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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 meeting 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 antenatal 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 maternal 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.
Women datasets from three waves of the Ghana Multiple Indicator Cluster Survey (GMICS) conducted in 2006, 2011 and 2017-2018 were analyzed for this study. The GMICS is a cross-sectional survey conducted by the Ghana Statistical Service (GSS) in association with the Ghana Health Service (GHS), Ministry of Health (MOH), and the Ministry of Education [21]. Funding and technical support were provided by the United Nations International Children’s Emergency Fund (UNICEF) and other international donors [21]. The main aim of the MICS surveys is to collect data on key indicators that assist countries to produce evidence for use in national development plans, policies, and programmes as well as assess the advancements towards the Sustainable Development Goals (SDGs) and other internationally-signed agreements [21]. Trained research enumerators were engaged to collect the data on behalf of GSS and UNICEF using a multi-stage stratified cluster sampling approach. This approach nationally surveyed women in urban and rural areas from the previous ten administrative regions in Ghana: Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East, and Upper West. The initial stage of data collection involved identifying and selecting enumeration areas based on the 2010 Population and Housing Census of Ghana. These enumeration areas became the primary sampling units. Next, in the second stage, households were listed from each of the selected enumeration areas and a sample of households was selected using systematic random sampling. This stage enabled the recruitment of reproductive-aged women from selected households. Data of 7795 women aged 15 to 49 years from all the three waves who had delivered 2 years prior to the data collection periods were included in this study. Antenatal care attendance is the main outcome variable for this study. This variable was extracted from a single-item survey question asking women who had given birth 2 years prior to the data collection about the number of times they attended antenatal care. Women were specifically asked, “How many times did you receive antenatal care during this pregnancy?” Women responded by providing a single number or range of numbers. For those who responded by giving a range, the minimum number was recorded as their answer. Guided by the WHO’s recommendation, these numbers were categorized under 4-scale response format: “none = 1”, “1-3 visits = 2”, “4+ visits = 3” and 8+ visits = 4″. We decided to collapse the none and “1-3 visits” into one category as “less than 4 visits” because only one woman did not attend ANC in the 2006 data. This categorization makes it easy for us to compare the models for the three data waves. Therefore, the newly created categories are as follows: “less than 4 visits (undesirable)=0”, “4 to 7 visits (adequate)=1” and 8+ visits (optimal) = 2″. Age of woman, education, polygyny status, wanted last-child, parity, death