Showing 31 results for Risk Factors
S Mehdipour, F Zolala, M Hoseinnejad, R Zahedi, E Najafi, M , N Farrokhnia, M Fathi,
Volume 14, Issue 2 (9-2018)
Abstract
Background and Objectives: Evidence suggests that underlying diseases increase the severity of influenza and lead to hospitalization or death. This study was conducted to determine the risk factors associated with hospitalization of patients in Afzalipour Hospital, Kerman, Iran during an outbreak of H1N1 influenza in December 2015.
Methods: In this case-control study, the case group comprised 85 patients who were hospitalized for influenza and the control group included 51 patients who had influenza symptoms and were discharged after required evaluations and check-up. The data were collected from both groups on a daily basis for two weeks. For data analysis, descriptive analysis, logistic regression analysis, Lasso Regression, and likelihood ratio were used. Analysis was performed using the Stata version 12 and R software.
Results: Among the variables examined, after removal of additional variables, 12 variables were introduced into the multivariate regression. The history of pulmonary disease and diabetes increased the odds of hospitalization following influenza by more than 11 (OR = 11.6, P. value = 0.003) and 9 times (OR = 9, P. value = 0.01), respectively.
Conclusion: Underlying disease and factors play a major role in exacerbating the disease. Therefore, the health system should take the necessary preventive measures when outbreaks occur.
F Feizmanesh, Aa Safaei,
Volume 14, Issue 3 (12-2018)
Abstract
Background and Objectives: Pulmonary embolism is a potentially fatal and prevalent event that has led to a gradual increase in the number of hospitalizations in recent years. For this reason, it is one of the most challenging diseases for physicians. The main purpose of this paper was to report a research project to compare different data mining algorithms to select the most accurate model for predicting pulmonary embolism in hospitalized patients. This model would provide the knowledge needed by the medical staff fir better decision making.
Methods: In this research, we designed a prediction model using different methods of machine learning that would best predict the probability of pulmonary embolism in patients at risk. Among data mining algorithms, Bayesian network, decisions tree (J48), logistic regression (LR), and sequential minimal optimization (SMO) were used. The data used in the study included risk factors and past history of patients admitted to the Lung Department of Shariati Hospital, Tehran, Iran.
Results: The results showed that the accuracy and specificity of all prediction models were satisfactory. The Bayesian model had the highest sensitivity in predicting pulmonary embolism.
Conclusion: Although the results showed a little difference in the performance of prediction models, the Bayesian model is a more appropriate tool to predict the occurrence of pulmonary embolism in hospitalized patients in this type of data. It can be considered a supportive approach along medical decisions to improve disease prediction.
H Tekeh, H Ansari, , N Noori, K Tirgarfakheri, F Zare,
Volume 15, Issue 2 (9-2019)
Abstract
Background and Objectives: Congenital heart disease (CHD) is the most common type of birth defect that accounts for 25% of all congenital anomalies. This study was conducted to identify the risk factors od congenital heart disease in southeast Iran.
Methods: In this case-control study, 353 cases were selected from children aged 0 to 59 months who suffered from congenital heart disease and were referred to the Children’s Heart Clinic of Zahedan. Moreover, 353 controls were selected from healthy children aged 0 to 59 months who presented to health centers in Sistan and Baluchistan Province. The cases and controls were matched for age, sex and place of residence. The data were collected using interviews with children’s mothers and analyzed using independent t-test, chi-square test, and multiple logistic regression models.
Results: This study showed that the lack of folic acid consumption in pregnancy (OR =11.8), mot using multivitamins during pregnancy (OR = 4.1), history of CHD in first-degree relatives of parents (OR=3.4), history of abortion (OR =3.4), presence of telecommunication rig in the vicinity of the house (OR=3) and exposure to secondhand smoke (OR=2.9) significantly increased the chance of a CHD (P <0.05).
Conclusion: Effective planning, emphasis on the use of supplements during pregnancy, and improved awareness of the society, especially high risk women, can be helpful in decreasing CHD in this region. Providing education regarding preventive factors seems to be necessary for health and medical workers to control risk factors and reduce costs associated with CHD.
Aa Abbasi, Hr Bahrami, B Beygi, E Musa Farkhani, V Vakili, F Rezaee Talab , R Eftekhari Gol , M Talebi,
Volume 15, Issue 2 (9-2019)
Abstract
Background and Objectives: Sleep disorders include problems involving the quality, timing and amount of sleep, which cause decreased functioning and discomfort during the daytime. Considering the importance of sleep in health and quality of life and the probability of the related disorders in the elderly, this study was conducted to investigate sleep disorders and their risk factors in an elderly population covered by Mashhad University of Medical Sciences.
Methods: We conducted one of the largest population-based cross-sectional studies in an elderly population covered by Mashhad University of Medical Sciences in 2016. In this study, a total 8496 elderly people aged 60-90 years old with sleep disorders were compared with 35041 elderly subjects without complaints. Data were extracted from the Sina Electronic Health Record System. Bivariate and multivariate logistic regression analysis were carried out using the STATA ® version 14 to determine associations between independent variables and sleep disorders.
