Prevalence of Unintended Pregnancy and its Association with Unmet Need for Contraception among Married Women in Bangladesh
Arzo Ahmed1*, Sabikun Nahar Sumi1, Umme Habiba2, Mousumi Datta2, Mashfiqul Huq Chowdhury1, Noor Muhammad Khan1
1Department of Statistics, Mawlana Bhashani Science and Technology University, Tangail-1902, Bangladesh
2Department of Mathematics, Mawlana Bhashani Science and Technology University, Santosh, Tangail-1902, Bangladesh
ABSTRACT
Objectives: Unmet need for contraception and unintended pregnancy is perceived as critical boundaries towards advancing women’s regenerative wellbeing and prosperity. This paper examines the current prevalence of unintended pregnancy and unmet need for contraception and explores the effect of unmet need for contraception in unwanted pregnancy in a nationwide representative sample in Bangladesh.
Methods: This cross-sectional study is based on data from Bangladesh Demographic Health Survey, 2014.
Participants were 4,074 married women of reproductive age (15-49 years). Pregnancy intention status for the last-born child was the leading result variable and the independent variable of basic concern was unmet need for contraception. In this analysis we used chi-square test of independence and binary logistic regression.
Results: An unmet need for contraception is a significant predictor of unintended pregnancy and average age of the sample populace was 24.36 years (SD 5.625). About 24.4% of the women explained their most recent pregnancy as unintended and the prevalence of unmet need for contraception was 17.9%. In the binary logistic model, the odds ratio indicates that women who had unmet need for contraception were about 32 times bound to have unintended pregnancy contrasted with the individuals who had not (95% CI = 17.284 – 60.434).
Conclusions: Women in rural areas had the highest prevalence of both unintended pregnancy and unmet need for contraception than women in urban. Findings suggest that, reducing unplanned pregnancy, planning and actualizing procedures that make awareness at the community level and reinforcing no unmet need for contraception are recommended in Bangladesh.
Keywords
Unintended pregnancy; Unmet need; Contraception; Odds ratio
Introduction
The problem of unintended pregnancy has been confronting by ladies living in each country, paying little heed to its advancement status. Unintended pregnancy is an expected danger for each explicitly sexually dynamic lady. It’s been an overall issue that influences women along with their families, society, as well as the nation. An unpredictable arrangement of social and mental factor puts women in danger for unintended childbearing [1]. The problem of unintended pregnancy has been crucial to demographers trying to get fruitfulness, to general wellbeing professionals in stopping unwanted pregnancy and to both groups in enhancing a woman's capacity to decide if and at what time to have kids [2]. Unwanted pregnancies have a wide scope of adverse consequences, for example, low birth weight, untimely birth [3], maternal gloom [4]–
[6], anxiety [7], poor physical and mental prosperity [8], and antenatal and delivery care, breastfeeding and infant mortality [9] have been documented and thus it has obtained growing research and policy attention during the most recent couple of decades. Mothers whose pregnancies are mistimed/unwanted pregnancies are more averse to start and use pre-birth and antenatal consideration, or look for it later than mothers who have planned pregnancies [10], [11].
It is such a general medical issue that may lead women to illness and death mainly through risky fetus removal in addition it also results in economic, social, and health crisis throughout the
world. And if unintended pregnancies could be controlled then up to 1 million maternal passings and 4.6 million disability-adjusted life years (DALYs) might be prevented globally, shown from the evidence of recent estimates [12]. In 2008, around the world out of 208 million pregnancies about 86 million (41%) were unwanted and of these unwanted pregnancies nearly 41 million (48%) finished in premature births, 33 million (almost 39%) finished in unwanted births, and around 11 million (nearly 13%) ended in miscarriages [13]. According to Population Reference Bureau reports (2009 estimation), unwanted pregnancy is a typical result for in excess of 200 million women overall who need to quit having children or delay their next pregnancy yet are not utilizing a successful technique for contraception [14].
In most cases, unintended pregnancies occur due to misuse or non-use of contraceptives, or noticeable contraceptive failure [15]. Unintended pregnancy is a significant danger factor for prompt premature birth and prosthetic involvement, and is considered to be the most difficult issue in the field of maternal and child morbidity wellbeing, and females’ regenerative wellbeing all-inclusive [16]– [18]. Unwanted pregnancy, as well as early termination create critical boundaries to accomplishing Millennium Development Goals (MDGs) related to the maternal and youngster wellbeing [19]. The contraceptive prevalence rate (CPR) expanded practically nearly six-fold from 8 percent to 45 percent between 1975 and 1993–94, and the corresponding fruitfulness rate has decreased from 6·4 births for each woman to 3·4 births for each woman between 1975 and 1994 [20]. Subsequently, throughout the time of 1994 to 2007, the pace of utilization of any type of contraception among wedded women has expanded by 11% (45% to 56%) also utilization rate of modern methods has expanded to 48% [21]. Three of each five wedded ladies in Bangladesh utilize a contraception technique, and of them a greater part about 52% utilize current strategies (modern methods) for contraception. Also practice of contraceptives has improved between 2007 to 2011 from 56 percent to 61 percent [22]. During 1993 to 2014, the percentage of unplanned pregnancy has also decreased, though, at a lethargic rate from 33 percent to 26 percent throughout the nation [23]. In spite of these accomplishments, the prevalence of unmet need for contraception despite everything stays high and has been expanding yet gradually lately. Demographic and Health Survey (DHS) characterizes unmet need for contraception as a circumstance when ladies are reluctant to take more kids or need to take around at least two years gap after the last pregnancy yet are not utilizing any types of contraception. The gap between women's regenerative expectations and their contraceptive behaviour is the main focus behind the idea of unmet need. According to World Health Organisation (WHO) definition: Women who are fertile and sexually dynamic yet are not utilizing any technique for contraception, and reporting not having any desire for additional child or needing to postpone the next child is considered to have unmet need. As indicated by Bangladesh Demographic and Health Survey (BDHS 2011), unmet need for family planning has expanded from 11 percent to 17 percent of currently married women between 2004 and 2007 and afterward diminished to 14 percent in 2011 and women residing in rustic zones found to have about 14% unmet need which is higher than women residing in metropolitan regions (about 11%) [22]. According to division, unmet need is most elevated in Chittagong division (about 21%) then least in Khulna division and Rangpur division (both are 10%) [22]. These discoveries uncover that unmet need is a developing concern and can be seen as a botched chance to report about unplanned pregnancy in the nation. Worldwide appraisals demonstrated that between 2010 and 2014 about 56.3 million abortions occurred annually and half of all abortions are assessed to be hazardous and 97% of these happen in developing countries [24]. It has been evaluated that about 82% of unintended pregnancies occurred because of unmet need for contraception [25]. About 54 million unintended pregnancies and 26 million abortions would be prevented each year if all
women having unmet need utilized a modern contraceptive method [26]. For the above context, it is important to concentrate more on undesirable pregnancy as well as unmet need for contraception in addition through study it is possible to understand the socioeconomic determining factors of these problems for developing effective tactics for the anticipation of unintended pregnancies. However, there stays a lack of exploration proof concerning the causes of relationship with unintentional pregnancy in Bangladesh. Here in our investigation, we plan to analyze the current prevalence of unplanned pregnancy as well as unmet need for contraception and investigate the impact of unmet need for contraception in unplanned pregnancy. Aimed at this reason, we utilized information from the most recent demographic and health survey of Bangladesh, that is nationwide representative as well as a trustworthy source of populace health statistics in Bangladesh.
Methods Study Design and Data Source:
Data for this cross-sectional study were extracted from Bangladesh Demographic and Health Survey conducted in 2014. The 2014 survey was the seventh to be conducted in the country. The survey was conducted by an autonomous national research institution under the Ministry of Health and Family Welfare namely, National Institute of Population Research and Training (NIPORT) and a notable research institution within the country namely, Mitra and Associates executed the survey. ICF International of Rockville (Maryland, USA) provided the technical assistance and United States Agency for International Development (USAID) provided the financial assistance [27]. A two-stage stratification technique was used to select sample households. Initially, 393 clusters were chosen in rural areas and 207 clusters were chosen in urban regions for 600 enumeration areas (EAs) with proportional probability. In the second stage, on average a sample of 30 households was selected per enumeration area (EA) by systematic sampling. Altogether 18,245 ever-married ladies aging somewhere in the range of 15 and 49 years were carefully chosen for interview of 2014 BDHS survey, of whom 17,863 were at last studied where reaction rate remained 98% [27]. Participants of 4,074 married women were extracted from 17,863 married women of generative age (15–49 years) from both rural residencies and urban residencies for this study.
Variable selection:
The result variable of this investigation was pregnancy expectation status for the last-born child among ladies. The conception of unintended pregnancy is recognized as a complicated and subtle one among researchers [28]. Albeit a subsample of the presently pregnant ladies stated their intention status for their present pregnancy, the subsample was not very numerous to even think about producing genuinely significant outcomes. Thus the most recent completed pregnancy occurred in the 5 years going before the review and any existing pregnancy was considered for the analysis. According to the traditional rules, needed later (alluding to ill-timed pregnancy) and needed no more (alluding to undesirable pregnancy) fall inside the extent of undesirable/
unplanned pregnancy [14], [29] and is normally utilized as a binary result variable i.e., intended = needed at that point, and unintended/ unplanned = needed later/ needed no more.
𝑌 = 1, 𝐼𝑓 𝑡𝑒 𝑖𝑡 𝑟𝑒𝑠𝑝𝑜𝑛𝑑𝑒𝑛𝑡 𝑠𝑡𝑎𝑡𝑒𝑑 𝑒𝑟 𝑙𝑎𝑠𝑡 𝑝𝑟𝑒𝑔𝑛𝑎𝑛𝑐𝑦 𝑎𝑠 𝑢𝑛𝑤𝑎𝑛𝑡𝑒𝑑 (𝑈𝑛𝑖𝑛𝑡𝑒𝑛𝑑𝑒𝑑) 0, 𝐼𝑓 𝑡𝑒 𝑖𝑡 𝑟𝑒𝑠𝑝𝑜𝑛𝑑𝑒𝑛𝑡 𝑠𝑡𝑎𝑡𝑒𝑑 𝑒𝑟 𝑙𝑎𝑠𝑡 𝑝𝑟𝑒𝑔𝑛𝑎𝑛𝑐𝑦 𝑎𝑠 𝑤𝑎𝑛𝑡𝑒𝑑 𝐼𝑛𝑡𝑒𝑛𝑑𝑒𝑑
The leading explanatory variable of this investigation was unmet need for contraception. The break between ladies’ regenerative expectations and their contraceptive behaviour is the main focus behind the idea of unmet need. Unmet need for contraception indicates the non-use of any contraceptive method among ladies who are prolific and sexually dynamic, yet need no new pregnancies or need to postpone the resulting pregnancy. Participants were explained the perception by the interviewer and the subsequent options were given for answering the query whether they had unmet need for contraception or not. In light of these reactions, we just kept those perceptions for which unmet need for contraception is appropriate. As an instance, ladies who were not fertile are not intended to utilize contraceptives and thus before analysis, we removed those observations from the dataset. The individuals who are at present utilizing any contraception strategy for dispersing and restricting were sorted as: Has no unmet need, otherwise has unmet need.
