1. Introduction
Diabetes mellitus is a chronic hyperglycemic condition, a metabolic disease, and it is due to metabolic disorders.[ 1 , 2 ] The incidences of diabetes is higher in recent eras.[ 3 ] According to the International Diabetes Federation, there will be a huge numbers of patients with diabetes in the future.[ 4 ] Diabetes is a chronic disease and has huge pressure on patients and the medical system, especially for patients with diabetic complications, for example, diabetic nephropathy (diabetes related renal impairment).[ 5 ] The life expectancy of patients with diabetes, especially patients with diabetic complications, is shorter than those of normal individuals.[ 6 ] One diabetic complication, for example, is diabetic nephropathy and it is responsible for cardiovascular diseases.[ 7 ] COVID-19 patients who had diabetes suffered a lot and had higher mortality than normal COVID-19-positive patients.[ 8 ] To improve the quality of life of patients with diabetes, it is necessary to understand the factors that are associated with diabetic nephropathy (diabetic kidney injury or diabetic kidney disease). Diabetic nephropathy is associated with inflammation.[ 9 ] Neuregulin-4[ 10 ] and the other biomarkers[ 11–13 ] have been reported to be associated with diabetic nephropathy. An early biomarker may proceed earlier diagnosis, treatment reduces diabetic nephropathy prevalence and slows diabetic nephropathy progression.[ 11 ] The prevalence of diabetic nephropathy among Chinese diabetic Mellitus patients is 22%.[ 14 ] However, the prevalence and association of diabetic nephropathy among newly diagnosed patients with diabetes in Hebei province of China are not available.
Globulin is a serum protein called immunoglobulin because it is associated with immune functions.[ 15 ] The main components of globulin are α1 , α2 , β , and γ . Globulin is associated with liver function.[ 16 ] Cross-sectional studies reported that urinary globulin has positive association with diabetic nephropathy.[ 15 , 17 ] A further case-control study is required to investigate the role of diabetic complication besides of urinary globulin in diabetic nephropathy.
The objectives of the single-center case-control study were to find the prevalence of diabetic nephropathy in newly diagnosed patients with diabetes in Hebei province of China and to develop the association between clinicopathological parameters of patients with diabetes and the prevalence of diabetic nephropathy.
2. Materials and methods
2.1. Ethics approval and consent to participate
The designed protocol (approval no. HHTCM2022046 dated 15 July 2018) was approved by the Hebei Hospital of Traditional Chinese Medicine review board. Written informed consent was taken from participants before the study. The study follows the law of China and the V2008 Declarations of Helsinki.
2.2. Inclusion criteria
Only newly diagnosed patients with diabetes aged more than 18 years were included in the study.
2.3. Exclusion criteria
Patients who had no data for urinary globulin (immunoglobulin), albumin, and/or creatinine in the records were excluded from the study. Patients with kidney diseases other than diabetic nephropathy (e.g., kidney cancer) were excluded.
2.4. Outcome measures
Demographic variables (gender, age, and ethnicity), anthropometric parameters (height, body weight, waist circumference, and body mass index [BMI]), health-related behaviors (drinker and smoker), and clinicopathological parameters (blood glucose, glycosylated hemoglobin, urine albumin, urine creatinine, liver functions enzymes) were evaluated.
2.5. Diabetes mellitus
The fasting blood glucose of 7.0 mM/L or more and/or glycosylated hemoglobin 6.5 mM/L or more was considered diabetes mellitus.[ 18 ]
2.6. Diabetic nephropathy
If the urine albumin to creatinine ratio was 30 or more (microalbuminuria ) then patients were considered diabetic nephropathy.[ 15 ]
2.7. Patients without nephropathy
If the urine albumin to creatinine ratio was less than 30 (non-albuminuria) then patients were considered without nephropathy.[ 15 ]
2.8. Body mass index
From 18.5 to 24.9 kg/m2 was considered a normal BMI, from 25 to 29.9 kg/m2 was considered overweight, and 30 kg/m2 or more was considered obese.[ 15 ]
2.9. Health-related behaviors
A person who had more than 12 drinks per year was considered a drinker.[ 19 ] A person who smokes more than 100 cigars was considered a smoker.[ 20 ]
2.10. Hypertension
Systolic blood pressure of 140 mm Hg or more and/or diastolic blood pressure of 90 mm Hg or more was considered hypertension.[ 21 ] Patients taking antihypertensive agents were classified as hypertensive subjects.
