Discussion Paper Series

University of Tokyo

Institute of Social Science
Panel Survey
東京大学社会科学研究所 パネル調査プロジェクト
ディスカッションペーパーシリーズ

Bullying Experience in Childhood and Health Outcomesin Adulthood

Yurie MOMOSE
Hiroshi ISHIDA（Uninversity of Tokyo）

October 2022
No.155東京大学社会科学研究所
INSTITUTE OF SOCIAL SCIENCE UNIVERSITY OF TOKYOInstitute of Social Sciences
University of Tokyo
Panel Survey Project Discussion Paper Series No. 155
October 2022

Bullying Experience in Childhood and Health Outcomes in Adulthood*
Yurie Momose(University of Tokyo)
Hiroshi Ishida(University of Tokyo)*This paper was presented at the Section on Asia and Asian America Roundtable of theannual meeting of the American Sociological Association, which was held at the Los
Angeles Convention Center, 6 August 2022. This research was supported by KAKENHI
Grant-in-Aid for Specially Promoted Research (Grant Numbers JP25000001 andJP18H05204) and Scientific Research (S) (Grant Numbers JP18103003 and JP22223005)
from the Japan Society for the Promotion of Science. The research support in conducting
the Japanese Life Course Panel Surveys (JLPS) was obtained from the Institute of Social
Science, University of Tokyo, and The Outsourcing, Inc. Yurie Momose acknowledges the
Research Fellowship for Young Scientists (22J10114) from the Japan Society for the
Promotion of Science. The Research Ethics Review Board at the Institute of Social Science,
University of Tokyo, approved the JLPS study. The permission to use JLPS data is
obtained from the Management Committee of the Japanese Life Course Panel Surveys.

1

Bullying Experience in Childhood and Health Outcomes in Adulthood

Abstract
This study examines whether the experience of being bullied at school has a long-term
impact on three health outcomes in adulthood in Japan: subjective health, mental health,and activity restriction. We employ a random effects model and the Karlson-Holm-Breen(KHB) method in order to decompose the total effect of being bullied at school on healthinequality into direct effect and indirect effect working through intervening factors
including education, marriage, socio-economic status, and social networks. The JapaneseLife Course Panel Surveys 2007-2020 (waves 1 through 14), a nationally representative
panel data set, are used for the analysis, and 2,260 male respondents and 2,608 female
respondents are included in the analysis. The results demonstrate that for both males andfemales the direct effect of being bullied at school was strong and significant. Bullying
experience in childhood had long-term impact on health outcomes in adulthood, regardlessof social background and mediating factors. Intervening factors mediated the association
between bullying experience and health outcomes, but their contributions were modest at
best.

Keywords: Health inequality, Bullying experience at school, the Japanese Life Course
Panel Surveys, the Karlson-Holm-Breen (KHB) method21. Introduction
Bullying experience in schools is recognized as a significant social concern,
affecting about one in three adolescents worldwide (Koyanagi et al. 2019). Japanese people
are believed to be less likely than Americans to commit any kind of deviant behavior(Roberts and LaFree 2004). However, Kobayashi and Farrington (2020) compared Japanand the U.S. in terms of the perpetration of bullying during school years. Their study
supported the hypothesis that Japanese students tended to bully more than American
students because they had more tolerant attitudes toward bullying. Similarly, Yoneyama
and Naito (2003) summarized the situation of bullying in Japan and claimed that bullying
involving the entire class was one of the most common forms of bullying in Japan. These
results confirm that bullying is one of the most serious educational and social issues inJapan.
In recent years, the long-term effects of bullying have been investigated in many
countries around the world, including Japan. Smokowski and Kopasz (2005) summarizedresearch on bullying and concluded that victims of bullying in childhood suffer long-term
effects on adult mental health, including anxiety, depression, substance use, and behavioral
disorders. According to a review by Arseneault (2018), the effects of being bullied may
persist even after the bullying has stopped. They suggested that addressing bullying can not
only reduce mental health symptoms in children, but also prevent mental health problems inadulthood. Their review further argued that bullying should be seen as another form ofchildhood abuse, along with parental physical abuse and neglect. These studies concluded
that further research is needed to better understand the mechanisms underlying the negative
outcomes and persistence of bullying.

