Factors associated with unintended pregnancy among women attending a public health facility in KwaZulu-Natal, South Africa South African Family Practice is co-published by Medpharm Publications, NISC (Pty) Ltd and Informa UK Limited [trading as the Taylor & Francis Group] S Afr Fam Pract ISSN 2078-6190 EISSN 2078-6204 © 2017 The Author(s) RESEARCH South African Family Practice 2017; 1(1):1–5 https://doi.org/10.1080/20786190.2017.1396790 Open Access article distributed under the terms of the Creative Commons License [CC BY-NC 3.0] http://creativecommons.org/licenses/by-nc/3.0 Factors associated with unintended pregnancy among women attending a public health facility in KwaZulu-Natal, South Africa Firoza Haffejeea*  , Laura O’Connorb, Nalini Govendera, Poovendhree Reddyc, Maureen Nokuthula Sibiyad  , Shanaz Ghumanc, Thembelihle Ngxongoe and Dorinda Borgb aDepartment of Basic Medical Sciences, Durban University of Technology, Durban, South Africa b Department of Chiropractic and Somatology, Durban University of Technology, Durban, South Africa cDepartment of Community Health Studies, Durban University of Technology, Durban, South Africa dFaculty of Health Sciences, Durban University of Technology, Durban, South Africa e Department of Nursing, Durban University of Technology, Durban, South Africa *Corresponding author, email: firozah@dut.ac.za Background: Across the globe a large proportion of pregnancies have been reported as unintended. There are no available reports from South Africa concerning the prevalence of unintended pregnancies. This study explored the prevalence of unintended pregnancies among South African women attending a public primary health care (PHC) clinic in KwaZulu-Natal (KZN), South Africa. It also investigated the relationship between demographic factors, contraceptive use, substance abuse and unintended pregnancy in this setting. Methods: A descriptive cross-sectional survey was conducted among patients (n = 328) attending a PHC clinic. Participants were recruited by convenience sampling. Women who attended the clinic on their first antenatal visit were invited to participate. Participants filled out questionnaires in either English or isiZulu. Association between pregnancy and categorical variables was assessed. Results: Participants were mostly single (89.9%; n = 267), unemployed (70.8%; n = 222) with a monthly income of less than R 1 500 per month (63.8%; n = 81). Two-thirds of the women (64.33%; n = 211) had unintended pregnancies. There was a significant relationship between marital status and unintended pregnancy. Women who were married or living with their partners were more likely to have planned their pregnancies as compared with those who were single or divorced. Unemployed women were more likely to have had unintended pregnancies. No other socio-demographic factors were linked to unintended pregnancy. Conclusion: It is concluded that in this population of South African women with low education levels and low income, the prevalence of unintended pregnancies is high. These unintended pregnancies are linked to single status as well as unemployment. Keywords: pregnancy, public sector health care, South Africa, unintended pregnancy Introduction Unintended pregnancies are those that are not wanted by both parents or mistimed at the time of conception.1,2 Approximately 86 million pregnancies in 2008 were unintended, with 74 million of these occurring in less developed countries.1 Moreover, 39% of unintended pregnancies resulted in live births, 48% in abortions and 13% in miscarriages.1 Unintended pregnancy is a major public health burden, because it is linked with negative health, social and economic consequences.1,3 Studies have shown that approximately 28% of unintended pregnancies in developing countries can be avoided.4 Planned or intended pregnancies empower women to improve decision-making regarding antenatal care (ANC), prenatal diagnosis and use of folic acid, and prevent exposure to teratogenic substances, thus enhancing the health and growth of the developing child.5 The risk of unintended pregnancy in sub-Saharan Africa remains high and is poorly resolved due to poor access to reproductive health care.6 In Botswana 44% of pregnancies are reported to be unintended.7 Although recent reports indicate that the rate of unintended pregnancies in South Africa is high, these reports do not provide the frequencies of these pregnancies.8 The 1998 South Africa demographic and health survey reported 61% and 46% unintentional first and second pregnancies, respectively, within South Africa.9 In addition, studies conducted in KwaZulu- Natal (KZN), South Africa, suggest that 84% of all pregnancies were unintended.10 It is important that more recent data be obtained in order to ascertain whether any changes in pregnancy intention have occurred in the last decade. Unintended pregnancies have been attributed to poor family planning and/or inadequate access to contraceptives, religious beliefs, inadequate understanding of contraception and reproductive health education, lack of inter-partner communication and sexual violence.11–16 Communication between partners with regard to family planning is related to the use of contraceptives and thus the prevention of unintended pregnancies.17 This is supported by Exavery et al. (2014), who suggest that single marital status is a risk factor for unintended pregnancies.18 Moreover, Font-Ribera et al. (2008) report that single women as well as those from disadvantaged socio- economic environments are more at risk of having an unintended pregnancy.5 Socio-economic inequalities may therefore affect a women’s ability to plan pregnancies, based on the resources available for raising a child. Moreover, risky behaviours such as alcohol abuse and smoking may lead to unintended pregnancies.19,20 Such health-risk behaviours predispose both the mother and the developing foetus to adverse pregnancy and neonatal outcomes. Based on the current knowledge of the risks related to unintended pregnancies and the scarcity of such studies in South Africa, this study aimed at exploring the factors associated http://orcid.org/0000-0002-3908-8949 http://orcid.org/0000-0003-1220-1478 mailto:firozah@dut.ac.za http://crossmark.crossref.org/dialog/?doi=10.1080/20786190.2017.1396790&domain=pdf 2 South African Family Practice 2017; 1(1):1–5 with unintended pregnancies among South African women attending a public primary health care clinic in KwaZulu-Natal (KZN), South Africa. This study is valuable as little is known about the relationship between demographic factors, contraceptive use, substance abuse and unintended pregnancy in this setting. Methods This was a descriptive cross-sectional survey, utilising a socio- demographic questionnaire as well as clinic records of recruited participants. The study was conducted from October 2015 to October 2016 at a primary health care (PHC) clinic in the eThekwini Municipality of KZN, South Africa. Women presenting at the clinic for the first time for ANC, between two and 30 weeks of pregnancy, were invited to participate. The average number of women that present for the first ANC visit annually is 1 800. Using this total population, a confidence level of 95% and a confidence interval of 5%, the required minimum sample size was 317. Participants were recruited by convenience sampling. Women who came to the clinic on their first antenatal visit were informed about the study by the research nurse and were invited to participate. Participation was voluntary and no one was coerced into answering the questionnaire. Women were excluded if they were too sick to participate or suffering from mental illness. After obtaining written informed consent, a total of 328 women completed two surveys and were examined by the clinic nurse, who extracted additional data from their clinic file. The surveys were available in isiZulu or English. A socio-demographic questionnaire, by Napier et al. (2009) was utilised to obtain information pertaining to the participant’s household living arrangements, family resources, employment status, income and education.21 Obtaining socio-demographic data assists in establishing the social and economic conditions that affect an individual and can be used to establish poverty levels.22 The researchers compiled a questionnaire to obtain information relative to contraceptive use, pregnancy and psychosocial factors relevant to pregnancy. This questionnaire was validated by a focus group, where each question was critically analysed and modified or removed if necessary. Prior to starting the study both questionnaires were pilot tested to ensure that the surveys were easy to administer and that there was no ambiguity in answering the questions. A chart review tool was developed to extract pregnancy and health-related information from the participants’ clinic charts. All data were collected on the participant’s first antenatal visit. Ethical approval to conduct the study was obtained from the Institutional Research Ethics Committee of Durban University of Technology (Ref: IREC 34/14 and IREC 045/14), eThekwini Health District and KZN Provincial Department of Health (Ref: HRKM 234/14). Statistical analysis Statistical analysis was conducted using STATA® version 11 (StataCorp LLC, College Station, TX, USA). Data were analysed using both descriptive and inferential statistics. Frequency distributions of categorical variables, means, standard deviation and ranges of continuous variables were calculated. Association between intended pregnancy and categorical variables was assessed using the chi-square or Fisher’s exact test, where applicable. For numerical data, independent Student t-tests were utilised. Multivariate regression modelling was done using a backward stepwise method with the inclusion of relevant covariates. Odds ratio were calculated for binary outcome variables. Confidence intervals (95%) were calculated and a p-value less than 0.05 was considered statistically significant. Results A total of 328 pregnant women were enrolled in the study. Their mean age was 26 ± 5.8 years, ranging from 15 to 44 years of age. Their demographic, psychosocial and pregnancy-related characteristics are highlighted in Table 1. They were mostly single (89.9%; n  =  267), unemployed (70.8%; n  =  222) with a monthly income of less than R1 500 per month (63.8%; n = 81). The mean gestational age at the time of enrolment was 13.8 ± 5.12 weeks with a range from two to 30 weeks. A third of the women (35.7%; n  =  117) intended to continue their pregnancy yet 75.4% (n = 205) reported having been using contraceptives. According to the clinical records, the majority of the women were not HIV positive (69.7%; n  =  145). Only 34.4% (n  =  109) indicated that they had ever drunk alcohol. Bivariate analysis showed that there was a significant relationship between marital status and unintended pregnancy, with those who were married or living with their partners more likely to have planned their pregnancy than those who were single or divorced (p < 0.001). Those who were currently unemployed were more likely to have had unintended pregnancies (p = 0.020), as seen in Table 2. No significant relationships were found between age, household income, being a recipient of a government grant or level of education and unintended pregnancy. HIV status did not affect the participants’ pregnancy intention. There was a significant relationship between not using contraception by those who had unintended pregnancies and reporting that they thought they could not get pregnant (p < 0.001). No significant Table 1: Participant demographics (n = 328) Variables Total n (%) Age Under 18 yrs 18 (6.2) 18–30 yrs 220 (74.8) > 30 yrs 56 (19.0) Marital status Married/living together 53 (16.3) Single 267 (81.9) Divorced/separated/widowed/other 6 (1.8) Contraception use 205 (75.4) Ever consumed alcohol 109 (34.4) Cigarette smoking 3 (0.95) Recreational drug use 6 (1.94) Currently employed 92 (29.3) Household income Less than 1 500 81 (63.8) 1 501 to 3 000 28 (22.0) > 3 000 19 (15.0) Recipient of a government grant 70 (37.9) Level of education None 9 (2.9) Primary school 9 (2.9) High school 228 (73.5) Post school 64 (20.6) HIV positive 63 (30.3) Factors associated with unintended pregnancy among women attending a public health facility in KwaZulu-Natal, South Africa 3 relationships were found between the use of home remedies to stop pregnancy, reported history of alcohol use, use of alcohol in the three months prior to falling pregnant or alcohol use while pregnant and unintended pregnancy. There was also no relationship between cigarette smoking and illicit drug use versus unintended pregnancy (see Table 2). Multivariate analysis, controlling for alcohol use prior to pregnancy, and level of education showed that single pregnant participants were 3.73 (1.82–7.62) times more likely to have reported that their pregnancy was unintended, with no other significant relationships being found (Table 3). Discussion This study ascertained factors that influence unintended pregnancy in women attending a public healthcare facility in KwaZulu-Natal, South Africa. Our results show that there is a high prevalence of unintended pregnancies in the study population, with only 36% reporting that they wanted the pregnancy. Unintended pregnancies were more common in single women and those who were not employed, with no other demographic or behavioural characteristics having an effect on pregnancy intention. Our finding of approximately two-thirds (64.33%) of the pregnancies being unintended is consistent with reports from studies conducted in America and Ghana.6,23 Reports from Tanzania estimate that about half of the pregnancies in that country are unintended.18 In contrast, pregnancy intention is high in the Chinese population, where more than 72% of the pregnancies were intended.24 The findings from the current study demonstrate that women with unintended pregnancies were more likely to be single compared with women whose pregnancies were intended. It must be noted that the proportion of single status within the study population was high, with a total of 82% of women being single. This is consistent with findings of high single status Table 2: Demographic, psychosocial and pregnancy-related variables relative to intended and unintended pregnancy (n = 328) Variables* Intended n (%) Unintended n (%) p-value Age 0.09 Under 18 yrs 4 (1.4) 14 (4.8) 18–30 yrs 72 (24.5) 148 (50.3) > 30 yrs 26 (8.8) 30 (10.2) *Marital status < 0.001 Married/living together 32 (9.8) 21 (6.4) Single 84 (25.8) 183 (56.1) Divorced/separated/wid- owed/other 1 (0.3) 5 (1.5) Contraception use 72 (26.5) 133 (48.9) 0.371 Reasons for not using contraception *I didn’t mind if I got pregnant 63 (24.5) 28 (10.9) < 0.001 *I thought I could not get pregnant at that time 14 (5.4) 80 (31.1) < 0.001 I had side effects from the birth control method I was using 8 (3.1) 20 (7.8) 0.416 I had problems getting birth control when I needed it 0 (0.0) 4 (1.6) 0.301 I thought my husband/ partner or I was sterile 2 (0.8) 3 (1.2) 1.000 My husband or partner didn’t want to use anything 2 (0.8) 5 (1.9) 1.000 Religious beliefs 0 (0.0) 2 (0.8) 0.540 Other 8 (3.1) 30 (11.7) 0.079 Use of home remedies to stop being pregnant 0 (0.0) 1 (0.5) 0.331 *Ever consumed alcohol 31 (9.8) 78 (24.6) 0.080 Alcohol use 3 months prior to pregnancy 16 (6.3) 33 (12.9) 0.744 Alcohol consumption while pregnant 6 (2.2) 5 (1.9) 0.210 Cigarette smoking 4 (1.4) 2 (0.8) 0.668 Recreational drug use 1 (0.35) 2 (0.8) 0.283 *Currently employed 42 (13.4) 50 (15.9) 0.020 Household income 0.122 Less than 1 500 26 (20.5) 55 (43.3) 1 501 to 3 000 10 (7.9) 18 (14.2) > 3 000 11 (8.7) 8 (6.3) Recipient of a government grant 21 (11.4) 49 (26.5) 0.271 Level of education 0.437 None 2 (0.6) 7 (2.3) Primary school 2 (0.6) 7 (2.3) High school 77 (24.8) 151 (48.7) Post school 27 (8.7) 37 (11.9) HIV positive 21 (10.1) 42 (20.2) 0.898 *p-value < 0.05; there were missing data for some of the variables. Table 3: Multivariate logistic regression of unintended pregnancy by marital status, alcohol used during pregnancy and beneficiary of a government and/or child grant *Model adjusted for alcohol use before pregnancy and level of education. **p-value < 0.05. Variable Unintended pregnancy** OR 95% CI p-value Marital status Married 1.00 *Single 3.73 1.82–7.62 < 0.001 Divorced 3.08 0.25–37.25 0.377 No alcohol use 1.00 Alcohol used prior to pregnancy 0.94 0.46–1.92 0.871 Alcohol during pregnancy 0.27 0.64–1.17 0.081 No grants 1.00 Government grants 1.24 0.62–2.47 0.549 Child grants 1.18 0.62–2.25 0.612 4 South African Family Practice 2017; 1(1):1–5 women had ever consumed alcohol, we found no relationship between alcohol use and pregnancy intention (p = 0.08). Unintended pregnancies contribute to unwanted population growth, subsequently compromising social services. Thus, the elimination of unintended pregnancies will enhance the well- being of women and their families. We suggest a need to improve the knowledge of contraception and family planning methods within this population, so that women are able to control their fertility and determine when to have children. We conclude that in this population of South African women with low education levels and low income, the prevalence of unintended pregnancies is high and that this is linked to single status. Acknowledgements – The authors thank Charity Wendy Nare, Charlene Singh and Deseree Rajpal for assisting with administration and coordination of the project. They also thank the nursing staff at the PHC facility for assistance with participant recruitment and data collection. They are grateful to all the patients who participated in the study. Funding – The research was funded by the SA Medical Research Council (grant number DUT/MH1). Disclosure statement No potential conflict of interest was reported by the authors. ORCID Firoza Haffejee   http://orcid.org/0000-0002-3908-8949 Maureen Nokuthula Sibiya    http://orcid.org/0000-0003-1220- 1478 References 1. Singh S, Sedgh G, Hussain R. Unintended pregnancy: worldwide levels, trends, and outcomes. Stud Fam Plann. 2010;41(4):241–50. https://doi.org/10.1111/sifp.2010.41.issue-4 2. Chauke L. Unwanted pregnancy-a review of contraception: clinical. Prof Nurs Today. 2007;11(1):10–4. 3. Dixit P, Ram F, Dwivedi LK. Determinants of unwanted pregnancies in India using matched case-control designs. BMC Pregnancy Childbirth. 2012;12(1):84. https://doi.org/10.1186/1471-2393-12-84 4. Ali MM, Cleland J, Shah IH. Condom use within marriage: a neglected HIV intervention. Bull W H O. 2004;82(3):180–86. 5. Font-Ribera L, Pérez G, Salvador J, et al. Socioeconomic inequalities in unintended pregnancy and abortion decision. J Urban Health. 2008;85(1):125–35. https://doi.org/10.1007/s11524-007-9233-z 6. Eliason S, Baiden F, Yankey BA, et al. Determinants of unintended pregnancies in rural Ghana. BMC Pregnancy Childbirth. 2014;14(1):261. https://doi.org/10.1186/1471-2393-14-261 7. Mayondi GK, Wirth K, Morroni C, et al. Unintended pregnancy, contraceptive use, and childbearing desires among HIV-infected and HIV-uninfected women in Botswana: across-sectional study. BMC Public Health. 2016;16(1):44. 8. Seutlwadi L, Peltzer K, Mchunu G, et al. Contraceptive use and associated factors among South African youth (18-24  years): a population-based survey. S Afr J Obstet Gynaecol. 2012;18(2):43–7. 9. Department of Health. South Africa demographic and health survey 1998. Full report: Department of Health (RSA) Pretoria. 2002. 10. Rochat TJ, Richter LM, Doll HA, et al. Depression among pregnant rural South African women undergoing HIV testing. J Am Med Assoc. 2006;295(12):1373–78. https://doi.org/10.1001/jama.295.12.1376 11. Goicolea I, San Sebastian M. Unintended pregnancy in the amazon basin of Ecuador: a multilevel analysis. Int J Equity Health. 2010;9(1):14. https://doi.org/10.1186/1475-9276-9-14 among women from peri-urban areas in South Africa.25 The high rate of unwanted pregnancies among single women is corroborated by studies in both American and other African populations 6,18,26−28 Researchers have argued that single women are more likely to engage in sexual activity for reasons other than child bearing.18 Moreover, an absence of inter-partner communication regarding pregnancy is reported to raise the risk of unintended pregnancies.27 Furthermore, this is reported to delay prenatal care.29 Our finding, that most of the women commenced prenatal care in the second semester, supports this. It must, however, be noted that traditional prenatal care programmes implemented in developed countries have been ineffective in developing countries, including South Africa, where prenatal care has been modified to the basic antenatal care approach, which requires women to report for their first antenatal visit prior to 20 weeks of gestation.30 Although bivariate analysis indicates a relationship between pregnancy intention and employment, we do not show a relationship between pregnancy intention and level of income. This is possibly due to the majority of women in the present study having a low level of income. Being single and with limited financial resources has the consequence of economic instability and thus difficulty to support a family. Furthermore, women with low income have higher rates of unintended pregnancies than those from higher income brackets and this could be related to poorer women using contraceptives infrequently and experiencing higher rates of contraceptive failure.27 Moreover, previous reports from low-income groups within the same geographic region have shown that women have difficulty in negotiating condom use with their male partners.31,32 Such difficulty will lead to infrequent condom use and thus the high level of unintended pregnancies. Our data showed no correlation between intention of pregnancy and education levels, but this may be related to the majority of the women having only some form of secondary education and nothing further. In contrast, pregnancy intention was inversely correlated with education levels in other African countries.28 Furthermore, lower levels of education are associated with increased pregnancy in single women, irrespective of the pregnancy being planned or unplanned.26 There was no relationship between pregnancy intention and contraceptive use. Over a third (36.6%) of the women reported that they thought they could not get pregnant. Thus, misconceptions regarding fertility and contraceptive use are prevalent. It is likely that contraceptive use was inconsistent as some women (19.5%; n = 64) who reported using contraceptives also provided reasons for not using them. This finding is consistent with a recent report that perceptions of low fertility lead to inconsistent contraceptive use.33 The latter report also indicates that prior sexual intercourse without pregnancy may lead to the assumption of subfertility and hence contraceptive non-use or inconsistent use.33 Previous studies have also linked unwanted pregnancies with alcohol and illicit drug use as well as cigarette smoking.23,34,35 However, this relationship was not found in the current study, possibly due to low levels of smoking (0.95%) and use of illicit drugs (1.94%) in the study population. This is consistent with other studies of South African pregnant women from the same background, which also indicated little or no substance abuse amongst these women.36 Although over a third (34.4%) of the http://orcid.org http://orcid.org/0000-0002-3908-8949 http://orcid.org http://orcid.org/0000-0003-1220-1478 http://orcid.org/0000-0003-1220-1478 Factors associated with unintended pregnancy among women attending a public health facility in KwaZulu-Natal, South Africa 5 25. Statistics South Africa. Gender statistics in South Africa 2011. Pretoria: Stats SA; 2011. 26. Musick K. Planned and unplanned childbearing among unmarried women. J Marriage Fam. 2002;64(4):915–29. https://doi.org/10.1111/ j.1741-3737.2002.00915.x 27. Finer LB, Henshaw SK. Disparities in rates of unintended pregnancy in the United States, 1994 and 2001. Perspect Sex Reprod Health. 2006;38(2):90–6. https://doi.org/10.1363/3809006 28. Palamuleni ME, Adebowale AS. Prevalence and determinants of unintended pregnancies in Malawi. Afr Population Stud. 2014;28(1):551. https://doi.org/10.11564/28-1-507 29. Dott M, Rasmussen SA, Hogue CJ, et al. Association between pregnancy intention and reproductive-health related behaviors before and after pregnancy recognition, national birth defects prevention study, 1997–2002. Matern Child Health J. 2010;14(3):373– 81. https://doi.org/10.1007/s10995-009-0458-1 30. Ngxongo TSP, Sibiya MN, Gwele NS. Experiences and views of the pregnant women regarding the Basic Antenatal Care approach to health care services provision in eThekwini district, KwaZulu-Natal. Res Rev: J Nurs Health Sci. 2016;3(1):5–14. 31. Ports KA, Haffejee F, Mosavel M, et al. Integrating cervical cancer prevention initiatives with HIV care in resource-constrained settings: a formative study in Durban, South Africa. Global Public Health. 2015;10(10):1238–51. https://doi.org/10.1080/17441692.2015.1008021 32. Haffejee F, Ports KA, Mosavel M. Knowledge and attitudes about HIV infection and prevention of mother to child transmission of HIV in an urban, low income community in Durban, South Africa: Perspectives of residents and health care volunteers. Health SA Gesondheid. 2016;21:171–78. https://doi.org/10.1016/j.hsag.2016.02.001 33. Borrero S, Nikolajski C, Steinberg JR, et al. “It just happens”: a qualitative study exploring low-income women’s perspectives on pregnancy intention and planning. Contraception. 2015;91(2):150–56. https://doi.org/10.1016/j.contraception.2014.09.014 34. Naimi TS, Lipscomb LE, Brewer RD, et al. Binge drinking in the preconception period and the risk of unintended pregnancy: implications for women and their children. Pediatrics. 2003;111(Supplement 1):1136– 41. 35. Seggie J. Alcohol and South Africa’s youth. S Afr Med J. 2012;102(7):587. https://doi.org/10.7196/SAMJ.6003 36. Haffejee F, Naicker T, Singh M, et al. Placental leptin in HIV-associated preeclampsia. Eur J Obstet Gynecol Reprod Biol. 2013;171(2):271–76. https://doi.org/10.1016/j.ejogrb.2013.09.027 Received: 15-08-2017 Accepted: 22-10-2017 12. Glasier A, Gülmezoglu AM, Schmid GP, et al. Sexual and reproductive health: a matter of life and death. The Lancet. 2006;368(9547):1595– 1607. https://doi.org/10.1016/S0140-6736(06)69478-6 13. Rosenfeld JA, Everett KD. Factors related to planned and unplanned pregnancies. J Fam Pract. 1996;43(2):161–67. 14. Amin Shokravi F, Howden Chapman P, Peyman N. Comparison study: risk factors of unplanned pregnancies in a Group of Iranian and New Zealander Women. Eur J Sci Res. 2009;26(1):108–21. 15. Cheng D, Schwarz EB, Douglas E, et al. Unintended pregnancy and associated maternal preconception, prenatal and postpartum behaviors. Contraception. 2009;79(3):194–98. https://doi. org/10.1016/j.contraception.2008.09.009 16. Khajehpour M, Simbar M, Jannesari S, et al. Health status of women with intended and unintended pregnancies. Public Health. 2013;127(1):58–64. https://doi.org/10.1016/j.puhe.2012.08.011 17. Kamal SM, Islam MA. Interspousal communication on family planning and its effect on contraceptive adoption in Bangladesh. Asia Pac J Public Health. 2012;24(3):506–21.https://doi.org/10.1177/1010539511399118 18. Exavery A, Kanté AM, Njozi M, et al. Predictors of mistimed, and unwanted pregnancies among women of childbearing age in Rufiji, Kilombero, and Ulanga districts of Tanzania. Reprod Health. 2014;11(1):63. https://doi.org/10.1186/1742-4755-11-63 19. O’Leary CM, Bower C. Guidelines for pregnancy: what’s an acceptable risk, and how is the evidence (finally) shaping up? Drug Alcohol Rev. 2012;31(2):170–83. https://doi.org/10.1111/dar.2012.31.issue-2 20. Reardon DC, Coleman PK, Cougle JR. Substance use associated with unintended pregnancy outcomes in the national longitudinal survey of youth. The Am J Drug Alcohol Abuse. 2004;30(2):369–83. https://doi.org/10.1081/ADA-120037383 21. Napier C, Oldewage-Theron W, Kearney J. Comparison of three school feeding strategies for primary school children in an informal settlement in Gauteng, South Africa. Health SA Gesondheid. 2009;14(1):1–8. 22. Joubert G, Ehrlich R, Katzenellenbogen J, et al. Epidemiology: a research manual for South Africa. Cape Town: Oxford University Press Southern Africa; 2007. 23. Orr ST, James SA, Reiter JP. Unintended pregnancy and prenatal behaviors among urban, black women in Baltimore, Maryland: the Baltimore preterm birth study. Ann Epidemiol. 2008;18(7):545–51. https://doi.org/10.1016/j.annepidem.2008.03.005 24. Qian X, Tang S, Garner P. Unintended pregnancy and induced abortion among unmarried women in China: a systematic review. BMC Health Serv Res. 2004;4(1):1. https://doi.org/10.1186/1472-6963-4-1 Introduction Methods Statistical analysis Results Discussion Funding – Disclosure statement References