2,478 research outputs found

    Prevalence and Determinants of Unintended Pregnancy in Mchinji District, Malawi; Using a Conceptual Hierarchy to Inform Analysis

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    Background: In 2012 there were around 85 million unintended pregnancies globally. Unintended pregnancies unnecessarily expose women to the risks associated with pregnancy, unsafe abortion and childbirth, thereby contributing to maternal mortality and morbidity. Studies have identified a range of potential determinants of unplanned pregnancy but have used varying methodologies, measures of pregnancy intention and analysis techniques. Consequently there are many contradictions in their findings. Identifying women at risk of unplanned pregnancy is important as this information can be used to help with designing and targeting interventions and developing preventative policies. Methods: 4,244 pregnant women from Mchinji District, Malawi were interviewed at home between March and December 2013. They were asked about their pregnancy intention using the validated Chichewa version of the London Measure of Unplanned Pregnancy, as well as their socio-demographics and obstetric and psychiatric history. A conceptual hierarchical model of the determinants of pregnancy intention was developed and used to inform the analysis. Multiple random effects linear regression was used to explore the ways in which factors determine pregnancy intention leading to the identification of women at risk of unplanned pregnancies. Results: 44.4% of pregnancies were planned. On univariate analyses pregnancy intention was associated with mother and fatherโ€™s age and education, marital status, number of live children, birth interval, socio-economic status, intimate partner violence and previous depression all at p<0.001. Multiple linear regression analysis found that increasing socio-economic status is associated with increasing pregnancy intention but its effect is mediated through other factors in the model. Socio-demographic factors of importance were marital status, which was the factor in the model that had the largest effect on pregnancy intention, partnerโ€™s age and motherโ€™s education level. The effect of motherโ€™s education level was mediated by maternal reproductive characteristics. Previous depression, abuse in the last year or sexual abuse, younger age, increasing number of children and short birth intervals were all associated with lower pregnancy intention having controlled for all other factors in the model. This suggests that women in Mchinji District who are either young, unmarried women having their first pregnancy, or older, married women who have completed their desired family size or recently given birth, or women who have experienced depression, abuse in the last year or sexual abuse are at higher risk of unintended pregnancies. Conclusion: A simple measure of pregnancy intention with well-established psychometric properties was used to show the distribution of pregnancy planning among women from a poor rural population and to identify those women at higher risk of unintended pregnancy. An analysis informed by a conceptual hierarchical model shed light on the pathways that lead from socio-demographic determinants to pregnancy intention. This information can be used to target family planning services to those most at risk of unplanned pregnancies, particularly women with a history of depression or who are experiencing intimate partner violence

    The correlates of natural method use in Moldova: is natural method use associated with poverty and isolation?

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    Natural method use is often associated with high levels of unwanted births and induced abortions. This study investigates the correlates of natural method use in Moldova, a country with one of the highest proportions of natural contraceptive users in Europe. We hypothesize that economic and spatial disadvantage increase the reliance on natural methods whereas exposure to FP programs decreases the probability of natural method use. The analysis considers a sub-sample of 5860 sexually-active women from the 2005 Demographic and Health Survey. Results from multilevel multinomial models, controlling for relevant characteristics and data structure, show that economic disadvantage increases the probability of natural method use; but the overall effect is small. Higher FP media exposure reduces natural method use; however this effect attenuates with age. We conclude that FP efforts directed towards the poorest may have limited impact, but interventions targeted at older women could reduce the burden of unwanted pregnancies

    Prevalence and Predictors of Unintended Births in Low and Middle-Income Countries: A Pooled Analysis of 27 Nationally Representative Surveys

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    Introduction Rates of unintended births (UIBs) are disproportionately high in low- and middle-income countries (LMICs) where the capacity to provide care to unexpected mothers and their offspring is often lagging. To decrease the prevalence of UIBs and their negative impacts on children, women, families, communities, and health systems of developing nations, global health stakeholders must understand the characteristics of a woman\u27s life in these regions that increase her risk for UIBs. This project identified and analyzed predictors of UIBs in Sub-Saharan Africa (SSA) and South-East Asia among all women of reproductive age. It built on findings from previous studies while also testing novel determinants in predictive models. The overall goal was to add to the conceptual understanding of sociodemographic, interpersonal, and family dynamic situations that predispose a woman to UIBs while factoring out overly specific regional influences. This can guide future research and inform public health practice in regions where comprehensive and context-specific studies on UIBs have not yet been done. Methods Nationally representative Demographic and Health Survey datasets from 27 LMICs across Africa and South-East Asia were appended. Weighted prevalence and 95% confidence intervals (CIs) were calculated while a Rao-Scott design-adjusted Chi-square test with second-order correction estimated bivariate associations between predictors and UIBs. Multivariate logistic regression models were used to predict odds of UIBs across three blocks of predictor variables. The first block produced unadjusted odds ratios by treating country of residence as the only predictor. The second block added sociodemographic and sexual and reproductive health (SRH) variables, while the third added variables about the woman\u27s partner, family power dynamics, and intimate partner violence. The regression analyses produced adjusted odds ratios (AORs), accompanying 95% CIs, and p-values for each predictor. Results The final sample (n=380,577) had an UIB prevalence of 19.4% (CI = 19.2 โ€“ 19.6). Model 3 showed the highest odds of UIBs among women from Lesotho (AOR = 11.13, CI = 8.54 โ€“ 14.51), as compared to all other countries; Africa (AOR = 2.62, CI = 2.09 โ€“ 3.29) as opposed to South-East Asia; and fragile regions (AOR = 1.44, CI = 1.30 โ€“ 1.59) compared to non-fragile regions. Also with the highest odds of UIBs were women aged 15-20 years (AOR = 1.65, CI = 1.40 โ€“ 1.94); women who were never married (AOR = 1.82, CI = 1.61 โ€“ 2.05), compared to those currently and formerly married; those with a primary education (AOR = 1.59, CI = 1.18 โ€“ 2.16); women with a parity of nine or more (AOR = 5.54, CI = 4.37 โ€“ 7.03), compared to women with parities of Conclusions Although not statistically significant, relatively low odds of UIBs were observed in women with low SES, no education, without knowledge of modern contraceptives, and whose partners had no education. These findings may indicate that decreased levels of empowerment lead to a lack of FP or women feeling unable to classify births as unintended. Governments and donors associated with Lesotho, Malawi, Namibia, and South Africa are encouraged to increase efforts towards FP outreach and the prevention of UIBs. Stakeholders must pay special attention to UIBs in fragile settings and SSA since these regions had significantly higher odds of UIBs compared to non- fragile regions and South-East Asia, respectively. Women 20 years of age and younger; women not currently married; women married at age nine or younger; women with high parity; women who have their healthcare choices made for them by a family member; and women who had sex forced on them are at significantly higher risk of UIBs. Therefore, SRH practitioners are urged to focus FP programming on these subgroups of women when comprehensive and context-specific studies from which they can inform their practice are not available. Lastly, since several of the sociodemographic and SRH associations with UIBs observed in Model 2 lost statistical significance after adding partner and interpersonal covariates in Model 3, it is important for researchers and survey implementers to take indicators reflective of family dynamics into account in subsequent analyses on UIBs

