Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Passive smoking in babies: the BIBE study (brief intervention in babies : effectiveness)

There is evidence that exposure to passive smoking in general, and in babies in particular, is an important cause of morbimortality. Passive smoking is related to an increased risk of pediatric diseases such as sudden death syndrome, acute respiratory diseases, worsening of asthma, acute-chronic middle ear disease and slowing of lung growth. The objective of this article is to describe the BIBE study protocol. The BIBE study aims to determine the effectiveness of a brief intervention within the context of Primary Care, directed to mothers and fathers that smoke, in order to reduce the exposure of babies to passive smoking (ETS)

Estudio del impacto ambiental del uso del bagazo como fuente de energía en centrales azucareros en Cuba. Estudio de caso "Melanio Hernández"

This work was carried out to study the environmental impacts produced by power generation from biomass (bagasse) in sugar mills in Cuba. For this purpose, with the collaboration of the Center for Energy and Industrial Processes (CEEPI), the University Center of Sancti Spiritus and using different research methods and techniques, conducted an environmental survey of the area. Gaseous emissions were characterized and the suspended solid particles, allowing knowing that these concentrations do not exceed the maximum emission limit set by the cubana Standard. In addition, the dispersion model applied DISPER allowed us to obtain information in crisis conditions of air emissions from sugar mill and distillery associated and concluded that emissions from the distillery are the pollutants that contribute more the atmosphere. The correlating emissions with respiratory diseases, (acute respiratory infections or subacute (IRA) and ASMA), concurrent Asthma Crisis (CAB) is the most affected. The calculated costs associated in these diseases, amounting to $ 119 599.23 per year. In order to minimize the negative alternatives are proposed to be implemented in industry and community.