Literature review part 1
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journal.pone.0213700.pdf
RESEARCH ARTICLE
Socioeconomic status, stressful life situations
and mental health problems in children and
adolescents: Results of the German BELLA
cohort-study
Franziska ReissID 1☯‡*, Ann-Katrin Meyrose1☯‡, Christiane Otto1, Thomas Lampert2,
Fionna Klasen 1 , Ulrike Ravens-Sieberer
1
1 Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, University Medical
Center Hamburg-Eppendorf, Hamburg, Germany, 2 Department of Epidemiology and Health Monitoring,
Robert Koch-Institute, Berlin, Germany
☯ These authors contributed equally to this work. ‡ These authors shared first authorship on this work.
Abstract
Aim
Children and adolescents with low socioeconomic status (SES) suffer from mental health
problems more often than their peers with high SES. The aim of the current study was to
investigate the direct and interactive association between commonly used indicators of SES
and the exposure to stressful life situations in relation to children’s mental health problems.
Methods
The prospective BELLA cohort study is the mental health module of the representative, pop-
ulation-based German National Health Interview and Examination Survey for children and
adolescents (KiGGS). Sample data include 2,111 participants (aged 7–17 years at baseline)
from the first three measurement points (2003–2006, 2004–2007 and 2005–2008). Hierar-
chical multiple linear regression models were conducted to analyze associations among the
SES indicators household income, parental education and parental unemployment
(assessed at baseline), number of stressful life situations (e.g., parental accident, mental ill-
ness or severe financial crises; 1- and 2-year follow-ups) and parent-reported mental health
problems (Strength and Difficulties Questionnaire; 2-year follow-up).
Results
All indicators of SES separately predicted mental health problems in children and adoles-
cents at the 2-year follow-up. Stressful life situations (between baseline and 2-year follow-
up) and the interaction of parental education and the number of stressful life situations
remained significant in predicting children’s mental health problems after adjustment for
control variables. Thereby, children with higher educated parents showed fewer mental
health problems in a stressful life situation. No moderating effect was found for household
PLOS ONE | https://doi.org/10.1371/journal.pone.0213700 March 13, 2019 1 / 16
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OPEN ACCESS
Citation: Reiss F, Meyrose A-K, Otto C, Lampert T,
Klasen F, Ravens-Sieberer U (2019)
Socioeconomic status, stressful life situations and
mental health problems in children and
adolescents: Results of the German BELLA cohort-
study. PLoS ONE 14(3): e0213700. https://doi.org/
10.1371/journal.pone.0213700
Editor: Kenji Hashimoto, Chiba Daigaku, JAPAN
Received: January 9, 2019
Accepted: February 26, 2019
Published: March 13, 2019
Copyright: © 2019 Reiss et al. This is an open access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the manuscript and its Supporting
Information files.
Funding: This article is part of a dissertation project
and received no specific funding for this work. The
BELLA study has been financially supported by the
German Science Foundation. The funder had no
role in study design, data collection and analysis,
decision to publish, or preparation of the
manuscript.
income and parental employment. Overall, the detected effect sizes were small. Mental
health problems at baseline were the best predictor for mental health problems two years
later.
Conclusions
Children and adolescents with a low SES suffer from multiple stressful life situations and are
exposed to a higher risk of developing mental health problems. The findings suggest that
the reduction of socioeconomic inequalities and interventions for families with low parental
education might help to reduce children’s mental health problems.
Introduction
Socioeconomic inequalities are an important topic in politics, social sciences and public health
research. Families with a low socioeconomic status (SES) are deprived in multiple ways and
suffer from a higher number of stressors related to finances, social relations, employment situ-
ations and health complaints than those with a high SES [1, 2]. These socioeconomic inequali-
ties affect not only parents’ but also children’s lives. For instance, children with low SES often
have worse access to education and social participation than their peers with high SES [3].
Moreover, children with low SES suffer more often from health problems than children with
high SES [4]. Results from a time-series analysis of 34 countries from 2002 to 2010 showed
that inequalities between socioeconomic groups increased in many domains of adolescent
health; thereby, adolescents with a low SES are more affected by psychological and physical
symptoms [5].
Worldwide, it is estimated that 13% to 20% of children and adolescents suffer from dis-
abling mental illness [6, 7]. When symptoms of mental health problems occur early in life this
has been shown to increase the risk of mental health problems in adulthood [8, 9].
Children and adolescents with low SES are two to three times more likely to develop mental
health problems than their peers with high SES [10]. In numerous studies, indicators of low
SES (commonly measured by the household income per capita, parental education and paren-
tal occupation status) were directly associated with increased mental health problems in chil-
dren and adolescents [11–13]. Indicators of childhood SES differentiate in predicting the
onset, persistence, and severity of mental disorders [14]. Household income and parental edu-
cation have a stronger impact on the mental health problems of children and adolescents than
parental unemployment or low occupation status, which refers to a low position in the occupa-
tional hierarchy [10]. Furthermore, parents with a university degree are more likely to have
children with higher positive psychological health than children of parents with no university
degree [15].
Additionally, low SES relates to a higher burden in different areas of everyday life and an
exposure to stressful life situations. Studies concluded that negative life events and other stress-
ors are clearly related to socioeconomic position [16] and lower parental education and lower
household income were associated with higher stress levels irrespective of adolescent’s gender
[17]. In more detail, SES is associated with the frequency of stressful life events and stress
responses [18]. Furthermore, the exposure to negative life events and family stress partly
explained the association between SES and the symptoms of mental health problems in a
Swedish sample of adolescents [19]. This is in line with results of a longitudinal study by Koe-
chlin and colleagues (2018) reporting that both childhood stressful life events and lower
Socioeconomic inequality and mental health problems in children and adolescents in Germany
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Competing interests: The authors have declared
that no competing interests exist.
maternal education level significantly predicted adjustment problems in adolescence [20].
Similar findings were reported for the mediating role of life stressors on the relationship
between SES and mental health status in young adults participating in a longitudinal US study
[21]. Altogether, it can be assumed that low SES is associated with more problems and stressful
life situations of the family, which increases the risk of children’s mental health problems. To
date, studies investigating the combined effects of SES indicators and stressful life situations as
well as their influence on mental health problems in children and adolescents are rare.
The objectives of our study were to investigate the direct and interactive effects of low SES
(i.e., household income, parental education and parental unemployment) and stressful life sit-
uations in relation to mental health problems in children and adolescents aged 7 to 17 years at
baseline. Blockwise multiple linear regression models were used to identify the direct effects of
SES indicators (measured at baseline) and the number of stressful life situations (measured at
1- and 2-year follow-ups) on children’s mental health problems. The interactive effects of SES
indicators and the number of stressful life situations with regard to children’s mental health
problems were further examined. Additional risk factors for children’s mental health problems
(e.g., family structure, initial mental health problems), along with age and gender were
included in the analyses as control variables. The study uses data from a population-based rep-
resentative sample of German children and adolescents from the BELLA cohort-study [22].