    Factors associated with underutilization of antenatal care services in Indonesia: results of Indonesia Demographic and Health Survey 2002/2003 and 2007

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    <p>Abstract</p> <p>Background</p> <p>Antenatal care aims to prevent maternal and perinatal mortality and morbidity. In Indonesia, at least four antenatal visits are recommended during pregnancy. However, this service has been underutilized. This study aimed to examine factors associated with underutilization of antenatal care services in Indonesia.</p> <p>Methods</p> <p>We used data from Indonesia Demographic and Health Survey (IDHS) 2002/2003 and 2007. Information of 26,591 singleton live-born infants of the mothers' most recent birth within five years preceding each survey was examined. Twenty-three potential risk factors were identified and categorized into four main groups, external environment, predisposing, enabling, and need factors. Logistic regression models were used to examine the association between all potential risk factors and underutilization of antenatal services. The Population Attributable Risk (PAR) was calculated for selected significant factors associated with the outcome.</p> <p>Results</p> <p>Factors strongly associated with underutilization of antenatal care services were infants from rural areas and from outer Java-Bali region, infants from low household wealth index and with low maternal education level, and high birth rank infants with short birth interval of less than two years. Other associated factors identified included mothers reporting distance to health facilities as a major problem, mothers less exposed to mass media, and mothers reporting no obstetric complications during pregnancy. The PAR showed that 55% of the total risks for underutilization of antenatal care services were attributable to the combined low household wealth index and low maternal education level.</p> <p>Conclusions</p> <p>Strategies to increase the accessibility and availability of health care services are important particularly for communities in rural areas. Financial support that enables mothers from poor households to use health services will be beneficial. Health promotion programs targeting mothers with low education are vital to increase their awareness about the importance of antenatal services.</p

    Pathways of the determinants of unfavourable birth outcomes in Kenya

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    This paper explores the pathways of the determinants of unfavourable birth outcomes, such as premature birth, the size of the baby at birth, and Caesarean section deliveries in Kenya, using graphical loglinear chain models. The results show that a number of factors which do not have direct associations with unfavourable birth outcomes contribute to these outcomes indirectly through intermediate factors. Marital status, the desirability of a pregnancy, the use of family planning, and access to health facilities have no direct associations with poor birth outcomes, such as premature births and the small size of the baby at birth, but are linked to these outcomes through antenatal care. Antenatal care is identified as a central link between various socio- demographic or reproductive factors and birth outcomes

