Notes to figures and tables
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Introduction
Figures 2 and 3: For 2015 data, the Queensland Registry of Births, Deaths and Marriages included Medical Certificate of Cause of Death information for the first time to contribute to the Indigenous status data item. This was associated with a decrease in the number of deaths for which the Indigenous status was ‘not stated’ and an increase in the number of deaths identified as Indigenous in Queensland. Although the Indigenous child mortality rate was higher in Queensland in 2015, for New South Wales, Western Australia and South Australia the rates were lower in 2015 than in 2014. This change in method means that time series data for Queensland are not directly comparable and caution should be used in interpreting the trend.
Figures 20, 21 and 22: Indigenous Region and Indigenous Area are based on the ABS’ 2011 Australian Standard Geography Standard (ASGS): Volume 2 – Indigenous Structure.
Tier 1 Health Status and Outcomes
1.01 Low birthweight
Data on birthweight is collected as part of the Perinatal National Minimum Data Set. Low birthweight data are reported for live births of 20 weeks’ gestation or more and less than 400 grams’ birthweight. Low birthweight is defined as less than 2,500 grams. Data excludes babies with unknown birthweight. Unless otherwise stated, Indigenous and non-Indigenous data exclude births where the mother’s or babies’ Indigenous status is not stated. Data excludes Australian non-residents, residents of external territories and records where state/territory of residence was not stated.
Figure 1.01-1: Data are by place of usual residence of the mother. Excludes non-residents, external territories and not stated state/territory of residence. Time series rates are calculated for low birthweight singleton babies (as inclusion of multiple births in trend analysis could confound results) and are presented for single years from 2000 to 2014.
Figure 1.01-2: Data are by place of usual residence of the mother. Excludes non-residents, external territories and not stated state/territory of residence. Includes all live-born low birthweight babies.
Figure 1.01-3: Data are presented by age of mother. Indigenous and non-Indigenous data exclude women with not stated age/date of birth. Includes all live-born low birthweight babies.
Figure 1.01-4: Data are presented by remoteness category. Indigenous and non-Indigenous data exclude women with a not stated state/territory of residence. Includes all live-born low birthweight babies.
1.02 Top reasons for hospitalisation
Data for this measure come from the AIHW’s analysis of the National Hospital Morbidity Database. Data are from public and most private hospitals in all jurisdictions. Care types 7.3, 9 & 10 (Newborn—unqualified days only; organ procurement; hospital boarder) have been excluded from analysis.
Rates have been directly age‑standardised using the 2001 Australian standard population. Rates for Indigenous Australians are calculated using backcast population estimates and projections (Series B) based on the 2011 Census.
Categories are based on the ICD-10-AM eighth edition (National Centre for Classification in Health 2013). Data related to principal diagnosis are reported by state/territory of usual residence of the patient hospitalised. Unless otherwise stated, hospital separations for dialysis are excluded from the analysis.
For total separations at a national level, the jurisdictions’ hospitalisation numbers and rates have been adjusted for Indigenous under-identification using a national adjustment factor of 1.09. This factor was derived from a study undertaken by the AIHW in 2011 and 2012 which assessed the level of Indigenous under-identification in hospital data in all states and territories by comparing information gathered from face-to face interviews in public hospitals with results from hospital records. By applying this factor, the number of Indigenous hospitalisations was increased by 9% and these additional hospitalisations were then subtracted from the number of hospitalisations for non-Indigenous Australians. For further information, see AIHW, 2013. This adjustment factor cannot be applied to separations presented by cause as identification may vary by principal diagnosis.
Current period data are presented from July 2013 to June 2015. Data are combined for two years due to small numbers when disaggregating separation data (e.g. by principal diagnoses, age or jurisdiction).
For jurisdictional breakdowns age-standardised rates for NSW, Vic, Qld, WA, SA, the NT and Australia have been calculated using the direct method, age-standardised by 5-year age groups to 75+ years. Age-standardised rates for Tasmania and the ACT have been calculated using the direct method, age-standardised by 5-year age group to 65+. As different age-groupings were used, caution must be used when comparing rates for Tasmania and the ACT, with rates for NSW, Vic, Qld, WA, SA, the NT and Australia.
Time series rates are age-standardised using the 2001 standard population and are presented for single years. Long-term trends are reported from 2004–05 to 2014–15 and include NSW, Victoria, Qld, WA, SA and the NT combined. The jurisdictions included differ between trends due to historical data quality issues.
Remoteness area is based on the ABS’ 2011 Australian Statistical Geography Standard (ASGS) and relates to the patient’s usual residence. Total includes hospitalisations where remoteness area of residence is unknown. Rates by remoteness are calculated using AIHW derived populations using ABS population estimates and projections based on the 2011 Census.
Figure 1.02-3: ‘Other’ includes: diseases of the musculoskeletal system and connective tissue; neoplasms; diseases of the nervous system; certain conditions originating in the perinatal period; diseases of the ear and mastoid process; diseases of the eye and adnexa; diseases of the blood and blood-forming organs and certain disorders involving the immune system; congenital malformations, deformations and chromosomal abnormalities; and factors influencing health status and contact with health services (except dialysis).
1.03 Injury and poisoning
Data for this measure come from the AIHW’s analysis of the National Hospital Morbidity Database. Refer to notes for measure 1.02 regarding these data. Cause of injury is based on the first reported external causes where the principle diagnosis was injury, poisoning and certain other consequences of external causes (ICD-10-AM codes S00-T98).
Table 1.03.1: ‘Other accidental exposures’ includes: exposure to electrical current, radiation and extreme ambient air temperature and pressure (W85–W99), smoke, fire and flames (X00–X09), contact with heat and hot substances (X10–X19), contact with venomous animals and plants (X20–X29), exposure to forces of nature (X30–X39). ‘Other external causes’ includes: event of undetermined intent (Y10–Y34), legal intervention and operation of war (Y35–Y36), sequelae of external causes of morbidity and mortality (Y85–Y89), supplementary factors classified elsewhere (Y90–Y98).
Figure 1.03-4: Data are reported by state/territory of usual residence of the patient hospitalised. Age-standardised rates for NSW, Vic, Qld, WA, SA, the NT and Australia have been calculated using the direct method, age-standardised by 5-year age groups to 75+. Age-standardised rates for Tasmania and the ACT have been calculated using the direct method, age-standardised by 5-year age group to 65+. As different age-groupings were used, rates for Tasmania and the ACT cannot be compared with the rates for NSW, Vic, Qld, WA, SA, the NT and Australia. In addition, rates for the ACT and Tasmania will fluctuate from year to year due to small number of hospitalisations for some conditions and should therefore be interpreted with caution.
1.04 Respiratory disease
Data for this measure mainly come from the ABS and AIHW analysis of 2012–13 AATSIHS and the AIHW’s analysis of the National Hospital Morbidity Database. Refer to notes for measure 1.02 regarding these data. Exceptions are noted below. Categories are based on the ICD-10-AM eighth edition (ICD-10-AM codes J00–J99).
For this measure data from the 2012–13 AATSIHS was used rather than the 2014–15 NATSISS, in which long-term health condition data were only collected in a short module, and as such, are not considered to be the best estimates of prevalence for long-term health conditions.
Figure 1.04-1: ‘Outer regional’ includes remote Victoria. ‘Remote’ excludes remote Victoria. Remoteness area is based on the ABS’ 2011 Australian Statistical Geography Standard ASGS and relates to the patient’s usual residence. Rates by remoteness are calculated using AIHW derived populations using ABS population estimates and projections (Series B) based on the 2011 Census.
Figure 1.04-3: Rates for NSW, Vic, Qld, WA, SA and the NT have been age-standardised by 5-year age groups to 75+. Age-standardised rates for Tasmania and the ACT have been calculated by 5-year age groups to 65+. Comparisons between jurisdictions should therefore be interpreted with caution.
Figure 1.04-4 includes a non-Indigenous comparison between the AHS collected in 2011–12 and the AATSIHS collected in 2012–13.
Figures 1.04-5 and 1.04-6: Mortality data are derived from the ABS National Mortality Database. See technical appendix entry for measure 1.22 for more information.
1.05 Circulatory disease
Data for this measure come from the ABS and AIHW analysis of 2012–13 AATSIHS, AIHW’s analysis of the National Hospital Morbidity Database, and ABS and AIHW analysis of the National Mortality Database. Refer to notes for measure 1.02 regarding hospitalisation data and notes for measure 1.22 and 1.23 regarding mortality data.
Data from the 2012–13 AATSIHS was used as it was measured through blood pressure tests rather than relying on diagnosed self-reported conditions as in the 2014-15 NATSISS.
Categories for hospitalisations and mortality are based on the ICD-10-AM eighth edition (National Centre for Classification in Health 2013): ICD-10-AM codes I00–I99.
Figure 1.05-1 and 1.05-2: Data reported in these figures is for people who reported having a current heart/circulatory problem which has lasted, or is expected to last, for 6 months or more. Data is from the AATSIHS core sample, which consists of the NATSIHS and NATSINPAS.
Figure 1.05-2 includes a non-Indigenous comparison between the AHS collected in 2011-2012 and the AATSIHS collected in 2012-13.
1.06 Acute rheumatic fever and rheumatic heart disease
Data for this measure come from the NT, Qld, WA and SA Rheumatic Heart Disease Control Program registers. Data from the SA register are only recently available and subject to some limitations, including no breakdowns available by age or sex. The NT RHD register has been operating in the Top End since 1997 and in Central Australia since 2001 and currently provides the strongest source of data on ARF and RHD. Comparisons between jurisdictions should not be made given registers are at different stages of coverage and completion. Indigenous status unknown is included in non-Indigenous numbers and rates. Crude rates per 1,000 for NT, Qld and WA are calculated using the total number of registrations for 2011–15 divided by the summed 30 June 2011, 2012, 2013, 2014 and 2015 populations based on the 2011 Census (series B estimates and projections). For SA, crude rates per 1,000 are calculated using the total number of registrations for 2013–15 divided by the summed 20 June 2013, 2014 and 2015 populations.
Figure 1.06-2: Hospitalisations with a principal diagnosis of acute rheumatic fever (I00–I02) or rheumatic heart disease (I05–I09).
1.07 High blood pressure
The majority of the data in this measure is from the 2012–13 AATSIHS. This survey collected both measured blood pressure and self-reported blood pressure. The total prevalence of high blood pressure is the total people who reported having high blood pressure/hypertension (regardless of measured blood pressure) plus people who did not report having high blood pressure/hypertension but who had a measured blood pressure of 140/90 mmHg or above. The denominators used in calculating prevalence rates exclude those persons who did not report having high blood pressure/hypertension whose blood pressure was not measured.
Data from the 2012–13 AATSIHS was used as it was measured through blood pressure tests rather than relying on diagnosed self-reported conditions as in the 2014–15 NATSISS.
Refer to notes for measure 1.02 for information on hospitalisation data. ICD-10-AM codes I10–I15.
Figure 1.07-2: This figure presents the percentage Indigenous adults with a measured blood pressure of 140/90 mmHg or above (the number above each bar), and splits this into the percentage of those who reported having high blood pressure and those that did not.
Figure 1.07-3: This figure presents age-specific rates of those who had measured blood pressure of 140/90 mmHg or above and does not include self-report data. Total is age-standardised.
Figure 1.07-3 includes a non-Indigenous comparison between the AHS collected in 2011–12 and the AATSIHS collected in 2012–13.
1.08 Cancer
Data for this measure come from the AIHW Australian Cancer Database and from ABS and AIHW analysis of the National Mortality Database. For information on the National Mortality Database, see notes for measure 1.22 and 1.23. For the AIHW Australian Cancer Database, data are reported for NSW, Vic, Qld, WA and the NT only. These five states and territories are currently considered to have adequate levels of Indigenous identification in cancer registry data for these periods. Data are presented in five-year groupings because of small numbers each year. Victorian data are of suitable quality from 2008 onwards so are only included for these years. The other four states and territories are included for all the years presented.
Figure 1.08-1: ICD-10 Codes for malignant neoplasms (cancer) include: C00–C97, D45, D46, D47.1, D47.3. Other malignant neoplasms include neoplasms of bone and articular cartilage (C40–C41); melanoma & other neoplasms of skin (C43–C44); neoplasms of mesothelial and soft tissue (C45–C49); neoplasms of eye, brain and other parts of central nervous system (C69–C72); neoplasms of thyroid and other endocrine glands (C73–C75); malignant neoplasms of independent (primary) multiple sites (C97).
Figure 1.08-2: Refer to notes for measure 1.22 for information on mortality time series data.
Figures 1.08-3 and 1.08-4: Results reported in this table may differ from those in jurisdictional reports because the underlying data may have been extracted from the master databases at different times. Jurisdictional results reported in these figures may be affected by variations in self-reported Indigenous status. Incidence rates are directly age-standardised using the 2001 Australian Standard Population, by 5 year age group to 75+.
Figure 1.08-6: The 5-year crude survival rate is the percentage of people who are still alive 5 years after their cancer diagnosis. The rates were calculated by the period method using the period 2004–12.
1.09 Diabetes
Data for this measure come from the 2012–13 AATSIHS and the 2014–15 National Hospital Morbidity Database. Data from the 2012–13 AATSIHS was used as it was measured through blood tests rather than relying on diagnosed self-reported conditions as in the 2014–15 NATSISS.
Figure 1.09-3 includes a non-Indigenous comparison between the AHS collected in 2011–12 and the AATSIHS collected in 2012–13.
1.10 Kidney disease
The key data for this measure come from the Australian and New Zealand Dialysis and Transplant Registry. Indigenous identification in the Registry is based on self-identification in hospital records. However, because of the heightened awareness of the extent of renal disease in Aboriginal and Torres Strait Islander peoples and the prolonged and repeated contact with renal units in hospitals, it is believed that Indigenous identification in the Registry is more complete than in general hospital data. Uses calendar year reporting. Total rates are directly age-standardised using the Australian 2001 standard population. Age-standardised rates have been calculated using the direct method, age-standardised by 5-year age groups to 65 years and over (except for time series which use 5-year age groups to 75 years and over). Data are presented in 3-year groupings because of small numbers each year, except for time series in which single years are reported.
1.11 Oral health
Data for this measure come from the 2012–13 AATSIHS, 2014–15 NATISS, the National Hospital Morbidity Database and the 2010 Child Dental Health Survey.
Figure 1.11-1: Data are from the 2012–13 AATSIHS. Self-reported data, consisting of persons reporting whether they have lost any of their adult teeth (excluding wisdom teeth), and if so, how many. ‘Complete tooth loss’ is comprised of persons who responded they have lost all of their adult teeth. ‘Loss of one or more teeth’ doesn’t include complete tooth loss. Excludes not stated responses.
Figure 1.11-2: Refer to notes for measure 1.02 for information on hospitalisation data. Dental problem categories are based on ICD-10-AM codes K02, K81, Z012. Data includes public and private hospitals in all jurisdictions. Data are directly age-standardised using the Australian 2001 standard population. Rates calculated based on 2011 Census. Excludes separations with care types 7.3, 9 and 10.
Figures 1.11-3 and 1.11-4: Data are from the 2010 Child Dental Health Survey. Data are for NT, Qld, SA, Tas, WA and ACT. Data for NSW and Vic not available.
1.12 HIV/AIDS, hepatitis and sexually transmissible infections
Data for this measure (except for HIV/AIDS data) come from the National Notifiable Disease Surveillance System. A major limitation of the notification data is that, for most diseases, they represent only a proportion of the total cases occurring in the community, that is, only those cases for which health care was sought, a test conducted and a diagnosis made, followed by a notification to health authorities. The degree of under‑representation of all cases is unknown and is most likely variable by disease and jurisdiction. ‘Diagnosis date’ was used to define the period of analysis. This date represents either the onset date or where the date of onset was not known, the earliest of the specimen collection date, the notification date, or the notification received date. In interpreting these data, it is important to note that changes in notifications over time may not solely reflect changes in disease prevalence or incidence. Changes in testing policies; screening programmes, including the preferential testing of high risk populations; the use of less invasive and more sensitive diagnostic tests; and periodic awareness campaigns may influence the number of notifications that occur over time. Rates have been directly age-standardised using the Australian 2001 standard population using 5-year age groups up to age 65+. Uses calendar year reporting. Data are presented in two-year or three-year groupings due to small numbers each year. ‘Other Australians’ includes notifications for non-Indigenous Australians and those for whom Indigenous status was not stated.
Not all notifications of chlamydial infection, gonococcal infection, and syphilis are sexually acquired. The national case definitions for these infections do not specifically distinguish between sites of infection or modes of transmission.
Figure 1.12-1: The supplied data for Chlamydia for NT is for genital infections only. From 1 July 2013, the national case definition for Chlamydia excludes ocular infections. Hepatitis C data includes ‘newly acquired’ and ‘unspecified’ infections identified under two disease codes ‘040’ and ‘053’. Hepatitis B data includes ‘newly acquired’ and ‘unspecified’ infections identified under two disease codes ‘039’ and ‘052’. Hepatitis B data is presented from 2007–09—prior to 2005 data is considered insufficient quality for reporting.
Figure 1.12-2: Data are from the National HIV Registry. Data are presented in three‑year groupings because of small numbers each year. Rates have been directly age-standardised using the 2001 Australian population.
Figure 1.12-3: Chlamydia data are reported for Qld, WA, SA and the NT. Gonorrhoea data are reported for Victoria, Qld, WA, SA, the NT, Tasmania and the ACT. These jurisdictions are considered to have adequate levels (>50% identification) of Indigenous identification in the respective data. They do not represent a quasi-Australian figure.
Figure 1.12-4: Hepatitis B data are reported for WA, SA, the NT, the ACT and Tasmania and includes ‘newly acquired’ and ‘unspecified’ infections identified under two disease codes (‘039’ and ‘052’). Hepatitis C data are reported for WA, SA, the NT and Tasmania (>50% identification) and includes ‘newly acquired’ and ‘unspecified’ infections identified under two disease codes (‘040’ and ‘053).
1.13 Community functioning
Data for this measure come from the 2002, 2008 and 2014–15 NATSISS.
Table 1.13-1: Unless otherwise indicated percentages are of the estimated total Aboriginal and Torres Strait Islander population aged 15 years and over. Note that for some data items the HPF differs from the Overcoming Disadvantage Report due to the HPF excluding not stated responses from the denominator.
1.14 Disability
The key data for this measure come from the 2014–15 Social Survey, the 2012–13 Health Survey, and the 2011 Census. The Surveys collected data on a broad definition of disability (i.e. those reporting a limitation, restriction, impairment, disease or disorder that has lasted, or expected to last, for 6 months or more which restricts everyday activities). Results are self‑reported and therefore could be under-stated.
The 2011 Census collected data on one element of disability—those reporting the need for assistance with core activities. Results therefore may understate the proportion of people with a disability. The Census measure of ‘need for assistance with core activities’ is conceptually comparable to the SDAC measure of severe or profound core or activity limitation.
The 2014–15 Social Survey, 2012–13 Health Survey, 2011 Census and 2012 Survey of Disability, Ageing and Carers data provide prevalence rates while the Disability Services NMDS is service use rate.
Figure 1.14-1: Data for this figure come from the self‑reported data from the 2014–15 Social Survey. Totals are directly age-standardised.
Table 1.14-1: Note that more than one disability type may be reported and thus the sum of the components may add to more than the total.
1.15 Ear health
For this measure data from the 2012–13 AATSIHS was used rather than the 2014–15 NATSISS, in which long-term health condition data were only collected in a short module, and as such, are not considered to be the best estimates of prevalence for long-term health conditions.
For this measure, deafness comprises complete deafness, partial deafness and hearing loss not elsewhere classified.
Ear or hearing problems comprise diseases of the ear and mastoid including deafness, otitis media, other diseases of the middle ear and mastoid, Meniere’s disease, other diseases of the inner ear and other diseases of the ear.
Figure 1.15-1: Refer to notes for measure 1.02 for information on hospitalisation data. ICD-10-AM codes H60–H95.
Figure 1.15-2: Data come from the annually conducted Bettering the Evaluation And Care of Health (BEACH) survey (now discontinued). Data include five combined BEACH years April 2010–March 2011 to April 2014–March 2015 inclusive. Classified according to the International Classification of Primary Care (ICPC-2) codes: H00–H99—Acute otitis media/myringitis = H71; other ear infections = H70, H72, H73, H74; hearing loss = H28, H84, H85, H86; other diseases of the ear = H01–H27, H29–H69, H75–H83, H87–H99.
Table 1.15-1 includes non-Indigenous data from the 2011–12 AHS and Indigenous data from the 2012–13 AATSIHS.
1.16 Eye health
Data in this measure are mainly from self-reported data from the 2012–13 AATSIHS and from eye examinations from the 2016 National Eye Health survey.
For this measure adult data from the 2012–13 AATSIHS was used rather than the 2014–15 NATSISS, in which long-term health condition data were only collected in a short module, and as such, are not considered to be the best estimates of prevalence for long-term health conditions.
The National Eye Health survey was conducted from March 2015 to April 2016 by the Centre for Eye Research Australia and Vision 2020 Australia. The survey was designed to assess the prevalence of the main eye conditions causing vision loss including cataract, diabetic retinopathy, refractive error and trachoma/trichiasis, as well as the prevalence of glaucoma and age-related macular degeneration. This survey included a sample of 4,836 people in private dwellings across Australia, including 3,098 non-Indigenous Australians aged 40 years and over and 1,738 Indigenous Australians aged 50 years and over, across 30 geographic areas.
Additionally, data are used from the previously annually conducted GP survey (BEACH) (now ceased). Classified according to ICPC-2 chapter codes: F01–99. Data from five combined BEACH years April 2010–March 2011 to April 2014–March 2015 inclusive.
='Medicare data has also been explored in relation to eye health services for Indigenous Australians with diabetes. Medicare data are adjusted for under-identification of Indigenous Australians in the Voluntary Indigenous Identifier (VII) database. MBS data excludes eye examinations and procedures provided in the public health system or under other arrangements that do not attract an MBS claim (e.g. some AMS and state/territory health services) and MBS items for eye health services may be used for a range of conditions besides diabetes (and reasons are not reported). Additionally, there is no specific MBS item to identify all people with diabetes and the proxy measure used only captures those who claimed a specific diabetes test within a two-year period. For example, in 2013–15, an estimated 28,400 Indigenous Australians claimed the MBS diabetes test, which is lower than the AATSIHS 2012–13 estimate of 49,100 Indigenous Australians having diabetes.
Figure 1.16-1: Data come from the 2016 National Eye Health Survey by cause of bilateral vision impairment for Indigenous adults 40 years and over and non-Indigenous adults 50 years and over.
Figure 1.16-2: Data come from the 2016 National Eye Health Survey by bilateral vision impairment by remoteness for Indigenous adults 40 years and over and non-Indigenous adults 50 years and over.
Figure 1.16-3: Data come from the 2016 National Eye Health Survey for adherence rates to the National Health and Medical Research Council diabetic eye examination guidelines by Indigenous status and remoteness. Current NHMRC guidelines recommend a diabetic eye examination annually for Aboriginal or Torres Strait Islander persons with diabetes and at least every 2 years for non-Indigenous Australians with diabetes.
Figure 1.16-4: Data come from the National Trachoma Surveillance and Reporting Unit (NTSRU) and was collected from screening in remote Aboriginal communities during 2014 in the NT, SA, WA and NSW. Caution must be taken when interpreting trachoma prevalence as screening was undertaken in predominantly remote and very remote communities designated as being at risk of endemic trachoma.
1.17 Perceived health status
Data from this measure are based on self-report data from ABS and AIHW analysis of the 2014–15 NATSISS.
Figures 1.17-1, 1.17-2 data includes non-Indigenous data from the 2014–15 NHS and Indigenous data from the 2014–15 NATSISS.
Figure 1.17-4: Long-term health conditions is based on self-reported data consisting of persons reporting a current medical condition which has lasted, or is expected to last, for six months or more.
1.18 Social and emotional wellbeing
Data for this measure come from the 2014–15 NATSISS, AIHW’s analysis of the National Hospital Morbidity Database and ABS and AIHW analysis of the ABS National Mortality database.
Figure 1.18-1: Level of psychological distress is based on the Kessler-5 (K5) measure of psychological distress. Overall levels of distress are based on frequency responses to the following five questions about feelings in the last 4 weeks:
- About how often did you feel nervous?
- About how often did you feel without hope?
- About how often did you feel restless or jumpy?
- About how often did you feel everything was an effort?; and
- About how often did you feel so sad that nothing could cheer you up?
As per the standard approach to scoring K-6 and K-10 items, the five psychological distress items are then scored from 1 for ‘none of the time’ to 5 for ‘all of the time’. These scores are then summed, yielding a scale with a minimum score of 5 (where response was ‘none of the time’ to all five questions) and a maximum score of 25 (where response was ‘all of the time’ to all five questions). The data are usually presented as two dichotomous groups—‘low/moderate’ (scores of 5 to 11.9) and ‘high/very high’ (scores of 12.0 to 25).
Figure 1.18-1: includes non-Indigenous data from the 2011–12 AHS and Indigenous data from the 2012–13 AATSIHS.
Figure 1.18-4: See measure 1.22 for notes. ICD-10 codes: X60-X84, Y87.0
Figures 1.18-5 and 1.18-6: Categories are based on the ICD-10-AM eighth edition (National Centre for Classification in Health 2013) and previous editions: ICD-10-AM codes F00–F99, G30, G47.0, G47.1, G47.2, G47.8, G47,9, 099.3, R44, R45.0, R45.1, R45.4, R48, Z00.4, Z03.2, Z04.6, Z09.3, Z13.3, Z50.2, Z50.3, Z54.3, Z61.9, Z63.1, Z63.8, Z63.9, Z65.8, Z65.9, Z71.4, Z71.5, Z76.0. Refer to notes for measure 1.02 regarding hospital data.
1.19 Life expectancy at birth
Data for this measure is sourced from ABS Life Tables for Aboriginal and Torres Strait Islander Australians, 2010–12, Cat. no. 3302.0.55.003.
Life expectancy at birth is the average number of years that a group of newborn babies would be expected to live if current death rates remain unchanged. This is a modelled estimate and serves as a guide to the health of the population.
Almost all deaths in Australia are registered; however, the quality of Indigenous status in deaths data varies over time and between jurisdictions. The volatility of Indigenous status recording in the Census also contributes to uncertainty in population estimates. These data issues, together with the small size of the Indigenous population, have led to problems calculating accurate Indigenous life expectancy estimates. As a result of improvements in methods of addressing data quality issues, there have been different estimates of the gap in life expectancy over the last decade, including 20 years, 17 years and 10–12 years. The latest publication includes revised estimates for 2005–07 and for the first time a time series. For details of technical issues refer to the ABS publication.
1.20 Infant and child mortality
For 2015 mortality data, the Queensland Registry of Births, Deaths and Marriages included Medical Certificate of Cause of Death information for the first time to contribute to the Indigenous status data item. This was associated with a decrease in the number of deaths for which the Indigenous status was ‘not stated’ and an increase in the number of deaths identified as Indigenous in Queensland. Although the Indigenous child mortality rate was higher in Queensland in 2015, for New South Wales, Western Australia and South Australia the rates were lower in 2015 than in 2014. This change in method means that time series data for Queensland are not directly comparable and caution should be used in interpreting the trend.
Data for this measure come from the ABS National Mortality Database (see notes for measure 1.22). Infant mortality rates are per 1,000 live births. ‘Infant’ includes persons with an age at death of under 1 year. For child mortality tables (0–4 years), the denominator for single year time series data is a three-year rolling average to account for an anomaly in the 2011 Indigenous population estimate for this age group. For current period reporting (2011–15), the denominator is the average of the population estimates for these five years.
Table 1.20-2: ‘Other conditions’ include: neoplasms; diseases of blood and blood-forming organs; endocrine, nutritional and metabolic diseases; mental and behavioural disorders; diseases of the nervous system; diseases of the eye and adnexa; diseases of the ear and mastoid process; diseases of the digestive system; diseases of the musculoskeletal system and connective tissues; diseases of the genitourinary system; and diseases of the skin and subcutaneous tissue.
1.21 Perinatal mortality
Data for this measure come from the ABS National Mortality Database. This database contains details of all deaths registered in Australia including information on fetal (stillbirths) and neonatal deaths (deaths occurring in live births up to 28 days of age) by age of the baby, sex, state/territory of birth, Indigenous status and cause of death (ICD-10). Also, refer to notes for measure 1.22 for more information on mortality data. Perinatal deaths are all fetal deaths (at least 20 weeks’ gestation or at least 400 grams birthweight) plus all neonatal deaths (death of a live-born baby within 28 days of birth). Perinatal death rates are calculated per 1,000 births for the calendar year.
Figure 1.21-3: From 2014, cells with small values have been randomly adjusted to protect confidentiality. Some totals will not equal the sum of their components. Cells with 0 values have not been affected by confidentialisation.
1.22 All causes age-standardised death rates
Mortality data are derived from the ABS National Mortality Database. Current period data cover the period 2011–15 and are reported for NSW, Qld, WA, SA and the NT combined. Data are presented in 5-year groupings because of small numbers each year. Time trends are also presented for the five jurisdictions for 1998–2015. These states and territories are considered to have adequate levels of Indigenous identification in mortality data for these periods. Time series data are presented for single years.
For 2015 mortality data, the Queensland Registry of Births, Deaths and Marriages included Medical Certificate of Cause of Death information for the first time to contribute to the Indigenous status data item. This was associated with a decrease in the number of deaths for which the Indigenous status was ‘not stated’ and an increase in the number of deaths identified as Indigenous in Queensland. Although the Indigenous child mortality rate was higher in Queensland in 2015, for New South Wales, Western Australia and South Australia the rates were lower in 2015 than in 2014. This change in method means that time series data for Queensland are not directly comparable and caution should be used in interpreting the trend.
Death rates are age-standardised death rates per 100,000 population using the 2001 Australian Estimated Resident population, by 5-year age group to 75 years and over. Non-Indigenous estimates are available for Census years only. In the intervening years, Indigenous population figures are derived from assumptions about past and future levels of fertility, mortality and migration. In the absence of non-Indigenous population figures for these years, it is possible to derive denominators for calculating non-Indigenous rates by subtracting the projected Indigenous population from the total population. Non-Indigenous population estimates have been derived by subtracting the 2011 Census-based Indigenous population projections from the 2011 Census-based total persons estimated resident population (ERP). Such figures have a degree of uncertainty and should be used with caution, particularly as the time from the base year of the projection series increases.
Age-specific death rates per 100,000 are not age-standardised. Care should be taken when interpreting mortality rates for Qld due to recent changes in the timeliness of birth and death registrations. Qld deaths data for 2010 have been adjusted to minimise the impact of late registration of deaths on mortality indicators.
Although most deaths of Aboriginal and Torres Strait Islander peoples are registered, it is likely that some are not accurately identified as Indigenous. Therefore, these statistics are likely to underestimate the Indigenous mortality rate. Time series analysis may also be affected by variations in the recording of Indigenous status over time. It is also difficult to identify the exact difference between the Indigenous and non-Indigenous mortality rates because of these data quality issues. Deaths prior to 2007 are by year of registration and state/territory of usual residence. Deaths from 2007 onwards are by reference year and state/territory of usual residence. Registration year prior to 2007 is equivalent to reference year from 2007 onwards. All causes of death data from 2007 onward are subject to a revisions process; once data for a reference year are ‘final’, they are no longer revised. Affected years are: 2011–12 (final), 2013 (revised), and 2014–15 (preliminary).
Table 1.22-1: Data for these five jurisdictions over-represent Indigenous populations in less urbanised and more remote locations. Mortality data for the five jurisdictions should not be assumed to represent the experience in the other jurisdictions.
Figure 1.22-2: Data are reported for Australia-level remoteness areas as a breakdown of remoteness areas by state/territory is not available for Aboriginal and Torres Strait Islander population estimates or projections. Remote areas include very remote and remote areas of Australia.
Figure 1.22-3: Potential years of life lost (PYLL) is an estimate of the number of additional years a person would have lived had they not died before a certain age, such as 75 years. Consequently, PYLL give greater weight to deaths in younger age groups. The impact these early deaths have at the population level can be measured by the PYLL number per 1,000 people, which totals all the potential years of life lost for all the deaths at each age group, divided by the number of people in that age group. The ‘gap’ is the difference between the PYLL rate for Indigenous and non-Indigenous populations.
1.23 Leading causes of mortality
Refer to notes for measure 1.22 for more information on mortality data. Causes of death are based on the tenth revision of the International Classification of Diseases (ICD-10). It should be noted that different causes may have different levels of under-identification that differ from the ‘all-cause’ coverage rates. It should also be noted that the quality of the cause of death data depends on every step of the process of recording and registering deaths (including the documentation available at each step of the process) from certification of death to coding of cause of death.
Chronic conditions are select ICD-10-AM mortality groups as defined by the Office for Aboriginal and Torres Strait Islander Health, 2009 and includes circulatory disease, cancer, endocrine/metabolic/nutritional disorders (including diabetes), respiratory diseases, digestive diseases, kidney diseases and nervous system diseases. The gap in mortality due to chronic conditions is for 2015 and is calculated as the difference in the rate of chronic disease between Indigenous and non-Indigenous Australians as a proportion of the rate difference for all causes. Chronic conditions accounted for 70% of Indigenous deaths in the time period 2011–15.
Table 1.23-1: Data for lung cancer, cervical cancer and digestive organ cancers are a subset of the data presented for all cancers. Data for diabetes are a subset of data presented for all endocrine, metabolic and nutritional disorders. Data for cervical cancer are for females only. ‘Other causes’ includes: diseases of the blood and blood‑forming organs and certain disorders involving the immune system, mental & behavioural disorders, diseases of the eye and adnexa, diseases of the ear and mastoid process, diseases of the skin & subcutaneous tissue, diseases of the musculoskeletal system and connective tissue, diseases of the genitourinary system (excluding kidney diseases), pregnancy, childbirth & the puerperium, congenital malformations, deformations and chromosomal abnormalities; and symptoms, signs and abnormal clinical findings not elsewhere classified.
Figure 1.23-1: Some of the cells within this figure have been randomised to ensure confidentiality of data. ABS recommends cells with small values be interpreted with caution. ICD-codes for external causes cover V01–Y98 with the categories: Intentional self‑harm (X60–X84, Y87.0), Transport accidents (V01–V99), Accidental drowning or accidental threats to breathing (W65–W84), Accidental poisoning by and exposure to noxious substances (X40–X49), and Assault (X85–Y09, Y87.1). ‘Other external causes’ includes all other external causes of death not presented elsewhere in this table.
Table 1.23-2: Data presented for acute myocardial infarction are a subset of data presented for ischaemic heart disease. Data presented for stroke are a subset of data presented for cerebrovascular disease in this table. Data presented for bowel cancer are a subset for all cancers of the digestive organs. Data presented for bronchus and lung cancer are a subset of data presented for all respiratory and intrathoracic organs. Data presented for cancer of the cervix are a subset of data presented for all cancers of the female genital organs in this table. ‘Other malignant neoplasms’ includes neoplasms of bone and articular cartilage; melanoma and other neoplasms of skin; neoplasms of mesothelial and soft tissue; neoplasms of eye, brain and other parts of central nervous system; neoplasms of thyroid and other endocrine glands; and malignant neoplasms of independent (primary) multiple sites. Data presented for COPD and asthma are a subset of data presented for all chronic lower respiratory diseases.
1.24 Avoidable and preventable deaths
Refer to notes for measure 1.22 and 1.23 for information on mortality data. This measure presents data for Potentially Avoidable Deaths as defined in the National Healthcare Agreement PI 16 for 2015. It includes deaths from conditions that are potentially preventable through individualised care and/or treatable through existing primary or hospital care. Due to changes in the specification of the indicator, data presented here are not comparable with that in previous HPF reports.
Table 1.24-1: Selected invasive infections consists of ICD-10 codes A38–A41, A46, A48.1, G00, G03, J02.0, J13–J16, J18, L03. The avoidable mortality classification includes Acute lymphoid leukaemia/Acute lymphoblastic leukaemia (C91.0) for those aged 0–44 years only. This cause has been included in only the relevant age groups and the subset included in the total.
Tier 2 Determinants of Health
2.01 Housing
Households are considered overcrowded if one or more additional bedrooms are required to satisfy the Canadian National Occupancy Standard. Proportions have been calculated on all occupied private dwellings excluding those where number of bedrooms was not stated and includes not stated state/territory if the categorisation is not based on state/territory. Persons exclude visitors and persons in households for which housing utilisation could not be determined.
Figure 2.01-4: ‘Private/other’ renter includes dwellings being rented from a real estate agent, parent/other relative or other person, dwellings being rented through a Residential park (includes caravan parks and marinas), government employer (includes Defence Housing Authority) and other employer (private).
