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Prevalence and predictors of child labour among junior public secondary school students in Enugu, Nigeria: a cross-sectional study
BACKGROUND: Globally, millions of children are involved in child labour. However, low- and middle-income countries are mostly hit. This study examined the predictors of child labour among public secondary school students in the Enugu metropolis. METHODS: This was a descriptive cross-sectional study...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262090/ https://www.ncbi.nlm.nih.gov/pubmed/34233655 http://dx.doi.org/10.1186/s12889-021-11429-w |
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author | Enebe, N. O. Enebe, J. T. Agunwa, C. C. Ossai, E. N. Ezeoke, U. E. Idoko, C. A. Mbachu, C. O. |
author_facet | Enebe, N. O. Enebe, J. T. Agunwa, C. C. Ossai, E. N. Ezeoke, U. E. Idoko, C. A. Mbachu, C. O. |
author_sort | Enebe, N. O. |
collection | PubMed |
description | BACKGROUND: Globally, millions of children are involved in child labour. However, low- and middle-income countries are mostly hit. This study examined the predictors of child labour among public secondary school students in the Enugu metropolis. METHODS: This was a descriptive cross-sectional study of 332 junior secondary students attending public schools in Enugu metropolis, Nigeria. Multistage sampling technique was used to select the six secondary schools and the students that participated in the study. Data collection was done from September to October 2018. Pretested structured, interviewer-administered questionnaire was used for data collection. The questionnaire contained information on the sociodemographic variables, the kind of work done by the respondents and the number of working hours spent weekly. UNICEF’s standard indicator for child labour was used to estimate the prevalence of child labour. Logistic regression was used to identify socioeconomic predictors of child labour. RESULTS: The prevalence of overall child labour was 71.7%, while for domestic and economic child labour prevalence were 52.1 and 34.0%, respectively. About 35.2% of the respondents worked under hazardous conditions while 8% were forced to work. Two-thirds (236, 65%) of the respondents who have heard about child labour perceived it as wrong. The child labourers mainly worked to render financial assistance to their parents. The predictors of child labour were class of study (AOR = 2.208 (95% CI: 1.199–4.066) and weekly income earned (AOR = 0.316 (95% CI: 0.176–0.567). CONCLUSION: The prevalence of child labour among junior students in public secondary schools in Enugu is high, and is predicted by the level of schooling and income earned. Economic and social reforms could contribute to addressing the predictors of child labour. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11429-w. |
format | Online Article Text |
id | pubmed-8262090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82620902021-07-08 Prevalence and predictors of child labour among junior public secondary school students in Enugu, Nigeria: a cross-sectional study Enebe, N. O. Enebe, J. T. Agunwa, C. C. Ossai, E. N. Ezeoke, U. E. Idoko, C. A. Mbachu, C. O. BMC Public Health Research Article BACKGROUND: Globally, millions of children are involved in child labour. However, low- and middle-income countries are mostly hit. This study examined the predictors of child labour among public secondary school students in the Enugu metropolis. METHODS: This was a descriptive cross-sectional study of 332 junior secondary students attending public schools in Enugu metropolis, Nigeria. Multistage sampling technique was used to select the six secondary schools and the students that participated in the study. Data collection was done from September to October 2018. Pretested structured, interviewer-administered questionnaire was used for data collection. The questionnaire contained information on the sociodemographic variables, the kind of work done by the respondents and the number of working hours spent weekly. UNICEF’s standard indicator for child labour was used to estimate the prevalence of child labour. Logistic regression was used to identify socioeconomic predictors of child labour. RESULTS: The prevalence of overall child labour was 71.7%, while for domestic and economic child labour prevalence were 52.1 and 34.0%, respectively. About 35.2% of the respondents worked under hazardous conditions while 8% were forced to work. Two-thirds (236, 65%) of the respondents who have heard about child labour perceived it as wrong. The child labourers mainly worked to render financial assistance to their parents. The predictors of child labour were class of study (AOR = 2.208 (95% CI: 1.199–4.066) and weekly income earned (AOR = 0.316 (95% CI: 0.176–0.567). CONCLUSION: The prevalence of child labour among junior students in public secondary schools in Enugu is high, and is predicted by the level of schooling and income earned. Economic and social reforms could contribute to addressing the predictors of child labour. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11429-w. BioMed Central 2021-07-07 /pmc/articles/PMC8262090/ /pubmed/34233655 http://dx.doi.org/10.1186/s12889-021-11429-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Enebe, N. O. Enebe, J. T. Agunwa, C. C. Ossai, E. N. Ezeoke, U. E. Idoko, C. A. Mbachu, C. O. Prevalence and predictors of child labour among junior public secondary school students in Enugu, Nigeria: a cross-sectional study |
title | Prevalence and predictors of child labour among junior public secondary school students in Enugu, Nigeria: a cross-sectional study |
title_full | Prevalence and predictors of child labour among junior public secondary school students in Enugu, Nigeria: a cross-sectional study |
title_fullStr | Prevalence and predictors of child labour among junior public secondary school students in Enugu, Nigeria: a cross-sectional study |
title_full_unstemmed | Prevalence and predictors of child labour among junior public secondary school students in Enugu, Nigeria: a cross-sectional study |
title_short | Prevalence and predictors of child labour among junior public secondary school students in Enugu, Nigeria: a cross-sectional study |
title_sort | prevalence and predictors of child labour among junior public secondary school students in enugu, nigeria: a cross-sectional study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262090/ https://www.ncbi.nlm.nih.gov/pubmed/34233655 http://dx.doi.org/10.1186/s12889-021-11429-w |
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