Correspondent: Roi Ocrico Isa
Email: [email protected]
INTRODUCTION
Alcohol is a dangerous psychoactive substance, a
contributing factor in many diseases and injuries. Relatively young people are
at risk of fatal injuries due to alcohol abuse. Every year, there are 3 million
or 5.3% of deaths due to alcohol consumption worldwide (WHO,
2023c). More than a quarter of the world's
population aged 15-19 years (adolescents) drink alcohol, with males being the
most at risk (WHO,
2023a). Based on age, junior high school
(SMP, Sekolah Menengah Pertama) and senior high school (SMA, Sekolah
Menengah Atas) students are among adolescents.
In Indonesia, the alcohol consumption behavior of the
population aged ten years and above tends to increase from 3.0% in 2007 to 3.3%
in 2018. North Sulawesi has the highest percentage of alcohol consumption at
16% based on 2018 research, followed by East Nusa Tenggara at 15.6% and Bali at
14%. Based on characteristics, nationally, the alcohol consumption behavior of
the population aged 10-14 years was 0.3%, and the age group 15-19 years was
3.7%, while in North Sulawesi, it was 1.09% and 12.88%, respectively (Riskesdas,
2019a); (Riskesdas,
2019b).
The adolescent period is the stage of life between
childhood and adulthood, ranging from 10 to 19 years. Physically, cognitively,
and psychosocially, adolescents experience rapid growth, becoming a unique and
vital period in human development that provides a good foundation for health (WHO, 2023b).
Based on data from the Central Statistics Agency (BPS,
Badan Pusat Statistik), in 2021, the number of Indonesians aged between
10 and 19 years was around 45,686,483, or 16.68% of the total population (Statistics, 2022). North Sulawesi Province is around 407,683 people or
15.45%, and in Bolaang Mongondow Regency in 2020, around 41,278 people or
17.06% of the total population are teenagers (North, 2023); (Mongondow, 2023). The prevalence of quality of life of Indonesian
adolescents in 2007 was still low at 7% �(Haryono &
Kurniasari, 2018). Quality of life can be influenced by
various health risk factors, including alcohol consumption behavior (Spilkova et al.,
2015)..
Studies conducted by (Buleno et al.,
2021)stated that more than 80% of
adolescents' quality of life in Kotamobagu City fell into the poor and moderate
categories. Research (Rizkillah et al.,
2023) showed that students'
sociodemographic factors, age, gender, Corona Virus Disease 2019 (Covid-19)
pandemic conditions, gratitude, student stress, addiction to gadgets, and
parents' relationship with adolescents affect quality of life. Studies
conducted by (Senduk et al.,
2019) there is a correlation between
alcohol consumption and quality of life. Research (Londa et al., 2017) shows a correlation between alcohol consumption and
quality of life in the Tomohon area. Research (Runtuwene et al.,
2022) showed that alcohol consumption was
correlated and became the most influential factor in a decrease in adolescent
health quality of life in South Minahasa Regency.
This study aims to analyze the correlation between
alcohol consumption, age, and gender with the health quality of life of junior
and senior high school students. The benefits of this research include providing
valuable insights for policymakers and educators to develop targeted
interventions to reduce alcohol consumption among adolescents. Additionally, it
will help in creating awareness programs that address the specific needs of
different age groups and genders, ultimately contributing to the improvement of
the quality of life for adolescents in Indonesia.
METHOD
This
type of research is analytical observational with a cross-sectional approach on
406 junior and senior high school students in Bolaang Mongondow Regency, conducted
from August 2023 to January 2024. Samples were taken using the multistage
random sampling method. Respondents were selected based on inclusion and
exclusion criteria. The variables studied were alcohol consumption habits, age,
and gender. Data were obtained through questionnaires, then data processing was
carried out. The instruments used in this study were WHOQoL-BREF and GSHS 2015
questionnaires. The results of the study data were tested for normality.
Shapiro-Wilk found that the data were not normally distributed. Spearman
correlation and logistic regression tests were carried out and presented as
tables and graphs.
RESULTS AND DISCUSSION
Table 1 shows the general characteristics of the
study sample. The lowest value of health quality of life was 33.00, and the
highest was 94.0, with a mean of 63.7 and a standard deviation of 10.70. Health
quality of life is divided into four domains, namely, physical domain (domain
1), psychological domain (domain 2), social relationship domain (domain 3), and
environmental domain (domain 4). Domain 1 obtained the lowest value of 31.00
and the highest of 100.0, with a mean of 68.6 and a standard deviation of
12.32. Domain 2 obtained the lowest value of 19.00 and the highest of 100.0,
with an average of 63.9 and a standard deviation of 16.17. Domain 3 obtained
the lowest value of 6.00 and the highest of 100.0, with an average of 57.4 and
a standard deviation 14.67. Domain 4 obtained the lowest value of 25.00 and the
highest of 100.0, with an average of 64.8 and a standard deviation of 13.45.
The lowest age was 11 years, and the highest was 19 years, with an average of
15.0 years and a standard deviation of 2.06.
Table 1. General
Characteristics of the Research Sample
|
|
N
|
Minimum
|
Maximum
|
Mean
|
Standard
Deviation
|
|
Quality
of life
|
406
|
33,00
|
94,0
|
63,7
|
10,70
|
|
Domain 1
|
406
|
31,00
|
100,0
|
68,6
|
12,32
|
|
Domain 2
|
406
|
19,00
|
100,0
|
63,9
|
16,17
|
|
Domain 3
|
406
|
6,00
|
100,0
|
57,4
|
14,67
|
|
Domain 4
|
406
|
25,00
|
100,0
|
64,8
|
13,45
|
|
Age
(years)
|
406
|
11
|
19
|
15,0
|
2,06
|
Table 2 shows the distribution
of research variable categories. The quality of health life of 239 people
(58.9%) was found to be moderate, and 167 people (41.1%) were categorized as
good. A total of 65 people (16%) have consumed alcohol, and 341 people (84%)
have never consumed alcohol. Based on age, 139 people (34.2%) were 10-14 years
old, 234 people (57.6%) were 15-17 years old, and 33 people (8.1%) were 18-19
years old. One hundred eighty-eight people (46.3%) were male and 218 (53.7%)
were female.
Table 2.
Category Distribution of Research Variables
|
Variable
Categories
|
N
|
Percentage
(%)
|
|
Quality of Life
|
Bad
|
0
|
0
|
|
Medium
|
239
|
58,9
|
|
Good
|
167
|
41,1
|
|
Total
|
406
|
100
|
|
Alcohol Consumption
|
Yes
|
65
|
16
|
|
No
|
341
|
84
|
|
Total
|
406
|
100
|
|
Age
|
10-14 years
|
139
|
34,2
|
|
15-17 years old
|
234
|
57,6
|
|
18-19 years old
|
33
|
8,1
|
|
Total
|
406
|
100
|
|
Gender
|
Male
|
188
|
46,3
|
|
Female
|
218
|
53,7
|
|
Total
|
406
|
100
|
Table 3 shows the distribution
of quality of life categories. Most respondents were in excellent and moderate
health and quality of life categories. The highest distribution in the good
category was 237 people (58.4%) in the physical domain, 206 people (50.7%) in
the psychological domain, and 204 people (50.2%) in the environmental domain.
The highest distribution of moderate categories was in the social relationship
domain, with 234 people (57.6%).
Table 3.
Category Distribution of Quality of Life
|
Quality
of Life Category
|
N
|
Percentage
(%)
|
|
|
Domain 1 (Physical)
|
Bad
|
1
|
0,2
|
|
Medium
|
168
|
41,4
|
|
Good
|
237
|
58,4
|
|
Total
|
406
|
100
|
|
Domain 2 (Psychological)
|
Bad
|
21
|
5,2
|
|
Medium
|
179
|
44,1
|
|
Good
|
206
|
50,7
|
|
Total
|
406
|
100
|
|
Domain 3 (Social
Relationships)
|
Bad
|
33
|
8,1
|
|
Medium
|
234
|
57,6
|
|
Good
|
139
|
34,2
|
|
Total
|
406
|
100
|
|
Domain 4 (Environment)
|
Bad
|
8
|
2,0
|
|
Medium
|
194
|
47,8
|
|
Good
|
204
|
50,2
|
|
Total
|
406
|
100
|
Table 4 shows that respondents
who had consumed alcohol for the first time were mainly in the age range of
12-13 years, with as many as 19 people (4.7%) respondents. Based on the number
of alcohol consumption during 1-2 days in a month (30 days), as many as 49
people (12.1%) were respondents. The highest amount of alcohol consumption was
<1 glass in a month by as many as 24 people (5.9%) respondents. The most
common way to get alcohol was by other means; as many as 24 people (5.9%) responded.
Based on who consumed the most alcohol, 34 people (8.4%) were respondents. The
number of times they consumed alcohol until they got drunk was 1-2 times; 25
(6.2%) respondents and 10 (2.5%) respondents were involved in problems due to
alcohol consumption 1-2 times.
Table 4.
Distribution of Alcohol Consumption Habits
|
Alcohol
Consumption Habits
|
N
|
Percentage
(%)
|
|
Yes
|
Age at first alcohol
consumption (years)
|
<7 years
|
6
|
1,5
|
|
8-9 years
|
4
|
1,0
|
|
10-11 years old
|
11
|
2,7
|
|
12-13 years old
|
19
|
4,7
|
|
14-15 years
|
13
|
3,2
|
|
16-17 years old
|
12
|
3,0
|
|
>18 years old
|
0
|
0
|
|
Total
|
65
|
16,0
|
|
No
|
341
|
84,0
|
|
|
Total
|
406
|
100
|
|
Yes
|
Number of alcohol
consumption in a month (days)
|
1-2 days
|
49
|
12,1
|
|
3-5 days
|
6
|
1,5
|
|
6-9 days
|
3
|
0,7
|
|
10-19 days
|
3
|
0,7
|
|
20-29 days
|
1
|
0,2
|
|
30 days
|
3
|
0,7
|
|
Total
|
65
|
16,0
|
|
No
|
341
|
84,0
|
|
|
Total
|
406
|
100
|
|
Yes
|
Total alcohol
consumption in a month (glasses)
|
<1 glass
|
24
|
5,9
|
|
1 glass
|
22
|
5,4
|
|
2 cups
|
4
|
1,0
|
|
3 glasses
|
5
|
1,2
|
|
4 glasses
|
0
|
0
|
|
>5 glasses
|
10
|
2,5
|
|
Total
|
65
|
16,0
|
|
No
|
341
|
84,0
|
|
|
Total
|
406
|
100
|
|
Yes
|
How to get alcoholic
beverages
|
Buy at the store
|
13
|
3,2
|
|
Get someone to buy it
for you
|
4
|
1,0
|
|
From friends
|
23
|
5,7
|
|
From the family
|
0
|
0
|
|
Stealing
|
1
|
0,2
|
|
Another way
|
24
|
5,9
|
|
Total
|
65
|
16,0
|
|
No
|
341
|
84,0
|
|
|
Total
|
406
|
100
|
|
Yes
|
Who to consume
alcohol with
|
With friends
|
34
|
8,4
|
|
With family
|
2
|
0,5
|
|
With strangers
|
1
|
0,2
|
|
On your own
|
28
|
6,9
|
|
Total
|
65
|
16,0
|
|
No
|
341
|
84,0
|
|
|
Total
|
406
|
100
|
|
Yes
|
Amount of alcohol
consumption to the point of intoxication
|
No
|
26
|
6,4
|
|
1-2 times
|
25
|
6,2
|
|
3-9 times
|
9
|
2,2
|
|
>10 times
|
5
|
1,2
|
|
Total
|
65
|
16,0
|
|
No
|
341
|
84,0
|
|
|
Total
|
406
|
100
|
|
Yes
|
The number involved
in problems due to alcohol consumption
|
No
|
48
|
11,8
|
|
1-2 times
|
10
|
2,5
|
|
3-9 times
|
2
|
0,5
|
|
>10 times
|
5
|
1,2
|
|
Total
|
65
|
16,0
|
|
No
|
341
|
84,0
|
|
|
Total
|
406
|
100
|
|
|
|
|
|
|
In health quality of life,
physical domain, psychological domain, social relationship domain,
environmental domain, alcohol consumption habits, age, and gender based on the
data normality test using Shapiro-Wilk, the p-value = <0.001 (<0.05),
which means that the data distribution is not normal (Table 5).
Table 5.
Shapiro-Wilk Data Normality Test Results
|
Shapiro-Wilk
|
|
Variables
|
P-value
|
|
Quality of Life
|
<0,001
|
|
Domain 1 (Physical)
|
<0,001
|
|
Domain 2 (Psychological)
|
<0,001
|
|
Domain 3 (Social Relationships)
|
<0,001
|
|
Domain 4 (Environment)
|
<0,001
|
|
Alcohol Consumption
|
<0,001
|
|
Age
|
<0,001
|
|
Gender
|
<0,001
|
Spearman correlation test
between alcohol consumption habits and health quality of life of junior and
senior high school students obtained a weak, unidirectional correlation (r =
-0.115) with significant statistical analysis (p = 0.020). The results of the
correlation test in each domain were respectively in the physical domain (r =
-0.074; p = 0.136), psychological domain (r = -0.101; p = 0.042), social
relationship domain (r = -0.065; p = 0.194), and environmental domain (r =
-0.159; p = 0.001). There is a tendency for alcohol consumption habits to
reduce the health and quality of life of junior and senior high school students
in the psychological domain and environmental domains (Table 6, Figure 1).
Table 6:
Correlation of Alcohol Consumption with Quality of Life
|
|
Correlation
Coefficient �
|
P-value
|
|
Alcohol
Consumption-Quality of Life
|
-0,115
|
0,020
|
|
Alcohol Consumption-Domain
1 (Physical)
|
-0,074
|
0,136
|
|
Alcohol Consumption-Domain
2 (Psychological)
|
-0,101
|
0,042
|
|
Alcohol Consumption-Domain
3 (Social Relationships)
|
-0,065
|
0,194
|
|
Alcohol Consumption-Domain
4 (Environment)
|
-0,159
|
0,001
|
Figure 1. Correlation of alcohol
consumption habits
with the health quality of life of
junior and senior high school students
The correlation between age and
health quality of life of junior and senior high school students based on the
Spearman correlation test obtained a weak, unidirectional correlation (r =
-0.159), which was significant (p = 0.001). The results of the correlation test
in each domain are successively in the physical domain (r = 0.019; p = 0.695),
psychological domain (r = -0.148; p = 0.003), social relationship domain (r =
-0.171; p = <0.001), and environmental domain (r = -0.153; p = 0.002). There
was a decreasing trend in the perceived quality of health life of junior and
senior high school students with age in the psychological, social relationship,
and environmental domains (Table 7, Figure 2).
Table 7.
