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R E S E A R C H A R T I C L E Open Access
Incidence of catastrophic expenditures
linked to obstetric and neonatal care at 92
facilities in Lubumbashi, Democratic
Republic of the Congo, 2015
Abel Mukengeshayi Ntambue
1*
, Françoise Kaj Malonga
1
, Karen D. Cowgill
2,3
, Michèle Dramaix-Wilmet
4
and Philippe Donnen
4,5
Abstract
Background: In the Democratic Republic of the Congo (DRC), more than 93% of users must pay out of pocket
for care. Despite the risk of catastrophic expenditures (CE), 94% of births in Lubumbashi are attended by skilled
personnel. We aimed to identify risk factors for CE associated with obstetric and neonatal care in this setting, to
document coping mechanisms employed by households to pay the price of care, and to identify consequences of
CE on households.
Methods: We used mixed methods and conducted both a cross-sectional study and a phenomenological study of
women who delivered at 92 health care facilities in all 11 health zones of Lubumbashi. In April and May 2015 we
followed 1,627 women and collected data on their health care and household expenses to determine whether they
experienced CE, defined as payments that reached or exceeded 40% of a household’s capacity to pay. Two months
after discharge, we conducted semi-structured interviews with 58 women at their homes to assess the consequences
of CE.
Results: In all, 261 of 1,627 (16.0%) women experienced CE. Whether a woman or her infant experienced complications
was an important contributor to her risk of CE; poverty, younger age, being unmarried, and delivering in a parastatal
facility or with more highly trained personnel also increased risk. Among a subset of women with CE interviewed 2
months after discharge, those who were in debt or who had lost their trading income or goods were unable to pay
their rent, their children’s school fees, or were obliged to reduce food consumption in the household; some had
become victims of mistreatment such as verbal abuse, disputes with in-laws, denial of paternity, abandonment by
partners, financial deprivation, even divorce.
Conclusions: We found a higher proportion of CE than previously reported in the DRC or in other urban settings in
Africa. We suggest that the government and funders in DRC support initiatives to put in place mutual-aid health risk
pools and health insurance and introduce and institutionalize free maternal and infant care. We further suggest that the
government ensure decent and regular payment of providers and improve the financing and functioning of health care
facilities to improve the quality of care and alleviate the burden on users.
Keywords: Expenditures, health, Obstetric labor complications, Democratic Republic of the Congo
© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
* Correspondence: abelntambue@yahoo.fr
1
Unité d’Epidémiologie et de Santé de la mère, du nouveau-né et de
l’enfant, École de Santé Publique, Université de Lubumbashi, Lubumbashi,
Democratic Republic of the Congo
Full list of author information is available at the end of the article
Ntambue et al. BMC Public Health (2019) 19:948
https://doi.org/10.1186/s12889-019-7260-9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Background
Skilled birth attendance is recognized as an intervention
that reduces maternal and perinatal mortality [1]. The
countries that have improved coverage in skilled birth
attendance are also those that showed great progress to-
ward attaining the target of Millennium Development
Goal 5, to improve maternal health [2]. In Africa, skilled
birth attendance has increased from 47% in 1990 to 78%
in 2015 [3]. Now, Sustainable Development Goal 3.1–2
is focused on universal coverage of skilled birth attend-
ance to attain a significant reduction in maternal and
perinatal mortality by 2030 [1,4]. Attaining this cover-
age has become a driving force of maternal health pro-
grams around the world [1,4,5].
However, this growth in the number of assisted deliv-
eries brings with it an increase in the burden on the
health system —in terms of infrastructure, medications,
equipment, and human resources for health [1,6]—the
Every Mother, Every Newborn initiative [4] reaffirms the
Abuja accords and insists on the responsibility of gov-
ernments to allocate at least 15% of their budgets to
health care, while encouraging new modes of financing
for development in the post-2015 era.
In the Democratic Republic of the Congo (DRC), the
budget allocated to health is low. In 2014, it was 10.8%
of the total budget [7]. It corresponded to US$ 2–3 per
resident per year, and represented only 30% of all total
health expenditure. It was trivial compared to the mini-
mum of US$ 86 per resident per year recommended in
2009 by the international high-level working group on
health (members cited in [8]) and, even considering ex-
ternal contributions which comprise 40% of health sys-
tem expenditures, the health expenditure per resident
per year was still low (US$ 23) [7]. Given that nearly two
thirds of this budget (63.9%) is taken up by health sector
administration, the provision of health services has be-
come entirely dependent on direct payments for care by
users. More than 93% of users must pay to access care
at health facilities [7].
In a country where the majority of the population is
poor [9], basing financing for the functioning of health
facilities on user fees entails two results [10]: first, care
becomes inaccessible, especially for impoverished house-
holds; second, women who go to health facilities to
deliver despite their poverty face a high risk of cata-
strophic expenses (CE) and reinforcement of their
poverty. Expenses are defined as catastrophic when they
are equal to or greater than 40% of the contributory cap-
acity of a household [11]. CE is not always synonymous
with a high cost of care; even relatively low expenditures
can be disastrous for a poor household whose entire
resources are needed for essentials. For these house-
holds, paying even a small sum can lead them into
poverty [12].
For over a decade, initiatives aiming at universal cover-
age of health care have multiplied in the DRC [5,13,
14]. In response to the Global Financing Facility (GFF)
[14], the DRC has put in place a national policy of health
care financing with the aim of increasing and harmoniz-
ing financing in support of national health plans and pri-
orities, and of thus radically improving the results
obtained in the area of women’s, infants’, and adoles-
cents’health [15]. At the national level in DRC, the inci-
dence of CE linked to general care has been reported as
10.8% [15]. In 2014, in Lubumbashi, we showed that ex-
penses tied to obstetric care were higher when compared
to other cities in Africa [16], but information on the in-
cidence of CE, its determinants and health and socioeco-
nomic consequences among women who deliver with
skilled attendance, is lacking. The rate of skilled birth at-
tendance is high (94.5%) despite the extent of poverty in
the city [17]; we wanted to discover the strategies used
by households to meet these fees despite their impover-
ishing nature.
