Duodu et al. BMC Pregnancy and Childbirth (2022) 22:59 https://doi.org/10.1186/s12884-022-04404-9 RESEARCH Open Access Trends in antenatal care visits and associated factors in Ghana from 2006 to 2018 Precious Adade Duodu1, Jonathan Bayuo2, Josephine Aboagye Mensah3, Livingstone Aduse‑Poku4, Francis Arthur‑Holmes5, Veronica Millicent Dzomeku6, Nutifafa Eugene Yaw Dey7, Pascal Agbadi6 and Jerry John Nutor8* Abstract Introduction: Given that maternal mortality is a major global health concern, multiple measures including antenatal care visits have been promoted by the global community. However, most pregnant women in Ghana and other sub‑ Saharan African countries do not attain the recommended timelines, in addition to a slower progress towards meet‑ ing the required minimum of eight visits stipulated by the World Health Organization. Therefore, this study explored the trends in antenatal care visits and the associated factors in Ghana from 2006 to 2018 using the Multiple Indicator Cluster Surveys. Methods: The study used women datasets (N = 7795) aged 15 to 49 years from three waves (2006, 2011, and 2017‑2018) of the Ghana Multiple Indicator Cluster Surveys (GMICS). STATA version 14 was used for data analyses. Univariable analyses, bivariable analyses with chi‑square test of independence, and multivariable analyses with robust multinomial logistic regression models were fitted. Results: The study found a consistent increase in the proportion of women having adequate and optimal antena‑ tal attendance from 2006 to 2018 across the women’s sociodemographic segments. For instance, the proportion of mothers achieving adequate antenatal care (4 to 7 antenatal care visits) increased from 49.3% in 2006 to 49.98% in 2011 to 58.61% in 2017‑2018. In the multivariable model, women with upward attainment of formal education, health insurance coverage, increasing household wealth, and residing in the Upper East Region were consistently associated with a higher likelihood of adequate and/or optimal antenatal care attendance from 2006 to 2018. Conclusion: Women who are less likely to achieve optimal antenatal care visits should be targeted by policies towards reducing maternal mortalities and other birth complications. Poverty‑reduction policies, promoting mater‑ nal and girl‑child education, improving general livelihood in rural settings, expanding health insurance coverage and infrastructural access, harnessing community‑level structures, and innovative measures such as telehealth and telemedicine are required to increase antenatal care utilization. Keywords: Prenatal care, maternal and child health, sub‑Saharan Africa, child morality, maternal mortality Background Globally, maternal mortality remains a major public health issue with an estimated 810 women dying from pregnancy-related complications daily [1]. In 2017, *Correspondence: Jerry.Nutor@ucsf.edu the World Health Organization (WHO) recorded 8 Department of Family Health Care Nursing, School of Nursing, University approximately 295,000 maternal deaths following preg- of California San Francisco, San Francisco, California, USA nancy and childbirth: 94% of these deaths occurred Full list of author information is available at the end of the article © The Author(s) 2022. 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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. Duodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 2 of 14 in low-and-middle-income settings with sub-Saharan from poorer households, and those in rural areas [19]. African (SSA) and Southern Asia accounting for 86% Additionally, access to transportation and number of [2]. These have led to calls for more actions to curb the children influence the level of ANC service utiliza- situation as highlighted in the Sustainable Develop- tion [20]. Although these findings help to understand ment Goal (SDG) three, which targets a reduction in the factors associated with ANC service utiliza- the global maternal mortality ratio to less than 70 per tion at a national level, they do not necessarily offer 100,000 live births by 2030 [3, 4]. Among the strate- insights into the trends across the regions of Ghana gies to overcome this challenge is timely utilization of and whether the aforementioned factors may differ on antenatal care which remains paramount particularly in regional basis. It is believed that by exploring existing SSA [5, 6]. datasets, it will be possible to uncover regional trends Antenatal care (ANC) refers to the routine care deliv- of ANC utilization and its associated factors which can ered to expectant mothers following conception to the better inform policy and practice. Therefore, this study onset of labour [7]. Adequate ANC support offers an explored the trends in ANC visits and the consistency opportunity to deliver health promotion and preventive in the associated factors associated with ANC visits in services [8]. Overall, ANC seeks to promote and protect Ghana from 2006 to 2018 using the Multiple Indicator the health of the expectant mother and the unborn baby Cluster Surveys. to improve health outcomes and transition to the post- natal period with minimum challenges. Thus, all preg- nant women need to receive adequate and timely ANC Methods support to promote a positive experience during the Data source and collection procedure period of conception. The timing of the first ANC visit is Women datasets from three waves of the Ghana Mul- of utmost importance as it helps to plan subsequent visits tiple Indicator Cluster Survey (GMICS) conducted in [9]. As suggested by the previous WHO Focused Ante- 2006, 2011 and 2017-2018 were analyzed for this study. natal Care (FANC) Framework, an expectant mother The GMICS is a cross-sectional survey conducted by the should have at least four ANC visits throughout preg- Ghana Statistical Service (GSS) in association with the nancy [10]. However, the updated framework by WHO in Ghana Health Service (GHS), Ministry of Health (MOH), 2016 highlighted a minimum of eight contacts with ANC and the Ministry of Education [21]. Funding and techni- services to adequately prepare for the delivery process cal support were provided by the United Nations Inter- and avoid complications [4, 