Unintended Pregnancy among Married Pregnant Women in Nepal

Kalpana Bastola; Subas Neupane; Kishor Hadkhale; Tarja I Kinnunen

doi:10.4172/2325-9795.1000197

Research Article, J Womens Health Issues Care Vol: 4 Issue: 4

Unintended Pregnancy among Married Pregnant Women in Nepal

*Kalpana Bastola^, Subas Neupane, Kishor Hadkhale and Tarja I Kinnunen**
School of Health Sciences, University of Tampere, 33014 University of Tampere, Finland
Corresponding author : Bastola Kalpana School of Health Sciences, University of Tampere, 33014 University of Tampere, Finland Tel:+358449727708; Fax:+358 3 3641 511 E-mail: Bastola.Kalpana.X@student.uta.fi
Received: December 30, 2014 Accepted: July 01, 2015 Published: July 03, 2015
Citation: Bastola K, Neupane S, Hadkhale K, Kinnunen TI (2015) Unintended Pregnancy among Married Pregnant Women in Nepal. J Womens Health,Issues Care 4:4. doi:10.4172/2325-9795.1000197

Abstract

Unintended Pregnancy among Married Pregnant Women in Nepal

Introduction: Unintended pregnancy is an issue for many women irrespective of the place of residence or country. This study examined the prevalence of unintended pregnancy and the factors associated with it among pregnant married women of Nepal.

Methodology: This study utilizes the data from Nepal Demographic and Health Survey (NDHS) 2011 which is a nationally representative cross-sectional survey. The survey was conducted among all women in the reproductive age group (15-49 years). However, the present analysis is restricted to married women who were pregnant at the time of survey (N=798). Logistic regression analysis was used to assess the association of unintended pregnancy with the socio-demographic factors.

Results: More than half (54.5%) of the currently pregnant women reported that their current pregnancy was unintended. The multivariate adjusted results indicate that older and educated women were less likely to experience unintended pregnancies. Unintended pregnancies were more common among women belonging to poorer quintile of the wealth index (OR 4.83, 95% CI 2.64-8.86), having more than two children (OR 6.15, 95 % CI 3.66- 10.33) or women with the history of terminated pregnancy (OR 2.85, 95% CI 1.70-4.70) as compared to the respective reference groups.

Conclusion: Unintended pregnancies are still very common in Nepal. Older and educated women were less vulnerable to unintended pregnancy whereas women with more than two children and women having the history of terminated pregnancy were more vulnerable to it. Therefore, programs and policies should be aimed at these women to reduce the number of unintended pregnancies.

