999 resultados para Food preservatives.
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BACKGROUND Compared to food patterns, nutrient patterns have been rarely used particularly at international level. We studied, in the context of a multi-center study with heterogeneous data, the methodological challenges regarding pattern analyses. METHODOLOGY/PRINCIPAL FINDINGS We identified nutrient patterns from food frequency questionnaires (FFQ) in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study and used 24-hour dietary recall (24-HDR) data to validate and describe the nutrient patterns and their related food sources. Associations between lifestyle factors and the nutrient patterns were also examined. Principal component analysis (PCA) was applied on 23 nutrients derived from country-specific FFQ combining data from all EPIC centers (N = 477,312). Harmonized 24-HDRs available for a representative sample of the EPIC populations (N = 34,436) provided accurate mean group estimates of nutrients and foods by quintiles of pattern scores, presented graphically. An overall PCA combining all data captured a good proportion of the variance explained in each EPIC center. Four nutrient patterns were identified explaining 67% of the total variance: Principle component (PC) 1 was characterized by a high contribution of nutrients from plant food sources and a low contribution of nutrients from animal food sources; PC2 by a high contribution of micro-nutrients and proteins; PC3 was characterized by polyunsaturated fatty acids and vitamin D; PC4 was characterized by calcium, proteins, riboflavin, and phosphorus. The nutrients with high loadings on a particular pattern as derived from country-specific FFQ also showed high deviations in their mean EPIC intakes by quintiles of pattern scores when estimated from 24-HDR. Center and energy intake explained most of the variability in pattern scores. CONCLUSION/SIGNIFICANCE The use of 24-HDR enabled internal validation and facilitated the interpretation of the nutrient patterns derived from FFQs in term of food sources. These outcomes open research opportunities and perspectives of using nutrient patterns in future studies particularly at international level.
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Introduction: There is little information regarding the impact of diet on disease incidence and mortality in Switzerland. Objectives: We aimed at assessing the associations between food availability and disease using ecological correlations. Methods: Time-trend ecologic study for period 1970 to 2009. Food availability was measured through the FAO food balance sheets. Standardized mortality rates (SMRs) were obtained from the Swiss Federal Office of Statistics. Cancer incidence data was obtained from the WHO Health for all database and the Vaud cancer registry. Association between food availability and mortality/incidence was assessed at lags 0, 5, 10 and 15 years by Spearman correlation. Results: Alcoholic beverages and fruit availability were positively associated with SMRs from all types of cardiovascular disease, while fish availability was negatively associated. Animal products, meat and animal fats were positively associated with SMR from ischemic heart disease only. For cancers, opposite results were found whether the association used SMRs or incidence rates. For all cancers, alcoholic beverages and fruits were positively associated with SMRs but negatively associated with incidence rates. Similar findings were obtained for all other foods, with the exception of vegetables, which were weakly and negatively associated with SMRs and incidence rates. Finally, a 15 years lag time reversed the association for animal and vegetal products, weakened the association for alcohol and fruits and strengthened the association for fish. Conclusion: Ecologic associations between food availability and disease vary considerably whether mortality or incidence rates are used. Great care should be taken when interpreting the results.
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Aims Food-deceptive pollination, in which plants do not offer any food reward to their pollinators, is common within the Orchidaceae. As food-deceptive orchids are poorer competitors for pollinator visitation than rewarding orchids, their occurrence in a given habitat may be more constrained than that of rewarding orchids. In particular, the success of deceptive orchids strongly relies on several biotic factors such as interactions with co-flowering rewarding species and pollinators, which may vary with altitude and over time. Our study compares generalized food-deceptive (i.e. excluding sexually deceptive) and rewarding orchids to test whether (i) deceptive orchids flower earlier compared to their rewarding counterparts and whether (ii) the relative occurrence of deceptive orchids decreases with increasing altitude. Methods To compare the flowering phenology of rewarding and deceptive orchids, we analysed data compiled from the literature at the species level over the occidental Palaearctic area. Since flowering phenology can be constrained by the latitudinal distribution of the species and by their phylogenetic relationships, we accounted for these factors in our analysis. To compare the altitudinal distribution of rewarding and deceptive orchids, we used field observations made over the entire Swiss territory and over two Swiss mountain ranges. Important Findings We found that deceptive orchid species start flowering earlier than rewarding orchids do, which is in accordance with the hypotheses of exploitation of naive pollinators and/or avoidance of competition with rewarding co-occurring species. Also, the relative frequency of deceptive orchids decreases with altitude, suggesting that deception may be less profitable at high compared to low altitude.
