Cavin Thesis 08102015

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Inequitable Contraceptive Knowledge in Sub-Saharan Africa:
Who Is Being Left Behind in the Fertility Transition?
Meredith Cavin
August 10, 2015
Abstract: This paper explores the factors that determine whether a woman has heard of any
effective contraceptive method in Ghana, Mali, and Nigeria. The Demographic and Health
Surveys enable the exploration of how education, wealth, age, urban residence, employment,
religion, and the possession of a television or radio affect the likelihood that a woman has heard
of family planning. This research provides a new perspective and fuller view of the reasons why
poorer and less educated women tend to have more children than wealthier and more educated
women do. Whereas country-level data suggests that socioeconomic development leads to
demand for fewer children and therefore fertility decline, this microdata analysis suggests that
socioeconomic development leads to family planning access – including prerequisite
contraceptive knowledge – which then facilitates fertility decline. In other words, poor and less
educated women might continue to have many children, in part, because they cannot access
family planning, and even more fundamentally, because they do not know that family planning
exists. Whether policy-makers are driven by population issues such as rapid population growth
and strained infrastructure or by individual issues such as freedom and self-determination, these
findings should motivate policy-makers to continue to work toward universal knowledge about
and access to family planning.
Purpose of the Paper
There are 85 million unintended pregnancies around the world each year (Sedgh et al
2014). In Africa, 80 out of 1,000 women of reproductive age have an unintended pregnancy in a
given year (Sedgh et al 2014). Further, it is estimated that 225 million women have an unmet
need1 for family planning globally, including 58% of women in Sub-Saharan Africa (Singh et al
2014). However, some economists question the theoretical possibility of having an unmet need
for family planning, reasoning that anyone sufficiently motivated to avoid childbearing will find
a way to use contraception or abstain from sex and that the cost of family planning is negligible
compared to the cost of raising a child (Pritchett 2014). In response, renowned demographer
John Bongaarts has asserted, “The fact that unwanted births occur proves that, for the women
1 The concept of “unmet need” applies to women of reproductive age (15-49) who are at risk of pregnancy,wish to
avoid pregnancy for at least two years, and are not using family planning. In the Singh et al report, only those using
modern contraceptives are considered to have their need met.

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having such births, the cost of avoiding them, rather than being trivial, exceeds the (net) cost of
having them” (Bongaarts 1994). Sociologist John Casterline has added that, “The scant empirical
attention to the magnitude of contraceptive costs and their effects on contraceptive decision
making reflects less than full respect for the potential power of the various possible obstacles of
contraceptive use” (Casterline et al 2001).
The purpose of this paper is to unearth inequities surrounding the most fundamental piece
of access to family planning: the simple knowledge that it exists. This paper will test the
hypothesis that wealthy and highly educated women are more likely to know that family
planning exists than poorer and less educated women. If this is true, then these wealthy and more
educated women face one fewer barrier to accessing family planning than their less advantaged
counterparts, and they have the advantage of being able to imagine a life in which they can
delay, space, and limit their births. Since family planning access enables women to pursue
schooling and employment, a disparity in contraceptive knowledge has the potential to fuel other
socioeconomic disparities (Bailey 2006).
The first part of this paper will review the literature about the demographic transition and
factors that influence fertility decisions. The second part of this paper use Demographic and
Health Survey data to determine which demographic variables are most associated with
knowledge of at least one effective contraceptive method in Sub-Saharan Africa.
The lowest nation-wide levels of contraceptive knowledge are in the Sahel region of
Africa. In other developing regions, the vast majority of women have heard of at least one
method of family planning. For example, 95.9% of women in Bolivia and 98.8% of women in
Pakistan report having heard of at least one method (STATcompiler). By contrast, only 60.6% of
women report knowing about at least one method in Chad (STATcompiler). Less than 90% of

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women know about family planning in many countries in the Sahel region, including Mauritania,
Mali, Niger, Chad, Sudan, Eritrea, Benin, Nigeria, and the Central African Republic
(STATcompiler).
This study will take a closer look at Ghana, Mali and Nigeria, three countries in West
Africa that have integrated Demographic and Health Survey data available going back twenty-
five years. Mali and Nigeria were selected for this study because of their low levels of
contraceptive knowledge. Ghana was selected because it is another West African country but has
a very high level of contraceptive knowledge; 97.8% of women there report knowing about at
least one method (STATcompiler).
As the data analysis in the second half of this paper will show, wealthy and educated
women in Mali and Nigeria are much more likely to know about family planning than their
poorer and less educated counterparts. While researchers cited in the literature review in the first
half of this paper suggest that wealthy and educated women have fewer children because they
want fewer children, the data analysis suggests that it may also be because they are more likely
than poorer and less educated women to have the knowledge, access, and means to achieve fewer
pregnancies. This paper’s findings suggest that if poorer and less educated women had
knowledge about and access to family planning they might also have fewer children. Whether
policy-makers are driven by population issues such as rapid population growth and strained
infrastructure or by individual issues such as freedom and self-determination, these findings
should motivate policy-makers to continue to work toward universal knowledge about and access
to family planning.
Demographic Transition Theory

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The costs and benefits of children are central to the demographic transition theory, put
forth by Frank Notestein in 1945. According to the this theory, societies experience a mortality
transition from high mortality to low mortality and a fertility transition from high fertility to low
fertility. When basic public health and medical improvements lead to reduced mortality, but
before fertility falls, countries can experience a period of extremely rapid population growth,
which can overwhelm countries with fragile governments and poor infrastructure. Most of the
world has already gone through a demographic transition. The United States, Western Europe
and parts of Asia currently have fertility rates that are lower than the replacement level2 of about
2.1 children per woman. Central and South America and most of Southeast Asia is also moving
toward smaller families. Most of the countries that have persistently high fertility rates are in
Sub-Saharan Africa.
Fertility rates and fertility preferences are arguably the result of women’s conscious or
subconscious calculations about the costs and benefits of children and the costs and benefits of
family planning - assuming they know family planning exists. Different governments have
implemented a range of antinatalist policies to discourage fertility and pronatalist policies to
encourage fertility. These policies seek to alter the costs and benefits of children and family
planning in order to manipulate individuals’ choices and to achieve desired demographic
outcomes.
Benefits of Children
At the country-level and the individual level, the fertility transition from high fertility to
low fertility is highly associated with traditional indicators of socioeconomic development and
2 Replacement level fertility is the fertility rate necessary to keep a population at exactly the same size if mortality
rates did not change and if there were no inward or outward migration. Therefore, a country with higher mortality
would have a higher replacement level.

