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Journal Article

Citation

Igissinov N, Aubakirova A, Orazova G, Akpolatova G, Urazova S, Tarzhanova D, Zhantureyeva A, Kuandykov Y. Iran. J. Public Health 2020; 49(1): 68-76.

Affiliation

Department of Family Medicine, South Kazakhstan Medical Academy, Shymkent, Kazakhstan.

Copyright

(Copyright © 2020, Tehran University of Medical Sciences)

DOI

unavailable

PMID

32309225

PMCID

PMC7152637

Abstract

BACKGROUND: As a result of the road traffic accidents 1.25 mln. of working-age people die each year on the roads. Frequency of the RTA is 11 times higher in our country than in Europe, that influence on demographic and economic situation in the republic. Creation of the math modeling and prediction of traffic mortality rate in Kazakhstan will allow to develop measure on its decrease.

METHODS: Short-term dotted prediction of population mortality level of Kazakhstan was used, in particular - methods of regressive analysis. General prognosis throughout the country up to 2021 was made on the basis of data for 1999-2018. The more relevant method for prediction is exponential function taking into account the features of mortality rate level trend.

RESULTS: Prediction of traffic fatalities without division into the age-related groups for 2019 is 2132±181 case with a probability 2/3. Expected levels for 2020-2027 cases, for 2021-1927 cases.Annual mortality decrease rate according to the 0-19 age-related at an average is 6.4% among men and 5.8% among women, according to age group as a whole - by 6.2%; from 20 up to 64 age related group - 5.1 % on all population category; older 65 age -group is by 2.2 %, 3.7 % among men, 2.9% among women as a whole.

CONCLUSION: In the foreseeable future the number of traffic deaths in Kazakhstan will tend to decrease at a slower pace. Mortality rates due to road traffic accidents among working-age men will be 3 times higher than women in this age group.

Copyright© Iranian Public Health Association & Tehran University of Medical Sciences.


Language: en

Keywords

Kazakhstan; Mortality; Prediction; Road-traffic accidents

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