It is suggested that higher CMI may indicate a greater risk of cognitive decline in older adults, and diabetes status significantly modified the CMI–GCF relationship.
Abstract
Cardiometabolic index (CMI) reflects visceral fat accumulation and lipid metabolism and has been linked to metabolic and cardiovascular diseases. Its association with cognitive function in older adults remains unclear. This study aimed to assess the relationship between CMI and global cognitive performance in a nationally representative sample of United States adults aged 60 years and older. We conducted a cross-sectional analysis of National Health and Nutrition Examination Survey 2011 to 2014 data (n = 1326). CMI was analyzed both as a continuous variable and by quartiles (Q1–Q4). Survey-weighted linear regression models examined associations with global cognitive function (GCF), adjusting sequentially for demographics (ModelI) and full covariates (ModelII). Threshold effects and smoothing curves explored nonlinear links. Interaction tests and subgroup analyses evaluated effect modification by diabetes status. In the minimally adjusted model, higher continuous CMI was associated with lower GCF (β = −2.46, 95% confidence interval [CI]: 4.58–−0.35; P = .0318), but this association was not significant after full adjustment (β = −0.56, 95% CI: 2.49–1.36; P = .5807). When using quartiles, a negative trend was observed in the crude (P for trend = .0392) and minimally adjusted models (P for trend = .0166) but not in the fully adjusted model (P for trend = .4825). Nonlinear analysis identified an inflection at CMI = 0.16 for digit symbol substitution test (β = 142.74, 95% CI: 70.18–215.30; P < .001) and GCF (β = 173.67, 95% CI: 77.01–270.32; P < .001). Diabetes status significantly modified the CMI–GCF relationship (P for interaction = .035). CMI is negatively associated with cognitive function in older adults. These findings suggest that higher CMI may indicate a greater risk of cognitive decline.
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.
Zhenyou Liu, Qingyuan Wang, Jin Zhang et al.· Inquiry : a journal of medic...· 0 citations
Relative fat mass (RFM), derived from height and waist circumference, may better reflect overall and central adiposity than body mass index. This study examined the association between RFM and cognitive impairment among older adults in the United States. We conducted a cross-sectional analysis using National Health and Nutrition Examination Survey 2011–2014 data, including 2730 participants aged ≥ 60 years with valid anthropometric data, cognitive assessment data, and covariate information required for the primary analysis. Cognitive function was evaluated using the Consortium to Establish a Registry for Alzheimer Disease (word learning & delayed recall tests), animal fluency, and digit symbol substitution tests. Cognitive impairment was defined as performance below the education-specific 25th percentile of a standardized global cognition z-score. Weighted logistic regression models estimated associations between RFM and cognitive impairment, adjusting for demographic, socioeconomic, lifestyle, and clinical factors. Nonlinearity was tested using restricted cubic spline and two-piecewise regression analyses. In the base-adjusted model, RFM was not significantly associated with cognitive impairment. After full adjustment for demographic, socioeconomic, lifestyle, dietary, and clinical factors, higher RFM was associated with increased odds of cognitive impairment (odds ratio = 1.05; 95% confidence interval: 1.02–1.09). Sensitivity analyses excluding participants with very high body mass index, trimming RFM outliers, modeling log-transformed RFM, and using waist circumference as an alternative adiposity measure yielded directionally consistent results. The relationship was linear (P_overall = .042; P_nonlinear = .253), with stronger associations in participants aged < 70 years, and those with hypertension or prior stroke. Hypertension (10%) and physical inactivity (9.4%) partially mediated this relationship, whereas depression and diabetes showed minimal effects. Higher RFM was associated with greater odds of test-based cognitive impairment among United States older adults after multivariable adjustment. The observed associations involving hypertension and physical activity status were exploratory and should not be interpreted as causal. Future longitudinal studies are needed to clarify temporality and evaluate the potential clinical utility of RFM in cognitive risk assessment.
Cardiometabolic multimorbidity (CMM) is an escalating public health challenge. The uric acid (UA)-to-high-density lipoprotein cholesterol (HDL-C) ratio (UHR) is a composite biomarker reflecting metabolic disturbance, but prospective evidence regarding the association between UHR and CMM remains limited. This prospective cohort study included 7435 adults aged ≥ 45 years from China Health and Retirement Longitudinal Study followed from 2011 to 2018. Cox proportional hazards models and restricted cubic spline analyses were used to examine the associations of UHR and cumulative UHR (CumUHR) with CMM. Receiver operating characteristic curves, net reclassification improvement, and integrated discrimination improvement were used to compare the incremental predictive performance of UHR and CumUHR with that of UA and HDL-C alone. Subgroup and sensitivity analyses were conducted to test the robustness of the findings. Among the 7435 participants, 1748 developed CMM. Kaplan–Meier analysis showed that the cumulative event rate of CMM increased progressively across UHR quartiles (log-rank + < .001). In the fully adjusted model, the highest UHR quartile (Q4) was associated with a significantly increased risk of CMM compared with the lowest quartile (Q1) (hazard ratio = 1.48, 95% confidence interval 1.27–1.77). When cumulative exposure was considered, elevated CumUHR remained an independent predictor of CMM (hazard ratio = 1.26, 95% confidence interval 1.15–1.39). Restricted cubic spline analyses further demonstrated significant nonlinear associations of both UHR and CumUHR with CMM risk, with inflection points observed around 8.5 for UHR and 35.7 for CumUHR. Furthermore, UHR and CumUHR showed better predictive performance for CMM than their individual components, with higher areas under the curve and significant improvements in net reclassification improvement and integrated discrimination improvement, whereas UA and HDL-C alone did not significantly improve these predictive indices. Higher UHR and CumUHR levels were independently associated with an increased risk of CMM in middle-aged and older adults. As composite indicators integrating UA and HDL-C, UHR and CumUHR may provide complementary information for cardiometabolic risk assessment and may help identify individuals at elevated risk of CMM when considered alongside established clinical risk factors.
