Page 1 of 27
Advances in Social Sciences Research Journal – Vol. 9, No. 11
Publication Date: November 25, 2022
DOI:10.14738/assrj.911.13422. Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis.
Advances in Social Sciences Research Journal, 9(11). 158-184.
Services for Science and Education – United Kingdom
Death Inequality During the First Year of Life in Morocco: A
Macro Level Analysis
Khadija LOUDGHIRI
National Institute of Statistics and Applied Economics (INSEA)
Avenue Allal El Fassi, Madinat Al Irfane, 10100, Rabat, Morocco
B.P: 6217 Rabat-Instituts
Fatima BAKASS
National Institute of Statistics and Applied Economics (INSEA)
Avenue Allal El Fassi, Madinat Al Irfane, 10100, Rabat, Morocco
B.P: 6217 Rabat-Instituts
Abdesselam FAZOUANE
National Institute of Statistics and Applied Economics (INSEA)
Avenue Allal El Fassi, Madinat Al Irfane, 10100, Rabat, Morocco
B.P: 6217 Rabat-Instituts
ABSTRACT
Disparities in child mortality are a reality in Morocco. These disparities coexist with
inequalities in: (i) the availability of primary health care (PHCs); (ii) the
socioeconomic status of the population as reflected by the prevalence of various
forms of poverty; as well as (iii) fertility levels (TFRs) and the status of women in
literacy and employment rates. Despite its limitations, this research provides a
macro-level understanding of the link between infant mortality and a range of
aggregates (political, economic, social and demographic).The metadata collected in
the 2014 census (RGPH-2014) RGPH-2014 was used to construct a provincial proxy
indicator of infant mortality by area of residence.This is considered as a dependent
variable that we have tried to explain by the above-mentioned indicators. This is
considered as a dependent variable that we have tried to explain by the above- mentioned indicators. The latter indicators reflect the socio-economic conditions
prevailing in each of the provinces by area of residence. In addition, they give
information on the availability of basic health services and on the woman's status.
A key finding is that the level of current fertility as measured by the TFR negatively
affects child survival. With a statistically significant regression coefficient of 2.912
(Pvalue =0.000), it can be argued that high fertility increases the risk of infant
mortality. In turn, the prevalence of overall poverty also has a statistically
significant effect on infant survival (β= -0.213 with a pvalue =0.029).
Keywords: infant-mortality, fertility, global poverty, Macro-level, Morocco.
INTRODUCTION
Under-five mortality, which is considered a major indicator of the level of development in
general and the physical well-being of children in particular (Shen & Williamson, 1997; Hanmer
Page 2 of 27
159
Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis. Advances in Social
Sciences Research Journal, 9(11). 158-184.
URL: http://dx.doi.org/10.14738/assrj.911.13422
et al., 2003), is a concern for nations around the world. In particular, child mortality, one of its
main components, is a good indicator of the health status of entire populations (Allotey and
Reidpath, 2002) and explains much of the variation in life expectancy between countries
(Rodgers, 2002).
Reducing child mortality has long been part of the international community's goals, primarily
within the MDGs and SDGs (United Nations, 2000; United Nations, 2015). Indeed, developing
countries have made substantial progress toward the fourth Millennium Development Goal,
although it varies widely across nations and geographies. United Nations data support the trend
of decreasing child mortality since the mid-1950s in almost every part of the world (United
Nations, 2019a; 2019b). Thus, the under-5 mortality rate has declined from 213‰ to 40‰ and
the infant mortality rate from 140‰ to 29‰. Some differences persist, however, between the
countries depending on their development level. For example, to cite only infant mortality, the
rate is currently 47‰ in the least developed countries and 32‰ for developing countries
versus a mere 4‰ in the developed world.
However, and despite the spectacular improvements in child survival over the past 30 years,
the burden of child deaths worldwide remains immense (UNICEF, 2020). An average of 14,000
children died before the age of five years each day in 2019, as compared to 34,000 in 1990 and
27,000 in 2000. Of the estimated 5.2 Million under-5 deaths in 2019, 2.8 Million were boys and
2.4 Million were girls. Approximately 6,700 newborns died each day in 2019. Neonatal death
represented a progressively larger share of under-5 deaths over time (In 2019, 47% versus
40% in 1990).
Literature generally classifies factors that influence health outcomes into economic,
technological, medical, environmental and societal categories. According to Mosley and Chen
(1984), there are two approaches to explain the infant mortality variation. The first one
adopted by social science research investigated the association between socioeconomic status
and mortality; the second related to epidemiological studies and was concerned by the
morbidity and the biological processes of diseases in the environment. The authors argued that
a new analytical approach incorporating both social and medical science methodologies was
needed and proposed framework based on five proximate determinants. Socioeconomic
determinants, which can be grouped at individual, households and community levels, must
operate through more the basic proximate determinants that in turn influence the risk of
disease and the outcomes of disease processes as mortality (Annex A).
Since, a variety of statistical modeling strategies, based on this framework, have become
common (Hill, 2003). Analysis of links between background factors and proximate
determinants, between infant mortality and both proximate determinants and background
factors and reduced-form models of net associations of background variables and child
mortality were thus conducted.
Many cross-national studies tried to identify the background explanatory factors of the child
mortality are globally based on five theories (Frey and Field, 2000):
modernization/industrialization, economic dependency/world-systems, economic
disarticulation, development state and gender stratification. The first four theories
fundamentally converge to the idea that an independent and equilibrated development
Page 3 of 27
160
Advances in Social Sciences Research Journal (ASSRJ) Vol. 9, Issue 11, November-2022
Services for Science and Education – United Kingdom
economy where the State is an important actor increases human well-being and decreases
infant mortality by improving education, housing, nutrition, health care, sanitation, and various
public services. Gender stratification can be used to argue that societies in which women have
a high level of empowerment will generally register low child mortality rate.
Baird and al.(2011) had shown a large negative association between per capita Gross Domestic
Product (GDP) and infant mortality. They also found that female infant mortality is more
sensitive than male infant mortality to negative economic shocks. Similarly, GDP per capita as
a proxy for income and public health expenditure as a percentage of GDP significantly affect
infant mortality rate according to Wellington (2014). On the other hand, an aggregate study
using data from 16 countries did find a relationship between income inequality and infant
mortality with declined association by age at death until aged 65 years from which it became
reversed (Rodgers, 2002).
Pison (2010) indicates that the socioeconomic development and health gains could explain the
child mortality decline around the world. The Increased agricultural yields and improved
transportation have reduced famines and related deaths in most parts of the world. Advances
in hygiene and the dissemination of education have also played a key role. Even in the poorest
regions, educating women is still associated with better health and reduced child mortality, as
it enables them to take better advantage of the availability of care. Health care provision has
improved, both to treat disease and to prevent it. Vaccinations, the first preventive tool, have
made a significant contribution to reducing infections, the main causes of death in children.
The impact of climate and environmental variables was also tested. Baird and al. (2011) argued
that both extreme heat and extreme rainfall affect the likelihood of infant survival. Similarly,
Geruso and Spears (2018) provided evidence on the effects of extreme heat and humidity on
infant mortality in the developing world.
Also, infant mortality is strongly associated with a number of socioeconomic and demographic
variables. The female participation in the labor force and education significantly affect infant
mortality (Zakir and al., 1999; Pamuk and al., 2011; Wellington, 2014; Ekholuenetale and al.,
2020).
A decrease in the maternal mortality ratio is associated with an increasing probability of under- five child survival (Shen & Williamson, 1997). This result were confirmed by a large
international study conducted by Sartorius and al. (2014) who concluded that the maternal
mortality were the most prominent attributable risk factor, followed by lack of access to
sanitation, water and lower female education.
Particularly, fertility and its components significantly affect infant mortality (Trussel and Pebly,
1984; Zakir and al., 1999; Kapileni, 1992; Rutstein 2000). Recently, using the DHS data about
60 poor countries during the period 1985-2008, Yount and al. (2014) have found that the
decline of Total Fertility Rate(TFR) were associated with improvements in child survival.
Ekholuenetale and al. (2020) have shown that households with large number of children (3&+)
had higher risk of infant mortality, compared to the other. The study of Knodel and al. (1984)
had shown that sib ship size is positively related to infant mortality established an association
between infant mortality and maternal age. Kaplan and al. (2015) had demonstrated that the
Page 4 of 27
161
Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis. Advances in Social
Sciences Research Journal, 9(11). 158-184.
URL: http://dx.doi.org/10.14738/assrj.911.13422
mortality risk decreases by 24% with each additional year of age of the mother at birth. Also,
age of first birth has a significant effect on mortality rates, reducing the mortality risk of the
earlier-born infant by a quarter for each additional year that a young women delays
reproduction, contraceptive prevalence appears to be negatively correlated with infant
mortality (Shen and Williamson, 2001).
In a comparative study based on DHS data from 42 countries, Rustein (2000) has established
that the risk of child mortality is inversely proportional to the length of births intervals. Also,
the risk of death in the childhood period is higher when the mother's age is over 35 years and
births intervals are less than 24 months. Knodel et al (1984) confirmed earlier that inter-birth
interval is an important factor in infant mortality. Kaplan and al. (2015) noted that a short
interval between births increases the mortality risk to the subsequent infant about fourfold.
It’s clear that a large number of factors influence the infant mortality improvement but many
however are strongly collinear, which makes analysis a complex process (Garenne and Vimard,
1984). In underdeveloped countries, it’s more difficult to isolate their effects. In addition, health
programs are often most intensive in the least healthy places, which tends to confuse observed
relationships even more (Flegg, 1982).
In our context, national statistics confirm that Morocco had already achieved an under-five
mortality rate below the Sustainable Development Goal (SDG) target of 25 or fewer deaths per
1000 live births (22.2 per 1000). In general, the mortality in Morocco has fallen considerably
as reflected in lower crude mortality rates and increased life birth expectancy. The life birth
expectancy has risen from under 50 years in the 1960s to over 75 years in recent years. The
infant mortality risk has fallen by 90% during the last six decades from 149 per thousand in
1962 Multiple Purposes Surveys (EOM) to 18 per thousand according to the National
Population and Family Health Survey (ENPSF-2018).
In Morocco, efforts have been made to reduce child mortality through child health strategies
and programs. A sharp decline has been recorded since 1950 as the rate has dropped from
151‰ to 20‰ today (ENPSF-2018). In addition, the most striking disparities are observed
between areas of residence (14.9‰ against 21.5‰ respectively in towns and in rural areas).
Similarly, disparities are noted according to the level of household wealth (10.9‰ for the
affluent level. against 16.9‰ for middle-income households and 23.5‰ for the poor).
However, there are no notable differences between boys and girls (18.3‰ versus 17.7‰
respectively). However, and compared to developed countries, infant mortality today is 5 times
higher, indicating that a significant portion of recorded infant deaths are still preventable.
However, despite the considerable and sustained efforts undertaken by Morocco to reduce
infant morbidity and mortality, the neonatal mortality rate in Morocco is 14 times higher than
in Sweden and in Japan as countries with the least risk of mortality. Therefore, it’s possible to
reduce more this component of mortality. Moreover, it should be noted that the differences in
neonatal chance of survival are widening more between countries during the last decades. In
fact, neonatal mortality, which was 12 times higher in Morocco than in Sweden or Japan in 1990,
rose to 14 times in 2019 (UNICEF, 2020).
Page 5 of 27
162
Advances in Social Sciences Research Journal (ASSRJ) Vol. 9, Issue 11, November-2022
Services for Science and Education – United Kingdom
Besides this inter-country disparity, there are also intra-country variations. However, while the
first ones can be assigned to the existence of development gaps between the countries, the
internal variability, despite sharing some explanatory factors with the former, can never be
justified or admitted.
The case of Morocco is not exceptional to the extent that inequality in the number of children
who die is observed by place of residence, by region, and by province . This inequality can be
attributed to several factors, as outlined in Mosley's conceptual framework. According to
Mosley and Chen (1984), the variation in infant mortality can be explained according to two
approaches. The first, embraced by social science research, focuses on the relationship between
socio-economic background and death, while the second approach, which is epidemiological in
nature, concentrates on the biological process of disease and morbidity. These authors, aware
of the need for a mixed approach, proposed a framework based on five proximate determinants:
(i) maternal factors (age, parity, birth spacing), (ii) environmental contamination; (iii) nutrient
deficiency; (iv) injuries (accidental, intentional) (v) and finally personal control of disease. This
approach considers that socioeconomic factors, measured at different levels, affect the health
and the survival of the children through the intermediate determinants.
The important downtrend of infant mortality was accompanied by a significant decline of
fertility. The TFR has decreased from 7 children in 1960s per a woman to 2.2 currently and
there is a total convergence both in urban and rural areas and all social strata. This paper
attempts to verify at the macro level [2] the impact that fertility can have on the infant mortality
level. Additional indicators were selected to control for confounding effects on fertility and
child mortality (poverty, basic health care coverage, and women's social status).
DATA AND METHODS
To verify the eventual links between fertility and infant mortality, we have adopted a macro- level analysis and the province/prefecture was the statistical unit of analysis.
Data sources
Various data sources were consulted in order to generate macro indicators at the provincial
level. Primarily, data from the RGPH-2014 made available by the High Commission for Planning
was used to produce a Macro Indicator that measures the probability of dying in the first
months of life. These meta-data provide information on a random sample of 10% of all
individuals enumerated in the RGPH-2014. This random sample, which is composed of
3,341,426 individuals, is nationally, regionally and provincially representative. It makes it
possible to create indicators considering the main demographic and socio-economic
characteristics (gender, place of residence, age groups, type of housing, etc.). The database also
contains very important information on the survival chances in the infant period that is used to
compute a measurement of the risk of death in the first months of life. This information
concerns: (i) the number of live births delivered during the 12 months prior to the census
reference date; (ii) as well as the number of deaths that occurred among these live deliveries
during the reference period.
Furthermore, and for analysis purposes, multidimensional poverty indicators were also used,
as developed by the HCP using the OPHI approach. This approach has based the measurement
of multidimensional poverty on a wide range of requirements which, if not met, constitute a
Page 6 of 27
163
Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis. Advances in Social
Sciences Research Journal, 9(11). 158-184.
URL: http://dx.doi.org/10.14738/assrj.911.13422
factor of poverty prevalence or manifestation, as well as a factor of its social reproduction.
These needs concern access to basic social services, water, electricity and sanitation. These
indicators were generated at the provincial level and by area of residence using data from the
RGPH-2014 (HCP, 2014).
Given the link between the occurrence of health events (morbidity and mortality) and
healthcare supply, the latter component was included in the model analysis. Therefore, the
availability of primary health care derived from a provincial database issued by the Moroccan
Ministry of Health is used to develop an indicator of the availability of primary health care. The
1978 Alma Ata (USSR) International Conference Declaration states that primary health care is
considered essential care (both curative and preventive/promotional) that is based on
scientifically sound methods, techniques, and practices. Primary health care is made universally
available to all individuals and families in the community at a cost that the community and the
country can afford at all stages of development. It constitutes the primary point at which
individuals, families, and the community come into contact with the national health system.
Methods
Dependent variable
This indicator is the ratio of deaths recorded among births in the last 12 months prior to the
2014 census (RGPH-2014) to births in the same period. It is considered to be a proxy for the
probability of death between birth and the first anniversary. Of course, the calculation of this
probability requires perfect knowledge of the total number of deaths (components D1 and D2
(Figure 1) within a particular generation of births (the 2014 generation in this study). However,
only the D1 component is provided by the RGPH-2014, which obviously implies an
underestimation of the risk of infant mortality. Nevertheless, considering the relatively low
level of infant mortality in Morocco, deaths in the first triangle constitute the largest share of
infant deaths [0; 1yr [. Guillaume Wunsch and Antonio Canedo (1978) consider three out of
four deaths to occur in this the first triangle if infant mortality is not more than 100‰. Thus,
taking into account the level of infant mortality in Morocco (18‰ according to ENPSF-2018), a
good auxiliary "proxy" indicator of infant mortality by province is this D1 component
(proxy=D1/N2014). The child mortality quotient (1q0) is obtained by a simple linear
transformation of this indicator (1q0=4*Proxy/3).
Figure 1. Diagram of child mortality components
Source: Developed by us
Admittedly, the selected proxy for mortality, as with any measure of mortality calculated from
retrospective surveys, has several limits. Firstly, the data used concern only the births of
women who were not single and who survived at the moment of the 2014 RGPH. Thus, no
Page 9 of 27
166
Advances in Social Sciences Research Journal (ASSRJ) Vol. 9, Issue 11, November-2022
Services for Science and Education – United Kingdom
Figure 2. Trends in neonatal, post-neonatal and infant mortality, Morocco, 1987-2018
Source : Developed by us
Despite this significant decline, the last population and health survey (ENPSF-2018) reveals
that infant mortality differ according to many socio-demographic indicators as the gender of
child, the area of residence, the mother's age at birth of the child,the birth rink, the Wealth- index of the house and the level of mother education (table1). This table shows that the boy are
more exposed to death in the neonatal period than the female. In the post-neonatal period, the
female child mortality is greater than the boy one (the sex ratios are respectively 1.27 and 0,55).
If we considere that the neonatal mortality is more likely a result of endegenous cause and that
the post-neonatal is due to exogenous one, we can suggested that the male births profite of
more interest accorded by their parents if we compare them at the females children.
The same, the infant in the urban area has more chance to survive until his/her first birthday
than the rural one.The mortality ratio is about 0,7 for both neonatal and postneonatal mortality.
In the table 1, we compare also the child mortality according to the mother age at the birth of
his/her child.Hence, except the neonatal mortality, the post-neonatal and the child mortality
are more higher if the age of the mother at the childbirth is too young (less than 24 years old)
or too old (greath than 35 years old).The risk of neonatal mortality is higher in births of the first
order and births of orders over 4. This finding remains true for postneonatal mortality, but only
for births of order 4 and above. As expected, the risk of infant mortality is inversely correlated
with the level of household wealth and with the level of mother education. Even though, the
effect of education is not so strong because of the classification adopted for this indicator
(certificate / no certificate).
At the national level, the improvement in child survival is mainly the result of a decrease in the
post-neonatal mortality (4.4 per thousand according to the ENPS-2018). The resistance to the
decline of the neonatal component [6] (13.6 per thousand according to ENPSF-2018) could be
explained by the prevalence of endogenous causes of death, which are more difficult to
eradicate, and requires, in particular, a high quality care for pregnant women. It’s not the case
of the post-neonatal mortality, which is more affected by preventable exogenous causes.
Undoubtedly, many programs and actions had contributed enormously to the decline in infant
mortality. It concerns: the Pregnancy and Childbirth Surveillance Programs; the strengthening
Page 12 of 27
169
Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis. Advances in Social
Sciences Research Journal, 9(11). 158-184.
URL: http://dx.doi.org/10.14738/assrj.911.13422
Figure 3. The global poverty rate and the total fertility rate by province and area of residence,
Morocco, 2014
Source : HCP
RESULTS
Descriptive analysis
It emerges from the descriptive analysis (Table 2) that the TFR varies by province from a
minimum of 1.6 to a maximum of 4.3 children per woman, with little heterogeneity (coefficient
of variation of 16.4%). There also appears to be some relative variability across the provinces
in terms of literacy among women, for which the coefficient of variation is 24.9%. In contrast,
strong provincial disparities emerge with respect to poverty, health care provision and infant
mortality. The provinces are very heterogeneous in terms of the overall poverty rate (85.7%)
and the number of inhabitants per primary health care facility (56.5%). We also note that the
proportion of deaths varies from a minimum of almost 0% to a maximum of 9.7% with a
coefficient of variation of 41.3% and an average proportion of 4.1% (Table 2). According to area
of residence, the variables are classified in the same order, with a few differences, according to
their degree of dispersion. In fact, the provinces in rural areas are more heterogeneous with
respect to the variables relating to women's activity, poverty and health care supply. In
contrast, in urban areas, with the exception of poverty and health care availability, the
provinces seem to be more homogenous with regard to the remaining variables.
Page 14 of 27
171
Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis. Advances in Social
Sciences Research Journal, 9(11). 158-184.
URL: http://dx.doi.org/10.14738/assrj.911.13422
global poverty and to the total fertility rate. Furthermore, the child’s mortality is positively and
strongly correlated with the second factorial axis. The first axis can be named “poverty-fertility- woman status” and the second one “child mortality”.
Table 3. Contributions of the various indicators to the development of the 1st Factorial Plan
axis, Morocco, 2014
Source : Developed by us
Figure 4. First factorial design of indicators, Morocco, 2014
Source : Developed by us
The projection of provinces on the first factorial plane suggests that rural area are more
characterized by a high level of mortality, fertility and poverty. The woman status in these
provinces is not so developed. In fact, the woman literacy and activity rates, in the rural area,
are low. In spite of the involvement of the woman in the farm activity and the burden she bears,
her work is unpaid, and she is more often declared as inactive. The urban areas, in the other
hands, are more characterized by a low level of fertility and of global poverty. These areas are
more concentrated in the left of the graphic which is defined by the indicators relating to a
Indicators
Component- 1 (λ1=3,4 ;
explained
variance
=56,8%)
Component- 1 (λ2=1,05 ;
explained
variance
=17,5%)
Global poverty 0,884 0,039
Healthcare_facilities 0,810 -0,189
Total fertility 0,615 0,345
Child mortality -0,056 0,950
Woman_activity -0,849 0,049
Woman_literacy -0,930 0,024
Page 17 of 27
174
Advances in Social Sciences Research Journal (ASSRJ) Vol. 9, Issue 11, November-2022
Services for Science and Education – United Kingdom
increase of about 3 points in the risk of mortality, all other things being equal. Except fertility,
the other indicators have a non-significant statistical effect. We have also tested a simple
regression model (infant mortality /total fertility rate) and the result confirms a statistically
significant effect of the total fertility rate on the infant mortality (4.885). Of course, our
objective is not to build a predictive model (R = 42% for multiple regression and 50% simple
regression) but already the variable total fertility rate alone explains half of the variability in
the chances of infant survival.
Table 4.Summary of the results of the multiple regression model
Source : Developed by us
DISCUSSION
In Morocco, there are regional, provincial and residential disparities in infant mortality. Such
disparities co-exist with inequities in: (i) primary health care provision; (ii) socioeconomic
conditions measured here by the presence of various forms of poverty; and (iii) fertility levels
(TFR) and women's status as measured here by their literacy and labor force participation
rates. Admittedly, these indicators have their limits, but they allow one to test at an aggregate
level the relationship between infant mortality and fertility by controlling for some of the
exogenous factors that seem to be influencing the two aspects of demographic change.
These indicators summarize the situation with respect to the main aggregates presented in the
theoretical framework of this thesis. For example, the number of primary health care facilities
per capita is very informative about the supply of health care and its accessibility. It is also a
mirror of the politics of health care supply model. Similarly, it gives an indication of the
commitment of the country to the various international conventions and declarations on
equitable health care and health for all. The availability of preventive and curative healthcare
has been improved, and immunizations, as the primary means of prevention, have contributed
greatly to the reduction of infectious diseases, which are the main cause of death for children.
The poverty rate, for its part, provides information on the success of economic, social and
sustainable development policies in eradicating inequality. A high poverty rate necessarily
means that there are many households in financial difficulties or in situations of deprivation. Of
course, where poverty is high, there is most likely a greater risk of illness and death, particularly
among the most vulnerable populations of whom the children is an integral part.
Explanatories
variables
Regression
coefficient
standard
error
Beta
(β)
t of
Student Pvalue
(Constante) -2,46 2,25 -1,09 0,28
Healthcare facilities 0,00 0,00 0,10 0,79 0,43
Total fertility rate 2,91 0,59 0,50 4,94 0,00
global poverty rate -0,05 0,03 -
0,26 -1,47 0,14
Woman activity
rate 0,04 0,04 0,12 0,84 0,40
Woman literacy
rate 0,01 0,03 0,05 0,27 0,79
Page 18 of 27
175
Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis. Advances in Social
Sciences Research Journal, 9(11). 158-184.
URL: http://dx.doi.org/10.14738/assrj.911.13422
Also, female literacy and labor force participation rates are indicators that provide information
on the status of women in a province. Conceptual models suggest that socio-demographic
characteristics directly or indirectly influence overall child well-being, of which chances of
survival are a core component. According to the literature, infant mortality is strongly related
to a number of socioeconomic and demographic variables. Women's labor force participation
and education significantly affect infant mortality (Ekholuenetale et al., 2020; Wellington, 2014;
Pamuk et al,. 2011).
Nonetheless, the introduction of all these indicators into a multiple regression model using the
Stepwise procedure showed that only the TFR fertility indicators and the poverty rate were
statistically significant. This finding is due partly to the high degree of correlation between the
indicators not included in the model and the poverty and fertility rates at the macro level. It is
clear that a large number of factors influence child survival, but many are highly collinear,
making the analysis complex (Garenne and Vimard, 1984). In developing countries, it is more
difficult to isolate their effects. In addition, health programs are often more intensive in less
healthy locations, which tends to further confound the observed relationships (Flegg, 1982).
Furthermore, empirically testing the hypothesized relationships between mortality and
fertility is not easy, since they are related to phenomena that occur simultaneously in most
developing countries (industrialization, urbanization, educational progress, etc.). Thus,
although several quantitative studies have found statistical correlations and temporal
associations consistent with these theoretical assumptions, other competing explanations
cannot be ruled out. In other words, a causal relationship that is valid for one population may
not be valid for another (Randall S. and LeGrand T., 2003).
Notwithstanding these limitations, the results found support the conclusions of several
previous studies adopting different methodologies and relating to different contexts. Our key
finding is that after controlling for poverty, education, female employment, and primary health
care provision, fertility levels affect child survival at the provincial level in both urban and rural
areas. In other words, as fertility declines, infant mortality declines significantly.
Many case studies suggest that a mother's education is one of the most important predictors of
infant and child mortality. But even after controlling for these socioeconomic variables, regional
differentials in infant mortality still persist. This leads to believe that there is some significant
sociocultural or other region specific factors that need to be investigated (Kalipeni, 1993).
Declining fertility improves the chances of child survival by many mechanisms. Taucher, (1982)
had written that the mechanism by which the decline in fertility may influence the level of infant
mortality is the modification of the structure of births with respect to at least three variables
related to infant mortality: birth order, the mother's age and the length of the previous birth
interval.
According to Trussel (1984), who have explored the relation between changes in reproductive
behavior and changes in child and maternal mortality, the elimination of fourth and higher
order births would reduce infant and child mortality by about 8 per cent. Increases in the
percentage of births to mothers under age 18 was associated with higher neonatal mortality
and an increase in the percentage of births to women aged 35 years was associated with higher
Page 19 of 27
176
Advances in Social Sciences Research Journal (ASSRJ) Vol. 9, Issue 11, November-2022
Services for Science and Education – United Kingdom
neonatal and infant mortality rates. Decreases in the occurrence of short birth intervals ( <24
months) reduced post-neonatal and infant mortality (Rutstein, 2000).
Many studies relate that reductions in fertility contribute to fall in infant mortality by enabling
parents to devote more time and resources to their children (Nanitashvili, 2014). So, when
parents have large families they may be less able to invest in their children, whether this be by
providing them adequate nutrition, healthcare or schooling (Palloni, 1999). Reher (2011)
arguedthat the decrease of women’s parity gave them more time to carry for their children. Lee
(2003) had shown that women who have to spent 70% of their adult lives, giving birth and
raising young children before the demographic transition spend only 14 per cent today.
At the macro level, the increase of TFR decrease the public expenditure by child especially the
health one as argued by Lee and Mason (2010) who have found a negative relationship between
the TFR and human capital expenditure per child in a study conducted between 1994 and 2004
in 19 countries. The reduction of the public expenditure by child may affect the availability of
the health care facilities and the provision of quality services to all children, which can in turn
increase the infant mortality risk.
With regard to births spacing, various mechanisms can be considered to explain the impact on
the infant survival like maternal nutritional depletion, suboptimal lactation related to
breastfeeding-pregnancy overlap, sibling competition, transmission of infectious diseases
among siblings and women's physiological regression (Conde-Agudelo and al., 2012). Birth
intervals less than 24 months were associated with increased risk of anaemia (Dairo and
Lawoyin, 2004). The mother anaemia during pregnancy increases the prevalence of a low
weight at birth which may affect the probability of death (Leno and al., 2017). In fact, Pebly and
al. (1991) had found that preceding birth intervals less than 24 months were associated with
increased risk of neonatal mortality. The effects of the shirt birth intervals on infant mortality
were stronger when preceding sibling died than when she/he survived (DaVanzo et al., 2008;
Blanco Villegas and Fuster, 2009).
Moreover, close births do not allow a woman to recover after childbirth, which weakens her
physical and physiological health. All this has a negative impact on the quality of care she
provides to her children and on her vigilance regarding the symptoms of serious illness of them.
Similarly, the risk of neglecting the vaccination of her children increases. The higher-ranked
children were less likely to be vaccinated (Parashar, 2005).
In the other hand, high fertility that is generally associated with early marriage and a low age
at first maternity translating a traditional system of norms characterized by unbalanced gender
relationship within the household. This imbalance is correlated to a woman's lack of autonomy.
They are not systematically involved in decision-making within their household and even
decisions regarding the use of maternal and child health care. However, this remedy could save
their life and the life of their children through adequate and timely management of
complications of pregnancy and childbirth. In the same sense, one of five women does not use
health services because of the lack of authorization from their husband (ENPSF-2018).
Indeed and despite the fact, that the woman status seems to be improved and that social
investment in a woman's body is no longer so geared towards procreation, numerous women
Page 20 of 27
177
Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis. Advances in Social
Sciences Research Journal, 9(11). 158-184.
URL: http://dx.doi.org/10.14738/assrj.911.13422
still suffering in a society characterized by a patriarchal dominance where the change of beliefs
and behavior is difficult (Zerari, 2006 ; Mielusel, 2015). The 2019 National Survey on Violence
against Women confirmed the persistence of conjugal violence which is more prevalent among
women whose husbands decide unilaterally on their contraception use (60.6%) compared to
that of women who decide on their own use (55.2%) or with those whose decision is taken
jointly with their husbands (50.4%) (HCP, 2019). Moreover, according to the same data source,
the mother-in law is also incriminated by married women victims of family violence (more than
25%). Effectively, the mother-in-low constitute a pole of resistance within Moroccan
households; particularly those with no-nuclear structure and she gives herself the right to make
some decisions regarding even the number of children to be born. In this context, women may
have a parity that exceeds the ideal number of children they would prefer and they will be more
exposed to physical and psychological illness, which in turns affect health and ultimately the
child survival.
This analysis should be improved if we had more observation units to take into account other
determinants of infant mortality like nutritional status and infant feeding (breastfeeding,
weaning and supplementation) , health care access and the use of health services by mothers
and children for family planning, prenatal care and childbirth, child immunization,...),
environmental conditions (water, climate pollution; rain and temperature,...), socio-economics
(education, age at first union, etc. ). Other limit of our analysis came from the fact that the data
used concerns only ever married women who were alive at the time of census. So, it did not
provide information on the survival status of births whose mothers died before the census and
who were being more exposed to. Similarly, the exclusion of unmarried mothers introduces
another bias of undetermined magnitude. Furthermore, the validity of data on child mortality
could be affected by the under-reporting of births or deaths. In our case, this risk could be
considered negligible given that the reference period "12 months before the 2014 population
census" could be considered as controllable and less affected by the memory effect.
Finally, the fact that fertility seems to be a key determinant of child survival must be relativized
as the causality also runs in the other direction. The causal relationship between infant
mortality and fertility had been a debate for long years but there is no consensus essentially
because of the lag in relationship between these two variables as argued by Chowdhury (1988).
The author believes that when a woman has multiple pregnancies, the chances of her child’s
survival are significantly reduced. A woman may thus decide to bear more children in the hope
that at least some will stay alive. A dynamic analysis is therefore essential to correctly analyze
the mortality-fertility relationship.
References
Allotey, A. Pascale & Reidpath, D. Daniel. Objectivity in Priority Setting Tools in Reproductive Health: Context and
the DALY, Reproductive Health Matters, 10:20, 2002, 38-46. DOI: 10.1016/S0968-8080(02)00075-7
Baird, S.& al. Aggregate Income Shocks and Infant Mortality in the Developing World. Review of Economics and
Statistics, 93(3), 2011, 847-856. https://doi.org/10.1162/REST_a_00084
Blanco Villegas, M. J., & Fuster, V. Birth Intervals and Infant Mortality in La Cabrera (Spain). Collegium
antropologicum, 33(1), 2009, 1-5. https://hrcak.srce.hr/39454
Chowdhury, A. R. The Infant Mortality-Fertility Debate : Some International Evidence. Southern Economic
Journal, 54(3), 1988, 666. https://doi.org/10.2307/1059010
Page 21 of 27
178
Advances in Social Sciences Research Journal (ASSRJ) Vol. 9, Issue 11, November-2022
Services for Science and Education – United Kingdom
Conde-Agudelo et al. Effects of Birth Spacing on Maternal, Perinatal, Infant, and Child Health : A Systematic
Review of Causal Mechanisms. Studies in Family Planning, 43(2), 2012, 93-114. https://doi.org/10.1111/j.1728-
4465.2012.00308.x
Dairo MD, Lawoyin TO. Socio-demographic determinants of anaemia in pregnancy at primary care level: A study
in urban and rural Oyo state, Nigeria. Afr. J. Med. Med. Sci. 2004; 33:213–217. PMid: 15819466
DaVanzo, J., Hale, L., Razzaque, A., & Rahman, M. The effects of pregnancy spacing on infant and child mortality in
Matlab, Bangladesh: how they vary by the type of pregnancy outcome that began the interval. Population studies,
62(2), 2008, 131-154. https://doi.org/10.1080/00324720802022089
Ekholuenetale, M. & al. Household factors associated with infant and under-five mortality in sub-Saharan Africa
countries. ICEP 14, 10, 2020. https://doi.org/10.1186/s40723-020-00075-1
Flegg, A. T. Inequality of Income, Illiteracy and Medical Care as Determinants of Infant Mortality in
Underdeveloped Countries. Population Studies, 36:3, 1982, 441-458, DOI: 10.1080/00324728.1982.10405597
Frey, R.S. & Field, C. The determinants of Infant Mortality in the Less Developed Countries: A Cross-National Test
of Five Theories. Social Indicators Research, 52, 2000, 215–234. https://doi.org/10.1023/A:1007093631977
Garenne, M. & Vimard, P. Un cadre pour l’analyse des facteurs de la mortalité des enfants. Cah. O.R.S.T.O.M., sér.
Sci. Hum., XX(2), 1084, 1984: 305-310.
https://www.researchgate.net/publication/32987746_Un_cadre_pour_l'analyse_des_facteurs_de_la_mortalite_de
s_enfants.
Geruso, M., & Spears, D. Neighborhood sanitation and infant mortality. American Economic Journal: Applied
Economics, 10(2), 2018, 125-62. DOI: 10.1257/app.20150431
Hanmer, L & al. Infant and child mortality in developing countries : Analysing the data for Robust determinants.
Journal of Development Studies, 40(1), 2003, 101-118. https://doi.org/10.1080/00220380412331293687
HCP & ONU Femmes. Note sur les violences faites aux femmes et aux filles. L’enquête nationale sur la violence à
l’encontre des femmes et des hommes 2019. Pp. 36. https://www.hcp.ma/Note-sur-les-violences-faites-aux- femmes-et-aux-filles_a2627.html
Hill, k. Frameworks for studying the determinants of child survival, Public Health Classics, Bulletin of the World
Health Organization, 81 (2), 2003, p. 138 – 139.
https://www.scielosp.org/article/ssm/content/raw/?resource_ssm_path=/media/assets/bwho/v81n2/v81n2a
11.pdf
Kalipeni, E. Determinants of infant mortality in Malawi : A spatial perspective. Social Science & Medicine, 37(2),
1993, 183-198. https://doi.org/10.1016/0277-9536(93)90454-C
Kaplan, H. & al. The Causal Relationship Between Fertility and Infant Mortality: Prospective Analyses of a
Population in Transition. In Population in the Human Sciences: Concepts, Models, Evidence (Oxford University
Press, 2015), p. 361.
Knodel, J. & Hermalin, A. I. Effects of Birth Rank, Maternal Age, Birth Interval, and Sibship Size on Infant and Child
Mortality : Evidence from 18th and 19th Century Reproductive Histories. American Journal of Public Health,
74(10), 1984, (October 1): pp. 1098-1106. https://doi.org/10.2105/AJPH.74.10.1098
Lee Ronald. The Demographic Transition : Three Centuries of Fundamental Change. Journal of Economic
Perspectives 17(4), 2003: 167-190. https://doi.org/10.1257/089533003772034943
Lee Ronald & Mason Andrew. Fertility, Human Capital, and Economic Growth over the Demographic Transition.
European Journal of Population / Revue Européenne de Démographie 26(2), 2010: 159-182.
https://doi.org/10.1007/s10680-009-9186-x
Leno, D. & al. Les déterminants maternels associés au petit poids pour l’âge gestationnel à la maternité de
l’hôpital Donka de Conakry. Revue de médecine périnatale, 9(3), 2017, 178-183.
https://doi.org/10.1007/s12611-017-0408-x
Page 22 of 27
179
Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis. Advances in Social
Sciences Research Journal, 9(11). 158-184.
URL: http://dx.doi.org/10.14738/assrj.911.13422
Mielusel, R. L’évolution du statut de la femme marocaine dans la civilisation, ma Mère !... de Driss Chraïbi et dans
Amour sorcier de Tahar Ben Jelloun : Liberté du choix ou choix de liberté? Voix Plurielles, 12(1), 2015, 139-152.
https://doi.org/10.26522/vp.v12i1.1180
Mosley, W. H. &L. C. Chen, An Analytical Framework for the Study of Child Survival in Developing Countries,
Population and Development Review, 1984, Vol. 10, Supplement: Child Survival: Strategies for Research (1984),
pp. 25-45. https://doi.org/10.2307/2807954
Nanitashvili, N. Infant Mortality and Fertility. Population Horizons Factsheet, N° 5:1-2, 2014.
https://www.ageing.ox.ac.uk/download/143
Palloni, A., Rafalimanana, H. The effects of infant mortality on fertility revisited: new evidence from latin america.
Demography, 36, 1999: 41–58. https://doi.org/10.2307/2648133
Pamuk, E. R., R. Fuchs, & W. Lutz. Comparing Relative Effects of Education and Economic Resources on Infant
Mortality in Developing Countries. Population and Development Review 37(4): 637–664 (December 2011)
Parashar, Sangeeta. Moving beyond the mother-child dyad: Women's education, child immunization and the
importance of context in rural India. Social Science & Medicine 61(5), 2005: 989-1000.
https://doi.org/10.1016/j.socscimed.2004.12.023
Pebley, Anne R., Albert I. Hermalin, and John Knodel. Birth spacing and infant mortality: Evidence for eighteenth
and nineteenth century German villages. Journal of Biosocial Science, 23.4, 1991: 445-459. DOI:
https://doi.org/10.1017/S0021932000019556
Pison, G. Le recul de la mortalité des enfants dans le monde : de grandes inégalités entre pays. Population et
Sociétés, 463, 2010, (janvier). https://www.ined.fr
Randall, S., & Legrand, T. K. Stratégies reproductives et prise de décision au Sénégal: le rôle de la mortalité des
enfants. Population, 58(6), 2003, 773-806. DOI 10.3917/popu.306.0773
Reher, David S. Economic and Social Implications of the Demographic Transition. Population and Development
Review 37, 2011: 11-33. https://doi.org/10.1111/j.1728-4457.2011.00376.x
Rodgers, G. B. Income and inequality as determinants of mortality: An international cross-section analysis a.
International journal of epidemiology, 31(3), 2002, 533-538.
Rutstein, S. O. Factors associated with trends in infant and child mortality in developing countries during the
1990s. Bulletin of the World Health Organization, 78(10), 2000:1256-70
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2560619/
Sartorius, B. K., & Sartorius, K. Global infant mortality trends and attributable determinants – an ecological study
using data from 192 countries for the period 1990–2011. Population Health Metrics, 12(1), 2014, 29.
https://doi.org/10.1186/s12963-014-0029-6
Shen, C., & Williamson, J. B. Child Mortality, Women’s Status, Economic Dependency, and State Strength : A Cross- National Study of Less Developed Countries. Social Forces, 76(2), 1997, 667-700. doi:10.2307/2580728.
Shen C. & Williamson, J. B. Accounting for Cross-National Differences in Infant Mortality Decline (1965-1991)
among Less Developed Countries : Effects of Social Women’s Status. Social Indicators Research, 53(3), 2001: 257-
288. https://doi.org/10.1023/A:1007190612314
Taucher, E. Effects of declining fertility on infant mortality levels: study based on data from five latin American
countries. Report INT-2103, 1982, Latin American Demographic Centre (CELADE).
Trussell, J. & Pebley, A. R. The Potential Impact of Changes in Fertility on Infant, Child and Maternal Mortality.
Studies in Family Planning, 15(6), 1984, 267. https://doi.org/10.2307/1966071
UNICEF. Levels & Trends in Child Mortality. Estimates developed by the UN Inter-agency Group for Child
Mortality Estimation. https://www.unicef.org/media/79371/file/UN-IGME-child-mortality-report-2020.pdf.pdf
United Nations. United Nations Millennium Declaration, Resolution adopted by the General Assembly on 18
September 2000
Page 23 of 27
180
Advances in Social Sciences Research Journal (ASSRJ) Vol. 9, Issue 11, November-2022
Services for Science and Education – United Kingdom
United Nations. Transforming our world: the 2030 Agenda for Sustainable Development, Resolution adopted by
the General Assembly on 25 September 2015
United Nations. World Population Prospects 2019, Under-five mortality (both sexes combined) by region,
subregion and country, 1950-2100, Estimates, 1950 – 2020, Excel files
United Nations. World Population Prospects 2019, Infant mortality (both sexes combined) by region, subregion
and country, 1950-2100, Estimates, 1950 – 2020, Excel files
Wellington, O. Determinant of Infant Mortality Rate : A Panel Data Analysis of African Countries. Developing
Country Studies, 4(18), 2014: 111-115.
Wunsch, G., & Canedo, A. La transformation des taux en quotients aux premiers âges de la vie. Genus, 1978, 133-
141. https://www.jstor.org/stable/29788214
Yount Kathryn M. et al. Fertility Decline, Girls Welfare, and Gender Gaps in Children’s Welfare in Poor Countries.
Demography 51(2), 2014: 535-561. https://doi.org/10.1007/s13524-014-0282-0
Zakir, M., & P. V. Wunnava. Factors affecting infant mortality rates: evidence from cross-sectional data, Applied
Economics Letters, 1999, 6, 271–273
Zerari, H. (s. d.). Femmes du Maroc entre hier et aujourd’hui : quels changements ? Recherches internationales,
77(3), 2006: 65-80. https://www.recherches-internationales.fr/RI77/RI77-hayat-zerari.pdf
Page 24 of 27
181
Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis. Advances in Social
Sciences Research Journal, 9(11). 158-184.
URL: http://dx.doi.org/10.14738/assrj.911.13422
ANNEX A. OPERATION OF THE FIVE GROUPS OF PROXIMATE DETERMINANTS ON THE
HEALTH DYNAMICS OF A POPULATION
Source: Population and Development Review, Vol. 10, Supplement: Child Survival: Strategies for
Research (1984), pp. 25-45
Page 25 of 27
182
Advances in Social Sciences Research Journal (ASSRJ) Vol. 9, Issue 11, November-2022
Services for Science and Education – United Kingdom
ANNEX B. ADMINISTRATIVE DIVISION OF MOROCCO
Region Province/ Prefecture
Population
2014 Total area Density
Number % (in
km2) % (inhabitants/km2)
Tanger- Tétouan-Al
Hoceïma
Tanger-Assilah, M’diq- Fnideq, Tétouan, Fahs-Anjra,
Larache, Al Hoceima,
Chefchaouen and Ouazzane
3 540
012 10.5 17262 2.4 205.1
Oriental
Oujda-Angad, Nador,
Driouech, Jerada, Berkane,
Taourirt, Guercif and Figuig.
2 302
182 6.8 90127 12.6 25.5
Fès-Meknès
Fez, Meknes, Hajeb, Ifrane,
Moulay Yacoub, Sefrou,
Boulmane, Taounate and
Taza,
4 216
957 12.5 40075 5.6 105.2
Rabat-Salé- Kénitra
Rabat, Salé, Skhirat-Témara,
Kénitra, Khémisset, Sidi
Kacem and Sidi Slimane.
4 552
585 13.5 18194 2.6 250.2
Béni Mellal- Khénifra
Beni Mellal, Azilal, Fqih
Bensaleh, Khénifra and
Khouribga
2 512
375 7.5 41033 5.8 61.2
Casablanca- Settat
Casablanca, Mohammedia,
El Jadida, Nouaceur,
Mediouna, Benslimane,
Berrechid, Settat and Sidi
Bennour.
6 826
773 20.3 19448 2.7 351.0
Marrakech- Safi
Marrakech, Chichaoua, Al
Haouz, Kelaa Sraghna,
Essaouira, Rhamna, Safi and
Youssoufia
4 504
767 13.4 39167 5.5 115.0
Drâa- Tafilalet
Ouarzazat, Midelt, Tinghir
and Zagora
1 627
269 4.8 115592 18.6 14.1
Souss- Massa
Agadir Ida-Outanane- Inezgane Aït Melloul,
Chtouka Aït Baha,
Taroudante, Tiznit and Tata.
2 657
906 7.9 53789 7.6 49.4
Guelmim- Oued Noun
Guelmim, Assa-Zag, Tan- Tan, Sidi Ifni, 414 489 1.2 46108 6.5 9.0
Laâyoune- Sakia El
Hamra
Laâyoune, Boujdour, Tarfaya
and Smara 340 748 1.0 140018 19.7 2.4
Dakhla- Oued Ed- Dahab
Oued-Eddahab and
Aousserd. 114 021 0.3 130998 18.4 0.9
National 33 610
084 100 710850 100 47.3
Source: Ministry of the Interior
Page 26 of 27
183
Loudghiri, K., Bakass, F., & Fazouane, A. (2022). Death Inequality During the First Year of Life in Morocco: A Macro Level Analysis. Advances in Social
Sciences Research Journal, 9(11). 158-184.
URL: http://dx.doi.org/10.14738/assrj.911.13422
ANNEX C. DIMENSIONS, COMPONENTS, INDICATORS, THRESHOLDS AND WEIGHTINGS
OF THE MULTIDIMENSIONAL POVERTY INDEX
Dimensio
n Component Indicator: definition of deprivation Weighting Education
Children's education If one of the children of school age 6-14 does not
attend school 1/6
1/3
Adult education If no member of the household aged 15 and over
has completed five years of schooling 1/6
Health
Handicap
If a member of the household is unable to perform
any of the following organic functions: vision,
hearing, walking, cognitive ability (remembering or
concentrating), body care and communication
1/6
1/3
Infant mortality If a child under 12 months died in the household 1/6
Living conditions
Potable water If the household does not have access to clean water
within a 30 minute walk from home 1/18
1/3
Electricity If the household does not have electricity 1/18
Sanitation If the household does not have a private toilet or
a healthy sanitation system 1/18
Flooring If the floor of the apartment is dirty, sand or dirt 1/18
Cooking mode If the household cooks with wood, charcoal or
manure 1/18
Asset holding
If the household does not own a car or tractor /
truck and does not own at least two of the
following items: telephone, television, radio,
motorcycle, bicycle and refrigerator
1/18
Source: HCP
[1] Maternal factors (age, parity, birth interval), environmental contamination (air,
food/water/fingers, skin/soil/inanimate objects, insect vectors), nutrient deficiency (calories,
protein, micronutrients), injury (accidental, intentional) and finally personal illness control
(personal preventive measures, medical treatment).
[2] Morocco's geographical and administrative division is reproduced in Annex B.
[3] The demographic weight of the (i)hard core of poverty, represented by the category of
households which combine the two forms of the sources of poverty, (ii) category of households
which are poor according to the multidimensional approach and not poor according to the
monetary approach, (iii) category of poor households according to the monetary approach and
non-poor according to the multidimensional approach, determines the global poverty rate.
[4] The monetary poverty rate measures the proportion of the population living below the
poverty line, conventionally defined at 60% of the median standard of living. This measurement
is therefore relative. It compares incomes within the population and does not take into account
the living conditions of low-income households.
[5] The multidimensional poverty rate gives the proportion of poor people, cumulating a
number of deprivations greater than the poverty line - at least 30% of the basic deprivations to
which households are exposed -. It expresses the ratio of the number of poor to the total number
of the population. More information is reproduced in Annex C.
Page 27 of 27
184
Advances in Social Sciences Research Journal (ASSRJ) Vol. 9, Issue 11, November-2022
Services for Science and Education – United Kingdom
[6] Neonatal Death Quotient measures the probability of dying before reaching the exact age of
one month;Post-neonatal mortality quotient measures the probability of dying between the
first month and the exact twelfth month; Infant mortality quotient measures the probability of
dying between birth and the first birthday;
[7] The DAO approach is intended to be a palliative alternative to the difficulties of geographical,
financial and cultural accessibility encountered in rural areas. An approach that is essentially
based on social mobilization around maternal and neonatal health and the participation of all
components of the local community.
[8] Luxury and modern’; ‘Economic and social’; ’slums’; ’Old medina’.