Short Abstract:

Utilizing NFHS-5 (2019-21) data, we assessed life expectancy and pre-mature mortality disparities between multidimensionally poor and non-poor. 23% multidimensional poverty was estimated using 11 indicators across 3 dimensions. The birth history and household reported deaths have been utilised for mortality estimation; the multidimensionally poor showed a 4-year lower life expectancy at birth.

Long Abstract:

Background

In the past decade, significant strides have been made globally to combat poverty and enhance overall health, yet disparities persist both within and between nations. The global multidimensional poverty index (G-MPI) indicates a notable decline in multidimensional poverty, from 32% (1.7 billion people) in 2010 to 19% (1.2 billion people) in 2022. Sub-Saharan Africa and South Asia have the largest populations of poor individuals. Despite a rise in global average life expectancy from 66.8 years in 2000 to 73.4 years in 2019, non-communicable diseases (NCDs) like cardiovascular diseases, cancer, and respiratory conditions continue to be major contributors to global mortality, particularly in low- and middle-income countries (LMICs).

The Oxford Poverty and Human Development Initiative (OPHI) and the United Nations Development Program (UNDP) have been pivotal in providing multidimensional poverty estimates through G-MPI, assessing deprivation in health, education, and living standards. Some countries have adapted this framework to their contexts by including additional indicators such as food insecurity, healthcare access, school attendance, and water reliability. Literature consistently highlights the strong association between poverty and adverse health outcomes, including higher morbidity, disability, and premature mortality. Factors beyond monetary poverty, such as household wealth and socio-economic circumstances, significantly influence health disparities and life expectancy.

India, with a rapidly growing economy and a vast population, has made substantial progress in reducing multidimensional poverty from 55% in 2005-06 to 16% in 2019-21. Simultaneously, life expectancy has risen from 63 years in 2000 to 70 years in 2020, and the infant mortality rate has significantly decreased. However, non-communicable diseases (NCDs) now account for a significant portion (66%) of all deaths in India in 2019, emphasizing the necessity for targeted interventions to address persistent inequalities.

This study aims to provide essential estimates of life expectancy and premature mortality among multidimensionally poor and non-poor individuals in India. It seeks to address the uneven progress in reducing multidimensional poverty, the concerning rise in premature mortality, and the dearth of studies examining the relationship between multidimensional poverty and health outcomes, particularly longevity and premature mortality. By exploring these dynamics, this study aims to deepen our understanding of how multidimensional poverty affects life expectancy and mortality in India, contributing to a more nuanced comprehension of the intricate interplay between poverty and health outcomes.

Methodology

This study utilized data from the fifth National Family and Health Survey (NFHS) conducted between 2019-21, a cross-sectional multi-round survey that provides comprehensive information on health, nutrition, and family welfare at national and sub-national levels. The survey collected information from 2,843,917 individuals in 636,699 households using two-stage stratified random sampling. The data collected included various indicators related to health, education, and standard of living.

To estimate multidimensional poverty, the Alkire-Foster (A-F) methodology was employed. This method uses a dual cut-off counting approach to categorize individuals as multidimensionally poor or non-poor. The study incorporated three dimensions - education, health, and standard of living - with each dimension being assigned an equal weight of 0.33. Among the 11 indicators used, two were related to education, three to health, and six to standard of living. The incidence of poverty (H), intensity of poverty (A), and Multidimensional Poverty Index (MPI) were calculated using these indicators. Notably, the dimensions used in MPI construction did not include any mortality indicators.

Regarding life expectancy, premature mortality, and adult mortality estimation, the study employed the life table method following a methodology developed by Gupta and Sudharsanan (2021). Person-years and deaths were estimated for various age groups, and the age-specific death rate (ASDR) was calculated. The ASDR was utilized to construct abridged life tables, which were then used to estimate life expectancy at birth, premature mortality (0q70), and adult mortality (45q15). Premature mortality (0q70) was defined as the probability of death under the age of 70 years, while adult mortality (45q15) was defined as the probability of death at the working age (from 15 to 60 years).

Life tables were constructed separately for multidimensionally poor and non-poor individuals and further stratified by sex (male and female). Confidence intervals for each specified group were estimated using popular bootstrap methods using publically available spreadsheet of Monte Carlo simulation.

Result

Multidimensional Poverty Levels: 23% of India's population experienced multidimensional poverty, 26% was vulnerable, and 6% endured severe poverty (Table 1). There were substantial regional variations, with states such as Bihar (46%), followed by Uttar Pradesh (35%) and Jharkhand (34%) had the highest prevalence rates, whereas Lakshadweep (1.9%), Goa (2.3%), and Kerala (2.5%) having the lowest levels of multidimensional poverty.

Life Expectancy at Birth (LEB): Life expectancy at birth was found to be 4 years lower among those experiencing multidimensional poverty compared to those who were not multidimensionally poor (poor: 66.1 years vs non-poor 69.6 years). This reduction in life expectancy was consistent across different caste and religion groups in India. The disparity in life expectancy between multidimensionally poor and non-poor individuals decreased at older ages.

Gender Disparities in Life Expectancy: Notably, there was a gender-based difference in life expectancy among individuals living with and without multidimensional poverty. The gap in life expectancy at birth between multidimensionally poor and non-poor males was 5.2 years, significantly higher than the 1.6 years observed among females.

Premature Mortality (0q70): Premature mortality (probability of death under age 70) was significantly higher among those experiencing multidimensional poverty. The males, in particular, faced a higher burden of premature mortality, emphasizing the health challenges associated with multidimensional poverty.

Adult Mortality (45q15): The pattern of adult mortality (probability of death at working ages, 15-60 years) indicated a higher mortality rate among those living in multidimensional poverty. Differences in adult mortality between the poor and non-poor were more pronounced among males.

Conclusion

These findings underline the critical need to address multidimensional poverty comprehensively, considering its profound impact on life expectancy, health outcomes, and mortality rates. Tailored interventions addressing regional disparities and gender-specific challenges are imperative to improve the overall well-being and life prospects of those affected by multidimensional poverty in India.