Referencing information: Elonheimo H, Gyllenberg D, Sillanmäki L, Sourander A (2016) Crime in the Continuum of Problems from Childhood to Adulthood: Results from the FinnCrime Study. A conference presentation in The VII Conference on Childhood Studies. University of Turku, June 7, 2016.

1. Crime in the Con+nuum of Problems
from Childhood to Adulthood:
Results from the FinnCrime Study
The VII Conference on Childhood Studies. University of
Turku, June 7, 2016.
Henrik Elonheimo
LL.D., Docent of Criminology
Faculty of Law & Research Centre for Child Psychiatry
University of Turku, Finland
E-mail: henelo@utu.fi
Co-authors (Research Centre for Child Psychiatry):
Gyllenberg D, Sillanmäki L, Sourander A

2. The FinnCrime Study
• Research Centre for Child Psychiatry
coordinates various big data sets (register
data & ques+onnaires) that can also be used
for studying crime
• The main criminological project is the follow-
up of the 1981 birth cohort
Henrik Elonheimo / FinnCrime 1

3. The Academic Context of FinnCrime
– Developmental life-course criminology (DLC)
• Builds on the Criminal career paradigm from the
1980s
– Epidemiological criminology
• Public health perspec-ve
• Empirical methods to study phenomena defined by
the law and criminal jus+ce
– How much crime there is? What is it like? How does it
change by age? What causes it?
– Paramount aims: Evidence-based criminal policy + theory
development
Henrik Elonheimo / FinnCrime 2

4. The main research ques+ons
Key criminological topics: natural histories and risk
factors of crime:
1) Occurrence of crime between ages 15-30: prevalence,
frequency (lambda), specializa+on, crime mix,
accumula+on, and trajectories of crime in the life-course
2) Psychosocial Predictors (age 8) & Correlates (ages
18-23) of crime: How can we iden-fy future offenders?
Are risk factors general or crime type / gender specific?
Are there different developmental trajectories of
offending with unique risk factors?
Henrik Elonheimo / FinnCrime 3

5. Material & Methods
The na+onally representa+ve, popula+on-based
sample includes 5,405 males and females born all
over Finland in 1981
– The original sample was 10% of the whole age group of
about 60,000 males and females
– A balanced gender distribu+on: 2717 (50.3%) males and
2688 (49.7%) females
Henrik Elonheimo / FinnCrime 4

6. Data on crime
The Finnish Na-onal Police Register: all police
contacts the subjects had between ages 15 to 30
= all cases where they have been suspected of crime
– In Finland, criminal responsibility begins at age 15
• Offenders categorized according to
– Crime type: drug / violent / property / traffic / drunk
driving / sexual offences
• Minor traffic offences excluded
– Offending frequency (e.g., casual, recidivist, ac-ve
recidivist)
Henrik Elonheimo / FinnCrime 5

7. Data on risk factors
Age 8 (1989)
• Data on demographic and psychosocial risk factors
• Ques+onnaires to:
1. Children: Children’s Depression Inventory (CDI)
Feelings of sadness, success, joy, worrying, self-esteem, fearfulness, self-blaming,
loneliness, sleeping problems, -redness, school aQainment, enjoying school and social
situa-ons, geRng along with people, having friends, feeling that is being cared by
someone
2. Parents and teachers (RuAer)
-evaluated the child’s behavior during the last 12 months on three scales:
– Conduct (the child steals, breaks things, is disobedient, lies, fights or argues with
other children)
– HyperacCvity (the child is restless, unable to sit s-ll and concentrate for any longer
while)
– EmoConal (anxiety, tension, fearfulness, withdrawal)
Henrik Elonheimo / FinnCrime 6

8. +Addi+onal ques+ons:
– Family structure (living with both biological parents or not)
(parents)
– Parents’ educa-onal level (comple+on of 12 years’
schooling vs. others) (parents)
– Child’s school performance (average / beoer / worse)
(teachers)
Henrik Elonheimo / FinnCrime

