Tobacco and Nicotine Consumption and the Motivation to Stop Smoking in Smokers With and Without Coronary Heart Disease

Summary

Background:

Smoking worsens the prognosis of patients with coronary heart disease (CHD). Only limited population-based data are available on smoking cessation and its characteristics in people with CHD. We compared smokers with and without CHD.

Methods:

We analyzed pooled data from nine waves (June 2023–August 2024) of two representative cross-sectional surveys in Germany (DEBRA and OptiCor). We included adults aged 35 years and above who provided information on their smoking behavior and CHD status (n = 11 069; 994 [9%] with CHD). The endpoints included smoking status, tobacco dependence, motivation to quit smoking, and attempts to do so, as well as the use of electronic inhalation products (e-cigarettes, tobacco heaters). Regression models with CHD as an independent variable were adjusted for age, sex, education, and income.

Results:

People with CHD were less likely to be current smokers (23.8%, 95% confidence interval [21.2; 26.6], versus 29.3% [28.5; 30.2]), but they were more likely to be former smokers (32.2% [29.3; 35.3] versus 18.9% [18.1; 19.6]). Being a smoker with CHD was associated with the use of electronic inhalation products (odds ratio [OR] = 2.53 [1.43; 4.48]), higher motivation to quit smoking (OR = 1.41 [1.02; 1.96]), and greater tobacco dependence (OR = 1.63 [1.05; 2.53]). Among current smokers and those who smoked in the past year, those with CHD were also more likely than those without CHD to have made at least one attempt to quit in the past year (OR = 2.90 [1.98; 4.25]).

Conclusion:

One-quarter of people with CHD smoke. Despite a greater degree of tobacco dependence, they show higher motivation and make more attempts to quit smoking compared with smokers without CHD. As smoking cessation is crucial in this group, healthcare professionals should consistently assess the smoking status of people with CHD and offer them evidence-based support for smoking cessation.

Coronary heart disease (CHD) and smoking are closely linked in terms of pathogenesis and disease course (1, 2). Smoking contributes to the development of atherosclerosis, impairs endothelial function and promotes thrombosis, thereby increasing the risk of cardiovascular events, such as myocardial infarction, and worsening the cardiovascular prognosis (3–7). Smoking cessation reduces cardiovascular mortality and lowers the risk of reinfarction (8, 9). According to a review of cohort studies published between 1980 and 2000, smoking cessation reduces cardiovascular mortality by 36 % (RR = 0.64; 95% confidence interval: [0.58; 0.71]) (10). The results must, however, be interpreted with caution in light of various sources of bias and differences in the time periods covered by the individual studies. When looking at the individual studies published since 1990, the absolute risk reductions observed ranged from about 4% to 18%. (10). Despite this evidence, many patients continue to smoke even after the onset of disease. More than half of these patients are still smoking one year after a myocardial infarction and they are at a higher risk of adverse events compared to persons who have stopped smoking (adjusted hazard ratio, aHR] = 1.70; [1.17; 2.47]) (11). In patients with stable coronary heart disease, smoking cessation reduced the risk of serious cardiovascular events (aHR = 0.56, [0.42; 0.76]), corresponding to a 44% relative risk reduction in the adjusted time-to-event analysis. The event rates observed over five years were 6.7% among those who had stopped smoking, compared with 9.2% among those who had continued to smoke. On the other hand, a mere reduction in smoking had no beneficial effect (7.4% versus 7.0%; aHR = 0.96; [0.74, 1.26]) and each additional year of smoking increased the risk of cardiovascular death or myocardial infarction by 8% (aHR = 1.08; [1.04; 1.12] per year) (9).

Evidence-based interventions, such brief medical advice (12), or behavioral counselling (13) significantly improve the success of smoking cessation. Pharmacotherapies lead to an additional six months of abstinence; the number needed to treat (NNT) is approximately 12–25 for nicotine replacement therapy (NRT) and 12–17 for varenicline (14). Behavioral support combined with pharmacotherapy achieves higher abstinence rates than either intervention alone (15). The fact that many affected persons still find it difficult to quit smoking underscores the need for tailored cessation strategies (16). E-cigarettes and tobacco heaters are increasingly used as potential aids for smoking cessation (17, 18). While they are perceived by some as less harmful, concerns remain regarding cardiovascular risks and persistent nicotine dependence (19). Currently, these products are not recommended for smoking cessation in Germany (15).

Despite these developments, little is known about smoking behavior, motivation to stop smoking and the use of e-cigarettes or tobacco heaters among smokers with CHD compared to smokers without CHD. International studies (20, 21) have shown that smokers with CHD or related conditions may have specific barriers to smoking cessation. These include:

• High nicotine dependence

• Fear of withdrawal symptoms

• Perceived lack of support/understanding from healthcare professionals

• Ambivalence towards the perceived stress-relieving effects of smoking following a cardiovascular event (20–23).

At the same time, being diagnosed with CHD or experiencing a cardiac event can be a teachable moment which increases the motivation to quit smoking; however, lasting abstinence is often not achieved because of persistent dependence and limited access to structured cessation programs within routine cardiac care (20, 21). These observations are consistent with the self-determination theory, which emphasizes the importance of intrinsic motivation and perceived competence for ensuring lasting behavioral changes (24).

This study examines smoking and smoking cessation behaviors as well as the use of e-cigarettes and tobacco heaters among adult smokers with and without self-reported CHD in Germany in order to address this gap in the evidence.

Methods

Study design

We analyzed pooled data from two cross-sectional studies conducted in parallel in Germany:

• the German Study on Tobacco Use (DEBRA, Deutsche Befragung zum Rauchverhalten; www.debra-study.info)

• the “Optimizing the Treatment of Chronic Ischemic Heart Disease by Training General Practitioners to Deliver Very Brief Advice on Physical Activity“ study (OptiCor; www.opticor-study.info).

The two studies were conducted by the same market research institute with the help of computer-assisted faceto-face household interviews. DEBRA collects data on the consumption of tobacco and electronic inhalation products among adults and adolescents aged 14 years or older. OptiCor examines the presence of coronary heart disease and associated health-related behaviors among persons aged 35 years or older.

In this analysis, we included participants aged 35 years or older who had completed the DEBRA module on tobacco consumption and also provided information on their CHD status as part of the OptiCor study. Data were pooled from nine survey waves conducted between June 2023 and August 2024. Both studies were pre-registered with the German Registry of Clinical Trials (Deutsches Register Klinischer Studien).

Further details on methodology, including sampling procedures, survey conduct and variable coding are provided in the eSupplement.

Sample and data collection

Participants were recruited from private households as part of a nationwide household survey covering various topics which was conducted every two months. In each wave, up to 2400 persons aged 14 years or more were surveyed. After application of the age limit (35 years or older), the inclusion requirement for the OptiCor study and the predefined DEBRA target sample, the size of the combined sample was about 1230 respondents per wave on average. Pooling of the nine waves yielded a final sample of 11 069 persons from whom complete information on both smoking behavior and CHD was available (eTable 1).

eTable 1. Sample size by survey wave.

Survey wave	Participants in absolute numbers
1	1364
2	1206
3	1135
4	1253
5	1222
6	1218
7	1164
8	1263
9	1244
Total	11 069

Variables

The complete questionnaires with item formulations are available online (DEBRA: www.osf.io/snm3p; OptiCor: www.osf.io/kvfnb; both translated into English).

The independent variable was self-reported CHD, defined as one of the following conditions diagnosed by a doctor:

• Angina pectoris

• Myocardial infarction

• Coronary artery bypass graft surgery, or

• Coronary intervention (balloon dilation or stent implantation).

Participants who reported at least one of these diagnoses were classified as persons with CHD.

The dependent variables from the DEBRA study comprised the smoking status with the options “current”, “former” and “never“. In current smokers, data on the following variables were collected in addition:

• Average number of cigarettes smoked per day

• Motivation for smoking cessation, measured using the Motivation to Stop Scale (MTSS) (25, 26)

• The severity of cigarette dependence, measured using the Heaviness of Smoking Index (HSI) (15, 27).

The use of electronic inhalation products (e-cigarettes or tobacco heaters) was recorded, regardless of smoking status. Attempts to stop smoking during the past year were reported by respondents smoking currently and during the past year.

Covariates included age, sex, net household income, and educational level.

Statistical analyses

Further details are provided in the pre-registered study protocol (https://osf.io/z4brd/files/mdb4k).

The descriptive prevalence of smoking status, use of e-cigarettes or tobacco heaters as well as sociodemographic characteristics were reported separately for persons with and without CHD as absolute numbers and relative frequencies (percentages) with 95% confidence intervals [95% CI]. Using survey weights provided by the market research institute, the data were weighted according to age, sex, household size and educational level to represent the German population. Details on the weighting procedure can be found at the following link: www.osf.io/s2wxc. In addition, a post hoc analysis of the prevalence of smoking status was performed by age group (35–54, 55–74 and 75 years or older).

Smoking and smoking cessation behaviors among current cigarette smokers were described by CHD status. The results were reported as absolute numbers and relative frequencies (percentages) with 95% confidence intervals or as the mean ± standard deviation (SD) or the median and interquartile range (IQR).

The associations between CHD (“yes “ versus “no“) and smoking behavior, smoking cessation behavior as well as the use of e-cigarettes or tobacco heaters were analyzed using regression models. We used a multivariable ordinal logistic regression to evaluate cigarette dependence (“low”, “moderate”, “high”). A multivariable logistic regression analysis was performed to assess motivation to quit smoking (“not motivated” versus “motivated”), the use of e-cigarettes or tobacco heaters (“yes” versus “no”) and attempts to quit smoking in the past year (“at least one attempt” versus “no attempt”). The models were adjusted for sex, educational level, income, and age. We excluded cases with missing data.

The statistical software used for the analyses was IBM SPSS Statistics Version 29.0.

Results

A total of 11 069 persons aged 35 years or older were included in the study; of these, 974 (8.8%) reported being diagnosed with CHD (weighted data). Participants with CHD were more likely compared to those without CHD to be male (61.8% versus 46.5%), older (75 years or older: 45.4% versus 14.6%), and less likely to have a high level of education (26.6 % versus 30.5 %) (Table 1). Missing data was minimal. Overall, data on income and educational level was missing in less than 1% of participants (Table 1).

Table 1. Prevalence of tobacco smoking, e-cigarette/tobacco heater use and sociodemographic characteristics by self-reported CHD (weighted data).

