Skip to main content

Main menu

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Article Collections
    • JASN Podcasts
    • Archives
    • Saved Searches
    • ASN Meeting Abstracts
  • Authors
    • Submit a Manuscript
    • Author Resources
  • Editorial Team
  • Subscriptions
  • More
    • About JASN
    • Alerts
    • Advertising
    • Editorial Fellowship Team
    • Feedback
    • Reprints
    • Impact Factor
    • Editorial Fellowship Application Process
  • ASN Kidney News
  • Other
    • CJASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology

User menu

  • Subscribe
  • My alerts
  • Log in
  • Log out
  • My Cart

Search

  • Advanced search
American Society of Nephrology
  • Other
    • CJASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology
  • Subscribe
  • My alerts
  • Log in
  • Log out
  • My Cart
Advertisement
American Society of Nephrology

Advanced Search

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Article Collections
    • JASN Podcasts
    • Archives
    • Saved Searches
    • ASN Meeting Abstracts
  • Authors
    • Submit a Manuscript
    • Author Resources
  • Editorial Team
  • Subscriptions
  • More
    • About JASN
    • Alerts
    • Advertising
    • Editorial Fellowship Team
    • Feedback
    • Reprints
    • Impact Factor
    • Editorial Fellowship Application Process
  • ASN Kidney News
  • Follow JASN on Twitter
  • Visit ASN on Facebook
  • Follow JASN on RSS
  • Community Forum
Clinical Epidemiology
You have accessRestricted Access

Kidney Disease and Increased Mortality Risk in Type 2 Diabetes

Maryam Afkarian, Michael C. Sachs, Bryan Kestenbaum, Irl B. Hirsch, Katherine R. Tuttle, Jonathan Himmelfarb and Ian H. de Boer
JASN February 2013, 24 (2) 302-308; DOI: https://doi.org/10.1681/ASN.2012070718
Maryam Afkarian
*Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michael C. Sachs
*Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bryan Kestenbaum
*Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Irl B. Hirsch
†Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, University of Washington, Seattle, Washington;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Katherine R. Tuttle
*Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington;
‡Providence Medical Research Center, Providence Sacred Heart Medical Center, Spokane, Washington and Kidney Research Institute, Department of Medicine, University of Washington, Seattle, Washington
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jonathan Himmelfarb
*Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ian H. de Boer
*Kidney Research Institute and Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data Supps
  • Info & Metrics
  • View PDF
Loading

Abstract

Type 2 diabetes associates with increased risk of mortality, but how kidney disease contributes to this mortality risk among individuals with type 2 diabetes is not completely understood. Here, we examined 10-year cumulative mortality by diabetes and kidney disease status for 15,046 participants in the Third National Health and Nutrition Examination Survey (NHANES III) by linking baseline data from NHANES III with the National Death Index. Kidney disease, defined as urinary albumin/creatinine ratio ≥30 mg/g and/or estimated GFR ≤60 ml/min per 1.73 m2, was present in 9.4% and 42.3% of individuals without and with type 2 diabetes, respectively. Among people without diabetes or kidney disease (reference group), 10-year cumulative all-cause mortality was 7.7% (95% confidence interval [95% CI], 7.0%–8.3%), standardized to population age, sex, and race. Among individuals with diabetes but without kidney disease, standardized mortality was 11.5% (95% CI, 7.9%–15.2%), representing an absolute risk difference with the reference group of 3.9% (95% CI, 0.1%–7.7%), adjusted for demographics, and 3.4% (95% CI, −0.3% to 7.0%) when further adjusted for smoking, BP, and cholesterol. Among individuals with both diabetes and kidney disease, standardized mortality was 31.1% (95% CI, 24.7%–37.5%), representing an absolute risk difference with the reference group of 23.4% (95% CI, 17.0%–29.9%), adjusted for demographics, and 23.4% (95% CI, 17.2%–29.6%) when further adjusted. We observed similar patterns for cardiovascular and noncardiovascular mortality. In conclusion, those with kidney disease predominantly account for the increased mortality observed in type 2 diabetes.

In 2012, there were an estimated 346 million individuals with diabetes worldwide.1 This number is expected to rise to >430 million by 2030.2 Diabetes is associated with substantially increased risk of mortality, particularly due to cardiovascular disease.3

Kidney disease, defined by increased urine albumin excretion and/or impaired GFR, is also strongly associated with increased risk of all-cause and cardiovascular mortality, both among persons with diabetes4,5 and in the general population.6–10 The critical effect of kidney disease on mortality in type 1 diabetes was emphasized in two recent reports.11,12 Each study demonstrated that excess mortality was confined to the subgroup with kidney disease.

The degree to which kidney disease captures risk of adverse health outcomes in type 2 diabetes has not been determined. The findings from type 1 diabetes may not extrapolate to type 2 diabetes because the latter is frequently associated with other comorbidities that affect mortality. This question has crucial public health implications because type 2 diabetes predominates among the 26 million US adults with diabetes13,14 and identifying predictors of excess mortality in type 2 diabetes is essential in order to optimally target risk-reduction strategies. The primary objective of this study was to quantify and compare the excess risk of all-cause and cause-specific mortality among individuals with type 2 diabetes in presence or absence of kidney disease.

Results

Of 15,762 individuals aged ≥20 years in the Third National Health and Nutrition Examination Survey (NHANES III), 15,046 have follow-up mortality data to 2006 and were included in this study (95.5%). Of these, 9.5% had type 2 diabetes (Table 1, Supplemental Table 1). Among persons with diabetes, 42.3% had kidney disease, as defined by albuminuria, impaired GFR or both (Figure 1). In comparison, 9.4% of people without diabetes had kidney disease. Participants with diabetes, kidney disease, or both were older and had higher mean systolic BP and higher mean concentrations of non-HDL cholesterol (Table 1).

View this table:
  • View inline
  • View popup
Table 1.

Baseline characteristics of participants

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Prevalence (A) and manifestations (B) of kidney disease in diabetic and nondiabetic subpopulations of the United States. Prevalence values are estimated percentages of total US population, calculated using NHANES sample weighing. Error bars indicate 95% CIs. Closed bars (▪) and open bars (□) represent prevalence in individuals with and without diabetes, respectively.

Ten-year cumulative all-cause mortality, standardized to average age, sex, and race in the whole population, was 19.1% (95% confidence interval [95% CI], 15.5–22.7) among people with diabetes compared with 8.6% (95% CI, 7.9–9.3) among people without diabetes. Standardized 10-year cumulative cardiovascular mortality was 11.2% (95% CI, 8.7–13.7) among people with diabetes compared with 4.0% (95% CI, 3.7–4.4) among people without diabetes. Standardized 10-year cumulative noncardiovascular mortality followed a similar pattern (Table 2).

View this table:
  • View inline
  • View popup
Table 2.

Ten-year standardized all-cause and cardiovascular mortality by diabetes status

In the reference group consisting of people with no diabetes or kidney disease, 10-year cumulative all-cause mortality, standardized to population age, sex and race, was 7.7% (95% CI, 7.0–8.3). Among people with diabetes and no kidney disease, the standardized mortality was 11.5% (95% CI, 7.9–15.2), hence an absolute risk difference compared with the reference group of 3.9% (95% CI, 0.1–7.7) when adjusted for age, sex and race and 3.4% (95% CI, −0.3 to 7.0) after additional adjustment for smoking, BP, and cholesterol. Among individuals with both diabetes and kidney disease, standardized mortality was 31.1% (95% CI, 24.7–37.5), with an absolute risk difference of 23.4% (95% CI, 17.0–29.9) after adjustment for age, sex, and race and 23.4% (95% CI, 17.2–29.6) after additional adjustment for smoking, BP, and cholesterol (Table 3). The same patterns were observed for both cardiovascular and noncardiovascular mortality (Table 3). We observed an interaction between diabetes and kidney disease on the additive scale in which the presence of both was associated with a significantly greater increase in mortality than the sum of increase in mortality with each risk factor alone (P<0.01). This interaction was not present when evaluated on the multiplicative scale (P=0.86).

View this table:
  • View inline
  • View popup
Table 3.

Ten-year standardized all-cause and cardiovascular mortality by diabetes and kidney disease status

We undertook additional analyses to confirm the robustness of the observed associations between kidney disease and mortality. We observed similar results in individuals who were and were not taking renin-angiotensin system (RAS) inhibitors (Supplemental Table 2), although small numbers of events were observed in some strata. We also evaluated the results after excluding 75 participants with estimated GFR (eGFR) <30 ml/min per 1.73 m2 (0.5% of the study population), and the results were not substantially different. Risk differences comparing participants with and without kidney disease were similar among participants with undiagnosed and diagnosed diabetes (Supplemental Figure 1). In addition, among individuals with type 2 diabetes, additional adjustment for diabetes-related variables (hemoglobin A1c [HbA1C], diabetes duration, and use of glucose-lowering medications) did not significantly alter the absolute difference in mortality comparing those with and without kidney disease (from 18.9% [95% CI, 12.6–25.2] to 17.9% [95% CI, 11.5–24.3]).

Albuminuria and impaired GFR were each independently associated with increased risks of all-cause mortality in presence or absence of diabetes (Figure 2, Supplemental Table 3). An interaction was detected between albuminuria and GFR among participants without diabetes on the additive (P<0.001) but not the multiplicative scale (P=0.31). This interaction was not statistically significant on either an additive or multiplicative scale in the smaller group with diabetes (P=0.23 and P=0.50, respectively). Associations of impaired GFR with increased mortality risk were observed across the range of albuminuria (Supplemental Figure 2).

Figure 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2.

Ten-year mortality in type 2 diabetes by kidney disease manifestation. Absolute differences in mortality risk were estimated using linear regression and were adjusted for age, sex, and race. Standardized 10-year all-cause cumulative incidences were estimated for the mean levels of the covariates in the study population. The dashed line indicates mortality in persons without diabetes or kidney disease (the reference group). The numbers above bars indicate excess mortality above the reference group. Error bars indicate 95% CIs.

Discussion

Type 2 diabetes was associated with substantially increased risk of all-cause and cardiovascular mortality in the US population, as expected. However, this excess risk was concentrated in the subgroup of people with diabetes and kidney disease, manifest as albuminuria, impaired GFR, or both. Kidney disease was common among people with diabetes and associated with substantially increased mortality risk. Absent kidney disease, diabetes was not associated with a large increase in risk of mortality.

The robust association of kidney disease with mortality in persons with or without diabetes has been observed in previous studies.4–10,15 This study extends this work by examining how kidney disease influences the association of diabetes with mortality. Risk differences were evaluated on the absolute scale, which is particularly relevant to clinical care and public health because it reflects the marginal risk to individuals and populations, taking into account the baseline risk among unexposed members of the population.16–18 Using this approach, we observed an additive interaction between diabetes and kidney disease such that the coexistence of kidney disease and diabetes was associated with a considerably larger excess mortality than the sum of excess risks associated with either risk factor alone. Such an interaction was not observed when evaluated on the relative scale, which has been applied in prior studies.7,19 Our results highlight people with both type 2 diabetes and kidney disease as a population at particularly high risk of adverse health outcomes.

Mortality rates in the absence of kidney disease have been studied in type 1 diabetes11,12,20,21 and a small cohort of individuals with type 2 diabetes.22 In contrast to these studies, which used indirect comparison to population standards, this study compared mortality in individuals with diabetes and no kidney disease directly with mortality in a group of individuals with no diabetes or kidney disease from the same population, using identical measures for assessment and adjusting for major confounders. Surprisingly, in absence of kidney disease, type 2 diabetes was not associated with a large increase in mortality risk. These results suggest that persons with diabetes are heterogeneous with respect to their risk of all-cause and cardiovascular mortality, and that kidney disease powerfully identifies a subset of people with increased health risk.

As observed in prior studies, albuminuria and impaired GFR were independent risk factors for death.4,5,7,9,10,23 The observation that impaired GFR alone is associated with a high mortality risk among persons with diabetes is important because this manifestation of diabetic kidney disease in particular is increasing over time.14 In addition, there was an interaction between albuminuria and impaired GFR such that their combination was associated with a greater difference in mortality than the sum of their individual effects. This interaction was statistically significant only among the large number of participants without diabetes but did not reach statistical significance in the smaller group of participants with diabetes or when risk was evaluated on the relative scale, as in prior studies.10,24

The major limitation of our study is its observational nature. As such, it is not possible to determine whether kidney disease is causally related to excess mortality risk. Kidney disease may be a noncausal marker of cumulative vascular damage. For example, microalbuminuria is highly correlated with general endothelial dysfunction and may reflect widespread vascular damage beyond kidney injury.25 Alternatively, kidney disease may contribute directly to mortality by promoting cardiovascular risk factors such as hypertension, insulin resistance, oxidative stress, endothelial dysfunction, and inflammation. Either way, the presence of kidney disease robustly identifies a diabetes subpopulation at high risk of death.

Additional limitations of this study include the evaluation of kidney function and albuminuria status at a single point in time, lack of follow-up regarding new diabetes diagnoses or changes in kidney function, potential misclassification in determination of cause of death based on International Classification of Diseases codes, and the relatively low prevalence of RAS inhibitor use. Of these, single-point evaluation of kidney function and albuminuria status and lack of follow-up information would likely reduce observed differences in mortality due to nondifferential misclassification. Use of RAS antagonists has become more common since NHANES III,14 but subgroup analyses demonstrating similar associations of diabetes and kidney disease with mortality with or without use of these medications suggest that results are applicable to current medical care. It should be noted that our data do not address the effect of RAS antagonists on mortality, rather their effect on the association between kidney disease and mortality. Study strengths include wide external validity of the data, large sample size, and number of events, uniform assessment of kidney function and diabetes, comparison with population-internal controls, and evaluation of associations and interactions on the clinically relevant additive scale.

This study supports a renewed focus on the prevention and treatment of kidney disease in diabetes. Most importantly, the subgroup with kidney disease appears to carry most of the excess all-cause and cardiovascular mortality risk of type 2 diabetes. Therefore, we suggest that people with both diabetes and kidney disease be targeted for therapeutic interventions designed to reduce cardiovascular disease and mortality.

Concise Methods

Study Population

The NHANES is a population-based program of studies conducted by the National Center for Health Statistics of the US Centers for Disease Control and Prevention. NHANES combines data from interviews, physical examinations, and laboratory assays on collected blood and urine specimens to assess the health and nutritional status of civilian, noninstitutionalized children and adults in the United States. Elderly and ethnic minorities (non-Hispanic blacks and Mexican Americans) are oversampled to enable a more detailed assessment of these groups. NHANES III was conducted between 1988 and 1994 and provides nationally representative data for 33,994 individuals aged ≥2 months. This study uses data from NHANES III participants aged ≥20 years, who participated in a health examination and had available data on medications used, serum creatinine, and urine albumin and creatinine concentrations. Of these, we included only participants who had follow-up mortality data through 2006 (15,046 of 15,762 of NHANES III participants, 95.5%). 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.

Diabetes Definition

Diabetes was defined as use of glucose-lowering medicines and/or HbA1C ≥6.5%, as per recent updates to diagnostic criteria for type 2 diabetes.14,26,27 HbA1C was used to detect diabetes in NHANES participants without necessitating fasting glucose measurements. HbA1C was measured using high-pressure liquid chromatography and standardized to the Diabetes Control and Complications Trials laboratory.28 We excluded participants with probable type 1 diabetes, defined as diabetes diagnosis before age 30 years, first insulin use within 2 years of diagnosis, and current insulin use. Diabetes duration was self-reported by questionnaire.29

Kidney Disease Definition

Kidney disease was defined as albuminuria, impaired GFR, or both. Albuminuria was defined as a urine albumin/creatinine ratio ≥30 mg/g.26,30 In NHANES, urine albumin and creatinine concentrations were measured in one random urine sample. Urine albumin was measured using a solid-phase fluorescent immunoassay, with intra-assay and inter-assay coefficients of variation <8%.31 Serum creatinine was measured using the kinetic Jaffe rate method.28 The NHANES III serum creatinine values were calibrated for use in the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation28 and the eGFR was calculated from the calibrated serum creatinine using the CKD-EPI equation.32 Impaired GFR was defined as a GFR ≤60 ml/min per 1.73 m2.

Other Clinical Characteristics

Age, sex, and race/ethnicity were obtained from questionnaire responses.29 Medicine use during the month before the NHANES physical examination was ascertained by in-person interviews. Body mass index was calculated as weight in kilograms divided by height in meters squared. BP was determined by the average of ≥3 consecutive measurements, separated by 30 seconds and after 5 minutes of rest. Total and HDL cholesterol were measured using a series of enzymatic reactions whose final product was measured using a calorimetric assay.33 Non-HDL cholesterol was evaluated because LDL cholesterol was not available in 56% of individuals (e.g., due to nonfasting status or triglyceride levels >400 mg/dl).28

Outcomes

The main outcomes were death from any cause and death from cardiovascular causes within 10 years of survey participation. These are binary outcomes that allow estimation of risk differences in the US population. Mortality data through December 31, 2006 were obtained by linkage to the National Death Index records using probabilistic matching,34 which was 98.5% complete. National Death Index records provide information on the date and underlying cause of death. Causes of death and definition of cardiovascular International Classification of Diseases codes are described in the Supplemental Material. There was no censoring for 10-year all-cause mortality. However, cause of death was unknown for 1.1% of the study population. Therefore, data on cause-specific mortality were available for 98.9% of this population.

Statistical Analyses

Raw cumulative incidences were estimated by taking the mean of the event indicators. Ten-year cumulative mortality was standardized to the age, sex, and race/ethnicity distribution of the study population. Standardized cumulative incidences were estimated by entering the average covariate values of the study population into the regression model with each possible value of diabetes and kidney disease in order to estimate the 10-year risk at the four possible levels of kidney disease and diabetes for a population with the covariates of the average US adults. Absolute differences in mortality risk were estimated using linear regression. Valid inference was obtained using a Taylor series linearization with adjustment for the sampling weights.35 Linear regression models were adjusted for categorical age (in 10-year categories), sex, and race/ethnicity; additionally adjusted for systolic and diastolic BP (continuous), use of BP medications (dichotomous), non-HDL cholesterol (continuous), and use of lipid-lowering medications (dichotomous); and, among persons with diabetes only, additionally adjusted for duration of diabetes (categories), use of glucose-lowering medications (categories), and HbA1C (continuous). Estimated measures of association were similar to those obtained from a time-to-event analysis using Cox proportional hazards regression.

All statistical analyses were performed using the Survey package36 in the R statistical software.37 The algorithms implement the same theory as the SUDAAN software.38 The analyses incorporated recommended sampling weights provided by the National Center for Health Statistics.29 These weights account for the differential probability of selection and nonresponse and allow for estimation and inference in the civilian, noninstitutionalized US population.35

Disclosures

None.

Acknowledgments

This manuscript was made possible by support from Grants 5K23DK089017-02, 1RO1DK087726, and 1R01DK088762 from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and Grants 5R01HL070938-06 and 1R01HL096875 from the National Heart, Lung, and Blood Institute (NHLBI).

The funding organizations had no role in the design and conduct of the study, collection, management, analysis and interpretation of the data or preparation, review, and approval of the manuscript. The findings and interpretations presented in this manuscript are solely the responsibility of the authors and do not necessarily represent the official viewpoints of the NIDDK, NHLBI, or the National Institutes of Health.

Footnotes

  • Published online ahead of print. Publication date available at www.jasn.org.

  • This article contains supplemental material online at http://jasn.asnjournals.org/lookup/suppl/doi:10.1681/ASN.2012070718/-/DCSupplemental.