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“modernization,” such as education level, literacy, urban residence, income, and wealth as
defined by household assets. Demographer John Bongaarts explains that, “As countries develop,
the [demographic transition] theory posits, the cost of having children rises and the benefits
wane, leading parents to want fewer children” (Bongaarts 2011).
Costs of Children
Limited ethnographic evidence presents a challenge to this widely accepted fertility
transition theory. Ethnographic evidence suggests that a lack of socioeconomic development may
lead to decreases in fertility - not increases - as long as couples have a realistic way to limit
fertility. Ethnographer Daniel Jordan Smith found that in Nigeria, “The main reasons to limit
fertility were a bad economy, general hard times, and the burdens and expenses of trying to
‘train’ children” (Smith 2004). Smith explicitly states that these rationale for having fewer
children are “different from the dominant popular Western tropes that tend to depict fertility
transition as part of a grand process of ‘progress,’ ‘modernization,’ and ‘development’” (Smith
2004).
Another major “cost” of bearing children is the risk of maternal mortality. This is a much
larger risk for some women than for others. Therefore, some women face a much higher health-
related “cost” of having children than other women do. Disparate risks of maternal mortality
exist within countries, and they certainly exist between countries. 99% of maternal deaths occur
in low-resource settings (Diamond-Smith 2011). In some countries, as many as one in six women
die of maternal causes over their lifetime, compared to one in 30,000 in Sweden in 2005
(Diamond-Smith 2011). Two factors lead to this disparity: maternal care and the number of times
a woman carries a pregnancy and is therefore at risk of maternal mortality. As former medical

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director of the International Planned Parenthood Federation Malcolm Potts stated, “Many
approaches to reducing maternal mortality (e.g. increasing the number of deliveries at health
facilities with skilled attendants or improving access to emergency obstetric care) are complex
and will take time to implement. In the meantime, maternal mortality can be reduced relatively
inexpensively by preventing unwanted pregnancy through family planning” (Diamond-Smith
2011).
Benefits of Family Planning
Family planning enables women to delay, space, and limit their childbearing in order to
improve maternal, infant, and child health outcomes. The health benefits of family planning are
well documented, for both maternal health and child health. Family planning reduces the risk of
maternal mortality by both reducing the total number of pregnancies and also the number of
high-risk pregnancies, such as among girls and young women who are not fully developed and
among older women (RAND 2002). Family planning also improves child health and survival by
reducing the number of births that have higher risks, such as births less than two years apart,
births to very young and older women, and higher-order births, meaning the birth of the fifth or
subsequent child (RAND 2002).
Family planning can also eliminate almost all of the demand for abortion, which is
especially important for women who cannot access safe and legal abortion. The family planning
literature generally agrees that wealthy women can access safe abortion anywhere, regardless of
laws that make it illegal (Campbell 2006). It is predominantly poor women who are not able to
find and afford the private practices that provide safe abortions.

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Costs of Family Planning
In 1975, economist Richard Easterlin wrote An Economic Framework for Fertility
Analysis in which he broke apart different kinds of costs of fertility regulation into “market
costs” and “psychic costs” (Easterlin 1975). He defines market costs as “the time and money
necessary to learn about and use specific techniques” (Easterlin 1975). Market costs, therefore,
include the price of a doctor’s visit, the price of any required tests, the price of transportation to
get to the clinic and then to the pharmacy, the price of the product(s), the price of any necessary
childcare, and the opportunity costs of lost wages. In Ghana, the direct market cost of male
condoms for one couple-year of protection is $281, or 6.7% of the annual per capita household
consumption GDP (Creanga 2011).
There are many market-based costs and barriers for consumers. These include poverty,
unaffordable prices, a lack of family planning funding, and inadequate supply chains (Campbell
2013). Many women, especially rural women, are also very far from places where they can get
contraceptives. Exacerbating the problem of geographic distance is “policymakers’ reluctance to
allow the easiest forms of birth control for women, mainly oral contraceptives and the popular
injectable contraceptives, to be distributed by volunteer citizens at the community level.”
(Campbell 2013).
Easterlin defines “psychic costs” or “subjective costs” as “the displeasure associated with
the idea or practice of fertility control” (Easterlin 1975). Qualitative research consistently shows
that family support or stigma is extremely important as women make fertility decisions. A 36-
year old married Nigerian man with three children said, “When I told [my mother] we were
intentionally not having children and that [my wife] Oluchi was using an IUD, my mother was
shocked. She condemned the practice and blamed Oluchi.” After this incident, Oluchi explained,

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“In our culture your marriage and your children are not simply your business. They are the
business of the whole extended family and the whole village” (Smith 2004).
In other instances, the support of one’s mother-in-law can make family planning a more
realistic option. An ethnography by Sharon Stash includes interviews with women in Nepal
about their views on family planning. She finds that, “A mother-in-law’s support insures that a
woman can maintain her status within the household, that she can be accompanied on visits to
the clinic, that she can take time off from her work to recuperate from an operation, and that she
can receive an allotment of food favorable to maintaining good health” (Stash 1999).
Differential Costs for Rich and Poor
Some of these psychic costs are greater for poor women than for wealthier women. Stash
writes, “Among the poor, the perceived risk of negative health effects is compounded by their
inability to meet the nutritional and rest requirements they feel contraceptive use requires” (Stash
1999). On sterilizations in particular, she writes, “The participants in this study included women
who were forced to return to manual jobs within a day or two of their sterilization operations”
(Stash 1999).
Yet another major cost that is greater for poor women than for wealthy women is the
healthcare access itself. Stash writes, “Those with less money to spend were forced to brave the
government system, but did so with trepidation” (Stash 1999). She writes about long lines at
government clinics, which mean greater opportunity costs. Further, poorer women seem to face
more stigma from healthcare providers. Stash notes that, “Providers also believe that uneducated
village women have difficulty in remembering to take oral contraceptives regularly” (Stash

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1999). Instead, these providers prefer to recommend hormonal injections for less educated
women.
Pritchett & Bongaarts Debate: Supply and Demand as the Chicken and the Egg
In line with the demographic transition theory, many demographers believe that
socioeconomic development leads to fertility decline mainly because women and couples who
are more urban, educated, and wealthy will want fewer children. Economist Lant Pritchett writes
that, “Policies that improve objective conditions for women – raising their income, increasing
their education, encouraging empowerment - are probably the most important voluntary and
sustainable way to achieve the reductions in fertility necessary to slow population growth”
(Pritchett 1994).
On the other hand, some demographers believe that realistic access to family planning is
necessary for couples to want fewer children. Demographer John Bongaarts cites the work of
sociologists Robinson and Cleland in writing, “When overall costs (including social, economic,
and health) of regulating fertility are high, the demand for fertility limitation is weak, because
there is little point in aiming for a goal that cannot be implemented without great difficulty (e.g.
by abstinence). In contrast, reduced costs allow couples to reassess, reaffirm and more readily
attain their fertility preferences” (Bongaarts 2011). In other words, “The means for attaining the
end will directly affect the formation of the ‘demand’ in the first place” (Robinson 1992).
The Pritchett and Bongaarts debate relies exclusively on country-level data and therefore
misses one probable and logical explanation for why wealthier women tend to have fewer
children and poorer women tend to have more children, which is that socioeconomic
development leads to family planning access – including prerequisite contraceptive knowledge –

