South Australian Monitoring and Surveillance System (SAMSS) Overall Health Status of South Australians
As measured by the Single Item SF1 General Health Status Question. Jodie Avery Holly Noack Tiffany Gill Anne Taylor Population Research and Outcome Studies
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Published April 2006 by the South Australian Department of Health
Population Research and Outcome Studies Unit
PO Box 287 Rundle Mall 5000
South Australia, Australia
The National Library of Australia Cataloguing-in-Publication entry:
National Library of Australia Cataloguing-in-Publication: South Australian Monitoring and surveillance system (SAMSS) : overall health status of South Australians : as measured by the Single Item SF1 General Health Status Question. ISBN 0 7308 9553 X. 1. Health surveys - South Australia. 2. Health status indicators - South Australia. I. Avery, Jodie. II. South Australian Monitoring and Surveillance System. III. South Australia. Dept. of Health. 614.429423
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Last printed 21/06/2006
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TABLE OF CONTENTS
EXECUTIVE SUMMARY .................................................................................7
Main Findings ............................................................................................................................ 7
CHAPTER 1. INTRODUCTION .....................................................................11
1.1 Background .................................................................................................................. 12 1.2 Use of the SF1 question in surveys ............................................................................. 13
1.2.1 International Use.............................................................................................................13 1.2.2 Australia .........................................................................................................................14 1.2.3 South Australia ...............................................................................................................15
1.3 Outline of this report ..................................................................................................... 16
CHAPTER 2. METHODOLOGY ....................................................................17
2.1 Aim ............................................................................................................................... 18 2.2 The SF1 question ......................................................................................................... 18 2.3 SAMSS methodology ................................................................................................... 19
2.3.1 Sample selection .............................................................................................................19 2.3.2 Introductory letter ...........................................................................................................19 2.3.3 Data collection................................................................................................................19 2.3.4 CATI...............................................................................................................................19 2.3.5 Questionnaire..................................................................................................................20 2.3.6 Call backs .......................................................................................................................20 2.3.7 Data processing...............................................................................................................20 2.3.8 Weighting .......................................................................................................................20
2.4 Variations in survey methods ....................................................................................... 21 2.5 Statistical Analyses ...................................................................................................... 21 2.6 Response rate and sample size................................................................................... 22
CHAPTER 3. POPULATION TRENDS OF OVERALL HEALTH STATUS...23
3.1 Prevalence of SF1 responses in South Australia over time......................................... 24 3.1.1 Prevalence of SF1 grouped responses over time ............................................................24 3.1.2 Prevalence of single category SF1 responses over time .................................................26
CHAPTER 4. NORMATIVE DATA FOR OVERALL HEALTH STATUS.......29
4.1 Population norms ......................................................................................................... 30 4.1.1 Individual categories.......................................................................................................30 4.1.2 Grouped categories .........................................................................................................33
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CHAPTER 5. DEMOGRAPHIC PROFILE OF OVERALL HEALTH STATUS.......................................................................................................................37
5.1 Demographics .............................................................................................................. 38 5.2 Socioeconomic Status.................................................................................................. 40 5.3 South Australian Health Regions ................................................................................. 41
CHAPTER 6. CHRONIC CONDITIONS, RISK FACTORS AND PSYCHOSOCIAL PROFILE OF OVERALL HEALTH STATUS...................43
6.1 Chronic Conditions ....................................................................................................... 44 6.2 Risk Factors.................................................................................................................. 45 6.3 Social Capital and Food Security ................................................................................. 47 6.4 Economics and Health Service Usage......................................................................... 48 6.5 Conclusion.................................................................................................................... 50
6.5.1 Recommendations ..........................................................................................................51
REFERENCES ..............................................................................................53
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LIST OF TABLES
Table 2.1: SAMSS Sample sizes and response rates July 2002 to December 2005...22 Table 4.1: Individual SF1 responses by sex for the South Australian population, 18
years and over, SAMSS 2005 ..............................................................................31 Table 4.2: Individual SF1 responses by age group for the South Australian population,
18 years and over, SAMSS 2005 .........................................................................32 Table 4.3: Grouped SF1 responses for the South Australian population, 2005, 18
years and over ......................................................................................................33 Table 5.1: SF1 groups by general demographics, 18 years and over, SAMSS 2005 .38 Table 5.2: SF1 by employment, education, income and marital status, 18 years and
over, SAMSS 2005 ..............................................................................................39 Table 5.3: SEIFA quintile prevalence by SF1 groups, 18 years and over, SAMSS
2005......................................................................................................................40 Table 5.4: SF1 responses by South Australian Health Regions, 18 years and over,
SAMSS 2005 .......................................................................................................41 Table 6.1: SF1 responses by chronic conditions, 18 years and over, SAMSS 2005 ..44 Table 6.2: SF1 responses by behaviours and risk factors, 18 years and over, SAMSS
2005......................................................................................................................46 Table 6.3: SF1 by Social Capital and Food Security, 18 years and over, SAMSS 2005
..............................................................................................................................47 Table 6.4: SF1 responses specific by days off work and health services used in the
last four weeks, 18 years and over, SAMSS 2005...............................................48
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LIST OF FIGURES
Figure 3.1: Prevalence of South Australians aged 18 years and over reporting “Excellent, Very Good or Good” health. .............................................................24
Figure 3.2: Prevalence of South Australians aged 18 years and over reporting “Fair or Poor” health. ........................................................................................................25
Figure 3.3: Prevalence of SF1 responses over time, South Australians aged 18 years and over................................................................................................................26
Figure 3.4: Standardised Prevalence of SF1 responses over time, South Australians aged 18 years and over.........................................................................................27
Figure 4.1: Prevalence of SF1 responses for the South Australian Population 18 years and over, SAMSS 2005........................................................................................30
Figure 4.2: Age and sex specific prevalence of “Excellent, Very Good and Good” health response to the SF1 question in South Australians, 18 years and over, SAMSS 2005 .......................................................................................................34
Figure 4.3: Age and sex specific prevalence of “Fair and Poor” health response to the SF1 question in South Australian, 18 years and over, SAMSS 2005 ..................35
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EXECUTIVE SUMMARY The aim of this report is to analyse data collected by the South Australian Monitoring and Surveillance System (SAMSS) for the SF1 question from adults aged 18 years and over, by demographic, social and other health indicators.
Main Findings
• The SF1 has been shown to be a valid tool in assessing the subjective health status of the South Australian population due to its consistency of results in surveys over time.
• From January 2005 until December 2005, 84.1% of South Australian
Monitoring and Surveillance System (SAMSS) respondents reported “Excellent, Very Good or Good” health and 15.9% reported “Fair or Poor” health.
Trends Over Time
• When age and sex standardised, there is no significant trend for the categories of “Excellent”, “Very Good” or “Good” health over time when all surveys from 2002 to 2005 are included. However for the categories of “Fair” and “Poor” health there was a statistically significant downward trend.
• These trends indicate that downward changes over time are occurring in the
worst categories of overall health status.
Executive Summary
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Population Norms
• Within the categories of “Excellent” and “Good” health, there are statistically significant differences between the proportions reported by males and females in South Australians aged 18 years and over. Males reported a statistically significantly higher proportion of “Good” health, but a statistically significantly lower proportion of “Excellent” health than females.
• In general, respondents in the lower age groups were statistically significantly
more likely to report “Excellent”, “Very Good”, “Good” health, and the older age groups more likely to report “Fair” or “Poor” health, however there were variations on this for each ten year age group.
Demographics and Population Groups
• A statistically significantly higher proportion of respondents aged 18 to 24 years, 25 to 34 years and 35 to 44 years reported “Excellent, Very Good or Good” health. Those aged 55 to 64 years, 65 to 74 years and 75 years or more reported statistically significantly higher proportions of “Fair or Poor” health.
• Respondents reporting a statistically significantly higher proportion of
“Excellent, Very Good or Good” health included: • those born in Australia; • those who were not of Aboriginal or Torres Strait Islander Status; • those who were employed; • those who had completed a Bachelor degree or higher; • those who had a household income of $40,001 or higher; and • those who were married or never married.
• The groups of respondents reporting a statistically significantly higher
proportion of “Excellent, Very Good or Good” health included: • those in the low, high and highest (most advantaged) SEIFA quintiles.
• Respondents from South Australian Country health regions, overall, were
statistically significantly less likely to report “Excellent, Very Good or Good” health than those respondents in metropolitan health regions.
Executive Summary
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Social Capital and Food Security
• People who thought that their neighbourhood was a safe place, thought that people in their neighbourhood generally trusted each other, and felt safe in their home all or most of the time reported statistically significantly higher levels of “Excellent, Very Good or Good” health.
• People who were food insecure, that is they ran out of food and did not have
enough money to get more reported statistically significantly lower levels of “Excellent, Very Good or Good” health.
Risk Factors
• A statistically significantly higher proportion of South Australians who possessed the following risk factors reported “Excellent, Very Good or Good” health: • those classified as having a normal body mass index; • those with risky or high risk levels of harm form alcohol in the short term; • those undertaking sufficient physical activity; • those who were non-smokers; • those who did not have current high cholesterol; and • those who did not have current high blood pressure.
Chronic Conditions
• A statistically significantly higher proportion of respondents who reported diabetes, current asthma, chronic obstructive pulmonary disease (COPD), cardiovascular disease, arthritis, osteoporosis or a disability reported “Fair or Poor” health.
Economics
• A statistically significantly lower proportion of those who reported that they had days off work, as they were unable to work or their health inhibited them from carrying out activities, reported “Excellent, Very Good or Good” health.
Executive Summary
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Health Service Use
• A statistically significantly lower proportion of respondents who reported that they used a GP, a hospital accident and emergency department, were admitted to hospital, used a hospital clinic or used a specialist reported “Excellent, Very Good or Good” health compared to those who had not used these services in the past four weeks.
Recommendations
• Literature supports the SF1 as a practical assessment of general health status, and this has been demonstrated in this report using South Australian data. Health promotion, prevention and education efforts targeting the improvement of the health status of groups reporting statistically significantly higher levels of “Fair or Poor” health should be a priority.
CHAPTER 1. INTRODUCTION
Introduction
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1.1 Background Increasingly in health surveys, a single question asking respondents to rate their general health is being used as an indication of overall health status, in addition to other questions regarding specific illnesses, conditions and risk factors. On this basis it was decided to include a single general health question as part of the South Australian Monitoring and Surveillance System (SAMSS)1. The most common general health question has been adapted from the first question of the Medical Outcomes Study (MOS) Short Form 36 (SF36)2, and is commonly referred to as the SF1. Responses to the SF1 can be used as a general indicator of self-reported health and wellbeing3. The SF1 refers to physical and mental health, as assessed by individuals, according to their own values, and has been found to be a strong indicator of future health care use and mortality4. The purpose of this question is to obtain subjective information about health status. This provides an alternative measure of health to that derived solely from prevalence data regarding illness, death or service use5. How people rate their own health is strongly related to their own experience of illness, disability and mental health status6. Self assessed health has been used in the routine monitoring of patient care and health care services, as well as an outcome for clinical trials, and may improve doctor patient interactions7. Responses to the SF1 give a holistic indication of the health and wellbeing of the individual. In 2004, the Australian Bureau of Statistics (ABS) presented an analysis of various demographic variables by the SF1 in a paper entitled Characteristics of people reporting Good or Better Health3. Data for this same question has been collected for South Australians as part of SAMSS since 2002, and as part of other surveys such as the Health Omnibus Survey (HOS) since 1994. One of the major limitations of many health status measures is their length and difficult interpretation and scoring methodology. For routine assessment, short measures are required. It is advantageous to use the single item SF1, and it is valuable assessment of general health status8. A single item question such as the SF1 not only provides insight into overall health status, it also allows simple interpretation and scoring of responses7. When core questionnaires are already long, the burden on
Introduction
13
the patient and the research team may need to be minimised. If comprehensive coverage of health status is not required as in a cross-sectional study, a single question has great advantages, such as brevity, decreased cost and ease of interpretation8.
1.2 Use of the SF1 question in surveys On a national and international scale the SF1 has been used in a variety of settings for over half a century8. The general health question is the first question of the SF36 and SF12 questionnaires, and has been used in other health and wellbeing questionnaires as a single question to evaluate health-related quality of life.
1.2.1 International Use Internationally, the SF1 has often been used in surveys to assess the general health of the population9 and also those who experience various chronic conditions, such as diabetes, asthma and cancer, or patients undergoing specific treatments7,10-13. This enables an evaluation alternative to biomedical measures of the success of treatment for specific conditions over time. A report on the association between three different instruments, measuring health status and satisfaction among patients with diabetes, found the SF1 to be a good alternative measure to the Total Illness Burden Index - diabetes related component (DM TIBI), and the SF36 Physical Function Index (PFI10), in assessing the effectiveness of treatment over time, in addition to biomedical studies12. Another study used the SF1 as a part of the SF36 questionnaire to evaluate the quality of life of patients on maintenance haemodialysis, over time13. Answers to the question were found to accurately reflect the clinical condition of the patients, and found that the SF1 was a valid measure of health status. The SF1 has been found to be an accurate predictor of mortality and morbidity in people suffering from conditions such as asthma or diabetes, or those undergoing haemodialysis, when compared to other clinical and laboratory instruments13-15. Responses to the SF1 question have also been used as estimates for the demand on health services in Sweden16. The SF1 has been used in the United States to gain an insight into how individuals may have benefited or been disadvantaged by the US Medicare system over time17. Results indicated that further research into the assessment of the success of the Medicare system was needed, in order to improve health care services in the United States.
Introduction
14
The ability of the SF1 to measure health status in different ethnic populations has also been tested. In the United States, the SF1 was asked in a sample of the Latino population to investigate whether self rated health had limitations in predicting mortality risks for this population14. It was concluded that the use of self rated health for cross ethnic comparisons of physical health may be problematic.
1.2.2 Australia At the national level, the SF1 has been used in the 1989 Australian Health Survey and the 1995, 2001 and 2004 National Health Surveys18. These results have been reported in the Australia’s Health report series19, as well as in the Social Health Atlas of Australia 19995. The ABS compiled a report concerning characteristics of people reporting good or better health, and the validity of the SF1 as a measure of health status was explored3. It was stated that although the SF1 is a measure of perceived rather than actual health, research indicated that self assessed health status is a predictor of mortality and morbidity. While self assessed health may not always be a measure of the respondents ‘true’ health status, it does reveal something about the respondent’s perception of his or her own health at a given point in time3. Monitoring self assessed health within Australia may also help develop an understanding about the perceptions of the proportion of people who report good or better health, yet also present as high risk drinkers, current smokers, have a sedentary lifestyle or are classified as being overweight or obese. Similarly, those who have a serious health complaint but report their health as good or better may also be of interest. Research shows that overall health status indicates an individuals own sense of their condition20. Thus if an individual’s or population’s own rating of their health is at odds with their actual health or risk factors, opportunities for targeted health promotion programmes are presented. The effect that ethnicity has on SF1 results has also been tested by the ABS during 1994, using the self assessed health data from a sample of the indigenous population. The ABS suggested that the language and cultural differences between indigenous communities might have led to “Excellent, Very Good or Good”, and “Fair or Poor” health having different meanings. For example, the level of English spoken in each indigenous community varied. This makes comparisons of the SF1 between
Introduction
15
indigenous groups difficult21. Further research using a question translated into the particular indigenous languages may be warranted. The Centre for Economic Policy Research at the Australian National University, investigated the reliability and stability of the SF1 as a tool to assess general health22. Data were analysed from the 1995 Australian National Health Survey, in which a random sample of respondents answered a standard self assessed general health questionnaire. The standard questionnaire started with the SF1 and followed with a set of health-related questions. Half of these respondents answered a modified questionnaire that asked the SF1 question twice, before and after the set of health-related questions. The results from this study demonstrated that when the SF1 was asked twice in a survey, 28% of the respondents changed their reported health status. Of the respondents who changed their response, a higher level of health was reported by 13.6% and 14.8% reported a lower level of health. Further investigation found that a higher proportion of older rather than younger persons changed their SF1 response. This leads to the questioning of reliability of the SF1 as a measure of heath status, particularly in the older population22. Additionally the CATI Technical Reference Group (CATI-TRG) found that the SF1 has only fair reliability and this may indicate that this item is not a good population based indicator of health status23,24.
1.2.3 South Australia Locally, The Inequality in South Australia Report 2004 analysed SF1 responses using the ABS age standardised estimates for statistical local areas (SLA) across South Australia6. Synthetic estimates used in the National Health Survey were applied to the South Australian data in this report. These predictions are based on a model fitted to survey information when appropriate data are not available5. The estimates were initially extrapolated from the SLAs in existence at the time. The precision of these synthetic measurements of SF1 data when compared to actual current South Australian SF1 data may be deficient. The SF1 has been used in the South Australian Monitoring and Surveillance System (SAMSS) since 20021. SAMSS is able to detect changes and facilitate understandings of trends in the prevalence of chronic conditions, risk and protective factors, and other determinants of health as it is conducted monthly25. Other South Australian surveys in which the SF1 has been asked include the South Australian Health Omnibus Surveys
Introduction
16
(HOS) of 1994, 1995, 1998, 2002 and 200426,27. The South Australian Health and Wellbeing Survey 2000, also used the SF1 question, as part of the SF12 questionnaire included in the survey28. A number of Social and Environmental Risk Context Information System (SERCIS) surveys including the 1999 Interpersonal Violence Survey29, the 2001 and 2004 Physical Activity Surveys30,31 and the 2001 Gambling Survey32 have also included the SF1. This report will address the use of the SF1 as part of SAMSS.
1.3 Outline of this report The remainder of this report will describe the methodology of the South Australian Monitoring Surveillance System (SAMSS) which has been used to collect data concerning overall health status; address population trends over time for overall health status in South Australia; provide normative data for South Australia; and analyse overall health status by demographic profile, chronic conditions, risk factors and psychosocial factors.
CHAPTER 2. METHODOLOGY
Methodology
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2.1 Aim The aim of this report is to analyse data collected in South Australian population surveys using the SF1 question for adults aged 18 years and over by demographic, social and other health indicators. The objectives of this report can be summarised as follows: • To review the literature at a local, national and international level regarding the
general health question; • To determine trends over time in the prevalence of self reported general health
status using the SF1 question for respondents aged 18 years and over from the South Australian Monitoring and Surveillance System (SAMSS); and
• To analyse self reported general health status using the SF1 in 2005 by relevant
chronic conditions, risk factors, demographic variables, social and other health indicators from SAMSS in 2005, for respondents aged 18 years and over.
2.2 The SF1 question In SAMSS, the SF1 question is asked as follows:
In general, would you say your health is:
• Excellent? • Very Good? • Good? • Fair? • Poor?
The SF1 is often described by other terms, including self assessed health status, perceived health, quality of life, individual health evaluation, general health status, overall health status and single item health status. This report will refer to these as the “SF1”.
Methodology
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2.3 SAMSS methodology
2.3.1 Sample selection All households in South Australia, with a number listed in the Electronic White Pages (EWP) were eligible for selection in the sample. For the period July 2002 to December 2003, 860 South Australian residential phone numbers were randomly selected per month. Since January 2004, 1000 South Australian residential telephone numbers per month have been randomly selected. Data were collected for all age groups, using surrogate interviews with the most appropriate adult for those aged under 16 years. The SF1 question was asked of respondents aged five years and over, however for comparability purpose, only data from respondents aged 18 years and over will be analysed in this report.
2.3.2 Introductory letter A letter introducing SAMSS was sent to the household of each selected telephone number. Within each household, the person who had their birthday last was selected for interview. The letter informed people of the purpose of the survey and indicated that they could expect a telephone call within the time frame of the survey.
2.3.3 Data collection Data were collected every month by a contracted agency and interviews were conducted in English. The majority of the data used in this report were collected between January 2005 and December 2005. Overall, the response rate for SAMSS in 2005 was 71.1%. Of each interviewers work, 10% was selected at random for validation by the supervisor. The contracted agency is a member of Interviewer Quality Control Australia (IQCA).
2.3.4 CATI The Computer Assisted Telephone Interview (CATI) system was used to conduct the interviews for SAMSS. 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
Methodology
20
required, to minimise bias. When open ended responses are required, these are transcribed exactly by the interviewer.
2.3.5 Questionnaire A copy of the complete SAMSS questionnaire is available from the PROS website: http://www.dh.sa.gov.au/pehs/PROS/samss-tech-paper2-survey.pdf
2.3.6 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. Replacement interviews for persons who could not be contacted or interviewed were not permitted.
2.3.7 Data processing Following data collection, the raw data from the CATI system were imported into SPSS for analysis. Open-ended responses were saved in Excel format and the response was either coded numerically and brought into the main SPSS database, or brought into SPSS as a string variable if necessary.
2.3.8 Weighting The data were weighted by age, sex and area of residence to reflect the structure of the population in South Australia to the latest Census or Estimated Residential Population33. Probability of selection in the household was calculated based on the number of adults in the household and the number of listings in the White Pages. Weighting was used to correct for disproportionality of the sample with respect to the population of interest. The weighting of data results in occasional rounding effects for the numbers. In all instruments the percentages should be the point of reference, rather than the actual number of responses.
Methodology
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2.4 Variations in survey methods Often for the purpose of analysis, answers to the SF1 question are grouped into two categories3. In the Australian surveys when the SF1 is asked, the responses are divided into two categories, 1: “Excellent, Very Good or Good” health, and 2: “Fair or Poor” health3,6,22. When the SF1 is used internationally, a variation of these classifications may occur. For example, in the United States and Sweden, these groupings vary, with 1: “Excellent or Very Good” health and 2: “Good, Fair or Poor” health13,15. In some international cases, the SF1 question contains an increased or decreased number of response options than the usual five. In one Swedish survey the only response options to the SF1 question were “Poor”, “Fair” and “Good”16. The methodology of obtaining SF1 question responses varies world wide, and within Australia and South Australia. In the United States, the use of postal surveys is common rather than face to face and telephone surveys15. This differs from SAMSS which uses Computer Assisted Telephone Interviewing (CATI)34. In South Australia, the SF1 question has also been asked in Health Omnibus Surveys, where the methodology varies as face to face surveys are conducted at the respondent’s home26. Face to face surveys may lead to participants responding more candidly to sensitive questions such as the SF1 in order to impress the interviewer22, although this was not shown by Dal Grande35 who found that using either face-to-face or telephone surveys did not influence SF1 responses.
2.5 Statistical Analyses Data for this report were analysed using the Statistical Package for the Social Sciences (SPSS version 13.0) for Windows36 and Epi Info Version 637. Univariate analyses were conducted, using χ2 tests to detect statistically significantly differences in prevalence and trends over time and statistical significance were determined at the p<0.05 level.
Methodology
22
2.6 Response rate and sample size The response rate for SAMSS has also been just below 70% since it started in 2002. The actual number of respondents differs throughout the year in SAMSS, yet it aims to reach approximately 600 respondents each month. Table 2.1 shows the sample sizes and response rates for all respondents in surveys which included the SF1 question, as well as the number of respondents aged 18 years and over in each survey year.
Table 2.1: SAMSS Sample sizes and response rates July 2002 to December 2005
Survey Year Completed interviews
(n>=18 years) Age group Response
rate (%)
SAMSS 2002 3028 (2574) All ages 69.3 SAMSS 2003 6237 (5330) All ages 68.7 SAMSS 2004 7249 (6205) All ages 69.4 SAMSS 2005 7259 (6275) All ages 71.1
CHAPTER 3. POPULATION TRENDS OF OVERALL HEALTH STATUS
Trends
24
3.1 Prevalence of SF1 responses in South Australia over time The SF1 has been asked in SAMSS since 20021. After initial administrative questions and demographics, it is the first question regarding health asked in SAMSS.
3.1.1 Prevalence of SF1 grouped responses over time The proportion of respondents aged 18 years and over who indicated that their general health was “Excellent, Very Good or Good” or “Fair or Poor”, in response to the SF1 question in SAMSS surveys July 2002 to December 2005 is shown in Figure 3.1 and Figure 3.2.
0
20
40
60
80
100
2002 2003 2004 2005
Year
(%)
Figure 3.1: Prevalence of South Australians aged 18 years and over reporting “Excellent, Very Good or Good” health.
Trends
25
0
20
40
60
80
100
2002 2003 2004 2005
Year
(%)
Figure 3.2: Prevalence of South Australians aged 18 years and over reporting “Fair or Poor” health.
Figure 3.1 and Figure 3.2 demonstrate that there is no difference in the raw proportions of respondents reporting “Excellent, Very Good or Good” or “Fair or Poor” health between SAMSS surveys over time (2002 to 2005) (χ2 = 0.344, p = 0.557). The consistency and replication of these results indicate that the SF1 question may be suitable to be used as a measuring tool for self assessed health status, however further testing of the validity and reliability of this question is also warranted, particularly in CATI surveys. The ongoing nature of SAMSS will allow this to occur into the future.
Trends
26
3.1.2 Prevalence of single category SF1 responses over time The prevalence of each response to the SF1 question, “Excellent”, “Very Good”, “Good”, Fair” and “Poor” health, over time for the SAMSS from 2002 to 2005 in South Australians aged, 18 years and over, is demonstrated in Figure 3.3.
