Investigating the role of health care at birth on inequalities in neonatal survival: evidence from Bangladesh

Inequities in neonatal mortality and use of health services: an explanatory model

Socio-economic inequalities in neonatal mortality are seen throughout the world[1], and indeed even in developed countries such as the UK newborns born into the poorest families are more likely to die than those from more wealthy backgrounds[2]. Socio-economic status is likely to influence neonatal survival through a range of proximate determinants such as maternal nutrition, birth spacing and family practices. However, there is evidence to suggest that at a national level a much greater proportion of the variance in neonatal mortality can be explained by access to health care rather than contextual factors such as income, female literacy, water and sanitation[3]. This may suggest that for neonates the most important pathway through which socio-economic inequalities affect outcomes is differential access to, and use of health care by rich and poor, or by educated and uneducated.

Care at birth is seen as the cornerstone of efforts to reduce neonatal mortality. However, in countries such as Bangladesh, where skilled care at birth is rare, those who receive it are much more likely to have experienced complications that are strongly associated with the probability of a neonatal death. This results in higher neonatal mortality for women giving birth in institutions in a range of settings[4], but this apparent disadvantage may mask importance differences in groups of women that access services. Studies have consistently demonstrated that wealthy or more educated women are much more likely to deliver in an institution or with skilled care[5–7], which may suggest that a larger proportion of these urban, richer or more educated women will have planned their birth at an institution rather than waiting for a complication to arise.

Even among those who access care only once complications arise, there is evidence that patterns of utilisation are different among the rich and poor. The Bangladesh Maternal Health Survey conducted in 2001[8] shows that poorer and less educated women experienced longer delays in recognition and decision to seek treatment for both life-threatening and non-life threatening complications. They also experienced longer journey times once the decision to seek care had been made. Further inequities may result from differential quality of care among rich and poor, even if they used the same institution[9]. Figure1 presents a simplified explanatory framework that demonstrates how the trajectories through which richer and poorer women receive care at birth may influence the outcomes for newborns.

Neonatal health within the context of Bangladesh

Neonatal mortality has fallen in Bangladesh over the last four decades from an estimated 74 per 1000 in 1975[10] to 27 per 1000 in 2009[11]. Much of this decline is thought to be as a result of efforts to reduce neonatal tetanus through maternal immunisation[12]. While the reduction is significant, as in many countries neonatal mortality has tended to fall less sharply than deaths in older children. As a result, neonatal mortality now makes up nearly half of all deaths in Bangladesh in children under the age of five, and about two-thirds of infant deaths. While Bangladesh has made significant progress in some areas of reproductive health such as uptake of family planning methods, indicators of safe motherhood have not markedly improved. Most recent estimates suggest that 27% give birth with a skilled attendant[11] and while uptake of institutional care at delivery at birth has increased, progress is slow, as illustrated by figures from the four surveys included in our study (see Figure2). Uptake is particularly low for the poorest quintile where little progress has been made.

Descriptive statistics

Table 2 and Figure3 show NMR disaggregated by urban/rural/wealth and place of birth. When wealth quintile 5 (richest) is considered, there is little difference in NMR between those who gave birth at home or in an institution for both urban and rural areas. For wealth quintile 1–4 (all but richest) that picture is different: there is a marked increase in NMR for urban dwellers giving birth in institutions, but the greatest difference is among rural dwellers where the NMR is twice as high. A chi squared test showed that the association between wealth and neonatal mortality for both rural and urban dwellers was significant for those who had institutional deliveries: (p = <0.001 for rural and p = 0.02 for urban). For home deliveries the chi squared test was not significant for either urban or rural women.

Wealth	Neonatal mortality rate (Confidence intervals in brackets)
Wealth quintile 5 (richest)	Urban	Rural
Home birth	26 (12–40)	34 (28–40)
Institutional birth	27 (16–39)	31 (16–45)
Wealth quintile 1–4 (all but richest)	Urban	rural
Home birth	36 (31–41)	42 (39–45)
Institutional birth	55 (41–69)	84 (61–107)
Education	Neonatal mortality rate (Confidence intervals in brackets)
No education
Home birth	44 (40–48)
Institutional birth	101 (65–136)
Primary education
Home birth	37 (33–41)
Institutional birth	82 (58–106)
Secondary education
Home birth	37 (32–43)
Institutional birth	43 (32–55)
Higher education
Home birth	16 (5–27)
Institutional birth	16 (7–25)