Download PDF

Keywords
Unintended pregnancy; Nepal; Demographic and health survey
Introduction
Becoming pregnant and having a baby are among the major events in the life of female as well as for the whole family. Santali et al. [1] defined unintended pregnancy as, “pregnancies that are reported to have been either unwanted (i.e., they occurred when no children, or no more children, were desired) or mistimed (i.e., they occurred earlier than desired)”. The targets of United Nations (UN) millennium development goal (MDG) 5 is to improve maternal health by reducing the maternal mortality ratio by three quarters and achieve universal access to reproductive health [2]. Providing all women access to high-quality family planning services would reduce unintended pregnancies, contributing directly to three MDGs: promoting gender equality and empowering women (MDG 3); reducing child mortality (MDG 4); and improving maternal health (MDG 5) [2].
Unintended pregnancy is not a problem of only low or middle income countries. Every second pregnancy in US, Japan and every third pregnancy in UK and France were reported as unintended [3,4]. In Jordan, Ecuador, Ethiopia and Nepal the prevalence of unintended pregnancy was almost 40 percent [5-8]. One in every three women in Bangladesh had an unintended pregnancy (9), but only one fifth of all pregnancies were reported to be unintended in Indonesia [9,10] and in India [11]. In a multicountry study including ten countries mainly from Africa, Asia and South-America, the prevalence of unintended pregnancy varied between countries. The lowest prevalence of unintended pregnancy was in Samoa (13 %) followed by Japan (20 %) whereas in Thailand, Tanzania and Bangladesh it was almost 35 percent. Peru, Brazil and Namibia had the highest prevalence of 63 percent, 55 percent and 50 percent respectively [12].
Various studies reveal that unintended pregnancy is linked with the increase in the morbidity and mortality in women and also with neglect in the care of child [4,11,13-17]. In the USA, women with unintended pregnancy were less likely to initiate and continue breastfeeding to their baby than women with intended pregnancy [16,18]. Infants and toddlers with both parents reporting them as unintended had an increased risk of being stunted as compared with children both of whose parents intended the pregnancy [17,19]. Children from unintended pregnancies were more likely to receive inadequate childhood vaccination [11,19] and were more likely than infants from planned pregnancies to have low birth weight [20]. An earlier study from Nepal found that the mothers with unintended pregnancy were more likely to receive inadequate prenatal care and to prefer home births [19]. The multicountry study also reported that women with a history of intimate partner violence had significantly higher odds of unintended pregnancy [12].
Despite the widely available family planning effort to reduce the proportion of unwanted pregnancies, the rate of unintended pregnancies is still significantly large in Nepal [21]. Unintended pregnancy can result directly from the contraceptive failure, inconsistent use of contraceptives, lack of knowledge on contraceptives and sometimes even rape [22]. In the USA, half of the unintended pregnancies were the results of contraceptive failure whereas almost two-thirds of unintended pregnancies in France were due to the results of contraceptive failure [3]. In the low and middle income countries, contraceptive failure accounts to nearly 15 percent [23]. One earlier study from the UK found that 34 percent of women with unintended pregnancy blamed contraceptive failure [24]. The number of previous births or parity was strongly related with the higher odds of unintended pregnancy in Ethiopia and Jordan [7,10]. Studies from Nepal, Ethiopia and Jordan among married women showed that older women and women with early age at marriage were more likely to have an unintended pregnancy compared to younger women and those with delayed age at marriage [7,8,10]. In the USA, unmarried women, black women, and women with less education or income were more likely to experience unintended births compared with married, white, and high-income women and women with college education [25].
Very few studies have focused on the determinants of unintended pregnancy particularly in Nepal. Therefore, this study provides and discusses a very important issue that needs attention from all the sectors of the society for the improvement in the health and wellbeing of pregnant mother and the baby. The aim of this study is to find out the prevalence of unintended pregnancy and the factors associated with it among married women who were pregnant at the time of survey in Nepal.
Materials and Methods
Data source and study population
This study is based on the data from the Nepal Demographic and Health Survey (NDHS) 2011, which was carried out by the Department of Health Services, Ministry of Health and Population in Nepal [21]. The 2011 NDHS is the fourth nationally representative comprehensive household survey conducted as part of the worldwide DHS project in the country. Ethical approval to conduct the survey was obtained from the National Health and Research Council in Nepal. All participants provided a verbal informed consent before the interview [21]. Permission to use the Nepal DHS data was obtained from MEASURE DHS ICF International, USA.
The NDHS used a multistage stratified cluster random sampling method. The study focused on different population, health and nutrition issues among women aged 15-49 years, men aged 15-59 and children < 5 years of age [21]. Interviews were completed for 12,674 women, resulting in a response rate of 98 percent. The interview was conducted in three main local languages (Nepali, Maithali and Bhojpuri) by trained interviewers. Questionnaires were finalized after the pre-test. The present study focused only on married women who were pregnant at the time of survey (n=798).
