Is exposure to secondhand smoke associated with current depression (PHQ-8) among never-smokers? Results from a survey among German adults

Analysis of patient health questionnaire-9 (PHQ-9) based depression prevalence according to a discordance between quantitative urinary cotinine levels and self-report of second-hand smoke exposure among adults: A cross-sectional study

Background

Second-hand smoke (SHS) exposure appears to be more common among individuals with depression. However, self-report of SHS exposure is an inaccurate classification compared to confirming SHS exposure using urinary cotinine (UC). Additionally, the dose-response relationship between depression and UC is controversial.

Methods

The severe stress rate and depression prevalence was estimated among 14530 Korean participants aged ≥19 years using data patient health questionnaire-9 (PHQ-9) and on UC from the Korean National Health and Nutrition Examination Survey. Measured UCs were divided into four categories: UC- (≤0.3 μg/L), UC± (0.4 μg/L-0.9 μg/L), UC+ (1.0 μg/L-11.9 μg/L), and UC++ (≥12.0 μg/L).

Results

About 55.0 % participants were female and participants' mean age was 51.1 years. Non-smokers were 80.3 %. Among non-smokers, non-SHS exposure participants (SR-) and SHS exposure participants (SR+) were 83.0 % and 17.0 %, respectively. When UC- was used as the reference subgroup, the UC++ subgroup showed a higher depression prevalence, whereas the UC ± subgroup showed a lower prevalence. In the same UC categories, the depression prevalence and severe stress rate were higher among females than among males. Furthermore, the SR + subgroup had a higher severe stress rate than the SR- subgroup.

Conclusions

Our study showed a paradoxical reduction in the depression prevalence and severe stress rate in the UC ± subgroup compared to the UC- subgroup. Additionally, the dose-response relationship between the SHS exposure biomarker and the depression prevalence was not linear. Our study indicates that an emotional stress-based model may be more appropriate for explaining the relationship between depression and SHS exposure.

Association between secondhand smoke exposure across the life course and depressive symptoms among Chinese older adults

BACKGROUND

There are limited data on the association between secondhand smoke (SHS) exposure across the life course and depressive symptoms among older adults. We aimed to investigate the association of childhood household SHS exposure, adulthood household SHS exposure, lifetime social SHS exposure, and their coexistence with depressive symptoms in older adults.

METHODS

Data were from the 2011-2012 and 2014 waves of the Chinese Longitudinal Healthy Longevity Survey. About 4000 participants (aged 60 years or older) were recruited in a randomly selected half of the counties and cities in China. Data on SHS exposure, past-year depressive symptoms, and covariates were collected using a questionnaire. The chi-square test (for categorical variables) and t-test (for continuous variables) were used to assess differences in the participant characteristics across groups of SHS exposures. We estimated the odds ratios (ORs) and 95 % confidence intervals (CIs) of depressive symptom according to different types of SHS exposure.

RESULTS

Childhood household SHS exposure (OR = 1.42, 95%CI = 1.22-1.66), adulthood household SHS exposure (OR = 1.41, 95%CI = 1.21-1.63) and lifetime social SHS exposure (OR = 1.35, 95%CI = 1.14-1.58) were associated with higher odds of depressive symptoms. Additionally, those with a higher SHS exposure score had higher odds of depressive symptoms (1 point: OR = 1.56, 95%CI = 1.22-2.00; 2 points: OR = 1.77, 95%CI = 1.39-2.25; 3 points: OR = 1.83, 95%CI = 1.45-2.31). The results were similar when stratified by lifetime nonsmoking, former smoking, and current smoking.

LIMITATIONS

Retrospective design may introduce recall bias.

CONCLUSIONS

SHS exposure was associated with higher odds of depressive symptoms in older adults, with the effect seeming to be addictive.

Machine-learning model for predicting depression in second-hand smokers in cross-sectional data using the Korea National Health and Nutrition Examination Survey

Objective

Depression among non-smokers at risk of second-hand smoke (SHS) exposure has been a neglected public health concern despite their vulnerability. The objective of this study was to develop high-performance machine-learning (ML) models for the prediction of depression in non-smokers and to identify important predictors of depression for second-hand smokers.

