hyperactivity symptoms—Roles of gender and family adversity

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Hair cortisol concentration in preschoolers with attention-deficit/ hyperactivity symptoms—Roles of gender and family adversity

MARK

⁎

Ursula Pauli-Potta, , Susan Schloßa, Isabelle Ruhla, Nadine Skoludab,d, Urs M. Naterb,c, Katja Beckera a

Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Philipps-University of Marburg, Hans Sachs Str. 6, D-35039 Marburg, Germany Clinical Biopsychology, Department of Psychology, Philipps-University of Marburg, Gutenbergstraße 18, D-35032 Marburg, Germany c Department of Psychology, University of Vienna, Liebiggasse 5, 1010 Vienna, Austria d Department of Psychiatry and Psychotherapy, University of Tübingen, Calwerstr. 14, 72076, Tübingen, Germany b

A R T I C L E I N F O

A B S T R A C T

Keywords: Hypothalamic-pituitary-adrenal axis dysregulation Hair cortisol concentration Preschool age ADHD symptoms Family adversity Gender

Objective: Previous studies on the association between hypothalamic-pituitary-adrenal axis (HPAA) activity and ADHD yielded inconsistent findings, particularly in younger children. This might be due to the heterogeneity of the disorder, making moderator effects of variables probable, which circumscribe more homogenous subgroups. There have been indications of moderator effects on this association by gender of child and exposure to family adversity. Moreover, difficulties in capturing long-term basal HPAA activity in younger children might have contributed to the inconsistencies. We therefore analyzed moderator effects of gender and family adversity while using the hair cortisol concentration (HCC) to assess integrated long-term HPAA. Methods: The community-based sample consisted of 122 4–5-year-old preschoolers (71 screened positive for elevated ADHD symptoms). ADHD symptoms were measured by a clinical parent interview and parent and teacher questionnaires. HCC in the most proximal 3-cm scalp hair segment was analyzed using luminescence immunoassay. An extended family adversity index was used. Results: Hierarchical linear regression analyses yielded an interaction effect (p < .05) between ADHD symptom groups and gender on HCC, indicating a low HCC in boys with elevated ADHD symptoms. Further exploratory analyses revealed that this interaction effect was most pronounced under the condition of family adversity. The results held after controlling for oppositional, anxiety, and depressive symptoms. Conclusion: Low HCC might indicate a specific pathogenic mechanism in boys with elevated ADHD symptoms. This mechanism might further involve an exposure to family adversity. However, the results need to be crossvalidated before definitive conclusions can be drawn.

1. Introduction Over the last decades, research has found evidence for a dysregulation of the hypothalamic-pituitary-adrenal axis (HPAA) in several psychiatric disorders (e.g. Lupien et al., 2009; Struber et al., 2014; Zorn et al., 2017). HPAA dysregulation can result from experiences such as prolonged exposure to stress, from genetic factors, and gene-environment interactions (Ouellet-Morin et al., 2009; Struber et al., 2014). Moreover, the timing of the environmental influences can be important. In infancy and toddlerhood, crucial normative developmental changes of HPAA functions occur, such as the emergence of HPAA basal diurnal rhythm in infancy, and the transition from the high HPAA reactivity of the first 6 months of life to the relative stress-hyporesponsive period of the preschool and childhood years. “Programming effects” of HPAA

⁎

Corresponding author. E-mail address: [email protected] (U. Pauli-Pott).

http://dx.doi.org/10.1016/j.psyneuen.2017.09.002 Received 9 May 2017; Received in revised form 14 July 2017; Accepted 1 September 2017 0306-4530/ © 2017 Elsevier Ltd. All rights reserved.

functions exerted by stress exposure have been found in infancy and early childhood, when the most rapid normative changes take place (Gunnar et al., 2009; Lupien et al., 2009). Deviations of HPAA parameters may thus indicate specific pathogenic mechanisms and developmental pathways of the psychiatric disorders. In attention-deficit/hyperactivity disorder (ADHD) and the broader domain of externalizing disorders (Achenbach et al., 1991), studies have indicated a hypo-activity of the HPAA. A recent meta-analysis of 22 studies found a small but significant association between ADHD and a low basal salivary cortisol level (d = −.31), while cortisol reactivity parameters were not consistently associated with ADHD (Scassellati et al., 2012). Likewise, a meta-analysis on externalizing symptoms revealed a small association with different basal salivary cortisol measures, but not with reactivity parameters (Alink et al., 2008). In this

