SwePub
Tyck till om SwePub Sök här!
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Orfanos P) ;pers:(Jenab M)"

Sökning: WFRF:(Orfanos P) > Jenab M

  • Resultat 1-3 av 3
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  • Ferrari, P., et al. (författare)
  • A bivariate measurement error model for nitrogen and potassium intakes to evaluate the performance of regression calibration in the European Prospective Investigation into Cancer and Nutrition study
  • 2009
  • Ingår i: European Journal of Clinical Nutrition. - : Springer Science and Business Media LLC. - 1476-5640 .- 0954-3007. ; 63:4s, s. 179-187
  • Tidskriftsartikel (refereegranskat)abstract
    • Objectives: Within the European Prospective Investigation into Cancer and Nutrition (EPIC) study, the performance of 24-h dietary recall (24-HDR) measurements as reference measurements in a linear regression calibration model is evaluated critically at the individual (within-centre) and aggregate (between-centre) levels by using unbiased estimates of urinary measurements of nitrogen and potassium intakes. Methods: Between 1995 and 1999, 1072 study subjects (59% women) from 12 EPIC centres volunteered to collect 24-h urine samples. Log-transformed questionnaire, 24-HDR and urinary measurements of nitrogen and potassium intakes were analysed in a multivariate measurement error model to estimate the validity of coefficients and error correlations in self-reported dietary measurements. In parallel, correlations between means of 24-HDR and urinary measurements were computed. Linear regression calibration models were used to estimate the regression dilution (attenuation) factors. Results: After adjustment for sex, centre, age, body mass index and height, the validity coefficients for 24-HDRs were 0.285 (95% confidence interval: 0.194, 0.367) and 0.371 (0.291, 0.446) for nitrogen and potassium intakes, respectively. The attenuation factors estimated in a linear regression calibration model were 0.368 (0.228, 0.508) for nitrogen and 0.500 (0.361, 0.639) for potassium intakes; only the former was different from the estimate obtained using urinary measurements in the measurement error model. The aggregate-level correlation coefficients between means of urinary and 24-HDR measurements were 0.838 (0.637, 0.932) and 0.756 (0.481, 0.895) for nitrogen and potassium intakes, respectively. Conclusions: This study suggests that 24-HDRs can be used as reference measurements at the individual and aggregate levels for potassium intake, whereas, for nitrogen intake, good performance is observed for between-centre calibration, but some limitations are apparent at the individual level. European Journal of Clinical Nutrition (2009) 63, S179-S187; doi: 10.1038/ejcn.2009.80
  •  
2.
  • Besson, H., et al. (författare)
  • A cross-sectional analysis of physical activity and obesity indicators in European participants of the EPIC-PANACEA study
  • 2009
  • Ingår i: International Journal of Obesity. - : Springer Science and Business Media LLC. - 1476-5497 .- 0307-0565. ; 33:4, s. 497-506
  • Tidskriftsartikel (refereegranskat)abstract
    • Objectives: Cross-sectional data suggest a strong association between low levels of physical activity and obesity. The EPIC-PANACEA ( European Prospective Investigation into Cancer-Physical Activity, Nutrition, Alcohol, Cessation of Smoking, Eating out of home And obesity) project was designed to investigate the associations between physical activity and body mass index (BMI) and waist circumference based on individual data collected across nine European countries. Methods: In the European Prospective Investigation into Cancer and Nutrition ( EPIC), 519 931 volunteers were recruited between 1992 and 2000, of whom 405 819 had data on main variables of interest. Height, body weight and waist circumference were measured using standardized procedures. Physical activity was assessed using a validated four-category index reflecting a self-reported usual activity during work and leisure time. The associations between physical activity and BMI and waist circumference were estimated using multilevel mixed effects linear regression models, adjusted for age, total energy intake, smoking status, alcohol consumption and educational level. Results: A total of 125 629 men and 280 190 women with a mean age of 52.9 (s.d. 9.7) and 51.5 (s.d. 10.0) years, respectively were included. The mean BMI was 26.6 kg/m(2) (s.d. 3.6) in men and 25.0 kg/m(2) (s.d. 4.5) in women. Fifty percent of men and 30% of women were categorized as being active or moderately active. A one-category difference in the physical activity index was inversely associated with a difference of 0.18 kg/m(2) in the mean BMI (95% confidence interval, CI, 0.11, 0.24) and 1.04-cm (95% CI 0.82, 1.26) difference in waist circumference in men. The equivalent figures for women were 0.31 kg/m(2) (95% CI 0.23, 0.38) and 0.90 cm ( 95% CI 0.71, 1.08), respectively. Conclusions: Physical activity is inversely associated with both BMI and waist circumference across nine European countries. Although we cannot interpret the association causally, our results were observed in a large and diverse cohort independently from many potential confounders.
  •  
3.
  • Kroeger, J., et al. (författare)
  • Specific food group combinations explaining the variation in intakes of nutrients and other important food components in the European Prospective Investigation into Cancer and Nutrition: an application of the reduced rank regression method
  • 2009
  • Ingår i: European Journal of Clinical Nutrition. - : Springer Science and Business Media LLC. - 1476-5640 .- 0954-3007. ; 63:4s, s. 263-274
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: To identify combinations of food groups that explain as much variation in absolute intakes of 23 key nutrients and food components as possible within the country-specific populations of the European Prospective Investigation into Cancer and Nutrition (EPIC). Subjects/Methods: The analysis covered single 24-h dietary recalls (24-HDR) from 36 034 subjects (13 025 men and 23 009 women), aged 35-74 years, from all 10 countries participating in the EPIC study. In a set of 39 food groups, reduced rank regression (RRR) was used to identify those combinations (RRR factors) that explain the largest proportion of variation in intake of 23 key nutrients and food components, namely, proteins, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, cholesterol, sugars (sum of mono-and disaccharides), starch, fibre, alcohol, calcium, iron, potassium, phosphorus, magnesium, vitamin D, beta-carotene, retinol and vitamins E, B1, B2, B6, B12 and C (RRR responses). Analyses were performed at the country level and for all countries combined. Results: In the country-specific analyses, the first RRR factor explained a considerable proportion of the total nutrient intake variation in all 10 countries (27.4-37.1%). The subsequent RRR factors were much less important in explaining the variation (<= 6%). Strong similarities were observed for the first country-specific RRR factor between the individual countries, largely characterized by consumption of bread, vegetable oils, red meat, milk, cheese, potatoes, margarine and processed meat. The highest explained variation was seen for protein, potassium, phosphorus and magnesium (50-70%), whereas sugars, beta-carotene, retinol and alcohol were only marginally explained (<= 5%). The explained proportion of the other nutrients ranged between these extremes. Conclusions: A combination of food groups was identified that explained a considerable proportion of the nutrient intake variation in 24-HDRs in every country-specific EPIC population in a similar manner. This indicates that, despite the large variability in food and nutrient intakes reported in the EPIC, the variance of intake of important nutrients is explained, to a large extent, by similar food group combinations across countries. European Journal of Clinical Nutrition (2009) 63, S263-S274; doi: 10.1038/ejcn.2009.85
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-3 av 3

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy