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IntroductionWe conducted a mortality case-control study to assess the risks of all-cause and major causes of death attributable to smoking in Tianjin from 2010 through 2014. The death registry–based study used data from The Tianjin All Causes of Death Surveillance System, which collects information routinely on smoking of the deceased in the death certificate of Tianjin Centers for Disease Control and Prevention.MethodsCases (n = 154,086) and controls (n = 25,476) were deaths at 35 to 79 years from smoking-related and nonsmoking-related causes, respectively. Mortality rate ratios (RRs) for ever smokers versus never smokers, with adjustment for sex, 5-year age group, education, marital status, and year of death, and smoking-attributed fractions were calculated.ResultsThe RRs in men were 1.38 (95% confidence interval [CI], 1.33–1.43) for all causes and 3.07 (95% CI, 2.91–3.24) for lung cancer, and in women were 1.46 (95% CI, 1.39–1.54) and 4.07 (95% CI, 3.81–4.35). The smoking-attributed fractions for all causes and for lung cancer in men were 15.4% and 50.2%, respectively, and in women were 7.3% and 32.7%, respectively. Smoking annually caused an average of 3,756 (9.4%) deaths, mostly from lung cancer in men (47.4%) and women (66.9%). Women who started smoking before 30 had a higher RR (1.79; 95% CI, 1.63–1.97) than men who did so (1.48; 95% CI, 1.41–1.56).ConclusionLung cancer was the main cause of smoking-induced deaths in both sexes. Tobacco use is a major cause of premature deaths in men aged 35 to 79 years. Young women must be urged to not start smoking because they could have greater risk of all-cause and lung cancer deaths than men do.

INTRODUCTION Smoking-attributed mortality is increasing steadily in most developing countries. The aim of the study is to assess the reduction in smoking-associated mortality following cessation. METHODS Death data were collected from 2016 to 2017. Cases were deaths from pre-defined diseases of interest (65298); controls were deaths from pre-defined non-smoking-related diseases (13527). Case versus control odds ratios for ex-smokers versus smokers were calculated by age, sex, marital status and education with standardized logistic regression. These are described as mortality rate ratios (RRs, calculated as odds ratios), with a group-specific confidence interval (CI). The statistical analysis of the data was conducted from June to August 2019. RESULTS For deaths from pre-defined non-smoking-related diseases at age 35–59 years, the RRs for quitting smoking 0–4, 5–9 or ≥10 years ago and never smoking were 0.66 (95% CI: 0.55–0.78), 0.58 (95% CI: 0.38–0.88), 0.61 (95% CI: 0.45–0.82), and 0.43 (95% CI: 0.39–0.46), respectively. The same trend was found at ages 60–69 years and 70–79 years. Younger age of quitting (25–44 or 45–64 years) appeared to be associated with greater protection among the age groups: RR was 0.55 (95% CI: 0.42–0.74) and 0.67 (95% CI: 0.56–0.79), respectively, at age 35–59 years. Among the patients who died of lung cancer, the strong protective effect can only be observed when the duration of quitting is ≥10 years. The effect of smoking cessation on the risk of death from cardiovascular disease can be observed when the duration of quitting is 1–5 years. CONCLUSIONS Longer durations of smoking cessation are associated with progressively lower mortality rates from the diseases of interest, such as lung cancer and other smoking related cancers. For sustainable monitoring of tobacco-attributed mortality, smoking information over decades, such as smoking duration and quit smoking years, should be recorded during registration of death.

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Background To observe road traffic violation behaviors among courier and take-out food delivery electric bike rider and to characterize road traffic injuries occurred in this occupational population. Methods A cross-sectional field study including roadside observational data collection and face-to-face interviews was conducted by retrospective response through street intercept. Results 600 target populations were observed, and 480 were interviewed. The rate of over speed was 91.3%, and windshield use during winter was 91.2%. Traffic rule violations included riding in the motor vehicle lane (32.8%), not waiting behind the white line at a red light (23.3%), and using a cell phone when riding (21.2%). Helmet use was significantly more common in daytime than night (P=0.028). About 46% rode e-bike more than 8 hours per day. 76% of interviewees had suffered a traffic crash. About 14% crashes happened in motor-vehicle lanes and 8% in sidewalks. A logistic regression analysis indicated that compared with uninjured riders, injured riders showed significantly greater odds ratios of unsafe behaviors for running red lights (OR=1.75), and a protective effect for wearing a helmet (OR=0.56). Discussion Road safety issues need to be addressed through establishment or improvement of e-bike legislation in this vulnerable occupational group.

INTRODUCTION The All Causes of Death Surveillance (ACDS) system was used to measure smoking-attributed mortality by inserting questions on smoking on death certificates. Smoking status information of the deceased has been routinely collected in death certificates since 2010. We describe a death registry-based case-control study using smoking and cause-of-death data for the period 2010-15. METHODS From 2010, three questions about the smoking status of the deceased were inserted in a revised death certificate: 1) Smoking status (current smoker, quit smoking, never smoker); 2) Number of cigarettes per day smoked; and 3) Number of years of smoking. A data-accuracy survey of 1788 telephone interviews of the family of the deceased was also conducted. Smoking habits (current/ex-smoker vs non-smoker) were compared in study cases (persons who died of lung cancer and other diseases known to be caused by smoking) and the controls (never smokers). Multivariate logistic regression analysis was conducted to estimate relative risks, RR (odds ratios) for smoking-attributed mortality, for lung cancer and all causes of death related to smoking, adjusted for 5-year interval age groups, education, marital status, and year of death. RESULTS During the study period (2010-15), the annual crude death reporting rates ranged from 6.5‰ to 7.0‰. The reporting rates of smoking status, smoking history and the number of cigarettes smoked daily were 95.5%, 98.6% and 98.6%, respectively. Compared to never smokers, the RR of ever smoking in males was 1.38 (95% CI: 1.33-1.43) for all causes of smoking-related deaths and 3.07 (95% CI: 2.91-3.24) for lung cancer, while in females the values were 1.46 (95% CI: 1.39-1.54) for all causes of smoking-related deaths and 4.07 (95% CI: 3.81-4.35) for lung cancer. The results in Tianjin are in accord with published results from previous studies. CONCLUSIONS Levels and trends in smoking attributed mortality can be measured at low cost by using the stable, complete and effective ACDS system in Tianjin.

a b s t r a c tTo investigate the levels of exposure to particulate-bound polycyclic aromatic hydrocarbon (PAH) and to estimate the risk these levels pose to traffic assistants (TAs) in Tianjin (a megacity in North China), a measurement campaign (33 all-day exposure samples, 25 occupational-exposure samples and 10 indoor samples) was conducted to characterize the TAs' exposure to PAHs, assess the cancer risk and identify the potential sources of exposure. The average total exposure concentration of 14 PAHs was approximately 2871 ± 928 ng/m 3 (on-duty), and 1622 ± 457 ng/m 3 (all-day). The indoor PAHs level was 1257 ± 107 ng/m 3 . After 8000 Monte Carlo simulations, the cancer risk resulting from exposure to PAHs was found to be approximately 1.05 × 10 −4 . A multivariate analysis was applied to identify the potential sources, and the results showed that, in addition to vehicle exhaust, coal combustion and cooking fumes were also another two important contributors to personal PAH exposure. The diagnostic ratios of PAH compounds agree with the source apportionment results derived from principal component analysis.