Journal Pre-proof Mental Health Outcomes Among Parents of a Child who has a Developmental Disability: Comparing Different Types of Developmental Disability Sandra M. Marquis, Kimberlyn McGrail, Michael V. Hayes PII:
S1936-6574(19)30192-X
DOI:
https://doi.org/10.1016/j.dhjo.2019.100874
Reference:
DHJO 100874
To appear in:
Disability and Health Journal
Received Date: 4 July 2019 Revised Date:
15 November 2019
Accepted Date: 18 November 2019
Please cite this article as: Marquis SM, McGrail K, Michael Hayes V, Mental Health Outcomes Among Parents of a Child who has a Developmental Disability: Comparing Different Types of Developmental Disability, Disability and Health Journal, https://doi.org/10.1016/j.dhjo.2019.100874. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Elsevier Inc. All rights reserved.
Mental Health Outcomes Among Parents of a Child who has a Developmental Disability: Comparing Different Types of Developmental Disability
Authors Sandra M. Marquisa Kimberlyn McGrailb Michael V.Hayesc a
School of Public Health and Social Policy University of Victoria PO BOX 1700 STN CSC Victoria, BC Canada V8W 2Y2
[email protected] b
School of Population and Public Health University of British Columbia, 201-2206 East Mall Vancouver, B.C. Canada V6T 1Z3
[email protected]
c
School of Public Health and Social Policy University of Victoria PO BOX 1700 STN CSC Victoria, BC Canada V8W 2Y2
[email protected]
Corresponding Author Sandra M. Marquis School of Public Health and Social Policy University of Victoria PO BOX 1700 STN CSC Victoria, BC Canada V8W 2Y2
[email protected] phone: 1-250-818-7855 fax: 250-472-4109 This work was supported by the British Columbia Health Social Determinants (grant #36800-54061) There have been no previous presentations of abstracts regarding this research Declaration of conflict of interest: none Abstract word count: 225 Complete manuscript word count: 3,485 Number of references: 65 Number of tables: 4
1 Mental Health Outcomes Among Parents with a Child who has a Developmental Disability: Comparing Different Types of Developmental Disability
Disclaimer: All inferences, opinions and conclusions drawn in this paper are those of the authors, and do not reflect the opinions or policies of the Data Steward.
Abstract Background: There is very little information on the effects of different types of developmental disability on the mental health of parents of children who have a DD. Objective: This paper compared the mental health of parents of children with Autism Spectrum Disorder (ASD), Down syndrome, Fetal Alcohol Syndrome (FAS) and other types of DD. Methods: A cross-sectional design was used to examine population-level administrative health data for mental health outcomes in cohorts of fathers and mothers of children with four different types of a DD. As well as type of DD, additional variables were examined, these included: sex of the parent, age of the parent at birth of the child with the DD, income, sex of the child with the DD, number of children in the family and place of residence. Results: For both fathers and mothers odds of a diagnosis of depression or another mental health problem were associated with type of DD. Parents of children with FAS experienced the greatest odds of a depression or other mental health diagnosis. Odds of a diagnosis for fathers were associated with low income. Odds of a diagnosis for mothers were associated with the sex of the child with the DD. Conclusions: These findings are important for understanding families which include a child with a DD, as a guide for future research, and for developing effective programs and services for these parents.
2
Key words: developmental disability, children, parents, depression, mental health
3 Introduction Existing research has found that parents of a child who has a DD have increased mental health problems compared to parents of children who do not have an DD 1–5. Anon (2019) ‘Details removed for double blind reviewing’ found significantly greater odds of a depression or a mental health diagnosis in parents of a child who has a DD compared to parents of a child without a DD. Less is known about the differences and dynamics of effect within the group of parents who have a child with a DD, particularly the potential differences between parents of children with different types of DD.
The few studies that exist frequently compare families of children with Autism Spectrum Disorder (ASD) to families of children with other types of DD or compare families of children with Down syndrome to families of children with other types of DD. Many of these have reported greater effects on stress levels or mental health in parents who have a child with ASD
7–9
compared to parents with children with other types of DD. However, Estes et al.
(2013) found no difference in psychological distress between parents of children with ASD and parents of children with other types of DD. Watson et al. (2013) reported greater parental stress in parents of children with FAS compared to parents of children with ASD. HauserCram et al. (2001) found that type of DD affected maternal but not paternal stress.
Other studies have reported a “Down syndrome advantage” with parents of children with Down syndrome experiencing less stress, 13,14 fewer psychiatric problems, 15 or greater well-being 16 than parents of children with other DD. However, Mitchell et al. (2015) reported no differences in parental stress in parents who had a child with Down syndrome compared to
4 parents of children with other DD, once mothers’ age, education and social support and child behavior problems were considered. Hodapp et al. (2012) concluded that any advantage of parents of children with Down syndrome compared to parents of children with other DD may be due to the advantages that are associated with increased maternal age at birth of the child.
There is evidence that a broad range of factors may affect the well-being of parents of children with a DD
19
. For example, some studies have found a negative relationship between
income level and parent stress in families with a child with a DD 13,20,21. Income has also been found to play a role in the effects of the presence of a child with a DD on the mental health of parents. Emerson et al. (2006) measured happiness, self-esteem and self-efficacy among mothers of children with a DD compared to mothers of children without a DD. They found that statistically controlling for differences in socio-economic position between the two groups fully accounted for the between-group differences in maternal happiness and accounted for over 50% of the elevated risk for poor self-esteem and self-efficacy. Using data from the Millennium Cohort Study in the United Kingdom, Emerson et al. ( 2010) found that both mothers and fathers of children with cognitive delay were at higher risk of psychiatric disorders than were mothers and fathers of children without cognitive delay. However, controlling for between-group differences in socio-economic conditions (income, job status, education, neighborhood deprivation etc.) reduced the difference in probable psychiatric disorder to non-significance for fathers and significantly attenuated the relationship for mothers.
5 Studies have reported on many other variables which may affect parental wellbeing in families with a child with an DD 19. Among others, these variables include: sex of the child with the DD 13,23,24, size of the family 25, child behavior 26–31, and stigma 32,33.
Current and conflicting research evidence regarding the effect of these variables may be due to the limited family and individual variables included in existing studies, the small size of most study samples, and failure to differentiate DD by type. Despite these limitations research evidence does indicate that care-giving is a stressful undertaking 19, and factors related to meeting the ongoing needs of children with a DD may be responsible for elevated use of health care services for depression and other mental health conditions 6.
The objective of this study was to compare the odds of a depression or mental health diagnosis for parents of children with varying types of DD. This study used a population-level administrative database to examine four categories of DD and other potentially significant variables. The data do not provide information on all of the potential variables which may affect parents of children who have a DD. However, the data can be used to differentiate between types of DD and do include potentially important variables such as maternal age and measures of income. In addition, the data were used to determine the effects of these variables on fathers and mothers separately. The population-level data and availability of evidencebased variables enables identification of potential risk factors among fathers and mothers of children who have a DD.
6 Methods This study used a cross-sectional design to analyze administrative health data from 1985-2014 for parents of children who have a DD and live in the province of British Columbia, Canada. Data were obtained from Population Data B.C. (PopData), which provides access to and linkages across multiple data sets for the entire population of B.C., with the exception of information on services provided through non-fee-for-service funding (a minority of services) and federally covered special populations.
The B.C. Ministry of Health approved use of the data. Ethics approval was granted by the University of Victoria Human Research Ethics Board (#15-043).
Three databases were linked. •
The Medical Services Plan (MSP) payment file contains administrative information for all fee-for-service care provided by physicians in B.C. The file includes the date of each visit to a physician, the diagnostic code (ICD-9), the Health Authority where the visit occurred, a subsidy code indicating low income status and the amount of the subsidy 34.
•
A central consolidation file of demographic information on all individuals in B.C. including birth date, sex and neighbourhood income quintile derived from census data 35,36
.
7 •
The hospital separation file contains information on all hospitalizations, including the date of admission and discharge and related diagnostic codes (ICD-9 and ICD-10)
37
.
Defining the cohorts The cohorts for analysis were developed first by identifying children with a DD using the algorithm developed by Lin, Balogh, et al. (2013). Using this algorithm, children aged 0-19 were identified by ICD-9 codes in MSP files and ICD-9 and ICD-10 codes in hospital separations files (see Appendix A). Children were then linked using MSP numbers to their mothers and fathers. The data were grouped overall as fathers and mothers, fathers and mothers from the same couple were not paired. There were no parents in the data with more than one child with a DD.
Primary outcomes The primary outcomes of depression and mental health outcomes were selected based upon prior work in which a number of outcomes were examined (depression, mental health, hypertension, back problems etc.) 4 and which found that depression and mental health problems were most significantly associated with having a child with a DD. Depression and mental health problems were measured using diagnostic codes in the physician and hospital files (see Appendix B). Only diagnoses following the birth of the child with the DD were used in analyses. Birth of the child with the DD was used as a common starting point for analyses. Birth of the child with the DD was used for two reasons 1) there was considerable variation in the data among parents in the length of time prior to the birth of the child with the DD; 2) determining the time of initial diagnoses for FAS and ASD was difficult, as these initial
8 diagnoses are often made months or years after first symptoms arise and the diagnoses may not be made by physicians and therefore are not found in the administrative data base. The implication is that the potential effects of having a child with a DD may present themselves in advance of the child receiving a formal diagnosis.
Explanatory variables Developmental disabilities were disaggregated to Autism Spectrum Disorder (ASD), Fetal Alcohol Syndrome (FAS), Down syndrome and Other as there is some evidence that these groups have different effects on mental health outcomes 7,10,12–17,24,39. The Other group contained all other types of DD not in the first three groups. Fetal Alcohol Syndrome was used rather than Fetal Alcohol Spectrum Disorder as there are no ICD codes for FASD.
Other explanatory variables were selected based upon availability in the administrative data and evidence of an effect in the literature. The variables used were: sex of the parent 40–44, sex of the child with the DD 23,24; age of the parent at birth of the child with the DD 18,45; number of children in the family 25,45; receipt of an MSP subsidy; neighborhood income quintile; and health authority in which the person lived.
This study used both an individual and neighborhood measure of socioeconomic status because the latter is limited as it is an ecological variable and the former is limited because it only differentiates low income (receiving a subsidy). There is considerable evidence that families with a child with a DD have lower income and savings levels than families of children without a DD 19,46–52 and that lower income or socio-economic status affects stress or the
9 mental health of parents with a child with a DD
13,20–22
. Neighborhood income is measured in
quintiles and individual subsidy is a binary measure (received a subsidy/did not receive a subsidy).
The variable Health Authority refers to the location where the individuals are living. Health services vary across the province of B.C., with access to an increased number and wider variety of services in southern (more urban) locations compared to northern locations. Differences in availability of services therefore may have an impact upon the findings in this study. In order to maximize the number of people included in the analyses, the last available income information and location (Health Authority) in the data were used. Due to missing postal codes, in all the cohorts in this study, the variables Health Authority and Neighbourhood Income Quintile had the most missing data.
Analysis Birth of a child with a DD was used as a common analytic starting point. Data were analyzed using logistic regression to determine whether parents were diagnosed with either depression or another mental health problem (not including depression) following birth of a child with a DD. SAS proc logistic 53 for binary data (“yes” had a diagnosis of depression at any time or “no” did not have a diagnosis of depression at any time) was used for all logistic regression analyses. Proc logistic fitted logistic regression models and estimated parameters by maximum likelihood using a Fisher’s Scoring algorithm. Individuals with any missing observations were automatically deleted during model formation by proc logistic. Initially variables were added manually to the model. This was tested against the three automatic
10 selection methods offered by proc logistic. Very little difference was found between the outcomes of the manual selection and the three automatic methods. Also, there was no difference in the outcomes between the three methods (forward, backward or stepwise). Stepwise selection was ultimately used for all of the proc logistic procedures. The probability level (alpha) was set at 0.01 for entry of the variables into the model and as a criterion for the variable to stay in the model. Odds ratios were produced for each variable that had a significant relationship with the outcome of interest. SAS proc logistic automatically dropped any variables that did not improve the fit of the regression model; therefore these variables do not appear in the final results tables.
Initially, mothers and fathers were included in a single model to enable comparison of odds of a diagnosis of depression or a mental health problem and then the data were stratified for separate analyses. In addition, a smaller subset of mothers and fathers was analyzed in order to reduce the variability of the sample for effects of time (cohort effect). The subset was of parents whose children with a DD were born between 1990 and 1995. In each of the models the same variables were used in analyses. These variables were based upon information in the literature and variables available in the administrative data.
