An Empirical Analysis of the Effect of Poverty on Health Care Utilization in Kenya

Abstract

Background Good health is a fundamental huma right, a valued asset, and a prerequisite for improved productivity. However, high poverty can lead to under utilization or lack of utilization of health care leading to poor health. Thus, poverty reduction and improvement of health care utilization are important in ensuring enjoyment of good health. Since 1982, poverty has remained above 40 per cent despite Kenya’s commitment to poverty reduction. Kenya’s health indicators have also not been impressive and health care utilization has remained low. Evidence shows that those who fell sick and reported lack of finances as the main reason for not seeking medical attention constituted 44 per cent, 38 per cent and 21.4 per cent in 2003, 2007 and 2013, respectively. These statistics point to poor health care utilization due to poverty. In Kenya, studies have concentrated on small segments of the population or parts of the country hence limiting generalization of the findings. Objective The objective of this paper was to determine the effect of poverty on health care utilization in Kenya. Method The study used a Negative Binomial Regression and the 2013 Kenya Household Expenditure and Utilization Survey dataset. The study also used Two Stage Residual Inclusion approach and a Control Function Approach to test and control for potential endogeneity and unobserved heterogeneity problems, respectively. Results The estimation results showed that reduction in poverty increased health care utilization. Other factors that had a positive and statistically significant effect on health care utilization were household size, early levels of education, and distance to the nearest health facility. Conclusion The study concludes that health care utilization is negatively affected by poverty other factors held constant. Thus, policies and strategies aimed at reducing poverty are needed. In particular the study recommends introduction of universal health care for all.

Critical Determinants of Demand for Services in the Nigeria Formal Sector Social Health Insurance Programme

“…Enrollee Income had the expected positive sign but insignificant effect on the demand for health insurance in this study, however, the positive sign implies that as income grows, the demand for health insurance would increase. The results of this study does not tally with the findings of Ajemunigbohun, Sogura and Azeez in Nigeria [36], Nanu in Ethiopia [37], Ali and Norman in Bangladesh [38] and Musyoka, Korir, Omolo and Nzai in Kenya [39] whose studies showed that income does significantly determine the demand for health insurance services. The insignificance of the variable might not be unconnected with the fact that salary levels were low, majority of the respondents in this study were in the lower income bracket, enrollees only pay 50% co-insurance for expensive investigations and 10% copayments for drugs.…”

“…The distance to provider variable had a positive relationship with the demand for health insurance and it is in line with the findings of Musyoka et al in Kenya [39], Tsegay et al in Ethiopia [40] and Nanu in Ethiopia [37]. The health insurance providers in the formal sector social health insurance programme in this study offer specialized services at the reference level and hence, charge higher prices.…”

“…The enrollee level of education was also found to be positively related to demand for health insurance. This positive relationship between the enrollee level of education and the demand for health insurance tallies with Ajemunigbonhun et al in Nigeria [36], Tsegay et al in Ethiopia [40], Ali and Norman in Bangladesh [38], Musyoka et al in Kenya [39] and Nurgadi et al in Indonesia [35]. This therefore means that the higher the level of education, the higher the demand for health insurance.…”

The relationship between a microfinance-based healthcare delivery platform, health insurance coverage, health screenings, and disease management in rural Western Kenya

“…Poverty can suppress healthcare access through inability to afford services, low service availability, and geographic accessibility issues [16,17]. In Kenya, poverty has been associated with less healthcare utilization [18,19] and more than a third of the overall population was living below the poverty line in 2016 [20]. Additionally, the Kenyan health system is largely funded by out-of-pocket payments from patients and efforts to address the inequity arising from this structure have been mostly unsuccessful [21].…”

The relationship between a microfinance-based healthcare delivery platform, health insurance coverage, health screenings, and disease management in rural Western Kenya

“…Poverty can suppress healthcare access through inability to afford services, low service availability, and geographic accessibility issues. (16,17) In Kenya, poverty has been associated with less healthcare utilization (18,19) and more than a third of the overall population was living below the poverty line in 2016. (20) Additionally, the Kenyan health system is largely funded by out-of-pocket payments from patients and efforts to address the inequity arising from this structure have been mostly unsuccessful.…”