Download Impact of climate change on reproductive health

FACULTY OF MEDICINE AND
HEALTH SCIENCES
Academic Year 2014 - 2015
Impact of climate change on reproductive
health
Amelie GISTELINCK
Promotor: Prof. Dr. Degomme, Olivier
Co-promotor: Van Braeckel, Dirk
Dissertation presented in the 2nd Master year
in the programme of
Master of Medicine in Medicine
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Table of contents Table of contents ........................................................................................................................ 1
Abstract ...................................................................................................................................... 6
Introduction ............................................................................................................................ 6
Objectives and methods.......................................................................................................... 6
Results .................................................................................................................................... 6
Discussion............................................................................................................................... 7
Samenvatting.............................................................................................................................. 8
Inleiding.................................................................................................................................. 8
Objectieven en methoden ....................................................................................................... 8
Resultaten ............................................................................................................................... 9
Discussie................................................................................................................................. 9
Introduction .............................................................................................................................. 10
Literature study ........................................................................................................................ 13
Defining reproductive health & reproductive behaviour...................................................... 13
Climate change ..................................................................................................................... 14
Climate change in Ethiopia................................................................................................... 16
Reproductive health: demography........................................................................................ 17
Reproductive behaviour: morbidity & mortality .................................................................. 19
Parity and family size........................................................................................................ 19
Birth spacing..................................................................................................................... 19
Unwanted pregnancy ........................................................................................................ 20
Age at first pregnancy....................................................................................................... 21
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Fertility preferences.......................................................................................................... 21
Family planning (FP) ....................................................................................................... 22
Reproductive behaviour in Ethiopia ..................................................................................... 22
Connecting reproductive health & climate change............................................................... 23
Perception ......................................................................................................................... 24
Migration .......................................................................................................................... 24
Marriage........................................................................................................................... 25
Fertility ............................................................................................................................. 26
Fertility preferences.......................................................................................................... 26
Tool: Family planning....................................................................................................... 27
Hypothesis & Methodology ..................................................................................................... 28
Objectives ............................................................................................................................. 28
Materials ............................................................................................................................... 29
Environmental indicators.................................................................................................. 29
Data on reproductive behaviour....................................................................................... 30
Methods ................................................................................................................................ 31
Environmental indicator ................................................................................................... 31
Merging and recoding the environmental variable .......................................................... 32
Data cleaning and recoding of reproductive behaviour variables................................... 32
Descriptive statistics ......................................................................................................... 33
Analytical statistics ........................................................................................................... 33
Descriptive statistics................................................................................................................. 34
Analytical statistics .................................................................................................................. 37
Confounding factors ............................................................................................................. 37
Urban-rural status ............................................................................................................ 37
Year of sample................................................................................................................... 37
Total children ever born ................................................................................................... 38
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Cohort year (age of mother in five year groups) .............................................................. 38
Reproductive history............................................................................................................. 39
First child under 16 .......................................................................................................... 39
First child under 20 .......................................................................................................... 40
Current reproductive status................................................................................................... 40
Total children ever born ................................................................................................... 40
Number of dead children per woman................................................................................ 41
Unwanted children............................................................................................................ 42
Current pregnancy wanted ............................................................................................... 42
Fertility preferences.............................................................................................................. 43
Ideal number of children................................................................................................... 43
Desire for more children................................................................................................... 44
Coverage............................................................................................................................... 45
Unmet need for family planning ....................................................................................... 45
Discussion ................................................................................................................................ 46
Determining significant confounding factors ....................................................................... 46
Urban women.................................................................................................................... 47
Children ever born to a woman ........................................................................................ 47
Cohort ............................................................................................................................... 47
Sample year....................................................................................................................... 48
Differences in reproductive behaviour in variously vulnerable areas .................................. 48
Evolution of differences over time ....................................................................................... 49
Interactions of desertification with other reproductive health influencing-factors .............. 49
Weaknesses of the study....................................................................................................... 50
Suggestions on future research ............................................................................................. 51
Implications of the research.................................................................................................. 51
Conclusion ............................................................................................................................ 52
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References ................................................................................................................................ 53
Annexes.......................................................................................................................................I
Annex 1.
Table with all variables of the final dataset ......................................................I
Annex 2.
Table with variables that will be used ..............................................................II
Annex 2.
Confidentiality document................................................................................ III
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Abstract Introduction
Climate change forms the paramount concern of today’s world, placing severe pressure on
various ecosystems of the planet Earth. Ethiopia, situated in East Sub-Saharan Africa is
particularly at risk in terms of desertification. Ethiopia covers an area of 1.1 million km² and
almost one third of the country’s land consists of arid, semi-arid, dry and sub-humid areas.
These areas are particularly prone to climate change and desertification. Ethiopia has an
estimated population of 95,933,000 and an annual population growth of 2.1%. The population
growth places a supplementary pressure on the land’s recourses. Since the Ethiopian economy
is still largely dependent on rain-fed agriculture, land degradation has its repercussions on the
inhabitants. Humans take up adaptation strategies to decrease their vulnerability. These
adaptation strategies can be observed in the field of reproductive behaviour. Reproductive
behaviour is related to reproductive health. Because of the importance of reproductive health
in a human’s life, we will investigate the response to desertification in terms of reproductive
behaviour.
Objectives and methods This study tried to investigate the responses in terms of reproductive behaviour to persisting
and progressive ecological degradation associated with climate change in Ethiopia.
Vulnerability to desertification is used as a proxy for climate change in Ethiopia. The main
objectives were to explore potential differences in areas that had a different vulnerability to
desertification, explore time trends in these differences and determine if desertification
interacts with other factors that influence reproductive behaviour. By linking georeferenced
demographic data to spatial data on desertification vulnerability, this study was able to
analyse the relation between reproductive behaviour and desertification. Nine indicators of
reproductive behaviour were used and four confounders were included in the analysis.
Results Our study findings indicate that fertility preferences are more likely to be higher in
desertification-vulnerable areas. The number of wanted pregnancies and the total number of
children ever born are also more probable of being higher in these areas. In areas that are not
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prone to desertification, women have a higher probability to have more unwanted children.
The rise in met needs for family planning appears to be more rapidly over the years in areas
that are not prone to desertification than in the areas prone to desertification.
Discussion The study confirmed the hypothesis that people in desertification prone areas display other
reproductive behaviour than people in areas that were not vulnerable to desertification. The
tenor of this adaptive behaviour can be considered as a ‘risk-insurance’ strategy. However,
further qualitative and quantitative research is needed. Furthermore, linkage of this research
with information on other hazards and with migratory data can be of particular interest.
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Samenvatting Inleiding Klimaatverandering vormt één van de belangrijkste gevaren voor onze wereld vandaag de
dag. Klimaatsverandering plaatst een grote druk op de verscheidene ecosystemen van onze
aarde. Ethiopië, gesitueerd in Oostelijk Sub-Saharisch Afrika, wordt vooral getroffen door
verwoestijning. Ethiopië heeft een oppervlakte van 1.1 miljoen km² en naar schatting één
derde van het land bestaat uit dorre, semi-dorre, droge en semi-droge gebieden. Het zijn
vooral deze gebieden die een risico vormen voor het optreden van verwoestijning. Ethiopië
heeft een geschatte bevolking van 96 miljoen inwoners en kent een jaarlijkse bevolkingsgroei
van 2.1%. De bevolkingsgroei plaatst een aanvullende druk op de natuurlijke bronnen van het
land. Sinds de Ethiopische economie grotendeels afhankelijk is van landbouw, heeft
bodemdegradatie een weerslag op de Ethiopische bevolking. Mensen ontwikkelen
adaptatiestrategieën om hun kwetsbaarheid te verminderen, onder andere op vlak van
reproductief gedrag. Omwille van het belang van reproductieve gezondheid in het leven van
een mens, zullen de veranderingen in reproductief gedrag als antwoord op de
woestijnvorming onderzoeken.
Objectieven en methoden Deze studie probeerde de reacties op progressieve ecologische degradatie in Ethiopië te
onderzoeken in termen van reproductief gedrag. Kwetsbaarheid voor woestijnvorming werd
gebruikt als een proxy voor de klimaatverandering in Ethiopië. De doelstellingen waren om
mogelijke verschillen tussen gebieden met een verschillende kwetsbaarheid voor
woestijnvorming te evalueren, de evolutie van deze verschillen te onderzoeken in de tijd en te
bepalen of woestijnvorming interageert met andere factoren die het reproductieve gedrag
beïnvloeden. Door geografische demografische gegevens te koppelen aan ruimtelijke
gegevens betreffende de kwetsbaarheid van woestijnvorming, was deze studie in staat om de
relatie tussen reproductief gedrag en verwoestijning te analyseren. Negen indicatoren voor
reproductief gedrag werden gebruikt en er werd gecorrigeerd voor vier verstorende factoren in
de analyse.
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Resultaten Onze bevindingen wijzen erop dat de voorkeuren voor reproductie meer kans hebben om
hoger te zijn in verwoestijnde gebieden. Het aantal gewenste zwangerschappen en het totaal
aantal kinderen dat ooit geboren is, zijn ook meer waarschijnlijk hoger in deze gebieden. In
gebieden die niet gevoelig zijn voor woestijnvorming, hebben vrouwen een hogere kans om
meer ongewenste kinderen te hebben. De daling van de onbevredigde behoeften betreffende
gezinsplanning lijkt sneller te gaan in gebieden die niet gevoelig zijn voor woestijnvorming
dan in de gebieden die vatbaar zijn voor woestijnvorming.