    ์ธ๋„๋„ค์‹œ์•„ ์—ฌ์„ฑ๋“ค์˜ ์˜๋„์น˜ ์•Š์€ ์ž„์‹  ๊ฒฝํ—˜๊ณผ ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ์˜ ์—ฐ๊ด€์„ฑ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๋ณด๊ฑด๋Œ€ํ•™์› ๋ณด๊ฑดํ•™๊ณผ(๋ณด๊ฑด์ •์ฑ…๊ด€๋ฆฌํ•™์ „๊ณต), 2021.8. ๊น€์„ ์˜.Often defined as mistimed or unwanted pregnancy, unintended pregnancy causes numerous negative health impacts on women as well as children. It is evident that its negative impacts extend to not only social and economic dimension but also to health dimension within the society. Thus, decreasing the prevalence of unintended pregnancy is imperative in public health. The global society already recognized it as urgent issue and called for addressing this problem. In the Global Strategy for Womenโ€™s and Childrenโ€™s Health, the United Nations(UN) has set the global goals to decrease the prevalence of unintended pregnancy which is known as one of the main causes of death for millions of girls and women suffering from unsafe abortions and severe complications related to pregnancy and childbirth. Due to the cooperation on global level, it has been reported that the number of unintended pregnancies worldwide has decreased by approximately 18% in 2015-2019 compared to 1990-1994. However, East Asia and Southeast Asia marked the lowest rate of decrease in unintended pregnancy by only 4%. Among the countries in East Asia and Southeast Asia region, women in Indonesia suffered unwanted pregnancy the most. Meanwhile, it has been widely discussed that womenโ€™s empowerment is also contributed to development. Also, empowering women has been regarded as one of the 21st century agendas in global health. When it comes to its terminology, womenโ€™s empowerment tends to be used interchangeably with womenโ€™s autonomy or womenโ€™s decision-making power. However, womenโ€™s empowerment should be distinguished from the concepts of autonomy or decision-making power in that it implies process-a dynamic aspect. To be specific, empowerment can be defined as a process which a person who had been denied of the ability to make strategic life choices among recognized alternatives is able to obtain such ability. Research on womenโ€™s empowerment is insufficient in public health, nonetheless, empowering women plays pivotal role in producing various social benefits including improving community health. The quantitative indicators of womenโ€™s empowerment through utilizing secondary data are limited and lack scholarly consensus in the academia today. Amongst commonly replaced indicators as proxy measures are decision-making power in households and attitude towards domestic violence. These indicators were proposed by the Demographic and Health Survey Program (DHS) to measure womenโ€™s degree of empowerment. Driven from the above narratives of womenโ€™s health and its relation to empowerment, this study constructed four domains to measure womenโ€™s empowerment quantitatively, which are decision-making power in households, attitude towards domestic violence, negotiation of sexual relations and decision-making power on respondentsโ€™ health. The latter two indicators were included after a thorough review of existing literature. The data used in this study was generated from IDHS (Indonesia Demographic and Health Survey) in 2017. For analysis, 14,118 out of 49,627 respondents are selected. The dependent variable is the experience of unintended pregnancy, which encompasses mistimed or unwanted pregnancy, in the last five years. The independent variables were as follow: womenโ€™s empowerment, parity, types of contraceptives, contraceptive discontinuation, respondentsโ€™ age at first birth, heard of family planning, husband/partnersโ€™ educational level, current age, wealth index, place of residence, occupation, province, respondentsโ€™ educational level. In this research, Stata/SE 14.2 was used for statistical analysis, and two models were presented: a model without womenโ€™s empowerment variables (Model 1) and a model with womenโ€™s empowerment variables (Model 2). Chi-squared test was performed to determine whether each independent variable had a significant association with unintended pregnancy. Multiple logistic analysis was also conducted to yield adjusted odds ratio (AOR). The result showed that 16.6% of Indonesian women became pregnant unintentionally within the last 5 years. Among the four domains that measure womenโ€™s empowerment, only the variable of decision-making power on respondentsโ€™ health was statistically significant. Specifically, the women who reported difficulties in deciding their own health had 1.14 times higher odds of undergoing unintended pregnancy than women who did not report difficulties. Moreover, in a subgroup analysis, among respondents who use modern contraceptive, women who report difficulties in accessing health services had 1.42 times higher odds of experiencing unintended pregnancy compared to women who did not report such difficulties. On the other hand, the other three domains, attitude towards domestic violence, decision-making power in household and negotiation of sexual relations, were not statistically significant. These statistically insignificant results can be explained with problematic aggregation or weighting, along with a potentially unperceived fundamental drawback in the study design. Due to the nature of the DHS, the indexes for measuring empowered status of women could not be interpreted variously in accordance with different context of culture, society and country. A qualitative study conducted in Yogyakarta, Indonesia discovered that womenโ€™s decisions for family planning were not only influenced by the sexual negotiations that occurred within their marital relations, but also unexpectedly by the internalization of the surrounding society and peer womenโ€™s norms of idealistic womanhood, such as having a child immediately within marriage and having at least one child from each gender. The qualitative research emphasized the significance of the womenโ€™s surrounding social environments and their norms and contexts to affect womenโ€™s reproductive plans and health, beyond the logistical conversations that occur between their spouses. Results of this study suggest that approaching prevention of unintended pregnancy among Indonesian women should consider various societal and economic perspectives and sectors. Acknowledging the higher odds of unintended pregnancy by women who report difficulties accessing health