Literature DB >> 28558671

Prevalence and determinants of unintended pregnancies amongst women attending antenatal clinics in Pakistan.

Muhammad Atif Habib1,2, Camille Raynes-Greenow3, Sidrah Nausheen4, Sajid Bashir Soofi4, Muhammad Sajid4, Zulfiqar A Bhutta4, Kirsten I Black5.   

Abstract

BACKGROUND: Unintended pregnancies are a global public health concern and contribute significantly to adverse maternal and neonatal health, social and economic outcomes and increase the risks of maternal deaths and neonatal mortality. In countries like Pakistan where data for the unintended pregnancies is scarce, studies are required to estimate its accurate prevalence and predictors using more specific tools such as the London Measure of Unplanned Pregnancies (LMUP).
METHODS: We conducted a hospital based cross sectional survey in two tertiary care hospitals in Pakistan. We used a pre tested structured questionnaire to collect the data on socio-demographic characteristics, reproductive history, awareness and past experience with contraceptives and unintended pregnancies using six item the LMUP. We used Univariate and multivariate analysis to explore the association between unintended pregnancies and predictor variables and presented the association as adjusted odds ratios. We also evaluated the psychometric properties of the Urdu version of the LMUP.
RESULTS: Amongst 3010 pregnant women, 1150 (38.2%) pregnancies were reported as unintended. In the multivariate analysis age < 20 years (AOR 3.5 1.1-6.5), being illiterate (AOR 1.9 1.1-3.4), living in a rural setting (1.7 1.2-2.3), having a pregnancy interval of = < 12 months (AOR 1.7 1.4-2.2), having a parity of >2 (AOR 1.4 1.2-1.8), having no knowledge about contraceptive methods (AOR 3.0 1.7-5.4) and never use of contraceptive methods (AOR 2.3 1.4-5.1) remained significantly associated with unintended pregnancy. The Urdu version of the LMUP scale was found to be acceptable, valid and reliable with the Cronbach's alpha of 0.85.
CONCLUSIONS: This study explores a high prevalence of unintended pregnancies and important factors especially those related to family planning. Integrated national family program that provides contraceptive services especially the modern methods to women during pre-conception and post-partum would be beneficial in averting unintended pregnancies and their related adverse outcomes in Pakistan.

Entities:  

Keywords:  Contraceptive methods; Family planning; London measure of unplanned pregnancies; Pakistan; Unintended pregnancies

Mesh:

Year:  2017        PMID: 28558671      PMCID: PMC5450067          DOI: 10.1186/s12884-017-1339-z

Source DB:  PubMed          Journal:  BMC Pregnancy Childbirth        ISSN: 1471-2393            Impact factor:   3.007


Background

Unintended pregnancies (pregnancies that are mistimed or unwanted) are a significant public health concern globally [1]. Of the estimated 210 million pregnancies that occur throughout the world each year, about 38% are unintended [2]. Twenty-two percent of global unintended pregnancies end in abortion, many of which take place with unsafe techniques and/or in unsafe circumstances and about 18% end in unplanned births, placing a substantial burden on health systems [1, 2]. Most of the unintended pregnancies occur in developing countries largely due to poor literacy and lack of knowledge and access to contraceptive methods [3, 4]. In these settings unintended pregnancies contribute significantly to adverse health, social and economic outcomes [4-8] and increase the risks of maternal death and neonatal, infant and child mortality [9]. Pakistan is a developing country where contraceptive prevalence remains low (35.4%) and the unmet need for family planning remains high (20.1%) contributing to high fertility rate (3.8 births/woman) and large numbers of unintended pregnancies [10, 11]. Annually about 2.25 million abortions are conducted in Pakistan and the national abortion rate is 50 per 1000 women (15-49 years) [12]. As abortion remains illegal, many of the procedures are undertaken in unsafe circumstances, leading to complications and adverse outcomes. Indeed in 2012 over 62,000 women were treated for complications [13]. Unsafe abortion also contributes to maternal mortality in Pakistan [14-16]. The reported prevalence of unintended pregnancies in Pakistan is between 16-46% [10-13]. Pakistan demographic and health surveys (PDHS) of 2006 and 2013 reported the prevalence of unintended pregnancies as 16% and 24% respectively [10, 11]. This estimate was based only on a single question with a dichotomous response on mistimed or unwanted pregnancy at the time of conception. Another study which estimated the prevalence of unintended pregnancies in Pakistan as 46% was based on an indirect modeling for unintended pregnancies from induced abortion rates [13]. These measures are not sufficient to accurately measure the burden of unintended pregnancies. However there is a more accurate, reliable and validated tool. The London Measure of Unplanned Pregnancies (LMUP) is a six item scale that has been widely used in both developed and developing countries [17-30]. Given the adverse impact of unintended pregnancies on maternal and neonatal morbidity and mortality, and the lack of available data, our aim was to investigate the prevalence of unintended pregnancy using the LMUP and examine the socio-demographic predictors in Pakistan.