11–13]. Also, the updated national Children’s Emergency Fund (UNICEF) and other framework emphasised the need for comprehensive international donors [21]. The main aim of the MICS and person-centred care at each visit [13]. Despite these surveys is to collect data on key indicators that assist new recommendations, approximately 69% of pregnant countries to produce evidence for use in national devel- women in SSA countries have at least only one ANC visit opment plans, policies, and programmes as well as assess which may suggest that most expectant mothers do not the advancements towards the Sustainable Development attain the recommended timelines. The report shows Goals (SDGs) and other internationally-signed agree- that there is much slower progress towards meeting the ments [21]. required minimum number of ANC visits stipulated by Trained research enumerators were engaged to collect WHO in most SSA countries [14]. the data on behalf of GSS and UNICEF using a multi- In Ghana, the national coverage of ANC service for stage stratified cluster sampling approach. This approach the previously recommended four visits is above the nationally surveyed women in urban and rural areas global average [15]. However, rural-urban and regional from the previous ten administrative regions in Ghana: discrepancies regarding service delivery and utiliza- Western, Central, Greater Accra, Volta, Eastern, Ashanti, tion may exist as some studies have noted that some Brong Ahafo, Northern, Upper East, and Upper West. expectant mothers, particularly those in the rural set- The initial stage of data collection involved identifying tings are unable to access ANC services [16, 17]. The and selecting enumeration areas based on the 2010 Pop- existing evidence so far suggests that regardless of ulation and Housing Census of Ghana. These enumera- the socio-economic and demographic factors, preg- tion areas became the primary sampling units. Next, in nant women enrolled on the National Health Insur- the second stage, households were listed from each of ance Scheme (NHIS) are likely to utilise ANC services the selected enumeration areas and a sample of house- than those who are not enrolled [18]. Also, pregnant holds was selected using systematic random sampling. women with formal education, residing in urban areas This stage enabled the recruitment of reproductive-aged in Ghana and who are wealthy are more likely to uti- women from selected households. Data of 7795 women lize ANC visits than those with no formal education, aged 15 to 49 years from all the three waves who had D uodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 3 of 14 delivered 2 years prior to the data collection periods were independent variables, and we have not observed any included in this study. violations. Measures Data preparation and Analysis Outcome variable Data analyses began by cleaning and recoding variables Antenatal care attendance is the main outcome vari- of interest in STATA version 14. The GMICS predefined able for this study. This variable was extracted from a survey weights for the differential probability selection single-item survey question asking women who had of sample were accounted for with the Taylor lineariza- given birth 2 years prior to the data collection about tion technique [24, 25]. This procedure adjusted for the the number of times they attended antenatal care. clustering, stratification, and design effects within the Women were specifically asked, “How many times did datasets. Univariable analyses were initially performed you receive antenatal care during this pregnancy?” on all three waves of datasets by calculating frequencies Women responded by providing a single number or and percentages of all the variables (see Table 1 - sec- range of numbers. For those who responded by giving ond, sixth, and tenth columns). Secondly, simple Pois- a range, the minimum number was recorded as their son regression was used to determine whether there answer. Guided by the WHO’s recommendation, these was a significant trend in ANC visits over the three numbers were categorized under 4-scale response for- data waves (2006, 2011, 2018) (Additional  file  1). Fur- mat: “none = 1”, “1-3 visits = 2”, “4+ visits = 3” and 8+ thermore, bivariable analyses were performed with a visits = 4″. We decided to collapse the none and “1-3 chi-square test of independence to estimate the rela- visits” into one category as “less than 4 visits” because tionship between the explanatory variables and the only one woman did not attend ANC in the 2006 data. outcome variable as presented in Table  1. Lastly, mul- This categorization makes it easy for us to compare the tivariable analyses with robust multinomial logistic models for the three data waves. Therefore, the newly regression models were conducted, treating the “less created categories are as follows: “less than 4 visits than 4 visits” category in the outcome variable (ante- (undesirable)=0”, “4 to 7 visits (adequate)=1” and 8+ natal care attendance) as the base. All the explanatory visits (optimal) = 2″. variables were independently (Table  2) and simultane- ously (see Table  3) regressed onto the outcome varia- Explanatory variables ble, regardless of the statistical significance value in the Age of woman, education, polygyny status, wanted last- bivariable analyses. The same processes were repeated child, parity, death of a previous child, health insurance, for all the three datasets used in this study, setting the household wealth index, urban-rural residence, and significance alpha level at 0.05. The relative risk ratio region of residence were treated as explanatory vari- and the adjusted relative risk ratio were reported. ables as seen in Table 1. We selected the variables from the datasets based on their reported significance to the outcome variable in the literature [5, 22, 23]. All vari- Ethical approval and Data availability ables were available in all the three datasets except for This study was performed following the Declaration of health insurance which was only available in the 2011 Helsinki and approved by the appropriate ethics com- and 2017-2018 datasets. The variables were measured mittee. The original survey data utilized for this sec- with single-item self-report questions and simple cat- ondary data analysis study was collected by trained field egorical response options. For instance, age of woman enumerators on behalf of UNICEF and GSS. The MICS was measured with the question, “How old are you?” team of UNICEF-Ghana, The Ethical Review Board of and participants responded by indicating their age the Ghana Health Service, and the Ghana Statistical in numbers which was later categorized by UNICEF. Service approved the study that collected the original Health insurance was measured with the question, “Are survey data. Therefore, ethics approval for this current you covered by any health insurance?” with response study was not required since the data is secondary and format comprising “Yes = 1” and “No = 2”. Education is available in the public domain. Before the collection of was measured by asking participants to respond to the the original survey data, informed consent was obtained question, “What is the highest level and grade or year from all the respondents. Adult verbal consents and child of school you have attended?” with responses ranging assents were obtained for the respondents younger than from, “early childhood education=0” to “higher = 6”. eighteen from their parents/guardians/adult household We used the Variance Inflation Factor (VIF) to check members to participate in the survey. Additionally, par- for the assumptions of multicollinearity among the ticipants were assured of anonymity and confidentiality. Duodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 4 of 14 Table 1 Cross‑tabulation between ANC visits and study variables in Ghana from 2006 to 2017‑2018 2006 2011 2017-2018 n (%) < 4 4-7 8+ n (%) < 4 4-7 8+ n (%) < 4 4-7 8+ Total 1456 (100) 389 (26.7) 717 (49.2) 350 (24.1) 2873 (100) 384 (13.4) 1436 (50.0) 1053 (36.6) 3466 (100) 519 (15.0) 2031 (58.6) 915 (26.4) Age (years) P ≤ 0.05 P ≤ 0.005 P ≤ 0.001 15‑24 433 31.4 49.6 19.0 705 (24.5) 17.1 50.8 32.1 952 (27.5) 17.5 60.4 22.1 (29.7) 25‑34 693 (47.6) 23.8 48.7 27.5 1436 (50.0) 10.6 48.0 41.4 1634 (47.2) 13.5 56.8 29.7 35+ 330 26.6 49.8 23.6 733 15.2 53.1 31.7 879 (25.4) 14.9 60.1 25.0 (22.7) (25.5) Education level P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 None or pre‑primary 537 (36.9) 35.0 48.9 16.1 833 (29.0) 22.1 59.5 18.4 774 (22.3) 20.1 64.2 15.8 Primary 320 34.0 48.2 17.8 642 15.3 50.3 34.4 729 (21.0) 21.1 57.4 21.5 (22.0) (22.3) JHS 496 (34.1) 17.2 52.6 30.3 1007 (35.0) 9.0 47.2 43.8 1341 (38.7) 12.3 61.2 26.5 Secondary & above 103 6.8 38.1 55.1 391 2.9 37.0 60.9 622 (17.9) 7.3 47.5 45.2 (7.1) (13.6) Polygyny P ≤ 0.05 P ≤ 0.001 P ≤ 0.001 Never/ formerly married 165 34.5 47.2 18.4 293 15.8 43.8 40.4 592 (17.1) 19.8 55.3 25.0 (11.3) (10.2) In one union 1027 (70.5) 25.1 47.8 27.0 2112 (73.5) 10.6 49.7 39.8 2331 (67.3) 13.0 58.0 29.0 Have co‑wives 264 28.0 56.0 16.0 468 (16.3) 24.6 55.2 20.2 543 (15.7) 18.2 64.8 17.0 (18.1) Wanted the last child P ≤ 0.001 P ≤ 0.05 P ≤ 0.001 Yes 884 (60.7) 20.1 52.1 27.8 1630 (56.7) 11.32 49.4 39.3 1711 (49.37) 12.14 58.57 29.3 Later/No More/others 572 36.9 44.83 18.31 1243 (43.3) 16.1 50.8 33.1 1755 (50.6) 17.8 58.7 23.6 (39.3) Parity P ≤ 0.05 P ≤ 0.001 P ≤ 0.01 Primiparous 321 26.5 47.2 26.3 619 7.3 47.7 45.1 791 (22.8) 13.5 54.0 32.5 (22.0) (21.5) Double 301 20.6 50.6 21.5 527 13.9 47.4 38.7 660 (19.1) 12.7 58.4 29.0 (20.7) (18.3) Multiparous 834 (57.3) 29.0 49.6 21.5 1727 (60.1) 15.4 51.6 33.0 2015 (58.1) 16.3 60.5 23.2 Had previous child loss P ≤ 0.05 P ≤ 0.001 P ≤ 0.001 No 1085 (74.5) 24.5 49.5 26.0 2186 (76.1) 11.9 48.9 39.2 2849 (82.2) 14.1 57.9 28.0 Yes 371 33.2 48.4 18.3 687 (23.9) 18.0 5.4 28.7 617 (17.8) 19.0 62.1 18.9 (25.5) Health Insurance P ≤ 0.001 P ≤ 0.001 Uninsured – – – – 773 22.3 47.9 29.8 1311 (37.8) 19.6 58.2 22.3 (26.9) Insured – – – – 2100 (73.1) 10.1 50.7 39.2 2155 (62.2) 12.2 58.9 28.9 D uodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 5 of 14 Table 1 (continued) 2006 2011 2017-2018 n (%) < 4 4-7 8+ n (%) < 4 4-7 8+ n (%) < 4 4-7 8+ Household wealth P ≤ 0.001 P ≤ 0.001 Poorest 335 39.9 49.7 10.4 637 25.7 61.2 13.1 747 (21.6) 24.1 59.7 16.2 (23.0) (22.2) Poorer 347 31.6 53.5 14.9 621 20.8 51.0 28.2 694 (20.0) 18.5 64.3 17.2 (23.9) (21.6) Middle 277 31.0 51.2 17.7 568 (19.8) 8.3 56.6 35.1 676 (19.5) 17.7 60.7 21.6 (19.0) Richer 286 (19.6) 17.1 49.2 33.7 517 7.0 45.0 48.0 709 (20.5) 8.7 57.9 33.4 (18.0) Richest 211 4.9 39.0 56.1 530 1.5 50.0 36.6 640 (18.5) 4.7 49.8 45.5 (14.5) (18.5) Urban-Rural residence P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 Urban 498 (34.2) 14.5 47.4 38.0 1214 (42.3) 5.9 44.2 49.9 1464 (42.3) 9.7 54.0 36.3 Rural 958 (65.8) 33.0 50.2 16.8 1659 (57.8) 18.8 54.2 27.0 2002 (57.8) 18.8 62.0 19.2 Region of residence P ≤ 0.001 P ≤ 0.001 P ≤ 0.001 Western 154 29.7 48.3 21.9 306 21.5 44.8 33.8 400 (11.5) 12.4 43.5 44.1 (10.6) (10.7) Central 112 33.0 45.6 21.4 279 12.0 54.8 33.2 341 (9.8) 14.8 56.8 28.4 (7.7) (9.7) Greater Accra 177 15.8 36.4 47.9 451 8.1 27.7 64.3 332 (9.6) 9.8 46.4 44.0 (12.2) (15.7) Volta 103 38.6 51.1 10.3 214 17.4 57.8 24.8 285 (8.2) 25.5 59.0 16.5 (7.1) (7.5) Eastern 195 40.7 44.7 14.6 327 6.8 55.8 37.3 402 (11.6) 19.3 58.3 22.3 (13.4) (11.4) Ashanti 222 17.0 50.4 32.6 511 9.0 44.1 46.9 788 (22.7) 12.9 65.9 21.3 (15.2) (17.8) Brong Ahafo 115 24.2 60.1 15.8 258 16.1 62.4 21.5 330 (9.5) 14.5 60.6 25.0 (7.9) (9.0) Northern 278 27.7 53.6 18.7 321 24.9 56.1 19.1 388 (11.2) 17.7 66.4 16.0 (19.1) (11.2) Upper East 61 13.8 53.1 33.1 120 11.2 71.0 17.7 112 4.6 64.2 31.3 (4.2) (4.2) (3.3) Upper West 40 20.5 63.2 16.3 85 9.7 74.2 16.1 88 15.2 70.8 14.1 (2.7) (3.0) (2.6) Duodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 6 of 14 Table 2 Unadjusted multinomial logit model showing correlates of ANC visits in Ghana from 2006 to 2017‑2018 2006 2011 2017-2018 < 4 4-7 8+ < 4 4-7 8+ < 4 4-7 8+ Age (years) Base RR [95% CI] RR [95% CI] Base RR [95% CI] RR [95% CI] Base RR [95% CI] RR [95% CI] 15‑24 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. 25‑34 1 1.3 1.9** 1 1.5* 2.1*** 1 1.2 1.7** [0.9, 1.8] [1.3, 2.8] [1.1, 2.2] [1.4, 3.2] [0.9, 1.6] [1.2, 2.5] 35+ 1 1.2 1.5 1 1.2 1.1 1 1.2 1.3 [0.8, 1.7] [0.9, 2.3] [0.8, 1.7] [0.7, 1.8] [0.8, 1.7] [0.9, 2.0] Education level None or pre‑primary 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Primary 1 1.0 1.1 1 1.2 2.7*** 1 0.852 1.298 [0.7, 1.5] [0.7, 1.8] [0.8, 1.8] [1.8, 4.2] [0.6, 1.2] [0.8, 2.1] JHS 1 2.2*** 3.8*** 1 1.9** 5.8*** 1 1.6** 2.8*** [1.5, 3.2] [2.5, 5.9] [1.3, 3.0] [3.7, 9.2] [1.1, 2.1] [1.8, 4.2] Secondary & above 1 4.0** 17.7*** 1 4.6*** 25.3*** 1 2.0** 7.9*** [1.5,11.01] [6.6, 47.4] [2.0, 10.6] [11.1, 57.5] [1.3, 3.3] [4.5, 13.6] Polygyny Never/formerly married 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. In one union 1 1.4 2.0* 1 1.7* 1.5 1 1.6** 1.8** [0.9, 2.2] [1.1, 3.6] [1.0, 2.8] [0.9, 2.5] [1.2, 2.2] [1.2, 2.6] Have co‑wives 1 1.5 1.1 1 0.8 0.3*** 1 1.3 0.7 [0.9, 2.4] [0.6, 2.0] [0.5, 1.4] [0.2, 0.6] [0.9, 1.9] [0.4, 1.3] Wanted the last child Yes 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Later/No More/others 1 0.5*** 0.4*** 1 0.7* 0.6** 1 0.7* 0.5*** [0.4, 0.6] [0.2, 0.5] [0.6, 0.9] [0.4, 0.8] [0.5, 0.9] [0.4, 0.8] Parity Primiparous 1 1.0 1.3 1 2.0** 2.9*** 1 1.1 1.7** [0.7, 1.5] [0.9, 2.0] [1.3, 3.0] [1.9, 4.5] [0.8, 1.5] [1.2, 2.4] Double 1 1.4 1.9** 1 1.0 1.3 1 1.2 1.6* [1.0, 2.1] [1.2, 3.0] [0.6, 1.6] [0.8, 2.0] [0.9, 1.8] [1.1, 2.4] Multiparous 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Had previous child loss No 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Yes 1 0.7* 0.5*** 1 0.7 0.5*** 1 0.8 0.5*** [0.5, 1.0] [0.4, 0.8] [0.5, 1.0] [0.3, 0.7] [0.6, 1.1] [0.3, 0.7] Health Insurance Uninsured 1 – – 1 0.4*** 0.3*** 1 0.6*** 0.5*** [0.3, 0.6] [0.2, 0.5] [0.5, 0.8] [0.4, 0.7] Insured 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Household wealth Poorest 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Poorer 1 1.4 1.8* 1 1.0 2.7*** 1 1.4 1.4 [0.9, 2.0] [1.1, 3.0] [0.7, 1.6] [1.6, 4.3] [1.0,2.0] [0.9, 2.1] Middle 1 1.3 2.2* 1 2.9*** 8.3*** 1 1.4 1.8* [0.9, 2.0] [1.2, 4.1] [1.5, 5.3] [4.1, 16.5] [0.9, 2.1] [1.1, 2.9] Richer 1 2.3** 7.6*** 1 2.7*** 13.4*** 1 2.7*** 5.7*** [1.4, 3.8] [4.2, 13.6] [1.5, 4.8] [7.6, 23.9] [1.7, 4.3] [3.5, 9.3] Richest 1 6.4*** 43.7*** 1 9.1*** 84.0*** 1 4.3*** 14.6*** [2.7, 14.8] [17.7, 108.0] [3.8, 21.7] [34.6, 203.8] [2.2, 8.4] [7.6, 27.7] Urban-Rural residence Urban 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Rural 1 0.5*** 0.2*** 1 0.4*** 0.2*** 1 0.6** 0.3*** [0.3, 0.7] [0.1, 0.3] [0.2, 0.6] [0.1, 0.3] [0.4, 0.8] [0.2, 0.4] Duodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 7 of 14 Table 2 (continued) 2006 2011 2017-2018 < 4 4-7 8+ < 4 4-7 8+ < 4 4-7 8+ Region of residence Western 1 0.7 0.2** 1 0.6 0.2** 1 0.7 0.8 [0.3, 1.5] [0.1, 0.6] [0.2, 2.2] [0.1, 0.6] [0.4, 1.5] [0.4, 1.5] Central 1 0.6 0.2** 1 1.3 0.3 1 0.8 0.4* [0.3, 1.3] [0.1, 0.6] [0.4, 4.8] [0.1, 1.1] [0.4, 1.6] [0.2, 0.9] Greater Accra 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Volta 1 0.6 0.1*** 1 1.0 0.2** 1 0.5 0.1*** [0.3, 1.2] [0.0, 0.2] [0.3, 3.7] [0.0, 0.7] [0.2, 1.0] [0.1, 0.3] Eastern 1 0.5* 0.1*** 1 2.4 0.7 1 0.6 0.3*** [0.2, 1.0] [0.1, 0.3] [0.5, 10.8] [0.2, 2.7] [0.3, 1.3] [0.1, 0.5] Ashanti 1 1.3 0.6 1 1.4 0.7 1 1.1 0.4** [0.6, 2.9] [0.3, 1.4] [0.4, 5.6] [0.2, 2.3] [0.5, 2.2] [0.2, 0.8] Brong Ahafo 1 1.1 0.2** 1 1.1 0.2** 1 0.9 0.4* [0.5, 2.5] [0.1, 0.6] [0.3, 4.4] [0.0, 0.6] [0.4, 1.8] [0.182, 0.8] Northern 1 0.8 0.2** 1 0.7 0.1*** 1 0.8 0.2*** [0.4, 1.7] [0.1, 0.6] [0.2, 2.3] [0.0, 0.3] [0.4, 1.5] [0.1, 0.4] Upper East 1 1.7 0.8 1 1.8 0.2** 1 3.0* 1.5 [0.7, 3.9] [0.3, 2.0] [0.5, 7.0] [0.1, 0.6] [1.3, 6.9] [0.7, 3.5] Upper West 1 1.3 0.34** 1 2.2 0.2** 1 1.0 0.2*** [0.7, 2.7] [0.1, 0.6] [0.6, 8.0] [0.1, 0.7] [0.5, 1.9] [0.1,0.4] More details regarding the data and ethical standards are antenatal care during pregnancy in the 2 years preced- available at: https:// mics. unicef. org/s urve ys. All methods ing the survey in 2006, 26.7% had less than 4 antenatal were performed in accordance with the relevant guide- care visits (undesirable antenatal care). The percentage lines and regulations. of those who had undesirable antenatal care drastically reduced in 2o11 (13.4%) and then it slightly increased Results in 2017-2018 (15.0%). About 49.3% of mothers had Maternal socio-demographic characteristics adequate antenatal care (4-7 antenatal care visits) in Overall, 7795 women aged 15 to 49 years from all the 2006 but there was a slight increase in the percent- three waves who had delivered 2 years before the data age of adequate antenatal care among mothers in 2011 collection periods were included in this study. Out of (50.0%). The percentage further increased to 58.6% in the 1456 mothers in 2006, 47.6% were 25-34 years old. 2017-2018. Generally, there was a consistent increase in This percentage increased to 50.0% in 2011 but reduced the proportion of women having adequate and optimal in 2017-2018 (47.2%). Regarding education, majority of ANC attendance from 2006 to 2018 across the women’s the mothers had no or pre-primary education (36.9%) in socio-demographic segments. However, marked socio- 2006, however, in 2011 (35.0%) and 2017-2018 (38.7%), economic and demographic disparities were observed. the majority were those who had junior high education. For instance, the proportion of women with second- Additionally, the percentage of women living in rural ary or higher education [2006, 55.1%; 2011, 60.9%; areas was higher (65.8%) in 2006 but decreased in 2011 2017-2018, 45.2%] consistently had at least three times (57.8%) which remained the same in 2017-2018. About higher proportion of optimal ANC attendance com- 73.1% of mothers in 2011 were insured but that of insured pared to women without education/pre-primary edu- mothers in 2017-2018 was lesser (62.2%). The remaining cation [2006, 16.1%; 2011, 18.4%; 2017-2018, 15.8%]. of the descriptive statistics are shown in Table 1. Also, women in the richest households [2006, 56.1%; 2011, 36.6%; 2017-2018, 45.5%] had at least three times higher proportion of optimal ANC attendance Trends in antenatal care visits in Ghana from 2006 compared to women of the poorest households [2006, to 2017-2018 10.4%; 2011, 13.1%; 2017-2018, 16.2%]. The propor- There was a statistically significant relationship tion of urban women who had optimal ANC attend- between years and ANC visits from 2006 through 2018 ance [2006, 38.0%; 2011, 49.9%; 2017-2018, 36.3%] for (Additional file  1). Out of the mothers who received their recent child was consistently at least twice as high Duodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 8 of 14 Table 3 Adjusted multinomial logit model displaying correlates of ANC visits in Ghana from 2006 to 2017‑2018 2006 2011 2017-2018 < 4 4-7 8+ < 4 4-7 8+ < 4 4-7 8+ Age (years) Base ARR [95% CI] ARR [95% CI] Base ARR [95% CI] ARR [95% CI] Base ARR [95% CI] ARR [95% CI] 15‑24 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. 25‑34 1 1.1 1.3 1 2.1** 2.7** 1 1.0 1.5 [0.7, 1.6] [0.7, 2.3] [1.3, 3.4] [1.5,4.9] [0.7, 1.5] [0.9, 2.5] 35+ 1 1.3 1.9 1 2.1** 2.5** 1 1.1 1.7 [0.8, 2.1] [1.0, 3.8] [1.2, 3.6] [1.3, 5.1] [0.7, 1.9] [0.9, 3.0] Education level None or pre‑primary 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Primary 1 1.5* 1.5 1 1.043 1.6 1 0.9 1.2 [1.0,2.4] [0.9, 2.6] [0.7, 1.6] [0.9, 2.6] [0.7, 1.3] [0.7, 2.1] JHS 1 3.1*** 3.5*** 1 1.3 2.0* 1 1.5 1.8* [2.0, 4.7] [2.1, 6.0] [0.8, 2.1] [1.1, 3.4] [1.0, 2.2] [1.1, 3.1] Secondary & above 1 4.1** 8.0*** 1 1.3 2.2 1 1.2 2.3* [1.4, 12.0] [2.6, 24.5] [0.5, 3.5] [0.8, 6.0] [0.7, 2.2] [1.2, 4.5] Polygyny Never/formerly married 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. In one union 1 1.2 1.7 1 2.1* 1.3 1 1.4 1.3 [0.7, 2.1] [0.9,3.4] [1.1, 3.9] [0.7, 2.6] [1.0, 2.1] [0.8, 2.1] Have co‑wives 1 1.5 1.3 1 1.3 0.6 1 1.3 0.9 [0.8, 2.8] [0.6, 3.0] [0.6, 2.5] [0.3, 1.2] [0.8, 2.1] [0.5, 1.6] Wanted the last child Yes 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Later/No More/others 1 0.5*** 0.3*** 1 0.6*** 0.4*** 1 0.8 0.646* [0.4, 0.6] [0.2, 0.5] [0.5, 0.8] [0.3, 0.6] [0.6, 1.0] [0.5, 0.9] Parity Primiparous 1 0.9 1.2 1 3.0*** 2.9** 1 1.1 1.6 [0.5, 1.6] [0.6, 2.4] [1.6, 5.7] [1.4, 5.8] [0.7, 1.8] [0.9, 2.9] Double 1 1.1 1.2 1 1.2 1.0 1 1.1 1.1 [0.7, 1.8] [0.7, 2.2] [0.7, 2.0] [0.6, 1.8] [0.7, 1.7] [0.7, 1.8] Multiparous 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Had previous child loss No 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Yes 1 0.8 0.7 1 0.9 0.8 1 0.8 0.6* [0.6, 1.2] [0.5, 1.1] [0.6, 1.4] [0.5, 1.4] [0.5, 1.2] [0.4, 1.0] Health Insurance Uninsured 1 – – 1 0.6** 0.5*** 1 0.7* 0.7* [0.4, 0.9] [0.3, 0.7] [0.5, 0.9] [0.5, 0.9] Insured 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Household wealth Poorest 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Poorer 1 1.5 2.3** 1 1.0 1.9* 1 1.6* 1.3 [1.0, 2.3] [1.3, 4.2] [0.6, 1.7] [1.1, 3.3] [1.1, 2.3] [0.8, 2.2] Middle 1 1.3 2.4* 1 2.6** 4.8*** 1 1.5 1.4 [0.8, 2.1] [1.1, 5.0] [1.3, 5.2] [2.3, 10.2] [0.9, 2.5] [0.8, 2.5] Richer 1 1.9 6.0*** 1 2.3* 5.9*** 1 2.799*** 4.001*** [1.0, 3.6] [2.7, 13.4] [1.1, 4.8] [2.5, 13.9] [1.566,5.002] [2.208,7.251] Richest 1 3.335* 15.64*** 1 7.3** 24.3*** 1 3.8** 5.9*** [1.251,8.893] [4.868,50.25] [2.1, 25.2] [6.7, 87.8] [1.7, 8.5] [2.6, 13.1] Urban-Rural residence Urban 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Rural 1 0.6* 0.7 1 0.6 0.6 1 0.9 0.6* [0.4, 1.0] [0.4, 1.2] [0.3, 1.2] [0.3, 1.1] [0.6, 1.4] [0.4, 1.0] Duodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 9 of 14 Table 3 (continued) 2006 2011 2017-2018 < 4 4-7 8+ < 4 4-7 8+ < 4 4-7 8+ Region of residence Western 1 1.3 0.8 1 1.9 0.9 1 1.1 2.0 [0.6, 3.0] [0.3, 1.9] [0.4, 9.4] [0.2, 3.7] [0.5, 2.4] [0.9, 4.4] Central 1 1.3 0.9 1 3.5 1.3 1 1.1 1.0 [0.6, 2.9] [0.4, 2.5] [0.8, 16.1] [0.4, 4.9] [0.6, 2.3] [0.4, 2.1] Greater Accra 1 Ref. Ref. 1 Ref. Ref. 1 Ref. Ref. Volta 1 1.4 0.5 1 3.1 1.1 1 0.9 0.6 [0.6, 3.3] [0.2, 1.4] [0.7, 14.6] [0.3, 4.3] [0.4, 1.9] [0.2, 1.3] Eastern 1 0.9 0.5 1 5.7* 2.2 1 1.0 0.6 [0.4, 2.0] [0.2, 1.0] [1.1, 29.6] [0.5, 9.0] [0.5, 1.9] [0.3, 1.3] Ashanti 1 2.364 1.9 1 3.8 2.7 1 1.4 0.6 [1.0, 5.6] [0.8, 4.3] [0.8, 18.7] [0.6, 11.2] [0.6, 2.8] [0.3, 1.3] Brong Ahafo 1 2.2 0.9 1 3.7 0.9 1 1.4 1.0 [0.9, 5.4] [0.3, 2.8] [0.8, 17.8] [0.2, 3.8] [0.7, 2.9] [0.5, 2.3] Northern 1 2.7* 1.8 1 2.6 1.0 1 1.7 1.1 [1.2, 6.3] [0.7, 4.8] [0.6, 12.1] [0.3, 3.9] [0.8, 3.6] [0.5, 2.6] Upper East 1 6.4*** 9.7*** 1 7.7* 2.4 1 6.6*** 7.3*** [2.5, 16.4] [3.6, 26.5] [1.6, 37.5] [0.6, 9.6] [2.5, 17.1] [2.6, 20.5] Upper West 1 5.8*** 3.4* 1 8.3** 2.0 1 2.1 0.9 [2.6, 12.6] [1.2, 9.5] [1.8, 39.1] [0.5, 7.9] [1.0, 4.5] [0.4, 2.2] Model details Number of strata 20 20 20 Number of Primary Sampling 291 775 649 Unit Number of Observations 1456 2873 3466 Exponentiated coefficients; 95% confidence intervals in brackets. * p < 0.05, ** p < 0.01, *** p < 0.001. compared to rural women [2006, 16.8%; 2011, 27.0%; a junior high school education (adjusted relative risk 2017-2018, 19.2%]. The results showed a statistically ratio [ARR] = 1.8, 95% CI: 1.1, 3.1) or secondary edu- significant relationship between all the explanatory var- cation and above (ARR = 2.3, 95% CI: 1.2, 4.5) were iables and antenatal care visits in 2006, 2011 and 2017- associated with a higher likelihood of optimal ANC 2018 as shown in Table 1. attendance. Unexpectedly, mothers who had children from unplanned pregnancies were consistently associ- Correlates of antenatal care visits in Ghana from 2006 ated with a lower likelihood of adequate and/or optimal to 2017-2018 ANC attendance from 2006 through 2017-2018 relative Tables  2 and 3 represent the unadjusted and adjusted to undesirable ANC attendance. For instance, com- multinomial logit models respectively, showing the pared to women who wanted their recent child, women correlates of ANC visits in Ghana from 2006 to 2017- who had unplanned births (ARR = 0.6, 95% CI: 0.5, 0.9) 2018. In the adjusted multinomial logit model, gener- were negatively associated with optimal ANC attend- ally, upward attainment of formal education, health ance relative to undesirable ANC attendance. Although insurance coverage, increasing household wealth, and death of previous child was only significantly related to residing in the Upper East region were consistently ANC attendance in the 2017-2018 model, it is worth associated with a higher likelihood of adequate and/ mentioning because of the unexpected observed asso- or optimal ANC attendance from 2006 through 2017- ciation. That is, we unexpectedly observed that women 2018 relative to undesirable ANC attendance among who had lost a previous child to death (ARR = 0.6, 95% childbearing women in Ghana. Examples of some of CI: 0.4, 1.0) was associated with a lower likelihood of the consistent factors in the 2017-2018 adjusted model optimal ANC attendance for their recent child. Parity are interpreted for purposes of brevity result interpre- was also observed to be significantly related to ANC tation. For the most recent year, compared to women attendance in the 2011 model. Lastly, women resid- with no formal education, women who had attained ing in the Upper East Region were consistently found Duodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 10 of 14 to have a higher likelihood of adequate and optimal education would increase women’s awareness, knowledge ANC attendance with increased odds of 6.6 (95% CI: of ANC services utilization and its consequences, thereby 2.5, 17.1) and 7.3 (95% CI: 2.6,20.5) respectively in informing their healthcare decision making. Higher edu- 2017-2018. cation is associated with an increase in the knowledge of obstetric complications, thereby leading to improved uti- Discussion lization of ANC services [33]. The positive effect of the The World Health Organization (WHO) recommends level of education complimented by the introduction of antenatal visits of at least eight times during pregnancy free maternal care policy on Ghana’s NHIS from 2008 and to initiate antenatal care (ANC) in the first trimester may have particularly contributed to the increase in pro- [13]. However, many women in developing countries do portion of higher ANC visits in 2011 and 2017-2018. not adhere to this recommendation [26]. In this study, we Unplanned pregnancy was negatively associated with examined the trends of, and factors associated with ANC ANC attendance. This finding is consistent with previ- utilization in Ghana. We found that the factors associ- ous studies in Ghana [34] and Bangladesh [35, 36] that ated with adequate or optimal ANC attendance from found that women who reported unintended pregnancies 2006 through 2017-2018 included higher attainment of at conception and did not terminate their pregnancies formal education, health insurance coverage, increas- were at higher risk of not using ANC services. Therefore, ing household wealth, urban residence, and residing in it is imperative to motivate and incorporate women with the Upper East Region. Also, there has been an increase unplanned pregnancies in the mainstream healthcare in the number of women having adequate ANC attend- service policies to increase their ANC attendance and to ance from 2006 to 2017-2018; the proportion of women lessen the related undesirable outcomes [35]. Although it increased from 49.3 to 49.98% from 2006 to 2011 and was only significantly related to ANC attendance in the 58.61% in 2017-2018. 2017-2018 model, it is worth mentioning due to its unex- The proportion of mothers achieving adequate ANC pected observed association that, the death of a previous (4-7 ANC visits) increased from 49.3% in 2006 to 49.98% child was negatively associated with ANC attendance. in 2011 to 58.61% in 2017-2018. Consistent with this This concurs with a study in Nigeria that found the death study, Alhassan and colleagues found that there has been of a preceding child to be associated with a lower likeli- an increase in the trends of ANC service utilization in hood of ANC attendance in the univariate models [37]. Ghana in the past decade [27]. This may be due to the Given that poor healthcare-seeking behaviour and health enactment and implementation of the Ghana National outcomes have been linked to low socioeconomic status Health Insurance Scheme (NHIS) in 2003 which aimed among people including pregnant women [38, 39], cover- to offer free medical care to pregnant women. This pol- ing the cost of medical care for pregnant women under icy includes the provision of a comprehensive exemption the NHIS could account for the increased ANC attend- package that provides ANC, postnatal care, and skilled ance. From our study, health insurance coverage was services [28]. The rise in utilization of ANC services may positively associated with ANC attendance. This con- also be due to a change in the WHO recommendations curs with multiple previous studies conducted in Ghana on ANC. In 2003, WHO recommended that in low- that found the possession of national health insurance income countries pregnant women without any compli- to be positively associated with attending ANC at least cations were required to visit health facilities at least four four times [18, 20, 34, 40, 41]. Therefore, the Govern- times during their pregnancies [29]. However, this policy ment of Ghana should continually strengthen the NHIS was reviewed by the WHO in 2016, recommending at and ensure that its goal of universal coverage is achieved least eight ANC visits throughout pregnancy to reduce given that it has the potential to help Ghana meet the perinatal deaths irrespective of the income level [13]. SDG 3 target by 2030. This increase in the minimum recommended number of In this study, the likelihood of optimal utilization of ANC visits means that pregnant women would have to ANC visits was found to be associated with an increase in visit healthcare facilities more frequently than they used household wealth; women from the richest homes were to do before 2016. more likely to obtain optimal ANC services compared to From this study, an increase in the level of education women from the poorest households in all the three sur- was found to be associated with adequate ANC attend- vey waves. Economic barriers, particularly the inability ance. Women who had secondary education and higher to pay have been linked to decreased utilization of ANC or junior high school were associated with adequate ANC services as observed by studies conducted in Nigeria and attendance compared to women with no formal educa- Nepal [42, 43]. These factors influence women’s ability to tion. Similar findings have been observed in many stud- regulate their health and facilitate easy access to maternal ies in low and middle-income countries [30–32]. Higher health care. Using a nationally representative data, the D uodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 11 of 14 