578272
research-article2015
JADXXX10.1177/1087054715578272Journal of Attention DisordersRacicka et al.
Article
Prevalence of Overweight and Obesity in Children and Adolescents With ADHD: The Significance of Comorbidities and Pharmacotherapy
Journal of Attention Disorders 1–14 © 2015 SAGE Publications Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1087054715578272 jad.sagepub.com
Ewa Racicka1, Tomasz Hanć2, Katarzyna Giertuga3, Anita Bryńska1, and Tomasz Wolańczyk1
Abstract Objective: Assessment of the prevalence of overweight and obesity in children and adolescents with ADHD with emphasis on pharmacological treatment and comorbid disorders. Method: We analyzed 408 medical records of patients with ADHD aged 7 to 18. Results: The prevalence of overweight (14.71% vs. 12.83%, χ2 = 3,586.43, p < .001) and obesity (6.37% vs. 3.45%, χ2 = 3,588.19, p < .001) was significantly higher in children with ADHD compared with the population. There was significantly higher incidence of obesity in patients with comorbid diagnosis of adjustment disorder (22.22% vs. 4.42%, χ2 = 5.66, p = .02) and mental retardation (19.05% vs. 4.42%, χ2 = 7.63, p = .005). Pharmacological treatment was associated with a higher incidence of obesity (8.37% vs. 2.76%, χ2 = 4.92, p = .03). Conclusion: Standardized body mass index (BMI), prevalence of overweight, and obesity was higher in patients with ADHD compared with the population. Higher incidence of obesity was shown in patients with analyzed comorbidities. (J. of Att. Dis. XXXX; XX(X) XX-XX) Keywords ADHD, BMI, overweight, obesity, body weight, body height
Introduction Association between ADHD and overweight/obesity has been a research topic over the last three decades. The results of previous studies suggest that ADHD is a risk factor of excess body weight (Cortese et al., 2008; Cortese & Morcillo, 2010; Cortese, Olzagasti, et al., 2013; Cortese, Faraone, Bernardi, Wang, & Blanco, 2013; Fliers et al., 2013; Hanć, Cieslik, Wolańczyk, & Gajdzik, 2012; Racicka, 2013). Higher body weight or body mass index (BMI) occurs in both children and adolescents with ADHD (Anderson, Cohen, Naumova, & Must, 2006; Byrd, Curtin, & Anderson, 2013; Chen, Kim, Houtrow, & Newacheck, 2010; Curtin, Bandini, Perrin, Tybor, & Must, 2005; Erhart et al., 2012; Faraone, Biederman, Monuteaux, & Spencer, 2005; Güngör, Celiloğlu, Raif, Özcan, & Selimoğlu, 2013; Hanć & Cieślik, 2008; Hanć et al., 2012; Holtkamp et al., 2004; Hubel, Jass, Marcus, & Laessle, 2006; Lam & Yang, 2007; Ptacek, Kuzelova, Paclt, Zukov, & Fischer, 2009; Schwartz et al., 2014; Spencer et al., 1996; Spencer et al., 2006; Swanson et al., 2006; Waring & Lapane, 2008; Yang, Mao, Zhang, Li, & Zhao, 2013) and adults with this diagnosis (Biederman et al., 2003; Cortese et al., 2013; Fuemmeler, Østbye, Yang, McClernon, & Kollins, 2011; Pagoto et al.,
2009). This has been confirmed by epidemiological studies (Anderson et al., 2006; Byrd et al., 2013; Chen et al., 2010; Erhart et al., 2012; Fuemmeler et al., 2011; Güngör et al., 2013; Lam & Yang, 2007; Waring & Lapane, 2008) as well as studies performed in clinical groups (Biederman et al., 2003; Curtin et al., 2005; Faraone et al., 2005; Hanć & Cieślik, 2008; Holtkamp et al., 2004; Spencer et al., 1996; Spencer et al., 2006; Swanson et al., 2006; Ptacek et al., 2009). Studies also indicate increased incidence of ADHD symptoms in people with obesity (Agranat-Meged et al., 2005; Altfas, 2002; Erermis et al., 2004; Fleming, Levy, & Levitan, 2005). At present, factors underlying the relationship between ADHD and obesity are investigated. Common 1
Department of Child Psychiatry, Medical University of Warsaw, Poland Department of Human Biological Development, Faculty of Biology, Institute of Anthropology, Adam Mickiewicz University in Poznan, Poland 3 Laboratory of Neuroplasticity, Nencki Institute of Experimental Biology, Warsaw, Poland 2
Corresponding Author: Ewa Racicka, Department of Child Psychiatry, Medical University of Warsaw, Marszalkowska 24, Warsaw, 00-576, Poland. Email: [email protected]
2
Journal of Attention Disorders
genes (Albayrak et al., 2013; Choudhry et al., 2013) and family factors such as parental socioeconomic status (van Egmond-Fröhlich, Widhalm, & de Zwaan, 2012) and birth weight (Hanć et al., 2015) are evaluated. The results of the available studies are not conclusive (Dubnov-Raz, Perry, & Berger, 2011; Mustillo et al., 2003). Different variables related to body weight should be considered regarding the association between ADHD and overweight or obesity. In our opinion, special attention should be paid to pharmacological treatment and comorbidities. Previous research has shown that pharmacologically untreated children have higher body weight compared with those in treatment (Schwartz et al., 2014; Waring & Lapane, 2008), whereas pharmacological treatment causes a decrease in body weight (Hanć & Cieślik, 2008; A. Poulton, 2005; A. Poulton et al., 2012; A. Poulton & Cowell, 2003; A. S. Poulton et al., 2013; Swanson et al., 2006). Depression, adjustment disorders, and other psychiatric disorders that often co-occur with ADHD (Biederman, Newcorn, & Sprich, 1991; Wilens et al., 2002) may also affect body weight (Biederman et al., 2003; Lin et al., 