July 2015
Volume 56, Issue 8
Free
Clinical and Epidemiologic Research  |   July 2015
Visual Impairment of Korean Population: Prevalence and Impact on Mental Health
Author Affiliations & Notes
  • Ga Eun Cho
    Department of Ophthalmology Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
  • Dong Hui Lim
    Department of Ophthalmology Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
  • Minji Baek
    The Korean Ophthalmological Society, Seoul, Korea
  • Hoyoung Lee
    Department of Ophthalmology Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
  • Sang Jin Kim
    Department of Ophthalmology Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
  • Se Woong Kang
    Department of Ophthalmology Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
  • for the Epidemiologic Survey Committee of the Korean Ophthalmological Society
    Department of Ophthalmology Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
  • Correspondence: Sang Jin Kim, Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-dong, Gangnam-gu, Seoul, 135-710, Korea; sangjinkim@skku.edu
Investigative Ophthalmology & Visual Science July 2015, Vol.56, 4375-4381. doi:10.1167/iovs.15-16462
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      Ga Eun Cho, Dong Hui Lim, Minji Baek, Hoyoung Lee, Sang Jin Kim, Se Woong Kang, for the Epidemiologic Survey Committee of the Korean Ophthalmological Society; Visual Impairment of Korean Population: Prevalence and Impact on Mental Health. Invest. Ophthalmol. Vis. Sci. 2015;56(8):4375-4381. doi: 10.1167/iovs.15-16462.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: We identified the prevalence and sociodemographic characteristics of people with visual impairment (VI), and determined the relationship between VI and mental health in the Korean population.

Methods: This is a cross-sectional study using the database of the Korean National Health and Nutrition Examination Survey from 2008 through 2012. A total of 28,392 participants at 19 years of age or older with data of visual acuity and mental health questionnaire was included. Prevalence of VI and its association with sociodemographic factors were analyzed. Multivariate regression analyses were conducted to determine the association of VI with mental health.

Results: Estimated prevalence of VI was 0.43% (95% confidence interval [CI], 0.35–0.52%) in adults aged 19 years and over. After adjusting for sex, the VI group was significantly older (P < 0.001). After adjusting for age and sex, the VI group showed increased odds ratios (ORs) for diabetes mellitus (P < 0.001), lower education (P < 0.001), no occupation (P = 0.046), restricted daily activity (P < 0.001), and being single (P = 0.002) compared to the control group. After adjusting for covariates, VI was not associated with any of mental health parameters (OR, 0.88 [95% CI, 0.53–1.47] for depressive symptom; 1.38 [0.91–2.09] for suicidal ideation; 1.26 [0.82–1.94] for perceived stress). However, restricted daily activity was the strongest risk factor for poor mental health (OR, 2.49 [2.22–2.79] for depressive symptom; 2.77 [2.51–3.06] for suicidal ideation; 2.30 [2.09–2.54] for perceived stress).

Conclusions: Visually impaired people showed significantly unfavorable sociodemographic status. Although VI was not directly associated with mental health, restricted daily activity and poor sociodemographic factors found in visually impaired people increased risk for poor mental health.