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at the individual level. If this is true, and if there is a way to extend family planning knowledge
and access to the poorest women and couples, then programs to expedite fertility decline can
indeed work while still fully respecting human rights and individual choice.
Study Design
Demographic and Health Survey (DHS) microdata can be used to explore the
determinants of contraceptive knowledge and the characteristics of women who have none. The
microdata in this analysis was collected in the Demographic and Health Surveys (DHS) and then
integrated and made available by the Integrated Demographic and Health Series (IDHS) based at
the Minnesota Population Center.
Data Source
Primarily funded by the U.S. Agency for International Development (USAID), DHS
provides technical assistance to host-country implementing agencies as they conduct
demographic and health surveys. These surveys are nationally representative and have large
samples, usually between 5,000 to 30,000 households (Survey Process 2015). They all include
women age 15-49, and many also include men age 15-54 or 15-59. To date, DHS has helped to
conduct more than 300 surveys in more than 90 countries (DHS Program 2015). DHS surveys
take approximately 18-20 months and are conducted in four phases: survey preparation and
questionnaire design, training and fieldwork, data processing, and the production of a final report
and data dissemination (Survey Process 2015).
IDHS adds great value to the DHS by integrating its microdata so that variables can be
compared more easily across survey years and national borders, despite different question

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wording or response classifications. When the below data analysis occurred, IDHS data was
available for nine countries: Egypt, Ethiopia, Ghana, India, Kenya, Malawi, Mali, Nigeria, and
Zimbabwe. In late-April 2015, IDHS released data from ten additional countries: Benin, Burkina
Faso, Cote d’Ivoire, Guinea, Malawi, Mozambique, Niger, Tanzania, Uganda, and Zambia. The
data includes three to six survey years for each country.
SelectedSamples
The samples for this data analysis come from Ghana, Mali, and Nigeria, all located in
West Africa. Since this study looks at whether a woman has heard of any method of family
planning, it is important to keep in mind that Southern Africa has been particularly hard-hit by
HIV/AIDS and that countries in that region have experienced a surge of reproductive health
education that has not reached other parts of the continent. Southern African countries have
relatively high levels of HIV/AIDS and relatively high levels of contraceptive knowledge, while
West African countries have relatively low levels of HIV/AIDS and contraceptive knowledge.
Since this paper is more interested in the role of contraceptives to prevent unwanted pregnancy
than to prevent the transmission of HIV/AIDS, it was important to select countries that all have
relatively low levels of HIV/AIDS.
These three countries have similar colonial histories but are different in many ways that
may impact health systems, gender equity, and the social diffusion of new ideas such as
contraceptive knowledge. All three countries declared their independence between 1957 and
1960, as did much of the rest of Africa. Ghana and Nigeria are both former British colonies
where English is the official language, while Mali is a former French colony, and French is the
official language. Ghana and Mali have avoided civil war, while Nigeria had a brutal civil war in

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the 1960s and has been culturally and politically divided for much of its history. Nigeria is
especially large and diverse, with more than 170 million people and more than five hundred
languages spoken (CIA 2015). Ghana seems to have better healthcare than Mali and Nigeria. The
average life expectancy in Ghana is 61 years, compared to 55 in Mali and 52 in Nigeria (World
Bank 2015).
Within these countries, the sample is limited to married women of reproductive age (15-
49), except for Nigeria 1999, which also includes girls ages 10-14. Though some DHS surveys
include men, the IDHS surveys only include women at this time. The literature is very clear that
men have far higher levels of at least one contraceptive method and particularly of male-
controlled methods. Since that is already well established, it is appropriate and preferred that this
analysis focus on contraceptive knowledge inequities among women, rather than between men
and women.
The IDHS data includes women of many relationship statuses, but this data analysis is
limited to married women, who constitute the vast majority of the sample. This seemed
appropriate since the majority of women in Africa do get married and have children, and public
health campaigns to increase contraceptive knowledge would need to work within a cultural
framework where that is the norm. Another reason for this decision is based on the assumption
that marriage would increase a woman’s contraceptive knowledge, all else equal. Friends and
relatives may be more comfortable discussing sexual activity and reproduction once that activity
occurs within a marriage and is culturally and religiously sanctioned.
Though this data analysis is limited to women of reproductive age, there were some
younger girls in the original dataset, from Nigeria 1999. Of the 1,556 girls age 10-14 in that
sample, 49 (3.15%) reported being married. These child brides were excluded from further data

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analysis for several reasons: they are a small portion of the total Nigerian sample, they are not
available in the data from Ghana or Mali, and married girls are likely very different from married
women. However, public health practitioners should continue to explore ways to extend
contraceptive access to child brides. Family planning can be lifesaving for women in general and
especially for girls who are not physically developed enough to safely carry a pregnancy and
give birth.
Multivariate Logistic Regression
This analysis explores the independent variables that determine whether a woman has
heard of any kind of effective contraceptive method. Since this is a binary dependent variable,
this analysis employs multivariate logistic regressions. The regressions were run using Stata
statistical software, and the regression commands included person weights to account for uneven
sampling. The equations includes each of the below independent variables, either as a dummy
variable or with the reference group indicated below. The regressions were run for each
individual sample separately, e.g. Nigeria 2013, and also pooled for all three countries. This
allows one to see how important a variable is in a given sample, to compare the importance of
that variable in one sample versus in another sample, and to see how the country itself can affect
the likelihood that a woman has heard of family planning.
Dependent Variable
The DHS surveys ask women about their knowledge of many specific contraceptive
methods. For Ghana, Mali, and Nigeria, the surveyor begins by asking women what methods of
family planning they have “heard about” (IDHS 2015). For any methods the respondent did not

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list on her own, the surveyor asks if she has heard of them. At this stage, the surveyor mentions a
brief description of each method. For example, the surveyor will ask a woman if she has heard of
implants, and will describe that, “Women can have several small rods placed in their upper arms
by a doctor or nurse which can prevent pregnancy for several years,” and the respondent should
answer whether or not she has heard of that method (IDHS 2015). The DHS captures whether
women who had heard of each method had responded “spontaneously” or after being “probed”
(IDHS 2015). For the purpose of this analysis, women in these two categories are combined and
considered to have “knowledge” of whatever contraceptive methods they have heard of.
There are two differences in question wording across the samples. First, some samples
included a transition into the family planning section meant to normalize contraceptive
knowledge or use. For example, in Ghana in 1988, the survey text instructed surveyors to say,
“Now I would like to talk about a different topic. There are various ways or methods that a
couple can use to delay or avoid a pregnancy” (IDHS 2015). The majority of samples did not
include a transition like this. It should be noted that the actual question text did not vary across
the surveys in this analysis. The second difference is that some surveys included contraceptive
methods that other surveys did not. Table 1 shows which methods were specifically mentioned in
which surveys. The methods lists were generally complete and similar, though Mali 1987 was
the only sample to specifically ask about abstinence or folkloric methods. Also, the female
condom and newer contraceptive methods such as implants and emergency contraception were
only mentioned by name in samples after 1990 and 2000 respectively.
Taking these slight variations into account, IDHS has gathered the responses from each
of the DHS contraceptive method questions and created an overarching variable about the type of
method. This variable categorizes women as knowing about a modern method, a traditional

