---
title: "Self-reported tuberculosis prevalence and vulnerability factors in six rural Indian districts"
id: "plos-one-16-self-reported-prevalence-of-tuberculosis-and-selected-associated-vulnerability"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-16-self-reported-prevalence-of-tuberculosis-and-selected-associated-vulnerability"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0360758"
published_at: "2026-10-16T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Self-reported tuberculosis prevalence and vulnerability factors in six rural Indian districts
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-16-self-reported-prevalence-of-tuberculosis-and-selected-associated-vulnerability
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0360758)
- **Published At:** 2026-10-16T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- Investigators conducted a community-based cross-sectional survey in six districts (Bhopal, Jaipur, Lucknow, Patna, Pune, Ratlam) using universal household sampling in randomly selected villages. - The final analytical dataset included 82,636 individuals from 12,736 households after data cleaning; males comprised 52% and 77% were aged ≥15 years. - Self-reported **tuberculosis** prevalence (defined as currently receiving ATT plus completed ATT within 2 years) was 0.15% (about 150 per lakh). - Reported prevalence of selected vulnerability factors: **HIV** reactivity 0.9%; current smokers 5%; self-reported **silicosis** 1.2%; occupational silica exposure ~1.1% ( 2 weeks 4%. - Crude stratified results showed higher TB prevalence in exposed subgroups: past smokers and current smokers, mine and construction workers with silica exposure, and **HIV**-reactive individuals; exact subgroup counts were small. - Investigators did not confirm TB with microbiological testing; TB status was self-reported (current ATT or treatment completed within 2 years). - No clustering adjustment was applied; authors argued sampling steps produced independent observations and universal sampling of households negated need for design-adjustment. - Study authors characterized subgroup estimates as exploratory because of small absolute event counts and wide confidence intervals in silicosis, silica-exposure, and **HIV** strata. - The dataset and findings are presented as grassroots evidence to help target active case finding under the National Tuberculosis Elimination Programme (NTEP) in high-burden rural settings. - Ethical approval was obtained from ICMR-NIIRNCD institute ethics committee; funding was provided by ICMR with no role in design or analysis.
## Clinical Analysis & Structured Key Points
Self-reported prevalence of tuberculosis and selected associated vulnerability factors among rural populations in six districts of India: A community-based cross-sectional study | PLOS One Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Article Authors Metrics Comments Media Coverage Peer Review Reader Comments Figures Figures Abstract Background Tuberculosis is a major public health challenge in India, contributing to one-fourth of global burden of TB disease. Comorbidities in uninfected individuals make them vulnerable to TB disease. This study estimates the self-reported prevalence of tuberculosis and selected vulnerability factors (HIV, current smoking, silicosis, occupational silica-dust exposure, diabetes mellitus and persistent cough >2 weeks) among the rural demography of six districts in India, with the aim of informing targeted active case finding under the National Tuberculosis Elimination Programme (NTEP). Methods The study conducted was a community-based cross-sectional survey carried out across six districts of India. Two blocks from each district was selected randomly followed by randomly selected villages under each block. A universal sampling technique was followed for including all the households of the randomly selected villages. The data were collected through a pre-tested semi-structured questionnaire schedule via face-to-face interviews at all the eligible households of the study sites. Descriptive analysis was performed, and the results were obtained in the form of frequencies and percentages. Results The ultimate data consisted of 82,636 individuals, with males at 52% and females at 47%. 77% of the study population were 15 years of age or older. This study analyzes a large dataset. The TB prevalence was around 150 per lakh of the population, while the prevalence of HIV-reactive individuals, current smokers, silicosis, occupational exposure to silica dust, diabetes mellitus and cough of greater than two weeks is found in 0.9%, 5%, 1.2%, 1.1%, 1.4% and 4% respectively. Discussion and conclusion The study highlights TB status and selected TB-vulnerable groups. The study has a large sample size, and it follows multipronged approach to study selected vulnerable population groups. This data may improve targeted active case finding among the high-risk groups as outlined by NTEP and provide better TB control strategy outcome at high TB burden settings. Citation: Anand PK, Singh M, Banerjee P, Sahay S, Bangar S, Ghosh BR, et al. (2026) Self-reported prevalence of tuberculosis and selected associated vulnerability factors among rural populations in six districts of India: A community-based cross-sectional study. PLoS One 21(10): e0360758. https://doi.org/10.1371/journal.pone.0360758 Editor: Yasir Alvi, National Institute of Tuberculosis and Respiratory Diseases, INDIA Received: June 8, 2026; Accepted: September 29, 2026; Published: October 16, 2026 Copyright: © 2026 Anand et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: Data is disclosed in the manuscript itself. Funding: This study was funded by the Indian Council of Medical Research (ICMR) vide File No. 5/8/5/44/ITRC/Implementation/2021/ECD-I. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Introduction TB is the 10 th leading cause of death worldwide and 2 nd leading cause of death from a single infectious agent worldwide after COVID-19 [ 1 ]. According to the Global TB Report 2025, India accounts for 25% of the Global TB Burden which is the highest in the world [ 1 ]. Tuberculosis is directly linked with the social determinants of health. As stated by the India TB Report 2024, TB is highly influenced by socio-economic development as well as health risk factors like HIV status, smoking habits, silicosis, occupational exposure to silica dust, diabetes mellitus and symptoms like persistent cough of more than 2 weeks. In order to better manage the TB epidemic, it is essential to focus on the underlying vulnerabilities among the demographic that is driving the disease transmission. WHO identifies key vulnerable populations as those with increased risk of TB exposure due to their living conditions, such as prisoners and migrants, individuals with weakened immune systems, and those with chronic illnesses. They face barriers to accessing healthcare services and may have poor health-seeking behaviour, which makes early identification and active case finding essential to ensure timely and effective TB care [ 3 ]. Tuberculosis is known to affect people with certain comorbidities disproportionately. Individuals who are suffering from Diabetes, People living with HIV (PLHIV), individuals with silicosis, construction site or mine workers having occupational exposure to silica dust as well as chronic smokers are included in this group [ 2 ]. The comorbidities may impact TB infection individually or overlap one another to create a much more complicated scenario. Like Diabetes is one of the risk factors of TB, known to downregulate immunity that put diabetics at a three-fold increased risk of developing active TB in comparison to non-diabetics [ 4 ]. Moreover Diabetics show complicated TB treatment outcomes as per the India TB Report 2024. The mindful focus on diagnosing, detecting and treating DM may have a beneficial impact on the control of the TB epidemic [ 4 ]. HIV another risk factor causes immunosuppression leading to twenty times at higher risk of developing TB in comparison to general population as per the India TB Report 2024. HIV is known to be responsible for 1,50,000 deaths due to TB worlwide [ 1 ]. Literature also states that silicosis and silica dust exposure is associated with increased risk of tuberculosis [ 5 ]. Then again Smoking has been established as an independent risk factor, with suppressive effects of smoke inhalation on the alveolar macrophage function as well as antibiotic resistance [ 2 ]. In India, TB is intertwined with socio-economic vulnerabilities and comorbidities, including diabetes, silicosis, occupational exposure to silica dust, smoking, and cough persisting for more than 2 weeks among other factors, which disproportionately affect marginalized and rural populations due to limited healthcare access, stigma, and delayed diagnosis. The incidence of DM is reported to be 9.6% and expected to rise to 10.9% by 2045 [ 6 ]. While a study showed 12.3% of the sandstone mine workers had radiograph indicating silicosis [ 7 ]. Though the exact proportion of the population employed by the industry of stone-mines, stone quarry or the construction sites is not known. Data on smoking showed 15.6% prevalence in India with bidi smoking being the commonest form of smoking specifically in rural areas [ 8 ]. Cough on the other hand is the cornerstone of TB diagnosis, persistent cough of over 2 weeks have higher sensitivity and lower specificity as per a TB diagnostic tool [ 9 ] while if unnoticed results in higher disease transmission rate [ 10 ]. These drivers elevate infection risk, worsen outcomes, and fuel drug resistance, challenging the National TB Elimination Programme’s aim to eliminate TB [ 5 ]. Thus ground level research is required to counter these social and high risk factors that drive the Indian TB epidemic. Moreover a study also stresses upon enhanced focus on research in India to better understand the conditions which are interlinked in order to launch effective prevention and management strategies [ 11 ]. Thus estimating the prevalence of these populations in a specific geographic backdrop can help us map TB propensity of a particular site and take specific measures in advance with respect to the TB preventive measures or bridge the gaps present in current NTEP implementation. This study was undertaken to estimate the prevalence of TB vulnerable population in Northern India. Objectives: To estimate the self-reported prevalence of tuberculosis and of selected factors that increase vulnerability to TB (HIV infection, current smoking, silicosis, occupational exposure to silica dust, diabetes mellitus and cough lasting more than two weeks) in the rural population of the six study districts. To describe the socio-demographic characteristics (age, gender, occupation and community group) of the study population. To examine the distribution of the selected vulnerability factors across socio-demographic strata. To produce grassroots-level evidence for strengthening targeted