Volume 2, No. 5 May 2024 p-ISSN 3032-3037| e-ISSN
3031-5786
Analysis of Dominant Risk
Factors for Stroke Incidence and Unhealthy Lifestyle at Sidomulyo Pekanbaru
Health Center
Chairil
Muhamadiyah University Riau, Pekanbaru, Riau, Indonesia
Email: chairil@umri.ac.id
Abstract
The introduction of health in the community is not only seen in
the health sector but also must be seen in all sectors that influence health
problems. Generally, there are two kinds of causes of stroke. The first is a blockage
of the arteries, called ischemic stroke, while the second cause is rupture of
blood vessels, or stroke ischemic, while the second cause is a rupture of blood
vessels called a hemorrhagic stroke. Other causes of stroke can be a temporary
disruption of blood flow to the brain, commonly referred to as an ischemic
attack (TIA). These three conditions have a series of potential factors that
trigger stroke. Hemorrhagic. Other causes of stroke can be a temporary
disruption of blood flow to the brain, commonly referred to as an ischemic
attack (TIA). These three conditions have a series of potential factors that
trigger stroke. The study employed the Spearman rank correlation test method to
investigate the relationship between smoking habits, alcohol consumption, lack
of physical activity, and the occurrence of stroke. It involved 41 respondents
from the Sidomulyo Health Center's jurisdiction. The findings revealed a
significant association between smoking habits and stroke, as indicated by a
significance value of 0.007, which is less than the threshold of 0.05.
Similarly, there was a significant relationship observed between alcohol
consumption and stroke, with a significance value of 0.016. However, the
analysis showed no significant correlation between lack of physical activity
and stroke, as the significance value of 0.446 exceeded the threshold of 0.05.
Keywords: Cigarettes, Alcohol, Lack Of
Activity, Stroke
Ii
Health advancement constitutes a fundamental aspect of national progress, striving to ensure that all individuals possess the capacity to lead healthy lives and attain an optimal level of health (Sciences et al., 2020). The objectives of health advancement encompass raising awareness, fostering willingness, and enhancing the capability of every individual to maintain a healthy lifestyle, thereby promoting the attainment of an ideal public health status (Bowleg, 2021). Realizing a healthy state is a very complex condition that is interrelated between the health sector and sectors outside health. Maintaining health is not solely the responsibility of the healthcare sector but also extends to other sectors beyond healthcare. Similarly, solving health problems in the community is not only seen from the health sector but also must be seen from all sectors that influence these health problems (Marahatta et al., 2020).
Many
factors affect health, both individual health and public health. For this,
Hendrik L Bloom described factors that affect health, including heredity,
health services, health status, environment, and behavior ((Zavala et al., 2021);(Chow et al., 2022)). Generally, there are two kinds of causes of stroke. The first cause
is a blockage of the arteries, called ischemic stroke, while the second cause
is the rupture of blood vessels, called a hemorrhagic stroke (Hong et al., 2021). Beyond the two causes mentioned,
other causes of stroke can be a temporary disruption of blood flow to the
brain, commonly referred to as Ischemic Attack (TIA). However, usually, the
symptoms of TIA stroke do not last long ((Pohl et al., 2021);(Amarenco, 2020)).
All
three conditions have a series of potential factors that trigger stroke. When nicotine and carbon monoxide in cigarette smoke damage the
cardiovascular system and open up the chances of stroke (Dorey, Scheerlinck, Nguyen, & Albertson, 2020). Smoking can reduce the
risk of stroke by 12%. Lack of exercise can
make a person overweight or obese, with diabetes and also high blood pressure.
That way, the risk of stroke will be higher. Therefore, try to be at least
active by exercising 150 minutes a week (Jeong et al., 2021). If you do not want to
struggle to exercise, do other physical movements and at least reduce your
sitting time. In addition to refreshing the body, exercise can reduce the risk
of stroke by 36 percent. This is undoubtedly a behavioral factor or lifestyle/bad habit that
can cause stroke, such as smoking, drinking alcohol, and lack of physical
activity (Yehuda
et al., 2023).
For the working area of the Sidomulyo
Health Center from January 2022 - March 2023, the number of patients with
stroke was 41 people who visited, which is not among the ten largest diseases (Amareta,
Perwiraningrum, & Arifianto, n.d.). This disease is thought to have
something to do with a bad individual hud
up style, smoking alcoholic beverages, lack of unhealthy activities, and
rudimentary food and beverage supervision factors that contribute to stroke (Kingham,
Kemps, Prichard, & Tiggemann, 2023). In addition, an unhealthy lifestyle is
also a risk factor, such as frequent consumption of fast food, alcohol,
smoking, drugs, lack of exercise, and high cholesterol and uric acid (Jakše,
Godnov, Fras, & Fidler Mis, 2024). Puskesmas Sidomulyo, located in the old
sub-district of Madani, is a vulnerable area at the western end of the city of
Pekanbaru; data from the Pekanbaru City Health Office states that the Sidomulyo
Health Center is among the top 10 highest visits of patients with hypertension (Ricka
Marliana, 2023).
The
submission above and the results of the initial survey in the field from December
2022 to March 2023 in the Sidomulyo Health Center Area found that there are
stroke patients with various factors behind it, so research needs to be carried
out related to the occurrence of stroke. Based
on this description, the formulation of the problem in this study needs to be
analyzed domina risk factors, which are reviewed unhealthy lifestyles or habits
associated with the incidence of stroke in the Working Area of the Sidomulyo
Health Center, Handsome District, Pekanbaru City. Therefore, this study aims to determine the risk
factors for domina reviewed unhealthy lifestyles or habits associated with the
incidence of stroke in the work area of the Sidomulyo Health Center in
Pekanbaru City by knowing the relationship between smoking, drinking alcohol,
and lack of activity factors with the occurrence of stroke in the work area of
the Sidomulyo Health Center, Tuah Madani District, Pekanbaru City.
This study contributes
to the field by examining the predominant risk factors for stroke incidence and
the unhealthy lifestyle habits associated with stroke within the Sidomulyo
Health Center's jurisdiction in Pekanbaru City. By utilizing the Spearman Rank
correlation test method, the research explores the interplay between smoking
habits, alcohol consumption, lack of physical activity, and the occurrence of
stroke. The results uncover noteworthy associations between smoking and alcohol
consumption and stroke, indicating a moderate correlation between these
behaviors and stroke risk. This study adds to the literature on stroke risk
factors by offering specific insights into how these lifestyle factors relate
to stroke incidence locally, informing targeted public health interventions and
prevention strategies.
The
uniqueness of this research lies in its focus on the particular population
served by the Sidomulyo Health Center, an area with a heightened prevalence of
hypertension. Employing the Spearman Rank correlation test method provides a
nuanced examination of the connections between lifestyle factors and stroke
risk, offering valuable insights for crafting tailored prevention and
intervention approaches for the local community. Moreover, the study
underscores the significance of addressing unhealthy lifestyle habits like
smoking and heavy drinking in stroke prevention endeavors, emphasizing the
necessity for comprehensive public health initiatives that target these
behaviors alongside established risk factors such as hypertension and physical
inactivity.
Research Methods
The study employed the Spearman Rank correlation test method to assess the correlation between variables. The selection of this method was driven by the nature of the data, where relationships between variables could be either positive or negative, and the data needed to be ordinally scaled. The research occurred at the Sidomulyo Health Center in the Tampan District of Pekanbaru City, from September 2022 to March 2023.
The research focused on stroke patients residing within the jurisdiction of the Sidomulyo Health Center, situated in the Tuah Madani District of Pekanbaru City. The study population comprised all individuals who had experienced stroke in the area, with a sample size of 41 respondents selected randomly. Data collection involved two approaches: primary data collection, which involved administering questionnaires to respondents within the health center's vicinity, and secondary data collection, which encompassed reviewing literature and gathering documentation from the health center.
The collected data is then processed through several steps, including editing to check the completeness of the data, coding to code the answer results, and tabulating to facilitate data analysis in the form of frequency distribution tables. The instrument used in this study was a questionnaire, which included questions about age, sex, environmental conditions, disease vectors, personal hygiene, snack habit behavior, and health services.
Next, data analysis was performed using the Spearman Rank correlation test method, which corresponds to the characteristics of the data used, where one or more variables are not normally distributed. This analysis aims to determine the relationship between variables in the study. Thus, the research methods include data collection techniques, data processing, and statistical analysis relevant to the research objectives.
Results and Discussion
The Spearman Rank Correlation Test Method was used to analyze the relationship between variables. This method was chosen due to the characteristics of the data utilized in the study:
1. The direction of the relationship between variables can be positive and negative.
2. The data used must be an ordinal scale.
3. There is no term independent variable (X) nor bound variable (Y).
4. Non-parametric statistical data where one or more variable data are
not normally distributed.
As for knowing whether the data
is parametric or nonparametric, as follows:
Table 1. One-Sample Kolmogorov-Smirnov Test
|
41 |
41 |
41 |
41 |
||
|
Normal Parametersa,b |
Mean |
6.34 |
6.93 |
7.15 |
6.59 |
|
Std. Deviation |
.762 |
.848 |
1.740 |
.894 |
|
|
Most Extreme Differences |
Absolute |
.318 |
.253 |
.190 |
.313 |
|
Positive |
.194 |
.253 |
.190 |
.224 |
|
|
Negative |
-.318 |
-.214 |
-.182 |
-.313 |
|
|
Test Statistic |
.318 |
.253 |
.190 |
.313 |
|
|
Asymp. Sig. (2-tailed) |
.000c |
.000c |
.001c |
.000c |
|
|
a. Test distribution is Normal. |
|||||
|
b. Calculated from data. |
|||||
|
c. Lilliefors Significance Correction. |
|||||
The provided data indicates that the data for the four variables are not normally distributed. Specifically, the variables for smoking habits, drinking habits, and stroke exhibit non-normal distribution, as evidenced by the significance value (Sig) of 0.000, which is less than the threshold of 0.05. Similarly, the data for the lack of activity variable demonstrates a non-normal distribution, with a significance value of 0.001. These findings are the basis for employing the Spearman Rank Correlation Test Method to analyze the relationship between these variables. Subsequently, the next step involves conducting the Spearman Rank Correlation Test to ascertain the relationships between the four variables, as presented in the table below.
Table 2. Correlations
|
|
Smoking Habits |
Drinking
Alcohol |
Lack of
Activity |
Stroke |
||
|
Spearman's pulled up |
Smoking Habits |
Correlation Coefficient |
1.000 |
.201 |
.158 |
.415** |
|
Sig. (2-tailed) |
. |
.209 |
.323 |
.007 |
||
|
N |
41 |
41 |
41 |
41 |
||
|
Drinking Alcohol |
Correlation Coefficient |
.201 |
1.000 |
-.020 |
.373* |
|
|
Sig. (2-tailed) |
.209 |
. |
.900 |
.016 |
||
|
N |
41 |
41 |
41 |
41 |
||
|
Lack of Activity |
Correlation Coefficient |
.158 |
-.020 |
1.000 |
.122 |
|
|
Sig. (2-tailed) |
.323 |
.900 |
. |
.446 |
||
|
|
|
N |
41 |
41 |
41 |
41 |
|
Stroke |
Correlation Coefficient |
.415** |
.373* |
.122 |
1.000 |
|
|
Sig. (2-tailed) |
.007 |
.016 |
.446 |
. |
||
|
N |
41 |
41 |
41 |
41 |
||
|
**. Correlation is
significant at the 0.01 level (2-tailed). |
||||||
|
*. Correlation is
significant at the 0.05 level (2-tailed). |
||||||
The results of the
table above need to be interpreted
as correlation analysis as follows.
1. See the significance of relationships
a. Variable smoking habits with stroke
b. Variable drinking habits with stroke
With a significance value (sig.) of 0.016, which is below the threshold of 0.05, there exists a significant relationship between drinking alcohol habits and stroke.
c. Variable lack of activity there is a significant relationship with stroke
Based on the output, significance value, or sig. (2-tailed) of 0.446 > 0.05 means no significant relationship exists between lack of activity and stroke.
2. See the strength level of a relationship
a.
Variable smoking habits with
stroke
The obtained correlation
coefficient is 0.415, indicating a moderate level of correlation between
smoking habits and stroke. This suggests a significant relationship between the
two variables.
b. Variable drinking habits with stroke
The output shows a correlation
coefficient of 0.373, indicating a moderate correlation between drinking habits
and stroke. This suggests a significant relationship between the two variables.
c. Variable lack of activity with stroke
Based on the output, a
coefficient of 0.122 indicates a very weak correlation between the lack of
physical activity variable and stroke.
3. See where your relationship is headed
a. Variable smoking habits with stroke
Based on the output, the
positive value of 0.415 signifies a unidirectional relationship between the two
variables. This implies that as smoking habits increase, the risk of stroke
also increases.
b. Variable drinking habits with stroke
According to the output,
the positive value of 0.373 indicates a unidirectional relationship between the
two variables. This suggests that as the habit of drinking alcohol increases,
the risk of stroke also increases.
c.
Variable lack of activity with
stroke
Based on the output, the positive value of 0.122 suggests a unidirectional relationship between the two variables. This implies that as the lack of physical activity increases, the risk of stroke also increases.
The conclusion is that smoking and drinking alcohol have a significant relationship with stroke risk. The relationship has a sufficient correlation with the direction the relationship is unidirectional. The higher the habit of smoking and drinking alcohol will cause an increased risk of stroke to our body. As indicated by Novida Rizky in 2011, the analysis revealed a noteworthy correlation between gender and the understanding of stroke risk factors (p = 0.020), as well as between educational level and the identification of early stroke symptoms (p = 0.006; r = 0.229). Similarly, according to Wayunah, in 2008, there was a significant link observed between hypertension (p = 0.035) and physical activity (p = 0.011) with the type of stroke. Notably, physical activity emerged as the most influential risk factor associated with this specific type of stroke, with an odds ratio (OR) of 5.8.
Discussion
The Spearman Rank Correlation Test Method results demonstrate a notable association between smoking and drinking habits and the likelihood of experiencing a stroke. Specifically, the correlation coefficients of 0.415 and 0.373, respectively, indicate a moderate correlation between these behaviors and the risk of stroke. These findings align with previous research, which has consistently linked smoking and heavy drinking to an elevated risk of stroke. It is essential to note the direction of these relationships. The positive correlation coefficients imply that as smoking and drinking habits increase, so does the risk of stroke. This suggests a one-way relationship where these habits contribute to stroke risk rather than stroke directly influencing them.
Conversely, the correlation coefficient of 0.122 between lack of physical activity and stroke risk is minimal, indicating no significant relationship between these factors. This finding aligns with prior studies that have identified physical activity as a protective factor against stroke. Overall, these results affirm the significance of smoking and drinking habits as substantial risk factors for stroke. They highlight the urgency of public health interventions aimed at reducing smoking and heavy drinking, particularly among populations vulnerable to stroke. Moreover, these findings align with existing research on stroke risk factors, reinforcing the importance of considering smoking and heavy drinking in stroke prevention and management efforts. To conclude, this study underscores the substantial link between smoking and drinking habits and stroke risk, emphasizing the need to address these behaviors in stroke prevention strategies, especially for high-risk populations.
Conclusion
References
Amarenco, Pierre. (2020). Transient ischemic attack. New
England Journal of Medicine, 382(20), 1933–1941.
Amareta, Dahlia Indah,
Perwiraningrum, Dhyani Ayu, & Arifianto, Aji Seto. (n.d.). Development
of audio-visual aid for health promotion media with Design Thinking at
Nutrition Care Center.
Bowleg, Lisa. (2021).
Evolving intersectionality within public health: from analysis to action. American
Journal of Public Health, Vol. 111, pp. 88–90. American Public Health
Association.
