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Scandinavian Journal of Child and Adolescent Psychiatry and Psychology logoLink to Scandinavian Journal of Child and Adolescent Psychiatry and Psychology
. 2019 May 30;7:52–59. doi: 10.21307/sjcapp-2019-008

Changes in delinquency according to socioeconomic status among Finnish adolescents from 2000 to 2015

Noora Knaappila 1,*, Mauri Marttunen 1, Sari Fröjd 2, Nina Lindberg 3, Riittakerttu Kaltiala-Heino 2,4,5
PMCID: PMC7709941  PMID: 33520768

Abstract

Background: Scientific literature suggests that the prevalence of delinquency amongst adolescents has decreased internationally in past decades. However, whether this change is consistent across all socioeconomic groups has not yet been studied.

Objective: The aim of this study was to examine changes in delinquency amongst Finnish adolescents according to socioeconomic status between 2000 and 2015.

Method: A population-based school survey was conducted biennially amongst 14-16-year-old Finns between 2000 and 2015 (n = 761,278). Distributions for delinquency and socioeconomic adversities (low parental education, not living with both parents and parental unemployment in the past year) were calculated using crosstabs. Associations between delinquency, time, and socioeconomic adversities were studied using binomial logistic regression results shown by odds ratios with 95 % confidence intervals.

Results: Delinquency was positively associated with all three socioeconomic adversities studied and cumulative socioeconomic adversity. Although the prevalence of delinquency varied only slightly between 2000 and 2015 in the overall population, it increased significantly amongst adolescents with most socioeconomic adversities.

Conclusions: The findings indicate that socioeconomic differences in delinquency have increased amongst Finnish adolescents in past decades. Delinquency prevention and intervention programs should take socioeconomic adversities into account.

Keywords: Adolescent, delinquency, socioeconomic factors, surveys and questionnaires

Introduction

Delinquency and other problem behaviors are rather common amongst adolescents (1, 2). Delinquency encompasses a wide range of antisocial acts which are illegal or lawfully interpreted as constituting delinquency, including theft, violence and destruction of property (3). The prevalence of delinquency amongst adolescents varies between 6 and 18 % in Europe and the United States of America (4, 5). Unlike assumed in the public debate, the prevalence of delinquency has not increased internationally in past decades, but on the contrary, it may have even decreased (6-9).

Research has identified several risk factors for delinquency, including male gender (10), genetic factors (10), lower intellectual ability (11), aggressiveness (1), mental health disorders (12, 13), exposure to maltreatment in childhood (14, 15) and delinquent peers (16). In addition, low socioeconomic status (SES) increases the risk for delinquency. SES is an aggregate concept comprising resource-based (such as material and social resources) and prestige-based (individual’s rank or status) indicators of socioeconomic position, which can be measured at both individual, household and neighborhood levels (17). It can be assessed through individual measures, such as education, income or occupation (18, 19), but also through composite measures that provide an overall index of socioeconomic level. Delinquency has been observed to be more common amongst adolescents living in non-intact families than amongst those living in intact families (2, 20-24). Delinquency has also been associated with low level of parental education (20-22, 24) and parental unemployment (25, 26).

Scientific evidence suggests that socioeconomic disparities have increased in several areas of adolescent health and well-being in the Nordic countries in past decades. Torikka et al. (27, 28) found that socioeconomic differences in the prevalence of depression, frequent alcohol use and drunkenness increased amongst Finnish adolescents from 2000 to 2011. Socioeconomic disparities also increased in self-rated health amongst Swedish adolescents between 2002 and 2014 (29). In a Finnish time series study (30), the overall prevalence of bullying at school varied only slightly between 2000 and 2015, but both bullying perpetration and victimization increased amongst adolescents with most socioeconomic adversities. Therefore, although the overall prevalence of delinquency has not increased, this may not be true in all socioeconomic groups. To the best of our knowledge, however, no studies have so far investigated changes in delinquency amongst adolescents according to the SES.

Delinquency has negative consequences for the individual, being associated with school dropout (31), substance abuse (32), mental health disorders (33) and criminality later in life (1). In addition to individual suffering, delinquent behavior has far-reaching impacts on society, impairing perceived safety in the community (34) and inflicting significant costs on the public economy (35). In order to prevent delinquency, scientific knowledge on its risk factors and trends is essential. The aim of this study was to examine changes in delinquency according to SES amongst Finnish adolescents between 2000 and 2015. Our research questions were:

  • RQ1.

    Did the prevalence of delinquency change amongst Finnish adolescents between 2000 and 2015?

  • RQ2.

    Was delinquency associated with socioeconomic adversities (low parental education, not living with both parents and parental unemployment in the past year)?

  • RQ3.

    Were the changes in delinquency over time similar across socioeconomic groups?

Methods

Data and participants

The School Health Promotion Study is a nationwide anonymous classroom survey that examines the health, health behavior and school experiences of Finnish adolescents. The survey has been conducted biennially since 1996 amongst 8th and 9th graders with pooled two-year data. The survey is sent to every municipality in Finland, and the municipalities decide if the schools in their area participate in the survey. This study comprises the responses of 8th and 9th graders between 2000 and 2015. Altogether, 761,278 (50,404-109,127 biennially) 8th and 9th graders participated in the survey. The 8th graders were 14-15 years old and the 9th graders were 15-16 years old at the time of the surveys. The biennial cohorts covered 43-82 % of the whole age cohort of the country. The study was approved by the ethics committee of Pirkanmaa Hospital District and the National Institute of Health and Welfare.

Measures

The self-report questions on delinquent behavior were adapted from the Finnish Self-Report Delinquency Study questionnaire, which is a modified version of the International Self-Report Delinquency Study (ISRD) instrument (36). The ISRD instrument has been shown to possess adequate reliability in test-retest studies (37). Delinquent behavior was elicited with five questions: ‘During the past 12 months have you 1) drawn tags or graffiti on walls or elsewhere?; 2) deliberately damaged or destroyed school property or the school building; 3) deliberately damaged or destroyed other property; 4) stolen from a shop or a stall; 5) beaten someone up?’ The questions remained constant over the study years. Response options to all questions were no (= 0), once (= 1), 2-4 times (= 2) and more than 4 times (= 3). A sum score ranging between 0 and 15 was formed of the five questions, in which a value of 4 or more (representing the 90th percentile) was used to indicate delinquency. The 90th percentile cut-off point has been used previously in the scientific literature (38). A considerable benefit of using a relative measure, as opposed to an absolute measure, is that it takes into account the varying prevalence of delinquency across different countries and cultures.

The socioeconomic variables recorded were parental education, parental unemployment in the past year and family structure. Parental education was elicited as follows: ‘What is the highest educational qualification your father/mother has achieved?’ The response options in the 2000 questionnaire were: ‘basic school/vocational school/high school and/or vocational school/university or polytechnic’. The response options varied a little over time: for instance, in the 2013 questionnaire there was a response option ‘no education’, which was removed again in the 2015 questionnaire. For the analyses, parental education was dichotomized as parental basic education only (including the response alternative ‘no education’) versus other. Parental unemployment was elicited as follows: ‘Have your parents been unemployed or laid off work during the past year?’ The response alternatives were the same in all questionnaires: ‘neither/one parent/both parents’. The family structure was elicited as follows: ‘My family consists of...’. The response options in the 2000 questionnaire were: ‘mother and father/mother and stepfather/father and stepmother/mother only/father only/spouse/other caregiver’. The response options varied slightly over time. For the analyses, family structure was dichotomized as living with both parents versus other. In this paper, all three variables are referred to as socioeconomic adversities. In addition, a variable ‘cumulative socioeconomic adversity’ was created, in which all three socioeconomic variables were combined: a score of 0 stood for having no socioeconomic adversities (living with both parents, no parental unemployment and at least one parent with higher than basic education) and a score of 4 stood for having all socioeconomic adversities studied (not living with both parents, both parents unemployed, both parents with basic education only). The prevalence of socioeconomic adversities is presented elsewhere (30).

Statistical analyses

All statistical analyses were conducted using SPSS software (Version 24). Distributions of delinquency and socioeconomic adversities for both sexes during the time period 2000-2015 are presented in Table 1. Bivariate associations were studied using binomial logistic regression results shown as odds ratios with 95 % confidence intervals. Delinquency was entered as dependent variable. In the first model, categorical time periods (2000-2001, 2002-2003, 2004-2005, 2006-2007, 2008-2009, 2010-2011, 2012-2013, 2014-2015) were entered as independent factors using the time period 2000-2001 as a reference category. In the second model, family structure (living with both parents/other), parental unemployment in the past year (neither/one parent/both parents) and parental education (both parents basic education only/other) were entered as independent factors one at a time. In the third model, the file was split according to categorical time periods and cumulative socioeconomic adversity was entered as an independent factor.

TABLE 1.

Delinquency and socioeconomic adversities among Finnish boys and girls in the 8th and 9th grades of comprehensive school.

