• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Arch Intern Med. Author manuscript; available in PMC Oct 23, 2009.
Published in final edited form as:
PMCID: PMC2766035
NIHMSID: NIHMS105019

Poor Glycemic Control in Diabetes and The Risk of Incident Chronic Kidney Disease Even in The Absence of Albuminuria and Retinopathy: The Atherosclerosis Risk in Communities (Aric) Study

Lori D. Bash, MPH,1,2 Elizabeth Selvin, PhD, MPH,1,2 Michael Steffes, MD, PhD,3 Josef Coresh, MD, PhD, MHS,1,2,4,5 and Brad C. Astor, PhD, MPH, MS1,2,4

Abstract

Background

Diabetic nephropathy is the leading cause of kidney failure in the US. The extent to which elevated glycated hemoglobin (HbA1c) is associated with increased risk of chronic kidney disease (CKD) in the absence of albuminuria and retinopathy, the hallmarks of diabetic nephropathy, is uncertain.

Methods

HbA1c was measured in 1,871 adults with diabetes followed for 11 years in the Atherosclerosis Risk in Communities Study. Incident CKD was defined as an estimated glomerular filtration rate (GFR) below 60 mL/min/1.73 m2 after 6 years of follow-up or a kidney disease-related hospitalization. We categorized HbA1c into 4 clinically relevant categories. Retinopathy and albuminuria were measured midway through follow-up.

Results

Higher HbA1c was strongly associated with risk of CKD in models adjusted for demographics, baseline GFR and cardiovascular risk factors. Compared to HbA1c values of <6.00%, HbA1cs of 6.00-7.00%, 7.00%-8.00%, and >8.00% had adjusted relative hazards of CKD of 1.4 (95% CI: 0.97-1.91), 2.5 (1.70-3.66) and 3.7 (2.76-4.90), respectively. Risk of CKD was higher among individuals with retinopathy and albuminuria, the association between HbA1c and incident CKD was observed even among those participants without either abnormality: adjusted relative hazards =1.46 (0.80-2.65), 1.17 (0.43-3.19) and 3.51 (1.67-7.40); p-trend=0.004.

Conclusion

We observed a positive association between HbA1c and incident CKD that was strong, graded, independent of traditional risk factors and present even in the absence of albuminuria and retinopathy. Hyperglycemia is an important indicator of risk of both diabetic nephropathy (with albuminuria or retinopathy) and of less specific forms of CKD.

Background

More than 26 million US adults have chronic kidney disease (CKD), defined by decreased glomerular filtration rate (GFR) or increased urinary albumin excretion.1 CKD is associated with an increased risk of cardiovascular disease (CVD) morbidity and mortality.2-7 As a major risk factor for CVD, the National Kidney Foundation8 and the American Heart Association9 place individuals with CKD in the highest risk group for intervention.

Diabetes is a leading cause of kidney failure in the U.S., accounting for more than 40% of all incident end-stage renal disease (ESRD) cases.10,11 12 Diabetes increases the risk for end-stage renal disease (ESRD) including disease that is a direct complication of diabetes as well as ESRD due to causes other than diabetes.13 Diabetes is closely associated with microvascular disease, often manifesting as retinopathy or albuminuria.14, 15 However, approximately one-third of individuals with diabetes have decreased kidney function without either albuminuria or retinopathy.16

Increased glycated hemoglobin (hemoglobin A1c, HbA1c) is related to the development of microvascular disease in diabetes, and their reduction is at the center of the clinical management of hyperglycemia. Randomized studies among individuals with type 1 diabetes have shown that intensive treatment slows progression of microvascular complications (nephropathy, retinopathy, neuropathy) as well as reduces the development and progression of microalbuminuria.17

The continuous relationship between HbA1c levels and incidence of moderate CKD among individuals with diabetes, however, has not been well quantified. It is also unknown whether moderately elevated HbA1c levels predict a decline in kidney function in the absence of detectable microvascular disease, as evidenced by albuminuria and/or retinopathy. An improved understanding from observational data of the risks and consequences of diabetes in the absence of albuminuria and retinal damage is particularly important given recent concerns about tight glycemic control and risk of mortality among certain high risk individuals with diabetes.18

We examined the long-term independent association between moderately elevated levels of HbA1c and incident CKD in a population-based observational sample of adults with diabetes and evaluated the consistency of this association among those with and without albuminuria and/or retinopathy.

