Kim CS, Suh SH, Choi HS, Bae EH, Ma SK, Kim B, Han KD, Kim SW. Impact of diabetes duration and hyperglycemia on the progression of diabetic kidney disease: Insights from the KNHANES 2019-2021. World J Diabetes 2025; 16(5): 102094 [DOI: 10.4239/wjd.v16.i5.102094]
Corresponding Author of This Article
Soo Wan Kim, MD, PhD, Professor, Department of Internal Medicine, Chonnam National University Medical School, Jebongro 42, Gwangju 61469, South Korea. skimw@chonnam.ac.kr
Research Domain of This Article
Endocrinology & Metabolism
Article-Type of This Article
Case Control Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Chang Seong Kim, Sang Heon Suh, Hong Sang Choi, Eun Hui Bae, Seong Kwon Ma, Soo Wan Kim, Department of Internal Medicine, Chonnam National University Medical School, Gwangju 61469, South Korea
Chang Seong Kim, Sang Heon Suh, Hong Sang Choi, Eun Hui Bae, Seong Kwon Ma, Soo Wan Kim, Department of Internal Medicine, Chonnam National University Hospital, Gwangju 61469, South Korea
Bongseong Kim, Kyung-Do Han, Department of Statistics and Actuarial Science, Soongsil University, Seoul 06978, South Korea
Co-corresponding authors: Kyung-Do Han and Soo Wan Kim.
Author contributions: Han KD and Kim SW contribute equally to this study as co-corresponding authors; Kim CS, Han KD and Kim SW conceived and designed the study; Kim CS and Kim BS participated in drafting the manuscript and provided revision and final editing; all authors analyzed the data, and reviewed the manuscript; all authors contributed to the article and approved the submitted the manuscript.
Supported by the National Research Foundation (NRF) of Korea, No. RS-2023-00217317.
Institutional review board statement: The study was approved by the Institutional Review Board of Chonnam National University Hospital (CNUH-EXP-2024-205).
Informed consent statement: The requirement for written informed consent was waived by the review board due to using anonymous and de-identified information. The institutional review board of the Korean Centers for Disease Control approved the KNHANES.
Conflict-of-interest statement: The authors have no conflicts of interest to declare.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Data sharing statement: The data underlying this article will be shared on reasonable request to the corresponding author.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Soo Wan Kim, MD, PhD, Professor, Department of Internal Medicine, Chonnam National University Medical School, Jebongro 42, Gwangju 61469, South Korea. skimw@chonnam.ac.kr
Received: October 9, 2024 Revised: February 20, 2025 Accepted: March 14, 2025 Published online: May 15, 2025 Processing time: 198 Days and 22.4 Hours
Abstract
BACKGROUND
Diabetes is a significant risk factor for chronic kidney disease, and diabetic kidney disease (DKD) is prevalent among patients with diabetes. Previous studies have indicated that the duration of diabetes and poor glycemic control are associated with an increased risk of DKD, but data on how the duration and severity of hyperglycemia specifically relate to DKD progression are limited.
AIM
To investigate the relationship between diabetes duration and glycemic control, and DKD progression in South Korea.
METHODS
We included 2303 patients with diabetes using the 2019-2021 Korea National Health and Nutrition Examination Surveys data. DKD was defined as an estimated glomerular filtration rate (eGFR) < 60 mL/min per 1.73 m2, urinary albumin-to-creatinine ratio ≥ 30 mg/g, or both. Diabetes duration and severity were classified into six categories each.
RESULTS
DKD prevalence was 25.5%. The DKD risk significantly increased in diabetes lasting 10-15 years or hemoglobin A1C (HbA1c) ≥ 8% compared to patients with newly diagnosed diabetes or HbA1c < 6.5%. Albuminuria developed with shorter diabetes duration and lower HbA1c than eGFR decline. The adjusted odds ratios for DKD were 3.77 [95% confidence interval (95%CI): 2.60-5.45] and 4.91 (95%CI: 2.80-8.63) in patients with diabetes lasting ≥ 20 years and HbA1c ≥ 10%, respectively, compared to those with new-onset diabetes and HgA1c < 6.5%.