For picking significant covariates, a writing search in conspicuous clinical databases was led for concentrates on unwanted pregnancy. In light of the writing survey, and accessibility inside the BDHS datasets, the subsequent covariates were chosen for this investigation: Age (<25/≥25);
Husband/partner’s age (<25/≥25); Type of residence (urban/rural); Division (Barisal, Chittagong, Dhaka, Khulna, Rajshahi, Rangpur, and Sylhet); Respondent’s highest education level: no education (no institutional education), primary (institutional education of 1–5 years), secondary/higher (institutional education of more than 5 years); Husband/partner's education level: no education (no institutional education), primary (institutional education of 1–5 years), secondary/higher (institutional education of more than 5 years); Husband’s occupation: blue collar (comprises engagements in hard manual labor, typically agriculture, manufacturing, construction, mining, or maintenance), white collar (includes clerical, administrative or managerial duties and stereotypically, eschew physical labor such as employments in business, service,health sector, teaching), others(includes unemployment, student etc.); Religion (muslim/non-muslim); Respondent currently working (yes/no); Household head (male/female);
Media Access(yes /no); First birth age (<18/≥18); First cohabitation age (<18/≥18); Total children ever born (≤2/ >2); Number of living children (≤2/>2); Number of Child loss (≤2/ >2);
Ideal number of children (≤2/ >2); Autonomy in own healthcare decision (yes/no); Terminated any pregnancy ever (yes/no); Presently residing with husband/partner (living with her/staying elsewhere); Currently using any contraception (yes/no); Visited by FP worker in past 6 months (yes/no); Husband's desire for children (both want same, husband wants more, husband wants fewer); Unmet need for contraception(yes/no); Wealth status(poor/middle/rich). These indicator factors have been remembered for this examination principally dependent on their impact in the existing writings concerning the subject. Media accesses of women were evaluated by asking the frequency of watching television, listening to the radio, and reading newspapers at least once a week. At long last, I classified media access into a dichotomous classification: 0 for no and 1 for yes.
Data Analysis
The BDHS dataset covers info on an extensive scope of factors. The dataset was checked to incorporate just those participants for whom all data vital for the current investigation were
accessible. Before starting the analysis, we weighted the data by sample weights to create population estimates. For displaying the basic sociodemographic features of the sample population descriptive analysis (frequency distribution) was performed. For demonstrating the group differences in regarding pregnancy expectations through the independent variables Pearson’s 𝜒2tests was implemented. To guarantee legitimacy for additional examination the independent variables were checked for multicollinearity. Based on the bivariate analysis results, variables that showed statistically significant association (p < 0.05) with pregnancy intention status were entered into the binomial logistic regression model all together and assess the net effect of unmet need for contraception on pregnancy intention status after controlling for other variables. For measuring the strength of relationships between pregnancy expectation status and the explanatory variables in the model, adjusted odds ratios (AOR) with 95% confidence intervals (CI) were calculated. Finally, the Wald test (a two-tailed p-value of <0.05) is performed to test the significance of the parameters. All analyses were done by using IBM SPSS Statistics version 23 and report writing was done by using MS word.
Results
Table 1 represents mean or percentage distributions of the socio-demographic characteristics and contraceptive behavior of the study participants.
Table 1: Socio-Demographic Characteristics& Contraceptive Behavior of the Sample Population by Variables Used in Analyses, BDHS 2014
Outcome variable Mean SD
Age 24.36 5.63
Variables No. of
Respondents (Percentage)
Variables No. of Respondents (Percentage)
Age Media access
< 25 2292 (56.3) No 1512 (37.1)
≥ 25 1782 (43.7) Yes 2562 (62.9)
Husband/partner’s Age First cohabitation age
< 25 343 (8.4) < 18 2903 (71.3)
≥ 25 3731 (91.6) ≥ 18 1171 (28.7)
Place of residence First birth age
Urban 1309 (32.1) < 18 1766 (43.3)
Rural 2765 (67.9) ≥ 18 2308 (56.7)
Division Total child ever born
Barisal 494 (12.1) ≤ 2 2957 (72.6)
Chittagong 783 (19.2) > 2 1117 (27.4)
Dhaka 720 (17.7) Number of child alive
Khulna 477 (11.7) ≤ 2 3100 (76.1)
Rajshahi 496 (12.2) > 2 974 (23.9)
Rangpur 516 (12.7) Number of Child loss
Sylhet 588 (14.4) ≤ 2 4059 (99.6)
Respondent’s education level > 2 15 (0.4)
No Education 507 (12.4) Ideal number of children
Primary 1096 (26.9) ≤ 2 3394 (83.3)
Secondary/Higher 2471 (60.7) > 2 680 (16.7)
Husband’s education level Autonomy in own healthcare decision
No Education 882 (21.6) No 1634 (40.1)
Primary 1238 (30.4) Yes 2440 (59.9)
Secondary/Higher 1954 (48.0) Terminated any pregnancy ever