Ghana Statistical Service [44] reported that women in the general livelihood in rural settings should be enacted as middle and highest wealth quintiles were more likely to these policies have the potential of improving the health- receive ANC services from healthcare professionals than seeking behaviours of women in rural areas to help those in the lowest quintiles. Despite the fee exemptions reduce maternal and child deaths. Moreover, informa- for ANC services, poor women are still unlikely to utilize tion, education, and communication aimed at stimulat- these services due to lack of adequate information, other ing health-seeking behaviours should be promoted at all costs (of drugs and supplies), transportation costs, and levels to increase the use of antenatal care services and discrimination by some health professionals [45]. lower the prevalence of adverse pregnancy outcomes. We found that women residing in urban areas were We also recommend the identification and harnessing of more likely to attend at least eight ANC services during community-level structures to improve maternal health pregnancy, compared to women residing in rural areas. in rural areas [54], which includes ensuring collaboration This aligns with the findings of studies conducted in between traditional birth attendants (TBAs) and health Ghana and other developing countries [46–49]. Proximity professionals in delivering essential maternal health ser- to health facilities, bad road networks, traditional beliefs vices. A typical example is delegating community mem- against patronage of health services, and unfavourable bers designated as mother-to-mother support group working conditions in rural areas for health professionals leaders or TBAs to serve as targeted support systems have been cited as some of the reasons for the low utiliza- for pregnant mothers to help their enrolment and reten- tion of ANC services in most developing countries [47, tion in ANC services. This will ensure the early utiliza- 50]. Also, compared to women residing in other regions, tion of ANC services which in turn increase the chances women residing in the Upper East Region of Ghana has of meeting the minimum target of eight ANC visits. Fur- the highest likelihood of optimal ANC service utilization. thermore, health insurance coverage should be expanded This finding is in line with that of Sakeah and colleagues to cover all costs related to pregnancy and childbirth, who found that 35.6% of women residing in Navrongo in whiles reducing unnecessary payments during ANC the Upper East Region visit ANC clinic adequately com- visits. There should also be the training of more health- pared to women living in Kintampo (33.2%) and Dodowa care providers and the initiation of targeted motivation (33.7%) in the erstwhile Brong Ahafo and Greater Accra schemes to attract and retain qualified staff in deprived Regions, respectively [51]. They also observed that rural communities to meet the growing shortages, especially areas in the Upper East Region have more community in rural areas. The Government of Ghana, through the health-based planning services (CHPS) compounds than Ministry of Health and Ghana Health Service, should most rural areas in other regions in Ghana [51]. in the long term provide adequate infrastructure (such Further to the above, we observed that parity was sig- as hospitals, clinics, health centres, laboratories, essen- nificantly associated with ANC attendance only in the tial equipment, and motorable roads) and ensure that 2011 model: primiparous women were more likely to they are functioning efficiently. In the short and medium utilise ANC services. Congruent with this finding in the terms, understaffed CHPS compounds, clinics, and 2011 logit model, previous studies [30, 52, 53] have also health centres in rural areas must collaborate with ade- found that women with higher parity tend to use ANC quately staffed hospitals to ensure proper referral systems services less. Potentially, this finding may be related to and utilize the expertise of their staff through telehealth the fact that multiparous women may have pregnancy- and telemedicine. These findings should inform policy related lived experiences that enable them to handle decisions at all levels and engender further epidemiologi- issues on their own with limited reliance of ANC ser- cal inquiries through mixed method designs to unravel vices. Primiparous women may lack these experiences community and facility level oddities on the factors influ- which may serve as a push factor to utilise ANC services. encing ANC utilization. However, the effect of parity on ANC visit was not sig- A key strength of this study was the use of a large, nificant in the model for the recent data wave. nationally representative survey datasets collected in The findings of this study provide several implications three waves by the Ghana Multiple Indicator Cluster for policy and practice. Mothers who could not obtain Survey (GMICS) in 2006, 2011 and 2017-2018 based optimal ANC services stand the chance of having com- on a standardised methodology for analyses. Therefore, plications associated with their pregnancies or child- our findings can be generalized. Secondly, the study births. These findings provide empirical-based evidence employed a complex sample analytic design to account to improve ANC services utilization in the regions where for sampling units and weighting. In addition, the study women find it difficult to have at least eight ANC visits. unravelled the population of pregnant women who are Deliberate policies aimed at reducing poverty, promot- more likely to achieve the optimal ANC visits as rec- ing maternal and girl-child education, and improving ommended by WHO, the predictive sociodemographic Duodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 12 of 14 factors and social inequalities and the achieved progress. Funding The main limitation of the study is that we used second- This research was funded by the University of California, San Francisco Population Health and Health Equity Fellowship program under grant number ary data which utilized a cross-sectional design. Hence, 7504575. the associations observed in this study did not infer