Boys (n = 381,527) Girls (n = 376,814) p
Age (Mean (SD)) 15.4 (0.7) 15.3 (0.6) < 0.001
Delinquency < 0.001
 Yes 11.0 6.4
 No 81.2 87.0
 Missing 7.7 6.6
Lives with both parents < 0.001
 Yes 74.4 73.7
 No 23.3 25.1
 Missing 2.3 1.2
Both parents only basic education < 0.001
 Yes 5.6 5.9
 No 86.8 87.5
 Missing 7.6 6.6
Parental unemployment past year < 0.001
 No 70.9 69.9
 One parent 23.6 25.6
 Both parents 3.2 3.3
 Missing 2.3 1.2

Results

Distributions of delinquency and socioeconomic adversities for both sexes during the time period 2000-2015 are presented in Table 1. Delinquency was more common amongst boys than girls: in the whole sample, 11 % of boys and 6 % of girls scored to the 90th percentile in delinquent behavior (Table 1). At the overall level, no significant changes were observed in the prevalence of delinquency amongst either boys or girls (Table 2).

TABLE 2.

Delinquency over time among Finnish boys and girls in the 8th and 9th grades of comprehensive school

2002-2003 2004-2005 2006-2007 2008-2009 2010-2011 2012-2013 2014-2015
Boys 0.6 (0.6-0.7) 0.5 (0.5-0.5) 0.5 (0.4-0.5) 0.5 (0.5-0.6) 0.5 (0.5-0.6) 0.5 (0.5-0.6) 0.4 (0.4-0.5)
Girls 0.6 (0.5-0.6) 0.5 (0.4-0.5) 0.4 (0.4-0.4) 0.6 (0.5-0.6) 0.6 (0.6-0.7) 0.5 (0.5-0.6) 0.3 (0.3-0.4)

Note. OR (95% CI). Time period 2000-2001 used as a reference category

Associations between delinquency and socioeconomic adversities are presented in Table 3. Delinquency was associated with all three socioeconomic adversities studied. Delinquency was more common amongst adolescents with parental basic education only compared to adolescents with higher parental education, and amongst adolescents not living with both parents compared to adolescents living with both parents. Delinquency was also positively associated with parental unemployment in the past year. The more socioeconomic adversities accumulated, the more likely was delinquency.

TABLE 3.

Delinquency by socioeconomic adversities among Finnish boys and girls in the 8th and 9th grades of comprehensive school

Boys Girls
Family structure
 Both parents ref ref
 Not living with both parents 1.9 (1.9-1.9) 1.9 (1.8-1.9)
Both parents with low education
 No ref ref
 Yes 1.7 (1.6-1.8) 1.5 (1.4-1.6)
Parental unemployment
 Neither parent ref ref
 One parent 1.5 (1.5-1.5) 1.6 (1.6-1.7)
 Both parents 3.9 (3.8-4.1) 3.2 (3.0-3.4)

Note. OR (95% CI)

Differences in delinquency between socioeconomic groups increased over the study period. Although the prevalence of delinquency varied only slightly between years amongst adolescents with least socioeconomic adversities, it increased amongst adolescents with most socioeconomic adversities amongst both sexes (Table 4). Similarly, although the ORs for delinquency varied only slightly amongst adolescents with least socioeconomic adversities, they increased amongst adolescents with most socioecomic adversities (Table 5).

TABLE 4.

Delinquency over time by cumulative socioeconomic adversity among Finnish boys and girls in the 8th and 9th grades of comprehensive school

2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 2010-2011 2012-2013 2014-2015 p*
Boys
Number of sociodemographic adversities
0 9.1 (1,851/20,280) 10.4 (2,792/26,737) 8.1 (2,289/28,427) 7.3 (2,230/30,572) 9.0 (2,640/29,479) 8.7 (2,291/26,408) 7.9 (1,764/22,457) 5.7 (642/11,238) < 0.001
1 12.2 (1,551/12,728) 14.8 (2,183/14,775) 11.0 (1,676/15,212) 10.6 (1,551/14,605) 12.3 (1,841/14,917) 12.4 (1,885/15,241) 11.3 (1,700/15,016) 9.4 (773/8,195) < 0.001
2 18.5 (869/4,696) 19.9 (998/5,005) 15.6 (762/4,874) 17.7 (791/4,478) 18.2 (851/4,664) 18.2 (923/5,067) 17.1 (941/5,495) 12.5 (394/3,158) < 0.001
3 26.9 (242/898) 26.7 (228/854) 26.2 (225/859) 31.0 (221/714) 30.0 (200/634) 29.6 (262/886) 26.0 (230/886) 24.0 (129/538) < 0.001
4 46.4 (51/110) 63.1 (82/130) 58.0 (69/119) 72.7 (96/132) 74.1 (106/143) 67.6 (119/176) 64.7 (145/224) 73.1 (144/197) < 0.001
Girls
Number of sociodemographic adversities
0 5.0 (972/19,334) 5.2 (1,291/24,946) 4.1 (1,110/26,882) 3.8 (1,121/29,410) 5.1 (1,460/28,625) 5.4 (1,375/25,437) 4.2 (913/21,970) 2.6 (290/11,269) < 0.001
1 7.1 (907/12,767) 7.5 (1,098/14,563) 6.3 (959/15,168) 6.1 (942/15,445) 7.9 (1,249/15,846) 8.8 (1,371/15,644) 6.9 (1,051/15,316) 4.3 (366/8,577) < 0.001
2 10.4 (542/5,188) 11.0 (591/5,360) 8.2 (465/5,662) 9.0 (456/5,062) 10.4 (529/5,085) 12.8 (741/5,785) 10.0 (615/104) 6.8 (243/3,556) < 0.001
3 14.2 (137/968) 14.2 (136/960) 14.6 (129/885) 16.0 (120/749) 18.1 (138/764) 16.8 (181/1,078) 14.9 (159/1,068) 9.0 (59/656) < 0.001
4 22.4 (19/85) 25.8 (24/93) 38.2 (34/89) 37.8 (37/98) 51.0 (52/102) 47.9 (78/163) 40.1 (69/172) 51.1 (47/92) < 0.001

Note. % (n/N); *p-values were calculated by Mantel–Haenzel χ2 test

TABLE 5.

Delinquency over time by cumulative socioeconomic adversity among Finnish boys and girls in the 8th and 9th grades of comprehensive school

2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 2010-2011 2012-2013 2014-2015
Boys
Number of sociodemographic adversities
1 1.3 (1.2-1.4) 1.5 (1.4-1.6) 1.4 (1.3-1.5) 1.5 (1.4-1.6) 1.4 (1.3-1.5) 1.5 (1.4-1.6) 1.5 (1.4–1.6) 1.7 (1.5–1.9)
2 1.9 (1.8-2.1) 2.2 (2.0-2.3) 2.1 (2.0-2.3) 2.8 (2.5-3.0) 2.3 (2.1-2.5) 2.4 (2.2-2.6) 2.4 (2.2–2.7) 2.4 (2.1–2.7)
3 3.0 (2.5-3.5) 3.1 (2.7-3.7) 4.1 (3.5-4.9) 5.9 (5.0-7.0) 4.6 (3.8-5.4) 4.5 (3.9-5.3) 4.2 (3.5–4.9) 5.4 (4.3–6.7)
4 6.6 (4.3-10.0) 15.7 (10.9-22.7) 17.2 (11.8-25.0) 35.3 (23.8-52.3) 31.8 (21.5-47.1) 24.0 (17.2-33.4) 23.3 (17.4–31.0) 50.5 (35.9–71.0)
Girls
Number of sociodemographic adversities
1 1.3 (1.2-1.5) 1.5 (1.4-1.6) 1.6 (1.4-1.7) 1.6 (1.5-1.8) 1.6 (1.5-1.7) 1.7 (1.6-1.8) 1.7 (1.6–1.9) 1.7 (1.4–2.0)
2 1.9 (1.7-2.1) 2.3 (2.1-2.5) 2.1 (1.9-2.3) 2.5 (2.2-2.8) 2,2 (2.0-2.4) 2.6 (2.4-2.8) 2.6 (2.3–2.9) 2.8 (2.4–3.3)
3 2.5 (2.0-3.0) 3.0 (2.5-3.7) 4.0 (3.3-4.8) 4.8 (3.9-5.9) 4.1 (3.4-5.0) 3.6 (3.0-4.2) 4.1 (11.5–21.5) 3.8 (2.8–5.0)
4 5.3 (3.0-9.2) 6.3 (3.9-10.1) 15.0 (9.7-23.2) 16.0 (10.5-24.2) 20.3 (13.6-30.2) 15.9 (11.6-21.7) 15.7 (11.5–21.5) 40.8 (26.5–62.7)

Note. OR (95 % CI). Adolescents in the same time period living with both parents, with at least one parent with higher than basic education and both parents employed used as a reference category

Discussion

In this study, we found that delinquency was associated with socioeconomic adversities amongst Finnish adolescents. Delinquency was more common among boys and girls with parental basic education only than amongst adolescents with higher parental education. Delinquency was also positively associated with not living with both parents and parental unemployment in the past year. The more socioeconomic adversities accumulated, the more likely was delinquency. Most importantly, although changes in the prevalence of delinquency were modest in the overall population, delinquency increased significantly amongst adolescents with most socioeconomic adversities.

