Mapping the spatial distribution of harmful umbilical cord stump care among neonates in Ethiopia: A spatial with

Berihun Bantie1, Natnael Moges2, Worku Awoke3

  • 1Department of Comprehensive Nursing, College of Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia.

Plos One
|October 24, 2024
PubMed

Insights

Harmful umbilical cord stump care is prevalent in Ethiopia, particularly in eastern and northern regions. Factors like rural residence and region of living significantly influence these practices, necessitating targeted interventions.

Area of Science:

  • Neonatal Health
  • Public Health
  • Epidemiology

Background:

  • Umbilical cord stump (UCS) care is critical for preventing neonatal infections, sepsis, and mortality.
  • Harmful traditional practices persist despite WHO recommendations for clean and dry cord care.
  • Data on the geographical distribution and risk factors for harmful UCS care in Ethiopia are limited.

Purpose of the Study:

  • To analyze the spatial distribution of harmful umbilical cord stump care practices in Ethiopia.
  • To identify individual and community-level risk factors associated with these practices.

Main Methods:

  • Secondary data analysis of the Ethiopian Demographic Health Survey (EDHS 2016) involving 7,168 live births.
  • Spatial analysis using ArcGIS and SaTScan to identify clusters of harmful UCS care.
  • Multilevel logistic regression to determine associated factors.

Main Results:

  • Prevalence of harmful UCS care was 15.09%, with significant spatial variations.
  • Hotspot areas identified in Somali, Tigray, and Amhara regions.
  • Factors associated with harmful practices include maternal age, rural residence, female neonates, and living in specific regions (Tigray, Somali, Harari).

Conclusions:

  • Harmful UCS care practices in Ethiopia exhibit non-random, clustered distribution in specific regions.
  • Both individual and community-level factors significantly predict these practices.
  • Targeted interventions are crucial for neonates in identified high-risk areas, addressing identified predictors.
Abstract