Discussie De studie bevestigde de hypothese dat mensen in verwoestijnings-gevoelige gebieden ander
reproductief gedrag stellen dan mensen in gebieden die niet kwetsbaar zijn voor
woestijnvorming. De reden voor specifiek dit soort adaptief gedrag kan gevonden worden in
de ‘risicoverzekering' strategie. Echter is verder kwalitatief en kwantitatief onderzoek nodig.
Bovendien kan het nuttig zijn deze informatie in verband te brengen met informatie over
andere
gevaren
(droogte,
oorlog,
etc.)
en
met
gegevens
over
migratie.
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Introduction What
is
the
impact
of
climate
change
on
reproductive
health?
Upon reading this title question there might arise a sensation of bewilderment. The linkage of
climate change and reproductive health may seem controversial, perhaps inexistent?
Nevertheless, this is all but the case. The relationship between reproductive health - a part of
which is formed by reproductive behaviour - and climate change is bidirectional and can be
investigated in either direction. This thesis will focus on the effects that climate change
related hazards - and more specifically desertification - have on human reproductive
behaviour.
“Reproductive health is a state of complete physical, mental and social well-being and not
merely the absence of disease or infirmity, in all matters relating to the reproductive system
and to its functions and processes. Reproductive health therefore implies that people are able
to have a satisfying and safe sex life and that they have the capability to reproduce and the
freedom to decide if, when and how often to do so.”(1) Considering the broad perception of
reproductive health, one can understand it is vastly rooted in educational, economic, cultural
contexts as well as the environmental context. Reproductive behaviour makes up a part of the
domain of reproductive health, focussing on the ideas people have on and choices people
make relevant to reproduction.
Today, climate change is an everyday-headliner in newspapers and broadcasts all over the
world. But what exactly do we mean when talking about climate change? In 1992, the United
Nations Framework Convention on Climate Change defined climate change as ‘A change of
climate which is attributed directly or indirectly to human activity that alters the composition
of the global atmosphere and which is in addition to natural climate variability observed over
comparable time periods.’ This change can and will bring about shifts not only in
environmental systems (e.g. extreme weather events, rising sea-levels) but also in human
systems (figure 1.).
Adaptation and mitigation strategies can be reckoned as shifts or as a reaction on shifts in
human systems. We refer to the ‘literature study’ section for further exploration of these
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terms, as well as for a brief consideration of the reproductive health field and the phenomenon
of climate change.
Figure 1. Conceptual diagram linking demographic change to vulnerability,
adaptation and migration in the context of climate change(2)
Since anthropogenic climate change is the paramount environmental concern of today’s world
and because of the significance of reproductive health in a human’s life - both in cause as in
consequence - this thesis tries to investigates the influences of climate stress on reproductive
behaviour (as a part of the reproductive health field) in a climate-change vulnerable context.
Ethiopia offers the perfect location because of its inherent governmental interests and efforts
in the domain of reproductive behaviour (Ethiopia is a patriarch in the family-planning policy
field) and because of its unique geography: Ethiopia is situated in Sub-Saharan Africa, a zone
highly susceptible to climate change. Furthermore, because it is the second largest country in
Africa, comparison over contrastingly affected regions is possible.
The literature on this subject tends to focus on migration as a reaction to climate stress.
Although we will give notion of the migratory adaptation strategy in the ‘literature study’
section, the research in this thesis will try to stay away from this theory to focus on other
noticeable adaptations to climate stress in the reproductive health field.
The main objective of the research is to investigate the reproductive behaviour in Ethiopian
areas that are variously vulnerable to desertification. Specifically, it attempts to measure the
demographic changes (in behaviour as well as in attitude) that have taken place from the year
2000 until 2011 in Ethiopia. The Demographic Health Survey census data from Ethiopia surveyed in the year 2000, 2005 and 2011 - will be used to trace demographic trends. A map
of ‘vulnerability to desertification’ will be linked to the demographic information in order to
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compare areas with different degrees of climate stress. Accordingly, trends can be interpreted
in terms of behavioural trends linked with climate stress.
The importance of mapping transitions and changes in reproductive behaviour as a reaction to
one of the most important calamities of our time should not be underestimated. Studies on this
subject could provide meaningful information for both policy makers, as for organisations in
the field. This thesis can be considered as an introduction to the subject and a call for further
research on this subject.
The first part of this thesis consists of a summary of the existing literature. Based on previous
research and a thorough review of the literature, a hypothesis will be formed and outlined in
the ‘methodology’ section. Furthermore, this section will also contain the details of the
methods of research. Following are the descriptive statistics and the analytic statistics. This
will bring us to a reporting of the results. Finally, after interpreting these results and critically
reflecting on the study in the ‘discussion’-section, a conclusion will be given.
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Literature study In this literature study, reproductive behaviour and climate change will be elucidated. For
each of these two domains, the case of Ethiopia is to be pinpointed. To begin with,
reproductive behaviour will be defined. Afterwards, a thorough dispatch of the phenomenon
of climate change will be given. Following, the importance of reproductive behaviour will be
highlighted, through ‘the ticking time bomb’ known as demography and through the potential
effects of reproductive behaviour on the morbidity and mortality outcomes for mothers and
children. Finally, an overview of the literature which interlinks reproductive behaviour with
climate change is presented.
Defining reproductive health & reproductive behaviour “Reproductive health is a state of complete physical, mental and social well-being and not
merely the absence of disease or infirmity, in all matters relating to the reproductive system
and to its functions and processes.” (1) In 1994, this universally accepted definition for
reproductive health was documented when the United Nations assembled the Fifth
International Conference on Population & Development (ICPD) in Cairo. Furthermore, the
definition captures the importance of a satisfying and safe sex life and the freedom of selfdetermination concerning sexual intercourse. Consequently, this implies the right for all
people “to be informed and to have access to safe, effective, affordable and acceptable
methods of family planning of their choice, as well as other methods of their choice for
regulation of fertility which are not against the law, and the right of access to appropriate
health-care services that will enable women to go safely through pregnancy and childbirth and
provide couples with the best chance of having a healthy infant.” Reproductive behaviour can
be regarded as the attitude people have towards reproduction. As the definition of
reproductive health highlights the importance of self-determination concerning sexual
intercourse and fertility regulation, reproductive behaviour can be considered as a subdivision
of reproductive health. Moreover, reproductive behaviour impacts reproductive health (see
section ‘Reproductive behaviour: morbidity & mortality’).
The outcome of the conference in Cairo was the ICPD Programme of Action focusing not
only on sexual and reproductive health but also interlinking population, environment, health,
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sustained economic growth, education and gender equity & equality. The 20-year Programme
of Action sets out a range of important objectives for the international community to
implement and conduct on a national level -taking into account the conditions in and
possibilities of each country. It should improve sexual and reproductive health with a
legislative and cultural-sensitive approach. The programme of action was an important call for
action and unique because of its holistic approach -interlinking population, economy, health,
education and the environment. There was an intergovernmental agreement that “All
countries should strive to make accessible through the primary health-care system,
reproductive health to all individuals of appropriate ages as soon as possible and no later than
the year 2015.” (1) Sexual and reproductive health is about reducing the adverse outcomes of
sexual activity and reproduction. Despite the international agreement to achieve universal
coverage of reproductive health by 2015, the burden of sexual and reproductive absence-ofhealth worldwide remains enormous.
The possible influences on reproductive behaviour are abundant: not only do reproductive
behaviour indicators interact with each other; there are also numerous influences from outside
the reproductive health domain. Parity, family size, ideal family size, child survival, birth
spacing, et cetera: all are positively correlated with the woman’s age, education or literacy,
marital status and age of marriage, social status and lifestyle. (3-5) Furthermore, maternal and
child mortality is related to residence (highest in rural areas) and economic status (highest
amongst the poor). (3,6) Governmental decisions can also impact reproductive health.
