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Sökning: WFRF:(Boshuizen Hendriek C)

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1.
  • Assi, Nada, et al. (författare)
  • Are Metabolic Signatures Mediating the Relationship between Lifestyle Factors and Hepatocellular Carcinoma Risk? Results from a Nested Case–Control Study in EPIC
  • 2018
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 27:5, s. 531-540
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The "meeting-in-the-middle" (MITM) is a principle to identify exposure biomarkers that are also predictors of disease. The MITM statistical framework was applied in a nested case-control study of hepatocellular carcinoma (HCC) within European Prospective Investigation into Cancer and Nutrition (EPIC), where healthy lifestyle index (HLI) variables were related to targeted serum metabolites.Methods: Lifestyle and targeted metabolomic data were available from 147 incident HCC cases and 147 matched controls. Partial least squares analysis related 7 lifestyle variables from a modified HLI to a set of 132 serum-measured metabolites and a liver function score. Mediation analysis evaluated whether metabolic profiles mediated the relationship between each lifestyle exposure and HCC risk.Results: Exposure-related metabolic signatures were identified. Particularly, the body mass index (BMI)-associated metabolic component was positively related to glutamic acid, tyrosine, PC aaC38:3, and liver function score and negatively to lysoPC aC17:0 and aC18:2. The lifetime alcohol-specific signature had negative loadings on sphingomyelins (SM C16:1, C18:1, SM(OH) C14:1, C16:1 and C22:2). Both exposures were associated with increased HCC with total effects (TE) = 1.23 (95% confidence interval = 0.93-1.62) and 1.40 (1.14-1.72), respectively, for BMI and alcohol consumption. Both metabolic signatures mediated the association between BMI and lifetime alcohol consumption and HCC with natural indirect effects, respectively, equal to 1.56 (1.24-1.96) and 1.09 (1.03-1.15), accounting for a proportion mediated of 100% and 24%.Conclusions: In a refined MITM framework, relevant metabolic signatures were identified as mediators in the relationship between lifestyle exposures and HCC risk.Impact: The understanding of the biological basis for the relationship between modifiable exposures and cancer would pave avenues for clinical and public health interventions on metabolic mediators.
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2.
  • Agogo, George O., et al. (författare)
  • A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data
  • 2016
  • Ingår i: BMC Medical Research Methodology. - : Springer Science and Business Media LLC. - 1471-2288. ; 16
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data. Methods: We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literature-reported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study. Results: Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations. Conclusions: The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.
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4.
  • de Hollander, Ellen L., et al. (författare)
  • The association between waist circumference and risk of mortality considering body mass index in 65-to 74-year-olds : a meta-analysis of 29 cohorts involving more than 58 000 elderly persons
  • 2012
  • Ingår i: International Journal of Epidemiology. - : OXFORD UNIV PRESS. - 0300-5771 .- 1464-3685. ; 41:3, s. 805-817
  • Tidskriftsartikel (refereegranskat)abstract
    • Background For the elderly, the association between waist circumference (WC) and mortality considering body mass index (BMI) remains unclear, and thereby also the evidence base for using these anthropometric measures in clinical practice. This meta-analysis examined the association between WC categories and (cause-specific) mortality within BMI categories. Furthermore, the association of continuous WC with lowest and increased mortality risks was examined. Methods Age-and smoking-adjusted relative risks (RRs) of mortality associated with WC-BMI categories and continuous WC (including WC and WC2) were calculated by the investigators and pooled by means of random-effects models. Results During a 5-year-follow-up of 32 678 men and 25 931 women, we ascertained 3318 and 1480 deaths, respectively. A large WC (men: >= 102 cm, women: >= 88 cm) was associated with increased all-cause mortality RRs for those in the 'healthy' weight {1.7 [95% confidence interval (CI): 1.2-2.2], 1.7 (95% CI: 1.3-2.3)}, overweight [1.1(95% CI: 1.0-1.3), 1.4 (95%: 1.1-1.7)] and obese [1.1 (95% CI: 1.0-1.3), 1.6 (95% CI: 1.3-1.9)] BMI category compared with the 'healthy' weight (20-24.9 kg/m(2)) and a small WC (<94 cm, men; <80 cm, women) category. Underweight was associated with highest all-cause mortality RRs in men [2.2 (95% CI: 1.8-2.8)] and women [2.3 (95% CI: 1.8-3.1]. We found a J-shaped association for continuous WC with all-cause, cardiovascular (CVD) and cancer, and a U-shaped association with respiratory disease mortality (P < 0.05). An all-cause (CVD) mortality RR of 2.0 was associated with a WC of 132 cm (123 cm) in men and 116 cm (105 cm) in women. Conclusions Our results showed increased mortality risks for elderly people with an increased WC-even across BMI categories- and for those who were classified as 'underweight' using BMI. The results provide a solid basis for re-evaluation of WC cut-points in ageing populations.
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5.
  • Fages, Anne, et al. (författare)
  • Investigating sources of variability in metabolomic data in the EPIC study : the Principal Component Partial R-square (PC-PR2) method
  • 2014
  • Ingår i: Metabolomics. - : Springer. - 1573-3882 .- 1573-3890. ; 10:6, s. 1074-1083
  • Tidskriftsartikel (refereegranskat)abstract
    • The key goal of metabolomic studies is to identify relevant individual biomarkers or composite metabolic patterns associated with particular disease status or patho-physiological conditions. There are currently very few approaches to evaluate the variability of metabolomic data in terms of characteristics of individuals or aspects pertaining to technical processing. To address this issue, a method was developed to identify and quantify the contribution of relevant sources of variation in metabolomic data prior to investigation of etiological hypotheses. The Principal Component Partial R-square (PC-PR2) method combines features of principal component and of multivariable linear regression analyses. Within the European Prospective Investigation into Cancer and nutrition (EPIC), metabolic profiles were determined by H-1 NMR analysis on 807 serum samples originating from a nested liver cancer case-control study. PC-PR2 was used to quantify the variability of metabolomic profiles in terms of study subjects age, sex, body mass index, country of origin, smoking status, diabetes and fasting status, as well as factors related to sample processing. PC-PR2 enables the evaluation of important sources of variations in metabolomic studies within large-scale epidemiological investigations.
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6.
  • Linseisen, Jakob, et al. (författare)
  • Consumption of meat and fish and risk of lung cancer: results from the European Prospective Investigation into Cancer and Nutrition
  • 2011
  • Ingår i: Cancer Causes and Control. - : Springer Science and Business Media LLC. - 1573-7225 .- 0957-5243. ; 22:6, s. 909-918
  • Tidskriftsartikel (refereegranskat)abstract
    • Evidence from case-control studies, but less so from cohort studies, suggests a positive association between meat intake and risk of lung cancer. Therefore, this association was evaluated in the frame of the European Prospective Investigation into Cancer and Nutrition, EPIC. Data from 478,021 participants, recruited from 10 European countries, who completed a dietary questionnaire in 1992-2000 were evaluated; 1,822 incident primary lung cancer cases were included in the present evaluation. Relative risk estimates were calculated for categories of meat intake using multi-variably adjusted Cox proportional hazard models. In addition, the continuous intake variables were calibrated by means of 24-h diet recall data to account for part of the measurement error. There were no consistent associations between meat consumption and the risk of lung cancer. Neither red meat (RR = 1.06, 95% CI 0.89-1.27 per 50 g intake/day; calibrated model) nor processed meat (RR = 1.13, 95% CI 0.95-1.34 per 50 g/day; calibrated model) was significantly related to an increased risk of lung cancer. Also, consumption of white meat and fish was not associated with the risk of lung cancer. These findings do not support the hypothesis that a high intake of red and processed meat is a risk factor for lung cancer.
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7.
