METHODS: This study includes 373,293 men and women, 25-70 years old, recruited between 1992 and 2000 from 10 European countries in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Habitual intake of nuts including peanuts, together defined as nut intake, was estimated from country-specific validated dietary questionnaires. Body weight was measured at recruitment and self-reported 5 years later. The association between nut intake and body weight change was estimated using multilevel mixed linear regression models with center/country as random effect and nut intake and relevant confounders as fixed effects. The relative risk (RR) of becoming overweight or obese after 5 years was investigated using multivariate Poisson regressions stratified according to baseline body mass index (BMI).
RESULTS: On average, study participants gained 2.1 kg (SD 5.0 kg) over 5 years. Compared to non-consumers, subjects in the highest quartile of nut intake had less weight gain over 5 years (-0.07 kg; 95% CI -0.12 to -0.02) (P trend = 0.025) and had 5% lower risk of becoming overweight (RR 0.95; 95% CI 0.92-0.98) or obese (RR 0.95; 95% CI 0.90-0.99) (both P trend <0.008).
CONCLUSIONS: Higher intake of nuts is associated with reduced weight gain and a lower risk of becoming overweight or obese.
METHODS: The HIV-CAUSAL Collaboration consisted of 12 cohorts from the United States and Europe of HIV-positive, ART-naive, AIDS-free individuals aged ≥18 years with baseline CD4 cell count and HIV RNA levels followed up from 1996 through 2007. We estimated hazard ratios (HRs) for cART versus no cART, adjusted for time-varying CD4 cell count and HIV RNA level via inverse probability weighting.
RESULTS: Of 65 121 individuals, 712 developed tuberculosis over 28 months of median follow-up (incidence, 3.0 cases per 1000 person-years). The HR for tuberculosis for cART versus no cART was 0.56 (95% confidence interval [CI], 0.44-0.72) overall, 1.04 (95% CI, 0.64-1.68) for individuals aged >50 years, and 1.46 (95% CI, 0.70-3.04) for people with a CD4 cell count of <50 cells/μL. Compared with people who had not started cART, HRs differed by time since cART initiation: 1.36 (95% CI, 0.98-1.89) for initiation <3 months ago and 0.44 (95% CI, 0.34-0.58) for initiation ≥3 months ago. Compared with people who had not initiated cART, HRs <3 months after cART initiation were 0.67 (95% CI, 0.38-1.18), 1.51 (95% CI, 0.98-2.31), and 3.20 (95% CI, 1.34-7.60) for people <35, 35-50, and >50 years old, respectively, and 2.30 (95% CI, 1.03-5.14) for people with a CD4 cell count of <50 cells/μL.
CONCLUSIONS: Tuberculosis incidence decreased after cART initiation but not among people >50 years old or with CD4 cell counts of <50 cells/μL. Despite an overall decrease in tuberculosis incidence, the increased rate during 3 months of ART suggests unmasking IRIS.
METHODS AND FINDINGS: The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.
CONCLUSIONS: These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.
METHODS: 2010-2015 incidence data for influenza A (IAV), influenza B (IBV), respiratory syncytial (RSV) and parainfluenza (PIV) virus infections were collected from 18 sites (14 countries), consisting of local (n = 6), regional (n = 9) and national (n = 3) laboratories using molecular diagnostic methods. Each site submitted monthly virus incidence data, together with details of their patient populations tested and diagnostic assays used.
RESULTS: For the Northern Hemisphere temperate countries, the IAV, IBV and RSV incidence peaks were 2-6 months out of phase with those in the Southern Hemisphere, with IAV having a sharp out-of-phase difference at 6 months, whereas IBV and RSV showed more variable out-of-phase differences of 2-6 months. The tropical sites Singapore and Kuala Lumpur showed fluctuating incidence of these viruses throughout the year, whereas subtropical sites such as Hong Kong, Brisbane and Sydney showed distinctive biannual peaks for IAV but not for RSV and PIV.
CONCLUSIONS: There was a notable pattern of synchrony of IAV, IBV and RSV incidence peaks globally, and within countries with multiple sampling sites (Canada, UK, Australia), despite significant distances between these sites.
OBJECTIVE: We examined the association between sweet-beverage consumption (including total, sugar-sweetened, and artificially sweetened soft drink and juice and nectar consumption) and pancreatic cancer risk.
DESIGN: The study was conducted within the European Prospective Investigation into Cancer and Nutrition cohort. A total of 477,199 participants (70.2% women) with a mean age of 51 y at baseline were included, and 865 exocrine pancreatic cancers were diagnosed after a median follow-up of 11.60 y (IQR: 10.10-12.60 y). Sweet-beverage consumption was assessed with the use of validated dietary questionnaires at baseline. HRs and 95% CIs were obtained with the use of multivariable Cox regression models that were stratified by age, sex, and center and adjusted for educational level, physical activity, smoking status, and alcohol consumption. Associations with total soft-drink consumption were adjusted for juice and nectar consumption and vice versa.
RESULTS: Total soft-drink consumption (HR per 100 g/d: 1.03; 95% CI: 0.99, 1.07), sugar-sweetened soft-drink consumption (HR per 100 g/d: 1.02; 95% CI: 0.97, 1.08), and artificially sweetened soft-drink consumption (HR per 100 g/d: 1.04; 95% CI: 0.98, 1.10) were not associated with pancreatic cancer risk. Juice and nectar consumption was inversely associated with pancreatic cancer risk (HR per 100 g/d: 0.91; 95% CI: 0.84, 0.99); this association remained statistically significant after adjustment for body size, type 2 diabetes, and energy intake.
CONCLUSIONS: Soft-drink consumption does not seem to be associated with pancreatic cancer risk. Juice and nectar consumption might be associated with a modest decreased pancreatic cancer risk. Additional studies with specific information on juice and nectar subtypes are warranted to clarify these results.
OBJECTIVE: The objective was to generate evidence on the association between WHO dietary recommendations and mortality from CVD, coronary artery disease (CAD), and stroke in the elderly aged ≥60 y.
DESIGN: We analyzed data from 10 prospective cohort studies from Europe and the United States comprising a total sample of 281,874 men and women free from chronic diseases at baseline. Components of the Healthy Diet Indicator (HDI) included saturated fatty acids, polyunsaturated fatty acids, mono- and disaccharides, protein, cholesterol, dietary fiber, and fruit and vegetables. Cohort-specific HRs adjusted for sex, education, smoking, physical activity, and energy and alcohol intakes were pooled by using a random-effects model.
RESULTS: During 3,322,768 person-years of follow-up, 12,492 people died of CVD. An increase of 10 HDI points (complete adherence to an additional WHO guideline) was, on average, not associated with CVD mortality (HR: 0.94; 95% CI: 0.86, 1.03), CAD mortality (HR: 0.99; 95% CI: 0.85, 1.14), or stroke mortality (HR: 0.95; 95% CI: 0.88, 1.03). However, after stratification of the data by geographic region, adherence to the HDI was associated with reduced CVD mortality in the southern European cohorts (HR: 0.87; 95% CI: 0.79, 0.96; I(2) = 0%) and in the US cohort (HR: 0.85; 95% CI: 0.83, 0.87; I(2) = not applicable).
CONCLUSION: Overall, greater adherence to the WHO dietary guidelines was not significantly associated with CVD mortality, but the results varied across regions. Clear inverse associations were observed in elderly populations in southern Europe and the United States.