Psychiatric research in the Northern Finland Birth Cohort 1986 – a systematic review

Abstract

The Northern Finland Birth Cohort 1986 is a large population-based birth cohort, which aims to promote health and wellbeing of the population. In this paper, we systematically review the psychiatric research performed in the cohort until today, i.e. at the age of 32 years of the cohort (2018). We conducted a systematic literature search using the databases of PubMed and Scopus and complemented it with a manual search. We found a total of 94 articles, which were classified as examining ADHD, emotional and behavioural problems, psychosis risk or other studies relating to psychiatric subjects. The articles are mainly based on two large comprehensive follow-up studies of the cohort and several substudies. The studies have often used also nationwide register data. The studies have found several early predictors for the aforementioned psychiatric outcomes, such as problems at pregnancy and birth, family factors in childhood, physical inactivity and substance use in adolescence. There are also novel findings relating to brain imaging and cognition, for instance regarding familial risk of psychosis in relation to resting state functional MRI. The Northern Finland Birth Cohort 1986 has been utilised frequently in psychiatric research and future data collections are likely to lead to new scientifically important findings.
Abbreviations: attention deficit hyperactivity disorder (ADHD); magnetic resonance imaging (MRI)

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Psychiatric research in the Northern Finland Birth
Cohort 1986 – a systematic review
Jouko Miettunen, Marianne Haapea, Lassi Björnholm, Sanna Huhtaniska,
Teija Juola, Lotta Kinnunen, Heli Lehtiniemi, Johannes Lieslehto, Nina Rautio
& Tanja Nordström
To cite this article: Jouko Miettunen, Marianne Haapea, Lassi Björnholm, Sanna Huhtaniska, Teija
Juola, Lotta Kinnunen, Heli Lehtiniemi, Johannes Lieslehto, Nina Rautio & Tanja Nordström (2019)
Psychiatric research in the Northern Finland Birth Cohort 1986 – a systematic review, International
Journal of Circumpolar Health, 78:1, 1571382, DOI: 10.1080/22423982.2019.1571382
To link to this article: https://doi.org/10.1080/22423982.2019.1571382
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REVIEW ARTICLE
Psychiatric research in the Northern Finland Birth Cohort 1986 –a systematic
review
Jouko Miettunen
a,b
, Marianne Haapea
a,b,c
, Lassi Björnholm
c,d
, Sanna Huhtaniska
a
, Teija Juola
a
,
Lotta Kinnunen
a,b
, Heli Lehtiniemi
a,b,e
, Johannes Lieslehto
a,b
, Nina Rautio
a,b
and Tanja Nordström
a,b,e
a
Center for Life Course Health Research, University of Oulu, Oulu, Finland;
b
Medical Research Center Oulu, Oulu University Hospital and
University of Oulu, Oulu, Finland;
c
Department of Psychiatry, Oulu University Hospital, Oulu, Finland;
d
Department of Psychiatry, Research
Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland;
e
Northern Finland Birth Cohorts, Faculty of Medicine, University of Oulu,
Oulu, Finland
ABSTRACT
The Northern Finland Birth Cohort 1986 is a large population-based birth cohort, which aims to
promote health and wellbeing of the population. In this paper, we systematically review the
psychiatric research performed in the cohort until today, i.e. at the age of 32 years of the cohort
(2018). We conducted a systematic literature search using the databases of PubMed and Scopus
and complemented it with a manual search. We found a total of 94 articles, which were classified
as examining ADHD, emotional and behavioural problems, psychosis risk or other studies relating
to psychiatric subjects. The articles are mainly based on two large comprehensive follow-up
studies of the cohort and several substudies. The studies have often used also nationwide register
data. The studies have found several early predictors for the aforementioned psychiatric out-
comes, such as problems at pregnancy and birth, family factors in childhood, physical inactivity
and substance use in adolescence. There are also novel findings relating to brain imaging and
cognition, for instance regarding familial risk of psychosis in relation to resting state functional
MRI. The Northern Finland Birth Cohort 1986 has been utilised frequently in psychiatric research
and future data collections are likely to lead to new scientifically important findings.
Abbreviations: attention deficit hyperactivity disorder (ADHD); magnetic resonance imaging (MRI)
ARTICLE HISTORY
Received 20 June 2018
Revised 9 January 2019
Accepted 12 January 2019
KEYWORDS
ADHD; behavioural
problems; birth cohort;
emotional problems;
psychosis risk; systematic
review
Introduction
Birth cohort studies were originally designed to
study early health outcomes, but already the earliest
birth cohorts, started in the 1940s, have also studied
later outcomes, including psychiatric problems and
diagnoses. Birth cohort studies have been useful for
instance when looking into early antecedents of
childhood/adolescent [1,2]oradultpsychiatricout-
comes [3,4].
TheNorthernFinlandBirthCohorts(NFBC)1966
and 1986 are two large population-based birth cohorts
that aim to promote the health and wellbeing of the
population. The NFBCs are among the oldest and most
studied birth cohorts in the world and especially in the
circumpolar region. The data have been collected
since the antenatal period from health records, ques-
tionnaires and clinical examinations up to today. The
older birth cohort, the NFBC1966, includes all people
with an expected date of birth in 1966 in Northern
Finland, whereas the younger birth cohort, the
NFBC1986, includes those with an expected date of
birth between 1 July 1985 and 30 June 1986. The two
birth cohorts have been studied extensively with over
1,000 peer-reviewed publications in various fields of
health sciences (http://www.oulu.fi/nfbc).
The focus in the NFBC1986 has been on children’s
psychiatric health from the beginning. The studies
have especially focused on attention deficit hyperac-
tivity disorder (ADHD), emotional and behavioural pro-
blems and psychosis risk from childhood to adult age.
