Different Risk Factors Between Disruptive Behavior Disorders and ADHD in Northern Finland Birth Cohort 1986

Abstract

Objective: To examine different risk factors between disruptive behavior disorders (DBD) and ADHD or combined DBD and ADHD. Method: The study population was derived from the Northern Finland Birth Cohort 1986. Psychiatric diagnoses were defined from the Schedule for Affective Disorders and Schizophrenia for School-Age Children–Present and Lifetime Version (K-SADS-PL) interview. The study sample was divided into four groups—people with DBD (n = 44), with ADHD (n = 91), with both (n = 72), and without either (n = 250)—to evaluate the different risk factors behind these disorders. Results: After adjusting with possible confounding factors, female gender and paternal admittance to inpatient psychiatric care increased the odds that an adolescent was having DBD. Childhood hyperactivity symptoms increased the odds of having ADHD and childhood hyperactivity symptoms and scholastic impairment increased the odds of having both disorders. Conclusion: Our study indicates DBD and ADHD have clearly different risk factors, and the impact of the paternal factors on DBD should be noted more than has been before.

Keywords

disruptive behavioral disorder ADHD conduct disorder oppositional defiant disorder comorbidity

Introduction

Disruptive behavior disorders (DBD) and ADHD are common and co-occurring psychiatric disorders among children and adolescents (Angold, Costello, & Erkanli, 1999).

Conduct disorder (CD) and oppositional defiant disorder (ODD) can be referred to as DBD (Steiner, Remsing, & Work Group on Quality Issues, 2007). CD is described as a repetitive and persistent pattern of antisocial, aggressive, or defiant conduct that extends beyond ordinary levels of childish mischief or adolescent rebelliousness (American Psychiatric Association [APA], 2000, World Health Organization [WHO], 1993). ODD occurs in younger children and is characterized by markedly defiant, disobedient, disruptive behavior, which do not include severe aggressive or antisocial behavior as in CD (APA, 2000; WHO, 1993). Childhood-onset ADHD is characterized by the symptoms of inattention, impulsivity, and hyperactivity (APA, 2000; WHO, 1993).

There are many studies about the risk factors of DBD or ADHD. An association has been found between maternal smoking during pregnancy and CD (Fergusson, Horwood, & Lynskey, 1993; Fergusson, Woodward, & Horwood, 1998; Wakschlag, Pickett, Cook, Benowitz, & Leventhal, 2002; Weitzman, Gortmaker, & Sobol, 1992), with an indirect or confounded way with other known and unknown developmental risk factors (Maughan, Taylor, Caspi, & Moffitt, 2004; Silberg et al., 2003). Low socioeconomic status (SES) of the parent and parental substance abuse has been found to predict the onset of CD (Loeber, Green, Keenan, & Lahey, 1995). Several family-related problems (Fergusson & Horwood, 1998) and a broken original family (especially among girls) have seemed to increase the risk of CD (Ilomäki et al., 2006). These days ADHD has been suggested being mostly heritable (Levy, Hay, McStephen, Wood, & Waldman, 1997; Williams et al., 2010). ADHD has also been associated with pregnancy and delivery complications such as preterm birth and low birth weight (Mick, Biederman, Prince, Fischer, & Faraone, 2002; Thapar, Cooper, Jefferies, & Stergiakouli, 2012). In various studies, ADHD or hyperactivity have also been associated with maternal smoking and/or substance abuse in pregnancy (Kotimaa et al., 2003; Linnet et al., 2003; Motlagh et al., 2011) although many of these studies have agreed ADHD being heritable and smoking relating to mother’s ADHD (Knopik et al., 2006; Knopik et al., 2005; Obel et al., 2011; Thapar et al., 2009). Also paternal smoking has been found to have an effect on attention control in children with ADHD (Altink et al., 2009).

However, there are not many studies which would evaluate the possibly different risk factors distinguishing these disorders as separate groups based on the presence of the comorbidity between these disorders. The prospectively collected data in the Northern Finland Birth Cohort (NFBC) 1986 make it possible to investigate a wide range of prenatal and early childhood factors and their possible associations for these psychiatric disorders. Therefore, we set it as our aims to examine more the comorbidity of DBD and ADHD compared with just one of these disorders. We were especially interested in biological and psychosocial factors that possibly affect the development of DBD and ADHD.

Method

Participants and Procedure

The NFBC 1986 is a prospective longitudinal study that consists of 9,432 children born alive in Northern Finland between July 1, 1985 and June 30, 1986 (Järvelin, Hartikainen-Sorri, & Rantakallio, 1993). Data have been collected during pregnancy, birth, when children were 7 to 8 years old (Taanila, Ebeling, Kotimaa, Moilanen, & Järvelin, 2004) and again when adolescents were 16 years old (Smalley et al., 2007). This study combines information about all of these follow-ups.

As we were interested in various biological and psychosocial factors that possibly affect the development of DBD and/or ADHD, we selected gender, two factors indicating birth complications—being born as small for gestational age (SGA) and preterm birth, two factors indicating the exhaustion of the mother during pregnancy—having unwanted pregnancy and the tiredness of the mother during pregnancy, parental smoking and alcohol drinking, having a single-parent family and lower SES, being the only child in the household, urban living environment, childhood hyperactivity symptoms, scholastic impairment, poor social coping with other children, and parental admittance to inpatient psychiatric care into our analyses.

Information about prenatal and birth outcomes was systematically collected at the antenatal clinics and birth hospital via self-report questionnaires and the delivery records (Järvelin et al., 1993). Infant birth weight was classified as SGA if weight was below the 10th percentile for gestational age in the birth cohort. Birth before 37 weeks gestational age was considered preterm. Unwanted pregnancy at the time was defined if the mother had admitted that the pregnancy was not wanted or wanted rather later than it occurred. The tiredness of the mother during pregnancy was defined if the mother had herself felt tired during pregnancy. Prenatal exposure to maternal smoking was defined as smoking prior to or at the time of conception and continuation of smoking after the 6th gestational week. Maternal alcohol drinking was defined if mother admitted drinking alcohol during pregnancy. Father was defined as a smoker if he had smoked one or more years and smoked more than five cigarettes, pipefuls or cigars per day. Paternal alcohol drinking was defined if father had drunk alcohol 2 to 3 times (or more) in a month and 5 to 20 (or more) drinks in a week.

Mothers provided information of the family and child development via postal questionnaire when children were 7 or 8 years old (Taanila et al., 2004). The structure of the family was classified as single-parent family if the child had one biological divorced, separated, or widowed parent or the mother of the child had never been married or co-habitated with the child’s father. SES of the family was defined as lower SES if both parents had stated being students, unoccupied, or were receiving pensions. The number of the children in the household, the living environment, and social coping were obtained directly from the postal questionnaire.

The permission to contact the child’s teacher was also included in the postal questionnaire. After admitting the permissions, the teachers of the children were contacted, and they assessed hyperactivity/inattention symptoms using the Rutter scale for teachers (RB2; Rutter, 1967). The hyperactivity/inattention subscale encompasses two hyperactivity items and one on inattention. Items are scored as 0 (not true), 1 (somewhat true), or 2 (certainly true). A child was considered having hyperactive/inattentive symptoms if he or she had a total score of 3 or more on these items. Teachers also assessed deficits in each core subject (reading, writing, and mathematical skills) as impaired/unimpaired. We defined scholastic impairment as impairment in at least one core subject.

The cohort was again followed-up in 2001, when adolescents were 15 to 16 years old, again with a postal questionnaire (Smalley et al., 2007). The questionnaire included a screening instrument for ADHD (the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior [SWAN] scale; Swanson et al., 2001). Based on the screening results of the SWAN scale, study population was divided into following categories: (a) likely ADHD cases (n = 530), (b) controls (n = 5,694), and (c) those who were neither (n = 389), and thereby excluded from further analyses. Eight hundred two adolescents (all likely ADHD cases who were living in Oulu or Lapland provinces, n = 487, and a random sample of controls, matched by geographical location, gender, and birth year, n = 315) were invited to participate in a clinical study focused on ADHD (Smalley et al., 2007). A total of 464 adolescents participated and their psychiatric diagnoses were obtained via the semi-structured Schedule for Affective Disorders and Schizophrenia for School-Age Children–Present and Lifetime Version (K-SADS-PL; Kaufman et al., 1997), conducted by master’s-level interviewers with the adolescents and their parents. All interviews were recorded by video or audiotape and the child and adolescent psychiatrists from the Oulu University Hospital and University of California, Los Angeles, confirmed all diagnoses. Interrater reliability was estimated as good (for ADHD Cohen’s kappa was 0.70, for other diagnoses Cohen’s kappa was 0.77; Hurtig, 2007). Seven adolescents were excluded due to mild mental retardation or genetic abnormality resulting in 457 adolescents with valid K-SADS-PL interview.

The study sample was divided into four groups: those who have been diagnosed with (a) only DBD, (b) only ADHD, (c) combined DBD and ADHD, and (d) no DBD or ADHD group (who had no record of having a diagnosis with any of these three disorders). This composition made it possible to evaluate the role of DBD comorbid with ADHD in different combinations (Figure 1).

Figure 1.

The chart of the participation flow.

Parental psychiatric history was obtained via the Finnish Hospital Discharge Register (FHDR). The FHDR includes information on all inpatient admissions to hospitals with discharge dates and diagnoses. Sund (2012) has concluded that the completeness and accuracy of the FHDR ranges from satisfactory to very good. Registration in FHDR is mandatory for all inpatient care in public and private hospitals. A parent was defined having some psychiatric disorder if he or she was hospitalized and diagnosed with any psychiatric disorder (International Classification of Diseases [ICD]; ICD-8 290-315, ICD-9 290-319, or ICD-10 F00-F99) before 2001.

Statistical Analysis

All statistical work was completed by IBM SPSS Statistics 19.0 (SPSS, Inc., 1989, 2010, an IBM company). The associations between prenatal and early childhood factors, and DBD, ADHD, and DBD & ADHD were examined with contingency tables and tested with Pearson’s chi-square test and Fisher’s exact test when appropriate. The multinomial logistic regression analysis was completed first to obtain unadjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) and then adjusted ORs and CIs for those variables that reached significance level below p = .1 in unadjusted analysis. Bonferroni correction was used to control the possible multiple comparison problems. All tests were two-tailed and the level for statistical significance was set as p < .05.

Results

According to the K-SADS-PL interview, there were a total of 116 study participants with DBD: 50 adolescents were diagnosed with both CD and ODD, 28 with only CD, and 38 with only ODD. Total of 163 adolescents were diagnosed with ADHD. These diagnoses were categorized into three mutually exclusive groups (Figure 1).

Using cross-tabulation with chi-square tests (or exact tests when appropriate), the preliminary results showed that several factors were associated with people with DBD and/or ADHD (Table 1). Especially strong associations were found with gender (more boys in all other groups than in DBD group where girls were the majority), single-parent family (more in DBD & ADHD group than others), childhood hyperactivity (more in ADHD and DBD & ADHD groups), scholastic impairment (more in ADHD and DBD & ADHD groups), and paternal admittance to inpatient psychiatric care (more in DBD group). After correcting the findings for the possible multiple comparison problems, only gender and childhood hyperactivity remained as statistically significant.

Table 1.

The Associations Between Prenatal and Early Childhood Factors and DBD and ADHD.

	None	DBD	ADHD	DBD & ADHD
Article I.	n (%)	n (%)	n (%)	n (%)	p	p ^a
Prenatal factors
Gender
Boys	155 (62)	17 (39)	70 (77)	47 (65)	<.001	**
Girls	95 (38)	27 (61)	21 (23)	25 (35)
SGA	2 (1)	0 (0)	2 (2)	1 (1)	.610^b
Preterm birth	15 (6)	1 (2)	4 (4)	3 (4)	.840^b
Unwanted pregnancy at the time	22 (10)	3 (8)	6 (8)	6 (9)	.937
Mother tired during pregnancy	47 (23)	10 (28)	17 (23)	22 (36)	.249
Maternal smoking during pregnancy	56 (23)	13 (31)	24 (28)	17 (25)	.664
Maternal alcohol drinking	32 (13)	6 (15)	9 (10)	12 (17)	.660
Paternal smoking	65 (26)	19 (43)	24 (26)	26 (36)	.060
Paternal alcohol drinking	17 (7)	3 (7)	10 (11)	3 (4)	.390
Family variables (7-8 years)
Single-parent family	14 (6)	2 (5)	7 (8)	13 (20)	.003
Lower socioeconomic status	14 (6)	1 (2)	2 (2)	5 (8)	.409^b
Only child	17 (8)	7 (16)	8 (9)	6 (10)	.347
Urban living environment	80 (33)	10 (23)	33 (38)	27 (42)	.209
School and friends (8 years)
Hyperactivity	9 (4)	3 (7)	15 (17)	17 (27)	<.001	***
Scholastic impairment	52 (23)	11 (26)	26 (30)	29 (47)	.003
Does not cope well with others	51 (23)	12 (28)	27 (21)	18 (29)	.422
Parental admittance to inpatient psychiatric care
Mother	10 (4)	3 (7)	2 (2)	4 (6)	.494
Father	13 (5)	9 (21)	11 (12)	7 (10)	.005

Note. DBD = disruptive behavior disorders; SGA = small for gestational age.

Statistical significance after using the Bonferroni correction: *p < .05. **p < .01. ***p < .001.

p value from Fisher’s Exact Test.

More information and the distributions of parental admittance to inpatient psychiatric care until 2001 are available in Supplementary Table. The diagnoses spread widely but the association between paternal substance abuse/dependence disorders and study groups was statistically significant (Fisher’s Exact Test p = .012), and anxiety (Fisher’s Exact Test p = .055) and psychotic (Fisher’s Exact Test p = .070) disorders of the father and maternal substance abuse/dependence disorders (Fisher’s Exact Test p = .064) showed a trend toward the statistical significance.

Further analysis applied unadjusted multinomial logistic regression analysis to examine the possible associations between biological and psychosocial factors and the people with DBD and/or ADHD (Table 2). Male gender (OR = 0.4, 95% CI = [0.2, 0.8]), paternal smoking (OR = 2.2, 95% CI = [1.1, 4.2]), and paternal admittance to inpatient psychiatric care (OR = 4.7, 95% CI = [1.9, 11.8]) seemed to associate with DBD; male gender (OR = 2.0, 95% CI = [1.2, 3.5]), childhood hyperactivity (OR = 5.1, 95% CI = [2.1, 12.1]), and paternal admittance to inpatient psychiatric care (OR = 2.5, 95% CI = [1.1, 5.8]) with ADHD; and single-parent family (OR = 4.0, 95% CI = [1.8, 9.1]), childhood hyperactivity (OR = 9.0, 95% CI = [3.8, 21.5]), and scholastic impairment (OR = 3.0, 95% CI = [1.7, 5.4]) with the comorbid group, all with statistical significance. After correcting the findings for the possible multiple comparison problems, only statistically significant associations were paternal admittance to inpatient psychiatric care for DBD, childhood hyperactivity for ADHD and single-parent family, and hyperactivity and scholastic impairment for the comorbid group.

Table 2.

The Unadjusted Multinomial Logistic Models for Prenatal and Early Childhood Factors and Pure DBD, Pure ADHD, and Comorbid DBD & ADHD.

