Data Issues Paper

Data Issues Paper

Data Issues Paper – September 2019
Ten to Men logo

Overview

The Data Issues Paper provides a summary of data-related issues that have been identified in the Ten to Men data. It has been designed to assist users of the data as they undertake research and analysis, and should be read in conjunction with the Data User Guide.

This paper provides information to data users on:

  • observed inconsistences and issues that they should be aware of when analysing and interpreting the Ten to Men data
  • recommendations and guidance in the management of identified data quality issues in the Ten to Men data.

The Data Issues Paper has been divided into three sections:

  • a history of the Ten to Men datasets, including the release date and suggested citations
  • changes to the structure of the Ten to Men datasets
  • hierarchical listing of identified data quality issues within each research domain.

Further sections will be added as any data-related issues emerge.

Read the publication

1. Ten to Men data

Periodically a new release of the Ten to Men datasets will be generated as additional information becomes available after each data collection wave. The releases will be numbered in sequential order and a new Digital Object Identifier (DOI) will be minted.
Releases 1.0 and 2.0 were issued by the University of Melbourne. Release 1.0 contains data from Wave 1 only, while Release 2.0 contains data from both Wave 1 and Wave 2.
Release 2.1 was released by the Australian Institute of Family Studies (AIFS) and comprised of updated Wave 1 and Wave 2 datasets. Relevant data from the respondent data have been included in the dataset within the wave, and these are no longer available as a separate dataset.
Table 1: Data releases and recommended citations

DateReleaseDatasetSuggested citation and DOI

July 2016
Release 1.0
Wave 1
Pirkis, J., English, D., & Currier, D. (2016). The Australian Longitudinal Study on Male Health (Ten to Men), 2013. [computer file]. Canberra: Australian Data Archive, The Australian National University. 

  • DOI:10.4225/87/587ebdbc851b1

August 2017
Release 2.0
Respondent Wave 1 Wave 2
Pirkis, J., English, D., & Currier, D. (2017). The Australian Longitudinal Study on Male Health (Ten to Men), 2013. [computer file]. Canberra: Australian Data Archive, The Australian National University. 

  • Respondent DOI: 10.4225/87/N8C9NP
  • Wave 1 DOI: 10.4225/87/Z4PEZN
  • Wave 2 DOI: 10.4225/87/2KHTSV

September 2019
Release 2.1
Wave 1 Wave 2
Bandara, D., Howell, L., & Daraganova, G. (2019). Ten to Men: The Australian Longitudinal Study on Male Health - Data Release 2.1, September 2019. Melbourne: Australian Institute of Family Studies. 

  • DOI: 10.26193/V2IVIG
2. Ten to Men Release 2.1

This section documents the structural changes that have been applied to the Ten to Men datasets. These structural changes will enhance the usability of the datasets, especially as additional waves are included in the future. They include the merging of datasets, resolving data inconsistencies, addressing quality issues and augmenting data resources with additional information.
These structural changes were implemented in Release 2.1 of the Ten to Men datasets and this section documents these changes. Table 2 provides a summary of these changes; further details can be found in the corresponding sections.
Table 2: Summary of changes to the dataset structure in Release 2.1

Change to structureSee section for further details

Addition of a data sharing framework
2.1

Respondent data added to Wave 1 and Wave 2 datasets, removing the need for a separate dataset
2.2

Renaming of variables to indicate wave, thus aligning with the standard naming convention for variables
2.3

Addition of a new research domain for linked data
2.4

Renaming of census linked variables to include reference year
2.5

2.1 Addition of a data sharing framework
To increase the utility of information while minimising disclosure risks with consideration to data sharing principles, a data sharing framework to differentiate the user's access level was proposed for the Ten to Men datasets. This resulted in two levels of datasets for each wave being generated - the General Release and Restricted Release.
A lower level of confidentialisation was applied to the Restricted Release dataset, with all initial information preserved. The only information not included in the dataset are names, addresses and other contact details. Access to the Restricted Release dataset may only be granted when data users are able to demonstrate a genuine need for the additional data and when they also meet the necessary additional security requirements.
The General Release dataset has undergone further data confidentialisation. In addition to the information removed for the Restricted Release dataset, further confidentialisation for the General Release dataset includes suppressing some variables, aggregating some response categories and recoding outlying values to a less extreme value. Users can consult the Ten to Men Data Dictionary for more information on the confidentialised variables.
As access requirements to the General Release dataset are less rigorous than for the Restricted Release dataset, this has improved accessibility to the Ten to Men datasets for users.
For further information about the Ten to Men datasets, including data access procedures, users can refer to sections 3 and 7 of the Ten to Men Data User Guide.
2.2 Availability of respondent dataset
Release 2.0 comprised of three Ten to Men datasets - Respondent, Wave 1 and Wave 2. The Respondent dataset contained key indicator data, such as the unique study identifier, age, household identifier and geographical information. The dataset within each wave contained the responses to the corresponding questionnaires.
In Release 2.1, relevant information from the respondent dataset has been included in the Ten to Men Wave 1 and Wave 2 datasets. This has removed the necessity of maintaining a separate respondent dataset, and thus only two datasets were released - Wave 1 and Wave 2. 
2.3 Renaming of variables to indicate wave
The standard naming convention of the Ten to Men variables specifies that the first character of the variable should indicate the wave, or be a 'z' if the variable is constant across waves.
In Releases 1.0 and 2.0, some variables in the respondent dataset did not follow this standard naming convention. Often the first character of these variables was 'z' yet they were not constant across waves with the variable label specifying whether it related to Wave 1 or Wave 2.
It is important that variables conform to the Ten to Men standard naming convention to maintain consistency and uniformity across the data. Therefore, in Release 2.1, variables were renamed to follow the standard naming convention; that is, the first character of the variable was changed to indicate the wave if the variable was not constant across waves.
Further details of all variables that were renamed are shown in Appendix A.
2.4 Renaming of variables to indicate research domain
The standard naming convention of the variables in the Ten to Men dataset specifies that the second and third characters of the variable should indicate the research domain. The research domain of all variables is also listed in the Data Dictionary.
In Release 2.0, one variable was identified where the second and third characters of the variable did not correspond to a research domain. The detail of this variable is shown below in Table 3.
As it is important to maintain consistency across the data products, this variable has been renamed in Release 2.1 to reflect the correct research domain.
Further details of all variables that were renamed are shown in Appendix A.
Table 3: List of Wave 2 variables that do not following naming convention

Release 2.0 variable nameResearch domain according to the standard naming convention (2nd and 3rd characters)Research domain listed in the Data Dictionary

bhxsex120a
hx
hx is not a research domain
Behaviours - sexual behaviour (bx)

2.5 Additional research domain for linked data
In Releases 1.0 and 2.0, the research domain of Data Collection (DC) comprised of key indicator variables and linked data. This included variables such as the Unique Study ID, Participation Indicators, Household Indicators, Statistical Area codes (SA1, SA2) and numerous Socio-Economic Indexes for Areas (SEIFA).
In Release 2.1, these variables were separated into two research domains to provide transparency about the data source. The key indicator variables remained in the research domain of Data Collection, while an additional research domain was created for Linked Data (LD).
As the standard naming convention of the variables specifies that the second and third characters of the variable name should indicate the research domain, this has resulted in the renaming of some variables to conform to this standard. That is, the second and third characters of the variable name were changed from 'DC' to 'LD'.
Further details of all variables that were renamed are shown in Appendix A.
2.6 Census based data
In Release 2.0, the respondent dataset contained linked data from the Australian Bureau of Statistics (ABS) 2011 Census. These variables did not contain any information to indicate the census year.
As new census data becomes available, it is important to include a census year reference in the variable name. In Release 2.1, the eighth and ninth characters of the variable name were changed to represent a year indicator. For example, the variable 'aldieod00i' has been renamed to 'aldieod11i', to indicate that it is based on the 2011 Census data. Additional data was also available for Wave 2, so this dataset also contains linked data from the ABS 2016 Census.
Further details of all variables that were renamed are shown in Appendix A.