services, policy makers and public health practitioners should consider addressing various infrastructural, physical, and psychological barriers that limit access to health services for Indonesian women. Despite the outcome of only one domain of womenโ€™s empowerment to be statistically significant in relation to the experience of unintended pregnancy, statistically insignificant outcomes of the other three domains should be interpreted with caution. Such statistical insignificance does not confirm that womenโ€™s empowerment initiatives have no implications towards decreasing the prevalence of unintended pregnancy among Indonesian women. Although this study did not capture the entirety of the multi-dimensional and dynamic aspects of womenโ€™s empowerment, its findings provide several implications. Further studies are required to determine whether the interventions for empowering women to prevent unintended pregnancy are more effective than other forms of interventions. As the current scholarly scope and tools on measuring womenโ€™s empowerment quantitatively are limiting, revision on current tools and development of new indexes are essential. To elaborate in further depths on the effects of womenโ€™s empowerment on womenโ€™s health, additional qualitative and mixed method approaches should be accompanied.์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์€ ํ•œ ๊ฐœ์ธ์˜ ์‹ ์ฒด, ์‹ฌ๋ฆฌ์  ๋ถˆ๊ฑด๊ฐ•์„ ์•ผ๊ธฐํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ๊ทธ ๋ถ€์ •์  ์˜ํ–ฅ์ด ํ•œ ๊ตญ๊ฐ€์˜ ์‚ฌํšŒ ๋ฐ ๊ฒฝ์ œ, ํ•œ ๊ตญ๊ฐ€์˜ ๋ณด๊ฑด์˜๋ฃŒ์ฒด๊ณ„์— ๊นŒ์ง€๋„ ํ™•์žฅ๋œ๋‹ค๋Š” ์ธก๋ฉด์—์„œ ๊ณต์ค‘ ๋ณด๊ฑดํ•™์ ์œผ๋กœ ์ค‘์š”ํ•œ ๋ฌธ์ œ์ด๋‹ค. UN์„ ๋น„๋กฏํ•œ ์„ธ๊ณ„ ์—ฌ๋Ÿฌ ๊ตญ๊ฐ€๋“ค์€ 2016๋…„์— ์—ฌ์„ฑ๊ณผ ์–ด๋ฆฐ์ด์˜ ๊ฑด๊ฐ•์„ ์œ„ํ•œ ์ „์„ธ๊ณ„์  ์ „๋žต(Global Strategy for Womenโ€™s and Childrenโ€™s Health)์„ ๋ฐœํ‘œํ•˜๋ฉฐ, 2030๋…„๊นŒ์ง€ ์ž„์‹ ๊ณผ ์ถœ์‚ฐ์œผ๋กœ ์ธํ•œ ํ•ฉ๋ณ‘์ฆ ๋ฐ ์•ˆ์ „ํ•˜์ง€ ์•Š์€ ์ž„์‹  ์ค‘๋‹จ์œผ๋กœ ์ธํ•ด ์‚ฌ๋งํ•˜๋Š” ์—ฌ์„ฑ์„ ์‚ด๋ฆฌ๊ธฐ ์œ„ํ•ด ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์„ ์˜ˆ๋ฐฉํ•˜๊ฒ ๋‹ค๋Š” ๋ชฉํ‘œ๋ฅผ ์„ธ์šฐ๊ธฐ๋„ ํ•˜์˜€๋‹ค. ๊ตญ์ œ์‚ฌํšŒ์˜ ๋…ธ๋ ฅ์˜ ๊ฒฐ๊ณผ๋กœ ์ „์„ธ๊ณ„์ ์œผ๋กœ ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์€ 1990๋…„-1994๋…„ ๋Œ€๋น„ 2015๋…„-2019๋…„์— ์•ฝ 18%์ •๋„ ๊ฐ์†Œํ–ˆ๋‹ค๊ณ  ๋ณด๊ณ ๋˜์—ˆ๋‹ค. ํ•˜์ง€๋งŒ, ๋™์•„์‹œ์•„ ๋ฐ ๋™๋‚จ์•„์‹œ์•„ ์ง€์—ญ์˜ ๊ฐ์†Œ์œจ์€ 4%์˜€์œผ๋ฉฐ, ์ด๋Š” ์ „์„ธ๊ณ„์—์„œ ๊ฐ€์žฅ ๋‚ฎ์€ ์ˆ˜์น˜์˜€๋‹ค. ์ด ์ง€์—ญ์— ์†ํ•˜๋Š” ๊ตญ๊ฐ€๋“ค ์ค‘ ์ธ๋„๋„ค์‹œ์•„์˜ ์—ฌ์„ฑ๋“ค์€ ์›์น˜ ์•Š์€ ์ž„์‹ ์„ ๊ฐ€์žฅ ๋งŽ์ด ๊ฒช๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ•œํŽธ, ์ „์„ธ๊ณ„์ ์œผ๋กœ ์—ฌ์„ฑ๋“ค์˜ ์—ญ๋Ÿ‰์„ ๊ฐ•ํ™”ํ•˜๊ณ  ๊ถŒ์ต์„ ์‹ ์žฅํ•˜๋Š” ๊ฒƒ(womenโ€™s empowerment)์ด ๊ฒฝ์ œ ๋ฐœ์ „๊ณผ ๊ฐœ๋ฐœ์— ๋„์›€์ด ๋œ๋‹ค๋Š” ๊ฒƒ์ด ์ฆ๋ช…๋˜์—ˆ์œผ๋ฉฐ, ๊ตญ์ œ๋ณด๊ฑด ์˜์—ญ์— ์žˆ์–ด์„œ 21์„ธ๊ธฐ ์•„์  ๋‹ค๋กœ ๊ผฝํžˆ๊ธฐ๋„ ํ•˜์˜€๋‹ค. ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ(womenโ€™s empowerment)๋Š” ์—ฌ์„ฑ์˜ ์ž์œจ์„ฑ(womenโ€™s autonomy)์ด๋‚˜ ์˜์‚ฌ๊ฒฐ์ •๊ถŒ(womenโ€™s decision-making power)๊ณผ ํ˜ผ์šฉ๋˜์–ด ์‚ฌ์šฉ๋˜๋Š” ๊ฒฝํ–ฅ์ด ์žˆ์ง€๋งŒ, ์ž„ํŒŒ์›Œ๋จผํŠธ๋Š” ์—ญ๋Ÿ‰์ด ๋ฐ•ํƒˆ๋œ ์ƒํƒœ์˜€๋˜ ์—ฌ์„ฑ์ด ์—ญ๋Ÿ‰์„ ํš๋“ํ•˜๋Š” โ€˜๊ณผ์ •โ€™์ด๋ผ๋Š” ๋™์ ์ธ ์˜๋ฏธ๋ฅผ ํ•จ์ถ•ํ•˜๊ณ  ์žˆ๋‹ค๋Š” ์ ์—์„œ, ์ž์œจ์„ฑ์ด๋‚˜ ์˜์‚ฌ๊ฒฐ์ •๊ถŒ๊ณผ ๊ฐ™์€ ์ •์ ์ธ ๊ฐœ๋…๊ณผ๋Š” ๊ตฌ๋ถ„๋œ๋‹ค. ์ด๋ ‡๋“ฏ ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ๊ฐ€ ์ค‘์š”ํ•˜๊ฒŒ ์—ฌ๊ฒจ์ง€๊ณ  ์žˆ์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ๋ณด๊ฑดํ•™ ๋ถ„์•ผ์—์„œ ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ๋ฅผ ์ฃผ์ œ๋กœํ•œ ์—ฐ๊ตฌ๋Š” ๋ถ€์กฑํ•œ ์‹ค์ •์ด๋‹ค. ์ด๋Ÿฐ ๋ฌธ์ œ์˜์‹์„ ๋ฐ”ํƒ•์œผ๋กœ ๊ธฐ์กด์˜ ์—ฐ๊ตฌ๋“ค์„ ๊ณ ์ฐฐํ–ˆ์„ ๋•Œ, ์–‘์  ์—ฐ๊ตฌ์—์„œ ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ์˜ ๋Œ€๋ฆฌ์ง€ํ‘œ๋ฅผ ๊ตฌ์„ฑํ•จ์— ์žˆ์–ด ํ•™์ž๋“ค๊ฐ„ ์ผ์น˜๋œ ํ•ฉ์˜๋‚˜ ์ผ๊ด€๋œ ๊ฒฝํ–ฅ์„ฑ์€ ํ™•์ธํ•  ์ˆ˜ ์—†์—ˆ๋‹ค. ํ•˜์ง€๋งŒ, ๊ฐ€์žฅ ๋งŽ์ด ์“ฐ์ด๋Š” ์ง€ํ‘œ๋กœ๋Š” โ€˜๊ฐ€์ • ๋‚ด ์˜์‚ฌ๊ฒฐ์ •๊ถŒโ€™๊ณผ โ€˜๊ฐ€์ • ํญ๋ ฅ์„ ์ •๋‹นํ™”ํ•˜๋Š” ํƒœ๋„โ€™ ๊ฐ€ ์žˆ์—ˆ์œผ๋ฉฐ, ํ•ด๋‹น ์ง€ํ‘œ๋“ค์€ ์ธ๊ตฌ๋ณด๊ฑด์กฐ์‚ฌ ํ”„๋กœ๊ทธ๋žจ(Demographic and Health Survey Program, DHS)์—์„œ ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ ์ธก์ •์„ ์œ„ํ•ด ์ œ์•ˆํ•œ ์ง€ํ‘œ๋“ค์ด๋‹ค. ๋”ฐ๋ผ์„œ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” ๋Œ€๋ฆฌ ์ง€ํ‘œ๋ฅผ ์ด 4๊ฐ€์ง€ ์„ธ๋ถ€ ์˜์—ญ์œผ๋กœ ๊ตฌ์„ฑํ•˜์˜€๋‹ค. DHS์—์„œ ์ œ์•ˆํ•œ ์ง€ํ‘œ์ธ โ€˜๊ฐ€์ • ๋‚ด ์˜์‚ฌ๊ฒฐ์ •๊ถŒโ€™๊ณผ โ€˜๊ฐ€์ • ํญ๋ ฅ์„ ์ •๋‹นํ™”ํ•˜๋Š” ํƒœ๋„โ€™ ์™ธ์—, ๊ธฐ์กด ๋ฌธํ—Œ ๊ณ ์ฐฐ์„ ํ†ตํ•ด ํŒŒ์•…ํ•œ โ€˜์„ฑ ๊ด€๋ จ ์ฃผ์ œ์— ๋Œ€ํ•œ ํ˜‘์ƒ๋ ฅโ€™ ๋ฐ โ€˜์‘๋‹ต์ž์˜ ๊ฑด๊ฐ•๊ณผ ๊ด€๋ จ๋œ ์˜์‚ฌ๊ฒฐ์ •๊ถŒโ€™์„ ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ ๋Œ€๋ฆฌ ์ง€ํ‘œ๋กœ ์‚ผ์•˜๋‹ค. ๋ถ„์„ ์‹œ ํ™œ์šฉํ•œ ์ž๋ฃŒ๋Š” 2017๋…„ ์ธ๋„๋„ค์‹œ์•„ DHS ์ž๋ฃŒ๋กœ, ์—ฐ๊ตฌ ๋Œ€์ƒ ์„ ์ • ๊ธฐ์ค€์— ๋”ฐ๋ผ ์ „์ฒด ํ‘œ๋ณธ์ธ 49,627๋ช… ์ค‘ 14,118๋ช…์„ ๋ถ„์„ ๋Œ€์ƒ์œผ๋กœ ์„ ์ •ํ•˜์˜€๋‹ค. ์ข…์† ๋ณ€์ˆ˜๋Š” ์˜๋„์น˜ ์•Š์€ ์ž„์‹  ๊ฒฝํ—˜ ์—ฌ๋ถ€๋กœ, ํšŒ์ƒ ํŽธํ–ฅ (recall bias)์„ ํ†ต์ œํ•˜๊ธฐ ์œ„ํ•ด 5๋…„ ์ด๋‚ด์— ์ž„์‹ ์„ ๊ฒฝํ—˜ํ•œ ์—ฌ์„ฑ ์ค‘ ์ „ํ˜€ ์›ํ•˜์ง€ ์•Š์•˜๋˜ ์ž„์‹ ์„ ๊ฒฝํ—˜ํ–ˆ๊ฑฐ๋‚˜, ์‹œ๊ธฐ๊ฐ€ ๋งž์ง€ ์•Š์€ ์ž„์‹  (mistimed pregnancy)์„ ๊ฒฝํ—˜ํ–ˆ์„ ๊ฒฝ์šฐ ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์„ ๊ฒฝํ—˜ํ•œ ๊ฒƒ์œผ๋กœ ์ •์˜ํ•˜์˜€๋‹ค. ๋…๋ฆฝ๋ณ€์ˆ˜๋กœ๋Š” ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ, ์ถœ์‚ฐ๋ ฅ, ํ”ผ์ž„๋„๊ตฌ ์ข…๋ฅ˜, ํ”ผ์ž„๋„๊ตฌ ์‚ฌ์šฉ ์ค‘๋‹จ ๊ฒฝํ—˜ ์—ฌ๋ถ€, ์ฒซ ์ถœ์‚ฐ ์—ฐ๋ น, ๊ฐ€์กฑ ๊ณ„ํš ๋ฉ”์‹œ์ง€ ์ฒญ์ทจ ๊ฒฝํ—˜ ์—ฌ๋ถ€, ์ธ๊ตฌ์‚ฌํšŒํ•™์  ๋ณ€์ˆ˜(ํ˜„์žฌ ์—ฐ๋ น, ๊ฑฐ์ฃผ ์ง€์—ญ, ๊ฑฐ์ฃผ ํ˜•ํƒœ, ์‘๋‹ต์ž ๋ฐ ๋‚จํŽธ์˜ ๊ต์œก ์ˆ˜์ค€, ์ง์—…, ์žฌ์‚ฐ ์ˆ˜์ค€)๊ฐ€ ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. ํ†ต๊ณ„ ๋ถ„์„์€ Stata/SE 14.2๋ฅผ ํ™œ์šฉํ•˜์˜€์œผ๋ฉฐ, ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ ๋ณ€์ˆ˜๊ฐ€ ๋“ค์–ด๊ฐ€์ง€ ์•Š์€ ๋ชจํ˜• (๋ชจํ˜• 1`)๊ณผ ๋“ค์–ด๊ฐ„ ๋ชจํ˜• (๋ชจํ˜• 2)์„ ๊ฐ๊ฐ ์ œ์‹œํ•˜์˜€๋‹ค. ์นด์ด ์ œ๊ณฑ ๊ฒ€์ •์„ ํ†ตํ•ด ๊ฐ ๋…๋ฆฝ๋ณ€์ˆ˜๊ฐ€ ์ข…์†๋ณ€์ˆ˜์™€ ์œ ์˜ํ•œ ๊ด€๋ จ์„ฑ์ด ์žˆ๋Š”์ง€ ํ™•์ธํ•˜์˜€๊ณ , ์ดํ›„ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€ ๋ถ„์„์„ ํ†ตํ•ด ์œ ์˜ํ•œ ์กฐ์ •๋œ ์˜ค์ฆˆ๋น„๋ฅผ ์‚ฐ์ถœํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ, ์ธ๋„๋„ค์‹œ์•„ ์—ฌ์„ฑ๋“ค ์ค‘ 16.6%๊ฐ€ ์ตœ๊ทผ 5๋…„ ์ด๋‚ด์— ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์„ ๊ฒฝํ—˜ํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ๋ฅผ ๊ตฌ์„ฑํ•˜๋Š” 4๊ฐœ์˜ ์„ธ๋ถ€์˜์—ญ ์ค‘ โ€˜์‘๋‹ต์ž์˜ ๊ฑด๊ฐ•๊ณผ ๊ด€๋ จ๋œ ์˜์‚ฌ๊ฒฐ์ •๊ถŒโ€™ ์˜์—ญ๋งŒ p-๊ฐ’์ด 0.05 ์ดํ•˜์—์„œ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ๊ด€๊ณ„๋ฅผ ๊ฐ–๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ, ๊ฑด๊ฐ•๊ณผ ๊ด€๋ จ๋œ ์˜์‚ฌ ๊ฒฐ์ •์— ๋ฌธ์ œ๊ฐ€ ์—†๋‹ค๊ณ  ์‘๋‹ตํ•œ ์—ฌ์„ฑ๋“ค์— ๋น„ํ•ด ์˜์‚ฌ ๊ฒฐ์ •์— ๋ฌธ์ œ๊ฐ€ ์žˆ๋‹ค๊ณ  ์‘๋‹ตํ•œ ์—ฌ์„ฑ๋“ค์ด ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์„ ๊ฒฝํ—˜ํ•  ์˜ค์ฆˆ๊ฐ€ 1.14๋ฐฐ๋กœ ๋†’์•˜์œผ๋ฉฐ, ์ด๋Š” ํ†ต๊ณ„์ ์œผ๋กœ๋„ ์œ ์˜ํ•˜์˜€๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ, ํ•˜์œ„์ง‘๋‹จ ๋ถ„์„์„ ํ†ตํ•ด ํ˜„๋Œ€์‹ ํ”ผ์ž„๋„๊ตฌ(Modern contraceptive methods)๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ์—ฌ์„ฑ๋“ค์—๊ฒŒ์„œ๋งŒ โ€˜์‘๋‹ต์ž์˜ ๊ฑด๊ฐ•๊ณผ ๊ด€๋ จ๋œ ์˜์‚ฌ๊ฒฐ์ •๊ถŒโ€™๊ณผ ์˜๋„์น˜ ์•Š์€ ์ž„์‹  ๊ฒฝํ—˜์ด ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ๊ด€๊ณ„๋ฅผ ๊ฐ–๋Š” ๊ฒƒ์œผ๋กœ ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ๋ฐ˜๋ฉด์—, ํ”ผ์ž„๋„๊ตฌ๋ฅผ ์‚ฌ์šฉํ•˜์ง€ ์•Š๋Š”๋‹ค๊ณ  ์‘๋‹ตํ•œ ์ง‘๋‹จ๊ณผ ์ „ํ†ต์  ํ”ผ์ž„๋„๊ตฌ(Traditional contraceptive methods)๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ์ง‘๋‹จ, ์žฅ๊ธฐ๊ฐ„ ๋ฐ ๋ถˆ๊ฐ€์—ญ์  ํ”ผ์ž„๋„๊ตฌ (Long-acting and permanent methods, LAPMs)๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ์ง‘๋‹จ์—์„œ๋Š” โ€˜์‘๋‹ต์ž์˜ ๊ฑด๊ฐ•๊ณผ ๊ด€๋ จ๋œ ์˜์‚ฌ๊ฒฐ์ •๊ถŒโ€™ ์˜์—ญ์ด ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์„ ๊ฒฝํ—˜ํ•  ์˜ค์ฆˆ์— ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜์ง€ ์•Š์•˜๋‹ค. ํ•œํŽธ, ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ ๋ณ€์ˆ˜์˜ 4๊ฐœ ์˜์—ญ ์ค‘ โ€˜๊ฐ€์ • ๋‚ด ์˜์‚ฌ๊ฒฐ์ •๊ถŒโ€™, โ€˜๊ฐ€์ • ํญ๋ ฅ์„ ์ •๋‹นํ™”ํ•˜๋Š” ํƒœ๋„โ€™ ๋ฐ โ€˜์„ฑ ๊ด€๋ จ ์ฃผ์ œ์— ๋Œ€ํ•œ ํ˜‘์ƒ๋ ฅโ€™ ๋ณ€์ˆ˜๋Š” ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ๊ณผ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์—ฐ๊ด€์„ฑ์„ ๊ฐ–๊ณ  ์žˆ์ง€ ์•Š์•˜๋‹ค. DHS์—์„œ ์ œ์•ˆํ•œ โ€˜๊ฐ€์ • ๋‚ด ์˜์‚ฌ๊ฒฐ์ •๊ถŒโ€™๊ณผ โ€˜๊ฐ€์ • ํญ๋ ฅ์„ ์ •๋‹นํ™”ํ•˜๋Š” ํƒœ๋„โ€™๊ฐ€ ์œ ์˜ํ•˜์ง€ ์•Š์€ ์ด์œ ๋Š” ๊ฐ ์˜์—ญ์„ ํ•˜๋‚˜์˜ ์ง€ํ‘œํ™” ํ•˜๋Š” ๊ณผ์ • ํ˜น์€ ๊ฐ€์ค‘์น˜์˜ ๋ถ€์žฌ ๋•Œ๋ฌธ์ผ ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ๋‹ค. ํŠนํžˆ โ€˜๊ฐ€์ • ๋‚ด ์˜์‚ฌ๊ฒฐ์ •๊ถŒโ€™์ด Kabeer๊ฐ€ ์ •์˜ํ•œ โ€œ์ „๋žต์  ์‚ถ์˜ ์„ ํƒโ€์„ ๋ฐ˜์˜ํ•˜๋Š”์ง€ ๊ฒ€ํ† ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ํ˜น์€ ๋ณธ์งˆ์ ์œผ๋กœ ๊ฐ ์˜์—ญ์ด ๊ฐ–๋Š” ์˜๋ฏธ๊ฐ€ ์„œ๋กœ ๋‹ค๋ฅธ ๊ตญ๊ฐ€, ์‚ฌํšŒ, ๋ฌธํ™”์  ๋งฅ๋ฝ์— ๋”ฐ๋ผ ๋‹ค๋ฅด๊ฒŒ ํ•ด์„๋  ์—ฌ์ง€๊ฐ€ ๊ฐ•ํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ํ•ด๋‹น ์ง€ํ‘œ์— ๋ฌธ์ œ๊ฐ€ ์žˆ๋‹ค๋Š” ํ•™์ž๋“ค์˜ ์ง€์ ๊ณผ ๊ถค๋ฅผ ๊ฐ™์ด ํ•œ ๊ฒƒ์ด๋ผ ๋ณผ ์ˆ˜๋„ ์žˆ์„ ๊ฒƒ์ด๋‹ค. โ€˜์„ฑ ๊ด€๋ จ ์ฃผ์ œ์— ๋Œ€ํ•œ ํ˜‘์ƒ๋ ฅโ€™ ์˜์—ญ์ด ์œ ์˜ํ•˜์ง€ ์•Š์€ ์ด์œ ๋Š” ์ธ๋„๋„ค์‹œ์•„๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•œ ์งˆ์  ์—ฐ๊ตฌ๋กœ๋ถ€ํ„ฐ ์‹œ์‚ฌ์ ์„ ์–ป์„ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ํ•ด๋‹น ์—ฐ๊ตฌ์— ๋”ฐ๋ฅด๋ฉด, ์„ฑ ๊ด€๋ จ ์ฃผ์ œ๋ฅผ ๋‚จํŽธ/ํŒŒํŠธ๋„ˆ์™€ ์ƒ์˜ํ•˜๊ณ  ํ˜‘์ƒํ•œ๋‹ค๊ณ  ํ•˜๋”๋ผ๋„ ์—ฌ์„ฑ๋“ค์ด ์‚ฌํšŒ ๋ฐ ์‚ฌํšŒ์  ๊ทœ๋ฒ”(๊ฒฐํ˜ผ ์งํ›„ ์ž„์‹ ์„ ํ•ด์•ผ ํ•œ๋‹ค๋Š” ํ’์กฐ, ์ž๋…€๋Š” ๊ฐ๊ธฐ ๋‹ค๋ฅธ ์„ฑ๋ณ„๋กœ ํ•œ ๋ช…์”ฉ์€ ๋ฐ˜๋“œ์‹œ ์žˆ์–ด์•ผ ํ•œ๋‹ค๋Š” ํ’์กฐ ๋“ฑ)๊ณผ ์ƒํ˜ธ์ž‘์šฉํ•˜๋ฉฐ, ๊ฒฐ๋ก ์ ์œผ๋กœ๋Š” ์—ฌ์„ฑ์˜ ์„ฑ์  ์ž๊ธฐ ๊ฒฐ์ •๊ถŒ์„ ์–ต์••ํ•˜๋Š” ํ˜•ํƒœ๋กœ ๋ฐœํ˜„๋˜์—ˆ์„ ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ์ฆ‰, ๋‚จํŽธ/ํŒŒํŠธ๋„ˆ์™€ ์„ฑ ๊ด€๋ จ ์ฃผ์ œ์— ๋Œ€ํ•œ ์‹ค์ œ์  ํ˜‘์ƒ๋ณด๋‹ค๋Š” ์‚ฌํšŒ์  ์žฌ๊ตฌ์„ฑ์„ ๊ฑฐ์นœ ์—ฌ์„ฑ์˜ ์žฌ์ƒ์‚ฐ ๋ชฉํ‘œ๊ฐ€ ๋” ํฌ๊ฒŒ ์ž‘์šฉํ•œ๋‹ค๊ณ  ํ•ด์„ํ•ด๋ณผ ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํ•œ ์ƒ๊ธฐ ๊ณ ์ฐฐ์€ ์ธ๋„๋„ค์‹œ์•„ ์—ฌ์„ฑ๋“ค์˜ ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์„ ์˜ˆ๋ฐฉํ•˜๊ธฐ ์œ„ํ•ด์„œ ๋‹ค์–‘ํ•œ ๊ฐ๋„์—์„œ์˜ ์ ‘๊ทผ์ด ํ•„์š”ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์„ ์‹œ์‚ฌํ•œ๋‹ค. ํŠนํžˆ, ํ•„์š”ํ•œ ๋ณด๊ฑด์˜๋ฃŒ์„œ๋น„์Šค๋ฅผ ๋ฐ›๋Š” ๊ฒƒ์— ๋ฌธ์ œ๊ฐ€ ์žˆ๋‹ค๊ณ  ์‘๋‹ตํ•œ ์—ฌ์„ฑ๋“ค์ด ๊ทธ๋ ‡์ง€ ์•Š์€ ์—ฌ์„ฑ๋“ค์— ๋น„ํ•ด์„œ ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์„ ๊ฒฝํ—˜ํ•  ์˜ค์ฆˆ๊ฐ€ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๊ธฐ ๋•Œ๋ฌธ์—, ์ธ๋„๋„ค์‹œ์•„ ์—ฌ์„ฑ๋“ค์˜ ๋ณด๊ฑด์˜๋ฃŒ์„œ๋น„์Šค ์ ‘๊ทผ์— ๋Œ€ํ•œ ๋ฌผ๋ฆฌ์  ๋ฐ ์‹ฌ๋ฆฌ์  ์žฅ๋ฒฝ์„ ํ•ด์†Œํ•˜๋Š” ๊ฒƒ์ด ํ•„์š”ํ•œ ๊ฒƒ์œผ๋กœ ์—ฌ๊ฒจ์ง„๋‹ค. ๋˜ํ•œ, ํ”ผ์ž„๋„๊ตฌ ์‚ฌ์šฉ ์ค‘๋‹จ์„ ๊ฒฝํ—˜ํ•œ ์—ฌ์„ฑ์ด ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์„ ๊ฒฝํ—˜ํ•  ์˜ค์ฆˆ๊ฐ€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜๊ธฐ ๋•Œ๋ฌธ์— ์—ฌ์„ฑ๋“ค์ด ํ”ผ์ž„๋„๊ตฌ ์‚ฌ์šฉ์„ ์ค‘๋‹จํ•˜๋Š” ์›์ธ์„ ๊ตฌ์ฒด์ ์œผ๋กœ ํŒŒ์•…ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋” ๋‚˜์•„๊ฐ€, ์ธ๋„๋„ค์‹œ์•„ ์‚ฌํšŒ์—์„œ ์‚ฌํšŒ์  ๊ทœ๋ฒ”์ด๋‚˜ ๋ถ„์œ„๊ธฐ๊ฐ€ ์—ฌ์„ฑ๋“ค์˜ ์žฌ์ƒ์‚ฐ ๊ณ„ํš๊ณผ ๊ฑด๊ฐ•์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ๋‹ค๋Š” ์ ์„ ๊ณ ๋ คํ•˜์—ฌ ๋ณด๊ฑดํ•™์  ์ค‘์žฌ๋ฅผ ์„ค๊ณ„ํ•ด์•ผ ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ์˜ ์„ธ๋ถ€ ์˜์—ญ 4๊ฐœ ์ค‘ 1๊ฐœ์˜ ์˜์—ญ๋งŒ์ด ์œ ์˜ํ•˜๊ฒŒ ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์— ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค๊ณ  ๋‚˜ํƒ€๋‚ฌ์ง€๋งŒ, ์ด ๊ฒฐ๊ณผ๋งŒ์„ ํ†ตํ•ด ์ธ๋„๋„ค์‹œ์•„์˜ ์˜๋„์น˜ ์•Š์€ ์ž„์‹  ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ๊ฐ€ ์˜๋ฏธ๋ฅผ ๊ฐ–์ง€ ์•Š๋Š”๋‹ค๊ณ  ๋‹จ์ •์ง“๊ธฐ๋Š” ์–ด๋ ต๋‹ค. ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ๋“ค์ด ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ๊ฐ€ ์‚ฌํšŒ์ ์œผ๋กœ ์—ฌ๋Ÿฌ ๊ด€๋ จ ๋ถ„์•ผ์—์„œ ํŽธ์ต๋“ค์„ ์‚ฐ์ถœํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์‹ค์ฆ์  ๊ทผ๊ฑฐ๋“ค์„ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฐ ๋งฅ๋ฝ์—์„œ, ๋ณธ ์—ฐ๊ตฌ๋Š” ์ธ๋„๋„ค์‹œ์•„ ์‚ฌํšŒ์—์„œ ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ์™€ ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ๊ฐ„์˜ ๊ด€๋ จ์„ฑ์„ ํƒ๊ตฌํ–ˆ๋‹ค๋Š” ์˜์˜๋ฅผ ๊ฐ–๋Š”๋‹ค. ํ•˜์ง€๋งŒ ์˜๋„์น˜ ์•Š์€ ์ž„์‹ ์„ ์˜ˆ๋ฐฉํ•˜๊ธฐ ์œ„ํ•ด ์—ฌ์„ฑ๋“ค์˜ ์—ญ๋Ÿ‰์„ ๊ฐ•ํ™”ํ•˜๊ณ  ๊ถŒ์ต์„ ์‹ ์žฅ(์ž„ํŒŒ์›Œ๋จผํŠธ)ํ•˜๋Š” ์ค‘์žฌ์˜ ํšจ๊ณผ์„ฑ์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ถ”๊ฐ€์ ์ธ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•  ๊ฒƒ์œผ๋กœ ์—ฌ๊ฒจ์ง„๋‹ค. ๋งŽ์€ ํ•™์ž๋“ค์ด ์ง€์ ํ–ˆ๋“ฏ, ๊ธฐ์กด์˜ ์—ฌ์„ฑ ์ž„ํŒŒ์›Œ๋จผํŠธ๋ฅผ ์–‘์ ์œผ๋กœ ์ธก์ •ํ•˜๋Š” ๋„๊ตฌ์— ๋Œ€ํ•œ ์ˆ˜์ •๊ณผ ๊ฐœ๋ฐœ์ด ์š”๊ตฌ๋˜๋ฉฐ, ์—ฌ์„ฑ๋“ค์˜ ์‚ฌํšŒ์  ์ƒํ˜ธ์ž‘์šฉ๊ณผ ์ž„ํŒŒ์›Œ๋จผํŠธ์˜ ์—ญ๋™์ , ๋‹ค์ธต์  ๋ฐ ๋‹ค์ฐจ์›์  ํŠน์„ฑ์„ ๊ณ ๋ คํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ถ”๊ฐ€์ ์ธ ํ˜ผํ•ฉ์—ฐ๊ตฌ ๋ฐ ์งˆ์ ์—ฐ๊ตฌ๊ฐ€ ๋ณ‘ํ–‰๋˜๋Š” ๊ฒƒ์ด ํ•„์š”ํ•˜๋‹ค.Chapter 1. Introduction 1 1.1. Background 1 1.2. Purpose of Study 3 1.3. Hypothesis 4 Chapter 2. Literature Review 5 2.1. Literature Review 5 2.1.1. The main variable: Women's empowerment 5 2.1.2. The outcome variable: Unintended pregnancy 8 2.1.3. The effect of women's empowerment on woman-centered health outcomes 10 2.2. Theoretical Framework 12 Chapter 3. Methods 13 3.1. Data Sources and Study Sample 13 3.2. Study Design 15 3.3. Variables 16 3.4. Ethical Considerations 27 Chapter 4. Results 28 Chapter 5. Discussion 50 Chapter 6. Conclusion 58 Abstract in Korean 61 Bibliography 66 Appendix 74์„

