i

ii

ABSTRACT

Identification of the determinants of maternal morbidity and mortality is a valid scientific

endeavour in its own right, but it is particularly relevant to any undertaking to improve maternal

health. By understanding the determinants of ill-health and their inter-relationships, it is

possible to develop treatments, seek preventative measures, target high-risk individuals and

groups, and assess the health implications of changes in the biological, physical, or social

environment. This paper provides a framework for studying the determinants of maternal

morbidity and mortality. Examples are cited from both developed and developing countries,

with an emphasis on the latter.

The term 'determinants' is defined broadly in this paper as encompassing all associations

between factors of interest and maternal health outcomes. Included within this are causes,

which primarily refer to pathogenic determinants of mortality; risk factors, which have a

biologically causal link to the outcome of interest; and risk indicators which are simply

associated with the outcome. Maternal health determinants are conceptualised as belonging to

one of three groups: determinants of pregnancy, determinants of morbidity, and determinants of

mortality. It is noted that methodological techniques for ascertaining the determinants of health

often reduce the issues under consideration to simplified, often linear, relationships between the

determinants and specific, usually negative, health outcomes. This approach is not always

appropriate since factors which are determinants from one perspective, may be outcomes from

another, and the repeat nature of pregnancy and morbidity makes the entire process a dynamic

one with many possible complex interactions. Risk indicators are often highly correlated, and

epidemiological strategies for analysis which eliminate confounders and look for single effects

are not always relevant.

Demonstrating associations requires a clear understanding of the types of health outcomes seen.

Maternal mortality, a single event occurring during pregnancy or the puerperium, is contrasted

to morbidity where four main patterns are seen including: diseases seen only during pregnancy

and the puerperium; diseases starting in pregnancy and the puerperium but continuing into the

interpartum period; diseases caused by pregnancy but not temporally located within the

pregnancy; and pre-existing diseases which are either temporarily or permanently worsened by

pregnancy.

After discussing outcome patterns, this paper describes the measurement of determinants.

Methods for obtaining information on the pathogenic causes of morbidity and mortality are

briefly summarized. The range of data sources, and measurement and analysis techniques for

identifying risk factors and indicators are discussed. Finally the study design implications of

attempting to show biologically causal relationships as opposed to associations are addressed.

iii

LIST OF CONTENTS

ABSTRACT

ii

LIST OF CONTENTS

iii

LIST OF TABLES AND FIGURES

iv

PREFACE

v

ACKNOWLEDGEMENTS

vi

1. INTRODUCTION

1

1.1 Defining ‘Outcomes’

2

1.2 Defining ‘Determinants’

5

2. CHOOSING OUTCOMES

7

2.1 Characterising and Identifying Pregnancy

7

2.2 Characterising and Identifying Maternal Morbidity

8

2.3 Characterising and Identifying Maternal Mortality

13

3. CHOOSING DETERMINANTS

15

3.1 Determinants of Pregnancy

15

3.2 Determinants of Morbidity and Mortality

17

4. DEMONSTRATION ASSOCIATIONS

20

4.1 Case Selection/Comparison Groups

20

4.2 Measures of Association

22

4.3 Conclusion

24

REFERENCES

26

iv

LIST OF TABLES AND FIGURES

Table 1 Percentage of women aged 15-49 who are pregnant at a given point in

time, for various levels of the general fertility rate

12

Table 2 List of proximate and distal determinants of fertility

16

Figure 1

Schema showing the broad categories of outcomes and determinants

related to mental health

3

Figure 2 Schema representing patterns of maternal morbidity 10

Figure 3 Diagram showing possibilities of selection bias 21

v

PREFACE

In January 1989, a new research initiative was launched by the Maternal and Child Epidemiology

Unit at the London School of Hygiene and Tropical Medicine. The primary objectives of this

programme are to evaluate existing methods for measuring maternal health in developing countries

and to develop, pilot and promote the use of new approaches. Two principal phases of activities

can be distinguished. The first comprised an eighteen month preparatory period, and the second a

three-year phase of field investigations in collaboration with six institutions in developing

countries.

The Phase I (1989-90) activities, supported by the British Overseas Development Administration

and the Ford Foundation, included:

-developing a computerized reference collection

- preparing four review papers on measuring maternal health

-conducting an illustrative analysis of survey data on maternity care in six African countries

- refining the Sisterhood Method for estimating the level of maternal mortality

-establishing formal links with other research groups working on maternal health

- hosting a Workshop to develop proposals for field activities in Phase II.

This document represents the third of the four review papers addressing methodological issues in

maternal health. The first paper sets the stage by examining definitional and conceptual issues that

underlie the measurement of maternal health. The remaining three focus on measurement-related

issues relevant to the three major purposes of information on maternal health:

- establishing levels and trends,

- identifying the determinants, and

- monitoring and evaluating programmes.

The first document, "Measuring maternal health: defining the issues", focuses on the implications

of the process of conceptualization for programmes and for measurement and considers maternal

health in the context of women's health (Graham and Campbell, 1990). The second paper,

"Measuring maternal mortality and morbidity: levels and trends", looks at the types of

methodologies, measures and sources of data available for measuring morbidity and mortality

(Campbell and Graham, 1990). This, the third, "Measuring the determinants of maternal morbidity

and mortality: defining and selecting outcomes and determinants, and demonstrating associations",

is organized around selecting morbidity and mortality outcomes and demonstrating associations

between them. The last paper, "Measuring the effectiveness of maternal health programmes",

examines the types of interventions used to improve maternal health with regard to the

methodologies available to assess impact and effectiveness (Graham and Campbell, 1991).

Phase II of the research initiative in Methodologies for Measuring Maternal Health will contribute

to strengthening the maternal health information base by identifying appropriate approaches for

meeting information needs in developing countries. For further details on this initiative, contact

the programme director, Dr Wendy Graham, at:

Maternal and Child Epidemiology Unit

London School of Hygiene and Tropical Medicine

Keppel Street, London WC1E 7HT.

vi

ACKNOWLEDGEMENTS

Preparation of this paper and three others on methodologies for measuring maternal health was

funded by a grant from the Ford Foundation. We acknowledge and appreciate the support of

three members of the Foundation in particular: Dr Marge Koblinsky, who was involved at the

initiation of the work; Mr Stuart Burden, who liaised with the project in the middle; and Dr José

Barzelatto, who enabled us to see it through to completion.

We are also indebted to our colleagues Dr Patricia Doyle, Dr Vincent Fauveau, Ms Véronique

Filippi, Ms Masuma Mamdani, Dr Melissa Parker and Dr Cleone Rooney who made several

editorial improvements to this particular paper. Our thanks are also due to Ms Lynne Davies for

her preparation of text and tables.

1

1. INTRODUCTION

Identifying the determinants of maternal morbidity and mortality is a valid scientific endeavour

in its own right, but it is particularly relevant to any undertaking to improve maternal health. By

understanding the determinants of ill-health and their inter-relationships, it is possible to

develop treatments, seek preventive measures, target high-risk individuals and groups, and

assess the health implications of changes in the biological, physical, or social environment. On

the other hand, it is also important to recognize that identifying and intervening against specific

determinants of maternal ill-health is not exclusively within the sphere of bio-medical expertise,

and that a multidisciplinary approach to studying and resolving health problems is imperative.

Recent investigations of the determinants of women's morbidity and mortality have either

adopted a condition-specific focus, such as work by Bang et al. (1989), the Reproductive

Morbidity Interdisciplinary Research Group (1991) and Wasserheit et al. (1989) seeking factors

contributing to reproductive tract infections, or have evolved around methods for operations

research in Safe Motherhood, such as the approach looking at delay factors taken by the

Prevention of Maternal Mortality Project of Columbia University (Thaddeus and Maine, 1990).

