Showing 4 results for Sleep Disorder
Mr Maracy, S Iranpour, A Esmaillzadeh, Ghr Kheirabadi,
Volume 10, Issue 1 (6-2014)
Abstract
Background & Objectives: Since the human diet is a combination of different foods and that this combination will affect the body differently from when these foods are received separately, the evaluation of dietary patterns is of great importance. The primary aim of this study was to examine the association between dietary patterns during pregnancy and postpartum depression.
Methods : This population-based, cross-sectional study was conducted on 771 women who attended the Ardabil's health care network. This study was carried out in a period of 4 months. In this study, systematic random sampling was used. Dietary data was collected using the Willett-format Dish-based 106 items Semi-quantitative Food Frequency Questionnaire (DS-FFQ) which was designed and validated specifically for Iranian adults. Dietary patterns were identified through exploratory factor analysis based on 34 predefined food groups. In the present study, individuals who obtained a rating of 13 or higher were considered to be suffering from postpartum depression. Logistic regression was used to estimate OR and 95% CI for postpartum depression in each quartile of patterns.
Results : In the present study, three dietary patterns were identified: mixed dietary pattern, semi-healthy dietary pattern, and fruits and vegetables dietary pattern. The last one was significantly associated with a reduced risk of postpartum depression.
Conclusion : The findings show that a diet of fruits and vegetables during pregnancy is associated with a reduction in the risk of PPD. Additional studies are recommended to confirm these finding.
F Ranjkesh, M Nasiri, Sh Sharif Nia , Ah Goudarzian, Sz Hosseinigolafshani ,
Volume 14, Issue 4 (3-2019)
Abstract
Background and Objectives: One of the most common problems during pregnancy is sleep disorders, which is the result of physiological, hormonal and physical changes in pregnancy and can be the basis for many disorders before, during, and after delivery. The aim of this study was to determine the psychometric properties of the persion version of Sleep Condition Indicator in a sample of Iranian pregnant women.
Methods: In present study, 300 pregnant women reffered to health center of Kowsar (affiliated to Qazvin University of Medical Sciences) that were gathered via accesible sampling method, completed the Sleep Condition Indicator in 2017. Face, content, and construct validity (convergent and divergent validity) and reliability of selected questionnaire were calculated.
Results: The results of exploratory and confirmatory factor analysis showed two sustained and distinct factors, including quantity in sleep quality and the consequences of low sleep quality. The two-factor fit of Sleep Condition Indicator was approved based on standard indicators. Convergent and divergent validity were acceptable for all factors. Moreover, the internal consistency and reliability of the construct were also acceptable.
Conclusion: The results of this study showed that the Sleep Condition Indicator is valid and reliable among pregnant women, so it seems that this tool can be used to screen sleep disorders in women during pregnancy.
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.
Farahnoosh Farnood, Elnaz Faramarzi, Aysouda Ghanizadegan, Seyyedeh Mina Hejazian, Sepideh Zununi Vahed, Mohammadreza Ardalan,
Volume 21, Issue 1 (6-2025)
Abstract
Background and Objectives: Sleep disorders are common issues in people's health and can be related to metabolic and kidney diseases. Studies have shown that the relationship between proteinuria and sleep disorders can be modified. Since this relationship has not been investigated in Iranian populations, this study examined the relationship between proteinuria and sleep in the Azar cohort population.
Methods: This cross-sectional study used data from the Azar cohort study with a population of 15,000. Based on the study's inclusion and exclusion criteria, 105 patients with proteinuria were selected. After age and sex matching, 420 patients without proteinuria were included in the control group. The patients' sleep patterns were assessed based on a designed questionnaire, and the results were compared between the two groups.
Results: None of the sleep factors significantly differed between the two groups with and without proteinuria (P>0.05). Moreover, the mean weight, waist circumference, systolic blood pressure, diastolic blood pressure, and body mass index (BMI) were significantly different in the two groups (P<0.001).
Conclusion: There was no significant relationship between proteinuria and sleep in the Azar cohort population. However, the weight, BMI, waist circumference, and systolic and diastolic blood pressure significantly differed between people with and without proteinuria.