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2012). The collection of multiple salivary samples across consecutive days, however, extends the time period (and reliability of measurement) often unsatisfactorily, and has the disadvantage of causing considerable stress (and a consequent increase in cortisol) due to the sampling procedure (Russell et al., 2012). The hair cortisol concentration (HCC), by contrast, appears to be free of these disadvantages and has proven to reliably and validly capture the accumulated, integrated long-term activity of the HPAA (Kirschbaum et al., 1990; Short et al., 2016; Stalder et al., 2017). Moreover, the measure can be expected to be particularly suitable to assess basal cortisol secretion at preschool and school age, because HPAA basal activity (diurnal rhythm) is already established and HPAA reactivity might make only a minor contribution to the accumulated measure due to the relative stress-hyporesponsiveness in this age period (Gunnar et al., 2009; Lupien et al., 2009). For these reasons, we used HCC in the present study. While one previous study used HCC in the context of externalizing symptoms in maltreatment (White et al., 2017), to our knowledge, this is the first study to use HCC in the context of ADHD. In the following, we analyze data from the first, preschool-age assessment wave of a larger longitudinal study examining developmental changes in the link between HPAA activity and ADHD symptoms. In this study, we assessed symptoms of ADHD instead of ADHD diagnoses (i.e. we used a dimensional measurement approach regarding ADHD) due to a higher sensitivity to the emerging, and often not yet full-blown, disease in the preschool period (Sonuga-Barke et al., 2011). Moreover, this approach is appropriate due to the dimensional nature of the distribution of ADHD symptoms in the general population (Coghill and SonugaBarke, 2012). We analyzed the following hypotheses: (1) We expected to find a negative association between ADHD symptoms and HCC, because a recent meta-analysis (Scassellati et al., 2012) pointed to a negative link between HPAA activity and ADHD. As recent research also pointed to moderator effects by gender of child and family psychosocial adversity factors, which might circumscribe more homogenous subgroups of ADHD, we expected the association between ADHD symptoms and HCC to be modified by (2) gender of child and (3) the presence vs. absence of family psychosocial adversity factors.

latter meta-analysis, however, the link between HPAA activity and externalizing symptoms depended on age. In samples of 0–5-year-old children, the authors found a small positive link between externalizing symptoms and basal salivary cortisol measures. More recent studies that involved large community-based samples were unable to confirm this positive link. In these studies, no associations emerged between externalizing symptoms at 3 years and the preceding diurnal salivary cortisol profile at 14 months (Saridjan et al., 2014), between externalizing symptoms at 4 years and concurrent morning salivary cortisol (Perez-Edgar et al., 2008) and between externalizing symptoms at age 3 and the developmental course of HPAA activity parameters (HillSoderlund et al., 2015). These findings, i.e. small effect sizes in general and age-dependent inconsistencies, might be caused in part by the heterogeneity of ADHD and externalizing disorders with respect to their etiology and developmental pathways (Nigg et al., 2005; Sonuga-Barke et al., 2010). Accordingly, the link between ADHD/externalizing symptoms and HPAA hypo-activity might be modified by third variables, characterizing subgroups of the disorders. With regard to this link, the child’s gender has been considered relatively often as a moderator variable. However, the respective findings have been inconclusive. While several studies found the associations to be somewhat stronger in boys than in girls (Alink et al., 2008; Pesonen et al., 2011; Poustka et al., 2010; Smider et al., 2002), others did not find the association to be modified by the gender of the child (Hill-Soderlund et al., 2015; Saridjan et al., 2014). Further studies have revealed the reverse finding, i.e. positive associations between HPAA activity parameters and externalizing symptoms in girls but not in boys (Marsman et al., 2008). Besides gender, recent theories and research have pointed to the role of exposure to family psychosocial adversity as a moderator variable. Several recent studies found that prolonged exposure to environmental adversity in childhood amplifies the association between HPAA dysregulation and emotional (van der Vegt et al., 2010; von Klitzing et al., 2012) as well as behavior problems (Ouellet-Morin et al., 2011). Ouellet-Morin et al. (2011) demonstrated that in 12-year-olds who had been bullied by peers and/or maltreated by an adult in the past years, the association between a low cortisol response and behavioral problems was stronger than in non-bullied/non-maltreated control children. The authors concluded that childhood adversity may cause neurobiological changes that affect the development of the HPAA and increase the vulnerability to develop behavioral problems (OuelletMorin et al., 2011). Studies in adopted preschool children (Koss et al., 2016) and preschoolers involved in child protective services (Bernard et al., 2015) showed an association between HPAA dysregulation, i.e. hypocortisolism, and attention or externalizing problems in these children compared to control children. Similarly, Laurent et al. (2014) demonstrated that preschool children exposed to adversity (composite score on, e.g., parental negative life events, marital instability, financial need) showed lower evening cortisol associated with higher externalizing symptoms. However, in a large-scale study on maltreatment (White et al., 2017), the expected associations between maltreatment, low hair cortisol concentration, and externalizing symptoms were found in older children and adolescents but not in children younger than 10 years. Other recent studies that also analyzed mediation processes between early psychosocial risks/poverty and ADHD symptoms by HPAA parameters (Hill-Soderlund et al., 2015; Isaksson et al., 2013) failed to show the expected links. However, these studies did not analyze interaction (i.e. moderator) effects between the psychosocial conditions and the HPAA parameters. A further reason for the small association between ADHD symptoms and HPAA activity, and for the inconsistent findings in younger children, might lie in the procedures used to assess HPAA activity. The vast majority of previous studies on this association used salivary cortisol parameters. Salivary and serum cortisol as well as urinary cortisol measures reflect the cortisol concentration only at a single time point or within a limited time frame of up to 24 h, respectively (Russell et al.,

2. Methods 2.1. Participants The present study draws on data from the first assessment wave of an ongoing larger longitudinal study from preschool to school age. The original sample of the study consisted of 198 children (115 boys, 58%). The community-based sample was recruited from childcare facilities located in the district of Marburg, Middle West Germany. Parents and their 4–5-year-old children were invited to take part in a longitudinal study following the development of preschoolers with and without ADHD symptoms. At the childcare facilities, a screening for ADHD symptoms was conducted. Parents filled in a screening questionnaire on ADHD symptoms (Döpfner et al., 2008; description see below). 113 preschoolers who scored above the lower bound of the 95% confidence interval of the clinical cut-off score of the questionnaire (equivalent to the 70th percentile of the questionnaire) and 85 children who scored below this point were included in the study sample. Overall, children therefore showed a broad spectrum of ADHD symptoms. Exclusion criteria were: IQ < 80, motor disabilities, sensory handicaps, chronic physical and mental diseases involving brain functions, indication of a trauma (serious physical maltreatment, life-threatening injury) experienced by the child, any continuous pharmacological treatment, and insufficient German language skills of parents or child. The intelligence level of the children was estimated by subtests (Word Reasoning, Vocabulary, Block Design, and Matrix Reasoning) of the German version of the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III) (Petermann, 2009). Mothers were asked about the remaining exclusion 26

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Table 1 Description of sample.

n Age in months m, sd Gender n (%) male female Education level of mother no compl. education basic education work qualification high school college Education level of father basic education work qualification high school college (no reply) Employment of mother full-time part-time none (no reply) Employment of father full-time part-time none (no reply) Symptom scores of the child ADHD parent rating m, sd ADHD teacher rating m, sd ADHD clinical interview m, sd ODD/CD parent rating m, sd anxiety/depr. parent rating m, sd

no elevated ADHD symptoms

elevated ADHD symptoms

51

71

58.3 (5.8)

Comparison between ADHD-symptom groups

Total sample

122

58.0 (6.1)

t = 0.24 p = .811 2

58.3 (6.0)

26 (51.0%) 25 (49.0%)

30 (42.3%) 41 (57.7%)

Chi (1) = 0.91 p = .348

56 (45.9%) 66 (54.1%)

0 (0%) 3 (5.9%) 15 (29.4%) 11 (21.6%) 22 (43.1%)

1 (1.4%) 7 (9.9%) 30 (42.2%) 9 (12.7%) 24 (33.8%)

Chi2 (4) = 4.74 p = .316

1 (0.8%) 10 (8.2%) 45 (36.9%) 20 (16.4%) 46 (37.7%)

6 (12.0%) 8 (16.0%) 18 (36.0%) 18 (36.0%) (1)

16 (23.5%) 16 (23.5%) 13 (19.1%) 23 (33.8%) (3)

Chi2 (3) = 6.02 p = .111

22 (18.0%) 24 (19.7%) 31 (25.4%) 41 (33.6%) (4)

7 (14.0%) 28 (56.0%) 15 (30.0%) (1)

16 (22.9%) 34 (48.6%) 20 (28.6%) (1)

Chi2 (2) = 1.53 p = .466

23 (19.2%) 62 (51.7%) 35 (29.2%) (2)

44 (88.0%) 1 (2.0%) 5 (10.0%) (1)

59 (84.3%) 2 (4.3%) 9 (11.4%) (1)

Chi2 (2) = 0.56 p = .756

103 (84.4%) 3 (2.5%) 14 (11.5%) (2)

0.55 (0.26)

1.39 (0.42)

0.52 (0.53)

0.98 (0.65)

3.81 (3.43)

7.64 (5.06)

6.18 (4.75)

10.35 (7.44)

5.11 (4.67)

7.46 (4.95)

t = 12.46 p < .001 t = 4.13 p < .001 t = 4.66 p < .001 t = 3.48 p < .001 t = 2.61 p = .010

1.04 (0.55) 0.78 (0.64) 6.01 (4.81) 8.52 (6.70) 6.44 (4.95)

ADHD: attention deficit/hyperactivity disorder; ODD/CD: oppositional defiant disorder/conduct disorder.

session at the childcare facilities (data from which will be published elsewhere), and a telephone interview with the mother. The initial telephone call (scheduling of appointments), the home visit, the playroom session, and the telephone interview were conducted in that order within a maximum time frame of six weeks. During the home visit, an interview with the mother regarding family psychosocial adversity factors was conducted, the child underwent an intelligence test, and the hair samples were collected. The playroom session comprised psychological tests and structured behavior observations of about 30 min duration conducted by two female research assistants. The clinical interview on the child’s ADHD symptoms was carried out by telephone. Parents and kindergarten teachers completed questionnaires on ADHD symptoms as well as oppositional/conduct and emotional symptoms of the child.

criteria in an initial telephone interview and in standardized interviews on the health and development of the child, burden in the family and life events experienced by parents and child. The records of the pediatric health check-ups of the child (continuous pediatric health screening conducted in Germany from infancy onwards) were examined. Of the original sample, 65 cases had to be excluded because parents refused to take part in the hair collection part of the study or because the child did not fulfill the criterion of minimum hair length of 3 cm; a further 11 cases had to be excluded later during hair processing due to insufficient hair in terms of length or amount. In total, 122 preschoolers with complete data (71 with and 51 without elevated ADHD symptoms) were included in the present analyses. Table 1 contains descriptive data of the sample and comparisons between the ADHD symptom groups. Groups did not differ with respect to age in months, gender of child, parental education level, and employment status, but did differ in terms of ADHD, oppositional defiant disorder/conduct disorder, and anxiety/ depressive symptom scores. Parents gave their written informed consent to participate in the study, and received an expense allowance of 50 Euros. The study was approved by the Ethics Committee of the Medical Faculty, University of Marburg.

