biostudies-literatureUnknown18(5)Akter E<h4>Background</h4>Assessing the quality of antenatal care (ANC) is imperative for improving care provisions during pregnancy to ensure the health of mother and baby. In Bangladesh, there is a dearth of research on ANC quality using nationally representative data to understand its levels and determinants. Thus, the current study aimed to assess ANC quality and identify the sociodemographic factors associated with the usage of quality ANC services in Bangladesh.<h4>Methods</h4>Secondary data analysis was conducted using the last two Bangladesh Demographic and Health Surveys (BDHSs) from 2014 and 2017-18. A total of 8,277 ever-married women were included in the analysis (3,631 from 2014 and 4,646 from 2017-18). The quality ANC index was constructed using a principal component analysis on thePloS onee0269767https://www.ebi.ac.uk/biostudies/studies/S-EPMC10155983biostudies-literatureLevels and determinants of quality antenatal care in Bangladesh: Evidence from the Bangladesh Demographic and Health Survey.PMC10155983Akter ENusrat NHossain ATArifeen SENahar QAhmed ARahman AEChowdhury METanwi TSTahsina TfalseLevels and determinants of quality antenatal care in Bangladesh: Evidence from the Bangladesh Demographic and Health Survey.<h4>Background</h4>Assessing the quality of antenatal care (ANC) is imperative for improving care provisions during pregnancy to ensure the health of mother and baby. In Bangladesh, there is a dearth of research on ANC quality using nationally representative data to understand its levels and determinants. Thus, the current study aimed to assess ANC quality and identify the sociodemographic factors associated with the usage of quality ANC services in Bangladesh.<h4>Methods</h4>Secondary data analysis was conducted using the last two Bangladesh Demographic and Health Surveys (BDHSs) from 2014 and 2017-18. A total of 8,277 ever-married women were included in the analysis (3,631 from 2014 and 4,646 from 2017-18). The quality ANC index was constructed using a principal component analysis on the2023-01-01T00:00:00Z20232025-04-04T11:13:25.21Z2025-04-04T11:13:25.21ZS-EPMC101559833713407410.1371/journal.pone.0269767