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Quality Of Life in South Australia as
Measured by the SF12 Health Status
Questionnaire
Population Norms For 2003
Trends From 1997 - 2003
Jodie Avery
Eleonora Dal Grande
Anne Taylor
Population Research and Outcome Studies Unit
Department of Human Services
South Australia
March 2004
2
ACKNOWLEDGMENTS
This work is copyright. It may be reproduced and the Population Research and Outcome Studies
(PROS) welcomes requests for permission to reproduce in the whole or in part for work, study or
training purposes subject to the inclusion of an acknowledgment of the source and not commercial use
or sale. PROS will only accept responsibility for data analysis conducted by PROS staff or under
PROS supervision.
Published March 2004 by the South Australian Department of Human Services
Population Research and Outcome Studies, Strategic Planning and Research Branch
PO Box 287 Rundle Mall 5000
South Australia, Australia
National Library of Australia Cataloguing in Publication entry:
Avery, Jodie.
Quality of life in South Australia as measured by the SF-12
Health Status Questionnaire : population norms for 2003 :
trends from 1997-2003.
ISBN 0 7308 9329 4.
1. Health surveys - South Australia. 2. Mental health -
South Australia - Statistics. 3. Public health - South
Australia v Statistics. I. Dal Grande, E. II. Taylor,
Anne, 1950- . III. South Australia. Dept. of Human
Services. Population Research and Outcome Studies Unit. IV.
Title.
614.429423
In accordance with the Copyright Act 1968 a copy of each book published
must be lodged with the National Library. Under relevant State or Territory
Legislation a copy must also be lodged with the appropriate library or
libraries in the state of publication. For information about Legal Deposit, see the
website at: http://www.nla.gov.au/services/ldeposit.html or contact the Legal
Deposit Unit, National Library of Australia on 02 6262 1312.
This document can be found online at:
http://www.dhs.sa.gov.au/pehs/PROS.html
3
TABLE OF CONTENTS
TABLE OF CONTENTS .........................................................................................3
LIST OF TABLES...................................................................................................5
LIST OF FIGURES .................................................................................................6
EXECUTIVE SUMMARY ........................................................................................9
CHAPTER 1: INTRODUCTION .............................................................................. 13
1.1 Background to the SF-12................................................................................ 13
CHAPTER 2: METHODS .......................................................................................15
2.1 Data Sources................................................................................................... 15
2.2 Data Analysis .................................................................................................. 16
CHAPTER 3: SF-12 POPULATION NORMS FOR SOUTH AUSTRALIA .............19
CHAPTER 4: SF-12 POPULATION TRENDS FOR SOUTH AUSTRALIA............ 27
CHAPTER 5: SF-12 BY VARIOUS CHRONIC CONDITIONS ...............................35
5.1 Diabetes........................................................................................................... 36
5.2 Arthritis............................................................................................................ 38
5.3 Heart Disease .................................................................................................. 40
5.4 Stroke............................................................................................................... 42
5.5 Cancer.............................................................................................................. 44
5.6 Osteoporosis................................................................................................... 46
5.7 Asthma............................................................................................................. 48
5.8 Other Respiratory Condition.......................................................................... 50
5.9 Mental Health Condition................................................................................. 52
5.10 Co-morbidity.................................................................................................. 54
CHAPTER 6: SF-12 BY HEALTH RISK FACTORS ..............................................57
4
6.1 High Blood Pressure ...................................................................................... 58
6.2 High Cholesterol ............................................................................................. 60
6.3 Body Mass Index............................................................................................. 62
6.4 Smoking Status............................................................................................... 64
6.5 Alcohol Use ..................................................................................................... 66
6.6 Multiple Risk Factors...................................................................................... 68
CHAPTER 7: SF-12 BY DIFFERENT POPULATION GROUPS............................ 71
7.1 South Australian Divisions of General Practice........................................... 71
7.2 SEIFA ............................................................................................................... 75
7.3 ARIA ................................................................................................................. 77
REFERENCES .......................................................................................................79
APPENDIX 1: HEALTH MONITOR INVITATION LETTER................................... 81
APPENDIX 2: HEALTH MONITOR METHODOLOGY SURVEY DESIGN ........... 83
A2.1 Sample selection........................................................................................ 83
A2.2 Data Collection ........................................................................................... 83
APPENDIX 3: HEALTH MONITOR QUESTIONNAIRE 2003 – JULY
(TRUNCATED) ....................................................................................................... 87
APPENDIX 4: HEALTH AND WELLBEING SURVEY INVITATION LETTER...... 93
APPENDIX 5: HEALTH AND WELLBEING SURVEY DESIGN AND
METHODOLOGY ...................................................................................................95
A5.1 Survey Design ............................................................................................ 95
A5.2 Data collection............................................................................................ 97
APPENDIX 6: SA, NT AND WA CATI HEALTH AND WELLBEING SURVEY
NOVEMBER 2000 .................................................................................................. 101
5
LIST OF TABLES
Table 3.1: 2003 SF-12 Norms for the general South Australian population, aged 18 years and
over ................................................................................................................................. 20
Table 3.2: 2003 SF-12 Norms for the general South Australian population, by age.............. 22
Table 3.3: 2003 SF-12 Norms for the general South Australian MALE population, by age ... 23
Table 3.4: 2003 SF-12 Norms for the general South Australian FEMALE population, by age
........................................................................................................................................ 24
Table 4.1: Mean SF-12 scores, general South Australian population, aged 18 & over, by year
........................................................................................................................................ 27
Table 4.2: Mean STANDARDISED SF-12 scores (95% confidence interval of the mean) for
the general South Australian population, aged 18 and over, by year............................. 28
Table 5.1: Mean SF-12 scores for South Australians doctor diagnosed with diabetes aged 18
years and over, 2000. ..................................................................................................... 36
Table 5.2: Age-sex adjusted mean SF-12 scores for South Australians diagnosed with
diabetes aged 18 years and over, 2000. ........................................................................ 36
Table 5.3: Mean SF-12 scores for South Australians diagnosed with arthritis aged 18 years
and over, 2000. ............................................................................................................... 38
Table 5.4: Age sex adjusted Mean SF-12 scores for South Australians diagnosed with
arthritis aged 18 years and over, 2000. .......................................................................... 38
Table 5.5: Mean SF-12 scores for South Australians diagnosed with heart disease aged 18
years and over, 2000. ..................................................................................................... 40
Table 5.6: Age-sex adjusted Mean SF-12 scores for South Australians diagnosed with heart
disease aged 18 years and over, 2000........................................................................... 40
Table 5.7: Mean SF-12 scores for South Australians diagnosed with Stroke aged 18 years
and over, 2000. ............................................................................................................... 42
Table 5.8: Age-sex adjusted Mean SF-12 scores for South Australians diagnosed with Stroke
aged 18 years and over, 2000. ....................................................................................... 42
Table 5.9: Mean SF-12 scores for South Australians diagnosed with Cancer aged 18 years
and over, 2000. ............................................................................................................... 44
Table 5.10: Age sex adjusted Mean SF-12 scores for South Australians diagnosed with
cancer aged 18 years and over, 2000. ........................................................................... 44
Table 5.11: Mean SF-12 scores for South Australians diagnosed with osteoporosis aged 18
years and over, 2000. ..................................................................................................... 46
Table 5.12: Age sex adjusted Mean SF-12 scores for South Australians diagnosed with
Osteoporosis aged 18 years and over, 2000. ................................................................. 46
Table 5.13: Mean SF-12 scores for South Australians diagnosed with current asthma aged
18 years and over, 2000. ................................................................................................ 48
Table 5.14: Age sex adjusted Mean SF-12 scores for South Australians with current asthma
aged 18 years and over, 2000. ....................................................................................... 48
Table 5.15: Mean SF-12 scores for South Australians currently diagnosed with any other
Respiratory Condition aged 18 years and over, 2000. ................................................... 50
Table 5.16: Age sex adjusted Mean SF-12 scores for South Australians with current
respiratory condition aged 18 years and over, 2000. ..................................................... 50
Table 5.17: Mean SF-12 scores for South Australians diagnosed with current Mental Health
Condition aged 18 years and over, 2000........................................................................ 52
Table 5.18: Age sex adjusted Mean SF-12 scores for South Australians with current mental
health condition aged 18 years and over, 2000.............................................................. 53
Table 5.19: Mean SF-12 scores for South Australians diagnosed with at least one or more
chronic conditions aged 18 years and over, 2000. ......................................................... 54
Table 5.20: Age-sex adjusted Mean SF-12 scores for South Australians with at least one or
more chronic conditions aged 18 years and over, 2000. ................................................ 55
Table 6.1: Mean SF-12 scores for South Australians diagnosed with current high blood
pressure aged 18 years and over, 2000 ......................................................................... 58
Table 6.2: Age sex adjusted SF-12 Mean scores for South Australians with current high
blood pressure aged 18 years and over, 2000 ............................................................... 58
Table 6.3: Mean SF-12 scores for South Australians diagnosed with current high cholesterol
aged 18 years and over, 2000 ........................................................................................ 60
Table 6.4: Age-sex adjusted Mean SF-12 scores for South Australians with current high
cholesterol aged 18 years and over, 2000...................................................................... 60
6
Table 6.5: Mean SF-12 scores for South Australians by body mass index category aged 18
years and over, 2000 ...................................................................................................... 62
Table 6.6: Age-sex adjusted Mean SF-12 scores for South Australians by body mass index
category aged 18 years and over, 2000 ......................................................................... 63
Table 6.7: Mean SF-12 scores for South Australians by smoking status aged 18 years and
over, 2000 ....................................................................................................................... 64
Table 6.8: Age-sex adjusted SF-12 Mean scores for South Australians by smoking status
aged 18 years and over, 2000 ........................................................................................ 65
Table 6.9: Mean SF-12 scores for South Australians in each drinking category aged 18 years
and over, 2000 ................................................................................................................ 66
Table 6.10: Age-sex adjusted Mean SF-12 scores for South Australians in each drinking
category aged 18 years and over, 2000 ......................................................................... 67
Table 6.11: Mean SF-12 scores for South Australians with at least one or more health risk
factors conditions aged 18 years and over, 2000 ........................................................... 68
Table 6.12: Age sex adjusted SF-12 Mean scores for South Australians with at least one or
more Health Risk Factors aged 18 years and over, 2000 .............................................. 69
Table 7.1: Proportion of respondents in each South Australian Division of General Practice
aged 18 years and over. ................................................................................................. 71
Table 7.2: Mean SF-12 scores for respondents in each South Australian Division of General
Practice. .......................................................................................................................... 72
Table 7.3: Age sex adjusted Mean SF-12 scores for each South Australian Division of
General Practice aged 18 years and over, 2000 ............................................................ 73
Table 7.4: Mean SF-12 scores for South Australians for each SEIFA IRSD quintile, 2000 ... 75
Table 7.5: Age-sex adjusted Mean SF-12 scores for South Australians for each SEIFA IRSD
quintile aged 18 years and over, 2000............................................................................ 76
Table 7.6: Mean SF-12 scores for South Australians in each ARIA Category aged 18 years
and over, 2000 ................................................................................................................ 77
Table 7.7: Age-sex adjusted Mean SF-12 scores for South Australians in each ARIA
Category aged 18 years and over, 2000 ........................................................................ 78
LIST OF FIGURES
Figure 3.1: Frequency Distribution for SF-12 Physical Component Summary (PCS) scores,
2003 ................................................................................................................................ 19
Figure 3.2: Frequency Distribution for SF-12 Mental Component Summary (MCS) scores,
2003 ................................................................................................................................ 19
Figure 3.3: 2003 SF-12 Norms for the general South Australian population, overall, Males
and Females, aged 18 years and over. .......................................................................... 20
Figure 3.4: 2003 SF-12 Norms for the general South Australian population, by age ............ 22
Figure 3.5: 2003 SF-12 Norms for the general MALE South Australian population by age... 23
Figure 3.6: 2003 SF-12 Norms for the general FEMALE South Australian population by age
........................................................................................................................................ 24
Figure 4.1: Mean STANDARDISED SF-12 Physical Component Summary (PCS) scores for
the general South Australian population, aged 18 years and over by year.................... 28
Figure 4.2: Mean STANDARDISED SF-12 Mental Component Summary (MCS) scores for the
general South Australian population, aged 18 years and over by year .......................... 28
Figure 4.3: Mean SF-12 Physical Component Summary (PCS) scores for the general
population, aged 18 years and over by year, for each gender and age group............... 29
Figure 4.4: Mean SF-12 Mental Component Summary (MCS) scores for the general
population, aged 18 years and over by year, for each gender and age group............... 32
Figure 5.1: Age-sex adjusted 2000 Mean SF-12 scores for South Australians diagnosed with
diabetes, aged 18 years and over. ................................................................................. 37
Figure 5.2: Age-sex adjusted 2000 Mean SF-12 scores for South Australians diagnosed with
arthritis, aged 18 years and over. ................................................................................... 39
Figure 5.3: Age-sex adjusted 2000 mean SF-12 scores for South Australians diagnosed with
heart disease, aged 18 years and over. ......................................................................... 41
7
Figure 5.4: Age-sex adjusted 2000 Mean SF-12 scores for South Australians diagnosed with
stroke, aged 18 years and over. ..................................................................................... 43
Figure 5.5: Age-sex adjusted 2000 Mean SF-12 scores for South Australians diagnosed with
cancer, aged 18 years and over. .................................................................................... 45
Figure 5.6: Age-sex adjusted mean 2000 SF-12 scores for South Australians diagnosed with
osteoporosis, aged 18 years and over............................................................................ 47
Figure 5.7: Age-sex adjusted 2000 mean SF-12 scores for South Australians diagnosed with
asthma, aged 18 years and over. ................................................................................... 49
Figure 5.8: Age-sex adjusted 2000 mean SF-12 scores for South Australians diagnosed with
respiratory condition, aged 18 years and over................................................................ 51
Figure 5.9: Age-sex adjusted 2000 mean SF-12 scores for South Australians with current
mental health condition, aged 18 years and over. .......................................................... 53
Figure 5.10: Age-sex adjusted 2000 SF-12 mean scores for South Australians with one or
more chronic conditions, aged 18 years and over. ......................................................... 55
Figure 6.1: Age-sex adjusted 2000 mean SF-12 scores for South Australians diagnosed with
high blood pressure, aged 18 years and over. ............................................................... 59
Figure 6.2: Age-sex adjusted 2000 mean SF-12 scores for South Australians diagnosed with
high cholesterol aged 18 years and over........................................................................ 61
Figure 6.3: Age-sex adjusted 2000 mean SF-12 scores for South Australians by body mass
index category, aged 18 years and over......................................................................... 63
Figure 6.4: Age-sex adjusted 2000 mean SF-12 scores for South Australians by smoking
status, aged 18 years and over. ..................................................................................... 65
Figure 6.5: Age-sex adjusted 2000 Mean SF-12 scores for South Australians in the each
drinking category aged 18 years and over, overall and age adjusted by sex................. 67
Figure 6.6: Age-sex adjusted 2000 SF-12 mean scores for South Australians with one or
more Health Risk Factors, aged 18 years and over. ...................................................... 69
Figure 7.1: Age-sex adjusted 2000 mean SF-12 Physical Component Summary scores for
South Australia in each Division of General Practice, aged 18 years and over. ............ 74
Figure 7.2: Age-sex adjusted 2000 mean SF-12 Mental Component Summary scores for
South Australia in each Division of General Practice, aged 18 years and over. ............ 74
Figure 7.3: Age-sex adjusted 2000 SF-12 mean scores for South Australians for each SEIFA
quintile, aged 18 years and over. .................................................................................... 76
Figure 7.4 Age-sex adjusted Mean SF-12 scores for South Australians living each ARIA
Category aged 18 years and over, 2000. ....................................................................... 78
8
Executive Summary
9
EXECUTIVE SUMMARY
Main Findings
This report summarises the Short Form 12 (SF-12) norms from surveys conducted by
Population Research and Outcome Studies (PROS), South Australian Department of
Human Services. The norms in this report are primarily obtained from the 2003 July
Health Monitor, as well as the South Australian results from the 2000 Wellbeing
Study, in order to obtain difference norms for chronic conditions, risk factors and
regions. The main results are highlighted below.
The SF-12 was derived from twelve questions of the SF-36. MCS (Mental
Component Summary) and PCS (Physical Component Summary) scales were
calculated from these questions, in order to provide a summary measure of health
status. The two scores range between 0 and 100, with increasing values equating to
better health.
South Australian SF-12 Population Norms
· Women aged 18 years and over in South Australia had statistically significantly
lower scores on both the SF-12 summary scores PCS and MCS than men.
· In general, norms for the PCS of the SF-12 are statistically significantly lower in
the older age groups.
· When PCS was analysed by both males and females by all age groups, a decline
with age was evident for both genders for the norms, however this decline is not
statistically significant.
· Norms for the MCS remained consistent across all ages, with no statistically
significant differences, even when adjusted for sex.
South Australian SF-12 Population Trends Over Time
· When standardised to the 2001 South Australian Census by age and sex, the
standardised mean PCS score for they year 2000 was statistically significantly
Executive Summary
10
lower than those for 1997 and 1998. However, the MCS summary scores did not
vary significantly over time (1997, 1998, 2000 and 2003).
South Australian SF-12 Scores By Chronic Conditions
· People diagnosed with diabetes, arthritis, stroke, cancer, osteoporosis and current
asthma scored statistically significantly lower on the PCS than people who do not
have these conditions. However, there were no statistically significant
differences on the MCS between people with these conditions and those who did
not have them.
· People with heart disease, a current respiratory condition or a current mental
health condition scored statistically significantly lower than those without these
conditions, on both summary scores of the SF-12.
· South Australians with one or more chronic conditions scored statistically
significantly lower than people who did not have any chronic conditions on both
summary scores of the SF-12.
· In general, those who had an increasing number of chronic conditions exhibited a
statistically significant decline in MCS scores, but this effect was not
demonstrated in their PCS scores.
South Australian SF-12 Scores By Health Risk Factors
· People with current high blood pressure scored statistically significantly lower on
the PCS than people without this risk factor, but there were no statistically
significant differences on the MCS between people with and without current high
blood pressure.
· People with current high cholesterol scored statistically significantly lower on
both summary scores than people who did not have current high cholesterol.
· People classified as obese according to their Body Mass Index (BMI) scored
statistically significantly lower on the PCS than all other categories of BMI.
· Current smokers scored statistically significantly lower on the PCS than people
who were non-smokers or ex-smokers. Ex-smokers score statistically
significantly lower on the MCS than people who are current smokers or non-
smokers.
Executive Summary
11
· Non-drinkers or people in the no risk alcohol drinking category, as well as those
in the intermediate to very high risk category, scored statistically significantly
lower on the PCS than people in the low drinking risk category. There were no
statistically significant differences in the scores for the MCS between people in
different drinking categories.
· South Australians with one or more health risk factors scored statistically
significantly lower on the PCS than people who do not any health risk factors.
· People with two or more health risk factors score statistically significantly lower
on the MCS scale than people who do not any health risk factors.
South Australian SF-12 Scores By Different Population Groups
· The highest scoring Divisions of General Practice for the PCS, were the
Limestone Coast, Adelaide Western, and Flinders and Far North, Divisions of
General Practice. The lowest scoring Divisions on the PCS were the Adelaide
Northern, Riverland, and Murray Mallee Divisions of General Practice.
· Respondents in the Adelaide Northern Division of General Practice scored
statistically significantly lower on the PCS scale than those than the Adelaide
Western Division.
· The highest scores for MCS were evident in the Barossa, Mid North and Adelaide
Hills Divisions of General Practice. The lowest scores on the MCS were in
Adelaide Central and Eastern, Adelaide North Eastern, Adelaide Northern and
Adelaide Western Divisions of General Practice.
· Respondents in the Barossa Division of General Practice scored statistically
significantly higher on the MCS scale than Adelaide Central and Eastern,
Adelaide Northern, Adelaide North East and Adelaide Western Division of
General Practice.
· South Australians who fell into the lowest SEIFA quintile scored statistically
significantly lower on both summary scores of the SF-12 than people who fell
into the highest SEIFA quintile.
· There was no significant difference in the PCS summary score between people
living in different ARIA categories.
· There was no significant difference in MCS scores between those living in
Metropolitan and Remote areas, as defined by ARIA. However, those living in
Executive Summary
12
Metropolitan areas scored statistically significantly lower on the MCS than
people living in Rural areas.
13
CHAPTER 1: INTRODUCTION
1.1 Background to the SF-12
The Medical Outcomes Study Short Form 12 Health Survey (SF-12) was derived in
the United States from the twelve questions of the SF-36, which make up the MCS
(Mental Component Summary) and PCS (Physical Component Summary) scales1,2, in
order to provide a shorter measure health status. The survey can be administered in
two to three minutes, which saves both time and resources in large-scale population
surveys. In the analysis of such surveys, it is often practical to use the two summary
measures, MCS and PCS, derived from the SF-12, which are able to satisfactorily
gauge the general health of the population2. The SF-36 has been validated in an
Australian population3. However, it is possible to use the US version of the SF-12 for
international comparability, using appropriate Australian general population
weighting4, and the US version has been used in this report.
The SF-12 includes 12 questions from the original SF-36 that are summarised into
two summary scores, the Mental Component Summary (MCS) and Physical
Component Summary (PCS) scales5. The two scores range between 0 and 100, with
increasing values equating to better health.
The SF-12 survey, from which the population norms in this document were derived,
was administered as a part of the 2003 July South Australian Health Monitor (HM), a
"user-pays" computer aided telephone interviewing (CATI) survey system that has
been in operation since 1999. Norms for different chronic diseases, health risk factors
and different geographical regions have also been derived from the South Australian
component of the Collaborative Health and Wellbeing Study, 20006.
The South Australian population norms presented in this report enable comparisons of
results from other studies and population groups with the general population. This
will be particularly useful when assessing changes in health outcomes for chronic
diseases.
The SF-12 has also been included in recent Social and Environmental Risk Context
Information System (SERCIS) Surveys6,7,8,9. These surveys have been undertaken by
the Population Research and Outcome Studies Unit, of the South Australian
Introduction
14
Department of Human Services. The information gained from these surveys will
enable changes in the SF-12 norms to be monitored over time.
15
CHAPTER 2: METHODS
2.1 Data Sources
2.1.1 The South Australian Health Monitor
The South Australian Health Monitor is a "user-pays" telephone survey system that
has been operational since 1999 and is administered by the Population Research and
Outcome Studies (PROS), Department of Human Services10. The Health Monitor is
an "omnibus-type" service available to government and non-government
organisations to obtain data on a range of health issues within South Australia (SA).
The idea of an omnibus survey is that several organisations share the cost of
conducting a survey.
Three regular SA-wide surveys are conducted each year. Additionally, other studies
into particular aspects of health are conducted on an ad-hoc basis. These ad-hoc
surveys may be conducted within South Australia, nationally, within a selection of
states and territories, or within particular regions of South Australia. An example of
the invitation letter sent to potential participants in the Health Monitor can be found in
Appendix 1. A further description of the methodology for this survey has been
included in Appendix 2, and the questionnaire used for the 2003 Health Monitor can
be found in Appendix 3.
2.1.2 The Collaborative Health and Wellbeing Survey
The 2000 Collaborative Health and Wellbeing Survey6 was originally proposed to
undertake a three state/territory CATI health and wellbeing survey (Western
Australia, South Australia and Northern Territory) utilising the already established
South Australian infrastructure.
The overall aim of the collaboration was to demonstrate the capacity for a public
health survey partnership between the three participating states and territory and the
Commonwealth.
A management group, was established to oversee the survey process. Each individual
state/territory also brought their own research teams and local experts to assist in the
design of the questionnaire.
Methods
16
South Australia conducted the telephone interviewing on behalf of the other states
using SERCIS (Social, Environmental and Risk Context Information System) which
is a telephone monitoring system designed to provide high quality data on large
samples of the South Australian/Australian population. SERCIS is managed within
the Population Research and Outcome Studies (PROS) Unit of the South Australian
Department of Human Services and overseen by an Advisory Committee. An
example of the invitation letter sent to potential participants in the Health and
Wellbeing Survey can be found in Appendix 4. A further description of the
methodology has been included in Appendix 5, and the questionnaire used for this
survey can be found in Appendix 6.
2.1.3 The Social and Environmental Risk Context Information
System
The South Australian Social and Environmental Risk Context Information System
(SERCIS) is a telephone survey system operating since 1995 and is administered by
the Population Research and Outcome Studies Unit, Department of Human Services.
