Main Risk Factors for Nephropathy in Type 2 Diabetes Mellitus Are Plasma Cholesterol Levels, Mean Blood Pressure, and Hyperglycemia FREE

DIABETIC nephropathy is a major cause of morbidity and is associated with increased cardiovascular mortality in type 2 diabetes mellitus.^1- 3 The specific pathological changes in the kidney, the clinical course, and the overall risk to develop nephropathy are quite similar in both types of diabetes.^4- 6

Conclusive evidence exists that strict control of hyperglycemia lowers the risk of nephropathy and of other diabetic complications in type 1 diabetes mellitus.^7- 10 The association between the risk of nephropathy and hyperglycemia was found to be nonlinear and continuous, with¹¹ or without¹² a threshold value of hemoglobin A_1c. However, data regarding this association in type 2 diabetes mellitus are inconclusive and conflicting.¹³ The decline in renal function over time has been associated with the initial glomerular filtration rate, initial urinary albumin excretion rate (UAE), hyperglycemia, and age.^14- 15 In a cross-sectional study of patients with type 2 diabetes mellitus, UAE was positively associated with hyperglycemia.¹⁶ The Oklahoma Indian Diabetes Study of patients with type 2 diabetes mellitus¹⁷ also found that hyperglycemia and elevated blood pressure were associated with an increased risk for renal failure. The results of a prospective study from Japan¹⁸ showed a reduction in the risk of nephropathy in patients with type 2 diabetes mellitus who were treated with an intensive insulin regimen. However, these patients were lean and sensitive to insulin. Therefore, it is uncertain whether these results could be extrapolated to the typical overweight, insulin-resistant patient with type 2 diabetes mellitus. In a long-term follow-up study of a mixed type 1 and type 2 diabetes mellitus cohort, Hellman and associates¹⁹ showed that a comprehensive diabetes treatment program resulted in reduced all-cause mortality. The large United Kingdom Prospective Diabetes Study²⁰ has not yet provided data on this issue. The St Vincent Declaration of 1994²¹ states that there is no convincing evidence that strict glucose control helps to slow the progression of nephropathy.

The present report summarizes data of a 2- to 9-year follow-up study of a large group of patients with type 2 diabetes mellitus in the Tel Aviv, Israel, area. All patients initially had normal UAE and were normotensive. We examined the influence of glucose control, mean blood pressure, plasma lipid concentration, and other potential risk factors on the development and progression of diabetic nephropathy. We also sought correlations between these parameters and clinical presentations of arteriosclerotic cardiovascular disease.

The UAE was determined during 1986 in more than 750 patients with type 2 diabetes mellitus, diagnosed according to World Health Organization criteria,²² whose urine was negative for protein using a dipstick test (Labstick, Ames, Iowa).

One hundred eight patients who had microalbuminuria were enrolled in a prospective study of the influence of angiotensin-converting enzyme inhibition on diabetic nephropathy.^23- 24 The patients with normal UAE (<30 mg/24 h) comprised the present series.

Additional inclusion criteria were as follows: age, 40 to 60 years; diagnosis of diabetes after age 40 years; known duration of diabetes of less than 5 years with a history of initial glucose control by diet or oral agents during the first 6 months; no evidence of systemic, renal, cardiac, or hepatic disease; normal blood pressure values on 2 consecutive examinations (systolic, ≤140 mm Hg and diastolic, ≤90 mm Hg; mean blood pressure, ≤107 mm Hg); serum creatinine level less than 124 µmol/L (1.4 mg/dL); and body mass index (BMI; calculated as the weight in kilograms divided by the square of the height in meters) less than 35 kg/m². Initially there were 621 eligible patients (men/women, 319/302) with a mean (± SD) age of 47.7 ± 4.5 years. The duration of diabetes was 0 to 5 years (mean ± SD duration, 1.92 ± 1.2 years). The mean (± SD) BMI was 24.9 ± 3.4 kg/m². Sixty-two patients received insulin, 235 were taking oral hypoglycemic agents, and 324 were using diet to control their diabetes.

Informed consent of the patients to use their data for research was obtained. The patients were followed up by their primary care physicians, who agreed to administer the patients' records in accordance with the protocol.

The physicians were advised to try to maintain patients' blood pressures within the normal range. However, there were no interventions in practical therapeutic decisions.

The minimum requirements included semiannual determinations of hemoglobin A_1c, serum creatinine, UAE, and blood pressure and annual determinations of plasma lipid levels and BMI.

Blood pressure was measured with mercury sphygmomanometers with the patients sitting after a 5-minute rest; the average of 2 determinations was recorded. The diastolic pressure was determined at Korotkoff phase V.

Antihypertensive therapy with calcium channel blockers and low-dose thiazides was initiated when mean blood pressure values of 105 mm Hg or higher were recorded on at least 2 consecutive visits.

Relevant clinical events were recorded, including death (all cause), nonfatal myocardial infarction, angina pectoris, congestive heart failure, and objectively verified peripheral vascular disease. The majority (95%) of the hospitalizations occurred in 2 regional hospitals. The records were reviewed by one of us (M.R.) and the diagnosis verified.

The follow-up was concluded in 1995 or earlier if an angiotensin-converting enzyme inhibiting agent was prescribed. The patients who died during the study were included until the time of death. The length of the follow-up ranged from 2 to 9 years (mean ± SD, 7.8 ± 0.9 years).

All laboratory examinations were done centrally and the assays were unchanged during the study period. Creatinine levels were determined using a routine kinetic automated method, as described by Bartels et al.²⁵ Hemoglobin A_1c levels were measured using affinity chromatography (Isolab, Akron, Ohio). The normal range of this assay is 0.035 to 0.056. Based on data from 8 different lot numbers, the coefficient of variation (intra-assay and interassay) was calculated to be less than 3%. Levels of total cholesterol and triglycerides were determined by the colorimetric enzymatic method of Allain et al²⁶ with the modifications of Badham and Trinder,²⁷ using an autoanalyzer (Hitachi 747, Hitachi, Japan). Levels of high-density lipoprotein (HDL) cholesterol were determined using a phosphotungstic acid precipitation step. The UAE was measured using 24-hour urine samples with an automated immunoturbidimetric assay.²⁸ The intraassay and interassay coefficients of variation of this method are 2.9% and 7.6%, respectively. All together, 8 to 15 collections of urine, 4 to 20 determinations of hemoglobin A_1c, 14 to 20 determinations of serum creatinine, and 5 to 10 determinations of plasma lipids were available for each patient. The mean blood pressure values were calculated for each visit (mean pressure was defined as diastolic pressure plus one third of the pulse pressure). The reciprocal creatinine value (100/creatinine value) was calculated for each visit²⁹ and the decline in renal function was expressed as a percentage of the initial value of the same patient (ΔCr). The socioeconomic status was defined as high or low according to the area of residence. The 50th percentile of the 3 main modifiable baseline characteristics, namely, levels of hemoglobin A_1c, total cholesterol, and mean blood pressure, were calculated. Patients in whom all 3 values were at the 50th percentile or higher were termed high risk, while all other patients were considered low risk.

All data are expressed as mean (± SD). Significance was defined as P<.05. The rate of decrease of reciprocal creatinine as a percentage of the initial value and the increase in the logarithm of albuminuria were calculated using linear regression analysis. The comparison between the groups of patients with normoalbuminuria, microalbuminuria, and macroalbuminuria, as well as those with different mean hemoglobin A_1c values, was performed using pooled variance Student t tests for independent variables. Stepwise logistic regression analysis was used to determine the correlations between the independent and the dependent variables. The relation between the mean values of hemoglobin A_1c and the risk for microalbuminuria was examined using 3 alternative models: simple exponential,³⁰ a threshold,³¹ and a change point model.³² Survival curves were plotted to compare high- and low-risk patients. Data were stored and processed using computer software (SPSS-PC for Windows, SPSS Inc, Chicago, Ill).

