Latest release

Gender Indicators, Australia

Indicators to aid exploration of economic and social differences between women and men over time, using data from ABS and other official sources

Print
Reference period
2020

Key statistics

  • Women’s full time adult average weekly ordinary time earnings were 86% of that of men.
  • Recorded crimes data showed women were five times more likely to be victims of sexual assault than men.
  • For the first time, there was equal representation between men and women parliamentarians in the Senate. 

Key series and indicators

Gender Indicators is being updated. The aim is to support easy access to key data relating to gender equality, with the ability to find more detailed data as needed. The preliminary version of this prototype can be found on our ABS Beta website: Gender Indicators, Australia, 2021 | Australian Bureau of Statistics (abs.gov.au)
 
The ABS welcomes feedback from users about their experience, the content and design of this prototype. Please provide feedback via the green feedback tab on the right hand side of the page, or for more detailed feedback please email: gender.statistics@abs.gov.au. 
 
Please note that the December 2020 release of Gender Indicators, Australia was the final release in that format.

The Key Series and associated Indicators for this publication are listed below.

Indicators with an update in 2020 are identified.

Updated for 2020INDICATORS
 ECONOMIC SECURITY
  1. Working Population
^ Labour force
^ Employment conditions
^ Underutilised labour
^ Not in the labour force
  2. Earnings, income and economic situation and Housing
^  Earnings
   Main source of income at retirement
   Superannuation
   Economic resources
   Financial stress
   Housing circumstances
  3. Selected tables with expanded populations
   Key series by Cultural and Linguistic Diversity, Indigenous status and Disability status
 EDUCATION
  4. Attainment
^  Year 12 or a formal qualification at Certificate II or above
^  Non-school qualification
   Literacy and numeracy skills
  5. Participation and Education & employment
^  Participation
^  Participation in a non-school qualification
   Work related learning
^  Education and employment
^  Starting salaries
  6. Selected tables with expanded populations
   Key series by Cultural and Linguistic Diversity, Indigenous status and Disability status
 HEALTH
  7. Health status
^  Health status (life expectancy)
^  Long-term health conditions
^  Living with a disability
^  Psychological stress
   Mental health
  8. Deaths
^  Death
^  Deaths from cancer
^  Deaths from diseases of the circulatory system
^  Suicides
^  Deaths in motor vehicle accidents
^  Drug induced deaths
^  Perinatal deaths
  9. Risk factors and Service
^  Risk factors (consumption of alcohol)
^  Smoking
^  Overweight/obese
^  Levels of exercise
^  Medicare services
 WORK AND FAMILY BALANCE
  10. Work and family balance
   Time use
   Caring for children
^  Providing care
^  Providing care to a person with disability
   Provided care to someone in the last week
   Time stress and work and family balance
   Work and family balance
^   Overall life satisfaction
^   Volunteering
  11. Selected tables with expanded populations
   Key series by Cultural and Linguistic Diversity, Indigenous status and Disability status
 SAFETY AND JUSTICE
  12. Safety and justice
^   Experiences of crime
^  Victimisation
^  Imprisonment
^  Offenders
 DEMOCRACY, GOVERNANCE AND CITIZENSHIP
  13. Democracy, Governance & Citizenship
^  Non-public sector employers
^  Parliamentarians
^  Membership of Commonwealth Government boards and bodies
^  Australian Public Service senior and middle managers
^  Justices and Judges
^  Order of Australia awards
^  Involvement in civic, community or social groups

^ Indicates all/ some of table has been updated with new data

Economic security

Key findings

The key findings for Economic Security are:

  1. For those aged 20-74 years, employed women are almost three times more likely than men to be working part-time in 2019–20.
  2. For parents whose youngest dependent child was under six, three in five employed mothers worked part-time compared to less than one in ten employed fathers.
  3. In May 2020, women’s full time adult average weekly ordinary time earnings were 86% of that of men. This ratio is the same as that in May 2019. This represents a gender pay gap (GPG) of 14%.

Data

The detailed data supporting the following insights are available from the Data downloads section of this publication:

  • Data Cube 1: Economic Security - Working population
  • Data Cube 2: Economic Security - Earnings, income & economic situation and Housing.
     

Insights

Working population

Employment and labour force participation

The following data are available in Data Cube 1, Table 1.1.

In 2019-20, two-thirds of women (67.6%) and more than three-quarters of men (78.1%) aged 20–74 years old participated in the labour force. The 2019-20 rate is the highest for women during the past 10 years.

Between 2009-10 and 2019-20, women aged 60 years or older accounted for three of the four largest increases for female labour force participation rates by age group:

  • 30-34 years, a 7.1% increase (70.7% to 77.8%)
  • 60-64 years, a 9.9% increase (41.8% to 51.7%)
  • 65-69 years, a 7.5% increase (17.3% to 24.8%)
  • 70-74 years, a 5.9% increase (4.8% to 10.7%).

In all age groups, except 15-19 years, the labour force participation rate for women is lower than that for men. The age groups with the largest difference were:

  • 30-34 years, a 13.9% difference (77.8% of women compared to 91.7% of men)
  • 35-39 years, a 15.1% difference (77.5% of women compared to 92.6% of men)
  • 60-64 years, a 13.1% difference (51.7% of women compared to 64.8% of men)

For parents aged 20–74 years, whose youngest child was under six years old, only around two-thirds of women compared to nine-tenths of men participated in the labour force:

  • 65.5% of women
  • 94.4% of men.

