Key Points
Question
Is there an association between strabismus and mental illness in the pediatric population?
Findings
In this cross-sectional study using data from a commercial insurance claims database of 12 005 189 children younger than 19 years, those with strabismus had higher odds of having anxiety disorder, schizophrenia, bipolar disorder, and depressive disorder compared with children without eye diseases.
Meaning
Understanding the association of mental illness with strabismus among children may improve diagnosis and management of psychiatric conditions for children with strabismus.
Abstract
Importance
Children with strabismus have poorer functional vision and decreased quality of life than those without strabismus.
Objective
To evaluate the association between strabismus and mental illness among children.
Design, Setting, and Participants
This cross-sectional study analyzed claims data from the OptumLabs Data Warehouse, a longitudinal deidentified commercial insurance claims database, from 12 005 189 patients enrolled in the health plan between January 1, 2007, and December 31, 2017. Eligibility criteria included age younger than 19 years at the time of strabismus diagnosis, enrollment in the health plan between 2007 and 2018, and having at least 1 strabismus claim based on International Classification of Diseases, Ninth Revision, Clinical Modification and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Clinical Modification codes. Controls were children in the same database with no eye disease codes other than refractive error reported. Demographic characteristics and mental illness claims were compared. Statistical analysis was conducted from December 1, 2018, to July 31, 2021.
Main Outcomes and Measures
Presence of mental illness claims.
Results
Among the 12 005 189 patients (6 095 523 boys [50.8%]; mean [SD] age, 8.0 [5.9] years) in the study, adjusted odds ratios for the association of mental illnesses with strabismus were 2.01 (95% CI, 1.99-2.04) for anxiety disorder, 1.83 (95% CI, 1.76-1.90) for schizophrenia, 1.64 (95% CI, 1.59-1.70) for bipolar disorder, 1.61 (95% CI, 1.59-1.63) for depressive disorder, and 0.99 (95% CI, 0.97-1.02) for substance use disorder. There was a moderate association between each strabismus type (esotropia, exotropia, and hypertropia) and anxiety disorder, schizophrenia, bipolar disorder, and depressive disorder; odds ratios ranged from 1.23 (95% CI, 1.17-1.29) for the association between esotropia and bipolar disorder to 2.70 (95% CI, 2.66-2.74) for the association between exotropia and anxiety disorder.
Conclusions and Relevance
This cross-sectional study suggests that there was a moderate association between strabismus and anxiety disorder, schizophrenia, bipolar disorder, and depressive disorder but not substance use disorder. Recognizing that these associations exist should encourage mental illness screening and treatment for patients with strabismus.
This cross-sectional study uses claims data from the OptumLabs Data Warehouse to evaluate the association between strabismus and mood disorders, schizophrenia, and anxiety disorders among children.
Introduction
Strabismus is one of the most common eye diseases in children, affecting 2% to 5% of children,1,2 or more than 1.5 million children in the US.3 There is growing evidence in the literature that patients with strabismus have decreased quality of life.4,5 Children with strabismus have lower visual function, including difficulties with school work and sports.6 In addition, several studies have demonstrated that there is negative bias against children with strabismus, by both peers and teachers.7,8,9 Children with strabismus also reported problems with self-image and experiences being teased for eye misalignment, glasses, and/or patching.10
Research suggests that patients with strabismus may have a higher risk of developing mental illness. For example, children with strabismus scored higher on measures of social phobia,11 and children with congenital esotropia and intermittent exotropia were more than 2 times likely than those without strabismus to develop a mental disorder by early adulthood.12,13 However, most of these studies were small and included patients from a particular geographic region. The purpose of this study was to investigate the association between strabismus and mental illness disorders among children with claims in the OptumLabs Data Warehouse, the largest available private health insurance claims database, representing a diverse population of ages, races and ethnicities, and geographic regions across the United States.14
Methods
This study was exempt from review by the institutional review board at the University of California, Los Angeles because information from the database was deidentified. All procedures were in accordance with the Declaration of Helsinski.15 This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies.
The study used claims from the OptumLabs Data Warehouse. OptumLabs is an open, collaborative research and innovation center founded in 2013 as a partnership between Optum and Mayo Clinic. The database contains deidentified, longitudinal health information on enrollees and patients, representing a diverse mixture of ages, races and ethnicities, and geographic regions across the United States.14 Claims data in the OptumLabs Data Warehouse include medical and pharmacy claims, laboratory test results, and enrollment records for commercial insurance and Medicare Advantage enrollees derived from an electronic health record. Medicare Part B (fee-for-service) and medical assistance programs are not included.
Medical claims data between January 1, 2007, and December 31, 2017, were used. Patients with strabismus or mental illness were identified as those who had a claim for the corresponding disease based on diagnosis codes in the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) or the International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) (Table 1). Patients without medical insurance, those older than 18 years, those with less than 6 months of total medical coverage since their first claim, and those with eye diseases other than strabismus were excluded. Controls consisted of children without any eye disease diagnoses other than refractive error.
Table 1. ICD-9-CM and ICD-10-CM Codes for Strabismus and Mental Disorders.
| Disease category | ICD-9-CM codes | ICD-10-CM codes |
|---|---|---|
| Strabismus | ||
| Strabismus | 378.0X-378.4X, 378.6X-378.8X, 368.2, 368.3X | H49.3X, H49.4X, H50.0X-H50.6X, H50.8X, H51.0X-H51.9X, H53.2X, H53.3X |
| Esotropia | 378.X, 378.21X, 378.22X, 378.34X, 378.35X, 378.41X, 378.71X, 378.84X, 378.85X | H50.0X, H50.31X, H50.32X, H50.42X, H50.43X, 50.51X, H50.81X, H51.12X |
| Exotropia | 378.1X, 378.23X, 378.24X, 378.42X, 378.83X, 378.86X | H50.1X, H50.33X, H50.34X, H50.52X, H51.11X, H51.2X |
| Hypertropia | 378.2, 378.20X, 378.3, 378.30X-378.33X, 378.4, 378.40X, 378.43X-378.45X, 378.61X, 378.62X, 378.87X | H50.3, H50.30X, H50.40X, H50.2X, H50.41X, H50.5, H50.50X, H50.53X-50.55X, H50.61X, H51.8X |
| Strabismus NOS | 378.6, 378.60X, 378.63X, 378.7, 378.72X, 378.73X, 378.8, 378.81X, 378.82X, 368.2X, 368.3X | H49.4X, H49.3X, H50.6, H50.60X, H50.69X, H50.8, H50.89X, H51.0X, H51, H51.9X, H53.2X, H53.3X |
| Mental disorders | ||
| Anxiety disorder | 300.0X, 300.2X, 309.21X, 313.23X | F40.9X, F40.0X, F40.1X, F40.21X, F40.240X, F40.241X, F40.8X, F41.9X, F93.0X, F94.0X |
| Depressive and related disorders | 296.2X, 296.3X, 296.82X, 296.9X, 298.0X, 300.4X, 311.X, 625.4X | F32.X, F33.X, F34.8X, F34.1X, F39.X, N94.3X |
| Substance-related and addictive disorders | 291.81X, 291.9X, 292.X, 293.89X, 303.X, 304.X, 305.X | F06.1X, F10.X, F11.X, F12.X, F13.X, F14.X, F15.X, F16.X, F17.2X, F18.X, F19.X |
| Bipolar and related disorders | 296.0X, 296.1X, 296.4X, 296.5X, 296.6X, 296.80X, 296.81X, 296.89X, 301.13X | F30.X, F31.X, F34.0X |
| Schizophrenia spectrum and other psychotic disorders | 295.X, 297.1X, 298.1X, 298.3X, 298.4X, 298.8X, 298.9X | F20.X, F22.X, F23.X, F25.X, F28.X, F29.X, F53.X |
| Dissociative disorder | 298.2X, 300.10X, 300.12X, 300.13X, 300.14X, 300.15X, 300.5X, 300.6X | F44.8X, F44.9X, F44.0X, F44.1X, F48.8X, F48.1X |
