NSW Population Health Survey (SAPHaRI). Centre for Epidemiology and Evidence, NSW Ministry of Health.
The indicator shows self-reported data collected through Computer Assisted Telephone Interviewing (CATI). Estimates were weighted to adjust for differences in the probability of selection among respondents and were benchmarked to the estimated residential population using the latest available Australian Bureau of Statistics mid-year population estimates. Adults are defined as persons aged 16 years and over in the NSW Population Health Survey.
In order to address diminishing coverage of the population by landline telephone numbers (<85% since 2010), a mobile phone number sampling frame was introduced into the 2012 survey.
Remote* includes very remote.
LL/UL 95%CI = lower and upper limits of the 95% confidence interval for the point estimate.
The NSW Ministry of Health has conducted the Adult Population Health Survey (since 1997) and the Child Population Health Survey (since 2001) through the New South Wales Population Health Survey, an ongoing survey of the health of people in NSW using computer-assisted telephone interviewing (CATI). The main aims of the surveys are to provide detailed information on the health of adults and children in NSW and to support planning, implementation and evaluation of health services and programs in NSW.
The survey instruments include question modules on health behaviours, health status, and other associated factors. The methods and all questions are approved for use by the NSW Population and Health Services Research Ethics Committee. While some questions are collected annually, other questions are collected less frequently. The instrument is translated into 5 languages: Arabic, Chinese, Greek, Italian and Vietnamese.
The target population for the survey is all state residents living in private households. The target sample was approximately 1,000 persons in each of the health administrative areas (total sample 8,000-16,000 depending on the number of administrative areas).
From 1997 to 2010 the random digit dialling (RDD) landline sampling frame was developed as follows. Records from the Australia on Disk electronic white pages (phone book) were geo-coded using MapInfo mapping software. The geo-coded telephone numbers were assigned to statistical local areas and area health services. The proportion of numbers for each telephone prefix was calculated by area health service. All prefixes were expanded with suffixes ranging from 0000 to 9999. The resulting list was then matched back to the electronic phone book. All numbers that matched numbers in the electronic phone book were flagged and the number was assigned to the relevant geo-coded area health service. Unlisted numbers were assigned to the area health service containing the greatest proportion of numbers with that prefix. Numbers were then filtered to eliminate continuous non-listed blocks of greater than 10 numbers. The remaining numbers were then checked against the business numbers in the electronic phone book to eliminate business numbers.
From 2011 onwards the RDD landline sampling frame was developed as follows: Australian Communications and Media Authority exchange district and charge zone prefixes were generated for each of the strata (that is Local Health Districts introduced in January 2011) using “best fit” postcode (ACMA 2011). All prefixes were expanded with suffixes ranging from 0000 to 9999. The sample was then randomly ordered within each stratum. The estimated numbers required for each stratum was then forwarded to Sampleworx, who used proprietary software to test each numbers current status (valid, invalid or unknown and business, non-business or unknown). The resulting valid non-business and valid unknown numbers were used for the survey.
From 2012 onwards mobile only phone users were included into the surveys using an overlapping dual-frame design, which incorporates three groups of respondents: landline only users, mobile only users and landline and mobile users.
The RDD mobile sampling frame was developed by Sampleworx and included using all known Australian mobile prefixes. Sampleworx used proprietary software to test each number to identify valid and invalid numbers. A random sample of valid mobile numbers was then provided for use for the survey.
The introduction of this design was prompted by the increasing numbers of mobile-only phone users in the general population. Because this design increases the representativeness of the survey sample the production of unbiased estimates over time is also improved. This improvement has been confirmed by an analysis of unweighted estimates, which indicated that a greater proportion of younger people, of males, and of people born overseas participated in the mobile sample compared with the landline sample. Further, comparison of the demographic characteristics of the survey sample for the first quarter of 2012 with the NSW population showed that the NSW Population Health Survey was more representative of the NSW population than the previous sample (Barr et al. 2012).
Due to this change in design, the 2012 NSW PHS estimates reflect both changes that have occurred in the population over time and changes due to the improved design of the survey.