This study, which follows on one that described the
variability of costs of obstetric and neonatal care in
Lubumbashi, aims to identify risk factors for CE associ-
ated with obstetric and neonatal care in Lubumbashi [16].
We measured the incidence of CE and its determinants,
documented coping mechanisms used by households to
pay the price of care, and identified socioeconomic and
health consequences of CE on households.
Methods
Study setting
The city of Lubumbashi covers an area of 747 km
2
and
has an estimated population of more than 2 million, for
an average density of 2,543 inhabitants per km
2
[18];
however, it comprises periurban areas where population
density is lower. Nearly 70% of its population lives on
less than US$1/day [9]. The city is divided into eleven
Health Zones (HZ), all but one of which has a General
Referral Hospital (GRH); on average, each HZ has 15
Health Centers (HC). More than 350 health care
facilities (hospitals, polyclinics, and HCs) are found in
Lubumbashi, with the majority –70%—in the dense
urban core [18]. The private sector accounts for more
than 60% of facilities. Almost 180 facilities in Lubumbashi
offer maternity services [19]. In 2012, 94.5% of deliveries
were assisted [17].
Population
We included facilities in all eleven HZs that had at least
25 deliveries in the month before our survey. In each of
the 92 facilities that met the inclusion criteria, we invited
all self-paying women admitted to the maternity to
participate. To be included, women had to be able to
speak French or another of the national languages, i.e.,
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Swahili, Tshiluba, Lingala, or Kikongo to communicate
with the researchers.
Women who could read and understand French were
given the opportunity to read the written consent form
themselves; for those who could not read or understand
French, the form was read and explained by a researcher
in another language in the presence of a person not in-
volved in the study (e.g., a unit administrator) whose
role was to confirm the content of the document.
Women were given the opportunity to ask questions
and then, if they chose, to sign the consent form.
Information about each woman was kept confidential.
All 1,627 women who gave birth in the selected health
care facilities between April and May 2015 were eligible
and gave consent to participate in the study. Inclusion
criteria and selection methods for the qualitative portion
that explored consequences of CE are described below,
with the description of the semi-structured interview. This
study was approved by the Medical Ethics Committee of
the University of Lubumbashi (UNILU/CEM/010/2011).
Study
We used mixed methods and conducted both a cross-
sectional study and a phenomenological study [20]. This
allowed us to appreciate two complementary aspects of
CE tied to obstetric and neonatal care. The cross-
sectional study (quantitative) allowed us to investigate
the determinants of CE, while phenomenology permitted
us to determine the short- to mid-term consequences of
these costs that could not have been adequately captured
by the quantitative approach. For the latter, we made
home visits 2 months after participants’discharge from
the maternity unit. Interviews and document reviews
were carried out by thirty trained assistants.
Data collection
Structured interview and document review
We used a structured questionnaire (Additional file 1)to
capture information about the expenditures —including
the reason for each payment—related to delivery, as
well as sociodemographic and economic information not
included in the medical record. From each woman’s
medical record, we collected data on reasons for admis-
sion, presence of complications, type of delivery and we
collected documentation of expenditures linked to deliv-
ery. We consulted the head of the maternity unit to
determine what charges were covered by each payment.
We followed payments made daily for the entire length
of stay [10], apart from receipts available from the
women or their family members, or in the files of the
maternity unit if the bill was not available. Payments
were validated after triangulation of information ob-
tained i) from the woman giving birth or her family, ii)
in the medical record, and iii) by confirmation from the
head of the maternity unit. For medications purchased
outside the facility or from staff at the facility, we docu-
mented payments based on receipts or, if the receipt was
missing, based on the woman’s report, but only if the
medication was identified, or the information validated
by the birth attendants. This was also the case for
laboratory tests and blood purchased at the blood bank.
If the total declared by the woman was higher than that
reported by the maternity team, and the proof of expen-
ditures were not available, the difference was attributed
to the category “other fees”, which often included gratu-
ities given to the health care personnel.
Semi-structured interviews
Semi-structured individual interviews (Additional file 2)
were conducted only at homes. We drew up an a priori
list addressing three essential themes: i) the woman’s
view on the quality of care she received; ii) her view of
the price of care at the maternity unit; and iii) the conse-
quences (problems) she faced as a result of the payments
made at the maternity. Considering each facility in
which a woman delivered as a “cluster”, the saturation
threshold was fixed at four redundant interviews in a
cluster that didn’t add anything to advancing the
conceptualization of the consequences of CE [20]. In the
end, we interviewed 58 women in 10 clusters. The inter-
views were recorded, then transcribed.
Data management and analysis
The data from the structured interviews and docu-
ment review were double-entered and stored in Excel
(Additional file 3). The total costs of care at delivery was
the sum of expenditures tied to obstetric and neonatal
care (medications, supplies, the act of delivery, cesarean
section, episiotomy, dressings, lab tests, newborn care,
stay, and medical record) [10].
To determine the household’s capacity to pay, we
estimated total expenditures —comprising payments for
food and other (housing, electricity, water, school fees,
holidays, birthdays, trips, clothing, furniture, communi-
cation, transport, leisure, fund transfers, as well as the
costs of delivery)–for the year preceding the survey
[12]. We asked women to report recurring expenditures
like food, communication, transportation, and leisure for
the month preceding the survey, and used these to
estimate for the entire year; for other non-food expendi-
tures, we estimated them for the whole year [21]. We
subtracted the food expenditures to obtain the house-
hold’s capacity to pay. We defined CE for obstetric and
neonatal care equal to or greater than 40% of the
household’s capacity to pay [12,22,23]. All expenditures
were expressed in US$ (at the time of this study, 920
Congolese francs (CDF) = US$1).
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To evaluate the impact of socioeconomic level on the
incidence of CE, we created a socioeconomic index [24].
We used principal components analysis (PCA) based on
the variables used in urban settings in the 2013
Demographic and Health Survey (DHS) [25]: household
(number of people per household, relationship with the
owner of the house, materials of the wall and roof,
source of water and electricity, source of energy for the
household, type of toilets), presence of radio, telephone,
freezer, television, computer, fan, sewing machine,
wheeled vehicle (bicycle, motorcycle, car), type of bed
and chairs. The socioeconomic well-being score was de-
rived from the first principal component, which was used
to construct the household socioeconomic index [25].