Measurement of variables
The outcome variable ‘unintended pregnancy’ was measured by the following question, “At the time you became pregnant, did you want to become pregnant then, did you want to wait until later, or did you not want to have any (more) children at all?” The three allowed response options were “wanted then” (planned), “wanted the pregnancy to happen later” (mistimed) and “did not want at all” (unwanted). In this study, those respondents who mentioned their current pregnancy was either mistimed or unwanted were merged and consider as ‘unintended pregnancy’ (Table 1). Otherwise the pregnancy was regarded as intended. Socio-demographic, pregnancy and autonomy related variables were used as independent variables and they are described in the Table 1.
	Table 1: Operational definition of variables and their categorization.
Statistical Analysis
All statistical tests were done using the Statistical Package for Social Sciences (SPSS for windows version 17). Cross tabulation with Pearson chi-square test was used to test the association between pregnancy intention and pregnancy related variables and sociodemographic variables. Sampling weights were used in the analyses when calculating the demographic statistics according to the instructions of DHS in order to make the data representative at the national level.
The bivariate logistic regression analyses were first used to identify the variables which are associated with the women’s pregnancy intention status (P<0.05). Odds Ratio (OR) and their 95% confidence intervals (CI) were calculated in different logistic regression models. Model I represents the unadjusted bivariate model whereas Model II was a multivariate model where all the studied variables were simultaneously adjusted using backward conditional method.
Results
More than half (n=430, 55%) of the pregnancies were unintended including two fifths (n=311, 40%) women who never wanted to become pregnant and nearly 14 percent units (n=108) who wanted to become pregnant later. Table 2 shows the demographic characteristics for all women and also separately for women with an unintended or an intended pregnancy. Several differences were observed between these two groups. For example, women with an unintended pregnancy were more often from the rural or mountainous area, poor, with no education, working in the agriculture or had more previous children than women with an intended pregnancy.
	Table 2: Demographic characteristics of all respondents and by pregnancy intention, numbers (%)¹.
Table 3 shows the odds ratios (95% CIs) for unintended pregnancy by the socio-demographic variables and other pregnancy related variables based on two logistic regression models. Findings from the unadjusted model (Model 1) shows that women in the oldest age category (35-49) years, living in the rural area, poor, working in the agricultural sector, having more than two children and having history of terminated pregnancy had the higher odds of unintended pregnancy compared to their respective reference groups. When the other covariates were included in Model II, the direction of the association between age and unintended pregnancy was reversed, which showed that women in the older age group were less likely (OR=0.18) to experience unintended pregnancy than women in the youngest age group. Women of the poorer quintile of wealth index had the highest odds (OR 4.83) of unintended pregnancy as compared to women belonging to any other of the quintiles. However, the association between quintile of wealth index and the prevalence of unintended pregnancy was not linear. Women with primary level of education were less likely (OR 0.32) to experience unintended pregnancy than women with no education at all. Women with more than two children ever born were more likely (OR 6.15) to experience unintended pregnancy than women with less than two children. In the same way, women with the history of terminated pregnancy were more likely (OR 2.85) to experience unintended pregnancy than women without history of unintended pregnancy.
	Table 3: Odds ratio (OR) and 95% confidence interval (CI) for unintended pregnancy among currently pregnant married women by socio-demographic, pregnancy related and autonomy related variables.
Discussion
In a nationally representative sample of 15-49 year-old pregnant women in Nepal, a high prevalence of unintended pregnancy (mistimed 40%, unwanted 15%) was found. Women in the oldest age group and those with primary education were less likely to experience unintended pregnancy than the other groups of women. Women of the poorer wealth quintile, having more than two children ever born and having a history of terminated pregnancy were more likely to experience an unintended pregnancy.
The direction of the association between age and unintended pregnancy was different in the crude and the adjusted regression models. When e.g. stratifying the cross-tabulation by the number of previous deliveries, the older women were less likely to perceive their pregnancy as unwanted especially if they did not have any previous children (data not shown). However, we were not able to stratify the Model II by parity as the model did not fit well possibly due to small numbers of women in some cells. The wealth index was found to be significantly associated with higher prevalence of unintended pregnancy in both models. However, the association was not linear which makes it difficult to interpret.
