Socio-demographic factors associated with early antenatal care visits among pregnant women in Malawi: 2004-2016.

INTRODUCTION: In 2016, the WHO published recommendations increasing the number of recommended antenatal care (ANC) visits per pregnancy from four to eight. Prior to the implementation of this policy, coverage of four ANC visits has been suboptimal in many low-income settings. In this study we explore socio-demographic factors associated with early initiation of first ANC contact and attending at least four ANC visits ("ANC4+") in Malawi using the Malawi Demographic and Health Survey (MDHS) data collected between 2004 and 2016, prior to the implementation of new recommendations.
METHODS: We combined data from the 2004-5, 2010 and 2015-16 MDHS using Stata version 16. Participants included all women surveyed between the ages of 15-49 who had given birth in the five years preceding the survey. We conducted weighted univariate, bivariate and multivariable logistic regression analysis of the effects of each of the predictor variables on the binary endpoint of the woman attending at least four ANC visits and having the first ANC attendance within or before the four months of pregnancy (ANC4+). To determine whether a factor was included in the model, the likelihood ratio test was used with a statistical significance of P< 0.05 as the threshold.
RESULTS: We evaluated data collected in surveys in 2004/5, 2010 and 2015/6 from 26386 women who had given birth in the five years before being surveyed. The median gestational age, in months, at the time of presenting for the first ANC visit was 5 (inter quartile range: 4-6). The proportion of women initiating ANC4+ increased from 21.3% in 2004-5 to 38.8% in 2015-16. From multivariate analysis, there was increasing trend in ANC4+ from women aged 20-24 years (adjusted odds ratio (aOR) = 1.27, 95%CI:1.05-1.53, P = 0.01) to women aged 45-49 years (aOR = 1.91, 95%CI:1.18-3.09, P = 0.008) compared to those aged 15-19 years. Women from richest socio-economic position ((aOR = 1.32, 95%CI:1.12-1.58, P<0.001) were more likely to demonstrate ANC4+ than those from low socio-economic position. Additionally, women who had completed secondary (aOR = 1.24, 95%CI:1.02-1.51, P = 0.03) and tertiary (aOR = 2.64, 95%CI:1.65-4.22, P<0.001) education were more likely to report having ANC4+ than those with no formal education. Conversely increasing parity was associated with a reduction in likelihood of ANC4+ with women who had previously delivered 2-3 (aOR = 0.74, 95%CI:0.63-0.86, P<0.001), 4-5 (aOR = 0.65, 95%CI:0.53-0.80, P<0.001) or greater than 6 (aOR = 0.61, 95%CI: 0.47-0.79, <0.001) children being less likely to demonstrate ANC4+.
CONCLUSION: The proportion of women reporting ANC4+ and of key ANC interventions in Malawi have increased significantly since 2004. However, we found that most women did not access the recommended number of ANC visits in Malawi, prior to the 2016 WHO policy change which may mean that women are less likely to undertake the 2016 WHO recommendation of 8 contacts per pregnancy. Additionally, our results highlighted significant variation in coverage according to key socio-demographic variables which should be considered when devising national strategies to ensure that all women access the appropriate frequency of ANC visits during their pregnancy.

Introduction

Following the ratification of the Millennium Development Goals in 2000, significant progress has been made in improving maternal and perinatal health internationally, demonstrated through a global 29% reduction in maternal deaths between 2000 and 2015 [1] and a 19% reduction in stillbirths in the same time period [2]. However, low-income countries (LIC) continue to experience disproportionately greater rates of maternal and perinatal mortality when compared to high income-countries (HIC) [1-4]. An estimated two-thirds of all maternal deaths in 2015 occurred in Sub-Saharan Africa, with the region experiencing a maternal mortality ratio (MMR) twice that of HIC and with latest data suggesting that geographic inequalities in maternal health continue to widen [1]. International and intraregional disparities in maternal health outcomes are, in part, attributable to the substantial variation in both coverage and uptake of key maternity services [5]. Antenatal care (ANC), the care of a woman and her foetus from conception until the onset of labour, is one such service in which coverage, especially within the first trimester of pregnancy, is particularly variable. Many LICs reporting higher MMR than the global average have low ANC coverage [6].

Since its inception in 2002, many LICs have adopted the World Health Organization’s (WHO) Focused Antenatal Care (FANC) model in which women are recommended to undertake at least four ANC visits during their pregnancy, at around weeks 12, 26, 32 gestation and between 36 and 38 weeks of gestation [7]. Whilst this model involves fewer visits per-pregnancy than models of care employed across HICs, both women’s attendance of their initial ANC visit within the first trimester and attending at least four visits (ANC4+) remains very low across the region of SSA [8]. Despite low uptake of ANC services under the FANC model, the WHO published recommendations in 2016, doubling the previous number of recommended ANC visits, now renamed as ‘contacts’, to eight within the duration of a woman’s pregnancy at 12, 20, 26, 30, 34, 36, 38 and 40 weeks of gestation [9]. These guidelines are supported by evidence from a number of trials which demonstrates that this model of care, more closely resembling contact-schedules employed across HICs, may lead to a reduction in perinatal death and improvements in women’s perception of care-quality when compared to the FANC model [10,11].

Malawi is one such country which, despite demonstrating progress in improving maternal outcomes since 2000 [12], continues to report women attend ANC both later and at a lesser frequency than recommended by the FANC model [13]. Pooled data from the Malawi Demographic and Health Surveys (MDHS) collected between 2000 and 2010 showed that only 10% of women accessed ANC within the first trimester and 49% of women achieved ANC4+ under the FANC model [13]. Ensuring both early access to ANC and ANC4+ for women in Malawi is important, as not only does ANC lead to improved maternal [10], newborn [14] and early childhood outcomes [15] but early initiation of ANC is positively associated with women attending both ANC4+ and attending at eight or more ANC visits in other settings [8]. Additionally, access to ANC is associated with improved probability that women will undergo facility-based delivery with the assistance of a skilled birth attendant, a vital service in improving maternal and perinatal health [16].

In this study we explore the social and demographic factors which are associated with women attending fourth contacts with her first visit occurring during or prior to 4 months gestation in Malawi between 2004 and 2016; we define this ‘ANC4+’. We have undertaken an analysis of MDHS data which was collected prior to publication of the WHO’s 2016 guidelines and adoption of these guidelines by the Malawian government. Whilst ours is not the first study to explore determinants or timeliness of ANC attendance in Malawi [13,17-20], our study is the first to include data collected as part of the 2015–2016 MDHS, the year prior to the implementation of the most recent WHO ANC guidelines. Our study is also the first to explore what factors are associated with both early initiation of ANC and attendance of four or more ANC visits through the use of a combined outcome variable. Therefore, this study is less likely to over-estimate the true proportion of women with ANC4+ visits since mostly the women with at least 4 ANC visits. Most women with at least four ANC visits but with first ANC visit was after five months tended to have pregnancy complications. In additional to socio-demographic factors we also explored the services that were accessed by the women during their ANC visits. Finally, we believe that the results of this study will provide vital insight into potential barriers for early initiation of ANC4+ visits in Malawi and other similar settings, providing key information to guide policy makers, clinicians or programme managers working in maternal and reproductive health.

Methods

Study design

We conducted a secondary analysis of the women’s questionnaire data collected from three Malawi Demographic and Health Surveys (MDHS) administered between 2004 and 2016 [21-23]. The Women’s Questionnaire is one of the four primary DHS survey questionnaires, accompanying the Household, Men’s and Biomarker Questionnaires, employed within the data collection process for the MDHS. This questionnaire is used to collect data from female participants on topics such as maternal and child health and healthcare use, contraception and women’s socio-economic status in the country of study. All women aged between 15–49 years are eligible for inclusion and any relevant participants are identified for recruitment via administration of the national Household Questionnaire. Within this study only those respondents who had given birth during in the preceding five years were included in the analysis.

Sampling procedure

The sampling frame used for the 2010 and 2015–16 MDHS is the frame of the Malawi Population and Housing Census (MPHC) conducted in Malawi in 2008 while the sampling frame for the 2004–5 MDHS was the 1998 MPHC provided by the Malawi National Statistical Office (NSO) [21-23] The sampling frame is a complete list of all census standard enumeration areas (SEAs) created for the 1998 or 2008 MPHC depending on the wave of the MDHS. A SEA is a geographic area that covers an average of 235 households. The sampling frame contains information about the SEA location, type of residence (urban or rural), and the estimated number of residential households.

The MDHS samples were stratified and selected in two stages. Each district was stratified into urban and rural areas; this yielded 56 sampling strata [21-23]. Sample of SEAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage point sampling [21-23].

