Quality of Maternal Health Services and their Utilization in Five States of Nigeria

Anastasia J. Gage, Ph.D.a, Onyebuchi Ilombu, MPH a, and Akanni Ibukun Akinyemi, Ph.D. b a Tulane University, b Obafemi Awolowo University

August 13, 2013

Corresponding author: Anastasia J. Gage, Department of Global Health Systems and Development, Tulane University, 1440 Canal Street, Suite 2200 TB-46, New Orleans, LA 70112, Phone: 504-988-3647, Fax: 504-988-3653, Email: agage@tulane.edu; agage11961@aol.com

Acknowledgments

The data analyzed in this paper was funded by the U.S. Agency for International Development (USAID) through Cooperative Agreement GHA-A-00-08-00003-00. The authors’ views expressed in this publication do not necessarily reflect the views of USAID or the United States Government. USAID played no role in the study design; in the collection, analysis and interpretation of data; in the writing of the article; and in the decision to submit it for consideration for presentation.

Abstract Using linked data from the 2009 COMPASS health facility and household surveys, this paper

examines the association of the quality of maternal health services with their use in the past five

years in five states of Nigeria. The results of multilevel logistic regression models revealed a strong

positive association between the availability of essential delivery care equipment and supplies and

the odds of initiating antenatal care in the first trimester of pregnancy. The odds of institutional

delivery were significantly higher in Local Government Areas (LGAs) that scored higher on

management practices that were supportive of quality maternal health services than in LGAs that

scored lower, after controlling for other factors. More comprehensive provider training on maternal

health had a significant negative association with skilled attendance at birth and institutional

delivery. The findings suggest that efforts to increase the utilization of maternal health services

should improve health facility management practices, ensure the availability of essential equipment

and supplies, and conduct further research to better understand how provider training may

influence service use.

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Introduction

Although substantial progress has been made in reducing maternal mortality worldwide, the

World Health Organization estimates that in 2010, 287,000 women died from potentially avoidable

or preventable problems in pregnancy or childbirth (WHO, 2012). Sub-Saharan Africa accounted for

more than half of the global burden of maternal deaths, with women in the region having a 1 in 39

chance of dying in pregnancy or child birth compared to a 1 in 3,800 risk in developed countries

(WHO, 2012) – the largest difference between poor and rich countries on any health indicator.

Nigeria, which constitutes less than 1 percent of the world population, had an estimated maternal

mortality ratio of 630 maternal deaths per 100,000 live births in 2010 and accounted for 14 percent

of global maternal deaths. Uptake of maternity care is relatively low in Nigeria. Data from the 2008

Nigeria Demographic and Health Surveys revealed that 58 percent of women who had a live birth in

the five years preceding the survey sought antenatal care from a skilled provider (doctor, nurse,

midwife or auxiliary nurse/midwife) and 48 percent reported visiting antenatal clinics at least four

times during pregnancy. Thirty-five percent of births occurred in a health facility and 39 percent

were assisted by a skilled provider (National Population Commission and ICF Macro, 2009). In light

of achieving the Millennium Development Goal of reducing the maternal mortality ratio by three-

quarters and improving access to reproductive health, there is an urgent need to examine how the

quality of care and other factors may improve the utilization of maternal health services.

It is widely acknowledged that the quality of health services has significant implications for

health outcomes. Empirical studies have confirmed that poor quality services may be associated

with low uptake of care and non-effective and non-timely management of life-threatening

complications of pregnancy and childbirth (Althabe et al., 2008; Fauveau and de Bernis, 2006; Raven

et al., 2012). The lack of sufficient drugs, reagents and instruments often prevents health workers

from preventing fatal outcomes and poor patient-provider interaction often may leave women

uninformed with little understanding of the importance of maternal health services (Conrad et al.,

2012). By comparison, receipt of good quality antenatal care has been found to significantly

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increase the chances of delivery attendance by skilled medical personnel (Adanu, 2010). It has also

been noted that the availability of quality services may not produce desired health outcomes if there

is little possibility for individuals to make healthy decisions and act on those decisions (World Health

Organization, 2010), suggesting the need for examining the relative contributions of supply and

demand-side factors to maternal health outcomes.

There is no consensus on the definition of the quality of maternal health care, partly due to

the inherent complexities of measuring the concept (Raven et al., 2012). Early attempts to define

and measure the quality of maternal health services were based on the quality of health framework

developed by Donabedian (1988), which focused on three aspects of health service delivery:

structure, process, and outcome. Structure refers to characteristics of the setting in which health

services are delivered, including the physical equipment, infrastructure, human resources, as well as

organizational characteristics, staff training, and remuneration. Process refers to the technical and

interpersonal aspects of provider-client interactions in health service delivery. This includes

diagnosis, patient education, communication and preventive care. Outcomes include health status,

health behaviour, knowledge, and client satisfaction. Hulton et al.’s (2005) quality of care

framework is instructive as it separates quality into two constituent parts: quality of the provision of

care within the institution and quality of care as experienced by users. The framework identifies 10

elements in assessing the quality of maternal health services, six of which relate directly to the

provision of care (human and physical resources; referral system; maternity information systems;

use of appropriate technologies; internationally recognized good practice; and management of

emergencies). The other four elements are related to women’s experience and include cognition;

respect; dignity and equity; and emotional support).

