Mobilizing communities to improve maternal health: results of an intervention in rural Zambia
Tim Ensor a, Cathy Green b, Paula Quigley b, Abdul Razak Badru b, Dynes Kaluba c & Tendayi Kureya d
a. University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute for Health Sciences, University of Leeds, Room G22, 101 Clarendon Road, Leeds, LS2 9JZ, England.
b. Health Partners International, Lewes, England.
c. District Health Office, Chongwe, Zambia.
d. Development Data, Lusaka, Zambia.
Correspondence to Tim Ensor (e-mail: firstname.lastname@example.org).
(Submitted: 04 April 2013 – Revised version received: 21 August 2013 – Accepted: 28 August 2013 – Published online: 04 November 2013.)
Bulletin of the World Health Organization 2014;92:51-59. doi: http://dx.doi.org/10.2471/BLT.13.122721
In Zambia, as in other low-income countries, maternal health indicators have remained stubbornly resistant to improvement: for example, the presence of skilled birth attendants at deliveries has hardly increased in the past 20 years and the maternal mortality ratio remains over 500 deaths per 100 000 live births.1 Two contributing factors have been consistently identified: (i) a lack of knowledge about when to access health-care services, which leads to delays in care seeking; and (ii) difficulties with transportation, which lead to delays in reaching health-care facilities.2–4 The problem of stagnating maternal health indicators has probably been exacerbated by a counter-urbanization trend, with people moving to more remote areas.5 Although most of the rural population of Zambia lives less than 8 km from a health centre, the average distance to a health-care facility equipped for safe delivery is more than 15 km.2 The 2007 Demographic and Health Survey (DHS) in the country reported that 57% of women in rural areas regarded distance as a barrier to accessing health care when sick.1
In 2003, Safe Motherhood Action Groups were established in Zambia as part of a national safe motherhood programme. Initially, they were supported by the United Nations Population Fund in North-West Province before being adopted by the Government of Zambia in a national programme. Each group serves a cluster of villages and is encouraged to meet regularly in a communal area. The aim was to mobilize communities to improve the health of women, men and children and reduce the number of human immunodeficiency virus infections. However, a lack of central coordination has meant that communities often found it difficult to know how to use these groups and, as a result, many of these remain dormant.
Our intervention involved revitalizing Safe Motherhood Action Groups to raise awareness of the need to prepare for pregnancy complications and delivery. The main aim was to improve both understanding of maternal health and access to maternal health-care services. Our approach was predicated on the assumption that women require not only knowledge about when they should seek skilled help but also their husbands’ approval for care seeking, which can be encouraged by community leaders. There is growing evidence that better utilization of maternal health-care services depends on mobilizing the entire community.6,7 For example, in a programme for improving birth preparedness in Nepal that focused only on women, knowledge of obstetric danger signs increased but there was little change in the proportion of deliveries involving a skilled birth attendant.8 It was suggested that the lack of progress occurred because education was provided only for women and not for the whole community and because other barriers to health care, such as the cost of getting to a facility, persisted. Our intervention involved the whole community.
We adopted a quasi-experimental approach to evaluating the effect of a complex community-based intervention that was devised to reduce barriers to the use of maternal health-care services and to increase deliveries involving a skilled birth attendant. The intervention was novel because it involved the whole community and emphasized social approval and its ability to bring about changes in behaviour. The involvement of men, older women and community leaders is vital in places where behaviour is dependent on their approval. In our intervention, men were encouraged to become emergency transport drivers, community leaders were invited to train as community volunteers and older women, who are often traditional birth attendants, were encouraged to become mother’s helpers and were trained to recognize obstetric danger signs. This reduced the likelihood that older women would pressure younger women to conform to dangerous practices.