Economic atmosphere, environmental changes, social climate, culture and religion: all can
interlink with reproductive health and reproductive behaviour. (7-9) Extensive literature is
available on reproductive health of refugees, in case of natural or man-induced disasters and
even in situations of environmental degradation. (7,10)
Climate change Here follows a brief assessment of the phenomenon of climate change: the earth’s temperature
is a function of the incoming solar energy, the outward-bound reflected energy and the energy
retained by the greenhouse effect. The short-wavelength energy emitted by the sun is
transformed to long-wave radiation when it hits the cooler earth’s surface. Longwave energy
is reflected and is substantially absorbed by greenhouse gases. Greenhouse gases re-emit the
energy in all directions, warming the lower atmosphere and the surface of the earth. Primary
examples of greenhouse gases include CO2, CH4, N2O and even H2O (water vapour) is a
greenhouse gas. These gases occur naturally in the earth’s ecosphere and accordingly the
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greenhouse effect is in part a naturally occurring phenomenon. Nevertheless, human activities
interfere with the natural greenhouse effect and amplify it. About half of all carbon dioxide
(with the other half remaining in the atmosphere) is stored over millions of years in coal, oil,
gas, et cetera. Over the past two centuries, human interference has been releasing, in part, this
stored carbon, increasing the concentration of greenhouse gases in the atmosphere and thus
elevating the earth’s temperature. Furthermore climate feedbacks accelerate the global
warming; examples given are melting of the Arctic ice sheet (no more reflection of energy by
sea ice), ocean acidification (less absorption of CO2) and thawing of permafrost (release of
stored carbon). (11)
The accelerating effects of positive feedback loops can be receptive to critical thresholds,
better known as the irreversible ‘tipping points’ - whereby small changes in a global climate
system are able to bring a relatively stable system into a brittle state. (12)
Global warming will bring about detrimental changes in some of the planet’s environmental
patterns and ecosystems. As mentioned previously, oceans acidify, ice is melting and
consequently the sea level rises, but changes also include weather shifts. Droughts are
expected to get longer and more severe; precipitation is expected to decrease in areas closer to
the equator and to increase in higher latitudes (due to more moisture evaporation); more
tropical storms and extreme weather events are predicted (foregoing get their energy from
warm ocean water: since the top layer of the ocean is getting warmer, storms will grow
stronger, with more wind and heavier precipitation); et cetera. (13)
The topic of anthropogenic climate change emerged on the public agenda in the ‘80s. In 1988,
the Intergovernmental Panel on Climate Change (IPCC) was founded. The purpose of IPCC is
assessing the field of climate change from a scientific and intergovernmental perspective. In
this way, the IPCC provides clear scientific information as a fundament for policy making. In
1992, the United Nations Framework Convention on Climate Change (UNFCCC) defined
climate change as “a change of climate which is attributed directly or indirectly to human
activity that alters the composition of the global atmosphere and which is in addition to
natural climate variability observed over comparable time periods.” (14)The UNFCCC
stipulates the framework for intergovernmental efforts that should tackle the challenge posed
by climate change. (15)
The IPCC Fifth Assessment Report that was published in 2014 came with considerable
commotion. The New York Times noted the warnings not to be new, but the language to be
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all the more “urgent and direct”. (16) The report argues that further warming will continue if
emissions of greenhouse gases continue; that it is extremely likely that human influence has
been the dominant cause of observed warming since 1950, with the level of confidence having
increased since the fourth report; that warming of the atmosphere and ocean system is
unequivocal; that many of the associated impacts such as sea level change (among other
metrics) have occurred since 1950 at rates unprecedented in the historical record; et cetera.
(17)
Climate change is a fact and it should be noted that it will hit those most vulnerable and those
least responsible - due to geographic, demographic, governmental and economic
characteristics - the hardest. (18) Climate change was responsible for 5.5 million disability
adjusted life years (DALYs) lost in 2000, predominantly striking the African region (figure
2.).
Figure 3. DALY’s lost to climate change in 2000, per world region (19)
Climate change in Ethiopia Ethiopia, situated in Sub-Saharan Africa, covers an area of 1.1 million km². More than 80% of
Ethiopia’s proximately 96 million inhabitants live in rural areas. (20,21) Ethiopia is a
highland country, known as ‘the Roof of East Africa’. Almost one third of the country’s land
consists of arid, semi-arid, dry and sub-humid areas. These areas are particularly prone to
climate change and desertification.(22) Climate is changing and will notably impact
Ethiopia’s temperature and precipitation patterns. Today, Ethiopia struggles with a worsening
rainfall regime (reduced total rains which start later, end sooner, fall harder and -whilst falling
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in a more clearly defined period- have an increasingly variable date of onset) with resultant
increased exposure to severe frosts, with worsening drought conditions, losses of topsoil and
reductions in soil fertility. Furthermore, substantial warming across the entire country has
exacerbated the dryness. (23,24)
The Ethiopian economy is still largely dependent on rain-fed agriculture, yet agricultural
production is prone to climate change and hampered by erratic rainfall, population pressures,
constant erosion, lack of conservation and agricultural policies. In rural Ethiopia, land
allocation is based on an important demographic factor - the household size - with larger
households advantaging. Land in Ethiopia is state-owned and is redistributed occasionally to
enable newly-formed households to have access to farmland. Consequently, if the population
grows or the land degrades, land holdings diminish, which makes people even more
vulnerable. (25)
Concluding: land resources in northern Ethiopia are currently under increasing pressure both
due to population growth and due to land degradation.
Reproductive health: demography Fertility can, in part, be seen as a predictor of the future world. Modest changes in fertility
have large effects on population growth. (26) Fertility does not only outline the forthcoming
number of people living on earth, it also largely determines the age distribution (and the
dependency ratio1) and -if calculated per country- geographic distribution.
There are numerous population theories, two of them being most espoused: the Malthusian
and the Boserupian theory. Malthus claims that population growth is exponential, while
productivity grows arithmetically. Consequently, resources will restrict population growth and
-size through positive ‘checks’ (famine, war, etc. which leads to increasing mortality) and
through negative ‘checks’ (premature adaptation to the recourse limits e.g. through later
marriage or through family planning). In other words, finite resources place a restriction on
population growth. Malthus did not reckon technological innovations that can incline resource
limitations and allow larger population growth. The theory of Boserup argues that resources
accommodate population growth, as innovation is greatest when population pressure is
highest. In other words, when the population approaches the limits of the resources, people
increase resources through developing new technologies that improve yields. (27) The process
1
“Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age
population--those ages 15-64.” (71)
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of demographic change and response appears not only to be continuous but also reflexive and
behavioural. Reflexive therein that a change in one component is altered by its change of
other components and behavioural therein that demographic change is eventually decided
upon by humans, with varying goals and incentives. (25)
The process of demographic change largely follows a standard model; this is called the
demographic transition model. Large parts of Africa are in another phase of this model than
Europe. This is because the process of demographic transition is, in part, connected with the
transformation from an agricultural society (large parts of Africa, including Ethiopia were
agriculture accounts for over half of the country’s gross domestic product (28)) to an
industrial society (as in Europe and North America). Over the course of this transition, five
phases are passed. Almost all countries have passed phase one, characterized by high death
rates and high birth rates. The second phase involves a decline in death rates, followed by the
third phase with a decline in birth rates. It is in between these phases that natural population
growth escalates and it is here that developing countries can be situated. Developed countries
are in stage four or five, characterized by low mortality rates and (even) low(er) birth rates.
However, the demographic transitions in Africa started later and the population growth
momentum is still underway. Africa is assumed to be “on a slower trajectory towards
replacement fertility because of its lower level of socio-economic development”. (29)
Throughout the demographic transition, the decline in fertility occurs heedless of the
economic conditions or family planning provisions (although contraception is the main way to
control fertility and bring about the desired family size). The main cause of the reduction in
fertility is low mortality but contextual factors as education, family planning provisions and
economic growth account for the diverse times of onset, speed and duration of events that
exist between different regions and countries. (30)
The demographic field is influenced by a plenitude of factors. Much research has been carried
out concerning economic trends and demography, family influences on fertility and social
climate and demography, but a great deal stays indefinite. We now know, for example, that
economic growth is related with declining mortality and fertility and that natural or man-made
calamities result in higher stress-levels, higher levels of migration, increased mortality and
fluctuations in fertility. (25) However, not much previous research has been conducted on
demographic responses to long-term environmental degradation. Thus, this study will be
focussing on the latter.
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Reproductive behaviour: morbidity & mortality Indicators that can be used to identify reproductive behaviour comprise, among others, parity,
family size, number of children under five, fertility preferences, birth spacing, unmet need for
family planning, unwanted pregnancy and age at first pregnancy. All are associated with
maternal, perinatal, neonatal, infant and child health. There are many more possible indicators
for reproductive behaviour, but we will discuss the morbidity and mortality (of mothers and
children) of some outcomes that seem the most relevant for this thesis.
Parity and family size
The WHO fact sheet on maternal mortality states that, despite a 50% drop in maternal
mortality between 1990 and 2013, worldwide, still approximately 800 women die every day
from preventable pregnancy- and childbirth related causes (haemorrhages, infections, preeclampsia, unsafe abortions, etc.). 99% of these maternal deaths occur in a developing
country, with a mean maternal mortality ratio (MMRatio: number of maternal deaths per 100
000 live births) of 230 per 100 000 live births -versus 16 per 100 000 in developed countries.
(31) The risks associated with parity can be seen in the parity-specific MMRatios: these tend
to be raised at parity 1, lowered at 2-3 and then continue to rise from parity 4 onwards. Not
only is the risk of maternal mortality, but also of perinatal and neonatal mortality associated
with high parity. (31-33) The risk of post-neonatal death rises with parity and seems “to be
attributable to the increased risk of infection in larger families.” (5) Children from large
families are more likely to be disadvantaged in terms of nutrition, healthcare and education.
(34) Furthermore, parity and family size are strong predictors of female labour supply. (35,36)
Birth spacing There are multiple ways in which spacing can be of influence on reproductive health.
Interpregnancy intervals can be associated with adverse maternal health outcomes.
