How maternity waiting home use influences attendance of antenatal and postnatal care

As highlighted in the International Year of the Nurse and the Midwife, access to quality nursing and midwifery care is essential to promote maternal-newborn health and improve survival. One intervention aimed at improving maternal-newborn health and reducing underutilization of pregnancy services is the construction of maternity waiting homes (MWHs). The purpose of this study was to assess whether there was a significant change in antenatal care (ANC) and postnatal care (PNC) attendance, family planning use, and vaccination rates before and after implementation of the Core MWH Model in rural Zambia. A quasi-experimental controlled before-and-after design was used to evaluate the impact of the Core MWH Model by assessing associations between ANC and PNC attendance, family planning use, and vaccination rates for mothers who gave birth to a child in the past 13 months. Twenty health care facilities received the Core MWH Model and 20 were identified as comparison facilities. Before-and-after community surveys were carried out. Multivariable logistic regression were used to assess the association between Core MWH Model use and ANC and PNC attendance. The total sample includes 4711 mothers. Mothers who used the Core MWH Model had better ANC and PNC attendance, family planning use, and vaccination rates than mothers who did not use a MWH. All mothers appeared to fare better across these outcomes at endline. We found an association between Core MWH Model use and better ANC and PNC attendance, family planning use, and newborn vaccination outcomes. Maternity waiting homes may serve as a catalyst to improve use of facility services for vulnerable mothers. A quasi-experimental controlled before-and-after design was used to assess associations between ANC and PNC attendance, family planning use, and vaccination rates for mothers who gave birth to a child in the past 13 months. Mothers birthed in 40 healthcare facilities in three provinces (Eastern, Luapula, and Southern) and seven districts (Chembe, Choma, Kalomo, Lundazi, Mansa, Nyimba, and Pemba) that were part of the SMGL initiative [24–26]. Twenty health care facilities received the minimum Core MWH Model and 20 were identified as comparison facilities [24, 25]. Population-level data were collected before implementation of the Core MWH Model in 2016 and after implementation in 2018. Specific details outlining the research methodology and survey are described in previous publications [23–25]. Institutional review board (IRB) ethical approval was obtained from the University of Michigan, Boston University, and the ERES Converge IRB in Zambia. For the before-and-after cross-sectional survey evaluating the impact of the Core MWH Model (clinical trial #{“type”:”clinical-trial”,”attrs”:{“text”:”NCT02620436″,”term_id”:”NCT02620436″}}NCT02620436) multi-stage random sampling procedures were used with probability proportionate to population size [24]. The sample consisted of mothers who met the following inclusion criteria: (1) had given birth in the last 13 months (to obtain recent birth data and reduce recall bias), (2) 15 years of age or older, and (3) lived in a village that was 9.5 km or farther from one of the health care facilities included in our sample [24]. Details of the primary impact study including sampling frame, selection, assignment of study clusters, and protocol are reported elsewhere [23–26]. Locally trained research assistants recruited, consented, and enrolled participants from eligible households in the study [23]. Participants provided written informed consent, which was documented in writing or with a fingerprint and witness signature prior to beginning the survey [23]. For participants under the age of 18 years, child assent and guardian or husband (if over the age of 18 years) was obtained [23]. Research assistants were literate in the appropriate local languages and English. All had previous experience collecting quantitative data for research studies. Research assistants were trained in human subjects’ protection and qualitative and quantitative data collection methods during a 5-day training [23–25]. Each household survey took approximately 45 minutes. Data were captured electronically on encrypted tablets using SurveyCTO Collect Software [23]. An in-depth description of measures used to assess change in use of the Core MWH Model, ANC and PNC attendance, family planning use, and vaccination rates is reported elsewhere [25]. In acknowledgment of their time, participants received a piece of local fabric as a token of appreciation [23]. Table 1 shows the measures used to construct the variables in our analysis. The analysis is divided into two major sections. First, descriptive statistics are provided to assess differences (using Rao-Scott chi-square tests) between baseline and endline with respect to the dependent variables (ANC and PNC, family planning use, and vaccination rates), independent variable (i.e., use of the Core MWH Model), and control variables (i.e., household size, marital status, number of births, age, and educational level). Second, multivariable logistic regression were used to assess the association between use of the Core MWH Model and ANC and PNC. Additionally, these models also focus on differences between the baseline and endline cohorts with respect to the ANC and PNC. Accordingly, unadjusted odds ratios (OR), adjusted odds ratios (AOR) and 95% confidence intervals (95% CI) were provided to show these associations (i.e., differences between groups). Finally, all analyses use design-adjusted analytic techniques to account for clustering within each of the seven districts where the sample of participants were obtained. All analyses use Stata 15.0.