In the Class statements the reference levels were formed as male for the variable of child sex, Vancouver Coastal for the variable of health authority, no subsidy for the variable of MSP subsidy, and highest income quintile for the variable of income quintile.
11 Results There were data available for 22,376 fathers and 25,066 mothers following the birth of the child with the DD (Table 1). The occurrence of depression and/or a mental health problem was high for both mothers (83.03%) and fathers (60.18%). When depression and other mental health problems were separated, 73.69% of mothers and 47.98% of fathers had a diagnosis of depression, while 62.4% of mothers and 42.32% of fathers had an occurrence of a mental health problem other than depression.
After adjusting for explanatory variables in the larger sample, mothers had higher odds of a diagnosis of depression (2.97 (CI 2.85-3.09)) and higher odds of a diagnosis of a mental health problem (2.17 (CI 2.08-2.26)) compared to fathers (Table 2). After adjusting for explanatory variables in the smaller sample, mothers still had higher odds of a diagnosis of depression (3.46 (CI 23.16-3.79)) and higher odds of a diagnosis of a mental health problem (2.49 (CI 2.29-2.70)) compared to fathers (Table 2). Table 3 and Table 4 show the stratified analyses for mothers and fathers. Having a child with ASD, FAS or Other compared to having a child with Down syndrome, increased odds of a depression (Table 3) or mental health problem (Table 4) diagnosis for both mothers and fathers. In all cases the effects of FAS were the greatest (odds ratios range from 1.8 to 2.8).
In the larger sample, for both mothers and fathers, higher age at birth of the reference child slightly decreased odds of a depression (Table 3) or mental health problem (Table 4) diagnosis. An increasing number of children in the family was also associated with slightly lower odds of a diagnosis of depression (Table 3) or of a mental health problem (Table 4)
12 diagnosis for both fathers and mothers. There was no association of the sex of the child with the DD with odds of a diagnosis of depression (Table 3) or a mental health problem (Table 4) for fathers. For mothers odds of a depression (1.15 (CI 1.07-1.23)) (Table 3) or mental health (1.11 (CI 1.04-1.18)) (Table 4) diagnosis were slightly increased if the child with the DD was female compared to male.
In the larger sample, receiving an MSP subsidy had no significant association with odds of a diagnosis of depression (Table 3) or a mental health problem (Table 4) for mothers, however, fathers had increased odds of a depression (1.20 (CI 1.12-1.30)) (Table 3) or mental health (1.30 (CI 1.20-1.40)) (Table 4) diagnosis if they were receiving an MSP subsidy. Neighborhood income quintile had no significant association with odds of a depression (Table 3) or mental health (Table 4) diagnosis for either mothers or fathers. There was no consistent pattern of association for health authority.
In the subset sample (mothers and fathers of children born 1990-1995) there were fewer variables associated with odds of a depression or a mental health diagnosis. However, similar to the larger sample, parental sex and type of DD were associated with odds of a depression (Table 3) or mental health (Table 4) diagnosis.
Discussion This study used population-level administrative health data for the first time to examine the factors involved in the mental health of parents of children who have a DD and to compare effects of type of DD. The use of population-level data has many benefits for studying
13 disability-related issues 54 and addresses some of the weaknesses of previous studies. Population-level data can be used to form large cohorts of people with relatively rare diagnoses 49,55,56
. The data do not rely on convenience sampling or self-reports; include information on
demographics; reduce loss to follow-up; provide large comparison groups 57; maintain privacy 57,58
; reduce selection bias 59; and include some of the individual variables that may be
associated with outcomes. Additionally, this study included population-level data on potentially important social (income and geographic location) and familial (parental age and number of children in the family) variables.
Findings from this study clearly show that at a population-level type of DD made a difference for odds of either a depression or mental health diagnosis for both fathers and mothers, with FAS showing the greatest effect. This is the first time that population-level data has been used to study the effect of type of DD. This study also found that there were additional predictors of depression and mental health problems in these families and that these varied depending upon the sex of the parent. A female child with a DD was associated with higher odds of a diagnosis for mothers but not for fathers. Low income (as measured by a subsidy for health insurance premiums) was associated with greater odds of diagnosis for fathers, but not for mothers.
A greater number of children in the family was associated with lower odds of diagnosis for both mothers and fathers. It is unknown whether the reduced odds of a diagnosis were due to a protective effect of having more children or due to a lack of time for parents to access
14 health services. Alternatively, there may be some selection bias apparent in these results; parents who feel that they are better able to cope may be choosing to have more children.
Variables which were significant in the larger sample but not in the smaller subset sample included measures of income, age of the parent at birth of the child with the DD, number of children in the family, and sex of the child with the DD. These differences between the larger sample and the smaller sample may be primarily due to sample size rather than to cohort effect. In the larger sample odds associated with age of the parent, sex of the child with the DD and number of children in the family were relatively small. However, given that the level of significance was selected as p=0.01, these variables should be given some consideration. Differences between the larger and smaller samples may further illustrate the importance of using large data bases to expand the study of disability-related topics.
While this study adds significant understanding, there are limitations to these analyses. The data analyzed were based upon ICD-9 and ICD-10 diagnostic codes used by physicians in the province of B.C. The researchers had no control over the timing or accuracy of diagnosis and coding by physicians. In addition, possible errors in coding and sorting the data may have occurred. There is no information in the data set on positive outcomes of having a child who has a DD. The data also does not include information on other potentially important social determinants variables such as ethnicity, parent education, and marital status, or individual variables such as child behavior or severity of the DD. There is difficulty in establishing the date of initial diagnoses for some DD groups, though this was acknowledged by using the date of birth as the anchoring point for all parents.
15 Conclusions from the data may also be limited by the fact that depression and mental health diagnoses prior to the birth of the child with the DD were not included in the analyses. The decision to exclude this data was made due to the differences in age between parents at the birth of their child; older parents (often parents of children with Down syndrome) had more years in which to have a depression or mental health diagnosis compared to younger parents (often parents of children with FAS). There was also no information collected regarding the length of time between diagnosis of the child with the DD and the initial post-birth mental health diagnosis of parents. Lack of these data limit the interpretation of the results regarding timing and development of mental health issues in these parents.
The data were grouped overall as fathers and mothers. Further population-level studies could match fathers and mothers from the same couple and examine the implications of a mental health diagnosis of one or more parents in the same couple.
Using population-level administrative data this study adds to the understanding of parents of children with a DD. The very large data set addresses common issues of small sample size and reliance on convenience sampling found in many studies of parents of children with an DD. Large data sets and lack of sampling bias improve the overall generalizability of findings 60. In addition, previous research on parents largely focused on mothers. This may be because mothers are often the primary caregivers of children who have a disability 61,62 and mothers may report more care-giving burden compared to fathers 62–65. This study shows that the predictors for fathers and mothers may be different. Based upon these findings it is evident that future research and program planning should place a focus on the mental health of both fathers and
16 mothers. Particular attention is warranted for those who have a low income and for parents of children with FAS. Future research may be able to shed further light on causal pathways and interventions that address the needs of children with a DD as well as supporting their families.
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Appendix A ICD-9 and ICD-10 codes used for identification of developmental disability (disabilities include Autism Spectrum Disorder, Down syndrome, Fetal Alcohol Syndrome and Other developmental disabilities)
Table A1. ICD-9 Codes for Developmental Disabilities ICD-9 Number
Disorder
299
Pervasive development disorders (e.g. autism)
317
Mild mental retardation
318
Moderate severe and profound mental retardation
319
Unspecified mental retardation
7580-7583
Chromosomal anomalies for which a developmental disability is typically present (e.g. Down syndrome, cri-du-chat syndrome)
7585
Other conditions due to autosomal anomalies
7588
Other conditions due to chromosome anomalies
7589
Conditions due to anomaly of unspecified chromosome
7595
Tuberous sclerosis
75981
Other and unspecified congenital anomalies: Prader–Willi
75983
Other and unspecified congenital anomalies: Fragile X
75989
Other and unspecified congenital anomalies: other (e.g. Menkes disease, Laurence–Moon–Biedl, Rubinstein–Taybi syndrome, etc.)
