Abstract
IMPORTANCE
Diabetic kidney disease is the leading cause of chronic and end-stage kidney disease in the United States and worldwide. Changes in demographics and treatments may affect the prevalence and clinical manifestations of diabetic kidney disease.
OBJECTIVE
To characterize the clinical manifestations of kidney disease among US adults with diabetes over time.
DESIGN, SETTING, AND PARTICIPANTS
Serial cross-sectional studies of adults aged 20 years or older with diabetes mellitus participating in National Health and Nutrition Examination Surveys from 1988 through 2014.
EXPOSURES
Diabetes was defined as hemoglobin A1c greater than 6.5% or use of glucose-lowering medications.
MAIN OUTCOMES AND MEASURES
Albuminuria (urine albumin-to-creatinine ratio≥30 mg/g), macroalbuminuria (urine albumin-to-creatinine ratio≥300 mg/g), reduced estimated glomerular filtration rate (eGFR <60 mL/min/1.73m2), and severely reduced eGFR (<30 mL/min/1.73m2), incorporating data on biological variability to estimate the prevalence of persistent abnormalities.
RESULTS
There were 6251 adults with diabetes included (1431 from 1988–1994, 1443 from 1999–2004, 1280 from 2005–2008, and 2097 from 2009–2014). The prevalence of any diabetic kidney disease, defined as persistent albuminuria, persistent reduced eGFR, or both, did not significantly change over time from 28.4%(95% CI, 23.8%–32.9%) in 1988–1994 to 26.2% (95% CI, 22.6%–29.9%) in 2009–2014 (prevalence ratio, 0.95 [95%CI, 0.86–1.06] adjusting for age, sex, and race/ethnicity; P = .39 for trend). However, the prevalence of albuminuria decreased progressively over time from 20.8%(95%CI, 16.3%–25.3%) in 1988–1994 to 15.9%(95%CI, 12.7%–19.0%) in 2009–2014 (adjusted prevalence ratio, 0.76 [95%CI, 0.65–0.89]; P < .001 for trend). In contrast, the prevalence of reduced eGFR increased from 9.2%(95%CI, 6.2%–12.2%) in 1988–1994 to 14.1%(95%CI, 11.3%–17.0%) in 2009–2014 (adjusted prevalence ratio, 1.61 [95%CI, 1.33–1.95] comparing 2009–2014 with 1988–1994; P < .001 for trend), with a similar pattern for severely reduced eGFR (adjusted prevalence ratio, 2.86 [95%CI, 1.38–5.91]; P = .004 for trend). Significant heterogeneity in the temporal trend for albuminuria was noted by age (P = .049 for interaction) and race/ethnicity (P = .007 for interaction), with a decreasing prevalence of albuminuria observed only among adults younger than 65 years and non-Hispanic whites, whereas the prevalence of reduced GFR increased without significant differences by age or race/ethnicity. In 2009–2014, approximately 8.2 million adults with diabetes (95%CI, 6.5–9.9 million adults) had albuminuria, reduced eGFR, or both.
CONCLUSIONS AND RELEVANCE
Among US adults with diabetes from 1988 to 2014, the overall prevalence of diabetic kidney disease did not change significantly, whereas the prevalence of albuminuria declined and the prevalence of reduced eGFR increased.
Diabetes mellitus is the most common cause of chronic kidney disease in the world, leading to multiple complications including end-stage renal disease, cardiovascular disease, infection, and death.1 Chronic kidney disease in the setting of diabetes or diabetic kidney disease (DKD), manifests clinically as albuminuria, reduced glomerular filtration rate (GFR), or both. Over the last 20 years, the prevalence of diabetes and DKD have increased.2
The natural history of DKD traditionally has been described as progressive albuminuria followed by a steady loss of GFR.3 However, this natural history may have changed over the last 2 decades. In particular, GFR loss has been observed prior to the development of albuminuria,4–6 a reduced GFR without albuminuria has been frequently described,6–9 and albuminuria has been observed to be transient or reversible.10–14 Changes in diabetes management over time include increased use of intensive glycemic control, improved blood pressure control, and increased use of renin-angiotensin-aldosterone system (RAAS) inhibitors.2 In this context, the prevalence of reduced GFR was previously reported to have increased among adults with diabetes in the United States from 1988 to 2008, whereas significant changes in albuminuria were not observed.2
In this study, temporal trends in albuminuria and reduced GFR were evaluated through 2014. Compared with prior analyses, more advanced DKD manifestations were evaluated, subgroups defined by age, race, and ethnicity were examined, and new data on persistence of abnormalities were incorporated. The overall goal was to identify priorities for DKD screening, target implementation of existing interventions, and design clinical trials for new treatments.
Methods
Study Population
The population-based National Health and Nutrition Examination Survey (NHANES) is a program of studies conducted by the National Center for Health Statistics designed to assess the prevalence of disease, disease risk factors, and nutritional status of adults and children in the United States. It uses a probability sampling design to select participants representative of the civilian, non institutionalized US population.15 NHANESIII took place in 1988–1994. Starting in 1999, NHANES became a continuous program, with data compiled in 2-year blocks. Health examinations including physical measurements and blood and urine collections are conducted at a mobile examination center. Each NHANES cycle oversamples persons of black race, Hispanic ethnicity, or both. The current study includes participants in NHANES III, NHANES1999–2004, NHANES 2005–2008, and NHANES 2009–2014 who were aged 20 years or older, underwent a health examination in the NHANES mobile examination center, and had available data for medication use, hemoglobin A1c, serum creatinine concentration, and urine albumin and creatinine concentrations. All NHANES protocols were approved by the research ethics review board of the National Center for Health Statistics, and all participants signed written informed consent forms.
Participants with diabetes mellitus, defined as use of glucose-lowering medications (insulin or oral hypoglycemic medications), hemoglobinA1c of 6.5%or greater, or both, were included in the present analyses.16,17 HemoglobinA1c was measured in all NHANES cycles using high-pressure liquid chromatography (coefficients of variation <3.0%).15 Self-reported history of diabetes was not used to define it because temporal changes in diabetes screening and diagnosis could lead to diabetes populations with differing disease severity over time and biased estimates of DKD prevalence. Fasting glucose or glucose concentrations following anoral glucose tolerance test also were not used to define diabetes because these criteria would reduce the numbers of participants available for the analyses and the power of the study.
