Out-of-pocket costs and time spent attending antenatal care services: a case study of pregnant women in selected rural communities in Zinder, Niger

Background: Despite an official policy of exemption from health care costs, pregnant women in Niger still face some out-of-pocket costs (OPC) in addition to time costs when they attend antenatal care (ANC) services. We aimed to: 1) assess the OPC for pregnant woman attending ANC, 2) estimate the time spent to attend ANC and the opportunity cost of that time, and 3) assess how OPC and time spent to attend ANC affected ANC attendance. Methods: Data were obtained from a quasi-experimental descriptive study carried out in the region of Zinder, Niger, which compared pre- and post-intervention cohorts of pregnant women (n = 1736 women who reported attending ANC during their current pregnancy). An ANC attendance score was developed to describe the timing of ANC attendance in regard to the WHO recommendation of attending 4 ANC sessions. OPC and time spent were evaluated separately for associations with ANC attendance using Spearman correlations. Results: The mean (±SD) age of pregnant women was 25.0 ± 6.4 yr, 19.0% were ≤ 19 yr and 99.7% were in their second or third trimester of gestation at the time of the interview. Among those who were > 13 weeks and > 27 weeks of gestation, 4.0 and 74.4% had attended ANC during their first and second trimesters, respectively. The median (1st quartile (Q1), 3rd quartile (Q3)) ANC score was 0 (− 1, 0), reflecting that the majority of women failed to follow the WHO recommendation. More than half of the women (72.5%) experienced OPC related to ANC. The majority of women (> 80%) reported spending ~ 3 h for an ANC visit, including travel and waiting time. Time spent to attend ANC was not associated with ANC attendance score. Women who experienced OPC, and those who received iron folic acid (IFA) or long-lasting insecticide-treated bednets during an ANC visit, were more likely to have a higher ANC attendance score compared to those who did not. Conclusion: OPC and time spent were not identified as barriers to ANC visits, and IFA and long-lasting insecticide-treated bednets distribution could be used to motivate pregnant women to attend ANC. Trial registration: The NiMaNu project was registered at www.clinicaltrials.gov as NCT01832688. Registered 16 April 2013.

The Niger Maternal Nutrition (NiMaNu) project was designed as a quasi-experimental descriptive study conducted in the Zinder region of Niger. This project consisted of a baseline survey, a programmatic intervention and an endline survey, as described in detail elsewhere [21–24]. This project aimed to improve ANC services through programmatic interventions and used a multi-stage clustered sampling design to compare pre-and post-intervention cohorts of pregnant women. The aspects of the multi-level intervention were based on formative research [21] and consisted of community-based behavior change communication activities in each selected village, provision of supplies and essential drugs (including IFA supplements), and quality improvement activities at selected IHC. The primary outcomes of the main NiMaNu study were attending an adequate number of ANC consultations for gestational age (GA), reported adherence to recommended IFA supplementation, knowledge of the benefits of IFA, and prevalence of anemia [24]. In Niger, the health system in a district is organized at three levels: 1) health posts (HPs) provide very basic outpatient curative and preventive care and are staffed primarily by community health workers, 2) integrated health centers (IHCs) serve several villages, provide outpatient and inpatient care, including labor and delivery, and are staffed by nurses, midwives and sometimes physicians, and 3) a district hospital provides diagnostics services, outpatient and inpatient curative care, and caesarean sections, and receives patient referrals from IHCs [25, 26]. The project was implemented in two health districts in the Zinder region selected for convenience based on their seasonal accessibility, their distance to the town of Zinder and the small number of interventions with limited scope being implemented within their catchment area (i.e., to avoid overlapping interventions conducted in the same area). Within the two selected health districts, 18 rural IHCs out of 45 were selected based on convenience sampling and each IHC was randomly assigned to the order of enrollment. Within the catchment area of each IHC, the village in which the IHC was located was automatically included and nine additional villages were randomly selected according to the following scheme: first, among villages with a HP, one was randomly selected for inclusion. Second, among the remaining villages in the IHC catchment area, 4 villages ≤10 km and 4 villages > 10 km were randomly selected for inclusion. For both the baseline and endline surveys, pregnant women from the IHC and HP villages and the first two additional villages from the subsequent randomization were enrolled with a target of enrolling 16–20 women per village and a sample size of approximately 77 women per IHC. Participants were identified using a random walk method within each village [27], with the starting point randomly selected as either the mosque, market or primary school. A local guide accompanied the survey teams to help identify pregnant women during the random walk process. When the target number of women was not met in the first 4 villages of an IHC, women were included in sequential order from the remaining villages on the randomization list of that IHC. The enrollment of participants in the baseline survey was implemented continuously over a period of 18 months with approximatively one new IHC surveyed each month. Pregnant women irrespective of GA were eligible for study participation, provided they had resided in a participating village for at least 6 months prior to enrollment and had no plans to move out of the study area within the next 2 months. A woman was excluded if she had a severe illness warranting immediate hospital referral or was unable to provide consent due to impaired decision-making