This paper is one of a series of four papers highlighting relevant methodological issues. As

with any other morbid condition, measuring the determinants of maternal ill-health requires five

steps:

1.choosing a particular outcome of interest;

2.hypothesizing an association between the outcome and a certain factor or factors;

3.measuring the outcome and factors;

4.demonstrating the association; and

5.specifying the nature of the mechanism linking the factors and the outcome.

The range of disciplines, study designs, data collection instruments, study populations, measures

of association and analysis techniques available for studying the determinants of maternal

morbidity and mortality does not differ substantially from the range available for examining the

determinants of most other health conditions. However, certain methods have special relevance

to maternal morbidity and mortality, and some pertinent measurement issues are frequently

neglected.

This paper is organized into four parts. After the introduction, which clarifies what is meant by

'outcomes' and 'determinants', the second section focuses on the patterns of maternal health

outcomes. Pregnancy and mortality are contrasted to morbidity, where four main patterns are

seen, including: (1) diseases seen only during pregnancy and the puerperium; (2) diseases

starting in pregnancy and the puerperium but continuing into the interpartum period; (3)

diseases caused by pregnancy but not temporally located within the pregnancy; and (4) pre-

existing diseases which are either temporarily or permanently aggravated by pregnancy. Section

3 presents the categories of determinants - determinants of pregnancy, mortality and morbidity -

as well as the tiers of determinants - pathogenic causes, risk factors and risk indicators. The

paper concludes by reviewing issues of study design, case selection and choice of comparison

2

groups, and measurement of exposures and outcomes which arise in the process of

demonstrating associations.

1.1Defining 'Outcomes'

Before contemplating ways of measuring the determinants of maternal health outcomes, an

understanding of the 'outcomes' under consideration is needed. Health, despite being defined as

a positive state of physical, mental and social wellbeing and not just the absence of disease

(WHO, 1948), is frequently used synonymously with ill-health; and maternal health is no

exception. The emphasis on the negative aspects of maternal health stems in part from the lack

of operational definitions and suitable indicators of both positive health and of social and mental

health, and, in part, from the view that pregnancy is pathogenic (Graham and Campbell, 1990;

Leavitt, 1988). There is a third reason for the emphasis on ill-health: analytical techniques for

ascertaining the determinants of health frequently simplify the linkages to linear relationships

between the determinants and single, usually negative, health outcomes.

This paper also concentrates on morbidity and mortality. However, even without the added

complexities of measuring positive health, the definition of outcomes remains complicated by

the relationship of maternal ill-health to pregnancy. Maternal morbidity and mortality lie at an

interface between reproduction and health, and even when a single negative outcome, such as

maternal death from postpartum haemorrhage, is selected for study, it must be recognized that a

woman passes through up to three stages, each conditional upon the preceding stage, in order to

become a case. For example, a woman must become pregnant, experience a problem associated

with the pregnancy (morbidity), and fail to have that problem resolved (mortality) in order to die

from pregnancy-related causes. With maternal morbidity, she must fall pregnant and experience

a problem associated with that pregnancy on a long- or short-term basis. Conceptualizing

maternal ill-health in this way with at least two stages for morbidity and three for death,

emphasizes that three relevant categories of determinants must be considered: determinants of

pregnancy, determinants of morbidity, and determinants of mortality (Figure 1).

Categories of determinants are not necessarily exclusive. While any one determinant may

appear in multiple categories, the mechanisms through which it acts, and the direction and

magnitude of its effects, will differ. A woman's age, for example, can determine her probability

of becoming pregnant, her risk of developing pregnancy-induced hypertension once pregnant,

and her probability of dying of eclampsia, given it develops. A specific determinant may also

have multiple mechanisms within a broad category. For example, age may determine mortality

either through a constitutional effect, or through its influence on a woman's ability to negotiate

needed medical care for herself.

Specific determinants which belong in several broad categories can act on maternal health in the

same, or in opposing, directions. For example, in most societies, educated women are exposed

to fewer pregnancies than uneducated women, and are more likely to seek and receive

appropriate care once they experience morbidity. In both cases, education lowers the risk of

mortality. On the other hand, women outside stable unions are less likely to be

3

4

exposed to the risk of pregnancy (Bongaarts and Potter, 1983), but in some situations are more

likely to die if they become pregnant (Kwast and Liff, 1988). Hence marriage both increases

and decreases the risk of maternal mortality and may have varying overall effects in different

countries.

Recognition of the three conditional stages of an outcome (pregnancy, morbidity, and mortality)

clarifies interpretation of the impact of determinants which may act on maternal morbidity and

mortality in opposing directions. There are, however, two obvious drawbacks to the framework

in Figure 1. Firstly, it fails to capture the dynamic nature of biological processes. Unlike the

representation in Figure 1, neither pregnancy nor morbidity are necessarily single events.

Instead, pregnancy for the individual woman comprises a pattern of childbearing including a

whole range of frequencies (gravidities) and intervals between pregnancies, while morbidity

may encompass a complex series of repeated episodes of various illnesses. This limitation is

overcome in theory for maternal mortality by indicators such as the lifetime risk which take an

aggregate perspective encompassing the entire reproductive period. The lifetime risk of

maternal mortality can be shown to be a function of the total gravidity rate, the all-cause

morbidity ratio per 100,000 pregnancies, and the case-fatality risk1.

Attempting to put the formula into practice highlights the second drawback to the framework in

Figure 1: the complexities of measuring morbidity risks, and their attendant case-fatalities, for

an entire range of morbidities make it virtually impossible to put the framework into use. This

is partly because, in contrast to pregnancy and mortality which can be expressed as binary

conditions (the woman is either pregnant or not, or dead or not), maternal morbidity is not a

single entity, and the most that can usually be said is that a woman does or does not have a

particular range of illnesses or symptoms. The nature of the specific morbidity per se, its

severity and its duration have an integral role in determining its amenability to treatment and

thus its prognosis; these factors vary widely from morbidity to morbidity. The availability and

accessibility of services are also influential in case-fatality and can be quite diverse for different

morbidities and/or settings. Consequently, there are many more biologically causal

determinants of morbidity and mortality than of fertility, and some of these are as yet

unidentified. In contrast to the models of the determinants of fertility, the difficulties of

identifying and measuring even those biologically causal determinants which are known, makes

the prospect of a testable model of the determinants of maternal mortality seem remote.

1.This is summarized as a formula which can be applied either to all-cause maternal mortality or

to cause specific lifetime risks:

5

1.2Defining 'Determinants'

Classifying determinants by the outcome they influence (pregnancy, morbidity, mortality) is not

sufficient; it is also necessary to delimit the range of determinants under consideration. Most

studies have primarily focused on causes of death and on age and parity as risk factors. An

important contribution of early work on Safe Motherhood has been to broaden perceptions of

what determines or 'causes' a maternal death. Several illustrations of the complex chain of

events leading to a maternal death, including Fatallah's 'Why did Mrs X die' (WHO, 1986) and

Kwast's case histories (WHO, 1987), have shown that although the most immediate

determinants of maternal death are medical causes, maternal health goes beyond medical issues.

Three additional categories which play an important role in determining the risk of death can be

identified: (1) health service factors, including the quality of care and the accessibility and

availability of preventative and curative health services; (2) reproductive factors, including the

woman's constitution, her parity, general health status, and age; and (3) socio-economic factors,

including urban/rural residence, education, income, status, and cultural factors.