Diabetic Kidney Disease
During NHANES mobile examination center screenings, urine albumin concentration was measured in a random, single voided urine sample using a solid-phase fluorescent immunoassay and creatinine concentration was measured using a Jaffe rate reaction. Albuminuria was defined as a urine albumin to-creatinine ratio (ACR) of 30 mg/g or greater, and macroalbuminuria was defined as a urine ACR of 300 mg/g or greater.4,16 Serum creatinine concentrations were measured by a kinetic rate Jaffe method, and values from NHANESIII and NHANES 1999–2000 were calibrated as previously described to account for laboratory drift in serum creatinine across NHANES cycles.15,18–20 Glomerular filtration rate was estimated from calibrated serum creatinine using the Chronic Kidney Disease Epidemiology Collaboration equation.21 Reduced estimated GFR (eGFR) was defined as less than 60 mL/min/1.73 m2 and severely reduced eGFR as less than 30 mL/min/1.73 m2.4 Any DKD was defined as albuminuria, reduced eGFR, or both.
To account for the biological variability inherent in urine ACR and serum creatinine measurements, the persistence of albuminuria and reduced eGFR was calculated among subsets of participants with repeat measurements of urine ACR or eGFR. Persistence was evaluated as the proportions of participants with abnormal values whose values were also abnormal on repeat testing (described in eMethods in the Supplement). Estimates of persistence were incorporated into the prevalence estimates as described below in the statistical methods section.
Other Clinical Characteristics
Age, sex, race/ethnicity, and duration of diabetes were assessed by questionnaire.15 Race/ethnicity was categorized as non-Hispanic white, non-Hispanic black, Mexican American, other Hispanic, and other or unknown race (including multiracial). Participants of all races and ethnicities were included in the analyses, and estimates were reported for non-Hispanic white, non-Hispanic black, and Mexican American race/ethnicity only. Type 1 diabetes was defined for descriptive purposes only using the following criteria: (1) diagnosis prior to 30 years of age; (2) first use of insulin within 2 years of diabetes diagnosis; and (3) current insulin use. Medications taken during a 1-month period preceding the NHANES physical examination were assessed by in-person interview.15 Medication data for 2009–2014 were based only on information from NHANES 2009–2012 because medication data were not available for NHANES 2013–2014 at the time of analysis. Body mass index was calculated as weight in kilograms divided by height in meters squared. Three or more consecutive blood pressure measurements separated by 30 seconds were made after 5 minutes of rest with the mean values used for analysis.
NHANES 2005–2008 data were used to describe clinical characteristics of US adults with diabetes by DKD status because this period included retinal photography. For this purpose, DKD status was defined by single urine and serum samples and thus did not reflect persistence. Diabetic retinopathy was defined as retinopathy or macular edema on retinal photography.
Statistical Methods
Analyses were performed using Stata version 11.1 (StataCorp) and R version 3.2.2 (RFoundation for Statistical Computing),22 and incorporated recommended NHANES weights to account for nonresponse bias and the sampling design.15 For each NHANES cohort, Stata svy commands were used to estimate the prevalence of DKD and other clinical characteristics among US adults with diabetes.
Binomial regression was used to test trends in DKD prevalence over time. NHANES III, NHANES 1999–2004, NHANES 2005–2008, and NHANES 2009–2014 were modeled primarily as non ordered independent variables. Tests for trend were performed using a continuous variable defined by the midpoint of each study period (in years). For each outcome, participants who had the outcome were considered to have a value equal to the outcome’s estimate of persistence, which allowed for estimation of DKD prevalence ratios accounting for possible misclassification of albuminuria, eGFR, or both. To account for the uncertainty in the estimate of the probability of persistence, a multiple imputation approach was used to obtain 95% CIs for adjusted prevalence ratios. The final variance of the prevalence ratios were estimated by using the rules of Rubin23 to combine between- and within-imputation variance estimates. Models were adjusted for age (in categories of 20–39 years, 40–59 years, and ≥60 years), sex, and race/ethnicity. An age or race/ethnicity × time interaction term allowed extraction of subgroup-specific effect estimates. Significance testing for all modelswas2-sided and the significance threshold was set at P < .05.
Results
Characteristics of US Adults With Diabetes
The unadjusted prevalence of diabetes in the United States increased from 6.0% in 1988–1994 to 9.8% in 2009–2014(Table 1).
Table 1.
Characteristics of US Adults With Diabetes, 1988 Through 2014
| NHANES Period
|
||||||||
|---|---|---|---|---|---|---|---|---|
| 1988–1994 (n = 1431)
|
1999–2004 (n = 1443)
|
2005–2008 (n = 1280)
|
2009–2014 (n = 2097)
|
|||||