3. Data quality issues

Data quality is measured by factors such as accuracy, validity, consistency and completeness; it is the responsibility of the data user to assess the data quality of the Ten to Men variables before any analysis is undertaken.
Most variables in the Ten to Men datasets have some proportion of missing data, which has been coded using the Ten to Men standard missing value code frame (see the Ten to Men Data User Guide for more information). The proportion and reasons for missing data should be considered before drawing any conclusions from the data.
This section contains a hierarchical listing of data quality issues that have been identified across the waves of Ten to Men. It includes information around the consistency of some variables across waves and the accuracy of various data. Further sections will be added as any additional data quality issues emerge.
Table 4 provides a summary of the identified data quality issues and the wave/s that are affected; further information can be found in the corresponding sections.
Table 4: Summary of data quality issues by wave

Research DomainData Quality IssueWave 1Wave 2See Section for further details

-
Additional Wave 1 participants identified and added to the dataset

 
3.1

-
Data from Parent Questionnaire


3.3

-
Outliers


3.1

-
Pilot data for Wave 2
 

3.11

Various
Variable naming inconsistencies in reference to the Research Domain
 

3.13

Behaviours - alcohol
Age of first drink of alcohol


3.6

Behaviours - tobacco
Age first smoked cigarette


3.7

Behaviours - weight
Height, Weight and Body Mass Index


3.4

Data collection indicator
Sample weights updates


3.12

Social determinants - socioeconomic status
Age of Respondents


3.2

Social determinants - socioeconomic status
Country of Birth

 
3.8

Social determinants - socioeconomic status
Language spoken at home

 
3.9

Social determinants - socioeconomic status
Level of Education completed


3.5

3.1 Outliers
All releases of the Ten to Men datasets contain the raw data, with variables that have not been cleaned for outliers. Data users are advised to take care when using and interpreting the Ten to Men data, as the presence of outliers may necessitate excluding values or categorising the extreme ends.
The exception to this is the categorising of the extreme ends for some variables as part of the confidentialisation process for the General Release datasets. The variables where this top/bottom coding has been applied are indicated in the Ten to Men Data Dictionary.
3.2 Respondents' age
The scope of Ten to Men was males aged 10-55 years (at Wave 1), with three cohorts:

  • males aged 10-14 years completing a Boys questionnaire
  • males aged 15-17 years completing a Young Men questionnaire
  • males aged 18 years and over completing an Adult questionnaire.

However, there were a small number of men invited to participate whose age was outside the scope, or who completed the incorrect questionnaire for their age. The inconsistency arises with less than 0.5% of the population and is likely to have occurred due to difference in time between sending out the hard copy questionnaires and the respondents completing the questionnaires. The survey data for these respondents has been retained in the Ten to Men datasets.
The inconsistencies are present in both Wave 1 and Wave 2 datasets in all Releases of the datasets.
3.3 Parent questionnaire data
For Wave 1 and Wave 2 of Ten to Men, the parents of the males aged 10-14 years also filled in a questionnaire. The parent was not assigned an ID and therefore it cannot be determined if the same parent filled in the questionnaire for both Wave 1 and Wave 2. This is important as some questions were subject to the parent's perception. For example, 'In the past 4 weeks, how often does your child feel happy?'
As a result, data users are advised to take extreme care if comparing responses from the Parent questionnaire across Wave 1 and Wave 2.
3.4 Anthropometric measurements
The Ten to Men questionnaires contain questions about anthropometric measurements. Some of the responses are implausible (e.g. a height of 1 cm).
All releases of the Ten to Men datasets contain the raw data, which has not been cleaned for outliers. The exception to this is the categorising of the extreme ends for some variables as part of the confidentialisation process for the General Release datasets.
Data users are advised to clean and make their own decisions when dealing with anthropometric measurements as they may contain erroneous data values that will affect derived values and interpretations.
3.5 Completeness of education level
In all waves and questionnaires of Ten to Men, there were question/s about the completed level of education. However, each questionnaire had different response categories for Wave 1 and Wave 2. Extreme care needs to be taken when using this education data, especially if comparing values across questionnaires.
Note that if creating groups, the Australian Standard Classification of Education (ASCED) could be used. In this case, Primary education should also include Year 7 for South Australia only. More information on the ASCED and how it is structured can be found on the ABS website.
3.6 Age when first drank alcohol
A data issue with the following question has been identified:

  • How old were you when you first drank more than just a sip or a taste of alcohol?

The question was included on three questionnaires (Boys, Young Men and Adults), and therefore a common variable was created to hold the responses for each wave. For example, the variable 'abaalcagem' contains the responses from the Boys, Young Men and Adult questionnaires for Wave 1.
The data issue arose as a format was applied to the responses to this question on the Boys questionnaire. No format, other than the missing value formats, was applied to the responses to this question on the Young Men and Adults questionnaires. When the data from the Boys questionnaire was merged with the data from the Young Men and Adults questionnaires, no format other than the missing value formats was applied.
As a result, the data from the Boys questionnaire for this question was incorrectly reduced by four years.
This data issue is present in Releases 1.0 and 2.0 of the Ten to Men datasets, but the raw data has been amended in Release 2.1.
Further details
The format applied to the responses to this question on the Boys questionnaire is shown in Table 5. The corresponding question in the Young Men and Adults questionnaires only had the missing value formats applied (codes -8 to -1). For example, if the respondent replied 10 years of age, the data entered was either 6 (Boys) or 10 (Young Men or Adult).
Table 5: Format applied to the Boys cohort

CodeFormat

-8
No questionnaire or interview completed

-7
Unable to determine value

-6
Value implausible

-5
Invalid multiple response

-4
Refused or not answered

-3
Don't know

-2
Not applicable

-1
Not asked

1
5 years old

2
6 years old

3
7 years old

4
8 years old

5
9 years old

6
10 years old

7
11 years old

8
12 years old

9
13 years old

10
14 years old

When the data from the Boys questionnaire was merged with the data from the Young Men and Adults questionnaires, no format other than the missing value formats was applied. The format for the Boys questionnaire was not applied and the formatted age value was replaced with the code. As a result, the age of the first drink of alcohol for the Boys data was reduced by four years (with the maximum age possible being 10).
The data (excluding the missing values) from Release 2.0 of the Ten to Men datasets is shown in Table 6. Responses from both the Boys and Young Men questionnaires are shown for comparison. Each cell in the table is colour coded:

  • black, representing implausible values given the age of the respondent at the time of the survey (e.g. a 10 year old cannot respond that they started drinking at 12 years)
  • grey, representing recorded responses
  • green, representing no recorded responses.

The issue with the data from the Boys questionnaire is clear from the number and distribution of years where there was no recorded response (green cells). This is especially evident when compared to the data from the Young Men questionnaire.
Table 6: Data released in Wave 1 and 2

3.7 Age when first smoked cigarettes
A data issue with the following question has been identified:

  • How old were you when you smoked your first cigarette?

The question was included on three questionnaires (Boys, Young Men and Adults), and therefore a common variable was created to hold the responses for each wave. For example, the variable 'abtcigagem' contains the responses from the Boys, Young Men and Adult questionnaires for Wave 1.
The data issue arose as a format was applied to the responses to this question on the Boys questionnaire. No format, other than the missing value formats, was applied to the responses to this question on the Young Men and Adults questionnaires. When the data from the Boys questionnaire were merged with the data from the Young Men and Adults questionnaires, no format other than the missing value formats was applied.
As a result, the data from the Boys questionnaire for this question were incorrectly reduced by four years.
This data issue is present in Releases 1.0 and 2.0 of the Ten to Men datasets, but the raw data has been amended in Release 2.1.
As it is the same data issue as described above, see section 3.6 for further details.
3.8 Country of birth
In Wave 1 of Ten to Men, each questionnaire contained three questions about the country of birth of the participant and their parents. There were various options for the response, including 'Other', where the respondent could specify any other country using the free text field.
The data were recorded in the three variables:

  • Participant's country of birth (asecobownm)
  • Mother's country of birth (asemocob1m)
  • Father's country of birth (asefacob1m).

These data were then re-coded using the Standard Australian Classification of Countries (SACC) and an additional nine variables at the 1-digit, 2-digit and 4-digit levels were created. These variables contain more detail than the categories provided on the questionnaire, as the 'Other' category has been expanded to include languages specified in the free text field. They are:

  • Participant's country of birth (asecobow1md, asecobow2md, asecobow4md)
  • Mother's country of birth (asemocob1md, asemocob2md, asemocob4md)
  • Father's country of birth (asefacob1md, asefacob2md, asefacob4md).

Although this classification is a three-level hierarchical structure, this has not been strictly applied to the data. Small values at the 2-digit and 4-digit levels have been confidentialised by replacing with 99 or 9999 instead of using the supplementary codes (not further defined (nfd)). Therefore care should be taken when using the variables at the 2-digit and 4-digit levels, as it will give higher 'Other' results than expected. Further details are shown in Table 7.
For data users, it is recommended that the variables at the 2-digit and 4-digit levels are used in conjunction with the 1-digit level variable. The confidentialised variables at the 2-digit and 4-digit levels can then be replaced with the corresponding nfd code.
Table 7: List of Country of Birth Codes

Country of Birth (1-digit code)Country of Birth (2-digit code)Suggested Replacement Country of Birth (2-digit code)Wave 1 Frequency

1
99
10 Oceania and Antarctica nfd
46

2
99
20 North-West Europe nfd
17

3
99
30 Southern and Eastern Europe nfd
26

4
99
40 North Africa and Middle East nfd
45

5
99
50 South-East Asia nfd
0

6
99
60 North-East Asia nfd
29

7
99
70 Southern and Central Asia nfd
28

8
99
80 Americas nfd
10

3.9 Language spoken at home
In Wave 1 of Ten to Men, each questionnaire contained a question about the language spoken at home. However, the response categories varied across the questionnaires.
Adult questionnaire
The Adult questionnaire had seven options for the response to the question about language. One option was 'Other', where the respondent could specify any other language using the free text field. These options are shown in Table 8.
Table 8: List of 'Other' Language Codes for Adult cohort

CodeLanguage

1201
English

2201
Greek

2401
Italian

4202
Arabic

6302
Vietnamese

7104
Mandarin

9999
Other

This data was then re-coded using the Australian Standard Classification of Languages (ASCL) and three variables at the 1-digit, 2-digit and 4-digit levels were created (aselangh1ad, aselangh2ad, aselangh4ad). These variables contain more detail than the categories on the questionnaire, as the 'Other' category has been expanded to include languages specified in the free text field.
Although detailed information on the language can be obtained, the small values at these levels have resulted in the variables being confidentialised (some values have been replaced by 99 or 9999). Care should be taken when using the variables at the 2-digit and 4-digit levels, as it will give higher 'Other' results than expected. Further details are shown in Table 9.
We recommend that the variables at the 2-digit and 4-digit levels be used in conjunction with the 'aselangh1ad' variable. The confidentialised variables at the 2-digit and 4-digit levels can then be replaced with the corresponding nfd code.
Table 9: List of Language Codes for Adult cohort

Language (1-digit level) aselangh1adLanguage (2-digit level) aselangh2adSuggested Replacement Language (2-digit level)Wave 1 Frequency

