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ORIGINAL ARTICLE
Year : 2018  |  Volume : 62  |  Issue : 2  |  Page : 75-81

Block-wise comprehensive health index in Gadchiroli: A tribal district in Maharashtra


Professor, Department of Community Medicine, Bharati Vidyapeeth Deemed University Medical College, Pune, Maharashtra, India

Correspondence Address:
Prakash Prabhakarrao Doke
Department of Community Medicine, Bharati Vidyapeeth Deemed University Medical College, Satara Road, Dhanakawadi, Pune - 411 043, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijph.IJPH_247_16

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Background: The National Health Mission expects bottom-up approach for preparing Project Implementation Plan and also expects special attention toward tribal areas. Some district-level health information is available from national health surveys, but subdistrict-level information is mostly not available. Gadchiroli is the farthest district from the state capital. There are 12 blocks in the district. It is a notified tribal district having 8.61%–81.50% tribal population in different blocks and block-wise urbanization varies from 0.00% to 37.10%. Objectives: The objective was to assess community health status at block level in Gadchiroli district and then develop comprehensive health index for ranking the blocks. Methods: The author has used available secondary data sources including Census, Survey of Cause of Death scheme, health management information system, Directorate of Economics and Statistics, and Maharashtra Medical Council. Ten indicators were selected after discussion with public health specialists to evolve comprehensive health index. Blocks having best statistic in each indicator were given 100 marks and other blocks were given proportionate marks. Thus, the highest possible score for any block was 1000. Results: The range of block-wise score was from 424 to 781. The highest scoring block was Gadchiroli and was an outlier. The comprehensive score was having correlation with urbanization, r = 0.63 (95% confidence limits, 0.09–0.88). After principal component analysis, the extracted three components were responsible for most of the variations. Conclusions: Reasonably reliable and valid block-wise data are available to carry out community health assessment and develop comprehensive health index. The index is useful for comparison among blocks.


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