Methods

We conducted a hospital based cross sectional survey between January 2015 and April 2015 to achieve a sample size of 3000 women. We hypothesized that 40% of all pregnancies in the antenatal population in our study setting would be unintended, where the population is poor and there are high levels of illiteracy, little knowledge of contraception and where first pregnancies occur at a young age [11]. The sample size was estimated using a prevalence rate of unintended pregnancies of 40%, a confidence level of 95%, a design effect of 1.5 and a non-response rate of 10%. The data collection was carried out in two tertiary care hospitals, one is located in Karachi city and the other one is located at district Dadu of Pakistan. Both hospitals have an average attendance of 100 females per day. Two female research assistants were trained and employed at both sites for data collection. All pregnant women attending the antenatal care clinic were eligible for recruitment. We developed a participant information sheet, consent form and an interview administered structured questionnaire. All material was translated into Urdu and then back translated into English to ensure the accuracy. The questionnaire was pre tested in an antenatal clinic that was not a study site. Women were given the participant information sheet to read, or when they were unable to read, the study was explained to them in Urdu by the research assistant. The questionnaire comprised of three sections; section one used the standard questions from demographic and health survey questionnaire to ascertain the characteristics and socio-demographic information of the respondent. Section two contained information about past reproductive history and family planning and section three used the Urdu version of pregnancy intention scale (LMUP) to ascertain unintended pregnancies. In this section questions were designed such that each response to the six questions was scored out of two, and summed to give a final pregnancy intendedness score between zero and 12. The intention scores were divided into three groups: zero-three (unplanned), four-nine (ambivalent) and ten-twelve (planned). Unintended pregnancy was the main outcome variable. Women with pregnancy intendedness scores less than 10 (including both ambivalent and unplanned pregnancies) were considered as unintended. The explanatory variables for analysis were informed by the literature and their availability in the dataset and are described in Tables 1 and 2. Variables were grouped into two categories; socio-demographic factors and women related factors. In the socio-demographic factors; age, residence, education and wealth index were considered. Age at marriage, gestational age, parity, birth interval, history of previous miscarriage or abortion, family planning knowledge, source of knowledge about family planning and family planning use were considered in the women related factors. Age at marriage was used as a proxy for age at first intercourse which is difficult to ask as it is a culturally sensitive question.
Table 1

Description of independent variables

VariablesDescription
Socio demographic factors
Area of residenceUrban and rural
Socio economic status of the householdSES was measured as quintiles of a linear index derived from household assets and utilities score, the wealth quintiles were divided into five (poorest, poorer, middle, richer, richest)
Women related factors
AgeCategorized as <20 years, 20-24 years, 25-29 years and >30 years
EducationYears of education completed (illiterate/years of education)
Age of marriageCategorized as = < 20 years and > 20 years, used as a proxy for age at first intercourse
Gestational ageRecorded in weeks and categorized as <28 weeks and 28 or more weeks
ParityDefined as the number of previous deliveries and categorized as = < 2 times and > 2 times
Birth intervalInterval from one child's birth date until the next child's birth date and categorized as <12 months, 12-24 months and > 24 months
History of abortion or miscarriageAny history of previous miscarriage and abortion and categorized as 1 = Yes and No = 2
Knowledge about family planning methodsEver heard of any family planning method and categorized as 1 = Yes and No = 2
Use of family planning methodsEver used any family planning method and categorized as 1 = Yes and No = 2
Table 2

London Measure of Unplanned Pregnancies (LMUP) scale

QuestionAnswerScore
At the time of conceptionAlways use contraception0
Inconsistently us contraception1
Not use contraception2
In terms of becoming a motherWrong time0
An OK time but not quite right1
Right time2
Just before falling pregnantNot intend to become pregnant0
Did not mind either way1
Intend to get pregnant2
Just before falling pregnantNot want a baby0
Have mixed feeling about having a baby1
Want a baby2
Before falling pregnant had you and your partnerNever discussed children0
Discuss children but no firm agreement1
Agreed to pregnancy2
Health actions before falling pregnanta No action0
1 action1
2 or more actions2

aHealth Actions include iron folic acid supplementation, cessation or reduction in smoking, tobacco/ Pan/ Gutka/