2.11. Urinary globulin
ELISA test (Thermo Fisher Scientific, Waltham, MA) was used for the measurement of urinary globulin (immunoglobulin).
The other clinicopathological parameters were evaluated by the ELISA test method.
2.12. Statistical analysis
Categoric variables are depicted as frequency (percentage). Continuous normal variables are depicted as mean ± standard deviation (SD). Continuous non- normal variables are depicted as median (range). InStat 3.01, GraphPad Software, San Diego, CA was used for statistical analysis purposes. The Fisher’s exact test or the Chi-Square test was used for the statistical analysis of categoric variables. An unpaired t test was used for statistical analysis of continuous normal variables with equal SDs and for normal variables with unequal SDs, an unpaired t test with Welch correction was used for statistical analysis. For continuous abnormal variables, the Mann–Whitney test was used for statistical analysis. The distribution of SDs within the group among continuous variables was checked whether distributed equally or not using the Brown–Forsythe test. Distribution of variables whether normal or non-normal were checked visually by the histogram method. Multiple regression analysis was performed to establish an association between outcome measures and diabetic nephropathy.[ 22 ] All results were considered significant for less than .05 P value at a 95% confidence interval.
3. Results
3.1. Study population
From January 15, 2018, to May 17, 2020, a total of 352 patients were diagnosed with diabetes mellitus (fasting blood glucose ≥ 7.0 mM/L and/or glycosylated hemoglobin ≥ 6.5 mM/L) at the Hebei Hospital of Traditional Chinese Medicine, Shijiazhuang, Hebei, China, and the referring hospitals. Among 352 patients, 47 patients had no data for urinary globulin, albumin, and/or creatinine in their records. Therefore, these were excluded from the study. Demographic variables, anthropometric parameters, and clinicopathological parameters of a total of 305 patients with diabetes were included in the analysis. The summary diagram of the study is presented in Figure 1 .
Figure 1.: The summary diagram of the study. Diabetic nephropathy: the urine albumin to creatinine ratio ≥ 30 (microalbuminuria ). Patients without nephropathy: the urine albumin to creatinine ratio < 30.
3.2. Outcome measures
A total of 206 (68%) males and 99 (32%) females from age 46 to 71 years were included in the analysis. The prevalence of diabetic nephropathy was 44%. No significant differences were reported for demographic variables of patients with diabetes between those who had diabetic nephropathy (case group, urine albumin to creatinine ratio ≥ 30) and patients without nephropathy (control group, urine albumin to creatinine ratio < 30; P > .05 for all). Female to male ratio was 1: 1.7 in the case group (Table 1 ).
Table 1 -
Demographics variables of patients with diabetes.
Parameters
Total
Diabetic nephropathy
Patients without nephropathy
Comparison between groups
Number of patients with diabetes
305
135
170
P value
95% CI
Df
Gender
Male
206 (68)
85 (63)
121 (71)
.1406 (Fisher’s exact test)
0.6336–1.053
N/A
Female
99 (32)
50 (37)
49 (29)
Age (yr)
Minimum
46
46
46
<.1319 (Mann–Whitney test)
N/A
N/A
Maximum
75
75
74
Median
61
59
61
Ethnicity
Han Chinese
267 (88)
119 (88)
148 (87)
.9072 (χ2 test)
N/A
1
Mongolian
34 (11)
14 (10)
20 (12)
Tibetan
4 (1)
2 (2)
2 (1)
Categoric variables are presented as frequency (percentage). Continuous abnormal variables are depicted as median (range).
P value < .05 is considered significant.
Diabetic nephropathy: the urine albumin to creatinine ratio ≥ 30 (microalbuminuria ).
Patients without nephropathy: the urine albumin to creatinine ratio < 30.
CI = confidence interval (using the approximation of Katz.), Df = degree of freedom, N/A = not applicable, χ2 -test = Chi-Square test.
Patients with diabetic nephropathy had higher body weight, waist circumference, and BMI than those of patients without nephropathy (P < .05 for all, t test, Table 2 ).
Table 2 -
Anthropometric parameters of patients with diabetes.