Apart from the number of people per household, variables
were dichotomized [25]. The percent of variance ex-
plained by the first component was 36.1% for this model.
We described the profile of health care facilities and of
participants included in the study with standard descrip-
tive statistics (proportion, mean and standard deviation,
median, minimum, and maximum). We used Mann-
Whitney and Kruskal-Wallis tests to compare expendi-
tures for each type of delivery between women who suf-
fered CE and those who did not to test the hypothesis of
differences in expenditures between these two groups.
Bonferroni’s correction was used for two-by-two com-
parisons of expenditures by type of delivery (uncompli-
cated vaginal, complicated vaginal and cesarean delivery)
and the occurrence of CE. We used a chi-squared test,
with a significance threshold of 5%, to compare the inci-
dence of CE (dependent variable) by characteristics of
women, socioeconomic level (low vs high), presence of a
more vs less highly skilled birth attendant, private
ownership of the facility (vs public or religious), the
occurrence of obstetric or neonatal complications (vs
uncomplicated delivery), and a long stay in the maternity
unit (vs a stay of 3 days or fewer) (independent vari-
ables). In the logistic regression model, all these vari-
ables were adjusted by the demographic characteristics
of the women. We calculated relative risk (RR) and 95%
confidence interval (CI) to evaluate the strength of the
association between the variables listed above and the
incidence of CE.
We used forward stepwise logistic regression with a
significance threshold of 5% to identify determinants of
CE, with resulting adjusted odds ratios (aOR) and 95%
CI. We included only independent variables with a
p-value of ≤0.10 in univariable analysis in the multivari-
able analysis. To avoid collinearity between obstetric and
neonatal complications and related care, we built two
models, one based on health care and the other on obstet-
ric and neonatal complications. We tested the fit of the
final model with the Hosmer-Lemeshow test [26]. All
analyses were conducted with Stata v13.1. We defined
complicated delivery according to WHO criteria as
“medical problems associated with obstetric labor, such as
hemorrhage (antepartum and postpartum), obstructed
labor, postpartum sepsis, placenta praevia, placental
abruption and premature rupture of membranes, compli-
cations of abortion, severe pre-eclampsia and eclampsia,
ectopic pregnancy and ruptured uterus or others”.
Neonatal care was categorized into three levels: basic care
offered to healthy newborns, emergency neonatal care
(EmNC) for newborns with intrapartum respiratory dis-
tress, and intensive care for sick or low-birth-weight
newborns [27].
Data from the semi-structured interviews were simul-
taneously translated from local languages into French at
the time of their transcription, then re-read. Initially, we
analyzed them to pull out the major consequences, then
we conducted a thematic analysis about the i) economic,
ii) social, and iii) health consequences of CE and the
possible associations among them [20].
Results
Profile of women
We included 1,627 women in our study. Table 1shows that
in the majority (61.1%) of women were recruited in the
HZs of Ruashi (21.8%), Lubumbashi (16.8%), Kampemba
(11.4%), and Katuba (11.1%). The HZs of Kisanga (8.2%),
Vangu (7.8%), Mumbunda (7.7%), Tshamilemba (6.3%),
Kenya (5.0%), and Kamalondo (3.8%) made up the
remaining 38.9%. Over the course of the survey, there were
no deliveries at the HC in the Kowe HZ. The majority of
women were recruited in HCs (42.0%) and GRHs (35.3%).
Polyclinics represented 13.5% of women, while the tertiary
hospitals, Sendwe and University Clinics of Lubumbashi
(UCL), each accounted for only 4.6% of women. More than
half the women (864, or 53.2%) came from private-sector
facilities; one quarter of these came from faith-based facil-
ities; the public sector accounted for 40.3% of participants,
and parastatal health facilities for 6.6%.
The average age of women in the sample was 27 years
(minimum 13, maximum 47). The average age of the
partners of those who were married was 34 years (min
17, max 64). Thirty-eight women (2.3%) were not
married. We divided participating women into quintiles
by wealth.
More than a third (35.8%) of women arrived at the
maternity unit on foot or by motorcycle or bicycle, 39%
arrived by public transport, and only a quarter arrived
(25.2%) by private transport. One hundred fourteen
(7.0%) of surveyed women had been referred from
another health care facility. In all, 659 women (40.5%)
had at least one complication during or following
delivery. Obstructed labor (14.8%), cervical and perineal
tears (13.2%), ante- and post-partum hemorrhage (5.3%),
and post-partum infections (3.1%) were the most
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commonly reported complications. One hundred ninety-
seven women (12.1%) delivered by caesarean. All the
newborns born to women who had complications stayed
in the neonatal intensive care unit, 24.9% to receive
emergency neonatal care and 74.1% to receive intensive
care for ill newborns.
At delivery, 88.9% of women were attended by mid-
wives and 6.0% by generalist physicians, while 5.2% were
attended by specialist physicians. The median length of
stay in the maternity unit was 3 days (min 1, max 64).
More than three quarters (79.1%) of women had pre-
selected the maternity unit where they would deliver.
Nearly half of all women (48.4%) delivered without
knowing in advance how much they would pay. In all,
261 of the 1,627 women recruited for the study (16.0%;
95% CI 14.3–17.9%) reported catastrophic expenses re-
lated to obstetric and neonatal care.
In all, 261 of 1,627 (16.0%) women experienced CE. In
Table 2, the median expenditure for delivery was higher
in women who experienced CE (US$ 54) compared with
those who did not (US$ 38; p< 0.001). In looking at each
type of delivery, we noted that the median expenditures
for a complicated vaginal birth were not significantly dif-
ferent between women who experienced CE and those
who did not (p= 0.69). On the other hand, the median
expenditure for those with uncomplicated vaginal births
who experienced CE was US$4 higher than for those
who did not experience CE, and those with cesarean sec-
tions and CE spent US$65 more than those who did not
experience CE (p= 0.043) or caesareans (p= 0.005).