SERCIS is used to conduct epidemiological surveys into particular health topics
amongst randomly selected populations of South Australia.
Three other SERCIS surveys have used the SF-12 and are included here to examine
trends over time for PCS and MCS scores. These surveys were undertaken in June
1997, August 1998 and November 20007,8,9.
2.2 Data Analysis
The data for the SF-12 summary scores have been calculated and presented in this
report in a number of different ways. Norms for South Australia, as well as trends
over time, are available here for both the PCS and MCS summary scales.
Means scores for the PCS and MCS scales have been used to compare groups, such as
different gender groups, and different age groups. Comparisons between those with
and without a particular condition, or health risk factor have also been made.
To compare between gender, age groups and demographic variables, univariate t-test
was used to test for statistical significance. The conventional 5% level of statistical
Methods
17
significance was used. To compare people with and without chronic conditions or
health risk factors, and people in different population groups, multiple linear
regression, adjusting for age and sex, was used to compute mean scores for each
summary score of the SF-12. The chronic conditions analysed were diabetes, arthritis,
heart disease, stroke, cancer, osteoporosis, asthma, other respiratory conditions, and
mental health conditions. The health risk factors analysed were high blood pressure,
high cholesterol, body mass index, smoking status and alcohol use. The different
population groups were the South Australian Divisions of General Practice, quintiles
of the Socio-Economic Index for Areas (Index of Relative Socio-Economic
Disadvantage)11, and Accessibility/Remoteness Index of Australia (ARIA)12
categories.
Each of the two summary scales of the SF-12, the PCS and MCS, for 1997, 1998,
2000, and 2003 were standardised to the 2001 South Australian Census population to
account for the changing age-sex population structure over time.
The values reported in the tables for each of the two summary scales of the SF-12 are
· mean score;
· 95% confidence interval of the mean;
· median score;
· standard deviation of the mean; and
· variance of the mean.
Methods
18
19
CHAPTER 3: SF-12 POPULATION NORMS FOR
SOUTH AUSTRALIA
The frequency distributions of scores obtained in the South Australian population
(aged 18 and over) in 2003, for the two summary scores of the SF-12, are illustrated
in Figure 3.1 and Figure 3.2.
Figure 3.1: Frequency Distribution for SF-12 Physical Component Summary (PCS)
scores, 2003
0
5
10
15
20
25
30
35
40
45
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70
score
percentage (%)
Figure 3.2: Frequency Distribution for SF-12 Mental Component Summary
(MCS) scores, 2003
0
5
10
15
20
25
30
35
40
45
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70
score
percentage (%)
Norms
20
The SF-12 norms for the PCS and MCS are presented in Table 3.1 for the overall
South Australian population aged 18 years and over, as well as for both the male and
female population in 2003.
Table 3.1: 2003 SF-12 Norms for the general South Australian population, aged
18 years and over
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Overall 2013 48.9 (48.6 - 49.4) 52.9 10.2 103.7
Male 979 49.7 (49.1 - 50.3) 53.5 9.6 92.1
Female 1034 48.4* (47.7 - 49.0) 52.2 10.7 113.9
Mental Component Summary (MCS)
Overall 2013 52.4 (52.0 - 52.8) 55.3 8.8 77.3
Male 979 53.4 (52.9 - 53.9) 55.9 7.8 60.8
Female 1034 51.4* (50.8 - 52.0) 54.7 9.5 91.0
Data Source: 2003 July Health Monitor
* statistically significantly different from those without condition (t-test p<0.05).
Figure 3.3 shows the SF-12 norms (PCS and MCS) for the overall South Australian
population, and by gender. Overall, women had statistically significantly lower
scores on both the PCS and MCS summary scores than men.
Figure 3.3: 2003 SF-12 Norms for the general South Australian population,
overall, Males and Females, aged 18 years and over.
35
40
45
50
55
60
Overall Male Female
score
PCS
MC S
Norms
21
Table 3.2 to Table 3.4 and Figure 3.4 to Figure 3.6 illustrate the breakdown by 10
year age groups of the SF-12 norms for the PCS and MCS, for the overall population
in 2003, 18 years and over, as well as by gender.
When analysed by age, it can be shown that in the older age groups, the norms for the
PCS of the SF-12 were statistically significantly lower. When analysed by both age
and sex, a decline for age is evident, however this is not statistically significant. The
MCS norms remain consistent across all ages, with no statistically significant
differences, even when adjusted for sex.
Norms
22
Table 3.2: 2003 SF-12 Norms for the general South Australian population, by
age
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
18 to 24 years 237 53.3 (52.5 – 53.9) 54 5.5 30.0
25 to 34 years 360 52.5 (51.8 – 53.2) 54 6.6 42.9
35 to 44 years 403 51.3 (50.5 - 52.2) 54 8.6 74.4
45 to 54 years 373 49.2 (48.2 – 50.2) 53 9.7 94.8
55 to 64 years 257 46.7 (45.4 – 48.0) 50 10.6 113.1
65 to 74 years 198 44.4 (42.7 - 46.1) 49 12.4 152.9
75+ years 185 39.4 (37.6 - 41.2) 41 12.4 153.6
Mental Component Summary (MCS)
18 to 24 years 237 51.6 (50.5 – 52.7) 55 8.5 72.9
25 to 34 years 360 52.5 (51.6 – 53.3) 55 8.1 65.6
35 to 44 years 403 51.7 (50.9 – 52.6) 54 8.9 79.2
45 to 54 years 373 51.5 (50.5 – 52.5) 55 9.6 91.3
55 to 64 years 257 53.4 (52.4 – 54.5) 56 8.4 69.9
65 to 74 years 198 53.8 (52.7 – 55.0) 57 8.4 70.7
75+ years 185 53.6 (52.2 – 54.9) 56 9.2 83.9
Data Source: 2003 July Health Monitor
Figure 3.4: 2003 SF-12 Norms for the general South Australian population, by
age
35
40
45
50
55
60
18 to 24
years
25 to 34
years
35 to 44
years
45 to 54
years
55 to 64
years
65 to 74
years
75+
years
score
PCS
MCS
Norms
23
Table 3.3: 2003 SF-12 Norms for the general South Australian MALE population,
by age
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
18 to 24 years 121 53.9 (53.0 - 54.8) 55 5.1 25.9
25 to 34 years 181 53.1 (52.3 - 53.9) 54 5.5 30.0
35 to 44 years 199 51.2 (49.9 – 52.3) 55 8.4 70.8
45 to 54 year 184 49.3 (47.9 – 50.7) 53 9.7 93.9
55 to 64 years 128 47.0 (45.1 – 48.9) 51 10.9 117.7
65 to 74 years 94 45.5 (42.9 - 47.9) 50 12.3 151.2
75+ years 71 40.9 (38.3 – 43.4) 43 10.9 119.5
Mental Component Summary (MCS)
18 to 24 years 121 53.7 (52.5 – 54.8) 56 6.6 43.8
25 to 34 years 181 53.9 (52.9 – 54.9) 56 6.8 46.0
35 to 44 years 199 53.2 (52.1 – 54.3) 56 7.9 63.7
45 to 54 years 184 52.4 (51.1 – 53.7) 55 9.0 81.6
55 to 64 years 128 53.7 (52.4 – 55.1) 57 7.7 59.7
65 to 74 years 94 54.0 (52.5 – 55.6) 56 7.8 60.2
75+years 71 53.4 (51.5 – 55.4) 56 8.3 68.3
Data Source: 2003 July Health Monitor
Figure 3.5: 2003 SF-12 Norms for the general MALE South Australian
population by age.
35
40
45
50
55
60
18 to 24
years
25 to 34
years
35 to 44
years
45 to 54
years
55 to 64
years
65 to 74
years
75+
years
score
PCS
MCS
Norms
24
Table 3.4: 2003 SF-12 Norms for the general South Australian FEMALE
population, by age
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
18 to 24 years 115 52.6 (51.5 – 53.7) 54 5.8 33.6
25 to 34 years 179 51.9 (50.8 – 53.0) 55 7.5 55.5
35 to 44 years 204 51.4 (50.2 – 52.7) 54 8.9 78.2
45 to 54 years 189 49.1 (47.7 – 50.5) 53 9.8 96.1
55 to 64 years 130 46.4 (44.6 – 48.2) 49 10.5 109.3
65 to 74 years 104 43.4 (40.9 – 45.8) 47 12.4 153.9
75+ years 114 38.5 (36.0 – 40.9) 40 13.2 173.9
Mental Component Summary (MCS)
18 to 24 years 115 49.4 (47.6 – 51.1) 53 9.7 81.4
25 to 34 years 179 50.2 (48.9 – 51.6) 54 9.0 81.4
35 to 44 years 204 50.3 (48.9 – 51.6) 53 9.5 90.6
45 to 54 years 189 50.6 (49.2 – 52.1) 54 9.9 99.7
55 to 64 years 130 53.1 (51.6 – 54.7) 56 8.9 80.3
65 to 74 years 104 53.7 (51.9 – 55.4) 57 8.9 80.8
75+ years 114 53.6 (51.8 – 55.4) 56 9.7 94.4
Data Source: 2003 July Health Monitor
Figure 3.6: 2003 SF-12 Norms for the general FEMALE South Australian
population by age
35
40
45
50
55
60
18 to 24
years
25 to 34
ye a rs
35 to 44
ye a rs
45 to 54
ye a rs
55 to 64
years
65 to 74
years
75+
ye ar s
score
PCS
MCS
27
CHAPTER 4: SF-12 POPULATION TRENDS FOR SOUTH
AUSTRALIA
The SF-12 questionnaire has been administered in three previous SERCIS CATI surveys
(June 1997, August 1998 and November 2000), as well as July 2003. Table 4.1 shows
the trends for the SF-12 summary component mean scores over time from 1997 to 2003.
Table 4.1: Mean SF-12 scores, general South Australian population, aged 18 &
over, by year
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
June 1997 2501 49.8 (49.4 – 50.2) 53.4 9.6 92.3
August 1998 3003 49.4 (49.0 – 49.7) 52.7 9.4 87.9
November 2000 2545 49.2 (48.9 – 49.6) 52.5 9.9 97.1
July 2003 2013 48.9 (48.6 – 49.4) 53.0 10.2 103.7
Mental Component Summary (MCS)
June 1997 2501 52.1 (51.7 – 52.4) 54.8 8.5 71.6
August 1998 3003 52.2 (51.9 – 52.5) 55.1 8.8 77.8
November 2000 2545 52.3 (51.9 – 52.6) 55.0 8.6 74.2
July 2003 2013 52.4 (52.0 – 52.8) 55.0 8.8 77.3
Data Sources: 1997 Mental Health Survey; South Australian Health Goals and Targets - Survey 2: The South Australian Health
Commission Purchasing Survey, August 1998; SA CATI Health and Wellbeing Survey, November 2000; Health Monitor July
2003.
Table 4.2, Figure 4.1 and Figure 4.2 show the standardised SF-12 mean scores over
time. The scores were standardised to the 2001 South Australian Census to account for
differences in age and sex in the population over time. The standardised mean PCS
score for the year 2000 was statistically significantly lower than those for 1997 and
1998. However, the MCS summary scores did not vary significantly over time. Figure
4.3 and Figure 4.4 shows the mean PCS and MCS scores by year, for ten–year age
groups for males and females. In general, there were no differences between the age and
sex groups for either the PCS or the MCS over time.
Trends
28
Table 4.2: Mean STANDARDISED SF-12 scores (95% confidence interval of the
mean) for the general South Australian population, aged 18 and over, by year.
PCS MCS
nMean (95% CI) Mean (95% CI)
June 1997 2501 49.1 (47.2 – 51.1)2000 52.2 (50.2 – 54.1)
August 1998 3003 49.3 (47.5 – 51.1)2000 52.2 (50.4 – 54.0)
November 2000 2545 48.5 (46.5 - 50.4)1997, 1998 52.3 (50.4 – 54.3)
July 2003 2013 49.0 (46.8 – 51.2) 52.3 (50.1 – 54.5)
Data Sources: 1997 Mental Health Survey; South Australian Health Goals and Targets - Survey 2: The South Australian Health
Commission Purchasing Survey, August 1998; SA CATI Health and Wellbeing Survey, November 2000; Health Monitor July 2003.
1997 statistically significantly different from 1997 (t-test p<0.05).
1998 statistically significantly different from 1998 (t-test p<0.05).
2000 statistically significantly different from 2000 (t-test p<0.05).
Figure 4.1: Mean STANDARDISED SF-12 Physical Component Summary (PCS)
scores for the general South Australian population, aged 18 years and over by year
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
Figure 4.2: Mean STANDARDISED SF-12 Mental Component Summary (MCS)
scores for the general South Australian population, aged 18 years and over by year
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
Trends
29
Figure 4.3: Mean SF-12 Physical Component Summary (PCS) scores for the
general population, aged 18 years and over by year, for each gender and age group
Males 18 to 24 years Females 18 to 24 years
Males 25 to 34 years Females 25 to 34 years
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
Trends
30
Figure 4.3: Mean SF-12 Physical Component Summary (PCS) scores for the
general population, aged 18 years and over by year, for each gender and age group
(continued)
Males 35 to 44 years Females 35 to 44 years
Males 45 to 54 years Females 45 to 54 years
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
Trends
31
Figure 4.3: Mean SF-12 Physical Component Summary (PCS) scores for the general
population, aged 18 years and over by year, for each gender and age group (continued)
Males 55 to 64 years Females 55 to 64 years
Males 65 to 74 years Females 65 to 74 years
Males 75 plus years Females 75 plus years
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
30
35
40
45
50
55
60
65
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
30
35
40
45
50
55
60
65
1997 1998 1999 2000 2001 2002 2003
25
30
35
40
45
50
55
60
65
70
1997 1998 1999 2000 2001 2002 2003
25
30
35
40
45
50
55
60
65
70
1997 1998 1999 2000 2001 2002 2003
Trends
32
Figure 4.4: Mean SF-12 Mental Component Summary (MCS) scores for the
general population, aged 18 years and over by year, for each gender and age group
Males 18 to 24 years Females 18 to 24 years
Males 25 to 34 years Females 25 to 34 years
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
Trends
33
Figure 4.4: Mean SF-12 Mental Component Summary (MCS) scores for the general
population, aged 18 years and over by year, for each gender and age group (continued)
Males 35 to 44 years Females 35 to 44 years
Males 45 to 54 years Females 45 to 54 years
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
Trends
34
Figure 4.4: Mean SF-12 Mental Component Summary (MCS) scores for the general
population, aged 18 years and over by year, for each gender and age group (continued)
Males 55 to 64 years Females 55 to 64 years
Males 65 to 74 years Females 65 to 74 years
Males 75 plus years Females 75 plus years
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
65
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
65
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
65
1997 1998 1999 2000 2001 2002 2003
35
40
45
50
55
60
65
1997 1998 1999 2000 2001 2002 2003
35
CHAPTER 5: SF-12 BY VARIOUS CHRONIC
CONDITIONS
This section presents the South Australian SF-12 scores for selected chronic
conditions and health risk factors for people aged 18 years and over for 2000. The
SF-12 scores for this section have been obtained from the 2000 Collaborative Health
and Wellbeing Survey6.
The following chronic conditions were examined:
· diabetes,
· arthritis,
· heart disease,
· stroke,
· cancer,
· osteoporosis,
· asthma,
· other respiratory conditions, and
· mental health conditions.
SF-12 scores are also presented by number of co-morbid conditions.
Age and sex adjusted scores are presented and significant differences between people
with and without a chronic condition were examined.
Chronic Conditions
36
5.1 Diabetes
Overall, 6.2% (95% CI 5.3-7.2, n=157) of respondents in South Australia in 2000
reported having medically confirmed diabetes. Table 5.1 shows the mean SF-12
scores for South Australians diagnosed with diabetes for the year 2000.
Table 5.1: Mean SF-12 scores for South Australians doctor diagnosed with
diabetes aged 18 years and over, 2000.
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Diabetes 157 40.5 (38.6 - 42.3) 43.3 11.8 137.9
No diabetes 2388 49.8 (49.4 – 50.2) 52.9 9.4 89.0
Mental Component Summary (MCS)
Diabetes 157 52.4 (50.9 – 54.0) 54.9 10.0 100.3
No diabetes 2388 52.3 (51.9 – 52.6) 55.2 8.5 72.6
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 5.2 that people diagnosed with diabetes scored statistically
significantly lower on the PCS than people who do not have diabetes. There were no
statistically significant differences between the groups on the MCS scale.
Table 5.2: Age-sex adjusted mean SF-12 scores for South Australians diagnosed
with diabetes aged 18 years and over, 2000.
PCS MCS
nMean (95% CI) Mean (95% CI)
Diabetes 157 43.5 (42.0 – 44.9)* 51.7 (50.3 – 53.0)
No diabetes 2388 49.6 (49.2 – 49.9) 52.3 (51.9 – 52.7)
Data Source: 2000 SA Health and Wellbeing Survey
* statistically significantly different from those without condition (t-test p<0.05).
Chronic Conditions
38
5.2 Arthritis
Overall, 20.5% (95% CI 19.0-22.1, n=522) of respondents in South Australia reported
having arthritis. Table 5.3 shows the mean SF-12 scores for South Australians
diagnosed with arthritis for the year 2000.
Table 5.3: Mean SF-12 scores for South Australians diagnosed with arthritis
aged 18 years and over, 2000.
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Arthritis 522 40.9 (39.9 – 41.9) 42.2 11.5 131.5
No arthritis 2023 51.4 (51.0 – 51.7) 53.8 8.1 65.7
Mental Component Summary (MCS)
Arthritis 522 52.7 (51.9 – 53.5) 55.8 9.1 83.5
No arthritis 2023 52.2 (51.8 – 52.5) 54.9 8.5 71.8
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 5.4 that people diagnosed with arthritis scored statistically
significantly lower on the PCS of the SF-12 than people who did not have arthritis.
There were no statistically significant differences between the groups on the MCS
scale.
Figure 5.2 shows the means scores for MCS and PCS adjusted for age and sex.
Table 5.4: Age sex adjusted Mean SF-12 scores for South Australians diagnosed
with arthritis aged 18 years and over, 2000.
PCS MCS
nMean (95% CI) Mean (95% CI)
Arthritis 522 43.1 (42.3 – 43.9)* 51.9 (51.1 – 52.7)
No arthritis 2023 50.8 (50.4 – 51.2) 52.4 (51.9 – 52.7)
Data Source: 2000 SA Health and Wellbeing Survey
* statistically significantly different from those without condition (t-test p<0.05).
Chronic Conditions
40
5.3 Heart Disease
Overall, 6.2% (95% CI 5.4-7.3, n=159) of respondents in South Australia reported
ever having heart disease. Table 5.5 shows the mean SF-12 scores for South
Australians diagnosed with heart disease for the year 2000.
Table 5.5: Mean SF-12 scores for South Australians diagnosed with heart
disease aged 18 years and over, 2000.
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Heart disease 159 40.1 (38.2 – 41.9) 52.9 12.1 145.9
No heart disease 2386 49.9 (49.5 – 50.2) 40.2 9.4 87.9
Mental Component Summary (MCS)
Heart disease 159 51.7 (50.0 - 53.3) 55.9 10.7 114.4
No heart disease 2386 52.3 (51.9 –52.6) 55.0 8.5 71.6
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 5.6 and that people diagnosed with heart disease scored
statistically significantly lower than people who did not have heart disease on both
summary scores of the SF-12.
Table 5.6: Age-sex adjusted Mean SF-12 scores for South Australians diagnosed
with heart disease aged 18 years and over, 2000.
PCS MCS
nMean (95% CI) Mean (95% CI)
Heart disease 159 44.4 (42.9 – 45.9)* 50.2 (48.8 – 51.6)*
No heart disease 2386 49.6 (49.2 – 49.9) 52.4 (52.0 – 52.7)
Data Source: 2000 SA Health and Wellbeing Survey
* statistically significantly different from those without condition (t-test p<0.05).
Chronic Conditions
42
5.4 Stroke
Overall, 2.0% (95% CI 1.5-2.6, n=51) of respondents in South Australia reported ever
having a stroke. Table 5.7 shows the mean SF-12 scores for South Australians ever
having a stroke for the year 2000.
Table 5.7: Mean SF-12 scores for South Australians diagnosed with Stroke aged
18 years and over, 2000.
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Stroke 51 36.1 (33.4 – 38.7) 37.6 9.4 87.6
No stroke 2494 49.5 (49.1 – 49.9) 52.8 9.7 93.7
Mental Component Summary (MCS)
Stroke 51 51.4 (48.7 - 53.9) 52.9 9.2 84.5
No Stroke 2494 52.3 (51.9 - 52.6) 55.0 8.6 74.0
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 5.8 that people diagnosed with stroke scored statistically
significantly lower on the PCS of the SF-12, than people who did not have stroke.
There were no statistically significant differences between these groups for the MCS.
Table 5.8: Age-sex adjusted Mean SF-12 scores for South Australians diagnosed
with Stroke aged 18 years and over, 2000.
PCS MCS
nMean (95% CI) Mean (95% CI)
Stroke 51 41.2 (38.6 – 43.7)* 49.9 (47.5 – 52.3)
No stroke 2494 49.4 (49.1 – 49.7) 52.3 (51.9 – 52.6)
Data Source: 2000 SA Health and Wellbeing Survey
* statistically significantly different from those without condition (t-test p<0.05).
Chronic Conditions
44
5.5 Cancer
Table 5.9 shows the mean SF-12 scores for South Australians diagnosed with cancer
for the year 2000. Overall, 4.8% (95% CI 4.0-5.7, n=122) of respondents in South
Australia reported ever having cancer.
Table 5.9: Mean SF-12 scores for South Australians diagnosed with Cancer aged
18 years and over, 2000.
nMean 95% CI Median Standard
Deviation Varianc
e
Physical Component Summary (PCS)
Cancer 122 42.1 (40.2 – 44.0) 43.3 10.7 113.8
No cancer 2423 49.6 (49.2 – 49.9) 52.9 9.7 93.6
Mental Component Summary (MCS)
Cancer 122 52.3 (50.6 – 53.9) 55.6 9.3 87.3
No cancer 2423 52.3 (51.9 – 52.6) 55.0 8.6 73.6
Data Source: 2000 SA Health and Wellbeing Survey Note:
It can be seen from Table 5.10 that people diagnosed with cancer scored statistically
significantly lower on the PCS than people who did not have cancer. There were no
statistically significant differences between the groups on the MCS scale.
Table 5.10: Age sex adjusted Mean SF-12 scores for South Australians
diagnosed with cancer aged 18 years and over, 2000.
PCS MCS
nMean (95% CI) Mean (95% CI)
Cancer 122 45.5 (43.8 – 47.1)* 51.6 (50.0 – 53.1)
No cancer 2423 49.4 (49.1 – 49.8) 52.3 (51.9 – 52.6)
Data Source: 2000 SA Health and Wellbeing Survey
* statistically significantly different from those without condition (t-test p<0.05).
Chronic Conditions
46
5.6 Osteoporosis
Overall, 4.2% (95% CI 3.5-5.1, n=108) of respondents in South Australia reported
having osteoporosis. Table 5.11 shows the mean SF-12 scores for South Australians
diagnosed with osteoporosis for the year 2000.
Table 5.11: Mean SF-12 scores for South Australians diagnosed with
osteoporosis aged 18 years and over, 2000.
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Osteoporosis 108 38.0 (35.6 – 40.4) 38.1 12.6 157.9
No osteoporosis 2437 49.7 (49.4 – 50.1) 52.8 9.4 88.7
Mental Component Summary (MCS)
Osteoporosis 108 51.9 (50.1 – 53.8) 54.4 9.6 92.2
No osteoporosis 2437 52.6 (51.9 – 52.6) 55.1 8.6 73.5
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 5.12 and that people diagnosed with osteoporosis scored
statistically significantly lower on the PCS scale than people who did not have
osteoporosis. There were no statistically significant differences between the groups
on the MCS scale.
Table 5.12: Age sex adjusted Mean SF-12 scores for South Australians
diagnosed with Osteoporosis aged 18 years and over, 2000.
PCS MCS
nMean (95% CI) Mean (95% CI)
Osteoporosis 108 42.3 (40.5 – 44.0)* 51.2 (49.5 – 52.9)
No osteoporosis 2437 49.5 (49.2 – 49.9) 52.3 (51.9 – 52.6)
Data Source: 2000 SA Health and Wellbeing Survey
* statistically significantly different from those without condition (t-test p<0.05).