Parameters
Total
Diabetic nephropathy
Patients without nephropathy
Comparison between groups
Number of patients with diabetes
305
135
170
P value
95 % CI
Df
Height (cm)
163.21 ± 13.22
160.15 ± 13.17
162.14 ± 17.18
.2674 (Unpaired t test)
−1.534 to 5.514
303
Body weight (kg)
60.18 ± 11.12
62.51 ± 9.12
57.12 ± 10.15
<.0001 (Unpaired t test with Welch correction)
−7.566 to −3.214
298
Waist circumference (cm)
109.52 ± 6.19
110.11 ± 9.15
107.15 ± 4.15
.0006 (Unpaired t test with Welch correction)
−4.636 to −1.284
177
Body mass index (kg/m2 )
25.47 ± 3.75
26.12 ± 4.15
24.51 ± 3.12
.0002 (Unpaired t test with Welch correction)
−2.457 to −0.7631
242
Variables are presented as mean ± standard deviation (SD).
The P value < .05 is considered significant.
Diabetic nephropathy: the urine albumin to creatinine ratio ≥ 30 (microalbuminuria ).
Patients without nephropathy: the urine albumin to creatinine ratio < 30.
CI = confidence interval (using the approximation of Katz.), Df = degree of freedom.
Health-related behaviors were the same among patients with diabetes either with nephropathy or patients without nephropathy (Table 3 , P > .05 for both, Fisher’s exact test).
Table 3 -
Health-related behaviors of patients with diabetes.
Parameters
Total
Diabetic nephropathy
Patients without nephropathy
Comparison between groups
Number of patients with diabetes
305
135
170
P value
95% CI
Drinker
165 (54)
75 (56)
90 (52)
.7287
0.8226–1.367
Smoker
169 (55)
78 (58)
91 (54)
.4878
0.8522–1.423
Variables are presented as frequency (percentage).
Fisher’s exact test was used for statistical analysis.
The P value < .05 is considered significant.
Diabetic nephropathy: the urine albumin to creatinine ratio ≥ 30 (microalbuminuria ).
Patients without nephropathy: the urine albumin to creatinine ratio < 30.
CI = confidence interval (using the approximation of Katz.), N/A = not applicable.
All clinicopathological parameters were more abnormal for diabetic nephropathic patients than those of patients without nephropathy (P < .0001, for all, Mann–Whitney test or Fisher exact test, Table 4 ).
Table 4 -
Clinicopathological parameters of patients with diabetes.
Parameters
Total
Diabetic nephropathy
Patients without nephropathy
Comparison between groups
Number of patients with diabetes
305
135
170
P value
Hypertension
205 (67)
120 (89)
85 (50)
<.0001* (Fisher’s exact test)
% HbA1C
Minimum
6.5
6.5
6.5
<.0001 (Mann–Whitney test)
Maximum
8
8
7.4
Median
6.8
7
6.8
Fasting blood glucose (mM/L)
Minimum
7
7
7
<.0001 (Mann–Whitney test)
Maximum
7.8
7.8
7.7
Median
7.25
7.4
7.2
Urine albumin (g/L)
Minimum
40
40
40
<.0001 (Mann–Whitney test)
Maximum
46
46
44
Median
42
43
41
Urine creatinine (g/L)
Minimum
1000
1000
1400
<.0001 (Mann–Whitney test)
Maximum
1500
1100
1500
Median
1420
1045
1470
Urine albumin to creatinine ratio (μg/mg)
Minimum
26.67
36.53
26.67
<.0001 (Mann–Whitney test)
Maximum
45.1
45.1
29.63
Median
29.05
40.76
28
Alanine transaminase (U/L)
Minimum
14
14
15
.009 (Mann–Whitney test)
Maximum
32
31
32
Median
26
25
26
High-density lipoprotein (mM/L)
Minimum
0.9
0.9
1
<.0001 (Mann–Whitney test)
Maximum
1.9
1.8
1.9
Median
1.2
1.1
1.3
Aspartate transaminase (U/L)
Minimum
14
14
15
.0086 (Mann–Whitney test)
Maximum
32
31
32
Median
26
25
26
Urinary globulin (immunoglobulin; g/L)
Minimum
25
25
26
<.0001 (Mann–Whitney test)
Maximum
40
40
32
Median
30
36
29
Alkaline phosphatase (U/L)
Minimum
55
60
55
<.0001 (Mann–Whitney test)
Maximum
100
100
90
Median
82
86
81
Blood urea nitrogen (mM/L)
Minimum
3
4
3.5
<.0001 (Mann–Whitney test)
Maximum
10
10
8.8
Median
6
8
5.7
Categoric variables are presented as frequency (percentage). Continuous abnormal variables are presented as median (range).