Data management

We extracted and combined data from the 2004–5, 2010 and 2015–16 MDHS. We classified the variables as relating to external environment (rural/urban location, survey year, and region of residence), socio-demographics (age of the woman, household wealth index, education, marital status and number of children ever born), knowledge (frequency of listening to radio or watching television)) and enablers (permission to visit health services, money to pay for health services, distance to health facilities, presence of companion, and desire for pregnancy). We also extracted the tests performed during ANC visits (blood, urine and blood pressure) as well as the services that were received (Iron tablets for 90+ days, HIV testing and counselling, sulfadoxine-pyrimethamine (SP)/Fansidar for malaria prophylaxis) amongst the women that had ANC.

The primary outcome was whether or not women had four or more antenatal care visits with a skilled service provider, namely a doctor/medical officer, clinical officer, assistant clinical officer, or nurse/midwife, with the first visit occurring in or prior to the four months of pregnancy. This was the recommended ANC schedule at the time for all the observations in the dataset (i.e., 2004–2016). This analysis included women with their most recent birth within two years preceding each MDHS.

Statistical analysis

We calculated counts, weighted percentages, weighted odds ratios (OR) and their associated 95% confidence intervals (95%CI). We performed data management and analysis using Stata version 16 (Stata Corp., Texas, USA). The weighting variable from each of the MDHS was divided by 1000000 [24]. We further calculated the equal weights for each sample cluster and divided the average weight for each cluster by three (as data from three survey rounds being used together), as illustrated by Friedman and Jang in 2002 [25]. We conducted weighted univariate, bivariate and multivariable logistic regression analysis of the effects of each of the predictor variables on the binary endpoint of early initiation of ANC4+. Multiple weighted logistic regression models were used with a forward and back-ward step-wise selection method. To determine whether a factor was included in the model, the likelihood ratio test (LRT) was used with a statistical significance of P< 0.05 as the threshold.

Ethical considerations

The individual consent was conducted by National Statistical Office (NSO) of Malawi during the DHS 2004/2005, 2010 and 2015/2016. We obtained permission to use this data from the MEASURE DHS. The Malawi DHS datasets were downloaded from https://www.dhsprogram.com/data/available-datasets.cfm. Furthermore, this study was approved by the College of Medicine Research Committee (COMREC) in Blantyre, Malawi (protocol #: P.10/19/2820). As this study used secondary anonymised data, individual informed consent was not required.

Results

Characteristics of women included in this study

The characteristics of the women included in the study are shown in Table 1. A total of 26386 women were evaluated between 2004 and 2016. Of these 6012 (23%) were interviewed in 2004/5 MDHS; 10802 (41%) were interviewed in the 2010 MDHS while 9572 (36%) were interviewed in the 2015/16 MDHS. We observed variation in the proportions of women by age group, with an increasing trend from 15 to 29 years and a decreasing trend from 25 years to 49 years (see Table 1). The median age of the respondents was 26 years (interquartile range (IQR): 22–32). Between 2004 and 2016, the highest proportion of women had between 2 and 3 children previously (37%) while the lowest proportion of the women had six or more children (18%). The median number of previous children was 3 (IQR: 2–5). The majority of women had primary education while the minority had tertiary education (see Table 1). Almost 44% (11702 of 26386) were from households of poor socio-economic level and we observed a higher proportion of the households from poor socio-economic position.

Table 1

Characteristics of women interviewed during the Malawi Demographic and Health Surveys conducted between 2004 and 2016.

Characteristics	Total		2004–5		2010		2015–16
	Number	%	Number	%	Number	%	Number	%
Total	26386	100.0	6012	100.0	10802	100.0	9572	100.0
Age group
15–19	2671	10.0	602	9.7	997	9.0	1072	11.3
20–24	8212	31.4	2081	35.4	3118	29.4	3013	31.3
25–29	6542	24.9	1486	25.0	2903	26.8	2153	22.8
30–34	4507	16.9	894	14.4	1897	17.4	1716	17.9
35–39	2889	10.9	583	9.7	1221	11.2	1085	11.3
40–44	1176	4.4	273	4.4	491	4.6	412	4.3
45–49	389	1.4	93	1.4	175	1.6	121	1.3
Region
North	4506	15.1	746	12.4	1955	15.1	1805	16.7
Centre	9204	38.3	2247	40.1	3679	38.3	3278	37.3
South	12676	46.6	3019	47.5	5168	46.6	4489	46.0
Number of children ever born
1	5787	22.2	1284	21.4	2023	19.0	2480	26.2
2–3	9621	36.7	2212	37.3	3859	36.2	3550	37.0
4–5	6274	23.6	1376	22.7	2713	24.8	2185	22.8
6+	4704	17.5	1140	18.5	2207	20.1	1357	14.0
Education level
None	4274	16.1	1481	24.0	1711	15.9	1082	11.5
Primary	17753	67.1	3859	64.8	7517	69.0	6377	66.5
Secondary	4104	15.7	659	11.0	1507	14.4	1938	20.0
Tertiary	255	1.1	13	0.2	67	0.7	175	1.9
Wealth index quintile
Poorest	5768	21.9	1160	18.7	2439	22.3	2169	23.2
Poorer	5934	22.4	1392	23.2	2446	22.4	2096	22.0
Middle	5670	21.3	1389	23.4	2428	22.1	1853	19.1
Richer	4968	18.6	1183	19.7	2030	18.6	1755	18.0
Richest	4046	15.8	888	14.9	1459	14.6	1699	17.7
Residence
Urban	3240	12.9	655	11.2	1037	11.1	1548	16.0
Rural	23146	87.1	5357	88.8	9765	88.9	8024	84.0
Sources of antenatal care knowledge
Frequency of listening to radio
Less than once a week	13571	52.0	2146	35.4	4767	44.7	6658	70.3
At least once a week	12815	48.0	3866	64.6	6035	55.3	2914	29.7
Frequency of watching television
Less than once a week	24136	91.4	5732	95.5	9762	90.0	8642	90.6
At least once a week	2250	8.6	280	4.5	1040	10.0	930	9.4
Barriers to access antenatal care
Permission to visit health services
No problem	23076	87.2	5490	91.5	9524	87.9	8062	83.8
Big problem	3310	12.8	522	8.5	1278	12.1	1510	16.2
Money to pay for health services
No problem	11893	44.6	2157	35.4	4948	46.1	4788	48.6
Big problem	14493	55.4	3855	64.6	5854	53.9	4784	51.4
Distance to health facilities
No problem	10910	41.4	2224	36.7	4274	40.6	4412	45.2
Big problem	15476	58.6	3788	63.3	6528	59.4	5160	54.8
Presence of companion
No problem	18762	70.6	4411	73.7	7380	67.8	6971	71.9
Big problem	7624	29.4	1601	26.3	3422	32.2	2601	28.1
No drugs at health facility
No problem	13473	49.7	6012	100.0	4253	38.5	3208	31.4
Big problem	12913	50.3	0	0.0	6549	61.5	6364	68.6
No female provider
No problem	20981	79.3	5158	86.1	8419	77.4	7404	77.2
Big problem	5405	20.7	854	13.9	2383	22.6	2168	22.8
Marital status
Never married	871	3.3	138	2.2	281	2.6	452	4.7
Married	22522	85.4	5257	87.7	9311	86.3	7954	83.1
Widowed	445	1.7	113	2.0	185	1.7	147	1.5
Divorced	2548	9.6	504	8.1	1025	9.5	1019	10.7

% = weighted percentage.

Eighty-seven percent of the women were from rural areas while twelve percent were from the urban areas, and more women were interviewed from rural areas (see Table 1). Although 12815 of 26386 listened to radio between 2004 and 2016, we observed a decreasing trend from 65% in 2004/5 to 30% in 2015/16. Overall, the majority of women (24136 of 26386) did not watch a television (TV) for more than once a week but the numbers watching TV increased from 5% in 2004/5 to 10% in 2015/16. Over the 2004 to 2016 surveys, women cited different barriers for them to access ANC and these barriers had different trends. The major barriers were long distance to health facilities (59% of 26386) and lack of money to use in accessing health services (55% of 26386). Across the survey populations, the majority of the women were married while the lowest proportion were widowed (see Table 1).

Factors associated with early antenatal care of at least four visits

Distribution of women by number of ANC visits

The distribution of women by number of ANC visits is shown in Table 2. Of the 26386, 7449 (28%) of the women had attended early initiation of ANC4+. We observed increasing trends in the proportion of women with early initiation of ANC4+ from 21% in 2004/5 to 37% in 2015/16 (P<0.001). The proportion of women with early initiation of ANC4+ decreased with increasing number of children ever born (see Table 2). The women from richest households (35%) had the highest coverage of early initiation of ANC4+ compared to those from the poorest households (25%). The rural women were less likely to demonstrate early initiation of ANC4+ than the urban women (see Table 2).