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method, a folkloric method, or no method. If a woman knows about a modern and a folkloric
method, for example, she is classified as having knowledge of the more reliable method type.
Since this paper is interested in women’s knowledge of all effective methods, it combines
women with knowledge of a modern method and women with knowledge of a traditional method
like abstinence, withdrawal, the rhythm method, or breastfeeding. Then it uses a newly generated
dummy variable: whether or not a woman has heard of any effective method of family planning.
For the remainder of this paper, women who have heard of any effective method are considered
to have “contraceptive knowledge”.
This analysis includes traditional methods for three main reasons. First, fertility decline in
Europe and the United States preceded widespread access to modern methods, supporting the
notion that traditional methods are sufficient to reduce fertility at the macro-level. Second, some
researchers have included traditional methods “because they are widely practiced in Sub-Saharan
African countries” (Creanga 2011). Third, traditional methods have been and are currently being
left out of policy discussions around global family planning. For example, the Guttmacher
Institute counts women using traditional methods of contraception as having an “unmet need” for
family planning. As one researcher summarized, “This [unmet need] equation has taken hold
despite the fact that the prototypical fertility transition, that of Europe, relied largely on the
traditional methods of withdrawal and abstinence, alongside abortion” (Johnson-Hanks 2002).
Modern and traditional methods are useful for different reasons. Modern contraceptives
are an important aspect of global family planning because they enable women to reliably avoid
childbearing while they finish school and at other critical time points in life. Traditional methods
are much less reliable than modern methods at the individual level (except when used perfectly).
Nonetheless, traditional methods allow women to reduce family size and send a signal to other

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women that it is possible to limit childbearing and pursue other parts of one’s life. Therefore,
they should not be ignored, especially in the early stages of any fertility transition.
Traditional family planning may have extremely important policy implications. Because
traditional methods are more “natural” than modern methods, they may be more acceptable in
certain cultures, especially for the purpose of birth spacing. Many cultures in Africa already have
long pregnancy intervals because breastfeeding and post-partum abstinence are the norm, and
other parts of the continent might benefit from knowing these practices are indeed useful
methods for intentional family planning. Also, as long as a woman knows about traditional
methods and has the power within her family to use them, they are nearly costless compared to
modern methods. This suggests that education about traditional methods could be a cost-
effective intervention for policy-makers seeking to reduce fertility rates.
Independent Variables
This model’s independent variables include the sample country (in the pooled
regression), the survey year (in the pooled regression), age, urban/rural residence, current
employment, religion, education, wealth, and the possession of a radio or television.
Country
Each regression in this model is run for an individual country and also pooled with the
country as an independent variable. This allows for comparisons about how important different
independent variables are in different countries and also for comparisons about how the country
itself affects contraceptive knowledge. For the pooled regressions, Nigeria serves as the
reference group.

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Age and Survey Year
This analysis utilizes five-year age groupings in order to account for any cohort effects.
Age groups were determined using the respondents’ reported age according to two questions in
each survey: “In what month and year were you born?” and “How old were you at your last
birthday?” This analysis also controls for survey year under the assumption that contraceptive
knowledge increases as time goes on, which appears to be true.
Residence
The literature indicates that contraceptive knowledge is positively correlated with living
in an urban area. Therefore, this analysis utilizes the dummy variable for “whether the woman’s
de facto residence was an urban or rural location” (IDHS 2015) In the Ghana and Mali DHS, a
woman living in a town with more than 5,000 residents is classified as urban. In the Nigeria
DHS, only women living a town or city with more than 20,000 residents in which the majority of
people do not work in agriculture are considered urban (IDHS 2015). Nigeria is more than four
times as populous as Ghana and Mali combined. Given this context, this analysis will maintain
the classifications of urban residence in the same way that each country’s implementing agency
chose to define it.
Ideally, these models would also include a woman’s childhood residence, since this might
expose her to different people and ideas than her adult residence. However, this variable is not
available for the most recent survey years for each sample. This makes it very difficult to include
the childhood residence variable in a model with other variables that also have limited

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availability. For example, the wealth and childhood residence variables only overlap for Ghana
2003, Mali 2006, and Nigeria 2003.
Employment
Another variable that is considered a determinant of contraceptive knowledge is
employment outside of the home, since employment can expose women to new people and new
ideas. Women who work may also have more money and more social power that could enable
them to pursue contraceptive knowledge and consider taking control of their fertility.
Questions about current employment were asked of all women ages 15-49 in Ghana,
Mali, and Nigeria, but the question wording varies substantially. In the three countries’ surveys
since 2008, the question is posed as, “Aside from your own housework, have you done any work
in the last seven days?” (IDHS 2015). Before 2008, the question was posed more generally as
“Are you currently working?” (IDHS 2015). The first IDHS sample for each country specifically
asks about paid work, while the latter ones do not mention compensation (IDHS 2015). Whether
women earn money or not, this is an important variable given that employment outside of the
home can expose women to new ideas and innovations.
Religion
The surveys for each sample asked, “What is your religion?” or a slight variation, such as
“What is your religious denomination?” in Ghana 1993, “What religion do your practice?” in
Mali 2012, and “What religion do you belong to?” in Nigeria 1990 (IDHS 2015). Each sample
used a different level of detail in classifying religion (e.g. Mali does not differentiate between
Catholic and Protestants), so this variable has been recoded using four main religion

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classifications: Muslim, Christian, traditional or animist, and no religion or “other”. The selected
reference group is Muslim, because there is a large Muslim population in each of these three
countries, whereas there is a large Christian population only in Ghana and Nigeria.
The majority of Ghanaians are Christian, while a majority of Malians are Muslim, and
Nigeria is divided almost evenly between the two religions. Though religion is an important
variable to explore, religion itself may be less important than the degree to which religion
influences law and policymaking, such as through Sharia law. It should be noted that many
predominantly Muslim countries in North Africa, including Morocco, Tunisia, and Egypt have
extremely high levels of contraceptive knowledge (STATcompiler). It is important to note that
religion is closely intertwined with other aspects of culture and to try to separate them if
possible. A study by Aine McCarthy finds that Catholic women in rural Tanzania have much
higher levels of contraceptive use than women from traditional religions, certainly not because of
Catholic teachings (McCarthy 2015). Rather, she suggests that women from the majority
religions (Islam and Christianity) tend to be more cosmopolitan and may have more social
connections with other women to facilitate the diffusion of contraceptive knowledge (McCarthy
2015). For this reason, religion is one of many variables in this model.
Experts in African fertility posit that Muslim women are less likely to have heard of
family planning than Christian women (Fraser 2015). McCarthy’s research suggests that women
with traditional or animist beliefs will be less likely to have heard of family planning than either
Muslims or Christians. People who report having no religion could be secular and progressive or
participate in traditional cultural practices that they do not consider religious, so it is difficult to
hypothesize whether they will be more or less likely to know about family planning.