Interpregnancy intervals of more than five years are associated with an increased risk of preeclampsia and labour dystocia and short interpregnancy intervals are linked with increased
risks of uterine rupture in vaginal births after previous cesarean delivery and with
uteroplacental bleeding disorders. (37) In a meta-analysis, the conclusions were confirmed
that too short birth- or pregnancy intervals are associated with adverse pregnancy outcomes
and elevated infant and child mortality and that too long birth intervals contribute to adverse
pregnancy outcomes. (38-40) Children with short birth spacing intervals are at increased risk,
because of four main reasons: breastfeeding is interrupted by the demands of a subsequent
19
pregnancy, a mother’s reproductive and nutritional recourses may be depleted, competition is
greater among a woman’s children and infectious diseases can spread more easily among
siblings. (5) On the other hand, inter-pregnancy intervals longer than five years are also
associated with increased risk on adverse perinatal outcomes due to physiological regression
of the mother. (41) Trussell & Pebley found that “the overall potential effect of spacing all
births at least two years apart would be a reduction in infant mortality of 10 percent and in
mortality of children under five 21 percent.” Children born within two years of an elder
sibling are 60% more likely to die as an infant and children born within 2-3 years have a 10%
increased risk, both compared to those born after more than three years. (31,42) Further, birth
spacing has a beneficial effect on the academic achievement of older siblings. (43)
Unwanted pregnancy The prevalence of unwanted births rises with birth order and the prevalence of mistimed births
relates to the preceding birth interval. Sub-Saharan Africa trends toward decreasing fertility
preferences and rising premarital sex. (33) As fertility preferences decline, there is a larger timegap between the completion of desired family size and the end of a woman’s reproductive years,
which leads to an increased exposure to unwanted pregnancies (insufficiently retained by FP
services) (44) Since each pregnancy and childbirth implies a health risk for a woman, unwanted
pregnancies are inherently a health risk and its global burden of disease amounts to 4.6 million
disability-adjusted life years. (45) However, unwanted births do not carry the same risk as wanted
pregnancies. Because of less time and money invested in antenatal and natal care, unwanted births
pose a greater threat to a mother’s health. Children of parents, who perceived their pregnancy as
unwanted, had a twofold increased risk of dying in the first 28 days of life.
(33,46,47) Myhrman et al identified a positive relation between unwanted children and
successive lower educational success. (48) Furthermore, unwanted pregnancies often go hand in
hand with induced abortions. Nearly one-third of all women in Nigeria would have an unwanted
pregnancy at some point in their lives. Many of them - both disadvantaged as advantaged- decide
to terminate the pregnancy by abortion. Eventually, worldwide, slightly more than half of all
unplanned pregnancies would end in an abortion. (33,49) These abortions can be clandestine and
unsafe and thus damaging a woman’s health and survival - especially for rural, poor, young and
less-educated women. Furthermore, unsafe abortions impact a country’s health care system, e.g.
because health care workers need to be skilled for complications of abortion and specific medical
services need to be provided. The investments that need to be made in order to provide this care
are lost to the detriment of other medical care. (50)
20
Age at first pregnancy
In general, first births are associated with higher levels of maternal mortality. What’s more is that
the mother’s age of first birth matters for maternal, perinatal and infant mortality. Young age is
associated with increased risk of maternal mortality - due to increased risk of maternal anaemia at age 20-29 the maternal mortality rates are lowest only to increase again as maternal age
increases above 30. (31,33) Women older than 35 years have the highest maternal mortality ratios.
(51) At an older age, women are at higher risk of haemorrhage, pregnancy-induced hypertension
and uterine prolapse. Young maternal age at first birth is also associated with adverse pregnancy
outcomes -obstructed labour, pre-eclampsia and too small pelvises to accommodate birth- and
increased risk of preterm birth and low birth weight. However, it should be noted that the number
of births at extreme ages is relatively small compared with middle-aged women. In this way, the
middle-aged group stays the largest contributor to maternal deaths, despite higher mortality ratios
in the extreme age categories. (32,33,52) Furthermore, research has proven that teenage mothers
have, on the average, more children than other women. This positive correlation can be assigned
to a longer reproductive exposure (more years of reproductive life after the first birth).
Nevertheless, it is also possible that teenage mothers are preselected through the age at first birth:
women with a larger desire of children tend to have an earlier onset of family life and first birth.
Finally, because early first births have an influence on life choices (for example, foreclose
educational opportunities), fertility preferences can be altered due to early first birth. (53,54)
There are other indicators of reproductive health that do not have a direct impact on maternal or
child morbidity and mortality, but that are nevertheless important. A woman’s fertility preferences
and the access to family planning have the potential of influencing the above and consequently
can impose health problems indirectly.
Fertility preferences
There are several possibilities for the measurement of fertility preferences: ideal family size,
ideal number of children, desired number of children, et cetera. (55) The linkage of fertility
preferences with future fertility has been an important subject for discussion in the
demographic literature. Morgan examined this literature and concluded that “intentions may
be of some use for population forecasting” but cautions that “these estimates are of only
moderate value in making fertility forecasts”. Fertility preferences predominantly reflect
personal values and attitudes. (55,56)
21
Family planning (FP)
Family planning refers to the fulfilled request to voluntary and safely plan and control
pregnancies, through usage of contraceptives or other techniques. Family planning programmes
are an effective strategy in the reproductive health sector - because of its broad range of
advantageous effects. Yet family planning is a notorious concept in political circles -because of
the perpetual linkage with religious concerns. Nonetheless, the main objective of family planning
is no longer the restraint of population growth.
In developing countries, the main goal of FP services is reducing maternal and child morbidity
and mortality. (5,31) Evidence suggests family planning to be cost-effective and feasible in
reducing maternal pregnancy-related mortality particularly in rural areas with poor health
infrastructure. (57) By increasing contraceptive prevalence, high parity and advanced age births
are reduced, however the influence on maternal age at first birth appears to be controversial. (33)
Family planning ensures optimal pregnancy timing (mother’s age at pregnancy) and spacing
(specifically the period between first and last born children increases rather than interbirth
spacing), limits the overall number of pregnancies per woman, prevents unwanted pregnancies
and consequent high-risk abortions and decreases STD prevalence. In this manner, FP secures
maternal, perinatal, infant and child health. (31,33,34,58) On the household level it applies that if
women could control their fertility better, then their education level, skill acquisition and
subsequently future wages would rise. Moreover, families with fewer children can invest more in
each child and FP can have intergenerational effects on the health and nutrition of populations. On
a national level, FP programmes might help countries to speed up the demographic transition and
ameliorate the economic, environmental, social and political climate. (6,36)
Reproductive behaviour in Ethiopia Ethiopia is the second largest country in sub-Saharan Africa, with an estimated population of
95,933,000. The Ethiopian population is youthful: 43% are under 15 years old. Ethiopia has
an average annual population growth rate2 of 2.1% - urban 3.6% and rural 1.8% - and a total
fertility rate (TFR3) of 4.1. The total fertility rate (TFR) in Ethiopia declined from 7.0 in 1990
to 4.8 in 2011 -predominantly due to declining fertility in rural areas- according to the 2011
Ethiopian Demographic and Health Survey. For comparison: in Eastern African and SubSaharan countries, the average TFR in 2011 was 5.1. Olsen argues four factors to be primarily
responsible for Ethiopia’s success in reducing fertility rates: “political will, generous donor
2
3
Rate of natural increase is the birth rate minus the death rate, expressed as a percent. Worldwide: 1.2%.
Average number of children ever born to a woman, at the end of her reproductive life. Worldwide: 2.5.
22
support, nongovernmental and public-private partnerships, and the Health Extension
Program”. (21,59)
The MMratio in Ethiopia is 420 women per 100,000 live births and the infant mortality rate4
is 50. The lifetime risk of maternal death5 is 1 on 67. The contraceptive use among married
women, aged 15-49 is 1.4% (worldwide: 0.8%), 6% of all births are attended by skilled health
personnel (worldwide: 67%) and 1.4% of all Ethiopians, aged 15-49, live with HIV/AIDS
(worldwide: 0.8%). (21)
General factors that influence reproductive behaviour and reproductive health in Ethiopia are
poverty, the age distribution and the various cultures and religions. Poverty is common in
Africa, pushing a lot of girls into prostitution or accepting help from ‘sugar daddies’6. High
risk reproductive behaviour is predominantly displayed by adolescents, a population group
with high numbers in Ethiopia. Younger adults are more likely to take part in unsafe sexual
practices and are more vulnerable to pregnancy and sexual transmitted diseases (the STD
prevalence in Ethiopia is among the highest in Africa, rising up to 86%). Furthermore, the
Islam and the Orthodox Church prohibit abortions, female genital mutilation is still a common
(cultural) practice, polygamy and extramarital sexual activities occur, et cetera. These all
largely impact reproductive behaviour and reproductive health. (60)
Connecting reproductive health & climate change The relationship between reproductive behaviour and climate change is bidirectional and can
be investigated in either direction. Attention has been drawn to the effects of demographic
changes (in particular population growth) on climate change. Reducing population growth
rates will not mitigate resource degradation, but slow growth rates and smaller population
sizes do benefit most environmental problems. (18) However, we should not omit the effects
of climate change on reproductive behaviour. For this reason, this study will regard the matter
in the other direction by assessing the impact of climatic variability and climate change on
reproductive behaviour.
The impacts of climate change on reproductive behaviour are typically conceptualized in
terms of vulnerability. Vulnerability is highly dynamic and can be seen as a function of three
4
Infant deaths per 1,000 live births. Worldwide: 38.
The probability that a 15 year old woman will eventually die from causes related to pregnancy or childbirth,
measured by combining the probability of becoming pregnant and the risk of death from each pregnancy.
Worldwide: one in 180.
6
Older financially secure men (’sugar daddies’), with whom girls are forced to initiate a sexual relationship, in
exchange for gifts, emotion or financial support.