CONCLUSION
Patients with diabetes lasting > 10 years or HbA1c > 8% had a higher risk of DKD, emphasizing the importance of early monitoring and management is crucial to prevent DKD progression.
Core Tip: This study reveals that approximately 25% of Korean adults with diabetes have diabetic kidney disease (DKD), with a significantly higher risk in patients with a diabetes duration of more than 10 years or a hemoglobin A1C (HbA1c) level above 8%. Albuminuria, an early marker of DKD, developed with shorter diabetes duration and lower HbA1c than the decline in estimated glomerular filtration rate. These findings highlight the need for vigilant kidney function monitoring in patients with long-standing diabetes or poor glycemic control.
Citation: Kim CS, Suh SH, Choi HS, Bae EH, Ma SK, Kim B, Han KD, Kim SW. Impact of diabetes duration and hyperglycemia on the progression of diabetic kidney disease: Insights from the KNHANES 2019-2021. World J Diabetes 2025; 16(5): 102094
Diabetes mellitus (DM) is a common metabolic disorder with prevalence increasing in the twenty-first century[1]. In 2013, 382 million adults had diabetes in 219 countries and territories, and the number was projected to rise to almost 600 million in 2035[2]. The rapid increase in DM prevalence increases both macrovascular and microvascular complications[3]. Critical metabolic changes, such as hyperglycemia, induce glomerular hyperfiltration and promote inflammation and fibrosis of kidneys in early diabetes[4,5]. Notably, the rising prevalence of diabetes-associated chronic kidney disease (CKD) mirrors the surge in DM prevalence[6]. Thus, patients with DM have a nearly 2-5-fold higher risk of CKD than those without DM[7,8].
The natural history of diabetic kidney disease (DKD) in patients with type 2 DM begins early with microalbuminuria, progressing to macroalbuminuria, decline in glomerular filtration rate (GFR), and ultimately end-stage kidney disease. Accordingly, CKD in patients with DM is clinically defined as persistent elevated urinary albumin excretion ≥ 30 mg/g, persistent reduced estimated GFR (eGFR) < 60 mL/min/1.73 m2, or both[9]. Albuminuria is an early biomarker of DKD. However, several studies reported that patients with DM with concomitant kidney impairment do not exhibit urinary albumin loss[9-12]. Moreover, although the risk factors, particularly the duration of diabetes and degree of hyperglycemia, are associated with DKD progression, many patients with poor glycemic control do not develop renal complications[13,14]. In this context, epidemiological data regarding the relationship of DM duration and hyperglycemia severity with CKD progression and albuminuria or kidney impairment are limited.
We hypothesized that the duration of diabetes and severity of hyperglycemia are critical determinants of DKD progression. Specifically, our study aimed to evaluate DKD prevalence and investigate the relationship of DM duration and hyperglycemia severity with DKD risk using data from the Korea National Health and Nutrition Examination Survey (KNHANES). Furthermore, we aimed to analyze the risk of kidney function decline and developing urinary albuminuria depending on DM duration and severity respectively.
MATERIALS AND METHODS
Data sources and study population
The KNHANES is a population-based cross-sectional survey assessing health-related behavior, health condition, and nutritional status of noninstitutionalized civilians from all geographic regions in South Korea, with an annual rate of approximately 10000 individuals. This survey uses a complex, stratified, multistage, cluster sampling method based on geographic area, sex, and age to select a sample representative of the entire South Korean population. The KNHANES comprises three component surveys: A health interview, a health examination, and a nutrition survey. These surveys collect comprehensive data on socioeconomic status, health behaviors, quality of life, healthcare utilization, anthropometric measures, and biochemical profiles using fasting blood serum and urine samples. Additional assessments include dental health, vision, hearing, bone density, X-ray test results, food intake, and dietary behavior. Data collection for these individual components is conducted through face-to-face interviews and self-administered questionnaires. Survey staff members undergo an intensive training course and complete supervised practice sessions before conducting fieldwork. Detailed quality control protocols, based on the consensus of committee members, are implemented in the survey and documented in the survey manuals. The details of the survey and methods were previously described[15]. This study used the 8th KNHANES dataset (KNHANES VIII, 2019-2021), comprising 22559 individuals.
