Abstract
Nigeria currently has the highest number of people living on less than USD1.90 a day, becoming what some analysts labeled “the poverty capital of the world.“ This article explores the multiple dimensions and predictors of household poverty in Nigeria using the 2018 Demographic and Health Survey data (n = 40,427). Results from Chi-square analysis indicate significant regional disparities in multidimensional poverty, which is endemic in the Northwest and Northeast regions that constitute 75.3% of Nigeria’s poorest households, 62.3% of household heads without formal education, and about half (49.7%) of households lacking access to electricity. Logistic regression results show that access to electricity is the most significant predictor of poverty in Nigeria, with an odds ratio (OR) of 10.46, followed by education (OR = 1.99), place of residence (OR = 0.37), land ownership (OR = 0.58), livestock ownership (0.57), number of bedrooms (1.32), and gender (0.73). Other significant predictors are drinking water sources, sanitation facilities, cooking fuel, and housing conditions. Reducing multidimensional poverty requires improving electricity supply and human development interventions in education, water, sanitation, and healthcare, targeting deprived households. These are essential for achieving sustainable development.
Similar content being viewed by others
References
Abubakar, I. R. (2019). Factors influencing household access to drinking water in Nigeria. Utilities Policy, 58, 40–51
Abubakar, I. R. (2021). Predictors of inequalities in land ownership among Nigerian households: Implications for sustainable development’. Land Use Policy, 101, 105194
Achia, T. N., Wangombe, A., & Khadioli, N. (2010). A logistic regression model to identify key determinants of poverty using demographic and health survey data. European Journal of Social Sciences, 13(1), 38–45
Adeoti, A. I. (2014). Trend and determinants of multidimensional poverty in rural Nigeria’. Journal of Development and Agricultural Economics, 6(5), 220–231
Aguilar, G. R., & Sumner, A. (2020). Who are the world’s poor? A new profile of global multidimensional poverty. World Development, 126, 104716
Aigbokhan, B. E. (2008). Growth, inequality, and poverty in Nigeria’. Discussion paper 3, prepared for United Nations Economic Commission for Africa (UNECA). Addis Ababa, Ethiopia: UNECA
Ajakaiye, O., Jerome, A. T., Olaniyan, O., Mahrt, K., & Alaba, O. A. (2016). Spatial and temporal multidimensional poverty in Nigeria. Growth and poverty in sub-Saharan Africa, 218
Alkire, S., Roche, J. M., & Vaz, A. (2017). Changes over time in multidimensional poverty: Methodology and results for 34 countries. World Development, 94, 232–249
Alkire, S., & Robles, G. (2016). Global Multidimensional Poverty Index 2016. University of Oxford, OPHI Briefing 41
Anand, S., & Sen, A. (1997). Concepts or Human Development and Poverty! A Multidimensional Perspective. UNDP, Poverty and human development: Human development papers: 1–20
Aodu, A. (2008). ‘Declare State of Emergency on Poverty in the North- Soludo’. 20 July 2008. Available: https://allafrica.com/stories/200807220083.html, [accessed: 06 August 2021]
Asselin, L. M. (2009). Analysis of multidimensional poverty: Theory and case studies. Economic Studies in Inequality, Social Exclusion and Well-Being (7 vol.). Ottawa: Springer Science & Business Media
Beegle, K., Christiaensen, L., Dabalen, A., & Gaddis, I. (2016). Poverty in a rising Africa. Washington: The World Bank
Bossert, W., Chakravarty, S. R., & D’Ambrosio, C. (2013). Multidimensional poverty and material deprivation with discrete data’. Review of Income and Wealth, 59(1), 29–43
Bourguignon, F., & Chakravarty, S. R. (2019). The measurement of multidimensional poverty’. Poverty, Social Exclusion and Stochastic Dominance (pp. 83–107). Singapore: Springer
Calvo, C. (2008). Vulnerability to multidimensional poverty: Peru, 1998–2002’. World Development, 36(6), 1011–1020
CIA (Central Intelligence Agency) (2021). Nigeria - The World Factbook. CIA, 30 November 2021. Available online: https://www.cia.gov/the-world-factbook/countries/nigeria/ [accessed: 06 December 2020]
