1
Covariates: Minimally adjusted model: age, height, sex, race, length of follow up (longitudinal only), baseline physical performance (longitudinal only) Fully adjusted model: adds weight, physical activity level, diabetes status METHODS SUMMARY & CONCLUSION INTRODUCTION It was hypothesized that, since the neurological and muscular systems are closely intertwined, neurological function would predict poorer mobility and accelerated decline. If this is true, neurological testing could be used to assess risk for impaired mobility and allow for earlier intervention and delayed decline. The objective was to identify which, if any, aspects of neurological function indicate the presence of or predict future impaired mobility in older adults. This study used data from the Baltimore Longitudinal Study of Aging (BLSA). Started in 1958, the BLSA is the longest running scientific research study on aging in the country. The research conducted is longitudinal and purely observational. The participants analyzed in this study were at least 60 years of age. Those from age 60 to 80 visit the BLSA biannually and those over age 80 visit annually. Finger tapping assessment and many basic neurological tests strongly predict mobility and therefore should be included in geriatric wellness exams. EMG testing is likely an unnecessary expense, unless assessing for pathology (i.e. peripheral neuropathy). Though some aspects of nerve conduction predict physical performance, they have relatively weak significance and do not predict decline. Subsequent research could analyze other neurological signs, such as irregularities in non-pathological reflexes, pronator drift, dysmetria, or disdiadochokinesia, to see if they predict physical performance or decline. Additionally, since this study analyzed a wide range of neurological and performance variables, the future scope should be narrowed in order to match particular areas of neurological dysfunction with specific aspects of poor mobility. Neurological Measures: Electromyography (EMG)- nerve conduction velocity and amplitude BLSA physical examination (conducted by nurses): o Finger tapping assessment o Tests for graphesthesia , cranial nerve abnormalities, Romberg sign, and pathological reflexes Performance Measures: Health ABC Physical Performance Battery: o Repeat chair stands o Standing balances- up to 30 s each for semi- and full- tandem and single leg stands o Narrow gait speed - fastest of 3 trials over 6 m in a 20 cm wide path o Usual gait speed - faster of 2 trials over 6 m Rapid gait speed- faster of 2 trials over 6 m Measures Population Statistics RESULTS Men N= 411* Women N= 407* Mean Age 74.9 72.6 Percent Black Race 17.5 29.7 Mean Measured BMI 27.7 27.3 Percent Sedentary (report ≤ 30 minutes of physical activity per week) 37.7 44.7 Percent with Pathological Nerve Conduction 51.4 31.7 Percent that Show 1+ Neurological Sign(s) 51.1 41.8 *N ≈ 450 for the EMG data, N ≈ 590 longitudinal analysis SAS Statistical Analysis Cross-sectional analyses: general linear models (discrete predictors) or linear regression (continuous predictors). Longitudinal analyses: logistic regression. Age associated changes to the neuromuscular system result in decreased muscular force, motor speed, coordination, and mobility. There exists strong evidence that decline in neurological and physical realms are closely tied. Decline in physical performance can cause inability to comfortably achieve everyday tasks and predict mortality. HABCPPB (points) R 2 = 0.417 p<0.001* Rapid Gait (m/s) R 2 = 0.410 p<0.001* Usual Gait (m/s) R 2 = 0.296 p<0.001* 0 5 10 15 20 25 30 35 40 45 Usual Gait Speed Rapid Gait Speed Physical Performance Battery Standing Balance Time Percent Declined Number of Dominant Hand Finger Taps in 10 Seconds Finger Tapping and Decline in Physical Performance 9-18 19-28 29-38 OR= 0.852 p< 0.001* OR= 0.931 p= 0.041* OR= 0.929 p= 0.029* OR= 0.924 p= 0.021* 0 5 10 15 20 25 30 35 40 45 Usual Gait Speed Rapid Gait Speed Physical Performance Battery Standing Balance Time Percent Declined Pathological Reflexes Pathological Reflexes and Decline in Physical Performance Present Absent OR= 0.411 p< 0.001* OR= 0.664 p= 0.082 OR= 0.645 p= 0.059 OR= 0.737 p= 0.207 Cross-Sectional Longitudinal *β values are from minimally adjusted model **∆µ= difference in physical performance mean between neurological groups