M C Ocké

National Institute for Public Health and the Environment (RIVM), Utrecht, Utrecht, Netherlands

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Publications (204)652.53 Total impact

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    ABSTRACT: We aimed (1) to describe and evaluate the "EPIC-Soft DataEntry" application developed as a user-friendly data entry tool for pan-European and national food consumption surveys among infants and children, and (2) to compare two food record-based dietary assessment methods in terms of food description and quantification using data quality indicators. EPIC-Soft DataEntry was used for both methods.
    European journal of nutrition. 06/2014;
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    ABSTRACT: Principal component analysis (PCA) and cluster analysis are used frequently to derive dietary patterns. Decisions on how many patterns to extract are primarily based on subjective criteria, whereas different solutions vary in their food-group composition and perhaps association with disease outcome. Literature on reliability of dietary patterns is scarce, and previous studies validated only 1 preselected solution. Therefore, we assessed reliability of different pattern solutions ranging from 2 to 6 patterns, derived from the aforementioned methods. A validated food frequency questionnaire was administered at baseline (1993-1997) to 39,678 participants in the European Prospective Investigation into Cancer and Nutrition-The Netherlands (EPIC-NL) cohort. Food items were grouped into 31 food groups for dietary pattern analysis. The cohort was randomly half-split, and dietary pattern solutions derived in 1 sample through PCA were replicated through confirmatory factor analysis in sample 2. For cluster analysis, cluster stability and split-half reproducibility were assessed for various solutions. With PCA, we found the 3-component solution to be best replicated, although all solutions contained ≥1 poorly confirmed component. No quantitative criterion was in agreement with these results. Associations with disease outcome (coronary heart disease) differed between the component solutions. For all cluster solutions, stability was excellent and deviations between split samples was negligible, indicating good reproducibility. All quantitative criteria identified the 2-cluster solution as optimal. Associations with disease outcome were comparable for different cluster solutions. In conclusion, reliability of obtained dietary patterns differed considerably for different solutions using PCA, whereas cluster analysis derived generally stable, reproducible clusters across different solutions. Quantitative criteria for determining the number of patterns to retain were valuable for cluster analysis but not for PCA. Associations with disease risk were influenced by the number of patterns that are retained, especially when using PCA. Therefore, studies on associations between dietary patterns and disease risk should report reasons to choose the number of retained patterns.
    The Journal of nutrition. 05/2014;
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    Dataset: Global
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    ABSTRACT: Abstract OBJECTIVES: To quantify global consumption of key dietary fats and oils by country, age, and sex in 1990 and 2010. DESIGN: Data were identified, obtained, and assessed among adults in 16 age- and sex-specific groups from dietary surveys worldwide on saturated, omega 6, seafood omega 3, plant omega 3, and trans fats, and dietary cholesterol. We included 266 surveys in adults (83% nationally representative) comprising 1,630,069 unique individuals, representing 113 of 187 countries and 82% of the global population. A multilevel hierarchical Bayesian model accounted for differences in national and regional levels of missing data, measurement incomparability, study representativeness, and sampling and modelling uncertainty. SETTING AND POPULATION: Global adult population, by age, sex, country, and time. RESULTS: In 2010, global saturated fat consumption was 9.4%E (95%UI=9.2 to 9.5); country-specific intakes varied dramatically from 2.3 to 27.5%E; in 75 of 187 countries representing 61.8% of the world's adult population, the mean intake was <10%E. Country-specific omega 6 consumption ranged from 1.2 to 12.5%E (global mean=5.9%E); corresponding range was 0.2 to 6.5%E (1.4%E) for trans fat; 97 to 440 mg/day (228 mg/day) for dietary cholesterol; 5 to 3,886 mg/day (163 mg/day) for seafood omega 3; and <100 to 5,542 mg/day (1,371 mg/day) for plant omega 3. Countries representing 52.4% of the global population had national mean intakes for omega 6 fat ≥ 5%E; corresponding proportions meeting optimal intakes were 0.6% for trans fat (≤ 0.5%E); 87.6% for dietary cholesterol (<300 mg/day); 18.9% for seafood omega 3 fat (≥ 250 mg/day); and 43.9% for plant omega 3 fat (≥ 1,100 mg/day). Trans fat intakes were generally higher at younger ages; and dietary cholesterol and seafood omega 3 fats generally higher at older ages. Intakes were similar by sex. Between 1990 and 2010, global saturated fat, dietary cholesterol, and trans fat intakes remained stable, while omega 6, seafood omega 3, and plant omega 3 fat intakes each increased. CONCLUSIONS: These novel global data on dietary fats and oils identify dramatic diversity across nations and inform policies and priorities for improving global health.
