Journal of School of Public Health and

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Background and Aim: Cardiovascular diseases (CVDs) are a major cause of death worldwide. The objective of this study was to determine the most important behavioral (inadequate nutrition, low physical activity, smoking and alcohol consumption) and non-behavioral (stress, high blood sugar, dyslipidemia, hypertension and obesity) risk factors for CVD among CVD patients hospitalized in Kermanshah Heart Hospital. This was a needs assessment study aiming at designing interventions for reducing CVD risk factors.
Materials and Methods: In this cross-sectional study 402 CAD patients (60.4% males and 39.6% females) were selected by consecutive sampling from among those hospitalized in Imam Ali Hospital for the first time. Data were collected using the Iranian version of WHO Stepwise questionnaire and the patients’ files and analyzed using the SPSS-16 software.
Results: The mean (±SD) age of the patients was 54.2 (±8.8) years. About 73% of them had a poor diet and 46.5% had low physical activity; in addition, 36% of the men had consumed alcohol in the previous year and 26.1% were smokers. Non-behavioral risk factors were quite common too. The proportions of the patients suffering from diabetes, hypertension and overweight-plus-obesity and abdominal obesity were 49.3%, 48.0%, 54.7% and 61.0%, respectively. Finally, 43.3% of the patients had high stress, 31.0% were hypertriglyceridemic and in another 21% hypercholesterolemia was seen.
Conclusion: Based on the findings it can be concluded that, as compared to other risk factors, imbalanced nutrition was more prevalent common among the patients. Another major risk factor was obesity, particularly abdominal obesity. In addition, blood glucose disorders were more common than dyslipidemia.
 

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Background and Aim: Cardiovascular diseases (CVD) are the leading cause of death globally, causing annually 17.3 million deaths, more than 75% of these deaths occurring in the low- and middle-income countries. Although extensive studies have been conducted to determine the risk factors for these diseases, limited studies have been performed to investigate these factors using a multilevel analysis method. The aim of this study was to determine the CVD risk factors in the staff of Mashhad University of Medical Sciences using a multilevel analysis approach, as well as compare the application of the conventional and multilevel logistic regressions in doing this according to the hierarchical structure of the data.
Materials and Methods: This was a case-control study including a total of 1091 randomly selected individuals from among the people in a prospective cohort study, namely, the “PERSIAN Cohort Study in Mashhad University of Medical Sciences” in 2018.  The case group included 152 patients with a definite diagnosis of CVD and the control group 939 staff members not suffering at the time from CVD. Data analysis was done using the STATA software. Data analysis (based on frequencies and percentages) was done using one-way and two-level logistic regression analysis at α = 0.05.
Results: Multivariate analysis showed that hypertension, smoking, fasting blood sugar and cholesterol were among the cardiovascular risk factors with a significant relationship with the disease. Based on the two-tier logistic regression model, the odds ratio for CVD in the hypertensive patients was 3.93 times that in individuals with a normal blood pressure with a confidence interval of 2.64-6.28. The risk in smokers was 1.85 (1.11-3.09) times that in nonsmokers. The CVD odds ratio in individuals with a high fasting blood glucose level (undiagnosed/uncontrolled diabetes) was 2.7 (1.18-6.18) times that in those with a normal blood pressure. There were no statistically differences between the case and control groups as regards the other variables ─ body mass index, diabetes (controlled or uncontrolled), or blood triglyceride level.
Conclusion: The findings show that statistical model selection can influence the results of data analysis in a dataset. It should be noted that the results of this study indicate a high prevalence of some cardiovascular risk factors among the staff. Another crucial point in this study is that the level of physical activity of the staff was found to be low, which would result in increased risk of overweight and obesity.
 

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Background and Aim: Air pollution has been widely established as an important risk factor for heart and respiratory diseases and mortality. The aim of this study was to compare the relationships between short-term exposure to air pollutants and hospital admissions, cardiovascular and respiratory deaths and total deaths in Ahvaz and Shahrekord, Iran.
 Materials and Methods: In this ecological and time-series study data were collected on hospital admissions, cardiovascular and respiratory deaths and total deaths between 2012 and 2018. For data analysis Quasi-Poisson regression combined with linear distributed lag models were used and adjusted for trend, seasonality, temperature, relative humidity, weekdays and holidays.
Results: Data analysis showed that in Ahvaz there were statistically significant direct correlations between PM₁₀ exposure and respiratory admissions, PM_2.5 exposure and total deaths and cardiovascular admissions, O₃ exposure and total deaths, and CO exposure and cardiovascular admissions. As regards Shahrekord, there were statistically significant direct correlations between PM₁₀ exposure and respiratory deaths, PM₁₀ exposure and cardiovascular deaths, PM_2.5 exposure and cardiovascular and respiratory admissions and respiratory deaths, O₃ exposure and total deaths, and CO exposure and respiratory deaths.
Conclusion: It seems there are statistically significant relationships between air pollution and hospital admissions and deaths in Ahvaz and, to a lesser extent, in Shahrekord.