Australian Institute of Health and Welfare (2021) Geographical variation in disease: diabetes, cardiovascular and chronic kidney disease, AIHW, Australian Government, accessed 25 March 2023.
Australian Institute of Health and Welfare. (2021). Geographical variation in disease: diabetes, cardiovascular and chronic kidney disease. Retrieved from https://www.aihw.gov.au/reports/chronic-disease/geographical-variation-in-disease
Geographical variation in disease: diabetes, cardiovascular and chronic kidney disease. Australian Institute of Health and Welfare, 03 August 2021, https://www.aihw.gov.au/reports/chronic-disease/geographical-variation-in-disease
Australian Institute of Health and Welfare. Geographical variation in disease: diabetes, cardiovascular and chronic kidney disease [Internet]. Canberra: Australian Institute of Health and Welfare, 2021 [cited 2023 Mar. 25]. Available from: https://www.aihw.gov.au/reports/chronic-disease/geographical-variation-in-disease
Australian Institute of Health and Welfare (AIHW) 2021, Geographical variation in disease: diabetes, cardiovascular and chronic kidney disease, viewed 25 March 2023, https://www.aihw.gov.au/reports/chronic-disease/geographical-variation-in-disease
Chronic kidney disease (CKD) estimates were based on measures of estimated glomerular filtration rate (eGFR) and albumin/creatinine ratio (ACR) from biomedical blood and urine samples taken as part of the 2011–12 AHS:NHMS. These 2 measures are combined to identify signs of CKD staging (see ‘CKD biomedical markers’). To confirm kidney disease, the reduction of kidney function marked by a low eGFR or signs of a damaged kidney detected by the presence of blood in the urine (haematuria) or the presence of albumin protein in the urine (albuminuria) should persist for at least 3 months (KHA 2019).
The AHS biomedical data provide prevalence estimates for signs of CKD. CKD is usually categorised into 5 stages according to the level of kidney function or the extent of damage in the kidney indicated by results of CKD biomarkers. The product suite does not report on the different stages of CKD but the overall prevalence of biomedical signs of CKD are referred to as the prevalence of CKD.
CKD biomedical markers:
The direct estimates of CKD prevalence were derived from ABS DataLab for state and territory and national levels, excluding survey population records where eGFR and ACR results were both missing (7% of the adult weighted biomedical sample).
CKD prevalence estimates for PHNs and PHAs were derived from modelling by the ABS using logistic regression. Note that remote and very remote SA2 areas and areas belonging to discrete Indigenous communities were excluded from the survey sample. CKD estimates for PHA including these areas have to be interpreted with caution.
For more details on the ABS method, refer to ABS AHS 2011–12 Modelled estimates for small areas: Explanatory notes in Technical notes.
Diabetes is a chronic condition marked by high levels of glucose in the blood. Type 2 diabetes is the most common form of diabetes. People with type 2 diabetes produce insulin, but do not produce enough, and/or cannot use it effectively. Type 2 diabetes is largely preventable with lifestyle factors such as physical inactivity, poor nutrition, overweight or obesity and high blood pressure closely related to the occurrence of type 2 diabetes.
The prevalence of type 2 diabetes was derived from the NDSS administrative data set as the number of NDSS registrants with type 2 diabetes. NDSS registrants with type 2 diabetes recorded were reclassified as having type 1 if:
This may result in a small proportion of registrants with a true type 2 diagnosis being reclassified to type 1 diabetes and will result in discrepancies with published data from the NDSS.
Heart, stroke and vascular diseases (HSVD) is a subset of cardiovascular disease (CVD) including the most common and serious types of CVD: coronary heart diseases (CHD) (angina, heart attack and other heart diseases)—also known as ischaemic heart disease—cerebrovascular diseases (including stroke), oedema, heart failure and diseases of arteries, arterioles and capillaries.
HSVD is reported in the prevalence dashboards (aligning with ABS NHS publications and data). The broader definition (all CVD) is reported in the hospitalisation and deaths dashboards.
Direct estimates of HSVD prevalence were derived from ABS DataLab for state and territory and for the whole country using the ABS 2017–18 NHS.
HSVD prevalence estimates for PHNs and PHAs were modelled by the ABS using logistic regression. Note that for PHA estimates, SA2 areas were excluded where most of the private dwelling population was classified as Very remote or belonged to discrete Indigenous communities, resulting in an underestimation of HSVD estimates for PHAs covering these areas. For more details on the ABS method, refer to ABS NHS 2017–18 Modelled estimates for small areas: Explanatory notes in Technical notes.
High blood pressure is a risk factor for stroke, ischaemic heart disease, heart failure and CKD. In 2015, high blood pressure was the fourth-leading risk factor contributing to disease burden (AIHW 2019a).
Uncontrolled high blood pressure is based on the measured blood pressure ranges from the survey, where people were classified as having uncontrolled high blood pressure if their systolic blood pressure was greater than or equal to 140 mmHg or their diastolic blood pressure was greater than or equal to 90 mmHg.
This measure excluded people who were taking blood-pressure-lowering medication and had their blood pressure under control with normal readings at the time of the survey.
In 2017–18, 31.6% of respondents aged 18 years and over did not have their blood pressure measured. For these respondents, blood pressure was imputed. For more information, see Appendix 2: Physical measurements in the 2017–18 National Health Survey (ABS 2018c).
The state and territory direct estimates were based on measured and imputed blood pressure values while the PHA and PHN estimates were modelled. The modelled estimates used both measured and imputed values of blood pressure. For more details on the ABS method, refer to ABS NHS 2017–18 Modelled estimates for small areas: Explanatory notes in Technical notes.
Overweight and obesity refers to excess body weight. Excess weight, especially obesity, is a major risk factor for CVD, type 2 diabetes, high blood pressure and other chronic conditions. Overweight and obesity categories are based on the body mass index (BMI), values derived by dividing a person’s weight in kilograms by the square of their height in metres (Table 4.1). In this product, BMI applies to the adult population (aged 18+) and was based on measured and imputed height and weight values of all survey respondents from the ABS 2017–18 NHS.
BMI (kg/m2)
Classification
Less than 18.5
Underweight
18.5 to less than 25
Healthy weight range
25 to less than 30
Overweight
30 or more
Obese
Source: WHO 2000.
In 2017–18, 33.8% of respondents aged 18 and over did not have their height and or weight measured. For these respondents, height and weight was imputed. For more information, see Appendix 2: Physical measurements in the 2017–18 National Health Survey (ABS 2018c).
The state and territory direct estimates were based on measured and imputed BMI while the PHA and PHN estimates were modelled. The modelled estimates used both measured and imputed values for the BMI. For more details on the ABS method, refer to ABS NHS 2017–18 Modelled estimates for small areas: Explanatory notes in Technical notes.
People who do not do sufficient physical activity have a greater risk of CVD, type 2 diabetes and osteoporosis. Being physically active improves mental and musculoskeletal health and reduces other risk factors such as overweight and obesity, high blood pressure and high blood cholesterol.
Australia’s Physical Activity and Sedentary Behaviour Guidelines (the Guidelines) are a set of recommendations outlining the minimum levels of physical activity required for health benefits, as well as the maximum amount of time one should spend on sedentary behaviours to achieve optimal health outcomes (Department of Health 2019):
The Guidelines recommend:
For the purposes of this report, people were considered insufficiently physically active if they met the criteria below based on self-reported data from the 2017–18 NHS:
The state and territory direct estimates were based on results from the ABS 2017–18 NHS for those aged 18 and over who answered the relevant questions, excluding those with incomplete or missing information (less than 1% of adults weighted survey sample) while the PHA and PHN estimates were modelled. For more details on the ABS method, refer to ABS NHS 2017–18 Modelled estimates for small areas: Explanatory notes in Technical notes.
Tobacco smoking is one of the largest preventable causes of death and disease in Australia, responsible for 9.0% of the total burden of disease in Australia in 2011. Tobacco smoking is associated with an increased risk of heart disease, diabetes, stroke, kidney disease and other conditions such as cancer, eye disease and respiratory conditions.
