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Showing 4 results for Chronic Kidney Disease
The Risk of Chronic Kidney Disease and Metabolic Syndrome in the Incidence of Coronary Heart Disease: Tehran Lipid and Glucose Study
Mh Panahi , P Yavari, D Khalili, Y Mehrabi, F Hadaegh, F Azizi,
Volume 9, Issue 4 (3-2014)
Abstract
Background & Objectives: We studied the risk of Chronic Kidney Disease (CKD), Metabolic Syndrome (MetS), and their interaction on the incidence of Coronary Heart Disease (CHD).
Methods: A population of 6568 participants (43.4% male) with a mean age of 48.4 years for males and 46.7 years for females and a median follow-up of 10.1 years was investigated. They were divided into 4 groups at baseline: CKD-/MetS-, CKD+/MetS-, CKD-/MetS+, CKD+/MetS+. Hazard Ratios (HRs) were calculated for each group and were compared to the first group using multivariate Cox regression analysis adjusted for age, education, smoking, total cholesterol, and the family history of cardiovascular diseases.
 Results: Men with CKD (without MetS) showed an HR of 1.74 (CI 95%: 1.16-2.60) for CHD events. The measured value was 2.34 (1.77-3.08) for men with MetS (without CKD). The respective results were in women 1.18 (0.64-2.19) and 2.59 (1.73-3.88). CKD and MetS had a significant negative interaction with CHD events (HR=0.40, 0.24-0.66). The interaction was not significant in women (P value=0.48).
Conclusion: The results of this study indicated that CKD without MetS was a risk factor for coronary heart disease in men but not in women.
Obesity Paradox: Incidence of Coronary Heart Disease in Patients with Chronic Kidney Disease and Metabolic Syndrome
Mh Panahi, P Yavari, D Khalili, Y Mehrabi, F Hadaegh, F Azizi,
Volume 11, Issue 1 (6-2015)
Abstract

Background & Objectives: Some studies on chronic diseases have indicated that obesity may result in a paradoxically longer survival. The present study was aimed to investigate the effect of Chronic Kidney Diseases (CKD) and Metabolic Syndrome (MetS) on the incidence of Coronary Heart Disease (CHD).

Methods: In order to record time to CHD events, a sample of 6,507 individuals (mean age 47.4 years, 43.4% males) was followed for nearly 10 years. Participants were also categorized into four groups according to presence/absence of CKD and MetS. Then, using a Multivariate Cox Regression, the Hazard Ratio (HR) of each group was estimated relative to individuals free of both CKD and MetS separately for obese (BMI&ge27.1 Kg/m2) and non-obese persons (BMI<27.1 Kg/m2).

Results: HR for non-obese patients with CKD but not MetS was obtained 2.06 (95%CI: 1.28-3.31) in men and 2.56 (1.04-6.31) in women. However, these associations were not significant for obese patients. Furthermore, among non-obese men and women with MetS alone, HR was estimated 2.52 (1.71-3.73) and 4.68 (2.20-9.95), respectively. For obese patients, these values were 1.70 (1.05-2.78) and 1.90 (1.16-3.13), respectively.

Conclusion: The results reflect that among those who had MetS alone, the risk of CHD incidence was twice higher in non-obese individuals compared to obese patients.


Association of Tea, Coffee, Caffeine and Chronic Kidney Disease: Tehran Lipid and Glucose Study
Zahra Gaeini, Parvin Mirmiran, Zahra Bahadoran, Fereidoun Azizi,
Volume 18, Issue 3 (12-2022)
Abstract
Background and Objectives: Dietary intakes are one of the factors influencing the incidence of chronic kidney disease. The present study was performed to investigate the possible long-term effects of caffeine, tea and coffee consumption on the incidence of chronic kidney disease.
Methods: 1780 adults participating in the third phase of the Tehran Lipid and Glucose Study (TLGS) (2006-2008) were selected for inclusion criteria. Dietary intakes were assessed using a food frequency questionnaire (FFQ). Demographic variables, anthropometrics, and biochemical data were measured at baseline and after six years of follow-up. To estimate the risk of chronic kidney disease, logistic regression analysis, adjusted for possible confounding variables, was used.
Results: Participants’ mean (±SD) age at baseline was 33.96±15.40 years. During six years of follow-up, the incidence of chronic kidney disease (CKD) in the population studied was 17.9%. After adjusting confounding variables, the incidence of CKD did not show any significant relationship with tea, coffee, or caffeine intakes (adjusted odds ratio and confidence intervals for CKD in the third tertile of tea and caffeine intake compared to the first tertile and in coffee drinkers compared to non-drinkers were 0.92 (0.68-1.25), 0.87 (0.63-1.21) and 1.17 (0.90-1.51), respectively).
Conclusion: Inverse and non-significant relationship between tea and caffeine consumption with the incidence of CKD and a direct and non-significant relationship between coffee consumption and the incidence of CKD were observed in this study, necessitating further prospective studies to investigate the effects of dietary intakes on CKD.

Association between Proteinuria and Sleep in the Azar Cohort Population: A Cross-Sectional Study
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.

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