An earlier study based on DHS survey from Nepal in 2006 found that 41 percent of the current pregnancies were unintended [8] whereas this study reveals that more than half (55%) of the current pregnancies were unintended. Since both of the studies were conducted in same country and draw the data from the same source population with similar sampling procedures, the results are comparable. This shows that the prevalence of unintended pregnancy is increasing in Nepal.
Earlier studies using DHS data based on ever married women in Bangladesh and Indonesia found that the prevalence of unintended pregnancy was nearly 30 percent and 20 percent respectively [9-10]. Similarly, DHS data from Ecuador shows that the prevalence of unintended pregnancy was almost 38 percent among women giving birth to a live singleton baby within two years prior to the survey date [20]. Ecuador, Indonesia and Nepal are very different kind of countries and differ a lot in terms of culture and religions. However, same standard questionnaire and methodology were used in all the countries making the results comparable to each other. Some other studies have reported the prevalence of unintended pregnancy to be nearly 43 percent among married women in reproductive age in Southern Ethiopia [7], 40 percent among women in reproductive age interviewed for Jordan Family Health Survey in Jordan [5] and 47 percent among (35-49 years) in Japan [4]. The World Health Organisation’s multicountry study revealed the overall prevalence of unintended pregnancy in these ten countries to be 38 percent, but it varied from 13 percent in Samoa to 63 percent in Peru [12]. However, the study was conducted among women whose last pregnancy was up to five years prior to the survey whereas the current study was among women who were pregnant at the time of the survey. Our findings suggest that the prevalence of unintended pregnancy among married women in Nepal was higher than that in these other countries, except for Brazil and Peru.
Earlier studies from Nepal, Indonesia and Bangladesh revealed that the higher the age of mother, the higher the odds of experiencing an unintended pregnancy [8-10,26] whereas the current study found that unintended pregnancy was more likely among younger women. The previous study from Nepal didn’t include the children ever born variable in the logistic regression model and also they have other different variables (listen to radio, watches television, family planning worker visit, travel time to nearest family planning centre, knowledge of family planning, ever use of family planning etc) as compared to the present study [8]. Previous studies conducted in Jordan, Indonesia and Bangladesh found that, the number of previous births or parity was strongly related with the odds of unintended pregnancy [5,9-10,26] which is similar to the findings of present study. An earlier study from Bangladesh based on DHS data found that women in the richer and richest wealth index category were less likely to report unintended pregnancy [9], which is in agreement with our findings showing that women in the poorer wealth index category were more likely to report unintended pregnancy.
It is evident from the present and the previous studies that the number of previous children a woman had is a distinct determinant of whether or not the pregnancy intended or unintended. It may therefore be effective to focus family planning campaigns more intensively on those families that already have two or more children. Overall, there is a substantial demand among Nepalese women for effective contraceptive methods. In 2011, almost one in four houses was female headed whereas nearly one in five women had ownership of house and land or land only in Nepal. Similarly, every two out of five women have no education in Nepal [27]. However, knowledge of contraception is universal and nearly half of the currently married women are using a method of contraception [21]. Twenty-seven percent of currently married women have an unmet need for family planning services, with 10 percent having an unmet need for spacing and 17 percent having an unmet need for limiting. Unmet need is higher in rural than in urban areas and is the highest among the women of age 15-19 years. One of the most common reasons for abortion among women was an unintended pregnancy (30 %) [21]. In Nepal, there is still the practice of early marriage whereas in some communities even child marriage is practiced. A delay in the age at marriage shifts the time for sexual activities especially in the Nepalese context. Therefore, the government of Nepal should address the issue of early marriage by investing in proper education and women empowerment. Unintended pregnancy is clearly a public health issue, a gender issue, and a population issue. Effectively addressing such a problem will result in multidimensional improvements for Nepalese women and Nepal as a whole.
Strengths of the study
The present study focused on married women who were pregnant at the time of the survey in Nepal. The DHS 2011 data are nationally representative and have been taken as the reference data for national policymaking. The results are also comparable to the DHS data from other countries. The questionnaire used in the survey was very specific, approved and derived from the DHS standard core questionnaires. The overall response rate of the survey was nearly 98%, which is extremely good in population studies. There were also very few missing data. A potential recall bias was addressed by only including the women who were pregnant at the time of survey instead of including all those who had given any births five years prior to the survey. Potential confounding factors were taken into account at analysis level by using multivariate models.
Limitations of the study
