Exploring outcomes for children who have experienced out-of-home care in Western Australia.

Abstract

Introduction
Children who have been in out-of-home care have faced significant issues during their lives, and they are considered one of the most vulnerable groups in society. Given the limited evidence in Western Australia about outcomes for care-leavers, this study represents a base line for future studies of care-leavers outcomes.

Objectives and Approach
A retrospective cohort study exploring the outcomes for young people born between 1990-1995, who have reached at least 18 years of age and have had a period of care, compared to other similar children in WA. This project used administrative linked data from the Department of Communities Child Protection and Family Support Division, Departments of Health, Education, and Corrective Services. This study undertook a descriptive approach to compare outcomes for young people who have left out-of-home care, and logistic regression modelling to explore the odds of having poorer outcomes among those who had a period in care.

Results
Young people aged 18 years and over who had been in out-of-home care had worse outcomes compared to controls. Care-leavers had nearly twice the hospital admission rate of those who never had contact with the child protection system, almost three times more likely to have a mental health related contact, less likely to achieve a high school completion certificate and attend University, and more likely to have a juvenile community sentence or adult detention.

A group of young people who had a period in care were identified as more likely to have ‘poorer outcomes’ compared to the rest of the Care group if they: were Aboriginal; female; born in a more disadvantaged area; and first entered care after the age of 10.

Conclusion/Implications
Young people who have been in care are at high risk of a range of poor outcomes, even compared to other children who have experienced similar disadvantage. Regardless of the causes, it is incumbent upon the State as acting ‘parents’ to provide the best possible support to improve their outcomes.

Introduction

The cancer burden preventable through modifications to risk factors can be quantified by calculating their population attributable fractions (PAFs). PAF estimates require large, prospective data to inform risk estimates and contemporary population-based prevalence data to inform the current exposure distributions, including among population subgroups.

Objectives and Approach

We provide estimates of the preventable future cancer burden in Australia using large linked datasets. We pooled data from seven Australian cohort studies (N=367,058) and linked them to national registries to identify cancers and deaths. We estimated the strength of the associations between behaviours and cancer risk using a proportional hazards model, adjusting for age, sex, study and other behaviours. Exposure prevalence was estimated from contemporary National Health Surveys. We harmonised risk factor data across the data sources, and calculated PAFs and their 95% confidence intervals using a novel method accounting for competing risk of death and risk factor interdependence.

Results

During the first 10-years follow-up, there were 3,471 incident colorectal cancers, 640 premenopausal and 2,632 postmenopausal breast cancers, 2,025 lung cancers and 22,078 deaths. The leading preventable causes were current smoking (53.7% of lung cancers), body fatness or BMI \(\geq\) 25kg/m2 (11.1% of colorectal cancers, 10.9% of postmenopausal breast cancers), and regular alcohol consumption (12.2% of premenopausal breast cancers). Three in five lung cancers, but only one in four colorectal cancers and one in five breast cancers, were attributable to modifiable factors, when we also considered physical inactivity, dietary and hormonal factors. The burden attributable to modifiable factors was markedly higher in certain population subgroups, including men (colorectal, lung), people with risk factor clustering (colorectal, breast, lung), and individuals with low educational attainment (breast, lung).

Conclusion/Implications

Estimating PAFs for modifiable risk factors across cancers using contemporary exposure prevalence data can inform timely public health action to improve health and health equity. Testing PAF effect modification may identify population subgroups with the most to gain from programs that support behaviour change and early detection.