How is the relationship between life style and cardiovascular diseases? A case- control study

Abstract

Background

Considering the high prevalence of cardiovascular diseases (CVDs) in most countries of the world and in Iran, lifestyle modification is emphasized as one of the effective factors for the prevention and control of these diseases. Therefore, this study aimed to investigate the association between lifestyle and CVDs.

Methods

This study utilized a case-control design, involving 99 individuals with CVDs such as hypertension, angina, heart attack, coronary artery disease, heart failure, arrhythmia, and valve diseases as the case group. The control group consisted of 396 participants without CVDs, all of whom were patients at Imam Ali and Imam Reza hospitals in Kermanshah in 2023. Inclusion criteria for the case group included a confirmed diagnosis by a physician, ages 18–65, use of at least one cardiac medication, no sensory or cognitive impairments, and the ability to communicate in Farsi or Kurdish. Additionally, participants could not have serious underlying conditions like metastatic cancer or kidney failure, nor could they be hemodynamically unstable. Data collection was conducted through convenience sampling and involved a questionnaire developed by Eshaghi et al., which included 46 questions across five domains: preventive measures, physical activity, nutrition, stress management, and social relationships. Trained interviewers worked with hospital administration to identify eligible participants in inpatient wards. Statistical analyses, including Chi-square tests, independent t-tests, and one-way ANOVA, were performed using Stata software. factors, including age, education, income, job, marital status, knowledge of computer, source of received health information, were adjusted during statistical analysis. The logistic regression model was used to determine the relationship between lifestyle and its dimensions and CVDs with the control of confounding variables, and adjusted odds ratio was reported with a confidence level of 95%.

Results

Based on the results the mean score of lifestyle in CVDs patients was 146.66 ± 23.87 and in the control group was 169.4 ± 25.86 and it means moderate level of lifestyle. There was significant relationship between life style and CVDs, so that with increasing one unit in the mean score of life style, the odds of CVDs significantly decreased by 6% (OR = 0.94, CI: [0.93, 0.96], p < 0.001). Although, a significantly relationship was found between the mean score of each dimention of life style (including prevention, physical activity, sports, …, healthy diet, stress management, social and interpersonal relationships) and CVDs. In other words, with increasing one unit in the mean score of the each dimention of life style, the odds of CVDs significantly decreased by at least 12% (p < 0.001).

Conclusion

According to the correlation between lifestyle and cardiovascular diseases, it is imperative to implement appropriate interventions. The enhancement of nutritional status, social connections, and stress management, alongside social and community-centered interventions to facilitate physical activity and healthy leisure activities, as well as individual coaching to enhance lifestyle, can contribute to the prevention and mitigation of CVDs prevalence. Therefore, it is advisable for policymakers in the health sector to prioritize these aspects in their intervention strategies.

Introduction

Interventional studies have shown that reducing risk factors will reduce the rate of coronary heart disease, stroke and other cardiovascular diseases [1]. Therefore, to prevent and control these diseases, it is emphasized to improve “lifestyle” [2]. Adhering to a healthy lifestyle plays a decisive role in increasing life expectancy [3], improving the quality of life and physical and mental health [4], and is also effective in preventing various diseases [5]. According to the definition of the World Health Organization, “Lifestyle” is the normal and usual daily activity that people have accepted in their lives; these activities affect people’s health. Lifestyle is a combination of behavioral patterns and individual habits throughout life, including eating habits, physical activity, stress, use of tobacco and alcohol, sleep quality [6, 7], weight control, immunization against diseases, adaptation to stress and the ability to use family and community support [6].

The general health of each person is directly related to his lifestyle [8]. Some habits and daily life activities have a positive effect on a person’s health, and some of these daily life activities are risk factors that are harmful and put a person’s health at risk [9]. There have been researched about the relationship between daily and usual life activities or lifestyle with improving the individual’s health, and today, the health effects of lifestyle are being paid attention in the whole world. For instance, as stated by Pasdar et al., [10] in their research conducted in Iran, smoking emerges as a distinct individual risk factor for CVDs. Furthermore, the confluence of smoking with additional risk factors like diabetes, hypertension, dyslipidemia, obesity, low physical activity, and old age escalates the susceptibility to CVDs. Also, among the risk factors for CVDs, dyslipidemia is commonly linked to the onset of CVDs. Conversely, recent research indicates that addressing unhealthy dietary practices and sedentary behavior plays a crucial role in managing dyslipidemia. Therefore, numerous scientific bodies advocate adopting nutritious dietary patterns like the Mediterranean Diet (MedDiet), Dietary Approaches to Stop Hypertension (DASH), Portfolio Diet, Vegetarian Diet, and Nordic Diet [11, 12]. People with an unhealthy lifestyle are more likely to have poor physical performance and poor health, and as a result, have an unfavorable quality of life [13, 14].

Since lifestyle is one of the factors affecting health [15, 16], therefore health status and lifestyle are closely related. The studies conducted in different parts of the world indicate that the incidence of CVDs can be significantly reduced with healthy lifestyle. Also, primary prevention through lifestyle modification has a high preventive potential [17, 18]. In Iran, previous studies examined the lifestyle of people suffering from CVDs, indicating that lifestyle level of these people was moderate to low [19, 20]. Examining the relationship between lifestyle and CVDs in Iran has shown different results in several studies with different populations or study designs. For example, the cros- sectional study of Rezapour Gatabi et al., [21] among 190 CVDs patients refered to 3 educational hospitals of Babol university of medical sciences using health and life style questionnaire, showed that a large number of CVDs patients had a poor lifestyle, but the relationship between lifestyle and health of patients was not significant. In addition, the results of the case- control study of Zareipour et al.‘s [22] among patients with ischemic heart dieaeses (IHDs) refered to health centers of Urmia city using lifestyle questionnaire (LSQ) showed that there statistically significant difference between the two studied groups in terms of weight control and nutrition and exercise and health, physical health, social health, spiritual well-being, mental health and disease prevention.

Since CVDs is a chronic process that starts at a young age and progresses gradually [23], effective measures to improve people’s lifestyle can be proper strategy in improving the health status and utilization of health services and reducing the prevalence of heart diseases and significant economic burden imposed on the patient and the society. Therefore, according to the mentioned contents and the prevalence of CVDs in the country and considering the role of people’s lifestyle in reducing the burden of these diseases, the present study aims to investigate the status of lifestyle, and analyze the relationship between the lifestyle and CVDs among patients referred to Imam Reza and Imam Ali hospitals in Kermanshah city.

Methods

Study design

This case-control study was conducted in 2023. Patients suffering from CVDs (hypertension, angina pectoris, heart attack, coronary artery diseases, heart failure, arrhythmia, valve diseases) referred to the inpatient heart and cardiac care departments in Imam Reza and Imam Ali hospitals in Kermanshah, which were recently diagnosed, considered as case group. In this study, the control group were other patients referred to the mentioned hospitals who were not suffering from CVDs. In addition to the inpatient department for heart patients, the mentioned hospitals have other departments such as gastroenterology, infectious diseases, urology, etc. Therefore, the control group was selected from admitted patients of other departments who have not been diagnosed with heart disease. These patients were included in the study, randomly based on these items: stable health status, desire to participate in the study, and the permission of the patient’s treatment team to participate in the study. This process continued until the completion of the questionnaires.

Sample and sampling method

The samples were selected using the convenience sampling sampling method and according to the inclusion criteria and willingness to participate in the study. For this purpose, considering the information of Eshghizadeh et al.‘s study [24], using the following formula, the mean and standard deviation of lifestyle in the case group and in the control group were 56.29 ± 9.5 and 51.41 ± 11.57, respectively. Taking into account the first type error of 5% and with a power of 80%, the number of samples in each group was estimated to be 99 people. According to the type of study design and with the aim of increasing the power of the study, four control will be taken for each case. In case-control studies, to increase the power of the study, the number of controls is increased up to 4 times [25]. Therefore, in thic study, 99 cases and 396 controls were included in the study.

The specific inclusion criteria for case group were confirmation of the cardiac disease diagnosis by the attending physician, consumption of at least one cardiac drug by the patient. These criteria for control group including diagnosed disease other than CVDs. In addition, age range of 18–65 years, no sensory perception disorder or mental retardation, ability to speak and understand Farsi language or Kurdi will be done by the patient or his family caregiver, the lack of serious and severe underlying disease (such as metastatic cancer, kidney failure) and hemodynamic instability were considered as other inclusion criteria for participants. The exclusion criteria were having a disease other than heart disease (for case group), age more than 65 years or less than 18 years, inability to speak and sensory disorder.