ability. As soon as the baseline survey was completed in an IHC, a multi-level programmatic intervention was implemented in that IHC and its catchment area, and the endline survey was rolled out 6 months after the completion of the baseline survey (in the first 12 IHCs only). The programmatic intervention included community-based behavior change communication activities in each selected village, provision of supplies and essential drugs (including IFA supplements), and quality improvement activities at selected IHC [24]. Two separate cohorts of women participated in the baseline and the endline survey, respectively. The baseline survey started in March 2014 and the endline survey started in November 2014, and both continued until September 2015. In each survey, pregnant women were interviewed twice, approximately 1 month apart, to collect socio-demographic information, anthropometric measurements (weight, height, mid-upper arm circumference (MUAC), symphysis-fundal height) and knowledge, attitudes and practices (KAP) related to IFA supplementation, diet and antenatal care (e.g., ANC attendance in the current pregnancy, OPCs of attending ANC, and time spent to attend ANC). Village and health center level information was collected through interviews with health center staff and/or head of villages. Gestational age: GA was assessed by asking each pregnant woman about the estimated number of months, lunar cycles and/or proximity to a religious or cultural event since she had her last menstrual period, if she already felt movements of the fetus in the current pregnancy and how long ago she first felt those movements, and two symphysis-fundal height measurements taken approximately 1 month apart. GA was then estimated based on the following obtained information: reported last menstrual period, time elapsed since the pregnant woman started to feel or perceive fetal movements, and the two symphysis-fundal height measurements. Methodological details are described elsewhere [28]. ANC attendance score based on GA: ANC attendance was assessed by asking each pregnant woman whether she attended ANC consultation at the IHC or HP or during outreach activities in the current pregnancy and the date she attended. The women’s responses were confirmed with their antenatal health booklet. Women were scored based on whether or not they had an ANC visit during each of four pregnancy intervals chosen based on the WHO ANC recommendation in place at the time of the present study [6]: first trimester: ≤13 weeks; second trimester: > 13 weeks to 27 weeks; first half of third trimester: > 27 weeks to 34 weeks; and second half of third trimester: > 34 weeks. For each interval, a woman received a score of 1 if she attended at least one ANC visit during that interval, and a score of − 1 if she did not attend ANC. If the woman’s fetal GA on the day of the interview was less than the end of the interval (i.e., woman had not yet completed that pregnancy interval) then she received a score of 0 for that interval, because she still had the opportunity to seek the recommended ANC in the respective period. The final ANC attendance score was calculated by adding these four scores together. Using a 3-value scale of − 1, 0 and 1 in each pregnancy interval differentiates those who attended a visit from those that did not, while also differentiating those whom may or may not attend their future visits. Additionally, we recalculated those scores according to the 2016 WHO recommendation of eight ANC contacts. Out-of-pocket costs per ANC visit attended during current pregnancy: OPC costs were assessed by asking women to report how much she spent to pay for transportation, to and from the health center for each ANC visit attended and health care-related expenses for the consultation, medications, and laboratory tests. OPC were calculated for each ANC visit attended based on the pregnant women’s reported costs of transportation, for an ANC visit and health care-related expenses. The cost data were collected in West African CFA (XOF). Time spent per ANC visit attended during current pregnancy: Time spent was assessed by asking each pregnant woman how much time she spent from the time she left her house until she returned and whether she used this time to accomplish other activities, if so what she did. Time spent was defined as the reported travel time to and from the site of ANC services plus the time spent in the health center while waiting for and receiving ANC and any related services. To calculate the opportunity cost of time, the variable “time spent to attend ANC”, which was collected as categorical variable, was converted into hours (i.e., a continuous variable) as follows: if a woman reported spending less than half day to attend ANC visit, she was considered having spent a mean (min, max) time of 3 (2, 4) hours; a half day was considered as a time of 6 (5, 7) hours; more than a half day, but less than 1 day, as a time of 9 (8, 10) hours; 1 day, a time of 12 (11, 13) hours; and 1 day and night, a time of 15 (14, 24) hours. Opportunity cost of time to attend ANC visit during current pregnancy: The opportunity cost of time to attend each ANC visit was the opportunity cost of wages foregone by the woman due to her health center visit. More specifically, the opportunity cost of time was equal to time spent to attend ANC multiplied by an estimated hourly wage. Previous reports from Maradi and Tahoua, two neighboring regions to Zinder, found that women who engaged in income-generating activities (IGAs) earned incomes ranging from 223 to 292 XOF (i.e., 0.37 to 0.48 United States dollars (USD) per day in Maradi; 1USD = 601.1615 XOF based on exchange rate on 31 December 2015) [29] and 1000 to 1500 XOF (i.e., 1.66 to 2.50 USD) per day in Tahoua, respectively [30, 31]. Because information on wage rate is extremely limited and because the majority of pregnant women reported being housewives in the present study (i.e. not paid or self-paid), we estimated that women worked 11 to 13 h per day and their daily earnings were in the range of daily earnings of women engaged in IGAs in Maradi and Tahoua (i.e. 223 to 1500 XOF). Based on