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Background: The prevalence of unintended pregnancy in Kenya continues to be high. The 2003 Kenya Demographic and Health Survey (KDHS) showed that nearly 50% of unmarried women aged 15-19 and 45% of the married women reported their current pregnancies as mistimed or unwanted. The 2008-09 KDHS showed that 43% of married women in Kenya reported their current pregnancies were unintended. Unintended pregnancy is one of the most critical factors contributing to schoolgirl drop out in Kenya. Up to 13,000 Kenyan girls drop out of school every year as a result of unintended pregnancy. Unsafe pregnancy termination contributes immensely to maternal mortality which currently estimated at 488 deaths per 100 000 live births. In Kenya, the determinants of prevalence and determinants of unintended pregnancy among women in diverse social and economic situations, particularly in urban areas, are poorly understood due to lack of data. This paper addresses the prevalence and the determinants of unintended pregnancy among women in slum and non-slum settlements of Nairobi.Methods: This study used the data that was collected among a random sample of 1262 slum and non-slum women aged 15-49 years in Nairobi. The data was analyzed using simple percentages and logistic regression.Results: The study found that 24 percent of all the women had unintended pregnancy. The prevalence of unintended pregnancy was 21 per cent among women in slum settlements compared to 27 per cent among those in non-slum settlements. Marital status, employment status, ethnicity and type of settlement were significantly associated with unintended pregnancy. Logistic analysis results indicate that age, marital status and type of settlement had statistically significantly effects on unintended pregnancy. Young women aged 15-19 were significantly more likely than older women to experience unintended pregnancy. Similarly, unmarried women showed elevated risk for unintended pregnancy than ever-married women. Women in non-slum settlements were significantly more likely to experience unintended pregnancy than their counterparts in slum settlements.The determinants of unintended pregnancy differed between women in each type of settlement. Among slum women, age, parity and marital status each had significant net effect on unintended pregnancy. But for non-slum women, it was marital status and ethnicity that had significant net effects.Conclusion: The study found a high prevalence of unintended pregnancy among the study population and indicated that young and unmarried women, irrespective of their educational attainment and household wealth status, have a higher likelihood of experiencing unintended pregnancy. Except for the results on educational attainments and household wealth, these results compared well with the results reported in the literature.The results indicate the need for effective programs and strategies to increase access to contraceptive services and related education, information and communication among the study population, particularly among the young and unmarried women. Increased access to family planning services is key to reducing unintended pregnancy among the study population. This calls for concerted efforts by all the stakeholders to improve access to family planning services among the study population. Increased access should be accompanied with improvement in the quality of care and availability of information about effective utilization of family planning methods. © 2013 Ikamari et al.; licensee BioMed Central Ltd.
The data for this paper were drawn from the study on “Prevalence, Perceptions, and Experiences of Unwanted Pregnancy among women in slum and non-slum settlements of Nairobi, Kenya” conducted by the African Population and Health Research Centre (APHRC) in 2009–10. The study was conducted among women aged 15–49 years in four communities- Korogocho, Viwandani, Jericho, and Harambee in Nairobi. Korogocho and Viwandani are slum settlements whereas Jericho and Harambeeare non-slum Settlements. The study collected data from a total of 1962 randomly-selected women. A two-stage sampling design was employed to recruit study participants. The initial stage involved a random sampling of households from the settlements. The sample of households was drawn from APHRC’s Nairobi Urban Health and Demographic Surveillance System (NUHDSS) which is implemented in these settlements. The second stage involved a simple random selection of one eligible woman in each of the sampled households. In the study, information was collected on women’s social, economic, demographic, pregnancy, birth histories (including miscarriages and or abortions, stillbirths, and neonatal deaths) as well as contraceptive behavior. It also collected information on unintended pregnancy among women, the number of times this had happened, and why the pregnancy was considered unintended. Women who admitted to experiencing unintended pregnancy were also asked how they managed the pregnancy. This paper is based on 1,272 women who re-reported ever being pregnant and who indicated whether their most recent pregnancy was intended or not. The study was approved by the Kenya Medical Research Institute (KEMRI). Informed consent for participation was also obtained from each of the respondents. The dependent variable is pregnancy intention, measured as a two-outcome variable and coded as intended pregnancy, if the pregnancy occurred at a time when the woman wanted it, and unintended pregnancy, if the pregnancy occurred at a time when the woman would have wanted it later or did not want it at all. The independent variables used in this paper include education (coded as none, primary and secondary/higher), wealth index (recoded as tertiles and labeled poor, middle and rich), ethnicity, parity, age, marital status, household size, employment status, and type of residence. These are some of the variables that have been found to affect incidence of unintended pregnancy elsewhere. The study used a mix of methods for data analysis. Simple percentages and cross-tabulation are used to analyze the levels and differentials in unintended pregnancy. Logistic regression is used in multivariate analysis of factors affecting unintended pregnancy. Results are presented as risk ratios, which represent the relative likelihood of exposure to the variable of interest. The risk ratio of the reference group or category is one (1.00). An odds ratio of greater than 1.00 indicates increased likelihood of experiencing unintended pregnancy while an odds ratio of less than 1.00 indicates a lower likelihood of experiencing unintended pregnancy. In the study, independent variables are considered significant if their effects on unintended pregnancy are statistically significant at the 95 per cent level of significance.
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