| Autism spectrum disorder | 299.X | F84.0X, F84.3X, F84.5X, F84.8X, F84.9X |
| Conversion disorder | 300.11X | F44.4X, F44.6X |
| Factitious disorder | 300.16X, 300.19X | F68.11X, F68.8X |
| Somatic symptom and related disorders | 300.7X, 300.8X, 300.9X, 307.8X, 307.9X, 316.X | F45.21X, F45.22X, F45.0X, F45.1X, F45.9X, F45.8X, F45.4X, F48.9X, F54.X, F99.X, G44.209X, R45.1X |
| Gender identity disorder (dysphoria) | 302.6X, 302.85X | F64.2X, F64.1X |
| Communication disorder | 307.0X, 307.3X, 315.35X, 315.36X, 315.4X, 315.5X | F80.8X, F80.0X, F82.X, F98.5X, F98.4X |
| Feeding and eating disorder | 307.1X, 307.5X | F50.X, F98.3X, F98.2X |
| Tic disorder | 307.2X | F95.X |
| Sleep-wake disorder | 307.4X | F51.9X, F51.02X, F51.09X, F51.01X, F51.03X, F51.19X, F51.11X, F51.12X, F51.8X, F51.3X |
| Elimination disorder | 307.6X, 307.7X | F98.0X, F98.1X |
| Trauma and stressor-related disorder | 308.3X, 309.22X, 309.23X, 309.81X, 313.89X | F43.0X, F43.1X, F93.8X, F94.8X, F94.1X, F98.8X |
| Adjustment disorder | 309.0X, 309.1X, 309.24X, 309.28X, 309.29X, 309.3X, 309.4X, 309.82X, 309.83X, 309.89X, 309.9X | F43.2X, F43.8X, F43.9X |
| Obsessive–compulsive and related disorder | 312.39X, 698.4X, 306.3X | F42.X, F63.3X, L98.1X |
| Disruptive, impulse control, and conduct disorders | 312.34X, 312.8X, 313.81X | F63.8X, F91.1X, F91.2X, F91.8X, F91.3X |
| Attention-deficit/hyperactivity disorder | 314.X | F90.X |
| Specific learning disorder | 315.0X, 315.1X, 315.2X | F81.0X, F81.8X, F81.2X, R48.0X |
| Neurodevelopmental disorder | 315.X, 315.9X | F81.9X, F88.X, F89.X |
| Intellectual disabilities | 317.X, 318.X, 319.X | F70.X, F71.X, F78.X, F72.X, F73.X, F79.X |
Abbreviations: ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; ICD-10-CM, International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Clinical Modification; NOS, not otherwise specified.
Extracted variables included age, sex, race and ethnicity, educational level of parents, household income, family net worth, geographic region, type of insurance, and comorbid conditions. Age for children with strabismus was determined as the age at the first strabismus claim; age for children without strabismus was the age at the first medical claim. Race and ethnicity were determined by the medial record and categorized as Asian, Black, Hispanic, White, or unknown. Insurance types included exclusive provider organization, health maintenance organization, point of service, preferred provider organization, indemnity, and other. Point of service refers to a managed care plan that is a hybrid of health maintenance organization and preferred provider organization, which allows participants to designate an in-network primary care professional but these participants are able to go outside the network for services.16 The presence of at least 1 systemic comorbid condition was used in the analysis to indicate general health. Comorbid conditions (Box) were selected based on a predictive model of 1-year mortality after hospital discharge among pediatric patients,17 which were also used in similar population studies investigating eye disease in children.18,19
Box. Comorbidities in Children With Strabismus and Children Without Eye Diseases.
