EARLY-LIFE PREDICTORS OF INTERNALIZING

SYMPTOM TRAJECTORIES IN CHILDREN

Murray Weeks, Ph.D. ,1 John Cairney, Ph.D. ,2,3,4 T. Cameron Wild, Ph.D. ,5 George B. Ploubidis, Ph.D. ,6

Kiyuri Naicker, MSc.,1 and Ian Colman, Ph.D.1,5*

1 Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Canada; 2 Department of

Family Medicine, McMaster University, Hamilton, Canada; 3 Department of Psychiatry & Behavioural

Neurosciences, McMaster University, Hamilton, Canada; 4 Department of Clinical Epidemiology and Biostatistics,

McMaster University, Hamilton, Canada; 5 School of Public Health, University of Alberta, Edmonton, Canada;

6 Department of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene and

Tropical Medicine, London, UK.

Short title: Predictors of internalizing trajectories

Keywords: depression; anxiety; risk factors; development; epidemiology

Word count: Text: 3702; abstract: 249; Tables: 3; Figures: 1.

Conflict of Interest: All authors declare to have no conflict of interest.

* Address for correspondence: I. Colman, PhD, Department of Epidemiology and Community Medicine, University of Ottawa, 451 Smyth Road, RGN 3230C, Ottawa, ON, K1H 8M5, Canada. Tel: + 1 613 562 5800 ext. 8715; Fax: +1 613 562 5465; Email: icolman@uottawa.ca

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ABSTRACT

Background: Previous research examining the development of anxious and depressive symptoms (i.e., internalizing

symptoms) from childhood to adolescence has often assumed that trajectories of these symptoms do not vary across

individuals. The purpose of this study was to identify distinct trajectories of internalizing symptoms from childhood

to adolescence, and to identify risk factors for membership in these trajectory groups. In particular, we sought to

identify risk factors associated with early appearing (i.e., child onset) symptoms versus symptoms that increase in

adolescence (i.e., adolescent onset).

Method: Drawing on longitudinal data from the National Longitudinal Survey of Children and Youth, latent class

growth modeling (LCGM) was used to identify distinct trajectories of internalizing symptoms for 6337 individuals,

from age 4-5 to 14-15. Multinomial regression was used to examine potential early-life risk factors for membership

in a particular trajectory group.

Results: Five trajectories were identified: ‘low stable’ (68%; reference group), ‘adolescent onset’ (10%), ‘moderate

stable’ (12%), ‘high childhood’ (6%), and ‘high stable’ (4%). Membership in the ‘adolescent onset’ group was

predicted by child gender (greater odds for girls), stressful life events, hostile parenting, aggression, and

hyperactivity. Membership in the ‘high stable’ and ‘high childhood’ trajectory groups (i.e., child-onset) was

additionally predicted by maternal depression, family dysfunction, and difficult temperament. Also, several

significant gender interactions were observed.

Conclusions: Causal mechanisms for child and adolescent depression and anxiety may differ according to time of

onset, as well as child gender. Some early factors may put girls at greater risk for internalizing problems than boys.

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INTRODUCTION

Depression and anxiety are among the most common psychiatric problems among adolescents [1]. Often

collectively described as internalizing disorders, these psychiatric problems not only decrease young people’s

quality of life, but also represent a significant social and economic cost to society [2, 3]. Although most individuals

will not meet DSM criteria for internalizing disorders, sub-threshold internalizing symptoms are and have been

identified as risk factors for the development of subsequent internalizing symptoms and disorders [4, 5].

A number of studies have examined typical developmental patterns of child and adolescent internalizing

symptoms using growth curve modeling (i.e., latent curve analysis) [6] to estimate the overall rate of change of such

symptoms over time [7, 8]. However, such methods assume a common trajectory that represents the average rate of

change and thus are unsuitable for identifying different trajectories categories in a population where not all

individuals follow a common developmental course [9]. In contrast, latent class growth modeling (LCGM) is a

semi-parametric approach that is able to identify homogeneous subgroups of individuals showing distinct patterns of

change in internalizing symptoms over time [9]. Importantly, studies using LCGM have shown that some

individuals’ internalizing symptoms increase or decrease over time, whereas others exhibit steadily high or low

symptoms [10-16].

Although such studies have highlighted the potential value of examining psychiatric symptoms across the

life-course, as well as the apparent heterogeneity in the development of internalizing symptoms, there are

nevertheless gaps in our understanding of the development of such symptoms. For example, only a few studies have

identified trajectories of internalizing symptoms [10], whereas a number of studies have examined latent classes of

either depressive or anxious symptoms alone [15, 17], neglecting the considerable overlap often reported between

these types of symptoms. In fact, epidemiological studies suggest rates of comorbidity between 30% and 75% [18,

19] for mood and anxiety disorders. Also, recent studies have typically focused on the development of internalizing

symptoms either in childhood or in adolescence [8, 11, 12, 20], rather than examining the changes in these

symptoms across these developmental periods. As a result, relatively little is known about the factors early in life

that may influence the time of onset of these symptoms. In particular, it is unclear to what extent early-life factors

may differentially predict the emergence of depressive and anxious symptoms in childhood versus during

adolescence.

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Based on previously identified risk factors for internalizing symptoms, it is possible that early-life factors

could help predict the timing of child versus adolescent internalizing symptom onset. For instance, internalizing

symptoms in childhood have been predicted by difficult child temperament [12, 21], maternal depression [11, 12,

17], family dysfunction and stress [8, 12], as well as negative parenting practices [11]. In contrast, internalizing

symptoms in adolescence have been predicted by delayed motor development [10], being female, lower SES [14],

and negative life events [22].

To our knowledge, the only studies examining the development of internalizing symptoms (i.e., trajectories

of combined anxious and depressive symptoms) from childhood into adolescence have examined average growth

curves (single trajectory), rather than identifying latent classes of symptom trajectories [23]. Therefore, it is unclear

whether risk factors can differentially predict child- versus adolescent-onset internalizing symptoms. Due to the

ability of LCGM to identify homogeneous subgroups represented by distinct trajectories of symptoms, this method

is particularly well suited to the identification of risk factors associated with the emergence of internalizing

symptoms in childhood versus adolescence. Importantly, if risk factors could differentiate between child-onset

versus adolescent-onset internalizing symptoms, this information could play a role in the development of programs

designed to reduce the occurrence and severity of these symptoms.

Aims of the Study

The goals of this study were to identify distinct groups of internalizing symptoms from childhood into

adolescence, and to identify early-life risk factors that may predict group membership in child- versus adolescent-

onset trajectories, in a large prospective cohort of Canadian children.

METHODS

This study was approved by the Research Ethics Board of the Ottawa Hospital. Statistics Canada obtained

written informed consent from parents of survey members (see below).

Sample

The National Longitudinal Study of Children and Youth (NLSCY) is a nationally representative

prospective cohort study of Canadians that is managed by Statistics Canada [24]. Data collection for the longitudinal

sample began in 1994/1995 and continued every two years until 2008/2009. In order to maximize sample size, our

sample was drawn from 6908 individuals who were age 2-3 years in Cycle 1 (1994/1995) or Cycle 2 (1996/1997) of

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the NLSCY. Our final sample included N=6337 individuals who had information on internalizing symptoms for at

least one age group from age 4-5 to age 14-15. Overall response rates for Cycles 1-8 were 91.5%, 88.7%, 78.7%,

74.1%, 67.9%, 66.9%, and 62.0% respectively [25]. Statistics Canada has acknowledged a number of factors as

important for understanding NLSCY non-response, including privacy concerns, respondent burden, experience and

training of interviewers, and incentives to respondents [26]. In order to deal with survey non-response bias, all

survey responses were weighted using the appropriate sampling weights provided by Statistics Canada. These

weights were based on the inverse of each child’s probability of selection and are adjusted for non-response at each

cycle of the survey [25].

Measures

Internalizing symptoms. Internalizing symptoms were assessed using a questionnaire that included 7 items

from the Ontario Child Health Study (OCHS-R) [27], assessing symptoms of anxiety and depression. The items

were derived from the Child Behavior Checklist (CBCL) [28] because they appeared to operationalize DSM-III

criteria for emotional disorder [29]. The CBCL subscales are derived from DSM-III and DSM-IV criteria [30] and

have been extensively evaluated in terms of their psychometric properties [27, 31]. From ages 4 to 11, parents

reported on their child’s symptoms. The statements were, (my child) “seems to be unhappy, sad or depressed,” “is

not as happy as other children,” “is too fearful or anxious,” “is worried,” “cries a lot,” “is nervous, highstrung, or

tense,” and “has trouble enjoying him/herself”. From ages 12 to 15, these same items are self-reported, albeit with

slightly different wording (e.g., “I am unhappy or sad,” “I am too fearful or nervous”). Response options were:

“never or not true,” “sometimes or somewhat true,” or “often or very true.” Cronbach’s alphas of 0.79 and 0.81 have

been reported for the child and parent reports [25, 32]. In the current study, total scores were grouped into 4

categories representing degrees of severity. This was done in order to account for floor effects and variation in

severity of symptoms (i.e., positively skewed distributions), following previously reported procedures [33, 34]: no

symptoms (scores below the 50th percentile), low symptoms (scores between the 51st and 75th percentile), moderate

symptoms (scores between the 76th and 90th percentile), and severe symptoms (scores above the 90th percentile).

Early-life risk factors. A number of variables were examined as potential predictors of subsequent group

membership in internalizing trajectories from age 4-5 to age 14-15. Therefore, these variables were measured when

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children were at or below age 4-5 (i.e., at baseline), with survey responses of the person most knowledgeable about

the child (PMK). This person was typically the mother.

Socioeconomic status. Socioeconomic status (SES) is operationalized in the NLSCY using household

income controlled for the ‘low-income cut off’ (LICO) score, which takes into account an individual’s income

relative to the community in which they live, as well as the size of their family [35]. For the current study, SES was

measured at age 2-3 and participants were considered to be ‘low SES’ if this value was in the bottom 10th percentile.

Physical, social and cognitive development. Children’s birth weight and gestational age were reported by

mothers when children were 0-3 years of age [25]. Using sex-specific Canadian population standards of birth weight

for gestational age [36], we classified individuals whose birth weight was in the bottom 10% of these standards as

being small for gestational age (SGA). At age 2-3, the PMK completed the Motor and Social Development (MSD)

Scale as a measure of ‘developmental milestones’. The MSD is a set of 15 ‘yes/no’ questions measuring aspects of

early motor, social, and cognitive development of young children (e.g., “has ____ ever spoken a partial sentence of 3

words or more?”). In the NLSCY, scores are based on the number of ‘yes’ answers, and MSD scores are then

standardized. For the current study, individuals were considered to have ‘low developmental milestones’ if their

score was in the bottom 10th percentile.

Sources of stress. Mothers were asked whether they had ever smoked or drank alcohol during pregnancy.

Other potential sources of stress included the presence of any chronic illnesses (e.g., diabetes) currently experienced

by the child at age 2-3, as well as the presence of 15 stressful life events (SLEs; e.g., death of a family member) that

children had experienced in the previous 24 months (from age 2-3 to age 4-5). Stressful life events were

dichotomized into ‘high stress’ (2 or more SLEs) versus ‘low stress’.

Parent and family characteristics. At child age 2-3, maternal depression was measured through self-

reported frequency and severity of symptoms over the past week through nine statements (e.g., “I felt depressed”).

Also at age 2-3, the PMK reported on the overall level of dysfunction in their family (e.g., “there are lots of bad

feelings in our family”), and the degree to which they employed a ‘hostile/ineffective’ parenting style (e.g., “How

often do you get angry when you punish your child?”) and ‘punitive/aversive’ parenting (e.g., “When ____ breaks

the rules or does things that he/she is not supposed to do, how often do you use physical punishment?”). These

variables were all dichotomized, where scores in the top 10th percentile represented ‘high’ scores.

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Child behavior. At child age 2-3, the PMK rated the overall degree of difficulty their child would present

for the average parent (i.e., difficult temperament). Also at age 2-3, scales derived from the OCHS-R [27], CBCL

[28], and the Montreal Longitudinal Survey [37] were used to measure children’s level of ‘physical aggression –

opposition’ (e.g., “gets into many fights”) and ‘hyperactivity – inattention’ (e.g., “can’t sit still, is restless, or

hyperactive”). These variables were dichotomized using a 90th percentile cut-off, where scores in the top 10th

percentile represented ‘high’ scores.

Statistical Analysis

LCGM was performed using the PROC TRAJ application [38] in SAS 9.3 (SAS Institute Inc, Cary, North

Carolina, USA). Models with three, four, five groups were examined. Our choice of model was based on model

parsimony as measured by the Bayesian Information Criterion (BIC) value and posterior probabilities for group

membership. Missing data were handled in PROC TRAJ using full information maximum likelihood (FIML) under

a missing at random (MAR) assumption.

Multinomial logistic regression in SAS 9.3 was used to examine potential risk factors for membership in a

particular trajectory group versus a reference group (Table 2). Child gender and SES were included as covariates in

regression models.

RESULTS

Trajectories of internalizing symptoms

BIC value for the 3-, 4-, 5-, and 6-group models were -39116.33, -37916.34, -37529.36, and

-37588.45 respectively. Average posterior probabilities for the 5-group model were good (.80 - .90). These were

comparable to those of the 4-group model (.84 - .87). Trajectory plots suggested that one trajectory in the 4-group

model may have been combining two meaningful trajectories in the 5-group model. Also, the inclusion of a 6th group

resulted in the largest group from the 5-group model being split into two identical trajectory groups. Thus, the 5-

group model was chosen as the most parsimonious and best fitting model.

As seen in Figure 1, the identified trajectories are as follows: 1) consistently low levels of symptoms—

‘low stable’ (reference group; 67.5%); 2) low levels from age 4-5 to age 8-9 and then a sharp increase until age 14-

15 — ‘adolescent onset’ (9.8%); 3) high levels at age 4-5 followed by a sharp decline until age 8-9, at which point

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the trajectory is similar to the ‘low stable’ group— ‘high childhood’ (7.4%); 4) mostly moderate levels from age 4-5

to age 14-15— ‘moderate stable’ (11.2%); and 5) consistently high levels throughout— ‘high stable’ (4.1%).

--------- Insert Figure 1 about here ----------

Risk factors for trajectory group membership

Proportions for the examined early-life risk factors are presented in Table 1. These are shown for the entire

sample, as well as stratified by child gender and by trajectory group. These proportions suggest a number of group

differences among trajectory groups. For instance, 2 or more SLEs, conduct/aggression, and

hyperactivity/inattention appeared to be less frequent in the ‘low stable’ group as compared to the other trajectory

groups.

--------- Insert Table 1 about here ----------

Predictors of group membership are described in Table 2. Several factors were associated with membership

in the ‘high stable’, ‘high childhood’, and ‘moderate stable’ trajectory groups (i.e., ‘child-onset’ trajectories) versus

the reference group. In particular, the odds of membership in the ‘high stable’ group were increased significantly in

the presence of maternal depression, family dysfunction, 2 or more SLEs, hostile/ineffective parenting,

conduct/aggression, hyperactivity/inattention, and difficult temperament. Predictors of the ‘high childhood’

trajectory included the presence of a chronic illness, maternal depression, 2 or more SLEs, hostile/ineffective and

punitive/aversive parenting, conduct/aggression, hyperactivity/inattention, and difficult temperament.

--------- Insert Table 2 about here ----------

Membership in the ‘adolescent onset’ trajectory was predicted by fewer early-life factors than either of the

‘child-onset’ trajectories. Most notably, membership in this trajectory was predicted by child gender. Girls had had

almost three times greater odds of being part of this group than boys. Other factors increasing the odds of

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membership in this trajectory were 2 or more SLEs, hostile/ineffective parenting, as well as conduct/aggression and

hyperactivity/inattention.

Gender differences

Gender differences were further explored by examining interactions with predictor variables and child

gender. Most notably, there was evidence of interactions in the prediction of ‘adolescent onset’ group membership

(see Table 3). Specifically, presence of a chronic illness, punitive/aversive parenting, hostile/ineffective parenting,

as well as conduct/aggression and hyperactivity/inattention were associated with greater odds of ‘adolescent onset’

group membership for girls than for boys. Also, low birth weight was associated with greater odds of ‘adolescent

onset’ group membership for boys than for girls.

--------- Insert Table 3 about here ----------

Additional interactions by child gender emerged with regard to the remaining trajectories. Family

dysfunction was associated with greater odds of group membership in the ‘high childhood’ and ‘high stable’

trajectories for girls than for boys, and conduct/aggression increased the odds of ‘high childhood’ trajectory

membership to a greater extent for girls than for boys. Also, mother drinking and smoking during pregnancy both

were associated with greater odds of ‘moderate stable’ trajectory group membership for girls than for boys.

DISCUSSION

This large nationally representative study identified five distinct trajectories of internalizing symptoms

from childhood into adolescence. This supports the growing number of studies [10-16] identifying several distinct

classes of anxious and depressive symptom trajectories in young people. It is increasingly clear that growth models

that assume that a single trajectory of change adequately represents the population are often inappropriate, in that

they ignore the inherent heterogeneity in the development of a number of phenomena, including internalizing

symptoms. Our study also identified child- versus adolescent-onset symptom trajectories. We were thus able to

identify risk factors associated with symptoms in these two age periods, adding to the understanding of the early

developmental precursors of qualitatively different pathways of internalizing symptoms.

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In general, early-life factors we examined were more predictive of child-onset than adolescent-onset

internalizing trajectories, suggesting that the early childhood environment may not be as important for predicting

adolescent anxiety and depression. However, previous studies have shown the importance of both early-life factors

[34, 39], as well as factors during late childhood and adolescence [22, 40], in predicting adolescent internalizing

symptoms. It is not clear why these previous results are at odds with those of the current study. One possible reason

is that these studies were methodologically dissimilar to the current study, in that they either did not include analysis

of symptom trajectories [34, 39, 40] or did not analyze trajectories from childhood to adolescence [22], and thus do

not provide directly comparable results.

Our results showed that a smaller number of factors in early childhood were nevertheless predictive of

adolescent-onset internalizing symptoms. For instance, hostile parenting increased the odds of the adolescent-onset

trajectory. This finding is consistent with previous research showing that parent rejection is important for the

development of adolescent depressive symptoms [41]. Early physical aggression and hyperactivity were also

predictive of the adolescent-onset trajectory, which supports findings from studies linking adolescent internalizing

outcomes with childhood aggression [42, 43] and hyperactivity [44, 45]. Also, 2 or more SLEs was also predictive

of this trajectory. Thus, the importance of early childhood for the development of internalizing symptoms in

adolescence may be limited to a relatively small number of factors.

In contrast, factors in late childhood and early adolescence may be of much greater importance in terms of

the development of adolescents’ internalizing symptoms. Indeed, some research suggests that, although early

childhood adversity can increase the risk for depression in adolescence, this effect may be mediated through

adolescent stress [46]. Other studies have shown the importance of late childhood stressors such parent

psychopathology [47] and negative life events [22] on depressive symptom trajectories in adolescence and young

adulthood. Thus, factors in late childhood and adolescence can be seen as leading toward dramatic changes in

internalizing symptoms for certain children, with early-life factors playing a less prominent role in this shift in

symptom severity.

Our results also showed that membership in the ‘adolescent-onset’ trajectory was strongly predicted by

child gender, with girls having almost 3 times higher odds of group membership than boys. This was not surprising,

considering studies showing not only that rates of depression and anxiety are higher among girls [48, 49], but that

these gender differences tend to emerge in adolescence [50, 51]. Other research has shown that girls are more likely

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to be in depressive symptom trajectories in adolescence [13, 14, 47]. We also found no effect of gender for the ‘high

childhood’ or ‘high stable’ trajectories, consistent with some previous research [12, 17]. However, other studies

suggest such gender differences may indeed emerge in childhood [15, 21].

The underlying reasons for this gender difference in the adolescent-onset trajectory are unclear. However,

our further analysis of gender differences suggests that some early risk factors might be particularly important for

the development of adolescent internalizing symptoms in girls. Punitive/aversive and hostile/ineffective parenting

were associated with membership in the ‘adolescent-onset’ trajectory for girls, but not boys. These findings are

consistent with previous studies suggesting that parenting style might have a stronger influence on depression for

college-age females [52] and that coercive parenting is associated with increased risk of depression in adolescent

girls, but not boys [53]. Conduct/aggression and hyperactivity/inattention also were associated with membership in

the ‘adolescent-onset’ trajectory for girls, but not boys. These results are consistent with studies suggesting that

physical aggression is positively related to depression among adolescent girls, but negatively related to depression

among adolescent boys [54], conduct problems in preschool lead to increased internalizing symptoms in adolescence

for girls only [55], and some subtypes of ADHD are associated with comorbid internalizing symptoms among girls,

but not boys [56].

Some researchers have proposed that, although there may be gender differences in early-life risk factors for

depression, gender differences in internalizing symptoms may only occur during adolescence because such risk

factors may trigger stronger reactions to stress for girls at this age [57]. Indeed, there is some evidence that

adolescent girls are more likely than boys to exhibit symptoms of anxiety and depression in response to various

types of stress such as peer and relationship stress [58]. However, our results also showed that being small for

gestational age increased the odds of membership in the ‘adolescent onset’ trajectory for boys only, suggesting that

some sources of stress may also be particularly problematic for boys. This finding is consistent with a recent study

examining the role of birth weight and stress on adolescent internalizing symptoms [33].

Gender interactions in the current study were also not limited to group membership in the ‘adolescent

onset’ group. In fact, family dysfunction increased the odds of group membership in the ‘high stable’ and ‘high

childhood’ groups for girls, but not boys. This supports a previous study of infants of depressed mothers, which

found that early exposure to marital conflict was associated with a subsequent increase in childhood internalizing

symptoms for girls, but not boys [59]. Also, conduct/aggression increased the odds of membership in the ‘high

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childhood’ group to a greater extent for girls than boys. Indeed, among children with conduct disorder, girls may be

at greater risk for comorbid disorders such as depression [60].

The current study has several limitations that should be mentioned. For instance, parents reported on their

children’s internalizing symptoms up until age 10-11, after which children began to self-report on these symptoms.

Therefore, it is unclear whether changes in internalizing trajectories were due partly to the change in respondent,

rather than entirely due to changes in symptom levels over time. However, this is a problem that is inherent to the

assessment of symptoms via questionnaires versus clinician ratings or other methods. Young children are often not

the best informants, and thus parents must often provide information on their child’s behalf. Older children are

capable of providing self-reports, and are arguably the most reliable source of information regarding their own

emotional state. Although trajectory groups were based on a large sample of children, the relatively small sample

sizes in some trajectory groups may have resulted in a lack of power to detect significant effects, including gender

interactions. Our study utilized survey data and, although well-known confounders of the association between the

risk factors and trajectories were included in the models, bias due to unmeasured confounders cannot be ruled out.

Furthermore, we only examined predictors of trajectory groups at baseline. It is important to note that there may be

time-varying factors influencing trajectories through important cross-sectional effects.

Our study also had a number of strengths. We used data from a large, nationally representative sample and

included incomplete cases with a principled approach to missing data. We were able to identify distinct trajectories

representing child- versus adolescent-onset of internalizing symptoms, as well as early-life risk factors for

membership in these trajectories. We also identified some important gender differences in the role played by various

risk factors, and thus added to the existing knowledge of early-life predictors of the course of internalizing

symptoms in young people.

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Acknowledgments

This research was supported by a grant from the SickKids Foundation and the Canadian Institutes of Health

Research (grant number SKF 116328), as well as funding from the Canada Research Chairs program for Dr.

Colman. The authors thank Dr. Zacharie Tsala Dimbuene and Dr. Jean-Michel Billette of Statistics Canada for their

assistance with data access and use. The research and analysis are based on data from Statistics Canada and the

opinions expressed do not represent the views of Statistics Canada.

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19

All(N=6337)

Low Stable (n=4279)

Moderate stable

(n=710)

Adolescent Onset

(n=618)

High Childhood(n=471)

High Stable

(n=259)

Female 48.6 46.7 43.0 70.9 43.3 52.1

Low SES 9.3 9.4 9.4 8.1 8.5 10.0

Low PPVT 9.7 9.2 11.6 7.5 13.1 11.3

Low MSD 9.8 9.8 12.1 7.2 9.9 9.7

Small for gestational age 7.7 7.1 9.9 7.7 9.0 9.0

Presence of chronic illness 25.6 24.5 27.4 22.0 32.2 33.3

Smoking during pregnancy 25.7 24.1 29.8 29.6 27.2 27.7

Drinking during pregnancy 16.8 16.1 20.7 13.6 21.4 18.7

Maternal depression 11.0 9.2 13.9 12.8 17.1 20.4

≥ 2 SLE 2.4 1.6 2.8 2.9 5.9 5.4

Family dysfunction 11.5 10.8 15.4 11.8 16.1 18.7

Hostile/ineffective parenting 12.0 10.7 12.4 15.2 19.7 20.4

Punitive/aversive parenting 14.9 13.7 14.2 17.2 18.7 18.0

Conduct/Aggression 13.1 10.9 15.4 16.4 19.4 24.3

Hyperactivity/Inattention 14.9 11.1 20.5 16.4 20.9 25.5

Difficult temperament 10.3 8.2 12.4 10.3 16.2 20.5

Table 1. Proportions for early-life risk factors

20

Risk FactorAdolescent Onset

(n=618)High Childhood

(n=471)High Stable

(n=259)Moderate stable

(n=710)

Gender (male as reference) *2.84 [2.35, 3.42] 0.90 [0.77, 1.05] *1.45 [1.12, 1.87] 0.90 [0.77, 1.05]

