The existence of Dibates mellitus in cases of Tuberculois patients. Findings in a Tribal population from Nikshay Data base

ABSTRACT

Introduction: For more than 75,000 years, tuberculosis (TB) has plagued humans over the planet. It is the greatest cause of infectious disease-related death worldwide, surpassing out HIV, though COVID-19 may overtake it. Approximately 1,200,000 individuals died as a direct result of this disease, and an additional 250,000 people who were HIV-positive died as a result of it, according to WHO estimates for 2018. Only eight nations, India (28%) China (9%) Indonesia (8%), Pakistan 6%, Nigeria 4% and Bangladesh 4%, account for two thirds of the world's TB infections, according to the World Health Organization (WHO) (3 percent) Needless to highlight India remains the top contributor for the disease. While Diabetes mellitus (DM) is one of the most common chronic disorders in our society. and incidentally India had been time and again given the name of Diabetic Capital of World. Interestingly animal models have been used to examine how hyperglycaemia affects the immunological response to M. tuberculosis, but a definite answer has not yet been established. Its widely accepted that DM is a risk factor for TB. Various published evidence point out that, if a person has both tuberculosis and diabetes, the risk of death increases. TB treatment results are negatively correlated with diabetes. Diabetes patients have a mortality risk ratio that is higher than that of the general population, even after correcting for age and other relevant confounders. Keeping in view of these facts and the paucity of published evidence when it comes to tribal hinterlands of Jharkhand we decided to do a cross sectional observation analysis of the Data avaialbel in Nikshay portal. Nikshay portal is Methods: District of Pakur in Jharkahnd was chosen as it is one of the districts sharing border with West Bengal, Bihar and Bangladesh is nearby.We used data from the adult population obtained from Nikshay portal for one year 2021, and divided into two subgroups. We conducted univariate analysis to find association of DM presence with different sociodemographic variables using chi square and unpaired t-test/Mann Whitney test for non -parametric data. Multivariable logistic regression models were used to predict the association of DM presence with epidemiological factors. Data was analysed using JASP software and p value <0.05 was considered statistically significant. Results: Out of 1687 registered TB patients we found 29 who were having Diabetes as co morbidity, Majority of them were male, while 19 of them were referred from private facility, three of them died and two were lost to follow up. Other predictors were found which increased the chances of having DM along with TB were middle age, and sex. Conclusions: As has been reported by others as well the problem of co infection of TB with DM is a reality and growing. The two programs are now being run under different heads which need to change. As seen most of the diabetics were from Private facilities meaning we might be missing more. More active case findings needs to be done so that no case of DM with TB is missed. Screening for DM among TB patients should be compulsory and treatment of co-morbidity should be included in adult health programmes. No conflict of interest