Prolonged elevated postprandial sugar augments severity in kidney disease: a North Indian hospital-based study

Abstract

Aim: Diabetes plays a major role in progression of renal failure. The risk-factor profile changes during the progression of chronic kidney disease (CKD) from mild/moderate to end-stage renal disease. The relationship between glycemic indices, blood pressure, body mass index (BMI) and age at diagnosis in Indians has been less investigated. We assessed association of these risk factors with CKD stages in Indian population. Methods: This study was carried out on patients (n = 162) who were diagnosed with CKD and normal control group (n = 155). For BMI, National Institutes for Health criteria were used to categorize the patients. Result: The mean age of CKD patients were significantly increased with the advancement of stage. BMI, systolic blood pressure (SBP), postprandial sugar level (PP), urea and creatinine were also significantly higher with elevated stages, whereas no differences were observed in diastolic blood pressure (DBP) and fasting blood sugar (FBS). The logistic regression study gave a significant result (p = 0.000) when we compared the group of CKD patients with established/prolonged postprandial blood sugar. It was independently associated with mild CKD [odds ratio (OR) = 5.213, 95% confidence interval (CI) = 2.06–13.21, p = 0.000], moderate CKD (OR = 7.724, 95% CI = 4.05–14.74, p = 0.000) and severe CKD (OR = 7.610, 95% CI = 4.03–14.36, p = 0.000). Conclusion: SBP and PP were the best predictors of prevalent nephropathy in this population, while DBP and FBS were found to be less effective. This may have implication for kidney disease risk stratification and protection.

• Chronic kidney disease
• nephropathy
• postprandial sugar
• systolic blood pressure

Introduction

The worldwide prevalence of diabetes is expected to increase from 4% in 1995 to 5.4% by 2025.1 Currently, the countries with the largest number of diabetic patients are India, China and USA. The acute and chronic complications of diabetes mellitus are major causes of hospital admissions. Asian patients have shown evidence of macro- and microvascular disease at the time of diagnosis of diabetes when compared to Europeans.2 Diabetes is the most common cause of kidney failure, accounting for ∼44% of new cases.3 Even when diabetes is controlled, the disease can lead to chronic kidney disease (CKD) and kidney failure. About 25 million people in the USA have diabetes and ∼180,000 people are suffering with kidney failure as a result of diabetes.4 The occurrence of nephropathy in India was less (8.9% in Vellore, 5.5% in Chennai) when compared with the occurrence of 22.3% in Asian Indians in the UK.5

The World Health Organization (WHO) has identified diabetes as a major health problem in Asia and, in this context, prevention of diabetes has become a high priority of health policies.6,7 The root of the problem is the current lifestyle causing visceral obesity; the long-term solution may be due to major changes in lifestyle.8,9 Besides causing premature mortality and morbidity and lowering the quality of life, it is a disease which imposes huge economic burden not only on the patients and their families but also in general on the health care system and society too.

The benefits of early diagnosis of the kidney disease extend beyond the kidney itself. Appropriate management of the co-morbid conditions reduces not only the overall and cardiovascular mortality but also improves the quality of life itself, reduces the economic burden and provides adequate time for the psychological, medical and economic preparation for renal replacement therapy.

Nevertheless, the dramatic increase of advanced diabetic nephropathy in type 2 diabetes requires additional measures targeted more specifically to the kidney. According to the recent recommendations of the American Diabetes Association and the National Kidney Foundation, two practically accessible parameters are critical for the detection10 and follow-up11 of CKD in patients with diabetes: the albumin excretion rate (AER) and the glomerular filtration rate (GFR) as estimated (e-GFR) by the Cockcroft–Gault formula (CG) or the Modification of Diet in Renal Disease (MDRD) equation. Sedentary lifestyle leads toward obesity and high glucose level in blood. Obesity is indexed by body mass index (BMI), and the point of interest is in the adverse health effects of abdominal fat because of its direct relationship with visceral fat.12

Elevated 2-h glucose concentration is not only an important risk factor for the development of type 2 diabetes, but also for cardiovascular disease (CVD).13 Prolonged postprandial glucose (PP) excursions are risk markers of insulin resistance and dyslipidemia that collectively impact on CVD risk14 that lead to CKD.

In this context, we hypothesized that higher established postprandial sugar, CVD and BMI may be increasing the severity of the kidney disease. Thus, the aim of this study was to examine the effect of the elevated postprandial glucose, CVD and BMI on the presentation and subsequent pathologic staging of kidney disease. In this study, n = 162 patients and n = 155 age-matched normal control groups were recruited, we determined isotopic GFR (i-GFR) by 51Cr-EDTA clearance (CG method) and classify the patients into three groups according to the degree of the severity.

