Cargando…

Tuberculosis Mortality by Occupation in South Africa, 2011–2015

Work-related tuberculosis (TB) remains a public health concern in low- and middle-income countries. The use of vital registration data for monitoring TB deaths by occupation has been unexplored in South Africa. Using underlying cause of death and occupation data for 2011 to 2015 from Statistics Sout...

Descripción completa

Detalles Bibliográficos
Autores principales: Kootbodien, Tahira, Wilson, Kerry, Tlotleng, Nonhlanhla, Ntlebi, Vusi, Made, Felix, Rees, David, Naicker, Nisha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313633/
https://www.ncbi.nlm.nih.gov/pubmed/30563175
http://dx.doi.org/10.3390/ijerph15122756
_version_ 1783383977983213568
author Kootbodien, Tahira
Wilson, Kerry
Tlotleng, Nonhlanhla
Ntlebi, Vusi
Made, Felix
Rees, David
Naicker, Nisha
author_facet Kootbodien, Tahira
Wilson, Kerry
Tlotleng, Nonhlanhla
Ntlebi, Vusi
Made, Felix
Rees, David
Naicker, Nisha
author_sort Kootbodien, Tahira
collection PubMed
description Work-related tuberculosis (TB) remains a public health concern in low- and middle-income countries. The use of vital registration data for monitoring TB deaths by occupation has been unexplored in South Africa. Using underlying cause of death and occupation data for 2011 to 2015 from Statistics South Africa, age-standardised mortality rates (ASMRs) were calculated for all persons of working age (15 to 64 years) by the direct method using the World Health Organization (WHO) standard population. Multivariate logistic regression analysis was performed to calculate mortality odds ratios (MORs) for occupation groups, adjusting for age, sex, year of death, province of death, and smoking status. Of the 221,058 deaths recorded with occupation data, 13% were due to TB. ASMR for TB mortality decreased from 165.9 to 88.8 per 100,000 population from 2011 to 2015. An increased risk of death by TB was observed among elementary occupations: agricultural labourers (MOR(adj) = 3.58, 95% Confidence Interval (CI) 2.96–4.32), cleaners (MOR(adj) = 3.44, 95% CI 2.91–4.09), and refuse workers (MOR(adj) = 3.41, 95% CI 2.88–4.03); among workers exposed to silica dust (MOR(adj) = 3.37, 95% CI 2.83–4.02); and among skilled agricultural workers (MOR(adj) = 3.31, 95% CI 2.65–4.19). High-risk TB occupations can be identified from mortality data. Therefore, TB prevention and treatment policies should be prioritised in these occupations.
format Online
Article
Text
id pubmed-6313633
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-63136332019-06-17 Tuberculosis Mortality by Occupation in South Africa, 2011–2015 Kootbodien, Tahira Wilson, Kerry Tlotleng, Nonhlanhla Ntlebi, Vusi Made, Felix Rees, David Naicker, Nisha Int J Environ Res Public Health Article Work-related tuberculosis (TB) remains a public health concern in low- and middle-income countries. The use of vital registration data for monitoring TB deaths by occupation has been unexplored in South Africa. Using underlying cause of death and occupation data for 2011 to 2015 from Statistics South Africa, age-standardised mortality rates (ASMRs) were calculated for all persons of working age (15 to 64 years) by the direct method using the World Health Organization (WHO) standard population. Multivariate logistic regression analysis was performed to calculate mortality odds ratios (MORs) for occupation groups, adjusting for age, sex, year of death, province of death, and smoking status. Of the 221,058 deaths recorded with occupation data, 13% were due to TB. ASMR for TB mortality decreased from 165.9 to 88.8 per 100,000 population from 2011 to 2015. An increased risk of death by TB was observed among elementary occupations: agricultural labourers (MOR(adj) = 3.58, 95% Confidence Interval (CI) 2.96–4.32), cleaners (MOR(adj) = 3.44, 95% CI 2.91–4.09), and refuse workers (MOR(adj) = 3.41, 95% CI 2.88–4.03); among workers exposed to silica dust (MOR(adj) = 3.37, 95% CI 2.83–4.02); and among skilled agricultural workers (MOR(adj) = 3.31, 95% CI 2.65–4.19). High-risk TB occupations can be identified from mortality data. Therefore, TB prevention and treatment policies should be prioritised in these occupations. MDPI 2018-12-05 2018-12 /pmc/articles/PMC6313633/ /pubmed/30563175 http://dx.doi.org/10.3390/ijerph15122756 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kootbodien, Tahira
Wilson, Kerry
Tlotleng, Nonhlanhla
Ntlebi, Vusi
Made, Felix
Rees, David
Naicker, Nisha
Tuberculosis Mortality by Occupation in South Africa, 2011–2015
title Tuberculosis Mortality by Occupation in South Africa, 2011–2015
title_full Tuberculosis Mortality by Occupation in South Africa, 2011–2015
title_fullStr Tuberculosis Mortality by Occupation in South Africa, 2011–2015
title_full_unstemmed Tuberculosis Mortality by Occupation in South Africa, 2011–2015
title_short Tuberculosis Mortality by Occupation in South Africa, 2011–2015
title_sort tuberculosis mortality by occupation in south africa, 2011–2015
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313633/
https://www.ncbi.nlm.nih.gov/pubmed/30563175
http://dx.doi.org/10.3390/ijerph15122756
work_keys_str_mv AT kootbodientahira tuberculosismortalitybyoccupationinsouthafrica20112015
AT wilsonkerry tuberculosismortalitybyoccupationinsouthafrica20112015
AT tlotlengnonhlanhla tuberculosismortalitybyoccupationinsouthafrica20112015
AT ntlebivusi tuberculosismortalitybyoccupationinsouthafrica20112015
AT madefelix tuberculosismortalitybyoccupationinsouthafrica20112015
AT reesdavid tuberculosismortalitybyoccupationinsouthafrica20112015
AT naickernisha tuberculosismortalitybyoccupationinsouthafrica20112015