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Record W2046229589 · doi:10.1177/1715163514552560

Demystifying the Air Quality Health Index

2014· article· en· W2046229589 on OpenAlexafffundvenueabout
Sarah Gutenberg

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of Waterloo
FundersCollege of Family Physicians of Canada
KeywordsAir quality indexEnvironmental healthAir pollutionPollutantIndex (typography)Environmental scienceMedicineHealth careCriteria air contaminantsAir pollutantsMeteorologyGeographyEconomic growth

Abstract

fetched live from OpenAlex

Air quality can be measured by 2 methods—first, by estimating the amount of emission from pollutant sources and, more accurately, by estimating the amount of pollutants in the air. Air quality can fluctuate seasonally, by time of day, by location and by changing weather conditions.1-4 The Air Quality Health Index (AQHI) is a national, simplified communication tool to measure and forecast air quality.1 The AQHI allows for individuals to take action to protect their health and support active living. The index can help patients to predict their exposures based on location and activity. Pharmacists can use the Air Quality Health Index tool to counsel their high-risk patients with asthma, chronic obstructive pulmonary disease, cardiovascular disease or diabetes, as well as seniors and families with children on how they can reduce their exposure to air pollution.1,5,6 Reducing exposure can in turn lead to a decrease in health risk in terms of morbidity and mortality. Every year, Health Canada estimates that air pollution in 8 Canadian cities causes nearly 6000 premature deaths. Long-term exposure to air pollution accounts for more than 70% of these deaths.1 The Canadian Medical Association estimated the yearly national economic costs from the health impacts of air pollution to be approximately 8 billion dollars (including lost productivity, health care costs, loss of life, pain and suffering).1,7 The Air Quality Health Index measures 3 specific pollutants. The first component measured by the AQHI is ground-level ozone. Ground-level ozone is an odourless, colourless gas and a major component of smog during the summer. Ground-level ozone levels are highest in the summer and afternoons, as formation of ozone requires heat and light. The major sources of ground-level ozone are fuel combustion from vehicles and from industry. Second, the AQHI measures particulate matter (PM). These particles are too small to see and can deposit deep into the lung alveoli, leading to systemic inflammation and changes in heart rate and blood pressure and accelerating the progression of atherosclerosis. Third, the AQHI measures the amount of nitrogen dioxide (NO2) in the air. Nitrogen dioxide is a major air pollutant found in smog and acid rain. Nitrogen dioxide forms mainly from the combustion of vehicles, combustion in fossil fuel power plants and industrial processes.1,4 The effects of short-term exposure to pollution include exacerbation of preexisting respiratory disease, including asthma and chronic obstructive pulmonary disease. Worsening of cardiovascular diseases such as ischemia, including increased rates of myocardial infarction, increased incidence of cardiac arrhythmia, exacerbation of heart failure and stroke can also occur.8 The effects of long-term exposure to pollution include the increased incidence of lung cancer and pneumonia, as well as the increased development of atherosclerosis. Long-term exposure may also lead to the development of new asthma and may delay lung development in children.1 The Air Quality Health Index is a scale designed to help your patients understand what the quality of air means to their health. The index is a counselling tool to show patients how to limit their exposure to air pollution.1 Pharmacists can educate their patients on how to adjust their activities so as to reduce intense outdoor activity during episodes of increased air pollution and to encourage outdoor physical activity on days when the index is low (Figure 1).2 The higher the number on the index, the greater the health risk. Numbers 1 to 3 indicate a low health risk. At this low level, the population is able to enjoy their usual outdoor activities and should be encouraged to be physically active outdoors. Numbers 4 to 6 on the scale indicate a moderate health risk, when the at-risk population should consider reducing or rescheduling their outdoor activities. Numbers 7 to 10 indicate a high risk. At these levels, children and the elderly and those with preexisting respiratory or cardiac disease should reduce or reschedule their outdoor activities. Levels on the scale above 10 rarely occur and are usually associated with forest fires. At these levels, the general population should also consider reducing or rescheduling outdoor activities, especially if experiencing symptoms of coughing or throat irritation (Table 1).9 Figure 1 The Air Quality Index Scale2 Table 1 Air Quality Health Index (AQHI) categories and health messages9 The AQHI tool provides Canadians with information that is consistent across Canada.1 All Canadians are able to check the quality of air prior to engaging in activities outside. Although there is no direct experimental evidence to support the effectiveness of the AQHI, there is indirect evidence that supports the short-term health benefits. A recent epidemiologic study in Ontario has shown that each unit increase in daily AQHI value is associated with a substantial increase in emergency and outpatient department visits for asthma, which can occur up to 2 days later. In addition, the Air Quality Health Index also gives advice on how Canadians can reduce personal and household emissions.1 In conclusion, the Air Quality Health Index is a Canadian counselling tool that can be used to advise high-risk patients to reduce exposure and health risk from air pollution by reducing or rescheduling their strenuous outdoor activities. Pharmacists can easily teach vulnerable patients this self-management behaviour. For more information on where to find the Air Quality Health Index, pharmacists and patients can check the Weather Network (www.theweathernetwork.com) and www.airhealth.ca.3 ■

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0140.003

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.

Opus teacher head0.073
GPT teacher head0.334
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations9
Published2014
Admission routes4
Has abstractyes

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