Quitting Smoking in Germany Evidence from the SOEP

Authors:

Emanuel Bennewitz †, Ashok Kaul † *

First Draft: February 2019. This Version: January 29, 2020

Abstract: This paper investigates the effects of sociodemographic characteristics on changes in smoking behavior in Germany from 2002 to 2016. Overall a decline in smoking prevalence can be observed in Germany. It discloses that political approaches to convincing people not to smoke or to quit smoking have been effective, and health awareness is steadily increasing. We demonstrate that the reduction in current smoking prevalence differs between sociodemographic groups. Therefore, we investigate the development of smoking prevalence and showcase the development of current smokers, never smokers and former smokers between different sociodemographic subgroups of the German population. Moreover, we estimate the probability of quitting with respect to sociodemographic characteristics and specific life events. We also shed light on quitting times of former smokers, that is the time passed since they quit. Our findings show that the decline in total smoking prevalence over time can mostly be traced back to younger-aged male groups and groups with higher socioeconomic status. It is the same group that seems to either quit smoking or never smoked. By analyzing quit times and modelling the probability of quitting, we find that belonging to the higher socioeconomic status as well as specific life events like a marriage or a transition to non-working status are associated with a substantially higher probability to quit.

Keywords: Smoking prevalence, quit time distribution, SOEP.

JEL Classification: I12, I18.

* Corresponding author: ashok.kaul@uni-saarland.de † Saarland University, Department of Economics, Campus Bldg. C3.1, Saarbrücken D-66123, Germany Quitting Tobacco in Germany – Evidence from the SOEP

1. Introduction What are the key drivers behind a smoker’s decision to quit, and which factors influence the probability of quitting? This paper aims to provide answers to these questions using the German Socioeconomic Panel (SOEP) data. Smoking is on the decline in Germany, as it is in most European and OECD countries. From 2002 to 2016, the smoking prevalence fell from 30 percent to 26 percent. Concurrently, sales of factory manufactured cigarettes plummeted from around 138 billion in 1998 to about 75 billion in 2016 (Statistisches Bundesamt: 2017). This is accompanied by a reduced total smoking intensity from 17 to 14 cigarettes per day (CPD) between 2002 and 2016. Smoking intensity declined even for heavy smokers (who by definition smoke 21 or more CPD) during that time from 32 to 30 CPD. Research has shown that changes in smoking intensities are mainly driven by stricter regulations (Anger, Kvasnicka and Siedler: 2010), health awareness (Owusu-Dabo et al.: 2011) and switching behavior (Berry et al.: 2019). Nevertheless, the rate of decline in Germany lags in comparison to other highly developed Western countries. Possible explanations for that lag are the comparatively low-levelled increase in the price of tobacco products, rather lax tobacco regulations in general, or that preventative measures have not worked as effectively on some subgroups of the population. At the same time, we find empirical evidence for only few people using e-cigarettes in 2016 (2 percent) with more than half of them (60 percent) being current smokers. Many researchers have argued that changes in smoking behavior are often heterogenous across the population (Westphal and Doblhammer: 2012; Schneider and Schneider: 2012; Krebsforschungsinstitut: 2004). However, and especially in Germany, socioeconomic differences are substantially affecting the development of smoking behavior in specific subgroups (Schulze and Lampert: 2006). They find that for some groups with low income and low education the probability to begin smoking is not declining but is in fact on the rise. Using the SOEP data, Heilert and Kaul (2017) provide a broad overview of such developments, identifying key differences in the development of smoking prevalence and average cigarette consumption among different socioeconomic groups.

We extend the work of Heilert and Kaul (2017) by focusing specifically on quitting behavior. More precisely, we aim to (i) investigate the development of smoking prevalence, (ii) showcase the development of current smokers, never smokers and former smokers in the German population and (iii) analyze the probability of quitting and the quitting times of formers smokers. The SOEP data provides the information necessary to conduct these analyses. For smoking prevalence, we bi-annually calculate smoking prevalence with latest data up to 2016. For the current smokers, former smokers and never smokers, specific questions from only 2002 and 2012 provide answers. Based on the information supplied in these two waves, we can conduct the third analysis of key drivers for quitting and the time passed since becoming a former smoker. With respect to socioeconomic variables, we employ three main variables of interest throughout all stages of the analysis—gender, age and a measure of a person’s socioeconomic status (SES). The SES variable is constructed based on the Sociodemographic Index (SDI) used in Foreman et al. (2018).

For smoking prevalence, our main findings are in line with those of other authors (e.g. Heilert and Kaul: 2017). The decline in total smoking prevalence over time can mostly be attributed to younger-aged male groups and higher SES groups. Based on our investigation of current smokers, former smokers and never smokers, we find that the reduction in current smoking prevalence differs between sociodemographic groups. Whereas young men with higher SES seem to either quit smoking or never smoked, males over the age of 49 show no structural changes from 2002 to 2012. A group of special interest are females and males with lower SES and an age between 50 and 59. This group has a higher current smoking prevalence in

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2012 than it did in 2002. In addition, 25 through 29 years old females with a lower SES are the only “young” group to experience an increase in smoking prevalence. It seems that the drivers working towards reducing smoking prevalence – namely tobacco control measures or health trends – have not affected this group in the same way as the others. This is one explanation for the relatively modest decline of total smoking prevalence in Germany. By estimating the probability of quitting, we find that the latter is a homogeneous function of the former across most socioeconomic groups. We cannot find any significant differences between the sex and most of the old groups or birth cohorts. The most important factors influencing the probability of quitting are the level of SES, certain life events, and the number of smoked cigarettes per day. Comparing the quit time distribution (QTD) between different age groups, the distribution of quit times shifts towards the right as age increases, which is in line with our expectations. We observe that older persons stopped smoking a longer time ago. Visible, but minor gender differences between 2002 and 2012 occur for the youngest age group. For males age 34 and younger, the share of quitters within the last year was higher in 2012. More females of the same age quit within the last year in 2002 than in 2012.

The remainder of this paper unfolds as follows. Chapter 2 describes the SOEP data, the data selection and weighting procedures, and the construction of our measure of the level of SES. Chapter 3 focuses on the development of smoking prevalence on the aggregate-level and for specific subgroups. Chapter 4 introduces the prevalence split among current smokers, former smokers and never smokers using information supplied in the 2002 and 2012 waves. In Chapter 5, we conduct a regression analysis of the probability to quitting, using a simple logarithmic general linear model (GLM) with Poisson distribution. In Chapter 5 we also describe the QTD in the two waves. Chapter 6 concludes.

2. Data To conduct our analysis, we employ longitudinal data from the German SOEP. The SOEP is the largest and longest-running longitudinal data set available in Germany and includes more than 20,000 individuals per year (Kroh et al.: 2018). Since 1984, SOEP has provided yearly micro data about German households. The SOEP individual questionnaire is split into 10 parts, covering a broad area of topics with a focus on socioeconomic information such as income, employment and education. To analyze quitting behavior, we draw information from the “Health and Illness” part of the questionnaire, which contains smoking-related questions. These questions were first introduced in 1998 as part of the SOEP questionnaire, but the questions were altered and reformulated in the first years. Since 2002, questions on smoking behavior have remained unchanged. To ensure consistency in our dataset, we focus on the time span from 2002 through 2016. Similar to Heilert and Kaul (2017), we construct an unbalanced panel of the adult population which, depending on the year, consists of between 16,000 and 27,000 individuals.1 To conduct our analysis on quitting tobacco in Germany, we construct different variables from the SOEP data. First, we construct a measure of current smoking prevalence, that is, the share of current smokers at a given point in time. A reduced share of smokers is evidence for either smokers quitting (cessation) or fewer people starting to smoke (initiation). In the SOEP, smoking is defined by people consuming cigarettes, cigars

1 Although from 1998 through 2006 people aged 17 are part of the full adult survey. For the purpose of consistency, only people aged 18 and older are considered in the main analysis. In 2006, the survey method changed. People aged 17 do not answer the normal adult questionnaire, but instead a special “youth” questionnaire. Indeed this “youth” questionnaire does not include questions about smoking behavior. ______

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or pipes.2 For our measurement of smoking prevalence, a dichotomous variable current smoker is constructed indicating whether or not a person is a current smoker. This variable does not distinguish between cigarette, pipe and cigar smokers, but explicitly does not include e-cigarette users. Second, in two waves, namely 2002 and 2012, the SOEP allows us to construct measures of smoking history. In these years, respondents were asked if they have ever smoked (at least 100 cigarettes). Based on this information (ever smoker), we can investigate quitting (instead of either quitting or less initiation). Technically, we combine the current smoker status (our smoker variable) with the ever smoker variable to split the total population into three subgroups: never smoker, former smoker, and current smoker.3 Finally, we aim to investigate the key drivers for quitting and changes in the quit time of former smokers. In the SOEP, former smokers are asked to state the year and month they gave up smoking. We use this information to determine the point in time of cessation and to specify a quit time distribution. A variety of research (e.g. Heilert and Kaul: 2017; Westphal and Doblhammer: 2012; Schneider and Schneider: 2012; Krebsforschungszentrum: 2004) show that smoking behavior differs across groups with different socioeconomic characteristics. To further investigate this relationship, we combine the information on smoking and quitting behavior with information on sociodemographic characteristics. Particularly, we analyze the smoking variables by age, gender and socioeconomic status (SES). Whereas information on gender and age is directly obtainable from the SOEP data, a combination of socioeconomic variables is required to address SES. We define an individual’s SES based on a Sociodemographic Index (SDI), comparable to the SDI used in Foreman et al. (2018).4

As in Foreman et al. (2018), our SES combines net income (Z1, in € per year, log space, and per capita) and 5 education (Z2, mean years of education per capita) as the two drivers of SES. Both indicators Zi are scaled 0 to 1 by taking the raw values Xi and scaling from the smallest (worst) to largest (best) possible values in each cross section (i.e. survey wave).6

, = , , 𝑋𝑋𝑖𝑖 − 𝑋𝑋𝑖𝑖 𝑚𝑚𝑚𝑚𝑚𝑚 𝑍𝑍𝑖𝑖 Then, a composite SES is computed by geometric𝑋𝑋𝑖𝑖 𝑚𝑚𝑚𝑚𝑚𝑚 mean− 𝑋𝑋 𝑖𝑖of𝑚𝑚 𝑚𝑚𝑚𝑚the two underlying indicators. The SES is expressed on a scale from 0 (lowest) to 1 (highest).

1 = 𝐼𝐼 𝐼𝐼

𝑆𝑆𝑆𝑆𝑆𝑆 �� 𝑍𝑍𝑖𝑖� 𝑖𝑖 2 The questionnaire of each year is available at https://www.diw.de/en/diw_02.c.222729.en/questionnaires.html. 3 Note that about 13 percent of respondents who did not (or not properly) answer the ever smoker question in 2012. Excluding these missing observations leads to a slightly different population for the analysis of smoking history, compared to the analysis of current smoking prevalence. 4 Generally speaking, the SDI is a measure to identify where countries or other geographic areas sit on the spectrum of development. The SDI was developed as part of the Global Burden of Diseases, Injuries and Risk Factors Study (GBD). 5 Foreman et al. (2018) additionally include the fertility rate (under 25 years). However, this measure is especially important for cross-country analyses and for shedding light on the differences between countries at different stages of economic development. Within a highly developed country such as Germany, the fertility rate does not serve the same purpose and including it as part of the SDI provides no substantial benefit. 6 Further descriptive statistics on the SES indicators can be taken from Table A1 in the Appendix and will be also available upon request. ______

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The split between people matching the group of lower or higher SES was operationalized by the median of SES. The share of people having an SES score lower than median is defined as the group with “lower socioeconomic status”, and the share with a score above median has been categorized as “higher socioeconomic status”.7 Using the demographic information on age, gender and SES, we provide a graphical and descriptive analysis of smoking behavior in Germany over time. As discussed, we employ unbalanced panel data from the SOEP. To ensure representativeness of the analysis, accompanying weights (cross-sectional weights) are used. Cross-sectional weights in the SOEP are person-related weighting variables and consider sampling probabilities, non-response and attrition. Detailed information about the structure of the survey method and sampling weights are summarized in Kroh et al. (2018). The provided weights are applied as suggested by Bohmann.8 For all years except 2010, 2012 and 2016, we use the standard cross-sectional weights that are included in SOEP (v33.1), which is the most recent SOEP version released in 2018. For 2010 and 2016, we use adjusted weights provided in the data set that account for the increased sample size in those years stemming from the inclusion of the data from the survey “Familien in Deutschland” (Families in Germany, FiD) in 2010 and “Refresher Sample (M3/M4)” in 2016. For 2012, the SOEP does not provide separate weights, only integrated weights. We solved this problem by using the standard weights of an older SOEP version (v30). This version does not contain data of the FiD survey and cross-sectional weights are believed to be correct.9

3. Smoking prevalence over time in Germany The starting point of our analysis of quitting behavior is the development of current smoking prevalence in Germany. A reduced smoking prevalence is often seen as a direct consequence of a combination of successful tobacco control measures and a secular trend (e.g. a health trend) against smoking (Lee, Glantz and Millett: 2011). Moreover, in recent years, apparently less harmful and accepted substitutes to conventional tobacco products, such as e-cigarettes and heat-not-burn products, have been introduced into the market. In this chapter, we first investigate the general development of smoking prevalence in Germany from 2002 through 2016. Second, like Heilert and Kaul (2017), we provide answers to the question whether the observed development of smoking prevalence differs across subgroups, defined by age, gender and socioeconomic status. Figure 1 depicts the development of smoking prevalence in Germany from 2002 through 2016. Across that time span, smoking prevalence declined from about 30 percent in 2002 to about 26 percent in 2016. In most years, smoking prevalence decreased continuously by less than 1 percentage point. From 2006 to 2008, a noticeable drop from 30 to 28 percent occurred. This drop can be explained by the ban on smoking in public places, including bars and restaurants, which came into effect in September 2007 (Nagelhout et al.: 2011).

7 As a sensitivity analysis, we estimate mortality rates for our sociodemographic subgroups defined by age, gender, and SES. Regardless of the well-known overestimation of mortality by SOEP data (e.g. Schnell and Trappmann (2006)), between-group differences are in line with mortality information obtainable by the German Federal Statistical Office. Aggregate statistics (without SES) compare well in terms of age and gender effects. Results of this comparison are available upon request. 8 For more information on provided weights in the SOEP data, see Bohmann: https://www.diw.de/documents/dokumentenarchiv/17/diw_01.c.571607.de/soepcampus_4_gewichtung_de.pdf 9 For more details on cross-section panel weights in the SOEP, see Heilert and Kaul (2017). ______

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Between genders, the level of smoking prevalence substantially differs throughout the entire time span. In 2002, male smoking prevalence was 36 percent, 11 percentage points above the level of female smoking prevalence (25 percent). Over time, this gap shrunk to 7 percentage points in 2016 (29 percent for males, 22 percent for females). While among males a total reduction of 7 percentage points, or about 19 percent, was observed (from 36 to 29 percent), female smoking prevalence only declined by 3 percentage points, or about 12 percent (from 25 to 22 percent). Consequently, the observed decline in the smoking prevalence of the overall German population is mostly attributed to a sharp decline in male smoking prevalence. From a policy perspective, the overall decline in smoking prevalence can be seen as a positive signal. It suggests that political approaches to convincing people not to smoke or to quit smoking have been effective, and health awareness is steadily increasing.

40 38 36 34 32 30 28 26 24 Smoking prevalence (in %) 22 20 2002 2004 2006 2008 2010 2012 2014 2016

All Men Women

Figure 1: Smoking prevalence (total and by gender), 2002-2016 Note: SOEP waves 2002–2016. Unbalanced panel. Data weighted by expansion factors supplied in the data set.

Next, we turn our attention to differences in smoking prevalence between age groups for the years 2002 and 2016. In 2002 for both men and women, the population’s younger half (49 and under) possess a higher smoking prevalence (grey bars), where young and early middle-aged people have the highest prevalence. As shown in Figure 2, smoking prevalence decreases steadily as people enter middle-age and on into retirement and elderhood. This decrease over age groups is steadier for men than it is for women. In 2016, we make a similar observation. However, the start of the smoking prevalence decline is later, not until 60-64 for men and 55-59 for women. There are clear reasons for this. For men, the decrease in smoking prevalence among the youngest groups is somewhat offset by the increase among late middle-aged men and early retirees. This results in a more consistent, albeit lower, smoking prevalence across most age groups. For women, smoking prevalence among the youngest age group dropped precipitously, to levels usually found in late elderhood.

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2016 2016 Men 2002 Women 2002 ≥ 80 ≥ 80

75-79 75-79

70-74 70-74

65-69 65-69

60-64 60-64

55-59 55-59

50-54 50-54

45-49 45-49

40-44 40-44

35-39 35-39

30-34 30-34

25-29 25-29

20-24 20-24

0 10 20 30 40 50 60 0 10 20 30 40 50 60 Smoking prevalence (in %) Smoking prevalence (in %)

Figure 2: Smoking prevalence (by gender and age groups), 2002 and 2016 Note: SOEP waves 2002–2016. Unbalanced panel. Data weighted by expansion factors supplied in the data set.10

Next, we focus on the differences in smoking prevalence by socioeconomic status (SES). Apart from the fact that male smoking prevalence is noticeably higher than women’s smoking prevalence, we also find evidence that a higher SES correlates with a lower smoking prevalence. This observation was also made by Hiscock et al. (2012) and Bobak, Jarvis and Skodova (2000). Figure 3 depicts the development of smoking prevalence by gender and SES. Because the share of female smokers with lower SES was higher in 2016 than in 2002, the decline in total smoking prevalence of women is exclusively caused by women with higher SES. Since 2002, there has been a strong decline in total smoking prevalence among males. So, we find an overall decrease of smoking prevalence for both SES groups. Thus, the total decline can be traced back to men of lower and higher SES. But for those with a higher SES, the declined prevalence was substantially stronger than for those with a lower SES. The main effect must then conclusively be attributed to men with a higher SES.

10 As a sensitivity analysis of smoking prevalence among total population and subgroups defined by gender and age group, we estimated smoking prevalence for a variety of different aggregations of age groups for each year from 1998 obtainable in the SOEP. ______

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15 Smoking prevalence (in %)

10 2002 2004 2006 2008 2010 2012 2014 2016 Women - lower socioeconomic status Women - higher socioeconomic status Men - lower socioeconomic status Men - higher socioeconomic status Figure 3: Smoking prevalence (by gender and socioeconomic status), 2002-2016 Note: SOEP waves 2002–2016. Unbalanced panel. Data weighted by expansion factors supplied in the data set.

To conclude, the key findings of our analysis of smoking prevalence differentiated by sociodemographic characteristics (gender, age and SES) show that the decline in total smoking prevalence can mostly be attributed to men from younger age groups and a higher SES.

4. Changes of initiation and quitting behavior as key drivers for decreased smoking prevalence There are two reasons why the observed decline in smoking prevalence has occurred – either more people have quit smoking or less people have started smoking. In this section, we aim to shed light on smoking behavior and try to unravel those two explanations. We use a specific question from the SOEP 2002 and 2012 waves to gain empirical evidence on the smoking behavior across the German population. In 2002 and 2012, respondents were asked if they had ever smoked. If they said they had, a follow up question clarified if they were currently smoking or if they had given up smoking. Similar to Heilert and Kaul (2017) and Hakulinen et al. (2015), we use this information to split the total population into three types of smoker: never smoker, former smoker, and current smoker. Breaking the total population down into those three groups allows us to uncover the drivers behind the smoking prevalence’s downward trend. Again comparing 2002 and 2012 and given a constant population distribution, three explanations are possible for less people currently smoking: (i) an increase in the share of never smokers, indicating lower smoking initiation; (ii) an increase in the share of former smokers, indicating more people quit smoking, or (iii) an increase in both shares, indicating the smoking prevalence decline is caused by both lower smoking initiation and higher quitting. Figure 4 shows the groups composition in 2002 and 2012. The share of never smokers is nearly unchanged between 2002 and 2012, only a small 0.5 percentage point increase was reported. The share of former smokers increased by 4.5 percentage points in 2012, and the share of current smokers decreased by 5 percentage points.

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100%

30.5% 25.4% 80%

60% 24.5% 29.0%

40%

20% 45.0% 45.5% Share of total population (in %) 0% 2002 2012 Never smoker Former smoker Current smoker

Figure 4: General population split (distribution of never, former and current smoker), 2002 and 2012 Note: SOEP waves 2002–2016. Unbalanced panel. Data weighted by expansion factors supplied in the data set.

Next, we evaluate this question in more detail using sociodemographic information. We start by investigating changes in the group composition by age and gender. The left panel of Figure 5 depicts the split between never smokers (grey line), former smokers (dark blue line) and current smokers (light blue line) for males by age. The dashed lines show the split in 2002, the solid lines the split in 2012, respectively. Independent of the year, the share of former smokers increases almost linearly with age, while the share of current smokers increases from age 20 through age 29, remains constant through age 54 and declines from that age onwards. The share of never smokers declines between age 20 and 59 and increases thereafter. Comparing the development of the three different groups over the decade from 2002 through 2012, for males over age 49, the split remained mostly unaltered. Males of age 49 and younger show a lower current smoking prevalence in 2012. In the youngest age group (20-24 years), this is caused by a higher share of never smokers. The same is true for the two age groups between age 40 and 49. For males of age 30 through 39, the share of former smokers is substantially higher in 2012 than in 2002. In summary, the lower current smoking prevalence of males in 2012 is explained by both lower smoking initiation and higher quitting. For females (Figure 5, right panel), the split between former smokers, never smokers and current smokers by age differs from the one we observe for males. For both 2002 and 2012, in contrast to the increased share of former male smokers with age, the share is almost constant across all age groups. The share of current smokers at both points in time remains relatively constant until age 49 and declines from that age onwards. Contrary to males, the share of never smokers among females age 50 and older increases substantially with each additional year, leading to more than 75 percent never smokers among females age 80 and older. For males, the same share is only at about 35 percent. Comparing the development of the three groups over time, for females over age 50, the split differs from the one for males. Unlike men, we observe in 2012 a substantially lower share of never smokers than in 2002, especially between age 50 and 74. There are also more former smokers, but the decline in never smokers overcompensates this development, leading to more current smokers among females age 50 and above. Below age 50, the split for females looks similar to the split for males. Two age groups show a higher share of never smokers in 2012 compared to 2002 (between age 20 and 24 as well as between age 40 and 44), and two age groups show a higher share of former smokers (between age 25 and 34). Thus, the development of smoking and quitting behavior among women differs substantially across age groups. In addition, the overall decline of never smokers among women over age

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49 levels out the increase in never smokers among males, leading to a constant development of the share of never smokers for the overall population. As a result, we find (i) descriptive evidence for an increased share of former smokers for both genders, (ii) a higher share of never smokers among young and middle age males and females as well as (iii) a substantially lower share of never smokers among older females (50+).

