1. 1 What does access to health care among the urban poor mean? Factors associated with use of “appropriate” maternal health services in the slum settlements of Nairobi, Kenya By Jean-Christophe Fotso, Alex Ezeh, Nyovani Madise, Abdhalah Ziraba and Reuben Ogollah INDEPTH Network AGM Nairobi, September 3-7, 2007

2. 2 Background : Maternal Deaths and Mortality Ratio (Deaths per 100,000 live births) Source: WHO/UNICEF/UNFPA, 2004 529,000 deaths527,000 deaths 247,000 deaths11,000 deaths 0 200 400 600 800 1,000 1,200 WorldDeveloping countries Sub-Saharan Africa Kenya Maternal Mortality Ratio (per 100,000)

3. 3 Background (Ct’d)  Kenya resolved to reduce MMR by 3/4 by 2015.  Kenya NRHSDS (1997-2010) Safe motherhood and child survival Key pillars include clean and safe delivery.  Urbanization, poverty and health inequities in SSA More than 50% of SSA population will be living in urban areas by 2030. About 7 out 10 inhabitants of Nairobi live in slums. Growing inequities between the poor and the non-poor. MDG-5: Attention to the growing urban poor populations in SSA.

4. 4 Background (Ct’d)  In the slums co-exist: Private, sub-standard and often unlicensed clinics, with Well equipped public, religious or large NGO facilities, generally in the outskirts of the slums.  Preferable to deliver at home or at TBA’s?  Misleading not to treat the two categories of HFs separately.

5. 5 Objectives  Improve understanding of maternity health seeking behaviors in resource-deprived urban settings Identify the factors which influence the choice of place of delivery among the urban poor; Distinction between sub-standard and “appropriate” health facilities; Formulate recommendations aimed at improving maternal health.

6. 6 Data and Methods  Data from a DSS-nested MHP 1,927 who had pregnancy outcomes in 2004-2005 25 HFs providing obstetric care  Dependent variable: Place of delivery Public/religious/large NGO HF: coded 2 Private, sub-standard HF: coded 1 Not HF (home, TBA …): coded 0  Covariates Socioeconomic variables Biodemographic and health-related covariates Slum residence (Korogocho, Viwandani)  Methods Descriptive analysis Ordered logistic - Partial proportional odds models

7. 7 Health facility deliveries in Kenya (1): All types of HFs; (2): Appropriate HFs 70 48 78 33 0 10 20 30 40 50 60 70 80 90 Percentage of women (%) Nairobi slums (1)Nairobi slums (2)NairobiRural Kenya

8. 8 Multivariate results: Socioeconomic & Residence † p<0.10; * p<0.05; ** p<0.01

9. 9 Multivariate results: B iodemo and health-related † p<0.10; * p<0.05; ** p<0.01

10. 10 Multivariate results: Interactions

11. 11 Recommendations  Provision of health services to the urban poor: Registration of private facilities and clinics – minimum criteria Provision of public health services in/near the slums Improvement of the quality of care (delays, attitude of staff) in public HFs  Health education campaigns Antenatal care attendance Advice/counseling on delivery and postnatal care, and other pregnancy-related issues Target groups:  Poorest, not educated, not working women  Higher parity women  Access to FP and RH services

12. 12  Acknowledgements: The World Bank The Wellcome Trust Thank you