We focused on the following four hypotheses: i) all indicators of low SES (i.e., household
income, parental education and parental unemployment) are separately associated with more
mental health problems of children and adolescents at the 2-year follow-up, ii) a higher num-
ber of stressful life situations is associated with more mental health problems of children and
adolescents at the 2-year follow-up, iii) the interaction of SES indicators with stressful life situ-
ations affects children’s and adolescents’ mental health problems (moderation effect), and (iv)
effects remain significant when control variables are added to the model.
Materials and methods
Study design
Analyses are based on the representative and prospective BELLA cohort study, which is the
mental health module of the National Health Interview and Examination Survey for Children
and Adolescents (KiGGS) in Germany [22]. The BELLA cohort study examines a randomly
selected subsample of KiGGS. Potential study participants were chosen in a multistage random
sampling from the official registers of the local residents’ registration offices, including 167
sample points throughout Germany. In the present study, data from the first three measure-
ment points of the BELLA study were used: BELLA baseline assessment (2003–2006), 1-year
follow-up (2004–2007) and 2-year follow-up (2005–2008). Where available, psychometrically
sound and internationally tested measures were used to assess demographic characteristics,
mental health problems and disorders in addition to risk and protective factors (e.g., a stressful
life situation). Data were collected by computer-assisted telephone interviews and subsequent
questionnaires. Parents provided written informed consent on behalf of their 7- to 17-year-old
children. Adolescents aged 14 years or older gave their written informed consent. For all mea-
surement points of the BELLA study, approvals from the ethics committee of the University
Hospital Charité in Berlin and the Federal Commissioner for Data Protection in Germany
were obtained. For further details on design and methods, see Ravens-Sieberer et al. [23].
Participants
In total, a sample of 2,863 children, adolescents (aged 7 to 17 years) and their parents partici-
pated in the baseline assessment of the BELLA study. For the present study, longitudinal data
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collected over a period of two years were used (gathered at baseline, 1- and 2-year follow-ups).
BELLA baseline participants were included in the present study if they i) participated in the
2-year follow-up (excluded: n = 673), ii) had valid data on mental health problems at the 2-year follow-up (excluded: n = 56 due to missing data in the Strengths and Difficulties Ques- tionnaire), iii) meet age criteria (9 to 19 years) at the 2-year follow-up (excluded: n = 16 were younger than 9 years or older than 19 years), and iv) lived together with at least one biological
parent or adoptive parent (excluded: n = 2 living with grandparents/other relatives, n = 3 living in a children home, n = 2 living on their own). Consequently, data from 2,111 children and adolescents could be analyzed. For a flow chart for selection of study participants based on
inclusion criteria, see Fig 1.
Measurements
Socioeconomic status. Parents provided information on the most commonly used indica- tors of SES: equivalent household net income (short: household income), parental education and parental occupation. The equivalent household net income was calculated by a family’s approximate monthly net equivalent income adjusted for household size and age-specific
needs of household members (Organization for Economic Cooperation and Development,
OECD-modified equivalence scale: head of household = 1, additional adult household mem-
bers = 0.5, children = 0.3) [24]. Parental education was measured by the mean of maternal and
Fig 1. Flow chart for selection of study participants based on the inclusion criteria.
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paternal years of education completed. Parents’ years of education were estimated by using
categories of German school-leaving certificates (e.g., 13 years for German Abitur as the gen- eral qualification for university entrance; 10 years for German Mittlere Reife, roughly compara- ble to American high school diploma; zero years for people still enrolled in school). In
addition, certificates of vocational qualifications were taken into account (e.g., 5 years for a
university degree; 3 years for a completed vocational training; 1.5 years for a completed basic
training, for example to become a parts processor). Thus, the highest educational degree (i.e.,
18 years for a university degree) comprises the regular number of school years completed (i.e.,
13 years) plus the average years of university education (i.e., 5 years) to achieve this educational
attainment in Germany. The current parental occupational status referred to the employment status as whether at least one parent was unemployed.
Stressful life situation. A stressful life situation is defined by the level of stress caused by the occurrence of a certain life situation. In this study, the term “life situation” is preferred
because the impact of a stressful life situation does not describe an event at a particular point
in time but rather is seen as a process. At both measurement points (1- and 2-year follow-ups),
parents were asked by means of a list of items if the following situations occurred over the past
12 months: 1) own serious illness or accident, 2) own mental illness, 3) divorce or separation from a partner, 4) severe financial crisis, 5) loss of employment (respondent or partner), 6) child problems in school and 7) trouble with the law or legal proceedings. Items were offered with response options no (0) and yes (1). If the occurrence of a certain life situation was affirmed, parents were subsequently asked to rate their stress level caused by this situation on a 4-point
scale (not stressful to very stressful). For the present analyses, responses to subsequent questions were dichotomized into not or little stressful (0) and quite or very stressful (1) and summed up to an overall score (ranging from 0 to 7) with higher scores indicating more stressful life situa-
tions. If certain life situations did not occur, it was included in the sum score as not stressful (because not experienced) (0). Finally, a sum score was calculated by gathering the overall scores for both measurement points and covering the additive number of stressful life situa-
tions over the investigated two years (ranging from 0 to 14 with higher scores indicating a
higher number of stressful life situations in the family).
Mental health problems. Mental health problems in children and adolescents were assessed by the parent-reported Strengths and Difficulties Questionnaire (SDQ, [25]) at base-
line and 2-year follow-up. The SDQ is a well-established, brief, reliable and valid screening
questionnaire for mental health problems in children and adolescents [26]. For this study, the
Total Difficulties Score was used to cover the four subscales of mental health problems (i.e.,
emotional symptoms, conduct problems, hyperactivity/inattention, and peer relationship
problems) with 20 items and a range from 0 to 40. Higher scores indicated more severe mental
health problems in children and adolescents. The items of the SDQ refer to the last 6 months
and were answered on a three-point scale (not true, somewhat true, certainly true). In the cur- rent study, internal consistencies were Cronbach’s α = 0.71 and α = 0.72 for the baseline and 2-year follow-up, respectively.
Control variables (gender, age, family structure, and children’s mental health problems
at baseline). Age (in years), gender (0 = female, 1 = male) and mental health problems of children and adolescents as well as family structure were assessed at baseline as control vari-
ables. Children’s mental health problems were measured by the parent-reported Strengths and Difficulties Questionnaire [SDQ, 25]; for more detailed information, see paragraph above.
Family structure was operationalized by children’s usual place of residence and dichotomized into living with both biological parents versus not living with both biological parents. The latter category included all children living in single-parent families (mother or father only), in step-
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parent families (mother or father with new partner) or living with adoptive parents. All control
variables were included in the multiple linear regression analyses.
Statistical analysis
Descriptive statistical analyses comprised the calculation of frequencies or means and standard
deviations for all analyzed variables. Furthermore, a correlation matrix served to investigate
bivariate associations between indicators of SES, number of stressful life situations, and mental
health problems (baseline and 2-year follow-up). According to Cohen [27], we interpreted a
correlation of r = .1 as small, r = .3 as medium and r = .5 as large. Multiple linear regression models were calculated using a hierarchical (blockwise) approach to test each of the four
hypotheses with one model. Thus, children’s mental health problems (2-year follow-up) were
predicted by:
Model 1: household income, parental education, parental unemployment (all assessed at
baseline)—testing hypothesis (i),
Model 2: Model 1 plus number of stressful life situations (between baseline and 2-year fol-
low-up)—testing hypothesis (ii),
Model 3: Model 2 plus interaction terms to test moderation effects (household income x
number of stressful life situations, parental education x number of stressful life situations,
parental unemployment x number of stressful life situations)—testing hypothesis (iii), and
Model 4: Model 3 plus control variables (gender, age, gender x age, family structure, mental
health problems; all assessed at baseline)—testing hypothesis (iv).
For the regression analyses, the metric predictors household income and parental education
as well as the control variable age were centered using the grand mean of the sample. Effect
sizes, p-values and corresponding 95% confidence intervals (CI) are reported. The overall fit of the models was evaluated by adjusted R2 statistics [28], and the significance of changes in model fit were determined by R2-Change and F-test [29]. To interpret the regression coeffi- cients of the regression models (β), we used guidelines by Cohen [27]: β = .1 indicated a small, β = .3 a medium and β = .5 a large effect. Prior to model calculations, we replaced missing data of predictors and control variables using the Expectation-Maximization (EM) algorithm to
include all cases (N = 2111). Missing values were below 2% for all predictors. In addition, a sensitivity analysis was computed to test the robustness of the results according to the missing
imputation (results with vs. without imputation). All analyses were computed using IBM SPSS Version 22. The significance level was deter-
mined as p < .05 for all analyses.
Results
Sample characteristics
In total, longitudinal data of N = 2,111 children and adolescents (48.7% female) were analyzed. At baseline, the participants were 7 to 17 years old (M = 11.96, SD = 3.09). Most children lived with both biological parents (78.4%), 11% of the children and adolescents lived with their
mothers, 0.7% with their fathers or with their mother/father and a new partner (8.3% and
0.4%, respectively), and 0.9% with adoptive or foster parents. In most cases, the mother
responded to questionnaires (baseline: 90.1%, 2-year follow-up: 90.7%).
Concerning the families’ SES, the equivalent household net income was 1,200 Euro, slightly
below the average in Germany [30]. Parents had a mean education of 12.99 years of school and
training (SD = 2.39), which corresponds to the average duration of school attainment in Ger- many (i.e., 12.65 years as determined in 2000 [31]). The years of education ranged from 1.5 to
18 years with 96.3% of parents having 10 to 18 years of education. In 12.1% of the families, at
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least one parent was unemployed; this finding is comparable to the unemployment rate in Ger-
many (11.7% in 2005), which was published by the Federal Labour Office [32]. Further charac-
teristics of the analyzed sample are presented in Table 1.
In total, n = 897 (42.5%) of parents reported at least one stressful life situation between the baseline and 2-year follow-up. Within the measurement period of two years, the number of
stressful life situations in the families ranged between zero and ten (M = 0.89, SD = 1.43). Most frequently, parents mentioned the following stressful life situations: severe financial crisis (n = 452, 10.7% of families), child problems in school (n = 442, 10.5%), and serious illness or accident of a parent (n = 330, 7.8%), for all frequencies see Table 2. Several stressful life situa- tions were reported at both measurement points: for instance, a severe financial crisis (n = 121, 5.7%), child problems in school (n = 88, 0.2%) or parental serious illness or accident (n = 59, 2.8%). These life situations repeatedly occurred or seem to be long-lasting stressors for family
life.
Bivariate analyses
The results of the bivariate analyses of household income, parental education, parental unem-
ployment, number of stressful life situations and children’s mental health problems at baseline
and 2-year follow-up are presented in Table 3. Bivariate correlation analyses revealed that a
lower household income, lower parental education, and parental unemployment were associ-
ated with higher rates of mental health problems in children and adolescents at baseline and at
the 2-year follow-up (Table 3). For household income and parental unemployment, effect sizes
were significant but small, and for parental education, effect sizes were small to medium.
Table 1. Descriptive characteristics of the study population.
Children and adolescents
(N = 2,111) n Valid % M (SD)
Gender 2,111
Male 1,083 51.3 Female 1,028 48.7
Age (years)
Baseline (7–17 years) 2,111 11.96 (3.09) 2-year follow-up (9–19 years) 2.111 14.09 (3.10)
Parental education (in years) 2,091 12.99 (2.39)
Household income (in 100€/month) 2,102 12.00 (5.82) Parental unemployment 2,106
None 1,851 87.7 At least one parent 225 12.1
Number of stressful life situations (counted between baseline and 2-year follow-up) 2,111 0.89 (1.43)
Family structure 2,107
Living with both biological parents 1,655 78.4 Living without both biological parents1 452 21.4
SDQ total score
Baseline 2,105 7.86 (5.11) 2-year follow-up 2,111 7.40 (5.10)
Note. 1 , i.e., living in single-parent families, in step-parent families or with adoptive parents
SDQ = Strengths and Difficulties Questionnaire [Goodman, 1997].
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Moreover, all three indicators of SES were significantly associated with the number of stressful
life situations. In detail, families with lower household income (r = -.153; p�.01), lower paren- tal education (r = -.116; p�.01), and parental unemployment (r = .163; p�.01) reported more stressful life situations than families with high SES. Furthermore, more reported stressful life
situations were significantly associated with higher rates of mental health problems in children
and adolescents at the 2-year follow-up (r = .318; p�.01). The mental health problems of chil- dren and adolescents measured at baseline were strongly related to mental health problems at
the 2-year follow-up (r = .676, p�.01) (see Table 3).
Multiple linear regression
The results of the hierarchical multiple linear regression are presented in Table 4. Findings by
means of Model 1 (adjusted R2 = .04) indicated that higher household income, higher parental education and parental employment are significantly associated with lower mental health
problems in children and adolescents at the 2-year follow-up; the corresponding effect sizes
were small according to Cohen [27] and slightly stronger for parental education (β = -.13; p < .001) than for household income (β = -.07; p = .004) and parental unemployment (β = 0.07; p = .003).
