A Probit Regression Analysis of Sustainable Disaster Preparedness in Erosion-Prone Areas of Abia State, Nigeria

Ikechukwu, Chike and Obaniyi, K. S. and Ikechukwu, Ozioko and Ojo, Ibukun Elizabeth and Owolabi, Ayotunde Olayinka and Bamiro, Olasunkanmi (2025) A Probit Regression Analysis of Sustainable Disaster Preparedness in Erosion-Prone Areas of Abia State, Nigeria. NIPES-Journal of Science and Technology, Research, 7 (1). pp. 1618-1622. ISSN eISSN-2682-5821| pISSN-2734-2352 © 2025

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Official URL: https://doi.org/10.37933/nipes/7.4.2025.SI189

Abstract

The study assessed the determinants of disaster preparedness in erosion-prone communities of Abia State, Nigeria, by employing the probit regression analysis. A sample size of seventytwo (72) respondents was selected using the two-stage sampling technique. Using the probit regression analysis, the relationship between the farmers’ perception of erosion causes and disaster preparedness was analyzed. A perception score was created and categorized into binary preparedness (1 = Prepared, 0 = Not Prepared) based on the mean (3). The independent variables included in the model were human activities, climate change, soil nature, and religion. The marginal effect was not included in this study. The results showed that farmers’ perception of gully erosion causes, particularly climate change, soil nature and religion, were statistically significant at a 1% level of significance, while human activity was found significant at a 5% level of significance, and they are negatively associated with disaster preparedness. Therefore, policymakers and development professionals should bridge these knowledge gaps by promoting science-driven understanding through education, extension services and effective communication methods. Also, local beliefs through a participatory approach should be incorporated without perpetuating a culture of inaction. Keywords—Sustainability, Technology, Climate change, Disaster Preparedness, Rural Development

Item Type: Article
Uncontrolled Keywords: Sustainability, Technology, Climate change, Disaster Preparedness, Rural Development
Subjects: S Agriculture > S Agriculture (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TD Environmental technology. Sanitary engineering
Divisions: Faculty of Medicine, Health and Life Sciences > School of Biological Sciences
Depositing User: KAYODE OBANIYI
Date Deposited: 16 Feb 2026 09:13
Last Modified: 16 Feb 2026 09:13
URI: https://eprints.lmu.edu.ng/id/eprint/5942

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