1
99
10 Northern European Languages, nfd
30

2
99
20 Southern European Languages, nfd
72

3
99
30 Eastern European Languages, nfd
56

4
99
40 Southwest and Central Asian Languages, nfd
57

5
99
50 Southern Asian Languages, nfd
2

6
99
60 Southeast Asian Languages, nfd
30

7
99
70 Eastern Asian Languages, nfd
20

Boys and Young Men questionnaires
The Boys and Young Men questionnaires only had three options for the response to this question about language, as shown in Table 10 and recorded as the variable 'aselangh1u'.
Table 10: List of Language Codes for Boys and Young Men cohorts

CodeLanguage

1
English

2
Another language

3
English and another language about equally

The respondent could specify the other language using the free text field and this was re-coded using the ASCL. Three variables at the 1-digit, 2-digit and 4-digit levels were created (aselangh1ud, aselangh2ud, aselangh4ud). However, the small values at this level has resulted in the variables being totally confidentialised (all values have been replaced by 9, 99 or 9999).
Therefore, no information about the other languages spoken at home is available in the Ten to Men datasets for the Boys and Young Men.
3.10 Additional Wave 1 participants
During Wave 2 of Ten to Men, 33 additional participants were identified for Wave 1. They were not included in the original Wave 1 dataset (Release 1.0) as their eligibility and consent status had not been determined at that stage, but this issue was resolved during Wave 2.
In Release 1.0, the sample size for Wave 1 was 15,988. This was comprised of the three cohorts:

  • 1,087 males aged 10-14 years completing a Boys questionnaire
  • 1,017 males aged 15-17 years completing a Young Men questionnaire
  • 13,884 males aged 18 years and over completing an Adult questionnaire.

In Releases 2.0 and 2.1, the 33 additional participants have been subsequently included in Wave 1, taking the reconciled sample size for Wave 1 to 16,021. The reconciled cohort sizes are:

  • 1,099 males aged 10-14 years completing a Boys questionnaire
  • 1,026 males aged 15-17 years completing a Young Men questionnaire
  • 13,896 males aged 18 years and over completing an Adult questionnaire.

3.11 Pilot data for Wave 2
Of the reconciled Wave 1 sample, there were 314 respondents who were interviewed in the Ten to Men pilot for Wave 2. These respondents did not complete a questionnaire during the course of the main data collection period for Wave 2.
In Releases 1.0 and 2.0, the pilot data have been included in Wave 2 datasets. The sample size was 12,250 males.
In Release 2.1, the data for these 314 respondents have been removed from the Wave 2 dataset. This has reduced the sample size for Wave 2 to 11,936 males. From this Release onwards, these 314 respondents will remain part of the pilot and not be included in the main sample.
3.12 Sample weights updates
Wave 2 weights were not available in Release 2.0 of the Ten to Men datasets. Wave 2 weights were calculated and were included for the first time in Release 2.1.
Upon review of the Ten to Men data, it was decided to update the Wave 1 weights. This was necessary to ensure that the weights for Wave 2 were developed using the same approach and references as those used in the calculation of the Wave 1 weights.
Release 2.1 of the Ten to Men datasets contains the updated sample weights for Wave 1, and the new sample weights for Wave 2.
3.13 Obstructive sleep apnoea
For Wave 2 of Ten to Men, there were four questions asked in the Adult questionnaire relating to obstructive sleep apnoea as part of the STOP-Bang questionnaire screening tool. Further information about this screening tool can be found on the STOP-Bang  website.
Four objective measures are also required as part of the STOP-Bang questionnaire screening tool: BMI, age, neck circumference and gender. The responses to these eight elements are scored, with the result indicating low, medium or high risk of obstructive sleep apnoea.
The resulting score was recorded in the Ten to Men Wave 2 dataset as the derived variable:

  • Risk of OSA (STOP-Bang) (bhsosarisad).

