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Estimation of Life Expectancy from Infant Mortality Rate at Districts Level

Author Affiliations

  • 1 Public Health Foundation of India, Fifth Floor, Plot No. 47, Sector 44, Institutional Area Gurgaon -122002 Haryana, INDIA

Int. Res. J. Social Sci., Volume 4, Issue (6), Pages 52-63, June,14 (2015)

Abstract

Monitoring the districts life expectancies is necessary for health policies and planning but it is difficult to get direct estimates because of the inaccessibility of age-specific death rates at the district level. Thus, the present study meets the challenges for the estimation of district level life expectancy. In this paper, I focused on the generation of mortality model for estimation of life expectancy at district level up to age 100+ and hence further to compute the abridged life table. For the development of the model, study exploited the age-specific death rate data from Sample Registration System for the period 1971-2010. It has been found that the linear regression model is the best fit method. The Study generated the regression model for India and all states by sex and then applied to districts of those states. The Study created the model by taking the only input as Infant mortality rate because at district level only the information on Infant and Child mortality is available, complete death information is unavailable. This study presents the life expectancies for districts of major states of India for the census year 2001. Examination for district variation reveals that life expectancy at birth is highest for district Udupi of state Karnataka and lowest for Kargil of Jammu and Kashmir. For themale, highest LEB is observed in Pune and Sangli of Maharashtra; for female, it is in Udupi of Karnataka. Thus, the study noted significant variation in life expectancy values across gender and district as well. At the same time, it has also brought out the extent of variation across districts within and between states in the country. Hence, results clearly affirm that the united approach of health interventions and policies will not work properly and henceforth may not help in reducing mortality differentials among districts. So, study recommends for health policies at small area level.

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