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Article

A Population-Based Cohort Study of the Association between Visual Loss and Risk of Suicide and Mental Illness in Taiwan

1
Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei 11490, Taiwan
2
Department of Nursing, Keelung Chang Gung Memorial Hospital, Keelung 20401, Taiwan
3
School of Public Health, National Defense Medical Center, Taipei 11490, Taiwan
4
Taiwanese Injury Prevention and Safety Promotion Association, Taipei 11490, Taiwan
5
Graduate Institute of Life Sciences, National Defense Medical Center, Taipei 11490, Taiwan
6
Department of Medical Research, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan
7
Department of Public Health, College of Medicine, Fu-Jen Catholic University, New Taipei City 24205, Taiwan
8
Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City 24205, Taiwan
9
Department of Microbiology and Immunology, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan
10
Department of Family Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan
*
Authors to whom correspondence should be addressed.
Healthcare 2023, 11(10), 1462; https://doi.org/10.3390/healthcare11101462
Submission received: 16 April 2023 / Revised: 27 April 2023 / Accepted: 13 May 2023 / Published: 18 May 2023

Abstract

:
The psychosocial and health consequences of ocular conditions that cause visual impairment (VI) are extensive and include impaired daily activities, social isolation, cognitive impairment, impaired functional status and functional decline, increased reliance on others, increased risk of motor vehicle accidents, falls and fractures, poor self-rated health, and depression. We aimed to determine whether VI increases the likelihood of a poor prognosis, including mental illness, suicide, and mortality over time. In this large, location, population-based, nested, cohort study, we used data from 2000 to 2015 in the Taiwan National Health Insurance Research Database (NHIRD), which includes diagnoses of all the patients with VI. Baseline features, comorbidities, and prognostic variables were evaluated using a 1:4-matched cohort analysis. Furthermore, comparisons were performed using Cox regression and Bonferroni-correction (for multiple comparisons) to study the association between VI and poor prognosis (mental illness, suicide). The study outcome was the cumulative incidence of poor prognosis among the visually impaired and controls. A two-tailed Bonferroni-corrected p < 0.001 was considered statistically significant. Among the 1,949,101 patients enlisted in the NHIRD, 271 had been diagnosed with VI. Risk factors for poor prognosis and the crude hazard ratio was 3.004 (95% confidence interval 2.135–4.121, p < 0.001). Participants with VI had an increased risk of poor prognosis according to the sensitivity analysis, with a poor prognosis within the first year and first five years. VI was associated with suicide and mental health risks. This study revealed that patients with VI have a nearly 3-fold higher risk of psychiatric disorders, including anxiety, depression, bipolar, and sleep disorders, than the general population. Early detection through comprehensive examinations based on increased awareness in the clinical context may help maintain visual function and avoid additional complications.

1. Introduction

Visual impairment (VI) is extremely common and affects more than 2.2 billion people worldwide [1]. Approximately 36 million people are blind, and an additional 217 million have significant (moderate-to-severe) VI [2]. According to Taiwan’s Ministry of the Interior, the number of visually impaired people in Taiwan has climbed from 19,423 in 1992 to 55,000 in 2022, with a 2000-person increase every year. The visually impaired population in Taiwan amounts to 0.24% of the overall population, compared to 0.5% in Europe and the United States; this is a low percentage in our location but is growing every year.
The wide-ranging psychosocial and health consequences of ocular conditions that cause VI include impaired activities of daily living, social isolation, cognitive impairment, impaired functional status and functional decline, increased reliance on others, risk of motor vehicle accidents, falls and fractures, poor self-rated health, and depression [3,4].
Adults with VI and disabling eye diseases have an increased risk of mortality [5] Moreover, case reports have suggested an association between VI and suicide. In a case-control study conducted in Sweden, researchers interviewed the families of 46 men and 39 women aged 65 years who completed suicide and compared the results with those of 84 men and 69 women aged 65 years who were still alive [6]. VI (odds ratio [OR] = 7.0; 95% confidence interval [CI]: 2.3–21.4), neurological disorders (OR = 3.8; 95% CI: 1.5–9.4), and malignant diseases (OR = 3.4; 95% CI: 1.2–9.8) were found to be independently associated with an increased risk of suicide. However, the statistical relevance of VI as a risk factor for suicide is debatable. VI has been identified as a risk factor in certain studies when combined with depression or poor overall health [7,8,9]. Age, male sex, disrupted marital status, mental and addictive disorders, depression, prior suicide attempts, family history of psychiatric disorders or suicide, a firearm in the house, and a recent severely stressful life event are all established risk factors for suicide [10]. However, in other investigations, VI did not demonstrate substantial hazard ratios or strong relationships with a higher risk of suicide [11,12,13,14].
Suicide and suicide attempts have been linked to chronic conditions such as cancer, and the number of health conditions increases the risk of suicide attempts [15]. Therefore, the risk of suicide may be influenced both directly and indirectly by VI. For example, a link between VI and self-rated health, which has been shown to be a predictor of mortality, has been discovered [16,17,18]. Thus, this study aimed to determine whether VI increases the risk of mental illness and/or suicide in a representative Taiwanese population.

2. Materials and Methods

2.1. Data Source

The Taiwan National Health Insurance (NHI) program was established in 1995 and covers >99% of the Taiwanese population (>23 million beneficiaries). The Taiwan NHI Research Database (NHIRD) contains the following encrypted data: patient identification number; date of birth; sex; date of admission and discharge; International Classification of Diseases, Ninth Revision, Clinical Modification (ICD−9-CM) diagnostic and procedure codes (up to five each); and outcomes. The Longitudinal Health Insurance Database (LHID) 2005, a subset of the NHIRD, has been used in this study. It contains data on the medical service utilization of approximately 1 million randomly selected beneficiaries, who represented approximately 5% of the Taiwanese population in 2005. The NHIRD was used to extract data from 2000 to 2015. The NHI administration regularly conducts random reviews of medical records to ensure diagnostic accuracy.
This study was a population-based cohort tracking study that recruited outpatients and inpatients from the Taiwan Longitudinal Health Insurance Database (LHID) between 1 January 2000 and 31 December 2015. Tandem Inpatient expenditures by admissions (DD), Registry for contracted medical facilities (HOSB), Registry for beneficiaries (ID), Registry for catastrophic illness patients (HV), variables include diagnosis, surgery, disposition, hospitalization and discharge dates, length of stay and medical costs; Registry for contracted medical facilities (HOSB)the variables include hospital location and hospital level.
This study was conducted in accordance with the Declaration of Helsinki. The institutional review board of Tri-Service General Hospital at the National Defense Medical Center in Taipei, Taiwan, approved this study, and the requirement for individual consent was waived because all identifying data were encrypted (TSGHIRB No. E202216004). The NHIRD is a freely accessible database that contains de-identified patient information to protect patient anonymity.

2.2. Study Design and Participants

This study is a retrospective cohort study that uses secondary database analysis. According to the International Classification of Diseases (ICD) and Related Health Problems, the World Health Organization divides VI into five categories. The first and second categories are moderate or severe VI with excellent visual acuity equal to or better than 3/60 (0.05). The third category is blindness with visual acuity between 3/60 (0.05) to 1/60 (0.02); the fourth category is blindness with visual acuity between 1/60 (0.02) to light perception; and the fifth category is blindness with no light perception. This study included a cohort of patients from the LHID database who were newly diagnosed with VI (ICD-9-CM 369.3 and 369.4). We excluded patients diagnosed with VI before 2000, poor prognosis before VI, unknown sex, and incomplete tracking data. The inclusion and exclusion criteria are shown in Figure 1. Moreover, the date of the diagnosis of VI was used as the index date. Participants in the control group were selected from the LHID 2005 cohort. The study and control cohorts were matched 1:4 according to sex, age, and the index date.

2.3. Outcome Measurement and Comorbidities

We individually assessed medical comorbidities associated with VI at enrollment and during the entire follow-up period, including diabetes mellitus (ICD-9-CM 250), hypertension (HTN; ICD-9-CM 401-405), renal disease (ICD-9-CM 580-589), hyperlipidemia (ICD-9-CM 272), thyrotoxicosis (ICD-9-CM 242), septicemia (ICD-9-CM 003.1, 036.1, 038), pneumonia (ICD-9-CM 480-486), chronic liver disease (ICD-9-CM 571), injury (ICD-9-CM 800-999), and tumor (ICD-9-CM 140-208); these are listed in Table S1 (see Supplementary Material).
All participants were followed up from the index date until the first diagnosis of VI, poor prognosis, death, withdrawal from the NHI program, or 31 December 2015. The covariates included sex, age group, geographical area of residence (north, center, south, and east of Taiwan), urbanization level of residence (levels 1–4), and monthly income (in New Taiwan Dollars: <18,000, 18,000–34,999, and ≥35,000). The urbanization level of residence was defined according to the population and various indicators of development. Level 1 was defined as a population of >1,250,000 with a specific designation of political, economic, cultural, and metropolitan development. Level 2 was defined as a population between 500,000 and 1,249,999, with an important role in politics, the economy, and culture. Finally, urbanization levels 3 and 4 were defined as populations between 149,999 and 499,999 and <149,999, respectively.
Risk factors evaluated for poor prognosis included mental disorders, at least three outpatient or inpatient visits, anxiety disorders (ICD−9-CM 300), depression (ICD−9-CM 296.2, 296.3, 300.4, and 311), bipolar disorder (ICD−9-CM 296.0, 296.4–296.8), sleep disorders (ICD−9-CM 307.4 and 780.5), post-traumatic stress disorder/acute stress disorder (ICD−9-CM 308 and 309.81), dementia (ICD−9-CM 290.0–290.4, 290.8, 290.9, and 331.0), eating disorders (ICD-CM 307.1 and 307.5), substance-related disorders (SRD; ICD-CM 291–292, 303.3, 303.9, and 304–305), psychotic disorders (ICD-CM 295 and 297–298), autism (ICD-CM 299.00), other mental disorders (not listed above, ICD−9-CM 290–319), suicide (ICD−9-CM E950–E959), death from all causes (ICD−9-CM 800–999), suicide mortality (ICD−9-CM E950–E959, immediate and subsequent mortality), and non-suicide mortality (ICD−9-CM000–999, E800–E949, E960–E969); these are listed in Table S1 (see Supplementary Material).

2.4. Statistical Analyses

To investigate the association between VI and risk of suicide and mental illness, we conducted the following statistical analyses to compare the clinical characteristics of the participants in the case and control groups. The clinical characteristics of the participants are expressed numerically. We compared the distribution of categorical characteristics and baseline comorbidities between the case and control groups using Fisher’s exact test and the chi-squared test. Continuous variables are presented as means and standard deviations and compared using the t-test.
As the primary goal of this study was to determine whether the clinical characteristics of patients are associated with poor prognosis, the Cox regression analyses were used to determine the risk of poor prognosis; the results are presented as hazard ratios (HRs) with the associated 95% CIs.
Associations between time-to-event outcomes and clinical characteristics were examined using the Kaplan–Meier method and multivariate Cox regression analysis with stepwise selection; the results are presented as adjusted HRs with the corresponding 95% CIs. The poor prognosis incidence (per 105 person-years) was calculated based on sex, age, and comorbidities for each cohort. Adjustments were made for age, sex, and concomitant comorbidities for inclusion in the multivariate model.
Bonferroni-correction for multiple comparisons was applied. A two-tailed Bonferroni-corrected p < 0.001 was considered statistically significant. All statistical analyses were performed using IBM SPSS Statistics for Windows version 22.0 (released 2013, IBM Corp., Armonk, NY, USA).

3. Results

Among the 1,949,101 patients in the LHID 2005 from the NHIRD, 539 had been diagnosed with VI. In total, 271 patients were assigned to the study cohort, and 1084 age-, sex-, and comorbidity-matched patients were assigned to the comparison cohort (Figure 1). The baseline data of the patients and control groups are shown in Table 1. The average age of the VI cohort was 39.01 ± 16.83 years, and the proportion of male patients was 52.03%. Among the study population, the majority of patients were aged ≦19 years (36.53%); 27.31% of patients were 65 years and older, 20.66% were 20–44 years, and 15.50% were 45−64 years old. Our findings show no significant differences in sex, age, thyrotoxicosis, septicemia, tumor, or season between the groups with and without VI after matching.
Furthermore, we analyzed individual outcomes, such as dementia, eating disorders, SRD, psychotic disorders, autism, and other mental disorders (Table 2). In general, VI was associated with an increased risk of individual outcomes, including dementia, eating disorders, SRD, and other mental disorders, even after excluding individuals with poor prognoses within the first year and first five years. Moreover, VI was associated with an increased risk of anxiety, depression, bipolar disorder, and sleep disorders, as well as individual types of all-cause mortality.
Figure 2 shows the Kaplan–Meier survival curve of patients with poor prognosis stratified by visual loss using the log-rank test; patients with visual loss had a significantly higher cumulative risk of developing a poor prognosis 16 years after the index date (log-rank test, p < 0.001).
Table 3 shows the Cox regression analysis of the factors associated with the risk of poor prognosis. The crude HR was 3.004 (95% CI: 2.135–4.121, p < 0.001). After adjusting for sex, age group, geographical area of residence, urbanization level of residence area, and monthly income, the adjusted HR was 2.956 (95% CI: 1.984–3.960, p < 0.001). Age, urbanization level, and level of care correlated with poor prognosis. Moreover, poor prognosis tended to occur in patients older than 45 years, regardless of urbanization level and level of care (p < 0.05). Notably, this study included more males than females. Moreover, the level of urbanization increased with the frequency of chronic diseases (e.g., HTN, renal disease), which more likely resulted in the crude and adjusted HR of poor prognosis (p < 0.05).
The patients were stratified by the variables presented in Table 3, and adjusted hazard ratios of different subgroups were calculated (Table 4). The visual loss group encountered 49 medical events due to first diagnosed poor prognosis in the 2552.73 person-years (PY) observed, representing a rate of 936.93 per 105 PYs; the group without visual loss encountered 97 medical events in the 10,352.96 person-years (PY) observed, representing a rate of 1614 per 105 PYs. After Bonferroni-correction for multiple comparisons, when compared to those without visual loss, patients with visual loss poor prognosis showed patients with visual loss poor prognosis ratio of 2.956 (95% CI 1.984–3.960, p < 0.001).
This study was designed to analyze the short-, medium-, and long-term effects of VI on patients. Factors in the poor prognosis subgroups (overall, 1-year, and 5-year subgroups) posed a significant risk compared to the group without VI (Table 5). Visual loss was associated with an increased risk of poor prognosis (aHR, 2.956; 95% CI, 1.984–3.960; p < 0.001); post-traumatic stress disorder (PTSD)/acute stress disorder (ASD) in VI was 5.835 fold higher (95% CI, 3.866−7.892; p < 0.001) than those without VI. In the present study, visual loss was associated with an increased risk of any poor prognosis from the subgroups, as well as with an increased risk of specific types of personality disorders, including mental disorders, anxiety, depression, bipolar, sleep disorders, PTSD/ASD, dementia, eating disorders, SRD, psychotic disorders, autism, other mental disorders, and suicide (Table 5). After Bonferroni-correction for multiple comparisons, notable increases in the first year in SRD with VI was 5.745-fold (95% CI, 3.882–7.759; p < 0.001), PTSD/ASD was 5.526-fold (95% CI, 3.884–7.801; p < 0.001), suicide mortality was 2.402-fold (95% CI, 1.362–3.780; p < 0.001), and non-suicide mortality was 3.765-fold (95% CI, 2.087–7.184; p < 0.001). After the fifth year, the increase in depression was 5.219-fold (95% CI, 3.467–6.920; p < 0.001). These associations remained significant after the visual loss diagnoses in the first year, persisting even after the first five years after experiences with visual loss, according to the sensitivity analysis (Table 5).