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    ABSTRACT: 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.
    PLoS ONE 01/2014; 9(6):e98647. · 3.53 Impact Factor
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    ABSTRACT: Diet may be associated with the development of type 2 diabetes through its effects on low-grade inflammation. We investigated whether an adapted dietary inflammatory index (ADII) is associated with a summary score for low-grade inflammation and markers of glucose metabolism. In addition, we investigated the mediating role of inflammation in the association between ADII and markers of glucose metabolism. We performed cross-sectional analyses of 2 Dutch cohort studies (n= 1024). An ADII was obtained by multiplying standardized energy-adjusted intakes of dietary components by literature-based dietary inflammatory weights that reflected the inflammatory potential of components. Subsequently, these multiplications were summed. Six biomarkers of inflammation were compiled in a summary score. Associations of the ADII (expressed per SD) with the summary score for inflammation and markers of glucose metabolism were investigated by using multiple linear regression models. Inflammation was considered a potential mediator in the analysis with markers of glucose metabolism. A higher ADII was associated with a higher summary score for inflammation [β-adjusted = 0.04 per SD (95% CI: 0.01, 0.07 per SD)]. The ADII was also adversely associated with insulin resistance [homeostatic model assessment of insulin resistance (HOMA-IR): β-adjusted = 3.5% per SD (95% CI: 0.6%, 6.3% per SD)]. This association was attenuated after the inclusion of the summary score for inflammation [β-adjusted+inflammation = 2.2% (95% CI: -0.6%, 5.0%)]. The ADII was also adversely associated with fasting glucose and postload glucose but not with glycated hemoglobin. The significant mediating role of low-grade inflammation in the association between the ADII and HOMA-IR suggests that inflammation might be one of the pathways through which diet affects insulin resistance.
    American Journal of Clinical Nutrition 10/2013; · 6.50 Impact Factor
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    ABSTRACT: S-adenosylmethionine (SAM) is synthesized from methionine, which is abundant in animal-derived protein, in an energy-consuming reaction. SAM and S-adenosylhomocysteine (SAH) correlate with body mass index (BMI). Plasma total concentration of the SAM-associated product cysteine (tCys) correlates with fat mass in humans and cysteine promotes adiposity in animals. In a cross-sectional study of 610 participants, we investigated whether SAM and SAH are associated with BMI via lean mass or fat mass and dietary protein sources as determinants of SAM and tCys concentrations. Plasma SAM was not associated with lean mass, but mean adjusted fat mass increased from 24 kg (95% CI: 22.6, 25.1) to 30 kg (95% CI: 28.7, 31.3) across SAM quartiles (P < 0.001) and trunk fat:total fat ratio increased from 0.48 to 0.52 (P < 0.001). Erythrocyte SAM was also positively associated with fat mass and trunk fat:total fat ratio. The association of SAM with fat mass was not weakened by adjustment for serum tCys, lipids, creatinine, or dietary or lifestyle confounders. Concentrations of the SAM precursor, methionine, and the SAM product, SAH, were not independently associated with adiposity. Intake of animal-derived protein was not related to serum methionine but was positively associated with plasma SAM (partial r = 0.11) and serum tCys (partial r = 0.13; P < 0.05 for both after adjustment for age, gender, and total energy intake). In conclusion, plasma SAM, but not methionine, is independently associated with fat mass and trunkal adiposity, suggesting increased conversion of methionine to SAM in obese individuals. Prospective studies are needed to investigate the interactions among dietary energy and animal protein content, SAM concentrations, and change in body weight and cardiometabolic risk.
