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Metrics details. The prevalence of unintended pregnancy in Kenya continues to be high. Unintended pregnancy is one of the most critical factors contributing to schoolgirl drop out in Kenya. Up to 13, 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 deaths per 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. This study used the data that was collected among a random sample of slum and non-slum women aged 15—49 years in Nairobi. The data was analyzed using simple percentages and logistic regression. 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. 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. Peer Review reports.

Unintended pregnancy, which includes both mistimed and unwanted pregnancies, is a global social and health challenge.

In sub-Saharan Africa, unintended pregnancy accounts for more than a quarter of the 40 million pregnancies that occur annually. Unintended pregnancies increase health and economic risks for children, women, men and families.

Research indicates that unintentional pregnancy is a key risk factor for adverse pregnancy and maternal outcomes, including mortality and morbidity associated with unsafe induced abortions [ 1 — 3 ] Unintended pregnancy has also been linked to low use of appropriate maternal health care [ 2 , 4 ]; [ 5 , 6 ].

Unintended pregnancy is also a major cause of unsafe abortion [ 1 — 3 , 6 ]. As in most of Africa, the prevalence of unintended pregnancy in Kenya continues to be high. In Adetunji's [ 7 ] study of eight sub-Saharan African countries, Kenya recorded the highest proportion of unintended childbearing. Up to 13, Kenyan girls drop out of school every year as a result of unintended pregnancy [ 10 ] In addition, unsafe pregnancy termination contributes immensely to maternal mortality which currently estimated at deaths per live births [ 9 ].

Studies have shown a wide range of correlates of unintended pregnancy. Unintended pregnancies mostly arise as a result of nonuse or incorrect use of contraceptives, or a noticeable contraceptive failure [ 6 , 7 , 11 ].

Unintended pregnancies have also been shown to be strongly associated with maternal age and number of previous births [ 2 , 7 , 11 — 13 ]. A prospective study in 2 governorates of Upper Egypt revealed that the majority of women never used contraception, and unintended pregnancy was more prevalent in this category of women compared to those who had ever contraception used [ 14 ].

In Chile, women aged less than 25 and of low socioeconomic status were more likely, than their peers living in households of better socioeconomic status, to have unplanned pregnancies [ 15 ]. In Harare, a significant association was found between unintended pregnancy and age, with women aged 19 years and below or 35 years and above having a higher risk of unintended pregnancy [ 16 ]. Similar results have been reported in several other studies.

Young women have higher likelihood of inconsistent or nonuse of effective family planning methods than older women and have greater risk to have mistimed than intended pregnancy [ 17 — 19 ].

Urban women, furthermore, are less likely than rural women to have more children than that which they regard as ideal. Research from different countries also indicate that women with better education levels were less likely than those with less education levels to have more children than that which they regard as ideal. Moreover, the higher education and the better socioeconomic status a woman had, and then it is less likely for her to have an unplanned pregnancy [ 2 , 7 , 11 — 13 ].

Existing literature on unintended pregnancy in Kenya has addressed its socio-demographic correlates, national prevalence, implications for maternal and child health and care-seeking, and repeatability [ 5 , 7 , 20 ].

These studies have relied largely on national large-scale or localized facility-based surveys. Little is therefore known about the prevalence and determinants of pregnancy among women from diverse socio-economic and livelihoods, particularly in urban areas of Kenya.

The current study addresses the prevalence and the determinants of unintended pregnancy among women in slum and non-slum settlements of Nairobi. Following rapid urban growth under enormous economic constraints, an increasing proportion of Kenyans now live in cities. However, urbanization in Kenya has produced critical geographic concentrations characterized by both prosperity and poverty. Cities, deeply divided along socio-economic lines, have thus emerged all over the country.

Currently, high-rent neighborhoods characterized by affluence exist next to slums noted for their squalor and impoverished livelihoods. Generally, livelihood conditions vary clearly between these zones, often translating into objective differences in health outcomes [ 21 ]. Poor urban settlement contexts set limits on the ability of women and men to safeguard their sexual and reproductive health, control their fertility, and implement their fertility aspirations [ 21 , 22 ].

Essentially, these settlements are characterized by extreme poverty and poor livelihood conditions, limited access to family planning services, illiteracy, sexual violence, and lack of access to quality health care, including ante and post-natal care services. They present particularly interesting and fertile locations for unintended pregnancy and related behavior [ 21 ]. The goal of this study was to generate new knowledge on the prevalence and determinants of unintended pregnancy among slum and non-slum women in Nairobi, Kenya.

Specifically, the study sought to a : examine the prevalence of unintended pregnancy in study settlements and b : explore the socio economic and demographic determinants of unintended pregnancy in the study communities. 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 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 second stage involved a simple random selection of one eligible woman in each of the sampled households.

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, women who re-reported ever being pregnant and who indicated whether their most recent pregnancy was intended or not.

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.

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. An odds ratio of greater than 1. 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.

Twenty-four percent of the pregnancy occurring among these women was reported as unintended, meaning they occurred at a time when the woman would have preferred to have it later or did not want it at all. The results show statistically significant variation in the incidence of unintended pregnancy according to the number of characteristics.

Women in formal employment and those in self-employment had lower incidence of unintended pregnancy The results of the analysis of the determinants of unintended pregnancy among the women who took part in this study are presented in two models.

Model I fitted the outcome variable and the socioeconomic variables namely: education, wealth index, employment status, ethnicity, household size and residence. Model II fitted all the variables included in Model I together with age, parity and marital status. As in the case of the bivariate analysis, the results shown in Model I indicate that education was not statistically associated with the occurrence of unintended pregnancy among the study population.

Women in non-slum settlements were about 2. Luhya and Luo women also remained more likely to experience unintended pregnancy compared to their Kikuyu counterparts.

Non-slum women were still 1. Considering marital status, currently married and formerly married women were less likely to experience unintended pregnancy compared to those who were never married. Further analysis of the determinants of unintended pregnancy in each of the settlements was conducted. The results show that in both types of settlements, ethnicity and marital status have each statistically significant effect on unintended pregnancy.

In both settlements, single women were significantly more likely to experience unintended pregnancy than their currently married or formerly married counterparts. Similarly, in both settlements, being Luo or Luhya was associated with a higher likelihood of experiencing unintended pregnancy compared to being a Kikuyu. Parity and age are the other factors that have statistically significant effects in the slum settlements only.

In the slum settlements, the likelihood of experiencing unintended pregnancy increased with parity. For example, women of parity 1—2 children and those of at least parity 3 were 2. In contrast, the likelihood of experiencing unintended pregnancy among the women in the slum settlements declined with the age of the woman.

Young women 15—19 are significantly more likely to experience unintended pregnancy compared to older women 20—34 or 35— This study addressed the prevalence, socio-economic and demographic correlates of unintended pregnancy among slum and non-slum women in Nairobi.

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Prevalence and determinants of unintended pregnancy among women in Nairobi, Kenya

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Metrics details. The prevalence of unintended pregnancy in Kenya continues to be high. Unintended pregnancy is one of the most critical factors contributing to schoolgirl drop out in Kenya.

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Comments: 1
  1. Fenrijind

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