The Underestimated Role of Refractive Error (Hyperopia,Myopia,and Astigmatism) and Strabismus in Children With ADHD

Abstract

Objective: To examine the association of refractive error (myopia, hyperopia, astigmatism) and strabismus with ADHD. Method: Based on data from the large, representative, epidemiological sample of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) study (N = 13,488), the associations of myopia, hyperopia, astigmatism, and strabismus with ADHD were examined, with and without consideration of other common ADHD risk factors. Results: In single logistic regression models, all examined forms of refractive error and strabismus showed an association with ADHD. After controlling for confounding variables, results remained stable and showed an increased risk for ADHD in children with hyperopia, astigmatism, and strabismus compared with the control group. Only the association between myopia and ADHD in children was not significant. Conclusion: Hyperopia, astigmatism, and strabismus seem to be independently associated with ADHD. Health care professionals in different medical fields should consider this association to adequately diagnose and treat affected children.

Keywords

attention deficit disorder ADHD refractive error strabismus epidemiology

Introduction

Visual perception influences children’s behavior and development, especially attentional abilities, and learning and reading processes (Buttross, 2000). Refractive error can lead to deficits in these competences and their development. Studies examining refractive error reported hyperopia to be associated with poorer performance on visual-cognitive and visual-motor tasks, compared with children without such a refractive error (Fredrick, 2002). W. Williams, Latif, Hannington, and Watkins (2005) found an association between hyperopia and academic skills. Children with hyperopia scored lower on (a) standardized assessment tests (English, mathematics, and science) as well as on (b) reading and writing exams (W. Williams et al., 2005). In addition, it has been pointed out (Shankar, Evans, & Bobier, 2007) that children with uncorrected hyperopia revealed reduced performance on tests of letter and word recognition, receptive vocabulary, and emergent orthography compared with children with emmetropia, which is defined as an absence of refractive error (Fredrick, 2002). Recently, another study showed that uncorrected hyperopia in children was associated with worse performance on early literacy tests (Kulp et al., 2016).

Interestingly, a diagnosis of ADHD, like inattention, hyperactivity, and impulsiveness, can have similar consequences: for example, impairment in academic skills, social skills, intellectual functioning, and occupational functioning (Faraone, Sergeant, Gillberg, & Biederman, 2003; Grizenko et al., 2012). A growing number of researchers focus on the association of childhood ADHD and academic skills, pointing out a negative association (Daley & Birchwood, 2010; Diamantopoulou, Rydell, Thorell, & Bohlin, 2007). It has been found that ADHD is related to lower grades, poorer reading, and mathematical skills as well as to an increased risk for repeating a school year (Loe & Feldman, 2007; Merrell & Tymms, 2001). Another study showed that inattention and hyperactivity were negatively associated with reading achievement in children (Rabiner, Coie, & Conduct Problems Prevention Research Group, 2000). Even though it is not recommended in all ADHD guidelines, some international ADHD guidelines recommend to rule out any other possible medical cause for the ADHD symptoms (e.g., American Academy of Pediatrics; Canadian ADHD Practice Guidelines) or even mention sensory deficits (S3 Guidelines ADHD). Thus, to exclude sensory deficits as a cause or trigger for the observed symptoms, vision screenings should be completed before diagnosing ADHD.

ADHD is a highly prevalent and heterogeneous psychiatric disorder of childhood onset. Worldwide prevalence rates of ADHD, including all editions of the Diagnostic and Statistical Manual of Mental Disorders (DSM), rank about 7%. In Germany, a rate of 4.8% was reported based on a large representative epidemiological study of the German Health Interview and Examination Survey for Children and Adolescents study (KiGGS study; Huss, Hölling, Kurth, & Schlack, 2008). ADHD is diagnosed mostly during school age, although first symptoms as well as associated cognitive and behavioral problems are often present before school entry (Arnett, MacDonald, & Pennington, 2013). Symptoms commonly change or decrease with age, but often persist into adulthood (Faraone et al., 2003; Grizenko et al., 2012). Uncorrected refractive errors and strabismus represent an important public health problem with childhood prevalence rates between 5% and 7.7% (Kvarnström, Jakobsson, Lennerstrand, & Dahlgaard, 2006; Lanca, Serra, & Prista, 2014). Interestingly, prevalence and severity of refractive errors, like hyperopia or myopia are also age-dependent and the onset also occurs during school age, which further emphasizes the relevance for both a detailed psychiatric and physical examination during the diagnostic procedure of ADHD (Castagno, Fassa, Carret, Vilela, & Meucci, 2014; O’Donoghue et al., 2010).

To date, only few studies investigated the association between refractive error and ADHD with mixed results (DeCarlo et al., 2014; DeCarlo, Swanson, McGwin, Visscher, & Owsley, 2016; Granet, Gomi, Ventura, & Miller-Scholte, 2005; Grönlund, Aring, Landgren, & Hellström, 2007; Mezer & Wygnanski-Jaffe, 2012). Although the majority observed that the prevalence of refractive error was higher in children and adolescents with ADHD compared with healthy controls (DeCarlo et al., 2014; DeCarlo et al., 2016; Granet et al., 2005; Grönlund et al., 2007; Mezer & Wygnanski-Jaffe, 2012), another study found no association (Fabian et al., 2013). Current research analyzing the association of refractive error and ADHD focuses only on the specific relationship of insufficiency of convergence or accommodation and ADHD, noting a greater occurrence of these both forms of refractive error in children with ADHD (Bartuccio, Taub, & Kieser, 2008; Borsting, Rouse, & Chu, 2005; Granet et al., 2005; Rouse et al., 2009). Both manifest in an inability to adequately focus or sustain focus at near, without undue effort (Bartuccio et al., 2008; Granet et al., 2005). Therefore, they typically become more evident in a school environment, where the need to focus on close objects increases, and an inability to do so potentially affects the child’s learning experience and performance negatively (Bartuccio et al., 2008; Sterner, Gellerstedt, & Sjöström, 2006).