2.3. Variables 2.3.1. Hair cortisol concentration (HCC) Several thin hair strands were cut as close as possible to the scalp from the posterior vertex region of the head. The first proximal scalpnear 3-cm segment was used for the determination of HCC. This 3-cm segment is thought to reflect the cumulative cortisol secretion of the past 3 months (Wennig, 2000) and therefore corresponds to the assessment of the child’s ADHD symptoms in the past 3 months in the clinical parent interview. Hair washing and cortisol extraction

2.2. Procedure Data were collected within the scope of a home visit, a “playroom” 27

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procedures were based on a laboratory protocol first described by Stalder et al. (Stalder et al., 2012), with minor modifications. In brief, hair samples were washed twice for 3 min using 3 mL isopropanol. For cortisol extraction, 10.0 ± 0.5 mg whole, finely cut hair samples were incubated in 1.8 mL methanol for 18 h at room temperature. After incubation, 1.6 mL of the extract was evaporated at 50 °C under a constant stream of nitrogen until the samples were completely dried. Finally, 150 μL HPLC gradient grade water (Fisher Scientific) was added and vials were vortexed for 20 s. For cortisol determination (single samples were run for analysis), 50 μL was applied for analysis using a commercially available cortisol luminescence immunoassay (LIA; IBL, Hamburg, Germany). As HCC showed a skewed distribution, the distribution was normalized by exclusion of two outliers exceeding the mean +3 SD and log-transformation. Potential influences of several confounders were checked. We found no significant association of HCC with the body mass index of the child (Spearman’s Rho = −.03), number of cigarettes smoked by the mother (Spearman’s Rho = −.06), hair color and curling, hair washing frequency, or use of hair products (gel, spray) (tscores 1.83–1.06).

seriously considered). Of the 122 participants, 66 (54%) showed no risks, while 56 (46%) showed at least one of the risk factors. In the following, we use the dichotomous variable “presence versus absence of psychosocial risk factors” (i.e. 0 versus 1 or more risks). 2.4. Control variables To control for possible influences of symptoms of oppositional defiant disorder/conduct disorder (ODD/CD) and anxiety/depressive disorders of the child and maternal ADHD symptoms, we assessed these variables using the following methods. 2.4.1. Symptoms of ODD/CD Mothers filled in the German FBB-SSV questionnaire, which measures ODD/CD symptoms of the child (Döpfner et al., 2008) according to the ICD-10. The scale shows high internal consistency (Cronbach’s alpha = .91) and validly discriminates between children with ODD/CD and controls (Gortz-Dorten et al., 2014). 2.4.2. Symptoms of anxiety and depression The Anxious/Depressed scale of the German version of the Child Behavior Checklist (CBCL4-18) by Döpfner et al. (1994) was employed. The scale shows significant associations with anxiety and emotional disorders, indicating good validity (Döpfner et al., 1994).

2.3.2. ADHD symptom assessment ADHD symptoms of the child were assessed using a structured clinical parent interview and by parent and teacher questionnaires. The Parental Account of Childhood Symptoms (PACS) interview (Taylor et al., 1986) in the modified preschool version (PrePACS) (Daley, 2010) was conducted with the mother. In this interview, parents are asked to assess the intensity and frequency of the circumscribed symptoms (Taylor et al., 1986) in the last 3 months (Bufferd et al., 2012; Egger and Angold, 2006). The ADHD scale of this interview shows good testretest reliability (.78, 15-week interval) and discriminates significantly between children with ADHD and healthy controls (Sonuga-Barke et al., 2003). Parents and kindergarten teachers filled in the preschool version of the ADHD rating scale (FBB-ADHS-V) (Döpfner et al., 2008). This questionnaire captures ADHD symptoms according to the ICD-10 and DSM-5. The parent and teacher version show high homogeneity (Cronbach’s alpha: .94 and .93) and good validity (differentiation between children with and without an ADHD diagnosis) (Breuer and Dopfner, 2008). The three ADHD scores intercorrelated as follows: FBBADHS-V parent and teacher score: .42 (p < .001); PrePacs score and FBB-ADHS-V teacher: .25 (p < .006); PrePacs score and FBB-ADHS-V parent: .60 (p < .001). We created a composite score by summing up the z-transformed scores of these ADHD scores. Internal consistency (Cronbach’s alpha) of the composite scale was .68. In the following, we use the dichotomous score positive vs. negative screening for elevated ADHD symptoms and the dimensional composite score. We refer to these variables as “ADHD symptom groups” and “ADHD symptom score”.

