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Mortality trends in systemic sclerosis in France and USA, 1980–1998: an age-period-cohort analysis

  • Epidemiology of Rheumatic Diseases
  • Published:
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Abstract

We compared trends of Systemic Sclerosis (SS) mortality in France and the USA over the period 1980–1998 and used an Age-Period-Cohort (APC) model to adjust on the age at death of SS patients. All deaths coded with SS as an underlying primary or secondary cause in the national French and US mortality databases from 1980 to 1998 were included in the analysis. SS age-standardized mortality rates increased from 7.2 to 10.3/million in US women (+43%), and from 3 to 3.9/million in French women (+22%). Most of the increase occurred in senior women. In contrast, SS age-standardized death rates remained stable among US men (around 3/million) and French men (around 2/million). In US women, the APC analysis shows a growing cohort effect between 1900 and 1940, tending to stabilize for following cohorts. Similar findings were obtained to a lesser extent in French women. In conclusion, SS mortality rates increased by more than 40% between 1980 and 1998 in the USA, mostly in women born between 1900 and 1940. Whether these trends reflect rising incidence of SS need to be documented. The observed dissimilarity between genders and countries underline that environmental exposure and gender-related factors likely play a major etiological role. Stabilization in the following birth cohorts suggests that the increase of mortality observed since 1980 may slow down in the near future.

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Abbreviations

AIC:

Akaike’s information criterion

APC:

Age-period-cohort

Δ Dev:

Difference of deviance

INSEE:

Institut National de la Statistique et des Etudes Economiques

NCHS:

National center for health statistics

SS:

Systemic sclerosis

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No funding was obtained for this study.

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Correspondence to Solen Kernéis.

Appendix

Appendix

A general formulation for the APC model for death rates λ(a,p) at age a in period p for persons in birth cohort (c = p−a) is:

$$ {\text{Log}}\left[ {\lambda ({\text{a}},{\text{p}})} \right] = {\text{f}}({\text{a}}) + {\text{g}}({\text{p}}) + {\text{h}}({\text{c}}). $$

We fit the model by Poisson regression, using the total number of person-years for each age-period combination with an offset term [15]. Year 1940 was taken as the reference to calculate Rate Ratios for each period and cohort. We restricted our analyses to ages 30–90 because of too few events in the extreme age groups.

We used the model-building procedure proposed by Clayton and Schifflers [13, 14]. Therefore, the following models were fitted to the data:

  • Model 1: Age

  • Model 2: Age-Drift

  • Model 3: Age-Period

  • Model 4: Age-Cohort

  • Model 5: Age-Period-Cohort

The drift parameter (model 2) fits a simple linear trend in incidence with time, without period or cohort effects. It may be expressed as a percentage change in incidence per year.

Comparing the age alone-model (model 1) to the other four models on both deviance and Akaike’s information criterion (AIC). Deviances were compared by computing the likelihood ratio test. As models 1–5 are not nested within each other, we also calculated AIC which penalizes the fit of models according to the number of parameters estimated from the data. A significant difference of deviance (Δ Dev) and a low AIC indicate a good fit of the model.

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Kernéis, S., Boëlle, PY., Grais, R.F. et al. Mortality trends in systemic sclerosis in France and USA, 1980–1998: an age-period-cohort analysis. Eur J Epidemiol 25, 55–61 (2010). https://doi.org/10.1007/s10654-009-9403-2

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  • DOI: https://doi.org/10.1007/s10654-009-9403-2

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