Kidney Res Clin Pract > Epub ahead of print
Deng, Zou, Chen, Hu, and Liao: Global burden and risk factors of chronic kidney disease in adolescents and young adults: a study from 1990 to 2019

Abstract

Background

Few studies have evaluated the global burden of chronic kidney disease (CKD) in adolescents and young adults (AYAs).

Methods

Age-standardized rates of incidence (ASIR), mortality (ASMR), and disability-adjusted life-years (ASDR) were used to describe the CKD burden in AYAs. The estimated annual percentage changes (EAPCs) were calculated to evaluate the temporal trends from 1990 to 2019. Risk factors were calculated by population attributable fractions.

Results

In 2019, the ASIR, ASMR, and ASDR of CKD in AYAs were 32.21 (95% uncertainty interval [UI], 23.73–40.81) per 100,000, 2.86 (2.61–3.11) per 100,000 and 236.85 (209.03–268.91) per 100,000, respectively. The ASIR was higher among females than males, whereas the ASMR was higher among males than females in 2019. From 1990 to 2019, significant increases in ASIR were found for CKD (EAPC, 0.98%; 95% confidence interval [CI], 0.95%–1.01%), although the ASMR had decreased (EAPC, –0.40%; 95% CI, –0.56% to –0.24%). The largest increase in ASIR was observed in countries with a middle sociodemographic index (SDI) (EAPC, 1.30%; 95% CI, 1.28%–1.33%), while the largest increase in ASMR was observed in high SDI. Globally, the proportional contribution of risk factors for CKD mortality varied across regions, with the highest proportions of high fasting plasma glucose being 14.04% in low SDI, compared with 24.01% in high SDI.

Conclusion

CKD is a growing global health problem in AYAs, especially in countries with a middle SDI. Targeted measures are needed to address the rising burden of CKD in AYAs, focusing on prevention, early diagnosis, and reducing disparities.

Introduction

Globally, chronic kidney disease (CKD) has emerged as one of the leading causes of mortality and disease burden; approximately 843.6 million patients were affected by CKD worldwide in 2017 [1]. Despite predominately manifesting in older populations, it is estimated that adolescents and young adults (AYAs) with CKD are vulnerable groups with poor treatment outcomes [2]. In addition, the increasing rates of childhood obesity, lipid abnormalities, diabetes mellitus (DM), and hypertension indicate that the number of young adults with CKD is likely to increase [3,4].
Accumulated evidence has reported that early-onset CKD (e.g., diagnosis before the age of 40 years) experienced many complex challenges with lower quality of life, increased healthcare utilization, and limited employment, independence, and relationships compared with healthy counterparts [5,6]. In addition, physiological complications of CKD, such as hypertension, dyslipidemia, hyperphosphatemia, and chronic inflammation, underlie many long-term outcomes and are likely to accumulate with disease duration [7,8]. For example, cardiovascular mortality is excessive in young adults with end-stage renal disease, with an increase 700-fold in 25- to 34-year-old patients undergoing dialysis [9]. Therefore, understanding the global burden of CKD in AYAs and its attributable risk factors is paramount.
Previous studies have reported on the global burden of CKD and its attributable risk factors in all age groups from 1990 to 2017 [10] and sex differences in CKD-associated mortality from 1990 to 2019 [11], or the burden from Asia [12,13], North Africa and Middle East region [14], and the United States [15]. AYAs represent a transitional phase between childhood and adulthood, characterized by numerous physical, psychological, and social changes [16]. However, existing health services often overlook their age-specific treatment and care needs, unlike services for children and older adults [17]. According to the age grouping and estimation methods of the Global Burden of Diseases (GBD) 2019, the age range of 15–39 years is widely recognized as the AYAs [17,18]. To date, no study has specifically described the global burden of CKD and its attributable risk factors in AYAs. Therefore, in the present study, we estimated the global epidemiological characteristics and secular trends of CKD, as well as the attributable risks for CKD in AYAs (15–39 years).

Methods

Data sources

The GBD 2019 database systematically evaluated the burden of 369 diseases and injuries and 87 risk factors in 204 countries from 1990 to 2019. A comprehensive description of the GBD study has been reported previously [19]. According to the sociodemographic index (SDI), the 204 countries were categorized into five regions: low SDI, low-middle SDI, middle SDI, high-middle SDI, and high SDI regions [20]. In the present study, data on estimates and their 95% uncertainty interval (UI) of incidence, death, and disability-adjusted life-years (DALYs) of CKD from 1990 to 2019, as well as its attributable risks were extracted in individuals aged between 15 and 39 years. GBD 2019 has detailed segmentation for each 5-year age group (15–19, 20–24, 25–29, 30–34, and 35–39 years).
The GBD study’s protocol has been approved by the Research Ethics Board at the University of Washington. Ethics approval and consent for publication for this study was exempted by the Ethics Committee of the First People’s Hospital of Chenzhou, because the GBD is a publicly available database and all participants’ data were anonymous.

