Skip to main content

Main menu

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Podcasts
    • Subject Collections
    • Archives
    • Kidney Week Abstracts
    • Saved Searches
  • Authors
    • Submit a Manuscript
    • Author Resources
  • Trainees
    • Peer Review Program
    • Prize Competition
  • About CJASN
    • About CJASN
    • Editorial Team
    • CJASN Impact
    • CJASN Recognitions
  • More
    • Alerts
    • Advertising
    • Feedback
    • Reprint Information
    • Subscriptions
  • ASN Kidney News
  • Other
    • ASN Publications
    • JASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
American Society of Nephrology
  • Other
    • ASN Publications
    • JASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Advertisement
American Society of Nephrology

Advanced Search

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Podcasts
    • Subject Collections
    • Archives
    • Kidney Week Abstracts
    • Saved Searches
  • Authors
    • Submit a Manuscript
    • Author Resources
  • Trainees
    • Peer Review Program
    • Prize Competition
  • About CJASN
    • About CJASN
    • Editorial Team
    • CJASN Impact
    • CJASN Recognitions
  • More
    • Alerts
    • Advertising
    • Feedback
    • Reprint Information
    • Subscriptions
  • ASN Kidney News
  • Visit ASN on Facebook
  • Follow CJASN on Twitter
  • CJASN RSS
  • Community Forum
Original ArticlesTransplantation
Open Access

Social Determinants of Health and Race Disparities in Kidney Transplant

Hannah Wesselman, Christopher Graham Ford, Yuridia Leyva, Xingyuan Li, Chung-Chou H. Chang, Mary Amanda Dew, Kellee Kendall, Emilee Croswell, John R. Pleis, Yue Harn Ng, Mark L. Unruh, Ron Shapiro and Larissa Myaskovsky
CJASN February 2021, 16 (2) 262-274; DOI: https://doi.org/10.2215/CJN.04860420
Hannah Wesselman
1Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Hannah Wesselman
Christopher Graham Ford
2Center for Healthcare Equity in Kidney Disease, University of New Mexico Health Sciences Center, Albuquerque, New Mexico
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Christopher Graham Ford
Yuridia Leyva
2Center for Healthcare Equity in Kidney Disease, University of New Mexico Health Sciences Center, Albuquerque, New Mexico
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xingyuan Li
3Eli Lilly and Company, Indianapolis, Indiana
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Xingyuan Li
Chung-Chou H. Chang
4Department of Medicine, University of Pittsburgh, School of Medicine, Pittsburgh, Pennsylvania
5Department of Biostatistics, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, Pennsylvania
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mary Amanda Dew
6Department of Psychiatry, University of Pittsburgh, School of Medicine, Pittsburgh, Pennsylvania
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kellee Kendall
4Department of Medicine, University of Pittsburgh, School of Medicine, Pittsburgh, Pennsylvania
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Kellee Kendall
Emilee Croswell
4Department of Medicine, University of Pittsburgh, School of Medicine, Pittsburgh, Pennsylvania
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
John R. Pleis
7Division of Research and Methodology, National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yue Harn Ng
8Department of Internal Medicine, University of New Mexico, School of Medicine, Albuquerque, New Mexico
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Yue Harn Ng
Mark L. Unruh
8Department of Internal Medicine, University of New Mexico, School of Medicine, Albuquerque, New Mexico
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ron Shapiro
9Mount Sinai Recanati/Miller Transplantation Institute, Icahn School of Medicine, New York, New York
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Larissa Myaskovsky
2Center for Healthcare Equity in Kidney Disease, University of New Mexico Health Sciences Center, Albuquerque, New Mexico
8Department of Internal Medicine, University of New Mexico, School of Medicine, Albuquerque, New Mexico
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Larissa Myaskovsky
  • Article
  • Figures & Data Supps
  • Info & Metrics
  • View PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Additional Files
  • Figure1
    • Download figure
    • Open in new tab
    • Download powerpoint
  • Figure 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1.

    Kidney transplant candidates included and excluded from study cohort.

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

    Cumulative incidence probability by event status, with pointwise 95% confidence interval.

  • Figure 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 3.

    Cumulative incidence probability by event status separated by race (White and Black), with pointwise 95% confidence interval.

Tables

  • Figures
  • Additional Files
    • View popup
    Table 1.