2.02 Access to functional housing with utilities
Data for this measure are derived from the 2014–15 National Aboriginal and Torres Strait Islander Social Survey (NATSISS).
Figure 2.02-1: Note that rising damp has been excluded from major structural problems to enable time series comparisons.
Figure 2.02-3: Indigenous households reporting a lack of working facilities for each of the first 4 Healthy Living Practices: ‘Washing people’ comprises households lacking a working bath or shower. ‘Washing clothes/bedding’ comprises households lacking washing machine and/or laundry tub. ‘Storing/preparing food’ comprises households without working stove/oven/cooking facilities or a kitchen sink or a working refrigerator. ‘Sewerage facilities’ comprises households lacking a working toilet. Excludes households for which information about working facilities was not reported.
There were differences in the question methodology between NATSISS 2002, 2008, 2014-15 and AATSIHS 2012–13 when asking about functional household facilities. In 2002, households were asked about the presence of working facilities and in 2008, 2012–13 and 2014–15 households were asked about the absence of working facilities.
In 2002, households were asked if they had adequate kitchen cupboard space as part of the food preparation facilities question. Households were not asked this in 2008, 2012–13 and 2014–15. Therefore, when comparing the proportion of households with working facilities for preparing food between 2002 and 2008, 2012–13 and 2014–15, caution should be used.
Figure 2.02-4: An acceptable standard of housing is defined as a household with four working facilities (for washing people, for washing clothes/bedding, for storing/preparing food and sewerage) and not more than two major structural problems.
2.03 Environmental tobacco smoke
Table 2.03-1: The question of ‘Whether any regular smokers smoke at home indoors’ was only asked of respondents with a daily smoker in the household. Therefore, the ‘No’ category for ‘Whether any regular smokers smoke at home indoors’ does not include non-smoking households or households where smoking occurs less than daily.
All figures exclude households in which the smoking status of members was not stated. Results only represent daily smokers in household (do not include smoking that is less than daily).
2.04 Literacy and numeracy
The data from this measure are from the National Assessment Program—Literacy and Numeracy (NAPLAN). Equating one test with another is a complex procedure and involves some degree of statistical error. For this reason, there may be minor fluctuations in the average NAPLAN test results from year to year when, in reality, the level of student achievement has remained essentially the same. It is only when there is a meaningful change in the results from one year to the next, or when there is a consistent trend over several years, that statements about improvement or decline in levels of achievement can be made confidently.
Some caution is required when interpreting changes in the performance across years as a new persuasive writing scale was introduced in 2011. The persuasive writing results for 2011 should not be directly compared with the narrative writing results from earlier years. Therefore, writing results are not reported toward the Closing the Gap target for reading, writing and numeracy, as they cannot be compared to the 2008 baseline.
Data for this report have been based on the annual NAPLAN results for 2008 to 2016. It is important to note that trends in results for Indigenous students will be impacted by changes in the levels of participation in NAPLAN. Participation rates are generally lower for Indigenous students, particularly in jurisdictions with more people living in remote areas.
2.05 Education outcomes for young people
Data for this measure come from the AIHW analysis of the ABS National Schools Statistics Collection (NSSC). Apparent retention rate is Year 10 or 12 students as a proportion of the corresponding cohort from the first year of secondary schooling (Year 7/8). NSSC data is sourced from the administrative records of relevant state and territory education systems. Accordingly, changes in administrative methods and systems can impact on the coherence of these statistics over time. In particular, the accuracy of identification of Aboriginal and Torres Strait Islander students can vary significantly between jurisdictions and over time. The following factors have not been taken into account in these statistics: students repeating a year of education; migration and other net changes to the school population, enrolment policies (including year starting high school which contributes to different age/grade structures between states and territories); and inter-sector transfer and interstate movements of students. In small jurisdictions, relatively small changes in student numbers can create apparently large movements in retention rates.
Table 2.05-1: The inclusion or exclusion of part-time students can also have a significant effect on apparent retention rates, especially in SA, Tasmania and the NT, which have relatively large proportions of part-time students. Data in various jurisdictions may be affected by changes in scope and coverage or processing methodology over time. Some rates, particularly those in the ACT may exceed 100%, largely reflecting the movement of students from non‑government to government schools in Years 11 and 12, and of residents who choose to enrol in a school in a different state or territory to which they reside e.g. NSW residents from surrounding areas enrolling in ACT schools. Note results over 100% have been set to 100%.
2.06 Educational participation and attainment of adults
Figure 2.06-1: ‘Technical or Further Education’ includes TAFE/VET/technical college, business college, and industry skills centre. Data comes from the 2014–15 NATSISS for the Indigenous Australian results and 2014 GSS for the non-Indigenous data.
Figure 2.06-2: ‘Completed year 9 or below’ includes persons never attended school. Excludes those still attending secondary school.
Figure 2.06-3: The data come the Higher Education Statistics Collection which records details of students enrolled and completing courses in higher education institutions.
Figure 2.06-4: The data come from the National Centre for Vocational Education Research. Non-identification rates for Aboriginal and Torres Strait Islander status in these data are high. Care also needs to be taken when comparing data across jurisdictions for load pass rates, as average module durations vary across jurisdictions. Percentages are calculated using the Indigenous and non-Indigenous estimated resident populations for 2011. Data represent number of completions and students may complete more than one course. Includes statements of attainment. The 2013 completions data was affected by under-reporting of completions in NSW due to reporting issues associated with the implementation of a new student administration and learning management system at TAFE NSW.
Figure 2.06-5: Qualifications are as classified under the ABS Classification of Qualifications. ‘Bachelor degree or above’ includes bachelor degree, doctorate, masters, graduate diploma, graduate certificate.
2.07 Employment
The labour force comprises all people contributing to, or willing to contribute to, the supply of labour. This includes the employed (people who have worked for at least 1 hour in the reference week) and the unemployed (people who are without work, but have actively looked for work in the last four weeks and are available to start work). The remainder of the population is not in the labour force. The labour force participation rate is the number of people in the labour force as a proportion of the working age population (15–64 years). The unemployment rate is the number of unemployed people as a proportion of the labour force. The employment to population ratio, also referred to as the employment rate, is employed people as a proportion of the population aged 15–64 years.
The Community Development Employment Program (CDEP) was included in the ABS classification of employment for the period that it operated.
‘Not stated’ responses are excluded.
2.08 Income
Figure 2.08-1: Equivalised household income quintile boundaries for the total population were derived from the 2014–15 National Health Survey and adjusted for Consumer Price Index (CPI) increases between the 2014–15 enumeration period of the National Health Survey and the 2014–15 enumeration period of the National Aboriginal and Torres Strait Islander Social Survey. These are lowest quintile $0–$435 per week; second quintile $436–$675 per week; third quintile $676–$1,018 per week; fourth quintile $1,019–$1,550 per week; highest quintile $1,551 or more per week. These have been applied to both the Indigenous and non-Indigenous populations.
Figure 2.08-2: Equivalised household income quintile boundaries for the total population as derived from the 2004–05 National Health Survey are: lowest quintile less than $295 per week; second quintile $295–$478 per week; third quintile $479–$688 per week; fourth quintile $689–$996 per week; highest quintile $997 or more per week. These have been applied to both the Indigenous and non-Indigenous populations.
Equivalised household income quintile boundaries for the total population as derived from the 2008–09 Survey of Income and Housing are: lowest quintile less than $330 per week; second quintile $330–$561 per week; third quintile $562–$835 per week; fourth quintile $836–$1,240 per week; highest quintile $1,241 or more per week. These have been applied to both the Indigenous and non-Indigenous populations.
Non-Indigenous: Equivalised household income quintile boundaries for the total population as derived from the 2011–13 Australian Health Survey are: lowest quintile less than $399 per week; second quintile $399–$638 per week; third quintile $639–$958 per week; fourth quintile $959–$1,437 per week; highest quintile $1,438 or more per week. Indigenous: Equivalised household income quintile boundaries for the total population were derived from the 2011–13 Australian Health Survey and adjusted for Consumer Price Index (CPI) increases between the 2011–12 enumeration period of the National Health Survey and National Nutrition and Physical Activity Survey and the 2012–13 enumeration period of the National Aboriginal and Torres Strait Islander Health Survey. These are: lowest quintile less than $407 per week; second quintile $407-$651 per week; third quintile $652-$978 per week; fourth quintile $979-$1,467 per week; highest quintile $1,468 or more per week.
Figures 2.08-3 and 2.08-4—see notes for Figure 2.08-1.
Figure 2.08-5: Adjusted for changes in the Consumer Price Index. Factors applied to change nominal dollar values to 2014–15 dollars for data collected earlier than 2014–15 are as follows: For all 2002 data, the adjustment is 1.373340. For all 2004–05 data, the adjustment is 1.306023. For all 2008 data, the adjustment is 1.154179. For 2011–13, adjustment for data from the 2011–12 Australian Health Survey is 1.071478, and 1.044499 for data from the 2012–13 Australian Aboriginal and Torres Strait Islander Health Survey.
2.09 Index of Disadvantage
The population of some states/territories was unable to be split into exact quintiles based on the SEIFA index of advantage/disadvantage. In all except one of these cases, the best approximate quintiles were calculated. Approximate population quintiles based on the SEIFA index of advantage/disadvantage were unable to be calculated for Tasmania because of the population spread.
2.10 Community safety
Figure 2.10-1: Data are from the AIHW’s analysis of the National Hospital Morbidity Database. Refer to notes for measure 1.02 regarding these data. Causes of injury are based on the first reported external cause as ‘assault’ (ICD-10-AM codes X85–Y08), where the principal diagnosis was ‘injury and poisoning’ (S00–T98).
Figure 2.10-2: Refer to notes for measure 1.22 for information on mortality data. ICD–10 codes X85–Y09 and Y87.1.
Figures 2.10-3 and 2.10-4: sourced from Recorded Crime—Victims, Australia 2015 (ABS cat. no. 4510.0) published in June 2016. This publication presents national statistics relating to victims of crime for a selected range of offences as recorded by police. Offences are classified according to the Australia and New Zealand Standard Offence Classification (ANZSOC). Relationship of offender to victim information is not currently available for WA, and there are some inconsistencies in relationship of offender to victim data across jurisdictions. All family and domestic violence related assaults are recorded even if the victim does not want to proceed with an assault charge.
2.11 Contact with the criminal justice system
Figures 2.11-1, 2.11-2 and 2.11-4: Data are from the AIHW Juvenile Justice National Minimum Dataset. Rates are based on AIHW juvenile justice data. Aboriginal and Torres Strait Islander peoples in juvenile justice are calculated using population estimates based on the 2006 Census (Series B). Age is calculated at the start of the financial year if the period of detention began before the start of the financial year. Otherwise age is calculated as at the start of the period of detention. For the ACT, single year of age population data was not available for rate calculations. Excludes WA and the NT.
Figure 2.11-5 and Table 2.11-1: Data are from the ABS National Prison Census. The ABS collects data from administrative records on people in prison custody on 30 June each year in all jurisdictions. This Census includes all prisoners in adult corrective services, but not persons in juvenile institutions, psychiatric care or police custody. These data provide a picture of persons in prison at a point in time and does not represent the flow of prisoners during the year.
Table 2.11-1: Rates are number per 10,000 adult population.
Figure 2.1-5: Age-standardised to the 2001 Australian population. In June 2013, the ABS ‘recast’ the historical ERP data for the September 1991 to June 2011 period, as a response to a methodological improvement in the Census Post-Enumeration Survey. In April 2014, the ABS ‘recast’ the historical estimates for Aboriginal and Torres Strait Islander populations. As a result, the rates per 100,000 adult persons in the source table have been recast, and all now use final ERP data based on the 2011 Census. In all states and territories except Qld, persons remanded or sentenced to adult custody are aged 18 years and over. Persons under 18 years are treated as juveniles in most Australian courts and are only remanded or sentenced to custody in adult prisons in exceptional circumstances. Prior to 2006, in Victoria, an adult referred to persons aged 17 years and over. Prior to 2000, in Tasmania, an adult referred to persons aged 17 years and over. In Qld, adult continues to be defined as persons aged 17 years and over. Individual state and territory data and national data reflect the age scope that applied to these jurisdictions in the relevant years. Apparent increases in 2006 may be due to changes in collecting and recording Indigenous information, or in the willingness of Indigenous people to self-identify.