| No. With Diabetes | Weighted % (95% CI)a | No. With Diabetes | Weighted % (95% CI)a | No. With Diabetes | Weighted % (95% CI)a | No. With Diabetes | Weighted % (95% CI)a | |
| US populationb | 6.0 (5.4–6.7) | 7.8 (7.2–8.5) | 9.4 (8.5–10.4) | 9.8 (9.2–10.4) | ||||
|
| ||||||||
| Demographics | ||||||||
|
| ||||||||
| Age, mean (95% CI), y | 59.7 (58.3–61.1) | 58.8 (57.6–59.9) | 59.1 (57.9–60.3) | 59.3 (58.5–60.0) | ||||
|
| ||||||||
| Female sexc | 736 | 48.9 (44.8–53.0) | 689 | 47.8 (45.1–50.1) | 629 | 50.4 (46.7–54.1) | 979 | 46.3 (43.4–49.2) |
|
| ||||||||
| Race/ethnicityd | ||||||||
|
| ||||||||
| Non-Hispanic white | 478 | 68.7 (63.5–73.5) | 556 | 63.6 (57.5–69.4) | 496 | 62.9 (54.8–70.3) | 719 | 59.2 (54.4–63.9) |
|
| ||||||||
| Non-Hispanic blackc | 452 | 16.9 (14.1–20.0) | 338 | 14.8 (11.5–18.9) | 373 | 17.2 (13.4–21.9) | 547 | 15.3 (12.4–18.7) |
|
| ||||||||
| Mexican American | 451 | 6.6 (5.4–8.0) | 430 | 8.1 (5.5–11.7) | 257 | 8.7 (6.4–11.6) | 373 | 10.4 (7.4–14.4) |
|
| ||||||||
| Diabetes duration, y | ||||||||
|
| ||||||||
| <5 | 306 | 25.8 (22.2–29.6) | 315 | 25.3 (22.0–28.9) | 266 | 22.3 (19.6–25.3) | 256 | 17.4 (15.3–19.8) |
|
| ||||||||
| 5-<10 | 190 | 15.8 (12.4–20.0) | 237 | 16.3 (14.2–18.7) | 222 | 18.3 (15.4–21.5) | 257 | 16.7 (15.1–18.5) |
|
| ||||||||
| 10-<20 | 243 | 14.7 (12.1–17.9) | 267 | 16.6 (14.4–19.0) | 275 | 21.6 (18.6–24.9) | 315 | 22.8 (19.9–26.1) |
|
| ||||||||
| ≥20 | 157 | 8.9 (7.1–11.1) | 258 | 17.4 (14.6–20.7) | 175 | 13.0 (11.0–15.3) | 227 | 14.9 (13.0–17.1) |
|
| ||||||||
| Diabetes previously undiagnosed | 503 | 34.8 (31.4–38.4) | 339 | 24.4 (21.6–27.4) | 316 | 24.9 (21.1–29.1) | 537 | 28.1 (25.8–30.1) |
|
| ||||||||
| Type 1 diabetes | 18 | 5.8 (2.4–13.4) | 17 | 2.4 (1.3–4.5) | 28 | 4.6 (3.1–6.9) | 41 | 4.5 (3.1–6.4) |
|
| ||||||||
| Medication Usee | ||||||||
|
| ||||||||
| Glucose lowering | 781 | 56.2 (52.0–60.3) | 1033 | 70.4 (67.0–73.5) | 937 | 74.2 (70.2–77.8) | 1125 | 74.5 (71.2–77.6) |
|
| ||||||||
| Oral medications only | 492 | 35.4 (31.7–39.3) | 811 | 54.2 (51.0–57.3) | 721 | 55.2 (51.4–58.9) | 811 | 51.8 (49.4–54.3) |
|
| ||||||||
| Insulin | 289 | 20.8 (17.0–25.1) | 222 | 16.2 (13.5–19.3) | 216 | 19.0 (16.6–21.7) | 314 | 22.7 (19.6–26.1) |
|
| ||||||||
| RAAS inhibitorse | 310 | 24.4 (21.0–28.3) | 620 | 41.7 (38.7–44.7) | 691 | 52.0 (47.7–56.2) | 861 | 56.2 (52.3–59.9) |
|
| ||||||||
| ACE inhibitors | 249 | 19.6 (16.5–23.1) | 493 | 32.1 (29.9–34.5) | 495 | 37.9 (34.6–41.3) | 579 | 36.0 (32.9–39.2) |
|
| ||||||||
| ARBs | 51 | 3.9 (1.9–8.0) | 135 | 10.2 (8.1–12.8) | 216 | 15.1 (12.2–18.5) | 295 | 20.5 (17.9–23.4) |
|
| ||||||||
| Aldosterone antagonists | 19 | 1.3 (0.7–2.4) | 21 | 1.3 (0.8–2.3) | 31 | 2.2 (1.4–3.4) | 26 | 1.9 (1.1–3.4) |
|
| ||||||||
| Lipid loweringf | 190 | 17.0 (13.5–21.2) | 426 | 34.5 (31.3–37.8) | 664 | 51.7 (47.6–55.8) | 803 | 51.8 (48.6–55.1) |
|
| ||||||||
| Statins | 134 | 11.9 (8.8–15.9) | 377 | 30.0 (27.0–33.2) | 553 | 42.3 (38.9–45.8) | 714 | 46.5 (43.3–49.8) |
|
| ||||||||
| Fibrates | 51 | 5.4 (3.8–7.8) | 54 | 4.6 (3.5–6.0) | 74 | 6.9 (4.9–9.7) | 85 | 5.9 (4.3–8.1) |
|
| ||||||||
| Physical Measurements, Mean (95% CI) | ||||||||
|
| ||||||||
| Body mass indexg | 30.6 (30.1–31.1) | 32.4 (31.8–33.1) | 33.0 (32.4–33.7) | 33.6 (33.0–34.1) | ||||
|
| ||||||||
| Systolic BP, mm Hg | 136.3 (134.8–137.8) | 132.4 (130.6–134.2) | 131.2 (129.6–132.8) | 130.1 (128.8–131.4) | ||||
|
| ||||||||
| Diastolic BP, mm Hg | 76.2 (75.4–77.1) | 70.1 (68.4–71.8) | 69.3 (68.1–70.4) | 68.9 (67.9–69.9) | ||||
|
| ||||||||
| Laboratory Measurements, Mean (95% CI) | ||||||||
|
| ||||||||
| Hemoglobin A1c, % | 8.1 (7.9–8.2) | 7.7 (7.6–7.9) | 7.3 (7.2–7.5) | 7.6 (7.5–7.7) | ||||
|
| ||||||||
| Total cholesterol, mg/dL | 223.8 (219.1–228.5) | 207.4 (203.3–211.5) | 190.4 (186.8–194.0) | 185.0 (182.5–187.6) | ||||
|
| ||||||||
| HDL cholesterol, mg/dL | 44.1 (42.7–45.6) | 46.3 (45.3–47.4) | 47.5 (46.3–48.7) | 45.9 (45.0–46.7) | ||||
|
| ||||||||
| LDL cholesterol, mg/dL | 137.1 (132.9–141.4) | 116.3 (111.8–120.7) | 104.5 (100.5–108.4) | 103.0 (100.0–106.0) | ||||
|
| ||||||||
| Triglycerides, mg/dL | 198.9 (185.0–213.8) | 179.0 (170.4–188.1) | 152.7 (143.5–162.5) | 142.3 (132.0–153.3) | ||||
Abbreviations: ACE, angiotensin-converting enzyme; ARBs, angiotensin-receptor II blockers; BP, blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NHANES, National Health and Nutrition Examination Surveys; RAAS, renin-angiotensin-aldosterone system.
SI conversion factors: To convert HDL, LDL, and total cholesterol to mmol/L, multiply by 0.0259; triglycerides to mmol/L, multiply by 0.0113.
Unless otherwise indicated.
Weighted percentage of the US population with diabetes regardless of kidney disease manifestations.
The numbers were corrected (compared with our previous study2).
Participants of all races and ethnicities were included in the analyses, and estimates were reported for non-Hispanic white, non-Hispanic black, and Mexican American race/ethnicity only.
Data for 2009–2014 are based only on information from NHANES 2009–2012 because medication data were not available for NHANES 2013–2014.
Definitions included new drugs that were not available during previous analyses.
Calculated as weight in kilograms divided by height in meters squared.
Over time, mean age and sex distribution of the diabetes populations were similar. However, the fraction of adults with diabetes who self-identified as Mexican American was higher and self-reported non-Hispanic white ethnicity was lower during later survey years. The mean duration of diagnosed diabetes increased in the later compared with earlier NHANES cycles. The mean body mass index also increased from 30.6 in 1988–1994 to 33.6 in 2009–2014.
Among 731 NHANES participants with diabetes who contributed 2 urine samples, ACR of greater than 30 mg/g was persistent in 58.9% of the repeat samples and an ACR of greater than 300 mg/g was persistent in 72.3% of the repeat samples (eFigure 1 and eTable 1 in the Supplement). Among 2076 NHANES participants with 2 serum samples, an eGFR of less than 60 mL/min/1.73 m2 was persistent in 70.4% of the repeat samples and an eGFR of less than 30 mL/min/1.73 m2 was persistent in 100% of the repeat samples (eFigure 2 and eTable 2).
The proportions of adults taking glucose-lowering medications, RAAS inhibitors, and statins were higher over time. Consistent with these changes, mean systolic and diastolic blood pressure, hemoglobin A1c, total cholesterol, low-density lipoprotein cholesterol, and triglycerides were lower in later compared with earlier years. These patterns were consistent across categories of age (eFigure 3 in the Supplement) and race/ethnicity (Figure). However, older adults were more likely than younger adults to be treated with glucose-lowering medications, RAAS inhibitors, and statins and achieved lower levels of hemoglobin A1c and low-density lipoprotein cholesterol (but not blood pressure) during all periods. In addition, during all periods, blacks and Mexican Americans were less likely than non-Hispanic whites to take glucose-lowering medications, RAAS inhibitors, and statins and did not achieve mean hemoglobin A1c values as low as non-Hispanic whites.
Figure. Medication Use and Trends in Clinical Targets for the Adult US Population With Diabetes by Race/Ethnicity.
Error bars indicate 95% CIs; NHANES, National Health and Nutrition Examination Surveys. Participants of all races and ethnicities were included in the analyses, and estimates were reported for non-Hispanic white, non-Hispanic black, and Mexican American race/ethnicity only.
Clinical Manifestations of DKD
Among US adults with diabetes, the overall prevalence of DKD did not change significantly from 1988 to 2014 (28.4% in 1988–1994 and 26.2% in 2009–2014; Table 2). However, the prevalence of albuminuria decreased from 20.8% to 15.9%, whereas the prevalence of reduced eGFR increased from 9.2% to 14.1% and the prevalence of severely reduced eGFR increased from 1.0% to 2.7%. Further adjustment for eGFR did not substantially alter results for temporal trends in the prevalence of albuminuria (eTable 3 in the Supplement). Significant heterogeneity in the temporal trend for albuminuria was noted by age (P = .049 for interaction) and race/ethnicity (P = .007 for interaction), with a decline in prevalence observed only among adults younger than 65 years and non-Hispanic whites (Table 3 and Table 4). In contrast, no significant heterogeneity in the temporal trend for reduced eGFR was observed.
Table 2.
Clinical Manifestations of Kidney Disease Among US Adults With Diabetes, 1988 Through 2014
| NHANES Period | No. With Diabetes | Unadjusted Prevalence, % (95% CI)
|
Adjusted Prevalence Ratio (95% CI)b | P Value for Trend | |
|---|---|---|---|---|---|
| Based on a Single Laboratory Value | Accounting for Persistencea | ||||
| Any diabetic kidney diseasec | |||||
| 1988–1994 | 640 | 42.5 (38.4–46.6) | 28.4 (23.8–32.9) | 1 [Reference] | .39 |
| 1999–2004 | 659 | 40.5 (37.5–43.6) | 27.3 (23.1–31.4) | 1.00 (0.90–1.11) | |
| 2005–2008 | 573 | 39.3 (36.0–42.7) | 27.1 (22.6–31.4) | 0.99 (0.88–1.10) | |
| 2009–2014 | 874 | 38.1 (35.3–41.0) | 26.2 (22.6–29.9) | 0.95 (0.86–1.06) | |
| Albuminuria (ACR ≥30 mg/g) | |||||
| 1988–1994 | 534 | 35.2 (31.1–39.5) | 20.8 (16.3–25.3) | 1 [Reference] | <.001 |
| 1999–2004 | 531 | 32.1 (29.0–35.3) | 18.9 (15.3–22.4) | 0.93 (0.79–1.06) | |
| 2005–2008 | 447 | 30.4 (27.6–33.4) | 17.9 (14.0–21.9) | 0.86 (0.75–1.01) | |
| 2009–2014 | 645 | 27.1 (24.1–30.3) | 15.9 (12.7–19.0) | 0.76 (0.65–0.89) | |
| Macroalbuminuria (ACR ≥300 mg/g) | |||||
| 1988–1994 | 155 | 7.9 (6.0–10.4) | 5.6 (2.8–8.4) | 1 [Reference] | .22 |
| 1999–2004 | 141 | 7.4 (5.9–9.2) | 5.4 (3.1–7.7) | 0.93 (0.65–1.31) | |
| 2005–2008 | 111 | 6.9 (5.4–8.7) | 4.9 (2.7–7.1) | 0.86 (0.60–1.23) | |
| 2009–2014 | 171 | 6.7 (5.6–8.2) | 5.0 (3.3–6.6) | 0.82 (0.59–1.14) | |
| Estimated GFR <60 mL/min/1.73 m2 | |||||
| 1988–1994 | 214 | 13.1 (10.9–15.7) | 9.2 (6.2–12.2) | 1 [Reference] | <.001 |
| 1999–2004 | 273 | 16.0 (14.1–18.2) | 11.6 (8.5–14.6) | 1.33 (1.09–1.63) | |
| 2005–2008 | 242 | 16.6 (14.2–19.4) | 11.8 (8.4–15.1) | 1.38 (1.09–1.75) | |
| 2009–2014 | 450 | 20.1 (18.5–21.8) | 14.1 (11.3–17.0) | 1.61 (1.33–1.95) | |
| Estimated GFR <30 mL/min/1.73 m2 | |||||
| 1988–1994 | 22 | 1.0 (0.5–2.0) | NA | 1 [Reference] | .004 |
| 1999–2004 | 39 | 1.7 (1.1–2.6) | NA | 1.86 (0.87–3.98) | |
| 2005–2008 | 28 | 1.8 (1.2–2.7) | NA | 1.93 (0.90–4.11) | |
| 2009–2014 | 62 | 2.7 (2.0–3.7) | NA | 2.86 (1.38–5.91) | |
Abbreviations: ACR, albumin-to creatinine ratio; GFR, glomerular filtration rate; NA, data not applicable; NHANES, National Health and Nutrition Examination Surveys.