0
5
10
15
20
25
30
35
40
45
50
2002 2003 2004 2005Survey Year
(%)
ExcellentVery goodGoodFairPoor
Figure 3.3: Prevalence of SF1 responses over time, South Australians aged 18 years and over
Figure 3.3 shows no statistically significant trends for the categories of “Excellent” (χ2 = 3.669, p = 0.554), “Very Good” (χ2 = 0.105, p = 0.7455), “Good” (χ2 = 0.577 p = 0.4473), “Fair” (χ2 = 0.057, p = 0.8114) or “Poor” (χ2 = 0.461, p = 0.497) health between 2002 and 2005.
Trends
27
The age and sex standardised proportions for each year of SAMSS are described in Figure 3.4.
0
5
10
15
20
25
30
35
40
45
50
2002 2003 2004 2005
Survey Year
(%)
Excellent
Very Good
Good
Fair
Poor
Figure 3.4: Standardised Prevalence of SF1 responses over time, South Australians aged 18 years and over
When standardised to the 2003 South Australian estimated residential population33, some differences in trends become apparent. Figure 3.4 demonstrates that there were no significant trends for the categories of “Excellent” (χ2 = 0.584, p = 0.44482), “Very Good” (χ2 = 2.779, p = 0.09552) or “Good” (χ2 = 1.534, p = 0.21548) over time when surveys from 2002 to 2005 are included. However, there were statistically significant downward trends apparent for both “Fair” (χ2 = 44.881, p = 0.0000) and “Poor” (χ2 = 4.029, p = 0.0440) health over time.
Trends
28
CHAPTER 4. NORMATIVE DATA FOR OVERALL HEALTH STATUS
Norms
30
4.1 Population norms Normative data are presented for the general South Australian population aged 18 years and over. These data are derived from SAMSS for the period January 2005 to December 2005, as these are the most recent data available for the South Australian population.
4.1.1 Individual categories Figure 4.1 demonstrates the frequency distribution of SF1 responses for the South Australian population. The most popular response was “Very Good” (36.5%), followed by “Good” (27.9%), “Excellent” (19.8%), “Fair” (12.0%) and lastly “Poor” (3.8%).
0
5
10
15
20
25
30
35
40
Excellent Very good Good Fair Poor
(%)
Figure 4.1: Prevalence of SF1 responses for the South Australian Population 18 years and over, SAMSS 2005
Norms
31
The distribution of the proportion of the South Australian population reporting each category of SF1 response, overall and by sex is outlined in Table 4.1. Within the categories of “Excellent” and “Good” health, there are statistically significant differences between the proportions of males and females. Males reported a statistically significantly higher proportion of “Good” health, but a statistically significantly lower proportion of “Excellent” health than females.
Table 4.1: Individual SF1 responses by sex for the South Australian population, 18 years and over, SAMSS 2005
SF1 response n % 95% CI
Excellent
Overall 1096 19.8 (18.7 - 20.8)
Male 504 18.6 (17.1 - 20.1) ↓
Female 592 20.9 (19.5 - 22.5) ↑
Very Good
Overall 2025 36.5 (35.3 - 37.8)
Male 986 36.3 (34.5 - 38.1)
Female 1039 36.7 (35.0 - 38.5)
Good
Overall 1545 27.9 (26.7 - 29.1)
Male 805 29.6 (27.9 - 31.4) ↑
Female 740 26.2 (24.6 - 27.8) ↓
Fair
Overall 668 12.0 (11.2 - 12.9)
Male 328 12.1 (10.9 - 13.3)
Female 340 12.0 (10.9 - 13.3)
Poor
Overall 211 3.8 (3.3 - 4.4)
Male 95 3.5 (2.9 - 4.2)
Female 117 4.1 (3.5 - 4.9)
TOTAL 5545 100.0 Data Source: SAMSS 2005 ↑↓ Statistically significantly higher or lower than other categories (χ2 test p<0.05)
The five SF1 response categories “Excellent”, “Very Good”, “Good”, “Fair” and “Poor” health, are broken down by age group in Table 4.2.
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Table 4.2: Individual SF1 responses by age group for the South Australian population, 18 years and over, SAMSS 2005
SF1 response n % 95% CI
Excellent
18 to 24 years 135 21.8 (18.7 - 25.2)
25 to 34 years 270 28.0 (25.2 - 30.9) ↑
35 to 44 years 245 22.7 (20.3 - 25.3) ↑
45 to 54 years 192 18.9 (16.6 - 21.4)
55 to 64 years 137 17.5 (15.0 - 20.4)
65 to 74 years 65 11.8 (9.4 - 14.8) ↓
75 years plus 52 9.8 (7.5 - 12.6) ↓
Very Good
18 to 24 years 262 42.3 (38.5 - 46.2) ↑
25 to 34 years 393 40.8 (37.7 - 43.9) ↑
35 to 44 years 415 38.4 (35.5 - 41.3)
45 to 54 years 379 37.2 (34.3 - 40.2)
55 to 64 years 273 35.0 (31.7 - 38.4)
65 to 74 years 158 28.9 (25.3 - 32.9) ↓
75 years plus 144 27.0 (23.4 - 30.9) ↓
Good
18 to 24 years 170 27.5 (24.1 - 31.1)
25 to 34 years 232 24.1 (21.5 - 26.9) ↓
35 to 44 years 314 29.0 (26.4 - 31.8)
45 to 54 years 285 28.0 (25.3 - 30.8)
55 to 64 years 200 25.6 (22.6 - 28.8)
65 to 74 years 177 32.4 (28.6 - 36.4) ↑
75 years plus 167 31.2 (27.4 - 35.3)
Fair
18 to 24 years 47 7.5 (5.7 - 9.9) ↓
25 to 34 years 66 9.9 (5.4 - 8.6) ↓
35 to 44 years 80 11.9 (6.0 - 9.1) ↓
45 to 54 years 113 16.9 (9.3 - 13.2)
55 to 64 years 118 17.7 (12.8 - 17.8) ↑
65 to 74 years 110 16.5 (17.0 - 23.7) ↑
75 years plus 134 20.1 (21.7 - 29.0) ↑ Poor
18 to 24 years 6 0.9 (0.4 - 2.0) ↓
25 to 34 years 3 0.3 -- #
35 to 44 years 27 2.5 (1.8 - 3.7) ↓
45 to 54 years 49 4.8 (3.7 - 6.3)
55 to 64 years 52 6.7 (5.2 - 8.7) ↑
65 to 74 years 37 6.8 (5.0 - 9.2) ↑
75 years plus 37 6.9 (5.0 - 9.3) ↑
TOTAL 5545 100.0 Data Source: SAMSS 2005 # Insufficient numbers for statistical test ↑↓ Statistically significantly higher or lower than other categories (χ2 test p<0.05)
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When compared to other age groups, those aged 18 to 24 years were statistically significantly more likely to report “Very Good” and “Good” health, and statistically significantly less likely to report “Fair” or “Poor” health. Those aged 25 to 34 years were statistically significantly more likely to report “Excellent” and “Very Good” health and statistically significantly less likely to report “Good” or “Fair” health. Those age 35 to 44 years were statistically significantly more likely to report “Excellent” health and statistically significantly less likely to report “Fair” or “Poor” health. Those aged 55 to 64 years were statistically significantly more likely to report “Good”, “Fair” or ‘Poor” health, and statistically significantly less likely to report “Excellent” or “Very Good” health. Those aged 75 years and over were statistically significantly more likely to report “Fair” or Poor” health and statistically significantly less likely to report “Excellent” or “Very Good” health. Those respondents in the 45 to 54 year age group were not found to have any differences reporting any category when compared to other age groups.
4.1.2 Grouped categories Table 4.3 describes the overall breakdown of the categories “Excellent, Very Good or Good”, and “Fair or Poor” health for the South Australian population aged 18 years and over in 2005.
Table 4.3: Grouped SF1 responses for the South Australian population, 2005, 18 years and over
SF1 response n % 95% CI Excellent, Very Good or Good 4665 84.1 (83.2 - 85.1) Fair or Poor 879 15.9 (14.9 - 16.8) TOTAL 5545 100.0
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Figure 4.2 and Figure 4.3 indicate the age and sex specific frequency distribution of SF1 groups, for the South Australian population.
0
20
40
60
80
100
18 to 24yrs
25 to 34yrs
35 to 44yrs
45 to 54yrs
55 to 64yrs
65 to 74yrs
75 yrs andover
Agegroup
(%)
MalesFemales
Figure 4.2: Age and sex specific prevalence of “Excellent, Very Good and Good” health response to the SF1 question in South Australians, 18 years and over, SAMSS 2005
Figure 4.2 demonstrates that males aged 18 to 24 years, 25 to 34 years, and 35 to 44 years were statistically significantly more likely to report “Excellent, Very Good or Good” health, than males in the other age groups (p<0.05). Females aged 18 to 24 years, 25 to 34 years, and 35 to 44 years were also statistically significantly more likely to report “Excellent, Very Good or Good” health, than females in the other age groups in 2005 (p<0.05).
