The pervasive effects of timing of parental mental health disorders on adolescent deliberate self-harm risk
The pervasive effects of timing of parental mental health disorders on adolescent deliberate self-harm risk
Nan HuID 0 1 2
Catherine L. Taylor 0 2
Rebecca A. Glauert 0 2
Jianghong Li 0 2
0 Telethon Kids Institute, The University of Western Australia , Nedlands, Western Australia , Australia
1 School of Population and Global Health, The University of Western Australia , Nedlands, Western Australia , Australia , 3 Centre for Child Health Research, The University of Western Australia , Nedlands, Western Australia , Australia , 4 WZB Berlin Social Science Centre , Berlin , Germany
2 Editor: Luca Cerniglia, International Telematic University Uninettuno , ITALY
Children whose parents have mental health disorders are at increased risk for deliberate self-harm (DSH). However, the effect of timing of parental mental health disorders on adolescent DSH risk remains under-researched. The aim of this study was to investigate how parental hospital admissions for mental health disorders and/or DSH in different developmental periods impact on the child's DSH risk in adolescence. A nested case-control sample was compiled from a total population cohort sample drawn from administrative health records in Western Australia. The sample comprised 7,151 adolescents who had a DSHrelated hospital admission (cases), and 143,020 matched controls who hadn't had a DSHrelated hospital admission. The occurrence of parental hospital admissions related to mental health disorders and/or DSH behaviours was then analysed for the cases and controls. The timing of the parental hospital admissions was partitioned into four stages in the child's life course: (1) pre-pregnancy, (2) pregnancy and infancy, (3) childhood, and (4) adolescence. We found that adolescents of a parent with mental health and/or DSH-related hospital admissions in all developmental periods except pregnancy and infancy were significantly more likely than controls to have a DSH-related hospital admission. Compared to parental hospital admissions that occurred during childhood and adolescence, those that occurred before pregnancy conferred a higher risk for adolescent DSH: adjusted odds ratio (aOR) = 1.25 for having only one parent hospitalised and 1.66 for having both parents hospitalised for mental health disorders; aOR = 1.97 for having any parent hospitalised for DSH, all being significant at the level of p < .001. This study shows that timing is important for understanding intergenerational transmission of DSH risk. The pre-pregnancy period is as critical as period after childbirth for effective intervention targeting adult mental health disorders and DSH, highlighting the important role of adult mental health services in preventing DSH risk in future generations.
Data Availability Statement: The datasets
generated and/or analysed during the current study
are not publicly available due to the terms of the
ethics approval granted by the Department of
Health Western Australia Human Research Ethics
Committee and data disclosure policies of the Data
Providers. The datasets may be available from the
Western Australia Data Linkage Branch at
and subject to the
approval from the Department of Health Western
Australia Human Research Ethics Committee and
Funding: This study was supported by the
Australian Research Council Linkage Project grant
(LP100200507). CLT is supported by the
Australian Research Council Centre of Excellence
for Children and Families over the Life Course
(CE140100027). The funders had no role in the
study design, data collection and analysis, decision
to publish, or preparation of the manuscript.
One in five children has a parent with a mental health disorder [
]. Children whose parents
have mental health disorders are themselves at increased risk of developing a mental health
disorder, including intentional self-injurious behaviours, with or without suicidal intent,
known as deliberate self-harm (DSH) [
]. DSH is a major public health issue affecting 17% of
people aged 15?24 years [
]. Risk factors for DSH in adolescents include maternal
pregnancy and birth complications [
], parental mental health disorders [
], and social
]. However, limited research has investigated the impact of the timing of
parental mental health disorders on adolescent DSH risk.
Previous research has shown that the earlier the child?s exposure to parental mental health
disorders, the greater the impact on the child?s psychosocial development [
]. For example,
maternal depression in infancy has a stronger influence on a child?s internalising disorders
than maternal depression in toddlerhood [
]. Furthermore, children exposed to parental
suicidal death in early childhood have an elevated risk of DSH-related hospital admissions,
compared to parental suicidal death experienced in later childhood and adolescence [
Biological parenting may commence well before pregnancy [
]. This is because parental
experiences prior to conception influence the development of the embryo and foetus,
ultimately affecting the lifetime health of the child [
]. People with poorer mental health before
pregnancy are more likely to have a higher number of health and social issues, which may
elevate the risk of DSH behaviours among the adolescent children [
]. Women with mental
health disorders before the conception of their child are more likely to have mental health
distress in the pre and postnatal periods, compared to women who do not have pre-existing
mental health conditions [
]. Perinatal period is a critical window for children?s physiological
and neurological development . Perinatal exposure to environmental stress may cause
epigenetic dysregulation, which may underlie the associations between adverse environmental
exposures early in life and increased risk for children?s psychopathology [
exposed to heightened maternal mental health distress during the perinatal periods have
elevated psychosocial problems during childhood [
]. The mechanisms for maternal mental
health problems during pre and postnatal period and increased psychosocial problems among
children are complex and involve a range of biological and psychosocial risk factors that may
be uniquely experienced early in life by the children, such as perinatal toxic stress, low
attachment and poor parenting skills [
Childhood is a period encompassing the critical development of the central nervous system
in response to environmental exposures [
]. Childhood exposure to parental mental health
disorders may result in increased emotional and behavioural dysregulation, which has been
linked to heightened DSH risk in adolescence [
]. ?Puberty is one of the central dramas of
the human life course? [
], where substantive biological and psychosocial changes occur.
Adolescence is a challenging time not only for adolescents themselves but also for parents,
especially parents with mental health disorders [
]. The adolescent children of parents with
mental health disorders are at especially high risk for DSH [
Building on our previous study which only examined parental lifetime (not developmental
period-specific) mental health disorders and/or DSH [
], we aimed to extend what is known
about parent-child transmission of DSH risk by specifically investigating the effect of the
timing of parental mental health and/or DSH-related hospital admissions on the child?s DSH risk
in adolescence. Understanding the impact of the timing of parental mental health disorders is
important in understanding the intergenerational transmission of mental health disorders,
including DSH, and it can inform effective intervention and prevention strategies. To date, no
research has investigated this issue. In this study, the child?s life course was partitioned into
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four stages: (1) pre-pregnancy, (2) pregnancy and infancy, (3) childhood and (4) adolescence,
based on theoretical and empirical evidence described above.
Materials and methods
As described above, this research advanced our previous study by examining the effect of the
timing of parental mental health disorders and/or DSH-related hospital admissions on
adolescent DSH risk [
]. In this study, we utilised the same administrative linked datasets, the same
nested case-control sample generated from the same sampling strategy, and the same methods
to identify exposures and outcomes.
This study used the linked administrative data routinely collected by multiple government
agencies in Western Australia (WA). The Data Linkage Branch (DLB) in WA managed the
cleaning and extraction of information for linking records from different data collections that
belong to the same person, by using unique identifiers (e.g., hospital unique medical record
number or electoral number), record date, and demographic variables such as name, date of
birth, residential address, and sex. Where the unique identifiers are not available across all data
collections, the demographic variables are compared using a probabilistic matching method to
calculate how likely records belong to the same person. Uncertain links are manually checked
for validity by the DLB. A de-identified linkage key specific to each person is generated and
stored in all data collections. The linkage accuracy is high: the proportion of invalid and
missed links are estimated to be 0.11% [
]. The de-identified individual records across
different data collections were merged using the linkage keys [
Four health related registers were linked for this study: the Hospital Morbidity Data
System (HMDS) including all hospital inpatient admissions; the Mental Health Information
System (MHIS) including mental health outpatients in public hospitals; the Emergency
Department Data Collection (EDDC) including emergency department presentations in all
hospitals under contract with the WA government; and the Death Registrations including all
deaths registered in WA. Covariates were sourced from the Midwives Notification System
(MNS) and the Birth Registrations that include all birth records in WA. All the
administrative data collections date back to 1980 and earlier, except the EDDC which contains records
We established the source population using the Birth Registrations and the MNS, including all
children born alive between 1981 and 2001 in WA identified as non-Aboriginal (244,104
males, 230,756 females). Given that DSH-related hospital admissions are a relatively rare
event, with the overall prevalence being less than 2% [
], a case-control sample was
generated from the source population using nested case-control sampling strategy. Cases (n = 7,151)
were composed of all the children who had a DSH-related hospital admission that occurred
between the ages of 10 and 19 (inclusive) and no later than the year 2011. Each case was
randomly matched with 20 controls by sex and year of birth. The matched controls (n = 143,020)
were sampled from the source population, and they must not have had any DSH-related
hospital admission or not have died by the date of the first DSH-related hospital admission of the
matched case. Parental records were linked to the child?s information by the DLB through the
Family Connection Systems.