    What are the relationships between the degree of pregnancy intention and key maternal and neonatal health outcomes in the Mchinji district of Malawi?

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    Background Every year 85 million women experience an unintended pregnancy. Unintended pregnancies may pose increased risks to mother and baby but the evidence is scarce and methodologically limited. This research aims to fill the gap in our knowledge about the pattern of pregnancy intention and the relationships between pregnancy intention and miscarriage, stillbirth, low birthweight, neonatal death and postnatal depression in a low-income country. Methods I validated the London Measure of Unplanned Pregnancy (LMUP) in the Chichewa language and used it to assess the degree of pregnancy intention of 4,244 pregnant women in Mchinji District, Malawi. Pregnancy outcome was ascertained after the neonatal period. I analysed these data to examine the determinants of pregnancy intention and the relationships between pregnancy intention and pregnancy outcomes using multivariate hierarchical regressions. I conducted focus group discussions on postpartum family planning (PPFP). Results The Chichewa LMUP is valid in Malawi and shows a similar pattern of pregnancy intention to the UK. Young, unmarried women having their first child, older, married women who have completed their family or who have recently given birth and women who have experienced depression or intimate partner violence are at increased risk of unintended pregnancies. The more unplanned a womanโ€™s pregnancy is, the less likely she is to access adequate care. More planned pregnancies have a lower risk of postnatal depression and possibly stillbirth; there was no significant relationship between pregnancy intention and miscarriage, low birthweight or neonatal death. Conclusion To prevent unintended pregnancies, at-risk women should be targeted by family planning services. These services, particularly PPFP, need strengthening. Including the LMUP in routine antenatal care would identify women who are at risk of inadequate care uptake, stillbirth and postnatal depression. During pregnancy these women should be given additional support to mitigate these risks. They should be followed-up postnatally to detect depression and prevent future unintended pregnancies through PPFP