	DBD				ADHD				Comorbid DBD & ADHD
	OR	95% CI	p	p ^a	OR	95% CI	p	p ^a	OR	95% CI	p	p ^a
Prenatal factors
Gender: Boys	0.39	[0.20, 0.75]	.005		2.04	[1.18, 3.54]	.011		1.15	[0.67, 1.99]	.612
SGA	n.e.				2.81	[0.39, 20.3]	.305		1.76	[0.16, 19.7]	.647
Preterm birth	0.36	[0.05, 2.83]	.334		0.72	[0.23, 2.23]	.569		0.68	[0.19, 2.42]	.553
Article II. Unwanted pregnancy at the time	0.79	[0.22, 2.79]	.714		0.76	[0.30, 1.94]	.562		0.91	[0.35, 2.35]	.847
Mother tired during pregnancy	1.26	[0.57, 2.80]	.571		0.96	[0.51, 1.81]	.900		1.80	[0.98, 3.33]	.060
Maternal smoking during pregnancy	1.48	[0.72, 3.04]	.285		1.28	[0.73, 2.23]	.388		1.08	[0.58, 2.02]	.809
Maternal alcohol drinking	1.15	[0.45, 2.95]	.776		0.74	[0.34, 1.62]	.452		1.32	[0.64, 2.73]	.450
Paternal smoking	2.16	[1.12, 4.19]	.022		1.02	[0.59, 1.76]	.945		1.61	[0.92, 2.81]	.095
Paternal alcohol drinking	1.00	[0.28, 3.58]	.996		1.69	[0.75, 3.85]	.209		0.60	[0.17, 2.09]	.419
Family variables (7-8 years)
Single-parent family	0.81	[0.18, 3.69]	.782		1.43	[0.56, 3.67]	.457		4.04	[1.79, 9.10]	.001	*
Lower socioeconomic status	0.39	[0.05, 3.05]	.370		0.39	[0.09, 1.75]	.220		1.36	[0.47, 3.92]	.574
Only child	2.37	[0.92, 6.11]	.075		1.25	[0.52, 3.01]	.621		1.31	[0.49, 3.46]	.593
Urban living environment	0.61	[0.28, 1.29]	.195		1.25	[0.75, 2.08]	.400		1.42	[0.81, 2.49]	.220
School and friends (8 years)
Hyperactivity	1.83	[0.48, 7.07]	.379		5.09	[2.14, 12.1]	<.001	**	9.03	[3.79, 21.5]	<.001	***
Scholastic impairment	1.17	[0.55, 2.48]	.682		1.45	[0.83, 2.52]	.188		2.99	[1.66, 5.38]	<.001	**
Does not cope well with others	1.30	[0.63, 2.73]	.478		1.54	[0.89, 2.68]	.124		1.38	[0.73, 2.59]	.318
Parental admittance to inpatient psychiatric care
Mother	1.76	[0.46, 6.65]	.407		0.54	[0.12, 2.51]	.431		1.41	[0.43, 4.64]	.570
Father	4.69	[1.87, 11.8]	.001	*	2.51	[1.08, 5.82]	.032		1.96	[0.75, 5.12]	.168

Note. DBD = disruptive behavior disorders; SGA = small for gestational age; n.e. = not estimated.

The ORs reaching statistical significance (p < .05) are in boldface.

The statistical significance after using the Bonferroni correction: *p < .05. **p < .01. ***p < .001.

The multinomial logistic regression model was then adjusted by including all statistically significant factors and those factors showing some trend toward the statistical significance (p ≤ .1) into the model. Gender, mother’s tiredness during pregnancy, paternal smoking, single-parent family, being the only child, childhood hyperactivity, scholastic impairment, and paternal admittance to inpatient psychiatric care remained therefore in the model (Table 3).

Table 3.

The Adjusted Multinomial Logistic Models for Prenatal and Early Childhood Factors and Pure DBD, Pure ADHD, and Comorbid DBD & ADHD.