4. Discussion

People with VI are at a higher risk of poor mental health outcomes, as well as physical comorbidities [19,20,21]. According to a study published in 2000, two-thirds (66.6%) of patients admitted for inpatient treatment for depression showed a diminished perception of ambient light [22]. According to a cross-sectional study comprising 213 participants (with depression and without depression), patients with depression were 4.5 times more likely to report lower perception of ambient light from age-related eye illness than those without depression. However, the mechanism underlying the association between depression and impaired perception remains unknown [23].
Previous studies have shown an association between VI and self-rated health [16,24,25]. Reduced vision had an independent influence on global health ranking by those under the age of 80 years [24]. Participants in the study who reported VI were twice as likely as those who did not report VI to indicate poor self-rated health (OR = 2.13, 95% CI: 1.94–2.33). Self-reported health is thought to reflect physical health conditions. When reporting self-rated health, a respondent may also consider healthy or unhealthy habits and activities [23].
Previous studies have reported that increased exposure to potentially stressful situations is associated with an increased risk of mental health problems in persons with VI. Studies have linked visual impairments to a high prevalence of post-traumatic stress disorder [25], higher risk of depression and anxiety [26,27], and burdensome life experiences such as loneliness [28]. While it has been discovered that mental health issues are more common in young persons with VI than in older persons with VI [29], studies have also indicated that older adults with VI have a higher prevalence of a range of mental health disorders when compared with similarly aged people in the general population [30]. Therefore, people with VI are more likely to have mental health problems, regardless of age; this is in line with the results of our study.
The present study found that, in addition to depression, VI may directly increase the risk of suicide (HR: 1.50, 95% CI: 0.90–2.49). When non-ocular characteristics, including medical comorbidities and self-rated health, were considered, individuals with VI had a 64% (HR: 1.64, 95% CI: 0.99–2.72) greater risk of death by suicide [31]. While blindness due to age-related illnesses (e.g., age-related macular degeneration), diabetic retinopathy, and glaucoma is not reversible, many impairments may be cured or prevented entirely, which may prevent development of several mental health disorders [32]. Nevertheless, despite their frequent contact with patients and understanding of the devastating effects of VI, ophthalmologists seldom diagnose or treat depression [33]. This decision making involves ophthalmologists’ ability to diagnose depression and suicidal behavior, as well as knowing when to send patients for psychiatric examination and care. Further research is needed to determine the frequency of cases with psychological difficulties that ophthalmologists encounter and appropriately manage. In addition, efforts to teach ophthalmologists in residency to effectively manage suicidal behaviors caused by VI are warranted.
PTSD may follow an exceptionally threatening or horrifying event, where the person experiencing it feels a severe threat of injury or death. Common symptoms of PTSD are re-experiencing the event in the form of flashbacks or nightmares, avoidance of stimuli associated with the event, alterations in cognition and mood, and increased arousal and reactivity [34]. As identified in a recent review, the one study that assessed PTSD prevalence specifically in people with VI was concerned with adolescents in a war conflict area [35]. This study found a lower prevalence of PTSD among those with impaired vision or hearing compared with those without impairments (4.2% versus 11.4%), which was explained by a lower exposure to traumatic events among those with VI [36]. However, in previous reviews, the prevalence estimates of PTSD in populations prone to VIs (older people, primary care patients) have ranged from 1.7% to 32.5% [37,38], which is both lower and higher, respectively, than those found in general population samples [39,40]. Thus, more studies are warranted to conclude whether individuals with VI are at a higher risk of PTSD.
While the current state of knowledge suggests that people with a visual impairment are more vulnerable to potentially traumatic events, few studies have examined the prevalence of PTSD. PTSD can occur after an exceptionally threatening or horrifying event in which the person experiencing it felt a severe threat of injury or death. Common symptoms of PTSD include re-experiencing the event in the form of flashbacks or nightmares, avoidance of stimuli associated with the event, and altered perceptions of the event [34].
According to a recent analysis, the one study that explicitly investigated PTSD prevalence in persons with a visual impairment was concerned with teenagers in a military conflict region [35]. This study revealed a lower prevalence of PTSD among people with impaired vision or hearing compared to those without impairments (4.2% versus 11.4%) [36], which was explained by the impaired group’s lesser exposure to stressful situations. PTSD prevalence estimates in populations prone to visual impairments (older persons, primary care patients) have ranged from 1.7% to 32.5% [37,38], which is both greater and lower than that seen in general population samples [39,40]. More study is needed to determine whether those with visual impairments are more likely to develop PTSD. More study is needed to determine which life experiences may be to blame for the probable difference in PTSD prevalence between the VI population and the general population.
Synthesis the above studies, PTSD is prone to forming in people with VI. Nonetheless, the degree and impact of PTSD in this population remains uncertain, and further investigation is necessary to advance knowledge regarding these aspects. This would entail conducting larger comparative studies using dependable methods and valid assessment tools. The current diagnostic instruments for traumatic events and PTSD must be validated and, if necessary, modified for individuals with VI. First, the influence of VI in the manifestation of PTSD symptoms, particularly intrusions, avoidance, and hyperarousal, must be considered. Second, PTSD and traumatic brain injury often co-occur, particularly in ex-service personnel, and traumatic brain injury may result in VI. Consequently, it may become challenging to attribute a symptom to a specific diagnosis. Third, PTSD diagnosis may be associated with an increase in vision problems due to heightened awareness and reporting of vision problems, neurophysiological manifestations, and medication side effects. Mental health professionals, vision rehabilitation specialists, and eye care providers should be acquainted with these factors to improve identification and treatment of PTSD in this population.
The major strength of our study is its population-based design. However, this study has some limitations. First, the NHIRD did not annually assess important risk factors associated with disabling eye conditions such as smoking, a risk factor for cataracts, and age-related maculopathy. Second, the NHIRD does not provide detailed information on variables, including socioeconomic factors, occupation, unhealthy behaviors, amount of alcohol consumption, and the genetic background of the subjects, that may affect the association between VI and poor mental health outcomes. Lastly, the study participants were selected based on their medical records in the NHIRD, so our ICD−9-CM code does not identify congenital VI and does not include an assessment of some risk factors associated with suicide, such as depression. Other than that, the fact that not all suicides are reported as suicides, may underestimate the data between VI and suicides. The bias caused by unknown confounders could not be avoided in this retrospective cohort study despite meticulous adjustments. Nevertheless, multivariate logistic regression models and Bonferroni-correction for multiple comparisons were used to adjust our results. The recommendation for future studies with higher methodological rigor is appropriate to address the limitations of the current study.

5. Conclusions

This study revealed that patients with VI have a nearly three-fold higher risk of mental disorders, including anxiety, depressive, bipolar, and sleep disorders, than the general population. After the sensitivity test, excluding the first year, patients with VI were found to have a nearly five-fold higher risk for PTSD/ASD. When the first five years were excluded, the data showed patients with VI to have a nearly five-fold higher risk for depression. Traumatic experiences appear to have a significant impact on the mental health in people with VI, and these results highlight their need for mental health care. The high prevalence of PTSD lends credence to the suggestion for a better-adapted health-care system for persons with visual impairment. People who are visually impaired may have a greater threshold for asking for assistance. Equally significant, health workers are unaware of the mental challenges connected with visual impairments [41].

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/healthcare11101462/s1, Table S1. Abbreviation, ICD-9-CM, and definition.

Author Contributions

Conceptualization, C.S. and W.-C.C.; methodology, C.-H.C. and C.-A.S.; software, C.-H.C. and C.-E.W.; validation, C.-A.S. and C.-H.T.; formal analysis, C.-H.C., F.-H.L. and C.-H.T.; data curation, F.-H.L. and D.Y.N.; writing—original draft preparation, C.S.; writing—review and editing, C.S. and W.-C.C.; supervision, W.-C.C. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by a grant from the Tri-Service Hospital Research Foundation (TSGH-B-112020). The funders had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of Tri-Service General Hospital (TSGHIRB No. E202216004). The need for individual consent was waived because all identifying data were encrypted.

Informed Consent Statement

Not applicable.

Data Availability Statement

Restrictions apply to the availability of these data. Data were obtained from National Health Insurance database and are available from the authors with the permission of National Health Insurance Administration of Taiwan.

Acknowledgments

The authors thank the Health and Welfare Data Science Center, Ministry of Health and Welfare (HWDC, MOHW), Taiwan, for allowing them access to the NHIRD.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

VI: visual impairment; NHIRD: National Health Insurance Research Database; LHID: Longitudinal Health Insurance Database; NHI: National Health Insurance; ICD−9-CM: International Classification of Diseases, Ninth Revision, Clinical Modification; HR: hazard ratio; CI: confidence interval; OR: odds ratio; SRD: substance-related disorders; HTN: hypertension; PTSD: post-traumatic stress disorder; ASD: acute stress disorder.

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Figure 1. Flowchart of the study sample selection from the National Health Insurance Research Database in Taiwan.
Figure 1. Flowchart of the study sample selection from the National Health Insurance Research Database in Taiwan.
Healthcare 11 01462 g001
Figure 2. Kaplan–Meier for survival of poor prognosis stratified by visual loss with log-rank test.
Figure 2. Kaplan–Meier for survival of poor prognosis stratified by visual loss with log-rank test.
Healthcare 11 01462 g002
Table 1. Baseline characteristics of the participants.
Table 1. Baseline characteristics of the participants.
Visual LossTotalWithWithoutp
Variablesn%n%n%
Total1355 27120.00108480.00
Gender 0.999
  Male70552.0314152.0356452.03
  Female65047.9713047.9752047.97
Age (years)39.12 ± 16.9739.01 ± 16.8339.15 ± 17.010.822
Age groups (yrs) 0.999
  ≦1949536.539936.5339636.53
  20−4428020.665620.6622420.66
  45−6421015.504215.5016815.50
  ≧6537027.317427.3129627.31
Insured premium (NT$) <0.001
  <18,000108580.0721278.2387380.54
  18,000–34,99914911.003713.6511210.33
  ≧35,0001218.93228.12999.13
DM <0.001
  Without118987.7522683.3996388.84
  With16612.254516.6112111.16
HTN <0.001
  Without119087.8223486.3595688.19
  With16512.183713.6512811.81
Renal disease <0.001
  Without118387.3122984.5095488.01
  With17212.694215.5013011.99
Hyperlipidemia <0.001
  Without127093.7324991.88102194.19
  With856.27228.12635.81
Thyrotoxicosis 0.862
  Without128895.0625694.46103295.20
  With674.94155.54524.80
Septicemia 0.999
  Without134098.8926898.89107298.89
  With151.1131.11121.11
Pneumonia 0.001
  Without123090.7724389.6798791.05
  With1259.232810.33978.95
CLD 0.014
  Without122790.5524389.6798490.77
  With1289.452810.331009.23
Injury <0.001
  Without117386.5721579.3495888.38
  With18213.435620.6612611.62
Tumor 0.972
  Without131997.3426497.42105597.32
  With362.6672.58292.68
Season 0.999
  Spring (Mar–May)32523.996523.9926023.99
  Summer (Jun–Aug)33024.356624.3526424.35
  Autumn (Sep–Nov)35526.207126.2028426.20
  Winter (Dec–Feb)34525.466925.4627625.46
Location <0.001
  Northern Taiwan38328.277828.7830528.14
  Central Taiwan37527.687226.5730327.95
  Southern Taiwan37527.687628.0429927.58
  Eastern Taiwan15211.223211.8112011.07
  Outlying islands705.17134.80575.26
Urbanization level <0.001
  1 (The highest)38728.567828.7830928.51
  240529.898129.8932429.89
  327019.934918.0822120.39
  4 (The lowest)29321.626323.2523021.22
Level of care <0.001
  Hospital center41530.6310036.9031529.06
  Regional hospital51137.719434.6941738.47
  Local hospital42931.667728.4135232.47
p: Chi-square/Fisher exact test on category variables and t-test on continue variables, DM: diabetes mellitus; HTN: hypertension; CLD: chronic liver disease.
Table 2. Study endpoint characteristics of the participants.
Table 2. Study endpoint characteristics of the participants.
Visual lossTotalWithWithoutp
Variablesn%n%n%
Total1355 27120.00108480.00
Poor prognosis <0.001
  Without120989.2322281.9298791.05
  With14610.774918.08978.95
Gender 0.999
  Male70552.0314152.0356452.03
  Female65047.9713047.9752047.97
Age (yrs)48.70 ± 18.8047.85 ± 18.2248.91 ± 18.940.003
Age groups (yrs) 0.012
  ≦1948035.429735.7938335.33
  20−4427220.075319.5621920.20
  45−6419114.104115.1315013.84
  ≧6541230.418029.5233230.63
Insured premium (NT$) <0.001
  <18,000108580.0721278.2387380.54
  18,000−34,99914911.003713.6511210.33
  ≧35,0001218.93228.12999.13
DM <0.001
  Without118387.3122281.9296188.65
  With17212.694918.0812311.35
HTN <0.001
  Without118687.5323285.6195488.01
  With16912.473914.3913011.99
Renal disease <0.001
  Without117886.9422683.3995287.82
  With17713.064516.6113212.18
Hyperlipidemia <0.001
  Without126092.9924389.67101793.82
  With957.012810.33676.18
Thyrotoxicosis <0.001
  Without127894.3225292.99102694.65
  With775.68197.01585.35
Septicemia 0.972
  Without133498.4526798.52106798.43
  With211.5541.48171.57
Pneumonia 0.447
  Without122590.4124088.5698590.87
  With1309.593111.44999.13
CLD 0.285
  Without121889.8923586.7298390.68
  With13710.113613.281019.32
Injury <0.001
  Without116585.9821177.8695488.01
  With19014.026022.1413011.99
Tumor 0.943
  Without131697.1226397.05105397.14
  With392.8882.95312.86
Season 0.002
  Spring31723.396222.8825523.52
  Summer35125.907326.9427825.65
  Autumn34025.096925.4627125.00
  Winter 34725.616724.7228025.83
Location <0.001
  Northern Taiwan38628.497728.4130928.51
  Central Taiwan37327.537226.5730127.77
  Southern Taiwan37727.827728.4130027.68
  Eastern Taiwan15711.593312.1812411.44
  Outlying islands624.58124.43504.61
Urbanization level <0.001
  1 (The highest)38328.277828.7830528.14
  241030.268330.6332730.17
  326919.854516.6122420.66
  4 (The lowest)29321.626523.9922821.03
Level of care <0.001
  Hospital center40930.189936.5331028.60
  Regional hospital51437.939334.3242138.84
  Local hospital43231.887929.1535332.56
p: Chi-square/Fisher exact test on category variables and t-test on continue variables, DM: diabetes mellitus; HTN: hypertension; CLD: chronic liver disease.
Table 3. Factors of poor prognosis according to Cox regression.
Table 3. Factors of poor prognosis according to Cox regression.
VariablesCrude HR95% CI95% CIpaHR95% CI95% CIp
Visual Loss
  WithoutReference Reference
  With3.0042.1354.121<0.0012.9561.9843.960<0.001
Gender
  Male1.4541.1121.893<0.0011.3521.0891.7980.001
  FemaleReference Reference
Age groups (yrs)
  ≦19Reference Reference
  20−441.1251.0442.0300.0071.0860.9721.9720.083
  45−641.5971.1252.224<0.0011.4591.0332.1060.016
  ≧651.8861.3012.482<0.0011.7671.2552.323<0.001
Insured premium (NT$)
  <18,000Reference Reference
  18,000−34,9990.7640.4891.1490.5890.8730.6171.3010.677
  ≧35,0000.6880.3750.9520.0020.7700.4861.0950.124
DM
  WithoutReference Reference
  With2.6981.7983.995<0.0012.5551.7263.870<0.001
HTN
  WithoutReference Reference
  With2.4851.5883.372<0.0012.3041.4483.271<0.001
Renal disease
  WithoutReference Reference
  With2.6561.6723.501<0.0012.6121.5623.399<0.001
Hyperlipidemia
  WithoutReference Reference
  With1.6521.1531.983<0.0011.5831.0971.8760.004
Thyrotoxicosis
  WithoutReference Reference
  With1.1080.8651.4040.1861.0850.7221.3150.274
Septicemia
  WithoutReference Reference
  With2.8921.9863.971<0.0012.5061.8723.501<0.001
Pneumonia
  WithoutReference Reference
  With1.6821.1352.543<0.0011.4461.0262.4890.028
CLD
  WithoutReference Reference
  With1.8971.3042.703<0.0011.5871.1042.555<0.001
Injury
  WithoutReference Reference
  With2.3591.6832.979<0.0012.1841.5972.862<0.001
Tumor
  WithoutReference Reference
  With1.9061.4012.345<0.0011.8861.3582.270<0.001
Season
  SpringReference Reference
  Summer1.2450.7841.7710.2661.0980.5671.5050.489
  Autumn1.5790.8961.8960.1931.2250.7041.7220.276
  Winter1.6061.0012.0350.0501.2970.7791.7810.251
Location Multicollinearity with urbanization level
  Northern TaiwanReference Multicollinearity with urbanization level
  Central Taiwan0.9090.5391.2120.471Multicollinearity with urbanization level
  Southern Taiwan0.9760.5711.2770.433Multicollinearity with urbanization level
  Eastern Taiwan0.7330.4521.0830.592Multicollinearity with urbanization level
  Outlying islands0.5620.2330.864<0.001Multicollinearity with urbanization level
Urbanization level
  1 (The highest)1.8961.3902.286<0.0011.5721.1372.030<0.001
  21.8341.3772.207<0.0011.5101.1081.997<0.001
  31.5671.2591.995<0.0011.3721.0241.8660.027
  4 (The lowest)Reference Reference
Level of care
  Hospital center2.8622.0303.782<0.0012.3851.8842.977<0.001
  Regional hospital2.1341.7712.853<0.0011.7861.2752.386<0.001
  Local hospitalReference Reference
HR = hazard ratio, CI = confidence interval, aHR = Adjusted HR: Adjusted variables listed in the table, DM: diabetes mellitus; HTN: hypertension; CLD: chronic liver disease.
Table 4. Factors of poor prognosis stratified by variables listed in the table by using Cox regression and Bonferroni correction for multiple comparisons.
Table 4. Factors of poor prognosis stratified by variables listed in the table by using Cox regression and Bonferroni correction for multiple comparisons.
Visual LossWithWithout (Reference)With vs. Without (Reference)
StrarifiedEventsPYsRate (per 105 PYs)EventsPYsRate (per 105 PYs)aHR95% CI95% CIp
Total492552.731919.519710,352.96936.932.9561.9843.960< 0.001
Gender
  Male261328.841956.59515386.61946.792.9431.9753.942< 0.001
  Female231223.891879.25464966.35926.232.8891.9393.871< 0.001
Age groups (yrs)
  ≦1916913.251751.98333657.91902.152.7661.8573.705< 0.001
  20−449499.611801.41192091.24908.552.8241.8953.782< 0.001
  45−648386.352070.66141432.60977.243.0172.0254.043< 0.001
  ≧6516753.522123.37313171.21977.543.0932.0774.144< 0.001
Insured premium (NT$)
  <18,000401996.952003.05788337.25935.563.0492.0464.084< 0.001
  18,000−34,9997353.111982.39101068.84935.593.0172.0254.043< 0.001
  ≧35,0002202.67986.839946.87950.501.4790.9921.9810.057
DM
  Without392091.181864.98869179.37936.882.8351.9033.798< 0.001
  With10461.552166.61111173.59937.293.2922.2104.410< 0.001
HTN
  Without402185.001830.66849111.44921.922.8281.8983.788< 0.001
  With9367.732447.45131241.521047.103.3282.2354.459< 0.001
Renal disease
  Without392128.851831.98839092.35912.862.8581.9183.829< 0.001
  With10423.882359.16141260.611110.573.0252.0304.053< 0.001
Hyperlipidemia
  Without432288.981878.57919713.08936.882.8551.9173.826< 0.001
  With6263.752274.886639.88937.683.4552.3184.628< 0.001
Thyrotoxicosis
  Without452373.771895.72929799.05938.872.8751.9303.852< 0.001
  With4178.962235.145553.91902.673.5272.3674.724< 0.001
Septicemia
  Without472515.051868.759410,190.66922.412.8851.9363.865< 0.001
  With237.685307.863162.301848.434.0892.7455.478< 0.001
Pneumonia
  Without422260.701857.83889407.45935.432.8291.8983.789< 0.001
  With7292.032397.019945.51951.873.5862.4074.804< 0.001
CLD
  Without412213.561852.22879388.34926.682.8471.9113.813< 0.001
  With8339.172358.7010964.621036.683.2402.1744.341< 0.001
Injury
  Without371987.551861.59859111.41932.902.8421.9073.807< 0.001
  With12565.182123.22121241.55966.533.1292.0994.191< 0.001
Tumor
  Without472477.401897.159410,056.88934.682.8911.9403.872< 0.001
  With275.332654.983296.081013.243.7322.5054.999< 0.001
Season
  Spring10584.121711.98222435.31903.382.6981.8113.615< 0.001
  Summer12687.031746.65242655.14903.912.7521.8473.686< 0.001
  Autumn13649.852000.46242588.67927.123.0732.0634.117< 0.001
  Winter14631.732216.14272673.841009.783.1262.0974.187< 0.001
Urbanization level
  1 (The highest)17734.372314.91312912.681064.313.0972.0794.149< 0.001
  215781.591919.16283123.44896.453.0492.0464.084< 0.001
