In 2006-2009, the target population for the New South Wales Population Health Survey was all residents living in households with private telephones. For each year, 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 unused 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 randomly selected.
Households were contacted using random digit dialling. One person from the household was randomly selected for inclusion in the survey.
In each year, 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 NSW Health Survey Program CATI facility carried out interviews. Up to 7 calls were made to establish initial contact with a household, and 5 calls were made in order to contact a selected respondent.
Call outcomes and response rates
Over the period 1997-2009, 150,877 interviews were were conducted of whom 3,188 were Aboriginal (approximately 2.1 per cent). Of these 2,367 were adults aged 16 years and over and 821 were children aged 0-15 years.
For analysis, the survey sample was weighted to adjust for differences in the probabilities of selection among subjects. 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 for Aboriginals and the Australian Bureau of Statistics 2007 mid-year population estimates for Aboriginals (excluding residents of institutions) for each area health service. Further information on the weighting process is provided elsewhere.[3,4]
Call and interview data were manipulated and analysed using SAS version 9.1. 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 estimates 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. In general, a wider confidence interval reflects less certainty in the estimate for that indicator. The width of the confidence interval relates to the differing sample size for each indicator. A wider confidence interval reflects less certainty in the estimate. 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.
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.
- 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. Sydney: Centre for Epidemiology and Research, NSW Department of Health, 2008. Available online at www.health.nsw.gov.au/resources/publichealth/surveys/health_survey_method.asp (accessed 28 May 2010).
- Steel D. NSW Population Health Survey: Review of the Weighting Procedures. Sydney: Centre for Epidemiology and Research, NSW Department of Health, 2006. Available online at www.health.nsw.gov.au/pubs/2006/review_weighting.html (accessed 9 February 2010).
- SAS Institute. The SAS System for Windows version 9.1. Cary, NC: SAS Institute Inc., 2009. Further information available from www.sas.com (accessed 28 May 2010).
|Source:||New South Wales Population Health Survey 2006-2009 (HOIST). Centre for Epidemiology and Research, NSW Department of Health.|
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|Produced by:||Centre for Epidemiology and Research, Population Health Division, NSW Department of Health.|
|Last updated on:||1 August 2010|