Aboriginal and Torres Strait Islander Peoples: Smoking Trends, Australia methodology

Latest release

Reference period

1994 to 2014-15

Released

19/10/2017

Next release Unknown

First release

Explanatory notes

Introduction

1 This publication describes trends in smoking habits among the Aboriginal and Torres Strait Islander population using data from a number of ABS surveys conducted throughout Australia, including remote areas, over the 20 year period from 1994 to 2014–15. Comparisons with trends for the non-Indigenous population during the period 1995 to 2014–15 are included where relevant.

2 The Menzies School of Health Research made a significant contribution to this publication, which is an outcome of a joint ABS and Menzies project to examine trends in smoking by Aboriginal and Torres Strait Islander peoples over a 20 year period by applying regression modelling to a subset of data from 12 health and social surveys by the ABS.

3 Further information on the smoking questions asked in each survey which are relevant to this piece of research is provided in Appendix 1: Smoking Questions by Survey. Appendix 2: Results of Modelling provides detailed information on the results of the modelling for average annual relative and absolute changes in tabular form, including significance levels and confidence intervals.

4 This release includes supporting time series tables which can be accessed via the Data downloads section. For the 2012–13 data in these tables, the 2012–13 NATSIHS has been used to provide consistency across the tables. This is because some of the smoking questions were not asked of every person in the 2012–13 AATSIHS.

5 Throughout this release, the term ‘Aboriginal and Torres Strait Islander’ refers to all persons who identified themselves as being of Aboriginal, Torres Strait Islander, or both Aboriginal and Torres Strait Islander origin.

6 Explanations of terms and concepts are provided in the Glossary.

Modelling estimates of average annual relative and absolute change

7 Regression modelling was used to estimate average annual relative and absolute change during the period 1994 to 2014–15. Further information about the modelling processes that were undertaken is provided in the Technical Note: Modelling Average Annual Change.

Dataset used for regression modelling

8 The dataset used for the regression modelling comprises Aboriginal and/or Torres Strait Islander persons and non-Indigenous persons who were selected to participate in any of the 12 national health and social surveys conducted by the ABS during the period from 1994 to 2014–15 and who were asked questions about smoking (Table 2.1). Predetermined survey reference points were used to measure the approximate length in time in years between 1 July 1994 and the relevant survey, and for determining whether a survey would be included in the analysis of trends before and after 1 January 2008. Surveys designated as occurring within a calendar year (e.g. 2008 NATSISS) were assigned a reference point of 1 July during that year. Surveys designated as occurring within a financial year (e.g. 2007–08 NHS) were assigned a reference point of 31 December during that year.

Table 2.1 ABS national health and social surveys used for regression modelling

Survey	Survey reference point	Sample size (no.) for analysis
Survey	Survey reference point	Smoking prevalence (18 years and over)	Smoking prevalence (15- 17 years)	Quit ratio(a)
ABORIGINAL AND TORRES STRAIT ISLANDER POPULATION
1994 National Aboriginal and Torres Strait Islander Survey	1 Jul 1994	7 700	893	–
2002 National Aboriginal and Torres Strait Islander Social Survey	1 Jul 2002	8 463	826	5 974
2004–05 National Aboriginal and Torres Strait Islander Health Survey	31 Dec 2004	5 756	–	4 188
2008 National Aboriginal and Torres Strait Islander Social Survey	1 Jul 2008	7 163	660	5 166
2012–13 Australian Aboriginal and Torres Strait Islander Health Survey	31 Dec 2012	8 157	757	5 738
2014–15 National Aboriginal and Torres Strait Islander Social Survey	31 Dec 2014	6 604	418	4 725
NON-INDIGENOUS POPULATION
1995 National Health Survey	1 Jul 1995	38 554	–	19 921
2001 National Health Survey	1 Jul 2001	17 693	–	9 192
2004–05 National Health Survey	31 Dec 2004	19 270	–	10 551
2007–08 National Health Survey	31 Dec 2007	15 571	935	8 164
2011–12 Australian Health Survey	31 Dec 2011	24 396	1 421	12 611
2014–15 National Health Survey	31 Dec 2014	14 253	815	7 012

a. 18 years and over who have ever smoked

9 Persons for whom smoking status was unknown were excluded (5,403).

10 Four of the surveys did not ask smoking questions of people aged 15–17 years (1995 NHS, 2001 NHS, 2004–05 NHS, 2004–05 NATSIHS). Non-smokers in the 1994 NATSIS were not asked if they were ex-smokers or had never smoked, and so could not be included in the analyses of the quit ratio. The education variable was not available for the 1995 NHS. Further information about which questions were asked in which survey can be found in Appendix 1: Smoking Questions by Survey.