2.4.3. Maternal ADHD symptoms Mothers filled in the German version of the Conners Adult ADHD Rating Scale (CAARS) (Christiansen et al., 2012) and were interviewed using the Wender-Reimherr Interview for adults (Rösler et al., 2008). Internal consistency (Cronbach’s alpha) of the interview scale is .82. The method validly differentiates between adults with and without an ADHD diagnosis (Rösler et al., 2008). The scores were summed up after z-transformation. 2.5. Statistical analyses In a preliminary analysis, we calculated the bivariate correlation coefficients among the study variables for validation purposes and to facilitate the interpretation of the results. We calculated the correlation coefficients between study and control variables (i.e. ODD/CD, anxiety/ depression symptoms of child, maternal ADHD symptoms) to identify those variables that have to be controlled for. We used Pearson productmoment correlations and point-biserial correlation coefficients. The point-biserial correlation coefficient is equivalent to a t-test, e.g., of an HCC difference between the ADHD symptom groups. To analyze the first hypothesis, i.e. that HCC is negatively associated with the ADHD symptoms of the child, we used the correlation coefficient between ADHD symptom groups and HCC. In the following steps (for control purposes), we analyzed the association with the continuous ADHD symptom score and adjusted these analyses for those control variables that were significantly associated with the ADHD variables using partial correlation coefficients. To analyze the second and third hypotheses, i.e. that gender of the child and family adversity modify (act as moderator variables) the association between ADHD symptoms and HCC, we used multiple hierarchical regression models. Specifically, we analyzed whether HCC differences in the ADHD symptom groups depended on gender (and family adversity, respectively) by use of hierarchical regression analysis with HCC as the criterion variable and ADHD symptom groups, gender, and the interaction effects between gender and ADHD symptom groups as predictor variables (Aiken and West, 1991; Cohen et al., 2003). The interaction effect was modeled by entering the product of the ADHD variable and the moderator variable into the regression equation after entering the two main effects (Aiken and West, 1991; Cohen et al., 2003). The change statistics of the hierarchical regression analyses indicate the amount of variance explained (and its significance) in the

2.3.3. Family adversity To assess adverse psychosocial conditions, we used the psychosocial risk index by Laucht et al. (2007), which represents an extended family adversity index (Biederman et al., 1995). The index has been used frequently in the context of ADHD and has proven to be valid, e.g. by predicting the development of ADHD (Biederman, 2005; Biederman et al., 1995) and the increased risk of developing ADHD symptoms in the presence of genetic vulnerability (Laucht et al., 2007). During a structured interview with the mother, the following risks were assessed: (1) low education level of a parent (parent without completed school education), (2) overcrowded living conditions (more than one person per room or a living space less than 50 m2), (3) at least one parent with a broken home background (institutional care of a parent/loss of a parent before the age of 12 years), (4) early parenthood (at least one parent was under 18 years old at the time of the child’s birth/relationship between parents lasting < 6 months at time of conception), (5) parental separation, and (6) unwanted pregnancy (an abortion was 28

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3.2. Associations between ADHD symptoms and HCC

criterion variables by the entered variable(s). Hypotheses 2 and 3 were tested in the final steps, i.e. by the introduction of the interaction effect into the regression analyses. In the subsequent analyses, we considered the ADHD symptom score and adjusted for those of the control variables that were significantly associated with the ADHD variables. For the latter purpose, we repeated the regression analyses and entered the control variables into the regression analyses before the ADHD variable and gender of child (and family adversity, respectively). In the case of a significant interaction effect, we explored whether the second moderator variable modified the result, i.e. whether the associations between HCC and ADHD symptoms, which depend on the expression of the first moderator variable, were modified by the expression of the other moderator. Hypotheses were tested with an alpha error of 5% (level of significance 0.05).

The association between ADHD symptom groups and HCC was not statistically significant (r = −.07, Table 2); thus, the first hypothesis has to be rejected. The ADHD symptom score was also not associated with HCC (r = −.02, Table 2). Adjustment for anxiety/depressive and ODD/CD symptoms of the child and maternal ADHD symptoms did not change these results (partial correlations between HCC and ADHD symptom groups: −.04; between HCC and ADHD symptom composite score: .04). 3.3. Moderator effect by gender of child The interaction effect between ADHD symptom groups and gender on HCC proved to be statistically significant (Fchange = 3.97, p = 0.049, Table 3). The same was true for the interaction effect between the ADHD symptom score and gender (Fchange = 6.89, p = 0.01, Table 3). The results did not change when potential confounders (variables that were associated with ADHD symptom variable or HCC), i.e. ODD/CD, anxiety/depressive symptoms of child, family adversity and maternal ADHD symptoms, were controlled (Table 3). Probing the significant interaction effect (Aiken and West, 1991; Cohen et al., 2003) revealed a significant negative linear regression of ADHD symptoms on HCC in the male subgroup (ADHD symptom groups: ß = −.27, t = 2.01, p < .05; ADHD symptom score: ß = −.35, t = 2.67, p < .01), while the regression was not significant in the female subgroup (ADHD symptom groups: ß = .10, t = 0.78; ADHD symptom score: ß = .16; t = 1.26). Boys with elevated ADHD symptoms thus showed lower HCC, while in girls, HCC and ADHD symptoms were not associated (see Fig. 1).

3. Results 3.1. Associations among study variables and between study and control variables For validation purposes, to facilitate the interpretation of results, and to determine those control variables that have to be adjusted, correlations among the study variables and between study and control variables were calculated (Table 2). HCC was significantly associated with gender of the child and family adversity. Boys showed a significantly higher HCC than girls and children with a family adversity background showed a lower HCC than those without such a background (Table 2). Family psychosocial adversity was also associated with more pronounced ADHD symptoms. To further explore these latter links, we calculated the correlation coefficients between each of the single psychosocial risks with HCC and the ADHD symptom score (Table 2). The risk factors of unwanted pregnancy, parental broken home background, and early parenthood were significantly associated with lower HCC. Elevated ADHD symptoms were significantly associated with parental separation. Both ADHD symptom variables were (nearly) significantly associated with anxiety/depressive and ODD/CD symptoms of the child and with maternal ADHD symptoms (Table 2). In the following, we therefore adjusted for these control variables.

