2 resultados para 6 CARBOHYDRATE SOURCES


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Objective. To evaluate the association between diabetes mellitus and health-related quality of life (HRQOL) controlled for several sociodemographic and anthropometric variables, in a representative sample of the Spanish population. Methods. A population-based, cross-sectional, and cluster sampling study, with the entire Spanish population as the target population. Five thousand and forty-seven participants (2162/2885 men/women) answered the HRQOL short form 12 questionnaire (SF-12). The physical (PCS-12) and the mental component summary (MCS-12) scores were assessed. Subjects were divided into four groups according to carbohydrate metabolism status: normal, prediabetes, unknown diabetes (UNKDM), and known diabetes (KDM). Logistic regression analyses were conducted. Results. Mean PCS-12/MCS-12 values were 50.9 ± 8.5/47.6 ± 10.2, respectively. Men had higher scores than women in both PCS-12 (51.8 ± 7.2 versus 50.3 ± 9.2; P < 0.001) and MCS-12 (50.2 ± 8.5 versus 45.5 ± 10.8; P < 0.001). Increasing age and obesity were associated with a poorer PCS-12 score. In women lower PCS-12 and MCS-12 scores were associated with a higher level of glucose metabolism abnormality (prediabetes and diabetes), (P < 0.0001 for trend), but only the PCS-12 score was associated with altered glucose levels in men (P < 0.001 for trend). The Odds Ratio adjusted for age, body mass index (BMI) and educational level, for a PCS-12 score below the median was 1.62 (CI 95%: 1.2–2.19; P < 0.002) for men with KDM and 1.75 for women with KDM (CI 95%: 1.26–2.43; P < 0.001), respectively. Conclusion. Current study indicates that increasing levels of altered carbohydrate metabolism are accompanied by a trend towards decreasing quality of life, mainly in women, in a representative sample of Spanish population.

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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.