Food insecurity is a global issue, and households in a society can experience food insecurity at different levels that could range from being mildly food insecure to severely food insecure. The severity of food insecurity is an ordinal categorical variable in nature and different types of ordinal logistic regression models could be used to model such variables. The purpose of this study is to identify the socioeconomic and demographic factors associated with household food insecurity in Namibia by fitting an ordinal logistic regression model using the 2015/2016 Namibia Household Income and Expenditure Survey. The proportional odds model (POM) and the partial proportional odds model (PPOM) were fitted and the performance of the two models was also compared. The PPOM was found to be the better model and based on the PPOM result, the study found factors such as the age of the household head, the household size, the source of income of a household, the annual income of the household, the education level attained by a household head and the geographical location of a household to be significant factors associated with severity of household food insecurity in Namibia.
References
[1]
Santos, M.P., Brewer, J.D., Lopez, M.A., Paz-Soldan, V.A. and Chaparro, M.P. (2022) Determinants of Food Insecurity among Households with Children in Villa El Salvador, Lima, Peru: The Role of Gender and Employment, a Cross-Sectional Study. BMCPublicHealth, 22, Article No. 717. https://doi.org/10.1186/s12889-022-12889-4
[2]
Gundersen, C. and Ziliak, J.P. (2015) Food Insecurity and Health Outcomes. HealthAffairs, 34, 1830-1839. https://doi.org/10.1377/hlthaff.2015.0645
[3]
Coleman-Jensen, A., Gregory, C. and Singh, A. (2014) Household Food Security in the United States in 2013. SSRNElectronicJournal. https://doi.org/10.2139/ssrn.2504067
[4]
Namibia Statistics Agency (2024) 2023 Population and Housing Census Main Re-port. Namibia Statistics Agency.
[5]
Integrated Food Security Phase Classification [IPC] (2020) Global Report on Food Crises 2020. IPC Global Partners. https://www.ipcinfo.org
[6]
Mbongo, L.T. (2017) Food Insecurity and Quality of Life in Informal Settlements of Katutura, Windhoek, Namibia. https://repository.unam.edu.na/handle/11070/2326
Agresti, A. (2012) 16.1 Delta Method. Categorical Data Analysis, 587-591. https://www.wiley.com/en-us/Categorical+Data+Analysis%2C+3rd+Edition-p-9780470463635
[9]
Lelisho, M.E., Wogi, A.A. and Tareke, S.A. (2022) Ordinal Logistic Regression Analysis in Determining Factors Associated with Socioeconomic Status of Household in Tepi Town, Southwest Ethiopia. The Scientific World Journal, 2022, Article ID: 2415692. https://doi.org/10.1155/2022/2415692
[10]
Das, S. and Rahman, R.M. (2011) Application of Ordinal Logistic Regression Analysis in Determining Risk Factors of Child Malnutrition in Bangladesh. NutritionJournal, 10, Article No. 124. https://doi.org/10.1186/1475-2891-10-124
[11]
Tuholske, C., Andam, K., Blekking, J., Evans, T. and Caylor, K. (2020) Comparing Measures of Urban Food Security in Accra, Ghana. FoodSecurity, 12, 417-431. https://doi.org/10.1007/s12571-020-01011-4
[12]
Vulnerability Analysis and Mapping Unit (2008) FSC Indicators Handbook. https://fscluster.org/handbook/Section_two_rcsi.html
[13]
Maxwell, D., Vaitla, B. and Coates, J. (2014) How Do Indicators of Household Food Insecurity Measure up? An Empirical Comparison from Ethiopia. FoodPolicy, 47, 107-116. https://doi.org/10.1016/j.foodpol.2014.04.003
[14]
Abreu, M.N.S., Siqueira, A.L., Cardoso, C.S. and Caiaffa, W.T. (2008) Ordinal Logistic Regression Models: Application in Quality of Life Studies. CadernosdeSaúdePública, 24, s581-s591. https://doi.org/10.1590/s0102-311x2008001600010
[15]
Zuhdi, S., Sari Saputro, D.R. and Widyaningsih, P. (2017) Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model. JournalofPhysics: ConferenceSeries, 855, Article ID: 012064. https://doi.org/10.1088/1742-6596/855/1/012064
[16]
Peterson, B. and Harrell, F.E. (1990) Partial Proportional Odds Models for Ordinal Response Variables. AppliedStatistics, 39, Article No. 205. https://doi.org/10.2307/2347760
[17]
Sasidharan, L. and Menéndez, M. (2014) Partial Proportional Odds Model—An Alternate Choice for Analyzing Pedestrian Crash Injury Severities. AccidentAnalysis&Prevention, 72, 330-340. https://doi.org/10.1016/j.aap.2014.07.025
[18]
McNulty, K. (2021) Handbook of Regression Modeling in People Analytics. Chapman and Hall/CRC, 256. https://doi.org/10.1201/9781003194156
[19]
Williams, R. (2006) Generalized Ordered Logit/Partial Proportional Odds Models for Ordinal Dependent Variables. The Stata Journal: Promoting Communications on StatisticsandStata, 6, 58-82. https://doi.org/10.1177/1536867x0600600104
[20]
Angiro, B. (2015) Multinomial Logit Modeling of Factors Associated with Multiple Sexual Partners from the Kenya Aids Indicator Survey 2007. AmericanJournalofTheoreticalandAppliedStatistics, 4, Article No. 170. https://doi.org/10.11648/j.ajtas.20150403.23
[21]
Andriani, P. and Chamidah, N. (2019) Modelling of Hypertension Risk Factors Using Logistic Regression to Prevent Hypertension in Indonesia. JournalofPhysics: ConferenceSeries, 1306, Article ID: 012027. https://doi.org/10.1088/1742-6596/1306/1/012027
[22]
Mittlböck, M. and Heinzl, H. (2001) A Note on R2 Measures for Poisson and Logistic Regression Models When Both Models Are Applicable. JournalofClinicalEpidemiology, 54, 99-103. https://doi.org/10.1016/s0895-4356(00)00292-4
[23]
Amrullah, E.R., Ishida, A., Pullaila, A. and Rusyiana, A. (2019) Who Suffers from Food Insecurity in Indonesia? InternationalJournalofSocialEconomics, 46, 1186-1197. https://doi.org/10.1108/ijse-03-2019-0196
[24]
Maharjan, K.L. and Joshi, N.P. (2011) Determinants of Household Food Security in Nepal: A Binary Logistic Regression Analysis. JournalofMountainScience, 8, 403-413. https://doi.org/10.1007/s11629-011-2001-2
[25]
Maziya, M., Mudhara, M. and Chitja, J. (2017) What Factors Determine Household Food Security among Smallholder Farmers? Insights from Msinga, Kwazulu-Natal, South Africa. Agrekon, 56, 40-52. https://doi.org/10.1080/03031853.2017.1283240
[26]
Mutisya, M., Ngware, M.W., Kabiru, C.W. and Kandala, N. (2016) The Effect of Education on Household Food Security in Two Informal Urban Settlements in Kenya: A Longitudinal Analysis. FoodSecurity, 8, 743-756. https://doi.org/10.1007/s12571-016-0589-3
[27]
Nkoko, N., Cronje, N. and Swanepoel, J.W. (2024) Factors Associated with Food Security among Small-Holder Farming Households in Lesotho. Agriculture&FoodSecurity, 13, 1-10. https://doi.org/10.1186/s40066-023-00454-0
[28]
Rahman, A. and Mishra, S. (2019) Does Non-Farm Income Affect Food Security? Evidence from India. TheJournalofDevelopmentStudies, 56, 1190-1209. https://doi.org/10.1080/00220388.2019.1640871
[29]
Nyangasa, M.A., Buck, C., Kelm, S., Sheikh, M. and Hebestreit, A. (2019) Exploring Food Access and Sociodemographic Correlates of Food Consumption and Food Insecurity in Zanzibari Households. InternationalJournalofEnvironmentalResearchandPublicHealth, 16, Article No. 1557. https://doi.org/10.3390/ijerph16091557
[30]
Shedenova, N. and Beimisheva, A. (2013) Social and Economic Status of Urban and Rural Households in Kazakhstan. Procedia—Social and Behavioral Sciences, 82, 585-591. https://doi.org/10.1016/j.sbspro.2013.06.314