Exploring the Relationship Between Alzheimer’s Disease and Age-Related Hearing Loss: A Literature Review
Bibliographic record
Abstract
Introduction: By 2050, the international prevalence of Alzheimer’s disease (AD) is expected to triple, resulting in immense healthcare costs and personal effect. In recent years, researchers have identified age-related hearing loss (ARHL) as one of the most prevalent causes in older adults to be associated with the predisposition for mild cognitive impairment (MCI) and AD. However, the relationship between the two remains unclear. Several plausible mechanisms explaining this hearing-cognition relationship have been suggested, such as social isolation, auditory activation, and neurobiological factors. This review seeks to investigate the literature examining the relationship between ARHL and dementia, how ARHL as a modifiable risk factor plays a role in the severity of cognitive decline in the AD and MCI population, and advocate for why further research on this topic is essential to help create a cognitively healthier and more informed older adult population. Methods: A comprehensive literature review of fifteen peer-reviewed articles was conducted using a predetermined protocol and inclusion criteria, such as keywords and databases. The search was limited to published articles in the English language from 2010 – present. Results: No associations were found between brain cortical thickness and those with AD and ARHL in comparison to those with SCD where an association was present. A moderate correlation was found between neurobiological factors such as ApoE4 to explain the relationship between AD and ARHL. The use of active hearing aids did not contribute to a cognitive benefit in those with moderate AD and ARHL compared to the use of placebo hearing aids, or after the secondary activation of hearing aids in the placebo group. Discussion: The literature shows inconclusive results about the mechanism linking ARHL and AD. The pattern of findings did not show consistent results between studies supporting a particular domain to explain the mechanism behind this relationship. Conclusion: Through conducting this review, a greater understanding and awareness about the role of ARHL as a risk factor of MCI and AD is provided. Ultimately, this is important in individual lifestyle changes to prevent the onset of ARHL, and subsequently dementia in order to live healthier and with higher quality as they age.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".