2.12 Child protection
Rates are calculated using Indigenous projections based on the 2011 Census of Population and Housing and should not be compared with rates calculated using ERPs or projections based on previous Censuses.
Figure 2.12-1: WA is currently unable to report a child’s characteristics based on their first substantiation. As a result, a small number of children may be double-counted in this table where they have more than one substantiation and the notifications had differing characteristics such as age or abuse type. In WA, Tasmania and the ACT, the proportion of substantiations for children with an unknown Indigenous status affects the reliability of these data. Indigenous populations sourced from ABS’ 2014 Estimates and Projections, Aboriginal and Torres Strait Islander Australians, 2001–2026 Series B. (ABS cat. no. 3238.0). December Indigenous populations are calculated as the average of the June population projections either side of the December. For example, the December 2012 population for Indigenous children is the average of the June 2012 and June 2013 population projections. All children populations are derived from the ABS’ 2014 Australian Demographic Statistics, December 2013 release (ABS cat. no. 3101.0). Non-Indigenous populations are derived by subtracting the Indigenous projection count from the ‘all children’ ERP. Data produced from the CP NMDS based on nationally agreed specifications may not match Queensland figures published elsewhere. Queensland data for 2014–15 onward are not comparable with data for previous years.
Figure 2.12-2 and Table 2.12-1: Indigenous populations sourced from ABS’ 2014 Estimates and Projections, Aboriginal and Torres Strait Islander Australians, 2001–2026 Series B. (ABS cat. no. 3238.0). All children counts are derived from the ABS’ 2013 Australian Demographic Statistics, June 2013 release (ABS cat. no. 3101.0). Non-Indigenous counts are derived by subtracting the Indigenous projection count from the ‘all children’ ERP.
Figure 2.12-3: This figure does not include Aboriginal and Torres Strait Islander children who were living independently or whose living arrangements were unknown. Family group homes and residential care are reported under ‘other caregiver’.
2.13 Transport
Table 2.13-6: ‘Total’ for Psychological distress excludes a small number of people for whom level of psychological distress was unable to be determined. Tables 2.13-7, 2.13-8, and 2.13-9, 2: ‘Total’ includes those who never go out or are housebound. Table 2.13-10: ‘Total’ includes not known and those who never go out or are housebound. Main reason for not using public transport was asked of people who had not used public transport in last 2 weeks but who had access to public transport in their area and were not housebound. ‘Other reasons’ includes takes too long, concerned about personal safety, costs too much, treated badly/discrimination and other reasons not further defined.
2.14 Indigenous people with access to their traditional lands
Data for this measure are derived from the 2014–15 NATSISS. Results represent only those people who answered on behalf of themselves, and excludes refusals and not asked. Estimates have been rounded and discrepancies may occur between sums of component items and totals.
Figure 2.14-1: excludes refusals and not asked.
2.15 Tobacco use
This measure presents self-reported data for Aboriginal and Torres Strait Islander peoples, the most recent source being the 2014–15 Social Survey. ‘Current smoker’ includes persons who smoke daily, weekly or other regular pattern (but less than weekly). Data are presented for those aged 15 years and over.
Figure 2.15-1: Data for non-Indigenous Australians are sourced from the 2014–15 NHS. Proportions have been directly age-standardised to the 2001 Australian ERP (based on the 2001 Census, using 10-year age groups to 55+) to account for differences in the age structure of the two populations. Rate differences between Indigenous and non-Indigenous Australians were statistically significant across all age groups.
Figure 2.15-2: Also includes data from the 2002 and 2008 NATSISS and the 2012–13 AATSIHS. Rate differences between 2002 and 2014–15 were statistically significant for Non-remote areas and Australia but not for Remote areas.
Figure 2.15-3: Also includes data from the 2002 and 2008 NATSISS and the 2012–13 AATSIHS. Data are presented for current smokers (as defined above), ex-smokers (don’t currently smoke, but had regularly smoked daily, or had smoked at least 100 cigarettes, or smoked pipes/cigars at least 20 times in their lifetime) and non-smokers (never smoked, never smoked regularly, smoked less than 100 cigarettes in their lifetime). Rate differences between 2002 and 2014–15 were significant for current smokers and ex-smokers but not for those who never smoked.
Figure 2.15-4: This figure presents relationships between being a non-smoker and selected socio-economic factors:
- SEIFA (Index of Advantage/Disadvantage)
- Education (Highest year of school completed). Note Year 10 or below includes those who never attended school.
- Income (equivalised gross household income). Quintile boundaries for total population were derived from the 2014–15 NHS and adjusted for CPI increases between the enumeration periods for the 2014–15 NHS and NATSISS. The first/lowest quintile: $0–435 per week; second quintile: $436–$675 per week; third quintile $676–$1,018 per week; fourth quintile: $1,019-$1,550 per week and fifth/highest quintile: $1,551 or more per week).
- Employment status (unemployed/employed).
Table 2.15-1: Also includes data from the 1994 NATSIS, the 2002 and 2008 NATSISS and 2012–13 AATSIHS. For the 1994 NATSIS, respondents were not asked how frequently they smoked cigarettes; for the other years presented, data are based on current smokers as defined above. Data is only available for those aged 18 years and over in the 2004–05 Health Survey, so it has been excluded.
Figure 2.15-5: Data are presented by Indigenous Region. For the Alice Springs Indigenous Region, 2012–13 AATSIHS data has been used because the Alice Springs sample used in the 2014–15 Social Survey was too small.
Figure 2.15-6: Time-series data for Indigenous Australians sourced from 1994 NATSIS, 2002, 2008 and 2014–15 NATSISS and 2012–13 AATSIHS. For Non-Indigenous Australians, data sourced from the 1989–90, 1995, 2001, 2007–08, 2011–12 (core), and 2014–15 National Health Surveys. The rate differences between Indigenous and non-Indigenous Australians are statistically significant at each time point. The declines for both Indigenous and non-Indigenous Australians over the periods presented are also statistically significant. This figure also includes key tobacco control measures, both Indigenous-specific and mainstream; though state/territory legislation (often introduced over a span of years) have mostly been excluded (e.g. smoke-free outdoor dining and pubs; smoke free cars).
2.16 Risky alcohol consumption
Data from this measure are sourced from the 2014–15 Social Survey, 2012–13 Health Survey and 2011–12 National Health Survey component. Risk level calculated on exceeding the NHMRC Australian Alcohol Guidelines 2009. For short-term/single occasion risk this is 5 or more standard drinks on any day over the last 12 months. For lifetime risk, this is consuming more than two standard drinks per day on average.
Figure 2.16-4: Refer to notes for measure 1.22 regarding mortality data. ICD-10 codes: K70, F10, X45, X65, Y15, E24.4, G31.2, G62.1, G72.1, I42.6, K29.2, K86.0
2.17 Drug and other substance use including inhalants
Data for this measure come from the 2014–15 Social Survey, 2012–13 Health Survey, non-Indigenous data from the 2013 AIHW National Drug Strategy Household Survey, and various other sources including the Drugs Use Monitoring in Australia (DUMA) programme run by the Australian Institute of Criminology (AIC) with funding by the Australian Government. The DUMA programme data used in this publication were made available through the AIC and were originally collected by the AIC by an independent data collector with the assistance of the NSW, Qld, SA and WA Police. Neither the collectors, the police, nor the AIC bear any responsibility for the analyses or interpretations presented herein.
Table 2.17-1: In non-remote areas substance use questions were self-completed by respondents whereas in remote areas respondents were asked questions in a personal interview. Proportions exclude not stated responses (people who accepted the substance use form but did not state if they had ever used substances) and 9% of Aboriginal and Torres Strait Islander people who did not complete the substance use module. ‘Total used substances in last 12 months’ includes heroin, cocaine, petrol, LSD/synthetic hallucinogens, naturally occurring hallucinogens, ecstasy/designer drugs, other inhalants and methadone. Sum of components may be more than total as the same person may have reported more than one type of substance used in the last 12 months.
2.18 Physical activity
The most recent data on physical activity come from the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATINPAS) and the NATSIHS, collected through the AATSIHS 2012–13. Comparison data for non-Indigenous have been sourced from the National Nutrition and Physical Activity Survey (NNPAS), 2011–12 component of the AHS.
Current physical activity guidelines (released by the Department of Health) recommend the following:
Supervised floor-based play in safe environments should be encouraged from birth to one year. Toddlers (1–3 years) and pre-schoolers (3–5 years) should be physically active every day for at least three hours, spread throughout the day. Children aged 5–17 years should accumulate at least 60 minutes of moderate to vigorous intensity physical activity every day. Adults aged 18–64 years should accumulate 150 to 300 minutes (2 ½ to 5 hours) of moderate intensity physical activity or 75 to 150 minutes (1 ¼ to 2 ½ hours) of vigorous intensity physical activity, or an equivalent combination of both moderate and vigorous activities, each week. Adults aged 65 years and over should aim to be physically active for 30 minutes every day.
The Guidelines also provide recommendations around sedentary behaviours:
Children younger than 2 years of age should not spend any time watching television or using other electronic media (DVDs, computer and other electronic games). For children 2 to 5 years of age, sitting and watching television and the use of other electronic media should be limited to less than one hour per day. Infants, toddlers and pre-schoolers (all children birth to 5 years) should not be sedentary, restrained, or kept inactive, for more than one hour at a time, with the exception of sleeping. Children aged 5–17 years should limit the use of electronic media to no more than two hours a day. It is recommendations that adults break up long periods of sitting as often as possible.
Definitions of physical activity levels:
In the AATSIHS 2012–13, respondents are classified as inactive if no walking, moderate or vigorous intensity physical activity was reported in the week prior to interview. Insufficiently active is defined as some activity but not enough to reach the levels required for ‘sufficiently active’; and ‘sufficiently active (for health)’ is defined as 150 minutes of moderate/vigorous physical activity from five or more sessions over a seven-day period.
Figure 2.18-3: The physical activity recommendation for children aged 5–17 years is 60 minutes or more per day. This figure shows the proportion of children who met the recommendations on all 3 days prior to interview.
Figure 2.18-4: The screen-based recommendation for children aged 5–17 years is no more than 2 hours per day for entertainment purposes. This figure shows the proportion of children who met the recommendations on all 3 days prior to interview.
2.19 Dietary behaviours
The National Health and Medical Research Council revised their Australian Dietary Guidelines in 2013. The guidelines specify recommendations for adequate minimum daily intake of fruit and vegetables according to age and sex. Where the guidelines specify ½ serves, respondents in the 2014–15 NATSISS must have stated that they consumed the next whole number of serves per day in order to meet the guidelines. Note this is different to the AATSIHS 2012–13 where the respondents were only required to meet the serving as rounded down to the closest full serve. Only full serves were collected. The following table summarises the NATSISS variation to the NHMRC Australian Dietary Guidelines:
NATSIS variation to the NHMRC Australian Dietary Guidelines
| Age groups | Recommended daily serves of vegetables | Recommended daily serves of fruit |
|---|---|---|
| 2-3 years | 2.51 | 1 |
| 4-8 years | 4.51 | 1.51 |
| 9-17 years | 52 | 2 |
| 18 years and over (excl. males 18–49) | 5.53 | 2 |
| 18–49 year-old males | 6 | 2 |
1 In the 2014–15 NATSISS, the respondent must have stated they consume at least the next whole number of serves per day to have reached the guidelines.
2 Actual guidelines for males aged 12–17 years have an additional ½ serve.
3 Actual guidelines exclude males aged 19–50 years and males 51–70 years have an additional ½ serve.
See NATSISS: Users Guide for further information (ABS, 2016). For the purposes of time series analysis, the definition of ‘recommended daily vegetable/fruit intake’ is calculated in accordance with the guidelines that are current for the relevant time period. AATSIHS data has been classified in line with the NATSISS to ensure consistency over time.
2.20 Breastfeeding practices
Data for this measure (except exclusive breastfeeding) are derived from the 2014–15 NATSISS.
Data for exclusive breastfeeding come from the AIHW analysis of the 2010 Australian National Infant Feeding Survey. The sample size for this survey was 28,759 mothers/carers, including 401 (1.4%) mothers/carers who identified as Aboriginal and Torres Strait Islander; 28,214 who identified as non-Indigenous; and 144 (0.5%) whose Indigenous status was missing. The survey was a national survey, and as such no population sub-group was oversampled (e.g. Aboriginal and Torres Strait Islander peoples). The sampling frame for the survey was Medicare enrolment database. If there was a delay in infants or children to enrol for Medicare, these infants/children were excluded from the population. The survey used mail survey method to collect data (with an option of online completion). The survey instrument was in English language only. Mothers/carers who could not read or write and did not seek help from others could not participate in the survey.
Figure 2.20-4: ‘Age (months)’ indicates an infant’s age in the months before a fluid other than breast milk was introduced. This is effectively the month before another fluid was introduced. For example, a child who was introduced to water when they were aged 4 months (in their fifth month of life) was exclusively breastfed to 4 months of age (that is, they had 4 completed months of exclusive breastfeeding). Similarly, a child who was introduced to water at age 1 month (in their second month of life) was exclusively breastfed to 1 month. Or, a child who was introduced to water at 0 months (in their first month of life) was exclusively breastfed to 0 months (or less than 1 month).
Figure 2.20-5: Includes children for whom breastfeeding status was not known.
2.21 Health behaviours during pregnancy
Figures 2.21-1 and 2.21-2 are from the 2014 National Perinatal Data Collection (Refer to notes for measure 1.01 regarding perinatal data). Data include women who gave birth in the period, whether resulting in a live or stillbirth, if the birthweight is at least 400 grams or the gestational age is 20 weeks or more. Provisional data were provided by Victoria. Mother’s tobacco smoking status during pregnancy is self-reported. Percentages are calculated after excluding records with missing or null values. Excludes data where Indigenous status not stated.
Figure 2.21-1: Data are directly age-standardised using the Australian female population who gave birth in 2011 as the standard population. Data exclude non-residents, external territories and not-stated residence.
Figure 2.21-2: Data exclude mothers for whom maternal age was not stated.
Figure 2.21-3: Excludes data for Victoria, as these data were not available before 2009. Data are based on state/territory of birth.
Figure 2.21-4 are from the 2014–15 NATSISS. Data are collected for mothers of Indigenous children aged 0–3 years.
2.22 Overweight and obesity
All figures published by ABS in Australian Aboriginal and Torres Strait Islander Health Survey: Updated results, released 6 June 2014 (ABS cat. no. 4727.0.55.006). Measured BMI data are only available for 2012–13.
Proportions exclude those for whom BMI was unknown or not stated (16.2% for Aboriginal and Torres Strait Islander peoples and 15.7% for non-Indigenous Australians aged 15 years and over).
Figure 2.22-1: Directly age-standardised proportions to the Australian 2001 standard population.
Figure 2.22-3: For information on the calculation of BMI scores for children see the ABS publication glossary.
The AATSIHS 2012–13 also collected data on waist circumference and waist-to-hip ratio of adults. These measurements can indicate the amount of excess fat carried around the abdomen, which indicates potential for developing certain chronic diseases related to overweight and obesity. The AATSIHS found 62% of Indigenous Australian men and 81% of Indigenous Australian women were considered to be at increased risk of developing chronic disease based on their waist circumference. Refining the risk assessment by using waist circumference in addition to BMI suggests that 85% of Indigenous Australian men who were overweight or obese and 97% of Indigenous Australian women who were overweight or obese were considered to be at increased risk of developing chronic disease.
Tier 3 Health System Performance
3.01: Antenatal care
Data for this measure come from the National Perinatal Data Collection (see measure 1.01 for more information). Data represent one calendar year. Data includes women who gave birth in the period to a live or stillborn baby who weighed at least 400 grams and/or whose gestational age was 20 weeks or more. Data exclude births where the mother’s Indigenous status was not stated. Antenatal visits relate to care provided by skilled birth attendants for reasons related to pregnancy. Data on care in the first trimester excludes women whose gestation at first antenatal visit was not stated. First trimester is up to and including 13 completed weeks. Data on antenatal care provided in the first trimester is likely to be under reported for WA and ACT.
Figure 3.01-1 uses age-standardised data. This time series excludes data from NSW due to a change in data collection practices from 2011. Data are based on place of usual residence of mother. The collection of data on the number of antenatal visits is not part of the Perinatal NMDS. The current question is not consistent across jurisdictions; therefore, caution should be used when interpreting the data. Rates are per 100 women who gave birth in the relevant period directly age-standardised using the Australian female population who gave birth in 2001.
Figures 3.01-2, 3.01-3 and 3.01-4: Data are directly age-standardised using the Australian female population who gave birth in 2014 as the standard population. For figures 3.01-2 and 3.01-3: Data are by place of usual residence of the mother. Excludes Australian non-residents, residents of external territories and not stated state/territory of residence.
Additionally, for Figure 3.05-3 For WA and ACT the first antenatal visit is reported by birth hospital or first hospital visit (respectively); therefore, data may not be available for women who attend their first antenatal visit outside the birth hospital or GP.
3.02 Immunisation
Data in this measure are based on the Australian Childhood Immunisation Register (ACIR), which is managed by Medicare Australia and holds information on childhood immunisation coverage. All children under seven years of age who are enrolled in Medicare are automatically included on the ACIR. Children who are not eligible to enrol in Medicare can be added to the ACIR when details of a vaccination are received from a doctor or immunisation provider.
Coverage estimates for Aboriginal and Torres Strait Islander children include only those who identify as such and are registered on the ACIR. Children identified as Aboriginal and Torres Strait Islander on the ACIR may not be representative of all Aboriginal and Torres Strait Islander children, and thus coverage estimates should be interpreted with caution. Children for whom Indigenous status was not stated are included with the non‑Indigenous children under the ‘other’ category.
Vaccination coverage is a measure of the proportion of people in a target population who have received the recommended course of vaccinations at a particular age as specified in the National Immunisation Program (NIP) Schedule. Since 2001, there have been changes in the definitions used to determine whether a child is considered to be fully immunised. The age at which older children are assessed has also changed from 6 years to 5 years of age. As a result, some trends should be interpreted with caution.
Vaccination coverage data from the ACIR and the 2012–13 AATSIHS results are not directly comparable because of the differences in the cohort used, population coverage, data collection method, method of calculating ‘fully immunised’ and vaccines included.
Figure 3.02-1: Data not available for children at age 6 years for 2001. From 2008, fully vaccinated status for 5 year olds is reported in place of that for 6 year olds, due to changes to NCIR reporting practices. From December 2013 the definition of the term ‘fully immunised’ includes pneumococcal for ACIR coverage reporting purposes, for those in the ‘Age 1 year’ cohort.
Table 3.02-1: Age calculated as at 30 September 2015; 1 year includes children aged 12–<15 months; 2 year includes children aged 24–<27 months and 5 year include children aged 60–<63 months.
Figure 3.02-2: Data for Indigenous Australians sourced from the 2012–13 AATSIHS. For the total population, data sourced from the 2009 Adult Vaccination Survey.
3.03 Health promotion
Figure 3.03-1 and 3.03-2: These data come from the 2012–13 AATSIHS. Proportions are of those who consulted a doctor in the previous 12 months. Given multiple response was allowed, the sum of components may exceed the total.
3.04 Early detection and early treatment
Figure 3.04-1: Rates were calculated using ABS backcast population estimates and projections based on the 2011 Census. MBS item 715 commenced May 2010—MBS codes 704, 706, 708 and 710 were reclassified as 715 for prior years. Financial year reporting.
Figure 3.04-2: Data are from BreastScreen Australia. For each period presented (two combined calendar years), rates are the number of women screened as a percentage of the eligible female population calculated as the average of the current and previous year’s ABS estimated resident population. Rates are directly age-standardised to the Australian 2001 standard population in 5-year age groups up to 69 years. ‘Other women’ includes women in the ‘not stated’ category for Aboriginal and Torres Strait Islander status. Indigenous status is self-reported; therefore, accuracy of Indigenous participation rates will be affected if women choose not to identify as Indigenous at the time of screening. These rates are likely to differ from Indigenous population data used by individual states and territories; this may result in different participation rates for Indigenous women between this report and state and territory data. Small numbers in individual states and territories will exacerbate any differences in published rates based on different population data.
Figure 3.04-3: Self-reported data from the 2012–13 AATSIHS. Proportion of women reporting that they have regular pap smear tests (frequency not qualified/quantified). Excludes not stated responses and ‘form not answered’.
Table 3.04-1: Data sourced from National Bowel Cancer Screening Program Register as at 31 December 2015. The FOBT positivity rate is the proportion of those with a valid screening test that had a positive FOBT result. The diagnostic assessment rate is the proportion of those with a positive FOBT result that received a follow-up diagnostic assessment (colonoscopy). Diagnostic assessment rate relies on information being reported back to the Register. As NBCSP forms are not mandatory there may be incomplete form return and incomplete data.
3.05 Chronic disease management
Figure 3.05-1 and 3.05-2: Medicare data presented by Indigenous status have been adjusted for under-identification in the Medicare Australia Voluntary Indigenous Identifier (VII) database. The methodology for this adjustment was developed and verified by the AIHW and the Department of Health for assessment of MBS and PBS service use and expenditure for Aboriginal and Torres Strait Islander peoples. Data are directly age-standardised using the 2001 Australian standard population, by 5-year age group up to 75 years and over. Data are based on date-of-processing (rather than date-of-service).
Figure 3.05-3: Sourced from May 2015 national Key Performance Indicator data. Data presented for around 32,930 Aboriginal and Torres Strait Islander peoples aged 15 years and over who are regular clients of Indigenous primary health care organisations. A regular client is defined as a person who has an active medical record—that is, a client who attended the primary health care organisation at least 3 times in the last 2 years. (Note limitation for clients who attend multiple health organisations). Valid data for this indicator were provided by around 210 organisations. Data indicate blood pressure and HbA1c (glycosylated haemoglobin) recorded in previous 6 months and kidney function tests (estimated glomerular filtration rate (eGFR) and/or albumin/creatinine ratio (ACR) tests) in previous 12 months to May 2015. The normal range for eGFR is ≥60 mL/min/173m2.
3.06 Access to hospital procedures
Data for this measure come from the AIHW’s analysis of the National Hospital Morbidity Database. Refer to notes for measure 1.02 regarding hospital data. Data in this measure are presented as a proportion of hospital separations and not as a population rate. Proportions are age-standardised.
Table 3.06-1: Hospitalisations with a principal diagnosis of dialysis (Z49) have been excluded.
Figure 3.06-2: Hospitalisations with a principal diagnosis of dialysis (Z49) or diagnosis not stated have been excluded.
Figure 3.06-3: Percentages are the proportion of hospitalisations with coronary heart disease as the principal diagnosis receiving either coronary angiography or coronary revascularisation.
3.07 Selected potentially preventable hospital admissions
Data for this measure come from the AIHW’s analysis of the National Hospital Morbidity Database. Refer to notes for measure 1.02 regarding hospital data. Rates in the figures are age-standardised.
Categories are based on the ICD-10-AM eighth edition (National Centre for Classification in Health 2013): codes J10, J11, J13, J14, A08.0, A35, A36, A37, A80, B01, B05, B06, B16.1, B16.9, B18.0, B18.1, B26, J45, J46, I50, I11.0, J81, E10.0–E10.9, E11.0–E11.9, E13.0–E13.9, E14.0–E14.9, J20, J41, J42, J43, J44, J47, J20, I20, I24.0, I24.8, I24.9, D50.1, D50.8, D50.9, I10, I11.9, E40, E41, E42, E55.0, E64.3, I00, I01, I02, I05, I06, I07, I08, I09, J15.3, J15.4, J15.7, J16.0, N10, N11, N12, N13.6, N15.1, N15.9, N28.9, N39.0, K25.0, K25.1, K25.2, K25.4, K25.5, K25.6, K26.0, K26.1, K26.2, K26.4, K26.5, K26.6, K27.0, K27.1, K27.2, K27.4, K27.5, K27.6, K28.0, K28.1, K28.2, K28.4, K28.5, K28.6, L02, L03, L04, L08, L88, L98.0, L98.3, N70, N73, N74, H66, J02, J03, J06, J31.2, K02, K03, K04, K05, K06, K08, K09.8, K09.9, K12, K13, K14.0, G40, G41, R56, O15, R02, I70.24, E09.52. Note some of these codes are for principal diagnosis only, some are for principal or additional diagnosis, and some are principal diagnosis with the exclusion of some procedure codes.
For more information on coding used, refer to the AIHW National Healthcare Agreement, PI-18 Selected potentially preventable hospitalisations, 2015.
Due to coding changes in the 8th edition there may be a large increase in separations with a diagnosis of Hepatitis B, therefore time series data for vaccine-preventable conditions are not presented.
