Contrasting male and female trends in tobacco-attributed mortality in China: evidence from successive nationwide prospective cohort studies
Bibliographic record
Abstract
BACKGROUND: Chinese men now smoke more than a third of the world's cigarettes, following a large increase in urban then rural usage. Conversely, Chinese women now smoke far less than in previous generations. We assess the oppositely changing effects of tobacco on male and female mortality. METHODS: Two nationwide prospective studies 15 years apart recruited 220,000 men in about 1991 at ages 40-79 years (first study) and 210,000 men and 300,000 women in about 2006 at ages 35-74 years (second study), with follow-up during 1991-99 (mid-year 1995) and 2006-14 (mid-year 2010), respectively. Cox regression yielded sex-specific adjusted mortality rate ratios (RRs) comparing smokers (including any who had stopped because of illness, but not the other ex-smokers, who are described as having stopped by choice) versus never-smokers. FINDINGS: Two-thirds of the men smoked; there was little dependence of male smoking prevalence on age, but many smokers had not smoked cigarettes throughout adult life. Comparing men born before and since 1950, in the older generation, the age at which smoking had started was later and, particularly in rural areas, lifelong exclusive cigarette use was less common than in the younger generation. Comparing male mortality RRs in the first study (mid-year 1995) versus those in the second study (mid-year 2010), the proportional excess risk among smokers (RR-1) approximately doubled over this 15-year period (urban: RR 1·32 [95% CI 1·24-1·41] vs 1·65 [1·53-1·79]; rural: RR 1·13 [1·09-1·17] vs 1·22 [1·16-1·29]), as did the smoking-attributed fraction of deaths at ages 40-79 years (urban: 17% vs 26%; rural: 9% vs 14%). In the second study, urban male smokers who had started before age 20 years (which is now typical among both urban and rural young men) had twice the never-smoker mortality rate (RR 1·98, 1·79-2·19, approaching Western RRs), with substantial excess mortality from chronic obstructive pulmonary disease (COPD RR 9·09, 5·11-16·15), lung cancer (RR 3·78, 2·78-5·14), and ischaemic stroke or ischaemic heart disease (combined RR 2·03, 1·66-2·47). Ex-smokers who had stopped by choice (only 3% of ever-smokers in 1991, but 9% in 2006) had little smoking-attributed risk more than 10 years after stopping. Among Chinese women, however, there has been a tenfold intergenerational reduction in smoking uptake rates. In the second study, among women born in the 1930s, 1940s, 1950s, and since 1960 the proportions who had smoked were, respectively, 10%, 5%, 2%, and 1% (3097/30,943, 3265/62,246, 2339/97,344, and 1068/111,933). The smoker versus non-smoker RR of 1·51 (1·40-1·63) for all female mortality at ages 40-79 years accounted for 5%, 3%, 1%, and <1%, respectively, of all the female deaths in these four successive birth cohorts. In 2010, smoking caused about 1 million (840,000 male, 130,000 female) deaths in China. INTERPRETATION: Smoking will cause about 20% of all adult male deaths in China during the 2010s. The tobacco-attributed proportion is increasing in men, but low, and decreasing, in women. Although overall adult mortality rates are falling, as the adult population of China grows and the proportion of male deaths due to smoking increases, the annual number of deaths in China that are caused by tobacco will rise from about 1 million in 2010 to 2 million in 2030 and 3 million in 2050, unless there is widespread cessation. FUNDING: Wellcome Trust, MRC, BHF, CR-UK, Kadoorie Charitable Foundation, Chinese MoST and NSFC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".