Introduction
The two most prevalent mental disorders in
the general population globally are depression
and anxiety. Stresses from the individual (such
as anxiety, insomnia), the community (such as
discrimination, isolation), and the environment
(such as natural disasters) can all have an impact
on the development of a disorder [1]. Natural
catastrophes may possess a negative influence
on psychological health, hastening the short- and
long-term development of psychiatric diseases
[2]. It has been observed that 10% to 40% of
earthquake survivors suffer from depression [3].
Turkey is a seismically active country located
in the complicated subduction zone of the
Eurasian, African, and Arabian plates [4]. A 7.8
magnitude earthquake jolted Southern Turkey
early on February 6th. The most recent numbers
show that 38,044 people died and 108,068 were injured. 56,080 buildings in ten provinces have
either fallen or suffered major damage, according
to damage surveys [5]. According to the World
Health Organization, 1.4 million children and
refugees are among the over 23 million people
who reside in Turkey’s affected regions. Research
undertaken after catastrophes imply that exposure
to earthquakes increases the probability of
acquiring a number of psychopathologies [6],
sadness is a common psychological reaction to
natural calamities, notably earthquakes [7,8].
Earthquakes have been associated with a rise in
psychopathology, namely Post-Traumatic Stress
Disorder (PTSD) and depression [9]. Depression
is a psychiatric illness characterized by prolonged
weeping and disinterest in common mental
disorders such as severe depression, bipolar
disorder, and schizophrenia. It really can induce
depressive problems, as well as a reduction in
interest in sympathetic nervous system activitieslike sleep, appetite, or sexual dysfunction, as well
as cognitive difficulties and physical symptoms
like fatigue and discomfort [10].
Few studies of post-seismic psychiatric illnesses
have been undertaken using randomly selected
samples of earthquake survivors. Earthquakes are
commonly linked to stress symptoms. According
to research conducted in Turkey after the 1999
earthquake, survivors suffered long-term illness
and stress [11, 12]. The most significant but small
predictors of traumatic stress symptoms were
gender, prior mental disorder, house destruction,
engagement in rescue organizations, prior trauma,
and loss of loved ones. First most important
determinant of traumatic stress symptoms was
dread during the earthquake [9, 13]. Earthquake
fear, difficulties expressing thoughts and feelings,
and emotional recovery accounted for 81% of
the variance in HTQ in a study of psychological
responses among survivors [14]. According to
psycho trauma research, PTSD is linked to a variety
of factors, including trauma exposure, the severity
of the loss, the intensity of the dread, a history of
mental illness, and others [15]. The outcomes of
all these research are challenging to evaluate due
to differences in earthquake severity, devastation,
time following the earthquake, sampling methods,
and measures used. The current investigation is
based on an epidemiological analysis of Turkish
earthquake survivors from 2023. The purpose
of this study was to investigate the occurrence
of stress, anxiety, and depression in the first few
weeks after the earthquake. The present research
aims to examine the following questions:
• Psychological impact as a result of a change
towards anxiety, stress, and depression
• Change in living patterns like food sleep and
worship
Methodology
Participants who reported having been affected by
the earthquake and who lived in Adana, a city of
1.8 million people in southern Turkey that suffered
a state of emergency as a result of the seismic
event, fulfilled the inclusion criteria. By random
sampling, 1491 respondents made up the final
sample. An anonymous online survey was sent
through institutional channels including email
and media relations as well as social networks
using the survey platform qualtrics. The reliability
of tool was determined through pre testing and
Cronbach alpha. After pretesting some questions are rephrased that helped to increase the reliability
of data similarity, the value of Cronbach alpha is
above 60% that depicts tool is reliable. By random
sampling, 1491 respondents made up the final
sample. The researchers focused at demographics,
physical and health activities including prayer,
sleep, antidepressant usage histories, and dietary
patterns, as well as health conditions like stress,
depression, and anxiety. In the current paper, only
survey metrics relevant to the study’s goal are
included. Individual data included age, sex, social
background, educational level, average earnings,
and health history. The widely used Depression,
Anxiety, and Stress Scale (DASS 21) was utilized
to measure emotional pain [16]. Each component’s
seven aspects were assessed on a Likert scale
ranging from 0 to 5, with 5 representing the most
important feature to the participant. The valid
values for each component, which ranged from
0 to 21, were added to determine the scores for
the depression, anxiety, and stress items. Using
defined cut-points, the intensity of the symptoms
was rated.