When considering significant differences over time excluding the 2010 and 2011 data points ensures that all of the estimates are from sampling frames that had adequate coverage of the population, that is 85% or more.
When the Australia on Disk electronic white pages became available, reliable introductory letters were sent to the selected households (1997 to 2008). Households were contacted using random digit dialling. Depending on the frame either one person from the household was randomly selected or the mobile phone holder was selected for inclusion in the survey.
Interviews are carried out continuously between February and December each year. An 1800 freecall contact number and website details are provided to potential respondents, so they can verify the authenticity of the survey and ask any questions regarding the survey. Trained interviewers at the Health Survey Program CATI facility carried out interviews until the end of 2014. For 2015, the NSW Population Health Survey was outsourced to McNair Ingenuity Research Pty Ltd, which is a social and market research company. All protocols related to the collection of respondent data have been implemented by McNair.
Up to 7 calls are made to establish initial contact with a household, and up to 5 calls are made in order to contact a selected respondent. Respondents reached by a landline phone number undergo a within-household selection process, where each member of the household has an equal chance of selection for interview. Respondents reached via mobile phone do not undergo this household selection process. Where a child under the age of 16 has been chosen within the household, the parent or main carer for that child completes the interview on their behalf. When an adult respondent that lives in a household with a child or children is selected for interview, at the end of their interview, they are offered to opportunity to complete a secondary interview about one of their children. In 2015, approximately 41% of all primary adult respondents living in households with at least one child under the age of 16 took up this option. If a parent completing an interview about their children is unsure of their child’s height and/or weight, the respondent is offered the opportunity to be contacted at a later date for this information.
For analysis, the survey sample was weighted to adjust for differences in the probabilities of selection among respondents. Post-stratification weights were used to reduce the effect of differing non-response rates among males and females and different age groups on the survey estimates. These weights were adjusted for differences between the age and sex structure of the survey sample. Population data based on Australian Bureau of Statistics estimates and population projections based on data from the NSW Department of Planning and Infrastructure have been used to calibrate weights to the population within each health administrative area. and the Australian Bureau of Statistics latest mid-year population estimates (excluding residents of institutions) for each health administrative area.
Call and interview data were manipulated and analysed using SAPHaRI and SAS version 9.4 (SAS). The Taylor series expansion method was used to estimate sampling errors of estimators based on the stratified random sample. The 95 per cent confidence interval provides a range of values that should contain the actual value 95 per cent of the time.
Estimates were smoothed using least-squares spline transformation (CEE, Adult survey methods: web page).
Further information on the methods and weighting process is provided elsewhere (CEE, Child survey methods: web page).
A proportional hazard regression model with time equal to one unit using PROC SURVEYREG in SAS software was fitted. PROC SURVEYREG produces relative risks while taking into account the complex survey design; the strata and weights. The strata are a combination of Local Health District and year. The weights are based on the probability of selection in the survey and the age and sex structure of the population each year. For trend analysis, the weights are recalibrated to te 2001 Australlian Standard Population by five year age groups to age standardise the analysis. Age-sex standardisation was implemented across the complete survey file (both adult and child records). Separate models were fitted for each sex, and each model had year as the independant variable and the binary indicator as the dependant variable.
Estimated annual rates of change for health indicators (and associated 95% confidence intervals) were calculated from these models as relative differences. If the confidence intervals for the relative difference did not overlap a value of 1, the change was considered statistically significant.
In the reporting of trend analysis results on the topic landing page data summary tables (such as http://www.healthstats.nsw.gov.au/IndicatorGroup/ChildObesityTopic ), up and down arrows are used to show statistically significant increasing and decreasing annual rates of change. If the rate of change is not statistically significant, the trend is considered stable as illustrated by horizontal arrows. For statistically significant trends, the percentage point difference between modelled prevalence for the most recent year of data and that for 5 (short term trend) or 10 years (long term trend) prior. The short term percentage point difference is based on the model incorporating the 5 most recent years of data. The long term trend analysis is based on the model incorporating yje 10 most recent years of data. For context, the raw prevalence (and associated 95% confidence interval) estimated from the survey for the most recent year is also reported in the data summry tables.
Australian Bureau of Statistics. Standard Population for Use in Age-Standardisation Table (Cat. no. 3101.0), 2013
Australian Communications and Media Authority (ACMA). Communications report 2010-11 series: Report 2 – Converging communications channels: Preferences and behaviours of Australian communications users. Commonwealth of Australia, 2011. Available at http://www.acma.gov.au/
Barr ML, Ritten JJ, Steel DG, Thackway SV. ‘Inclusion of mobile phone numbers into an ongoing population health survey in New South Wales, Australia: design, methods, call outcomes, costs and sample representativeness’. BioMed Central: Medical Research Methodology 2012, 12:177 (22 November 2012). Available at www.biomedcentral.com/1471-2288/12/177.
Centre for Epidemiology and Evidence. NSW Adult Population Health Survey Methods. CEE, NSW Ministry of Health. Available at http://www.health.nsw.gov.au/surveys/adult/Pages/default.aspx
Centre for Epidemiology and Evidence. NSW Child Population Health Survey Methods. CEE, NSW Ministry of Health. Available at http://www.health.nsw.gov.au/surveys/child/Pages/default.aspx
PitneyBowes Software. MapInfo (software). PBS as MapInfo Corporation: version 1997. Available at www.pbinsight.com.au
Sampleworx Pty Ltd. Available at http://www.sampleworx.com.au
SAS Institute. The SAS System Enterprise Guide version 7.15 (software). Cary, NC: SAS Institute Inc., 2017. Available at www.sas.com
United Directory Systems. Australia on Disk (software). UDS: version 2004. Available at www.uniteddirectorysystems.com
The indicator includes those who had either diabetes or high blood glucose and did not have gestational diabetes.
The questions used to define the indicator were: Have you ever been told by a doctor or hospital you have diabetes? Have you ever been told by a doctor or hospital you have high blood glucose? If female, Were you pregnant when you were first told you had diabetes or high blood glucose? Have you ever had diabetes or high blood glucose apart from when you were pregnant?
• 11.1% of adults aged 16 years and over (12.6% of men and 9.7% of women) had diabetes or high blood glucose as estimated from the 2018 NSW Adult Population Health Survey (self-reported using Computer Assisted Telephone Interviewing or CATI). It is likely that there are many people with diabetes in NSW who are unaware they have it.
• Prevalence estimates have been increasing over time.
• Diabetes prevalence increases with age and socioeconomic disadvantage and diabetes is more prevalent among Aboriginal people.
• In NSW between 2012-13 and 2018-19, the hospitalisation rate for diabetes as a principal diagnosis did not change substantially. In 2018-19, the rate of hospitalisation for diabetes as a principal diagnosis was 162.5 per 100,000 population (187.1 per 100,000 population for males and 141.5 per 100,000 population for females). In 2017-18, there was an average of 1.3 hospitalisations for diabetes per person in NSW.
• While Type 2 diabetes accounts for up to 90% of all diabetes cases in the community, it accounted for around 66% of all hospitalisations for diabetes in 2018-19. Type 1 diabetes accounted for around 27% of hospitalisations and gestational diabetes for around 6%.
• While diabetes was the principal (underlying) cause of around 3% of all deaths in NSW in 2017 (1,609 deaths), around 6% of all deaths in that year were directly related to diabetes (2,930 deaths) and 11% (5,922) involved diabetes in some way. Cardiovascular disease was the most common cause of death among people with diabetes.
As estimated from the 2017-18 National Health Survey: First Results, 4.9% of adults aged 18 years and over (5.5% of men and 4.3% of women) had diabetes.
Diabetes mellitus is a group of closely related chronic conditions characterised by high blood sugar (glucose) levels. In uncontrolled diabetes, glucose builds up in the bloodstream and leads to a range of short- and long-term problems, including damage to vital organs.
Diabetes and its associated complications contribute significantly, both directly and indirectly, to mortality, morbidity, poor quality of life of sufferers and carers and the cost of health care. Experts agree that diabetes now represents one of the most challenging public health problems of the 21st century worldwide (Tanamas et al. 2013). Diabetes and cardiovascular conditions together are the causes of about one-third of all years of life lost due to premature death and about one-fifth of all years lost to premature death or years lived with a disability in NSW. The contribution of diabetes to the total disease burden in Australia in 2011 was 2.3% (AIHW 2016).
There are three main forms of diabetes mellitus: Type 1 diabetes, Type 2 diabetes and gestational diabetes. Type 1 diabetes is estimated to be present in 10-15% of people with diabetes and is caused by a combination of genetic and environmental factors, but there are no known modifiable risk factors for this form of diabetes. Type 2 diabetes accounts for about 85-90% of all diabetes cases and primarily affects people older than 40 years. Several modifiable risk factors play a role in the onset of Type 2 diabetes, including obesity, physical inactivity and poor nutrition, as does genetic predisposition and ageing. Gestational diabetes mellitus occurs during pregnancy in about 3-8% of females not previously known to have diabetes. It is a temporary form of diabetes and usually resolves after the baby is born (Beers et al. 1999). The fourth, minor group, includes diabetes secondary to other conditions, for example diseases of the pancreas or drug-induced or chemical-induced diabetes.
Diabetes can lead to acute and chronic complications. Acute metabolic disturbances can lead to coma. Chronic high blood glucose levels (hyperglycaemia) are associated with long-term damage, dysfunction and failure of virtually every body organ, especially the heart and blood vessels, eyes, kidneys and nerves. Consequently, diabetes predisposes those suffering from it to many severe conditions, including cardiovascular disease, as well as visual loss, amputations and renal failure.
Sustained, individualised management substantially reduces the risk of complications in people with diabetes. A combination of diet, exercise and medication (including insulin injections) is used in combination with very frequent monitoring of blood glucose levels and other risk factors (for example blood lipids and blood pressure) and regular screening for complications.
In the past, Type 1 diabetes was called 'insulin-dependent diabetes mellitus' (IDDM) or 'juvenile-onset' and Type 2 diabetes was called 'non-insulin-dependent diabetes mellitus' (NIDDM). However, as insulin is often used to treat patients with Type 2 diabetes, the old terminology has been discouraged by the WHO since 2000 (NCCH Volume 5 2000).
Diabetes mellitus and diabetes insipidus are completely different conditions. Diabetes insipidus (DI, Central diabetes insipidus) is a temporary or chronic disorder that causes sufferers to excrete excessive quantities of otherwise normal urine and excessive thirst. Excessive urination and thirst are the features in common with diabetes mellitus , hence a Greek word for syphon (diabetes) is used in the name of both conditions. Diabetes insipidus is caused by deficiency of hormone called vasopressin (ADH) and is much less common than diabetes mellitus (Beers MH et al. 1999). This topic and data in the Report refer to diabetes mellitus.
Tanamas SK et al. The Australian diabetes, obesity and lifestyle study (AusDiab). Baker IDI Heart and Diabetes Institute, 2013.
Beers MH, Berkow R. The Merck manual of diagnosis and therapy. West Point: Merck & Co, 1999.
Australian Institute of Health and Welfare. Australian Burden of Disease Study: Impact and causes of illness and death in Australia 2011. Australian Burden of Disease Study series no. 3. BOD 4. Canberra: AIHW, 2016.
National Centre for Classification in Health. The International statistical classification of diseases and related health problems, 10th Revision, Australian Modification (ICD-10-AM). Volume 5. Sydney: NCCH, 2000.
The best way to reduce the harm caused by diabetes is by preventing the onset of Type 2 diabetes. Diabetes shares many modifiable risk factors with other lifestyle-related chronic diseases such as cardiovascular diseases. These include smoking, physical inactivity, poor diet, too much alcohol and being overweight. This means that strategies related to the prevention, early detection and optimal management of these risk factors will lead to better health outcomes for people with Type 2 diabetes and other lifestyle-related chronic diseases.
