Data Matthew James The central role that peoples health and well - PowerPoint PPT Presentation

Health and Welfare Data Matthew James The central role that people’s health and well -being play in social cohesion and community change

Proportion of the adjusted health gap explained by differences in social determinants and health risk factors between Indigenous and non-Indigenous Australians, 2011 – 13 Social determinants Gap due to other factors 34.4% 46.8% (unexplained component) Healh risk factors 18.8% Overlap between social determinants & health risk factors (10.8%) Aboriginal and Torres Strait Islander Health Performance Framework 2

Life expectancy increases with socioeconomic position Life expectancy at age 65, by sex, by socioeconomic group Life expectancy at birth, by sex, by socioeconomic group (SEIFA), 2011 (SEIFA), 2011 88 25 86 85.3 86 84.4 22.9 22.6 83.5 84 83 22.2 82.7 Life expectancy (years) Life expectancy (years) 21.5 81.6 21.2 82 20.9 79.8 80 20.1 78.5 20 77.3 78 18.9 18.2 76 17.7 74 72 70 15 Q1 (lowest) Q2 Q3 Q4 Q5 (highest) Q1 (lowest) Q2 Q3 Q4 Q5 (highest) Socioeconomic group Socioeconomic group Males Females Males Females Source: Health-adjusted life expectancy in Australia: expected years lived in full health 2011. Australian Burden of Disease Study series no.16. BOD 17. Canberra: AIHW. IHW 2017 3

Lowest socioeconomic group (SEIFA) has highest all-cause mortality rate Age-standardised mortality rate, all causes, by sex, 2015 Quintile 5 (highest) Quintile 4 Socioeconomic group Quintile 3 Quintile 2 Quintile 1 (lowest) 0 100 200 300 400 500 600 700 800 per 100,000 Females Males Source: AIHW 2017. Mortality Over Regions and Time (MORT) books. Socioeconomic group, 2011-2015. 4

Life expectancy at birth, by PHN, 2014-2016 Low: Northern Territory 77.7 years High: Northern Sydney 85.7 years 5 Source: Source: AIHW analysis of the Australian Bureau of Statistics Life Tables, 2014 – 2016.

Life expectancy at birth, by PHN, 2014-2016: Sydney Low: Nepean Blue Mountains 81.9 years (18 th in Australia) High: Northern Sydney 85.7 years (1 st in Australia) 6 Source: Source: AIHW analysis of the Australian Bureau of Statistics (ABS) Life Tables, 2014 – 2016.

Mortality rates, by LGA, 2016 High: Derby-West Kimberley 1068.8 The mortality rate for Derby-West Kimberley is 3.1 times the rate for Nedlands Low: Nedlands 345.1 7 Source: AIHW Mortality Over Regions and Time (MORT) books, 2017. Data by LGA.

Mortality rates, by LGA, 2016: Sydney Low: Ku-ring-gai The mortality rate 352.6 for Campbelltown is (395 th in Australia) 1.8 times the rate for Ku-ring-gai High: Campbelltown 618.7 (110 th in Australia) 8 Source: AIHW Mortality Over Regions and Time (MORT) books, 2017. Data by LGA.

Broader regional areas with consistently high mortality rates 2011-2016 Kimberley region North western NSW and Northern Tablelands regions Northern and eastern 9 Tasmania Source: AIHW Mortality Over Regions and Time (MORT) books, 2017. Data by LGA.

Potentially avoidable mortality rates are decreasing over time Age-standardised death rates for potentially avoidable deaths, by sex, 1997 to 2016 300 250 Deaths per 100,000 population 200 150 100 50 0 2016 1997 2002 2007 2012 Year Males Females 10 Source: National Mortality Database

Potentially avoidable deaths, by LGA, 2016 High: Derby-West Kimberley 365.4 The potentially avoidable deaths rate for Derby- West Kimberley is 8.6 times the rate for Burnside Low: Burnside 42.3 11 Source: AIHW Mortality Over Regions and Time (MORT) books, 2017. Data by LGA.

Potentially avoidable deaths, by LGA, 2016: Sydney The rate of potentially avoidable deaths for Campbelltown Low: is 3 times the rate Waverley for Waverley 46.8 (278 th in Australia) High: Campbelltown 141.7 (64 th in Australia) 12 Source: AIHW Mortality Over Regions and Time (MORT) books, 2017. Data by LGA.

