South Australian Health & Wellbeing Survey

Transcription

1 South Australian Health & Wellbeing Survey DECEMBER 2000 Eleonora Dal Grande Anne Taylor David Wilson Centre for Population Studies in Epidemiology South Australian Department of Human Services

2 ACKNOWLEDGMENTS We would like to acknowledge Edourad d Espaignet, Alison Daly, Joy Eshpeter, Wilawan Kanjanapan, David Saunders and Gary Starr for their contributions toward the survey. Their direction and support were important in the design of this survey. This work is copyright. It may be reproduced and CPSE 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 no commercial use or sale. CPSE will only accept responsibility for data analyses conducted by CPSE staff or under CPSE supervision. Published May 2002 by the South Australian Department of Human Services PO Box 6 Rundle Mall Adelaide 5000 South Australia, Australia National Library of Australia Cataloguing-in-Publication: Dal Grande, E. South Australian health and wellbeing survey : December ISBN X. 1. Public health - South Australia. 2. Public welfare - South Australia. 3. Health surveys - South Australia. 4. Medical care - South Australia. I. Wilson, David. II. Taylor, Anne, III. South Australia. Dept. of Human Services. IV. Title In accordance with the Copyright Act 1968 a copy of each book published must be lodged with the National Library and respective deposit libraries in each state. Further copies of this publication may be purchased from the Centre for Population Studies in Epidemiology (CPSE) or may be downloaded from the CPSE web site: 2

3 TABLE OF CONTENTS EXECUTIVE SUMMARY...5 CHAPTER 0: BACKGROUND AND METHODOLOGY Introduction Survey design Data collection Data processing CHAPTER 0: DEMOGRAPHIC PROFILE OF RESPONDENTS Demographic characteristics ARIA (Accessibility/Remoteness Index of Australia) CHAPTER 0: MENTAL HEALTH Introduction Kessler psychological distress scale SF Self-reported mental health condition CHAPTER 1: HEALTH CONDITIONS Introduction Diabetes Arthritis Heart disease Stroke Cancer Osteoporosis Asthma Other respiratory conditions High cholesterol High blood pressure Injury requiring medical treatment CHAPTER 2: HEALTH CARE UTILISATION Introduction Used a health service in the last 12 months Spent a night in hospital in the last 12 months

4 CHAPTER 3: HEALTH RISK FACTORS Introduction Physical activity Body Mass Index Alcohol risk Smoking Nutrition CHAPTER 4: HEALTH RELATED ISSUES Perceived control of life events Psychosocial events Medication use Days off from usual activities Limited amount of work done REFERENCES APPENDIX 1: STATE/TERRITORY SURVEY COMMITTEES APPENDIX 2: SERCIS ADVISORY COMMITTEE APPENDIX 3: SA REGION DEFINITIONS APPENDIX 4: LETTER INTRODUCING THE SURVEY APPENDIX 5: WA, NT & SA CATI HEALTH AND WELLBEING QUESTIONNAIRE

5 EXECUTIVE SUMMARY

6 Executive summary In November 2000 a three state population health survey assessing Health and Well- Being was conducted in South Australia as well as the Northern Territory and Western Australia. The overall aim of the survey was to demonstrate the capacity of a public health partnership and collaboration between the three participating states and territories and the Commonwealth. In addition, the survey aimed to assess the wellbeing of the populations using a set of standardised and validated instruments; benchmark results against participating states; and finally develop a process that could be used by States wanting to work in collaboration on similar projects. Approximately n=2500 interviews were undertaken in each of the states using the existing CATI (Computer-Assisted Telephone Interviewing) infrastructure in SA to collect the data. Rural and remote areas were over-sampled to provide reasonable estimates for these regions. Issues that were covered included: Mental health (including the SF12 and Kessler 10), Health conditions, Health care utilisation, Health risk factors (physical activity, BMI, alcohol, smoking, nutrition), Perceived control of life events, and Demographics and other social characteristics. In all, 2454 adults (18 years and over) in South Australia were interviewed and the overall response rate was 64%. Using the ARIA classification, 962 adults reside in metropolitan area (highly accessible,), 851 adults reside in rural areas of South Australia (accessible, moderately accessible) 732 adults reside in the remote areas of South Australia (remote, very remote). Reports highlighting state/territory or regional differences are being produced [1]. In addition, Western Australian and the Northern Territory have produced their independent state/territory reports [2,3]. This report summarises on the South Australian findings of the survey. In addition to the main results, analysis was done between metropolitan, rural and remote areas using ARIA classifications. Where possible, trend analysis were made with data from SERCIS surveys conducted between 1997 to 1999 where identical questions were asked. The following dot points highlight the main results. 6

7 Executive summary Mental Health The prevalence of psychological distress determined by the Kessler 10 for South Australia was 12.8%. Using the SF12, the mean scores for the Physical Component Summary (PCS) and Mental Component Summary (MCS) has remained constant between 1997 and Using the self-report measure of mental health condition, (that is, a mental condition confirmed by a medical practitioner in the twelve months prior to the survey, or those who were currently receiving treatment for a mental condition), 12.9% of adults were identified as suffering a mental health condition. People living in rural (10.3%) and remote (9.6%) areas of South Australia had a lower prevalence of a current self-reported diagnosed mental health condition than people living in the metropolitan area (13.5%). There were no difference in the prevalence of current self-reported diagnosed mental health condition between the surveys conducted in 1997 and Health conditions 6.2% of respondents in South Australia reported having medically confirmed diabetes. This prevalence rate has been rising since % of South Australians have been told by a doctor that they have arthritis. The prevalence of arthritis has remain constant over the 1997 to 2000 period. The prevalence in remote South Australia (15.5%) was lower than metropolitan (20.6%) and rural (21.1%) South Australia. The prevalence of adults ever having heart disease was 6.2%, having a stroke was 2.0%, and ever having cancer was 4.8%. The prevalence of osteoporosis in South Australia was 4.2%. Adults living in rural South Australia (2.4%) had lower rates of osteoporosis (metropolitan was 4.6% and remote SA was 2.8%). The prevalence of osteoporosis has remain constant over the 1997 to 2000 period. 12.7% of South Australians have been told by a doctor that they have current asthma. The prevalence of current confirmed asthma has been rising since % of South Australia have been told by a doctor they have other respiratory problems such as bronchitis, emphysema, chronic lung diseases, that has lasted six months or more. The prevalence of ever having high cholesterol was 19.7% and the prevalence of those who still have high cholesterol was 7.5%. The rate of ever having high cholesterol has been rising since

8 Executive summary The prevalence of ever having high blood pressure was 22.7% and the prevalence of those who still have high blood pressure was 11.0%. The rate of ever having high blood pressure has been decreasing since % of South Australians had an injury in the last 12 months that required medical treatment. There were no differences between rural/remote areas and metropolitan area. Health care utilisation 90.6% of South Australians had used a health service in South Australia in the previous 12 months. People living in rural (87.7%) and remote (82.3%) South Australia had a lower proportion of health service use in the previous 12 months than people living in metropolitan areas (91.3%). 84.6% of South Australians used primary health care services, 6.2% used mental health services, 26.9% used hospital based services and 35.3% used allied health services in the previous 12 months. People living in rural (80.7%) and remote (78.0%) areas of South Australia had a lower proportion of using primary health care services (metropolitan areas was 85.6%). People living in remote South Australia (32.7%) had a higher proportion of using hospital based services in the previous 12 months (metropolitan areas was 26.4%). The proportion of South Australians who had spent at least one night in a hospital in the previous 12 months was 12.6%: 6.0% spent the night in a private hospital and 6.9% spent the night in a public hospital. People living in remote South Australia (15.9%) had a higher proportion of spending at least one night in a hospital in the previous 12 months. Health risk factors People who work full time or part time were asked to described the main type of physical activity they do at work. 56.8% mostly sat, 18.3% mostly walked and 21.4% mostly did heavy labour or physically demanding work. People living in the rural (31.1%) and remote (29.7%) areas were more likely to do physically demanding work (metropolitan areas was 19.4%). In a usual week, 85.2% of South Australians walked for at least 10 minutes at a time, while at work, for recreation, exercise, to get to and from places, or for any other reason, on at least one day in the week. In a usual week, 87.1 % of South Australians had done moderate activities for at least 10 minutes at a time, such as brisk walking, bicycling, vacuuming, gardening, or anything else that caused some increases in breathing or heart rate, on at least one day in the week. 8

9 Executive summary In a usual week, 33.0% of South Australians had done activities designed to increase muscle strength or tone for at least 10 minutes at a time, such as lifting weights, pull-ups, push-ups or sit ups, on at least one day in the week. In a usual week, 48.2% of South Australians had done vigorous activities for at least 10 minutes at a time, such as running, aerobics, heavy yard work, or anything else that caused large increases in breathing or heart rate, on at least one day in the week. The prevalence of people classified as underweight was 9.5%, overweight was 40.9%, and obese was 15.5%. The prevalence of adults who were classified as underweight was lower in the rural (6.5%) and remote areas (6.5%) than metropolitan areas (10.1%). The prevalence of underweight, overweight and obese has remain constant in the 1997 and 2000 period. 3.3% of South Australians were determined to be intermediate to high alcohol risk drinkers. This rate has decreased over the last four years. Rural (5.9%) and remote (6.9%) South Australians had higher proportions of intermediate to high risk alcohol drinkers than people living in metropolitan areas (2.7%). The proportion of household members that smoke inside the home was found to be 12.4%. This rate was higher for people living in rural (15.5%) and remote (15.5%) areas of South Australian (metropolitan areas was 11.7%). 19.9% of adults in South Australia reported that they were current smokers. Remote (26.5%) South Australians had higher proportions of current smokers than people living in metropolitan areas (19.2%). Perceived control of life events There were a higher proportion of people living in the remote areas of South Australia who often or always felt a lack of control with their financial situation and their personal life. 9

10 Executive summary 10

11 CHAPTER 1: BACKGROUND AND METHODOLOGY

12 Background and methodology 1.1 Introduction Following discussions at National CATI (Computer Assisted Telephone Interviewing) Technical Reference Group meetings, a joint submission from Western Australian (WA), Northern Territory (NT) and South Australia (SA) was submitted to the Commonwealth Department of Health and Aged Care. The proposal was to undertake a three state/territory CATI health and wellbeing survey utilising the already established SA 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. In particular, the project (nominally called the WANTS survey), aimed to: Demonstrate a partnership between WA/NT/SA CATI TRG members and the Commonwealth; Assess the wellbeing of the WA, NT and SA population using a set of standardised and validated instruments; Benchmark results against participating states; and overall Develop a process that could be used by States wanting to work in collaboration on similar projects. A management group, comprising Alison Daly (WA), Edouard D Espaignet (NT), David Wilson and Anne Taylor (SA) and Joy Eshpeter (Commonwealth) 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. The names of those involved are included in Appendix 1. SA 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 Centre for Population Studies in Epidemiology Unit of the South Australian Department of Human Services and overseen by an Advisory Committee (Appendix 2). This report summarises the main South Australian findings of the survey. 12

13 Background and methodology 1.2 Survey design Sample selection All households in SA with a telephone connected and the telephone number listed in the latest version of the EWP (Electronic White Pages) were eligible for selection in the sample. The target number of interviews for South Australia was In this study, the total number of interviews for South Australia were determined to be distributed as 900 interviews in the metropolitan area, 800 interviews in rural areas, and 800 interviews in remote areas. These geographic regions are defined in Section The minimum sample size of 800 was necessary to enable populations estimates of health conditions and behaviours to be made with a reasonable confidence intervals. A random sample of the whole state would be representative of the population structure, but health estimates for rural and remote areas would have wide confidence intervals. Such estimates would do little to describe health in the less populated areas of the state. A stratified sample was therefore determined to be the best use of survey resources. As a consequence of the need to over-sample non-metropolitan areas, separate samples were drawn for each of the three geographic regions (metro/rural/remote). These samples represented increasing proportions of the population as remoteness increased. A summary of the target number of interviews as a proportion of the estimated residential population in each region in 1999 is shown in Table 1.1. The estimated residential population figures supplied by the Australian Bureau of Statistics were the most up-to-date available at the time of sampling and were used for these purposes. The initial sample sizes drawn from the EWP were based on the best recent estimates of response rates available to the survey team. Table 1.1 Target interviews by region as a proportion of population size Region Target interviews Residential population 18+ * sample proportion Metropolitan , % Rural , % Remote , % * Estimated Residential Population ABS

14 Background and methodology Within each household, the person who had their birthday last was selected for interview. There was no replacement for non-contactable persons Definition of geographic regions The state can be divided into three regions representing metropolitan (capital city), rural, and remote areas. The rural and remote areas were substantially less populated than the metropolitan region. Rural and remote areas were a particular focus of the survey in terms of assessing health status and health service planning requirements. Defining remoteness of population locations from health and other services has been an issue of considerable discussion in recent years and has resulted in two classifications: Rural, Remote and Metropolitan Area (RRMA) [4] and the Accessibility/Remoteness Index of Australia (ARIA) [5]. Regions were defined as aggregations of postcode areas in the state. Postcodes were taken as the geographic reference as this was the only reliable location data available in the telephone listing database that could be extrapolated to larger regions. Postcodes are readily translated to SLA's (Statistical Local Areas) in which estimated population numbers are published. This connection between address and ABS data was necessary for weighting of the data to reflect population proportions by age and gender (see Section 1.4.2). Postcode to region lists for South Australia are detailed in Appendix 3. The definitions of regions in South Australia were based on ARIA (Accessibility/Remoteness Index of Australia) codes [5]. ARIA seeks to define remoteness from services in terms of distance by road. All populated locations in Australia are given an ARIA value ranging from 0 for high accessibility to 12 for high remoteness. This index is also available as five categories, which are better suited to classifications such as required by the present study. ARIA categories were used to define regions in SA in the following way: Highly Accessible (ARIA score ) defined metropolitan; Accessible (ARIA score ) and Moderately Accessible (ARIA score ) together defined rural; and Remote (ARIA score ) and Very Remote (ARIA score ) together defined remote regions. The postcode to region list for SA in Appendix 3 was derived from the postcode to ARIA category specification [6]. 14

15 Background and methodology Introductory letter A letter introducing the health survey (Appendix 4) was sent to the household of each selected telephone number. The letter 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 Questions Initial questionnaire design was based on a previous SERCIS survey - the 1997 Mental Health Survey [7]. Modifications were made based on management group discussions and individual state/territory sub-committee recommendations. The full list of questions asked in this survey is contained in Appendix Pilot testing Before the conduct of the main survey, the questionnaire was pilot tested (n=50). Pilot testing took place from Tuesday 17 th October 2000 to Thursday 19 October Modifications were made to the questionnaire following the debrief on Friday 20 th October. 1.3 Data collection Data collection was undertaken by the contacted agency, Harrison Health Research. The survey commenced on 1 st November 2000 and concluded on Thursday 21 st December. Telephone calls were made between 9:30 am and 9.00 pm, seven days a week. Professional interviewers conducted the interviews and were supervised by Harrison Health Research and SERCIS personnel. Disposition codes were supplied to SERCIS staff daily, or as required, to ensure careful monitoring of survey activities. On contacting the household, the interviewer initially identified themselves and the purpose of the survey. 15

16 Background and methodology 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 Call backs At least six 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 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. 16

17 Background and methodology Response rate The overall response rate was 63.8%. Initially a sample of 5170 was drawn. Sample loss of 1181 occurred due to non-connected numbers (844), non-residential numbers (153), respondent unavailable (145) and fax/modem connections (39). From the eligible sample of 3989, the response rate and participation rate were calculated as shown in Table 1.2. Table 1.2: Response rates SA n % Initial eligible sample Refusals Non-contact after six attempts Respondent unable to speak English, Italian, Greek, Croatian, Chinese (traditional and simplified) or Vietnamese Incapacitated and unable to be interviewed Terminated interviews Hearing impaired Completed interviews Response rate Participation rate Response rate = completed interviews / initial eligible sample Participation rate = completed interviews / (initial eligible sample - non-contact after six attempts) 1.4 Data processing Analysis Raw data from the CATI system were analysed using SPSS Version Weighting The data presented in this report were weighted by age, gender, and probability of selection in the household. Weighting was used to correct for the disproportionality of the sample with respect to the populations of interest. The weights reflect unequal sample inclusion probabilities and compensate for differential non-response. The 17

18 Background and methodology adult populations, aged 18 years or over, of South Australia were obtained from the Australian Bureau of Statistics. The most recently available population estimates, being the estimated residential population for 1999, were used. The data were weighted using the ABS data so that the health estimates calculated would be representative of the adult populations of those three states. Probability of selection of the adult in the household was calculated from the number of adults in the household and the number of telephone listings in the EWP that reach the household. As each region involved a discrete sample, these were weighted separately. The estimated residential populations in regions were aggregated from SLA's using the geographic information used to define the regions (see Section 1.2.2). Combined weights to enable state level analyses were constructed from the region weights by applying the sampling proportions in each region. In this way, metropolitan responses, for example, were weighted up slightly and remote responses were weighted down substantially Data interpretation The weighting of the data results in occasional rounding effects for the numbers. In all instances the percentages should be the point of reference rather than the actual numbers of respondents. The percentages presented in this report have been processed on the figures pre-rounding Comparisons Where possible, comparisons were made between the results of this survey and data obtained in previous SERCIS surveys where identical questions were asked. The χ 2 test was used to detect significant differences in the proportion between two SERCIS surveys when the question was only included in two SERCIS surveys. The χ 2 for trend test was used to test for significant changes in the proportions over time when the question was included in three or more SERCIS surveys. 18

19 CHAPTER 2: DEMOGRAPHIC PROFILE OF RESPONDENTS

20 Demographic profile 2.1 Demographic characteristics The primary demographic descriptions of the South Australian sample showing gender, age, and household compositions, are presented in Table 2.1 Table 2.1: Demographic profile - sex, age, household size SA n % Gender Male Female Age groups 18 to 25 years to 34 years to 44 years to 54 years to 64 years to 74 years years and over Household size (18 years and over) or more Number of children in the household None or more Not stated Total

21 Demographic profile The demographic descriptions of the samples are continued in Table 2.2. This presents marital status and educational attainment. For those respondents born in Australia, Aboriginal and Torres Strait Islander status is shown. Table 2.2: Demographic profile - marital status, educational attainment, country of birth, Aboriginal or Torres Strait Islander Marital status SA n % Never married De facto Married Separated Divorced Widowed Not stated Educational attainment Never attended school Some primary school Completed primary school Some high school Completed high school ie year 12, form 6, HSC TAFE or Trade Certificate or Diploma University, CAE or some other tertiary institute degree Other Born in Australia Yes No Total Aboriginal or Torres Strait Islander Yes No Refused Total

22 Demographic profile The demographic descriptions continues in Table 2.3, showing work status and occupation. Table 2.3: Demographic profile - work status, lifetime occupation, pension or benefit from DSS Work status SA n % Full time employed Part time employed Unemployed Home duties Retired Student Other Refused Lifetime occupation Manager or administrator Professional Para-professional Trades person Clerk Sales person or personal service worker Plant or machine operator or driver Labourer or related worked Home duties Never worked Total Received pension or benefit from the Department of Social Security # Yes No Don t know Total Note: The other category for lifetime occupation has not been re-coded into the existing categories. # Only asked of those who do not work full time. 22

23 Demographic profile Household financial status is shown in Table 2.4. The questions asked of respondents related to their views on excess discretionary income, and the gross annual income of the household. Table 2.4: Demographic profile - money situation, gross annual household income Money situation SA n % Spending more money than getting Have just enough money to get through to the next pay There is some money left over each week but just spent it Can save a bit every now and then Can save a lot Don t know Refused Gross annual household income Up to $12, $12,001 to $20, $20,001 to $40, $40,001 to $60, $60,001 to $80, More than $80, Not stated / refused Don t know Total

24 Demographic profile 2.2 ARIA (Accessibility/Remoteness Index of Australia) The report will highlight analysis by metropolitan, rural and remote using Accessibility/Remoteness Index of Australia (ARIA). This index was developed to define remoteness for rural and remote Australia. ARIA was developed by the Information and Research Branch, Department of health and Aged Care, and the National Key Centre for Social Applications of Geographic Information Systems (GISCA) at the University of Adelaide in 1999 [5,6]. This index of remoteness was to overcome the problems of the Rural, Remote and Metropolitan Area (RRMA) classification which was developed in 1994 [4]. The RRMA was based on statistical local areas (SLAs) as classified in the 1991 Census and population density, distances to large population centres. ARIA was to overcome the limitations of RRMA [6]; 1) the classifications are available only at the SLA level and 2) the boundaries are based on 1991 Census. The ARIA was developed using the methodology underlying the RRMA and Geographical Information Systems (GISCA). The GIS database contained road, locality and service information to calculate a remoteness index and GIS methodology was used to measure remoteness. Remoteness was defined as assessibility to the four categories of the 201 service centres across Australia and road distances of 11,340 population localities to these service centres. Socio-economic, urban/rural and population size factors were not included in the definition. For each localities, a continuous value was given where 0 means highly accessible and 12 mean highly remote. ARIA values are available at population localities (towns or cities), Censuses Collection Districts (CD), postcode and statistical local area. ARIA can be grouped into five categories: Highly Accessible (ARIA score ) - locality has unrestricted access to a wide range of goods, services and opportunities for social interaction. Accessible (ARIA score ) - locality has some restrictions to accessibility of some goods, services and opportunities for social interaction. Moderately Accessible (ARIA score ) - locality has significantly restricted accessibility of goods, services and opportunities for social interaction. Remote (ARIA score ) - locality has very restricted accessibility of goods, services and opportunities for social interaction. 24

