884 resultados para Food and Nutrition Information Center (U.S.)


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BACKGROUND/OBJECTIVES: Phytoestrogens are estradiol-like natural compounds found in plants that have been associated with protective effects against chronic diseases, including some cancers, cardiovascular diseases and osteoporosis. The purpose of this study was to estimate the dietary intake of phytoestrogens, identify their food sources and their association with lifestyle factors in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. SUBJECTS/METHODS: Single 24-hour dietary recalls were collected from 36 037 individuals from 10 European countries, aged 35–74 years using a standardized computerized interview programe (EPIC-Soft). An ad hoc food composition database on phytoestrogens (isoflavones, lignans, coumestans, enterolignans and equol) was compiled using data from available databases, in order to obtain and describe phytoestrogen intakes and their food sources across 27 redefined EPIC centres. RESULTS: Mean total phytoestrogen intake was the highest in the UK health-conscious group (24.9 mg/day in men and 21.1 mg/day in women) whereas lowest in Greece (1.3 mg/day) in men and Spain-Granada (1.0 mg/day) in women. Northern European countries had higher intakes than southern countries. The main phytoestrogen contributors were isoflavones in both UK centres and lignans in the other EPIC cohorts. Age, body mass index, educational level, smoking status and physical activity were related to increased intakes of lignans, enterolignans and equol, but not to total phytoestrogen, isoflavone or coumestan intakes. In the UK cohorts, the major food sources of phytoestrogens were soy products. In the other EPIC cohorts the dietary sources were more distributed, among fruits, vegetables, soy products, cereal products, non-alcoholic and alcoholic beverages. CONCLUSIONS: There was a high variability in the dietary intake of total and phytoestrogen subclasses and their food sources across European regions.

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Objective: A phytoestrogen-rich diet has been suggested to protect against a variety of common diseases but UK intake data on phytoestrogens or their food sources is sparse. This study aims to estimate the average intake of isoflavones, lignans, enterolignans and coumestrol from 7-day food diaries (7dFD), and to provide data on total isoflavone, lignan and phytoestrogen consumption by food group. Design: Development of a food composition database for twelve phytoestrogens and analysis of soya food and phytoestrogen consumption in a population-based study. Setting: Men and women, aged 40-79 years from the general population participating in EPIC-Norfolk between 1993 and 1997, with nutrient and food data from 7dFD. Subjects: A subset of 20 437 participants. Results: The median daily phytoestrogen intake for men was 1.20mg (interquartile range (IQR) 0.93-1.54 mg; mean 1.50 mg, SD 1.50 mg) and 0.89 mg for women (IQR 0.71-1.14 mg; mean 1.20 mg, SD 1.70 mg). In soya-consumers (SC), median daily intakes were higher: 2.86 mg in men (IQR – 1.30-7.27mg; mean 5.05 mg, SD 5.03 mg) and 3.14 mg in women (IQR – 1.09-7.33mg; mean 5.40 mg, SD 6.09 mg). In both men and women, bread made the greatest contribution to phytoestrogen intake – 40.7% and 35.7% respectively. In SC men and women, vegetable dishes and soya/goat’s/sheep’s milks were the main contributors – 42.6% and 18.9% in men and 38.8% and 29.1% in women, respectively. Conclusions: The ability to estimate phytoestrogen intake in Western populations more accurately will aid investigations into their suggested effects on health.

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The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^

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It is the aim of this paper to examine iron supplementation programs which receive funding from United States Agency for International Development (USAID) but approach combating iron deficiency anemia in two vastly different ways. A brief literature review and background information on iron deficiencies and the differences between supplementation programs and micronutrient fortification were reviewed. Two non-governmental organizations (NGO's) were examined for this paper: the Food and Nutrition Technical Assistance II (FANTA) and the MicroNutrient Initiative. The FANTA program included an educational component to their supplementation program while the MicroNutrient Initiative solely used supplementation of micronutrients to their population. Methods used were cost-benefit analysis and cost-effectiveness analysis to determine the overall effectiveness of each program in reducing iron deficiency anemia in each population, if the added costs of the incentives in the FANTA program changed the cost-effectiveness of the program compared to the MicroNutrient Initiative program and to determine which program imparted the greatest benefit to each population by reducing the disease burden in Disability Adjusted Life Years (DALY). Results showed that the unit cost of the FANTA program per person was higher than the MicroNutrient Initiative program due to the educational component. The FANTA program reduced iron deficiency anemia less overall but cost less for each percentage point of anemia decreased in their respective populations. The MicroNutrient Initiative program had a better benefit cost ratio for the populations it served. The MicroNutrient Initiative's large scale program imparted many advantages by reducing unit cost per person and decreasing iron deficiency anemia. The FANTA program was more effective at decreasing iron deficiency anemia with less money: $5,660 per 1% decrease in iron deficiency anemia versus $18,450 per 1% decrease in iron deficiency anemia for the MicroNutrient Initiative program. ^ In conclusion, economic analysis cannot measure all of the benefits associated with programs that contain an educational component or large scale supplementation. More information needs to be gathered by NGOs and reported to USAID, such as detailed prevalence rates of iron deficiency anemia among the populations served. Further research is needed to determine the effects an educational supplementation program has on compliance rates of participants and motivation to participate in supplementation programs whose aim is to decrease iron deficiency anemia in a targeted population.^

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Viral hepatitis is a significant public health problem worldwide and is due to viral infections that are classified as Hepatitis A, B, C, D, and E. Hepatitis B is one of the five known hepatic viruses. A safe and effective vaccine for Hepatitis B was first developed in 1981, and became adopted into national immunization programs targeting infants since 1990 and adolescents since 1995. In the U.S., this vaccination schedule has led to an 82% reduction in incidence from 8.5 cases per 100,000 in 1990 to 1.5 cases per 100,000 in 2007. Although there has been a decline in infection among adolescents, there is still a large burden of hepatitis B infection among adults and minorities. There is very little research in regards to vaccination gaps among adults. Using the National Health and Nutrition Examination Survey (NHANES) question "{Have you/Has SP (Study Participant)} ever received the 3-dose series of the hepatitis B vaccine?" the existence of racial/ethnic gaps using a cross-sectional study design was explored. In this study, other variables such as age, gender, socioeconomic variables (federal poverty line, educational attainment), and behavioral factors (sexual practices, self-report of men having sex with men, and intravenous drug use) were examined. We found that the current vaccination programs and policies for Hepatitis B had eliminated racial and ethnic disparities in Hepatitis B vaccination, but that a low coverage exists particularly for adults who engage in high risk behaviors. This study found a statistically significant 10% gap in Hepatitis B vaccination between those who have and those who do not have access to health insurance.^

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Mode of access: Internet.

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"March 1990."

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Shipping list no.: 2012-0266-P (pt. 1A), 2012-0262-P (pt. 1B), 2012-0267-P (pt. 1C), 2012-0317-P (pt. 2), 2013-0006 (pt. 3), 2013-0008-P (pt. 4), 2013-0027-P (pt. 5), 2013-0033-P (pt. 6), 2013-0042-P (pt. 7), 2013-0038-P (pt. 9).

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Shipping list number: 2011-0276-P (pt. 1A), 2011-0274-P (pt. 1B), 2011-0283-P (pt. 1C), 2011-0318-P (pt. 2), 2011-0339-P (pt. 4), 2011-0366-P (pt. 5), 2011-0375-P (pt. 6), 2011-0367-P (pt. 7), 2011-0372-P (pt. 8), 2012-0014-P (pt. 9).