For those parents whose youngest child was 6-14 years old, the female participation rate greatly increases, though still below that of men, likely reflecting some women re-entering the work force once their children reach primary school age:

  • 80.2% of women
  • 92.4% of men.

Occupation

The following data are available in Data Cube 1, Table 1.6.

The gender composition of the workforce aged 20–74 years old differs across occupations and industries.

In 2019-20, managers are almost twice as likely to be men (61.4%) than women (38.6%).

In 2019–20, the female dominated occupations with the highest proportion of women remain unchanged over the last decade:

  • Clerical and administrative workers (72.7%)
  • Community and personal service workers (70.3%)
  • Sales workers (58.1%).

Those occupations with the highest proportion of men in 2019-20 have remained unchanged from the previous year, though over the last decade Labourers have replaced Managers as the third most male dominated occupation:

  • Machinery operators and drivers (89.3%)
  • Technicians and trades workers (83.8%)
  • Labourers (65.5%).
  1. Data were calculated as an average of four quarters (August, November, February, May) in the financial year. 
  2. Occupation is classified according to the Australian and New Zealand Standard Classification of Occupations (ANZSCO), 2006 (cat. no. 1220.0).     
  3. This release of Gender Indicators, Australia, uses the population benchmarks from ABS Labour Force, Australia, Aug 2020.    

Industry

The following data are available in Data Cube 1, Table 1.3.

The industries with the highest proportions of women and men have remained consistent over the past decade.

In 2019–20, the industries with the highest proportion of women aged 20-74 were:

  • Health care and social assistance (77.9%)
  • Education and training (71.6%)
  • Retail trade (55.2%)
  • Accommodation and food services (54.5%)
  • Administrative and support services (52.9%)

In 2019–20, the industries with the highest proportion of men aged 20-74 were:

  • Construction (87.3%)
  • Mining (83.0%)
  • Transport, postal and warehousing (79.8%)
  • Electricity, gas, water and waste services (76.2%)
  • Manufacturing (72.5%)
  1. Data were calculated as an average of four quarters (August, November, February, May) in the financial year.
  2. Industry is classified according to the Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006 (cat. no. 1292.0).
  3. This release of Gender Indicators, Australia, uses the population benchmarks from ABS Labour Force, Australia, Aug 2020.                                        

Employment conditions

The following data are available in Data Cube 1, Tables 1.9, 1.10 and 1.12.

Part-time employees

For those aged 20-74 years, employed women (43.0%) are more likely than men (16.0%) to be working part-time in 2019–20. This is the situation across all age groups.

The differences in part-time working arrangements were most pronounced for parents with dependent children:

  • For parents whose youngest child was under six, three in five employed mothers (59.1%) worked part-time compared to less than one in ten employed fathers (7.9%)
  • For parents whose youngest child was aged 6-14 years, close to half of all employed mothers (47.7%) worked part-time, compared to less than one in ten employed fathers (8.7%).

In 2019-20, the average number of hours worked by both women and men working part-time was the same (17.7 hours per week). However, for those working full-time, women (36.2 hours) worked fewer hours on average than men (39.8 hours).

Casual employees

In 2019, around the same proportion of female (21.2%) and male (18.3%) employees aged 20-74 years did not have paid leave entitlements.

When considering all employees aged 15 years and over, women (26.4%) are more likely to work in casual jobs than men (22.5%) based upon access to paid leave entitlements. For women, those aged 15-34 years were the most likely to be employed casually (36.3%). For men, those aged 65 years or older were most likely to be employed casually (38.1%).

Underutilised labour

The following data are available in Data Cube 1, Tables 1.14, 1.15 and 1.16.

In 2019–20, the unemployment rate was similar for women and men aged 20–74 years old (4.8% females and 4.9% males).

In 2019-20, the highest unemployment rates for both women and men were in the younger age groups:

  • 15-19 years, with females 16.1% and males 19.9%
  • 20-24 years, with females 8.6% and males 10.6%.

The lowest rates of unemployment for women under 65 years in 2019-20 were between 40 and 59 years:

  • 40-44 years, 4.1% unemployment rate
  • 45-49 years, 3.9% unemployment rate
  • 50-54 years, 3.9% unemployment rate
  • 55-59 years, 3.8% unemployment rate.

In comparison, the lowest rates of unemployment for men aged under 65 years in 2019-20 were between 30 and 49 years:

  • 30-34 years, 3.9% unemployment rate
  • 35-39 years, 3.9% unemployment rate
  • 40-44 years, 3.7% unemployment rate
  • 45-49 years, 4.0% unemployment rate.

For parents aged 20-74 years, with a dependent child under six years, the unemployment rate for mothers (5.3%) is almost double that of fathers (2.8%).

In 2019-20, for those aged 20-74 years, the underemployment rate for women was 10.3% and for men was 7.2%. This represents people in the labour force who wanted, and were available for, more hours of work than they currently had.

Adding people who are either unemployed or underemployed together creates an underutilised labour force population, from which an underutilisation rate can be derived. The labour force underutilisation rate in Australia in 2019–20 for those aged 20–74 years old was higher for women (15.1%) than it was for men (12.1%).

​​​​​​​People not in the labour force

The following data are available in Data Cube 1, Table 1.17.

In 2019-20, a third of women (32.4%) and just over one in five men (21.9%) aged 20–74 years old were not in the labour force.

The largest difference between men and women was for people aged between 30 and 39 years where women were around three times more likely than men to be out of the labour force:

  • 30-34 years, 22.2% of women compared with 8.3% men
  • 35–39 years, 22.5% of women compared with 7.4% men.