    Baseline characteristics by transplant status

    VariablesTotalReceived a TransplantaDiedbCensoredc
    (n=1056)(n=363)(n=413)(n=280)
    Demographic characteristicsd
     Race/ethnicity
      Non-Hispanic White, n (%)789 (75)298 (82)309 (75)182 (65)
      Non-Hispanic Black, n (%)267 (25)65 (18)104 (25)98 (35)
     Sex (female), n (%)406 (38)141 (39)146 (35)119 (43)
     Age (in yr), mean (SD)57±1352±1461±1256±13
     Education (≤high school), n (%)496 (47)147 (41)212 (51)137 (49)
     Household income (<US$50,000), n (%)739 (74)214 (62)316 (81)209 (79)
     Insurance status, n (%)
      Public only277 (26)148 (41)62 (15)67 (24)
      Private only370 (35)98 (27)152 (37)120 (43)
      Public and private400 (38)113 (31)194 (48)93 (33)
     Occupation (≥skilled manual worker), n (%)512 (49)190 (52)201 (49)121 (43)
     Marital status (not married), n (%)512 (48)171 (47)195 (47)146 (52)
     Final status after KAS, n (%)e428 (41)130 (36)166 (40)132 (47)
    Medical factors
     BMI, mean (SD)29.6±6.329.3±6.229.6±6.329.9±6.3
     Charlson Comorbidity Index, median (IQR)4.0 (3.0–5.0)4.0 (2.0–4.0)5.0 (4.0–6.0)4.0 (2.0–5.0)
     Type of dialysis, n (%)
      None366 (35)168 (46)87 (21)111 (39)
      Hemodialysis583 (55)158 (44)277 (67)148 (53)
      Peritoneal dialysis107 (10)37 (10)49 (12)21 (8)
     Dialysis duration in yr, median (IQR)0.2 (0.0–0.7)0.2 (0.0–0.7)0.3 (0.1–0.9)0.2 (0.0–0.7)
     Burden of kidney disease (range: 1–5), median (IQR)4.0 (3.0–4.7)3.7 (3.0–4.3)4.0 (3.0–4.7)3.7 (3.0–4.7)
     No. of potential donors, median (IQR)17 (11–29)20 (12–30)15 (10–28)18 (10–27)
     Have a potential living donor at T1 (yes), n (%)556 (54)225 (64)183 (46)148 (54)
    Cultural factors
     Experience of discrimination (any), n (%)268 (26)70 (19)119 (29)79 (28)
     Perceived racism (range: 1–5), median (IQR)2.3 (2.0–2.8)2.3 (2.0–2.5)2.3 (2.0–2.8)2.4 (2.0–2.8)
     Medical mistrust (range: 1–5), mean (SD)2.4±0.52.4±0.52.5±0.52.5±0.5
     Trust in physician (range: 1–5), mean (SD)2.2±0.52.2±0.52.2±0.52.2±0.5
     Family loyalty (range: 8–80), mean (SD)49.8±9.449.5±9.649.6±9.250.7±9.5
     Religious objection to living-donor kidney transplant, n (%)
      No objection361 (35)139 (39)135 (34)87 (31)
      Mixed (neutral + no objection)100 (10)32 (9)50 (12)18 (6)
      Any objection580 (56)189 (53)218 (54)173 (62)
     Overall religiosity (range: 1–9), median (IQR)7.0 (4.5–9.0)6.0 (4.0–8.5)7.0 (5.0–9.0)7.5 (5.0–9.0)
    Psychosocial characteristics
     Social support (range: 12–48), median (IQR)44.0 (39.0–48.0)45.0 (41.0–48.0)44.0 (38.0–47.0)43.0 (37.0–47.0)
     Self-esteem (range: 1–4), median (IQR)3.1 (2.9–3.5)3.1 (2.9–3.6)3.0 (2.8–3.5)3.1 (2.8–3.5)
     Mastery (range: 1–4), median (IQR)3.0 (2.7–3.1)3.0 (2.9–3.1)2.9 (2.7–3.1)3.0 (2.7–3.1)
     Internal locus of control (range: 1–6), mean (SD)4.0±1.13.8±1.14.1±1.04.1±1.1
     External locus of control (range: 1–6), mean (SD)3.4±0.83.3±0.73.5±0.93.5±0.8
     Anxiety (≥moderate), n (%)47 (4)13 (4)21 (5)13 (5)
     Depression (≥moderate), n (%)42 (4)11 (3)20 (5)11 (4)
    Transplant knowledge and education
     Transplant knowledge (range: 0–27), median (IQR)22.0 (20–23.0)23.0 (21.0–24.0)21.0 (19.0–23.0)21.0 (19.0–23.0)
     No. learning activities (range: 0–8), median (IQR)5.0 (3.0–6.0)5.0 (4.0–6.0)4.0 (3.0–5.0)4.0 (3.0–5.0)
     Total h of learning activities (range: 0–185), median (IQR)10.3 (6.0–21.5)12.0 (7.0–29.0)10.0 (5.3–20.5)9.5 (4.5–19.0)
     Transplant concerns (range: 0–30), mean (SD)10.9±4.710.9±4.810.9±4.510.8±4.9
     Donor preference, n (%)
      Deceased donor135 (13)46 (13)50 (12)39 (14)
      Living donor815 (77)287 (79)313 (76)215 (77)
      No preference104 (10)29 (8)49 (12)26 (9)
     Willing to accept living donor volunteer, n (%)934 (90)333 (93)355 (88)246 (90)
     Willing to ask for living donor donation, n (%)582 (57)205 (58)222 (56)155 (57)
    Years from evaluation to final follow-up, mean (range)3.1 (0.003–8.5)2.8 (0.07–7.7)3.3 (0.06–8.2)3.4 (0.003–8.5)
    • KAS, Kidney Allocation System; IQR, interquartile range, i.e., the interval between the 25th and 75th percentiles; UPMC, University of Pittsburgh Medical Center; UNOS, United Network for Organ Sharing.