Initially, out of 22559 individuals, 18511 participants aged ≥ 20 years were identified. Of these, we excluded 15828 people without DM. Additionally, 381 participants with missing data necessary for covariate adjustments were also excluded. Finally, 2303 participants were included in our analysis. The Institutional Review Board of Chonnam National University Hospital (CNUH-EXP-2024-205) approved the study protocol, which was performed according to the 1964 Declaration of Helsinki and its later amendments. The requirement for written informed consent was waived by the review board due to using anonymous and de-identified information. The institutional review board of the Korean Centers for Disease Control approved the KNHANES.
Measurements and lifestyle habits
Data on medical histories and lifestyle habits were collected using a self-report questionnaire. The subjects were categorized as current smokers or nonsmokers. Participants were classified as non-drinkers, mild-to-moderate drinkers (1.0-30.0 g alcohol/day), or heavy drinkers (≥ 30.0 g alcohol/day). Additionally, the subjects were classified as regular or non-regular exercisers based on their responses to a modified version of the International Physical Activity Questionnaire. Anthropometric measurements were performed by specially trained examiners, and blood samples were collected after fasting for at least 8 h. For each participant, the body mass index was calculated by dividing the body weight (kg) by the height squared (m2). Detailed information regarding measurements is provided elsewhere[16].
Definition of diabetes, DKD, and comorbidities
The presence of DM was defined by fasting plasma glucose ≥ 126 mg/dL, current use of any antidiabetic medications or insulin, a previous history of DM, or hemoglobin A1C (HbA1c) ≥ 6.5%[17]. DKD was defined as elevated urinary albumin excretion [urinary albumin-to-creatinine ratio (UACR) ≥ 30 mg/g], eGFR < 60 mL/min/1.73 m2, or both in patients with DM. The eGFR was calculated using the CKD-Epidemiology Collaboration creatinine equation. Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or taking antihypertensive drugs. Dyslipidemia was defined as low-density lipoprotein cholesterol level ≥ 160 mg/dL, triglyceride ≥ 120 mg/dL, high-density lipoprotein cholesterol < 40 mg/dL in men and < 50 mg/dL in women, or using lipid-lowering drugs. The subjects were classified into six categories for DM duration: New onset, < 5, 5-10, 10-15, 15-20, and ≥ 20 years. Additionally, we divided the participants into six categories based on HbA1c: < 6.5%, 6.5%-7%, 7%-8%, 8%-9%, 9%-10%, and ≥ 10%.
Statistical analysis
DKD prevalence was estimated by the number of DKD patients divided by the number of DM patients based on the cross-sectional information of the KNHANES VIII (2019-2021). The baseline characteristics were presented as percentages (SE) for categorical variables and mean ± SE for continuous variables. Comparisons of participant’s characteristics according to the presence of DKD were conducted using the t-test and the χ2 test for categorical variables. An analysis of covariance adjusted for age, sex, regular exercise, and history of cardiovascular disease, hypertension, and dyslipidemia was used to determine statistical differences in the eGFR and UACR according to DM duration and severity. Multivariate adjusted logistic regression analysis was conducted to examine the association of DM duration and HbA1c with DKD prevalence and calculate odds ratios (ORs) and 95% confidence intervals (95%CIs) of these outcomes according to the 6 categories. Model 1 was adjusted for age and sex, while model 2 was adjusted for age, sex, regular exercise, and history of cardiovascular disease, hypertension, and dyslipidemia. Another multivariate logistic regression with adjustment for confounders was performed to analyze the risk of low eGFR or albuminuria. In a subgroup analysis, ORs for DKD according to DM duration and severity were examined in participants based on sex, age of 65 years, and presence of hypertension. All analyses were performed using SAS (version 9.4, SAS Institute, Cary, NC, United States). Two-sided P values < 0.05 indicated statistical significance.
RESULTS
Participants’ characteristics
Table 1 summarizes the participants’ demographic characteristics. The study population comprised 2,303 individuals with DM. Among them, 615 were diagnosed with CKD. DKD prevalence among patients with DM was 25.5%, indicating that the estimated number of DKD patients in the entire Korean population is 1193443. DKD was more prevalent with increasing age. Compared with the no DKD group, the DKD group had longer DM duration and higher HbA1c. The prevalence of cardiovascular disease and hypertension was higher among participants with DKD compared to those without DKD. Moreover, the DKD group had higher UACR and fasting glucose levels than the no DKD group. However, there was no significant difference in body mass index and total cholesterol levels between both groups.