This may reflect the age group of women more likely to be having children, and taking a major role in their care, since the median age of mothers at birth in 2019 was 31.5 years, as detailed in Births, Australia, 2019.

  1. Data averaged using 12 months in the financial year.                                                                                        
  2. This release of Gender Indicators, Australia, uses the population benchmarks from ABS Labour Force, Australia, Aug 2020.                 

​​​​​​​Earnings, income and economic situation

​​​​​​​Earnings

The following data are available in Data Cube 2, Table 2.5.

In May 2020, women's full time adult average weekly ordinary time earnings were 86% of that of men. This ratio is the same as that in May 2019. This represents a gender pay gap (GPG) of 14%.

The GPG measures the relative position of women and men in the economy. For further discussion on the gender pay gap see the following articles:

Education

Key findings

The key findings for Education are:

  1. Women are more likely than men to have attained a Bachelor degree or above qualification.
  2. For graduates of most fields of study, females are paid less than their male counterparts. In 2020, the field study with the largest difference was Dentistry ($79,300 for females compared to $90,000 for males).
     

Data

The detailed data supporting the following insights are available from the Data downloads section of this publication:

  • Data Cube 4: Education - Attainment
  • Data Cube 5: Education - Participation and Education & employment.
     

Insights

Attainment

Year 12 or a formal qualification of Certificate II or above

The following data are available in Data Cube 4, Table 4.1.

In 2020, around 4 in 5 people aged 15 to 64 years had attained Year 12 or a formal qualification at Certificate II or above (80.8% of females and 79.4% of males).

In 2020, for those aged 20-24 years:

  • 92.5% of women compared to 87.5% of men had attained Year 12 or a formal qualification of Certificate II or above.
  • 48.0% of women compared to 39.0% of men had a formal qualification at Certificate II or above.

Over the past 10 years, there has generally been increases in attainment of a formal qualification of Certificate of II or above for all age groups, with the increase most notable for women aged between 35 and 49 years:

  • 35-39 years, a 16.5% increase between 2010 and 2020 (62.7% to 79.2%)
  • 40-44 years, a 15.8% increase between 2010 and 2020 (59.2% to 75.0%)
  • 45-49 years, a 11.5% increase between 2010 and 2020 (58.2% to 69.7%).
  1. Includes any of the following: Year 12; Certificate II, III, or IV; Advanced Diploma or Diploma; Bachelor Degree; Graduate Diploma or Graduate Certificate, or Post Graduate Degree.
  2. Males and females who have attained Year 12 or a formal qualification at Certificate II or above as a proportion of all persons for each sex and age group.                                                                                
  3. Certificate II or above includes Certificate I & II Level n.f.d. but excludes school qualifications.

Certificate III or above

The following data are available in Data Cube 4, Table 4.3.

For people aged 18-64 years in 2020, around 3 in 5 women (62.4%) and men (60.6%) had attained a formal qualification of Certificate III or above.

In 2020, more women (72.2%) then men (65.4%) aged 25-29 years had attained a formal qualification of Certificate III or above. 

In 2010, for those aged 25-29 years, women and men had around the same level of attainment for Certificate III or above. Women have since increased their attainment levels for Certificate III or above, while men’s attainment has remained around the same:

  • Women increased from 63.2% in 2010 to 72.2% in 2020
  • Men remained around the same at 62.1% in 2010 and 65.4% in 2020.
  1. Includes any of the following: Certificate III, or IV; Advanced Diploma or Diploma; Bachelor Degree; Graduate Diploma or Graduate Certificate, or Post Graduate Degree.
  2. Prior to 2013, people permanently unable to work were excluded from the scope of the Survey of Education and Work (SEW).
  3. Comparison of data over time will be impacted by revisions to the Estimated Resident Population following each Census and subsequent Post-Enumeration Survey (PES). Re-basing following the 2011 Census and subsequent PES appeared in SEW for the first time in the May 2014 estimates, but the new time series of benchmarks was not back-cast through the SEW time series; hence the ABS recommends caution in making such comparisons. The 2013 to 2014 comparison is most affected by this re-basing. While this issue may impact on estimates of proportions, its impact will be more prominent in estimates of counts of persons.
  4. The method for avoiding the release of confidential data from 2014 onwards includes the random adjustment of data. Discrepancies may occur between sums of the component items and totals.
  5. Males and females who have attained a formal qualification at Certificate III or above as a proportion of all persons for each sex and age group.

Bachelor Degree or above

The following data are available in Data Cube 4, Table 4.5.

In 2020, women are more likely to have a Bachelor Degree or above than men in all age categories. For those aged 25-29 years, around half of women (48.3%) and around a third of men (36.1%) had attained a Bachelor Degree or above.

Over the past decade, the proportion of people aged 18-64 years old in Australia with a Bachelor Degree or above has increased for both men and women. However, it has increased at a higher rate for women:

  • Attainment for women increased 10.7% (from 26.4% in 2010 to 37.1% in 2020)
  • Attainment for men increased 7.0% (from 22.4% in 2010 to 29.4% in 2020).
    1. Prior to 2013, people permanently unable to work were excluded from the scope of the Survey of Education and Work (SEW).
    2. Comparison of data over time will be impacted by revisions to the Estimated Resident Population following each Census and subsequent Post-Enumeration Survey (PES). Re-basing following the 2011 Census and subsequent PES appeared in SEW for the first time in the May 2014 estimates, but the new time series of benchmarks was not back-cast through the SEW time series; hence the ABS recommends caution in making such comparisons. The 2013 to 2014 comparison is most affected by this re-basing. While this issue may impact on estimates of proportions, its impact will be more prominent in estimates of counts of persons.
    3. The method for avoiding the release of confidential data from 2014 onwards includes the random adjustment of data. Discrepancies may occur between sums of the component items and totals.
    4. Males and females who have attained a Bachelor Degree or above as a proportion of all persons for each sex and age group.

