1,720,984 research outputs found
Anthropometric measures and incident type 2 diabetes.
No full text<p>HRs estimated from modified Cox regression with age as the underlying time scale, using Prentice weights. Centre-specific estimates are combined using random effects meta-analysis.</p
Cumulative incidence of type 2 diabetes over 10 y by BMI and waist circumference groups in women.
No full text<p>Red line, WC<80 cm; blue line, WC≥80–87.9 cm; black line, WC≥88 cm.</p
Long-Term Risk of Incident Type 2 Diabetes and Measures of Overall and Regional Obesity: The EPIC-InterAct Case-Cohort Study
No full text<div><h3>Background</h3><p>Waist circumference (WC) is a simple and reliable measure of fat distribution that may add to the prediction of type 2 diabetes (T2D), but previous studies have been too small to reliably quantify the relative and absolute risk of future diabetes by WC at different levels of body mass index (BMI).</p> <h3>Methods and Findings</h3><p>The prospective InterAct case-cohort study was conducted in 26 centres in eight European countries and consists of 12,403 incident T2D cases and a stratified subcohort of 16,154 individuals from a total cohort of 340,234 participants with 3.99 million person-years of follow-up. We used Prentice-weighted Cox regression and random effects meta-analysis methods to estimate hazard ratios for T2D. Kaplan-Meier estimates of the cumulative incidence of T2D were calculated. BMI and WC were each independently associated with T2D, with WC being a stronger risk factor in women than in men. Risk increased across groups defined by BMI and WC; compared to low normal weight individuals (BMI 18.5–22.4 kg/m<sup>2</sup>) with a low WC (<94/80 cm in men/women), the hazard ratio of T2D was 22.0 (95% confidence interval 14.3; 33.8) in men and 31.8 (25.2; 40.2) in women with grade 2 obesity (BMI≥35 kg/m<sup>2</sup>) and a high WC (>102/88 cm). Among the large group of overweight individuals, WC measurement was highly informative and facilitated the identification of a subgroup of overweight people with high WC whose 10-y T2D cumulative incidence (men, 70 per 1,000 person-years; women, 44 per 1,000 person-years) was comparable to that of the obese group (50–103 per 1,000 person-years in men and 28–74 per 1,000 person-years in women).</p> <h3>Conclusions</h3><p>WC is independently and strongly associated with T2D, particularly in women, and should be more widely measured for risk stratification. If targeted measurement is necessary for reasons of resource scarcity, measuring WC in overweight individuals may be an effective strategy, since it identifies a high-risk subgroup of individuals who could benefit from individualised preventive action.</p> <h3></h3><p> <em>Please see later in the article for the Editors' Summary</em></p> </div
Tea consumption based on data from a food frequency questionnaire in the sub-cohort of the EPIC-InterAct project by country (<i>n</i> = 15,227).
No full text<p>Bar represents median (p25–p75); error line represents p5 till p95.</p
Characteristics of the subcohort by BMI group in men of the InterAct study.
No full text<p>Data are means and SDs for continuous and percentages and frequencies for categorical variables. Twenty men in the subcohort were underweight (BMI<18.5 kg/m<sup>2</sup>) and were excluded from this table; 41 men in the subcohort had missing values for BMI and were excluded from this table.</p>a<p>Data on WC and waist-hip ratio were not collected at the centre in Umea, Sweden (excluded from these summaries).</p>b<p>Family history data were not collected at the centres in Italy, Spain, Oxford, or Heidelberg, so these countries have been excluded when calculating percentages of individuals with/without a family history of diabetes.</p
Hazard ratios for type 2 diabetes per 1 SD increase in WC (SD = 11.2 cm) in women.
No full text<p>Heterogeneity between centres: <i>I</i><sup>2</sup> = 69% (<i>p</i><0.001). HRs estimated from modified Cox regression with age as the underlying time scale, using Prentice weights. Centre-specific estimates are combined using random effects meta-analysis.</p
Association between tea consumption as a categorical variable (>0-<1 vs. 0, 1-<4 vs. 0, ≥4 vs. 0 cups/d) based on data from a food frequency questionnaire and risk of type 2 diabetes (<i>n</i> = 26,039).
No full text<p>Country-specific Hazard Ratios (HR) and 95% Confidence Intervals (95%CI) were pooled using random effects meta-analyses. HR were adjusted for sex, smoking status, physical activity level, education level, intake of energy, protein, carbohydrates, saturated fatty acids, mono-unsaturated fatty acids, poly-unsaturated fatty acids, alcohol, fiber, coffee, juices, soft-drinks, milk, and body mass index.</p
Investigation of gene–diet interactions in the incretin system and risk of type 2 diabetes: the EPIC-InterAct study
Get PDFAims/hypothesis
The gut incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) have a major role in the pathophysiology of type 2 diabetes. Specific genetic and dietary factors have been found to influence the release and action of incretins. We examined the effect of interactions between seven incretin-related genetic variants in GIPR, KCNQ1, TCF7L2 and WFS1 and dietary components (whey-containing dairy, cereal fibre, coffee and olive oil) on the risk of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct study.
Methods
The current case-cohort study included 8086 incident type 2 diabetes cases and a representative subcohort of 11,035 participants (median follow-up: 12.5 years). Prentice-weighted Cox proportional hazard regression models were used to investigate the associations and interactions between the dietary factors and genes in relation to the risk of type 2 diabetes.
Results
An interaction (p = 0.048) between TCF7L2 variants and coffee intake was apparent, with an inverse association between coffee and type 2 diabetes present among carriers of the diabetes risk allele (T) in rs12255372 (GG: HR 0.99 [95% CI 0.97, 1.02] per cup of coffee; GT: HR 0.96 [95% CI 0.93, 0.98]); and TT: HR 0.93 [95% CI 0.88, 0.98]). In addition, an interaction (p = 0.005) between an incretin-specific genetic risk score and coffee was observed, again with a stronger inverse association with coffee in carriers with more risk alleles (0–3 risk alleles: HR 0.99 [95% CI 0.94, 1.04]; 7–10 risk alleles: HR 0.95 [95% CI 0.90, 0.99]). None of these associations were statistically significant after correction for multiple testing.
Conclusions/interpretation
Our large-scale case-cohort study provides some evidence for a possible interaction of TCF7L2 variants and an incretin-specific genetic risk score with coffee consumption in relation to the risk of type 2 diabetes. Further large-scale studies and/or meta-analyses are needed to confirm these interactions in other populations
Hazard ratios for type 2 diabetes per 1 SD increase in BMI (SD = 4.4 kg/m<sup>2</sup>) in women.
No full text<p>Heterogeneity between centres: <i>I</i><sup>2</sup> = 59% (<i>p</i> = 0.012). HRs estimated from modified Cox regression with age as the underlying time scale, using Prentice weights. Centre-specific estimates are combined using random effects meta-analysis.</p
Association between tea consumption based on data from a food frequency questionnaire and risk of type 2 diabetes obtained by spline regression with 3 knots (1, 4, 7 cups per day) and 0 cups per day as reference (<i>n</i> = 26,039).
No full text<p>Dotted lines represent 95% confidence intervals (95%CI). <i>P</i><sub>non-linearity</sub> = 0.20. Hazard ratios were adjusted for sex, smoking status, physical activity level, education level, intake of energy, protein, carbohydrates, saturated fatty acids, mono-unsaturated fatty acids, poly-unsaturated fatty acids, alcohol, fiber, coffee, juices, soft-drinks, milk, and body mass index.</p
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