School of Public Health (ETDs)

Permanent URI for this community

https://hdl.handle.net/10539/37953

Browse

Browsing School of Public Health (ETDs) by Author "Blaauw, Duane"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Occupational characteristics and economic activities of health workers in the quarterly labour force survey: 2008-2017
    (University of the Witwatersrand, Johannesburg, 2024) Dinga, Aphiwe; Blaauw, Duane
    ackground There is global emphasis on the importance of research and analyses of health labour markets. The latter is defined as dynamic systems consisting of the demand and supply of health workers, influenced by a country’s regulations and institutions. However, there is limited national data to inform a health labour market analysis. Aim The aim of the study was to analyse the demographic, occupational characteristics and the economic activities of health workers who were surveyed in the Quarterly Labour Force Survey (QLFS) from 1 January 2008 to 31 December 2017. Methodology This study was a cross-sectional secondary data analysis of the health workers captured in the QLFS, a household survey that is conducted every three months by Statistics South Africa. The survey focuses on the labour market activities of individuals aged 15 to 64 years who live in South Africa. The sample analysed for this study was all health workers surveyed in the QLFS during the study period. Both the South African Standard Classification of Occupations (SASCO) and the Standard Industry Classification (SIC) codes were used to extract data on all health occupations to ensure that the entire health workforce in the QLFS was included in the current study. To identify predictors of employment a multiple logistic regression was carried out. STATA ® 15 was used for the statistical analysis. Results The study sample comprised a total of 5 502 health workers. Nurses constituted the highest proportion of health workers in the survey (60.1%) while medical doctors and dentists represented 10.0%. Nurses were older than the other categories of health workers with a mean age of 43.6 years (SD±10.3), compared to the mean age of 41.8 (SD±10.8) for doctors, 38.6 (SD±10.4) for mid-level health workers and 37.8 (±10.8) for allied health workers. The majority (59.0%) of health workers were employed in the public sector, and in urban areas (83.8%). Only 4.6% of doctors and 7.0% of allied health workers were employed in rural areas. Overall, the study found that fewer than 1% of health workers reported more than one job during the 10-year period. The results of the logistic regression showed that the odds of employment were approximately two times higher for health workers between the ages of 36-45 and 46-55 years old and 1.8 times higher for health workers between the ages of 26-35. There were 0.5 odds of employment for health workers aged 56-64 years compared to the reference age group of 18–25-year-olds. Females were less (0R=0.56) likely to be employed as compared to males. Compared to health workers in urban areas, those in rural areas were less (0.47) likely to be employed. Health workers were 0.53 times less likely to be employed outside the health industry as compared to being employed in the health industry. Conclusion Although the QLFS provides useful information on the health workforce in South Africa, the results highlight the need for investment in a robust human resources for health information system