Transition-period Metabolic Disorders in Bovines: Pathophysiology, Diagnosis and Integrated Management Strategies

Abstract

This review synthesized current knowledge on major conditions including fatty liver, ketosis, milk fever, and hypomagnesaemia, with emphasis on their underlying mechanisms, risk factors, and management strategies. Metabolic diseases were recognized as major constraints to productivity, health, and welfare in dairy cattle, particularly during the transition period. These disorders primarily arised from negative energy balance and mineral imbalances associated with physiological, nutritional, and environmental stress. The pathophysiology of these disorders involved complex interactions among metabolic, endocrine, and immune systems, which resulted in reduced milk production, impaired fertility, and increased susceptibility to infectious and metabolic diseases. Subclinical forms were found to be more prevalent than clinical cases and contributed substantially to economic losses due to their often undetected nature and long-term effects on performance. Advances in diagnostic approaches, including metabolic profiling and precision livestock farming technologies, improved early detection, monitoring, and decision-making at the herd level. Biomarkers such as non-esterified fatty acids, β-hydroxybutyrate, calcium, and magnesium were widely used for identifying both subclinical and clinical conditions and for assessing metabolic status. Nutritional strategies, including controlled-energy diets, dietary cation–anion difference manipulation, and targeted supplementation of minerals and vitamins, were identified as key preventive measures. Integrated herd-level management approaches that combined nutrition, health monitoring, housing, and environmental management were shown to be essential for mitigating disease risk and improving overall herd performance. Overall, improving metabolic health was considered critical for enhancing productivity, animal welfare, and sustainability in modern dairy production systems.