Health insurance status of US living kidney donors.
OBJECTIVE
Ensuring follow-up of living kidney donors (LKDs) is essential to long-term preventive care. We sought information on health insurance status of US LKDs, with particular attention to age, gender, and ethnicity.


METHODS
The United Network for Organ Sharing/Organ Procurement Transplantation Network database was queried for associations among age at donation, race, gender, and health insurance status. We studied all US LKDs between July 2004 and September 2006.


RESULTS
A total of 10,021 LKDs with known health insurance status were studied, 1765 (18%) of whom lacked health insurance at donation. There were 4852 donors without health insurance information. Younger kidney donors had higher rates of being uninsured (age 18 to 34: 26.2%; age 35 to 49: 15.2%; age 50 to 64: 11.2%; age >65: 3.8%; P < 0.0001), as did men (19.5 versus 16.3% for women; P < 0.0001), and ethnic minorities (white 13.4%, black 21%, Hispanic 35.6%, Asian 26.7%; P < 0.0001).


CONCLUSIONS
This study confirms that younger patients, ethnic minorities, and men are less likely to have health insurance when donating a kidney, which could negatively affect adherence to long-term follow-up.
Gibney
Eric M
EM
Piedmont Transplant Center, Piedmont Hospital, Atlanta, Georgia, USA. eric.gibney@piedmont.org
Doshi
Mona D
MD
Hartmann
Erica L
EL
Parikh
Chirag R
CR
Garg
Amit X
AX
D000293:Adolescent; D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data; D000367:Age Factors; D000368:Aged; D001213:Asian / Q000706:statistics & numerical data; D016009:Chi-Square Distribution; D005260:Female; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data*; D007348:Insurance, Health / Q000706:statistics & numerical data*; D016030:Kidney Transplantation / Q000009:adverse effects / Q000208:ethnology / Q000706:statistics & numerical data*; D019520:Living Donors / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009392:Nephrectomy / Q000009:adverse effects / Q000706:statistics & numerical data*; D012042:Registries; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors; D009927:Tissue and Organ Procurement / Q000706:statistics & numerical data; D014481:United States; D044465:White People / Q000706:statistics & numerical data; D055815:Young Adult