Husband’s occupation No 3477 (85.3)
Blue collar 2758 (67.7) Yes 597 (14.7)
White collar 1215 (29.8) Currently residing with husband/partner
Others 101 (2.5) Staying elsewhere 590 (14.5)
Wealth index Living with her 3484 (85.5)
Poor 1605 (39.4) Currently using any contraception
Middle 788 (19.3) No 1315 (32.3)
Rich 1681 (41.3) Yes 2759 (67.7)
Religion Visited by FP worker in past 6 months
Non-Muslim 335 (8.2) No 3068 (75.3)
Muslim 3739 (91.8) Yes 1006 (24.7)
Respondent currently working Husband's expectation for children
No 3199 (78.5) Both want same 3338 (82.0)
Yes 875 (21.5) Husband wants more 458 (11.2)
Household head Husband wants fewer 278 (6.8)
Male 3726 (91.5) Unmet need for contraception
Female 348 (8.5) No 3346 (82.1)
Yes 728 (17.9)
By analyzing the mean or percentage distribution table, we can see that the mean age of the respondents was 24.36 years (with SD 5.625) and 56.3% women were aged below 25 years and rest of 43.7% women were aged 25 years or more at the time of the survey. Majority of the respondents’ husbands (91.6%) age was 25 years or above and only 8.4% respondents’ husbands age was below 25 years. Two-third of the participants were from the rural area with percentage of 67.9% and the remaining one-third of the participants were from urban area. Among all participants’ highest participants nearly one-fifth of the participants were from Chittagong division (19.2%) and second highest participants were from Dhaka division (17.7%), while only 14.4%, 12.7%, 12.2% and 12.1% participants were living in Sylhet, Rangpur, Rajshahi and Barisal, and the lowest number of participants about 11.7% were from Khulna. As compared to husbands, nearly two-third (60.7%) of the women completed secondary or higher education whereas less than half (48.0%) of their husbands completed secondary or higher education. But in case of primary education and no formal education husbands had a higher rate than women and the rate of primary education among women and their husbands were 26.9% and 30.4%
respectively, also 12.4% women and 21.6% of their husbands had no formal education. Most of the women’s husband were involved in blue collar activities about 67.7% and more than a quarter of the women’s husband (29.8%) were involved in white collar profession while only 2.5%
women’s husband were involved in other activities like unemployed, student etc. Well over one- third (41.3%) of the women were belonged to rich wealth status, and also more than one third (39.4%) of the women were belonged to poor class while less than one-fifth (19.3%) of the women were from middle class. On the basis of religion, most of the women were Muslim with highest percentage of 91.8% and only 8.2% women were non-muslim. Also majority of the
women more than two-third of the women currently had no employment having percentage of 78.5% and only one-fifth (21.5%) of the women had currently employment. All over most of the household were male headed about 91.5% and the rest 8.5% households were female headed.
And more than three-fifths of the respondents had media access (62.9%) while only 37.1%
respondents had no media access. More than two-third of the women about 71.3% experienced first cohabitation prior to arriving at the age of 18 years and only the remaining 28.7% ladies experienced first cohabitation at the age of 18 years or above. Also about 43.3% ladies experienced first childbirth prior to arriving at the age of 18 years and the rest 56.7% ladies experienced first childbirth at the age of 18 years or above. Women had two or less number of children ever born was 72.6% and the rest had more than two children ever born. The proportion of women who had two or less number of living children was 76.1% and 23.9% had more than two living children. Almost all of the women about 99.6% had two or less number of child loss and only a very few percent about 0.4% had more than two child loss. All over 83.3% like 4 out of 5 women are said to have two or fewer children and less than one-fifth (16.7%) women with more than two children have a fair number of children. About 59.9% women confirmed that they were involved in their health care decision and women who stated that they had no involvement in own health care decision was 40.1%. Less than one-fifth of the women (14.7%) ever terminated a pregnancy and women had no terminated pregnancy ever was 85.3%. Maximum women (85.5%) were living with their husband and only 14.5% were staying elsewhere. About 67.7% women reported using any contraceptive method whereas women reported not using any contraceptive method was 32.3%. There were 24.7% of women who were visited by FP worker in last 6 months and more than three-quarter (75.3%) of the women weren’t visited by FP worker in last 6 months. Desire for children among women and husband was- “both want same” was maximum about 82%, “husband wants more” was about 11.2% and a very little percentage only about 6.8% was “husband wants fewer”. Little less than one-fifth of the women (17.9%) reported that they were facing unmet need for contraception and the rest 82.1% women facing no unmet need for contraception.