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0
20
40
60
80
100
18 to 24yrs
25 to 34yrs
35 to 44yrs
45 to 54yrs
55 to 64yrs
65 to 74yrs
75 yrs andover
Agegroup
(%)
MalesFemales
Figure 4.3: Age and sex specific prevalence of “Fair and Poor” health response to the SF1 question in South Australian, 18 years and over, SAMSS 2005
Figure 4.3 illustrates that males aged 55 to 64 years, 65 to 74 years and 75 years and over were statistically significantly more likely to report “Fair or Poor” health than males in the other age groups (p<0.05). However, only females aged 65 to 74 years and 75 years and over were statistically significantly more likely to report “Fair or Poor” health than females in the other age groups in 2005 (p<0.05).
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CHAPTER 5. DEMOGRAPHIC PROFILE OF OVERALL HEALTH
STATUS
Demographics
38
5.1 Demographics Demographic data are presented for the general South Australian population aged 18 years and over for the period January 2005 to December 2005. Table 3.1 shows SF1 by general demographic variables such as age, gender, country of birth and Aboriginal or Torres Strait Islander origin. A statistically significantly higher proportion of respondents aged 18 to 24 years, 25 to 34 years and 35 to 44 years reported “Excellent, Very Good or Good” health. Those aged 55 to 64 years, 65 to 74 years and 75 or more years reported statistically significantly higher proportions of “Fair or Poor” health. A statistically significantly higher proportion of respondents born in Australia reported “Excellent, Very Good or Good” health, as well as a statistically significantly higher proportion of those who were not of Aboriginal or Torres Strait Islander Status.
Table 5.1: SF1 groups by general demographics, 18 years and over, SAMSS 2005
Excellent, Very Good or Good Fair or Poor n % 95% CI n % 95% CI
Sex Male 2295 84.5 (83.1 - 85.8) 422 15.5 (14.2 - 16.9) Female 2370 83.8 (82.4 - 85.1) 45 16.2 (14.9 - 17.6)
Age Group 18 to 24 yrs 567 91.6 (89.1 - 93.5) ↑ 52 8.4 (6.5 - 10.9) ↓ 25 to 34 yrs 896 92.8 (91.0 - 94.3) ↑ 69 7.2 (5.7 - 9.0) ↓ 35 to 44 yrs 974 90.1 (88.2 - 91.7) ↑ 107 9.9 (8.3 - 11.8) ↓ 45 to 54 yrs 856 84.1 (81.7 - 86.2) 162 15.9 (13.8 - 18.3) 55 to 64 yrs 610 78.1 (75.1 - 80.9) ↓ 171 21.9 (19.1 - 24.9) ↑ 65 to 74 yrs 399 73.1 (69.2 - 76.6) ↓ 147 26.9 (23.4 - 30.8) ↑ 75 yrs and over 363 68.0 (63.9 - 71.8) ↓ 171 32.0 (28.2 - 36.1) ↑
Country of Birth Australia 3649 85.0 (83.9 - 86.1) ↑ 643 15.0 (13.9 - 16.1) ↓ UK / Ireland 499 83.1 (79.8 - 85.8) 102 16.9 (14.2 - 20.2) Other 517 79.4 (76.1 - 82.3) ↓ 134 20.6 (17.7 - 23.9) ↑
ATSI status No 4641 84.2 (83.2 - 85.2) ↑ 869 15.8 (14.8 - 16.8) ↓ Yes 22 72.3 (54.7 - 84.9) 9 27.7 (15.1 - 45.3) Not Stated 2 62.8 (22.0 - 91.0) # 1 37.2 (9.0 - 78.0) #
OVERALL 4665 84.1 (83.2 - 85.1) 879 15.9 (14.9 - 16.8) Data Source: SAMSS 2005 # Insufficient numbers for statistical test ↑↓ Statistically significantly higher or lower than other categories (χ2 test p<0.05)
Demographics
39
Table 5.2 shows SF1 groups by variables such as education, employment, household income and marital status. A statistically significantly higher proportion of respondents who were employed, had completed a Bachelor degree or higher, had a household income of $40,001 or higher, and those married or never married reported “Excellent, Very Good or Good” health. Conversely, a statistically significantly higher proportion of those retired or unable to work, who had no schooling or had completed secondary school, those with a household income of equal to or less than $40,000, and those separated, divorced or widowed reported “Fair or Poor” health.
Table 5.2: SF1 by employment, education, income and marital status, 18 years and over, SAMSS 2005
Excellent, Very Good or Good Fair or Poor n % 95% CI n % 95% CI
Employment Employed (self / wages / salary) 3078 91.4 (90.4 - 92.3) ↑ 288 8.6 (7.7 - 9.6) ↓
Home duties 419 81.9 (78.3 - 85.0) 93 18.1 (15.0 - 21.7) Unemployed / Student 278 87.1 (83.0 - 90.3) 41 12.9 (9.7 - 17.0)
Retired / Unable to work / other
891 66.1 (63.5 - 68.6) ↓ 457 33.9 (31.4 - 36.5) ↑
Education No schooling to secondary 2411 80.7 (79.2 - 82.0) ↓ 578 19.3 (18.0 - 20.8) ↑
Trade / Cert / Diploma 1205 85.6 (83.6 - 87.3) 203 14.4 (12.7 - 16.4)
Degree or higher 1043 91.6 (89.8 - 93.1) ↑ 96 8.4 (6.9 - 10.2) ↓ Household income
up to $20,000 503 64.9 (61.5 - 68.2) ↓ 272 35.1 (31.8 - 38.5) ↑ $20,001-40,000 901 78.3 (75.8 - 80.6) ↓ 250 21.7 (19.4 - 24.2) ↑ $40,001-60,000 790 88.8 (86.6 - 90.7) ↑ 99 11.2 (9.3 - 13.4) ↓ $60,001-80,000 721 92.9 (90.9 - 94.5) ↑ 55 7.1 (5.5 - 9.1) ↓ More than $80,000 1162 91.6 (89.9 - 93.0) ↑ 107 8.4 (7.0 - 10.1) ↓
Not stated/ ref. 589 86.1 (83.3 - 88.4) 95 13.9 (11.6 - 16.7) Marital Status
Married / De facto 3199 85.2 (84.0 - 86.3) ↑ 555 14.8 (13.7 - 16.0) ↓
Separated / Divorced 307 76.3 (71.9 - 80.2) ↓ 95 23.7 (19.8 - 28.1) ↑
Widowed 220 67.0 (61.7 - 71.9) ↓ 108 33.0 (28.1 - 38.3) ↑ Never married 936 88.6 (86.5 - 90.4) ↑ 120 11.4 (9.6 - 13.5) ↓ Refused 3 100.0 -- # 0 0.0 -- #
OVERALL 4665 84.1 (83.2 - 85.1) 879 15.9 (14.9 - 16.8) Data Source: SAMSS 2005 # Insufficient numbers for statistical test ↑↓ Statistically significantly higher or lower than other categories (χ2 test p<0.05)
Demographics
40
5.2 Socioeconomic Status Grouped SF1 responses by Socioeconomic Index for Areas, Index of Relative Socioeconomic Disadvantage (SEIFA IRSD)38 are described in Table 5.3.
Table 5.3: SEIFA quintile prevalence by SF1 groups, 18 years and over, SAMSS 2005
Excellent, Very Good or Good Fair or Poor n % 95% CI n % 95% CI
SEIFA quintile
Lowest 681 77.9 (75.0 - 80.5) ↓ 193 22.1 (19.5 - 25.0) ↑
Low 957 84.2 (82.0 - 86.2) 179 15.8 (13.8 - 18.0)
Middle 913 83.3 (81.0 - 85.4) 183 16.7 (14.6 - 19.0)
High 988 85.9 (83.8 - 87.8) 162 14.1 (12.2 - 16.2) Highest 1116 87.6 (85.7 - 89.3) ↑ 158 12.4 (10.7 - 14.3) ↓
OVERALL 4656 84.2 (83.2 - 85.1) 875 15.8 (14.9 - 16.8) Data Source: SAMSS 2005 ↑↓ Statistically significantly higher or lower than other categories (χ2 test p<0.05) The postcodes of 13 cases were not able to be classified into SEIFA quintiles
Table 5.3 demonstrates that statistically significantly higher proportions of those living in the lowest SEIFA quintile (most disadvantaged) reported “Fair or Poor” health. A statistically significantly higher proportion of those in the low, high and highest SEIFA quintiles reported “Excellent, Very Good or Good” health.