3.08 Cultural competency
Figure 3.08-1: These data come from the Online Service Reporting (OSR) data collection. 2014–15 OSR data count all auspice services individually when calculating rates, therefore caution should be exercised when comparing rates with earlier data collection periods. Valid data on health activities were provided by 203 Indigenous primary health care organisations. The percentages supplied in this table are calculated as a proportion of these 203 services. Mechanisms for gaining high level advice on cultural matters affecting service delivery include local cultural advisory body, Board sub-committee that includes Aboriginal staff/local community members and/or Board members. Multiple response item, sum is greater than total.
Figure 3.08-2: Rate per 10,000 measures the health workforce available (numerator) to service the population (denominator). Denominator used in rates is the relevant Census count by Indigenous status minus those where occupation is not stated.
Figure 3.08-3: More than one response was allowed; therefore, the sum may exceed 100%. Estimates for access to dentists were asked of persons aged 2 years and over and estimates for access to mental health services were asked of persons aged 18 years and over.
Table 3.08-1: Self-reported data from the 2012–13 AATSIHS. More than one response allowed for ‘reason for not going to health care provider’; sum of components may exceed total. ‘Other health professional’ include: nurse, sister, and Aboriginal (and Torres Strait Islander) health worker. For ‘Dentist’ data includes persons aged 2 years and over. For ‘Counsellor’ data includes persons aged 18 years and over; data excludes ‘not asked’. ‘Total Health Services’ includes persons who reported that they needed to go to a dentist (persons aged 2 years and over), Doctor, other health professional, hospital, or counsellor (persons aged 18 years and over) in the last 12 months, but did not go.
Figure 3.08-4: Self-reported data from the 2014–15 Social Survey. People aged 15 years and over who consulted a doctor or specialist in the previous 12 months. Note an additional response category (‘rarely’) was included in the 2014–15 Social Survey, so data should not be compared with previous years.
3.09 Discharge against medical advice
Data for this measure come from AIHW’s analysis of the National Hospital Morbidity Database. Refer to notes for measure 1.02 regarding hospital data. Data in this measure are presented as a proportion of hospital separations and not as a population rate. Proportions are age-standardised. Hospitalisations with a principal diagnosis of dialysis (Z49) or mental and behavioural disorders (F00–F99, R44, R48, G30) have been excluded.
Figure 3.09-4: ‘Other’ includes: neoplasms, certain conditions originating in the perinatal period, diseases of the ear and mastoid process, diseases of the eye and adnexa, diseases of the genitourinary system, diseases of the musculoskeletal system, diseases of the blood and blood-forming organs and certain disorders involving the immune system, and congenital malformations and deformations and chromosomal abnormalities.
3.10 Access to mental health services
Figure 3.10-1: Data from five combined BEACH years (April 2010–March 2011 to April 2014–March 2015 inclusive). ‘Mental health-related problems’ classified according to ICPC-2 codes (Classification Committee of the World Organization of Family Doctors (WICC) 1998) and/or ICPC-2 PLUS codes. Data for Aboriginal and Torres Strait Islander peoples and other Australians have not been weighted. Rates were directly age‑standardised (number per 1,000 encounters) using total BEACH encounters in the period as the standard. ‘Other Australians’ includes non-Indigenous patients and patients for whom Indigenous status was not stated. ICPC–2 codes: P04–P05, P07–P13, P18, P20, P22‑P25, P27–P69, P71, P75, P77–P82, P85–P86, P98–P99.
Figure 3.10-2: The data for this figure come from the AIHW National Community Mental Health Care Database (NCMHCD). The quality of the Indigenous identification in this database varies by jurisdiction and should be interpreted with caution. Rates were directly age-standardised using the Australian 2001 standard population. Number per 1,000 population based on estimated resident population as at 30 June 2014.
Figures 3.10-3 and 3.10-4: Refer to notes for measure 1.02 regarding hospitalisation data. Mental health related conditions included are based on the ICD-10-AM eighth edition (National Centre for Classification in Health 2013) and previous editions: ICD-10-AM codes F70–F79; F20–F29; F00–F09; F99; F50–F59; F30–F39; F60–F69; F10–F19; F80–F89; F40–F49; F90–F98; F00–F99; G30, G47.0, G47.1, G47.2, G47.8, G47.9, O99.3, R44, R45.0, R45.1, R45.4, R48, Z00.4, Z03.2, Z04.6, Z09.3, Z13.3, Z50.2, Z50.3, Z54.3, Z61.9, Z63.1, Z63.8, Z63.9, Z65.8, Z65.9, Z71.4, Z71.5, Z76.0. Principal diagnosis code used.
3.11 Access to alcohol and other drug services
Table 3.11-1: Refer to notes for measure 3.03 for information on the OSR data collection. 27 of the 63 respondent Indigenous substance-use services provided valid data for the number of residential treatment/rehabilitation episodes of care. Twelve services provided valid data for the number of sobering-up/residential respite episodes of care; 57 services provided valid data for the number of non-residential/follow-up/aftercare episodes of care. Excludes 466 episodes of care that had unknown Indigenous status. Substance-use clients and episodes of care for 2014–15 are lower than those reported for 2012–13 in the previous HPF report. One type of Patient Information and Recall System was not extracting correct substance-use data for non-residential services in some organisations. Substance-use clients and episodes of care in the previous report were over-estimated as a result of this.
Figure 3.11-1: Refer to notes for measure 3.03 for information on the OSR data collection. Of the 63 respondent Aboriginal and Torres Strait Islander substance use services, 27 provided valid data for the number of residential treatment/ rehabilitation episodes of care; 12 services provided valid data for the number of sobering-up/residential respite episodes of care; and 57 services provided valid data for the number of non-residential/follow-up/aftercare episodes of care. Excludes 466 episodes of care that had unknown Indigenous status (3 for residential treatment/rehabilitation, 298 for sobering-up/residential respite and 165 for non-residential/follow-up/aftercare).
Substance-use clients and episodes of care for 2014–15 are lower than those reported for 2012–13 in the previous HPF report. One type of Patient Information and Recall System was not extracting correct substance-use data for non-residential services in some organisations. Substance-use clients and episodes of care in the previous report were over-estimated as a result of this.
Figure 3.11-2: Sourced from the national AODTS NMDS.
Figure 3.11-3: Refer to notes for measure 1.02 regarding hospitalisation data. For principal diagnoses related to alcohol use, includes ICD-10-AM codes: F10, K70, T51, K75, X65, X45, Y15. For principal diagnoses related to drug use, includes ICD-10-AM codes: T36–T40, T42–T43, T52, F11–F15, F18–F19, P961, C171 and 0355.
3.12 Aboriginal and Torres Strait Islander people in the health workforce
Table 3.12-1: Self-reported data from the 2011 Census. The table includes a detailed breakdown of occupations as defined by the Australian and New Zealand Classification of Occupations (ANZSCO). ‘n.a.’ means data not available. ‘n.p.’ refers to data not published (data cannot be released due to quality issues and confidentiality). Numbers less than 10 are considered too unreliable for general use due to the impact of randomisation of small cell values to avoid the release of confidential data. Per cent change between the reporting periods 1996 and 2011 based on the average annual change over the period. (Average period change of Indigenous health workforce numbers determined using regression analysis). Rate per 10,000 measures the health workforce available (number) to service the population (denominator). Denominator used in rates is the 2011 Census count by Indigenous status minus those where occupation is not stated. Rate difference is non-Indigenous rate minus Indigenous rate.
Both 2001 and 2006 figures for ‘Registered Nurses’ include Midwifery and Nursing Professionals not further defined (nfd).
‘Generalist Medical Practitioners’ includes General Medical Practitioner and Resident Medical Practitioner, and Specialist Physician (general medicine).
The 2006 data for ‘Other medical practitioners’ includes Anaesthetist, Pathologist, Psychologist, Neurosurgeon, and Medical Practitioners nfd. The 2001 figure includes Emergency Medical Specialist, Obstetrician and Gynaecologist, Pathologist, Radiologist, Psychiatrist, Surgeon (General), Medical Practitioners nfd and the 1996 figure includes Specialist Medical Practitioner.
The 2006 data for ‘Psychologist’ includes Clinical Psychologist, Psychotherapist, Educational Psychologist, Organisational Psychologist, Psychologist nfd and Psychologist nec. However, both the 1996 and 2001 figures are Clinical Psychologist and Psychotherapist combined.
The 2006 data for ‘Other health therapy professionals’ includes Chiropractor, Osteopath, Homeopath, Naturopath, Complementary Health Therapists not elsewhere classified (nec). The 2001 figure includes Chiropractor and Naturopath and the 1996 figure includes Chiropractor and Natural Therapy Professionals.
‘Health Promotion Officers’ could not be identified separately in 2001 and 1996 due to different occupation classifications. These were included in Community Workers in 2001 and 1996 and not included in the table.
The 2006 data for ‘Other health diagnostic and promotion professionals’ includes Health Professionals nfd and Health Diagnostic and Promotional Professionals nfd.
The 2006 data for ‘Health services managers’ includes Medical Administrators only. Health and Welfare Services Managers nec and Health and Welfare Services Managers nfd were included in Other. The 2001 data for Medical Administrators could not be published separately due to quality issues and has been included in Other. The 1996 figure is for Medical Administrators.
‘Nursing Support Worker and Personal Care Workers’ includes Therapy Aide, and in 2006 includes Hospital Orderly, which in 2001 and 1996 was grouped with Nursing Assistants and Personal Care Assistants occupations because there was no such category.
In 2006, ‘Other’ includes Medical Laboratory Scientist, Counsellors nec, Medical Laboratory Technician, Anaesthetic Technician, Cardiac Technician, Operating Theatre Technician, Pharmacy Technician, Medical Technicians nec, Optical Dispenser, Optical Mechanic, Diversional Therapist, Massage Therapist, Personal Carers and Assistants nfd, Special Care Workers nfd, Natural Remedy Consultant. The 2001 figure includes Health Information Manager, Medical Laboratory Scientist, Medical Technical Officer, Primary Products Inspector, Anatomist or Physiologist, Safety Inspector, Admissions Clerk, Weight Loss Consultant, Massage Therapist, Natural Remedy Consultant. The 1996 figure includes Health Information Manager, Medical Laboratory Scientist, Medical Laboratory Technician, Medical Technicians nec, Primary Products Inspector, Safety Inspector, Admissions Clerk, Weight Loss Consultant, Massage Therapist, Natural Remedy Consultant.
For some occupations, such as Nurses, Medical Practitioners, and Pharmacists, there are slight differences between the 2006 figures in this table and those in the Health and Community Services Labour Force 2006, and the Aboriginal and Torres Strait Islander Health Labour Force Statistics and Data Quality Assessment reports. These discrepancies are due to the impact of aggregating randomised data from data sets with different small cell distributions and the use of different occupation classifications (in the case of the second report).
3.13 Competent governance
Table 3.13-1: The data for this table come from the Office of the Registrar of Indigenous Corporations (ORIC). In 2014–15, compliance analysis was able to be completed for 86 companies incorporated under the Corporations (Aboriginal and Torres Strait Islander) Act 2006 and registered with ORIC.
Table 3.13-2 and Table 3.13-3: Refer to notes for measure 3.03 for information on the OSR data collection.
Table 3.13-3: Questions were not applicable for all services. Percentage was calculated based on the number of services that have a governing committee or board (163 of the 203 organisations providing primary health care services and 65 of the 67 organisations providing substance use services).
3.14 Access to services compared with need
Figure 3.14-1: Data come from the ABS and AIHW analysis of the ABS National Mortality Database and the 2015–16 Medicare data. Rate ratios for avoidable mortality (Refer to measure 1.22 for further notes and rate ratios for avoidable mortality data). Medicare data is for non-referred GP (total) claims. Indigenous data has been adjusted for under-identification in the Medicare Australia Voluntary Indigenous Identifier (VII) database. Data have been directly age-standardised using the 2001 Australian standard population, by 5-year grouping up to 75 years and over. Rate ratio is the rate for Indigenous Australians divided by the rate for non-Indigenous Australians. The data show that although Indigenous Australians are up to around 4 times as likely to die from causes considered potentially avoidable given effective and timely health care, they are only accessing health care at slightly higher rates than non-Indigenous Australians. This reflects a potentially large unmet need for health care among Indigenous Australians.