25 Demographic profile Very Remote (ARIA score ) - locality has very little accessibility of goods, services and opportunities for social interaction. For this survey, the postcode was used to determine the ARIA value. Some postcodes did not have an ARIA value, so the nearest postcode or locality was used (see Appendix 3). In this report, all analyses will be conducted by three ARIA categories: Metropolitan - highly accessible (ARIA score ), Rural - accessible and moderately Accessible (ARIA score ), and Remote - remote and very remote (ARIA score ). The number of adults interviewed for each ARIA category is shown in Table 2.5. Table 2.5: ARIA categories n Metropolitan Adelaide 962 Rural areas of South Australia 851 Remote areas of South Australia 732 Total

26 Demographic profile 26

27 CHAPTER 3: MENTAL HEALTH

28 Mental health 3.1 Introduction In this report, the mental health status of respondents is reported using four different methods, namely; Kessler psychological distress scale; SF-12; and Self-reported mental health condition; These next sections contain the following for each method: The description of the method and background explanation for use; Scoring rational; Prevalence of having a mental health condition in South Australia using the nominated method; and Demographic profile of adults with a mental health condition as determined by the nominated method. 28

29 Mental health 3.2 Kessler psychological distress scale Description The Kessler psychological distress 10 item scale or K10 was developed to measure anxiety and depressive disorders on a general population [8,9]. The scale has five response categories intended to yield a global measure of psychosocial distress based on questions about the level of anxiety and depressive symptoms in the most recent four-week period [10]. The answers to each of the individual questions of the Kessler psychological distress scale are listed in Table 3.1. Table 3.1: Kessler psychological distress scale - questions and categories In the past four weeks, about how often did you feel tired out for no good reason? n % All of the time Most of the time Some of the time A little of the time None of the time In the past four weeks, about how often did you feel nervous? All of the time Most of the time Some of the time A little of the time None of the time Total In the past four weeks, about how often did you feel so nervous that nothing could calm you down? All of the time Most of the time Some of the time A little of the time None of the time Total

30 Mental health Table 3.1: Kessler psychological distress scale - questions and categories (cont) In the past four weeks, about how often did you feel hopeless? n % All of the time Most of the time Some of the time A little of the time None of the time In the past four weeks, about how often did you feel restless or fidgety? All of the time Most of the time Some of the time A little of the time None of the time Total In the past four weeks, about how often did you feel so restless you could not sit still? All of the time Most of the time Some of the time A little of the time None of the time Total In the past four weeks, about how often did you feel depressed? All of the time Most of the time Some of the time A little of the time None of the time In the past four weeks, about how often did you feel everything was an effort? All of the time Most of the time Some of the time A little of the time None of the time Total

31 Mental health Table 3.1: Kessler psychological distress scale - questions and categories (cont) In the past four weeks, about how often did you feel so sad that nothing could cheer you up? n % All of the time Most of the time Some of the time A little of the time None of the time In the past four weeks, about how often did you feel worthless? All of the time Most of the time Some of the time A little of the time None of the time Total Scoring of the Kessler 10 to determine psychological distress The creators of the Kessler 10 have not developed or published details on the scoring of the scale. However, various scoring of Kessler 10 have been developed and are described below Kessler scoring method A - anxiety or depressive disorder A scoring of the Kessler 10 have been described by the Clinical Research Unit for Anxiety & Depression (CRUFAD), School of Psychiatry, University of NSW [8]. The response categories are converted to Likert scales but reversed ie value of 1 for none of the time to 5 for all of the time. These 10 items are summed to give scores ranging between 10 and 50. CRUFAD developed cutoff scores for the Kessler 10 by comparing the score against the CIDI instrument [11]. Both instruments were included in the Australian Survey of Mental Health and Well-being [8,11]. Table 3.2 shows the proportion of respondents in South Australia who were determined to be low or no risk of having anxiety or depressive disorder, medium risk and high risk according to the Kessler

32 Mental health Overall, 2.2% (95% CI , n=57) of respondents in South Australia were determined to have a high risk of having anxiety or depressive disorder (Table 3.2). Table 3.2: Anxiety or depressive disorder according to the Kessler 10 n % (95% CI) Low or no risk (score of 12 to 15) ( ) Medium risk (score of 16 to 29) ( ) High risk (score of 30 to 50) ( ) Total Note: The weighting of the data can result in rounding discrepancies or totals not adding (see Section 1.5.2). Table 3.3 contains the three risk levels of anxiety or depressive disorder according to the Kessler 10 for each of South Australian regions. There were no statistically significant differences in the proportion of respondents with high risk of anxiety or depressive disorder between the regions. Table 3.3: Anxiety or depressive disorder according to the Kessler 10 Metropolitan Rural Remote n % (95% CI) n % (95% CI) n % (95% CI) Low or no risk ( ) ( ) ( ) Medium risk ( ) ( ) ( ) High risk ( ) ( ) ( ) Total Statistically significantly higher or lower (χ 2 test, p < 0.05) than state overall figure Note: The weighting of the data can result in rounding discrepancies or totals not adding (see Section 1.5.2). The following table (Table 3.4) shows the demographic profile of people with high risk of anxiety or depressive disorder for South Australia. The demographic profile of people with high risk of anxiety or depressive disorder was not undertaken for each of the South Australian regions because of insufficient numbers. 32

