Male and Female Adult Population Health Status in China: A Cross-Sectional National Survey
Bibliographic record
Abstract
BACKGROUND: With rapid economic growth and globalization, lifestyle in China has been changing dramatically. This study aimed to describe the male and female adult Chinese population health status. METHODS: The Chinese Third National Health Services Survey was conducted in 2003 to collect information about health status and quality of life from randomly selected residents. Of the 193,689 respondents to the survey (response rate 77.8%), 139,831 (69,748 male and 70,083 female) respondents who were 18 years of age or older were analyzed. RESULTS: Among the respondents, fewer males than females rated their overall wellbeing as being poor or very poor (4.8% versus 6.2%), reported illness in the last 2 weeks (14.1% versus 17.4%), presence of physician diagnosed chronic disease (15.0% versus 17.7%) and at least one functional problem in seven items of the quality of life (26.9% versus 32.8%). More males than females were currently smoking (52.4% versus 3.4%) and drank alcohol more than three times per week (16.5% versus 1.1%). Physically inactive rate was similar between males and females (85.8% versus 87.0%). Fewer rural respondents reported chronic disease than urban respondents (13.0% versus 19.9% for males and 15.5% versus 22.8% for females). In all seven items of the quality of life measured, rural respondents reported less problems than urban respondents (26.2% versus 28.7% for males and 32.0% versus 34.7% for females). CONCLUSION: Males had better health status than females in terms of self-perceived wellbeing, presence of illness, chronic disease, and quality of life. However, smoking and frequent alcohol drinking was more prevalent among males than that among females. In contrast with the social-economic gradient in health commonly found in the literature, the wealthier urban population in China was not found to be healthier than the rural population in terms of physician diagnosed chronic disease.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".