School of Psychiatry

The NSW Child Development Study (NSW-CDS):

Using the 2009 Australian Early Development Census

with record linkage to identify risk and protective

factors for adolescent mental health outcomes

Vaughan Carr, Alessandra Raudino, Enwu Liu, Melissa Green,

Kristin Laurens, Sally Brinkman, Rhoshel Lenroot, Felicity

Harris, Luming Juo

A 15-20 year project to identify early

childhood vulnerability and protective

factors for several health, social and

wellbeing outcomes in adolescence and

young adulthood.

AIMS: To help inform policy changes and

early intervention & prevention programs

NSW-Child Development Study

[Record Linkage Research]

• Multi-agency (administrative databases)

• Multi-generational (child and parents)

• Longitudinal (repeated waves of record linkage)

• Phase 1: Two sequential record linkages (age 0-5; 0-

11)

• Phase 2: Record linkage for adolescent outcomes

(age: 0-16)

• Incorporating data from surveys:

• Teacher-reported (AEDC) @ age ~5yr (2009)

• Self-reported (MCS) @ age ~11yr (2015)

Datasets included in Phase 1 of the study

Datasets included in Phase 1 of the study

Record linkage 1 datasets:

Health Records Perinatal (Midwives) Data Collection

(NSW Ministry of Health)

Registry of Births, Deaths, and Marriages – Births and Deaths (Australian Bureau of Statistics)

ABS Mortality Data Collection (Australian Bureau of Statistics)

Emergency Department Data Collection (NSW Ministry of Health)

Admitted Patient Data Collection (NSW Ministry of Health)

Mental Health Ambulatory Data Collection (NSW Ministry of Health)

Education Records

– Australian Early Development Census (Commonwealth Department of Education, Employment, & Workplace Relations)

– Best Start Kindergarten Assessment (NSW Department of Education and Communities)

Community Services Records

Child Protection, Out of Home Care, and Brighter Futures Data Collections (NSW Department of Family & Community Services)

Crime Statistics

BOCSAR (Bureau of Crime Statistics and Research)

Datasets included in Phase 1 of the study

Datasets included in Phase 1 of the study

Record linkage 1 datasets:

Health Records

Perinatal (Midwives) Data Collection

Registry of Births, Deaths, and Marriages – Births and Deaths

ABS Mortality Data Collection

Emergency Department Data Collection

Admitted Patient Data Collection

Mental Health Ambulatory Data Collection

Education Records

• Best Start Kindergarten Assessment

Child Development Records

• Australian Early

Development Census

(Kindergarten)

Crime Statistics Records

BOCSAR Reoffending

Community Services Records

Case Management System Child Protection Out of Home Care Early Intervention Programs:

Brighter Futures

Record linkage 2 datasets:

Health Records

Perinatal (Midwives) Data Collection

Registry of Births, Deaths, and Marriages – Births and Deaths

ABS Mortality Data Collection

Emergency Department Data Collection

Admitted Patient Data Collection

Mental Health Ambulatory Data Collection

Mental Health Outcome and

Assessment Toolkit

Pharmaceutical Drugs of Addiction

Subsystem

Education Records • Best Start Kindergarten

Assessment

• NAPLAN (Grade 3 and 5)

• Suspensions and Expulsions

• Student Enrolment Records

• *Survey of School Promotion of Emotional and Social Health

Child Development Records

• Australian Early

Development Census

(Kindergarten)

• *NSW-CDS Middle

Childhood Survey (Grade 6)

Crime Statistics Records

BOCSAR Reoffending

Community Services Records

Case Management System Child Protection Out of Home Care Early Intervention Programs:

Brighter Futures and Strengthening Families

Putting the AEDC data to use:

The impact of childhood infection on

developmental vulnerability

Infectious Diseases and their Sequelae

• Maternal prenatal infections and adult psychosis

(esp. SZ) in offspring.

• Childhood infections and later illness & disability:

• Behavioural problems, poor cognitive functioning

• Autism, learning difficulties

• Asthma, eczema, allergies

• Adult anxiety, depression, schizophrenia, affective

psychosis

• Adult SZ: increased rates of auto-immune diseases

and inflammatory markers

• Research Question: What are the effects of

infections on psychosocial development (AEDI)?

AEDC DOMAINS Emotional maturity

-Pro-social & helping, anxious/fearful, aggressive, hyperactive and inattentive behaviours;

Social competence

-Overall social competence, approaches to learning, readiness to explore new things, responsibility and respect;

Physical health and wellbeing

-Physical readiness for school, physical independence, gross and fine motor skills;

Language and cognitive skills

-Basic and advanced literacy and numeracy, interest in literacy/numeracy, and memory;

Communication and general knowledge

-Proficiency in understanding and listening.

Selected domain descriptives from the NSW AEDC dataset (n= 87 026)

Percentiles based on National AEDC data, i.e. created on basis of all children who participated in the AEDC nationally.

Developmentally vulnerable

Developmentally at risk

On track

Domain <10th percentile (%)

10th-25th percentile (%)

25th-50th percentile (%)

>50th percentile (%)

Physical health and wellbeing 8.6 12.9 21.3 57.2

Social competence 8.8 14.0 23.0 54.2

Emotional maturity 7.4 14.3 24.7 53.6

Language and cognition 5.9 9.5 19.4 65.2

Communication skills and general knowledge

9.2 15.8 19.2 55.9

Method

• All children selected had a Perinatal record and an APDC

record up to age 4yr

• Cases = Children defined as developmentally vulnerable

(i.e., <10th percentile on a given AEDC domain) at age 5yr

• Controls = Children defined as NOT developmentally

vulnerable (i.e., >10th percentile on a given AEDC domain)

• Controls matched to cases on age, ESL and SEIFA; 3

controls for each case

• Exposure = hospital admission >24hr for infectious disease

(number of days hospitalised was recorded)

Method

• Confounds:

• Perinatal (birth weight; maternal: age, smoking during

pregnancy, gestational diabetes, diabetes mellitus, hyper-

tension, pre-eclampsia)

• FaCS record of abuse or neglect

• Sex

• Admission to hospital for non-infectious disease

• Data analysis:

• Conditional logistic regressions

Results

Admissions AEDI

Emotional Maturity

AEDI

Language & Cognition

UOR AOR P UOR AOR P

Any Infection 1.7 1.4 <.0001 1.9 1.5 <.0001

Viral 1.7 1.4 .0007 1.8 1.3 .002

Bacterial 1.5 1.3 .1205 1.8 1.5 .0129

Other 1.6 1.3 .001 1.8 1.5 <.0001

Non-CNS 1.7 1.4 <.0001 1.9 1.4 <.0001

CNS - - - - - -

Similar patterns for Social Competence, Communication & General Knowledge,

and Physical Health & Wellbeing

Conclusions

• Risk of developmental psychological vulnerability on

school entry is increased in children admitted to hospital

with infectious diseases

• There is a dose-response relationship with probability of

psychological vulnerability increasing with number of

days spent in hospital

Thank you

Dr. Stacy Tsoumakis

Dr. Maina Kariuki

A/Prof. Kimberlie Dean

Ms. Stephanie Dick

Ms Brooke McIntyre

Mr Philip Hull

and all the NSW-CDS study partners and collaborators