    In 2020, the age group with the highest level of attainment of Bachelor Degree or above differed between women and men. The age group with the highest level of attainment for each sex was:

    • 30-34 years for women (50.1%)
    • 35-44 years for men (39.8%).
    1. Prior to 2013, people permanently unable to work were excluded from the scope of the Survey of Education and Work (SEW).
    2. Comparison of data over time will be impacted by revisions to the Estimated Resident Population following each Census and subsequent Post-Enumeration Survey (PES). Re-basing following the 2011 Census and subsequent PES appeared in SEW for the first time in the May 2014 estimates, but the new time series of benchmarks was not back-cast through the SEW time series; hence the ABS recommends caution in making such comparisons. The 2013 to 2014 comparison is most affected by this re-basing. While this issue may impact on estimates of proportions, its impact will be more prominent in estimates of counts of persons.
    3. The method for avoiding the release of confidential data from 2014 onwards includes the random adjustment of data. Discrepancies may occur between sums of the component items and totals.
    4. Males and females who have attained a Bachelor Degree or above as a proportion of all persons for each sex and age group.

    Non-school qualification

    The following data are available in Data Cube 4, Table 4.7.

    Around two-thirds of people aged 15-64 years had attained a non-school qualification in 2020: 64.3% of females compared to 62.7% of males. This is the highest rate for attainment of a non-school qualification for both women and men over the last decade.

    The highest levels of non-school qualifications for women in 2020 were:

    • Bachelor degree (22.7%)
    • Certificate III/IV (13.1%)
    • Advanced Diploma/Diploma (11.1%)
    • Postgraduate Degree (8.5%).

    The highest levels of non-school qualifications for men in 2020 were:

    • Certificate III/IV (20.8%)
    • Bachelor degree (17.5%)
    • Advanced Diploma/Diploma (8.8%)
    • Postgraduate Degree (7.9%).
    1. Includes 'Certificate not further defined' and 'Level not determined'. 
    2. Prior to 2013, people permanently unable to work were excluded from the scope of the Survey of Education and Work (SEW).
    3. Comparison of data over time will be impacted by revisions to the Estimated Resident Population following each Census and subsequent Post-Enumeration Survey (PES). Re-basing following the 2011 Census and subsequent PES appeared in SEW for the first time in the May 2014 estimates, but the new time series of benchmarks was not back-cast through the SEW time series; hence the ABS recommends caution in making such comparisons. The 2013 to 2014 comparison is most affected by this re-basing. While this issue may impact on estimates of proportions, its impact will be more prominent in estimates of counts of persons.
    4. The method for avoiding the release of confidential data from 2014 onwards includes the random adjustment of data. Discrepancies may occur between sums of the component items and totals.
    5. Males and females who have attained a non-school qualification as a proportion of all persons aged 15-64 years for each sex.

    ​​​​​​​Main field of education for non-school qualification

    The following data are available in Data Cube 4, Tables 4.10 and 4.11.

    The main fields of non-school qualifications have remained consistent for both females and males over the past 10 years.

    In 2020, the top three main fields of non-school qualification for women were:

    • Management and commerce (26.9%)
    • Society and culture (19.9%)
    • Health (16.5%).

    In 2020, the top three main fields of non-school qualifications for men were:

    • Engineering and related technologies (28.4%)
    • Management and commerce (20.5%)
    • Architecture and building (10.9%).
    1. Includes 'Mixed field programmes' and 'Field not determined'. 
    2. Prior to 2013, people permanently unable to work were excluded from the scope of the Survey of Education and Work (SEW).
    3. Comparison of data over time will be impacted by revisions to the Estimated Resident Population following each Census and subsequent Post-Enumeration Survey (PES). Re-basing following the 2011 Census and subsequent PES appeared in SEW for the first time in the May 2014 estimates, but the new time series of benchmarks was not back-cast  through the SEW time series; hence the ABS recommends caution in making such comparisons. The 2013 to 2014 comparison is most affected by this re-basing. While this issue may impact on estimates of proportions, its impact will be more prominent in estimates of counts of persons.
    4. The method for avoiding the release of confidential data from 2014 onwards includes the random adjustment of data. Discrepancies may occur between sums of the component items and totals.
    5. Males and females who have attained a non-school qualification by field of qualification as a proportion of persons with a non-school qualification for each sex and age group.

    While there are more women (16.5%) than men (5.5%) with a Health qualification, there are significantly less women (12.6%) than men (25.3%) with Postgraduate Health qualifications.

    In the field of Engineering and related technologies more women than men who have a qualification in this field have a Postgraduate Degree (women 15.9% and men 5.9%) or a Bachelor Degree (women 38.7%, men 19.0%). The majority of men have a Certificate III/IV qualification (women 23.3%, men 53.7%). However, men overall have a much larger share of the total qualifications in this field (144,400 women compared with 1,466,600 men).

