Skip to main content
  • More from ADA
    • Diabetes
    • Clinical Diabetes
    • Diabetes Spectrum
    • ADA Standards of Medical Care
    • ADA Scientific Sessions Abstracts
    • BMJ Open Diabetes Research & Care
  • Subscribe
  • Log in
  • My Cart
  • Follow ada on Twitter
  • RSS
  • Visit ada on Facebook
Diabetes Care

Advanced Search

Main menu

  • Home
  • Current
    • Current Issue
    • Online Ahead of Print
    • Special Article Collections
    • ADA Standards of Medical Care
  • Browse
    • By Topic
    • Issue Archive
    • Saved Searches
    • Special Article Collections
    • ADA Standards of Medical Care
  • Info
    • About the Journal
    • About the Editors
    • ADA Journal Policies
    • Instructions for Authors
    • Guidance for Reviewers
  • Reprints/Reuse
  • Advertising
  • Subscriptions
    • Individual Subscriptions
    • Institutional Subscriptions and Site Licenses
    • Access Institutional Usage Reports
    • Purchase Single Issues
  • Alerts
    • E­mail Alerts
    • RSS Feeds
  • Podcasts
    • Diabetes Core Update
    • Special Podcast Series: Therapeutic Inertia
    • Special Podcast Series: Influenza Podcasts
    • Special Podcast Series: SGLT2 Inhibitors
    • Special Podcast Series: COVID-19
  • Submit
    • Submit a Manuscript
    • Journal Policies
    • Instructions for Authors
    • ADA Peer Review
  • More from ADA
    • Diabetes
    • Clinical Diabetes
    • Diabetes Spectrum
    • ADA Standards of Medical Care
    • ADA Scientific Sessions Abstracts
    • BMJ Open Diabetes Research & Care

User menu

  • Subscribe
  • Log in
  • My Cart

Search

  • Advanced search
Diabetes Care
  • Home
  • Current
    • Current Issue
    • Online Ahead of Print
    • Special Article Collections
    • ADA Standards of Medical Care
  • Browse
    • By Topic
    • Issue Archive
    • Saved Searches
    • Special Article Collections
    • ADA Standards of Medical Care
  • Info
    • About the Journal
    • About the Editors
    • ADA Journal Policies
    • Instructions for Authors
    • Guidance for Reviewers
  • Reprints/Reuse
  • Advertising
  • Subscriptions
    • Individual Subscriptions
    • Institutional Subscriptions and Site Licenses
    • Access Institutional Usage Reports
    • Purchase Single Issues
  • Alerts
    • E­mail Alerts
    • RSS Feeds
  • Podcasts
    • Diabetes Core Update
    • Special Podcast Series: Therapeutic Inertia
    • Special Podcast Series: Influenza Podcasts
    • Special Podcast Series: SGLT2 Inhibitors
    • Special Podcast Series: COVID-19
  • Submit
    • Submit a Manuscript
    • Journal Policies
    • Instructions for Authors
    • ADA Peer Review
Epidemiology/Health Services Research

The Association Between Age of Onset of Type 2 Diabetes and the Long-term Risk of End-Stage Kidney Disease: A National Registry Study

  1. Jedidiah I. Morton1,2⇑,
  2. Danny Liew2,
  3. Stephen P. McDonald3,4,
  4. Jonathan E. Shaw1,2 and
  5. Dianna J. Magliano1,2
  1. 1Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
  2. 2School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
  3. 3Australia and New Zealand Dialysis and Transplant Registry, South Australia Health and Medical Research Institute, Adelaide, South Australia, Australia
  4. 4Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
  1. Corresponding author: Jedidiah I. Morton, jedidiah.morton{at}baker.edu.au
  1. J.E.S. and D.J.M. are joint senior authors.

Diabetes Care 2020 Aug; 43(8): 1788-1795. https://doi.org/10.2337/dc20-0352
PreviousNext
  • Article
  • Figures & Tables
  • Suppl Material
  • Info & Metrics
  • PDF
Loading

Abstract

OBJECTIVE The long-term risk of end-stage kidney disease (ESKD) in type 2 diabetes is poorly described, as is the effect that younger age of diabetes onset has on this risk. Therefore, we aimed to estimate the effect of age of onset on the cumulative incidence of ESKD from onset of type 2 diabetes.

RESEARCH DESIGN AND METHODS This study included 1,113,201 people with type 2 diabetes registered on the Australian National Diabetes Services Scheme (NDSS) followed from 2002 until 2013. The NDSS was linked to the Australia and New Zealand Dialysis and Transplant Registry and the Australian National Death Index.