Dapel, Z. (2018). Poverty in Nigeria: Understanding and Bridging the Divide between North and South’. Washington DC: Center for Global Development. Available: https://www.cgdev.org/blog/poverty-nigeria-understanding-and-bridging-divide-between-north-and-south [accessed: 06 June 2020]
Deng, Q., Li, E., & Zhang, P. (2020). Livelihood sustainability and dynamic mechanisms of rural households out of poverty: An empirical analysis of Hua County, Henan Province, China. Habitat International, 99, 102160
Duclos, J. Y., Sahn, D., & Younger, S. D. (2006). Robust multidimensional spatial poverty comparisons in Ghana, Madagascar, and Uganda. The World Bank Economic Review, 20(1), 91–113
Program, D. H. S. (2019). Survey Dataset Files. Nigeria: Standard DHS, 2018. The DHS Program. Available online: https://dhsprogram.com/data/dataset/Nigeria_Standard-DHS_2018.cfm?flag=1, [Accessed: 5 February 2020]
Gazzeh, K., & Abubakar, I. R. (2018). Regional disparity in access to basic public services in Saudi Arabia: A sustainability challenge. Utilities Policy, 52, 70–80
Gounder, R., & Xing, Z. (2012). Impact of education and health on poverty reduction: Monetary and non-monetary evidence from Fiji. Economic Modelling, 29(3), 787–794
Gulyani, S., Bassett, E. M., & Talukdar, D. (2014). A tale of two cities: A multi-dimensional portrait of poverty and living conditions in the slums of Dakar and Nairobi. Habitat International, 43, 98–107
Habyarimana, F., Zewotir, T., & Ramroop, S. (2015). Analysis of demographic and health survey to measure poverty of household in Rwanda. African Population Studies, 29(1), 1472–1482
Hanandita, W., & Tampubolon, G. (2016). Multidimensional poverty in Indonesia: trend over the last decade (2003–2013). Social Indicators Research, 128(2), 559–587
Ifegbesan, A. P., Rampedi, I. T., & Annegarn, H. J. (2016). Nigerian households’ cooking energy use, determinants of choice, and some implications for human health and environmental sustainability. Habitat International, 55, 17–24
Leal Filho, W., Eustachio, J. H. P., Dinis, M. A. P., Sharifi, A., Venkatesan, M., Donkor, F. K. … Vargas-Hernández, J. (2022). Transient poverty in a sustainable development context (pp. 1–14). International Journal of Sustainable Development & World Ecology
Kazeem, Y. (2018). Nigeria has become the poverty capital of the world. 25 June 2018. Available online: https://qz.com/africa/1313380/nigerias-has-the-highest-rate-of-extreme-poverty-globally/ [accessed: 16 May 2021]
Mitra, S., Posarac, A., & Vick, B. (2013). Disability and poverty in developing countries: a multidimensional study’. World Development, 41, 1–18
National Universities Commission (2020). Nigerian Universities. Available online: https://www.nuc.edu.ng/nigerian-univerisities/ [accessed: 06 June 2021]
NBS (National Bureau of Statistics). (2010). Nigeria Poverty Profile, 2010. Nigeria: NBS: Abuja
NBS. (2016). Formal and Informal Sector Split of Gross Domestic Product 2015’. Abuja, Nigeria: NBS
NPC & ICF International. (2019). Nigeria Demographic and Health Survey, 2018. Abuja, Nigeria, and Rockville. Maryland, USA: NPC and ICF International
Oxford Poverty and Human Development Initiative (OPHI) (2019). Nigeria Country Briefing. Multidimentional Poverty Index Databank. University of Oxford. Available online: https://ophi.org.uk/wp-content/uploads/CB_NGA_2019_2.pdf [accessed: 03 March 2021]
Padda, I. U. H., & Hameed, A. (2018). Estimating Multidimensional Poverty Levels in Rural Pakistan: A Contribution to Sustainable Development Policies. Journal of Cleaner Production, 197(1), 435–442
Pasha, A. (2017). Regional perspectives on the multidimensional poverty index’. World Development, 94, 268–285
Rana, R., & Singhal, R. (2015). Chi-square test and its application in hypothesis testing. Journal of the Practice of Cardiovascular Sciences, 1(1), 69, 1–3
Robinson, C. (2019). Energy poverty and gender in England: A spatial perspective. Geoforum, 104, 222–233
Rogan, M. (2016). Gender and multidimensional poverty in South Africa: Applying the global multidimensional poverty index (MPI). Social Indicators Research, 126(3), 987–1006
Santos, M. E., & Villatoro, P. (2018). A multidimensional poverty index for Latin America’. Review of Income and Wealth, 64(1), 52–82
Sperandei, S. (2014). Understanding logistic regression analysis. Biochemia medica, 24(1), 12–18
Stoeffler, Q., Alwang, J., Mills, B., & Taruvinga, N. (2016). Multidimensional poverty in crisis: Lessons from Zimbabwe. The journal of development studies, 52(3), 428–446
United Nations. (2018). The Sustainable Development Goals Report 2018. New York: United Nations
UNDP. (2018). 2018 Human Development Data Bank. New York: United Nations
Wagle, U. (2005). Multidimensional poverty measurement with economic well-being, capability, and social inclusion: a case from Kathmandu, Nepal. Journal of Human Development, 6(3), 301–328
Wedgwood, R. (2007). Education and poverty reduction in Tanzania. International Journal of Educational Development, 27(4), 383–396
WHO. (2017). Progress on drinking water, sanitation, and hygiene: 2017 update and SDG Baseline. Geneva: WHO Library Cataloguing-in-Publication Data
World Bank (2017). A Wake Up Call: Nigeria Water Supply, Sanitation, and Hygiene Poverty Diagnostic. WASH Poverty Diagnostic. Washington, DC: World Bank
World Bank. (2018). Poverty and Shared Prosperity 2018: Piecing Together the Poverty Puzzle. Washington, DC: The World Bank
World Bank, World Development Indicators 2019. DataBank. Washington, DC: World Bank., & < (2019a). https://databank.worldbank.org/source/world-development-indicators#, [accessed: 16 October 2019]
Word Bank (2019b). Nigeria At-A-Glance. Available online: https://www.worldbank.org/en/country/nigeria. [accessed: 18 May 2021]
Yu, J. (2013). Multidimensional poverty in China: Findings based on the CHNS. Social Indicators Research, 112(2), 315–336
Yuan, Y., Xu, M., Cao, X., & Liu, S. (2018). Exploring urban-rural disparity of the multiple deprivation index in Guangzhou City from 2000 to 2010. Cities, 79, 1–11
Acknowledgements
The author gratefully acknowledges the DHS Program for providing the 2018 Nigeria DHS dataset used in this study.
Funding
This study did not receive any funding support.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing Interests
The author declares no competing of conflict of interest in conducting this study.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendices
Appendix A: Summary of reviewed country-level studies on MP in developing countries
Author | Country | Objective | Method | Key poverty indicators |
---|---|---|---|---|
Pasha (2017) | 28 developing countries | Assess MP using an alternative weighting scheme | Multiple correspondence analysis | Education, child mortality, water, sanitation, housing, electricity |
Batana (2013) | 14 countries in Sub-Saharan Africa | Measure MP among women | Alkire–Foster Multidimensional Poverty Index (MPI) | Education, water, sanitation, electricity, assets, floor material, body-mass index (BMI) |
Santos & Villatoro (2018). | 17 Latin American countries | Develop and measure MPI for Latin America, 2005–2012 | MPI for Latin America | Housing, water, sanitation, education, employment, assets, energy, social protection |
Duclos et al., (2006) | Ghana, Madagascar, and Uganda. | Compare MP among three African countries | Bivariate stochastic dominance techniques | Expenditure and health (child stunting) |
Achia et al., (2010) | Kenya | Assess poverty determinants | Principal Components Analysis (PCA) | Drinking water, education, and cooking fuel |
Habyarimana et al., (2015) | Rwanda | Assess the household socio-economic status | PCA | Water, sanitation, housing, cooking fuel, assets ownership |
Stoeffler et al., (2016) | Zimbabwe | Explore changes in MP, 2001–2012 | Alkire–Foster MPI | Education, health, housing, employment, water, cooking fuel, assets. |
Rogan (2016) | South Africa | Measure the gender-poverty gap among households | Global MPI | Education, mortality nutrition, water, electricity, sanitation, cooking fuel, assets. |
Hanandita & Tampubolon (2016) | Indonesia | Examine MP trend, 2003–2013 | Alkire–Foster MPI and Spearman correlation | Income, morbidity, education |
