To discuss different trends of the geographical distribution of cancer mortality, progressively more complex surface models were fitted to cancer death certification data in the 95 Italian provinces for the period 1975-77, using trend surface analysis. This method is based on fitting first to sixth order regression equations, where dependent variables are latitude and longitude, and the independent one is the standardized mortality ratio (SMR) for various cancer sites. The procedure was implemented using the SYMAP package and appropriate routines ad hoc developed. General patterns in geography of cancer in Italy were therefore identified (such as the marked North/South gradient in mortality from most sites), thus helping in discerning main underlying pictures and permitting identification of local abnormalities (positive or negative residuals, corresponding to high or low mortality areas), which are often obscured by more general patterns using standard methods of analysis. Results and maps are presented and discussed in detail with reference to total mortality and three major sites (lung and intestines in males and female breast) for which regression surfaces with satisfactory fitting were identified. Some of the positive residuals (i.e. those for lung and breast cancer in women in urban concentrations of Central and Southern Italy) were already known, and explainable in terms of available knowledge of the causes of the neoplasms, chiefly smoking and reproductive habits in the past. Other findings, such as the consistent area of positive residuals in a chiefly rural area around the mouth of the river Po, offer useful suggestions for further aetiological research.

Trends surface models applied to the analysis of geographical variations in cancer mortality / C. Cislaghi, A. Decarli, C. La Vecchia, G. Mezzanotte, M. A. Vigotti. - In: REVUE D'EPIDEMIOLOGIE ET DE SANTE PUBLIQUE. - ISSN 0398-7620. - 38:1(1990), pp. 57-69.

Trends surface models applied to the analysis of geographical variations in cancer mortality

C. Cislaghi
Primo
;
A. Decarli
Secondo
;
C. La Vecchia;
1990

Abstract

To discuss different trends of the geographical distribution of cancer mortality, progressively more complex surface models were fitted to cancer death certification data in the 95 Italian provinces for the period 1975-77, using trend surface analysis. This method is based on fitting first to sixth order regression equations, where dependent variables are latitude and longitude, and the independent one is the standardized mortality ratio (SMR) for various cancer sites. The procedure was implemented using the SYMAP package and appropriate routines ad hoc developed. General patterns in geography of cancer in Italy were therefore identified (such as the marked North/South gradient in mortality from most sites), thus helping in discerning main underlying pictures and permitting identification of local abnormalities (positive or negative residuals, corresponding to high or low mortality areas), which are often obscured by more general patterns using standard methods of analysis. Results and maps are presented and discussed in detail with reference to total mortality and three major sites (lung and intestines in males and female breast) for which regression surfaces with satisfactory fitting were identified. Some of the positive residuals (i.e. those for lung and breast cancer in women in urban concentrations of Central and Southern Italy) were already known, and explainable in terms of available knowledge of the causes of the neoplasms, chiefly smoking and reproductive habits in the past. Other findings, such as the consistent area of positive residuals in a chiefly rural area around the mouth of the river Po, offer useful suggestions for further aetiological research.
Regression Analysis; Mortality; Neoplasms; Lung Neoplasms; Humans; Death Certificates; Breast Neoplasms; Models, Statistical; Male; Italy; Intestinal Neoplasms; Female
Settore MED/01 - Statistica Medica
1990
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/188646
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