Studies in sub-Saharan Africa have used different methodologies for evaluating the quality of

care in maternal health, including facility audit and clinical records (Sharan et al., 2011), exit

interviews (Osungbade et al., 2008), and community-based surveys (Galadanci, 2007). Such

evaluations have focused on assessing infrastructure, equipment, and supplies; type of care

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provided; provider-client experiences (Conrad et al., 2012); the availability of skilled providers

(Rockers et al., 2009); the actual services that are performed during antenatal care visits such as

abdominal examinations, blood pressure measurement, blood and urine examinations (Galadanci et

al., 2007); and the availability of services such as emergency obstetric care and neonatal health care;

referral systems; and transportation (Kongnyuy et al., 2009). The interpersonal dimensions of care

are often overlooked, partly due to lack of data. These aspects include the social and psychological

aspects of care – welcoming of clients, staff helpfulness and friendliness, provider communication,

and patient understanding.

Studies have generally shown that maternal health services in some countries of sub-

Saharan Africa are deficient in terms of providing basic emergency obstetric care (Conrad et al.,

2012; Ijadunola et al., 2010) and lack the capacity to perform tests for syphilis and bacteriuria or

address the effects of severe anemia and malaria in pregnancy (Osungbade et al., 2008). Maternal

health services have also been noted to lack essential drugs, reagents and instruments, to have poor

quality patient education, to lack timely referral and transportation services, and to have an

inadequate number and mix of skilled providers (Kongnyuy et al., 2009). Poor record keeping in

maternal health facilities has also been noted to hinder patient monitoring (Sarker et al., 2010).

Many studies have also evaluated maternal health care utilization outcomes in their assessment of

the quality of maternal health services and have concluded that in many parts of sub-Saharan Africa,

levels of maternal health care are poor (Ijadunola et al., 2010). However, few studies have linked

the supply aspects of maternal health care to demand for maternal health services.

Tremendous resources have been expended on health facility surveys in sub-Saharan Africa.

However, few of them are conducted in tandem with or designed to be linked to household surveys,

making it difficult to assess the influence of service quality on the utilization of maternal health

services. The objectives of this study were to examine the association between the quality of

maternal health services and their use in five states of Nigeria. It is hypothesized that women would

be more likely to use maternal health services in local government areas (LGAs) with higher indices

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of (a) provider training in maternal health care; (b) supportive maternal health care management

practices; (c) availability of basic equipment and supplies for the provision of antenatal and

delivery/newborn care services.

Data

The data for the present study were drawn from the 2009 end-of project survey for the

Community Participation for Action in the Social Sectors (COMPASS) project in Nigeria. The study,

which consisted of a health facility survey, a household survey, and a school survey, was

implemented by MEASURE Evaluation/Tulane University and the Center for Research, Evaluation

and Resource Development (CRERD). The survey was conducted in 51 local government areas

(LGAs) in the Federal Capital Territory (FCT) and the states of Bauchi, Kano, Lagos, and Nasarawa

where the COMPASS project was implemented. The purpose of COMPASS was to integrate health

and education by enhancing FP/RH services, promoting child survival and improving basic literacy

and numeracy. The Institutional Review Board of Tulane University and CRERD granted ethical

approval for the study.

The household survey used a multi-stage stratified sampling design and collected

information on reproductive and maternal health, child health, and primary school education among

a representative sample of women aged 15-49 and men aged 15-64. At the first stage of sampling,

enumeration areas were selected within each state, with probability proportional to the number of

LGAs per state as follows: 1:1:2:2:1 for Bauchi, FCT, Kano, Lagos, and Nasarawa, respectively. At the

second stage of sampling, 25 households were selected within each sample enumeration area using

systematic random sampling. Fieldwork for the household survey started in mid-June 2009 and was

completed by early July, 2009.

The survey of primary health care facilities (comprehensive health care centers, public

primary health care centers, health clinics, maternity clinics, private clinics, uniformed services

clinics, health posts, and dispensaries) and patent medicine vendors (PMVs) was implemented at the

same time as the household survey. The sample for the facility survey was drawn from a list of all

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public and primary health care facilities and PMVs serving the population interviewed in the

household survey. As a result, the facility survey included some service delivery points that were

located outside of the enumeration areas selected for the household survey. Due to sample size

considerations, the LGA (as opposed to the enumeration area) was used to link the facility and

household survey in order to determine the influence of maternal health service quality on

individual health outcomes. To the extent possible, all primary health care facilities and PMVs were

included when defining LGA-based measures of HF readiness and the quality of care.

Outcomes

Four outcomes were examined: initiation of antenatal care (ANC) in the first trimester of

pregnancy; receipt of four or more ANC visits; delivery assistance by a skilled provider; and delivery

in a health facility. All outcomes were dichotomous.

LGA-level Variables

Four variables measured the quality of maternal health care at the LGA-level: (a) index of

provider training in maternal health care; (b) index of supportive management practices; (c) index of

the availability of basic equipment and supplies for the provision of antenatal services; and (d) index

of the availability of basic equipment and supplies for the provision of delivery/newborn care

services.

Index of provider lifetime in-service training in maternal health (antenatal care (ANC)/ postpartum

care (PPC) and delivery/newborn care): Eight items measured whether the ANC/PPC provider had

ever received in-service training in each of the following subjects: (a) antenatal care; (b)

counseling/health education for maternity clients; (c) management of risk pregnancies; (d) mother-

to-child transmission of HIV/AIDS; (e) postnatal care; (f) family planning; (g) sexually transmitted

infection; (h) other subjects. Each component was a dichotomous variable measuring whether

training in a given subject had been received. An additional 8 items measured whether the

delivery/newborn care provider had ever received in-service training in each of the following

subjects: (whether the health care provider had ever received training on the following subjects: (a)

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care during labor and delivery; (b) use of partograph; (c) life-saving skills/emergency complications;

(d) other delivery care subject; (e) neonatal resuscitation; (f) mother-to-child transmission of

HIV/AIDS; (g) exclusive breastfeeding; and (h) other newborn care training. Cronbach’s alpha for the

resulting index was 0.9539. The index ranged from 0 to 16. The LGA-based index represented the

mean provider MH training index per facility in the LGA. The LGA-based index ranged from 0 to 9,

with an average of 2.689 [SD = 2.324] per LGA surveyed.

Index of management practices supportive of quality maternal health (ANC/PPC or

delivery/newborn care) services: Components of this 28-item measured the presence of observed

up-to-date client registers with entry in the past 7 days; availability of systems for client feedback;

content of supervisory visits of ANC service provision in the past 6 months; and routine use of quality

assurance methods. Questions on use of quality assurance methods asked non-PMVs whether any

of the following methods of quality assurance were routinely used by the facility: (a) supervisory

checklist for health system components (e.g., service-specific equipment, medications and records)

based on standards and protocol; (b) supervisory checklist for health service provision (e.g.,

observation checklist) based on standards and protocol; (c) system for identifying and addressing

quality of care that is implemented by staff or specific service level; (d) facility-wide review of

mortality; (e) periodic audit of medical records or service registers; (f) quality assurance

committee/team; (g) regional/district health management teams; and (h) other method.

Components pertaining to ANC supervision measured (h) number of times in the last six

months the provider’s ANC and/or PPC work has been supervised and for the most recent

supervisory visit, whether the supervisor (i) checked the provider’s records/reports; (j) observed

his/her work; (k) provided feedback on his/her performance; (l) provided updates on administrative

or technical issues related to his/her work; (m) discussed problems the provider had encountered;

(n) discussed job expectations; and (n) anything else.

Components pertaining to supervision of delivery/newborn care measured (h) number of

times in the last six months the provider’s delivery/newborn care was supervised and for the most

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recent supervisory visit, whether the supervisor (i) checked the provider’s records/reports; (j)

observed his/her work; (k) provided feedback on his/her performance; (l) provided updates on

administrative or technical issues related to his/her work; (m) discussed problems the provider had

encountered; (n) discussed job expectations; and (n) anything else.

Components pertaining to the availability of systems for client feedback asked whether the

health facility had the following systems for determining client opinion about the health facility or its

services: (o) suggestion box; (p) client survey form; (q) client interview; (r) other system. The variable

measuring up-to-date ANC client registers consisted of four categories: no register, register not seen,

register seen – last entry more than 7 days ago, and register seen – entry in past 7 days.

Components pertaining to supervision measured (h) number of times in the last six months the

provider’s delivery/newborn care was supervised and for the most recent supervisory visit, whether

the supervisor (i) checked the provider’s records/reports; (j) observed his/her work; (k) provided

feedback on his/her performance; (l) provided updates on administrative or technical issues related

to his/her work; (m) discussed problems the provider had encountered; (n) discussed job

expectations; and (n) anything else.

The variable measuring up-to-date birth registers consisted of four categories: no register,

register not seen, register seen – last entry more than 7 days ago, and register seen – entry in past 7

days. One component of the index measured whether a skilled birth attendant (doctor, nurse or

midwife) was present at the facility or on call 24 hours a day, including weekends to provide delivery

care and their actual involvement in conducting deliveries. This variable was coded as follows: 4 if a

skilled attendant was present and always conducted deliveries; 3 if a skilled attendant was present

but deliveries were sometimes conducted by primary or auxiliary level staff; 2 if a skilled attendant

was on call and always conducted deliveries; 1 if a skilled attendant was on call but deliveries were

sometimes conducted by primary or auxiliary level staff; and 0 if a skilled attendant was not present

or on call 24 hours a day, including weekends, to provide delivery care. The resulting additive

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facility-based index ranged from 0 to 23 and had a Cronbach’s alpha of 0.9109. Our LGA-based

index was the mean management practices index per MH non-PMV in the LGA.

Index of essential equipment and supplies for quality ANC and PPC services: The index comprised the

following essential equipment: (a) blood pressure gauge; (b) stethoscope; (c) fetal stethoscope.

These components of the index were binary and measured the availability of the equipment. Other

components of the scale measured:

Availability of the following medicines for treating pregnancy complications: (f) amoxicillin; (g) contrimoxazole;

Availability of the following first line antimalarials: (h) Artemisine (Cotecin); (i) Coartem; and (j) Quinine;

Availability of the following (additional) medications for treating the three common STIs, namely, gonorrhea, chlamydia, and syphilis: (k) Cotrimoxazole (Septrin); (l) Doxycycline PO (Vitadar); (m) Erythromycin oral; (n) Benzathine benzyl penicillin injection (IM); (o) Benzyl Penicillin (Procaine) injection (IM/IV); (p) Streptomycin injection.