Findings by means of Model 2 (adjusted R2 = .12) indicated that the number of stressful life situations contributed significantly to children’s mental health problems at the 2-year follow-
up. More stressful life situations indicated higher rates of children’s mental health problems
(medium effect; β = 0.29; p�.001). In this model, parental education was still associated with children’s mental health problems, whereas household income and parental unemployment
had no significant effects on children’s mental health problems at the 2-year follow-up.
In Model 3 (adjusted R2 = .13), interaction terms of the independent variables were added to the previous predictors to investigate moderation effects. For the interaction of parental
education and the number of stressful life situations, a significant (but small) effect on chil-
dren’s mental health problems was found at the 2-year follow-up (β = -0.08; p = .003). Thus, children of parents with higher education living in a stressful life situation showed fewer men-
tal health problems than children of parents with lower education living in a stressful life situa-
tion. Moreover, parental employment status also moderated the association between the
number of stressful life situations and children’s mental health problems significantly (β =
Table 2. Stressful life situations at all measurement points.
Children and adolescents (N = 2.111)
n (valid %) Stressful life situations
1 T0-T1 T1-T2 Total
2
Parental serious illness or accident 145 (6.9) 185 (8.8) 330 (7.8)
Parental mental illness 100 (4.7) 95 (4.5) 195 (4.6)
Divorce or separation from partner 50 (2.4) 61 (2.9) 111 (2.6)
Severe financial crisis 217 (10.3) 235 (11.1) 452 (10.7)
Loss of employment (respondent or partner) 132 (6.3) 116 (5.5) 248 (5.9)
Child problems in school 209 (9.9) 233 (11.0) 442 (10.5)
Trouble with the law or legal proceedings 57 (2.7) 51 (2.4) 108 (2.6)
Note. 1 multiple answers possible
T0 = Baseline, T1 = 1-year follow-up, T2 = 2-year follow-up 2 total of stressful life situations between Baseline and 2-year follow-up.
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-0.06, p = .049). Thus, parental unemployment increases the risk for mental health problems in children and adolescents in general (main effect) and especially when less stressful life situa-
tions were reported (interaction effect). In families with a high number of stressful life situa-
tions, parental employment status has no additional negative effect on children’s and
adolescents’ mental health.
Finally, Model 4 (adjusted R2 = .50) included the control variables age, gender, family struc- ture and children’s mental health problems at baseline (in addition to previous predictors and
interaction terms). In this model, none of the single indicators of SES remained statistically
significant; however, the number of stressful life situations continued to be a significant pre-
dictor of children’s mental health problems at the 2-year follow-up. Overall, the results of the
moderator analyses (including the control variables) revealed that children are at higher risk of
showing mental health problems if their parents have lower education and report a higher
number of stressful life situations than their peers with a high number of stressful life situations
but higher-educated parents. Therefore, the number of stressful life situations can be attenu-
ated by a higher level of parental education. Our findings revealed the importance of parental
education, but neither household income nor parental unemployment had significant effects
on mental health in children and adolescents at the 2-year follow-up in the final model (Model
4).
The inclusion of control variables (i.e., age, gender, family structure and children’s mental
health problems at baseline) in Model 4 indicated that children’s mental health problems at
baseline were the strongest predictor for their mental health problems at the 2-year follow-up
(β = 0.61; p�.001). Moreover, the age of the participants significantly predicted children’s mental health problems, with younger children showing more noticeable problems than older
children. Furthermore, a significant interaction of age and gender was observed: boys had a
stronger decrease in mental health problems over time than girls. Living without both biologi-
cal parents was associated with higher mental health problems at the 2-year follow-up, but this
effect did not reach significance (p = .053). Overall, 50% of the variance in children’s mental health problems at the 2-year follow up could be explained in the final model.
Table 3. Pairwise correlation coefficients of indicators of SES, number of stressful life situations, and mental health problems.
Parental
education
(in years, T0,
centred)
Unemployment of father
and/or mother
Number of stressful life situations
(counted, between T0 and T2)
SDQ, total
score
(T0, parent
report)
SDQ, total
score
(T2, parent
report)
Household income (in 100€, T0, centred)
r .489�� -.286�� -.153�� -.169�� -.155��
n 2,085 2,098 2,102 2,097 2,102 Parental education (in years, T0,
centred)
r -.147�� -.116�� -.197�� -.176��
n 2,089 2,091 2,087 2,091 Parental unemployment (father and/or
mother)
r .163�� .126�� .106��
n 2,106 2,102 2,106 Number of stressful life situations
(counted, between T0 and T2)
r .249�� .318��
n 2,105 2,111 SDQ, total score (T0, parent report) r .676��
n 2,105
Note. T0 = Baseline, T2 = 2-year follow-up, SDQ = Strengths and Difficulties Questionnaire [Goodman, 1997], significant effects in bold. � p �.05
�� p � .01.
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To test the robustness of the presented results, we compared the models with and without
missing data imputation (statistics not presented). This sensitivity analysis confirmed our
results, indicating similar coefficients, significances and proportions of explained variance.
Discussion
The present study was the first to investigate the direct and interactive association between sin-
gle indicators of SES and stressful life situations in relation to mental health problems in chil-
dren and adolescents using data from a large population-based sample from Germany. All
indicators of low SES as well as a high number of stressful life situations were associated with
more mental health problems in children and adolescents. As a main finding of the study, only
number of stressful life situations and the interaction between parental education and number
Table 4. Relationship between indicators of SES, number of stressful life situations and its interaction on mental health problems in children and adolescents two
years later.
Model 1 Model 2 Model 3 Model 4
B β p 95% CI of B
B β p 95% CI of B
B β p 95% CI of B
B β p 95% CI of B
Intercept 7.27 <
.001
7.04;7.50 6.41 <
.001
6.14;6.64 6.38 <
.001
6.13;6.61 1.90 <
.001
1.58;2.23
Household income (in 100€, T0, centered)
-0.06 -.07 .004 -0.11;-
0.02
-0.04 -.05 .054 -0.08;-
0.00
-0.04 -.05 .093 -0.09;0.01 0.00 .00 .910 -0.03;0.04
Parental education (in years, T0,
centered)
-0.28 -.13 <
.001
-0.39;-
0.18
-0.25 -.12 <
.001
-0.34;-
0.14
-0.16 -.08 .005 -0.28;-
0.04
-0.00 -.00 .973 -0.09;0.09
Parental unemployment (father and/
or mother)
1.02 .07 .003 0.34;1.70 0.43 .03 .199 -0.34;0.99 0.91 .06 .033 0.07;1.74 0.19 .01 .550 -0.44;0.83
Number of stressful life situations
(counted, between T0 and T2)
1.04 .29 <
.001
0.91;1.20 1.04 .29 <
.001
0.88;1.21 0.54 .15 <
.001
0.41;0.67
Household income × number of stressful life situations
-0.01 -.01 .746 -0.04;0.03 -0.01 -.02 .371 -0.04;0.01
Parental education × number of stressful life situations
-0.09 -.08 .003 -0.16;0.03 -0.09 -.07 <
.001
-0.13;-
0.04
Parental unemployment × number of stressful life situations
-0.39 -.06 .049 -0.77;-
0.00
-0.24 -.04 .110 -0.53;0.05
Gender of child (male) 0.16 .02 .326 -0.16;0.47
Age of child (in years, T0, centered) -0.11 -.07 .002 -0.18;-
0.04
Gender × age of child (T0) -0.15 -.07 .003 -0.25;- 0.05
Family structure: without both
biological parents (T0)
0.39 .03 .053 -0.01;0.79
SDQ, total score (T0, parent report) 0.61 .61 <
.001
0.58;0.64
Model fit indices
Adjusted R2 .04 .12 .13 .50 ΔF(df1,df2), p-value ΔF(3, 2107) = 30.76, p < .001 ΔF(1, 2106) = 197.66, p < .001 ΔF(3, 2103) = 4.19, p = .006 ΔF(5, 2098) = 309.81, p < .001
Note. Model 1: effects of household income, parental education, parental unemployment (all assessed at baseline) on mental health problems in children and adolescents two years later–testing hypothesis 1; Model 2: Model 1 plus the number of stressful life situations (between baseline and 2-year follow-up)–testing hypothesis 2; Model 3:
Model 2 plus interaction terms to test moderation effects (household income x number of stressful life situations, parental education x number of stressful life situations,
parental unemployment x number of stressful life situations)–testing hypothesis 3; Model 4: Model 3 plus control variables (gender, age, gender x age, family structure,
mental health problems; all assessed at baseline)–testing hypothesis 4.
T0 = Baseline assessment, T2 = 2-year follow-up, SDQ = Strengths and Difficulties Questionnaire [Goodman, 1997], significant effects in bold.
https://doi.org/10.1371/journal.pone.0213700.t004
Socioeconomic inequality and mental health problems in children and adolescents in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0213700 March 13, 2019 10 / 16
of stressful life situations remained significant in predicting children’s mental health problems
at the 2-year follow-up after adjustment for fundamental variables. Nonetheless, existing chil-
dren’s mental health problems at baseline was the strongest predictor of mental health prob-
lems at the 2-year follow-up.
In more detail, the study revealed that each indicator of SES separately contributed to chil-
dren’s mental health problems at the 2-year follow-up; however, the detected effects were
small for household income and parental unemployment, and small to medium for parental
education. Thus, parental education was the strongest predictor, whereby children from fami-
lies with higher-educated parents showed a lower risk of developing mental health problems
than their peers with lower-educated parents. The importance of parental education within
the indicators of SES was also determined by other studies [33]. McLaughlin et al. [14]
reported in a US nationally representative sample of 5,692 adults that low parental education,
although unrelated to disorder onset, significantly predicted disorder persistence and severity,
whereas financial hardship predicted the onset of disorders at every life-course stage but
showed no relation with disorder persistence or severity. Parental occupation had no signifi-
cant impact on the onset, persistence and severity of mental disorders [14]. Our results are in
line with previous results of the BELLA study investigating trajectories of mental health prob-
lems by maternal education: Children of mothers with low education had significantly more
mental health problems during childhood and adolescence than children of mothers with high
education [34]. Therefore, education not only affects income and occupational success but
also helps people make better decisions about health, marriage, parenting and improves social
interaction [35]. All of these skills are important in addressing the mental health problems of
children and adolescents.
The effects of single SES indicators on children’s mental health problems (Model 1) partly
disappeared when further variables were included (see Models 2 to 4). The results revealed
that SES indicators explain the occurrence of mental health problems in children and adoles-
cents only to some extent and must thus be considered in the context of other influencing cir-
cumstances. Families with low SES are exposed to multiple mechanisms of social segregation
and disadvantage [16]. The accumulation of stressors or negative life situations is linked to
these mechanisms. The great advance of this study was to observe the impact of a stressful life
situation within the period of two years and therefore covered a relatively wide but clearly
defined timespan.
Our results indicated that the number of stressful life situations, such as parental mental ill-
ness or accident, a severe financial crisis, loss of employment, child’s school problems, divorce
or separation or trouble with the law, are more likely in families with low SES than in those
with high SES. Furthermore, our study findings supported the second hypothesis that a higher
number of stressful life situations is associated with more mental health problems in children
and adolescents at the 2-year follow-up (Model 2). A Norwegian study found comparable
results, whereby the accumulation of negative life events and the presence of family stressors
partly explained the relation between mental health symptoms and SES in children and adoles-
cents aged 11 to 13 years [19]. A National Epidemic Survey from the US with more than
30,000 participants aged 18 to 24 years reported similar results, whereby exposure to a number
of stressful life events was examined as an important pathway through which SES and other
demographic variables impact mental health in young adults [21]. Our study contributes find-
ings to this research field, indicating that these associations are already visible in young chil-
dren. Previous findings of the BELLA study also showed that mental health problems were
more likely to occur between the ages of 7 and 12 and after the age of 19 years [23] and high-
lights the importance of including younger children in the examination.
Socioeconomic inequality and mental health problems in children and adolescents in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0213700 March 13, 2019 11 / 16
Moreover, the pathway of stressful life situations through which SES impacts mental health
is also recognizable in intergenerational relations between parents and their children. SES-
associated stressful life situations during childhood and adolescence have long-term effects, as
results from a French longitudinal study suggest that the experienced accumulation of negative
childhood situations not only contributes to children’s current mental health problems, such
as depression or anxiety, but also continues to affect their mental health in adulthood [36].
The findings of a review concluded that differential exposure to stress and negative life events
are one of the mechanisms in which socioeconomic inequalities in health are produced in soci-
ety [16]. Therefore, low SES and the experience of stressful life situations are mutually associ-
ated with each other and can therefore affect each other. Intergenerational mobility, i.e., the
possibility of changing an individual’s social position compared to parental social position is
linked to health inequalities, indicating that social advancement has a positive effect on health,
whereas social decline has a negative effect on health [37].
