Factors associated with patients' mobility rates within the provinces of Iran.

BACKGROUND: The absence of a referral system and patients' freedom to choose among service providers in Iran have led to increased patient mobility, which continues to concern health policymakers in the country. This study aimed to determine factors associated with patient mobility rates within the provinces of Iran. METHODS: This cross-sectional study was conducted in Iran. Data on the place of residence of patients admitted to Iranian public hospitals were collected during August 2017 to determine the status of patient mobility within each province. The sample size were 537,786 patients were hospitalized in public hospitals in Iran during August 2017. The patient mobility ratio was calculated for each of Iran's provinces by producing a patient mobility matrix. Then, a model of factors affecting patient mobility was identified by regression analysis. All the analyses were performed using STATA14 software. RESULTS: In the study period, 585,681 patients were admitted to public hospitals in Iran, of which 69,692 patients were referred to the hospital from another city and 51,789 of them were admitted to public hospitals in the capital of the province. The highest levels of intra-provincial patient mobility were attributed to southern and eastern provinces, and the lowest levels were observed in the north and west of Iran. Implementation of negative binomial regression indicated that, among the examined parameters, the distribution of specialist physicians and the human development index had the highest impact on intra-provincial patient mobility. CONCLUSION: The distribution of specialists throughout different country areas plays a determining role in patient mobility. In many cases, redistributing hospital beds is impossible, but adopting different human resource policies could prevent unnecessary patient mobility through equitable redistribution of specialists among different cities.

A Cluster-wise Linear Regression Model to Investigate the Effect of Demographical and Clinical Variables on the Average Depression Score.

Background: Depression is a prevalent illness in the world. Given the importance of mental disorders, many researchers have investigated the effects of different variables on average depression scores. In this study, we decided to investigate the effect of some explanatory variables on the average depression score. Methods: The data were provided from the second phase of the Kerman Coronary Artery Diseases Risk Factors study (KERCADRS), which took place between 2014 and 2018. To obtain more precise connections between depression ratings and predictor variables, we employed a cluster-wise linear regression model. Results: The total number of the participants in this study was 9811, out of whom 2144 were allocated to cluster 1, 4540 to cluster 2, and 3127 to cluster 3. The average depression score was 13.76 ± 7.6 in cluster 1, 4.39 ± 4.7 in cluster 2, and 10.83 ± 6.7 in cluster 3. However, the average depression score for all the data was 8.5 ± 7.2. In all the clusters, the average depression score of females was significantly greater than that of men (P < 0.001). In cluster 1, the age category of 35-54 years, in cluster 2, the age category of 55-80 years, and in cluster 3, the age category of 15-34 years had a maximum average depression score. Conclusion: We may classify the 3 clusters as having a low (cluster 2), moderate (cluster 3), or high (cluster 1) depression score, according to the age group with the highest artery diseases risk. The patients were 55-80 years, 15-34 years, and 35-54 years in cluster 2 (low), cluster 3 (moderate), and cluster 1 (high), respectively.

The Prevalence and 5-Year Incidence Rate of Cigarette Smoking and Water-Pipe Tobacco Smoking and Their Associated Factors among 15 to 80 Years Old Urban Population in Southeast Iran: Results from KERCADR Study.

Background: Cigarette and tobacco smoking are closely associated with chronic cardiovascular disease and lung cancer. We aimed to assess the prevalence and 5-year incidence rate (IR) of these two risk factors for cardiovascular diseases in Kerman, southeastern of Iran. Methods: 10015 individuals aged 15-80 were recruited to the study between 2014 and 2018 (Kerman coronary artery disease (CAD) risk factors study, KERCADRS) of which 2820 had also participated in the first phase (5 years earlier). We took fasting blood samples and collected demographic information and data on cigarette and water-pipe tobacco smoking (WPTS) through interviews. Findings: The overall prevalence of cigarette smoking increased from 8.1% in phase1 to 8.8% in phase 2. During the same period, the prevalence of WPTS increased from 10% to 14%, especially in the age groups of 15-45 years. The prevalence of opium dependance was higher among cigarette smokers compared to WPT users. The overall 5-year IR of cigarette and WPTS was 3.6 and 4.65 per 1000 person-years respectively. The highest IRs of cigarette smoking and WPTS were reported in the age group of 15-39 years, and IR of WPTS was higher among women. Obesity, diabetes, and hypertension associated with a reduced IRs of cigarette and WPTS. Conclusion: Over the past five years, the prevalence of cigarette smoking has increased slightly, but WPTS has increased more rapidly, especially among women. The highest prevalence of cigarette and WPT smoking was in the age groups of 15-39 years. Smoking is shifting from cigarette smoking to WPTS. Age- and gender-oriented interventions would help correct the unhealthy life style in the community and prevent further smoking-related morbidities and mortalities.