ADHD and Mental Health Status in Brazilian School-Age Children

Abstract

Objective: To assess the prevalence of ADHD, mental health status, and risk factors in a sample of Brazilian children. Method: Target sample consisted of all children from 5 to 13 years registered in the public elementary school. Children with ADHD were compared with those without ADHD for sociodemographic, risk factors, and Child Behavior Checklist (CBCL) symptom dimensions. Multivariate models estimated determinants of ADHD diagnosis. Results: Of the target sample, consents and complete information were obtained from 1,830 children (91.8%). The prevalence rate of ADHD was 5.1% (95% confidence interval [CI] = [4.2, 6.2]). In contrast to controls, children with ADHD presented higher levels of symptoms in the CBCL dimensions. In multivariate analyses, the diagnosis of ADHD was significantly influenced by maternal educational status (p = .019), income class (p = .012), and prenatal exposure to tobacco (p = .032). Conclusion: Prevalence and demographic features of ADHD in Brazil are similar to what has been reported worldwide.

Keywords

ADHD mental health epidemiology risk factor children

Introduction

ADHD is a common disorder among children, with symptoms often persisting through adolescence and adulthood (Biederman & Faraone, 2005; Polanczyk & Rohde, 2007). The disorder is disabling, affecting quality of life and performance at school (Biederman & Faraone, 2005; Goldman, Genel, Bezman, & Slanetz, 1998). Prevalence estimates are necessary to match educational and medical resources to the population needs (Costello, Egger, & Angold, 2005). Despite the large number of epidemiology studies focusing on ADHD, prevalence estimates range from as low as 1% to as high as nearly 20% (Faraone, Sergeant, Gillberg, & Biederman, 2003; Offord, 1985; Scahill & Schwab-Stone, 2000; Szatmari, 1992). This significant variability raises questions about whether social or cultural factors may influence the occurrence of the disorder (Anderson, 1996; Bird, 1996; Timimi & Taylor, 2004). In a meta-regression analysis (Polanczyk, Lima, Horta, Biederman, & Rohde, 2007), it was found that methodological characteristics, mainly the requirement of functional impairment as a criterion for the diagnosis, as well as source of information, and diagnostic criteria, were significantly associated with heterogeneity of results (Polanczyk et al., 2007).

To attenuate the heterogeneity between studies, investigations on specific geographic areas or subpopulations are necessary (Polanczyk & Jensen, 2008; Polanczyk et al., 2007). It has also been suggested that studies collected information on clinical impairment and separately interviewed parents and teachers, mirroring the clinical diagnosis process and keeping constant the set of criteria associated with variability of estimates (Polanczyk & Jensen, 2008).

Three main strategies are available to aggregate information from parents and teachers: the so-called “and rule” (i.e., a symptom is considered present only if it is endorsed by two informants), the “or rule” (i.e., a symptom is considered present if endorsed by one of two informants), and the best estimate procedure (the clinical examination, in which an experienced clinician reviews all available data, reconciles any discrepancies, and makes a diagnostic decision based on the merging of reports or the best estimate source; Polanczyk & Jensen, 2008).

Although ADHD has been considerably studied in Brazil, important discrepancy in methods exist, yielding results that range from 0.9% (Goodman et al., 2005) to 26.8% (Vasconcelos et al., 2003). Studies using the best estimate procedure and requiring functional impairment for the diagnosis found prevalence rates from 0.9% to 1.8% (Fleitlich-Bilyk & Goodman, 2004; Goodman et al., 2005). Adopting the “and rule,” prevalence was considerably higher (Pastura, Mattos, & Araujo, 2007; Rohde et al., 1999). Because findings are so discrepant, population-based studies using strict methodological approaches need to be conducted (Polanczyk & Jensen, 2008). Accordingly, herein we aimed to estimate the prevalence of ADHD in children registered in the elementary school of a low-income city in the southeast region of Brazil, using parents and teachers as informants and requiring functional impairment for the diagnosis. We present the prevalence rates by demographics and age, and investigate the clinical characteristics of individuals who satisfied ADHD diagnostic criteria. We also assessed treatment rate for those with ADHD. We hypothesized that the prevalence estimate detected in this sample would be similar to the worldwide pooled prevalence (Polanczyk et al., 2007), that demographic and clinical characteristics of individuals with ADHD would be consistent with the existing literature, and that treatment rate would be low (Polanczyk & Jensen, 2008).

Method

Setting and Sample

This study was conducted in the context of a large ongoing populational study aiming to investigate the mental health of children and adolescents in Brazil (Attention-Brazil Project; Arruda, 2010). The current study was conducted in the city of Santa Cruz das Palmeiras, located in the state of São Paulo, southeast region of Brazil. According to the demographic census performed in 2008, Santa Cruz das Palmeiras covers an area with 32,862 inhabitants. Among these people, 30,387 (92.4%) live in the urban area. The Human Development Index is 0,796 and life expectancy is 73.71 years, and fecundity rate is 2.13, numbers that are similar to the Brazilian rates, according to the Brazilian Institute of Geography and Statistics (IBGE). Our sample frame consisted of all children from 5 to 13 years registered in any of the five public elementary schools of the city (N = 2,173).

Procedures

In February of 2009, during the planning for the 2009 school year, all teachers of the public school system were trained by one of the authors (MAA) in a 4-hr session. They were given information about the study and educated on how to answer the questionnaire and how to guide and supervise the parents in this task. Engaging the teachers was considered to be an essential step, as the questionnaire was long and relatively time-consuming (see below), as well as to increase participation. Parents or children’s guardians were then invited to attend a meeting at school (during the 1st week of the school year) and filled the questionnaire, under the supervision of the teachers which, in turn, were supervised by one of the authors of this study (MAA). Meanwhile, children remained with monitors, practicing physical activities. Three months later, the teachers were asked to complete the rating scale for each of their students.

A written informed consent was obtained from either the parents or the legal guardians. The study was approved by the Human Research Committee of the São José do Rio Preto School of Medicine, a State University of São Paulo, Brazil.

Measures

Parents completed the study questionnaire, which assesses sociodemographic characteristics, risk factors, current and past health and medical treatment history of the child, parental information, ADHD symptoms, and emotional and behavioral symptoms.

ADHD symptoms were assessed by the Swanson, Nolan, and Pelham-IV Rating Scale (MTA-SNAP-IV scale), which was completed by parents and teachers (Swanson et al., 2001). The MTA-SNAP-IV scale consists of 18 items each one corresponding to the 18 ADHD symptoms according to Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) criteria. The Portuguese version was reached after a systematic process of translation, back-translation, evaluation of semantic equivalence and psychometric properties, debriefing, and definition of a final version (Mattos, Serra-Pinheiro, Rohde, & Pinto, 2006). A symptom was considered positive if rated “quite a bit” or “very much.” ADHD was considered present if six or more inattentive and/or six or more hyperactivity–impulsivity symptoms were reported by the caregiver (Criteria A) and at least two symptoms were endorsed by the teacher, indicating pervasiveness across home and school (Criteria C). The reason we have prioritized the parent’s report was the low interrater reliability estimates between parent and teacher reports of ADHD symptoms (Zuddas et al., 2006), and the relatively short period of observation and familiarity of the teacher toward the child in the present study (3 months). The symptoms must be present before the age of 7 years with a minimal duration of symptoms of 6 months, according to maternal report (Criteria B), causing a clinically significant impairment in familial, social, and/or academic functioning (Criteria D). To avoid information bias, parents were asked to fulfill the MTA-SNAP-IV scale based on child behavior without the effect of ADHD medications. Accordingly, if children were not using ADHD medications, current symptoms were assessed. In those using ADHD medications, prior (to medication) symptoms were assessed.

Emotional and behavioral symptoms were assessed by the Child Behavior Checklist for children aged 4 to 18 years (CBCL 4-18; Achenbach & Edelbrock, 1983), completed by the parents. The CBCL is a widely used dimensional measure of childhood psychopathology, translated to Portuguese and validated in Brazil (Bordin, Mari, & Caieiro, 1995). The first section includes 20 items related to the child’s social competency in three distinct contexts: activities (i.e., child’s participation in sports, hobbies, games, jobs, and chores), social relations (i.e., interactions in family, with friends, groups, organization, clubs, and teams), and school performance. The second section consists of 112 items on behavior or emotional symptoms during the past 6 months as rated on a 3-point scale (“not true,” “somewhat or sometimes true,” and “very true or often true”) resulting individual scores in 10 scales: “withdrawal,” “somatic complaints,” “anxiousness/depression,” “social,” “thought,” “attention,” “delinquent,” “aggressive behavior,” “internalizing,” and “externalizing” problems. The sum of scores of all scales defines the “total problem score.” Symptoms are pooled in dimensions according to the standard profiles. Data are presented here as a raw score. Functional impairment was defined according to the score in the social competency scale of all children who satisfied the minimum number of ADHD symptoms (Criteria A).

To assess previous diagnosis and psychopharmacological treatment, parents responded to three multiple-choice questions in the questionnaire concerning previous medical diagnosis of ADHD and previous or current use of ADHD medications available in Brazil. Accordingly, current and past medications were used, but diagnoses focused on the most recent (current or past) untreated period.

Data Analysis

Children with ADHD were compared with those without ADHD for sociodemographic (age, gender, race, maternal and parental education status, parent’s marital status, number of people in the household), risk (intrauterine exposure to alcohol, tobacco, and other drugs), and CBCL symptom-dimensions characteristics with Student’s t test and analysis of variance (ANOVA) for continuous variables and chi-square for categorical variables. The same comparisons were performed between the different subtypes of ADHD. As a secondary analysis, children with ADHD with and without history of treatment were also compared with regard to sociodemographic and CBCL symptom-dimensions characteristics.

Multivariate analyses

We developed nested multivariate models estimating ADHD diagnosis (dependent variable) as a function of age; gender; race; parent’s marital status; maternal and paternal educational status; income class; prenatal exposure to tobacco, alcohol, and other drugs; number of people living in the household; prematurity; and preeclampsia (independent variables).

The level of significance adopted was 5%. Statistical analysis was performed with the aid of the SPSS 15.0 for Windows (SPSS Inc., Chicago, IL).

Results

Overview

Our target sample consisted of children from 5 to 13 years, registered in any of the five public elementary schools of the city (N = 2,173). Of the target sample, consent was obtained from 1,994 (91.8%), and analyzable data (complete sociodemographic and ADHD information) from 1,830 (84.2% of target sample and 91.8% of respondents). In the vast majority of cases, the questionnaire was completed by the mother (82.2%); it was responded by the father in 5.2% and by other caregivers (e.g., grandparents living with the child) in 12.6%. Overall, 51.5% of the children were boys, 52.8% were from the middle class (household income between US$641 and US$2,763).

Prevalence, Correlates, and Subtypes

A total of 94 children fulfilled criteria for ADHD, accounting for a prevalence rate of 5.1% (95% confidence interval [CI] = [4.2, 6.2]) in the sample. Table 1 contrasts children with and without ADHD in regard of sociodemographic and risk characteristics. Relative to children without ADHD, children with ADHD were significantly more likely to be older (p = .005), male (p = .004), and from low-income families (p < .001). They were also more likely to have the household head with lower educational status (p = .008) and separated or divorced parents (p = .037). Mothers of children with ADHD were more likely to have smoked (p = .012) or used alcohol (p = .016) during pregnancy relative to those children without ADHD.

Table 1.

Comparison of Sociodemographic Characteristics Between Children With ADHD Versus Non-ADHD (n =1,830).

Sociodemographic characteristic	Non-ADHD (n = 1,736)	ADHD (n = 94)	Statistic, p value
Age, M (SD)	7.89 (1.6)	8.37 (1.6)	t = −2.825, p = .005
Sex, n (%)
Male	881 (50.7)	62 (66.0)	χ² = 8.258, p = .004
Race, n (%)
White	1,012 (60.6)	53 (60.2)	χ² = 0.004, p = .99
Non-White	659 (39.4)	35 (39.8)
Socioeconomic class, n (%)
A/B	318 (18.3)	9 (9.6)	χ² = 15.693, p < .001
C	925 (53.3)	41 (43.6)
D/E	493 (28.4)	44 (46.8)
Household head educational status, n (%)
Illiterate	131 (7.9)	14 (15.6)	χ² = 11.842, p = .008
0-5 years of study	826 (49.7)	51 (56.7)
6-10 years of study	654 (39.4)	22 (24.4)
>10 years of study	50 (3.0)	3 (3.3)
Parents’ marital status, n (%)
Married/live together	1,216 (73.1)	55 (62.5)	χ² = 4.738, p = .037
Separated/divorced	447 (26.9)	33 (37.5)
Number of people living in the household, M (SD)	4.6 (1.748)	4.82 (1.684)	t = −1.009, p = .313
Intrauterine exposure to alcohol, n (%)	157 (9.9)	16 (18.8)	χ² = 6.815, p = .016
Intrauterine exposure to tobacco, n (%)	458 (28.3)	37 (41.1)	χ² = 6.813, p = .012
Intrauterine exposure to other drugs, n (%)	26 (1.7)	2 (2.3)	χ² = .210, p = .655

Note: Socioeconomic classes—A/B: household income higher than US$2,763; C: between US$641 and US$2,763; D/E: below US$641.

Of children with ADHD, 41 (43.6%) presented the inattentive subtype, 30 (31.9%) the combined subtype, and 23 (24.5%) the hyperactive-impulsive subtype. Children with different subtypes did not significantly differ with regard to sociodemographic characteristics (data available on request), except for age. Children with the hyperactive-impulsive subtype were significantly younger than children with the inattentive subtype (M = 7.70, SD = 1.55 vs. M = 8.73, SD = 1.45; p = .03).

In multivariate analyses, the diagnosis of ADHD was most significantly influenced by maternal educational status (6-10 years of study vs. illiterate, p = .019), income class (household income below US$641 [D/E] vs. household income higher than US$2,763 [A/B], p = .012), and prenatal exposure to tobacco (p = .032). Other variables did not significantly contribute to the model.

ADHD and Emotional and Behavioral Symptoms

Compared with children without ADHD, children with ADHD had significantly higher scores of all but the withdrawn dimension of the CBCL. ADHD subtypes varied regarding their scores on three (anxiety-depressive, attention, and aggressive) out of eight dimensions of CBCL. Figure 1 presents the CBCL scores in each dimension for children with ADHD overall and stratified by subtype in comparison with those without ADHD.

Figure 1.

Comparison of children with ADHD diagnosis versus non-ADHD and between ADHD subtypes in regard to CBCL symptom dimensions.

ADHD Treatment

Among the 94 children with ADHD, 75 provided information on their treatment history, and 14 of them had ever been treated for ADHD (either methylphenidate or tricyclic antidepressants). When comparing children with ADHD treated with medication to those without history of medication treatment, no differences were seen for age (p = .144), race (p = .117), and sex (p = .99). Relative to untreated ADHD children, children ever treated were more likely to have significantly higher SNAP-IV total score (M = 37.3, SD = 9.8; M = 31.7, SD = 7.6; p = .024) according to the parents, but not according to teachers (p = .202). Also, mothers of children with the history of treatment presented a higher education level, with a marginal significance level (p = .052; full data available on request).

Discussion

We estimated the ADHD prevalence in a representative sample of children 5 to 13 years of age registered in the public educational system of a low-income community from the southeast region of Brazil. We used parents and teachers as informants and required functional impairment for the diagnosis. Prevalence, demographic features, and clinical characteristics were in line with the literature. Of notice, children with ADHD had significantly higher scores on seven (out of eight) dimensions of CBCL. Only 14 out of 75 children with ADHD and available data had a lifetime history of medication treatment for ADHD. As expected, positive history of treatment was associated with a higher level of symptoms and higher household head education.

This study aggregated information from parents and teachers requiring clinical impairment for the diagnosis. Results in Brazil, as elsewhere, reported very discrepant rates of ADHD prevalence (Fleitlich-Bilyk & Goodman, 2004; Goodman et al., 2005; Rohde et al., 1999), probably explained by their important methodological differences, including different samples, different diagnostic interviews, different diagnostic rules, and different methods to define the DSM-IV requirement of clinically significant functional impairment. Our study tried to address the discrepancy by enrolling all children registered in the school system, by using the “and” rule, and by using a validated and literally not ethically influenced tool (social scale score of the CBCL) to measure global impairment. As mentioned in the introduction, methodological characteristics have a significant impact on the heterogeneity of ADHD prevalence studies, and this might be the case for these studies in particular (Polanczyk et al., 2007).

Children with ADHD were more likely to have intrauterine exposure to tobacco in adjusted analyses. The association between prenatal exposure to tobacco and ADHD has been consistently documented in cross-sectional (Froehlich et al., 2009) and longitudinal studies (D’Onofrio et al., 2008; Galera et al., 2011), and it has also been suggested by neuroimaging (Rivkin et al., 2008) and genotypic variability (Becker, El-Faddagh, Schmidt, Esser, & Laucht, 2008). The developmental consequences of prenatal tobacco exposure seem to be influenced by genetic predisposition, neurobehavioral disinhibition, and gender (Cornelius & Day, 2009).

Other factors associated with ADHD included low educational status of the household head and divorced parents. As our study did not assess causality, longitudinal studies are necessary to disentangle the role of social, cultural, economical, and biological influences (Galera et al., 2011).

Children with ADHD were also more likely to display emotional and behavioral symptoms relative to control, and this has been vastly documented by studies with different methods, enrolling culturally diverse samples (Roessner, Becker, Rothenberger, Rohde, & Banaschewski, 2007).

With regard to treatment rates, the prevalence of lifetime medication use of 18.6% is somewhat higher than the estimates of less than 5% found in other samples from Brazil, Puerto Rico, and Venezuela (Polanczyk et al., 2008). This might be explained because we considered lifetime history of treatment and did not restrict it to stimulants.

This study must be understood in the context of its limitations. First, we used respondent-based rating scales. An interviewer-based diagnostic interview would be preferable, and we trained teachers on the scales and supervised parents during the ratings to minimize this limitation. Second, other conditions, such as autism spectrum disorder, that may explain inattentive and/or hyperactive-impulsive symptoms were not assessed. However, studies that employed this strategy found similar rates (Rohde et al., 1999), probably because these cases are scarce in the population and do not significantly impact the results. Third, the sample we ascertained is representative of a single city, and findings cannot be necessarily generalized to the whole country. Fourth, assessing the functional impairment according to the CBCL social scale score, did not allow us to differentiate the impairment caused by symptoms of ADHD or other possible comorbid disorder.

This study assessed 84.2% of all children ages 5 to 13 years registered in the public school system of a poor community located in the southeast region of Brazil and found an ADHD prevalence of 5.1% (95% CI = [4.2, 6.2]). We used the most stringent diagnostic criteria and detected a similar rate in studies conducted in different regions of the country and a worldwide pooled prevalence. It adds to the existing literature by demonstrating consistent cross-cultural estimates and construct validity and by contributing data in understudied populations. Further studies should be conducted in a way that a more homogeneous worldwide pooled prevalence is computed in the future.

Footnotes

Declaration of Conflicting Interests

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

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Marco A. Arruda, MD, PhD, is a Child and Adolescent Neurologist, Director of the Glia Institute of Neuroscience and the coordinator of the Attention Brazil Project, a large nationwide epidemiologic survey. He researches since 1990 in the following areas: headache in children and adolescents, epidemiology of mental health and ADHD in children and adolescents.

Cícero Nardini Querido is a graduate medical student in the University of São Paulo Medical School and in the Scientific Initiation Program of the National Institute of Developmental Psychiatry for Children and Adolescents, São Paulo, Brazil.

Marcelo E. Bigal, MD, PhD, is the Head of the Merck Investigator Studies Program, Scientific Engagements and Education. His former position was as Associated Professor of Neurology in the Albert Einstein College of Medicine. Over 200 publications, 3 books, and 32 book chapters on this period of time on migraine, chronic daily headaches, and Alzheimer’s Disease.

Guilherme V. Polanczyk, MD, PhD, is a Child and Adolescent Psychiatrist, Associated Professor of the University of São Paulo Medical School and Executive Director of the National Institute of Developmental Psychiatry for Children and Adolescents (São Paulo, Brazil). He integrates the Mental Disorders Expert Group of the Global Burden of Diseases Study and is Associated Editor of the Revista Brasileira de Psiquiatria and Junior Editor of the European Child & Adolescent Psychiatry.

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