100% - - - 2002 100% - - - 2002 Men -◊- 2012 Women -◊- 2012 80% 80%

60% 60%

40% 40%

20% 20%

Share of total male population (in %) (in population male of total Share 0% 0% Share of total female population (in %) (in population female of total Share

Figure 5: Split into types of smoker (by gender and age group), 2002 and 2012 Note: SOEP waves 2002–2016. Unbalanced panel. Data weighted by expansion factors supplied in the data set.

Next, we turn our attention towards the split between current smokers, former smokers and never smokers grouped by age, gender and the SES. Figure 6 shows the split between current smokers, former smokers and never smokers across age groups by gender and SES. The upper left panel describes men with lower SES, the upper right panel men with higher SES and the lower two panels depict the same split for women respectively.

For males with lower SES (Figure 6, upper left panel), current smoking prevalence is exceptionally high at a young age in both waves (between about 40 and 60 percent). From around age 50 and above, the prevalence declines continuously until age 80 (between 5 and 10 percent). At the same time, the share of former smokers increases roughly with each age group. The curves for never smokers are slightly u-shaped, with higher shares in early and late ages. From 2002 (dashed lines) to 2012 (solid lines), changes are most visible at the beginning and in the middle of the age distribution. Between age 20 and age 49, current prevalence dropped between 3 and 13 percentage points over the course of one decade. For the young (age 20 through 29), this drop is mostly attributed to a higher share of never smokers. Consequently, the share of former smokers is lower in 2012 than it was in 2002. Males with lower SES between 55 and 64 years of age, have higher smoking prevalence in 2012 than those in 2002. For this age group, the share of former smokers remained constant while the share of never smokers shrank. For males with higher SES (Figure 6, upper right panel), above age 50, the split looks remarkably similar to males with lower SES. For those younger than 50, compared to lower SES, males with higher SES consist of more never smokers. In addition, the development between 2002 and 2012 looks more favorable for young males with higher SES. The share of never smokers increased strongly and the share of former smokers increased moderately throughout most age groups from 20 through 54 years of age. As a result, current smoking prevalence is much lower in 2012 than in 2002. ______

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For females with lower SES (Figure 6, lower left panel), the split of the three groups across age looks remarkably similar to the overall split for females (see Figure 5). The share of never smokers first declines for the youngest age groups, increases again and after a new decline for the two mid-aged groups the share of never smokers increases group by group with the age of 55 or more years. At a lower level, the curve for the shares of former smokers mirrors the curve for never smokers. The share of current smokers is highest for women aged 45 through 49 years and distinctly decreases with every next higher age group. The only obvious difference between current smokers among all women and current smokers among women with a lower SES can be found within the level of share. Among women with lower SES the share of current smokers is higher. Comparing 2002 and 2012 data, we observe a higher share of current smokers above age 49, driven by a lower share of never smokers. In addition, for females with lower SES and age 25 through 29, we find the share of current smokers to be higher in 2012 than in 2002. Accordingly, we observe fewer never smokers for this age group in 2012. For females with higher SES (Figure 6, upper right panel), the split differs from the other three panels. These women have a much lower current smoking prevalence across all ages. In addition, for younger age groups (age below 50), the share of current smokers declined from 2002 to 2012. This is a result of both lower smoking initiation and higher quitting. For older women, there are some age groups with fewer never smokers, but for these groups the share of former smokers increased, leveling out the effect and leading to almost the same level of current smokers. All in all, we find that changes in the split between current smokers, former smokers and never smokers from 2002 to 2012 strongly depends on sociodemographic variables. Whereas young men of higher SES seem to either quit smoking or not start smoking at all in the more recent wave, males over age 49 show no structural changes over the same time period. A group of special interest are females and males with lower SES aged between 50 and 59. These groups have higher current smoking prevalence in 2012 than in 2002. In addition, females age 25 through 29 and lower SES are the only “young” group with an increased smoking prevalence. It seems that the drivers for a reduced smoking prevalence, namely tobacco control measures, health trends or less harmful alternatives, have not affected these groups as they did for others. This pattern may be an explanation for the relatively modest decline of total smoking prevalence in Germany.

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100% 100% Men - lower SES - - - 2002 Men - higher SES - - - 2002 -◊- 2012 -◊- 2012 80% 80%

60% 60%

40% 40%

20% 20%

0% 0% Share of all men of Share men with all lower SES (in %) Share of all men with higher SES (in %) (in SES higher with men of all Share

100% 100% Women - lower SES - - - 2002 Women - higher SES - - - 2002 -◊- 2012 -◊- 2012 80% 80%

60% 60% (in %) 40% (in %) 40%

20% 20% Share of all women with lower SES lower with women of all Share 0% SES higher with women of all Share 0%

Figure 6: Smoking history (by gender, SES and age group), 2002 and 2012 Note: SOEP waves 2002–2016. Unbalanced panel. Data weighted by expansion factors supplied in the data set.

5. The relationship between socioeconomic characteristics and quitting In this section, we pin down socioeconomic characteristics of smokers that decided to quit. Moreover, we assess to what extent certain life events can be identified to have a positive impact on the decision to quit smoking. The main objective of this section is to investigate the relationship between the probability of quitting and socioeconomic characteristics or life events. A further objective of this section will be to look at the time passed after successful quit attempts (quit time). For investigating the probability of quitting, we construct a dataset that includes a binary quitting variable used for regression analysis. We are interested in analyzing the influence of SES and a set of predictors for the probability to quit. Based on the SOEP data, we observe whether a smoker quits smoking in the period 2002 to 2016. We use the information on smoking status obtained in each wave and define quitting as a switch from smoker to non-smoker between successive waves. More formally, we estimate the probability

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Pr( = 1) = ( )

Where Ri is the variable that takes the value 1𝑅𝑅 if𝑖𝑖 a smokerΦ became𝑋𝑋𝑖𝑖𝛽𝛽𝑖𝑖 a non-smoker (quitter), and the value 0 if a smoker did not quit. To analyze the relationship between socioeconomic characteristics and quitting, we employ a simple logarithmic GLM model with Poisson distribution. As covariates Xi, we use our main variables of interest, the SES as well as gender and age. Between age and SES, an interaction term is included as well. In addition, the model includes dummy variables for certain triggering life events occurring between two waves, consisting of an additional child living in the household, a marriage, and a transition to non-working status.11 Each of them takes the value 1 if between two successive waves the event occurred and 0 otherwise. Further predictors we control for are the birth cohort (four dummy variables), the smoking intensity before quitting (normal smoker vs. heavy smoker with the distinction of 21 CPD), a regional variable differentiating between the person living in West or East Germany, and the year the survey wave was conducted. Table 1 provides the corresponding regression analysis results. We find statistical evidence that with a higher SES the probability of quitting increases substantially. Also, the probability for older people aged 50 and over is higher compared to people aged 30 to 49 years. But this age effect is influenced by the level of SES. We find evidence of an interaction effect between age and higher SES. More specifically, people aged 50 and older with higher SES have a significantly lower probability of quitting than persons aged 30 through 49 years with higher SES. Moreover, all three life events (additional child in household, a marriage, and a transition to non-working status) have a significant positive impact on the probability of quitting. Instead, being a heavy smoker (consuming more than 21 CPD) and living in East Germany are associated with lower probabilities. Of our birth cohort dummies, only the earliest birth cohort is significantly different from zero in comparison to those born between 1960 and 1969. Though, we cannot determine a statistically significant gender difference nor time trend.

11 To determine whether an additional child lives in the household, we compared the information on the number of children living in the household. If the number of children increased between two successive waves, our variable was set to 1, otherwise to 0. To determine a change in marital status, we compared the marital status information between two waves. If the person comes from a different status (e.g., single, divorced, widowed) and is married in the following wave, our variable received the value 1, and 0 otherwise. This variable also takes into account the cohabitation of same-sex persons. In order to identify a transition to non-working status, it was examined between the waves whether a person had changed from an alternative state to (i) not at all gainfully employed, (ii) unemployed or (iii) retired. If this is the case, our variable was assigned the value 1, otherwise the value 0. ______

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VARIABLES Outcome (Quitting) SOCIODEMOGRAPHICS 0.4123 Higher SES (0.041) Age group (reference: 31-49 years) 0.1248 <30 years (0.058) 0.0210 50-64 years (0.060) 0.1498 >64 years (0.095) Birth cohort (reference: 1960-1969) 0.2446 1910-1939 (0.090) 0.0441 1940-1959 (0.050) -0.0011 1970-1998 (0.044) 0.451 Male (0.027) LIFE EVENTS 0.6500 Additional child in household (0.056) 0.3331 Marriage (0.071) 0.3841 Transition to non-working (0.048) CONTROLS -0.5740 Heavy smoker (reference: normal smoker) (0.050) -0.1581 Living in East Germany (0.088) -0.0060 Year of survey (0.003) INTERACTION EFFECTS Age group and SES interaction (reference: high SES and 40-49 years) -0.1893 high SES # <30 years (0.076) 0.01607 high SES # 50-64 years (0.066) 0.3817 high SES # 64 years (0.088) OBSERVATIONS 64,842 Table 1: GLM model results. Note: The outcome is a binary variable of value 1 if a former smoker quitted, and 0 otherwise. Standard errors are depicted in parentheses. Significant coefficients (p<0.05) are depicted in bold.

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Figure 7 outlines the main results of our analysis. The figure bins the GLM-estimated coefficients for our variables of interest’s relationship with the probability of quitting. The figure allows comparing the variables’ impact on the probability to quit smoking. We distinguish four types of variables, which are sociodemographic variables, variables for life events, control variables, and interaction effects. Among all other variables, significant negative coefficients can only be identified for two of our control variables. The strongest negative coefficient on the quitting probability results from being a heavy smoker. This coefficient is more than three times stronger as the indicator for living in East Germany, the other significant negative control variable. These outcomes indicate that (i) the probability of quitting for heavy smokers is way smaller compared to normal smokers and (ii) that quitting is less common in the eastern part of Germany than in the western part. On the opposite (positive) site, we identify the life event of an additional child in the household as the factor with the most positive association with quitting probability. It suggests that having responsibility for another person’s health may directly affect own smoking behavior. In addition, the other two variables for life events have a significant influence on the probability of quitting, too. Both coefficients are only slightly lower than the coefficient for a high SES, which is the second highest significant and positive coefficient. That means, the probability of quitting is higher if one belongs to the higher SES group (in comparison to the lower SES group). In comparison to the estimated life events, the coefficients on age and birth cohort are only significant for one group each and considerably smaller. For the interaction of SES and age group, the coefficients for all age categories are significant. In comparison to the reference group (aged 31-49 with higher SES) the coefficient for those aged 65 and over with higher SES is the highest. Being negative means the probability of quitting is lower for the aged 65 and older with higher SES. The coefficient for those aged 50 through 64 with higher SES is only about half the coefficient for the aged 65 and older. For the respondents aged under 30 and higher SES the probability of quitting, on the other hand, is positive indicating a higher probability in comparison to the reference group.

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PROBABILITY OF QUITTING lower 0 higher Sociodemographics Level of SES Higher SES *

Age of Inividuals Under 30 yrs. 50-64 yrs. * 65 yrs. or older

Birth cohort 1910-1939 * 1940-1959 1970-1998

Gender Men

Life Events Additional child in household * Transition to non-working * Marriage *

Controls Heavy smoker (21+ CPD) * Living in East Germany * Year

Interaction Effects Higher SES & under 30 yrs. * Higher SES & 50-64yrs. * Higher SES & 65 yrs. or older *

Figure 7: Coefficient plot of the estimated probabilities for quitting from the GLM Note: The outcome is a binary variable of value 1 if a former smoker quitted, and 0 otherwise. The 95% confidence intervals are represented by the dark blue line to the left and right of the coefficient displayed as a dot. Significant coefficients (p<0.05) are marked with an asterisk (*).

Next, we shed light on the variable quit time in detail among age, gender and SES. In the SOEP data, as discussed in previous sections, we have information on former smokers in two waves, 2002 and 2012. We first investigate this information via analyzing the so-called quit time distribution (QTD) of different sociodemographic groups. The QTD is the distribution of the time passed since a former smoker quitted smoking. Lee et al. (2017), who also analyzed the QTD, used sex- and age-specific data on population and smoking habits in the United States from 1990. In our analysis, we also pay attention to differences in SES and use a more granular split of QTD.

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Figure 8 depicts the QTD across age groups for male and female former smokers. Comparing the QTD between different age groups, the distribution of quit times shifts towards the right as age increases, which is in line with our expectations. We observe that older persons stopped smoking a longer time ago. Moreover, for most age groups the distribution between genders looks fairly similar. Finally, the QTD in 2002 resembles the QTD in 2012 fairly well. Visible, but minor differences between 2002 and 2012 occur for the youngest age group (less than 35 years of age) and for age group 35 through 44. For older people, quit times shift to the right. Thus, in the same age group, people stopped smoking less recently in 2012 than in 2002. For the younger groups, this trend is not as clear. For males age 34 and younger, the share of quitters within the last year (dark blue colored bar) was higher in 2012. For females of the same age, it occurred the other way around, that is, more females quit within the last year in 2002 than in 2012.

Men Women

2012 2012 65 or more 65 or more 65 or 65 or yrs. 2002 yrs. 2002 more yrs. more yrs.

2012 2012 55-64 yrs. 55-64 yrs. 55-64 yrs 2002 55-64 yrs 2002

2012 2012 45-54 yrs. 45-54 yrs. 45-54 yrs. 2002 45-54 yrs. 2002

2012 2012 35-44 yrs. 35-44 yrs. 35-44 yrs. 2002 35-44 yrs. 2002

2012 2012 less than less than less than less than 35 yrs. 2002 35 yrs. 2002 35 yrs. 35 yrs. 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% Quit time distribution (in %) Quit time distribution (in %)

Figure 8: Quit time distribution (by gender and aggregated age groups), 2002 and 2012 Note: SOEP waves 2002–2016. Unbalanced panel. Data weighted by expansion factors supplied in the data set.

Note that our data is not particularly well suited to investigate the success of quitting and thus probability of short-term relapse. Due to the structure of the SOEP data, in most cases, we can only observe the smoking status between two years. An unsuccessful quit attempt between the two waves remains unrevealed. Within the first year after quitting, other authors such as García-Rodríguez et al. (2014) find relapse rates of above 50 percent. This leads us to conclude that the shares of the QTD for the two categories “under 1 year” and “1 to under 2 years” could be underestimated.

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Depicting the QTD on a more granular level by gender and SES (Figure 9 in the Appendix), provides some additional insights. For example, young men (35 years or younger) with lower SES have the largest share of recent quitters (less than two years) among the four groups. Contrary to the finding that young men with lower SES are more recent quitters, the share of recent quitters for women in the same age is larger for higher SES. Comparing waves, it seems that for younger age groups the share of recent quitters (less than one or two years) is larger in 2012 than it is in 2002. This is especially true for men age 35 through 44 with higher SES, where we observe a visibly larger share of recent quitters in 2012 compared to 2002. Men with lower SES are the only exception to this rule, having a higher share of recent quitters in the 2002 wave. Nevertheless, apart from these observations, the overall QTD by gender, age and SES does not differ substantially from the one displaying only age and gender (Figure 8). In summary, we find that – although the smoking behavior varies significantly across socioeconomic groups – the probability of quitting is fairly homogenous across gender, age groups and birth cohorts. It seems that the main drivers for quitting are certain life events, the level of SES and the number of cigarettes smoked per day.

6. Conclusion In this paper, we provide a variety of descriptive statistics of people quitting smoking in Germany.We estimate the probability of quitting based on several variables of interest, most notably the SES. We find that smoking is on the decline, mostly due to former smokers’ quitting instead of lower smoking initiation. On a more detailed level, we see that the groups with the strongest decline in current smoking prevalence both show lower smoking initiation and higher quitting rates. A noteworthy example of such a group are young males of higher SES. Persons with higher SES stand out in our regression analysis by having a significantly higher probabilities of quitting compared to those with lower SES. In contrast, the group with lower SES shows constant or even increased current smoking prevalence between 2002 and 2016. It seems as if the drivers for a reduced smoking prevalence, namely tobacco control measures, health trends or less harmful alternatives, have not affected these groups in the same way as they did others. This is one explanation for a relatively modest decline of total smoking prevalence in Germany. On the other side, we find evidence from our regression analysis, that certain life events such as a marriage, an additional child in the household or a transition to non-working are strongly associated with higher quit rates. In summary, our paper mainly serves as a starting point for a more detailed research on quitting smoking. An especially promising area for such research is the relationship between quitting traditional tobacco products and switching to smoke-free products such as e-cigarettes, heat-not-burn products and other potentially less harmful alternatives. Switching to different products may in turn be an important factor for increasing the probability to quit smoking at all.

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García-Rodríguez, O., Secades-Villa, R., Flórez-Salamanca, L., Okuda, M., Liu, S. M., & Blanco, C. (2013). Probability and predictors of relapse to smoking: results of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Drug and alcohol dependence, 132(3), 479-485.

Hakulinen, C., Hintsanen, M., Munafò, M. R., Virtanen, M., Kivimäki, M., Batty, G. D., & Jokela, M. (2015). Personality and smoking: Individual‐participant meta‐analysis of nine cohort studies. Addiction, 110(11), 1844-1852.

Heilert, D., Kaul, A., (2017). Smoking Behaviour in Germany – Evidence from the SOEP. The German Socio-Economic Panel study, German Institute for Economic Research (DIW Berlin).

Hiscock, R., Bauld, L., Amos, A., Platt, S. (2012). Smoking and socioeconomic status in England: the rise of the never smoker and the disadvantaged smoker. Journal of Public Health, 34(3):390–396.

Kroh, M., Kühne, S., Siegers, R., Belcheva, V. (2018). SOEP-Core – Documentation of Sample Sizes and Panel Attrition (1984 until 2016). SOEP Survey Papers 480: Series C. Berlin: DIW/SOEP.

Krebsforschungszentrum, D. (2004). Rauchen und soziale Ungleichheit – Konsequenzen für die Tabakkontrollpolitik. Technical report, Deutsches Krebsforschungszentrum, Heidelberg.

Lee, P. N., Fry, J. S., Hamling, J. F., Sponsiello-Wang, Z., Baker, G., & Weitkunat, R. (2017). Estimating the effect of differing assumptions on the population health impact of introducing a Reduced Risk Tobacco Product in the USA. Regulatory Toxicology and Pharmacology, 88, 192-213.

Lee, J., T., Glantz, S., A., Millett, C. (2011). Effect of Smoke-Free Legislation on Adult Smoking Behaviour in England in the 18 Months following Implementation. PLoS ONE 6(6): e20933.

Nagelhout, G., E., Mons, U., Allwright, S., Guignard, R., Beck, F., Fong, G., T., De Vries, H., Willemsen, M., C., (2011). Prevalence and predictors of smoking in "smoke-free" bars. Findings from the International Tobacco Control (ITC) Europe Surveys. Soc Sci Med. 2011;72(10):1643-51.

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Owusu-Dabo, E., Lewis, S., McNeill, A., Gilmore, A., & Britton, J. (2011). Support for smoke-free policy, and awareness of tobacco health effects and use of smoking cessation therapy in a developing country. BMC Public Health, 11(1), 572.

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Schulze, A. and Lampert, T. (2006). Bundes-Gesundheitssurvey: soziale Unterschiede im Rauchverhalten und in der Passivrauchbelastung in Deutschland: Beiträge zur Gesundheitsberichterstattung des Bundes. Robert Koch-Institut, Berlin.

Statistisches Bundesamt (2017). Rückgang bei Zigaretten und Feinschnitt im Jahr 2016. Pressemitteilung vom 13. Januar 2017 – 014/17. https://www.destatis.de/DE/PresseService/Presse/Pressemitteilungen/2017/01/PD17_014_799pdf.pdf ?__blob=publicationFile

Westphal, C. and Doblhammer, G. (2012). The Diffusion of Smoking in East and West Germany: Smoking Patterns by Birth Year. Population (english edition), 67(4):653–670.

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8. Appendices A SES Indicators Table A1: Income group by SES level, 2012

Year Column Row lower SES higher SES SES total lower SES higher SES SES total In Per Cent Income groups 0 – 5,000 1.1 0.2 0.7 83.7 16.3 100.0 >5,000-10,000 5.4 1.6 3.5 77.5 22.5 100.0 >10,000-15,000 11.2 2.5 6.9 81.6 18.4 100.0 >15,000-20,000 15.7 4.0 9.9 79.5 20.5 100.0 >20,000-25,000 15.6 6.6 11.1 70.1 29.9 100.0 >25,000-30,000 14.0 7.5 10.8 65.1 34.9 100.0 >30,000-35,000 11.3 8.8 10.1 56.3 43.7 100.0 >35,000-40,000 6.7 10.4 8.5 39.1 60.9 100.0 >40,000-45,000 5.1 9.8 7.4 34.1 65.9 100.0 >45,000-50,000 3.9 8.8 6.3 30.7 69.3 100.0 >50,000-55,000 2.6 7.1 4.9 26.9 73.1 100.0 >55,000-60,000 2.2 6.4 4.3 25.5 74.5 100.0 >60,000-65,000 1.7 5.1 3.4 24.4 75.6 100.0 >65,000-70,000 1.0 4.0 2.5 19.4 80.7 100.0 >70,000-75,000 0.8 4.1 2.4 15.9 84.1 100.0 >75,000-80,000 0.4 2.6 1.5 13.8 86.2 100.0 >80,000-85,000 0.3 2.2 1.2 10.1 89.9 100.0

>85,000-90,000 0.3 1.7 1.0 13.4 86.6 100.0 >90,000-95,000 0.2 1.0 0.6 19.4 80.7 100.0 >95,000-100,000 0.2 1.0 0.6 16.0 84.0 100.0 >100,000-110,000 0.2 1.4 0.8 11.1 88.9 100.0 >110,000-120,000 0.1 0.7 0.4 11.0 89.0 100.0 >120,000-130,000 0.1 0.6 0.3 11.8 88.2 100.0 >130,000-140,000 0.0 0.5 0.3 6.0 94.0 100.0 >140,000-150,000 0.0 0.2 0.1 13.6 86.4 100.0 >150,000-175,000 0.1 0.5 0.3 20.3 79.7 100.0 >175,000-200,000 0.0 0.2 0.1 10.0 90.0 100.0 >200,000-225,000 0.0 0.1 0.0 12.5 87.5 100.0 >225,000-250,000 0.0 0.1 0.1 7.1 92.9 100.0 >250,000-300,000 0.0 0.2 0.1 5.9 94.1 100.0 >300,000-400,000 0.0 0.2 0.1 8.7 91.3 100.0 >400,000-500,000 0.0 0.0 0.0 20.0 80.0 100.0 >500,000 0.0 0.1 0.1 10.0 90.0 100.0 TOTAL 100.0 100.0 100.0 50.0 50.0 100.0 Note: The table shows net income per household. To calculate the SES, we use this variable in logs per capita.

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Table B1: Number of educational years by SES level, 2012

Year Column Row lower SES higher SES SES total lower SES higher SES SES total In Per Cent Groups of educational years 6-8.5 years 5.9 0.0 3.0 100.0 0.0 100.0 9-10 years 25.3 0.0 13.0 100.0 0.0 100.0 10.5-11 years 50.2 0.4 26.0 99.4 0.7 100.0 11.5-12 years 18.3 37.3 27.5 34.3 65.7 100.0 13-16 years 0.4 36.8 18.0 1.0 99.0 100.0 17-18 years 0.0 25.6 12.4 0.0 100.0 100.0 TOTAL 100.0 100.0 100.0 51.5 48.5 100.0 Note: The table shows educational years per capita. Groups correspond to the following degree: Years of education Degree 6 -8.5 years: 100% no degree 9 -10 years: ~89% lower secondary school (66%) or secondary school without vocational training (23%) 10.5 - 11 years: ~100% lower secondary school with vocational training 11.5 - 12 years: ~90% secondary school with vocational training 13 - 16 years: ~90% tech. college certification w/o vocational training (43%) or tech. college degree (47%) 17-18 years: 100% university degree

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B Smoking Prevalence Table B1: Smoking prevalence by gender and age group

Year 2002 2004 2006 2008 2010 2012 2014 2016 In Per Cent All 30.4 29.7 29.8 28.2 27.3 27.2 26.8 25.6 Women 25.0 24.8 26.0 24.2 24.0 24.0 23.1 22.3 Men 36.0 34.9 33.9 32.4 30.8 30.5 30.8 29.2 Age groups 18-19* ------20-24 43.7 43.4 43.4 37.8 32.7 32.6 29.4 24.7 25-29 39.9 40.4 38.3 38.4 40.2 36.9 32.7 28.1 30-34 39.4 37.5 37.5 38.0 34.3 34.4 33.8 32.3 35-39 40.6 37.4 37.2 32.3 29.6 32.3 32.3 31.5 40-44 39.2 42.2 40.2 36.4 33.9 32.8 32.4 33.2 45-49 43.1 38.7 37.8 34.9 37.2 35.6 34.2 33.1 50-54 33.2 34.8 38.2 37.9 35.6 35.2 33.3 32.2 55-59 26.7 28.7 26.5 30.8 31.5 31.2 34.3 31.7 60-64 20.7 20.8 21.4 21.3 24.0 24.8 28.7 27.4 65-69 14.3 15.2 15.5 16.8 15.9 18.4 19.4 19.6 70-74 12.9 11.0 11.1 11.8 12.0 12.6 13.3 15.1 75-79 8.8 9.7 10.6 7.5 8.2 9.1 9.1 8.9 ≥ 80 3.5 5.1 6.3 6.5 5.6 5.8 4.7 4.3 Note: Age group 18-19 is omitted due to insufficient number of observations.

Table B2: SES All

Year 2002 2004 2006 2008 2010 2012 2014 2016 SES In Per Cent Lower 32.0 31.3 33.0 32.2 31.4 31.0 31.7 30.7 Higher 28.2 27.7 25.8 23.0 22.1 22.7 21.3 20.0

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Table B3: Lower SES, Women

Year

2002 2004 2006 2008 2010 2012 2014 2016 Age groups In Per Cent 18-19* ------20-24 50.1 46.9 46.8 45.2 46.9 37.8 37.1 25.1 25-29 39.9 43.3 47.2 45.0 51.0 44.3 41.4 41.2 30-34 42.3 38.7 39.5 44.0 40.2 42.4 47.2 42.5 35-39 50.8 46.3 52.5 37.7 37.4 38.1 42.2 39.7 40-44 47.4 49.3 55.0 44.7 39.4 35.8 39.2 39.4 45-49 43.0 38.4 47.5 46.3 51.4 49.3 45.4 39.0 50-54 32.7 34.9 35.9 37.1 36.4 43.6 40.7 40.3 55-59 25.2 26.9 26.7 30.9 32.9 33.1 38.4 42.6 60-64 17.0 16.4 18.5 21.4 22.0 24.9 29.5 23.8 65-69 8.2 10.3 14.2 17.2 15.6 16.7 17.0 19.4 70-74 8.7 7.1 7.2 10.3 13.3 13.8 15.8 15.3 75-79 5.5 7.5 7.1 5.9 4.6 6.9 7.5 8.8 ≥ 80 2.8 3.2 5.2 4.0 4.4 3.9 3.6 2.0 Note: Age group 18-19 is omitted due to insufficient number of observations.

Table B4: Higher SES, Women

Year 2002 2004 2006 2008 2010 2012 2014 2016 Age groups In Per Cent 18-19* ------20-24 26.4 32.0 28.7 22.8 15.2 23.5 14.1 11.6 25-29 26.1 31.9 25.1 27.4 21.4 24.6 19.4 21.4 30-34 26.3 19.2 22.3 21.4 22.9 23.1 18.9 17.7 35-39 28.3 28.8 23.4 17.7 13.2 20.0 20.5 20.2 40-44 29.0 35.0 31.4 29.9 24.4 24.1 19.0 23.4 45-49 29.1 28.2 24.8 24.2 25.3 23.7 24.7 20.4 50-54 22.9 23.4 26.9 25.6 24.5 22.7 22.5 21.2 55-59 20.6 19.2 19.5 18.4 21.8 21.0 20.7 18.2 60-64 16.0 16.0 16.6 12.7 15.8 15.2 17.8 19.2 65-69 12.4 13.8 14.0 10.5 9.2 13.0 13.3 14.9 70-74 14.3 7.4 13.3 9.9 8.5 7.1 10.2 10.7 75-79 11.0 15.6 10.2 1.8 7.6 13.5 12.0 5.0 ≥ 80 6.1 5.7 8.8 8.9 4.6 2.8 2.9 6.6 Note: Age group 18-19 is omitted due to insufficient number of observations.

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Table B5: Lower SES, Men

Year 2002 2004 2006 2008 2010 2012 2014 2016 Age groups In Per Cent 18-19* ------20-24 55.1 52.7 56.7 48.0 41.3 46.2 45.0 41.8 25-29 56.7 55.6 51.7 55.8 57.2 56.9 55.1 44.1 30-34 57.2 62.1 60.5 59.1 50.2 56.4 55.2 53.3 35-39 54.9 51.4 51.5 56.1 51.6 51.1 53.2 47.6 40-44 54.6 52.1 51.6 49.5 49.6 47.9 48.3 47.4 45-49 57.4 53.5 51.6 47.5 48.5 46.1 46.1 47.7 50-54 43.9 47.0 54.4 53.0 53.8 44.5 42.8 45.2 55-59 31.9 34.7 31.5 44.1 41.2 42.5 47.7 36.1 60-64 27.7 31.1 27.5 25.8 29.8 31.7 36.2 39.9 65-69 20.8 21.1 18.2 22.6 21.4 21.8 24.4 24.1 70-74 18.6 16.3 15.8 15.9 14.6 13.6 13.5 19.6 75-79 11.0 8.9 13.9 11.2 12.1 11.8 12.7 11.9 ≥ 80 4.6 7.5 7.3 10.3 8.3 8.3 8.1 6.5 Note: Age group 18-19 is omitted due to insufficient number of observations.

Table B6: Higher SES, Men

Year 2002 2004 2006 2008 2010 2012 2014 2016 Age groups In Per Cent 18-19* ------20-24 38.9 37.7 32.6 31.2 21.0 24.7 23.5 20.0 25-29 38.0 35.5 34.6 28.3 38.5 29.0 24.6 18.8 30-34 38.9 39.0 33.2 33.5 31.6 28.5 27.5 24.3 35-39 36.4 31.1 32.0 26.8 29.7 28.6 24.5 25.1 40-44 32.1 36.5 30.7 25.9 27.7 29.4 31.1 29.6 45-49 42.8 36.7 31.6 26.0 27.8 28.4 25.8 28.5 50-54 30.6 31.8 34.3 34.4 28.3 34.1 29.1 23.2 55-59 26.7 30.7 25.5 24.6 25.7 25.3 29.2 28.4 60-64 19.8 15.5 20.6 21.6 25.6 21.1 26.7 21.1 65-69 17.6 16.3 14.7 12.2 13.2 20.1 20.5 16.7 70-74 11.8 13.4 11.7 10.0 6.9 12.7 10.9 12.3 75-79 17.3 13.5 14.2 8.2 10.8 7.7 5.2 7.7 ≥ 80 3.0 10.6 7.9 9.8 5.9 8.5 4.4 7.1 Note: Age group 18-19 is omitted due to insufficient number of observations.

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C Population split between never, former, and current smokers Table C1: 2002

Smoking Behavior Never Smoker Former Smoker Current Smoker In Per Cent All 45.0 24.5 30.5 Women 56.1 18.9 25.1 Men 33.5 30.3 36.1 Age groups 18-19* - - - 20-24 42.6 13.6 43.8 25-29 45.5 14.5 40.0 30-34 42.1 18.3 39.7 35-39 38.4 20.9 40.7 40-44 36.1 24.6 39.3 45-49 32.4 24.3 43.3 50-54 38.6 28.1 33.3 55-59 42.9 30.4 26.7 60-64 47.6 31.7 20.7 65-69 56.8 28.9 14.3 70-74 53.2 33.9 12.9 75-79 62.2 29.0 8.8 ≥ 80 69.5 27.0 3.5 Note: Age group 18-19 is omitted due to insufficient number of observations.

Table C2: SES, 2002

Smoking Behavior Never Smoker Former Smoker Current Smoker In Per Cent All 45.0 24.5 30.5 Lower 45.6 22.4 32.0 Higher 44.6 27.2 28.2

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- 25 - Quitting Tobacco in Germany – Evidence from the SOEP

Table C3: Lower SES, Women 2002

Smoking Behavior Never Smoker Former Smoker Current Smoker Age groups In Per Cent 18-19* - - - 20-24 39.6 10.2 50.2 25-29 46.4 13.5 40.1 30-34 37.7 19.7 42.7 35-39 32.9 16.2 50.9 40-44 35.4 17.1 47.5 45-49 35.7 21.3 43.0 50-54 46.5 20.7 32.8 55-59 59.7 15.0 25.3 60-64 69.4 13.6 17.0 65-69 77.7 14.1 8.2 70-74 76.1 15.2 8.7 75-79 79.7 14.8 5.5 ≥ 80 82.0 15.2 2.8 Note: Age group 18-19 is omitted due to insufficient number of observations.

Table C4: Higher SES, Women 2002

Smoking Behavior Never Smoker Former Smoker Current Smoker Age groups In Per Cent 18-19* - - - 20-24 51.2 22.3 26.4 25-29 58.4 15.5 26.1 30-34 53.8 19.7 26.5 35-39 48.1 23.4 28.5 40-44 42.0 28.9 29.2 45-49 43.9 26.7 29.3 50-54 52.6 24.5 22.9 55-59 53.2 26.1 20.7 60-64 60.6 23.4 16.0 65-69 61.5 26.1 12.4 70-74 56.5 29.2 14.3 75-79 65.7 23.2 11.1 ≥ 80 76.2 17.7 6.1 Note: Age group 18-19 is omitted due to insufficient number of observations.

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- 26 - Quitting Tobacco in Germany – Evidence from the SOEP

Table C5: Lower SES, Men 2002

Smoking Behavior Never Smoker Former Smoker Current Smoker Age groups In Per Cent 18-19* - - - 20-24 33.3 11.4 55.3 25-29 27.8 15.4 56.8 30-34 25.5 17.0 57.6 35-39 27.8 17.4 54.9 40-44 25.8 19.2 55.0 45-49 22.6 19.6 57.8 50-54 24.7 31.3 43.9 55-59 29.2 39.0 31.9 60-64 26.1 46.2 27.7 65-69 39.0 40.2 20.8 70-74 29.9 51.5 18.6 75-79 36.9 52.0 11.1 ≥ 80 39.1 56.3 4.6 Note: Age group 18-19 is omitted due to insufficient number of observations.

Table C6: Higher SES, Men 2002

Smoking Behavior Never Smoker Former Smoker Current Smoker Age groups In Per Cent 18-19* - - - 20-24 49.8 11.1 39.2 25-29 48.3 13.6 38.0 30-34 44.5 16.6 38.9 35-39 39.7 23.9 36.4 40-44 38.6 29.3 32.1 45-49 27.8 29.2 42.9 50-54 31.9 37.5 30.6 55-59 29.8 43.6 26.7 60-64 30.0 50.2 19.9 65-69 36.0 46.3 17.7 70-74 32.0 56.2 11.8 75-79 33.7 49.1 17.3 ≥ 80 43.1 53.9 3.0 Note: Age group 18-19 is omitted due to insufficient number of observations.

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- 27 - Quitting Tobacco in Germany – Evidence from the SOEP

Table C7: 2012

Smoking Behavior Never Smoker Former Smoker Current Smoker In Per Cent All 45.5 29.0 25.4 Women 52.7 23.6 23.6 Men 36.3 33.7 30.0 Age groups 18-19* - - - 20-24 55.9 14.1 30.1 25-29 49.2 15.8 35.0 30-34 41.0 25.3 33.7 35-39 43.4 24.1 32.5 40-44 44.1 23.7 32.2 45-49 38.0 26.3 35.6 50-54 33.7 31.6 34.7 55-59 33.7 35.1 31.2 60-64 39.1 36.3 24.6 65-69 45.6 35.6 18.8 70-74 51.3 35.5 13.2 75-79 56.8 33.8 9.4 ≥ 80 58.4 35.4 6.2 Note: Age group 18-19 is omitted due to insufficient number of observations.

Table C8: SES, 2012

Smoking Behavior Never Smoker Former Smoker Current Smoker In Per Cent All 45.5 29.0 25.4 Lower 42.9 26.7 30.4 Higher 46.9 30.7 22.4

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- 28 - Quitting Tobacco in Germany – Evidence from the SOEP

Table C9: Lower SES, Women 2012

Smoking Behavior Never Smoker Former Smoker Current Smoker Age groups In Per Cent 18-19* - - - 20-24 42.6 22.3 35.1 25-29 35.9 21.5 42.5 30-34 28.0 27.8 44.2 35-39 43.1 16.7 40.3 40-44 41.9 21.7 36.4 45-49 30.5 21.4 48.1 50-54 32.0 24.9 43.1 55-59 40.0 28.3 31.6 60-64 51.1 24.7 24.2 65-69 61.8 21.6 16.5 70-74 68.8 17.0 14.1 75-79 76.0 17.0 6.9 ≥ 80 79.7 16.0 4.3 Note: Age group 18-19 is omitted due to insufficient number of observations.

Table C10: Higher SES, Women 2012

Smoking Behavior Never Smoker Former Smoker Current Smoker Age groups In Per Cent 18-19* - - - 20-24 66.2 11.9 21.9 25-29 58.6 18.9 22.6 30-34 52.0 25.8 22.2 35-39 54.2 23.4 22.3 40-44 57.1 20.8 22.1 45-49 46.4 30.4 23.2 50-54 42.6 34.8 22.6 55-59 42.5 35.6 21.9 60-64 51.9 32.5 15.6 65-69 54.5 30.9 14.7 70-74 64.7 28.8 6.5 75-79 53.4 31.1 15.5 ≥ 80 60.3 36.6 3.1 Note: Age group 18-19 is omitted due to insufficient number of observations.

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- 29 - Quitting Tobacco in Germany – Evidence from the SOEP

Table C11: Lower SES, Men 2012

Smoking Behavior Never Smoker Former Smoker Current Smoker Age groups In Per Cent 18-19* - - - 20-24 49.8 7.4 42.8 25-29 42.6 4.9 52.6 30-34 24.4 21.1 54.5 35-39 23.5 27.9 48.5 40-44 25.8 25.8 48.4 45-49 31.9 20.9 47.3 50-54 26.5 29.6 43.9 55-59 19.4 36.7 43.9 60-64 20.9 46.5 32.6 65-69 34.6 43.6 21.8 70-74 34.2 50.7 15.1 75-79 38.7 49.6 11.7 ≥ 80 36.9 54.7 8.5 Note: Age group 18-19 is omitted due to insufficient number of observations.

Table C12: Higher SES, Men 2012

Smoking Behavior Never Smoker Former Smoker Current Smoker Age groups In Per Cent 18-19* - - - 20-24 59.6 17.4 23.0 25-29 53.1 16.2 30.7 30-34 46.7 25.7 27.6 35-39 44.1 29.2 26.6 40-44 44.5 26.8 28.7 45-49 40.5 30.8 28.7 50-54 30.9 35.5 33.6 55-59 33.1 42.0 24.9 60-64 35.9 43.7 20.4 65-69 30.4 48.6 21.0 70-74 32.3 54.3 13.4 75-79 43.2 48.3 8.5 ≥ 80 33.5 57.1 9.4 Note: Age group 18-19 is omitted due to insufficient number of observations.

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- 30 - Quitting Tobacco in Germany – Evidence from the SOEP

D Quit Time Distribution Table D1: Gender, 2002

Quit Time Distribution All Men Women In Per Cent under 1 year 11.0 9.6 13.7 1 to under 2 years 7.0 6.2 8.3 2 to under 3 years 5.9 5.7 6.3 3 to under 6 years 11.5 10.5 13.1 6 to under 11 years 13.2 12.6 14.3 11 to under 16 years 14.7 15.4 13.5 16 to under 21 years 10.7 10.4 11.1 21 to under 31 years 16.8 18.1 14.6 31 to under 41 years 6.9 8.5 4.1 41 to under 51 years 1.9 2.6 0.7 51 or more years 0.4 0.5 0.2

Table D2: Age, 2002

under 41 yearsunder under 1 year 2 years under 1 to 3 years under 2 to 6 years under 3 to years 11 under 6 to 16 years under 11 to 21 years under 16 to 31 years under 21 to 31 to 51 years under 41 to years more 51 or

In Per Cent Age Groups 18-19* ------20-24 42.1 24.3 9.8 22.9 1.0 0.0 0.0 0.0 0.0 0.0 0.0 25-29 32.7 17.9 10.2 30.2 5.8 3.2 0.0 0.0 0.0 0.0 0.0 30-34 17.8 18.6 14.2 21.6 17.9 9.4 0.4 0.0 0.0 0.0 0.0 35-39 14.8 10.0 11.3 16.7 23.2 16.5 6.2 1.2 0.0 0.0 0.0 40-44 14.7 9.1 5.1 11.4 16.1 21.8 11.6 10.2 0.0 0.0 0.0 45-49 11.6 8.0 6.2 10.6 14.2 19.7 17.8 11.7 0.2 0.0 0.0 50-54 8.9 4.5 6.4 13.8 15.3 17.3 15.3 16.5 2.0 0.0 0.0 55-59 7.2 2.3 5.7 7.7 15.1 12.8 13.2 24.1 12.0 0.0 0.0 60-64 6.4 2.4 3.8 9.8 9.8 17.3 11.3 26.7 12.5 0.2 0.0 65-69 5.2 4.8 2.5 6.4 13.1 15.7 9.0 23.7 16.8 2.7 0.0 70-74 4.1 4.4 3.2 7.1 6.7 14.2 10.0 29.2 13.9 6.8 0.3 75-79 3.5 0.7 2.3 5.7 13.3 9.6 13.5 24.6 13.7 12.7 0.5 ≥ 80 0.0 2.0 1.0 1.9 5.8 6.7 17.1 36.2 12.7 8.2 8.3 Note: Age group 18-19 is omitted due to insufficient number of observations.