of a previous child, health insurance, household wealth index, urban-rural residence, and region of residence were treated as explanatory variables 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 variables were available in all the three datasets except for health insurance which was only available in the 2011 and 2017-2018 datasets. The variables were measured with single-item self-report questions and simple categorical response options. For instance, age of woman was measured with the question, “How old are you?” and participants responded by indicating their age in numbers which was later categorized by UNICEF. Health insurance was measured with the question, “Are you covered by any health insurance?” with response format comprising “Yes = 1” and “No = 2”. Education was measured by asking participants to respond to the question, “What is the highest level and grade or year of school you have attended?” with responses ranging from, “early childhood education=0” to “higher = 6”. We used the Variance Inflation Factor (VIF) to check for the assumptions of multicollinearity among the independent variables, and we have not observed any violations. Cross-tabulation between ANC visits and study variables in Ghana from 2006 to 2017-2018 433 (29.7) 330 (22.7) 733 (25.5) 320 (22.0) 642 (22.3) 103 (7.1) 391 (13.6) 165 (11.3) 293 (10.2) 264 (18.1) 572 (39.3) 321 (22.0) 619 (21.5) 301 (20.7) 527 (18.3) 371 (25.5) 773 (26.9) 335 (23.0) 637 (22.2) 347 (23.9) 621 (21.6) 277 (19.0) 517 (18.0) 211 (14.5) 530 (18.5) 154 (10.6) 306 (10.7) 112 (7.7) 279 (9.7) 177 (12.2) 451 (15.7) 103 (7.1) 214 (7.5) 195 (13.4) 327 (11.4) 222 (15.2) 511 (17.8) 115 (7.9) 258 (9.0) 278 (19.1) 321 (11.2) 61 (4.2) 120 (4.2) 112 (3.3) 40 (2.7) 85 (3.0) 88 (2.6) Data analyses began by cleaning and recoding variables of interest in STATA version 14. The GMICS predefined survey weights for the differential probability selection of sample were accounted for with the Taylor linearization technique [24, 25]. This procedure adjusted for the clustering, stratification, and design effects within the datasets. Univariable analyses were initially performed on all three waves of datasets by calculating frequencies and percentages of all the variables (see Table Table11 – second, sixth, and tenth columns). Secondly, simple Poisson regression was used to determine whether there was a significant trend in ANC visits over the three data waves (2006, 2011, 2018) (Additional file 1). Furthermore, bivariable analyses were performed with a chi-square test of independence to estimate the relationship between the explanatory variables and the outcome variable as presented in Table Table1.1. Lastly, multivariable analyses with robust multinomial logistic regression models were conducted, treating the “less than 4 visits” category in the outcome variable (antenatal care attendance) as the base. All the explanatory variables were independently (Table 2) and simultaneously (see Table 3) regressed onto the outcome variable, regardless of the statistical significance value in the bivariable analyses. The same processes were repeated for all the three datasets used in this study, setting the significance alpha