Methods

Study population

Data were taken from the Atherosclerosis Risk in Communities (ARIC) Study. This prospective biracial observational cohort of 15,792 individuals (including 2,187 persons with diabetes) between the ages of 45 and 64 (mean age: 54 (SD 5.8), 55% female, 74% white, 26% African American at baseline) was recruited from a probability sample of four U.S. communities (Forsyth County, NC; Jackson, MS; suburban Minneapolis, MN; and Washington County, MD). Participants took part in examinations starting with a baseline visit (visit 1) between 1987 and 1989. Individuals had 3 follow-up examinations in approximately three year intervals at community clinics, as well as annual follow-up telephone interviews between visits. Hospitalized events were ascertained continuously from ARIC's inception through December 31, 2004. Details of the ARIC cohort have been published elsewhere.19

In the present study, we included all participants with diabetes at the second ARIC visit (visit 2: 1990-1992), the only visit in which HbA1c was measured. Diabetes mellitus was defined as a fasting glucose of ≥ 126 mg/dL, nonfasting glucose of ≥ 200 mg/dL, self-reported physician diagnosis of diabetes mellitus or use of oral hypoglycemic medication or insulin. A total of 1,054 (56%) of 1,871 of individuals were identified based on self-reported diabetes. A total of 1,655 (88%) individuals were identified based on elevated plasma glucose: 1,556 (83%) with fasting plasma glucose of at least 126 mg/dL and an additional 99 (7%) with a nonfasting glucose of at least 200 mg/dL. Only 216 (11.5%) individuals reported having diabetes without also having an elevated plasma glucose.

We excluded participants who were missing HbA1c values at visit 2 (n=28), missing serum creatinine values at ARIC visit 1 or visit 2 (n=20), those with an estimated GFR < 60 mL/min/1.73 m2 at either ARIC visit 1 or visit 2 (n=229), participants who reported a race other than white or African American (n=3) and African Americans from the Minnesota and Washington County study centers (n=8). Analyses are based on the remaining 1,871 study participants. The study was approved by the institutional review boards at each of the sites, and written informed consent was obtained from all participants.

Data collection

Demographic and health behavior data, medical history, and measurements of height, weight and blood pressure were obtained during each clinical examination. Blood was drawn at all clinic visits as described previously.20

HbA1c was assayed from stored whole blood samples from the second ARIC visit using Tosoh high-performance liquid chromatography instruments in a secondary reference laboratory of the National Glycohemoglobin Standardization Program at the University of Minnesota Medical Center, Fairview, and certified by the International Federation of Clinical Chemists.21-23 HbA1c measurements were available for 2,159 (98.7%) of 2,187 participants with diabetes. HbA1c concentrations were recalibrated to correct for an upwards bias that was observed in a previous validation study comparing samples before and after long-term storage.22

A modified kinetic Jaffe method was used to measure serum creatinine at ARIC visit 2 and visit 4. Serum creatinine concentration was corrected for interlaboratory differences and indirectly calibrated to the Cleveland Clinic measurement by subtraction of 0.24 mg/dL from the visit 2 values and the addition of 0.18 mg/dL to the visit 4 values and then used to estimate GFR.3, 24 Estimated GFR was calculated using the simplified Modification of Diet in Renal Disease equation developed at the Cleveland Clinic: estimated GFR = 186.3 × (serum creatinine [mg/dL]-1.154) × (age-0.203) × (0.742 if female) × (1.21 if African American).25

Three seated blood pressure measurements were taken by certified technicians using a random-zero sphygmomanometer after 5 minutes of rest. The mean of the second and third readings was recorded. Enzymatic methods were used to obtain total plasma cholesterol, high-density lipoprotein (HDL) cholesterol and triglycerides while low-density lipoprotein (LDL) cholesterol was calculated from these using the Friedewald equation.26

Smoking status was determined by self-reported cigarette smoking. Prevalent CHD was defined as a history of physician-diagnosed myocardial infarction, evidence of a prior myocardial infarction by electrocardiogram (presence of a major or minor Q-wave abnormality with T-wave or ST-segment abnormality) or self-reported prior coronary revascularization procedure. Self-reported medication use (eg: antihypertensives, or antidiabetics) was verified by bottle inspection.