beetle nut chewing and seeking medical advice

Description of independent variables London Measure of Unplanned Pregnancies (LMUP) scale aHealth Actions include iron folic acid supplementation, cessation or reduction in smoking, tobacco/ Pan/ Gutka/ beetle nut chewing and seeking medical advice The ethical review committee of Aga Khan University granted ethical approval (Ref: 3710-Ped-ERC-15). Written informed consent was obtained from all participants. In cases where the woman was illiterate, consent was documented by a thumbprint on the consent form and confirmed by a signature from a literate witness. All the names and personal information regarding the participants were kept confidential and all identifying information was removed from analysis. The data were analyzed using IBM SPSS version 19 [31]. Initially the scoring of the responses from the data extracted from LMUP was done and the prevalence of unintended pregnancy was calculated using data from all six of the questions in the pregnancy intention instrument. Family planning profile of the participants was also established and comparison of contraception knowledge and use between the data of this study and PDHS 2012 was carried out. Univariate analyses were run between socio demographic factors and women related factors. Degree of association was assessed using chi squared tests. The demographic characteristics with a p-value <0.25 were then examined using logistic regression analyses. In multivariate analysis adjusted odds ratios and 95% confidence intervals were calculated to determine the degree of association between associated factors and pregnancy intention. In order to validate the Urdu version of the scale we conducted psychometric analysis of the Urdu LMUP. We assessed the proportion of missing data and considered item endorsement, with item response option endorsements of <80% considered to be acceptable [21–23, 26, 30]. To measure the reliability of scale, we evaluated the internal consistency by calculating the Cronbach’s alpha statistic using the standard cut off point of 0.7 and also looked at the corrected item-total correlations [21–23, 26, 30]. We also did Principal component analysis to evaluate the internal structure of the LMUP. The scale would be considered valid if all items load onto one component with an Eigenvalue larger than one (i.e. are measuring the same construct) [22, 26, 30].

Results

A total of 3010 women were included in the analysis with a mean gestational age of 26 weeks at the time of recruitment. Overall, 1150 (38.2%) pregnancies in the antenatal population were unintended, of which 420 (13.9%) were ambivalent and 730 (24.3%) were unplanned. The remaining 1860 (61.8%) pregnancies were considered intended. The socio demographic profile and women related factors are documented in Table 3. The majority of women (69.5%) were aged more than 25 years, 51.6% were illiterate and half of the women lived in a rural area. Among the study population the two lowest and two highest wealth quintiles accounted for 40.2% and 40.1% respectively. We found that 55.0% of women were aged 20 years or younger at the time of their marriage, 46.1% had a parity of two or more and 53.6% reported a short birth interval of ≤ 12 months. Among study participants 17.4% reported a previous miscarriage or abortion.
Table 3

Frequency distribution of sociodemographic and women related variables

VariableDescriptionN (%)
Pregnancy IntentionUnintended (Score <10)1150 (38.20)
Intended (Score >10)1860 (61.7)
Area of ResidenceRural1509 (50.1)
Urban1501 (49.9)
Wealth IndexPoorest599 (19.9)
Second612 (20.3)
Middle593 (19.7)
Fourth604 (20.1)
Richest602 (20)
Pregnant women age<20 years135 (4.5)
20-24 Years783 (26)
25-29 Years1297 (43.1)
> = 30 Years795 (26.4)
Pregnant women’s educationIlliterate1552 (51.6)
Primary or less (1-5 years of schooling)379 (12.6)
Middle(6-8)159 (5.3)
Matric(9-10)505 (16.8)
Intermidiate & above (>10)251 (8.3)
Graduation and above (>12)164 (5.4)
Pregnant women’s Age at marriage≤20 Years1656 (55)
> 20 Years1354 (45)
Gestational age<28 weeks1467 (48.7)
> = 28 weeks1541 (51.2)
Parity<=21161 (53.9)
>2994 (46.1)
Birth Interval≤ 12 months1200 (53.6)
>12 months1038 (46.4)
History of Abortion/MiscarriageYes523 (17.4)
No2487 (82.6)
Knowledge about Family PlanningNo306 (10.2)
Yes2704 (89.8)
Ever Used family planning methodsNo2004 (66.6)
Yes1006 (33.4)
Frequency distribution of sociodemographic and women related variables The family planning profile is outlined in Table 4. Overall 89.9% women had knowledge about at least one of the contraceptive methods but only 33.4% reported using them. For modern methods 96.2% of women had knowledge of the pill, followed by injectables (94.6%), condoms (88.3%), intrauterine devices (83.5%), implants (73.5%), female sterilisation (60.9%), and male sterilisation (15.1%). However use of contraception remained low with the most commonly used being condoms (19%) followed by injectables (9.7%), the pill (9.6%), intra uterine device (2.9%), and implants (2.5%). For traditional methods only 14.5% and 34.5% of women had knowledge about the rhythm and withdrawal methods while 13.8% and 46.1% women reported using the rhythm method and withdrawal method respectively. Knowledge about emergency contraception was also low as only 25% of women were aware of it and only 23.7% reported having ever used it. The data regarding source of information for family planning revealed that health care providers (59.9%) are the main source of information followed by peers (22.2%), husbands (15.0%) and the media (1.4%). Our family planning data was consistent with the recent PDHS data and displays a notable contraceptive knowledge and practice gap (Fig. 1).
Table 4

