A Population-Based Study on the Prevalence and Risk Factors of Chronic Kidney Disease in the Adult Population of Shiraz, Southern Iran

Global health inequalities of chronic kidney disease: a meta-analysis

BACKGROUND

Chronic kidney disease (CKD) is a significant contributor to global morbidity and mortality. This study investigated disparities in age, sex and socio-economic status in CKD and updated global prevalence estimates through systematic review and meta-analysis.

METHODS

Five databases were searched from 2014 to 2022, with 14 871 articles screened, 119 papers included and data analysed on 29 159 948 participants. Random effects meta-analyses were conducted to determine overall prevalence, prevalence of stages 3-5 and prevalence in males and females. Influences of age, sex and socio-economic status were assessed in subgroup analyses and risk of bias assessment and meta-regressions were conducted to explore heterogeneity.

RESULTS

The overall prevalence of CKD was 13.0% [95% confidence interval (CI) 11.3-14.8] and 6.6% (95% CI 5.6-7.8) for stages 3-5. The prevalence was higher in studies of older populations (19.3% for stages 1-5, 15.0% for stages 3-5) and meta-regression demonstrated an association of age, body mass index, diabetes and hypertension with prevalence of stages 3-5. The prevalence of CKD stages 1-5 was similar in males and females (13.1% versus 13.2%), but the prevalence of stages 3-5 was higher in females (6.4% versus 7.5%). Overall prevalence was 11.4%, 15.0% and 10.8% in low-, middle- and high-income countries, respectively; for stages 3-5, prevalence was 4.0%, 6.7% and 6.8%, respectively. Included studies were at moderate-high risk of bias in the majority of cases (92%) and heterogeneity was high.

CONCLUSION

This study provides a comprehensive assessment of CKD prevalence, highlighting important disparities related to age, sex and socio-economic status. Future research should focus on targeted screening and treatment approaches, improving access to care and more effective data monitoring, particularly in low- and middle-income countries.

Prevalence of Chronic Kidney Disease and Associated Factors among the Diabetic and Prediabetic Population in the Bandare-Kong Cohort Study; A Population-Based Study

BACKGROUND

This investigation aims to examine the relationship between diabetes and prediabetes with chronic kidney disease (CKD) while taking into account key risk factors such as gender, age, lifestyle, smoking habits, and blood pressure.

METHODS

Between November 17, 2016, and November 22, 2018, 4063 subjects aged 35 to 70 years were enrolled in the first phase of the Bandare-Kong Non-Communicable Disease (BKNCD) Cohort Study, which is part of the PERSIAN (Prospective Epidemiological Research Studies in IrAN) cohort and was conducted in a coastal region of the Hormozgan province in southern Iran. CKD was calculated using the Modification of Diet in Renal Disease (MDRD) formula based on glomerular filtration rate (GFR)<60 mL/min per 1.73 m2 , or albumin/Cr>30 mg/g in random urine, self-reported kidney failure, or dialysis. Urine albumin and creatinine were determined by standard kits (Pars Azmoon, Tehran, Iran) and the BT1500 automatic chemistry analyzer (Biotecnica Instruments, Rome, Italy).

RESULTS

The prevalence of CKD was found to be 15.3%, with 29.6% identified in diabetic individuals and 16.5% in prediabetic patients. So, the prevalence of CKD in diabetics was higher than prediabetics and normal people. Increased age, dysglycemia (diabetes or prediabetes), hypertension, and use of angiotensin receptor blockers were markedly associated with an elevated risk of CKD in adults.

CONCLUSION

The study emphasizes the importance of early detection and management of CKD risk factors, particularly among high-risk individuals, to mitigate CKD progression and associated complications. By addressing modifiable risk factors, proactive screening, and enhanced awareness, significant strides can be made in reducing CKD burden and improving patient outcomes.

The national trend of the burden of Chronic Kidney Disease (CKD) in Iran from 1990 to 2019

Purpose

Chronic Kidney Disease (CKD) has become the 8th leading cause of death in Iran in 2017, 5 steps up from 1990. This is important as hypertension, diabetes, and chronic glomerulonephritis along with exposure to toxins or heavy metals are the main risk factors for the disease. Despite its heavy burden, there are limited studies on the incidence and prevalence of the disease in the Iranian adult population. The present article studies the burden of CKD at the national level in 2019, and its trend over the past three decades.

