Mapping of children with malnutrition in kelantan utilizing open geographic information system (gis) and remote sensing platform

• Main Author: Zabidi Azhar, Mohd Hussin
• Format: Monograph
• Language: English
• Published: Pusat Pengajian Sains Perubatan 2013
• Subjects: R Medicine (General)
• Online Access: http://eprints.usm.my/54874/1/DR.%20ZABIDI%20AZHAR%20MOHD%20HUSSIN%20-%20e.pdf; http://eprints.usm.my/54874/

The Mapping of Children with Malnutrition in Kelantan Utilizing Open Source Geographic Information System (GIS) and Remote Sensing Platform" study was started at 31 October until 30 September 2010 and extends till 31 December 2010. This study was one of the university research {RU) grant headed by Prof. Zabidi Azhar Husin @ Mohd Hussin. The main objective of this study was to identify malnourish children (severe) from 1 day to 6 years old from 12 clinics in Kota Bharu via mapping the location of children with USM Growth Monitor and Geoinformation System {GIS).In this study, data collection was done through the "USM Growth Monitor" online system produced in this study. Through this system, raw data from all the clinic were entered by the nurses involve at the clinic and is able to retrieve direct to research centre at USM. Data regarding Geoinformation System such as soil structure, water source and so on were getting from Malaysian Remote Sensing Agency (ARSM). Kota Bharu district was chosen as a study area for this research from 10 districts in Kelantan after successful research at Tum pat {2007). At the beginning of the study, Anthropometric data such as date of birth, birth weight, birth length and also weaning information of the children aged between 1 day to 6 years old were assemble from every health clinic (Kiinik Kesihatan in Kota Bharu District. Birth weight and length data according to children age were converting to nutritional status using Epilnfo programme (Epi Info'" Version 3.4). The total of 4616 data were collected consist of 2285 {49.5%) boys and 2331{50.5%) girls. Outcome from nutritional status analysis shown that 3.4% of the children were Overweight, 15.3% were undernourished [10.3% were moderate undernourished {-2SD) and 4.5% were severe undernourished {-3SD)]. From this preliminary result, Remote sensing techniques were using to identify the home location of the children and correlation with GIS information and nutritional status were assessed.