Heterogeneity in the Adoption of COVID-19 Preventive Measures Among Adults in Ethiopia: A Cluster Analysis Approach

Abstract

This study investigates the extent of heterogeneity in the adoption of preventive measures among adult individuals in Ethiopia. Utilizing a nationally representative cross-sectional survey conducted by the World Health Organization in 2021, encompassing 895 participants, we explore the varying patterns of preventive measure adoption. Hierarchical cluster analysis is employed to discern potential subgroups within the respondents based on their adoption of preventive measures. Subsequently, logistic regression analysis is applied to ascertain the factors associated with the identified group divisions. We identify two distinct groups characterized by their responses to nine preventive measures. Group 1 comprises the majority of respondents (87%) who exhibit lower frequencies of adopting preventive measures. In contrast, Group 2 consists of 13% of respondents who demonstrate a higher frequency of adopting preventive measures. The amalgamation of cluster analysis and logistic regression outcomes yields insightful implications for the profile of preventive measure adoption. Our logistic regression analysis delves into the determinants influencing membership in the identified subgroups. Notably, it uncovers that individuals with a higher educational attainment exhibit a 2.33-fold greater likelihood of belonging to Group 1, signifying their relatively lesser adoption of preventive measures. In conclusion, this study not only sheds light on the heterogeneity within the adoption of preventive measures among Ethiopian adults but also underscores the influence of education on the propensity to adopt such measures. The findings contribute to better understanding of the dynamics surrounding public health behavior in the context of a pandemic. Keywords: COVID-19, Cluster analysis, Ethiopia, Heterogeneity, Logistic regression, Preventive measures.