RESULTS Between 2002 and 2013, there were 7,592 incident cases of ESKD during 7,839,075 person-years of follow-up. In the first 10–15 years following the onset of diabetes, the incidence of ESKD was highest in those with an older age of onset of diabetes, whereas over longer durations of diabetes, the incidence of ESKD became higher in those with younger-onset diabetes. After 40 years of diabetes, the cumulative incidence of ESKD was 11.8% and 9.3% in those diagnosed with diabetes at ages 10–29 and 30–39 years, respectively. When death from ESKD without renal replacement therapy was included, the incidence of ESKD remained higher in older-onset diabetes for the initial 20 years, with no clear effect of age thereafter.

CONCLUSIONS The long-term risk of ESKD in type 2 diabetes is high, which disproportionately affects those with younger onset of diabetes because they are more likely to survive to longer diabetes durations.

Introduction

One of the most burdensome and costly complications of diabetes is end-stage kidney disease (ESKD) (1,2). People with diabetes are at considerably increased risk for the development of ESKD (3), and diabetic nephropathy (DN) is now the leading cause of ESKD, accounting for one-third of incident cases worldwide (4). Despite this significant burden, estimates of the long-term risk of ESKD for those with type 2 diabetes are scarce.

The primary limiting factor in the estimation of long-term risk has been that ESKD is a relatively rare event (5). Thus, to generate reliable estimates of ESKD incidence, studies must be of considerable size and duration, and include people with a wide spread of ages of onset of diabetes. Consequently, with the exception of Indigenous populations at very high risk for ESKD (6,7), there has been only one study sufficiently large enough to estimate long-term risk of ESKD. Finne et al. (5) estimated the cumulative risk of ESKD after 20 years of type 2 diabetes at 0.74% using a Finnish national cohort study, defining ESKD as initiation of renal replacement therapy (RRT), and concluded that the risk of ESKD in type 2 diabetes is low. However, one-third of the people in their cohort were diagnosed with diabetes at >70 years of age, and initiation of RRT at onset of ESKD diminishes dramatically with increasing age (8). Furthermore, the study excluded people diagnosed with diabetes at <40 years of age, who may be at in-creased risk for ESKD, especially at longer durations (6). Thus, the long-term risk of ESKD in type 2 diabetes may be considerably greater than this work would suggest.

Additionally, the relationship between age of onset of type 2 diabetes and risk for ESKD is poorly described. In particular, it is unclear whether the pathophysiology of DN in younger-onset diabetes is somehow different from older-onset diabetes, or whether survival to longer durations of diabetes in this group simply allows more time for DN to progress to ESKD (4). While it is clear that at a given age those with younger-onset diabetes are at higher risk of ESKD (7), when duration of diabetes is controlled for, reports of the effect of age of onset have been inconsistent (5,7). This is probably because noninitiation of RRT and the competing risk of death have not been considered, both of which are highly dependent on age (8,9), and are therefore likely to be especially important in describing the ef-fect of age of onset on long-term ESKD risk (10).

Clearly, more information is needed on the long-term risk of ESKD for people with type 2 diabetes, and the effect that a younger age of diabetes onset has on this risk. Therefore, we linked nationwide diabetes, ESKD, and death registries in Australia to produce a cohort of >1 million people with type 2 diabetes and estimated the incidence of ESKD from the onset of diabetes by age of onset.

Research Design and Methods

Data Sources

The National Diabetes Services Scheme (NDSS) was established by the Australian government in 1987 to deliver diabetes-related products at subsidized prices and provide information to people with diabetes. As such, its clinical data are limited to the date of onset of diabetes, diabetes type, and use of insulin. The NDSS is estimated to include 80–90% of people with diagnosed diabetes in Australia (11). We included as our study population individuals with type 2 diabetes registered on the NDSS as of 1 January 2002 and all new registrants from this date until 31 December 2013. In the NDSS database, diabetes type is classified by a health care practitioner at the time of registration. However, because there is often uncertainty in this diagnosis, especially at the time of diagnosis (when registration is usually completed), certain clinical characteristics were also required to be satisfied for assignment of diabetes type for the current analysis (Supplementary Appendix). Registrants with missing data on age, sex, or type of diabetes were excluded from all analyses (n = 104). Registrants diagnosed with diabetes after the age of 79 years were excluded (n = 61,361), because beyond 79 years the vast majority of ESKD is not treated with RRT (8). Because Aboriginal and Torres Strait Islander Australians are able to access services the NDSS provides through other means and are therefore not well represented on the NDSS, our analysis was restricted to non-Indigenous Australians.

NDSS registrants were matched to the Australian and New Zealand Dialysis and Transplant Registry (ANZDATA), Australian Pharmaceutical Benefits Scheme (PBS), and Australian National Death Index (NDI). ANZDATA is a registry for the purpose of collecting data on all patients who undergo kidney transplantation and/or dialysis. All RRT units in Australia contribute to ANZDATA, and very few people have opted out since its inception. Thus, the registry is essentially 100% complete. The PBS is an Australian government program that subsidizes the cost of medicines and collects data on all prescriptions dispensed in Australia under the scheme. In the current analysis, the PBS was used only in the classification of diabetes type. The NDI contains records of all registered deaths in Australia since 1980. This study used data from 1 January 2002 up to and including 31 December 2013. Linkage was performed by the Australian Institute of Health and Welfare, as previously reported (12).