Methods

In 2019, the Global Burden of Disease (GBD) study provided an annual estimation of the burden of 369 diseases and injuries in 204 countries from 1990 until 2019. The data estimating CKD and related mortality in Iran were collected from the disease registry, survey, and scientific literature. All-ages and age-standardised indices of incidence, prevalence, deaths, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) were extracted for both sexes.

Results

Since 1990, the age-standardized incidence (34.7% (95% uncertainty interval 30.8 - 38.8)) and prevalence (19.6% (17.7 - 21.8)) of CKD have risen, while a 21.5% (-28.8 - -15.4) and 18.0% (-35.4 - -10.8) decrease were noted in age-standardized DALYs and deaths rates, respectively. The lowest prevalence was reported in the eastern and western provinces.

Conclusion

Current study provides comprehensive knowledge about the CKD burden, suggesting the Iranian healthcare system has been more effective in averting deaths rather than managing morbidities. Multi-sectoral action plans are needed to strengthen preventive and early detection programs in high-risk areas.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01298-y.

Trends of national and sub-national burden attributed to kidney dysfunction risk factor in Iran: 1990-2019

BACKGROUND

Kidney dysfunction is a risk factor for cardiovascular disease and chronic kidney disease. Herein, we aimed to describe the attributable burden of kidney dysfunction at the national and sub-national levels in Iran.

METHODS

The Global Burden of Disease (GBD) 2019 data were extracted on the deaths, disability-adjusted life years (DALYs), years of life lost, and years lived with disability attributed to the risk factor of kidney dysfunction by age and sex at the national and provincial levels from 1990-2019. Also, risk exposure was reported by summary exposure value (SEV) with a range of 0 to 100. The estimated values were based on a comparative risk assessment framework.

RESULTS

In 2019, the age-standardized death rate and age-standardized DALYs rate attributable to kidney dysfunction were 58.2 (95% uncertainty interval of 48.8-68.1) and 1127.2 (981.1-1282.7) per 100,000 population in Iran, respectively. Also, the Sistan and Baluchistan province (1729.3 [1478.3-2006.4]) and the province of Tehran (681.9 [571.4-809.8]) had the greatest and lowest age-standardized DALYs rates, respectively. Nationally, SEVs increased from 22.8 to 26.2. The age-standardized burden attributable to kidney dysfunction had a positive association with age advancement. The attributable age-standardized deaths and DALYs rates in all socio-demographic index regions decreased from 1990-2019. Also, the highest and lowest attributable age-standardized DALYs rates of kidney dysfunction came from ischemic heart disease and peripheral artery disease in 2019, respectively.

CONCLUSION

Although the attributed age-standardized DALYs and death rates decreased from 1990-2019, risk exposure increased and remains a crucial risk factor in Iran. Therefore, policymakers should consider preparing a preventive program that takes into account different levels of prevention of kidney dysfunction.

Prevalence of chronic kidney diseases and its determinants among Iranian adults: results of the first phase of Shahedieh cohort study

Background

Chronic kidney disease (CKD) is one of the major global causes of mortality, described as the most neglected chronic disease. This study aimed to determine the prevalence and determinants of CKD in the setting of the Shahedieh cohort study in Yazd, Iran.

Methods

This cross-sectional study was conducted on adults in the baseline phase of the Shahedieh cohort study in Yazd, Iran. In this study, 9781 participants aged 30–73-year-old were investigated. The data used in this study included demographic and clinical variables and blood samples. Adjusted odds ratios were employed using multivariate logistic regression; meanwhile, population attributable risks for CKD were calculated and reported.

Results

CKD prevalence was 27.5% (95%CI: 26.57–28.34) in all participants, 24% in male, and 30.3% in female. The results of multivariate logistic regression analysis identified age (OR = 1.89, 95%CI:1.082–1.96), women (OR = 1.62, 95%CI: 1.45–1.79), BMI ≥ 30 (OR = 1.40,95%CI: 1.20–1.62), diabetes (OR = 1.38, 95%CI: 1.22–1.57), hypertriglyceridemia(OR = 1.20, 95%CI: 1.01–1.43), history of cardiovascular disease (OR = 1.20, 95%CI: 1.01–1.43), hypertension (OR = 1.18, 95%CI: 1.04–1.33), smoking (OR = 1.17, 95% CI: 1.02–1.33), LDL ≥ 130 (OR = 1.15, 95%CI: 1.01–1.31), history of kidney stone (OR = 1.14, 95%CI: 1.01–1.32) and hypercholesterolemia (OR = 1.14, 95%CI: 1.01–1.32) as risk factors for CKD. Among individual factors, obesity (11.25%), Hypertriglyceridemia (9.21%), LDL ≥ 130 (7.12%) had the greatest Population-Attributable Fraction, followed by Hypercholesterolemia (5.2%), diabetes (5.05%), smoking (3.73%) and high blood pressure (2.82%).