Studies on unintended pregnancies are complicated by the fact that women’s perception of whether the pregnancy was planned or wanted can change over time. The answer is more likely to be accurate if pregnancy intention is asked in the early stage rather than in the late stage of pregnancy. The present study could not consider the time for how long the women had been pregnant. One of the major limitations of this study is that this study was unable to study the relationship between contraceptive use and unintended pregnancy due to lack of availability of data on contraceptive use. However, many studies across the world have already shown a relationship between these two variables. In the present study, knowledge on family planning was taken into account but at a very rough level only. The data on whether the respondents had heard about family planning from different sources or not might not reveal the true knowledge on family planning. People might have just heard about it but do not know how to use it or to have access to it. Since the study is a cross sectional study, no causal relationship between the variables can be proved. There is also a possibility of residual confounding due to unmeasured and unknown confounding factors.
Conclusion
This study shows that more than a half of the pregnancies were unintended, which is already a challenging issue. While older age and having education were associated with lower likelihood of an unintended pregnancy, poor economic condition of the family, a higher number of previous births and the history of terminated pregnancy were found to increase the likelihood of an unintended pregnancy. These factors should be taken into account when promoting family planning in Nepal in the future.
References
Santelli J, Rochat R, Hatfield-Timajchy K, Gilbert BC, Curtis K, et al. (2003) The measurement and meaning of unintended pregnancy. Perspect Sex Reprod Health 35: 94-101. United Nation Development Program (2015) Millennium Goals. Black KI, Gupta S, Rassi A, Kubba A (2010) Why do women experience untimed pregnancies? A review of contraceptive failure rates. Best Pract Res Clin ObstetGynaecol 24: 443-455. Goto A, Yasumura S, Reich MR, Fukao A (2002) Factors associated with unintended pregnancy in Yamagata, Japan. SocSci Med 54: 1065-1079. Johnson K, Al Zoubi O, Wulfe M (2004) Mistimed and unwanted pregnancies in Jordan, Department of Statistics, Amman, Jordan. Eggleston E (2000) Unintended pregnancy and women's use of prenatal care in Ecuador. SocSci Med 51: 1011-1018. Geda NR and Lako TK (2011) A population based study on unintended pregnancy among married women in a district in Southern Ethiopia. J Geography and Regional Planning 4:417-427. Adhikari R, Soonthorndhada K, Prasartkul P (2009) Correlates of unintended pregnancy among currently pregnant married women in Nepal. BMC Int Health Hum Rights 9: 17. Kamal M, Islam A (2011) Prevalence and socioeconomic correlates of unintented pregnancy among women in rural Bangladesh. SaludPublica Mex 53: 108-115. Jaeni N, McDonald P, Utomo ID (2009) Determinants of unintended pregnancy among ever-married women in Indonesia: An analysis of the 2007 IDHS. ANU College of Arts & Social Science. Singh A, Singh A, Mahapatra B (2013) The consequences of unintended pregnancy for maternal and child health in rural India: evidence from prospective data. Matern Child Health J 17: 493-500. Pallitto CC, García-Moreno C, Jansen HA, Heise L, Ellsberg M, et al. (2013) Intimate partner violence, abortion, and unintended pregnancy: results from the WHO Multi-country Study on Women's Health and Domestic Violence. Int J GynaecolObstet 120: 3-9. Gessessew A (2010) Abortion and unwanted pregnancy in Adigrat Zonal Hospital, Tigray, north Ethiopia. Afr J Reprod Health 14: 183-188. Why do so many women still die in pregnancy or childbirth? (2014) World Health Organization. David HP (2011) Born unwanted: mental health costs and consequences. Am J Orthopsychiatry 81: 184-192. Sable MR, Washington CC, Schwartz LR, Jorgenson M (2007) Social well-being in pregnant women: intended versus unintended pregnancies. J PsychosocNursMent Health Serv 45: 24-31. Shapiro-Mendoza C, Selwyn BJ, Smith DP, Sanderson M (2005) Parental pregnancy intention and early childhood stunting: findings from Bolivia. Int J Epidemiol 34: 387-396. Taylor JS, Cabral HJ (2002) Are women with an unintended pregnancy less likely to breastfeed? J FamPract 51: 431-436. Singh A, Singh A, Thapa S (2015) Adverse consequences of unintended pregnancy for maternal and child health in Nepal. Asia Pac J Public Health 27: NP1481-1491. Eggleston E, Tsui AO, Kotelchuck M (2001) Unintended pregnancy and low birthweight in Ecuador. Am J Public Health 91: 808-810. Ministry of Health and Population (MOHP) Nepal, New ERA, and ICF International Inc. (2012). Nepal demographic and health survey 2011. Kathmandu. Nepal: Ministry of Health and Population, New ERA, and ICF International, Calverton, Maryland. Klima CS (1998) Unintended pregnancy. Consequences and solutions for a worldwide problem. J Nurse Midwifery 43: 483-491. World health Organisation (2015), Family Planning. Henderson D (2009) A third of women in UK who have an unintended pregnancy blame contraceptive failure. BMJ 339: b2975. Mosher WD, Jones J, Abma JC (2012) Intended and unintended births in the United States: 1982-2010. Natl Health Stat Report : 1-28. Rahman M (2012) Women's autonomy and unintended pregnancy among currently pregnant women in Bangladesh. Matern Child Health J 16: 1206-1214. Central Bureau of Statistics (2015) Government of Nepal

Journal of Womens Health, Issues and CareISSN: 2325-9795

Unintended Pregnancy among Married Pregnant Women in Nepal

Abstract

Keywords

Introduction

Materials and Methods

Results

Discussion

Conclusion

References

Track Your Manuscript

Explore SciTechnol

Google Scholar citation report

Citations : 1315

Journal of Womens Health, Issues and Care peer review process verified at publons

Journal Highlights

Tweets by @

Media Partners

Associations