Table 2

Distribution of women by number of antenatal care visits in Malawi between 2004 and 2016.

Characteristics	Total				2004–5				2010				2015–16
	<4 ANC		ANC4+		<4 ANC		ANC4+		<4 ANC		ANC4+		<4 ANC		ANC4+
	n	%	n	%	n	%	n	%	n	%	n	%	n	%	n	%
Total	18937	71.9	7449	28.1	4755	78.7	1257	21.3	8199	76.0	2603	24.0	5983	63.2	3589	36.8
Age group
15–19	1931	72.6	740	27.4	467	76.7	135	23.3	735	74.4	262	25.6	729	68.9	343	31.1
20–24	5857	71.4	2355	28.6	1613	77.2	468	22.8	2348	75.3	770	24.7	1896	63.3	1117	36.7
25–29	4678	71.7	1864	28.3	1197	80.4	289	19.6	2182	75.0	721	25.0	1299	61.3	854	38.7
30–34	3244	72.2	1263	27.8	723	80.1	171	19.9	1472	78.0	425	22.0	1049	61.9	667	38.1
35–39	2077	71.8	812	28.2	461	77.8	122	22.2	938	76.3	283	23.7	678	63.6	407	36.4
40–44	877	74.7	299	25.3	222	82.0	51	18.0	384	79.0	107	21.0	271	65.0	141	35.0
45–49	273	71.4	116	28.6	72	78.2	21	21.8	140	82.5	35	17.5	61	50.5	60	49.5
Region
North	3180	70.7	1326	29.3	588	77.9	158	22.1	1462	75.3	493	24.7	1130	62.8	675	37.2
Centre	6541	71.5	2663	28.5	1804	80.1	443	19.9	2707	74.1	972	25.9	2030	63.0	1248	37.0
South	9216	72.6	3460	27.4	2363	77.7	656	22.3	4030	77.8	1138	22.2	2823	63.5	1666	36.5
Number of children ever born
1	3905	67.3	1882	32.7	951	73.3	333	26.7	1435	70.8	588	29.2	1519	61.6	961	38.4
2–3	6909	72.1	2712	27.9	1762	79.6	450	20.4	2937	76.2	922	23.8	2210	63.0	1340	37.0
4–5	4586	73.6	1688	26.4	1128	81.3	248	18.7	2091	77.5	622	22.5	1367	64.2	818	35.8
6+	3537	75.0	1167	25.0	914	79.9	226	20.1	1736	78.8	471	21.2	887	65.0	470	35.0
Education level
None	3267	76.7	1007	23.3	1206	81.4	275	18.6	1337	79.0	374	21.0	724	67.1	358	32.9
Primary	12893	72.7	4860	27.3	3065	79.1	794	20.9	5767	76.7	1750	23.3	4061	64.3	2316	35.7
Secondary	2678	65.6	1426	34.4	478	71.1	181	28.9	1061	70.6	446	29.4	1139	59.8	799	40.2
Tertiary	99	39.9	156	60.1	6	32.7	7	67.3	34	50.5	33	49.5	59	36.0	116	64.0
Wealth index quintile
Poorest	4323	75.1	1445	24.9	954	82.2	206	17.8	1939	79.8	500	20.2	1430	66.5	739	33.5
Poorer	4309	72.8	1625	27.2	1111	79.1	281	20.9	1873	77.1	573	22.9	1325	63.9	771	36.1
Middle	4110	72.7	1560	27.3	1103	79.1	286	20.9	1820	75.3	608	24.7	1187	64.6	666	35.4
Richer	3563	71.7	1405	28.3	925	77.9	258	22.1	1533	75.0	497	25.0	1105	63.7	650	36.3
Richest	2632	65.4	1414	34.6	662	73.9	226	26.1	1034	70.9	425	29.1	936	55.8	763	44.2
Residence
Urban	2108	67.3	1132	32.7	491	74.8	164	25.2	751	73.2	286	26.8	866	56.6	682	43.4
Rural	16829	72.8	6317	27.2	4264	79.0	1093	21.0	7448	76.4	2317	23.6	5117	64.4	2907	35.6
Sources of antenatal care knowledge
Frequency of listening to radio
Less than once a week	9740	71.9	3831	28.1	1765	81.8	381	18.2	3692	77.8	1075	22.2	4283	64.7	2375	35.3
At least once a week	9197	71.9	3618	28.1	2990	77.0	876	23.0	4507	74.6	1528	25.4	1700	59.7	1214	40.3
Frequency of watching television
Less than once a week	17503	72.7	6633	27.3	4550	78.9	1182	21.1	7444	76.5	2318	23.5	5509	64.5	3133	35.5
At least once a week	1434	63.5	816	36.5	205	73.0	75	27.0	755	72.0	285	28.0	474	50.6	456	49.4
Barriers to access antenatal care
Permission to visit health services
No problem	16620	72.1	6456	27.9	4357	78.9	1133	21.1	7250	76.2	2274	23.8	5013	62.9	3049	37.1
Big problem	2317	70.4	993	29.6	398	76.7	124	23.3	949	74.8	329	25.2	970	64.8	540	35.2
Money to pay for health services
No problem	8303	70.2	3590	29.8	1668	76.7	489	23.3	3728	75.8	1220	24.2	2907	61.3	1881	38.7
Big problem	10634	73.3	3859	26.7	3087	79.7	768	20.3	4471	76.2	1383	23.8	3076	64.9	1708	35.1
Distance to health facilities
No problem	7674	70.6	3236	29.4	1720	76.7	504	23.3	3258	76.4	1016	23.6	2696	61.9	1716	38.1
Big problem	11263	72.8	4213	27.2	3035	79.8	753	20.2	4941	75.8	1587	24.2	3287	64.3	1873	35.7
Presence of companion
No problem	13428	71.8	5334	28.2	3487	78.6	924	21.4	5625	76.3	1755	23.7	4316	62.9	2655	37.1
Big problem	5509	72.1	2115	27.9	1268	78.7	333	21.3	2574	75.4	848	24.6	1667	64.0	934	36.0
No drugs at health facility
No problem	9991	74.2	3482	25.8	4755	78.7	1257	21.3	3246	76.1	1007	23.9	1990	62.7	1218	37.3
Big problem	8946	69.7	3967	30.3	0	0.0	0	100.0	4953	76.0	1596	24.0	3993	63.4	2371	36.6
No female provider
No problem	15046	71.8	5935	28.2	4090	78.8	1068	21.2	6391	76.1	2028	23.9	4565	62.2	2839	37.8
Big problem	3891	72.3	1514	27.7	665	77.8	189	22.2	1808	75.8	575	24.2	1418	66.4	750	33.6
Marital status
Never married	629	73.7	242	26.3	110	80.2	28	19.8	213	74.9	68	25.1	306	71.1	146	28.9
Married	16134	71.7	6388	28.3	4146	78.4	1111	21.6	7057	75.9	2254	24.1	4931	62.4	3023	37.6
Widowed	330	74.1	115	25.9	92	80.2	21	19.8	144	78.2	41	21.8	94	64.1	53	35.9
Divorced	1844	73.1	704	26.9	407	80.6	97	19.4	785	77.4	240	22.6	652	65.4	367	34.6

<4 ANC = Less than four early antenatal care (ANC) visits.

ANC4+ = At least four ANC visits prior to six months of first ANC visit.

% = weighted percentage.

Crude odds ratios of women having early antenatal care of at least four visits

The crude odds ratios for early initiation of ANC4+ are presented in Table 3. There was increasing trend in the odds of women demonstrating early initiation of ANC4+ from 2004 to 2016 (P<0.001). There was a decreasing trend in the odds in early initiation of ANC4+ with the number of children ever born (Table 3). Watching TV was associated with higher likelihood of ANC4+ (OR = 1.53, 95%CI: 1.31–1.79, P<0.001).

Table 3

Bivariate and multivariate odds ratios for factors associated with attending at least four or more antenatal care visits prior to prior to six months of first antenatal care visit in Malawi, 2004–2016.