In the primary analysis, ESKD was defined as initiation of RRT; date of onset of ESKD was derived from ANZDATA, and date of death was derived from the NDI. To distinguish between ESKD due to DN and total ESKD in people with diabetes, we used ANZDATA information on primary renal disease to conduct a sensitivity analysis restricted to DN as the listed cause of ESKD. Because some people may not be offered RRT and others may opt out of it, defining ESKD as initiation of RRT (treated ESKD) will underestimate the incidence of ESKD. Therefore, we also estimated the incidence of ESKD including as incident cases individuals who did not initiate RRT, but for whom ESKD was recorded as a cause of death on their death certificate (untreated ESKD). This is possible because survival for those who have ESKD and do not receive RRT is likely to be short (13). ESKD in mortality data were defined as previously described (8). Briefly, an incident case was defined when the underlying cause of death was chronic renal failure (ICD-10 codes N18.0, N18.5, N18.8, and N18.9), hypertensive renal failure (I12.0, I13.1, and I13.2), or unspecified renal failure (N19), or when chronic renal failure (N18.0 and N18.5) was listed as an associated cause of death. Additionally, if the underlying cause of death was listed as diabetes and first contributing cause of death was listed as ESKD, this was also counted as untreated ESKD.

This study was approved by the Alfred Hospital Ethics Committee (Project No.: 15/15) (Melbourne, Victoria, Australia) and the Australian Institute of Health and Welfare Ethics Committee (EO 2015/1/148) (Canberra, Australian Capital Territory, Australia).

Data Analysis

NDSS registrants were followed from 1 January 2002 or date of registration, if later, until onset of ESKD, death, or end of follow-up on 31 December 2013. Incidence rates were calculated by dividing the total number of new cases of ESKD by the total person-years of follow-up in 5-year duration of diabetes intervals. When untreated ESKD was included, analyses were as above, but date of ESKD onset was defined as the date of death for those with untreated ESKD. Similarly, mortality rates in those without ESKD were estimated by following NDSS registrants from 1 January 2002 or date of registration, if later, until death, onset of ESKD, or end of follow-up on 31 December 2013. Incidence rates were calculated separately based on the age of diabetes onset, which was divided into six categories: 10–29, 30–39, 40–49, 50–59, 60–69, and 70–79 years. If age of diagnosis was unavailable for a participant, age of registration on the NDSS was used. When diagnosis and registration date are both available, the dates are generally similar; however, to determine whether using the registration date instead of the diagnosis date materially affected the results, ESKD incidence rates were estimated using only those with an available diagnosis date (70% of registrants) in a sensitivity analysis.

To estimate the cumulative incidence of ESKD from the onset of diabetes, life table models were constructed that simulate the annual progression of a cohort with diabetes initially free of ESKD and followed from diabetes onset. Separate life tables were constructed for each of the aforementioned categories of age of onset of diabetes. Life tables were truncated at the end of the 5-year duration interval beyond which there were ≤10 incident cases of ESKD. These models were based on duration-specific and age-specific transition rates: incidence of ESKD from onset of diabetes and all-cause mortality by attained age in those without ESKD. These transition rates were estimated for each category separately. Analyses were also stratified by sex. Incidence rates were calculated by dividing the total number of new cases of ESKD by total person-years of follow-up in 1-year duration of diabetes intervals. Age-specific mortality rates for each category were estimated using a Gompertz distribution (14) and applied from the midpoint of each category of age of diabetes onset (e.g., in the 40–49 category, mortality rates were applied from age 45), with the exception of the age category 10–29 years, for which rates were applied from age 25 (the mean age of onset in this category). CIs were obtained using 500 bootstrap replicates of each age of onset category. For each bootstrap sample, incidence and mortality rates were estimated, and a life table was constructed; 95% CIs represent the 2.5th and 97.5th centile value of each estimated parameter from these bootstrapped life tables.

Statistical analyses were performed in the Stata 15 statistical software (StataCorp, College Station, TX).

Results

Study Population

The characteristics of the study population are summarized in Table 1 and Supplementary Table 1. This study included 1,113,201 people with type 2 diabetes. The median age of onset was 58.1 years (interquartile range 49.0–66.5). During 7,839,075 person-years of follow-up, there were 7,592 incident cases of treated ESKD and 192,005 deaths without ESKD. There were 5,671 deaths attributed to ESKD in individuals who did not initiate RRT, and the vast majority of these cases were in the older categories of age of onset (Supplementary Table 2).

