EUGLOREH project
THE STATUS OF HEALTH IN THE EUROPEAN UNION:
TOWARDS A HEALTHIER EUROPE

FULL REPORT

PART II - HEALTH CONDITIONS

5. HEALTH IMPACTS OF NON COMMUNICABLE DISEASES AND RELATED TIME-TRENDS

5.12. Liver cirrhosis

5.12.2. Data sources

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5.12.2. Data sources

 

 

Official death certification numbers for cirrhosis over the period 1970-2002 were derived from the World Health Organization (WHO) database (WHO Statistical Information System, 2006b) for 28 European countries, plus separately England and Wales, and Scotland. European Union (EU) as a whole included the 27 countries as to January 2007. For Belgium, data were available only up to 1996, for Denmark up to 2001, and for Switzerland up to 1992. Data for Croatia were available only since 1985, for the Czech Republic since 1986, for Estonia since 1994, for Latvia since 1996, for Lithuania since 1993, for Slovakia since 1992 and for Slovenia since 1985. No data was available for Cyprus.

During the calendar period considered, three different Revisions of the International Classification of Diseases (ICD) were used (WHO, 1967; WHO, 1977; WHO, 1992). Since no appreciable change was introduced in the coding procedures of deaths from cirrhosis during this period, classification of cirrhosis deaths was recoded, for all calendar periods and countries, according to the Tenth Revision of the ICD (WHO, 1992).

Estimates of the resident populations, based on official censuses, were also obtained from the WHO database (WHO Statistical Information System, 2006b). From the matrices of the certified deaths and resident populations, age-specific rates for each five-year age group and calendar period were computed. Age-standardized rates per 100,000 population, at all ages and truncated at age 35 to 64 years, were computed using the direct method based on the world standard population (Doll and Smith, 1982). In a few countries, data were missing for one or more calendar years. No extrapolation was made for missing data.

 

Joinpoint regression analysis was used to identify years where a significant change in the linear slope (on a log scale) of the temporal trend occurred (Chu et al, 1999; Kim et al, 2000). This analysis chooses the best fitting point(s) (called joinpoint(s)) at which the trend changes significantly. The analysis starts with the assumption of constant change in rate over time (i.e., no joinpoint, which is a straight line, on a log scale), and then tests whether one or more joinpoints (up to 3) are significant and must be added to the model. In the final model each joinpoint (if any) informs of a significant change in trend (including both changes in direction or in the rate of increase/decrease). The estimated annual percent change (APC) is then computed for each of the identified trends by fitting a regression line to the natural logarithm of the rates using calendar year as a regressor variable. In the graphs, lines are used to represent the predicted trend in the joinpoint analysis, and symbols to represent the observed rates. Joinpoint regression models are performed using the “Joinpointsoftware from the Surveillance Research Program of the US National Cancer Institute (National Cancer Institute, 2005).

Alcohol consumption data (litres of ethanol per year) for selected countries were derived from the WHO (WHO Statistical Information System, 2006a).