32. Long-lasting Mental and Physical Effects of Bullying at School
It is a well-known fact that being bullied can have a variety of negative effects. For
example, being a victim of bullying has an impact on the well-being of children, including
subjective health, anxiety disorders, depression, physical symptoms, sleep disturbances,loneliness, social isolation, low self-esteem, feelings of hopelessness, self-harm, andaggression (Chai et al. 2020；Zhang et al. 2019b).
In recent years, however, there has been growing concern that the effects of beinga bullying victim can have negative consequences not only in childhood but also
throughout life (Arseneault 2018). The experience of bullying can negatively affect social
factors such as educational attainment and socioeconomic status, create difficulties inbuilding social networks due to social isolation, result in dissatisfaction with relationships,
and lead to health inequalities such as mental and physical illness (Carlisle and Rofes 2007;
McDougall and Vaillancont 2015; Wolke and Lereya 2015). In the area of health status,
research has mainly focused on mental health (Gibb et al. 2011; Takizawa et al. 2014), withcomparatively little evidence about the effects on individuals’ physical health (Zhang et al.
2019a; Zhang et al. 2019b). Even though an increasing number of studies reveal longlasting impacts of bullying experience, the effects appear to be mixed and the mechanisms
are not readily apparent (Wolke and Lereya 2015).
The experience of being bullied as a child has received a great deal of attention inrecent years, not only from researchers who primarily study bullying, but also from those
who primarily study health inequality. This increase in attention is related to a surge in
research examining the physical and mental health effects of trauma and negative events
over the past 50 years (Thoits 2010). Traditionally, the focus of research on childhood
trauma and negative events has been on acute or exceptionally high-stress events such as
parental death and abuse. However, research also suggests that the accumulation of stress in4

everyday life, usually studied by sociologists, influences health status (Harris and Schorpp2018). The experiences of stress caused by work, family, bullying, poverty, and social
isolation are commonplace. Priest et al. (2019) found that the combined and cumulative
experiences of bullying victimization and racism exacerbate the risks to mental andphysical health. Wolke and Lereya (2015, p.879) claimed that “being bullied is still often
wrongly considered as a ‘normal rite of passage’” and that childhood bullying has been
ignored as a major public health concern. Due to these suggestive findings, the importanceof examining the link between bullying and health has increased over the years, evenamong health inequality researchers.
In addition, many studies have incorporated gender differences into their analyticalframeworks, given the fact that prior research on bullying has encouraged the inclusion ofgender as a factor in the analysis (Zhao et al. 2021). Cao et al. (2020), having studied theimpact of bullying on mental health, broke down the effects of bullying on suicidal ideation
into direct effects and indirect effects mediated by loneliness, finding that women weremore likely to suffer from psychological maladjustment after being victims of bullying.
Other studies found that women are more likely to experience the detrimental effects offrequent bullying and have a higher incidence of depression (Gomez-Baya et al. 2017;
Lucas-Molina et al. 2018). In contrast, there are findings that indicate that men are more
likely to be victims of bullying than women because they are more likely to be rejected bytheir peers, and that men also have poorer physical health due to bullying (Carbone-Lopez
2010; Veenstra et al. 2010). These studies suggest that neither women nor men have amonopoly on the suffering bullying can induce, nor is it clear that one gender consistently
faces more extreme effects from the bullying experience.
Research on health inequalities has also focused on gender and has accordingly
highlighted gender differences. According to Thoits (2010), who reviewed the findings of5

