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PLOS One logoLink to PLOS One
. 2024 Sep 19;19(9):e0307386. doi: 10.1371/journal.pone.0307386

Trends in smoking initiation and cessation over a century in two Australian cohorts

Alan L James 1,2,#, Gulser Caliskan 3,#, Giancarlo Pesce 4, Simone Accordini 3, Michael J Abramson 5, Dinh Bui 6, Arthur W Musk 7,8, Matthew W Knuiman 8, Jennifer L Perret 9,10, Deborah Jarvis 11, Cosetta Minelli 11, Lucia Calciano 3, Jennie Hui 12,13, Michael Hunter 8,13, Paul S Thomas 14, E Haydn Walters 15, Judith Garcia-Aymerich 16,17,18, Shyamali C Dharmage 9,, Alessandro Marcon 3,‡,*
Editor: Billy Morara Tsima19
PMCID: PMC11412490  PMID: 39298431

Abstract

Background

Historical data on smoking can enhance our comprehension of the effectiveness of past tobacco control policies and play a key role in developing targeted public health interventions. This study was undertaken to assess trends in smoking initiation and cessation in Australia for the period 1910–2005.

Methods

Rates of smoking initiation and cessation were calculated for participants in two population-based cohorts, the Busselton Health Study and the Tasmanian Longitudinal Health Study. The effects of time trends, gender and age group were evaluated.

Results

Of the 29,971 participants, 56.8% ever smoked. In males, over the period 1910–1999, the rate of smoking initiation in young adolescents remained high with a peak in the 1970s; in older adolescents it peaked in the 1940s and then declined; in young adults it showed a steady decline. In females, the rate of smoking initiation in young adolescents rose sharply in the 1960s and peaked in the 1970s, in older adolescents it increased throughout the period, and in young adults it declined after 1970. In the period 1930–2005, 27.3% of 9,605 people aged 36–50 years who smoked ceased smoking. Rates of cessation in this age group increased throughout but decreased in males after 1990 and plateaued around 2000 in females.

Conclusion

Our findings show substantial variation in the efficacy of tobacco control policies across age groups, with a notable lack of success among the younger population.

Introduction

Cigarette smoking remains a major preventable global health problem [13], with increased risks of cancer, chronic airflow obstruction, emphysema, and vascular disease [1, 4]. People who smoke have a reduced life expectancy of approximately 10 years compared with those who do not; cessation of smoking before 40 years of age largely reduces this increased mortality risk [57].

Public health campaigns to ban tobacco advertising, increasing the cost of cigarettes, health warnings on packaging and restriction of sales to minors have been successful in reducing the prevalence of smoking [1, 8]. In 2019, the prevalence of current smoking was highest in 40–60 year old Australians, consistent with fewer younger people taking up smoking in recent generations [3].

In Australia, public health groups began raising awareness of the detrimental health effects of smoking after the US Surgeon General’s report in 1964, however public health campaigns specifically targeting smoking such as the Quit Campaign only began in 1983, followed by health warnings on packaging and the National Tobacco Campaign in 1997 [9]. These measures have been associated with a steady reduction in the prevalence of smoking. In particular, health warnings, including pictorial representation of smoking related diseases on packaging and laws prohibiting the sale of cigarettes to minors, have all been associated with reduced smoking in teenagers [10]. These approaches and others, including increased cost of cigarettes, mass media controls and introduction of smoke-free environments, have been continued in Australia as part of the National Tobacco Strategies and state-based campaigns.

Despite these gains, the 2022/23 Australian Secondary Students’ Alcohol and Drug (ASSAD) survey found that over 10% of school children aged 12–15 in the country reported lifetime smoking [11]. Similarly, up to 15% of younger adolescents (aged 11–15 years) continue to take up cigarette smoking in Europe [2, 12], unlike the falling trends of smoking initiation in older adolescents (16–20 years) and young adults (21–35 years) [12].

Prevalence rates of smoking reflect the balance between smoking initiation and cessation. In Australia, smoking cessation showed a general increase which was predicted to continue [1315]. In Europe, cessation rates in males have increased over many decades and have also increased in younger females more recently, especially in Northern Europe [16], with similar trends in North America [13, 17]. Knowledge of such trends could help tailor public health interventions by identifying specific groups who will thus experience a disproportionate exposure to tobacco, such as Aboriginal and Torres Strait Islander people, those who are culturally and racially marginalised, people with mental illness, and people living in rural, regional, and remote areas [3]. Specific groups or conditions where the need for smoking cessation is greatest include pregnancy and breastfeeding, the young and those with pre-existing co-morbidities, particularly coronary heart disease [18].

Understanding historical trends in smoking habits can provide context for current and future public health policies. In this analysis, we made use of two long-standing community-based health studies to assess trends in smoking initiation and cessation over 95 years.

Methods

Study design and population

The Tasmanian Longitudinal Health Study (TAHS) investigated all 7 years-old children attending schools in that State in 1968 (the proband cohort) and their siblings [19]. Thirty percent of the cohort now live across all the other states in Australia. Data were obtained on 5,729 probands (participation rate 78.4%) and 12,104 siblings (participation rate 71.6%) who took part in follow-up studies in 2002 and 2007, respectively.

The Busselton Health Study (BHS) began a series of cross-sectional surveys in 1966 in the regional urban area of Busselton in Western Australia [20]. Children and adults were recruited from the general population through schools and public media campaigns between 1966 and 1983 and by media campaigns (including schools) and direct mailing to all local-government area residents on the electoral rolls (voting is compulsory in Australia) from 1990 to 2020 [21]. For the present analysis, data were obtained from eight time points between 1966 and 2015. The number of participants ranged from 1057 (1987) to 5080 (2010–2015) (S1 Table); participation rates were fairly high, ranging from 54% (1987) to 91% (1966).

We analysed data from TAHS and BHS separately and after pooling. We performed data pooling for study waves where questionnaire items on smoking habits were comparable. Pooling involved generating aggregated datasets comprising the numbers of cases of smoking initiation/cessation and person-years at risk, categorised by cohort, gender, age of participants (rounded to the nearest integer), and period (calendar year). The pooled datasets are available as S1 and S2 Datasets. Comparability of the crude rates of smoking initiation/cessation was also assessed to ensure that data pooling was appropriate.

Ethics approval and consent to participate

Ethical approval was obtained for this retrospective analysis of pooled data originally collected from the TAHS and BHS studies. The use of TAHS data was approved by the Melbourne School of Population Health Human Ethics Advisory Group (protocol number: 1545792.1). The use of BHS data was approved by the Human Ethics Committee of the University of Western Australia (protocol number: RA/4/1/8288). Consent to participate was not required as all data had been fully anonymized before the statistical analysis was conducted. The authors had no access to information that could identify individual participants. Data were accessed between 1 October 2017 and 30 April 2021.

Data on smoking

For TAHS, smoking status was derived from the question “In your lifetime, have you smoked at least 100 cigarettes or equal amounts of cigars, pipes or any other tobacco product?”. Former smoking was defined, among those who smoked, as having not smoked at all within the last 4 weeks. Age at initiation/cessation was based on the question, “How old were you when you started/stopped smoking?” (Table 1).

Table 1. Questionnaire items on smoking.

Study Smoking Status Age at initiation Age at cessation
BHS 1966 Non-Smoker / Ex-Smoker / Smoker? Age starting smoking? Age ceased smoking?
BHS 1969 Are you a Non-Smoker () At what age did you start smoking? At what age did you stop smoking for good?
Ex-Smoker ()
Smoker ()
BHS 1972 Which of the following best describes your smoking habits? If applicable, age started If applicable, age ceased
Non-Smoker ()
Cigarette Smoker ()
BHS 1975
Ex-Smoker ()
Pipe Smoker ()
Cigar Smoker ()
BHS 1978 BHS 1981 BHS 1987 Have you ever smoked at least one cigarette per day for as long as one month? No () Yes () How old were you when you first began to smoke at least one cigarette per day? How long ago is it since you last smoked at least one cigarette per day?
Do you now smoke at least one cigarette per day?
No () Yes ()
BHS 2010 Have you ever smoked cigarettes? No () Yes () At what age did you start smoking? How old were you when you last stopped smoking?
Do you currently smoke manufactured or hand-rolled cigarettes?
No () Yes ()
TAHS PROBANDS In your lifetime, have you smoked at least 100 cigarettes or equal amounts of cigars, pipes or any other tobacco product? How old were you when you started smoking? How old were you when you stopped smoking?
NO/YES
TAHS SIBLINGS Do you currently smoke (within the last 4 weeks)?

For BHS, slightly different types of questions were available to define smoking status and age at initiation/cessation at distinct study waves (Table 1). For participants on more than one occasion, the first available information was used to define age at initiation, and the last available to define cessation [12, 16].

Statistical analysis

Analyses were performed using STATA 16 software (Stata Corp. College Station, TX, USA). Separate analyses were conducted for males and females. Participants with missing information on smoking status or age at initiation (n = 530) or cessation (n = 320) were excluded (Fig 1).

Fig 1. Study flowchart.

Fig 1

* subjects with missing data on smoking status or age at initiation. † subjects starting smoking outside the eligible age range (11–35 years). ** subjects with missing data on quitting or age at cessation. †† people quitting smoking outside the eligible age range (35–50 years).

Rates of smoking initiation (per 1,000/year) were calculated retrospectively from childhood to the most recent assessment, as the ratio between the number of people starting smoking and total time at risk (person-years). Participants were considered at risk from age 11 to age at the last study or age 35, which ever came first, since few people reported taking up smoking outside this range [12].

Rates of smoking cessation (per 1,000/year) were calculated as the ratio between the number of people who quit smoking and total time at risk (person-years), defined as years from initiation to cessation for those who quit or to the last questionnaire available for people who were still actively smoking, after excluding life-long non-smoking individuals [16]. Participants were considered at risk from age 16 to age at the last study or age 65, which ever came first, since data were sparse outside this range.

Crude rates of smoking initiation and cessation were reported by decades over the periods 1910–1999 and 1930–2005 respectively, for TAHS and BHS separately and using the pooled dataset. The analysis of smoking initiation was conducted for three separate age groups, referred to as young adolescents (11–15 years), older adolescents (16–20 years), and young adults (21–35 years) [12]. The crude analysis of smoking cessation was conducted for subjects aged 16–35, 36–50, and 51–65 years.

Smoothed trends in smoking initiation/cessation with 95% confidence intervals were estimated using generalized linear models and a negative binomial distribution, a logarithmic link function, and an offset for log person-years. Period (time) was modelled as the main independent variable using natural splines with equally spaced inner knots. The number of knots that provided the best fit according to the Bayesian Information Criterion (BIC) were selected (S2 Table). Each analysis was restricted to calendar years with more than 100 person-years at risk to avoid sparse data. As a consequence, the adjusted analysis of smoking cessation was restricted to participants aged 36–50 years (data were sparse in 2000–2005 and 1980–1989 for the 16–35 and 51-65-year age groups, respectively). Multivariable models were adjusted for study group by including a categorical independent variable (coded as TAHS probands, TAHS siblings, and BHS for initiation; for cessation, it was recoded as TAHS and BHS due to sparse data), and age. Age2 was also included to account for non-linearity (except for the analyses on initiation stratified by age group).

As the risk of relapse is high in the first year after quitting, while it drastically drops afterwards [22], we performed a sensitivity analysis defining sustained smoking cessation as having quit smoking for at least two years (with person-years re-calculated accordingly), in order to exclude subjects who might have quit for a shorter time before the survey.

Results

After exclusions, 29,971 participants made up the pooled dataset for the analysis on smoking initiation (Fig 1). S1 Fig illustrates the number of BHS and TAHS participants included according to the period of data collection. From BHS, 13,014 participants took part in at least one wave (Fig 1) including 2,486 at multiple time points. Overall, there were 15,227 (50.2% female), and the median age at participation was 49 years (Table 2).

Table 2. Number and characteristics of subjects included in the analyses, by study group.

BHS a TAHS TAHS Overall
Probands Siblings
Analysis on initiation (1910–1999)
Subjects (n) 12,790 5,524 11,657 29,971
Female (%) 6,817 (53.3) 2,708 (49.0) 5,626 (48.3) 15,151 (50.6)
Birth cohort, year (median, min–max) 1945 (1873–1965) 1961 (1960–1962) 1959 (1936–1968) 1957 (1873–1968)
Age, year (median, min–max) 56 (16–98) 43 (41–45) 49 (39–71) 49 (16–98)
Ever smoking (%) 6,942 (54.3%) 3,261 (59.0%) 6,816 (58.5%) 17,019 (56.8%)
Age at initiation, year (mean±SD) 18.5±5.7 16.5±3.7 16.6±3.6 17.4±4.7
Total years at risk for initiation (age range 11–35 years) 195,996 77,717 165,646 439,359
Analysis on cessation (1930–2005)
Subjects (n) 3,287 2,110 4,208 9,605
Quitting (%) 1,010 (30.7%) 457 (21.7%) 1,154 (27.4%) 2,621 (27.3%)
Age at cessation, year (mean±SD) 43.1±4.4 39.7±2.2 42.2±4.0 42.2±4.1
Total years at risk for cessation (in age range 36–50 years) 34,617 15,296 37,455 87,368

a participants at multiple time points were only considered once; age at last time point reported for descriptive purposes

S3 and S4 Tables compare age at smoking initiation and cessation, respectively, reported at different waves of the BHS study.

There were 17,019 (56.8%) participants who had smoked regularly at some time in their life and mean age at smoking initiation was 17.4 years.

Over the period 1910–1999, the crude rates of smoking initiation were highest at age 15–16 for males (127.1 per 1,000/year) and at age 17–18 for females (98.9 per 1,000/year) (Table 3).

Table 3. Crude rates of smoking initiation and person-years at risk for males and females, by age group (1910–1999)a.

Males Females
Age group (years) Rate (per 1,000/year) Person-years Rate (per 1,000/year) Person-years
11–12 18.7 29,446 9.7 30,109
13–14 53.9 28,022 33.2 29,297
15–16 127.1 24,110 89.6 26,676
17–18 123.9 18,215 98.9 21,899
19–20 61.8 14,406 46.0 18,176
21–22 33.7 12,630 20.2 16,607
23–26 13.3 23,355 10.1 31,359
27–30 6.2 22,114 6.1 29,895
31–35 1.7 26,682 2.3 35,868

a calculated using the pooled dataset (TAHS + BHS)

In young adolescents, the crude rates of smoking initiation overall were relatively stable in males but were lower in females until 1970 and then increased steeply such that, by 1980–1989, rates of smoking initiation among females had almost reached those in males (87.8 vs 91.2 per 1,000/year) (S5 and S6 Tables). In older adolescents, initiation rates peaked in 1940–49 for males (173.9 per 1,000/year) and 1970–79 for females (107.9 per 1,000/year) and decreased thereafter. In young adults smoking initiation rates steadily decreased for males (S5 Table) over the period 1910–1999, from 61.9 to 2.4 per 1,000/year, while smoking initiation rates were consistently lower in females (S6 Table), peaking in the 1940s and declining thereafter.

Adjusted smoothed trends of smoking initiation between 1910 and 1980 for all age groups combined (11–35 years) showed decreasing trends for males and increasing trends for females (Fig 2, panel A).

Fig 2.

Fig 2

Estimated trends in smoking initiation (panel A) and smoking cessation (panel B) with 95% confidence intervals, by sex*. * blue lines: males; red lines: females. Generalized linear models with negative binomial distribution, logarithmic link function, an offset for log person-years, and adjusted for study group, age, and age2; time was modelled using natural splines with equally spaced inner knots (see S2 Table for the number of knots).

Adjusted trends supported the patterns observed for crude rates when stratified by age group (Fig 3), with three exceptions.

Fig 3.

Fig 3

Estimated trends in smoking initiation with 95% confidence intervals for males (panel A) and females (panel B), by age group*. * green lines: age 11–15; orange lines: age 16–20; grey lines: age 21–35. Generalized linear models with negative binomial distribution, logarithmic link function, an offset for log person-years, and adjusted for study group, age, and age2; time was modelled using natural splines with equally spaced inner knots (see S2 Table for the number of knots).

First, the increasing trend after 1970 in young adolescent males was less evident in the adjusted analysis; for both genders, the adjusted rates also indicated a peak in the 1970s. Second, older female adolescents had a steady increase in smoking initiation. Third, young adult females had a decreasing trend from the 1950s (~30 per 1,000/year) to the 1990s (~0 per 1,000/year).

In the pooled dataset for the analysis of smoking cessation (1930–2005), subjects quitting were 27.3% of people who smoked in the age range 36–50 years (Fig 1) and mean age at cessation was 42.2 years (Table 2).

The crude rates of smoking cessation were less consistent between TAHS and BHS compared with smoking initiation (S7 Table). Nonetheless, for both studies higher crude rates of cessation were seen after 1970. The crude rates of smoking cessation obtained from the pooled analysis are reported in Table 4.

Table 4. Crude rates of smoking cessation and person-years at risk for males and females, by age group (1930–2005)a.

Males Females
Age group (years) Rate (per 1,000/year) Person-years Rate (per 1,000/year) Person-years
36–37 21.3 10085 17.8 8047
38–39 26.6 9522 23.3 7698
40–41 41.7 8585 42.2 7011
42–43 31.8 7148 25.7 5684
44–45 35.5 5071 28.9 3828
46–47 24.9 3884 24.8 2858
48–50 43.1 4198 46.5 2926

a calculated using the pooled dataset (TAHS + BHS)

The adjusted smoothed trends between 1935 and 2005 were also consistent with this long-term increase in smoking cessation (Fig 2, panel B) but highlighted a decrease in cessation among males since 1990, and a plateau for females around 2000.

The sensitivity analysis based on ≥2 years of sustained cessation showed consistent time and age trends in smoking cessation compared to the main analysis, although the magnitude of the rates varied slightly (S1 Appendix).

Discussion

Between 1910 and 1999 up to 57% of people in Australia regularly smoked cigarettes at some stage in their lives, usually starting at 15–16 years of age. In males, rates of smoking initiation have continued to decline in older adolescents and young adults but were high throughout the period. In females, rates of smoking initiation have steadily increased in both young and older adolescents and declined in young adults. The peaks and declines in females show a 30-year lag compared with males so that, in young adolescents, rates of smoking initiation were similar in males and females by the 1980s. Between 1930 and 2005 only 27% of those who smoked in the age range 36–50 years stopped smoking, usually around the age of 42 years. Rates of smoking cessation increased since the 1930s in both males and females although slowed after 1990 in males and after the year 2000 in females.

Smoking initiation

A study of global trends in smoking initiation in 2019 showed that 82.6% of people who smoke began between the ages of 15 and 24 years and that 18.5% began smoking regularly by the age of 15 years; the relevant figures for Australia were 16.9% for males and 17.1% for females [23]. The Australian 2022–23 National Drug Strategy Household Survey [24] showed that, for those aged 18–24 years, 10.5% of males and 8.3% of females currently smoke, continuing a downward trend from 2001 (34.6% and 29.6% respectively). These data agree with our findings on downward and converging trends for age at initiation of smoking, so that in the most recent birth cohort (1980–89) mean age at smoking initiation was 18.0 years for men and 17.4 for women [25].

A study of smoking initiation in four European regions [12], using a similar analysis to the present study, also showed that between 1970 and 2009, initiation rates were highest in older adolescents (aged 16–20 years) and decreased in males and to a lesser extent in females, converged in males and females by around 2005, and that initiation occurred at lower ages over time. During periods of observation that overlapped with the present study, similar rates and trends in initiation in males and females were also observed in Europe [12]. These trends continued in general beyond the period of observation of the present study, except that young male and female adolescents showed increasing and higher rates of initiation in the present study than those observed in the European study [12]. The comparable overall trends observed in Europe and Australia align with similar global social and marketing factors, and health policies that influenced smoking initiation. The increased initiation rates in young adolescents in Australia suggests a group that needs long-term monitoring and targeting.

Smoking cessation

The long-term increase in smoking cessation that was observed from 1935 to 1990 in the present study is promising. However, the slowing down (in males) and plateauing (in females) of cessation rates that was observed by 2005 is concerning.

Using modelling methods and large data bases to estimate current and future prevalence and cessation rates of smoking, Holford et al. showed that cessation rates were higher in later birth cohorts and increased with age in all cohorts in both males and females in the US [13]. However, using similar methods based on Australian data, Gartner et al. found a decrease in cessation rates in younger (20–30 years) males and females in the period 2001–2007 [14]. Trends were variable in the age group 31–50 years during the same period, with an increase in cessation rates in males and a slight decrease in females. In our study, fully adjusted cessation rates for different age groups could not be calculated due to smaller sample sizes. However, the crude rates of cessation showed a decrease in younger (16–35 years) males during 2000–2005 and in older (51–65 years) males and females during 1990–1999, and a continuing upward trend in younger females (16–50 years) (S7 and S8 Tables).

Comparing the cessation rates over a similar period (1995–2005) and age range (36–50 years) in our study (Fig 2) with those in Europe [16], several trends were evident. Firstly, cessation rates were generally higher in Australia than in Europe, except in North Europe, likely attributable to more widespread or effective implementation of tobacco control policies [16]. Secondly, cessation rates increased in Europe and the US [13, 16] while they changed very little among Australian women and even decreased slightly among Australian men in our study. These discrepancies may be related to our different methodology compared to most reports based on repeated cross-sectional surveys, or to imprecise estimated trends in most recent years due to sparse data. It is also possible that the rates calculated for ages 36–50 years in our study did not apply to a wider age range. Nonetheless, a higher rate of quitting for females compared to males has also been observed in a recent study in Australia [15]. Stable or decreasing cessation rates could be in part related to an increase over time, in our fixed cohort, in the proportion of long-term smoking individuals who face greater challenges when attempting to quit. Thirdly, cessation rates in females were greater than in males in Europe while in Australia they initially showed a lag of about 15 years in females compared with males although were similar by 2005. Data from North America and UK [17] using quit ratios, and Europe [16] showed that the rates of smoking cessation were higher below the age of 40 years in females but higher above the age of 40 in males. Peaks of cessation across all European regions in their mid to late 20s in females with a more blunted peak in males of a similar age [16], likely represented smoking cessation related to pregnancy and child rearing. These trends suggest that focusing public health programs on specific groups is effective, and that targeting young adult males may be a strategy to enhance smoking cessation in Australia.

Strengths and limitations

The main strength of the present study was the use of two large, representative population studies with repeated measures over up to 70 years and birth cohorts extending over almost a century [19, 26].

However, we made secondary use of data that were not specifically collected for investigating temporal trends in smoking habits. We acknowledge the potential bias arising from imbalance of participants across ages and birth cohorts due to attrition of the cohorts over time related to dropouts and mortality [15]. Our historical analysis regrettably lacks data on the recent epidemic of use of e-cigarettes and other alternative nicotine-containing products.

There were some differences between the BHS and TAHS, including wording of questionnaires, age of participants and periods of data collection. Analyses therefore were undertaken separately for each study group and, in pooled analysis, with adjustments for study group. To avoid sparse data we did not assess the standardised cessation rates by age group, which were likely to differ in both males and females [16, 17]. Given the long periods of observation, there were changes in the population of participants over time including older age of reported smoking cessation, possibly due to smoking persistence or relapses in people with higher levels of nicotine addiction (S3 Table). Recall bias may also affect reported ages of smoking initiation and/or cessation. Although the mean age of smoking initiation remained consistent between waves of the BHS study, approximately 30% reported age of initiation greater or lesser by more than 2 years at the second wave (S2 Table). Likewise, the mean age at smoking cessation remained similar; however roughly 40% participants exhibited a variation of more than 1 year between the two study waves (S3 Table).

BHS and TAHS samples may not be fully representative of the broader Australian population, which could limit generalisability of our results. Regional centres have 3–5% higher prevalence of current smoking compared with major cities [29]. Compared with national Australian data [27, 28], the Busselton population showed higher proportions of adults formerly smoking in both genders between 1973 and 1984, and higher proportions of lifetime non-smoking individuals in women but not men [21]. Compared with a sample from the Australian National Health Survey 2011, Busselton adults aged 46–64 years studied between 2005 and 2007 were similar on a number of key health indicators, however the prevalence of current tobacco smoking in Busselton was 10%, lower than the national average for this age group at the time (15%) [29]. Finally, the trends seen in smoking initiation and cessation may depend to some extent on changing demographics in the Busselton population over the last century.

Implications of findings

The determinants of smoking initiation in high income countries are social and behavioural and include location, having friends or family who smoke, alcohol use, perceived relief of stress, and the influence of marketing [3032]. These widespread influences on initiating smoking are reflected in the upward trends in smoking initiation observed in the young adolescents in the present study. Efforts to counteract these influences [1, 8, 3335] likely account for the downward trends in smoking initiation in young adults and older adolescent males in our study. The trends in smoking initiation and cessation we have observed in two Australian samples tend to match those seen in other affluent countries and regions [12, 16]. This suggests that similar social and public health influences affect these behaviours. It is notable that the high rates of smoking initiation in males, particularly in those between 16–20 years of age, coincide with the first and second World Wars (1910–1919 and 1940–1949 in S4 Table). Further peaks in smoking initiation after the 1960s likely reflect evolving social attitudes of the times and the implementation of more aggressive marketing strategies for smoking. The lags in smoking initiation and cessation rates between females and males observed in the present study may also reflect social pressures. The higher rates of initiation in Australia in young adolescents, compared with Europe, and the slowing of cessation rates observed in the early part of this century suggest that targeted public health measures are needed in these areas.

Although considerable gains have been made in addressing the smoking epidemic, at least in the more affluent countries, studies in Australia, Europe and North America continue to show high rates of current smoking with a gradual reduction in age of smoking initiation and a decline in rates of smoking cessation. With a few notable exceptions, the prevalence of current smoking has decreased globally in 15–24 year olds, predominantly due to a reduction in smoking initiation [23], although smoking cessation may contribute in younger females [16, 17].

The adoption of the WHO Framework Convention on Tobacco Control has been associated with considerable reductions in the prevalence of smoking [36]. However, population growth has resulted in an increase in the total number of people who smoke globally [23]. Persisting high levels of current smoking may be due to low rates of cessation in susceptible individuals with higher levels of nicotine addiction, and/or a reduction in public health efforts and funding [37] to counter smoking initiation, particularly in young adolescents from low socio-economic groups. It is also recognised that smoking initiation rates are higher and smoking cessation rates are lower in specific groups such as indigenous communities [38] and in those with long-term mental illness [39]. Multiple factors such as high levels of exposure to smoking and marginalization contribute to the challenge of reducing smoking prevalence in Indigenous communities, although substantial progress has been made in the last decades [40]. The development of acceptable and culturally appropriate interventions is required to address these complex, overlapping issues.

Over the course of the last century, factors that have contributed to smoking have included global conflicts, high volume manufacture of cigarettes, brand recognition and social marketing. More recently e-cigarettes and vaping have arisen as an additional possible gateway to cigarette smoking [41, 42]. e-Cigarette use in the past month has increased from 4.2% in 2017 to 15.7% in 2022, particularly in young adults [3].

Conclusions

The present study has provided a historical view of the trends in smoking initiation and smoking cessation over the last century using standardised rates for comparisons across regions and countries. It shows striking period, age and gender effects, with a lesser effect of cohort, suggesting that the efficacy of tobacco control policies has not been uniform across all age groups, with a notable lack of success among the younger population since the 1970s.

The changes observed over time represent a balance of global social, mental health, political and marketing pressures on the one hand and public health measures on the other. The comparisons between Australia, Europe and other high-income countries demonstrate similar patterns likely related to global influences of social, media and public health campaigns. The persistence of a health inequity due to smoking, particularly among susceptible groups, suggests the need for identifying more specific risk factors for smoking initiation [34], developing better targeted approaches for smoking cessation [43] and addressing the emerging risks associated with e-cigarettes and increased mental health disorders.

Supporting information

S1 Fig. Number of BHS and TAHS participants included in the analysis according to the period of data collection.

(DOC)

pone.0307386.s001.doc (34KB, doc)
S1 Appendix. Sensitivity analysis on sustained smoking cessation.

(DOC)

pone.0307386.s002.doc (95KB, doc)
S1 Dataset. Minimal data set to replicate the analyses on smoking initiationa.

a variables included: cohort, sex, A (age), P (calendar year), D and pop (cases of smoking initiation and person-years at risk).

(CSV)

pone.0307386.s003.csv (138.1KB, csv)
S2 Dataset. Minimal data set to replicate the analyses on smoking cessationa.

a variables included: cohort, sex, A (age), P (calendar year), D and pop (cases of smoking cessation and person-years at risk), D2 and pop2 (sensitivity analysis: cases of sustained smoking cessation and person-years at risk).

(CSV)

pone.0307386.s004.csv (250.7KB, csv)
S1 Table. Distribution of the characteristics of BHS participants by study wave.

(DOC)

pone.0307386.s005.doc (40.5KB, doc)
S2 Table. Values of the Bayesian Information Criterion (BIC) for the different numbers of knots tested in the natural spline functions for period, by analysis and sex.

(DOC)

pone.0307386.s006.doc (66KB, doc)
S3 Table. Comparison of age at smoking initiation reported at different BHS wavesa.

a analysis restricted to the subjects who reported to be ever smokers at both waves under comparison.

(DOC)

pone.0307386.s007.doc (41.5KB, doc)
S4 Table. Comparison of age at smoking cessation reported at different BHS wavesa.

a analysis restricted to the subjects who reported to be quitters at both waves under comparison.

(DOC)

pone.0307386.s008.doc (39KB, doc)
S5 Table. Crude rates of smoking initiation per 1000/year and person-years at risk for males by age group, cohort and perioda.

a cells with less than 100 person-years at risk were omitted.

(DOC)

pone.0307386.s009.doc (42.5KB, doc)
S6 Table. Crude rates of smoking initiation per 1000/year (and person-years at risk) for females by age group, cohort and perioda.

a cells with less than 100 person-years at risk were omitted.

(DOC)

pone.0307386.s010.doc (42.5KB, doc)
S7 Table. Crude rates of smoking cessation per 1000/year (and person-years at risk) for males, by cohort and period.

(DOC)

pone.0307386.s011.doc (42.5KB, doc)
S8 Table. Crude rates of smoking cessation per 1000/year (and person-years at risk) for females, by cohort and period.

(DOC)

pone.0307386.s012.doc (59.5KB, doc)

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

Article processing charges were supported by the special fund at the University of Verona dedicated to Open Access publications. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Thomas Behrens

21 Feb 2024

PONE-D-24-00230Trends in smoking initiation and cessation over a century in two Australian cohortsPLOS ONE

Dear Dr. Marcon,

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Reviewer #1: The authors describe smoking initiation and cessation among two Australian cohorts (Tasmanian Longitudinal Health Study (TAHS) and Busselton Health Study (BHS)) who were 7 years old in 1966 and 1968 and followed for 40-50 years.

The most recent data were collected in 2005, nearly 20 years ago and well before the e-cigarette era, which radically changed youth nicotine addiction patterns. The authors briefly note this in the abstract and in the main text at line 391. The development of e-cigarettes, however, needs to be more carefully taken into account when interpreting the relevance of the results to public health policy making today. This does not invalidate the findings as far as they go, but require more cautious conclusions about current relevance of those findings.

The results were pooled into a single analysis. There is nothing wrong in principle with doing this, but the smoking questions were slightly different in the two studies. How they were combined and any associated limitations and uncertainties need to be described in more detail.

The authors censored data for people who stopped smoking before age 35. This is a major problem, since many adolescents who experiment with cigarettes stop by young adulthood. To provide an accurate balance between initiation and cessation, the full range of cessation ages need to be included.

How were the statistical adjustments made (line 186)?

RE: Data availability: The authors state, "All relevant data are within the manuscript and its Supporting Information files," but I don't see the actual raw data. The raw data also needs to be made available per PLOS ONE policies.

Reviewer #2: Trends in smoking initiation and cessation over a century in two Australian cohorts (PONE-D-24-00230)

Thank you for the possibility to peer-review the abovementioned study. The aim of the study was to investigate the trends of smoking initiation and cessation in Australia between 1910 and 2005. The topic is important as smoking remains one of the largest threats for public health. In this study, time trends, as well as gender and age effects were evaluated within nearly 30.000 participants of two population-based cohorts. The findings highlight that tobacco control policies have had less success among younger populations.

I would like to point out a few questions and comments:

1. The authors mention in the introduction that, according to previous literature, public health campaigns to ban tobacco advertising, increasing the cost of cigarettes, health warnings on packaging and restriction of sales to minors have been successful in reducing the prevalence of smoking. Further, they conclude that the efficacy of tobacco control policies has not been uniform across all age groups, with a notable lack of success among the younger population since the 1970s. I was wondering what tobacco control policies have been made in Australia during the studied time period? Can you see the effects of certain policy changes? Have some policy changes been more effective than others? Can you say if some policy changes have better effects on the younger / older population than others?

2. The study was conducted in Australia. How do the authors consider the generalizability of the findings into other countries?

3. What are the current tobacco policies in Australia? Can the authors make more explicit policy recommendations based on their findings?

4. Could the authors please add the (original) number of participants in the BHS cohort to the “study desing and population” paragraph?

5. The eligible age range for smoking cessation was 35-50 years to restrict to participants with a similar age distribution in the two cohorts. The age range for smoking initiation (11-35 years) was based on previous literature. Could the authors give information from previous literature, how many smokers do stop smoking at this chosen age? Does this age range cause selection bias to the results? How many smokers give up smoking, e.g., already in their late twenties or early thirties?

6. The authors state as the main finding of the study: “Between 1910 and 1999 up to 57% of people in Australia regularly smoked cigarettes.” How representative are these two cohorts of the total Australian population? Can the authors tell a bit more about the selection criteria for the Busselton Health Study cohort? Are children who attended school in Tasmania in 1968 similar to the total Australian population? There was some loss to follow up, does this affect the representativeness?

7. The authors recommend targeting young adult males to enhance smoking cessation in Australia. However, as discussed above, the study only investigated smoking cessation after the age of 35 years.

Reviewer #3: # Review summary

Thank you for the opportunity to review the manuscript 'Trends in smoking

initiation and cessation over a century in two Australian cohorts'.

The manuscript reports on the rates of initiation and cessation estimated from

longitudinal cohort studies conducted in Australia beginning in the latter part

of the 20th century. The authors estimated trends in the rate of initation and

cessation of regular smoking amongst those who never (regularly) smoked and

those who do smoke, respectively.

The statistical analysis is not quite complete, with some additional work

needed to satisfy a reasonable scientific standard for this type of analysis. I

have a few criticisms/suggestions for the introduction and discussion as the

literature review does not accurately reflect the available knowledge for the

Australian context, and the strengths and limitations of the study could be

amended. I'll provide feedback section-by-section. I believe the extent of

the amendments would be best described as 'major revisions'.

## Introduction

1st paragraph: The following reference is relevant to the 2nd sentences,

providing an Australian estimate on the number of years of life lost for those

who continue to smoke:

- Banks, E., Joshy, G., Weber, M.F. et al. Tobacco smoking and all-cause

mortality in a large Australian cohort study: findings from a mature

epidemic with current low smoking prevalence. BMC Med 13, 38 (2015).

https://doi.org/10.1186/s12916-015-0281-z

In addition; it was also estimated (contemporaneously to reference [5] in the

manuscript) that those in the UK who quit before age 40 largely avoid the

loss:

- Pirie, K., Peto, R., Reeves, G. K., Green, J., & Beral, V. (2013). The 21st

century hazards of smoking and benefits of stopping: a prospective study of

one million women in the UK. The Lancet, 381(9861), 133-141.

https://doi.org/10.1016/S0140-6736(12)61720-6

2nd paragraph: References [2,7] are specific to the European setting, however

this is not clear in the text. In fact, there are ongoing surveys which have

estimates for adolescent smoking in Australia, the 'ASSAD' survey, see for

example this report (either the 2017 or 2023 release should have been

referenced):

https://www.health.gov.au/resources/publications/secondary-school-students-use-of-tobacco-and-e-cigarettes-2022-2023?language=en

3rd paragraph: Another reference that is important to the (global) understanding

of initiation and cessation rates is the study of Holford et al, in 2014:

- Holford, T. R., Levy, D. T., McKay, L. A., Clarke, L., Racine, B., Meza, R.,

... & Feuer, E. J. (2014). Patterns of birth cohort–specific smoking

histories, 1965-2009. American journal of preventive medicine, 46(2),

e31-e37.

which has also been picked up in Canada as a basis for their own model (but not

of particular interest for this paper).

The authors highlight certain priority populations, however these have been

revised as of 2021 in Australia (nor does reference [3] provided by the

authors mention those in jail). Care should be taken that Aboriginal and Torres

Strait Islander people is capitalised correctly - the Australian co-authors on

this paper should be able to provide guidance on these sensitive practises.

The National Preventive Health Strategy 2021-2030 for Australia identifies the

following priority populations:

- Aboriginal and Torres Strait Islander people

- Culturally and linguistically diverse (CALD)

- LGBTQI+

- people with mental illness

- people of low socioeconomic status

- people with disability

- rural, regional, and remote

Source:

https://www.health.gov.au/resources/publications/national-preventive-health-strategy-2021-2030?language=en

I would also advise against the wording 'resistant to cessation'; this is

suggestive of a white, straight, able-bodied 'default' that is superior in some

way to the 'other'.

Instead I would rephrase the sentence on lines 94-97 to "Knowledge of such trends

could help tailor public health interventions by identifying specific groups who

will thus experience a disproportionate exposure to tobacco; such as Aboriginal

and Torres Strait Islander people, culturally and racially marginalised, people

with mental illness, and people living in rural, regional, and remote areas."

The ethics of _only_ discussing disparity and disadvantage is also

questionable, i.e. progress should also be included:

- Lovett R, Thurber KA, Wright A, Maddox R, Banks E. Deadly progress: changes

in Australian Aboriginal and Torres Strait Islander adult daily smoking,

2004-2015. Public Health Res Pract. 2017;27(5):e2751742.

https://doi.org/10.17061/phrp2751742

4th paragraph: The Australia context is not as scarcely studied as the authors

suggest. In addition to the references above (the study on mortality by Banks,

the ASSAD survey), there is also a study on cessation rates by Gartner et al,

from 2009, along with a newer pre-print that extends the work to cover the

better part of 80 years:

- Gartner, C. E., Barendregt, J. J., & Hall, W. D. (2009). Predicting the

future prevalence of cigarette smoking in Australia: how low can we go and

by when?. Tobacco control, 18(3), 183-189.

- Wade, S., Weber, M. F., Sarich, P., Vaneckova, P., Behar-Harpaz, S., Ngo,

P. J., ... & Caruana, M. (2022). Bayesian calibration of simulation models:

A tutorial and an Australian smoking behaviour model. arXiv preprint

arXiv:2202.02923.

And there is the following study on long-term trends in cross-sectional surveys

of Australians (incl. the age at initiation, and the overall number that

initiate):

- Vaneckova P, Wade S, Weber M, Murray JM, Grogan P, et al. (2021)

Birth-cohort estimates of smoking initiation and prevalence in 20th century

Australia: Synthesis of data from 33 surveys and 385,810 participants. PLOS

ONE 16(5): e0250824. https://doi.org/10.1371/journal.pone.0250824

## Methods

### Data on smoking

Relapse is common after only 1 month of cessation, see:

Herd, N., Borland, R., & Hyland, A. (2009). Predictors of smoking relapse by

duration of abstinence: findings from the International Tobacco Control (ITC)

Four Country Survey. Addiction, 104(12), 2088-2099.

therefore there is likely a lot of misclassification amongst those who had

quit 1 or 2 years before the most recent measurement. If possible, the

observation of smoking status could be censored to 2 years prior to the

most recent survey in either the main analysis, or as a sensitivity analysis.

### Statistical analysis

The number of knots considered and the BIC for each model should be reported.

The predictions of the model should also be compared to the data used; e.g.

for each data point, a _prediction_ interval (not confidence interval) should be

provided, then outliers and the coverage of the intervals should be assessed.

## Discussion

1st sentence: Revise, the data suggests that 57% of people regularly smoked

over the entire period, but at any one point in the period it may have been

lower or higher than this.

2nd sentence: Revise: "Between 1930 and 2005 only 27% of those who smoked in

the age range 35-50 years stopped smoking"

### Smoking initiation

1st parapgraph: Reference [13] in the manuscript did not use any local sources

of data on age at initiation (see its supplementary material); it would be

better to use the published sources of information which include the National

Drug Strategy Household Survey (NDSHS) 2019 (reference [3] in manuscript) or

tThe reference to Vaneckova et al, 2019, I provided earlier also provides local

data on the proportion of those who (ever) smoked that start smoking by a given

age. The NDSHS 2019 also indicates that fewer than 20% of 18-24 year olds smoke

(10% daily, and 7% occasional), therefore the final sentence should be amended.

## Smoking cessation

Line 316: remove repeated 'effective'.

Line 321: Reference [9] does not estimate quit rates; therefore the comparison

is not valid.

A comparison here could be made to the results provided in the pre-print above

(Wade et al, 2022). Perhaps, more importantly, to other studies such as Holford

et al, 2014, or Gartner et al, 2009.

A critical missing piece of context is that the National Tobacco Campaign

(1997-2001) was in full effect during the period where it has been estimated in

this manuscript that cessation rates were in decline. This requires some

explanation; either the authors would need to substantiate why cessation rates

were in decline or explain why their model disagrees with a fairly reasonable

expectation that they would (likely) be increasing.

One potential explanation I can offer is the reliance on adjustment for age

(and age^2) in a period where less data on cessation from younger smokers is

available (i.e. fewer eventual relapsers are reporting that they had quit). As

mentioned above, a sensitivity analysis which censors observations of cessatio

n events 2 years before the surveys might be helpful here.

### Strengths and limitations

The age-stratified analysis of initiation doesn't appear to account for the

differences in distribution of age in later periods (e.g. for the period

1990-1999, no survey contained an individual aged 21 in that period according

to Table 2); thus the analysis would under-estimate the initiation rate.

Another (likely) source of bias in the initiation rate is survivor bias. This

would lead to under-estimation of the initiation rate in older cohorts.

Misclassification of those who ever smoked (versus never smoked) would also

lead to under/mis-estimation of initiation rates in earlier cohorts; this

misclassification has been observed in the Busselton study itself:

- Visalpattanasin, P., Wearne, K. L., & Armstrong, B. K. (1987). Trends in the

uptake of smoking in Busselton, Western Australia. Australian and New

Zealand Journal of Public Health, 11, 21-s.

Wade et al, 2022, shows (Table S2-10,S2-12) that not accounting for this effect

can materially impact the estimate of both the proportion that initiate within a

cohort and the cessation rate in a calendar year.

An obvious, but not stated, limitation is that the cohorts are not random

samples from the complete Australian population; they are more representative

of 'regional' Australia than metropolitan Australia and given that regional

status is an influence on smoking behaviour - this suggests some care should be

taken when generalising to the Australian population.

### Implications

Line 382: The 'hard core' smokers hypothesis is not considered infallible, see

- Skinner, A., Occhipinti, JA. & Osgood, N.D. A dynamic modelling analysis of

the impact of tobacco control programs on population-level nicotine

dependence. Sci Rep 11, 1866 (2021).

https://doi.org/10.1038/s41598-021-81460-9

Line 385-387: At face value I agree that initiation and cessation rates are

less favourable in Aboriginal and Torres Strait Islander communities, this was

not the focus of reference [23] nor is it covered in [24] for mental illness.

Enduring high prevalence in older populations, described in Lovett et al, 2017,

are supportive of the need for more focus on cessation in Aboriginal and

Torres Strait Islander people. I would rework this last sentence using the

following text from the Conclusions of [23] as a starting point, with some

simplifications needed to put it in the context of the study in the manuscript:

> The challenges for indigenous people are much greater and include poverty,

marginalization, challenges in accessing resources, high rates of smoking, and

acceptance of smoking in families and communities. This review has underscored

the complexity of achieving smoking cessation and the need to collaboratively

develop interventions that are acceptable and appropriate to local

populations.

Line 393: A more up-to-date reference on the use of vaping amongst youth in

Australia is provide by the ASSAD survey I mentioned above, e.g. 15.7% of

students reported using vapes in the past month in 2022, up from 4.2% in 2017.

## Conclusions

Line 411: I'd leave out 'political conflict' unless further commentary on the

difficulty in adoption of the FCTC, re-commitment to MPOWER, and recent changes

in vaping policy are provided in the Discussion.

I'd also pivot away from saying 'unacceptably high level of tobacco use' when

this is being written by and from the perspective of people who do not belong

to the groups being talked about (it could read as an admonishment rather than

coming from a place of empathy). An alternative might be "The persistence of

(health) inequity caused by smoking amongst marginalised people suggests..."

although I recognise it isn't the plainest English.

# Summary of review

The key changes to the analysis I would recommend are:

1. A sensitivity analysis that considers censoring quit events 2 years earlier,

or use this as a main analysis (and include the uncensored as a sensitivity

analysis).

2. Report the number of knots considered and the BIC of each model tested.

3. Provide prediction intervals and overlay the observed data for the main

analysis model.

Depending on these results, I expect that some of the conclusions may need

moderation.

The other issues raised in each section can be addressed via amendments to the

text.

Lastly, I would amend some of the language used throughout, replacing 'smoker'

with 'person who smoked' or similar, as per guidance I have received about

labelling and stigmatisation, also see:

- Hefler M, Durkin SJ, Cohen JE, et alNew policy of people-first language to

replace ‘smoker’, ‘vaper’ ‘tobacco user’ and other behaviour-based labels.

Tobacco Control 2023; 32:133-134.

- Renee D Goodwin, Lisa K Walker, Time to Stop Using the Word “Smoker”:

Reflecting on the Role of Language in Advancing the Field of Nicotine and

Tobacco Research, Nicotine & Tobacco Research, Volume 24, Issue 12,

December 2022, Pages 1847–1848.

https://doi.org/10.1093/ntr/ntac218

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Reviewer #2: No

Reviewer #3: Yes: Stephen Wade

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Decision Letter 1

Billy Morara Tsima

12 Jun 2024

PONE-D-24-00230R1Trends in smoking initiation and cessation over a century in two Australian cohortsPLOS ONE

Dear Dr. Marcon,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Academic Editor

PLOS ONE

Journal Requirements:

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Reviewers' comments:

Reviewer's Responses to Questions

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Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Line 92: The Surgeon General Report was published in 1964.

I still worry about drawing strong conclusions about prevention programs today based on such old data.

Line 543-544: Drop this statement. It isn’t really based on your data and doesn’t add anything.

I still don’t understand how the applicants actually did the pooling. It sounds like they just dumped all the data into a single file. Please be more precise.

Also, did the surveys account for complex survey design? If so, how was that considered in the analysis and pooling?

Reviewer #2: (No Response)

Reviewer #3: The authors have comprehensively and accurately responded to all my feedback, with only one minor exception that I'll put on the record to help the authors in any further investigation. Otherwise, the manuscript is worthy of publication and the discussion provides interesting comparison of trends in starting and stopping smoking between settings (US, Europe, Australia).

# Minor feedback

Original feedback: C3.8) The predictions of the model should also be compared to the data used; e.g. for each data point, a _prediction_ interval (not confidence interval) should be provided, then outliers and the coverage of the intervals should be assessed.

Author's response: We have conducted a descriptive analysis on temporal trends in the rates of smoking initiation and smoking cessation using natural splines to model time. The analysis was aimed at describing and visualizing the observed temporal patterns in the study area. For such purposes, we believe it was correct to report confidence intervals, which quantify the uncertainty around the estimated rates based on sample data, under the assumption that the underlying model was correct. Since we were not making out-of-sample predictions or forecasting future observations, we believe we do not need to estimate a prediction interval, which would be used to quantify the uncertainty around a future observation or out-of-sample prediction by accounting for both the uncertainty in the parameter estimate and the inherent variability of future observations. Forecasting was beyond the scope of our analysis, considering the study design and sparse data issues for more recent periods.

Reply: I would still recommend (perhaps in future investigations) that within-sample predictive checks are done on models. This is not to assess how the model performs out of sample. For example, if less (or more) than 95% of the (within sample) prediction intervals contain the observed value, then it is plausible/likely that the model is missing detail or (in very rare cases) was not fit correctly - this also has bearing on whether the confidence intervals themselves have the stated coverage.

Even though your analysis is not Bayesian, a relevant resource is Bayesian Data Analysis by Gelman:

Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2014). Bayesian Data Analysis.

# Data availability

I'd recommend confirming that the cell-sizes in the spreadsheet provided do not violate any data confidentiality or other Ethics agreements about using the data. Line data does not need to be made available according to my own understanding of the PLOS ONE data policy.

# Some fixes for references

1. I spotted some inconsistency with shortened journal name vs full name (and capitalisation of PLoS ONE vs PLOS ONE)

2. Check capitalisation in reference 26, and title case (?) in 28 ,34, 41, and 43.

3. pdf links seemed not to work (probably just a rendering issue).

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Stephen Wade

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Decision Letter 2

Billy Morara Tsima

4 Jul 2024

Trends in smoking initiation and cessation over a century in two Australian cohorts

PONE-D-24-00230R2

Dear Dr. Marcon,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Billy Morara Tsima, MD MSc

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Number of BHS and TAHS participants included in the analysis according to the period of data collection.

    (DOC)

    pone.0307386.s001.doc (34KB, doc)
    S1 Appendix. Sensitivity analysis on sustained smoking cessation.

    (DOC)

    pone.0307386.s002.doc (95KB, doc)
    S1 Dataset. Minimal data set to replicate the analyses on smoking initiationa.

    a variables included: cohort, sex, A (age), P (calendar year), D and pop (cases of smoking initiation and person-years at risk).

    (CSV)

    pone.0307386.s003.csv (138.1KB, csv)
    S2 Dataset. Minimal data set to replicate the analyses on smoking cessationa.

    a variables included: cohort, sex, A (age), P (calendar year), D and pop (cases of smoking cessation and person-years at risk), D2 and pop2 (sensitivity analysis: cases of sustained smoking cessation and person-years at risk).

    (CSV)

    pone.0307386.s004.csv (250.7KB, csv)
    S1 Table. Distribution of the characteristics of BHS participants by study wave.

    (DOC)

    pone.0307386.s005.doc (40.5KB, doc)
    S2 Table. Values of the Bayesian Information Criterion (BIC) for the different numbers of knots tested in the natural spline functions for period, by analysis and sex.

    (DOC)

    pone.0307386.s006.doc (66KB, doc)
    S3 Table. Comparison of age at smoking initiation reported at different BHS wavesa.

    a analysis restricted to the subjects who reported to be ever smokers at both waves under comparison.

    (DOC)

    pone.0307386.s007.doc (41.5KB, doc)
    S4 Table. Comparison of age at smoking cessation reported at different BHS wavesa.

    a analysis restricted to the subjects who reported to be quitters at both waves under comparison.

    (DOC)

    pone.0307386.s008.doc (39KB, doc)
    S5 Table. Crude rates of smoking initiation per 1000/year and person-years at risk for males by age group, cohort and perioda.

    a cells with less than 100 person-years at risk were omitted.

    (DOC)

    pone.0307386.s009.doc (42.5KB, doc)
    S6 Table. Crude rates of smoking initiation per 1000/year (and person-years at risk) for females by age group, cohort and perioda.

    a cells with less than 100 person-years at risk were omitted.

    (DOC)

    pone.0307386.s010.doc (42.5KB, doc)
    S7 Table. Crude rates of smoking cessation per 1000/year (and person-years at risk) for males, by cohort and period.

    (DOC)

    pone.0307386.s011.doc (42.5KB, doc)
    S8 Table. Crude rates of smoking cessation per 1000/year (and person-years at risk) for females, by cohort and period.

    (DOC)

    pone.0307386.s012.doc (59.5KB, doc)
    Attachment

    Submitted filename: Responses to comments (R1).docx

    pone.0307386.s013.docx (209.9KB, docx)
    Attachment

    Submitted filename: responses to comments (R2).docx

    pone.0307386.s014.docx (26.5KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.


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