Availability of Sulphadoxine-Pyrimethamine: (q) Amalar; (r) Fansidar;

Availability of tetanus toxoid vaccine (in stock)

With the exception of tetanus toxoid vaccine, which was binary, each of the other components of

the scale comprised three categories: observed, reported and not available, which were coded 2, 1,

and zero, respectively. No data were collected on medication for treating trichomoniasis or on

equipment and supplies for conducting diagnostic tests for anemia, urine protein, urine glucose or

syphilis. The resulting 16-item facility-based index had a Cronbach’s alpha of 0.9269 and ranged

from 0 to 28. Our measure of the LGA index of essential equipment and supplies was the mean index

per health facility in the LGA and ranged from 0 to 23, with a mean of 8.956 [SD = 5.209] per LGA

surveyed.

Index of essential equipment and supplies for quality delivery and newborn care services: The index

comprised the following essential equipment and supplies for delivery: (a) skin antiseptic (e.g.,

chlorhexidine, savlon, detol); (b) intravenous infusion set; (c) injectable ergometrine; (d) syringes

and needles; (e) suture material with needle; (f) sterile scissors/blade; (g) needle holder; (h) manual

vacuum aspirator; and (i) dilation and curatage kit. Other components of the index measured the

availability of the following supplies for the baby: (j) bag and mask or tube and mask for baby

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resuscitation; (k) baby scale; (l) baby height scale; (m) tape rule; (n) mucous extractor; and (o) cord

ties or clamps. All components of the index were binary and measured the availability of a given

item. The resulting 15-item facility-based index had a Cronbach’s alpha of 0.9739 and ranged from 0

to 15. Our measure of the LGA index of essential equipment and supplies for delivery and newborn

care was the mean index of delivery/newborn care health facility in the LGA and ranged from 0 to

15, with a mean of 6.4 [SD = 5.237] per LGA surveyed. Each of the above-listed indices was

categorized into a binary variable indicating whether the LGA was at/above or below the median

value of the index of interest for all LGAs included in the analysis.

Individual-level variables

The analysis also controlled for the following individual-level variables: age (as reported in

continuous years); highest level of school attended (none (reference group), primary, or secondary

or higher); marital status (married (reference group); living together; or not in union); type of place

of residence (rural (reference group) versus urban/semi-urban); state (Lagos (reference group);

Bauchi, Kano, Federal Capital Territory, or Nasarawa); household wealth (low (reference group),

medium or high); and perception of distance as a big problem in accessing health services (yes or

no). Household wealth represented terciles of an index constructed from the presence of the

following amenities or items in the household, using principal components analysis: refrigerator,

electricity, piped water, flush toilet, a bicycle, a motorcycle, a car, television, radio, and a

telephone/cellular phone). The first component was used as the measurement of household wealth

since it explained the major part of the common variances of all ten components (44.2 percent) and

the scree plot inspection revealed a distinct one-factor solution. The Kaiser-Meyer Olkin measure of

sampling adequacy was 0.867 for the household wealth index.

Methods

We used F-tests to examine the differences between LGAs in prevalence of the outcomes of

interest by measures of the quality of maternal health care. Multilevel logistic regression was used

to estimate the association of LGA-based quality of care measures with the outcomes of interest,

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thereby accounting for the hierarchical clustered structure of the data, which if ignored, could

generate improper estimates of the standard errors. Multilevel models also incorporate random

effects at the LGA and individual levels in the regressions to account for unobserved individual and

LGA-level factors. Separate regression models were estimated for each outcome using the

generalized latent and mixed model command (GLLAMM) in Stata 11.0 (Rabe-Hesketh and Skrondal,

2008).

We estimated odds ratios (ORs) and 95percent confidence intervals (CIs) from regression

statistics. To test for multicollinearity, we calculated variance inflation factors (VIFs) for explanatory

variables included in each regression. The mean VIF was 1.92 and the highest was 2.73, signifying

that each independent variable was not highly correlated with the other independent variables in

the regressions. Intra-class correlation coefficients (ICC) were used to evaluate how the outcomes of

interest varied between LGAs and may be interpreted as the proportion of variation in a given

outcome that can be explained at the LGA level. If most of the variation in a given outcome is

explained by individual-level measures, the ICC would be close to 0. The intra-class correlation for

our two-level logistic random intercept models with an intercept variance of σ2µ, is calculated as:

ρ = (σ2µ / (σ2

µ + π2/3))

where π2/3 = 3.29 and represents the level-1 residual variance for a logit model

The analytical sample consisted of 1,394 last births that occurred to women in the five years

preceding the survey and that had no missing data on the variables of interest.

Results

Sample Characteristics

Table 1 presents the socio-demographic characteristics of mothers in the sample as well as

measures of maternal health service quality in their LGAs of residence. Mothers were 32.1 years old

on average and nearly a third had never been to school. The vast majority of mothers were

currently married at the time of the interview, with one out of five being in a cohabiting union. A

third of mothers lived in poor households and nearly ten percent perceived distance to the health

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facility as a big problem in accessing care. Slightly more than half of mothers resided in LGAs that

were at/above the median in terms of the management practices that were supportive of quality

maternal health services and in terms of the availability of equipment and supplies for quality

delivery and newborn care.

