: To investigate measures aimed at defining the nutritional status of cystic fibrosis (CF) populations, this study compared standard anthropometric measurements and total body potassium (TBK) as indicators of malnutrition. Methods: Height, weight, and TBK measurements of 226 children with CF from Royal Children's Hospital, Brisbane, Australia, were analyzed. Z scores for height for age, weight for age, and weight for height were analyzed by means of the National Centre for Health Statistics reference. TBK was measured by means of whole body counting and compared with predicted TBK for age. Two criteria were evaluated with respect to malnutrition: (1) a z score < -2.0 and (2) a TBK for age <80% of predicted. Results: Males and females with CF had lower mean height-for-age and weight-for-age z scores than the National Centre for Health Statistics reference (P < .01), but mean weight-for-height z score was not significantly different. There were no significant gender differences. According to anthropometry, only 7.5% of this population were underweight and 7.6% were stunted. However, with TBK as an indicator of nutritional status, 29.9% of males and 22.0% of females were malnourished. Conclusion: There are large differences in the percentage of patients with CF identified as malnourished depending on whether anthropometry or body composition data are used as the nutritional indicator. At an individual level, weight-based indicators are not sensitive indicators of suboptimal nutritional status in CF, significantly underestimating the extent of malnutrition. Current recommendations in which anthropometry is used as the indicator of malnutrition in CF should be revised.
Resumo:
In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.