Ten patients discontinued the follow-up and could not be located. The data for 15 patients were incomplete. Twenty-two patients died during the follow-up period. The cause of death was related to coronary heart disease in 13 patients, cerebrovascular accident in 2, malignancy in 2, a motor vehicle crash in 1, and unknown in 4. Thus, the analysis of renal outcome was determined for 574 patients.

In 373 patients (65%), the normoalbuminuria persisted throughout the study (UAE, <30 mg/24 h). Two hundred one patients (35%) developed microalbuminuria, and 90 (16%) of these patients progressed to macroalbuminuria (UAE, >300 mg/24 h). The initial main characteristics of the patients in the 3 groups are outlined in Table 1. The annual mean values of total cholesterol, mean blood pressure, and hemoglobin A_1c in these 3 groups during the follow-up period are shown in Figure 1. The patients who progressed to nephropathy had significantly higher initial plasma values of hemoglobin A_1c, total cholesterol, low-density lipoprotein cholesterol, and triglycerides and lower values of HDL than those who maintained normal UAE. Also, the initial mean blood pressure was significantly higher in the patients who developed nephropathy. The impact of the individual baseline parameters on the risk for microalbuminuria is outlined in Table 2. A comparison of high- and low-risk patients showed that the odds ratio for microalbuminuria was almost 43 (95% confidence interval [CI], 25-106; P<.001). Thus, these 3 parameters (hemoglobin A_1c ≥0.09, total cholesterol ≥5.24 mmol/L [203 mg/dL], and mean blood pressure ≥95 mm Hg) when present together define patients at high risk for diabetic nephropathy. Furthermore, the risk (odds ratio) for progression to macroalbuminuria during follow-up was 18 (95% CI, 11-33; P=.001) among high- vs low-risk patients. Univariate analyses showed significant correlations between the decline in renal function (ΔCr as a percentage of the initial value in the same patient) and the mean study values of total cholesterol concentration (r=0.60; P<.001), mean blood pressure (r=0.57; P<.001), and hemoglobin A_1c (r=0.46; P<.001). Also, levels of low-density lipoprotein cholesterol, HDL, triglyceride concentration, BMI, cigarette smoking, low socioeconomic class, and male sex were significantly associated with ΔCr. Similar correlations also were found with albuminuria (expressed as the mean of the last 2 values).

The relative impact on the kidney of these variables was examined using multiple logistic regression analysis. Total cholesterol, mean blood pressure, and hemoglobin A_1c were the main determinants of the subsequent decline in renal function. The degree of albuminuria was influenced also by the BMI, HDL values, and age. The risk for microalbuminuria was predicted by the initial values of total cholesterol, mean blood pressure, hemoglobin A_1c, HDL, and BMI. The duration to the development of microalbuminuria was mainly determined by the mean blood pressure, BMI, and HDL values.

Patients were analyzed according to treatment group at baseline (diet, oral agents, or insulin). When included in the regression models, the mode of treatment itself had no predictive power for subsequent renal outcome. The introduction of insulin treatment during the study was strongly associated with the patient being at high risk at baseline (r=0.53; P=.001) and with the subsequent development of microalbuminuria (odds ratio, 9.55:1; 95% CI, 4.12-23.56; P=.001 for patients receiving insulin vs those not receiving insulin, respectively). However, when the treatment mode was included in the multivariate model this correlation was no longer apparent. The introduction of antihypertensive treatment had no further association with renal outcome when regulated for the average mean blood pressure values.