Table 2 also shows differences for NMR by mother’s education and place of delivery. A similar pattern can be seen. Clearly babies whose mothers received no education or primary education had very markedly higher NMRs if born in institutions as compared with those born at home. Little difference was seen by place of birth among newborns whose mothers had secondary or further education. The graph in Figure4 clearly demonstrates that differentials for mortality by level of mother’s education are much greater for babies born in government institutions than for those who were born at home. The chi squared tests are both significant but more so for the group giving birth in institutions: (p = <0.0001 for institutional births compared to a p =0.021 for home births).

Results of multivariate analysis

The basic model was built on neonatal mortality as a dichotomous outcome. Six stratified models were developed:

Institutional births and poor outcomes for the poor

The markedly larger socioeconomic differentials in neonatal mortality for those born in hospitals suggests strongly that provision of care at birth is particularly failing to meet the needs of disadvantaged women and their newborns. Both the descriptive and regression results clearly demonstrate that wealth has a markedly greater impact on neonatal outcomes for those giving birth in institutions compared to those giving birth at home. This suggests poor women are either arriving too late, or the care they receive is inadequate. While the descriptive analysis for education shows a very similar pattern, evidence from the multivariate analysis is less compelling: while not significant, there is a marked increase in OR for neonatal death for no education, primary and secondary education for women giving birth at home compared to those with higher education. The lack of significance may well be as a result of small sample size, and the findings may reflect the fact that the reference group of those women who have received further education is a particularly small and elite group with very low overall neonatal mortality.

The difference in neonatal outcomes from institutions between the urban and rural poor is also marked. This could be either because the characteristics of the two groups are different, or because access to services is more difficult in rural areas. In many countries rural poverty may be deeper and more chronic than in urban areas, and the population may be less educated[14]. There is some evidence that the rural population in this study are indeed different in character: we cannot directly compare wealth between urban and rural groups using the asset index, but if we examine education, over half (53%) of the rural quintiles 1–4 had no education compared to 34% of urban quintiles 1–4. However, another plausible reason could be the increased journey time when seeking care for rural women, which could detrimentally impact on outcome. The Bangladesh Maternal Health Services and Maternal Mortality Survey 2001[8] found that only 26% of rural women with complications reported travelling less than 30 minutes to reach a provider or facility compared with 59% of urban respondents. Around 8% of women reported travelling for more than 3 hours, which obviously is likely to have negative consequences.

While utilisation data are often disaggregated, data on institutional outcomes are not routinely analysed – indeed the idea of inequity in outcomes from services is not well developed within the literature. This work suggests that such measures could be important, and provide a much more comprehensive picture than utilisation data alone. For instance, an apparent increase in utilisation among the poorest might mask the fact that many of these women are only arriving at hospital once complications are well advanced, thus reducing their chance of positive outcomes. Ideally such analysis should include attention to fresh stillbirths, which are often used as an indicator of care at birth. However, very limited data are available: DHS infrequently collect data on stillbirths, and quality is questionable, along with a further limitation that fresh and macerated stillbirths are not differentiated[15]. Indeed, it is worth considering that the extremely negative outcomes experienced by poor women would be even more concerning if stillbirths could be included, as poor or delayed intrapartum care may often result in the foetus dying during labour, so will not be included as a neonatal death.

The fact that due to sample size quintiles 1–4 were grouped together probably also results in an underestimation of the disadvantage faced by the poorest in terms of neonatal outcomes. Examining the difference in mortality between the top and bottom socio-economic groupings is a commonly used method of examining inequality, but has the limitation of failing to ascertain the distribution of mortality across the population. Another measure that could address this would be calculation of concentration curves or indices for the different groups as this takes into account mortality for the whole range of wealth. Further studies using this technique may be valuable.

Analysis over time of perinatal institutional outcomes can provide valuable evidence on quality of care. It would be assumed that as uptake of skilled care at birth increases, outcomes would improve as more and more women with uncomplicated pregnancies make an active choice to give birth in hospital. However, there are suggestions that in some cases increased demand actually has a negative impact on quality, as staff and resources are placed under greater pressure[16]. Monitoring of institutional mortality rates, particularly among the poorest could give some indication of any unintended negative consequences resulting from efforts to increase uptake of services.