Current tobacco smoking refers to a person who reported smoking manufactured (packet) cigarettes, roll-your-own cigarettes, cigars and pipes, daily or at least once a week but excluding chewing tobacco, electronic cigarettes (and similar) and smoking of non-tobacco products. Note that current tobacco smoking encompasses both people who smoke less frequently than daily and daily smokers—a larger group than for ‘current daily smoking’. See details in the ABS National Health Survey: users’ guide, 2017–18.
The same question items were asked in the 2 surveys and pooled into 1 data set—the ABS’s 2017–18 Smoker status, Australia—to increase sample size and produce more robust estimates.
The state and territory direct estimates were based on results from the survey while the PHA and PHN estimates were modelled. For more details on the ABS method, refer to ABS NHS 2017–18 Modelled estimates for small areas: Explanatory notes in Technical notes.
The age composition of a population differs greatly across geographic regions of the states and territories and this has an influence on the size of the population at risk.
The measure reported is the proportion of people aged 65 and over by the geographical areas in scope in 2016.
Residential aged care data from the National Aged Care Data Clearinghouse contain informative statistics on the population living permanently in aged care residence.
The measure reported is the proportion of the population aged 70 and over living permanently in residential aged care as at June 2018 by all geographical areas in the scope of this project. Disease prevalence estimates sourced from NHSs reflect only the prevalence of the population usually living in private dwellings. The extent to which the prevalence estimates potentially underrepresent the actual local population is useful information for planning and public health interventions.
The measure reported is the overall proportion of the Indigenous population by geographical area in 2016.
In the Census, each person who speaks a language other than English at home is asked how well they speak English (referred to as ENGP in the Census dictionary). The measure reported is the percentage of persons speaking a language other than English at home who reported their English proficiency level as ‘not well’ or ‘not at all’.
Census information was collected on the highest level of education attained (referred to as HEAP in the Census dictionary). This is a single measure of a person’s overall level of educational attainment, whether it be a school or non-school qualification.
For the purposes of this project, the measure reported is the proportion of people aged 25–74 whose overall level of educational attainment falls in the lowest (secondary or lower education, certificates I, II, including people who did not attend school) and highest (bachelor degree or higher) categories for comparison. Not all education levels (e.g., diploma, advanced diploma or certificates III and IV) are reported, hence the sum of the 2 proportions may not add up to 100.
The IRSD is 1 of 4 area-based socioeconomic indexes developed by the ABS using information collected in the Census of Population and Housing. The IRSD represents the socioeconomic conditions of geographic areas by measuring aspects of relative disadvantage. The IRSD scores each area by summarising attributes of their population, such as low income, low educational attainment, high unemployment, and jobs in relatively unskilled occupations. A low score indicates relatively greater disadvantage while a high score indicates a relative lack of disadvantage. The IRSD reflects the overall or average socioeconomic position of the population of an area; it does not show how individuals living in the same area might differ from each other in their socioeconomic position nor does it show the relative disadvantage between individuals living in different areas (ABS 2018a).
Based on the IRSD, population-based quintile groups were used to report on the proportion of sub-populations of interest who live in each quintile. Five equal groups were formed based on the population of these areas, with quintile 1 being the most disadvantaged socioeconomic group through to quintile 5, the least disadvantaged.
At the national level each population quintile roughly represents one-fifth of the population. As such, 20% in each quintile group is used as a benchmark for comparison with socioeconomic group population distributions in smaller areas. The population in small areas is unevenly distributed across socioeconomic groups and may fluctuate between 0% and 100%, reflecting differences in socioeconomic disadvantage between areas. This measure is presented for state and territory and PHAs only. The highest and lowest categories (least and most disadvantage) are provided only for comparison in the Population characteristics graph, hence the sum of the 2 proportions may not add to 100.
For further information on Socio-Economic Indexes for Areas (SEIFA) .
Unemployment is based on labour force status information collected during the Census (referred as LFSP in the Census dictionary). LFSP measures employment status among individuals aged 15 and over in the labour force.
The measure reported is the proportion of people who are unemployed and looking for full or part-time work aged 15–64.
The access to internet measure (referred as NEDD in the Census dictionary) collected in the Census is based on occupied private dwelling. The measure reported is the percentage of occupied private dwellings with no access to internet.
