Health-Related Quality of Life Among Pregnant Women With Pre-pregnancy Smoking and Smoking Cessation During Pregnancy in China: National Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: Previous studies have hardly explored the influence of pre-pregnancy smoking and smoking cessation during pregnancy on the health-related quality of life (HRQoL) of pregnant women, which is a topic that need to be addressed. In addition, pregnant women in China constitute a big population in the largest developing country of the world and cannot be neglected. OBJECTIVE: This study aims to evaluate the HRQoL of pregnant women in China with different smoking statuses and further estimate the association between pre-pregnancy smoking, smoking cessation, and the HRQoL. METHODS: A nationwide cross-sectional study was conducted to determine the association between different smoking statuses (smoking currently, quit smoking, never smoking) and the HRQoL in pregnant women across mainland China. A web-based questionnaire was delivered through the Banmi Online Maternity School platform, including questions about demographics, smoking status, and the HRQoL. EuroQoL Group's 5-dimension 5-level (EQ-5D-5L) scale with EuroQoL Group's visual analog scale (EQ-VAS) was used for measuring the HRQoL. Ethical approval was granted by the institutional review board of the First Affiliated Hospital of Sun Yat-sen University (ICE-2017-296). RESULTS: From August to September 2019, a total of 16,483 participants from 31 provinces were included, of which 93 (0.56%) were smokers, 731 (4.43%) were ex-smokers, and 15,659 (95%) were nonsmokers. Nonsmokers had the highest EQ-VAS score (mean 84.49, SD 14.84), smokers had the lowest EQ-VAS score (mean 77.38, SD 21.99), and the EQ-VAS score for ex-smokers was in between (mean 81.04, SD 17.68). A significant difference in EQ-VAS scores was detected between nonsmokers and ex-smokers (P<.001), which indicated that pre-pregnancy smoking does have a negative impact on the HRQoL (EQ-VAS) of pregnant women. Compared with nonsmokers, ex-smokers suffered from more anxiety/depression problems (P=.001, odds ratio [OR] 1.29, 95% CI 1.12-1.50). Among ex-smokers, the increased cigarette consumption was associated with a lower EQ-5D index (P=.007) and EQ-VAS score (P=.01) of pregnant women. Compared to smokers, no significant difference was found in the ex-smokers' EQ-5D index and EQ-VAS score (P=.33). CONCLUSIONS: Smoking history is associated with a lower HRQoL in pregnant Chinese women. Pre-pregnancy smoking is related to a lower HRQoL (EQ-VAS) and a higher incidence of depression/anxiety problems. Smoking cessation during pregnancy does not significantly improve the HRQoL of pregnant Chinese women. Among ex-smokers, the more cigarettes they smoke, the lower HRQoL they have during pregnancy. We suggest that the Chinese government should strengthen the education on quitting smoking and avoiding second-hand smoke for women who have pregnancy plans and their family members.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".