Case definitions of chronic kidney disease and death

According to the GBD 2019, CKD was defined as an estimated glomerular filtration rate (eGFR) less than 60 mL/min/1.73 m2 or albumin to creatinine ratio less than 30 mg/g. For CKD mortality, the International Classification of Diseases (ICD) codes were applied (Supplementary Table 1, available online); adjustments for differences in case definitions and study methods were also made [10]. The burden of CKD was categorized into five causes: CKD due to hypertension, CKD due to glomerulonephritis, CKD due to type 1 DM, CKD due to type 2 DM, and CKD due to other and unspecified causes. For every individual with CKD, ICD codes were used for primary renal diseases to map individuals to GBD cause groupings. Individuals with CKD but no ICD code for primary renal diseases were classified as having CKD of unspecified cause [10].

Estimation of the disease burden and attributable risk factors for chronic kidney disease

The general estimation methods for disease burden are available elsewhere [19,21] and Supplementary Methods (available online). In addition, to calculate the disease burden attributable to risk factors, GBD 2019 uses integrated rule-based evidence to provide comparable risk quantification over time and across populations [21].

Statistical analysis

The age-standardized rates (ASRs) and their UIs were calculated based on a global standard (World Health Organization 2000–2025) to quantify the burden of CKD [21]. The following equation was used:
Age-standardized rate = i = 1A aiwii = 1Awi
Where ai is the age-specific rate and wi is the weight in the same age subgroup of the chosen reference standard population. A is the number of different age groups.
The estimated annual percentage changes (EAPCs) in the ASRs were used to evaluate the trend in the burden of CKD. The natural logarithm of the ASR was fitted to the following regression line model: ln (ASR) = α + βx + ɛ, where x is the calendar year. The EAPC and its 95% confidence interval (CI) were derived from the following regression model: y = 100 (exp (β) − 1), where y is the EAPC [22]. When the lower limit of the 95% CI of the estimated EAPC was greater than 0, the ASR was considered to show an upward trend during the observation period. Conversely, when the upper limit of the 95% CI of the EAPC estimate was less than 0, the ASR was considered to show a downward trend. Otherwise, the ASR was considered stable [23].
Data collation, analysis, and graphical rendering were performed using Python and R software (version 3.5.3; R Foundation for Statistical Computing).

Results

The global burden of chronic kidney disease from 1990 to 2019

In 2019, there were 955,902 (95% UI, 704,185–1,211,169) incidence cases of early-onset CKD globally, an absolute increase of about 406,543 compared to 1990. The age-standardized incidence rate (ASIR) per 100,000 people increased from 25.04 in 1990 (95% UI, 18.51–31.65) to 32.21 in 2019 (95% UI, 23.73–40.81), showing a statistically significant upward trend (EAPC, 0.98%; 95% CI, 0.95%–1.01%). The number of deaths and DALYs attributed to early-onset CKD in 2019 was 84,800 (95% UI, 77,499–92,397) and 7,029,475 (95% UI, 6,203,734–7,980,873), respectively. The age-standardized mortality rate (ASMR) per 100,000 decreased from 2.96 (95% UI, 2.76–3.15) in 1990 to 2.86 (95% UI, 2.61–3.11) in 2019 (EAPC, –0.40%; 95% CI, –0.56% to –0.24%). However, the changing trend of DALYs showed no statistically significant overall trend (Tables 13; Supplementary Tables 2 and 3, available online).

The global burden of chronic kidney disease by sex and age

In terms of incidence, both in 1990 and 2019, there were more cases in females. The ASIRs for females and males in 2019 were 34.33 (95% UI, 25.26–43.50) per 100,000 people and 30.14 (95% UI, 22.32–38.15) per 100,000 people, respectively. However, the burden was greater among males than females. In 2019, the ASMR and age-standardized DALY rate (ASDR) for males were 3.32 (95% UI, 3.05–3.67) per 100,000 people and 253.82 (95% UI, 225.76–287.52) per 100,000 people, which were higher than 2.38 (95% UI, 2.10–2.64) per 100,000 people and 219.45 (95% UI, 187.72–252.02) per 100,000 people for females, respectively.
From the perspective of changing trends, ASIRs of different sexes showed upward trends from 1990 to 2019. In trends of ASMR, females showed a downward trend (EAPC, –0.87%; 95% CI, –1.08% to –0.65%), while males showed no statistical significance. In trends of ASDR, females showed a downward trend (EAPC, –0.32%; 95% CI, –0.44% to –0.19%), while males showed an upward trend (EAPC, 0.19%; 95% CI, 0.09%–0.30%).
The burden of CKD in five age groups was characterized by an increase in morbidity, mortality, and DALYs with increasing age, which is highest in the 35–39-year age group. The increase in CKD burden with age did not differ between the sexes (Tables 13, Figs. 1, 2; Supplementary Tables 2, 3 and Supplementary Fig. 1, available online).