The intervention involved improving the effectiveness of Safe Motherhood Action Groups by training volunteers and developing and strengthening systems in the community that help women get to heath-care facilities, such as existing arrangements for emergency transport. In practice, training was cascaded across communities: core trainers trained lead volunteers at district health offices and lead volunteers, in turn, trained volunteers within each community. Since the literacy level of volunteers and communities was poor, we adopted a largely paper-free approach to training volunteers and to communicating with communities. Each trained volunteer coordinated a cycle of four community discussions on safe pregnancy and delivery, with additional discussions on neonatal care. Both women and men were encouraged to participate. In addition, communities were encouraged to develop plans for helping women access maternal health services, which included ensuring that transport was accessible and that people (i.e. “mother’s helpers”) were available to assist with child-minding or to accompany women to health-care facilities. Communities were also asked to think about other actions that could be taken to ensure that pregnant women were taken to a health centre in an emergency (e.g. the introduction of a local “law”), to consider social issues that could have a bearing on maternal health, such as violence against women, and to ensure that women without family or other support were included in any initiatives. Although there was some investment in equipment and supplies at health-care facilities in the intervention areas, most was provided towards the end of the intervention period and was unlikely to have had a substantial impact on the use of maternal health-care services.
The intervention was also intended to reduce the delay many women experience in reaching health-care facilities. The distances involved and the poor road conditions mean that, for rural communities, travel is often slow and may be dangerous. Moreover, emergency transport to hospitals is seldom available at health centres. As part of the intervention, community transport, appropriate to the terrain, was provided for groups of two or three villages. In most cases, bicycle ambulances were provided but, in areas where the terrain was particularly uneven or sandy, communities were given ox or donkey carts. One community, which is situated next to a river, was provided with a boat. In addition, health centres were provided with motorcycle ambulances. Each community identified a group of volunteers who were willing to operate and maintain the vehicles and some basic training was provided through the intervention. Follow-up reviews revealed that, in most cases, the vehicles had been well maintained by the communities and that additional vehicle operators were being recruited and trained. Information on the use of emergency transport during the intervention period was obtained by asking women if they had used community transport or transport provided by a health-care facility to reach a health-care facility or hospital for delivery. Additional information on transport was available through a community monitoring system, which was established as part of the intervention to report on women’s use of emergency transport and of health services, such as antenatal care.
The intervention was implemented in six districts selected by the Zambian Ministry of Health largely because they were not already receiving substantive assistance from donors to improve maternal health. Three districts – Serenje, Mongu and Choma – took part in phase one, which started in July 2011, and three – Chama, Kaoma and Mkushi – took part in phase two, which started in January 2012. As a result of the experience gained in phase one, implementation of the intervention – the procurement of vehicles, for example – was slightly quicker in phase two. Otherwise the interventions were identical. Two catchment areas were selected for the intervention in Serenje, Mongu, Choma and Chama, three were selected for Kaoma and one was selected for Mkushi. Each district had a basic emergency obstetric care centre to which smaller health centres or posts were most likely to refer patients. The intervention covered about 25% of the population of each district and included a total of 250 000 inhabitants. In addition, data were collected in five control districts with similar maternal health indicators to monitor changes over time. Any spill-over effects of the intervention were minimized by ensuring that control districts were not adjacent to intervention districts.
A baseline survey of recent births was conducted between December 2010 and May 2011 in both intervention and control districts to assess: (i) current use of maternal and neonatal health-care services; (ii) knowledge of maternal care, including when antenatal care should first be received, and of obstetric danger signs; and (iii) use of community systems that help women obtain care, such as savings schemes and emergency transport (Table 1). A list of all births in the three months before the survey in each area was made using information provided by Safe Motherhood Action Groups. The sample size of women who had recently given birth was 3405 at baseline: 1775 in intervention districts and 1630 in control districts. In the final survey, which was carried out in October 2012, the sample size was 2788: 1445 in intervention districts and 1343 in control districts.
Table 1. Maternal health indicators in intervention and control districts before and after the intervention, 2010–2011, Zambia
For any intervention for improving maternal health care, it is important to know whether it is sustainable, scalable and cost effective. Although a full cost-effectiveness analysis was outside the scope of this study, we examined some of the costs involved. The main start-up costs were for training volunteers and providing vehicles. We assumed that 20% of volunteers would drop out of the programme each year. The main recurrent costs were for maintenance of vehicles and transportation. As a summary measure, we used the incremental cost per additional delivery involving a skilled birth attendant.
Ethical approval for the study was obtained from the University of Zambia Biomedical Research Ethics Committee. All study participants were provided with, or had read out to them, an informed consent form approved by the ethics committee. The form provided information on the study, on how data would be used and on the participant’s right to withdraw at any time.