    • ↵a Includes receiving a living-donor transplant at UPMC (n=109; White=100, Black=9), deceased-donor transplant at UPMC (n=218; White=167, Black=51), living-donor transplant at another center (n=15; White=14, Black=1), deceased-donor transplant at another center (n=14; White=12, Black=2), unknown transplant type at another center (n=7; White=5, Black=2). Unknown transplant type because UPMC does not have access to the UNOS data for other transplant centers, and participants could not be reached for verification, despite several attempts.

    • ↵b Died before or after waitlist but before receiving a transplant.

    • ↵c Censoring includes closed by patient choice (n=26–13 before waitlisting and 13 after waitlisting), clinic rejected (n=28), clinic removed patient from waiting list (n=56), transferred to another center (n=19), still in transplant evaluation (n=8), incomplete evaluation (n=114), or still on waitlist (n=29).

    • ↵d n=1 missing for transplant concerns; n=2 missing for occupation, transplant knowledge, donor preference; n=4 missing for family loyalty score; n=5 missing in medical mistrust index, trust in physician; n=6 missing in total social support; n=7 missing for internal and external locus of control, experienced discrimination in health care; n=8 missing for self-esteem scale; n=9 missing for total h engaged in learning activities; n=9 missing for insurance type; n=11 missing for racism in health care; n=15 missing for religious objection to living-donor kidney transplant; n=19 for willing to accept living donor volunteer; n=31 for having living donor; n=32 for willing to ask for living donor donation; n=53 missing/unknown for income.

    • ↵e Final status after KAS refers to whether the patient’s ultimate outcome (i.e., transplant, died, censored) occurred either before or after the KAS policy changes of 2014 to all of the tables that include this variable.

    • View popup
    Table 2.

    Fine-Gray proportional subdistribution hazard model for time from evaluation to receiving any transplanta (n=997)b

    VariablesModel 1Model 2Model 3
    Subdistribution Hazard Ratio95% Confidence IntervalSubdistribution Hazard Ratio95% Confidence IntervalSubdistribution Hazard Ratio95% Confidence Interval
    Model 1
     Race/ethnicity
      Non-Hispanic White1 (ref)1 (ref)1 (ref)
      Non-Hispanic Black0.600.46 to 0.780.670.51 to 0.900.740.55 to 0.99
    Model 2
     Demographic characteristics
      Age (in yr)0.970.96 to 0.980.980.97 to 0.99
      Household income (<US$50,000)0.580.45 to 0.740.650.50 to 0.85
      Insurance status
       Private only1 (ref)1 (ref)
       Public only0.620.46 to 0.830.600.44 to 0.80
       Public and private0.750.57 to 0.990.670.52 to 0.88
     Medical factors
      Charlson Comorbidity Index0.820.76 to 0.890.850.78 to 0.91
      Type of dialysis
       None1 (ref)
       Hemodialysis0.720.56 to 0.91
       Peritoneal dialysis0.740.50 to 1.10
    Model 3
     Final status after KASc2.381.77 to 3.19
     Cultural factors
      Overall religiosityd0.960.91 to1.00
     Psychosocial characteristics
      Social supportd1.041.01 to 1.06
     Transplant knowledge and education
      Transplant knowledged1.061.00 to 1.11
      No. learning activitiesd1.081.01 to 1.16
    • Higher value, greater amount (or higher score) on a particular variable. KAS, Kidney Allocation System; SHR, subdistribution hazard ratio.

