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  • 1
    Abstract: Scores of overall diet quality have received increasing attention in relation to disease aetiology; however, their value in risk prediction has been little examined. The objective was to assess and compare the association and predictive performance of 10 diet quality scores on 10-year risk of all-cause, CVD and cancer mortality in 451,256 healthy participants to the European Prospective Investigation into Cancer and Nutrition, followed-up for a median of 12.8y. All dietary scores studied showed significant inverse associations with all outcomes. The range of HRs (95% CI) in the top vs. lowest quartile of dietary scores in a composite model including non-invasive factors (age, sex, smoking, body mass index, education, physical activity and study centre) was 0.75 (0.72-0.79) to 0.88 (0.84-0.92) for all-cause, 0.76 (0.69-0.83) to 0.84 (0.76-0.92) for CVD and 0.78 (0.73-0.83) to 0.91 (0.85-0.97) for cancer mortality. Models with dietary scores alone showed low discrimination, but composite models also including age, sex and other non-invasive factors showed good discrimination and calibration, which varied little between different diet scores examined. Mean C-statistic of full models was 0.73, 0.80 and 0.71 for all-cause, CVD and cancer mortality. Dietary scores have poor predictive performance for 10-year mortality risk when used in isolation but display good predictive ability in combination with other non-invasive common risk factors.
    Type of Publication: Journal article published
    PubMed ID: 27409582
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  • 2
    Keywords: FOLLOW-UP ; TOOL ; COHORT ; prevention ; VALIDITY ; MELLITUS ; METAANALYSIS ; EXTERNAL VALIDATION ; IDENTIFYING INDIVIDUALS ; LIFE-STYLE INTERVENTIONS
    Abstract: BACKGROUND: The comparative performance of existing models for prediction of type 2 diabetes across populations has not been investigated. We validated existing non-laboratory-based models and assessed variability in predictive performance in European populations. METHODS: We selected non-invasive prediction models for incident diabetes developed in populations of European ancestry and validated them using data from the EPIC-InterAct case-cohort sample (27,779 individuals from eight European countries, of whom 12,403 had incident diabetes). We assessed model discrimination and calibration for the first 10 years of follow-up. The models were first adjusted to the country-specific diabetes incidence. We did the main analyses for each country and for subgroups defined by sex, age (〈60 years vs 〉/=60 years), BMI (〈25 kg/m(2)vs 〉/=25 kg/m(2)), and waist circumference (men 〈102 cm vs 〉/=102 cm; women 〈88 cm vs 〉/=88 cm). FINDINGS: We validated 12 prediction models. Discrimination was acceptable to good: C statistics ranged from 0.76 (95% CI 0.72-0.80) to 0.81 (0.77-0.84) overall, from 0.73 (0.70-0.76) to 0.79 (0.74-0.83) in men, and from 0.78 (0.74-0.82) to 0.81 (0.80-0.82) in women. We noted significant heterogeneity in discrimination (pheterogeneity〈0.0001) in all but one model. Calibration was good for most models, and consistent across countries (pheterogeneity〉0.05) except for three models. However, two models overestimated risk, DPoRT by 34% (95% CI 29-39%) and Cambridge by 40% (28-52%). Discrimination was always better in individuals younger than 60 years or with a low waist circumference than in those aged at least 60 years or with a large waist circumference. Patterns were inconsistent for BMI. All models overestimated risks for individuals with a BMI of 〈25 kg/m(2). Calibration patterns were inconsistent for age and waist-circumference subgroups. INTERPRETATION: Existing diabetes prediction models can be used to identify individuals at high risk of type 2 diabetes in the general population. However, the performance of each model varies with country, age, sex, and adiposity. FUNDING: The European Union.
    Type of Publication: Journal article published
    PubMed ID: 24622666
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  • 3
    Abstract: OBJECTIVE: There is uncertainty about the direction and magnitude of the associations between parity, breastfeeding and the risk of coronary heart disease (CHD). We examined the separate and combined associations of parity and breastfeeding practices with the incidence of CHD later in life among women in a large, pan-European cohort study. METHODS: Data were used from European Prospective Investigation into Cancer and Nutrition (EPIC)-CVD, a case-cohort study nested within the EPIC prospective study of 520,000 participants from 10 countries. Information on reproductive history was available for 14,917 women, including 5138 incident cases of CHD. Using Prentice-weighted Cox regression separately for each country followed by a random-effects meta-analysis, we calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for CHD, after adjustment for age, study centre and several socioeconomic and biological risk factors. RESULTS: Compared with nulliparous women, the adjusted HR was 1.19 (95% CI: 1.01-1.41) among parous women; HRs were higher among women with more children (e.g., adjusted HR: 1.95 (95% CI: 1.19-3.20) for women with five or more children). Compared with women who did not breastfeed, the adjusted HR was 0.71 (95% CI: 0.52-0.98) among women who breastfed. For childbearing women who never breastfed, the adjusted HR was 1.58 (95% CI: 1.09-2.30) compared with nulliparous women, whereas for childbearing women who breastfed, the adjusted HR was 1.19 (95% CI: 0.99-1.43). CONCLUSION: Having more children was associated with a higher risk of CHD later in life, whereas breastfeeding was associated with a lower CHD risk. Women who both had children and breastfed did have a non-significantly higher risk of CHD.
    Type of Publication: Journal article published
    PubMed ID: 27378766
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