Depression, one of the most common mental disorders, is considered as a major health problem in many developed countries. The association of visual impairment (VI) and depression has been investigated by several population-based studies and the majority of these studies found a significant association between VI and depression.16 Also, impacts of VI on other psychological aspects, including anxiety,7 poor perceived health,8 risk of suicide,9,10 and cognitive impairment,11 have been well documented in population- or hospital-based studies. Most previous population-based studies on the association of VI and mental health were conducted in Western countries. A few of them were conducted in Asian countries using elderly population.1,4 Other studies regarding Asian population were either hospital-based or limited to specific ophthalmic diseases.7,11,12 
Korean patients with depression were found to show different clinical characteristics from American patients. Korean patients experienced less frequency of depressive mood and guilt, but higher frequency of suicidality and hypochondriasis.13 As one of the fastest developed countries, a recent report revealed that Koreans in general showed higher mortality rates from suicide than other developed countries.14 However, to our knowledge there has been no population-based study regarding the association of VI and mental health in Koreans. Therefore, the objectives of this study were to identify the prevalence and sociodemographic characteristics of participants who have VI, and determine the relationship between VI and mental health parameters, including depressive symptom, suicidal ideation, and perceived stress, in South Korea using data from the Korea National Health and Nutrition Examination Survey (KNHANES) that represents the nationwide population. 
Methods
KNHANES Study
The KNHANES study is an ongoing, population-based, cross-sectional survey in South Korea conducted by the Korea Centers for Disease Control and Prevention and the Korean Ministry of Health and Welfare. It is composed of three different sections: a health interview, a health examination, and a nutrition survey. To obtain a representative sample of the population, this survey used a stratified multistage probability sampling method based on the component ratio of population, geographic area, and administrative district. Respondents with data were assigned weightings to ensure an equal probability of being sampled and to cover missing data. The detailed design of KNHANES has been described previously.15 Response rates were 77.8%, 82.8%, 81.9%, 80.4%, and 80.0% in 2008, 2009, 2010, 2011, and 2012, respectively. Ophthalmologic survey and examination were conducted on participants aged ≥19 years from July 2008 to December 2012. This study analyzed data obtained from this period. Of 37,982 subjects who participated in KNHANES, we limited the analyses to adults aged ≥19 years (Fig. 1). We excluded subjects without best-corrected visual acuity (BCVA) for prevalence analysis. In addition, we excluded those without a mental health questionnaire for association analysis. Finally, a total of 28,392 subjects (12,095 men and 16,297 women) was included in this study. Institutional Review Board of Samsung Medical Center approved the present study, which was conducted in accordance with the Declaration of Helsinki. 
Figure 1
 
Flow chart of the study population.
Figure 1
 
Flow chart of the study population.
Visual Acuity (VA) Assessment
Initially, uncorrected VA and corrected VA with the subject's own glasses or contact lens were measured at a distance of 4 m using an international standard vision chart based on logMAR Scale (Jin's vision chart, Seoul, Korea). When the presenting VA was worse than logMAR 0.1 (Snellen, 20/25), examination with automated or subjective refraction was performed using automated keratorefractometer (KR-8800; Topcon, Tokyo, Japan). If the second VA was worse than logMAR 0.1, pin hole was added to measure the final corrected VA. VI was defined as BCVA of worse than logMAR 0.5 (Snellen, 20/63) in the better-seeing eye, according to the definition of low vision, defined as VA worse than logMAR 0.48 but better than or equal to logMAR 1.30 in the better seeing eye (Snellen, ≥20/400, <20/60) and blindness, defined as VA worse than logMAR 1.30 in the better seeing eye (Snellen, <20/400) by the World Health Organization (WHO).16 Control group was defined as subjects with BCVA of logMAR 0.5 or better in the better-seeing eye. 
Mental Health Questionnaire
Mental health questionnaire was included in a section of health interview. Under the supervision of a trained investigator, participants self-reported to serial questionnaires. Depressive symptom (“yes” vs. “no”) was assessed by asking “Have you felt sad or despair continuously for longer than 2 weeks that was enough to interfere with daily life during the last year?” Perceived stress was assessed by asking “How much stress do you usually experience in your daily life?” For answer, numerical measures of stress (4 = severe stress, 3 = moderate stress, 2 = slight stress, 1 = no stress) were used. For analysis, we categorized the responses as “severe or moderate stress” and “slight or no stress.” To assess suicidal ideation, participants were asked, “Have you thought seriously about suicide in the past 12 months?” This question also was answered with a “yes” or “no” response. 
Definition of Variables
Data regarding demography and medical history were obtained from KNHANES IV and V. They were defined and categorized as below. Participants were divided into six age groups: 19 to 29, 30 to 39, 40 to 49, 50 to 59, 60 to 69, and 70 years or older. Comorbidities, including diabetes mellitus and hypertension, were divided to participants with and without a history of comorbidities. House income status was divided into quartiles: the lowest (≤25%), lower middle (>25%, ≤50%), upper middle (>50%, ≤75%), and the highest (>75%). Education status was divided into three groups: participants with education of 6 years or less (elementary school), those with 7 to 12 years of education (middle school and high school), and those with more than 12 years of education (university). Occupation was categorized as participants with and without occupation (unemployed, retired, student, and homemaker). Marital status was divided into three groups: married, separated (divorced, widowed, and separated), and never married based on questionnaire responses. Restricted daily activity was surveyed from health interview by asking a question “Currently do you experience any restriction in your daily life due to health, physical, or mental disabilities?” Participants were categorized into two groups: participants with and without restricted daily activity. 
Statistical Analysis
The data were analyzed with SAS software version 9.2 (SAS, Inc., Cary, NC, USA) using proc survey procedures to analyze the presented data properly using variable of strata, cluster, and weight. We used KNHANES sample weight to adjust for oversampling, nonresponse, and the Korean population from 2008 through 2012. The standard errors of estimates were calculated. P values less than 0.05 were considered statistically significant. Logistic regression analysis was conducted to evaluate associations between depressive symptom, perceived stress, suicidal ideation, sociodemographic factors, and VI. Estimates of odds ratios (ORs) and 95% confidence intervals (CIs) were used as the measure of association. The referent group was participants in the control group. Two models were constructed for logistic regression. One was analyzed after adjusting age and sex. The other was adjusted for age, sex, and other sociodemographic factors found to be associated with VI. Additional logistic regression analysis was performed to evaluate how three mental health measures were related to each other after adjustment for sex, age groups, and presence of VI. Subjects with missing values for any covariates were excluded from the multivariate logistic regression analysis. 
Results
Prevalence of VI
Of the 283,949 participants, 187 had BCVA worse than logMAR 0.5 (Snellen 20/63) in the better-seeing eye. Estimated prevalence of VI were 0.43% (95% CI, 0.35–0.52%) in adults aged 19 years and over, 0.65% (95% CI, 0.54–0.79%) in adults aged 40 years and over during 2008–2012 (Fig. 2). Prevalence of VI increased with age, with highest prevalence in age group over 70 years (2.52%; 95% CI, 2.01–3.16%). Prevalence of women and men were similar to each other in the younger adult group. However, in the age group 40 to 49 years, prevalence in men (0.32%; 95% CI, 0.12–0.81%) was significantly (P < 0.001) higher than that in women (0.03%; 95% CI, 0.01–0.14%). In the age group of 60 to 69 years, prevalence of women (0.97%; 95% CI, 0.62–1.50%) was significantly (P = .010) higher than that of men (0.38%; 95% CI, 0.20–0.70%). 
Figure 2
 
Sex and age-specific weighted prevalence of VI in Korea during a 5-year period (2008–2012).
Figure 2
 
Sex and age-specific weighted prevalence of VI in Korea during a 5-year period (2008–2012).
General Characteristics of the VI Group
The general characteristics of participants are listed in Table 1. We analyzed the association between VI and each sociodemographic factor. After controlling for sex, participants in the VI group showed increased ORs for older age (P < 0.001) than those in the control group. After controlling for age and sex, increased ORs for diabetes mellitus (P < 0.001), lower level of education (P < 0.001), no occupation (P = 0.046), and being separated or never married (P = 0.002) were detected in the VI group compared to the control group. Restricted daily activity was most strongly associated with VI. The risk for restricted daily activity increased 5-fold in the VI group (P < 0.001). Sex, house income, and presence of hypertension were not associated with VI after controlling for age and sex. 
Table 1
 
Association of VI and Sociodemographic Factors Using Logistic Regression Analyses
Table 1
 
Association of VI and Sociodemographic Factors Using Logistic Regression Analyses
Association Between VI and Mental Health
We calculated ORs of VI group for depressive symptom, suicidal ideation, and perceived stress. Visual impairment increased ORs for depressive symptom and thought of suicide. However, VI failed to increase the OR for perceived stress in unadjusted analysis (Table 2). After controlling for age and sex, suicidal ideation and perceived stress were significantly associated with VI. In multivariate regression analysis, VI was not significantly associated with any mental health parameter (Tables 35). 
Table 2
 
Association of VI and Mental Health Using Logistic Regression Analyses
Table 2
 
Association of VI and Mental Health Using Logistic Regression Analyses
Table 3
 
Association of Potential Risk Factors and Depressive Symptom Using Logistic Regression Analysis
Table 3
 
Association of Potential Risk Factors and Depressive Symptom Using Logistic Regression Analysis
Table 4
 
Association of Potential Risk Factors and Suicidal Ideation Using Logistic Regression Analysis
Table 4
 
Association of Potential Risk Factors and Suicidal Ideation Using Logistic Regression Analysis
Table 5
 
Association of Potential Risk Factors and Perceived Stress Using Logistic Regression Analysis
Table 5
 
Association of Potential Risk Factors and Perceived Stress Using Logistic Regression Analysis
Associations Between Sociodemographic Data and Mental Health
Among confounding variables, female sex and restricted daily activity were consistently detected to be the significant risk factors for depressive symptoms, suicidal ideation, and perceived stress (Tables 35). Restricted daily activity showed the highest ORs for all three parameters (OR, 2.49; 95% CI, 2.22–2.79; P < 0.001 for depressive symptom; OR, 2.77; 95% CI, 2.51–3.06; P < 0.001 for suicidal ideation; OR, 2.30; 95% CI, 2.09–2.54; P < 0.001 for perceived stress). Older age groups had protective effect for depressive symptoms and perceived stress. Lower level of education significantly increased ORs for depressive symptom and suicidal ideation. Being separated and never married were associated with depressive symptom and suicidal ideation. 
Association of Depressive Symptom, Perceived Stress, and Suicidal Ideation
After adjustment for sex, age groups, and presence of VI, depressive symptom (OR, 7.20; 95% CI, 6.48–7.99; P < 0.001) and perceived stress (OR, 3.52; 95% CI, 3.20–3.87; P < 0.001) were strongly associated with suicidal ideation, respectively. 
Discussion
Although prevalence of VI has been investigated widely in many population-based studies, the sociodemographic characteristics of visually impaired people and their impacts on mental health had gained relatively little attention. Current study on demographic characteristics of people with VI in Korea as well as prevalence revealed that they tended to be older, unemployed, and separated or never married with lower level of education and more restriction in daily activities compared to those of the control group. We found that VI itself was not associated with poor mental health in Koreans. However, the poor sociodemographic characteristics found in people with VI contributed to increased risk for depressive symptom, suicidal ideation, and perceived stress. 
This study demonstrated a five-year nationwide prevalence of VI among Korean adults. Although direct comparison is limited because of the differences in age stratification and/or the definition of VI, prevalence of VI in Korea seemed to be lower when compared to age-specific or age-standardized prevalence of VI from population-based studies conducted in the Western countries.1719 The prevalence of VI in Korea also is lower than those of other Asian countries including China,20 Hong Kong,21 and Taiwan.22 However, the prevalence of VI in Korea is similar to or higher than that of Japan.23,24 Although the reason for this relatively low prevalence is unclear, racial difference in prevalence of eye disease, recent advances in ophthalmologic diagnosis, and treatment can be possible reasons.25 Previous studies on prevalence of VI using KNHANES study revealed rates of 1.1% (<20/63, ≥20/400) and 0.9% (< 20/63) among adults aged over 40 years.15,26 They used data only from 2008 to 2009 or 2010, while this study combined data from 5 years. 
In this study, prevalence of VI was increased in older age groups. In addition, VI was significantly associated with older age after controlling for sex. Increasing prevalence of VI in older age has been consistently found in many previous population-based studies.15,1724,26 Sex predilection in VI has been controversial. As in our results, sex has not been associated with VI with or without adjustment for age and other covariates in previous studies.19,2224 On the other hand, male sex21 or female sex has been proposed to be risk factor in a study of Latinos19 and Koreans26 without adjustment for age. 
Low education level, unemployment, and being separated/divorced or never married were the characteristics of visually impaired people in Korea. Our results reaffirm the common demographic features of visually impaired people found in other countries and races.19,21,24 Unlike reports from Hong Kong21 and Western countries,19 house income did not have significant association with VI in Koreans, which was in consistent with a study regarding Japanese population.24 Exclusion of institutionalized individuals from KNHANES, and adjustment with age and sex, and cultural difference, such as presence of extended family, might have led to different results. 
Whether these unfavorable demographic features are risk factors for VI or whether VI is the cause of these features is not apparent from this cross-sectional study. However, it is obvious that, as one of the fastest aging countries, increasing number of elderly with VI is expected in Korea. Our study can provide evidence for future plans that target high risk groups of people with the above demographic features to support easy access to health care services to prevent VI and to decrease socioeconomic burdens. 
In the current study, VI was associated with suicidal ideation and perceived stress in age and sex-adjusted analyses. However, VI was not associated with depressive symptom, suicidal ideation, or perceived stress after adjusting for various confounding factors. Our result is contradictory to many hospital- and population-based studies that have reported significant associations of VI and depression,14,6,27 suicide,9,10 and perceived stress.27 In addition to methodological differences, such as self-reported vision13,9,10 (instead of objectively measured vision) and diagnostic scale14,6,27 (instead of a single question for mental health assessment) existed between these reports and ours, previous studies did not adjust for many potential confounding factors as we did in the current study. We found that among adjusted covariates, restricted daily activity was the most strongly associated with VI and all mental health parameters. Thus, VI might be associated with increased risk for depressive symptom, suicidal ideation, and perceived stress indirectly mediated by restricted daily activity. 
Our study showed that functional disability resulting from VI was the strong risk factor for lower mental health, contrary to VI itself. Similar result was reported in a study of the elderly in Britain, in which VI had little impact on the level of depression and anxiety after adjusting activity of daily living as a confounding factor.5 Zhang et al.28 also reported that visual function, not VA, had significant impact on depression using data from the National Health and Nutrition Examination Survey. Bookwala et al.6 demonstrated how poor vision affected mental health through functional disability, such as physical limitation, driving limitation, and social isolation. Therefore VI-induced disability to independently carry out routine daily activities might have more impact on mental health than objectively measured VA. 
While most previous studies focused on depression among elderly population, we included young adults aged 19 to 40 years. Underlying clinical diagnosis responsible for VI can be different in young or middle-aged adults from those in the elderly. Therefore, the impact of VI on mental health status might be different between the young and old groups. For example, since shorter duration of vision loss can induce higher level of emotional distress,27 people with VI from congenital diseases may have adopted to VI from their childhood and learned skills to manage activities for daily living. Therefore, they may not feel acute depression or stress. In fact, Loprinzi et al.29 reported that in adults at 20 to 39 years of age, VI was not associated with depression or panic disorder. It is interesting that physical activity (defined as moderate or vigorous activities for at least 10 minutes) was not associated with mental health in their cohort, emphasizing the fact that functional disability has more effect on mental health than motion disability. 
This study has several limitations. Duration and onset of decreased vision and primary ocular diagnosis were not analyzed. These factors can affect the degree of VI's impact on mental health parameter. Unlike previous studies, depressive symptom and perceived stress were assessed by a single question. Assessment of depressive symptom3,3032 and perceived stress33 by a single question was validated previously with high specificity and sensitivity, and several studies investigated mental health in patients with specific diseases using the psychometric measures of the KNHANES.34,35 However, reliability and validity of the mental health questionnaire in the KNHANES has not been studied before to our knowledge and this might have contributed to the controversial results. Furthermore, because the question was answered dichotomously by a “yes” or “no” response (depressive symptom) or answers were categorized by a “yes” or “no” response (perceived stress), the degree to which each variable existed for the individual participant was not reflected in statistical analyses. Nevertheless, although the single-question measure probably had limited reliability, they offer a practical tool for assessing mental health in large epidemiologic studies. 