Results: In multivariate analysis, male gender (AOR=0.58; 95% CI: 0.55-0.61), being married (AOR=0.88; 95% CI: 0.83-0.93), overweight and lightweight compared to normal weight (AOR=1.27; 95% CI: 1.21-1.34 and AOR=1.20; 95% CI: 1.04-1.38, respectively), smoking (AOR=2.22; 95% C.I: 2.05-2.40), high blood pressure (AOR=1.44; 95% C.I: 1.37-1.52), diabetes (AOR= 1.49; 95% C.I: 1.40-1.58) and depression (AOR=3.05; 95% C.I: 2.74-3.38) variable remained in the final model after adjusting for confounders.
Conclusion: In this study, gender, marital status, body mass index, smoking, blood pressure, diabetes and depression were the main determinants of sleep disorders. It is necessary to identify the risk factors and perform appropriate interventions to improve the sleep.
F Amiri , H Sharifi, E Ghorbani , Fs Mirrashidi, M Mirzaee, N Nasiri,
Volume 15, Issue 2 (9-2019)
Abstract
Background and Objectives: Congenital hypothyroidism is one of the reasons for mental retardation and premature death of infants. Since identification of the determinants of hypothyroidism plays a significant role in its prevention, this study was conducted to determine the prevalence of congenital hypothyroidism and to investigate its determinants in newborn infants.
Methods: This study was a secondary analysis of the data of the neonatal congenital hypothyroidism screening program. Hypothyroidism was diagnosed based on the Thyroid Stimulating Hormone (TSH) level in the heel prick blood samples on the third to fifth day of life. The data of infants born in Jiroft hospitals were collected from Jiroft Health Center and analyzed using descriptive statistics and Poisson regression test.
Results: In this study, 4998 newborns (2450, 49.02% female, 2548, 98 / 50% male) were investigated. The study samples were newborns born from March to March 2016. The prevalence of congenital hypothyroidism was 1 in 135 live births. The prevalence of congenital hypothyroidism was higher in babies born by cesarean section (IRR = 2.2, 95% CI =1.1-4.1), newborns admitted to the NICU (IRR = 4.6, 95% CI=2.4-8.9), and babies with high birth weight (IRR = 5.3, 95% CI =3.5-8.1).
Conclusion: The prevalence of hypothyroidism was higher in this study compared to other studies. Its prevalence was higher in males than in females. Genetic and environmental differences may explain this difference. The prevalence of hypothyroidism was higher in infants born through cesarean section and newborns hospitalized in NICU.
M Saberi, M Hosseinpour , A Khaleghnejad Tabari, H Soori, Mr Maracy,
Volume 16, Issue 1 (6-2020)
Abstract
Background and Objectives: Congenital anomalies are also known as birth defects and congenital disorders. Congenital anomalies occur in about 3-7% of the newborn babies worldwide. The purpose of this study was to determine the incidence of congenital anomalies and their determinants in hospitals affiliated with Isfahan University of Medical Sciences in 1395.
Methods: This cross-sectional study was conducted in all infants born in 1395. The data were analyzed with the SPSS software version 20 using Binary logistic regression.
Results: Of 5455 births in Isfahan hospitals, 121 neonates were diagnosed with major congenital anomalies. The total incidence of major congenital anomalies was 2.2 per 100 births. The results showed a statistically significant relationship between maternal blood group, consanguinity, sex and height of infant with congenital anomalies in newborns (P <0.05). Moreover, 26.7% of all abnormalities were related to limbs and the lowest percentage was related to genetic abnormalities, digestive system, anus, and spine with an incidence of 0.7% for each.
Conclusion: More attention should be paid to premarital genetic counseling in order to identify the consanguinity factor as a risk factor for genetic abnormalities. Moreover, pregnant women should be educated about the timely intake of micronutrients to control abnormalities.
Hr Bahrami Taghanaki , E Mosa Farkhani , R Eftekhari Gol , P Bahrami Taghanaki , S Bokaei, A Taghipour, B Beygi,
Volume 16, Issue 3 (11-2020)
Abstract
Background and Objectives: Diabetes is considered as one of the most common endocrine disorders worldwide. The aim of this study was to investigate the factors associated with diabetic complications.
Methods: A case-control study was performed on the data of 70089 diabetic patients (4622 cases and 53613 controls) extracted from the SINA Electronic Health Record (SinaEHR®) in a population covered by Mashhad University of Medical Sciences in 2018. The effect of independent variables on the likelihood of diabetic complications was investigated using single-variable and multivariate logistic regression models with the control of the potential confounding effects.
Results: Using the multivariate logistic regression, the odds of developing diabetic complications were 0.35 (0.31-0.38) for living in the city, 0.73(0.67-0.79) for living in the suburbs and 0.31(0.28-0.33) for living in rural areas relative to the metropolises, 0.84 (0.78-0.91) for illiterate subjects, 0.70 (0.66-0.75) for physical activity, 1.51(1.34-1.71) for stage 1 hypertension and 1.87 (1.43-2.44) for stage 2 hypertension relative to normal blood pressure, 0.79(0.74-0.85) for uncontrolled low density lipoprotein and 1.42(1.33-1.51) for uncontrolled hemoglobin A1C.