Adopting such a broad view of determinants has several advantages: it places both outcomes

and possible interventions in their social context thereby increasing the potential for success in

various cultural settings; it suggests more potential points of intervention; and it is more likely

to lead to interventions with multiple health impacts. A broad definition is not without its

disadvantages however, since the effects of intricate relationships can be difficult to demonstrate

and successful interventions against complex situations, such as low socio-economic status, are

not easily implemented and may be perceived by decision makers to lie outside the scope of

health interventions. Furthermore, if the relationship between a determinant and the outcome is

complex, the underlying mechanism may be misinterpreted, and manipulation of some

determinants, particularly those which are not biologically causal, will not necessarily result in

the desired change. A solution which avoids the latter difficulty, without restricting the focus to

pathogenic causes, is to emulate research into the determinants of fertility and of child mortality

and consider several tiers of determinants.

In a now classic study, Davis and Blake (1956) postulated that social, economic and

environmental factors act through eleven 'intermediate fertility variables' to influence fertility.

These include: (1) factors affecting exposure to intercourse; (2) factors affecting exposure to

conception; and (3) factors affecting gestation and successful parturition. The development of

this framework, which emphasized that all changes in the outcome (fertility) must be mediated

through the eleven intermediate biological mechanisms, led to considerable progress in

understanding fertility determinants. Further developments have reduced these eleven

'proximate'2 factors to a model predicting the total fertility rate using four main variables of

interest: stable sexual union (marriage), contraception, lactation and induced abortion

(Bongaarts and Potter, 1983).

2."Proximate" and "distal" determinants are used in the demographic literature on fertility to

describe biologically causal and socioeconomic determinants, respectively.

6

The above fertility models have influenced the construction of frameworks of infant and child

health, which also emphasize that more distant socioeconomic determinants must be

behaviourally or environmentally linked to adverse health outcomes through biological

mechanisms (Mosley and Chen, 1984; van Norren and van Vianen, 1986). The implication for

maternal health is to suggest, for instance, that although low levels of female education may be

positively associated with poor maternal health outcomes, improvements in a distal determinant,

such as female education, will not necessarily reduce maternal mortality unless, for example,

they also lead to changes in fertility patterns, uptake of care, or constitutional factors. An

extreme example is seen among well educated women in the Faith Assembly of God, a

fundamentalist religious sect in the United States. These women have a maternal mortality ratio

of 872/100,000 in part because they refuse to use medical services (Kaunitz et al., 1984).

Conversely, some oil-rich Arab States have been able to reduce maternal mortality markedly

through almost universal high-quality care, without simultaneous improvements in women's

status (Rosenfield and Maine, 1987). By contrast, improvements in proximate determinants,

such as effective treatment of a potentially fatal morbidity, will necessarily decrease the lifetime

risk of maternal death, providing all other influencing factors remain constant.

Despite potential misinterpretation of the effects of distal determinants, a broad view of the

determinants of maternal morbidity and mortality is maintained in this paper. The terms

'determinants', 'risk indicators', 'risk factors', and 'causes', as well as 'antecedents', 'influences',

'covariates' and 'correlates', all of which have been used interchangeably in the health literature

to describe the associations between the outcome of interest and other factors, are defined here

in order to keep some distinctions in the layering of determinants. 'Determinants' is used as a

broad term describing all factors associated with the outcome of interest. Within 'determinants',

three tiers are defined: 'causes', which describe pathogenic (medical) causes of morbidity or

mortality; 'risk factors' which have a biologically causal link to the outcome of interest; and 'risk

indicators' which include all other determinants (Backett et al., 1984).

7

2. CHOOSING OUTCOMES

The first step in demonstrating an association is to decide the maternal health outcomes of

interest. Of the three possible stages a woman can pass through, pregnancy, morbidity, and

mortality, two -- pregnancy and mortality -- pose relatively few conceptual problems, although

both can be difficult to measure. Pregnancy and mortality each have an implicit role in the ICD-

10 definition, which states that a pregnancy-related death is the death of a woman while

pregnant or within 42 days of termination of pregnancy (WHO, 1990a). Although maternal

morbidity seems an intuitive and necessary intermediary, there is no clear-cut definition of what

constitutes a maternal morbidity (Campbell and Graham, 1990; Graham and Campbell, 1990).

At this early phase in conceptualizing and understanding the epidemiology of maternal

morbidity, it is necessary to determine which morbidities are influenced by pregnancy at all and

thus which are maternal morbidities before commencing to study their determinants. At a

minimum, conditions leading to maternal mortality should be included, but it is also known that

many serious consequences of pregnancy affect women beyond the narrow time-band when

maternal deaths can occur. A broader definition, removing the time limitation and including all

conditions directly or indirectly arising from, or aggravated by, childbearing and its

management, does not diminish the measurement difficulties (Campbell and Graham 1990;

Graham and Campbell, 1990). The next three subsections discuss ways of characterizing each

of the stages of pregnancy, morbidity and mortality.

2.1 Characterizing and Identifying Pregnancy

The state of pregnancy is conceptually simple to describe. Pregnancy occurs when the

conditions leading to conception are present and sexual intercourse takes place; these factors, or

proximate determinants, are relatively well described and quantified (Bongaarts and Potter,

1983). However, unlike fertility research which often establishes pregnancy by the ensuing

birth, research into maternal health may necessitate detecting pregnancy in its early stages. The

ease of ascertaining pregnancy depends on whether laboratory tests, clinical examinations, or

women's reports are used and on the gestational age of the pregnancy, with early pregnancies

being the most difficult to detect.

Pragmatically, studies have to rely on women's cooperation to obtain good quality information

on pregnancy, and little is gained, for example, by using assays to detect early pregnancy unless

women want their pregnancies detected. The critical factor is rarely the technical difficulty of

determining pregnancy but rather women's willingness to disclose their pregnancies to

researchers. If substantial numbers of women do not know or are unwilling to state that they are

pregnant, it becomes difficult to obtain a representative sample (Airey and Campbell, 1988;

Baretto et al., 1992; Peoples-Sheps et al., 1988). An illustration of this is provided by a drug

trial using ivermectin to cure river blindness in Liberia which went to considerable lengths to

identify and exclude pregnant women. The investigators found that, on average, their questions

had a specificity of 98% but a sensitivity of only 79% (Pacque et al., 1991). For very early

pregnancies, sensitivity was as low as 26%. That is, only 26% of the women subsequently

found to be pregnant correctly identified themselves as pregnant. Similarly, Airey and

Campbell (1988) found significant underreporting of early pregnancies in several of the

Demographic and Health Surveys.

8

2.2 Characterizing and Identifying Maternal Morbidity

In contrast to pregnancy and mortality, maternal morbidity takes many forms. It can be an acute

or a chronic condition, which is either recognized and acknowledged as an illness or is not

apparent to the respondent. The perception of symptoms of morbidity vary between cultures

and can manifest in ways that are physically apparent to all, apparent to a trained eye, or

measurable only with certain instruments. The seriousness of specific morbidities also varies:

some are instantaneously lethal, while others are potentially lethal, disabling, or simply

discomforting. Morbidity events may be single episodes which resolve spontaneously, are

treated, or have permanent incurable effects, while others may recur occasionally or frequently.

Finally, each specific morbidity may have a whole spectrum of manifestations. For example,

haemoglobin levels are normally distributed, with anaemia, which occurs at the low end of the

distribution, ranging from mild to severe. Uterine prolapse, on the other hand, may manifest

itself through several symptom complexes, appearing as pain in some women and incontinence

in others. The forms taken by a particular morbidity are partly a function of its type and partly

due to its interaction with the woman's constitution and underlying health status.