Defined as the fraction of participants with elevated ACR, reduced estimated GFR, or both, on initial examination whose values remained abnormal during repeat testing. The estimated persistence of estimated GFR of less than 30 mL/min/1.73m2 was 100%.
Adjusted for age, sex, and race/ethnicity.
Defined as urine ACR of 30 mg/g or greater or estimated GFR of less than 60 mL/min/1.73m2, or both.
Table 3.
Prevalence of Albuminuria and Reduced Estimated Glomerular Filtration Rate Among US Adults With Diabetes by Age, 1988 Through 2014
| NHANES Period | No. With Diabetes | Unadjusted Prevalence, % (95% CI)
|
Adjusted Prevalence Ratio (95% CI)b | P Value for Trend | |
|---|---|---|---|---|---|
| Based on a Single Laboratory Value | Accounting for Persistencea | ||||
| Albuminuria (ACR ≥30 mg/g)c | |||||
| Adults aged <65 y | |||||
| 1988–1994 | 256 | 33.5 (28.3–39.1) | 19.5 (13.5–25.4) | 1 [Reference] | .001 |
| 1999–2004 | 244 | 30.0 (25.9–34.4) | 17.6 (12.9–22.3) | 0.89 (0.72–1.11) | |
| 2005–2008 | 224 | 26.6 (22.9–30.7) | 15.7 (10.5–20.8) | 0.80 (0.64–0.99) | |
| 2009–2014 | 327 | 23.9 (20.6–27.6) | 14.0 (10.1–18.0) | 0.70 (0.57–0.87) | |
| Adults aged ≥65 y | |||||
| 1988–1994 | 278 | 37.7 (31.7–44.2) | 22.1 (15.9–28.4) | 1 [Reference] | .15 |
| 1999–2004 | 287 | 35.7 (31.6–39.9) | 20.7 (15.9–25.5) | 0.94 (0.77–1.15) | |
| 2005–2008 | 223 | 36.8 (33.6–40.2) | 21.9 (17.0–26.8) | 0.96 (0.80–1.16) | |
| 2009–2014 | 318 | 32.3 (28.2–36.7) | 19.2 (14.9–23.4) | 0.84 (0.68–1.03) | |
| Reduced Estimated Glomerular Filtration Rate (eGFR <60 mL/min/1.73 m2)d | |||||
| Adults aged <65 y | |||||
| 1988–1994 | 40 | 4.0 (2.4–6.5) | 2.9 (0–5.9) | 1 [Reference] | .15 |
| 1999–2004 | 43 | 5.3 (3.8–7.4) | 3.9 (1.3–6.5) | 1.45 (0.80–2.61) | |
| 2005–2008 | 53 | 6.0 (4.3–8.3) | 4.3 (1.8–6.9) | 1.62 (0.89–2.94) | |
| 2009–2014 | 95 | 7.6 (5.9–9.9) | 5.5 (2.9–8.2) | 1.95 (1.12–3.39) | |
| Adults aged ≥65 y | |||||
| 1988–1994 | 174 | 27.3 (23.3–31.8) | 19.3 (13.4–25.3) | 1 [Reference] | <.001 |
| 1999–2004 | 230 | 34.3 (30.1–38.8) | 24.6 (18.4–30.9) | 1.26 (1.04–1.54) | |
| 2005–2008 | 189 | 34.6 (28.6–41.3) | 24.4 (18.0–30.9) | 1.28 (0.99–1.64) | |
| 2009–2014 | 355 | 40.6 (36.5–44.8) | 28.9 (22.9–34.9) | 1.53 (1.27–1.85) | |
Abbreviations: ACR, albumin-to-creatinine ratio; NHANES, National Health and Nutrition Examination Surveys.
Defined as the fraction of participants with elevated urine albumin-to-creatinine ratio, reduced estimated glomerular filtration rate, or both, on initial examination whose values remained abnormal during repeat testing.
Adjusted for age, sex, and race/ethnicity.
The age × time interaction was P = .049.
The age × time interaction was P = .41.
Table 4.
Prevalence of Albuminuria and Reduced Estimated Glomerular Filtration Rate Among US Adults With Diabetes by Race/Ethnicity, 1988 Through 2014
| NHANES Period | No. With Diabetes | Unadjusted Prevalence, % (95% CI)
|
Adjusted Prevalence Ratio (95% CI)b | P Value for Trend | |
|---|---|---|---|---|---|
| Based on a Single Laboratory Value | Accounting for Persistencea | ||||
| Albuminuria (ACR ≥30 mg/g)c | |||||
| Non-Hispanic white | |||||
| 1988–1994 | 179 | 35.9 (30.6–41.5) | 21.2 (14.9–27.5) | 1 [Reference] | .001 |
| 1999–2004 | 179 | 28.5 (24.6–32.8) | 17.1 (12.8–21.4) | 0.81 (0.65–0.99) | |
| 2005–2008 | 169 | 28.9 (25.3–32.8) | 17.4 (12.8–22.1) | 0.82 (0.68–1.00) | |
| 2009–2014 | 204 | 24.1 (20.0–28.7) | 14.2 (9.9–18.5) | 0.67 (0.53–0.85) | |
| Non-Hispanic black | |||||
| 1988–1994 | 153 | 32.9 (28.5–37.6) | 19.4 (14.0–24.9) | 1 [Reference] | .50 |
| 1999–2004 | 127 | 36.1 (31.0–41.6) | 21.1 (15.6–26.6) | 1.09 (0.89–1.33) | |
| 2005–2008 | 131 | 32.7 (27.7–38.0) | 19.2 (13.7–24.8) | 1.00 (0.81–1.22) | |
| 2009–2014 | 173 | 30.8 (27.4–34.4) | 18.3 (13.7–22.9) | 0.93 (0.78–1.11) | |
| Mexican American | |||||
| 1988–1994 | 184 | 34.5 (29.3–40.0) | 20.4 (14.2–26.6) | 1 [Reference] | .95 |
| 1999–2004 | 179 | 36.0 (31.5–40.7) | 20.9 (15.4–26.3) | 1.03 (0.85–1.25) | |
| 2005–2008 | 95 | 35.5 (28.8–42.8) | 21.0 (14.2–27.8) | 1.01 (0.79–1.30) | |
| 2009–2014 | 131 | 35.1 (29.6–41.0) | 21.0 (15.1–27.0) | 1.00 (0.80–1.24) | |
| Reduced Estimated Glomerular Filtration Rate (eGFR <60 mL/min/1.73 m2)d | |||||
| Non-Hispanic white | |||||
| 1988–1994 | 102 | 14.2 (11.4–17.7) | 9.8 (5.5–14.0) | 1 [Reference] | <.001 |
| 1999–2004 | 138 | 18.6 (16.1–21.3) | 12.9 (8.7–17.1) | 1.36 (1.06–1.73) | |
| 2005–2008 | 123 | 19.0 (15.1–23.8) | 13.3 (8.1–18.6) | 1.42 (1.05–1.92) | |
| 2009–2014 | 206 | 23.4 (21.2–25.7) | 16.1 (12.1–20.0) | 1.65 (1.32–2.06) | |
| Non-Hispanic black | |||||
| 1988–1994 | 63 | 12.0 (9.6–15.0) | 8.2 (4.6–11.8) | 1 [Reference] | <.001 |
| 1999–2004 | 63 | 14.2 (11.4–17.5) | 9.6 (5.3–14.0) | 1.18 (0.89–1.56) | |
| 2005–2008 | 70 | 16.4 (12.1–22.0) | 11.5 (6.1–17.0) | 1.39 (1.01–1.92) | |
| 2009–2014 | 120 | 19.0 (16.1–22.4) | 13.0 (9.0–17.1) | 1.55 (1.20–2.01) | |
| Mexican American | |||||
| 1988–1994 | 43 | 6.7 (4.2–10.4) | 4.6 (1.5–7.7) | 1 [Reference] | .14 |
| 1999–2004 | 56 | 7.6 (5.3–10.8) | 5.3 (2.3–8.3) | 1.11 (0.66–1.86) | |
| 2005–2008 | 31 | 8.4 (5.2–13.5) | 5.8 (1.8–9.8) | 1.21 (0.67–2.21) | |
| 2009–2014 | 50 | 10.4 (7.8–13.7) | 7.2 (3.0–11.4) | 1.42 (0.88–2.31) | |
