Modeling Household Solid Waste Generation in Urban Estates Using SocioEconomic and Demographic Data, Kisumu City, Kenya

Abstract

Knowledge on household solid waste quantity is essential for planning solid waste management strategy for a given city. Lack of reliable studies on household solid waste (HSW) generation is a key challenge in proper HSW management. The objective of this study was to model HSW generation using socio-economic and demographic data in urban estates. The study adopted a cross-sectional descriptive research design. Three estates representing three socioeconomic groups; High Income (Milimani), Middle Income (Migosi), Low Income (Obunga) were selected through multi-stage simple random sampling. A stratified proportionate random sample of 368 households was selected from a study population of 8651 households. Household survey questionnaires were used to obtain primary data on socioeconomic and demographic characteristics of households while Direct Waste Weighing was used to obtain primary data on the amount of monthly HSW generated. Multiple linear regression was used to model the amount of HSW generated in Kilograms based on household size, household monthly income, household monthly expenditure on food and age of the household head. The findings of this study revealed that household size, household monthly income, household monthly expenditure on food and age of the household head explained over 97% of monthly HSW generation at 95% confidence level across high income (R2 =0.975 ) middle income (R2 =0.984) and low income ( R2 =0.976 ) socio-economic groups respectively indicating that the predictor variables selected for the regression are good predictors of HSW generation. The study concluded that socio-economic and demographic data were appropriate in modeling HSW generation. The models predicting solid waste generation are useful analytic tools in the design of solid waste management programs and are useful in areas where there is urgent need of planning for solid waste management.