    Journal of Nutrition 09/2013; · 4.20 Impact Factor
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    ABSTRACT: The aim of the present study was to validate thirty-eight picture series of six pictures each developed within the PANCAKE (Pilot study for the Assessment of Nutrient intake and food Consumption Among Kids in Europe) project for portion size estimation of foods consumed by infants, toddlers and children for future pan-European and national dietary surveys. Identical validation sessions were conducted in three European countries. In each country, forty-five foods were evaluated; thirty-eight foods were the same as the depicted foods, and seven foods were different, but meant to be quantified by the use of one of the thirty-eight picture series. Each single picture within a picture series was evaluated six times by means of predefined portions. Therefore, thirty-six pre-weighed portions of each food were evaluated by convenience samples of parents having children aged from 3 months to 10 years. The percentages of participants choosing the correct picture, the picture adjacent to the correct picture or a distant picture were calculated, and the performance of individual pictures within the series was assessed. For twenty foods, the picture series performed acceptably (mean difference between the estimated portion number and the served portion number less than 0·4 (sd < 1·1)). In addition, twelve foods were rated acceptable after adjustment for density differences. Some other series became acceptable after analyses at the country level. In conclusion, all picture series were acceptable for inclusion in the PANCAKE picture book. However, the picture series of baby food, salads and cakes either can only be used for foods that are very similar to those depicted or need to be substituted by another quantification tool.
    The British journal of nutrition 06/2013; · 3.45 Impact Factor
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    ABSTRACT: OBJECTIVE: To monitor the effectiveness of salt-reduction initiatives in processed foods and changes in Dutch iodine policy on Na and iodine intakes in Dutch adults between 2006 and 2010. DESIGN: Two cross-sectional studies among adults, conducted in 2006 and 2010, using identical protocols. Participants collected single 24 h urine samples and completed two short questionnaires on food consumption and urine collection procedures. Daily intakes of salt, iodine, K and Na:K were estimated, based on the analysis of Na, K and iodine excreted in urine. SETTING: Doetinchem, the Netherlands. SUBJECTS: Men and women aged 19 to 70 years were recruited through random sampling of the Doetinchem population and among participants of the Doetinchem Cohort Study (2006: n 317, mean age 48·9 years, 43 % men; 2010: n 342, mean age 46·2 years, 45 % men). RESULTS: While median iodine intake was lower in 2010 (179 μg/d) compared with 2006 (257 μg/d; P < 0·0001), no difference in median salt intake was observed (8·7 g/d in 2006 v. 8·5 g/d in 2010, P = 0·70). In 2006, median K intake was 2·6 g/d v. 2·8 g/d in 2010 (P < 0·01). In this 4-year period, median Na:K improved from 2·4 in 2006 to 2·2 in 2010 (P < 0·001). CONCLUSIONS: Despite initiatives to lower salt in processed foods, dietary salt intake in this population remains well above the recommended intake of 6 g/d. Iodine intake is still adequate, although a decline was observed between 2006 and 2010. This reduction is probably due to changes in iodine policy.