Chronic Conditions
48
5.7 Asthma
Overall, 12.7% (95% CI 11.5-14.1, n=324) of respondents have current medically
confirmed asthma. Table 5.13 shows the mean SF-12 scores for South Australians
currently diagnosed with asthma for the year 2000.
Table 5.13: Mean SF-12 scores for South Australians diagnosed with current
asthma aged 18 years and over, 2000.
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Asthma 324 47.2 (46.0 – 48.4) 50.4 10.8 116.4
No asthma 2212 49.5 (49.1 – 49.9) 52.8 9.7 93.2
Mental Component Summary (MCS)
Asthma 324 51.1 (50.1 – 52.2) 53.3 9.5 90.1
No asthma 2212 52.5 (52.1 – 52.8) 55.1 8.5 71.9
Data Source: 2000 SA Health and Wellbeing Survey.
It can be seen from Table 5.14 that people with current asthma scored statistically
significantly lower than people who did not have current asthma on the PCS of the
SF-12. There were no statistically significant differences between the groups on the
MCS scale.
Table 5.14: Age sex adjusted Mean SF-12 scores for South Australians with
current asthma aged 18 years and over, 2000.
PCS MCS
nMean (95% CI) Mean (95% CI)
Asthma 324 46.2 (45.2 – 47.2)* 51.5 (50.5 – 52.4)
No asthma 2212 49.7 (49.3 – 50.1) 52.4 (52.0 – 52.7)
Data Source: 2000 SA Health and Wellbeing Survey
* statistically significantly different from those without condition (t-test p<0.05).
Chronic Conditions
49
Figure 5.7 shows the means scores for MCS and PCS adjusted for age and sex.
Figure 5.7: Age-sex adjusted 2000 mean SF-12 scores for South Australians
diagnosed with asthma, aged 18 years and over.
35
40
45
50
55
60
PCS MCS
score
Asthma
No Asthma
Chronic Conditions
50
5.8 Other Respiratory Condition
Overall, 2.6% (95% CI 2.1-3.4, n=67) of respondents reported current respiratory
conditions other than asthma such as bronchitis, emphysema, or chronic lung disease
that has lasted six months or more for the year 2000. Table 5.15 shows the mean SF-
12 scores for South Australians ever having and currently having other respiratory
problems
Table 5.15: Mean SF-12 scores for South Australians currently diagnosed with
any other Respiratory Condition aged 18 years and over, 2000.
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Respiratory
Condition 67 36.7 (33.7 – 39.7) 37.6 12.2 147.8
No respiratory
condition 2478 49.6 (49.2 – 49.9) 52.8 9.6 91.4
Mental Component Summary (MCS)
Respiratory
condition 67 50.3 (47.8 – 52.6) 50.6 9.8 96.7
No respiratory
condition 2478 52.3 (51.9 – 52.6) 55.1 8.6 73.6
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 5.16 that people with a current respiratory condition scored
statistically significantly lower than on both summary scores people who did not have
a current respiratory condition.
Table 5.16: Age sex adjusted Mean SF-12 scores for South Australians with
current respiratory condition aged 18 years and over, 2000.
PCS MCS
nMean (95% CI) Mean (95% CI)
Respiratory condition 67 39.5 (37.3 – 41.6)* 49.0 (46.9 – 51.1)*
No respiratory condition 2478 49.5 (49.2 – 49.9) 52.4 (52.0 – 52.7)
Data Source: 2000 SA Health and Wellbeing Survey
Figure 5.8 shows the means scores for MCS and PCS adjusted for age and sex.
Chronic Conditions
52
5.9 Mental Health Condition
Current diagnosed mental health condition was determined if the respondent:
· was diagnosed with a mental health condition in the last 12 months; or
· was currently receiving treatment for a mental health condition.
Respondents indicating that a doctor had told them, in the last 12 months, that they
had a mental health condition were asked if they still had the specific condition.
Overall, 8.0% (95% CI 7.0 – 9.2, n=205) of respondents in South Australia reported a
diagnosed mental health condition using this definition. Table 5.17 shows the mean
SF-12 scores for South Australians diagnosed with a current mental health condition
for the year 2000.
Table 5.17: Mean SF-12 scores for South Australians diagnosed with current
Mental Health Condition aged 18 years and over, 2000.
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Mental health
condition 205 46.3 (44.6 – 47.9) 46.9 12.1 146.4
No mental health
condition 2340 49.5 (49.1 – 49.9) 52.8 9.6 91.9
Mental Component Summary (MCS)
Mental health
condition 205 41.5 (39.8 – 43.0) 41.6 11.7 136.3
No mental health
condition 2340 53.2 (52.9 – 53.5) 55.5 7.6 57.7
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 5.14 that people with a current mental health condition
scored statistically significantly lower on both summary scores than people who did
not have current mental health condition.
Chronic Conditions
53
Table 5.18: Age sex adjusted Mean SF-12 scores for South Australians with
current mental health condition aged 18 years and over, 2000.
PCS MCS
Mean (95% CI) Mean (95% CI)
Mental health condition 205 46.4 (45.1 – 47.6)* 41.6 (40.5 – 42.7)*
No mental health condition 2340 49.5 (49.1 – 49.9) 53.2 (52.9 – 53.5)
Data Source: 2000 SA Health and Wellbeing Survey
* statistically significantly different from those without condition (t-test p<0.05).
Figure 5.9 shows the means scores for MCS and PCS adjusted for age and sex.
Figure 5.9: Age-sex adjusted 2000 mean SF-12 scores for South Australians with
current mental health condition, aged 18 years and over.
35
40
45
50
55
60
PCS MCS
score
Mental Health Condition
No Mental Health Condition
Chronic Conditions
54
5.10 Co-morbidity
Multiple health conditions were derived by accumulating the nine health conditions
that were reported. These health conditions were diabetes, arthritis, heart disease,
stroke, cancer, osteoporosis, asthma, other respiratory conditions, and mental health
conditions. Overall, 56.4% (n = 1436) of people aged 18 and over had none of the
conditions listed, 27.7% (n=705) had one condition, 10.3% (n= 261) had two chronic
conditions, and 5.6% (n = 143) had three to five chronic conditions. No respondent in
South Australia reported having more than five chronic conditions for the year 2000.
Table 5.19: Mean SF-12 scores for South Australians diagnosed with at least one
or more chronic conditions aged 18 years and over, 2000.
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
No chronic health condition 1436 52.8 (52.5 – 53.1) 54.8 6.5 41.8
One chronic health
condition 705 47.4 (46.6 – 48.2) 49.9 10.4 107.1
Two chronic health
conditions 261 42.4 (40.9 – 43.7) 44.5 11.3 128.5
Three to five chronic health
conditions 143 35.2 (33.4 – 36.9) 33.5 10.8 117.5
Mental Component Summary (MCS)
No chronic health condition 1436 52.9 (52.6 – 53.3) 50.6 7.1 50.1
One chronic health
condition 705 52.2 (51.5 – 52.9) 55.7 9.8 95.9
Two chronic health
conditions 261 50.1 (48.8 – 51.4) 52.5 10.9 117.7
Three to five chronic health
conditions 143 49.4 (57.6 – 51.1) 50.7 10.6 111.5
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 5.14 that South Australians with the one or more chronic
conditions score statistically significantly on both summary scores lower than people
who did not have any chronic conditions.
Chronic Conditions
55
Table 5.20: Age-sex adjusted Mean SF-12 scores for South Australians with at
least one or more chronic conditions aged 18 years and over, 2000.
PCS MCS
nMean (95% CI) Mean (95% CI)
No chronic health
condition 1436 51.9 (51.5 – 52.4) 53.4 (52.9 – 53.8)
One chronic health
condition 705 48.1 (47.4 – 48.7) 52.1 (51.5 – 52.7)
Two chronic health
conditions 261 44.8 (43.7 – 45.9) 49.4 (48.4 – 50.5)
Three to five chronic
health conditions 143 40.8 (39.0 – 42.6) 48.9 (47.3 – 50.7)
Data Source: 2000 SA Health and Wellbeing Survey. Note: PCS: Physical Component Summary. MCS: Mental Component
Summary
Figure 5.10 shows the means scores for MCS and PCS adjusted for age and sex.
Analyses showed that an increasing number of conditions contributed to a statistically
significant decline in both PCS scores (F=2108.84, df=4, p<0.01), and MCS scores
(F=1603.5, df=4, p<0.01)
Figure 5.10: Age-sex adjusted 2000 SF-12 mean scores for South Australians
with one or more chronic conditions, aged 18 years and over.
35
40
45
50
55
60
No conditions One condition Two conditions Three to Five
conditions
PCS
MCS
57
CHAPTER 6: SF-12 by Health Risk Factors
This section presents the South Australian SF-12 scores for selected health risk factors
for people aged 18 years and over.
The following health risk factors were examined:
· high blood pressure,
· high cholesterol,
· body mass index,
· sufficient physical activity,
· smoking, and
· alcohol.
SF-12 scores were presented by the number of health risk factors that people may
have.
Age and sex adjusted scores were also presented to test for significant differences
between people with and without a health risk factor.
Health Risk Factors
58
6.1 High Blood Pressure
Overall, 11.0% (95% CI 9.8-12.3, n=279) of respondents in South Australia reported
having current high blood pressure. Table 6.1 shows the mean SF-12 scores for South
Australians with current high blood pressure for the year 2000.
Table 6.1: Mean SF-12 scores for South Australians diagnosed with current high
blood pressure aged 18 years and over, 2000
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
High blood pressure 279 42.6 (41.2 – 43.9) 44.8 11.9 142.5
No high blood pressure
/ don’t know 2266 50.1 (49.7 – 50.5) 53.1 9.2 85.4
Mental Component Summary (MCS)
High blood pressure 279 52.1 (50.9 – 53.2) 54.5 9.7 94.8
No high blood pressure
/ don’t know 2266 52.3 (51.9 – 52.6) 55.1 8.5 94.8
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 6.2 that people with current high blood pressure scored
statistically significantly lower scored statistically significantly lower than people who
did not have current asthma on the PCS of the SF-12. There were no statistically
significant differences between the groups on the MCS scale. than people who did
not have current high blood pressure.
Table 6.2: Age sex adjusted SF-12 Mean scores for South Australians with
current high blood pressure aged 18 years and over, 2000
PCS MCS
nMean (95% CI) Mean (95% CI)
High blood pressure 279 45.5 (44.4 – 46.5)* 51.3 (50.3 – 52.4)
No high blood pressure
/ don’t know 2266 49.7 (49.3 – 50.1) 52.4 (52.0 – 52.7)
Data Source: 2000 SA Health and Wellbeing Survey
* statistically significantly different from those without condition (t-test p<0.05).
Health Risk Factors
59
Figure 6.1 shows the means scores for MCS and PCS adjusted for age and sex.
Figure 6.1: Age-sex adjusted 2000 mean SF-12 scores for South Australians
diagnosed with high blood pressure, aged 18 years and over.
35
40
45
50
55
60
PCS MCS
score
High Blood Pressure
No / Don't Know High Blood Pressure
Health Risk Factors
60
6.2 High Cholesterol
Overall, 7.5% (95% CI 6.5-8.6, n=191) of respondents in South Australia reported
having current high cholesterol. Table 6.3 shows the mean SF-12 scores for South
Australians diagnosed with high cholesterol for the year 2000.
Table 6.3: Mean SF-12 scores for South Australians diagnosed with current high
cholesterol aged 18 years and over, 2000
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
High cholesterol 191 44.1 (44.5 – 45.8) 48.2 11.4 130.9
No high cholesterol /
don’t know 2354 49.7 (49.3 – 50.5) 52.9 9.6 92.1
Mental Component Summary (MCS)
High cholesterol 191 50.6 (49.2 – 52.1) 53.9 10.0 100.6
No high cholesterol /
don’t know 2354 52.4 (52.1 – 52.7) 55.1 8.5 71.9
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 6.4 that people with current high cholesterol score
statistically significantly lower scored statistically significantly lower on both
summary scores than people who did not have current high cholesterol.
Table 6.4: Age-sex adjusted Mean SF-12 scores for South Australians with
current high cholesterol aged 18 years and over, 2000
PCS MCS
nMean (95% CI) Mean (95% CI)
High cholesterol 191 46.8 (45.5 – 48.1)* 49.7 (45.6 – 49.2)*
No high cholesterol / Don’t
know 2354 49.4 (49.1 – 49.8) 52.5 (52.1 – 52.8)
Data Source: 2000 SA Health and Wellbeing Survey
* statistically significantly different from those without condition (t-test p<0.05).