11 Starting with the 2004–05 NATSIHS and 2004–05 NHS, persons who did not currently smoke and who had never smoked daily were asked additional questions as to whether they had ever smoked 100 cigarettes or more in their life or smoked pipes, cigars or other tobacco products at least 20 times in their life. Those who answered yes to either of these additional questions were classified as ex-smokers. This had the effect of increasing the number of ex-smokers and decreasing those who had ‘never smoked’ relative to the methodology used in the earlier surveys.

12 The non-Indigenous surveys excluded Very Remote areas of Australia and discrete Aboriginal and Torres Strait Islander communities but these exclusions are unlikely to affect national estimates for the non-Indigenous population.

Variables used when estimating average annual relative change

13 The following table indicates which variables were used when estimating average annual relative change in smoking prevalence, smoking initiation and smoking cessation and the reference categories used for comparisons.

Table 2.2 ABS national health and social surveys, variables used for estimating average annual relative change - personal characteristics

Variable	Categories		Model
Variable	Categories		Smoking prevalence	Smoking initiation	Smoking cessation
PERSONAL CHARACTERISTICS
Sex	1	Male	X	X	X
Sex	2	Female (reference)
Age group	2	18–24 years (reference)	X		X
	3	25–34 years
	4	35–44 years
	5	45–54 years
	6	55 years and over
Age	1	15 years (reference)		X
	2	16 years
	3	17 years
Indigenous status	1	Non-Indigenous (reference)	X	X	X
Indigenous status	2	Aboriginal and/or Torres Strait Islander
Highest year of school completed	1	Year 12 or equivalent (reference)	X		X
	2	Year 11 or below or never attended school
	3	Not stated or not applicable(a)
Smoker status	1	Smoker	X	X
Smoker status	2	Non-smoker (reference)
Quit status – persons who have ever smoked	1	Ex-smoker			X
Quit status – persons who have ever smoked	0	Smoker (reference)
GEOGRAPHICAL CHARACTERISTICS
Jurisdiction	NSW	New South Wales (reference)	X	X	X
	VIC	Victoria
	QLD	Queensland
	SA	South Australia
	WA	Western Australia
	TAS	Tasmania
	NT	Northern Territory
	ACT	Australian Capital Territory
Remoteness	1	Non-remote (reference)	X	X	X
Remoteness	2	Remote
TIMES
Number of years between survey reference point and 1 July 1994	Continuous variable taking values in the range of 0 to 20.5 years (0–1994 NATSIS) (reference)		X	X	X
Survey reference point after 1 January 2008	1	After	X	X	X
Survey reference point after 1 January 2008	2	Before (reference)

a. Education variable that was not available in 1995 NHS was categorised as ‘not known’.

Variables used when estimating average annual absolute change

14 The following table indicates which variables were used when estimating average annual absolute change in smoking prevalence, smoking initiation and smoking cessation and the reference categories used for comparisons.

Table 2.3 ABS national health and social surveys, variables used for estimating average annual absolute change

Variable	Categories		Model
Variable	Categories		Smoking prevalence	Smoking initiation	Smoking cessation
Sex	0	Female (reference)	X	X	X
Sex	1	Male
Age group	2	18–24 years (reference)	X		X
	3	25–44 years
	4	45 years and over
Age	1	15 years (reference)		X
	2	16 years
	3	17 years
Indigenous status	1	Non-Indigenous (reference)	X	X	X
	2	Aboriginal and/or Torres Strait Islander
	2	Aboriginal and/or Torres Strait Islander
Smoking prevalence – 18 years and over	Continuous variable		X
Smoking prevalence – 15–17 years	Continuous variable			X
Quit ratio	Continuous variable				X
Remoteness	1	Non-remote (reference)	X	X	X
Remoteness	2	Remote
Number of years between survey reference point and 1 July 1994	Continuous variable taking values in the range of 0 to 20.5 years (0–1994 NATSIS) (reference)		X	X	X
Survey reference point after 1 January 2008	1	After	X	X	X
Survey reference point after 1 January 2008	2	Before (reference)

Acknowledgment

15 The data used in this publication was dependent on the high level of cooperation received from Aboriginal and Torres Strait Islander peoples and their communities. Without their continued cooperation, the wide range of Aboriginal and Torres Strait Islander statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.

