Correlates of unintended pregnancy among currently pregnant married women in Nepal

  • Ramesh Adhikari1, 2Email author,

    Affiliated with

    • Kusol Soonthorndhada2 and

      Affiliated with

      • Pramote Prasartkul2

        Affiliated with

        BMC International Health and Human Rights20099:17

        DOI: 10.1186/1472-698X-9-17

        Received: 23 October 2008

        Accepted: 11 August 2009

        Published: 11 August 2009

        Abstract

        Background

        Women living in every country, irrespective of its development status, have been facing the problem of unintended pregnancy. Unintended pregnancy is an important public health issue in both developing and developed countries because of its negative association with the social and health outcomes for both mothers and children. This study aims to determine the prevalence and the factors influencing unintended pregnancy among currently pregnant married women in Nepal.

        Methods

        This paper reports on data drawn from Nepal Demographic and Health Survey (NDHS) which is a nationally representative survey. The analysis is restricted to currently pregnant married women at the time of survey. Association between unintended pregnancy and the explanatory variables was assessed in bivariate analysis using Chi-square tests. Logistic regression was used to assess the net effect of several independent variables on unintended pregnancy.

        Results

        More than two-fifth of the currently pregnant women (41%) reported that their current pregnancy was unintended. The results indicate that age of women, age at first marriage, ideal number of children, religion, exposure to radio and knowledge of family planning methods were key predictors of unintended pregnancy. Experience of unintended pregnancy augments with women's age (odds ratio, 1.11). Similarly, increase in the women's age at first marriage reduces the likelihood of unintended pregnancy (odds ratio, 0.93). Those who were exposed to the radio were less likely (odds ratio, 0.63) to have unintended pregnancy compared to those who were not. Furthermore, those women who had higher level of knowledge about family planning methods were less likely to experience unintended pregnancy (odds ratio, 0.60) compared to those having lower level of knowledge.

        Conclusion

        One of the important factors contributing to high level of maternal and infant mortality is unintended pregnancy. Programs should aim to reduce unintended pregnancy by focusing on all these identified factors so that infant and maternal mortality and morbidity as well as the need for abortion are decreased and the overall well-being of the family is maintained and enhanced.

        Background

        The issue of unintended pregnancy has been essential to demographers seeking to understand fertility, to public health practitioners in preventing unintended childbearing and to both groups in promoting a woman's ability to determine whether and when to have children [1]. Unintended pregnancy can result from contraceptive failure, non-use of contraceptives, and less commonly, rape and it can create serious health consequences for women, children and family [2].

        There is very little published literature that focuses on the determinants of unintended pregnancy in developing countries and particularly in Nepal. However, some research studies conducted outside of Nepal have shown the relation between unintended pregnancy and socio-economic and demographic characteristics. Moreover, there is very little known about unintended pregnancy in cultural contexts.

        An unintended pregnancy is a pregnancy that is either mistimed (i.e., they occurred earlier than desired) or unwanted (i.e. they occurred when no children, or no more children were desired) at the time of conception [1]. Unintended pregnancy is a potential hazard for every sexually active woman. It is a worldwide problem that affects women, their families, society and nation. A complex set of social and psychological factors puts women at risk of unintended pregnancy. Abortion is a frequent consequence of unintended pregnancy and in the developing countries it can result into serious long-term, negative health effects including infertility and maternal death [2].

        Women living in every country, irrespective of the development status, have been facing the problem of unintended pregnancy. Over 100 million acts of sexual intercourse take place each day resulting in around 1 million conceptions, about 50 percent of which are unplanned and about 25 percent are definitely unwanted [3]. The data suggest that approximately 49 percent of all pregnancies in the United States [4], 46 percent in Yamagata, Japan [5], 35 percent in both Iran [6] and Nepal [7] are unintended. Almost all occurred due to non-use of family planning method or contraception failure. About 50 percent of all unintended pregnancies in the United States are due to contraceptive failure [8]. Therefore, unintended pregnancy is an issue that cannot be ignored. Many pregnant women will want or need to end a pregnancy to avoid risks to their lives and health, psychological trauma, and socioeconomic turmoil [9].

        International Conference on Population and Development (ICPD) held in Cairo in 1994 and fourth world conference on women held in 1995 in Beijing have emphasized women empowerment as a basic tool for a country's overall development and improving the quality of life of the people[10]. ICPD declared that advancing gender, empowering women and eliminating all kinds of violence against women, and ensuring women's ability to control their own fertility are cornerstones of population and development related programs [11].

        A study conducted among college students in Nepal revealed that only about half of the male students (55%) had used condom at the first premarital sexual intercourse [12]. Similarly, the other study showed that 20 percent of rural and 16 percent of urban married women aged 15–49 reported method failure as the reason for their unintended pregnancy [13]. Furthermore, the other research estimated that during the first year of vasectomy, 1.7 percent women could become pregnant [14] which leads to the higher number unintended pregnancies and abortions. Furthermore, a study conducted at 5 major hospitals showed that abortion related hospitalization accounted for 20 percent to 48 percent of the total obstetric and gynecological cases [15]. Despite the legalization of abortion laws (March 2002 onwards) in the country, due to the lack of awareness about the law and facility centers, many women still seek abortion clandestinely and most often they consult unskilled or unqualified health workers, resulting in high rates of abortion related morbidity and mortality [16].

        The underlying cause of high prevalence of unintended pregnancy needs further investigation and exploration in order to be better understood and appropriately addressed by reproductive health programs. It is essential to identify the risk factors of unintended pregnancy and to provide services to address those who are at risks. To develop effective strategies for the prevention of unintended pregnancies, it is necessary to understand the factors affecting unintended pregnancies. It is hypothesized that women in the vulnerable group (illiterate, living in the rural area, working on agricultural sector), and who are not exposed to mass media lead to low knowledge of family planning methods and low utilization of the health services which in turn lead to higher unintended pregnancy.

        This study aims to determine the prevalence and the factors influencing unintended pregnancy among currently pregnant married women in Nepal. The findings of this study aim to guide reproductive health program planners and policy makers to understand various factors influencing unintended pregnancy and to assist in implementation of the reproductive health program which will decrease unintended pregnancy as well as reduce the risk of maternal and infant morbidity and mortality. Though there are very few studies on unintended pregnancy in Nepal, this type of research which focuses on currently pregnant married women has not yet been undertaken in the country.

        Methods

        This paper reports on data drawn from Nepal Demographic and Health Survey (NDHS), 2001 which is a nationally representative sample survey. This cross sectional survey was conducted among married women in the reproductive age (15–49 years). The primary purpose of the NDHS is to generate recent and reliable information on fertility, family planning, infant and child mortality, maternal and child health, and nutrition. The sample for the survey is based on a two-stage, stratified, nationally representative sample of households. At the first stage of sampling, 257 PSUs, 42 in urban areas and 215 in rural areas, were selected using systematic sampling with probability proportional to size method.

        Out of 8,726 married women of the reproductive age interviewed, 751 (8.6%) were currently pregnant at the time of the survey. Among those women, 28 respondents were excluded from the analysis due to missing data on the intention status for their current pregnancy. Only currently pregnant women were selected for this study to minimize underreporting of unplanned pregnancies. It also reduces recall bias as it gathers information on the current pregnancy and not on the pregnancy history.

        Pregnancy planning is measured by respondents' perceived desire of current pregnancy. The question was "At any 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 options were wanted then (planned), wanted the pregnancy to happen later (mistimed) and did not want at all (unwanted). Those respondents who mentioned their current pregnancy is either mistimed or unwanted were merged and consider as 'unintended pregnancy'. Thus, this variable is categorized into two categories: unintended and intended. Women's literacy status is categorized into 2 categories; illiterate and literate. The purpose is to analyze the effect of literacy status on unintended pregnancy (Table 1).
        Table 1

        Operational definitions of variables and their measurements

        Variables

        Description

        Measurement scale

        Unintended pregnancy

        Type (intendedness) of current pregnancy

        Dichotomous

          

        0 = Intended

          

        1 = Unintended

        Age of women

        Respondent's current age at time of survey

        Ordinal for bivariate analysis

          

        0 = 15–24 years

          

        1 = 25–34 years

          

        2 = 35–49 years

          

        Interval scale for multivariate

        Ideal number of children

        Women's concept or preferences about the number of children

        Ordinal for bivariate analysis

          

        1 = One

          

        2 = Two

          

        3 = Three and more

          

        Interval scale for multivariate

        Parity

        Number of children given by the respondents

        Ordinal for bivariate analysis

          

        0 = None

          

        1 = One

          

        2 = Two

          

        3 = Three and more

          

        Interval scale for multivariate

        Age at first marriage

        Respondents' completed age at the time of marriage

        Ordinal for bivariate analysis

          

        0 = Less than 16 years

          

        1 = 16 years and more

          

        Interval scale for multivariate

        Women's education

        Literacy status of women

        Ordinal

          

        0 = No education/illiterate

          

        1 = Literate

        Women's occupation

        Types of women's work

        Nominal

          

        0 = Not working/agriculture

          

        1 = Non-agriculture

        Place of residence

        Types of place of residence of the respondent

        Dichotomous

          

        0 = Urban

          

        1 = Rural

        Radio exposure

        Listen to radio every day

        Dichotomous

          

        0 = No

          

        1 = Yes

        TV exposure

        Watch television at least once a week

        Dichotomous

          

        0 = No

          

        1 = Yes

        Travel time to the nearest family planning sources

        Travel time needed to reach the nearest family planning sources from her residence

        Ordinal

          

        0 = Less than 30 minutes

          

        1 = 30–60 minutes

          

        2 = More than 1 hour

          

        3 = No response/don't know

        Family planning field worker's visit

        Women who are visited by family planning program's worker in the last 12 months

        Dichotomous

          

        0 = Not visited

          

        1 = Visited

        Religion

        Women's religion

        Dichotomous

          

        0 = Non-Hindu

          

        1 = Hindu

        Woman's autonomy

        Autonomy on own health care and how to spend own earned money

        Nominal

          

        0 = No autonomy

          

        1 = Some autonomy

        Knowledge about family planning methods

        Knowledge score of different family Planning method

        Ordinal

          

        0 = Lower knowledge

          

        1 = Higher knowledge

        Ever use of family planning method

        Respondents who had ever use of any contraceptive or not in the past

        Dichotomous

          

        0 = Never used

          

        1 = Ever used

        Association between unintended pregnancy and the explanatory variables was assessed in bivariate analysis using Chi-square tests. Logistic regression was used to assess the net effect of several independent variables on unintended pregnancy. Before the multivariate analysis, multicollinearity between the variables was assessed and the least important variables were removed from the logistic model. Statistical Package for Social Science (SPSS) was used for analysis.

        Results

        Among the surveyed married women of reproductive age, less than one in ten respondents (8.6% out of 8,726) was currently pregnant at the time of the survey. Among these currently pregnant respondents, about one-fifth mentioned that they wanted their current pregnancy later (mistimed; 21%) and the other one-fifth reported that they did not want their current pregnancy at all (unwanted; 20%). Conclusively, more than two-fifth of the currently pregnant married women (41%) reported their current pregnancies were unintended.

        When stratifying the women in different characteristics, it was found that the percentage of women who have experienced current pregnancy as unintended varied by different settings. More than two-fifth illiterate women (44%), women who had no job or worked in agricultural sector (42%), and resided in rural area (42%) had significantly higher incidence of unintended pregnancy compared to their counterparts. In terms of religion, more than half of non-Hindu women (52%) while only about two-fifth of Hindu women (39%) had reported their current pregnancy as unintended (Table 2).
        Table 2

        Pregnancy intention by selected characteristics

          

        Experience of unintended pregnancy (%)

        Total

        Number

        Demographic characteristics

           

        Age group***

        15–24

        31.3

        415

         

        25–34

        48.4

        247

         

        35–49

        76.5

        61

        Ideal number of children#

        1–2 children

        39.2

        404

         

        Three or more

        44.4

        303

        Total children ever born***

        None

        20.7

        195

         

        One

        28.8

        184

         

        Two

        48.2

        122

         

        Three or more

        64.9

        222

        Age at first marriage**

        Less than 16 years

        46.2

        339

         

        16 year or more

        36.3

        384

        Socio-economic characteristics

           

        Literacy status**

        Illiterate

        44.4

        486

         

        Literate

        34.0

        237

        Occupation

        Not working/agriculture

        41.8

        671

         

        Non agriculture

        30.4

        52

        Place of residence

        Rural

        41.7

        673

         

        Urban

        31.7

        50

        Access to health information/services

        Listens to radio **

        No

        45.3

        469

         

        Yes

        33.0

        254

        Watches television

        No

        42.5

        583

         

        Yes

        34.6

        140

        Travel time to nearest family planning center ##**

        Up to 30 minutes

        38.0

        363

         

        31–60 minutes

        45.0

        167

         

        More than one hour

        54.1

        91

        Family planning worker visit*

        Not visited

        39.8

        663

         

        Visited

        54.0

        60

        Socio-cultural factors

           

        Religion**

        Non-Hindu

        52.2

        112

         

        Hindu

        38.9

        611

        Women autonomy*

        No autonomy

        38.7

        571

         

        Some autonomy

        49.7

        152

        Knowledge and practice of family planning method

        Knowledge about family planning method**

        Lower

        46.4

        411

         

        Higher

        33.8

        312

        Ever use of family planning method

        Never use

        39.4

        518

         

        Ever use

        44.9

        205

         

        Total

        41.0

        723

        Note: * = p < .05, ** = p < .01 *** = p < .001, # Those respondents who didn't know the sources of FP methods are excluded, ## Travel time is only for those who knew the sources of FP

        As expected, the percentage of women reporting unintended pregnancies increased with age (31% of the women aged less than 25 years to 77% of the women aged 35 and above years). Similarly, women with higher birth order reported significantly higher rate of unintended pregnancy. Furthermore, women who got married at early age (before 16 years) had significantly higher rate of unintended pregnancy (46%) compared to those who got married at 16 years or later (36%).

        The result shows that the exposure to mass media is significantly negatively associated with the level of unintended pregnancy. For instance, only about one third of the respondents who were exposed to the radio have reported their current pregnancy as unintended (33%) while the proportion was more than two-fifth (45%) for those who were not exposed to radio. Similarly, access to health services is negatively associated with the proportion of unintended pregnancy. Those respondents who resided near the family planning sources (less than 30 minutes travel distance) reported significantly much lower (38%) experienced unintended pregnancy compared to those who resided far (more than 1 hour travel distance) from the family planning sources (54%). Likewise, the study found that higher the level of knowledge of family planning methods, the lower the percentage of women reporting the current pregnancy as unintended (34%). Against expectation, those respondents who were visited by family planning workers in the last 12 months had higher level of unintended pregnancy (54%) compared to those who were not visited by family planning worker (40%). Similarly, women who have some autonomy had significantly higher level of unintended pregnancy (50%) than those who have no autonomy (39%) (Table 2).

        Binary logistic regression model was used to assess the net effect of each of the independent variables on the dependent variable, while controlling for the other variables in the model. Three models had been used in the analysis. The first model contained the individual factors such as demographic characteristics, socio-economic factors, and access to health information/services. In the second model, socio-cultural factors were added. In the third model, intervening variables such as knowledge and ever use of family planning methods were added and the effect of intervening variables and independent variables on unintended pregnancy was observed. After assessing multicollinearity in the variables, it was found that the variables 'age of women' and 'number of children ever born' were highly correlated. So the variable 'children ever born' was not entered in the logistic regression model.

        In the first model, age of the women has positive and statistically significant impact on unintended pregnancy. On the other hand, ideal numbers of children, age at first marriage and exposure to the radio have negative and statistically significant effect with unintended pregnancy. The results indicate that with an increase in women's age, the odds of women experiencing unintended pregnancy also increases (OR, 1.12) by keeping other individual variables constant in the model. In terms of ideal number of children, the likelihood of reporting unintended pregnancy decreases (OR, 0.76) with an increase in the ideal number of children. Similarly, increase in age at first marriage reduces the likelihood of unintended pregnancy among women (OR, 0.94). Regarding radio exposure, those who were exposed to the radio were less likely to have unintended pregnancy (OR, 0.60) compared to those who were not exposed.

        All these four variables retained their significance even after inclusion of socio-cultural factors (religion and women's autonomy) in the model 2. The reduction on the odds ratio of the variables such as age, ideal number of children, age at first marriage, radio exposure after inclusion of socio-cultural variables indicated that the socio-cultural factors were also important predictors of unintended pregnancy. Model 2 further explained that Hindu women were less likely to have experienced unintended pregnancy (OR = 0.48) compared to other religion keeping all other variables constant in the model.

        Model 3 presents the final results after adding intervening variables in model 2. Even after inclusion of the knowledge and ever used of family planning methods variables in model 3, the four individual and one socio-cultural variable were still statistically significant. Furthermore, out of two intervening variables, knowledge about family planning methods had statistically significant effect (OR = 0.60) on experience of unintended pregnancy. Those women who had higher level (more than average score) of knowledge about family planning methods are less likely (OR = 0.60) to experience unintended pregnancy compared to those who have lower level of knowledge (less than average score) about family planning methods (Table 3).
        Table 3

        Estimated odds ratios for having unintended pregnancy among currently pregnant married women by selected predictors

          

        Odds ratios

          

        Model (I)

        Model (II)

        Model (III)

        Demographic characteristics

        Age (in years)

        1.112***

        1.106***

        1.105***

         

        Ideal number of children (number)

        0.761*

        0.751*

        0.725**

         

        Age at first marriage (in years)

        0.937**

        0.926**

        0.929*

        Socio-economic characteristics

        Literacy

           
         

        Illiterate (ref.)

           
         

        Literate

        1.221

        1.212

        1.336

         

        Occupation

           
         

        Not working/agriculture (ref.)

           
         

        Non-agriculture

        0.708

        0.587

        0.580

         

        Place of residence

           
         

        Urban (ref.)

           
         

        Rural

        0.981

        0.963

        0.984

        Access to health information/services

        Listens to radio

           
         

        No (ref.)

           
         

        Yes

        0.603**

        0.583**

        0.628*

         

        Watches television

           
         

        No (ref.)

           
         

        Yes

        0.930

        0.954

        0.959

         

        FP worker visit

           
         

        Not Visited (ref.)

           
         

        Visited

        1.385

        1.199

        1.274

         

        Travel time to nearest FP source

           
         

        Up to 30 minutes (ref.)

           
         

        31–60 minutes

        1.200

        1.159

        1.110

         

        More than one hour

        1.549

        1.460

        1.344

         

        No response

        0.665

        0.699

        0.607

        Socio-cultural factors

        Religion

           
         

        Non-Hindu (ref.)

           
         

        Hindu

        -

        0.482**

        0.468**

         

        Women autonomy

           
         

        No autonomy (ref.)

           
         

        Some autonomy

        -

        1.305

        1.374

        Knowledge and practice of FP

        Knowledge of FP

           
         

        Lower (ref.)

           
         

        Higher

        -

        -

        0.600**

         

        Ever use of FP

           
         

        No (ref.)

           
         

        Yes

        -

        -

        0.994

         

        -2 log likelihood

        868.1

        852.0

        844.9

         

        Cox & Snell R square

        0.102

        0.122

        0.131

        Note * = p < .05, ** = p < .01 *** = p < .001, ref = reference category

        Discussion

        This study has attempted to investigate the influencing factors such as demographic, socioeconomic, socio-cultural, access to health information/services and knowledge and ever use of family planning methods on unintended pregnancy. Present study showed that unintended pregnancy is common among Nepalese women. It indicates higher demand for family planning program. The result of this study suggests that all women, regardless of age, socioeconomic, or socio-cultural status, would benefit from increased efforts to ensure that pregnancies are intended.

        The bivariate analysis showed that the variables such as age, total children ever born, age at first marriage, literacy status, radio exposure, travel time to the nearest family planning source, family planning workers' visit, religion, women's autonomy and knowledge about family planning methods are important in explaining unintended pregnancy. The multivariate analysis supported some of the findings of the bivariate analysis and indicated a different pattern of effect for few other variables. In the multivariate analysis, age of women, ideal number of children, age at first marriage, radio exposure, religion and knowledge about family planning methods were found to have statistically significant influence on unintended pregnancy.

        This study has shown that the higher the age of women, the higher the probability of having current pregnancy as unintended. It is similar to the study conducted in currently married pregnant women in Iran [6] and all women of reproductive age in Nigeria [17].

        A contradictory result was observed from the logistic regression regarding the association of ideal number of children on an unintended pregnancy. In the multivariate analysis, ideal number of children was negatively associated with unintended pregnancy indicating that those women who desired more children were less likely to experience unintended pregnancy. One reason could be more people (93%) live in rural areas and rural women perceive greater benefit from having more children. Hence our sample reflected that the decline in desired family size in Nepal resulted in increased exposure to the risk of having unintended pregnancy.

        Like the study in Japan [5], we found significant negative relationship between age at first marriage and unintended pregnancy in Nepal. One of the reasons could be that early marriage leads to earlier initiation of sexual intercourse, which exposes women to an extended period when they are at risk of getting pregnant and is thus related to a higher likelihood of experiencing unintended pregnancy. The other reason could be that the women who married early may have limited access to services or may experience particular difficulty in practicing contraception.

        The multivariate results showed that those who have had regular access to mass media (radio) were less likely to report unintended pregnancy compared to those who have not. It means mass media has played an important role in reducing unintended pregnancy because it gives wider range of knowledge [18, 19] and leads to adopt contraception and sensitizes couple about the family norms so that they have low parity and low unintended pregnancy [20, 21].

        Unintended pregnancy was more common in non-Hindu women compared to Hindu women. One of the reasons could be that Hindu women are likely to accept pregnancy as "Given by God" or "Treasure of the Family". The other reason might be due to considerable proportion (38%) of Muslim women included in non-Hindu category. Islam restricts women's activities in ways that other religions do not [22].

        We hypothesized that women who have higher knowledge about family planning methods (more than average) are less likely to experience unintended pregnancy. Our result supports the hypothesis that if a woman has higher knowledge of family planning methods, she is more likely to be aware of the benefits of those methods which in turn will motivate her to use the family planning methods and be less likely to have unintended pregnancy. The similar result is found in Ecuador as well [23].

        In this study, there was no significant association between the experience of unintended pregnancy and women's education as in Japan [5], and occupation like the study found in Iran [6]. In Japan, most of the women are educated and they prefer not to have children or to have fewer children compared to other Asian countries. So there is no significant difference in the experience of unintended pregnancy among different educational levels of Japanese women. In case of Nepal, the literacy rate of women is very low and a large number of women do not have more than primary education and other social cultural factors strongly influence the intended pregnancy status; hence education is statistically not significant. However, it should not be concluded that education is not significantly related to intended pregnancy status and thus we should not ignore the importance of education for the better life of women.

        Similarly, contrary to the hypothesis, the present study found that women's autonomy has no significant impact on unintended pregnancy. In this study, women's autonomy was measured from the final say on their 'own health care' and 'spending their own earned money'. This is because in a patriarchal society, women are often given less opportunity to be self-supporting and have to depend on the male partners/relatives for their survival [24] and the possibility that women who earned cash are associated with households of low economic status and the job itself was low status jobs.

        Although statistically not significant, women who had exposure to Television and lived near health facilities had lower chances of unintended pregnancy than women in the comparison group. Ever use of family planning method has significant relationship with intended pregnancy status of women in many literatures. However, the result from this study is not similar to those findings. Some of the reasons identified were the complexity of using contraceptive or lack of methods choice and financial barriers hindering effective use of contraceptive methods. It was seen that the individual or community perception about contraception is an important factor, which affects contraceptive use. Similarly, misconception leads to discontinuation and decreased use of contraception and increases the level of unintended pregnancy [10]. Thus it can be argued that misconception about family planning methods exist among Nepalese women. High family planning method failure among married women in the reproductive age is also prevalent in Nepal [13]. However it does not imply that contraceptive use is not an important determinant of unintended pregnancy among married pregnant women in Nepal, it rather reflects the situation that the variable ever use of family planning methods acts indirectly on unintended pregnancy in this study.

