An updated systematic review and meta-analysis on portable air cleaners and blood pressure: Recommendations for users and manufacturers
Bibliographic record
Abstract
Fine particulate matter (PM2.5) air pollution is a leading contributor to the global burden of cardiovascular disease (CVD). One important underlying mechanism is an increase in blood pressure (BP). A growing number of studies have reported a beneficial effect of portable air cleaners (PACs) on systolic and diastolic BP; SBP and DBP. We conducted an updated systematic review and meta-analysis of studies using true versus sham mode filtration reporting the effects on BP. Of 214 articles identified up to February 5, 2023, seventeen (from China, USA, Canada, South Korea and Denmark) enrolling approximately 880 participants (484 female) met the inclusion criteria for meta-analyses. Aside from studies conducted in China, research on PACs and BP has been conducted in relatively low pollution settings. Mean indoor PM2.5 concentrations during the active and sham mode purification were 15.9 and 41.2 µg/m3, respectively. The mean efficiency of PACs against indoor PM2.5 was 59.8 % (ranging from 23 % to 82 %). True mode filtration was associated with a pooled mean difference of − 2.35 mmHg (95 % confidence interval [CI]: − 4.5, − 0.2) and − 0.81 mmHg (95 % CI: − 1.86, 0.24) in SBP and DBP, respectively. After removing the studies with high risk of bias, the magnitude of the pooled benefits on SBP and DBP increased to − 3.62 mmHg (95 % CI: − 6.69, − 0.56) and − 1.35 mmHg (95 % CI: − 2.29, − 0.41), respectively. However, there are several barriers to the use of PACs, specifically in low- and middle-income countries (LMICs), such as the initial purchase cost and filter replacements. There may be several avenues to help overcome these economic burdens and improve cost effectiveness, such as implementing government or other subsidized programs to distribute PACs targeting vulnerable and higher-risk individuals. We propose that environmental health researchers and healthcare providers should be better trained to educate the public regarding the use of PACs to reduce the impacts of PM2.5 on cardiometabolic diseases globally.
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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 | 0.028 | 0.108 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.027 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".