# Motor–Speech Performance in Very Old Speakers: Associations With Physio‐Anatomical and Cognitive‐Linguistic Factors

## TL;DR

This study examines how speech and motor skills change in very old speakers and what factors influence these changes.

## Contribution

Provides the first normative data on motor–speech performance in 80–100-year-old speakers and identifies key predictors.

## Key findings

- Older age within the 80–100 range is linked to slower sequential motion rate (SMR) task performance.
- Dentures and higher education are associated with slower articulation and AMR task performance.
- Good language skills correlate with faster motor–speech performance in very old speakers.

## Abstract

Motor–speech skills slow down with age, but health care professionals lack normative data, especially on the vastly growing population of very old (VO) speakers. The execution of different motor–speech tasks requires both fine‐motoric and cognitive abilities.

To study the performance on oral diadochokinetic (DDK) rate and narrative speech tempo in typically ageing 80–100‐year‐old speakers and to investigate whether they are predicted by age, dentition, hearing, cognitive status, language skills or educational level.

This cross‐sectional study comprises 50 typically ageing VO Finnish speakers. Their motor–speech performance was evaluated by alternating motion rate (AMR) syllables /pa/, /ta/ and /ka/ and sequential motion rate (SMR) syllable sequence /pataka/ and two speech tempo parameters (speaking and articulation rate) in semi‐spontaneous narrative. The association between task performance and background variables was studied by multiple linear regression analysis.

The VO speakers’ normative performance in DDK, speaking and articulation rates was predicted by physio‐anatomical and cognitive‐linguistic factors. Older age within the 80–100‐year range was associated only with slower execution of the SMR task. Wearing dentures predicted slower tempo in the AMR tasks and articulation rate. The highest educational level predicted slower tempo in the AMR tasks. Good language skills were positively associated with motor‐speech performance: Better phonemic fluency predicted faster AMR /pa/ and SMR /pataka/, and a higher Western Aphasia Battery Aphasia Quotient predicted a faster speaking rate.

The VO speakers had relatively well‐preserved motor–speech skills. Consistent with previous studies, the mean DDK, speaking and articulation rates were, nevertheless, slower in the VO speakers than in younger speakers in prior research. As a novel finding, SMR was slower than AMR in the VO speakers, which deviates from the trend observed in Finnish adults and younger elderly. This study suggests that natural teeth, younger age and good language skills safeguard the motor–speech skills from slowing down. However, it seems characteristic for the most highly educated VO speakers to perform slower than peers in the AMR tasks.

The results of this study will help to identify the manifestations of typical ageing. They also give insight into the life‐long evolution of speech skills and into the relationship between the motoric and linguistic facets of speech.

What is already known on the subject
Motor–speech performance slows down with ageing because of physio‐anatomical and cognitive‐linguistic changes. Speech tempo is, thus, a sensitive biomarker for neurological alterations.
What this study adds to existing knowledge
Formerly missing data on very old (VO) speakers’ typical motor–speech skills and their predictors. Within‐group differences are promoted by age, dentition, language skills and educational level.
What are the clinical implications of this work?
DDK, speaking and articulation rates are suitable means for clinical motor–speech assessment even in the oldest speakers. In addition to chronological age, speech–language pathologists should consider a range of individual physio‐anatomical and cognitive‐linguistic factors that contribute to speech performance. We recommend conducting AMR tasks /pa/, /ta/ and /ka/ together with an SMR /pataka/ task and comparing the results with culturally valid age‐specific norms (if available), as their atypical relationship may indicate neuropathology.

Motor–speech performance slows down with ageing because of physio‐anatomical and cognitive‐linguistic changes. Speech tempo is, thus, a sensitive biomarker for neurological alterations.

Formerly missing data on very old (VO) speakers’ typical motor–speech skills and their predictors. Within‐group differences are promoted by age, dentition, language skills and educational level.

DDK, speaking and articulation rates are suitable means for clinical motor–speech assessment even in the oldest speakers. In addition to chronological age, speech–language pathologists should consider a range of individual physio‐anatomical and cognitive‐linguistic factors that contribute to speech performance. We recommend conducting AMR tasks /pa/, /ta/ and /ka/ together with an SMR /pataka/ task and comparing the results with culturally valid age‐specific norms (if available), as their atypical relationship may indicate neuropathology.