Chart from Case and Deaton for the US (Case and Deaton 2017) All-cause mortality by race and ethnicity, ages 50-54 White non-Hispanics 900 high school or less Black non-Hispanics 700 White non-Hispanics (all) 500 300 Hispanics 2000 2005 2010 2015 Survey year 13

Employment rate by sex, age 15 – 64, February 1978 to June 2018 trend data (per cent) 90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0 Male Female ABS Labour Force Survey 14

Employment rate non-Indigenous men aged 20-64, left school at 14 or below 90% 86% 80% 70% 60% 54% 50% 40% 30% 20% 10% 0% 1976 1981 1986 1991 1996 2001 2006 2011 Unpublished census data 15

Employment rate, non-Indigenous men aged 20-64, with and without a post school qualification (cert III and above) 100% With post school Without post school 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 1971 1976 1981 1986 1991 1996 2001 2006 2011 Unpublished census data 16

Employment rate, for men and women with a year 10 or below level of education, May 2008 to May 2017 (age 15-64) 100.0% Male 90.0% Female 80.0% 67.4% 70.0% 65.5% 65.3% 65.4% 64.9% 63.3% 62.6% 60.7% 60.6% 60.0% 60.0% 51.1% 51.6% 49.2% 48.8% 48.2% 48.4% 49.4% 48.5% 48.7% 50.0% 46.5% 40.0% 30.0% 20.0% 10.0% 0.0% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Unpublished data from the ABS Survey of Education and Work 17

Full-time, employment rate, for men and women with a year 10 or below level of education, May 2008 to May 2017 (age 15-64) 100.0% 90.0% Male 80.0% Female 70.0% 60.0% 55.4% 53.4% 52.8% 52.2% 51.7% 49.9% 48.6% 48.1% 50.0% 46.7% 46.5% 40.0% 30.0% 22.7% 23.5% 21.1% 21.2% 21.7% 21.6% 20.6% 19.6% 20.1% 18.9% 20.0% 10.0% 0.0% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Unpublished data from the ABS Survey of Education and Work 18

Proportion of persons whose self-assessed health is excellent by highest level of educational attainment, age 15 – 64, 2014-15 45.0 40.0 35.0 31.7 30.0 27.8 25.0 20.1 18.4 20.0 17.8 17.0 15.0 10.0 5.0 0.0 Postgrad Bachelor Degree Advanced Year 12 Year 11/Year 10/Cert I/II Year 9 and below/Never degree/Graduate Dip/Diploma/Cert III/IV attend school and no Dip]/Graduate Cert non-school qual Clear gradient by highest level of education ABS 2016. National Health Survey (2014 – 15), Expanded Confidentialised Unit Record File (CURF), DataLab. Findings based on use of ABS Microdata. 19

Proportion of persons whose self-assessed health is excellent by highest level of educational attainment, age 50-59, 2014-15 45.0 40.0 37.1 35.0 30.3 30.0 25.0 20.0 15.8 12.7 12.6 15.0 10.0 10.0 5.0 0.0 Postgrad Bachelor Degree Advanced Year 12 Year 11/Year 10/Cert Year 9 and below/No degree/Graduate Dipl/Diploma/Cert I/II school and no non- Dip/Graduate Cert III/IV school qual Clear gradient by highest level of education ABS 2016. National Health Survey (2014 – 15), Expanded Confidentialised Unit Record File (CURF), DataLab. Findings based on use of ABS Microdata. 20

Education. Average life expectancy (at 30-years of age) Average life expectancy at 30-years of age (only for people born in Sweden ). Education, gender Year 60 58 56 54 52 50 48 46 44 42 40 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Pre-upper-secondary, women Upper-secondary, women Post-secondary, women Pre-upper-secondary, men Upper-secondary, men Post-secondary, men Source: Sweden Population Statistics, Statistics Sweden.. Six Questions about Swedish Healthcare, Swedish Board of Health and Welfare 21

Healthcare-related avoidable mortality, Sweden Healthcare-related avoidable mortality – number of deaths per 100 000 inhabitants aged 35-79 years. Age-standardised statistics. Education, gender Per 100 000 inhabitants 160 140 120 100 80 60 40 20 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Pre-upper-secondary, women Upper-secondary, women Post-secondary, women Pre-upper-secondary, men Upper-secondary, men Post-secondary, men Source: Cause of Death Register, National Board of Health and Welfare . Six Questions about Swedish Healthcare, Swedish Board of Health and Welfare 22

Education. Avoidable deaths from ischaemic heart disease, Sweden Avoidable deaths from ischaemic heart disease per 100 000 inhabitants age 35 – 79, Age-standardised. Education Per 100 000 inhabitants 350 300 250 200 150 100 50 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Pre-upper-secondary, women Upper-secondary, women Post-secondary, women Pre-upper-secondary, men Upper-secondary, men Post-secondary, men Source: Cause of Death Register, National Board of Health and Welfare. Six Questions about Swedish Healthcare, Swedish Board of Health and Welfare 23

Daily smoking by socioeconomic area, age 18 + Per cent 30 23.9 25 22.4 20.3 20.2 18.7 20 15.2 14.1 15 12.4 10.7 10 6.9 5 0 Lowest 2 3 4 Highest 2001 2004 2007 2010 2013 2016 Clear socioeconomic gradient. Rates declined across all groups but second highest and highest area declining at fastest rate than the lowest group. AIHW customise analysis of the NDSHS 24