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Adolescent first DSH-related hospital admission (outcome)
The outcome for this study was the child?s first DSH-related hospital admission that occurred
between the ages of 10 and 19 during the study period (1981?2011). DSH-related hospital
admissions were identified from the HMDS and the EDDC, and DSH-related deaths were
identified from the Death Registrations. The identification of DSH-related hospital admissions
was based on the International Statistical Classification of Diseases and Related Health
Problems, 8th/9th Revisions, Clinical Modification (ICD-8/9-CM: E950-E959), and the 10th
Revision, Australian Modification (ICD-10-AM: X60-X84). The convention in previous research
was followed to include the ?events with undetermined intent? (ICD-8/9-CM: E980-E989;
ICD-10-AM: Y10-Y34) due to possible under-recording of DSH episodes in clinical settings
(Hawton & Fortune, 2008). For records in the EDDC, the presenting symptom, the major
diagnostic category, and the human intent of injury were used to identify any DSH-related
The first DSH-related hospital admissions were mainly identified in the HMDS (52.3%),
followed by the EDDC (45.9%). Of children with DSH-related hospital admissions,
approximately 1% died during the study period (2.0% for males, 0.3% for females). Of the first
DSHrelated hospital admissions, 7.2% were coded as ?event with undetermined intent? (8.7% for
males, 6.4% for females).
As described in the Study Population section above, we used an incidence density sampling
strategy to create the nested case-control sample for the analysis. For each case and the 20
matched controls, we considered the time when the case child had his/her first DSH-related
hospital admission as the end point of the observations for both the case and the 20 controls,
and the case and the controls were matched by the date of birth. Therefore, there was an equal
length of exposure interval allowing for the identification of parental admissions for the case
and the 20 controls.
Parental mental health and/or DSH-related hospital admissions (exposure)
Hospital admissions related to parental mental health disorders or DSH were identified from the
HMDS, the MHIS, and the EDDC using the ICD codes (mental health disorders: ICD-8/9-CM:
290?319, ICD-10-AM: F01-F99; the same ICD codes as described above were used to identify
parental DSH-related hospital admissions), and the presenting symptom and the major
diagnostic category in the EDDC. This study focused on parental mental health and/or DSH-related
hospital admissions that occurred prior to the end of exposure period. We combined maternal
and paternal hospital admissions, this is because our preliminary analyses did not show maternal
and paternal admissions had significantly different impacts on adolescent DSH risk.
The timing of children?s exposure to parental mental health and/or DSH-related hospital
admissions was partitioned into four distinct time periods as shown in Fig 1.
The definition for each time period is:
1. Pre-pregnancy: the time period prior to one year before the child?s birth .
2. Pregnancy and infancy: the time period between one year before and one year after the
child?s birth. We combined pregnancy and infancy to ensure an adequate sample size for
robust statistical estimates (n 16 for cases and n 25for controls). Additionally, there has
been a call for prenatal care to be provided in conjunction with postnatal care to parents
with mental health disorders to ensure seamless perinatal care for the best possible start in
life for their children [
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Fig 1. Timing of parental mental health and/or DSH-related hospital admissions.
3. Childhood: the time period between the 1st and the 10th birthday. Childhood was not
divided into early childhood (1?4 years) and late childhood (5?9 years), because our
preliminary results did not show a significant difference between these two periods in the
effects of parental mental health and/or DSH-related hospital admissions on adolescent
4. Adolescence: the time period between the 10th and 20th birthday .
The following groups of covariates associated with parental mental health disorders and
adolescent DSH risk were identified [
16, 17, 38
] hence adjusted for this study. The first group was
child perinatal factors including birth weight percentile by gestation, gestational age, and birth
]. The second group was early maternal socio-demographic characteristics, including
maternal age and marital status at the time of the child?s birth, and the socioeconomic status
(SES) of the neighbourhood where the mother resided at the time of the child?s birth. The age
of father or the mother?s partner at childbirth was also available in the linked data, with 5% of
the values being missing. We adjusted for paternal age in all the analyses, and the results largely
remain unchanged. Regarding SES, only the variable reflecting the neighbourhood SES for
mothers was available. However, 80% of the mothers in this study sample reported to be in a
marital or a de facto relationship at the childbirth, thus this information would also largely
reflect the neighbourhood SES for the fathers. The covariates in the first two groups were
identified from the MNS and the Birth Registrations. The index of neighbourhood SES is
developed by the Australian Bureau of Statistics [
], and it takes into account the income,
educational attainment, and employment status of people residing in a census collection
district containing approximately 250 dwellings.
