Limits...
Sex differential in mortality trends of old-aged Danes: a nation wide study of age, period and cohort effects.

Jacobsen R, Oksuzyan A, Engberg H, Jeune B, Vaupel JW, Christensen K - Eur. J. Epidemiol. (2008)

Bottom Line: Here we investigate whether this mortality pattern is mainly explained by period effects, cohort effects or both.The observed rates were better described by the age, period and cohort model than by other models.Cohort effects on the mortality of the oldest Danish women and men played a significant but minor role compared to period effects.

View Article: PubMed Central - PubMed

Affiliation: Institute of Public Health, Epidemiology, University of Southern Denmark, Odense C, Denmark. rjacobsen@health.sdu.dk

ABSTRACT

Objective: Over the last half century the mortality rates in Denmark for females above age 80 have declined dramatically whereas the decline for males have been modest, resulting in a change in sex-ratio for centenarians from 2 to 5. Here we investigate whether this mortality pattern is mainly explained by period effects, cohort effects or both. This can provide clues for where to search for causes behind the changes in sex differential in mortality seen in many Western countries during the last decades.

Methods: Age-period-cohort study of mortality for all Danish women and men aged 79-98 during the period 1949-2006.

Outcome measures: Relative risks for deaths and second order differences for exploration of the nonlinear variation.

Results: Both the overall trends in mortality differences and the fluctuations in mortality for both men and women were better explained by period effects than by cohort effects. The observed rates were better described by the age, period and cohort model than by other models.

Conclusions: Our results suggest that causes for both the overall increased difference in mortality and the short term fluctuations in mortality rates are primarily to be found in the period dimension. Cohort effects on the mortality of the oldest Danish women and men played a significant but minor role compared to period effects.

Show MeSH

Related in: MedlinePlus

Model selection scheme used in this study. The pure age model is compared with the age-drift model to test for linear components. The age-drift is compared with the age-period and age-cohort to test for irregularities attributable to cohort and period, respectively. If none of these models describe the data well, the age-period-cohort model should be tried
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2749933&req=5

Fig1: Model selection scheme used in this study. The pure age model is compared with the age-drift model to test for linear components. The age-drift is compared with the age-period and age-cohort to test for irregularities attributable to cohort and period, respectively. If none of these models describe the data well, the age-period-cohort model should be tried

Mentions: In order to select an appropriate model for the description of the observed mortality rates, a similar approach as the scheme given by Clayton and Schifflers [37, 38] was used (Fig. 1). In the pure age model, no temporal change is present (i.e. no change in mortality neither over time nor for specific generations). In the age-period model, the age-specific logarithms of the mortality rates are increased (or decreased) from one period to the other by the same quantity regardless of age. This is for example the case when a new exposure enters at some calendar time and exerts the same effect over all ages. When exposures are clustered by generation, then on a logarithmic scale the age-specific differences in mortality between any pair of cohorts are approximately constant for all ages, and the age-cohort model is expected to give the best fit. In the special case where the data are equally well described by an age-period or an age-cohort model, the age-drift model is used, where the drift is an effect that cannot be distinguished between period and cohort. When the age-period and the age-cohort models do not describe the data well, then the age-period-cohort model should be tried [37].Fig. 1


Sex differential in mortality trends of old-aged Danes: a nation wide study of age, period and cohort effects.

Jacobsen R, Oksuzyan A, Engberg H, Jeune B, Vaupel JW, Christensen K - Eur. J. Epidemiol. (2008)

Model selection scheme used in this study. The pure age model is compared with the age-drift model to test for linear components. The age-drift is compared with the age-period and age-cohort to test for irregularities attributable to cohort and period, respectively. If none of these models describe the data well, the age-period-cohort model should be tried
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2749933&req=5

Fig1: Model selection scheme used in this study. The pure age model is compared with the age-drift model to test for linear components. The age-drift is compared with the age-period and age-cohort to test for irregularities attributable to cohort and period, respectively. If none of these models describe the data well, the age-period-cohort model should be tried
Mentions: In order to select an appropriate model for the description of the observed mortality rates, a similar approach as the scheme given by Clayton and Schifflers [37, 38] was used (Fig. 1). In the pure age model, no temporal change is present (i.e. no change in mortality neither over time nor for specific generations). In the age-period model, the age-specific logarithms of the mortality rates are increased (or decreased) from one period to the other by the same quantity regardless of age. This is for example the case when a new exposure enters at some calendar time and exerts the same effect over all ages. When exposures are clustered by generation, then on a logarithmic scale the age-specific differences in mortality between any pair of cohorts are approximately constant for all ages, and the age-cohort model is expected to give the best fit. In the special case where the data are equally well described by an age-period or an age-cohort model, the age-drift model is used, where the drift is an effect that cannot be distinguished between period and cohort. When the age-period and the age-cohort models do not describe the data well, then the age-period-cohort model should be tried [37].Fig. 1

Bottom Line: Here we investigate whether this mortality pattern is mainly explained by period effects, cohort effects or both.The observed rates were better described by the age, period and cohort model than by other models.Cohort effects on the mortality of the oldest Danish women and men played a significant but minor role compared to period effects.

View Article: PubMed Central - PubMed

Affiliation: Institute of Public Health, Epidemiology, University of Southern Denmark, Odense C, Denmark. rjacobsen@health.sdu.dk

ABSTRACT

Objective: Over the last half century the mortality rates in Denmark for females above age 80 have declined dramatically whereas the decline for males have been modest, resulting in a change in sex-ratio for centenarians from 2 to 5. Here we investigate whether this mortality pattern is mainly explained by period effects, cohort effects or both. This can provide clues for where to search for causes behind the changes in sex differential in mortality seen in many Western countries during the last decades.

Methods: Age-period-cohort study of mortality for all Danish women and men aged 79-98 during the period 1949-2006.

Outcome measures: Relative risks for deaths and second order differences for exploration of the nonlinear variation.

Results: Both the overall trends in mortality differences and the fluctuations in mortality for both men and women were better explained by period effects than by cohort effects. The observed rates were better described by the age, period and cohort model than by other models.

Conclusions: Our results suggest that causes for both the overall increased difference in mortality and the short term fluctuations in mortality rates are primarily to be found in the period dimension. Cohort effects on the mortality of the oldest Danish women and men played a significant but minor role compared to period effects.

Show MeSH
Related in: MedlinePlus