Digital Lifestyles, Predictive Analytics, and Health Outcomes: Exploring the Intersection of Technology Use, Artificial Intelligence, and Multimorbidity in Shaping Public Health in Bangladesh

Bangladesh is undergoing a rapid digital transformation, which is reshaping patterns of daily life and influencing health trajectories across the lifespan. This article integrates insights from three distinct yet interconnected domains to present a comprehensive perspective on the intersection of technology, predictive analytics, and public health. First, evidence from a cross-sectional investigation in Dhaka highlights the prevalence, determinants, and consequences of problematic smartphone use among preschool-aged children (3-5 years). The findings suggest that socioeconomic factors, parenting practices, and urban lifestyles contribute to early and excessive digital exposure, with potential negative implications for cognitive development, behavioral regulation, and long-term health risks such as sedentary lifestyles and digital dependence. Second, advancements in artificial intelligence (AI) provide powerful tools for predictive healthcare, particularly in oncology. Recent studies demonstrate that AI-based models can accurately forecast cancer recurrence and patient survival rates, thereby supporting clinicians in tailoring personalized interventions and improving clinical decision-making. Third, lessons from the COVID-19 pandemic underscore the critical role of multimorbidity and diagnostic biomarkers in shaping patient outcomes, particularly in intensive care units where diabetic patients faced disproportionately high mortality rates. By synthesizing these strands, this article argues for the development of an integrated digital health framework in Bangladesh that addresses the dual challenges of lifestyledriven risks and clinical disease management. Such a framework would prioritize early intervention in digital health behaviors, invest in AI-driven predictive analytics for chronic and acute conditions, and strengthen the integration of diagnostic biomarkers into real-world clinical practice.