  • van Duijnhoven, Fraenzel J. B., et al. (författare)
  • Fruit, vegetables, and colorectal cancer risk: the European Prospective Investigation into Cancer and Nutrition
  • 2009
  • Ingår i: American Journal of Clinical Nutrition. - : Elsevier BV. - 1938-3207 .- 0002-9165. ; 89:5, s. 1441-1452
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: A high consumption of fruit and vegetables is possibly associated with a decreased risk of colorectal cancer (CRC). However, the findings to date are inconsistent. Objective: We examined the relation between self-reported usual consumption of fruit and vegetables and the incidence of CRC. Design: In the European Prospective Investigation into Cancer and Nutrition (EPIC), 452,755 subjects (131,985 men and 320,770 women) completed a dietary questionnaire in 1992-2000 and were followed up for cancer incidence and mortality until 2006. A multivariate Cox proportional hazard model was used to estimate adjusted hazard ratios (HRs) and 95% CIs. Results: After an average follow-up of 8.8 y, 2,819 incident CRC cases were reported. Consumption of fruit and vegetables was inversely associated with CRC in a comparison of the highest with the lowest EPIC-wide quintile of consumption (HR: 0.86; 95% CI: 0.75, 1.00; P for trend 0.04), particularly with colon cancer risk (HR: 0.76; 95% CI: 0.63, 0.91; P for trend < 0.01). Only after exclusion of the first 2 y of follow-up were these findings corroborated by calibrated continuous analyses for a 100-g increase in consumption: HRs of 0.95 (95% CI: 0.91, 1.00; P 0.04) and 0.94 (95% CI: 0.89, 0.99; P = 0.02), respectively. The association between fruit and vegetable consumption and CRC risk was inverse in never and former smokers, but positive in current smokers. This modifying effect was found for fruit and vegetables combined and for vegetables alone (P for interaction, 0.01 for both). Conclusions: These findings suggest that a high consumption of fruit and vegetables is associated with a reduced risk of CRC, especially of colon cancer. This effect may depend on smoking status. Am J Clin Nutr 2009;89:1441-52.
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8.
  • Agogo, George O., et al. (författare)
  • Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design : EPIC Case Study
  • 2014
  • Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:11, s. e113160-
  • Tidskriftsartikel (refereegranskat)abstract
    • In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted twopart regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.
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9.
  • Agudo, Antonio, et al. (författare)
  • Impact of Cigarette Smoking on Cancer Risk in the European Prospective Investigation into Cancer and Nutrition Study
  • 2012
  • Ingår i: Journal of Clinical Oncology. - 0732-183X .- 1527-7755. ; 30:36, s. 4550-4557
  • Tidskriftsartikel (refereegranskat)abstract
    • Purpose Our aim was to assess the impact of cigarette smoking on the risk of the tumors classified by the International Agency for Research on Cancer as causally associated with smoking, referred to as tobacco-related cancers (TRC). Methods The study population included 441,211 participants (133,018 men and 308,193 women) from the European Prospective Investigation Into Cancer and Nutrition. We investigated 14,563 participants who developed a TRC during an average follow-up of 11 years. The impact of smoking cigarettes on cancer risk was assessed by the population attributable fraction (AF(p)), calculated using the adjusted hazard ratios and 95% CI for current and former smokers, plus either the prevalence of smoking among cancer cases or estimates from surveys in representative samples of the population in each country. Results The proportion of all TRC attributable to cigarette smoking was 34.9% (95% CI, 32.5 to 37.4) using the smoking prevalence among cases and 36.2% (95% CI, 33.7 to 38.6) using the smoking prevalence from the population. The AF(p) were above 80% for cancers of the lung and larynx, between 20% and 50% for most respiratory and digestive cancers and tumors from the lower urinary tract, and below 20% for the remaining TRC. Conclusion Using data on cancer incidence for 2008 and our AF(p) estimates, about 270,000 new cancer diagnoses per year can be considered attributable to cigarette smoking in the eight European countries with available data for both men and women (Italy, Spain, United Kingdom, the Netherlands, Greece, Germany, Sweden, Denmark). 
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