The glycemic control of the patients remained fairly stable throughout the study (Figure 1). Overall there was a gradual increase of less than 0.01 in hemoglobin A_1c values. There was an inverse correlation between the initial hemoglobin A_1c values and the increase of those values during follow-up (r=−0.44; P=.001). Table 3 shows the mean study hemoglobin A_1c values by quintiles. There was no consistent pattern of progression with age or duration of diabetes mellitus from the low to high values of hemoglobin A_1c. The patients with low mean values of hemoglobin A_1c also had lower mean total cholesterol and higher HDL cholesterol values than those with poor glycemic control. They also had a lower BMI and lower mean blood pressure values. The correlation between any pair of these parameters was highly significant: mean blood pressure vs total cholesterol values, r=0.54 (P<.001); mean blood pressure vs hemoglobin A_1c, r=0.34 (P<.001); mean blood pressure vs BMI, r=0.50 (P<.001); mean blood pressure vs HDL, r=0.45 (P<.001); total cholesterol vs hemoglobin A_1c, r=0.62 (P<.001); BMI vs hemoglobin A_1c, r=0.55 (P<.001); and BMI vs total cholesterol, r=0.65 (P<.001).

Table 3 demonstrates that more patients developed albuminuria with each 0.01 increase in the hemoglobin A_1c level, from as low as 0.06 in patients with hemoglobin A_1c below 0.08 to as high as 0.75 in the patients with hemoglobin A_1c levels above 0.11. The possibility for a nonlinear relation between the risk of microalbuminuria and hemoglobin A_1c values was examined by grouping the hemoglobin A_1c values in small intervals of 0.0045 and 0.009 in the tails. The hemoglobin A_1c values were modeled with indicator variables in a logistic regression model of the prevalence of microalbuminuria with covariates to adjust for age at onset of diabetes, the duration of diabetes, mean blood pressure, total cholesterol values, and sex. The reference group for the adjusted relative odds was the group of patients with hemoglobin A_1c values of 0.060 to 0.078. Three logistic regression models were tested,^30- 32 and the results were similar. The exponential model confirmed the impression of nonlinearity (r²=0.73; P=.001) and seemed to represent the data most closely.

Sixty-two patients encountered definite clinical events related to arteriosclerosis: 36 had a nonfatal myocardial infarction, 22 developed unequivocal angina pectoris, 4 had congestive heart failure, and 10 developed peripheral vascular disease. These events, grouped with the 22 patients who died, were correlated with the baseline characteristics. Event-free survival was significantly higher in the low-risk patients (P<.001), as shown in Figure 2. The odds ratio for any of the cardiovascular end points (including all-cause mortality) was 14.75 (95% CI, 8.72-24.95; P<.001) among the high-risk vs low-risk patients. The odds ratios for cardiovascular end points according to individual risk factors are detailed in Table 4.

In this study the risk factors for diabetic nephropathy in type 2 diabetes mellitus are borne out from long-term, noninterventional follow-up of a large and initially uniform group of patients. Logistic regression analysis highlighted the role of glucose control along with the levels of total cholesterol and mean blood pressure as joint major risk factors for the subsequent renal outcome. The importance of blood pressure control in this context is widely accepted and needs no further underscoring.^33- 34 The predictive role of plasma cholesterol concentration in diabetic nephropathy has also been documented in type 1³⁵ and type 2 diabetes mellitus.³⁶ However, the importance of lowering blood glucose levels was previously uncertain.

Among our patients, elevated hemoglobin A_1c levels were associated both with crossing the threshold to nephropathy and the degree of progression of renal impairment. The pattern of the correlation between values of hemoglobin A_1c and the risk for albuminuria was exponential but without a definite threshold value, as is most probably the case in type 1 diabetes mellitus.¹¹ One hundred fifty-five patients had baseline values higher than the 50th percentile of all 3 major risk factors, namely, total cholesterol (>5.25 mmol/L [203 mg/dL]), mean blood pressure (>95 mm Hg), and hemoglobin A_1c (>0.09). These patients comprised 27% of the total patient population and their odds ratio for diabetic nephropathy was 43, compared with those who had 2 or fewer risk factors in the 50th percentile or higher. These higher-risk patients also had a 15-to-1 risk for clinical end points of arteriosclerotic cardiovascular disease compared with the rest of the study population. The definition of a high-risk group with only 3 parameters is easy and enables the development of preventive strategies concentrating on these patients. The association between clinical phenomena of arteriosclerosis and these risk factors is time honored. The new aspect highlighted by this study is that these characteristics are all within the normal or previously accepted range for this population. Their combination in a single patient, however, is associated with a very high risk for microvascular and macrovascular complications of diabetes.