In this paper, we systematically review the psychiatric
research performed in the NFBC1986 until 2018, i.e. at
the age of 32 years of the cohort.
Methods
Literature search
We conducted a systematic literature search using
PubMed (Medline) and Scopus (Elsevier) databases in
May 2018. The main search criteria were “Northern
CONTACT Jouko Miettunen jouko.miettunen@oulu.fi Center for Life Course Health Research, University of Oulu, PO Box 5000, Oulu, Finland
Supplemental data for this article can be accessed here
INTERNATIONAL JOURNAL OF CIRCUMPOLAR HEALTH
2019, VOL. 78, 1571382
https://doi.org/10.1080/22423982.2019.1571382
© 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which
permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Finland Birth Cohort 1986”OR “Northern Finland Birth
Cohort 1985–1986”. We also checked all publications of
two authors who were involved in most of the early
psychiatric studies of the cohort (“Northern Finland Birth
Cohort”AND (“Moilanen I”OR “Taanila A”)). Additionally,
we searched manually for articles from the extensive
publication list maintained by the NFBC cohorts (http://
www.oulu.fi/nfbc) and reviewed reference lists of the
accepted articles from the literature search. Articles pub-
lished after the systematic search were manually added to
the review. Abstracts of the articles were checked by two
authors and the final inclusion was done by consensus
between the authors. The two inclusion criteria were that
the study included data from the NFBC1986 and exam-
ined any psychiatric or psychological subject.
Sample
The NFBC1986 is based on 9,362 pregnant women and
their 9,479 live-born babies in Northern Finland (for-
mer provinces of Oulu and Lapland), with an expected
date of birth between 1 July 1985 and 30 June 1986.
The live-births in this study represent 99% of all births
in the region [5]. The NFBC1986 is a genetically homo-
geneous population, including approximately 99.9%
Caucasian people and 0.1% with Sami origin. The
area is located between latitudes 65–70 degrees
north. The overall study design has been approved
and is under the review of the Ethical Committee of
the Northern Ostrobothnia Hospital District, Finland.
The original articles of this literature review are largely
based on two comprehensive data collections of the
whole cohort, one in childhood (8 years) and one in
adolescence (15–16 years), and on subsamples collected
in childhood and early adulthood. Register data and
earlier collected data of the NFBC1986 have also been
utilised in the studies.
The 8 year follow-up was conducted in the spring of
the children’s first school year (either 1993 or 1994),
and the 15–16 year follow-up between April 2001 and
February 2002. The former included questionnaires to
parents and teachers and the latter to adolescents and
their parents.
Other follow-ups including various questionnaires,
interviews, cognitive tests and brain imaging have
been performed for selected subsamples. Adolescents
with ADHD symptoms and controls have been investi-
gated at ages 16–18 years [6] and 21–25 years [7]. The
Oulu Back Study, which also included psychiatric mea-
sures, was conducted when adolescents were 18 years
old [8]. Those with psychosis risk based on parental
psychosis or prodromal symptoms at age 15–16 years
were invited to the Oulu Brain and Mind Study I at age
21–25 years [9]. At age 25–27 years, children who were
born to mothers who were smoking during pregnancy
and their controls were invited to the Oulu Brain and
Mind Study II [10]. There has also been a small sub-
study for single-parent and reconstructed families,
when children were 9 years old [11].
Measures of psychiatric symptoms
The data collections with time points, sample sizes and
used psychiatric measures are summarised in Figure 1.
Measures relating to ADHD, emotional and behavioural
problems and psychosis risk and methods in cognition
and brain imaging studies are presented briefly below.
ADHD symptoms
ADHD-related symptoms were measured with a tea-
cher rated Rutter B2 (RB2) scale in childhood [12], and
with Strengths and Weaknesses of ADHD symptoms
and Normal Behaviors (SWAN) questionnaire in ado-
lescence and in early adulthood [13]. The RB2 scale
includes 26 items, 3 of which are considered to mea-
sure hyperactivity. The Rutter items were scored from
0 to 2 (0 = does not fit, 1 = fits partly, 2 = fits well). In
the SWAN questionnaire parents rate their children
into a 7-point statement scale for 18 items, of which
nine measure inattentive and nine hyperactive-impul-
sive symptoms. Some studies have used the Youth
Self-Report (YSR) subscale of attention problems [14].
In the YSR questionnaire, adolescents rate themselves
for how true (scale from 0–2) each item is now or was
within the past six months. In addition, diagnostic
interviews (Schedule for Affective Disorders and
Schizophrenia for School-Age Children–Present and
Lifetime Version, K-SADS-PL [15]) were conducted in
the ADHD sub-study at age 16–18 years [6].
Emotional and behavioural problems
Emotional (or internalising) and behavioural (or exter-
nalising) problems were measured in childhood with
Rutter A2 (RA2) and RB2 scales, and in adolescence
and early adulthood with the YSR [16]. The NFBC
studies used a modified parent rated RA2 scale with
five emotional and four behavioural items. In the RB2
scale, there are four items measuring emotional pro-
blems and six behavioural problems. The version of
the YSR questionnaire used included 30 items for
emotional problems and 29 items for behavioural
problems. These have been analysed continuously or
using different cut-offs. Some studies also included
register data, such as diagnoses of depression and
criminal records.
2J. MIETTUNEN ET AL.

