839 resultados para ACTIVITY INDEX


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Objectives To examine the effects of overall level and timing of physical activity (PA) on changes from a healthy body mass index (BMI) category over 12 years in young adult women. Patients and Methods Participants in the Australian Longitudinal Study on Women's Health (younger cohort, born 1973-1978) completed surveys between 2000 (age 22-27 years) and 2012 (age 34-39 years). Physical activity was measured in 2000, 2003, 2006, and 2009 and was categorized as very low, low, active, or very active at each survey, and a cumulative PA score for this 9-year period was created. Logistic regression was used to examine relationships between PA accumulated across all surveys (cumulative PA model) and PA at each survey (critical periods PA model), with change in BMI category (from healthy to overweight or healthy to obese) from 2000 to 2012. Results In women with a healthy BMI in 2000, there were clear dose-response relationships between accumulated PA and transition to overweight (P=.03) and obesity (P<.01) between 2000 and 2012. The critical periods analysis indicated that very active levels of PA at the 2006 survey (when the women were 28-33 years old) and active or very active PA at the 2009 survey (age 31-36 years) were most protective against transitioning to overweight and obesity. Conclusion These findings confirm that maintenance of very high PA levels throughout young adulthood will significantly reduce the risk of becoming overweight or obese. There seems to be a critical period for maintaining high levels of activity at the life stage when many women face competing demands of caring for infants and young children.

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The last few decades have witnessed application of graph theory and topological indices derived from molecular graph in structure-activity analysis. Such applications are based on regression and various multivariate analyses. Most of the topological indices are computed for the whole molecule and used as descriptors for explaining properties/activities of chemical compounds. However, some substructural descriptors in the form of topological distance based vertex indices have been found to be useful in identifying activity related substructures and in predicting pharmacological and toxicological activities of bioactive compounds. Another important aspect of drug discovery e. g. designing novel pharmaceutical candidates could also be done from the distance distribution associated with such vertex indices. In this article, we will review the development and applications of this approach both in activity prediction as well as in designing novel compounds.

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Tuberculosis (TB) is a life threatening disease caused due to infection from Mycobacterium tuberculosis (Mtb). That most of the TB strains have become resistant to various existing drugs, development of effective novel drug candidates to combat this disease is a need of the day. In spite of intensive research world-wide, the success rate of discovering a new anti-TB drug is very poor. Therefore, novel drug discovery methods have to be tried. We have used a rule based computational method that utilizes a vertex index, named `distance exponent index (D-x)' (taken x = -4 here) for predicting anti-TB activity of a series of acid alkyl ester derivatives. The method is meant to identify activity related substructures from a series a compounds and predict activity of a compound on that basis. The high degree of successful prediction in the present study suggests that the said method may be useful in discovering effective anti-TB compound. It is also apparent that substructural approaches may be leveraged for wide purposes in computer-aided drug design.

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The prevalence of obesity worldwide has increased dramatically over the last few decades. Poor dietary habits and low levels of exercise in adolescence are often maintained into adulthood where they can impact on the incidence of obesity and chronic diseases. A 3-year longitudinal study of anthropometric, dietary and exercise parameters was carried out annually (2005 - 2007) in 3 Irish secondary schools. Anthropometric measurements were taken in each year and analysed longitudinally. Overweight and obesity were at relatively low levels in these adolescents. Height, weight, BMI, waist and hip circumferences and TST increased significantly over the 3 years. Waist-to-hip ratio (WHR) decreased significantly over time. Boys were significantly taller than girls across the 3 years. A 3-day weighed food diary was used to assess food intake by the adolescents. Analysis of dietary intake data was determined using WISP©. Mean daily energy and nutrient intakes were reported. Mean daily energy and macronutrient intakes were analysed longitudinally. The adolescents’ diet was characterised by relatively high saturated fat intakes and insufficient fruit and vegetable consumption. The dietary pattern did not change significantly over the 3 years. Boys consumed more energy than girls over the study period. A validated questionnaire was used to assess physical activity and sedentary activity levels. Boys were substantially more active and had higher energy expenditure estimates than girls throughout the study. A significant longitudinal decrease in physical activity levels among the adolescents was observed. Both genders spent more than the recommended amount of time (hrs/day) pursing sedentary activities. The dietary pattern in these Irish adolescents is relatively poor. Of additional concern is the overall longitudinal decrease in physical activity levels. Promoting consumption of a balanced diet and increased exercise levels among adolescents will help to reduce future public health care costs due to weight-related diseases.