Table 1 about here

Bivariate Associations

Eighteen percent of women in the sample received antenatal care from a health professional

in the first trimester and 32 percent made four or more antenatal visits to a skilled provider. Half of

deliveries were assisted by skilled medical personnel (doctor, nurse or midwife) and 44 percent

occurred in a health facility (see Table 2). There was a positive association between residing in an

LGA with stronger maternal health care management practices and the delivery care utilization

rates. For example, the proportion of mothers whose most recent delivery in the past five years was

attended by skilled personnel was 46 percent in LGAs that were below the median on the index of

maternal health care management practices compared to 52 percent in LGAs that were at/above the

median. Maternal health care utilization rates did not vary according to the ranking of the LGA in

terms of the availability of delivery/newborn care equipment and supplies in its health facilities.

Table 2 about here

For the two other measures of maternal health care quality, differentials in maternal health

care utilization outcomes were contrary to expectations. A significantly higher proportion of women

made four or more antenatal care visits, were assisted by skilled personnel at delivery, and delivered

in a health facility in LGAs that were below (as opposed to at/above) the median index of provider

training in maternal health-relevant topics. A similar pattern is observed with regard to the

availability of ANC/PPC equipment and supplies in health facilities in the LGA. For example, the

institutional delivery rate was 49 percent in LGAs that were below the median in terms of the

availability of ANC/PPC equipment and supplies compared to 39 percent in LGAs that were at/above

the median on this measure. This pattern could reflect the fact that clients of maternal health

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services may seek care in other LGAs if the availability of quality services in their LGAs of residence is

poor.

Multivariate Results

LGA level

Tables 3 and 4 show the multilevel regression results for the ANC and delivery care

outcomes, respectively. Greater availability of essential equipment and supplies for quality delivery

and newborn care services was associated with increased odds of initiating ANC with a health

professional in the first trimester of pregnancy (OR = 1.527; 95 percent CI = 1.031, 2.262). The odds

of institutional delivery were higher in LGAs with more supportive management practices for quality

delivery/newborn care services (OR = 1.873; 95 percent CI = 1.230, 2.851). Contrary to expectations,

the odds of skilled attendance at birth and institutional delivery were significantly lower in LGAs in

which providers had received lifetime training on a wider range of maternal health care topics than

in LGAs where providers had been trained on a narrower range of topics.

Table 3 about here

Individual Level

The individual-level results were worthy of note. The odds of initiating antenatal care in the

first trimester, making four or more antenatal care visits, being assisted at delivery by skilled

personnel and delivering in a health facility were significantly lower for respondents who were older.

Women with primary education and those with secondary/higher education had significantly higher

odds for all four outcomes than those who were uneducated. Place of residence was not

significantly associated with the antenatal care outcomes. However, as expected, urban women had

odds of skilled attendance at delivery and institutional delivery that were significantly higher than

those of rural women. Household wealth was not associated with the odds of initiating antenatal

care in the first trimester. The odds of four or more antenatal care visits, skilled attendance at

delivery, and institutional delivery were at least twice as high among mothers from households with

high as opposed to low levels of wealth.

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Table 4 about here

Although state was not associated with the odds of making four or more antenatal care

visits, mothers from the states of Bauchi and Kano had significantly lower odds of receiving antenatal

care in the first trimester, skilled attendance at delivery and institutional delivery than those from

Lagos state. In addition, the odds of institutional delivery were 2.327 (95 percent CI = 1.400, 3.867)

times as high in FCT as in Lagos State. Women who reported that distance to the health facility was

a big problem had significantly higher odds of receiving antenatal care in the first trimester, making

four or more antenatal care visits and being attended at delivery by skilled personnel than those

who did not report distance to be a big problem in accessing health care.

The relative importance of individual-level and LGA-level variables in accounting for variation

in the maternal health care utilization outcomes of interest was estimated by calculating the ratio of

the LGA-level variance to the total variance (the intra-class correlation), a measure of the degree to

which the outcomes were clustered at the LGA-level. Using the estimates from the null model (with

just a multilevel constant term, the LGA-specific random effect and no explanatory variables), we

obtained an intra-LGA correlation of 0.209 for initiation of antenatal care in the first trimester of

pregnancy, 0.152 for four or more antenatal care visits, 0.365 for skilled attendance at birth, and

0.359 for institutional delivery. These estimates implied that even though more than half the

variation in maternal health care utilization outcomes is explained by individual-level characteristics,

more than a third of the explained variance in the delivery care utilization outcomes is attributable

to LGA-level measures of the quality of maternal health services.

Cross-level interactions

We also examined how aspects of the maternal health care service delivery environment interacted

with individual characteristics to result in use or non-use of maternal health services (results

available upon request). None of the interaction terms between the following LGA-based measures

of the quality of maternal health services and respondent’s education and age were statistically

significant: (a) maternal health care management practices; (b) provider training in maternal health

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topics; and (c) availability of equipment and supplies for the delivery of quality antenatal care and

postpartum care services. The only significant interaction was found between the availability of

essential equipment and supplies for quality delivery and newborn care services (OR=0.967; 95

percent CI =0.938, 0.997; p = 0.033) and respondent’s age in the regressions for four or more

antenatal care visits (not shown). This interaction term suggested that increasing age was

associated with significantly lower odds of having four or more ANC visits in LGAs that ranked higher

than others in terms of the availability of equipment and supplies for delivery and newborn care.