  • Copyright © 2013 by the American Society of Nephrology

References

  1. ↵
    World Health Organization: Diabetes Fact Sheet, 2012. Available at: http://www.who.int/mediacentre/factsheets/fs312/en/index.html. Accessed September 12, 2012
  2. ↵
    1. Shaw JE,
    2. Sicree RA,
    3. Zimmet PZ
    : Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract 87: 4–14, 2010
    OpenUrlCrossRefPubMed
  3. ↵
    1. Seshasai SR,
    2. Kaptoge S,
    3. Thompson A,
    4. Di Angelantonio E,
    5. Gao P,
    6. Sarwar N,
    7. Whincup PH,
    8. Mukamal KJ,
    9. Gillum RF,
    10. Holme I,
    11. Njølstad I,
    12. Fletcher A,
    13. Nilsson P,
    14. Lewington S,
    15. Collins R,
    16. Gudnason V,
    17. Thompson SG,
    18. Sattar N,
    19. Selvin E,
    20. Hu FB,
    21. Danesh J,
    22. Emerging Risk Factors Collaboration
    : Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med 364: 829–841, 2011pmid:21366474
    OpenUrlCrossRefPubMed
  4. ↵
    1. de Boer IH,
    2. Katz R,
    3. Cao JJ,
    4. Fried LF,
    5. Kestenbaum B,
    6. Mukamal K,
    7. Rifkin DE,
    8. Sarnak MJ,
    9. Shlipak MG,
    10. Siscovick DS
    : Cystatin C, albuminuria, and mortality among older adults with diabetes. Diabetes Care 32: 1833–1838, 2009pmid:19587367
    OpenUrlAbstract/FREE Full Text
  5. ↵
    1. Ninomiya T,
    2. Perkovic V,
    3. de Galan BE,
    4. Zoungas S,
    5. Pillai A,
    6. Jardine M,
    7. Patel A,
    8. Cass A,
    9. Neal B,
    10. Poulter N,
    11. Mogensen CE,
    12. Cooper M,
    13. Marre M,
    14. Williams B,
    15. Hamet P,
    16. Mancia G,
    17. Woodward M,
    18. Macmahon S,
    19. Chalmers J,
    20. ADVANCE Collaborative Group
    : Albuminuria and kidney function independently predict cardiovascular and renal outcomes in diabetes. J Am Soc Nephrol 20: 1813–1821, 2009pmid:19443635
    OpenUrlAbstract/FREE Full Text
  6. ↵
    1. Szczech LA,
    2. Best PJ,
    3. Crowley E,
    4. Brooks MM,
    5. Berger PB,
    6. Bittner V,
    7. Gersh BJ,
    8. Jones R,
    9. Califf RM,
    10. Ting HH,
    11. Whitlow PJ,
    12. Detre KM,
    13. Holmes D,
    14. Bypass Angioplasty Revascularization Investigation (BARI) Investigators
    : Outcomes of patients with chronic renal insufficiency in the bypass angioplasty revascularization investigation. Circulation 105: 2253–2258, 2002pmid:12010906
    OpenUrlAbstract/FREE Full Text
  7. ↵
    1. Astor BC,
    2. Hallan SI,
    3. Miller ER 3rd,
    4. Yeung E,
    5. Coresh J
    : Glomerular filtration rate, albuminuria, and risk of cardiovascular and all-cause mortality in the US population. Am J Epidemiol 167: 1226–1234, 2008pmid:18385206
    OpenUrlCrossRefPubMed
    1. Bello AK,
    2. Hemmelgarn B,
    3. Lloyd A,
    4. James MT,
    5. Manns BJ,
    6. Klarenbach S,
    7. Tonelli M,
    8. Alberta Kidney Disease Network
    : Associations among estimated glomerular filtration rate, proteinuria, and adverse cardiovascular outcomes. Clin J Am Soc Nephrol 6: 1418–1426, 2011pmid:21527648
    OpenUrlAbstract/FREE Full Text
  8. ↵
    1. Hemmelgarn BR,
    2. Manns BJ,
    3. Lloyd A,
    4. James MT,
    5. Klarenbach S,
    6. Quinn RR,
    7. Wiebe N,
    8. Tonelli M,
    9. Alberta Kidney Disease Network
    : Relation between kidney function, proteinuria, and adverse outcomes. JAMA 303: 423–429, 2010pmid:20124537
    OpenUrlCrossRefPubMed
  9. ↵
    1. Matsushita K,
    2. van der Velde M,
    3. Astor BC,
    4. Woodward M,
    5. Levey AS,
    6. de Jong PE,
    7. Coresh J,
    8. Gansevoort RT,
    9. Chronic Kidney Disease Prognosis Consortium
    : Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: A collaborative meta-analysis. Lancet 375: 2073–2081, 2010pmid:20483451
    OpenUrlCrossRefPubMed
  10. ↵
    1. Groop PH,
    2. Thomas MC,
    3. Moran JL,
    4. Wadèn J,
    5. Thorn LM,
    6. Mäkinen VP,
    7. Rosengård-Bärlund M,
    8. Saraheimo M,
    9. Hietala K,
    10. Heikkilä O,
    11. Forsblom C,
    12. FinnDiane Study Group
    : The presence and severity of chronic kidney disease predicts all-cause mortality in type 1 diabetes. Diabetes 58: 1651–1658, 2009pmid:19401416
    OpenUrlAbstract/FREE Full Text
  11. ↵
    1. Orchard TJ,
    2. Secrest AM,
    3. Miller RG,
    4. Costacou T
    : In the absence of renal disease, 20 year mortality risk in type 1 diabetes is comparable to that of the general population: A report from the Pittsburgh Epidemiology of Diabetes Complications Study. Diabetologia 53: 2312–2319, 2010pmid:20665208
    OpenUrlCrossRefPubMed
  12. ↵
    US Centers for Disease Control and Prevention: 2011 National Diabetes Fact Sheet, 2011. Available at: http://www.cdc.gov/diabetes/pubs/pdf/ndfs_2011.pdf. Accessed August 12, 2011
  13. ↵
    1. de Boer IH,
    2. Rue TC,
    3. Hall YN,
    4. Heagerty PJ,
    5. Weiss NS,
    6. Himmelfarb J
    : Temporal trends in the prevalence of diabetic kidney disease in the United States. JAMA 305: 2532–2539, 2011pmid:21693741
    OpenUrlCrossRefPubMed
  14. ↵
    1. Barkoudah E,
    2. Skali H,
    3. Uno H,
    4. Solomon SD,
    5. Pfeffer MA
    : Mortality rates in trials of subjects with type 2 diabetes. J Am Heart Assoc 1: 8–15, 2012pmid:23130114
    OpenUrlCrossRefPubMed
  15. ↵
    1. Rothman KJ,
    2. Greenland S,
    3. Walker AM
    : Concepts of interaction. Am J Epidemiol 112: 467–470, 1980pmid:7424895
    OpenUrlPubMed
    1. Blot WJ,
    2. Day NE
    : Synergism and interaction: Are they equivalent? Am J Epidemiol 110: 99–100, 1979pmid:463868
    OpenUrlPubMed
  16. ↵
    1. Saracci R
    : Interaction and synergism. Am J Epidemiol 112: 465–466, 1980pmid:7424894
    OpenUrlPubMed
  17. ↵
    Fox CS, Matsushita K, Woodward M, Bilo HJ, Chalmers J, Heerspink HJ, Lee BJ, Perkins RM, Rossing P, Sairenchi T, Tonelli M, Vassalotti JA, Yamagishi K, Coresh J, de Jong PE, Wen CP, Nelson RG; Chronic Kidney Disease Prognosis Consortium: Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: A meta-analysis. Lancet 380: 1662–1673, 2012
  18. ↵
    1. Borch-Johnsen K,
    2. Andersen PK,
    3. Deckert T
    : The effect of proteinuria on relative mortality in type 1 (insulin-dependent) diabetes mellitus. Diabetologia 28: 590–596, 1985pmid:4054448
    OpenUrlCrossRefPubMed
  19. ↵
    1. Rossing P,
    2. Hougaard P,
    3. Borch-Johnsen K,
    4. Parving HH
    : Predictors of mortality in insulin dependent diabetes: 10 year observational follow up study. BMJ 313: 779–784, 1996pmid:8842069
    OpenUrlAbstract/FREE Full Text
  20. ↵
    1. Lutgers HL,
    2. Gerrits EG,
