Background

Unplanned pregnancy is a major public, clinical, and social health problem around the world because it often leads to induced abortion and subsequent complications, which are often caused by insufficient abortion care services, particularly in resource-constrained settings [1]. Between 2015 and 2019, there were 121 million unintended pregnancies, leading to a global average of 64 unintended pregnancies per 1000 women aged 15 to 49 years [2]. About 61% of unintended pregnancies resulted in abortion, resulting in a global abortion rate of 39 abortions per 1,000 women aged 15 to 49 [2]. Unintended pregnancies account for around 44% of all pregnancies globally, with around 55% of unintended pregnancies in developed countries ending in abortion [3]. In sub-Saharan Africa (SSA), there was 33.9% unintended pregnancy rate [4]. The rate of unintended pregnancies and their effects can be minimized by increasing the availability, accessibility and affordability of contraception [5]. Individuals are increasingly trying to avoid unwanted births due to long-term global decreases in ideal family size and changes in the age at which people want to start families [6].

Unplanned pregnancy can be attributed to non-use of modern contraceptive methods among sexually active women [7]. More than 200 million women in developing countries choose to postpone their next pregnancy or stop childbirth altogether, but many still rely on inadequate or obsolete contraceptive methods, if they use contraception at all [8]. According to a previous report, 342 203 women died from maternal causes, but contraceptive use avoided 272 040 maternal deaths (44%), meaning that the number of maternal deaths would have been 1.8 times higher if contraceptive use had not been used [9]. A further 104 000 maternal deaths per year could be avoided by addressing the unmet need for contraceptives (29% reduction) [9]. In several resource-poor countries, the number of unintended pregnancies and unmet contraception needs remains high. Evidence-based research has shown that the use of contraception to avoid unplanned pregnancy is a substantial and successful primary prevention method [10, 11].

If family planning needs are met to delay, space, and limit the number of children women have, millions of girls and women in the world's poorest countries, including The Gambia, will see an improvement in their living conditions. Albeit, nearly 222 million women in developing countries do not use a modern form of contraception to prevent pregnancy [12, 13]. The third Sustainable Development Goal (SDG-3) prioritizes universal access to sexual and reproductive health care services, including reducing unmet contraceptive needs. The third Sustainable Development Goal (SDG-3) aims to ensure healthier lives and foster well-being for everyone at all ages [14]. To achieve this, adequate and long-term efforts are needed to eliminate several barriers to health-care service use, including family planning, especially in resource-constrained settings.

Evidence-based studies have reported about 18.4% prevalence of unplanned pregnancy among grand multiparous Gambian women [15] and 15.3% of unintended pregnancy among women aged 15–49 years in The Gambia [16]. While substantial resources have been allocated in Gambia to the provision of modern contraceptive methods, the total fertility rate is still high at 5.4 births per woman and an annual growth rate of 3.3 percent [17]. In all health centres in the region, the Gambian National Reproductive Health Policy (NRHP) provides for the provision of free family planning services. Despite this massive investment by the government and foreign donors in family planning, the contraceptive prevalence remains low (30.4%) [18], with about 17.6% of women having unmet family planning needs [19]. According to The Gambia Bureau of Statistics, births could be wanted at the time (planned), wanted at a later time (mistimed), or not wanted at all (unwanted) [17].

Unplanned pregnancy has been associated with many factors, including socio-demographic and economic factors, early sexual debut, accessibility to health care services, unmet need for family planning, higher parity, failure of contraceptives, preference of the partner for children, and domestic abuse [20,21,22,23]. Furthermore, age and age at sexual debut, religion, marital status and parity, education, residence have been reported as determinants of unplanned pregnancy [4]. To the best of our knowledge, there is no study in the Gambia that has examined the patterns and determinants of unplanned pregnancy among Gambian women of childbearing age. The objective of this study was to examine the prevalence and factors associated with unplanned pregnancy among women of reproductive age in The Gambia.