	CHD yes 8.8 % (N = 974)		CHD no 91.2 % (N = 10 082)
	% [95% CI]	n	% [95% CI]	n
Age in years
35–54	11.4 [9.5; 13.6]	111	43.4 [42.5; 44.4]	4 378
55–74	43.2 [40.1; 46.4]	421	42.0 [41.0; 43.0]	4 233
≥ 75	45.4 [42.2; 48.6]	442	14.6 [13.9; 15.3]	1 472
Missing	0	0	0	0
Gender
Male	61.8 [58.7; 64.9]	602	46.5 [45.6; 47.5]	4 693
Female	38.2 [35.1; 41.3]	372	53.4 [52.5; 54.4]	5 387
Missing (diverse)	0	0	0.0 [0.0; 0.0]	2
Educational level*1
Low	45.3 [42.1; 48.5]	441	29.1 [28.2; 30.0]	2 937
Medium	28.0 [25.2; 31.0]	273	40.3 [39.3; 41.3]	4 064
High	26.6 [23.8; 29.5]	259	30.5 [29.6; 31.4]	3 073
Missing	0.1 [0.0; 0.6]	1	0.1 [0.0; 0.2]	8
Income*2
Low	8.3 [6.7; 10.2]	81	6.1 [5.6; 6.6]	615
Medium	65.1 [61.9; 68.0]	633	61.1 [60.1; 62.0]	6 159
High	26.6 [23.8; 29.5]	259	32.5 [31.6; 33.5]	3 280
Missing	0.1 [0.0; 0.6]	1	0.3 [0.2; 0.4]	28
Tobacco smoking status
Current tobacco smokers*3	23.8 [21.2; 26.6]	232	29.3 [28.5; 30.2]	2 958
–Co-users*6	6.9 [4.0; 11.0]	16	4.3 [3.6; 5.1]	128
–Non-co-users	93.5 [89.6; 96.3]	217	95.7[94.9; 96.4]	2 831
Missing	0	0	0	0
Former tobacco smokers*4	32.2 [29.3; 35.3]	314	18.9 [18.1; 19.6]	1 900
–Co-users*6	1.9[0.7; 4.1]	6	1.5 [1.0; 2.2]	29
–Non-co-users	97.8 [95.5; 99.1]	307	98.5 [97.8; 99.0]	1 871
Missing	0	0	0	0
Never-tobacco smokers*5	43.9 [40.8; 47.1]	428	51.8 [50.8; 52.8]	5 224
–Co-users*6	0.2 [0.0; 1.3]	1	0 [0.0; 0.0]	0
–Non-co-users	99.8 [98.7; 99.9]	427	100 [1.0; 1.0]	5 224
Missing	0	0	0	0

The data is presented as percentages and absolute numbers, with 100% representing the total for each column; the figures are aggregated from nine survey waves carried out in 2023 and 2024. The column percentages do not always add up to exactly 100% due to rounding. Values below 100% are due to missing data. Values slightly above 100% can arise due to rounding when survey weighting is applied.

Italics indicates analyses that refer to the respective subgroup mentioned above.

^*1Educational level in ascending order: low = no school leaving certificate or general school leaving certificate; medium = intermediate secondary school leaving certificate; high = university of applied sciences or general university entrance qualification

^*2Monthly net household income: low = about <20^th income percentile; middle = about 20^th–80^th income percentile; high = about >80^th income percentile

^*3Current tobacco smokers are persons who reported “smoking cigarettes daily” or “not smoking cigarettes but consuming tobacco in another form”.

^*4Former tobacco smokers are persons who reported that they “completely stopped smoking in the past year” or “completely stopped smoking more than a year ago”.

^*5“Never-tobacco smokers” are persons who reported that they “have never been smokers (i.e., have never smoked for a year or longer)”.

^*6Co-users are persons who reported concurrent use of at least one of the following electronic inhalation products: e-cigarettes and/or tobacco heaters.

CHD, coronary heart disease; n, absolute number

Current smoking was less common among participants with CHD (23.8% versus 29.3%), whereas former smoking was more common (32.2 % versus 18.9 %). Overall, 180 of the respondents (1.6%) used e-cigarettes or tobacco heaters; of these, 23 (2.3%) with CHD and 157 (1.6%) without CHD. The use of e-cigarettes or tobacco heaters was higher among current smokers with coronary heart disease compared to those without CHD (6.9% versus 4.3%) (Table 1).

A post hoc analysis by age group showed that the prevalence of current smoking differed significantly between age groups. Among 35– to 54-year-olds with CHD, the prevalence of current smoking was 43.8%, compared to 38.3% among persons of the same age group without CHD. In the 55– to 74-year-old age group, the corresponding prevalence rates were 30.6% and 28.0%, respectively. The lowest prevalence was found among persons aged 75 years or older (12.5 % versus 6.5 %) (eTable 2). It is likely that these age-related patterns contribute to the overall difference in smoking prevalence between persons with and without CHD.

eTable 2. Prevalence of tobacco smoking by age group and self-reported CHD (weighted data).