Appendix 1 - smoking questions by survey

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Table 3.1 Smoking questions by survey(a), Aboriginal and Torres Strait Islander population

1994 NATSIS (13 years and over)	2002 NATSISS (15 years and over)	2004–05 NATSIHS (18 years and over)	2008 NATSISS (15 years and over)	2012–13 AATSIHS (15 years and over)	2014–15 NATSISS (15 years and over)
Do you smoke cigarettes? (include packet and roll-your-own)	Non-remote: Do you currently smoke? Remote: Do you smoke?	Do you currently smoke?	Do you currently smoke?	Do you/Does (name) currently smoke?	Do you currently smoke?
	Non-remote: Do you smoke regularly, that is, one smoke a day or more? Remote: Do you have one smoke a day or more?	Non-remote: Do you smoke regularly, that is, at least once a day? Remote: Do you have at least one smoke a day?	Do you smoke regularly, that is, at least once a day?	Non-remote: Do you/Does (name) smoke regularly, that is, at least once a day? Remote: Do you/Does (name) have at least one smoke a day?	Do you smoke regularly, that is, at least once a day?
	Have you ever smoked regularly, (that is, one smoke a day or more)?	Do you smoke at least once a week?	Do you smoke at least once a week?	Do you/Does (name) smoke at least once a week?	Do you smoke at least once a week?
		Have you ever smoked regularly, (that is at least once a day)?	Have you ever smoked regularly, (that is at least once a day)?	Non-remote: Have you/Has (name) ever smoked regularly, that is, at least once a day? Remote: Have you/Has (name) ever had at least one smoke a day?	Have you ever smoked regularly, (that is at least once a day)?
		Have you smoked at least 100 cigarettes in your entire life?	Have you smoked at least 100 cigarettes in your entire life?	Have you/Has (name) smoked at least 100 cigarettes in your/his/her entire life?	Have you smoked at least 100 cigarettes in your entire life?
		Have you ever smoked pipes, cigars or other tobacco products at least 20 times in your entire life?	Have you ever smoked pipes, cigars or other tobacco products at least 20 times in your entire life?	Have you/Has (name) ever: Chewed tobacco Smoked pipes Smoked cigars Smoked other tobacco products (specify)	Have you ever smoked pipes, cigars or other tobacco products at least 20 times in your entire life?
				Do you/Does (name) (1st, 2nd,…4th category selected) daily?
				Have you/Has (name) ever (1st, 2nd,…4th category selected) 20 times in your/his/her entire life?
		How old were you when you first started to smoke regularly (that is at least once a day)?		How old were you/was (name) when you/he/she first started to smoke regularly (that is, at least once a day)?
			Have you tried to quit or reduce the amount you smoke in the last 12 months/year?	Non-remote: In the last 12 months did you/(name) attempt to quit smoking?	Have you tried to quit or reduce the amount you smoke in the last 12 months/year?
				Remote: In the last year, have you/has (name) tried to stop smoking?

a. All surveys conducted by personal interview. Only those questions relevant to this research are listed.

Table 3.2 Smoking questions by survey(a), non-Indigenous population

1995 NHS (18 years and over)	2001 NHS (18 years and over)	2004–05 NHS (18 years and over)	2007–08 NHS (15 years and over)	2011–12 AHS (15 years and over)	2014–15 NHS (15 years and over)
Do you currently smoke?	Do you currently smoke?	Do you currently smoke?	Do you/does (proxy name) currently smoke?	Do you/does (proxy name) currently smoke?	Do you/does (proxy name) currently smoke?
Do you smoke regularly, that is, at least once a day?	Do you smoke regularly, that is, at least once a day?	Do you smoke regularly, that is, at least once a day?	Do you/does (proxy name) smoke regularly, that is, at least once a day?	Do you/does (proxy name) smoke regularly, that is, at least once a day?	Do you/does (proxy name) smoke regularly, that is, at least once a day?
Have you ever smoked regularly, that is, at least once a day?	Have you ever smoked regularly, that is, at least once a day?	Do you smoke at least once a week?	Do you/does (proxy name) smoke at least once a week?	Do you/does (proxy name) smoke at least once a week?	Do you/does (proxy name) smoke at least once a week?
		Have you ever smoked regularly (that is at least once a day)?	Have you/has (proxy name) ever smoked regularly, that is, at least once a day?	Have you/has (proxy name) ever smoked regularly, that is, at least once a day?	Have you/has (proxy name) ever smoked regularly, that is, at least once a day?
		Have you smoked at least 100 cigarettes in your entire life?	Have you/has (proxy name) smoked at least 100 cigarettes in your entire life?	Have you/has (proxy name) smoked at least 100 cigarettes in your entire life?	Have you/has (proxy name) smoked at least 100 cigarettes in your entire life?
		Have you smoked pipes, cigars or other tobacco products at least 20 times in your entire life?	Have you/has (proxy name) ever smoked pipes, cigars or other tobacco products at least 20 times in [your/his/her] entire life?	Have you/has (proxy name) ever smoked pipes, cigars or other tobacco products at least 20 times in [your/his/her] entire life?	Have you/has (proxy name) ever smoked pipes, cigars or other tobacco products at least 20 times in [your/his/her] entire life?
		How old were you when you first started to smoke regularly (that is, at least once a day)?	How old were you/was (name) when you/he/she first started to smoke regularly (that is, at least once a day)?	How old were you/was (proxy name) when you/he/she first started to smoke regularly (that is, at least once a day)?	How old were you/was (first name) when you/he/she first started to smoke regularly (that is, at least once a day)?

a. Only those questions relevant to this research are listed.