In Release 2.0, this variable had values of 0 or 1, rather than the 0–8 scale or a Low/Medium/High format. In Release 2.1, the intention was to recalculate the derived variable. However, only seven of the eight elements of the STOP-Bang questionnaire screen were available, as we did not have information about the neck circumference. As a result, this derived variable (bhsosarisad) has been removed from the datasets in Release 2.1.
3.14 Derived variables
The Ten to Men dataset contains numerous derived variables, including scale and summary scores. They are calculated for analytical data enrichment. The calculation of these derived variables require input from multiple raw variables, and it is possible that one or more of these input data values may be missing. Missing values are given negative numeric values according to the Ten to Men standard missing value code frame. More information about this code frame can be found in the Ten to Men Data User Guide. 
In Release 1.0 and 2.0, any negative data values were replaced with zero in the calculation of the derived variables. This could introduce misinterpretation of data, depending on the derivation of each variable. For example, the mean of individual components may be underestimated when zero is assigned to a missing value. There were also a couple of scores that were incorrectly calculated. For example, the elements of the General Wellbeing Scale were not reversed scored before calculating the mean. 
Therefore, data users using release 1.0 or 2.0 are advised to re-check and review the interpretation of the derived variables, as the derived variable values may be underestimated or overestimated. 
In Release 2.1, derived variables were re-calculated, and a set of guidelines were developed for the treatment of missing input variables. These are: 

  • If all of the missing input values had the same code frame, the derived variable was assigned the same missing value as per the code frame. For example, if all input variables were -4, the derived variable was assigned to be -4. 
  • If the input variables had any combination of missing values and some valid data values, the derived variable was assigned the missing value code of -7 (Unable to determine value).
Appendix A

The table below shows a list of all variables in the original respondent dataset that have been renamed.
Table 11: Details of variables in respondent dataset that have been renamed

LabelOld Variable NameNew Variable Name
Wave 1Wave 2

SA1 code confidentialised (2011 Census based)
zdcsa1codmd
aldsa1c11md
bldsa1c11md

SA1 code confidentialised (2016 Census based)
n/a
n/a
bldsa1c16md

SA2 code confidentialised (2011 Census based)
zdcsa2codmd
aldsa2c11md
bldsa2c11md

SA2 code confidentialised (2016 Census based)
n/a
n/a
bldsa2c16md

SA Modified Monash Model Classification
zdcmmmcsam
adcmmmcsam
bdcmmmcsam

ASGS Region (2011 Census Based)
zdcremotem
aldremt11m
bldremt11m

ASGS Region (2016 Census Based)
n/a
n/a
bldremt16m

State (2011 Census Based)
zshstate0id
aldstat11id
bldstat11id

State (2016 Census Based)
n/a
aldstat16id
bldstat16id

Number of Household Participants
zdchmparted
adchmparted
n/a

Sampling Weights (2011 Census Based)
zdcwgt001md
adcwgts11md
n/a

Sampling Weights (2016 Census Based)
n/a
n/a
n/a

SEIFA Index of Relative Socio-Economic Disadvantage - Rank (2011 Census Based)
zdcirsdr0i
aldirdr11i
bldirdr11i

SEIFA Index of Relative Socio-Economic Disadvantage - Rank (2016 Census Based)
n/a
n/a
bldirdr16i

SEIFA Index of Relative Socio-Economic Disadvantage - Percent (2011 Census Based)
zdcirsdp0i
aldirdp11i
bldirdp11i

SEIFA Index of Relative Socio-Economic Disadvantage - Percent (2016 Census Based)
n/a
n/a
bldirdp16i

SEIFA Index of Relative Socio-Economic Disadvantage - Decile (2011 Census Based)
zdcirsdd0i
aldirdd11i
bldirdd11i

SEIFA Index of Relative Socio-Economic Disadvantage - Decile (2016 Census Based)
n/a
n/a
bldirdd16i

SEIFA Index of Relative Socio-Economic Advantage and Disadvantage - Rank (2011 Census Based)
zdcirsadri
aldiadr11i
bldiadr11i

