(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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The prediction incidence of the three most common cancers among Iranian military community during 2007-2019a time series analysis..pdf Download (983kB) |
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 |
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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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