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      Unmet need for contraception and its association with unintended pregnancy in Bangladesh

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          Abstract

          Background

          Unmet need for contraception and unintended pregnancy are important public health concerns both in developing and developed countries. Previous researches have attempted to study the factors that influence unintended pregnancy. However, the association between unmet need for contraception and unwanted pregnancy is not studied adequately. The aim of the present study was to measure the prevalence of unmet need for contraception and unwanted pregnancy, and to explore the association between these two in a nationally representative sample in Bangladesh .

          Methods

          Data for the present study were collected from Bangladesh demographic and health survey conducted in 2011. Participants were 7338 mothers ageing between 13 and 49 years selected from both rural and urban residencies. Planning status of last pregnancy was the main outcome variable and unmet need for contraception was the explanatory variable of primary interest. Cross tabulation, chi-square tests and logistic regression (Generalised estimating equations) methods were used for data analysis.

          Results

          Mean age of the sample population was 25.6 years (SD 6.4). Prevalence of unmet need for contraception was 13.5%, and about 30% of the women described their last pregnancy as unintended. In the adjusted model, the odds of unintended pregnancy were about 16 fold among women who reported facing unmet need for contraception compared to those who did not (95% CI = 11.63–23.79).

          Conclusion

          National rates of unintended pregnancy and of unmet need for contraception remain considerably high and warrant increased policy attention. Findings suggests that programs targeting to reduce unmet need for contraception could contribute to a lower rate of unintended pregnancy in Bangladesh. More in-depth and qualitative studies on the underlying sociocultural causes of unmet need can help develop context specific solutions to unintended pregnancies.

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          Most cited references22

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          To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health.

          Two modeling approaches are commonly used to estimate the associations between neighborhood characteristics and individual-level health outcomes in multilevel studies (subjects within neighborhoods). Random effects models (or mixed models) use maximum likelihood estimation. Population average models typically use a generalized estimating equation (GEE) approach. These methods are used in place of basic regression approaches because the health of residents in the same neighborhood may be correlated, thus violating independence assumptions made by traditional regression procedures. This violation is particularly relevant to estimates of the variability of estimates. Though the literature appears to favor the mixed-model approach, little theoretical guidance has been offered to justify this choice. In this paper, we review the assumptions behind the estimates and inference provided by these 2 approaches. We propose a perspective that treats regression models for what they are in most circumstances: reasonable approximations of some true underlying relationship. We argue in general that mixed models involve unverifiable assumptions on the data-generating distribution, which lead to potentially misleading estimates and biased inference. We conclude that the estimation-equation approach of population average models provides a more useful approximation of the truth.
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            Disparities in Rates of Unintended Pregnancy In the United States, 1994 and 2001

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

              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.
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                Author and article information

                Contributors
                brammaputram@gmail.com
                Shangfenghust@sina.com
                sanni.yaya@uOttawa.ca
                +86-027-8369-2731 , zcfeng@hust.edu.cn
                Journal
                BMC Pregnancy Childbirth
                BMC Pregnancy Childbirth
                BMC Pregnancy and Childbirth
                BioMed Central (London )
                1471-2393
                12 June 2017
                12 June 2017
                2017
                : 17
                : 186
                Affiliations
                [1 ]ISNI 0000 0004 0368 7223, GRID grid.33199.31, School of Medicine and Health Management, Tongji Medical College, , Huazhong University of Science and Technology, ; Wuhan, Hubei 430030 China
                [2 ]School of International Development and Global Studies, University of Ottawa, Ottawa, ON K1N 6N5 Canada
                Article
                1379
                10.1186/s12884-017-1379-4
                5469146
                e1362e4b-498b-48f9-8fe6-56b11a36f712
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 8 March 2016
                : 7 June 2017
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Obstetrics & Gynecology
                unintended pregnancy,unmet need for contraception,reproductive health,bangladesh

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