Key Takeaways
- In 2023, approximately 712 million people worldwide lived in extreme poverty, defined as less than $2.15 per day in 2017 PPP terms, accounting for 8.7% of the global population
- As of 2022, the global extreme poverty rate stood at 8.5%, with a total of 689 million people affected, down from 1.9 billion in 1990
- In 2019, before the COVID-19 pandemic, 648 million people were in extreme poverty globally, representing 8.4% of the world population using the $1.90/day line (updated to $2.15)
- In Sub-Saharan Africa, 429 million people (35%) lived in extreme poverty in 2022, hosting nearly 60% of the world's poor
- South Asia had 207 million in extreme poverty in 2022 (10.4% rate), down from higher levels pre-pandemic
- In East Asia and Pacific, extreme poverty affected 24 million people (0.5%) in 2022, a remarkable decline
- Niger had the highest multidimensional poverty rate at 74.8% in 2023 MPI
- Globally, multidimensional poverty headcount was 19.1% in 2023, with 1.1 billion poor, intense deprivation average 44.3%
- In India, 16.4% (234 million) multidimensionally poor in 2019-21, down from 55% in 2005-06
- In 2022, 333 million children under 5 (one in six) stunted due to poverty-related malnutrition
- 148 million children under 5 stunted in 2022, 35 million wasted, mostly in poorest households
- 258 million children out of school globally in 2023, 60% from poorest quintiles
- Since 1990, 1.1 billion people escaped extreme poverty, fastest decline 2000-2015 at 1% annually
- COVID-19 pushed 70-95 million extra into extreme poverty in 2020, largest reversal since 1990
- Extreme poverty share fell from 38% in 1990 to 8.7% in 2023, but absolute numbers stagnant post-2014
Progress against extreme poverty is real but has stalled recently.
Child and Vulnerable Groups Poverty
Child and Vulnerable Groups Poverty Interpretation
Global Poverty Rates
Global Poverty Rates Interpretation
Multidimensional Poverty
Multidimensional Poverty Interpretation
Regional and Country-Specific Poverty
Regional and Country-Specific Poverty Interpretation
Trends and Projections
Trends and Projections Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
David Kowalski. (2026, February 13). Poverty In The World Statistics. Gitnux. https://gitnux.org/poverty-in-the-world-statistics
David Kowalski. "Poverty In The World Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/poverty-in-the-world-statistics.
David Kowalski. 2026. "Poverty In The World Statistics." Gitnux. https://gitnux.org/poverty-in-the-world-statistics.
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