    Public Health Nutrition 06/2013; · 2.25 Impact Factor
  • Marga C Ocké
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    ABSTRACT: This paper aims to describe different approaches for studying the overall diet with advantages and limitations. Studies of the overall diet have emerged because the relationship between dietary intake and health is very complex with all kinds of interactions. These cannot be captured well by studying single dietary components. Three main approaches to study the overall diet can be distinguished. The first method is researcher-defined scores or indices of diet quality. These are usually based on guidelines for a healthy diet or on diets known to be healthy. The second approach, using principal component or cluster analysis, is driven by the underlying dietary data. In principal component analysis, scales are derived based on the underlying relationships between food groups, whereas in cluster analysis, subgroups of the population are created with people that cluster together based on their dietary intake. A third approach includes methods that are driven by a combination of biological pathways and the underlying dietary data. Reduced rank regression defines linear combinations of food intakes that maximally explain nutrient intakes or intermediate markers of disease. Decision tree analysis identifies subgroups of a population whose members share dietary characteristics that influence (intermediate markers of) disease. It is concluded that all approaches have advantages and limitations and essentially answer different questions. The third approach is still more in an exploration phase, but seems to have great potential with complementary value. More insight into the utility of conducting studies on the overall diet can be gained if more attention is given to methodological issues.
    Proceedings of The Nutrition Society 01/2013; · 3.67 Impact Factor
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    Proceedings of The Nutrition Society 01/2013; 72(OCE5). · 3.67 Impact Factor
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    ABSTRACT: PURPOSE: Methodological differences in assessing dietary acrylamide (AA) often hamper comparisons of intake across populations. Our aim was to describe the mean dietary AA intake in 27 centers of 10 European countries according to selected lifestyle characteristics and its contributing food sources in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. METHODS: In this cross-sectional analysis, 36 994 men and women, aged 35-74 years completed a single, standardized 24-hour dietary recall using EPIC-Soft. Food consumption data were matched to a harmonized AA database. Intake was computed by gender and center, and across categories of habitual alcohol consumption, smoking status, physical activity, education, and body mass index (BMI). Adjustment was made for participants' age, height, weight, and energy intake using linear regression models. RESULTS: Adjusted mean AA intake across centers ranged from 13 to 47 μg/day in men and from 12 to 39 μg/day in women; intakes were higher in northern European centers. In most centers, intake in women was significantly higher among alcohol drinkers compared with abstainers. There were no associations between AA intake and physical activity, BMI, or education. At least 50 % of AA intake across centers came from two food groups "bread, crisp bread, rusks" and "coffee." The third main contributing food group was "potatoes". CONCLUSIONS: Dietary AA intake differs greatly among European adults residing in different geographical regions. This observed heterogeneity in AA intake deserves consideration in the design and interpretation of population-based studies of dietary AA intake and health outcomes.
    European Journal of Nutrition 12/2012; · 3.13 Impact Factor
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    ABSTRACT: BACKGROUND: Acrylamide is a chemical compound present in tobacco smoke and food, classified as a probable human carcinogen and a known human neurotoxin. Acrylamide is formed in foods, typically carbohydrate-rich and protein-poor plant foods, during high-temperature cooking or other thermal processing. The objectives of this study were to compare dietary estimates of acrylamide from questionnaires (DQ) and 24-h recalls (R) with levels of acrylamide adduct (AA) in haemoglobin. METHODS: In the European Prospective Investigation into Cancer and Nutrition (EPIC) study, acrylamide exposure was assessed in 510 participants from 9 European countries, randomly selected and stratified by age, sex, with equal numbers of never and current smokers. After adjusting for country, alcohol intake, smoking status, number of cigarettes and energy intake, correlation coefficients between various acrylamide measurements were computed, both at the individual and at the aggregate (centre) level. RESULTS: Individual level correlation coefficient between DQ and R measurements (r (DQ,R)) was 0.17, while r (DQ,AA) and r (R,AA) were 0.08 and 0.06, respectively. In never smokers, r (DQ,R), r (DQ,AA) and r (R,AA) were 0.19, 0.09 and 0.02, respectively. The correlation coefficients between means of DQ, R and AA measurements at the centre level were larger (r > 0.4). CONCLUSIONS: These findings suggest that estimates of total acrylamide intake based on self-reported diet correlate weakly with biomarker AA Hb levels. Possible explanations are the lack of AA levels to capture dietary acrylamide due to individual differences in the absorption and metabolism of acrylamide, and/or measurement errors in acrylamide from self-reported dietary assessments, thus limiting the possibility to validate acrylamide DQ measurements.