Additionally, parental death due to any causes that occurred before the end of the exposure
period was adjusted for as a covariate, and it was identified from the Death Registrations.
Finally, children?s lifetime hospital admissions related to mental health disorders that occurred
before the end of the exposure period were included as a covariate, using the same ICD codes
and data source for the identification of parental mental health admissions described above.
Data analysis and statistical methods
We first examined the frequency distribution for each covariate among cases and controls
(Table 1). For each developmental period, we conducted conditional logistic regression
analysis to estimate the change in the odds of adolescent DSH (i.e., odds ratio, or OR) associated
with having a parent with a hospital admission related to a mental health disorder, DSH
behaviours, and both, compared to having no parents with mental health or DSH-related hospital
admissions. For each developmental period, we also compared the effect of having only one
parent with a mental health hospital admission with the effect of having both parents with
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mental health hospital admissions on the odds of adolescent DSH. Because the number of
children with both parents having a DSH-related hospital admission was very small, we only
examined the effect of having any (i.e., at least one) parent with a DSH-related hospital
admission on the odds of adolescent DSH (Table 2).
All the conditional regression analyses yielded ORs that were adjusted for the matching
factors in the case-control design, including the child?s sex, year of birth, and age at the end of the
exposure period. We conducted a series of multivariable regression analyses by progressively
controlling for an increasing number of covariates. The modelling was completed in three
steps. First (model 1), we adjusted for perinatal factors (birth weight by gestation, gestational
age, birth order), early maternal socio-demographic factors (maternal age, maternal marital
status, and maternal neighbourhood socioeconomic status at the time of the child?s birth), and
parental all-cause deaths. Second (model 2), we further adjusted for parental mental health
and/or DSH-related hospital admissions that occurred in other developmental periods. This
was to control for the interdependence of parental mental health disorders and DSH
behaviours in different developmental periods. Last (model 3), we further adjusted for children?s
The numbers in the parentheses refer to the percentages of children across all the categories in cases and controls respectively. For example, 48.83% (n = 3491) of the
cases did not have any parents with lifetime mental health or DSH-related hospital admissions. Two cases and 48 controls did not have their parents? records linked up,
leaving 7149 cases and 142972 controls included in this analysis.
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mental health hospital admissions in order to examine the extent to which the effects of
parental admissions on the odds of adolescent DSH is accounted for by children?s mental health
disorders, which has been shown to be the strongest covariate for DSH [
All covariates were treated as categorical factors following the conventional treatment of
these factors in existing literature (see categorisations in Table 1). Two cases and 48 controls
did not have their father?s records linked up, leaving 7,149 cases and 142,972 controls included
in the analyses. P values less than 0.05 were considered statistically significant, using a
twotailed test. Confidence intervals at 95% level were calculated. All statistical analyses were
conducted using SAS (EG) statistical software version 6.1 (SAS Institute Inc., Cary, NC, USA).
Effect of having a parent with a mental health hospital admission
In the sections below, we described the results in relation to having only one and both parents
with mental health hospital admissions.
Having only one parent with a mental health hospital admission. Among children with
a parent having a mental health hospital admission, the majority had only one parent with a
mental health admission (cases: 83%, controls: 89% in Table 2). Table 3 shows that after
controlling for all covariates in model 3, having only one parent with a lifetime mental health
admission was associated with a 1.26-fold (95%CI: 1.16?1.36, p<0.0001) increase in the odds
of having a DSH-related hospital admission during adolescence, compared to having no
parents with either mental health or DSH-related hospital admissions.