2013; Reeves, Postolache, & Snitker, 2008). For example, investigators searching for the causes of obesity in patients from obesity clinic indicate the more frequent prevalence of psychiatric disorders including depression and adjustment disorders in patients with obesity (Kalarchian et al., 2007; Scott, McGee, Wells, & Browne, 2008; Simon et al., 2006; Stunkard, Faith, & Allison, 2003; Wilens et al., 2002; Mühlhans, Horbach, & de Zwaan, 2009). Small number of patients in clinical trials (AgranatMeged et al., 2005; Erermis et al., 2004; Hubel et al., 2006), the lack of assessment of the pharmacological treatment impact (Chen et al., 2010; Spencer et al., 1996) and comorbid disorders (Altfas, 2002; Anderson et al., 2006; Chen et al., 2010; Curtin et al., 2005; Fleming et al., 2005; Lam & Yang, 2007; Spencer et al., 1996), the absence of a formal diagnosis of ADHD (Anderson et al., 2006; Chen et al., 2010; Erermis et al., 2004; Hubel et al., 2006; Mustillo et al., 2003; Waring & Lapane, 2008), as well as the lack of a control group (Agranat-Meged et al., 2005; Altfas, 2002; Fleming et al., 2005) and data on socioeconomic status (Holtkamp et al., 2004) are the limitations of the most conducted studies so far. The aim of the study was to assess the prevalence of overweight and obesity in children and adolescents with ADHD with particular emphasis on the impact of pharmacological treatment and comorbid disorders. Based on previous research, we hypothesized the following: Hypothesis 1: The prevalence of weight problems will be greater in children and adolescents with ADHD compared with the general population.
Hypothesis 2: Concomitant disorders and treatment have an impact on the prevalence of overweight and obesity in this group of patients.
Method Ethical and Financial Statements The study has been approved by the Ethics Committee of the Warsaw Medical University, and has therefore been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.
Study Group Seven hundred medical records of patients aged 7 to 18, admitted to outpatient psychiatry clinic at Public Pediatric Teaching Hospital in Warsaw from 1999 to 2012 due to ADHD symptoms, have been analyzed. We included only charts with complete information on height, weight, age, sex, comorbidities, and pharmacological treatment. This yielded a final total of 408 charts. Then, we chose the first visit within 2.5 years from initial visit, which contained all the necessary information (min. 11 days, max. 799 days) for analysis. Children were seen at various intervals for followup visits. The diagnosis was performed according to diagnostic criteria of Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR; American Psychiatric Association, 2000) for one of the three ADHD types: predominantly inattentive or impulsive/hyperactive and combined type. The diagnosis made by child-trained and experienced psychiatrists working in outpatient clinic included an interview with patient and his family, Diagnostic Structured Interview for ADHD and Hiperkinetic Disorder according to International Classification of Diseases (ICD)10 and DSM-IV TR (Wolańczyk & Kołakowski, 2005), the Behavioral Disorders Supplement of Diagnostic Intervew Kiddie-SADS–Present and Lifetime Version (KiddieSADS-PL), and observation of patient behavior. Parents were asked to provide background records and school reports as well as to complete behavior rating scales. The child’s teachers were also asked to complete behavior rating scales. For the comorbidity diagnosis, other supplements of KiddieSADS were administered by the same child psychiatrist; diagnosis was based on the diagnostic criteria for ICD-10 (World Health Organization, 1994). The diagnosis was performed during at least three appointments during which children also underwent physical, neurological, and developmental examination. In valid cases, laboratory tests were done (such as morphology, Thyroid Stimulating Hormone [TSH]) and psychological diagnostic such as Wechsler Intelligence Scale–Revised (WISC-R) and testing for learning disabilities
3
Racicka et al. were performed by trained psychologists. Measurements were made by psychiatrist or trained nurse. Exclusion criteria included diabetes, dysfunction of the thyroid gland, and others somatic disorders that could affect the body weight of patients, as well as pervasive developmental disorder due to specific dietary habits in this group. Data on age, sex, height, weight, medical treatment, and comorbid disorders were collected from medical records. Information concerning patients was collected from visits records, which included all the above-mentioned data. This means that information relating to medication therapy and comorbid disorders applied to individual visits. In case of patients who were on medication, we took the data on the treatment onset. The course of comorbid disorders was not included. Based on the data of onset of pharmacological treatment and the data of assessment, the duration of treatment was calculated. Then we estimated cumulated dose of drugs using the following equation: mg/day × days of treatment up to the moment of assessment. Cumulated dose was calculated based on the assumption that the drugs were received 7 days/week and holiday breaks were taken into account.
