Maternal health care utilization in rural Jordanian villages: Patterns and predictors
Abstract
Background. Different individual (demographic) characteristic and health system related characteristics have been identified in the literature to contribute to different rates of maternal health care utilization in developing countries. This study is going to evaluate the individual and quality of health predictors of maternal health care utilization in rural Jordanian villages. Methods. Data from a 2004 survey was used. Individual (predisposing and enabling) variables, quality of health care variables, and maternal care utilization variables were selected for 477 women who had a live birth during the last 5 years. The conceptual framework used in this study will be the Aday-Andersen model for health services utilization. Results. 82.4% of women received at least one antenatal care visit. Individually, village of residence (p=0.036), parity (p=0.048), education (p=0.006), and health insurance (p=0.029) were found to be significant; in addition to respectful treatment (p=0.045) and clean facilities (p=0.001) were the only quality of health care factors found to be significant in predicting antenatal care use. Using logistic regression, living in southern villages (OR=4.7, p=0.01) and availability of transportation (sometimes OR=3.2, p=0.01 and never OR=2.4, p<0.05) were the only two factors to influence maternal care use. Conclusions. Living in the South and transportation are major barriers to maternal care utilization in rural Jordan. Other important cultural factors of interest in some villages should be addressed in future research. Perceptions of women regarding quality of health services should be seriously taken into account.
Subject Area
Public health|Health care
Recommended Citation
Alkhaldi, Sireen M, "Maternal health care utilization in rural Jordanian villages: Patterns and predictors" (2008). Texas Medical Center Dissertations (via ProQuest). AAI3297452.
https://digitalcommons.library.tmc.edu/dissertations/AAI3297452