mortality-table-india

This repository contains data on life expectancy in India and its states/union territories from 1970-75 to 2016-20.

Data Source

The data is sourced from the "SRS-Abridged_Life_Tables_2016-2020.pdf" published by the Office of the Registrar General & Census Commissioner, India. This publication presents abridged life tables based on the Sample Registration System (SRS) for the period 2016-20.

Data Description

• Life Expectancy at Birth (e₀⁰): This metric represents the average number of years a newborn is expected to live, assuming that age-specific mortality rates during the period of study remain constant.
• Life Expectancy at Age 1 (e₁⁰): This metric represents the average expected life span after surviving through the first year of life.
• Life Expectancy at Different Ages: The data also includes life expectancy for various age groups, such as infancy, age 10, age 30, and age 70.

Data Presentation

The data is presented in various forms, including:

• Tables: Detailed tables provide age-specific probabilities of death, number of survivors, and life expectancy for each age group, categorized by sex and residence (rural/urban).
• Charts: Charts visualize the trends and comparisons of life expectancy at birth, age 1, and other specific ages across different states/union territories and time periods.
• Trend Tables: These tables provide historical data on life expectancy at birth for different states/union territories, showcasing the changes over time.

Data Analysis

The data reveals significant insights into the mortality experience and longevity of the Indian population.

Key Observations:

• Overall Increase in Life Expectancy: Life expectancy at birth for India has increased steadily over the past decades. For the period 2016-20, the life expectancy at birth is estimated at 70.0 years, an increase of 0.3 years from 2015-19.
• Gender Gap in Life Expectancy: Females consistently exhibit higher life expectancy than males across all states/union territories.
• Regional Variations: Significant variations in life expectancy exist between different states/union territories. States like Kerala and Delhi show higher life expectancy compared to others like Bihar and Assam.

Data Usage

This data can be valuable for researchers, policymakers, and anyone interested in studying:

• Population Health: Analyze mortality trends, identify areas with lower life expectancy, and develop public health interventions.
• Demographic Changes: Understand the aging population and its implications for healthcare, social security, and economic development.
• Socioeconomic Inequalities: Explore the relationship between life expectancy and factors like income, education, and access to healthcare.

Note: Please note that the "Jammu & Kashmir" data represents the erstwhile state, including the present-day Union Territories of Jammu & Kashmir and Ladakh, as the data pertains to the period 2016-2019. Additionally, imputation based on a geographic approach was used to generate life tables for cases with no reported deaths in specific age groups and sex. You may want to independently verify the accuracy of the imputed values.