Male tobacco smoke load and non-lung cancer mortality associations in Massachusetts

<p>Abstract</p> <p>Background</p> <p>Different methods exist to estimate smoking attributable cancer mortality rates (Peto and Ezzati methods, as examples). However, the smoking attributable estimates using these methods cannot be generalized to all population sub-groups. A simpler method has recently been developed that can be adapted and applied to different population sub-groups. This study assessed cumulative tobacco smoke damage (smoke load)/non-lung cancer mortality associations across time from 1979 to 2003 among all Massachusetts males and ages 30–74 years, using this novel methodology.</p> <p>Methods</p> <p>Annual lung cancer death rates were used as smoke load bio-indices, and age-adjusted lung/all other (non-lung) cancer death rates were analyzed with linear regression approach. Non-lung cancer death rates include all cancer deaths excluding lung. Smoking-attributable-fractions (SAFs) for the latest period (year 2003) were estimated as: 1-(estimated unexposed cancer death rate/observed rate).</p> <p>Results</p> <p>Male lung and non-lung cancer death rates have declined steadily since 1992. Lung and non-lung cancer death rates were tightly and steeply associated across years. The slopes of the associations analyzed were 1.69 (95% confidence interval (CI) 1.35–2.04, r = 0.90), and 1.36 (CI 1.14–1.58, r = 0.94) without detected autocorrelation (Durbin-Watson statistic = 1.8). The lung/non-lung cancer death rate associations suggest that all-sites cancer death rate SAFs in year 2003 were 73% (Sensitivity Range [SR] 61–82%) for all ages and 74% (SR 61–82%) for ages 30–74 years.</p> <p>Conclusion</p> <p>The strong lung/non-lung cancer death rate associations suggest that tobacco smoke load may be responsible for most prematurely fatal cancers at both lung and non-lung sites. The present method estimates are greater than the earlier estimates. Therefore, tobacco control may reduce cancer death rates more than previously noted.</p

Smoking and Ischemic Heart Disease Disparities Between Studies, Genders, Times, and Socioeconomic Strata

Large, unexplained, but possibly related disparities exist between heart disease risks observed in differing genders, educational levels, times, and studies. Such heart disease disparities might be related to cumulative tobacco smoke damage (smoke load) disparities that are overlooked in standard assessments of point smoking status. So, I reviewed possible relationships between smoke load and heart disease levels across genders, educational strata, years, and leading studies. Smoker heart disease risk assessments in the Nurses Health Study (Nurses), Cancer Prevention Study-II (CPS-II), and British Doctors studies were compared and related to their likely selection and misclassification biases. Relationships between smoke loads and United States (US) education- and gender-related heart disease mortality disparities were qualitatively assessed using lung cancer rates as a smoke load proxy. The high heart disease mortality risks observed in smoking Nurses in 1980–2004 and in less educated US women in 2001 were qualitatively associated with their higher smoke loads and lower selection and exposure misclassification biases than in the CPS-II and Doctors studies. Smoking-attributable heart disease death tolls and disparities extrapolated from mortality ratios from the CPS-II and Doctors studies may be substantial underestimates. Such studies appear to have compared convenience samples of light smokers to lighter smokers instead of comparing representative smokers to the unexposed. Further efforts to minimize smoke exposures and better quantify cumulative smoking-attributable burdens are needed

Smoking as a Risk Factor for Injury Death: A Meta-analysis of Cohort Studies

Background. Injury and tobacco effects represent one-quarter of the global burden of disease. Under- standing the causes of injury and the effects of smoking may help reduce those burdens. Some smokers have high risks of injury.We provide an initial meta-analysis of cohort associations between smoking and fatal injury. Methods. Three authors independently searched MEDLINE, and bibliographies of the pertinent studies found, for cigarette smoker-specific injury death data which allowed estimation of an appropriate relative risk (RR) and 95% confidence interval (CI). Relative risks and dose response were summarized by fixed effects and Poisson modeling, respectively. Results. Six studies covering 10 pertinent cohorts were located. Associations between smoking and injury death have been significant after adjustment or, in effect, stratification for age, race, sex, country, and, respectively, alcohol, marriage, education, and body mass; job and time period; job, alcohol, and exercise; etc. Summary dose-response trends were significantly positive (P &lt; 0.00005). Cigarette smoking predicted summary injury death crude RRs of 1.61 (CI 1.44-1.81) vs never smokers and 1.39 (CI 1.25-1.55) vs ex-smokers. Conclusions. Smoking has significant, consistent,dose- response, often strong and independent, prospective associations with injury death, internationall

Current Smoking and Risk of Coronavirus Infection and Illness in a Highly Controlled Challenge Study: A Re-analysis of the British Cold Study.

