Migrant workers in Italy: an analysis of injury risk taking into account occupational characteristics and job tenure

Abstract Background Migrants resident in Italy exceeded 5 million in 2015, representing 8.2% of the resident population. The study of the mechanisms that explain the differential health of migrant workers (as a whole and for specific nationalities) has been identified as a priority for research. The international literature has shown that migrant workers have a higher risk of total and fatal injury than natives, but some results are conflicting. The aim of this paper is to study the injury risk differentials between migrants, born in countries with strong migratory pressure (SMPC), and workers born in high income countries (HIC), taking into account individual and firm characteristics and job tenure. In addition to a comprehensive analysis of occupational safety among migrants, the study focuses on Moroccans, the largest community in Italy in the years of the analysis. Methods Using the Work History Italian Panel-Salute integrated database, only contracts of employment in the private sector, starting in the period between 2000 and 2005 and held by men, were selected. The analysis focused on economic sectors with an important foreign component: engineering, construction, wholesale and retail trade, transportation and storage. Injury rates were calculated using a definition of serious occupational injuries based on the type of injury. Incidence rate ratios (IRR) were calculated using a Poisson distribution for panel data taking into account time-dependent variables. Results Injury rates among SMPC workers were higher than for HIC workers in engineering (15.61 ‰ py vs. 8.92 ‰ py), but there were no significant differences in construction (11.21 vs. 10.09), transportation and storage (7.82 vs. 7.23) and the wholesale and retail sectors (4.06 vs. 4.67). Injury rates for Moroccans were higher than for both HIC and total migrant workers in all economic sectors considered. The multivariate analysis revealed an interaction effect of job tenure among both SMPC and Moroccan workers in the construction sector, while in the wholesale and retail trade sector an interaction effect of job tenure was only observed among Moroccan workers. Conclusions Migrant workers have higher occupational injury rates than Italians in the engineering and construction sectors, after two years of experience within the job. Generally the risk differentials vary depending on the nationality and economic sector considered. The analysis of injury risk among migrant workers should be restricted to serious injuries; furthermore, job tenure must be taken into account

Primeros registros de tersina (Tersina viridis) para la ecoregión chaqueña de Argentina

El Tersina (Tersina viridis) se distribuye desde Panamá hasta la provincia de Misiones en Argentina (Schaefer 1953, Short 1975, Ridgely & Tudor 2009). Sin embargo,el comportamiento errático que muestra a menudo esta especie hace esperable registros en lugares lejanos a su área de distribución regular (Olrog 1959, Short 1975,Hilty 2011).Sumando mérito a su fama de errante, en este trabajo presentamos los primeros registros del Tersina para la Ecoregión del Chaco Seco, cinco para Córdoba y uno para Formosa. Estos nuevos registros suman ejemplos al consenso general que existe en favor de los hábitos erráticos de esta especie (Di Giacomo et al. 1995, Hilty 2011) dando a entender por consiguiente que se tratan de individuos transitorios o accidentales.Fil: Zelaya, Patricia Viviana. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto de Ecología Regional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; ArgentinaFil: Salvador, Sergio A..Fil: Giraudo, Hugo.Fil: Klavins, Juan

Determination of the geographical origin of green coffee beans using NIR spectroscopy and multivariate data analysis

In this work, near infrared (NIR) spectroscopy and multivariate data analysis were investigated as a fast and non disruptive method to classify green coffee beans on continents and countries bases. FT-NIR spectra of 191 coffee samples, origin from 2 continents and 9 countries, were acquired by two different laboratories. Laboratory-independent Partial Least Square-Discriminant Analysis and interval PIS-DA models were developed by following a hierarchical approach, i.e. considering at first the continent and then the country of origin as discrimination rule. The best continent-based classification model was able to identify correctly more than 98% in prediction, whereas 100% of them were correctly predicted by the best country-based classification model. The inter-laboratory reliability of the proposed method was confirmed by McNemar test, since no significant differences (P > 0.05) were found. Furthermore, a validation was performed predicting the spectral test set of a laboratory using the model developed by the other one