Higher remnant cholesterol inflammatory index is associated with increased frailty risk in the UK Biobank

Remnant cholesterol inflammatory index in relation to frailty burden and longitudinal trajectories: Findings from CHARLS and ELSA.

BACKGROUND Frailty represents a critical geriatric syndrome characterized by increased vulnerability to stressors, underpinned by chronic inflammation and metabolic dysregulation. This study aimed to investigate the prospective association between baseline Remnant Cholesterol Inflammatory Index (RCII) and both baseline frailty and long-term progression trajectories in two large, ethnically diverse aging cohorts. METHODS This study utilized data from the China Health and Retirement Longitudinal Study (CHARLS; n = 8916) and the English Longitudinal Study of Aging (ELSA; n = 5732). RCII was calculated from baseline remnant cholesterol (RC) and high-sensitivity C-reactive protein (hs-CRP). Frailty was assessed using a 32-item frailty index (FI). Linear mixed-effect models were used to examine associations between RCII tertiles and FI trajectories. RESULTS In cross-sectional analyses, the highest RCII tertile was associated with a significantly increased baseline FI in both CHARLS and ELSA after full adjustment. In longitudinal analyses, results for RC alone indicated that while high levels were associated with consistently elevated frailty, they were not consistently associated with an accelerated rate of progression, characterized by parallel trajectories. A significant interaction between the highest RCII tertile and time was observed in CHARLS (β = 0.197, 95% CI: 0.060 to 0.335, P = 0.020) and ELSA (β = 0.055, 95% CI: 0.042 to 0.069, P < 0.001). CONCLUSION Higher baseline RCII is consistently associated with both greater baseline frailty and is also associated with steeper frailty trajectories in older adults. These findings suggest that RCII may serve as a valuable biomarker to identify older adults at high risk for functional decline.

Relationship Between Cardiometabolic Index and Incident Frailty in Middle-Aged and Older Adults: A Cohort Study

Introduction The cardiometabolic index (CMI), a comprehensive indicator for assessing body fat distribution and serum lipid level, has been found to be associated with biological aging. But the potential relationship between CMI and incident frailty remains unclear. Herein, we designed this study to delve into the relationship between CMI and frailty incidence in adults aged 45 years or older. Methods Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). Participants were categorized into quartiles (Q1–Q4) according to CMI levels. Multivariable logistic regression model and restricted cubic spline (RCS) analyses were performed to evaluate the connection between CMI and incident frailty risk. In addition, we conducted subgroup and interaction analyses to investigate heterogeneity across distinct subgroups. Results A total of 6200 participants were enrolled in our study, with an average age of 57.92 ± 8.57 years, 48.64% males. During a 7-year follow-up, 1166 (18.81%) participants developed frailty, and the incidence showed an increasing trend from Q1 to Q4. The fully adjusted odds of developing frailty increased by 1% for per 1-SD increment in CMI (OR = 1.02, 95% CI:1.00-1.03, P = 0.005). The participants with the highest CMI quartile (Q4) had a significantly elevated risk of developing frailty compared to those in the lowest CMI group (Q1) (OR = 1.06, 95% CI:1.02-1.09, P < 0.001). Subgroup analyses demonstrated consistent results across various subgroups (P for interaction > 0.05). The RCS analysis confirmed a positive association of CMI with incident frailty, and nonlinear relationship was observed (P for overall < 0.001, P for nonlinear = 0.012). Conclusion Higher CMI levels were associated with an increased likelihood of developing frailty. Given its accessibility, CMI may have potential value as a population-level marker for frailty risk assessment.

Cumulative lipid–inflammatory indices and the risk of cardiometabolic multimorbidity: a prospective cohort study

Background Cardiometabolic multimorbidity (CMM) has become a major global public health challenge. Although dyslipidemia and chronic low-grade inflammation are known to contribute to cardiometabolic diseases, their long-term cumulative combined effects on the risk of CMM remain poorly understood. This study aimed to evaluate the associations of cumulative lipid-inflammatory indices with incident CMM in a large prospective cohort. Methods A total of 25,376 participants from the Kailuan cohort were included and followed up until December 31, 2023. Nine cumulative lipid-inflammatory exposure indices were constructed via trapezoidal area-under-the-curve calculation using repeated measurements from 2006 to 2010. The primary outcome was incident CMM, defined as the concurrence of at least two cardiometabolic diseases including type 2 diabetes, ischemic heart disease and stroke. Multivariable Cox regression, restricted cubic spline analyses, competing-risk models, and subgroup analyses were applied. Results During a median follow-up of 13.0 years, 481 incident CMM events were documented. All nine cumulative lipid-inflammatory indices were independently and positively associated with an elevated risk of CMM in a dose-response manner. Incorporating these indices into conventional risk model improved risk reclassification and discriminatory ability. Conclusions Elevated cumulative lipid-inflammatory indices are associated with a higher risk of incident CMM. These composite markers may serve as auxiliary indicators for preliminary risk stratification, while causal relationships cannot be confirmed based on this observational cohort alone.

Evidence from two large prospective cohorts: variations in remnant cholesterol inflammation index and the risk of cardiometabolic multimorbidity in middle-aged and elderly populations.

OBJECTIVE While residual cholesterol (RC) and high-sensitivity C-reactive protein (hs-CRP) are independent risk factors for cardiometabolic multimorbidity (CMM), their combined predictive value remains unclear. We investigated the predictive utility of the remnant cholesterol inflammation index (RCII) for CMM incidence. METHODS The RCII was derived from 5,870 participants in the China Health and Retirement Longitudinal Study (CHARLS) and 2,295 in the English Longitudinal Study of Ageing (ELSA), calculated as RC (mg/dL) × hs-CRP (mg/L) / 10. Longitudinal analyses in a subcohort (n = 5,966) further assessed the associations between cumulative RCII, changes in RCII and CMM incidence. RESULTS Each ln-unit increase in baseline RCII was associated with a 14% (CHARLS: HR 1.14, 95% CI 1.09-1.19) and 21% (ELSA: HR 1.21, 95% CI 1.10-1.34) higher CMM risk. Similarly, cumulative RCII increments raised CMM risk by 20% (CHARLS: HR 1.20, 95% CI 1.11-1.29) and 30% (ELSA: HR 1.30, 95% CI 1.11-1.51). Transition patterns analysis showed that stable high RCII levels conferred the highest CMM risk compared to stable low RCII levels. RCII demonstrated moderate independent predictive capability for CMM and outperformed RC or hs-CRP alone. CONCLUSION By integrating lipid and inflammatory pathways, the RCII was significantly associated with incident CMM and may enhance early risk stratification.

Association of the combined triglyceride-glucose and frailty index with chronic kidney disease: evidence from two national cohort studies

Residual Cholesterol Inflammatory Index: A Predictor of Cardiovascular-Kidney-Metabolic Syndrome; Insights from NHANES and CHARLS Cohorts.

RCII exhibited an independent and positive association with CKM risk in the US and Chinese populations, with consistent dose-response and nonlinear trends, and may be a practical and integrative biomarker for identifying individuals with an increased CKM risk.