Household saving during pregnancy and facility delivery in Zambia: A cross-sectional study

Financial barriers cause many women in low- and middle-income countries to deliver outside of a health facility, contributing to maternal and neonatal mortality. Savings accrued during pregnancy can increase access to safe delivery services. We investigated the relationship between household saving during pregnancy and facility delivery. A cross-section of 2381 women who delivered a child in the previous 12 months was sampled from 40 health facility catchment areas across eight districts in three provinces in Zambia in April and May of 2016. During a household survey, women reported on their perceptions of the adequacy of their household savings during their recent pregnancy. Households were categorized based on women’s responses as: did not save; saved but not enough; and saved enough. We estimated crude and adjusted associations between perceived adequacy of savings and facility delivery. We also explored associations between savings and expenditures on delivery. Overall, 51% of women surveyed reported that their household saved enough for delivery; 32% reported saving but not enough; and 17% did not save. Household wealth was positively associated with both categories of saving, while earlier attendance at antenatal care was positively associated with saving enough. Compared with women in households that did not save, those in households that saved but not enough (aOR 1.63; 95% CI: 1.17, 2.25) and saved enough (aOR 2.86; 95% CI: 2.05, 3.99) had significantly higher odds of facility delivery. Both categories of saving were significantly associated with higher overall expenditure on delivery, driven in large part by higher expenditures on baby clothes and transportation. Our findings suggest that interventions that encourage saving early in pregnancy may improve access to facility delivery services. Data were collected during baseline of an ongoing cluster randomized controlled trial evaluating the impact of a maternity waiting home intervention in April and May of 2016 [clinicaltrials.gov identifier: ({“type”:”clinical-trial”,”attrs”:{“text”:”NCT02620436″,”term_id”:”NCT02620436″}}NCT02620436)]. The trial covers 40 health facility catchment areas in Choma, Kalomo and Pemba districts in Southern Province, Nyimba and Lundazi districts in Eastern Province, and Mansa and Chembe districts in Luapula Province and has been described extensively elsewhere (Lori et al., 2016; Scott et al., 2018a). Households were identified using a multi-stage random sampling procedure. In the first stage of sampling, every village within the study facility catchment areas were visited and GPS co-ordinates were taken. Co-ordinates were then used to determine the distance of each village center to their designated health facility by travel distance along the most direct route, and only villages at least 10 km (rounding up from 9.5 km) from their designated health facility were considered in subsequent stages of sampling. Ten villages were randomly selected from each catchment area with probability proportional to population size. In the second stage of sampling, an exhaustive list of households that had delivered in the previous 12 months was created with input from the facility and traditional leadership, and the households were randomly ordered. Each household was then visited in that random order and confirmed for eligibility. The process continued down the list until approximately six eligible households were enrolled in each village. To be eligible, women had to have delivered a child during the previous 12 months and be at least 15 years old. If a household had more than one eligible participant, one respondent was selected at random by the electronic data capture system. The target sample size was 2400. Ethical approvals were obtained from the [Boston University] Institutional Review Board (Protocol number [H-34526]) and ERES Converge in Zambia (Protocol number [2015-Dec-012]). Household savings was measured using a nested pair of closed-ended questions. Women were first asked whether they had ‘money set aside in preparation for [their] last delivery’. Those who answered ‘yes’ were then asked whether they thought they had ‘saved enough money’. For the analysis, responses were coded as perceived adequacy of savings with three categories: did not save; saved but not ‘enough’; and saved ‘enough’. These questions captured respondents’ perceptions and were not corroborated with objective estimates of savings values. Questions on savings were designed to elicit information on household savings, not only a women’s personal savings, and additional data were collected on where savings were stored and who else contributed. Information on when during pregnancy saving started, measured by gestational age in months, was also collected. Finally, women reported whether they had ever saved at a bank, and rated the importance of saving for delivery using a likert scale from not important to very important. The primary outcome of interest was delivery at a health facility. We recorded the location of each woman’s last delivery, including the facility where she delivered if she delivered at a health facility. Analysis focused on the dichotomous outcome of whether delivery occurred at a health facility, regardless of type or location. Perceived quality of delivery services is also an outcome of interest, and was measured among women who delivered at a health facility. Women were asked whether or not they experienced problems with the quality of the following: technical quality of medical care received, respect shown by healthcare workers, privacy during delivery, and cleanliness of the healthcare facility. These data were analysed as a dichotomous variable indicating whether or not pregnant women reported at least one problem with their delivery facility. We also explore the relationship between perceived adequacy of savings and expenditures on delivery. Data on several expenditure categories related to delivery were collected in the local currency (Zambian Kwacha, ZMW): delivery supplies, baby clothes, transportation, stay at a maternity waiting home, provider/health center fees, informal payments, tips, in-kind resources, drugs, diagnostic tests and other fees. We collected demographic characteristics at the individual and household levels to investigate associations with savings behaviour. This included age, years of education, distance from designated clinic (in kilometers), marital status, number of household members, parity, gravida, HIV status and household wealth. Marital status and HIV status were coded as dichotomous indicators. An indicator of household wealth was constructed with principle component analysis of asset information. All other demographic variables were included as continuous variables in the analysis. We collected data on the number of antenatal care visits each woman attended during her pregnancy, and when she attended her first session measured by gestational age in months. Lastly, we asked each woman where she had intended to deliver, and who the primary decision maker was for the location of delivery. This was coded as a dichotomous variable indicating whether or not the woman herself was the primary decision maker. First, we calculated descriptive statistics, stratifying by perceived adequacy of savings during pregnancy. We conducted a set of t-tests comparing participant characteristics across categories of perceived adequacy of savings. Next, we fit a series of logistic regression models to estimate crude and adjusted associations between perceived adequacy of savings and facility delivery. Among those who delivered at a health facility, we repeated the analysis to estimate the relationship between savings and perceived quality of delivery services. Finally, we summarized expenditures on delivery and conducted a set of t-tests comparing expenditures across savings categories. All models were fit using Stata version 14 (College Station, TX, USA: StataCorp LP). All standard errors were clustered at the village level to account for the study design.