Instruments

To measure the lifestyle, the healthy lifestyle assessment questionnaire of Eshaghi et al., [26] was used. The face and content validity and reliability of this tool was investigated in the mentioned study and the opinions of 8 experts in the field of lifestyle, geriatric medicine, or questionnaire design, as well as 10 elderly people, were applied. The reliability of the tool was also done with the participation of 30 elderly people. Cronbach’s alpha coefficient was calculated as 0.72. Also, in our study reliability of this questionnaire was determined by using the opinions of 30 participants. The Cronbach’s alpha coefficient was found to be equal to 0.76. This questionnaire including 46 questions and five domains including: prevention (15 questions; score range from 15 to 75 ), physical activity, sports, recreation and entertainment (5 questions; score range from 5 to 25), healthy eating (14 questions; score range from 14 to 70), stress management (5 questions; score range from 5 to 25), social and interpersonal relationships (7 questions; score range from 7 to 35). The response scale of this questionnaire includes action repetition scale and multiple choice scales (single answer or multiple answer). The participants answered each of the questions based on 5 point likert scale including: very high (score 5) high (score 4), moderate (score 3), low (score 2), very low (score 1). The total score of life style is obtained from the sum of the scores of the questions. After summarizing the scores of the questions, the score is 46–99: unfavorable lifestyle, 100–154 score: moderate lifestyle, and 155–211 score: favorable lifestyle.

Data collection

After obtaining the ethics code of study from the ethics committee of Kermanshah University of Medical Sciences, the data was collected by two interviewers who were trained by the research team. The data was collected from February 28, 2023, to June 9, 2023 in Imam Reza and Imam Ali hospitals of Kermanshah during 40 days. The interviewers visited the inpatient wards after coordinating with the hospital manager to identify the participants. After confirmation from the medical team of the participants, the objectives of the study were explained to them, and then an informed consent form was obtained. If the participants was unable to complete the questionnaire for any reason, including illiteracy, the interviewers asked the question and record the answer.

Statistical analysis

The collected data were entered into SPSS software version 22. According to the normality or non-normality of data distribution, parametric or non-parametric tests were used to determine the relationship between the studied variables. Descriptive statistics were also used to determine the distribution or mean of variables according to case and control groups. For quantitative data, mean and standard deviation were reported, and for qualitative variables, frequency and percentage were reported. To analyze the data, chi-square statistical tests or independent t-tests were used to compare the distribution of qualitative or quantitative variables in the two control groups. One-way analysis of variance (ANOVA) was used to compare the mean of life style according to the demographic characteristics Also, the logistic regression model was used to determine the relationship between lifestyle and the outcome under study and with the control of confounding variables, and the raw and adjusted odds ratio was reported with a confidence level of 95%. Factors, including age, education, income, job, marital status, knowledge of computer, source of received health information, were adjusted during statistical analysis.

Results

The mean age of the control and case groups was 40.47 ± 12.41, and 43.51 ± 12.17 years, respectively. In the control group, most of the participants were male and diploma or under diploma. In the case group, most of the participants were female and had academic education. In both groups, most of the participants were married and living in the city. The level of familiarity with computer knowledge was moderate to high in 46.46% and 35.36% of case and control groups, respectively. Other demographic characteristics of both groups are shown in Table 1. Also, as shown in Table 1, there is a statistically significant difference between knowledge of computer (p < 0.01), income (p < 0.001), and job status (p < 0.001), source of received health information (p < 0.01) among the control and case group.

Table 1.

Distribution of demographic variables among participants

Variable		Individuals with non-CVDs conditions N (%)	CVDs patientsN (%)	P-value
Mean Age		40.47±12.41	43.51±12.17	0.029
Gender	Male	206 (52.0)	48 (48.5)	0.529
	Female	190 (48.0)	51 (51.5)
Education	Illiterate	26 (6.57)	11 (11.11)	0.106
	Diploma and Under Diploma	188 (47.47)	37 (37.37)
	Academic	182 (45.96)	51 (51.52)
Marital status	Single	158 (39.9)	31 (31.31)	0.116
	Married	238 (60.1)	68 (68.69)
Place of residence	Urban	329 (83.08)	82 (82.83)	0.952
	Rural	67 (16.92)	17 (17.17)
Knowledge of computer	Unfamiliar	84 (21.21)	18 (18.18)	0.014
	Very low	96 (24.24)	11 (11.11)
	low	76 (19.19)	24 (24.24)
	Moderate	98 (24.75)	37 (37.37)
	High	42 (10.61)	9 (9.09)
Income status	Enough	338 (85.35)	47 (47.47)	0.001
	Not enough	58 (14.65)	52 (52.53)
Job status	Retired	28 (7.07)	15 (15.15)	0.000
	Unemployed	57 (14.39)	7 (7.07)
	Employed	79 (19.95)	33 (33.33)
	Other	232 (58.59)	44 (44.44)
Source of received health information	Public Media	153 (38.64)	37 (37.37)	0.01
	Physician	5 (1.26)	6 (6.06)
	Social Networks	118 (29.8)	35 (35.35)
	Other	120 (30.3)	21 (21.21)

Considering that there was a statistically significant difference between the case and control groups in age, education, income, job, marital status, knowledge of computer, source of received health information, the results have been adjusted for theses demographic characteristics. According to Table 2, the mean score of lifestyle among CVDs patients was 146.66 ± 23.87 and in the control group was 169.4 ± 25.86 and it means moderate level of lifestyle. In addition, in both case and control groups, mean score of prevention was highest and mean score of physical activity, sports, recreation and entertainment was the lowest. There is a statistically significant difference between the case and control groups in all domains of lifestyle.

Table 2.

The comparison of life style and its dimensions mean score by individuals with non-CVDs conditions and CVDs patients

Variables	CVDs patients	Standard Error	Individuals with non-CVDs conditions	Standard Error	P-value
Adjusted mean of life style	146.66 ± 25.86	2.6	169.40 ± 23.87	1.2	< 0.001
Prevention*	47.18 ± 75.42	7.58	53.76 ± 180.09	9.05	< 0.001
Physical activity, sports, …*	14.45 ± 38.8	3.9	18.98 ± 69.45	3.49	< 0.001
Healthy diet*	38.89 ± 74.62	7.5	45.65 ± 145.46	7.31	< 0.001
Stress management*	17.23 ± 28.15	2.83	19.19 ± 68.25	3.43	< 0.001
Social and interpersonal relationships*	28.58 ± 37.11	3.73	28.52 ± 105.86	5.32	< 0.001

*Adjusted for age, education, income, job, marital status, knowledge of computer, source of received health information

As shown in Table 3, based on the results of logistic regression analysis, in both crude and adjusted models, there is a significant positive relationship between lifestyle with CVDs. So that with increasing one unit in the score of life style, the odds of CVDs significantly decreased by 4% (OR = 0.96, CI: [0.95, 0.97], p < 0.001) and in adjusted model, with increasing one unit in the score of life style, the odds of CVDs significantly decreased by 6% (OR = 0.94, CI: [0.93, 0.96], p < 0.001). Although, a significantly relationship was found between mean score of each dimentions of life style and CVDs. In adjusted model, with increasing one unit in the mean score of each dimentions including prevention, physical activity, sports, …, healthy diet, stress management, and social and interpersonal relationships, the odds of CVDs significantly decreased by 12% (OR = 0.88, CI: [0.85, 0.91], p < 0.001), 38% (OR = 0.62, CI: [0.56, 0.69], p < 0.001), 18% (OR = 0.82, CI: [0.78, 0.87], p < 0.001), 22% (OR = 0.78, CI: [0.72, 0.85], p < 0.001), and 12% (OR = 0.88, CI: [0.82, 0.92], p < 0.001), respectively. In other words, with increasing one unit in the mean score of each dimention of life style, the odds of CVDs significantly decreased by at least 12%. This is while in the Crude model, the odds of CVDs significantly decreased by at least 9%.

Table 3.

Results of logistic regression analysis, associations between the life style’s dimensions and CVDs

Variables	Crude model			Adjusted model
	Odds Ratio	P>|z|	[95% CI]	Odds Ratio	P>|z|	[95% CI]
Life style	0.96	< 0.001	0.95, 0.97	0.94	< 0.001	0.93, 0.96
Prevention*	0.91	< 0.001	0.89, 0.94	0.88	< 0.001	0.85, 0.91
Physical activity, sports, …*	0.7	< 0.001	0.64, 0.76	0.62	< 0.001	0.56, 0.69
Healthy diet*	0.88	< 0.001	0.85, 0.91	0.82	< 0.001	0.78, 0.87
Stress management*	0.83	< 0.001	0.77, 0.89	0.78	< 0.001	0.72, 0.85
Social and interpersonal relationships*	0.89	< 0.001	0.85, 0.93	0.88	< 0.001	0.82, 0.92

*Adjusted for age, education, income, job, marital status, knowledge of computer, source of received health information

Discussion

The results of this case-control study, which was conducted with the aim of investigating the relationship between lifestyle and CVDs, showed that there is a negative and significant relationship between lifestyle and CVDs. This result is consistent with the results of Park et al.‘s and Colpani et al.,‘s studies [18, 27]. However, in the study of Rezapour gatabi et al., [21] no statistically significant relationship was found between lifestyle and CVDs. It can be said, in the current study the illiteracy and low level of education of a large number of patients can indicate the possibility of the lack of knowledge needed for a suitable lifestyle. In terms of employment status, as can be seen, CVDs were retired and unemployed, which is a major reason for inactivity and unhealthy lifestyle. In additin, the level of computer knowledge of most of the participants in both groups was low and lower and it affect individual’s ability for achive more information on activities imprveing health status.

In this study, the lifestyle was evaluated on moderate level, which is in line with Abedi et al.,‘s study in 2013, where the most of the research units (41.1%) had moderate lifestyle. The results of this study showed that some dimendions of the lifestyle of patients with CVDs, including eating habits at moderate level, stress at good level, physical activity and exercise were at weak level. Therefore, the results of this study can be used in various fields such as nursing education, management of nursing services and research to improve the health level of the society [28], while the findings of Firoz Jah’s study showed that a large number of patients who were suffering from CVDs, had a poor lifestyle and only a few of them had a good and proper lifestyle. Based on the results of this study, it is necessary to pay attention and emphasize the role of health education with the aim of familiarizing patients with a suitable lifestyle to prevent the occurrence of diseases such as cardiovascular disease as a preventive factor [20].

In the current study, the score of dimensions including stress management and physical activity, sports… was lower than other dimensions, it can be said that the skills of stress management and establishing interpersonal and social relationships of people have improved as a result of life experience of the past years and can be effective in reducing people’s CVDs, therefore, it is recommended to take necessary measures to improve these skills. Also, encouraging people to engage in physical activity as one of the dimensions of lifestyle requires actions at the individual and community level, and in addition to holding training courses to create motivation in people, the relevant managers should provide access to the necessary facilities for sports and physical activity at the community level.

In present study, incom status of most individyuals in the case group was not enaugh and it can be affective on life style. This is while people with favorable economic status have better health status due to the over-care. Results of Wang et al.,‘s study [29] indicate that lifestyle plays a mediating role in the relationship between socioeconomic status (SES) and health. In addition, according to Davari et al.,’s study [30] the effect of SES on cardiovascular health is significant. The SES is a combination of various characteristics, including income, employment status, education, etc., but in the present study, only the income of the participants was examined, so the results of the study may have been affected. In addition, based on previous studies [31, 32], comorbidity are prevalent in CVDs patients, however, based on self report nature of our study, this item is not considered.

Based on the Simmel, Weber and Bourdieu’s theory, some of the elements of lifestyle are eating habbits, the type transportation, the ways of spending leisure and recreation, smoking in public environment [33]. Therefore, different organizations should plan in their field of work to improve each of these conditions. In the present study, considering the relationship between healthy diet and CVDs, carrying out measures to benefit the individuals from a healthy diet by the decision makers, can be effective in reducing the prevalence of CVDs. Also, according to Chapin’s theory [34], cultural assets, income, material assets and participation in social group activities are the factors that make up lifestyle. Considering that in this study, most of the people with CVDs did not have enough income and income affects the lifestyle components [35], people with low income should be considered in lifestyle improvement programs.

One of the strengths of this study is its case-control design. Other studies have investigated the lifestyle status of people with CVDs using descriptive analysis dedign and without comparing with the control group. Also, the hospitals in which the present study was conducted are the largest hospitals in the west of Iran, where patients from different provinces with different ethnicities and races visit these two hospitals, and the studied sample can be indicative of the lifestyle and Cardiovascular diseases of the country. Based on our knowledge and also review of previous studies, no study was found that nvestigated the correlation of heart knowledge and cardiac risk factors with readiness for lifestyle modification in patients with cardiovascular diseases in the west of Iran.

Limitations

One of the limitation of this study is self-report nature of the lifestyle assessment, for minimize bias or ensure the accuracy of the data, the questionnaire was completed by the participants. If the participants had a problem in understanding any of the questions of questionnaire, the interviewer carefully explained the question to the participants so that the answer would have sufficient accuracy. Inaddition, in order to comply with the principles of evidence-based practice, medical researchers are required to report the clinical relevance of the results to the clinical community. This helps disseminate evidence in a useful and understandable way for end users such as patients, healthcare practitioners and policy/decision makers. Information on “p’’ values is not sufficient to achieve these requirements, and because it provides insufficient and limited information, clinical researchers must provide the clinical relevance of their results to help busy clinicians easily interpret research results in clinical practice. Calculation of effect size (ES), minimal detectable change (MDC)/difference (MDD), and standard error of measurement (SEM) are examples of distribution-based methods that provide correlation between clinical outcomes. Inaddition, due to the self-report nature of the study, it was not possible to identify comorbidity in the case and control groups confirmed by the physician, and this is another limitations of the study.

In addition, according to the data collected, the type of CVDs of the participants was not specified for each individual and the participants were included in the study solely based on the presence of CVDs conditions including hypertension, ischemic heart disease, arrhythmias, heart failure, valve diseases. Therefore, it is not possible to present the distribution of CVDs in the case group at this time to perform disease-specific analyses for the most common CVDs conditions. Another limitation of the current study is that the optimal parameters for ascertaining the sample size within the present research context are not satisfied. In order to accurately establish the sample size, it is advisable to utilize the same methodological framework and measurement instrument as those employed in the original study. In instances where the research is of a descriptive nature, it is more beneficial to utilize a contextually relevant study for sample size determination; however, this study adopts an analytical framework, and no preceding analytical research has been identified in Iran that utilized the questionnaire developed by Eshghizadeh et al.‘s [24] (the instrument employed in this study) within a case-control design. Consequently, the aforementioned criteria are not fulfilled in this investigation, thereby necessitating the reliance on a study that shared a similar design to the current research for the purpose of sample size calculation.

Conclusion

Based on the results of the present study, there is a negative and statistically significant relationship between people’s lifestyle and CVDs, which emphasizes that it is necessary to take steps to improve the lifestyle of people from an early age. Considering the impact of improving nutritional status, improving social relations and stress management, as well as social and community-oriented interventions in order to provide conditions for physical activity and healthy recreation and entertainment, and individual training in improving individual’s life style, followed by prevention and reduction the prevalence of cardiovascular diseases, it is recommended that the relevant policy makers focus on these items in their intervention planning.

It is also recommended that researchers in the future conduct a qualitative study to investigate the obstacles and challenges of individuals in improving lifestyle and then reducing the incidence of heart diseases with the participation of people from different groups. Conducting interventional studies to investigate the impact of each of the potentially influential variables on lifestyle improvement and comparing their impact with the aim of determining the most effective factors in each of the different age and gender groups can provide good results for proper planning. Furthermore, given that the comorbidity of the participants was not accounted for in this study, it is recommended that researchers prioritize this factor in forthcoming research. Given the significance of potential confounding variables in the correlation between lifestyle and cardiovascular well-being, the undertaking of longitudinal research to explore the causal crelationship between lifestyle and cardiovascular health outcomes may yield valuable findings for design of impactful interventions.

Abbreviations

CVDs

Cardiovascular Diseases

CHDs

Chronic Heart Diseases

SES

Socioeconomic Status

HRQoL

Health Related Quality Of Life

IHDs

Ischemic Heart Dieaeses

CI

Confidence Interval

Authors’ contributions

RM, AMK, BK: Conception or design of the work; KhS: Data collection; ShR and BK: Data analysis and interpretation; BK, HD, ShR, and ESh: Drafting the article, Critical revision of the article, and Final approval of the version to be submitted.

Funding

No funding to declare.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

The ethical committee of the KUMS (Kermanshah University of medical sciences) approved the study protocol (ethics code IR.KUMS.MED.REC.1401.253). All participating provided written informed consent for participating in this study. The text of written informed consent was explained to illiterate individuals, if they were satisfied, the consent form was received. This study was performed in accordance with relevant guidelines and regulations in the Declaration of Helsinki.

Competing interests

The authors declare no competing interests.