Author(s) :

Jihun Jung.

Volume/Issue :

Abstract :

Hypertension risk is an important concern in the area of public health since increased blood pressure elevates the risk of cardiovascular disease, stroke, and other long-term complications. However, it is often under-recognized in young adults. In this study, a simulation-based quantitative modeling approach was taken to examine predictors of hypertension among young adults in the United States. A total of 2,000 individuals aged from 18 to 39 were generated by simulation grounded by prior literature to reflect plausible demographic, behavioral, anthropometric, and metabolic patterns reported in prior epidemiological research in the United States. Variables included age, sex, race/ethnicity, body mass index (BMI), smoking status, alcohol use, physical activity, fasting glucose, total cholesterol, and hypertension status. The simulated sample was summarized by descriptive statistics, and binary logistic regression was used to estimate the independent correlations between aforementioned predictors and hypertension. Hypertension prevalence in the simulated sample was reported to be around 11.5%. Higher age within the young adult range, higher BMI, smoking, increased glucose, male sex, and Black race were positively correlated with greater odds of hypertension. Physical activity indicated a statistically significant protective association with hypertension odds, with participants meeting guidelines for physical activity having lower modeled odds of hypertension. Among the modeled predictors, BMI was reported to be the strongest correlations with hypertension risk. The model indicated acceptable discriminatory performance, and the area under the receiver operating characteristic curve was around 0.77. Overall, the findings in this study suggest that hypertension risk in young adults is shaped by multiple demographic, behavioral, and metabolic factors, emphasizing the value of simulation-based modeling in public health research.