Why COVID-19 strengthens the case to scale up assault on non-communicable diseases: role of health professionals including physical therapists in mitigating pandemic waves
Bibliographic record
Abstract
As SARS-CoV-2, the virus responsible for COVID-19, spread globally, the most severely affected sub-populations were the elderly and those with multi-morbidity largely related to non-communicable diseases (NCDs), e.g., heart disease, hypertension, type 2 diabetes, obesity. NCDs are largely preventable with healthy nutrition, regular activity, and not smoking. This perspective outlines the rationale for health professionals' including physical therapists' role in reducing COVID-19 susceptibility. Evidence is synthesized supporting the pro-inflammatory effects of the western diet, increasingly consumed globally, inactivity, and smoking; and the immune-boosting, anti-inflammatory effects of a whole food plant-based diet, regular physical activity, and not smoking. An increased background of chronic low-grade systemic inflammation associated with unhealthy lifestyle practices appears implicated in an individual's susceptibility to SARS-CoV-2. It is timely to re-double efforts across healthcare sectors to reduce the global prevalence of NCDs on two fronts: one, to reduce SARS-CoV-2 susceptibility; and two, to reduce the impact of subsequent waves given high blood pressure and blood sugar, common in people with multi-morbidity, can be improved within days/weeks with anti-inflammatory healthy lifestyle practices, and weight loss and atherosclerosis reduction/reversal, within months/years. With re-doubled efforts to control NCD risk factors, subsequent waves could be less severe. Health professionals including physical therapists have a primary role in actively leading this initiative.
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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 | 0.018 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.018 | 0.025 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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".