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Prime Determinants that Influence "Life Expectancy":An Analysis across Indian States Using Multiple Regressions


Affiliations
1 Department of Operations Management & Quantitative Techniques, Indian Institute of Management, Indore, Madhya Pradesh, Pin Code-453556, India
 

Background/Objectives: To explore life expectancy in Indian states and also to determine how life expectancy is influenced by determinants such as gender, per-capita income, gender, age and area.

Method/Statistical Analysis: An extensive literature review from various developing and developed countries was initially done to understand the validity of indicators. Suitable indicators that can be focused for Indian states were selected. Secondary data from reliable sources and databases (For Ex. Like India Stat) were collected to perform this study. Regression analysis applying linear multiple regression and stepwise regression using Minitab software has been extensively used to arrive at the key determinants that affect life expectancy in various Indian states.

Findings: Overall, the analyses of the Indian states indicate that literacy rate, access of doctors in rural areas, income, preferences of states (inclusive of geography) by Indian people to reside play as key factors in determining and improving Life Expectancy. Findings include that females have a higher life expectancy than males living in the urban area in most of the Indian states. Also, findings indicate that literacy rate and net income plays a significant role in affecting life expectancy at birth positively in both urban and rural areas in all the states. Geography of the states also plays a key factor that affects life expectancy.

Findings indicate that people who live in mid and south India have a higher life expectancy than those residing in the northern states.

Improvement/Applications: Findings and analysis indicates the suitable steps, that the policy makers of state as well as centre need to take, that can enhance life expectancy and quality of life across the Indian states. Also certain other factors like type of diseases that inhibit life expectancy can be studied in future in detail as they may influence life expectancy in a higher way.


Keywords

Life Expectancy, Quality of Life, Policy, Indian States, Regression Modelling.
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Abstract Views: 267

PDF Views: 156




  • Prime Determinants that Influence "Life Expectancy":An Analysis across Indian States Using Multiple Regressions

Abstract Views: 267  |  PDF Views: 156

Authors

Senthil Kumar Anantharaman
Department of Operations Management & Quantitative Techniques, Indian Institute of Management, Indore, Madhya Pradesh, Pin Code-453556, India

Abstract


Background/Objectives: To explore life expectancy in Indian states and also to determine how life expectancy is influenced by determinants such as gender, per-capita income, gender, age and area.

Method/Statistical Analysis: An extensive literature review from various developing and developed countries was initially done to understand the validity of indicators. Suitable indicators that can be focused for Indian states were selected. Secondary data from reliable sources and databases (For Ex. Like India Stat) were collected to perform this study. Regression analysis applying linear multiple regression and stepwise regression using Minitab software has been extensively used to arrive at the key determinants that affect life expectancy in various Indian states.

Findings: Overall, the analyses of the Indian states indicate that literacy rate, access of doctors in rural areas, income, preferences of states (inclusive of geography) by Indian people to reside play as key factors in determining and improving Life Expectancy. Findings include that females have a higher life expectancy than males living in the urban area in most of the Indian states. Also, findings indicate that literacy rate and net income plays a significant role in affecting life expectancy at birth positively in both urban and rural areas in all the states. Geography of the states also plays a key factor that affects life expectancy.

Findings indicate that people who live in mid and south India have a higher life expectancy than those residing in the northern states.

Improvement/Applications: Findings and analysis indicates the suitable steps, that the policy makers of state as well as centre need to take, that can enhance life expectancy and quality of life across the Indian states. Also certain other factors like type of diseases that inhibit life expectancy can be studied in future in detail as they may influence life expectancy in a higher way.


Keywords


Life Expectancy, Quality of Life, Policy, Indian States, Regression Modelling.

References