Economics, Business and Management: Recent Advances Vol. 2

Introduction: Food poverty and insecurity among household members have adverse consequences for dietary quality and may lead to inadequate nutrition, thereby affecting the physical, emotional and financial well-being of household members. In recent years, Zanzibar has experienced increasing food-insecurity pressures, with IPC classifications indicating worsening food conditions in several regions and highlighting the need for robust household-level measurement approaches. Previous studies in Tanzania have commonly used the Food Consumption Score and the Food Insecurity Experience Scale to assess food access and food poverty. However, these measures may be limited in capturing actual dietary energy intake. Therefore, this study adopts a more direct approach by using food consumption measured in kilocalories per adult equivalent per day to estimate food poverty.

Aim of the Study: The aim of this study is to investigate the socio-economic and demographic determinants of food poverty among household heads in Zanzibar using data from the 2019/2020 Household Budget Survey, and to identify the key factors influencing household access to adequate food, measured in kilocalories, in both Unguja and Pemba islands.

Material and Methods: Data from 2,788 household heads in the Household Budget Survey were used. The objective of the study was to investigate the socio-economic and demographic variables affecting household heads' access to food in Zanzibar. Using 2,200 kcal as the baseline consumption threshold, equivalent to TSh 1,571.1091, food poverty was estimated among adults in Zanzibar. Stratification was based on area and weighted by occupancy. A two-stage stratified design-based binary logistic model was applied, and the area under the receiver operating characteristic curve was used to evaluate model accuracy. Descriptive statistics for the covariates of poverty were computed, and food-poor and non-food-poor households were estimated.

Results: The weighted binary logistic regression model showed that household size, educational attainment of the household head, total monthly expenditure and household location were significant determinants of food poverty at the 5% level. Specifically, larger household size was associated with a higher likelihood of food poverty, while higher educational attainment reduced the probability of being food poor. Higher monthly household expenditure significantly improved food consumption levels, thereby reducing the risk of food poverty. Households headed by individuals with no or low educational attainment had significantly higher odds of food poverty than those headed by individuals with higher education levels. The model demonstrated strong predictive performance, with an area under the receiver operating characteristic curve of 0.9278, indicating excellent classification accuracy. No statistically significant difference was observed between rural and urban households in food-poverty status (p > 0.05).

Conclusion: Household size, educational attainment of the household head, total  monthly expenditure and location were the significant correlates influencing food poverty.