Surveillance in Practice

Transcription

1 Surveillance in Practice Evidence and Effectiveness Associate Professor Anne Taylor South Australian Department of Health

2 Evidence and effectiveness Evidence Health policy makers, health planners & health promoters Standardised methods Comparable Effectiveness Has it made a change? Did the information make a difference? 2

3 Australia 3

4 South Australia (SA) 4th largest state in area Population = 1.5 million (14% of Australia) State of festivals and fine wine 4

5 SA Festivals and Fine Wine 5

6 SA Festivals and Fine Wine 6

7 South Australian Monitoring & Surveillance System (SAMSS) Commenced July 2002 Continuous chronic disease and risk factor surveillance system CATI (Computer Assisted Telephone Interviews) n = 600 per month Random selection of South Australians of all ages (0+ years) 7

8 Health Omnibus Survey (HOS) Conducted annually since early 1990s Face-to-face interviews 15+ year olds Representative, clustered area sample n=3000 per year each September/October 8

9 Structure of presentation Time & Place 9

10 Time & Place Ways to use surveillance data T I M E Trends Interventions Mapping Extract Risk factors P L A C E Physical Activity Life style Alcohol Cigarette Eating 10

11 Time & Place T - Trends 11

12 Trends Long term movement in time series data Early warning system Detecting change Linked to interventions Important for evidence based policy & program development Emphasises priorities Measuring progress 12

13 Prevalence of BMI (adults) in SA Prevalence (%) Prevalence Year Year Underw eight Normal Overw eight Obese Source: Health Omnibus Surveys, 18+ years, age-gender standardised Underw eight Normal Overw eight Obese 13

14 Prevalence of obesity in metropolitan (urban) and country (rural/remote) South Australia Obesity prevalence (%) Metropolitan Country Year Source: Health Omnibus Surveys, 15+ years 14

15 Trends Consistency in methodology Consistency in questions Analysis techniques 15

16 Time & Place I Interventions 16

17 Interventions Measuring success or otherwise for health promoters, of policy initiatives, for health planners Has the intervention produced the desired results? Mindful of other influences Powerful tool 17

18 Fruit and vegetable consumption campaign Go for 2&5 Campaign Awareness raising and educating Comprehensive Media Campaign May-June 2005 National and State based activities $A100,000 in SA; Nationally $A4.75 million Go for 2&5 Fruit and Vegetable man events 18

19 Fruit & vegetable consumption campaign 19

20 Proportion eating 5+ serves vegetables/day (pre and post campaign) Prevalence of 5+ serves vegetables (%) July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 Month Source: SAMSS

21 Proportion eating 5+ serves vegetables/day (pre and post campaign) by Gender Male Female Prevalence of 5+ serves vegetables (%) July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 Source: SAMSS Month 21

22 Proportion eating 5+ serves vegetables/day (pre and post campaign) by BMI Underweight/Normal Overweight/Obese Prevalence of 5+ serves vegetables (%) July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 Source: SAMSS Month 22

23 Proportion eating 2+ serves fruit per day (pre and post campaign) Prevalence 2+ fruit (%) July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 Month Source: SAMSS

24 Proportion eating 2+ serves fruit per day (pre and post campaign) by Season Prevalence 2+ fruit (%) July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 Month Winter Jul-Oct Summer Nov-Jun 24

25 Need for an intervention?? 25

26 BMI (adults) by SEIFA Underweight <18.5 Normal Overweight Obese Proportion (%) lowest quintile low quintile middle quintile high quintile highest quintile SEIFA quintile Data Source: HOS , age 18 years and over 26

27 Prevalence of obesity and percentage increase, % increase 100 Prevalence of obesity (%) % increase in obesity prevalence 0 lowest low middle high highest SEIFA category 0 Data Source: HOS , age 18 years and over 27

28 Time & Place M - Mapping 28

29 Mapping Maps are Clear Quick to assess Interpretation presented Common in all types of public health surveillance Care with survey surveillance Sparsely populated areas Limitation of the data Recognise epidemics 29

30 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 30

31 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 31

32 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 32

33 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 33

34 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 34

35 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 35

36 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 36

37 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 37

38 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 38

39 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 39

40 Monitoring risk factors - OBESITY Prevalence of obesity: % % % % % % Health Omnibus Survey, 18+ years Population Research and Outcome Studies Unit Health System Improvement and Reform Division 40

41 Time & Place E Extract 41

42 Accumulation of data Geographic Health regions Divisions of General Practice Priority populations Aboriginal & Torres Strait Islanders (ATSI) Carers People with psychological distress Socioeconomic status (SEIFA) Arthritis CVD (Cardiovascular Disease) 42

