Pulmonary Tuberculosis and Lung Cancer Risk in Current Smokers: The Seoul Male Cancer Cohort Study

Authors evaluated pulmonary tuberculosis (PTB) history as a risk factor for lung cancer in current male smokers in a prospective, population-based cohort study. The subjects were the 7,009 males among the participants in the Seoul Male Cancer Cohort Study for whom there was full information on PTB history and smoking habits. With a 16-yr follow-up, 93 cases of lung cancer occurred over the 99,965 person-years of the study. The estimated relative risk (RR) of PTB history of current smokers in lung cancer after adjusting for three confounders - intake of coffee and tomatoes, and age at entry - was 1.85 (95% CI: 1.08-3.19). The observed joint RRs and attributable risks (ARs) across strata of three confounders were greater than the expected, indicating a positive interaction. Thus a history of PTB in current smokers may be another risk factor for lung cancer. Based on a synergic interaction, a heavy male smoker with a PTB history would be expected to belong to the group at high risk of lung cancer.     

Influence of Body Mass Index,Smoking, and Blood Pressure on Survival of Patients with Surgically-Treated,Low Stage Renal Cell Carcinoma: A 14-Year Retrospective Cohort Study

The association of body mass index, smoking, and blood pressure, which are related to the three well-established risk factors of renal cell carcinoma, and survival in patients with renal cell carcinoma is not much studied. Our objective was to evaluate this association. A cohort of 1,036 patients with low stage (pT1 and pT2) renal cell carcinoma who underwent radical or partial nephrectomy were enrolled. We retrospectively reviewed medical records and collected survival data. The body mass index, smoking status, and blood pressure at the time of surgery were recorded. Patients were grouped according to their obesity grade, smoking status, and hypertension stage. Survival analysis showed a significant decrease in overall (P = 0.001) and cancer-specific survival (P < 0.001) with being underweight, with no differences of smoking status or perioperative blood pressure. On multivariate analysis, perioperative blood pressure ≥ 160/100 mmHg (HR, 2.642; 95% CI, 1.221-5.720) and being underweight (HR, 4.320; 95% CI, 1.557-11.984) were independent predictors of overall and cancer-specific mortality, respectively. Therefore, it is concluded that being underweight and perioperative blood pressure ≥ 160/100 mmHg negatively affect cancer-specific and overall survival, respectively, while smoking status does not influence survivals in patients with renal cell carcinoma.     

Periodontal risk assessment in a teaching hospital population in Saudi Arabia’s Eastern Province

ObjectiveWith this cross-sectional study, we aimed to evaluate factors associated with moderate and high risk of periodontal disease (PD) progression in the Saudi population.MethodsWe reviewed 281 patients’ clinical charts from predoctoral periodontal clinics at the dental teaching hospital in the College of Dentistry (COD) at Imam Abdulrahman Bin Faisal University (IAU) in Dammam, Saudi Arabia. After obtaining ethical approval, we determined the Periodontal Risk Assessment (PRA) of the included patients based on the modified criteria developed by Lang and Tonetti (2003). We used logistic regression on stratified data and divided the results into two categories (low-moderate and high risk) to assess the effect modifier for potential risk factors. We used SPSS version 22 for data analysis, and considered a P-value ≤ 0.05 to be statistically significant.ResultsOut of the 281 patients, 104 (37.0%) were male and 177 (63.0%) were female, with a mean age of 39.9 ± 14.0 years; 78.1% were Saudi nationals, 77% were married, and 44.6% were in the age group of 30 to 49. The PRA revealed 86 (30.5%) to represent high risk, 108 (38.3%) denoted moderate risk, and 88 (31.2%) signaled low risk for periodontitis. Logistic regression analysis showed that males were three times more likely to have high PRA (OR = 3.24) and to be married (OR = 2.77), as well as to be active smokers (OR = 8.87). The highest predictive factors of high PRA were 8 or more pockets ≥ 5 mm (OR = 29.0), those with active diabetes mellitus (DM; OR = 10.2), and those with 8 or more missing teeth (OR = 9.15).ConclusionSaudi males who are married and have residual periodontal pockets, are actively diabetic, and with missing teeth are at high risk of PD. Further research is needed with a larger sample size comparing the general population with and without PD.     

Sex-specific environmental influences affecting MS development

Vitamin D status, smoking, and Epstein–Barr virus infection (EBV) may all contribute to explain differences in disease prevalence and incidence of Multiple Sclerosis (MS). MS affects women more often than men, and recent cross-sectional study assessments provide evidence of increased female to male prevalence in relapsing remitting MS patients, suggesting that sex hormones may exert an active role in disease pathogenesis. Studies in both humans and animal disease models demonstrate a functional synergy for the immunomodulatory effects of Vitamin D3 and 17-β estradiol. Both smoking and EBV infection clearly increase MS risk, and smoking history has also been associated with poorer disease prognosis. However, neither factor can explain the recent trend indicating greater female prevalence. Therefore, large population-based case–control studies from well defined geographic areas with homogeneous populations should be performed, in order to define environmental factor effects, and sex hormone influences, to better understand prevalence and incidence gender differences observed.     

Process evaluation of a mHealth program: Lessons learned from Stop My Smoking USA,a text messaging-based smoking cessation program for young adults

Objective

Report lessons learned in an RCT of Stop My Smoking (SMS) USA, a mHealth smoking cessation program for young adult smokers.

Methods

164 18–24-year-olds were recruited nationally, online in 2011. Program evaluation data were provided at 12-week post-Quit Day.

Results

(1) Inviting participants to complete a brief text messaging survey and then asking them to complete a longer online survey resulted in the highest response rate (89%). (2) The positive tone of program messages was the most commonly noted program strength. (3) Suggested improvements included more social connectivity and additional assistance overcoming stressful situations. (4) Half of intervention participants moved through the program linearly and half went through various paths that reflected multiple relapses. Suggestions to use pharmacotherapy resulted in 22% of heavy smokers to utilize it.

Conclusion

Participant feedback provided concrete ways in which this and other young adult-focused interventions can improve messaging and program features to be even more salient.

Practice implications

Future young adult mHealth interventions could: Integrate models that are flexible to different “paths” of behavior change; address stressful life events directly and comprehensively; integrate proactive messaging that promotes pharmacotherapy options; and use text messaging as a gateway to longer online surveys.     

Smoking and weight among patients using clozapine

Abstract

Background: Both obesity and smoking are common in schizophrenia patients taking clozapine, causing cardiovascular disease and premature deaths. Methods: Two hundred and thirty-seven patients with schizophrenia or related psychoses treated with clozapine completed the Liverpool University Neuroleptic Assessment Scale (LUNSERS) and a questionnaire including current height, weight, changes therein and smoking status. Aims: The aim of this study was to analyze weight and weight change in smoking and non-smoking patients taking clozapine. A possible interaction between obesity and smoking was explored. Results: No association was found between weight change and smoking status during clozapine treatment. There was no significant difference in body mass index (BMI) between non-smokers and smokers. In the analysis of covariance (ANCOVA) with BMI as the dependent variable, the best fitting model comprised age, sex, intensity of sedation, and reported amount of smoking as explanatory variables (ηp²= 0.116; P = 0.029; power = 0.750). None of the explanatory proportions of any single factor was significant. Conclusions: Estimated according to reported weight gain and BMI, no difference was found between smoking and non-smoking clozapine-treated patients. Number of cigarettes smoked explained BMI if age and sex were taken into account. This result is in line with the findings of some general population studies, where heavy smoking has been associated with a greater risk of obesity.