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Objectives: Prevalence rate of diabetes is high among migrants. Whether migrants are correctly addressed to a standard quality of care for diabetes and are properly followed up are the questions addressed by this retrospective cohort study., Methods: Compliance to one or repeated Guideline Composite Indicator (GCI), a standard process indicator of care quality, was tested in migrants compared to non-migrant Italian residents with diabetes, living in Tuscany Region, Italy, in years 2011-2015. For those with no GCI, the analysis was repeated for the chance of being tested by at least one or more HbA1c measurements., Results: GCI compliance, in a single or repeated manner over time, was significantly less likely by about 15-20% among migrants (n = 3992) compared to non-migrants (n = 130,874), even after fully matching both cohorts. For those with no GCI, being tested by HbA1c was still significantly less likely among migrants., Conclusions: Being addressed to a standard quality of care is impaired among migrant patients with diabetes living in Tuscany compared to non-migrants. Migrants, moreover, have a significantly lower probability of adhering to guidelines or to be tested by HbA1c measurement over time.

Using several longitudinal datasets describing putative factors affecting influenza incidence and clinical data on the disease and health status of over 150 million human subjects observed over a decade, we investigated the source and the mechanistic triggers of influenza epidemics. We conclude that the initiation of a pan-continental influenza wave emerges from the simultaneous realization of a complex set of conditions. The strongest predictor groups are as follows, ranked by importance: (1) the host population's socio- and ethno-demographic properties; (2) weather variables pertaining to specific humidity, temperature, and solar radiation; (3) the virus' antigenic drift over time; (4) the host population'€™s land-based travel habits, and; (5) recent spatio-temporal dynamics, as reflected in the influenza wave auto-correlation. The models we infer are demonstrably predictive (area under the Receiver Operating Characteristic curve 80%) when tested with out-of-sample data, opening the door to the potential formulation of new population-level intervention and mitigation policies., Competing Interests: IC, EK, JE, JS, AR No competing interests declared, (© 2018, Chattopadhyay et al.)

Aims: Obesity has been found to be protective in heart failure (HF), a finding leading to the concept of an obesity paradox. We hypothesized that a preserved cardiorespiratory fitness in obese HF patients may affect the relationship between survival and body mass index (BMI) and explain the obesity paradox in HF., Methods and Results: A total of 4623 systolic HF patients (LVEF 31.5 ± 9.5%, BMI 26.2 ± 3.6 kg/m(2) ) were recruited and prospectively followed in 24 Italian HF centres belonging to the MECKI Score Research Group. Besides full clinical examination, patients underwent maximal cardiopulmonary exercise test at study enrolment. Median follow-up was 1113 (553-1803) days. The study population was divided according to BMI (<25, 25-30, >30 to ≤35 kg/m(2) ) and predicted peak oxygen consumption (peak VO2 , <50%, 50-80%, >80%). Study endpoints were all-cause and cardiovascular deaths including urgent cardiac transplant. All-cause and cardiovascular deaths occurred in 951 (28.6%, 57.4 per person-years) and 802 cases (17.4%, 48.4 per 1000 person-years), respectively. In the high BMI groups, several prognostic parameters presented better values [LVEF, peak VO2 , ventilation/carbon dioxide slope, renal function, and haemoglobin (P < 0.01)] compared with the lower BMI groups. Both BMI and peak VO2 were significant positive predictors of longer survival: both higher BMI and peak VO2 groups showed lower mortality (P < 0.001). At multivariable analysis and using a matching procedure (age, gender, LVEF, and peak VO2 ), the protective role of BMI disappeared., Conclusion: Exercise tolerance affects the relationship between BMI and survival. Cardiorespiratory fitness mitigates the obesity paradox observed in HF patients., (© 2016 The Authors. European Journal of Heart Failure © 2016 European Society of Cardiology.)

Background: Atrial fibrillation (AF) is common in heart failure (HF). It is unclear whether AF has an independent prognostic role in HF. The aim of the present study was to assess the prognostic role of AF in HF patients with reduced ejection fraction (EF)., Methods: HF patients were followed in 17 centers for 3.15years (1.51-5.24). Study endpoints were the composite of cardiovascular (CV) death and heart transplant (HTX) and all-cause death. Data analysis was performed considering the entire population and a 1 to 1 match between sinus rhythm (SR) and AF patients. Match process was done for age±5, gender, left ventricle EF±5, peakVO2±3 (ml/min/kg) and recruiting center., Results: A total of 3447 patients (SR=2882, AF=565) were included in the study. Considering the entire population, CV death and HTX occurred in 114 (20%) AF vs. 471 (16%) SR (p=0.026) and all-cause death in 130 (23%) AF vs. 554 (19.2%) SR patients (p=0.039). At univariable Cox analysis, AF was significantly related to prognosis. Applying a multivariable model based on all variables significant at univariable analysis (EF, peakVO2, ventilation/carbon dioxide relationship slope, sodium, kidney function, hemoglobin, beta-blockers and digoxin) AF was no longer associated with adverse outcomes. Matching procedure resulted in 338 couples. CV death and HTX occurred in 63 (18.6%) AF vs. 74 (21.9%) SR (p=0.293) and all-cause death in 71 (21%) AF vs. 80 (23.6%) SR (p=0.406), with no survival differences between groups., Conclusion: In systolic HF AF is a marker of disease severity but not an independent prognostic indicator., (Copyright © 2015 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.)

This paper explores the impact of residential mobility on educational outcomes. By considering a large Dutch city with substantial internal residential mobility, we examine how residential mobility influences the decision of students to drop out of school. The paper exploits a rich administrative dataset with extensive information on educational, individual, family, housing and moving characteristics of students. It combines a matching design with a multivariate regression analysis, such that the evaluation draws on a well-comparable control group for the treated students. Accounting for individual, family, educational, neighborhood and housing characteristics, as well as for school and year fixed effects, we observe that residential mobility increases the probability of school dropout in the first few years after moving. The estimated effect changes, however, to a lower risk of early school leaving after an initial period, and then changes again to a higher risk after 6years. This effect remains, regardless the level of education the students attended, or whether the student moves to a better or a worse neighborhood., (Copyright © 2015 Elsevier Inc. All rights reserved.)