Methods

ML algorithms were created using demographic and clinical data from the Korea National Health and Nutrition Examination Survey (KNHANES) participants from 2014, 2016, and 2018 (N = 11,463). The Patient Health Questionnaire was used to diagnose depression with a total score of 10 or higher. The final model was selected according to the area under the curve (AUC) or sensitivity. Shapley additive explanations (SHAP) were used to identify influential features.

Results

The light gradient boosting machine (LGBM) with the highest positive predictive value (PPV; 0.646) was selected as the best model among the ML algorithms, whereas the support vector machine (SVM) had the highest AUC (0.900). The most influential factors identified using the LGBM were stress perception, followed by subjective health status and quality of life. Among the smoking-related features, urine cotinine levels were the most important, and no linear relationship existed between the smoking-related features and the values of SHAP.

Conclusions

Compared with the previously developed ML models, our LGBM models achieved excellent and even superior performance in predicting depression among non-smokers at risk of SHS exposure, suggesting potential goals for depression-preventive interventions for non-smokers during public health crises.

Is secondhand smoke associated with mental health issues? A narrative review of the evidence and policy implications

Secondhand smoke (SHS) is a well-established cause of lung cancer, respiratory disease, heart disease and developmental issues in children, with an overwhelming evidence base spanning over four decades. In this narrative review, we describe studies which have also linked self-reported or cotinine-assessed SHS exposure in the home, workplace and other settings to mental health disorders including depression, suicide, anxiety, and psychological distress in children and adults, sleeping disorders, Attention Deficit Hyperactivity Disorder and behavioural issues in children, and dementia in older adults. In general, evidence indicates that SHS exposure is associated with these disorders in a dose-response manner, with higher odds reported in people who are exposed to SHS at high levels, frequently, and in the home environment. Most studies so far are cross-sectional albeit in large, nationally representative samples from various countries with a smaller number of longitudinal studies. More research is needed in this area to determine whether SHS is a direct cause of adverse mental health outcomes, and whether creating smokefree environments leads to improved mental wellbeing. In particular, more research is needed on the impact of smokefree home environments, an area which has received relatively little focus in smokefree interventions which generally target public places.

Passive exposure to e-cigarette emissions is associated with worsened mental health

BACKGROUND

Cigarette smoking, secondhand cigarette smoke (SHS) exposure, and e-cigarette use ("vaping") are each associated with increased rates of depressive symptoms and other internalizing mental health disorders. The prevalence of vaping has increased greatly, yet the mental health correlates of secondhand exposure to e-cigarette emissions are as yet to be investigated. This study examined the potential adverse mental health outcomes associated with different tobacco exposures (direct and passive), with a particular focus on the mental health correlates of secondhand exposure to e-cigarette emissions.

METHODS

The Population Assessment of Tobacco and Health Study data collected from a sample of 16,173 Wave 4 adults were used to test the hypothesis that secondhand e-cigarette emissions exposure is associated with increased odds of internalizing mental health disorders. Individuals were categorized as exclusive cigarette smokers, exclusive e-cigarette users, cigarette and e-cigarette dual users, exclusive noncombustible tobacco users, secondhand smoke exposed non-users, secondhand e-cigarette emissions exposed non-users, and non-users with no current SHS/secondhand e-cigarette aerosol exposure. Adjusted weighted logistic regression analysis was used to investigate the association between exposure type and internalizing problems as assessed by scores on the Global Appraisal of Individual Needs-Short Screener (GAIN-SS), a widely used instrument for assessing mental health problems.

RESULTS

Cigarette smokers (AOR = 2.53, 95% CI: 2.19-2.92), e-cigarette users (AOR = 3.14, 2.41-4.09), dual users (AOR = 3.37, 2.85-4.00), noncombustible tobacco users (AOR = 1.48, 1.01-2.17), SHS exposed non-users (AOR = 1.63, 1.37-1.94), and secondhand e-cigarette emissions exposed non-users (AOR = 1.43, 1.03-1.99) were each associated with increased odds of moderate to severe internalizing mental health problems as compared to unexposed non-users. Odds of internalizing problems among SHS and secondhand e-cigarette emissions exposed non-users did not differ (p = 0.46).

