Presentation (CTI)

OBJECTIVES: To assess whether more detailed measures of urbanicity identify meaningful differences in health service access and utilization between areas in Nepal reclassified from rural to urban and long-established urban areas following Nepal’s 2015 federal restructuring of administrative units.
METHODS: Using the Nepal Demographic and Health Surveys (NDHS) 2011, 2016, and 2022, we conducted descriptive analyses to summarize patterns using means and percentiles at the cluster level to assess how health service access, utilization, and selected health measures varied across three complementary spatial frameworks.First, we applied rural-urban transition categories, distinguishing areas that remained rural by formal designation (R→R), those that transitioned from rural to urban (R→U), and those with longstanding urban status (U→U). Second, we derived an agrarian index from NDHS variables capturing agricultural occupation, agricultural land ownership, and livestock ownership, characterizing agrarian context along a continuum. Third, we incorporated the Degree of Urbanization (DEGURBA), a functional settlement classification based on population size, density, contiguity, and built-up structure derived from census and satellite data, to compare health service access, utilization, and selected health indicators across settlement types.
RESULTS: Consistently rural areas (R→R) performed poorest across most indicators, while longstanding urban areas (U→U) generally performed best. Newly transitioned areas (R→U) showed substantial heterogeneity, sometimes resembling rural areas and sometimes intermediate. Stratifying R→U clusters using the agrarian index clarified this heterogeneity, distinguishing high-, mid-, and low-agrarian clusters that ranged from rural-like to urban-like performance. DEGURBA produced a consistent three-tier pattern, with rural, peri-urban, and urban clusters showing progressively better outcomes.
CONCLUSIONS: Overall, reliance on binary administrative classifications masks substantial within-category variation. Incorporating functional and agrarian-based classifications into routine health data use and planning could support more context-appropriate service delivery and equitable resource allocation, particularly in transitioning municipalities.