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Showing 3 results for Holakouie-Naieni

Seyed Mohammad Mojtahedzadeh, Kourosh Holakouie-Naieni, Shahrzad Nematollahi, Amir Hossein Mazarei,
Volume 15, Issue 1 (6-2017)
Abstract

Background and Aim: Considering the protection of, and safeguarding, the health of industrial workforce, this study was conducted to determine the prevalence of overweight and obesity in the personnel of Abadan oil refinery in the south-west of Iran and factors related to it.

Materials and Methods: The study included 721 oil refinery staff members randomly selected based on the yearly occupational health examination records. The information recorded included anthropometric measurements and blood test results; in addition, Breslow lifestyle and Global Physical Activity (GPAQ) questionnaires were completed for each subject.

Results: The mean body mass index (BMI) was 28.2 for men and 27.5 for women. The prevalence of obesity and overweight were 29.8% and 48.7%, respectively. Further analysis of the data showed that the prevalence rates were different between men and women; while 48.6% and 30.24% of the men suffered from overweight and obesity, respectively, the corresponding proportions among women were 50% and 15%. Overweight and obesity were associated with age, fasting blood glucose level, lipid profile and hypertension (in all cases    p < 0.001).

Conclusion: The prevalence of overweight and obesity among Abadan oil refinery staff is higher as compared to the mean values in the general population in Iran or to personnel of other industries globally. Development and implementation of public educational programs with particular emphasis on high-risk individuals, such as middle-aged people and those with a low socioeconomic status, and focusing on healthy lifestyle and rotation shift workers can be effective, resulting in improvements in physical and general health of the personnel.


Kourosh Holakouie-Naieni, Mohammad Ali Mansournia, Shahrzad Nematollahi, Mahin Nomali, Mehdi Haresabadi, Mohammad Isaq Mohammadi, Tanaz Valadbeigi,
Volume 19, Issue 3 (3-2022)
Abstract

Background and Aim: The aim of this study was to determine the risk factors of growth failure of one-year old children in the suburban regions of Bandar-e-Abbas City based on a population-based cohort study conducted by Bandar Abbas Health Research Station, affiliated to School of Public Health, Tehran University of Medical Sciences in the south of Iran.
Materials and Methods: In this prospective cohort study in 2021, data on the growth of 540 one-year old infants obtained in a cohort study aiming to identify contributors to mother and child health in the suburbs of Bandar-e-Abbas City, Iran were used. The outcomes included weight, height, and head circumference growth failures among one-year infants. Data analysis was performed using the STATA software version 14, the statistical tests being descriptive statistics and univariate and multiple logistic regressions.
Results: Low birth weight was found to increase the odds of one-year-old children’s weight growth failure 3.05 times (the adjusted odds ratio, OR = 3.05; 95% CI: 8.91-1.04). A low socioeconomic status reduced the odds of head circumference growth failure 59% (the adjusted OR = 0.41; 95% CI: 0.19-0.89), and a low birth weight increased the odds of head circumference growth failure 2.46 times (adjusted OR = 2.46; 95% CI: 1.01-5.97). None of the maternal and childhood factors were related to the one-year-old child height growth failure.
Conclusion: The findings of this study show that low birth weight increases the odds of normal body growth and head circumference growth failures at the age on one year, while a low socioeconomic status reduces the odds of head circumference growth failure. There are no relations between any of the maternal and childhood factors and height growth failure at the age of one year.
 
Maryam Nouravaran Feizabadi, Kourosh Kourosh Holakouie-Naieni , Abbas Rahimi Foroushani, Ali Taghipour,
Volume 19, Issue 4 (3-2022)
Abstract

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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