The Effect of Socioeconomic Status on Health Service Utilization in Kenya: Econometric Analysis

Abstract

Kenya has been in the forefront in designing policies to reduce disparities in access to health care and in health outcomes. The Government has been working to improve the health sector performance in with Vision 2030. In particular, the Government of Kenya launched the universal health coverage (UHC) agenda in 2018 as one of the big four development initiatives. The initiatives outside the health sector, which have also been piloted, include revitalizing the manufacturing sector and improving housing conditions. This was in a bid to achieve effective service coverage and financial protection in events of sickness. Despite the progress made towards achieving equity in health and in access to health care, socioeconomic disparities in health care utilization continue to persist. On this backdrop this study uses econometric methods to examine the effects of socioeconomic factors on health care utilization in Kenya shortly before the launch of the UHC agenda. This study employed LPM, logit and probit regressions on data samples from the Kenya Integrated Household Budget Survey (KIHBS), collected by the Kenya National Bureau of Statistics in 2015/16. This survey data has comprehensive information on all the variables needed for the analysis of disparities in access to health care in Kenya. The 2015/16 KIHBS consisted of 5,360 clusters, split into four equal sub-samples. The sampling frame is stratified into urban and rural areas within each of 47 counties resulting in 92 sampling strata with Nairobi city and Mombasa counties being wholly urban. The sample size was determined independently for each county, resulting in a national sample of 24,000 households. The econometric analysis shows that an individual’s age, income per capita, household size, per capita income, gender, education level, employment status, area of residence and insurance are all significant determinants of health service utilization. The descriptive statistics reveal that insurance coverage is low (16.8%) and that women with formal sector employment comprise only 11.0% of total wage employment. As expected, per capita income, a major determinant of health service utilization in this data set, is highly skewed, and at the survey time (2015/16), it averaged around Ksh 4,600 per month. Separately, economic variables (income, employment, health insurance) and the social background variables (gender, marital status, and age) have large impacts on health service utilization but the impacts of their interactions are relatively minor. In particular, only the interactions of gender with wage employment and with insurance have utilization effects that are different from zero. Insurance coverage alone is associated with a large increase in health service utilization. Utilization of health services in Kenya is still low; hence the government needs to come up with measures to reduce health service utilization disparities related to gender, literacy levels, different income groups, enrolment into health insurance, health awareness levels, and also should design other kinds of assistance for the most affected groups, like men, and persons associated with disadvantageous marriage arrangements, such as the widowed, divorced, and the separated