Furthermore, we noted that the median household
capacity to pay (contributive capacity) was US$9 lower
among women who had CE compared to those who did
not (p= 0.015) regardless of the type of delivery.
In Table 3, the incidence of CE was different by HZ.
Women who delivered in the HZ of Kisanga, Ruashi,
Kamalondo,Tshiamilemba, Kenya, and Kampemba in-
curred CE less than half as often as those who delivered
in the HZ of Lubumbashi. The incidence of CE ranged
from 18.3 to 32.6% in the HZs of Lubumbashi, Mum-
bunda, and Katuba, but the differences did not attain
statistical significance. The incidence likewise varied by
type of facility. The incidence of CE was almost two
times higher in the provincial hospital (Sendwe) and in
the GRH compared to the Health Centers. Women who
delivered in facilities that were public, private non-
religious, or owned by a parastatal entity had more than
two times the risk of having CE compared to those who
delivered in private religious facilities.
In Table 4, younger age of the woman, although not of
her partner, was associated with the variation in inci-
dence of CE. Unmarried women had more than twice
the risk of having CE compared to those who were mar-
ried. The incidence of CE was 16 and 23 times higher,
Table 1 Profile of parturient women surveyed, Lubumbashi,
DRC, 2015
Variables Total (n= 1627) Percent
Health Zones
Lubumbashi 274 16.8
Katuba 181 11.1
Mumbunda 126 7.7
Vangu 127 7.8
Kisanga 133 8.2
Ruashi 354 21.8
Kamalondo 61 3.7
Tshiamilemba 103 6.3
Kenya 82 5.0
Kampemba 186 11.4
Type of facility
Health center 684 42.0
Sendwe (provincial referral hospital) 74 4.6
General referral hospital 574 35.3
University Clinics of Lubumbashi (UCL) 75 4.6
Polyclinics 220 13.5
Sector of ownership
Private, religious 214 13.1
Public 655 40.3
Para-statal commercial 108 6.6
Private, non-religious 650 40.0
Age (years)
< 20 172 10.6
20–34 1215 74.6
≥35 240 14.8
Marital status
Married 1589 97.7
Not married 38 2.3
Partner’s age (years)
< 25 114 7.0
25–34 784 48.2
35–44 589 36.2
≥45 115 7.1
Unknown 25 1.5
Wealth quintile
Q1 (very poor) 302 18.6
Q2 317 19.5
Q3 311 19.1
Q4 344 21.1
Q5 (very rich) 353 21.7
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respectively, among the lowest and second-lowest wealth
quintiles compared to the highest.
Table 4also shows that women who were referred
from one facility to another had nearly three times the
risk of CE compared to those who were not. Women
who had any complication —eclampsia, placenta praevia,
obstructed labor, pre- or post-partum hemorrhage, or uter-
ine rupture—had at least three and a half times higher risk
of CE compared with those who had no complications.
Women who had complicated vaginal births had
nearly twice the risk of CE compared with those who
had an uncomplicated birth, and those who delivered by
Table 2 Median total expenditures and total capacity to pay by type of delivery and experience of catastrophic expenses, city of
Lubumbashi, DRC, 2015 (Mann-Whitney test with Bonferroni correction)
Type of delivery Non-catastrophic expenses Catastrophic expenses p
Total (n) Median in US$ (minimum-maximum) Total (n) Median in US$ (minimum-maximum)
Total expenditures for obstetric and neonatal care
Uncomplicated vaginal 906 34 (10–220) 95 38 (10–163) 0.043
Complicated vaginal 356 43 (12–396) 73 42 (12–272) 0.69
Caesarean 104 323 (82–966) 93 388 (108–924) 0.005
Total 1366 38 (10–966) 261 54 (10–924) < 0.001*
Total household capacity to pay
Uncomplicated vaginal 906 104 (20–2462) 95 65 (20–222) 0.03
Complicated vaginal 356 122 (19–3009) 73 54 (20–199) 0.04
Caesarean 104 569 (112–3201) 93 392 (55–1297) 0.031
Total 1366 114 (19–3201) 261 123 (20–1297) 0.015*
*Kruskal-Wallis
Table 3 Incidence of catastrophic expenses by HZ, type and sector of health care facility, Lubumbashi, DRC, 2015
Variables Total Incidence of CE (%) RR 95% CI p
Health Zones < 0.001
Lubumbashi 274 25.9 1
Katuba 181 32.6 1.3 0.9–1.7
Mumbunda 126 18.3 0.7 0.5–1.1
Vangu 127 17.3 0.7 0.4–1.0
Kisanga 133 15.0 0.6 0.4–0.9
Ruashi 354 11.6 0.5 0.3–0.6
Kamalondo 61 8.2 0.3 0.1–0.7
Tshiamilemba 103 7.8 0.3 0.2–0.6
Kenya 82 4.9 0.2 0.1–0.5
Kampemba 186 4.3 0.2 0.1–0.3
Type of facility < 0.001
Health center 684 11.6 1
Sendwe (provincial referral hospital) 74 23.0 2.0 1.2–3.1
General referral hospital 574 20.0 1.7 1.3–2.3
University Clinics of Lubumbashi (UCL) 75 18.7 1.6 0.9–2.6
Polyclinics 220 16.4 1.4 0.9–2.0
Sector of ownership < 0.001
Private, religious
a
214 6.1 1
Public 655 20.5 3.4 2.0–5.8
Para-statal commercial 108 12.0 2.0 1.1–4.1
Private, non-religious 650 15.5 2.6 1.5–4.5
a
Used for comparison because these are the health facilities in which the price of care is most stable and where care is perceived by women to be of good quality
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Table 4 Incidence of catastrophic expenses (CE) by sociodemographic and economic characteristics of women, evolution of the
delivery and length of stay in the maternity unit, Lubumbashi, DRC, 2015
Variables Total Incidence of CE (%) RR 95% CI p
Age (years) 0.10
< 20 172 20.4 1.6 0.9–2.5
20–34 1215 16.1 1.3 0.9–1.9
≥35 240 12.5 1
Marital status < 0.001
Married 1589 15.5 1
Not married 38 36.8 2.4 1.5–3.5
Partner’s age (years) 0.39
< 25 114 14.9 0.8 0.4–1.4
25–34 784 16.7 0.9 0.6–1.3
35–44 589 15.3 0.8 0.5–1.2
≥45 115 19.1 1
Unknown 25 4.0 0.2 0.1–1.1
Wealth quintile < 0.001
*
Q1 (very poor) 302 44.7 22.5 11.0–46.8
Q2 317 31.6 15.9 7.7–33.3
Q3 311 3.2 1.6 0.7–4.1
Q4 344 2.6 1.3 0.5–3.4
Q5 (very rich) 353 2.0 1
Referral status < 0.001
Referred 114 40.4 2.8 2.2–3.6
Not referred 1513 14.2 1
Complications < 0.001
Post-partum infection 50 58.0 9.1 6.4–12.5
Pre & post-partum hemorrhage 86 41.9 6.5 4.6–9.1
