From smoke to stroke: quantifying the impact of smoking on stroke prevalence.

Purpose: The objective of this study is to assess the impact of smoking on stroke prevalence and to delineate the relationship between smoking-related factors and the risk of stroke, incorporating an analysis of demographic variations influencing this association.

Methods: Our analysis encompassed 9,176 participants, evaluating clinical attributes alongside smoking-related characteristics such as duration of cigarette consumption, and levels of nicotine, tar, and carbon monoxide. We employed weighted univariate logistic regression and restricted cubic splines to examine the association between smoking indicators and stroke risk, complemented by subgroup analyses for demographic differentiation.

Results: The overall prevalence of stroke in our cohort was 3.4%. Statistically significant associations were found between stroke incidence and factors such as age, gender, education, and marital status (p < 0.05). Adjusted logistic regression models showed increased odds ratios (ORs) for stroke with higher nicotine and carbon monoxide levels across progressively adjusted models: Model 1 (unadjusted), Model 2 (adjusted for age, gender), Model 3 (further adjusted for education, marital status, BMI, PIR), and Model 4 (fully adjusted for additional factors including hypertension, hyperlipidemia, diabetes, and drinking). Specifically, ORs for nicotine increased from 2.39 in Model 1 to 2.64 in Model 4; for carbon monoxide, from 1.10 to 1.11 over the same models.​The threshold analysis using restricted cubic splines revealed critical points for stroke risk increase at smoke exposure levels of 410 units, tar 12 mg, nicotine 1.1 mg, and carbon monoxide 12 ppm. Above these thresholds, stroke risk escalates significantly. Additionally, the presence of family smoking history was associated with higher stroke risks compared to those without such history.

Conclusion: This study confirms that smoking significantly contributes to increased stroke risk, particularly through exposure to nicotine and carbon monoxide. The findings emphasize the necessity for tailored stroke prevention strategies that specifically address smoking behaviors and consider demographic susceptibilities. Incorporating smoking-related indicators into risk assessment models could enhance the precision of stroke prevention efforts.