40 years of stress research, women live longer than men, but suffer from more acuteillnesses, chronic health conditions, and serious functional impairments. Some sources
consulted in the review also state that women and men have the same incidence of mental
health problems, while differing in the types of problems they encounter. Therefore, when
examining the long-lasting health impacts of bullying, it is important to understand thedifferences between men and women and sensitize analyses to their distinctive risks.
In summary, research on the health effects of being a victim of bullying at school
has gained momentum in recent years, and this research has begun to suggest that there are
long-term physical and psychological consequences. However, the mechanisms of the longlasting effects of bullying experience in childhood on health inequality in adulthood require
further investigation. It has been pointed out that bullying affects health in adulthood;
however, it is not clear whether these impacts result from the direct effect of bullying orfrom indirect effects via mediating factors. Furthermore, it is necessary to examine whether
these effects differ between men and women.
This study examines whether the experience of being bullied at school has a longterm impact on three health outcomes in adulthood in Japan: subjective health, activity
restriction, and mental health. We decompose the total effect of being bullied at school on
health inequality into, first, the direct effect of bullying itself, and, second, indirect effects
working through intervening factors such as education, life events, socio-economic
conditions, and social networks. Moreover, we take advantage of panel surveys toincorporate both time invariant and time-varying factors affecting health outcomes. Finally,
we also focus on gender and examine whether these effects differ between men andwomen.

6

3. Methods
3.1 Data
The data set used in this study comes from the Japanese Life Course Panel Surveys(JLPS) 2007-2020 (waves 1 through 14), a nationally representative panel data set,conducted every year since 2007. The JLPS is composed of the youth sample, which
comprised those who were aged 20 to 34 in 2007, and the middle-aged sample which
comprised those who were aged 35 to 40 in 2007. The JLPS added the youth sample in2019 in order to compensate for the aging of original sample respondents. The refresh
youth sample included respondents who were aged 20 to 31 in 2019. After deleting caseswith missing values, 2,260 male respondents and 2,608 female respondents were used foranalyses. For further details regarding the JLPS, see Ishida (2015; 2017) and Ishida, Arita,
and Fujihara (2020).

3.2 Variables
We used three outcome variables: subjective health, mental health score, and noactivity restriction. Subjective health is measured using the following question about selfreported health: “How do you feel about your health condition?” Responses are coded as:
poor (1), not good (2), ordinary (3), good (4), and very good (5). Mental health scores arecomputed by summing the responses to five questions about the respondent’s mental state:“How often in the last month did you feel the following? A Feeling quite nervous, B
Feeling so down in the dumps that nothing could cheer you up, C Feeling calm andpeaceful, D Feeling downhearted and blue, and E Feeling happy.” Responses are coded as
constantly (1), nearly constantly (2), occasionally (3), rarely (4), and not at all (5). For
items C and E, the response categories were reversed so that the higher the value, the betterthe mental state. The variable “no activity restriction” is coded using the question: “How7

often in the last month did you feel that activities like housekeeping and work were limited
because of your health conditions?” Responses with “rarely” and “not at all” are coded as 1,
and 0 otherwise.
The treatment variable is the experience of bullying at school. Among the list of
events which the respondents experienced, those who reported yes to the item, “I wasbullied at school,” are coded 1, and 0 otherwise. A number of social background variables
are included as controls. Father’s and mother’s educations are coded as 1 when theyattended two-year junior college or four-year university and 0 otherwise. A dummy
variable indicating “unknown” is included due to a relatively large number of cases withmissing responses. The number of books at home when the respondent was 15 years old isused as an indicator of household cultural capital. We created two measures to capture
economic well-being when the respondent was growing up. The first is a dummy variableindicating that the respondent was living in a home owned by their parents when he/she
was 15 years old. Second, a question about the standard of living when the respondent was
15 years old is coded as “wealthy” (5), “somewhat wealthy” (4), “average” (3), “somewhat
poor” (2), and “poor” (1). Finally, a variable indicating whether the respondent had any
life-restricting illness or disorder before he/she was 18 years old was created to measurebaseline health condition. These background variables are time-invariant and fixed for theentire period of the panel survey.
We also introduced a number of mediating variables. The respondent’s educational
attainment is coded as 1 when the respondent attended institutions of higher education and0 otherwise. This variable is time-invariant and does not change across waves. The
following mediating variables are time-variant and may change across waves. Being
unmarried is determined by a marital status question asked in every wave. Current living
standard is measured by the response to the question on the self-reported standard of living
8

