The study investigated the effects of regional and socio-economic determinants on average levels (i.e., a level analysis), and the contribution of these determinants to wealth-related inequality (i.e., a gap analysis) of two health care indicators – SBA and measles immunization – in Kenya.
The results indicated that measles immunization coverage was relatively high in Kenya compared to other sub-Saharan African countries. Wealth-related inequalities of measles immunization were relatively low in the country but still higher than in countries like Zambia. On the other hand the SBA levels were among the lower in relation to other sub-Saharan African countries and the wealth-related inequalities were among the highest, however, Kenya was comparable to countries like Zambia and Madagascar. In a recent study comparing maternal and child health interventions inequality (relative C) in 54 countries, Kenya was ranked 18th for SBA and 17th for measles immunization [26
Within Kenya large differences in coverage were also noticed between provinces for both indicators investigated. The SBA coverage in Nairobi (90%) (followed by Central province) was higher than in other provinces and in Nairobi the socio-economic inequalities were relatively low. This was to be expected given that the health facilities are easily accessible, unlike in Rift Valley where access to health facilities is usually a problem. Nairobi and Central province also showed relatively high coverage immunization levels and low inequalities. This study confirms the results of 2002 SIA [7
] which also indicated that Nairobi and Central province improved measles immunization coverage equity. In 2008/09, all provinces were below the 95% SIA target and Nyanza and Western province were still below the 80% “routine” target, with especially high socio-economic inequalities in Nyanza.
SBA coverage or inequality did not remarkably vary over time. A significant improvement in measles immunization equity was observed in 2008/09. Following a nation-wide outbreak in 2005, SIA, first conducted in 2002, were followed up in 2006 [27
]. These interventions seemed to have reached the poorest quintiles which were particularly left behind in the preceding surveys.
The level analysis indicated that the following socio-economic variables were significantly associated with SBA: household wealth, mother’s education and ethnic group. It has been noted that poor women face various barriers in the utilization of maternal health services: high costs of health services, poor transportation, inadequate health facilities, poor health decision making, insecurity at night in slums, or cumbersome hospital procedures (e.g. required proof of antenatal care attendance) [2
]. Education has been reported to be a major determinant of maternal health care utilization [29
]. Indeed, education improves the ability to evaluate where and when to seek care, and to correctly interpret and assimilate health messages [30
]. As reported in other studies [31
], women from different ethnic groups were less likely to use SBA compared to the Kikuyu. This community was identified as the most consistent in terms of their reproductive ideals and behaviors (e.g. low desired number of children) [33
]. In this study, antenatal care attendance showed an important association with SBA use. Antenatal care interventions are an opportunity to reach pregnant women with messages and interventions, leading to improved maternal and newborn health [34
The stratified analysis identified the characteristics of subgroups close to the 95% immunization coverage target: richest quintile, parent’s secondary or higher education level, and the subgroups far away from this target (<80%): poorest quintile, Luo or Masai communities, parent’s with no formal education, father not working or working in the services or agricultural sector, Western province, no skilled antenatal care, birth order 4 and above. Household wealth, parent’s education and father’s occupation were found to be associated with immunization in other sub-Saharan African countries [35
The study also investigated the effects of determinants on the wealth-related inequality of SBA and measles immunization, i.e., what makes that poor people have lower levels. The wealth-related inequalities in both health care indicators were, apart from the direct effect of wealth itself, mainly due to differences in parent’s education. Antenatal care attendance and birth order were also important contributors; in addition to their effect on SBA and measles immunization levels, they were unequally distributed across wealth groups. As reported in [15
], poor women were more likely to have more children. This last observation has been studied in [39
] and was characterised as an inequity in itself. Province and ethnic group contributed more to SBA use than to measles immunization. Interestingly, rural residence reduced inequality in measles immunization by 19%. This is explained by the fact that, though more prevalent among the poor, rural residence had a positive effect on measles immunization. This could be a result of the SIA efforts in reaching geographically disadvantaged households by implementing vaccination sites (schools, churches, mosques) in the remote and rural areas of the country [7
DHS are internationally comparable surveys [40
] but the comparison with other sub-Saharan countries included DHS from different years between 2007 and 2012, possibly skewing the observed differences. Results of the trends analysis should be interpreted carefully because the available information differed between 1993/1998 and 2003/2008. Since 1999, women were asked to provide information about pregnancies resulting in live births during the five years prior to the survey. Before, the reference period was three years; the number of children included was lower. The study is limited to the information collected through DHS; other factors could have played a role in the analyses. Assessing access (cost and distance) to health facilities might be especially interesting when analysing inequalities in SBA. About 20% of household heads were not the parents of the child; their occupation may have been useful as well.
This study brought to light several considerations when planning interventions aimed at improving health care coverage and equity.
Firstly, the decomposition analysis provided several areas to be targeted in order to reduce inequality in health care. These were: poverty reduction, educational attainment (preferably secondary level and above), antenatal care attendance and parity. Successful interventions targeting the consumer costs for transport and obstetric care barrier (e.g. community loan funds), mother’s education (e.g. community educators), or family planning (e.g. community-based delivery of services) were documented [30
Secondly, the “mass deprivation” and “queuing” patterns of SBA and measles immunization presented in the trends analysis suggest that a broad strengthening of the whole system, possibly combined with targeting, is required [41
]. A program targeting the rural poor was already implemented for measles immunization through the SIA, and was initiated in two districts of Nyanza in 2001 through the Skilled Care Initiative (SCI). SCI consists in the decentralization of routine and emergency obstetric care.
Thirdly, the analysis by province highlighted inequalities between provinces and wealth-related inequality within provinces. A more in-depth analysis determining the location of the most vulnerable sub-groups within provinces would help in better reaching the whole population during interventions.
Finally, each intervention should be consistent with the socioeconomic and political context which plays a proximate role in the process to equity illustrated in the conceptual framework proposed by the Commission on Social Determinants of Health (CSDH) [42
]. The Kenyan context seems prone to changes for more equity in health. In the last decade, many initiatives were launched by the Kenyan government to improve social conditions and health, and some had an explicit equity goal [15
]. Observations resulting from the study at hand are especially in line with the National Population Policy for Sustainable Development goals: improvement of the standard of living; health through education on how to prevent illness and premature death among mothers and children; sustenance of the on-going demographic transition to further reduce fertility; and responsible parenthood. Moreover, Kenya, as a country partner of the CSDH, was involved in the “Country Work Stream” aiming at turning evidence on the social determinants of health and health equity into effective policies. Whereas the National Reproductive Health Policy that was launched in 2007 did not overtly address issues of social determinants of health, the National Reproductive Health Strategy of 2009–2015 alluded to these. It was noted that the goal of reducing health inequities can only be achieved effectively by involving the population in decisions, mobilization, devolving and allocation of resources. The community strategy was aimed at enhancing community access to health care so as to improve productivity, which in turn would lead to reduction in poverty, hunger, child and maternal deaths [43
]. Similarly the Second National Health Sector Strategic Plan of Kenya Annual Operational Plan 6 of July 2010–June 2011 reiterated the need to address equity through the community strategy [44
]. However the results of the above efforts are yet to be realized.