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

Participant number, incident treated ESKD, number of deaths in those without treated ESKD, time to ESKD, and diabetes duration at end of follow-up, by age of onset of diabetes and sex

Incidence of ESKD

Table 2 reports the incidence of treated ESKD at different diabetes duration intervals by age of onset of diabetes. Incidence increased with increasing duration of diabetes. ESKD incidence rates were higher in males than in females (Supplementary Table 3). This sex difference was larger in those with diabetes onset before age 40 years compared with diabetes onset after 40 (Supplementary Table 4). Incidence rates were higher in the older categories of age of onset for the first 10–15 years of diabetes (Supplementary Table 5). However, at longer durations of diabetes the incidence of ESKD became higher in those with younger diabetes onset. At any given age, those with a longer duration of diabetes were at markedly higher risk for ESKD (Supplementary Table 6), and the magnitude of this effect of diabetes duration was substantially more than the effect of age. When untreated ESKD was included (Supplementary Table 7), those older at onset remained at a higher risk of ESKD for the first 20 years of diabetes, beyond which there were no obvious differences in incidence across different categories of age of onset.

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

Incidence rate of treated ESKD at different diabetes duration intervals; stratified by age of onset of diabetes

Cumulative Incidence of ESKD

During the first 10–15 years of diabetes, younger onset of diabetes afforded some protection against ESKD for a given duration of diabetes (Table 3 and Fig. 1A). Over longer durations of diabetes, the cumulative incidence of treated ESKD was highest in those with younger onset of diabetes. In the categories of younger-onset diabetes, males were at a substantially higher risk of ESKD compared with females: in those with diabetes onset before 30 years of age, the risk of ESKD in males was more than twofold that of females after 40 years of diabetes (17.4% and 7.7%, respectively). Figure 1B and Supplementary Table 8 show the cumulative incidence of ESKD when untreated ESKD is included. The cumulative incidence was higher in older categories of age of onset of diabetes for the first 20 years of diabetes, beyond which the cumulative incidence became more similar across categories of age of onset.

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

Cumulative incidence of treated ESKD (%) at different diabetes durations, stratified by age of onset of diabetes and sex

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

Cumulative incidence of ESKD by duration of type 2 diabetes stratified by age of onset of diabetes. Insets show the first 15 years of diabetes. A: Treated ESKD only. B: Treated and untreated ESKD.

Sensitivity Analyses

Incidence of treated ESKD was similar when only those who had an available date at diagnosis of diabetes were analyzed (Supplementary Table 9). The difference in incidence rates between categories of age of onset of diabetes was smaller when only those who developed ESKD due to DN are considered (Supplementary Table 10). Additionally, the proportion of ESKD due to DN decreased with increasing age of onset of diabetes (Supplementary Table 2).

Conclusions

We observed that the incidence of ESKD in type 2 diabetes increases with increasing duration of diabetes as well as age, leading to a complex association of ESKD risk with age of onset of diabetes. During the first 10–15 years of diabetes those with an older age of onset of diabetes were at higher risk for ESKD, with younger age of onset tending to higher risk at longer durations. However, because duration of diabetes is the predominant determinant of ESKD risk and those with younger-onset type 2 diabetes are more likely to survive to longer diabetes durations, younger-onset clearly confers a higher long-term risk of ESKD. The cumulative incidence of ESKD by 40 years of diabetes duration was as high as 11.8% for those with type 2 diabetes diagnosed before age 30 years and 9.3% in those diagnosed aged 30–39.

The incidence of ESKD in this study is noticeably higher than recently published estimates from Finland (5). As mentioned, this may be partly due to their inclusion of elderly individuals with diabetes, who are far less likely to initiate RRT at the onset of ESKD. Consistent with this, when only those with diabetes onset before 60 years in their study are considered, estimates of cumulative ESKD are comparable. Similarly, results in our study are commensurate with a population-based study from Canada (15), although the Canadian study included both type 1 and 2 diabetes. Most other estimates of the incidence of ESKD from onset of type 2 diabetes are derived from Indigenous populations, in whom the risk of ESKD is considerably higher (6,7,15). The concordance of our estimates with those previously published in non-Indigenous populations supports the generalizability of our results to other high-income nations. It is therefore apparent and not unexpected that the risk of ESKD is high over long durations of type 2 diabetes.

We observed that in type 2 diabetes, as is the case for type 1 diabetes (16–18), diabetes duration is the predominant determinant of ESKD risk. Our results suggest that the incidence of ESKD may be higher in type 2 than type 1 diabetes, especially beyond 20 years’ duration (16–18), which may be partly explained by poorer glycemic control in type 2 diabetes (19,20), as well as by a greater prevalence of hypertension and dyslipidemia (21), major risk factors for progression of chronic kidney disease (4). Indeed, Luk et al. (22) found the higher incidence of ESKD in type 2 diabetes was largely driven by obesity, hypertension, and dyslipidemia, and several studies have documented an increase in vascular complications in younger-onset type 2 compared with type 1 diabetes (23).