Studies linking ADHD to other (than accommodative and convergence insufficiency) common forms of refractive error, like myopia, hyperopia, astigmatism, and strabismus, are sparse and further research in this field is urgently needed considering the fundamental role of vision for academic achievement. To the best of our knowledge, only two studies (Grönlund et al., 2007; Mezer & Wygnanski-Jaffe, 2012) investigated visual function and ocular features in children with ADHD and suggested a higher rate of different forms of refractive errors (i.e., myopia, hyperopia, astigmatism) and strabismus in children with ADHD. Although one study (Mezer & Wygnanski-Jaffe, 2012) reported refractive errors in 39% of the examined children with ADHD, another study (Grönlund et al., 2007) found that 76% of children with ADHD had a refractive error. They concluded that refractive error can hamper the development of children with ADHD (Mezer & Wygnanski-Jaffe, 2012). Vice versa (ADHD in children with refractive error), two other studies (Chung, Chang, Rhiu, Lew, & Lee, 2012; Mohney et al., 2008) reported an elevated rate of 15.7% (Chung et al., 2012) and 17.7% (Mohney et al., 2008) of ADHD in children with strabismus. They concluded that childhood strabismus might contribute to ADHD-related symptoms (Chung et al., 2012).

In summary, there is broad base of evidence that both refractive error and strabismus and ADHD negatively affect children’s behavior, learning, reading, and attentional abilities. Therefore, it is crucial to disentangle the role of refractive error and strabismus and ADHD to optimize diagnostics and treatment. In addition, it seems to be relevant to scrutinize whether refractive error and strabismus and ADHD are associated with other shared risk factors, like, for example, premature birth (Goktas, Sener, & Sanac, 2012; van Dyk et al., 2015), or solely show similar symptoms and consequences. This article aims to analyze whether refractive error and strabismus is associated with an increased risk for a diagnosis of ADHD and if so, if specific forms of refractive error or strabismus are at higher risk. These research questions were analyzed based on the data from the large, representative, cross-sectional, epidemiological sample of the KiGGS (N = 13,488) while considering common environmental risk factors (children’s age and gender, socioeconomic status, maternal age at childbirth, and low birth weight/preterm birth), which have been shown to be closely related to both, refractive errors and strabismus and ADHD (Goktas et al., 2012; C. Williams et al., 2008).

Materials and Method

Design and Sample

The KiGGS study represents a large representative, cross-sectional epidemiological examination conducted by the Robert Koch Institute. During May 2003 to May 2006, a total number of 17,641 children and adolescents aged between 0 and 17 years and their parents participated. All participants were physically and medically examined. All parents completed an extensive health questionnaire, which involved physical, mental, and social health, and children aged 11 years and older completed a broad range of self-administered questionnaires. Also, a computer-assisted personal interview was undertaken and physical measurements and laboratory tests were conducted.

The study was approved by the Charité Universitätsmedizin Berlin ethics and the Federal Office for Protection Data and completely complies with the Declaration of Helsiniki. Further information related to study design, objectives, procedures, and measurements of the KiGGS study can be found in Kurth et al. (2008).

Participants

The current analysis involved a total number of 13,488 children between 3 and 17 years with valid information regarding a diagnosis of ADHD (see Figure 1). As an ADHD diagnosis is not applicable in children aged younger than 3 years (Huss et al., 2008), children up to the age of 3 years were excluded from any further analysis.

Figure 1.

Flow diagram of the sample selection showing in the first box all participants of the study, then the excluded cases of the used sample in the second box (due to cases not appropriate for age and missing information on ADHD), and finally in the lowest box the valid cases used for the analysis.

Parents of the participants were asked whether their child was ever diagnosed with ADHD, and, if “yes,” whether the diagnosis was made by a medical doctor or psychologist. The diagnosis therefore relied on a parental statement, not on a specific diagnostic examination. For an estimation of the validity of the parental answer (whether their child has ever been diagnosed with ADHD, and if yes whether the diagnose was made by a psychologist or physician), symptomatic information was correlated with the scale “hyperactivity” of the strengths and difficulties questionnaire (SDQ) and revealed a value of Cronbach’s α = .78 (see also Schlack et al., 2014). In addition, a receiver operating characteristic curve (ROC) analysis with the hyperactivity scale of the SDQ as explanatory variable and the diagnosis question as criterion was applied and revealed a AUC (area under the curve) of .86. Both test results suggest parental answers being a valid measure (Schlack et al., 2014). Based on this question, the ADHD group included a total number of 660 (4.9%) children and adolescents between 3 and 17 years. The control group included a total number of 12,828 (95.1%) children and adolescents aged between 3 and 17 years, who never received an ADHD diagnosis. Within the ADHD group, 527 (79.8%) children were male, while only 6,224 (48.5%) children were male in the control group. Thus, males received significantly more ADHD diagnoses than females (χ² = 246.45; df = 1; p < .001). Within the ADHD group 57 (8.6%) of the children were 3 to 6 years, 215 (32.6%) were 7 to 10 years, 202 (30.6%) were 11 to 13 years, and 186 (28.2%) were 14 to 17 years, while in die control group 3,509 (27.4%) children were 3 to 6 years, 3,542 (27.6%) were 7 to 10 years, 2,581 (20.1%) were 11 to 13 years, and 3,196 (24.9%) were 14 to 17 years old (χ² = 124.86; df = 3; p < .001).

Predictors

Information regarding refractive errors and strabismus was measured within the parent questionnaire by asking if the child had ever one of the following three specified forms of refractive error: myopia, hyperopia, astigmatism, or strabismus. For each form of refractive error and strabismus, parents could answer the question with “yes,” “no,” or “don’t know.” Regarding all forms of refractive error and strabismus any “don’t know” replies were excluded from any further analysis.

Myopia

The occurrence (“yes”) of myopia (N = 1,600; 13.2%) was compared with the nonoccurrence (“no”) group of a myopia (N = 10,512; 86.8%).

Hyperopia

Children and adolescents with (“yes”) hyperopia (N = 996; 8.4%) were compared with children without (“no”) hyperopia (N = 10,832; 91.6%).

Astigmatism

Also the group of children and adolescents with (“yes”) astigmatism (N = 767; 6.5%) were investigated compared with the group of children without (“no”) astigmatism (N = 11,117; 91.6%).

Strabismus

The same differentiation was made for the occurrence (“yes”) of strabismus (N = 533; 4.4%) and the nonoccurrence (“no”) of strabismus (N = 11,599; 95.6%).

Control Variables

The potential control variables included children’s age and gender, parental socioeconomic status, maternal age at childbirth, and low birth weight/premature birth. Socioeconomic status measures social class including information of both parents regarding their professional and educational status and total family household income. An individual score was calculated (range of sum-score: 3-21) based on the definition of Kurth and colleagues (2008) and Winkler and Stolzenberg (1999) (Kurth et al., 2008; Winkler and Stolzenberg, 1999). According to common literature indications (Gustafsson & Källén, 2011; van Dyk et al., 2015), mother’s age at childbirth was divided into three categories (“⩽20years,” “21-35years,” “⩾36years”), low birth weight was defined as a birth weight less than 2,500 g and premature birth was defined as a birth prior to 37th week of gestation (Botting, Powls, Cooke, & Marlow, 1997; Halmøy, Klungsøyr, Skjærven, & Haavik, 2012; Mick, Biederman, Prince, Fischer, & Faraone, 2002).

Statistical Analysis

Statistical Package for Social Science (SPSS), version 22.0, was used to compute descriptive analysis and concurrent and prospective associations. Logistic regression analyses were conducted to calculate the associations (odds ratios [ORs] with 95% confidence intervals [CI]) between myopia, hyperopia, astigmatism, and strabismus variables and ADHD. All of the potential examined control variables that were significantly associated with ADHD were included in adjusted multivariable models. Statistical significance was evaluated two-sided at the 5% level.

Results

Association of Potential Confounding Variables and ADHD

To identify potential associations between the control variables and ADHD, single logistic models were computed. Results from the single models showed that all considered control variables were associated with ADHD (Table 1). Therefore, participants’ age and gender, socioeconomic status, young maternal age at childbirth, and low birth weight/premature birth were considered as control variables in any further computed adjusted multivariable model analyses.

Table 1.

Regression Analysis for the Relevant Control Variables Predicting ADHD (N = 13,488).

Predictor	Outcome ADHD diagnosis				OR (95% CI)
	No		Yes		OR (95% CI)
	n	%	n	%	Single models
Gender
Female (ref)	6,604	98.0	133	2.0
Male	6,224	92.2	527	7.8	4.20 [3.46, 5.10]
Age
3-17					1.08 [1.06, 1.10]
Socioeconomic status scale
3 (lowest)-21 (highest)					1.07 [1.05, 1.09]
Mothers age at childbirth
⩽20years	564	91.9	50	8.1	1.78 [1.31, 2.4]
21-35years	10,589	95.3	528	4.7
⩾36years	799	96.0	33	4.0	0.83 [0.58, 1.19]
Low birth weight/premature birth
No (ref)	9,928	95.3	487	4.7
Yes	1,996	94.2	123	5.8	1.26 [1.02, 1.54]

Note. The significant results are printed in bold letters. OR = odds ratio; CI = confidence interval; ref = reference.

Association of Myopia, Hyperopia, Astigmatism, and Strabismus With ADHD

Within the ADHD group, 40.2% (N = 265) children showed any form (myopia, hyperopia, astigmatism) of refractive error or strabismus, while 29.5% (N = 3,786) of the control group had a refractive error or strabismus (χ² = 33.86; df = 1; p < .001). Although 16.2% (N = 91) of the ADHD children and 13.1% (N = 1,509) of the children in the control group were myopic (χ² = 4.75; df = 1; p < .05), 13.0% (N = 71) of the ADHD group and 8.2% (N = 925) of the control group participants were hyperopic (χ² = 15.59; df = 1; p < .001). Furthermore, significant group differences appeared between the ADHD group and the healthy control group regarding astigmatism and strabismus. Over 10.9% (N = 60) of the ADHD and 6.2% (N = 702) of the control group suffered from astigmatism (χ² = 18.96; df = 1; p < .001), and 8.2% (N = 47) of the ADHD and 4.2% (N = 486) of the control group from strabismus (χ² = 21.01; df = 1; p < .001) (Table 2).

Table 2.

Group Differences for the ADHD and the Control Group Regarding Myopia, Hyperopia, Astigmatism, and Strabismus.

Predictor	Outcome ADHD diagnosis				Group difference
	No		Yes		Group difference
	n	%	n	%	χ²	df	p
Visual impairment					33.86	1	<.001
No	9,042	70.5	395	59.8
Yes	3,786	29.5	265	40.2
Myopia					4.57	1	<.05
No	10,041	86.9	471	83.8
Yes	1,509	13.1	91	16.2
Hyperopia					15.59	1	<.001
No	10,357	91.8	475	87.0
Yes	925	8.2	71	13.0
Astigmatism					18.96	1	<.001
No	10,627	93.8	490	89.1
Yes	707	6.2	60	10.9
Strabismus					21.01	1	<.001
No	11,075	95.8	524	91.8
Yes	486	4.2	47	8.2

Note. χ² = Pearsons; df = degrees of freedom.

All examined forms of refractive error (myopia, hyperopia, and astigmatism) and strabismus were associated with ADHD in single models. Results revealed a higher risk for ADHD in children with myopia (OR: 1.29, 95% CI: [1.02, 1.62]), hyperopia (OR: 1.67, 95% CI: [1.29, 2.17]), astigmatism (OR: 1.84, 95% CI: [1.39, 2.43]), and strabismus (OR: 2.04, 95% CI: [1.49, 2.79]) compared with children with no refractive error or strabismus (Table 3).

Table 3.

Regression Analysis for Myopia, Hyperopia, Astigmatism, and Strabismus With ADHD (N = 13,488).

Predictor	Outcome ADHD diagnosis				OR (95% CI)
	No		Yes		OR (95% CI)
	n	%	n	%	Single models
Myopia
No (ref)	10,041	86.9	471	83.8
Yes	1,509	13.1	91	16.2	1.29 [1.02, 1.62]
Hyperopia
No (ref)	10,357	91.8	475	87.0
Yes	925	8.2	71	13.0	1.67 [1.29, 2.17]
Astigmatism
No (ref)	10,627	93.8	490	89.1
Yes	707	6.2	60	10.9	1.84 [1.39, 2.43]
Strabismus
No (ref)	11,075	95.8	524	91.8
Yes	486	4.2	47	8.2	2.04 [1.49, 2.79]

Note. The significant results are printed in bold letters. OR = odds ratio; CI = Confidence interval; ref = reference.

After controlling for potential confounding variables (children’s age and gender, socioeconomic status, young maternal age at childbirth, and low birth weight/premature birth) all results remained stable, except the association of myopia and ADHD. Children and adolescents with hyperopia (OR: 1.63, 95% CI: [1.23, 2.18]), astigmatism (OR: 1.85, 95% CI: [1.36, 2.6]) and strabismus (OR: 2.13, 95% CI: [1.52, 2.99]) showed a higher risk for ADHD compared with children without any form of refractive error or strabismus (Table 4).

Table 4.

Regression Analysis for Myopia, Hyperopia, Astigmatism, and Strabismus With ADHD (N = 13,488), Controlled for Children’s Age and Gender, Socioeconomic Status, Maternal Age at Childbirth, and Low Birth Weight/Premature Birth.

Predictor	Outcome ADHD diagnosis				OR (95% CI)
	No		Yes		OR (95% CI)
	n	%	n	%	Single models
Myopia
No (ref)	10,041	86.9	471	83.8
Yes	1,509	13.1	91	16.2	1.12 [0.86, 1.46]
Hyperopia
No (ref)	10,357	91.8	475	87.0
Yes	925	8.2	71	13.0	1.63 [1.23, 2.18]
Astigmatism
No (ref)	10,627	93.8	490	89.1
Yes	707	6.2	60	10.9	1.85 [1.36, 2.6]
Strabismus
No (ref)	11,075	95.8	524	91.8
Yes	486	4.2	47	8.2	2.13 [1.52, 2.99]

Note. The significant results are printed in bold letters. OR = odds ratio; CI = Confidence interval; ref = reference.

Discussion

The present study examined the role of myopia, hyperopia, astigmatism, and strabismus in the occurrence of ADHD based on a large, representative, cross-sectional, epidemiological data set from Germany. The observed general, that is, nonspecific for ADHD, prevalence rates of myopia (13.2%), hyperopia (8.4%), astigmatism (6.5%), and strabismus (4.4%) are comparable with other European prevalence rates for children and adolescents (Czepita, Mojsa, Ustianowska, Czepita, & Lachowicz, 2006; Donnelly, Stewart, & Hollinger, 2005; Logan, Shah, Rudnicka, Gilmartin, & Owen, 2011; O’Donoghue et al., 2010; O’Donoghue et al., 2011; Villarreal, Ohlsson, Abrahamsson, Sjöström, & Sjöstrand, 2000). In single models, an increased risk for ADHD in children with myopia, hyperopia, astigmatism, and strabismus was observed compared with children without refractive error or strabismus. In multiple models, all results, except the relation between myopia and ADHD, remained stable. Thus, children with hyperopia (OR: 1.63, 95% CI: [1.23, 2.18]), astigmatism (OR: 1.85, 95% CI: [1.36, 2.6]), and strabismus (OR: 2.13, 95% CI: [1.52, 2.99]) showed an increased risk for ADHD. Our results are generally in line with other studies, which also demonstrated an association between refractive error or strabismus and ADHD (Borsting et al., 2005; DeCarlo et al., 2014; DeCarlo et al., 2016; Granet et al., 2005; Grönlund et al., 2007; Mezer & Wygnanski-Jaffe, 2012). It seems plausible to assume that refractive error and strabismus may reduce concentration and thus can cause symptoms of inattention and increased undesirable activity with the consequence of affecting the child’s behavior, learning, and school performance (Bartuccio et al., 2008; Sterner et al., 2006). However, it is also crucial to point out that our results describe a positive association, but do not allow conclusions about causal mechanisms. One possible explanation of the observed association is that some children with refractive error or strabismus might be incorrectly diagnosed with ADHD, because their difficulties resulting from refractive error or strabismus (which might be not or insufficiently treated), in combination with other, subclinical behavioral problems, “mimic” ADHD (mainly inattentive type) symptoms. These children may not be able to keep their attention focused as compared with children without refractive error or strabismus. At the same time, if they are struggling to visually focus on their work, they may have difficulties completing tasks in the required amount of time (DeCarlo et al., 2016; Granet et al., 2005). Above that it could be hypothesized that the association of refractive error and strabismus and ADHD might be influenced by shared risk factors. But since we have controlled for several possible common risk factors and the association of refractive error and strabismus and ADHD remains significant, the relation between both disorders seems to be independent from these examined factors. Another—and probably additional—explanation of the positive association is that children with ADHD might be more often examined ophthalmologically to exclude a potential physical cause of the ADHD symptoms, compared with children without ADHD. Therefore, due to a higher rate of ophthalmological examinations in the group of ADHD children, more refractive error and strabismus might be discovered and possibly also slight refractive error or strabismus might be diagnosed more frequently, compared with children without ADHD.

Until now, the underlying mechanisms of the association between refractive error and strabismus and ADHD remain unclear and need further investigation. However, the presence of hyperopia, astigmatism, or strabismus might lead to misdiagnosis, diagnostic confusion, or exacerbation of (sub)clinical ADHD symptoms (Chung et al., 2012; Granet et al., 2005).

Interestingly, our results depict no association of myopia and ADHD after controlling for possible confounders. This finding was somewhat counterintuitive, as other studies showed an association of myopia and ADHD (Grönlund et al., 2007; Mezer & Wygnanski-Jaffe, 2012). But they have not controlled for a broad range of other common ADHD risk factors. This could be seen as an example of how much confounding factors like children’s age and gender, socioeconomic status, young maternal age at childbirth, and low birth weight/premature birth influence the association of myopia and ADHD. To the best of our knowledge, no research has been done to differ between the association of the different forms of refractive error (myopia, hyperopia, and astigmatism) and strabismus with ADHD, although the three forms of refractive error and strabismus obviously lead to different impairments in the child’s visual perception. Myopia compared with hyperopia, astigmatism, and strabismus causes only deficits in far seeing. It could be hypothesized that deficits in near seeing, which occur in children with hyperopia, strabismus, and astigmatism become more evident in the school environment due to an increased demand for focusing also on close objects. Therefore, refractive error and strabismus influencing near seeing potentially affect the child’s academic performance and attention abilities more than refractive error, which affect far seeing, like myopia. Studies have argued that the requirement for extra accommodative effort in the uncorrected hyperopic child may result in headache, eyestrain, intermitted blur, and difficulties in focusing attention on near objects as well as subsequent reading and academic performances (Grisham & Simons, 1986; Kulp et al., 2016; Simons & Gassler, 1988; Stewart-Brown, Haslum, & Butler, 1985). Interestingly, on the contrary to hyperopia, which is associated with lower academic performance (Shankar et al., 2007; W. Williams et al., 2005), several studies pointed out a strong link between increased myopia in children with higher educational outcomes (Mutti, Mitchell, Moeschberger, Jones, & Zadnik, 2002; Saw et al., 2007). Saw and colleagues (2007) showed a positive association between myopia and school grades and concluded that school grades may reflect the amount of time spent with near work, including reading and writing on school-related work and also time spent with reading from an early age, influencing the development of myopia (Saw et al., 2007). Mutti and colleagues (2002) concluded that the association of myopia and better school performance might be besides higher levels of time spent with near work also due to genetic factors (Mutti et al., 2002). Altogether, a clear diagnostic classification is of high importance to not confound symptoms of different forms of refractive error and strabismus and ADHD. It can thus be speculated that myopia relies more on confounding risk factors like premature birth, reducing the general influence on ADHD.

Limitation

To our knowledge, this was the first study that examined the association of myopia, hyperopia, astigmatism, and strabismus with ADHD within a large, representative, cross-sectional, epidemiological German population. Results have to be interpreted with caution due to the common methodological limitations of large epidemiological studies. First, our study lacked qualitative information regarding each form and severity of refractive error and strabismus. We had no sufficiently valid information regarding treatment of the refractive error and strabismus; therefore, the study fails to make a distinction between corrected and uncorrected refractive errors and strabismus. Also, we could not include information on how the refractive error and strabismus was measured or even if a valid medical diagnosis was available. Hence, a weakness of the study is that diagnoses were confirmed by simply asking whether a certain diagnosis had been established, but not through medical examination. Above that, the retrospective self-reports may be subject to recall bias, even though it seems unlikely that parental report of refractive error and strabismus was biased. Information on any ADHD diagnosis relied on a parental report of a medical diagnosis by a doctor or psychologist. Unfortunately, it was not possible to examine the association about specific ADHD subtypes (i.e., predominately inattentive, predominantly hyperactive-impulsive) since they were not differentiated in this study. Furthermore, we have no information concerning treatment/correction of the refractive error and strabismus (i.e., glasses) or applied medication. With respect to the role of psychostimulants in this context, studies revealed mixed results: Although a recent study (Martin, Aring, Landgren, Hellström, & Andersson Grönlund, 2008) reported improved visual acuity and field function when children with ADHD were treated with psychostimulants compared with untreated children, another study (Grönlund et al., 2007) showed that medication did not improve refractive error in ADHD. Improved vision after strabismus surgery has recently been shown to be associated with reduction of ADHD symptoms (parental reports; Chung et al., 2012). Merdler and colleagues (2017) assessed the association between strabismus and mental disorders and found an association between uncorrected strabismus and ADHD and anxiety disorders. Strabismus correction was not significantly associated with mental disorders (Merdler et al., 2017).

But a clear differentiation between cooperation-depending and objectively measured refractive error and strabismus awaits further elaboration.

However, the present study includes a broad range of well-established risk factors for ADHD and refractive error and strabismus that were reported in several studies (children’s age and gender, socioeconomic status, young maternal age at childbirth, and low birth weight/premature birth) and which were considered as potential control variables (Gustafsson & Källén, 2011; Linnet et al., 2006; van Dyk et al., 2015).

Conclusion

In summary, our findings provide evidence that refractive error (like hyperopia and astigmatism) and strabismus increases the risk for an ADHD diagnosis in children and adolescents, while myopia shows no association after controlling for confounding variables. The results suggest that health care professionals of different medical fields should be aware of the association to adequately address a possible dual impairment during the diagnostic and treatment process. It can thus be emphasized that an ophthalmologic examination should be applied prior to (or in the process of) ADHD diagnosing, to rule out the possibility that visual deficits underlie symptoms resembling ADHD. In return, children with refractive error and strabismus should also be monitored for symptoms of ADHD since this group of patients might have an increased risk for the development of ADHD.

To gain more insights into the reported association of refractive error and strabismus and ADHD, further studies should consider children’s age at onset of refractive error and strabismus and age at ADHD diagnosis. Also, future research should differentiate between corrected and uncorrected refractive errors and strabismus. Moreover, future research should analyze the possible impact and interplay of ADHD treatment and treatment of refractive error and strabismus. To investigate and determine the most effective treatment strategies, the associations between forms and severity of both refractive error and strabismus and ADHD and the underlying mechanisms of this effect need further, also prospective, examination.

Footnotes

Acknowledgements

The authors would like to thank the adolescents who participated in this study, and their parents for filling in the questionnaires and answering our questions.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The German Health Interview and Examination Survey for children and adolescents (KiGGS) study was funded by the German Ministry of Health, the German Ministry of Education and Research, and the Robert Koch Institute (Berlin, Germany).

Author Biographies

Charlotte Reimelt postgraduate PhD student at the department of child and adolescent psychiatry and psychotherapy at TU Dresden. Her research focusses on influence factors on the development of attention deficit hyperactivity disorder in children and adolescents.

Nicole Wolff, PhD, is Postdoc at the department of child and ado- lescent psychiatry and psychotherapy at TU Dresden. Her research focusses on childhood disorders, like obsessive compulsive disor- ders, autism spectrum disorders and attention deficit hyperactivity disorder their underlying neural correlates and the improvement of diagnostic and therapy in clinical settings.

Heike Hölling is epidemiologist and health scientist, at the depart- ment of epidemiology and health monitoring, Robert Koch Institute, Berlin, Germany.She is head of unit mental health and her main research interest lays on child and adolescent mental health.

Sabine Mogwitz, MD, is research member at the department of child and adolescent psychiatry and psychotherapy at TU Dresden. Her research focusses on pharmacotherapy of tic disorders and Tourette syndrome as well on general and specific (i.e. in disorders like attention deficit disorder) mental health related issues of chil- dren and adolescents.

Stefan Ehrlich, MD, is the director of the Division of Psychological & Social Medicine and Developmental Neurosciences and also chief of the Eating Disorder Treatment and Research Center at the department of child and adolescent psychiatry and psychotherapy at TU Dresden. He is a professor of Psychological & Social Medicine at the Faculty of Medicine at TU Dresden.

Veit Roessner, Prof, MD, is director of the department of child and adolescent psychiatry and psychotherapy at TU Dresden. His research focusses on attention deficit hyperactivity disorder, tic disorders and Tourette syndrome, obsessive-compulsive disor- ders, and autism spectrum disorders.

References

Arnett

A. B.

MacDonald

Pennington

B. F.

(2013). Cognitive and behavioral indicators of ADHD symptoms prior to school age. Journal of Child Psychology and Psychiatry, 54, 1284-1294.

Bartuccio

Taub

M. B.

Kieser

(2008). Accommodative insufficiency: A literature and record review. Optometry & Vision Development, 39, 35-40.

Borsting

Rouse

Chu

(2005). Measuring ADHD behaviors in children with symptomatic accommodative dysfunction or convergence insufficiency: A preliminary study. Optometry—Journal of the American Optometric Association, 76, 588-592.

Botting

Powls

Cooke

R. W.

Marlow

(1997). Attention deficit hyperactivity disorders and other psychiatric outcomes in very low birthweight children at 12 years. Journal of Child Psychology and Psychiatry, 38, 931-941.

Buttross

(2000). Attention deficit-hyperactivity disorder and its deceivers. Current Problems in Pediatrics, 30, 41-50.

Castagno

V. D.

Fassa

A. G.

Carret

M. L. V.

Vilela

M. A. P.

Meucci

R. D.

(2014). Hyperopia: A meta-analysis of prevalence and a review of associated factors among school-aged children. BMC Ophthalmology, 14, 163-182.

Chung

S. A.

Chang

Y. H.

Rhiu

Lew

Lee

J. B.

(2012). Parent-reported symptoms of attention deficit hyperactivity disorder in children with intermittent exotropia before and after strabismus surgery. Yonsei Medical Journal, 53, 806-811.

Czepita

Mojsa

Ustianowska

Czepita

Lachowicz

(2006). Prevalence of refractive errors in schoolchildren ranging from 6 to 18 years of age. Annales Academiae Medicae Stetinensis, 53, 53-56.

Daley

Birchwood

(2010). ADHD and academic performance: Why does ADHD impact on academic performance and what can be done to support ADHD children in the classroom? Child: Care, Health and Development, 36, 455-464.

10.

DeCarlo

D. K.

Bowman

Monroe

Kline

McGwin

Owsley

(2014). Prevalence of attention-deficit/hyperactivity disorder among children with vision impairment. Journal of American Association for Pediatric Ophthalmology and Strabismus, 18, 10-14.

11.

DeCarlo

D. K.

Swanson

McGwin

Visscher

Owsley

(2016). ADHD and vision problems in the National Survey of Children’s Health. Optometry & Vision Science, 93, 459-465.

12.

Diamantopoulou

Rydell

A.-M.

Thorell

L. B.

Bohlin

(2007). Impact of executive functioning and symptoms of attention deficit hyperactivity disorder on children’s peer relations and school performance. Developmental Neuropsychology, 32, 521-542.

13.

Donnelly

U. M.

Stewart

N. M.

Hollinger

(2005). Prevalence and outcomes of childhood visual disorders. Ophthalmic Epidemiology, 12, 243-250.

14.

Fabian

I. D.

Kinori

Ancri

Spierer

Tsinman

Simon

G. J. B.

(2013). The possible association of attention deficit hyperactivity disorder with undiagnosed refractive errors. Journal of American Association for Pediatric Ophthalmology and Strabismus, 17, 507-511.

15.

Faraone

S. V.

Sergeant

Gillberg

Biederman

(2003). The worldwide prevalence of ADHD: Is it an American condition? World Psychiatry, 2, 104-113.

16.

Fredrick

D. R.

(2002). Myopia. British Medical Journal, 324, 1195-1199.

17.

Goktas

Sener

E. C.

Sanac

A. S.

(2012). An assessment of ocular morbidities of children born prematurely in early childhood. Journal of Pediatric Ophthalmology & Strabismus, 49, 236-241.

18.

Granet

D. B.

Gomi

C. F.

Ventura

Miller-Scholte

(2005). The relationship between convergence insufficiency and ADHD. Strabismus, 13, 163-168.

19.

Grisham

J. D.

Simons

H. D.

(1986). Refractive error and the reading process: A literature analysis. Journal of the American Optometric Association, 57, 44-55.

20.

Grizenko

Fortier

M.-E.

Zadorozny

Thakur

Schmitz

Duval

Joober

(2012). Maternal stress during pregnancy, ADHD symptomatology in children and genotype: Gene-environment interaction. Journal of the Canadian Academy of Child & Adolescent Psychiatry, 21, 9-15.

21.

Grönlund

M. A.

Aring

Landgren

Hellström

(2007). Visual function and ocular features in children and adolescents with attention deficit hyperactivity disorder, with and without treatment with stimulants. Eye, 21, 494-502.

22.

Gustafsson

Källén

(2011). Perinatal, maternal, and fetal characteristics of children diagnosed with attention-deficit–hyperactivity disorder: Results from a population-based study utilizing the Swedish Medical Birth Register. Developmental Medicine & Child Neurology, 53, 263-268.

23.

Halmøy

Klungsøyr

Skjærven

Haavik

(2012). Pre- and perinatal risk factors in adults with attention-deficit/hyperactivity disorder. Biological Psychiatry, 71, 474-481.

24.

Huss

Hölling

Kurth

B.-M.

Schlack

(2008). How often are German children and adolescents diagnosed with ADHD? Prevalence based on the judgment of health care professionals: Results of the German health and examination survey (KiGGS). European Child & Adolescent Psychiatry, 17, 52-58.

25.

Kulp

M. T.

Ciner

Maguire

Moore

Pentimonti

Pistilli

. . . Ying

G. S.

(2016). Uncorrected hyperopia and preschool early literacy: Results of the Vision in Preschoolers-Hyperopia in Preschoolers (VIP-HIP) Study. Ophthalmology, 123, 681-689.

26.

Kurth

B.-M.

Kamtsiuris

Hölling

Schlaud

Dölle

Ellert

. . . Wolf

(2008). The challenge of comprehensively mapping children’s health in a nation-wide health survey: Design of the German KiGGS-Study. BMC Public Health, 8, Article 196.

27.

Kvarnström

Jakobsson

Lennerstrand

Dahlgaard

(2006). Preventable vision loss in children: A public health concern? American Orthoptic Journal, 56, 3-6.

28.

Lanca

Serra

Prista

(2014). Strabismus, visual acuity, and uncorrected refractive error in Portuguese children aged 6 to 11 years. Strabismus, 22, 115-119.

29.

Linnet

K. M.

Wisborg

Agerbo

Secher

N. J.

Thomsen

P. H.

Henriksen

T. B.

(2006). Gestational age, birth weight, and the risk of hyperkinetic disorder. Archives of Disease in Childhood, 9, 655-660.

30.

Loe

I. M.

Feldman

H. M.

(2007). Academic and educational outcomes of children with ADHD. Journal of Pediatric Psychology, 32, 643-654.

