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已发表论文
代谢模式与肾功能下降的性别特异性关联：中国东南部一项回顾性队列研究
Authors Zhao Z, Ni X, Xu J, Ran X, Wang T, Zhang P, Chen Y, Ma H, Wu Q
Received 26 August 2025
Accepted for publication 16 December 2025
Published 25 December 2025 Volume 2025:18 Pages 8225—8235
DOI https://doi.org/10.2147/JMDH.S560234
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Jagdish Khubchandani
Zhaoyang Zhao, Xiaoqing Ni, Jiale Xu, Xiaojiang Ran, Tao Wang, Penghui Zhang, Yihe Chen, Haiyan Ma, Qiong Wu
Department of Epidemiology and Biostatistics, School of Public Health and Nursing, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, People’s Republic of China
Correspondence: Haiyan Ma; Qiong Wu, Department of Epidemiology and Biostatistics, School of Public Health and Nursing, Hangzhou Normal University, Yuhangtang Road, Yuhang District, Hangzhou, 311121, People’s Republic of China, Tel +86-0571-28862736 ; +86-18888925145, Email mahaiyan@hznu.edu.cn; 20220094@hznu.edu.cn
Purpose: To construct sex-specific metabolic patterns and investigate their effect on renal function decline among individuals without chronic kidney disease (CKD).
Patients and Methods: The subjects were from a community-based health survey in China from 2012 to 2018. 8511 eligible participants with at least three times of investigations were included. Metabolic patterns were constructed by Latent Profile Analysis based on total cholesterol, blood pressure, and fasting glucose. Renal function decline was defined as eGFR < 90 mL/[min• 1.73m2]. The effect of metabolic patterns on renal function decline over time was evaluated using Generalized Estimating Equations (GEE).
Results: Women were classified into No Metabolic Abnormalities (NMA), Hypertension-Impaired Fasting Glucose-Borderline Dyslipidemia (HIB), and Hypertension-Hyperglycemia-Borderline Dyslipidemia (HHB). Men were classified into NMA, Hypertension-Impaired Fasting Glucose-Normal Total Cholesterol (HIN), and Hypertension-Hyperglycemia-Normal Total Cholesterol (HHN). Compared to NMA, the risk of renal function decline over time was approximately 1.33 times higher in the HIB group and 1.41 times higher in the HHB group (95% CIs: 1.29– 1.37 and 1.25– 1.59, respectively). Consistently, these groups showed a faster eGFR decline over time than NMA. For men, the risks of renal function decline increased by 26% per year in the HIN group compared to NMA (95% CI = 1.19– 1.33). No such time-dependent association was observed in the HHN group. Both HIN and HHN groups showed no significant effect on accelerated eGFR decline.
Conclusion: Women with HIB and HHB, and men with HIN, have an accelerated risk of renal function decline. Earlier management of metabolic abnormalities is critical for kidney protection.
Keywords: metabolic abnormality, estimated glomerular filtration rate, renal function decline, gender difference, latent profile analysis
Department of Epidemiology and Biostatistics, School of Public Health and Nursing, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, People’s Republic of China
Correspondence: Haiyan Ma; Qiong Wu, Department of Epidemiology and Biostatistics, School of Public Health and Nursing, Hangzhou Normal University, Yuhangtang Road, Yuhang District, Hangzhou, 311121, People’s Republic of China, Tel +86-0571-28862736 ; +86-18888925145, Email mahaiyan@hznu.edu.cn; 20220094@hznu.edu.cn
Purpose: To construct sex-specific metabolic patterns and investigate their effect on renal function decline among individuals without chronic kidney disease (CKD).
Patients and Methods: The subjects were from a community-based health survey in China from 2012 to 2018. 8511 eligible participants with at least three times of investigations were included. Metabolic patterns were constructed by Latent Profile Analysis based on total cholesterol, blood pressure, and fasting glucose. Renal function decline was defined as eGFR < 90 mL/[min• 1.73m2]. The effect of metabolic patterns on renal function decline over time was evaluated using Generalized Estimating Equations (GEE).
Results: Women were classified into No Metabolic Abnormalities (NMA), Hypertension-Impaired Fasting Glucose-Borderline Dyslipidemia (HIB), and Hypertension-Hyperglycemia-Borderline Dyslipidemia (HHB). Men were classified into NMA, Hypertension-Impaired Fasting Glucose-Normal Total Cholesterol (HIN), and Hypertension-Hyperglycemia-Normal Total Cholesterol (HHN). Compared to NMA, the risk of renal function decline over time was approximately 1.33 times higher in the HIB group and 1.41 times higher in the HHB group (95% CIs: 1.29– 1.37 and 1.25– 1.59, respectively). Consistently, these groups showed a faster eGFR decline over time than NMA. For men, the risks of renal function decline increased by 26% per year in the HIN group compared to NMA (95% CI = 1.19– 1.33). No such time-dependent association was observed in the HHN group. Both HIN and HHN groups showed no significant effect on accelerated eGFR decline.
Conclusion: Women with HIB and HHB, and men with HIN, have an accelerated risk of renal function decline. Earlier management of metabolic abnormalities is critical for kidney protection.
Keywords: metabolic abnormality, estimated glomerular filtration rate, renal function decline, gender difference, latent profile analysis