The bivariate associations between socioeconomic adversities and delinquency were in agreement with those reported in earlier research (20, 25, 26, 39-43). Low parental education, parental unemployment and a non-traditional family structure are all associated with economic hardship in the family, which is a risk factor of delinquency (44-46). Also the prevalence of substance use and mental health problems, which are associated with delinquency, is higher amongst low-SES adolescents (47-49). Parental monitoring is a central protective factor against delinquency, and lower levels of parental monitoring in low-SES families may partly explain why these adolescents engage more in delinquent behavior (50, 51). Adolescents with socioeconomic adversities are also less likely to be committed to school and academic performance and more likely to get involved in peer groups that engage in delinquent behavior (52, 53).

Our most important finding was that differences in delinquency according to SES increased significantly amongst Finnish adolescents between 2000 and 2015. The finding is novel as changes in delinquency according to SES have not been studied previously. However, increased socioeconomic disparities have been observed in many other areas of adolescent health and well-being, such as smoking and bullying at school (27, 28, 30, 54-56). Why differences in delinquency have increased amongst adolescents in past decades is not known. According to Willis (57), some adolescents from low-SES background may adopt low SES as a part of their identities. Therefore, low-SES adolescents may perceive certain behaviors that are more common amongst people from lower socioeconomic backgrounds, such as smoking and delinquency, as a means of reinforcing their identities. It is possible that the identity processes of adolescents from different socioeconomic backgrounds are diverging in a way which has led to increased socioeconomic disparities in delinquency. Also societal changes, such as changes in income distribution, increased long-term unemployment and school inequaliszation, may have contributed to low-SES adolescents being worse off than earlier (58, 59).

Methodological considerations

This study has some limitations. First, self-report data are susceptible to recall bias. Adolescents may perceive parental education difficult to recall, which may explain why the proportion of missing responses is a little higher on that question than on other questions. However, the proportions of missing responses on all questions studied were very small and therefore hardly affected the results. Second, mischievous responding must be considered in self-report studies. Mischievous responders are defined as ‘young people who provide extreme, and potentially untruthful, responses to multiple questions’ (60). The extent of mischievous responding was not assessed in this study. However, there is no reason to assume that the prevalence of mischievous responding would have changed drastically over years and therefore affected the results.

Despite the limitations, this study has several strengths. It is based on an exceptional nationwide time series study with a long time span and a large sample size consisting of Finnish 8th and 9th graders (n = 761,278) and a high participation rate (43-82 %). The sampling and timing of the study were held constant over the study years. Self-reported delinquency uncovers considerably more incidents than official crime statistics, and anonymity is likely to reduce the biasing effect of social desirability in the responses (38). The questionnaire included several different measures of family SES that were held constant across years, which enabled us to study the association of delinquency with several proxy measures and also a composite measure of SES.

Clinical significance

Socioeconomic adversities are a central risk factor of delinquency amongst adolescents, and it seems that in the twenty-first century delinquency has become even more common amongst adolescents with low SES. Therefore, socioeconomic adversities should be considered in the prevention of delinquency as well as delinquency interventions.

Footnotes

Conflicts of interest

The authors declare no conflicts of interest.

