Annual fat mass change is a significant predictor of mortality in female hemodialysis patients.
BACKGROUND
Although obesity confers an increased risk of mortality in the general population, it has been reported to be associated with improved survival in dialysis patients. However, the influence of fat mass change over time on mortality in dialysis patients has not been determined.


METHODS
This relationship was examined in 190 female maintenance hemodialysis patients. Fat mass was measured twice with a 12-month interval, using dual energy X-ray absorptiometry (DEXA). The patients were followed up for 5 years, and predictors for all-cause death were examined using Kaplan-Meier analysis and Cox proportional hazards analyses.


RESULTS
During the 5-year follow-up period, 65 patients died. Annual fat mass changes in the expired group tended to be greater than in the surviving group (-1.0 +/- 2.5 vs. -0.3 +/- 2.6 kg; P = 0.0776), although initial body fat mass was not significantly different. Kaplan-Meier analysis revealed that patients with decreased fat mass (N = 110) had a significantly lower survival rate, compared with those with increased fat mass (N = 80; P = 0.021). Multivariate Cox proportional hazards analyses demonstrated that annual fat mass change was a significant predictor of all-cause mortality after adjustments for confounding factors, such as age, serum albumin, serum creatinine, and the presence of diabetes. An increase in annual fat mass of 1 kg reduced mortality by 14.5%.


CONCLUSIONS
These results demonstrate that the decrease in annual fat mass is a significant predictor for mortality in female hemodialysis patients. Fat mass change is also a useful parameter for measurement of nutritional status in hemodialysis patients.
Fujino
Yoko
Y
Shirasagi Hospital Kidney Center, Osaka, Japan.
Ishimura
Eiji
E
Okuno
Senji
S
Tsuboniwa
Naoki
N
Maekawa
Kiyoshi
K
Izumotani
Tsuyoshi
T
Yamakawa
Tomoyuki
T
Inaba
Masaaki
M
Nishizawa
Yoshiki
Y
D015502:Absorptiometry, Photon; D000273:Adipose Tissue / Q000502:physiology*; D000368:Aged; D001823:Body Composition / Q000502:physiology*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D009752:Nutritional Status; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D006435:Renal Dialysis / Q000401:mortality*; D013534:Survival