Figure 6.2 shows the means scores for MCS and PCS adjusted for age and sex.
Health Risk Factors
62
6.3 Body Mass Index
Self reported height and weight were used to calculate Body Mass Index (BMI)14.
Overall, 3.7% (95% CI 3.0–4.5, n=94) of respondents in South Australia were
defined as underweight according to BMI, 43.8% (95% CI 41.8–45.7, n=1114) were
classified as normal, 32.2% (95% CI 30.3–34.0, n=818) were classified as
overweight, and 14.6% (95% CI 13.3–16.1, n=372) were classified as obese for the
year 2000.
Table 6.5 shows the mean SF-12 scores for South Australians in each BMI category.
Table 6.5: Mean SF-12 scores for South Australians by body mass index
category aged 18 years and over, 2000
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Underweight
(BMI < 18.50) 94 50.8 (48.9 – 52.7) 54.6 8.9 80.6
Normal Weight
(BMI 18.50 – 24.99) 1114 50.8 (50.2 – 51.3) 53.6 9.1 83.1
Overweight
(BMI 25-29.9) 818 49.1 (48.5 – 49.8) 52.0 9.4 90.6
Obese
(BMI 30.00+) 372 45.5 (44.4 – 46.6) 48.8 11.2 125.9
Mental Component Summary (MCS)
Underweight
(BMI < 18.50) 94 51.4 (49.6 – 53.3) 54.9 9.0 81.1
Normal weight
(BMI 18.50 – 24.99) 1114 52.4 (51.9 – 52.9) 55.1 8.2 67.3
Overweight
(BMI 25-29.9) 818 53.0 (52.4 – 53.6) 55.9 8.4 71.1
Obese
(BMI 30.00+) 372 50.5 (49.5 – 51.5) 53.1 9.9 98.9
Data Source: 2000 SA Health and Wellbeing Survey
Health Risk Factors
63
It can be seen from Table 6.6 that people who currently fell into the obese category
scored statistically significantly lower on the PCS compared to all other categories of
BMI. People who currently fell into the obese also score statistically significantly
lower on the MCS than those who currently fell into the normal weight or overweight
categories, but not to those who were classified as underweight.
Table 6.6: Age-sex adjusted Mean SF-12 scores for South Australians by body
mass index category aged 18 years and over, 2000
PCS MCS
nMean (95% CI) Mean (95% CI)
Underweight 94 49.7 (47.9 – 51.5) OB 52.1 (50.4 – 53.9)
Normal weight 1114 50.4 (49.8 – 50.9) OV,OB 52.6 (52.1 – 53.1) OB
Overweight 818 49.5 (48.9 – 50.2) N,OB 52.6 (52.0 – 53.2) OB
Obese 372 45.9 (44.9 – 46.8) U,N.,OV, 50.4 (49.5 – 51.2) N,OV
Data Source: 2000 SA Health and Wellbeing Survey
Ustatistically significantly different from those classified as underweight (t-test p<0.05).
Nstatistically significantly different from those classified as normal (t-test p<0.05).
OB statistically significantly different from those classified as overweight (t-test p<0.05).
OV statistically significantly different from those classified as obese (t-test p<0.05).
Figure 6.3 shows the means scores for MCS and PCS adjusted for age and sex.
Figure 6.3: Age-sex adjusted 2000 mean SF-12 scores for South Australians by
body mass index category, aged 18 years and over.
35
40
45
50
55
60
PCS MCS
score
Underweight
Normal
Overweight
Obese
Health Risk Factors
64
6.4 Smoking Status
Overall, 19.9% (95% CI 18.4-21.5, n=506) of respondents were current smokers,
39.3% (95% CI 37.4-41.2, n=1000) were ex-smokers and 40.8% (95% CI 38.9-42.8,
n=1039) were non-smokers.
Table 6.7 shows the SF-12 means scores for South Australians according to their
smoking status for the year 2000.
Table 6.7: Mean SF-12 scores for South Australians by smoking status aged 18
years and over, 2000
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Non-smoker 1039 49.8 (50.4 – 50.6) 53.0 9.8 96.2
Ex-smoker 1000 48.7 (48.1 – 49.3) 51.8 9.9 98.2
Current smoker 506 49.2 (48.3 – 50.1) 52.2 9.8 95.8
Mental Component Summary (MCS)
Non-smoker 1039 51.9 (51.3 – 52.4) 54.9 9.0 81.4
Ex-smoker 1000 53.2 (52.7 – 53.7) 55.8 8.3 65.9
Current smoker 506 51.3 (50.5 – 52.0) 53.5 8.6 73.2
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 6.8 that current smokers score statistically significantly
lower on the PCS than people who are non-smokers or ex-smokers. Ex-smokers score
statistically significantly lower on the MCS than people who are current smokers or
non-smokers.
Health Risk Factors
65
Table 6.8: Age-sex adjusted SF-12 Mean scores for South Australians by
smoking status aged 18 years and over, 2000
PCS MCS
nMean (95% CI) Mean (95% CI)
Non-smoker 1039 49.7 (49.2 – 50.3)C52.0 (51.5 – 52.6)E
Ex-smoker 1000 49.6 (49.0 – 50.2) C 52.9 (52.3 – 53.4) NC
Current smoker 506 47.5 (46.7 – 48.3)EN 51.6 (50.9 – 52.4)E
Data Source: 2000 SA Health and Wellbeing Survey
C statistically significantly different from those who are current smokers (t-test p<0.05).
E statistically significantly different from those who are ex smokers (t-test p<0.05).
N statistically significantly different from those who are non smokers (t-test p<0.05).
Figure 6.4 shows the means scores for MCS and PCS adjusted for age and sex.
Figure 6.4: Age-sex adjusted 2000 mean SF-12 scores for South Australians by
smoking status, aged 18 years and over.
35
40
45
50
55
60
PCS MCS
score
Non Smoker
Ex Smoker
Non Smoker
Health Risk Factors
66
6.5 Alcohol Use
Respondents were asked how many days during the week they consumed alcohol, as
well as the number of drinks they usually consumed in a day. Alcohol risk was then
calculated using this information to categorise respondents into non-drinkers, no risk
drinkers, low risk drinkers, intermediate risk drinkers, high risk drinkers and very high
risk drinkers15. Overall, 53.5% (95% CI 51.5-55.4, n=1361) of respondents in South
Australia were non-alcohol drinkers or were classified as no risk, 43.2% (95% CI
41.3-45.2, n=1099) of respondents were low risk drinkers and 3.3% (95% CI 2.7-4.1,
n=84) of respondents were intermediate to very high risk. Table 6.9 shows the SF-12
means scores for South Australians in different alcohol drinking categories for the
year 2000
Table 6.9: Mean SF-12 scores for South Australians in each drinking category
aged 18 years and over, 2000
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Non-Alcohol or no risk 1361 48.1 (47.5 – 48.6) 51.7 10.3 105.9
Low risk 1099 50.7 (50.2 – 51.2) 53.4 9.1 82.5
Intermediate to very
high risk 84 49.4 (47.3 – 51.5) 50.6 9.8 97.1
Mental Component Summary (MCS)
Non-Alcohol or no risk 1361 52.7 (52.2 – 53.1) 55.7 8.6 74.6
Low risk 1099 51.7 (51.2 – 52.2) 54.0 8.6 74.1
Intermediate to very
high risk 84 53.5 (51.8 – 55.3) 55.7 7.9 62.9
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 6.10 that people who were non-drinkers or in the no risk
drinking category, as well as those in the intermediate to very high risk category
scored statistically significantly lower category on the PCS than people in the low
drinking risk category. There were no statistically significant differences between
categories for the MCS.
Health Risk Factors
67
Table 6.10: Age-sex adjusted Mean SF-12 scores for South Australians in each
drinking category aged 18 years and over, 2000
PCS MCS
nMean (95% CI) Mean (95% CI)
Non-alcohol or no
risk 1361 48.2 (47.7 – 48.8)L51.9 (51.5 – 52.5)
Low risk 1099 50.7 (49.9 – 51.2)N,I 52.5 (51.9 – 53.1)
Intermediate to very
high risk 84 48.4 (46.5 – 50.4)L53.6 (51.8 – 55.4)
Data Source: 2000 SA Health and Wellbeing Survey
N statistically significantly different from those who were non-drinkers on in the no risk category(t-test p<0.05).
L statistically significantly different from those who were in the low risk category(t-test p<0.05).
I statistically significantly different from those who were in the intermediate to very high risk category(t-test p<0.05).
Figure 6.5 shows the means scores for MCS and PCS adjusted for age and sex for
each drinking category.
Figure 6.5: Age-sex adjusted 2000 Mean SF-12 scores for South Australians in
the each drinking category aged 18 years and over, overall and age adjusted by
sex.
35
40
45
50
55
60
PCS MCS
score
Non-Alcohol or No Risk
Low Risk
Intermediate to Very High Risk
Health Risk Factors
68
6.6 Multiple Risk Factors
Multiple health risk factors were derived by accumulating the five health risk factors
that were reported. These health conditions are high blood pressure, high cholesterol,
overweight and obesity, smoking and high risk alcohol use. Overall 36.8% (n=937)
of people aged 18 and over had none of the risk factors listed, 42.7% (n=1088) had
one risk factor, 16.1% (n=409) had two risk factors, and 4.4% (n=111) had three to
four risk factors. No respondents reported that they had more than four risk factors.
Table 6.11 shows the mean SF-12 scores for people with at least one or more health
risk factors for the year 2000.
Table 6.11: Mean SF-12 scores for South Australians with at least one or more
health risk factors conditions aged 18 years and over, 2000
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
No health risk factors 1436 51.3 (50.8 – 51.9) 54.1 8.7 75.3
One health risk factors 70
5
48.9 (48.4– 49.6) 52.2 9.8 96.1
Two health risk factors 261 46.8 (45.8 – 47.8) 50.4 10.5 110.9
Three or four health risk
factors 143 43.4 (41.1 – 45.7) 45.9 12.2 148.9
Mental Component Summary (MCS)
No health risk factors 1436 52.3 (51.8 – 52.9) 55.1 8.3 68.1
One health risk factors 705 52.6 (52.1 – 53.1) 55.2 8.4 71.1
Two health risk factors 261 51.8 (50.9 – 52.7) 54.9 9.5 90.7
Three or four health risk
factors 143 49.8 (47.9 – 51.5) 52.6 9.5 89.7
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 6.12 that South Australians with one or more health risk
factors scored statistically significantly lower on the PCS than people who did not
have any health risk factors. People with two or more health risk factors score
Health Risk Factors
69
statistically significantly lower on the MCS scale than people who do not any health
risk factors.
Table 6.12: Age sex adjusted SF-12 Mean scores for South Australians with at
least one or more Health Risk Factors aged 18 years and over, 2000
PCS MCS
nMean (95% CI) Mean (95% CI)
No health risk factors 1436 50.8 (50.2 – 51.4) 52.7 (52.1 – 53.2)
One health risk factors 705 49.1 (48.6 – 49.7) 52.5 (51.9 – 52.9)
Two health risk factors 261 47.2 (46.3 – 48.0) 51.6 (50.8 – 52.5)
Three or four health risk factors 143 44.7 (43.1 – 46.4) 49.1 (47.5 – 50.7)
Data Source: 2000 SA Health and Wellbeing Survey.
Figure 6.6 shows the means scores for MCS and PCS adjusted for age and sex.
Analyses showed that an increasing number of conditions contributed to a statistically
significant decline in both PCS scores (F=1749, df=4, p<0.01), and also MCS scores
(F=1540.54, df=4, p<0.01)
Figure 6.6: Age-sex adjusted 2000 SF-12 mean scores for South Australians with
one or more Health Risk Factors, aged 18 years and over.
35
40
45
50
55
60
No risk
factors
One risk
factor
Two risk
factors
Three to four
risk factors
PCS
MCS
Health Risk Factors
70
71
CHAPTER 7: SF-12 BY DIFFERENT POPULATION
GROUPS
This section presents the South Australian mean SF-12 scores for to different health
regions: South Australian Divisions of General Practice, Socio-Economic Index for
Areas (SEIFA), and Accessibility/Remoteness Index of Australia (ARIA)
classification. Age and sex adjusted scores were presented to test for significant
differences.
7.1 South Australian Divisions of General Practice
Table 7.1 shows the proportion of South Australians in each Division of General
Practice.