Chow, Lisa S.,
Gerszten, Robert E., Taylor, Joan M., Pedersen, Bente K., Van Praag, Henriette,
Trappe, Scott, Febbraio, Mark A., Galis, Zorina S., Gao, Yunling, & Haus,
Jacob M. (2022). Exerkines in health, resilience and disease. Nature Reviews
Endocrinology, 18(5), 273–289.
Dorey, Alyrene,
Scheerlinck, Pieter, Nguyen, Hoanvu, & Albertson, Timothy. (2020). Acute
and chronic carbon monoxide toxicity from tobacco smoking. Military Medicine,
185(1–2), e61–e67.
Hong, Ji Man, Kim, Da
Sol, & Kim, Min. (2021). Hemorrhagic transformation after ischemic stroke:
mechanisms and management. Frontiers in Neurology, 12, 703258.
Jakše, Boštjan,
Godnov, Uroš, Fras, Zlatko, & Fidler Mis, Nataša. (2024). Associations of
Dietary Intake with Cardiovascular Risk in Long-Term “Plant-Based Eaters”: A
Secondary Analysis of a Cross-Sectional Study. Nutrients, 16(6),
796.
Jeong, Su Min, Jeon,
Keun Hye, Shin, Dong Wook, Han, Kyungdo, Kim, Dahye, Park, Sang Hyun, Cho, Mi
Hee, Lee, Cheol Min, Nam, Ki Woong, & Lee, Seung Pyo. (2021). Smoking
cessation, but not reduction, reduces cardiovascular disease incidence. European
Heart Journal, 42(40), 4141–4153.
Kingham, Amelia,
Kemps, Eva, Prichard, Ivanka, & Tiggemann, Marika. (2023). The effect of
spatial separation on food and drink choices from an online menu. Eating Behaviors,
51, 101816.
Marahatta, Sujan Babu,
Yadav, Rajesh Kumar, Giri, Deena, Lama, Sarina, Rijal, Komal Raj, Mishra, Shiva
Raj, Shrestha, Ashish, Bhattrai, Pramod Raj, Mahato, Roshan Kumar, &
Adhikari, Bipin. (2020). Barriers in the access, diagnosis and treatment
completion for tuberculosis patients in central and western Nepal: A
qualitative study among patients, community members and health care workers. PloS
One, 15(1), e0227293.
Pohl, Marietta,
Hesszenberger, David, Kapus, Krisztian, Meszaros, Janos, Feher, Andrea, Varadi,
Imre, Pusch, Gabriella, Fejes, Eva, Tibold, Antal, & Feher, Gergely.
(2021). Ischemic stroke mimics: a comprehensive review. Journal of Clinical
Neuroscience, 93, 174–182.
Ricka Marliana,
P032014401074. (2023). Penerapan Mirror Therapy dalam meningkatkan kekuatan
otot pada lansia dengan Stroke non Hemoragik di Wilayah Kerja Puskesmas
Sidomulyo. Poltekkes Kemenkes Riau.
Sciences, National
Academies of, Division, Medicine, Health, Board on Population, Practice, Public
Health, People, Committee on Informing the Selection of Leading Health
Indicators for Healthy, & 2030. (2020). Leading health indicators 2030:
advancing health, equity, and well-being.
Yehuda, Maayan Bar,
Barak, Sharon, Hutzler, Yeshayahu, Ng, Kwok, Giladi, Ariela, Meir, Lilach Bar,
Marques, Adilson, Zigdon, Avi, Zwilling, Moti, & Reges, Orna. (2023).
Cardiovascular risk profiles clusters among children and adolescents with
disabilities. BMC Public Health, 23(1), 896.
Zavala, Valentina A.,
Bracci, Paige M., Carethers, John M., Carvajal-Carmona, Luis, Coggins, Nicole
B., Cruz-Correa, Marcia R., Davis, Melissa, de Smith, Adam J., Dutil, Julie,
& Figueiredo, Jane C. (2021). Cancer health disparities in racial/ethnic minorities
in the United States. British Journal of Cancer, 124(2), 315–332.
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Copyright holder: Chairil (2024) |
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First publication right: Advances in Social Humanities Research |
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