Random Effects

To test the significance of the random intercept, the likelihood ratio test was applied by

calculating the difference in the observed deviances between the random intercept models

presented here and ordinary logistic regression models with the same explanatory variables. A

deviance difference of zero was obtained for timely initiation of ANC, 5.34 for four or more ANC

visits, 3.78 for skilled attendance at delivery, and 0.06 for institutional delivery. Halving the tail

probability associated with the chi-squared distribution with 1 degree of freedom (the difference in

parameters between the two types of models) yielded p<.05 for four or more ANC visits and skilled

attendance at birth. These results imply that the differences between LGAs were statistically

significant for these outcomes and that the odds of making four or more ANC visits and skilled

attendance at birth were determined by factors not captured by the observed covariates. Important

unmeasured factors could have included variations in cultural beliefs surrounding delivery, road

conditions, and factors underlying the placement of maternal health services.

Discussion

Previous studies on maternal health care utilization have given much emphasis on

household and individual determinants (i.e., the demand elements). Although many researchers

believe that the collection of household and individual information on service use should be

combined with information about the characteristics of health facilities that are available to the

population (i.e., the supply elements), few surveys permit service environment data to be linked to

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population data. The current study is one of few to contribute to the knowledge of how aspects of

the structure of maternal health care services are associated with individual-level outcomes. The

study assessed the association between elements of maternal health service provision and key

population behaviors – timely initiation of antenatal care, four or more antenatal care visits, skilled

attendance at birth, and institutional delivery – by linking data from facility inventories and provider

interviews with household survey data.

The study found a strong positive association between the availability of essential delivery

care equipment and supplies in health facilities in the LGA of residence and women’s odds of

initiating prenatal care in the first trimester of pregnancy. The odds of institutional delivery were

significantly higher in LGAs that scored higher on management practices supportive of quality

maternal health services than in LGAs that scored lower, after controlling for other factors. Two

findings were contrary to expectations and call for further research. More comprehensive provider

training on maternal health in a LGA had a significant negative association with skilled attendance at

birth and institutional delivery. Furthermore, in LGAs that scored higher on the availability of

essential delivery and newborn care equipment and supplies, the odds of four or more ANC visits

were more negative as respondent’s age increased than in LGAS that scored lower on this indicator.

The study has raised important methodological issues as to how best to measure the quality

of maternal health services and how best to link population and facility data. In the survey,

household responses were used to generate a list of health facilities and a sample of facilities was

derived from this list. Although the survey identified the universe of facilities actually used by the

household, the administrative boundaries of the LGA of residence were artificially imposed on the

data for the purposes of identifying level 2 units for the multilevel regressions. The question arises

as to whether the sampled facilities that fell within a given LGA characterized well where residents

were obtaining maternal health care. There are two caveats. Even though the set of facilities

actually used by the population was identified, there were many individuals in the population who

did not use any facilities for maternal health. Thus, limiting the study to facilities used by the

16

population likely introduced biases. Second, imposing the artificial boundaries of the LGA on the

facility data mixes two concepts: “Where LGA residents could go” and “where LGA residents do go”

for health services. Alternative approaches that allow one to draw a catchment area around a

facility and draw a random sample of facilities within this radius may have been more appropriate,

and are quite feasible with GIS maps of enumeration areas and surrounding facilities. While GPS

codes were obtained for health facilities in the survey, they were not obtained for the households or

the enumeration area, an important omission.

An important question surrounds whose definition of quality matters for the use of maternal

health services in low-income settings: the individual, the community, or the profession? In a

landmark article by Haddad et al. (1998) on what quality means to lay people, the following

components pertaining to the structure of the facility were identified: availability of drugs;

availability of facility services; accessibility of the facility; presence of health worker; conditions of

buildings and rooms; availability of hospital beds; delivery of services not conditional upon prior

payments; cleanliness of rooms; availability of diagnostic equipment/devices; availability of running

water; free drugs and services; availability and state of washrooms; availability of roads, bridges,

and electricity; availability of in-patient food, quality of meals; availability of phone or shortwave

radio, and availability of integrated services. Future analysis will consider these issues explicitly and

assess their associations with maternal health care utilization. An additional consideration is that

the service supply environment (and lay people’s perceptions of quality) could differ by type of place

of residence and the condition of transportation networks. In areas with good transportation

networks, facilities located far away from a given household could still be accessible, making the

quality of care in the LGA of residence less salient for determining the maternal health outcomes of

interest.

Another issue in evaluating the quality of maternal health services in the present study had

to do with sample size – ensuring that there were enough facilities and service providers that were

interviewed in order to characterize the quality of maternal health service provision in areas that

17

were smaller than the LGA. That was a challenge. Other limitations of the data stemmed from their

cross-sectional nature, which made it difficult to establish causality. Endogeneity was also of

concern. If maternal health services were placed where the demand for them and fertility levels

were high, failure to consider this factor could lead to an overstatement of some of the results.

Temporal ordering was also of concern as it was not clear that measures of the service delivery

environment for maternal health preceded the utilization outcomes of interest. Structural and

process aspects of quality may have changed over the 2-5 year period preceding the survey, making

earlier facility surveys conducted in 2005 and 2007 potentially more relevant than the 2009 facility

survey data analyzed in the present study. It is also to be noted that the health facility and

household surveys were conducted in the 51 LGAs that were targeted at the start of the COMPASS

project and the results of the analysis are not representative of Bauchi, FCT, Lagos, Kano and

Nasarawa states. No provider-client observations were conducted during the health facility survey,

which prevented an assessment of the association between process components of the quality of

maternal health care and utilization outcomes.

