Dzomeku et al. BMC Pregnancy Childbirth (2021) 21:518 https://doi.org/10.1186/s12884-021-03989-x RESEARCH Open Access Prevalence, progress, and social inequalities of home deliveries in Ghana from 2006 to 2018: insights from the multiple indicator cluster surveys Veronica Millicent Dzomeku1, Precious Adade Duodu2, Joshua Okyere3, Livingstone Aduse‑Poku4, Nutifafa Eugene Yaw Dey5, Adwoa Bemah Boamah Mensah1, Emmanuel Kweku Nakua6, Pascal Agbadi1 and Jerry John Nutor7* Abstract Background: Delivery in unsafe and unsupervised conditions is common in developing countries including Ghana. Over the years, the Government of Ghana has attempted to improve maternal and child healthcare services including the reduction of home deliveries through programs such as fee waiver for delivery in 2003, abolishment of delivery care cost in 2005, and the introduction of the National Health Insurance Scheme in 2005. Though these efforts have yielded some results, home delivery is still an issue of great concern in Ghana. Therefore, the aim of the present study was to identify the risk factors that are consistently associated with home deliveries in Ghana between 2006 and 2017–18. Methods: The study relied on datasets from three waves (2006, 2011, and 2017–18) of the Ghana Multiple Indicator Cluster surveys (GMICS). Summary statistics were used to describe the sample. The survey design of the GMICS was accounted for using the ‘svyset’ command in STATA‑14 before the association tests. Robust Poisson regression was used to estimate the relationship between sociodemographic factors and home deliveries in Ghana in both bivariate and multivariable models. Results: The proportion of women who give birth at home during the period under consideration has decreased. The proportion of home deliveries has reduced from 50.56% in 2006 to 21.37% in 2017–18. In the multivariable model, women who had less than eight antenatal care visits, as well as those who dwelt in households with decreas‑ ing wealth, rural areas of residence, were consistently at risk of delivering in the home throughout the three data waves. Residing in the Upper East region was associated with a lower likelihood of delivering at home. Conclusion: Policies should target the at‑risk‑women to achieve complete reduction in home deliveries. Access to facility‑based deliveries should be expanded to ensure that the expansion measures are pro‑poor, pro‑rural, and pro‑ uneducated. Innovative measures such as mobile antenatal care programs should be organized in every community in the population segments that were consistently choosing home deliveries over facility‑based deliveries. *Correspondence: Jerry.Nutor@ucsf.edu 7 Department of Family Health Care Nursing, School of Nursing, University of California San Francisco, San Francisco, CA, USA Full list of author information is available at the end of the article © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat ivecom mons.o rg/ licens es/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Dzomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 2 of 12 Keywords: Prenatal care, Antenatal care, Pregnancy, Skilled birth attendance Introduction interventions to reduce Ghana’s maternal mortality ratio Improving the maternal health of women is essential to (MMR) which currently stands at 310 per 100,000 live their overall health and wellbeing. Evidence shows that births and are largely attributable to inadequate access about 140 million women give birth per annum, with to quality skilled delivery, emergency obstetric, and about 810 to 890 dying daily as a result of preventable newborn care and family planning [15]. Ghana’s MMR causes related to pregnancy and childbirth [1, 2], and is still very high compared to the global target of less sub-Saharan Africa (SSA) alone accounts for about two- than 70 per 100,000 live births by 2030 [4], and therefore thirds of all these maternal deaths [3]. Consequently, the implementation of policy interventions including several efforts have been coordinated by international an improved shift from home deliveries to IBD is criti- organizations and individual governments to significantly cal. Reports on Ghana’s regional trend in skilled delivery reduce maternal mortality to under 70 deaths per 100,000 from 2014 to 2016 indicate that Upper East Region and live births by 2030, as a global target set by the Sustain- Volta Region consistently recorded the highest and low- able Development Goal three (SDG 3.1) [2, 4]. One of est skilled delivery coverage over the 3 years, respectively such efforts has been the global campaign to reduce [14]. Ghana has made substantial progress to reduce the home deliveries and increase institutional birth deliveries prevalence of home deliveries by reducing some social (IBD) towards skilled birth attendance (SBA), a critical inequalities through the introduction of the Commu- benchmark indicator for monitoring the progress of the nity-based Health Planning and Services (CHPS) initia- Millennium Development Goal five (MDG 5) as well as tive, and the free maternal health care policy through the the new SDG 3 and with a 90% global target [4]. This has National Health Insurance Scheme (NHIS) in 2005 [16, seen an increase in IBD from as low as 5% in 2005 to 48% 17]. These initiatives contributed significantly to reduc- in 2019 [1]. Home delivery refers to the practice of child- ing home delivery from 45% in 2007 to 20% in 2017 [18]. birth that occurs at the place of residence of the pregnant Despite the significant concerted global and national woman or the homes of other people [5, 6]. These births efforts, uptake of IBD remains low, with many childbear- are attended by unskilled personnel including traditional ing women continuing to deliver their babies at home due birth attendants (TBAs), relatives, and friends as sub- to limited access to maternal healthcare services includ- stitutes for skilled birth attendants [5, 7]. A skilled birth ing delivery services [7, 19, 20]. Hence, there is a need to attendant is “an accredited health professional – such estimate the prevalence and explore the nuances associ- as a midwife, doctor or nurse – who has been educated ated with home delivery. and trained to proficiency in the skills needed to man- Available global evidence indicates that women’s deci- age normal (uncomplicated) pregnancies, childbirth, and sions to deliver at home or at a health institution is the immediate postnatal period, and in the identification, influenced by prevailing social inequalities, and these management and referral of complications in women substantial inequalities have the greatest burden among and newborns” [8]. Home delivery continues to gain the poor and lower social strata [21, 22]. Social inequali- considerable attention due to its strong association with ties manifesting in the dimensions of education, wealth higher neonatal and maternal mortalities arising from quintile, place of residence, distance to the health facil- concomitant obstetric complications such as sepsis, peri- ity, among others have been posited to influence the partum cardiomyopathy, embolism, haemorrhage, as well prevalence and progress to reduce home deliveries [23]. as other obstetric dangers [9–11]. Other reported risks In Ghana, previous studies report that social inequali- for home delivery include abandonment of the recom- ties such as rural residency, poor wealth status, no for- mended practices of colostrum provision and breastfeed- mal education, not being covered by the national health ing, deserting the child and mother’s immunizations and insurance scheme, and male-headed households exacer- nutrition supplementation, and lack of check-up for the bate home deliveries in the country [5, 24–26]. However, child and mother postnatally [12, 13]. to the best of our knowledge, no study has investigated Ghana, an SSA country, has a national SBA target of the progress that has been made in reducing home deliv- 80% towards shifting the paradigm from home deliveries ery over the years as well as examine the magnitude of to IBD [14]. In 2016, the proportion of births or deliver- the social inequalities relating to home delivery in Ghana. ies by skilled birth attendants was 56.2%, and this was Therefore, this study sought to fill the dearth in litera- significantly below the national target [14]. The national ture by examining the prevalence, progress and social SBA target is part of the maternal and child health inequalities associated with home deliveries from 2006 to D zomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 3 of 12 2018 using data from the Multiple Indicator Cluster Sur- post” and “Other public”); Private medical sector (“Pri- vey (MICS). The study findings will inform policy inter- vate hospital”, “Private Clinic”, “Private maternity home” ventions towards attaining both the national and global and “Other private medical”); and Other. We assigned a targets regarding maternal and child health. value of “1” to the home response and all other options were assigned “0”. Methods Data and collection procedure Explanatory variables The current study used datasets collected in three waves The explanatory variables in the models were selected by the Ghana Multiple Indicator Cluster Survey (GMICS) after a review of the literature and their availability in the in 2006, 2011, and 2017/2018. The GMICS is a cross- dataset [28–30]. The authors explored the following vari- sectional survey conducted by Ghana Statistical Service ables: age of woman, education, polygyny, wanted last- (GSS) in collaboration with the Ghana Health Service child, parity, antenatal care (ANC) attendance, previous (GHS), Ministry of Health (MOH), and the Ministry of child loss experience, health insurance, household wealth Education [27]. The survey received funding and tech- index, urban–rural residence, and region of residence. nical support from the United Nations International The ANC variable was recoded as 0–3 times (less than Children’s Emergency Fund (UNICEF) and other interna- 3), 4–7 times, and 8 times and above. It would have been tional donors [27]. The primary goal of the MICS surveys helpful to compare women who did not attend ANC at all is to analyze key indicators that assist countries to pro- with the other categories, but data on ANC attendance duce data for use in national development plans, policies, in 2006 revealed that only one woman indicated she did and programmes. On top of that, the GMICS is intended not have an ANC visit. Therefore, to make ANC effect to assess progress towards SDGs and other agreements on Home delivery comparable over time, we decided to signed internationally [27]. group those with no ANC attendance with those who had MICS surveys use a multi-stage stratified cluster design 1 up to 3 visits. We included the variable on respondent’s to select a probability sample of households and women previous child loss experience in our models to ascertain (15–49 years). This approach was used to nationally sur- its association with giving birth to their children in the vey women in urban and rural areas from the erstwhile home. It is not clear from the dataset or the question- ten administrative regions in Ghana namely, Western, naire whether the experience of child loss occurred in a Central, Greater Accra, Volta, Eastern, Ashanti, Brong health facility or the home or any other place. Ahafo, Northern, Upper East, and Upper West. At the All these variables were available in all three datasets first stage based on the 2010 Population and Housing except that of health insurance which was available in Census (PHC) of Ghana, enumeration areas (EAs) were 2011 and 2017/2018; we included this variable because of randomly selected, becoming the primary sampling units its policy implication on maternal and child health. We (PSUs). Every household within the EA is listed to create did not include in our model the variable on religious a sampling frame and a sample of households was chosen affiliations of the respondents because it had no data on it in the second stage using systematic random sampling. in the most recent GMICS dataset (the 2017/18 dataset). Then reproductive-aged women were recruited from As indicated in Table 1, participants responded to all the these selected households. A total of 7,795 women within variables using simple response options. the ages of 15 to 49  years who had delivered two years before the data collection for all the three waves partici- Data preparation and analysis pated in this study. The datasets were cleaned, and variables recoded in STATA version 14. We accounted for survey weights for Measures the differential probability selection of the sample. The Outcome variable variances were calculated to adjust for clustering, strati- The outcome variable is the place of delivery, therefore fication, and design effects using the Taylor lineariza- home delivery is the focal point for the present study. tion technique [31]. We first conducted specific survey This variable was derived from the survey question ask- waves (2006, 2011, and 2017–18) univariates analyses, ing the participants about the place of their child delivery computing frequencies and percentages of all variables two years before the start of the survey. Participants were (Table  1—second, fifth, and eighth columns). Secondly, specifically asked this question, “Where did you give birth bivariate analyses were performed with Chi-square test to (name of child)?” The response format to this ques- of independence, estimating the relationship between tion were these: Home (“respondent’s home” and “other’s the explanatory variables and outcome variable (place home”); Public medical sector (“Government hospital”, of delivery – home or facility delivery) as presented in “Government clinic/health centre”, “Government health Table 1. Lastly, multivariate analyses with robust Poisson Dzomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 4 of 12 Table 1 Summary statistics of sociodemographic correlates and home deliveries in Ghana, 2006 to 2017–18 2006 2011 2017–18 Delivered at home Delivered at home Delivered at home n (%) NO YES N NO YES n% NO