Beyond adequate: Factors associated with quality of antenatal care in western Tanzania. Issue 3 (19th September 2020)

• Record Type: Journal Article
• Authors: Young, Marisa R.; Morof, Diane; Lathrop, Eva; Haddad, Lisa; Blanton, Curtis; Maro, Godson; Serbanescu, Florina
• Is Part Of: International journal of gynaecology and obstetrics. Volume 151:Issue 3(2020)
• Page Start: 431
• Page End: 437
• Publication Date: 2020-09-19
• Subjects: Antenatal -- Pregnancy -- Prenatal care -- Principal component analysis -- Quality of care -- Tanzania; Gynecology -- Periodicals; Obstetrics -- Periodicals; Electronic journals; 618
• DOI: 10.1002/ijgo.13349
• Languages: English
• ISSNs: 0020-7292

Abstract

Abstract: 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. Abstract : Principal component analysis is a low‐cost, feasible method of identifying drivers of quality of antenatal care that may apply to multiple settings.