    Similarly, women with a qualification in the field of Architecture and building tend to have higher level qualifications. Of women with a qualification in this field, 23.2% have a Postgraduate Degree (compared with 2.0% of men) and 36.9% a Bachelor Degree (compared with 7.6% of men). The majority of men have a Certificate III/IV qualification (women 15.2%, men 70.4%). However, men overall also have a much larger share of the total qualifications in this field (77,700 women compared with 563,900 men).

    Participation

    Apparent retention rate

    The following data are available in Data Cube 5, Table 5.3.

    In 2019, the apparent retention rate from Year 7/8 to Year 12 was higher for females (88.6%) than males (79.6%). This rate has improved over the past decade. In 2009, this rate was 81.4% for females and 70.8% for males.

    Enrolment in apprenticeships and traineeships by age

    The following data are available in Data Cube 5, Table 5.7.

    In 2020, enrolments in an apprenticeship or traineeship for males (13.7%) aged 15-24 years were almost seven times higher than that of females (2.0%).

    Education and employment

    Not fully engaged in education and/or employment by selected age groups (NEET)

    The following data are available in Data Cube 5, Table 5.13.

    In 2020, around the same proportions of women (30.1%) and men (27.8%) aged 20-24 years were not fully engaged in education and/or employment. This is the highest value for males over the past decade, and nearly the highest for females.

    For those aged 15-19 years who were not fully engaged in education and/or employment in 2020, females (13.5%) had a lower engagement rate than males (15.3%). For females, this is the highest rate since 2011. For males, this equals the previous highest rate over the past decade, which occurred in 2010.

    1. In 2013 and 2014 education data is restricted to formal study (study for a qualification). Data for previous years include some people who may have been undertaking non-formal learning. For more information see the 'Education glossary', available from the 'Methodology' tab of this publication.
    2. Prior to 2013, people permanently unable to work were excluded from the scope of the Survey of Education and Work (SEW).
    3. Comparison of data over time will be impacted by revisions to the Estimated Resident Population following each Census and subsequent Post-Enumeration Survey (PES). Re-basing following the 2011 Census and subsequent PES appeared in SEW for the first time in the May 2014 estimates, but the new time series of benchmarks was not back-cast through the SEW time series; hence the ABS recommends caution in making such comparisons. The 2013 to 2014 comparison is most affected by this re-basing. While this issue may impact on estimates of proportions, its impact will be more prominent in estimates of counts of persons.
    4. The method for avoiding the release of confidential data from 2014 onwards includes the random adjustment of data. Discrepancies may occur between sums of the component items and totals.
    5. This table refers to males and females not fully engaged in education and/or employment as a proportion of persons for each sex and age group. People are categorised as fully engaged in education and/or employment if they are: employed full-time; studying full-time; or both studying part-time and employed part-time.   

    Median starting salary for undergraduates

    The following data are available in Data Cube 5, Table 5.15.

    In 2020, the median starting salary for female undergraduates was $63,400 compared to $65,000 for male undergraduates. While a disparity has consistently remained, the median starting salary increased at a higher rate for female undergraduates ($7,000) from 2016 compared to males ($5,000).

    The top five study areas with the highest median starting salary in 2020 were the same for both females and males:

    • Dentistry
    • Medicine
    • Engineering
    • Social Work
    • Teacher education.

    Across all but four study areas, female undergraduates were paid less than male graduates. The field study with the largest difference was Dentistry ($79,300 for females compared to $90,000 for males).

    Health

    Key findings

    The key findings for Health are:

    1. Women are expected to live 4.1 years longer than men, though the gap is narrowing.  In 1965-67, the gap was 6.6 years.
    2. In 2019, dementia remained the leading cause of death for women, where it has been ranked since overtaking Ischaemic heart disease in 2017. Dementia has now overtaken lung cancer as the second leading cause of death (following Ischaemic heart disease) for males.

    Data

    The detailed data supporting the following insights are available from the Data downloads section of this publication:

    • Data Cube 7: Health - Health status
    • Data Cube 8: Health - Deaths
    • Data Cube 9: Health - Risk factors and Services.
       

    Insights

    Health status

    ​​​​​​​Life expectancy

    The following data are available in Data Cube 7, Table 7.1.

    Life expectancy at birth is greater for Australian females than males, however male life expectancy is improving at a faster rate than that of females:

    • In 2017-19, life expectancy at birth for females was 85.0 years compared with 80.9 years for males: a gap of 4.1 years
    • Around 50 years ago (1965-67), life expectancy for females was 74.2 years compared with 67.6 years for males: a gap of 6.6 years.

    According to Life Expectancy at Birth in Life Tables, States, Territories and Australia, 2017-19, reasons for improvements in life expectancy include:

    • Improved health services
    • Safer working environments
    • Advances in medicine and technology.

    Living with a disability

    The following data are available in Data Cube 7, Table 7.6.

    Females reported disability at a lower rate (15.7%) than men (16.5%) in 2018.

    Leading causes of death

    The following data are available in Data Cube 8, Table 8.2.

    For females, dementia remained the leading cause of death, where it has been ranked since overtaking Ischaemic heart disease in 2017. Dementia has now overtaken lung cancer as the second leading cause of death (following Ischaemic heart disease) for males in 2019.

    The number of deaths due to dementia has been increasing consistently over the last 10 years for both females and males. Since 2009, the age-standardised death rate for dementia has increased by 36.0% for females and 31.8% for males, to reach 46.1 and 38.1 deaths per 100,000 people for females and males, respectively in 2019.