The survey has a single question with a Likert
scale from 1 to 3. The domain mostly focuses on
inadequate food consumption or uncertainty over
the household’s food supply. The range of possible
responses is “I’m not sure about my next meal” to
“I’m eating what my body requires.” Participants
were asked to indicate how their prayer activity
has changed since the earthquake in response to
a single question with a single response option
ranging from 1 to 6. From 1 (I no longer pray) to 6
(I am much busier than usual).
To evaluate sleep, two things were employed.
Participants were initially questioned about how
long they regularly slept each night before the
earthquake (sleep quantity). Participants revealed
how the earthquake has impacted their normal
level of sleep by answering the inquiry “When the
earthquake happened, I...” Five more choices were
available, ranging from “am sleeping much better
than normal” to “am sleeping considerably worse
than usual” [16].
Statistical Analysis
Researchers produced descriptive statistics such as
percentages and frequencies from categorical data.
For the dependent variable, Standard Deviations
(SD) and means were calculated. The nonparametric
Kruskal-Wallis test, Wilcoxon ranksum,
and Spearman’s correlation analyses were
performed to assess depression, anxiety, and stress levels depending on participants’ socioeconomic
and demographic characteristics, as well as their
health condition. In order to identify fluctuations
in alcohol, smoking, sleep, and physical activity
use individually, responses for each behavior
were reclassified into either negative change
(-1), no change (0), or positive evolution (+1).
To measure the impact of well-being on lifestyle
behavior, a multiple lifestyle behavior index was
developed, to sum up, scores from four healthrelated
behaviors. This composite health change
score had an output range between -4 and +4.
To illustrate the effects of depression, stress, and
anxiety levels on this score, average composite
health behavior change scores were computed
alongside their respective SD. Logistic regression
analysis was performed to check the negative
alteration the behavior of an individual had any
link with the depression, anxiety and stress. By
considering age, marital status, household income,
gender, years of education, and injury/ disease
status in our analysis with a 95% Confidence
Interval (CI), researchers were able to provide
crude estimates as well as adjusted estimates for
these findings. We utilized logistic regression to
determine whether any modifications in individual
behavioral qualities were linked with stress,
depression, and anxiety. A p-value of less than
P<0.05 was considered statistically significant for
all analyses. It is applied on the adjusted model
because logistic regression provide accurate
answer either the relationship is prevailed or not
and what is the exact difference there is no middle
ground in the application of the logistic model.
Results
Table 1 outlines health and the socio-demographic characteristics of our study sample, which was comprised of 1491 respondents with a mean age 50.5 ± 14.9 years, 1005 females overall. Of those surveyed, 937 (62.8%) were married or in relationship while 693 (46.5%), reported having at severe injury. The average score of depression was 1.9 with a standard deviation of 1.3; for anxiety, the mean rating was 1.5 ± 1.0; and stress had an average score of 1.6 ± 1.1 respectively. Participants were active on average at 309 minutes/ week before earthquake. On average, prior to the earthquake, participants reported getting 6.7 ± 1.0 hours of sleep each night with half (756 people or 50.7%) claiming their sleep quality had not changed since then. In the account of earthquake 729 (48.9%) participants were having negative changes in their food routines while 454 (30.5%) were reported no change. A large number of respondents 1319 (88.5%) claimed that they were not in anti-depression while 172 (11.5%) were in anti-depression. Whereas, 1338 (89.7%) got no change and the 103(6.9%) were recorded negative change in their anti-depression condition.
Table 1: Demographic attributes of the population
|
N |
Percentage or Mean (SD) |
Age (years) |
1491 |
50.5 (14.9) |
Sex |
Men |
486 |
32.6 |
Women |
1005 |
67.4 |
Marital status |
Unmarried |
306 |
20.5 |
Div./Sep/Widow |
248 |
16.6 |
Married |
937 |
62.8 |
Level of Education |
1491 |
16.3 (5.1) |
Household income |
<$1000/ Month |
389 |
26.1 |
$1000–<$2000/Month |
443 |
29.7 |
≥$2000/Month |
659 |
44.2 |
Injury status |
No |
798 |
53.5 |
Yes |
693 |
46.5 |
DAS (Depression, Anxiety, Stress) score |
Depression |
1491 |
1.9 (1.3)) |
Anxiety |
1491 |
1.5 (1.0) |
Stress |
1491 |
1.6 (1.1) |
Physical activity (mints/week) |
1491 |
309.1 (359.5) |
Sleep (Hours/night) |
609 |
6.7 (1.0) |
Use of anti-depressant |
Yes |
172 |
11.5 |
No |
1319 |
88.5 |
Prayer/worship |
Often |
301 |
20.2 |
weekly or less |
322 |
21.6 |
1-2 per day |
250 |
16.8 |
2–3 per day |
286 |
19.2 |
4 or 5 per day |
332 |
22.3 |
Change in food routine |
Negative change |
729 |
48.9 |
No change |
454 |
30.5 |
Positive change |
308 |
20.7 |
Change in sleep quality |
Negative change |
607 |
40.7 |
No change |
756 |
50.7 |
Positive change |
128 |
8.6 |
Change in use of anti-depression |
Negative change |
103 |
6.9 |
No change |
1338 |
89.7 |
Positive change |
50 |
3.4 |
Change in offer prayer |
Negative change |
396 |
26.6 |
No change |
825 |
55.3 |
Positive change |
270 |
18.1 |
Table 2 describes that the difference in psychological distress based on sociodemographic and health characteristics in relation to the depression, anxiety and stress. High stress score was noted in the females as compared to the males however, there was no significant difference in the anxiety and depression score of the both males and females. Younger people aged between 18-45 were having high depression, anxiety and stress level as compared to the other aged groups. Respondents who were married or divorced were having lower depression, anxiety and stress scores as compared to the people who were not married. After analyzing the data, we discovered a notable inverse relationship between years of education and depression scores; however, there was no link observed between anxiety or stress levels. Those in the lowest income demographic experienced higher depression scores than those with greater incomes; however, no distinction was determined between various weekly household earnings and anxiety or stress levels. Respondents identified as having an injury were reported significantly more pronounced depression, anxiety, and stress scores compared to those without such health issue. With respect to depression, anxiety, and stress, Table 2 shows the differences in psychological distress depending on socio-demographic and health variables. Females were shown to have higher stress scores than males, but there was no discernible difference in the scores for anxiety or depression between the sexes. Younger people between the ages of 18 and 45 reported greater levels of stress, anxiety, and depression than elderly adults. When compared to those who were not married those who were married or divorced scored less depressed, anxious, and stressed. After doing a thorough analysis of the data, we found no connection between anxiety or stress levels and the number of years of schooling and depression ratings. The lowest income group had higher depression levels than the highest income group. When respondents with injuries were detected, their levels of melancholy, worry, and stress were much greater than those of respondents who did not have such health difficulties.
Table 2: Depression, anxiety and stress varies according to socioeconomic and health circumstances
Characteristic |
Depression Mean (SD) |
p-Value |
Anxiety Mean (SD) |
p-Value |
Stress Mean (SD) |
p-Value |
Sex |
women |
4.2 (4.7) |
|
2.0 (3.1) |
|
4.9 (4.0) |
|
Men |
4.1 (5.0) |
0.171 |
2.0 (3.5) |
0.102 |
4.2 (4.8) |
0.005* |
Age (years) |
18–45 |
5.2 (5.1) |
|
2.7 (3.2) |
|
6.4 (4.6) |
|
46 to 65 |
3.3 (4.0) |
<0.001*** |
1.3 (2.9) |
<0.001 *** |
3.9 (3.9) |
<0.001 *** |
>65 |
2.7 (3.4) |
|
1.0 (2.0) |
|
1.1 (2.9) |
|
Marital status |
Unmarried |
6.2 (4.3) |
|
2.9 (3.8) |
|
5.7 (4.2) |
|
Div./Sep/Widow |
5.0 (5.2) |
<0.001 *** |
2.0 (3.1) |
<0.001*** |
4.0 (3.1) |
<0.001 *** |
Married |
3.2 (3.9) |
|
1.2 (2.4) |
|
4.1 (3.2) |
|
Level of education
(Continuous variable) |
−0.081 |
0.002 * |
−0.059 |
0.297 |
−0.011 |
0.541 |
Household income |
<$1000/Month |
4.7 (5.0) |
|
2.1 (2.9) |
|
3.5 (4.2) |
|
$1000–<$2000/Month |
3.2 (4.6) |
0.039 * |
1.7 (3.0) |
0.101 |
4.0 (3.1) |
0.112 |
≥$2000/Month |
3.9 (3.8) |
|
1.3 (3.0) |
|
4.3 (3.6) |
|
Diagnosed with physical injury |
No |
3.8 (4.1) |
|
1.8 (3.0) |
|
4.2(3.5) |
|
Yes |
4.7 (5.0) |
0.001 *** |
2.7 (3.7) |
<0.0001 *** |
4.9 (4.3) |
0.003 |
Note: * denotes the significant difference between p-value of correlation for the variables, level of education, household income sex of the respondents and depression, anxiety stress mean
*** depicts the highly significant association between p-value for the age and marital status of the respondents and depression.
According to the degree of sadness, anxiety, and stress, Table 3 shows the mean changes in composite health behavior scores. Except for exceptionally severe cases of despair and anxiety, fewer people had each symptom as symptoms increased. Taking into account sadness, anxiety, and stress, it was shown that, with the exception of cases of really severe anxiety or stress, the average composite health behavior change score fell as symptoms got worse
Table 3:The degree of sadness, anxiety, and stress is used to stratify the composite health conduct variance
Psychosomatic Distress Factors |
n (%) |
Composite Health con |
Severity (Range of Scores) |
|
Change Score Mean (SD) |
Depression |
Very Low (0–4) |
920 (61.7) |
−0.42 (1.25) |
Below Average (5–6) |
175 (11.7) |
−1.03 (1.25) |
Average (7–10) |
206 (13.8) |
−1.22 (1.34) |
Above Average (11–13) |
79 (5.3) |
−1.28 (1.42) |
Very high (>13) |
111 (7.4) |
−1.45 (1.44) |
Anxiety |
Very Low (0–3) |
1175 (78.8) |
−0.58 (1.28) |
Below Average (4–5) |
115 (7.7) |
−1.20 (1.40) |
Average (6–7) |
83 (5.6) |
−1.24 (1.35) |
Above Average (8–9) |
40 (2.7) |
−1.50 (1.52) |
Very High (>9) |
78 (5.2) |
−1.23 (1.61) |
Stress |
Very Low (-7) |
1077(72.2) |
-0.49 (1.25) |
Below Average(8-9) |
143 (9.6) |
-1.34 (1.23) |
Average (10–12) |
121 (8.1) |
-1.25 (1.46) |
Above Average (13–16) |
105 (7.0) |
-1.43 (1.43) |
Very High (>16) |
45 (3.0) |
-1.33 (1.69) |
Table 4 shows a link between DAS marriage status, gender, age, level of education, income, and injury status and detrimental changes in behavior. Only accustomed ORs are accessible to see after taking into consideration age, years of education, gender, marital status, family income, and diagnosed injury status (which had no impact on the associations). Looking at the results, participants who experienced a decrease in food routines were more expected to suffer from higher symptoms of depression 1.01 (95% CI: 1.06-1.11), anxiety 1.02 (95% CI: 1.05-1.13), and stress 1.01 (95% CI: 1.05-1.11). Individuals who experienced a negative change in their sleep patterns were more possible to agonize from heightened symptoms of depression OR= 1.15 (95% CI: 1.15-1.23), anxiety OR=1.19, (95% CI: 1.19, 1.31), and stress (adjusted OR=1.29 (95% CI: 1.26, 1.35). For those who reported a decrease in anti-depression, they were more likely to experience higher levels of depression OR=1.05 (95% CI: 1.04-1.13), anxiety OR=1.01 (95% CI: 1.06 -1.18), and stress symptoms (OR=1). Additionally, those who reported a negative change in their prayer/ worship habits were more prospective to have greater levels of depression (adjusted OR= 1.02 (95% CI: 1 .04-1.10), anxiety OR= 1.01 (95% CI: 1.04-1.12), and stress symptoms OR= 1.01 (95% CI: 107-113). The results remain consistent for combined variation scores.
Table 4:The association between mental distress and detrimental behavioral changes related to health
Adjusted Model (n = 1261)# |
|
Depression |
Anxiety |
Stress |
Logistic Regression |
Odds Ratio (95% CI) |
|
|
Food routine |
1.01 ** (1.06, 1.11) |
1.02 * (1.05, 1.13) |
1.01 ** (1.05, 1.11) |
Sleep |
1.15 * (1.15, 1.23) |
1.19 * (1.19, 1.31) |
1.29 * (1.26, 1.35) |
use of anti-depression |
1.05 * (1.04, 1.13) |
1.01 ** (1.06, 1.18) |
1.01 ** (1.05, 1.15) |
Prayer/Worship |
1.02 * (1.04, 1.10) |
1.01 ** (1.04, 1.12) |
1.01 ** (1.07, 1.13) |
|
Linear Regression–score estimate (95% CI) |
|
|
Composite change score |
−0.09 * (−0.10, −0.07) |
−0.10 * (−0.12, −0.07) |
−0.10 * (−0.12, −0.08) |
Note: In Logistic regression there is “no change/positive change”. *** P < 0.001; # Which is adjusted for age, years of education, gender, marital status, household income and chronic disease status.
The first variable food routine, use of anti-depression, prayers and worship, had highly significant ** p.value for the odds ratio of depression while it had * significant p-value for the Anxiety and depression. Similarly sleep had * significant p-value for depression, anxiety and stress.
Discussion
The current study looked at how eating habits, sleeping patterns, medicine use, and prayer activity changed as environmental factors after the earthquake, individual health attitudes as well as a cumulative value for the health behavior change index. Key findings of the study indicated that the three aspects of psychological distress: depression, anxiety, and stress were demonstrated to be substantially correlated with changes in health behavior, both individually and as a composite score. Several research have been carried out to study the relationship between various natural changes and components associated with psychological discomfort. For example, Substantial research has been done on the harmful impact that natural catastrophes have on mental health [17,18]. Much attention has been placed on post-disaster mental health issues such as depression and PTSD, with earthquakes functioning as a basis [19]. Much emphasis has been paid to negative mental health impacts [20- 22]. According to the current study, the aggregate healthcare behavior modification score fell as depression intensity increased. In the preceding example, participants with intermediate symptoms of depression reported a somewhat negative change (0.42 points) in the aggregate health related behaviors modification score, whereas those with really severe symptoms reported a significantly positive shift (1.45 points). Higher levels results of DAAS were associated with unfavorable improvements in the composite health behavior change scores. According to the results of logistic regression, a negative change in any behavior was strongly linked to a greater vulnerability of experiencing depression, anxiety, and stress. Natural disasters have a detrimental effect on the lives, connections, and mental and physical wellness of victims in the short, medium, and long term. One of the most common mental health problems among these sufferers is PSTD [23]. A review conducted previously indicated that earthquakes predisposed sufferers to a variety of mental health issues, including anxiety, depression, suicide, and PTSD [24]. Psychological impacts, such as suicidal ideation, become more prevalent. Suicide ideation can be exacerbated by major depression, a history of previous mental health troubles, property damage, economic concerns, injuries or loss of relatives, and life-threatening disorders [24]. Disaster-related nutritional changes may have an impact on one’s mental and physical health [25]. According to the current study, food insecurity has slightly increased, affecting dietary practices and leading to psychological discomfort. In Nepal, a 2015 study indicated that, according to the domestic food security availability index, food insecurity increased from 12.4% (6.9% - 21.2%) to 17.6% (11.7% - 25.6%) [26]. The same study was presented in Port-au-Prince, Haiti, and revealed that more than 50% of the people there experienced moderate to severe food insecurity, it might result in psychological and physical health issues in the future [27]. There was a greater incidence of depressive symptomatology in those who had suffered physiological injury as a consequence of the earthquake. This discovery supports an earlier Peruvian research [28]. According to a study persons who lost loved ones in the 2007 Pisco earthquake had an 11% frequency of depression. Moreover, the latter research and another [29]. According to studies done following the 2008 Wenchuan earthquake, depressed symptoms were prevalent in those who had suffered physical harm, but there were no appreciable differences from healthy people, this is in line with the findings of the present research.. The trauma of a family member’s injuries is likely to be greater for the person since it may compound the emotional consequences of the earthquake. Sleeplessness has been linked to a higher