9. • Military call-up (only males)
• The ques+ons concerned
1. demographic, family, and life event variables
2. adap+ve func+oning
3. mental health
4. substance use
Instruments:
• Young Adult Self-Report (YASR)
– externalizing (delinquency, aggressiveness, intrusiveness)
– internalizing scales (withdrawal, anxious–depressiveness)
– thought and aoen+on problems
– soma+c complaints scales
• Sense of coherence (Antonovsky)
Henrik Elonheimo / FinnCrime 8
Data at age 18 (1999)

10. • The Finnish Na-onal Military Register
• Diagnoses between ages 18-23, based on medical examina+ons
during call-up and service
• ICD-10 classifica+on
• Diagnoses classified into six groups:
– Personality (behavioral problems or an+sociality)
– Substance use
– Psycho+c
– Anxiety (fear of social situa+ons, public places, panic disorders)
– Depressive
– Adjustment disorders
• Also those individuals reached who have not been in contact with
psychiatric services in the health care sector
Henrik Elonheimo / FinnCrime 9
Data on psychiatric disorders

11. Data on mortality
• Ques+on: How is the individual level of
offending associated with mortality?
• Data on mortality and causes of death were
received from Sta-s-cs Finland (up to age 30)
Henrik Elonheimo / FinnCrime 10

12. Results on male youth crime (ages
16-20)
• Prevalence: 23% of the males registered for crime
• Prevalence of different types of offenders
• Property 318 11%
• Traffic 314 11%
• Violent 205 7%
• Drunk drivers 152 5%
• Drug offenders 106 4% All crime types correlated with each other.
• Frequency of offending (lambda)
0 crimes 2205 77%
1-2 425 15%
3-5 120 4%
>5 116 4%
HIGH ACCUMULATION: The most criminally active 4% committed 72% all crimes.

13. Childhood (independent) predictors of
male youth crime
• Broken family
• Low parental education
• Conduct problems
• Hyperactivity
Reservations:
• The risk factors do not determine criminal future
• Causality may stem from family conflict, parenting practices,
stress, discontinuity, heredity rather than a broken family or low
SES as such
12

14. Independent correlates at age 18
• Small community size (casual crime only)
• Parents’ divorce
• Dating (casual crime only)
• Self-reported delinquency
• Regular smoking
• Regular drunkenness
13

15. General findings
• Almost all psychosocial problems correlated with
crime
• Problems were related par+cularly to ac+ve
offenders
• Support for a general theory: The same factors
predicted many crime types

16. Service use
Although the most crime-ac+ve group was able to self-
report mul+ple problems (age 18), only 3% had u+lized
mental health services during the last 12 months
à Services did not reach the ones most in need

17. Psychiatric Diagnoses & Crime
• 10% of the boys had psychiatric disorder(s)
– This group commioed almost 50% of all crime
– Almost half of them (48%) had been registered for crime (from
the others, the propor+on of offenders was only 19%)
• Personality and substance use disorders were par+cularly
criminogenic
– Mere depression was not associated with offending
• Also psychiatric disorders covaried linearly with offending
frequency
– Of all offenders, 23% had been diagnosed
– Of the ac+ve recidivist group, 59% had psychiatric disorder(s)

18. Crimes between ages 15-30
Henrik Elonheimo / FinnCrime 17
• 2304 (43%) of the subjects had been registered
for offending
– Of males 1626 (60%)
– Of females 678 (25%)
• Altogether over 16,400 crimes
– Property and traffic crime were the most common
crime types; their share of all criminal incidents was
68%
– Sex crimes were the most rare, less than 1% of all
incidents

19. Crime is a male phenomenon
• Male share of all crimes 83%; female share 17%
• Of all offenders, 71% male
• Propor-on of males in each crime type (% of incidents)
1. Sex (98)
2. Drunk driving (92)
3. Violence (89)
4. Traffic (87)
5. Property (78)
6. Drug (77)
Henrik Elonheimo / FinnCrime 18

