Smoking-attributable Mortality in Korea, 2020: A Meta-analysis of Four Databases.

Objectives: Estimating the number of deaths caused by smoking is crucial for developing and evaluating tobacco control and smoking cessation policies. This study aimed to determine smoking-attributable mortality (SAM) in Korea in 2020. Methods: Four large-scale cohorts from Korea were analyzed. A Cox proportional-hazards model was used to determine the hazard ratios (HRs) of smoking-related death. By conducting a meta-analysis of these HRs, the pooled HRs of smoking-related death for 41 diseases were estimated. Population-attributable fractions (PAFs) were calculated based on the smoking prevalence for 1995 in conjunction with the pooled HRs. Subsequently, SAM was derived using the PAF and the number of deaths recorded for each disease in 2020. Results: The pooled HR for all-cause mortality attributable to smoking was 1.73 for current male smokers (95% CI, 1.532-1.954) and 1.631 for current female smokers (95% CI, 1.371-1.94). Smoking accounted for 33.2% of all-cause deaths in men and 4.6% in women. Additionally, it was a factor in 71.8% of male lung cancer deaths and 11.9% of female lung cancer deaths. In 2020, smoking was responsible for 53,930 male deaths and 6,283 female deaths, totaling 60,213 deaths. Conclusions: Cigarette smoking was responsible for a significant number of deaths in Korea in 2020. Monitoring the impact and societal burden of smoking is essential for effective tobacco control and harm prevention policies.

Smoking-attributable mortality among Korean adults in 2019.

OBJECTIVES: Tobacco use ranks among the leading preventable causes of death worldwide. This study was conducted to calculate the mortality rate attributable to smoking in Korea for 2019 and to highlight the importance of tracking and monitoring smoking-related deaths for public health purposes. METHODS: Population attributable risk (PAR) was used to estimate the number of deaths related to smoking in 2019. PAR percentages were applied to the estimated mortality figures for various diseases, with PAR determined based on relative risk (RR). Levin's formula was used to calculate PAR, and RR was adjusted for age and alcohol consumption using Cox proportional hazards regression model to derive disease-specific regression coefficients. The analysis incorporated previously determined smoking rates from 1985, and use rates of novel tobacco products were not considered. RESULTS: The findings revealed a total of 67,982 smoking-attributable deaths in Korea in 2019, 56,993 of which occurred in men and 11,049 in women. The PAR of smoking for various causes of death in adult men was highest for lung cancer at 74.9%, followed by pneumonia (29.4%), ischemic heart disease (42.3%), and stroke (30.2%). For women, the PAR for smoking-related death was highest for lung cancer (19.9%), followed by stroke (7.6%), pneumonia (5.7%), and ischemic heart disease (9.1%). CONCLUSIONS: In countries experiencing rapid fluctuations in smoking rates, including Korea, regular studies on smoking-related mortality is imperative. Furthermore, it is necessary to investigate smoking-related deaths, including the prevalence of novel tobacco product use, to accurately gauge the risks associated with emerging tobacco products.

Do Weight Changes Affect the Association between Smoking Cessation and the Risk of Stroke Subtypes in Korean Males?

(1) Background: We investigated whether weight changes affect the association between smoking cessation and stroke risk; (2) Methods: Overall, 719,040 males were categorized into eight groups according to smoking status (sustained smokers, non-smokers, long-term quitters (quit > 4 years), and recent quitters (quit < 4 years)) and post-cessation weight change (-5 kg, -5.0 to 0.1 kg, maintainers, 0.1-5.0 kg, and >5.0 kg). The hazard ratios (HR) and 95% confidence intervals (CI) for incident total, ischemic, and hemorrhagic strokes, including subarachnoid and intracerebral hemorrhage, were calculated using Cox proportional hazard models; (3) Results: We detected 38,730 strokes (median follow-up, 25.7 years), including 30,609 ischemic and 9055 hemorrhagic strokes. For recent quitters with a >5.0 kg or 0.1-5.0 kg weight increase, maintainers, or those who lost 0.1-5 kg, the multivariable HR for total stroke was 0.73 (95% CI, 0.67-0.79), 0.78 (95% CI, 0.74-0.82), 0.77 (95% CI, 0.69-0.85), 0.84 (95% CI, 0.77-0.90), and 1.06 (95% CI, 0.92-1.23), respectively, compared with that of sustained smokers; (4) Conclusions: Comparable patterns were obtained for stroke subtypes. Thus, we strongly recommend quitting smoking, as weight gain after quitting smoking does not alter the stroke-related benefits.

Prediction of cancer survivors' mortality risk in Korea: a 25-year nationwide prospective cohort study.

OBJECTIVES: This study aimed to investigate the factors affecting cancer survival and develop a mortality prediction model for Korean cancer survivors. Our study identified lifestyle and mortality risk factors and attempted to determine whether health-promoting lifestyles affect mortality. METHODS: Among the 1,637,287 participants in the Korean Cancer Prevention Study (KCPS) cohort, 200,834 cancer survivors who were alive after cancer diagnosis were analyzed. Discrimination and calibration for predicting the 10-year mortality risk were evaluated. A prediction model was derived using the Cox model coefficients, mean risk factor values, and mean mortality from the cancer survivors in the KCPS cohort. RESULTS: During the 21.6-year follow-up, the all-cause mortality rates of cancer survivors were 57.2% and 39.4% in men and women, respectively. Men, older age, current smoking, and a history of diabetes were high-risk factors for mortality, while exercise habits and a family history of cancer were associated with reduced risk. The prediction model discrimination in the validation dataset for both KCPS all-cause mortality and KCPS cancer mortality was shown by C-statistics of 0.69 and 0.68, respectively. Based on the constructed prediction models, when we modified exercise status and smoking status, as modifiable factors, the cancer survivors' risk of mortality decreased linearly. CONCLUSIONS: A mortality prediction model for cancer survivors was developed that may be helpful in supporting a healthy life. Lifestyle modifications in cancer survivors may affect their risk of mortality in the future.

Association between Early Menopause, Gynecological Cancer, and Tobacco Smoking: A Cross-Sectional Study.

BACKGROUND: The rates of smoking among women are rising. Previous studies have shown that smoking is associated with early menopause. However, the association of gynecological cancer, including breast and cervical cancer, with early menopause and smoking, remains unclear. Therefore, this study aimed to determine the association between smoking and early menopause, breast cancer, and cervical cancer. METHODS: This cross-sectional study used data from the Korean National Health and Nutritional Survey Examination (KHANES) (2016-2018). Early menopause was defined as menopause before 50 years of age. RESULTS: A total of 4,481 participants were included in the analysis. There was no association between early menopause and cervical cancer (adjusted odds ratio [aOR]: 1.435, 95% confidence interval [CI]: 0.730-2.821), but women who had experienced early menopause had a significantly higher risk of breast cancer than women who had experienced normal menopause (aOR: 1.683, 95% CI: 1.089-2.602, p=0.019). Early menopause was not associated with an increased risk of breast cancer in ever-smoker (aOR: 0.475, 95% CI: 0.039-5.748), but was associated with a significantly increased risk of breast cancer in never-smokers (aOR: 1.828, 95% CI: 1.171-2.852). CONCLUSIONS: Early menopause was associated with an increased risk of breast cancer in women who had never smoked, but not in women who had ever smoked.