Program and Policy Implications

The findings call for interventions that target specific elements of maternal health service

delivery. Efforts to increase the utilization of maternal health care services should improve health

facility management practices, ensure the availability of essential equipment and supplies, and

conduct further research to better understand the linkages between provider training and the

utilization of maternal health services. As this study focused on the structural aspects of the quality

of maternal health services, research is needed to elucidate the linkages between the social-

psychological aspects of care and the utilization of maternal health services.

18

References

Adanu R. M. K. Utilization of Obstetric Services in Ghana between 1999 and 2003. African Journal of Reproductive Health. 2010; 14(3):153. Althabe, F., Bergal, E., Cafferta, M., et al. (2008). Strategies for improving the quality of health care in maternal and child health in low- and middle-income countries: an overview of systematic reviews. Paediatric and Perinatal Epidemiology, 22 (S1), 42–60. Conrad, P., De Allegri, M., Moses, A., Larsson, E. C., Neuhann, F., Müller, O., & Sarker, M. (2012). Antenatal Care Services in Rural Uganda: Missed Opportunities for Good-Quality Care. Qualitative Health Research, 22, 619-629. Donabedian, A. (1988). The quality of care. How can it be assessed? Journal of the American Medical Association,260, 1743-8. Fauveau, V., & de Bernis, L., 2006. Good obstetrics revisited: too many evidence based practices and devices are not used. International Journal of Gynaecology and Obstetrics, 94, 179–184. Galadanci, H. S., C. L. Ejembi, et al. (2007). Maternal health in Northern Nigeria: a far cry from ideal. British Journal of Obstetrics and Gynaecology, 114, 448-452. Haddad, S., Fournier, P., Machouf, N., & Yatara, F. (1998). What does quality mean to lay people? Community perceptions of primary health care services in Guinea. Social Science & Medicine, 47, 381-94. Hulton, Louisa, A., Matthews, Zoe and Stones, R.W. (2005) A framework for assessing quality of

maternal health services and preliminary findings form its application in Urban India. Southampton,

UK: Southampton Statistical Sciences Research Institute. (S3RI Applications and Policy Working

Papers, (A05/03).

Ijadunola, K. T., Ijadunola, M. Y., Esimai, O. A, & Abiona, T. C. (2010). New paradigm old thinking: The case for emergency obstetric care in the prevention of maternal mortality in Nigeria. BMC Women’s Health, 10, 6. Kongnyuy, E. J., Hofman, J., Mlava, G., Mhango, C., & Van der Broek, N. (2009). Availability, utilization and quality of basic and comprehensive emergency obstetric care services in Malawi. Maternal Child Health Journal, 13, 687-694. National Population Commission (NPC) [Nigeria] and ICF Macro. (2009). Nigeria Demographic and Health Survey 2008. Abuja, Nigeria: National Population Commission and ICF Macro. Osungbade, K., Oginni, S., & Olumide, A. (2008). Content of antenatal care services in secondary health care facilities in Nigeria: Implication for quality of maternal health care. International Journal for Quality in Health Care, 20, 346-351. Raven, J. H., Tolhurst, R. J., Tang, S., van den Broek, N. (2012). What is quality in maternal and neonatal health care? , 28, e676-83.

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Rockers, P. C., Wilson, M. L., Mbaruku, G., Kruk, M. E. (2009). Source of antenatal care influences facility delivery in rural Tanzania: A population-based study. Maternal Child Health Journal, 13, 879-888. Sarker, M., Schmid, G., Larrson, E., Kirenga, S., De Allegri, M., Neuhann, F., Mbnda, T., Lekule, I., & Muller, O. (2010). Quality of antenatal care in rural southern Tanzania: A reality check. BMC Research Notes, 3, 209. Sharan, M., Ahmed, S., Ghebrehiwet, M., & Rogo, K. (2011). The quality of the maternal health

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WHO.

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Table 1: Characteristics of mothers whose last child was born in the past five years, Nigeria

2009

Characteristic percent or

Mean (S.D) N

Age 32.7 (8.414) 1324 Education

None 37.5 523 Primary 34.2 477 Secondary/higher 28.3 394

Marital status Currently married 70.9 989 Living together 20.7 288 Not in union 8.4 117

Household wealth ** Low 33.9 472 Medium 38.2 532 High 28.0 390

Distance to health facility problematic No 90.1 1256 Yes 9.9 138

LGA-level variables MH Management practices Index

Below Median 44.6 621 At/above Median 55.5 773

Delivery/newborn care equipment/ supplies availability index

Below Median 45.9 640 At/above Median 55.1 754

Provider training in maternal health Index

Below Median 49.9 695 At/above Median 50.1 699

ANC/PPC equipment/supplies availability index

Below Median 52.9 737 At/above Median 47.1 657

Place of residence Rural 55.4 772 Urban 44.6 622

State Lagos 28.6 399 Bauchi 12.0 167 Kano 25.5 233 FCT 16.7 355 Nasarawa 17.2 240

N 100.0 1324

Data are weighted.

