Nipah virus (NiV) is a highly lethal zoonotic pathogen. Its re-emergence in India in early 2026 has heightened global public health concerns. This study systematically assessed the risk of NiV importation into China from five affected countries. India and Bangladesh posed moderate importation risks, whereas Malaysia, the Philippines, and Singapore presented low risks. The findings emphasize that coupling existing defenses with sustained multi-source surveillance and dynamic risk modeling is essential to mitigate risks of stochastic NiV entry.

Hyperuricemia (HUA) has become a global health issue due to its rapidly increasing prevalence. Growing evidence from population and animal studies suggests

Overweight-related hypertension (OrH), defined by the coexistence of excess body weight and hypertension (HTN), is an increasing health concern elevating cardiovascular disease risks. This study evaluates the prediction performance of polygenic risk scores (PRS) and methylation risk scores (MRS) for OrH in 7,605 Chinese participants from two cohorts: the Chinese Academy of Sciences (CAS) and the National Survey of Physical Traits (NSPT). In CAS cohort, which predominantly consists of academics, males showed significantly higher prevalence of obesity, hypertension (HTN), and OrH, along with worse metabolic syndrome indicators, compared to females. This disparity was less pronounced in NSPT cohort and in broader Chinese studies. Among ten PRS methods, PRScsx was the most effective, enhancing prediction accuracy for obesity (AUC = 0.75), HTN (AUC = 0.74), and OrH (AUC = 0.75), compared to baseline models using only age and sex (AUC = 0.55–0.71). Similarly, Lasso-based MRS models improved prediction accuracies for obesity (AUC = 0.70), HTN (AUC = 0.73), and OrH (AUC = 0.78). Combining PRS and MRS further boosted prediction accuracy to the AUC of 0.77, 0.76, and 0.80, respectively. These models stratified individuals into high (> 0.6) or low (< 0.1) risk categories, covering 59.95% for obesity, 31.75% for HTN, and 43.89% for OrH, respectively. Our findings highlight a higher OrH risk among male academics, emphasize the influence of metabolic and lifestyle factors on MRS predictions, and highlight the value of multi-omics approaches in enhancing risk stratification. Highlights: Polygenic risk scores and methylation risk scores were systematically evaluated in predicting the risk of obesity, hypertension, and overweight related hypertension in Chinese participants. PRScsx demonstrated robust accuracy in PRS profiling, while Lasso-based MRS showed superior performance in MRS profiling. Moreover, integrating multi-omics analyses further improved disease risk profiling for these conditions, highlighting their potential for personalized care and prevention strategies. Gender disparity in the prevalence of metabolism-related disorders largely changed in recent three decades in China. Male to female prevalence ratio for obesity, hypertension, and overweight related hypertension reached striking high as 3.8, 2.9 and 4.7 among academics. These differences are likely influenced by the complex interplay among epigenetic factors, lifestyle and metabolic health.