Characteristics (n = 26386)	Bivariate analysis		Multivariate analysis
	OR (95%CI)	P-value	OR (95%CI)	P-value
Age group
15–19	1.00		1.00
20–24	1.06 (0.90–1.26)	0.49	1.27 (1.05–1.53)	0.01
25–29	1.05 (0.88–1.25)0.59	0.22	1.44 (1.15–1.81)	0.002
30–34	1.02 (0.85–1.23)	0.82	1.49 (1.15–1.93)	0.003
35–39	1.04 (0.85–1.28)	0.69	1.64 (1.22–2.20)	0.001
40–44	0.90 (0.68–1.18)	0.44	1.51 (1.05–2.16)	0.02
45–49	1.06 (0.70–1.61)	0.77	1.91 (1.18–3.09)	0.008
Year
2004/5	1.00		1.00
2010	1.16 (1.02–1.33)	0.025	1.15 (1.01–1.32)	0.04
2015/16	2.15 (1.89–2.45)	<0.001	2.03 (1.78–2.32)	<0.001
Region
North	1.00
Centre	0.96 (0.84–1.11)	0.56
South	0.91 (0.79–1.04)	0.18
Number of children ever born
1	1.00		1.00
2–3	0.80 (0.71–0.90)	<0.001	0.74 (0.63–0.86)	<0.001
4–5	0.74 (0.65–0.85)	<0.001	0.65 (0.53–0.80)	<0.001
6+	0.69 (0.59–0.80)	<0.001	0.61 (0.47–0.79)	<0.001
Education level
None	1.00		1.00
Primary	1.23 (1.08–1.41)	0.003	1.10 (0.95–1.28)	0.19
Secondary	1.72 (1.46–2.03)	<0.000	1.24 (1.02–1.51)	0.032
Tertiary	4.95 (3.20–7.66)	<0.001	2.64 (1.65–4.22)	<0.001
Wealth index quintile
Poorest	1.00		1.00
Poorer	1.12 (0.97–1.30)	0.11	1.14 (0.98–1.31)	0.09
Middle	1.13 (0.98–1.31)	0.10	1.15 (1.00–1.34)	0.06
Richer	1.19 (1.02–1.38)	0.023	1.16 (0.99–1.35)	0.06
Richest	1.60 (1.37–1.86)	<0.001	1.32 (1.12–1.58)	<0.001
Residence
Urban	1.00
Rural	0.72 (0.63–0.83)	<0.001
Sources of antenatal care knowledge
Frequency of listening to radio
Less than once a week	1.00
At least once a week	1.00 (0.91–1.10)	1.00
Frequency of watching television
Less than once a week	1.00
At least once a week	1.53 (1.31–1.79)	<0.001
Barriers to access antenatal care
Permission to visit health services
No problem	1.00
Big problem	1.09 (0.95–1.25)	0.23
Money to pay for health services
No problem	1.00
Big problem	0.86 (0.78–0.94)	0.001
Distance to health facilities
No problem	1.00
Big problem	0.90 (0.82–0.99)	0.028
Presence of companion
No problem	1.00
Big problem	0.99 (0.89–1.09)	0.80
No drugs at health facility
No problem	1.00
Big problem	1.25 (1.14–1.37)	<0.001
No female provider
No problem	1.00
Big problem	0.98 (0.87–1.09)	0.67
Marital status
Never married	1.00
Married	1.11 (0.85–1.45)	0.45
Widowed	0.98 (0.62–1.55)	0.94
Divorced	1.03 (0.76–1.40)	0.85

OR = weighted odds ratios of attending at least four antenatal care (ANC) visits prior to six months of first ANC visit.

95%CI = 95% Confidence Interval.

Adjusted odds ratios of women having early antenatal care of at least four visits

The adjusted odds ratios for early initiation of ANC4+ are presented in Table 3. The likelihood of women having early initiation of ANC4+ varied by age, survey year, number of children ever born to the woman, education level and wealth index quintile. After adjusting for age, number of children ever born to the woman, education level and wealth index quintile; there was an increasing trend in the likelihood of having early initiation of ANC4+ by year of survey. Women who were wealthier, and more educated, and married were more likely to have had early initiation of ANC4+ (see Table 3). On the other hand, women with more children were less likely to have reported early initiation of ANC4+ visits.

Services received by antenatal care women

The services accessed by women that attended ANC in Malawi are shown in Fig 1. The proportion of women that had a blood sample taken for full blood count increased from 32% in 2004/5 to 91% in 2015/16 (Chi-Square P <0.001). Similarly, there was increasing trend in the proportion of women with urine test from 18% in 2004/5 to 32% in 2015/16 (P<0.001). We also observed an increasing trend in the proportion of ANC women that were given at least two doses of Fansidar/SP for malaria prophylaxis from 79% in 2004/5 to 91% in 2015/16 (P<0.001). The percentage of women that had HIV testing at ANC increased from 0% in 2004/5 to 92% in 2010 and 88% in 2015/16. There was an increase in the proportion of women with blood pressure measurement from 73% in 2004/5 to 82% in 2015/16. We observed increasing trend in the percentage of women that received iron tablets from 80% to 92% (see Fig 1).

Fig 1

Services received by women that attended antenatal care in Malawi between 2004 and 2016.

SP = Sulfadoxine-Pyrimethamine, % = weighted percentage.

Timing of antenatal care visits

The median time of presenting for the first ANC care was 5 months (IQR: 4–6). Over the time period, there is strong evidence of association between timing of first ANC visit by survey year (P<0.001). The proportion of women with less than four ANC visits varied by survey year and month of first ANC visit. In general, the proportion of women with less than four ANC visits was the highest in 2010 while the least was observed in 2004.

The characteristics of women with at least four ANC visits regardless of the timing of the first ANC visit are shown in Table 4. A total of 12738 women had at least 4 ANC visits regardless of timing of their first visit. Of these, 9353 (74%) started ANC after the fourth month of pregnancy. Between 2004 and 2016, we observed a decreasing trend in the proportion of women with who attended their first ANC visit after four months from 88% in 2004/5 to 61% in 2015/16. There was increasing trend in proportion of women with late attendance of ANC by parity (see Table 4). However, increasing level of education was associated with increasing trend in the proportion of women with early attendance of ANC from 21% amongst those with no education to 52% amongst those with tertiary education.

Table 4

Distribution of women with at least four antenatal care visits by the socio-demographic characteristics of the women in Malawi between 2004 and 2016.

Characteristics	ANC attendance for women with ANC4+
	Early		Late
	n	%	n	%
Total	3385	26.0	9353	74.0
Age group
15–19	327	26.4	888	73.6
20–24	1046	26.5	2867	73.5
25–29	870	25.9	2371	74.1
30–34	581	26.4	1604	73.6
35–39	373	25.5	1035	74.5
40–44	133	22.8	444	77.2
45–49	55	26.2	144	73.8
Year
2004/5	405	12.1	2957	87.9
2010	1081	22.5	3507	77.5
2015/16	1899	39.1	2889	60.9
Region
North	674	30.2	1523	69.8
Centre	1158	25.0	3396	75.0
South	1553	25.5	4434	74.5
Number of children ever born
1	834	27.5	2151	72.5
2–3	1255	26.9	3297	73.1
4–5	771	25.3	2233	74.7
6+	525	23.1	1672	76.9
Education level
None	417	21.3	1541	78.7
Primary	2224	25.9	6177	74.1
Secondary	645	28.1	1545	71.9
Tertiary	99	52.0	90	48.0
Wealth index quintile
Poorest	691	27.7	1807	72.3
Poorer	678	23.9	2139	76.1
Middle	708	25.1	1988	74.9
Richer	637	25.8	1803	74.2
Richest	671	28.0	1616	72.0
Residence
Urban	527	28.0	1268	72.0
Rural	2858	25.7	8085	74.3
Sources of antenatal care knowledge
Frequency of listening to radio
Less than once a week	1805	28.1	4486	71.9
At least once a week	1580	24.0	4867	76.0
Frequency of watching television
Less than once a week	2982	25.5	8515	74.5
At least once a week	403	30.8	838	69.2
Barriers to access antenatal care
Permission to visit health services
No problem	2934	25.6	8247	74.4
Big problem	451	29.0	1106	71.0
Money to pay for health services
No problem	1716	28.4	4158	71.6
Big problem	1669	24.1	5195	75.9
Distance to health facilities
No problem	1530	27.1	3914	72.9
Big problem	1855	25.2	5439	74.8
Presence of companion
No problem	2454	26.0	6720	74.0
Big problem	931	26.0	2633	74.0
No drugs at health facility
No problem	1532	21.9	5277	78.1
Big problem	1853	30.5	4076	69.5
No female provider
No problem	2717	25.9	7556	74.1
Big problem	668	26.5	1797	73.5
Marital status
Never married	102	25.8	274	74.2
Married	2903	25.8	8079	74.2
Widowed	46	22.2	170	77.8
Divorced	334	28.5	830	71.5

% = weighted percentage.