Eclampsia 27 40.7 6.4 3.6–10.1
Placenta Prævia 22 31.8 5.0 2.5–8.8
Soft-tissue tears 214 25.7 4.0 2.9–5.6
Placental abruption 20 25.0 3.9 1.7–7.7
Obstructed labor 240 23.3 3.6 2.6–5.1
None 968 6.4 1
Type of delivery < 0.001
Uncomplicated vaginal 1001 9.5 1
Complicated vaginal 429 17.0 1.8 1.4–2.4
Caesarean 197 47.2 5.0 3.9–6.3
Neonatal care < 0.001
Basic 971 9.1 1
Emergency 163 39.9 4.4 3.3–5.8
Intensive 493 21.9 2.4 1.9–3.1
Type of skilled birth attendant < 0.001
Nurses and midwives 1446 14.0 1
General physician 97 29.9 2.1 1.5–2.9
Specialist physician 84 35.7 2.6 1.8–3.4
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caesarean had five times the risk compared to those who
had an uncomplicated delivery.
Among women whose newborns received emergency
or intensive care, the incidence of CE was 2.4–4.4 times
higher compared to mothers of healthy newborns. It was
also more than two times higher when deliveries were
managed by generalist or specialist physicians as op-
posed to nurses and midwives.
Women who did not plan to give birth in the facility
in which they ended up giving birth had nearly twice the
risk of CE as compared to those who delivered in the
planned facility. The length of stay increased the risk of
CE. Women who stayed more than 3 days in the mater-
nity unit had at least twice the risk of CE compared with
those who stayed no more than 3 days.
The multivariable model (Table 5) shows results simi-
lar to those seen in the univariable analyses. Poverty,
management of obstetric or neonatal complications,
provision of care by highly qualified personnel, care pro-
vided in facilities of parastatal entities and referral in the
course of delivery –all factors associated with higher
charges –increased the risk of CE.
Alternatives for the payment of obstetric and neonatal
care
Quantitative aspects
The means of payment of maternity fees differed for
women who suffered CE and those who did not. In Fig. 1,
we see that, even though in both groups the woman and
her partner were the main source for payment of the
maternity fees, the proportion of women assisted by
non-governmental organizations (NGO) and family was
at least twice as high among women with CE as among
those without CE. Among the couples who had paid the
maternity fees themselves, the origin of fees paid were
different between the two groups (p< 0.001). The pro-
portion of those who were able to draw on savings was
higher among women who were not victims of CE
(82.5%) than among those who were (32.7%). Similarly,
the proportion of women who used their trading capital
(funds that enabled the woman or her partner to engage
in commercial activities) to pay the charges for care was
three times higher among women who were not victims
of CE (6.6%) than among those who were (2.0%). The
proportion of couples who had borrowed or requested a
salary advance and that of couples who had sold or
mortgaged household goods to pay the charges for care
was higher among women who had experienced CE as
opposed to those who had not.
Qualitative aspects
Even though women who suffered CE were able to draw
on various options to pay fees, they perceived the cost of
care –unknown at admission –as a great burden which
the whole family had to struggle to confront. Following are
selected statements by participants who experienced CE:
“I didn’t know it was a caesarean, I didn’t even know
how much I had to pay; I was referred urgently from a
health center.”[Participant 1]
“I didn’t know how much it should cost, the nurses
were discussing with my sister.”[Participant 2]
“I planned to save in the last month of my pregnancy,
but the birth was premature, it took us by surprise.”
[Participant 3]
“Not a single medication was given to us by the
maternity [unit]; we always paid for them out of our
own pocket [woman or family] …if we’d had the
money for the hospital stay and the surgical
intervention, I would have left immediately, because I
was not ill.”[Participant 4]
As shown above in the quantitative part, families
resorted to different options to finance health care fees.
“At the time of the last caesarean, my family paid
for everything even though they shouldn’t have; this
time, he (husband) had to get by with his family.”
[Participant 5]
Table 4 Incidence of catastrophic expenses (CE) by sociodemographic and economic characteristics of women, evolution of the
delivery and length of stay in the maternity unit, Lubumbashi, DRC, 2015 (Continued)
Variables Total Incidence of CE (%) RR 95% CI p
Delivery facility 0.03
Planned 1287 15.0 1
Not planned 340 20.0 1.3 1.1–1.7
Length of stay (days) < 0.001
≤3 1143 12.4 1
4–14 419 19.8 1.6 1.2–2.0
≥15 65 55.4 4.5 3.4–5.7
*Chi-squared test for trend
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“My husband gave me everything, I don’t know how he
did it, I don’t know how much he earns approximately
per month; I think at least he did what was necessary
to save during the pregnancy.”[Participant 6]
“My husband hasn’t worked for several months, and I
didn’t work either in the last months of my pregnancy:
I had no money when I delivered, I didn’t know who
would pay these fees; but my family and my in-laws
did.”[Participant 7]
“In any case, my husband is a man: he had to
manage, this time my family should not have to take
on so much expense.”[Participant 8]
Consequences to households of catastrophic expenses
associated with obstetric and neonatal care
When women experience CE for obstetric and neonatal
care at health facilities, it changes their standard of living
and households must confront difficult choices: “treat
the woman and the newborn and let the family die of
hunger, or not”. This study allowed us to observe that
there are many consequences of these expenditures.