3.4. Moderator effect by family adversity The interaction effects between family adversity and ADHD symptom groups on HCC was not significant (adversity × ADHD symptom groups: Fchange = 0.70). The interaction effect between family adversity and ADHD symptom score also did not reach statistical significance (adversity × ADHD symptom score: Fchange = 0.74). Thus, in the presence of a family psychosocial adversity background, ADHD symptoms were not, in general, more closely associated with HCC than in the absence of family adversity. Further exploratory analyses,

Table 2 Intercorrelations of the study variables. 1 1: ADHD symptom groups 2: ADHD symptom composite score 3: HCC 4: family adversity - low education level of parent - overcrowded living conditions - parent with broken home background - early parenthood - parental separation - unwanted pregnancy 5: gender of child 6: ODD/CD symptoms 7: anxiety/depressive symptoms 8: maternal ADHD symptoms

–

2 .64 –

3 ***

4

5

6

7

8

−.07 −.02

.05 .19*

.09 −.14

.31 .48***

.23 .35**

.16 .21*

–

−.29** –

−.20* .02

−.09 .03

−.07 .16

.04 .13

−.16 –

.00 .55*** –

−.06 .18 .29*** –

.08 −.06

.14 .03

−.11 −.03

.12

.05

−.23**

−.03 .14 −.11

.03 .21* .02

−.21* −.08 −.24**

***

***

Correlation coefficients among study and control variables are listed above the diagonal; correlation coefficients between the single family adversity factors and ADHD symptom variables and HCC are listed below the diagonal. ADHD: attention deficit/hyperactivity disorder; ODD/CD: oppositional defiant disorder/conduct disorder; HCC: hair cortisol concentration. * p < .05. ** p < .01. *** p < .001.

29

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Table 3 Association between HCC and ADHD symptoms (groups/scores): Interaction effect with gender of child. Multiple hierarchical linear regression analyses A. Interaction effect between ADHD symptom groups and gender Criterion: HCC Step Variable(s) added

R

R2change

Fchange(df)

pchange

Model A1: 1 2 3 4

.29 .35 .35 .39

0.08 0.04 0.00 0.03

10.53 (1,118) 4.93 (1,117) 0.24 (1,116) 3.97 (1,115)

.002 .028 .625 .049

.30

0.09

11.43 (3,116)

.012

.37 .37 .41

0.04 0.00 0.03

5.91 (1,115) 0.28 (1,114) 3.94 (1,113)

.017 .930 .049

Multiple hierarchical linear regression analyses B. Interaction effect between ADHD symptom composite scores and gender of child Criterion: HCC Step Variable(s) added R

R2change

Fchange(df)

pchange

Model B1: 1 2 3 4

.29 .35 .35 .41

0.08 0.04 0.00 0.05

10.53 (1,118) 4.93 (1,117) 0.00 (1,116) 6.89 (1,115)

.002 .028 .999 .010

.31

0.10

3.15 (4,115)

.017

.38 .38 .44

0.04 0.00 0.05

5.56 (1,114) 0.28 (1,113) 7.24 (1,112)

.020 .598 .008

family adversity gender of child ADHD symptom groups gender × ADHD symptom groups

Model A2: adjustment for control variables 1 family adversity ODD/CD symptoms anxiety/depressive symptoms maternal ADHD symptoms 2 gender of child 3 ADHD symptom groups 4 gender × ADHD symptom groups

family adversity gender of child ADHD symptom score gender × ADHD symptom score

Model B2: adjustment for control variables 1 family adversity ODD/CD symptoms anxiety/depressive symptoms maternal ADHD symptoms 2 gender of child 3 ADHD symptom score 4 gender × ADHD symptom score

ADHD: attention deficit/hyperactivity disorder; ODD/CD: oppositional defiant disorder/conduct disorder; HCC: hair cortisol concentration.

while no such association emerged in girls. This effect was most pronounced in the presence of high adversity, indicating that boys with elevated ADHD symptoms showed lower HCC particularly when exposed to family adversity. The present study is the first to investigate HCC in the context of ADHD. Underscoring the validity of measurement in the present study, in line with the results of previous research, we found HCC to be significantly higher in boys than in girls (see the meta-analysis by Stalder et al., 2017) and significantly lower in children exposed to family adversity than in children without such adversity (see the review by Struber et al., 2014). A detailed exploratory analysis, moreover, revealed that risk factors indicating prolonged inadequate parental care (e.g. unwanted pregnancy, early parenthood) primarily caused this association. In this respect, our finding corresponds well to Struber et al.’s (2014) notion that HPAA hypo-activity results from environmental adversity, which is accompanied by an absence or a low quality of parental care. Our finding of no general link between HCC and ADHD/externalizing symptoms is in line with the results of recent studies in preschool children (e.g. Hill-Soderlund et al., 2015; Saridjan et al., 2014). The finding of a stronger link in boys than in girls corresponds to the results of some of the studies in school-aged children (Pesonen et al., 2011). However, other studies revealed contradictory results. The inconsistencies have been assumed to be at least partly attributable to comorbid symptoms of ODD/CD or anxiety/depression (Northover et al., 2016). In the present study, however, we controlled for these comorbid symptoms. Therefore, it is more probable that the use of HCC facilitated the identification of the moderator effect of gender in the