For each developmental period, the effect of having only one parent with a mental health
admission on the odds of adolescent DSH was significantly, yet largely attenuated, after
controlling for parental mental health and/or DSH-related admissions that occurred in other
developmental periods in model 2 (Table 3). After controlling for children?s mental health
hospital admissions in model 3, having only one parent with a mental health hospital admission
before pregnancy, during childhood, and during adolescence was associated with a 1.25-fold
(95%CI: 1.14?1.37, p<0.001), a 1.15-fold (95%CI: 1.05?1.26, p<0.01), and a 1.22-fold (95%CI:
1.11?1.34, p<0.001) increase in the odds of adolescent DSH respectively, compared to having
no parent with either mental health or DSH-related hospital admissions during that specific
developmental period (Table 3).
Both parents with a mental health hospital admission. Table 3 shows that after
controlling for all covariates in model 3, having both parents with a lifetime mental health hospital
admission was associated with a 1.41-fold (95%CI: 1.21?1.65, p<0.001) increase in the odds of
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a Effects were measured in odds ratios (95% confidence interval in parentheses) derived from conditional logistic regression analysis, in reference to adolescents of
unaffected parents during specific developmental periods (i.e., no mental health or DSH-related hospital admissions).
b Model 1: Adjusting for perinatal factors (gestational age, birth weight percentile by gestation, birth order), early maternal socio-demographic factors (maternal marital
status, maternal age, neighbourhood socioeconomic status at the time of the child?s birth), parental all-cause deaths; Model 2: Further adjusting for parental mental
health and/or DSH-related admissions in other developmental periods, except for the effects of lifetime parental mental health admissions; Model 3: Further adjusting
for children?s lifetime mental health admissions.
c These results refer to the ratios of aORs associated with having both parents with mental health admissions to having only one parent with mental health admissions.
For example, the first number 1.57 refers to the ratio of 3.05 to 1.95.
d Parental mental health admissions during the child?s adolescence must occur prior to the end of the observation for that child.
p < 0.05
adolescent DSH, compared to having no parents with either mental health or DSH-related
The effects of having both parents with a mental health hospital admission before
pregnancy, during childhood, and during adolescence had a significant, yet largely attenuated,
effect on the odds of adolescent DSH, after controlling for parental mental health and/or
DSH-related hospital admissions in other developmental periods in model 2. However, after
further controlling for children?s mental health hospital admissions in model 3, only having
both parents with a mental health hospital admission before pregnancy was significantly
associated with the odds of adolescent DSH (aOR = 1.66, 95%CI: 1.23?2.25, p<0.001) (Table 3).
Compared with having only one parent with a mental health admission, having both parents
with a mental health hospital admission did not have a significantly stronger effect on the odds
of adolescent DSH, when controlling for all covariates in model 3 (ratios of aORs in Table 3).
Effect of having a parent with a DSH-related hospital admission
PLOS ONE | https://doi.org/10.1371/journal.pone.0220704
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a Effects were measured in odds ratios (95% confidence interval in parentheses) derived from conditional logistic
regression analysis, in reference to adolescents of unaffected parents during specific development periods (i.e., no
mental health or DSH-related hospital admissions).
b Model 1: Adjusting for perinatal factors (gestational age, birth weight percentile by gestation, birth order), early
maternal socio-demographic factors (maternal marital status, maternal age, maternal neighbourhood socioeconomic
status at the time of the child?s birth), parental all-cause deaths; Model 2: Further adjusting for parental mental health
and/or DSH-related hospital admissions in other developmental periods, except for the effects of lifetime parental
mental health admissions; Model 3: Further adjusting for children?s lifetime mental health admissions.
c Parental DSH-related admissions during the children?s adolescence must occur prior to the end of follow-up.
p < 0.05
Parental DSH-related hospital admissions that occurred before pregnancy, during
pregnancy and infancy, and during childhood were associated with a 1.82- to 2.15-fold increase in
the odds of adolescent DSH, after controlling for parental mental health and/or DSH-related
hospital admissions that occurred in other periods in model 2. However, only parental
DSHrelated hospital admissions that occurred before pregnancy remained to have a significant and
strong effect on the odds of adolescent DSH (aOR = 1.97, 95%CI: 1.53?2.55, p<0.001), after
further controlling for children?s mental health hospital admissions in model 3 (Table 4).
Effect of having parents with both mental health and DSH-related hospital
It should be noted that mental health and DSH-related hospital admissions did not necessarily
co-occur in one parent. It may be the case that mental health admissions occurred in one
parent, and DSH-related admissions occurred in the other. After controlling for all covariates,
having parents with both lifetime mental health and DSH-related hospital admissions was
associated with a 1.83-fold (95%CI: 1.66?2.02, p<0.001) increase in the odds of adolescent
DSH, compared to having no parents with either mental health or DSH-related admissions.