IntroductionMeta-analyses have shown an association between smoking and the risk of Coronavirus Disease 2019 (COVID-19) disease severity, but the risk of smoking and coronavirus infection is less clear.Aims and methodsWe re-analyzed data from the British Cold Study, a 1986-1989 challenge study that exposed 399 healthy adults to 1 of 5 "common cold" viruses (including n = 55 for coronavirus 229E). Participants with cotinine levels below 15 ng/mL (noncurrent smokers) were compared with participants with higher cotinine levels or self-reported smoking (current smokers). We calculated overall and coronavirus-specific unadjusted and adjusted relative risks (RRs) for current smoking and each outcome (infection and illness), and tested whether each association was modified by the type of respiratory virus.ResultsCurrent smokers had a higher adjusted risk than noncurrent smokers for infection (adjusted RR [aRR] = 1.12, 95% CI: 1.01, 1.25) and illness (aRR = 1.48, 95% CI: 1.11, 1.96). Neither association was modified by an interaction term for smoking and type of virus (infection: p = .44, illness: p = .70). The adjusted RR estimates specific to coronavirus 229E for infection (aRR = 1.22, 95% CI: .91, 1.63) and illness (RR = 1.14, 95% CI: .62, 2.08) were not statistically significant.ConclusionsThese RRs provide estimates of the strength of associations between current smoking and infection and illness that can be used to guide tobacco control decisions.ImplicationsSystematic reviews and meta-analyses have found an association between smoking and COVID-19 disease severity, but fewer studies have examined infection and illness. The British Cold Study, a high-quality challenge study that exposed healthy volunteers to respiratory viruses including a coronavirus, provides an opportunity to estimate the RR for current smoking and infection and illness from coronaviruses and other viruses to guide tobacco control decisions. Compared with noncurrent smokers, current smokers had a 12% increased risk of having a laboratory-confirmed infection and a 48% increased risk of a diagnosed illness, which was not modified by the type of respiratory virus including a coronavirus

Smoking as a Risk Factor for Accident Death: A Meta-analysis of Cohort Studies.

This meta-analysis discusses the consistency, strength, dose-response, independence, and generalizability of published cohort data on accident death relative risks in smokers. To locate data, three authors independently searched MEDLINE, and bibliographies of the pertinent studies found, for data which allowed estimation of an appropriate cigarette smoker accident death relative risk (and 95% confidence interval). Relative risks and dose-response were summarized by fixed effects and Poisson modeling, respectively. Four pertinent cohort studies including eight populations were located. Cigarette smoking predicted summary accident death relative risks of 1.51 (95% confidence interval 1.27-1.78) versus never smokers and 1.35 (1.17-1.57) versus ex-smokers. Summary dose-response trends were significant (P�0.0000) versus never or least smoking referents. In individual studies, the smoking:accident death association persisted after adjustment or, in effect stratification, for age, race, sex, and occupation: occupation and time period; or numerous cardiac risk factors. This meta-analysis found significant, consistent, dose-response, often strong and independent (of age, race, and sex), prospective associations of smoking with accident death, internationally. Further studies and warnings of the smoking:accident death associations seem merited (c) 200

Relationship between obesity and coronary heart disease among urban Bangladeshi men and women.

The aim of the study was to examine the association of different measures of obesity (body mass index or BMI, waist circumference or WC, waist to hip ratio or WHR and waist height ratio or WHtR) with coronary heart disease (CHD) in a Bangladeshi population. The study included 189 hospitalized CHD cases (133 men and 52 women) and 201 controls (137 men and 68 women). Logistic regression was done to assess the associations between obesity and CHD. The mean age was 53.1 ± 8.3 for men and 51.9 ± 8.4 for women. After adjustment for confounders the odds ratio (OR) of CHD for men was 1.69 (95% CI, 1.24-2.32), 1.94 (95% CI 1.40-2.70), and 1.32 (95% CI, 1.01-2.16) per 1 standard deviation (SD) increase in BMI, WC, and WHtR respectively. The OR for women was 2.64 (CI, 1.61-4.34), 1.82 (95% CI 1.12-2.95), 2.32 (95% CI, 1.36-3.96), and 1.94 (95% CI, 1.23-3.07) per 1 SD increase in BMI, WC, WHtR and WHR respectively. Since both total obesity and abdominal adiposity were associated with development of CHD and since measurement of WC and BMI are inexpensive, both should be included in the clinical setting for CHD risk assessment for this group of population