Psychosis risk
Vulnerability to psychosis in the NFBC1986 was defined as
having either prodromal symptoms or familial risk (FR)
based on parental psychoses. The register-based informa-
tion about the individual’s later-life psychosis was formed
by utilising the Care Register for Health Care (previously
known as the Finnish Hospital Discharge Register), Finnish
outpatient registers, Finnish Centre for Pensions, and the
registers of the National Social Insurance Institute [17]. In
adolescence, prodromal symptoms of psychosis were
assessed using the PROD-screen (a screen for prodromal
symptoms of psychosis), which has 21 items, of which 12
Figure 1. Data collections of the psychiatric studies in the Northern Finland Birth Cohort 1986.
INTERNATIONAL JOURNAL OF CIRCUMPOLAR HEALTH 3

items specifically target psychotic-like experiences [18]. In
theOuluBrainandMindStudyI,prodromalsymptoms
were also assessed using the Structured Interview for
Prodromal Syndromes (SIPS) [19]. Psychosis was also stu-
died using register diagnoses and in sub-studies using
interviews.
Cognition
Cognitive studies so far fare based on the ADHD sub-
study and on the Oulu Brain and Mind Study I, which
included subsamples for ADHD and psychosis risk
research [9]. The ADHD sub-study included the
Wechsler Adult Intelligence Scale–Revised (WAIS–R)
measuring working memory, the Conners’Continuous
Performance Test (CPT) measuring response inhibition
and state regulation, and the Attention Network Task
(ANT) measuring interference control [20,21]. Oulu Brain
and Mind Study I included an extensive battery of
cognitive tests, which have been studied separately,
such as response initiation, vocabulary and matrix rea-
soning, or as one overall cognitive score [10,22–24].
Neuroimaging
The neuroimaging studies reported so far are based on the
Oulu Brain and Mind study I [9], where participants under-
went magnetic resonance imaging (MRI) scanning with the
GE Signa 1.5 T scanner at Oulu University Hospital. Brain
function was assessed with face-task blood oxygen level
dependent (BOLD) functional MRI (fMRI) and resting state
BOLD fMRI [25,26]. Grey-matter volume was assessed from
T1-weighted structural scans. White-matter microstructure
properties were assessed with diffusion tensor imaging
(DTI) [27]. The analyses of the neuroimaging data were
carried out with FMRIB Software Library (FSL).
Results
Our systematic search found 314 articles in Scopus and
135 in PubMed. After removing duplicates, the number
of articles was 341. We found 94 original articles related
to psychiatry, of which 11 were found through the
manual search. The included articles are listed in the
Supplement Table 1, with references, sample sizes, a
short summary of psychiatric methods used and com-
ments. The main findings of these articles are sum-
marised below in the following categories: ADHD,
emotional and behavioural problems, psychosis risk
and other studies.
ADHD
A total of 33 articles focused on ADHD, which was
studied either by different ADHD symptoms in childhood
or adolescence or by diagnosis assessed in the ADHD
sub-study. At the age of 8 years, 9.5% of children had
hyperactive problems assessed with the RB2 scale [28].
At the age of 15–16 years, parents reported boys more
often having problems than girls in the SWAN scale, but
in the YSR attention scale, girls themselves reported as
having more problems [29]. Based on the SWAN screen
and diagnostic interviews, the estimated prevalence of
persistent ADHD diagnosis in childhood and adolescence
was 6.7%, the prevalence of ADHD only in childhood was
12.6% and only in adolescence 8.5% [6].
Risk factors for ADHD
Table 1 presents the studied risk factors for ADHD. In
many studies, maternal smoking has been associated
with ADHD [30–32]. Also, other pregnancy related fac-
tors, such as maternal thyroid dysfunction [33], prenatal
exposure to synthetic glucocorticoids [34], maternal
adiposity prior to pregnancy [35] and increased placen-
tal size [36] have been associated with later ADHD
symptoms.
Some studies have evaluated different develop-
mental factors as risk factors for ADHD; intellectual
disability of a child associated with hyperactivity pro-
blems in childhood [28], and mixed-handedness has
been associated with ADHD symptoms, both in child-
hood and adolescence [37]. Executive functioning,
state regulation and social risk factors have been asso-
ciated with ADHD symptoms in adolescence [21].
Scholastic impairment in childhood has been asso-
ciated with comorbid diagnoses of behavioural pro-
blems and ADHD in adolescence [38]. Also, major
depression or oppositional defiant disorder by the
age of 13 years, has been associated with persistent
ADHD diagnosis in adolescence [39].
The type of the family affected ADHD symptoms in
adolescence, so that a divorced or reconstructed family
increased the score of the ADHD scale among boys, and
a reconstructed family increased reported YSR attention
problems among boys and girls [29]. Also having any
hospital-treated injuries was associated with hyperac-
tive symptoms in childhood and with ADHD symptoms
and diagnosis in adolescence [40]. In genetic studies, it
has been found that the allelic variants of the dopa-
mine β-hydroxylase gene are associated with ADHD
symptoms in adolescence [41].
Associating factors with ADHD
ADHD symptoms have also been linked to factors mea-
sured at the same time or at a later point in time. For
example, childhood ADHD symptoms have been asso-
ciated with scholastic impairment in reading, writing and
mathematics [42]. Also, childhood inattention-hyperactivity
4J. MIETTUNEN ET AL.

symptoms have been associated with adolescent obesity
and physical inactivity [43].
In adolescence, ADHD symptoms increased the
frequency of the executive function deficits [20]and
were associated with various psychosocial well-being
factors [44]. Also, ADHD symptoms were associated
with prodromal symptoms for psychosis in adoles-
cence [40] and affected substantially on crime [45].
Diagnosis of ADHD in adolescence was associated
with comorbidity with various psychiatric disorders
and family environment related factors [46], and
increased suicidal ideation and deliberate self-harm
[47]. Comorbidity of ADHD and disruptive beha-
vioural disorder were associated with more severe
symptoms of conduct disorder [48] and psychiatric
hospitalisation [49]. Young adults with past ADHD
showed some differences in brain white matter [50]
and had structural and functional deficits in caudate
associated with abnormal working memory function
compared to healthy controls [7].
Table 1. Statistically significant findings of risk factors for ADHD symptoms or diagnosis in the Northern Finland Birth Cohort 1986.
Risk factors Outcomes and risk estimates (95% confidence intervals)
Pregnancy-related risk factors
Maternal smoking before pregnancy ADHD symptoms in childhood (ORs): 1.4 (1.0–2.0)
a
[30]
Maternal smoking during pregnancy In childhood (ORs): ADHD symptoms: 1.5 (1.1–2.1)
a
[30], 1.6 (1.3–2.0)
b
[31];
hyperactivity: 1.3 (1.1–1.6)
c
[32]
High social adversity ADHD symptoms in childhood (OR): 2.2 (1.4–3.3)
b
[31]
Maternal thyroid-stimulating hormone concentration Among girls in childhood (ORs): inattention 1.2 (1.0–1.4)
d
, high total score
1.2 (1.0–1.5)
d
, combined ADHD symptoms 1.4 (1.1–1.8)
d
[33]
Prenatal exposure to synthetic glucocorticoids (sGC) Inattention in childhood (β): 0.97 (0.16–1.80)
e
,p= 0.02 [34]
Mother being overweight and gaining a large amount of weight during
gestation
ADHD symptoms in childhood (OR): 2.1 (1.2–3.7)
f
[35] (Nordic ADHD
network result)
Placental weight ADHD symptoms among boys in childhood (ORs): 1.1 (1.0–1.2)
g
;in
adolescence: 1.2 (1.0–1.4)
g
[36]
Childhood-related risk factors
Divorced family ADHD symptoms among boys in adolescence (ORs): 9.3 (1.5–3.4)
h
[29]
Non-intact family Hyperactive/impulsive symptoms (β): −0.17 (p< 0.01) [21]
Reconstructed family In adolescence (ORs): ADHD symptoms among boys: 10.5 (2.1–3.5)
h
;
attention problems: among boys 1.6 (1.1–2.4)
h
, girls 1.7 (1.3–2.3)
h
[29]
Intellectual disability Different hyperactive symptoms (ORs): being very restless 3.8 (2.3–6.3),
being squirmy/fidgety child 4.2 (2.6–6.8), having poor concentration/
short attention span 6.1 (3.7–10.1) [28]
Mixed handedness In adolescence (ORs): inattention 3.0 (1.4–6.4)
i
and ADHD symptoms 2.7
(1.2–6.0)
i
[37]
Response inhibition Inattentive symptoms (β): 0.23 (p< 0.001) and hyperactive/impulsive
symptoms (β): 0.17 (p< 0.01) [21]
Childhood hyperactivity ADHD diagnosis in adolescence (ORs) 3.3 (1.2–9.2)
j
, for comorbid disruptive
behavioural disorder and ADHD diagnoses 7.4 (2.6–21.1)
j
[38]
Scholastic impairment in childhood Comorbid disruptive behavioural disorder and ADHD diagnoses (OR): 3.1
(1.5–6.4)
j
[38]
Major depression by age 13 years Persisting ADHD diagnosis in adolescence (OR): 8.8 (1.1–68.5) [39]
Oppositional defiant disorder by age 13 years Persisting ADHD diagnosis in adolescence (OR): 2.4 (1.0–5.6) [39]
Any hospital-treated injuries Hyperactivity symptoms in childhood (HRs): 1.4 (1.0–1.9)
k
; in adolescence:
ADHD symptoms 1.5 (1.1–2.0)
k
, diagnosis of ADHD 2.3 (1.2–4.5)
k
[40]
Other risk factors
Allelic variants of the dopamine β-hydroxylase gene ADHD symptoms in adolescence among males (ORs): 5.01 (1.8–14.5, marker
rs2073837), 1.9 (1.0–3.5, rs1079727), 2.0 (1.1–3.7, rs 1,079,595), 2.1
(1.1–3.8, rs1124491), 1.9 (1.1–3.6, rs1800497)[41]
Abbreviations: ADHD = attention deficit hyperactivity disorder, OR = odds ratio, β= regression beta coefficient, HR = hazard ratio.
Adjusting factors:
a
Gender, alcohol use during pregnancy, parental education and family structure.
b
Smoking during pregnancy, social adversity, birth weight and gestational age.
c
Gender, maternal age, alcohol use during pregnancy, family structure and socioeconomic status.
d
Smoking during pregnancy, parity, maternal age and maternal education.
e
Total prenatal sGC dose, interval between prenatal sGC exposure and birth, gender, smoking during pregnancy, parity, birth weight, placental weight,
maternal age, parental education and family structure.
f
Gender, smoking during pregnancy, gestational age, birth weight, maternal age, maternal education, family structure and cohort country.
g
Maternal pre-pregnancy body mass index, smoking during pregnancy, gestational weight gain and age, parity, birth weight, gestational age, parental
education, family structure and socioeconomic status.
h
Birth order, parity, socioeconomic status.
i
Gender, birth weight and gestational age.
j
Gender, maternal tiredness during pregnancy, paternal smoking, family structure, being only child, hyperactivity at 8 years old, paternal admittance to
inpatient psychiatric care.
k
Gender, parity, family structure, socioeconomic status.
INTERNATIONAL JOURNAL OF CIRCUMPOLAR HEALTH 5

Emotional and behavioural problems
There were a total of 38 published articles studying
emotional and behavioural problems. Of the cohort
members, 14.3% scored above the cut-off point for
signs of probable psychiatric disturbance (i.e. having
significant emotional and behavioural problems in the
RB2 total scale) in childhood [51]. Marked gender differ-
ences were found in emotional and behavioural pro-
blems in children and adolescents; the proportion of
scoring above the cut-off point was higher for boys
(19.8%) than for girls (8.7%). Behavioural problems
(9.2%; boys 14.0% and girls 4.1%) were more common
than emotional problems (4.1%; boys 4.3% and girls
3.9%) among children [51]. In adolescence, girls had
more emotional and behavioural problems than boys
[52]. Comparison between individuals of the NFBC1986
at the age of 15–16 years and Greek adolescents aged
18 years showed that Finnish boys scored lower than
Greek boys on 10 of the 11 YSR subscales, especially in
the anxious/depressed scale, and that Finnish girls
scored higher than Greek girls on the somatic com-
plaints and delinquent behaviour scales [53].
Risk or associating factors for emotional problems in
childhood and adolescence
Table 2 presents the risk and associating factors for
emotional and behavioural problems. Regarding emo-
tional problems, female gender [54], single-parent
family [51], problems in motor functions and learning
difficulties [55], multi-site musculoskeletal pain [8] and
physical inactivity [56] were common factors associated
with more severe emotional problems. In addition, use
of cannabis and alcohol in adolescence in females pre-
dicted later inpatient hospital diagnoses of emotional
disorders (e.g. depression), but similar results were not
seen in males [16]. One study found that prenatal glu-
cocorticoid treatment did not predict emotional pro-
blems in childhood, but it was related to a total RB2
problem score [34].
Risk or associating factors for behavioural problems
in childhood and adolescence
Several factors have been examined in relation to beha-
vioural problems among children and adolescents (see
Table 2). Risk factors associated with behavioural pro-
blems were prenatal (e.g. smoking/drinking while preg-
nant, low birth weight), family related (e.g. teenage
mother, single parent) and environmental/socioeco-
nomic factors (e.g. economic exclusion, material depri-
vation) [e.g. 57,58]. Recently, several studies have
looked accumulation of early risk factors to various
outcomes in adolescence and adulthood, such as psy-
chosocial problems [57], school functioning [59], sub-
stance use [60,61] and criminality [62,63]. As to the
prenatal risk factors, the size of the placenta was asso-
ciated with antisocial behaviour [36]. Maternal smoking
during pregnancy was related to behavioural problems
both in childhood and in adolescence in both genders
[64]. The relationship between maternal smoking dur-
ing pregnancy and pain in adolescence was mediated
by childhood and adolescent behavioural problems
[64]. It has also been shown that female gender and
Table 2. Statistically significant findings of risk factors for emotional and behavioural problems in the Northern Finland Birth Cohort
1986.
Risk factors Outcomes and risk estimates (95% confidence intervals)
Pregnancy-related factors
Placental weight Behavioural problems in childhood among boys (OR): 1.1 (1.0–1.3)
a
[36]
Childhood-related risk factors
Single-parent family In childhood (ORs): behavioural problems: among boys 1.8 (1.3–2.5)
b
and girls 2.2 (1.3–3.7)
b
; emotional
problems: boys 2.0 (1.1–3.2)
b
and girls 2.0 (1.1–3.5)
b
[51]
Younger age in the classroom In childhood (ORs): behavioural problems: 1.5 (1.3–1.8); emotional problems: 2.1 (1.7–2.7) [55]
Learning difficulties In childhood (ORs): behavioural problems: among boys 3.1 (2.5–4.0)
c
and girls 3.9 (2.6–5.8)
c
; emotional
problems: among boys 3.0 (2.0–4.6)
c
and girls 5.3 (3.6–8.1)
c
[56]
Intellectual disability Mixed type of problems in childhood (OR): 5.6 (1.9–16.3) [28]
Other risk factors
Multi-site musculoskeletal pain at ages of
16 and 18 years
At the age of 18 years (RRs): distress among boys 3.5 (2.1–5.9)
d
and girls 1.8 (1.2–2.7)
d
; anxiety among boys
1.8 (1.4–2.3)
d
and girls 1.5 (1.0–2.2)
d
[8]
Physical inactivity In adolescence (ORs): anxious/depressed symptoms among boys 2.9 (1.5–5.7)
e
; withdrawn/depressed
symptoms among boys 2.8 (1.8–4.2)
e
and girls 2.3 (1.5–3.6)
e
; somatic complaints among girls 1.4 (1.0–1.9)
e
;
rule-breaking behaviour among girls 1.8 (1.3–2.5)
e
[55]
Abbreviations: OR = odds ratio, RR = risk ratio.
Adjusting factors:
a
Maternal pre-pregnancy body mass index and gestational weight gain, smoking during pregnancy, parity, gestational age, birth weight, maternal age,
parental education, family structure, socioeconomic status.
b
Birth order, parity, maternal age at the time of the child’s birth, socioeconomic status and place of residence.
c
Child’s age, parental education, family structure, socioeconomic status and fine and gross motor skills.
d
Body mass index, level of physical activity, sitting and smoking status at 18 years.
e
Body mass index, family structure, income and parental education.
6J. MIETTUNEN ET AL.

paternal psychiatric hospitalisation are related to dis-
ruptive behaviour disorders without ADHD in adoles-
cence [49].
Some specific child characteristics were associated
with behavioural problems: behavioural problems
were more common among children with intellectual
disability [28] and also learning difficulties were asso-
ciated with behavioural problems in childhood [54].
