NHANES observational studySmoking statusBasic characteristics of participants’ smoking behavior

A total of 116,876 US residents participated in seven rounds of the NHANES survey between 2005 and 2018. After the data were screened, 11,372 participants were included to assess the interrelationship between smoking status and the risk of developing depression. The mean age of the participants was 45.89 ± 17.09 years, with 6,109 (53.71%) males and 5,263 (46.29%) females.

The study participants were categorized into three groups based on their smoking status. Of the total participants, 49.59% (n = 5640) were nonsmokers, 25.04% (n = 2848) were ex-smokers, and 25.37% (n = 2884) were current smokers. Table 1 displays their clinical characteristics. Current smokers were younger and predominantly male, non-Hispanic white, and non-Hispanic black. Additionally, they had lower BMIs, PIRs, and education levels than did the other two groups. The study revealed that participants had a greater likelihood of consuming alcohol, residing with their parents, and experiencing health conditions such as asthma, emphysema, chronic bronchitis, and depression. The study participants were divided into two groups based on their PHQ-9 scores. Of the total participants, 54.8% (n = 10,451) were classified as nondepressed (PHQ-9 < 10) and 54.8% (n = 921) were classified as depressed (PHQ-9 ≥ 10). Table S2 shows the clinical characteristics of both groups.

Table 1 Baseline characteristics of participants by smoking statusAssociation between smoking status and depression

This study utilized multivariable logistic regression analysis to construct three models to examine the association between smoking status and depression (Table 2). The research findings indicate that, both in the unadjusted and adjusted models, compared to nonsmokers and former smokers, current smokers have a 1.94-fold increased risk of developing depression, showing a positive correlation with the risk of developing depression (OR 1.94; 95% CI 1.64–2.31; P < 0.001).

Table 2 Weighted multivariate adjusted logistic regression of smoking status and depression riskSmoking intensityBasic characteristics of participants’ smoking intensity

We identified 4868 individuals who provided complete daily smoking data for the past 30 days through screening of participant smoking intensity-related data. The participants were then categorized into four groups (Q1-Q4) based on their daily smoking data. The clinical characteristics of each group are shown in Table 3. The Q4 group, which had the highest number of daily cigarettes, was found to be older, with fewer females, a greater preference for alcohol, and a greater proportion of non-Hispanic whites than the other three groups. The study revealed that individuals with lower levels of education were more likely to have asthma, diabetes, hypertension, tumors, emphysema, chronic bronchitis, and coronary heart disease. The clinical characteristics of smoking intensity for participants with non-depression or depression are presented in Table S3.

Table 3 Baseline characteristics of participants by Smoking volumeAssociation between smoking intensity and depression

Multivariate logistic regression analysis revealed that the association between smoking intensity and the risk of developing depression persisted (Table 4). The study revealed that the risk of developing depression increased as smoking frequency increased. Smokers in the Q4 group, who smoked the most, had a 1.66-fold greater risk of developing depression than did those in the Q1 group (OR 1.66; 95% CI 1.26–2.17; P < 0.01).

Table 4 Weighted multivariate adjusted logistic regression of smoking volume and depression riskSmoking cessation durationBasic characteristics of participants’ smoking cessation duration

In this study, we analyzed a total of 9879 participants, who were categorized into four groups (Q1-Q4) based on the duration of smoking cessation. The Q4 group, which had the longest smoking cessation duration, was found to be older, predominantly male, mostly non-Hispanic white, and had higher education, stable marital status, and higher income than the other three groups. Additionally, Table 5 shows a higher prevalence of diabetes, hypertension, tumors, heart failure and depression in this group. Additionally, the clinical characteristics of smoking cessation duration for individuals with and without depression are shown in Table S4. tumors3.1.3.2 Association between smoking cessation duration and depression.

Table 5 Baseline characteristics of participants by smoking cessation duration

The relationship between smoking cessation duration and the risk of developing depression was analyzed by adjusting for various confounding factors (Table 6). All models demonstrated that quitting smoking was linked to a decreased risk of developing depression (all models, P for trend < 0.001). In Model II, compared to the Q1 group with the shortest smoking cessation duration, the Q4 group with the longest smoking cessation duration showed a 52% reduction in the risk of developing depression.

Table 6 Weighted multivariate adjusted logistic regression of smoking cessation duration and depression riskSmoothed fitted curves and threshold effect analysis

We found a nonlinear relationship between smoking cessation duration and the risk of developing depression through smooth fitted curves. The results indicate that as smoking cessation duration increases, the risk of developing depression continuously decreases (Fig. 4). The two-stage linear regression model results indicate that the inflection point for the threshold effect between the time to quit smoking and the risk of developing depression was 4 years (Table 7). This study revealed that smoking cessation duration can reduce the risk of developing depression. Compared to those with a smoking cessation duration of less than 4 years or more than 4 years, the risk of depression onset decreased with each additional year of smoking cessation, but overall, the risk of depression onset steadily decreased with increasing smoking cessation duration (P < 0.01).

