Global Burden and Trend of Anemia Due to Chronic Kidney Disease in G20 Countries from 1990-2021: A Benchmarking Systematic Analysis
Bibliographic record
Abstract
Introduction: Anemia due to chronic kidney disease (CKD) poses a significant health challenge, especially within the G20 nations, which represent major global economies. CKD is a major contributor to morbidity and mortality worldwide, accounting for over 1.5 million deaths annually. This study marks the first comprehensive analysis of the burden of anemia due to CKD across G20 countries, spanning the period from 1990 to 2021. It uniquely includes the initial two years of the COVID-19 pandemic, a time when healthcare systems were disrupted, and chronic disease management faced unprecedented challenges. Through this research, we aim to provide crucial insights that could guide policy adjustments and enhance healthcare strategies in these leading economies. Method: Employing the methodology of the Global Burden of Disease study, we estimated the prevalence and years lived with disability (YLDs) attributable to anemia due to CKD across the G20 countries from 1990 to 2021. The findings are detailed in both absolute counts and age-standardized rates (per 100,000 person-years), analyzing variations by age, sex, year, and location. Result: From 1990 to 2021, the total prevalence count of anemia due to CKD in G20 countries increased from 23.4 million (95% uncertainty interval: 21.7-25.4 million) to 43.6 million (40.2-47.2 million), while YLDs rose from 682,987 (457,723-970,504) to 1,129,130 (746,335-1,609,101). The age-standardized prevalence rate (ASPR) saw a total decrease of 14% during this period. The highest annual percentage change (APC) in ASPR was observed in the United States at 0.54%, followed by Bulgaria at 0.36%, and Romania at 0.005%, with the rest of the G20 nations experiencing decreases. In terms of age-standardized YLD rates (ASYLDR), the highest increase was noted in the USA at 0.45%, while other countries observed decreases. Indonesia recorded the highest ASPR at 1,295 (1,145-1,476) cases, followed by India at 1,108.91 (1,019-1,206) cases per 100,000 person-years. India also had the highest ASYLDR at 46.36 (31.64-64.59), whereas Canada reported the lowest at 3.77 cases per 100,000 person-years in 2021. By age group, those over 70 years had the highest prevalence at 24.1 million (21.5-26.8 million), followed by 50-74 years at 18.9 million (16.9-21.3 million), and 20-54 years at 7.6 million (6.9-8.4 million), with under 20 years at 579,600 (507,533-663,437) in 2021. Regarding YLDs, the over 70 age group experienced the highest number at 634,404 (418,602-908,932) in 2021. Gender-wise, females observed a higher increase in burden, with the total percentage change (TPC) in prevalence for males versus females at 86% versus 87%, and YLDs between 50% and 75% from 1990 to 2021. Conclusion: The findings of the study, reveal a nearly doubled prevalence and a significant increase in disability burden, despite a 14% decrease in the age-standardized prevalence rate. The findings highlight geographic and demographic disparities, with the highest increases observed in the United States, Bulgaria, and Romania, and notable burdens among the elderly and females. Public health policies should prioritize enhanced screening, early intervention, and tailored educational initiatives to address the notable demographic and geographic disparities revealed by this study. Clinically, the integration of advanced diagnostics, personalized treatment strategies, and improved patient education on lifestyle and treatment adherence is crucial.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.006 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".