Urinary albumin excretion was measured from a spot urine sample at ARIC visit 4 (1996-1998) as the ratio of albumin to creatinine (ACR, in mg/g). Albuminuria was defined as ACR ≥30 mg/g (which includes both the categories of micro- and maroalbuminuria). Retinography was conducted at ARIC visit 3 (1993-1995) in one randomly selected eye of each participant. A modification of the Airlie House classification system was used to grade lesions typical of diabetic retinopathy from a 45° color fundus photograph of one eye from each participant. Severity scores were assigned as follows: level 10, none; level 20, minimal nonproliferative retinopathy (microaneurysms only or blot hemorrhages only); level 35, early nonproliferative retinopathy (microaneurysms and at least one of the following: venous loops, soft exudate or hard exudate, and questionable intraretinal microvascular abnormalities or venous beading); levels 43 to 47, moderate to severe nonproliferative retinopathy (microaneurysms and at least one of the following: intraretinal microvascular abnormalities, venous beading, hemorrhages, and microaneursyms exceeding those in standard photograph 2A); level ≥60, proliferative retinopathy. We considered a severity score of 20 or higher to be presence of retinopathy.27-29

Outcomes

Incident CKD was defined as an estimated GFR below 60 mL/min/1.73 m2 at visit 4 (1996-1998, approximately 6 years after visit 2), or kidney disease noted during a hospitalization.30 All hospitalizations and deaths among ARIC participants were ascertained through review of medical records, annual follow-up interviews and death certificates. Identification of hospital events was limited to those taking place in acute care hospitals and did not include events occurring in nursing homes, psychiatric hospitals, or other locations. Deaths were recorded regardless of location, and death certificates were abstracted for both underlying and contributory causes of death. Hospitalizations identified through active surveillance and used to identify cases included:_hospitalizations (discharges or deaths) coded for chronic renal disease, (International Classification of Diseases, Ninth Revision [ICD-9] codes 581-583 or 585-588), hypertensive renal disease (403), hypertensive heart and renal disease (404), unspecified disorder of kidney and ureter (593.9), diabetes with renal manifestations (250.4), kidney transplantation, renal dialysis, or adjustment/fitting of catheter (V42.0, V45.1, or V56), hemodialysis (39.95) or peritoneal dialysis (54.98), without acute renal failure (584, 586, 788.9, and 958.5) as the primary or secondary hospitalization code.31

Statistical analysis

We categorized HbA1c into categories (<6%, 6-7%, 7-8%, or >8%) corresponding to current ADA guideline categories.32 Baseline characteristics of the population were compared across CKD status and HbA1c categories using chi-squared and t tests. Incidence rates of CKD during follow-up were compared across HbA1c categories. Follow-up time was calculated from the time of the second ARIC examination to the first date of CKD diagnosis, defined as the earliest of either the fourth examination (if GFR decline was indicated), or the discharge date of a CKD-related hospitalization. Participants were censored at the earliest time of either death, withdrawal, or on December 31, 2004. Adjusted hazard ratios and their 95% confidence intervals for the time to development of CKD were computed using Cox proportional hazards models after first testing the assumption of proportionality of hazards over time. Models were developed comparing participants by HbA1c category as well as by continuous HbA1c. The continuous association between HbA1c and incident CKD was estimated from a Poisson regression model including a fourth-order polynomial for HbA1c, adjusted to the incidence rate for a 60 year old white male with a baseline eGFR of 90 mL/min/1.73 m2. Multivariable models included age, race, gender, study center, baseline eGFR, BMI, hypertension status, use of antihypertensives, prevalent coronary heart disease (CHD), smoking status, LDL- and HDL-cholesterol and triglyceride concentrations. Analyses were repeated after stratification by the presence of albuminuria at visit 4 and retinopathy at visit 3 among participants for whom these data were available (n= 1,231).

All statistical analyses were conducted using Stata statistical software Version 9.233 or SAS Version 9.1.34

Results

Among the 1,871 participants, higher HbA1c values were directly associated with female sex, African American race, higher estimated GFR, fasting glucose, prevalent CHD, hypertension, use of antihypertensives and antidiabetics, body mass index, and triglycerides (Table 1). Higher HbA1c category also was associated with lower HDL concentrations.