    What has reproductive health decision-making capacity got to do with unintended pregnancy? Evidence from the 2014 Ghana Demographic and Health Survey.

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    INTRODUCTION: Women's reproductive health decision-making is indispensable for improving their reproductive health and achieving Sustainable Development Goal three. This study explored the association between reproductive health decision-making capacity and unintended pregnancy among women in Ghana. MATERIALS AND METHODS: We used data from the 2014 version of the Ghana Demographic and Health Survey. The unit of analysis for this study was pregnant women at the time of the survey (679). Bivariate and multivariable analyses were conducted using Pearson chi-square tests and binary logistic regression respectively. RESULTS: We found that women who had the capacity to make reproductive health decision [AOR = 0.61; CI = 0.51-0.89] were less likely to experience unintended pregnancies, compared to those who did not have the capacity. Age was found to have a statistically significant influence on unintended pregnancy, with women aged 25-29 years [AOR = 0.29; CI = 0.13-0.63], 30-34 years [AOR = 0.18; CI = 0.08-0.45], and 35-39 years [AOR = 0.26; CI = 0.10-0.68] being less likely to experience unintended pregnancy compared to those aged 15-19 years. Women with primary level of education were more likely to have unintended pregnancies, compared to those with no education [AOR = 2.07; CI = 1.12-3.84]. CONCLUSION: This study has filled the gap in the already existing literature on the association between reproductive health decision making capacity and unintended pregnancy in Ghana and has created a room for specific interventions geared towards reducing unintended pregnancies, especially among women who are not capable of making reproductive health decisions, women aged 15-19 years, those with primary education, Traditionalists and unmarried women