in each wave: “wealthy” (5), “somewhat wealthy” (4), “average” (3), “somewhat poor” (2),and “poor” (1). Whether the respondent had a friend in every wave is used to determine the“currently has no friends” variable. Four network-related questions are used to determine
the extent of the respondent’s social network ties: “Who do you talk to when you want todiscuss the following matters? A about work or study, B about job referrals, C about
relationships with friends and partners, D about borrowing significant amounts of money
when you are in need because of job loss or illness.” A list of possible people (such as
parents, partners, children, and siblings) the respondent may specify was provided. If the
respondent replied “none,” the variable is coded as 1, and 0 when the respondent chose any
one of the listed people. These four social network variables are labelled as follows: “noone to talk to about work and study,” “no one to talk to about job referral,” “no one to talkto about relationships,” and “no one to talk to about borrowing money.” These questions
were asked every other wave.
Finally, age and aged squared are included as controls. We also control for survey
samples (the youth sample, the middle-aged sample, and the refresh youth sample), and thewaves (wave 1 to wave 14) but do not show these coefficients in the following tables.
Descriptive statistics are shown in Table 1.

[TABLE 1 ABOUT HERE]

3.3 Statistical Model
In order to take advantage of the panel-type data set, we use a random effects
model. This method can include both time-invariant predictors and time-varying predictors
and can be written as follows:9yit = 𝜃! + γzi + βxit + αi + ϵit

where yit is outcome variable, 𝜃! is a set of time dummy variables, zi is a set of timeinvariant predictors, and xit is a set of time-varying predictors. αi is a set of randomvariables with a specified probability distribution and is assumed to be independent of therest of the variables in the equation. Finally, ϵit indicates an error term.
In order to decompose the effect of the treatment (bullying experience) on theoutcome, we use the Karlson-Holm-Breen (KHB) method (Breen et al. 2013, 2021; Karlson
et al. 2012; Kohler et al. 2011 ). A comparison of the total and direct effects of thetreatment on the outcome in nested nonlinear models is affected by both confounding due
to mediating variables and rescaling of the model. In other words, when a mediating
variable is included in a nonlinear equation model, the coefficient of the treatment variable
will change, regardless of whether it is correlated with that mediator, as long as themediator is correlated with the outcome. The KHB method will estimate the effect ofconfounding (indirect portion) net of rescaling and provide a statistical test for indirect
effect.

4. Results
Table 2 shows the results of fitting two models by gender separately for threehealth outcomes. The first model predicts health outcomes by the treatment variable(bullying at school) and confounding variables (social backgrounds). The second model
predicts health outcomes by bullying at school, social background variables, and mediating
variables.

10

[TABLE 2 ABOUT HERE]

We begin with the first health outcome, subjective health, in Table 2 (left-handside panel). Let us focus on the first row, the coefficients for the school bullying variable.
For both males and females, the effect of bullying at school is negative and significant after
controlling for social background. The experience of being bullied during childhood is
associated with worse subjective health in adulthood. After introducing mediating
variables, the effect of bullying at school is reduced slightly for males and females.
However, the effect of bullying experience continues to be substantial and statisticallysignificant. The experience of school bullying affects subjective health regardless ofeducation, marriage, economic well-being, and social network.
We next report the results for the second health outcome, mental health (Table 2,
middle panel). Just like the results for subjective health, for both males and females theeffect of bullying experience at school is negative and significant after social backgroundvariables were controlled. After introducing mediating variables, the effect of bullying
experience is reduced but remains substantial and statistically significant. The experience ofbeing bullied during childhood is associated with a worse mental health state in adulthood,even after social background and mediating experiences of education, marriage, economic
status, and social network are controlled for.
Finally, we show the results for the third health outcome, no activity restriction(right-hand side panel). For both males and females, the school bullying variable exerts
negative and significant effect on no activity restriction after controlling for social
background, and again after controlling for mediating variables. The introduction ofmediating variables reduces the effect of school bullying for males, but hardly changes theeffect for females. These results indicate that the experience of school bullying reduces the11

odds of having no activity restriction in adulthood, regardless of all the confounding andmediating factors we considered. In other words, people who had childhood experience ofbullying are more likely to experience activity restriction due to health conditions.