5
23
general conditions: the nature of the biophysical exposure (in case of Ethiopia: mainly
droughts), a population’s sensitivity (in the event of drought: especially agricultural
communities appear to be sensitive) and the coping and adaptation capacity of the population
(through changing of practices, technology, etc.). (2)
The nature of the biophysical changes and the consequent exposure on humans in Ethiopia
was highlighted in the section ‘Climate change in Ethiopia’. To gain insight in the sensitivity
of the Ethiopian population, we begin with elucidating the perception of Ethiopians on
environmental degradation. The core coping and adaptation strategy on environmental
degradation is migration. We will set forth this core response, but since this study will not
focus on this response, other adaptation strategies will also be regarded: marriage, fertility and
fertility preferences. Lastly, family planning -as a tool for the latter adaption strategies- will
be considered.
Perception
Awareness about ecological degradation (and linkage to population) can be seen at two levels
-public and governmental. Governmental awareness is demonstrated in the Ethiopian NAPA,
which states rapid population growth to be “a cause of decline in resources base”.
Consequently, slowing population growth or investments in reproductive health/family
planning are considered among the country’s priority adaptation actions. On the other hand,
public awareness about environmental degradation is more precarious to measure. The
linkage between severity of resource degradation and the public awareness of this severity can
be demonstrated by differences in reproductive behaviour: lower ideal number of children,
lower average parity rates, lower desired number of children, lower current fertility and higher
practice of family planning. Additionally, people in land-scarce areas are found to be more
aware about the imbalance between population & resources and peasants are not only aware
of deterioration but also about the causes of deterioration. (25,61)
Migration
In light of climate change, research is centred on migration. Ratifying this focus point, we
refer to the United Nations Population Fund (UNFPA) agenda. The UNFPA agenda says that
it is generally agreed that “the greatest single impact of climate change (through severe
coastal weather events, shoreline erosion, coastal flooding and agricultural disruption) might
be on human migration”. (18)
24
During years following drought there appear to have been a substantial emigration of men and
a displacement of population towards the centres. (62) Research on demographic changes
associated with food shortages concludes that migration is the principal individual-level
strategy for coping with drought in the Sahel. (63) Ezra set up a study in the ‘90s to address
the short- and long-term demographic consequences of ecological degradation and food
supply instability in Ethiopia. This study also found migration as the most remarkable and
immediate response to famine crisis: 23% of the household movements were due to factors
related to ecological degradation. Because of recurrence of droughts and famines, internal
migration has always been historically significant in Ethiopia. Movement of people from
drought-prone and ecologically degraded areas (in the northern regions) to the fertile areas (in
the west and south-western regions) is regarded as a necessary aspect of Ethiopia’s economic
and social development. (25)
For the drought-prone areas, conditions of food insecurity are likely to become part of the
everyday lives of the residents. Under ecological stress and land-resource degradation, the
immediate response one expects from farming households is seasonal labour migration and
involvement in off-farm employment activities. Seasonal migration is becoming more and
more hampered due to regionalisation policies, wars, et cetera. Albeit, creating autonomous
regional states has accelerated the growth of regional towns, offering a substitute for
agricultural employment. (25) Also, migration to other rural areas is regarded as more
challenging because of a widespread lack of arable or grazing land due to deforestation,
erosion and other environmental degradation, and population pressures. (64) Thus, it seems
that the rural Ethiopian population will have to address alternatives in their spectrum of
adaptive
potential
to
adjust
to
future
environmental
conditions.
The pitfall is to focus on migration while adaptation opportunities are legio. That is why the
UNFPA agenda concludes with the consideration that -since climate change is part of a larger
web of issues involving interactions between development, population and environmentdecision-making aimed at integrated mitigation and adaptation efforts should situated within
this broader picture. (18)
Marriage Ezra noticed attitudinal changes on the timing of marriages, with postponement during
periods of droughts and famine. Also, a strong positive association between the level of
harvest and the number of marriages in the given community was found. All were more
significant in poorer households. Nevertheless, even among the so-called wealthier
25
households, ecological stress has gradually made postponement of marriages acceptable (for
both sexes). (25)
Fertility
Changes in fertility can be an alternative adaptation strategies, with family planning as its
tool. Demographic change can be an adaptation process but meanwhile it can also exert a
strong influence on the adaptive capacity: excessive population growth can put major pressure
on existing ecosystems and consequently contribute to environmental degradation. (2,61)
In the literature, there is no consensus on fertility effects upon events as storms, wars,
droughts, famines, et cetera. Low level storms can effectuate a rise in fertility, while high
level storms are indefinite in their effect on fertility. Pregnancies can be postponed during an
event that places stress on people, with catching up afterwards. But fertility can also decrease
in the years following drought. Furthermore, fertility can also be linked to migration.
Migration directly reduced fertility through the separation of husbands and wives and
indirectly causes diminished survival likelihood of children. However, fertility can also
increase as a reaction to stressors. The idea is that children mitigate the adverse outcomes of
floods, wars and other by preserving family property rights, by compensating future disability
of parents and by diversifying income sources. This is called the ‘risk-insurance hypothesis’.
(62,63,65-67)
Partially due to the introduction of family planning, families with fewer children are
considered to be “better positioned to deal with current challenges, including
environmentally-related difficulties”. Family planning is mentioned as a component of
adaptation strategies that would boost resilience. (64)
Fertility preferences
The ideal number of children, one of the indicators of behavioural change, appears to be lower
in regions where land is scarce than in regions with less environmental degradation. The
desired number of children is a more practical indicator that confirms the tendency mentioned
above. Women in more severe environmental degraded areas show lesser preferences for
additional children. Moreover, despite the traditional cultural norms and values, 34% of all
women in Ezra’s study replied not wanting to have (additional) children. However, the ‘riskinsurance hypothesis’ can also be reflected on the fertility preferences, with people affected
by stressors reacting by wanting more children. (25,65,66) 26
Tool: Family planning
The past two decades, Ethiopia has managed to strengthen its family planning policy: the
contraceptive prevalence rate (CRP) has increased by a factor nine from 1990 to 2011.
However, in 2014 24% of all Ethiopian women still express to have an unmet need for family
planning. Because Ethiopia is projected to be the world’s tenth most populous country by
2050, Ethiopia set an ambitious CRP rate of 66% by 2015. In 2014, this CRP rate amounts to
34%. (59,68)
Accordingly, the National Regional State Programmes of Plan on Adaptation to Climate
Change (Afar, Dire Dawa, Gambella and other) acknowledge that continuous education and
awareness raising campaigns -concerning the importance of limited family size and family
economics- as well as the provision of reproductive health services need to be essential
components of such intervention, in order to allay the impacts of population pressure and
unsustainable resource uses. (69)
As can be noticed above, there has been much research on migration as an adaptive response
to environmental degradation, while other possible adaptations strategies have been
neglected. Therefore, this study will focus on noticeable differences in reproductive behaviour
as
a
reaction
to
environmental
stress.
27
Hypothesis & Methodology Objectives The study will try to investigate the responses in terms of reproductive behaviour to
persisting and progressive ecological degradation associated with climate change.
Specifically, it attempts to measure the changes in reproductive behaviour that have taken
place from 2000-2011 and interpret them in the context of the vulnerability to desertification
of the Ethiopian population. The hypothesis, based on previous research and a thorough
review of existing literature, is that desertification (considered as a proxy for ecological
degradation stemming from human-induced climate change) causes changes in demographic
behaviour and attitude. Specifically, since the Ethiopian population proves to be aware of
environmental degradation, the literature suggests Ethiopians will respond in following ways:
migration to fertile lands or urban areas, declining fertility rates, increasing demand for family
planning, postponement of marriages and lower fertility preferences. However, due to limited
data availability, this study will only take into account: 1) reproductive history (specifically:
early age at first birth); 2) total number of children ever born (as a parameter for fertility); 3)
content on current reproductive status (wantedness of current pregnancy and children); 4)
fertility preferences and 5) coverage of family planning (as a tool for reproductive behaviour).
The major objectives of the study are following:
•
examine if there are differences in reproductive behaviour between residents of non to
low desertification vulnerable areas and high to very high desertification vulnerable
areas;
•
determine if identified differences evolve over the three sampling years and thus
prelude transitions;
•
explore the interactions of desertification with other factors that influence reproductive
behaviour.
The secondary objective is to:
•
determine significant confounders for the above potential relationships.
28
As mentioned in the literature study, reproductive health is influenced by a great deal of
factors. Therefore, in the analysis, correction for these factors will be needed. According to
availability in the dataset, following determinants will be controlled for: 1) age (in five year
cohorts); 2) total children ever born to a woman; 3) residential status (urban or rural); 4)
region of residence and 5) sampling year (2000, 2005 or 2011).
Materials Environmental indicators In order to detect a possible link between human behaviour in terms of fertility and climate
changes, we mainly use the indicator of ‘vulnerability to desertification’.
Global desertification vulnerability (figure 2.) (70)
The global map for desertification vulnerability can be found (open source) on the website of
the United States Department of Agriculture - Natural Recourses Conservation Service. It has
been produced in 1998 and the database is managed by Reich, geographer at the governmental
USDA centre. The map data is rasterized on a 2 minute grid cell (roughly two kilometres)
with a minimum scale of 1:5,000,000. It displays four vulnerability classes, based on soil
climate and soil classification.
In substance, the desertification vulnerability map is based on a reclassification of the global
soil climate map (or global biomes map, based on a combination of soil moisture regimes and
soil temperature regimes) and the global soil map (which shows the distribution of the twelve
soil orders according to soil taxonomy).
Figure 3. Global map of vulnerability to desertification (70)
29
Data on reproductive behaviour (72)
The Integrated Demographic and Health Series (IDHS) datasets are based upon the
Demographic Health Surveys (DHS). DHS are the main source of information on health in the
developing world. The data of DHS arises from nationally-representative health surveys
carried out in low resource countries since the 1980s until present, funded by the U.S. Agency
for International Development (USAID). The Integrated DHS project depends upon
collaborations between the Minnesota Population Center (MPC), ICF International (which
manages the survey process in partnership with host countries), USAID (which funds the data
collection) and national agencies of participating countries. It is funded by the National
Institute of Child Health and Human Development (NICHD). IDHS is modelled, in part, on
the Integrated Public Use Microdata Series (IPUMS) projects - containing samples of census
data from around the world- created at the Minnesota Population Center. IDHS facilitates
analysis of DHS data across time and space because of its consistent coding over time and
over countries, but also through the costless availability of web-based variable-specific search
and selection tools across surveys -enabling researchers to create customized datasets.
We use the available IDHS datasets of Ethiopia -available for 2000, 2005 and 2011- which
include women aged 15-49 years old. Accordingly, all data should be treated as characteristics
of the woman with possibly more than one woman per household included in a sample and
only households with women of childbearing age included. Since this study involves
reviewing human behaviour in terms of fertility, women of childbearing age are exactly the
30
study population required for this research. To protect the confidentiality, names and lowlevel geographic information of the respondents are not included. A case is identified through
the variable ‘CASEID’, which is constructed by concatenating the sample point or cluster
number, the household number and the respondent’s line number. However, since the
finalized dataset in this research comprises multiple years, the year of sample also has to be
taken into account to uniquely identify a case.
Global positioning system (GPS) data for the 2000, 2005 and 2011 Ethiopian census was
obtained via the DHS website. This data will be used to link the environmental indicators to
the demographic datasets. As previously mentioned, a dataset was obtained from the IDHS
website, which included 31 variables for all three Ethiopian samples (2000, 2005 and 2011).
Since not all variables are used, we refer to annex 1 for a complete overview of the variables.
After obtaining this dataset, four variables (available in the ‘births sample’ on the DHS
website) were added to the sample, these comprise: total number of sons who have died
(V206), total number of daughters who have died (V207), age of mother at first birth giving
(V212) and wantedness of current pregnancy (V225). Linkage to the IDHS dataset was based
on the CaseID. In this way, foregoing information was specified for every case of the IDHS
dataset.
Methods Environmental indicator For the geographical assessment of this study, QuantumGIS® 2.6.1 -an open source
geographic
information
system-
for
Windows®
is
used.
Global desertification vulnerability
The high quality bitmap of desertification vulnerability was added to QGIS as a raster layer.
Consequently, the map was georeferenced in the same spatial reference system (WGS84) as
the DHS GPS shapefiles of Ethiopia (2000, 2005, 2011), which were used as vector layers.
Each of these three vector layers were attributed a new variable ‘desert’ and the DHS
sampling units were selected by hand and assessed in accordance with the raster layer colour
codes.
In SPSS, the new variable ‘desert’ [1;5] was merged with the datasets (2000, 2005 and 2011)
that comprise the markers indicative for reproductive behaviour.
31
Merging and recoding the environmental variable
For each sample-year, we now have one dataset with both variables ‘desertification’. These
three datasets were merged. In this way, we obtained our definite dataset, comprising all three
sample years and both environmental variables. Consequently, both environmental variables
were recoded into dichotomous variables. The new variables differentiated between non to
mild climate change -assigned value 1 (values 1 and 2 for the desertification variable) and
high to very high affected areas -coded 2 (value 4 and 5 for desertification). Moderate struck
areas (valued 3 for desertification) and missings were ruled out. In this stadium, a control of
the dataset was conducted by checking the accordance of the number of cases per year in the
merged dataset with the number of cases in each three original IDHS-dataset (2000, 2005 and
2011). Data cleaning and recoding of reproductive behaviour variables
DHS data are processed with the general rule that missing values -coded 9, 99, 999, etc.- will
be assigned to questions were no answer can be made up. Significant exceptions include
geographic variables and variables related to the woman’s birth history. For these variables,
missing values are not accepted and will be pursued. Inconsistency is coded 7, 97, 997, etc.
and codes 8, 98, 998, etc. are used for ‘unknown’. Not in universe in IDHS means
‘inapplicable’.
Furthermore,
some
variables
needed
to
be
computed
or
recoded.
A cohort variable ‘YOB’ was computed by subtracting the age from the year of sample.
Subsequently, this variable was recoded to a five year cohort variable (1951-1955 into ‘9’,
1956-1960 into ‘8’, etc., until 1991-1996 into ‘1’). From the variables ‘sons who have died’
and ‘daughters who have died’, the ‘children who have died’ was computed. The variable
‘age of respondent at first birth’ was recoded into two variables: ‘first birth under 16’ and
‘first birth under 20’. A variable that comprised the number of unwanted children was
computed by subtracting ‘ideal kid’ (but only if numeric values were reported) and ‘children
who have died’ from the ‘total children ever born’. In this way, we obtained a continuous
variable, with positive values in case of more unwanted children per woman. The negative
values (in case of ‘more wanted children’) were excluded. The ideal number of children was
recoded into a dichotomous variable with an ideal of less than five children recoded into zero
and
an
ideal
of
five
children
of
more
recoded
into
one.
Similarly, the variable for ‘desire for children’ was recoded. If a woman doesn’t want children
anymore, she is coded zero, if she does want more children, she is coded one.
32
The variable for wantedness of pregnancy was recoded into a dichotomous variable: zero is
now current pregnancy unwanted and one is now current pregnancy wanted.
Finally, a dichotomous variable was recoded from the variable ‘unmet need for family
planning’, with zero in case of failure or unmet need and one in case of met need.
Ultimately the finalized dataset is obtained and ready for statistics, comprising a total of 44
variables. The table listed in annex 2 shows the five categorical variables that will be used,
with their corresponded coding. The grey coloured variables in annex 1 list all the variables
that were used for the analysis
Descriptive statistics
Simple descriptive analysis is conducted -using the ‘Descriptive statistic’ commands in SPSSto explore the sample: important general trends will be given, as well as evolutions over time. Analytical statistics
For the analysis of the sample, a sample plan was designed in order to take into account that
clusters of households can have confounding effects on the analysis. For example, households
in the same village are more likely to have similar outcomes, as well as they are more likely to
have similar influencing factors. By making and implementing a sample plan, based on the
primary
sampling
units,
we
tried
to
correct
for
this
distortion.
All of the following analyses will use the SPSS complex sample analysis: for continuous
variables and for categorical variables respectively the general linear model and the logistic
regression will be adopted. Pseudo R square tests will be used as goodness-of-fit
measurements.
To begin with, for every dependent variable, a univariate analysis was performed in function
of the desertification vulnerability, to see if desertification in se had an influence on the
dependent variable. Afterwards, the dependent variable was inserted into a model, correcting
for confounding factors (namely: urban-rural status, Ethiopian region of residence, cohort age
(in five year categories), total children ever born and sample year). In this way, the impact of
desertification in a more realistic setting could be assessed. Finally, by inserting the dependent
variable in a model that includes second grade interactions with desertification (specifically
‘desertification with urban-rural status’, ‘desertification with cohort age’ and ‘desertification
with year of sample’), modifiers could be identified. 33
Descriptive statistics The finalized dataset has a total of 45,952 cases: 15,367 for 2000, 14,070 for 2005 and 16,515
for 2011. The dataset is made up of women, aged 15 to 49. The mean age in the dataset is
27.9, for the distribution: see graph 1. Graph 1. Distribution of age (in five year groups)
Of all women in the sample, 96.8% are usual residents of the household unit. Three out of ten
women in the sample live in an urban area and seven out of ten in a rural area. Withal three
out of ten of the 15-19 year old women live in an urban area compared to two out of ten 45-49
year old women, with a declining trend of urban women over age. Over the period 2000 to
2011, the number of women living in an urban environment, has risen from 29.6% to 32.3%.
34
Table 2. Distribution of the dichotomous dependent variables
In table 2, the distributions of the dichotomous variables in the sample are shown. One in
three women reported having no children (yet), while one in ten reported having one child
with a downward percentage of women having more children towards two women in the
sample reported having 18 children (see graph 3). Four out of ten women have no dead
children (see graph 4) and one woman out of ten has at least one unwanted child.
Graph 3. Total children ever born per woman
Graph 4. Total children ever died per woman
Data on desertification vulnerability was available for 38,014 observations, yielding 7938
missings. The distribution of desertification in the population as well as per region is
displayed, respectively in graph 5 and in graph 6. The graph that shows the regions in
35
function of desertification, confirms the literature: desertification occurs in specific regions
(specifically Tigray, Affar and Dire Dawa). (24,25)
Graph 5. Distribution of desertification in the sample population
Graph 6. Distribution of desertification per region
36
Analytical statistics Confounding factors For all analyses, the confounding factors that were used include: 1) urban-rural status; 2) year
of sample; 3) total children ever born; 4) year of birth of woman. In every analysis, the
confounders are significantly (P<0.05) related to the dependent variable, except for: the
urban-rural status for the dependent variable ‘first child under 20’ and the year of birth for the
dependent variable ‘unwanted children’. The results of the confounding factors will be
discussed below, for the tables we refer to the further sections.