The burden of chronic kidney disease by sociodemographic index regions

In 2019, the highest ASIR occurred in the middle SDI, which was 37.49 (95% UI, 27.29–47.60) per 100,000 people. Regarding the variation trend of ASIR, all five SDIs showed an upward trend from 1990 to 2019. The middle SDI showed the most apparent upward trend, with EAPC being 1.30% (95% CI, 1.28%–1.33%).
In 2019, the ASMR was the highest in low SDI, with a value of 3.78 (95% UI, 3.28–4.29) per 100,000 people. In terms of the trend of change from 1990 to 2019, only the high SDI showed an upward trend, and the EAPC of ASMR was 0.47% (95% CI, 0.28%–0.67%). There was no statistical significance in the change of low-middle SDI, while the other three SDI regions showed downward trends.
In 2019, low-middle SDI and low SDI had the highest ASDRs, which were 290.52 (95% UI, 257.55–326.58) per 100,000 people and 288.27 (95% UI, 250.44–327.98) per 100,000 people, respectively. The lowest value was 95.65 (95% UI, 77.95–117.88) per 100,000 people with high SDI. Consistent trends were found for ASMR (Tables 13, Figs. 1, 2; Supplementary Tables 2 and 3, available online).

The burden of chronic kidney disease by geographic regions

In 2019, the ASIR of early-onset CKD was highest in Central Asia, Eastern Europe, and Central Latin America, all exceeding 60 per 100,000 people. In contrast, Western Europe, Australasia, and Eastern Sub-Saharan Africa were the lowest, all lower than 12.55 per 100,000 people. Regarding the variation trend of ASIR, only high-income North America showed a downward trend. All the other 20 regions showed upward trends, with North Africa and the Middle East showing the most apparent upward trend.
In 2019, the highest and lowest ASMR of early-onset CKD occurred in Central Latin America and Western Europe, with values being 5.18 (95% UI, 4.56–5.85) per 100,000 people and 0.23 (95% UI, 0.22–0.25) per 100,000 people, respectively. Regarding changing trends, ASMR was on the rise in Central Latin America, the Caribbean, and high-income North America.
In 2019, the ASDR of early-onset CKD was highest in Central Latin America, which was 449.54 (95% UI, 387.80–519.44) per 100,000 people, and lowest in Western Europe, which was 43.96 (95% UI, 33.74–57.12) per 100,000 people. Regarding the variation trend of ASDR, 11 regions showed downward trends, six showed no statistical significance, and four regions showed upward trends (Tables 13, Fig. 1; Supplementary Tables 2 and 3, available online).

The burden of chronic kidney disease by country

In 2019, the maximum of the ASIR was 12 times higher than the minimum in all 204 countries. The highest occurred in Nicaragua and the lowest in Spain, which was 99.93 (95% UI, 76.89–121.75) per 100,000 people and 8.85 (95% UI, 4.71–13.11) per 100,000 people, respectively. As shown in Fig. 3, darker colors represent more severe ASIR, which was mainly distributed in Latin America, West Asia, Northern Europe, and East Asia. Only the United States of America, the Republic of Korea, Ethiopia, Burundi, and the Solomon Islands showed downward trends in ASIR from 1990 to 2019. A total of countries showed upward trends, with Western Asia, North Africa, and Latin America showing the most obvious upward trend.
In 2019, the ASMRs of early-onset CKD were highest in Palau, Micronesia (Federated States of America), Kiribati, Nauru, and the Marshall Islands, all more than 10 per 100,000 people. The lowest were in France, Slovenia, and Iceland, all less than 0.16 per 100,000 people. From 1990 to 2019, the ASMRs of 72 countries (35.29%) showed upward trends. Twenty-nine countries (14.22%) showed stable trends and 103 countries (50.49%) showed downward trends.
The ASDRs of early-onset CKD also varied in different countries in 2019. In Palau, Micronesia (Federated States of China), Kiribati, and Nauru, the ASDRs were all over 900 per 100,000 people, while in Sweden, Iceland, Norway, and Spain, they were below 36 per 100,000 people. As shown in Fig. 3, countries with high ASMR burden were distributed in Central Asia, South Asia, and Southeast Asia between 1990 and 2019, 72 countries (35.29%) showed upward trends in ASDR, with Ukraine and Latvia showing the most obvious upward trend. A total of 104 countries (50.98%) showed downward trends, with the Republic of Korea and Poland showing the most obvious trends.