Finally, our study findings partly supported the third hypothesis because of the interaction
of one SES indicator, i.e., parental education, and the number of stressful life situations, which
affected children’s and adolescents’ mental health problems. Household income and parental
unemployment showed no moderation effects on the association between a stressful life situa-
tion and children’s mental health problems (Model 4). Therefore, the effect of a stressful life
situation on children’s mental health problems depends on the level of parental education:
children of higher-educated parents are less affected by a stressful life situation and for that
reason less likely to develop mental health problems than their peers with lower-educated
parents. Thus, parental education can be interpreted as a major resource to avoid the develop-
ment of children’s mental health problems, even if families suffer from stressful life situations.
Possibly, higher educated parents experience life situations less stressful compared to less edu-
cated parents and/or are better equipped to handle stressful life situations. Grzywacz and col-
leagues (2004) found in a cross-sectional analysis a stronger negative impact of daily stressors
on mental health among less educated adults; even if higher-educated adults reported more
daily stressors, stressors reported by those with less education were more severe [38]. Addi-
tionally, women with higher education described lower perceived stress and greater control
experiences in everyday life [39] and high education was found to be an important sociodemo-
graphic factor of various coping strategies [40]. Individuals with a higher level of education
have more cognitive abilities and a better social position, which also buffers the impact of a
stressful life situation on psychological distress [41]. A high parental education can be consid-
ered as one social determinant that provides the knowledge to deal with stressful life situations.
With regard to the common measurements of SES, we assume that the strong impact of paren-
tal education can be partly explained as SES indicators built on one another. Concerning intra-
generational mobility, educational attainment is an essential aspect of occupational success
and financial resources [42].
Furthermore, our final model (Model 4) indicated that existing mental health problems in
children and adolescents at baseline were the strongest predictor of mental health problems
two years later. The results highlight the importance of persistence and early onset of mental
health problems in childhood. A previous finding of the BELLA study showed that over a
6-year period, 10.2% of all children showed persistent, acute or recurrent mental health prob-
lems [23]. Moreover, mental health problems in childhood often persist until adulthood. Find-
ings from the US National Comorbidity Survey stated that half of all lifetime cases start by the
age of 14 [43]. Overall, our study findings underline the focus on longitudinal analyses because
mental health problems in children are a critical issue in this sensitive phase of development
from childhood to adolescence and further on to young adulthood.
Socioeconomic inequality and mental health problems in children and adolescents in Germany
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Strengths
The BELLA study is one of the most important cohort-studies that examines mental health
problems in a population-based representative sample of children, adolescents and young
adults in Germany. The strengths of the study are the large sample size and its longitudinal
design, which enables the examination of mental health problems over time, including chil-
dren aged seven years or older. Our contribution to research involves the analysis of single
indicators of SES, which allows a deeper consideration of the differences between the com-
monly used indictors of SES. The hierarchical theory-based modeling in linear regression anal-
yses helped to understand the disappearing effect of SES indicators on mental health problems
in children and adolescents. Our results highlight the importance of considering a wider spec-
trum of living circumstances, e.g., health complaints, schooling, or dealing with difficult situa-
tions, in families with a low SES in future research. Finally, examination of the number of
stressful life situations that occurred between different measuring points significantly contrib-
utes to a better understanding of the association between low SES and mental health problems
in children and adolescents. This study takes the temporality of these situations into account
and is therefore not limited to a cross-sectional time point.
Limitations
Despite the strengths of this study, some limitations should be considered. First, indicators of
SES were measured only by parent-reports at baseline. No data were available to consider
changes in SES at the follow-up measurement points. Nonetheless, SES indicators such as
parental education are supposed to be relatively stable in this age group. Second, drop-outs
within the cohort of the BELLA study were more frequent for participants with low SES
(2-year follow-up: OR = 1.06; 95% CI = 1.02–1.10) but independent of parent-reported general
health or mental health of children and adolescents as reported by Ravens-Sieberer et al. [23].
Third, because we included young children from age seven or older in our analyses, mental
health problems in children and adolescents were gathered by parent-reports.
Conclusion
In conclusion, the impact of a stressful life situation on mental health problems in children
and adolescents depends on the SES. Children from families with low SES are at higher risk of
suffering from different stressful life situations. Furthermore, a stressful life situation is associ-
ated with mental health problems in children and adolescents. For this reason, it is important
to focus not only on the indicators of SES, such as household income, parental education or
parental occupation, but also on the broader current life situation with various burdens of
stress in analyses on the mental health of children and adolescents. For future research, it
would be interesting to examine other indicators (besides SES) that affect the association
between a stressful life situation and children’s mental health, e.g., personal and social
resources (e.g., social support or self-efficiency). In terms of opportunities for intervention and
prevention, the aspect of parental education turned out as the most critical issue. Children
with less educated parents obviously need more support in dealing with stressful life situations
(e.g., parental illness or accident or severe financial crises) than their peers in a comparable sit-
uation but with higher-educated parents.
Supporting information
S1 Data. Socioeconomic status, stressful life situations and mental health.
(XLS)
Socioeconomic inequality and mental health problems in children and adolescents in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0213700 March 13, 2019 13 / 16
Acknowledgments
The authors thank all of the children, adolescents, their parents and young adults who partici-
pated in this study for their time and involvement. We are very grateful to all the researchers
and students who worked on this project and made it possible, especially to: Claus Barkmann,
Anne-Catherine Haller and the BELLA study Group. We would like to thank the Robert
Koch-Institute and the Charité Berlin for their ongoing support and cooperation.
Author Contributions
Conceptualization: Franziska Reiss, Ann-Katrin Meyrose, Christiane Otto, Ulrike Ravens-
Sieberer.
Data curation: Franziska Reiss, Ann-Katrin Meyrose, Christiane Otto.
Formal analysis: Ann-Katrin Meyrose, Christiane Otto.
Funding acquisition: Fionna Klasen, Ulrike Ravens-Sieberer.
Investigation: Franziska Reiss, Thomas Lampert, Fionna Klasen.
Methodology: Franziska Reiss, Ann-Katrin Meyrose, Christiane Otto, Ulrike Ravens-Sieberer.
Project administration: Thomas Lampert, Fionna Klasen, Ulrike Ravens-Sieberer.
Resources: Thomas Lampert, Fionna Klasen, Ulrike Ravens-Sieberer.
Software: Ann-Katrin Meyrose, Christiane Otto.
Supervision: Christiane Otto, Thomas Lampert, Fionna Klasen, Ulrike Ravens-Sieberer.
Validation: Franziska Reiss, Ann-Katrin Meyrose, Christiane Otto, Fionna Klasen, Ulrike
Ravens-Sieberer.
Visualization: Franziska Reiss, Ann-Katrin Meyrose.