Psychologically distant interaction with the father was
associated with behavioural problems at school in a
sub-study based on single parent and reconstructed
families [11].
Effects of emotional and behavioural problems on
other factors
Emotional and behavioural problems have been
reported to associate with multi-site musculoskeletal
pains in adolescence [65]. Behavioural problems in
adolescence were also associated with low back pain
[66]. Furthermore, both genders with behavioural pro-
blems in adolescence were less likely to report high
overall academic performance and plans of continuing
into higher education [67]. Conduct disorder sym-
ptoms and inattention-hyperactivity in childhood
increased the risk for obesity and physical inactivity
in adolescence [43]. When emotional problems were
considered as risk factors for different outcomes, chil-
dren with emotional problems were more prone to
withdrawal in adolescence [68]. Each YSR subscale
was strongly associated with concurrent self-reported
life satisfaction in adolescence [68]. In the adjusted
models including substance use, family patterns,
place of residence, family occupational level, parental
alcohol use and parental psychiatric disorder, beha-
vioural problems in childhood and adolescence
predicted later violent crimes or offences against
property in both males and females [16]. Further, in
general, behavioural problems in childhood, but not
emotional problems, were associated with smoking,
alcohol use, and the use of other substances in ado-
lescence [16]. NFBC1986 has also been a part of CARTA
consortium; the consortium study found no causal
association between smoking heaviness and depres-
sion or anxiety [69].
Psychosis risk
In total, there were 27 studies on psychosis risk, most of
these studies explored either prodromal symptoms or
clinical risk (CR), some looked also psychotic diagnoses.
There were 177 cases with known psychosis (based on
registers) in the sample until age of 27 years, the cumu-
lative incidence of all psychoses was 1.9% [17].
Familial risk
Parental psychosis was a significant predictor of off-
spring’s psychosis [17]. FR for psychosis has been inves-
tigated in relation to brain function and structure in
eight previous studies. Figure 2 summarises group dif-
ferences between FR participants and controls in the
fMRI studies and one structural MRI study.
Three studies investigating FR participants and
controls explored functional connectivity in different
brain networks using resting state fMRI. The studies
found that FR participants (vs. controls) demonstrated
decreased default mode network activation [23],
lower central executive network activation [70]and
increased activation in the cerebellum [71]. In a study
of face-processing, fMRI activation to dynamic happy
and fearful faces (relative to control stimulus) were
compared between FR and controls [26]. The authors
found group differences in activation in the prefrontal
Figure 2. Summary of group differences between familial risk (FR) for psychosis and controls in functional and structural MRI
studies in the Northern Finland Birth Cohort 1986. Blue represents decreased fMRI/MRI signal in FR (vs. controls) and red
represents an increase in fMRI/MRI signal in FR (vs. controls).
INTERNATIONAL JOURNAL OF CIRCUMPOLAR HEALTH 7

cortex (PFC) and decreased connectivity between the
amygdala and the PFC in the FR group (vs. controls).
Association between brain grey matter volume and
psychosis risk was investigated using voxel-based mor-
phometry in FSL to map regional grey-matter volumes
in FR participants, CR participants that had prodromal
syndrome according to the SIPS, participants with both
FR and CR, and controls [72]. Individuals with both FR
and CR showed lower cerebellar grey-matter volume
when compared to controls and no other group differ-
ences were found. In one recent study, it was found
that the lowest connectivity in the face-processing net-
work was observed in a group with high polygenic risk
score for schizophrenia [73].
Brain structure in FR individuals was also investigated
using brain diffusion measures (DTI) in two studies. No
differences were discovered in whole-brain central white
matter regions in any DTI measures between FR partici-
pants and controls [27]. Body mass index (BMI) asso-
ciated with lower integrity of white matter in several
brain areas, whereas an opposite pattern was detected
in the control group [74]. Furthermore, there was a
group-by-BMI interaction (FR vs. controls) in the above
white matter microstructural measures.
Somatic health and risk for psychosis
Besides the above reported findings on the effects of
BMI, the associations of other physical measures, as well
as different blood markers, with psychosis risk have also
been studied in the NFBC1986. Physical inactivity in
adolescence was shown to be associated with first-
onset psychosis during a 4-year follow-up period after
adjusting for several confounders [75]. At the same age,
no co-occurrence was reported for other cardiometa-
bolic risk factors, including glucose and lipid metabo-
lism, and first-onset psychosis [76]. In addition, no
association was found between cardiometabolic risk
factors and FR [77].
Levels of circulating inflammatory marker C-reactive
protein (CRP) were associated with schizophrenia by
the age of 27 years [78]. Finally, parental somatic illness
in childhood may also increase psychosis risk in the
offspring. The effect was emphasised in the accumula-
tion of illnesses, as well as in some specific diagnostic
groups [79].
Adolescence substance use and risk for psychosis
Adolescence substance use was studied in relation to
prodromal symptoms and the incidence of psychosis in
four studies [80–83]. The information on substance use
was collected using postal questionnaires and during
the cohort study in adolescence, whereas diagnoses of
psychoses were based on register data.
Adolescents who had tried cannabis (5.6% of the
sample) had higher scores of prodromal symptoms of
psychosis compared to those who had not used canna-
bis. There was also a dose-dependent effect showing
increase in prodromal symptoms as a function of can-
nabis use [80]. In follow-up until the age of 30 years, the
risk of psychosis was higher in individuals who had
used cannabis in adolescence even when adjusted
with prodromal symptoms, also with a dose-dependent
effect showing an increased incidence of psychosis
among those with the most frequent cannabis use [81].