Discussion

The primary aim of this study was to explore the social and demographic factors associated with early initiation of ANC4+ in women in Malawi between 2004 and 2016 using MDHS data from three nationally representative surveys. Most studies exploring the factors associated with ANC uptake have not taken into account the month of the first ANC visit in calculating the distributions of women with ANC4+ visits. To our knowledge, this is the first study in Malawi that has analysed the likelihood of a pregnant woman having early initiation of ANC4+ visits. Whilst attendance of ANC4+ has often been a focus of ANC service use research in SSA, both early attendance for the first ANC visit and undertaking the recommended number of visits per-pregnancy are important for pregnancy outcomes. Early initiation of ANC allows healthcare workers to improve both maternal and perinatal outcomes by undertaking screening and tests that are more efficacious in early pregnancy, including accurate gestational dating or screening for maternal anaemia [9]. Identification of these complications early allows for the appropriate management for the length of pregnancy to improve outcomes. It is equally important that women also undertake visits for the length of their pregnancy, not only so indicated screening and treatment can continue, but to prepare women for birth and potential complications of delivery, which can lead to increased likelihood of women seeking facility delivery [26].

The results of this study provide vital insight into how coverage of ANC4+ changed during this time period and may highlight potential barriers that could be faced whilst rolling-out the updated WHO eight ‘contact’ ANC model, through identification of which women are at risk of attending ANC too late and at an insufficient frequency. However, it should be noted that whilst early initiation of ANC is significantly associated with attendance of ANC4+ and ANC8+ in other LMIC settings [8], other socio-demographic determinants of ANC8+ in Malawi may not be consistent with those found in this study due to increased time commitment and possible associated costs of attending an increased number of visits. Additionally, the focus of this study is limited to individual-level socio-demographic factors and their influence on early initiation of ANC4+. As we outline below, we are unable to fully explore the effect of other key determinants of health care seeking such as quality of care on ANC attendance as this is not suitably captured within the datasets we used for our analysis.

Significant predictors of early initiation of ANC4+ attendance, determined through our analysis and discussed below, included maternal factors (number of children ever born, age, marital status) and socio-economic factors (wealth quintile and education status). The positive relationship between higher wealth and education status and increased likelihood of early initiation of ANC4+ highlight considerable inequalities present in ANC attendance in the population. Our results demonstrate that women are significantly more likely to have initiated ANC4+ early in 2015 than in 2004 (21% of women in 2004 vs 37% of women in 2015). Similarly, women who received care were more likely to receive key interventions during their ANC as we found substantial increases in the coverage of essential interventions between 2004 and 2016 including undertaking full blood counts, performing urine dipsticks to detect bacteremia and/or pre-eclampsia, malaria prophylaxis and HIV testing suggesting an overall improvement in quality of ANC services. Whilst this is promising, only 37% of women surveyed in 2015 had initiated ANC4+ early. With the sub-optimal number of women attending the ANC4+, the implementation of the at least eight ANC visits in settings like Malawi may not be feasible as echoed by authors of studies analyzing coverage of ANC in other LIC settings [8].

We have reported a number of key determinants of early initiation of ANC4+ in this study. Increasing number of children ever born was associated with a reduced likelihood of ANC4+, with those women who have delivered more than 5 children being the least likely to undergo early initiation of ANC4+ visits. These findings are largely consistent with literature both in Malawi [13] and across SSA [27] and other LIC with high MMR [13]. It is plausible that women who have given birth and accessed these services before, possibly multiple times, are less likely to seek care as they feel that they are equipped with sufficient knowledge to proceed without formal maternity care. Additionally, the quality of maternity care women receive in Malawi remains variable, with some women reporting extensive stock outs and reception of treatment that lacked dignity or respect [28]. Although we infer quality of ANC service, we did not have data on quality of ANC services as such data were not collected by the MDHS. Women who have experienced poor quality may be less likely to seek care again, something that may happen with increasing frequency as number of children ever born increases. The relationship between increasing number of children ever born and reduced access to services is not unique to ANC but is present across other essential maternal and child health services both in Malawi and a number of countries with higher fertility rates [28]. The link between higher order births and increased risk of maternal and perinatal mortality is well described in the literature and it is possible that the inverse relationship between number of children ever born and service-use may be a contributing factor in this phenomenon [29].

Interestingly, whilst increasing number of children ever born was found to be associated with a reduced likelihood of early initiation of ANC4+, the opposite appears true regarding age, as women aged between 45 and 49 in our study population were nearly twice as likely to attend ANC4+ earlier than the youngest mothers after adjusting for number of children ever born and other factors. Whilst this association has been supported by findings from a number of studies exploring coverage of ANC, it has not been universally reported in the literature [27]. Older age does seem to affect care-seeking for other maternity services with older nulliparous women more likely to access facility delivery than their younger counterparts in a number of SSA regions [30].

Factors pertaining to a woman’s socio-economic status, namely wealth quintile and level of education were found to be associated with early initiation of ANC4+ in this study. Women in the highest wealth quintile and those who had undertaken tertiary education were more likely to have initiated ANC early than their counterparts. The associations between both education and wealth level and maternal care seeking are similarly well documented in SSA and is not limited to access to ANC [13,27,31]. Despite women from lower wealth quintiles being least likely demonstrate early initiation of ANC4+ services provided through both public and Christian mission (CHAM) facilities in Malawi have been exempt from user-fees, and therefore free at the point of use, since 2004. This suggests that out-of-pocket payments provided to healthcare workers when accessing services is unlikely to explain the relationship between wealth level and the primary outcome. This relationship however could be explained by other costs associated with accessing services such as transportation. Initial exemption of user-fees following the initialization of service-level agreement between the Malawian Ministry of Health and CHAM facilities lead to increased utilization of maternity services in CHAM facilities [32]. However, in Tanzania cost was found to be a barrier for accessing ANC services [33].

Our study does have several limitations. Whilst the combined outcome variable capturing early attendance and complete attendance of the FANC model may be useful in determining who is more likely to engage successfully with ANC services, we were unable to assess the quality of these visits which may have impacted on a woman’s propensity to seek further care. Additionally, the results for any variable captured in the MDHS survey at the time of administration may differ from the result at the time of last pregnancy and birth (i.e., changes in wealth or education over time). Similarly, time lag between administration and last birth may make survey responses vulnerable to recall bias and, as with all survey data, data captured in the MDHS is self-reported and subject to reporting bias, such as social desirability bias. We also recognize that the important factors which might influence ANC such as hypertension, diabetes and previous HIV status prior to the current pregnancy were not captured in the MDHS hence these were not included in this analysis. Finally, although HIV status being captured in the MDHS, there is no information on the timing of the HIV status to the pregnancy.

Conclusion

In conclusion, whilst coverage of early initiation of ANC4+ and key ANC interventions in Malawi have increased significantly since 2004, there remains inequality in determinants of access to early initiation of ANC4+. Key socio-economic factors (education and and wealth) continue to impact women’s likelihood of accessing these vital services and in 2016, just over a third of women surveyed were undertaking the recommended number of visits under the FANC model with the first ANC visit initiated early. Ensuring that all women are able to engage with ANC services at the appropriate point in their pregnancy and at the correct frequency will require consideration of the impact of inequality on how women engage with ANC services.

(ZIP)

Click here for additional data file.

7 Apr 2021

PONE-D-21-03728

Socio-demographic factors associated with early antenatal care visits among pregnant women in Malawi: 2004-2016

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Additional Editor Comments:

This manuscript covers a relevant topic for reduction of maternal and neonatal mortality and morbidity in Malawi. The authors took 3 publicly available community surveys datasets from Malawi and conducted a secondary analysis to determine what variables are associated with the earlier initiation of antenatal care (ANC) and attendance of four or more ANC visits. They use a new and useful way of combining these two outcomes together by counting 4 or more only if the woman did the first ANC visit in the first trimester of gestation and attended by a skilled provider. This way it avoids overestimation of the true proportion of women with 4 or ANC visits since women initiating ANC visits after the first trimester tend to have multiple visits due to complications. They define a binary outcome ANC4+ according to this definition. For the analysis, they appended the 3 community surveys datasets into one dataset with 26,386 records and conducted univariate and multiple logistic regressions.

I must comment the authors for the really well writing.

Issues:

1. The authors state that they used survey weights as they were offered in the dataset. This would be fine if the analysis of each survey was done separately. And then do some combination of those estimates. But here, apparently the analysis was done as if we had weights of just one survey. This is problematic. Please explain what was done to the weights prior to their use into the models.

2. As one of the reviewers comment below the main outcome here is a combination of the two other outcomes (earlier initiation of antenatal care, and attendance of four or more ANC visits). These captures different goals and the second outcome has the problem of change in policy over time.

