Iranian Journal of

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Background & Objectives: Changing the pattern of mortality gives important perspective of health determinants. The aim of this study is to detect location and time of mortality pattern change in country using statistical change point method during 1971-2009 Years.
Methods: We assume for years before and after 0 k , t y has a Poisson distribution with means 0 l and 1 l , respectively. We used several methods for estimation change point in real data by assume Poisson model.
Results: Using two simulated and real data analysis showed that the change point has been occurred in year 1993 and this confirmed by all methods.
Conclusion: Our findings have shown that the change pattern of mortality trend in Iran is related to improvement of health indicators and decreasing mortality rate in Iran.

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Background & Objectives: In the analysis of mortality trend in the Iran that is basically a sequences of observations sorted by time, there is a point where the statistical properties of the mortality trend change so that the first k₀ observations have a distribution of F₀ and other n-k₀ observations have a distribution of F₁. The point k₀ is unknown and called the change point. The aim of this paper was to detect the location of the change point and estimate it in the real mortality data of the country.

 

Methods: In this study, X_t indicated the number of mortality in time t (year) and because of the numeric nature of the variable, we considered the Poisson model for the variable X_t.

We assumed in early years (t0), X_t had a Poisson distribution with a mean of ʎ₀ and for later years (t>k₀), X_t had a Poisson distribution with a mean of ʎ₁ .In theory, we used the MIC method, a modification of the SIC method. For detecting more than one change point, we used the binary segmentation process in the mortality trend.

 

Results: The results showed that the change point occurred in 1993 and 1997.

 

Conclusion: The finding of this study showed three periods with different rates in the mortality trend of Iran.