Fig. 4

Smooth curve fit graph (solid red line represents smooth curve fit between variables, blue band represents 95% confidence interval of fit)

Table 7 Threshold effect analysisSerum cotinine levelsBasic characteristics of participants’ serum cotinine levels

A total of 10,842 participants participated in this study. The relationship between tobacco smoke exposure and the risk of developing depression, including serum cotinine levels, was analyzed from various perspectives. Table 8 displays the clinical characteristics of the participants based on their serum cotinine levels. The group with the highest cotinine levels (T3) consisted mostly of non-Hispanic white and black males with lower levels of education compared to the other two groups. They were predominantly unmarried or divorced/separated, had low household incomes, and had a higher prevalence of asthma, emphysema, chronic bronchitis, and depression. They were predominantly unmarried or divorced/separated, had low household incomes, and had a higher prevalence of asthma, emphysema, chronic bronchitis, and depression. Alcohol consumption was also more common in this group. They were predominantly unmarried or divorced/separated, had low household incomes, and had a higher prevalence of asthma, emphysema, chronic bronchitis, and depression. The clinical characteristics of patients with different serum cotinine levels in the depression group and nondepression group are presented in Table S5.

Table 8 Baseline characteristics of participants by Serum cotinine levelsAssociation between serum cotinine levels and depression

After adjusting for multiple confounders, Model II confirmed that there was a positive association between serum cotinine levels and the risk of developing depression. Specifically, for every 0.01 ng/mL increase in the serum cotinine concentration, the likelihood of developing depression increased by 0.14% (OR = 1.0014, 95% CI: 1.0009–1.0019, p < 0.001). This association was also observed when converting continuous variables to categorical variables. Compared to that in the T1 group, the risk of developing depression increased as the serum cotinine level increased in both the T2 group (OR = 1.45) and the T3 group (OR = 2.13) (Table 9).

Table 9 Weighted multivariable-adjusted logistic regression of Serum cotinine levels and depression riskMendelian randomization studyMR results of smoking status and depression

Smoking status was classified as never smoked, previously smoked, or currently smoking. Eligible SNPs were screened from each of the three UKB datasets, and only SNPs with F-statistics greater than 10 (Table S6) were included to avoid bias from weak instrumental variables. The MR results showed (Fig. 5A-C) that in the IVW model, never smoking, past smoking, and current smoking were causally associated with the risk of developing depression, with the former being a protective factor and the latter two being risk factors. Current smokers had a 2.57-fold greater risk of developing depression than did previous smokers.

Fig. 5

MR Result. (A) Never smoker (B) Current smoker (C) Previous smoker

MR–Egger and IVW were used to test the heterogeneity of the MR results, and the data showed that some MR results were heterogeneous (P < 0.05). However, this did not affect the reliability of the MR results (Table 10). MR–Egger and MR–PRESSO were used to test the multivariate validity of the MR results, and the P–value for both methods was > 0.05, indicating that there was no horizontal pleiotropy in the MR results (Table 11).

Table 10 Heterogeneity cochran Q test resultTable 11 Test results for genetic pleiotropy

The funnel plot indicates that the SNPs that met the screening criteria were mostly symmetrical and did not exhibit significant outliers, thus increasing the robustness of the MR results. To test the sensitivity of the IVW results, we used the leave-one-out method. After removing any one SNP, the results of the remaining SNPs were on the same side of the null line, indicating that the removal of any one SNP did not significantly affect the results. Forest plots for individual SNPs enhanced the confidence of the MR results. Scatter plots demonstrating the correlation trend between exposure and outcome (Figure S1-S3).

MR results of cotinine levels and depression

Eligible SNPs were screened from the EBI dataset, and SNPs with F-statistics < 10 were excluded to avoid bias from weak IVs (Table S6). The MR results (Figure S4 and Table S7) showed no significant causal relationship between cotinine levels and the risk of developing depression in the IVW model (OR = 0.99, 95% CI: 0.97–1.02, p = 0.63).

The MR results were tested for heterogeneity and horizontal pleiotropy. The results indicated no significant heterogeneity or horizontal pleiotropy (Table S8 and S9). Additionally, the reliability of the MR results was further validated using funnel plots, leave-one-out plots, forest plots, and scatter plots (Figure S5).