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Table 2 Prevalence of maternal health care utilization outcomes by selected measures of the quality of maternal health care in the local government area of residence and sex, last births in the past five years, Nigeria 2009

Maternal Health Service Quality in LGA

Antenatal Care from Health Professional in the First Trimester

Four or More Antenatal Care Visits

Skilled Attendance at Delivery

Delivery in a Health Facility

N

MH Management practices Index Below Median 19.0 40.0 45.7 39.8 621 At/above Median 17.0 27.2 52.0 46.0 773 Significance *** * *

Delivery/newborn care equipment/ supplies availability index

Below Median 15.8 56.2 46.8 41.3 640 At/above Median 19.1 60.0 51.9 45.7 764

Provider training in maternal health Index

Below Median 19.4 37.7 58.6 51.7 695 At/above Median 15.8 24.9 40.0 35.1 699

*** *** *** ANC/PPC equipment/supplies availability index

Below Median 22.3 35.3 54.2 48.9 737 At/above Median 13.2 28.0 45.4 38.9 657

** * ** **

Total 17.7 31.6 49.8 43.9 1394

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Table 3 Results of multilevel logit models of initiation of antenatal care in the first trimester and four or more antenatal visits, last births in the past five years in five states of Nigeria, 2009

Received Antenatal Care in First Trimester

Four or More Antenatal Care Visits

OR 95percent CI OR 95percent CI

Individual-level variables

Age 0.975* (0.956, 0.994) 0.976** (0.961, 0.992)

Education

Primary 2.034*** (1.346, 3.072) 1.843*** (1.325, 2.563)

Secondary/ higher 2.024** (1.292, 3.169) 2.007*** (1.389, 2.901)

Marital status

Cohabiting 0.855 (0.600, 1.217) 0.884 (0.647, 1.208)

Not in union 0.470* (0.247, 0.896) 0.851 (0.537, 1.349)

Place of residence

Urban 0.961 (0.539, 1.714) 1.027 (0.618, 1.710)

Semi-urban 0.693 (0.401, 1.196) 0.666 (0.412, 1.076)

State

Bauchi 0.231*** (0.101, 0.530) 0.917 (0.425, 1.977)

Kano 0.237*** (0.124, 0.454) 0.605 (0.308, 1.192)

FCT 1.256 (0.727, 2.169) 1.475 (0.735, 2.957)

Nasarawa 1.565 (0.838, 2.921) 1.824 (0.868, 3.833)

Household wealth

Medium 1.277 (0.801, 2.035) 1.526* (1.025, 2.272)

High 1.633 (0.949, 2.810) 2.361*** (1.481, 3.765)

Distance to health facility problematic

2.633*** (1.637, 4.233) 1.997*** (1.305, 3.054)

LGA-level Variables

MH management practices 0.894 (0.545, 1.468) 0.596 (0.329, 1.079)

Delivery care equipment availability

1.527* (1.031, 2.262) 1.155 (0.728, 1.832)

Provider training in MH-relevant topics

0.908 (0.590, 1.395) 0.708 (0.414, 1.208)

ANC equipment and supplies 0.749 (0.482, 1.164) 1.384 (0.805, 2.382)

Constant (S.E.) -1.138 (0.519) * -0.668 (0.479)

LGA Random Part

Variance (covariance) 1.038e-21 (1.061e-11) 0.185 (0.092)

Number of respondents 1394 1394

No. of LGAs 45 45

Log likelihood -582.246 -798.047

*** p<.001 ** p<.01 * p<.05

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Table 2 Results of multilevel models of skilled attendance at birth and institutional delivery, last births in the past five years

in five states of Nigeria, 2009

Skilled Attendance at Birth Institutional Delivery

OR 95percent CI OR 95percent CI

Individual-level Variables

Age 0.978** 0.962, 0.994 0.977** 0.962, 0.993

Education

Primary 1.461* 1.053, 2.027 1.786*** 1.294, 2.464

Secondary/ higher 1.767** 1.228, 2.542 1.877*** 1.314, 2.681

Marital status

Cohabiting 0.907 0.658, 1.252 0.866 0.635, 1.182

Not in union 0.601* 0.378, 0.955 0.594* 0.372, 0.947

Place of residence

Urban 1.733* 1.035, 2.902 1.980** 1.218, 3.218

Semi-urban 0.964 0.597, 1.556 0.897 0.569, 1.415

State

Bauchi 0.268*** 0.122, 0.591 0.258*** 0.133, 0.497

Kano 0.222*** 0.113, 0.436 0.284*** 0.165, 0.487

FCT 1.730 0.859, 3.482 2.327*** 1.400, 3.867

Nasarawa 0.873 0.419, 1.819 1.142 0.659, 1.976

Household wealth

Medium 2.535*** 1.703, 3.772 1.628* 1.108, 2.392

High 3.161*** 1.975, 5.059 2.072** 1.317, 3.261

Distance to health facility problematic

1.914** 1.206, 3.038 1.330 0.846, 2.093

LGA-level Variables

MH management practices 1.600 0.891, 2.876 1.873** 1.230, 2.851

Delivery care equipment availability

1.055 0.672, 1.657 1.050 0.754, 1.464

Provider training in MH-relevant topics

0.534* 0.316, 0.901 0.515*** 0.346, 0.764

ANC equipment and supplies 1.159 0.678, 1.980 1.114 0.743, 1.670

Constant (S.E.) -0.292 (0 .497) -0.562 (0.443)

LGA Random Part

Variance (covariance) 0.169 (0.094) 0.018 (0.055)

Number of respondents 1394 1394

No. of LGAs 45 45

Log likelihood -751.009 -760.077

*** p<.001 ** p<.01 * p<.05