3. Line 131 put space between primary and outcome.

4. Line 138. Stata is not an acronym. So do not write STATA write please Stata. See Official Stata documentation.

5. In the limitations or in discussion in general please point out that there was a change in the requirement of minimal ANC visits over the course of these surveys.

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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Reviewer #1: Well written research - from justification, to methods and conclusion. I would like to suggest the following:

1. The underlying premise/assumption should be made clear and mentioned; women when instructed by health professionals to have 4 visits that their performance will be the same/projected to be the same when they are recommended to have 8 ANC visits. This may not be necessarily true.

2. It is important to address the socio-demographic factors in the discussion as "markers" for health professionals to pick up and potentially provide a "person-centered approach" in health management to ensure that maximum health services offered given the socio-economic constraints

3. "watching TV`' is a proxy to wealth and do not find it useful to highlight it as a finding for any use. Health care providers will be less likely to ask client if she watched TV as part of clinical encounter and similarly this will not be considered for health policy action. Would suggest to drop this variable.

4. Question: Are the health services really "free"? Often, in countries where this is stated, there are other expenses paid during a health visit. I would suggest not to rule this out and consider transport costs as the only limiting factor.

5. The authors touched on briefly the "Quality of Care" and "respectful care" - these elements are often very much related to setting, low quality (lower levels of care with potentially stock outs) and respect issues with low paid/unsupervised/unregualted health professionals in rural/low socio-economic settings. This needs further elaboration in the discussion and needs to mentioned that this was not part of data

6. SSA acronym missing in list of abbreviations

7. Conclusion section should not only address policy makers/program managers. Please see point 2.

Otherwise congratulations to research team for this manuscript!

Reviewer #2: The paper is relevant and touches on an important aspect of maternal and child health. The following are my comments:

General comment: Correct any spelling errors, eg line 234/235 should read “of a pregnant woman” and not “of a pregnant women”.

Methods: provide a description of the study area.

Reviewer #3: The authors modelled socio-demographic factors associated with early initiation (within four months of pregnancy) of first ANC contact and attending at least four ANC visits (ANC4+) in Malawi using data collected in 2004, 2010, and 2016 Malawi Demographic and Health Survey (MDHS) health surveys. These ANC data were collected before 2016 WHO revised recommendations of increasing the number of antenatal care (ANC) visits per pregnancy from four to eight. The outcome variable was binary on attending at least 4 ANC visits, with a first visit occurring during or before 4 months gestation. A binary regression was used to ascertain association with several purported factors. Predictors were included in the model based on their univariate association having a likelihood ratio test at less than P< significant level. The paper is well written and researched and add base knowledge on the uptake of modern ANC care. However, I have several concerns about data description and statistical elements.

a) There is clarity of the numbers of women interviewed for the ain survey and the women who and a pregnancy/birth in the last two years of the surveys, which is the same used here. Please could you add a column showing the number of women who were pregnant in the last two years versus the number of women interviewed for the respective main surveys as an indication of external validity.

b) The sample weights in the respective surveys were valid and benchmarked to a survey. Once the data are combined, you can not use the original weights since the circumstances have changed, the weight will need to reduce. Thus, please could adjusting the weights in the combined data set.

c) Two outcomes are combined: early ANC initiation and number of ANC visits. I think the two serve different though similar purposes in ANC care; the first helps to early problems detection and managing them during the pregnancy time; the second for measuring and monitoring pregnant woman contact with skilled health personnel. So would rather you analyse three outcomes: early ANC visit, ANC4, and combined.

d) What using a cut pint of 8 ANC, will Malawi have already passed the new 2016 recommendations? Or rather at the rate, when will Malawi achieve this? Then how will you advise the MoH in Malawi?

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Reviewer #1: Yes: Wisal Mustafa Hassan Ahmed

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Reviewer #3: Yes: Samuel Manda

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4 Jun 2021

Additional Editor Comments:

This manuscript covers a relevant topic for reduction of maternal and neonatal mortality and morbidity in Malawi. The authors took 3 publicly available community surveys datasets from Malawi and conducted a secondary analysis to determine what variables are associated with the earlier initiation of antenatal care (ANC) and attendance of four or more ANC visits. They use a new and useful way of combining these two outcomes together by counting 4 or more only if the woman did the first ANC visit in the first trimester of gestation and attended by a skilled provider. This way it avoids overestimation of the true proportion of women with 4 or ANC visits since women initiating ANC visits after the first trimester tend to have multiple visits due to complications. They define a binary outcome ANC4+ according to this definition. For the analysis, they appended the 3 community surveys datasets into one dataset with 26,386 records and conducted univariate and multiple logistic regressions.

I must comment the authors for the really well writing.

Issues:

1. The authors state that they used survey weights as they were offered in the dataset. This would be fine if the analysis of each survey was done separately. And then do some combination of those estimates. But here, apparently the analysis was done as if we had weights of just one survey. This is problematic. Please explain what was done to the weights prior to their use into the models.

RESPONSE: Thank you for your comment. As you mention above, the original weights were calculated separately for each survey round of the DHS and stored as the weighting variable V005. As instructed by the DHS program, this variable was divided by 1000000 to come up with the sample weight used in the analysis. Our analytical approach follows the standards recommended by the DHS program for DHS data analysis, which we have now referenced within the manuscript.

We set the data to incorporate the weights using the STATA command: svyset [pw=wgt], psu(PSU). For regression models we used importance weights as implemented in this code for the final model: xi: logit anc i.age_gr i.region i.ceb i.edlev i.windex i.year i.radfreq i.mstatus[iw=wgt], or. It should also be noted that we stratified the analysis by year for all the tables except Table 3 and Table 4. In Table 3 we assessed the effect of the year on the outcome hence we did not stratify the analysis. In Table 4 we aimed to show the proportion of women presenting early or late amongst all the women with at least 4 ANC visits.

2. As one of the reviewers comment below the main outcome here is a combination of the two other outcomes (earlier initiation of antenatal care, and attendance of four or more ANC visits). These captures different goals and the second outcome has the problem of change in policy over time.

RESPONSE: Thank you for this comment. We agree that that early initiation of ANC and ‘complete’ ANC attendance are different yet interrelated outcomes when evaluating access to ANC services. Considering ANC4+ in isolation does not provide sufficient insight into the distribution of visits across the entire pregnancy. Similarly, whilst we believe early attendance of ANC1 is associated with ‘complete’ ANC attendance, using early attendance as the sole primary outcome does not capture the coverage of later, and equally important, visits during pregnancy.

Both early initiation and ‘complete’ attendance of the ANC scheduled are important, undoubtedly for different reasons, and therefore combining them into one primary outcome provides a more accurate representation of access to ANC in this setting. We have highlighted in our introduction why we feel it is important that women attend both early and complete ‘set’ of visits in lines (81-87). “ Ensuring both early access to ANC and ANC4+ for women in Malawi is important, as not only does ANC lead to improved maternal [10], newborn [14] and early childhood outcomes [15] but early initiation of ANC is positively associated with women attending both ANC4+ and attending at eight or more ANC visits in other settings [8]. “

Regarding the effect of policy change over time, our analysis uses data that was collected prior to the adoption of the 8-contact schedule in Malawi therefore we are only able to focus on understanding what access to ANC4 was prior to the policy change. We agree that understanding determinants of ANC8+ is obviously a very important and pertinent research question within Malawi but this is outside the remit of this paper (and the current availability of national data) and we feel that our analysis is still important in evaluating women’s access of services prior to the adoption of a new policy.

3. Line 131 put space between primary and outcome.

RESPONSE: Thank you for highlighting we have now revised accordingly

4. Line 138. Stata is not an acronym. So do not write STATA write please Stata. See Official Stata documentation.

RESPONSE: Thank you for highlighting we have now revised accordingly

5. In the limitations or in discussion in general please point out that there was a change in the requirement of minimal ANC visits over the course of these surveys.

RESPONSE: Thank you for your comment. As highlighted above data collection for the 2015-2016 DHS occurred prior to the publication of the WHO recommendations for 8 ANC contacts in 2016. Therefore, these recommendations had not been adopted by the Malawian government during the data collection period. We have added a sentence to our introduction to clarify this: lines 99-100: “. We have undertaken an analysis of MDHS data which was collected prior to publication of the WHO’s 2016 guidelines and adoption of these guidelines by the Malawian government.”

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Declarations

We declare that there is no conflict of interest in publishing this paper. The authors would like to thank the MEASURE DHS for granting access to use the datasets for Malawi. Funding for the project was provided by UK Research and Innovation (UKRI) through the GCRF Thanzi la Onse (Health of All) research programme (MR/P028004/1). During the study period, WN, JC, TC, AP, TM, JMB, PR and TBH worked for on the project. The funder had no role in the study design, data collection and analysis, decision to publish, or the presentation of the manuscript.