YES Total 1456 (100) 49.44 50.56 2873 (100) 68.65 31.35 3466 (100) 78.63 21.37 Age (years) P = 0.560 P ≤ 0.005 P = 0.300 15–24 433 (29.73) 47.72 52.28 705 (24.53) 69.35 30.65 952 (27.47) 78.36 21.64 25–34 693 (47.60) 51.45 48.55 1436 (49.97) 71.60 28.40 1634 (47.16) 79.10 20.90 35 + 330 (22.67) 47.45 52.55 733 (25.50) 62.18 37.35 879 (25.37) 78.03 21.97 Education P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 None or pre‑primary 537 (36.87) 30.76 69.24 833 (29.00) 43.48 56.52 774 (22.34) 67.24 32.76 Primary 320 (21.98) 46.56 53.44 642 (22.34) 67.24 32.76 729 (21.02) 72.97 27.03 JHS 496 (34.05) 63.99 36.01 1007 (35.04) 80.01 19.99 1341 (38.70) 81.02 18.98 Secondary and above 103 (7.09) 85.58 14.42 391 (13.62) 95.33 4.67 622 (17.94) 94.28 5.72 Polygyny P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 Never/ formerly married 165 (11.33) 59.24 40.76 293 (10.19) 75.05 24.95 592 (17.08) 77.61 22.39 In one union 1,027 (70.52) 51.36 48.64 2112 (73.52) 72.01 27.99 2331 (67.25) 81.27 18.73 Have co‑wives 264 (18.14) 35.85 64.15 468 (16.29) 49.47 50.53 543 (15.66) 68.37 31.63 Wanted last-child P = 0.060 P = 0.107 P = 0.109 Yes 884 (60.74) 51.34 48.66 1630 (56.74) 69.30 30.70 1711 (49.37) 79.75 20.25 Later/No More/others 572 (39.26) 46.50 53.50 1243 (43.26) 67.79 32.21 1755 (50.63) 77.53 22.47 Parity P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 Primiparous 321 (22.04) 62.47 37.53 619 (21.54) 86.73 13.27 791 (22.82) 84.60 15.40 Double 301 (20.65) 55.34 44.66 527 (18.33) 72.72 27.28 660 (19.05) 81.63 18.37 Multiparous 834 (57.30) 42.30 57.70 1727 (60.13) 60.93 39.07 2015 (58.13) 75.29 24.71 ANC attendance P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 less than 4 times 389 (26.71) 25.26 74.74 384 (13.38) 32.89 67.11 519 (14.98) 51.66 48.37 4–7 times 717 (49.23) 50.75 49.25 1436 (49.98) 66.55 33.45 2031 (58.61) 80.60 19.40 8 times and more 350 (24.06) 73.58 26.42 1053 (36.64) 84.57 15.43 915 (26.41) 89.55 10.45 Previous child loss experience P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 No 1085 (74.51) 52.09 47.91 2186 (76.08) 72.07 27.93 2849 (82.20) 79.85 20.15 Yes 371 (25.49) 41.68 58.32 687 (23.92) 57.75 42.25 617 (17.80) 72.99 27.01 Health Insurance P ≤ 0.001 P ≤ 0.001 Uninsured — — — 773 (26.89) 55.51 44.49 1311 (37.82) 69.11 30.89 Insured — — — 2100 (73.11) 73.48 26.52 2155 (62.18) 84.41 15.59 Household wealth P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 Poorest 335 (23.00) 22.88 77.12 637 (22.16) 38.92 61.08 747 (21.55) 63.17 36.83 Poorer 347 (23.86) 32.34 67.66 621 (21.61) 58.68 41.32 694 (20.03) 70.95 29.05 Middle 277 (19.04) 45.78 54.22 568 (19.79) 70.60 29.40 676 (19.51) 77.67 22.33 Richer 286 (19.61) 74.70 25.30 517 (17.98) 85.53 14.47 709 (20.45) 87.04 12.96 Richest 211 (14.50) 90.33 9.67 530 (18.46) 97.48 2.52 640 (18.46) 96.69 3.31 Urban–Rural residence P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 Urban 498 (34.21) 77.76 22.24 1214 (42.25) 88.01 11.99 1464 (42.25) 90.17 9.83 Rural 958 (65.79) 34.71 65.29 1659 (57.75) 54.48 45.52 2002 (57.75) 70.18 29.82 Region P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 Western 154 (10.60) 39.41 60.59 306 (10.66) 63.15 36.85 400 (11.53) 78.98 21.02 Central 112 (7.70) 47.25 52.75 279 (9.72) 63.81 36.19 341 (9.83) 74.75 25.25 Greater Accra 177 (12.16) 83.70 16.30 451 (15.71) 89.16 10.84 332 (9.58) 93.21 6.79 Volta 103 (7.10) 43.55 58.48 214 (7.46) 64.35 35.65 285 (8.23) 68.59 31.41 Eastern 195 (13.37) 41.52 58.48 327 (11.37) 78.58 21.42 402 (11.60) 78.56 21.44 Ashanti 222 (15.22) 59.65 40.35 511 (17.78) 75.78 24.22 788 (22.73) 81.72 18.28 D zomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 5 of 12 Table 1 (continued) 2006 2011 2017–18 Delivered at home Delivered at home Delivered at home n (%) NO YES N NO YES n% NO YES Brong Ahafo 115 (7.87) 57.23 42.77 258 (8.99) 62.10 37.90 330 (9.51) 86.64 13.36 Northern 278 (19.10) 34.62 65.38 321 (11.17) 38.51 61.49 388 (11.19) 58.33 41.67 Upper East 61 (4.16) 43.60 56.40 120 (4.17) 66.45 33.55 112 (3.25) 94.93 5.07 Upper West 40 (2.72) 29.08 70.92 85 (2.97) 62.13 37.87 88 (2.55) 80.77 19.23 regression models incorporating all explanatory variables has reduced from 50.56% in 2006 to 21.37% in 2017–18 were used to model the prevalence of home delivery as (Table  1). The following sociodemographic factors were well as examine its relationship, regardless of statisti- consistently associated with home deliveries in Ghana at cal significance in the bivariate analyses as presented in a significant threshold of P ≤ 0.001: education, polygyny, Table 2. Because Poisson regression is applied to a binary parity, antenatal care (ANC) attendance, previous child variable, the robust error variance technique is used to loss experience, health insurance, household wealth, avoid overestimating the error of the estimated preva- urban–rural residence, and region of residence (Table 1). lence ratio (PR). The preference for prevalence ratio over The proportion of childbearing women who gave birth odds ratio is adequately explained elsewhere [32, 33], and to their children in their homes in these disadvantaged the same thing applies to our study. The prevalence ratio population segments (rural, poor households, none or and the adjusted prevalence ratio are reported. low formal education) was consistently higher than the national average and their colleagues in advantaged pop- OR PR = ulation groups (Table 1): residing in a rural area [65.29% (1+ p1 ∗ [OR− 1]) in 2006; 45.52% in 2011; 29.82% in 2017] (Fig. 1), resid- where p 1 is the prevalence of delivery at home. ing in the poorest household [77.1 2% in 2006; 61.08% in We repeated these processes for all the three survey 2011; 36.83% in 2017] (Fig.  1), and women without for- waves used in this study. Statistical significance is deter- mal education [69.24% in 2006;56.52% in 2011; 32.76% in mined using 95% confidence intervals (CIs) and an alpha 2017] (Fig. 1). Of the wome who gave birth to children at value of 0.05. home, higher proportion of them had the following soci- odemographic characteristics: women who had co-wives [64.15% in 2006; 50.53% in 2011; 31.63% in 2017], women Ethics approval and data availability who had three or more children [57.70% in 2006; 39.07% The study was performed in accordance with the Dec- in 2011; 24.71% in 2017], less than 4 times ANC attend- laration of Helsinki and approved by appropriate ethics ance [74.74% in 2006; 67.11% in 2011; 48.37% in 2017] committee. Trained field enumerators collected data on (Fig.  1), women who have ever had child loss expere- behalf of UNICEF and GSS. The MICS team of UNICEF- ince before their recent child [58.32% in 2006; 42.25% in Ghana, the Ethical Review Board of the Ghana Health 2011; 27.01% in 2017], women without health insurance Service, and the Ghana Statistical Service approved the [44.49% in 2011; 30.89% in 2017], and residing in the study. Informed consent was obtained from all respond- Volta [58.48% in 2006; 35.65% in 2011; 31.41% in 2017] ents, and assent was obtained for respondents younger and Northern [65.38% in 2006; 61.49% in 