Table 1 Baseline characteristics of the study participants, KNHANES 2019 to 2021.
Characteristics
No diabetic kidney disease
Diabetic kidney disease
P value
Unweighted number
1688
615
Weighed number
3479066
1193443
Age, years
59.13 ± 0.37
64.09 ± 0.67
< 0.001
20-39
6.79 (0.87)
2.83 (0.82)
< 0.001
40-64
59.39 (1.36)
44.06 (2.52)
≥ 65
33.83 (1.27)
53.11 (2.53)
Sex (male)
57.73 (1.43)
59.52 (2.26)
0.5045
Smoking
0.3969
Never
48.70 (1.48)
49.24 (2.30)
Former
30.38 (1.37)
27.37 (2.09)
Current
20.92 (1.30)
23.39 (2.08)
Alcohol consumption
0.2791
Never
33.46 (1.31)
37.59 (2.34)
Mild
54.50 (1.40)
50.61 (2.40)
Heavy
12.04 (0.95)
11.80 (1.59)
Duration of diabetes mellitus, years
< 0.0001
New onset
36.80 (1.41)
24.51 (2.10)
< 5
25.06 (1.18)
17.89 (1.80)
5-10
15.41 (1.11)
15.69 (1.75)
10-15
11.15 (0.92)
15.56 (1.75)
15-20
6.25 (0.67)
8.04 (1.26)
≥ 20
5.34 (0.55)
18.30 (1.70)
Hemoglobin A1C (%)
7.09 ± 0.04
7.62 ± 0.08
< 0.0001
< 6.5
24.42 (1.2)
22.92 (2.06)
6.5-7
35.38 (1.32)
19.48 (1.76)
7-8
25.74 (1.29)
26.21 (2.17)
8-9
7.67 (0.80)
13.31 (1.62)
9-10
2.52 (0.45)
7.07 (1.12)
≥ 10
4.27 (0.66)
11.01 (1.69)
eGFR (mL/min/1.73 m2)
91.89 ± 0.41
76.94 ± 1.17
< 0.0001
UACR (mg/g)
9.35 ± 0.16
201.98 ± 19.42
< 0.0001
Regular physical activity
39.11 (1.44)
31.96 (2.18)
0.0056
Cardiovascular disease
10.23 (0.83)
13.78 (1.52)
0.0358
Hypertension
53.07 (1.54)
71.67 (2.30)
< 0.0001
Dyslipidemia
47.81 (1.42)
50.12 (2.54)
0.4134
WC (cm)
90.86 ± 0.29
91.35 ± 0.47
0.3835
Height (cm)
163.85 ± 0.28
163.06 ± 0.46
0.1502
Weight (cm)
69.89 ± 0.42
68.51 ± 0.72
0.1013
BMI (kg/m2)
25.9 ± 0.12
25.6 ± 0.19
0.1753
Fasting glucose (mg/dL)
134.66 ± 1.08
146.82 ± 2.66
< 0.0001
Total cholesterol (mg/dL)
176.62 ± 1.21
173.27 ± 2.23
0.1726
DKD prevalence according to diabetes duration and severity
After categorizing subjects into six groups based on the percentage of DM duration and HgA1c level, we performed the covariance analysis to evaluate eGFR and UACR according to DM duration and severity. eGFR and UACR significantly decreased and increased (P < 0.0001), respectively, as the duration of DM increased (P < 0.0001) even after adjusting for potential confounding factors (Figure 1A). Similar associations were observed between UACR and HgA1c categories (P = 0.0094). However, eGFR showed no statistically significant negative association with HgA1c categories (P = 0.4831; Figure 1B).
Figure 1 The trend in estimated glomerular filtration rate and urinary albumin-to-creatinine ratio in participants with diabetes mellitus.