Methods

Data extraction

The study relied on secondary data from the Gambia's 2018 Multiple Indicator Cluster Survey (MICS). The study's data came from 3790 women of reproductive age who had recently given birth. The Gambia MICS, which took place in 2018, provided technical guidance on the quality or excellence of survey information to be collected, statistical monitoring, data collection, and data analysis, with the goal of improving the country's national statistical capability. MICS ensures the measurement of key points on which countries depend to generate data used in policy formulations and program planning in order to track their progress toward achieving the SDGs, as well as Gambia's National Development Plan (NDP) and other international obligations to which the country is a signatory. The MICS' contribution to improving Gambian data and device control, as well as providing technical expertise in the design, implementation, and analysis of such systems. The creation of the MICS program by the United Nations International Children's Emergency Fund (UNICEF) was largely motivated by the need to assist countries in gathering data on a global scale.

The Gambia MICS 2018 sample was designed to provide estimates for a large number of indicators on the situation of children and women at the national level, for urban and rural areas, and for the eight LGAs: Banjul, Kanifing, Brikama, Mansakonko, Kerewan, Kuntaur, Janjanbureh, and Basse. A multistage stratified cluster randomized sampling was used in the survey. The first stage involved randomly selecting enumeration areas (EAs) or clusters within each substratum with a probability proportional to size. The main sampling strata within each local government area were identified as urban and rural areas, and the sample of households was selected in two stages. The primary sampling unit was household. Following the completion of a household listing within the selected enumeration areas, a systematic sample of 20 households was drawn in each sample enumeration area. During the fieldwork period, all enumeration areas were visited. The global MICS program's procedures and standard guidelines were adapted to The Gambia MICS 2018 final questionnaires and used throughout the survey.

Variable selection and measurement

Outcome

The study outcome was unplanned pregnancy. The outcome variable was derived from the question; “Wanted last child then?” This was coded as “1” if a respondent answered “no” for unplanned pregnancy and “0” if otherwise. According to The Gambia Bureau of Statistics (GBS), births wanted at the time is regarded as planned pregnancy [17].

Explanatory variables

Table 1 showed the explanatory variables used in this study. The list of variables include: age (in years), household wealth quintiles, education, health insurance, ethnicity, functional disabilities, parity, marital status, age at first marriage/union, Local Government Area (LGA), residential status, overall happiness, age (in years) at sexual debut, ever used any method to avoid pregnancy, reading newspaper/magazine, listening to radio, watching television and family motility. Household wealth index quintiles was computed using a set of household assets in line with previous studies [24, 25]. See Table 1 for the details.

Table 1 Description/definition of explanatory variables
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Ethical consideration

We used publicly available datasets that were already accepted in March 2017 by the Government of Gambia and the Scientific Coordinating Committee (SCC) of the Medical Research Council (MRC) for the survey protocol. It is also on record that each survey participant received verbal consent. The ability to participate in the survey and their confidentiality and anonymity were guaranteed for all the survey respondents.

Statistical analysis

Stata survey (‘svy’) module was used to adjust for stratification, clustering and sampling weights. The Variance Inflation Factor (VIF) was used to assess multicollinearity, using a cut-off of 10 to detect significant concerns [26]. There was no variable omitted in the model due to lack of multicollinearity. Weighted percentages were used to describe the demographic characteristics.. To estimate the adjusted odds ratios, all statistically significant variables from the bivariate analysis were included in the multivariable logistic regression model using a 20% significance level. The predictive margins was conducted as a post-estimation of logit model. The model is presented thus;

$$\mathrm{Pr}\left(Y=1|\mathrm{Set}\left[\mathrm{E}=\mathrm{e}\right]\right)=\sum_{z}{\widehat{p}}_{ez}\mathrm{Pr}\left(Z=z\right);$$

where Set[E = e] reflects putting all observations to a single exposure level e, and Z = z refers to a given set of observed values for the covariate vector Z. Furthermore, \({\widehat{p}}_{ez}\)is the predicted probabilities of unplanned pregnancy (outcome variable) for any E = e and Z = z. The margin estimates indicate a weighted average over the distribution of the covariates and are equal to estimates got by standardizing to the entire population. As a post logit test, the exposure E is set to the level e for all women in the dataset, and the logit coefficients are used to compute predicted probabilities for every woman at their observed covariate pattern and newly exposure value [27, 28]. At p < 0.05, the statistical significance was determined in the adjusted model. For data processing, Version 14 of Stata (StataCorp., College Station, TX, USA) was used.