Materials and methods

Study of population and clinical evaluation of patients

This consecutive cluster study included all patients who attended the outpatient department for kidney disease at the Department of Nephrology, Sir Sunderlal Hospital Banaras Hindu University, Varanasi, India, from January 2008. Exclusion criteria included patients <18 years of age, and patients who were mentally incapable of furnishing their own consent.

If the patient met the appropriate criteria, we visited the patient prior to treatment to explain the study and asked for patient’s participation. After receiving the formal consent from the patient, we conducted 30-min interview with the patient. Data involving presentation, diagnosis and staging were collected from the office and hospital charts, and face-to-face interview with the patient. The interview was based on pre-designed questionnaire that included questions about height and weight, age, health care and utilization, health habits, and physical activity level. This study was carried out on patients (n = 162) who were diagnosed with CKD and normal control group (n = 155) (Figure 1).

Figure 1. Distribution of CKD patient’s stages with normal control group in the study cohort (n = 317).

Estimation of BMI

According to WHO (1998),15 the BMI cutoff in Europeans for overweight (≥25 kg/m²) and obesity (≥30 kg/m²) are higher than Asian-pacific region. Steering committee (WHO Western Pacific Region, 2000;16 the international association for the study of obesity and international obesity task force) recommended the cutoff for overweight (≥23 kg/m²) and obesity (≥25 kg/m²) for Asians. However, the exact classification criteria are shown in Table 1.15,16 BMI was measured at the time of hospital admission for treatment and the above criteria were used to categorize patients.

Table 1. Classification of BMI in adult Europids (WHO, 1998)15 and Asians (WHO, 2000).16

	BMI (kg/m^2)
Classifications	Europids	Asians
Underweight	<18.5	<18.5
Normal range	18.5–24.9	18.5–22.9
Overweight	≥25	≥23
At risk	25.0–29.9	23.0–24.9
Obese I	30.0–34.9	25.0–29.9
Obese II	35.0–39.9	≥30
Obese III	≥40

GFR estimations

Single serum creatinine measurements were performed the day before the isotopic measurement of i-GFR to calculate using CG formula.17

As this equation was originally designed to estimate creatinine clearance expressed in milliliters per minute, the results were adjusted to body surface area calculated by the formula of Dubois and Dubois.18

Kidney disease staging

The stages of CKD are mainly based on measured or e-GFR. There are five stages but kidney function is normal in Stage 1 and Stage 5 (end stage). In our study, we classify our patient in three groups: mild CKD (n = 60–89), moderate CKD (n = 30–59) and severe CKD (n = 15–29) on the basis of GFR [All GFR value normalized to an average surface area (size) of 1.73 m²].

Statistical analysis

Presentation and pathologic factors were compared among the CKD groups. Two-tailed tests were used at all times, and statistical significance was set a priori at p < 0.05. Statistical analyses were performed with SPSS for Windows 16.0 (Chicago, IL). All univariate analyses used Student’s t-test or χ² tests, as appropriate. Multivariate analysis, by logistic regression, was performed to evaluate the postprandial sugar associated with the severity of CKD.

Results

The baseline characteristics of patients

The characteristics of the patients at baseline are shown in Table 2. The mean age of severe CKD (60.8 ± 9.1 years) patients was significantly higher (p < 0.000) than moderate CKD (56.7 ± 9.1 years), mild CKD (51.0 ± 10.9) and normal patients (55.2 ± 10.6). BMI, systolic blood pressure (SBP), postprandial sugar level (PP), urea and creatinine were significantly higher in severe CKD patients in comparison to other groups [(p < 0.05), whereas no differences were seen in diastolic blood pressure (DBP) and fasting blood sugar (FBS)].

Table 2. Characteristics of CKD patients at baseline and laboratory data during the follow-up period (mean with slandered deviation and 95% CI for mean).