Table 2.Association of Unintended Pregnancy with Explanatory Variables, BDHS 2014
Explanatory variables
Last pregnancy by intention status
(n = 4,074)
Total (%)
χ2- value
P- value Unintende
d (24.4)
Intended (75.6) Number
(%)
Number (%) Age
< 25 510 (51.3) 1782 (57.9) 2292 (56.3) 13.099 .000
≥ 25 484 (48.7) 1298 (42.1) 1782 (43.7) Husband’s Age
< 25 70 (7.0) 273 (8.9) 343 (8.4) 3.233 .072
≥ 25 924 (93.0) 2807 (91.1) 3791 (91.6) Place of residence
Urban 275 (27.7) 1034 (33.6) 1309 (32.1) 12.018 .001 Rural 719 (72.3) 2046 (66.4) 2765 (67.9)
Division
Barisal 134 (13.5) 360 (11.7) 494 (12.1)
20.405 .002 Chittagong 170 (17.1) 613 (19.9) 783 (19.2)
Dhaka 165 (16.6) 555 (18.0) 720 (17.7) Khulna 132 (13.3) 345 (11.2) 477 (11.7) Rajshahi 142 (14.3) 354 (11.5) 496 (12.2) Rangpur 101 (10.2) 415 (13.5) 516 (12.7) Sylhet 150 (15.1) 438 (14.2) 588 (14.4) Respondent’s education level
No Education 164 (16.5) 343 (11.1) 507 (12.4)
49.977 .000 Primary 320 (32.2) 776 (25.2) 1096 (26.9)
Secondary/ Higher 510 (51.3) 1961 (63.7) 2471 (60.7) Husband’s education level
No Education 271 (27.3) 611 (19.8) 882 (21.6)
38.022 .000 Primary 324 (32.6) 914 (29.7) 1238 (30.4)
Secondary/Higher 399 (40.1) 1555 (50.5) 1954 (48.0) Husband’s occupation
Blue collar 700 (70.4) 2058 (66.8) 2758 (67.7)
15.161 .001 White collar 285 (28.7) 930 (30.2) 1215 (29.8)
Others 9 (0.9) 92 (3.0) 101 (2.5)
Wealth index
Poor 455 (45.8) 1150 (37.3) 1605 (39.4)
28.707 .000 Middle 197 (19.8) 591 (19.2) 788 (19.3)
Rich 342 (34.4) 1339 (43.5) 1681 (41.3) Religion
Non-Muslim 55 (5.5) 280 (9.1) 335 (8.2) 12.604 .000 Muslim 939 (94.5) 2800 (90.9) 3739 (91.8)
Respondent currently working
No 739 (74.3) 2460 (79.9) 3199 (78.5) 13.597 .000
Yes 255 (25.7) 620 (20.1) 875 (21.5)
Household head
Male 919 (92.5) 2807 (91.1) 3726 (91.5) 1.672 .196
Female 75 (7.5) 273 (8.9) 348 (8.5)
Media access
No 432 (43.5) 1080 (35.1) 1512 (37.1) 22.696 .000 Yes 562 (56.5) 2000 (64.9) 2562 (62.9)
First cohabitation age
< 18 750 (75.5) 2153 (69.9) 2903 (71.3) 11.302 .001
≥ 18 244 (24.5) 927 (30.1) 1171 (28.7) First birth age
< 18 521 (52.4) 1245 (40.4) 1766 (43.3) 44.009 .000
≥ 18 473 (47.6) 1835 (59.6) 2308 (56.7) Total child ever born
≤ 2 535 (53.8) 2422 (78.6) 2957 (72.6) 232.502 .000
> 2 459 (46.2) 658 (21.4) 1117 (27.4) Number of child alive
≤ 2 570 (57.3) 2530 (82.1) 3100 (76.1) 254.038 .000
> 2 424 (42.7) 550 (17.9) 974 (23.9) Number of child loss
≤ 2 991 (99.7) 3068 (99.6) 4059 (99.6) .158 .691
> 2 3 (0.3) 12 (0.4) 15 (0.4)
Ideal number of children
≤ 2 815 (82.0) 2579 (83.7) 3394 (83.3) 1.640 .200
> 2 179 (18.0) 501 (16.3) 680 (16.7) Autonomy in own healthcare decision
No 399 (40.1) 1235 (40.1) 1634 (40.1) .001 .981 Yes 595 (59.9) 1845 (59.9) 2440 (59.9)
Terminated any pregnancy ever
No 840 (84.5) 2637 (85.6) 3477 (85.3) .740 .390
Yes 154 (15.5) 443 (14.4) 597 (14.7)
Currently residing with husband/partner
Staying elsewhere 113 (11.4) 477 (15.5) 3484 (85.5) 10.294 .001 Living with her 881 (88.6) 2603 (84.5) 590 (14.5)
Currently using any contraception
No 270 (27.2) 1045 (33.9) 1315 (32.3) 15.736 .000 Yes 724 (72.8) 2035 (66.1) 2759 (67.7)
Visited by FP worker in last 6 months
No 726 (73.0) 2342 (76.0) 3068 (75.3) 3.639 .056 Yes 268 (27.0) 738 (24.0) 1006 (24.7)
Husband's expectation for children
Both want same 792 (79.7) 2546 (82.7) 3338 (81.9)
5.401 .067 Husband wants
more
131 (13.2) 327 (10.6) 458 (11.2) Husband wants
fewer
71 (7.1) 207 (6.7) 278 (6.8) Unmet need for contraception
No 735 (73.9) 2611 (84.8) 3346 (82.1) 60.046 .000
Yes 259 (26.1) 469 (15.2) 728 (17.9)
Table 2 shows results of chi-square tests which comparing the corresponding percentage of respondents who reported unintended pregnancies contrary to a variety of demographic, social and economic, health-related factors and contraceptive behaviors. Implementing the chi-square test of independence, it is found that among the context oriented variables respondent’s age, residence, division, respondent’s education, husband’s education, husband’s occupation, wealth index, religion, respondent currently working, media exposure, first cohabitation age, first birth age, total child ever born, number of child alive, currently residing with husband/partner, presently utilizing any contraception and unmet need for contraception all had a statistically significant correlation with respondents pregnancy intention status of Bangladesh (P-value <
0.05). Other variables are not found significantly associated with pregnancy intention status (P- value > 0.05).