Abbreviations: ACR, albumin-to-creatinine ratio; NHANES, National Health and Nutrition Examination Surveys.
Defined as the fraction of participants with elevated urine albumin-to-creatinine ratio, reduced estimated glomerular filtration rate, or both, on initial examination whose values remained abnormal during repeat testing.
Adjusted for age, sex, and race/ethnicity.
The race/ethnicity × time interaction was P = .007.
The race/ethnicity × time interaction was P = .99.
Clinical Characteristics of Adults With Various Manifestations of DKD
InNHANES2005–2008, using estimates that do not take into account persistence of albuminuria or reduced eGFR, 39.3% of adults with diabetes had DKD manifested as albuminuria (21.6%), reduced eGFR (8.9%), or both (8.8%) (eTable 4 in the Supplement). Compared with participants with out reduced eGFR, those with reduced eGFR were older, had a longer duration of diabetes, were more likely to be women and white, and were more likely to take RAAS inhibitors and lipid-lowering medications, have lower hemoglobin A1c, have diabetic retinopathy, and report a history of clinically diagnosed macrovascular disease regardless of whether albuminuria was also present.
Discussion
Among representative samples of adults with diabetes mellitus in the United States, there was a change in the clinical manifestations of kidney disease over the last 26 years, with a decline in the prevalence of albuminuria and an increase in the prevalence of reduced eGFR. These changes were independent of characteristics of adults with diabetes. Changes in the more severe manifestations of macro albuminuria and eGFR of less than 30 mL/min/1.73m2 were consistent with those of albuminuria and eGFR of less than 60 mL/min/1.73 m2, respectively.
Significant heterogeneity in the temporal trend for albuminuria prevalence was noted by age and race/ethnicity. The lower prevalence of albuminuria over time was observed only among adults younger than 65 years and non-Hispanic whites, whereas the prevalence of reduced eGFR appeared to increase without significant differences by age or race/ethnicity. The proportion of US adults with diabetes who met any criteria for DKD was stable over time, with an estimate of 26.2% (95% CI, 22.6%–29.9%) in 2009–2014. Using 2010 census data, this translates to a prevalence of approximately 8.2 million people (95% CI, 6.5–9.9 million people) with any DKD, including 4.6 million people (95% CI, 3.4–5.8 million people) with albuminuria, 1.9 million people (95% CI, 1.0–2.8 million people) with macroalbuminuria, 4.5 million people (95% CI, 3.3–5.7 million people) with reduced eGFR, and 0.9 million people (95% CI, 0.6–1.3 million) with severely reduced eGFR.
We previously reported an increase in the prevalence of reduced eGFR but no significant change in the prevalence of albuminuria among US adults with diabetes from 1988 to 2008.2 In this study, the analyses of data collected through 2014 demonstrated a significant temporal decrease in the prevalence of albuminuria in addition to a continuation of the increase in prevalence of reduced GFR. Furthermore, we evaluated temporal trends in more advanced manifestations of DKD, observing an increase in the prevalence of severely reduced GFR that paralleled that of reduced GFR. We also examined relevant subgroups, observing significant age and race/ethnicity × time interactions and identifying older adults and racial/ethnic minorities as groups with less favorable trends for albuminuria. Repeat testing was used to more accurately define DKD based on the persistence of albuminuria and reduced eGFR. Albuminuria and eGFR have substantial biological (intra individual) variation, and current guidelines recommend that only persistent abnormalities be considered diagnostic of DKD.1
The lower prevalence of albuminuria observed over time maybe attributable to a higher rate of prescribed diabetes therapies (glucose-lowering medications, RAAS inhibitors, and statins). Lowering blood glucose level has consistently reduced the development of albuminuria in clinical trials,24–26 and an increase in the use of glucose-lowering medications and lower mean hemoglobin A1c values were observed over time in this study. Furthermore, RAAS inhibitors and blood pressure control reduce albuminuria through hemodynamic and other mechanisms,27,28 and the increasing use of these agents and lower mean blood pressure levels were also noted over time. The lack of decline in albuminuria prevalence among blacks and Mexican Americans may be attributable in part to less frequent use of proven diabetes therapies, as observed herein and in other reports.29
Reasons for the increasing prevalence of reduced eGFR cannot be conclusively discerned from these data. Estimated GFR declines with age, but aging is not likely to be responsible for the observed trends in eGFR because the age distribution of the US adult population with diabetes did not change significantly over time and trends persisted after adjustment for demographic factors. It is possible that hemodynamic effects of RAAS inhibitors and improved blood pressure control could contribute to lower eGFR. Alternatively, an increasing duration of diabetes may be contributing to kidney damage.