Conclusion: Various risk factors were identified to increase the odds ratio of diabetic complications. The most important risk factors were uncontrolled glycosylated hemoglobin and stage 1 and 2 hypertension. Control of these factors can reduce the chance of diabetic complications in diabetic patients.
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 (12-2021)
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.
L Shams, Gh , T Nasiri, M Meskarpour Amiri,
Volume 17, Issue 4 (3-2022)
Abstract
Background and Objectives: The aim of this study was to investigate the relationship between socioeconomic status and non-communicable diseases (NCD) risk factors in one of the northern counties of Iran.
Methods: A descriptive-analytical cross-sectional study was conducted in Langrud County in 2019. In this study, 906 rural and urban households were surveyed using mixed sampling. The data collection tool was the standard questionnaire of "NCD disease care system". Households’ exposure to NCD behavioral risk factors (including unhealthy diet, sedentary lifestyle and smoking) in different socio-economic groups was examined and compared with logistic regression models using the STATA software.
Results: The probability of smoking in illiterate subjects and those with unfinished high school education and high school diploma was 5.1, 7.5 and 4.2 times higher than those with university education (OR = 5.1,7.5,4.2; P <0.05). The probability of unhealthy diets in the first and second quartiles of income (very low and low income) was 3.4 and 2.6 times higher compared to the people in the fourth quartile of income (high income) (P <0.05; OR = 3.4, 2.6).
Conclusion: The micro-level socioeconomic inequalities (within the county) have a significant relationship with households’ exposure to NCD risk factors. Reducing socio-economic inequalities at the micro level should be considered as an appropriate tool to reduce health inequality at the macro level.
M Bagbanian, M Momayyezi, H Fallahzadeh, M Mirzaei,
Volume 17, Issue 4 (3-2022)
Abstract
Background and Objectives: Drug use not only affects a person's physical and mental health, but also affects the health of others in the community. Various variables, including demographic and social factors, affect drug use. The present study was conducted to investigate the prevalence of drug use and related factors in the participants of Shahedieh Cohort Study.
Methods: A descriptive study was performed using the first phase of Shahedieh cohort study on 10194 adult residents of Shahdieh, Zarch, and Ashkezar in 2015-2016. The aim of the cohort study was to assess the prevalence of non-communicable diseases and their risk factors in adults aged 35-70 years. Data were analyzed with the SPSS 20 using chi-square and logistic regression.
Results: The prevalence of illicit drug use in the present study was 15.5% with a mean age of onset of 31.5 ± 9.2 years. The most common drug was opium (98.2%). The most common method of drug use was inhalation (98.1%). The logistic regression showed that male gender (P< 0.001), age 40 to 49 years (P<0.001), low education (below high school diploma) (P<0.001), positive history of smoking (P<0.001) and alcohol consumption (P<0.001) were the most important factors associated with drug use. In addition, a positive history of ischemic heart disease (P=0.007) and psychiatric disorders (P=0.02) were the diseases related to drug use.
Conclusion: The prevalence of drug use was high in the study population. There is an urgent need for intervention and preventive measures to solve this complex social problem.
Mohammad Khajedaluee, Maliheh Dadgar Moghaddam, Amir-Reza Khajedaluee, Hiva Sharebiani, Hamidreza Bahrami Taghanaki, Maryam Ziadi Lotfabadi, Zeinab Shateri Amiri,
Volume 18, Issue 4 (3-2023)
Abstract
Background and Objectives: Cardiovascular diseases are the leading cause of adult mortality in many developing countries. This study aims to compare the estimation of the ten-year relative risk of cardiovascular events using the Framingham criteria with a native model.
Methods: This population-based cross-sectional study was conducted in 2014, focusing on the adult population (≥16 years) of Mashhad. Stratified random cluster sampling was employed to gather participants' information based on Framingham's criteria. Data mining, utilizing the decision tree algorithm design, was evaluated using Rapidminer v5.3 software and the cross-validation method.
Results: Out of 2978 individuals, 1930 (64.9%) were women and 1041 (35.1%) were men, with a mean age of 43.5±14.7. Applying the Framingham criteria, the ten-year risk levels of cardiovascular disease were estimated as follows: 77.8% at a low-risk level, 13.4% at a medium-risk level, and 8.8% at a high-risk level.
Regarding data mining, model number (1) achieved an accuracy of 79.56%, indicating that the predicted risk levels using the Framingham algorithm matched the observed values at 95.24% for the low-risk level, 90.8% for the medium-risk level, and 33.13% for the high-risk level. As for model number (2), an accuracy of 82.78% was obtained, with the matching values being 98.20% for the low-risk level, 0.42% for the medium-risk level, and 53.01% for the high-risk level.
Conclusion: The Framingham criteria demonstrate limited effectiveness in predicting medium and high-risk levels in the Mashhad population. According to the local model, smoking and high blood pressure in adulthood are the most significant factors in predicting the risk of cardiovascular diseases in young individuals.