Family planning knowledge, use and source of information

Knowledge n (%)Ever used n (%)Health care providers n (%)Media n (%)Husband n (%)Peers n (%)Others n (%)
Any family planning method2706 (89.9)904 (33.4)1621 (59.9)39 (1.44)406 (15.0)602 (22.2)36 (1.3)
Condoms2658 (88.3)505 (19.0)1555 (58.5)40 (1.5)827 (31.1)226 (8.5)11 (0.4)
Pill2896 (96.2)278 (9.6)1955 (67.5)130 (4.5)46 (1.6)733 (25.3)32 (1.1)
IUD2513 (83.5)73 (2.9)1819 (72.4)30 (1.2)25 (1.0)608 (24.2)30 (1.2)
Injectable2847 (94.6)276 (9.7)1987 (69.8)80 (2.8)31 (1.1)715 (25.1)34 (1.2)
Implants2212 (73.5)55 (2.5)1712 (77.4)13 (0.6)20 (0.9)453 (20.5)13 (0.6)
Female sterilization1833 (60.9)04 (0.2)1510 (82.4)16 (0.9)31 (1.7)236 (12.9)38 (2.1)
Male Sterilization455 (15.1)02 (0.4)271 (59.6)05 (1.1)40 (8.7)129 (28.4)10 (2.2)
Emergency Contraception753 (25.0)178 (23.7)386 (51.2)05 (0.6)93 (12.3)267 (35.5)03 (0.4)
Rhythm436 (14.5)60 (13.8)199 (45.7)04 (0.9)125 (28.6)102 (23.3)07 (1.5)
Withdrawal1038 (34.5)478 (46.1)158 (15.2)03 (0.3)654 (63.0)195 (18.8)28 (2.7)
Fig 1

Comparison of contraception knowledge and use between survey for prevalence and determinants of unintended pregnancies among women attending antenatal clinics in Pakistan and PDHS 2012. **PIS~Pregnancy Intension Survey (Present study), **PDHS~Pakistan Demographic and Health Survey

Family planning knowledge, use and source of information Comparison of contraception knowledge and use between survey for prevalence and determinants of unintended pregnancies among women attending antenatal clinics in Pakistan and PDHS 2012. **PIS~Pregnancy Intension Survey (Present study), **PDHS~Pakistan Demographic and Health Survey Table 5 shows the univariate association between unintended pregnancy and the independent variables. Unintended pregnancy in Pakistani women was significantly associated with age < 20 years (OR 1.3 1.1-1.7), being poor (OR 1.8 1.3-2.3), being illiterate (OR 1.4 1.1-1.7), living in a rural setting (OR 1.5 1.1-1.8), having a pregnancy interval of ≤ 12 months (OR 1.8 1.3-2.9), having a previous history of miscarriage/abortion (OR 1.8 1.2-2.1), having parity of > 2 (OR 1.5 1.2-1.8), having no knowledge of any contraceptive method (OR 1.7 1.5-1.8) and never use of contraceptive methods (OR 1.2 1.1-3.8).
Table 5

Unadjusted association between unintended pregnancy and predictor variables, Pakistan 2015