33 Mental health Table 3.4: High risk of anxiety or depressive disorder according to the Kessler 10 by demographic variables Variable South Australia n % Gender Male Female Age group (years) 18 to 34 years to 44 years to 54 years to 64 years or more years Household size (18 years and over) 1 adult adults or more adults Number of children (less than 18 years) No children or more children Marital Status Married/De Facto Separated/Divorced Widowed - - Never Married Highest educational qualification obtained Secondary Trade/Apprenticeship/Certificate/ Diploma Degree or higher Country of birth Australia Overseas Region overall Statistically significantly higher or lower (χ 2 test, p < 0.05) than overall region figure # Insufficient numbers for statistical test Note: The weighting of the data can result in rounding discrepancies or totals not adding (see Section 1.5.2). 33

34 Mental health Table 3.4: High risk of anxiety or depressive disorder according to the Kessler 10 by demographic variables (cont) Variable South Australia n % Work status Employed full time Employed part time Unemployed # Home duties, student, retired or other Lifetime occupation Manager, professional, para-professional Trades person, clerk, sales person or personal service worker Plant or machine operator or driver, labourer or related worker Home duties, never worked Money situation Spending more money than getting Have just enough money to get through to next pay There is some money left over each week but just spent it # Can save a bit every now and then Can save a lot # Don t know / not stated # Gross annual household income Less than $20, $20,000 to < $40, $40,001 to < $80, $80,001 or more # Not stated Region overall Receive Pension or Benefit (if not employed) Yes No Statistically significantly higher or lower (χ 2 test, p < 0.05) than overall region figure # Insufficient numbers for statistical test Note: The weighting of the data can result in rounding discrepancies or totals not adding (see Section 1.5.2). 34

35 Mental health Kessler scoring method B - psychological distress An alternative scoring of the Kessler 10 have been used in the NSW Health 1997 and 1998 Survey reports [10]. Similar to the previous method, the response categories are converted to Likert scales but reversed ie value of 1 for none of the time to 5 for all of the time. These 10 items are summed to give scores ranging between 10 and 50 and are then converted to a T-score by subtracting the mean of the score and dividing by the standard deviation of the score. These scores were then standardised with a mean of 50 and standard deviation of 10. K10 standardised = (K10 summed items - mean (K10 summed items)) Standard deviation (K10 summed items) x The cutoff was determined by taking one standard deviation above the mean, value of 60 to determine a high level of psychological distress. Overall, 12.8% (95% CI , n=326) of respondents reported having psychological distress according to the Kessler 10 (Table 3.5). Table 3.5: Psychological distress according to the Kessler 10 n % No Yes Total Note: The weighting of the data can result in rounding discrepancies or totals not adding (see Section 1.5.2) Kessler 10 by demographic variables and region The prevalence of psychological distress determined by the Kessler 10 for each of the South Australian regions is shown in Table 3.6. There were no statistically significantly differences in the proportion of respondents with psychological distress between the regions. 35

36 Mental health Table 3.6: Prevalence of psychological distress in South Australia by region Metropolitan Rural Remote n % (95% CI) n % (95% CI) n % (95% CI) Yes ( ) ( ) ( ) No ( ) ( ) ( ) Total Statistically significantly higher or lower (χ 2 test, p < 0.05) than state overall figure Note: The weighting of the data can result in rounding discrepancies or totals not adding (see Section 1.5.2). Figure 3.1: Proportion of people with psychological distress in South Australia by region Proportion SA State Metropolitan Rural Remote 36

37 Mental health Table 3.7: Psychological distress in South Australia by demographic variables and region Variable Metropolitan Rural Remote n % n % n % Gender Male Female Age group (years) 18 to 24 years to 34 years to 44 years to 54 years to 64 years to 74 years or more years # Household size (18 years and over) 1 adult adults adults or more adults # # Number of children (less than 18 years) No children or more children Marital Status Married/De Facto Separated/Divorced Widowed # # Never Married Highest educational qualification obtained Secondary Trade/Apprenticeship/Certificate/ Diploma Degree or higher # Country of birth Australia - non-aboriginal & Torres Strait Islander Australia - Aboriginal & Torres Strait Islander # Overseas Region overall Statistically significantly higher or lower (χ 2 test, p < 0.05) than overall region figure # Insufficient numbers for statistical test Note: The weighting of the data can result in rounding discrepancies or totals not adding (see Section 1.5.2). 37