[TABLE 3 ABOUT HERE]

Table 3 reports the results of the decomposition of the effect of school bullying
using the KHB method1. There are three panels for three health outcomes: subjective
health, mental health, and no activity restriction. The row labelled “Reduced” indicates thetotal effect of bullying at school after social background variables are controlled, “Full”
indicates the direct effect of bullying after mediating factors are introduced, and“Difference” indicates the indirect effect of bullying through mediating factors.
One new finding in Table 3 is the results of the indirect effects. They are all
significant, except for the “no activity restriction” for females. However, the extent of theseindirect effects is modest, and a small portion of the effect of school bullying goes throughmediating factors when indirect effects are significant. The decomposition for the effect on
subjective health (the left-hand side panel) indicates that the extent of indirect effect (theproportion of Difference to Reduced in the table) is 0.249 for males and 0.109 for females.
In other words, about a quarter of the total effect of bullying at school on subjective healthamong men, and about one tenth among women, are explained by mediating factors. As
shown in Table 2, among the mediating variables, the following exert significant impact on
subjective health for both males and females: being unmarried, having no friends, and

1 The Reduced effects are slightly different from the effects reported in Table 2 because
they adjust for re-scaling. The Full effects are the same as those reported in Table 2.
12lower economic well-being. These factors are, in part, responsible for why bullying
experience influences subjective health.
The middle panel of Table 3 shows the decomposition of the effect of school
bullying on mental health. The indirect effect through mediators comprises 15 percent formales and 12 percent for females of the total effect of bullying. A modest but significant
portion of the association between school bullying and mental health is thus explained bymediating factors. Among mediators, marriage, economic well-being, and some social
network variables significantly affect mental health, suggesting that they play an importantrole in mediating the influence of school bullying on mental health.
Finally, the right-hand side panel of Table 3 presents the decomposition of theeffect of school bullying on no activity restriction. The indirect effect comprises 13 percent
for males and virtually none for females. Among men, economic well-being and having nofriends appear to mediate the association between school bullying and no activity
restriction, as these two factors significantly affect no activity restriction as shown in Table
2. Among women, the impact of school bullying is entirely direct without going throughmediating factors.

5. Discussion
While the importance of examining the linkage between school bullying
victimization and health inequalities in adulthood has been recognized over the years, themechanisms underlying the persistent linkage have not been fully understood. This study
examined whether the experience of being bullied at school has long-term impacts on threehealth outcomes in adulthood in Japan: subjective health, mental health, and activity
restriction. In order to unveil the mechanism of persistent impacts of school bullying, weused the random effects model and the Karlson-Holm-Breen (KHB) method. We13decomposed the total effect of being bullied at school on health inequality into direct effectand indirect effect through intervening factors including education, marriage, socioeconomic status, and social networks.
Our analyses revealed that the experience of being bullied during childhood was
associated with worse subjective health, lower mental health status, and activity restrictionin adulthood for both men and women. Our decomposition analysis showed that the
impacts of school bullying were primarily direct: the experience of school bullying
continued to affect all three health outcomes, regardless of education, marriage, economic
well-being, or social network. The intervening factors explained only a small portion of theassociation between school bullying and health inequalities. With regard to genderdifferences, our results suggest virtually no gender differentiation in the extent ofassociation between school bullying and health outcomes and the decomposition pattern
except for one instance where the indirect effect on no activity restriction was not
significant among women. Overall, the persistent effects of bullying into the adulthood andthe role of mediating factors in explaining the underlying mechanisms are very muchsimilar between men and women.
Our findings parallel in many ways those of Wolke and Lereya (2015) and
Sweeting et al. (2020), who reported that the experience of bullying in school had lasting
effects on mental and physical health years later. On the other hand, our study shows thatthe ability of mediating factors to explain the relationship between school bullying andhealth outcomes is modest at best. Previous studies reported a larger role played byintervening factors. Sweeting et al. (2020) found that negative experiences in childhood
such as bullying and abuse led to later negative experiences such as serious accidents,
illness, and divorce, which in turn affected mental and physical health in adulthood.
However, it should be noted that Sweeting et al. (2020) used the cumulative number of14high-level stress events as mediating factors, while our study used the presence and absenceof daily life experiences. As Wolke and Lereya (2015) summarized in their review, thechildren of the victims of school bullying were found to have lower educational attainment,
less earnings, less likelihood of keeping a job, and worse financial management skills.
These studies suggest that it is possible for the experience of bullying victimization to havenegative effects on a wide range of economic and social characteristics which may act as
mediating factors. Research to discover these intervening factors has just begun, and more
research is needed in the future.
Our study found that the experience of being bullied as a child is an important risk
factor for increasing health inequalities. Given the life-long negative health impacts, as
Arseneault (2018) pointed out, while traditional bullying prevention and intervention
programs may improve the lives of young victims currently attending school by reducing
the likelihood of being bullied, they are unlikely to solve the problems of those who werevictimized in the past. There is an imminent need to consider relief systems and policies forpast victims of bullying in schools.