The types of chronic kidney disease

In 2019, the proportion of global deaths for CKD due to other and unspecified causes and CKD due to glomerulonephritis ranked the highest, accounting for 33.00% and 31.22%, respectively. In the composition of DALYs, the first three were CKD due to other and unspecified causes, CKD due to glomerulonephritis, and CKD due to hypertension, with proportions being 37.99%, 30.38%, and 13.38%, respectively. Compared with high SDI, the proportion of CKD due to glomerulonephritis was higher in low SDI, while the proportion of CKD due to type 2 DM was lower (Fig. 4). Across the sexes, the proportion of CKD burden due to glomerulonephritis was higher in males than females (32.22% vs. 29.79% for death, 32.39% vs. 28.01% for DALYs) (Supplementary Figs. 2 and 3, available online).

Attributable risk factors for death and disability-adjusted life-year

In 2019, globally, the top three attributable risk factors for early-onset CKD death and DALYs were high systolic blood pressure (SBP, 28.15% and 28.05%), high fasting plasma glucose (23.54% and 18.24%) and high body mass index (BMI, 8.30% and 7.78%). Across the sexes, males were more affected by high SBP than females (30.53% vs. 24.85% for death, 30.77% vs. 24.82% for DALYs). At different SDI levels, population attributable fractions (PAFs) of varying risk factors were also different. The PAF of high fasting plasma glucose at low SDI was 14.04%, compared with 24.01% at high SDI (Fig. 5).
In different age groups, high fasting plasma glucose had the greatest effect in the 15–19-year and 20–24-year age groups. High SBP had the greatest influence in the 25–29, 30–34, and 35–39-year age groups, with the PAF reaching 37.98% for death and 38.41% for DALYs in the 35–39-year agr group. The influence of risk factors increases with age (Supplementary Fig. 4, available online).