Table 3: Logistic Regression Coefficients of Unintended Pregnancy Among Women of Reproductive Age in Bangladesh, 2014 (Adjusted Odds Ratios (AOR))
Parameter 𝜷 S.E. Wald df Sig. Exp(𝜷) 95% C.I. for
Exp(𝜷) Lower Upper Age
< 25® 1
≥ 25 -.590 .110 28.910 1 .000*** .554 .447 .687 Place of residence
Urban® 1
Rural .118 .098 1.455 1 .228 1.125 .929 1.362
Division
Barisal® 1
Chittagong -.338 .147 5.284 1 .022* .713 .535 .951
Dhaka -.116 .150 .600 1 .439 .891 .664 1.194
Khulna .218 .158 1.915 1 .166 1.244 .913 1.695
Rajshahi .180 .156 1.331 1 .249 1.197 .882 1.624 Rangpur -.337 .162 4.294 1 .038* .714 .519 .982
Sylhet -.147 .158 .859 1 .354 .864 .633 1.177
Respondent’s education level No
Education®
1
Primary .080 .135 .354 1 .552 1.083 .832 1.411
Secondary/
Higher
-.090 .144 .391 1 .532 .914 .689 1.212 Husband’s education level
No
Education®
1
Primary -.007 .113 .003 1 .953 .993 .796 1.240
Secondary/
Higher
-.026 .126 .044 1 .834 .974 .761 1.247 Husband’s occupation
Blue collar® 1
White collar .051 .093 .306 1 .580 1.053 .877 1.264 Others -1.004 .367 7.478 1 .006** .366 .178 .752 Wealth index
Poor® 1
Middle -.014 .117 .014 1 .906 .986 .784 1.240
Rich -.084 .123 .464 1 .496 .919 .722 1.171
Religion
Non-Muslim® 1
Muslim .345 .165 4.373 1 .037* 1.412 1.022 1.950 Respondent currently working
No® 1
Yes .159 .095 2.794 1 .095 1.173 .973 1.413
Media access
No® 1
Yes .039 .102 .144 1 .705 1.039 .852 1.268
First cohabitation age
< 18® 1
≥ 18 .307 .113 7.388 1 .007** 1.359 1.089 1.695 First birth age
< 18® 1
≥ 18 -.264 .098 7.279 1 .007** .768 .634 .930 Total child ever born
≤ 2® 1
> 2 .534 .218 5.999 1 .014* 1.706 1.113 2.615 Number of child alive
≤ 2® 1
> 2 1.004 .222 20.389 1 .000*** 2.729 1.765 4.220 Currently residing with husband/partner
Staying elsewhere®
1
Living with her .439 .135 10.510 1 .001*** 1.551 1.189 2.022 Currently using any contraception
No® 1
Yes 2.883 .310 86.210 1 .000*** 17.863 9.720 32.827 Unmet need for contraception
No® 1
Yes 3.476 .319 118.46
1
1 .000*** 32.319 17.284 60.434 Constant -4.764 .415 131.87
6
1 .000*** .009
Note: ® indicate reference category and *** P < 0.001, ** P < 0.01, * P < 0.05
From Table 3, it is shown that respondent’s age, division, husband’s occupation, religion, first cohabitation age, first birth age, total child ever born, number of child alive, currently residing with husband/partner, currently using any contraception and unmet need for contraception all have a significant impact on pregnancy intention status.
Binary logistic regression was used to measure the effect of several factors on the likelihood that respondents stated their last pregnancy as unintended. The full model containing all predictors was statistically significant, 𝜒2 26, 𝑁 = 4,074 = 631.667, 𝑝 < 0.001, showing that the model had the ability to make a distinction between respondents who reported and didn’t report last pregnancy as unintended. The model all in all clarified between 14.4% (Cox and Snell R square) and 21.4% (Nagelkerke R squared) of the variance in pregnancy intention status, and effectively grouped 77.3% of cases. As presented in Table 3, just nine of the explanatory variables made a unique statistically significant impact to the model (respondent’s age, religion, first cohabitation age, first birth age, total child ever born, number of child alive, currently residing with husband/partner, currently using any contraception and unmet need for contraception).
The strongest predictor of reporting unintended pregnancy was having unmet need for contraception, recording an odds ratio of 32.3. This indicated that respondents who had unmet need for contraception were over 32.3 times more likely to report unintended pregnancy than those who did not have unmet need for contraception, controlling for all other factors in the model. The odds ratio of 17.8 for currently using any contraception was second strong predictor
of reporting unintended pregnancy, indicating that respondents who were currently using any contraception were 17.8 times more likely to report unintended pregnancy than those who weren’t currently using any contraception, controlling for other factors in the model which indicates that the contraception method that the respondents currently using is not working or choosing a wrong contraception method or not using it with properly following the indicated instructions or irregular use of contraception.
Multivariate analysis shows a negative regression coefficient of women with age ≥ 25 years.
That means women of age ≥ 25 years are less likely to have unintended pregnancy than women of age < 25 years. Odds ratio indicates that older women are 45% less likely to report having an unintended pregnancy.
Multivariate analysis also reveals that women of Chittagong and Rangpur have a negative regression coefficient and significant tendency to have less unintended pregnancy compared to Barisal division. It is noticed that Chittagong and Rangpur division's respondents are both 28%
less likely to have unintended pregnancy than Barisal division respondents, respectively. But the odds ratio of women in the Dhaka, Khulna, Rajshahi and Sylhet divisions did not show significant association since p-value > 0.05.
The result also illustrates that the occupation of respondent’s husbands shows a significant association. Husbands involving in others occupation (Student, Unemployment, etc.) are less likely (odds ratio is .366) to have unintended pregnancy than husbands involving in blue collar activities. The odds value also increases to 1.053 to husbands involving in white collar activities than husbands involving in blue collar activities. But this outcome did not indicate significant relationships since p-value > 0.05.
The study demonstrates that religion has a significant association with pregnancy intention status.
The result indicates Muslim women are 1.4 times more likely to have unintended pregnancy compared to Non-muslim women. The odds ratio indicated that age at first cohabitation had a strong positive association with pregnancy intention status. Respondents who had first cohabitation at 18 years or above are found to have unintended pregnancy 1.36 times more likely compared with those who had first cohabitation at below 18 years.