Appendix 2 - results of modelling

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These tables provide the results of the modelling for average annual relative and absolute changes. Note that significance levels are given only for main effects and interactions that are in the interest of this research. For the purposes of this research, a significance level of p=0.05 or less indicates that an interaction is statistically significant. An average annual relative or absolute change is statistically significant if it falls between the upper and lower limits of the confidence interval specified.

Table 4.1 Relative changes, smoking prevalence

Indicator	Population used in modelling	Surveys included in the analysis	Significance level	Sub-groups of interest	Average annual relative change (%)	Confidence interval
Annual proportion change, controlling for age and sex	18 years and over	All (12)	Interaction of Indigenous status with time: p=0.07	Non-Indigenous	–2.5	[–2.8; –2.2]
Annual proportion change, controlling for age and sex	18 years and over	All (12)	Interaction of Indigenous status with time: p=0.07	Aboriginal and Torres Strait Islander	–1.9	[–2.5; –1.4]
Annual proportion change, controlling for age, sex, remoteness, state/territory, education	18 years and over	All (12)	Interaction of Indigenous status with time: p<0.01	Non-Indigenous	–2.7	[–3.2; –2.3]
	18 years and over	All (12)	Interaction of Indigenous status with time: p<0.01	Aboriginal and Torres Strait Islander	–1.0	[–1.6; –0.4]
Annual proportion change, controlling for sex	Aboriginal and Torres Strait Islander population, 18 years and over	Only Aboriginal and Torres Strait Islander surveys (6)	Interaction of age group with time: p<0.01	18–24 years	–3.1	[–4.3; –1.9]
				25–34 years	–2.2	[–2.9; –1.5]
				35–44 years	–1.9	[–3.1; –0.7]
				45–54 years	–0.4	[–1.6; 0.1]
				55 years and over	–0.5	[–2.0; 1.0]
Annual proportion change, controlling for age, sex, state/territory	Aboriginal and Torres Strait Islander population, 18 years and over	Only Aboriginal and Torres Strait Islander surveys (6)	Interaction of education with time: p<0.01, remoteness with time: p<0.01	School education level (Year 12 or equivalent), non-remote	–3.3	[–4.6; –2.0]
				School education level (Year 11 or below or never attended school), non-remote	–1.3	[–2.1; –0.5]
				School education level (Year 12 or equivalent), remote	–0.8	[–2.3; 0.7]
				School education level (Year 11 or below or never attended school), remote	1.2	[0.4; 2.1]
Annual proportion change, controlling for age, sex, remoteness, state/territory, education	Aboriginal and Torres Strait Islander population, 18 years and over	Aboriginal and Torres Strait Islander surveys (6)	Interaction of intervention variable with time: p=0.01	Before 2008	0.7	[–0.6; 1.9]
		Aboriginal and Torres Strait Islander surveys (6)	Interaction of intervention variable with time: p=0.01	2008 and after	–2.1	[–3.9; –0.3]
Annual proportion change, controlling for age, sex, remoteness, state/territory, education	Non-Indigenous population, 18 years and over	National/Australian Health Surveys (6)	Interaction of intervention variable with time: p=0.28	Before 2008	–1.3	[–2.4; –0.3]
	Non-Indigenous population, 18 years and over	National/Australian Health Surveys (6)	Interaction of intervention variable with time: p=0.28	2008 and after	–2.8	[–5.3; –0.3]

Table 4.2 Relative changes, smoking initiation

Indicator	Population used in modelling	Surveys included in the analysis	Significance level	Sub-groups of interest	Average annual relative change (%)	Confidence interval
Annual proportion change, controlling for age and sex	15–17 years	5 surveys (1994, 2002, 2008, 2012–13, 2014–15)	Not applicable	Aboriginal and Torres Strait Islander	–4.3	[–5.9; –2.6]
Annual proportion change, controlling for age, sex, remoteness, state/territory	15–17 years	5 surveys (1994, 2002, 2008, 2012–13, 2014–15)	Not applicable	Aboriginal and Torres Strait Islander	–4.1	[–5.7; –2.5]
Annual proportion change, controlling for age, sex, remoteness, state/territory	Aboriginal and Torres Strait Islander population, 15–17 years	Aboriginal and Torres Strait Islander surveys (6)	Interaction of intervention variable with time: p=0.09	Before 2008 2008 and after	1.8 –5.1	[–2.5; 6.4] [–11.4; 1.6]