	Normal n = 155		Mild CKD n = 23		Moderate CKD n = 68		Severe CKD n = 71
Characteristics	Mean ± SD	95% CI for mean	Mean ± SD	95% CI for mean	Mean ± SD	95% CI for mean	Mean ± SD	95% CI for mean	p Value
Age (years)	55.2 ± 10.6	53.5–56.9	51.0 ± 10.9	46.3–55.8	56.7 ± 9.1	54.5–58.9	60.8 ± 9.1	58.7–63.0	0.000
BMI (kg/m^2)	23.9 ± 4.3	23.3–24.7	25.7 ± 3.6	24.2–27.3	25.0 ± 3.2	24.2–25.8	25.4 ± 3.8	24.5–26.3	0.025
Systolic BP (mmHg)	127.4 ± 18.4	124.5–130.9	127.0 ± 19.2	118.7–135.3	132.7 ± 19.4	128.0–137.4	136.0 ± 18.0	131.7–140.2	0.008
Diastolic BP (mmHg)	81.0 ± 11.2	79.2–82.7	79.2 ± 13.7	73.3–85.2	81.3 ± 10.9	78.7–84.0	84.7 ± 12.7	81.7–87.7	0.092
FBS (mg/dl)	126.2 ± 67.5	115.5–136.9	121.2 ± 49.7	99.7–142.7	125.9 ± 49.4	113.9–137.8	139.4 ± 85.2	119.2–159.5	0.496
PP (mg/dl)	135.9 ± 69.0	124.9–146.8	186.3 ± 75.1	153.8–218.7	179.4 ± 72.8	161.8–197.0	182.5 ± 81.7	163.2–201.9	0.000
Urea (mg/dl)	32.0 ± 22.2	28.5–35.5	42.7 ± 21.4	33.4–52.0	54.0 ± 22.7	48.4–59.4	93.7 ± 31.8	86.1–101.2	0.000
Creatinine (mg/dl)	1.6 ± 1.3	1.4–1.8	1.6 ± 0.8	1.2–1.9	2.1 ± 1.0	1.7–2.3	2.4 ± 0.9	2.18-2.62	0.000

Notes: SD = slandered deviation, CI = confidence interval, FBS = fasting blood sugar, PP = postprandial blood sugar.

Association of demographic and clinicopathologic presentation with disease stages

Association of demographic and clinicopathological presentation with disease stages are listed in Table 3. Patients at their latter half of life (>50 years) were significantly prone to severity in kidney disease (p < 0.01). On the basis of BMI, weight groups were found to be independently associated with disease stages. In severe CKD, 39.4% patients belong to Obese I and 12.7% with Obese II but in normal group only 29% individuals belong to Obese I and 5.2% belong to Obese II. When we compared fasting and postprandial blood sugar levels with disease stages, only postprandial blood sugar was found to be independently associated with the advancement of the disease stages (p < 0.000).

Table 3. Association between demographic presentation and pathologic factors with stages of CKD (χ² test).

Characteristics	Normal (n = 155) (%)	Mild CKD (n = 23) (%)	Moderate CKD (n = 68) (%)	Severe CKD (n = 71) (%)	p Value
Age at diagnosis (years)
≤50	36.8	39.1	25.0	15.5	0.006
>50	63.2	60.9	75.0	84.5
BMI (kg/m^2)
Underweight	3.9	0.0	1.5	2.8	0.008
Normal	40	21.7	26.5	26.8
Overweight/at risk	21.9	4.3	17.6	18.3
Obese I	29.0	69.6	50.0	39.4
Obese II	5.2	4.3	4.4	12.7
FBS (mg/dl)
Normal	47.7	47.8	30.9	36.6	0.310
Early diabetes	23.9	21.7	29.4	25.4
Established diabetes	28.4	30.4	39.7	38.0
PP (mg/dl)
Normal	73.5	34.8	26.5	26.8	0.000
Early diabetes	9.0	30.4	47.1	49.3
Established diabetes	17.5	34.8	26.5	23.9

Notes: FBS = fasting blood sugar, PP = postprandial blood sugar.

Established/prolonged postprandial blood sugar was found to be associated with advancement of the disease stage. The increased frequency of moderate and sever CKD presentation persisted on multinomial logistic regression analysis (Table 4), suggesting an independent association between mild CKD [odds ratio (OR) = 5.213, 95% confidence interval (CI) = 2.06–13.21, p = 0.000], moderate CKD (OR = 7.724, 95% CI = 4.05–14.74, p = 0.000) and severe CKD (OR = 7.610, 95% CI = 4.03–14.36, p = 0.000).

Table 4. Association of postprandial sugar with CKD stages (multinomial logistic regression analysis).

		95% CI
Variable	OR	Lower	Upper	p Value
CKD
Normal	1.0	–	–	–
Mild CKD	5.213	2.06	13.21	0.000
Moderate CKD	7.724	4.05	14.74	0.000
Severe CKD	7.610	4.03	14.36	0.000

Note: The reference category is normal postprandial sugar.