Table 1
Characteristics of the cohort of 1879 Individuals with Diabetes by HbA1c Category at Baseline

A total of 361 cases of incident CKD occurred during a mean follow-up of 11 years (incidence rate = 17.0 CKD cases per 1,000 person-years). A total of 120 cases were identifed based on a follow-up eGFR<60 mL/min/1.73 m2 and 292 participants were based on a kidney-related hospitalization or death (51 met both criteria). Figure 1 compares the cumulative risk of developing CKD by HbA1c category. From lowest to highest category, 11.8%, 16.5%, 23.8% and 31.3% of participants developed CKD over the length of the study (log rank p<0.001). The incidence rate was progressively higher with higher category of HbA1c (Table 2). Cases detected by decreased estimated GFR at visit 4 (6-years after the baseline HbA1c) are indicated by the steeper rise of the cumulative incidence curve at this follow-up time. The trend for higher risk of decreased kidney function remained after adjustment for age, race and sex as shown by the graded association across the entire range of HbA1c levels (Figure 2, which caps HbA1c concentrations at an upper limit for the overall sample).

Figure 1
Kaplan-Meier Survival Estimates for HbA1c by Category
Figure 2
Adjusted Incidence Rates (IR) of CKD by HbA1c
Table 2
Incidence of CKD by HbA1c Category

The association of HbA1c and risk of CKD remained after further adjustment for other CKD risk factors including study center, BMI, hypertension, use of antihypertensive medications, prevalent CHD, smoking status, LDL- and HDL-cholesterol, and triglyceride concentrations (Table 2). Individuals with HbA1c between 6and 7%, between 7% and 8%, and greater than 8% had 1.37 (95% CI: 0.97-1.91), 2.49 (95% CI: 1.70-3.66) and 3.67 (95% CI: 2.76-4.90) times the hazards, respectively, of progressing to incident CKD compared to individuals with diabetes and HbA1cs of 6.0% or less. In analyses of HbA1c as a continuous risk factor, each 1% higher HbA1c level was associated with a 31% higher risk of developing CKD. The association was observed for both components of the combined case definition of incident CKD, though the association was somewhat weaker in analyses limited to events detected by a decrease in estimated GFR at visit 4 (HR 1.13, 95% CI 1.03-1.25, per 1% higher HbA1c) than for kidney-related hospitalizations (HR 1.33, 95% CI 1.26-1.40, per 1% higher HbA1c). The association was not appreciably altered when controlling for total cholesterol, white blood cell count or use of angiotensin-converting enzyme inhibitors at baseline (results not shown). The association remained in analyses setting the time of incident CKD to the midpoint between the two visit dates for cases defined by a decrease in estimated GFR (results not shown).

Stratified Analyses

Individuals who had developed either retinopathy or albuminuria by visits 3 and 4 respectively, (Table 3) were at much higher risk of CKD than those with neither abnormality.

Table 3
Adjusted Hazard Ratio of Incident CKD, by HbA1c Category, by Albuminuria and Retinopathy Status**

Among the 217 cases of incident CKD occurring in participants who had undergone both retinography and urinalysis, almost one quarter developed among individuals with only retinopathy (24%, n=52), half that among those with only albuminuria (13%, n=28), and the remaining two-thirds among individuals with both (29.5%; n=64), or neither (33.6%; n=73) complication. The association of HbA1c with incident CKD, however, was similar across these subgroups. A hazard ratio of 1.27 (95% CI: 1.08-1.51) for a one percent increase in HbA1c was observed in those without either retinopathy or albuminuria, consistent with the overall observed hazards. Also consistent with overall trends, the trend for higher risk of decreased kidney function remained within each stratum of abnormalities (those developing neither albuminuria nor retinopathy, only one, or both), after adjustment for age, race and sex as shown by the graded association across the entire range of HbA1c levels (Figure 3, capping HbA1c at an upper limit of the stratum-specific 95th percentiles).

Figure 3
Adjusted Incidence Rates (IR) of CKD by HbA1c and Microvascular Complication Status

We found no statistically significant interactions between HbA1c and any demographic characteristics. We observed higher risk associated with higher HbA1c in analyses even after stratifying by gender, race, hypertension status, history of CHD and diabetes treatment status (data not shown).

