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Kidney Transplantation

Population-based Trends in Obesity and Kidney Transplantation Among Patients With End-stage Kidney Disease

Wakam, Glenn K. MD1; Sheetz, Kyle H. MD, MS1,2; Gerhardinger, Laura MA2; Montgomery, John R. MD1,2; Waits, Seth A. MD1,2

Author Information
doi: 10.1097/TXD.0000000000001163

Abstract

INTRODUCTION

In 2019, the president of the United States signed an executive order entitled Advancing American Kidney Health.1 This directive outlines plans to reduce the risks of kidney failure, improve the quality of care for patients with end-stage kidney disease (ESKD), and increase access to kidney transplantation. Central to the success of these initiatives will be the management of a growing population of patients with ESKD and obesity. Not only does obesity increase the progression of kidney failure, but it also leads to lower hemodialysis fistula maturation rates, decreases access to transplantation, and negatively impacts post transplant outcomes.2-8

Despite its broad clinical and epidemiologic importance, contemporary data on the prevalence of obesity in patients with ESKD are limited. In 2002, approximately 30% of patients with ESKD had concurrent obesity (body mass index [BMI] >30 kg/m2), with rates increasing at twice that of the non-ESKD population.9 Unfortunately, a comprehensive follow-up to that literature is lacking. For the non-ESKD population, it is known that rates of obesity vary widely by state, making it unlikely that obesity has affected transplant centers across the United States equally. This may be particularly important because of how the Centers for Medicare and Medicaid Services organize efforts to improve the quality and value of care through a system of 18 regional ESKD networks. There is known geographic variation in ESKD incidence, clinical outcomes, dialysis access, and transplantation rates, but correlation to rates of obesity are unclear.10-12 This suggests that better data on how the obesity epidemic currently impacts patients with ESKD may have policy implication and also impact how transplant centers are addressing these new challenges in clinical care.13

Using population-based data from the United States Renal Data System, we assessed trends in the proportion of beneficiaries with ESKD and obesity between 2008 and 2016. To better understand the interplay between obesity and kidney transplantation, we investigated rates of transplant among patients in different weight classifications. Finally, we evaluated how these trends correlated and varied across geographic regions of the United States.

MATERIALS AND METHODS

Data Source and Study Population

We used patient-level data from the US Renal Data System (USRDS) for the years 2008 through 2016 to identify a prevalent cohort of patients with ESKD in the United States. The USRDS is composed of several files that provide detailed demographic, clinical, and claims-based information for Medicare beneficiaries on dialysis. Beneficiaries are identified by unique identifiers that permit the linking of information across the various files included in the USRDS. We used the Medical Evidence files to obtain information on demographics, including age, race, and geographic location. These files also contain information on patient comorbidities (eg, presence of hypertension, diabetes, and congestive heart failure). Receipt of kidney transplant was also included in the analysis. Details on the selection of patients are included in Figure 1.

FIGURE 1.
FIGURE 1.:
Flow diagram detailing cohort selection. BMI, body mass index; USRDS, United States Renal Data System.

Outcomes

The USRDS is unique compared with other claims-based registries because it incorporates data on patients’ BMI (kg/m2). We extracted BMI data from the medical evidence file, transplant files, and the CROWNWeb files, which are collected by Medicare from dialysis and other facilities where beneficiaries receive care. All patients included in the study cohort had a BMI on record at the time of dialysis initiation, which coincides with enrollment in the registry. Most patients have numerous BMI measurements filed throughout their time on dialysis. For those with multiple BMI measurements in the same year, we report the mean value for that patient. For those with data missing for a given year, we retained their most recent BMI before the year of interest. We obtained information on kidney transplantation from the linked United Network for Organ Sharing files also included in the USRDS registry. Patients who received a kidney transplant before the initiation of dialysis were included. Patients receiving >1 kidney transplant during the study period were counted once. Those who had already received a transplant were excluded from transplant rate estimates.