    • ↵a Main event, received a transplant; competing event, died, censoring, still on waitlist or other removal.

    • ↵b Sample size used for Models 1, 2, and 3: n=997 (i.e., those with complete data on all variables; 346 received a transplant, 385 died, 266 censored).

    • ↵c Final status after KAS refers to whether the patient’s ultimate outcome (i.e., transplant, died, censored) occurred either before or after the KAS policy changes of 2014 to all of the tables that include this variable.

    • ↵d The SHR for these variables are per one-point higher in each scale.

    • View popup
    Table 3.

    Fine-Gray proportional subdistribution hazard model for time from evaluation to receiving a deceased-donor kidney transplanta (n=1036)b

    VariablesModel 1Model 2Model 3
    Subdistribution Hazard Ratio95% Confidence IntervalSubdistribution Hazard Ratio95% Confidence IntervalSubdistribution Hazard Ratio95% Confidence Interval
    Model 1
     Race/ethnicity
      Non-Hispanic White1 (ref)1 (ref)1 (ref)
      Non-Hispanic Black0.910.67 to 1.230.920.68 to 1.240.920.67 to 1.26
    Model 2
     Other demographic characteristics
      Age (in yr)0.980.97 to 0.990.990.98 to 1.00
     Medical factors
      Charlson Comorbidity Index0.820.75 to 0.900.850.77 to 0.93
    Model 3
     Final status after KASc4.173.03 to 5.73
     Cultural factors
      Overall religiosityd0.930.88 to 0.98
     Psychosocial characteristics
      Social supportd1.031.00 to 1.05
     Transplant knowledge and education
      Number of learning activitiesd1.101.02 to 1.19
    • Higher value, greater amount (or higher score) on a particular variable. KAS, Kidney Allocation System; DDKT, deceased-donor kidney transplant; LDKT, living-donor kidney transplant; SHR, subdistribution hazard ratio.

    • ↵a Main event, received DDKT; competing event, LDKT, died; censoring, still on waitlist or other removal; missing, unknown donor type.

    • ↵b Sample size used for Models 1, 2, and 3: n=1036 (i.e., those with complete data on all variables; 231 received a transplant, 525 died, 280 censored).

    • ↵c Final status after KAS refers to whether the patient’s ultimate outcome (i.e., transplant, died, censored) occurred either before or after the KAS policy changes of 2014 to all of the tables that include this variable.

    • ↵d The SHR for these variables are per one-point higher in each scale.

    • View popup
    Table 4.

    Fine-Gray proportional subdistribution hazards model for time from evaluation to receiving a living-donor kidney transplanta (n=961)b

    VariablesModel 1Model 2Model 3
    Subdistribution Hazard Ratio95% Confidence IntervalSubdistribution Hazard Ratio95% Confidence IntervalSubdistribution Hazard Ratio95% Confidence Interval
    Model 1
     Race/ethnicity
      Non-Hispanic White1 (ref)1 (ref)
      Non-Hispanic Black0.280.14 to 0.530.420.22 to 0.830.490.26 to 0.95
    Model 2
     Other demographic characteristics
      Age (in yr)0.980.96 to 0.990.980.96 to 0.99
      Household income (<US$50,000)0.520.34 to 0.810.590.38 to 0.92
      Insurance status
       Private only1 (ref)1 (ref)
       Public only0.310.16 to 0.580.320.17 to 0.60
       Public and private0.470.29 to 0.760.460.28 to 0.75
     Medical factors
      BMI0.970.94 to 0.990.960.93 to 0.99
      Type of dialysis
       None1 (ref)1 (ref)
       Hemodialysis0.490.31 to 0.790.520.33 to 0.84
       Peritoneal dialysis0.430.21 to 0.880.430.21 to 0.86
      Have a potential living donor at T1 (yes)3.982.34 to 6.793.672.15 to 6.26
    Model 3
     Cultural factors
      Religious objection to living-donor kidney transplant0.02
       No objection1 (ref)
       Mixed0.450.19 to 1.04
       Any objection0.620.42 to 0.92
      Transplant knowledge and education
       Transplant knowledgec1.121.02 to 1.23
    • Higher value, greater amount (or higher score) on a particular variable. BMI, body mass index; DDKT, deceased-donor kidney transplant; LDKT, living-donor kidney transplant; SHR, subdistribution hazard ratio.

