Epidemiology and trend of stomach cancer mortality in Iran

Background and aims: Stomach cancer is one of the most common cancers and the second cause of deaths among cancers worldwide cancer in the world. This study aimed to estimate the rate and trend of death from stomach cancer in Iranian population between 2006 and 2010. Methods: This study was a cross-sectional conducted using mortality data in Iranian population between 2006 and 2010. The number of deaths, death rate, and sex ratio of mortality, mortality rates by age and gender groups, and trends of mortality from stomach cancer were calculated and reported. Cochrane Armitage test was used for linear trend by Winpepi software to study the trends of Stomach cancer mortality. Results: The results showed that between 2006 and 2010, 34950 cases of death have been reported from stomach cancer. The mortality rate per 100,000 reached from 11.22 in 2006 to 11.06 in 2010. All years studied indicated that death due to stomach cancer were higher in males than females. Also, with increasing age, the mortality rate of stomach cancer was increased. Conclusion: Our findings showed the decreasing trend of mortality due to stomach cancer may be due to increasing in lifespan and survival, enjoying the better diagnostic and therapeutic procedures for patients, and underestimation of the number of stomach cancer deaths. Since the cancer is the most frequent cause of death among cancers in Iran, additional investigation is necessary to determine the risk factors of the cancer to decline the mortality rate

Epidemiology and trends in mortality from liver cancer in Iran

Review: Background: Liver cancer is the sixth most common cancer and the third leading cause of cancer is. The true prevalence of infection in cancer remains unknown But the incidence of these cancers in 1.7 of all cases of cancer. The aim of this study was to examine the changes of liver cancer mortality in the population during the years 2006 to 2010. Materials and Methods: In this study, the reported data were used for the face of death in the country. After the initial planning of this study, data were collected during cancer-related deaths and entered into a pre-designed form. Results: The results of the calculation of mortality rates per hundred thousand people showed the death rate from cancer has increased from 4.78 to 5.37. The mortality rates in all years of the study show Liver cancer in men is higher than women with increasing age, the death rate from this cancer also increases. Discussion and conclusions: According to the research of liver cancer is on the rise and liver cancer screening in low therefore recommended that in patients with hepatitis B, liver cancer screening is to detect cases. Key words: Liver, cancer, the mortality , Iran

Trend of bladder cancer mortality in Iran (2006 to 2010)

Abstract Introduction: Bladder cancer is the most common tumor of the urinary tract and the ninth cancer in terms of incidence in both sexes in the world. Bladder cancer is the second most common cancer in men in Iran. This study aimed to investigate the trend of death from bladder cancer in Iran. Materials and Methods: This study was conducted by the use of data on mortality in Iran during 2006-10. Data on mortality from cancer within the study period were collected and entered on a pre-designed form. Mortality rates per 105 persons were calculated by age group and sex, and the trend of mortality from this cancer was determined. Results: The results from the calculation of mortality rates per 105 persons indicated that the death rate from bladder cancer is reduced from 1.12 to 1.09. The mortality rates during all the years under study showed that increasing age increases bladder cancer in men. Discussion: No particular change was observed in the analysis of the trend of tobacco use in Iran in the last two decades, which can be considered as one of the causes of constancy of mortality trend from bladder cancer. However, given the increase in the number of people over 65 and the observed growing trend in bladder cancer incidence in various regions of the country, it is recommended that health policies are adopted in order to prevent risk factors behind this type of cancer such as tobacco and harmful industrial materials

Identification of Risk Factors Associated with Tuberculosis in Southwest Iran: A Machine Learning Method

BackgroundTuberculosis is a principal public health issue. Reducing and controlling tuberculosis did not result in the expected success despite implementing effective preventive and therapeutic programs, one of the reasons for which is the delay in definitive diagnosis. Therefore, creating a diagnostic aid system for tuberculosis screening can help in the early diagnosis of this disease. This research aims to use machine learning techniques to identify economic, social, and environmental factors affecting tuberculosis.MethodsThis case-control study included 80 individuals with TB and 172 participants as controls. During January-October 2021, information was collected from thirty-six health centers in Ahvaz, southwest Iran. Five different machine learning approaches were used to identify factors associated with TB, including BMI, sex, age , marital status, education, employment status, size of the family, monthly income, cigarette smoking, hookah smoking, history of chronic illness, history of imprisonment, history of hospital admission, first-class family, second-class family, third-class family, friend, co-worker, neighbor, market, store, hospital, health center, workplace, restaurant, park, mosque, Basij base, Hairdressers and school. The data was analyzed using the statistical programming R software version 4.1.1.ResultsAccording to the calculated evaluation criteria, the accuracy level of 5 SVM, RF, LSSVM, KNN, and NB models is 0.99, 0.72, 0.97,0.99, and 0.95, respectively, and except for RF, the other models had the highest accuracy. Among the 39 investigated variables, 16 factors including First-class family (20.83%), friend (17.01%), health center (41.67%), hospital (24.74%), store (18.49%), market (14.32%), workplace (9.46%), history of hospital admission (51.82%), BMI (43.75%), sex (40.36%), age (22.83%), educational status (60.59%), employment status (43.58%), monthly income (63.80%), addiction (44.10%), history of imprisonment (38.19%) were of the highest importance on tuberculosis.ConclusionThe obtained results demonstrated that machine-learning techniques are effective in identifying economic, social, and environmental factors associated with tuberculosis. Identifying these different factors plays a significant role in preventing and performing appropriate and timely interventions to control this disease