VariableUnintended pregnancy n (%)OR p value
Area of Residence
Rural670 (58.3)1.5 (1.1-1.8)<0.001
Urban480 (41.7)Ref
Wealth Index
Poorest266 (23.1)1.8 (1.3-2.3)<0.001
Second259 (22.5)1.7 (1.2-2.1)<0.001
Middle244 (21.2)1.6 (1.1-2.0)<0.001
Fourth199 (17.3)1.1 (0.9-1.4)0.311
Richest182 (15.8)Ref
Pregnant women age
<20 years41 (3.6)1.3 (1.1-1.7)<0.001
20-24 Years205 (17.8)0.4 (0.3-0.5)<0.001
25-29 Years519 (45.1)0.7 (0.6-0.8)<0.001
> = 30 Years385 (33.5)Ref
Pregnant women’s education
Illiterate552 (48)1.4 (1.1 -1.7)0.011
Primary or less (1-5 years of schooling)153 (13.3)1.1 (0.7-1.5)0.769
Middle (6-8)62 (5.4)1.0 (0.6-1.6)0.995
Matric (9-10)216 (18.8)1.2 (0.8-1.7)0.398
Intermidiate & above (>10)103 (9)1.1 (0.7-1.6)0.683
Graduation and above (>12)64 (5.6)Ref
Pregnant women’s Age at marriage
≤ 20 Years648 (56.3)1.1 (0.9-1.3)0.248
> 20 Years502 (43.7)Ref
Gestational age
<28 weeks534 (46.4)1.2 (0.6-1.4)0.071
> = 28 weeks616 (53.6)Ref
Parity
>2528 (51.4)1.5 (1.2-1.8)<0.001
<=2500 (48.6)Ref
Birth Interval
≤ 12 months521 (50.2)1.8 (1.3-2.9)0.003
>12 months516 (49.8)Ref
History of Abortion/Miscarriage
Yes259 (22.5)1.8 (1.2-2.1)<0.001
No891 (77.5)ref
Knowledge about Family Planning
No95 (8.3)1.7 (1.5-1.9)0.007
Yes1055 (91.7)ref
Ever Used family planning methods
No657 (57.1)1.2 (1.1-3.8)<0.001
Yes493 (42.9)ref
Unadjusted association between unintended pregnancy and predictor variables, Pakistan 2015 In the multivariate analysis (Table 6) being poor and having history of miscarriage/abortion no longer remained associated with unintended pregnancies but age < 20 years (AOR 3.5 1.1-6.5), being illiterate (AOR 1.9 1.1-3.4), living in a rural setting (AOR 1.7 1.2-2.3), having a pregnancy interval of = < 12 months (AOR 1.7 1.4-2.2), having a parity of >2 (AOR 1.4 1.2-1.8), having no knowledge about contraceptive methods (AOR 3.0 1.7-5.4) and never use of contraceptive methods (AOR 2.3 1.4-5.1) remained significantly associated with unintended pregnancy.
Table 6

Adjusted association between unintended pregnancies and of predictor variables, Pakistan 2015

VariableUnintended pregnancy n (%)AOR p value
Area of Residence
Rural670 (58.3)1.7 (1.2-2.3)<0.001
Urban480 (41.7)ref
Wealth Index
Poorest266 (23.1)1.4 (0.9-2.2)0.063
Second259 (22.5)1.7 (0.9-1.8)0.068
Middle244 (21.2)1.6 (0.8-1.8)0.087
Fourth199 (17.3)1.1 (0.8-1.4)0.311
Richest182 (15.8)ref
Pregnant women age
<20 years41 (3.6)3.5 (1.1-6.5)0.022
20-24 Years205 (17.8)1.0 (0.7-1.4)0.937
25-29 Years519 (45.1)1.1 (0.9-1.4)0.345
> = 30 Years385 (33.5)ref
Pregnant women’s education
Illiterate552 (48)1.9 (1.1-3.4)0.025
Primary or less (1-5 years of schooling)153 (13.3)1.8 (1.0-3.1)0.053
Middle (6-8)62 (5.4)1.8 (0.9-3.5)0.100
Matric (9-10)216 (18.8)1.9 (1.1-3.2)0.022
Intermidiate & above (>10)103 (9)1.5 (0.8-2.6)0.195
Graduation and above (>12)64 (5.6)ref
Parity
>2528 (51.4)1.4 (1.2-1.8)<0.001
<=2500 (48.6)ref
Birth Interval
≤ 12 months521 (50.2)1.7 (1.4-2.2)<0.001
>12 months516 (49.8)ref
History of Abortion/Miscarriage
Yes259 (22.5)1.1 (0.7-1.8)0.080
No891 (77.5)ref
Knowledge about Family Planning
No95 (8.3)3.0 (1.7-5.4)<0.001
Yes1055 (91.7)ref
Ever Used family planning methods
No657 (57.1)2.3 (1.4-5.1)<0.001
Yes493 (42.9)ref
Adjusted association between unintended pregnancies and of predictor variables, Pakistan 2015 The psychometric analysis of the Urdu LMUP demonstrated relatively high internal consistency, with the Cronbach’s alpha score at 0.85 and the all item-rest correlations were 0.207 for item 1, 0.483 for item 2, 0.487 for item 3, 0.494 for item 4, 0.467 for item 5 and 0.235 for item 6. We did not observe any missing data (Table 7). The LMUP score distribution was non-normal and the median score was 10 (inter-quartile range 5–11). The principal component analysis confirmed that all six items loaded onto one component (Eigenvalue = 3.81) and the six items component loadings were 0.146 for item 1, 0.865 for item 2, 0.870 for item 3, 0.902 for item 4, 0.815 for item 5 and 0.331 for item 6. We also report the full range of the LMUP scores (Fig. 2).
Table 7