The inclusion criteria of our study required that diabetes be diagnosed after age 40 years and was initially regulated by diet or oral hypoglycemic agents. Thus, the probability of finding cases of type 1 diabetes mellitus among these patients was low. Other studies that found a correlation between hemoglobin A_1c values and albuminuria were mostly cross-sectional observations.^16,18 A recent 6-year follow-up study from Finland³⁷ found that the subsequent development of albuminuria was best predicted by the initial values of serum insulin. The Japanese study by Ohkudo and colleagues¹⁸ examined a relatively small group but was well designed and long-term. Their results seem to support the introduction of intensive metabolic control in patients with type 2 diabetes mellitus. However, their patients were relatively young, lean (BMI, 19-21 kg/m²), treated with insulin, and must have been exceptionally cooperative to maintain near normal levels of glycosylated hemoglobin (hemoglobin A_1c, 0.06-0.07). Furthermore, the insulin requirements were modest and there was no mention of weight gain during the study period. The applicability of the results of their study to patients with type 2 diabetes mellitus in the western hemisphere is therefore uncertain.

The recommendations of the American Diabetes Association³⁸ advocating hemoglobin A_1c levels of 0.07 as a therapeutic goal in patients with type 2 diabetes mellitus are based mainly on the extrapolation of the Diabetes Control and Complications Trial.⁷ In type 2 diabetes mellitus, however, this goal will require substantially larger doses of insulin with as yet uncertain effects. The recently published feasibility results of the Veterans Affairs Cooperative Study on Glycemic Control and Complications in NIDDM³⁹ indicate that excellent glycemic control in men with type 2 diabetes mellitus is possible for a limited period. However, the benefit-risk ratio of such intensive therapy has not yet been established. The applicability of these conclusions to women is also uncertain.

Our data have several drawbacks. First, this was an uncontrolled observational study; second, the follow-up periods were variable; third, the clinical treatment of the patients was not uniform; and fourth, the method of assessment of renal function is inaccurate. However, the long period of observation, the uniformity of the initial data, the relative stability of mean blood pressure, hemoglobin A_1c, and cholesterol values throughout the study, and the use of each patient as his/her own control enable these data to be used in the evaluation of their association with diabetic nephropathy. Furthermore, this study is probably one of the last of its kind. The increasing use of angiotensin-converting enzyme inhibitors in patients with diabetes will obscure the natural course of nephropathy. Also, despite the lack of direct evidence derived from controlled studies, withholding available modalities of intervention for the management of risk factors becomes increasingly difficult from the point of view of medical ethics.

Finally, our data indicate that the progression of diabetic nephropathy is truly multifactorial. The list of risk factors includes (in a declining order of significance) elevated levels of plasma total cholesterol, small increments in mean blood pressure, hyperglycemia, high BMI, low levels of HDL, high levels of low-density lipoprotein, cigarette smoking, a low socioeconomic class, and male sex. The similarity of this list to the risk factors for atherosclerosis is striking. Indeed, the patients who were at high risk for microalbuminuria also had a 15-times higher risk for clinical end points of arteriosclerotic cardiovascular disease.

Accepted for publication September 25, 1997.

Supported in part by the Tyomkin Research Grant, provided by Yehudit and Avi Tyomkin, Kfar Shmariahu, Israel (Dr Ravid).

Reprints: Mordchai Ravid, MD, Department of Medicine, Meir Hospital, Kfar-Sava 44281, Israel.