To a lesser extent than duration, age of onset of diabetes also affected ESKD risk. Incidence of ESKD was higher at a given duration in those diagnosed later in life for the first 10–15 years of diabetes. This may be partly related to the well-established increasing risk for ESKD from any cause with increasing age (8). Indeed, other causes of ESKD were more common in those older at onset of diabetes, and the effect of age on ESKD incidence is smaller when only those who developed ESKD due to DN are considered. However, it should be noted that assigning a single cause for ESKD becomes increasingly difficult with increasing age due to the frequent presence of multiple risk factors. The association with age is also consistent with observations that those diagnosed with diabetes later in life are more likely to present with nephropathy at diagnosis of diabetes (24) and would therefore in general require less of an insult to kidney function to progress to ESKD. Moreover, it is reasonable to assume an increased prevalence of hypertension in the older age groups (25), which would be expected to accelerate the progression of DN.

However, at longer durations of diabetes, those with younger onset were at a substantially higher risk for ESKD. This observation is principally due to differences in attained age, because by definition, those with a later onset of diabetes are older at any given duration. There are two important consequences of higher attained age. First, the propensity to initiate RRT decreases dramatically with increasing age (8); thus, the incidence of ESKD as measured by initiation of RRT decreases. Indeed, when untreated ESKD is included, there was no clear excess risk among those with younger-onset diabetes, even at longer durations. Second, the competing risk of death with ESKD will be much greater with older onset of diabetes at any given duration (9). Thus, when duration of diabetes is adequately controlled for, younger-onset of diabetes carries less of a risk for ESKD during the initial years following onset, possibly because of better renal function at onset of diabetes. Nevertheless, those diagnosed with diabetes later in life are more likely to die before the onset of ESKD than those diagnosed earlier in life, and are therefore less likely to attain longer durations of diabetes. This is in large part responsible for the observation that the long-term risk of ESKD is higher in younger-onset diabetes, and we have found no evidence to suggest younger onset of diabetes leads to a greater risk of ESKD beyond the effect of attaining longer diabetes durations.

Notably, sex played an important role in risk for ESKD in younger-onset diabetes: risk of ESKD was markedly higher among males compared with females with diabetes onset before 40, whereas sex was less important for older-onset diabetes, consistent with earlier studies (3,5,15). The excess risk in males is unlikely to be explained by differences in classic risk factors for progression of DN, as evidence suggests that males with diabetes are more likely to achieve risk factor targets (26), although results are inconsistent across studies (27). As the protective effect in females is lost with increasing age of onset of diabetes, our results are compatible with a hypothesized protective effect of estrogens (28).

This nationwide, population-based study is the largest to have estimated the incidence of ESKD from onset of diabetes and is the first to estimate the risk of ESKD in a non-Indigenous population with type 2 diabetes beyond 25 years of diabetes duration. However, several important limitations of this analysis deserve consideration. While the NDSS is estimated to capture 80–90% of people with diagnosed type 2 diabetes in Australia (11), this may be biased toward those who require the services the NDSS provides, and in particular, may underrepresent those who manage diabetes with diet and exercise alone. Additionally, because this study uses administrative data, we do not have detailed information on comorbidities associated with progression of DN and therefore could not investigate the contribution of these comorbidities to the observed association between age of onset of diabetes and ESKD risk, nor their effect on ESKD risk in general. Importantly, we do not have information on baseline kidney function and so cannot comment on the rate of decline in kidney function and whether this differs by age of onset.

While we have attempted to be as thorough in our definition of diabetes type as is practical, there will be a degree of misclassification with any definition of diabetes based on administrative data. We believe the degree of misclassification is small, because our population characteristics are similar to other known populations of type 1 and type 2 diabetes. Furthermore, we are lacking data on incident ESKD before 2002, and because incidence is likely to have fallen between NDSS inception and 2002, our results may overestimate the effect of duration on the risk of ESKD in diabetes relative to an inception cohort study. Finally, although ANZDATA and the NDI are virtually 100% complete, estimates of the true incidence of ESKD using either treated ESKD or both treated and untreated ESKD will involve some uncertainty. The incidence of treated ESKD should be extremely accurate at younger ages but will become a poorer marker of ESKD as age increases (8). This is theoretically overcome with the combination of treated and untreated ESKD; however, misclassification will still occur, because inaccuracies in the listed cause of death are not uncommon (29), although this should apply similarly across all ages.

In conclusion, this large, population-based nationwide linkage study indicates that the long-term risk of ESKD in type 2 diabetes is high, which disproportionately affects those with younger-onset type 2 diabetes because they are more likely to survive to longer diabetes durations. Our data did not, however, clearly support the hypothesis that younger-onset type 2 diabetes increases the risk of ESKD beyond its effects mediated by attainment of longer diabetes durations. This study supports the notion that delaying the onset of type 2 diabetes would be an effective method for reducing the risk of ESKD, and also adds to the body of evidence (4,30–32) highlighting the urgent requirement for development and implementation of effective interventions that attenuate the progression of DN in type 2 diabetes.