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BACKGROUND: Intronic variation in the FTO (fat mass and obesity-associated) gene has been unequivocally associated with increased body mass index (BMI; in kg/m(2)) and the risk of obesity in populations of different ethnicity. OBJECTIVE: We examined whether this robust genetic predisposition to obesity can be attenuated by being more physically active. DESIGN: The FTO variant rs1121980 was genotyped in 20,374 participants (39-79 y of age) from the European Prospective Investigation into Cancer and Nutrition-Norfolk Study, an ethnically homogeneous population-based cohort. Physical activity (PA) was assessed with a validated self-reported questionnaire. The interaction between rs1121980 and PA on BMI and waist circumference (WC) was examined by including the interaction term in mixed-effect models. RESULTS: We confirmed that the risk (T) allele of rs1121980 was significantly associated with BMI (0.31-unit increase per allele; P < 0.001) and WC (0.77-cm increase per allele; P < 0.001). The PA level attenuated the effect of rs1121980 on BMI and WC; ie, whereas in active individuals the risk allele increased BMI by 0.25 per allele, the increase in BMI was significantly (P for interaction = 0.004) more pronounced (76%) in inactive individuals (0.44 per risk allele). We observed similar effects for WC (P for interaction = 0.02): the risk allele increased WC by 1.04 cm per allele in inactive individuals but by only 0.64 cm in active individuals. CONCLUSIONS: Our results showed that PA attenuates the effect of the FTO rs1121980 genotype on BMI and WC. This observation has important public health implications because we showed that a genetic susceptibility to obesity induced by FTO variation can be overcome, at least in part, by adopting a physically active lifestyle.

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BACKGROUND The correlation between noninvasive markers with endoscopic activity according to the modified Baron Index in patients with ulcerative colitis (UC) is unknown. We aimed to evaluate the correlation between endoscopic activity and fecal calprotectin (FC), C-reactive protein (CRP), hemoglobin, platelets, blood leukocytes, and the Lichtiger Index (clinical score). METHODS UC patients undergoing complete colonoscopy were prospectively enrolled and scored clinically and endoscopically. Samples from feces and blood were analyzed in UC patients and controls. RESULTS We enrolled 228 UC patients and 52 healthy controls. Endoscopic disease activity correlated best with FC (Spearman's rank correlation coefficient r = 0.821), followed by the Lichtiger Index (r = 0.682), CRP (r = 0.556), platelets (r = 0.488), blood leukocytes (r = 0.401), and hemoglobin (r = -0.388). FC was the only marker that could discriminate between different grades of endoscopic activity (grade 0, 16 [10-30] μg/g; grade 1, 35 [25-48] μg/g; grade 2, 102 [44-159] μg/g; grade 3, 235 [176-319] μg/g; grade 4, 611 [406-868] μg/g; P < 0.001 for discriminating the different grades). FC with a cutoff of 57 μg/g had a sensitivity of 91% and a specificity of 90% to detect endoscopically active disease (modified Baron Index ≥ 2). CONCLUSIONS FC correlated better with endoscopic disease activity than clinical activity, CRP, platelets, hemoglobin, and blood leukocytes. The strong correlation with endoscopic disease activity suggests that FC represents a useful biomarker for noninvasive monitoring of disease activity in UC patients.

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Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering “free or low cost visits”, meeting “all of the patient’s health care needs”, and seeing “the patient quickly” were all ranked higher than geographic reasons. Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts.

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Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. ^ During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. ^ Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering "free or low cost visits", meeting "all of the patient's health care needs", and seeing "the patient quickly" were all ranked higher than geographic reasons. ^ Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts. ^

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The relationship between the frequency of eating, physical activity and Body Mass Index (BMI) was investigated. Seventy five women, aged 24 to 55, were recruited from Florida International University. Via interview, subjects provided information regarding demographics and habitual eating frequency over 24-hours, and completed both the Baecke Questionnaire of Habitual Physical Activity and the Health Insurance Plan of New York Questionnaire on Physical Activity. Pearson correlations and partial correlation coefficients were used to assess the relationship between eating frequency, physical activity, age, and BMI. Results revealed significant positive correlations between eating frequency and total physical activity scores, and leisure time physical activity scores, but not between eating frequency and physical activity on the job. Partial correlations suggest that there may be an effect of eating frequency on BMI both through an effect on physical activity and through another mechanism. These results suggest that more frequent eaters tend to be more physically active, which may partially explain why lower body weights is associated with more frequent eating.

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In the absence of telehealth technology, rural patients must travel to a regional or metropolitan hospital for a preadmission consultation one week before their surgery. Currently, examination of the patient’s chest using a stethoscope (auscultation) is not possible over a telehealth network as existing digital stethoscopes have been designed for in-person auscultation. We report on the initial phase of research which ultimately aims to design a digital stethoscope for use in the telehealth context. This initial research phase describes the complexity of the activity of preadmission clinics and the implications for the design of the stethoscope. The research is conducted through field studies of existing face-to-face and remote consultations.

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Much research has investigated the differences between option implied volatilities and econometric model-based forecasts. Implied volatility is a market determined forecast, in contrast to model-based forecasts that employ some degree of smoothing of past volatility to generate forecasts. Implied volatility has the potential to reflect information that a model-based forecast could not. This paper considers two issues relating to the informational content of the S&P 500 VIX implied volatility index. First, whether it subsumes information on how historical jump activity contributed to the price volatility, followed by whether the VIX reflects any incremental information pertaining to future jump activity relative to model-based forecasts. It is found that the VIX index both subsumes information relating to past jump contributions to total volatility and reflects incremental information pertaining to future jump activity. This issue has not been examined previously and expands our understanding of how option markets form their volatility forecasts.