Demographics
41
5.3 South Australian Health Regions Table 5.4 demonstrates SF1 responses specific to South Australian Health regions. When the two South Australian metropolitan regions were compared with the country regions as an overall group, a statistically significantly lower proportion of those in the country regions reported “Excellent, Very Good or Good” health. When compared individually, there were no statistically significant differences in SF1 responses between South Australian Health regions.
Table 5.4: SF1 responses by South Australian Health Regions, 18 years and over, SAMSS 2005
Excellent, Very Good or Good Fair or Poor n % 95% CI n % 95% CI
Health Regions Central Northern Adelaide 2328 84.7 (83.4 - 86.0) 419 15.3 (14.0 - 16.6)
Southern Adelaide 1126 85.1 (83.1 - 87.0) 196 14.9 (13.0 - 16.9)
SA Country 1212 82.1 (80.1 - 84.0) ↓ 264 17.9 (16.0 - 19.9) ↑
Health Regions Central Northern Adelaide 2328 84.7 (83.4 - 86.0) 419 15.3 (14.0 - 16.6)
Southern Adelaide 1126 85.1 (83.1 - 87.0) 196 14.9 (13.0 - 16.9)
Hills Mallee 348 79.5 (75.4 - 83.0) 90 20.5 (17.0 - 24.6)
Wakefield 293 84.3 (80.1 - 87.8) 54 15.7 (12.2 - 19.9)
Mid North 73 76.9 (67.5 - 84.2) 22 23.1 (15.8 - 32.5)
Riverland 98 84.5 (76.8 - 89.9) 18 15.5 (10.1 - 23.2)
South East 210 85.9 (81.0 - 89.7) 35 14.1 (10.3 - 19.0)
Eyre 87 80.8 (72.3 - 87.1) 21 19.2 (12.9 - 27.7) Northern & Far Western 102 80.8 (73.1 - 86.7) 24 19.2 (13.3 - 26.9)
OVERALL 4665 84.1 (83.2 - 85.1) 879 15.9 (14.9 - 16.8) Data Source: SAMSS 2005 ↑↓ Statistically significantly higher or lower than other categories (χ2 test p<0.05)
Demographics
42
CHAPTER 6. CHRONIC CONDITIONS, RISK FACTORS
AND PSYCHOSOCIAL PROFILE OF OVERALL HEALTH STATUS
Conditions and Risks
44
6.1 Chronic Conditions Respondents were asked a range of questions concerning conditions such as diabetes, asthma, chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), osteoporosis and arthritis. The definition used for current asthma is whether respondents had ever been told by a doctor that they had asthma, and had experienced symptoms (wheeze, shortness of breath or chest tightness) of asthma in the last 12 months, or had taken treatment for asthma in the last 12 months39. Disability was determined by respondents stating that they were limited in any way in any activities because of an impairment or health problem. It can be seen from Table 6.1 that a statistically significantly higher proportion of respondents who reported diabetes, current asthma, chronic obstructive pulmonary disease (COPD), cardiovascular disease, arthritis, osteoporosis or a disability reported “Fair or Poor” health.
Table 6.1: SF1 responses by chronic conditions, 18 years and over, SAMSS 2005
Excellent, Very Good or Good Fair or Poor n % 95% CI n % 95% CI
Diabetes
No 4455 85.6 (84.6 - 86.5) ↑ 751 14.4 (13.5 - 15.4) ↓ Yes 210 62.1 (56.8 - 67.1) ↓ 128 37.9 (32.9 - 43.2) ↑
Current Asthma (ACAM Def)
No / Don't Know 4068 85.1 (84.1 - 86.1) ↑ 713 14.9 (13.9 - 15.9) ↓ Yes 598 78.2 (75.1 - 81.0) ↓ 167 21.8 (19.0 - 24.9) ↑
COPD
No / Don't Know 4463 85.3 (84.3 - 86.2) ↑ 768 14.7 (13.8 - 15.7) ↓ Yes 202 64.6 (59.1 - 69.7) ↓ 111 35.4 (30.3 - 40.9) ↑
Cardiovascular disease (heart attack / angina)
No 4439 86.7 (85.8 - 87.6) ↑ 680 13.3 (12.4 - 14.2) ↓ Yes 226 53.2 (48.4 - 57.9) ↓ 199 46.8 (42.1 - 51.6) ↑
Arthritis No 3825 89.4 (88.4 - 90.3) ↑ 455 10.6 (9.7 - 11.6) ↓ Yes 841 66.4 (63.8 - 69.0) ↓ 425 33.6 (31.0 - 36.2) ↑
Osteoporosis No /Don't Know 4525 85.6 (84.6 - 86.5) ↑ 762 14.4 (13.5 - 15.4) ↓ Yes 140 54.5 (48.4 - 60.4) ↓ 117 45.5 (39.6 - 51.6) ↑
Disability No/ Don’t know 3948 91.4 (90.5 - 92.2) ↑ 374 8.6 (7.8 - 9.5) ↓ Yes 717 58.7 (55.9 - 61.4) ↓ 506 41.3 (38.6 - 44.1) ↑
OVERALL 4665 84.1 (83.2 - 85.1) 879 15.9 (14.9 - 16.8) Data Source: SAMSS 2005 ↑↓ Statistically significantly higher or lower than other categories (χ2 test p<0.05)
Conditions and Risks
45
6.2 Risk Factors Respondents were asked a range of questions concerning behaviours such as smoking, drinking alcohol and levels of physical activity performed, and questions on risk factors such as height and weight. The SF1 responses of respondents are described in Table 6.2. A statistically significantly higher proportion of those classified as having a normal body mass index (BMI) (weight (kg)/ height2 (m2)), according to the World Health Organization classifications40 reported “Excellent, Very Good or Good” health. Of those respondents classified as obese, a statistically significant higher proportion reported “Fair or Poor” health. A statistically significant higher proportion of those with risky or high risk levels of harm from alcohol in the short-term, reported “Excellent, Very Good or Good” health. Those who undertook no physical activity reported statistically significantly lower proportions of “Excellent, Very Good or Good” health. Those reporting activity but not sufficient according to Sufficient Physical Activity Definition 141 also reported a statistically significantly lower proportion of “Excellent, Very Good or Good” health. However, a statistically significantly higher proportion of those undertaking sufficient physical activity (Definitions 1 and 2) reported “Excellent, Very Good or Good” health. Respondents who were non-smokers were statistically significantly more likely to report “Excellent, Very Good or Good” health. A statistically significantly higher proportion of ex or current smokers reported “Fair or Poor” health. Respondents who had been told by a doctor that they currently had high cholesterol reported statistically significantly lower levels of “Excellent, Very Good or Good” health as did those respondents who had been told by a doctor that they currently had high blood pressure, or were taking medication for high blood pressure.