Discussion

We observed a strong association between higher HbA1c and the incidence of CKD in adults with diabetes. This association was independent of traditional CKD risk factors and was observed across the entire range of HbA1c levels examined. This is one of few prospective studies to examine the risk of incident CKD in a large biracial community-based cohort. We included all individuals with diabetes, used an HbA1c assay certified by international programs and used for over two decades in the DCCT and EDIC23 and followed participants for an average of over 11 years. Even in the absence of both modest amounts of albuminuria and retinopathy, two hallmarks of diabetic microvascular disease, HbA1c was positively associated with incident CKD.

Diabetic nephropathy is diagnosed in the presence of persistent albuminuria (>30 mg/24 hours) equivalent to 30 mg/g (urinary albumin/creatinine), diabetic retinopathy, and no evidence of other kidney or renal tract disease.14 These results, however, demonstrate the importance of identifying the risk of developing kidney disease among individuals with diabetes even in the absence of albuminuria or retinopathy.

Sixty percent of persons with type 2 diabetes and hypertension develop nephropathy.12 Among adults with diabetes, 13% have decreased eGFR, while 64% experience albuminuria.16 There are about 1.1 million adults over the age of 40 with both type 2 diabetes and decreased eGFR. Well over half (59%) of these adults do not have albuminuria, and an estimated 0.3 million lack both albuminuria and retinopathy.16 In this population based study, among the 217 cases of incident CKD occurring in participants who had undergone both retinography and urinary albumin measurements, one-third (n=73; 33.6%) developed among individuals without albuminuria or retinopathy, nearly one-third (n=64; 29.5%) developed among individuals with both albuminuria and retinopathy, and the remaining 37% (n=80) developed among individuals with retinopathy (24%, n=52) or albuminuria (13%, n=28).

The Framingham Heart Study offspring cohort showed that there was an increased odds of developing incident CKD associated with abnormal glycemic status,35 and while we know that tight glycemic control decreases the risk of diabetes complications and CVD and CKD progression,17, 36, 37 kidney pathology has been underexplored in individuals with type 2 diabetes.14 Findings from the MRFIT study (a multicenter prospective cohort of men) showed that men with diabetes are at increased risk for both all-cause ESRD as well as ESRD due to causes other than diabetes.13 his study cannot address the specific pathophysiologic mechanisms relating elevated HbA1c levels to incident CKD, there are a number of biologically plausible explanations for observed associations, many potentially acting through damage to the glomerular basement membrane. Hemodynamic factors and advanced glycation end-products also may play significant roles in kidney disease progression among both individuals with and without diabetes.38-41 Evidence links glucose excursions,42 insulin resistance,43 and diabetes44, 45 to decreased diurnal blood pressure decline (non-dipping). Evidence also suggests that non-dippers with diabetes have poorer cardiovascular prognoses,42 more target organ damage46 and sympathetic activation in diabetic nephropathy.47 In our analysis, adjusting for blood pressure and antihypertensive medication use did not change the association. We could not, however, account for intra-individual physiologic variation over time or diurnal variations of systemic pressure. Glycemia also may affect intra-renal pressure. Intra-glomerular hypertension can contribute to progression of diabetic nephropathy even in the absence of systemic hypertension.38

Unfortunately, the ARIC Study did not collect information on type of diabetes of participants. The age at first diabetes diagnosis was asked of ARIC participants at the third visit (3 years after Visit 2, the baseline of these analyses). Among those participants diagnosed prior to Visit 2 (n=773), the mean time from diagnosis to Visit 2 was 10 years (sd = 9). Only 43 (3.8% of those asked, n=1134) reported being diagnosed at age 30 or younger, suggesting that very few had Type 1 diabetes.

The current study is also limited by the lack of a direct measure of kidney function. Direct measurement of kidney function is impractical in large cohorts, and most studies have relied on serum creatinine-based estimates of GFR. Estimated GFR was based on single measures of creatinine at three different visits (measures at visits 1 and 2 to exclude prevalent cases, and at visit 4 to define incident cases). The association of higher HbA1c and CKD was also observed in analyses limited to hospitalizations involving a kidney diagnosis.