Age groups		CHD yes		CHD no
		% [95% CI]	n	% [95% CI]	n
35–54 years	Current tobacco smokers*1	43.8 [34.4; 53.4]	49	38.3 [36.8; 39.7]	1 676
	Former tobacco smokers*2	32.1 [23.6; 41.6]	36	15.4 [14.3; 16.5]	674
	Never-tobacco smokers	24.1 [16.5; 33.1]	27	46.3 [44.8; 47.8]	2 028
55–74 years	Current tobacco smokers*1	30.6 [26.2; 35.2]	129	28.0 [26.7; 29.4]	1 187
	Former tobacco smokers*2	29.9 [25.5; 34.5]	126	21.6 [20.4; 22.9]	915
	Never-tobacco smokers	39.6 [34.9; 44.4]	167	50.3 [48.8; 51.9]	2 131
≥ 75 years	Current tobacco smokers*1	12.5 [9.5; 15.9]	55	6.5 [5.3; 7.8]	95
	Former tobacco smokers*2	34.5 [30.0; 39.1]	152	21.1 [19.1; 23.3]	311
	Never-tobacco smokers	53.1 [48.3; 57.8]	234	72.4 [70.1; 74.7]	1 066

^*1Current tobacco smokers are persons who reported “smoking cigarettes daily” or “not smoking cigarettes but consuming tobacco in another form”.

^*2Former tobacco smokers are persons who reported that they “completely stopped smoking in the past year” or “completely stopped smoking more than a year ago”.

CHD, coronary heart disease

Current smokers with CHD were more likely to be highly tobaccodependent (HSI 5–6: 10.0% versus 6.0%), while the average daily cigarette consumption was similar (15.8 ± 8.7 versus 15.3 ± 8.1). In the combined group of current smokers and those who smoked last year, attempts to quit smoking in the past year were more common among persons with CHD compared to those without CHD (10.4% versus 4.9%) (Table 2).

Table 2. Smoking behavior and smoking cessation-related indicators among current cigarette smokers after self-reported CHD.

	Current cigarette smokers
	CHD yes (N = 269)		CHD no (N = 3371)
	% [95% CI]	n	% [95% CI]	n
Cigarettes per day	Mean (SD): 15.8 (8.7)		Mean (SD): 5.3 (8.1)
Severity of cigarette dependence (HSI)*1
Low	31.2 [25.7; 37.1]	84	29.4 [27.9; 31.0]	991
Medium	56.1 [50.0; 62.2]	151	61.6 [60.0; 63.2]	2 075
High	10.0 [6.7; 14.3]	27	6.0 [5.2; 6.8]	201
Smoking cessation attempts in the past year*2
None	88.8 [84.5; 92.3]	239	94.7 [93.9; 95.5]	3 194
At least one	10.4 [7.0; 14.7]	28	4.9 [4.2; 5.7]	165
Number of smoking cessation attempts in the past year *3	Mean (SD) [min–max]: 1.8 (1.8) [1–10] Median (IQR): 1.0 (1.0)		Mean (SD) [min–max]: 2.1 (5.5) [1–50] Median (IQR): 1.0 (1.0)
Motivation for smoking cessation *4
Motivated	19.7 [15.1; 25.0]	53	17.7 [16.4; 19.0]	595
Not motivated	79.9 [74.6; 84.5]	215	81.9 [80.6; 83.2]	2 761

The data is presented as percentages (absolute numbers), with 100% representing the total for each column; the figures are aggregated from nine survey waves carried out in 2023 and 2024. The column percentages do not always add up to exactly 100% due to rounding. Values below 100% are due to missing data.

^*1Heaviness of Smoking Index (HSI) is calculated based on the number of cigarettes smoked per day and the time until the first cigarette after waking-up: low cigarette dependence: HSI 0–1; moderate cigarette dependence: HSI 2–4; high cigarette dependence: HSI 5–6;

^*2Indicates serious attempts to stop smoking within the past twelve months;

^*3Only persons with more than one attempt;

^*4Measured using the Motivation to Stop Smoking Scale (MTSS): Response options 1–2 = not motivated; response options 3–7 = motivated.

