MODELLING ASSOCIATIONS BETWEEN EXTREME POVERTY TRAJECTORIES AND POPULATION GROWTH FOR HEALTH SYSTEMS PLANNING
Author(s)
Abdul Ajeed Mohathasim Billah, Sr., RPh, PhD, Kiruba M Mohandoss, PhD.
Professor, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, India.
Professor, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, India.
OBJECTIVES: Long-term shifts in extreme poverty and population size shape future pressures on health systems, yet the interaction between these trajectories is not well characterised. This study explored the association between national poverty trends and population growth to inform strategic planning in settings where demographic expansion may counteract gains in poverty reduction.
METHODS: An ecological, longitudinal analysis was undertaken using publicly available datasets on extreme poverty from the World Bank Poverty and Inequality Platform, processed by “ourworldindata.org”, and historical, contemporary population data compiled from HYDE, Gapminder, and United Nations World Population Prospects. Countries with at least ten matched observations between 1990 and 2023 were included. Linear slopes describing the annual change in extreme poverty were computed for each country and used to group trajectories as rapid reduction, moderate reduction, minimal change, or worsening. Population growth rates over the same period were derived. Patterns were examined descriptively and using simple linear models, adjusting for world region and income group. Absolute numbers of people living in extreme poverty were estimated to contextualise implications for health-systems demand.
RESULTS: Rapid poverty reduction was generally observed in countries with stable or slow population growth, whereas regions with limited improvement or worsening poverty had higher average population growth. In several low-income settings, falling poverty percentages coincided with rising absolute numbers of people in extreme poverty due to demographic expansion. Associations remained after adjustment for region and income level.
CONCLUSIONS: Countries experiencing modest poverty reduction alongside sustained population growth may face increased future pressure on health-system capacity and financial protection schemes. Integrating poverty and demographic trends into planning frameworks can support more realistic forecasting of health-service needs.
METHODS: An ecological, longitudinal analysis was undertaken using publicly available datasets on extreme poverty from the World Bank Poverty and Inequality Platform, processed by “ourworldindata.org”, and historical, contemporary population data compiled from HYDE, Gapminder, and United Nations World Population Prospects. Countries with at least ten matched observations between 1990 and 2023 were included. Linear slopes describing the annual change in extreme poverty were computed for each country and used to group trajectories as rapid reduction, moderate reduction, minimal change, or worsening. Population growth rates over the same period were derived. Patterns were examined descriptively and using simple linear models, adjusting for world region and income group. Absolute numbers of people living in extreme poverty were estimated to contextualise implications for health-systems demand.
RESULTS: Rapid poverty reduction was generally observed in countries with stable or slow population growth, whereas regions with limited improvement or worsening poverty had higher average population growth. In several low-income settings, falling poverty percentages coincided with rising absolute numbers of people in extreme poverty due to demographic expansion. Associations remained after adjustment for region and income level.
CONCLUSIONS: Countries experiencing modest poverty reduction alongside sustained population growth may face increased future pressure on health-system capacity and financial protection schemes. Integrating poverty and demographic trends into planning frameworks can support more realistic forecasting of health-service needs.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
RWD96
Topic
Real World Data & Information Systems
Topic Subcategory
Distributed Data & Research Networks
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, SDC: Reproductive & Sexual Health, STA: Multiple/Other Specialized Treatments