Kidney Week

Abstract: PUB245

Latent Multimorbidity Phenotypes and Kidney Outcomes in Middle-Aged and Older Adults

Session Information

• Publication Only

Category: CKD (Non-Dialysis)

• 2201 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

• Huang, Hai, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China

Hai Huang

• Chen, Junzhe, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China

Junzhe Chen, PhD

• Tang, Ying, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China

Ying Tang, MD, PhD

• Lu, Yi, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China

Yi Lu

• Zhu, Yuqi, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China

Yuqi Zhu

Background

Multimorbidity, defined as the coexistence of ≥2 chronic conditions, is increasingly prevalent among middle-aged and older adults. However, traditional approaches based on disease counts or single diseases fail to capture nonrandom disease clustering patterns.

Methods

A total of 6,954 participants from the China Health and Retirement Longitudinal Study (CHARLS) were included. 14 chronic conditions were incorporated into latent class analysis (LCA) to identify multimorbidity patterns among adults aged ≥45 years. Multivariable logistic regression models were used to examine associations between multimorbidity patterns and renal outcomes. Renal outcome was defined as ≥30% decline in eGFR, ≥50% increase in serum creatinine, or follow-up eGFR <15 mL/min/1.73 m2. Network analysis was performed to identify central diseases and nonrandom disease associations.

Results

Five multimorbidity patterns were identified: relatively healthy (57.4%), cardiometabolic (12.7%), respiratory disease (6.7%), arthritis-digestive (20.1%), and multisystem patterns (4.1%). Compared with the relatively healthy pattern, only the cardiometabolic pattern was independently associated with adverse renal outcomes after full adjustment (OR 1.94, P=0.007). Network analysis showed that dyslipidemia and heart disease had the highest network connectivity and bridging roles within the multimorbidity network.

Conclusion

Distinct multimorbidity patterns were identified among middle-aged and older adults, and the cardiometabolic pattern was independently associated with adverse renal outcomes.

Association Between Five Multimorbidity Phenotypes and Adverse Renal Outcomes

Centrality Measures