The definition of maternal health initially proposed by Graham and Campbell (1990) and

elaborated by WHO (1990b) encompasses positive and negative outcomes from any cause

related to childbearing or its management. Although nulligravid women are excluded, the scope

of the definition is only slightly narrowed since maternal morbidity can occur any time

following the first pregnancy and continuing beyond the menopause. The definition proposed

by Graham and Campbell (1990) is further sub-divided to parallel the definition of maternal

mortality: pregnancy either causes morbidity directly or it interacts with the woman's underlying

health condition to cause disease. This concept can be applied to both physical and other forms

of ill-health. For example, pregnancy can lead to eclampsia (direct physical ill-health), or it can

aggravate underlying essential hypertension (indirect physical ill-health). Alternatively, a

teenager socially well-adapted to her milieu may become outcast as an unwed mother, or a

woman with an untreated vesico-vaginal fistula may experience a combination of physical,

mental and social ill-health.

Unfortunately, the link between pregnancy and specific morbidities is not always as apparent as

the above examples. Even if morbidity coincides with pregnancy or the puerperium, it is not

necessarily maternal morbidity. A study by Datta et al., (1980) in India reports that only 30%

of morbidity during this period is related to pregnancy or the puerperium, implying that 70% of

morbidity is not pregnancy-related. By contrast, studies in developing countries have shown

that between 80 to 95% of mortality during pregnancy and the puerperium is pregnancy related

(Chen et al., 1974; Fortney et al., 1984). Furthermore, while the International Classification of

Disease lists codes falling within the maternal death definition, no such criteria are provided for

pregnancy-related morbidity (WHO, 1977). When underlying morbidity (e.g. diabetes) is

exacerbated so markedly by pregnancy that it results in death, it is uncontroversial to label the

death an indirect maternal one. If the same morbidity is only slightly aggravated, however, it

may be difficult to recognize it as an indirect maternal morbidity in the absence of detailed

knowledge of the natural history of the disease and its previous presentation in the woman.

Indeed it may only be possible to attribute risks associated with pregnancy to populations of

women rather than to individuals. Criteria for "normality" are not present in all cases. For

example, Weigel and Weigel (1988) argue that nausea and vomiting during pregnancy are signs

of good health and that women experiencing these symptoms are not ill. Unless explicit

9

definitions of maternal morbidity are made, and similar ranges of conditions included, data from

different studies will not be comparable.

Building up a picture of disease patterns in the absence of pregnancy is virtually impossible in

many settings where the majority of women will have been pregnant at least once by a certain

age. Settings where this is not the case, as for example in some developed countries, tend to

experience low rates of morbidity anyway, and women who remain nulligravid in both

developed and developing country settings are likely to differ from their gravid counterparts in

many ways, not least in their fecundability. For example, MacKie et al., (1991) studied the risks

of complications of melanoma in four groups of women: women with initial melanoma

diagnosis before first pregnancy, during pregnancy, after last pregnancy, and between

pregnancies. The investigators were unable to compare these with nulliparous women with

melanoma because none were available in the study area. Special sub-groups who voluntarily

avoid pregnancy, such as nuns, have been used to understand aspects of reproductive

epidemiology, but this approach has extremely limited potential (Nathanson, 1985).

Three further factors influence the morbidity outcome and have implications for its

identification and the ease and timing of its measurement: the availability of treatment, the

repeatable nature of pregnancy, and the possibility of health benefits arising from pregnancy.

Some treatments may completely remove all signs and symptoms of the morbidity, while others

leave physical traces which can remain constant or be exacerbated by subsequent pregnancies or

other events. In extreme cases, the damage may be so great as to prevent further pregnancy,

leading to the paradoxical result that women with fewer pregnancies may be the ones bearing

the greatest cost of pregnancy (Graham and Danso-Manu, 1988). Secondly, the effect of

repeated pregnancies on underlying health status may lead to cumulative insults to a woman's

health. This would suggest that higher parity women maybe an ideal group in which to study

maternal morbidity. However, the frequency of, and intervals between, pregnancy are highly

related to other biological factors which play a role in health, particularly age. This makes it

difficult to adjust for the effects of these events separately, since high-parity pregnancies will

almost inevitably result from shorter intervals and occur at older ages. In assessing the impact

of pregnancy on a woman who has had five pregnancies, it is unclear whether the incremental

effect on her health should be assessed by comparing her to a woman of the same age with four

pregnancies or to an older woman of the same parity. The need to control for other important

variables in addition to age and parity, such as socio-economic status, may rapidly lead to small

numbers of women under consideration in each category of a data set.

Finally, it must not be assumed that the effects of pregnancy on women's health are necessarily

negative. Studies of the long-term sequelae of pregnancy suggest that the hormonal

consequences of pregnancy may provide strong protective effects against breast and ovarian

cancer (Beral, 1985; Booth et al., 1989; Green et al., 1988), while pregnancy has been found to

have no affect on the prognosis of malignant melanoma (MacKie et al., 1991)

Morbidity Matrix. Figure 2 presents maternal morbidity in a simplified schematic form with

four dimensions. It is intended to highlight measurement-related issues encountered when

10

Figure 2. Schema representing patterns of maternal morbidity

Dimension I: Diseases observable only during pregnancy and the puerperium

(1)

(2)

(3)

Dimension II: Diseases starting during pregnancy or the puerperium, but

continuing beyond it

(4)

(5)

Dimension III: Disease associated with pregnancy but not temporally

located within it

(6)

(7)

Dimension IV: Underlying disease exacerbated by pregnancy

(8)

(9)

(10)

(11)

11

investigating maternal morbidity, including relevant study populations and feasible reference

periods. The first dimension, shown by I:1-3, illustrates diseases seen only during pregnancy,

delivery and the puerperium. Such conditions are usually recognized as being 'caused' by the

pregnancy, since they are temporally associated with it, and in many ways are the simplest

morbidities to identify as conditions or diseases of pregnancy, not least by women themselves.

Despite associating these conditions with pregnancy, women may not, however, perceive them

as problems but rather as 'normal' aspects of pregnancy. Defining and probing for symptoms is

necessary to identify problems of interest, such as nausea, which may not be perceived as, or

indeed be, maternal morbidities. On the other hand, if women's own perceptions of their health

problems are to be included, room must be left for open-ended ascertainment of problems such

as backache, haemorrhoids or spirit-possession, since these self-reported morbidities may not

correspond to medically defined symptoms or be of concern to investigators. Examples of

diseases showing the patterns of morbidity shown in Figures I:1-3 include ante- and postpartum

haemorrhage, obstructed labour, infection, hepatitis, vomiting, urinary tract infections, monilia,

gestational diabetes, cholestatic jaundice of pregnancy, pregnancy induced hypertension, and

eclampsia.

Since the morbidities in dimension I must coincide with the relatively brief 46 week period of

pregnancy and the puerperium to be considered maternal morbidities, they can be difficult to

study in the community because of the relative scarcity of pregnancy (Airey and Campbell,

1988; Filippi et al., 1990; Peoples-Sheps et al., 1988). Table 1 estimates the percentage of

reproductive age women pregnant at a given point in time. It shows that, depending on the

general fertility rate, between 3 and 20% of women of reproductive age can be expected to be

pregnant, and between 0.4 and 2% will be at a specific gestational month. This is compounded

by difficulties in ascertaining early pregnancy and the fact that not all pregnant women will have

a specific illness of interest. Morbidities also vary with gestational age of pregnancy. Unless

good, representative records are available or morbidities can be recalled over long periods,

acquiring a representative sample with sufficient women at various gestational ages to inquire

about current morbidity status or morbidity in the previous two weeks can be daunting. In other

words, even though maternal morbidity is reported to be at least 16 times more common than

maternal mortality, it can still be rare on a period basis (Datta et al., 1980).

