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Introduction Physical exercise deters the risk and reduce the adjusted Odds Ratio related to obesity and cardiometabolic diseases but the amount of physical exercise required for initiating those potential advantageous developments in the human body for normal obese individuals is still debatable and thus made many face the health burden during pandemic, despite of their claiming to be physically active. Objective The primary aim of this review was to find an ideal duration and form of exercise that could help reduce the risk of cardiometabolic diseases and its complications for subjects with obesity and deranged cardiometabolic risk markers. Method Electronic database PubMed/MedLine, Scopus and PEDro for available literature on Experimental studies and RCT on exercise prescription and its effect on anthropometric measurements as well as key biomarkers in obese individuals, 451 records were procured, 47 full text articles were identified to assess eligibility criteria out of which 19 were finally included in the review. Results There exists a strong association between cardiometabolic profile and physical activity, poor diet, sedentary lifestyle and continuous exercises for longer duration can lead to reduction in obesity and subjects with cardiometabolic diseases. Conclusion Various confounding factors that may affect the outcome of physical activity training have not been considered in a standard format by all the authors in the articles reviewed. There was variation in duration of physical activity and energy expenditure required for inducing the changes in different cardiometabolic biomarkers.

Agriculture production all over the world is directly influenced by rainfall which is an important weather parameter. The changes in rainfall can cause the failure of crops and even lead to starvation and ruin the economy of a country. The economy of a country becomes inferior due to catastrophic circumstances like floods, drought, and landslides. Thus the prediction of future values with the highest accuracy is very crucial to regulate and avoiding the undesirable influences of instabilities in rainfall. Under current research work, SARIMA, ANN, and hybrid SARIMA-ANN models are applied to identify the future pattern and for availing essential proposals for scheduling agriculture procedures such that variations in rainfall may not affect the economy. The data of monthly rainfall was collected from RARS, Pilicode for the northern zone, RARS, Pattambi for the central zone, and RARS, Vellayani for the southern zone. The results revealed that ANN model predicted future values of rainfall with the highest precision for the northern and central zone, whereas for the southern zone, SARIMA (1,0,1) (2,0,0)12 gave anticipated values with more accuracy. The comparison of projected rainfall among different zones indicated that the northern part might receive the highest amount of rainfall, the central zone indicated moderate rainfall, and the southern part of Kerala with the least amount of rainfall. The study also recommended the farmers take necessary safeguards to regulate the adverse influences of fluctuations in rainfall such that it might not affect agricultural production and the economy of the country.