Correlation of Age with Quality of Life
|
|
Correlation
Coefficient �
|
P-value
|
|
Age-Life Quality
|
-0,159
|
0,001
|
|
Age-Domain 1 (Physical)
|
0,019
|
0,695
|
|
Age-Domain 2
(Psychological)
|
-0,148
|
0,003
|
|
Age-Domain 3 (Social
Relationships)
|
-0,171
|
<0,001
|
|
Age-Domain 4 (Environment)
|
-0,153
|
0,002
|
Figure 2. Correlation of age with health
quality of life of junior and senior high school students
Spearman's correlation test
between gender and the quality of health life of junior and senior high school
students showed a correlation coefficient value (r = 0.090) with a statistical
analysis that was not meaningful (p = 0.069). The results of the correlation
test in each domain are successively in the physical domain (r = 0.054; p =
0.277), psychological domain (r = 0.136; p = 0.006), social relationship domain
(r = 0.043; p = 0.386), and environmental domain (r = 0.022; p = 0.656). There
is a tendency for gender to affect junior and senior high school students'
health and quality of life in the psychological domain (Table 8, Figure 3).
Table 8.
Correlation of Gender with Quality of Life
|
|
Correlation
Coefficient (r)
|
P-value
|
|
Gender-Quality of Life
|
0,090
|
0,069
|
|
Gender-Domain 1 (Physical)
|
0,054
|
0,277
|
|
Gender-Domain 2
(Psychological)
|
0,136
|
0,006
|
|
Gender-Domain 3 (Social
Relationships)
|
0,043
|
0,386
|
|
Gender-Domain 4
(Environment)
|
0,022
|
0,656
|
Figure 3. Correlation between gender and
health
quality of life of junior and senior
high school students
In Table 9, the correlated
independent variables based on bivariate analysis were subjected to logistic
regression calculation. Age was the most influential independent variable (p =
0.020). Students aged 15-17 had a chance of 1.664 times lower health quality of
life than students aged 10-14. The independent variables jointly influenced the
dependent variable (R2N = 0.0295), meaning that alcohol consumption and age
together had a 2.95% effect on the health quality of life of junior and senior
high school students.
Table 9. Logistic
Regression of Variables Correlated with Quality of Life
|
|
OR
|
P-value
|
R2N
|
|
Alcohol Consumption (Yes -
No)
|
1,588
|
0,115
|
0,0295
|
|
Age (15-17 years - 10-14
years)
|
1,664
|
0,020
|
|
Age (18-19 years - 10-14
years)
|
1,466
|
0,335
|
|
Quality of Life = Moderate vs Quality of Life = Good
|
Alcohol Consumption Habits
The
results of this study show that the quality of health of junior and senior high
school students in Bolaang Mongondow Regency is mainly in the moderate
category. A weak unidirectional correlation (r = -0.115) was significant (p =
0.020) between alcohol consumption habits and the health quality of life of
junior and senior high school students. There were significant correlations in
the psychological domain (p = 0.042) and environmental domain (p = 0.001) with
unidirectional correlation direction (r = -0.101) and (r = -0.159). Habitual
alcohol consumption will reduce health and quality of life as well as in the
psychological domain and environmental domains.
Research
conducted by Senduk et al, there is an association between alcohol consumption
and quality of life (Senduk et al., 2019). A variety of health risk
factors can threaten quality of life, one of the most serious of which is
behavior such as alcohol consumption, especially in adolescence (Spilkova et al., 2015). Alcohol addiction is
categorized as a mental health disorder that causes permanent changes in brain
function. These changes will cause cognitive and concentration impairment in
adolescents, reducing their intelligence and learning achievement (Family, 2022).
Alcohol
dependence can cause a person to be less productive due to limitations in
performing daily activities; there will be problems at work and poor work
performance (Runtuwene et al., 2022). According to Lito et al.,
there is a curiosity factor in consuming alcohol, and there is also influence
from the surrounding environment, such as friendship groups. (MB, 2021). The family environment and
place of residence also affect adolescents' alcohol consumption habits if there
are family members who consume alcohol or have a permissive attitude toward the
habit (Aprellia et al., 2024). Another study conducted by
Hung et al. stated that adolescents who experience alcohol dependence will
experience a decrease in the quality of life in the psychological domain
(related to mental health) and the environmental domain (related to a sense of
dissatisfaction with the surrounding environment). (Hung et al., 2015).
