Europe PMC

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Abstract 


Background

Decreased lean body mass or muscle mass is associated with decreased bone mineral density in individuals with preserved renal function. However, the association between muscle mass and bone mineral density in chronic kidney disease (CKD) patients is not well known. The aim of this study was to assess the relationship between muscle mass estimated from urine creatinine (UCr) and bone mineral density in Korean CKD patients.

Methods

This cross-sectional study analyzed 1872 participants from the Korean Cohort Study for Outcome in Patients With Chronic Kidney Disease (KNOW-CKD) cohort. Participants underwent UCr (g/day) and bone mineral density measurements, which were measured at the lumbar spine, total hip, and femoral neck by dual-energy X-ray absorptiometry. Patients were divided into three groups according to the tertiles of 24 h UCr (T1-T3).

Results

The mean values for 24 h urine creatinine of T1, T2, and T3 were 0.83 ± 0.23 g, 1.18 ± 0.24 g, and 1.55 ± 0.38 g, respectively. A total of 172 patients were diagnosed with osteoporosis. The number of patients in each group was 92 (14.4%) in T1, 45 (7.3%) in T2, and 35 (5.7%) in T3. The odds ratio (95% confidence interval) for osteoporosis was 0.37 (0.20-0.69) for 1 g/day increase of UCr. Compared with T1, the odds ratios (95% confidence interval) for osteoporosis were 0.58 (0.39-0.87) for T2 and 0.51 (0.32-0.80) for T3.

Conclusion

Low 24-h UCr was associated with low bone mineral density. Low 24 h UCr was significantly and independently associated with osteoporosis in Korean pre-dialysis CKD patients. Further research is warranted to verify the influence of muscle mass on bone health in CKD.

References 


Articles referenced by this article (27)


Show 10 more references (10 of 27)

Similar Articles 


To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.


Funding 


Funders who supported this work.

Korea Disease Control and Prevention Agency (12)