HSI, Heaviness of Smoking Index; IQR, interquartile range; CHD, coronary heart disease; CI, confidence interval; min, minimum; max, maximum; SD, standard deviation

Adjusted regression analyses confirmed that current cigarette smokers with CHD had higher odds (probability) of co-using e-cigarettes or tobacco heaters compared to current cigarette smokers without CHD (odds ratio [OR] = 2.53; [1.43; 4.48]; p = 0.001), a higher motivation for smoking cessation (OR = 1.41; [1.02; 1.96]; p = 0.040; reference: “no motivation for smoking cessation“), and higher cigarette dependence (OR = 1.63; [1.05; 2.53]; p = 0.031; reference: “moderate level of dependence”) . Among current smokers and those who smoked in the past year, those with CHD were also more likely compared to those without CHD to have made at least one attempt to quit smoking in the past year (OR = 2.90 [1.98; 4.25]; p<0.001; reference: no attempt to stop smoking in the past years) (Table 3).

Table 3. Associations between the presence of CHD and tobacco use, smoking cessation behavior, and the use of e-cigarettes/tobacco heaters among current cigarette smokers.

	OR for smoking-related endpoints among participants with CHD (versus without CHD)
Smoking-related endpoints	OR [95% CI]	p-value
Severity of cigarette dependence (HSI)*1
High vs. low/moderate (ref)	1.63 [1.05; 2.53]	0.031
Low vs. moderate/high (ref)	1.15 [0.86; 1.52]	0.349
Co-use*2
No	Reference
Yes	2.53 [1.43; 4.48]	0.001
Motivation for smoking cessation*3
Not motivated	Reference
Motivated	1.41 [1.02; 1.96]	0.040
Smoking cessation attempts in past year*4
No	Reference
Yes, at least one	2.90 [1.98; 4.25]	< 0.001

Odds ratios greater than 1 indicate a higher probability of the respective outcome in persons with CHD. Multivariable logistic regression models were calculated for all variables and adjusted for sex, education, income, and age.

^*1The variable was dichotomized using dummy coding to allow for separate regression analyses of the two extremes of cigarette dependence: (1) high (5–6) versus low/moderate (0–4) and (2) low (0–1) versus moderate/high (2–6)

^*2Reflects the current use of e-cigarettes and/or tobacco heaters in addition to cigarette smoking

^*3Measured using the Motivation to Stop Smoking Scale (MTSS): response options 1–2 = not motivated; response options 3–7 = motivated

^*4Smoking cessation attempts in the past year among the subgroup of current smokers and those who smoked in the past year.

HSI, Heaviness of Smoking Index; CHD, coronary heart disease; CI, confidence interval;

OR, odds ratios; ref, (respective) reference group

Discussion

In Germany, about a quarter of people with CHD continue to smoke. Smokers with CHD reported greater motivation and more attempts to quit smoking than those without CHD, even though their level of dependence was higher. This indicates that continuing to smoke is more likely due to inadequate access to smoking cessation treatments than to a lack of motivation to quit smoking.

Consequently, smoking cessation should be a core element of secondary prevention: Physicians should routinely record a patient’s smoking status and proactively offer counseling and guideline-recommended interventions, such as behavioral support and pharmacotherapy—especially for highly dependent smokers. This includes follow-up care and, in some cases, a referral. Proactively offering smoking cessation support interventions can significantly increase the uptake of treatments, according to a Swiss multicenter before-after study on smokers hospitalized for an acute coronary syndrome. The study found that a motivational interviewing-based intervention increased the proportion of smoking cessation counseling (87% versus 22%; p<0.001) and nicotine replacement therapy (NRT) prescriptions at discharge (58% versus 18%, RR = 3.3; [2.4; 4.3]; p<0.001). However, the increase in 12-month abstinence did not reach statistical significance (51% versus 43%; RR = 1.20; [0.98; 1.46]; p = 0.08) (28).