Anthropometric Measurements Measurements of body height were carried out according to the standard technique (Chumlea & Guo, 2006; de Onis, Onyango, Van den Broeck, Chumlea, & Martorell, 2004) by trained medical staff. Body weight was measured with a medical scale (Radwag PUE c/31) with an accuracy of ±100 g. Height was measured using a Harpenden anthropometric instrument with an accuracy of 0.1 cm. The examined children were weighted in their underwear. The measurements were performed between 9 a.m and 4 p.m. BMI was calculated on the basis of body weight and height. Height, weight, and BMI were later standardized according to sex and age using the growth references for Polish population (Kułaga et al., 2010). These growth charts give standard measurements at an interval of 1 year; therefore, for calculating the z scores, we assumed a constant rate of change of the mean and standard deviation between 1 year and the next. Overweight and obesity were assessed according to criteria of Obesity Task Force (IOTF; Cole, Bellizzi, Flegal, & Dietz, 2000; Cole, Flegal, Nicholls, & Jackson, 2007). IOTF cut-off points corresponded approximately to 90th percentile of BMI for overweight and 98th percentile for obesity (Cole et al., 2007). The calculated frequencies were then compared with the prevalence of overweight and obesity in the Polish population in the same age group (Kułaga et al., 2011). This reference provided data on prevalence of overweight and obesity separately in boys and girls in 1 year age categories for 7 to 18 years. Using these data and the numbers of boys and girls in following years of age, we
calculated the number of children who were overweight and obese. Then the numbers from 1 year age classes were summed up to estimate overweight and obesity rates (%) in the whole sample of boys and girls, without division on age. One sample t test was used to assess the differences in standardized height, weight, and BMI between patients with ADHD and population (z scores = 0). Chi-square test was used to assess differences in prevalence of overweight and obesity between children with ADHD and population and for assessment of association between chosen comorbidities and pharmacological treatment and prevalence of overweight and obesity in ADHD patients. Differences at the level of p < .05 were considered as statistically significant. The forward stepwise regression method was used to build the multifactorial models of z scores for children with ADHD for height, weight, and BMI determination. Comorbid disorders and cumulated dose of medications as well age and sex were tested as independent variables. The correctness of models fitting into the empirical data was estimated using the variance analysis. The criterion of model accuracy was the statistical significance of F value on the level of p < .05. Stepwise logistic regression with Quasi-Newton estimation method was used to assess probability of overweight or obesity based on adjusted analysis of comorbid disorders and quartiles of cumulated dose of medications. Separate models where tested for overweight, obesity, and the sum of overweight and obesity. All statistical analyses were conducted with Statistica 10 software.
Results In this study, body weight of 408 patients with ADHD aged 7 to 18 years (M = 11.24 years, SD = 2.54 years, min = 6.89, max = 18.66) was evaluated. Boys constituted 85.78% of the group (350 of 408 patients). In 182 (44.61%) patients, comorbid conditions were diagnosed. The most common were oppositional defiant disorder (ODD) and conduct disorder (CD; n = 83, 20.34%). Mild mental retardation was found in 21 (5.15%) and adjustment disorders in 9 (2.12%) patients. Most of the respondents at the time of study received medication (n = 263, 64.46%). The most frequently used were metylphenidate (MPH) osmotic release oral system (OROS; 24% of the sample) and short-acting stimulants (14.95% of the sample). Mean doses, duration of treatment, and cumulated dose are presented in Table 1. Details of the prevalence of overweight and obesity in the sample are shown in Tables 2 and 3 and Figure 1. Patients with ADHD had significantly lower height (t = −3.50, p < .001) and higher standardized BMI compared with the population (t = 2.25, p = .02). When controlling for sex, significant difference was only found for height (t = −3.38, p < .001; see Table 4).
4
Journal of Attention Disorders
Table 1. Characteristics of Treatment. Medication
n
% of the sample
OROS Dose (mg/day) Duration (days) Cumulated dose MPH IR Dose (mg/day) Duration Cumulated dose Atomoxetinum Dose (mg/day) Duration Cumulated dose Risperidone Dose (mg/day) Duration Cumulated dose Imipraminum Dose (mg/day) Duration Cumulated dose
98
24
61
M
SD
28.54 159.04 5,659.97
14.83 168.42 9,044.44
22.74 149.97 3,603.42
12.98 124.58 4,149.41
41.67 136.12 5,910.588
12.24 120.23 5,964.65
Minimum-maximum 18-81 11-799 198-64,719 10-60 27-589 420-18,440 25-60 35-504 2,100-22,500 0.25-2 49-504 12.25-924 10-101 35-425 650-42,500
14.95
18
4.41
19
4.66
34
1.19 187.74 270.49
0.54 158.75 288.53
46.96 120.24 6,604.44
24.39 73.90 7,912.51
9.33
Note. MPH IR = metylphenidate immediate release.
Table 2. Prevalence of Overweight and Obesity in ADHD Patients According to IOTF Criteria. Boys (n = 350)
Girls (n = 58)
Total (N = 408)
n
%
n
%
n
%
Overweight Obesity Overweight/obesity (total)
52 23 75
14.86 6.57 21.43
8 3 11
13.79 5.17 18.97
60 26 86
14.71 6.37 21.08
Note. IOTF = International Obesity Task Force.
Both the prevalence of overweight (14.71% vs. 12.83%, χ2 = 3,586.43, p < .001) and obesity (6.37% vs. 3.45%, χ2 = 3,588.19, p < .001) was significantly higher in children with ADHD compared with the population (see Table 5). When sex was controlled, statistically significant difference was demonstrated only in the group of boys. The incidence of obesity in boys with ADHD was higher by 2.27% compared with the population (χ2 = 1.74, p = .04). Unadjusted analysis showed significantly higher incidence of obesity in patients with comorbid diagnosis of adjustment disorder (22.22% vs. 4.42%, χ2 = 5.66, p = .02), mild mental retardation (19.05% vs. 4.42%, χ2 = 7.63, p = .005), and pharmacological treatment (8.37% vs. 2.76%, χ2 = 4.92, p = .03; see Tables 6 and 7). Detailed analysis showed that the higher incidence of obesity in this group was associated only with the use of OROS MPH (12.24% vs. 2.78%, χ2 = 8.46, p = .004).
Adjusted analysis using the forward stepwise regression method has shown significant positive relation of MPH OROS cumulated dose and z scores for height (β = 0.11, t = 2.23, p = .03) and weight (β = 0.13, t = 2.62, p = .009; see Table 8). Adjustment disorders were positively related to z scores for weight (β = 0.12, t = 2.35, p = .02) and BMI (β = 0.10, t = 2.07, p = .04). Mental retardation was linked with increase in z scores for BMI (β = 0.11, t = 2.24, p = .03) Logistic regression was used to assess the relation between potential risk factors and the rate of overweight and obesity. Adjusted analysis has shown only two variables increasing the risk of obesity and overweight/obesity: mental retardation (for obesity: OR = 0.21, 95% CI = [0.06, 0.73], p = .01; for overweight/obesity: OR = 0.36, 95% CI = [0.14, 0.94], p = .04) and MPH OROS treatment (for obesity: OR = 0.25, 95% CI = [0.08, 0.80], p = .02; for overweight/obesity: OR = 0.36, 95% CI = [0.17, 0.76], p < .01; see Table 9).
5
Racicka et al. Table 3. Prevalence of Overweight and Obesity According to IOTF, Annual Age Categories. Overweight Wiek 7 8 9 10 11 12 13 14 15 16 17 18
Obesity
n
n
%
n
18 (14♂ + 4♀) 47 (43♂ + 4♀) 58 (53♂ + 5♀) 50 (40♂ + 10♀) 53 (39♂ + 14♀) 55 (40♂ + 15♀) 45 (43♂ + 2♀) 31 (28♂ + 3♀) 29 (26♂ + 3♀) 7 (6♂ + 1♀) 12 (11♂ + 1♀) 3 (2♂ + 1♀)
4 (4♂) 7 (7♂) 13 (12♂ + 1♀) 6 (5♂ + 1♀) 5 (3♂ + 2♀) 10 (9♂ + 1♀) 5 (5♂) 4 (2♂ + 2♀) 3 (3♂) 2 (2♂) 0
22.22
1 (1♀) 4 (1♂ + 3♀) 1 (1♂) 2 (2♂) 4 (3♂ + 1♀) 3 (3♂) 4 (4♂) 2 (2♂) 1 (1♂) 1 (1♂) 3 (3♂) 0
1 (1♀)
14.89 22.41 12.00 9.43 18.18 11.11 12.90 10.34 28.57 0 33.33
Overweight/Obesity %
n
%
5.56
5
27.78
8.51
11
23.40
1.72
14
24.14
4.00
18
16.00
7.55
8
16.98
5.45
9
23.64
8.89
13
20.00
6.45
6
19.35
3.45
4
13.79
14.29
3
42.86
25.00
3
25.00
0
1
33.33
Note. IOTF = Obesity Task Force.
1,0
0,5
0,0
-0,5
-1,0
z scoref for BMI z scores for height z scores for weight 7
8
9
10
11
12
13
14
15
16
Age (years)
Figure 1. Mean z scores for children with ADHD for height, weight, and BMI in subsequent years of life. Note. BMI = body mass index.
17
18
6
Journal of Attention Disorders
Table 4. Evaluation of Differences in the Standardized Height, Weight, and BMI Between Patients With ADHD and Population. Mean z scores Boys
Height Weight BMI Height Weight BMI Height Weight BMI
Girls
General (♂+♀)
−0.22 0.01 0.11 −0.16 0.11 0.22 −0.21 0.02 0.13
SD
t
p
1.21 1.17 1.15 1.23 1.20 1.22 1.21 1.18 1.16
−3.38 0.18 1.85 −0.97 0.72 1.40 −3.50 0.45 2.25
research-article2015
JADXXX10.1177/1087054715578272Journal of Attention DisordersRacicka et al.
Article
Prevalence of Overweight and Obesity in Children and Adolescents With ADHD: The Significance of Comorbidities and Pharmacotherapy
Journal of Attention Disorders 1–14 © 2015 SAGE Publications Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1087054715578272 jad.sagepub.com
Ewa Racicka1, Tomasz Hanć2, Katarzyna Giertuga3, Anita Bryńska1, and Tomasz Wolańczyk1
Abstract Objective: Assessment of the prevalence of overweight and obesity in children and adolescents with ADHD with emphasis on pharmacological treatment and comorbid disorders. Method: We analyzed 408 medical records of patients with ADHD aged 7 to 18. Results: The prevalence of overweight (14.71% vs. 12.83%, χ2 = 3,586.43, p < .001) and obesity (6.37% vs. 3.45%, χ2 = 3,588.19, p < .001) was significantly higher in children with ADHD compared with the population. There was significantly higher incidence of obesity in patients with comorbid diagnosis of adjustment disorder (22.22% vs. 4.42%, χ2 = 5.66, p = .02) and mental retardation (19.05% vs. 4.42%, χ2 = 7.63, p = .005). Pharmacological treatment was associated with a higher incidence of obesity (8.37% vs. 2.76%, χ2 = 4.92, p = .03). Conclusion: Standardized body mass index (BMI), prevalence of overweight, and obesity was higher in patients with ADHD compared with the population. Higher incidence of obesity was shown in patients with analyzed comorbidities. (J. of Att. Dis. XXXX; XX(X) XX-XX) Keywords ADHD, BMI, overweight, obesity, body weight, body height
Introduction Association between ADHD and overweight/obesity has been a research topic over the last three decades. The results of previous studies suggest that ADHD is a risk factor of excess body weight (Cortese et al., 2008; Cortese & Morcillo, 2010; Cortese, Olzagasti, et al., 2013; Cortese, Faraone, Bernardi, Wang, & Blanco, 2013; Fliers et al., 2013; Hanć, Cieslik, Wolańczyk, & Gajdzik, 2012; Racicka, 2013). Higher body weight or body mass index (BMI) occurs in both children and adolescents with ADHD (Anderson, Cohen, Naumova, & Must, 2006; Byrd, Curtin, & Anderson, 2013; Chen, Kim, Houtrow, & Newacheck, 2010; Curtin, Bandini, Perrin, Tybor, & Must, 2005; Erhart et al., 2012; Faraone, Biederman, Monuteaux, & Spencer, 2005; Güngör, Celiloğlu, Raif, Özcan, & Selimoğlu, 2013; Hanć & Cieślik, 2008; Hanć et al., 2012; Holtkamp et al., 2004; Hubel, Jass, Marcus, & Laessle, 2006; Lam & Yang, 2007; Ptacek, Kuzelova, Paclt, Zukov, & Fischer, 2009; Schwartz et al., 2014; Spencer et al., 1996; Spencer et al., 2006; Swanson et al., 2006; Waring & Lapane, 2008; Yang, Mao, Zhang, Li, & Zhao, 2013) and adults with this diagnosis (Biederman et al., 2003; Cortese et al., 2013; Fuemmeler, Østbye, Yang, McClernon, & Kollins, 2011; Pagoto et al.,
2009). This has been confirmed by epidemiological studies (Anderson et al., 2006; Byrd et al., 2013; Chen et al., 2010; Erhart et al., 2012; Fuemmeler et al., 2011; Güngör et al., 2013; Lam & Yang, 2007; Waring & Lapane, 2008) as well as studies performed in clinical groups (Biederman et al., 2003; Curtin et al., 2005; Faraone et al., 2005; Hanć & Cieślik, 2008; Holtkamp et al., 2004; Spencer et al., 1996; Spencer et al., 2006; Swanson et al., 2006; Ptacek et al., 2009). Studies also indicate increased incidence of ADHD symptoms in people with obesity (Agranat-Meged et al., 2005; Altfas, 2002; Erermis et al., 2004; Fleming, Levy, & Levitan, 2005). At present, factors underlying the relationship between ADHD and obesity are investigated. Common 1
Department of Child Psychiatry, Medical University of Warsaw, Poland Department of Human Biological Development, Faculty of Biology, Institute of Anthropology, Adam Mickiewicz University in Poznan, Poland 3 Laboratory of Neuroplasticity, Nencki Institute of Experimental Biology, Warsaw, Poland 2
Corresponding Author: Ewa Racicka, Department of Child Psychiatry, Medical University of Warsaw, Marszalkowska 24, Warsaw, 00-576, Poland. Email: [email protected]
2
Journal of Attention Disorders
genes (Albayrak et al., 2013; Choudhry et al., 2013) and family factors such as parental socioeconomic status (van Egmond-Fröhlich, Widhalm, & de Zwaan, 2012) and birth weight (Hanć et al., 2015) are evaluated. The results of the available studies are not conclusive (Dubnov-Raz, Perry, & Berger, 2011; Mustillo et al., 2003). Different variables related to body weight should be considered regarding the association between ADHD and overweight or obesity. In our opinion, special attention should be paid to pharmacological treatment and comorbidities. Previous research has shown that pharmacologically untreated children have higher body weight compared with those in treatment (Schwartz et al., 2014; Waring & Lapane, 2008), whereas pharmacological treatment causes a decrease in body weight (Hanć & Cieślik, 2008; A. Poulton, 2005; A. Poulton et al., 2012; A. Poulton & Cowell, 2003; A. S. Poulton et al., 2013; Swanson et al., 2006). Depression, adjustment disorders, and other psychiatric disorders that often co-occur with ADHD (Biederman, Newcorn, & Sprich, 1991; Wilens et al., 2002) may also affect body weight (Biederman et al., 2003; Lin et al., 2013; Reeves, Postolache, & Snitker, 2008). For example, investigators searching for the causes of obesity in patients from obesity clinic indicate the more frequent prevalence of psychiatric disorders including depression and adjustment disorders in patients with obesity (Kalarchian et al., 2007; Scott, McGee, Wells, & Browne, 2008; Simon et al., 2006; Stunkard, Faith, & Allison, 2003; Wilens et al., 2002; Mühlhans, Horbach, & de Zwaan, 2009). Small number of patients in clinical trials (AgranatMeged et al., 2005; Erermis et al., 2004; Hubel et al., 2006), the lack of assessment of the pharmacological treatment impact (Chen et al., 2010; Spencer et al., 1996) and comorbid disorders (Altfas, 2002; Anderson et al., 2006; Chen et al., 2010; Curtin et al., 2005; Fleming et al., 2005; Lam & Yang, 2007; Spencer et al., 1996), the absence of a formal diagnosis of ADHD (Anderson et al., 2006; Chen et al., 2010; Erermis et al., 2004; Hubel et al., 2006; Mustillo et al., 2003; Waring & Lapane, 2008), as well as the lack of a control group (Agranat-Meged et al., 2005; Altfas, 2002; Fleming et al., 2005) and data on socioeconomic status (Holtkamp et al., 2004) are the limitations of the most conducted studies so far. The aim of the study was to assess the prevalence of overweight and obesity in children and adolescents with ADHD with particular emphasis on the impact of pharmacological treatment and comorbid disorders. Based on previous research, we hypothesized the following: Hypothesis 1: The prevalence of weight problems will be greater in children and adolescents with ADHD compared with the general population.
Hypothesis 2: Concomitant disorders and treatment have an impact on the prevalence of overweight and obesity in this group of patients.
Method Ethical and Financial Statements The study has been approved by the Ethics Committee of the Warsaw Medical University, and has therefore been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.
Study Group Seven hundred medical records of patients aged 7 to 18, admitted to outpatient psychiatry clinic at Public Pediatric Teaching Hospital in Warsaw from 1999 to 2012 due to ADHD symptoms, have been analyzed. We included only charts with complete information on height, weight, age, sex, comorbidities, and pharmacological treatment. This yielded a final total of 408 charts. Then, we chose the first visit within 2.5 years from initial visit, which contained all the necessary information (min. 11 days, max. 799 days) for analysis. Children were seen at various intervals for followup visits. The diagnosis was performed according to diagnostic criteria of Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR; American Psychiatric Association, 2000) for one of the three ADHD types: predominantly inattentive or impulsive/hyperactive and combined type. The diagnosis made by child-trained and experienced psychiatrists working in outpatient clinic included an interview with patient and his family, Diagnostic Structured Interview for ADHD and Hiperkinetic Disorder according to International Classification of Diseases (ICD)10 and DSM-IV TR (Wolańczyk & Kołakowski, 2005), the Behavioral Disorders Supplement of Diagnostic Intervew Kiddie-SADS–Present and Lifetime Version (KiddieSADS-PL), and observation of patient behavior. Parents were asked to provide background records and school reports as well as to complete behavior rating scales. The child’s teachers were also asked to complete behavior rating scales. For the comorbidity diagnosis, other supplements of KiddieSADS were administered by the same child psychiatrist; diagnosis was based on the diagnostic criteria for ICD-10 (World Health Organization, 1994). The diagnosis was performed during at least three appointments during which children also underwent physical, neurological, and developmental examination. In valid cases, laboratory tests were done (such as morphology, Thyroid Stimulating Hormone [TSH]) and psychological diagnostic such as Wechsler Intelligence Scale–Revised (WISC-R) and testing for learning disabilities
3
Racicka et al. were performed by trained psychologists. Measurements were made by psychiatrist or trained nurse. Exclusion criteria included diabetes, dysfunction of the thyroid gland, and others somatic disorders that could affect the body weight of patients, as well as pervasive developmental disorder due to specific dietary habits in this group. Data on age, sex, height, weight, medical treatment, and comorbid disorders were collected from medical records. Information concerning patients was collected from visits records, which included all the above-mentioned data. This means that information relating to medication therapy and comorbid disorders applied to individual visits. In case of patients who were on medication, we took the data on the treatment onset. The course of comorbid disorders was not included. Based on the data of onset of pharmacological treatment and the data of assessment, the duration of treatment was calculated. Then we estimated cumulated dose of drugs using the following equation: mg/day × days of treatment up to the moment of assessment. Cumulated dose was calculated based on the assumption that the drugs were received 7 days/week and holiday breaks were taken into account.
Anthropometric Measurements Measurements of body height were carried out according to the standard technique (Chumlea & Guo, 2006; de Onis, Onyango, Van den Broeck, Chumlea, & Martorell, 2004) by trained medical staff. Body weight was measured with a medical scale (Radwag PUE c/31) with an accuracy of ±100 g. Height was measured using a Harpenden anthropometric instrument with an accuracy of 0.1 cm. The examined children were weighted in their underwear. The measurements were performed between 9 a.m and 4 p.m. BMI was calculated on the basis of body weight and height. Height, weight, and BMI were later standardized according to sex and age using the growth references for Polish population (Kułaga et al., 2010). These growth charts give standard measurements at an interval of 1 year; therefore, for calculating the z scores, we assumed a constant rate of change of the mean and standard deviation between 1 year and the next. Overweight and obesity were assessed according to criteria of Obesity Task Force (IOTF; Cole, Bellizzi, Flegal, & Dietz, 2000; Cole, Flegal, Nicholls, & Jackson, 2007). IOTF cut-off points corresponded approximately to 90th percentile of BMI for overweight and 98th percentile for obesity (Cole et al., 2007). The calculated frequencies were then compared with the prevalence of overweight and obesity in the Polish population in the same age group (Kułaga et al., 2011). This reference provided data on prevalence of overweight and obesity separately in boys and girls in 1 year age categories for 7 to 18 years. Using these data and the numbers of boys and girls in following years of age, we
calculated the number of children who were overweight and obese. Then the numbers from 1 year age classes were summed up to estimate overweight and obesity rates (%) in the whole sample of boys and girls, without division on age. One sample t test was used to assess the differences in standardized height, weight, and BMI between patients with ADHD and population (z scores = 0). Chi-square test was used to assess differences in prevalence of overweight and obesity between children with ADHD and population and for assessment of association between chosen comorbidities and pharmacological treatment and prevalence of overweight and obesity in ADHD patients. Differences at the level of p < .05 were considered as statistically significant. The forward stepwise regression method was used to build the multifactorial models of z scores for children with ADHD for height, weight, and BMI determination. Comorbid disorders and cumulated dose of medications as well age and sex were tested as independent variables. The correctness of models fitting into the empirical data was estimated using the variance analysis. The criterion of model accuracy was the statistical significance of F value on the level of p < .05. Stepwise logistic regression with Quasi-Newton estimation method was used to assess probability of overweight or obesity based on adjusted analysis of comorbid disorders and quartiles of cumulated dose of medications. Separate models where tested for overweight, obesity, and the sum of overweight and obesity. All statistical analyses were conducted with Statistica 10 software.
Results In this study, body weight of 408 patients with ADHD aged 7 to 18 years (M = 11.24 years, SD = 2.54 years, min = 6.89, max = 18.66) was evaluated. Boys constituted 85.78% of the group (350 of 408 patients). In 182 (44.61%) patients, comorbid conditions were diagnosed. The most common were oppositional defiant disorder (ODD) and conduct disorder (CD; n = 83, 20.34%). Mild mental retardation was found in 21 (5.15%) and adjustment disorders in 9 (2.12%) patients. Most of the respondents at the time of study received medication (n = 263, 64.46%). The most frequently used were metylphenidate (MPH) osmotic release oral system (OROS; 24% of the sample) and short-acting stimulants (14.95% of the sample). Mean doses, duration of treatment, and cumulated dose are presented in Table 1. Details of the prevalence of overweight and obesity in the sample are shown in Tables 2 and 3 and Figure 1. Patients with ADHD had significantly lower height (t = −3.50, p < .001) and higher standardized BMI compared with the population (t = 2.25, p = .02). When controlling for sex, significant difference was only found for height (t = −3.38, p < .001; see Table 4).
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Journal of Attention Disorders
Table 1. Characteristics of Treatment. Medication
n
% of the sample
OROS Dose (mg/day) Duration (days) Cumulated dose MPH IR Dose (mg/day) Duration Cumulated dose Atomoxetinum Dose (mg/day) Duration Cumulated dose Risperidone Dose (mg/day) Duration Cumulated dose Imipraminum Dose (mg/day) Duration Cumulated dose
98
24
61
M
SD
28.54 159.04 5,659.97
14.83 168.42 9,044.44
22.74 149.97 3,603.42
12.98 124.58 4,149.41
41.67 136.12 5,910.588
12.24 120.23 5,964.65
Minimum-maximum 18-81 11-799 198-64,719 10-60 27-589 420-18,440 25-60 35-504 2,100-22,500 0.25-2 49-504 12.25-924 10-101 35-425 650-42,500
14.95
18
4.41
19
4.66
34
1.19 187.74 270.49
0.54 158.75 288.53
46.96 120.24 6,604.44
24.39 73.90 7,912.51
9.33
Note. MPH IR = metylphenidate immediate release.