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal
relationships that could have appeared to influence this research.

15

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Table 1. Descriptive Statistics
A ll

M alesObs

MeanStd. Dev.

Min

Subjective Health

20,635

2.307

0.880

Mental Health

20,635

62.55

17.43

No Activity Restriction

20,6350.848

20,635

Respondent's higher education
Currently unmarried

F em ales

Max

Obs

Mean

Std. Dev.

Min

Max

Obs

Mean

Std. Dev.

Min

0

4

9,306

2.290

0.893

0

100

9,306

62.59

17.54

0.359

0

1

9,306

0.877

0.228

0.420

0

1

9,306

20,635

0.521

0.500

0

1

20,635

0.398

0.490

0

1

Currently has no friends

20,635

0.024

0.154

0

Current living standard

20,635

2.027

0.773

No one to talk to about work and study

20,6350.063

No one to talk to about job referral

20,6350.401

No one to talk to about relationships

20,635

No one to talk to about borrowing money

Max

0

4

11,329

2.321

0.869

0

4

0

100

11,329

62.52

17.33

0

100

0.329

0

1

11,329

0.825

0.380

0

1

0.188

0.391

0

1

11,329

0.261

0.439

0

1

9,306

0.532

0.499

0

1

11,329

0.512

0.500

0

1

9,306

0.438

0.496

0

1

11,329

0.366

0.482

0

1

1

9,306

0.037

0.188

0

1

11,329

0.014

0.118

0

1

0

4

9,306

2.026

0.806

0

4

11,329

2.029

0.746

0

4

0.243

0

1

9,306

0.096

0.294

0

1

11,329

0.036

0.187

0

1

0.490

0

1

9,306

0.378

0.485

0

1

11,329

0.421

0.494

0

1

0.113

0.317

0

1

9,306

0.186

0.389

0

1

11,329

0.054

0.225

0

1

20,635

0.151

0.358

0

1

9,306

0.186

0.389

0

1

11,329

0.123

0.328

0

1

No higher education

20,635

0.598

0.490

0

1

9,306

0.586

0.493

0

1

11,329

0.608

0.488

0

1

Higher education

20,635

0.276

0.447

0

1

9,306

0.282

0.450

0

1

11,329

0.271

0.444

0

1

Unknown

20,635

0.126

0.332

0

1

9,306

0.132

0.338

0

1

11,329

0.122

0.327

0

1

No higher education

20,635

0.708

0.455

0

1

9,306

0.681

0.466

0

1

11,329

0.730

0.444

0

1

Higher education

20,635

0.177

0.382

0

1

9,306

0.178

0.382

0

1

11,329

0.177

0.382

0

1

Unknown

20,635

0.115

0.319

0

1

9,306

0.141

0.348

0

1

11,329

0.093

0.290

0

1

Number of books at home when 15 years old

20,63587.90

110.76

0

500

9,306

91.86

117.240500

11,32984.65

105.020500

Homeownership when 15 years old

20,635

0.785

0.411

0

1

9,306

0.770

0.421

0

1

11,329

0.796

0.403

0

1

Living standard when 15 years old

20,635

2.074

0.810

0

4

9,306

2.060

0.811

0

4

11,329

2.086

0.809

0

4

Illness or disorder before 18 years old

20,635

0.037

0.190

0

1

9,306

0.037

0.190

0

1

11,329

0.037

0.190

0

1

Age

20,63536.014

7.331

20

52

9,306

35.864

7.205

20

52

11,32936.137

7.431

20

52

Age squared

20,6351350.75

526.42

400

2704

9,306

1338.15514.84400

2704

11,3291361.10535.55400

2704

Youth sample

20,635