A: Estimated glomerular filtration rate (eGFR) and albuminuria trends according to the duration of diabetes; B: eGFR and albuminuria trends according to hemoglobin A1C levels. Models were adjusted for age, sex, regular exercise, and previous history of hypertension, dyslipidemia, and cardiovascular disease. DM: Diabetes mellitus; eGFR: Estimated glomerular filtration rate; UACR: Urinary albumin creatinine ratio; HbA1c: Hemoglobin A1C.
Risk of DKD according to DM duration and severity
The prevalences and risk of DKD according to DM duration and HgA1c were assessed through a multivariate logistic regression analysis after controlling for the above-mentioned possible confounders (Table 2). As the duration and severity of DM increased, the risk of DKD also gradually increased in a dose-dependent manner. Significant positive linear associations were observed for the risk of DKD with increased DM duration and HgA1c levels (P for trend < 0.0001). In individuals with DM lasting 10-15 years, the risk was significantly higher compared to new-onset diabetes (adjusted OR: 1.849; 95%CI: 1.272-2.688). Particularly, participants with DM lasting > 20 years had a 3.77-fold increased risk of DKD compared to those with new-onset diabetes (adjusted OR: 3.765; 95%CI: 2.602-5.449). Similarly, individuals with HbA1c levels of 8%-9% had a significantly increased risk of DKD compared to those with HbA1c levels < 6.5%. Those with HbA1c levels ≥ 10% had a 4.91-fold increased risk (adjusted OR: 1.911; 95%CI: 2.795-8.630).
Table 2 Odds ratio of diabetic kidney disease according to duration or severity of diabetes mellitus.
In patients with DM, the risk of kidney dysfunction (eGFR < 60 mL/min/1.73 m²) and albuminuria (UACR ≥ 30 mg/g Cr) was analyzed based on DM duration and severity (Table 3). The risk of albuminuria increased significantly in patients with DM duration > 10 years and HbA1c > 8% compared to the reference group. However, kidney function decline significantly progressed in patients with DM duration > 20 years, but there was no linear relationship with HbA1c (P for trend = 0.1786).
Table 3 Odds ratio of kidney outcomes according to duration or severity of diabetes mellitus.
Group
eGFR < 60 mL/min/1.73 m2
UACR ≥ 30 mg/g Cr
Percentage (SE)
Adjusted, OR (95%CI)
Percentage (SE)
Adjusted, OR (95%CI)
Duration of diabetes mellitus (years)
New onset
3.22 (0.68)
1 (reference)
16.11 (1.67)
1 (reference)
< 5
5.76 (1.03)
1.349 (0.740, 2.459)
15.57 (1.85)
0.917 (0.627, 1.343)
5-10
6.46 (1.35)
1.578 (0.826, 3.014)
22.28 (2.62)
1.456 (0.987, 2.148)
10-15
8.04 (1.88)
1.877 (0.950, 3.711)
29.19 (3.25)
2.057 (1.394, 3.034)
15-20
7.21 (1.91)
1.112 (0.538, 2.297)
27.02 (3.98)
1.729 (1.080, 2.767)
≥ 20
28.46 (3.68)
4.875 (2.626, 9.050)
41.93 (3.73)
3.351 (2.243, 5.009)
P for trend
< 0.001
< 0.001
Hemoglobin A1C (%)
< 6.5
9.28 (1.33)
1 (reference)
18.47 (1.97)
1 (reference)
6.5-7
6.19 (0.96)
0.693 (0.423, 1.134)
11.85 (1.37)
0.606 (0.423, 0.869)
7-8
6.49 (1.13)
0.808 (0.482, 1.352)
22.50 (1.96)
1.377 (0.966, 1.964)
8-9
8.90 (2.35)
1.387 (0.688, 2.797)
35.20 (3.96)
2.793 (1.792, 4.353)
9-10
8.47 (3.38)
1.487 (0.529, 4.178)
47.09 (5.99)
5.288 (3.078, 9.085)
≥ 10
6.42 (2.62)
1.788 (0.679, 4.711)
43.46 (5.91)
4.945 (2.832, 8.635)
P for trend
0.1786
< 0.001
Subgroup analyses
For age-based subgroup analyses, participants were classified into categories of < 65 and ≥ 65 years. In all subgroup analyses according to age, sex, and hypertension, longer DM duration and higher HbA1c were consistently associated with the risk of DKD without significant differences between the subgroups (Table 4).