Results

Overall, approximately 25.3% (95% CI: 23.1%-27.6%) of the women reported unplanned pregnancy. Table 2 showed the results of unplanned pregnancy among the Gambian women. In addition, there were differences in unplanned pregnancy across the levels of women characteristics. Unplanned pregnancy was higher among advanced age women. Women aged 40–44 and 45–49 years had 30.1% and 40.0% unplanned pregnancies respectively. Those without health insurance, from Jola ethnic group, have functional disabilities, 5 + number of children ever born and single/never married had 25.6%, 37.2%, 42.3%, 29.5%, 77.8% unplanned pregnancy respectively. See Table 2 below for the details.

Table 2 Distribution of unplanned pregnancy across women’s characteristics (n = 3,790)
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In Table 3, we showed the factors associated with unplanned pregnancy among Gambian women. Women aged 30–34 years had 45% reduction in unplanned pregnancy, when compared with those aged 15–19 years (AOR = 0.55; 95% CI: 0.32, 0.94). The Fula and non-Gambian women had 30% (AOR = 0.70; 95% CI: 0.54, 0.92) and 45% (AOR = 0.55; 95% CI: 0.36, 0.86) reduction in unplanned pregnancy respectively, when compared with the Mandinka women. Those who had no functional difficulties had 47% reduction in unplanned pregnancy, when compared with women who had functional difficulties (AOR = 0.53; 95% CI: 0.30, 0.91). Respondents who had given births to 3–4 and 5 + children were 1.79 (AOR = 1.79; 95% CI: 1.34, 2.39) and 3.02 (AOR = 3.02; 95% CI: 2.08, 4.39) times as likely to have unplanned pregnancy respectively, when compared with women who had given birth to 1–2 children. Single women were 11.38 times as likely to have unplanned pregnancy, when compared with women currently married/in union (AOR = 11.38; 95% CI: 6.38, 20.29). LGA was significantly associated with unplanned pregnancy. Furthermore, women who were neither happy nor unhappy and 18 + at sexual debut were 1.39 and 1.34 times as likely to have unplanned pregnancy, when compared with the very happy women and those < 18 at sexual debut. See Table 3 for the details.

Table 3 Factors associated with unplanned pregnancy in The Gambia
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In Table 4, the predictive margins estimates were calculated to decipher the effects of the factors associated with unplanned pregnancy. From the predictive margins results, assuming the distribution of all factors remained the same among women, but every woman was aged 15–19 years or without health insurance, we would expect 26.9% and 21.0% of unplanned pregnancy respectively. If every woman had functional difficulties, we would expect 31.6% of unplanned pregnancy. If instead the distribution of women’s age, education, health insurance, ethnicity, functional difficulties, parity, were as observed and other covariates remained the same among women, but all women lived in Banjul, we would expect 33.3% of unplanned pregnancy. See Table 4 for the details.

Table 4 Predictive margins of unplanned pregnancy among women of reproductive age in The Gambia
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Discussion

To the best of our knowledge, this is the first study that has examined the prevalence and factors associated with unplanned pregnancy in The Gambia using a population-based data. Based on the findings of this study, approximately one-quarters of Gambian women of reproductive age reported unplanned pregnancy. Since poor use of modern contraceptive methods is the origin of unintended pregnancy [18], the relatively high prevalence of unplanned pregnancy is expected. This may be a major contributing factor to the degree of unintended pregnancy [19]. This is in line with results from a number of recent studies that looked at the prevalence of, and/or unmet needs for contraceptive use in The Gambia [18, 19]. This is consistent with previous findings on the prevalence of unplanned or unintended pregnancy in several resource-poor settings. In SSA, there was a pooled 33.9% prevalence of unintended pregnancy [4]. In Nigeria, Kenya and Ethiopia, this was about 11.0% and 24.0% respectively [29,30,31]. In a multi-country study, an overall unintended pregnancy prevalence rate of 29% was found, ranging from 10.8% in Nigeria to 54.5% in Namibia [16]. Results from the 2014 data showed a prevalence of 15.3% [16], whereas using the 2018 data, this increased to one-quarters indicating an upward trend.