Comorbidities
Septicemia (except in labor)
Mycoses
Cancer of brain and nervous system
Leukemias
Coagulation and hemorrhagic disorders
Diseases of white blood cells
Epilepsy; seizures
Essential hypertension
Hypertension with complications and secondary hypertension
Conduction disorders
Cardiac dysrhythmias
Cardiac arrest and ventricular fibrillation
Congestive heart failure; nonhypertensive
Acute cerebrovascular disease
Pneumonia (except that caused by tuberculosis or sexually transmitted infection)
Influenza
Aspiration pneumonitis; food or vomitus
Respiratory failure; insufficiency
Nervous system congenital anomalies
Intrauterine hypoxia and birth asphyxia
Fracture of neck of femur (hip)
Intracranial injury
Fever of unknown origin
Shock
Developmental disorders
Statistical Analysis
Statistical analysis was conducted from December 1, 2018, to July 31, 2021. Data extractions were conducted using SQL Software DBVisualizer Pro 10.0.15 (DbVis Software AB), and statistical analyses were performed using R, version 3.5.3 (R Group for Statistical Computing).20 Descriptive statistics were first calculated and presented for children with strabismus and children without eye diseases. Continuous variables were compared using t tests, and categorical variables were compared using χ2 tests. The unadjusted odds ratios (ORs) for mental illness were calculated with 95% CIs using univariate logistic regression models. Adjusted effects were estimated using multivariable logistic regression models with potential confounding variables. Potential confounding variables (ie, race and ethnicity and income level) were determined based on preliminary comparisons of the variable between children with strabismus and children without eye diseases. If there were no differences in the variable between the 2 groups, the variable was not considered to be a potential confounder. In addition, for variables that were highly interrelated (ie, family net worth and household income), only 1 variable was selected as a potential confounder.
To examine the association of eye disease with each mental illness, patients with other types of mental illnesses were excluded from the corresponding analysis (ie, when calculating the OR estimates), and patients without any mental illnesses served as the reference group in all the analyses. Similarly, when assessing the association of each subtype of strabismus with each mental illness, patients with other subtypes of strabismus were further excluded so that participants without any eye diseases were kept in the control group in all comparisons. To investigate whether there were collinearities between mental illnesses, a χ2 test was performed between each mental illness pair (ie, depression and anxiety). All P values were from 2-sided tests and results were deemed statistically significant at P < .05.
Results
A total of 12 005 189 participants (6 095 523 boys [50.8%]; mean [SD] age, 8.0 [5.9] years) were enrolled in the study; 352 636 children had strabismus, while 11 652 553 children had no eye disease diagnoses (control group). The characteristics of the enrolled children are listed in Table 2. The mean (SD) age was 8.0 (4.5) years in the strabismus group and 8.0 (5.9) years in the control group. The strabismus group had a slight predominance of female patients (50.1%), and most children were White (51.6%), came from a family with a household income greater than or equal to $40 000 (51.0%), had point-of-service insurance (68.7%), and had at least 1 comorbid condition (64.5%).
Table 2. Characteristics of Children With Strabismus vs Children Without Eye Diseases.
| Characteristic | Children, No. (%) | P value | |
|---|---|---|---|
| With strabismus (n = 352 636) | Without eye disease (n = 11 652 553) | ||
| Age at first claim, mean (SD), y | |||
| First strabismus diagnosis claim | 8.0 (4.5) | NA | <.001 |
| First claim | NA | 8.0 (5.9) | |
| Time from first claim to last enrollment date, mean (SD), y | 4.1 (3.0) | 4.2 (3.2) | <.001 |
| Sex | |||
| Female | 176 640 (50.1) | 5 731 188 (49.2) | <.001 |
| Male | 175 928 (49.9) | 5 919 595 (50.8) | |
| Race and ethnicity | |||
| Asian | 15 504 (4.4) | 453 549 (3.9) | <.001 |
| Black | 15 704 (4.5) | 762 199 (6.5) | |
| Hispanic | 21 350 (6.1) | 955 136 (8.2) | |
| White | 181 935 (51.6) | 5 755 047 (49.4) | |
| Unknown | 118 143 (33.5) | 3 726 622 (32.0) | |
| Parental educational level | |||
| Less than high school | 456 (0.1) | 35 256 (0.3) | <.001 |
| High school diploma | 36 456 (10.3) | 1 796 056 (15.4) | |
| Less than a bachelor’s degree | 122 513 (34.7) | 4 459 012 (38.3) | |
| Bachelor’s degree and/or higher degree(s) | 92 946 (26.4) | 2 134 778 (18.3) | |
| Unknown | 100 265 (28.4) | 3 227 451 (27.7) | |
| Household income, $ | |||
| <40 000 | 14 442 (4.1) | 732 556 (6.3) | <.001 |
| 40 000-74 999 | 27 074 (7.7) | 1 214 096 (10.4) | |
| 75 000-124 999 | 46 980 (13.3) | 1 640 746 (14.1) | |
| 125 000-199 999 | 46 883 (13.3) | 1 253 487 (10.8) | |
| ≥200 000 | 58 884 (16.7) | 1 142 923 (9.8) | |
| Unknown | 158 373 (44.9) | 5 668 745 (48.6) | |
| Family net worth, $ | |||
| <25 000 | 31 063 (8.8) | 1 519 594 (13.0) | <.001 |
| 25 000-149 999 | 40 019 (11.3) | 1 610 897 (13.8) | |
| 150 000-249 999 | 24 284 (6.9) | 838 076 (7.2) | |
| 250 000-499 999 | 42 913 (12.2) | 1 265 207 (10.9) | |
| ≥500 000 | 79 057 (22.4) | 1 702 434 (14.6) | |
| Unknown | 135 300 (38.4) | 4 716 345 (40.5) | |
| Census region | |||
| Midwest | 98 512 (28.0) | 3 057 701 (26.3) | <.001 |
| Northeast | 75 482 (21.4) | 1 375 678 (11.8) | |
| South | 128 646 (36.5) | 5 149 334 (44.3) | |
| West | 49 344 (14.0) | 2 028 115 (17.5) | |
| Type of insurance | |||
| EPO | 40 849 (11.6) | 1 331 557 (11.4) | <.001 |
| HMO | 27 711 (7.9) | 869 464 (7.5) | |
| Indemnity | 2035 (0.6) | 108 378 (0.9) | |
| Other | 3649 (1.0) | 247 448 (2.1) | |
| POS | 242 204 (68.7) | 7 832 967 (67.2) | |
| PPO | 36 188 (10.3) | 1 262 739 (10.8) | |
| Presence of ≥1 comorbidity | |||
| Yes | 227 382 (64.5) | 5 364 198 (46.0) | <.001 |
| No | 125 254 (35.5) | 6 288 355 (54.0) | |
Abbreviations: EPO, exclusive provider organization; HMO, health maintenance organization; NA, not applicable; POS, point of service; PPO, preferred provider organization.
The study evaluated 5 mental illness diagnoses: anxiety disorder, depressive disorder, substance use or addictive disorder, “bipolar disorder” (bipolar and related disorders), and “schizophrenia” (schizophrenia spectrum and other psychotic disorders). Their prevalence between children with and children without strabismus is shown in Table 3. Overall, children with strabismus had a higher prevalence of the mental illness diagnoses included, with the exception of substance use disorder, whose prevalence was lower among children with strabismus. There was an association between strabismus and anxiety disorder, depressive disorder, bipolar disorder, and schizophrenia before and after adjusting for age, sex, race and ethnicity, census region, educational level of caregiver, family net worth, and the presence of at least 1 comorbid condition. The adjusted ORs were 2.01 (95% CI, 1.99-2.04; P < .001) for anxiety disorder, 1.83 (95% CI, 1.76-1.90; P < .001) for schizophrenia, 1.64 (95% CI, 1.59-1.70; P < .001) for bipolar disorder, and 1.61 (95% CI, 1.59-1.63; P < .001) for depressive disorder. Substance use disorder had a negative unadjusted association with strabismus (OR, 0.85; 95% CI, 0.83-0.87; P < .001); however, after adjustment for confounders, the association between substance use disorder and strabismus was not significant (OR, 0.99; 95% CI, 0.97-1.02; P = .48).
Table 3. Data on Mental Illnesses for Children With Strabismus or Esotropia vs Children Without Eye Diseases.
| Mental illnesses | Patients, No. (%) | Univariable | Multivariable | Patients, No. (%) | Univariable | Multivariable | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Strabismus (n = 352 636) | Control (n = 11 652 553) | Unadjusted OR (95% CI) | P value | Adjusted OR (95% CI)a | P value | Esotropia (n = 184 005) | Control (n = 11 652 553) | OR (95% CI) | P value | Adjusted OR (95% CI)a | P value | |
| Anxiety disorder | 40 946 (11.6) | 751 270 (6.4) | 2.29 (2.26-2.31) | <.001 | 2.01 (1.99-2.04) | <.001 | 18 435 (10.0) | 751 270 (6.4) | 1.90 (1.87-1.93) | <.001 | 1.88 (1.85-1.91) | <.001 |
| Depressive disorder | 28 036 (8.0) | 736 561 (6.3) | 1.60 (1.58-1.62) | <.001 | 1.61 (1.59-1.63) | <.001 | 12 152 (6.6) | 736 561 (6.3) | 1.28 (1.25-1.30) | <.001 | 1.49 (1.46-1.52) | <.001 |
| Substance-related and addictive disorders | 6946 (2.0) | 344 282 (3.0) | 0.85 (0.83-0.87) | <.001 | 0.99 (0.97-1.02) | .48 | 2993 (1.6) | 344 282 (3.0) | 0.67 (0.65-0.70) | <.001 | 0.97 (0.93-1.01) | .12 |
| Bipolar and related disorders | 4116 (1.2) | 110 152 (0.9) | 1.57 (1.52-1.62) | <.001 | 1.64 (1.59-1.70) | <.001 | 1745 (0.9) | 110 152 (0.9) | 1.23 (1.17-1.29) | <.001 | 1.51 (1.44-1.59) | <.001 |
| Schizophrenia spectrum and other psychotic disorders | 2764 (0.8) | 60 905 (0.5) | 1.91 (1.83-1.98) | <.001 | 1.83 (1.76-1.90) | <.001 | 1112 (0.6) | 60 905 (0.5) | 1.42 (1.33-1.50) | <.001 | 1.61 (1.51-1.71) | <.001 |
Abbreviation: OR, odds ratio.
Adjusted for age, sex, race and ethnicity, census region, parental educational level, family net worth, and the presence of at least 1 comorbidity.
The association between strabismus and mental illness was further studied by dividing the strabismus group into those with esotropia (52.2%) (Table 3), exotropia (46.3%), and hypertropia (12.5%) (Table 4). Some patients had multiple strabismus diagnoses, so they were included in the analysis of each subtype. For the esotropia group, the adjusted OR for anxiety disorder was 1.88 (95% CI, 1.85-1.91; P < .001), the adjusted OR for depressive disorder was 1.49 (95% CI, 1.46-1.52; P < .001), the adjusted OR for substance use disorder was 0.97 (95% CI, 0.93-1.01; P = .12), the adjusted OR for bipolar disorder was 1.51 (95% CI, 1.44-1.59; P < .001), and the adjusted OR for schizophrenia was 1.61 (95% CI, 1.51-1.71; P < .001) (Table 3). For the exotropia group, the adjusted OR for anxiety disorder was 2.13 (95% CI, 2.10-2.16; P < .001), the adjusted OR for depressive disorder was 1.67 (95% CI, 1.64-1.70; P < .001), the adjusted OR for substance use disorder was 0.92 (95% CI, 0.87-0.95; P < .001), the adjusted OR for bipolar disorder was 1.68 (95% CI, 1.60-1.76; P < .001), and the adjusted OR for schizophrenia was 1.85 (95% CI, 1.75-1.95; P < .001) (Table 4). For the hypertropia group, the adjusted OR for anxiety disorder was 2.12 (95% CI, 2.06-2.19; P < .001), the adjusted OR for depressive disorder was 1.61 (95% CI, 1.55-1.67; P < .001), the adjusted OR for substance use disorder was 0.97 (95% CI, 0.90-1.04; P = .38), the adjusted OR for bipolar disorder was 1.69 (95% CI, 1.55-1.85; P < .001), and the adjusted OR for schizophrenia was 1.85 (95% CI, 1.66-2.06; P < .001). In summary, esotropia, exotropia, and hypertropia were associated with increased odds of anxiety disorder, depressive disorder, bipolar disorders, and schizophrenia. However, exotropia was associated with decreased odds of substance use disorder, and no associations were found between substance use disorder and esotropia and hypertropia.
Table 4. Data on Mental Illnesses for Children With Exotropia or Hypertropia vs Children Without Eye Diseases.
| Mental illnesses | Patients, No. (%) | Univariable | Multivariable | Patients, No. (%) | Univariable | Multivariable | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Exotropia (n = 163 439) | Control (n = 11 652 553) | OR (95% CI) | P value | Adjusted OR (95% CI)a | P value | Hypertropia (n = 43 987) | Control (n = 11 652 553) | OR (95% CI) | P value | Adjusted OR (95% CI)a | P value | |
| Anxiety disorder | 21 296 (13.0) | 751 270 (6.4) | 2.70 (2.66-2.74) | <.001 | 2.13 (2.10-2.16) | <.001 | 5253 (11.9) | 751 270 (6.4) | 2.46 (2.39-2.54) | <.001 | 2.12 (2.06-2.19) | <.001 |
| Depressive disorder | 14 320 (8.8) | 736 561 (6.3) | 1.85 (1.82-1.88) | <.001 | 1.67 (1.64-1.70) | <.001 | 3428 (7.8) | 736 561 (6.3) | 1.64 (1.58-1.70) | <.001 | 1.61 (1.55-1.67) | <.001 |
| Substance-related and addictive disorders | 3255 (2.0) | 344 282 (3.0) | 0.90 (0.87-0.93) | <.001 | 0.92 (0.87-0.95) | <.001 | 850 (1.9) | 344 282 (3.0) | 0.87 (0.81-0.93) | <.001 | 0.97 (0.90-1.04) | .38 |
| Bipolar and related disorders | 2097 (1.3) | 110 152 (0.9) | 1.81 (1.73-1.89) | <.001 | 1.68 (1.60-1.76) | <.001 | 523 (1.2) | 110 152 (0.9) | 1.67 (1.53-1.82) | <.001 | 1.69 (1.55-1.85) | <.001 |
| Schizophrenia spectrum and other psychotic disorders | 1416 (0.9) | 60 905 (0.5) | 2.21 (2.10-2.33) | <.001 | 1.85 (1.75-1.95) | <.001 | 343 (0.8) | 60 905 (0.5) | 1.98 (1.78-2.21) | <.001 | 1.85 (1.66-2.06) | <.001 |
Abbreviation: OR, odds ratio.
Adjusted for age, sex, race and ethnicity, census region, parental educational level, family net worth, and the presence of at least 1 comorbidity.
The eTable in the Supplement shows the associations between mental illness pairs. All mental illnesses were associated with each other based on the large estimated OR, which ranged from 9.16 (95% CI, 9.09-9.22) for anxiety disorder and substance use disorder to 70.67 (95% CI, 69.34-71.86) for bipolar disorder and schizophrenia. However, the agreement between each mental illness pair was low, with κ ranging from 0.07 for anxiety disorder and schizophrenia to 0.43 for anxiety disorder and depressive disorder, with no collinearity. For reference, κ of 0 indicates no agreement, 0.75 indicates good agreement, and 1 indicates complete agreement.21
Discussion
Strabismus among children was associated with anxiety disorder, schizophrenia, bipolar disorder, and depressive disorder. The odds of having these psychiatric diagnoses were higher among children with strabismus than children without eye disease, with an estimated OR ranging from 1.61 to 2.01. This finding is comparable to a study conducted in Germany, which found that children with strabismus had more mental health problems (OR, 1.50 [95% CI, 1.14-1.98]; P = .005).22 In the US, a limited number of studies have shown that children with congenital esotropia were 2.6 times more likely to receive a mental health diagnosis by young adulthood12 and that children with intermittent exotropia were 2.7 times more likely to receive a mental health diagnosis by young adulthood.13 It is probable that our study found a lower risk than these studies because our study was cross-sectional and claims based, whereas these studies observed the children to early adulthood and were based on medical records.
