Social determinants of health among culturally and linguistically diverse people in Australia

The 2021 Census collected a range of socioeconomic variables, some of which were considered as determinants of long-term health conditions among CALD populations in this project. The specific variables used are described in more detail below:

• Level of highest educational attainment was asked of people aged 15 and over and includes both school and non-school education. This variable provides a single measure of a person’s overall level of highest educational attainment. For analysis, this variable was classified as secondary education or lower (including no education), high school certificate, bachelor's degree or higher. For more information on this Census data item, see Level of highest educational attainment (HEAP). In the regression models that included this variable, the ‘Bachelor's degree or higher’ category was selected as the reference category. 
• Labour force status for people aged 15 and over was recorded and analysed as employed (full time or part time), unemployed or not in labour force for the week prior to the Census. For more information on this Census data item, see Labour force status (LFSP). In the regression models that included this variable, the ‘Employed’ category was selected as the reference category. 
• Occupation describes the primary job or occupation held by employed people in the week prior to Census Night and who are aged 15 and over at the time of the Census. This variable was derived from the corresponding Census data item comprising an 8-level classification (managers, professionals, technicians and trade workers, community and personal service workers, clerical and administrative workers, sales workers, machinery operators and drivers, labourers), which is coded using the Australian and New Zealand Standard Classification of Occupations (ANZSCO), 2013, Version 1.3. The categories of ‘unemployed’ and ‘not in the labour force’ were included to ensure full coverage of the analysis population. For more information on this Census data item, see Occupation (OCCP). In the set of logistic regression models that included this variable, the ‘Managers’ category was selected as the reference category. 
• Income was analysed using equivalised total household income. This variable is household income adjusted by the application of an equivalence scale to facilitate comparison of income levels between households of differing size and composition. This variable reflects that a larger household would normally need more income than a smaller household to achieve the same standard of living. For analysis, this variable was classified into 7 categories:
  • $0-$299 ($0-$15,599 per annum)
  • $300-$499 ($15,600-$25999 per annum)
  • $500-$799 ($26000-$41599 per annum)
  • $800-$1,249 ($41,600-$64,999 per annum)
  • $1,250-$1,749 ($65,000-$90,999 per annum)
  • $1,750-$2,499 ($91,000-$129,999)
  • $2,500 or more ($130,000 or more per annum).

For more information on this Census data item, see Equivalised total household income (HIED). In the regression models that included this variable, the ‘$2,500 or more ($130,000 or more annually)’ category was selected as the reference category. 

Housing circumstances included tenure type and housing suitability. Tenure describes whether a dwelling is owned, being purchased or rented. This variable is derived directly from the corresponding Census data item, which collects the information from people residing in occupied private dwellings. The categories for this variable include owned outright, owned with a mortgage, rented, and other. The ‘Other’ category of the tenure type variable includes ‘rent-free’, ‘life tenure scheme’, ‘shared equity arrangement’ and the ‘other’ category of the tenure type Census data item.

Housing suitability is a measure of housing utilisation based on a comparison of the number of bedrooms in a dwelling with a series of household demographics, such as the number of usual residents, their relationship to each other, age, and sex. For analysis, housing suitability was classified as ‘at least 1 extra bedroom needed’, ‘no extra bedrooms needed or spare’, ‘has at least 1 spare bedroom available’. In the regression models that included the tenure type and/or the housing suitability data items, the ‘no extra bedrooms needed or spare’, and the 'Owner outright' categories were selected as the reference categories, respectively.

For more information on the tenure type Census data item, see Tenure type (TEND) and for information on the housing suitability Census data item, see Housing suitability (HOSD).

The remoteness of people’s places of usual residence was classified using the Australian Statistical Geographical Standard (ASGS) remoteness structure. The derived remoteness variable included the ‘Major cities’, ‘Inner Regional’, ‘Outer Regional’, ‘Remote’ and ‘Very remote’ categories. In the models that included the derived remoteness variable, the ‘Major cities’ category was selected as the reference category. 

Marital status was derived from the ‘social marital status’ variable which records a person’s relationship status based on their current living arrangements as ‘married in a registered marriage’, ‘married in a de facto marriage’ or ‘not married’. Social marital status is based on ‘registered marital status’ and ‘relationship to other person in household’. Persons recorded as ‘not married’ were re-classified in this report as either ‘never married’, ‘separated’, ‘divorced’ or ‘widowed’ using the ‘registered marital status' variable. Some people were classified in a married category in ‘social marital status’ and in an unmarried category on ‘registered marital status’; these were left as married as it is most likely to reflect their current circumstances. Some people were classified as ‘not married’ on the ‘social marital status’ variable and married on registered marital status. These were kept as married as it could not be determined if they were separated, divorced or widowed. For more information on the social marital and the registered marital status Census data items, please visit Social marital status (MDCP) and Registered marital status (MSTP). The scope of both data items includes people aged 15 and over. In the regression models that included this combined marital status variable, the ‘Married in registered marriage’ category was selected as the reference category. 

Australian citizenship indicates whether a person is an Australian citizen after having met several requirements or permanent residency. This is a proxy measure of residency which can impact on a person’s ability to access health services. Different migrant groups may vary in their tendency to seek citizenship. For more information on this Census data item, see Australian citizenship (CITP). In the regression models that included this variable, the ‘Australian citizen’ category was selected as the reference category.

Age is calculated in the Census from date of birth or stated age if date of birth is not provided. Where a respondent does not answer the question, age is imputed using other information on the form and using an age distribution of the population. For more information on this Census data item, see Age (AGEP).

Age group derived using this Census data item to include the ‘15-24’, ‘25-34’, ‘35-44’, ‘45-54’, ‘55-64’, ‘65-74’, and the ’75 and over’ age groups. In the regression models that included this variable, the ‘15-24’ category was selected as the reference category. 

Sex in the 2021 Census is based on a person’s sex characteristics, such as their chromosomes, hormones and reproductive organs (ABS 2022b). While typically based upon the sex characteristics observed and recorded at birth or infancy, a person's sex can change over the course of their lifetime and may differ from their sex recorded at birth (AIHW 2022a). For more information on Sex in the 2021 Census, see the Census Dictionary. The regression analyses were stratified by sex, with data only available for the two categories ‘male’ and ‘female’.