76071
Foetal alcohol syndrome
76077
Foetal hydantoin syndrome
Table A2. ICD-10 Codes for Developmental Disabilities ICD-10 Number
Disorder
F700
Mild mental retardation with the statement of no, or minimal, impairment of behavior
F701
Mild mental retardation, significant impairment of behaviour requiring attention or treatment
F708
Mild mental retardation, other impairments of behavior
F709
Mild mental retardation without mention of impairment of behavior
F710
Moderate mental retardation with the statement of no, or minimal, impairment of behavior
F711
Moderate mental retardation, significant impairment of behaviour requiring attention or treatment
F718
Moderate mental retardation, other impairments of behavior
F719
Moderate mental retardation without mention of impairment of behavior
F720
Severe mental retardation with the statement of no, or minimal, impairment of behavior
F721
Severe mental retardation, significant impairment of behaviour requiring attention or treatment
F728
Severe mental retardation, other impairments of behavior
F729
Severe mental retardation without mention of impairment of behavior
F730
Profound mental retardation with the statement of no, or minimal, impairment of behavior
F731
Profound mental retardation, significant impairment of behaviour requiring attention or treatment
F738
Profound mental retardation, other impairments of behavior
F739
Profound mental retardation without mention of impairment of behavior
F780
Other mental retardation with the statement of no, or minimal, impairment of behaviour
F781
Other mental retardation, significant impairment of behaviour requiring attention or treatment
F788
Other mental retardation, other impairments of behavior
F789
Other mental retardation without mention of impairment of behavior
F790
Unspecified mental retardation with the statement of no, or minimal, impairment of behavior
F791
Unspecified mental retardation, significant impairment of behaviour requiring attention or treatment
F798
Unspecified mental retardation, other impairments of behavior
F799
Unspecified mental retardation without mention of impairment of behavior
F840
Childhood autism
F841
Atypical autism
F843
Other childhood disintegrative disorder
F844
Overactive disorder associated with mental retardation and stereotyped movements
F845
Asperger’s syndrome
F848
Other pervasive developmental disorders
F849
Pervasive developmental disorder, unspecified
Q851
Tuberous sclerosis
Q860
Foetal alcohol syndrome
Q861
Foetal hydantoin syndrome
Q871
Aarskog, Prader–Willi, de Lange, Seckel, etc.
Q8723**
Rubinstein–Taybi
Q8731**
Sotos
Q878 Q90
Other Down syndrome
Q91 – Q939
Chromosomal abnormalities not elsewhere classified
Q971
Female with more than three chromosomes
Q992
Fragile X Syndrome
Q998
Other specified chromosomal abnormalities
Appendix B Table B1. ICD Numbers for Depression
ICD Numbers
Disorder
ICD-9
309
Adjustment reaction
311
Depressive disorder, not elsewhere classified
50B
Anxiety/depression
ICD-10 F32
Depressive episode
F33
Recurrent depressive episode
F34
Persistent mood disorder
F38
Other mood disorders
Table B2. ICD Numbers for Mental Health Problems other than Depression
ICD Numbers ICD-9
Disorder
291-293
Psychotic conditions due to use of psychoactive substances
295-298
Other psychoses
300-308
Neurotic disorders, personality disorders and other nonpsychotic mental disorders
312
Disturbance of conduct not elsewhere classified
ICD-10 F10 – F19
Mental and behavioural disorders due to use of psychoactive substances
F20 – F25, F28, F29
Schizophrenia, schizotypal and delusional disorders
F30
Manic episode
F31
Bipolar affective disorder
F40 – F45, F48
Neurotic, stress-related and somatoform disorders
F50 – F55, F59
Behavioural syndromes associated with physiological disturbances and physical factors
F60 – F66, F68, F69
