Assessment of Solid Waste Management Practices Among Residents of Funtua Local Government Area, Katsina State
Abstract
Nafisat Umar, F. Ladan, A.K. Salihu, R. Balarabe and M. G. Hayat
Solid waste management is an important environmental and public-health concern, particularly where population growth and household activities increase the amount of waste generated beyond the capacity of available collection and disposal services. This study assessed solid waste management practices among residents of Funtua Local Government Area, Katsina State, Nigeria. A descriptive cross-sectional design was used, and 384 adult residents from six selected wards participated. Data were collected using a closed-ended questionnaire and analysed with the Statistical Package for the Social Sciences (SPSS), version 23. Descriptive statistics, frequencies, percentages and Likert-scale mean scores were used. Food remnants were the most frequently reported waste type (46.9%), followed by glass (42.2%); residential households were the most frequently identified source (41.7%). Overall, 290 respondents (75.6%) had poor knowledge of solid waste management, while 66 (17.0%) had good knowledge and 28 (7.4%) had average knowledge. The aggregate mean score for reported waste-management practices was 2.8, interpreted in the dissertation as poor practice. Large population and lack of waste-collection facilities were among the leading perceived barriers, each with a mean score of 3.92. Blocked drainage, stagnant water and mosquito breeding received a mean score of 4.0 as a perceived consequence of poor waste management. The findings indicate gaps in residents’ knowledge and reported practices alongside constraints in collection infrastructure and service access. Community education, accessible collection points, reliable collection schedules, improved local-government resourcing and community-health-nurse engagement are recommended. Results are presented as reported in the source dissertation; inconsistencies in some original table labels and interpretation rules should be checked against the final dataset before journal submission.