    Mapping Research Trends on Illegal Abortion Behavior: A Bibliometric Study

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    Research on the topic of illegal abortion is quite a concern, but more discussed macro in a legal point of view and health policy. Micro-analysis with a similar topic has been conducted on a limited basis with the background of the issue of illegality which cannot prevent abortion behavior. This study aims to analyze the scientific literature to find general trends and analyze indicators related to the topic of behavior from illegal abortion practices around the world. This paper uses a bibliometric methodology, utilizing data taken from the Scopus database from 1968 to 2021, and visualizing the data using the VOSviewer. 310 papers from different nations were uncovered in the investigation. When the study's findings are compared to the total number of citations and related publications, it becomes clear that the United States and the United Kingdom continue to dominate research on illegal abortion activity. The great majority of articles on this topic are mostly in the social science sector. By identifying keywords, it can be seen that the majority of research topics continue to center on large-scale issues including abortion, contraception, and unsafe abortion. This study enables us to define unlawful abortion in an individual setting as the behavior a person engages in when deciding to abort a pregnancy, regardless of whether it is carried out by themself, another person, medical professional, health workers, health facilities, or by other parties that deviate from the abortion laws that are in effect in the nation. This study offers crucial conclusions and suggestions for future thematic research opportunities that are sustainable. &nbsp
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