Discussion

In the 1980s, however, when past restrictions to accept type 2 diabetics for dialysis were relaxed, admission of type 2 diabetic patients for dialysis increased dramatically; we called this a “medical catastrophe of worldwide dimensions”.19 In the 1990s and in the early years of the first decade after 2000, the rate of admission of type 2 diabetics for dialysis continued to increase. More recently, however, the admission rate has stabilized in the USA [United States Renal Data System (USRDS) Registry, www.usrds.org/adr.htm] as well as in Europe.20

The present study investigated the risk factors associated with the development of subsequent pathological staging of kidney disease that had abnormal renal function. In this study involving 162 patients, 85.8% patients had an eGFR <59 mL/min/1.73 m². However, in the MDRD study, as many as 19% of patients with GFR between 25 and 55 mL/min/1.73 m² experienced improvement or stabilization of their renal function during the 2-year study period.21 A community-based study of CKD among type 2 diabetic Chinese patients in Taiwan showed that the prevalence of CKD was 38%.22 However, Lu et al.23 reported the prevalence of CKD as high as 63.9% in downtown Shanghai, China. The marked variation in the prevalence of CKD might be due to the difference in study cohort characteristics.

Hypertension is a well-recognized risk factor for diabetic patients to develop advancement in CKD stages. However, in the present study, the association with SBP was stronger than those with other BP indices (DBP) based on likelihood ratio comparison. Globally, the risks of kidney diseases afforded by BP have been investigated for prevalent, incident kidney diseases, and for the progression of established disease. The focus has often been on people with non-optimal BPs. Risks have also been assessed across the persistence of BP measurements including in people with diabetes. Comparisons have often examined the issues of whether ambulatory, office, day or night time BPs were similar determinants of nephropathies.24–27 Few studies have directly compared different BP variables from the same measurements for the prediction of nephropathy, including in people with diabetes. These studies have generally emphasized the importance of SBP over DBP in promoting the development and progression of diabetic nephropathy.28 In the Ohasama Study,24 SBP was a significant predictor of microalbuminuria while pulse pressure was not. In a cohort of London individuals with CKD at baseline, pulse pressure was stronger than systolic BP in predicting further decline in kidney function over a mean follow-up duration of 172 days.29

In the present study higher age group, obesity and elevated postprandial glucose affected the patients, although these parameters were higher among subjects with advanced stage of CKD. First, higher postprandial glucose concentrations in the elderly age result from lower rates of glucose disappearance because postprandial suppression of endogenous glucose production and systemic appearance of ingested glucose do not differ between the groups. Postprandial hyperglycemia differs from fasting hyperglycemia in pathophysiology and the risk of adverse outcomes. Postprandial hyperglycemia results mainly from a moderate to severe decrease in muscle insulin sensitivity and late-phase insulin secretary response to oral glucose; whereas fasting hyperglycemia results mainly from a defect in hepatic insulin sensitivity and first-phase insulin response.30 Levitan et al.31 reveled through a meta-analysis of 38 prospective studies, which demonstrated that non-diabetic postprandial hyperglycemia significantly raises the likelihood of cardiovascular events or even death and that the relationship remains after cardiovascular risk factors have been adjusted for. The underlying pathobiologic changes linking elevated postprandial glucose and cardiovascular diseases consist mainly of elevated oxidative stress and endothelial dysfunction, leading to atherothrombotic propensities of elevated postprandial glucose, such as oxidation of LDL cholesterol, vasoconstriction and thrombogenicity.32 Moreover, interventions targeting elevated postprandial glucose are of clinical significance for optimizing comprehensive glycemic control in individuals with diabetes and with impaired glucose regulation to lower the risk of adverse outcomes.33,34

Thus, this study with ample evidence to support the fact that SBP, obesity and postprandial hyperglycemia is linked to increased risk of CKD and poorer subsequent survival.

Conclusion

In conclusion, although both glycemic indices are significant predictors of prevalent CKD, the present study suggests that postprandial hyperglycemia is the more effective predictor, and combination of elevated SBP adds influence to the advancement of disease stages. These findings largely support applicability in this population of current recommendations for preventing the onset and slowing the progression of CKD. Once CKD is diagnosed, it is destined to progress to end-stage renal disease. Hence during early stages, aggressive BP control and decreasing postprandial glucose with the use of established drugs would be much effective in retarding progression to end-stage renal disease.

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article. There is neither medical writing nor editorial assistance was used for the preparation of this article. The authors declare that all of them have made substantial contribution toward the writing of this article.

This study was supported by departmental contingency for research and research grant “Dr. D. S. Kothari Post Doctoral Fellowship” from University Grants Commission, India, availed through Banaras Hindu University [No. F.4/2006(BSR)/13-581/2012(BSR].

Acknowledgments

We thank all medical and nursing staffs of Nephrology and Diabetes Care for the design and conduct of the study and team members of Department of Nephrology and Centre for Genomic Disorder, Banaras Hindu University of India for the guidance and comments.