NSW Health provides support for the prevention and optimal management of Type 2 diabetes through a broad range of programs:
The NSW Healthy Eating and Active Living (HEAL) Strategy 2013-2018 provides a whole of government framework to promote and support healthy eating and active living in NSW and to reduce the impact of lifestyle-related chronic disease. Further information on the NSW HEAL strategy is available from http://www.health.nsw.gov.au/heal/Pages/default.aspx.
Get Healthy at Work is a new NSW Government initiative that aims to improve the health of working adults. It focuses on healthy weight, physical activity, healthy eating, active travel, smoking and harmful alcohol consumption. Further information on the NSW Get Healthy at Work initiative is available from http://www.health.nsw.gov.au/healthyworkers/pages/default.aspx
This free, confidential telephone-based coaching service supports NSW adults to make sustained improvements in healthy eating, physical activity, and achieving and maintaining a healthy weight. Further information on the Get Healthy Information and Coaching Service is available from http://www.gethealthynsw.com.au
This initiative is intended to support informed, healthier food choices in NSW. As of 1 February 2012, major food retailing outlets with 20 or more stores in NSW and more than 50 stores nationally are required to include information about the kilojoule (kj) content of standard products on their menu boards. The 8700 Find Your Ideal Figure website provides information, links, tips, online calculators and tools, including a mobile phone application. Further information is available from www.8700.com.au.
The built environment can play an important role in promoting and supporting healthy behaviours. Research demonstrates the link between the modern epidemic of lifestyle-related chronic diseases such as cardiovascular diseases and Type 2 diabetes, and the way we live in the built environment. Car-dominated transport, coupled with a lack of active transport options (walking, cycling and public transport), reduce opportunities for physical activity. Sprawling low-density residential developments with poor access to amenities including healthy, fresh food and poor connectivity can negatively impact on both mental and physical health.
The NSW Agency for Clinical Innovation established the Endocrine Network in 2007 to assist clinicians working with patients who have diabetes or obesity to develop best practice guidelines for treatment and to provide direction for diabetes and obesity research, education and management. The Endocrine Network has a number of priority areas including the development of the NSW Model of Care for Diabetes Mellitus covering the identification, treatment and management of people with Type 1 and 2 diabetes, gestational diabetes and diabetes in pregnancy. Further information on the Endocrine Network is available from http://www.aci.health.nsw.gov.au/networks/endocrine
The NSW Chronic Disease Management Program (CDMP) aims to deliver an integrated, patient focused, whole person approach to effective health management to improve the quality of life of people with chronic and complex conditions, their carers and families and to prevent unplanned and avoidable hospital admissions. It achieves this by coordinating a statewide chronic disease management approach. The CDMP focuses on the five major chronic diseases recognised as having a major impact on the burden of disease in NSW: diabetes, chronic obstructive pulmonary disease (mainly emphysema and chronic bronchitis), coronary artery disease (also known as coronary or ischaemic heart disease), hypertension (high blood pressure), and congestive heart failure. It is overseen by the Chronic Disease Management Office. Further information on the NSW Chronic Disease Management Program (Connecting Care in the Community) is available from http://www.health.nsw.gov.au/cdm/pages/default.aspx
The NSW Chronic Care for Aboriginal People (CCAP) Program is managed by the NSW Agency for Clinical Innovation. The aim of the CCAP is to prevent and manage conditions including diabetes, heart disease, stroke, hypertension and kidney disease among Aboriginal people. These conditions share common risk factors, and common approaches are needed to address them in Aboriginal communities. Further information on the NSW Chronic Care for Aboriginal People Program is available from https://www.aci.health.nsw.gov.au/networks/ccap
NSW Ministry of Health at www.health.nsw.gov.au
Diabetes Australia at http://www.diabetesaustralia.com.au/
Australian Bureau of Statistics at http://www.abs.gov.au
Australian Institute of Health and Welfare and its National Centre for Monitoring Diabetes at http://www.aihw.gov.au
Australian Diabetes Society and its National Association of Diabetes Centres at http://www.diabetessociety.com.au/nadc.asp
healthdirect at http://www.healthdirect.gov.au