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Education
This model includes female education, measured as the highest level of school that a
woman has attended. Women were asked whether they have ever attended school and, if so,
“What is the highest level of school you attended?” (IDHS 2015) Taking into account “variations
in question wording reflecting the structure of each country’s educational system,” IDHS divides
educational levels into four categories: no education, primary education, secondary education, or
higher education (IDHS 2015). The selected reference group is “no education,” as it is
hypothesized that education increases the likelihood of contraceptive knowledge in a dose-
dependent manner, where each higher level of education corresponds with a higher likelihood of
contraceptive knowledge. The multivariate regression required that secondary education and
higher education be combined. This was because higher education had an extremely small
sample for each country and because, in Ghana and Nigeria, higher education perfectly predicted
contraceptive knowledge, which disrupted the rest of the statistical model.
The IDHS also provides variables for literacy, which is theoretically important, as it
enables women to read pamphlets or billboards that contain information about family planning.
However, this model uses the educational level variable instead of the literacy variable, in part
because of doubts about the quality of the literacy variable. For example, women who had
attended secondary school or higher were simply assumed to read at the highest literacy level
and were coded as such. A researcher from the Bixby Center for Global Reproductive Health
who does research in northern Nigeria suggests that this automatic classification may be overly
optimistic (Fraser 2015). Another reason to use the education variable instead of the literacy
variable is that attending school exposes girls to social networks that can facilitate the spread of
new ideas, including information about family planning.

21
Wealth
As the demographic transition theory states, socioeconomic development is a very
important determinant of fertility decline, and presumably its proximate determinants:
contraceptive knowledge and contraceptive use. Wealth is the most relevant variable to capture
socioeconomic development. The DHS provides a wealth index, which is “a composite measure
of a household’s cumulative living standard” (Wealth Index 2015). It is calculated using
variables such as ownership of consumer items, dwelling characteristics, and access to water and
sanitation facilities (Wealth Index 2015). The wealth index is weighted and then broken into five
wealth quintiles.
This model uses wealth quintiles as dummy variables, and the reference group is the
poorest quintile, so one can easily compare any other quintile to the poorest quintile. It is
important to note that wealth quintiles capture relative wealth, not absolute wealth and therefore
do not capture economic inequality within a country or between countries. For example, if a
country’s population is almost entirely poor except for the top 1%, then the poorest and middle
quintiles would have very similar levels of wealth. Similarly, comparisons across countries are
inhibited because, for example, the middle quintile in Ghana may be substantially wealthier than
the middle quintile in Nigeria. Despite these considerations, this model uses wealth quintiles for
their straightforward interpretations and comparisons within a country.
Radio and Television
In every sample, respondents were asked whether their household had a series of
possessions, including a radio and a television. In Nigeria 2008, the question was more

22
specifically whether the household had a radio or television that was “in good working order”
(IDHS 2015).
The possession of a television or radio is an imperfect proxy for whether a woman
watches television or listens to the radio and, therefore, is potentially exposed to stories or
information campaigns about family planning methods. It is important to note that televisions
and radios are two of the many household possessions that are incorporated into the household
wealth scores in addition, as previously stated, to dwelling characteristics and access to water
and sanitation facilities. Therefore, the possession of a television or radio is being put into the
model directly through the possession variables and indirectly through the wealth variable.
Because of that, the model’s inclusion of television and radio could theoretically underestimate
the impact of these possessions as well as the impact of one’s wealth. If anything, the true effects
of these variables may be even larger than they appear in the regression results.
Results
As the results and figures will show, this paper’s hypothesis is correct: wealthy and
educated women are indeed more likely to know that family planning exists than poorer and less
educated women are. This is especially true in countries like Mali and Nigeria that still have
relatively low levels of contraceptive knowledge at the national level.
Figure 1 shows the percentage of women at each educational level who have heard of an
effective method of family planning. The graph shows these differentials for samples from
Nigeria 2008, Mali 2006, and Ghana 2008. It also shows these differentials for samples from
Nigeria 2013 and Mali 2012. Data from the most recent Ghana sample is not yet available. As
shown, Nigeria’s levels of contraceptive knowledge have become somewhat more equitable by

23
educational level from 2008 to 2013. In 2008, only 42% of women with no formal education had
heard of family planning, and that number rose to 70% only five years later. Mali shows a
similar progression. In 2006, 67% of women with no formal education had heard of family
planning, compared to 83% in 2012. Still, contraceptive knowledge is very inequitable in both
Nigeria and Mali: educated women have much higher levels of contraceptive knowledge than
their less educated or uneducated peers. By contrast, knowledge of family planning was almost
universal in Ghana in 2008. More than 99% of women with a primary education or higher had
heard of family planning, and 92% of those with no formal education had, which is much higher
than the level of contraceptive knowledge for uneducated women in Nigeria and Mali.
Figure 2 shows how contraceptive knowledge has increased among the least educated
women in each country since 1988-1990. Contraceptive knowledge has increased for uneducated
women in all three countries, which is a positive trend. Ghana’s uneducated women have had
higher levels of contraceptive knowledge than uneducated women in Mali and Nigeria at each
time point, increasing from 66% in 1988 to 92% in 2008. However, Ghana’s trend seems to be
leveling off, suggesting that the last 8% of uneducated women who still do not know about
family planning may be particularly difficult to reach. Mali and Nigeria’s uneducated women
have lower levels of contraceptive knowledge than uneducated Ghanaian women do. However,
the trend lines in Mali and Nigeria suggest that contraceptive knowledge has rapidly spread
among communities of uneducated women and that this trend will likely continue before
reaching a plateau as in Ghana.
Similar to Figure 1, which showed disparate levels of contraceptive knowledge by
educational level, Figure 3 shows disparate levels of contraceptive knowledge by wealth quintile.
This graph shows the level of contraceptive knowledge at each of the five wealth quintiles for

24
Nigeria 2008 and 2013, Mali 2006 and 2012, and Ghana 2008. Nigeria 2008 shows a particularly
dramatic disparity in contraceptive knowledge by wealth. Less than 40% of the poorest women
reported having heard of family planning, compared to 50% for the next poorest quintile, 70%
for the middle quintile, 85% for the next wealthiest quintile, and more than 95% for the
wealthiest quintile. That disparity shrunk somewhat between 2008 and 2013 in Nigeria, as
contraceptive knowledge increased for each wealth quintile and increased the most for those in
poorer quintiles. Still, Nigeria’s figures show dramatic inequality in contraceptive knowledge.
Mali shows similar levels of contraceptive inequity. In 2006, 92% of women in the
wealthiest quintile had heard of family planning, compared to 71% for the second wealthiest
quintile and 66% for the poorest quintile. Interestingly, in Mali, the middle and poor quintiles
have similarly low levels of contraceptive knowledge, especially in 2006. Since wealth is
measured here as relative wealth, it is possible that the middle quintile and poorest quintile have
very similar levels of absolute wealth. Contraceptive knowledge increased for all wealth
quintiles from 2006 to 2012.
As in Figure 1, which showed that Ghana has almost universal contraceptive knowledge
with relatively small inequities by educational level, Figure 3 shows relatively small inequities
by wealth. 91% of the poorest Ghanaians have heard of family planning, which is far higher than
the levels of contraceptive knowledge for corresponding poorest quintile in Nigeria and Mali,
which were 64% in Nigeria in 2013 and 76% in Mali in 2012.
Figures 4, 5, and 6 show the results of multivariate logistic regressions for the most
recent sample available from each country. These logistic regressions are presented with odds
ratios. An odds ratio is a measure of the effect that an independent variable has on a dependent
variable, as expressed by the increased likelihood that a certain outcome will occur. For example,