Disorders of adult personality and behaviour
1 Table 1. Descriptive Statistics for Families of the Child with a DD Variable Number of fathers Number of mothers Mean age of fathers at birth of the child with the DD Mean age of mothers at birth of the child with the DD Mean number of children in the family
Families of Children with a DD 22,376 25,066 32.85 (S.D. 6.73) 30.42 (S.D. 6.09) 1.15 (SD 0.36) Range 1-7
Type of Developmental Disability ASD FAS Down syndrome Other
15,316 (58.20%) 1,844 (7.01%) 2,380 (9.04%) 6,780 (25.76%)
Income quintile at birth of the child with the DD Lowest 2nd 3rd 4th Highest
4,643 (26.25%) 3,813 (21.55%) 3,429 (19.38%) 3,155 (17.83%) 2,650 (14.98%)
Number and percent of fathers who have a depression and/or mental health problem following birth of the child with the DD Number and percent of mothers who have a depression and/or mental health problem diagnosis following birth of the child with the DD
13,465 (60.18%)*
Number and percent of fathers who have a diagnosis of depression following birth of the child with the DD Number and percent of mothers who have a diagnosis of depression following birth of the child with the DD
10,735 (47.98%)†
Number and percent of fathers who have a diagnosis of a mental health problem following birth of the child with the DD Number and percent of mothers who have a diagnosis of a mental health problem following birth of the child with the DD
9,470 (42.32%)‡
* significantly different (p<0.0001) † significantly different (p<0.0001) ‡ significantly different (p<0.0001)
20,812 (83.03%)*
18,470 (73.69%)†
15,658 (62.47%)‡
2 Table 2 . Predictors of a Depression or Mental Health Diagnosis for Mothers and Fathers, Odds Ratios (CI) Variable
Depression Diagnoses of Mothers and Fathers 1985-2014 (n=43,052)
Parents’ sex (female vs male)
2.966 (2.845-3.092)
Depression Diagnoses of Mothers and Fathers of Children Born 1990-1995 (n=9,955) 3.457 (3.157-3.788)
Mental Health Problem Diagnoses of Mothers and Fathers 1985-2014 (n=43,052) 2.167 (2.082-2.255)
Mental Health Problem Diagnoses of Mothers and Fathers of Children Born 1990-1995 (n=9,955) 2.485 (2.285-2.702)
Age at birth of the child with the DD
0.981 (0.978-0.985)
N.S.
0.978 (0.975-0.981)
N.S.
Sex of the child with the DD (female vs male)
1.098 (1.049-1.150)
N.S.
1.066 (1.020-1.114)
N.S.
Number of children in the family
0.739 (0.699-0.780)
N.S.
0.727 (0.689-0.766)
N.S.
ASD vs Down syndrome
1.326 (1.231-1.429)
1.541 (1.300-1.825)
1.248 (1.160-1.343)
1.316 (1.119-1.548)
FAS vs Down syndrome
2.107 (1.862-2.384)
2.015 (1.581-2.570)
2.610 (2.318-2.939)
2.635 (2.077-3.344)
Other vs Down syndrome
1.483 (1.368-1.609)
1.436 (1.199-1.720)
1.429 (1.321-1.546)
1.288 (1.084-1.531)
Lowest vs highest
N.S.
N.S.
N.S.
N.S.
2nd vs highest
N.S.
N.S.
N.S.
N.S.
3rd vs highest
N.S.
N.S.
N.S.
N.S.
4th vs highest
N.S.
N.S.
N.S.
N.S.
1.104 (1.048-1.163)
N.S.
1.175 (1.119-1.235)
1.192 (1.073-1.325)
1.267 (1.187-1.351)
1.245 (1.080-1.436)
1.138 (1.070-1.211)
1.186 (1.040-1.353)
Type of DD
Income quintile
Receipt of an MSP subsidy Health authority Interior vs Vancouver Coastal Fraser vs Vancouver Coastal
1.128 (1.069-1.190)
1.051 (0.936-1.182)
1.206 (1.145-1.270)
1.407 (1.260-1.572)
Island vs Vancouver Coastal
1.376 (1.291-1.467)
1.369 (1.190-1.576)
1.412 (1.329-1.502)
1.556 (1.365-1.773)
Northern vs Vancouver Coastal
1.171 (1.080-1.270)
1.085 (0.918-1283)
0.897 (0.831-0.969)
0.952 (0.816-1.111)
3 N.S. (not significant)
4 Table 3. Predictors of a Depression Diagnosis for Parents of Children who have a Developmental Disability, Odds Ratios (CI) Variable
Mothers of Children 1985-2014 (n=23,028)
Mothers of Children Born 1990-1995 (n=5,314)
Fathers of Children 1985-2014 (n=19,997)
Fathers of Children Born 1990-1995 (n=4,641)
Age at birth of the child with the DD
0.973 (0.958-0.978)
N.S.