2011; 41.67% in than eighteen from parents/guardians/adult household 2017] regions. member before data collection. More details regarding the data and ethical standards are available at: https:// Sociodemographic correlates regressed on home mics.u nicef.o rg/s urve ys. Therefore, ethics approval for deliveries in Ghana, 2006 to 2017–2018 this study was not required since the data is secondary In the multivariable model, ANC attendance, house- and is available in the public domain. hold wealth, urban–rural residence, and region of resi- dence were consistently associated with home deliveries Results throughout the three data waves (Table 2; Fig. 1). We also Summary statistics of sociodemographic correlates highlighted the policy relevance of factors (such as for- and home deliveries in Ghana, 2006 to 2017–18 mal education and having health insurance) that were Generally, the proportion of women who give birth at significantly associated with home deliveries in the last home has decreased. The proportion of home deliveries two recent data waves (Table  2). Beyond indicating the Dzomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 6 of 12 Table 2 Sociodemographic correlates regressed on home deliveries in Ghana, 2006 to 2017–2018 2006 2011 2017–18 PR [95% CI] APR [95% CI] PR [95% CI] APR [95% CI] PR [95% CI] APR [95% CI] Total Age (years) 15–24 0.995 1.242* 0.810* 1.333* 0.985 1.036 [0.843,1.174] [1.038,1.486] [0.660,0.994] [1.054,1.685] [0.774,1.253] [0.774,1.386] 25–34 0.924 1.100 0.751*** 1.040 0.951 1.112 [0.796,1.072] [0.976,1.238] [0.633,0.890] [0.893,1.211] [0.764,1.183] [0.900,1.374] 35 + Ref Ref Ref Ref Ref Ref Education None or pre‑primary 4.802*** 1.677 12.11*** 2.131** 5.724*** 1.786* [2.644,8.723] [0.993,2.832] [6.998,20.95] [1.216,3.736] [3.465,9.457] [1.070,2.982] Primary 3.706*** 1.462 7.018*** 1.671 4.724*** 1.782* [2.032,6.759] [0.868,2.463] [4.006,12.30] [0.960,2.908] [2.852,7.824] [1.061,2.994] JHS 2.498** 1.251 4.284*** 1.461 3.317*** 1.705* [1.379,4.525] [0.759,2.061] [2.411,7.609] [0.830,2.573] [2.075,5.303] [1.039,2.800] Secondary and above Ref Ref Ref Ref Ref Ref Polygyny Never/formerly married Ref Ref Ref Ref Ref Ref In one union 1.193 1.119 1.122 0.876 0.837 0.889 [0.937,1.520] [0.908,1.379] [0.841,1.497] [0.686,1.117] [0.645,1.086] [0.670,1.180] Have co‑wives 1.574*** 1.201 2.025*** 0.943 1.413* 1.051 [1.209,2.049] [0.942,1.531] [1.488,2.756] [0.715,1.244] [1.032,1.934] [0.758,1.457] Wanted last child Yes Ref Ref Ref Ref Ref Ref Later/No More/others 1.099 1.042 1.049 1.119 1.109 1.045 [0.966,1.252] [0.932,1.166] [0.904,1.218] [0.975,1.285] [0.935,1.316] [0.886,1.232] Parity Primiparous Ref Ref Ref Ref Ref Ref Double 1.190 1.337** 2.056*** 1.832*** 1.193 1.242 [0.960,1.475] [1.103,1.621] [1.526,2.771] [1.384,2.426] [0.900,1.582] [0.941,1.641] Multiparous 1.537*** 1.398** 2.945*** 2.263*** 1.604*** 1.231 [1.279,1.848] [1.139,1.717] [2.263,3.833] [1.684,3.042] [1.239,2.078] [0.907,1.670] ANC attendance less than 4 times 2.829*** 1.605*** 4.349*** 1.767*** 4.626*** 2.443*** [2.226,3.594] [1.322,1.950] [3.472,5.447] [1.412,2.211] [3.480,6.149] [1.808,3.301] 4–7 times 1.864*** 1.291** 2.167*** 1.294* 1.857*** 1.302* [1.466,2.370] [1.077,1.547] [1.753,2.679] [1.057,1.583] [1.418,2.430] [1.001,1.692] 8 times and more Ref Ref Ref Ref Ref Ref Previous child loss experience No Ref Ref Ref Ref Ref Ref Yes 1.217*** 0.936 1.513*** 0.957 1.340* 1.049 [1.091,1.359] [0.841,1.040] [1.302,1.758] [0.830,1.104] [1.055,1.702] [0.864,1.272] Health Insurance Uninsured — — 1.678*** 1.161* 1.981*** 1.517*** [1.430,1.968] [1.017,1.325] [1.643,2.390] [1.283,1.794] Insured — — Ref Ref Ref Ref Household wealth Poorest 7.974*** 3.441*** 24.26*** 6.689*** 11.12*** 4.240*** [4.873,13.05] [1.967,6.016] [10.24,57.46] [2.376,18.83] [6.076,20.34] [2.248,7.999] Poorer 6.997*** 3.254*** 16.41*** 5.703*** 8.768*** 3.617*** [4.240,11.55] [1.858,5.700] [6.826,39.44] [2.060,15.79] [4.810,15.98] [1.950,6.707] Middle 5.606*** 3.077*** 11.67*** 5.505** 6.740*** 3.222*** [3.329,9.439] [1.742,5.434] [4.789,28.46] [1.995,15.19] [3.671,12.37] [1.697,6.118] D zomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 7 of 12 Table 2 (continued) 2006 2011 2017–18 PR [95% CI] APR [95% CI] PR [95% CI] APR [95% CI] PR [95% CI] APR [95% CI] Richer 2.616*** 1.908* 5.747*** 3.303* 3.913*** 2.509** [1.506,4.545] [1.097,3.319] [2.273,14.53] [1.217,8.962] [2.061,7.428] [1.298,4.850] Richest Ref Ref Ref Ref Ref Ref Urban–Rural residence Urban Ref Ref Ref Ref Ref Ref Rural 2.935*** 1.504** 3.796*** 1.846*** 3.033*** 1.670** [2.252,3.826] [1.174,1.928] [2.939,4.903] [1.428,2.387] [2.137,4.305] [1.205,2.314] Region Western 3.717*** 1.491 3.401*** 0.940 3.094** 1.683 [2.162,6.388] [0.984,2.261] [1.803,6.414] [0.619,1.428] [1.482,6.460] [0.756,3.750] Central 3.236*** 1.336 3.339*** 1.186 3.717*** 2.040 [1.873,5.590] [0.811,2.201] [1.794,6.217] [0.821,1.715] [1.790,7.717] [0.922,4.515] Greater Accra Ref Ref Ref Ref Ref Ref Volta 3.462*** 1.198 3.290*** 0.958 4.625*** 1.699 [2.016,5.947] [0.781,1.839] [1.693,6.392] [0.609,1.508] [2.277,9.393] [0.778,3.711] Eastern 3.587*** 1.307 1.976 0.836 3.157** 1.489 [2.118,6.076] [0.856,1.995] [0.977,3.999] [0.517,1.352] [1.528,6.523] [0.667,3.322] Ashanti 2.475** 1.244 2.235* 0.851 2.691* 1.712 [1.401,4.373] [0.803,1.926] [1.175,4.250] [0.553,1.311] [1.249,5.801] [0.750,3.905] Brong Ahafo 2.624** 1.088 3.498*** 0.908 1.968 0.984 [1.439,4.783] [0.681,1.736] [1.831,6.683] [0.616,1.337] [0.867,4.464] [0.419,2.309] Northern 4.010*** 1.232 5.674*** 1.094 6.135*** 2.087 [2.316,6.945] [0.795,1.908] [3.109,10.36] [0.751,1.593] [3.065,12.28] [0.948,4.597] Upper East 3.459*** 1.143 3.096*** 0.633* 0.747 0.329* [1.973,6.066] [0.731,1.787] [1.650,5.807] [0.419,0.958] [0.311,1.792] [0.125,0.865] Upper West 4.350*** 1.273 3.494*** 0.746 2.831** 1.022 [2.568,7.371] [0.823,1.970] [1.872,6.522] [0.498,1.118] [1.326,6.044] [0.440,2.373] Model details Number of strata 20 20 20 Number of Primary Sampling Unit 291 775 649 Number of Observations 1456 2873 3466 Exponentiated coefficients; 95% confidence intervals in brackets * p < 0.05, ** p < 0.01, *** p < 0.001 consistent risk factors of home deliveries, we interpreted likely to deliver at home compared to their urban coun- the significantly adjusted prevalence ratios of the 2017– terparts (Table 2). 18 dataset given that it represents current risk factors of home deliveries in Ghana (Table 2). Women with no edu- Discussion cation or pre-primary education, primary and junior high Findings from our study suggest that home deliveries school education were more likely to deliver at home in Ghana have been decreasing in the past few years. compared those with secondary school or higher educa- The proportion of women who delivered at home were tion. Generally, there is a decreasing trend of delivery at 50.56% in 2006, 31.35% in 2011, and 21.37% in 2017– home with increasing level of education. Also, women 2018. However, women who had less than eight ANC vis- who attended ANC 4–7 times, or less than 4 times were its, dwelt in households with decreasing wealth, lived in more likely to deliver at home compared with those with the rural area, and resides in the Upper East region (in 8 or more ANC attendance, Furthermore, women with- 2011 and 2017–18) were consistently at risk of delivering out health insurance subscription (compared to health in the home throughout the three data waves. This sug- insured women) and women in the richer or middle or gest that the location of the woman and social status are poorer or poorest households (compared to women in significant factors in the choice of a place for delivery. the richest households) were more likely to deliver at The home delivery prevalence reported in our study home. Finally, women in rural settlements were more is consistent with that of 2015 Ghana Health Service Dzomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 8 of 12 Fig. 1 Trend graphs of sociodemographic disparities in home deliveries in Ghana, 2006 to 2017–18. Trend graphs showing consistent correlates of home deliveries in Ghana, 2006–2017‑18 statistics, and the findings of Ganle and colleagues and development partners need to invest more in edu- (2019) who found that about a quarter of women cational opportunities and expand the current Free still deliver at home in Ghana [34, 35]. The need for Secondary School policy. improvement in access to healthcare in Ghana is Results from this study suggest that though supervised imperative. The Government of Ghana, like many deliveries are expected to be affordable and, in most governments of other developing countries, have rec- cases, free in Ghana, several geographic, health system, ognized that delivery in unsafe and unsupervised con- and socio-demographic factors, prevent women from ditions is common in the country [34]. The Therefore, utilizing these services. From our study, ANC attendance over the years, the Government of Ghana has initiated was among the factors that were consistently associated several programs to improve maternal healthcare ser- with home deliveries across the years. The prevalence vices including reduction of home deliveries through rate of home deliveries for women who attended ANC programs such as fee waiver for delivery in 2003, abol- less than 4 times was almost three times as high as that ishment of delivery care cost in 2005, and the introduc- of those who attended ANC 8 times or more. The find- tion of the National Health Insurance Scheme in 2005. ing is consistent with that of other studies done in Ghana Though these efforts have yielded some results, our [39, 40]. ANC has been reported to be a determinant of results and other statistics revealed that home delivery whether pregnant women will deliver within health facili- is still an issue of great concern in Ghana [36]. Consist- ties in Ghana [24]. Expectant mothers who are informed ently, women from disadvantaged groups (such as rural, about pregnancy complications are more likely to deliver uneducated, households with lower socioeconomic sta- in healthcare facilities compared to uninformed preg- tus, and those from Upper East) had higher proportions nant women according to previous studies conducted of home deliveries compared to the national average. in Tanzania and Bangladesh [41, 42]. Education dur- Women with no formal education or below secondary ing ANC helps allay fears or the perception women level education were more likely to deliver at home. may have towards facility or supervised delivery. Super- This is because women with little or no education may vised deliveries within health facilities provide women not be adequately informed about the risks associated with information on the risks and complications they with home births [37, 38]. This is consistent with pre- may encounter during labour and delivery. The World vious studies conducted in Ghana [5]. The government Health Organization’s decision to recommend eight ANC D zomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 9 of 12 contacts instead of at least four contacts may have been 2002, the free maternal health policy, and the National influenced by these factors [43]. Risk assessment and Health Insurance Scheme (NHIS) in a bid to improve medical examinations during ANC lead to early recog- access to maternal healthcare. Under the Ghana National nition of complications that may arise during and after Health Insurance Scheme policy, all pregnant women delivery. Counselling and advice during ANC sessions on may enrol without paying the required premium. This the need to seek supervised delivery positively influence has obviously improved access to maternal and childcare women’s decision to deliver within health facilities [44]. in Ghana. However, some women refuse to enrol in the Other studies, however, have found that increased ANC scheme with the view that they may be made to pay addi- visits may lead to a rise in the probability of home deliv- tional money when they utilize supervised deliveries in eries by expectant mothers [40]. health facilities. Previous studies have reported evidence Though the reduction in home deliveries over the past of informal payments at the hospital despite enrolment few years has been well documented, findings from our in the NHIS [53, 54]. This trend worsens the already dire study and other studies [45] suggest that there are rural– situation for poorer women without health insurance. urban differences. We found that 29.82% of women resid- Based on our study findings we recommend that birth ing in rural areas delivered at home compared to 9.83% plan should include recognition of danger signs, a plan of women living in urban areas in 2017–2018. Though for place of delivery, and a plan for a skilled birth atten- the percentage of rural women who delivered at home dant. Also, efforts should be made to identify women decreased from 2006 (65.29%) to 2018 (29.82%), it is still who are not likely to receive skilled supervision in health a far cry for home deliveries for urban women. This is facilities during ANC. Reasons for their potential refusal consistent with the findings of studies from other African should be ascertained, and adequate support in terms countries such as Nigeria [46], Tanzania [47], and Ethio- of assistance with transportation to health facilities, fol- pia [48]. In 2015, the Ghana Statistical Services reported low-up, purposeful home visits, and counselling should a 59% versus 90% home deliveries in rural and urban be given to these women. Given the low prevalence rate areas in Ghana respectively [35]. The huge percentage of of supervised deliveries in rural areas, efforts should be home deliveries among rural women is a major concern made to increase the number of health facilities, improve for the realization of the Sustainable Development Goals rural health services, enhance the quality of road net- (SDGs) for reducing deaths among mothers and infants works linking urban and rural areas, and referral sys- globally. The disparity in the number of health facilities tems in rural areas. Also, to expand access to maternal in rural and urban areas in Ghana leads to a difference health services in rural areas, telehealth and telemedicine in accessibility to maternal health services, referrals, and can be utilized. Telehealth can take the form of remote specialist facilities. Also, the regions of the country with patient monitoring, storage and transmission of medical more rural areas especially the Upper East Region had information, and mobile health communication. The use greater prevalence rate of home deliveries compared to of telehealth can reduce the burdens patients encoun- the more urban regions like Greater Accra region and ter such as traveling for specialty care. Telehealth can Ashanti region. The regions with more rural areas have improve monitoring, communication, and timeliness of the most people with lower levels of education, low deliveries [55]. Barriers to access to supervised deliveries income, and beliefs that hinder them from accessing in rural areas can be addressed by creating awareness on supervised deliveries. One of such beliefs is the percep- negative beliefs and traditions that may influence mater- tion that traditional birth attendants (TBAs) provided nal health. In addition, the free maternal health policy better care than the care given by skilled health profes- should be expanded to cover most medical supplies sionals. This has been reported by various studies [41, 49, and services to reduce the financial burden on women 50]. These findings underscore the relevance of improv- and their families during supervised delivery. Although ing collaboration between health facilities and TBAs as strengthening and encouraging enrolment in the NHIS well as giving TBAs some form of training in delivery and will help improve supervised delivery, the management referrals to reduce maternal mortality, especially in rural of various health facilities should address issues related to areas. hidden costs and informal payments during supervised Household wealth and health insurance were factors deliveries. Finally, access to secondary level education that related to home deliveries according to our study or higher needs to be improved by the government and results. Findings from our study and other studies suggest development partners. that home delivery decreased with an increase in finan- cial stands [36, 51, 52]. The Government of Ghana has Strengths and limitations of the study enacted policies such as the Community-based Health A key strength of our study was the use of a large, nation- Planning and Services (CHPS) initiative nationwide in ally representative survey datasets collected in three Dzomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 10 of 12 waves by the Ghana Multiple Indicator Cluster Survey for publication. PA was responsible for the conceptualization and design, (GMICS) in 2006, 2011 and 2017/2018 based on a stand- data acquisition, formal analyses, interpretation of data, literature search and drafting, review and editing of the manuscript for publication. JO, LAP, NEYD, ardised methodology for analyses. Therefore, our findings ABBM, EKN and JJN were responsible for design and drafting, review and edit‑ can be generalized. Secondly, the study employed a com- ing of the manuscript for publication. VMD and PA are the guarantors of the plex sample analytic design to account for sampling units paper. JJN Supervised the study. All the authors have read the manuscript and approved the final version to be published. and weighting. Besides, the study unmasked the popula- tion of women who are at risk of home delivery, the asso- Funding ciated sociodemographic factors and social inequalities This research was funded by University of California, San Francisco Population Health and Health Equity Fellowship program. as well as the progress made. The main limitation of the study is that we used secondary data which utilized a Availability of data and materials cross-sectional design. Hence, the associations observed The datasets that were used in this study is freely available at https://m ics. unicef.o rg/ surve ys once permission is sought and granted by UNICEF. in this study do not infer a causal relationship between the predictors and the outcome variables. The study was Declarations also restricted to variables available in the GMICS Data. Also, there was difficulty in determining the “where” and Ethics approval and consent to participate “how” of the previous child loss variable; it is not clear The study was performed in accordance with the Declaration of Helsinki and approved by appropriate ethics committee. Trained field enumerators from the dataset or the questionnaire whether the experi- collected data on behalf of UNICEF and GSS. The MICS team of UNICEF‑Ghana, ence of child loss occurred in a health facility or the home The Ethical Review Board of the Ghana Health Service, and the Ghana Statisti‑ or any other place, therefore, it will be difficult to make cal Service approved the study. Before data collection, child assents and adult verbal consents to participate in the survey were obtained from participants. any concrete conclusions on its effect on the place of sub- Additionally, participants were assured of anonymity and confidential‑ sequent delivery. From the summary statistics, however, ity. Informed consent was obtained from all respondents, and assent was it does appear that women who experienced previous obtained for respondents younger than eighteen from parents/guardians/ adult household member. More details regarding the data and ethical stand‑ child loss were associated with a higher likelihood of giv- ards are available at: https:// mics. unicef. org/ surve ys. Therefore, ethics approval ing birth in the home in a bivariate model. Our recom- for this study was not required since the data is secondary and is available mendation for the designers of the GMICS questionnaire in the public domain. All methods were performed in accordance with the relevant guidelines and regulations. is that this question should have a follow-up question to ascertain where and how the respondent loss her child. Consent for publication Not applicable. Conclusion Competing interests Generally, the proportion of women who give birth at The authors have no conflicts of interest to declare. home has decreased. The proportion of home deliv- Author details eries has reduced from 50.56% in 2006 to 21.37% in 1 Department of Nursing, Faculty of Allied Health Sciences, College of Health 2017–18. In the multivariable model, women who had Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, 2 less than eight antenatal care visits, dwelt in households Ghana. Department of Nursing and Midwifery, School of Human and Health Sciences, University of Huddersfield, Queensgate, Huddersfield, England, UK. with decreasing wealth, rural areas of residence, and 3 Department of Population and Health, University of Cape Coast, Private Mail residing in the Upper East region (in the year 2011 and Bag, Cape Coast, Ghana. 4 Department of Epidemiology, College of Public 2017–18) were consistently at risk of delivering in the Health & Health Professions, College of Medicine, University of Florida, Florida, USA. 5 Department of Psychology, University of Ghana, P.O. Box LG 84, Legon, home throughout the three data waves. Policies should Ghana. 6 Department of Epidemiology and Biostatistics, School of Public target the at-risk-women to achieve complete reduction Health, Kwame Nkrumah University of Science and Technology, Kumasi, 7 in home deliveries. Access to facility-based deliveries Ghana. Department of Family Health Care Nursing, School of Nursing, Univer‑sity of California San Francisco, San Francisco, CA, USA. should be expanded and ensure that the expansion meas- ures are pro-poor, pro-rural, and pro-uneducated. Inno- Received: 14 March 2021 Accepted: 2 July 2021 vative measures such as mobile antenatal care programs can be organized in every community in the population segments that were consistently choosing home deliver- ies over facility-based deliveries. References 1. Ketemaw A, Tareke M, Dellie E, Sitotaw G, Deressa Y, Tadesse G, et al. Factors associated with institutional delivery in Ethiopia: a cross sectional Acknowledgements study. BMC Health Serv Res. 2020;20(1):266. The authors thank the United Nations International Children’s Emergency 2. World Health Organization. Maternal mortality [Internet]. 2019 [cited Fund (UNICEF) for their support and free access to the original data used in 2021 Jan 28]. Available from: https:// www.w ho.i nt/ news‑ room/ fact‑ this study. sheets/ detail/ mater nal‑m orta lity 3. United Nations, Department of Economic and Social Affairs, Population Authors’ contributions Division. World mortality report 2019: highlights. 2019. VMD and PAD contributed to conceptualization and design, interpretation 4. United Nations. Take Action for the Sustainable Development Goals of data, literature search and drafting, review and editing of the manuscript [Internet]. United Nations Sustainable Development. 2020 [cited 2021 D zomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 11 of 12 Feb 21]. Available from: https:// www.u n. org/ susta inabl edeve lopme nt/ 23. Hajizadeh M, Alam N, Nandi A. Social inequalities in the utilization of sustai nable‑d evel opment‑ goals/ maternal care in Bangladesh: have they widened or narrowed in recent 5. Budu E. Predictors of home births among rural women in Ghana: analysis years? Int J Equity Health. 2014;13(1):120. of data from the 2014 Ghana demographic and health survey. BMC 24. Dankwah E, Zeng W, Feng C, Kirychuk S, Farag M. The social Pregnancy Childbirth. 2020;20(1):523. determinants of health facility delivery in Ghana. Reprod Health. 6. Ibrahim S, Handiso T, Jifar M, Yoseph E. Analyzing prevalence of home 2019;16(1):101. delivery and associated factors in Anlemo District, Southern Ethiopia. Int 25. Enuameh YAK, Okawa S, Asante KP, Kikuchi K, Mahama E, Ansah E, et al. Ann Med. 2017;1(6). Factors influencing health facility delivery in predominantly rural com‑ 7. Ahinkorah BO, Seidu A‑A, Budu E, Agbaglo E, Appiah F, Adu C, et al. munities across the three ecological zones in ghana: a cross‑sectional What influences home delivery among women who live in urban areas? study. Plos One. 2016;11(3):e0152235. Analysis of 2014 Ghana Demographic and Health Survey data. Plos One. 26. Ganle JK, Mahama MS, Maya E, Manu A, Torpey K, Adanu R. Under‑ 2021;16(1):e0244811. standing factors influencing home delivery in the context of user‑fee 8. World Health Organization. Skilled birth attendants, factsheet. Geneva: abolition in Northern Ghana: evidence from 2014 DHS. Int J Health World Health Organization; 2008. [cited 2021 Feb 21]. Available from: Plann Manage. 2019;34(2):727–43. (https:// www. who. int/ mater nal_c hild_a dole scent/ events/2 008/m dg5/ 27. Ghana Statistical Service. Multiple Indicator Cluster Survey facts heet_ sba. pdf ). (MICS2017/2018): Survey Findings Report. Accra: GSS. 2018. [Internet]. 9. Delibo D, Damena M, Gobena T, Balcha B. Status of Home Delivery and [cited 2021 Feb 23]. Available from: https://w ww.u nicef. org/g hana/ Its Associated Factors among Women Who Gave Birth within the Last media/ 576/fi le/ Ghana% 20Mult iple% 20Clus ter% 20Indi cator% 20Surv ey. 12 Months in East Badawacho District, Hadiya Zone, Southern Ethiopia. pdf Biomed Res Int. 2020;2020:4916421. https:// doi.o rg/ 10.1 155/ 2020/ 49164 28. Chea SK, Mwangi TW, Ndirangu KK, Abdullahi OA, Munywoki PK, 21 Abubakar A, et al. Prevalence and correlates of home delivery amongst 10. Shah N, Rohra DK, Shams H, Khan NH. Home deliveries: reasons and HIV‑infected women attending care at a rural public health facility in adverse outcomes in women presenting to a tertiary care hospital. J Pak Coastal Kenya. Plos One. 2018;13(3):e0194028. Med Assoc. 2010;60(7):555–8. 29. Dickson KS, Adde KS, Amu H. What Influences Where They Give Birth? 11. Tessema GA, Laurence CO, Melaku YA, Misganaw A, Woldie SA, Hiruye Determinants of Place of Delivery among Women in Rural Ghana A, et al. Trends and causes of maternal mortality in Ethiopia during [Internet]. Vol. 2016, International Journal of Reproductive Medicine. 1990–2013: findings from the Global Burden of Diseases study 2013. BMC Hindawi; 2016: p. e7203980. [cited 2021 Feb 23]. Available from: Public Health. 2017;17. [cited 2021 Feb 20]. Available from: https://w ww. https://w ww. hinda wi. com/ journa ls/i jrmed/ 2016/ 720398 0/ ncbi. nlm. nih. gov/ pmc/ artic les/ PMC529 0608/ 30. Ahinkorah BO. Non‑utilization of health facility delivery and its cor‑ 12. Darega B, Dida N, Tafese F, Ololo S. Institutional delivery and postnatal relates among childbearing women: a cross‑sectional analysis of the care services utilizations in Abuna Gindeberet District, West Shewa, 2018 Guinea demographic and health survey data. BMC Health Serv Oromiya Region, Central Ethiopia: a Community‑based cross sectional Res. 2020;20(1):1016. study. BMC Pregnancy and Childbirth. 2016;16(1):1–7. https:// www.n cbi. 31. West BT, Sakshaug JW, Aurelien GAS. How big of a problem is nlm. nih. gov/ pmc/a rticl es/ PMC493 6291/. analytic error in secondary analyses of survey data? Plos One. 13. Jafree SR, Zakar R, Mustafa M, Fischer F. Mothers employed in paid work 2016;11(6):e0158120. and their predictors for home delivery in Pakistan. BMC Pregnancy Child‑ 32. Tamhane AR, Westfall AO, Burkholder GA, Cutter GR. Prevalence odds birth [Internet]. 2018;18. [cited 2021 Feb 21]. Available from: https:// www. ratio versus prevalence ratio: choice comes with consequences. Stat ncbi.n lm. nih. gov/ pmc/ artic les/P MC60 91079/ Med. 2016;35(30):5730–5. 14. Ghana Health Service. 2016 Annual Report [Internet]. 2017 [cited 2021 33. Martinez BAF, Leotti VB, Silva G de S e, Nunes LN, Machado G, Corbellini Feb 21]. Available from: https:// www.g hana health serv ice. org/ downl LG. Odds Ratio or Prevalence Ratio? An Overview of Reported Statisti‑ oads/ GHS_A NNUAL_ REPORT_ 2016_n.p df cal Methods and Appropriateness of Interpretations in Cross‑sectional 15. Ghana Health Service. Ghana Annual Report 2019 [Internet]. WHO | Studies with Dichotomous Outcomes in Veterinary Medicine. Front Vet Regional Office for Africa. 