Repository of Research and Investigative Information

Repository of Research and Investigative Information

Baqiyatallah University of Medical Sciences

The prediction incidence of the three most common cancers among Iranian military community during 2007-2019: a time series analysis

(2019) The prediction incidence of the three most common cancers among Iranian military community during 2007-2019: a time series analysis. J Prev Med Hyg. E256-e261. ISSN 1121-2233

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Official URL: http://www.ncbi.nlm.nih.gov/pubmed/31650063

Abstract

Objective: Cancers are one of the most important public health problems in Iran. Because of the importance of cancers, the purpose of the current study was to the prediction of the future incidence of the most common cancers among Iranian military community (MC) by using the time series analysis during 2007 to 2019. Methods: In the current cross-sectional study, all registered cancers among Iranian MC entered the study. To select the best model of prediction, various methods including autocorrelation function (ACF), partial autocorrelation function (PACF), and Akaike information criterion (AIC) statistics were used. All analysis was performed by using ITSM, stata14, and Excel2010 software. Results: The most prevalent cancers among Iranian MC were breast, prostate, and colon cancers respectively. The time series analysis was shown that the trend of all mentioned cancers in Iranian MC will increase in the coming years. Conclusions: The trend of most prevalent cancers among Iranian MC was increasing but the different factors like the growth of population size and improving the registration system should be regarded.

Item Type: Article
Keywords: Aged Breast Neoplasms/*epidemiology Colorectal Neoplasms/*epidemiology Female Humans Incidence Iran/epidemiology Male Middle Aged Military Family/*statistics & numerical data Military Personnel/*statistics & numerical data Models, Statistical Prostatic Neoplasms/*epidemiology Veterans/*statistics & numerical data Cancer Iranian military community Time series
Divisions:
Page Range: E256-e261
Journal or Publication Title: J Prev Med Hyg
Journal Index: Pubmed
Volume: 60
Number: 3
Identification Number: https://doi.org/10.15167/2421-4248/jpmh2019.60.3.1058
ISSN: 1121-2233
Depositing User: مهندس مهدی شریفی
URI: http://eprints.bmsu.ac.ir/id/eprint/1375

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