	DBD				ADHD				Comorbid DBD & ADHD
	OR	95% CI	p	p ^a	OR	95% CI	p	p ^a	OR	95% CI	p	p ^a
Prenatal factors
Gender: Boys	0.40	[0.18, 0.89]	.025		1.63	[0.86, 3.07]	.134		0.84	[0.40, 1.75]	.637
Mother tired during pregnancy	1.15	[0.48, 2.75]	.746		0.81	[0.40, 1.65]	.569		1.46	[0.68, 3.14]	.335
Paternal smoking	1.80	[0.81, 4.02]	.150		0.72	[0.37, 1.42]	.347		1.34	[0.64, 2.80]	.441
Family variables (7-8 years)
Single-parent family	0.20	[0.02, 2.12]	.180		1.16	[0.35, 3.90]	.807		2.69	[0.82, 8.78]	.102
Only child	3.34	[0.95, 11.8]	.061		1.68	[0.58, 4.87]	.341		0.76	[0.20, 2.92]	.684
School and friends (8 years)
Hyperactivity	2.45	[0.56, 10.8]	.236		3.31	[1.19, 9.22]	.022		7.41	[2.60, 21.1]	<.001	**
Scholastic impairment	1.55	[0.65, 3.73]	.325		1.50	[0.78, 2.88]	.229		3.13	[1.52, 6.44]	.002	*
Parental admittance to inpatient psychiatric care
Father	4.54	[1.46, 14.1]	.009		2.40	[0.82, 7.00]	.110		1.65	[0.48, 5.74]	.428

Note. DBD = disruptive behavior disorders.

The ORs reaching statistical significance (p < .05) are in boldface.

The statistical significance after using the Bonferroni correction: *p < .05. **p < .01. ***p < .001.

After adjusting the model, male gender (OR = 0.4, 95% CI = [0.2, 0.9]) and paternal admittance to inpatient psychiatric care (OR = 4.5, 95% CI = [1.5, 14.1]) remained statistically significant associations for people with pure DBD. In addition, being the only child in the family (OR = 3.3, 95% CI = [1.0, 12.0]) achieved some trend toward the statistical significance. The childhood hyperactivity (OR = 3.3, 95% CI = [1.2, 9.2]) was the only remaining factor associating with the group with pure ADHD with statistical significance. In the comorbid DBD and ADHD group, only childhood hyperactivity (OR = 7.4, 95% CI = [2.6, 21.1]) and scholastic impairment (OR = 3.1, 95% CI = [1.5, 6.4]) remained statistically significant. After correcting for the possible multiple comparison problems, only statistically significant associations were hyperactivity and scholastic impairment in the comorbid group.

Discussion

Our study indicates that there are clearly different factors behind DBD, ADHD, and a combination of them.

Several previous studies have stated an association between maternal smoking during pregnancy and DBD (Wakschlag et al., 2002). In contrast, we did not found such an association. This result suggests that exposure in itself may not be the key causal factor; rather, other factors associated with maternal smoking during pregnancy may have a greater impact on psychiatric problems later on for the adolescent.

Paternal smoking seemed to have some association with DBD in our study population although the effect seemed to disappear after adjusting the model. However, it is worth noticing because the studies of paternal smoking and its effects are quite rare. In general, secondhand tobacco smoke exposure at home has been found to associate with behavioral problems among pre-schoolers (Twardella et al., 2010) which indicate that there might be some effects that are worth studying. It was interesting that the alcohol drinking of parents was not influential in our study though some studies have stated that the substance abuse of both parents is associated with CD (Loeber et al., 1995). The paternal admittance to inpatient psychiatric care seemed to affect the diagnosis of DBD in adolescents. The research is often focused on the mother but based on these results, perhaps greater attention should also be directed toward the father’s influence on the well-being of children and adolescents.

Only a few early life predictors were significantly associated with people with ADHD in our study: After adjusting the multinomial logistic regression model, only childhood hyperactivity remained statistically significant. The lack of prenatal and early childhood factors affecting ADHD may be seen to support the latest research that states ADHD might be more heritable than the result of external factors (Williams et al., 2010). Despite various studies have associated ADHD or hyperactivity with parental smoking and/or substance abuse during pregnancy, our findings indicate that parental smoking during pregnancy or early childhood does not affect child’s ADHD to the extent that has been stated before. Recently, Obel et al. (2011) reached a similar conclusion with maternal smoking and hyperkinetic disorder. The previously found association may have been partly because of the comorbidity with DBD or genetic factors: Mothers with ADHD possibly cannot stop smoking during pregnancy, even if they are advised to do so.

