Survival Analysis of Under-five Mortality in West Sulawesi Indonesia
using Cox Regression
Mieke Nurmalasari
1
, Linta Ifada
2
and Setia Pramana
3
1
Department of Health Information Management, Faculty of Health and Science, Universitas Esa Unggul, Jl. Arjuna Utara
No. 9, Kebon Jeruk, Jakarta Barat 11510, Indonesia
2
BPS’ Statistics Indonesia, Jakarta, Indonesia
3
Department of Computational Statistics, Politeknik Statistika STIS, Jakarta, Indonesia
Keywords: Survival Analysis, Under-five Mortality, Cox Regression, Hazard Ratio, Mortality Rate.
Abstract: Reducing infant mortality is one of the targets of SDGs goal 3, promoting wellbeing for all at all ages and
ensuring healthy lives. Although the under-five mortality in Indonesia has declined, some provinces show a
high mortality rate such as West Sulawesi. Hence, efforts to decrease the rate is still needed by identifying
the main determinant of under-five mortality. The main objective of this study is to determine the main factors
that affect under-five mortality in West Sulawesi using Intercensal Population Survey 2015. In this study, the
impact of mother’s education, age of first delivery, previous birth interval, birth type, the gender of the under-
five child, and paramedics help during labor were investigated using the Cox Proportional Hazard Regression.
All variables impacted mostly to the survival rate of under-five children. Female under-five children had a
lower hazard (risk) of death compared to the males. Twin had a three times higher hazard of death as compared
to single born children. In addition, higher mother’s education tends to have a lower hazard.
1 INTRODUCTION
All health issues in the SDGs are integrated into goal
number 3, which is to ensure a healthy life and
wellbeing for all at all ages. Reducing the mortality
rate for infants and under-five children is one of the
target SDGs' goals (United Nations, 2017).
Countries around the world have been trying to
reduce child mortality in the last few decades. Child
mortality is an important indicator of children’s
health. The under-five mortality rate is the number of
under-five deaths (1 5 years) per 1000 live births
within one year. This mortality can describe the level
of health problems of children under five, the level of
primary health services and the success of primary
health (Danzhen You, Lucia Hug, Simon Ejdemyr,
Jan Beise and World, 2015).
In general, under-five mortality in Indonesia has
declined. However, some provinces have a high
mortality rate. The highest under-five mortality is
dominated by Provinces in Eastern Indonesia, one of
them is West Sulawesi Province. Based on the Health
Office report 2016, there has been a decrease in child
mortality rates over the past year in West Sulawesi
from 2010 to 2015. It was 16.4 per 1000 live births in
2010 and 14.26 per 1000 live birth in 2015 (Dinas
Kesehatan Provinsi Sulawesi Barat, 2016). However,
West Sulawesi became the province with the highest
number of infant deaths (IMR) in Indonesia which is
50 infant deaths that occurred in 1000 live births.
Infant mortality also increased in 2017 (Dinas
Kesehatan Provinsi Sulawesi Barat, 2017). Factors
influence this situation need to be investigated to
know the right policy in reducing the rate.
The main objective of this study is to determine
the main factors that affect or influence the survival
of under-five in West Sulawesi.
2 METHOD
This study used secondary data namely Intercensal
Population Survey 2015 in Indonesia performed by
BPS-Statistics Indonesia. The unit of this study is
under-five born children. There are 2549 cases in
West Sulawesi.
The response variable is the death risk of under-
fives which measured by under-fives survival time
from birth until death. The survival time is presented
in months which ranges between 0 to 60 months. The
92
Nurmalasari, M., Ifada, L. and Pramana, S.
Survival Analysis of Under-five Mortality in West Sulawesi Indonesia using Cox Regression.
DOI: 10.5220/0009566900920096
In Proceedings of the 1st International Conference on Health (ICOH 2019), pages 92-96
ISBN: 978-989-758-454-1
Copyright
c
2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
explanatory variables are the mother’s education,
mother’s first age of giving birth, previous birth
interval, birth type, the gender of the under-five child
and whether paramedics help labor. The impact of
these variables was investigated using the Cox
Proportional Hazard Regression.
The Cox proportional hazard model is a survival
model that measures the relationship between one or
more covariates with time. The risk of the event per
time unit changes over time at baseline levels of
covariates was denoted by h
0
(t). The hazard function
was represented by h(t). The hazard ratio was
expressed by h(t)/h
0
(t). The Cox proportional hazard
model was defined by the equation:
ℎ(𝑡)
0
(𝑡)
= 𝑒
(𝛽
1
𝑥
1
+𝛽
2
𝑥
2
+⋯+𝛽
𝑝
𝑥
𝑝
)
(1)
Here h(t) hazard at time t, h
o
(t) is a baseline
hazard, x
p
is the p-th explanatory variable.
3 RESULT
3.1 Descriptive Analysis
From Table 1, we can observe that there are 254
(10%) infants could not survive before reaching five
years old. The percentage of infants who died before
5 years from the family whose mother has low
education (up to elementary school) is higher (12.3%)
than, other educational backgrounds.
The age of the mother at the first delivery seems
to be the risk of under-five mortality. Furthermore,
22.6% of the infant with the mother’s age at first
delivery above 35 years old was dead.
Moreover, infants with the birth type of multiple
(twin, triplets, etc) have almost triple risk to die as
compared to the single born infant. In addition, a male
infant has a higher risk to die before five as compared
to a female infant.
3.2 Survival Analysis
3.2.1 Kaplan Meier
The curve of Kaplan Meier in Figure 1 shows that at
the beginning of the first year the curve looked
decrease. It means that they are struggling to survive,
but afterward, the probability of the children to
survive is relatively stable until five years old or the
cumulative survival of the child was 60 months.
Figure 1: Overall Under-five child survival status in West
Sulawesi.
Table 1: Sample characteristics.
Variables
Died (n=254)
Alive (n=2295)
Total (n=2549)
n (%)
n (%)
n (%)
Mother’s education status
Low
158 (12.3%)
1126 (87.7%)
1284 (100%)
Middle
80 (8.2%)
901 (91.8%)
981 (100%)
High
16 (5.6%)
268 (94.4%)
284 (100%)
Mother’s age at the first delivery
20-35 years old
150 (9.6%)
1416 (90.4%)
1566 (100%)
<20 or >35 years old
97 (10.2%)
855 (89.8%)
952 (100%)
≥ 35 years old
7 (22.6%)
24 (77.4%)
31 (100%)
Previous birth interval
<24 months
117 (11.9%)
863 (88.1%)
980 (100%)
≥24 months
137 (8.7%)
1432 (91.3%)
1569 (100%)
Birth Type
Single
239 (9.6%)
2258 (90.4%)
2497 (100%)
Multiple
15 (28.8%)
37 (71.2%)
52 (100%)
Gender
Male
164 (12.2%)
1185 (87.8%)
1349 (100%)
Female
90 (7.5%)
1110 (92.5%)
1200 (100%)
Paramedics at Labor
Non-Medic
89 (11.2%)
704 (88.8%)
793 (100%)
Medic
165 (9.4%)
1591 (90.6)
1756 (100%)
Survival Analysis of Under-five Mortality in West Sulawesi Indonesia using Cox Regression
93
An overview of the under-five child in West
Sulawesi from the Kaplan Meier curve based on
explanatory variables can be seen in Figure 2 up to
Figure 6. The Kaplan Meier curve in Figure 2, it
appears that the survival curve of an under-five child
who has mothers with higher education is above the
survival curve of an under-five child who has mothers
with middle education and low. It could be concluded
that under-five child who has mothers with higher
education has a tendency to survive longer compared
to under-five who have mothers with middle and low
education.
Figure 2: Kaplan Meier curve for under-five survival in
West Sulawesi based on mother’s education.
According to Figure 3, it shows that mother which
age of first delivery above 35 years old tends to have
less survival compared to mother’s ideal first age of
giving birth (20-35).
Figure 3: Kaplan Meier curve for under-five survival in
West Sulawesi based on mother’s age of first delivery.
Figure 4 is the Kaplan-Meier curve which shows
that the survival curve for infants with previous birth
intervals more than 24 months is above the survival
curve for infants whose birth intervals are less than 24
months. This indicates that toddlers born to mothers
whose birth intervals are more than 24 months tend to
have the opportunity to survive longer.
Figure 4: Kaplan Meier curve for under-five survival in
West Sulawesi based on previous birth interval.
Kaplan Meier curve for under-five survival in
Figure 5 demonstrate that the curve of multiple birth
type is below the survival curve for a child with a
single birth type. Twin birth types are more likely
smaller for life longer than under-fives with a single
birth type.
Figure 5: Kaplan Meier curve for under-five survival in
West Sulawesi based on birth type.
Figure 6 shows that the cumulative survival for
under five for females seems to have lived longer than
the male because the survival curve of the female is
above the male.
Figure 6: Kaplan Meier curve for under-five survival in
West Sulawesi based on gender.
ICOH 2019 - 1st International Conference on Health
94
Table 2: Parameter estimation for Cox Regression Survival Model.
Variable
β (Se)
p-value
Hazard Ratio
Mother’s education status
Low*
Middle
High
-
-0.481 (0.141)
-0.897 (0.273)
0.001
0.001
0.618
0.408
Mother’s age of first delivery
20-35 years old*
< 20 years old
≥ 35 years old
-
-.0.027 (0.134)
0.986 (0.391)
0.840
0.012
0.973
2.681
Previous birth interval
< 24 months*
≥ 24 months
-.345 (0.131)
0.008
0.708
Birth type
Single*
Multiple
1.151 (0.271)
0,0001
3.161
Gender
Male*
Female
-0.510 (.131)
0,001
0.601
Paramedics labor
-0.080 (0.136)
0.556
.923
*Reference
3.2.2 Cox Regression Model
We use Cox regression to the model prediction of the
time (measured in weeks). We explore which factors
are associated with the risk of the under-five mortality
of children in West Sulawesi.
The result from the Cox Regression model in
Table 2 shows that almost all the explanatory
variables in the model were statistically significant
except variable paramedic labor.
The hazard ratio value indicates that mothers who
have higher education are less likely to have infant
deaths. This is in line with research conducted by
(Ettarh and Kimani, 2012), (Mwangi Muriithi, 2015)
and (Aheto, 2019). Mothers with secondary or higher
education have a higher desire to seek information or
knowledge about health care.
The hazard ratio based on the age of birth delivery
shows that mothers with age of first delivery > 35
years have a higher risk to not survive 2.681 times
compare to the ideal mother’s ages of first delivery
(20 35 years old).
Meanwhile, a mother who has a longer birth
interval with a previous birth, then the tendency for
children to die will decrease (Kayode, Adekanmbi
and Uthman, 2012). The close birth distance between
the first child to the next child can cause problems,
both mental and physical health. The World Health
Organization (WHO) and Badan Koordinasi
Keluarga Berencana Nasional (BKKBN) recommend
that the next birth interval should be two to three years
to minimize the risk of child and maternal mortality.
The type of births with twins has a greater chance
of dying 3.161 times compared to single births.
(Monden and Smits, 2017) also explain in their
research that twin births are more at risk of dying than
single childbirths.
The hazard ratio for gender indicates that the
female has a longer survival time than the male. The
results of this study are also the same as the research
conducted by (Ruggieri et al., 2016) and (Afeez et al.,
2018). Female toddlers are more able to survive than
male toddlers in terms of the immune system and
genetic factors. Female’s under-five children are
more immune to diseases.
4 CONCLUSIONS
All variables impacted mostly to the survival rate of
under-five children. Female under-five children had a
lower hazard (risk) of death compared to the males.
Twin under-five children had four times higher
hazard of death as compared to single born children.
Higher mother’s education tends to have a lower
hazard.
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