Table 4 Subgroup analysis of odds ratio for diabetic kidney disease according to age, sex and hypertension.
Group
Subgroup
Percentage (SE)
Adjusted, OR (95%CI)
Subgroup
Percentage (SE)
Adjusted, OR (95%CI)
P for interaction
Duration of DM (years)
< 65 years
≥ 65 years
0.1113
New onset
16.51 (2.04)
1 (reference)
24.26 (3.06)
1 (reference)
< 5
13.51 (2.28)
0.772 (0.472, 1.260)
31.96 (3.53)
1.312 (0.849, 2.029)
5-10
20.21 (3.65)
1.281 (0.739, 2.219)
35.31 (4.15)
1.680 (1.040, 2.713)
10-15
32.41 (4.99)
2.317 (1.349, 3.980)
32.33 (4.23)
1.576 (0.951, 2.612)
15-20
21.08 (6.25)
1.311 (0.572, 3.005)
36.70 (5.18)
1.785 (1.011, 3.152)
≥ 20
55.29 (8.71)
5.694 (2.708, 11.974)
53.68 (4.21)
3.644 (2.293, 5.792)
Hemoglobin A1C (%)
0.1732
< 6.5
16.88 (2.62)
1 (reference)
33.95 (3.18)
1 (reference)
6.5-7
7.98 (1.64)
0.419 (0.238, 0.735)
27.12 (2.9)
0.761 (0.510, 1.137)
7-8
19.03 (2.63)
1.117 (0.659, 1.893)
36.79 (3.32)
1.306 (0.873, 1.954)
8-9
30.67 (5.11)
2.193 (1.155, 4.165)
49.57 (5.88)
2.527 (1.501, 4.256)
9-10
41.61 (7.35)
4.166 (2.065, 8.404)
66.52 (8.15)
4.587 (1.914, 10.993)
≥ 10
46.55 (6.63)
4.911 (2.567, 9.394)
48.96 (11.36)
2.417 (0.947, 6.170)
Duration of DM (years)
Male
Female
0.2914
New onset
20.86 (2.34)
1 (reference)
15.14 (2.18)
1 (reference)
< 5
19.70 (2.64)
0.827 (0.536, 1.277)
19.64 (2.88)
1.218 (0.738, 2.01)
5-10
24.70 (3.96)
1.116 (0.668, 1.865)
27.24 (3.80)
1.964 (1.155, 3.338)
10-15
34.57 (4.75)
1.754 (1.061, 2.900)
29.24 (4.35)
1.996 (1.183, 3.366)
15-20
26.28 (5.12)
1.015 (0.563, 1.828)
36.23 (6.40)
2.543 (1.325, 4.882)
≥ 20
59.20 (5.08)
3.970 (2.338, 6.739)
48.47 (5.35)
3.783 (2.235, 6.402)
Hemoglobin A1C (%)
0.7956
< 6.5
27.10 (3.07)
1 (reference)
20.68 (2.73)
1 (reference)
6.5-7
15.65 (2.15)
0.501 (0.326, 0.769)
16.17 (2.19)
0.750 (0.467, 1.207)
7-8
24.22 (2.77)
0.962 (0.611, 1.516)
28.29 (3.14)
1.574 (0.997, 2.486)
8-9
35.79 (5.23)
1.992 (1.090, 3.643)
39.67 (5.91)
3.047 (1.651, 5.625)
9-10
51.09 (8.14)
4.135 (2.040, 8.382)
45.17 (8.34)
5.387 (2.278, 12.741)
≥ 10
47.75 (7.58)
4.482 (2.210, 9.089)
45.48 (8.99)
5.662 (2.099, 15.276)
Duration of DM (years)
No hypertension
Hypertension
0.6858
New onset
13.17 (2.10)
1 (reference)
23.73 (2.74)
1 (reference)
< 5
11.39 (2.83)
0.827 (0.425, 1.608)
25.48 (2.74)
0.987 (0.66, 1.477)
5-10
22.03 (4.45)
1.941 (1.031, 3.655)
28.72 (3.55)
1.169 (0.748, 1.827)
10-15
19.92 (4.61)
1.689 (0.855, 3.334)
40.21 (4.56)
1.938 (1.206, 3.114)
15-20
19.78 (5.81)
1.601 (0.732, 3.501)
36.28 (5.53)
1.448 (0.82, 2.558)
≥ 20
42.89 (7.31)
4.648 (2.269, 9.518)
59.05 (4.16)
3.338 (2.127, 5.238)
Hemoglobin A1C (%)
0.7324
< 6.5
16.55 (3.08)
1 (reference)
29.14 (2.88)
1 (reference)
6.5-7
8.00 (1.78)
0.426 (0.233, 0.782)
21.3 (2.24)
0.686 (0.481, 0.978)
7-8
15.05 (2.59)
0.872 (0.475, 1.601)
33.67 (2.98)
1.421 (0.962, 2.098)
8-9
27.97 (5.87)
1.98 (0.961, 4.078)
45.71 (5.38)
2.553 (1.551, 4.201)
9-10
36.83 (8.11)
3.323 (1.44, 7.669)
65.61 (7.89)
5.473 (2.588, 11.574)
≥ 10
35.68 (7.52)
3.381 (1.469, 7.782)
58.71 (8.69)
6.784 (3.019, 15.246)
DISCUSSION
