Factors influencing olfactory function in an adult general population sample: the CHRIS study
Bibliographic record
Abstract
The sense of smell allows for the assessment of the chemical composition of volatiles in our environment. Different factors are associated with reduced olfactory function, including age, sex, as well as health and lifestyle conditions. However, most studies that aimed at identifying the variables that drive olfactory function in the population suffered from methodological weaknesses in study designs and participant selection, such as the inclusion of convenience sample or only of certain age groups, or recruitment biases. We aimed to overcome these issues by investigating the Cooperative Health Research in South Tyrol (CHRIS) cohort, a population-based cohort, by using a validated odor identification test. Specifically, we hypothesized that a series of medical, demographic and lifestyle variables is associated with odor identification abilities. In addition, our goal was to provide clinicians and researchers with normative values for the Sniffin' Sticks identification set, after exclusion of individuals with impaired nasal patency. We included 6,944 participants without acute nasal obstruction and assessed several biological, social, and medical parameters. A basic model determined that age, sex, years of education, and smoking status together explained roughly 13% of the total variance in the data. We further observed that variables related to medical (positive screening for cognitive impairment and for Parkinson's disease, history of skull fracture, stage 2 hypertension) and lifestyle (alcohol abstinence) conditions had a negative effect on odor identification scores. Finally, we provide clinicians with normative values for both versions of the Sniffin' Sticks odor identification test, i.e. with 16 items and with 12 items.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".