2020 [cited 2021 Feb 21]. Available from: Sci. 2017;4 [cited 2021 Feb 23]. Available from: https:// www. front iersin. https://w ww. afro. who. int/p ubli catio ns/ ghana‑ annual‑ report‑ 2019 org/ artic les/ 10. 3389/ fvets.2 017. 00193/f ull 16. Koduah A, van Dijk H, Agyepong IA. The role of policy actors and con‑ 34. Ganle JK, Kombet ML, Baatiema L. Factors influencing the use of textual factors in policy agenda setting and formulation: maternal fee supervised delivery services in Garu‑Tempane District, Ghana. BMC exemption policies in Ghana over four and a half decades. Health Res Pregnancy and Childbirth. 2019;19(1):1‑1. Policy Syst. 2015;13(1):27. 35. GSS; GHS; ICF International. Ghana demographic health survey. Demo‑ 17. Johnson FA, Frempong‑Ainguah F, Matthews Z, Harfoot AJP, Nyarko P, graphic and Health Survey 2014. 2015. Baschieri A, et al. Evaluating the Impact of the Community‑Based Health 36. Koduah A, van Dijk H, Agyepong IA. The role of policy actors and con‑ Planning and Services Initiative on Uptake of Skilled Birth Care in Ghana. textual factors in policy agenda setting and formulation: maternal fee PLoS One. 2015;10(3). Available from: https:// www. ncbi. nlm.n ih.g ov/ exemption policies in Ghana over four and a half decades. Health Res pmc/ artic les/P MC43 66226/. [cited 2021 Feb 21] Pol Syst. 2015;13(1):1–20. 18. Ghana Statistical Service, Ghana Health Service, ICF International. Ghana 37. Kifle MM, Kesete HF, Gaim HT, Angosom GS, Araya MB. Health facility or Statistical Service (GSS), Ghana Health Service (GHS), and ICF Interna‑ home delivery? Factors influencing the choice of delivery place among tional. Ghana Maternal Health Survey 2017: Key Findings. Rockville: GSS, mothers living in rural communities of Eritrea. J Health Popul Nutr. GHS, and ICF; 2018. [cited 2021 Feb 21]. Available from: (https:// www. 2018;37(1):22. dhspro gram. com/ pubs/ pdf/ SR251/S R251. pdf ). 38. Moindi RO, Ngari MM, Nyambati VCS, Mbakaya C. Why mothers still 19. Barrow A, Jobe A, Onoh VI, Maduako KT. Prevalence and factors deliver at home: understanding factors associated with home deliver‑ associated with institutional‑based delivery in the gambia: further ies and cultural practices in rural coastal Kenya, a cross‑section study. analysis of population‑based cross‑ sectional data. Afr J Reprod Health. BMC Public Health. 2016;16(1):114. 2020;24(2):176–86. 39. Hazarika I. Factors that determine the use of skilled care during deliv‑ 20. Geleto A, Chojenta C, Musa A, Loxton D. Barriers to access and utilization ery in India: implications for achievement of MDG‑5 targets. Matern of emergency obstetric care at health facilities in sub‑Saharan Africa: a Child Health J. 2011;15(8):1381–8. systematic review of literature. Syst Rev. 2018;7(1):1‑4. https:// www. ncbi. 40. Akazili J, Doctor HV, Abokyi L, Hodgson A, Phillips JF. Is there any rela‑ nlm. nih. gov/ pmc/ articl es/P MC62 34634/. tionship between antenatal care and place of delivery? Findings from 21. Mackenbach JP. The persistence of health inequalities in modern welfare rural northern Ghana. Afr J Health Sci. 2011;18(1‑2):62–73. states: the explanation of a paradox. Soc Sci Med. 2012;75(4):761–9. 41. Sarker BK, Rahman M, Rahman T, Hossain J, Reichenbach L, Mitra DK. 22. O’Campo P, Urquia M. Aligning method with theory: a comparison of Reasons for preference of home delivery with traditional birth attend‑ two approaches to modeling the social determinants of health. Matern ants (TBAs) in rural Bangladesh: a qualitative exploration. PloS one. Child Health J. 2012;16(9):1870–8. 2016;11(1):e0146161. Dzomeku et al. BMC Pregnancy Childbirth (2021) 21:518 Page 12 of 12 42. Danforth EJ, Kruk ME, Rockers PC, Mbaruku G, Galea S. Household deci‑ 50. Balde MD, Bangoura A, Sall O, Balde H, Niakate AS, Vogel JP, Bohren MA. A sion‑making about delivery in health facilities: evidence from Tanzania. J qualitative study of women’s and health providers’ attitudes and accept‑ Health Popul Nutr. 2009;27(5):696. ability of mistreatment during childbirth in health facilities in Guinea. 43. Organization world health. WHO Recommendation on Antenatal care Reprod Health. 2017;14(1):1–3. for positive pregnancy experience. WHO Recommendation on Antenatal 51. Palamuleni M. Determinants of non‑institutional deliveries in Malawi. care for positive pregnancy experience. 2016. Malawi Med J. 2011;23(4):104–8. 44. Duysburgh E, Ye M, Williams A, Massawe S, Sie A, Williams J, Mpembeni R, 52. Shahabuddin AS, De Brouwere V, Adhikari R, Delamou A, Bardaj A, Loukanova S, Temmerman M. Counselling on and women’s awareness of Delvaux T. Determinants of institutional delivery among young married pregnancy danger signs in selected rural health facilities in B urkina F aso, women in Nepal: evidence from the Nepal Demographic and Health G hana and T anzania. Trop Med Int Health. 2013;18(12):1498–509. Survey, 2011. BMJ open. 2017;7(4):e012446. 45. Dankwah E, Zeng W, Feng C, Kirychuk S, Farag M. The social determinants 53. Dzakpasu S, Soremekun S, Manu A, Ten Asbroek G, Tawiah C, Hurt L, of health facility delivery in Ghana. Reprod Health. 2019;16(1):1‑10. Fenty J, Owusu‑Agyei S, Hill Z, Campbell OM, Kirkwood BR. Impact of free 46. Onah HE, Ikeako LC, Iloabachie GC. Factors associated with the use delivery care on health facility delivery and insurance coverage in Ghana’s of maternity services in Enugu, southeastern Nigeria. Soc Sci Med. Brong Ahafo Region. PloS one. 2012;7(11):e49430. 2006;63(7):1870–8. 54. Witter S, Arhinful DK, Kusi A, Zakariah‑Akoto S. The experience of Ghana 47. Mrisho M, Schellenberg JA, Mushi AK, Obrist B, Mshinda H, Tanner M, in implementing a user fee exemption policy to provide free delivery Schellenberg D. Factors affecting home delivery in rural Tanzania. Trop care. Reprod Health Matters. 2007;15(30):61–71. Med Int Health. 2007;12(7):862–72. 55. du Toit M, Malau‑Aduli B, Vangaveti V, Sabesan S, Ray RA. Use of telehealth 48. Kitui J, Lewis S, Davey G. Factors influencing place of delivery for women in the management of non‑critical emergencies in rural or remote in Kenya: an analysis of the Kenya demographic and health survey, emergency departments: a systematic review. J Telemed Telecare. 2008/2009. BMC Pregnancy and Childbirth. 2013;13(1):1–0. 2019;25(1):3–16. 49. Bohren MA, Vogel JP, Tunçalp Ö, Fawole B, Titiloye MA, Olutayo AO, Ogunlade M, Oyeniran AA, Osunsan OR, Metiboba L, Idris HA. Mistreat‑ ment of women during childbirth in Abuja, Nigeria: a qualitative study Publisher’s Note on perceptions and experiences of women and healthcare providers. Springer Nature remains neutral with regard to jurisdictional claims in pub‑ Reprod Health. 2017;14(1):1–3. lished maps and institutional affiliations. Ready to submit your research ? Choose BMC and benefit from: • fast, convenient online submission • thorough peer review by experienced rese archers in your field • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations • maximum visibility for your research: over 100M website views per year At BMC, research is always in progress. Learn more biomedcentral.com/submissions