    3. Sluiter WJ,
    4. Ubink-Veltmaat LJ,
    5. Landman GW,
    6. Links TP,
    7. Gans RO,
    8. Smit AJ,
    9. Bilo HJ
    : Life expectancy in a large cohort of type 2 diabetes patients treated in primary care (ZODIAC-10). PLoS ONE 4: e6817, 2009pmid:19714245
    OpenUrlCrossRefPubMed
  21. ↵
    1. Astor BC,
    2. Matsushita K,
    3. Gansevoort RT,
    4. van der Velde M,
    5. Woodward M,
    6. Levey AS,
    7. Jong PE,
    8. Coresh J,
    9. Astor BC,
    10. Matsushita K,
    11. Gansevoort RT,
    12. van der Velde M,
    13. Woodward M,
    14. Levey AS,
    15. de Jong PE,
    16. Coresh J,
    17. El-Nahas M,
    18. Eckardt KU,
    19. Kasiske BL,
    20. Wright J,
    21. Appel L,
    22. Greene T,
    23. Levin A,
    24. Djurdjev O,
    25. Wheeler DC,
    26. Landray MJ,
    27. Townend JN,
    28. Emberson J,
    29. Clark LE,
    30. Macleod A,
    31. Marks A,
    32. Ali T,
    33. Fluck N,
    34. Prescott G,
    35. Smith DH,
    36. Weinstein JR,
    37. Johnson ES,
    38. Thorp ML,
    39. Wetzels JF,
    40. Blankestijn PJ,
    41. van Zuilen AD,
    42. Menon V,
    43. Sarnak M,
    44. Beck G,
    45. Kronenberg F,
    46. Kollerits B,
    47. Froissart M,
    48. Stengel B,
    49. Metzger M,
    50. Remuzzi G,
    51. Ruggenenti P,
    52. Perna A,
    53. Heerspink HJ,
    54. Brenner B,
    55. de Zeeuw D,
    56. Rossing P,
    57. Parving HH,
    58. Auguste P,
    59. Veldhuis K,
    60. Wang Y,
    61. Camarata L,
    62. Thomas B,
    63. Manley T,
    64. Chronic Kidney Disease Prognosis Consortium
    : Lower estimated glomerular filtration rate and higher albuminuria are associated with mortality and end-stage renal disease. A collaborative meta-analysis of kidney disease population cohorts. Kidney Int 79: 1331–1340, 2011pmid:21289598
    OpenUrlCrossRefPubMed
  22. ↵
    1. van der Velde M,
    2. Matsushita K,
    3. Coresh J,
    4. Astor BC,
    5. Woodward M,
    6. Levey A,
    7. de Jong P,
    8. Gansevoort RT,
    9. van der Velde M,
    10. Matsushita K,
    11. Coresh J,
    12. Astor BC,
    13. Woodward M,
    14. Levey AS,
    15. de Jong PE,
    16. Gansevoort RT,
    17. Levey A,
    18. El-Nahas M,
    19. Eckardt KU,
    20. Kasiske BL,
    21. Ninomiya T,
    22. Chalmers J,
    23. Macmahon S,
    24. Tonelli M,
    25. Hemmelgarn B,
    26. Sacks F,
    27. Curhan G,
    28. Collins AJ,
    29. Li S,
    30. Chen SC,
    31. Hawaii Cohort KP,
    32. Lee BJ,
    33. Ishani A,
    34. Neaton J,
    35. Svendsen K,
    36. Mann JF,
    37. Yusuf S,
    38. Teo KK,
    39. Gao P,
    40. Nelson RG,
    41. Knowler WC,
    42. Bilo HJ,
    43. Joosten H,
    44. Kleefstra N,
    45. Groenier KH,
    46. Auguste P,
    47. Veldhuis K,
    48. Wang Y,
    49. Camarata L,
    50. Thomas B,
    51. Manley T,
    52. Chronic Kidney Disease Prognosis Consortium
    : Lower estimated glomerular filtration rate and higher albuminuria are associated with all-cause and cardiovascular mortality. A collaborative meta-analysis of high-risk population cohorts. Kidney Int 79: 1341–1352, 2011pmid:21307840
    OpenUrlCrossRefPubMed
  23. ↵
    1. Deckert T,
    2. Feldt-Rasmussen B,
    3. Borch-Johnsen K,
    4. Jensen T,
    5. Kofoed-Enevoldsen A
    : Albuminuria reflects widespread vascular damage. The Steno hypothesis. Diabetologia 32: 219–226, 1989pmid:2668076
    OpenUrlCrossRefPubMed
  24. ↵
    1. American Diabetes Association
    : Standards of medical care in diabetes—2011. Diabetes Care 34[Suppl 1]: S11–S61, 2011pmid:21193625
    OpenUrlFREE Full Text
  25. ↵
    1. International Expert Committee
    : International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 32: 1327–1334, 2009pmid:19502545
    OpenUrlFREE Full Text
  26. ↵
    US Centers for Disease Control and Prevention, National Center for Health Statistics: National Health and Nutrition Examination Survey III (1988–1994): Laboratory File Documentation, 2006. Available at: ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/nhanes/nhanes3/1A/lab-acc.pdf. Accessed August 12, 2011
  27. ↵
    US Centers for Disease Control and Prevention, National Center for Health Statistics: National Health and Nutrition Examination Survey III (1988–1994): Household Adult Data File Documentation, 1996. Available at: ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/nhanes/nhanes3/1A/ADULT-acc.pdf. Accessed August 12, 2011
  28. ↵
    1. KDOQI
    : KDOQI Clinical Practice Guidelines and Clinical Practice Recommendations for Diabetes and Chronic Kidney Disease. Am J Kidney Dis 49[Suppl 2]: S12–S154, 2007pmid:17276798
    OpenUrlCrossRefPubMed
  29. ↵
    1. Chavers BM,
    2. Simonson J,
    3. Michael AF
    : A solid phase fluorescent immunoassay for the measurement of human urinary albumin. Kidney Int 25: 576–578, 1984pmid:6737844
    OpenUrlCrossRefPubMed
  30. ↵
    1. Levey AS,
    2. Stevens LA,
    3. Schmid CH,
    4. Zhang YL,
    5. Castro AF 3rd,
    6. Feldman HI,
    7. Kusek JW,
    8. Eggers P,
    9. Van Lente F,
    10. Greene T,
    11. Coresh J,
    12. CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration)
    : A new equation to estimate glomerular filtration rate. Ann Intern Med 150: 604–612, 2009pmid:19414839
    OpenUrlCrossRefPubMed
  31. ↵
    1. Hommes F
    1. Bachorik P,
    2. Kwiterovich P
    : The measurement of plasma cholesterol, low density lipoprotein- and high density lipoprotein cholesterol. In: Techniques in Diagnostic Human Biochemical Genetics: A Laboratory Manual, edited by Hommes F, New York, Wiley-Liss Inc., 1991, pp 425–429
  32. ↵
    US Centers for Disease Control and Prevention, National Center for Health Statistics: National Health and Nutrition Examination Survey III (1988–1994): Linked mortality file. 2009. (Accessed August 12, 2011, at http://www.cdc.gov/nchs/data_access/data_linkage/mortality/nhanes3_linkage.htm.)
  33. ↵
    National Center for Health Statistics: Analytic and Reporting Guidelines: The Third National Health and Nutrition Examination Survey, NHANES III (1988–1994), Hyattsville, MD, US Centers for Disease Control and Prevention, 1996
  34. ↵
    CRAN Package Repository: Survey: analysis of complex survey samples, 2011. Available at: http://CRAN.R-project.org/package=survey. Accessed June 2011
  35. ↵
    R Development Core Team. R: A Language and Environment for Statistical Computing, Vienna, Austria, R Foundation for Statistical Computing, 2008
  36. ↵
    Lumley T: Complex Surveys: A Guide to Analysis Using R, Hoboken, NJ, Wiley, 2010
PreviousNext
Back to top

