Examining tuberculosis stigma among mining communities of Gombe state using structural equation modeling approach

Tuberculosis is a global public health concern. Despite attempts to detect and cure tuberculosis, around 300,000 cases were missed in Nigeria by 2023. This is primarily among key and vulnerable populations, especially miners. Major factors of this gap include barriers to health care access, inadequate health-seeking behaviour in the community, low socioeconomic situations, and stigma. However, few research has investigated TB-related stigma in Nigeria. Unfortunately, no studies had looked into the causes of TB-related stigma among miners. The current study used structural equation modelling to investigate the association between stigma and tuberculosis among miners in Gombe State, Nigeria. Cross-sectional survey was conducted using convenience sampling, with 292 respondents recruited from mining towns in Gombe State, Nigeria. Participants were interviewed with a structured questionnaire. A structural equation model was used to investigate the direct and indirect causes of TB-related stigma in mining communities. Chi-square was one of the indicators used to assess the structural equation and multivariate regression among others. A structural equation model found that gender strongly predicts TB stigma (β = -4.99, p = 0.041), with males experiencing higher stigma levels. Education (β = -0.85, p = 0.429) and income (β = -0.54, p = 0.516) were not significant predictors, indicating that stigma exists regardless of socioeconomic position. There was a negative correlation between TB knowledge and stigma (β = -0.42, p < 0.001), with fear of contagion being the largest driver (β = 0.51, p < 0.001). Our findings suggest that gender strongly predicts TB stigma, with males experiencing higher stigma levels, although education and income were not predictors. To minimise stigma associated with tuberculosis, a multi-level approach involving education, governmental reforms, and social norms is needed.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-30
DOI
https://doi.org/10.5281/zenodo.17200065
Primary Topic
Mathematical Biology Tumor Growth
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Examining tuberculosis stigma among mining communities of Gombe state using structural equation modeling approach

Zenodo (CERN European Organization for Nuclear Research)
Mathematical Biology Tumor Growth
article

Examining tuberculosis stigma among mining communities of Gombe state using structural equation modeling approach

article en

Abstract

Tuberculosis is a global public health concern. Despite attempts to detect and cure tuberculosis, around 300,000 cases were missed in Nigeria by 2023. This is primarily among key and vulnerable populations, especially miners. Major factors of this gap include barriers to health care access, inadequate health-seeking behaviour in the community, low socioeconomic situations, and stigma. However, few research has investigated TB-related stigma in Nigeria. Unfortunately, no studies had looked into the causes of TB-related stigma among miners. The current study used structural equation modelling to investigate the association between stigma and tuberculosis among miners in Gombe State, Nigeria. Cross-sectional survey was conducted using convenience sampling, with 292 respondents recruited from mining towns in Gombe State, Nigeria. Participants were interviewed with a structured questionnaire. A structural equation model was used to investigate the direct and indirect causes of TB-related stigma in mining communities. Chi-square was one of the indicators used to assess the structural equation and multivariate regression among others. A structural equation model found that gender strongly predicts TB stigma (β = -4.99, p = 0.041), with males experiencing higher stigma levels. Education (β = -0.85, p = 0.429) and income (β = -0.54, p = 0.516) were not significant predictors, indicating that stigma exists regardless of socioeconomic position. There was a negative correlation between TB knowledge and stigma (β = -0.42, p < 0.001), with fear of contagion being the largest driver (β = 0.51, p < 0.001). Our findings suggest that gender strongly predicts TB stigma, with males experiencing higher stigma levels, although education and income were not predictors. To minimise stigma associated with tuberculosis, a multi-level approach involving education, governmental reforms, and social norms is needed.

Zenodo (CERN European Organization for Nuclear Research)
AIDS Prevention Initiative in Nigeria (NG), Health Foundation (GB), Gombe State University (NG)
No poverty
Openalex Percentile: Top 46%
Mathematical Biology Tumor Growth
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Examining tuberculosis stigma among mining communities of Gombe state using structural equation modeling approach · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS