UBOS MPI Census: Lack of Insurance Health leading cause of multidimensional poverty in Uganda.

Mar 26, 2026 - 17:22
Mar 26, 2026 - 17:24
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UBOS MPI Census: Lack of Insurance Health leading cause of  multidimensional poverty in Uganda.
Minister Amos Lugolobi launches the MPI on Thursday as ED UBOS Dr. Chris Mukisa looks on

According to experts, The multidimensional poverty index (MPI) is a measure of poverty that captures simultaneous deprivation experienced by individuals across multiple dimensions of life including in health, income, basic services, such as hunger, lack of shelter, fear of the future, access to school, inability to read, powerless among others.  

Uganda’s Multidimensional poverty index was reported as at 0.270 with the highest sub region reported as Karamoja at 0.569 and the lowest as Kampala at 0.88 meaning that the Kampala ‘s figure as it nears to zero represents a better living condition for individual in the city.

The findings in the MPI particularly reveal that Nationally in every 100 individuals 27 are deprived across all multiple dimensions.

Specifically, healthy insurance have been reported as the highest among the deprived individual representing 52.6% followed by cooking fuel and technology at 51.6%. This according to the report indicate highest in rural than in urban areas.

While commissioning the MPI report, State Minister Amos Lugolobi from the Finance Ministry said that now that Uganda has the baseline data, there is a need for policy makers to use the statistics in the MPI Census 2024, to target areas revealed in the report for evidence planning.

“Am glad that today UBOS has supplies us with Statistics to plan for the country. The challenge is about the users. The MPI indication of the 0.270 poverty level report means we are not doing badly looking at the numbers. For the planner we have a job to asses the extent of the difference variables to improve them” he said.

While giving his opening remarks, at the dissemination event held on 26the March 2026 at Statistics House, the Executive Director UBOS, Dr. Chris Mukiza noted the importance of the multidimensional poverty index census (MPI) indicators in understanding individual poverty levels and how far it has contributed in achieving SDGs.

He said according to research, it has revealed that the household poverty is higher in new district that the established ones showing that income ends up with the local elites calling upon policy makers to utilize the report

“When implementing new targets, I urge the policy makers to take a kin interest in the report aimed at ending poverty as we prepare the next national budget” he said

Hon. Ekanya Geoffrey from the Parliament committee on finance, called for enhancement of usage of statistics from UBOS by MDAs to target interventions.

He pointed out one issue that “Climate change loss and damage aspect needs to be considered in the budget to take care of the vulnerable people who depend on natural resources such as fishing, forestry and agriculture” he said.

The Acting Chairperson, of the UBOS Board of Directors Mrs. Irene Birungi Mugisha said the board is taking pride in overseeing fostering quality and reliable statistics by UBOS focusing on achieveing the goal of eliminating poverty.

“Quality statistics is a strategic asset that enables informed decisions to improve livelihoods, supporting development plans, programs essential to the development process.

UNDP Representative said that the MPI is a key tool in the modern I exclusive society in enhancing budget allocation when it comes to elimination of poverty, achieving various SDGs and that the UN body is looking forward to witness better program designs of social protection, climate resilience among others.

In the finding of the multidimensional poverty index presented by Stephen Balya of UBOS, he mentioned that following the census as a source of information, the report is tackling various SDGs including SDG 1 on “eliminating poverty of all forms beyond only income poverty” among other.

He said the survey focused on different dimensions, indicators, and deprivation cut-offs used to compute deprivation status including: source of energy, access to clean drinking water, unemployment, financial services, housing materials, cooking fuel and technology, asset ownership among others.  

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