Household Air Pollution and Arthritis in Low- and Middle-Income Countries: Evidence from the World Health Organization's Study on Global Ageing and Adult Health
Bibliographic record
Abstract
Evidence points to a clear link between air pollution exposure and several chronic diseases. However, investigations regarding arthritis are still lacking. Ambient air pollution and smoking have been associated with a higher risk of rheumatoid arthritis, though the evidence regarding osteoarthritis is inconsistent. Further, most of this evidence stems from high-income countries. Household air pollution exposure may be an important risk factor for arthritis in low- and middle-income countries (LMICs) but is largely unstudied. Women in these regions can be exposed to high levels of air pollution through cooking activities. Women, in general, are also at higher risk of arthritis, compared to men. We examined household air pollution (electricity vs. gas/kerosene/paraffin; coal/charcoal/wood; or agriculture/crop/animal dung/shrubs/grass used for cooking) as a risk factor for arthritis in 6 LMICs (China, Ghana, India, Mexico, the Russian Federation and South Africa) using data from Wave I of the multiwave panel World Health Organization Study on Global AGEing and Adult Health (SAGE) (2007-2010). The use of liquid (aOR=1.73, 95%CI: 1.33-2.25) or solid (coal/charcoal/wood: aOR=1.73, 95%CI: 1.32-2.27; agriculture/crop/animal dung/shrubs/grass: aOR=2.00 (1.47-2.72) for cooking was strongly associated with an increased odds of arthritis, compared to electricity, in pooled weighted analyses. Sex (female), age (≥50 years), obesity (BMI ≥30.00) and the comorbidities angina pectoris, diabetes, chronic lung disease, depression and hypertension were also associated with a higher odds of arthritis. Underweight (BMI<18.50) and higher education levels (college/university completed/post-graduate) were associated with a lower odds of arthritis. This study is among the first to examine household air pollution in LMICs as a risk factor for arthritis. These findings suggest that exposure to household air pollution might be associated with an increased odds of arthritis in these regions.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".