43 Accumulation of data The Health Status of South Australians by SEIFA Chartbook of the Health and Wellbeing Status of Aboriginal and Torres Strait Islanders in South Australia 2006 The Health and Wellbeing of Adult Family Carers in South Australia The Health Status of People Living in SA Divisions of General Practice The Epidemiology of Cardiovascular Disease in South Australia March 2007 An Epidemiological Analysis of Arthritis Prevalence Among South Australian Adults The Health Status of People Living in the Southern Adelaide Health Region: Overweight and Obese, Physical Activity and Nutrition Which South Australians Experience Psychological Distress? 43

44 Division of General Practice report 14 Divisions Local networks of General Practitioners (doctors) July 2002-Dec 2003 (18 months) 7346 interviews (range 2240 to 120 per division) Jan 2004 Dec 2006 (2 years) interviews (range 5200 to 300 per division) 44

45 Self-Reported BMI by Divisions of General Practice (obese, as classified by WHO BMI criteria) 18+ years July 2002 December 2003 January 2004 December 2006 Obese Obese n % (95% CI) n % (95% CI) Adelaide Central and Eastern ( ) ( ) Adelaide Northern ( ) ( ) Adelaide North East ( ) ( ) Adelaide Southern ( ) ( ) Adelaide Western ( ) ( ) Adelaide Hills ( ) ( ) Barossa ( ) ( ) Eyre Peninsula ( ) ( ) Flinders and Far North ( ) ( ) Limestone Coast ( ) ( ) Mid North Rural SA ( ) ( ) Murray Mallee ( ) ( ) Riverland ( ) ( ) Yorke Peninsula ( ) ( ) Overall ( ) ( ) 45

46 Sufficient physical activity by Divisions of General Practice 18 years and over (state average = 50.8%) July 2002 to December 2003 January 2004 to December Adelaide Central and Eastern Adelaide Northern Adelaide North East Adelaide Southern Adelaide Western Adelaide Hills Barossa Eyre Peninsula Flinders and Far North Limestone Coast Mid North Rural SA Murray Mallee Riverland Yorke Peninsula Division of General Practice Proportion (%)

47 Aboriginal and Torres Strait Islanders report Census % of SA adults identify as Aboriginal & Torres Strait Islanders Surveillance system 0.7% of sample identified as ATSI 47

48 BMI by Aboriginal and Torres Strait Islander status Proportion (%) * * Underw eight/ normal Overw eight Obese Indigenous Non Indigenous Source: SAMSS July 2002-Dec 2005, 18+ years 48

49 Mental health status by Aboriginal & Torres Strait Islander status Proportion (%) * * 5 0 Current diagnosed Mental health condition Psychological distress Suicidal ideation Indigenous Non Indigenous SAMSS July 2002-Dec

50 Overall health status by Aboriginal and Torres Strait Islander status Proportion (%) * * Excellent Very good Good Fair Poor Indigenous Non Indigenous Source: SAMSS July 2002-Dec

51 Time & Place P Physical Activity 51

52 Proportion undertaking sufficient physical activity by season Prevalence of sufficient activity, all ages July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 month Winter Jul-Oct Summer Nov-Jun Source: SAMSS

53 Proportion undertaking sufficient physical activity by BMI Underweight/Normal Overweight/Obese Prevalence of sufficient activity % July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 month Winter Jul-Oct Summer Nov-Jun Source: SAMSS

54 Proportion undertaking sufficient physical activity by gender Data source: SAMSS, age 16 years and over 54

55 Proportion undertaking sufficient physical activity by income Data source: SAMSS, age 16 years and over 55

56 Proportion undertaking sufficient physical activity by SEIFA Data source: SAMSS, age 16 years and over 56

57 Proportion undertaking sufficient physical activity by overall health status Data source: SAMSS, age 16 years and over 57

58 Proportion undertaking sufficient physical activity by smoking status Data source: SAMSS, age 16 years and over 58

59 Time & Place L Lifestyle 59

60 Household money situation by gender (spending more money than getting, just enough money to get through to next pay, money left over but just spend it) Males Trend (smoothed) Males Trend (smoothed) Trend (smoothed) Females Trend (smoothed) Proportion (%) Proportion (%) Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Year Year Data source: SAMSS, age 16 years and over 60

61 Time & Place A - Alcohol 61

62 Standard drink definitions in different countries Australia Austria Belgium Denmark Finland France Hungary Italy Japan Netherlands Portugal UK USA Grams of alcohol 62

63 Recommendations of safe level of alcohol consumption Australia (proposed) Austria Belgium* Denmark* Finland* France Italy Females Males Japan Netherlands Portugal UK USA Grams of pure ethanol per day (*converted from w eekly recommendation) 63

