A team of scientists from Durham, NC have been examining the amount of physiological ageing taking place in people aged around 45 years, who have a slower walking speed. Their results have been published in JAMA Network Open, a peer-reviewed open-access online journal. The scientists used data from a New Zealand study to test their hypothesis: slow walking by people who were middle-aged, reflected their biological and cognitive ageing.
The study used was the Dunedin Multidisciplinary Health and Development Study, which followed a birth cohort, born between 1972-1973, following them over five decades to age 45 years. Most of the cohort were around 3 years old when the first tests were conducted. The data was analysed between April and June 2019. 91% of the original cohort reached their 45th birthday and most of them had their walking speed measured. Throughout the time they were part of the cohort, they also had other measurements taken, including BMI (body mass index), waist to hip ratio, cardiorespiratory fitness, cholesterol levels, blood pressure, blood tests to measure certain levels, gum health and tooth decay. The participants differed in their rates of ageing from 0-3 years of physiological change per one year of time. Independent panels of researchers checked the facial ageing of the participants by evaluating standardised photographs when the participants were 45 years.
At the end of the study, the participants also took part in a scan to help detect age-related changes to the brain, and also a neurological function test. They had also been tested as children for intelligence, language, emotional and behavioural regulation and motor skills. The socio-economic status of their families were also taken into account.
The adult participants were subjected to tests to evaluate their walking speed - at their usual speed, dual task gait speed, where they were asked to complete a simple task while walking, and their maximum gait speed. Their physical functions were assessed, using surveys and tested through tasks to assess grip strength, hand-eye co-ordination and balance as well as other skills.
The scientists found that those participants who had a slower walking speed at age 45, also showed a smaller volume of brain, more white matter lesions, smaller cortical areas and more cortical thinning. These are all signs of biological ageing, that had increased to more than expected for their age. These participants tended to be assessed as older by the panel looking at the facial photographs and their cardiorespiratory health, teeth and gum health and immune systems also seemed to be that of older people than 45 years. The researchers also noted that their scores as children also tended to be worse and that these could be used to predict who would have a slower walking speed at age 45.
Previously, gait speed has been used as an indicator in older people. The scientists noted that it could be used for younger people. Slower walking speed was linked with poor physical function in midlife, associated with accelerated ageing in both organ systems and in the face. It was linked with reduction in brain size and volume and the amount of white matter, which is linked with dementia, was increased. Poorer neurocognitive function was also associated with slower walking, including a lower IQ score. The scores also reflected the participants’ scores as children.
The scientists suggested that more research is needed to find out how physical measurements such as gait speed affected brain health, and how to target interventions effectively to prevent people becoming prematurely old before their time. This study also helps to explain how gait speed can be used so effectively to predict Alzheimer’s disease. The scientists had not specifically measured gait speed during the whole of the study, so it was difficult to show changes in gait speed. However, they recommended that gait speed be considered as an important measure of health.
Rasmussen, L.J.H., et al., Association of Neurocognitive and Physical Function with Gait Speed in Midlife, JAMA Network Open, 2019;2(10):e1913123