Urban-­rural status
Women (of equal parity, age and sample year) living in rural areas are less likely to
•
have had their first child under 16 than women living in urban areas (P=0.000, OR
1.270);
•
have more unwanted children (P=0.000, estimate 0.115) than women in urban areas.
Women (of equal parity, age and sample year) living in rural areas are more likely to
•
have more children than women residing in urban areas (P=0.000, estimate -1.782);
•
want their pregnancy than in urban areas (P=0.039, OR -0.288);
•
have a higher ideal number of children than women in urban areas (P=0.000, OR
0.267);
•
have dead children than women in urban areas (P=0.000, estimate -0.097);
•
have an unmet need concerning family planning (P=0.000, OR 7.097) than women in
urban areas;
•
want any more children compared to women in urban areas (P=0.000, OR 0.657).
Year of sample
In 2011, women (of equal parity, age and urban-rural status) had a lower probability of:
•
having given their first birth under 16 than in 2000 and 2005 (P=0.000; OR 2000:
1.638 & OR 2005: 1.616);
•
having given their first births under 20 than women interviewed in 2000 and 2005
(P=0.000, OR 2000: 2.695 & OR 2005: 1.822);
•
having more dead children than women in 2000 (P=0.000, estimate 2000: 0.226);
37
•
not wanting their pregnancy than women in 2000 and 2005 (resp. P=0.000 and
P=0.001, resp. OR -0.988 and OR -0.462);
•
wanting more children than women interviewed in 2000 and 2005 (P=0.000, OR
respectively 2.224 & 1.135).
In 2011, women (of equal parity, age and urban-rural status) had a higher probability of:
•
having less total children ever born than in 2005 and in 2000 (respectively P=0.018,
estimate 0.105 an P=0.034, estimate 0.098);
•
having a met need for FP than in 2000 and in 2005 (P=0.000, OR respectively 0.443
and 0.176).
Total children ever born
Women (of equal urban-rural status, age and sample year) with a higher number of children
ever born are less likely to:
•
have wanted pregnancies (P=0.000, OR increases 0.150 per child);
•
have a lower ideal number of children (P=0.000, OR increases 1.254 per birth)
•
have a met need for family planning (P=0.000, OR 0.866).
Women (of equal urban-rural status, age and sample year) with a higher number of children
ever born are more likely to:
•
have had their first child under 16 (P=0.000, OR increases 1.538 per child);
•
have had their first child under 20 (P=0.000, OR increases 1.998 per child);
•
have more dead children (P=0.000, OR increases 1.538 per child);
•
have more unwanted children (significant, estimate increases 0.200 per child);
•
want no more children (P=0.000, OR increases 0.787 per birth).
Cohort year (age of mother in five year groups)
Older women (of equal urban-rural status, parity and sample year) are less probable to:
•
have had her first child under 20 than a younger woman (P=0.000, OR 0.640);
•
have had their first child under 16 (P=0.000, OR 0.730) compared to younger women;
•
have an unmet needs for FP compared to younger women (P=0.000, OR increases
1.178 per 5 year age category).
Older women (of equal urban-rural status, parity and sample year) are more probable to:
38
•
want their current pregnancy (P=0.025, OR 0.107) compared to younger women;
•
not want any more children than younger women (P=0.000, OR increases 0.721 per 5
year category);
•
have a higher ideal number of children than younger women with the same amount of
children ever born (P=0.003, OR increases 1.038 per 5 year age cohort of women).
Reproductive history First child under 16 Desertification has no significant relation to having a first child under the age of 16, after
correcting for confounding factors. A significant interaction effect between desertification and
year of birth (cohort year in 5 year categories) is found. This means that the effect of
desertification is different depending on the age of the mother: for younger mothers (but with
same parity, same urban-rural status, same sample year and same children ever born), the
effect of desertification increased the probability of having had their first child before 16,
while the opposite is true among older women (P=0.000, OR increases 1.124 per five year age
category).
39
First child under 20 Desertification has no significant relation to having a first child under the age of 16, after
correcting for confounding factors. Again, a significant interaction effect between
desertification and cohort year is found. Namely, the effect of desertification is dependent on
a women’s age. Desertification increases the probability of a young mother (with same parity,
same urban-rural status, same sample year and same children ever born) of having had their
first child under the age of 20, contrary to older women who’s probability is decreased by
desertification (P=0.000, OR increases 1.163 per age category).
Current reproductive status Total children ever born 40
After correction for confounders, desertification has a significant effect on the total children
ever born (P=0.000, OR 1.494). A significant interaction effect between desertification and
the urban-rural status is found. The probability for urban women of the same sample year to
have less children, is increased in non-desertificated areas compared to desertificated areas
(P=0.048, estimate -0.232).
Number of dead children per woman
Desertification does not have a significant effect on the children who have died per woman
after correction for confounders. Desertification and urban-rural status are significantly
related for the number of dead children. For urban women of the same parity, interviewed in
the same sampling year and of the same age, living in non desertificated areas decreases the
probability of having more dead children than in desertificated areas (P=0.000, estimate 0.182).
41
Unwanted children
Women in non-desertification-vulnerable areas are more likely to have more unwanted
children, even when correction for confounders is conducted (P=0.000, estimate 0.185).
Nevertheless, the design effect of this model argues that there is a lot of heterogeneity in the
model (design effect 2.709). When placing desertification in an interaction model, the
interaction of desertification with cohort year appears to have a significant relation to
unwanted children. While young women - of the same parity, urban-rural status and sample
year - are more probable of having more unwanted children in desertificated areas than in
non-desertificated areas, the opposite is true for old women (P=0.000, estimate 0.114).
Current pregnancy wanted
42
Of all women who were pregnant at the time of the research, pregnant women in nondesertification-vulnerable areas are less likely to want their current pregnancy than women in
vulnerable areas, even after correcting for confounders (P=0.000, OR 0.373).
Fertility preferences Ideal number of children The ideal number of children (considered by women) is more likely to be higher in
desertificated areas, this stays significant after correcting for confounders (P=0.000, OR
0.410).
43
Desire for more children
In areas with low vulnerability to desertification, women have a higher probability of not
wanting any more children than in desertification-prone areas, even after correcting for
confounders (P=0.000, OR 0.499). The interaction between desertification and urban-rural
status is significant, meaning that urban women (of same parity, same age, same sample year
and same children ever born) in non-desertification vulnerable areas are more likely to want
more children than urban women in desertificated areas (P=0.001, OR 1.598).
44
Coverage Unmet need for family planning The interaction between desertification and year of sample is found significant. For women
(with same parity, same urban-rural status, same age and same children ever born) that were
interviewed in 2000 and 2005, desertification increased the likelihood of met needs (resp.
P=0.002 and P=0.011, OR respectively 0.477 & 0.564). Furthermore, the interaction between
desertification and urban-rural status is significant, meaning that urban women (with same
parity, same age, same sample year and same children ever born) in non-desertification
vulnerable areas were more likely to have met needs for FP than urban women in
desertificated areas.
45
Discussion Previous research showed that populations can respond to hazards by altering their
reproductive behaviour. However, apart from agreement on migration being an adaptation
strategy, there are inconsistencies and shortages on reportage of reproductive behavioural
changes as a reaction to environmental degradation.
This study tried to explore the influence of the advancing desertification in Ethiopia on human
reproductive behaviour by comparing desertificated areas with undisturbed areas over an
eleven year period. Reproductive behaviour was regarded from a woman’s perspective, in
terms of reproductive history (age of first child), current reproductive status (total children
ever born, died children and wantedness of current pregnancy), fertility preferences (ideal and
desired children) and coverage (family planning need).
The hypothesis was that ecological degradation stemming from desertification brings about
changes in reproductive behaviour and attitude. Accordingly, the objectives of the study were
exploring differences in reproductive behaviour between residents of non to low
desertification vulnerable areas and high to very high desertification vulnerable areas,
examining if the differences evolve over the sampling years, exploring the interactions of
desertification with other factors that influence reproductive behaviour and determining
significant confounders for the above potential relationships.
Determining significant confounding factors For the nine variables that were adopted to measure the reproductive history, -status and preferences and to measure the FP-coverage, all five confounding variables that were included
have proven to be significant in the confounder models. This can be attributed to the careful
selection with which these confounding factors had been chosen: selection was based on the
literature as well as on common sense. Specifically, available confounders that were used in
this study were: the urban-rural status, the total number of children ever born to a woman, the
cohort group to which a woman belonged and the year of interview. Since all confounders
that were used appeared to be significant for every outcome variable, we won’t mention them
46
any further in the discussion. This study was not able to control for all potential confounding
factors, but this will be scrutinized later in the discussion.
Urban women
This study points out that women living in cities, compared to rural women, are more likely to
have lower fertility preferences (lower ideal number of children and lower desire for more
children). Furthermore, actual reproductive behaviour seems to confirm these lower
preferences: urban women are more likely to have fewer children, have more unwanted
children and more unwanted current pregnancies. The repercussion of the facilities
(employment, health services, education, etc.) that a city offers and of a city its unique
socioeconomic setting on the latter cannot be denied. The literature confirms this important
determinant of reproductive behaviour. (3-6)
Children ever born to a woman The linkage of fertility preferences with future fertility is an important subject for discussion
in the demographic literature. This study acknowledges a linkage: women with fewer children
are more likely to have a lower ideal number of children and have more unwanted
pregnancies. (55,56) Logically, these women are more probable to have a met need for FP.