Conditions and Risks
46
Table 6.2: SF1 responses by behaviours and risk factors, 18 years and over, SAMSS 2005
Excellent, Very Good or Good Fair or Poor n % 95% CI n % 95% CI
BMI Classification* Underweight (up to 18.5) 102 85.8 (78.4 - 91.0) 17 14.2 (9.0 - 21.6)
Normal (18.5 to 24.9) 2011 87.8 (86.4 - 89.1) ↑ 280 12.2 (10.9 - 13.6) ↓
Overweight (25 to 29.9) 1609 84.5 (82.8 - 86.0) 296 15.5 (14.0 - 17.2)
Obese (30 and over) 715 76.4 (73.6 - 79.0) ↓ 220 23.6 (21.0 - 26.4) ↑
OVERALL 4436 84.5 (83.5 - 85.5) 813 15.5 (14.5 - 16.5) Alcohol - Short term risk*
Non-drinker / Low risk 3239 83.2 (82.0 - 84.3) ↓ 656 16.8 (15.7 - 18.0) ↑
Risky / High-risk 1422 86.4 (84.7 - 88.0) ↑ 224 13.6 (12.0 - 15.3) ↓ Alcohol - Long term risk*
Non-drinker / Low risk 4485 84.1 (83.1 - 85.0) 848 15.9 (15.0 - 16.9)
Risky / High-risk 176 85.2 (79.7 - 89.4) 31 14.8 (10.6 - 20.3) OVERALL 4662 84.2 (83.1 - 85.1) 879 15.8 (14.9 - 16.9)
Physical Activity D1*
No activity 756 71.5 (68.7 - 74.1) ↓ 301 28.5 (25.9 - 31.3) ↑ Activity but not sufficient 1400 81.7 (79.8 - 83.5) ↓ 314 18.3 (16.5 - 20.2) ↑
Sufficient activity 2467 90.6 (89.4 - 91.6) ↑ 256 9.4 (8.4 - 10.6) ↓ OVERALL 4622 84.1 (83.1 - 85.1) 871 15.9 (14.9 - 16.9)
Physical Activity D2*
No activity 756 71.5 (68.7 - 74.1) ↓ 301 28.5 (25.9 - 31.3) ↑ Activity but not sufficient 1910 83.8 (82.2 - 85.2) 371 16.2 (14.8 - 17.8)
Sufficient activity 1947 90.7 (89.5 - 91.9) ↑ 198 9.3 (8.1 - 10.5) ↓ OVERALL 4613 84.1 (83.1 - 85.1) 870 15.9 (14.9 - 16.9)
Smoking Status
Non-smoker 2050 86.9 (85.5 - 88.2) ↑ 309 13.1 (11.8 - 14.5) ↓
Ex-smoker 1744 82.3 (80.7 - 83.9) ↓ 374 17.7 (16.1 - 19.3) ↑
Smoker 872 81.6 (79.1 - 83.8) ↓ 197 18.4 (16.2 - 20.9) ↑ Current High Blood Pressure
No / Don’t know 3984 88.0 (87.0 - 88.9) ↑ 545 12.0 (11.1 - 13.0) ↓
Yes 681 67.1 (64.2 - 69.9) ↓ 334 32.9 (30.1 - 35.8) ↑ Current High Cholesterol
No / Don’t know 4125 86.5 (85.5 - 87.4) ↑ 646 13.5 (12.6 - 14.5) ↓
Yes 540 69.8 (66.5 - 73.0) ↓ 234 30.2 (27.0 - 33.5) ↑ OVERALL 4665 84.1 (83.2 - 85.1) 879 15.9 (14.9 - 16.8)
Data Source: SAMSS 2005. ↑↓ Statistically significantly higher or lower than other categories (χ2 test p<0.05) * Total number of respondents varies in each case due to missing data required to calculate derived variables.
Conditions and Risks
47
6.3 Social Capital and Food Security Social capital generally relates to the non-financial resources available within a community or a family such as the collective value of all "social networks" and the inclinations that arise from these networks to do things for each other42. A number of questions were asked to establish the level of social capital within South Australia. The data are presented in grouped SF1 responses in Table 6.3.
Table 6.3: SF1 by Social Capital and Food Security, 18 years and over, SAMSS 2005
Excellent, Very Good or Good Fair or Poor n % 95% CI n % 95% CI
Neighborhood a safe place*
No/Don't know 125 77.7 (70.7 - 83.4) ↓ 36 22.3 (16.6 - 29.3) ↑ Yes 1426 84.6 (82.8 - 86.2) ↑ 260 15.4 (13.8 - 17.2) ↓
People generally trust each other*
No/Don't know 281 80.9 (76.4 - 84.6) 67 19.1 (15.4 - 23.6) Yes 1270 84.7 (82.8 - 86.5) 229 15.3 (13.5 - 17.2)
Feel safe in home*
Some/None of time/don’t know 35 70.4 (56.6 - 81.2) ↓ 15 29.6 (18.8 - 43.4) ↑
All/ Most of the time 1516 84.4 (82.6 - 86.0) ↑ 281 15.6 (14.0 - 17.4) ↓
Control over decisions *
Disagree/Neutral/Don't know 100 68.3 (60.4 - 75.2) ↓ 47 31.7 (24.8 - 39.6) ↑
Agree 1450 85.4 (83.6 - 87.0) ↑ 249 14.6 (13.0 - 16.4) ↓ OVERALL 1551 84.0 (82.3 - 85.6) 296 16.0 (14.4 - 17.7)
Food Insecure* No/Don't know 1469 84.4 (82.6 - 86.0) ↑ 271 15.6 (14.0 - 17.4) ↓ Yes 62 61.9 (52.1 - 70.8) ↓ 38 38.1 (29.2 - 47.9) ↑
OVERALL 1531 83.2 (81.4 - 84.8) 309 16.8 (15.2 - 18.6) Data Source: SAMSS 2005 * Question only asked eight months in the year ↑↓ Statistically significantly higher or lower than other categories (χ2 test p<0.05)
A statistically significantly higher proportion of South Australians who felt that their neighbourhood was a safe place reported “Excellent, Very Good or Good” health, as did those who felt safe in their home all or most of the time. Additionally a statistically significantly higher proportion of people who had control over life decisions reported “Excellent, Very Good or Good” health. A statistically significantly higher level of people who ran out of food and did not have enough money to buy more, known as those who were Food Insecure, reported “Fair or Poor” health.
Conditions and Risks
48
6.4 Economics and Health Service Usage Respondents were asked a range of questions concerning how many days off work they had taken in the past four weeks and also how often they used specific health services. The proportions reporting “Excellent, Very Good or Good” or “Fair or Poor” health are described in Table 6.4
Table 6.4: SF1 responses specific by days off work and health services used in the last four weeks, 18 years and over, SAMSS 2005
Excellent, Very Good or Good Fair or Poor n % 95% CI n % 95% CI
Days unable to work
None 4053 87.0 (86.0 - 87.9) ↑ 608 13.0 (12.1 - 14.0) ↓
At least one day 612 69.3 (66.2 - 72.3) ↓ 271 30.7 (27.7 - 33.8) ↑ Unable to carry out activities due to health
None 3806 89.0 (88.0 - 89.9) ↑ 470 11.0 (10.1 - 12.0) ↓
At least one day 859 67.7 (65.1 - 70.2) ↓ 409 32.3 (29.8 - 34.9) ↑ Used a GP
None 3173 90.3 (89.2 - 91.2) ↑ 342 9.7 (8.8 - 10.8) ↓
At least one day 1492 73.5 (71.6 - 75.4) ↓ 537 26.5 (24.6 - 28.4) ↑ Used hospital accident and emergency dept
None 4579 84.5 (83.5 - 85.4) ↑ 842 15.5 (14.6 - 16.5) ↓
At least one day 86 69.9 (61.3 - 77.3) ↓ 37 30.1 (22.7 - 38.7) ↑
Admitted to hospital
None 4580 84.6 (83.6 - 85.6) ↑ 833 15.4 (14.4 - 16.4) ↓
At least one day 85 64.8 (56.3 - 72.4) ↓ 46 35.2 (27.6 - 43.7) ↑
Used a hospital clinic
None 4429 85.4 (84.4 - 86.4) ↑ 756 14.6 (13.6 - 15.6) ↓
At least one day 236 65.6 (60.6 - 70.3) ↓ 124 34.4 (29.7 - 39.4) ↑
Used a specialist
None 4240 85.3 (84.3 - 86.3) ↑ 729 14.7 (13.7 - 15.7) ↓
At least one day 425 73.9 (70.2 - 77.3) ↓ 150 26.1 (22.7 - 29.8) ↑ OVERALL 4665 84.1 (83.2 - 85.1) 879 15.9 (14.9 - 16.8)
Data Source: SAMSS 2005 ↑↓ Statistically significantly higher or lower than other categories (χ2 test p<0.05)
Table 6.4 indicates that a statistically significantly lower proportion of those who reported that they had days off work as they were unable to work or their health inhibited them from carrying out activities reported “Excellent, Very Good or Good” health. Additionally, a statistically significantly lower proportion of respondents who
Conditions and Risks
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reported that they used a GP, a hospital accident and emergency department, were admitted to hospital, used a hospital clinic or used a specialist reported “Excellent, Very Good or Good” health compared to those who had not use these services in the past four weeks.
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6.5 Conclusion Responses to the overall health question (SF1) in South Australian surveys demonstrate that it is generally a reliable measuring tool of self assessed health, as consistent prevalence of responses are shown over time. The SF1 is able to be used as a subjective tool to measure overall health status. Over time, standardised prevalence data for SAMSS surveys indicated statistically significantly downward trends over time for “Fair” and “Poor” health. These trends indicate that changes over time are occurring in the worst categories of overall health status. SF1 responses were also examined specific to demographics, population groups, social capital, behavioural and health risk factors, long term conditions and actions taken. These results demonstrated that specific variables lead to increased reporting of “Fair or Poor” health. Groups that report “Fair or Poor” health should be paid special attention when overall population health is being considered. The SF1 is statistically significantly associated with health and risk factors and this has been shown using SAMSS data. This indicates that, in general, the SF1 identifies “Fair or Poor” health in the case of those with chronic conditions and health risk factors, and “Excellent, Very Good or Good” health in the absence of chronic conditions.