Conclusion

The results showed that the main determinants of CKD are potentially modifiable risk factors. Therefore, implementing early detection and screening programs in people at risk as well as preventive measures such as lifestyle modification programs and risk factors controlling can prevent the disease.

Comparative Analysis for Prediction of Kidney Disease Using Intelligent Machine Learning Methods

Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing prevalence, high risk of progression to end-stage renal disease, and poor morbidity and mortality prognosis. It is rapidly becoming a global health crisis. Unhealthy dietary habits and insufficient water consumption are significant contributors to this disease. Without kidneys, a person can only live for 18 days on average, requiring kidney transplantation and dialysis. It is critical to have reliable techniques at predicting CKD in its early stages. Machine learning (ML) techniques are excellent in predicting CKD. The current study offers a methodology for predicting CKD status using clinical data, which incorporates data preprocessing, a technique for managing missing values, data aggregation, and feature extraction. A number of physiological variables, as well as ML techniques such as logistic regression (LR), decision tree (DT) classification, and K-nearest neighbor (KNN), were used in this work to train three distinct models for reliable prediction. The LR classification method was found to be the most accurate in this role, with an accuracy of about 97 percent in this study. The dataset that was used in the creation of the technique was the CKD dataset, which was made available to the public. Compared to prior research, the accuracy rate of the models employed in this study is considerably greater, implying that they are more trustworthy than the models used in previous studies as well. A large number of model comparisons have shown their resilience, and the scheme may be inferred from the study's results.

A simple prediction model of hyperuricemia for use in a rural setting

Currently, the most widely used screening methods for hyperuricemia (HUA) involves invasive laboratory tests, which are lacking in many rural hospitals in China. This study explored the use of non-invasive physical examinations to construct a simple prediction model for HUA, in order to reduce the economic burden and invasive operations such as blood sampling, and provide some help for the health management of people in poor areas with backward medical resources. Data of 9252 adults from April to June 2017 in the Affiliated Hospital of Guilin Medical College were collected and divided randomly into a training set (n = 6364) and a validation set (n = 2888) at a ratio of 7:3. In the training set, non-invasive physical examination indicators of age, gender, body mass index (BMI) and prevalence of hypertension were included for logistic regression analysis, and a nomogram model was established. The classification and regression tree (CART) algorithm of the decision tree model was used to build a classification tree model. Receiver operating characteristic (ROC) curve, calibration curve and decision curve analyses (DCA) were used to test the distinction, accuracy and clinical applicability of the two models. The results showed age, gender, BMI and prevalence of hypertension were all related to the occurrence of HUA. The area under the ROC curve (AUC) of the nomogram model was 0.806 and 0.791 in training set and validation set, respectively. The AUC of the classification tree model was 0.802 and 0.794 in the two sets, respectively, but were not statistically different. The calibration curves and DCAs of the two models performed well on accuracy and clinical practicality, which suggested these models may be suitable to predict HUA for rural setting.

Prevalence of chronic kidney disease in Bangladesh: a systematic review and meta-analysis

BACKGROUND

Worldwide, chronic kidney disease (CKD) is a major public health issue, with a leading cause of death and disability. The aim of our study to estimate the prevalence of CKD in the Bangladeshi population based on existing data of previous studies.

METHODS

In this systematic review and meta-analysis study, electronic search engines of PubMed, Google Scholar, Scopus, and the national journal databases were used to find relevant published articles until December 31, 2019. Based on predefined inclusion/exclusion criteria, nine studies were included, and RevMan V5.0 statistical software was used for meta-analysis.

RESULTS

The outcomes of the included studies (nine studies, a total of 225,206 participants) based on meta-analysis showed an overall prevalence of CKD in Bangladeshi people of 22.48%, which was higher than the global prevalence of CKD. The prevalence of CKD in females was higher with high heterogeneity (I² 90%) in contrast to male participants (25.32% vs. 20.31%).

CONCLUSION

Above all, this study revealed a higher rate of prevalence of CKD in Bangladeshi people. So, it needs more attention to concern public health policymakers and the government to control and reduce the high-risk of disability due to CKD.