Low SES 0.73 [0.53, 1.01] 0.88 [0.63, 1.23] 0.91 [0.58, 1.42] 0.93 [0.71, 1.22]

Low MSD 0.69 [0.48, 1.00] 0.76 [0.54, 1.07] 0.79 [0.49, 1.29] 1.18 [0.92, 1.51]

Low PPVT 0.90 [0.64, 1.25] 1.07 [0.76, 1.51] 1.07 [0.68, 1.68] *1.42 [1.09, 1.84]

Small for gestational age 1.11 [0.81, 1.52] 1.15 [0.80, 1.66] 1.07 [0.66, 1.73] 1.21 [0.91, 1.62]

Chronic illness 0.86 [0.66, 1.13] *1.81 [1.38, 2.37] 1.37 [0.97, 1.94] 1.30 [1.03, 1.64]

Smoking during pregnancy 1.09 [0.80, 1.48] 0.92 [0.62, 1.37] 1.32 [0.87, 2.00] *1.34 [1.00, 1.78]

Drinking during pregnancy 0.68 [0.47, 1.00] 1.25 [0.84, 1.85] 1.30 [0.83, 2.02] *1.40 [1.03, 1.91]

Maternal depression 1.17 [0.88, 1.56] *2.15 [1.65, 2.80] *2.18 [1.54, 3.08] *1.65 [1.30, 2.09]

≥ 2 SLE *1.88 [1.03, 3.42] *4.39 [2.70, 7.14] *4.08 [2.16, 7.70] *4.71 [3.11, 7.12]

Family dysfunction 0.91 [0.68, 1.21] *1.59 [1.21, 2.08] *1.94 [1.38, 2.73] *1.77 [1.42, 2.21]

Hostile/ineffective parenting *1.65 [1.28, 2.11] *2.19 [1.71, 2.81] *2.03 [1.45, 2.84] 1.04 [0.81, 1.34]

Punitive/aversive parenting 1.25 [0.98, 1.60] *1.34 [1.04, 1.74] 0.95 [0.64, 1.39] 1.08 [0.86, 1.35]

Conduct/Aggression *1.68 [1.31, 2.15] *2.46 [1.94, 3.12] *2.69 [1.97, 3.68] *1.49 [1.18, 1.87]

Hyperactivity/Inattention *1.56 [1.22, 2.01] *1.71 [1.32, 2.22] *2.66 [1.95, 3.63] *2.17 [1.77, 2.67]

Difficult temperament 1.21 [0.89, 1.64] *3.02 [2.36, 3.88] *2.42 [1.71, 3.43] *1.76 [1.38, 2.24]

* Odds ratio significant at p < .05

21

Table 3. Significant gender interactions predicting the odds of trajectory group membership (‘low stable’ group as reference)

Interactions by Gender Trajectorygroup

Interactionp-value

OR (95% CI)for girls

OR (95% CI)for boys

Mother drink while pregnant Moderate stable p<.001 2.41 [1.59, 3.66] 0.78 [0.49, 1.27]

Mother smoked while pregnant Moderate stable p=.006 2.07 [1.37, 3.12] 0.93 [0.63, 1.39]

Small for gestational age Adolescent Onset p=.020 0.89 [0.60, 1.32] 1.93 [1.15, 3.25]

Chronic illness Adolescent Onset p=.014 1.12 [0.81, 1.56] 0.53 [0.33, 0.87]

Family DysfunctionHigh Childhood p=.024 2.24 [1.51, 3.33] 1.20 [0.82, 1.75]

High Stable p=.042 2.62 [1.71, 4.00] 1.24 [0.69, 2.23]

Punitive/aversive Parenting Adolescent Onset p=.007 1.58 [1.18, 2.11] 0.73 [0.45, 1.18]

Hostile ParentingModerate stable p=.031 1.43 [0.99, 2.08] 0.81 [0.57, 1.16]

Adolescent Onset p=.012 2.10 [1.55, 2.85] 1.02 [0.64, 1.64]

Conduct/Aggression Adolescent Onset p=.038 2.09 [1.53, 2.85] 1.17 [0.75, 1.83]

High Childhood p=.020 3.52 [2.41, 5.15] 1.98 [1.46, 2.69]

Hyperactivity/Inattention Adolescent Onset p=.027 1.93 [1.42, 2.63] 1.03 [0.65, 1.64]

22