Usefulness of occupation and industry information in mortality data in South Africa from 2006 to 2015
Abstract Background There is no population based occupational health surveillance system in South Africa, thus mortality data may be a cost effective means of monitoring trends and possible associations with occupation. The aim of this study was to use deaths due to pneumoconiosis (a known occupatio...
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doaj-e853173ff2cf4ba99d3bbf82ce1f4e122020-11-25T03:49:24ZengBMCBMC Public Health1471-24582019-07-0119111110.1186/s12889-019-7177-3Usefulness of occupation and industry information in mortality data in South Africa from 2006 to 2015Kerry S Wilson0Nisha Naicker1Tahira Kootbodien2Vusi Ntlebi3Felix Made4Nonhlanhla Tlotleng5National Institute for Occupational Health, National Health Laboratory ServiceNational Institute for Occupational Health, National Health Laboratory ServiceNational Institute for Occupational Health, National Health Laboratory ServiceNational Institute for Occupational Health, National Health Laboratory ServiceNational Institute for Occupational Health, National Health Laboratory ServiceNational Institute for Occupational Health, National Health Laboratory ServiceAbstract Background There is no population based occupational health surveillance system in South Africa, thus mortality data may be a cost effective means of monitoring trends and possible associations with occupation. The aim of this study was to use deaths due to pneumoconiosis (a known occupational disease) to determine if the South African mortality data are a valid data source for occupational health surveillance in South Africa. Methods Proportions of complete occupation and industry information for the years 2006–2015 were calculated for working age and retired adults. Deaths due to pneumoconiosis were identified in the data set and mortality odds ratios calculated for specific occupations and industry in reference to those who reported being unemployed using logistic regression. Results Only 16.1% of death notifications provided a usual occupation despite 43.1% of the population being employed in the year. The MORs for occupation provided significant increased odds of pneumoconiosis for miners (9.04), those involved in manufacturing (4.77), engineers and machinery mechanics (6.85). Along with these jobs the Mining (9.8), Manufacture (2.2) and Maintenance and repair industries (6.0) have significantly increased odds of pneumoconiosis deaths. The data can be said to provide a useful source of occupational disease information for surveillance where active surveillance systems do not exist. Conclusion The findings indicate valid associations were found between occupational disease and expected jobs and industry. The most useful data are from 2013 onwards due to more detailed coding of occupation and industry.http://link.springer.com/article/10.1186/s12889-019-7177-3MortalityPneumoconiosisMiningManufacturing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kerry S Wilson Nisha Naicker Tahira Kootbodien Vusi Ntlebi Felix Made Nonhlanhla Tlotleng |
spellingShingle |
Kerry S Wilson Nisha Naicker Tahira Kootbodien Vusi Ntlebi Felix Made Nonhlanhla Tlotleng Usefulness of occupation and industry information in mortality data in South Africa from 2006 to 2015 BMC Public Health Mortality Pneumoconiosis Mining Manufacturing |
author_facet |
Kerry S Wilson Nisha Naicker Tahira Kootbodien Vusi Ntlebi Felix Made Nonhlanhla Tlotleng |
author_sort |
Kerry S Wilson |
title |
Usefulness of occupation and industry information in mortality data in South Africa from 2006 to 2015 |
title_short |
Usefulness of occupation and industry information in mortality data in South Africa from 2006 to 2015 |
title_full |
Usefulness of occupation and industry information in mortality data in South Africa from 2006 to 2015 |
title_fullStr |
Usefulness of occupation and industry information in mortality data in South Africa from 2006 to 2015 |
title_full_unstemmed |
Usefulness of occupation and industry information in mortality data in South Africa from 2006 to 2015 |
title_sort |
usefulness of occupation and industry information in mortality data in south africa from 2006 to 2015 |
publisher |
BMC |
series |
BMC Public Health |
issn |
1471-2458 |
publishDate |
2019-07-01 |
description |
Abstract Background There is no population based occupational health surveillance system in South Africa, thus mortality data may be a cost effective means of monitoring trends and possible associations with occupation. The aim of this study was to use deaths due to pneumoconiosis (a known occupational disease) to determine if the South African mortality data are a valid data source for occupational health surveillance in South Africa. Methods Proportions of complete occupation and industry information for the years 2006–2015 were calculated for working age and retired adults. Deaths due to pneumoconiosis were identified in the data set and mortality odds ratios calculated for specific occupations and industry in reference to those who reported being unemployed using logistic regression. Results Only 16.1% of death notifications provided a usual occupation despite 43.1% of the population being employed in the year. The MORs for occupation provided significant increased odds of pneumoconiosis for miners (9.04), those involved in manufacturing (4.77), engineers and machinery mechanics (6.85). Along with these jobs the Mining (9.8), Manufacture (2.2) and Maintenance and repair industries (6.0) have significantly increased odds of pneumoconiosis deaths. The data can be said to provide a useful source of occupational disease information for surveillance where active surveillance systems do not exist. Conclusion The findings indicate valid associations were found between occupational disease and expected jobs and industry. The most useful data are from 2013 onwards due to more detailed coding of occupation and industry. |
topic |
Mortality Pneumoconiosis Mining Manufacturing |
url |
http://link.springer.com/article/10.1186/s12889-019-7177-3 |
work_keys_str_mv |
AT kerryswilson usefulnessofoccupationandindustryinformationinmortalitydatainsouthafricafrom2006to2015 AT nishanaicker usefulnessofoccupationandindustryinformationinmortalitydatainsouthafricafrom2006to2015 AT tahirakootbodien usefulnessofoccupationandindustryinformationinmortalitydatainsouthafricafrom2006to2015 AT vusintlebi usefulnessofoccupationandindustryinformationinmortalitydatainsouthafricafrom2006to2015 AT felixmade usefulnessofoccupationandindustryinformationinmortalitydatainsouthafricafrom2006to2015 AT nonhlanhlatlotleng usefulnessofoccupationandindustryinformationinmortalitydatainsouthafricafrom2006to2015 |
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