Table 4.3 Relative changes, smoking cessation

Indicator	Population used in modelling	Surveys included in the analysis	Significance level	Sub-groups of interest	Average annual relative change (%)	Confidence interval
Annual proportion change, controlling for age and sex	18 years and over	All except 1994 (11)	Interaction of Indigenous status with time: p=0.07	Non-Indigenous	2.6	[2.2; 2.9]
Annual proportion change, controlling for age and sex	18 years and over	All except 1994 (11)	Interaction of Indigenous status with time: p=0.07	Aboriginal and Torres Strait Islander	3.7	[2.5; 4.8]
Annual proportion change, controlling for age, sex, remoteness, state/territory, education	18 years and over	All except 1994 (11)	Interaction of Indigenous status with time: p=0.94	Non-Indigenous	3.3	[2.7; 3.9]
				Aboriginal and Torres Strait Islander	3.2	[2.1; 4.4]
Annual proportion change, controlling for age, sex, state/territory, education	Aboriginal and Torres Strait Islander population, 18 years and over	Aboriginal and Torres Strait Islander surveys, except 1994 (5)	Interaction of remoteness with time: p<0.01	Non-remote	3.6	[2.5; 4.8]
			Interaction of remoteness with time: p<0.01	Remote	0.7	[–0.2; 2.6]
Annual proportion change, controlling for age, sex, remoteness, state/territory, education	Aboriginal and Torres Strait Islander population, 18 years and over	Aboriginal and Torres Strait Islander surveys, except 1994 (5)	Interaction of intervention variable with time: p<0.11	Before 2008	8.3	[1.5; 15.5]
			Interaction of intervention variable with time: p<0.11	2008 and after	2.4	[0.2; 4.7]
Annual proportion change, controlling for age, sex, remoteness, state/territory, education	Non-Indigenous population, 18 years and over	National/Australian Health Surveys (6)	Interaction of intervention variable with time: p=0.76	Before 2008	2.9	[1.6; 4.2]
	Non-Indigenous population, 18 years and over	National/Australian Health Surveys (6)	Interaction of intervention variable with time: p=0.76	2008 and after	2.4	[–0.5; 5.4]

Table 4.4 Absolute changes, smoking prevalence

Indicator	Population used in modelling	Surveys included in the analysis	Significance level	Sub-groups of interest	Average annual absolute change (percentage point)	Confidence interval
Annual percentage point change, controlling for age, sex and remoteness	18 years and over	All (12)	Interaction of Indigenous status with time: p=0.87	Non-Indigenous	–0.3	[–0.4; –0.2]
	18 years and over	All (12)	Interaction of Indigenous status with time: p=0.87	Aboriginal and Torres Strait Islander	–0.3	[–0.5; –0.1]
Annual percentage point change, controlling for age and sex	Aboriginal and Torres Strait Islander population, 18 years and over	Aboriginal and Torres Strait Islander surveys (6)	Interaction of remoteness with time: p<0.01	Remote	0.0	[–0.2; 0.3]
Annual percentage point change, controlling for age and sex		Aboriginal and Torres Strait Islander surveys (6)	Interaction of remoteness with time: p<0.01	Non-remote	– 0.6	[–0.8; –0.3]
Annual percentage point change, controlling for age, sex and remoteness	Aboriginal and Torres Strait Islander population, 18 years and over	Aboriginal and Torres Strait Islander surveys (6)	Interaction of intervention variable with time: p=0.33	Before 2008	0.0	[–0.5; 0.4]
		Aboriginal and Torres Strait Islander surveys (6)	Interaction of intervention variable with time: p=0.33	2008 and after	–0.4	[–1.1; 0.2]
Annual percentage point change, controlling for age, sex and remoteness	Non-Indigenous population, 18 years and over	National/Australian Health Surveys (6)	Interaction of intervention variable with time: p=0.91	Before 2008	–0.2	[–0.3; –0.1]
	Non-Indigenous population, 18 years and over	National/Australian Health Surveys (6)	Interaction of intervention variable with time: p=0.91	2008 and after	–0.2	[–0.8; 0.4]

Table 4.5 Absolute changes, smoking initiation

Indicator	Population used in modelling	Surveys included in the analysis	Significance level	Sub-groups of interest	Average annual absolute change (percentage point)	Confidence interval
Annual percentage point change, controlling for age, sex and remoteness	15-17 years	5 surveys (1994, 2002, 2008, 2012-13, 2014-15)	Not applicable	Aboriginal and Torres Strait Islander	–0.9	[–1.2; –0.6]
Annual percentage point change, controlling for sex and remoteness	Aboriginal and Torres Strait Islander population, 15-17 years	Aboriginal and Torres Strait Islander surveys (6)	Interaction of age with time: p<0.01	15 years old	–0.4	[–0.8; 0.1]
				16 years old	–0.7	[–1.2; –0.2]
				17 years old	–1.7	[– 2.2; –1.2]
Annual percentage point change, controlling for age, sex and remoteness	Aboriginal and Torres Strait Islander population, 15-17 years	Aboriginal and Torres Strait Islander surveys (6)	Interaction of intervention variable with time: p=0.02	Before 2008	0.0	[–0.9; 1.0]
		Aboriginal and Torres Strait Islander surveys (6)	Interaction of intervention variable with time: p=0.02	2008 and after	–1.9	[–3.0; –0.7]