Discussion

Based on data from the GBD 2019, we report an increase in ASIR in AYAs between 1990 and 2019, with the highest incidence concentrated in countries with a middle SDI and among females. Conversely, downward trends were found for the ASMR and ASMR, with the highest burden in countries with a low SDI. In addition, the secular trends in age-standardized incidence, death, and DALY rates, as well as patterns of attributable risk factors for early-onset CKD were heterogeneous across regions and countries. These findings indicated that preventing and controlling CKD in AYAs is still one of the great challenges.
According to the GBD study, AYAs aged 15 to 39 years constitute a substantial portion of the global population and represent a heterogeneous population [17,18]. Accumulating evidence has reported the burden of cardiovascular disease , type 2 DM, and cancer [17,18,24]. However, no studies have specifically reported the global burden of CKD in AYAs. In contrast to the stable trends in global age-standardized prevalence and mortality rates of CKD in all age groups [10,11], we found that AYAs tended to show an increasing incidence of CKD globally. Additionally, compared to children and the elderly, the incidence rate of CKD among AYAs has shown a more pronounced increasing trend over the past three decades [25]. More importantly, the PAF of CKD risk factors differed between different populations. For example, high fasting plasma glucose was the most important risk factor for CKD burden in the overall global population [10], whereas high SBP mainly accounted for CKD burden in AYAs. A potential explanation seems to be that AYAs may be more prone to the effects of high SBP [4,24]. Those suggested that targeted strategies are needed for the prevention and management of CKD in AYAs.
Despite all SDI regions showing upward trends, the middle SDI saw the most significant increase in ASIR since 1990. The reasons for the observed changes in CKD incidence are unclear, which may contribute to a combination of factors related to risk factor prevalence, healthcare access, the quality of care, population demographics, data quality, healthcare awareness, and socioeconomic conditions [1,26]. For example, a more universal detection and lower glomerular filtration rate boundary value was used to indicate kidney replacement therapy in middle SDI regions than other regions [27].
The burden of CKD in AYAs appeared to be increasing in the high SDI region, although downward trends were reported in low, middle, and middle-high SDI. Similar results were found in region-specific burden studies [13,14,28]. The potential reasons related to the increasing burden of CKD in high SDI regions may contribute to the high prevalence and inadequate control of risk factors for CKD in these regions, such as DM, hypertension, and high BMI [29]. The improvement of medical technology and effective healthcare reform in low-income countries may also be related to a decline in the CKD burden in these regions [28]. However, the disparities existing in CKD burden between different SDI regions will be further increased if these trends continue. Therefore, more resources for CKD-related prevention and therapeutic services are needed in countries with an increasing burden of early-onset CKD, particularly in locations with high SDI.
Marked variations in CKD burden were observed between the sexes, with a higher incidence of CKD in females and higher mortality in males. This sex disparity can be explained partially by disparities in behavioral and metabolic risk factors, disparities in access to kidney care levels, and differences in the underlying pathophysiology of disease [30,31]. For example, some risk factors for CKD, such as DM and hypertension, were more prevalent in females due to factors like obesity or hormonal changes related to pregnancy [18]. In addition, females may be more likely to seek medical attention and undergo health screenings [32], which could lead to earlier detection of CKD cases. Moreover, higher risk of occupational exposures, lower treatment compliance, faster progression to kidney disease, and lower use of health services among males may explain higher rates of CKD mortality [30]. Taken together, the heterogeneity by sex in CKD burdens calls for more attention to the high incidence of early-onset CKD in females and the high mortality and DALY attributable to CKD in males, and targeted preventative programs should be considered to control sex-specific risk factors and improve survival in young patients.
Globally, high SBP and fasting plasma glucose were the leading risk factors for mortality and DALYs from CKD in AYAs, which is consistent with previous studies of all age groups in low-and middle-income countries [28]. In addition, the high SDI region had the highest ASIRs of CKD due to hypertension [33]. Notably, due to the complexity of CKD etiology, a proportion of CKD deaths and DALYs are not directly attributable to DM or hypertension but can result from various other causes, such as glomerulonephritis and unspecified causes. Therefore, efforts to prevent and manage hypertension and DM [34,35], as well as kidney disease screening and early intervention for glomerulonephritis [36] should be strengthened and supported in AYAs.
To our knowledge, this is the first study to explore the global burden of CKD in AYAs. However, the GBD study had several limitations described and discussed elsewhere [19]. First, several data sources were included when estimating disease mortality and incidence for each country. Geographical proximity and predictive covariates are used to make estimates for countries with sparse or absent data, which might lead to an overestimation of the burden of CKD [10]. Second, most CKD cases were defined relying on one measurement of eGFR and albumin to creatinine ratio in GBD and lack of repeated measures evaluation. Previous studies suggested that CKD cases might be overestimated by using a single measurement of eGFR or albuminuria [37]. In addition, ascertainment of causes of CKD depends on the validity of ICD coding; however, CKD was often caused by comorbid conditions, which might lead to uncertainty about the definite underlying cause of CKD [38]; and thus, a proportion cause of CKD attributed to glomerulonephritis might be overshadowed by the large proportion of “other/unspecified.” Finally, although GBD methodologies and results are considered reliable and robust, they are necessarily limited by the quality of the available data and measurement methods, such as the exchangeability of data quality among individuals and changes in testing practices over time. For example, improvements in healthcare infrastructure and diagnostic capabilities globally might have led to enhanced detection of CKD, thereby influencing the rising incidence of CKD, especially in low SDI regions [28]. Therefore, the results should be interpreted with caution and further studies still be needed.
In conclusion, the present study showed that the number of CKD patients in AYAs has overall increased from 1990 to 2019, although the global ASR of death has generally decreased. Countries in a middle SDI experienced the largest increase in ASIR, while countries in a low SDI experienced the highest rate of age-standardized death. High SBP, high fasting plasma glucose, and high BMI are the main attributable risk factors for the burden of CKD. Furthermore, variations in the CKD burden and its attributable risk factors in different countries and regions highlight the critical role of targeted prevention strategies, including recognition and comprehensive control of established risk factors in AYAs and aggressive treatment of risk factors in high-risk populations, especially in hypertension, DM, and obesity patients aged 15 to 39 years.

Notes

Conflicts of interest

All authors have no conflicts of interest to declare.

Data sharing statement

The data are available from the GBD Results Tool of the Global Health Data Exchange (GHDx) (http://ghdx.healthdata.org/gbd-results-tool).

Authors’ contributions

Conceptualization: HD, BH, XL

Data curation: HD, QZ, ZC

Formal analysis: HD, QZ

Methodology, Validation: HD, ZC

Supervision: BH, XL

Writing–original draft: HD

Writing–review & editing: All authors

All authors read and approved the final manuscript.

Acknowledgments

The authors thank all the survey teams of the Global Burden of Diseases study group for their contribution and the study participants who contributed their information.

Figure 1.

EAPC of global and regional age-standardized incidence, death, and DALYs rates for early-onset chronic kidney disease from 1990 to 2019.

ASDR, age-standardized DALY rate; ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; CI, confidence interval; DALYs, disability-adjusted life-years; EAPC, estimated annual percent change; SDI, sociodemographic index.
j-krcp-23-331f1.jpg
Figure 2.