Endorsement and response options for the LMUP scale

Endorsement of the PI items and response optionLMUP Pakistan
ItemsCategoryn%
At the time of conception0. Always use contraception64221.3
1. Inconsistently use contraception2197.3
2. Not use contraception214971.4
In terms of becoming a mother0. Wrong time62920.9
1. An OK time but not quite right1454.8
2. Right time223674.3
Just before falling pregnant0. Not intend to become pregnant73424.4
1. Did not mind either way1986.6
2. Intend to get pregnant207869.0
Just before falling pregnant0. Not want a baby72924.2
1. Have mixed feelings about having a baby1103.7
2. Want a baby217172.1
Before falling pregnant had you and your husband0. Never discussed children60120.0
1. Discussed children but no firm agreement2749.1
2. Agreed to pregnancy213570.9
Health actions before falling pregnant0. No Action100133.3
1. Action126742.1
2 or more Actions74224.7
Total3010100.0
Fig 2

Distribution of Pregnancy intention score

Endorsement and response options for the LMUP scale Distribution of Pregnancy intention score

Discussion

In our study the estimated prevalence of unintended pregnancies in women attending the antenatal care clinic was 38.2% which is consistent with the estimated global prevalence [1]. This estimate is higher than previously reported data of 16% and 24% in PDHS 2006 and 2013 [10, 11] but lower than the 46% reported in the study conducted by Sathar et al. [12]. These previous studies used a dichotomous scale whereas we employed the six item LMUP [17–30, 32]. The prevalence of unintended pregnancies in our study is higher than the studies from Iran (33.7%) [21], Kenya (24%) [33], Ethiopia (27.9%) [34] and Sudan (30.2%) [35] but lower than in Nepal (41%) [36], Papua New Guinea (49.4%) [20], Tanzania (45.9%) [37] and Ghana (70%) [38]. The most relevant comparable data are those from Iran and Papua New Guniea [20, 21] who also used the LMUP, although in Papua New Guinea a five item partial LMUP was used as item 6 was dropped to be locally appropriate. Our study showed that the likelihood of unintended pregnancies is significantly associated with age less than 20 years. This is consistent with the Papua New Guinean, Kenyan and Tanzanian data [20, 33, 37] and makes sense given that younger women have higher fertility, higher frequency of sexual intercourse, lower knowledge of contraceptive methods and higher rates of contraceptive failure relative to older women [33, 37, 39, 40]. Likewise women who were illiterate were more likely to have an unintended pregnancy [20, 35, 36] which is consistent with evidence documenting that literate women have a better understanding of their rights and responsibilities and have more freedom, control and participation in decisions around contraception use and family planning [41-44]. In our study parity was significantly associated with unintended pregnancies. Women who had a parity of greater than two were more likely to have an unintended pregnancy. This finding is comparable to studies conducted in other developing countries [20, 34, 35, 38, 45]. Similar to parity, short birth intervals of less than 12 months were also found to be significantly associated with unintended pregnancies in our study as has been noted elsewhere [20, 46, 47]. Consistent with the available literature [20, 33–38], our study found that unintended pregnancy is strongly associated with a lack of awareness of contraceptive methods. As contraceptive awareness has been found to be directly related to its’ use [48-50] it is essential to implement initiatives to improve community knowledge about contraceptive methods. Our study also found that women who had never used contraception had twice at risk of having an unintended pregnancy compared to current users, as is consistent with the literature [20, 33–38, 51]. Furthermore, ever use of modern methods (including condoms, pills, IUDs, injectables, implants, male and female sterilization and emergency contraception) was very low and use of traditional methods high (Table 4). This use of modern methods is alarmingly low, particularly the long acting reversible contraceptives (LARC) such as intrauterine devices (IUDs) and implants, possibly due to fear of infertility and side effects [52, 53]. Our data is consistent with the recent PDHS which estimated the unmet need to be 20.1% [11, 54] which is well below that of neighboring countries like India, Nepal and Bangladesh [55-57]. It is evident that National family planning programs are failing to reach many women in need of contraception [52, 58]. Studies from Pakistan have demonstrated that lack of spousal communication, religious beliefs, concerns about infertility and side effects and supply side factors such as poor access, lack of counseling and insufficient availability of modern methods are the major hurdles to the acceptance of modern contraceptive methods [59-61]. Antenatal and postnatal counseling programs in other countries have demonstrated they can improve contraceptive prevalence [62-65]. Similar initiatives could easily be integrated into the Pakistan lady health workers (LHW) program (which has a workforce of more than 100,000 LHWs) [66]. Of course increased availability of modern methods of contraception would need to accompany any such educational program. After adjusting for other factors women living in rural areas exhibited increased odds of an unintended pregnancy compared to their urban counterparts, a finding consistent with previous studies in similar settings [37, 67, 68], this is likely to be associated with the higher prevalence of poverty, illiteracy, poor contraceptive knowledge and little access to modern contraceptive methods and services in rural areas. Additionally rural women may not have autonomy in decision making and may have little or no say in family planning decisions [68, 69]. Our results indicate that the Urdu LMUP in Pakistan performed very well, with demonstrated reliability and validity in terms of acceptability, targeting, internal consistency and structural validity. The validation results are comparable (Table 7) with the similar validation studies for LMUP conducted in Iran, Malawi, India, United States and Brazil [21–23, 26, 30]. The use of a validated pregnancy intention scale (LMUP) to estimate unintended pregnancies was the main strength of our study, but there are some limitations. Firstly there is a possibility of recall bias due to retrospective nature of the questionnaire. Secondly the cross-sectional design does not allow causal inferences and lastly the results may not be generalizable to the whole country since the study was conducted only in two tertiary care hospitals. And finally is the lack of a test-retest analysis in the psychometric data for the stability of the scores. Although efforts are being made by both private and public institutions, access to modern methods remains a challenge in Pakistan. Similarly the provision of safe abortion services remained a neglected area due to its illegal status and stigmatization [70]. Recent estimates suggest that about 25,000 unintended pregnancies and their related abortions and unplanned births could be averted over a 5-year period only by changing 4% of current oral contraceptive users in Pakistan to LARC [71]. Community midwives and lady health visitors are well placed to provide LARC services [52] that will allow women the possibility of birth spacing and family limiting [72]. As many women in Pakistan do not have the freedom to decide about family planning it is essential that men are also engaged in education programs which have been found to effectively improve attitudes and behaviors, a decrease in the fertility and an increase in the contraceptive use [73].