Table 4.6 Absolute changes, smoking cessation

Indicator	Population used in modelling	Surveys included in the analysis	Significance level	Sub-groups of interest	Average annual absolute change (percentage point)	Confidence interval
Annual percentage point change, controlling for age, sex and remoteness	18 years and over	All except 1994 (11)	Interaction of Indigenous status with time: p=0.51	Non-Indigenous	0.6	[0.5; 0.8]
	18 years and over	All except 1994 (11)	Interaction of Indigenous status with time: p=0.51	Aboriginal and Torres Strait Islander	0.5	[0.2; 0.8]
Annual percentage point change, controlling for age and sex	Aboriginal and Torres Strait Islander population, 18 years and over	Aboriginal and Torres Strait Islander surveys, except 1994 (5)	Interaction of remoteness with time: p<0.01	Non-remote	0.9	[0.6; 1.1]
Annual percentage point change, controlling for age and sex			Interaction of remoteness with time: p<0.01	Remote	0.2	[–0.1; 0.4]
Annual percentage point change, controlling for age, sex and remoteness	Aboriginal and Torres Strait Islander population, 18 years and over	Aboriginal and Torres Strait Islander surveys, except 1994 (5)	Interaction of intervention variable with time: p=0.16	Before 2008	1.2	[0.1; 2.4]
			Interaction of intervention variable with time: p=0.16	2008 and after	0.3	[–0.2; 0.8]
Annual percentage point change, controlling for age, sex and remoteness	Non-Indigenous population, 18 years and over	National/Australian Health Surveys (6)	Interaction of intervention variable with time: p=0.35	Before 2008	0.2	[0.0; 0.5]
	Non-Indigenous population, 18 years and over	National/Australian Health Surveys (6)	Interaction of intervention variable with time: p=0.35	2008 and after	0.8	[–0.4; 2.0]

Technical note - modelling average annual change

Introduction

1 Regression modelling was used to produce estimates of average annual relative and absolute change. This Technical Note provides further information about the modelling processes that were undertaken. Information about the dataset and variables used in the modelling is provided in the Explanatory Notes.

Modelling average annual relative change

2 Logistic regression is widely used in many fields, including the medical and social sciences, as a statistical method for modelling categorical outcomes. Binary logistic regression is used for modelling a dichotomous outcome (for example, modelling 1 and 0, where 1 = event/outcome of interest occurs and 0 = event/outcome of interest does not occur). In this publication, this method is used to estimate average annual relative change, as people are either smokers or not, or have successfully quit or not. The output of the logistic regression model is usually presented in terms of the odds that the event will occur. For each categorical characteristic in the model a comparison group is selected.

3 The binary logistic model for estimating the likelihood of an event can be expressed as follows:

\(\Large{log \left(\frac{p_{event}}{p_{non \ event}}\right)=\alpha+\beta_{1} x_{1}+\cdots+\beta_{k} x_{k}}\)

where \(\alpha\) is the intercept, the \(\beta_{1}, \ldots, \beta_{k}\) are \(k\) regression coefficients, and the \(x_{1}, \ldots, x_{k}\) are a set of \(k\) explanatory variables for each individual in the data.

4 This model indicates that the log of the odds of an event occurring is a linear function of the explanatory variables. The coefficients of the model can be estimated using standard maximum likelihood techniques.

5 To take into account the sample design of the surveys, sampling weights were applied in the models. To adjust for possible dependence of units within clusters due to clustering sample design, clustering was also implemented into the modelling process.

6 The time variable is the primary explanatory variable of interest in all models as it describes the annual relative trend in the outcome variable (smoking prevalence for people aged 18 years and over, smoking initiation among people aged 15-17 years, or the quit ratio for people aged 18 years and over).