0.636

0.481

0

1

9,306

0.655

0.475

0

1

11,329

0.620

0.486

0

1

Middle-aged

20,635

0.313

0.464

0

1

9,306

0.298

0.457

0

1

11,329

0.325

0.469

0

1

Refresh youth sample

20,635

0.051

0.221

0

1

9,306

0.047

0.212

0

1

11,329

0.055

0.228

0

1

Male dummy

20,635

0.451

0.498

0

1

9,306

1.000

0.000

1

1

11,329

0.000

0.000

0

0

Three Health Outcomes

Treatment variable
Bullying at school
Mediating variables

Social network items

Social background variables
Father's education

Mother's education

Survey samples

21

Table 2. Random Effect Models of Predicting Three Health Outcomes by Gender
Subjective Health

Mental Health

Males
Model 1
Coef.

FemalesModel 2

Std. Err.

Coef.

Std. Err.

Model 1
Coef.

Males
Model 2

Std. Err.

Coef.

Std. Err.

Model 1
Coef.

FemalesModel 2

Std. Err.

Coef.

Std. Err.

Model 1
Coef.

Model 2

Std. Err.

Coef.

Std. Err.

Treatment variable
Bullying at school-0.153 ** 0.039-0.114 ** 0.038-0.173 ** 0.031-0.153 ** 0.029-6.710 ** 0.770-5.609 ** 0.742-4.503 ** 0.630-3.981 ** 0.601

Mediating variables
Respondent's higher education

0.051

0.032

0.085 ** 0.028

0.344

Currently unmarried-0.068 ** 0.025-0.094 ** 0.022-2.536 ** 0.488

0.627-3.563 ** 0.439

0.911

0.567

Currently has no friends-0.160 ** 0.048-0.163 *0.067-4.120 ** 0.938-2.445Current living standard

0.177 ** 0.012

0.134 ** 0.011

2.638 ** 0.239

2.644 ** 0.223

No one to talk to about work and study-0.042-0.113 ** 0.042-1.0460.599-2.547 ** 0.808

No one to talk to about job referral-0.073 ** 0.019-0.014-1.682 ** 0.365-0.961 ** 0.309

No one to talk to about relationships-0.0430.024-0.100 ** 0.036-0.8150.470-3.097 ** 0.692

No one to talk to about borrowing money-0.0040.023-0.0310.024-1.756 ** 0.449-2.278 ** 0.472

1.306

Social network items
0.030

0.016

Social background variables
Father's education (base: no higher education)
Higher education

0.089 *

0.041

0.063

0.040

0.032

0.036

0.002

0.035

2.087 ** 0.805

1.731 *

0.782

0.076

0.747

-0.3000.720

Unknown-0.005

0.071

0.003

0.067

-0.0780.060-0.060

0.057

2.527

1.376

2.835 *

1.315

-0.6201.223-0.203

1.170

Higher education

0.059

0.047

0.044

0.044

0.025

0.040

0.005

0.039

-0.6680.907-0.835

0.870

0.912

0.832

0.630

0.798

Unknown-0.0630.068-0.0330.065-0.0300.066-0.0290.063-1.8061.324-1.3881.268-0.8381.355-0.914

1.293

Number of books at home when 15 years old

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.001

0.003

0.001

0.003

0.003

0.003

0.004

0.003

Homeownership when 15 years old-0.0060.038-0.024

0.036

0.025

0.034

0.017

0.033

-0.0030.731-0.456

0.702

0.781

0.709

0.542

0.676

Living standard when 15 years old

0.112 ** 0.020

0.052 ** 0.019

0.123 ** 0.017

0.080 ** 0.017

1.374 ** 0.388

0.401

0.380

1.710 ** 0.355

0.799 *

0.345

Illness or disorder before 18 years old-0.351 ** 0.077-0.321 ** 0.073-0.373 ** 0.068-0.327 ** 0.065-2.3701.503-1.732