Approximately 20% of individuals classified as diabetic according to our definition did not meet the American Diabetes Association criteria for diabetes in place at the time (fasting glucose of ≥ 140 mg/dL), and only approximately 40% of our sample was prescribed medications for diabetes. Because of these “early” cases of diabetes, there are a number of individuals with HbA1c values in the normal range. Risks across HbA1c were consistent across all population subgroups and did not differ by diabetes treatment status.

Because measures for albuminuria were only available at visit 4, we could only exclude prevalent cases of CKD Stage 3 or greater, and therefore our sample may include individuals with prevalent CKD Stage 1 or 2 at baseline. Measurements of HbA1c, retinography and urinary albumin excretion were performed only once, and at three different time points from one another (retinography at visit 3 and urinalysis at visit 4). By relying on a single measure taken to detect either retinopathy or albuminuria, some cases may be missed. Those without albuminuria at visit 4 are unlikely to have had albuminuria 6 years earlier.48 Likewise, if damage was not detected on retinal imaging taken at the third visit, it is unlikely that significant damage was present at the time of the second visit. Though specific findings of retinal damage may not be consistently observed over time, previous data from the ARIC study found regression of identified damage to be uncommon among individuals with diabetes.49 As in any study such as this, there is still potential for residual confounding due to unmeasured or mismeasured variables.

In summary, we observed a positive association between HbA1c and incident CKD that was strong, graded, independent of traditional risk factors, and present even at mildly elevated levels of HbA1c. In this population based setting, approximately one third of CKD incidence occurred in the presence of both albuminuria and retinopathy, and one third occurred in the absence of both conditions. These data suggest that glycemic control is a significant modifiable risk factor in the pathology of kidney disease among individuals with diabetes, both in the presence and absence of other microvascular damage. These results also suggest that urinary albumin screening alone may not be adequate for CKD detection among individuals with type 2 diabetes.

Acknowledgments

The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts N01-HC-55015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, and N01-HC-55022. The authors thank the staff and participants of the ARIC study for their important contributions.

Funding Source: Supported in part by grant numbers 5R01-DK-076770-02, 5T32-HL-007024-33, and 5T32-RR-023253-02 from the National Institutes of Health.