Writing – original draft: Franziska Reiss, Ann-Katrin Meyrose.
Writing – review & editing: Franziska Reiss, Ann-Katrin Meyrose, Christiane Otto, Thomas
Lampert, Fionna Klasen, Ulrike Ravens-Sieberer.
References 1. Senn TE, Walsh JL, Carey MP. The Mediating Roles of Perceived Stress and Health Behaviors in the
Relation Between Objective, Subjective, and Neighborhood Socioeconomic Status and Perceived
Health. Ann Behav Med. 2014; 48(2): 215–24. https://doi.org/10.1007/s12160-014-9591-1 PMID:
24648016
2. Weyers S, Dragano N, Mobus S, Beck EM, Stang A, Mohlenkamp S, et al. Poor social relations and
adverse health behaviour: stronger associations in low socioeconomic groups? Int J Public Health.
2010; 55(1): 17–23. https://doi.org/10.1007/s00038-009-0070-6 PMID: 19774341
3. Engels D, Thielebein C. Zusammenhang von sozialer Schicht und Teilnahme an Kultur-, Bildungs- und
Freizeitangeboten für Kinder und Jugendliche. [Association between social class and participation in
cultural, education and leisure programs for children and adolescents.]. Köln; 2011.
4. Vukojevic M, Zovko A, Talic I, Tanovic M, Resic B, Vrdoljak I, et al. Parental Socioeconomic Status as a
Predictor of Physical and Mental Health Outcomes in Children—Literature Review. Acta Clin Croat.
2017; 56(4): 742–8. https://doi.org/10.20471/acc.2017.56.04.23 PMID: 29590731
5. Elgar FJ, Pfortner TK, Moor I, De Clercq B, Stevens GW, Currie C. Socioeconomic inequalities in ado-
lescent health 2002–2010: a time-series analysis of 34 countries participating in the Health Behaviour in
School-aged Children study. Lancet. 2015; 385(9982): 2088–95. https://doi.org/10.1016/S0140-6736
(14)61460-4 PMID: 25659283
Socioeconomic inequality and mental health problems in children and adolescents in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0213700 March 13, 2019 14 / 16
6. Polanczyk GV, Salum GA, Sugaya LS, Caye A, Rohde LA. Annual research review: A meta-analysis of
the worldwide prevalence of mental disorders in children and adolescents. J Child Psychol Psychiatry.
2015; 56(3): 345–65. https://doi.org/10.1111/jcpp.12381 PMID: 25649325
7. Belfer ML. Child and adolescent mental disorders: the magnitude of the problem across the globe. J
Child Psychol Psychiatry. 2008; 49(3): 226–36. https://doi.org/10.1111/j.1469-7610.2007.01855.x
PMID: 18221350
8. Sv Stumm, Deary IJ, Kivimäki M, Jokela M, Clark H, Batty GD. Childhood behavior problems and health
at midlife: 35-year follow-up of a Scottish birth cohort. J Child Psychol Psychiatry. 2011; 52(9): 992–
1001. https://doi.org/10.1111/j.1469-7610.2011.02373.x PMID: 21294730
9. Roza SJ, Hofstra MB, van der Ende J, Verhulst FC. Stable prediction of mood and anxiety disorders
based on behavioral and emotional problems in childhood: a 14-year follow-up during childhood, ado-
lescence, and young adulthood. Am J Psychiatry. 2003; 160(12): 2116–21. https://doi.org/10.1176/
appi.ajp.160.12.2116 PMID: 14638580
10. Reiss F. Socioeconomic inequalities and mental health problems in children and adolescents: A sys-
tematic review. Soc Sci Med. 2013; 90: 24–31. https://doi.org/10.1016/j.socscimed.2013.04.026 PMID:
23746605
11. Najman JM, Hayatbakhsh MR, Clavarino A, Bor W, O’Callaghan MJ, Williams GM. Family poverty over
the early life course and recurrent adolescent and young adult anxiety and depression: a longitudinal
study. Am J Public Health. 2010; 100(9): 1719–23. https://doi.org/10.2105/AJPH.2009.180943 PMID:
20634459
12. Amone-P’Olak K, Burger H, Ormel J, Huisman M, Verhulst FC, Oldehinkel AJ. Socioeconomic position
and mental health problems in pre- and early-adolescents: the TRAILS study. Social Psychiatry Psychi-
atric Epidemiology. 2009; 44(3): 231–8. https://doi.org/10.1007/s00127-008-0424-z PMID: 18714424
13. Ravens-Sieberer U, Erhart M, Gosch A, Wille N. Mental health of children and adolescents in 12 Euro-
pean countries-results from the European KIDSCREEN study. Clin Psychol Psychother. 2008; 15(3):
154–63. https://doi.org/10.1002/cpp.574 PMID: 19115436
14. McLaughlin KA, Breslau J, Green JG, Lakoma MD, Sampson NA, Zaslavsky AM, et al. Childhood
socio-economic status and the onset, persistence, and severity of DSM-IV mental disorders in a US
national sample. Soc Sci Med. 2011; 73(7): 1088–96. https://doi.org/10.1016/j.socscimed.2011.06.011
PMID: 21820781
15. Padilla-Moledo C, Ruiz JR, Castro-Pinero J. Parental educational level and psychological positive
health and health complaints in Spanish children and adolescents. Child Care Health Dev. 2016; 42(4):
534–43. https://doi.org/10.1111/cch.12342 PMID: 27097753
16. Lantz PM, House JS, Mero RP, Williams DR. Stress, life events, and socioeconomic disparities in
health: Results from the Americans’ changing lives study. J Health Soc Behav. 2005; 46(3): 274–88.
https://doi.org/10.1177/002214650504600305 PMID: 16259149
17. Glasscock DJ, Andersen JH, Labriola M, Rasmussen K, Hansen CD. Can negative life events and cop-
ing style help explain socioeconomic differences in perceived stress among adolescents? A cross-sec-
tional study based on the West Jutland cohort study. BMC Public Health. 2013; 13: 532. https://doi.org/
10.1186/1471-2458-13-532 PMID: 23724872
18. Baum A, Garofalo JP, Yali AM. Socioeconomic status and chronic stress—Does stress account for
SES effects on health? In: Adler NE, Marmot M, McEwen B, Stewart J, editors. Socioeconomic Status
and Health in Industrial Nations: Social, Psychological, and Biological Pathways. Annals of the New
York Academy of Sciences. 896. New York: New York Acad Sciences; 1999. p. 131–44.
19. Boe T, Serlachius AS, Sivertsen B, Petrie KJ, Hysing M. Cumulative effects of negative life events and
family stress on children’s mental health: the Bergen Child Study. Soc Psychiatry Psychiatr Epidemiol.