Economic Consequences
In terms of economics, women who had CE were first of
all insolvent. They were indebted and used their trading
funds or sold their goods to pay these bills. Because of
their insolvency, these women were detained in the ma-
ternity unit and denied care such as bandages, analge-
sics, and newborn cord care.
“Since I was in the hospital, I couldn’t trade and I
couldn’t help my husband: everything was screwed
[messed up]. On his own, he had to pay for everything:
food, school fees, transportation, clothes, etc. In these
conditions, that’s how we didn’t have money to pay for
health care.”[Participant 9]
“I had to stop my petty trading, to stay in the hospital
until someone pays all the bills.”[Participant 10]
“As for the children, I have seven, and they stay by
themselves at home because their dad is a motorcyclist
[motorcycle taxi driver] and he stays downtown late to
earn what’s needed; my oldest daughter even got
pregnant.”[Participant 11]
“I had asked the nurses to keep my baby if they
wanted, and to let me go look for money until I could
pull together the necessary sum.”[Participant 12]
“We pawned some of our clothes, the chairs, our
flatscreen and my capital (trading money), with a view
to getting the first installment of the fees …when the
hospital asked us to pay the rest, we took on debt from
one of our neighbors.”[Participant 13]
Quality of care during the stay in the maternity
They were also victims of disrespectful care.
“There were days when I didn’t receive paracetamol
and my dressing wasn’t changed because I hadn’t yet
Table 5 Determinants of catastrophic expenses among
parturient women surveyed, Lubumbashi, DRC, 2015
Variables [n= 1627; CE = 261]
aOR 95% CI p
Sector
a&b
0.65
Public vs private religious 1.3 0.6–2.6
Parastatal entity vs private religious 1.3 0.5–3.8
Private non-religious vs private religious 1.5 0.7–3.2
Not married vs married
a&b
1.6 0.7–3.4 0.24
Socioeconomic level
a&b
< 0.001
Q1 vs Q5 38.7 17.6–85.2
Q2 vs Q5 23.5 10.7–51.8
Q3 vs Q5 1.6 0.6–4.2
Q4 vs Q5 1.3 0.5–3.6
Referred vs not referred
a
1.9 1.1–3.6 < 0.001
Type of delivery
a
< 0.001
Complicated vaginal vs uncomplicated 1.9 1.2–2.9
Caesarean vs uncomplicated 7.5 3.6–15.4
Obstetric complications
b
< 0.001
Infections vs none 20.8 7.4–58.0
Pre & post-partum hemorrhage vs none 9.4 5.0–17.7
Eclampsia vs none 4.7 1.5–15.0
Placenta Prævia vs none 5.6 1.5–21.0
Soft-tissue tears vs none 4.2 2.5–7.1
Placental abruption vs none 2.4 1.2–9.5
Obstructed labor vs none 4.8 2.8–8.2
Newborn care
a
< 0.001
Emergency vs basic 2.8 1.4–5.4
Intensive vs basic 2.9 1.9–4.3
Skilled birth attendant at delivery
a
< 0.001
Generalist physician vs midwives 2.2 0.9–5.1
Specialist physician vs midwives 3.9 1.8–8.5
Length of stay (days)
b
< 0.001
3–14 1.3 0.9–1.9
≥15 3.6 1.5–8.1
a
included only in model 1, built on the basis of care received by women and
newborns;
b
included only in model 2, built on the basis of complications
requiring obstetric and neonatal care;
a&b
included in both models
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paid even a part of the fees for treatment …my baby’s
cord was also not cleaned because I hadn’t paid for
their medications.”[Participant 14]
“Because I was slow to pay for care, the person who
took care of me wouldn’t greet me in the morning; she
didn’t ask me how I’d slept, either.”[Participant 15]
“Before I’d paid for the care, when the midwife
changed my dressing, she didn’t speak to me. When
she spoke to me, it was to remind me that I should pay
the bill. I couldn’t even complain about the pain when
she rubbed my wound …I was afraid she would stop
the dressing since I hadn’t yet paid.”[Participant 16]
Household subsistence
After leaving the maternity, women who were in debt or
those who had lost their trading income or goods were un-
able to pay their rent, their children’s school fees, or were
obliged to reduce food consumption in the household.
“Since I got out of the maternity, we haven’t paid our
rent. The landlord threw us out. And since we weren’t
able to find food with the children, I came here to my
parents’house until I can resume my activities, if I
find money …the friends we borrowed from for the
maternity come every day demanding payment and
threatening to take us to court.”[Participant 17]
“My two children don’t go to school because we haven’t
paid the fees for 3 months …they are with my parents,
because here sometimes we go to sleep hungry.”
[Participant 18]
Relationships with partner and family
Women have been victims of marital conflict and mis-
treatment –verbal abuse, threats of divorce, disputes
with in-laws, denial of paternity, absconding of partner,
financial deprivation, or dissolution of the partnership—
since they are viewed as the source of excessive ex-
penses. The following statements shed light on some of
the consequences on households of catastrophic expen-
ditures tied to obstetric and neonatal care.
“Since the delivery, my husband has left the house on
the pretext that he was going to look for money …his
friends and family have told me that I made him carry
the responsibility for the pregnancy.”[Participant 19]
“We hadn’t quarreled, but he didn’t come see me at
the hospital, not a single member of his family came to
see me; they didn’t even think that I also needed to
eat, it was my aunt who always brought me food.”
[Participant 20]
“My mother-in-law said I wasn’t fit because I delivered
by caesarean.”[Participant 21]
“They (my in-laws) told me that I was the cause of the
unhappiness or curse of their child [my husband] …
because of me, everything he does doesn’t work …and
that my pregnancy made him poor.”[Participant 22]
Fig. 1 Modes and payment options for charges for care for households
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Access to care for other members of the household
CE has likewise been at root of inability to financially ac-
cess other care (postnatal and preschool consultations,
consultations for illness) for the woman and other mem-
bers of the household. This has led them to resort to
other means of management (self-medication, traditional
care, or prescriptions in a drugstore).