Article Information

Acknowledgments. The authors thank Agus Salim (Baker Heart and Diabetes Institute) for discussion about the statistical methods used in this study. The authors also thank Bendix Cartensen (Steno Diabetes Center Copenhagen, Gentofte, Denmark) for his extremely helpful comments on the first draft of the manuscript.

Funding. J.I.M. is supported by an Australian Government Research Training Program Scholarship and Monash Graduate Excellence Scholarship. J.E.S. and D.J.M. are supported by a National Health and Medical Research Council Investigator Grant (1002663). This work is partially supported by the Victorian Government’s Operational Infrastructure Support Program.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. J.I.M. contributed to the design of the study and interpretation of data, performed the statistical analysis and literature search, and wrote and revised the manuscript. D.L. contributed to the design of the study, analysis and interpretation of data, and revision of the manuscript. S.P.M. contributed to acquisition and interpretation of data and revision of the manuscript. J.E.S. and D.J.M. are principal investigators and made substantial contributions to the design of the study, acquisition and interpretation of the data, and revision of the manuscript and contributed to the literature search. J.I.M. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. Parts of this study were presented in abstract form at the 80th Scientific Sessions of the American Diabetes Association, 12–16 June 2020.

Footnotes

  • This article contains supplementary material online at https://doi.org/10.2337/figshare.12273110.

  • Received February 20, 2020.
  • Accepted May 4, 2020.
  • © 2020 by the American Diabetes Association
https://www.diabetesjournals.org/content/license

Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at https://www.diabetesjournals.org/content/license.