Figure 3.14-2 and 3.14-3: See notes for measure 3.05 for information on Medicare data. Indigenous rates have been adjusted for under-identification in the Medicare Australia VII database. Data directly age-standardised using the 2001 Australian standard population, by 5-year age group up to 75+. Financial year data presented. Each year the Indigenous time-series will be re-based using the VII patients up to June of the current year. Rebasing is seen as improving the time-series as the weighting sample size is increased each year and each patient identified will have all their MBS data flagged and weighted. If data is not rebased, then over time the comparison between time periods will become skewed.
Figure 3.14-3: Refer to notes for measure 3.03 for information on the OSR data collection. Average period change determined using regression analysis. Per cent change between 1999–2000 and 2014–15 based on the average annual change over the period. 2008–09 OSR data counts all auspice services individually when calculating rates, therefore caution should be exercised when comparing rates with earlier data collection periods. Eligible services only for 2007–08 services.
3.14-6: Refer to notes for measure 1.02 regarding hospitalisation data. Data includes public and private hospitals in all jurisdictions. Directly age-standardised using the Australian 2001 standard population. ‘Outer regional’ includes remote Victoria. ‘Remote’ excludes remote Victoria. Disaggregation by remoteness area is based on the ABS’ 2011 ASGS and relates to the patient’s usual residence. Rates by remoteness are calculated using the AIHW derived populations using the ABS population estimates and projections based on the 2011 Census.
Table 3.14-1: Self-reported data from the 2012–13 AATSIHS. More than one response allowed for ‘reason for not going to health care provider’; sum of components may exceed total. ‘Other health professionals’ include: nurse, sister, and Aboriginal (and Torres Strait Islander) health worker. For ‘Dentists’ data includes persons aged 2 years and over. For ‘Counsellors’ data includes persons aged 18 years and over; data excludes ‘not asked’. ‘Total Health Services’ includes persons who reported that they needed to go to a dentist (persons aged 2 years and over), Doctor, other health professional, hospital, or counsellor (persons aged 18 years and over) in the last 12 months, but did not go.
3.15 Access to prescription medicines
Figure 3.15-2: Constant price health expenditure for 2011–12 to 2014–15 is expressed in terms of 2013–14 prices. Indigenous population estimates used to estimate the expenditure figures are all derived from 2011 Census base. For Pharmaceutical Benefits Scheme (PBS) data, improvements in the quality of the voluntary Indigenous identifier (VII) has resulted in a change of methodology. In the previous report, the VII data was adjusted for under identification based on patient counts (e.g. in the previous report the adjusted identification for PBS expenditure was 1.5% Indigenous). For the 2013-14 data it was assumed that the VII was complete enough to use and no adjustment was done. This accounts for the drop in PBS Indigenous expenditure when comparing results from the previous report.
Figure 3.15-3: Per person expenditure in Remote/Very remote & All regions varies due to the different populations in these regions. Expenditure per person in All regions is based on the Australia-wide population. ‘Other PBS special supply’ includes all other Australian Government benefits paid on pharmaceuticals that have not been classified to the other categories, including S100 drugs (excluding the Aboriginal health services component) and other programmes such as the Community Pharmacy and Pharmacy Awareness and Targeted Assistance Pharmaceutical Aids and Appliances.
3.16 Access to after-hours primary care
Figures 3.16-1 and 3.16-2: Refer to notes for measure 3.05 for information on Medicare data. Data are directly age-standardised using the 2001 Australian standard population, by 5-year age group up to 75+. MBS items for after-hours care: 597, 598, 599, 600, 5000–5067 and 5200–5267. These data may double count after hours care provided in selected Emergency Departments claiming Medicare through Section 19.2.
Figure 3.16-3: Data from five combined BEACH years (April 2010–March 2011 to April 2014–March 2015 inclusive). ‘Other Australians’ includes non-Indigenous patients and patients for whom Indigenous status was not stated. ‘Other’ arrangements also include ‘referral to other services’ which was removed as an option from April 2009 onwards. Subtotal is less than the sum of the components as GPs can have more than one type of after-hours arrangement. There were 2,900 encounters with after-hours arrangements missing (230 with Indigenous patients and 2,670 with Other patients).
Figure 3.16-4 and Table 3.16-1: The data come from the National Non-Admitted Patient Emergency Department Care Database (NNAPEDCD). As the scope of the NNAPEDCD has changed since 2013–14, comparison with earlier years should be with caution. Data include all types of visits at emergency departments. For 2014–15, it is estimated that about 88% of emergency occasions of service were reported to the NNAPEDCD (based on emergency occasions of service reported to the NNAPEDCD for 2013–14). An estimate of coverage for 2015–16 has not been calculated as the most recent data on emergency services were for 2013–14, and are hence now two years out of date. In 2014–15, coverage varied and it was estimated to range from 100% in Major cities to 18% in Very remote areas.
The quality of the data reported for Indigenous status in emergency departments has not been formally assessed. In addition, the scope of the NNAPEDCD may not include some emergency services provided in areas where the proportion of Indigenous people (compared with other Australians) may be higher than average. Therefore, the information on Indigenous status presented should be used with caution. Please refer to Appendix A of Emergency department care 2015–16: Australian hospital statistics for more details. Data for the Australian Capital Territory were not available at the time the tables were prepared. After hours is defined as on Sunday, before 8am or from 12pm on a Saturday, or before 8am or from 6pm on a weekday.
3.17 Regular GP or health service
Self-reported data from the 2012–13 AATSIHS.
Figure 3.17-1 and 3.17-2: Excludes ‘don’t know’. ‘Other’ includes traditional healer and other health care provider. The list of specific health care providers may have posed problems for those who were confused between an Aboriginal Medical Service and a Community Clinic, or for those who simply did not know the kind of provider they usually visited.
Figure 3.17-3: Multiple response item. Proportions will not add to total. Some respondents may not have known which providers were available in their local area. The list of specific health care providers may have posed problems for those who were confused between an Aboriginal Medical Service and a Community Clinic. ‘Other’ includes Traditional Healer and other health care provider.
Figure 3.17-4: Patient experience reported by non-remote respondents aged 15 years and over who had seen a doctor or specialist in the previous 12 months. Regular source of health care category ‘Doctor/GP’ excludes doctors/GPs at an AMS or hospital, which are reported under their own category. AMS/CC represents Aboriginal Medical Service/Community Clinic.
3.18 Care planning for clients with chronic diseases
Figure 3.18-1: For information on Medicare data, refer to notes for measure 3.05.
Figure 3.18-2: Self-reported data from the AATSIHS (2012–13 NATSIHS component) and, for non-Indigenous Australians, the AHS (2011–12 NHS component).
Figures 3.18-3 and 3.18-4: Sourced from national Key Performance Indicators (nKPI) for Aboriginal and Torres Strait Islander primary health care data collection. Presents proportion of regular clients who have Type 2 diabetes and for whom a GP Management Plan (MBS item 721) was claimed within the previous 24 months and for whom a Team Care Arrangement (MBS item 723) was claimed within the previous 24 months Some results may differ to nKPI results published elsewhere due to revisions to the national database.
3.19 Accreditation
Figure 3.19-1: Data are from public hospitals only. Jurisdiction based on location of hospital. Data are reported for Qld, WA, SA and NT only. These four jurisdictions are considered to have adequate levels of Indigenous identification over the time period reported, although the level of accuracy varies by jurisdiction and hospital. Hospitalisation data for these jurisdictions should not be assumed to represent the hospitalisation experiences in other jurisdictions. ‘Other’ includes hospitalisations for non-Indigenous Australians and those for whom Indigenous status was not stated. The proportion is the number of separations in accredited hospitals by Indigenous status and state/territory divided by the total number of separations by Indigenous status and state/territory. Hospitals’ accreditation status may change over time. Interpretation of changes in hospital separations in accredited hospitals over time needs to be cautious. Excludes care types 7.3, 9 and 10 (newborn—unqualified days only, organ procurement, hospital boarder).
Figure 3.19-2: Data are from public hospitals only. Remoteness category based on location of hospital. Total includes 7,532 separations from hospitals where remoteness area was unknown/not stated. The proportion is the number of separations in accredited hospitals by Indigenous status and remoteness category divided by the total number of separations by Indigenous status and remoteness category.
Figure 3.19-2: Aboriginal and Torres Strait Islander proportions are based on Medicare Local populations. GPA+ data is for the period 2013 while AGPAL data is financial year 2012–13.
3.20 Aboriginal and Torres Strait Islander people training for health-related disciplines
Table 3.20-1 and Figures 3.20-1 and 3.20-2: These data come from the Higher Education Collections. Includes undergraduate, postgraduate, domestic and international university students. The data take into account the coding of Combined Courses to two fields of education. As a consequence, counting both fields of education for Combined Courses means that the totals may be less than the sum of detailed fields of education. For Table 3.20-1, ‘other’ includes those whose Indigenous status is unknown. Excludes unknown age group. Data published in corresponding tables in previous cycles incorrectly described completions for all courses rather than health-related courses only.
Table 3.20-2: Data sourced from NCVER National VET Provider collection. (Refer to notes for measure 2.06 regarding VET data). ‘Completions’ represents number of completions; students may complete more than one course. ‘Enrolled’ represents number of enrolments; students may be enrolled in more than one course. ‘Other’ includes those whose Indigenous status is unknown. Rates are calculated using Indigenous 2012 population projections based on the 2011 census for ages 15–64 years and for other Australians using the Australian 2012 population projections based on the 2011 census for ages 15–64. ‘n.p.’ means data not published (data cannot be released due to quality issues and confidentiality).
3.21 Expenditure on Aboriginal and Torres Strait Islander health compared to need
Figure 3.21-1: Some of the increase in Indigenous health expenditure per person may have been due to improvements in data collection rather than actual change. Due to the change in methodology from 2006 Census based population estimates to 2001 Census based population there has been a break in the time series from 2010-11 onwards. This has reduced per person health expenditure. This can be seen by comparing the result for 2010-11 using the 2006 based population with the lower finding for 2010-11 using the 2011 based population.
Figure 3.21-2: ACT per person expenditure estimates are not calculated because estimates for the ACT include substantial expenditures for NSW residents. As a result, the ACT population is not an appropriate denominator. Admitted patient expenditure adjusted for Aboriginal and Torres Strait Islander under-identification. Includes other recurrent expenditure on health, not elsewhere classified, such as family planning previously reported under ‘Other health services (n.e.c.)’. Health administration costs for NSW, Vic, SA and Tas are zero, as these jurisdictions have allocated administrative expenses into the functional expenditure categories.
Figure 3.21-3: Nominal expenditure in $m per year.
Figure 3.21-4: ‘Primary care’ is defined as services that are provided to the whole population and initiative by a patient. ‘Secondary and tertiary services’ are those generated within the health system through a referral such as specialist services. ‘Community health services’ includes other recurrent expenditure on health, not elsewhere classified, such as family planning previously reported under ‘Other health services (nec)’.
Figure 3.21-5: ‘GP’ includes general practitioners and vocationally registered general practitioners. ‘Other unreferred’ includes enhanced primary care, practice nurses and other unreferred services. For Medicare benefits (MBS) data, improvements in the quality of the voluntary Indigenous identifier (VII) has resulted in a change of methodology. In the previous report, the VII data was adjusted for under identification based on patient counts. For the 2013-14 data it was assumed that the VII was complete enough to use and no adjustment was done.
3.22 Recruitment and retention of staff
Figure 3.22-1: Data is from the National Health Workforce Data Set (NHWDS) medical practitioners 2015 (AIHW publication). FTE is based on total weekly hours worked. Standard working week is 40 hours. Data excludes provisional registrants.
Figure 3.22-2: Data from the Rural Workforces Agencies National Minimum Data Set. Excludes 815 GPs for whom remoteness category or length of stay in current practice was unknown. Remoteness categories based on 2011 Australian Statistical Geography Standard (ASGS).
Figures 3.22-3 and 3.22-4: Refer to notes for measure 3.03 for information on the OSR data collection. Figure 3.22-3: Data sourced from OSR data collection 2014–15 (AIHW publication Table B36). The 2014–15 collection includes 203 primary health-care organisations. Vacancies are calculated as a proportion of total funded FTE for health/clinical positions and administrative/support positions.
Figure 3.22-4: Data sourced from SAR, DSR and AIHW OSR data collections. Number of vacant FTE positions as a proportion of total funded FTE positions (both occupied and vacant). Since 2008–09, OSR data counts all auspice services individually when calculating rates, therefore caution should be exercised when comparing rates with earlier data collection periods.