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Objectives@#The coronavirus disease 2019 (COVID-19) pandemic led to increased mortality rates. To assess this impact, this ecological study aimed to estimate the excess death counts in southern Iran. @*Methods@#The study obtained weekly death counts by linking the National Death Registry and Medical Care Monitoring Center repositories. The P-score was initially estimated using a simple method that involved calculating the difference between the observed and expected death counts. The interrupted time series analysis was then used to calculate the mean relative risk (RR) of death during the first year of the pandemic. @*Results@#Our study found that there were 5571 excess deaths from all causes (P-score=33.29%) during the first year of the COVID-19 pandemic, with 48.03% of these deaths directly related to COVID-19. The pandemic was found to increase the risk of death from all causes (RR, 1.26; 95% confidence interval [CI], 1.19 to 1.33), as well as in specific age groups such as those aged 35-49 (RR, 1.21; 95% CI, 1.12 to 1.32), 50-64 (RR, 1.38; 95% CI, 1.28 to 1.49), and ≥65 (RR, 1.29; 95% CI, 1.12 to 1.32) years old. Furthermore, there was an increased risk of death from cardiovascular diseases (RR, 1.17; 95% CI, 1.11 to 1.22). @*Conclusions@#There was a 26% increase in the death count in southern Iran during the COVID-19 pandemic. More than half of these excess deaths were not directly related to COVID-19, but rather other causes, with cardiovascular diseases being a major contributor.
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Background:Despite progress in the health indexes in recent years, health inequalities remain as a global challenge within and between regions and countries. This study is the first to quantify the socioeconomic inequity in gastroesophageal reflux disease [GERD] using the concentration index
Methods: In this cross-sectional study, we used baseline data [7012 subjects] from the Fasa Cohort Study [the Southern Iran]. The principal component analysis was used to construct socioeconomic status of the participants. The concentration index and concentration curve were used to measure socioeconomic- related inequality in GERD. Decomposition of concentration index was also done to identify the contribution of each explanatory variable to the wealth-related inequality in GERD prevalence
Results: The prevalence of GERD was 16.9% [95% CI: 15.9-17.7%]. The overall concentration index for GERD was 0.093 [95% CI: 0.062-0.166]. Correspondingly, this figure for men and women were 0.116 [95% CI: 0.062-0.171%] and 0.091 [95% CI: 0.044-0.137%], respectively. The main contributors of socioeconomic-related inequality in GERD prevalence were socioeconomic status [64.4%], alcohol drinking [29%], and age [8.4%]
Conclusion: GERD is significantly more concentrated among richest people. There was significant socioeconomic inequality in GERD according to some individual factors. These inequalities need to be addressed by policy makers to identify the vulnerable subgroups and to reduce the disease burden in the community
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OBJECTIVE@#To predict the trend of cutaneous leishmaniasis and assess the relationship between the disease trend and weather variables in south of Fars province using Seasonal Autoregressive Integrated Moving Average (SARIMA) model.@*METHODS@#The trend of cutaneous leishmaniasis was predicted using Mini tab software and SARIMA model. Besides, information about the disease and weather conditions was collected monthly based on time series design during January 2010 to March 2016. Moreover, various SARIMA models were assessed and the best one was selected. Then, the model's fitness was evaluated based on normality of the residuals' distribution, correspondence between the fitted and real amounts, and calculation of Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC).@*RESULTS@#The study results indicated that SARIMA model (4,1,4)(0,1,0) in general and SARIMA model (4,1,4)(0,1,1) in below and above 15 years age groups could appropriately predict the disease trend in the study area. Moreover, temperature with a three-month delay (lag3) increased the disease trend, rainfall with a four-month delay (lag4) decreased the disease trend, and rainfall with a nine-month delay (lag9) increased the disease trend.@*CONCLUSIONS@#Based on the results, leishmaniasis follows a descending trend in the study area in case drought condition continues, SARIMA models can suitably measure the disease trend, and the disease follows a seasonal trend.
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Objective To predict the trend of cutaneous leishmaniasis and assess the relationship between the disease trend and weather variables in south of Fars province using Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Methods The trend of cutaneous leishmaniasis was predicted using Mini tab software and SARIMA model. Besides, information about the disease and weather conditions was collected monthly based on time series design during January 2010 to March 2016. Moreover, various SARIMA models were assessed and the best one was selected. Then, the model's fitness was evaluated based on normality of the residuals’ distribution, correspondence between the fitted and real amounts, and calculation of Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC). Results The study results indicated that SARIMA model (4,1,4)(0,1,0)
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OBJECTIVES: The survival rate of thalassemia patients has not been conclusively established, and the factors associated with survival remain unclear. This study aimed to determine the survival rate of thalassemia among patients in southern Iran and to identify the factors associated with mortality from thalassemia. METHODS: This retrospective cohort study was conducted based on a retrospective review of the medical records of 911 beta-thalassemia patients in 2014. Data analysis was conducted using the Kaplan-Meier method and Cox regression analysis. RESULTS: Overall, 212 patients (23.3%) died, and 26.8% had thalassemia intermedia. The 20-year, 40-year, and 60-year survival rates were 85%, 63%, and 54%, respectively. Both crude and adjusted analyses found that education, marital status, ferritin levels, and comorbidities were related to mortality. CONCLUSIONS: Sociodemographic and hematological factors were found to be significantly associated with the survival rate of thalassemia. Addressing these factors may help healthcare providers and physicians to provide the best possible care and to improve the survival rate.