In this issue

Journal of the American Society of Nephrology: 24 (2)
Journal of the American Society of Nephrology
Vol. 24, Issue 2
February 2013
  • Table of Contents
  • Table of Contents (PDF)
  • Index by author
View Selected Citations (0)
Print
Download PDF
Sign up for Alerts
Email Article
Thank you for your help in sharing the high-quality science in JASN.
Enter multiple addresses on separate lines or separate them with commas.
Kidney Disease and Increased Mortality Risk in Type 2 Diabetes
(Your Name) has sent you a message from American Society of Nephrology
(Your Name) thought you would like to see the American Society of Nephrology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Kidney Disease and Increased Mortality Risk in Type 2 Diabetes
Maryam Afkarian, Michael C. Sachs, Bryan Kestenbaum, Irl B. Hirsch, Katherine R. Tuttle, Jonathan Himmelfarb, Ian H. de Boer
JASN Feb 2013, 24 (2) 302-308; DOI: 10.1681/ASN.2012070718

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Request Permissions
Share
Kidney Disease and Increased Mortality Risk in Type 2 Diabetes
Maryam Afkarian, Michael C. Sachs, Bryan Kestenbaum, Irl B. Hirsch, Katherine R. Tuttle, Jonathan Himmelfarb, Ian H. de Boer
JASN Feb 2013, 24 (2) 302-308; DOI: 10.1681/ASN.2012070718
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like

Jump to section

  • Article
    • Abstract
    • Results
    • Discussion
    • Concise Methods
    • Disclosures
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data Supps
  • Info & Metrics
  • View PDF

More in this TOC Section

  • Cardiovascular Risk Based on ASCVD and KDIGO Categories in Chinese Adults: A Nationwide, Population-Based, Prospective Cohort Study
  • Effect of Kidney Function on Relationships between Lifestyle Behaviors and Mortality or Cardiovascular Outcomes: A Pooled Cohort Analysis
  • Subtyping CKD Patients by Consensus Clustering: The Chronic Renal Insufficiency Cohort (CRIC) Study
Show more Clinical Epidemiology

Cited By...