    European Journal of Nutrition 11/2012; · 3.13 Impact Factor
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    ABSTRACT: OBJECTIVE: Consuming a variety of fruit and vegetables provides many different micronutrients and bioactive compounds. Whether this contributes to the beneficial association between fruit and vegetables and incident CHD and stroke is unknown. DESIGN: Prospective population-based cohort study. SETTING: The Netherlands. SUBJECTS: Men and women (n 20 069) aged 20-65 years. Participants completed a validated 178-item FFQ, including nine fruit and thirteen vegetable items. Variety in fruit and vegetables was defined as the sum of different items consumed at least once per 2 weeks over the previous year. Hazard ratios (HR) for variety in relation to incident CHD and stroke were calculated using multivariable Cox proportional hazards models additionally adjusted for quantity of fruit and vegetables. RESULTS: Variety and quantity in fruit and vegetables were highly correlated (r = 0·81). Variety was not associated with total energy intake (r = -0·01) and positively associated with nutrient intakes, particularly vitamin C (r = 0·70). During 10 years of follow-up, 245 cases of CHD and 233 cases of stroke occurred. Variety in vegetables (HR per 2 items = 1·05; 95 % CI 0·94, 1·17) and in fruit (HR per 2 items = 1·00; 95 % CI 0·87, 1·15) were not related to incident CHD. Variety in vegetables (HR per 2 items = 0·93; 95 % CI 0·83, 1·04) and in fruit (HR per 2 items = 1·03; 95 % CI 0·89, 1·18) were also not related to incident stroke. CONCLUSIONS: More variety in fruit and vegetable consumption was associated with higher intakes of fruit and vegetables and micronutrients. Independently of quantity, variety in fruit and vegetables was related neither to incident CHD nor to incident stroke.
    Public Health Nutrition 03/2012; · 2.25 Impact Factor
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    ABSTRACT: Diets high in vegetables and fruits have been suggested to be inversely associated with risk of gastric cancer. However, the evidence of the effect of variety of consumption is limited. We therefore investigated whether consumption of a variety of vegetables and fruit is associated with gastric and esophageal cancer in the European Prospective Investigation into Cancer and Nutrition study. Data on food consumption and follow-up on cancer incidence were available for 452,269 participants from 10 European countries. After a mean follow-up of 8.4 years, 475 cases of gastric and esophageal adenocarcinomas (180 noncardia, 185 cardia, gastric esophageal junction and esophagus, 110 not specified) and 98 esophageal squamous cell carcinomas were observed. Diet Diversity Scores were used to quantify the variety in vegetable and fruit consumption. We used multivariable Cox proportional hazard models to calculate risk ratios. Independent from quantity of consumption, variety in the consumption of vegetables and fruit combined and of fruit consumption alone were statistically significantly inversely associated with the risk of esophageal squamous cell carcinoma (continuous hazard ratio per 2 products increment 0.88; 95% CI 0.79-0.97 and 0.76; 95% CI 0.62-0.94, respectively) with the latter particularly seen in ever smokers. Variety in vegetable and/or fruit consumption was not associated with risk of gastric and esophageal adenocarcinomas. Independent from quantity of consumption, more variety in vegetable and fruit consumption combined and in fruit consumption alone may decrease the risk of esophageal squamous cell carcinoma. However, residual confounding by lifestyle factors cannot be excluded.