Conclusion

The high prevalence of unintended pregnancies resulting in induced abortions and unplanned births in Pakistan highlight the urgent need for a concerted effort through a private and public partnership to improve the knowledge and access to modern contraceptive methods and safe abortion services. An integrated national family program that provides contraceptive services to women during pre-conception and post-partum would be beneficial in averting unintended pregnancies and their related adverse outcomes in Pakistan.
  47 in total

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Authors:  James Trussell
Journal:  Contraception       Date:  2004-08       Impact factor: 3.375

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Authors:  Abiodun I Adanikin; Uche Onwudiegwu; Olabisi M Loto
Journal:  Eur J Contracept Reprod Health Care       Date:  2013-07-25       Impact factor: 1.848

Review 3.  Intention to become pregnant and low birth weight and preterm birth: a systematic review.

Authors:  Prakesh S Shah; Taiba Balkhair; Arne Ohlsson; Joseph Beyene; Fran Scott; Corine Frick
Journal:  Matern Child Health J       Date:  2011-02

4.  Unintended pregnancy amongst an early pregnancy clinic cohort: Identifying opportunities for preventative health interventions.

Authors:  Kate Cheney; Kyra A Sim; Mario D'souza; Marilena Pelosi; Kirsten I Black
Journal:  Aust N Z J Obstet Gynaecol       Date:  2016-05-02       Impact factor: 2.100

5.  Effectiveness of a theory-based postpartum sexual health education program on women's contraceptive use: a randomized controlled trial.

Authors:  Jian Tao Lee; Jia Ling Tsai; Tsung Shan Tsou; Min Chi Chen
Journal:  Contraception       Date:  2010-12-24       Impact factor: 3.375

6.  Predictors of unintended pregnancy in Kersa, eastern Ethiopia, 2010.

Authors:  Nega Kassa; Yemane Berhane; Alemayehu Worku
Journal:  Reprod Health       Date:  2012-01-12       Impact factor: 3.223

7.  Conceptualisation, development, and evaluation of a measure of unplanned pregnancy.

Authors:  G Barrett; S C Smith; K Wellings
Journal:  J Epidemiol Community Health       Date:  2004-05       Impact factor: 3.710