64 Australian alcohol guidelines (2001) Old guidelines Males On average no more than 4 standard drinks a day (no more than 28 standard drinks a week) No more than 6 standard drinks in any one day 1 or 2 alcohol free days per week Females An average of no more than 2 standard drinks per day (no more than 14 standard drinks per week) Not more than 4 standard drinks in any one day 1 or 2 alcohol-free days per week 64

65 Australian alcohol guidelines (Draft Oct 2007) New guidelines (low risk drinking) Males & Females 2 standard drinks or less in any one day 65

66 Time & Place C - Cigarettes 66

67 Smoking interventions Tobacco control $A4 million per year (South Australia) Smoking cessation Quit programs, media and social marketing Prevention Focus: youth, ATSI, schools 67

68 Proportion of adults smoking Prevalence of smokers % July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 Month Data source: SAMSS, age 16 years and over

69 Proportion of adult smokers by gender Male Female 69 Prevalence of smokers % July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 Graphs by sex Month Data source: SAMSS, age 16 years and over

70 Smoking policy and legislation Dec 2004 Smoke-free workplaces May 2007 Ban on smoking in cars with children less than 16 years Nov 2007 All enclosed public places and workplaces Current policy targeting retail sales displays 70

71 Proportion of adults reporting smoking undertaken in the home Data source: SAMSS, age 16 years and over 71 Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jun Prevalence of those smoke inside occasionally or frequently (%) Month

72 Time & Place E - Eating 72

73 Proportion of those who drink low fat milk Prevalence of those who drink low fat milk (%) July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 bimonthly Data source: SAMSS, age 16 years and over 73

74 Proportion of those who drink low fat milk by gender Male Female Data source: SAMSS, age 16 years and over July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 Prevalence of those who drink low fat milk (%) Graphs by sex Monthly

75 Proportion of those who drink low fat milk by age under 50 year 50 years + Data source: SAMSS, age 16 years and over July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 Prevalence of those who drink low fat milk (%) Graphs by two age groups Monthly

76 Proportion of those who drink low fat milk by metropolitan and country location Metro. Adelaide SA Country July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 Prevalence of those who drink low fat milk (%) Monthly Graphs by AREA3 Area of residence (Health regions) Data source: SAMSS, age 16 years and over 76

77 Proportion of those who drink low fat milk by income low income < $40,000 high income >= $40,001 Data source: SAMSS, age 16 years and over July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 Prevalence of those who drink low fat milk (%) Graphs by Income group Monthly

78 Proportion of those who drink low fat milk by chronic condition none at least 1 condition Data source: SAMSS, age 16 years and over July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 July 2002 January 2003 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 Prevalence of those who drink low fat milk (%) Graphs by At least one chronic conditions Monthly

79 Average serves of fast food consumed per year Data source: SAMSS, age 16 years and over 79 Average number fast food meals consumed per year July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 Monthly

80 Average serves of fast food consumed per year by gender Male Female Data source: SAMSS, age 16 years and over 80 Average number fast food meals consumed per year July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 Monthly

81 Average serves of fast food consumed per year by metropolitan and country location Metro. Adelaide SA Country Average number fast food meals consumed per year July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 July 2003 January 2004 July 2004 January 2005 July 2005 January 2006 July 2006 January 2007 July 2007 Monthly Graphs by AREA3 Area of residence (Health regions) Data source: SAMSS, age 16 years and over 81

82 Measuring effectiveness 82

83 Effectiveness Health promotion activities informed by data Health planning State Strategic Plan Media Evaluation 83

84 South Australia s Strategic Plan Objectives 1. Growing prosperity 2. Improving wellbeing 3. Attaining sustainability 4. Fostering creativity and innovation 5. Building communities 6. Expanding opportunity 98 targets 84

85 SA Strategic Plan Target 2.2 Healthy weight Increase the proportion of South Australians 18 and over with healthy weight by 10 percentage points by 2014 Target 2.6 Chronic diseases Increase by 5 percentage points, the proportion of people living with a chronic disease whose self-assessed health status is good or better Target 2.7 Psychological wellbeing Equal or lower than the Australian average for psychological distress by

86 Effectiveness Health promotion campaigns informed by data Health planning State Strategic Plan Media Evaluation 86

87 Risk factor surveillance results in the media 87

88 Effectiveness Health promotion campaigns informed by data Health planning State Strategic Plan Media Evaluation 88

89 Evaluation 89

90 Evaluation Center for Disease Control (CDC) 1 Level of usefulness Simplicity Flexibility Data quality Acceptability Representativeness Timeliness Stability 1. CDC (1988). Guidelines for evaluating surveillance systems. MMWR. 37(S5), pp

91 Conclusion Aim Improvement on health outcomes Value for money Use of data An effective risk factor surveillance system will provide the evidence for change 91

92 Contact Details Population Research & Outcome Studies (PROS) South Australian Department of Health PROS Website: 92