Spatial analysis of the relationship between mortality from cardiovascular and cerebrovascular disease and drinking water hardness
Journal Article; Research Support, Non-U.S. Gov't; Reproduced with permission from Environmental Health Perspectives. Previously published scientific papers have reported a negative correlation between drinking water hardness and cardiovascular mortality. Some ecologic and case-control studies suggest the protective effect of calcium and magnesium concentration in drinking water. In this article we present an analysis of this protective relationship in 538 municipalities of Comunidad Valenciana (Spain) from 1991-1998. We used the Spanish version of the Rapid Inquiry Facility (RIF) developed under the European Environment and Health Information System (EUROHEIS) research project. The strateg…
Geographical Distribution of Cardiovascular Mortality in Comunidad Valenciana (Spain)
Comunidad Valenciana is one of the seventeen autonomous regions into which Spain is divided. It is located on the east coast of Spain, next to the Mediterranean sea, with an area of 23,255 km2 and with 4,009,329 inhabitants in 1996. From an administrative point of view there are three levels of aggregation: provinces (3 units), health areas (20 units) and municipalities (541 units).
Statistical relationship between hardness of drinking water and cerebrovascular mortality in Valencia: a comparison of spatiotemporal models
The statistical detection of environmental risk factors in public health studies is usually difficult due to the weakness of their effects and their confounding with other covariates. Small area geographical data bring the opportunity of observing health response in a wide variety of exposure values. Temporal sequences of these geographical datasets are crucial to gaining statistical power in detecting factors. The spatiotemporal models required to perform the statistical analysis have to allow for spatial and temporal correlations, which are more easily modelled via hierarchical structures of hidden random factors. These models have produced important research activity during the last deca…
Temporal aggregation in chain graph models
The dependence structure of an observed process induced by temporal aggregation of a time evolving hidden spatial phenomenon is addressed. Data are described by means of chain graph models and an algorithm to compute the chain graph resulting from the temporal aggregation of a directed acyclic graph is provided. This chain graph is the best graph which covers the independencies of the resulting process within the chain graph class. A sufficient condition that produces a memory loss of the observed process with respect to its hidden origin is analyzed. Some examples are used for illustrating algorithms and results.