however, showed that the interaction effects between ADHD symptom group/score and gender was statistically significant in the subgroup of children with high family psychosocial adversity and was not significant in children with low family adversity (Table 4). Thus, in the context of family psychosocial adversity, in particular boys with elevated ADHD symptoms showed lower HCC, while in the context of low family adversity, no association between ADHD symptoms and HCC emerged either in boys or in girls (Fig. 2). 4. Discussion Results of previous studies on the association between HPAA activity and ADHD or externalizing symptoms have often been inconsistent, particularly in younger children. This might be attributable to the etiological and phenotypic heterogeneity of the disorders, making moderator effects of variables probable, which circumscribe more homogenous subgroups. Moreover, the previously used measures for HPAA activity reflect rather short-term, state-dependent cortisol secretion patterns, which might be less suitable for capturing the basal activity of the HPAA. Using HCC to assess the accumulated, integrated long-term HPAA activity in a community-based preschool sample, we expected to find the overall negative association between HPAA activity and ADHD symptoms that has been described in older children as well as moderator effects by gender of child and exposure to family adversity. We found no general association with ADHD symptoms. The association depended on the child’s gender and his/her exposure to family adversity: Boys with elevated ADHD symptoms showed a lower HCC, 30

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Table 4 Interaction effects between ADHD symptoms and gender on HCC within subgroups of children with and without family adversity. Children with family adversity Modela

Interaction effect (Step 2)

A1 A2 B1 B2

gender × ADHD gender × ADHD gender × ADHD gender × ADHD

Children A1 A2 B1 B2

R

R2change

Fchange(df)

pchange

symptom symptom symptom symptom

groups groups scores scores

.41 .47 .42 .49

0.12 0.10 0.13 0.11

7.37 6.15 7.60 6.54

(1,50) (1,48) (1,50) (1,47)

.009 .017 .008 .014

without family adversity gender × ADHD symptom gender × ADHD symptom gender × ADHD symptom gender × ADHD symptom

groups groups scores scores

.23 .24 .24 .27

0.00 0.00 0.02 0.02

0.11 0.10 1.03 0.98

(1,62) (1,60) (1,62) (1,59)

.746 .753 .315 .327

A1: Step 1: gender of child, ADHD symptom groups; Step 2: gender × ADHD symptom groups. A2: Step 1: ODD/CD symptoms, anxiety/depressive symptoms, maternal ADHD, gender of child, ADHD symptom groups; Step 2: gender × ADHD symptom groups. B1: Step 1: gender of child, ADHD symptom score; Step 2: gender × ADHD symptom score. B2: Step 1: ODD/CD symptoms, anxiety/depressive symptoms, maternal ADHD, gender of child, ADHD symptom score; Step 2: gender × ADHD symptom score. a Hierarchical regression models.

(2016) regarding the higher environmental (and genetic) effects on ADHD symptoms in boys. Therefore, the finding is in line with the notion that prolonged early adversity leads to neurobiological vulnerability, which causes on the one hand HPAA dysregulation and on the other hand ADHD symptoms specifically in boys. However, there are further possible explanations for this finding. For example, family adversity might have triggered the development of ADHD symptoms and low HCC in boys with a specific genetic disposition (Laucht et al., 2007; Ouellet-Morin et al., 2009). Formal or molecular genetic analyses are necessary to determine this. Our results might stimulate corresponding research analyzing the mechanisms underlying the links between HCC and emerging ADHD symptoms in more detail. The following limitations might be seen in the present study: A consideration of neuropsychological indicators of cognitive endophenotypes of the children might have provided more insights into the mechanisms underlying the obtained links. Moreover, although the present sample size is comparatively large in the context of HCC, an even larger sample would have allowed for a more in-depth analysis, e.g. of the different components of family psychosocial adversity. To conclude, in the present study, we showed that the association between ADHD symptoms and HPAA activity (as indicated by HCC) was modified by gender of the child. This moderator effect, moreover, was specifically pronounced under the condition of exposure to family adversity. These results are in line with findings of stronger genetic as well as environmental effects on ADHD symptoms in boys than in girls. HCC might indicate specific ADHD-related pathways at an early developmental stage. In future research, moderator effects by gender and family adversity on links between HPAA parameters and ADHD should be considered and further circumscribed to facilitate analyses of the mechanisms that underlie these links.

Fig. 1. Illustration of the significant interaction effects of (a) gender × ADHD symptom group and (b) gender × ADHD symptom score on HCC. Variables have been standardized. (a) Solid line: regression of HCC on ADHD symptom group (y = −.27x, p < .05) in boys; Dotted line: regression of HCC on ADHD symptom group (y = .10x) in girls. (b) Solid line: regression of HCC on ADHD symptom score (y = −.35x, p < .01) in boys; Dotted line: regression of HCC on ADHD symptom score (y = .16x) in girls.