25
if urban residence has an odds ratio of 2, then women who live in urban areas are 2 times more
likely than women living in rural areas to have heard of family planning, all else equal.
Interpretations of odds ratios for dummy variables that only have two possible classifications,
like urban or rural, are fairly straightforward.
Interpretations for independent variables with many classifications, such as five wealth
quintiles, require the selection of a reference group, as discussed in the above section on
independent variables. In these analyses, the odds ratio would measure the effect of the
independent variable – e.g. highest wealth quintile – on contraceptive knowledge, relative to the
reference group, which in this case is the poorest wealth quintile. The interpretation is the same
as for dummy variables. For example, if the odds ratio for the highest wealth quintile is 6, then a
woman in the highest wealth quintile is 6 times more likely to have heard of family planning
than a woman in the wealth reference group, which is the poorest wealth quintile. The odds ratio
of the reference group is always set at 1. The conceptual logic for this is that, for example,
women in the poorest wealth quintile are 1 times as likely (or 100% as likely) to have heard of
family planning as those in the poorest wealth quintile.
Figure 4 shows the multivariate logistic regression results for Ghana 2008. In that
sample, the most important variables that affect contraceptive knowledge are age and education.
Women between the ages of 30-34 are the most likely to have heard of an effective method of
family planning; they are 14.6 times more likely to have heard of an effective method than the
age reference group, which is women aged 15-19. Women who have completed secondary
education or higher are 3.9 times more likely to have heard of any effective method than the
education reference group, which is women without any formal education. However, the
confidence interval for the 3.9 figure extends below 1, which means it is possible that more

26
educated women are not any more likely to have heard of family planning than uneducated
women, and the 3.9 value is only statistically significant at the 90% value, so it should be
interpreted with caution. The importance of primary education is much stronger and also meets a
higher threshold of statistical significance. Women who have completed primary education are
10.1 times more likely to have heard of any effective method of family planning than women
who have attended no school. This is the only sample in which primary school seems to have a
greater effect on family planning knowledge than secondary or higher education.
Figure 5 shows the multivariate logistic regression results from Mali 2012. In this
sample, the independent variables that most greatly increase the likelihood of contraceptive
knowledge are education and wealth. Women who have completed secondary education or
higher are 3.5 times more likely to have heard of any effective method of family planning than
women who have attended no school, all else equal. Primary education also increases the
likelihood of contraceptive knowledge but to a lesser degree. Women who have completed
primary education are 1.7 times more likely to have heard of any effective method of family
planning than women who have attended no school, all else equal. Women in the wealthiest
quintile of women are 4.8 times as likely to have heard of an effective method than women in the
poorest quintile. There appears to be a “dose-response” relationship between wealth and
contraceptive knowledge, since each increase in the wealth quintile corresponds with a greater
likelihood that a woman has heard of family planning.
Figure 6 shows the results from Nigeria 2013 and tells a similar story to that of Mali
2012: education and wealth have the largest effects on contraceptive knowledge. Women who
attended secondary school or higher are 5.1 times more likely to have heard of any effective
method of family planning than women who have attended no school, all else equal. As in Mali,

27
primary education also increases the likelihood of contraceptive knowledge but to a lesser
degree. Women who have completed primary education are 2.4 times more likely to have heard
of any effective method of family planning than women who have attended no school, all else
equal. Also mirroring the pattern observed in Mali, there appears to be a “dose-response”
relationship between wealth and contraceptive knowledge in Nigeria. Women in the top four out
of five wealth quintiles are all more likely to have heard of family planning than women in the
poorest wealth quintile. Women in the poorer wealth quintile are 50% more likely, women in the
middle quintile are 70% more likely, women in the richer quintile are 3.1 times more likely, and
women in the richest quintile are 6.8 times as likely to have heard of an effective method of
family planning than women in the poorest quintile, all else equal.
Table 2 contains the odds ratios for each variable in each sample and in a pooled logistic
regression that uses Nigeria as a reference group. Pooling the data facilitates a look at how the
country in which women live can be considered another independent variable that influences the
likelihood that they have heard of family planning. The results from the pooled regression in the
last column show that women in Ghana are 18.1 times more likely to have heard of an effective
method of family planning than women in Nigeria, after controlling for survey year, age, urban
residence, employment, religion, education, relative wealth, and the possession of a television or
radio. Women in Mali were 2.3 times more likely than women in Nigeria to have heard of an
effective method, after controlling for the same independent variables.
Discussion

28
The results discussed above confirm the hypothesis that wealthy and highly educated
women are more likely to know that family planning exists than poorer and less educated women
are. It is striking that wealthy women are much more likely to know about family planning than
poor women in Nigeria and in Mali, even after controlling for education, age, urban residence,
employment, religion, and the possession of a television or radio. This new empirical evidence
lends legitimacy to the sometimes unsupported assertion that poor and less educated women face
even greater costs and barriers to accessing family planning than wealthier and more educated
women. This research demonstrates a wealth-related disparity at the most basic level of
contraceptive access, which is simply knowing that family planning exists.
These findings challenge the demographic transition theory’s principle that
socioeconomic development is a prerequisite for fertility decline. Instead, these findings suggest
that socioeconomic development as measured by wealth and education may actually be a proxy
measure for contraceptive knowledge and access. It may be that contraceptive access – and not
only wealth and education – helps to explain why wealthier and more educated women tend to
have fewer children than poorer and less educated women. These findings support the assertion
by researcher Martha Campbell, that policymakers in places facing unsustainably high fertility
rates need not wait for socioeconomic development to precede fertility decline. Instead, they may
be able to facilitate knowledge about and access to family planning in order to expedite fertility
decline within “a human rights framework” (Campbell 2009).
The results of this research are consistent with the theory of the diffusion of innovation,
which is a way of looking at how a new behavior spreads throughout a population. It is often
applied to consumer behavior and health behavior. Generally, the first people to try a new
product or adopt a new behavior, people called early innovators, tend to be more educated, more

29
affluent, and more urban (Cleland 2001). The innovators are followed by the early adopters, the
early majority, the late majority, and the laggards.
On the diffusion of the innovation of family planning, demographer Ron Lesthaeghe’s
research states that the early innovators are a “restricted group” (Lesthaeghe 2001). They share
their innovative knowledge and behaviors about family planning with their immediate and
trusted environment, which begins the diffusion of the innovation of family planning. The
innovation can then spread through and beyond these groups in the form of informal social
diffusion or formal social diffusion. Informal social diffusion includes social networks like
classmates, coworkers, and friends. This informal diffusion process depends greatly upon how
much social mixing there is. Lesthaeghe notes, “Permeability across social classes, for instance,
often results in a ‘trickle down’ effect” (Lesthaeghe 2001). He adds, “If one has reasons to
believe that a society has important social cleavages that cause impermeability, messages [about
the benefits, acceptability, and possibility of using family planning] need to be tailor made to suit
each of these segregated networks” (Lesthaeghe 2001).
These tailored messages to segregated networks can utilize modes of formal social
diffusion. Whereas informal social diffusion is a naturally occurring social process, formal social
diffusion is an intentional intervention to spread knowledge, product usage, or a new health
behavior. Modes of formal social diffusion include public service announcements, television
advertisements, sexuality education classes, health educator home visits, and posters.
Interventions that utilize both informal and formal diffusion processes will be discussed in the
below section on recommendations.
Study Limitations