There was amonotonic increase in diabetes duration from 1988 to 2014. During the same interval, there was no change in mean age, suggesting that the mean age of diabetes onset may have decreased. Earlier age at diabetes onset combined with decreased mortality due to cardiovascular disease and other diabetes complications30 could allow adults with diabetes time to develop progressive long-term kidney damage. In NHANES 2005–2008, reduced eGFR was associated with retinopathy and macrovascular disease, regardless of whether albuminuria was present, suggesting that reduced eGFR is occurring in the setting of other long-term diabetes complications.
To reduce the prevalence of reduced GFR in diabetes, new therapies may be needed. The shift in clinical manifestations of DKD has implications for clinical trials. Clinical trials of novel DKD therapies commonly target patients with macro albuminuria because they are at high risk of GFR loss,14 particularly when GFR is already low. However, adults with macro albuminuria forma small and diminishing subset of those with diabetes, estimated at 5.0% in the 2009–2014 NHANES survey, and even fewer have concomitant reduced eGFR. To mitigate the large public health effect of the growing DKD population in the United States and around the world,1,31 clinical trials will need to address a broader range of DKD presentations.
This study has limitations. First, it is possible that incomplete standardization of serum creatinine, urine albumin, and creatinine measurements over time may have contributed to the temporal drift, as previously described.2 Second, the estimates of persistence were based on a subsample of each NHANES cohort, potentially reducing precision; however, reliance on these subsamples was unlikely to have biased the analyses of temporal trends. Third, data were not available to determine the underlying causes of DKD, and some of the identified kidney disease was likely caused by processes other than diabetes. Fourth, the proportion of adults with type 1 diabetes was small and therefore results are primarily relevant to adults with type 2 diabetes. Strengths of this study include use of nationally representative data, incorporation of persistence into the estimation of prevalence based on relevant repeat albuminuria and serum creatinine measurements, and ascertainment of both moderate and severe DKD.
Conclusions
Among US adults with diabetes from 1988 to 2014, the overall prevalence of DKD did not change significantly, whereas the prevalence of albuminuria declined and the prevalence of reduced eGFR increased.
Supplementary Material
Key Points.
Question
Have the clinical manifestations of kidney disease among adults with diabetes changed over time?
Findings
In serial cross-sectional studies of US adults with diabetes mellitus participating in National Health and Nutrition Examination Surveys, no change in the prevalence of diabetic kidney disease was observed from 1988 through 2014, but there was a significant decrease in the prevalence of albuminuria and a significant increase in the prevalence of reduced glomerular filtration rate.
Meaning
The clinical manifestations of diabetic kidney disease changed from 1988 to 2014, with a lower prevalence of albuminuria and a higher prevalence of reduced glomerular filtration rate in 2014 compared with 1988.
Acknowledgments
Funding/Support: This research was funding by grants R01DK087726, R01DK088762, R01DK099199, K23DK089017, and R01DK104706 from the National Institute of Diabetes and Digestive and Kidney Diseases, grant UL1TR000423 from the National Institute of Clinical and Translational Sciences, components of the National Institutes of Health, grant 4-15-CKD-20 from the American Diabetes Association, and unrestricted funding from Northwest Kidney Centers.
Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Footnotes
Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Hall reported receiving other from the Group Health Cooperative and the American Kidney Fund. Dr Tuttle reported receiving personal fees for serving as a consultant to Eli Lilly and Company, Amgen, Noxxon Pharma, and Boehringer-Ingelheim. Dr de Boer reported receiving personal fees for serving on advisory boards for Bayer, Boehringer-Ingelheim, Ironwood, Amgen, and Janssen; grants from Abbvie, the National Institute of Diabetes and Digestive and Kidney Diseases, the National Heart, Lung, and Blood Institute, the American Diabetes Assocation, and the Juvenile Diabetes Research Foundation; and research equipment and supplies from Abbott and MedTronic. No other disclosures were reported.
Disclaimer: The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institutes of Health, the American Diabetes Association, or Northwest Kidney Centers.
Author Contributions: Dr de Boer had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Heagerty, Tuttle, Weiss, de Boer.
Acquisition, analysis, or interpretation of data: Afkarian, Zelnick, Hall, Heagerty, Tuttle, de Boer.
Drafting of the manuscript: Afkarian, Tuttle, de Boer.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Zelnick, Heagerty.
Obtained funding: de Boer.
Administrative, technical, or material support: Afkarian.
Study supervision: Hall, de Boer.