Age
The
results of this study indicate that age has a weak unidirectional correlation
(r = -0.159), which is significant (p = 0.001) in the quality of health of
junior and senior high school students in Bolaang Mongondow Regency. There was
a significant correlation in the psychological domain (p = 0.003), social
relationship domain (p = <0.001), and environmental domain (p = 0.002) with
a weak unidirectional correlation respectively (r = -0.148), (r = -0.171) and
(r = -0.153). There is a tendency to decrease the perception of health and
quality of life with age in the psychological, social relationship, and
environmental domains.
There
is a correlation between sociodemographic factors and quality of life. Age
affects quality of life; there is a decrease over time (Sari et al., 2021). Significant general and
quality of life differences were also found in different age groups and can be
observed since adolescence (Purba et al., 2018). Research in Maranh�o
(Brazil) in 2018 showed that age variables were significantly associated with
adolescent health and quality of life (p = 0.021). The age group in the study
was divided into two groups, namely, groups aged �15 years and >15 years.
From the observation, it was found that the group aged >15 had a healthy
quality of life with moderate (68.2%) and poor (81.4%) categories. Based on the
calculation, the odds of 0.515 times the quality of health life of adolescents
in the group aged >15 years is lower than those aged 15 years (OR
0.515) (Alencar et al., 2022)..
A
longitudinal study conducted over four years in Hong Kong suggests two theories
that explain the decline in health and quality of life as people age. First, as
people age, their demands and responsibilities increase. Second, it is assessed
by the maturation of cognitive function and a more realistic way of looking at
the world. (Shek & Li, 2016).
Gender
�� This study showed that gender did not
correlate with the quality of health life of junior and senior high school
students in Bolaang Mongondow Regency (r = 0.090; p = 0.069). In addition, a
significant correlation test result was obtained in the psychological domain (p
= 0.006) with a weak correlation in the same direction (r = 0.136). There is a
tendency for male students to have a better perception of health and quality of
life compared to female students in the psychological domain.
Pinaria
et al.'s study found no significant relationship between gender and quality of life
(Pinaria et al., 2024). Kumayas et al. in South
Minahasa Regency stated that gender was not associated with adolescent quality
of life. In general, from the four domains, it was found that adolescent girls'
quality of life was better than adolescent boys (M, 2022). In contrast to the
research results obtained by Alencar et al. in Brazil, there is a significant
relationship between gender and adolescent health quality of life (p = 0.002).
In the study, it was also observed that the quality of life of female adolescents
was lower than that of male adolescents (Alencar et al., 2022). This difference was also
found in a study conducted on 415 adolescents in Manado City, where there was a
small relationship between female adolescents' health quality (Porajow et al., 2021).
Differences
in adolescents' health and quality of life by gender may be related to the
different pubertal transition periods of males and females. This affects their
emotions, thoughts, decisions, and interactions with the outside world. (WHO, 2023b). Today's instantaneous life
leads to earlier menarche in adolescent girls. This can cause (psychological)
feelings not by their ideal conditions. In addition, women tend to pay more
attention to their bodies' appearance than men.
CONCLUSION
Based on the results of
this research, it can be concluded that there is a correlation between alcohol
consumption habits and age with the quality of health life of junior and senior
high school students in Bolaang Mongondow Regency, while gender is not
significant. Age was the most influential independent variable on health and
quality of life in this study. The implications of these findings suggest that
targeted interventions focusing on younger age groups could be more effective
in improving the overall health and quality of life of adolescents. It is
recommended that future research explore the underlying reasons for the lack of
gender significance and investigate additional factors that might influence
adolescent health and quality of life, such as socioeconomic status, educational
environment, and family dynamics. Moreover, longitudinal studies could provide
deeper insights into how these variables interact over time, offering a more
comprehensive understanding of the factors affecting adolescent well-being.
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