20. Prevalence of crime types, ages 15-30
Males
1. traffic 47.4%
2. property 21.0%
3. violence 15.6%
5. drunk dr 12.3%
6. drug 6.8%
7. sexual crime 1.3%
Females
1. traffic 14.6%
2. property 8.5%
3. violence 3.4%
4. drug 2.4%
5. drunk dr 2.0%
6. sexual crime .04%
• The order of
prevalence of the
crime types is almost
iden+cal across
genders
• Prevalence for every
type of crime is
considerably higher for
males than females

21. 20
• One of the best know phenomena in criminology: crime
peaks in late adolescence
– However, does it stand for
• Prevalence, frequency or both?
• Both genders?
• Various crime types?
Age-crime curve

22. Age-crime curve: what we found
• Prevalence peaks in late teenage years,
lowering evenly with age (towards age 30)….
• ….But only for males à the age-crime curve is
gender specific: no peak age for females
– The female rate of criminal par+cipa+on remained
at a stably low level throughout the years, with
only a slight decreasing trend toward age 30

23. General prevalence of crime
Henrik Elonheimo / FinnCrime 22

24. Prevalence of crime & crime types between ages
15-30 in males & females

25. General lambda
Henrik Elonheimo / FinnCrime 24

26. Overlap between the crime types,
ages 15-30
• All crime types correlated significantly with each other

27. Pairwise overlap of crime types
26
• The strongest pairwise associa+on between drug and
property offenses: of drug offenders, 75% had also
property crimes

28. Henrik Elonheimo / FinnCrime 27
• Males: The most criminally ac+ve 1% of the males was
responsible for 34% of the crimes commioed by all males
– over half (53%) of crimes can be aoributed to the worst
3% of males
• Females: The most criminally ac+ve 1% of the females
responsible for 57% of all female crimes
• All: Of pooled males and females, the most criminally ac+ve
1% accounted for 42% of all crimes
Concentra+on of crime, ages 15-30

29. Henrik Elonheimo / FinnCrime 28
Crime & death up to age 30

30. 29
The risk of death increased along with the level of
offending.

31. Henrik Elonheimo / FinnCrime 30
The risk of death was even higher for female than
male offenders.

32. Henrik Elonheimo / FinnCrime 31
offenders’ death causes were less oten
natural, including more accidents, suicide, and
homicide.
When we categorized the causes of death into
four groups:
1. Natural, sickness
2. Accidents
3. Suicide
4. Homicide

33. 32
• Crime can be predicted already in childhood
• Independent risk factors / correlates arose from all
informaCon sources available at different ages
• children’s / youngsters’ self-reports
• parent & teacher reports
• medical reports
à Various possibili+es to detect the risk
• Lambda was directly associated with various adversi+es
• Early death is the ul+mate form of adverse health and ill-
being experienced by offenders
Main conclusions

34. TheoreScal implica+ons
• Crime as a part of problem gravitaSon along
the life-course
• Crime may result from stress or frustraSon
caused by the accumulaSon of negaSve life
events
Henrik Elonheimo / FinnCrime 33

35. Criminal policy implica+ons
Henrik Elonheimo / FinnCrime 34
• Offenders’ need for rehabilitaSon should be more effec+vely
recognized in the criminal jus+ce system
• Crime as a public health rather than a penal problem
• Referring to services should be more systema+c
• The role of different actors: school, army, police
• Also contact with the police would offer a possibility for
screening for offenders’ health problems and guiding them
to further services
• Early intervenSon, because problems are seen early
• There is evidence on the cost-effec-veness of early preven+on
programmes
• They benefit child development also from other than a
criminological perspec+ve

36. • How to target interven+ons?
– Aoen+on to
• those with the highest risk
• general risk factors & correlates
– Due to the overlap between the crime types and the similarity of
their risk factors, preven+on is likely to effect mul+ple crime
types at the same +me
• Versa+le interven+ons targe+ng mul+ple risk factors
at the same +me
• Parent-training, home visi+ng programs, prenatal & child
welfare clinics
– Strongest Families programme of University of Turku
• Relieving the stresses related to divorce & low SES
• Family media+on & other restora-ve prac-ces
35

37. Thank you!
Correspondence: henelo@utu.fi
Henrik Elonheimo / FinnCrime 36