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Limited quality of childbirth care in sub-Saharan Africa primarily affects the poor. Greater quality is available in facilities providing advanced management of childbirth complications. We aimed to determine whether Maternity Waiting Homes (MWHs) may be a tool to improve access of lower socio-economic women to such facilities. Secondary analysis of a cross-sectional hospital survey from Iringa District, Tanzania was carried out. Women who delivered between October 2011 and May 2012 in the only District facility providing comprehensive Emergency Obstetric Care were interviewed. Their socio-economic profile was obtained by comparison with District representative data. Multivariable logistic regression was used to compare women who had stayed in the MWH before delivery with those who had accessed the hospital directly. Out of 1072 study participants, 31.3% had accessed the MWH. In multivariable analysis, age, education, marital status and obstetric factors were not significantly associated with MWH stay. Adjusted odds ratios for MWH stay increased progressively with distance from the hospital (women living 6-25 km, OR 4.38; 26-50 km, OR 4.90; >50 km, OR 5.12). In adjusted analysis, poorer women were more likely to access the MWH before hospital delivery compared with the wealthiest quintile (OR 1.38). Policy makers should consider MWH as a tool to mitigate inequity in rural childbirth care.
The study was carried out in Iringa District, a mostly rural district in the Tanzanian Southern Highlands, with an habitable surface of 9857 km2. The estimated population of 254 023 was served by 73 health facilities in 2012, including one District-designated diocesan hospital, 6 health centres and 66 dispensaries. C-EmOC services were available only in the Hospital, equipped with a 45 bed Maternity Ward. In 2012, 7645 institutional deliveries were recorded in the District, with 2140 (28.0%) in the C-EmOC facility, and 5505 (72.0%) in primary care facilities. In 2011–12, the only MWH in the district was adjacent to the hospital. It offered basic accommodation with toilets and cooking facilities for pregnant women, and required payment of a small daily fee. Women admitted to the MWH were self-referred or referred by a health worker from a peripheral facility. This study was based on secondary analysis of a cross-sectional survey of women who delivered in the only C-EmOC facility in Iringa District (Tosamaganga District-designated Hospital) between October 2011 and May 2012. Women were interviewed to collect data on access and quality of services (‘hospital survey’) (Straneo et al. 2014), as part of a development intervention aiming to strengthen maternal and newborn services. A baseline population socio-economic profile was obtained from a district-representative household survey (‘community survey’) described elsewhere (Straneo et al. 2016). Data collected included socio-demographic characteristics of women discharged and pregnancy outcomes. A pre-test validated, structured questionnaire was administered by ward staff at discharge. Where relevant (e.g. type of stillborn, birth weight, time of newborn death), data were extracted from the women’s files. Neonatal and perinatal mortality definitions followed WHO guidelines (WHO 2006). Obstetric risk factor was defined according to national guidelines (Jahn et al. 1998; MoHSw 2008), and includes primigravidae, gravida >4, previous cesarean section and poor obstetric history. Women were asked about village of residence. Euclidean distances to C-EmOC were remotely estimated by using a geographical information system and reference points at village level, like health facility or village centre. Intervals applied were ≤5, 6–25, 26–50, >50 km, in accordance with similar studies (Høj et al. 2002; Wild et al. 2012). Characteristics of the population of women who had stayed in the MWH and of those who had accessed the maternity ward directly were examined. Variables examined were age, tribe, parity, education, marital status, sex of household head, distance of residence from the hospital, obstetric risk, socio-economic strata (SES). Sample size for the primary study was calculated to detect a 30% difference among the socio-economic groups accessing the C-EmOC facility compared with the baseline community SES groups, with a significance level of 5 and 90% power. Socio-economic stratification of the district population was obtained from a District-representative cross-sectional survey conducted in 2009. It was based on durable household goods or housing characteristics (thatched roof, non-mud floor, radio, mobile phone, bicycle). Five SES were obtained using principal component analysis, labelled 1–5 from lowest to highest. The socio-economic profile of women with a hospital delivery was obtained by applying the cut-offs of socio-economic quintiles from the District population (Straneo et al. 2014). SES quintiles were collapsed into two categories (1–4 and 5) in multivariable analysis, to assess differential access of poorer women compared with the wealthiest. Data entry and cleaning was done using Epidata version 3.1. Data were analysed using STATA version 9. Characteristics of women who stayed at MWH and of those who directly accessed the hospital were summarized using proportions and 95% CI. Factors associated with staying at MHW were assessed by multivariable logistic regression. Crude and adjusted odds ratios with 95% CI were estimated and P-values calculated with the Wald test. Pregnancy outcomes were examined for MWH users and non-users in bivariate analysis. Proportions and 95% CI were calculated for each group and chi-squared test was applied to estimate P-values. Multivariable analysis on fetal/neonatal outcomes could not be performed due to small counts in some sub-groups. All P < 0.05 values (two-sided) were considered statistically significant.
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