Answers are grounded in this paper and cite their sources.
Utilizing geographic information systems (GIS) for spatial analysis is crucial for examining, assessing, and visualizing the health status of different regions. There has been a high maternal and infant mortality rate in West Java, Indonesia, leading to a need for spatial information to support the government in planning healthcare. This study aims to examine and compare the geographic clusters between maternal mortality ratio (MMR) and infant mortality rate (IMR) utilizing tools in a GIS environment; it also aims to assess how those clusters relate to socioeconomic conditions. Data on mortalities and demography in 2020 were collected from the Department of Health Regional and Statistics Bureau. The Getis-Ord Gi* hotspot was applied for the IMR and MMR spatial clustering (low and high numbers-clusters). Further, the ordinary least square (OLS) was implemented to generate the correlation between MMR-IMR clusters and socioeconomic factors. Our results show that significantly low clusters of both MMR and IMR (with 95-99% confidence levels) were located close to urban and highly developed areas. The spatial pattern of hot and cold MMR clusters was similar to the IMR clusters (> 0.68). OLS models showed a high relationship between selected variables and IMR (R2 = 0.80), but low relationship with MMR (R2 = 0.20). A significant correlation was found between IMR and population density, income, and percentage of the population without education, while MMR was related to the number of health facilities. These findings illustrated the performed analysis capability to identify priority areas for maternal and childcare services.
No takes yet. Share an insight, caveat, or question.
Fikriyah et al. (2025) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: