A Novel Measure of Housing Insecurity, Poverty and Use of Unclean Cooking Fuel Are Associated With Greater Food Insecurity in Slums and Informal Settlements. (14th June 2022)

• Record Type: Journal Article
• Authors: Boateng, Godfred; Adams, Ellis
• Is Part Of: Current developments in nutrition. Volume 6(2022)Supplement 1
• Page Start: 94
• Page End: 94
• Publication Date: 2022-06-14
• Subjects: Nutrition -- Periodicals; Nutritional Physiological Phenomena; Nutrition; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 612.3
• DOI: 10.1093/cdn/nzac051.010
• Languages: English
• ISSNs: 2475-2991

Abstract

Abstract: Objectives: Globally, an estimated 1.6 billion people live in inadequate housing, with 1 billion living in slums and informal settlements. However, there has not been a way of measuring inadequate housing or housing insecurity in the global South, neither is there an understanding of the relationship between housing insecurity and food insecurity in slums and informal settlements. Using a newly validated scale, we assessed the effect of housing insecurity on food insecurity among the urban poor. Methods: Data for this study were collected from three slums in Ghana (N = 1, 033). First, we assessed measures of housing insecurity (Multilevel Multidimensional Housing Insecurity Scale-MMHIS) and food insecurity (Household Food Insecurity Access Scale - HFIAS); we then assessed slum severity (Slum Severity Index- SSI), poverty, and subjective socio-economic status (SES) as confounding variables. Finally, we assessed choice of food over water or energy, neighborhood health, type of cooking fuel, and socio-demography. Following descriptive and bivariate analyses, we built an additive multivariable model by including all covariates significant at p < 0.05. We assessed the effect of housing insecurity on food insecurity using Poisson regression, adjusting for both confounding and socio-demographic variables. Results: In the bivariate models, MMHIS (IRR = 1.07, p < .001), SSI (IRR = 1.11, p < .001), and Poverty (IRR = 1.19, p < .001), were associated with an increase in the estimated rate ratios of food insecurity while subjective SES was associated with a decrease in food insecurity (IRR = 0.90, p < .001). In the multivariable model, MMHIS (IRR = 1.04, p < .001) and poverty (IRR = 1.17, p < .05) were significantly associated with an increase in the food insecurity rate ratios. Other measures that increased the rate ratio of food insecurity included the choice of food over energy or water (IRR = 1.27, p < .01), use of charcoal (IRR = 1.15, p < .05), and female headed households (IRR = 1.17, p < .001). Higher SES and neighborhood health scores were associated with decreased food insecurity rate ratios. Conclusions: These data show that housing insecurity is a significant predictor of greater food insecurity in slums. Funding Sources: This work was supported by a Pilot Project Grant at the University of Texas at Arlington and the Keough School of Global Affairs at the University of Notre Dame.