30
There are some concerns about the quality of data in Nigeria, prompted by some very
unexpected findings. Though the unexpectedly sharp increase in contraceptive knowledge among
Nigeria’s poorest women from 1999 to 2003 in Figure 2 suggests that Nigeria 2003 may contain
false data, other researchers are more concerned with the Nigeria’s 1999 data. In an evaluation of
his own research, Bongaarts expressed concern about Nigeria’s DHS data. He wrote, “The first
country report for the 1999 survey in Nigeria presents persuasive evidence of substantial
underreporting for events resulting in the underestimation of levels of fertility and child
mortality” (Bongaarts 2008). At the 2015 Population Association of America conference, a
USAID employee who works on the DHS project reviewed this paper’s findings and added her
concern about the Nigeria 1999 data, which she reported had some “data quality issues” (Choi
2015). She noted that USAID was only invited to assist Nigeria with the 1999 survey after the
fieldwork had already been done (Choi 2015). Other reviewers also suggested examining
sampling problems with Nigeria’s data in all years.
This research is limited in its ability to examine the role of informal social diffusion
because of limited relevant variables in the IDHS data. It has variables about formal diffusion,
such as radio and television. Education and current employment can be a proxy for social
interactions with others, but they are not an ideal way to measure social connectedness. There is
one IDHS variable for associations with women’s groups, but it is only available for one of the
samples used in this study.
One possible issue in the data is that there could be underreporting of contraceptive
knowledge since sexual knowledge among women is taboo in many cultures. If some women,
such as younger women, are systematically more likely to underreport contraceptive knowledge,
then there could be reporting bias.

31
This analysis does not capture the ways that some independent variables may interact
with other independent variables, such as whether education has a larger effect size for younger
women than for older women. This analysis does address one likely interaction; since the survey
year is likely to interact with the effect sizes of other independent variables, this analysis
separates different survey years in order to see how effect sizes shift over time.
Potential Future Research
Future research could use older samples to replicate the regressions in this paper for
earlier samples from Ghana, Mali, and Nigeria in order to see how the importance of a certain
independent variable changes over time. This would enable researchers to observe how the
diffusion of innovation has proceeded in Ghana as compared to Mali and Nigeria. Since
contraceptive knowledge among uneducated women has plateaued in Ghana and continues to
rise in Mali and Nigeria, it seems likely that Ghana is simply farther along in the diffusion of
contraceptive knowledge. This paper did not include samples from before 2008 because the
models showed that wealth is an extremely important determinant of contraceptive knowledge
and, though the DHS has wealth data from the earlier samples, it is not yet integrated into the
IDHS datasets. Regressions using older data without the wealth variable would likely
overestimate the importance of education, since education and wealth are generally highly
correlated. If and when this older wealth data is integrated, it will be an asset in determining how
the impact of wealth on contraceptive knowledge has changed over time.
Another area of potential research is the comparison of men’s knowledge with women’s
knowledge. There are DHS samples that include men, but men are not yet integrated into the
IDHS. DHS reports from Ghana, Mali, and Nigeria indicate that men have almost universal

32
knowledge of at least one method of family planning, regardless of educational level or wealth.
In Mali and Nigeria, women have far lower levels of contraceptive knowledge than men do. As
demonstrated in this paper, there are tremendous inequities among women based on
socioeconomic status; DHS reports show that these inequities are much smaller among men. It
seems that maleness is an important independent variable that affects contraceptive knowledge
and that maleness interacts with other variables, essentially wiping out the importance of
education and wealth on contraceptive knowledge.
Conclusions and Recommendations
Since this paper shows that there remains a large disparity in contraceptive knowledge
between wealthy and poor women, policymakers should consider ways to expedite the diffusion
of family planning knowledge. Researchers and policymakers should carefully evaluate the
effectiveness of recent and ongoing programs that utilize local resources to expand contraceptive
knowledge and access in resource-constrained settings. These local resources include trusted
early innovators and local purchasing power. In India, non-profit organizations have trained
traditional medicine men and supplied them with contraceptives to sell within their large and
already established distribution networks (Cheshes 2002). In the United States, Planned
Parenthood trains teenaged peer educators to talk about family planning with other teenagers and
Latina women to talk with other Latina women. In Ethiopia, female farmers are trained to
discuss family planning and distribute contraceptives to other female farmers (Prata 2013). One
major advantage of these programs is that the female clients communicate with people in their
own community who already have their trust, which is particularly important in matters of sexual
health. As contraceptive knowledge grows, demand for contraceptives should also grow since

33
consumers often demand a product or see a need for a product only after they learn it exists and
that it is attainable; examples include the copy machine, television remote controls, disposable
diapers, personal computers, garage door openers, and adhesive notes (Campbell et al 2013). As
African economies grow and wealthier African women demand more and more contraceptives,
programs can also utilize a total market approach, in which profits from sales to higher-income
consumers are used to subsidize lower-cost contraceptives to lower-income consumers and free
contraceptives for the lowest-income consumers.
As earlier research has shown, access to family planning enables women to pursue
schooling and employment (Bailey 2006). If poor and less educated women do not have the
knowledge and ability to access voluntary family planning and its numerous benefits, while
richer and more educated women do, then this unequal distribution of access to voluntary family
planning may further drive inequality between the rich and poor. Conversely, more equitable
access to voluntary family planning may serve as an equalizer by giving poor women more
choices about their future. Whether policymakers are driven more by population issues such as
rapid population growth, strained infrastructure, and political instability or by individual issues
such as freedom and self-determination, they should continue to work toward universal
knowledge about and access to voluntary family planning.

34
References
Bailey, M. J. (2006) More Power to the Pill: The Impact of Contraceptive Freedom on Women's
Life Cycle Labor Supply. The Quarterly Journal of Economics 121.1 289-320.
Bongaarts, J. (1994). The Impact of Population Policies: Comment. Population and Development
Review, 616-620.
Bongaarts, J. (2008). Fertility Transitions in Developing Countries: Progress or Stagnation?
Studies in Family Planning, 39(2), 105-110.
Bongaarts, J. (2011). Can Family Planning Programs Reduce High Desired Family Size in Sub-
Saharan Africa? International Perspectives on Sexual and Reproductive Health, 37(1), 209-216.
Campbell, M., Prata, N., & Potts, M. (2013). The Impact of Freedom on Fertility Decline.
Journal of Family Planning and Reproductive Health Care, 39, 44-50.
Campbell, M. & Bedford, K. (2009). The Theoretical and Political Framing of the Population
factor in Development. Philosophical Transactions of the Royal Society B: Biological Sciences,
3101-3113.
Campbell, M., Sahin-Hodoglugil, N., & Potts, M. (2006). Barriers to Fertility Regulation: A
Review of the Literature. Studies in Family Planning, 37(2), 87-98.
Casterline, J. (2001). Diffusion Processes and Fertility Transition: Introduction. In Diffusion
Processes and Fertility Transition - Selected Perspectives. Washington, D.C.: National Academy
Press.
Casterline, J., Sathar, Z., & Haque, M. (2001). Obstacles to Contraceptive Use in Pakistan: A
Study in Punjab. Studies in Family Planning, 95-110.
Cheshes, J. (2002, November 1). Hard-Core Philanthropist. Mother Jones.
Choi, Y. (2015, May 2). Nigeria 1999 Data Quality Issues [Personal interview].
CIA - World Factbook: Nigeria. (2015). Retrieved May 18, 2015, from
https://www.cia.gov/library/publications/the-world-factbook/geos/ni.html
Cleland, J. (2001). Potatoes and Pills: An Overview of Innovation-Diffusion Contributions to
Explanations of Fertility Decline. In Diffusion Processes and Fertility Transition - Selected
Perspectives. Washington, D.C.: National Academy Press.
Creanga, A., Gillespie, D., Karklins, S., & Tsui, A. (2011). Low Use of Contraception Among
Poor Women in Africa: An Equity Issue. Bulletin of the World Health Organization, 258-266.
DHS Program. (2015). Retrieved May 18, 2015, from http://www.dhsprogram.com/