The P value < .05 is considered significant.
Diabetic nephropathy: the urine albumin to creatinine ratio ≥ 30 (microalbuminuria ).
Patients without nephropathy: the urine albumin to creatinine ratio < 30.
* 95% CI: confidence interval (using the approximation of Katz.): 2.413 to 6.311, HbA1C: Glycated hemoglobin.
A total of 285 (93%) were taking one or two oral hypoglycemic agents. A total of 130 (96%) from the diabetic nephropathy, case group and 155 (91%) patients without the nephropathy, control group were taking one or two oral hypoglycemic agents (P = .1018, Fisher’s exact test).
3.3. Association between outcome measures and diabetic nephropathy
Abnormal urinary globulin (P = .041, multivariate analysis) was reported as a significant biomarker for diabetic nephropathy. Aspartate transaminase (P = .0651, multivariate analysis), alkaline phosphatase (P = .0661, multivariate analysis), hypertension (P = .0821, multivariate analysis), and blood urea nitrogen (P = .0842, multivariate analysis) were not significantly associated with diabetic neuropathy. However, they are near the statistical cutoff value. Association between outcome measures and diabetic nephropathy is reported in Table 5 .
Table 5 -
Association between outcome measures and diabetic nephropathy.
Parameters
Odd ratio
95 % CI
P value
Body weight (≥60 kg vs <60 kg)
0.9854
0.8524–1.0112
.0681
Waist circumference (≥95 cm vs < 95 cm)
0.8245
0.7421–0.9852
.0692
Body mass index (Obese vs non-obese)
0.9254
0.8254–0.9852
.0741
Hypertension (hypertensive vs non-hypertensive)
0.8214
0.7142–0.8123
.0821
% HbA1C (≥6.5 vs <6.5)
0.6524
0.8214–0.0941
.0714
Fasting blood glucose (≥7 mM/L vs < 7 mM/L)
0.7422
0.9214–0.9824
.0821
Alanine transaminase (abnormal vs normal)
0.8122
0.0821–0.0824
.0824
High-density lipoprotein (abnormal vs normal)
0.1421
0.0841–0.9849
.0952
Aspartate transaminase (abnormal vs normal)
0.8541
0.7741–0.8841
.0651
Urinary globulin (abnormal* vs normal)
1.1231
1.2451–1.8521
.041
Alkaline phosphatase (abnormal vs normal)
0.8411
0.7841–0.9841
.0661
Blood urea nitrogen (abnormal vs normal)
0.9411
0.8414–0.9841
.0842
Multivariate analysis,
An odd ratio of more than 1 and a P value less than .05 was considered significant.
Patients without nephropathy were considered the control group.
CI = confidence interval, HbA1C = Glycated hemoglobin.
* Significant biomarker for diabetic neuropathy.
4. Discussion
The current study reported that higher urinary globulin is associated with diabetic nephropathy. The results of the current study are parallel with those of cross-sectional studies.[ 15 , 17 , 23 ] A cross-sectional study[ 15 ] was performed on the Chinese population on the NHANES official website, but inclusion criteria were limited. A cross-sectional study performed on the Egyptian population[ 17 ] had a small sample size. A cross-sectional study performed on the Chinese population[ 23 ] was more skewed toward all diabetic complications. Renal injuries increase the urinary concentration of globulin.[ 24 ] Also, available studies[ 15 , 17 , 23 ] are cross-sectional studies that provide differences, not true changes.[ 23 ] Urinary globulin is a biomarker for the prognosis of diabetic nephropathy.
Aspartate transaminase and alkaline phosphatase were not significantly associated with diabetic neuropathy. However, they are near the statistical cutoff value. Not only kidney functions but urine globulin is also associated with liver functions.[ 16 ] Besides urinary globulin, the duration of diabetes and the presence of other diabetic complications are also essential parameters for diabetic nephropathy.
