NSW Population Health Survey (SAPHaRI). Centre for Epidemiology and Evidence, NSW Ministry of Health.
Smoothed estimates are shown in the graph. Actual estimates are shown in the table. Smoothed estimates have been derived from the actual estimates, that were statistically adjusted to minimise random variation from year to year and provide more stable smoothed estimates for population health planning and monitoring.
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.Mobile phone numbers have been included since the 2012 survey (using an overlapping dual-frame design) because of diminishing coverage of the population by landline sampling frames (<85 % since 2010). Associations between mobile-only phone users and some health indicators, even after adjusting for age, sex and region, were observed in 2012. Thus significant differences that were observed between 2011 and 2012 should be reported with caution, as they will reflect both real and design changes. LL/UL 95%CI = lower and upper limits of the 95% confidence interval for the point estimate.
The questions used to define the indicator were: How tall are you without shoes? How much do you weigh without clothes or shoes?
For 18 years and over, BMI is calculated as follows: BMI = weight(kg)/height(m)². Categories for this indicator include: underweight (BMI less than 20.0), healthy weight (BMI from 20.0 to 24.9), overweight (BMI from 25.0 to 29.9) and obese (BMI of 30.0 and over). Obesity was further classified into: Obesity Class I (BMI between 30.0 and 34.9), Obesity Class II (BMI between 35.0 and 39.9) and Obesity Class III (BMI of 40.0 or over).
For children and adolescents, the same categories are used but they are linked to international cut off points by sex, between 2 and 18 years of age, defined to pass through a BMI of 16, 17, and 18.5 for underweight, 25 for overweight, and 30 for obesity at age 18 years (Cole et al. 2000; Cole et al. 2007).
The validity of self-reported height and weight has been investigated in adult, adolescent, and young adult populations. While many studies have observed a high correlation (96 per cent agreement) between BMI calculated from self-reported and measured height and weight, there is ample evidence that self-reported height and weight is not as exact as measured height and weight but is adequate for conducting epidemiological research.
The indicator covering Overweight or Obesity includes those who are overweight or obese: that is, with a Body Mass Index (BMI) of 25.0 or higher: overweight (BMI from 25.0 to 29.9) and obese (BMI of 30.0 and over).
Cole T, Bellizzi M, Flegal K, Dietz W. Establishing a standard definition for child overweight and obesity worldwide: International survey. British Medical Journal 2000; 320. Available at www.bmj.com/cgo/content/full/320/7244/1240 (accessed 17 January 2013).
Cole Y, Flegal K, Nicholls D, Jackson A. Body mass index cut offs to define thinness in children and adolescents: International survey. British Medical Journal 2007; 335(7612): 194. Available at www.bmj.com/cgo/content/full/335/7612/194 (accessed 17 January 2013).
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 were made to establish initial contact with a household, and up to 5 calls were made in order to contact a selected respondent. Adult respondents living in households with children are offered to opportunity to complete an interview about their children. At present, approximately 5% of all primary adult respondents take 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 andSAS 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).
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 www.acma.gov.au/webwr/_assets/main/lib410148/report2-convergent_comms.pdf
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. 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. 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 www.sampleworx.com.au.html
SAS Institute. The SAS System for Windows version 9.3 (software). Cary, NC: SAS Institute Inc., 2011. Available at www.sas.com
United Directory Systems. Australia on Disk (software). UDS: version 2004. Available at: www.uniteddirectorysystems.com
• 52.5% of adults aged 16 years and over (58.8% of men and 46.1% of women) were overweight or obese as estimated from the 2014 NSW Adult Population Health Survey (self-reported using Computer Assisted Telephone Interviewing or CATI).
• 61.1% of persons aged 18 years and over (68.3% of males and 53.7% of females) in NSW were overweight or obese as estimated from the 2011-12 Australian Health Survey (interviewer-administered questionnaire and measured weight and height).
• 20.4% of students aged 12-17 years (25.5% of boys and 14.2% of girls) were overweight or obese as estimated from the 2011 NSW School Students Health Behaviours Survey (self-completed questionnaire).
• 22.8% of students in years K, 2, 4, 6 and 10 (24.0% of boys and 21.5% of girls) were overweight or obese as estimated from the 2010 NSW Schools Physical Activity and Nutrition Survey (measured).
• 22.8% of students in years K, 2, 4, 6 and 10 (24.0% of boys and 21.5% of girls) were overweight or obese as estimated from the 2010 NSW Schools Physical Activity and Nutrition Survey (measured).
• 21.5% of children aged 5-16 years (24.6% of boys and 17.9% of girls) were overweight or obese as estimated from the 2014 NSW Population Health Survey (parent-reported using CATI).
• 25.6% of children aged 5-17 years were overweight or obese as estimated from the 2011-12 Australian Health Survey (measured).
• 57.4% of Aboriginal adults aged 16 years and over were overweight or obese as estimated from the 2014 NSW Adult Population Health Survey (self-reported using CATI).
Self-reported data on overweight and obesity have been collected for adults in NSW since 1997 through the NSW Population Health Survey and since 1977-78 through the Australian Health Surveys, National Health Surveys (from 1995). Measured data on overweight and obesity have been collected for adults in NSW through the National Nutrition Survey (1995) and the Australian and National Health Survey (2011-12 and 2007-08 respectively).
Self-reported data on overweight and obesity have been collected for students in NSW since 2005 through the NSW School Students Health Behaviours Survey and measured data on overweight and obesity have been collected for students in NSW since 1985 through the Australian Health and Fitness Survey and the NSW Schools Fitness and Physical Activity Survey (1997) and the NSW Schools Physical Activity and Nutrition Survey (2004 and 2010).
Parent-reported data on overweight and obesity have been collected for children in NSW since 2007 through the NSW Population Health Survey. Measured data on overweight and obesity have been collected for children in NSW since 2008 through the National Health Survey.
Prevalence estimates, although differing slightly between surveys because of different sampling frames, participation rates and modes of collection (telephone versus self-completed questionnaires versus face-to-face personal interview versus measured) have all been increasing over time although the rate of increase has lessened.
A total of 39,289 hospitalisations were attributed to high body mass in NSW in 2013-14, which was approximately 1.3% of all hospitalisations. The rate of hospitalisations attributed to high body mass decreased by more than 18% in the decade up to 2012-13. This was chiefly due to the rate decreasing by more than 20% between 2009-10 and 2011-12 caused by a change in coding of diabetes in hospital data. This coding change was implemented in NSW hospitals on 1 July 2010. In the decade up to 2009-10, the rate of hospitalisation attributable to high body mass increased by 8% in NSW. The hospitalisation rate in males was 40% greater than the rate in females throughout the decade.
A total of 2,693 deaths were estimated to be caused by high body mass in NSW in 2013, which was approximately 5.5% of all deaths. The rate of death attributed to high body mass has decreased in the decade up to 2013 and the decline was similar in males and females.
Australian Bureau of Statistics. National Health Survey: Summary of Results. Cat no 4362.0. State Tables, 2007-2008. Available at: http://www.abs.gov.au/ausstats/abs@.nsf/mf/4364.0
Booth M, Macaskill P, McLellan L, Phongsavan P, Okely AD, Patterson J. NSW Schools Fitness and Physical Activity Survey. Sydney: NSW Department of School Education, 1997.
Centre for Epidemiology and Evidence. NSW Adult Population Health Survey. NSW Ministry of Health. Available at: http://www.health.nsw.gov.au/publichealth/surveys/index.asp
Centre for Epidemiology and Evidence. NSW Child Population Health Survey. NSW Ministry of Health. Available at: http://www.health.nsw.gov.au/publichealth/surveys/index.asp
Centre for Epidemiology and Evidence. NSW School Students Health Behaviours Survey. NSW Ministry of Health. Available at: http://www.health.nsw.gov.au/publichealth/surveys/index.asp
Pyke JE. The Australian Health and Fitness Survey 1985: The fitness, health and physical performance of Australian school students aged 7-15 years. Adelaide: The Australian Council for Health, Physical Education and Recreation (ACHPER), 1987.