Households were classified as overcrowded if they were estimated to require at least 1 bedroom or more than they have. It compares the number of bedrooms in a dwelling together with household demographics such as the number of usual residents, their relationships to one another, as well as their age and sex. The criteria used to assess the suitability of dwelling utilisation, were based on the Canadian National Occupancy Standard and are as follows.
Hospitalisation counts are counts of admitted patient episodes of care and not individual patients. This can include multiple hospitalisations experienced by the same individual if the individual had more than 1 hospitalisation for a vascular disease in the given time period.
For this report, hospitalisations referred to episodes of care where the selected condition was recorded as:
The following hospitalisation records were excluded from the analysis:
Hospital diagnosis data used ICD-10-AM (ninth and 10th editions). The ICD-10-AM diagnosis codes for vascular disease are included in Table 4.2.
Condition
ICD-10-AM codes
CKD (excluding dialysis)
Diabetic nephropathy
Hypertensive kidney disease
Glomerular diseases
Kidney tubule-interstitial diseases
Chronic kidney failure
Unspecified kidney failure
Other disorders of kidney and ureter
Congenital malformations
Complications related to dialysis and kidney transplant
Preparatory care for dialysis
Kidney transplant and dialysis status
E10.2, E11.2, E13.2, E14.2
I12, I13, I15.0, I15.1
N00–N08
N11, N12, N14, N15, N16
N18
N19
N25–N28, N39.1,N39.2
Q60–Q63
T82.4, T86.1
Z49.0
Z94.0, Z99.2
Dialysis
Haemodialysis
Peritoneal dialysis
Z49.1
Z49.2
Acute kidney injury (AKI)
Acute nephritis syndrome
Acute tubule-interstitial nephritis
Acute kidney failure
Diabetes with other specified kidney complication including acute kidney failure/impairment and medullary (papillary) necrosis
Postpartum acute kidney failure and kidney failure after abortion and ectopic or molar pregnancy
Post procedural kidney failure
N00
N10
N17
E10.29,E11.29,E13.29,E14.29
O90.4,O08.4
N99.0
All cardiovascular disease
I00–I99
Data have been suppressed if the:
To fully capture the contribution of CKD, AKI, and type 2 diabetes to deaths from these conditions, death records were extracted for people who had these conditions listed on the death certificate as the underlying or associated cause of death:
Cardiovascular deaths were enumerated only when CVD was listed as the underlying cause of death.
Death records for which information on sex, age, or place of usual residence was missing, were excluded in the calculation of rates or statistics by geography but included in the totals for persons, all ages and all Australia. In addition, Australian death counts include deaths from Other territories, such as Christmas Island, Cocos (Keeling Island), Jervis Bay Territory and with unknown usual residence.
Cause of death is coded according to the rules set forward in the various versions of the ICD. The relevant codes for CKD, AKI, CVD and diabetes deaths using in this product are included in Table 4.3.
ICD-10 codes
Chronic kidney disease
E10.2, E11.2, E12.2, E13.2, E14.2
N00–N07
N11, N12, N14, N15
N25–N28, N39.1, N39.2, E85.1, D59.3, B52.0
T82.4,T86.1
Type 2 diabetes
E11,O24.1
Cardiovascular disease
Death rates are based on 5 years of combined mortality data from 2013 to 2017, due to the small number of diabetes and CKD deaths. At the PHN-area level, diabetes and CKD mortality rates are presented by broad age groups (under 55, 55–74 and 75 and over) and sex, while at the PHA level, data are available only for persons.
ABS 2018a. Socio-Economic Indexes for Areas (SEIFA): technical paper. ABS cat. no. 2033.0.55.001. Canberra: ABS.
ABS 2018c. National Health Survey: first results, 2017–18. ABS cat. 4364.0.55.001. Canberra: ABS.
AIHW 2019a. Australian Burden of Disease Study: impact and causes of illness and death in Australia 2015. Australian Burden of Disease Study series no. 19. Cat. no. BOD 22. Canberra: AIHW.
Department of Health 2019. Australia's Physical Activity and Sedentary Behaviour Guidelines and the Australian 24-Hour Movement Guidelines. Canberra: Department of Health.
Kidney Health Australia 2019. National Strategic Action Plan for Kidney Disease.
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