        The concept of "intended ness of pregnancy" is complex and it would probably be better to treat it as a continuous rather than a bicategorical variable [25]. Women are often ambivalent about their intention to become pregnant or not. Nonetheless, measures of unintended pregnancy that use the intended/unintended dichotomy remain valuable because they allow us to assess trends over time and differences among population subgroups [26]. It has been shown that the perception of intended ness of pregnancy varies during the gestational period and after the delivery [27]. The use of a measure of mistimed pregnancies may be especially problematic, since a birth can be mistimed by a short amount of time or a longer period of time, each possibly having different implications [1, 28]. Furthermore, many studies compare only intended pregnancies to unintended pregnancies, but do not examine mistimed and unwanted pregnancies separately, even though studies that do separate unwanted from mistimed pregnancies have found many differences in the mother's interpretation of pregnancy intention and the outcomes associated with it [1, 2, 46, 26, 2932]. Moreover, if we take children born in the preceding five years or life time, that information may in fact underestimate unplanned childbearing since women may rationalize unplanned births and declare them as planned once they occur. The data used in this paper recorded the intendedness of current pregnancy among the currently pregnant women. It also minimizes underreporting of unintended pregnancy as well as reduces recall bias. In that sense, our study must be less biased than other studies that interview women at different times after delivery.

        There are some limitations to interpret the results of this study. First, as pointed out previously, we restricted our subjects to only currently pregnant married women at the time of survey, so obtained prevalence of women with experience of unintended pregnancy should not be generalized to the general population in Nepal. The main objectives of this study are to determine the prevalence and examine the factors influencing unintended pregnancy among currently pregnant married women in Nepal. Thus we intentionally selected a group of women who were currently pregnant during the period of survey, though risk factors of mistimed and unwanted pregnancy is not same, Second, because a cross sectional design of the study and all of the items analyzed in the logistic regression analysis were information at the time of survey, the analysis can only provide evidence of statistical association between those items and the experience of unintended pregnancy and cannot show the cause-effect relationships.

        Conclusion

        In conclusion, no single factor accounted for the high rates of unintended pregnancy; many factors contributed in this regard. Among them, this study has found that age of women, perceived ideal number of children, women's age at first marriage, radio exposure, religion and knowledge of family planning methods are strong predictors of unintended pregnancy. In short, it can be concluded that program should aim to reduce unintended pregnancy by focusing on all these identified factors so that infant and maternal mortality and morbidity as well as the need for abortion is decreased and the overall well-being of the family is maintained and enhanced.

        Declarations

        Acknowledgements

        The authors thanks MEASURE DHS + for providing access to the data. The authors also like to thanks to Ms. Sabitri Bhusal, Ms. Jyotsna Tamang and Dr. Fariha Haseen for their suggestions.

        Authors’ Affiliations

        (1)
        Geography and Population Department, Mahendra Ratna Campus, Tribhuvan University
        (2)
        Institute for Population and Social Research (IPSR), Mahidol University

