In recent years, metabolic diseases represented by diabetes, hypertension, obesity, dyslipidemia, non-alcoholic fatty liver disease, and hyperuricemia are common and frequently occurring diseases in the world, which have become one of the major social and public issues of the world. A large amount of research confirmed that active health management, including physical activity, physical fitness, and nutritional interventions are associated with health benefits in individuals with metabolic diseases of all ages. Therefore, it is of great importance to establish and implement an effective and popularized health management model of metabolic diseases, which are difficult research hotspots.

Computational intelligence and artificial intelligence (AI) have a remarkable role in the development of smart healthcare systems by integrating smart technologies (preferably wearable devices) into conventional medicine, including the diagnosis, monitoring, and intervention of illness. These web-based intervention technologies have brought new models for the diagnosis, treatment, and health management of metabolic diseases and have produced promising results.

In this Special Issue, we are looking for papers that will bring an innovative and integrated vision on interventions for metabolic disease in adults and provide state-of-the-art knowledge on those topics. We welcome innovative, simple, and feasible health intervention technologies and management models (active learning, active monitoring, active interventions technology, health promotion, or an integrated program incorporating web-based interventions) to improve active health literacy, physical activity, healthy lifestyle, and the management of metabolic diseases in adults. We welcome original research and review articles.

Potential topics include but are not limited to the following:

• Active health management innovative model for metabolic disease in adults
• Community-based programs for the promotion of physical activity in adults
• Nutritional intervention for metabolic disease in adults
• Web-based interventions for metabolic disease in adults
• The mediators that contribute to the intervention effect
• Health-related outcomes of active health management and web-based interventions for metabolic disease in adults
• Metabolic disease-related monitoring technology with e-health and m-health
• Computational intelligence and artificial intelligence (AI) in metabolic disease
• Patient with metabolic disease diagnostics via e-health and m-health solutions
• Health system solutions using Internet of Medical Things (IoMT)