7 The logic of the modelling approach is as follows.

Firstly, models were built for each outcome variable with time, age (or age group), sex and Indigenous status and an interaction term was added between Indigenous status and time. The interaction was then tested to see whether it was significant or not. If the interaction is significant then it can be concluded that there is a significantly different relative trend for the Aboriginal and Torres Strait Islander population and the non-Indigenous population. More covariates were then added into the model to understand whether controlling for remoteness, state/territory and/or education changed the interaction.
The next step was to model outcomes separately for the Aboriginal and Torres Strait Islander and non-Indigenous populations. Sex and age were tested as covariates in the model, including whether there were significant interactions between these covariates and the time variable. A significant interaction means significantly different relative trends for the different categories of the covariate. If any interactions were not significant then these were removed sequentially until all remaining interactions were significant (p<0.05), removing the least significant first. More covariates were then added and their interactions with time assessed to determine whether there were also significantly different trends by remoteness, state/territory or education.
Finally, an assessment was undertaken to determine whether relative trends were different before and after the increased attention to and funding for tobacco control programs targeted to the Aboriginal and Torres Strait Islander population since 2008. This involved creating a new variable with a value of 0 for before 1 January 2008 and a value of 1 for after 1 January 2008. The interaction of this variable with time was added to the models for the Aboriginal and Torres Strait Islander and non-Indigenous populations, along with the other covariates. If the interaction between this new variable with time is significant, this indicates that after 2008 the relative trend was different from what it was before 2008. Note that these models do not include any of the other significant interactions with time that were detected in the initial subgroup analysis

8 It should be noted that the power to detect a significant interaction for this research is low, especially for the smoking initiation analysis. This is due to the smaller number of surveys before and after 2008. This implies that if a significant effect was not detected, a true effect may still exist; however, it also means that there is a high level of confidence in the significant effects found.

Modelling average annual absolute change

9 Linear regression is the most widely used of all statistical techniques. It is typically used for modelling linear, additive relationships between a scalar dependent variable and one or more explanatory variables that can be either numerical or categorical. For each categorical characteristic in the model a comparison group is selected. In this publication, this method is used to estimate average annual absolute change, assuming the percentage point gap between two estimates is a linear relationship.

10 The linear regression model can be expressed as follows:

\(\Large{y=\alpha+\beta_{1} x_{1}+\dots+\beta_{k} x_{k}+\varepsilon}\)

where \(\alpha\) is the intercept, the \(\beta_{1}, \ldots, \beta_{k}\) are \(k\) regression coefficients, and the \(x_{1}, \dots, x_{k}\) are a set of \(k\) explanatory variables. The coefficients of the model can be estimated using standard least squares or maximum likelihood techniques.

11 The average absolute (percentage point) changes were analysed at the aggregated level rather than at the individual level.

12 Estimates of smoking prevalence, initiation and quitting were calculated for age-sex-remoteness groups in each survey. To take into account the sample design of the surveys, sampling weights were applied to individual data.

13 Regression models were then built for each outcome variable with time, age (or age group), sex, remoteness and Indigenous status and an interaction term between Indigenous status and time was added. The interaction was then tested to see whether it was significant or not. If the interaction is significant then it can be concluded that there is a significantly different absolute trend for the Aboriginal and Torres Strait Islander and the non-Indigenous populations. To take into account the different levels of uncertainty of estimates due to sampling error, all regression models used the weighted least squares method with the inverse of the estimate variance as the weight. The estimated variances were calculated from the individual data using the Jackknife method.

14 The next step was modelling of outcomes separately for the Aboriginal and Torres Strait Islander and non-Indigenous populations. Age, sex and remoteness were tested as covariates in the model and significant interactions between these covariates and the time variable were checked. A significant interaction means that there are significantly different trends for the different categories of the covariate. If any interactions were not significant then these were removed sequentially until all remaining interactions were significant (p<0.05), removing the least significant first.

15 Finally, an assessment was undertaken to determine whether absolute trends were different before and after the increased attention to and funding for tobacco control programs targeted to the Aboriginal and Torres Strait Islander population since 2008. This involved creating a new variable with a value of 0 for before 1 January 2008 and a value of 1 for after 1 January 2008. The interaction of this variable with time was added to the models for the Aboriginal and Torres Strait Islander and non-Indigenous populations along with the other covariates. If the interaction between this new variable with time is significant, this indicates that after 2008 the relative trend was different from what it was before 2008. Note that these models do not include any of the other significant interactions with time that were detected in the initial subgroup analysis

16 It should be noted that the power to detect a significant effect for this research is lower than for modelling relative declines due to the model’s use of aggregated data rather than individual data. This implies that if a significant effect was not detected, a true effect may still exist; however, it also means that there is a high level of confidence in the significant effects found.

Glossary

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Aboriginal and Torres Strait Islander peoples

People who identified themselves, or were identified by another household member, as being of Aboriginal origin, Torres Strait Islander origin, or both.

Average annual absolute change

Describes an average annual change between two proportions as a percentage point difference. For example, a decline in smoking prevalence from 50% to 25% would be an absolute change of 25 percentage points.

Average annual relative change

Describes an average annual percentage change between two proportions. For example, a decline in smoking prevalence from 50% to 25% would be a relative change of 50%.

Covariates

Characteristics which influence people’s smoking habits, such as their age and sex.

