Abstract
Nutritional traits simulating at an awesome local geographic level is vital for effective nutritional promotion programs, provision of better nutritional services and population-specific nutritional planning and management. Deficient in
micro-dataset readily available for attributes of individuals at small areas affects the local and national agencies on the route ahead of their smooth managing of the serious nutritional issues and related risks in the community. A solution of this ongoing challenge would be to form a method to simulate reliable small area statistics. This paper provides a dashing appraisal of the methodologies for simulating nutritional traits of populations at geographical limited areas. Findings reveal that microsimulation-based spatial models have the significant robustness over the other methods stated in this study representing a more precise means of simulating nutrition-related traits of population at the small area levels.
micro-dataset readily available for attributes of individuals at small areas affects the local and national agencies on the route ahead of their smooth managing of the serious nutritional issues and related risks in the community. A solution of this ongoing challenge would be to form a method to simulate reliable small area statistics. This paper provides a dashing appraisal of the methodologies for simulating nutritional traits of populations at geographical limited areas. Findings reveal that microsimulation-based spatial models have the significant robustness over the other methods stated in this study representing a more precise means of simulating nutrition-related traits of population at the small area levels.
Original language | English |
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Pages (from-to) | 25-30 |
Number of pages | 6 |
Journal | Computational Biology and Bioinformatics |
Volume | 6 |
Issue number | 1 |
Publication status | Published - May 2018 |