Effects of age,period and cohort on stroke mortality among a middle-aged Lithuanian urban population from 1980 to 2004

Abstract

Aims: The main purpose of this paper was to assess the effect of age, period, and cohort on stroke mortality rates among a Lithuanian urban population aged 25—64 years (1041 men and 724 women) between 1980 and 2004. Methods: Routine stroke mortality data were obtained from official Kaunas region mortality register by codes 430—438 and I60—I69 in the 9th and in the 10th revisions of the International Classifications of Diseases (ICD), respectively. Mortality rates per 100,000 persons for men and women were age-adjusted using the age distribution of the European Standard Population. Age-specific mortality rates were analysed by sex, period, and birth cohort in eight 5-year age groups and five 5-year age groups. Goodness of fit of the Poisson regression models were evaluated using Pearson and Freeman-Tukey residuals. The age-period and age-period-cohort models provided a significantly better fit than a model with the factors ``age'' and ``cohort''. Results: During the study period, mortality rates decreased from 46.8 to 33.0 per 100,000 for men, and from 20.2 to 18.1 per 100,000 for women (average annual decrease of —1.3%, p<0.1 for men, and —1.6%, p<0.03 for women). An age effect was present in both sexes. The definite upward period effect was observed from 1990 to 1994 both among men and women, and was followed by a sharp fall during 2000—4. Cohort and period effects have contained relevant information which partially explained trends in stroke mortality among a 25—64 year-old Lithuanian urban population. Conclusions: During the period of 1980—2004, the mortality trend declined among women only. The period effect contains relevant information for the explanation of increasing mortality rates during 2000—4 among men and women. The Poisson regression models could be applied for the examination and explanation of the different causes of the population mortality.

Keywords

Age age-period-cohort model mortality rates mortality trends sex

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