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Previous studies have reported a high prevalence of chronic otitis media (OM) and hearing impairment (HI) in Aboriginal children in the Northern Territory (NT) of Australia. Children affected by these disorders are believed to be at increased risk for adverse outcomes in early childhood development, school attendance, academic performance, and child maltreatment and youth offending. However, to date, there have been no studies quantifying the association between HI and these outcomes in this population.
This study will investigate the association between HI and the 5 outcomes in Aboriginal children living in remote NT communities.
Individual-level information linked across multiple administrative datasets will be used to conduct a series of retrospective observational studies on selected developmental and school outcomes. The predictor variables for all studies are the results from audiometric hearing assessments. The outcome measures are as follows: Australian Early Development Census results, representing developmental readiness for school, assessed around 5 years of age; Year 1 school attendance rates; Year 3 school-based academic performance, assessed in the National Assessment Program—Literacy and Numeracy; incidence of child maltreatment events (including both notifications and substantiated cases); and incidence of a first guilty verdict for youth offenders. Confounding and moderating factors available for the analysis include both community-level factors (including school fixed effects, socioeconomic status, level of remoteness, and housing crowdedness) and individual-level factors (including maternal and perinatal health and hospital admissions in early childhood).
The study commenced in 2018, with ethics and data custodian approvals for data access and linkage. This has enabled the completion of data linkage and the commencement of data analysis for individual component studies, with findings expected to be published in 2019 and 2020.
This study will provide first evidence of the impact of OM-related HI on the developmental, educational, and social outcomes of Australian Aboriginal children. The findings are expected to have significant implications for policy development, service design, and resource allocation.
RR1-10.2196/15464
Children’s experiences during infancy and early childhood are critical to their health and educational and socioemotional well-being throughout their life course [
Otitis media (OM) and the associated HI among Australian Aboriginal children has been extensively researched [
Although there is an abundance of the literature showing the correlations among child maltreatment, youth offending, early childhood development, school performance, and school attendance [
To address this research gap, the Hearing Loss in Kids (HeLoKids) Project aims to apply a life-course epidemiological approach [
Specifically, the study will undertake a series of studies that test the following hypotheses:
HI is independently associated with poorer developmental outcomes at the time of entry into full-time school (aged about 5 years).
HI is independently associated with lower school attendance rates in Year 1 (aged about 6-7 years).
HI is independently associated with poorer academic achievements in Year 3 (aged about 8 years).
HI is independently associated with higher risk of child maltreatment.
HI is independently associated with higher risk of youth offending.
Conceptual diagram indicating the pathways of influence of hearing impairment on life trajectories and the interplay between them (SES: socioeconomic status).
The NT is located in the north and central part of Australia, with an area of 1,352,176 square kilometers. It has the smallest total population among Australian states and territories, with an estimated resident population of 247,300 in 2018 [
The HeLoKids Project will be conducted as a series of retrospective observational cohort studies to examine the association between HI and a range of developmental, educational, and social outcomes. These studies will utilize administrative datasets held within an extensive repository of deidentified unit-level information for NT children, which has been incrementally developed since 2009 [
The Remote Hearing Assessment (RHA) dataset contains middle ear examination and audiometric assessment information collected by the NT Outreach Hearing Health Program [
The NT Outreach Hearing Health Program uses pure tone audiometry to assess children’s hearing ability and determine the type (sensorineural, conductive, mixed, or indeterminate) and level of hearing loss. The level of hearing loss of an ear is calculated by taking the average of the thresholds of hearing (as deviation from normal threshold, in decibels Hearing Level—dB HL) for 3 frequencies: 500 Hz, 1000 Hz, and 2000 Hz. The results for each ear are classified as either normal or 1 of 4 ordinal categories of hearing loss, namely mild (16-30 dB HL), moderate (31-60 dB HL), severe (61-90 dB HL), and profound (91 dB HL or greater). This relatively conservative classification of hearing loss was chosen over the more widely used World Health Organization classification, as it is deemed more suitable for children aged under 15 years [
The dataset provided to this study includes information collected from 2007 to 2015, for over 8000 children and young people aged between 0 and 21 years, which is about 22% of the NT Aboriginal population in this age group. Children and young people access these services through referral by primary care services. From January 2013, access to these services was prioritized according to clients’ need for service. This means that the children and young people whose records are captured in the RHA dataset are not a random sample of the general population, and the information is likely to be biased toward those with abnormal middle ear examination and hearing difficulties.
The study cohort comprises NT-born Aboriginal children, with hearing assessment results in the RHA dataset and with a residential location classified as
Otitis media—related hospital admission diagnoses and surgical procedures used to exclude children who had received surgical treatment, with International Classification, 10th Revision-Australian Modification codes.
ICD-10AMa Code | Diagnosis/procedure | |
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||
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H65 | Nonsuppurative otitis media |
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H66 | Suppurative and unspecified otitis media |
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H72 | Perforation of tympanic membrane |
|
||
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41527-00 | Myringoplasty, transcanal approach |
|
41530-00 | Myringoplasty postaural or endaural approach |
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41533-01 | Myringoplasty with atticotomy |
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41542-00 | Myringoplasty with ossicular chain reconstruction |
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41551-00 | Mastoidectomy by intact canal wall technique with myringoplasty |
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41554-00 | Mastoidectomy by intact canal wall technique with myringoplasty and ossicular chain reconstruction |
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41560-00 | Modified radical mastoidectomy with myringoplasty |
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41560-01 | Radical mastoidectomy with myringoplasty |
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41563-00 | Modified radical mastoidectomy with myringoplasty and ossicular chain reconstruction |
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41563-01 | Radical mastoidectomy with myringoplasty and ossicular chain reconstruction |
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41626-00 | Myringotomy, unilateral |
|
41626-01 | Myringotomy, bilateral |
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41632-00 | Myringotomy with insertion of tube, unilateral |
|
41632-01 | Myringotomy with insertion of tube, bilateral |
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41635-01 | Excision of lesion of middle ear with myringoplasty |
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41638-01 | Excision of lesion of middle ear with myringoplasty and ossicular chain reconstruction |
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41789-00 | Tonsillectomy without adenoidectomy |
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41789-01 | Tonsillectomy with adenoidectomy |
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41801-00 | Adenoidectomy without tonsillectomy |
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90114-00 | Other procedures on eardrum or middle ear |
aInternational Classification, 10th Revision-Australian Modification.
For this study, the term “hearing loss” (HL) is used for a single ear to refer to a certain degree of loss of hearing ability, whereas “hearing impairment” (HI) is used for an individual’s state of hearing loss in both ears. The dependent variables used across all component studies will be HI, and its values will be derived from the hearing assessment data contained in the RHA dataset. It will be an ordinal variable comprising the following categories:
Normal hearing: normal audiometry results in both ears.
Unilateral hearing loss: normal in one ear and any degree of hearing loss in the other.
Mild HI: mild hearing loss in the better hearing ear.
Moderate-or-worse HI: moderate-or-worse hearing loss in the better hearing ear.
Although OM tends to develop early in life in NT Aboriginal children and be persistent and often asymptomatic [
This study aimed to investigate the impact of HI on the 5 aspects of life-course trajectory, listed in the following sections.
The Australian Early Development Census (AEDC) is a cross-sectional national census of all children at the time of school entry, and it has been conducted triennially since 2009 [
Data on the outcomes of early childhood development will be accessed from the AEDC dataset, one of the linked administrative datasets used in this study. The AEDC data available for this study contain data from the censuses held in 2009, 2012, and 2015. The first type of outcome variables is directly available in the AEDC dataset and are the dichotomous results of developmental vulnerability for individual domains and the summary measure of
The second type of outcome variables is the domain scores, which are continuous variables. These outcome measures will be used because of the fact that a high proportion of children in our study cohort have been assessed as
The outcome measure for this component will be children’s annual school attendance rate for Year 1 (aged approximately 6-7 years). Year 1 is chosen, as it is the first year of compulsory school attendance in the NT and as, in the study population, school attendance rates decrease with increasing year level. The data source will be the School Attendance dataset, provided by the NT Department of Education, which contains records of enrollment and daily attendance status for students studying in NT Government schools for the period 2005 to 2016. The school attendance outcome will be expressed as the number of school days attended per year, with approximately 200 school days available per year.
The outcome measure for children’s academic performance in early years of primary school will be taken from the National Assessment Program–Literacy and Numeracy (NAPLAN) dataset. NAPLAN is an annual national assessment program, which commenced in 2008, and is undertaken by all students in Australia in years 3, 5, 7, and 9 (aged approximately 8, 10, 12, and 14 years, respectively) [
The data source for this study is the NT Government Child Protection dataset, which is a statutory data collection of child maltreatment—related contacts with child protection services. The research dataset will include information on all notifications (reports), substantiated cases, and episodes of out-of-home care. The outcome measures for this study will be the cumulative incidence of first notification of child maltreatment and the cumulative incidence of first substantiated case of child maltreatment. The time to event will be calculated from date of birth to the earliest of the following: date of each event of interest, date of death, the last observed date in the linked datasets, or the designated end of follow-up date for the study. Data are available from 1999 to 2017.
The Youth Justice dataset was provided by the NT Department of the Attorney-General and Justice, and this contains records of youth offending in the NT. The outcome measure for this study will be the cumulative incidence of first episode of a proven guilty offence within the youth justice system. The starting point for follow-up will be the 10th birthday, which is the minimum legal age of criminal responsibility, and the follow-up time will be calculated to the date of first offence or censored at the date of death, the last observed date in the linked datasets, or the set endpoint for follow-up of this study. Data are available for the period 1997 to 2017.
The selection of control variables will vary between studies and the availability of the relevant variables in the linked datasets. We will draw reference from published literature in selecting control variables known to have confounding or moderating effects on the association being investigated. Individual-level control variables will be retrieved from the linked health, education, child protection, and justice datasets, including maternal and perinatal factors from the Perinatal Registry dataset (a statutory collection containing information for all births in the NT), as well as hospital admission diagnoses from the NT Hospital Separation Dataset. Community-level factors will include relative level of geographic remoteness (as measured with ARIA+), housing crowdedness (as measured with average household size and average persons per bedroom in the community), and socioeconomic disadvantage (as measured with the Index of Relative Socio-Economic Disadvantage) [
For each component study, statistical analyses will start with descriptive statistics to examine the distribution of key demographic, control, predictor, and outcome variables in the study cohort. The approach of complete-case analysis will be adopted in regression analysis. As this approach may lead to exclusion of participants with missing data, we will include comparisons of the study cohort and those excluded from analysis using suitable statistical methods (z-test,
The dependent variable, HI, is structured as an ordinal variable, and we anticipate a
The study investigating the impact on AEDC outcomes will use logistic regression for dichotomous outcomes and linear regression on continuous ones. In the studies investigating the impact of HI on Year 1 attendance rates and NAPLAN results, multivariate linear regression models will be fitted to estimate the association between HI and the school-based outcome measures, and the models will include school-fixed effects to control for the average observed and unobserved differences in schools and students of the schools. In the studies examining the association between HI and child maltreatment and between HI and youth offending, multivariate survival analysis will be used by fitting Cox proportional hazard models.
In these component studies, a parsimonious model building strategy will be adopted in the regression modeling process. Univariate regression analysis will first be carried out to select variables with
The final part of the study will investigate the interplay of key early childhood factors known to be associated with youth offending. It will examine how and to what extent the outcome of youth offending in NT Aboriginal children is shaped by the health, developmental, educational, and social factors investigated in this study, including HI, AEDC outcomes, Year 1 attendance rates, Year 3 NAPLAN results, and child maltreatment. The analysis will also examine the influence from key demographic factors relevant to children’s family and school learning circumstances. Structural equation modeling (SEM), using path analysis methods, will be utilized to quantify the relative impact of these factors on the outcome of youth offending. Distributional assumptions will be assessed to identify any outliners. The model will examine the direct pathway through which HI is associated with youth offending; it will also include the indirect pathways by which AEDC outcomes, Year 1 school attendance, and Year 3 NAPLAN results act as mediators in the direct pathway. In the SEM analysis, the
The study commenced in 2018. Ethics clearance and data custodian approvals for data access and linkage have been obtained. This has enabled the completion of data linkage and the commencement of data analysis for individual component studies. Findings are expected to be submitted for publication in peer-reviewed journals in 2019 and 2020.
The availability of the RHA dataset for data linkage with a wide range of health, education, child protection, and youth justice datasets has provided an unprecedented opportunity for investigating the impact of HI on life-course trajectory of Aboriginal children and young people. The hearing assessment results obtained through pure tone audiometry for a large cohort of remote-dwelling Aboriginal children have enabled the direct use of HI as the predictor variable in this study, instead of using its precursor or causative condition, OM, which may introduce an unknown level of misclassification. It is expected that this study will provide the first comprehensive evidence for the impact of HI on these various measures of the life-course trajectory in the study population. Furthermore, the comparatively large sample and the use of raw test scores of AEDC and NAPLAN as continuous variables will provide a robust statistical power, which will increase the likelihood of detecting significant association with the selected outcomes. In each of the component studies, we will discuss sources of potential bias. One example is that children included in the RHA database are not a random sample of remote Aboriginal children in the NT, with a risk of selection bias. A second source of potential bias is the use of complete-case analysis. We will also discuss the likely direction of potential bias and the extent to which they may affect the validity of our results.
The findings of this study will have significant implications for government departments and health and social service providers in policy development, service design, and resource allocation. The results can also be used as baseline measurements for monitoring interventions aimed at improving the ear and hearing health of Aboriginal children, as well as their developmental, educational, and social outcomes. The use of a linked administrative dataset in this study will further illustrate the utility of data linkage research methods for informing comprehensive service planning and evaluation.
Australian Early Development Census
acute otitis media
Accessibility and Remoteness Index of Australia
chronic suppurative otitis media
decibels hearing level
Hearing Loss in Kids
hearing impairment
National Assessment Program–Literacy and Numeracy
Northern Territory
otitis media
otitis media with effusion
Remote Hearing Assessment
South Australia
structural equation modeling
This study was funded by the Australian Department of Prime Minister and Cabinet through the Linking NT and Australian Government (LiNTAG) Project. The authors would like to acknowledge the support of the NT Departments of Health, Education, Territory Families, and Justice through the Child Youth and Development Research Partnership (CYDRP). The authors would also like to thank the many data custodians and the staff of the SA NT DataLink for their assistance in the linkage and supply of the research datasets. The views expressed in this publication are those of the authors and are not necessarily those of the government departments that have supported the study.
JYS, SS, and SG initiated the conception and design of the study. JYS and VH prepared the statistical analysis plan. All authors have contributed to the design of each component study, and they have participated in the writing of the paper and given approval for its publication.
None declared.