This effect was 44% (95%CI: 30?59%, p<0.001) higher than the effect of having parents with a
lifetime mental health admission only (without DSH).
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Fig 2. Effect of parental mental health and/or DSH-related hospital admissions on the odds of adolescent DSH.
Fig 2 shows that after controlling for all covariates, having parents with both mental health
and DSH-related hospital admissions before pregnancy, during childhood, and during
adolescence was associated with a 1.36 to 1.43-fold increase in the odds of adolescent DSH,
compared to having no parents with either mental health or DSH-related hospital admissions in
that specific period. Fig 2 also shows that having parents with both mental health and
DSHrelated hospital admissions before pregnancy, during childhood, and during adolescence was
associated with increased odds of adolescent DSH, compared to having parents with a mental
health admission only in that specific period. This increase was only significant for childhood
(the ratio of aORs = 1.24, 95%CI: 1.06?1.45, p<0.01).
In line with previous research, this study showed that having a parent with a mental health
hospital admission during childhood or adolescence increased adolescent DSH risk [
Most importantly, this study has demonstrated that parental mental health disorders and/or
DSH-related hospital admissions that occurred before pregnancy had a strong influence on
children?s DSH risk in adolescence. This influence remained after controlling for important
psychosocial covariates and parental mental health and/or DSH-related hospital admissions
that occurred in pregnancy and infancy, childhood and adolescence. Moreover, this study has
shown that parental mental health and/or DSH-related hospital admissions that occurred
before pregnancy have a greater impact on adolescent DSH risk, compared to those that
occurred during childhood and adolescence. We found that among children who had a parent
with a mental health disorders and/or DSH-related hospital admission, nearly half of them had
a parent experiencing such a hospital admission before the conception of the child. This is
consistent with previous research showing that a preconception history of mental health problems
was present in the majority of women who had perinatal depressive symptoms , suggesting
that the effects of preconception mental health problems may be partly due to the chronicity of
mental health disorders. Therefore, this study calls for adequate attention to preconception
mental health in future research and interventions aimed at reducing the DSH risk among
People of reproductive age who have mental health disorders may receive inadequate
preconception care or psychosocial support [
] which may increase the risk of pregnancy
complications  and fetal growth restriction [
], leading to increased risk of DSH in
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adolescence . Further, psychosocial adversities associated with mental health disorders and
DSH behaviours before pregnancy are likely to persist through pregnancy and into the
postnatal period, affecting parenting capacities [
] and in turn the children?s mental health problems
] and DSH in adolescence [
This study has shown that having both parents with a mental health admission before
pregnancy had a stronger effect on adolescent DSH risk than having only one parent with a mental
health admission before pregnancy. Comparatively, the effect of having both parents with a
mental health admission did not differ significantly from the effect of having only one parent
on adolescent DSH risk in pregnancy and infancy, childhood and adolescence.
Another interesting finding in this study is that before pregnancy, during childhood, and
during adolescence, parental DSH-related hospital admissions moderately increased
adolescent DSH risk beyond the effect of parental mental health admissions, and this is in line with
previous research [
]. Additionally, we found that before pregnancy, parental DSH-related
hospital admissions had a stronger effect on adolescent DSH risk, compared to parental mental
health admissions. These findings together may have suggested that before pregnancy, parental
history of DSH may be a unique and stronger predictor for their children?s DSH risk in
adolescence, compared to the history of mental health disorders.
Last, after controlling for parental mental health and/or DSH-related hospital admissions in
childhood and adolescence and children?s lifetime mental health admissions, we did not find
that parental hospital admissions occurring during pregnancy and infancy increased
adolescent DSH risk. This may suggest that the effect of parental mental health problems during this
period on adolescent DSH risk is partially accounted for by both children?s and their parents?
mental health disorders that occur during childhood and adolescence, which may have a more
direct impact on adolescent DSH risk.