31.

Logan

N. S.

Shah

Rudnicka

A. R.

Gilmartin

Owen

C. G.

(2011). Childhood ethnic differences in ametropia and ocular biometry: The Aston Eye Study. Ophthalmic & Physiological Optics, 31, 550-558.

32.

Martin

Aring

Landgren

Hellström

Andersson Grönlund

(2008). Visual fields in children with attention-deficit/hyperactivity disorder before and after treatment with stimulants. Acta Ophthalmologica, 86, 259-264.

33.

Merdler

Giladi

Sorkin

Shapira

Galili

Margulis

. . . Hassidim

(2017). Strabismus and mental disorders among Israeli adolescents. Journal of American Association for Pediatric Ophthalmology and Strabismus, 21, 185-189.

34.

Merrell

Tymms

P. B.

(2001). Inattention, hyperactivity and impulsiveness: Their impact on academic achievement and progress. British Journal of Educational Psychology, 71, 43-56.

35.

Mezer

Wygnanski-Jaffe

(2012). Do children and adolescents with attention deficit hyperactivity disorder have ocular abnormalities? European Journal of Ophthalmology, 22, 931-935.

36.

Mick

Biederman

Prince

Fischer

M. J.

Faraone

S. V.

(2002). Impact of low birth weight on attention-deficit hyperactivity disorder. Journal of Developmental & Behavioral Pediatrics, 23, 16-22.

37.

Mohney

B. G.

McKenzie

J. A.

Capo

J. A.

Nusz

K. J.

Mrazek

Diehl

N. N.

(2008). Mental illness in young adults who had strabismus as children. Pediatrics, 122, 1033-1038.

38.

Mutti

D. O.

Mitchell

G. L.

Moeschberger

M. L.

Jones

L. A.

Zadnik

(2002). Parental myopia, near work, school achievement, and children’s refractive error. Investigative Ophthalmology & Visual Science, 43, 3633-3640.

39.

O’Donoghue

Mcclelland

J. F.

Logan

N. S.

Rudnicka

A. R.

Owen

C. G.

Saunders

K. J.

(2010). Refractive error and visual impairment in school children in Northern Ireland. British Journal of Ophthalmology, 94, 1155-1159.

40.

O’Donoghue

Rudnicka

A. R.

McClelland

J. F.

Logan

N. S.

Owen

C. G.

Saunders

K. J.

(2011). Refractive and corneal astigmatism in White school children in Northern Ireland. Investigative Ophthalmology & Visual Science, 52, 4048-4053.

41.

Rabiner

Coie

J. D.

, & Conduct Problems Prevention Research Group. (2000). Early attention problems and children’s reading achievement: A longitudinal investigation. Journal of the American Academy of Child & Adolescent Psychiatry, 39, 859-867.

42.

Rouse

Borsting

Mitchell

G. L.

Kulp

M. T.

Scheiman

Amster

. . . Gallaway

(2009). Academic behaviors in children with convergence insufficiency with and without parent-reported ADHD. Optometry & Vision Science, 86, 1169-1177.

43.

Saw

S.-M.

Cheng

Fong

Gazzard

Tan

D. T. H.

Morgan

(2007). School grades and myopia. Ophthalmic & Physiological Optics, 27, 126-129.

44.

Schlack

Mauz

Hebebrand

Hölling

, & KiGGS Study Group. (2014). Did the prevalence of parent reported diagnoses of attention deficit hyperactivity disorder (ADHD) increase between 2003-2006 and 2009-2012 in germany?. Bundesgesundheitsblatt-Gesundheitsforschung-Gesundheitsschutz, 57(7), 820-829.

45.

Shankar

Evans

M. A.

Bobier

W. R.

(2007). Hyperopia and emergent literacy of young children: Pilot study. Optometry & Vision Science, 84, 1031-1038.

46.

Simons

H. D.

Gassler

P. A.

(1988). Vision anomalies and reading skill: A meta-analysis of the literature. Optometry & Vision Science, 65, 893-904.

47.

Sterner

Gellerstedt

Sjöström

(2006). Accommodation and the relationship to subjective symptoms with near work for young school children. Ophthalmic & Physiological Optics, 26, 148-155.

48.

Stewart-Brown

Haslum

M. N.

Butler

(1985). Educational attainment of 10-year-old children with treated and untreated visual defects. Developmental Medicine & Child Neurology, 27, 504-513.

49.

van Dyk

Springer

Kidd

Steyn

Solomons

van Toorn

. (2015). Familial-environmental risk factors in South African children with attention-deficit hyperactivity disorder (ADHD): A case-control study. Journal of Child Neurology, 30, 1327-1332.

50.

Villarreal

M. G.

Ohlsson

Abrahamsson

Sjöström

Sjöstrand

(2000). Myopisation: The refractive tendency in teenagers. Prevalence of myopia among young teenagers in Sweden. Acta Ophthalmologica Scandinavica, 78, 177-181.

51.

Williams

Northstone

Howard

Harvey

Harrad

R. A.

Sparrow

J. M.

(2008). Prevalence and risk factors for common vision problems in children: Data from the ALSPAC study. British Journal of Ophthalmology, 92, 959-964.

52.

Williams

Latif

Hannington

Watkins

(2005). Hyperopia and educational attainment in a primary school cohort. Archives of Disease in Childhood, 90, 150-153.

53.

Winkler

Stolzenberg

(1999). The social layer index in a national health survey. Gesundheitswesen, 61(2), S178-S183.