Each type of strabismus (esotropia, exotropia, and hypertropia) in this study had an increased association with 4 mental illness subgroups. There is prior evidence that patients with esotropia, exotropia, or hypertropia have increased risk of developing mental illness.23,24 However, it is unclear whether the type of strabismus has an association with the magnitude of mental illness risk. In 1 study, children with exotropia (intermittent exotropia and convergence insufficiency) were more likely to develop mental illness than those without strabismus, whereas children with esotropia (congenital, accommodative, and nonaccommodative) were not more likely to develop mental illness compared with controls.23 However, a similar study found that children with congenital esotropia were more likely than controls to develop mental illness.12 Among adults, patients with divergence insufficiency but not convergence insufficiency were more likely to have been hospitalized and to have used medication for mental health diagnoses.24 Studies are needed to investigate whether strabismus type is associated with mental illness risk.
It is unclear why exotropia had a decreased association with substance abuse. It is known that some substances, such as alcohol, can exacerbate strabismus.25 Patients with strabismus may limit substance use for this reason, and certain populations (ie, those with intermittent exotropia) may be more inclined to avoid substances if they manifest detectable strabismus only with substance use. However, this finding is different from that of a study of Chinese children aged 6 to 17 years, which found that children with strabismus had a higher self-reported history of drinking but not smoking compared with children without strabismus.26
Limitations
This study has some limitations, including its cross-sectional design and use of claims data, for which incomplete reporting is possible. A causality between strabismus and mental illness cannot be established in this study design. It is likely that the association between strabismus and mental illness is complex and varies with type of mental illness. Some studies have demonstrated that there is a negative social bias against children with strabismus,8,9 which may cause these children to experience higher levels of social stress, predisposing them to develop mental illness. There may also be a genetic basis for the association between certain types of strabismus and mental illness. For example, a polymorphism of the PMX2B (GenBank AB015671) gene has been associated with constant exotropia and schizophrenia.27
Another limitation is our use of a commercial health care payer database. Therefore, our results may not reflect patients with no insurance or with government insurance. However, the OptumLabs Data Warehouse includes a large and diverse population across all 50 states. The prevalence rates of strabismus and depression in our population were 2% and 3%, respectively, which are similar to other large studies.1,2,28,29 Analysis of a large database may yield statistically significant data even with a small, clinically unimportant difference between groups. However, the magnitude of the ORs ranging from 1.51 to 2.13 in this study may well be clinically substantial.
A criticism of research using claims data is that there is a chance of inflation of medical diagnoses with more physician visits.30 For example, it is possible that people who seek more medical care have more medical diagnoses in general. This possibility could mean that patients with strabismus may have more mental illness diagnoses just because they have more physician visits than those without eye diseases, making the association between strabismus and mental illness more likely. However, if this possibility were the case, all mental illnesses should be positively associated with strabismus, which we did not find for strabismus and substance abuse. In addition, patients with one mental illness may have a higher chance of having another mental illness. The χ2 test between each mental illness pair showed that mental illnesses were associated with each other, as shown by high estimated ORs, but the agreement was not high because there was no collinearity between them. Furthermore, each mental illness was analyzed as a single outcome while excluding all other mental illnesses from the comparisons, so the estimated OR should not be affected by collinearity (if any) between mental illnesses. Another limitation of claims-based research is the possibility of coding errors. However, the use of ICD-9-CM and ICD-10-CM codes is an accepted method for studying large databases.31,32
Future work is needed to explore the association between strabismus and various mental illnesses. It would be helpful to study whether the magnitude and type of strabismus are associated with the severity of mental illness. It would also be useful to study whether correction of strabismus can help mental illness. There is some mixed evidence regarding this in the literature. Some studies show that strabismus surgery can improve measures of quality of life and anxiety and depression scores.4,33 However, another study has demonstrated that surgical correction of intermittent exotropia is not associated with the risk of subsequently developing mental illness in early adulthood.34 More research is needed to study specific types of strabismus and whether there is a threshold age or strabismus severity for treatment to have an effect on mental health.
Conclusions
We found an increased association of mental illness with strabismus. Research has shown that only 15% to 30% of children with mental illness receive treatment owing to underrecognition.35 These results should alert ophthalmologists and optometrists to counsel children and their caregivers regarding the risk for mental illness. They should consider incorporating a screening tool for mental health problems for patients with strabismus and referral of pediatric patients with strabismus for mental health evaluation.
eTable. Associations Between Mental Illnesses
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Associated Data
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Supplementary Materials
eTable. Associations Between Mental Illnesses