The rate of diabetics in India is the second highest in the world, and the widespread of the disease is a growing public health concern. With an aim to raise awareness and educate the community on diabetes and the importance of regular screening, Neuberg Anand Reference Laboratory, one of the top 4 Pathology laboratory chains in India organized a walk-a-thon today.
The event was flagged off at Suvarna Bhavana via Yelahanka and routed back to Suvarna Bhavan saw participants including medical practitioners, common people who spread the message and created awareness on non communicable diseases through placards and hoardings. A talk on Diabetes Lifestyle management by Dr. Nidhi R, Consultant, Neuberg Anand Reference Laboratory was also organized for the participant as a part of awareness and education on diabetes.
COVID 19 has been affecting us in ways we could never imagine. Even after the pandemic is theoretically gone, its effects can still be seen. And, when coupled with another (silent) killer i.e. “Diabetes”, the results are all the more astonishing. Recent findings by the Department of Data Science, Neuberg Anand Reference Laboratory reveal a striking spike in the number of cases of pre-diabetes and diabetes, as compared to the pre-COVID era. Dr. Sujay Prasad, Medical Director, Neuberg Diagnostics said, “There was a rise in the number of diabetics with about 5% increase. Even prediabetes cases increased by 10%. Also, the onset of diabetes increased by 3% in the 21-40 age group and by 7% in the 41-60 age group. A whopping 15% rise in the onset of prediabetes was seen in the age group between 21-40 and 10% in the 41-60 age groups. Gender wise there was no particular inclination observed in the cases. This spike in cases may be due to a combination of factors such as lack of physical activity during the lockdown period, mental stress, COVID-19 illness, and subsequent hospitalisation, etc.”
Department of Data Science at Neuberg Anand Reference Laboratory was set up in 2015. Neuberg Anand is very few labs in the country to have a dedicated department of data science to make sense of laboratory data.