Predictors of Women Political Participation in Nairobi City County: An Empirical Exposition of Kenya's 2022 Elections

Political participation of women in urban setups has been substantially negated from existing studies as most of the present studies appear to largely focus on semi-urban and ruralsetups. This has created false equivalence by equating or drawing conclusions and generalizations on what is happening elsewhere to the local context.Although strides have been made in Kenya to mainstream gender issues in political participation and representation, the country is still grappling with gender disparities.This empirical study explores predictors of women political participation in Nairobi City County, Kenya. Data was collected from elected and nominated leaders in Nairobi City County (N=144). Because the population of the study was relatively small and accessible, census technique was applied to collect data from the entire population. A Cross-sectional survey research design was applied to solicit data both for independent and depend variables at a point in time.The study employed exploratory factor analysis to reduce variables associated with women participation in politics into key constructs. Consequently, Pearson correlation and multiple linear regression were used to test associations.Using desktop research and reviewing existing literature on factors associated with women political participation, twelve factors were pointed out. Consequently, data was collected on the extent to which the twelve factors influenced women political participation. These 12 factors were: Education, income, political affiliation, age, ethnicity, family structure, ethics and values, language, social support, religion, attitudes, and community safety. To ensure the scope of the study was researchable, exploratory factor analysis was applied to reduce the factors based on the Eigen value of 1. Furthermore, exploratory factor analysis enabled the study to establish whether the predictor variables had significant factor loadings, that is, test the structural validity of the variables under study. From the analysis of data, it was found that variables had high convergent validity and three components were extracted: education level, political affiliation, and income.Results from Pearson Correlation analysis indicated that income (r= (144), .688, p< .05.), political party affiliation (r= (144), .583, p< .05.), and education level (r= (144), .710, p< .05.) had a statistically significant influence on women political participation. Findings of this study have theoretical and practical implication on the factors associated with women political participation.