Title:The Relationship between Age-Related Kidney Dysfunction and Framingham Risk Score in Healthy People in China
Volume: 3
Issue: 3
Author(s): Xiaojuan Bai, Lulu Han, Jing Liu, Weiguang Zhang, Hongyu Zhou, Shaochen Dong, Ying Sun and Xiangmei Chen
Affiliation:
Keywords:
Aging, cardiovascular risk factors, Framingham risk score, glomerular filtration rate, creatinine clearance rate.
Abstract: Background: Aging process reduces kidney function, glomerular filtration rate (GFR) and/or creatinine clearance rate (Ccr), and also significantly increases the risk level for cardiovascular diseases. The classical Framingham risk equation provides a method for predicting cardiovascular risk, but it does not include the kidney function indexes. In this study, we investigated the relationship between age-related kidney function and Framingham risk score (FRS) in healthy Chinese people, and validated to assess the risk factor by GFR/Ccr.
Methods: This community-based cross-sectional study recruited 505 healthy subjects (age from 35 to 93 yr.) with both genders is during September 2007 to June 2008 in Shenyang. Framingham risk equation was used to evaluate cardiovascular risk factors and generate FRS. GFR and Ccr were calculated with Cockcroft-Gault (CG) equation (GFRCG), abbreviated Modification of Diet in Renal Disease Study (MDRD) equation (GFRMDRD1) and modified MDRD equation (GFRMDRD2). All data were sorted according to FRS (low, moderate and high) risk levels, and five different age groups (≤44 yr; 45-54 yr; 55-64 yr; 65-74 yr and ≥75 yr). The ANOVA, correlation, partial correlation between GFR/Ccr and FRS, as well as other risk factors were analyzed with SPSS16.0 statistical package.
Results: As the FRS level increased, GFRCG, GFRMDRD1, GFRMDRD2 and Ccr decreased about 10 to 30% (low > moderate > high risk group, p < 0.01). While the subjects were getting older, GFRCG, GFRMDRD1, GFRMDRD2 and Ccr showed significant reduction (P < 0.001). Ccr decreased about 50% from the young to oldest group (p < 0.001). There was a significantly inverse correlation between FRS and GFR with Ccr having the Pearson correlation coefficient -0.586 (GFRCG, P < 0.001), - 0.449 (GFRMDRD1 and GFRMDRD2, P < 0.001), -0.459 (Ccr, P < 0.001). However, the relationship between FRS and Ccr was lost after controlling for age and other confounding variables.
Conclusion: In healthy population, we found inverse correlations between Framingham risk score and GFR, Ccr and GFR were independently related to the FRS with similar correlation coefficient among three equations. With the increase of FRS, the GFR and Ccr decrease. Aging is the major factor of GFR and Ccr reduction in the healthy population. We suggest that GFR/Ccr could be used as risk indexes for cardiovascular diseases.