This study confirmed the literature in terms of teenage pregnancy and higher fertility
outcomes on the point that women who had a teenage pregnancy have a higher probability to
have more children at the end of their reproductive life: women with a higher number of
children were more likely to have had their first child under 16 year or under 20 year. (53,54)
Lastly, one can see the logic in the relation between total children ever born and number of
dead children: the more children, the more risk of having dead children. The same applies for
unwanted children: the more children, the more risk of having unwanted children.
Cohort This study noticed a trend of younger mothers reporting more first births under 16 or 20 years
old: this could mean an actual transition in reproductive behaviour or it could be assigned to
recall bias. Older women appear to have lower fertility desires (which seems logic since their
fertility preferences are more likely to be fulfilled by then) but higher fertility preferences.
The latter could, in concordance with the literature, indicate a fertility transition towards
lower fertility rates. (29) The finding that younger women are less probable to want their
current pregnancy could support this possibility. Moreover, this study found that unmet needs
47
for FP are higher for younger women. This could also explain why younger women are less
likely to want their current pregnancy.
Sample year
Because this study wanted to explore trends over time, the year of sample was assessed as a
confounding factor. All dependent variables showed a (linear) trend over the three sampling
years, except for the number of unwanted children. The large decline from the year 2000 to
2011 in unmet need for family planning can be assigned to the effort put into family planning
policies and services over the last 15 years. (59) Consequently, in 2011 women were more
likely to want their current pregnancy. The increase in family planning services could also
explain the decline in teenage pregnancies that is noticed in this study. Concordant with the
literature, fertility preferences and current fertility appear to be declining, precluding a
fertility transition. (25,29)
Differences in reproductive behaviour in variously vulnerable areas The differences in reproductive behavioural indicators between variously vulnerable areas
that this study was able to demonstrate, relate to following variables: ideal number of
children, desire for more children, current pregnancy wanted, unwanted children and total
number of children.
Of all women who were pregnant at the time of the research, pregnant women in nondesertification-vulnerable areas were less likely to want their current pregnancy than women
in vulnerable areas. The latter can be considered in the context of the higher fertility
preferences that are noticed in desertificated areas: the ideal number of children is more likely
to be higher and the desire for children is more probable to be stronger in areas that are
vulnerable to desertification, while in non-prone areas, the number of unwanted children is
more likely to be higher. Not only preferences and opinions on children differ considerably,
the behaviour between differently affected areas also differs. Desertification seems to increase
the number of children a woman has. The literature on the effects of calamities and
environmental degradation on reproductive behaviour are contradictory: fertility preferences
appear to be lower in regions with more land degradation. (25) However as a response to
calamities, one can observe fluctuations in fertility; droughts can lead to decreases in fertility;
wars, floods or other stressors can lead to increased fertility. The results in this study can be
explained within the theory of ‘risk-insurance’: children are thought to mitigate the adverse
48
outcomes calamities by preserving family property rights, by compensating future disability
of parents and by diversifying income sources. If women in desertificated areas have this
mind-set, it could explain the higher fertility preferences and the resultant higher fertility
outcomes noticeable in more desertification-vulnerable areas. (62,63,65-67)
Evolution of differences over time This study finds only one variable with a time trend that interacts with desertification
vulnerability: the unmet need for family planning. The rise in met needs for family planning
appeared to unfold faster over the years in areas that are not prone to desertification. This
could indicate that family planning services were set up to a larger extent in nondesertification vulnerable areas than in areas at risk. However, no such evidence was found in
the literature or on the internet. Accordingly, after careful examination of the Ethiopian policy
and implementation of family planning, we cannot prove that family planning services were
not set up uniformly throughout the whole country. (59) Another hypothesis - that could be
confirmed when considering all the latter findings - is that the need for family planning has
not increased equally in areas vulnerable to desertification compared to non-vulnerable areas.
Women in desertificated areas could have a lower demand for family planning, due to their
‘risk-insurance’ reproductive behaviour, while the ongoing demographic transition increases
the need in non-desertificated areas. (29,65,66)
Interactions of desertification with other reproductive health influencing-­factors For both the variable of ‘first child under 16’ as for ‘first child under 20’, the same outcomes
were found. The likelihood of a young woman having had her first child below the age of 16
or below 20 was found to be increased by desertification. Contrastingly, for older women the
effect of desertification decreased the chance of having had her first child below 16 or 20. It
cannot be deduced in this study why this is the case.
The urban-rural gap for the desire for children is larger in desertificated areas, with the desire
for children of women desertificated cities resembling the women’s desire in nondesertificated cities. This can be explained through the ‘isle’-effect cities have. Desertification
mainly affects agricultural societies while cities can be considered as safe havens, offering a
unique setting with lots of possibilities for employment, family planning services, education,
et cetera.
49
The urban-rural gap for total children ever born is larger in non-desertificated areas. Urban
women in non-desertification vulnerable areas are more likely to have fewer children than
urban women in desertification vulnerable areas. Migratory flows to regional cities in
desertificated areas could be an explanation for this finding. Women from rural desertificated
regions that migrate to regional cities would have, in accordance with all of the above
findings, more children.
The urban-rural gap for dead children is smaller in non-desertificated areas: urban women in
non-desertificated areas are less likely to have children died than women that live in
desertificated cities. This could be explained through higher levels of stress and stressors in
desertificated cities (with hampered food supplies, immigrants from the surrounding rural
areas, etc.).
The urban-rural gap for family planning is larger in non-desertificated areas: urban women in
non-desertificated areas have a much higher fulfilled need for FP than urban women in
desertificated areas. As noted above, information on regional implementation of family
planning programmes were not found, accordingly, we can only assume a difference across
regions.
Young women - of the same parity, urban-rural status and sample year - are more probable of
having more unwanted children in desertificated areas than in non-desertificated areas while
the opposite is true for old women. This trend cannot be explained in this study.
Weaknesses of the study The data used in this study was not optimal. The global map of vulnerability to desertification
was issued in 1998, while this study examined reproductive behaviour that occurred from the
year 2000 until the year 2011. Consequently, if there would have occurred changes in the
environmental state, this study would have missed the effects. Furthermore, the variable
‘vulnerability to desertification’ is not a solid measurement for climate change. The map that
is used is not only hand-assessed (and thus prone to human error), also it was not a GEOTIFF
or another high-definition, geo-referenced map. The (I)DHS data was not perfect in the sense
that it did not include all variables relevant to the study and that it only covered a 11 year
period (too little to detect long-term fertility transitions). Marital status, educational level and
income could not be included in this study as confounding variables - because they were not
available - despite their proved importance in previous research. (3-6) Lastly, demographic
50
misreporting is a pitfall in demographic research, with potential serious effects, certainly in
case of large datasets as the (I)DHS samples.
Concerning the analysis: the ‘complex sample’ was used in SPSS to do the analysis.
However, with this type of analysis it is impossible to determine the distribution in case of
continues variables. Since the three variables that were used in this study appeared to be notnormally distributed, a wrong analysis might have skewed the results.
Wars, drought, famines, family planning programmes and other events that could impact
reproductive health have not been taken into account in this study. Migration - proven to be a
major adaptive strategy - could not be measured and assessed precisely in this study. Hence
this study focussed on the people who stayed behind (partly because of missing ‘migratory’
variables in 2011 and 2005). Another pitfall is that there was no qualitative data collection
and accordingly demographic responses are hard to interpret in terms of ‘changes in attitude’.
Suggestions on future research Future research should identify all potential confounders and implement them in its analysis.
Environmental data should be coupled not only to data on reproductive behaviour but also to
migratory data, in order to consider the broader picture. Future research that compares
reproductive behaviour between environmental refugees or immigrants and left-behinds
should be conducted. Furthermore, information on events as droughts, famines, etc. should
have to be taken into account. The environmental data needs to be coupled in time to the data
on reproductive health, so that short-term responses can be detected. Moreover, studies should
comprise a larger period of time. In that way, trends in reproductive behaviour in cohorts
could be explained more easily. Finally, since this field investigates human responses,
qualitative research is indispensable.
Implications of the research The importance of mapping transitions and changes in reproductive behaviour as a reaction to
one of the most important calamities of our time is hard to underestimate. Research on this
subject could provide meaningful information for both policy makers, as for organisations in
the field by exposing potential barriers for development. When reaching environmental
tipping points, knowledge on behavioural reactions and resolutions could be essential.
Research in the field of responses in reproductive behaviour to environmental stress gives us
time to think about future problems, time ahead of the problems to outline solutions, time to
51
sensitize, time to adapt and, as Benjamin Franklin said, “Lost time is never found again”. This
study could be considered as an introduction and hopes to be an impetus for such further
research.
Conclusion The study confirmed the hypothesis that people in desertification prone areas display other
reproductive behaviour than people in areas that were not vulnerable to desertification. The
tenor of this adaptive behaviour can be considered as a ‘risk-insurance’ strategy. However,
further qualitative and quantitative research is needed. Furthermore, linkage of this research
with information on other hazards and with migratory data can be of particular interest.
52
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Annexes Annex 1.
Table with all variables of the final dataset
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Annex 2. Table with variables that will be used
I
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II
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Annex 3. Confidentiality document
III
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