    1. Care needs to be taken when interpreting data derived from deaths registered in Victoria. As a result of joint investigations between the ABS and the Victorian Registry 2,739 death registrations from 2017 and 2018 were identified that had not previously been provided to the ABS, and which were in scope of the 2019 reference year. An issue associated with the Registry's previous processing system (replaced in 2019) resulted in delays to the provision of some death registrations to the ABS. Whilst these are included in overall total numbers of all cause deaths for 2019 in line with ABS scope rules, a time series adjustment has been applied to deaths due to suicide presented in this table, to enable a more accurate comparison of mortality over time for this cause. When the time series adjustment is applied, affected deaths are presented in the year in which they were registered (i.e. removed from 2019 and added to 2017 or 2018). See Technical note: Victorian additional registrations and time series adjustments in Causes of Death, Australia, 2019 for detailed information on this issue.       
    2. Causes listed are the top 15 leading causes of death for all deaths registered in 2019, based on the WHO recommended tabulation of leading causes. As the ranking of leading causes may change each year, the causes included in this table may differ to those in previous Gender Indicators publications. See Mortality tabulations and methodologies in Causes of Death, Australia, 2019 for further information on the WHO recommended tabulation of leading causes. For previous WHO tabulations of leading causes, please refer to earlier releases of the Causes of Death, Australia publication.                                                    
    3. All causes of death data from 2006 onward are subject to a revisions process - once data for a reference year are 'final', they are no longer revised. Affected data in this table are: 2009 - 2016 (final), 2017 (revised), 2018 and 2019 (preliminary). See the Data quality section of the 'Methodology' in the Causes of Death, Australia, 2019 publication and Causes of Death Revisions, 2016 Final Data (Technical Note) and 2017 Revised Data (Technical Note) in Causes of Death, Australia, 2018 (cat. no. 3303.0).                                        
    4. See the Data quality section of the 'Methodology' in the Causes of Death, Australia, 2019 publication for further information on specific issues related to interpreting time-series and 2019 data.                                  
    5. Age-standardised death rates (SDRs) enable the comparison of death rates between populations with different age structures. The SDRs in this table are presented on a per 100,000 population basis, using the estimated mid-year population (30 June). Some rates are unreliable due to small numbers of deaths over the reference period. This can result in greater volatility of rates. As such, age-standardised death rates based on a death count of fewer than 20 have not been published, and appear as 'np'. See the 'Glossary' and the Mortality tabulations and methodologies section of the 'Methodology' in the Causes of Death, Australia, 2019 publication for further information.
    6. Changes in coding processes have been applied to 2019 data. See the Classifications and Mortality coding sections of the 'Methodology' in Causes of Death, Australia, 2019 for further information.

    The following data are available in Data Cube 8, Table 8.8.

    In 2019, men (19.8%) had an age-standardised death rate from suicide three times higher than that of women (6.3%). The age-specific death rate from suicide was highest for women in the 35-44 age group (9.4%) and highest for men in the 85 and over age group (32.3%).

    Work and family balance

    Key findings

    The key findings for Work and Family Balance are:

    1. In 2018-19, 93.5% of primary parental leave (paid or unpaid) was taken by women in the non-public sector.
    2. Proportionally, managers are much more likely than those in non-managerial positions in the non-public sector to access parental leave.
    3. In 2018, more than double the number of women (618,800) than men (241,900) provided primary care to a person with a disability.
    4. Female volunteering decreased from around four in ten in 2010 to three in ten in 2019.

    Parental leave in the non-public sector

    The following data are available in Data Cube 10, Table 10.3.

    The data discussed in this section refers to non-public organisations with 100 or more employees. Under the Workplace Gender Equality Act 2012, non-public sector employers with 100 or more employees must report annually to the Workplace Gender Equality Agency (WGEA) on the gender composition of their workforce.

    WGEA defines primary parental leave as leave taken by a member of a couple or a single carer, regardless of gender, identified as having greater responsibility for the day-to-day care of a child. Secondary parental leave is defined as leave taken by a member of a couple or a single carer, regardless of gender, who is not the primary carer. Primary parental leave is the type of leave most likely to affect people's career trajectories.

    In 2018–19, for non-public sector employees:

    • 93.5% of primary parental leave (paid or unpaid) was taken by women
    • 96.1% of secondary parental leave (paid or unpaid) was taken by men. 

    Proportionally, managers in the non-public sector were more likely than non-managers to use primary parental leave in 2018-19:

    • Around one in 15 women who were managers in the non-public sector accessed primary parental leave (a rate of 6.8 per 100)
    • Around one in 24 women in non-managerial positions in the non-public sector accessed primary parental leave (a rate of 4.1 per 100)
    • Around one in 167 men who were managers in the non-public sector accessed primary parental leave (a rate of 0.6 per 100)
    • Around one in 333 men in non-managerial positions in the non-public sector accessed primary parental leave (a rate of 0.3 per 100).

    Overall, more than 96,100 women employed in the non-public sector used some form of parental leave in 2018-19 compared with just over 38,300 men.

    Providing primary care

    The following data are available in Data Cube 10, Table 10.4.

    In 2018, 6.1% of women (618,800) provided primary care to a person with a disability, compared to 2.5% of men (241,900).

    Women (45.7%) were more likely than men (41.9%) to be employed and providing primary care to a person with disability.

    Volunteering

    The following data are available in Data Cube 10, Table 10.10.

    For people aged 18 years and over, the total rate of volunteering through an organisation has declined since 2010. For persons aged 18 years and over, the volunteering rate has declined from 36.2% in 2010, to 30.9% in 2014 and to 28.8% in 2019. The decline has been most evident for females, whose rate decreased from 38.1% in 2010 to 28.1% in 2019.