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Reviewer #2: Yes

Reviewer #3: Yes

________________________________________

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

________________________________________

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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5. Review Comments to the Author

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Reviewer #1: Well written research - from justification, to methods and conclusion. I would like to suggest the following:

1. The underlying premise/assumption should be made clear and mentioned; women when instructed by health professionals to have 4 visits that their performance will be the same/projected to be the same when they are recommended to have 8 ANC visits. This may not be necessarily true.

RESPONSE: Thank you for your comment. We agree that there are a number of complex socio-demographic and health system factors which influence women’s attendance of a prescribed ‘set number’ of ANC contacts which may vary when changing the primary outcome from 4 contacts to 8.

As these data were collected before the initiation of 2016 ‘8 contacts’ WHO recommendation we are unable to determine if there are common determinants of attending ANC4+ and ANC8+ in Malawi. However, we are fairly confident that in other low- and middle-income country settings early initiation of ANC has a significant impact on a woman’s likelihood on attending 4+ or 8+ visits as referenced in the introduction of our paper (Jiwani et al. 2020- reference 8 in manuscript reference list). As our primary outcome incorporates timely initiation of ANC it may be reasonable to assume that the determinants of our primary outcome could also affect likelihood of attending 8+ visits, although this would require further study.

We have added these clarifications to the second paragraph of our discussion, lines 261-271:

“The results of this study provide vital insight into how coverage of ANC4+ changed during this time period and may highlight potential barriers that could be faced whilst rolling-out the updated WHO eight ‘contact’ ANC model, through identification of which women are at risk of attending ANC too late and at an insufficient frequency. However, it should be noted that whilst early initiation of ANC is significantly associated with attendance of ANC4+ and ANC8+ in other LMIC settings [8], other socio-demographic determinants of ANC8+ in Malawi may not be consistent with those found in this study due to increased time commitment and possible associated costs of attending an increased number of visits.”

2. It is important to address the socio-demographic factors in the discussion as "markers" for health professionals to pick up and potentially provide a "person-centered approach" in health management to ensure that maximum health services offered given the socio-economic constraints

RESPONSE: Thank you. Whilst we agree in the need for consideration of socio-demographic factors in health management we feel that through our discussion we provide ample exploration of the importance of the variables that we have found to impact access to services. We feel that providing detailed direction on how to incorporate these factors into service management is outside of the remit of this paper.

3. "watching TV`' is a proxy to wealth and do not find it useful to highlight it as a finding for any use. Health care providers will be less likely to ask client if she watched TV as part of clinical encounter and similarly this will not be considered for health policy action. Would suggest to drop this variable.

RESPONSE: We have removed this sentence from the abstract as agree it is not worth highlighting given it will not be considered directly for health policy action. As you mention “watching TV” is a proxy for wealth therefore we retain it in our analysis, also because studies conducted in similar settings included this variable under exposure to media (Rwabilimbo et al 2020, reference 32 of manuscript) and including such a variable therefore enhances comparability of the study findings under these settings.

4. Question: Are the health services really "free"? Often, in countries where this is stated, there are other expenses paid during a health visit. I would suggest not to rule this out and consider transport costs as the only limiting factor.

RESPONSE: Thank you, we agree that in this, and other similar settings there is certainly a number of unmeasured costs associated with accessing health services. In Malawi, as we highlight in our discussion, health services are provided free of charge through the public sector but the patient pays their own transport to and from the health facility, we now have highlighted in-text that this may be a factor that affects decision to seek care: lines 340-343: “This suggests that out-of-pocket payments provided to healthcare workers when accessing services is unlikely to explain the relationship between wealth level and the primary outcome. This relationship however could be explained by other costs associated with accessing services such as transportation.”

Through our multivariate analysis, as seen in Table 3, we found no independent effect of women’s perception that ‘money to pay for health services’ or ‘distance to health facility’ being a ‘big problem’ when accessing services on our primary outcome.

5. The authors touched on briefly the "Quality of Care" and "respectful care" - these elements are often very much related to setting, low quality (lower levels of care with potentially stock outs) and respect issues with low paid/unsupervised/unregualted health professionals in rural/low socio-economic settings. This needs further elaboration in the discussion and needs to mentioned that this was not part of data

RESPONSE: Thank you for your comment. The focus of our study is purely on individual level socio-demographic factors on early initiation of ANC4+ in Malawi and we have taken care to ensure this is made clear, for instance in the titling of our manuscript and through the description of our methods. We agree that there are many other factors, including actual and perceived quality of service provision, that will impact individual’s propensity to seek care and that they have not been explored in this paper. We have added to our discussion to clarify that we are unable to explore the effect of variables related to quality of care on care seeking and that these variables likely have a significant effect at line (256-258).

“Additionally, the focus of this study is limited to individual-level socio-demographic factors and their influence on early initiation of ANC4+. As we outline below, we are unable to fully explore the effect of other key determinants of health care seeking such as quality of care on ANC attendance as this is not suitably captured within the datasets we used for our analysis.”

6. SSA acronym missing in list of abbreviations

RESPONSE: Thank you for highlighting this, we have now included SSA in the list of abbreviations.

7. Conclusion section should not only address policy makers/program managers. Please see point 2.

RESPONSE: Thank you. We agree that policy makers/program managers are not that only target audience for this paper and have amended our conclusion accordingly.

Otherwise congratulations to research team for this manuscript!

RESPONSE: Thank you very much!

Reviewer #2: The paper is relevant and touches on an important aspect of maternal and child health. The following are my comments:

General comment: Correct any spelling errors, eg line 234/235 should read “of a pregnant woman” and not “of a pregnant women”.

RESPONSE: Thank you for highlighting this, we have made the correction and thoroughly checked through our manuscript for spelling errors.

Methods: provide a description of the study area.

RESPONSE: The study involves all the 28 districts of Malawi. More details are provided in the manuscript from line 108 to 121.

Reviewer #3: The authors modelled socio-demographic factors associated with early initiation (within four months of pregnancy) of first ANC contact and attending at least four ANC visits (ANC4+) in Malawi using data collected in 2004, 2010, and 2016 Malawi Demographic and Health Survey (MDHS) health surveys. These ANC data were collected before 2016 WHO revised recommendations of increasing the number of antenatal care (ANC) visits per pregnancy from four to eight. The outcome variable was binary on attending at least 4 ANC visits, with a first visit occurring during or before 4 months gestation. A binary regression was used to ascertain association with several purported factors. Predictors were included in the model based on their univariate association having a likelihood ratio test at less than P< significant level. The paper is well written and researched and add base knowledge on the uptake of modern ANC care. However, I have several concerns about data description and statistical elements.

a) There is clarity of the numbers of women interviewed for the aim survey and the women who and a pregnancy/birth in the last two years of the surveys, which is the same used here. Please could you add a column showing the number of women who were pregnant in the last two years versus the number of women interviewed for the respective main surveys as an indication of external validity.

RESPONSE: Thank you very much for the compliment. The MDHS only captures detailed information on the most recent birth (in the 24 months prior to the survey) and no other births were captured. We therefore feel we would not be able to accurately generate a column in table one which detailed the number of women who were pregnant in the survey year as requested above. Through the sampling frame employed by the MDHS we feel that the sample from which our data has been taken provides a representative sample of the population of Malawi and suitably demonstrates the external validity of our methodology.

b) The sample weights in the respective surveys were valid and benchmarked to a survey. Once the data are combined, you can not use the original weights since the circumstances have changed, the weight will need to reduce. Thus, please could adjusting the weights in the combined data set.

RESPONSE: The weights were specific for each survey round and our analysis did not change. All we did as shown in Table 1, we stratified the analysis by survey year and pooled the results as well. As for the regression analysis, we used importance weights and included the variable year as an explanatory variable.

c) Two outcomes are combined: early ANC initiation and number of ANC visits. I think the two serve different though similar purposes in ANC care; the first helps to early problems detection and managing them during the pregnancy time; the second for measuring and monitoring pregnant woman contact with skilled health personnel. So would rather you analyse three outcomes: early ANC visit, ANC4, and combined.

RESPONSE: Thank you for your comment. We agree that both early initiation of ANC and ‘complete’ attendance of ANC (i.e. 4 visits) are important outcomes when evaluating access to ANC services in any setting. We also feel that the combination of these outcomes into one primary outcome, as is the methodology of our analysis in this manuscript, provides a novel analysis of DHS data which we believe provides a better indication of ‘complete’ coverage of ANC as its captures these two key outcomes as interrelated and equally important in coverage of services.