References

1. Coresh J, Selvin E, Stevens LA, et al. Prevalence of chronic kidney disease in the united states. JAMA. 2007;298:2038–2047. [PubMed]
2. Manjunath G, Tighiouart H, Coresh J, et al. Level of kidney function as a risk factor for cardiovascular outcomes in the elderly. Kidney Int. 2003;63:1121–1129. [PubMed]
3. Manjunath G, Tighiouart H, Ibrahim H, et al. Level of kidney function as a risk factor for atherosclerotic cardiovascular outcomes in the community. J Am Coll Cardiol. 2003;41:47–55. [PubMed]
4. Muntner P, He J, Hamm L, Loria C, Whelton PK. Renal insufficiency and subsequent death resulting from cardiovascular disease in the united states. J Am Soc Nephrol. 2002;13:745–753. [PubMed]
5. Fried LF, Shlipak MG, Crump C, et al. Renal insufficiency as a predictor of cardiovascular outcomes and mortality in elderly individuals. J Am Coll Cardiol. 2003;41:1364–1372. [PubMed]
6. Henry RM, Kostense PJ, Bos G, et al. Mild renal insufficiency is associated with increased cardiovascular mortality: The hoorn study. Kidney Int. 2002;62:1402–1407. [PubMed]
7. Wattanakit K, Coresh J, Muntner P, Marsh J, Folsom AR. Cardiovascular risk among adults with chronic kidney disease, with or without prior myocardial infarction. J Am Coll Cardiol. 2006;48:1183–1189. [PubMed]
8. Levey AS, Beto JA, Coronado BE, et al. Controlling the epidemic of cardiovascular disease in chronic renal disease: What do we know? what do we need to learn? where do we go from here? national kidney foundation task force on cardiovascular disease. Am J Kidney Dis. 1998;32:853–906. [PubMed]
9. Sarnak MJ, Levey AS, Schoolwerth AC, et al. Kidney disease as a risk factor for development of cardiovascular disease: A statement from the american heart association councils on kidney in cardiovascular disease, high blood pressure research, clinical cardiology, and epidemiology and prevention. Circulation. 2003;108:2154–2169. [PubMed]
10. Collins AJ, Kasiske B, Herzog C, et al. Excerpts from the united states renal data system 2004 annual data report: Atlas of end-stage renal disease in the united states. Am J Kidney Dis. 2005;45:A5–7. [PubMed]
11. Dubose TD., Jr American society of nephrology presidential address 2006: Chronic kidney disease as a public health threat--new strategy for a growing problem. J Am Soc Nephrol. 2007;18:1038–1045. [PubMed]
12. So WY, Kong AP, Ma RC, et al. Glomerular filtration rate, cardiorenal end points, and all-cause mortality in type 2 diabetic patients. Diabetes Care. 2006;29:2046–2052. [PubMed]
13. Brancati FL, Whelton PK, Randall BL, Neaton JD, Stamler J, Klag MJ. Risk of end-stage renal disease in diabetes mellitus: A prospective cohort study of men screened for MRFIT. multiple risk factor intervention trial. JAMA. 1997;278:2069–2074. [PubMed]
14. Brenner & Rector's the Kidney. 7th. W.B. Saunders Company; 2004.
15. So WY, Kong AP, Ma RC, et al. Glomerular filtration rate, cardiorenal end points, and all-cause mortality in type 2 diabetic patients. Diabetes Care. 2006;29:2046–2052. [PubMed]
16. Kramer HJ, Nguyen QD, Curhan G, Hsu CY. Renal insufficiency in the absence of albuminuria and retinopathy among adults with type 2 diabetes mellitus. JAMA. 2003;289:3273–3277. [PubMed]
17. Effect of intensive therapy on the development and progression of diabetic nephropathy in the diabetes control and complications trial the diabetes control and complications (DCCT) research group. Kidney Int. 1995;47:1703–1720. [PubMed]
18. NHLBI Communications Office. For safety, NHLBI changes intensive blood sugar treatment strategy in clinical trial of diabetes and cardiovascular disease. Available at: http://public.nhlbi/nih.gov/newsroom/home/GetPressRelease.aspx?id=2551.
19. The atherosclerosis risk in communities (ARIC) study: Design and objectives. the ARIC investigators. Am J Epidemiol. 1989;129:687–702. [PubMed]
20. Papp AC, Hatzakis H, Bracey A, Wu KK. ARIC hemostasis study--I. development of a blood collection and processing system suitable for multicenter hemostatic studies. Thromb Haemost. 1989;61:15–19. [PubMed]
21. Little RR. Glycated hemoglobin standardization--national glycohemoglobin standardization program (NGSP) perspective. Clin Chem Lab Med. 2003;41:1191–1198. [PubMed]
22. Selvin E, Coresh J, Jordahl J, Boland L, Steffes MW. Stability of haemoglobin A1c (HbA1c) measurements from frozen whole blood samples stored for over a decade. Diabet Med. 2005;22:1726–1730. [PubMed]
23. Steffes M, Cleary P, Goldstein D, et al. Hemoglobin A1c measurements over nearly two decades: Sustaining comparable values throughout the diabetes control and complications trial and the epidemiology of diabetes interventions and complications study. Clin Chem. 2005;51:753–758. [PMC free article] [PubMed]