In addition to cannabis use, heavy smoking (i.e. 10 or
more cigarettes a day) in adolescence was indepen-
dently associated with an increased risk of psychosis
by the age of 30 years also with a dose-dependent
effect [82]. During the same follow-up period, the use
of inhalants was associated with incident psychosis
even after controlling for baseline psychotic experi-
ences and substance use, among others [83].
Other studies in psychosis risk
Difficulty in making contact with others, as measured by
sub-score of the PROD-screen in adolescence, was asso-
ciated with an elevated risk of psychosis during the fol-
lowing years, but not with other psychiatric disorders
[84]. Neuropsychological functioning of individuals at
CR and FR for psychosis was assessed in three studies in
the Oulu Brain and Mind Study I. A study using 19
cognitive variables reported that individuals with psycho-
sis performed worse in fine motor skills when compared
with at-risk groups [22]. In another study, the at-risk
groups outperformed the psychosis group in semantic
fluency response initiation [23]. Neither of these studies
found differences between the at-risk groups and con-
trols. A study investigating cognitive performance and
two candidate dopamine receptor D2 polymorphisms,
namely rs6277 and rs1800497, found an association
between poorer cognitive performance and minor allele
rs1800497 in those at FR, but not in those at CR, suggest-
ing different cognitive phenotypes in different risk
groups for psychosis [24]. The statistically significant risk
factors for psychosis are summarised in Table 3.
Other work
The first psychiatric article in the NFBC1986 reported
that 1.5% of the cohort members’mothers used psy-
chotropic drugs during pregnancy [85]. Maternal
advanced age, multiparity, overweight, smoking, alco-
hol use, and low social class increased and failure to
ensure contraception decreased the regular use of
psychotropic drugs during pregnancy.
8J. MIETTUNEN ET AL.

Of the adolescents, about 30% reported loneliness
[86], which was associated with deliberate self-harm
[87] and a dislike of school [88]. More girls (10%)
than boys (7%) were alexithymic in adolescence.
Mother’s low level of education, a broken childhood
home, and living in a rural area were associated with
higher alexithymia [89]. In an fMRI study of subsam-
ple of 104 young adults, early traumas were asso-
ciated with deviant brain response to fearful faces
and weaker performance in fearful facial expression
recognition [90].
Discussion
Main results
So far there have been 94 studies on different psychia-
tric topics in the NFBC1986. The studies have identi-
fied associated factors, brain imaging findings and
cognitive deficits in relation to ADHD, emotional and
behavioural problems and psychosis risk. The studies
have revealed several early risk factors for these men-
tal health problems. For instance: maternal smoking
during pregnancy has been linked with ADHD and
behavioural problems; social problems with ADHD,
emotional problems and psychosis risk; low physical
activity and substance use with emotional and beha-
vioural problems and psychosis risk; and single family
with ADHD and emotional and behavioural problems.
Several brain regions were associated with FR of psy-
chosis in the NFBC1986. Specifically, the brain imaging
data suggest that FR relates to alterations in the
default mode network, central executive network, cer-
ebellum and PFC.
Significance of the NFBC1986 findings
The early studies focused mainly on ADHD and other
childhood mental health problems, but during recent
years there has been an increase in studies, especially
in psychosis risk research. The ADHD studies got a lot
of attention as for instance the top journal in the
field of child and adolescent psychiatry, the Journal
of the American Academy of Child and Adolescent
Psychiatry, published several NFBC1986 studies in a
special issue in 2007.
There has been significant international collaboration
in the NFBC1986, as two-thirds of the studies (63 out of
94) included international co-authors from, for instance,
Imperial College London, University of Cambridge,
University of California Los Angeles, and University of
Michigan. NFBC1986 has been also part of the Nordic
ADHD network [30,31,35,42]. The number of psychiatric
studies in the NFBC1986 has increased rapidly during
the last years, as 69 of 94 studies (73%) were published
in 2010 or later. The current research is extremely
active, as 21 studies were published 2017–2018.
Comparison to other birth cohort studies
There are several birth cohorts worldwide. The other
birth cohorts in circumpolar region include e.g. the
Finnish nationwide register-based birth cohorts (chil-
dren born 1987 and 1997) [91], the Uppsala Birth
Cohort Multigeneration Study (UBCoS, 1915–1929)
[92], and the Norwegian Mother and Child Cohort
Study (MoBa, 1999–2009) [93]. The first aboriginal
birth cohort has started in Canada with a focus on
causes of fat gain [94]; however there are no birth
Table 3. Statistically significant findings of risk factors for psychosis in the Northern Finland Birth Cohort 1986.
Risk factors
Risk estimates (95% confidence
intervals) for psychotic diagnoses
Adolescent physical inactivity Any psychosis (OR): 3.3 (1.4–7.9)
a
[75]
Increased CRP levels at adolescence Schizophrenia (OR): 1.25 (1.1–1.5)
b
[78]
Paternal neoplasms before age 18 years Any psychosis (OR): 2.8 (1.4–5.6)
c
[79]
Paternal factors influencing health status and contact with health services before 18y Any psychosis (OR): 2.7 (1.4–5.3)
c
[79]
Any adolescent cannabis use Any psychosis (HR): 2.9 (1.7–4.7) [81]
Using cannabis more than 5 times Any psychosis (HR): 3.0 (1.1–8.0)
d
[81]
Adolescent tobacco (more than 10 cigarettes/day) use Any psychosis (HR): 2.0 (1.1–3.5)
e
[82]
Adolescent inhalant use more than 5 times Any psychosis (HR): 3.1 (1.1–3.0)
f
[83]
Two or more social problem items in PROD-screen in adolescence Any psychosis (RR): 3.6 (2.1–6.1)
g
[84]
Three or more social problem items in PROD-screen in adolescence Any psychosis (RR): 6.2 (2.6–15.0)
g
[84]
Abbreviations: CRP = C-reactive protein, OR = odds ratio, HR = Hazard ratio, RR = Risk ratio, PROD-screen = a screen for prodromal symptoms of psychosis.
