Statistical Modelling 6 (2006), 159173
Space-cohort Bayesian models in ecological studies
Dolores Catelan
Department of Statistical Sciences,
University of Udine,
Via Treppo 18,
I33100 Udine
Italy
eMail:
catelan@dss.uniud.it
Annibale Biggeri
Department of Statistics 'G. Parenti', University of Florence
and
Biostatistics Unit, CSPO
Florence, Italy
Emanuela Dreassi
Department of Statistics 'G. Parenti', University of Florence
Florence, Italy
Corrado Lagazio
Department of Statistical Sciences,
University of Udine, Udine, Italy
Abstract:
The ecological association between ‘low educational level’
and lung cancer mortality, both
recorded atmunicipality level, is investigated. Six birth
cohortswere retained from 1905 to 1940. Education
data were derived from censuses of the period 192191.
The education score was defined as prevalence
of less educated people and was measured on a relative scale,
defining a different threshold for ‘low
educational level’ at each census. Four potentially relevant
ages at first exposure were defined (20, 30, 40,
50) to explore the temporal pattern of the disease. Thus,
mortality in each cohort was matched to relative
education at different periods corresponding to different
ages at first exposure. The relevance of each
age at first exposure and the degree of association between
education and lung cancer mortality (males,
Tuscany, 197199) were evaluated, defining a set of
hierarchical Bayesian models, each corresponding to
a different aetiologic hypothesis. Results show an inverse
relationship between low education score and
mortality for lung cancer, whose intensity decreases by
cohort and becomes positive in the last one. This
association was more evident for age at first exposure
in the range 2030 years. These results
are consistent
with the epidemiological transition of risk factors
among socioeconomic classes and are coherent with the
biological model of initiating carcinogen agents.
Keywords:
birth cohort; disease mapping; lung cancer;
hierarchical spacetime Bayesian models;
timedependent covariates
Example
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