Statistical Analysis

We calculated the proportion of prevalent beneficiaries within BMI categories defined by the Centers for Disease Control and Prevention.14 First, we report those with a BMI classified as underweight (BMI <18.5), normal (18.5 to <25.0), overweight (25.0 to <30.0), or obese (≥30.0). We then report the proportion of beneficiaries with class 1 (30.0 to <35.0), class 2 (35.0 to <40.0), and class 3 (≥40.0) obesity. We compared rates of kidney transplantation across these groups as well. The transplant rate in patients with obesity was calculated as the number of patients transplanted who were classified as having class 1 obesity or greater divided by the total amount of transplant patients. We used simple linear regression to determine trends in the proportion of beneficiaries within each category of BMI. For these analyses, the outcome was the proportion of beneficiaries within a given category in a given year. The dependent variable was year modeled as a continuous variable. To ensure the cohorts of patients did not change significantly over time, we looked at the 3 most common comorbidities in ESKD beneficiaries (hypertension, diabetes, and congestive heart failure) and trended them over time for each weight class (obese, overweight, normal, underweight). These data, available in Table S1, SDC, https://links.lww.com/TXD/A353, demonstrated that the characteristics of the study population remained consistent over time.

All statistical analyses were performed using STATA statistical software version 14.2 (College Station, TX). All estimates were derived using robust confidence intervals. We used a 2-sided approach at the 5% significance level for all hypothesis testing. Maps were drawn using STATA. This study was deemed exempt by the institutional review board at the University of Michigan.

RESULTS

We identified 1 079 410 total beneficiaries who were diagnosed with ESKD between 2008 and 2016 (Table 1). Beneficiaries with obesity (BMI ≥ 30.0) had a younger mean age (60.8 y, SD = 13.6) than those who were underweight (BMI < 18.5; 65.2 y, SD = 17.0), normal (BMI 18.5 to <25.0; 65.4 y, SD = 16.0), or overweight (BMI 25.0 to <30.0; 64.4 y, SD = 14.6). Although the rates of most comorbid conditions were qualitatively similar across categories of BMI, the rates of diabetes increased significantly from 33.0% in beneficiaries who were underweight to 67.7% in patients with obesity (P < 0.01 for trend).

TABLE 1. - Demographic and clinical characteristics of end-stage kidney disease beneficiaries from 2008 to 2016
No. (%)
Incident beneficiary characteristics, 2008–2016 Underweight Normal Overweight Obese
No. of beneficiaries 71 750 274 683 309 707 423 270
Age at baseline, mean (SD), y 65.1 (17.0) 65.3 (16.0) 64.4 (14.6) 60.7 (13.6)
Age categories, y
 18–29 3366 (4.7) 8711 (3.2) 6284 (2.0) 8070 (1.9)
 30–44 5629 (7.8) 22 026 (8.0) 25 225 (8.1) 45 924 (10.8)
 45–54 8234 (11.5) 33 339 (12.1) 42 211 (13.6) 74 814 (17.7)
 55–64 13 559 (18.9) 55 003 (20.0) 70 281 (22.7) 117 589 (27.8)
 65–79 25 125 (35.0) 98 441 (35.8) 117 112 (37.8) 145 227 (34.3)
 80 and older 15 837 (22.1) 57 163 (20.8) 48 594 (15.7) 31 646 (7.5)
Sex
 Female 36 298 (50.6) 106 270 (38.7) 115 527 (37.3) 203 604 (48.1)
 Male 35 450 (49.4) 168 408 (61.3) 194 169 (62.7) 219 657 (51.9)
Race/Ethnicity
 Hispanic 7694 (10.7) 38 962 (14.2) 47 433 (15.3) 53 154 (12.6)
 Non-Hispanic Black 20 731 (28.9) 70 288 (25.6) 80 236 (25.9) 123 858 (29.3)
 Non-Hispanic White 36 771 (51.2) 144 099 (52.5) 165 158 (53.3) 231 377 (54.7)
 Other 6554 (9.1) 21 334 (7.8) 16 880 (5.5) 14 881 (3.5)
Comorbidities
 Diabetes 23 696 (33.0) 124 462 (45.3) 173 286 (56.0) 286 510 (67.7)
 Myocardial infarction 11 437 (15.9) 49 141 (17.9) 58 035 (18.7) 74 505 (17.6)
 Peripheral vascular disease 8993 (12.5) 33 097 (12.0) 37 334 (12.1) 50 518 (11.9)
 Chronic obstructive pulmonary disease 8753 (12.2) 25 006 (9.1) 26 293 (8.5) 43 375 (10.2)
 Cerebrovascular disease 7327 (10.2) 26 922 (9.8) 28 951 (9.3) 34 611 (8.2)
Hypertension 59 174 (82.5) 234 469 (85.4) 269 785 (87.1) 373 675 (88.3)
 Congestive heart failure 19 455 (27.1) 78 239 (28.5) 93 150 (30.1) 142 264 (33.6)
Underweight (BMI <18.5), normal (BMI 18.5 to <25.0), overweight (BMI 25.0 to <30), and obese (BMI ≥30).
BMI, body mass index.