        References

        1. Santelli JS, Rochat R, Hatfield-Timajchy K, Gilbert B, Curtis K, Cabral R: The measurement and meaning of unintended pregnancy. Perspectives on Sexual and Reproductive Health 2003,35(2):94–101.View ArticlePubMed
        2. Kilma SC: Unintended pregnancy: consequences and solutions for a worldwide problem. Journal of Nurse-Midwifery 1998,43(6):483–491.View Article
        3. UNFPA: The states of the world's population. The right to choose: Reproductive rights and reproductive health UNFPA New York 1997.
        4. Henshaw SK: Unintended pregnancy in the United States. Family Planning Perspective 1998,30(1):24–29.View Article
        5. Goto A, Seiji Y, Michael RR, Akira F: Factors associated with unintended pregnancy in Yamagata, Japan. Social Science Medicine 2002, 54:1065–1079.View ArticlePubMed
        6. Abbasi-Shavazi MJ, Hosseini-chavoshi M, Aghajanian A, Delavar B, Mehyar A: Unintended pregnancies in the Islamic Republic of Iran: Level and Correlates. Asia-Pacific Population Journal 2004,19(1):27–38.
        7. Ministry of Health [Nepal], New Era, and ORC Macro: Nepal Demographic and Health Survey 2001. Calverton, Maryland, USA: Family Health Division, Ministry of Health; New Era and ORC Macro 2002.
        8. Forrest JD: Epidemiology of unintended pregnancy and contraceptive use. Am J Obstet Gynecal 1994,170(5):1485–1489.
        9. Ipas: Adolescent, Unwanted Pregnancy and Abortion. Policies, Counselling and Clinical Care Chapel Hill, NC, Ipas 2004.
        10. Senanayake P: Determinants of unwanted pregnancies and induced abortions in developing Countries. Sexual and Reproductive Health, Recent Advances, Future Directions (Edited by: Puri CP, Van Look PFA). New age international private limited publishers New Delhi 2001.
        11. UNFPA: The state of world population, the new generation. UNFPA, New York 1998.
        12. Adhikari R, Tamang J: Premarital sexual behavior among male college students of Kathmandu, Nepal. BMC Public Health 2009, 9:241.View ArticlePubMed
        13. Tamang A, Nepal B, Adhikari R: Contraception, Unwanted Pregnancies and Induced Abortion in Kathmandu Valley. Abortion in Nepal: post legalization challenges-experience from neighboring countries and strategies for Nepal, Kathnandu, Nepal 2002, 8–10.
        14. Nazerali H, Thapa S, Hays M, Pathak LR, Pandey KR, Sokal DC: Vesectomy effectiveness in Nepal: a retrospective study. Contraception 2003, 67:397–401.View ArticlePubMed
        15. CREHPA: A situation analysis; management of abortion related complications in hospitals of Nepal 1999.
        16. CREHPA: Saving women's lives: Post legalized challenges and initiative to insure access to safe abortion in Nepal 2002. Reproductive Health Research Policy Brief 4
        17. Okonogua FE, Odimegwu C, Ajabor H, Daru PH, Johnson A: Assessing the prevanence and determinants of unwanted pregnancy and induced abortion in Nigeria. Studies in Family Planning 1999,30(1):67–77.View Article
        18. Flora JA, Maibach EW: Cognitive responses to AIDS information: the effect of issue involvement and message appeal. Comm Res 1990, (17):759–774.
        19. Oni GA, McCarthy J: Contraceptive knowledge and practice in Ilorin, Nigeria: 1983–1988. Studies in Family Planning 1990,21(2):104–109.View ArticlePubMed
        20. Westoff CF, Rodriguez G: The mass media and family planning in Kenya. International Family Planning Perspectives 1995, (21):26–31.
        21. Odimegwu CO: Family planning attitudes and use in Nigeria: a factor analysis. Family Planning Prospective 1999,25(2):86–92.View Article
        22. Caldwell JC: Routes to low mortality in poor countries. Population and Development Review 1986, 12:171–200.View Article
        23. Eggleston E: Determinants of unintended pregnancy among women in Ecuador. International Family Planning Perspectives 1999,25(1):27–33.View Article
        24. Mason KO, Taj AM: Differences between women and men's reproductive goals in developing countries. Population and Development Review 1987,13(4):611–638.View Article
        25. Bachrach CA, Newcomer S: Intended pregnancies and unintended pregnancies: distinct categories or opposite ends of a continuum? Fam Plann Perspect 1999,31(5):251–252.View ArticlePubMed
        26. Finer LB, Henshaw SK: Disparities in rates of unintended pregnancy in the United States, 1994 and 2001. Perspectives on Sexual and Reproductive Health 2006,38(2):90–96.View ArticlePubMed
        27. Besculides M, Laraque F: Unintended pregnancy among the urban poor. J Urban Health 2004,81(3):340.PubMed
        28. Pulley LV, Klerman LV, Tang H, Baker BA: The extent of pregnancy mistiming and its association with maternal characteristics and pregnancy outcomes. Perspectives on Sexual and Reproductive Health 2002,34(4):206–211.View ArticlePubMed
        29. Eggleston E, Tsui AO, Kotelchuck M: Unintended pregnancy and low birth weight in Ecuador. Social Science & Medicine 2001,51(7):808–810.
        30. Joyce TJ, Kaestner R, Korenman S: The effect of pregnancy intention on child development. Demography 2000,37(1):83–94.View ArticlePubMed
        31. Mohllajee AP, Curtis KM, Morrow B, Marchbanks P: Pregnancy intention and its relationship to birth and marital outcomes. Obstetrics and Gynecology 2007,109(3):678–686.View ArticlePubMed
        32. Taylor JS, Cabral HJ: Are women with an unintended pregnancy less likely to breastfeed? The Journal of Family Practice 2002,51(5):431–436.PubMed
        33. Pre-publication history

          1. The pre-publication history for this paper can be accessed here:http://​www.​biomedcentral.​com/​1472-698X/​9/​17/​prepub

        Copyright

        © Adhikari et al. 2009

        This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.