Table 2. Prevalence of Overweight and Obesity in ADHD Patients According to IOTF Criteria. Boys (n = 350)
Girls (n = 58)
Total (N = 408)
n
%
n
%
n
%
Overweight Obesity Overweight/obesity (total)
52 23 75
14.86 6.57 21.43
8 3 11
13.79 5.17 18.97
60 26 86
14.71 6.37 21.08
Note. IOTF = International Obesity Task Force.
Both the prevalence of overweight (14.71% vs. 12.83%, χ2 = 3,586.43, p < .001) and obesity (6.37% vs. 3.45%, χ2 = 3,588.19, p < .001) was significantly higher in children with ADHD compared with the population (see Table 5). When sex was controlled, statistically significant difference was demonstrated only in the group of boys. The incidence of obesity in boys with ADHD was higher by 2.27% compared with the population (χ2 = 1.74, p = .04). Unadjusted analysis showed significantly higher incidence of obesity in patients with comorbid diagnosis of adjustment disorder (22.22% vs. 4.42%, χ2 = 5.66, p = .02), mild mental retardation (19.05% vs. 4.42%, χ2 = 7.63, p = .005), and pharmacological treatment (8.37% vs. 2.76%, χ2 = 4.92, p = .03; see Tables 6 and 7). Detailed analysis showed that the higher incidence of obesity in this group was associated only with the use of OROS MPH (12.24% vs. 2.78%, χ2 = 8.46, p = .004).
Adjusted analysis using the forward stepwise regression method has shown significant positive relation of MPH OROS cumulated dose and z scores for height (β = 0.11, t = 2.23, p = .03) and weight (β = 0.13, t = 2.62, p = .009; see Table 8). Adjustment disorders were positively related to z scores for weight (β = 0.12, t = 2.35, p = .02) and BMI (β = 0.10, t = 2.07, p = .04). Mental retardation was linked with increase in z scores for BMI (β = 0.11, t = 2.24, p = .03) Logistic regression was used to assess the relation between potential risk factors and the rate of overweight and obesity. Adjusted analysis has shown only two variables increasing the risk of obesity and overweight/obesity: mental retardation (for obesity: OR = 0.21, 95% CI = [0.06, 0.73], p = .01; for overweight/obesity: OR = 0.36, 95% CI = [0.14, 0.94], p = .04) and MPH OROS treatment (for obesity: OR = 0.25, 95% CI = [0.08, 0.80], p = .02; for overweight/obesity: OR = 0.36, 95% CI = [0.17, 0.76], p < .01; see Table 9).
5
Racicka et al. Table 3. Prevalence of Overweight and Obesity According to IOTF, Annual Age Categories. Overweight Wiek 7 8 9 10 11 12 13 14 15 16 17 18
Obesity
n
n
%
n
18 (14♂ + 4♀) 47 (43♂ + 4♀) 58 (53♂ + 5♀) 50 (40♂ + 10♀) 53 (39♂ + 14♀) 55 (40♂ + 15♀) 45 (43♂ + 2♀) 31 (28♂ + 3♀) 29 (26♂ + 3♀) 7 (6♂ + 1♀) 12 (11♂ + 1♀) 3 (2♂ + 1♀)
4 (4♂) 7 (7♂) 13 (12♂ + 1♀) 6 (5♂ + 1♀) 5 (3♂ + 2♀) 10 (9♂ + 1♀) 5 (5♂) 4 (2♂ + 2♀) 3 (3♂) 2 (2♂) 0
22.22
1 (1♀) 4 (1♂ + 3♀) 1 (1♂) 2 (2♂) 4 (3♂ + 1♀) 3 (3♂) 4 (4♂) 2 (2♂) 1 (1♂) 1 (1♂) 3 (3♂) 0
1 (1♀)
14.89 22.41 12.00 9.43 18.18 11.11 12.90 10.34 28.57 0 33.33
Overweight/Obesity %
n
%
5.56
5
27.78
8.51
11
23.40
1.72
14
24.14
4.00
18
16.00
7.55
8
16.98
5.45
9
23.64
8.89
13
20.00
6.45
6
19.35
3.45
4
13.79
14.29
3
42.86
25.00
3
25.00
0
1
33.33
Note. IOTF = Obesity Task Force.
1,0
0,5
0,0
-0,5
-1,0
z scoref for BMI z scores for height z scores for weight 7
8
9
10
11
12
13
14
15
16
Age (years)
Figure 1. Mean z scores for children with ADHD for height, weight, and BMI in subsequent years of life. Note. BMI = body mass index.
17
18
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Journal of Attention Disorders
Table 4. Evaluation of Differences in the Standardized Height, Weight, and BMI Between Patients With ADHD and Population. Mean z scores Boys
Height Weight BMI Height Weight BMI Height Weight BMI
Girls
General (♂+♀)
−0.22 0.01 0.11 −0.16 0.11 0.22 −0.21 0.02 0.13
SD
t
p
1.21 1.17 1.15 1.23 1.20 1.22 1.21 1.18 1.16
−3.38 0.18 1.85 −0.97 0.72 1.40 −3.50 0.45 2.25