References

  1. ↵
    1. Spiegel BMR,
    2. Melmed G,
    3. Robbins S,
    4. Esrailian E
    . Biomarkers and health-related quality of life in end-stage renal disease: a systematic review. Clin J Am Soc Nephrol 2008;3:1759–1768
    OpenUrlAbstract/FREE Full Text
  2. ↵
    1. Slabaugh SL,
    2. Curtis BH,
    3. Clore G,
    4. Fu H,
    5. Schuster DP
    . Factors associated with increased healthcare costs in Medicare Advantage patients with type 2 diabetes enrolled in a large representative health insurance plan in the US. J Med Econ 2015;18:106–112
    OpenUrlPubMed
  3. ↵
    1. Narres M,
    2. Claessen H,
    3. Droste S, et al
    . The incidence of end-stage renal disease in the diabetic (compared to the non-diabetic) population: a systematic review. PloS One 2016;11:e0147329
    OpenUrlPubMed
  4. ↵
    1. Thomas MC,
    2. Cooper ME,
    3. Zimmet P
    . Changing epidemiology of type 2 diabetes mellitus and associated chronic kidney disease. Nat Rev Nephrol 2016;12:73–81
    OpenUrlCrossRefPubMed
  5. ↵
    1. Finne P,
    2. Groop P-H,
    3. Arffman M, et al
    . Cumulative risk of end-stage renal disease among patients with type 2 diabetes: a nationwide inception cohort study. Diabetes Care 2019;42:539–544
    OpenUrlAbstract/FREE Full Text
  6. ↵
    1. Wang Z,
    2. Hoy WE
    . Remaining lifetime risk for developing end stage renal disease among Australian Aboriginal people with diabetes. Diabetes Res Clin Pract 2014;103:e24–e26
    OpenUrl
  7. ↵
    1. Pavkov ME,
    2. Bennett PH,
    3. Knowler WC,
    4. Krakoff J,
    5. Sievers ML,
    6. Nelson RG
    . Effect of youth-onset type 2 diabetes mellitus on incidence of end-stage renal disease and mortality in young and middle-aged Pima Indians. JAMA 2006;296:421–426
    OpenUrlCrossRefPubMedWeb of Science
  8. ↵
    1. Sparke C,
    2. Moon L,
    3. Green F, et al
    . Estimating the total incidence of kidney failure in Australia including individuals who are not treated by dialysis or transplantation. Am J Kidney Dis 2013;61:413–419
    OpenUrlCrossRefPubMedWeb of Science
  9. ↵
    1. Huo L,
    2. Magliano DJ,
    3. Rancière F, et al
    . Impact of age at diagnosis and duration of type 2 diabetes on mortality in Australia 1997-2011. Diabetologia 2018;61:1055–1063
    OpenUrl
  10. ↵
    1. Jiang Y,
    2. Fine JP,
    3. Mottl AK
    . Competing risk of death with end-stage renal disease in diabetic kidney disease. Adv Chronic Kidney Dis 2018;25:133–140
    OpenUrlPubMed
  11. ↵
    1. Australian Institute of Health and Welfare
    . Diabetes prevalence in Australia: an assessment of national data sources. Diabetes Series No. 12. Cat. No. CVD 46. Canberra, Australia, AIHW, 2009
  12. ↵
    1. Loh V,
    2. Harding J,
    3. Koshkina V,
    4. Barr E,
    5. Shaw J,
    6. Magliano D
    . The validity of self-reported cancer in an Australian population study. Aust N Z J Public Health 2014;38:35–38
    OpenUrlCrossRefPubMed
  13. ↵
    1. Chandna SM,
    2. Da Silva-Gane M,
    3. Marshall C,
    4. Warwicker P,
    5. Greenwood RN,
    6. Farrington K
    . Survival of elderly patients with stage 5 CKD: comparison of conservative management and renal replacement therapy. Nephrol Dial Transplant 2011;26:1608–1614
    OpenUrlCrossRefPubMed
  14. ↵
    1. Yashin AI,
    2. Iachine IA,
    3. Begun AS
    . Mortality modeling: a review. Math Popul Stud 2000;8:305–332
    OpenUrl
  15. ↵
    1. Jiang Y,
    2. Osgood N,
    3. Lim HJ,
    4. Stang MR,
    5. Dyck R
    . Differential mortality and the excess burden of end-stage renal disease among First Nations people with diabetes mellitus: a competing-risks analysis. CMAJ 2014;186:103–109
    OpenUrlAbstract/FREE Full Text
  16. ↵
    1. Helve J,
    2. Sund R,
    3. Arffman M, et al
    . Incidence of end-stage renal disease in patients with type 1 diabetes. Diabetes Care 2018;41:434–439
    OpenUrlAbstract/FREE Full Text
    1. Gagnum V,
    2. Saeed M,
    3. Stene LC,
    4. Leivestad T,
    5. Joner G,
    6. Skrivarhaug T
    . Low incidence of end-stage renal disease in childhood-onset type 1 diabetes followed for up to 42 years. Diabetes Care 2018;41:420–425
    OpenUrlAbstract/FREE Full Text
  17. ↵
    1. Toppe C,
    2. Möllsten A,
    3. Waernbaum I, et al.; Swedish Childhood Diabetes Study Group and the Swedish Renal Register
    . Decreasing cumulative incidence of end-stage renal disease in young patients with type 1 diabetes in Sweden: a 38-year prospective nationwide study. Diabetes Care 2019;42:27–31
    OpenUrlAbstract/FREE Full Text
  18. ↵
    1. UK Prospective Diabetes Study (UKPDS) Group
    . Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet 1998;352:837–853
    OpenUrlCrossRefPubMedWeb of Science
  19. ↵
    1. Nathan DM,
    2. Zinman B,
    3. Cleary PA, et al.; Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Research Group
    . Modern-day clinical course of type 1 diabetes mellitus after 30 years’ duration: the diabetes control and complications trial/epidemiology of diabetes interventions and complications and Pittsburgh epidemiology of diabetes complications experience (1983-2005). Arch Intern Med 2009;169:1307–1316
    OpenUrlCrossRefPubMedWeb of Science
  20. ↵
    1. Eppens MC,
    2. Craig ME,
    3. Cusumano J, et al
    . Prevalence of diabetes complications in adolescents with type 2 compared with type 1 diabetes. Diabetes Care 2006;29:1300–1306
    OpenUrlAbstract/FREE Full Text
  21. ↵
    1. Luk AO,
    2. Lau ES,
    3. So WY, et al
    . Prospective study on the incidences of cardiovascular-renal complications in Chinese patients with young-onset type 1 and type 2 diabetes. Diabetes Care 2014;37:149–157
    OpenUrlAbstract/FREE Full Text
  22. ↵
    1. Magliano DJ,
    2. Sacre JW,
    3. Harding JL,
    4. Gregg EW,
    5. Zimmet PZ,
    6. Shaw JE
    . Young-onset type 2 diabetes mellitus - implications for morbidity and mortality. Nat Rev Endocrinol. 2020;16:321–331
  23. ↵
    1. Hillier TA,
    2. Pedula KL
    . Complications in young adults with early-onset type 2 diabetes: losing the relative protection of youth. Diabetes Care 2003;26:2999–3005
    OpenUrlAbstract/FREE Full Text
  24. ↵
    1. Australian Bureau of Statistics
    . 4364.0.55.001 - National Health Survey: First Results, 2017-18 [Internet]. Available from https://www.abs.gov.au/ausstats/abs@.nsf/mf/4364.0.55.001. Accessed 13 March 2020
  25. ↵
    1. Juutilainen A,
    2. Kortelainen S,
    3. Lehto S,
    4. Rönnemaa T,
    5. Pyörälä K,
    6. Laakso M
    . Gender difference in the impact of type 2 diabetes on coronary heart disease risk. Diabetes Care 2004;27:2898–2904
    OpenUrlAbstract/FREE Full Text
  26. ↵
    1. Wannamethee SG,
    2. Papacosta O,
    3. Lawlor DA, et al
    . Do women exhibit greater differences in established and novel risk factors between diabetes and non-diabetes than men? The British Regional Heart Study and British Women’s Heart Health Study. Diabetologia 2012;55:80–87
    OpenUrlCrossRefPubMedWeb of Science
  27. ↵
    1. Clotet S,
    2. Riera M,
    3. Pascual J,
    4. Soler MJ
    . RAS and sex differences in diabetic nephropathy. Am J Physiol Renal Physiol 2016;310:F945–F957
    OpenUrlCrossRef
  28. ↵
    1. Magliano D,
    2. Liew D,
    3. Pater H, et al
    . Accuracy of the Australian National Death Index: comparison with adjudicated fatal outcomes among Australian participants in the Long-term Intervention with Pravastatin in Ischaemic Disease (LIPID) study. Aust N Z J Public Health 2003;27:649–653
    OpenUrlCrossRefPubMed
  29. ↵
    1. Pavkov ME,
    2. Knowler WC,
    3. Hanson RL,
    4. Nelson RG
    . Diabetic nephropathy in American Indians, with a special emphasis on the Pima Indians. Curr Diab Rep 2008;8:486–493
    OpenUrlCrossRefPubMed
    1. Ritz E,
    2. Zeng X
    . Diabetic nephropathy - epidemiology in Asia and the current state of treatment. Indian J Nephrol 2011;21:75–84
    OpenUrlPubMed
  30. ↵
    1. McDonald SP
    . Placing Aboriginal kidney disease in context. CMAJ 2014;186:93–94
    OpenUrlFREE Full Text
PreviousNext
Back to top
Diabetes Care: 43 (8)

