Mapping Child Abuse Vulnerability, Case Study-Nairobi County

Abstract

Child abuse is a major public problem in Kenya and most cases are informed by the social setting and surroundings of the children. Nairobi County being the capital city of Kenya leads in the number of child abuse cases reported. Increased stress levels among parents and caregivers are a predictor of child abuse. The neighbourhood of child abuse is largely informed by social organizations. Identifying neighbourhoods which are vulnerable to child abuse is the first step in abuse identification and prevention measures. This study aimed at identifying subcounties that are most vulnerable to child abuse in Nairobi County using socio-economic risk factors. Spatial data on child abuse with eight risk factors were identified. Ordinary Least Squares was used to determine redundancy of the risk factors their significance of the risk factors for modelling child abuse. Geographically Weighted Regression (GWR) was used to model child abuse vulnerability. Results were validated using spearman rank correlation coefficient The study results were presented in tables, charts and maps. Unemployment, poverty density, population density, education, household size, age of the child, gender of the child and parental conflicts were the risk factors of child abuse. Unemployment, education, household size, poverty density and population density were used. Variance Inflation Factors of all the five risk factors were below 7.5 and therefore there were no redundant risk factors. Education, poverty density and population density were found to be significant factors for modelling child abuse. Model performance according to GWR R squared was 0.66. This is the percentage of vulnerability that the three risk factors accounted for. Spearman rank correlation coefficient was 0.375 which means there was fairly strong correlation between the predicted values and reported cases in 2022. Kibra, Embakasi North, Starehe and Kasarani sub-counties reported high cases to child abuse vulnerability. Population density was positively related with child abuse vulnerability while population density and education were negatively related with child abuse. It was recommended that in management of child abuse, children departments are encouraged to take a broad view of the environment in which the children are growing up in and provide child protection mechanisms in the risk areas that will create a safer environment for the children to live in. The study proposes further research to identify other risk factors that contributes to child abuse by increasing the scope of respondents.