The indicators used to assess the effect of the intervention on maternal health care were, before delivery, knowledge that antenatal care should first be received in the first trimester, receipt of antenatal care, knowledge of obstetric danger signs (i.e. fever, discharge, blood loss, severe headache and retained placenta) and use of emergency transport and, subsequently, delivery involving a skilled birth attendant, delivery at a health-care facility, receipt of postnatal care within 6 days and use of modern contraceptives after giving birth. Changes in these indicators due to the intervention were assessed using a difference-in-difference approach that involved a proxy counterfactual drawn from households in control districts. This approach controls for confounding factors and for any general changes that would have occurred over time in the absence of the intervention.
The basic equation used in the difference-in-difference approach was:where Y is the binary response variable (e.g. delivery at a health-care facility or knowledge of three obstetric danger signs), T is a time variable (baseline = 0, final survey = 1), I is the intervention variable (intervention district = 1, control district = 0), X is a vector of covariates, including education (i.e. highest level achieved), household wealth, the woman’s age and parity and the distance of the woman’s home from the health centre. The impact of the intervention is expressed by the parameter β3, β1 is a measure of the general change in the response variable between baseline and final surveys, β2 represents the general difference in the response variable between intervention and control areas, β0 is a constant, γ is a vector representing the impact of covariates and e is an error term.
Since the accuracy of the difference-in-difference approach is greater if time trends in the control and intervention groups are similar and the time trends are more likely to be similar if the characteristics of the individuals in the groups are broadly similar, we used propensity score matching to match individuals in intervention districts with similar individuals in control districts. Individuals without a close match were excluded from the analysis. Three types of propensity score matching were used: (i) nearest-neighbour matching, which provides a one-to-one match between an observation in the intervention group and the nearest observation in the control group; (ii) calliper matching, which matches observations within a defined distance (i.e. the difference in propensity score between an observation in the intervention group and the nearest observation in the control group); and (iii) radius matching, which takes a weighted average of all observations within a defined distance. Matching reduced the average difference between control and intervention areas to below 10% for most key characteristics. The remaining differences were controlled for by including the relevant characteristics in the difference-in-difference specification.
For both phases of the intervention, significant increases were observed between baseline and final surveys in the proportion of women who (i) knew they should receive antenatal care in the first trimester, (ii) knew three or more obstetric danger signs and (iii) used emergency transport (Table 2). Data from the community monitoring system confirmed the magnitude of the increase in the use of emergency transport.
Table 2. Percentage point change in selected maternal health indicators associated with the intervention, by intervention phase, 2011–2012, Zambia
The final survey showed that 75% of deliveries took place at a health-care facility after the intervention compared with 49% before. In general, there were improvements in all six intervention districts in the proportion of deliveries that involved a skilled birth attendant and that took place at a health-care facility and in the proportion of women who received appropriate antenatal and postnatal care and who used modern contraception after giving birth (Fig. 1). In particular, the proportion of deliveries involving a skilled birth attendant increased in all districts; only the increase in Mkushi was not significant. Although improvements were generally observed in all other indicators, the proportion of women who received four or more antenatal care visits decreased in Serenje and the proportion who received postnatal care within 6 days of delivery decreased in Mongu and Mkushi. We believe that the decrease in postnatal care may have been an artefact of the data collection process because respondents often rounded up the time when they received care to the nearest week. Hence, care that was actually received within 6 days was recorded as occurring outside this period.
Fig. 1. Absolute percentage change in selected maternal health indicators associated with the intervention (difference between baseline and final surveys), by district, 2011–2012, Zambia
The difference-in-difference approach, both with and without propensity score matching, showed that the intervention was associated with a greater increase in maternal health indicators in intervention districts than control districts (Table 3). Depending on the type of matching applied, the proportion of women who used emergency transport increased by between 12.4 and 18.7%; the proportion who knew that antenatal care should be provided in the first trimester increased by between 14.5 and 15.7%; and the proportion who knew three obstetric danger signs increased by between 10.3 and 14.9%. In addition, the proportion of deliveries that involved a skilled birth attendant at a health-care facility increased by between 16.4 and 21.0% and the proportion that involved a skilled birth attendant outside a health-care facility increased by between 9.0 and 16.7%. The increase in the proportion of women who received four or more antenatal care visits and in those who received postnatal care within 6 days was not significantly different from the increase observed in control districts. Data from the community monitoring system, which provided information to the end of 2012, 2 months after the final survey, indicated that just over 70% of women received postnatal care during 2012.
