Risk factor mapping and case map of environmentally based disease in Yogyakarta

BACKGROUND A geographic information system (GIS) is required to guide interventions into prevent ARI and reduce the incidence of cases. The purpose of this study is to find out whether there is spatial autocorrelation in the spread of ARI; to obtain spatial information about the ARI risk factors, t...

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Main Authors: Hariza Adnani, Achmad Arman Subiyanto, Diffah Hanim, Endang Sutisna Sulaeman
Format: Article
Language:English
Published: Faculty of Medicine Universitas Indonesia 2019-08-01
Series:Medical Journal of Indonesia
Subjects:
map
Online Access:http://mji.ui.ac.id/journal/index.php/mji/article/view/3093
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spelling doaj-87d6799e46234cf5b94a99bb2abbcc462020-11-25T02:39:23ZengFaculty of Medicine Universitas Indonesia Medical Journal of Indonesia0853-17732252-80832019-08-0128210.13181/mji.v28i2.30933093Risk factor mapping and case map of environmentally based disease in YogyakartaHariza Adnani0Achmad Arman Subiyanto1Diffah Hanim2Endang Sutisna Sulaeman3Graduate Programs in Health Promotion and Comunity Empowerment, Universitas Sebelas Maret, Surakarta, IndonesiaMasters Program in Family Medicine, Universitas Sebelas Maret, Surakarta, IndonesiaMaster Program in Nutrition, Universitas Sebelas Maret, Surakarta, IndonesiaMaster Program in Public Health, Universitas Sebelas Maret, Surakarta, Indonesia BACKGROUND A geographic information system (GIS) is required to guide interventions into prevent ARI and reduce the incidence of cases. The purpose of this study is to find out whether there is spatial autocorrelation in the spread of ARI; to obtain spatial information about the ARI risk factors, the ARI case map, and the factors related to the occurrence of ARI. METHODS This study is a quantitative research study with case-control study design.The sampling technique was purposive sampling. Spatial analysis techniques used were buffers and spatial clustering. The measurement of spatial autocorrelation was calculated by Moran’s Index method. RESULTS The risk factors for ARI based on the history of ARI disease were cough and cold in the last one year, and cough and cold lasting more than two weeks (OR = 15.691; 95% CI = 6.558–37.546 and OR = 6.645; 95% CI = 3.013–14.652). The risk factors for ARI based on the house physical environment were the room density, existence of glass windows on the house roof, electricity as a light source, presence of family members who smoke, and proximity to pollution exposure and waste disposal. Moran's Index value shows positive spatial autocorrelation. CONCLUSIONS GIS produces ARI distribution patterns. Based on the results of the cluster, the incidence of ARI cases in this region are interrelated or one case with another case is closely related, due to its close position. http://mji.ui.ac.id/journal/index.php/mji/article/view/3093case studygeographic information systemhealth risk assessmentinfectious diseasesmap
collection DOAJ
language English
format Article
sources DOAJ
author Hariza Adnani
Achmad Arman Subiyanto
Diffah Hanim
Endang Sutisna Sulaeman
spellingShingle Hariza Adnani
Achmad Arman Subiyanto
Diffah Hanim
Endang Sutisna Sulaeman
Risk factor mapping and case map of environmentally based disease in Yogyakarta
Medical Journal of Indonesia
case study
geographic information system
health risk assessment
infectious diseases
map
author_facet Hariza Adnani
Achmad Arman Subiyanto
Diffah Hanim
Endang Sutisna Sulaeman
author_sort Hariza Adnani
title Risk factor mapping and case map of environmentally based disease in Yogyakarta
title_short Risk factor mapping and case map of environmentally based disease in Yogyakarta
title_full Risk factor mapping and case map of environmentally based disease in Yogyakarta
title_fullStr Risk factor mapping and case map of environmentally based disease in Yogyakarta
title_full_unstemmed Risk factor mapping and case map of environmentally based disease in Yogyakarta
title_sort risk factor mapping and case map of environmentally based disease in yogyakarta
publisher Faculty of Medicine Universitas Indonesia
series Medical Journal of Indonesia
issn 0853-1773
2252-8083
publishDate 2019-08-01
description BACKGROUND A geographic information system (GIS) is required to guide interventions into prevent ARI and reduce the incidence of cases. The purpose of this study is to find out whether there is spatial autocorrelation in the spread of ARI; to obtain spatial information about the ARI risk factors, the ARI case map, and the factors related to the occurrence of ARI. METHODS This study is a quantitative research study with case-control study design.The sampling technique was purposive sampling. Spatial analysis techniques used were buffers and spatial clustering. The measurement of spatial autocorrelation was calculated by Moran’s Index method. RESULTS The risk factors for ARI based on the history of ARI disease were cough and cold in the last one year, and cough and cold lasting more than two weeks (OR = 15.691; 95% CI = 6.558–37.546 and OR = 6.645; 95% CI = 3.013–14.652). The risk factors for ARI based on the house physical environment were the room density, existence of glass windows on the house roof, electricity as a light source, presence of family members who smoke, and proximity to pollution exposure and waste disposal. Moran's Index value shows positive spatial autocorrelation. CONCLUSIONS GIS produces ARI distribution patterns. Based on the results of the cluster, the incidence of ARI cases in this region are interrelated or one case with another case is closely related, due to its close position.
topic case study
geographic information system
health risk assessment
infectious diseases
map
url http://mji.ui.ac.id/journal/index.php/mji/article/view/3093
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AT achmadarmansubiyanto riskfactormappingandcasemapofenvironmentallybaseddiseaseinyogyakarta
AT diffahhanim riskfactormappingandcasemapofenvironmentallybaseddiseaseinyogyakarta
AT endangsutisnasulaeman riskfactormappingandcasemapofenvironmentallybaseddiseaseinyogyakarta
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