Given the alarming prevalence of waterpipe smoking, preventive measures should be adopted among university students taking into account the influence of peers, siblings and parents in the lessening social tolerance of waterpipe smoking.

BackgroundSeveral case-control studies have shown associations between the risk of different cancers and self-reported opium use. Inquiring into relatively sensitive issues, such as the history of drug use, is usually prone to information bias. However, in order to justify the findings of these types of studies, we have to quantify the level of such a negative bias. In current study, we aimed to evaluate sensitivity of self-reported opioid use and suggest suitable types of control groups for case-control studies on opioid use and the risk of cancer.MethodsIn order to compare the validity of the self-reported opioid use, we cross-validated the response of two groups of subjects 1) 178 hospitalized patients and 2) 186 healthy individuals with the results of their tests using urine rapid drug screen (URDS) and thin layer chromatography (TLC). The questioners were asked by trained interviewers to maximize the validity of responses; healthy individuals were selected from the companions of patients in hospitals.ResultsSelf-reported regular opioid use was 36.5% in hospitalized patients 19.3% in healthy individuals (p-value> 0.001).The reported frequencies of opioid use in the past 72 hours were 21.4% and 11.8% in hospitalized patients and healthy individuals respectively. Comparing their responses with the results of urine tests showed a sensitivity of 77% and 69% among hospitalized patients and healthy individuals for self-reports (p-value = 0.4). Having corrected based on the mentioned sensitivities; the frequency of opioid regular use was 47% and 28% in hospitalized patients and healthy individuals, respectively. Regular opioid use among hospitalized patients was significantly higher than in healthy individuals (p-value> 0.001).ConclusionOur findings showed that the level of opioid use under-reporting in hospitalized patients and healthy individuals was considerable but comparable. In addition, the frequency of regular opioid use among hospitalized patients was significantly higher than that in the general population. Altogether, it seems that, without corrections for these differences and biases, the results of many studies including case-control studies on opioid use might distort findings substantially.

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Context:Colorectal cancer (CRC) is the third most prevalent cancer worldwide which is less common in the Middle East. It is also the second leading cause of cancer-related mortality and represents a major public health problem in developed countries. Objectives: The present review aimed to explore the differences among the reports on number and age standardized incidences of CRC in both sexes in different areas of Iran to find the incidence trend of this cancer. Data Sources: All the published reports citing the incidence of CRC in Iran were collected by conducting a literature search in international databases. Study Selection: English articles were included where there was a clear definition of the population of patients under study and where the criteria for diagnosing CRC were well described. Data Extraction: One author read each paper and extracted several studies and then the studies suitable for inclusion were reported in three categories. Results: We identified 181 independent studies dating back to 2003; 168 full text articles were assessed for eligibility. However, 136 full text articles were excluded due to different reasons. Finally, 26 studies were suitable for inclusion in the analysis. The highest and lowest (age standardized rates) ASRs were respectively 3.4 and 2.6 in males and 11.42 and 10.56 in females. Time showed a slightly increasing trend in recent years. Conclusions: Although Iran was expected to have a low incidence rate of CRC, recent studies revealed a slightly increasing trend for the incidence rate of CRC. This finding shows the necessity to consider CRC screening as an important issue in health policy priorities.

Background and objectives The present study aimed to investigate the relation between anemia and hemoglobin (Hgb) concentration, physical performance, and cognitive function in a large sample of Iranian elderly population. Methods Data were collected from Bushehr elderly health (BEH) program. A total of 3000 persons aged ≥60 years were selected through multistage random sampling. Hemoglobin values lower than 12 and 13 g/dL were considered as anemia for women and men, respectively. The cognitive function was measured using the Mini-cog test and Category fluency test (CFT), and the physical function was measured using handgrip strength (muscle strength), Relative handgrip strength (RHGS), and 4.57-m usual gait speed. Univariate and adjusted multivariate logistic regression and linear regression with Stata MP (version 15) were run, and a p-value of < 0.05 was used as statistically significant for all analyses. Results Among participants, 7.43% were anemic, and 115 (51.57%) simultaneously had anemia and cognitive disorder. There were significant associations between red blood cell count (RBC), hemoglobin (Hgb), platelet count (PLT), and hematocrit percentage (HCT) with cognitive impairment. Additionally, Hgb concentration was significantly associated with all physical measures (Mean handgrip, Relative handgrip, and usual gait speed) and late recall (mini-cog) among the whole participants. This association remained statistically significant after considering multi-cofounders. In contrast, after stratifying the participants by gender, the association between Hgb concentration and usual gait speed was decreased in both men and women; moreover, Hgb association with cognitive measures (category fluency test and late recall) was no longer significant (all p-values > 0.05). Conclusion There was a cross-sectional and significant association between anemia and functional variables (e.g., Relative and mean handgrip) in Iranian elderly population, whereas Semantic memory, Late recall, and walking were more affected by gender.

Our study emphasized the implementation of preventive measures like education and needle exchange program as harm-reduction strategies. Drop in Centers are important for the management of health problems, including HIV infection and social problems such as crime. Periodic epidemiological studies on DICs are necessary to monitor and modulate the services delivered by these centers.

Medical oxygen is a critical element in the treatment process of COVID-19 patients which its shortage impacts the treatment process adversely. This study aims to apply machine learning (ML) to predict the requirement for oxygen-based treatment for hospitalized COVID-19 patients. In the first phase, demographic information, symptoms, and patient's background were extracted from the databases of two local hospitals in Iran, and preprocessing actions were applied. In the second step, the related features were selected. Lastly, five ML models including logistic regression (LR), random forest (RF), XGBoost, C5.0, and neural networks (NNs) were implemented and compared based on their accuracy and capability. Among the variables related to the patient's background, consuming opium due to the high rate of opium users in Iran was considered in the models. Of the 398 patients included in the study, 112 (28.14%) received oxygen-based treatment. Shortness of breath (71.42%), fever (62.5%), and cough (59.82%) had the highest frequency in patients with oxygen requirements. The most important variables for prediction were shortness of breath, cough, age, and fever. For opioid-addicted patients, in addition to the high mortality rate (23.07%), the rate of oxygen-based treatment was twice as high as non-addicted patients. XGBoost and LR obtained the highest area under the curve with values of 88.7% and 88.3%, respectively. For accuracy, LR and NNs achieved the best and same accuracy (86.42%). This approach provides a tool that accurately predicts the need for oxygen in the treatment process of COVID-19 patients and helps hospital resource management.

Background:The number of HIV cases in Iran is increasing. Knowledge of the changing epidemiology of HIV is fundamental for service planning and prevention activities. This study aims to estimate the number of HIV-infected cases by the capture and recapture method for size estimation.Materials and Methods:From 2002 to 2009, we used three different centers – hospitals, the Voluntary Counseling and Testing (VCT) center, and a central prison in Fars Province for data retrieval. The overlaps between these centers were investigated to determine the true estimate of HIV cases. Finally, interactions were analyzed by a linear logarithm model with STATA version 9 software.Results:We observed 5167 HIV cases. The number of males was ten times more than that of females. The most frequent age range was between 15 and 44 years. The majority of cases (n = 3347) were retrieved from the VCT center. The least number of infected persons were located in the prison and hospitals. The estimated number of cases in Fars Province was 14,925 from 2002 to 2009. The best model consisted of three sources.Conclusion:Covering the system of medicine deputy for registering the number of infected cases with HIV is poor in Iran. Improvements in making arrangements for enhancing the quality of data related to HIV-infected cases are essential for solving this problem and must be on the agenda for medical policymaking.