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Table D3: Age and gender, 2002

under 1 year 2 years under 1 to 3 years under 2 to 6 years under 3 to years 11 under 6 to 16 years under 11 to 21 years under 16 to 31 years under 21 to 41 years under 31 to 51 years under 41 to years more 51 or

In Per Cent All 11.0 7.0 5.9 11.5 13.2 14.7 10.7 16.8 6.9 1.9 0.4 Women 18-19* ------20-24 39.8 21.6 10.9 26.1 1.7 0.0 0.0 0.0 0.0 0.0 0.0 25-29 36.2 18.1 10.6 21.6 8.8 4.7 0.0 0.0 0.0 0.0 0.0 30-34 19.5 10.1 11.2 25.5 26.6 6.9 0.2 0.0 0.0 0.0 0.0 35-39 10.9 11.6 13.0 17.5 21.3 14.6 11.1 0.0 0.0 0.0 0.0 40-44 16.1 9.0 4.8 11.7 13.2 18.6 11.8 14.8 0.0 0.0 0.0 45-49 7.8 9.5 5.1 9.7 12.8 20.1 19.4 15.6 0.0 0.0 0.0 50-54 11.2 5.8 5.2 7.8 17.2 16.7 16.9 18.0 1.3 0.0 0.0 55-59 16.7 2.0 1.6 6.9 12.5 14.0 10.5 22.2 13.6 0.0 0.0 60-64 10.0 2.6 0.6 9.2 17.3 17.0 8.8 19.0 15.7 0.0 0.0 65-69 6.5 9.8 4.2 13.5 9.8 15.5 3.5 22.7 13.3 1.2 0.0 70-74 6.1 4.0 7.0 6.2 4.7 11.6 15.2 33.5 8.1 3.7 0.0 75-79 4.1 2.0 4.5 15.3 17.3 7.5 15.2 21.2 6.1 6.8 0.0 ≥ 80 0.0 0.0 2.9 2.7 10.3 6.2 29.1 39.6 3.4 0.0 5.7 Men 18-19* ------20-24 45.7 28.5 8.0 17.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 25-29 28.6 17.7 9.8 40.2 2.3 1.4 0.0 0.0 0.0 0.0 0.0 30-34 16.3 26.4 17.0 18.0 9.9 11.8 0.6 0.0 0.0 0.0 0.0 35-39 18.3 8.5 9.9 16.0 25.0 18.2 1.9 2.3 0.0 0.0 0.0 40-44 13.4 9.2 5.3 11.2 18.5 24.5 11.4 6.4 0.0 0.0 0.0 45-49 15.1 6.5 7.3 11.5 15.5 19.4 16.4 8.1 0.3 0.0 0.0 50-54 7.5 3.8 7.1 17.5 14.2 17.6 14.4 15.5 2.4 0.0 0.0 55-59 3.9 2.4 7.1 8.0 15.9 12.3 14.1 24.8 11.5 0.0 0.0 60-64 5.2 2.3 4.8 10.0 7.3 17.4 12.2 29.2 11.4 0.2 0.0 65-69 4.6 2.7 1.8 3.4 14.5 15.8 11.4 24.1 18.4 3.3 0.0 70-74 3.4 4.5 1.9 7.4 7.5 15.2 8.2 27.7 16.0 7.9 0.4 75-79 3.2 0.0 1.1 0.5 11.1 10.7 12.5 26.4 17.8 15.9 0.8 ≥ 80 0.0 3.0 0.0 1.5 3.5 7.0 10.9 34.4 17.5 12.5 9.6 Note: Age group 18-19 is omitted due to insufficient number of observations.

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Table D4: Lower SES, 2002

under 31 yearsunder under 1 year 2 years under 1 to 3 years under 2 to 6 years under 3 to years 11 under 6 to 16 years under 11 to 21 years under 16 to 21 to 41 years under 31 to 51 years under 41 to years more 51 or

In Per Cent All 11.8 5.7 5.7 10.9 13.9 14.0 10.1 17.7 7.7 2.2 0.3 Women 18-19* ------20-24 42.1 24.3 9.8 22.9 1.0 0.0 0.0 0.0 0.0 0.0 0.0 25-29 32.7 17.9 10.2 30.2 5.8 3.2 0.0 0.0 0.0 0.0 0.0 30-34 17.8 18.6 14.2 21.6 17.9 9.4 0.4 0.0 0.0 0.0 0.0 35-39 14.8 10.0 11.3 16.7 23.2 16.5 6.2 1.2 0.0 0.0 0.0 40-44 14.7 9.1 5.1 11.4 16.1 21.8 11.6 10.2 0.0 0.0 0.0 45-49 11.6 8.0 6.2 10.6 14.2 19.7 17.8 11.7 0.2 0.0 0.0 50-54 8.9 4.5 6.4 13.8 15.3 17.3 15.3 16.5 2.0 0.0 0.0 55-59 7.2 2.3 5.7 7.7 15.1 12.8 13.2 24.1 12.0 0.0 0.0 60-64 6.4 2.4 3.8 9.8 9.8 17.3 11.3 26.7 12.5 0.2 0.0 65-69 5.2 4.8 2.5 6.4 13.1 15.7 9.0 23.7 16.8 2.7 0.0 70-74 4.1 4.4 3.2 7.1 6.7 14.2 10.0 29.2 13.9 6.8 0.3 75-79 3.5 0.7 2.3 5.7 13.3 9.6 13.5 24.6 13.7 12.7 0.5 ≥ 80 0.0 2.0 1.0 1.9 5.8 6.7 17.1 36.2 12.7 8.2 8.3 Men 18-19* ------20-24 51.1 29.3 12.4 7.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 25-29 41.8 19.9 3.4 34.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30-34 19.5 22.0 14.7 14.2 7.6 22.0 0.0 0.0 0.0 0.0 0.0 35-39 29.4 10.2 12.1 12.6 22.2 11.6 2.0 0.0 0.0 0.0 0.0 40-44 19.1 12.9 2.4 12.3 22.7 14.3 12.0 4.4 0.0 0.0 0.0 45-49 14.2 5.4 13.3 7.0 17.0 24.7 5.7 11.9 0.8 0.0 0.0 50-54 9.1 2.5 10.7 23.9 13.8 15.5 7.4 15.4 1.8 0.0 0.0 55-59 4.2 2.7 8.5 11.4 17.8 11.7 15.5 17.3 10.8 0.0 0.0 60-64 5.6 1.2 5.2 11.5 8.0 13.9 13.0 29.4 12.1 0.2 0.0 65-69 5.2 4.0 0.9 3.5 16.6 15.8 13.4 21.3 16.6 2.7 0.0 70-74 5.0 3.3 2.6 7.6 10.1 16.2 6.5 28.4 13.8 5.8 0.6 75-79 4.6 0.0 0.6 0.4 11.4 12.6 12.4 22.6 19.6 15.7 0.0 ≥ 80 0.0 2.7 0.0 2.2 4.4 9.2 9.7 39.3 16.8 10.2 5.6 Note: Age group 18-19 is omitted due to insufficient number of observations.

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Table D5: Higher SES, 2002

In Per Cent All 10.0 8.3 6.2 12.2 12.6 15.6 11.4 15.9 6.0 1.6 0.4 Women 18-19* ------20-24 44.9 26.0 9.3 18.4 1.4 0.0 0.0 0.0 0.0 0.0 0.0 25-29 46.3 16.4 15.6 13.9 0.1 7.7 0.0 0.0 0.0 0.0 0.0 30-34 9.8 15.6 10.7 30.6 28.3 5.0 0.0 0.0 0.0 0.0 0.0 35-39 11.2 12.7 10.3 19.6 18.2 17.0 11.0 0.0 0.0 0.0 0.0 40-44 12.6 8.7 4.7 13.7 13.2 21.5 14.5 11.1 0.0 0.0 0.0 45-49 7.3 4.9 4.3 10.8 12.7 21.6 19.5 19.1 0.0 0.0 0.0 50-54 10.3 5.4 4.1 12.2 7.9 14.4 20.4 23.9 1.3 0.0 0.0 55-59 7.8 1.7 3.1 7.2 13.5 5.5 7.5 35.7 18.1 0.0 0.0 60-64 6.1 6.8 0.0 7.3 17.6 6.7 8.4 22.1 24.9 0.0 0.0 65-69 0.8 27.2 0.0 10.3 2.0 13.0 1.1 21.9 23.6 0.0 0.0 70-74 0.0 0.0 15.6 0.0 0.7 15.2 20.1 40.9 0.0 7.4 0.0 75-79 0.0 0.0 12.8 0.0 14.5 0.0 12.6 35.2 17.2 7.7 0.0 ≥ 80 0.0 0.0 17.9 0.0 0.0 2.2 31.7 38.5 0.0 0.0 9.7 Men 18-19* ------20-24 38.7 27.4 2.4 31.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 25-29 10.7 14.7 18.5 47.5 5.4 3.2 0.0 0.0 0.0 0.0 0.0 30-34 13.7 30.2 18.9 21.2 11.8 3.2 1.0 0.0 0.0 0.0 0.0 35-39 12.2 7.5 8.7 17.8 26.5 21.8 1.9 3.5 0.0 0.0 0.0 40-44 10.7 7.4 6.8 10.7 16.5 29.4 11.1 7.3 0.0 0.0 0.0 45-49 15.7 7.2 3.5 14.3 14.5 16.1 23.0 5.8 0.0 0.0 0.0 50-54 5.8 5.1 3.2 10.7 14.5 19.9 21.9 15.7 3.2 0.0 0.0 55-59 3.3 1.9 4.8 2.7 13.0 13.3 11.9 36.4 12.6 0.0 0.0 60-64 4.5 4.2 4.2 7.7 6.1 22.8 10.8 29.0 10.4 0.2 0.0 65-69 3.4 0.2 3.4 3.4 10.2 15.9 7.5 29.6 21.9 4.5 0.0 70-74 0.0 6.9 0.4 7.1 1.9 13.0 11.6 26.3 20.6 12.1 0.0 75-79 0.0 0.0 2.3 0.8 10.4 6.4 12.8 35.0 13.5 16.1 2.5 ≥ 80 0.0 3.8 0.0 0.0 1.3 1.7 13.9 22.2 19.4 18.3 19.4 Note: Age group 18-19 is omitted due to insufficient number of observations.

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- 34 - Quitting Tobacco in Germany – Evidence from the SOEP

Table D6: Gender, 2012

Quit Time Distribution All Women Men In Per Cent under 1 year 8.9 8.5 9.6 1 to under 2 years 5.2 4.3 6.5 2 to under 3 years 3.7 3.5 4.1 3 to under 6 years 9.3 7.3 12.2 6 to under 11 years 15.0 13.8 16.8 11 to under 16 years 12.9 13.4 12.1 16 to under 21 years 8.6 8.6 8.7 21 to under 31 years 18.2 19.6 16.2 31 to under 41 years 11.5 13.1 9.1 41 to under 51 years 4.8 5.4 3.9 51 or more years 1.8 2.4 0.8

Table D7: Age, 2012

In Per Cent 18-19* ------20-24 51.6 12.1 15.8 18.6 1.9 0.0 0.0 0.0 0.0 0.0 0.0 25-29 30.7 12.7 10.0 29.9 12.6 4.2 0.0 0.0 0.0 0.0 0.0 30-34 23.1 14.1 9.3 17.4 29.6 6.4 0.1 0.0 0.0 0.0 0.0 35-39 19.2 5.5 3.8 19.6 31.5 18.2 2.0 0.2 0.0 0.0 0.0 40-44 10.0 7.7 3.7 15.2 20.6 21.8 11.7 9.2 0.0 0.0 0.0 45-49 7.8 9.9 2.9 7.9 19.2 13.6 15.4 23.1 0.2 0.0 0.0 50-54 9.7 4.7 2.9 8.0 19.5 15.3 8.3 27.4 4.2 0.0 0.0 55-59 4.6 2.2 3.7 7.6 12.1 16.3 8.7 29.0 14.9 0.8 0.0 60-64 3.7 3.6 3.7 5.6 13.4 14.4 10.6 22.4 20.9 1.9 0.0 65-69 4.3 1.1 3.3 4.5 9.9 12.4 10.5 23.2 20.9 9.9 0.0 70-74 1.8 1.8 1.8 5.3 10.5 10.6 9.0 16.6 24.8 16.2 1.6 75-79 0.5 0.5 1.4 5.6 6.5 10.3 13.7 21.7 18.5 16.4 4.9 ≥ 80 0.7 1.1 0.5 2.2 2.9 8.2 6.9 25.4 20.9 11.6 19.7 Note: Age group 18-19 is omitted due to insufficient number of observations.

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Table D8: Age and gender, 2012

In Per Cent All 8.9 5.2 3.7 9.3 15.0 12.9 8.6 18.2 11.5 4.8 1.8 Women 18-19* ------20-24 41.1 16.4 22.0 19.0 1.5 0.0 0.0 0.0 0.0 0.0 0.0 25-29 33.5 12.1 14.5 26.0 7.4 6.4 0.0 0.0 0.0 0.0 0.0 30-34 18.6 16.6 6.8 18.5 33.5 5.8 0.2 0.0 0.0 0.0 0.0 35-39 21.4 4.7 2.6 21.4 32.4 14.8 2.6 0.0 0.0 0.0 0.0 40-44 1.8 5.2 0.9 17.8 28.9 24.0 12.7 8.8 0.0 0.0 0.0 45-49 5.2 10.2 2.4 8.0 18.2 17.1 17.0 21.8 0.0 0.0 0.0 50-54 8.1 2.0 0.6 12.0 19.1 16.0 10.7 26.8 4.7 0.0 0.0 55-59 4.6 1.2 4.6 9.2 12.9 13.0 10.2 21.1 22.0 1.2 0.0 60-64 1.6 8.3 1.4 8.8 10.8 8.6 11.3 26.1 22.2 0.8 0.0 65-69 6.3 2.0 4.9 5.2 14.1 6.4 6.4 24.7 15.6 14.5 0.0 70-74 1.6 0.3 2.0 7.6 7.4 14.3 5.2 19.5 18.5 23.6 0.0 75-79 1.2 0.0 3.9 2.3 5.7 7.9 28.3 20.8 14.1 15.2 0.7 ≥ 80 2.3 3.9 0.0 6.5 2.7 11.7 1.6 25.6 21.0 7.3 17.4 Men 18-19* ------20-24 72.7 3.4 3.4 17.7 2.9 0.0 0.0 0.0 0.0 0.0 0.0 25-29 25.1 13.7 1.1 37.4 22.7 0.0 0.0 0.0 0.0 0.0 0.0 30-34 29.4 10.7 12.6 15.8 24.2 7.3 0.0 0.0 0.0 0.0 0.0 35-39 16.8 6.3 5.1 17.7 30.6 21.6 1.3 0.5 0.0 0.0 0.0 40-44 15.7 9.5 5.6 13.4 14.8 20.4 11.0 9.5 0.0 0.0 0.0 45-49 10.0 9.7 3.3 7.8 20.0 10.7 14.0 24.3 0.4 0.0 0.0 50-54 11.1 7.3 5.0 4.3 19.9 14.6 6.1 28.0 3.8 0.0 0.0 55-59 4.6 3.0 3.0 6.5 11.4 18.8 7.6 35.0 9.5 0.5 0.0 60-64 4.8 1.1 4.8 3.9 14.7 17.4 10.3 20.4 20.2 2.4 0.0 65-69 3.4 0.7 2.5 4.2 8.0 15.1 12.4 22.5 23.3 7.8 0.0 70-74 1.9 2.3 1.7 4.5 11.6 9.3 10.3 15.5 27.0 13.7 2.1 75-79 0.3 0.7 0.4 6.9 6.8 11.3 7.6 22.1 20.4 16.9 6.7 ≥ 80 0.0 0.0 0.7 0.6 3.0 6.7 9.0 25.3 20.9 13.3 20.6 Note: Age group 18-19 is omitted due to insufficient number of observations.

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Table D9: Lower SES, 2012

In Per Cent All 7.4 4.3 4.3 8.6 13.6 13.3 9.9 19.8 11.2 5.6 2.0 Women 18-19* ------20-24 27.8 24.2 33.8 11.7 2.6 0.0 0.0 0.0 0.0 0.0 0.0 25-29 16.2 17.6 19.1 40.3 3.3 3.5 0.0 0.0 0.0 0.0 0.0 30-34 17.8 12.0 10.7 25.2 23.4 10.9 0.0 0.0 0.0 0.0 0.0 35-39 28.6 2.8 0.0 27.4 13.9 23.5 3.9 0.0 0.0 0.0 0.0 40-44 0.7 4.3 0.7 20.4 28.4 22.2 13.7 9.5 0.0 0.0 0.0 45-49 0.6 10.2 0.9 10.7 20.4 5.2 24.6 27.4 0.0 0.0 0.0 50-54 15.1 2.0 2.1 10.9 18.6 12.6 3.7 28.2 6.9 0.0 0.0 55-59 3.3 0.9 7.5 10.3 10.2 15.7 14.2 20.8 15.6 1.7 0.0 60-64 1.8 10.1 2.1 7.7 11.9 9.3 9.6 22.7 23.6 1.2 0.0 65-69 11.1 3.2 1.1 6.4 13.8 9.0 5.9 25.5 7.4 16.6 0.0 70-74 2.7 0.4 2.4 12.1 9.2 6.0 5.1 25.1 19.9 17.1 0.0 75-79 0.7 0.0 2.9 3.1 7.6 5.7 34.1 17.9 14.1 12.9 0.9 ≥ 80 0.0 3.1 0.0 8.0 4.1 6.6 2.5 29.8 21.8 7.4 16.6 Men 18-19* ------20-24 65.8 0.0 0.0 34.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 25-29 42.0 2.2 5.3 11.4 39.1 0.0 0.0 0.0 0.0 0.0 0.0 30-34 43.9 3.5 6.6 23.0 13.8 9.3 0.0 0.0 0.0 0.0 0.0 35-39 18.6 3.4 6.3 13.8 26.4 28.9 2.6 0.0 0.0 0.0 0.0 40-44 10.4 2.4 11.5 8.5 19.4 26.4 11.3 10.1 0.0 0.0 0.0 45-49 16.2 7.4 3.9 6.4 15.0 10.5 12.0 28.5 0.0 0.0 0.0 50-54 9.1 9.9 7.8 5.3 19.8 15.7 5.1 25.8 1.6 0.0 0.0 55-59 1.5 2.9 4.2 4.8 13.3 21.5 4.8 36.4 10.6 0.0 0.0 60-64 2.7 1.0 7.0 2.7 21.0 19.7 12.8 19.1 12.5 1.5 0.0 65-69 4.9 1.2 0.0 4.8 6.8 14.6 16.1 26.0 16.8 8.7 0.0 70-74 1.1 1.8 1.8 4.3 14.8 11.8 10.1 15.8 22.1 13.4 2.9 75-79 0.4 0.9 0.4 5.9 9.4 12.4 9.6 23.4 16.4 14.5 6.8 ≥ 80 0.0 0.0 1.2 0.0 3.7 7.4 12.5 26.9 18.9 14.5 14.9 Note: Age group 18-19 is omitted due to insufficient number of observations.

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Table D10: Higher SES, 2012

In Per Cent All 10.5 6.1 3.2 10.0 16.4 12.4 7.4 16.6 11.8 4.0 1.6 Women 18-19* ------20-24 59.6 5.5 5.6 29.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 25-29 45.5 8.3 11.4 15.8 10.4 8.6 0.0 0.0 0.0 0.0 0.0 30-34 19.0 19.1 4.7 14.8 39.1 3.0 0.3 0.0 0.0 0.0 0.0 35-39 18.1 5.6 3.9 18.7 41.0 10.8 2.0 0.0 0.0 0.0 0.0 40-44 2.6 5.9 1.1 15.8 29.3 25.4 11.9 8.2 0.0 0.0 0.0 45-49 7.5 10.3 3.2 6.7 17.1 22.9 13.2 19.1 0.0 0.0 0.0 50-54 5.1 1.9 0.0 12.4 19.3 17.5 13.8 26.2 3.8 0.0 0.0 55-59 6.6 1.5 0.4 7.5 16.9 9.3 4.6 21.7 31.1 0.4 0.0 60-64 1.3 4.5 0.1 11.2 8.7 7.2 14.8 33.1 19.2 0.0 0.0 65-69 0.6 0.5 9.5 3.7 14.4 3.2 7.0 23.7 25.5 11.9 0.0 70-74 0.0 0.2 1.6 1.3 4.8 26.0 5.3 11.6 16.6 32.7 0.0 75-79 2.6 0.0 6.7 0.0 0.0 14.2 11.2 29.2 13.9 22.2 0.0 ≥ 80 6.8 5.3 0.0 3.8 0.0 21.4 0.0 17.5 19.3 7.2 18.7 Men 18-19* ------20-24 78.7 6.3 6.3 3.4 5.3 0.0 0.0 0.0 0.0 0.0 0.0 25-29 20.5 16.8 0.0 44.5 18.2 0.0 0.0 0.0 0.0 0.0 0.0 30-34 22.6 14.0 15.4 12.5 29.0 6.4 0.0 0.0 0.0 0.0 0.0 35-39 15.5 8.5 4.2 20.6 33.7 16.4 0.3 0.9 0.0 0.0 0.0 40-44 19.2 14.2 1.7 16.7 11.8 16.3 10.8 9.2 0.0 0.0 0.0 45-49 5.9 11.2 2.8 8.7 23.4 10.8 15.3 21.5 0.6 0.0 0.0 50-54 12.5 5.3 2.9 3.6 20.0 13.9 6.8 29.5 5.5 0.0 0.0 55-59 7.5 3.2 2.0 8.0 9.6 16.3 10.2 33.8 8.5 0.9 0.0 60-64 8.3 1.4 1.1 6.0 4.0 13.4 6.0 22.5 33.2 3.9 0.0 65-69 1.1 0.0 6.3 3.3 9.7 15.9 6.9 17.4 33.1 6.3 0.0 70-74 3.0 3.0 1.7 4.7 7.0 5.6 10.6 15.2 34.0 14.1 0.9 75-79 0.0 0.2 0.4 9.6 0.1 8.3 2.6 18.8 30.6 23.0 6.2 ≥ 80 0.0 0.0 0.0 1.3 1.9 5.8 4.2 23.1 23.6 11.7 28.4 Note: Age group 18-19 is omitted due to insufficient number of observations.

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Men - lower SES Men - higher SES

65 or more 2012 65 or more 2012 65 or 65 or yrs. 2002 yrs. 2002 more yrs. more yrs.

2012 2012 55-64 yrs. 55-64 yrs. 55-64 yrs 2002 55-64 yrs 2002

2012 2012 45-54 yrs. 45-54 yrs. 45-54 yrs. 2002 45-54 yrs. 2002

2012 2012 35-44 yrs. 35-44 yrs. 35-44 yrs. 2002 35-44 yrs. 2002

less than 2012 less than 2012 less than less than 35 yrs. 2002 35 yrs. 2002 35 yrs. 35 yrs. 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% Quit time distribution (in %) Quit time distribution (in %)

Women - lower SES Women - higher SES

2012 65 or more 65 or more 2012 65yrs. or 65 or 2002 yrs. 2002 more yrs. more yrs.

2012 2012 55-64 yrs. 55-64 yrs. 55-64 yrs 2002 55-64 yrs 2002

2012 2012 45-54 yrs. 45-54 yrs. 45-54 yrs. 2002 45-54 yrs. 2002

2012 2012 35-44 yrs. 35-44 yrs. 35-44 yrs. 2002 35-44 yrs. 2002

2012 2012 less than less than less than less than 35 yrs. 2002 35 yrs. 2002 35 yrs. 35 yrs. 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% Quit time distribution (in %) Quit time distribution (in %)

Figure 9: Quit time distribution (by gender, SES and aggregated age groups), 2002 and 2012 Note: SOEP waves 2002–2016. Unbalanced panel. Data weighted by expansion factors supplied in the data set.

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