35
Diamond-Smith, N., & Potts, M. (2011). A Woman Cannot Die from a Pregnancy She Does Not
Have. International Perspectives on Sexual and Reproductive Health, 37(3), 155-158.
Easterlin, R. (1975). An Economic Framework for Fertility Analysis. Studies in Family
Planning, 6(3), 54-63.
Fraser, A. (2015, May 2). Suggested Future Research [Personal interview].
Guttmacher - Adding It Up: Investing in Sexual and Reproductive Health. (2014, December 1).
Retrieved May 18, 2015.
IDHS - Survey Text. (2015). Retrieved August 10, 2015, from https://www.idhsdata.org/idhs-
action/variables/group
Johnson-Hanks, J. (2002). On the Modernity of Traditional Contraception: Time and the Social
Context of Fertility. Population and Development Review, 28(2), 229-249.
Lesthaeghe, R., & Vanderhoeft, C. (2001). Ready, Willing, and Able: A Conceptualization of
Transitions to New Behavioral Forms. In Diffusion Processes and Fertility Transition - Selected
Perspectives. Washington, D.C.: National Academy Press.
McCarthy, A. (2015). Working Paper.
Prata, N., Weidert, K., Fraser, A., & Gessessew, A. (2013). Meeting Rural Demand: A Case for
Combining Community-Based Distribution and Social Marketing of Injectable Contraceptives in
Tigray, Ethiopia. PLoS ONE.
Pritchett, L. (1994). Desired Fertility and the Impact of Population Policies. Population and
Development Review, 1-1.
RAND - International Family Planning Programs: Criticisms and Responses. (2002). Retrieved
May 18, 2015, from http://www.rand.org/pubs/research_briefs/RB5063/index1.html
Robinson, W., & Cleland, J. (1992). The Influence of Contraceptive Costs on the Demand for
Children. Family Planning Programmes and Fertility, 106-122.
Sedgh, G., Singh, S., & Hussain, R. (2014). Intended and Unintended Pregnancies Worldwide in
2012 and Recent Trends. Studies in Family Planning, 301-314.
Singh, S., Darroch, J., & Ashford, L. (2014). Adding It Up: The Costs and Benefits of Investing
in Sexual and Reproductive Health 2014. Retrieved August 10, 2015.
Smith, D. (2004). Contradictions in Nigeria's Fertility Transition: The Burdens and Benefits of
Having People. Population and Development Review, 30(2), 221-238.

36
Stash, S. (1999). Explanations of Unmet Need for Contraception in Chitwan, Nepal. Studies in
Family Planning, 30(4), 267-287.
STATcompiler. (n.d.). Retrieved April 15, 2015, from http://www.statcompiler.com/
Survey Process. (2015). Retrieved May 18, 2015, from http://www.dhsprogram.com/What-We-
Do/Survey-Process.cfm
Wealth Index. (2015). Retrieved May 18, 2015, from http://www.dhsprogram.com/topics/wealth-
index/Index.cfm
World Bank - Life Expectancy at Birth, Total (Years). (2015). Retrieved May 18, 2015, from
http://data.worldbank.org/indicator/SP.DYN.LE00.IN

38
0
10
20
30
40
50
60
70
80
90
100
Nigeria 2008 Nigeria 2013 Mali 2006 Mali 2012 Ghana 2008
Figure 1: The Percentage ofMarried WomenFrom Each Educational Level Who
Have Heard of Any Effective Methodof FamilyPlanningin Nigeria2008 & 2013,
Mali 2006 & 2012, Ghana 2008, Derivedfrom IDHS Microdata
No Education
Primary Eduation
Secondary Education
Higher Education
Source: Integrated Demographic and Health Series
0
10
20
30
40
50
60
70
80
90
100
1985 1990 1995 2000 2005 2010 2015
Figure 2: The Percentage of Married WomenWithNo Formal Education Who
Have Heard of Any Effective Methodof FamilyPlanningin Ghana, Mali,and
Nigeriafrom 1987 to 2013, Derivedfrom IDHS Microdata
Ghana
Mali
Nigeria

39
0
10
20
30
40
50
60
70
80
90
100
Nigeria 2008 Nigeria 2013 Mali 2006 Mali 2012 Ghana 2008
Figure 3: The Percentage of Married WomenFrom Each WealthQuintile Who
Have Heard of Any Effective Methodof FamilyPlanningin Nigeria2008 & 2013,
Mali 2006 & 2012, Ghana 2008, Derivedfrom IDHS Microdata
Poorest
Poorer
Middle
Wealthier
Wealthiest

40
0 5 10 15 20
Figure 4: Odds Ratios for Factors that Influence WhetherAWomanHas Heard of
Any Effective MethodofFamily Planningin Ghana in2008,
Derivedfrom IDHS Microdata
Age 20-24 *
Age 25-29 **
Age 30-34 ***
Age 35-39 **
Age 40-44 ***
Age 45-49 ***
Urban
Currently Working *
Christian **
Traditional or Animist
No Religion or Other
Seconardy or Higher *
Primary ***
Wealthiest
Wealthier
Middle
Poorer
Has Radio ***
Has TV
Statistical significance:*** = 90%, ** = 95%, * = 90%, Confidence intervals marked by palecolored range
Age reference group: Age 15-19; Religion reference group: Muslim;Education reference group: No formal
education; Wealth reference group: Poorest quintile

41
0 5
Any Effective MethodofFamily Planningin Mali in 2012,
Age 20-24 **
Age 25-29 ***
Age 30-34 ***
Age 35-39 **
Age 40-44
Age 45-49
Urban ***
Currently Working ***
Christian
Traditional or Animist
No Religion or Other
Seconardy or Higher ***
Primary ***
Wealthiest ***
Wealthier ***
Middle ***
Poorer
Has Radio ***
Has TV

42
0 5 10
Any Effective MethodofFamily Planningin Nigeriain2013,
Age 20-24 ***
Age 25-29 ***
Age 30-34 ***
Age 35-39 ***
Age 40-44 ***
Age 45-49 ***
Urban ***
Currently Working ***
Christian ***
Traditional or Animist ***
No Religion or Other ***
Seconardy or Higher ***
Primary ***
Wealthiest ***
Wealthier ***
Middle ***
Poorer ***
Has Radio ***

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