In this Issue

August 2020, 43(8)
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by Author
  • Masthead (PDF)
Sign up to receive current issue alerts
View Selected Citations (0)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word about Diabetes Care.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
The Association Between Age of Onset of Type 2 Diabetes and the Long-term Risk of End-Stage Kidney Disease: A National Registry Study
(Your Name) has forwarded a page to you from Diabetes Care
(Your Name) thought you would like to see this page from the Diabetes Care web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
The Association Between Age of Onset of Type 2 Diabetes and the Long-term Risk of End-Stage Kidney Disease: A National Registry Study
Jedidiah I. Morton, Danny Liew, Stephen P. McDonald, Jonathan E. Shaw, Dianna J. Magliano
Diabetes Care Aug 2020, 43 (8) 1788-1795; DOI: 10.2337/dc20-0352

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Add to Selected Citations
Share

The Association Between Age of Onset of Type 2 Diabetes and the Long-term Risk of End-Stage Kidney Disease: A National Registry Study
Jedidiah I. Morton, Danny Liew, Stephen P. McDonald, Jonathan E. Shaw, Dianna J. Magliano
Diabetes Care Aug 2020, 43 (8) 1788-1795; DOI: 10.2337/dc20-0352
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Research Design and Methods
    • Results
    • Conclusions
    • Article Information
    • Footnotes
    • References
  • Figures & Tables
  • Suppl Material
  • Info & Metrics
  • PDF

Related Articles

Cited By...

More in this TOC Section

  • Prediabetes, Diabetes, and the Risk of All-Cause and Cause-Specific Mortality in a Japanese Working Population: Japan Epidemiology Collaboration on Occupational Health Study
  • Thirty-Year Trends in Complications in U.S. Adults With Newly Diagnosed Type 2 Diabetes
  • Social Deprivation and Incident Diabetes-Related Foot Disease in Patients With Type 2 Diabetes: A Population-Based Cohort Study
Show more Epidemiology/Health Services Research

Similar Articles

Navigate

  • Current Issue
  • Standards of Care Guidelines
  • Online Ahead of Print
  • Archives
  • Submit
  • Subscribe
  • Email Alerts
  • RSS Feeds

More Information

  • About the Journal
  • Instructions for Authors
  • Journal Policies
  • Reprints and Permissions
  • Advertising
  • Privacy Policy: ADA Journals
  • Copyright Notice/Public Access Policy
  • Contact Us

Other ADA Resources

  • Diabetes
  • Clinical Diabetes
  • Diabetes Spectrum
  • Scientific Sessions Abstracts
  • Standards of Medical Care in Diabetes
  • BMJ Open - Diabetes Research & Care
  • Professional Books
  • Diabetes Forecast

 

  • DiabetesJournals.org
  • Diabetes Core Update
  • ADA's DiabetesPro
  • ADA Member Directory
  • Diabetes.org

© 2021 by the American Diabetes Association. Diabetes Care Print ISSN: 0149-5992, Online ISSN: 1935-5548.