References

  • 1.Remschmidt H, Walter R. What becomes of delinquent children?: results of the Marburg child delinquency study. Dtsch Arztebl Int 2010;107(27):477–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Murray J, Farrington DP. Risk factors for conduct disorder and delinquency: key findings from longitudinal studies. Can J Psychiatry 2010;55(10):633–42. [DOI] [PubMed] [Google Scholar]
  • 3.Young S, Greer B, Church R. Juvenile delinquency, welfare, justice and therapeutic interventions: a global perspective. BJPsych Bull 2017;41(1):21–9.28184313 [Google Scholar]
  • 4.Coker KL, Smith PH, Westphal A, Zonana H V., McKee SA. Crime and psychiatric disorders among youth in the US population: an analysis of the national comorbidity survey–adolescent supplement. J Am Acad Child Adolesc Psychiatry 2014;53(8):888–98. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Bjorkenstam E, Bjorkenstam C, Vinnerljung B, Hallqvist J, Ljung R. Juvenile delinquency, social background and suicide – a Swedish national cohort study of 992 881 young adults. Int J Epidemiol. 2011;40(6):1585–92. [DOI] [PubMed] [Google Scholar]
  • 6.Australian Bureau of Statistics 2018. [cited 2018 Nov 22]. Available from: http://www.abs.gov.au/ausstats/abs@.nsf/mf/4519.0
  • 7.Youth Justice Statistics 2014/15 2016. [cited 2018 Nov 22]. Available from: https://www.gov.uk/government/collections/youth-justice-statistics
  • 8.Elonheimo H. Evidence for the crime drop: survey findings from two Finnish cities between 1992 and 2013. J Scand Stud Criminol Crime Prev 2014;15(2):209–17. [Google Scholar]
  • 9.Svensson R, Ring J. Trends in Self‐Reported youth crime and victimization in Sweden, 1995-2005. J Scand Stud Criminol Crime Prev 2007;8(2):185–209. [Google Scholar]
  • 10.Moffitt TE. The New Look of behavioral genetics in developmental psychopathology: gene-environment interplay in antisocial behaviors. Psychol Bull 2005;131(4):533–54. [DOI] [PubMed] [Google Scholar]
  • 11.Koolhof R, Loeber R, Wei EH, Pardini D, D’escury AC. Inhibition deficits of serious delinquent boys of low intelligence. Crim Behav Ment Heal 2007;17(5):274–92. [DOI] [PubMed] [Google Scholar]
  • 12.Sailas ES, Feodoroff B, Virkkunen M, Wahlbeck K. Mental disorders in prison populations aged 15-21: national register study of two cohorts in Finland. BMJ 2005;330(7504):1364–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Robertson AA, Dill PL, Husain J, Undesser C. Prevalence of mental illness and substance abuse disorders among incarcerated juvenile offenders in Mississippi. Child Psychiatry Hum Dev 2004;35(1):55–74. [DOI] [PubMed] [Google Scholar]
  • 14.Mann EA, Reynolds AJ. Early Intervention and juvenile delinquency prevention: evidence from the Chicago longitudinal study. Soc Work Res 2006;30(3):153–67. [Google Scholar]
  • 15.Mersky JP, Topitzes J, Reynolds AJ. Unsafe at any age: linking childhood and adolescent maltreatment to delinquency and crime. J Res Crime Delinq 2012;49(2):295–318. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Haynie DL, Osgood DW. Reconsidering peers and delinquency: how do peers matter? Soc Forces 2005;84(2):1109–30. [Google Scholar]
  • 17.Krieger N, Williams DR, Moss NE. Measuring social class in us public health research: concepts, methodologies, and guidelines. Annu Rev Public Health 1997;18(1):341–78. [DOI] [PubMed] [Google Scholar]
  • 18.Galobardes B, Shaw M, Lawlor DA, Lynch JW, Davey Smith G. Indicators of socioeconomic position (part 1). J Epidemiol Community Health 2006;60(1):7–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Galobardes B, Shaw M, Lawlor DA, Lynch JW, Davey Smith G. Indicators of socioeconomic position (part 2). J Epidemiol Community Health 2006;60(2):95–101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Sourander A, Elonheimo H, Niemelä S, Nuutila A-M, Helenius H, Sillanmäki L, et al. Childhood predictors of male criminality: a prospective population-based follow-up study from age 8 to late adolescence. J Am Acad Child Adolesc Psychiatry 2006;45(5):578–86. [DOI] [PubMed] [Google Scholar]
  • 21.Isir AB, Tokdemir M, Küçüker H, Dulger HE. Role of family factors in adolescent delinquency in an Elazig/Turkey reformatory. J Forensic Sci 2007;52(1):125–7. [DOI] [PubMed] [Google Scholar]
  • 22.Elonheimo H, Sourander A, Niemelä S, Nuutila A-M, Helenius H, Sillanmäki L, et al. Psychosocial correlates of police-registered youth crime. A Finnish population-based study. Nord J Psychiatry 2009;63(4):292–300. [DOI] [PubMed] [Google Scholar]