Despite these limitations, the strength of KNHANES is that it is a population-based study with very large sample sizes and relatively high response rates. In addition, our study has important meaning in that it is the first study to our knowledge to demonstrate that VI (defined as objective visual acuities) does not have impact on mental health after controlling for restricted activity and other sociodemographic factors in Koreans. 
In conclusion, visually impaired people experience significantly more unfavorable sociodemographic status than a control group, although it was impossible to establish the cause and effect in this study. This study also revealed that VI itself did not have significant impact on mental health. However, restricted daily activity and poor sociodemographic factors commonly found in visually impaired people did contribute to increased risk for poor mental health. Notably, restricted daily activity was the strongest risk factor for having depressive symptom, suicidal ideation, and perceived stress in Korean population. This result indicates that VI has an indirect impact on mental health by decreasing the functional ability to perform daily activities, emphasizing the necessity of appropriate rehabilitation program to target people with risk factors. 
Acknowledgments
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. The authors alone are responsible for the content and writing of the paper. 
Disclosure: G.E. Cho, None; D.H. Lim, None; M. Baek, None; H. Lee, None; S.J. Kim, None; S.W. Kang, None 
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Appendix
Epidemiologic Survey Committee of the Korean Ophthalmological Society 
Se Woong Kang, MD, PhD (Chair); Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea 
Seung-Hee Baek, MD, PhD; Department of Ophthalmology, Kim's Eye Hospital, Konyang University College of Medicine, Seoul, Korea 
Chan Yun Kim, MD, PhD; Institute of Vision Research, Department of Ophthalmology, Yonsei University College of Medicine, Seoul, Korea 
Sang-Duck Kim, MD, PhD; Department of Ophthalmology, Wonkwang University College of Medicine, Iksan, Korea 
Seung-Hyun Kim, MD, PhD; Department of Ophthalmology, Korea University College of Medicine, Seoul, Korea 
Jong Soo Lee, MD, PhD; Department of Ophthalmology, Pusan National University College of Medicine, Busan, Korea 
Key Hwan Lim, MD, PhD; Department of Ophthalmology, Ewha Womans University School of Medicine, Seoul, Korea 
Ki Ho Park, MD, PhD; Department of Ophthalmology, Seoul National University College of Medicine, Seoul, Korea 
Young Jeung Park, MD, PhD; Department of Ophthalmology, Cheil Eye Hospital, Daegu, Korea 
Jae Pil Shin, MD, PhD; Department of Ophthalmology, Kyungpook National University School of Medicine, Daegu, Korea 
Su Jeong Song, MD, PhD; Department of Ophthalmology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea 
Suk-Woo Yang, MD, PhD; Department of Ophthalmology, The Catholic University of Korea College of Medicine, Seoul, Korea 
Kyung-Chul Yoon, MD, PhD; Department of Ophthalmology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea 
Seung-Young Yu, MD, PhD; Department of Ophthalmology, Kyung Hee University School of Medicine, Seoul, Korea 
Figure 1
 
Flow chart of the study population.
Figure 1
 
Flow chart of the study population.
Figure 2
 
Sex and age-specific weighted prevalence of VI in Korea during a 5-year period (2008–2012).
Figure 2
 
Sex and age-specific weighted prevalence of VI in Korea during a 5-year period (2008–2012).
Table 1
 
Association of VI and Sociodemographic Factors Using Logistic Regression Analyses
Table 1
 
Association of VI and Sociodemographic Factors Using Logistic Regression Analyses
Table 2
 
Association of VI and Mental Health Using Logistic Regression Analyses
Table 2
 
Association of VI and Mental Health Using Logistic Regression Analyses
Table 3
 
Association of Potential Risk Factors and Depressive Symptom Using Logistic Regression Analysis
Table 3
 
Association of Potential Risk Factors and Depressive Symptom Using Logistic Regression Analysis
Table 4
 
Association of Potential Risk Factors and Suicidal Ideation Using Logistic Regression Analysis
Table 4
 
Association of Potential Risk Factors and Suicidal Ideation Using Logistic Regression Analysis
Table 5
 
Association of Potential Risk Factors and Perceived Stress Using Logistic Regression Analysis
Table 5
 
Association of Potential Risk Factors and Perceived Stress Using Logistic Regression Analysis
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