    Life satisfaction

    The following data are available in Data Cube 10, Table 10.9.

    In 2019, there was a similar proportion of women (78.5%) and men (76.6%) reporting above average life satisfaction.

    Safety and justice

    Key findings

    The key findings for Safety and Justice are:

    1. In 2019, recorded crimes data showed women were five times more likely to be victims of sexual assault than men.
    2. Over the past decade, illicit drug offences have continued as the leading principal serious offence for women, and experienced the largest increase in most serious offence for both women and men.

    Experience of physical or threatened assault or violence

    The following data are available in Data Cube 12, Tables 12.5 and 12.7.

    In 2018-19, females (4.4%) aged 15 years or older were less likely than males (5.2%) aged 15 years or older to have experienced physical or threatened physical assault in the past 12 months.

    However, for the 15-19 years age group in 2018-19, females (8.7%) were as likely as males (8.0%) to have experienced physical or threatened physical assault in the past 12 months.

     

    Victimisation rates - Sexual assault

    The following data are available in Data Cube 12, Table 12.8.

    In 2019, the number of recorded incidents of female victims of sexual assault was more than five times higher than that for males:

    • 174.8 per 100,000 females
    • 34.8 per 100,000 males.

    Over the past decade, these rates have increased for both women (143.8 per 100,000 females in 2010) and men (26.1 per 100,000 males in 2010), with there continuing to be a disproportionately higher rate of women who were victims of sexual assault.

    1. Victimisation rates are expressed as victims per 100,000 of the ABS Estimated Resident Population (ERP) by sex. They are calculated using the ERP as at the midpoint of the reference period (i.e. 30 June). Rates have been revised with the finalised rebased population estimates released using the results of the 2016 Census of Population and Housing.                             
    2. Statistics produced on the basis of date reported may be affected over time by lags in completing and/or processing some crime reports. Where offences reported in the reference year are not processed for inclusion in the national statistics until the following year, revised data are included in subsequent publications and noted accordingly. In this graph, 2018 data have been revised to address this lag in reporting.

    ​​​​​​​Sentenced prisoners

    The following data are available in Data Cube 12, Table 12.11.

    In 2019, 7.4% of sentenced prisoners were female (2,117 females compared to 26,605 males).

    As at 30 June 2019, a higher proportion of female sentenced prisoners than male sentenced prisoners had a most serious offence of:

    • Illicit drug offences (22.5% compared to 14.1%)
    • Fraud, deception and related offences (8.8% compared to 1.7%)
    • Theft and related offences (7.7% and 3.2%).

    As at 30 June 2019, a higher proportion of male sentenced prisoners than female sentenced prisoners had a most serious offence of:

    • Sexual assault and related offences (15.9% compared to 1.9%)
    • Acts intended to cause injury (18.5% compared to 13.5%).
    1. For the definition of most serious offence, see 'Methodology' in Prisoners in Australia.                
    2. Offence data for 2009 are based on ASOC 2008, with the exception of data for Qld and WA which are based on ASOC 1997. Data for 2010 are based on ASOC 2008 for all states and territories and data for 2011 onwards are based on the Australian and New Zealand Standard Offence Classification (ANZSOC), 2011 (cat. no. 1234.0). Caution should be exercised in comparing offence data. See 'Methodology' in Prisoners in Australia.

    From 2009 to 2019 the most notable changes in the proportions of female sentenced prisoners by most serious offence were:

    • Illicit drug offences increased from 16.1% to 22.5%
    • Unlawful entry with intent increased from 7.0% to 11.0%
    • Fraud, deception and related offences decreased from 12.7% to 8.8%
    • Theft and related offences decreased from 10.8% to 7.7%.
    1. For the definition of most serious offence, see 'Methodology' in Prisoners in Australia.                
    2. Offence data for 2009 are based on ASOC 2008, with the exception of data for Qld and WA which are based on ASOC 1997. Data for 2010 are based on ASOC 2008 for all states and territories and data for 2011 onwards are based on the Australian and New Zealand Standard Offence Classification (ANZSOC), 2011 (cat. no. 1234.0). Caution should be exercised in comparing offence data. See 'Methodology' in Prisoners in Australia.

    From 2009 to 2019 the most notable changes in the proportion of male sentenced prisoners by most serious offence were for:

    • Illicit drug offences, up from 9.8% of male sentenced prisoners to 14.1%
    • Robbery, extortion and related offences, down from 9.5% to 7.3%.
    1. For the definition of most serious offence, see 'Methodology' in Prisoners in Australia.                
    2. Offence data for 2009 are based on ASOC 2008, with the exception of data for Qld and WA which are based on ASOC 1997. Data for 2010 are based on ASOC 2008 for all states and territories and data for 2011 onwards are based on the Australian and New Zealand Standard Offence Classification (ANZSOC), 2011 (cat. no. 1234.0). Caution should be exercised in comparing offence data. See 'Methodology' in Prisoners in Australia.

    Democracy, governance and citizenship

    Key findings

    The key findings for Democracy, Governance and Citizenship are:

    1. Only 17.1% of CEO positions in the non-public sector were occupied by women in 2018-19. This proportion has not improved from 2017-18.
    2. The public sector female leadership representation has improved, with women occupying 48.6% of senior leadership roles and outnumbering men in middle management roles (52.2%) for the second consecutive year.
    3. For the first time in Australia’s history, there was equal representation between men and women parliamentarians in the Senate as of 1 January 2020. However, women still comprise only three in ten federal parliamentarians in the House of Representatives.
    4. As of 30 June 2020, 37% of Commonwealth Justices and Judges were women, the highest proportion over the past decade.