Similarly, age of respondents at first birth also exhibits a significant impact on the dependent variable, which shows respondents who had her first birth at the age of below 18 years are more experiencing unwanted pregnancy than the respondents who had her first birth at 18 years or above. Multivariate analysis shows a negative regression coefficient of respondents who had her first birth at 18 years or above. Odds ratio indicates that respondents who had her first birth at 18 years or above are 23% less likely to have unintended pregnancy than respondents who had her first birth at below 18 years. This result also shows significant since p-value < 0.05.
Total child ever born and number of living children also shows a positive association with pregnancy intention status. Multivariate analysis indicates that unintentional pregnancy increases with total child ever born and number of living children. Women with more than two children ever born and number of living children are respectively 1.7 times and 2.7 times more likely to have unintended pregnancy than women with two or less number of total child ever born and number of living children.
Discussions
Finally, the result illustrates that women who were currently residing with their husband/partner has a strong positive association with pregnancy intention status. The result indicates that women who were currently residing with their husband/partner showed 1.5 times more likely to have unintended pregnancy than ladies who were currently staying elsewhere.
According above analysis here are some recommendations -
Different social policies and exertion should be formulated to guarantee the advancement in human administrations organizations are running smoothly and consistently in the nation over, as well as the remotest region.
The study proposes building awareness with respect to the bad marks of unintended pregnancy among husbands with blue collar activities. In the long term, education of women ought to be expanded and women giving their first birthat least 18 years or aboveare recommended to reduce unplanned pregnancy.
Projects focusing to lessen unmet need for contraception, and legitimate rules ought to be created to quantify the degree and fundamental reasons for unmet need with an end goal to diminish the burden of unintended pregnancy in Bangladesh.
Enhancing the awareness about family planning among couples who are currently residing with their partners and first cohabitation before 18 years should be strictly prohibited.
More in-depth studies on the influence of behavioral and cultural practices on unintended pregnancy and also the reasons of unmet need for contraception can be helpful for developing explicit ways of unintended pregnancies.
Conclusion
By doing this study, we have reached to a conclusion that the prevalence of unintended pregnancy and unmet need for contraception are extensively high with critical incongruities through the residence. Unmet need for contraception and current use of contraception has a major effect on unintended pregnancy because women who not having any desire to take additional kids or want to postpone the next should use a proper contraception method otherwise there would have quite possibility of experiencing an unintentional pregnancy. Although 67.7% women were currently using any contraception, still there were many who were experiencing unwanted pregnancy. And in many case, this may be unintentional due to immaturity, unconsciousness and inadequate or lack of knowledge about family planning and contraception.
Limitations
The study has few limitations. The data were cross-sectional and in a cross-sectional study, it is hard to get causal relationships since this is a 1-time estimation of exposure and outcome. For this reason, there is no guarantee about causal relationships in the study. We can just get proof of
statistical relationship between the things of interest and the experience of unintended pregnancy.
As well as, we have Bangladesh Health and Demographic Survey (BDHS) 2014 as latest data source so far during this six years’ period the rate and perception about pregnancy intention and contraception utilization among women might be changed. Also data for currently pregnant women would give more significant result but the number was not too many to even think about producing statistically meaningful results. So we have to take consideration about the latest completed pregnancy occurred in the five years going before the study and any current pregnancy.
Acknowledgement Authors are grateful who have participated in this research.
References
[1] C. S. Klima, “Unintended pregnancy consequences and solutions for a worldwide problem,” Journal of Nurse-Midwifery., vol. 43, no. 6, pp. 483–491, (1998), doi:
10.1016/S0091-2182(98)00063-9.
[2] J. Santelli, R. Rochat, K. H. Timajchy, B. C. Gilbert, K. Curtis, R. Cabral, J. S. Hirsch, and L. Schieve, “The Measurement and Meaning of Unintended Pregnancy,” Perspective on Sexual and Reproductive Health, vol. 35, no. 2, pp. 94–101, (2003), doi: 10.1363/3509403.
[3] P. Dixit, F. Ram, and L. K. Dwivedi, “Determinants of unwanted pregnancies in India using matched case-control designs,” BMC Pregnancy & Childbirth, vol. 12, (2012), doi:
10.1186/1471-2393-12-84.
[4] M. A. Lara, C. Navarro, L. Navarrete, A. Cabrera, J. Almanza, F. Morales, and F. Juarez,
“Sintomas Depresivos En El Embarazo,” Salud Ment, vol. 29, no. 4, pp. 55–62, (2006).
[5] Y. Lau and D. W. F. Keung, “Correlates of depressive symptomatology during the second trimester of pregnancy among Hong Kong Chinese,” Social Science & Medicine, vol. 64, no. 9, pp. 1802–1811, (2007), doi: 10.1016/j.socscimed.2007.01.001.
[6] J. E. M. Nakku, G. Nakasi, and F. Mirembe, “Postpartum major depression at six weeks in primary health care: Prevalence and associated factors,” African Health Sciences, vol. 6, no. 4, pp. 207–214, (2006), doi: 10.5555/afhs.2006.6.4.207.
[7] J. M. Najman, J. Morrison, G. Williams, M. Andersen, and J. D. Keeping, “The mental health of women 6 months after they give birth to an unwanted baby: A longitudinal study,” Social Science and Medicine., vol. 32, no. 3, pp. 241–247, (1991), doi:
10.1016/0277-9536(91)90100-Q.
[8] K. Hardee, E. Eggleston, E. L. Wong, Irwanto, and T. H. Hull, “Unintended pregnancy and women’s psychological well-being in Indonesia,” J. Biosoc. Sci., vol. 36, no. 5, pp. 617–
626, (2004), doi: 10.1017/S0021932003006321.