incidence of depression symptomatology. Teens who survived an earthquake and later acquired PTSD had a 50% increased chance of developing sleeplessness, according to a retrospective research [30]. Another study revealed that resilience mediates the association between stress and insomnia [31]. In contrast, other studies [32,30] it has been demonstrated that insomnia precedes psychopathology. The intricate relationship between anxiety and sleeplessness may be explained by how sleep affects emotion regulation and memory consolidation [33]. As a result, future research should give more proof in situations like as earthquakes and other natural calamities. Not only the disasters affect living conditions, but also it can drastically alter human thinking towards religions [34]. Our research indicated that disasters had a lower impact on worshiping behaviors. Some of the religious approaches that Muslims regularly apply to cope with difficulties in life are religiosity, belief, trusting God, prayer, forgiveness, supplication, and recitation of the Quran, remembrance of God, patience, and gratitude [35]. These practices help to reduce negative impacts due to disasters and give strength to restore emotional stability
Recommendation
After the Turkish earthquake in 2023, the aim
of this study is to spot any early indications of
PTSD. Accurate statistics are still needed for
public health policy. These techniques need to be
enhanced in light of credible and relevant scientific
understanding to enable the early recognition and
therapy of depression, anxiety, and stress. For
instance, we showed that vulnerable populations
in Turkey, such as those suffering with physical
violence and food shortages, require special
attention [36]. Although these people may be
more prone to post-disaster PTSD, treatments may
focus on pre-existing mental health conditions,
such as insomnia. In this situation, early detection
and therapy of PTSD can aid in anticipating
and preventing later adverse consequences,
such as poor quality of life, hopelessness, and
suicide. Natural catastrophes of all types are
becoming more common across the world. Thus,
psychiatrists must accept responsibility for the
effects of trauma, conduct more extensive research
on methods of working with trauma survivors,
and design therapies based on scientific evidence.
A seismically dangerous zone encompasses 92%
of Turkey. An awareness and training program
for certain skills would help in the development
of a sense of mastery and control, minimizing
psychological suffering among survivors.
Conclusion
People were more likely to exhibit depressed
symptoms if they had a history of mental illness,
had relatives who had had earthquake injuries, had
political or social support, experienced moderate
food insecurity, or had any degree of sleeplessness
symptoms. Also, those who had severe food
insecurity, physical earthquake injuries, or any
degree of sleeplessness were more likely to
exhibit signs of anxiety. Our study broadens our
understanding of these factors as they pertain to
earthquakes.
Limitations
This research has limitations. Most importantly,
due of the sampling limitations, the results should
be interpreted with care. It is highly suggested not
to apply the findings of this study to the broader
population because we utilized a non-probability sampling strategy. However, while interpreting the
results, it is important to consider methodological
limitations such the cross-sectional pattern,
non-probabilistic sampling method, and a small
number of samples. Further evidence of these
limits is needed to improve local therapies and
stop harmful impacts on mental health. Further
research with a more representative age range and
participants chosen at random may be required
to replicate these findings. It is also worth noting
that several important elements (for example, loss
of family members and/or property damage) that
may be related to the participants’ mental health
were not gathered and examined in this study.
This study did not gather or investigate women
issues in particular. As a result, it is strongly
advised that such aspects be included in future
research to better understand the consequences of
catastrophes on mental health and strength.
Acknowledgements
The authors would like to express their gratitude
to the interviewers and study participants.
Funding
This research did not receive any specific grant
from funding agencies in the public, commercial,
or not-for-profit sectors.
Data Availability Statement
None
Conflict of Interest
The authors declare no potential conflicts of interest
with respect to research, financial relationship,
authorship and/or publication of this article.
Ethical Consent
Participants were told of the study’s goals and
methodology before the interview process began,
and their verbal informed consent to participate
was then obtained. The Committee of University
of Agriculture, University’s Department of Sociology
accepted ethical consent (Ethics-PK-2023).
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