The proportion of beneficiaries within each category of BMI are included in Figure 2A and B. The largest cohort of beneficiaries were those with obesity (n = 423 270; 39.2%). There were 274 683 (25.4%) beneficiaries with a normal BMI. Among beneficiaries with obesity, the largest proportion of beneficiaries had class 1 obesity (n = 215 458, 50.4%).

FIGURE 2.
FIGURE 2.:
A and B, Shows the proportion of Medicare beneficiaries with end-stage kidney disease within each class (underweight, normal, overweight, obese) defined by BMI. Categories were defined by underweight (BMI <18.5), normal (BMI 18.5 to <25.0), overweight (BMI 25.0 to <30), Obese (BMI ≥30) (A). Classes of obesity were defined as class 1 (30.0 to <35.0), class 2 (35.0 to <40.0), and class 3 (≥40.0) obesity (B) BMI, body mass index.

The proportion of beneficiaries on dialysis with obesity increased significantly between 2008 (36.8%) and 2016 (40.2%; slope 0.28%/y, 95% confidence interval [CI], 0.05-0.51) (Table 2). This was accompanied by a significant decrease in the proportion of beneficiaries with a normal BMI on dialysis between 2008 (26.8%) and 2016 (24.4%; slope –0.21%/y, 95% CI, –0.35 to –0.07). The rate of transplant among patients with obesity increased significantly between 2008 (30.2%) and 2016 (37.4%; slope 0.67%/y, 95% CI, 0.11-1.22).

TABLE 2. - Trends in obesity and transplant rate for beneficiaries with end-stage kidney disease between 2008 and 2016
Prevalent rate % (N)
Year Underweight Normal Overweight Obese
 2008 7.3 (6515) 26.8 (23 859) 29.1 (25 962) 36.8 (32 733)
 2016 5.8 (29 240) 24.4 (122 070) 29.6 (147 952) 40.2 (201 212)
Trend (95% CI) –0.12 (–0.20 to –0.05) –0.21 (–0.35 to –0.07) 0.07 (0.04 to 0.09) 0.28 (0.05 to 0.51)
Transplant rate % (N)
Year
 2008 4.9 (124) 28.7 (727) 36.3 (921) 30.2 (765)
 2016 3.9 (449) 24.2 (2782) 34.6 (3976) 37.4 (4297)
Trend (95% CI) –0.08 (–0.21 to –0.05) –0.42 (–0.82 to –0.03) –0.16 (–0.34 to 0.08) 0.67 (0.11 to 1.22)
These data reflect the incident cohort by year. Underweight (BMI <18.5), normal (BMI 18.5 to <25.0), overweight (BMI 25.0 to <30), and obese (BMI ≥30). The trend is the slope from linear regression models representing the annual rate of change between 2008 and 2016.
BMI, body mass index (kg/m2); CI, confidence interval.