The greater use of e-cigarettes or tobacco heaters among smokers with CHD may indicate that these products are perceived as potential smoking cessation aids or less harmful alternatives—especially in the context of high dependence, limited smoking cessation support and psychosocial barriers among persons with cardiovascular disease (21, 29). However, the available evidence with regard to the effectiveness and safety of these products is mixed, in particular in this population (30, 31). In Germany, these products are not recommended for smoking cessation (15). From a public health perspective, the fact that these products are more commonly used among patients with CHD may point to an unmet need for effective smoking cessation interventions. Physicians should answer questions from patients about these products by providing balanced information and acknowledge the product use as a possible indicator of motivation to quit smoking, and, at the same time, highlight evidence-based pharmacological and behavioral interventions as the first-line treatment options.

It is important to note that people with CHD showed greater motivation for smoking cessation and made more frequent attempts to quit smoking. This is in line with findings, indicating that being diagnosed with a chronic disease or an acute cardiac event can be a teachable moment for behavioral changes (32). Despite this, high levels of tobacco dependence remain a major barrier to long-term abstinence. Smoking cessation reduces mortality and events of recurrence in persons with CHD (33–35), particularly when behavioral and pharmacological interventions are combined (36). However, the implementation of guideline-recommended smoking cessation support is still inadequate, and structured interventions have so far not been sufficiently integrated into routine care (37).

Thus, it is crucial to integrate systematic cessation support into existing health care structures. Disease management programs (DMP) for CHD and cardiological rehabilitation provide suitable platforms for structured interventions; even so, smoking cessation is often not addressed with the same degree of consistency as other secondary prevention measures (38). Treatment outcomes in patients with CHD could be significantly improved by implementing evidence-based behavioral and pharmacological interventions in a standardized and consistent manner.

In Germany, there are also structural barriers: Until recently, smoking cessation medications were largely not eligible for reimbursement. As a result, the use of evidence-based pharmacotherapies, such as NRT or varenicline, has been significantly hampered, particularly in patients with high tobacco dependence (14). The recent decision to allow reimbursement under certain conditions offers an important opportunity to reduce this gap in care and strengthen the implementation of guidelinebased treatment (39). Physicians should be encouraged to systematically integrate these treatments into the smoking cessation support for patients with cardiovascular disease.

Strengths and limitations

Two key strengths of our study are the large population-based sample and the detailed capture of smoking-related behavior. The limitations of this study include its cross-sectional design, which does not allow for causal interpretations, as well as the use of self-reported data, which may be influenced by recall bias or social desirability effects. The OptiCor study‘s high opt-out rate may have led to selection bias, since people with a greater health awareness or stronger motivation to change their behavior may have been more willing to participate.

The fact that the CHD status was based on self-reported information and could not be clinically validated could have led to misclassifications. However, the prevalence of self-reported CHD in our sample (8.8%) is consistent with estimates from population-based surveys of the Robert Koch Institute (e.g., the DEGS1 study: approximately 9%), which supports the plausibility of the self-reported data (40). In an ongoing clinical study involving primary care practices, selfreported CHD has been consistent with a confirmed ICD-10 diagnosis in the vast majority of cases (personal communication, Kastaun S., Institute of General Practice, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; 2026; based on unpublished data from the OptiCor pilot study cRcT). Further limitations include missing information about the time when CHD was diagnosed, CHD severity or cardiovascular events, the inability to assess long-term abstinence, as well as the lack of differentiation between various types of e-cigarettes and tobacco heaters. Therefore, future research should make use of longitudinal study designs, clinical validation and more detailed surveys to help develop targeted cessation strategies.