Temporal trend of age-standardized incidence, death, and DALY rates for early-onset chronic kidney disease, globally and by sociodemographic index from 1990 to 2019.

ASDR, age-standardized DALY rate; ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; DALY; disability-adjusted life-year.
j-krcp-23-331f2.jpg
Figure 3.

The age-standardized incidence, death, and DALY rates and its EAPC for chronic kidney disease by country in 2019.

ASDR, age-standardized DALY rate; ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; EAPC, estimated annual percent change; DALYs, disability-adjusted life-years.
j-krcp-23-331f3.jpg
Figure 4.

Proportional of CKD deaths (A) and disability-adjusted life-years (B) by underlying cause in 1990 and 2019.

CKD, chronic kidney disease; SDI, sociodemographic index.
j-krcp-23-331f4.jpg
Figure 5.

Proportion of chronic kidney disease deaths (A) and DALYs (B) attributable to risk factors globally in 2019.

ASDR, age-standardized DALY rate; ASMR, age-standardized mortality rate; DALYs, disability-adjusted life-years; SDI, sociodemographic index.
j-krcp-23-331f5.jpg
Table 1.
The ASIR due to CKD in adolescents and young adults in 1990 and 2019 and its temporal trends
Characteristic ASIR per 100,000 (95% UI)
EAPCs (95% CI), 1990–2019
1990 2019
Sex
 Both 25.04 (18.51–31.65) 32.21 (23.73–40.81) 0.98 (0.95 to 1.01)
 Female 27.53 (20.37–34.80) 34.33 (25.26–43.50) 0.90 (0.86 to 0.94)
 Male 22.62 (16.48–28.60) 30.14 (22.32–38.15) 1.08 (1.04 to 1.11)
SDI
 Low SDI 22.94 (17.38–28.22) 26.43 (20.04–32.82) 0.64 (0.56 to 0.72)
 Low-middle SDI 28.45 (21.43–35.24) 33.51 (25.23–42.11) 0.68 (0.61 to 0.75)
 Middle SDI 26.39 (19.43–33.31) 37.49 (27.29–47.60) 1.30 (1.28 to 1.33)
 High-middle SDI 25.29 (18.12–32.57) 31.70 (22.42–41.57) 0.99 (0.89 to 1.08)
 High SDI 18.12 (12.26–24.63) 22.97 (15.94–30.37) 0.73 (0.68 to 0.77)
Region
 East Asia 19.01 (13.44–24.52) 21.34 (14.32–28.71) 0.63 (0.51 to 0.75)
 Southeast Asia 29.12 (21.77–36.21) 39.63 (29.77–49.80) 1.07 (1.05 to 1.10)
 Oceania 34.20 (26.35–41.86) 40.11 (30.88–49.23) 0.41 (0.34 to 0.48)
 Central Asia 50.13 (39.22–61.49) 68.14 (52.61–84.48) 1.22 (1.08 to 1.35)
 Central Europe 27.94 (19.88–36.24) 36.39 (26.17–48.04) 1.06 (0.95 to 1.17)
 Eastern Europe 41.99 (29.68–54.53) 62.88 (45.32–83.31) 1.62 (1.37 to 1.86)
 High-income Asia Pacific 21.19 (14.69–28.37) 22.14 (15.23–29.73) 0.28 (0.15 to 0.41)
 Australasia 11.34 (7.02–16.14) 15.31 (9.74–21.57) 0.86 (0.76 to 0.97)
 Western Europe 11.05 (6.86–15.75) 12.15 (7.82–17.19) 0.28 (0.21 to 0.36)
 Southern Latin America 15.56 (10.40–20.89) 19.18 (13.11–25.51) 0.83 (0.79 to 0.87)
 High-income North America 20.15 (13.27–28.48) 18.48 (12.16–25.10) –0.67 (–0.84 to –0.51)
 Caribbean 29.18 (21.90–36.77) 46.37 (34.53–58.34) 1.45 (1.26 to 1.64)
 Andean Latin America 18.79 (13.48–24.35) 31.14 (22.31–40.32) 1.74 (1.69 to 1.79)
 Central Latin America 35.91 (26.56–45.91) 61.37 (46.39–76.24) 1.71 (1.58 to 1.83)
 Tropical Latin America 28.76 (20.79–36.81) 37.42 (26.69–48.07) 0.75 (0.65 to 0.86)
 North Africa and Middle East 25.78 (18.52–33.24) 47.97 (34.81–60.75) 2.12 (2.09 to 2.15)
 South Asia 31.93 (24.26–39.56) 33.01 (24.86–41.60) 0.29 (0.19 to 0.39)
 Central Sub-Saharan Africa 15.29 (11.03–19.48) 18.37 (13.03–23.70) 0.70 (0.64 to 0.76)
 Eastern Sub-Saharan Africa 14.11 (10.12–18.05) 15.33 (10.96–19.88) 0.43 (0.33 to 0.53)
 Southern Sub-Saharan Africa 34.69 (25.96–43.43) 42.61 (31.68–53.32) 0.66 (0.41 to 0.91)
 Western Sub-Saharan Africa 27.29 (20.74–33.56) 32.79 (24.95–40.46) 0.93 (0.67 to 1.18)

ASIR, age-standardized incidence rate; CI, confidence interval; CKD, chronic kidney disease; EAPCs, estimated annual percentage changes; SDI, sociodemographic index; UI, uncertainty interval.

