Showing 3 results for Holakoui-Naeini
M Ostadghaderi, Aa Hanafi Bojd , Sh Nematollahi, K Holakoui-Naeini ,
Volume 17, Issue 1 (Vol 17,No.1, Spring 2021 2021)
Abstract
Background and Objectives: The incidence of colorectal cancer has increased significantly in Iran in recent decades. The pattern of occurrence varies in different populations. A study was conducted to perform a spatial analysis of colorectal cancer and some of its risk factors in Iran using GIS.
Methods: The data of this descriptive-analytic study included colorectal cancer incidence as a dependent variable and physical activity, Body Mass Index and smoking as independent variables recorded by the Cancer Department, Center for Non-Communicable Diseases Management, the Ministry of Health and Medical Education and the care system for non-communicable disease risk factors according to province and gender in 2009. Data was analyzed using the ArcGIS 10.3 software and spatial correlation analysis, hot spots analysis, and geographic weighted regression model.
Results: The spatial relationship between the disease and some of its risk factors was confirmed by the model of geographical weight regression, according to which the northern and central provinces had the highest risk of colorectal cancer compared to other regions of the country.
Conclusion: The results of this study showed that spatial analysis could be useful in identifying disease patterns, prioritizing the factors affecting it, and controlling the disease through strategic planning and interventions.
K Holakoui-Naeini, Ma Mansournia, Sh Naderian, R Beiranvand, M Bidkhori, Kh Maajani, Sh Nematollahi,
Volume 17, Issue 2 (Vol 17,No.2, Summer 2021 2021)
Abstract
Background and Objectives: Pre-natal mental health problems are major causes of disease burden, especially in lower socio-economic groups of population. The present study used data of a prospective cohort study to estimate the risk of mental health problems, including depression, anxiety, and stress, on birth weight.
Materials and Methods: This study used data of 398 pregnant women who were participants of the Bandar Abbas Pregnancy Cohort Study (BAPC) during 2017-2020. Data of depression, anxiety, and stress were collected using DASS-21items questionnaire in pregnancy. Low Birth Weight (LBW), as birthwieght below 2500 grams, was calculated according to infant`s vaccination log. Modified Poisson regression models with logarithm link function and significance level of 5% were applied to estimate the effect of depression, anxiety and stress on LBW.
Results: Compared to the subjects without mental health problems, the risk of LBW increased by 8.03 times in the severe depression (95% CIs: 5.55-11.62), by 8.06 times in the moderate stress (95% CIs: 5.64-11.51), by 3.13 times in the severe anxiety (95% CIs: 1.18-8.31), and by 8.43 in the highly severe anxiety (95% CIs: 5.80-12.25).
Conclusions: Severe and moderate levels of depression, anxiety, and stress all had statistically significant effects on LBW. Pre-natal screening services can help mitigate the burden of mental health by timely detection and referral. Moreover, designing and implementing consultation programs for pregnant women and their fsmilies, expecially their spouses, to provide emotional support and to improve marital relationship are amongst the suggestions.
Sa Hashemi, K Holakoui-Naeini, Ma Mansournia, R Akrami, M Nomali, T Valadbeigi, V Mennati, Ha Adineh, Mr Taghavi, M Ghafouri, S Poorbarat, A Hoseinzadeh, M Farahdel, Mr Armat, M Haresabadi,
Volume 17, Issue 3 (Vol 17,No.3, Atumn 2021 2021)
Abstract
Background and Objectives: COVID-19 is a new disease and little information is available on its risk factors. The aim of this study was to determine the mortality risk factors in patients with COVID-19 in the northeast of Iran.
Materials and Methods: A case-control study was conducted. Patients of both sexes with a confirmed diagnosis of Covid-19 infection who died during the study were studied as the case group and patients who were in good general health and ready for discharge were studied as the control group. Data analysis was performed with the STATA software version 14 using descriptive statistics and univariate and multiple logistic regression tests.
Results: Six hundred and eleven patients were studied (27% cases and 73% controls). Multiple logistic regression analysis showed that the odds of death were 2.8 times higher in patients over 80 years compared to patients aged 50-60 years. In addition, age under 40 years reduced the odds of mortality by 85% and living in rural areas increased odds of death by 2.2 times. Cough, general fatigue, pain, nausea and vomiting increased the odds of COVID19 survival.
Conclusion: The odds of mortality were higher in elder patients with COVID-19. In addition, living in rural areas increased the odds of mortality in patients. Cough and fatigue reduced mortality; however, it is needed to address other hidden factors for sound judgment.
