P-ISSN: 2808-5957
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2294
STRUCTURAL MODEL OF PAPUAN CHILDREN’S QUALITY OF LIFE
IN DIFFERENT ECOSYSTEM ZONES IN PAPUA
Stefanus P. Manongga
1
, Serlie Littik
2
Faculty of Public Health, Nusa Cendana University, Kupang, East Nusa Tenggara, Indonesia
1
pietermanongga7@gmail.com
2
serlie.littik@staf.undana.ac.id
ARTICLE INFO
ABSTRACT
Published: January 27
th
, 2023
The purpose of the study was to examine the situation of children's quality
of life and assess the role of various related factors to the quality of life of
children in various ecosystem zones in Papua Province. The study was
conducted in four districts representing three ecosystem zones, namely the
mainland coastal zone (Merauke and Sarmi Regencies), the middle plain
zone (Nabire Regency) and the mountain zone (Jayawijaya Regency). This
research was designed cross-sectionally, where the selection of the research
site used a multistage sampling procedure with stratification and cluster
techniques. Randomly involved 1481 sample households that had children
under five for three zones. Data collection was carried out through
structured interviews, observations and field measurements. To determine
whether there are differences in related variables between ecosystem zones,
the least significant different and Kruskal Wallis test is used. Testing and
assessing the impact of malnutrition on child development, Structural
Equation Modelling-Regression is used with a partial least square approach
using the help of the SmartPLS application version 2.0. The results showed
that the population of Papuan children with the risk of quality of life
disorders (at risk) reached 50.57% and was the largest in the mountainous
zone. Generally, they have impaired negative mood function, while children
in the mountainous zone have impaired motor, autonomic, cognitive, social
and negative mood functions.
Keywords: children’s life quality,
at-risk, ecosystem, moderation effect
This work is licensed under CC
BY-SA 4.0
INTRODUCTION
Previous studies have shown that there is a link between malnutrition and the development
of abnormal child behavior. Malnutrition has an influence on metabolic changes (Dipasquale et
al., 2020; Love, 1986; Thompson et al., 2020), while changes in nutritional status have an impact
on metabolism and immune cell function (Alwarawrah et al., 2018). Sorhaindo & Feinstein (2006)
stated that children with malnutrition are very susceptible to metabolic changes that have an impact
on decreasing cognitive abilities, brain performance as well as immunity and susceptibility to
infectious diseases. Whereas, Liu et al. (2004) point out that malnutrition affects neurocognitive
deficits, which in turn affects persistent externalizing behavior problems throughout childhood and
adolescence. Early neurocognitive deficits can also be used as predictors of the onset of antisocial
behavior (Chamberlain et al., 2016; Dotterer et al., 2021; Fishbein & Pease, 1994; Fishbein, 2001;
Moffitt, 1990).
Malnutrition is still an important issue in Indonesia. According to the results of Riskesdas
2018 (Ministry of Health of the Republic of Indonesia, 2019) it was revealed that the prevalence
of nutritional status based on the BB/U index in children aged 0-23 months was 3.9% suffering
from malnutrition and malnutrition as much as 13.8%. The prevalence of nutritional status based
on the TB/U index in children aged 0-23 months, revealed as many as 19.3% of short births and
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very short births of 11.5%. Meanwhile, in Papua Province, 2018 regional health research data
(Ministry of Health of the Republic of Indonesia, 2019) shows that the prevalence of stunted
children reaches 33.1%, while the 2021 Indonesian Nutritional Status Study (SSGI) reaches
29.5%. The condition of stunted children is widespread in most districts in Papua, where the
highest stunting prevalence is Dogiyai Regency (57.5%) and the lowest in Sarmi Regency (19%).
Similarly, Papua has the lowest Human Development Index (HDI) in Indonesia, at 60.62. This
situation is found in about two-thirds of all districts in Papua having HDI with a low – very low
category. This condition reflects the situation of stunting problems that can have a negative impact
on the quality of life (QoL) of children.
QoL children are important, not only as an investment in the future of society, but also
because children are an important group of themselves and deserve to experience well-being today
(Wallander & Koot, 2016). QoL measurements are critical in evaluating alternative treatments and
interventions and identifying children with special needs (Eiser, 1997) as well as the development
of better child welfare policies (OECD, 2021).
However, the definition of QoL varies widely and doesnot have an absolute consensus, some
of which are given in (Wallander & Koot, 2016). QoL is a multidimensional construct that includes
physical, mental, social and behavioral components of well-being and functioning. In addition,
QoL is a subjective perception of how an individual feels around himself that is attributed and not
attributed to health status (Barnes & Jenney, 2002). QoL reflects children's or families' views on
the impact of treatment, which are not directly linked to disease status or traditional clinical
measures of severity. Such a definition is based on the inadequacy of function or in the sense of
"conformity" between aspiration and experience. Therefore, evaluating QoL and understanding
the influence of health on individual QoL is part of the realized health care concept (Kostak, 2006)
The concept of multidimensional QoL has been echoed by the World Health Organization
(WHO), since 1949 by stating that health is not only free from diseases and or disorders, but also
a condition of good physical, mental and social health (Loonen et al., 2001; Spieth and Harris,
1996). Furthermore, in 1995, WHO recognized the importance of evaluating and improving the
QoL of society for the reason that people live longer than ever before and that health screenings,
must look beyond the causes of death and pain to examine the health relationship with individual
QoL, hence WHO recognizes the importance of evaluating and improving the QoL of society.
Researchers have changed the way they check health, looking beyond the causes of death and pain
to examine the health link with an individual's QoL. As people live longer than ever, researchers
have changed the way they check health by looking beyond the causes of death and pain to examine
the health link to an individual's QoL. The WHO then defines QoL as an individual's perception
of their position in life in the cultural context and value system in which they live and in relation
to their goals, expectations, standards, and concerns (WHO, 1998). When QoL is considered in
the context of health and disease, it is called Health-related quality of life (HRQOL). Current
researchers agree that HRQOL is multidimensional and includes domains related to physical,
mental, emotional, and social functioning as well as the social context in which people live
(Ferrans, 2005; Lin et al., 2013; Slabaugh et al., 2017)
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Several previous researchers have identified the role of environmental factors on children's
QoL. Improvingchildren's interactions with nature has positive benefits for health-related quality
of life (HRQOL) (Sherman, et al., 2005; Tillmann, et al., 2018). Meanwhile, Rezaei et al. (2021)
found that there was a significant negative relationship between the QoL of cerebral palsy children
and environmental barriers around the child. Kostak (2006) states that environmental factors
(including the condition of regional ecosystem zones) have a strong influence on the social and
psychological development of children. The child's QoL depends on the complex relationship
between the child himself and their social environment. The functions and behavior of children are
closely related to their social environment, which has been considered part of them. For this reason,
environmental factors such as family, relationships with peers, neighbors and health organizations
need to be considered. The results of a literature review from Gill (2014) support the view that
the environment provides a "balanced diet" for childhood experiences that promote healthy child
development, well-being and positive environmental attitudes and values.
Although there are quite a lot of studies that show the influence of the environment on the
quality of life related to child health (HRQOL), but still not many researchers examine how the
geographical context affects this relationship (Tillmann et al., 2018). The context of geography
becomes important because children begin to develop their sense of place during early childhood.
They have the curiosity and five senses to explore and manipulate matter in their environment to
understand the world around them. A sense of place then develops into a sense of belonging that
contributes to their overall social and emotional development (Brillante & Mankiw, 2015).
For the purposes of measuring HRQOL in child populations, Verrips et al. (1999)
recommended seven domains, plus emotional responses to health status problems, namely physical
complaints, motor function, autonomy function, cognitive function, social function, positive
mood, and negative mood. In this regard, this research is focused on assessing the situation of
children's HRQOL and assessing the role of various factors related to HRQOL for children under
five years old in various ecosystem zones in Papua Province. The study was conducted in four
districts representing three ecosystem zones, namely the mainland coastal zone (Merauke and
Sarmi Regencies), the middle plain zone (Nabire Regency), and the mountain zone (Jayawijaya
Regency).
METHOD
This study was designed cross-sectionally to study the dynamics of correlation between risk
factors and effects in the form of health status through a point time approach. In the context of this
study, the correlation dynamics of various latent variables or constructs are studied, which are
formed in the household investment model for the quality of life of the child. Each latent construct
has several measures or are referred to as indicators/observed variables. In this case a latent
construct is modeled as a factor underlying the related indicators. Latent constructs are intended,
namely the physical environment (A), social environment (B), maternal parenting (D),
environmental sanitation (E), disease control efforts (F), malnutrition (H), history of illness (I),
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child development (J) and quality of life of the child (K). The conceptual framework of the
structural model of Papuan child development, presented in Figure 1.
Figure 1. Structural Model Framework for Papuan Child Development
The study was conducted in Papua Province, namely in three ecosystem zones, namely the
mainland coastal zone (< 100 m asl), the medium plain zone (>100 - < 1000 m asl) and the
mountain zone (>1000 m asl). The selection of the study site was carried out based on a multistage
sampling procedure with stratification and cluster techniques. The sample size for the lowland
strata was 724 households, the temperate plains 381 households and the highlands 373 households,
bringing the total to 1481 households.
Primary data collection was carried out using structured interview techniques using
questionnaires, observations and measurements. Measurement of latent constructs of the physical
environment, used 34 indicators in nominal and ordinal scales, social environment 45 indicators
in nominal and ordinal scales, maternal parenting 5 indicators in ordinal scales, environmental
sanitation 11 indicators in nominal and ordinal scales, disease control efforts 35 indicators in
nominal and ordinal scales, malnutrition 4 indicators in ordinal scales, sick history 3 indicators in
ordinal scales, Child development 4 indicators in nominal scale and child quality of life 7 indicators
in likert scale. In-depth interviews were also conducted with community leaders at the research
site.
Each child's quality of life domain has a set of question sets, which are as many as 8 question
items about the child's perceived feelings in the last 30 days. Furthermore, the collected d ata,
analyzed using amultivariate nalysis, in the form of testing measurement models and structural
models. To test the prediction model of relational and causal relationships, Structural Equation
Modelling-Regression (SEM) with a partial least square (PLS) approach using the help of the
SmartPLS application version 3.2.9 was used. In addition, the Kruskal Wallis test is used to see
the difference in certain variables between ecosystem zones.
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RESULT AND DISCUSSION
The Quality of Life Situation of Papuan Children
The quality of life of children under five is measured using health-related quality of life
instruments, where each child's quality of life sector consists of 8 questions (Adaptation from
Verrips et al., 1999). The quality of life of a normal child and or at risk refers to the standards that
Skarr et al. (2002). The quality of life of the child is normal, if the total value of ≥ 65.48 (≥1
elementary school) and the quality of life of the child is "at risk" if the total value is <65.48. The
quality of life of children at risk, is intended to be children of toddler age from the results of
individual perspective measurements, who are suspected of having impaired quality of life (at
risk) in one or all sectors of quality of life.
The results showed that the average quality of life value of Papuan children was 66.89 ±
15.94; meaning that Papuan children are in a normal quality of life status (≥ value of 65.48). If it
is combined in the population of healthy children, that is, if it has an average total value of 81.38
± 15.90 (Skarr et al., 2002) then Papuan children cannot be classified into the population of healthy
children. Reviewed by ecosystem zone, it found that the average quality of life of children in the
coastal zone of the mainland was highest or better (73.69 ± 15.52) than that of children living in
the middle plains zone (66.49 ± 16.45) and the mountain zone (63.42 ± 17.93). Even children who
live in mountainous zones, generally are in the status of at risk (value <65.48) or have a risk of
experiencing impaired quality of life.
Table 1. Average Quality of Life Score of Papuan Toddlers by Child Quality of Life Sector and
Ecosystem Zone
Children's Quality of
Life Sector
Ecosystem Zones
Papua
Coastal
Mainland
Intermediate
Plains
Mountains
Physical Functions
81,56 ± 17,44
73.86 ± 18.97
74.44 ± 20.11
76.67 ± 18.54
Motor Functions
74,81 ± 21,97
69.28 ± 20.75
64.22 ± 24.07
68.76 ± 21.46
Autonomy Functions
75,60 ± 23,04
66.91 ± 23.67
61.78 ± 25.47
66.24 ± 22.59
Cognitive Function
67,16 ± 20,96
65.85 ± 18.36
59.51 ± 20.98
63.47 ± 19.32
Social Functions
76,95 ± 16,76
66.19 ± 24.21
60.52 ± 23.56
66.23 ± 22.81
Positive Mood
Function
77,28 ± 21,31
70.80 ± 20.22
69.69 ± 22.00
71.54 ± 19.51
Negative Mood
Function
62,49 ±
20,72
52.55 ± 19.32
53.79 ± 18.98
55.34 ± 19.28
Children's Quality of
Life
73,69 ± 15,52
66,49 ± 16,45
63,42 ± 17,93
66,89 ± 15,94
Source: Processed from Primary Data
The quality of life of Papuan children was reviewed according to the quality of life sectors
(Table 1), it was found that physical, motor, autonomic, social, and positive mood functions were
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in normal status, with an average score of ≥ 65.48. In contrast, cognitive function and negative
mood are in the status of at risk (value <65.48) or risk of experiencing impairment. Similarly,
based on ecosystem zones, cognitive function and negative mood of children in the mainland
coastal zone and the middle plains zone were found to be at risk. In contrast the motor,
autonomous, cognitive, social and negative mood functions of children in the mountainous zone
are at risk status (62.36 ± 15.24). This condition indicates that generally Papuan children
experience impaired negative mood function, especially children in the mountain zone experience
impaired motor, autonomic, cognitive, social and negative mood functions.
The distribution of Papuan toddlers according to the level of quality of life and ecosystem
zones, is presented in Table 2. It appears that the population of Papuan children with a risk of
quality of life disorders (at risk) reaches 50.57% and normal 49.43%. This incident is related to
unfavorable environmental conditions, including inadequate maternal parenting, inadequate
nutritional intake or even not getting adequate basic health services.
Table 2. Kruskal Wallis Test Results Distribution of Prevalence of Papuan Children According
to Quality of Life Level and Ecosystem Zone
Ecosystem Zones
Children's Quality of Life
Kruskal Wallis Test
Normal
(≥65.48)
At Risk
(≥65.48)
Mean Rank
p. Sig
Coastal Mainland
54.38
45.62
786,98
21,442 (P<0.01)
Intermediate Plains
47.51
52.49
729,99
Mountains
41.62
58.38
661,62
Papua
49.43
50.57
Source: Processed from Primary Data
The distribution of Papuan children identified as quality of life at risk according to ecosystem
zones, found the highest prevalence in the mountain zone, followed by the middle plains zone and
the mainland coastal zone. The results of the Kruskal Wallis test show that there are significant
differences between ecosystem zones in terms of children's quality of life. The prevalence of
children with quality of life at risk is more prevalent in mountainous zones than in other zones.
Structural Model of Children's Quality of Life
In order to identify the factors that play a role in influencing the quality of life of the child, a
hypothesis is formulated that "Physical environment, social environment, maternal parenting,
malnutrition, history of illness and child development have a direct or indirect effect on the quality
of life of the child."
The results of the evaluation of the structural model of the child's quality of life show that
together, factors of the physical environment, social environment, maternal parenting,
malnutrition, history of illness and child development, can explain the child's quality of life by
44.16% (R
2
: 0.441603), while the rest is explained by other factors. The magnitude of R
2
belongs
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to the category of large effect size because it has an R
2
value of greater than 0.26 (Cohen, 1988).
Furthermore, based on the results of the path parameter coefficient test, it was found that factors
of the physical environment, social environment, maternal parenting, malnutrition, history of
illness and child development had a direct significant effect on the quality of life of children with
T-values. Statistics above the rule of thumb of 1.64. Thus, the model of the structural equation of
the quality of life of the child can be written as follows:
Quality of Life of the Child (K)= 0.200875 Physical Environment (A) + 0.486745 Social
Environment (B) + 0.081597 Maternal Parenting (D) – 0.043471 Malnutrition (H) – 0.051840
Pain (I) + 0.073678 Child Development
The explanation of the structural model of the child's quality of life is as follows:
1) The physical environment, social environment, maternal parenting, malnutrition, illness and
child development significantly affect the quality of life of the child, especially in the domains
of quality of motor function, autonomy, cognitive, social and positive mood. If the six factors
together increase by one unit, the child's quality of life will increase by 0.747584 units. The
largest contribution to the value in a row is the social environment with a coefficient of β =
0.486745, followed by the physical environment with a coefficient of β= 0.200875, maternal
parenting with a coefficient of β= 0.081597, and child development with a coefficient of β=
0.073678.
2) Malnutrition constructs and a child's sick history have a significant negative influence on the
child's quality of life. An increase in one unit of each construct will decrease successively by
β = – 0.043471 and β= -0.051840 units of child quality of life
The above model of structural equations shows the direction and magnitude of the influence
of factors directly associated with the quality of life of the child. Figure 2 shows the association of
influences between factors present in the structural model of a child's quality of life, either directly
or indirectly.
Description: ------: Insignificant
____: Significant
Figure 2. Structural Model Test Results of Children's Quality of Life
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Structural Model of Children's Quality of Life Moderated Ecosystem Zone
The moderation effect test is intended to determine the presence or absence of interaction
between moderator variables and independent variables (Predictors) in influencing dependent
variables. It is known that variabel moderation is a variable that has a strong contingent effect with
the relationship of bound variables (Endogenous) and free variables (Exogenous). The purpose of
the existence of moderation variables, that is, to influence or change the initial relationship between
free variables and bound variables. The moderation variable used in this study was the ecosystem
zone type, which was tested against the relationship of various exogenous latent constructs in
influencing the child's quality of life.
The results of the path parameter coefficient test on the SmatPLS output, found a structural
model of the child's quality of life moderated by the ecosystem zone (Figure 2) is as follows:
1) Maternal parenting initially significantly affected the child's quality of life, but with the
inclusion of ecosystem zone-moderated interaction variables became insignificant with
a t-statistical value below the rule of thumb of 1.64.
2) The physical environment, social environment and development of children have a
significant effect on the quality of life of children, on the contrary, malnutrition and a
history of illness have a significant negative effect on the quality of life of children with
a t-statistical value above the rule of thumb of 1.64.
3) Zone-moderated interactions with maternal parenting, malnutrition and child
development did not significantly affect the child's quality of life with a t-statistical value
below the rule of thumb of 1.64. On the contrary, the interaction of ecosystem zones
with the physical environment and social environment has a significant negative effect
on the child's quality of life; Meanwhile, the interaction of ecosystem zones with a
history of illness had a significant effect on the quality of life of children with a T-
Statistic value above the rule of thumb of 1.64. Therefore, it can be concluded that
differences in ecosystem zones have a significant effect on the physical environment,
social environment and history of illness, thus encouraging children to be in certain
conditions of quality of life.
Referring to the results of the analysis above, a structural equation model of the quality of
life of children moderated by the ecosystem zone is obtained as follows:
Child Quality of Life = 0.842284 Physical Environment + 0.526949 Social Environment –
0.077993 Malnutrition – 0.193718 History of Illness + 0.103798 Child Development + 0.724209
Ecosystem Zone (Zonek) – 0.744882 A*Zonek – 0.075388 B*Zonek + 0.183360 I*Zonek
Spatially, structural models of children's quality of life indicate that the physical
environment, social environment, child development and ecosystem zone type can improve the
child's quality of life; On the contrary, malnutrition and a history of illness significantly suppress
the child's quality of life. However, at the level of certain ecosystem zones, it can moderate the
influence of the physical environment and the social environment so that the child's quality of life
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is low. Similarly, at the level of certain ecosystem zones can moderate the history of illness so that
the child's quality of life improves.
Discussion
This study has examined six factors related to the quality of life of Papuan children, namely
the physical environment, social environment, maternal parenting, history of illness, malnutrition
and child development. Together, these six factors were able to explain the total variation in
children's quality of life by 44.2%. This R
2
magnitude is included in the large effect size category
because it has an R
2
greater than 0.26 (Cohen, 1988). A similar study by Sitaresmi et al. (2022) in
Indonesia conducted in Sleman Regency, Yogyakarta, yielded lower R
2
results (0.128) for children
with acute health problems, younger age, history of low birth weight, abnormal childbirth, lower
paternal education levels, and government-paid insurance for low-income families. The same was
also found by Masini et al. (2021) who reported an R
2
smaller than 0.20. However, research by
Aksaralikitsunti & Sanmaneechai (2022) gives a greater R
2
, i.e. R
2
= 0.528 for Physical Health
and R
2
= 0.397 for Psychosocial Health. This difference in R
2
suggests that HRQoL in childhood
is a multidimensional construct with many subdimensions that can vary based on environmental,
social, cultural context and sample size (Masini et al., 2021).
Social environmental factors had the largest significant influence (48.7%) on children's
quality of life, followed by the physical environment 20.1%, maternal parenting 8.2%, child
development 7.4%, sick history -5.2%, and malnutrition -4.3%. The physical environment, social
environment and development of the child have a significant effect on the quality of life of the
child, on the contrary, malnutrition and a history of illness have a significant negative effect on the
quality of life of the child. However, differences in ecosystem zones have a significant effect on
the physical environment, social environment and sick history, thus encouraging children to be in
certain quality of life conditions. This is in line with previous research that the environment, such
as the physical condition of the house, the physical environment of the community, transportation,
and social support of the community can provide obstacles to the quality of a child's life (Rezaei
et al., 2021) or even improve the quality of life of the child (Kostak, 2006; Sherman et al., 2005;
Tillmann et al., 2018).
The contribution of the direct influence of malnutrition is relatively small, but it significantly
suppresses the quality of life of the child. In addition, malnutrition can indirectly suppress the
quality of life of children through an intermediate variable mechanism, namely child development.
It was previously revealed that malnutrition suppresses child development by -4.7%, which results
in the child's quality of life being not optimal. This situation is possible because the child's quality
of life is sensitive to changes in the child's development. The physical and intellectual development
of the child follows the growth of the child himself. This is in accordance with the opinion of
Barnes and Jenney (2002) that quality of life is a concept that is sensitive to changes in child
development. As a result of physical and intellectual development, it will follow the growth of the
child, where his perception of health and health will change.
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Malnourished children will show behavioral changes, including their interaction with their
environment decreases and results in a decrease in the child's quality of life, especially the quality
of motor function, autonomy, cognitive, social, and mood positive. Malnourished children
generally show decreased activity, fussiness and displeasure and low curiosity, which will
eventually experience hindered mental and social development. This is in line with previous
research findings that malnutrition has an influence on metabolic changes (Dipasquale et al., 2020;
Love, 1986; Thompson et al., 2020), decreased immune cell function (Alwarawrah et al., 2018),
as well as an impact on decreasing cognitive ability, brain performance as well as immunity and
susceptibility to infectious diseases (Sorhaindo & Feinstein, 2006).
On the other hand, malnutrition also has an impact on language delays (Khandelwa et al.,
2020), so that these children will experience difficulties in social interaction and problem solving
(Hay et al., 2009). Gibney et al. (2009) explains this condition by stating that malnourished
children will experience structural and functional changes in the brain. Stunted children who
experienced iron and zinc deficiency showed changes in behavior. These children showed
decreased activity, were more cranky and did not feel happy and did not show much curiosity (low
exploration instinct) when compared to children who were well nourished. Meanwhile, Liu et al.
(2004) state that the consequences of neurocognitive deficits due to malnutrition in turn contribute
to persistent externalization behavior problems throughout childhood and adolescence. Early
neurocognitive deficits are also predictors of the onset of antisocial behavior (Fishbein, 2001;
Fishbein & Pease, 1994; Liu et al., 2004; Liu, & Raine, 2006; Liu & Raine, 2017; Moffitt, 1990).
Malnutrition in children who are in their infancy has an effect on physical development
(Warsito et al., 2012) and intelligence (Aurora, 2021), which will eventually boil down to the
child's quality of life. In more severe and chronic circumstances, malnutrition causes impaired
body growth, smaller bodies followed by a small brain size. The number of cells in the brain
decreases and there is an immaturity and imperfection of biochemical organization in the brain.
This situation affects the development of children's intelligence (Aurora 2021; Ministry of Health,
2002). It is also stated that the brain is an organ used to think and the center of receiving external
stimuli, where this activity requires large amounts of nutrients. The brain is an organ that needs a
source of glucose fuel (Monosaccharide) and proportionally consumes the greatest energy
compared to other organs of the body. The brain also needs proteins, essential fatty acids (Steiner,
2019), as well as various vitamins and minerals. This nutrient is used to multiply nerve cells,
facilitate the passage of nerves (Neurotransmitters) and various activities related to other brain
functions.
Related to the course of nerves,proteins and amino acids play an important role in influencing
brain function and mental health. Many of the neurotransmitters in the brain are made from amino
acids, including the neurotransmitter dopamine made from tyrosine and neurotransmitter serotonin
made from tryptophan. If the required amino acids are not available, then the level of certain
neurotransmitters in the brain will decrease, and both brain function and mood will be affected.
When the body is deficient in tryptophan then serotonin production is not enough, and low brain
serotonin levels are associated with low mood, even some individuals show an aggressive attitude.
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2023
Regarding the findings of this study, it shows that Papuan children generally experience negative
mood function disorders, namely sad, aggressive, quick-tempered attitudes, anxiety, jealousy and
worry. This is a phenomenon due to the high prevalence of children under five experiencing
consumption deficits (Energy and protein) as well as chronic and acute malnutrition problems in
Papua.
Another interesting thing about the findings of this study is that when the moderation
variables of ecosystem zone type were included in the analysis model, malnutrition was found to
remain as one of the factors that suppressed the child's quality of life. The contribution of the
influence of malnutrition moderated by the ecosystem zone variable on the child's quality of life
increased, i.e. initially by -4.3% to -7.8%, while the interaction of the ecosystem zone with
malnutrition was insignificantly associated with the child's quality of life. This situation indicates
that all types of ecosystem zones in Papua have the potential to increase the incidence of
malnutrition so as to reduce the quality of life of children. This is relevant because it is related to
the existence of ecosystem services.
Papua's ecosystem, which consists of three types of ecosystem zones (coastal land, middle
plains and mountains) is dominated by forests with high biological and non-biological abundances,
in addition to the vast land resources for agricultural activities. The people of Papua region make
available forest and land resources as a source of life, which they receive in various forms of
provisional, regulatory, cultural and supporting services as expressed in the Report of the
Conceptual Framwork Millennium Ecosystem Assessment Working Group (2005). Papuan
children have been invited and introduced by their parents to the surrounding natural resources
(Forests and agriculture) from an early age so that they become a place to play and learn, even
until they reach adulthood. The habit of living in such an ecosystem environment, it is perceived
that society can improve the development and quality of life of children. However, forests and
available land can also have negative influences on human health (Including children's quality of
life), especially related to unwise forest exploitation.
CIFOR (2007) revealed that forests are a source of nuts, fruits, shrubs, roots, mushrooms,
and animals of various sizes. Many types of biological resources that live in forests contain
nutrients important for human health. Forests are also a source of medicines, including
contraceptive compounds, muscle relaxants, anti-bacterial compounds, aprodicials, and drugs used
to treat heart failure, malaria, cancer, and other diseases. However, food sources from forests have
the potential to threaten health, including tropical roots (Cassava) containing little cyanide and
aflatoxin toxins that are carcinogenic in corn or other foodstuffs contaminated by fungi. In
addition, forest exploitation causes an increase in malaria, especially during logging, which causes
puddles so that mosquitoes breed.
As a result of unwise exploitation of forests and land, it will lead to degradation in terms of
the ability of ecosystem services. The decline in the potential of ecosystem services will have far-
reaching implications for human life, including the quality of life of children. Increased
malnutrition is a consequence of the declining ability of ecosystem services to provide food, water
sources, disease regulation, education and so on.
Structural Model of Papuan Children’s Quality of Life in Different Ecosystem Zones in Papua
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The epidemiological evidence of the quality of life of Papuan children above shows the high
prevalence of children with impaired physical, motor, autonomic, social, cognitive, positive mood
and negative mood. The determinants of the causes of impaired quality of life for Papuan children
are stunted and a history of illness, where malnutrition contributes -4.3%. In addition, the
interaction of ecosystem zones with the physical environment and social environment can also
worsen the quality of life of children, so the handling of these factors needs to be prioritized.
Minimizing and resolving the quality disturbances of Papuan toddlers above, it is considered
important to do, namely:
1) Optimizing children's educational potential is intended as an effort to increase children's
potential to learn from various complementary resources available. It is intended that
children have the ability to interconnect and take advantage of all the complementary
resources provided by each learning environment, both formal and informal such as play
groups, ECCE (early childhood education), and so on. According to Toisuta (2009) that
before entering formal schooling, children have been formed and influenced by their
social and cultural context which is the fundation of their personality and intellectual
growth, namely a rich and value-laden socio-religious experience, traditional patterns in
the family that are the basis for children to grow, understanding and use of mother
tongue in associations and karmic systems of relationships with others, and other
determinants in the form of nutritional status and health. Disorders of nerves and brain
cells caused by malnutrition and disease have a critical influence on cognitive,
emotional and other motor functions. Thus education is a matter of compatibility (read
probability of learning), that is, whether a child's background and experience are
compatible with societal expectations and or according to the standards imposed to be
able to enter the initial level of formal education. If the child's context and background
meet the intended expectations, the probability (success) of the child learning is high. If
the opposite is not complete or there is only minimal conformity then the probability of
achieving effective learning is low. For this reason, Conny (2009) recommends an
overhaul of how to educate and how to teach children by implementing brain-based
learning. The right hemisphere is more lateral and divergent, while the left hemisphere
is vertical and convergent. Both hemispheres of the brain must develop in balance
through various learning experiences. This reciprocal learning experience points to the
flexibility of the brain and the flexibility of human behavior.
2) Empowering the community ecosystem environment in managing forest and land
resources to improve the quality of life of children. The ecosystem environment of
society is intended to be a population that occupies a certain geographical area, has a
social structure, organization and interaction between individuals and their
organizations. The community ecosystem environment has three main components
(Junanto, 2011), namely human-society (Has social, economic, political, educational
and trust values), manufacturing components (Human work in the form of buildings,
equipment machines, and so on) and natural components (soil, water, forests, minerals
Structural Model of Papuan Children’s Quality of Life in Different Ecosystem Zones in Papua
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and various other organic systems) that provide services for the survival of human
components and their work. These three components of the ecosystem are an
interdependent whole, so that efforts to optimize one component and ignore the other,
result in the expected results not being achieved. Related to efforts to improve the quality
of life of children, it is known that all types of ecosystem zones in Papua have forest and
land resources with high biological and non-biological abundances. However, currently
it is alleged that forests and lands have been degraded due to unwise exploitation,
resulting in forests and land not being optimal in providing various ecosystem services
to improve community welfare, including improving the quality of life of children. A
strategic step is to optimize the role of environmental components of community
ecosystems, namely empowering people and their works to develop in line with the
carrying capacity of natural resources (Forests and land). Thus, forest and land resources
are maintained in function, namely providing various services for improving community
welfare, including improving the quality of life of children.
CONCLUSION
The quality of life of Papuan children is in normal quality of life status, but has not been
classified into the population of healthy children. The population of Papuan children with the risk
of quality of life disorders (at risk) reaches 50.57% and is the most in the mountain zone. Papuan
children generally experience impaired negative mood function, while children in the mountainous
zone experience impaired motor, autonomic, cognitive, social and negative mood functions.
Improving the physical environment, social environment, maternal parenting and child
development will improve the quality of life of the child, especially the quality of motor functions,
autonomy, social, cognitive, and positive mood. On the contrary, malnutrition and a history of
illness cause the child's quality of life to be low. The factors that most strongly influence on the
quality of life of the child are the social environment in the form of indicators of the activities of
basic health programs (weighing, immunization, supplementary feeding) and the mother's
perception of the disease. In contrast, malnutrition in the form of short child indicators contributes
the least, but significantly suppresses the child's quality of life to be low.
Malnutrition in the form of short children moderated by ecosystem zones has the potential to
increase the prevalence of short children, resulting in a significant decrease in the quality of life of
children by -7.8%; While a history of illness worsens malnutrition through a decrease in nutritional
intake and ultimately suppresses the child's quality of life to be low. The synergistic interaction of
malnutrition and a history of illness results in a high incidence of children's quality of life at risk.
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