Inequalities in utilization of maternal health care services: Evidence from Matlab, Bangladesh

1. Inequalities in utilization of maternal health care services: Evidence from Matlab, Bangladesh Iqbal Anwar ICDDR,B, Bangladesh

2. Context • What we know • MMR is high in Bangladesh (320/100,000 LB) • Maternal mortality is difficult to monitor but process indicators are valid and easy to monitor • Most of the maternal deaths are preventable and the technical interventions needed are well understood • The “Three delays“ need to be addressed by establishing a functioning EOC system

3. Context (contd.) But we are not certain about: How an enabling environment can be created to make EOC functional in poor resource-settings And we know little about: How the program outputs (by ongoing EOC interventions) are reaching the poor

4. Research questions The study was conducted during 2002-3 with support from World Bank, to answer the following research questions • To what extent women, particularly poorer women in Matlab, Bangladesh are using the available EOC services? • What are the factors that determine / hinder the utilization of EOC services?

5. The study area Bangladesh

6. EOC interventions in Matlab 1987- Home-based maternity services initiated in Block C & D, supported by a referral linkages with Matlab and Chandpur. 1991- Interventions expanded in all four Blocks (A,B,C &D) 1996- A shift in strategy; Subcentres are upgraded (C in 1996, D in 1998, B in 2000 and finally A in 2001) 2003- Comprehensive EOC established in government health complex (sub-district level)

7. Data sources & management • This is a secondary data analysis study: Monitoring and service data from ICDDR,B Matlab (1997-2001) were analysed to answer the research questions. • Data sources • Pictorial cards (pregnancy monitoring tools) • Maternity registers of Matlab clinic and 4 subcentres • Socioeconomic census conducted in 1996 • Qualitative data (In-depth interview) from delivering • mothers • Statistical analysis • Wealth quintiles from 1996 census (asset score) • Data linking, by mothers RID and child’s date of birth • Bivariate and multivariate analysis in SPSS-10 • Rating of qualitative responses

8. Result: Indicator status at a glance(Total number of deliveries =12080)

11. R:P =2.9 R:P=3.7 R:P=9.2 R:P=8.0

12. R:P=2.0 R:P=1.1 R:P=1.5 R:P=1.2

13. R:P=3.2 R:P=3.1 R:P=2.6 R:P=3.3 R:P=2.5

14. Effect of other covariates upon delivery by a skilled birth attendant Maternaleducation Birth order No. ANC visits Education of mother Maternal age No of ANC visit Maternal age Birth order

15. (Facility based data) N=1047 N=285 N=484 N=863 N=375 N=3054 R:P=4.1 R:P=2.3 R:P=2.3 R:P=1.6 R:P=2.6 R:P=2.3

16. Logistic regression model • Dependent variable • birth attendant (0=unskilled; 1=skilled) • Independent variables • socioeconomic status • age of mother • number of ANC visits • birth order • education of the mother • area of residence • year of birth

17. Predictors for skilled attendance at birth • Number of ANC visits • Socioeconomic status • Area / Blocks • Birth order • Education of mother • Age of mother • Year of delivery

18. Barriers in accessing EOC services • Fear of referral to district level facilities • Influence of husband • Indirect cost (transport/food/attendants etc.) • Concern that delivery may take place on way • Distance • Household responsibilities • Previous bad experiences

19. Conclusion • Trends of EOC program outputs are increasing in ICDDR,B service area but distribution not yet equitable • Most of the barriers explored are related to cost • Pro-poor strategies need to be adopted to increase utilization and to reduce inequality: Demand side financing and/or decentralization of services may be policy options. • ANC should be emphasized as a service improvement tool for better utilization of maternity services.