To investigate the prevalence and influencing factors of cardiometabolic multimorbidity (CMM) among middle-aged and elderly populations in Xizang, and to develop a nomogram prediction model for assessing CMM risk, thereby providing evidence-based references for disease prevention and control strategies.

Utilizing data from the Xizang survey site of the Southwest China Natural Population Cohort Study, a total of 3 012 participants were included for statistical analysis. Chi-square tests and multivariate logistic regression were employed to identify determinants of CMM, followed by construction of a nomogram prediction model. The model’s performance was validated through Hosmer-Lemeshow goodness-of-fit testing and calibration curve analysis.

Among 3 012 participants, the prevalence of cardiometabolic multimorbidity (CMM) was 25.1%. Multivariable logistic regression analysis identified the following independent risk factors: advanced age (≥65 years: OR=2.484, 95%CI：1.967-3.138), male gender (OR=1.636, 95%CI：1.363-1.963), nocturnal sleep duration <7 hours (OR=1.527, 95%CI：1.101-2.118), frequent snoring (OR=1.392, 95%CI：1.095-1.769), poor self-rated health (OR=2.141, 95%CI：1.606-2.853), BMI ≥28 kg/m² (OR=1.993, 95%CI：1.498-2.651), and central obesity (OR=1.674, 95%CI: 1.345-2.083). The model demonstrated satisfactory goodness-of-fit (Hosmer-Lemeshow χ²=2.430, P=0.965) with calibration curve analysis showing excellent agreement between predicted and observed probabilities.

Preventive strategies should prioritize middle-aged and elderly individuals with the identified risk profiles: advanced age (≥65 years), male gender, nocturnal sleep deprivation (<7 hours), frequent snoring, suboptimal self-rated health, overweight/obesity, and central obesity. The nomogram model developed based on these influencing factors demonstrates certain predictive value for assessing CMM risk in middle-aged and elderly populations in Xizang.