Performance Outcome Not Significant Minimally adjusted model, only Minimally and fully adjusted models Independent predictor Neurological Predictor HABC PPB (points) Chair Stands (#/s) Balance Time (s) Narrow Gait (m/s) Usual Gait (m/s) Rapid Gait (m/s) Sensory NCV (m/s) *β= 0.013 β= 0.002 β= 0.474 β= 0.009 β= 0.004 β= 0.004 Motor NCV (m/s) β= 0.014 β= 0.002 β= 0.568 β= 0.007 β= 0.005 β= 0.011 Sensory NCA (mV) β= 0.012 β= 0.003 β= 0.252 β= 0.009 β= 0.005 β= 0.006 Motor NCA (mV) β= 0.057 β= 0.012 β= 1.374 β= 0.042 β= 0.021 β= 0.030 Finger Taps (#/10 s) β= 0.034 β= 0.009 β= 0.627 β= 0.022 β= 0.012 β= 0.025 Graphesthesia (Able/Unable) **∆µ= 0.218 ∆µ= 0.042 ∆µ= 8.046 ∆µ= 0.125 ∆µ= 0.051 ∆µ= 0.105 Cranial Nerves (Norm/Abnorm) ∆µ= 0.178 ∆µ= 0.014 ∆µ= 7.647 ∆µ= 0.140 ∆µ= 0.042 ∆µ= 0.056 Romberg Sign (Neg/Pos) ∆µ= 0.424 ∆µ= 0.088 ∆µ= 15.865 ∆µ= 0.225 ∆µ= 0.077 ∆µ= 0.170 Path Reflexes (Abs/Pres) ∆µ= 0.130 ∆µ= 0.028 ∆µ= 4.763 ∆µ= 0.068 ∆µ= 0.039 ∆µ= 0.059 Hypothesis Note: Other neurological predictors did not have enough power to be analyzed or were not significant predictors of decline in physical performance when using the fully adjusted model. REFERENCES 1. Barry, BK, et al. The consequences of resistance training for movement control in older adults. J Gerontol, 2009. 2. Bodwell, JA, et al. Age and features of movement influence motor overflow. J Am Geriatr Soc, 2003. 3. Deshpande, et al. Association of lower limb cutaneous sensitivity with gait speed in the elderly: The Health ABC Study. Am J Phys Med Rehabil, 2008. 4. Deshpande, N, et al. Physiological correlates of age-related decline in vibrotactile sensitivity. Neurobiol Aging, 2008. 5. Deshpande, N, et al. Sensorimotor and psychosocial correlates of adaptive locomotor performance in older adults. Arch Phys Med Rehabil, 2008. 6. Deshpande, N, et al. Validity of clinically derived Cumulative Somatosensory Impairment Index. Arch Phys Med Rehabil, 2010. 7. Ferrucci, L, et al. Neurological examination findings to predict limitations in mobility and falls in older persons without a history of neurological disease. Am J Med, 2004. 8. Hirsch, CH, et al. Predicting late-life disability and death by the rate of decline in physical measures. Age Ageing, 2012 9. Hong, SL, et al. A new perspective on behavioral inconsistency and neural noise in aging: compensatory speeding of neural communication. Front Aging Neurosci, 2012. 10.Hortobágyi, T, et al. Mechanisms responsible for the age-associated increase in coactivation of antagonist muscles. Exerc Sport Sci Rev, 2006. 11.Isojärvi, H, et al. Exercise and fitness are related to peripheral nervous system function in overweight adults. Med Sci Sport Exercise, 2010. 12.Leishear, K, et al. Vitamin B12 and homocysteine levels and 6-year change in peripheral nerve function and neurological signs. J Gerontol Mel Sci, 2012. 13.Missitzi, J, et al. Genetic variation of maximal velocity and EMG activity. Int J Sports Med, 2008. 14.Sachchietti, MS, et al. Neuromuscular dysfunction in diabetes: role of nerve impairment and training status. Med Sci Sports Exerc, 2012. 15.Sayers, SP. High-speed power training: a novel approach to resistance training in older men and women: a brief review and pilot study. J Strength Cond Res, 2007. 16.Schrack, JA, et al. The role of energetic cost in the age-related slowing of gait speed. J Am Geriatr Soc, 2012. 17.Simonsick, EM, et al. Measuring higher level physical function in well- functioning older adults: expanding familiar approaches in the Health ABC Study. J Gerontol, 2001. 18.Strotmeyer, ES, et al. Sensory and motor peripheral nerve function and lower-extremity quadriceps strength: The Health, Aging, and Body Composition Study. J Am Geriatr Soc, 2009. 19. Strotmeyer, ES, et al. The relationship of reduced peripheral nerve function and diabetes with physical performance in older white and black adults: The Health, Aging, and Body Composition Study. Diabetes Care, 2008. 20. Wakeling, JM. Motor unit recruitment during vertebrate locomotion. Anim Biol, 2005. 21. Wilkins, CH, et al. Mild physical impairment predicts future diagnosis of dementia of the Alzheimers type. J Am Geriatr Soc, 2013. Meaningful Decline (Longitudinal analyses): Usual gait speed decline ≥ 0.08 m/s/yr Rapid gait speed decline ≥ 0.10 m/s/yr HABCPPB score decline ≥ 0.14 points/yr Standing balance time decline ≥ 6.00 s/yr

