Association Between Egg Consumption and Dementia Risk in the EPIC-Spain Dementia Cohort

Current evidence suggests that egg composition might have potential neuroprotective effects. Our aim was to determine the association between egg consumption and the risk of dementia in a Mediterranean population. MethodsThis study was carried out in 3 centers from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Spain Dementia Cohort, i.e., 25,015 participants aged 30-70 years, recruited in 1992-1996, and followed up for a mean of 21.5 years. ResultsA total of 774 incident dementia cases were diagnosed and validated, of which 518 were Alzheimer's disease (AD). Data on egg consumption were estimated using a validated dietary history questionnaire at recruitment. Cox proportional hazards models, adjusted for confounders, were used in the analyses. No association was observed between egg consumption and either total dementia [hazard ratio between extreme quartiles (HRQ4vs.Q1: 1.05; 95% CI 0.85-1.31; p-trend = 0.93)] or AD (HRQ4vs.Q1 0.93; 95% CI 0.72-1.21; p-trend = 0.50) risks. After dividing the population by adherence to the relative Mediterranean diet (rMED) score, a borderline inverse association was found between egg intake and both total dementia (HRQ4vs.Q1: 0.52; 95% CI 0.30-0.90; p-trend = 0.10) and AD (HRQ4vs.Q1: 0.52; 95% CI 0.27-1.01; p-trend = 0.13) risks within participants with low adherence to rMED score. However, no association was observed in participants with medium and high adherence to rMED score. ConclusionThis prospective study suggests that egg consumption is associated with a reduced risk of dementia, and specifically of AD, in the adult population with low adherence to rMED score; whereas it has no impact in subjects with moderate and high MD adherence

Temporal evolution of brain cancer incidence in the municipalities of Navarre and the Basque Country, Spain

Background: Brain cancer incidence rates in Spain are below the European’s average. However, there are two regions in the north of the country, Navarre and the Basque Country, ranked among the European regions with the highest incidence rates for both males and females. Our objective here was two-fold. Firstly, to describe the temporal evolution of the geographical pattern of brain cancer incidence in Navarre and the Basque Country, and secondly, to look for specific high risk areas (municipalities) within these two regions in the study period (1986–2008). Methods: A mixed Poisson model with two levels of spatial effects is used. The model also included two levels of spatial effects (municipalities and local health areas). Model fitting was carried out using penalized quasi-likelihood. High risk regions were detected using upper one-sided confidence intervals. Results: Results revealed a group of high risk areas surrounding Pamplona, the capital city of Navarre, and a few municipalities with significant high risks in the northern part of the region, specifically in the border between Navarre and the Basque Country (Gipuzkoa). The global temporal trend was found to be increasing. Differences were also observed among specific risk evolutions in certain municipalities. Conclusions: Brain cancer incidence in Navarre and the Basque Country (Spain) is still increasing with time. The number of high risk areas within those two regions is also increasing. Our study highlights the need of continuous surveillance of this cancer in the areas of high risk. However, due to the low percentage of cases explained by the known risk factors, primary prevention should be applied as a general recommendation in these populations.This research has been supported by the Spanish Ministry of Science and Innovation (project MTM 2011-22664, jointly sponsored with FEDER grants and project MTM2014-51992-R), and by the Health Department of the Navarre Government (project 113, Res.2186/2014)

A Set of Reliable Samples for the Study of Biomarkers for the Early Diagnosis of Parkinson's Disease

BackgroundParkinson's disease (PD) is a progressive neurodegenerative disorder, diagnosed according to the clinical criteria that occur in already advanced stages of PD. The definition of biomarkers for the early diagnosis of PD represents a challenge that might improve treatment and avoid complications in this disease. Therefore, we propose a set of reliable samples for the identification of altered metabolites to find potential prognostic biomarkers for early PD. MethodsThis case-control study included plasma samples of 12 patients with PD and 21 control subjects, from the Spanish European Prospective Investigation into Cancer and Nutrition (EPIC)-Navarra cohort, part of the EPIC-Spain study. All the case samples were provided by healthy volunteers who were followed-up for 15.9 (+/- 4.1) years and developed PD disease later on, after the sample collection. Liquid chromatography coupled to tandem mass spectrometry was used for the analysis of samples. ResultsOut of 40 that were selected and studied due to their involvement in established cases of PD, seven significantly different metabolites between PD cases and healthy control subjects were obtained in this study (benzoic acid, palmitic acid, oleic acid, stearic acid, myo-inositol, sorbitol, and quinolinic acid). These metabolites are related to mitochondrial dysfunction, the oxidative stress, and the mechanisms of energy production. ConclusionWe propose the samples from the EPIC study as reliable and invaluable samples for the search of early biomarkers of PD. Likewise, this study might also be a starting point in the establishment of a well-founded panel of metabolites that can be used for the early detection of this disease.he EPIC study received financial support from the International Agency for Research on Cancer (AEP/93/06), the European Commission (SO-97-200302-05F02 and SP23-CT-2005-006438), the Health Research Fund (FIS) of the Spanish Ministry of Health, the Red Temática de Investigación Cooperativa de Centros de Cáncer (RTICCC C03/10 and RD06/0020), the Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), the participating Regional Governments of Andalusia, Basque Country, Murcia and Navarra, and the Catalan Institute of Oncology (ICO). This study was furthermore supported by the Ministry of Health of the Basque Government, Exp 20161109

Inverse-probability weighting and multiple imputation for evaluating selection bias in the estimation of childhood obesity prevalence using data from electronic health records

Background and objectives: Height and weight data from electronic health records are increasingly being used to estimate the prevalence of childhood obesity. Here, we aim to assess the selection bias due to missing weight and height data from electronic health records in children older than five. Methods: Cohort study of 10,811 children born in Navarra (Spain) between 2002 and 2003, who were still living in this region by December 2016. We examined the differences between measured and non-measured children older than 5 years considering weight-associated variables (sex, rural or urban residence, family income and weight status at 2–5 yrs). These variables were used to calculate stabilized weights for inverse-probability weighting and to conduct multiple imputation for the missing data. We calculated complete data prevalence and adjusted prevalence considering the missing data using inverse-probability weighting and multiple imputation for ages 6 to 14 and group ages 6 to 9 and 10 to 14. Results: For 6–9 years, complete data, inverse-probability weighting and multiple imputation obesity age-adjusted prevalence were 13.18% (95% CI: 12.54–13.85), 13.22% (95% CI: 12.57–13.89) and 13.02% (95% CI: 12.38–13.66) and for 10–14 years 8.61% (95% CI: 8.06–9.18), 8.62% (95% CI: 8.06–9.20) and 8.24% (95% CI: 7.70–8.78), respectively. Conclusions: Ages at which well-child visits are scheduled and for the 6 to 9 and 10 to 14 age groups, weight status estimations are similar using complete data, multiple imputation and inverse-probability weighting. Readily available electronic health record data may be a tool to monitor the weight status in children