Associations Between Cardiovascular Risk Factors and Audiometric Hearing: Findings From the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
OBJECTIVES: The objectives of the study were to determine, among a population-based sample of Canadian adults, if risk factors for cardiovascular disease (alone and in combination) were associated with hearing loss. Cross-sectional and longitudinal associations (the latter with about 3 years of follow-up) were examined. Risk factors considered included diabetes, dyslipidemia, hypertension, obesity, and smoking. We also aimed to determine if associations were modified by sex and age group (45 to 54, 55 to 64, 65 to 74, and 75 to 86 years old at baseline). DESIGN: A secondary analysis of data collected for the Canadian Longitudinal Study on Aging was performed. Data were collected in two waves, the first between 2012 and 2015, and the second between 2015 and 2018. Hearing was measured using screening air-conduction pure-tone audiometry. The outcome of interest was defined as the mid-frequency (1000, 2000, 3000, and 4000 Hz) pure-tone average for both ears. Diabetes was defined based on self-reported physician diagnosis, use of diabetes medications, or a hemoglobin A1c level ≥6.5%. Dyslipidemia was determined by blood lipid profile as defined using the Canadian guidelines for the diagnosis and treatment of dyslipidemia (low-density lipoprotein cholesterol ≥3.5 mmol/L or non-high-density lipoprotein cholesterol ≥4.3 mmol/L). Hypertension was determined by self-reported physician diagnosis or an average systolic blood pressure ≥140 mm Hg or an average diastolic blood pressure ≥90 mm Hg. Obesity was defined as a waist-to-height ratio ≥0.6. Smoking history was determined by self-report (current/former/never-smoker). Two composite measures of cardiovascular risk were also constructed: a count of the number of risk factors and a general cardiovascular risk profile (Framingham) score. Independent associations between risk factors for cardiovascular disease and hearing were determined using multivariable regression models. Survey weights were incorporated into the analyses. All results were disaggregated by sex. Effect modification according to age was determined using multiplicative interaction terms between the age group and each of the risk factor variables. A complete case (listwise deletion) approach was performed for the primary analysis. We then repeated the multivariable regression analyses using multiple imputation using chained equations to determine if the different approaches to dealing with missing data qualitatively changed the outcomes. RESULTS: In longitudinal analyses, hypertension and the general cardiovascular risk profile score were associated with greater loss of hearing over the 3-year follow-up period for both sexes. In addition, smoking in males and obesity in females were associated with faster rates of hearing decline. In cross-sectional analyses, smoking, obesity, diabetes, and composite measures were each independently associated with worse hearing for both sexes (although for females, obesity was only associated with hearing loss in the 55 to 64-year-old age group). The results were similar for the complete case and multiple imputation approaches, but more cross-sectional associations were observed using multiple imputation. CONCLUSIONS: Diabetes, obesity, hypertension, and smoking were associated with hearing loss. Higher combinations of risk factors increased the risk of hearing loss. Further studies are needed to confirm age and sex differences and whether interventions to address these risk factors could slow the progression of hearing loss in older adults.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".