Childhood mortality and poverty in Kenya: levels, patterns and differentials
This research project focused on the estimation of the current levels of childhood mortality (measured by Under-five) in Kenya, generally, and in light of poverty, using secondary' data from the 2005/06 Kenya Integrated Household Budgetary Survey (KIHBS2005/06), which was conducted by the Kenya National Bureau of Statistics (KNBS)in the Ministry of planning and National Development. The main objective was specifically, to assess childhood mortality levels, patterns and differentials with respect to poverty in Kenya. This was done by investigating how childhood mortality was related to some of the households' socio-economic and environmental characteristics such as; poverty status (food, absolute and hardcore), place of residence, region of residence and educational level. Jndirect estimation method was applied to the data. Estimation of the probability of dying between birth and certain exact childhood ages q(x), was done using the Trussell variant form of the Brass technique. This method focuses on number of children ever born (CEB), children dead (CD) and number of women aged 15-49;from births histories of women in the age group 15 - 49 interviewed in the survey. Estimates of #' •..• childhood mortality rates were obtained by various factors that were thought to influence and affect them. Moreover, household's socio-economic characteristics are known to have significant impact on child mortality. Outcome measures include childhood and under-five mortality rates. The socio-economic variables selected for the study were poverty (absolute poor and non-poor), place of residence; other proximate variables are toilet facility, source of drinking water, cooking fuel etc. The framework adopted in this study was based on the one developed by Mosley & Chen (1984)for studying child survival in developing countries. The results of the analyses are presented and discussed in chapter 4. The results from the Trussell estimation indicated that childhood (U-5) mortality is still high in Kenya; and that poverty increases levels of childhood mortality. With respect to the first objective, levels of childhood mortality in Kenya are still high with regional variations maintaining the trends of high, medium and low mortality zones. U-5 mortality ranged from 46 to 145 per 1,000 live births (without poverty); and from a low of 30 to a high of 168 when poverty is included in the estimations. Sex differentials ranged from a low 59 (males) in Nairobi to a high of 199 (males) in North Eastern province. Further, the findings show that childhood mortality, as measured by (qs), is much lower than that of 115 obtained in the 2003KDHS. The findings further suggest that female U-5 mortality is higher than that of male mortality in two provinces of Kenya: Coast and Nyanza, which is in contrast with findings often cited in literature. Thus, the female advantage has been reversed according to this study in these two regions, as male child mortality is normally higher than that of female. The results thus confirm the study objectives that poverty is negatively associated with childhood mortality when other conditions are constant. Another observation made that was contrary to expectat~op was that of higher mortality rates among the non-poor households than the pOof, observed in two provinces: North Eastern and Central. In conclusion, the study findings also pointed out some measures that could be taken to reduce childhood and under-five mortality. First, reduction of poverty levels in general and specifically food and absolute was necessary if the levels and differentials in childhood mortality were to be lowered in Kenya. Secondly, improvement in rural settings to levels that approach those of urban ones for instance health care facilities and improvement in infrastructure. Thirdly, more effort needs to be put in place especially in the high mortality zones of Coast, Nyanza and Western to stem the high mortality levels if Millennium Development Goal number four (MDG4) is to be achieved in Kenya by 2015.