  38423.651888.35192139.70887.973.0282.0324.057< 0.001
  4 (The lowest)9613.121467.90192177.14872.702.3951.6083.209< 0.001
Level of care
  Hospital center19932.562037.40282960.75945.713.0682.0594.110< 0.001
  Regional hospital17876.211940.17384020.84945.082.9231.9623.916< 0.001
  Local hospital13743.961747.41313371.37919.512.7061.8163.625< 0.001
PYs = Person-years; aHR = Adjusted Hazard ratio: Adjusted for the variables listed in Table 3.; CI = confidence interval, DM: diabetes mellitus; HTN: hypertension; CLD: chronic liver disease.
Table 5. Factors of poor prognosis subgroups by using Cox regression and Bonferroni correction for multiple comparisons.
Table 5. Factors of poor prognosis subgroups by using Cox regression and Bonferroni correction for multiple comparisons.
Visual LossWithWithout (Reference)With vs. Without (Reference)
Sensitivity TestPoor Prognosis SubgroupsEventsPYsRate (per 105 PYs)EventsPYsRate (per 105 PYs)aHR95% CI95% CIp
OverallOverall492552.731919.519710,352.96936.932.9561.9843.960<0.001
Mental disorders402552.731566.957510,352.96724.433.0872.0734.143<0.001
Anxiety102552.73391.741610,352.96154.553.7152.4814.969<0.001
Depression122552.73470.081810,352.96173.863.8592.5875.253<0.001
Bipolar32552.73117.52910,352.9686.931.9301.1232.6480.003
Sleep disorders72552.73274.221110,352.96106.253.5842.4604.709<0.001
PTSD/ASD22552.7378.35210,352.9619.325.8353.8667.892<0.001
Dementia12552.7339.17210,352.9619.322.8791.9503.926<0.001
Eating disorders02552.730.00210,352.9619.320.000--0.992
SRD12552.7339.17310,352.9628.981.6041.0772.5860.019
Psychotic disorders22552.7378.35510,352.9648.302.2761.5573.244<0.001
Autism02552.730.00210,352.9619.320.000--0.987
Other mental disorders22552.7378.35510,352.9648.302.1861.4223.097<0.001
Suicide12552.7339.17410,352.9638.641.4360.9761.9460.104
All-caused mortality82552.73313.391810,352.96173.862.5781.7163.444<0.001
Suicide mortality12552.7339.17310,352.9628.982.0011.3592.663<0.001
Non-suicide mortality72552.73274.221510,352.96144.892.6821.7843.606<0.001
In the first year excludedOverall402390.111673.56769690.47784.283.7092.0664.128<0.001
Mental disorders322390.111338.85589690.47598.533.1922.1454.276<0.001
Anxiety72390.11292.87129690.47123.833.3732.2704.522<0.001
Depression102390.11418.39139690.47134.154.4532.9865.963<0.001
Bipolar22390.1183.6879690.4772.241.6541.1132.207<0.001
Sleep disorders62390.11251.0399690.4792.873.9352.5805.174<0.001
PTSD/ASD22390.1183.6829690.4720.645.5263.8847.801<0.001
Dementia12390.1141.8429690.4720.642.2701.9433.868<0.001
Eating disorders02390.110.0029690.4720.640.000--0.999
SRD12390.1141.8419690.4710.325.7453.8827.759<0.001
Psychotic disorders22390.1183.6849690.4741.282.8931.9403.894<0.001
Autism02390.110.0029690.4720.640.000--0.998
Other mental disorders12390.1141.8449690.4741.281.4480.8241.9350.093
Suicide12390.1141.8449690.4741.281.4930.9251.9430.075
All-caused mortality72390.11292.87149690.47144.472.8981.9423.875<0.001
Suicide mortality12552.7339.17310,352.9628.982.4021.3623.780<0.001
Non-suicide mortality62552.73235.041110,352.96106.253.7652.0877.184<0.001
In the first 5 years excludedOverall241751.061370.60487136.88672.562.9411.9733.945<0.001
Mental disorders191751.061085.06377136.88518.432.9822.0084.001<0.001
Anxiety51751.06285.5487136.88112.093.6372.4364.874<0.001
Depression81751.06456.8797136.88126.115.2193.4676.920<0.001
Bipolar21751.06114.2247136.8856.052.8781.9113.892<0.001
Sleep disorders31751.06171.3267136.8884.072.9081.9423.903<0.001
PTSD/ASD01751.060.0017136.8814.010.000--0.987
Dementia01751.060.0017136.8814.010.000--0.979
Eating disorders01751.060.0017136.8814.010.000--0.999
SRD01751.060.0017136.8814.010.000--0.993
Psychotic disorders11751.0657.1127136.8828.022.9201.9763.923<0.001
Autism01751.060.0017136.8814.010.000--0.999
Other mental disorders01751.060.0037136.8842.040.000--0.996
Suicide01751.060.0027136.8828.020.000--0.993
All-caused mortality51751.06285.5497136.88126.113.2312.1694.339<0.001
Suicide mortality02552.730.00210,352.9619.320.000--0.992
Non-suicide mortality52552.73195.87710,352.9667.613.6812.3046.724<0.001
PYs = Person-years; aHR = Adjusted Hazard ratio: adjusted for the variables listed in Table 3. CI = confidence interval, DM: diabetes mellitus; HTN: hypertension; CLD: chronic liver disease.
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MDPI and ACS Style

Sung, C.; Chung, C.-H.; Lin, F.-H.; Chien, W.-C.; Sun, C.-A.; Tsao, C.-H.; Weng, C.-E.; Ng, D.Y. A Population-Based Cohort Study of the Association between Visual Loss and Risk of Suicide and Mental Illness in Taiwan. Healthcare 2023, 11, 1462. https://doi.org/10.3390/healthcare11101462

AMA Style

Sung C, Chung C-H, Lin F-H, Chien W-C, Sun C-A, Tsao C-H, Weng C-E, Ng DY. A Population-Based Cohort Study of the Association between Visual Loss and Risk of Suicide and Mental Illness in Taiwan. Healthcare. 2023; 11(10):1462. https://doi.org/10.3390/healthcare11101462

Chicago/Turabian Style

Sung, Chieh, Chi-Hsiang Chung, Fu-Huang Lin, Wu-Chien Chien, Chien-An Sun, Chang-Huei Tsao, Chih-Erh Weng, and Daphne Yih Ng. 2023. "A Population-Based Cohort Study of the Association between Visual Loss and Risk of Suicide and Mental Illness in Taiwan" Healthcare 11, no. 10: 1462. https://doi.org/10.3390/healthcare11101462

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