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The Food Assistance Monthly Participation Report is a monthly summary of Food Assistance program participation, Statewide and for each Iowa county. Breakouts are reported for participants also in the FIP program, those only receiving Food Assistance, and those that are receiving economic assistance under other programs (primarily Medicaid). This report may also be known as the F-1 Report.
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Summary of food stamp errors.
The role of energetic value in dynamic brain response adaptation during repeated food image viewing.
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The repeated presentation of simple objects as well as biologically salient objects can cause the adaptation of behavioral and neural responses during the visual categorization of these objects. Mechanisms of response adaptation during repeated food viewing are of particular interest for better understanding food intake beyond energetic needs. Here, we measured visual evoked potentials (VEPs) and conducted neural source estimations to initial and repeated presentations of high-energy and low-energy foods as well as non-food images. The results of our study show that the behavioral and neural responses to food and food-related objects are not uniformly affected by repetition. While the repetition of images displaying low-energy foods and non-food modulated VEPs as well as their underlying neural sources and increased behavioral categorization accuracy, the responses to high-energy images remained largely invariant between initial and repeated encounters. Brain mechanisms when viewing images of high-energy foods thus appear less susceptible to repetition effects than responses to low-energy and non-food images. This finding is likely related to the superior reward value of high-energy foods and might be one reason why in particular high-energetic foods are indulged although potentially leading to detrimental health consequences.
Resumo:
The Food Assistance Monthly Participation Report is a monthly summary of Food Assistance program participation, Statewide and for each Iowa county. Breakouts are reported for participants also in the FIP program, those only receiving Food Assistance, and those that are receiving economic assistance under other programs (primarily Medicaid). This report may also be known as the F-1 Report.
Resumo:
The Food Assistance Monthly Participation Report is a monthly summary of Food Assistance program participation, Statewide and for each Iowa county. Breakouts are reported for participants also in the FIP program, those only receiving Food Assistance, and those that are receiving economic assistance under other programs (primarily Medicaid). This report may also be known as the F-1 Report.
Resumo:
The Food Assistance Monthly Participation Report is a monthly summary of Food Assistance program participation, Statewide and for each Iowa county. Breakouts are reported for participants also in the FIP program, those only receiving Food Assistance, and those that are receiving economic assistance under other programs (primarily Medicaid). This report may also be known as the F-1 Report.
Resumo:
The Food Assistance Monthly Participation Report is a monthly summary of Food Assistance program participation, Statewide and for each Iowa county. Breakouts are reported for participants also in the FIP program, those only receiving Food Assistance, and those that are receiving economic assistance under other programs (primarily Medicaid). This report may also be known as the F-1 Report.
Resumo:
The Food Assistance Monthly Participation Report is a monthly summary of Food Assistance program participation, Statewide and for each Iowa county. Breakouts are reported for participants also in the FIP program, those only receiving Food Assistance, and those that are receiving economic assistance under other programs (primarily Medicaid). This report may also be known as the F-1 Report.
Resumo:
The Food Assistance Monthly Participation Report is a monthly summary of Food Assistance program participation, Statewide and for each Iowa county. Breakouts are reported for participants also in the FIP program, those only receiving Food Assistance, and those that are receiving economic assistance under other programs (primarily Medicaid). This report may also be known as the F-1 Report.
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A-8A summary of food stamp errors active and negative cases
Resumo:
The Food Assistance Monthly Participation Report is a monthly summary of Food Assistance program participation, Statewide and for each Iowa county. Breakouts are reported for participants also in the FIP program, those only receiving Food Assistance, and those that are receiving economic assistance under other programs (primarily Medicaid). This report may also be known as the F-1 Report.