This cross-sectional population-based study aimed to investigate the relationship of DM duration and hyperglycemia severity with DKD prevalence among patients with DM. The overall DKD prevalence among these patients was 25.5%, indicating that approximately 1 out of 4 patients with DM have DKD. Moreover, the adjusted ORs for the risk of DKD (defined by eGFR < 60 mL/min/1.73 m2 or albuminuria ≥ 30 mg/g) increased as diabetes duration increased or glycemic control worsened compared to those with newly diagnosed diabetes or normal HbA1c.
DKD prevalence estimation is essential to develop CKD management and prevention strategies for end-stage kidney disease in patients with diabetes[18]. In the United States National Health and Nutrition Examination Survey from 2009 to 2014, the estimated prevalence of CKD was 25% in participants with diabetes[19]. Similarly, our study also showed approximately 25.5% of DKD prevalence in patients with diabetes. However, among individuals with diabetes, DKD prevalence varies widely between countries, with estimates ranging from 26% to 53% in Asian countries and from 28% to 69% in the United States and European countries[20-26]. These variations in DKD prevalence reflect differences in age and sex distributions in DKD definition and creatinine determination methods besides the true regional differences[27]. Most conducted studies were cross-sectional with a different mean follow-up duration, not considering the duration of diabetes or degree of hyperglycemic control when evaluating the prevalence of DKD in patients with diabetes.
A Saudi registry study found that DKD prevalence increased with DM duration, with the highest prevalence reported in DM lasting > 15 years[28]. In 5102 participants with diabetes in the United Kingdom Prospective Diabetes Study with a median of 15 years of follow-up, 38% and 29% of patients developed albuminuria and kidney impairment, respectively[10]. A previous study using the KNHANES dataset from 2008 to 2011 also showed that longer diabetes duration was associated with an increased risk of CKD[26]. However, previous studies neither stratified the duration of diabetes nor adjusted for other potential DKD-related confounding factors. Although the overall prevalence of DKD was 25.5% in our study, longer duration of diabetes and higher HbA1c were associated with increased prevalence and risk of DKD in patients with diabetes in a dose-dependent manner. Our results showed that DKD prevalence increased to 54% for those with DM lasting > 20 years. Moreover, our findings indicated that the risk of DKD increased with the duration of diabetes, showing a 1.8-fold and 3.8-fold increase for those with diabetes lasting 10-15 years and > 20 years, respectively. Therefore, long-lasting exposure to the diabetes milieu is associated with the risk of DKD.
Albuminuria exhibited a higher prevalence and increased risk earlier than eGFR decline. When analyzing DKD as two separate clinical manifestations, eGFR and albuminuria, the risk of albuminuria was significantly elevated for DM lasting 10-15 years compared to new-onset diabetes, whereas the risk of eGFR decline showed a significant increase for DM lasting > 20 years. Although microalbuminuria lacks the sensitivity and specificity to accurately predict kidney outcomes for patients with diabetes, albuminuria is the most commonly used biomarker of DKD and may reflect it earlier than eGFR[9,29].