2018; 53(1): 1–9. https://doi.org/10.1007/s00127-017-1451-4 PMID: 29090324
20. Koechlin H, Donado C, Berde CB, Kossowsky J. Effects of Childhood Life Events on Adjustment Prob-
lems in Adolescence: A Longitudinal Study. J Dev Behav Pediatr. 2018; 39(8): 629–41. https://doi.org/
10.1097/DBP.0000000000000596 PMID: 29944491
21. Businelle MS, Mills BA, Chartier KG, Kendzor DE, Reingle JM, Shuval K. Do stressful events account
for the link between socioeconomic status and mental health? J Public Health. 2014; 36(2): 205–12.
22. Ravens-Sieberer U, Kurth BM. The mental health module (BELLA study) within the German Health
Interview and Examination Survey of Children and Adolescents (KiGGS): study design and methods.
Eur Child Adolesc Psychiatry. 2008; 17(1): 10–21.
23. Ravens-Sieberer U, Otto C, Kriston L, Rothenberger A, Döpfner M, Herpertz-Dahlmann B, et al. The
longitudinal BELLA study: Design, methods and first results on the course of mental health problems.
Eur Child Adolesc Psychiatry. 2015; 24(6): 651–63. https://doi.org/10.1007/s00787-014-0638-4 PMID:
25428179
Socioeconomic inequality and mental health problems in children and adolescents in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0213700 March 13, 2019 15 / 16
24. Lampert T, Müters S, Stolzenberg H, Kroll L, Group KS. Messung des sozioökonomischen Status in der
KiGGS-Studie–Erste KiGGS-Folgebefragung (KiGGS Welle 1). [Measurement of socioeconomic status
in the KiGGS study. First follow-up (KiGGS Wave 1).]. Bundesgesundheitsblatt—Gesundheits-
forschung—Gesundheitsschutz 2014; 57(7).
25. Goodman R. The Strengths and Difficulties Questionnaire: a research note. J Child Psychol Psychiatry.
1997; 38(5): 581–6. PMID: 9255702
26. Goodman R. Psychometric properties of the strengths and difficulties questionnaire. J Am Acad Child
Adolesc. 2001; 40(11):1337–45.
27. Cohen J. Statistical power analysis for the behavioral sciences 2ed. Hillsdale, NJ: Lawrence Erlbaum
Associates; 1988.
28. Nagelkerke NJD. A note on a general definition of the coefficient of determination. Biometrika. 1991; 78
(3): 691–2.
29. Field A. FiDiscovering statistics using IBM SPSS statistics.: SAGE Publications; 2013.
30. Statistisches Bundesamt [German Federal Statistical Office]. Wirtschaftsrechnungen. Einkommens-
und Verbrauchsstichprobe Einkommensverteilung in Deutschland. [Economic accounts. Distribution of
income and consumption in Germany.]. Wiesbaden: Statistischen Bundesamt; 2006.
31. Baten J, de Jong H. Internationale Vergleiche [International comparisons]. In: Rahlf T, editor. Deutsch-
land in Daten Zeitreihen zur Historischen Statistik [Germany in facts Histrical statistics]. Bonn: Bundes-
zentrale für politische Bildung; 2015. p. 304–19.
32. Bundesagentur für Arbeit [Federal Labour Office]. II.C. Arbeitslosigkeit [Unemployment]. Nürnberg:
Bundesagentur für Arbeit; 2006.
33. Davis E, Sawyer MG, Lo SK, Priest N, Wake M. Socioeconomic risk factors for mental health problems
in 4-5-year-old children: Australian population study. Acad Pediatr. 2010; 10(1): 41–7. https://doi.org/
10.1016/j.acap.2009.08.007 PMID: 20129480
34. Meyrose A-K, Klasen F, Otto C, Gniewosz G, Lampert T, Ravens-Sieberer U. Benefits of maternal edu-
cation for mental health trajectories across childhood and adolescence. Soc Sci Med. 2018; 202: 170–
8. https://doi.org/10.1016/j.socscimed.2018.02.026 PMID: 29554584
35. Oreopoulos P, Salvanes KG. Priceless: The Nonpecuniary Benefits of Schooling. J Econ Perspect.
2011; 25(1): 159–84.
36. Melchior M, Touchette E, Prokofyeva E, Chollet A, Fombonne E, Elidemir G, et al. Negative events in
childhood predict trajectories of internalizing symptoms up to young adulthood: an 18-year longitudinal
study. PloS one. 2014; 9(12): e114526. https://doi.org/10.1371/journal.pone.0114526 PMID: 25485875
37. Gunther S, Moor I, Knochelmann A, Richter M. Intergenerationale Mobilität und gesundheitliche
Ungleichheiten in Ost- undWestdeutschland. Eine Trendanalyse von 1992 bis 2012. [Intergenerational
mobility and health inequalities in East and West Germany: A trend analysis from 1992 to 2012]. Bun-
desgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz. 2018; 61(1):78–88. https://doi.org/
10.1007/s00103-017-2655-1 PMID: 29138900
38. Grzywacz JG, Almeida DM, Neupert SD, Ettner SL. Socioeconomic status and health: a micro-level
analysis of exposure and vulnerability to daily stressors. J Health Soc Behav. 2004; 45(1): 1–16. https://
doi.org/10.1177/002214650404500101 PMID: 15179904
39. Gallo LC, Shivpuri S, Gonzalez P, Fortmann AL, de los Monteros KE, Roesch SC, et al. Socioeconomic
status and stress in Mexican-American women: a multi-method perspective. J Behav Med 2013; 36(4):
379–88. https://doi.org/10.1007/s10865-012-9432-2 PMID: 22644814
40. Holahan CJ, Moos RH. Personal and contextual determinants of coping strategies. J Pers Soc Psychol.
1987; 52(5):946–55. PMID: 3585703
41. Mandemakers JJ, Monden CWS. Does education buffer the impact of disability on psychological dis-
tress? Soc Sci Med (1982). 2010; 71(2):288–97.
42. Pollak R, Allmendinger J, Trappmann M, Ehlert M, Gatermann D, Heisig J, et al. Soziale Mobilität, Ursa-
chen für Auf- und Abstiege. Studie für den 4. Armuts- und Reichtumsbericht der Bundesregierung im
Auftrag des Bundesministeriums für Arbeit und Soziales. Berlin; 2013.
43. Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-of-
onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psy-
chiatry. 2005; 62(6):593–602. https://doi.org/10.1001/archpsyc.62.6.593 PMID: 15939837
Socioeconomic inequality and mental health problems in children and adolescents in Germany
PLOS ONE | https://doi.org/10.1371/journal.pone.0213700 March 13, 2019 16 / 16