SEIFA Index of Relative Socio-Economic Advantage and Disadvantage - Rank (2016 Census Based)
n/a
n/a
bldiadr16i

SEIFA Index of Relative Socio-Economic Advantage and Disadvantage - Percent (2011 Census Based)
zdcirsadpi
aldiadp11i
bldiadp11i

SEIFA Index of Relative Socio-Economic Advantage and Disadvantage - Percent (2016 Census Based)
n/a
n/a
bldiadp16i

SEIFA Index of Relative Socio-Economic Advantage and Disadvantage - Decile (2011 Census Based)
zdcirsaddi
aldiadd11i
bldiadd11i

SEIFA Index of Relative Socio-Economic Advantage and Disadvantage - Decile (2016 Census Based)
n/a
n/a
bldiadd16i

SEIFA Index of Economic Resources - Rank (2011 Census Based)
zdcierr00i
aldierr11i
bldierr11i

SEIFA Index of Economic Resources - Rank (2016 Census Based)
n/a
n/a
bldierr16i

SEIFA Index of Economic Resources - Percent (2011 Census Based)
zdcierp00i
aldierp11i
bldierp11i

SEIFA Index of Economic Resources - Percent (2016 Census Based)
n/a
n/a
bldierp16i

SEIFA Index of Economic Resources - Decile (2011 Census Based)
zdcierr00i
aldierd11i
bldierd11i

SEIFA Index of Economic Resources - Decile (2016 Census Based)
n/a
n/a
bldierd16i

SEIFA Index of Education and Occupation - Rank (2011 Census Based)
zdcieor00i
aldieor11i
bldieor11i

SEIFA Index of Education and Occupation - Rank (2016 Census Based)
n/a
n/a
bldieor16i

SEIFA Index of Education and Occupation - Percent (2011 Census Based)
zdcieop00i
aldieop11i
bldieop11i

SEIFA Index of Education and Occupation - Percent (2016 Census Based)
n/a
n/a
bldieop16i

SEIFA Index of Education and Occupation - Decile (2011 Census Based)
zdcieod00i
aldieod11i
bldieod11i

SEIFA Index of Education and Occupation - Decile (2011 Census Based)
n/a
n/a
bldieod16i

Sex in the past 12 months
bhxsex120a
n/a
bbxsex120a

Glossary

Glossary of terms

TermDescription

General Release
This dataset includes data from which the more sensitive information has been removed. Confidentialisation has also been considered for all variables, and applied if required.

Respondent dataset
A dataset containing key indicator data, such as the unique study identifier, age, household identifier and geographical information.

Restricted Release
This dataset includes information at a more detailed level than the General Release datasets. Items include language, occupation and country of birth at the 4-digit levels.

Update
An update occurs when significant changes are made to an existing release. For example, the update to Release 2.0 resulted in it being reissued as Release 2.1.

Wave dataset
A dataset containing the responses to the corresponding questionnaire of a given wave.

Acknowledgements

Ten to Men: The Australian Longitudinal Study on Male Health was commissioned by the Commonwealth Department of Health. The study was initially conducted by the University of Melbourne who released datasets, including data documentation, for Wave 1 and Wave 2. Roy Morgan Research undertook the data collection and initial data processing for these two waves.

After a competitive tender process in 2017, the Australian Institute of Family Studies (AIFS) was awarded the tender to conduct Wave 3. Since then, the Wave 1 and Wave 2 datasets, including data documentation, have been updated by AIFS.

Publication details

Data Issues Paper
Published by the Australian Institute of Family Studies, September 2019
Suggested citation:

Howell, L., Bandara, D., Mohal, J., Andalón, M., Silbert, M., Garrard, B., Swami, N., & Daraganova G. (2019). Ten to Men: The Australian Longitudinal Study on Male Health - Data Issues Paper, Version 1.0, September 2019. Melbourne: Australian Institute of Family Studies.

Download Publication