24. Coresh J, Astor BC, McQuillan G, et al. Calibration and random variation of the serum creatinine assay as critical elements of using equations to estimate glomerular filtration rate. Am J Kidney Dis. 2002;39:920–929. [PubMed]
25. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. modification of diet in renal disease study group. Ann Intern Med. 1999;130:461–470. [PubMed]
26. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18:499–502. [PubMed]
27. Klein R, Sharrett AR, Klein BE, et al. The association of atherosclerosis, vascular risk factors, and retinopathy in adults with diabetes : The Atherosclerosis Risk in Communities Study. Ophthalmology. 2002;109:1225–1234. [PubMed]
28. Sharrett AR, Hubbard LD, Cooper LS, et al. Retinal arteriolar diameters and elevated blood pressure: The Atherosclerosis Risk in Communities Study. Am J Epidemiol. 1999;150:263–270. [PubMed]
29. Hubbard LD, Brothers RJ, King WN, et al. Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the Atherosclerosis Risk in Communities Study. Ophthalmology. 1999;106:2269–2280. [PubMed]
30. Shoham DA, Vupputuri S, Diez Roux AV, et al. Kidney disease in life-course socioeconomic context: The atherosclerosis risk in communities (ARIC) study. Am J Kidney Dis. 2007;49:217–226. [PubMed]
31. International classification of diseases, 9th revision, clinical modification (ICD-9-CM) Washington, D.C: U.S. Department of Health and Human Services, Public Health Service Health Care Financing Administration; 1991.
32. Standards of medical care in diabetes--2007. Diabetes Care. 2007;30 1:S4–S41. [PubMed]
33. StataCorp. Stata statistical software: Release 9.2. College Station, Texas: Stata Corporation; 2003.
34. SAS Institute Inc. Cary, NC, USA.:2002-2003;Release 9.1.
35. Fox CS, Larson MG, Leip EP, Meigs JB, Wilson PW, Levy D. Glycemic status and development of kidney disease: The framingham heart study. Diabetes Care. 2005;28:2436–2440. [PubMed]
36. Wali RK, Henrich WL. Chronic kidney disease: A risk factor for cardiovascular disease. Cardiol Clin. 2005;23:343–362. [PubMed]
37. Lancet. Vol. 352. UK prospective diabetes study (UKPDS) group; 1998. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33) pp. 837–853. [PubMed]
38. Forbes JM, Fukami K, Cooper ME. Diabetic nephropathy: Where hemodynamics meets metabolism. Exp Clin Endocrinol Diabetes. 2007;115:69–84. [PubMed]
39. Burns KD. Angiotensin II and its receptors in the diabetic kidney. Am J Kidney Dis. 2000;36:449–467. [PubMed]
40. Zhang SL, Filep JG, Hohman TC, Tang SS, Ingelfinger JR, Chan JS. Molecular mechanisms of glucose action on angiotensinogen gene expression in rat proximal tubular cells. Kidney Int. 1999;55:454–464. [PubMed]
41. Huebschmann AG, Regensteiner JG, Vlassara H, Reusch JE. Diabetes and advanced glycoxidation end products. Diabetes Care. 2006;29:1420–1432. [PubMed]
42. Pistrosch F, Reissmann E, Wildbrett J, Koehler C, Hanefeld M. Relationship between diurnal blood pressure variation and diurnal blood glucose levels in type 2 diabetic patients. Am J Hypertens. 2007;20:541–545. [PubMed]
43. Afsar B, Sezer S, Elsurer R, Ozdemir FN. Is HOMA index a predictor of nocturnal nondipping in hypertensives with newly diagnosed type 2 diabetes mellitus? Blood Press Monit. 2007;12:133–139. [PubMed]
44. Cuspidi C, Meani S, Lonati L, et al. Short-term reproducibility of a non-dipping pattern in type 2 diabetic hypertensive patients. J Hypertens. 2006;24:647–653. [PubMed]
45. Darcan S, Goksen D, Mir S, et al. Alterations of blood pressure in type 1 diabetic children and adolescents. Pediatr Nephrol. 2006;21:672–676. [PubMed]
46. Izzedine H, Launay-Vacher V, Deray G. Abnormal blood pressure circadian rhythm: A target organ damage? Int J Cardiol. 2006;107:343–349. [PubMed]
47. Tamura K, Tsurumi Y, Sakai M, et al. A possible relationship of nocturnal blood pressure variability with coronary artery disease in diabetic nephropathy. Clin Exp Hypertens. 2007;29:31–42. [PubMed]
48. Caramori ML, Fioretto P, Mauer M. Enhancing the predictive value of urinary albumin for diabetic nephropathy. J Am Soc Nephrol. 2006;17:339–352. [PubMed]
49. Wong TY, Klein R, Amirul Islam FM, et al. Three-year incidence and cumulative prevalence of retinopathy: The Atherosclerosis Risk in Communities Study. Am J Ophthalmol. 2007;143:970–976. [PMC free article] [PubMed]
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

  • MedGen
    MedGen
    Related information in MedGen
  • PubMed
    PubMed
    PubMed citations for these articles
  • Substance
    Substance
    PubChem Substance links