8.  Effect of socioeconomic characteristics on age at marriage and total fertility in Nepal.

Authors:  Pushkar Maitra
Journal:  J Health Popul Nutr       Date:  2004-03       Impact factor: 2.000

9.  Evaluation of the psychometric properties of the London Measure of Unplanned Pregnancy in Brazilian Portuguese.

Authors:  Ana Luiza Vilela Borges; Geraldine Barrett; Osmara Alves Dos Santos; Natalia de Castro Nascimento; Fernanda Bigio Cavalhieri; Elizabeth Fujimori
Journal:  BMC Pregnancy Childbirth       Date:  2016-08-24       Impact factor: 3.007

10.  Predictors of Unintended Pregnancy among Married Women in Hamadan, Western Iran: A Case-Control Study.

Authors:  Parvin Cheraghi; Jalal Poorolajal; Babak Moeini; Zahra Cheraghi
Journal:  Iran J Public Health       Date:  2013-08       Impact factor: 1.429

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  27 in total

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Authors:  Judith Stephenson; Nicola Heslehurst; Jennifer Hall; Danielle A J M Schoenaker; Jayne Hutchinson; Janet E Cade; Lucilla Poston; Geraldine Barrett; Sarah R Crozier; Mary Barker; Kalyanaraman Kumaran; Chittaranjan S Yajnik; Janis Baird; Gita D Mishra
Journal:  Lancet       Date:  2018-04-16       Impact factor: 79.321

2.  Magnitude of Unintended Pregnancy and Associated Factors Among Pregnant Women in Debre Markos Town, East Gojjam Zone, Northwest Ethiopia: A Cross-Sectional Study.

Authors:  Kumneger Nigussie; Genet Degu; Habtamu Chanie; Hayimro Edemealem
Journal:  Int J Womens Health       Date:  2021-01-28

3.  Psychometric properties of the Dutch version of the London Measure of Unplanned Pregnancy in women with pregnancies ending in birth.

Authors:  Joline Goossens; Sofie Verhaeghe; Ann Van Hecke; Geraldine Barrett; Ilse Delbaere; Dimitri Beeckman
Journal:  PLoS One       Date:  2018-04-18       Impact factor: 3.240

4.  Unintended pregnancy and associated factors among unmarried female students: A case of Bahir Dar University.

Authors:  Dagnachew Belay; Abebaw Alem; Salle Zerihun; Gashaw Antehun; Zewuditu Nega; Balew Zeleke; Yinager Workineh; Addisu Melese; Getenet Dessie; Emiru Ayalew
Journal:  Heliyon       Date:  2020-06-27

5.  Do modern family planning methods impact women's quality of life? Jordanian women's perspective.

Authors:  Mohammad S Alyahya; Heba H Hijazi; Hussam A Alshraideh; Nihaya A Al-Sheyab; Dana Alomari; Sara Malkawi; Sarah Qassas; Samah Darabseh; Yousef S Khader
Journal:  Health Qual Life Outcomes       Date:  2019-10-15       Impact factor: 3.186

6.  Validation of the London Measure of Unplanned Pregnancy among pregnant Australian women.

Authors:  Adina Y Lang; Jennifer A Hall; Jacqueline A Boyle; Cheryce L Harrison; Helena Teede; Lisa J Moran; Geraldine Barrett
Journal:  PLoS One       Date:  2019-08-08       Impact factor: 3.240

7.  Evaluating the Chichewa version of the London Measure of Unplanned Pregnancy in Malawi: a validation update.

Authors:  Jennifer A Hall; Judith Stephenson; Geraldine Barrett
Journal:  BMC Res Notes       Date:  2021-06-10

8.  Gender of children and social provisions as predictors of unplanned pregnancies in Pakistan: a cross-sectional survey.

Authors:  Sadiq Naveed; Usman Ghani Lashari; Ahmed Waqas; Mariam Bhuiyan; Hafsa Meraj
Journal:  BMC Res Notes       Date:  2018-08-14

9.  Unintended pregnancy and associated factors among pregnant women in Arsi Negele Woreda, West Arsi Zone, Ethiopia.

Authors:  Robera Olana Fite; Abdurahman Mohammedamin; Tilaye Workneh Abebe
Journal:  BMC Res Notes       Date:  2018-09-17

10.  Comparing the order of the London Measure of Unplanned Pregnancy and the Demographic and Health Survey question on pregnancy intention in a single group of postnatal women in Malawi - the effect of question order on assessment of pregnancy intention.

Authors:  Jennifer A Hall; Judith Stephenson; Geraldine Barrett
Journal:  BMC Res Notes       Date:  2018-07-17
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