7 Conclusion Myanmar's multidimensional poverty is widespread and affects nearly two-thirds of Myanmar's population either directly or through vulnerability to future poverty. One in three people (32.6%, approximately 17.9 million) are multidimensionally poor, and a further 19.5 million are at risk. Applying an adapted MPI to the PPS 2025 data moves beyond income measurement to capture the overlapping deprivations, encompassing education, health and living standards, which shape household wellbeing during a period of compounding conflict, macroeconomic instability and recurrent natural hazards. The analysis establishes not only where poverty is concentrated and how deep it runs, but what kind of poverty households experience and why similar poverty levels demand different responses in different contexts. That last question, what kind, is the analytical contribution that headline headcount figures cannot provide. Poverty in Myanmar is shaped by a tension between severity and scale, requiring attention to both the deepest deprivation and the largest concentrations of poor people. Rakhine and Kayah record the highest poverty incidence and intensity nationally, with over 68 percent of their populations multidimensionally poor and poor households deprived in roughly half of all indicators simultaneously. But the largest absolute concentrations of poor people are found in Ayeyarwady, Sagaing, Mandalay and Shan, which together account for roughly half of the 17.9 million MPI-poor nationally despite recording only moderate MPI scores. Effective responses require balancing depth-focused engagement in the most severely affected areas with scale-oriented coverage where poverty is widespread but less acute. Township-level evidence further shows that state-level averages conceal substantial within-state disparity, with poverty clustering in specific sub-areas regardless of the broader state/region profile. Poverty is driven by different combinations of structural disadvantages, contextual pressures and repeated shocks. The analysis distinguishes two interacting drivers, namely structural household disadvantages and contextual area-level conditions, whose relative weight varies considerably across states/regions. In Kayah, Rakhine and Ayeyarwady, observed poverty substantially exceeds what household characteristics alone would predict, indicating that conflict, displacement, restricted mobility and disrupted services are the binding constraints. In Kachin, Mon and Mandalay, poverty aligns closely with structural predictions, indicating that long-standing disadvantages in education, employment and income are the primary drivers rather than acute contextual shocks. A third pattern, high structural vulnerability partially moderated by favourable area-level conditions, characterizes urban areas such as Yangon, where households are not currently classified as poor but are highly sensitive to disruption. Repeated shocks compound all three patterns: economic shocks affect more than half of households nationally; conflict shocks carry the highest amplification effect of any shock type; and the cumulative effects of economic, natural hazard, conflict and health shocks erode coping capacity and accelerate transitions from vulnerability into deep poverty. L AYE R S O F DE P R I VAT I O N : M u l t i di m en si on a l Pov er t y i n M y anmar 47