Dimension II:4-5 in Figure 2 illustrates diseases starting during pregnancy or the puerperium

and continuing into the interpartum period. As with conditions typified by dimension I, such

diseases are frequently perceived as maternal morbidities. Because such conditions are likely to

be chronic, they can often be picked up through prevalence studies. If a condition is permanent,

its point prevalence may be high enough to ensure sufficient women are identified during cross-

sectional surveys. The chronic aspect also means, however, that such diseases may change over

time and become part of the background health status of the woman. If subsequent pregnancies

are not precluded, they may interact with, and possibly worsen the condition. The availability of

treatment can also play a role in the ease of detecting these types of morbidities. Examples of

conditions typified by dimension II: 4-5 include fistula, haemorrhoids, varicose veins, anaemia,

and possibly other nutritional deficiencies.

Dimension III:6-7 reflects diseases associated with pregnancy and the puerperium, but not

temporally located within the same time period. Because such conditions are not necessarily

associated with pregnancy by women or researchers, extensive data sets and creative analyses

12

Table 1.Percentage of women age 15-49 who are pregnant at a given moment in time, for

various levels of the general fertility rate

Country Year General

Fertility Rate

per 10001

Percentage

pregnant at given

point in time2

Percentage at

specific

gestational month

at a given point in

time

Japan 1986 45 3 0.4

Canada 1985 54 4 0.5

France 1986 58 4 0.5

USA 1985 60 5 0.5

Mauritius 1986 67 5 0.6

Thailand 1985 73 5 0.6

Ireland 1985 75 6 0.6

Brazil 1985 76 6 0.6

Mexico 1980 97 7 0.8

Costa Rica 1984 122 9 1.0

Egypt 1982 152 11 1.3

Bangladesh 1981 162 12 1.4

Honduras 1981 197 15 1.6

Pakistan 1976 206 15 1.7

Afghanistan 1979 233 17 1.9

Rwanda 1978 236 18 2.0

1.The General Fertility Rate (GFR) is the live births per 1000 women aged 15-49 Source: UN

(1989).

2.The percentage pregnant at a given point in time is roughly estimated by multiplying the GFR

by 9 months gestation.

12 months per year

This figure slightly underestimates the number of women pregnant since not all pregnancies

result in live births.

3.The percentage at any given month of gestation is calculated by dividing the GFR by 12

months per year.

13

may be required to show an association. Some studies, such as those reported by Omran and

Standley (1978, 1981), have attempted to associate parity with various gynaecological

conditions including menstrual problems, vaginal discharge, itching, prolapse, urinary problems,

nutritional status, and vaginal or cervical abnormalities. Other less obvious long-term

morbidities associated with parity include diabetes mellitus, and may include all circulatory

disease, hypertensive disease, ischaemic heart disease, and sub-arachnoid haemorrhage (Beral,

1985; Green et al., 1988).

The final representation, dimension IV:8-11, depicts situations where background disease is

either temporarily or permanently worsened by pregnancy. Following parallels with maternal

mortality, these are the 'indirect' maternal morbidities. In such cases, the subsequent pregnancy

can act in a threshold, or a continuous manner. Understanding the interaction of indirect

morbidities and pregnancy requires knowledge of the natural history of the disease, basic

information which is often lacking. For example, epidemiological studies are frequently carried

out among 'white middle class males' and extrapolated to other groups (Cotton, 1990), making it

difficult to understand how conditions are influenced by pregnancy. Indirect morbidities

known, or suspected, to be exacerbated by pregnancy include AIDS, leprosy, tuberculosis,

malaria, malnutrition, and essential hypertension.

In 1957, Jewett argued the case eloquently for expanding our definition of maternal morbidity

using poliomyelitis as an example: "This disease can kill old or young, male or female, pregnant

or non pregnant, and might on the one hand be called non-obstetric. On the other hand, since its

incidence in pregnant women is thought to be much greater than in other adults, must it not be

called obstetric?" (Jewett, 1957). Much work remains to be done on the epidemiology of

maternal morbidity, particularly with regard to indirect morbidities, outcomes not temporally

associated with pregnancy or the puerperium, conditions affecting organs or systems besides the

reproductive tract, and factors affected by the pattern of childbearing rather than by individual

pregnancies. Although the morbidities involved are not fully listed, Figure 2 suggests ways of

thinking about the variety of outcomes and the target populations needed to study them.

2.3Characterizing and Identifying Mortality

Death is the final irreversible end-point of ill-health and there is little conceptual ambiguity

about it as an outcome. Rather, problems arise in locating a representative sample of deaths in

the community, and in ascribing pathogenic causes. These measurement problems are

discussed in detail by Campbell and Graham (1990), and include inadequate vital registration

and lack of proper medical certification of death. For deaths which are not medically attended,

causes must be reconstructed using "verbal autopsies" which rely on lay sign and symptom

reporting. Lack of medical training, different concepts of illness, sensitivity of the subject,

and/or trauma of the circumstances may make precise causes difficult to elicit. For example, in

their study of maternal mortality in Addis Ababa, Kwast and Liff (1988) attribute two deaths to

"Zar", describing it as "a condition which may manifest in bizarre behaviour, convulsive

seizures and extreme apathy. Several conditions would fit this description, e.g. typhus,

eclampsia or meningitis." Respondents may not know, recall or wish to inform the interviewer

about a given maternal death. The reluctance to discuss abortion-related deaths, for example, is

documented (Baretto et al., 1992). Even within medical facilities deaths may not be ascribed a

pathogenic cause due to the limitations of medical knowledge, clinical skills, diagnostic tests,

and autopsy techniques and facilities, as well as the lack of availability or the lack of skill of

those carrying them out. Numerous studies in both developed and developing countries have

14

shown official statistics to misclassify between 2-73% of maternal deaths as non-maternal

deaths (Campbell and Graham, 1990); very little work has been done on misclassification of

cause within the overall category of maternal causes (Grubb et al., 1988).

15

3. CHOOSING DETERMINANTS

The outcome chosen for investigation depends on several criteria including the priority of the

problem, its prevalence and preventability, the context, and the investigator's interests. Once an

outcome is selected, determinants must be hypothesized, and the study design and analysis

techniques selected. Much of this choice is dictated by the type of outcome under consideration

and the categories and tiers of determinants being explored. Epidemiological techniques will

play a large role in examining risk factors, while techniques derived from sociology and other

behavioural science disciplines must be used to study socio-economic and other more distal

influences.

3.1 Pregnancy Determinants

The proximate and more distal determinants of fertility contribute to maternal morbidity and

mortality because pregnancy is a pre-condition. Models of the proximate determinants suggest

for example, that non-contracepting, non-lactating women in stable sexual unions are most

exposed to the risk of pregnancy, and that on an aggregate level, these characteristics, together

with induced abortion, primarily determine the total fertility rate (Bongaarts and Potter, 1983).

Age is another important determinant which influences both fecundability and the likelihood of

exposure to intercourse. The implications of these proximate determinants of pregnancy for

maternal health have been illustrated by Graham and Airey (1987), who among others, show

that in many settings the majority of maternal deaths come from the mid-reproductive ages

where the most women are giving birth, despite the youngest and oldest women having the

highest age-specific risks per pregnancy. Although not yet demonstrated empirically, the same

relationships are likely to hold for age and maternal morbidity.

