Key Points Question Which is the more important factor in the development of gastrointestinal (GI) cancer: frequency of drinking alcohol or quantity of alcohol consumed per occasion? Findings In this cohort study of 11 737 467 participants, the risk of GI cancer was significantly associated with drinking frequency. Compared with similar weekly alcohol consumption levels, the risk of GI cancer increased with a higher frequency of drinking but decreased with larger amounts per occasion. Meaning This study suggests that frequent drinking may be a more important risk factor for incident GI cancers than the amount of alcohol consumed per occasion, and patients should be careful with their drinking habits, including regular consumption of small amounts of alcohol.

Background: While smoking elevates the risk for cardiovascular disease (CVD) among atrial fibrillation (AF) patients, whether smoking cessation after AF diagnosis actually leads to reduced CVD risk is unclear. We aimed to determine the association of smoking cessation after AF diagnosis with subsequent CVD Risk among South Korean men. Methods: This retrospective cohort study included 2372 newly diagnosed AF male patients during 2003-2012 from the Korean National Health Insurance Service database. Self-reported smoking status within 2 years before and after diagnosis date were determined, after which the participants were divided into continual smokers, quitters (smokers who quit after AF diagnosis), sustained-ex smokers (those who quit prior to AF diagnosis), and never smokers. Participants were followed up from 2 years after AF diagnosis until 31 December 2015 for CVD. Cox proportional hazards regression was used to determine the adjusted hazard ratios (aHRs) and 95% confidence interval (CIs) for CVD according to the change in smoking habits before and after AF diagnosis. Results: The mean (standard deviation, minimum-maximum) age of the study subjects was 62.5 (8.6, 41-89) years. Among AF patients, quitters had 35% reduced risk (aHR 0.65, 95% CI 0.44-0.97) and never smokers had 32% reduced risk (aHR 0.68, 95% CI 0.52-0.90) for CVD compared to continual smokers (p for trend 0.020). Similarly, compared to continual smokers, quitters had 41% risk-reduction (aHR 0.59, 95% CI 0.35-0.99) and never smokers 34% risk-reduction (aHR 0.66, 95% CI 0.46-0.93) for total stroke (p for trend 0.047). Quitters had 50% reduction (aHR 0.50, 95% CI 0.27-0.94), sustained ex-smokers had 36% reduction (aHR 0.64, 95% CI 0.42-0.99), and never smokers had 39% reduction (aHR 0.61, 95% CI 0.41-0.91) in ischemic stroke risk (p for trend 0.047). The risk-reducing effect of quitting on CVD risk tended to be preserved regardless of aspirin or warfarin use. Conclusions: Smoking cessation after AF diagnosis was associated with reduced CVD, total stroke, and ischemic stroke risk.

BackgroundObesity is a global epidemic. Behavior change monitoring using a smartphone application (app) can support weight management in obese patients. These apps must undergo usability testing, which is an important step in mobile healthcare app development. The current study aimed to develop a mobile app for behavioral monitoring and to test its usability including technical effectiveness, user efficiency, and user satisfaction for obese adults.MethodsDevelopment of the Dr. Youth app components included information on behavioral monitoring indicators and their obesity subtypes. The usability of the app was tested with 50 obese adults in a university hospital. Participants were asked to complete eight tasks for evaluating the technical effectiveness of the app. The time to complete each task was measured to test user efficiency. To explore user satisfaction, each participant completed the System Usability Scale (SUS). Descriptive statistics were used to examine the mean user efficiency and SUS scores.ResultsFifty adults (14 men and 36 women, aged 20–59 years) who are obese (body mass index ≥25 kg/m2) were recruited. The mean age of participants was 42.6 years (standard deviation [SD], 10.8 years); their mean body mass index was 29.6 kg/m2 (SD, 5.7 kg/m2). The tasks were completed with a 99% success rate. The overall mean SUS score was 76.65 (SD, 15.43).ConclusionThe Dr. Youth app shows acceptable technical effectiveness, user efficiency, and user satisfaction. Future study is warranted to establish the app’s clinical efficacy.

BackgroundThe combined effect of transitions of metabolic health and weight on cardiovascular disease (CVD) remains unclear. We aimed to examine the association of concurrent changes of metabolic health and weight on CVD over time.Methods and ResultsThe study population consisted of 205 394 from the Korean National Health Insurance Service. Metabolic health was determined by fasting serum glucose, total cholesterol, and blood pressure levels, while obesity was determined by body mass index. All participants were divided into either metabolically healthy nonobese (MHNO), metabolically healthy obese, metabolically unhealthy nonobese, or metabolically unhealthy obese for each of the first (2002–2003) and second (2004–2005) health screening periods, after which participants were followed‐up for CVD from 2006 to 2015. Cox proportional hazards regression was used to determine adjusted hazard ratios (aHRs) and 95% CIs. Among initial MHNO participants, those who became metabolically healthy obese (aHR, 1.25; 95% CI, 1.10–1.41), metabolically unhealthy nonobese (aHR, 1.23; 95% CI, 1.15–1.31), and metabolically unhealthy obese (aHR, 1.34; 95% CI, 1.12–1.61) had elevated risk for CVD compared with those who remained MHNO. Conversely, improving metabolic health and obesity were associated with reduced CVD risk among initially metabolically unhealthy nonobese to secondary MHNO (aHR, 0.79; 95% CI, 0.73–0.84), metabolically unhealthy obese to MHNO (aHR, 0.68; 95% CI, 0.58–0.81), and metabolically unhealthy obese to metabolically healthy obese (aHR, 0.73; 95% CI, 0.66–0.80) participants.ConclusionsChanges toward metabolically unhealthy or obese states resulted in increased CVD risk. Improving metabolic health along with reducing weight may lead to decreased risk of CVD.

Although smoking has a significant impact on mortality and morbidity of cancer patients, many patients continue to smoke post-diagnosis. The purpose of this study was to investigate prevalence and predictors of sustained smoking among male cancer survivors. Materials and Methods The Korean National Health Insurance Service-National Health Screening Cohort database was used for this population-based, retrospective study. Study subjects were 15,141 men who were diagnosed with their first incident cancer between 2004 and 2011. Changes in smoking status before and after a cancer diagnosis were investigated. For patients who were current smokers pre-diagnosis, association between post-diagnosis sustained smoking and demographic, socioeconomic, and clinical variables were examined. Results Of the 4,657 pre-diagnosis smokers, 2,255 (48%) had quit after cancer diagnosis, while 2,402 (51.6%) continued to smoke. In a multivariate logistic regression analysis, younger age at cancer diagnosis (adjusted odds ratio [aOR], 1.37; 95% confidence interval [CI], 1.21 to 1.55; p < 0.001), low socioeconomic status (aOR, 1.29; 95% CI, 1.15 to 1.45; p ! 0.001), pre-diagnosis heavy smoking (aOR, 1.24; 95% CI, 1.09 to 1.41; p=0.001), diagnosis of nonsmoking-related cancer (aOR, 1.67; 95% CI, 1.42 to 1.96; p < 0.001), and high serum glucose level (aOR, 1.23; 95% CI, 1.03 to 1.46; p=0.019) were associated with sustained smoking after a cancer diagnosis. Conclusion Almost half of the male smokers continue to smoke after a cancer diagnosis. Targeted interventions for smoking cessation should be considered for patients with younger age, low socioeconomic status, heavy smoking history, non-smoking-related cancer, and high blood glucose levels.