0.987 (0.983-0.991)
N.S.
Sex of the child with the DD (female vs male)
1.150 (1.074-1.231)
N.S.
N.S.
N.S.
Number of children in the family
0.743 (0.687-0.804)
N.S.
0.732 (0.679-0.790)
N.S.
ASD vs Down syndrome
1.395 (1.257-1.549)
1.457 (1.131-1.877)
1.231 (1.109-1.368)
1.638 (1.299-2.067)
FAS vs Down syndrome
2.440 (2.028-2.935)
1.761 (1.219-2.543)
1.841 (1.556-2.178)
2.335 (1.689-3.229)
Other vs Down syndrome
1.534 (1.368-1.721)
1.239 (0.947-1.622)
1.412 (1.259-1.582)
1.620 (1.266-2.073)
Lowest vs highest
N.S.
N.S.
N.S.
N.S.
2nd vs highest
N.S.
N.S.
N.S.
N.S.
3rd vs highest
N.S.
N.S.
N.S.
N.S.
4th vs highest
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
1.201 (1.115-1.293)
N.S.
Interior vs Vancouver Coastal
1.328 (1.208-1.460)
1.338 (1.067-1.678)
1.216 (1.113-1.329)
N.S.
Fraser vs Vancouver Coastal
1.150 (1.065-1.243)
1.077 (0.900-1.288)
1.107 (1.028-1.191)
N.S.
Island vs Vancouver Coastal
1.454 (1.322-1.599)
1.467 (1.173-1.835)
1.318 (1.208-1.438)
N.S.
Northern vs Vancouver Coastal
1.175 (1.045-1.322)
1.078 0.836-1.389)
1.163 (1.041-1.300)
N.S.
Type of DD
Income quintile
Receipt of an MSP subsidy Health authority
N.S. (not significant)
5 Table 4. Predictors of a Mental Health Problem Diagnosis for Parents of Children who have a Developmental Disability, Odds Ratios (CI) Variable
Mothers of Children 1985-2014 (n=23,028)
Mothers of Children Born 1990-1995 (n=5,314)
Fathers of Children 1985-2014 (n=19,997)
Fathers of Children Born 1990-1995 (n=4,641)
Age at birth of the child with the DD
0.971 (0.967-0.976)
N.S.
0.984 (0.980-0.988)
N.S.
Sex of the child with the DD (female vs male)
1.110 (1.044-1.180)
N.S.
N.S.
N.S.
Number of children in the family
0.716 (0.665-0.770)
N.S.
0.735 (0.680-0.794)
N.S.
ASD vs Down syndrome
1.330 (1.206-1.467)
1.457 (1.164-1.824)
1.141 (1.025-1.270)
1.179 (0.934-1.487)
FAS vs Down syndrome
2.834 (2.401-3.347)
2.612 (1.867-3.654)
2.381 (2.009-2.822)
2.777 (1.992-3.872)
Other vs Down syndrome
1.425 (1.281-1.586)
1.296 (1.021-1.646)
1.408 (1.254-1.582)
1.281 (1.001-1.640)
N.S.
N.S.
N.S.
N.S.
Type of DD
Income quintile Lowest vs highest 2nd vs highest
N.S.
N.S.
N.S.
N.S.
3rd vs highest
N.S.
N.S.
N.S.
N.S.
4th vs highest
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
1.297 (1.204-1.397)
N.S.
Interior vs Vancouver Coastal
1.177 (1.081-1.282)
1.263 (1.047-1.524)
1.095 (1.001-1.198)
1.115 (0.929-1.338)
Receipt of an MSP subsidy Health authority Fraser vs Vancouver Coastal
1.251 (1.165-1.343)
1.589 (1.356-1.862)
1.155 (1.071-1.244)
1.240 (1.063-1.446)
Island vs Vancouver Coastal
1.495 (1.372-1.628)
1.809 (1.493-2.193)
1.332 (1.220-1.455)
1.353 (1.130-1.620)
Northern vs Vancouver Coastal
0.874 (0.788-0.970)
1.035 (0.835-1.283)
0.920 (0.821-1.031)
0.864 (0.692-1.079)
N.S. (not significant)
6