Adjusting factors:
a
Gender, family structure, parental socioeconomic status and parent’s physical activity.
b
Gender, age, body mass index, smoking and alcohol use, and maternal education.
c
Gender, perinatal complications, paternal age, parental socioeconomic status, parental psychiatric comorbidity and child’s cannabis use.
d
PROD-screen, other substance use, frequent alcohol use, daily tobacco smoking and parental psychosis.
e
PROD-screen, cannabis use, frequent alcohol use, other substance use, parental substance abuse and parental psychosis.
f
PROD-screen, cannabis use, comorbid mental disorder and parental substance use,
g
Gender and parental psychosis.
INTERNATIONAL JOURNAL OF CIRCUMPOLAR HEALTH 9

cohorts in the area yet focusing also on mental health
issues. Future birth cohort studies in the north should
also focus on mental health of indigenous population.
So far, the only studies on mental health in these
populations are from Australia [95].
There have been several other birth cohorts, which
have been investigating factors related to psychosis. A
review of antecedents of schizophrenia in birth cohorts
found 11 birth cohorts from 7 countries [3]. The Avon
Longitudinal Study of Parents and Children (ALSPAC)
birth cohort is one of the largest of the younger birth
cohorts (children born in the early 1990s). The studies in
relation to psychosis and depression have been recently
reviewed [2].
Regarding cannabis use, smoking and the risk for
psychosis, the NFBC1986 results are in line with the
findings in the ALSPAC cohort, where they were asso-
ciated with both depression and psychotic episodes
[2]. Interestingly, in the NFBC1986 the prevalence esti-
mates are very high when compared to other samples,
both in ADHD [6] and in psychoses [17]. The high
prevalence estimates enable to investigate these dis-
orders diversely in the NFBC1986.
When we compare the NFBC1986 with the older
birth cohort NFBC1966, the younger cohort includes
more high-quality registers and the childhood and ado-
lescence follow-up include substantially more mental
health related data than the older cohort. The older
birth cohort has been studied especially for adult schi-
zophrenia [4], while the research in the younger birth
cohort has been more varied.
Based on our experience on the birth cohorts, the
future cohorts should start early, e.g. include informa-
tion already on mental well-being of mothers during
pregnancy and have large enough sample size with
frequent follow-ups with good participation rates.
These are not easily achieved goals; the challenges in
general and especially in indigenous populations
relate, e.g. to locating participants, to the maintenance
between follow-up waves and to cross-cultural differ-
ences between the researchers and the cohort partici-
pants [96].
Strengths and limitations
The strengths of birth cohort samples in general, and
also of the NFBC1986, include the prospective design
and large number of population-based age-matched
comparison subjects for those with mental health
problems. This design provides unique possibilities
to analyse causal relationships, such as the effect of
risk factors during pregnancy and delivery on later
risk of illness; the studies have also collected a large
number of potential covariates, which have been
included in statistical models. Good participation
rate, homogeneous population and possibility to uti-
lise register data have been the major advantages to
conduct birth cohort research in the Northern
Finland. There have only been two large data collec-
tions in the NFBC1986. However, the participation in
these two follow-ups has been very good, approxi-
mately 90% of teachers and 88% of parents partici-
pated when children were 8 years, and 76% of
adolescents and 72% of parents when children were
15–16 years. When compared to other population-
based studies, it can be noted that the NFBC1986 is
genetically and culturally highly homogeneous. A
major benefit in the NFBC1986 is also the possibility
to utilise large nationwide health registers. Linking
the cohort data to register data enables researchers
to study various outcomes, such as hospital care,
relatively easily and with low attrition. The
NFBC1986 studies utilising cognitive and brain ima-
ging data differ from most of the other studies on
these topics, as in those studies cases are often col-
lected from clinical samples and from one treatment
setting, and controls are not included or are of strictly
selected volunteers.
Conclusions
The studies in the NFBC1986 have found several early
predictors for different psychiatric outcomes. There are
also several interesting findings related to brain ima-
ging and cognition. The next large follow-up of the
NFBC1986 will begin in 2019. This follow-up will include
some of the same topics as before, but also new instru-
ments relating, for instance, to empathy, temperament,
anxiety and depression. The current review can be used
to learn about the work done in the NFBC1986 until
today. The data is available for future research on
request (see: http://www.oulu.fi/nfbc). The NFBC1986
has been utilised frequently in psychiatric research
and future data collections are likely to lead to new
scientifically important findings.
Acknowledgments
Wewouldliketoacknowledgeall the participants in this
study and the researchers who collected the data.
Disclosure statement
No potential conflict of interest was reported by the authors.
10 J. MIETTUNEN ET AL.

Funding
This work was supported by the Academy of Finland
[268336]; Alfred Kordelinin Säätiö; Juho Vainion Säätiö
[201610329]; Orion Research foundation; Suomen
Kulttuurirahasto [00160427]; Suomen Lääketieteen Säätiö.
ORCID
Jouko Miettunen http://orcid.org/0000-0003-0575-2669
Lassi Björnholm http://orcid.org/0000-0002-3371-4638
Sanna Huhtaniska http://orcid.org/0000-0002-0292-2581
Lotta Kinnunen http://orcid.org/0000-0001-5428-6938
Johannes Lieslehto http://orcid.org/0000-0001-8258-8458
Tanja Nordström http://orcid.org/0000-0002-1170-9125
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