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Ranking and clustering Iranian provinces based on important health indicators of vital horoscope in rural areas by using multivariate methods
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Ghodratollah Roshanaei   , Maliheh Safari , Javad Faradmal , Manocher Karami , Zahra Kouselo |
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Abstract: (6591 Views) |
| Introduction: Gaining information about the condition of a society from various aspects is one of the main requirements for planning. Assessment and determination of social condition would help the executives to quickly estimate the essential requirements. In regard to the lack of proper ranking and clustering information related to provinces with the use of related variables due to health indicators of vital horoscope in rural areas, we conducted this study with the aim of ranking and clustering of provinces using these indicators.
Materials and methods: Provinces were ranked based on the group of vital horoscope indices related to the rural areas published by the Ministry of Health. Multivariate analysis of the principal components and factorial analysis were used to rank the provinces and cluster analysis was applied to specify the homogeneous provinces. The data were analyzed by using SPSS16 and R3.1.1 software.
Results: Three extracted factors of mortality, fertility and population, and performance indices were composed more than 86% of data variations. Ranking based on the first factor indicated that south and north Khorasan and Kordestan conditions were unfavorable, while, Tehran and Mazandaran were in favorable conditions. The cluster analysis also placed the similar provinces in terms of health and social indicators in one group.
Conclusion: This study showed that the provinces with favorable socio-economic conditions were those with closest distance to the Capital and also those with more social and cultural exchanges due to the tourist industries. Since the socio-economic facilities are not distributed equally through the country, therefore, more equitable socio-economic attention and care to more deprived areas seems essential, which eventually would lead to the growth and development of health indicators in the country |
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| Keywords: Cluster analysis, Statistical Factor Analysis, Vital Statistics, Rural Population |
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Full-Text [PDF 631 kb]
(1847 Downloads)
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Type of Study: Research |
Subject:
General
Received: 2014/12/3 | Accepted: 2015/06/27 | Published: 2015/12/14
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