    • ↵a Main event, received LDKT; competing event, DDKT, died; censoring, still on waitlist or other removal; missing, unknown donor type.

    • ↵b Sample size used for Models 1, 2, and 3: n=961 (i.e., those with complete data on all variables; 117 received a transplant, 585 died, 259 censored).

    • ↵c The SHR for this variable is per one-point higher in the scale.

Additional Files

  • Figures
  • Tables
  • Supplemental Data

    • Supplemental Data
PreviousNext
Back to top

In this issue

Clinical Journal of the American Society of Nephrology: 16 (2)
Clinical Journal of the American Society of Nephrology
Vol. 16, Issue 2
February 08, 2021
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • 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 CJASN.
Enter multiple addresses on separate lines or separate them with commas.
Social Determinants of Health and Race Disparities in Kidney Transplant
(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
Social Determinants of Health and Race Disparities in Kidney Transplant
Hannah Wesselman, Christopher Graham Ford, Yuridia Leyva, Xingyuan Li, Chung-Chou H. Chang, Mary Amanda Dew, Kellee Kendall, Emilee Croswell, John R. Pleis, Yue Harn Ng, Mark L. Unruh, Ron Shapiro, Larissa Myaskovsky
CJASN Feb 2021, 16 (2) 262-274; DOI: 10.2215/CJN.04860420

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Request Permissions
Share
Social Determinants of Health and Race Disparities in Kidney Transplant
Hannah Wesselman, Christopher Graham Ford, Yuridia Leyva, Xingyuan Li, Chung-Chou H. Chang, Mary Amanda Dew, Kellee Kendall, Emilee Croswell, John R. Pleis, Yue Harn Ng, Mark L. Unruh, Ron Shapiro, Larissa Myaskovsky
CJASN Feb 2021, 16 (2) 262-274; DOI: 10.2215/CJN.04860420
del.icio.us logo Digg logo Reddit logo Twitter logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like

Jump to section

  • Article
    • Visual Abstract
    • Abstract
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Disclosures
    • Funding
    • Acknowledgments
    • Supplemental Material
    • Footnotes
    • References
  • Figures & Data Supps
  • Info & Metrics
  • View PDF

More in this TOC Section

Original Articles

  • Incidence and Risk Factors for Dialysis Reinitiation among Patients with a History of Dialysis Dependency
  • Survey of Salary and Job Satisfaction of Transplant Nephrologists in the United States
  • Implications of Accumulated Cold Time for US Kidney Transplantation Offer Acceptance
Show more Original Articles

Transplantation

  • Patterns in Tacrolimus Variability and Association with De Novo Donor-Specific Antibody Formation in Pediatric Kidney Transplant Recipients
  • Association of HLA Mismatches and Histology Suggestive of Antibody-Mediated Injury in the Absence of Donor-Specific Anti-HLA Antibodies
  • Survey of Salary and Job Satisfaction of Transplant Nephrologists in the United States
Show more Transplantation

Cited By...

  • Barriers to Kidney Transplantation in Racial/Ethnic Minorities
  • Google Scholar

Similar Articles

Related Articles

  • Barriers to Kidney Transplantation in Racial/Ethnic Minorities
  • PubMed
  • Google Scholar

Keywords

  • kidney transplantation
  • social determinants of health
  • disparities

Articles

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

Information for Authors

  • Submit a Manuscript
  • Trainee of the Year
  • Author Resources
  • ASN Journal Policies
  • Reuse/Reprint Policy

About

  • CJASN
  • ASN
  • ASN Journals
  • ASN Kidney News

Journal Information

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

More Information

  • Advertise
  • ASN Podcasts
  • ASN Publications
  • Become an ASN Member
  • Feedback
  • Follow on Twitter
  • Subscribe to ASN Journals
  • Wolters Kluwer Partnership

© 2022 American Society of Nephrology

Print ISSN - 1555-9041 Online ISSN - 1555-905X

Powered by HighWire