“Since I had no money to go to the health center, when
my daughter fell ill, I went to get, on credit, malaria
medications from the pharmacy of my friend’s little
brother.”[Participant 23]
“After discharge from the maternity, I didn’t go back to
the hospital for the weighing and vaccination of the
child: I didn’t have the fees for transport and to pay to
the hospital …I’m using traditional medicine for
hemorrhoids which bother me since the delivery.”
[Participant 24]
In Fig. 2, we show a schematic of the consequences tied
to CE from obstetric and neonatal care in Lubumbashi.
Discussion
In this study, we found that 16.0% of women were
victims of CE linked to obstetric and neonatal care. This
incidence was higher if the women were poor, had
maternal or neonatal complications, or were treated by
highly trained health care personnel. This is higher than
the overall incidence of catastrophic expenses due to
health care reported in 2014 in DRC by the World Bank,
which was 10.8% [15]. In an earlier study [16], we
showed that, given that the transportation network in
Lubumbashi is easily accessible and affordable, the con-
tribution of the price of transport to the total payment
at the time of delivery remains low (3.2–8.2%). Thus,
even without taking transport into account, the inci-
dence of CE in Lubumbashi is higher than in urban set-
tings in various sub-Saharan African countries [28–31].
In our study, we found that women in the two lowest
wealth quintiles had, respectively, 23 and 16 times higher
risk of CE than those in the highest. In several cities of
Africa, similar results have been reported [28–32]. It is
not surprising that without health insurance or universal
coverage, the poor should be at higher risk of CE. The
dependence of the health care facilities and health care
system on user payments has weakened the leadership of
the state and its regulatory power over price-setting for
care so that, in a city where more than 60% of the facilities
are private [19] and where neither mutual aid organiza-
tions or health insurance exists [18], it is cost of living for
health care providers, rather than rational factors linked
to the functioning of the facility, that determines the
variability in the price of care. Each facility has its prices
for care, and within a facility, for the same acts, women
may pay different amounts. This is seen even in public
facilities presumed to function for the public good [7].
Further, 5% of the revenue of these facilities is paid to the
central office of the HZ and so on, up to the Ministry of
Health [11].
Fig. 2 Short-term consequences of catastrophic expenses (CE) linked to obstetric and neonatal care in the city of Lubumbashi, DRC, 2015. (points
framed in black: direct consequences of CE; points framed in dashed red lines: indirect consequences of CE; black arrows: relationships among
consequences of CE)
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Complications and the extra fees they entail also increase
risk of CE. We noted that when there were complications at
delivery, women had at least twice the risk of CE. Medical
and nursing services, the amount of medications used, new-
born care, the length of stay, and complementary care in the
case of referrals are, in general, responsible for this increase.
High-quality obstetric care certainly has costs, whether
these are supported by users or by other players [33].
When health expenditures become catastrophic, they
constitute a barrier to the use of care, limit its quality,
and reinforce the poverty of households [10]. Insufficient
salaries from the state lead health care providers to im-
pose additional fees for each service [34]. To improve
their income, the GRHs and HCs overlap the services
they offer in their care bundles [35]. When primary care
that would normally be provided at the HC level is pro-
vided in the GRHs or polyclinics, it costs at least twice
as much. Women pay different amounts for the same
services according to whether they are cared for by a
midwife, a generalist physician, or a specialist physician.
HCs are over-medicalized, offering services that ought to
be offered only at higher levels of the health care system.
This contributes to the increase in price of primary care
[35], and to a lack of continuity of care within the system;
women who are referred have to pay more than those
who are not. Furthermore, in addition to paying for ser-
vices, women must buy medications, supplies, and equip-
ment, either from providers or from the pharmacy in the
hospital or from outside the hospital. Because this is a sec-
tor in which the state has little control [11], the risk of
overbilling is very high, given that these things constitute
a source of extra income for the facilities and the staff.
Most women who encounter these exorbitant charges
are not prepared for them, because they don’t anticipate
having complications. The consequences they face are
major, ranging from detention in the maternity unit in
the short term, to sliding further into poverty in the
medium term. Several studies [10,28,36] report similar
observations and also note that these consequences are
likely to persist beyond the short to the medium, and
long term in the life of the household.
Mechanisms for coping with direct out-of-pocket
payments
Why, in a city where 70% of the population is poor [9]
and care financially unaffordable [7], does the rate of de-
liveries attended by skilled personnel remain high?
Mobilization of clan in the form of contributions from close
and extended family members to pay for pregnancy –and
delivery–related health care not only attenuates economic
consequences but also justifies subsequent health care
provider-assisted deliveries despite these families’poverty.
But this clan solidarity has consequences. Because they are
considered the cause of excessive expenditures, women
whose health care costs reach catastrophic levels because of
complications may become victims of mistreatment such as
verbal abuse, disputes with in-laws, denial of paternity, aban-
donment by partners, financial deprivation, even divorce –
all of which are factors likely to reinforce their poverty [10].
Alternatives for health care financing in the DRC
Initiatives that aim to alleviate the price of obstetric care –
either through result-based or health systems strengthen-
ing approaches–have been tested in several countries in
Africa [37–46]. De Brouwere et al. [47] report that results
are mixed. According to these authors, “the schemes
studied in the context of financing obstetric care have not
shown, in an absolute way, either growth in use of services
or improvement of results in terms of health. In terms of
equity, there was little support for reduction of CE”[47]
(our translation).
Witter et al. [48] document the elements to take into
account to implement a policy to protect women from
high price of care. These elements corroborate the deter-
minants of CE we observed in the city of Lubumbashi.
They write: “adopting a good package of measures for a
given context cannot be done in a mechanical fashion.
The balance between the constraints of supply and de-
mand may vary, and the conception of an appropriate
policy should consider the availability of resources, the
cultural expectations of roles and responsibilities, as well
as the way in which the health services are financed and
organized”(our translation). Emphasizing the determi-
nants of CE in the city of Lubumbashi, our study shows
that approaches aiming to protect women from CE
should not be one-dimensional. On the demand side,
there is the socioeconomic level of the population; on
the supply side, there is the organizational context, the
quality of care, available financing, management of hu-
man resources for health, and cost of living.