level at 0.05. The relative risk ratio and the adjusted relative risk ratio were reported. Unadjusted multinomial logit model showing correlates of ANC visits in Ghana from 2006 to 2017-2018 1.3 [0.9, 1.8] 1.9** [1.3, 2.8] 1.5* [1.1, 2.2] 2.1*** [1.4, 3.2] 1.2 [0.9, 1.6] 1.7** [1.2, 2.5] 1.2 [0.8, 1.7] 1.5 [0.9, 2.3] 1.2 [0.8, 1.7] 1.1 [0.7, 1.8] 1.2 [0.8, 1.7] 1.3 [0.9, 2.0] 1.0 [0.7, 1.5] 1.1 [0.7, 1.8] 1.2 [0.8, 1.8] 2.7*** [1.8, 4.2] 0.852 [0.6, 1.2] 1.298 [0.8, 2.1] 2.2*** [1.5, 3.2] 3.8*** [2.5, 5.9] 1.9** [1.3, 3.0] 5.8*** [3.7, 9.2] 1.6** [1.1, 2.1] 2.8*** [1.8, 4.2] 4.0** [1.5,11.01] 17.7*** [6.6, 47.4] 4.6*** [2.0, 10.6] 25.3*** [11.1, 57.5] 2.0** [1.3, 3.3] 7.9*** [4.5, 13.6] 1.4 [0.9, 2.2] 2.0* [1.1, 3.6] 1.7* [1.0, 2.8] 1.5 [0.9, 2.5] 1.6** [1.2, 2.2] 1.8** [1.2, 2.6] 1.5 [0.9, 2.4] 1.1 [0.6, 2.0] 0.8 [0.5, 1.4] 0.3*** [0.2, 0.6] 1.3 [0.9, 1.9] 0.7 [0.4, 1.3] 0.5*** [0.4, 0.6] 0.4*** [0.2, 0.5] 0.7* [0.6, 0.9] 0.6** [0.4, 0.8] 0.7* [0.5, 0.9] 0.5*** [0.4, 0.8] 1.0 [0.7, 1.5] 1.3 [0.9, 2.0] 2.0** [1.3, 3.0] 2.9*** [1.9, 4.5] 1.1 [0.8, 1.5] 1.7** [1.2, 2.4] 1.4 [1.0, 2.1] 1.9** [1.2, 3.0] 1.0 [0.6, 1.6] 1.3 [0.8, 2.0] 1.2 [0.9, 1.8] 1.6* [1.1, 2.4] 0.7* [0.5, 1.0] 0.5*** [0.4, 0.8] 0.7 [0.5, 1.0] 0.5*** [0.3, 0.7] 0.8 [0.6, 1.1] 0.5*** [0.3, 0.7] 0.4*** [0.3, 0.6] 0.3*** [0.2, 0.5] 0.6*** [0.5, 0.8] 0.5*** [0.4, 0.7] 1.4 [0.9, 2.0] 1.8* [1.1, 3.0] 1.0 [0.7, 1.6] 2.7*** [1.6, 4.3] 1.4 [1.0,2.0] 1.4 [0.9, 2.1] 1.3 [0.9, 2.0] 2.2* [1.2, 4.1] 2.9*** [1.5, 5.3] 8.3*** [4.1, 16.5] 1.4 [0.9, 2.1] 1.8* [1.1, 2.9] 2.3** [1.4, 3.8] 7.6*** [4.2, 13.6] 2.7*** [1.5, 4.8] 13.4*** [7.6, 23.9] 2.7*** [1.7, 4.3] 5.7*** [3.5, 9.3] 6.4*** [2.7, 14.8] 43.7*** [17.7, 108.0] 9.1*** [3.8, 21.7] 84.0*** [34.6, 203.8] 4.3*** [2.2, 8.4] 14.6*** [7.6, 27.7] 0.5*** [0.3, 0.7] 0.2*** [0.1, 0.3] 0.4*** [0.2, 0.6] 0.2*** [0.1, 0.3] 0.6** [0.4, 0.8] 0.3*** [0.2, 0.4] 0.7 [0.3, 1.5] 0.2** [0.1, 0.6] 0.6 [0.2, 2.2] 0.2** [0.1, 0.6] 0.7 [0.4, 1.5] 0.8 [0.4, 1.5] 0.6 [0.3, 1.3] 0.2** [0.1, 0.6] 1.3 [0.4, 4.8] 0.3 [0.1, 1.1] 0.8 [0.4, 1.6] 0.4* [0.2, 0.9] 0.6 [0.3, 1.2] 0.1*** [0.0, 0.2] 1.0 [0.3, 3.7] 0.2** [0.0, 0.7] 0.5 [0.2, 1.0] 0.1*** [0.1, 0.3] 0.5* [0.2, 1.0] 0.1*** [0.1, 0.3] 2.4 [0.5, 10.8] 0.7 [0.2, 2.7] 0.6 [0.3, 1.3] 0.3*** [0.1, 0.5] 1.3 [0.6, 2.9] 0.6 [0.3, 1.4] 1.4 [0.4, 5.6] 0.7 [0.2, 2.3] 1.1 [0.5, 2.2] 0.4** [0.2, 0.8] 1.1 [0.5, 2.5] 0.2** [0.1, 0.6] 1.1 [0.3, 4.4] 0.2** [0.0, 0.6] 0.9 [0.4, 1.8] 0.4* [0.182, 0.8] 0.8 [0.4, 1.7] 0.2** [0.1, 0.6] 0.7 [0.2, 2.3] 0.1*** [0.0, 0.3] 0.8 [0.4, 1.5] 0.2*** [0.1, 0.4] 1.7 [0.7, 3.9] 0.8 [0.3, 2.0] 1.8 [0.5, 7.0] 0.2** [0.1, 0.6] 3.0* [1.3, 6.9] 1.5 [0.7, 3.5] 1.3 [0.7, 2.7] 0.34** [0.1, 0.6] 2.2 [0.6, 8.0] 0.2** [0.1, 0.7] 1.0 [0.5, 1.9] 0.2*** [0.1,0.4] Adjusted multinomial logit model displaying correlates of ANC visits in Ghana from 2006 to 2017-2018 1.1 [0.7, 1.6] 1.3 [0.7, 2.3] 2.1** [1.3, 3.4] 2.7** [1.5,4.9] 1.0 [0.7, 1.5] 1.5 [0.9, 2.5] 1.3 [0.8, 2.1] 1.9 [1.0, 3.8] 2.1** [1.2, 3.6] 2.5** [1.3, 5.1] 1.1 [0.7, 1.9] 1.7 [0.9, 3.0] 1.5* [1.0,2.4] 1.5 [0.9, 2.6] 1.043 [0.7, 1.6] 1.6 [0.9, 2.6] 0.9 [0.7, 1.3] 1.2 [0.7, 2.1] 3.1*** [2.0, 4.7] 3.5*** [2.1, 6.0] 1.3 [0.8, 2.1] 2.0* [1.1, 3.4] 1.5 [1.0, 2.2] 1.8* [1.1, 3.1] 