Distal determinants of fertility are often considered at both the societal and individual level

(Cochrane 1979; Lesthaeghe et al., 1981). Social institutions, cultural norms, economic and

environmental conditions as well as women's education, status, employment, ethnicity, and

family size desires have been identified as important distal determinants. These are listed

together with the proximate determinants in Table 2. Generally, higher levels of education,

income and women's status are associated with lower levels of fertility, and it is assumed that

they have a similar association with maternal morbidity and mortality, although this is by no

means certain. Louden (1987) argues, for instance, that maternal health, as opposed to neonatal

and infant health, is resistant to socio-economic indicators and is much more a function of

medical care. Indeed, until the 1930s, women of higher social class in England and Wales had

higher rates of maternal mortality probably because they were more likely to be delivered by

doctors in hospitals and consequently develop sepsis. More recently, Presern (1991) reports that

traditional midwives refuse to deliver low-caste Nepali women who thus probably receive better

quality delivery care because they are more likely to turn to modern medical facilities.

Women's employment generally reduces fertility as well. The anticipated direction of its impact

on maternal health is difficult to assess however. Studies of child health often assume that the

autonomy and resources gained through women's employment will improve child health, but it

is uncertain whether women can or will command these resources for their own health. In some

situations, women may continue to work to the detriment of their health just to remain in

employment. This possibility, coupled with the potential for occupational health

16

Table 2. List of proximate and distal determinants of fertility

Proximate determinants proposed by Davis and Blake (1956):

I Factors affecting exposure to intercourse

A Those governing the formation and dissolution of unions in the reproductive period

1. Age of entry into sexual union

2. Permanent celibacy: proportion of women never entering into sexual union

3. Amount of reproductive period spent after or between unions

a. When unions are broken by divorce, separation or desertion

b. When unions are broken by the death of the husband

B Those governing the exposure to sexual intercourse within union

4. Voluntary abstinence

5.Involuntary abstinence (from impotence, illness, unavoidable but temporary

separations)

6. Coital frequency

II Factors affecting exposure to conception (conception variables)

7. Fecundity or infecundity, as affected by involuntary causes

8. Use or non-use of contraception

a. by mechanical or chemical means

b. by other means

9.Fecundity or infecundity as affected by voluntary causes (sterilization, sub-incision,

medical treatment)

III Factors affecting gestation and successful parturition

10. Fetal mortality from involuntary causes

11. Fetal mortality from voluntary causes

Postpartum infecundability and lactational infecundability should be added to these proximate

determinants.

Socioeconomic and environmental determinants proposed by Bulatao and Lee (1983):

Social Institutions,

cultural norms,

economic and

environmental

conditions

Socio-economic

characteristics

Reproductive history

Demand for

children

Supply of

children

Fertility

regulation

costs

Motivation

to control

fertility Fertility

regulation to

limit family

size

Fertility

17

hazards, makes it difficult to speculate on the likely impact of employment on maternal health.

It is equally difficult to anticipate the direction of an effect of ethnicity as this is likely to be

mediated through a variety of culturally influenced behaviours.

3.2 Morbidity and Mortality Determinants

Conceptualization of the determinants of maternal morbidity and mortality is in the initial stages

of development. Studies have tended to focus on biomedical determinants, variously classified

as genetic or constitutional, environmental, and behavioral risk factors. A review of over 60

studies of the determinants of maternal ill-health shows that the most commonly-stated 'causes'

are pathogenic causes, such as haemorrhage and sepsis. These, together with investigations of

age and parity as biomedical risk factors concentrating health risks among very young and very

old women and nulliparous and grand multiparous women, far outnumber studies investigating

other tiers of determinants. Research which moves away from a clinical orientation with its

underlying paradigm of biologically causal links and biochemical markers, and considers a

wider range of determinants, is rare. This may be partly because maternal health is viewed not

as a public health issue but rather as a medical problem to be handled at the individual level.

The public health relevance of such clinically-oriented epidemiological research in developing

countries is being increasingly called into question (Akin, 1991). Narrowly focused studies

such as those dominating the maternal health literature often ignore the effects of important

confounding variables. Similarly, the fact that women may change their behaviour if they

perceive threats to their health is unrecognized, or is ignored because it is considered

analytically intractable. The policy conclusions arising from such narrow studies will tend to

favour medical interventions without considering mitigating effects of socio-economic factors

on the adoption and impact of the advocated interventions (Mosley and Chen, 1984; Akin,

1991).

Ultimately of course, most morbidities are of a physical nature and so biological factors must

come into play. However, studying the bacterial pathogens present in women with puerperal

sepsis may have relatively little impact on prevention in settings where malnourished women,

delivering in unhygienic environments with untrained personnel, have all kinds of contaminants

introduced through repeated vaginal examinations and die of sepsis because they cannot

command the resources to seek effective treatment when they experience problems.

Debates on the value of considering different tiers of health determinants have a long history.

Myntti (1991) contrasts the social medicine movement of the nineteenth century, where the

suggestions for preventing typhus included unlimited democracy, education and the

disestablishment of the Catholic church, with current trends whereby physicians,

epidemiologists and public health officials recommend treatment technologies and individual

behaviour modification. Such varying perspectives on the prevention of disease are unlikely to

be reconciled easily although it is anticipated that the variety of disciplines now involved in

maternal health will enhance the scope, and hopefully the quality, of the research. For example,

Myntti (1991) describes the present day role of anthropologists as counteracting 'the willingness

of many researchers to end the analysis with a simple documentation of behaviour rather than

investigating the context in which such behaviour takes place'. For health practitioners,

however, exploring the context of morbidity and mortality can be threatening to their

professionalism as it may lead away from solutions found in single technologies or

prescriptions, and even out of the health domain altogether. Multidisciplinary studies may also

18

point to determinants of ill-health which are not amenable to intervention at all in a given

context.

An important element in understanding the determinants of morbidity and mortality involves the

relationship of morbidity to mortality. As shown in Figure 1, each stage is conditional on the

previous one, and maternal mortality is conditional on maternal morbidity. Thus pregnancy and

the characteristics of a specific morbidity, including its severity, duration and pathogenic nature,

are frequently labelled "causes" of maternal mortality. These characteristics, their interaction

with the woman and with other morbidities or risk factors for the prognosis of morbidity, and

the availability, accessibility, quality and effectiveness (including compliance) of services and

treatments are grouped as determinants of death. For clarity however, it is preferable to separate

those which are primarily determinants of morbidity or pregnancy. Similarly, one type of

morbidity may lead to another without necessarily leading to death. Uterine atony may, for

example, lead to uterine rupture. In other words, influences which are determinants in one

instance may be outcomes in another depending on the stage which is under consideration.

Tiers of Determinants. Not all determinants are known and it is impossible to describe ways of

measuring all of them. However, some common determinants are briefly discussed below

following the three tiers; pathogenic causes of mortality, biologically causal risk factors, and

risk indicators.

Pathogenic causes of maternal mortality include all fatal conditions aggravating or aggravated

by pregnancy. The complications of pregnancy, childbirth and the puerperium listed in the ICD-

9 include 40 major three-digit divisions (WHO, 1977). The most common direct causes of

death however are haemorrhage, sepsis, obstructed labour, hypertensive diseases of pregnancy

and complications of illegally induced abortion, while common indirect causes include malaria,

and hepatitis.

Reproductive factors, including the woman's constitution, her age, parity, and general health

status are the most commonly considered factors as they can be measured relatively easily in

facility-based studies. Reproductive factors are thought to play a biologically causal role

although some, such as age and parity may influence women's confidence and use of services.

Often however, studies merely demonstrate an association with age and parity and recommend

targeting of high risk women for special care without exploring the mechanisms for the

association.