a causal relationship between the predictors and the out- Availability of data and materials The datasets that were used in this study is freely available at https://m ics. come variables. The study was also restricted to variables unicef.o rg/ visit ors/ sign‑i n once permission is sought and granted by UNICEF. available in the GMICS Data. Declarations Conclusions Ethics approval and consent to participate This study has offered insights into the trends of This study was performed following the Declaration of Helsinki and approved ANC utilization and its associated factors in Ghana by the appropriate ethics committee. The original survey data utilized for this to inform policy and practice. This study’s analy- secondary data analysis study was collected by trained field enumerators on behalf of UNICEF and GSS. The MICS team of UNICEF‑Ghana, The Ethical ses showed a consistent increase in the proportion of Review Board of the Ghana Health Service, and the Ghana Statistical Service women having adequate and optimal ANC attendance approved the study that collected the original survey data. Therefore, ethics from 2006 to 2017-2018. The proportion of mothers approval for this current study was not required since the data is secondary and is available in the public domain. Before the collection of the original achieving adequate ANC (4-7 ANC visits) increased survey data, informed consent was obtained from all the respondents; adult from 49.3% in 2006 to 49.98% in 2011 to 58.61% in verbal consents and child assents were obtained for the respondents younger 2017-2018. In the multivariable model, women with than eighteen from their parents/guardians/adult household members to participate in the survey. Additionally, participants were assured of anonymity upward attainment of formal education, health insur- and confidentiality. More details regarding the data and ethical standards are ance coverage, increasing household wealth, and available at: https:// mics.u nicef.o rg/ surve ys. All methods were performed in residing in the Upper East Region of Ghana were accordance with the relevant guidelines and regulations. consistently associated with a higher likelihood of Consent for publication adequate and/or optimal ANC attendance from 2006 Not applicable. to 2017-2018. Women who are less likely to achieve Competing interests optimal ANC visits should be targeted by policies The authors have no conflicts of interests to declare. towards reducing maternal mortalities and other birth complications. Poverty-reduction policies, promoting Author details1 Department of Nursing and Midwifery, School of Human and Health Sci‑ maternal and girl-child education, improving general ences, University of Huddersfield, Queensgate, Huddersfield, England, UK. livelihood in rural settings, expanding health insur- 2 School of Nursing, The Hong Kong Polytechnic University, Kowloon, Hong 3 ance coverage and infrastructural access, harnessing Kong. Child Health Directorate, Komfo Anokye Teaching Hospital, Post Office Box 1934, Adum ‑, Kumasi, Ghana. 4 Department of Epidemiology, College community-level structures, and innovative measures of Public Health & Health Professions, College of Medicine, University of Flor‑ such as telehealth and telemedicine are required to ida, Gainesville, USA. 5 Department of Sociology and Social Policy, Lingnan increase ANC utilization. University, 8 Castle Peak Road, Tuen Mun, Hong Kong. 6 Department of Nurs‑ ing, Faculty of Allied Health Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. 7 Department Supplementary Information of Psychology, University of Ghana, P.O. Box LG 84, Legon, Ghana. 8 Department of Family Health Care Nursing, School of Nursing, University of California San The online version contains supplementary material available at https:// doi. Francisco, San Francisco, California, USA. org/1 0. 1186/ s12884‑ 022‑ 04404‑9. Received: 27 April 2021 Accepted: 12 January 2022 Additional file 1. Year of data collection regressed on antenatal care visit and predicted margins. Acknowledgements References The authors thank the United Nations International Children’s Emergency 1. Ahinkorah BO, Seidu A‑A, Budu E, Mohammed A, Adu C, Agbaglo E, et al. Fund (UNICEF) for their support and free access to the original data used in Factors associated with the number and timing of antenatal care visits this study. among married women in Cameroon: Evidence from the 2018 Cameroon Demographic and Health Survey. J Biosoc Sci. 2021:1–11. https:// doi. org/ Authors’ contributions 10.1 017/S 00219 32021 00007 9. PAD contributed to the conceptualization and design, interpretation of 2. World Health Organization. Maternal mortality [Internet]. 2020 [cited data, literature search and drafting, review and editing of the manuscript for 2021 Apr 18]. Available from: https://w ww.w ho. int/ news‑r oom/ fact‑ publication. PA was responsible for the conceptualization and design, data sheets/ detail/ matern al‑m orta lity acquisition, formal analyses, interpretation of data, literature search and draft‑ 3. UNICEF. Maternal mortality [Internet]. UNICEF DATA 2020 [cited 2021 Apr ing, review and editing of the manuscript for publication. JB, JAM, LAP, FAH, 18]. Available from: https://d ata. unicef. org/ topic/m ater nal‑h ealth/m ater VMD, NEYD and JJN were responsible for the design and drafting, review and nal‑ morta lity/ editing of the manuscript for publication. PAD and PA are the guarantors of 4. World Health Organization. World health statistics 2019: monitoring the paper. JJN and VMD supervised the study. All the authors have read the health for the SDGs, sustainable development goals. World Health manuscript and approved the final version to be published. Organization; 2019 [cited 2021 Apr 18]. Available from: https:// apps. who. int/ iris/ handle/1 0665/ 324835 Duodu et al. BMC Pregnancy and Childbirth (2022) 22:59 Page 13 of 14 5. Okedo‑Alex IN, Akamike IC, Ezeanosike OB, Uneke CJ. Determinants of 24. Nielsen RB, Seay MC. Complex Samples and Regression‑Based antenatal care utilisation in sub‑Saharan Africa: a systematic review. BMJ Inference: Considerations for Consumer Researchers. J Consum Aff. 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