    International Journal of Cancer 03/2012; 131(6):E963-73. · 6.20 Impact Factor
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    ABSTRACT: To evaluate the impact of different modes of administration (face-to-face v. telephone), recall days (first v. second), days of the week (weekday v. weekend) and interview days (1 d later v. 2 d later) on bias in protein and K intakes collected with 24 h dietary recalls (24-HDR). Two non-consecutive 24-HDR (collected with standardised EPIC-Soft software) were used to estimate protein and K intakes by a face-to-face interview at the research centres and a telephone interview, and included all days of the week. Two 24 h urine collections were used to determine biomarkers of protein and K intake. The bias in intake was defined as the ratio between the 24-HDR estimate and the biomarker. Five centres in Belgium, Czech Republic, France, the Netherlands and Norway in the European Food Consumption Validation (EFCOVAL) study. About 120 adults (aged 45-65 years) per centre. The bias in protein intake in the Czech Republic and Norway was smaller for telephone than face-to-face interviews (P = 0·01). The second 24-HDR estimates of protein intake in France and K intake in Belgium had a larger bias than the first 24-HDR (P = 0·01 and 0·04, respectively). In the Czech Republic, protein intake estimated during weekends and K intake estimated during weekdays had a larger bias than during other days of the week (P = 0·01). In addition, K intake collected 2 d later in the Czech Republic was likely to be overestimated. The biases in protein and K intakes were comparable between modes of administration, recall days, days of the week and interview days in some, but not all, study centres.
    Public Health Nutrition 02/2012; 15(7):1196-200. · 2.25 Impact Factor
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    European Journal of Nutrition 01/2012; · 3.13 Impact Factor
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    ABSTRACT: Fortification with folic acid was prohibited in the Netherlands. Since 2007, a general exemption is given to fortify with folic acid up until a maximum level of 100 µg/100 kcal. This maximum level was based on a calculation model and data of adults only. The model requires parameters on intake (diet, supplements, energy) and on the proportion of energy that may be fortified. This study aimed to evaluate the model parameters considering the changing fortification market. In addition, the risk of young children exceeding the UL for folic acid was studied. Folic acid fortified foods present on the Dutch market were identified in product databases and by a supermarket inventory. Together with data of the Dutch National Consumption Survey-Young Children (2005/2006) these inventory results were used to re-estimate the model parameters. Habitual folic acid intake of young children was estimated and compared to the UL for several realistic fortification scenarios. Folic acid fortified foods were identified in seven different food groups. In up to 10% of the population, the proportion of energy intake of folic acid fortified foods exceeded 10% - the original model parameter. The folic acid intake from food supplements was about 100 µg/day, which is lower than the intake assumed as the original model parameter (300 µg). In the scenarios representing the current market situation, a small proportion (<5%) of the children exceeded the UL. The maximum fortification level of 100 µg/100 kcal is sufficiently protective for children in the current market situation. In the precautionary model to estimate the maximum fortification levels, subjects with high intakes of folic acid from food and supplements, and high energy intakes are protected from too high folic acid intakes. Combinations of high intakes are low in this population. The maximum levels should be monitored and revised with increasing fortification and supplementation practices.
    Food & Nutrition Research 01/2012; 56.
  • Public Health Nutrition - PUBLIC HEALTH NUTR. 01/2012;
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    ABSTRACT: PURPOSE: We investigated whether group-level bias of a 24-h recall estimate of protein and potassium intake, as compared to biomarkers, varied across European centers and whether this was influenced by characteristics of individuals or centers. METHODS: The combined data from EFCOVAL and EPIC studies included 14 centers from 9 countries (n = 1,841). Dietary data were collected using a computerized 24-h recall (EPIC-Soft). Nitrogen and potassium in 24-h urine collections were used as reference method. Multilevel linear regression analysis was performed, including individual-level (e.g., BMI) and center-level (e.g., food pattern index) variables. RESULTS: For protein intake, no between-center variation in bias was observed in men while it was 5.7% in women. For potassium intake, the between-center variation in bias was 8.9% in men and null in women. BMI was an important factor influencing the biases across centers (p < 0.01 in all analyses). In addition, mode of administration (p = 0.06 in women) and day of the week (p = 0.03 in men and p = 0.06 in women) may have influenced the bias in protein intake across centers. After inclusion of these individual variables, between-center variation in bias in protein intake disappeared for women, whereas for potassium, it increased slightly in men (to 9.5%). Center-level variables did not influence the results. CONCLUSION: The results suggest that group-level bias in protein and potassium (for women) collected with 24-h recalls does not vary across centers and to a certain extent varies for potassium in men. BMI and study design aspects, rather than center-level characteristics, affected the biases across centers.