Yu (2013) | China | Estimate MP prevalence, 2000–2009 | Alkire–Foster MPI | Income, education, BMI, living standard, social security |
Padda & Hameed (2018) | Rural Pakistan | Estimate MP levels in rural areas | PCA | Water, sanitation, housing, rural living, energy source |
Alkire and Seth (2015) | India | Analyze the changes in MP, 1999–2006 | Global MPI | Education, water, sanitation, electricity, assets, mortality, nutrition, cooking fuel |
Ajakaiye et al., (2016) | Nigeria | Examine MP using five deprivation indicators | First-order dominance method | Education, water, sanitation, shelter, electricity |
Adepoju (2018) | Rural Nigeria | Examine MP transitions among rural households, 2010–2012 | Alkire–Foster MPI and Logistic regression | Education, housing, water sanitation, health, assets |
Adeoti (2014) | Rural Nigeria | Investigate household poverty levels, 2004–2010 | Logit regression | Education, housing, sanitation, health, assets |
Appendix B. Descriptive statistics of study variables
Variables | Description | Min | Max | Mean | SD |
---|---|---|---|---|---|
Wealth index | 1 = poorest, 2 = poorer, 3 = middle, 4 = richer and 5 = richest | 1 | 5 | 3.042 | 1.375 |
Gender of household head | 1 = Male, 2 = Female | 1 | 2 | 1.191 | 0.393 |
Age of household head | Continuous variable | 15 | 98 | 45.749 | 15.766 |
Ethnicity of household head | 1 = Hausa, 2 = Yoruba, 3 = Igbo, and 4 = other | 1 | 4 | 3.062 | 0.961 |
Household size | Continuous variable | 1 | 37 | 4.651 | 3.175 |
Total number of rooms | Continuous variable | 1 | 24 | 2.217 | 1.437 |
Place of residency | 1 = urban, 2 = rural | 1 | 2 | 1.585 | 0.493 |
Geopolitical region | 1 = North-central, 2 = Northeast, 3 = Northwest, 4 = Southeast, 5 = South-south, 6 = Southwest. | 1 | 6 | 3.441 | 1.734 |
State | 36 states of Nigeria and the FCT | 1 | 37 | 19.081 | 10.733 |
Highest education level | 0 = no formal education, 1 = primary, 2 = secondary, 3 = higher | 0 | 3 | 1.335 | 1.080 |
Access to electricity | 0 = No, 1 = Yes | 0 | 1 | 0.553 | 0.497 |
Ownership of agricultural land | 0 = No, 1 = Yes | 0 | 1 | 0.596 | 0.491 |
Ownership of livestock | 0 = No, 1 = Yes | 0 | 1 | 0.444 | 0.498 |
Drinking water source | 0 = surface water, 1 = unprotected spring, 2 = unprotected dug well, 3 = tanker truck/pushcart, 4 = bottled/sachet water, 5 = rainwater, 6 = protected spring, 7 = protected dug well, 8 = borehole, 9 = public tap/standpipe, 10 = piped into dwelling/yard | 0 | 10 | 5.551 | 2.052 |
Type of sanitation facility | 0 = no facility/bush/field, 1 = hanging or bucket toilet, 2 = pit latrine without slab/open pit, 3 = pit latrine with slab, 4 = ventilated improved pit latrine, 5 = composting toilet, 6 = flush to somewhere else/don’t know where, 7 = flush to pit latrine, 8 = flush to septic tank, 9 = toilet that flush to piped sewer system | 0 | 9 | 3.715 | 1.970 |
Type of cooking fuel | 0 = no food cooked in the house, 1 = biomass/other, 2 = wood, 3 = charcoal/coal/lignite, 4 = kerosene, 5 = biogas, 6 = natural gas, 7 = LPG, 8 = electricity | 0 | 8 | 2.684 | 1.032 |
Main floor material | 1 = earth/sand, 2 = parquet/wood, 3 = palm/bamboo/other, 4 = vinyl/asphalt strips, 5 = ceramic tiles, 6 = cement, 7 = carpet/rug | 1 | 7 | 5.011 | 1.509 |
Main wall material | 0 = no walls, 1 = cane/palm/bamboo, 2 = dirt/earth, 3 = stone with mud/lime, 4 = plywood/wood planks, 5 = cardboard, 6 = metal/zinc, 7 = cement, 8 = bricks, 9 = cement blocks | 0 | 9 | 5.332 | 2.908 |
Main roof material | 0 = no roof, 1 = thatch/palm/bamboo, 2 = rustic mat/cardboard, 3 = wood/plank, 4 = metal/zinc, 5 = ceramic tiles, 6 = cement, 7 = roofing shingles | 0 | 7 | 3.502 | 1.308 |
Home water treatment | 0 = no, 1 = yes | 0 | 1 | 0.081 | 0.273 |
Place for handwashing | 0 = not observed, 1 = observed | 0 | 1 | 0.806 | 0.314 |
Possession of mosquito nets | 0 = no, 1 = yes | 0 | 1 | 0.617 | 0.486 |
Rights and permissions
About this article
Cite this article
Abubakar, I.R. Multidimensional Poverty among Nigerian Households: Sustainable Development Implications. Soc Indic Res 164, 993–1014 (2022). https://doi.org/10.1007/s11205-022-02963-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11205-022-02963-0