TB prevention and screening strategies among high-risk groups. Methodology Study design and setting The study was a community-based cross-sectional study, conducted in six districts of India namely: Bhopal (Madhya Pradesh), Jaipur (Rajasthan), Lucknow (Uttar Pradesh), Patna (Bihar), Pune (Maharashtra) and Ratlam (Madhya Pradesh); selected on the basis of location of the collaborating centres. The study was conducted under the academic and technical supervision of Indian Council of Medical Research- National Institute of Implementation Research (ICMR-NIIRNCD), Jodhpur, Rajasthan. Sampling methodology In the first stage, six districts included in the study were purposively selected as they were the established operational areas of the collaborating investigators. This provided feasibility for multi-centric fieldwork. These districts were known to have higher TB Burden and delays in care-seeking. In the second stage within each district, two blocks were selected randomly. From each selected block, list of villages with active Nehru Yuva Kendra Sangathan (NYKS) youth clubs were obtained from NYKS office. From this list of villages with NYKS youth clubs, 5 villages per block were select. This random selection of villages was done in accordance with the simple random sampling as done under the NYKS study [ 22 ]. In the fourth and final stage universal sampling was done of all the households and family members under the selected villages of the district. Study population The study population included all permanent residents residing in the selected study areas/sites belonging to all age groups and genders. Eligibility criteria of the respondent: All the families who were residing in the study sites were selected on household basis. One member from each family was selected as the household respondent for purpose of collecting information. Sample size and sampling technique The final study population comprised approximately 82,636 individuals. Universal sampling was employed, wherein all eligible households in the six selected districts were surveyed to achieve complete enumeration and minimize selection bias. Households found locked were revisited twice at different time points. Study variables The primary outcome was tuberculosis vulnerability, defined as reported by the people of present TB status as well as having diabetes mellitus, HIV infection, silicosis, occupational silica exposure and individuals having smoking habit. All the variables were categorised as per the operational definition chosen in the study (elaborated in Table 4 ). Another aspect emphasized in the study is the TB prevalence, which is calculated by adding the new and old cases of TB. New cases were represented by the “Currently receiving ATT” while the old cases were represented by “Completed ATT in the past 2 years”. Adding both of these values give us TB Prevalence. Independent variables included age group, sex, occupation, and community group. Data collection method and tool Data were obtained via household-based face-to-face interviews using a pretested semi-structured questionnaire administered by trained investigators. A designated adult respondent provided information for all household members in local dialect. The tool, developed from review of relevant literature and national programme guidelines, assessed socio-demographic characteristics, diabetes mellitus, HIV infection, and silicosis or occupational silica exposure and opinion of the investigators of the study and subject experts. Data analysis The data was cleaned and the study sites were geographically represented. The categorical data was expressed as percentages and frequencies. Ethical considerations The study followed the ethical guidelines as prescribed by the Indian Council of Medical Research (ICMR) guidelines 2025. The Institute Ethics Committee of ICMR-NIIRNCD, Jodhpur granted the ethics approval after going over the research protocol (File No. IEC-ICMR-NIIRNCD/2021/25/3). This study was funded by the Indian Council of Medical Research (ICMR) vide File No. 5/8/5/44/ITRC/Implementation/2021/ECD-I. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Informed consent was obtained from all the participants. Results The initial dataset comprised 84,004. Data cleaning involved removal of blank entries (n = 576), records with cough for >2 weeks (n = 112), missing district information (n = 33), and records with unverifiable respondent identification (n = 647). No missing values were observed for block or village variables. The final analytical dataset consisted of 82,636 records and was used for statistical analysis. Table 1 illustrates the geographical distribution of the study participants in the respective study sites with the distribution of individuals among these places. The study presents information of status of TB and known vulnerable factors among 82636 individuals residing in 12736 households in 6 districts of 5 states in India. This information was collected from 12736 adult respondents found available at these households to represent their family. Table 2 presents the socio-demographic characteristics of the study population. Of the 82,636 participants, 52% were male (n = 43,134), 47% female (n = 39,478), and 1% identified as third gender (n = 24). The majority were aged ≥15 years (77%, n = 63,445), while 7% (n = 6,058) were <6 years and 16% (n = 13,133) were aged 6–15 years.. Largest occupation group with 60% share was “Not in labour force” represented by women, children and dependent senior