Another major category of determinants are health service factors. Here it is helpful to

distinguish between curative and preventative interventions, although once again the

conditionality of the three stages means that an intervention which cures morbidity prevents

death. It is common to distinguish between interventions by modern and traditional health

practitioners as well as those carried out by women themselves. As regards risk factors, this is

perhaps less useful than distinguishing between iatrogenic or harmful practices and helpful or

beneficial ones. These can be generally grouped under the quality of care. The accessibility and

availability of preventative and curative health services also belong in the health service

category. Thaddeus and Maine (1990) have reviewed the literature on maternal health care

utilization and proposed a useful framework examining three phases of delay: (1) delay in

deciding to seek care on the part of the individual, the family or both; (2) delay in reaching an

adequate health facility; and (3) delay in receiving adequate care at the facility.

19

This final category, socio-economic factors, is extremely broad and often includes urban/rural

residence, education, income, status, and cultural factors as risk indicators. Because such

influences are not necessarily causal, it is important to elaborate on the expected direction of an

association and possible reasons behind it while recognizing the potential for confounding. For

example, the evidence on the importance of maternal education has led to several exchanges

(Harrison, 1989a, 1989b; Maine et al., 1989). Hospital studies often find that illiterate women

have higher maternal mortality ratios than more educated women, leading some to argue that

female education will reduce maternal mortality. Others counter that such an assumption

assumes a causal relationship which is not adequately demonstrated by such studies. Indeed

much of the effect of education may be due to selection bias, as in many countries illiterate

women normally deliver at home and only use hospitals for complicated deliveries, arriving late

and often moribund. If access to health services is controlled for by only considering women

booked into the health system, further insight into the effects of education can be gained. In

Zaria, Nigeria between 1976-9, women with lower educational levels had better survival than

more highly educated women (110 versus 250 maternal deaths per 100,000 live births

respectively) (Harrison, 1985). By contrast, a hospital study in Port Harcourt in 1987-9 showed

women with less than secondary school education experienced almost five times the maternal

mortality of booked women with secondary or higher education (640 versus 130 maternal

deaths per 100,000 live births respectively)(Briggs and Oruambo, 1991). Some differences may

be due to underlying health status but it is also likely that ability to pay for health services and

staff attitudes play an important role (Campbell et al., 1991; Harrison et al., 1991). Further

exploration of the reasons for such differentials may lead to remedies well within the means of

hospital staff and available resources.

Arriving at an operational measure of a proposed determinant is another important but

potentially difficult task. For instance, many studies mention status of women as an important

aggregate level determinant of maternal health. Yet to assess the impact of women's status on

maternal mortality requires an indicator of status to be identified and measured. The status of a

woman cannot, however, be determined as easily as her age. The International Women's Rights

Action Watch (Isaacs et al., 1988) lists over 170 possible indicators of women's status, some of

which are characteristics of the woman while others apply to a local community or an entire

country. Even age is not necessarily simple to measure in countries where women are not aware

of their date of birth. In addition to obtaining a date of birth from the woman or from a birth

certificate, methods used to estimate women's dates of birth include local calendars, age in years

or in age groups, age at marriage and marriage duration, and even osteological evidence.

A move beyond pathogenic causes and biomedical risk factors to multiple risk indicators also

poses analytical problems. Risk indicators emerging from a broad view of determinants are

often highly correlated, and epidemiological strategies for analysis that discuss elimination of

confounders and single effects may be inappropriate. Unfortunately, despite sophisticated

analytical techniques developed to determine the relationship between socioeconomic variables

and child mortality, such literature often gives rise to conclusions that are so sweeping (such as

the richer and more educated you are, the better your health) that they are of little use to policy

makers (Akin, 1991).

20

4. DEMONSTRATING ASSOCIATIONS

Once the outcomes and determinants have been identified, it remains to select the study

population, to measure the outcomes and determinants, and to demonstrate an association.

4.1 Case Selection/Comparison Groups

In many situations, the choice of the outcome of interest and the availability of data determines

the study population. In investigations of maternal health, this choice is complicated by the

three stages through which a woman passes and it is important to keep in mind how case or

study population selection may influence the results. Furthermore, in many study designs, but

particularly in case-control studies, selection of an inappropriate comparison group is a major

source of bias.

For example, a study following up women after delivery to assess postpartum depression may

demonstrate that very young mothers are at greatest risk of depression. However, because the

study starts with women who are pregnant, it only considers the risk of depression given a

woman is pregnant and fails to recognize that very young women are less exposed to the risk of

pregnancy. In case-control studies, this dilemma presents itself in the choice of a control. A

case-control study of the risk of ectopic pregnancy associated with contraceptive use in

developing countries which opted to use both pregnant and non pregnant controls illustrates this

point. Results showed that while tubal ligation increased the risk of ectopic pregnancy given a

woman was pregnant (Odds Ratio=10.9), it substantially decreased the risk of ectopic pregnancy

overall (Odds Ratio=0.2) (Gray and Campbell, 1985). The choice and interpretation of a

comparison group in such instances is crucial.

This issue of the three stages of pregnancy, morbidity and mortality can lead to other potential

sources of error. If for example, cases are chosen using births or pregnancies as the sampling

unit, high parity women are more likely to be represented, all else being the same. If the

comparison group is then sampled from among women at large, then the parity distribution in

the cases and comparison group will be spuriously different.

Furthermore, the question of the representativeness of the study population affects the extent to

which results can be generalized to the population at large. For example, a study of risk factors

for case fatality in hospitals may be well designed, but still have little relevance in settings

where few women have access to hospital facilities and the majority of deaths take place at

home.

Finally, in many developing countries, the selection biases involved in most facility-based

studies are extremely large. Campbell and Graham (1990) demonstrate that selection bias

associated with mortality among women with unbooked deliveries in Zaria, Nigeria may

account for a five-fold magnification of the risk of maternal death. The potential for selection

biases to affect women appearing at facilities can be seen in Figure 3 which illustrates for

induced abortion that hospital deaths can be a very small subset of total complications. If these

women are compared to a non-random sample of women with uncomplicated induced

abortions, large biases will result. If on the other hand,they are compared to hospitalized cases

who survive complications, the questions that can be answered are limited primarily to medical

management (Baretto et al., 1992).

21

Figure 3. Diagrma showing possibilities of selection bias

Women

Sexually active

reproductive-age

women

Pregnant women

Unaccepted

pregnancy

Induced abortion

Complications

Hospitalized

Die Survive

Sexually inactive and/or

non-reproductive age

women

Non-pregnant women

Accepted pregnancy

Continued pregnancy

No complications

Not hospitalized

Die Survive

22

4.2 Measures of Association

Study designs to establish risk factors. Identification of risk factors for morbidity and

mortality involves establishing several criteria including a biological link, often assessed

through strength of the association, presence of dose response, and biological plausibility, and a

temporal sequence. The techniques for establishing risk factors are generally epidemiological

and consider individual level associations, and use prospective and retrospective rather than

cross-sectional designs. This is because while cross-sectional and ecological methods can

provide valuable clues to associations between variables, only studies incorporating a time

element can truly establish risk factors which precede disease.

Opportunities for considering maternal deaths or potentially fatal morbidities using prospective

or intervention studies are limited. In addition to ethical difficulties and the problems of loss to

follow-up, enormous numbers are needed and the time scale and cost are prohibitive unless

cohorts likely to exhibit high mortality rates are identified. For example, to answer the widest

range of questions on maternal health, a cohort of never pregnant women would need to be

identified (possibly as early as their own birth or conception) and followed through pregnancy,

morbidity and death. The problems of following such an 'average risk' group could be

circumvented by selecting a 'cohort' of unbooked hospital admissions with a high likelihood of

death. This group of women is highly selected however and more distal factors such as

accessibility to health services or risk of pregnancy could not be studied and representativeness

of the community at large would be low. For these reasons, the use of prospective studies,

especially in the community, are rare (Peoples-Sheps et al., 1988; Datta et al., 1980). Ongoing

surveillance areas such as Matlab in Bangladesh, the sites monitored by the MRC in The

Gambia or Sine Salloum in Senegal are more practical to use but such surveillance is rare and

tends to concentrate on mortality measurement. Historical cohorts can also be used but only in

settings where good records are maintained (Beral, 1985).

