Methodological limitations and recommendations in publications on migrant population health in Spain

El objetivo es describir las limitaciones y las recomendaciones metodológicas identificadas por los autores de artículos originales sobre inmigración y salud en España. Se realizó una revisión bibliográfica de artículos originales publicados en español e inglés entre 1998 y 2012, combinando descriptores de inmigración y salud. Se incluyeron 311 artículos; de ellos, 176 (56,6%) mencionaban limitaciones y 15 (4,8%) emitían recomendaciones. Entre las limitaciones más mencionadas destacan el reducido tamaño de las muestras, problemas de validez interna y representatividad de la muestra con infrarrepresentación o sobrerrepresentación de determinados grupos, problemas de validez de la información recogida y datos faltantes relacionados sobre todo con los instrumentos de medición, y ausencia de variables clave de ajuste o estratificación. En función de los resultados obtenidos, se proponen una serie de recomendaciones para minimizar las limitaciones habituales y avanzar en la calidad de los trabajos científicos sobre inmigración y salud en nuestro ámbito.Our objective was to describe the methodological limitations and recommendations identified by authors of original articles on immigration and health in Spain. A literature review was conducted of original articles published in Spanish or English between 1998 and 2012 combining keywords on immigration and health. A total of 311 articles were included; of these, 176 (56.6%) mentioned limitations, and 15 (4.8%) made recommendations. The most frequently mentioned limitations included the following: reduced sample sizes; internal validity and sample representativeness issues, with under- or overrepresentation of specific groups; problems of validity of the collected information and missing data mostly related to measurement tools; and absence of key variables for adjustment or stratification. Based on these results, a series of recommendations are proposed to minimise common limitations and advance the quality of scientific production on immigration and health in our setting.El Subprograma Inmigración y Salud (SIS) del CIBER de Epidemiología y Salud Pública (CIBERESP) financió la realización de la revisión bibliográfica. La Sociedad Española de Epidemiología (SEE) financió los gastos derivados de la publicación

Optimization of adsorptive removal of α-toluic acid by CaO2 nanoparticles using response surface methodology

The present work addresses the optimization of process parameters for adsorptive removal of α-toluic acid by calcium peroxide (CaO2) nanoparticles using response surface methodology (RSM). CaO2 nanoparticles were synthesized by chemical precipitation method and confirmed by Transmission electron microscopy (TEM) and high-resolution TEM (HRTEM) analysis which shows the CaO2 nanoparticles size range of 5–15 nm. A series of batch adsorption experiments were performed using CaO2 nanoparticles to remove α-toluic acid from the aqueous solution. Further, an experimental based central composite design (CCD) was developed to study the interactive effect of CaO2 adsorbent dosage, initial concentration of α-toluic acid, and contact time on α-toluic acid removal efficiency (response) and optimization of the process. Analysis of variance (ANOVA) was performed to determine the significance of the individual and the interactive effects of variables on the response. The model predicted response showed a good agreement with the experimental response, and the coefficient of determination, (R2) was 0.92. Among the variables, the interactive effect of adsorbent dosage and the initial α-toluic acid concentration was found to have more influence on the response than the contact time. Numerical optimization of process by RSM showed the optimal adsorbent dosage, initial concentration of α-toluic acid, and contact time as 0.03 g, 7.06 g/L, and 34 min respectively. The predicted removal efficiency was 99.50%. The experiments performed under these conditions showed α-toluic acid removal efficiency up to 98.05%, which confirmed the adequacy of the model prediction