Table 7.1: Proportion of respondents in each South Australian Division of
General Practice aged 18 years and over.
Division of General Practice n %
Adelaide Central and Eastern 338 13.3
Adelaide Northern 295 11.6
Adelaide North East 246 9.7
Adelaide Southern 679 26.7
Adelaide Western 322 12.7
Adelaide Hills 107 4.2
Barossa 81 3.2
Eyre Peninsula 102 4.0
Flinders and Far North 51 2.0
Limestone Coast 99 3.9
Mid North Rural 67 2.6
Murray Mallee 55 2.2
Riverland 50 2.0
Yorke Peninsula 52 2.0
Data Source: 2000 SA Health and Wellbeing Survey
Table 7.2 shows the mean SF-12 scores in each Division of General Practice for the
year 2000.
Population Groups
72
Table 7.2: Mean SF-12 scores for respondents in each South Australian Division
of General Practice.
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Adelaide Central and Eastern 338 49.3 (48.2 – 50.3) 52.1 9.8 96.7
Adelaide Northern 295 48.7 (47.6 – 49.8) 51.5 9.6 91.3
Adelaide North East 246 49.4 (48.2 – 50.6) 53.2 9.7 93.3
Adelaide Southern 679 49.3 (48.5 – 50.0) 52.7 10.1 101.1
Adelaide Western 322 50.6 (49.6 – 51.7) 53.7 9.5 91.0
Adelaide Hills 107 48.2 (46.0 – 50.4) 53.1 11.5 131.9
Barossa 81 48.2 (46.3 – 50.2) 49.9 8.9 78.2
Eyre Peninsula 102 49.1 (47.1 – 51.1) 52.9 9.9 99.8
Flinders and Far North 51 49.9 (47.2 – 52.7) 53.8 9.9 97.5
Limestone Coast 99 50.2 (48.5 – 51.9) 53.1 8.6 74.5
Mid North Rural 67 47.6 (45.1 – 50.1) 51.1 10.3 106.3
Murray Mallee 55 48.1 (45.6 – 50.5) 51.2 9.1 82.3
Riverland 50 47.8 (44.8 – 50.9) 52.7 10.6 112.8
Yorke Peninsula 52 48.2 (45.2 – 51.2) 53.1 10.8 115.5
Mental Component Summary (MCS)
Adelaide Central and Eastern 338 51.8 (50.9 – 52.8) 54.9 9.1 82.8
Adelaide Northern 295 51.1 (50.1 – 52.1) 54.0 8.8 77.7
Adelaide North East 246 51.7 (50.6 – 52.9) 55.7 9.6 92.6
Adelaide Southern 679 52.7 (52.0 – 53.3) 54.9 8.1 66.0
Adelaide Western 322 51.0 (50.0 – 52.1) 54.9 9.5 89.5
Adelaide Hills 107 53.6 (52.3 – 54.8) 55.8 6.5 42.5
Barossa 81 55.2 (53.8 – 56.6) 56.5 6.3 39.3
Eyre Peninsula 102 53.3 (51.7 – 54.9) 55.5 8.2 66.5
Flinders and Far North 51 52.1 (49.6 – 54.7) 54.8 9.0 81.4
Limestone Coast 99 52.7 (51.1 – 54.4) 55.6 8.4 69.8
Mid North Rural 67 53.9 (52.1 – 55.6) 55.8 7.3 53.8
Murray Mallee 55 53.5 (51.2 – 55.8) 56.6 8.5 727
Riverland 50 52.8 (50.3 – 55.2) 55.3 8.5 72.9
Yorke Peninsula 52 53.6 (51.5 – 55.8) 55.9 7.6 58.4
Data Source: 2000 SA Health and Wellbeing Survey
Population Groups
73
Table 7.3 shows the age-sex adjusted SF-12 summary scores for the South Australian
Divisions of General Practice. The highest scoring areas on the PCS were Flinders
and Far North, Adelaide Western, and Limestone Coast Divisions of General Practice
and the lowest were Murray Mallee, Riverland and Adelaide Northern Divisions of
General Practice. The highest scores for MCS were evident in the Barossa, Mid
North Rural and Adelaide Hills Divisions of General Practice, and the lowest were in
Adelaide Western, Adelaide Northern, and Adelaide Central and Eastern.
Table 7.3: Age sex adjusted Mean SF-12 scores for each South Australian
Division of General Practice aged 18 years and over, 2000
PCS MCS
nMean (95% CI) Mean (95% CI)
Adelaide Central and Eastern 338 49.3 (48.4 – 50.3) 51.9 (50.9 - 52.8)B
Adelaide Northern 295 48.0 (46.9 – 49.1)W51.2 (50.3 - 52.2)B
Adelaide North East 246 49.4 (48.3 – 50.5) 51.9 (50.8 - 52.9)B
Adelaide Southern 679 49.6 (48.9 – 50.3) 52.6 (51.9 - 53.2)
Adelaide Western 322 50.5 (49.4 – 51.4) 50.9 (50.1 - 51.9)B
Adelaide Hills 107 48.1 (46.4 – 49.9) 53.5 (51.9 - 55.1)
Barossa 81 48.8 (46.9 – 50.8) 55.0 (53.2 - 56.9)
Eyre Peninsula 102 48.8 (47.0 – 50.5) 53.5 (51.6 - 54.9)
Flinders and Far North 51 49.7 (47.2 – 52.2) 52.3 (49.9 - 54.6)
Limestone Coast 99 50.6 (48.8 – 52.3) 52.6 (50.9 - 54.3)
Mid North Rural 67 48.2 (45.9 – 50.3) 53.7 (51.7 - 55.7)
Murray Mallee 55 47.6 (45.2 – 50.0) 53.4 (51.1 - 55.6)
Riverland 50 47.8 (45.3 – 50.3) 52.8 (50.4 - 55.1)
Yorke Peninsula 52 48.6 (46.2 – 51.1) 53.4 (51.0 - 55.7)
Data Source: 2000 SA Health and Wellbeing Survey
W statistically significantly different from those living in Adelaide Western Division (t-test p<0.05).
B statistically significantly different from those living in Barossa Division (t-test p<0.05).
Figure 7.1 show that some regions scored statistically significant differently in PCS
and MCS summary scores. Respondents in the Adelaide Northern Division of
General Practice scored statistically significantly lower on PCS scale than those than
the Adelaide Western Division.
Respondents in the Barossa Division of General Practice scored statistically
significantly higher on MCS scale than Adelaide Central and Eastern, Adelaide
Northern, Adelaide North East and Adelaide Western Division of General Practice.
Population Groups
74
Figure 7.1: Age-sex adjusted 2000 mean SF-12 Physical Component Summary
scores for South Australia in each Division of General Practice, aged 18 years
and over.
Figure 7.2: Age-sex adjusted 2000 mean SF-12 Mental Component Summary
scores for South Australia in each Division of General Practice, aged 18 years
and over.
35
40
45
50
55
60
Adelaide Central and Eastern
Adelaide Northern
Adelaide North East
Adelaide Southern
Adelaide Western
Adelaide Hills
Barossa
Eyre Peninsula
Flinders and Far North
Limestone Coast
Mid North Rural
Murray Mallee
Riverland
Yorke Peninsula
35
40
45
50
55
60
Population Groups
75
7.2 SEIFA
The Socio-Economic Index for Areas (Index of Relative Socio-Economic
Disadvantage) (SEIFA IRSD)11 scores for each South Australian postcode, were
divided into five quintiles, where the lowest quintile contained the postcodes with the
lowest 20% of socio-economic disadvantage. SF-12 Mean scores were calculated for
each SEIFA IRSD quintile. Overall 16.8% (n = 414) of people aged 18 and over fell
into the lowest (1st) SEIFA IRSD quintile, 21.9% (n = 559) fell in the 2nd SEIFA
IRSD quintile, 20.3% (n = 518) fell in the 3rd SEIFA quintile, and 17.7% (n =451) fell
in the 4th SEIFA IRSD quintile and 23.6% (n =603) fell in the highest (5th) SEIFA
IRSD quintile.
Table 7.4 shows the mean SF-12 scores for South Australians in each SEIFA IRSD
quintile for the year 2000.
Table 7.4: Mean SF-12 scores for South Australians for each SEIFA IRSD
quintile, 2000
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
1st quintile (lowest) 414 48.1 (47.0 – 49.1) 52.2 10.7 114.3
2nd quintile 559 49.3 (48.5– 50.1) 51.7 9.2 84.4
3rd quintile 518 49.7 (48.8 – 50.6) 53.2 10.2 103.3
4th quintile 451 49.5 (48.6 – 50.4) 53.2 9.8 95.6
5th quintile (highest) 603 49.4 (48.7 – 50.2) 50.2 9.6 92.1
Mental Component Summary (MCS)
1st quintile (lowest) 414 51.4 (50.5 –52.2) 53.7 8.7 74.9
2nd quintile 559 51.7 (50.9 – 52.5) 54.6 9.0 81.1
3rd quintile 518 52.1 (51.3 – 52.8) 55.0 8.5 72.4
4th quintile 451 52.8 (51.9 – 53.6) 55.8 9.1 83.6
5th quintile (highest) 603 53.2 (52.6 – 53.8) 55.2 7.8 60.5
Data Source: 2000 SA Health and Wellbeing Survey
Population Groups
76
It can be seen from Table 7.5 that South Australians who fell into the lowest (1st)
SEIFA IRSD quintile scored statistically significantly lower than people who fell into
all higher SEIFA IRSD quintiles on the PCS summary score. Those in the lowest (1st)
and 2nd SEIFA IRSD quintile, scored statistically significantly lower than people who
fell into the 4th and 5th (highest) SEIFA IRSD quintiles on the MCS summary score.
Those in the 3rd SEIFA IRSD quintile also scored statistically significantly lower than
people who fell into the 5th (highest) SEIFA IRSD quintile on the MCS summary
score. Figure 7.3 shows the mean scores for MCS and PCS adjusted for age and sex.
Table 7.5: Age-sex adjusted Mean SF-12 scores for South Australians for each
SEIFA IRSD quintile aged 18 years and over, 2000
PCS MCS
nMean (95% CI) Mean (95% CI)
1st quintile (lowest) 414 47.9 (47.0 – 48.8)2,3,4,5 51.4 (50.5 – 52.2) 4,5
2nd quintile 559 49.3 (48.6 – 50.1)151.7 (51.0 – 52.4) 4, 5
3rd quintile 518 49.5 (48.7 – 50.3)152.1 (51.3 – 52.8) 5
4th quintile 451 49.8 (48.9 – 50.6)152.9 (52.1– 53.6)1,2
5th quintile (highest) 603 49.5 (48.8 – 50.2)153.1 (52.4– 53.8)1,2,3
Data Source: 2000 SA Health and Wellbeing Survey
1 statistically significantly different from those 1st SEIFA quintile (t-test p<0.05).
2 statistically significantly different from those 2nd SEIFA quintile (t-test p<0.05).
3 statistically significantly different from those 3rd SEIFA quintile (t-test p<0.05).
4 statistically significantly different from those 4th SEIFA quintile (t-test p<0.05).
5 statistically significantly different from those 5th SEIFA quintile (t-test p<0.05).
Figure 7.3: Age-sex adjusted 2000 SF-12 mean scores for South Australians for
each SEIFA quintile, aged 18 years and over.
35
40
45
50
55
60
1st quintile 2nd quintile 3rd quintile 4th quintile 5th quintile
PCS
MCS
Population Groups
77
7.3 ARIA
Mean SF-12 scores were calculated for three categories of the
Accessibility/Remoteness Index of Australia12 (ARIA). Overall 80.7% (n = 2055) of
people aged 18 and over resided in the Metropolitan Area, 15.5% (n = 393) resided in
the Rural Area, and 3.8% (n = 97) resided in the Remote Area.
Table 7.6 shows the mean SF-12 scores for South Australians in each SEIFA quintile
for the year 2000.
