Obesity Related Mortality in the Next Generation: Projections Based on Machine Learning for Young Americans (1999–2035)

ABSTRACT Introduction Obesity is a growing public health crisis, particularly among young adults. This study projected obesity related mortality rates in the United States, providing an outlook on future trends. Methods Data were obtained from the CDC Wide‐ranging Online Data for Epidemiologic Research (CDC WONDER) multiple causes of death database, focusing on the underlying cause of death as obesity (ICD‐10 codes E66.0‐E66.9) for young adults aged 18–39. Temporal trends in crude mortality rate (CMR) were assessed using Joinpoint software. Future mortality rates were forecasted using an optimal Autoregressive Integrated Moving Average (ARIMA) model. Results Between 1999 and 2023, there were 19,451 deaths with obesity as the underlying cause of death (males 60.58%) in young adults aged 18–39. Overall, the CMR showed an annual percent change (APC) of 3.13% (95% CI 2.45%–3.85%) for 1999–2023. The forecasted APC for 2024–2035 was 1.30% (95% CI 0.35%–2.31%). For females, CMR increased from 0.4/100,000 in 1999 to 0.8/100,000 in 2023, showing an APC of 2.44% (95% CI 1.71%–3.18%) with a forecasted APC of 2.81% (95% CI 2.74%–2.87%). For males, CMR increased from 0.6/100,000 in 1999 to 1.4/100,000 in 2023, showing an APC of 3.59% (95% CI 2.78%–4.42%) with a forecasted APC of 3.16% (95% CI 3.12%–3.20%). Conclusion This study demonstrated the efficacy of machine learning in projecting public health trends, providing critical insights into the future burden of obesity‐related mortality among young adults in the United States.