Table 2.
The ASMR due to CKD in adolescents and young adults in 1990 and 2019 and its temporal trends
Characteristic ASMR per 100,000 (95% UI)
EAPCs (95% CI), 1990–2019
1990 2019
Sex
 Both 2.96 (2.76–3.15) 2.86 (2.61–3.11) –0.40 (–0.56 to –0.24)
 Female 2.74 (2.48–2.98) 2.38 (2.10–2.64) –0.87 (–1.08 to –0.65)
 Male 3.17 (2.91–3.44) 3.32 (3.05–3.67) –0.04 (–0.17 to 0.09)
SDI
 Low SDI 4.09 (3.59–4.61) 3.78 (3.28–4.29) –0.30 (–0.38 to –0.22)
 Low-middle SDI 3.68 (3.31–4.07) 3.76 (3.35–4.17) –0.09 (–0.31 to 0.13)
 Middle SDI 3.71 (3.44–4.00) 3.23 (2.99–3.50) –0.85 (–1.03 to –0.67)
 High-middle SDI 2.13 (1.97–2.30) 1.42 (1.30–1.54) –2.15 (–2.44 to –1.85)
 High SDI 0.76 (0.74–0.79) 0.79 (0.72–0.91) 0.47 (0.28 to 0.67)
Region
 East Asia 2.83 (2.43–3.27) 1.48 (1.27–1.72) –3.11 (–3.62 to –2.60)
 Southeast Asia 5.77 (5.22–6.41) 4.87 (4.32–5.49) –0.81 (–0.91 to –0.70)
 Oceania 4.25 (3.51–5.02) 4.51 (3.66–5.68) –0.02 (–0.26 to 0.22)
 Central Asia 4.06 (3.77–4.48) 4.67 (4.07–5.35) –0.56 (–0.99 to –0.13)
 Central Europe 1.61 (1.56–1.66) 0.81 (0.70–0.94) –2.40 (–2.74 to –2.07)
 Eastern Europe 1.64 (1.59–1.70) 1.15 (1.02–1.28) –2.63 (–3.12 to –2.13)
 High-income Asia Pacific 0.93 (0.88–0.98) 0.29 (0.27–0.31) –3.99 (–4.21 to –3.77)
 Australasia 0.31 (0.29–0.34) 0.32 (0.28–0.36) 0.03 (–0.13 to 0.19)
 Western Europe 0.38 (0.37–0.39) 0.23 (0.22–0.25) –2.01 (–2.15 to –1.87)
 Southern Latin America 1.71 (1.59–1.82) 1.47 (1.31–1.66) –0.69 (–0.84 to –0.55)
 High-income North America 0.76 (0.75–0.78) 0.93 (0.87–0.98) 1.06 (0.92 to 1.21)
 Caribbean 3.11 (2.74–3.56) 4.20 (3.36–5.17) 1.13 (1.06 to 1.21)
 Andean Latin America 3.39 (3.06–3.77) 3.03 (2.41–3.76) –0.66 (–1.05 to –0.28)
 Central Latin America 3.33 (3.25–3.42) 5.18 (4.56–5.85) 1.79 (1.69 to 1.89)
 Tropical Latin America 2.95 (2.84–3.06) 1.78 (1.69–1.87) –1.94 (–2.25 to –1.64)
 North Africa and Middle East 2.48 (2.22–2.76) 2.01 (1.64–2.46) –0.86 (–0.99 to –0.73)
 South Asia 3.42 (2.90–3.90) 3.73 (3.23–4.26) 0.13 (–0.18 to 0.45)
 Central Sub-Saharan Africa 4.51 (3.61–5.44) 3.57 (2.67–4.50) –0.86 (–0.91 to –0.82)
 Eastern Sub-Saharan Africa 4.19 (3.45–4.80) 3.25 (2.68–3.83) –1.06 (–1.12 to –0.99)
 Southern Sub-Saharan Africa 4.47 (3.99–5.11) 4.52 (3.59–5.44) –0.31 (–1.13 to 0.52)
 Western Sub-Saharan Africa 4.88 (4.03–5.97) 4.34 (3.37–5.34) –0.36 (–0.41 to –0.30)

ASMR, age-standardized mortality rate; CI, confidence interval; CKD, chronic kidney disease; EAPCs, estimated annual percentage changes; SDI, sociodemographic index; UI, uncertainty interval.

