750 resultados para Nutrition surveys
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BACKGROUND Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.
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Community School District Audit Report - Special Investigation
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Objective: To assess if screening programs and treatment of preoperative malnutrition have been implemented into surgical practice to decrease morbidity. There is strong evidence that postoperative morbidity can be minimized by early identifying and treating patients at nutritional risk before major surgery.The validated nutritional risk score (NRS) is recommended by the European Society of Parenteral and Enteral Nutrition for nutritional screening. It remains unclear whether routine preoperative nutritional assessment and perioperative nutrition is widely implemented.Methods: A survey was conducted in 173 Swiss and Austrian surgical departments. Implementation of nutritional screening, perioperative nutrition, and estimated impact on clinical outcome were assessed. Non-responders were repeatedly contacted by the authors.Results: The overall response rate was 55%, whereby 69% (54/78) of Swiss and 44% (42/95) of Austrian centers responded. Despite 80% and 59% of the responding centers are aware of a reduced complication rate and shortened hospital stay, respectively, only 20% of them implemented routine nutritional screening. Financial (49%) and logistic restrictions (33%) are the predominant reasons against the routine clinical use. Screening is mainly performed either in the outpatient's clinic (52%) or during admission (54%). The NRS is only used by 14%. Instead, various clinical (78%), e.g. BMI and laboratory findings (56%), e.g. albumine, are used. Indication for perioperative nutrition is based on preoperative screening in 49%.While 23% use preoperative nutrition, 68% apply nutritional support pre- and postoperatively. Preoperative nutritional treatment ranged from three days (33%), to five days (31%) and even seven days (20%).Conclusion: Despite malnutrition is well recognized as major risk factor for increased postoperative morbidity, the majority of surgeons are reluctant to implement routine screening and nutritional support. If nutritional assessment is performed, local institutional screening parameters are still preferred. It remains difficult to overcome traditions, and to change surgeon's mind.
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Continuous respiratory-exchange measurements were performed on ten moderately obese and ten lean young women for 1 h before, 3 h during, and 3 h after either parenteral (IV) or intragastric (IG) administration of a nutrient mixture infused at twice the postabsorptive, resting energy expenditure (REE). REE rose significantly from 0.98 +/- 0.02 to 1.13 +/- 0.03 kcal/min (IV) and from 0.99 +/- 0.02 to 1.13 +/- 0.02 kcal/min (IG) in the lean group; from 1.10 +/- 0.02 to 1.27 +/- 0.03 kcal/min (IV) and from 1.11 +/- 0.02 to 1.29 +/- 0.03 (IG) in the obese group. These increases resulted in similar nutrient-induced thermogenesis of 10.0 +/- 0.7% (IV) and 9.3 +/- 0.9% (IG) in the lean group; of 9.2 +/- 0.7% (IV) and 10.1 +/- 0.8% (IG) in the obese. Nutrient utilization was comparable in both groups and in both routes of administration, although the response time to IG feeding was delayed. These results showed no significant difference in both the thermogenic response and nutrient utilization between moderately obese and control groups using acute IV or IG feeding.
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This research involved two studies: one to determine the local geoid to obtain mean sea level elevation from a global positioning system (GPS) to an accuracy of ±2 cm, and the other to determine the location of roadside features such as mile posts and stop signs for safety studies, geographic information systems (GIS), and maintenance applications, from video imageries collected by a van traveling at traffic speed.
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Background: The objective of the present study was to compare three different sampling and questionnaire administration methods used in the international KIDSCREEN study in terms of participation, response rates, and external validity. Methods: Children and adolescents aged 8–18 years were surveyed in 13 European countries using either telephone sampling and mail administration, random sampling of school listings followed by classroom or mail administration, or multistage random sampling of communities and households with self-administration of the survey materials at home. Cooperation, completion, and response rates were compared across countries and survey methods. Data on non-respondents was collected in 8 countries. The population fraction (PF, respondents in each sex-age, or educational level category, divided by the population in the same category from Eurostat census data) and population fraction ratio (PFR, ratio of PF) and their corresponding 95% confidence intervals were used to analyze differences by country between the KIDSCREEN samples and a reference Eurostat population. Results: Response rates by country ranged from 18.9% to 91.2%. Response rates were highest in the school-based surveys (69.0%–91.2%). Sample proportions by age and gender were similar to the reference Eurostat population in most countries, although boys and adolescents were slightly underrepresented (PFR <1). Parents in lower educational categories were less likely to participate (PFR <1 in 5 countries). Parents in higher educational categories were overrepresented when the school and household sampling strategies were used (PFR = 1.78–2.97). Conclusion: School-based sampling achieved the highest overall response rates but also produced slightly more biased samples than the other methods. The results suggest that the samples were sufficiently representative to provide reference population values for the KIDSCREEN instrument.
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BACKGROUND: There is a growing use of mobile devices to access the Internet. We examined whether participants who used a mobile device to access a brief online survey were quicker to respond to the survey but also, less likely to complete it than participants using a traditional web browser. FINDINGS: Using data from a recently completed online intervention trial, we found that participants using mobile devices were quicker to access the survey but less likely to complete it compared to participants using a traditional web browser. More concerning, mobile device users were also less likely to respond to a request to complete a six week follow-up survey compared to those using traditional web browsers. CONCLUSIONS: With roughly a third of participants using mobile devices to answer an online survey in this study, the impact of mobile device usage on survey completion rates is a concern. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01521078.
What is "clinical data"? Why and how can they be collected during field surveys on medicinal plants?
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ETHNOPHARMACOLOGICAL RELEVANCE: "Reverse pharmacology", also called "bedside-to-bench" or "field to pharmacy" approach, is a research process starting with documentation of clinical outcome as observed by patients with different therapeutic regimens. The treatment most significantly associated with cure is selected for future studies: first, clinical safety and efficacy; then in vivo and vitro studies. Some clinical data, i.e. details on patient status and progress, can be collected during ethnobotanical surveys; they will help clinical researchers and, once effectiveness and safety are established, will also help users of traditional medicine make safer and more effective choices. To gather clinical data successfully, ethnopharmacologists need to be backed by an appropriate team of specialists in medicine and epidemiology. Ethnopharmacologists can also gather important data on traditional medicine safety. MATERIALS AND METHODS: The first step is to create a consensus on the meaning of "clinical data", their interest and importance. An understanding of why "a cure is not a proof of effectiveness" is a starting point to avoid faulty interpretation of the clinical observations. RESULTS: Experience showed that, with the "bedside-to-bench" approach, a treatment derived from traditional recipe can be scientifically validated (in terms of safety and effectiveness) with a cost of less than a million euros, thus providing an end-product that is affordable, available and sustainable. CONCLUSIONS: With rigorous clinical study results, medicinal plant users gain the possibility to refine heath strategies. The field surveyor may gain a better relationship with the population, once she/he is seen as bringing information useful for the quality of care in the community.