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Author Notes:

Marisa R. Young, Department of Gynecology and Obstetrics, Emory University Hospital Midtown, Atlanta, GA, USA., Emmail: myoun31@emory.edu

GM contributed to data collection and field work in Tanzania. FS and CB designed, implemented, and analyzed the survey data. MRY, DM, EL, LH, CB FS, and GM all contributed to the study design and planning. Analysis was performed by MRY with assistance from CB and DM. The first draft of the manuscript was written by MRY with substantial input and revision provided by DM, EL, LH, CB, FS, and GM. The authors’ views expressed in this publication do not necessarily reflect the views of the Centers for Disease Control and Prevention.

We would like to acknowledge the donors (Bloomberg Philanthropies, Fondation H&B Agerup), Dr. Paul Chaote, Kigoma Regional Medical Officer, Ministry of Health, Community Development, Gender, Elderly and Children, Tanzania, CDC/DRH staff Alicia Ruiz and Fernando Carlosama; AMCA Tanzania staff Abdulaziz Ali Msuya and Rose Rusibamayila and their dedicated field work interviewers, and all the women who participated in the study.

The authors have no conflicts of interest.



  • Science & Technology
  • Life Sciences & Biomedicine
  • Obstetrics & Gynecology
  • Antenatal
  • Pregnancy
  • Prenatal care
  • Principal component analysis
  • Quality of care
  • Tanzania

Beyond adequate: Factors associated with quality of antenatal care in western Tanzania


Journal Title:



Volume 151, Number 3


, Pages 431-437

Type of Work:

Article | Post-print: After Peer Review


Objective: To determine quality of antenatal care (ANC). Most literature focuses on ANC attendance and services. Less is known about quality of care (QoC). Method: Data were analyzed from the 2016 Kigoma Reproductive Health Survey, a population-based survey of reproductive-aged women. Women with singleton term live births were included and principal component analysis (PCA) was used to create an ANC quality index using linear combinations of weights of the first principal component. Nineteen variables were selected for the index. The index was then used to assign a QoC score for each woman and linear regression used to identify factors associated with receiving higher QoC. Results: A total of 3178 women received some ANC. Variables that explained the most variance in the QoC index included: gave urine (0.35); gave blood (0.34); and blood pressure measured (0.30). In multivariable linear regression, factors associated with higher QoC included: ANC at a hospital (versus dispensary); older age; higher level of education; working outside the home; higher socioeconomic status; and having lower parity. Conclusion: Using PCA methods, several basic components of ANC including maternal physical assessment were identified as important indicators of quality. This approach provides an affordable and effective means of evaluating ANC programs.

Copyright information:

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/rdf).
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