Strengths and limitations
The greatest strength of this study is the use of linked administrative data, which has offered
several advantages over traditional self-reported data. First, study samples are drawn from the
whole population to minimise selection bias, which has been a major concern in survey studies
on mental health [
]. Second, data are collected objectively using standardised clinical
diagnoses (e.g., ICD codes) by clinical personnel. Third, long-term routine collections make the
data on early exposure accessible, such as maternal socio-demographic factors during perinatal
period, and parental mental health disorders and DSH behaviours in early developmental
periods. Fourth, data linkage improves the identification of factors that may be perceived as
stigmatising, such as mental health disorders and DSH behaviours, which are subject to
underreporting in survey data. Last, data linkage assembles life-course events in a chronological
order more accurately than self-reported data, and this establishes more robust time sequences
for making causal inferences.
The results of this study should be interpreted in light of several limitations. First, mental
health disorders and DSH behaviours were only able to be identified if a person presented at a
hospital or an emergency department. The information about mental health related
consultations with a general practitioner, or a psychiatrist/psychologist who works in private practice,
and prescriptions of medications for the treatment of mental health disorders are not available
in the linked data. Therefore, the results in this study only reflect the impact of more severe
parental mental health disorders and/or DSH behaviours on adolescent DSH risk [
Additionally, outpatient records in private hospitals are not available in the linked data. However,
this may only have a small impact on the results, because private hospitals in Australia primarily
provide inpatient care, which has been captured by the HMDC dataset used in this study [
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Second, due to the small sample size, pregnancy and infancy were aggregated into one
period in this study, in order to improve statistical power for robust estimates. However, it
should be noted that these are two distinct periods, and there may be different mechanisms
underpinning the influence of parental mental health problems that occur in different periods
on the child?s mental health. Therefore, these two periods should be examined separately in
Third, emigration records were not available in the linked data. An estimated rate of
emigration from WA was under 2% in the general population [
]. We could not identify specific
individuals who emigrated from WA during the study period, thus mental health or
DSHrelated admissions recorded outside WA could not be accessed.
Fourth, only parental mental health admissions that occurred after the year 1966 could be
identified, which means that parental mental health and/or DSH-related admissions may be
under-reported. This may be particularly an issue for parental admissions before pregnancy
and may result in the underestimation of the effect of parental admissions before pregnancy
on adolescent DSH risk.
Fifth, no information was available to indicate the presence of suicidal intent in the linked
administrative data, therefore we could not identify whether suicidal intent was involved in a
DSH admission. Last, the information about whether the children resided with their parents in
each developmental period was generally not available in the administrative data used for this
study. Therefore, we could not differentiate certain environmental influence (e.g., parent-child
interactions, family functioning) from biological influence (e.g., genetic predisposition to
mental disorders and/or DSH).
This study showed the pervasive intergenerational effects of DSH risk over time. The
intergenerational effects were evident before adults became parents, and persisted when their children
reached adolescence. The findings call for mental health promotion and intervention policies
and practices that extend across lifetimes. This extended vision of the life-course approach
should target mental health before pregnancy, which is far earlier than the period considered
in current intervention strategies and policies aimed at reducing adolescent DSH risk. Further,
integrated child and family mental health services should begin in pregnancy and provide
continuous support for children as they grow up. The capacity for service systems to operate
intergenerationally depends on the extent to which services are integrated across different stages of
the life course, and how well transitions between child, adolescent and adult mental health
services are managed [
]. Rigorous investigation is needed to establish the mechanisms
underlying the effect of the timing of parental mental health disorders and DSH behaviours on
adolescent DSH risk.
We acknowledge the data custodians and the partnership of the Western Australian
Government Department of Health, who provided support as well as data for this project. We also
acknowledge the Western Australian Data Linkage Branch for linking the records. This article
does not necessarily reflect the views of the government department.
Conceptualization: Nan Hu, Catherine L. Taylor, Rebecca A. Glauert, Jianghong Li.
Formal analysis: Nan Hu.
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Funding acquisition: Catherine L. Taylor, Rebecca A. Glauert, Jianghong Li.
Methodology: Nan Hu, Catherine L. Taylor, Rebecca A. Glauert, Jianghong Li.
Project administration: Rebecca A. Glauert.
Software: Rebecca A. Glauert.
Supervision: Catherine L. Taylor, Rebecca A. Glauert, Jianghong Li.
Validation: Nan Hu, Catherine L. Taylor.
Writing ? original draft: Nan Hu.
Writing ? review & editing: Catherine L. Taylor, Rebecca A. Glauert, Jianghong Li.
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