Insulin resistance is a key driver of cardiometabolic diseases, including stroke. The single-point insulin sensitivity estimator (SPISE) is a novel non-invasive marker of insulin sensitivity calculated from fasting triglycerides, high-density lipoprotein cholesterol and body mass index. However, its association with cardiometabolic multimorbidity (CMM) and stroke in the general population remains unclear. This study aimed to investigate the prospective association between SPISE and incident CMM and stroke in middle-aged and older Chinese adults. This prospective cohort study included 6,624 participants aged 45 years and older from the China Health and Retirement Longitudinal Study (CHARLS) with follow-up through 2020. SPISE was calculated using a validated formula. Cox proportional hazards regression models, restricted cubic spline analyses, Kaplan-Meier survival curves, and subgroup analyses were employed to evaluate the associations between SPISE and incident CMM and stroke. Over a median follow-up of 114 months, 632 participants (9.5%) developed incident stroke, and 696 (10.5%) developed CMM. In fully adjusted multivariable models, each one-unit increase in the baseline SPISE index was significantly associated with a 10% decreased risk of incident stroke (HR = 0.90, 95% CI: 0.86–0.94) and a 15% decreased risk of CMM (HR = 0.85, 95% CI: 0.81–0.89). Compared to the low SPISE reference group (< 6.61), individuals in the high SPISE category (≥ 6.61) exhibited a 27% lower risk of stroke (HR = 0.73, 95% CI: 0.62–0.88) and a 48% lower risk of CMM (HR = 0.52, 95% CI: 0.43–0.62). Restricted cubic spline analyses confirmed strictly linear, inverse dose-response relationships between SPISE and both outcomes. These protective associations remained structurally robust across diverse demographic and clinical subgroups, with significant effect modification identified solely for baseline heart disease and age concerning the CMM outcome. Higher SPISE is independently and linearly associated with reduced risks of incident CMM and stroke in middle-aged and older Chinese adults. As a simple, low-cost marker derived from routine clinical measurements, SPISE may serve as a practical tool for cardiometabolic risk stratification in primary care settings.
Cardiometabolic multimorbidity (CMM), the co-occurrence of at least two cardiometabolic diseases, poses a significant public health threat. The Cholesterol, High-density Lipoprotein, and Glucose (CHG) index is an emerging surrogate marker of insulin resistance, yet its association with CMM, particularly when integrated with obesity indices, remains unexplored.This prospective cohort study analyzed 6991 adults aged ≥ 45 years without baseline CMM from the China Health and Retirement Longitudinal Study (CHARLS). Multivariable Cox regression, Kaplan-Meier curves, and restricted cubic splines were used to assess associations between CHG-obesity composite indices and CMM risk. Predictive performance was evaluated using time-dependent receiver operating characteristic (ROC) analysis, Harrell's C-index, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). A Fine-Gray competing-risks model, subgroup analyses, and sensitivity analyses were also conducted. Over a median follow-up of 9 years, 677 participants developed CMM. Each 1-unit increase in CHG-related indices was significantly associated with elevated CMM risk, with fully adjusted HRs ranging from 1.01 to 1.86. The Fine-Gray competing risk model confirmed this robust association. CHG-WC and CHG-WHtR yielded the highest C-index (both 0.701). All CHG-related indices significantly improved risk reclassification and discrimination relative to conventional risk factors (all continuous NRI and IDI, p < 0.05). Hypertension significantly modified the association. Sensitivity analyses confirmed robustness. CHG-composite indices are significantly associated with increased CMM risk and show potential as practical tools for risk stratification in middle-aged and older adults.
PURPOSE
Type 2 diabetes (T2D) is associated with functional decline in older adults, but whether baseline physical function predicts its incidence remains unclear. This study examined whether the Short Physical Performance Battery (SPPB) predicts incident T2D in older Koreans, and whether resting heart rate (RHR) modifies this association.
METHODS
We included 1,041 community-dwelling adults aged ≥ 65 years (mean age = 72.2 years; 58.3% women) without T2D at baseline from the KoGES-Anseong cohort (2013-2020). SPPB scores were categorized as high (≥ 10) or low (< 10), and RHR was dichotomized at the median. Incident T2D was ascertained through fasting glucose, physician diagnosis, or diabetes medication. Cox proportional hazards models (adjusted for demographic, metabolic, and lifestyle factors) estimated hazard ratios (HRs) and 95% confidence intervals (CIs) over 5294 person-years of follow-up.
RESULTS
High SPPB scores were associated with a lower risk of T2D (HR = 0.49, 95% CI 0.25-0.94). This association was observed only in participants with elevated RHR (HR = 0.37, 95% CI 0.17-0.81), but not in those with lower RHR. Among individual SPPB domains, only lower-extremity strength showed a significant association with reduced T2D risk.
CONCLUSION
In older adults, superior physical function substantially reduces the risk of T2D, with lower-extremity strength as the primary contributor. Importantly, this benefit remains robust among individuals with elevated RHR, underscoring functional performance as a practical target for preventive strategies.
Soomin Lee, Dooyong Park, JinWon Rho et al.· European Geriatric Medicine· 0 citations