the daily earnings of women engaged in IGAs in Maradi and Tahoua and an assumed minimum of 11 work hours per day, the hourly wage estimated for pregnant women in the present study was 20 to 136 XOF per hour (i.e., 0.033 to 0.23 USD). Indicators of household socio-economic status (SES), food security, and dietary diversity: Three proxy indices (household assets, household livestock, and housing quality) were developed to estimate SES using principal component analyses of available baseline household level indicators, including ownership of a set of assets, number of livestock, and home building materials, among others [32], as described in more detail previously [22]. Household food insecurity was assessed using the Household Food Insecurity Access (HFIA) categories [33]. Pregnant women’s dietary practices were assessed using a list-based food frequency questionnaire, and those who reported consuming at least five of ten defined food groups in the previous 24 h were considered to meet the Minimum Dietary Diversity for Women (MDD-W) [34]. The sample size of the main NiMaNu study was estimated to detect a difference of 10% in the prevalence of anemia as a primary outcome assuming a significance level of 0.05, power of 0.80, and a design effect of 2 [28]. The baseline and endline surveys enrolled different women with sample sizes of 1385 and 922, respectively. As previously presented [24], both cohorts of women differed in a few of their personal and household characteristics, such as the proportion of adolescent women, health facility delivery during last pregnancy, level of household food insecurity, principal occupation of the household head and season of enrolment in the survey (Supplemental Table 1). The intervention did not affect reported ANC attendance [24]; in addition there was no association between the variable “impact” indicating if a participant was enrolled in the baseline or in the endline survey and their ANC score, and no modification of the relationship between ANC score and OPC by the variable indicating if a participant was enrolled in the baseline or in the endline survey. Therefore, all available data from the baseline and endline surveys were combined in the present analysis for a sample size of 1736 women (75.2% of women surveyed) who reported having attended at least one ANC visit in their current pregnancy. This sample size provides high precision in estimation. Specifically, we can estimate the ANC attendance prevalence with precision of ±3.5% (95% CI) and the ANC attendance score with 95% confidence interval (CI) of ±0.05 standard deviation (SD). Statistical analyses were performed using the SAS System, version 9.4 (SAS Institute Inc., Cary, NC, USA). A detailed statistical analysis plan is available online [28]. Descriptive analysis of initial characteristics of study participants was performed. Any OPC for ANC visits attended during current pregnancy (yes or no), mean OPC of attended ANC visits per woman, and mean time spent for ANC visits per woman were tested separately for associations with the ANC attendance score based on the 2002 and 2016 WHO recommendation of at least four ANC visits and eight ANC contacts, respectively in minimally adjusted models including GA (in weeks) using Spearman correlations and in covariate adjusted models using partial Spearman correlations. As additional sensitivity analysis, the same test for association were repeated stratified by survey cohort. The partial Spearman correlation technique is a non-parametric analog to the covariate adjustment used in linear regression models to control for confounding. For each woman we first considered three different assumptions regarding her time spent per ANC visit attended (i.e., a mean, a minimum and a maximum value) and each of these values was used in the analysis. There was no variability in the relationship between time spent and ANC attendance score. Therefore, we decided to use the mean time spent in the analysis. The mean ANC attendance score was compared via ANCOVA in the group of women who experienced no OPC and the group of women with any OPC. This was completed for both minimally adjusted and adjusted analyses. In the sub-sample of women who reported any ANC related cost, we performed a sensitivity analysis by looking at the relationship between ANC attendance score and specific OPCs for consultation, transportation and exam; and we also looked at the relationship between OPC expenses in private clinics and ANC attendance score. Potential adjustment covariates were identified based on a literature review and background knowledge of the association of cost and time with ANC attendance [28], and were examined by performing bivariate analyses. These included individual characteristics (i.e., maternal age, education level, marital status, rank of the woman in a polygamous marriage, occupation, age at first pregnancy, number of pregnancies, number of living children, outcome of previous pregnancy (child born alive and still living, stillbirth and abortion), location of delivery during last pregnancy (health facility vs home), gestational age (in weeks), self-reported experience of any danger signs during the current pregnancy, and referral to health center because of low MUAC (< 23 cm) measured during enrollment), household level characteristics (i.e., household asset index, household livestock index and housing quality used as a proxy of household SES (with each index treated as binary variable i.e., above median vs at or below the median), household head’s education level, principal occupation of the household head, level of household food insecurity (HFIAS categories), receipt of food assistance (yes or no), environmental characteristics (season of enrollment), ANC visit characteristics (OPCs and time spent attending actual ANC visits), and receipt of IFA or insecticide-treated bed nets during ANC). Only covariates significantly associated with the ANC attendance score at a level of significance ≤0.1 were included in the covariate adjusted models.

• ouédraogo, césaire t.
• vosti, stephen a.
• wessells, k. ryan
• arnold, charles d.
• faye, m. thierno
• hess, sonja y.