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6.5.1 Recommendations The SF1 should continue to be used as a tool to measure overall health status. SF1 responses in various surveys demonstrated that the SF1 is a satisfactory measuring tool of self assessed health showing consistency over time. Groups that report “Fair or Poor” health should be paid special attention when overall population health is being considered. Health promotion, prevention and education efforts targeting the improvement of the health status of these groups reporting statistically significantly higher levels of “Fair or Poor” health should be a priority. Conversely, it is important to monitor people who report good or better health, yet also present as high risk drinkers, are current smokers, have a sedentary lifestyle or are classified as being overweight or obese. Similarly, those who have a serious health complaint but report their health as good or better may also be of interest, as they may not be aware of opportunities available to them to better their health, or reduce their risk.
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REFERENCES
1. Population Research and Outcome Studies Unit. The South Australian Monitoring and Surveillance System (SAMSS) 2002 - 20. Brief Report. Vol. 2005 South Australian Department of Health, 2002.
2. Ware J, Donald Sherbourne C. The MOS 36-Item Short-Form Health Survey (SF-36). Medical Care 1992;30(6):473-83.
3. Australian Bureau of Statistics. 4828.0.55.001 Characteristics of People Reporting Good or Better Health. 2004.
4. McCallum J, Shadbolt B, Wang D. Self-rated health and survival: a 7-year follow-up study of Australian elderly. Am J Public Health 1994;84(7):1100-5.
5. Glover J, Tennant S. A Social Health Atlas of Australia. 2nd ed. Vol. 5. South Australia Commonwealth of Australia, 1999.
6. Hetzel D, Page A, Glover J, Tennant S. Inequality in South Australia. Key Determinants of Well being. Vol. 1. The Evidence South Australia Department of Health, 2004.
7. Jenkinson C, Peto V, Coulter A. Measuring change over time: a comparison of results from a global single item of health status and the multi-dimensional SF-36 health status survey questionnaire in patients presenting with menorrhagia. Qual Life Res 1994;3(5):317-21.
8. Bowling A. Just one question: If one question works, why ask several? J Epidemiol Community Health 2005;59(5):342-345.
9. Ahluwalia IB, Holtzman D, Mack KA, Mokdad A. Health-related quality of life among women of reproductive age: Behavioral Risk Factor Surveillance System (BRFSS), 1998-2001. J Womens Health (Larchmt) 2003;12(1):5-9.
10. Juniper EF, Buist AS, Cox FM, Ferrie PJ, King DR. Validation of a Standardized Version of the Asthma Quality of Life Questionnaire. Chest 1999;115(5):1265-1270.
11. Wagner J. Acceptability of the Schedule for the Evaluation of Individual Quality of Life-Direct Weight (SEIQoL-DW) in youth with type 1 diabetes. Quality of Life Research 2004;13(7):1279-1285.
References
54
12. Kerr EA, Smith DM, Kaplan SH, Hayward RA. The Association between Three Different Measures of Health Status and Satisfaction among Patients with Diabetes. Med Care Res Rev 2003;60(2):158-177.
13. Kalantar-Zadeh K, Kopple JD, Block G, Humphreys MH. Association Among SF36 Quality of Life Measures and Nutrition, Hospitalization, and Mortality in Hemodialysis. J Am Soc Nephrol 2001;12(12):2797-2806.
14. Finch BK, Hummer RA, Reindl M, Vega WA. Validity of Self-rated Health among Latino(a)s. Am. J. Epidemiol. 2002;155(8):755-759.
15. Wyshak G. Behavioral practices and mortality in women former college athletes and nonathletes. Health Care Women Int 2003;24(9):808-21.
16. Gerdtham U-G, Johannesson M. New estimates of the demand for health: results based on a categorical health measure and Swedish micro data. Social Science & Medicine 1999;49(10):1325-1332.
17. Haffer SC, Bowen SE. Measuring and improving health outcomes in Medicare: the Medicare HOS program. Health Care Financ Rev 2004;25(4):1-3.
18. Australian Bureau of Statistics. 4364.0 National Health Survey 2001: Summary of Results. Vol. 2004, 2002.
19. Australian Institute of Health and Welfare. Australia's Health 2002. Canberra: AIHW, 2002.
20. Goldstein MS, Siegel JM, Boyer R. Predicting changes in perceived health status. Am J Public Health 1984;74(6):611-4.
21. Cunningham J, Sibthorpe B, Anderson I. 4707.0 Occasional Paper: Self-Assessed Health Status, Indigenous Australians, 1994. Vol. 2004 Australian Bureau of Statistics, 1997.
22. Crossley TF, Kennedy S. The reliability of self-assessed health status. J Health Econ 2002;21(4):643-58.
23. Daly A, Taylor A. Results of Field testing Three Modules of Core Health questions for Inclusion in a Nation-Wide Preventable Chronic Disease and Behavioural Risk Factor Survey Module Manual. Canberra: CATI Technical Reference Group, National Public Health Partnership, 2003.
References
55
24. Daly A, Taylor A. Results of Second Field testing Three Modules of Core Health questions for Inclusion in a Nation-Wide Preventable Chronic Disease and Behavioural Risk Factor Survey Module Manual. Canberra: CATI Technical Reference Group, National Public Health Partnership, 2004.
25. Population Research and Outcome Studies Unit. SAMSS Survey Questionnaire. South Australian Monitoring and Surveillance System (SAMSS) Technical Paper Series No. 2/04. Vol. 2005 South Australian Department of Health, 2004.
26. Population Research and Outcome Studies Unit. The Health Omnibus Survey (HOS) Methodology 2002-04. Brief Report South Australian Department of Health, 2002.
27. Wilson DW, M. Taylor, A. The South Australian Health Omnibus Survey. Health Promotion Journal of Australia. 1992;2(3):47-49.
28. Dal Grande E, Taylor A, Wilson D. South Australian Health and Wellbeing Survey - December 2000. Vol. 2005 South Australian Department of Human Services, 2000.
29. Dal Grande E, Woollacott T, Taylor A, Starr G, Anastassiadis K, Ben-Tovim D, Westhorp G, Hetzel D, Sawyer M, Cripps D, Goulding S. Interpersonal Violence and Abuse Survey - September 1999. Vol. 2005 South Australian Department of Human Services, 1999.
30. Gill T, Taylor A, Williams M, Starr G. Physical Activity in South Australian Adults - November 2001. Vol. 2005 South Australian Deprtment of Health, 2001.
31. Gill T, Taylor A, Physical Activity Council Research Panel. Physical Activity in South Australian Adults September 2004. South Australian Department of Health, 2005.
32. Taylor A, Dal Grande E, Gill T, Delfabbro P, Glenn V, Goulding S, Weston H, Barton S, Rogers N, Stanley A, Blandy R, Tolchard B, Kingston R. Gambling patterns of South Australians and associated health indicators - May 2001. Vol. 2005 South Australian Department of Human Services, 2001.
33. Australian Bureau of Statistics. 3235.4.55.001 Population by Age and Sex, South Australia. 2004.
References
56
34. Population Research and Outcome Studies Unit. SAMSS Survey Methodology. South Australian Monitoring and Surveillance System (SAMSS) Technical Paper Series No. 1/04. Vol. 2005 South Australian Department of Health, 2004.
35. Dal Grande E. Telephone Monitoring of Public Health Issues: A Comparison of Telephone Sampling Techniques. [Master of Public Health Thesis]. The University of Adelaide, 2002.
36. SPSS Inc. SPSS Advanced Statistics 12.0.1. Chicago: SPSS Inc, 2003.
37. Dean A, Dean J, Coulombier D, al. e. Epi Info, Version 6: a word-processing, database and statistics program for public health on IBM-compatible microcomputers. Atlanta, Georgia, USA: Centers for Disease Control and Prevention, 1995.
38. Statistics. ABo. Socio-Economic Indexes for Areas, Australia, 2001. Canberra: ABS, 2003.
39. Australian Centre for Asthma Monitoring. Asthma in Australia 2003. AIHW Cat. no. ACM 1. Canberra: AIHW Asthma Series 1, 2003.
40. World Health Organization. Obesity: preventing and managing the global epidemic. Report of a WHO consultation on obesity Geneva, 3-5 1997. Geneva: WHO, 2000.
41. Armstrong T, Bauman A, Davies J. Physical Activity Patterns of Australian Adults. Results of the 1999 National Physical Activity Survey. AIHW Cat No. CVD 10. Canberra.: Australian Institute of Health and Welfare, August 2000.
42. Putnam RD. Bowling Alone. The collapse and revival of American community. New York.: Simon and Schuster, 2000.