38 Mental health Table 3.7: Psychological distress in South Australia by demographic variables and region (cont) Variable Metropolitan Rural Remote n % n % n % Work status Employed full time Employed part time Unemployed # # Home duties, student, retired or other Lifetime occupation Manager, professional, paraprofessional Trades person, clerk, sales person or personal service worker Plant or machine operator or driver, labourer or related worker Home duties, never worked Money situation Spending more money than getting Have just enough money to get through to next pay There is some money left over each week but just spent it Can save a bit every now and then Can save a lot Don t know / not stated Gross annual household income Less than $20, $20,000 to < $40, $40,001 to < $80, $80,001 or more Not stated Region overall Receive Pension or Benefit (if not employed) Yes No Statistically significantly higher or lower (χ 2 test, p < 0.05) than overall region figure # Insufficient numbers for statistical test Note: The weighting of the data can result in rounding discrepancies or totals not adding (see Section 1.5.2). 38

39 Mental health 3.3 SF Description The Short Form 12 (SF-12) health status measure was developed in the United States by the Medical Outcomes Study. It is a subset of the SF-36 and is a valid measure of health status in Australia [12]. The scoring of the SF-12 was done as specified in the SF-12 scoring manual [13]. The SF-12 consists of 12 questions addressing quality of life issues, which were aggregated into two summary scales: the physical component summary scale (PCS), in which a higher score indicates better physical health; and the mental component summary scale (MCS), in which a higher score indicates better mental health; and The two scores range between 0 and 100. The two summary scales (physical and mental) can be used to compare respondents with and without conditions or experiences. The summary scales of the SF-12 are based on fewer items than the same scales determined by the SF-36. The literature shows some loss of precision when using the shorter version, but this is offset by considerable saving in survey time and costs. The SF-12 was therefore considered a good alternative instrument for this survey PCS and MCS summary statistic All respondents were asked the SF-12 questions. Table 3.8 shows the mean scores, with 95% confidence intervals, for the two summary scales of the SF-12. The mean scores of the PCS and MCS has remained constant over the last four years. Table 3.8: Mean scores for the SF-12 summary scales by year of survey Physical component summary (PCS) Mental component summary (MCS) Year of survey n Mean (95% CI) Mean (95% CI) 1997 July [7] ( ) 52.1 ( ) 1998 May [14] ( ) 52.3 ( ) 1998 October [15] ( ) 52.2 ( ) 2000 December ( ) 52.3 ( ) 39

40 Mental health Figure 3.2: Mean scores for the SF-12 summary scales by year of survey Mean score Year PCS MCS Note: 1998 figure is the average of the two surveys conducted in PCS score by demographic variables and region Table 3.9 shows the mean scores, 95% confidence interval of the mean, standard deviation of the mean, and standard error of the mean for the physical summary scale of the SF-12 by various demographic variables. Higher mean scores indicate better overall physical health. 40

41 Mental health Table 3.9: PCS score by demographic variables and region Variable Metropolitan Rural Remote n Mean (95% CI) n Mean (95% CI) n Mean (95% CI) Gender Male ( ) ( ) ( ) Female ( ) ( ) ( ) Age group (years) 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 or more years ( ) ( ) ( ) Household size (18 years and over) 1 adult ( ) ( ) ( ) 2 adults ( ) ( ) ( ) 3 adults ( ) ( ) ( ) 4 or more adults ( ) ( ) ( ) Number of children (less than 18 years) No children ( ) ( ) ( ) 1 or more children ( ) ( ) ( ) Marital Status Married/De Facto ( ) ( ) ( ) Separated/Divorced ( ) ( ) ( ) Widowed ( ) ( ) ( ) Never Married ( ) ( ) ( ) Highest educational qualification obtained Secondary ( ) ( ) ( ) Trade/Apprenticeship/ Certificate/ Diploma ( ) ( ) ( ) Degree or higher ( ) ( ) ( ) Country of birth Australia - non-aboriginal & Torres Strait Islander ( ) ( ) ( ) Australia - Aboriginal & Torres Strait Islander ( ) ( ) ( ) Overseas ( ) ( ) ( ) Total ( ) ( ) ( ) 41