As we have highlighted above in response to the editors comments we feel that previous analyses which use four or more ANC visits as the primary outcome have only evaluated the proportion of women attending four ANC visits regardless of timing of the first ANC visit- we felt this was inadequate within our analysis for the reasons described above.

Therefore, we do not feel that separating the primary outcome into its composite parts (early initiation, ANC4) as you suggest here would add to our analysis as our primary aim was to ascertain the proportion of women for which both of these outcomes are true. We note that kind words of the editor in their description of our primary outcome as “a new and useful way of combining these two outcomes together by counting 4 or more only if the woman did the first ANC visit in the first trimester of gestation and attended by a skilled provider. This way it avoids overestimation of the true proportion of women with 4 or ANC visits since women initiating ANC visits after the first trimester tend to have multiple visits due to complications”. In addition please note that in table 4 you are able to see the proportion of women who attend ANC4+ stratified by early or late initiation of ANC1.

d) What using a cut pint of 8 ANC, will Malawi have already passed the new 2016 recommendations? Or rather at the rate, when will Malawi achieve this? Then how will you advise the MoH in Malawi?

RESPONSE: Whilst we agree that this is certainly a vital research question in its own right we feel that this is outside of the remit of the analysis within this current manuscript and we would be unable to draw accurate conclusions or predictions about this using the MDHS data, which was collected before the policy of 8 ANC visits started. Our analysis does show that the ‘complete’ ANC attendance was lower than recommended by the FANC policy in place in Malawi at the time and therefore we do highlight in the conclusion section that this may mean that Malawi is less likely to achieve high coverage of ANC8 as coverage of ANC4 was low prior to policy change.

________________________________________

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Reviewer #1: Yes: Wisal Mustafa Hassan Ahmed

Reviewer #2: No

Reviewer #3: Yes: Samuel Manda

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13 Jul 2021

PONE-D-21-03728R1

Socio-demographic factors associated with early antenatal care visits among pregnant women in Malawi: 2004-2016

PLOS ONE

Dear Dr. Ng'ambi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Additional Editor Comments:

Major issue:

The authors seem to have misunderstood the message about the weights. The current description of the weights use is for just a single survey procedure. When there is a combination of surveys the weights must be corrected. Please do see the comments from the reviewer bellow. And please add the details of such weighting procedure in the statistical analysis section.

Minor issues:

Abstract

- Put the the ORs and 95%CI for the factors you mention in the results

- There still “STATA” instead of “Stata” in the abstract.

Line 91 “..” corect to be “.”

Methods

- There is nowhere in this manuscript a description of what women are included in the analysis. Line 105 says it is a secondary analysis of the women’s questionnaire data. Not many readers of PlosONE will know what is this questionnaire. Please state briefly what women are included in the survey (women with a pregnancy in the last 5 years prior to the survey, for example). Such statement should be added to the abstract as well.

Results

- Table 1 and 2 are using weights? Please add footnote explaining that.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #3: Yes

**********

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Reviewer #1: Yes

Reviewer #3: Yes

**********

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Reviewer #1: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #3: Thanks to the authors for attending to the revision of their paper. I am largely satisfied but there a few clarifications which they may want to consider, and hopefully, make the paper better.

a) On the question of the number of women having a most recent birth (in the 24 months before the survey); in my previous comments, I was pointing to having a column indicating the overall number of women aged 15-49 interviewed for the main survey vs the women having a most recent birth (in the 24 months before the survey). For example, in there a total of 11,698 women (15-49) were interviewed for the main questionnaire vs 6012 (51%%). Also, the captions of Tables 1 and 2 may be misleading at first sight because it talks of women interviewed, rather than women with a recent birth (24 months before the survey). Thus, if one puts a column on Table 1 indicating the number of women from which this sample came, e.g. 2,407 women in the age group 15-19 vs 602 analyzed here, etc.

b) I applaud that the authors in accounting for the design of the surveys by way of weighted analyses. And in most surveys, designs weights are combined with missing data and non-response. However, when analyzing combined data of multiple MDHS datasets, individual survey weights would need to be adjusted correctly to represent a case in the combined data sets. See for example.

�  Alexander, C. H. (2002). Still Rolling: Leslie Kish's ‘Rolling Samples’ and The American Community Survey. Survey Methodology, 28:1, 35-41

�  Friedman, E.M., Jang, D. & Williams T.V. (2002) Combined estimates from four quarterly survey data sets. Proceedings of the American Statistical Association Joint Statistical Meetings - Section on Survey Research Methods, pp.1064-1069. Alexandria, VA: American Statistical Association.

c) On the question of 8+ ANC visits, one could use it as sensitivity analysis.

**********

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Reviewer #1: Yes: Wisal Mustafa Hassan Ahmed

Reviewer #3: No

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25 Aug 2021

Response to Editor Comments

1.) “The authors seem to have misunderstood the message about the weights. The current description of the weights use is for just a single survey procedure. When there is a combination of surveys the weights must be corrected. Please do see the comments from the reviewer bellow. And please add the details of such weighting procedure in the statistical analysis section.”

Thank you for highlighting this. We have amended the weighting procedure as directed and made changes to the manuscript accordingly. Please see response to reviewer three for a detailed description of our actions.

2.) “Put the ORs and 95%CI for the factors you mention in the results”

Thank you, we have now added the ORs and 95% CI for all results that are reported in the abstract. Changes can be seen at lines 34-44, as indicated by highlighting. In addition, we have added that the results for the primary outcome into the abstract as well as seen at line 35.

3.) “There still “STATA” instead of “Stata” in the abstract.”

Thank you for highlighting. This has been amended as show at line 25.

4.) “Line 91 “..” correct to be “.””

Thank you for highlighting. This has been amended as show at line 99.

5.) “Methods - There is nowhere in this manuscript a description of what women are included in the analysis. Line 105 says it is a secondary analysis of the women’s questionnaire data. Not many readers of PlosONE will know what is this questionnaire. Please state briefly what women are included in the survey (women with a pregnancy in the last 5 years prior to the survey, for example). Such statement should be added to the abstract as well.”

We have now amended the manuscript to include a description of the survey sample in both the abstract, at line 25-27, and in the main text at line 115 - 122.

6.) “Results - Table 1 and 2 are using weights? Please add footnote explaining that.”

Thank you for highlighting. We have now added footnotes to all tables and figures to show that weights were used in calculating proportions/percentages and odds ratios.

Response to Reviewer Comments

a) On the question of the number of women having a most recent birth (in the 24 months before the survey); in my previous comments, I was pointing to having a column indicating the overall number of women aged 15-49 interviewed for the main survey vs the women having a most recent birth (in the 24 months before the survey). For example, in there a total of 11,698 women (15-49) were interviewed for the main questionnaire vs 6012 (51%%). Also, the captions of Tables 1 and 2 may be misleading at first sight because it talks of women interviewed, rather than women with a recent birth (24 months before the survey). Thus, if one puts a column on Table 1 indicating the number of women from which this sample came, e.g. 2,407 women in the age group 15-19 vs 602 analyzed here, etc.

Thank you for the clarification of your previous comment. We feel that addition of the column may not be of any value as such women to be included in the other column did not have a recent birth of whom their antenatal care is being assessed in terms of healthcare seeking behaviour.

Additionally, we have updated the titles of table 1 and 2 to more accurately reflect their contents, in this case that they refer exclusively to women who delivered in the past five years of the survey.

b) I applaud that the authors in accounting for the design of the surveys by way of weighted analyses. And in most surveys, designs weights are combined with missing data and non-response. However, when analyzing combined data of multiple MDHS datasets, individual survey weights would need to be adjusted correctly to represent a case in the combined data sets. See for example.

Thank you very much for the direction regarding the survey weights and for providing additional sources that we were able to use to strengthen our analysis. We have now employed an equal weights approach as heighted in Friedman et al (2002). We have provided a description of our methods at line 149 and added Friedman et al’s paper to the reference list at number 25.

Following this weight approach we found that ‘frequency of watching television’ which was significant in the previous analysis is no longer significant factor in the presence of other variables. Further, different percentages as shown by Tables and Figures also changed. Please refer to the Tables and Figures for more details on the change.

c) On the question of 8+ ANC visits, one could use it as sensitivity analysis.

As for 8+ ANC, we had 513 (2% of 26,234) women who had at least 8 ANC visits. We did not perform the sensitivity analysis since the numbers are small and a future analysis should examine this after when the recommendations have been in place for longer.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

25 Jan 2022

Socio-demographic factors associated with early antenatal care visits among pregnant women in Malawi: 2004-2016

PONE-D-21-03728R2

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31 Jan 2022

PONE-D-21-03728R2

Socio-demographic factors associated with early antenatal care visits among pregnant women in Malawi: 2004-2016

Dear Dr. Ng'ambi:

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