Given the difficulties associated with prospective studies, much of the research on risk factors

will be retrospective. As mentioned earlier, case-control studies often face difficulties selecting

the appropriate comparison group - a dead control or a living one for mortality studies; a

pregnant or non-pregnant one for morbidity and mortality studies; one suffering the same

condition for mortality studies. The problems of obtaining unbiased and comparable data for

the two groups are considerable. For example, relatives of a maternal death might simply not

know about the circumstances or might provide a different level of accuracy to the control or the

relatives of the control. Also problematic in case-control studies are the multiple layers of risk

which mean that comparison groups have to be chosen carefully. The choice of the appropriate

control becomes difficult and will heavily influence the determinants studied (Campbell, 1983).

In developing countries with limited health service coverage, behavioural and socio-economic

factors related to uptake of care are likely to introduce heavy biases.

It is imperative that case-control studies of maternal health give adequate consideration to the

exact question being asked and to the choice of comparison group. If cases are selected from

hospitals, pregnant controls should be from among women who intended to deliver in the same

place as the case did. Thus for many questions a woman who ends up as a complicated hospital

case after intending to deliver at home should have a control who delivered at home. Despite

these problems, case-control studies are a promising, but as yet underused approach. Only one

developing country case-control study of maternal mortality has been cited in the literature to

23

date (Bhatia, 1985; 1986); most case-control studies of maternal morbidity have been carried

out in developed countries. Careful case-control study designs can also be used to examine

medical practices within hospital settings. A common belief is that problems arise in getting

women to the hospital; that once women are there, medical services will help. The evidence for

this is contradictory and numerous studies have identified avoidable factors within the hospitals

(Campbell et al., 1991; Thaddeus and Maine, 1990).

The pattern of morbidity also plays a role in determining the methodology used. If the research

is concerned with rare conditions, the study must either follow high risk groups prospectively

(which limits the breadth of risk factors that can be considered) or else rely on a retrospective

design. Similarly, the location of the study -- ie community vs hospital -- is likely to be

determined by characteristics of the disease. If conditions manifest signs which can only be

detected clinically, health examinations are required and health facilities may be the only

possible venue.

Study designs to establish risk indicators. Risk indicators can be identified through a much

broader set of techniques than the search for risk factors. Many of the determinants under

consideration, such as educational level, are relatively long-term characteristics of the woman

and so establishing a temporal sequence is less problematic. Nevertheless it is important to be

aware of reverse causality. For example a woman's status may be improved by her having

children while a morbid condition such as fistula will lower a woman's status in the community.

The levels of analyses possible also vary: cross-national aggregate level assessments, secular

trends, as well as individual level analyses may be conducted.

Some of the analyses of risk indicators have used focus group or case history techniques to gain

a qualitative picture of the processes that contribute to maternal health from the perspective of

the health provider and the woman herself (Kwast, 1987). Other examinations of the broader

level factors have used standard techniques of multivariate analysis (Crook et al., 1991; Findley,

1989). Akin (1991) and Manton et al. (1991) suggest that for some types of conditions, health

measurement requires a combination of subjective, socio-anthropological techniques and

objective analytical and statistical procedures. Manton et al. (1991) have developed procedures

called the Grade of Membership, which they feel is free from restrictive assumptions, to look at

a multiplicity of variables. With this they are able to identify complex response profiles from

discrete response data.

Measures of association. The most common analytical methods for demonstrating

associations basically consist of comparing levels of morbidity or mortality among different

subgroups. This can be achieved either by comparing prevalence or by comparing incidence

rates or risks. Calculation of these measures of incidence or prevalence are discussed in depth

by Campbell and Graham (1990). Once these measures are calculated, analysis can consist of

straightforward comparisons between two groups or can involve more complex, n by n way

comparisons using cross-tabulations. For example, Fauveau et al. (1988) report that the

maternal mortality ratios for deaths from postpartum haemorrhage were 110, 90 and 230 per

100,000 live births for women aged 15-19, 20-34 and 35-44 years respectively. Alternatively,

multivariate techniques may be used to simultaneously adjust for the effects of many variables.

An alternative to directly comparing rates and risks is to calculate relative risks. This measure,

which is derived from cohort studies, involves looking at the ratio of two rates or risks, and

24

implies the relative likelihood of an outcome in a group with one characteristic compared to

another group with a different characteristic. For example, a prospective study of Navajo

women shows that women with cesarian-sections were four times more likely to develop

postpartum fever or endometritis than women having vaginal deliveries (Relative Risk=4.0)

(Slocumb and Kunitz, 1977). A third measure, the odds ratio (or relative odds), is calculated

from retrospective or cross-sectional studies. For instance, a case control study of ectopic

pregnancy found that in developing countries women who smoked were four times more likely

to have an ectopic pregnancy than non-smoking pregnant controls (OR=4.0) (Campbell and

Gray, 1987).

A fourth and final measure of association is the attributable risk. This measure is influenced by

the frequency of the determinant in the study population and describes the maximum proportion

of the disease that can be attributed to the determinant. One potential application of attributable

risk is with indirect morbidities; it should be possible to calculate the proportion of the disease

attributable to pregnancy in most settings.

4.3 Conclusion

This paper has reviewed the steps involved in measuring the determinants of maternal morbidity

and mortality. The first decision is frequently choosing the outcome and determining the

feasibility of measuring it. With maternal morbidity outcomes, this may be problematic since

these are less well-defined, infrequently studied, and require further methodological

development. The next step, choosing and measuring determinants, is simplified if the three

stages of pregnancy, morbidity, and mortality are kept in mind and it is recognized that the

overall impact of a determinant is the net effect of its influences on the risk of pregnancy,

morbidity and mortality. The distinction between causal determinants and risk indicators is

another useful step as it facilitates interpretation of results. Finally once outcomes and

determinants have been measured, it remains to demonstrate an association and thus show that a

factor is indeed a determinant of maternal morbidity or mortality. The most appropriate

methods to use depend on the type of study, the indicator and the study aims. Relative risks and

odds ratios can be derived from individual level data used to examine biologically causal

associations, while ecological methods are useful for generating hypotheses.

The sequence of steps involved in demonstrating an association presented above is an idealized

one. Often, opportunities for demonstrating associations are presented through routine data or

reanalysis of existing data. Such analyses are to be encouraged since data collection is costly

and data are frequently underutilized. Occasionally, natural experiments are created by changes

in factors which influence maternal health and these instances should also be exploited. For

example, Ekwempu et al. (1990) demonstrated the impact of structural adjustment programmes

on maternal health by looking at changes in the numbers of deliveries and complicated

deliveries after hospital charges were introduced. In other instances, study contexts limit

feasible designs and measuring and interpreting the determinants of maternal morbidity and

mortality require innovative methods.

Many authors express dissatisfaction with both the epidemiological focus and some socio-

economic approaches to studying health. The former only considers medical factors while the

latter either results in broad generalizations which act through a black box or makes very

specific observations which are only applicable in very specific contexts. It is increasingly

25

suggested that a proper understanding of health needs to harness social, economic behavioural

and cultural information and insights to address biomedical questions. Integration of socio-

economic and behavioural models with bio-medical models may be possible in looking at risk

indicators but as yet insights gained from disciplines outside epidemiology do not address

biological causality.

26

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