CONCLUSIONS

This is the first study, to our knowledge, to identify an association between recent secondhand exposure to e-cigarette emissions and mental health problems, and the risk is comparable to that of SHS. Corroboration of this relationship needs further research to explicate directionality and mechanisms underlying this association.

Secondhand Smoke in the Workplace Is Associated With Depression in Korean Workers

Background

Smoking negatively affects health, and previous studies argue that secondhand smoke (SHS) has a significantly negative health effect. We investigated whether SHS in the workplace influences workers' depression.

Methods

Three years of data (2014, 2016, and 2018) from the Korean National Health and Nutrition Examination Survey were analyzed. Participants who were not current smokers were classified into the occupational SHS exposed and non-exposed groups. Multivariate logistic regression was performed to estimate odds ratios (ORs) and 95% confidence intervals (CIs) by adjusting various covariates. Stratified analysis with variables, such as year, sex, occupational classification, average working hours, was additionally performed.

Results

The crude ORs of depression was 1.51 (95% CI: 1.27–1.80), and the fully adjusted OR with all the covariates was 1.57 (95% CI: 1.30–1.88). This indicated a significant relationship between occupational SHS and depression. The ORs increased every 2 years: 1.07 (95% CI: 0.79–1.44) in 2014, 1.88 (95% CI: 1.34–2.64) in 2016, and 2.07 (95% CI: 1.43–2.99) in year 2018. Stratification analysis also showed a significant association between SHS and depression among those in the prolonged work hours group and male employees, as well as blue- and white-collar workers.

Conclusion

SHS in the workplace was significantly associated with workers' depression. Our study provides insights into the impact of exposure to SHS for workers and provides a basis for further research and policy-making in this field.

Neuroprotective effects of Olea europaea L. fruit extract against cigarette smoke-induced depressive-like behaviors in Sprague-Dawley rats

Depression is broadly acclaimed as a mental health anomaly and despite advancements in the development of antidepressant drugs, they are linked with side effects. Dietary modifications and medicinal plants like olives can be used as effective strategies due to their antioxidant, immune-modulatory, antiinflammatory, and anticonvulsant properties. Considering the compositional alterations in olive fruits during ripening, the antidepressant potential of olive fruits at different degrees of ripeness, that is, un-ripened (green) and ripened (black) was investigated. Rats were randomly divided into five groups: G₀ (Normal diet), G₁ (Normal diet + smoke exposure (SE), G₂ (Normal diet + SE + Citalopram), G₃ (Normal diet + SE + Green olive extract), and G₄ (Normal diet + SE + Black olive extract). Depressive-like behaviors were induced in all groups through cigarette smoke exposure except G₀ . Green and black olive extracts prevented depressive behaviors by reducing the immobility time of rats in forced swim test and tail suspension test while increased the latency to respond in hot plate assay. Moreover, lipid peroxidation in brain tissue was reduced with citalopram, green, and black olive extracts. Additionally, treatments also enhanced the antioxidant pool of brain tissues. Histological examination revealed that olive extracts and citalopram prevented cigarette smoke-induced moderate to severe necrosis and congestion in the brain parenchyma and elucidated antidepressant potential by improving the expression of monoamine oxidase-A, solute carrier family 6 member 4, and brain-derived neurotrophic factor genes. Conclusively, olives may act as a promising antidepressant agent in ameliorating cigarette smoke-induced depressive-like behaviors. PRACTICAL APPLICATIONS: Olive extracts at both ripening stages revealed an antidepressant-like effect almost similar to the standard antidepressant drug and also prevented oxidative damages. Therefore, from the current findings, it can be recommended that food ingredients with antidepressant potential like olives should be incorporated in future interventions to combat depression/psychiatric anomalies and diet therapy should be encouraged to alleviate lifestyle-related disorders.