Hardy L. SPANS 2010 - NSW Schools Physical Activity and Nutrition Survey - Executive Summary. Sydney: University of Sydney, 2012.
Department of Health and Ageing. 2007 Australian National Child Nutrition and Physical Activity Survey. Available at: http://www.health.gov.au/internet/main/publishing.nsf/Content/phd-nutrition-childrens-survey-keyfindings
There are health problems associated with being either underweight or overweight. Although underweight can be a serious risk to health (leading to malnutrition and other health problems such as osteoporosis), public health focus is on excess body weight, as this is a much greater problem in the Australian population (AIHW Cat. no. AUS 122 2010)
Excess weight, especially obesity, is a risk factor for cardiovascular disease, Type 2 diabetes, some musculoskeletal conditions and some cancers. As the level of excess weight increases, so does the risk of developing these conditions. In addition, being overweight can hamper the ability to control or manage chronic disorders (AIHW Cat. no. AUS 122 2010)
Excess weight in children increases the risk of poor health, both during childhood and later in adulthood. Children who are overweight or obese are at greater risk of developing chronic conditions such as asthma and Type 2 diabetes; and may experience negative social and mental wellbeing (AIHW Cat. no. AUS 122 2010).
Body mass is derived from a person's weight and height. The Body Mass Index (BMI) is the weight in kilograms divided by the square of the height in metres (kg/m2). A person considered overweight or obese has a BMI of at least 25 kg/m2. For more details on the BMI, see the Methods section.
Previously considered a problem in high-income countries, overweight and obesity are now also on the rise in low- and middle-income countries, especially in urban areas. The World Health Organization has estimated that by 2015 there will be 2.3 billion adults who are overweight, and more than 700 million who will be obese (World Health Organization 2006).
In Australia in 2003, high body mass was responsible for 7.5% of the total burden of disease with Type 2 diabetes and ischaemic heart disease accounting for almost three-quarters of this burden (Begg et al. 2007)
Australian Bureau of Statistics. National Health Survey: Summary of Results, 2007-2008 (Reissue). Cat. no. 4364.0. Canberra: ABS, 2009. Available at: http://www.abs.gov.au/ausstats/abs@.nsf/mf/4364.0/
Australian Institute of Health and Welfare. Australia’s health 2010. Australia’s health series no. 12. Cat. no. AUS 122. Canberra: AIHW, 2010. Available at: http://www.aihw.gov.au/publication-detail/?id=6442468376
Begg S, Vos T, Barker B. The burden of disease and injury in Australia, 2003. Cat. no. PHE 82 edition. Canberra: AIHW, 2007. Available at: http://www.aihw.gov.au/publication-detail/?id=6442467990
World Health Organization. Obesity and overweight. Fact sheet no. 311. Geneva: WHO, 2006. Available at: http://www.who.int/mediacentre/factsheets/fs311/en/index.html
The NSW Healthy Eating and Active Living 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.
The Strategy has four key strategic directions:
Australian Bureau of Statistics at http://www.abs.gov.au
Australian Institute of Health and Welfare at http://www.aihw.gov.au
healthdirect at http://www.healthdirect.gov.au
National Health and Medical Research Council. Clinical practice guidelines for the management of overweight and obesity in adults, adolescents and children in Australia. Melbourne: National Health and Medical Research Council, 2013. Available at: https://www.nhmrc.gov.au/guidelines-publications/n57
NSW Department of Education and Training and NSW Ministry of Health. Live Life Well @ School. NSW Department of Education and Training & NSW Ministry of Health website. Available at: http://www.healthykids.nsw.gov.au/teachers-childcare/live-life-well-@-school.aspx/index.htm
NSW Government. Good for kids. Good for life. Available at: http://www.goodforkids.nsw.gov.au/parents-carers
NSW Government: NSW Ministry of Health, NSW Department of Education and Training, Sport and Recreation, a division of Communities NSW and the Heart Foundation. Munch and Move. NSW Government website. Available at: http://www.healthykids.nsw.gov.au/campaigns-programs/about-munch-move.aspx
NSW Ministry of Health. Healthy Eating Active Living. Available at: http://www.health.nsw.gov.au/heal/pages/default.aspx.