References
- 1.Tuttle KR, Bakris GL, Bilous RW, et al. Diabetic kidney disease: a report from an ADA consensus conference. Diabetes Care. 2014;37(10):2864–2883. doi: 10.2337/dc14-1296. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.de Boer IH, Rue TC, Hall YN, Heagerty PJ, Weiss NS, Himmelfarb J. Temporal trends in the prevalence of diabetic kidney disease in the United States. JAMA. 2011;305(24):2532–2539. doi: 10.1001/jama.2011.861. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Tuttle KR, Stein JH, DeFronzo RA. The natural history of diabetic nephropathy. Semin Nephrol. 1990;10(3):184–193. [PubMed] [Google Scholar]
- 4.Costacou T, Ellis D, Fried L, Orchard TJ. Sequence of progression of albuminuria and decreased GFR in persons with type 1 diabetes: a cohort study. Am J Kidney Dis. 2007;50(5):721–732. doi: 10.1053/j.ajkd.2007.08.005. [DOI] [PubMed] [Google Scholar]
- 5.Perkins BA, Ficociello LH, Roshan B, Warram JH, Krolewski AS. In patients with type 1 diabetes and new-onset microalbuminuria, the development of advanced chronic kidney disease may not require progression to proteinuria. Kidney Int. 2010;77(1):57–64. doi: 10.1038/ki.2009.399. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Molitch ME, Steffes M, Sun W, et al. Epidemiology of Diabetes Interventions and Complications Study Group. Development and progression of renal insufficiency with and without albuminuria in adults with type 1 diabetes in the Diabetes Control and Complications trial and the Epidemiology of Diabetes Interventions and Complications study. Diabetes Care. 2010;33(7):1536–1543. doi: 10.2337/dc09-1098. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Tsalamandris C, Allen TJ, Gilbert RE, et al. Progressive decline in renal function in diabetic patients with and without albuminuria. Diabetes. 1994;43(5):649–655. doi: 10.2337/diab.43.5.649. [DOI] [PubMed] [Google Scholar]
- 8.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(24):3273–3277. doi: 10.1001/jama.289.24.3273. [DOI] [PubMed] [Google Scholar]
- 9.Thomas MC, Macisaac RJ, Jerums G, et al. Nonalbuminuric renal impairment in type 2 diabetic patients and in the general population (National Evaluation of the Frequency of Renal Impairment Co-existing with NIDDM [NEFRON] 11) Diabetes Care. 2009;32(8):1497–1502. doi: 10.2337/dc08-2186. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Bojestig M, Arnqvist HJ, Karlberg BE, Ludvigsson J. Glycemic control and prognosis in type I diabetic patients with microalbuminuria. Diabetes Care. 1996;19(4):313–317. doi: 10.2337/diacare.19.4.313. [DOI] [PubMed] [Google Scholar]
- 11.Perkins BA, Ficociello LH, Silva KH, Finkelstein DM, Warram JH, Krolewski AS. Regression of microalbuminuria in type 1 diabetes. N Engl J Med. 2003;348(23):2285–2293. doi: 10.1056/NEJMoa021835. [DOI] [PubMed] [Google Scholar]
- 12.Rossing P, Hougaard P, Parving HH. Progression of microalbuminuria in type 1 diabetes: ten-year prospective observational study. Kidney Int. 2005;68(4):1446–1450. doi: 10.1111/j.1523-1755.2005.00556.x. [DOI] [PubMed] [Google Scholar]
- 13.de Boer IH, Rue TC, Cleary PA, et al. Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study Research Group. Long-term renal outcomes of patients with type 1 diabetes mellitus and microalbuminuria: an analysis of the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications cohort. Arch Intern Med. 2011;171(5):412–420. doi: 10.1001/archinternmed.2011.16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.de Boer IH, Afkarian M, Rue TC, et al. Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Research Group. Renal outcomes in patients with type 1 diabetes and macroalbuminuria. J Am Soc Nephrol. 2014;25(10):2342–2350. doi: 10.1681/ASN.2013091004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.US Centers for Disease Control and Prevention; National Center for Health Statistics. [Accessed December 1, 2010];National Health and Nutrition Examination Survey 1988–1994, 1999–2000, 2001–2002, 2003–2004, 2005–2006, and 2007–2008 documentation files. http://www.cdc.gov/nchs/nhanes.htm.
- 16.Diabetes Control and Complications Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993;329(14):977–986. doi: 10.1056/NEJM199309303291401. [DOI] [PubMed] [Google Scholar]
- 17.Cowie CC, Rust KF, Byrd-Holt DD, et al. Prevalence of diabetes and high risk for diabetes using A1C criteria in the US population in 1988–2006. Diabetes Care. 2010;33(3):562–568. doi: 10.2337/dc09-1524. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.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(5):920–929. doi: 10.1053/ajkd.2002.32765. [DOI] [PubMed] [Google Scholar]
- 19.Selvin E, Manzi J, Stevens LA, et al. Calibration of serum creatinine in the National Health and Nutrition Examination Surveys (NHANES) 1988–1994, 1999–2004. Am J Kidney Dis. 2007;50(6):918–926. doi: 10.1053/j.ajkd.2007.08.020. [DOI] [PubMed] [Google Scholar]
- 20.Coresh J, Selvin E, Stevens LA, et al. Prevalence of chronic kidney disease in the United States. JAMA. 2007;298(17):2038–2047. doi: 10.1001/jama.298.17.2038. [DOI] [PubMed] [Google Scholar]
- 21.Levey AS, Stevens LA, Schmid CH, et al. CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604–612. doi: 10.7326/0003-4819-150-9-200905050-00006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.R Foundation for Statistical Computing. A language and environment for statistical computing. http://www.R-project.org.
- 23.Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York, NY: J Wiley & Sons; 1987. [Google Scholar]
- 24.Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med. 2008;359(15):1577–1589. doi: 10.1056/NEJMoa0806470. [DOI] [PubMed] [Google Scholar]
- 25.Duckworth W, Abraira C, Moritz T, et al. VADT Investigators. Glucose control and vascular complications in veterans with type 2 diabetes. N Engl J Med. 2009;360(2):129–139. doi: 10.1056/NEJMoa0808431. [DOI] [PubMed] [Google Scholar]
- 26.DCCT/EDIC Research Group. Effect of intensive diabetes treatment on albuminuria in type 1 diabetes: long-term follow-up of the Diabetes Control and Complications Trial and Epidemiology of Diabetes Interventions and Complications study. Lancet Diabetes Endocrinol. 2014;2(10):793–800. doi: 10.1016/S2213-8587(14)70155-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Klahr S, Levey AS, Beck GJ, et al. Modification of Diet in Renal Disease Study Group. The effects of dietary protein restriction and blood-pressure control on the progression of chronic renal disease. N Engl J Med. 1994;330(13):877–884. doi: 10.1056/NEJM199403313301301. [DOI] [PubMed] [Google Scholar]
- 28.Parving HH, Lehnert H, Bröchner-Mortensen J, Gomis R, Andersen S, Arner P Irbesartan in Patients with Type 2 Diabetes and Microalbuminuria Study Group. The effect of irbesartan on the development of diabetic nephropathy in patients with type 2 diabetes. N Engl J Med. 2001;345(12):870–878. doi: 10.1056/NEJMoa011489. [DOI] [PubMed] [Google Scholar]
- 29.Stark Casagrande S, Fradkin JE, Saydah SH, Rust KF, Cowie CC. The prevalence of meeting A1C, blood pressure, and LDL goals among people with diabetes, 1988–2010. Diabetes Care. 2013;36(8):2271–2279. doi: 10.2337/dc12-2258. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Gregg EW, Li Y, Wang J, et al. Changes in diabetes-related complications in the United States, 1990–2010. N Engl J Med. 2014;370(16):1514–1523. doi: 10.1056/NEJMoa1310799. [DOI] [PubMed] [Google Scholar]
- 31.Molitch ME, Adler AI, Flyvbjerg A, et al. Diabetic kidney disease: a clinical update from Kidney Disease: Improving Global Outcomes. Kidney Int. 2015;87(1):20–30. doi: 10.1038/ki.2014.128. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.