[9] M. Kamal and A. Islam, “Prevalence and socioeconomic correlates of unintented pregnancy among women in rural Bangladesh,” Salud Publica Mex., vol. 53, no. 2, pp.
108–115, (2011), doi: 10.1590/s0036-36342011000200003.
[10] T. J. Joyce and M. Grossman, “Pregnancy wantedness and the early initiation of prenatal care,” Demography, vol. 27, no. 1, pp. 1–17, (1990), doi: 10.2307/2061549.
[11] M. R. Sable, J. W. Stockbauer, W. F. Schramm, and G. H. Land, “Differentiating the barriers to adequate prenatal care in Missouri, 1987-88,” Public Health Rep., vol. 105, no.
6, pp. 549–555, (1990).
[12] M. Rahman, “Women’s autonomy and unintended pregnancy among currently pregnant women in Bangladesh,” Matern. Child Health J., vol. 16, no. 6, pp. 1206–1214, (2012), doi: 10.1007/s10995-011-0897-3.
[13] S. Singh, G. Sedgh, and R. Hussain, “Unintended Worldwide Pregnancy : and Outcomes Trends , Levels ,” Population Council, Studies in Family Planning, vol. 41, no. 4, pp. 241–
250, (2010).
[14] G. Bishwajit, S. Tang, S. Yaya, and Z. Feng, “Unmet need for contraception and its association with unintended pregnancy in Bangladesh,” BMC Pregnancy and Childbirth, vol. 17, no. 1, pp. 1–9, (2017), doi: 10.1186/s12884-017-1379-4.
[15] J. Bongaarts, “Trends in Unwanted Childbearing in the Developing World,” Population Council, Studies in Family Planning, vol. 28, no. 4, p. 267, (1997), doi: 10.2307/2137858.
[16] S. Horvath and C. A. Schreiber, “Unintended Pregnancy, Induced Abortion, and Mental Health,”, Curr. Psychiatry Rep., vol. 19, no. 11, (2017), doi: 10.1007/s11920-017-0832-4.
[17] S. Dastgiri, M. Yoosefian, M. Garjani, and L. Kalankesh, “Induced Abortion: a Systematic Review and Meta-analysis,” Mater. Socio Medica, vol. 29, no. 1, p. 58, (2017), doi:
10.5455/msm.2017.29.58-67.
[18] T. Melese, D. Habte, B. M. Tsima, K. D. Mogobe, K. Chabaesele, G. Rankgoane, T. R.
Keakabetse, M. Masweu, M. Mokotedi, M. Motana, and B. M. Ntshabele, “High levels of post-abortion complication in a setting where abortion service is not legalized,” PLoS One, vol. 12, no. 1, pp. 1–13, (2017), doi: 10.1371/journal.pone.0166287.
[19] E. Oulman, T. H. M. Kim, K. Yunis, and H. Tamim, “Prevalence and predictors of unintended pregnancy among women: An analysis of the Canadian Maternity Experiences Survey,” BMC Pregnancy and Childbirth, vol. 15, no. 1, pp. 1–8, (2015), doi:
10.1186/s12884-015-0663-4.
[20] M. Mazharul Islam and A. H. M. Saidul Hasan, “Mass media exposure and its impact on family planning in Bangladesh,” J. Biosoc. Sci., vol. 32, no. 4, pp. 513–526, (2000), doi:
10.1017/S0021932000005137.
[21] National Institute of Population Research and Training (NIPORT), Mitra and Associates, and Macro International. “Bangladesh Demographic and Health Survey 2007,” Dhaka, Bangladesh and Calverton, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates, and Macro International, (2009).
[22] National Institute of Population Research and Training (NIPORT), Mitra and Associates, and ICF International, “Bangladesh Demographic and Health 2011,” pp. 1–430, (2013).
[23] A. Huda, K. Sarker, A. J. Azmi, and L. Reichenbach, “Understanding Unintended Pregnancy in Bangladesh : Country Profile Report,” STEP UP Res. Rep., no. December, p.
76, (2013), doi: 10.1177/0022034510376046.
[24] J. Amo-Adjei and E. K. M. Darteh, “Unmet/met need for contraception and self-reported abortion in Ghana,” Sex. Reprod. Healthc., vol. 13, pp. 118–124, (2017), doi:
10.1016/j.srhc.2017.02.002.
[25] Guttmacher Intstitute, “Induced Abortion Worldwide,” Fact Sheet, no. May, pp. 0–1, 2016.
[26] Susheela Singh and Jacqueline E. Darroch and S. S. and J. E. Darroch, “Adding It Up:
Costs and Benefits of Contraceptive Services Estimates for 2012,” Guttmacher Institute, United Nations Population Fund (UNFPA), 201, no. June, (2012).
[27] National Institute of Population Research and Training (NIPORT), Mitra and Associates, and ICF International, “Bangladesh Demographic and Health Survey 2014,” Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT, Mitra and Associates, and ICF International, (2016).
[28] A. O. Tsui, R. McDonald-Mosley, and A. E. Burke, “Family planning and the burden of unintended pregnancies,” Epidemiologic Reviews., vol. 32, no. 1, pp. 152–174, (2010), doi:
10.1093/epirev/mxq012.
[29] A. Exavery, A. M. Kante, M. Njozi, K. Tani, H. V Doctor, A. Hingora, and J. F Phillips,
“Predictors of mistimed, and unwanted pregnancies among women of childbearing age in Rufiji, Kilombero, and Ulanga districts of Tanzania,” Reproductive Health, vol. 11, no. 1, pp. 1–9, (2014), doi: 10.1186/1742-4755-11-63.
