Identifying Risk Factors and Predicting Incident NAFLD in a Chinese Cohort: A Retrospective Cohort Study and Nomogram Development
Jie Wei, Nan Wang, Qiongqiong Wang, Junjun Liu, Meihong Cai, Liangjun Zhang, Yue Han, Jingjing Guo, Shanliang ZhongBackground
Nonalcoholic fatty liver disease (NAFLD) poses a significant challenge to global health as one of the most common chronic liver conditions. The early identification of high‐risk individuals, however, remains difficult. Therefore, this study was conducted to investigate principal risk factors and to construct a predictive nomogram for the onset of NAFLD within a Chinese population.
Methods
We conducted a retrospective cohort study using health examination data from 10,440 individuals at Nanjing Meishan Hospital (2020–2024). Following exclusions, a final cohort of 1380 participants without baseline NAFLD was identified. Demographic, clinical, and laboratory data were subsequently collected. We employed Cox proportional hazards regression models to determine the independent risk factors. A nomogram was constructed using significant predictors to estimate the 1‐, 2‐ and 3‐year risk of NAFLD, and its discrimination was internally validated by repeated 10‐fold cross‐validation.
Results
Among the participants, 39.23% of males and 20.49% of females developed NAFLD. Multivariable analysis identified male gender (HR = 0.48, p < 0.001), BMI > 25 kg/m 2 (HR = 3.11, p < 0.001), elevated triglycerides (TG, HR = 1.28, p = 0.030), low high‐density lipoprotein cholesterol (HDL‐C, HR = 0.69, p = 0.019), elevated uric acid (UA, HR = 1.57, p < 0.001), and high triglyceride‐glucose index (TyG, HR = 1.64, p < 0.001) as independent predictors. Dose–response analyses revealed nonlinear relationships for BMI, TG, and TyG. Occupational exposures showed no significant association with NAFLD. The nomogram showed good discrimination (C‐index 0.73) and calibration, with a mean C‐index of 0.73 across 100 repetitions of 10‐fold cross‐validation.
Conclusion
This study confirms that male gender, obesity, elevated TG, low HDL‐C, hyperuricemia, and high TyG index are significant independent risk factors for NAFLD. The nomogram developed herein offers a practical approach to estimating individualized NAFLD risk, thereby supporting early targeted intervention in high‐risk populations.