The comorbid DBD and ADHD group was perhaps the most interesting. It was clearly different from pure DBD group and slightly different from pure ADHD group. The difference between pure ADHD group and the comorbid group was found in association with the family type and in the scholastic impairment. The children of the single-parent families seemed to have stronger risks belonging to the comorbid group as well as comorbid DBD and ADHD seemed to increase the scholastic impairment. After adjusting the model, the effect on scholastic impairment remained statistically significant. Also childhood hyperactivity achieved statistically significant associations in both models.

There were some remarks in our study population. First is the formation of the study sample that is based on the ADHD screen, which might have led to some of the pure DBD cases to be left out. That causes the relatively small number of adolescents with DBD in our study sample. However, the composition should be more valid in case of pure ADHD and combined DBD and ADHD. Second, the gender differences between disorders in our study population were quite interesting. There were more girls than boys among adolescents with DBD although it is usually opposite (Murray & Farrington, 2010). That could be explained by the fact that most of the boys were diagnosed with combined DBD and ADHD whereas the majority of the girls diagnosed only with DBD. Also, there is a possibility that some of the girls with ADHD might have been unnoticed due to the possible difficulties recognizing ADHD among them (Quinn & Wigal, 2004). In addition to all this, the study sample is rather small, which can also increase the role of coincidence. The small study sample also causes the lack of power in our analysis and the disappearance of the results after correcting for multiple comparison problems are mainly due to the small study sample. Therefore, the results should be evaluated carefully before generalizing to larger populations as such and more research is needed with larger populations.

Despite these remarks, the NFBC 1986 constitutes a unique resource that is well documented from the beginning of the study participants’ birth to the present day. NFBC 1986 also enables further studies concerning, for example, behavioral problems in future.

In conclusion, based on our research, some associations could be seen between DBD and paternal smoking and psychiatric illness, previous hyperactivity symptoms and the paternal admittance to inpatient psychiatric care associated with ADHD, and the family structure and scholastic impairment as well as childhood hyperactivity with comorbid group, but it is not possible to clearly state the trajectories that could lead to these outcomes. However, all these three clearly different findings about DBD, ADHD, and combination of them underline the observable difference found between people with one or both of these disorders. Further analyses with different study populations are needed to strengthen the findings.

Footnotes

Declaration of Conflicting Interests

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

Funding

This study was supported by the Academy of Finland (127101), the National Institute of Mental Health (MH 63706), the European Commission (QLG1-CT-2000-01643), The Alma and K. A. Snellman Foundation, The Yrjö Jahnsson Foundation, and The Foundation for Psychiatric Research, Finland.

Supplementary Material

Supplementary material is available for this article online.

Author Biographies

Tanja Nordström, MSc, is a doctoral graduate student in the Institute of Health Sciences at the University of Oulu, Finland.

Tuula Hurtig, PhD, is a post-doc researcher in the Institute of Health Sciences at the University of Oulu and in the Institute of Clinical Medicine, Department of Child Psychiatry at the University and University Hospital of Oulu, Finland.

Alina Rodriguez, PhD, is professor of psychology, Mid Sweden University, Östersund, Sweden, and Visiting professor at the Department of Epidemiology and Biostatistics, Imperial College London, London, UK.

Jukka Savolainen, PhD, is a professor in the School of Criminology at the University of Nebraska, Omaha, United States.

Arja Rautio, MD, PhD, is a research professor in the Centre for Arctic Medicine in Thule Institute at the University of Oulu, Finland.

Irma Moilanen, MD, PhD, is a professor of child psychiatry in the Institute of Clinical Medicine, Department of Child Psychiatry at the University and University Hospital of Oulu, Finland.

Anja Taanila, PhD, is a professor in the Institute of Health Sciences at the University of Oulu and in the Primary Health Care Unit at the University Hospital of Oulu, Finland.

Hanna Ebeling, MD, PhD, is a professor of child psychiatry in the Institute of Clinical Medicine, Department of Child Psychiatry at the University and University Hospital of Oulu, Finland.

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