Prevalence and associated factors of skilled birth attendants in Bangladesh: A combined statistical and machine learning analysis
Jakia Sultana Mim, Md. Shihab Mostafa, Bodrunnahar Barna, Ahmed Nuzat Sadia, Raisul Islam, Abdullah Al Islam, Kanchan Thapa · 2026
Read Prevalence and associated factors of skilled birth attendants in Bangladesh: A combined statistical and machine learning analysis by Jakia Sultana Mim, Md. Shihab Mostafa, Bodrunnahar Barna, Ahmed Nuzat Sadia, Raisul Islam, Abdullah Al Islam, Kanchan Thapa (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13592634.txt.
Description
Jakia Sultana Mim and six colleagues examine who gets a skilled attendant at childbirth in Bangladesh, where mother and newborn deaths remain high. Their data come from the 2022 national health survey. Standard regression sorted the social and economic factors first. Machine learning models then classified births a second way, checking which factors mattered most and how well each method predicted attendant use.
About sixty eight percent of women delivered with a doctor, nurse, or midwife present. Schooling stood out: educated mothers had about four times the odds of skilled help compared with unschooled mothers. Wealth, four or more pregnancy checkups, and town living each raised the odds, while village living lowered them. A random forest model scored best at prediction. Mim and the team urge focused help for poor and rural mothers.
Catalog record
| CREATOR | Jakia Sultana Mim, Md. Shihab Mostafa, Bodrunnahar Barna, Ahmed Nuzat Sadia, Raisul Islam, Abdullah Al Islam, Kanchan Thapa |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 38 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |