Corresponding Author: Mayang
Rizqia Diningtyas
E-mail: [email protected]
INTRODUCTION
Food insecurity is a global issue and its alleviation
is one of Indonesia's priorities (Suryana, 2014). This issue is defined in the 2030 SDGs target 2.1,
namely zero hunger and achieving food security for all people to food that is
safe, nutritious, and sufficient throughout the year, especially for the poor
and those in vulnerable situations, including babies (Prayitno et al., 2022). However, now, this problem is still a major challenge. Even though it has
shown an increase in food security, Indonesia still needs to be higher than
other countries. If seen from the Global Food Security Index in 2021,
Indonesia's food security score is 59.2 percent. It is ranked 69 out of 113
countries worldwide (Megantara & Prasodjo, 2021). Even if you look at the
changes compared to 2020, Indonesia is in the second worst place after Uruguay,
which has dropped 12 ranks.
One of the indicators to see
the achievement of food security in Indonesia is using moderate and severe food
insecurity based on the experience scale produced by the Central Bureau of
Statistics (Hannavi, 2018). In 2021 it will be 4.79
percent. This means there are 4 to 5 people out of 100 unable to access food
continuously during the last year. In addition, there is also a Food Security
Index (IKP) produced by the Food Security Agency. There are still disparities
in food security between provinces. In Indonesia's western and central parts,
they are already very resistant and food secure. However, in eastern Indonesia,
they are very food insecure. This indicates Indonesia has not achieved overall
food security (Agustino & Widodo, 2022).
Food security that has not been
achieved due to a lack of continuous access to nutritious and sufficient food
can be at greater risk for malnutrition. Children may be affected even when
food insecurity is only at the household level. Indonesia is still facing
nutritional problems, especially among children. Although the trend is
decreasing, the prevalence of stunting (low height for age) and wasting (low
weight for height) in children under five years old (toddlers) is still quite
high. Based on the BPS publication (2021), the prevalence of toddler stunting
in 2019 was 27.67, as well as the prevalence of toddler wasting in 2019 of 7.4
percent.
Various kinds of consequences
can arise from food insecurity, one of which is health. There is a relationship between food insecurity and health.
Food insecurity can affect physical, mental, and social health and the quality
of life directly or indirectly due to malnutrition (Gundersen &
Ziliak, 2015). Food insecurity can be analyzed from the individual,
household, to country levels. When households tend to be food insecure,
household members will tend to have poor health conditions. This signals that a
country with high food insecurity will have an increasingly unhealthy
population.
When viewed by age group, the under-five population
has the second highest health complaints after the elderly, namely 34.92
percent in 2021. Even though this figure has decreased compared to 2019 which
reached 64.71 percent, if you look at the absolute figure it is still quite
large, namely around 7 million more children with health complaints. In
children aged 0-19, the percentage of health complaints decreased with age and
increased again in the age group of 20 to 69 years and over.
Studies on food insecurity and health issues are
important to research because everyone and households should have equal
opportunities to access adequate and nutritious food on an ongoing basis for a
healthy life. There have been many studies analyzing the impact of food
insecurity on the health of children under five across countries. Food
insecurity is significantly related to poor child health (Wardani et al., 2020). Several other studies have also explained the link
between toddlers living in food-insecure households and increased incidence of
diabetes, hypertension, anemia, stunting, and childhood obesity (Gundersen &
Ziliak, 2018); (Thomas et al., 2019).
In Indonesia, studies on food insecurity on health
have also been carried out. However, they have not specifically explained the
relationship to the age group of children. The effect of food insecurity on
health outcomes has been carried out but has not specifically explained health
in children (Sari & Nachrowi,
2022). Even though children's health is important,
especially during the golden age or the first 1000 days, health at the
beginning of life will affect health during adolescence and adulthood. Health
in children also has a high return on investment. With good health, they can
get good jobs and income, which determines the quality of the next generation
(Mayer-Foulkes, 2004).
In addition, it is important to analyze food
insecurity on health in the age group of children because there are fundamental
differences between children and adults. Some of the differences such as anatomical structure
and function of biochemistry, immunology, and physiology. Children tend to be
more susceptible to disease. When exposed to the same disease, more severe
symptoms will be felt in children than in adults (Marzuki et al., 2021). In addition, households with children are more
vulnerable to food insecurity. The percentage of food-insecure households with
children is greater than households without children, at 14.8 percent and 8.8
percent, respectively (Yunita, 2021).
In analyzing health, another important variable that
needs to be included is immunization. This is because immunization is a
preventive step that aims to increase immunity both in the short and long term.
Immunization not only prevents and reduces the number of morbidity, disability,
and death from the disease as well as the formation of herd immunity. The
immunization variable was ignored in the previous study, so it was suspected
that an omitted variable bias would arise. Not include immunization variables
because there is missing information due to using samples across the individual
age range (Sari & Nachrowi,
2022). Therefore, it is important to include immunization variables in analyzing
health determinants in toddlers.
Based on the background above, this study aims
to identify the relationship between the level of food insecurity and the
health of toddlers by using the order logit regression model from the March
2021 Susenas data.
METHODS
This research uses Susenas
data for March 2021, conducted by the Central Bureau of Statistics (BPS). The
data used in this study is cross-sectional data at the individual level. The
health outcome variable used in this study described health complaints during
the last month in children aged 0 to 59 months. Health complaints (heat, cough,
runny nose, diarrhea, dizziness, chronic illness, or others). A more severe
health condition is characterized by health complaints that interfere with
work, school, or daily activities. This health complaint variable is classified
into three categories: there are no health complaints, and there are health
complaints that do not interfere with daily activities. There are health
complaints that interfere with daily activities.
The main independent variable used is food
insecurity, measured by eight access-to-food questions. The question is adapted
from the Food Insecurity Experience Scale (FIES) developed by FAO's Voices of
the Hungry (VoH). There are four possible answers, including Yes, No, Do not
know, and Refuse to answer (questions in the attachment). The classification of
levels of food insecurity follows Ballard et al. (2005); if all questions are
answered no, then the household is classified as food secure; if questions 1 to
3 have yes answers (partially or completely) and no answers to questions 4 to
8, then the household is classified as mild food insecure; if questions 4 to 6
have yes answers (partially or completely) and no answers to questions 7 to 8,
then the household is classified as moderate food insecurity. If questions 7 to
8 have a yes answer (partially or completely), the household is classified as
severely food insecure.
The unit of
analysis in this study is individuals aged 0 to 59 months (4 years). The
Susenas questionnaire is asked at the household level for information on food
insecurity, so it is assumed that all individuals in the same household have
experienced the same food insecurity. The method used is descriptive and
inferential analysis. Descriptive analysis is used to see an overview of the
existing conditions of the variables that will be used in further processing by
analyzing trends, patterns, and differences through numbers or percentages, or
graphs. While inferential analysis is used to answer research objectives in
analyzing the relationship between variables.
The dependent
variable used in this study is categorical, namely toddler health complaints
which are divided into three categories, namely code 0 if there are no health
complaints; code 1 if there is a health complaint but does not interfere with
daily activities; and code 2 if there are health complaints that interfere with
daily activities. Of the three categories, it shows that there is a level of
health in toddlers where the higher the code, the more severe the health
complaints experienced by the toddler. Assuming that the errors have a logistic
distribution, the analysis used to determine the determinants of the health of
these toddlers uses an ordered logistic regression model, as follows:
Where i is the number of samples, 1, �, n, and
ε are the error terms. Children's health outcomes using a toddler health
complaint (CH) approach. This indicates that toddlers who have complaints have
unhealthy conditions. Then F is food consumption in quality and quantity using
the household food insecurity approach, which indicates that the more food
insecurity a household has, the lower the food consumption. The important
control variable I am the immunization status of children under five, whether
they have been immunized or not for other control variables used in this study,
namely the individual characteristics of toddler X such as gender, age and
health insurance, Q's household characteristics such as smoking status,
sanitation, drinking water sources, water shortage status and food assistance
and the characteristics of M's biological mother such as education, marital
status, and working status.
A coefficient value
of βi will be generated from the logistic regression model results.
However, the coefficient values in the logistic regression analysis cannot be
used to make direct interpretations. In order to be interpreted, it is
necessary to transform the calculation of each resulting estimated coefficient
to obtain the odds ratio (or) value.
RESULTS AND DISCUSSION
Before analysis, a Chow Test was carried out to see if
there were structural differences between toddlers who lived with their
biological mothers and those who did not. Based on the results of the Chow
Test, it can be concluded that there is a statistically significant difference
at the 5 percent alpha level, so this study will focus only on toddlers who
live with their biological mothers. Based on these criteria, the number of
samples used was 88,545 individuals.
Overall, 69 percent
of toddlers experienced health complaints during the last month and the
remaining 31 percent had health complaints during the last month. Based on the
existence of health complaints, it can be examined more deeply whether these
complaints interfere with daily activities or not, such as playing or
preschool. Toddler health complaints are classified into two categories,
namely, health complaints that do not interfere with daily activities, and there
are health complaints that interfere with daily health. Overall, 16 percent had
health complaints that did not bother them and 15 percent had health complaints
that bothered them.
About 76 percent of children under five live in
food-insecure households, and 24 percent live in food-insecure families. Of the
under-fives who live in food insecure households, when viewed from the level of
food insecurity, it is dominated by mild food insecurity at 17 percent, then
moderate food insecurity at 5 percent, and severe food insecurity at 2 percent.
Individual
characteristics described in this study are immunization status, age, gender,
and ownership of under-five health insurance. Overall, the percentage of
toddlers who were immunized was 59 percent while the rest did not carry out
immunizations at all. If seen based on age characteristics, in this study the
average age of toddlers was 2 years. In this study, the percentage of toddlers
who do not have health insurance is 51.63 percent. Free health insurance comes
from central and regional government assistance, namely BPJS PBI and Jamkesda,
with a total of 28.98 percent.
In contrast, health insurance is paid independently for
government and private services. Alternatively, company facilities where their
parents work, namely 19.66 percent. If based on gender, as a whole sample, the
percentage of male toddlers is greater than that of females. The percentage of
toddler boys is 52 percent, and girls are 48 percent.
Household characteristics are also differentiated according
to sanitation facilities and proper drinking water sources. Households with
proper sanitation, namely households with facilities for defecation alone or
with certain households with the type of toilet used is a gooseneck or
plengsengan with a lid and a place for final disposal of feces in the form of a
septic tank or Waste Management Agency (WWTP). The percentage of children under
five in households with inadequate sanitation and drinking water sources is
29.11 percent and 31.18 percent, respectively. The percentage of children under
five living in households that have experienced water shortages is 4.38
percent. As much as 70.34 percent of children under five live in households
where there is at least one member of the household who smokes.
The mother's characteristics that will be
explained are the last level of education, marital status, and working status.
Toddlers dominated the sample in this study with biological mothers with
secondary school (junior high and high school) levels, namely 56.12 percent,
then those who had never attended school and elementary school level (SD) of
22.95 percent and tertiary level of 20. .93 percent. Based on marital status,
the overall sample of children under five whose mothers had been married was
2.48 percent. Meanwhile, based on their working status, the sample in the study
was more than half whose mothers did not work, namely 57.47 percent.
Table 2. β Coefficient Estimation Results with Logit Order
|
Variable
|
Specifications 1
|
Specifications 2
|
Specifications 3
|
|
(1)
|
(2)
|
(3)
|
(4)
|
|
Food Insecurity
|
|
|
|
|
light
|
0.368***
|
0.364***
|
0.361***
|
|
|
(0.024)
|
(0.024)
|
(0.024)
|
|
currently
|
0.226***
|
0.225***
|
0.221***
|
|
|
(0.042)
|
(0.042)
|
(0.042)
|
|
critical
|
0.215***
|
0.210***
|
0.210***
|
|
|
(0.059)
|
(0.060)
|
(0.060)
|
|
|
|
|
|
|
Non-Immunization Status
|
0.036**
|
0.032*
|
0.034**
|
|
|
(0.017)
|
(0.017)
|
(0.017)
|
|
FI*immune
|
|
|
|
|
Light
|
0.001
|
0.001
|
0.002
|
|
|
(0.037)
|
(0.037)
|
(0.037)
|
|
Currently
|
0.211***
|
0.208***
|
0.213***
|
|
|
(0.064)
|
(0.064)
|
(0.064)
|
|
Critical
|
0.085
|
0.080
|
0.083
|
|
|
(0.090)
|
(0.091)
|
(0.091)
|
|
Inpatient
|
0.
479***
|
0.474***
|
0.475***
|
|
|
(0.034)
|
(0.034)
|
(0.034)
|
|
Jamkes
|
|
|
|
|
Help
|
0.144***
|
0.139***
|
0.138***
|
|
|
(0.016)
|
(0.016)
|
(0.016)
|
|
Non-Aid
|
0.001
|
0.001
|
0.007
|
|
|
(0.018)
|
(0.020)
|
(0.021)
|
|
Toddler Gender
|
0.045***
|
0.046***
|
0.046***
|
|
|
(0.014)
|
(0.014)
|
(0.014)
|
|
Toddler Age
|
0.010*
|
0.022**
|
0.005
|
|
|
(0.005)
|
(0.005)
|
(0.005)
|
|
Proper sanitation
|
|
0.038**
|
0.040***
|
|
|
|
(0.016)
|
(0.016)
|
|
Drink decent
|
|
0.129***
|
0.134***
|
|
|
|
(0.016)
|
(0.016)
|
|
Lack of water
|
|
0.123***
|
0.121***
|
|
|
|
(0.034)
|
(0.034)
|
|
Food aid
|
|
0.100***
|
0.096***
|
|
|
|
(0.019)
|
(0.019)
|
|
Smoker's household
|
|
0.128***
|
0.123***
|
|
|
|
(0.015)
|
(0.016)
|
|
Mother's education
|
|
|
|
|
Middle-High School
|
|
|
0.026
|
|
|
|
|
(0.018)
|
|
> high school
|
|
|
-0.073***
|
|
|
|
|
(0.023)
|
|
Mother's marital status
|
|
|
0.089*
|
|
|
|
|
(0.047)
|
|
Mother's Working Status
|
|
|
0.107***
|
|
|
|
|
(0.015)
|
|
cut1
|
1,001
|
1230
|
1.355
|
|
|
(0.019)
|
(0.027)
|
(0.054)
|
|
cut2
|
1947
|
2.177
|
2,302
|
|
|
(0.020)
|
(0.028)
|
(0.055)
|
|
Number of Samples
|
88545
|
88545
|
88545
|
|
Prob > chi2
|
0.0000
|
0.0000
|
0.0000
|
|
Pseudo R2
|
0.0053
|
0.0064
|
0.0069
|
|
LL
|
-73675.43
|
-73588.83
|
-73554.72
|
|
AIC
|
147378.9
|
147215.7
|
147155.4
|
|
BIC
|
147510.3
|
147394.1
|
147371.4
|
|
|
|
|
|
*90% ; **95%; ***99%
Source: Susenas
2021, processed
The inferential analysis used in this study is ordered
logistic regression. Logistic order regression is a method used to see the
relationship between variables with the dependent variable, which has more than
two categories and levels. Model selection and robustness tests are carried out
by conducting the LR test and checking the consistency of the coefficient
values and the direction of the variable of interest. This test is carried out
by entering the control variable in stages.
Specification 1 only includes control variables for
individual characteristics. A control variable for household characteristics is
added in specification two. Finally, a control variable for biological mother
characteristics is added in specification three. Based on the results of the LR
test, the largest pseudo R2 value, the largest log-likelihood value, and the
smallest AIC and BIC values, the model chosen for further analysis is
specification 3. The results of order logit regression can also be analyzed using the odds ratio (or) value.
Table 3. Estimation of Odd Ratio Equation Order Logit
|
Variable
|
Specifications 3
Odd Ratio
|
|
(1)
|
(2)
|
|
Food Insecurity
|
|
|
light
|
1.434***
|
|
|
(0.035)
|
|
currently
|
1.248***
|
|
|
(0.053)
|
|
critical
|
1.234***
|
|
|
(0.074)
|
|
|
|
|
Non-Immunization Status
|
1,034*
|
|
|
(0.018)
|
|
FI_immune
|
|
|
Light
|
1,002
|
|
|
(0.037)
|
|
Currently
|
1.238***
|
|
|
(0.079)
|
|
Critical
|
1,086
|
|
|
(0.099)
|
|
Inpatient
|
1.609***
|
|
|
(0.055)
|
|
Jamkes
|
|
|
Help
|
1.148***
|
|
|
(0.019)
|
|
Non-Aid
|
1.007
|
|
|
(0.021)
|
|
Toddler Gender
|
1.047***
|
|
|
(0.015)
|
|
Toddler Age
|
1006
|
|
|
(0.005)
|
|
Proper sanitation
|
1,041**
|
|
|
(0.017)
|
|
Drink decent
|
1.143***
|
|
|
(0.019)
|
|
Lack of water
|
0.128***
|
|
|
(0.039)
|
|
Food aid
|
1.101***
|
|
|
(0.021)
|
|
Smoker's household
|
1.131***
|
|
|
(0.018)
|
|
Mother's education
|
|
|
Middle-High School
|
1027
|
|
|
(0.018)
|
|
> high school
|
0.928***
|
|
|
(0.022)
|
|
Mother's marital status
|
1,093*
|
|
|
(0.051)
|
|
Mother's Working Status
|
1.113***
|
|
|
(0.016)
|
*90% ; **95%; ***99%
Source: Susenas 2021, processed
The follow-up analysis
aims to see the effect of household food insecurity on children's health
according to per capita expenditure which is divided into three categories,
namely the low, middle, and high groups. This aims to confirm that food
insecurity indicates that the community lives in a financially limited society.
Table 4. Estimation of Coefficient Value (β) and Odd
Ratio (OR)
Equation Order Logit based on Per Capita Spending Group
|
Variable
|
Per Capita Expenditure Level
|
|
|
Low
|
Intermediate
|
On
|
|
|
β
|
OR
|
β
|
OR
|
β
|
OR
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
(6)
|
(7)
|
|
Food Insecurity
|
|
|
|
|
|
|
|
Light
|
0.414***
|
1.513***
|
0.313***
|
1.368***
|
0.393***
|
1,482***
|
|
(0.033)
|
(0.050)
|
(0.041)
|
(0.057)
|
(0.091)
|
(0.135)
|
|
Currently
|
0.274***
|
1.315***
|
0.194**
|
1,214**
|
0.155
|
1.168
|
|
(0.052)
|
(0.069)
|
(0.078)
|
(0.094)
|
(0.218)
|
(0.255)
|
|
Critical
|
0.238***
|
1.269***
|
0.280**
|
1.323**
|
-0.054
|
0947
|
|
(0.074)
|
(0.094)
|
(0.111)
|
(0.147)
|
(0.288)
|
(0.273)
|
|
Non-Immunization Status
|
-0.002
|
0997
|
0.083***
|
1,087***
|
0.021
|
1,022
|
|
|
(0.027)
|
(0.027)
|
(0.027)
|
(0.029)
|
(0.043)
|
(0.040)
|
|
FI*immune
|
|
|
|
|
|
|
|
Light
|
-0.015
|
0.985
|
0.021
|
1021
|
0.122
|
1,129
|
|
|
(0.050)
|
(0.050)
|
(0.063)
|
(0.064)
|
(0.146)
|
(0.165)
|
|
Currently
|
0.250***
|
1.284***
|
0.166
|
1,181
|
0.209
|
1,233
|
|
|
(0.078)
|
(0.101)
|
(0.122)
|
(0.144)
|
(0.328)
|
(0.404)
|
|
Critical
|
0.062
|
1,064
|
0.178
|
1,195
|
0.040
|
1040
|
|
|
(0.112)
|
(0.119)
|
(0.170)
|
(0.203)
|
(0.447)
|
(0.465)
|
|
Inpatient
|
0.0497***
|
1.645***
|
0.0482***
|
1,620***
|
0.0418***
|
1.519***
|
|
|
(0.508)
|
(0.095)
|
(0.053)
|
(0.086)
|
(0.070)
|
(0.107)
|
*90% ; **95%; ***99%
Source: processing results
Most of the variables are significant at various levels
of significance. In contrast, the variables that are not significant are the
interaction variables between the levels of mild and severe food insecurity and
immunization, non-assisted health insurance, toddler age, mother's education at
the junior secondary level (SMP/equivalent) to upper secondary (SMA/ equal) and
the mother's marital status.
The direction or sign of the coefficient can only
interpret analysis based on the value of the beta coefficient. The food
insecurity variable has a positive sign in both equation models, which means
that toddlers living in households with mild, moderate, and severe food
insecurity have a greater chance of experiencing more severe health complaints
compared to toddlers living in food-insecure households. Households prone to
light food have concerns that they will not have enough food and will still be
able to eat even with a small variety of food that can affect the health of
their toddlers. This finding aligns with the research (Handriyanti &
Fitriani, 2021) that
children living in food-insecure households have a greater chance of
experiencing poor health conditions than those in food-insecure households.
These results are consistent after checking the robustness in several model
conditions.
Based on the odds ratio, the more severe the level of
household food insecurity, the smaller the value of or. Toddlers living in mild
food insecure households have a 1.434 times chance of toddlers living in food
insecure households experiencing health complaints getting worse, while
toddlers living in moderately food insecure households have a 1.248 times
chance of toddlers living in a mild food insecure household. food insecurity
for increasingly severe health complaints. Toddlers living in severely food
insecure households have a 1.234 times chance that toddlers living in food
insecure households experience health complaints getting worse. This indicates
that households that are bland and food insecure, even without hunger, are very
vulnerable to affecting the health of their toddlers.
Immunization status and ownership of health insurance
assistance for toddlers and toddlers of the male sex have a value of or more
than 1, which means they have a greater chance of health complaints. Toddlers
who do not get immunizations have a 1,034 times greater chance of experiencing
health complaints getting worse. Toddlers with health insurance sourced from
government assistance have 1.148 times the chance of toddlers who do not have
health insurance experiencing health complaints getting worse. Toddlers who are
male have 1,047 times the chance of women experiencing health complaints that
interfere with daily activities.
The existence of an
interaction variable between food insecurity and immunization indicates that
there is a conditional relationship between household food insecurity on
children's health which is determined by their immunization status. The chance
of experiencing health complaints in toddlers living in moderately
food-insecure households is greater than in toddlers living in mildly
vulnerable households. Toddlers who live in moderate food insecure households
and receive immunizations have a 1.543 times chance of toddlers who do not get
immunizations experiencing health complaints. However, for toddlers who live in
severely food insecure households, the chance is smaller than the others, and
the interaction variable with immunization is not significant. This indicates
that toddlers living in severe food insecurity are susceptible to disease, so
immunization does not have much effect on increasing the toddler's immune
system.
The higher the per capita expenditure group, the more
variable household food insecurity at medium and low levels is increasingly
insignificant. In the upper group, children under five living in moderate and
severe food insecurity households were not statistically significant for health
complaints; only mild food insecurity levels were statistically significant.
The low per capita expenditure group has almost the same pattern as the overall
model. In the low group of households, mild, moderate, and severe food
insecurity was statistically significant to children's health complaints.
In addition, household food insecurity on children's
health according to per capita expenditure can also show a comparison of
objective poverty and subjective poverty. FAO combines objective and subjective
aspects of food insecurity. Three of the FIES questions can be considered to
refer to subjective perceptions. In contrast, the other five questions ask
about objective experiences due to a lack of money or other resources (Herlina et al., 2020). The findings of this study prove that there is a
subjective perception that food insecurity can not only be experienced by
households who have a low economy but can also occur in upper-income households
have high incomes, which is in line with (Dudek &
Myszkowska-Ryciak, 2020).
The immunization variable was not statistically
significant for children's health complaints in the low and high per capita
expenditure groups. It was only significant in the medium per capita
expenditure group. Furthermore, the effect of the variable health insurance
assistance in the three groups of per capita expenditure also shows the same
pattern as the entire model, which is statistically significant and positively
related.
Based on the odds ratio, the level of light food
insecurity is greatest in households with the low per capita expenditure group,
then the upper group, and lastly, the middle group. In the low per capita
expenditure group, toddlers living in mild food insecure households have a
1.513 times chance of toddlers living in food insecure households experiencing
severe health complaints. In the upper per capita expenditure group, toddlers
living in mild food insecure households have 1.482 times the chance of toddlers
living in food insecure households experiencing health complaints getting
worse. In the middle per capita expenditure group, toddlers living in mildly
food insecure households have a 1.375 times chance that toddlers living in food
insecure households experience health complaints getting worse.
CONCLUSION
In this study, it can be concluded that
household food insecurity is related to toddler health complaints. Based on the
food insecurity level, the order logit regression analysis results prove that
food insecurity is significant and has a positive effect on health complaints.
Food insecurity occurs not only in low-income household groups but also in
high-income household groups.
Other determinants that statistically
significantly influence children's health complaints are immunization,
government-assisted health insurance, gender, sanitation and proper drinking
water sources, water shortage status, food assistance, smoking household
status, mother's education above high school/equivalent, status marriage, and
working status of the mother. When viewed from the direction of influence, a
mother's education above SMA/equivalent has a negative influence on children's
health complaints, while immunization, government assistance health insurance,
gender, sanitation, proper drinking water sources, water shortage status, food
assistance, smoker's household status, marital status and working status of the
mother have a positive influence on children's health complaints.
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