Self-reported health as a predictor of cardiometabolic multimorbidity in Chinese older adults: a national cross-sectional study.

Abstract

While self-reported health (SRH) robustly predicts clinical outcomes, its quantitative association with cardiometabolic multimorbidity (CMM) remains insufficiently characterized, particularly within low- and middle-income countries (LMICs). We aimed to quantify the dose-response relationship between SRH and CMM prevalence among older adults in China and to identify key sociodemographic effect modifiers. Utilizing cross-sectional data from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS), we analyzed 9,762 participants aged ≥65 years (mean age 83.2 ± 11.3). SRH was categorized as good, neutral, or bad. CMM was defined as the presence of ≥2 conditions among coronary heart disease, stroke, diabetes, hypertension, or dyslipidemia. Multivariable-adjusted logistic regression assessed the SRH-CMM association. Stratified analyses evaluated effect modification by sex, age group, and residence (city/town/rural). Declining SRH demonstrated a graded association with increased CMM prevalence. Compared to "good" SRH, "bad" SRH was associated with a four-fold elevated CMM risk [adjusted odds ratio (aOR) = 3.992, 95% confidence interval (CI): 3.425-4.652], while "neutral" SRH conferred a two-fold risk elevation (aOR = 2.063, 95% CI: 1.835-2.320). Each one-level deterioration in SRH was associated with more than a doubling of the odds (aOR = 2.009, p < 0.001). The association was significantly stronger in males (aOR for bad vs. good = 4.441) than in females (aOR = 3.727), peaked among individuals aged 65-74 years (aOR = 4.785), and attenuated in centenarians (aOR = 3.441). City residents exhibited the highest risk elevation (aOR = 5.326, 95% CI: 3.961-7.163) compared to their rural counterparts (aOR = 3.662, 95% CI: 2.851-4.704; P-interaction = 0.006). SRH exhibits a strong, independent dose-dependent association with CMM burden in older adults, capturing cumulative biological aging beyond traditional biomarkers. Integrating SRH into clinical risk stratification may optimize preventive interventions for high-risk subgroups, particularly older city males and individuals reporting health deterioration.