Hypertension and blood urea nitrogen were not significantly associated with diabetic neuropathy. However, they are near the statistical cutoff value. Diabetic nephropathy complication is very common in hypertensive patients.[ 25 ] Since some antihypertensive agents such as angiotensin receptor blockers could affect urinary albumin excretion, these medications were considered an important clinical parameter for microalbuminuria .
Higher numbers of male patients reported diabetic neuropathy than female patients. The results of gender bias in the prevalence of diabetic neuropathy are consistent with those of cross-sectional studies[ 15 , 17 , 23 ] and a meta-analysis[ 14 ] but are not consistent with those of a cross-sectional study.[ 26 ] More awareness and early diagnosis of diabetic neuropathy among Chinese males than among Chinese females are responsible for the higher prevalence of diabetic neuropathy in males.[ 27 ] Also, smoking which is a risk factor for diabetic nephropathy in Chinese diabetic males,[ 28 , 29 ] is reported more common in males than females. Further sex-oriented research is required.
The prevalence of diabetic nephropathy in the Hebei province of China was reported higher than a meta-analysis on patients with type 2 diabetes in the other provinces of China (44% vs 22%).[ 14 ] Also, 20 to 30 percent rate of diabetic kidney disease has been reported in the Turkish patients with type 2 diabetes.[ 30 ] The prevalence of diabetic nephropathy shows geographical and gender variation in China.[ 14 ] National strategies for screening and treatment of diabetic nephropathy are required in China.
The limitations of the study include the single center nature of the work, the study applies to the Han Chinese population, and data are not generalized. Furthermore, patients were diabetic only, the association between urinary globulin and non-diabetic kidney damage is not developed. Besides urinary globulin, the association between serum globulin levels and diabetic nephropathy is not developed. The association of the other pathological parameters was found insignificant, but the justification for the same was not provided. Patients with a urine albumin to creatinine ratio ≥ 30 were enrolled in the study. However, patients with diabetes may have renal damage without microalbuminuria .[ 11 ] Since patients with diabetic nephropathy had a very low level of urinary albumin excretion, the presence of nephropathy must be determined by multiple measurements of urinary albumin. In addition, it is questionable that patients with normo-albuminuria and overt renal dysfunction were classified into patients without the nephropathy group. To suggest the diagnostic value of urinary globulin for diabetic nephropathy, sensitivity and specificity analyses are essential. The diagnostic benefits of urinary globulin with those of known biomarkers such as urinary β 2 -microglobulin are required to compare. In addition, it has been revealed that urinary levels of β 2 -microglobulin are increased in diabetic nephropathy.[ 31 ]
5. Conclusion
The prevalence of diabetic nephropathy in the Hebei province of China is reported higher than in the other provinces of China. Urinary globulin excretion is associated (a weak association) with the presence of nephropathy defined by urinary albumin excretion in patients with diabetes. Urinary globulin is a biomarker for the prognosis of diabetic nephropathy. Urinary globulin may provide information for a biopsy of the kidney in cases of patients with diabetes. The duration of diabetes and the presence of other diabetic complications are also essential parameters for diabetic nephropathy. Han Chinese males in the Hebei province of China are more susceptible to diabetic nephropathy than females if diabetic. Antihypertensive agents could affect urinary albumin excretion.
Acknowledgments
The authors are thankful to the medical and non-medical staff of the Hebei Hospital of Traditional Chinese Medicine, Shijiazhuang, Hebei, China.
Author contributions
Conceptualization: Xiaoya Ren, Xianghui Yu.
Formal analysis: Yange Tang.
Funding acquisition: Ninglin Kang, Yange Tang.
Investigation: Xiaolei Li.
Methodology: Xianghui Yu, Xiaolei Li, Yange Tang, Jie Wu.
Resources: Xiaoya Ren, Xianghui Yu, Yange Tang.
Software: Xiaoya Ren, Xianghui Yu, Jie Wu.
Supervision: Xiaoya Ren, Ninglin Kang, Jie Wu.
Validation: Xiaolei Li, Jie Wu.
Visualization: Ninglin Kang, Xiaolei Li.
Writing – original draft: Xiaoya Ren.
Writing – review & editing: Xiaoya Ren.
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