Study on South Asian Diabetic Subjects on Different Attributes: A Statistical Approach

Abstract

Diabetes is a serious problem in today's world. Stress TTH (tension type headache) is another epidemic which is growing with a very fast pace. Diabetes is a disease of the body that prevents the metabolism of blood sugar (glucose). This increases the blood glucose to a risky level. The present study aims to analyze diabetes with the latest IoT and big data analysis techniques and its correlation with stress (TTH) on human health. Authors have tried to include age, gender, and insulin factor and its correlation with diabetes. IoT helps us to connect each other, that is, it is known a smart connecting thing (a sort of “universal global neural network” in cloud). It comprises of smart connecting machine with other machine, object, and a lot more. Big data refers to huge sets of data that are also large enough in terms of variety and velocity. Due to this, it becomes more difficult to handle, organise, store, process, and manipulate such data using traditional techniques of storage and processing. Stress especially TTH (tension type headache) is a serious problem in today's world. Now every person in this world is facing headache and stress-related problems in daily life. The authors have collected this big data and studied the people; they have studied their tension level and helped them to cure it. In this chapter, they analyze the correlation between diabetes and stressors. For the analysis, they collected sample of 30 subjects from hospitals of Delhi in random fashion who have been suffering from diabetes from their health insurance providers without disclosing any personal information (PI) or sensitive personal information (SPI) by law. To identify each case sample IDs like S1, S2, etc. has been allotted to the subjects. Sample data has been collected for following parameters: gender, age, diabetes type, insulin dependency, obesity status, CAD status, and CAN status. They have used the Tableau s/w for this analysis. Overall, an interesting observation during the research was that none of the female subjects having diabetes is below 25 years, that is, early age diabetes cases are less comparative to males subjected to the case sampling should not be impacted for age group gender biasing.