Table 3. Change in maternal health indicators associated with the intervention, by analytical approach, 2011–2012, Zambia
The start-up cost of training volunteers was 408 United States dollars (US$) per neighbourhood committee, each of which covered four Safe Motherhood Action Groups on average; training was provided for the lead volunteer, regular volunteers and follow-up support. The start-up costs for vehicles were annualized according to their assumed useful life (Table 4). We found that around 5% of volunteers dropped out of the programme each year, rather than the 20% anticipated. Recurrent costs included the cost of maintenance, which was a proportion of the start-up cost (Table 4), and the cost of the fuel or animal feed used while transporting women to a health centre or hospital. Also included was the cost of a project staff member with a social development or nursing background who was assigned to each district to manage the programme and organize training in partnership with members of the District Health Management Team. The estimated annual cost of running the programme in the six districts, including annualized capital and recurrent costs, was US$ 115 489, which is equivalent to US$ 0.46 per capita or US$ 15 per delivery involving a skilled birth attendant. Our analysis indicates that the intervention was responsible for an increase of 20% in deliveries involving a skilled birth attendant, which corresponds to an increase of 1694 deliveries. Consequently, the incremental cost per additional delivery involving a skilled birth attendant was US$ 68. If the intervention were implemented in all areas of the six districts, the total cost would be US$ 386 389, the per capita cost would be US$ 0.37, the cost per delivery would be US$ 12 and the incremental cost per delivery would be US$ 54.
The intervention was associated with significant improvements in women’s knowledge of when they should receive antenatal care and of obstetric dangers signs, in the use of emergency transport, in deliveries involving a skilled birth attendant and in the use of modern contraception. However, the increase in the proportion of women who received four or more antenatal care visits and in those who received postnatal care within 6 days was not significant, which may have resulted from women or interviewers rounding up the time when they received care to the nearest week.
Since we used a quasi-experimental approach to evaluate changes in a relatively small total population of 250 000, the findings are necessarily weaker than if randomization had been used. Moreover, the intervention was complex and incorporated several activities in the community. Consequently, it was not possible to separate out the effect of individual components, particularly since an underlying principle of the intervention was that community members themselves should decide on the details of its implementation. Increasing the use of maternal health-care services probably depends on a combination of better community knowledge, the development of strategies to prepare for birth and the provision of emergency transport.
We found that the incremental cost per additional delivery involving a skilled birth attendant would be US$ 54 if the intervention were implemented throughout the six districts studied. This cost is comparable to that of other demand-side interventions in developing countries. For example, in a maternal incentive scheme in Nepal, the estimated cost of each additional delivery at a health-care facility was around US$ 110 and the cost of a voucher scheme in Bangladesh was US$ 70 per delivery.9,10
Since our intervention was largely dependent on community volunteers, retention was a key issue. We did not offer material incentives to volunteers apart from small items such as T-shirts (for identification), pens and exercise books. Vastly different volunteer drop-out rates have been reported by other programmes: one study in urban Bangladesh had a drop-out rate of 90% in the year after training, whereas a programme developed for rural areas in Uganda had a rate of only 14% after 18 months.11,12 Early indications are that the drop-out rate in our intervention areas in Zambia was low, at around 5%. Moreover, an analysis conducted towards the end of the 18-month implementation period found rates ranging from 1 to 12% (mean: 5.4%) in the six districts.13 Two factors that may be important for retaining volunteers are the time that has to be devoted to the work each week (for our intervention, the average was 3 hours) and a strong belief in the value of the programme, which would ensure a high level of intrinsic motivation.
Steps are now underway to absorb the intervention into a government programme. The function of the project staff members who managed the programme and organized training will be taken over by district offices, which are now in the process of scaling up the intervention. It is encouraging that implementation took less time in districts that participated in the second phase of the intervention. Although there remain concerns about the loss of volunteers, it is expected that volunteers will be phased out over time once social approval for the behavioural changes promoted by the intervention is established. It will be interesting to see how this affects sustainability. Future evaluations should monitor whether change becomes self-perpetuating and, if so, how long volunteers need to be active for this to occur.
This study was funded by aid from the Government of the United Kingdom of Great Britain and Northern Ireland.
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