family members. ‘Agriculture & Allied’ category of occupation was the largest group with 14% share. Among the community groups studied ‘Other Backward Classes’ scored highest rank with 44% share of study population. This group was followed by ‘Scheduled Caste’ community group with 30% share. Download: PNG larger image TIFF original image Table 1. Geographical distribution of the study participants (n = 82636). https://doi.org/10.1371/journal.pone.0360758.t001 Download: PNG larger image TIFF original image Table 2. Characteristics of the study participants (n = 82636). https://doi.org/10.1371/journal.pone.0360758.t002 Table 3 presents key clinical, behavioural and occupational characteristics of the study population (N = 82,636). Prior tuberculosis was reported by 0.29%of the population, and 0.08% reported recent completion of anti-tubercular treatment and ongoing treatment was found in 0.07% of the study sample. TB Prevalence is calculated from the table by adding the values under “Currently receiving ATT” and “Completed ATT within the last 2 years” which gave a total of 0.15%. As TB statuses could not be confirmed through microbiological laboratory testing, it could not be effectively classified into active TB cases and other criteria. So, the above-mentioned two categories were defined according to the self-reporting nature of the study. “Currently receiving ATT” signified active cases as they were receiving therapy, while “Completed ATT within the last 2 years” signified individuals who completed therapy recently but have a chance of relapse. The majority of relapse cases of TB occur in the first two years of treatment completion. HIV reactivity was observed in 0.9% of individuals. The majority were never smokers (94%). Self-reported silicosis (1.2%) and occupational silica exposure (<2%) were also noted among the population. Diabetes was reported by 1.4% and cough was present in 4% of participants. Download: PNG larger image TIFF original image Table 3. Distribution of Tuberculosis and other vulnerable groups among the participants (n = 82636). https://doi.org/10.1371/journal.pone.0360758.t003 Table 4 tabulates all the operational definitions that has been considered in the study questionnaire for assessing the health status of the individuals through self reporting. While Table 5 tabulates the prevalence, percentages and 95% CI of all the diseases and risk factors considered in the study and give the raw values with approximation. We will notice that adjustment for clustering or sampling design was not done in the study. This is because initially the districts were chosen as per the presence of collaborator centres, followed by selection of two blocks by simple random sampling. Villages under each block were again chosen by simple random sampling. Finally all the households and every member of each village were considered for the study through universal sampling. As the observations under each district were independently selected and there is no intra-cluster correlation or unequal selection probability, so there is no requirement for clustering or sampling design adjustment. Download: PNG larger image TIFF original image Table 4. Disease status and their operational definitions for the study. https://doi.org/10.1371/journal.pone.0360758.t004 Download: PNG larger image TIFF original image Table 5. Prevalence of TB and vulnerable groups along with respective 95% Confidence Intervals (n = 82636). https://doi.org/10.1371/journal.pone.0360758.t005 Table 6 is representing the stratified distribution of prevalence among the various categories of the vulnerable groups. It portrays that study participants belonging to the respective exposed groups of the vulnerable population have higher prevalence of Tuberculosis. The smokers recorded the highest prevalence of TB (Past smokers: 1.07%; Current Smokers: 0.36%), followed by silica exposure among mine workers and construction site workers showing a remarkably higher prevalence of TB (Exposure at mines:0.32%; Exposure at building construction: 0.67%). People with HIV also have a higher TB prevalence (0.56%) than the non-reactive group (0.15%). While the participants with diabetes mellitus and cough greater than 2 weeks had TB prevalence of 0.35% and 0.29% respectively. Lower prevalence was observed under the respective unexposed group, suggesting positive association between the vulnerabilities and TB prevalence. Download: PNG larger image TIFF original image Table 6. Distribution of TB status by vulnerable groups (Crude analysis). https://doi.org/10.1371/journal.pone.0360758.t006 The results show a small absolute number of events in the silicosis, silica-exposure and HIV-reactive strata. These subgroups contain very small absolute numbers of TB cases, resulting in wide confidence intervals. The estimates found in the study must therefore be regarded as exploratory and hypothesis-generating rather than definitive. Table 7 describes the prevalence of TB among HIV positives individuals from different studied districts. It is evident from the available data that each district had around 1% TB prevalence among its HIV positive individuals. However, among these districts, Pune reported highest 1.25% prevalence of TB, whereas Jaipur, Lucknow and Patna recorded least 0% prevalence of TB among HIV positive individuals. Download: PNG larger image TIFF original image Table 7. The prevalence of TB in the districts among the HIV positive cases. https:/
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