Dimensions like these can only be taken into account in
the context of a broad strategy of financing and health sys-
tems strengthening. This was the case for Morocco [49]
and Rwanda [50], which obtained remarkable results in
terms of maternal health after considerable reforms and a
large increase in the financing of the health care system.
This has not been the case in the DRC because the
National Plan for Health Development (2010–2015) has
not been fully implemented. According to the United
Nations Millennium Project 2005 [51], “practical invest-
ments and policies for a functioning health system include
training and retaining competent, motivated health workers,
strengthening management systems, providing adequate
supplies of essential drugs, and building clinics and labora-
tory facilities. Eliminating user fees for essential health ser-
vices, improving community health education, promoting
behavior change, and involving communities in decision-
making and service delivery are also critical measures”.
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For example, in the current context of organization and
provision of obstetric and neonatal care in Lubumbashi, it
is urgently necessary to reinforce the leadership of the
Ministry of Health to oversee and regulate the establish-
ment and functioning of health care facilities that provide
obstetric and neonatal care. The ministry should also over-
see and regulate respect for the technical platform and
continuity of care between the different levels of the health
care system, as well as the standardization of fees accord-
ing to the type of care provided to mothers and infants.
Study limitations
In this setting, patients don’t always request bills or
invoices for expenses; this carries with it a risk of bias,
since women may have forgotten an expenditure made
by a family member [21], while staff may have in-
tentionally avoided mentioning informal payments like
gratuities [10]. Such a bias could have contributed to an
underestimation of payments by the woman. To signifi-
cantly reduce the impact of this bias, we triangulated the
data collected from various sources, as described in the
methods. It is also possible that the food expenses of
households were underestimated given that purchases
are very fragmented over the course of the month [21],
which increases the risk of forgetting some during our
interviews. Such a bias would also have caused an
underestimate of the incidence of CE.
Conclusion
In this study, we measured the incidence of CE, its
determinants, coping mechanisms used by households
to pay the price of care, and identified socioeconomic
and health consequences of CE.
We observed that direct payment for obstetric and
neonatal care causes CE. The women who are vulnerable
to CE are those with a low socioeconomic status and
who have obstetric or neonatal complications. Also, the
dependence on the health care system, including pay-
ments to staff, on user fees increases the risk of these ex-
penditures. CE causes a cycle of poverty and constitutes
a barrier to universal coverage of respectful, high-quality
basic and emergency obstetric and neonatal care.
To guarantee universal coverage of high-quality health
care, we suggest that the government and funders in DRC
support initiatives to put in place mutual-aid health risk
pools and health insurance, which are still rare in the
DRC, and that they introduce and institutionalize free
maternal and infant care.
Also, by guaranteeing a decent and regular payment of
providers and improving the financing and functioning
of health care facilities, the government could substan-
tially reduce the portion of system expenditures carried
by households via direct payment as a condition for ac-
cess to care.
Additional files
Additional file 1: Expenses for obstetric and neonatal care in
Lubumbashi: data collectiontool. (DOC 349 kb)
Additional file 2: Interview guide. (DOCX 15 kb)
Additional file 3: Description of data. (XLSX 596 kb)
Abbreviations
95%CI: 95% confidence interval; aOR: Adjusted Odds Ratio; CDF: Congolese
Francs; CE: Catastrophic expenditure; DHS: Demographic and Health Survey;
DRC: Democratic Republic of the Congo; EmNC: Emergency Neonatal Care;
GFF: Global Financing Facility; GRH: General Reference Hospital; HC: Health
Centre; HZ: Health Zone; NGO: Non-governmental organizations;
PCA: Principal component analysis; Q: Quintile; RR: Relative Risk;
UCL: University Clinics of Lubumbashi; UN: United Nations; US$: US Dollar;
WHO: World Health Organization
Acknowledgements
Not Applicable.
Authors’contributions
AMN, FKM, MDW and PD conceptualized the research question. AMN
conceived of the study and its design and participated in its coordination,
conducted the statistical analysis, wrote the methods, results, helped to draft the
manuscript and incorporated comments from co-authors for the final draft. FKM
participated in the design of the study and coordination (collection of data) and
helped to draft the manuscript. MDW conducted the statistical analysis, wrote
the methods and proofread the manuscript critically. PD wrote the first draft of
the paper, wrote the background information, discussion and proofread the
drafts before submission. KDC interpreted data and critically revised the final draft.
All authors read and approved the final draft of the manuscript.
Funding
This research was funded by the l’Académie de Recherche et d’Enseignement
Supérieur (ARES) in the P3-Lub03 program. Funding covered only the
collection of data and the initial English translation of this manuscript.
Availability of data and materials
All data generated or analyzed during this study are included in this
published article and its supplementary information files.
Ethics approval and consent to participate
Written informed consent was obtained from each woman prior to inclusion
in the study and was reassessed at each contact. The study protocol was
approved by the Comité d’Éthique Médicale (CEM; Medical Ethics Committee)
of the University of Lubumbashi (CEM-UNILU: UNILU/CEM/010/2011).
Consent for publication
Participants gave consent for direct quotes from interviews to be used in
this manuscript.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Unité d’Epidémiologie et de Santé de la mère, du nouveau-né et de
l’enfant, École de Santé Publique, Université de Lubumbashi, Lubumbashi,
Democratic Republic of the Congo.
2
School of Interdisciplinary Arts and
Sciences, University of Washington Tacoma, Tacoma, USA.
3
Department of
Global Health, University of Washington, Seattle, USA.
4
Centre de recherche
en Epidémiologie, Biostatistiques et recherche clinique, École de Santé
Publique Université Libre de Bruxelles, Brussels, Belgium.
5
Centre de
Recherche en Politiques et systèmes de santé-Santé internationale, École de
Santé Publique Université Libre de Bruxelles, Brussels, Belgium.
Ntambue et al. BMC Public Health (2019) 19:948 Page 13 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Received: 19 September 2018 Accepted: 30 June 2019
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