A Review of Spatial Analysis Application in Childhood Malnutrition Studies
Aida Soraya Shamsuddin1, Wan Azdie Mohd Abu Bakar1, Sharifah Norkhadijah Syed Ismail2
1Department of Nutrition Sciences, Kulliyyah of Allied Health Sciences, International Islamic University Malaysia (IIUM), Pahang, Malaysia.
Insights
Spatial analysis is crucial for understanding childhood malnutrition, identifying geographic patterns and risk factors. This review highlights its importance in combating malnutrition globally.
Area of Science:
- Public Health
- Geographic Information Systems (GIS)
- Epidemiology
Background:
- Malnutrition affects approximately 230 million children under 5 globally.
- Over half of deaths in children under 5 are linked to malnutrition.
- Spatial analysis is increasingly used to understand and address this critical issue.
Purpose of the Study:
- To evaluate the current use of spatial analysis in childhood malnutrition studies.
- To identify common spatial analysis methods and associated factors.
- To inform strategies for malnutrition eradication.
Main Methods:
- Systematic review of 27 articles from ScienceDirect, Scopus, PubMed, and CINAHL.
- Data extraction included study objectives, areas, malnutrition types, data sources, software, and analysis methods.
- Analysis focused on identifying spatial analysis techniques and associated risk factors.
Main Results:
- Ten spatial analysis methods were identified in the reviewed literature.
- The Bayesian geoadditive regression model was the most frequently applied method.
- Spatial analysis effectively determines geographic distribution, identifies malnutrition hotspots, and correlates risk factors.
Conclusions:
- Spatial analysis is vital for mapping malnutrition prevalence and identifying high-risk areas.
- Understanding geographic patterns aids in developing targeted interventions.
- This review underscores the role of spatial analysis in global efforts to eliminate childhood malnutrition.
Abstract:
Approximately 230 million children under 5 years old of age suffer from malnutrition and over half of the children below 5 years old deaths are due to malnutrition nowadays. To gain a better understanding of this problem, the application of spatial analysis has risen exponentially in recent years. In this review, the present state of information on the use of spatial analysis in childhood malnutrition studies was evaluated using four databases of digital scientific journals: ScienceDirect, Scopus, PubMed and CINAHL. We chose 2,278 articles from the search results and a total of 27 articles met our criteria for review. The following information was extracted from each article: objective of study, study area, types of malnutrition, subject, data sources, computer software packages, spatial analysis and factors associated with childhood malnutrition. A total of 10 spatial analysis methods were reported in the reviewed articles and the Bayesian geoadditive regression model was the most common method applied in childhood malnutrition studies. This review highlights the importance of the application of spatial analysis in determining the geographic distribution of malnutrition cases, hotspot areas and risk factors correlated with childhood malnutrition. It also provides implications for strategic initiatives to eradicate all forms of malnutrition.
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