Cardiometabolic multimorbidity (co-existence of ≥1 cardiometabolic diseases) is increasingly common, while its prevalence in the U.S. is unknown. We utilized data from 10 National Health and Nutrition Examination Survey (NHANES) two-year cycles in U.S. adults from 1999 to 2018. We reported the age-standardized prevalence of cardiometabolic multimorbidity in 2017–2018 and analyzed their trends during 1999–2018 with joinpoint regression models. Stratified analyses were performed according to gender, age, and race/ethnicity. In 2017–2018, the prevalence of cardiometabolic multimorbidity was 14.4% in the U.S., and it was higher among male, older, and non-Hispanic Black people. The three most common patterns were hypertension and diabetes (7.5%); hypertension, diabetes, and CHD (2.2%); and hypertension and CHD (1.8%). During 1999–2018, the prevalence of cardiometabolic multimorbidity in U.S. adults increased significantly, with an averaged two-year cycle percentage change (AAPC) of 3.6 (95% CI: 2.1 to 5.3). The increasing trend was significant for both genders, most age groups except for 60–79 years, and non-Hispanic White people. For common patterns, the trend was increasing for hypertension and diabetes and hypertension, diabetes, and CHD, while it was decreasing for hypertension and CHD. Our findings provide evidence that cardiometabolic multimorbidity has risen as an austere issue of public health in the U.S.

Zonghai Yao, Aditya Parashar, Huixue Zhou, Won Seok Jang, Feiyun Ouyang, Zhichao Yang, Hong Yu. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2025.

Background: Evidence indicates that certain healthy lifestyle factors are associated with non-alcoholic fatty liver disease (NAFLD). However, little is known about the effect of combined healthy lifestyle factors. Objective: To assess the association of combined healthy lifestyle factors with the incidence of NAFLD. Methods: This cohort study was conducted in Changsha, Hunan Province, China. The healthy lifestyles factors studied were not being a current smoker, having a healthy diet, engaging in physical activity, having a normal body mass index (BMI) and engaging in non-sedentary behavior. NAFLD was diagnosed based on abdominal ultrasonography. Logistic regression models were conducted to investigate the associations being studied. Results: Of the 5411 participants, 1280 participants had NAFLD, with a prevalence of 23.7% at baseline. The incidence of NAFLD among participants without NAFLD at baseline was found to be 7.2% over a mean follow-up of 1.1 years. Compared with participants with 0–1 low-risk factors, the OR of NAFLD was 0.50 (95% CI: 0.29–0.82, p = 0.008) for those with at least 4 low-risk factors. Similar associations were observed in subgroup analyses and sensitivity analyses. Conclusion: This study suggests that a combined healthy lifestyle pattern may considerably decrease the risk of NAFLD in Chinese government employees.

Large language models have shown success as a tutor in education in various fields. Educating patients about their clinical visits plays a pivotal role in patients' adherence to their treatment plans post-discharge. This paper presents EHRTutor, an innovative multi-component framework leveraging the Large Language Model (LLM) for patient education through conversational question-answering. EHRTutor first formulates questions pertaining to the electronic health record discharge instructions. It then educates the patient through conversation by administering each question as a test. Finally, it generates a summary at the end of the conversation. Evaluation results using LLMs and domain experts have shown a clear preference for EHRTutor over the baseline. Moreover, EHRTutor also offers a framework for generating synthetic patient education dialogues that can be used for future in-house system training.