Table 7.6: Mean SF-12 scores for South Australians in each ARIA Category
aged 18 years and over, 2000
nMean 95% CI Median Standard
Deviation
Variance
Physical Component Summary (PCS)
Metropolitan 2005 49.3 (48.9 – 49.7) 52.7 9.9 98.3
Rural 393 48.7 (47.7 – 49.7) 51.7 9.6 92.8
Remote 97 49.6 (47.7 – 51.5) 53.1 9.4 88.2
Mental Component Summary (MCS)
Metropolitan 2005 52.0 (51.7 – 52.4) 54.9 8.8 76.5
Rural 393 54.4 (52.7 – 54.2) 55.9 7.8 60.7
Remote 97 52.6 (50.9 – 54.4) 55.5 9.7 75.4
Data Source: 2000 SA Health and Wellbeing Survey
It can be seen from Table 7.7 that there is no difference in the PCS summary scores
between people living in different ARIA categories. Nor is there a difference in MCS
scores between those living in Metropolitan and Remote areas. However, those living
in Metropolitan areas score statistically significantly lower on the MCS than people
who live in Rural areas.
Population Groups
78
Table 7.7: Age-sex adjusted Mean SF-12 scores for South Australians in each
ARIA Category aged 18 years and over, 2000
PCS MCS
nMean (95% CI) Mean (95% CI)
Metropolitan 2005 49.3 (48.9 – 49.7) 52.0 (51.7 - 52.4)
Rural 393 49.1 (48.2 – 49.9) 53.3 (52.5 – 54.2)R
Remote 97 49.1 (47.3 – 50.9) 52.7 (51.0 – 54.4)
Data Source: 2000 SA Health and Wellbeing Survey
R statistically significantly different to those living in rural areas (t-test p<0.05).
Figure 7.4 show the mean scores for MCS and PCS adjusted for age and sex across
regions.
Figure 7.4 Age-sex adjusted Mean SF-12 scores for South Australians living each
ARIA Category aged 18 years and over, 2000.
35
40
45
50
55
60
Metropolitan Rural Remote
PCS
MCS
79
REFERENCES
1. Ware JE. The SF-36 Health Survey, Manual and Interpretation Guide.
Boston: The Health Institute, New England Medical Centre, 1993.
2. Ware J, Kosinski M, Keller S. A 12-Item Short–Form Health Survey:
Construction of Scales and Preliminary Tests of Reliability and Validity.
Medical Care. 1996; 34: 220-233.
3. McCallum J. The SF-36 Physical and Mental Health Summary Scales:
Australian Validation. Health Outcomes and Quality of Life Measurement
Conference Transcript 1995 p75-80.
4. Wilson D, Tucker G, Chittleborough C. Rethinking and rescoring the SF-12.
Social and Preventive Medicine. 2002; 47: 172-177.
5. Ware J, Kosinski M, Keller S. SF-12: How to score the SF-12 Physical and
Mental Health Summary Scales. 1995: Boston: The Health Institute, New
England Medical Centre, 1993.
6. Dal Grande E, Taylor A, and Wilson D. South Australian Health and
Wellbeing Survey, December 2000. Centre for Population Studies in
Epidemiology. Department of Human Services South Australia, 2002.
7. Taylor A, Dal Grande E, and Parsons J. Mental Health Status of South
Australians October 1997, Behavioural Epidemiology Unit, South Australian
Health Commission.
8. Taylor A, Dal Grande E, Woollacott T, Starr G. South Australian Health
Goals and Targets, Health Monitoring Indicators: Report 1 - July 1998.
Centre for Population Studies in Epidemiology. Department of Human
Services South Australia, 1998.
9. Taylor A, Dal Grande E, Starr G, McKechnie S, Griffith F, Gaughwin A. A
Survey of Ambulatory Health Services in South Australia: Where People Go
and Why - October 1998. Centre for Population Studies in Epidemiology.
Department of Human Services South Australia, 1998.
10. Kenny B. Brief Report 2002-12 The Health Monitor Survey Methodology.
Population Research and Outcome Studies Unit. 2002. Online [accessed:
January 2004] http://www.dhs.sa.gov.au/pehs/PROS/br-monitor-method02-
12.pdf
References
80
11. Australian Bureau of Statistics. Census of Population and Housing. Socio-
economic Indexes for Areas. Information paper. ABS Catalogue no. 2039.0.
1996
12. Measuring Remoteness: Accessibility/Remoteness Index of Australia (ARIA).
Information and Research Branch, Department of Health and Aged Care, and
the National Key Centre for Social Applications of Geographical Information
Systems (GISCA), University of Adelaide. Department of health and Aged
Care Occasional Papers: New Series No. 6, August 1999. Online [accessed:
October 2000] http://www.health.gov.au/ari/aria.htm
13. Wilson D, Starr G, Taylor A and Dal Grande E. Random digit dialling and
Electronic White Pages samples compared: demographic profiles and health
estimates. Australian and New Zealand Journal of Public Health. 1999; 23:
627-633.
14. World Health Organization. Obesity: preventing and managing the global
epidemic. Report of a WHO consultation on obesity. Geneva, 3-5 1997.
Geneva: WHO 2000.
15. National Heart Foundation of Australia. Risk Factor Prevalence Study:
Survey no.3 1989.
16. Australian Bureau of Statistics. Estimated Residential Population by Age and
Sex, Catalogue 3235.1 – 3235.8, 2001.
81
APPENDIX 1: HEALTH MONITOR INVITATION
LETTER
July 2003
Dear Householder,
I am writing to seek your assistance in an important health survey being conducted on behalf
of a range of organisations which are involved in the delivery of health services to South
Australians.
One of our interviewers will be contacting your household in the next few weeks to speak to
the adult in the household who had the last birthday. The interview will be conducted over
the telephone and will take around 15 minutes. Your phone number has been selected
randomly from all telephone listings in the state and over 2000 people will be interviewed. All
information collected will be confidential.
Your participation in the survey is very important. The results of the survey will help
authorities in planning and developing health services that meet the needs and concerns of
your community.
If you have any queries about the survey please contact the Population Health Study Hotline,
on 1800 635 352.
Yours sincerely,
Anne Taylor
A/Manager
Population Research and Outcome Studies Unit
Health Monitor Invitation Letter
82
83
APPENDIX 2: HEALTH MONITOR METHODOLOGY
SURVEY DESIGN
A2.1 Sample selection
All households in South Australia with a telephone connected and the telephone number
listed in the Electronic White Pages (EWP) were eligible for selection in the sample.
Telephone numbers were randomly selected from the Adelaide and country regions EWP
telephone listings13.
Within each household, the person who had their birthday last, and was 18 years or older,
was selected for interview. There was no replacement for non-contactable persons.
A2.1.1 Introductory letter
A letter introducing the survey (Appendix 1) was sent to the household of each selected
telephone number. This informed people of the purpose of the survey and indicated that they
could expect to be contacted by telephone within the time frame of the survey.
A2.1.2 Questions
The SF-12 questionnaire was obtained from the Health Institute, New England Medical
centre, Boston, Massachusetts, where the survey was developed2. In addition, 15
demographic questions were asked, as were questions regarding health risk factors. Before
the conduct of the main survey, the questionnaire was pilot tested (n=50).
A2.2 Data Collection
Data collection was undertaken by the contracted agency, Harrison Health Research. Pilot
testing took place in July 2003. The survey commenced on 9th July 2003 and concluded on
27th July 2003. Telephone calls were made between 10.00 am and 9.00 pm, seven days a
week. Professional interviewers conducted the interviews and were supervised by Harrison
Health Research and PROS personnel. Disposition codes were supplied to PROS staff daily,
or as required, to ensure careful monitoring of survey activities.
Health Monitor Methods
84
On contacting the household, the interviewer initially identified themselves and the purpose
of the survey.
A2.2.1 CATI
The CATI III (Computer Assisted Telephone Interview) system was used to conduct the
interviews. This system allows immediate entry of data from the interviewer’s questionnaire
screen to the computer database. The main advantages of this system are the precise ordering
and timing of call backs and correct sequencing of questions as specific answers are given.
The CATI system enforces a range of checks on each response with most questions having a
set of pre-determined response categories. In addition, CATI automatically rotates response
categories, when required, to minimise bias. When open-ended responses were required,
these were transcribed exactly by the interviewer.
A2.2.2 Call backs
At least ten call-backs were made to the telephone number selected to interview household
members. Different times of the day or evening were scheduled for each call-back. If a
person could not be interviewed immediately they were re-scheduled for interview at a time
suitable to them. Where a refusal was encountered, another interviewer generally (at the
discretion of the supervisor) called later, in an endeavour to obtain the interview(s).
Replacement interviews for persons who could not be contacted or interviewed were not
permitted.
A2.2.3 Validation
Of each interviewer’s work, 10% was selected at random for validation by the supervisor. In
addition, Harrison Health Research is a member of Interviewer Quality Control Australia
(IQCA), a national quality control assurance initiative of the Market Research Society of
Australia. Accredited organisations must strictly adhere to rigorous quality assurance
requirements and are subject to regular audits by IQCA auditors.
A2.2.4 Response rate
The overall response rate was 68.5%. Initially, a sample of 3400 was drawn. Sample loss
occurred due to fax / modem connections (39), non–connected numbers (374), no contact due
to no answer / always busy / answering machine (229), and non–residential numbers (62).
From the eligible sample of 2925, the response rate was calculated as shown in Table A2.1.
Health Monitor Methods
85
Table A2.1: Summary of response rate
Response rate n %
Initial Eligible Sample 2925 100.0
Refusals 423 14.5
Non-contact after 10 attempts 251 8.6
Foreign language 75 2.6
Incapacitated 103 3.5
Terminated 60.2
Respondent unavailable 63 2.2
Completed interviews 2005 68.5
The participation rate, which is the percentage of completed interviews following a
successful contact being made with the household, was 81.6%.
A2.3.2 Weighting
Weighting was used to correct for disproportionality of the sample with respect to the
population of interest16. The data were weighted by age and sex to reflect the structure of the
population in South Australia over the age of 18 years and probability of selection in the
household. Probability of selection in the household was calculated on the number of adults
in the household and the number of listings in the White Pages that reach the household.
Health Monitor Methods
86
87
APPENDIX 3: HEALTH MONITOR QUESTIONNAIRE
2003 – JULY (TRUNCATED)
INTRODUCTION
Good …… My name is …………………
I’m calling on behalf of the South
Australian Department of Human
Services. We are conducting a survey
on a range of health issues. You
were recently sent a letter about the
survey on behalf of the Department
of Human Services.
1. Did you receive the letter?
(single response)
1. Yes [ ]
2. No [ ]
3. Don’t know [ ]
Could I please speak with the person
in the household, aged 18 and over,
who was the last to have a birthday.
I can assure you that all information
given will remain confidential. The
answers from all people interviewed
will be gathered together and
presented in a report. No individual
answers will be passed on.
DEMOGRAPHICS
As some of the next questions relate
to certain groups of people only,
could you please tell me:
2. How old you are?
(single response)
1.
Enter age
__ __
2. Not stated [999]
Sequence Guide: If 2 < 999 Go to 4.
3. Which age group are you in? Would it
be …
(Read options - single response)
1. 18 to 24 years [ ]
2. 25 to 34 years [ ]
3. 35 to 44 years [ ]
4. 45 to 54 years [ ]
5. 55 to 64 years [ ]
6. 65 to 70 years [ ]
7. 71 to 74 years [ ]
8. 75 years or over [ ]
9. Refused [ ]
If 3 = 9 End interview.
4. Voice (ask if unsure)
(single response)
1. Male [ ]
2. Female [ ]
5. Including yourself, how many people
aged 18 and over live in this
household?
(Single response. Enter number of people
18 years and over. Enter 0 if none)
1.
Enter number
__ __
2. Not stated [999]
6. How many children under 18 years live
in your household?
(Single response
.
Enter number of people
18 years and over
)
1.
Enter number
__ __
2. Not stated [999]
7. What is the postcode of the house?
(Single response, enter 5999 if not known)
1.
Enter number
__ __
2. Not stated [5999]
Sequence Guide: If 7 < 5999 Go to 9
8. What town or suburb do you live in?
(Single response, enter town/suburb)
1.
Enter town/suburb
____________
Health Monitor 2003 Questionnaire
88
QUALITY OF LIFE (SF12)
These first few questions ask for your
views about your health.
9. In general, would you say your health
is:
(Read options - single response)
1. Excellent [ ]
2. Very good [ ]
3. Good [ ]
4. Fair [ ]
5. Poor [ ]
The following items are about activities
that you might do during a typical day.
10. Does your health now limit you in
undertaking moderate activities, such
as moving a table, pushing a vacuum
cleaner, bowling or playing golf? Does
your health limit you?
(Read option, single response)
1. A lot [ ]
2. A little [ ]
3. Not at all [ ]
11. What about climbing several flights of