ABSTRACT
OBJECTIVES: We verified subnational (state/union territory (UT)/district) claims of achievements in reducing tuberculosis (TB) incidence in 2020 compared with 2015, in India. DESIGN: A community-based survey, analysis of programme data and anti-TB drug sales and utilisation data. SETTING: National TB Elimination Program and private TB treatment settings in 73 districts that had filed a claim to the Central TB Division of India for progress towards TB-free status. PARTICIPANTS: Each district was divided into survey units (SU) and one village/ward was randomly selected from each SU. All household members in the selected village were interviewed. Sputum from participants with a history of anti-TB therapy (ATT), those currently experiencing chest symptoms or on ATT were tested using Xpert/Rif/TrueNat. The survey continued until 30 Mycobacterium tuberculosis cases were identified in a district. OUTCOME MEASURES: We calculated a direct estimate of TB incidence based on incident cases identified in the survey. We calculated an under-reporting factor by matching these cases within the TB notification system. The TB notification adjusted for this factor was the estimate by the indirect method. We also calculated TB incidence from drug sale data in the private sector and drug utilisation data in the public sector. We compared the three estimates of TB incidence in 2020 with TB incidence in 2015. RESULTS: The estimated direct incidence ranged from 19 (Purba Medinipur, West Bengal) to 1457 (Jaintia Hills, Meghalaya) per 100 000 population. Indirect estimates of incidence ranged between 19 (Diu, Dadra and Nagar Haveli) and 788 (Dumka, Jharkhand) per 100 000 population. The incidence using drug sale data ranged from 19 per 100 000 population in Diu, Dadra and Nagar Haveli to 651 per 100 000 population in Centenary, Maharashtra. CONCLUSION: TB incidence in 1 state, 2 UTs and 35 districts had declined by at least 20% since 2015. Two districts in India were declared TB free in 2020.
Subject(s)
Epidemiological Monitoring , Tuberculosis , Disease Eradication , Humans , Incidence , India/epidemiology , Mycobacterium tuberculosis/isolation & purification , Tuberculosis/diagnosis , Tuberculosis/epidemiology , Tuberculosis/prevention & controlABSTRACT
Background: High levels of cholesterol in the body can be alarming and point toward a possible cardiac or diabetic problem. Current evidence reveals that the harmful low-density lipoproteins (LDL) cholesterol tend to increase in poorly controlled diabetes, whereas the useful high-density lipoprotein (HDL) cholesterol, known for its protective anti-inflammatory and antioxidant activities, is decreased. With a positive evidence of periodontal disease being implicated in diabetes, it was decided to investigate whether there was any association between serum HDL, LDL, glycated hemoglobin (HbA1c) and periodontal status with Type II diabetes mellitus patients. Materials and Methods: A total of 500 nonsmoking patients (males and females) aged between 35 and 55 years with Type 2 diabetes mellitus and no other systemic disease were selected from the diabetic center, Diacon hospital, Bengaluru, Karnataka, India. Periodontal examination consisted of the clinical parameters, namely, attachment loss, gingival index (GI) and plaque index based on which the patients were divided into periodontally healthy and diseased groups. Blood samples were collected from each patient to evaluate the serum levels of HDL, LDL and HbA1c. Results: No significant differences were observed between the HDL, LDL and HbA1c levels in both the periodontal groups (P > 0.05). Linear regression analysis showed significant positive correlations of clinical attachment level with LDL and negative correlation with HbA1c, whereas GI has a positive correlation with LDL and negatively with HDL and Hba1c levels (P < 0.05). Conclusion: Varied associations were found between dyslipidemia, glycemic control and periodontal inflammation. Further longitudinal as well as interventional studies may be beneficial to ascertain the causal relationship between cholesterol levels, periodontal status and diabetes mellitus.