    European Journal of Nutrition 12/2011; · 3.13 Impact Factor
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    ABSTRACT: Elaidic acid is the main unnatural trans fatty acid isomer occurring during partial hydrogenation of vegetable oils used as ingredients for the formulation of processed foods. The main objective is to assess associations between processed food intakes and plasma phospholipid elaidic acid concentrations within the European Prospective Investigation into Cancer and Nutrition study. A cross-sectional study was used to determine fatty acid profiles in 3,003 subjects from 16 centers. Single 24-h dietary recalls (24-HDR) were collected using a standardized computerized interview program. Food intakes were computed according to their degree of processing (moderately/nonprocessed foods, processed staple foods, highly processed foods). Adjusted ecological and individual correlations were calculated between processed food intakes and plasma elaidic acid levels. At the population level, mean intakes of highly processed foods were strongly correlated with mean levels of plasma elaidic acid in men (P = 0.0016) and in women (P = 0.0012). At the individual level, these associations remained but at a much lower level in men (r = 0.08, P = 0.006) and in women (r = 0.09, P = 0.0001). The use of an averaged 24-HDR measure of highly processed food intakes is adequate for predicting mean levels of plasma elaidic acid among European populations.
    Nutrition and Cancer 11/2011; 63(8):1235-1250. · 2.70 Impact Factor

Publication Stats

6k Citations
652.53 Total Impact Points

Institutions

  • 1996–2014
    • National Institute for Public Health and the Environment (RIVM)
      • • Centre for Nutrition and Health
      • • Centre for Prevention and Health Services Research (PZO)
      Utrecht, Utrecht, Netherlands
  • 2007–2012
    • Wageningen University
      • Division of Human Nutrition
      Wageningen, Provincie Gelderland, Netherlands
  • 1999–2012
    • International Agency for Research on Cancer
      Lyons, Rhône-Alpes, France
  • 2011
    • Ghent University
      • Department of Public Health
      Gent, VLG, Belgium
  • 2002–2011
    • Catalan Institute of Oncology
      • Cancer Epidemiology Research Programme (PREC)
      Badalona, Catalonia, Spain
    • Cancer Research UK Cambridge Institute
      Cambridge, England, United Kingdom
  • 2009
    • German Cancer Research Center
      • Division of Cancer Epidemiology
      Heidelberg, Baden-Wuerttemberg, Germany
    • University of Melbourne
      Melbourne, Victoria, Australia
    • Umeå University
      Umeå, Västerbotten, Sweden
  • 2007–2009
    • German Institute of Human Nutrition
      • Department of Epidemiology
      Potsdam, Brandenburg, Germany
    • Danish Cancer Society
      København, Capital Region, Denmark
  • 2004–2009
    • University Medical Center Utrecht
      • Julius Center for Health Sciences and Primary Care
      Utrecht, Provincie Utrecht, Netherlands
  • 2003–2009
    • University of Cambridge
      • Department of Public Health and Primary Care
      Cambridge, ENG, United Kingdom
    • CRO Centro di Riferimento Oncologico di Aviano
      Aviano, Friuli Venezia Giulia, Italy
    • Technische Universität München
      München, Bavaria, Germany
    • University of Oslo
      • Department of Biostatistics
      Oslo, Oslo, Norway
  • 2006
    • Universitetet i Tromsø
      • Department of Community Medicine
      Tromsø, Troms Fylke, Norway
    • University of Oxford
      • Nuffield Department of Clinical Medicine
      Oxford, ENG, United Kingdom
  • 2003–2004
    • Radboud University Medical Centre (Radboudumc)
      • Department of Human Genetics
      Nymegen, Gelderland, Netherlands
  • 1995–1997
    • Universiteit Utrecht
      • University Medical Center Utrecht
      Utrecht, Provincie Utrecht, Netherlands