Jackknife method

A method used to estimate variance through a process called replicate weighting. A small group of households in the sample is assigned a zero weight and then the remaining records are re-weighted to the survey benchmark population. This process is repeated a number of times to produce a set of replicate weights for each record. These replicate weights are used for calculating the variances of the estimates by finding the difference between the estimate for each replicate group and the original estimate. This difference is then used in calculating the standard error of the estimate.

Non-remote

Geographical areas within the 'Major cities of Australia', 'Inner regional Australia' and 'Outer regional Australia' categories of the Australian Statistical Geography Standard (ASGS).

Quit ratio

The number of people who have successfully quit smoking as a proportion of the number of people who have ever smoked (including current smokers)

Regression modelling

Logistic regression is used as a statistical method for modelling categorical outcomes. Further information on the regression models used for this publication can be found in the Explanatory Notes.

Remote

Geographical areas within the 'Remote Australia' and 'Very remote Australia' categories of the Australian Statistical Geography Standard (ASGS) Remoteness Structure.

Smoker status

Information was collected from persons aged 15 years and over or 18 years and over (depending on the survey) on their smoking habits and the extent to which they were smoking at the time of the interview. Smoking refers to the regular smoking of tobacco products, including manufactured (packet) cigarettes, roll-your-own cigarettes, cigars and pipes, but excluding chewing tobacco and the smoking of non-tobacco products (for example, marijuana). Based on this information, people were characterised as:

current smoker – they currently smoke daily, weekly or other regular pattern (but less than weekly),
ex-smoker – they previously smoked daily or had smoked 100 or more cigarettes in their lifetime or had smoked pipes, cigars or other tobacco products at least 20 times in their lifetime, or
never smoked – they had never smoked daily and had smoked less than 100 cigarettes in their lifetime and had smoked pipes, cigars or other tobacco products less than 20 times in their lifetime.

Smoking initiation

In this publication, smoking prevalence for people aged 15–17 years is used as an indicator of trends in smoking initiation.

Smoking prevalence

Current smokers as a proportion of the relevant total population.

Statistical significance

Differences between population estimates are said to be statistically significant when it can be stated with 95% confidence that there is a real difference between the populations.

Survey reference point

A predetermined date assigned to each survey for the purpose of measuring the approximate length of time (in years) between 1 January 1994 and the relevant survey.

Year 12 or equivalent

In this publication, ‘Year 12 or equivalent’ refers to people who reported their highest year of school completed was Year 12 or an equivalent school qualification.

AATSIHS	Australian Aboriginal and Torres Strait Islander Health Survey
ABS	Australian Bureau of Statistics
AHS	Australian Health Survey
ASGS	Australian Statistical Geography Standard
NATSIHS	National Aboriginal and Torres Strait Islander Health Survey
NATSIS	National Aboriginal and Torres Strait Islander Survey
NATSISS	National Aboriginal and Torres Strait Islander Social Survey
NHS	National Health Survey
no.	number
p	probability
RSE	relative standard error

APA

Aboriginal and Torres Strait Islander Peoples: Smoking Trends, Australia methodology

APA

Explanatory notes

Introduction

Modelling estimates of average annual relative and absolute change

Dataset used for regression modelling

Table 2.1 ABS national health and social surveys used for regression modelling

Variables used when estimating average annual relative change

Table 2.2 ABS national health and social surveys, variables used for estimating average annual relative change - personal characteristics

Variables used when estimating average annual absolute change

Table 2.3 ABS national health and social surveys, variables used for estimating average annual absolute change

Acknowledgment

Appendix 1 - smoking questions by survey

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Table 3.1 Smoking questions by survey(a), Aboriginal and Torres Strait Islander population

Table 3.2 Smoking questions by survey(a), non-Indigenous population

Appendix 2 - results of modelling

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Table 4.1 Relative changes, smoking prevalence

Table 4.2 Relative changes, smoking initiation

Table 4.3 Relative changes, smoking cessation

Table 4.4 Absolute changes, smoking prevalence

Table 4.5 Absolute changes, smoking initiation

Table 4.6 Absolute changes, smoking cessation

Technical note - modelling average annual change

Introduction

Modelling average annual relative change

Modelling average annual absolute change

Glossary

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​​​​​​​Aboriginal and Torres Strait Islander peoples

Average annual absolute change

Average annual relative change

Covariates

Jackknife method

Non-remote

Quit ratio

Regression modelling

Remote

​​​​​​​Smoker status

​​​​​​​Smoking initiation

​​​​​​​Smoking prevalence

Statistical significance

Survey reference point

Year 12 or equivalent

Quality declaration

​​​​​​​Institutional environment

Relevance

Timeliness

Accuracy

Coherence

Interpretability

Accessibility

Abbreviations

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Aboriginal and Torres Strait Islander peoples

Smoker status

Smoking initiation

Smoking prevalence

Institutional environment