While the Gambian government may have recognized the issue of unplanned pregnancies and committed to improving reproductive and sexual health care services, evidence suggests that there has been insufficient progress. Several factors were identified to be associated with unplanned pregnancy. In contrast to women aged 15–19 years, women in other age groups were more likely to have unplanned pregnancies, according to our research. This is consistent with the findings from a previous study [16]. Also, this result is in line with a study by Hubacher, Mavranezouli, and McGinn [32], who examined the prevalence of unintended pregnancies in SSA and the possible role of contraceptive implants in reducing them. They discovered that women aged 20–24, 25–29, and 30–34 years had the highest proportion of unintended pregnancies, compared to those aged 15–19 years [32]. According to Calvert et al. [33], who also reported from Tanzania, the risk of unplanned pregnancies rises with age. This result may be clarified by the fact that adult women might already have the ideal number of children and thus view any additional pregnancy as undesired or unplanned. Furthermore, women who had no functional difficulties had reduction in unplanned pregnancy, when compared with those with functional difficulties. Women with functional difficulties may lack physical accessibility to sexual and reproductive health care services, such as contraceptive products and health information as access to health information has been reported to have positive impact to health-seeking behaviour [34,35,36,37].

Furthermore, unplanned pregnancies were more common among single or unmarried women. This is consistent with the findings from a previous study which indicated that increased risk of unplanned pregnancy among single women [31], could be attributed to non-use of contraception or contraceptive failure, as certain single women may assume that contraceptive use has significant side effects [38], whereas others may believe that it reduces sexual pleasure, and therefore have unprotected intercourse, raising the risk of unplanned pregnancies [22, 38,39,40,41,42]. In addition, higher parity was a predisposing factor of unplanned pregnancy [31]. Women with higher number of children ever born could be regarded as already having the desired number of children and thus consider any additional pregnancy as unplanned or unwanted. On the other hand, women aged 18 + at sexual debut had higher odds of unplanned pregnancy. This is contrary to a previous study which found that unplanned pregnancy was associated with younger age at sexual debut [33].

Unplanned pregnancies were found to be substantially correlated with geographic area and ethnicity [29]. We found the Fulas and non-Gambian women had reduction in unplanned pregnancy respectively, when compared with the Mandinka women. In addition, women’s LGA of origin was significantly associated with unplanned pregnancy. It is possible there are more healthcare institutions in certain geographical locations, or related interventions may have been conducted within an ethnic group or geographical locations. The geospatial differentials in health care service utilization has been reported in previous studies [43,44,45,46].

Strengths and limitations

The strengths of this analysis are that the pregnancy aim determination was not affected by the result of pregnancy and that the probability of recall bias was minimized because the data were only obtained for the index pregnancy. The use of population-based data was useful and representative for plausible comparisons. There are still, however, some drawbacks. First, other scholars raised doubts about how planned and unplanned pregnancies are described (for example, since the reactions of a woman to a pregnancy she has categorized as unplanned may be conflicting or ambivalent), as well as about discrepancies between the purpose of a woman and her pregnancy feelings. Therefore, it may be a limitation of our research to use a single item to assess pregnancy intent. Second, we were unable to find causal links between the purpose of pregnancy and the established risk factors because of the cross-sectional study design.

Conclusion

This research showed that the prevalence of unplanned pregnancy was relatively high (25.3%) in the study settings, indicating the need for more exposure to this issue. Family planning services for women of reproductive age, especially those at high risk of unplanned pregnancy, should be accessible widely and easily. Our findings indicate, in particular, that better sex education and increased awareness of contraceptive methods are required for women. In addition, to improve the efficacy and quality of the use of contraceptive methods, women without family support can require individualized guidance and counselling.