  • 23.Goodnight JA, D’Onofrio BM, Cherlin AJ, Emery RE, Van Hulle CA, Lahey BB. Effects of Multiple maternal relationship transitions on offspring antisocial behavior in childhood and adolescence: a cousin-comparison analysis. J Abnorm Child Psychol 2013;41(2):185–98. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Elonheimo H, Sourander A, Niemelä S, Helenius H. Generic and crime type specific correlates of youth crime: a Finnish population-based study. Soc Psychiatry Psychiatr Epidemiol 2011;46(9):903–14. [DOI] [PubMed] [Google Scholar]
  • 25.Hay C, Fortson EN, Hollist DR, Altheimer I, Schaible LM. Compounded risk: the implications for delinquency of coming from a poor family that lives in a poor community. J Youth Adolesc 2007;36(5):593–605. [Google Scholar]
  • 26.Paternoster R, Brame R. Multiple routes to delinquency? A test of developmental and general theories of crime. Criminology 1997;35(1):49–84. [Google Scholar]
  • 27.Torikka A, Kaltiala-Heino R, Luukkaala T, Rimpelä A. Trends in alcohol use among adolescents from 2000 to 2011: the role of socioeconomic status and depression. Alcohol Alcohol 2017;52(1):95–103. [DOI] [PubMed] [Google Scholar]
  • 28.Torikka A, Kaltiala-Heino R, Rimpelä A, Marttunen M, Luukkaala T, Rimpelä M. Self-reported depression is increasing among socio-economically disadvantaged adolescents – repeated cross-sectional surveys from Finland from 2000 to 2011. BMC Public Health 2014;14(1):408. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Ahlborg M, Svedberg P, Nyholm M, Morgan A, Nygren JM. Socioeconomic inequalities in health among Swedish adolescents – adding the subjective perspective. BMC Public Health 2017;17(1):838. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Knaappila N, Marttunen M, Fröjd S, Lindberg N, Kaltiala-Heino R. Socioeconomic trends in school bullying among Finnish adolescents from 2000 to 2015. Child Abuse Negl 2018;86:100–8. [DOI] [PubMed] [Google Scholar]
  • 31.Aizer A, Doyle J Jr. Juvenile incarceration, human capital and future crime: evidence from randomly-assigned judges. National Bureau of Economic Research. NBER Working Paper No. 19102, Issued in June 2013. Available from: http://www.nber.org/papers/w19102
  • 32.Welty LJ, Hershfield JA, Abram KM, Han H, Byck GR, Teplin LA1. Trajectories of substance use disorder in youth after detention: a 12-year longitudinal study. J Am Acad Child Adolesc Psychiatry 2017;56(2):140–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Fazel S, Doll H, Långström N. Mental disorders among adolescents in juvenile detention and correctional facilities: a systematic review and metaregression analysis of 25 surveys. J Am Acad Child Adolesc Psychiatry 2008;47(9):1010–9. [DOI] [PubMed] [Google Scholar]
  • 34.Kohm SA. Spatial dimensions of fear in a high-crime community: fear of crime or fear of disorder? Can J Criminol Crim Justice 2009;51(1):1–30. [Google Scholar]
  • 35.Hinkkanen V. Rikollisuuden kustannukset. Rikollisuustilanne 2012. Rikollisuus ja seuraamusjärjestelmä tilastojen valossa. Oikeuspoliittisen tutkimuslaitoksen tutkimuksia [The cost of crime. Crime situation and crime system in the light of statistics. Research by the Institute for Legal Studies, Finland] 2013;264:421–30. [Google Scholar]
  • 36.Junger-Tas J, Terlouw G-J, Klein MW. Delinquent behavior among young people in the western world: first results of the international self-report delinquency study. Kugler; 1994. [Google Scholar]
  • 37.Zhang S, Benson T, Deng X. A test-retest reliability assessment of the international self-report delinquency instrument. J Crim Justice 2000;28(4):283–95. [Google Scholar]
  • 38.Savioja H, Helminen M, Fröjd S, Marttunen M, Kaltiala-Heino R. Delinquency and sexual experiences across adolescence: does depression play a role? Eur J Contracept Reprod Heal Care 2017;22(4):298–304. [DOI] [PubMed] [Google Scholar]
  • 39.Bartlett R, Holditch-Davis D, Belyea M. Clusters of problem behaviors in adolescents. Res Nurs Health 2005;28(3):230–9. [DOI] [PubMed] [Google Scholar]
  • 40.Maughan B, Collishaw S, Meltzer H, Goodman R. Recent trends in UK child and adolescent mental health. Soc Psychiatry Psychiatr Epidemiol 2008;43(4):305–10. [DOI] [PubMed] [Google Scholar]
