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Space-cohort Bayesian models in ecological studies

Department of Statistics G‘. Parenti’, University of Florence, Florence, Italy, Department of Statistical Sciences, University of Udine, Udine, Italy, catelan{at}dss.uniud.it

Annibale Biggeri

Department of Statistics G‘. Parenti’, University of Florence, Florence, Italy, 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

The ecological association between ‘low educational level' and lung cancer mortality, both recorded at municipality level, is investigated. Six birth cohorts were retained from 1905 to 1940. Education data were derived from censuses of the period 1921-91. 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, 1971-99) 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 20-30 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.

Key Words: birth cohort • disease mapping • lung cancer • hierarchical space-time Bayesian models • time-dependent covariates

Statistical Modelling, Vol. 6, No. 2, 159-173 (2006)
DOI: 10.1191/1471082X06st111oa


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