Methods

Introduction

In 2009, the NSW Department of Health, in conjunction with the 8 area health services, completed the eighth year of the New South Wales Population Health Survey, a continuous survey of the health of people of New South Wales using computer assisted telephone interviewing (CATI). The main aims of the survey are to: provide information on the health of the people of New South Wales; support the planning, implementation and evaluation of health services and programs in New South Wales.

Prior to the introduction of the continuous survey in 2002, the Centre for Epidemiology and Research conducted adult health surveys in 1997 and 1998, an older people's health survey in 1999, and a child health survey in 2001. The reporting plan for the continuous survey includes an annual report on adult health for the whole state and annual reports on adult health for selected indicators by area health service.

This section describes the methods used for the 2009 Report on Adult Health from the New South Wales Population Health Survey, which reports the health of residents aged 16 years and over.

Survey instrument

The survey instrument for the New South Wales Population Health Survey was developed by the Health Survey Program in consultation with key stakeholders, area health services, other government departments, and a range of experts.

The survey instrument included: questions used in previous surveys, new questions developed specifically for 2009, and questions developed specifically for some area health services. All questions not previously used were submitted to the NSW Population and Health Services Research Ethics Committee for approval prior to use. New questions were also field tested prior to inclusion in the survey. The survey instrument was translated into 5 languages: Arabic, Chinese, Greek, Italian and Vietnamese.

Survey sample

In 2009, the target population for the New South Wales Population Health Survey was all residents living in households with private telephones. The target sample comprised approximately 1,500 people in each of the 8 area health services (a total sample of 12,000).

The sampling frame was developed as follows. Records from the Australia on Disk electronic white pages (phone book) were geo-coded using MapInfo mapping software.[1,2] The geo-coded telephone numbers were assigned to statistical local areas and area health services. The proportion of numbers for each telephone prefix by area health service was calculated. 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 nonlisted 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. Finally, numbers were stratified by area health service and randomly selected by area health service.

Households were contacted using random digit dialling. One person from the household was randomly selected for inclusion in the survey.

Interviews

In 2009, interviews were carried out continuously between February and December. Selected households with addresses in the electronic phone book were sent a letter describing the aims and methods of the survey 2 weeks prior to initial attempts at telephone contact. An 1800 freecall contact number was provided for potential respondents to verify the authenticity of the survey and to ask any questions regarding the survey. Trained interviewers at the Health Survey Program CATI facility carried out interviews. 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.

Call outcomes and response rates

In 2009, a total of 12,707 interviews were conducted, with at least 1,260 interviews in each area health service and 10,719 with adults aged 16 years or over. The overall participation rate was 58.7 per cent (the number of completed interviews divided by the sum of the number of completed interviews and the number of refusals).

Data analysis

For analysis, the survey sample was weighted to adjust for differences in the probabilities of selection among respondents. These differences were due to the varying number of people living in each household, the number of residential telephone connections for the household, and the varying sampling fraction in each health area.

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 and the Australian Bureau of Statistics 2007 mid-year population estimates (excluding residents of institutions) for each area health service. Further information on the methods and weighting process is provided elsewhere.[3-4]

Call and interview data were manipulated and analysed using SAS version 9.2.[5] The SURVEYFREQ procedure in SAS was used to analyse the data and calculate point estimates and 95 per cent confidence intervals for the estimates. The SURVEYFREQ procedure calculates standard errors adjusted for the design effect factor or DEFF (the variance for a non-random sample divided by the variance for a simple random sample). It uses the Taylor expansion method to estimate sampling errors of estimators based on the stratified random sample.[5]

The 95 per cent confidence interval provides a range of values that should contain the actual value 95 per cent of the time. The width of the confidence interval relates to the differing sample size for each indicator. In general, a wider confidence interval reflects less certainty in the estimate for that indicator. If confidence intervals do not overlap then the observed estimates are significantly different. If confidence intervals overlap slightly the observed estimates may be significantly different but further testing needs to be done to establish that significance. For a pairwise comparison of subgroup estimates, the p value for a two-tailed test was calculated using the t-test for differences in means from independent samples and a modified form of t-test, which accounts for the dependence of the estimates, to test for differences between sub-group estimates and total estimates.[5]

In the online HTML version of the report, the bottom of each table contains a link to a downloadable CSV file which contains an estimate of the number of people in the population corresponding to the prevalence estimates for that indicator.

Indices of geographic remoteness and socioeconomic disadvantage: ARIA and SEIFA

The Accessibility-Remoteness Index of Australia Plus (ARIA+) is the standard Australian Bureau of Statistics (ABS) endorsed measure of remoteness.[6] It is derived using the road distances from populated localities to the nearest service centres across Australia. For each locality, the accessibility to services is expressed as a continuous measure from 0 (high accessibility) to 15 (high remoteness) and grouped into 5 categories: major cities, inner regional, outer regional, remote, and very remote.

The Socio-Economic Indexes for Areas (SEIFA) describe the socioeconomic aspects of geographical areas in Australia, using a number of underlying variables such as family and household characteristics, personal educational qualifications, and occupation.[7] The SEIFA index used to provide breakdowns of the New South Wales Population Health Survey data in 2009 is the Index of Relative Socio-Economic Disadvantage. This index is calculated on attributes such as low income and educational attainment, high unemployment, and people working in unskilled occupations. The SEIFA index values are grouped into 5 quintiles, with quintile 1 being the least disadvantaged and quintile 5 being the most disadvantaged.

Both the ARIA+ and SEIFA indexes were assigned to the respondents in 2009 based on respondents' postcode of residence. Rates for each SEIFA quintile were calculated for several health indicators included in this report to enable socioeconomic comparisons.

Definition of urban and rural

In this report, the term urban means the respondent lived in 1 of the 4 area health services designated as metropolitan: Northern Sydney & Central Coast, South Eastern Sydney and Illawarra, Sydney South West, and Sydney West. The term rural means the respondent lived in 1 of the 4 area health services designated as rural: Greater Southern, Greater Western, Hunter & New England, and North Coast.

References

Australia on Disk [software]. Sydney: Australia on Disk, 2004.
MapInfo [software]. Troy, NY: MapInfo Corporation, 1997.
Barr M, Baker D, Gorringe M, and Fritsche L. NSW Population Health Survey: Description of Methods. Available online at www.health.nsw.gov.au/resources/publichealth/surveys/health_survey_method.asp (accessed 27 August 2010).
Steel D. NSW Population Health Survey: Review of the Weighting Procedures. Available online at www.health.nsw.gov.au/pubs/2006/review_weighting.html (accessed 27 August 2010).
SAS Institute. The SAS System for Windows version 9.2. Cary, NC: SAS Institute Inc., 2009. Further information available from www.sas.com (accessed 27 August 2010).
Australian Bureau of Statistics. ASGC Remoteness Classification: Purpose and Use. Census Paper No. 03/01. Commonwealth of Australia, 2003.
Australian Bureau of Statistics. 1996 Census of Population and Housing: Socio-Economic Indexes for Areas, Information Paper, Catalogue no. 2039.0. Canberra: ABS, 1998.

Tables

Source:	New South Wales Population Health Survey 2009 (HOIST). Centre for Epidemiology and Research, NSW Department of Health.
Print version:	Although this page can be printed directly from your web browser, a higher quality version is available as a PDF file that can be printed or viewed on screen.
Produced by:	Centre for Epidemiology and Research, Population Health Division, NSW Department of Health.
Last updated on:	1 January 2011