preschoolers. Gender differences in ADHD prevalence and severity are not yet completely understood. A recent large-scale twin study revealed a probably genetically-based female protective effect against ADHD. In girls, ADHD-related genetic and environmental factors were less strongly associated with the behavioral symptoms of the disease (Taylor et al., 2016). Accordingly, one might also expect to find weaker associations between biological markers of ADHD and the behavioral symptoms of the disease in girls. Moreover, gender differences in ADHD symptoms have recently been found to be partially based on differences in cognitive endophenotypes such as working memory, processing speed, and inhibitory control (Arnett et al., 2015), which (besides other brain regions) involve the dorsolateral prefrontal cortex and the hippocampus. These structures, on the other hand, are significantly involved in the regulation of HPAA activity (Lupien et al., 2009). It might therefore be that specific ADHD-related deviations of these brain regions, which are more pronounced in boys than in girls, affect developing HPAA functioning. As ADHD-related cognitive endophenotypes can be validly captured in preschool years (see Pauli-Pott and Becker, 2011), in future research it would be worthwhile to analyze whether ADHD-related cognitive endophenotypes mediate the association between HCC and ADHD symptoms differently in boys and girls. The moderator effect of gender emerged exclusively in the presence of family adversity, i.e., under this condition, boys with elevated ADHD symptoms showed lower HCC, while the link was not significant in girls. This finding has to be regarded as descriptive and should be interpreted with caution. Nevertheless, it corresponds well to those studies which found attention problems to be associated with HPAA dysregulation in the presence of environmental adversity (Ouellet-Morin et al., 2011) as well as to the above-mentioned finding by Taylor et al.

Funding The research for this article was funded by a grant from the German Research Foundation (DFG, Be2573/3-1,2) to Prof. Dr. Katja Becker and Prof. Dr. Ursula Pauli-Pott.

Conflicts of interest None. 31

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Fig. 2. Illustration of the interaction effects of gender × ADHD symptom group and gender × ADHD symptom score on HCC in children with (b, d) and without (a, c) family adversity. Variables have been standardized. (a) Solid line: regression of HCC on ADHD symptom group (y = −.17x) in boys without family adversity; Dotted line: regression of HCC on ADHD symptom group (y = −.07x) in girls without family adversity. (b) Solid line: regression of HCC on ADHD symptom group (y = −.50x, p = .015) in boys with family adversity; Dotted line: regression of HCC on ADHD symptom group (y = .31x) in girls with family adversity. (c) Solid line: regression of HCC on ADHD symptom score (y = −.23x) in boys without family adversity; Dotted line: regression of HCC on ADHD symptom score (y = .03x) in girls without family adversity. (d) Solid line: regression of HCC on ADHD symptom score (y = −.44x, p = .037) in boys with family adversity; Dotted line: regression of HCC on ADHD symptom score (y = .35x) in girls with family adversity. 189–205. Döpfner, M., Görtz-Dorten, A., Lehmkuhl, G., 2008. DISYPS-II Diagnostik-System für psychische Störungen nach ICD-10 und DSM-IV für Kinder und Jugendliche—II. Huber, Bern. Daley, D., 2010. Preschool-Parent Account of Child Symptoms. Pre-Pacs. Egger, H.L., Angold, A., 2006. Common emotional and behavioral disorders in preschool children: presentation, nosology, and epidemiology. J. Child Psychol. Psychiatry 47, 313–337. Gortz-Dorten, A., Ise, E., Hautmann, C., Walter, D., Dopfner, M., 2014. Psychometric properties of a German parent rating scale for oppositional defiant and conduct disorder (FBB-SSV) in clinical and community samples. Child Psychiatry Hum. Dev. 45, 388–397. Gunnar, M.R., Talge, N.M., Herrera, A., 2009. Stressor paradigms in developmental studies: what does and does not work to produce mean increases in salivary cortisol. Psychoneuroendocrinology 34, 953–967. Hill-Soderlund, A.L., Holochwost, S.J., Willoughby, M.T., Granger, D.A., Gariepy, J.L., Mills-Koonce, W.R., Cox, M.J., 2015. The developmental course of salivary alphaamylase and cortisol from 12 to 36 months: relations with early poverty and later behavior problems. Psychoneuroendocrinology 52, 311–323. Isaksson, J., Nilsson, K.W., Lindblad, F., 2013. Early psychosocial adversity and cortisol levels in children with attention-deficit/hyperactivity disorder. Eur. Child Adoles. Psychiatry 22, 425–432. Kirschbaum, C., Steyer, R., Eid, M., Patalla, U., Schwenkmezger, P., Hellhammer, D.H., 1990. Cortisol and behavior. 2. Application of a latent state-trait model to salivary cortisol. Psychoneuroendocrinology 15, 297–307. Koss, K.J., Mliner, S.B., Donzella, B., Gunnar, M.R., 2016. Early adversity, hypocortisolism, and behavior problems at school entry: a study of internationally adopted children. Psychoneuroendocrinology 66, 31–38. Laucht, M., Skowronck, M.H., Becker, K., Schmidt, M.H., Esser, G., Schulze, T.G., Rietschel, M., 2007. Interacting effects of dopamine transporter gene and psychosocial adversity on attention-deficit/hyperactivity disorder symptoms among 15-yearolds from a high-risk community sample. Arch. Gen. Psychiatry 64, 585–590. Laurent, H.K., Neiderhiser, J.M., Natsuaki, M.N., Shaw, D.S., Fisher, P.A., Reiss, D., Leve, L.D., 2014. Stress system development from age 4.5–6: family environment predictors and adjustment implications of HPA activity stability versus change. Dev. Psychobiol. 56, 340–354. Lupien, S.J., McEwen, B.S., Gunnar, M.R., Heim, C., 2009. Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nat. Rev. Neurosci. 10, 434–445. Marsman, R., Swinkels, S.H.N., Rosmalen, J.G.M., Oldehinkel, A.J., Ormel, J., Buitelaar, J.K., 2008. HPA-axis activity and externalizing behavior problems in early adolescents from the general population: the role of comorbidity and gender—The TRAILS

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