Hyperglycemia causes kidney injury by generating advanced glycation end products and inducing oxidative injury and hypoxia[30]. HbA1c remains the gold standard for monitoring glycemic control in patients with diabetes. In this study, the risk of DKD was 2.3-fold and 4.9-fold higher with HbA1c of 8%-9% and > 10%, respectively. Therefore, uncontrolled hyperglycemia significantly increases the risk of DKD in diabetes patients. Accordingly, the landmark study of Diabetes Control and Complications and Trial established that tight glucose control reduced the risk of DKD[31]. However, HbA1c is limited by its delayed reflection of dysglycemia, variability due to underlying comorbidities, and a lack of specificity in differentiating between fasting and postprandial hyperglycemia[32]. Although the risk of albuminuria increased progressively with increased HbA1c, a significant association with eGFR decline was not observed. The reason for this discrepancy might be that transient hyperglycemia or hypoglycemia after a period of poor glucose control and alongside increased glycemic variability, not reflected in HbA1c, has long-term effects on the development and progression of kidney dysfunction[14,33].
Elevated blood pressure is an important risk factor for the development of DKD in both type 1 and type 2 diabetes[34]. Hypertension and diabetes have a synergistic influence on the risk of new-onset DKD[35]. However, our subgroup analyses showed that the relative risk of DKD attributable to diabetes, based on increased diabetes duration and HbA1c levels, did not significantly differ between participants with or without hypertension. Further prospective studies are needed to determine the association between hypertension status and the risk of DKD according to the duration and severity of diabetes. Furthermore, future studies should evaluate whether blood pressure control in patients with diabetes can decrease the risk of DKD.
Our study has several limitations. First, being a cross-sectional study, it did not establish a causal relationship between DKD and DM duration and severity. Second, the UACR was assessed using a single random urine sample. Thus, we could not conduct repeated measurements to determine albuminuria. Third, the definition of DKD in our study is based solely on the presence of albuminuria or low eGFR in patients with DM rather than on a pathological diagnosis. This definition has been used in most epidemiological studies because performing kidney biopsies on all CKD patients with diabetes is not feasible. Fourth, the generalizability of the results should be approached with caution, as the study participants were exclusively from the Korean population. Lastly, although type 1 and 2 diabetes have different epidemiological characteristics, we could not distinguish between the two types of diabetes in our study. Despite these limitations, the strength of our study is the representative sample of the noninstitutionalized Korean civilian population. Further longitudinal studies including other ethnic groups are required to explore the effects of DM duration and the severity of hyperglycemia on the development of DKD, to better understand the link between diabetes and DKD.
CONCLUSION
Our study found that approximately 25% of Korean adults with diabetes have DKD. The risk of developing DKD significantly increases in patients with diabetes lasting > 10 years or HbA1c > 8%. Notably, the risk of albuminuria, an early marker of DKD, increased during earlier stages of DM and in less severe hyperglycemia compared to the decline in kidney function. These findings highlight the necessity of vigilant kidney function monitoring in patients with long-standing diabetes or poor glycemic control.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Endocrinology and metabolism
Country of origin: South Korea
Peer-review report’s classification
Scientific Quality: Grade A, Grade A
Novelty: Grade A, Grade B
Creativity or Innovation: Grade A, Grade B
Scientific Significance: Grade A, Grade B
P-Reviewer: Horowitz M; Wang WS; Younes S S-Editor: Lin C L-Editor: A P-Editor: Zhang XD
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Low SK, Sum CF, Yeoh LY, Tavintharan S, Ng XW, Lee SB, Tang WE, Lim SC. Prevalence of Chronic Kidney Disease in Adults with Type 2 Diabetes Mellitus.Ann Acad Med Singap. 2015;44:164-171.
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Barutta F, Bellini S, Canepa S, Durazzo M, Gruden G. Correction to: Novel biomarkers of diabetic kidney disease: current status and potential clinical application.Acta Diabetol. 2022;59:439-441.
[RCA] [PubMed] [DOI] [Full Text][Reference Citation Analysis (0)]