Conclusion

Even though people with CHD are motivated to stop smoking, it is common that they continue to smoke due to dependence and structural barriers. Improved access to evidence-based pharmacotherapy, integration of structured smoking cessation support into cardiovascular care and careful incorporation of harm-reduction approaches are crucial for transforming motivation into sustained abstinence and thereby improving the prognosis of these patients. Given the importance of smoking cessation in this high-risk group, simply routinely recording patients‘ smoking status and providing brief medical advice (e.g., ABC or 5A) would already represent a step forward.

eMETHODS

Study design

Our analyses are based on data from two studies conducted nationwide in Germany:

• German Study on Tobacco Use (DEBRA, Deutsche Befragung zum Rauchverhalten), and

• Optimizing the Treatment of Chronic Ischemic Heart Disease by Training General Practitioners to Deliver Very Brief Advice on Physical Activity (OptiCor). The analyses presented in this article are based on data from studies pre-registered with the German Registry of Clinical Trials (DEBRA: DRKS00011322, DRKS00017157, DRKS00028054; OptiCor: DRKS00031304).

Sample and data collection

The nationwide sampling was based on a dual-frame design that combined, in equal parts, random stratified sampling and quota sampling (www.osf.io/s2wxc). Every two months, the market research institute recruited up to 2400 persons aged 14 or older living in private households as part of a cross-cutting household survey that took about 40 to 60 minutes to complete. While it is theoretically possible to participate again across multiple rounds, this is considered highly unlikely. Thus, each wave is considered an independent cross-sectional sample. In each survey wave, approximately 2000 participants complete the DEBRA module on tobacco use, which corresponds to a predetermined target sample size. In addition, the OptiCor study invited all persons aged 35 or older who were eligible to participate to answer questions about CHD and the associated health-related behaviors. Participation in the OptiCor module was on an opt-in basis, with approximately 80% of eligible respondents agreeing to participate. The sequence of the survey modules had been predetermined: The DEBRA module was conducted prior to the OptiCor module, while the number of additional survey topics could vary. After application of the age limit (35 years or older), the inclusion requirement for the OptiCor study and the predefined DEBRA target sample, the size of the combined sample was on average 1230 respondents per wave.

Variables

As part of the OptiCor study, self-reported CHD was determined using four established questions that were adapted from a large German health survey (40). Participants were asked whether they had ever been diagnosed by a physician with any of the following conditions:

Myocardial infarction

• Angina pectoris

• Myocardial infarction

• Coronary artery bypass graft surgery, or

• Coronary intervention (balloon dilation or stent implantation).

The responses were coded dichotomously (yes/no; also refer to Table 1 in the study protocol: www.osf.io/mdb4k).

Smoking status was classified as current smokers, former smokers or never-smokers. Additionally, the average number of cigarettes smoked per day was recorded for persons who were currently smoking. Motivation for smoking cessation was assessed using the Motivation to Stop Scale (MTSS) (25, 26). For regression analyses, MTSS was dichotomized in: “motivated to stop smoking “ (levels 3–7) and “not motivated to stop smoking “ (levels 1–2). The severity of cigarette dependence was measured using the Heaviness of Smoking Index (HSI) (27, 15) and categorizes as follows: “low dependence“ (0–1), “moderate dependence“ (2–4), “high dependence“ (5–6). The use of electronic inhalation products comprises e-cigarettes and tobacco heaters. For the regression analyses, the concurrent use of electronic inhalation products (“yes” or “no”) among current smokers was modeled, defined as the current use of e-cigarettes and/or tobacco heaters in addition to smoking conventional tobacco products. No separate analyses were conducted for e-cigarettes and tobacco heaters. Persons who stated that they currently smoke or had stopped smoking within the past twelve months also reported on their attempts to quit smoking in the past year (“at least one attempt” versus “no attempts” as well as the number of attempts). Depending on the research question, the analyses focused on different groups:

• Current smokers (cigarettes, pipes, cigars, or cigarillos)

• Current cigarette smokers, and

• Persons who stopped smoking in the past twelve months.

Covariates included age (for descriptive prevalence in the age groups 35–54, 55–74 or ≥ 75 years), sex (male or female), net household income (“low”: <20^th percentile; “middle”: 20^th–80^thpercentile; “high”: > 80^th percentile; OECD-equivalent household income, www.osf.io/387fg), as well as educational level (“low” = no school leaving certificate or general school leaving certificate; medium = intermediate secondary school leaving certificate; high = university of applied sciences or general university entrance qualification).