4.1** [1.4, 12.0] 8.0*** [2.6, 24.5] 1.3 [0.5, 3.5] 2.2 [0.8, 6.0] 1.2 [0.7, 2.2] 2.3* [1.2, 4.5] 1.2 [0.7, 2.1] 1.7 [0.9,3.4] 2.1* [1.1, 3.9] 1.3 [0.7, 2.6] 1.4 [1.0, 2.1] 1.3 [0.8, 2.1] 1.5 [0.8, 2.8] 1.3 [0.6, 3.0] 1.3 [0.6, 2.5] 0.6 [0.3, 1.2] 1.3 [0.8, 2.1] 0.9 [0.5, 1.6] 0.5*** [0.4, 0.6] 0.3*** [0.2, 0.5] 0.6*** [0.5, 0.8] 0.4*** [0.3, 0.6] 0.8 [0.6, 1.0] 0.646* [0.5, 0.9] 0.9 [0.5, 1.6] 1.2 [0.6, 2.4] 3.0*** [1.6, 5.7] 2.9** [1.4, 5.8] 1.1 [0.7, 1.8] 1.6 [0.9, 2.9] 1.1 [0.7, 1.8] 1.2 [0.7, 2.2] 1.2 [0.7, 2.0] 1.0 [0.6, 1.8] 1.1 [0.7, 1.7] 1.1 [0.7, 1.8] 0.8 [0.6, 1.2] 0.7 [0.5, 1.1] 0.9 [0.6, 1.4] 0.8 [0.5, 1.4] 0.8 [0.5, 1.2] 0.6* [0.4, 1.0] 0.6** [0.4, 0.9] 0.5*** [0.3, 0.7] 0.7* [0.5, 0.9] 0.7* [0.5, 0.9] 1.5 [1.0, 2.3] 2.3** [1.3, 4.2] 1.0 [0.6, 1.7] 1.9* [1.1, 3.3] 1.6* [1.1, 2.3] 1.3 [0.8, 2.2] 1.3 [0.8, 2.1] 2.4* [1.1, 5.0] 2.6** [1.3, 5.2] 4.8*** [2.3, 10.2] 1.5 [0.9, 2.5] 1.4 [0.8, 2.5] 1.9 [1.0, 3.6] 6.0*** [2.7, 13.4] 2.3* [1.1, 4.8] 5.9*** [2.5, 13.9] 2.799*** [1.566,5.002] 4.001*** [2.208,7.251] 3.335* [1.251,8.893] 15.64*** [4.868,50.25] 7.3** [2.1, 25.2] 24.3*** [6.7, 87.8] 3.8** [1.7, 8.5] 5.9*** [2.6, 13.1] 0.6* [0.4, 1.0] 0.7 [0.4, 1.2] 0.6 [0.3, 1.2] 0.6 [0.3, 1.1] 0.9 [0.6, 1.4] 0.6* [0.4, 1.0] 1.3 [0.6, 3.0] 0.8 [0.3, 1.9] 1.9 [0.4, 9.4] 0.9 [0.2, 3.7] 1.1 [0.5, 2.4] 2.0 [0.9, 4.4] 1.3 [0.6, 2.9] 0.9 [0.4, 2.5] 3.5 [0.8, 16.1] 1.3 [0.4, 4.9] 1.1 [0.6, 2.3] 1.0 [0.4, 2.1] 1.4 [0.6, 3.3] 0.5 [0.2, 1.4] 3.1 [0.7, 14.6] 1.1 [0.3, 4.3] 0.9 [0.4, 1.9] 0.6 [0.2, 1.3] 0.9 [0.4, 2.0] 0.5 [0.2, 1.0] 5.7* [1.1, 29.6] 2.2 [0.5, 9.0] 1.0 [0.5, 1.9] 0.6 [0.3, 1.3] 2.364 [1.0, 5.6] 1.9 [0.8, 4.3] 3.8 [0.8, 18.7] 2.7 [0.6, 11.2] 1.4 [0.6, 2.8] 0.6 [0.3, 1.3] 2.2 [0.9, 5.4] 0.9 [0.3, 2.8] 3.7 [0.8, 17.8] 0.9 [0.2, 3.8] 1.4 [0.7, 2.9] 1.0 [0.5, 2.3] 2.7* [1.2, 6.3] 1.8 [0.7, 4.8] 2.6 [0.6, 12.1] 1.0 [0.3, 3.9] 1.7 [0.8, 3.6] 1.1 [0.5, 2.6] 6.4*** [2.5, 16.4] 9.7*** [3.6, 26.5] 7.7* [1.6, 37.5] 2.4 [0.6, 9.6] 6.6*** [2.5, 17.1] 7.3*** [2.6, 20.5] 5.8*** [2.6, 12.6] 3.4* [1.2, 9.5] 8.3** [1.8, 39.1] 2.0 [0.5, 7.9] 2.1 [1.0, 4.5] 0.9 [0.4, 2.2] Exponentiated coefficients; 95% confidence intervals in brackets. * p < 0.05, ** p < 0.01, *** p < 0.001. This study was performed following the Declaration of Helsinki and approved by the appropriate ethics committee. The original survey data utilized for this secondary data analysis study was collected by trained field enumerators on behalf of UNICEF and GSS. The MICS team of UNICEF-Ghana, The Ethical Review Board of the Ghana Health Service, and the Ghana Statistical Service approved the study that collected the original survey data. Therefore, ethics 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 survey data, informed consent was obtained from all the respondents. Adult verbal consents and child assents were obtained for the respondents younger than eighteen from their parents/guardians/adult household members to participate in the survey. Additionally, participants were assured of anonymity and confidentiality. More details regarding the data and ethical standards are available at: https://mics.unicef.org/surveys. All methods were performed in accordance with the relevant guidelines and regulations.
