Determinants of Maternal Health and Family Planning Service Coverage in Nepal: Modelling of Routine Data (Determinants of Maternal Health and Family Planning Service Coverage in Nepal)
This analysis identifies the determinants of maternal health and FP services coverage in Nepal using statistical models.
- The districts with a higher proportion of female household heads had higher coverage of institutional delivery.
- Compared to districts in Province 1, districts in Province 2, Bagmati Province, and Gandaki province had lower composite coverage of maternal health services.
- Districts with Limbu and Rai as the predominant cast had lower composite coverage of maternal health services, while the districts with Magar as predominant caste had higher coverage compared to districts with Brahmin as predominant caste.
- Compared to fiscal year 2014/2015, the coverage of maternal health services improved significantly in the year 2018/2019.
- Districts with Rai, Limbu, Chhetri and Newar as predominant caste had lower mCPR while districts with Magar, Gurung and Tharu as predominant caste had higher mCPR compared to districts with Brahmins as predominant caste.
- Compared to Province 1, Gandaki Province, Lumbini Province and Bagmati Province had lower mCPR while other provinces did not differ significantly.
- Based on 95% CI, study revealed significant variation in composite coverage of maternal health services as well as FP service.
- The number of districts with less than the average value of composite coverage of maternal health services and mCPR was 30 and 37 respectively out of 77 districts.
- With the current federal structure where delivery of essential health services has been devolved to local level governments (LLGs), there is greater opportunity for tailored targeted interventions in districts with low coverage of maternal health services and FP services. Low coverage districts for both the maternal health and FP services should be a priority focus.
- Similar analysis can be replicated in the future considering municipality as a unit of analysis once the data on dependent and independent variables is available. This could help LLGs for formulating specific plans to address the gap.
- Predictors of service coverage may change with the impact of policy initiatives, expansion of health services and overall development of the districts. Regular analysis identifying districts lagging in terms of service coverage could be useful.
- The study revealed variations across districts based on predominant caste of the district. For example, districts with Limbu as predominant caste have lower composite coverage of maternal health services as well as mCPR compared to Brahmin. Further studies will be useful to determine if certain caste specific cultural practices are serving as facilitator or barrier to service utilisation.
- Poverty gap in the district, which is the measure of the depth or intensity of poverty was not associated with any of the coverage indicators. Further studies are indicated to assess if the intensity of poverty is still a determinant of service coverage particularly for services covered in this study which are offered free of cost, and in some cases with financial incentives.
- Such studies with individual as unit of analysis may also reveal if the disparities within the districts are masked at district level.
Department of Health Services (DoHS), Ministry of Health and Population (MoHP), Nepal; UKaid Nepal Health Sector Programme 3 (NSHP3)/Monitoring, Evaluation and Operational Research (MEOR), USAID’s Strengthening Systems for Better Health (SSBH). 2020. Determinants of maternal health and family planning service coverage in Nepal: modelling of routine data. Kathmandu, Nepal: DoHS, MoHP, Nepal.
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