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Application of geographically weighted regression analysis to assess predictors of short birth interval hot spots in Ethiopia

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  • Desalegn Markos Shifti
  • Catherine Chojenta
  • Elizabeth G Holliday
  • Deborah Loxton

Abstract

Background: Birth interval duration is an important and modifiable risk factor for adverse child and maternal health outcomes. Understanding the spatial distribution of short birth interval, an inter-birth interval of less than 33 months, and its predictors are vital to prioritize and facilitate targeted interventions. However, the spatial variation of short birth interval and its underlying factors have not been investigated in Ethiopia. Objective: This study aimed to assess the predictors of short birth interval hot spots in Ethiopia. Methods: The study used data from the 2016 Ethiopia Demographic and Health Survey and included 8,448 women in the analysis. The spatial variation of short birth interval was first examined using hot spot analysis (Local Getis-Ord Gi* statistic). Ordinary least squares regression was used to identify factors explaining the geographic variation of short birth interval. Geographically weighted regression was used to explore the spatial variability of relationships between short birth interval and selected predictors. Results: Statistically significant hot spots of short birth interval were found in Somali Region, Oromia Region, Southern Nations, Nationalities, and Peoples’ Region and some parts of Afar Region. Women with no education or with primary education, having a husband with higher education (above secondary education), and coming from a household with a poorer wealth quintile or middle wealth quintile were predictors of the spatial variation of short birth interval. The predictive strength of these factors varied across the study area. The geographically weighted regression model explained about 64% of the variation in short birth interval occurrence. Conclusion: Residing in a geographic area where a high proportion of women had either no education or only primary education, had a husband with higher education, or were from a household in the poorer or middle wealth quintile increased the risk of experiencing short birth interval. Our detailed maps of short birth interval hot spots and its predictors will assist decision makers in implementing precision public health.

Suggested Citation

  • Desalegn Markos Shifti & Catherine Chojenta & Elizabeth G Holliday & Deborah Loxton, 2020. "Application of geographically weighted regression analysis to assess predictors of short birth interval hot spots in Ethiopia," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-18, May.
    • Handle: RePEc:plo:pone00:0233790
    DOI: 10.1371/journal.pone.0233790
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    References listed on IDEAS

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    1. Chang-Lin Mei & Ning Wang & Wen-Xiu Zhang, 2006. "Testing the Importance of the Explanatory Variables in a Mixed Geographically Weighted Regression Model," Environment and Planning A, , vol. 38(3), pages 587-598, March.
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