  • Efficacy, safety and response predictors of adjuvant astragalus for diabetic kidney disease (READY): study protocol of an add-on, assessor-blind, parallel, pragmatic randomised controlled trial
  • 11. Microvascular Complications and Foot Care: Standards of Medical Care in Diabetes--2021
  • Linking Kidney and Cardiovascular Complications in Diabetes--Impact on Prognostication and Treatment: The 2019 Edwin Bierman Award Lecture
  • Going in Early: Hypoxia as a Target for Kidney Disease Prevention in Diabetes?
  • Shaping Up Mitochondria in Diabetic Nephropathy
  • Characterization of the renal cortical transcriptome following Roux-en-Y gastric bypass surgery in experimental diabetic kidney disease
  • Targeting Inflammation in Diabetic Kidney Disease: Is There a Role for Pentoxifylline?
  • Diabetic Kidney Disease: It Dont Get No Respect
  • Association of Urine Haptoglobin With Risk of All-Cause and Cause-Specific Mortality in Individuals With Type 2 Diabetes: A Transethnic Collaborative Work
  • 11. Microvascular Complications and Foot Care: Standards of Medical Care in Diabetes-2020
  • Sodium Glucose Cotransporter-2 Inhibition and Cardiorenal Protection: JACC Review Topic of the Week
  • Retinopathy progression and the risk of end-stage kidney disease: results from a longitudinal Japanese cohort of 232 patients with type 2 diabetes and biopsy-proven diabetic kidney disease
  • Effect of Canagliflozin on Renal and Cardiovascular Outcomes across Different Levels of Albuminuria: Data from the CANVAS Program
  • Sodium-Glucose Cotransporter 2 Inhibition and Diabetic Kidney Disease
  • Transforming growth factor {beta} (TGF{beta}) and related molecules in chronic kidney disease (CKD)
  • 11. Microvascular Complications and Foot Care: Standards of Medical Care in Diabetes--2019
  • Long-Term Effects of Intensive Glycemic and Blood Pressure Control and Fenofibrate Use on Kidney Outcomes
  • Increasing Mortality in Adults With Diabetes and Low Estimated Glomerular Filtration Rate in the Absence of Albuminuria
  • Diabetic Kidney Disease: A Determinant of Cardiovascular Risk in Type 1 Diabetes
  • Segmental Sclerosis and Extracapillary Hypercellularity Predict Diabetic ESRD
  • 10. Microvascular Complications and Foot Care: Standards of Medical Care in Diabetes--2018
  • Diabetes and CKD in the United States Population, 2009-2014
  • Diabetic Kidney Disease: Challenges, Progress, and Possibilities
  • Therapeutic Considerations for Antihyperglycemic Agents in Diabetic Kidney Disease
  • SGLT2 Inhibition in the Diabetic Kidney--From Mechanisms to Clinical Outcome
  • Microvascular Outcomes after Metabolic Surgery (MOMS) in patients with type 2 diabetes mellitus and class I obesity: rationale and design for a randomised controlled trial
  • Second-Line Agents for the Treatment of Type 2 Diabetes and Prevention of CKD
  • Albuminuria Changes and Cardiovascular and Renal Outcomes in Type 1 Diabetes: The DCCT/EDIC Study
  • Diabetes, Kidney Disease, and Cardiovascular Outcomes in the Jackson Heart Study
  • Association of Urinary Biomarkers of Inflammation, Injury, and Fibrosis with Renal Function Decline: The ACCORD Trial
  • Understanding CKD among patients with T2DM: prevalence, temporal trends, and treatment patterns--NHANES 2007-2012
  • Is Bariatric Surgery an Effective Treatment for Type II Diabetic Kidney Disease?
  • Update on Prevention of Cardiovascular Disease in Adults With Type 2 Diabetes Mellitus in Light of Recent Evidence: A Scientific Statement From the American Heart Association and the American Diabetes Association
  • Update on Prevention of Cardiovascular Disease in Adults With Type 2 Diabetes Mellitus in Light of Recent Evidence: A Scientific Statement From the American Heart Association and the American Diabetes Association
  • Diabetic Kidney Disease: Much Progress, But Still More to Do
  • Comprehensive Care for People With Diabetic Kidney Disease
  • Diabetic Kidney Disease: A Call to Action: Preface
  • Hypertension and Diabetic Kidney Disease in Children and Adolescents
  • Effects of Sevelamer Carbonate on Advanced Glycation End Products and Antioxidant/Pro-Oxidant Status in Patients with Diabetic Kidney Disease
  • Chronic administration of AM251 improves albuminuria and renal tubular structure in obese rats
  • Mitochondrial Hormesis and Diabetic Complications
  • Diabetic Kidney Disease: A Report From an ADA Consensus Conference
  • Diabetes and Cardiovascular Disease in Older Adults: Current Status and Future Directions
  • Urinary excretion of RAS, BMP, and WNT pathway components in diabetic kidney disease
  • Association of Serum Concentration of TNFR1 With All-Cause Mortality in Patients With Type 2 Diabetes and Chronic Kidney Disease: Follow-up of the SURDIAGENE Cohort
  • Sodium Glucose Transport 2 (SGLT2) Inhibition Decreases Glomerular Hyperfiltration: Is There a Role for SGLT2 Inhibitors in Diabetic Kidney Disease?
  • The impact of chronic kidney disease and cardiovascular comorbidity on mortality in a multiethnic population: a retrospective cohort study
  • Does Losartan Prevent Progression of Early Diabetic Nephropathy in American Indians With Type 2 Diabetes?
  • Google Scholar

Similar Articles

Related Articles

  • PubMed
  • Google Scholar

Articles

  • Current Issue
  • Early Access
  • Subject Collections
  • Article Archive
  • ASN Annual Meeting Abstracts

Information for Authors

  • Submit a Manuscript
  • Author Resources
  • Editorial Fellowship Program
  • ASN Journal Policies
  • Reuse/Reprint Policy

About

  • JASN
  • ASN
  • ASN Journals
  • ASN Kidney News

Journal Information

  • About JASN
  • JASN Email Alerts
  • JASN Key Impact Information
  • JASN Podcasts
  • JASN RSS Feeds
  • Editorial Board

More Information

  • Advertise
  • ASN Podcasts
  • ASN Publications
  • Become an ASN Member
  • Feedback
  • Follow on Twitter
  • Password/Email Address Changes
  • Subscribe

© 2021 American Society of Nephrology

Print ISSN - 1046-6673 Online ISSN - 1533-3450

Powered by HighWire