    Leadership roles - Non-public sector

    The following data are available in Data Cube 13, Tables 13.1 and 13.2.

    The data discussed in this section refers to non-public sector organisations with 100 or more employees. Under the Workplace Gender Equality Act 2012, non-public sector employers with 100 or more employees must report annually to the Workplace Gender Equality Agency (WGEA) on the gender composition of their workforce.

    Female leadership roles in the non-public sector have increased over the past six years, though a considerable gap remains:

    Proportion of women in senior leadership roles in the non-public sector, 2013-14 to 2018-19
     2013-142018-196 year percentage point difference
     %%%
    Female CEOs15.717.11.4 (a)
    Female Key Management Personnel (KMP)26.131.55.4
    Female Other Executives/General Managers27.832.24.4
    Female Directors (b)23.726.83.1
    Female Chair persons (b)12.014.12.1

    a. The percentage of female CEOs remained the same between 2017-18 and 2018-19.
    b. Chair persons are listed separately, but are also included in the figures for Directors.

     

    In 2018-19, more than 4 in 5 Chief Executive Officer (CEO) roles in the non-public sector were occupied by men (82.9%). While the proportion of female CEOs had increased by 1.4 percentage points between 2013-14 to 2017-18, the rate (17.1%) stayed the same between 2017-18 to 2018-19.

    In 2018-19, the industries with the largest proportions of female CEO’s were:

    • Health care and social assistance (41.4% of CEOs were female)
    • Education and training (35.8% of CEOs were female).

    Between 2013-14 and 2018-19, the industries with the largest increases in the proportion of women in CEO positions were:

    • Arts and Recreation Services (9.1 percentage points increase)
    • Rental, Hiring and Real Estate Services (7.8 percentage points increase).

    Leadership roles - Public sector

    The following data are available in Data Cube 13, Table 13.6.

    Over the decade to 30 June 2020, the proportion of female senior and middle managers in the Australian Public Service has been increasing:

    • 48.6% of Senior Executive Service (SES) managers were women, up from 37.2% in 2010
    • The proportion of women (52.2%) in Executive Level (EL) positions has surpassed men (47.8%) for the second year in a row.

    Parliamentarians

    This section presents information from data provided to the ABS by the Australian Commonwealth Parliamentary Library.

    In January 2019, three in ten federal parliamentarians in the House of Representatives were women and almost two in five federal parliamentarians in the Senate were women. Over the last decade, the proportion of female federal parliamentarians in the House of Representatives has increased slowly. Levels of female representation in the Senate has remained largely unchanged since 2012. However, over the last decade, the average proportion of women has been consistently higher in the Senate (38.2%) than in the House of Representatives (26.8%).

    One in five (20.0%) Federal Government Ministers and over a quarter (26.1% ) of Federal Government Cabinet Ministers were women, as of January 1, 2019.

    Justices and Judges

    The following data are available in Data Cube 13, Table 13.7.

    As of 30 June 2020, 37% of Commonwealth Justices and Judges were women, the highest proportion over the past decade, comprising 61 women and 104 men.

    There are less female than male Justices and Judges in each of the High Court, Federal Court, Family Court, Federal Circuit Court and State Supreme Courts/Courts of Appeal, as of 30 June 2020:

    Justices and Judges, 30 June 2020
     Female Justices/JudgesMale Justices/Judges
     Number%Number%
    High Court Justices 342.9%457.1%
    Federal Court1426.9%3873.1%
    Family Court1847.4%2052.6%
    Federal Circuit Court2638.2%4261.8%
    State Supreme Court / Court of Appeal4927.7%12872.3%

    Data downloads

    Contents table

    1. Economic security - working population

    Data files
    Download xlsx [467.42 KB]

    2. Economic security - earnings, income and economic situation

    Data files
    Download xlsx [260.67 KB]

    3. Economic security - selected tables with expanded populations (tables not updated for 2020)

    Data files
    Download xls [335 KB]

    4. Education - attainment

    Data files
    Download xlsx [245.98 KB]

    5. Education - participation and education & employment

    Data files
    Download xlsx [262.03 KB]

    6. Education - selected tables with expanded populations (tables not updated for 2020)

    Data files
    Download xls [259 KB]

    7. Health - health status

    Data files
    Download xlsx [179.31 KB]

    8. Health - deaths

    Data files
    Download xlsx [158.64 KB]

    9. Health - risk factors and services

    Data files
    Download xlsx [195.93 KB]

    10. Work and family balance

    Data files
    Download xlsx [175.94 KB]

    11. Work and family balance - selected tables with expanded populations (tables not updated for 2020)

    Data files
    Download xls [114 KB]

    12. Safety and justice

    Data files
    Download xlsx [190.76 KB]

    13. Democracy, governance and citizenship

    Data files
    Download xlsx [217.56 KB]

    Gender Indicators 2020, all data cubes

    Data files
    Download zip [2.11 MB]

    Previous catalogue number

    This release previously used catalogue number 4125.0.

    History of changes

    16/12/2020 - No data has been amended.

    1. Added Key statistics section.
    2. Replaced 'then' with 'than' in Safety and justice Key findings #1.
    3. Replaced 'Key finding' with 'Key findings' as a heading in Work and family balance section.

    Methodology

    Gender Indicators, Australia methodology, 2020