Table 3.
The ASDR due to CKD in adolescents and young adults in 1990 and 2019 and its temporal trends
Characteristic ASDR per 100,000 (95% UI)
EAPCs (95% CI), 1990–2019
1990 2019
Sex
 Both 230.83 (208.70–255.62) 236.85 (209.03–268.91) –0.05 (–0.16 to 0.06)
 Female 229.02 (203.46–258.05) 219.45 (187.72–252.02) –0.32 (–0.44 to –0.19)
 Male 232.60 (209.30–260.57) 253.82 (225.76–287.52) 0.19 (0.09 to 0.30)
SDI
 Low SDI 297.86 (264.34–331.83) 288.27 (250.44–327.98) –0.12 (–0.18 to –0.06)
 Low-middle SDI 277.11 (247.55–310.36) 290.52 (257.55–326.58) 0.08 (–0.09 to 0.26)
 Middle SDI 282.77 (255.22–313.04) 271.69 (240.00–307.31) –0.33 (–0.44 to –0.22)
 High-middle SDI 177.37 (156.58–200.72) 143.16 (120.07–168.96) –1.03 (–1.17 to –0.88)
 High SDI 86.63 (72.51–104.16) 95.65 (77.95–117.88) 0.52 (0.45 to 0.58)
Region
 East Asia 216.86 (186.75–248.94) 138.82 (114.95–165.43) –1.82 (–2.12 to –1.52)
 Southeast Asia 423.57 (382.04–475.41) 397.09 (346.97–450.76) –0.40 (–0.49 to –0.32)
 Oceania 334.39 (280.81–396.92) 371.71 (306.63–453.44) 0.16 (–0.03 to 0.34)
 Central Asia 319.59 (288.26–358.36) 375.47 (323.81–430.04) –0.21 (–0.51 to 0.09)
 Central Europe 133.46 (119.59–150.85) 93.29 (76.04–114.32) –1.16 (–1.41 to –0.91)
 Eastern Europe 155.60 (134.25–182.71) 138.50 (109.54–174.78) –1.16 (–1.45 to –0.87)
 High-income Asia Pacific 86.36 (76.52–97.81) 49.31 (39.34–61.82) –1.89 (–2.04 to –1.75)
 Australasia 45.31 (36.28–58.55) 50.12 (38.46–63.84) 0.18 (0.06 to 0.29)
 Western Europe 53.38 (42.74–67.17) 43.96 (33.74–57.12) –0.81 (–0.87 to –0.74)
 Southern Latin America 143.33 (127.25–161.37) 133.23 (114.15–154.14) –0.31 (–0.38 to –0.23)
 High-income North America 99.62 (80.47–122.94) 109.57 (90.99–132.97) 0.51 (0.34 to 0.68)
 Caribbean 257.24 (225.04–298.73) 354.05 (292.18–421.64) 1.17 (1.13 to 1.22)
 Andean Latin America 253.94 (226.93–283.13) 255.88 (208.87–307.02) –0.19 (–0.49 to 0.11)
 Central Latin America 292.18 (260.09–332.24) 449.54 (387.80–519.44) 1.68 (1.61 to 1.76)
 Tropical Latin America 232.87 (211.66–258.89) 175.32 (150.10–207.14) –1.14 (–1.36 to –0.92)
 North Africa and Middle East 208.07 (184.15–235.88) 205.76 (168.46–251.78) –0.09 (–0.19 to 0.00)
 South Asia 259.45 (222.69–296.89) 280.69 (245.22–319.24) 0.22 (–0.07 to 0.50)
 Central Sub-Saharan Africa 320.88 (263.95–383.09) 268.45 (211.57–329.28) –0.66 (–0.71 to –0.62)
 Eastern Sub-Saharan Africa 302.76 (254.95–344.28) 252.13 (213.40–292.44) –0.77 (–0.83 to –0.72)
 Southern Sub-Saharan Africa 319.08 (283.23–361.91) 335.30 (272.77–401.31) –0.07 (–0.71 to 0.56)
 Western Sub-Saharan Africa 346.89 (289.30–414.73) 327.17 (265.01–393.23) –0.15 (–0.20 to –0.11)

ASDR, age-standardized disability-adjusted life-year rate; CI, confidence interval; CKD, chronic kidney disease; EAPCs, estimated annual percentage changes; SDI, sociodemographic index; UI, uncertainty interval.

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