There was significant geographic variation across the United States with rates of obesity ranging from 32.3% to 45.4% and transplant rates among those patients ranging from 22.4% to 46.8%. Figure 3A shows the proportion of beneficiaries with ESKD and obesity by state. Patients with obesity tend to cluster in the Midwestern and Southern regions of the country, whereas the coastal regions had a qualitatively lower proportion of patients with obesity. Figure 3B displays the obesity transplant rates by state. There is a weak correlation between states with increased rates of obese ESKD patients and states with an increased obesity transplant rate as indicated with r = 0.40 (P = 0.003). Finally, we analyzed the difference in BMI between beneficiaries who received a kidney transplant from a deceased donor and beneficiaries who received a transplant from a living donor. Those receiving transplants from a deceased donor had a mean BMI of 28.8, (SD 6.4) and those receiving transplants from living donor had a mean of 28.4 (SD 6.2), which was not a clinically significant difference.

FIGURE 3.
FIGURE 3.:
A, Map of the United States detailing the proportion of Medicare beneficiaries with obesity and end-stage kidney disease by state from 2008 to 2016. Proportions were stratified into quartiles. B, Map of the United States detailing the rate of transplants performed on Medicare beneficiaries with obesity and end-stage kidney disease by state. Rates were stratified into quartiles.

DISCUSSION

This population-based study suggests that beneficiaries with obesity now represent the largest demographic of Medicare beneficiaries with ESKD in the United States. This demographic has also experienced the largest growth over the decade studied between 2008 and 2016. We observed significant geographic variation in rates of obesity among patient with ESKD, concentrating in the Midwestern and Southern states. Furthermore, states with higher rates of obese ESKD beneficiaries poorly correlated with higher rates of transplant in patients with obesity. These data highlight the importance of incorporating obesity treatment strategies into initiatives or policies aiming to improve care for patients with ESKD.

Policies designed to increase rates of kidney transplantation have not historically included provisions to address implications of the obesity epidemic. For instance, the Advancing American Kidney Health initiative encourages cost and quality interventions with a particular focus on increasing rates of kidney transplant1; however, for the growing proportion of ESKD patients with obesity, increasing BMI is associated with lower rates of access to kidney transplant and worse outcomes. The lack of strong geographic correlation between ESKD beneficiary obesity rates and obese beneficiary transplant rates demonstrates that transplant centers handle these patients differently, offering an opportunity to study and align best practice to improve kidney transplant candidacy. One potential target is to improve access to and utilization of bariatric surgery, the most effective and durable treatment for obesity. Despite known benefits, it remains underutilized in the ESKD population.15,16 In addition to facilitating durable weight loss, bariatric surgery improves diabetic control and hypertension and likely bolsters candidacy for kidney transplant.17 Recent work has shown that bariatric surgery is safe and effective in this group despite historic reluctance to perform elective operations in this high-risk population.18

Medical comorbidities such as diabetes, hypertension, and cardiovascular disease are more common in patients with obesity, which contributes to higher rates of morbidity and cardiovascular mortality in the ESKD population.19 Obesity at the time of dialysis initiation adversely impacts both management through lower fistula maturation rates and cure through decreased access to transplant compared with patients with a normal BMI.4,8 Conversely, once on dialysis, patients with obesity have been found to have a lower risk of all-cause mortality—an effect often referred to as the obesity paradox.20 Although the paradox has been demonstrated numerous times, the association may obscure the potential benefits of healthy weight loss—including improved candidacy for kidney transplant. These competing risks highlight the importance of understanding trends in obesity among patients with ESKD, especially as prevalence increases over time.

This study should be interpreted with the context of certain limitations. Although focusing on Medicare beneficiaries with ESKD may limit generalizability, Medicare covers the majority of ESKD patients across the United States. Claims-based registries often lack clinical granularity; however, the USRDS addresses this by collecting data specific to ESKD care. For the purposes of this study, the USRDS collects data from dialysis centers that are required to document beneficiaries’ heights and weights at the time of dialysis initiation and at subsequent episodes. This enables accurate assignment of BMI data across a large population of beneficiaries. Missing data can limit the effectiveness of claims-based studies; however, for the variables collected, missingness was <1%.

Beneficiaries with obesity are now the largest and fastest growing demographic among patients with ESKD in the United States. There is significant geographic variation in the prevalence of beneficiaries with obesity, with weak correlation to rates of kidney transplantation. These findings suggest that any policies and practices aiming to improve outcomes for patients with kidney disease would be enhanced by a greater focus on obesity management and prevention.

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