  • 41.Morgan PL, Li H, Cook M, Farkas G, Hillemeier MM, Lin Y. Which kindergarten children are at greatest risk for attention-deficit/hyperactivity and conduct disorder symptomatology as adolescents? Sch Psychol Q 2016;31(1):58–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Collishaw S, Goodman R, Pickles A, Maughan B. Modelling the contribution of changes in family life to time trends in adolescent conduct problems. Soc Sci Med 2007;65(12):2576–87. [DOI] [PubMed] [Google Scholar]
  • 43.Harris-Mckoy DE. Examining parental control, parent-adolescent relationship, delinquency, and criminal behavior. 2013. [Dissertation]. Available from: http://diginole.lib.fsu.edu/islandora/object/fsu:183746/datastream/PDF/view [Google Scholar]
  • 44.Kim Y, Hagquist C. Trends in adolescent mental health during economic upturns and downturns: a multilevel analysis of Swedish data 1988-2008. J Epidemiol Community Health 2018;72(2):101–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Baum A, Fleming R, Reddy DM. Unemployment stress: loss of control, reactance and learned helplessness. Soc Sci Med 1986;22(5):509–16. [DOI] [PubMed] [Google Scholar]
  • 46.Agnew R, Matthews SK, Bucher J, Welcher AN, Keyes C. Socioeconomic status, economic problems, and delinquency. Youth Soc 2008;40(2):159–81 [Google Scholar]
  • 47.Marmot MG. Understanding social inequalities in health. Perspect Biol Med 2003;46(3x):S9–23. [PubMed] [Google Scholar]
  • 48.Marmot M, Wilkinson RG. Social organization, stress, and health In: Marmot M, Wilkinson RG. Social determinants of health. Oxford University Press; 2005, pp. 6–30. [Google Scholar]
  • 49.Grucza RA, Krueger RF, Agrawal A, Plunk AD, Krauss MJ, Bongu J, et al.. Declines in prevalence of adolescent substance use disorders and delinquent behaviors in the USA: a unitary trend? Psychol Med 2018;48(09):1494–503. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Hartinger-Saunders RM, Rine CM, Wieczorek W, Nochajski T. Family level predictors of victimization and offending among young men: rethinking the role of parents in prevention and interventions models. Child Youth Serv Rev 2012;34(12):2423–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Kaufman TML, Kretschmer T, Huitsing G, Veenstra R. Why does a universal anti-bullying program not help all children? Explaining persistent victimization during an intervention. Prev Sci 2018;19(6):822–32. [DOI] [PubMed] [Google Scholar]
  • 52.Ferguson H, Bovaird S, Mueller M. The impact of poverty on educational outcomes for children. Paediatr Child Health 2007;12(8):701–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Moss HB, Lynch KG, Hardie TL. Affiliation with deviant peers among children of substance dependent fathers from pre-adolescence into adolescence: associations with problem behaviors. Drug Alcohol Depend 2003;71(2):117–25. [DOI] [PubMed] [Google Scholar]
  • 54.Frederick CB, Snellman K, Putnam RD. Increasing socioeconomic disparities in adolescent obesity. Proc Natl Acad Sci U S A 2014;111(4):1338–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Matthiessen J, Stockmarr A, Biltoft-Jensen A, Fagt S, Zhang H, Groth MV. Trends in overweight and obesity in Danish children and adolescents: 2000-2008 – exploring changes according to parental education. Scand J Public Health 2014;42(4):385–92. [DOI] [PubMed] [Google Scholar]
  • 56.Doku D, Koivusilta L, Rainio S, Rimpelä A. Socioeconomic differences in smoking among Finnish adolescents from 1977 to 2007. J Adolesc Health 2010;47(5):479–87. [DOI] [PubMed] [Google Scholar]
  • 57.Hagan J, Willis P. Learning to labor: How working class kids get working class jobs. Contemp Sociol 1996;25(4):451. [Google Scholar]
  • 58.Rotko T, Aho T, Mustonen N, Linnanmäki E. Bridging the Gap? Review into actions to reduce health inequalities in Finland 2007–2010. Terveyden ja hyvinvoinnin laitos (THL); 2011;116 p. Available from: http://www.julkari.fi/handle/10024/80012
  • 59.Karvonen S, Tokola K, Rimpelä A. Well-being and academic achievement: differences between schools from 2002 to 2010 in the Helsinki metropolitan area. J Sch Health 2018;88(11):821–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Robinson-Cimpian JP. Inaccurate estimation of disparities due to mischievous responders. Educ Res 2014;43(4):171–85. [Google Scholar]

Articles from Scandinavian Journal of Child and Adolescent Psychiatry and Psychology are provided here courtesy of Psychiatric Research Unit, Region Zealand Psychiatry, Denmark.

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