The impact of teenage pregnancy on school dropout in Brazil: a Bayesian network approach
Abstract Background As reported by the World Health Organization, adolescent pregnancy is a major public health concern given its impact on the life of mothers and their family members. In this study we investigated possible cause-effect relations between teenage pregnancy and school dropout, and ot...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-10-01
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| Series: | BMC Public Health |
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| Online Access: | https://doi.org/10.1186/s12889-021-11878-3 |
| _version_ | 1819009047532142592 |
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| author | Emerson Cruz Fabio Gagliardi Cozman Wilson Souza Albertina Takiuti |
| author_facet | Emerson Cruz Fabio Gagliardi Cozman Wilson Souza Albertina Takiuti |
| author_sort | Emerson Cruz |
| collection | DOAJ |
| description | Abstract Background As reported by the World Health Organization, adolescent pregnancy is a major public health concern given its impact on the life of mothers and their family members. In this study we investigated possible cause-effect relations between teenage pregnancy and school dropout, and other attributes that gravitate around them, using the Bayesian network approach. Methods We used a database prepared by the Adolescent House Project and invited experts in the areas of Health, Education and Social Assistance to answer a survey containing questions aimed at detecting possible causal relationships. To perform the statistical analysis and the numerical simulations we employed the language and formalism of Bayesian networks. Results The analysis indicated a strong cause-effect relation between teenage pregnancy and school dropout, bolstered by economic vulnerability. We were able to identify the profile of the female teenager who drops out from school: white girls older than 15 years who got pregnant at least once, are not working to generate an income, and who belong to the group where the family income is less than or equal to US$780 per month. Also we detected the “maternal impact factor", i.e., the effect caused by whether or not the mothers of the teenagers have experienced teenage pregnancy. Conclusion There are many factors that lead teenagers to drop out of school; we confirmed not only the commonsense notion that pregnancy of the teenager is a major factor but found that a history of teenage pregnancy on the part of the mother is a major factor. Moreover, Bayesian networks emerged as an interesting mathematical framework to perform the statistical analysis. |
| first_indexed | 2024-12-21T00:50:09Z |
| format | Article |
| id | doaj.art-7ef5ea0a0d6d411d9bcbf961be789bd7 |
| institution | Directory Open Access Journal |
| issn | 1471-2458 |
| language | English |
| last_indexed | 2024-12-21T00:50:09Z |
| publishDate | 2021-10-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| spelling | doaj.art-7ef5ea0a0d6d411d9bcbf961be789bd72022-12-21T19:21:26ZengBMCBMC Public Health1471-24582021-10-012111810.1186/s12889-021-11878-3The impact of teenage pregnancy on school dropout in Brazil: a Bayesian network approachEmerson Cruz0Fabio Gagliardi Cozman1Wilson Souza2Albertina Takiuti3Escola Politécnica, Universidade de São PauloEscola Politécnica, Universidade de São PauloPrograma Saúde do Adolescente, Secretaria de Estado da Saúde de São PauloPrograma Saúde do Adolescente, Secretaria de Estado da Saúde de São PauloAbstract Background As reported by the World Health Organization, adolescent pregnancy is a major public health concern given its impact on the life of mothers and their family members. In this study we investigated possible cause-effect relations between teenage pregnancy and school dropout, and other attributes that gravitate around them, using the Bayesian network approach. Methods We used a database prepared by the Adolescent House Project and invited experts in the areas of Health, Education and Social Assistance to answer a survey containing questions aimed at detecting possible causal relationships. To perform the statistical analysis and the numerical simulations we employed the language and formalism of Bayesian networks. Results The analysis indicated a strong cause-effect relation between teenage pregnancy and school dropout, bolstered by economic vulnerability. We were able to identify the profile of the female teenager who drops out from school: white girls older than 15 years who got pregnant at least once, are not working to generate an income, and who belong to the group where the family income is less than or equal to US$780 per month. Also we detected the “maternal impact factor", i.e., the effect caused by whether or not the mothers of the teenagers have experienced teenage pregnancy. Conclusion There are many factors that lead teenagers to drop out of school; we confirmed not only the commonsense notion that pregnancy of the teenager is a major factor but found that a history of teenage pregnancy on the part of the mother is a major factor. Moreover, Bayesian networks emerged as an interesting mathematical framework to perform the statistical analysis.https://doi.org/10.1186/s12889-021-11878-3Teenage pregnancySchool dropoutBayesian networksCausality |
| spellingShingle | Emerson Cruz Fabio Gagliardi Cozman Wilson Souza Albertina Takiuti The impact of teenage pregnancy on school dropout in Brazil: a Bayesian network approach BMC Public Health Teenage pregnancy School dropout Bayesian networks Causality |
| title | The impact of teenage pregnancy on school dropout in Brazil: a Bayesian network approach |
| title_full | The impact of teenage pregnancy on school dropout in Brazil: a Bayesian network approach |
| title_fullStr | The impact of teenage pregnancy on school dropout in Brazil: a Bayesian network approach |
| title_full_unstemmed | The impact of teenage pregnancy on school dropout in Brazil: a Bayesian network approach |
| title_short | The impact of teenage pregnancy on school dropout in Brazil: a Bayesian network approach |
| title_sort | impact of teenage pregnancy on school dropout in brazil a bayesian network approach |
| topic | Teenage pregnancy School dropout Bayesian networks Causality |
| url | https://doi.org/10.1186/s12889-021-11878-3 |
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