1.440-6.361 ** 1.398-5.178 ** 1.335

Age-0.025 *0.010-0.025 *0.010-0.0040.009-0.014

0.009

0.251

0.196

0.060

0.200

0.580 ** 0.170

0.140

0.179

Age squared

0.000

0.000

0.000

0.000

0.000 ** 0.000

0.000

0.000

-0.0040.003-0.0020.003-0.008 ** 0.002-0.002

0.002

Constant

2.917 ** 0.186

2.767 ** 0.196

2.605 ** 0.164

2.627 ** 0.179

59.539 ** 3.868

49.030 ** 3.226

55.640 ** 3.503

Mother's education (base: no higher education)

56.485 ** 3.663

Number of observations

9,306

11,3299,306

Number of individuals

2,260

2,608

2,260

Wald chi2

368.6

685.7

514.2

**p ＜.01，*p ＜.05.

22

756.3

117.6

11,329
2,608
414.3

158.3

530.8

Table 2. Random Effect Models of Predicting Three Health Outcomes by Gender (continued)
No Activity Restriction
Males
Model 1
Coef.

FemalesModel 2

Std. Err.

Coef.

Std. Err.

Model 1
Coef.

Model 2

Std. Err.

Coef.

Std. Err.

Treatment variable
Bullying at school-0.652 ** 0.127-0.555 ** 0.124-0.476 ** 0.092-0.483 ** 0.093

Mediating variables
Respondent's higher education

0.127

0.110

0.159

Currently unmarried-0.1750.105

0.578 ** 0.088

0.090

Currently has no friends-0.407 *0.198-0.460Current living standard

0.329 ** 0.055

0.176 ** 0.047

No one to talk to about work and study-0.0600.147-0.2670.176

No one to talk to about job referral-0.038

0.091

0.036

0.068

No one to talk to about relationships

0.015

0.117

-0.1520.149

No one to talk to about borrowing money-0.1320.107-0.095

0.101

0.257

Social network items

Social background variables
Father's education (base: no higher education)
Higher education-0.1100.142-0.1570.139-0.325 ** 0.112-0.369 ** 0.114

Unknown-0.3350.239-0.3170.231-0.211

0.187-0.1850.188

Higher education

0.277

0.163

0.237

0.158

0.050

0.127

-0.0140.129

Unknown

0.327

0.232

0.377

0.226

-0.0260.208-0.006

0.208

Number of books at home when 15 years old

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

Homeownership when 15 years old-0.0130.128-0.067

0.124

0.082

0.106

0.066

0.106

Living standard when 15 years old

0.034

0.068

-0.073

0.068

0.097

0.053

0.046

0.055

Illness or disorder before 18 years old-0.802 ** 0.240-0.726 ** 0.232-1.231 ** 0.193-1.227 ** 0.194

Age-0.0270.050-0.0350.051-0.119 ** 0.039-0.0330.041

Age squared

0.000

0.001

0.000

0.001

0.001 ** 0.001

0.000

0.001

Constant

3.491 ** 0.907

3.285 ** 0.943

4.347 ** 0.707

2.124 ** 0.764

Mother's education (base: no higher education)

Number of observations

9,306

Number of individuals

2,260

Wald chi2

51.5

11,329
2,608
110.2

111.1

**p ＜.01，*p ＜.05.

23

175.6

Table 3. Decomposition of the Effect of School Bullying on Three Health Outcomes Using the KHB Method
Subjective Health
Males

Mental HealthFemales

Coef.

Std. Err.

Coef.

Reduced-0.153 **

0.039

Full

-0.114 **0.038

proportion of Full to Reduced

0.743

Difference-0.039 **proportion of Differenc to Reduced

0.255

Std. Err.

Males

No Activity Restriction
Females

Males

Females

Coef.

Std. Err.

Coef.

Std. Err.

Coef.

Std. Err.

Coef.

Std. Err.

-0.173 ** 0.031-6.710 **0.770-4.503 **0.630-0.636 **0.123-0.474 **0.092-0.153 ** 0.029-5.609 **0.742-3.981 **0.601-0.555 **0.124-0.483 **

0.093

0.889

0.836

-0.019 ** 0.004-1.101 **

0.110

0.164

Bullying at school

0.007**p ＜.01，*p ＜.05.

24

0.884
0.134

-0.552 **
0.123

0.873
0.082

-0.081 **
0.127

1.018
0.021

0.009
-0.0180.010

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