STAR Poster 2013FINAL

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Covariates:

• Minimally adjusted model: age, height, sex, race, length of follow up (longitudinal only), baseline physical performance (longitudinal only) • Fully adjusted model: adds weight, physical activity level, diabetes status

METHODS

SUMMARY & CONCLUSION

INTRODUCTION

• It was hypothesized that, since the neurological and muscular systems are closely intertwined, neurological function would predict poorer mobility and accelerated decline. • If this is true, neurological testing could be used to assess risk for impaired mobility and allow for earlier intervention and delayed decline. • The objective was to identify which, if any, aspects of neurological function indicate the presence of or predict future impaired mobility in older adults.

• This study used data from the Baltimore Longitudinal Study of Aging (BLSA). • Started in 1958, the BLSA is the longest running scientific research study on aging in the country. • The research conducted is longitudinal and purely observational. • The participants analyzed in this study were at least 60 years of age. Those from age 60 to 80 visit the BLSA biannually and those over age 80 visit annually.

• Finger tapping assessment and many basic neurological tests strongly predict mobility and therefore should be included in geriatric wellness exams. • EMG testing is likely an unnecessary expense, unless assessing for pathology (i.e. peripheral neuropathy). Though some aspects of nerve conduction predict physical performance, they have relatively weak significance and do not predict decline. • Subsequent research could analyze other neurological signs, such as irregularities in non-pathological reflexes, pronator drift, dysmetria, or disdiadochokinesia, to see if they predict physical performance or decline. • Additionally, since this study analyzed a wide range of neurological and performance variables, the future scope should be narrowed in order to match particular areas of neurological dysfunction with specific aspects of poor mobility.

Neurological Measures: • Electromyography (EMG)- nerve conduction velocity and amplitude • BLSA physical examination (conducted by nurses):

o Finger tapping assessment

o Tests for graphesthesia , cranial nerve abnormalities, Romberg sign, and pathological reflexes

Performance Measures: • Health ABC Physical Performance Battery:

o Repeat chair stands o Standing balances- up to 30 s each for semi- and full- tandem and single leg stands o Narrow gait speed - fastest of 3 trials over 6 m in a 20 cm wide path o Usual gait speed - faster of 2 trials over 6 m

• Rapid gait speed- faster of 2 trials over 6 m

Measures

Population Statistics

RESULTS

Men N= 411*

Women N= 407*

Mean Age 74.9 72.6

Percent Black Race 17.5 29.7

Mean Measured BMI 27.7 27.3

Percent Sedentary (report ≤ 30 minutes of physical activity per week)

37.7 44.7

Percent with Pathological Nerve Conduction

51.4 31.7

Percent that Show 1+ Neurological Sign(s)

51.1 41.8

*N ≈ 450 for the EMG data, N ≈ 590 longitudinal analysis

SAS Statistical Analysis • Cross-sectional analyses: general linear models (discrete predictors) or linear regression (continuous predictors). • Longitudinal analyses: logistic regression.

• Age associated changes to the neuromuscular system result in decreased muscular force, motor speed, coordination, and mobility. • There exists strong evidence that decline in neurological and physical realms are closely tied. • Decline in physical performance can cause inability to comfortably achieve everyday tasks and predict mortality.

HABCPPB (points)

R2= 0.417 p<0.001*

Rapid Gait (m/s)

R2= 0.410 p<0.001*

Usual Gait (m/s)

R2= 0.296 p<0.001*

0

5

10

15

20

25

30

35

40

45

Usual Gait Speed

Rapid Gait Speed

Physical Performance

Battery

Standing Balance Time

Pe

rce

nt

De

clin

ed

Number of Dominant Hand Finger Taps in 10 Seconds

Finger Tapping and Decline in Physical Performance

9-18

19-28

29-38

OR= 0.852 p< 0.001*

OR= 0.931 p= 0.041*

OR= 0.929 p= 0.029*

OR= 0.924 p= 0.021*

0

5

10

15

20

25

30

35

40

45

Usual Gait Speed

Rapid Gait Speed

Physical Performance

Battery

Standing Balance Time

Pe

rce

nt

De

clin

ed

Pathological Reflexes

Pathological Reflexes and Decline in Physical Performance

Present

Absent

OR= 0.411 p< 0.001*

OR= 0.664 p= 0.082

OR= 0.645 p= 0.059

OR= 0.737 p= 0.207

Cross-Sectional Longitudinal *β values are from minimally adjusted

model **∆µ= difference in

physical performance mean

between neurological groups

Performance Outcome

Not Significant

Minimally adjusted model, only

Minimally and fully adjusted models

Independent predictor

Neurological Predictor

HABC PPB

(points)

Chair Stands (#/s)

Balance Time

(s)

Narrow Gait

(m/s)

Usual Gait

(m/s)

Rapid Gait

(m/s)

Sensory NCV (m/s)

*β= 0.013

β= 0.002

β= 0.474

β= 0.009

β= 0.004

β= 0.004

Motor NCV (m/s)

β= 0.014

β= 0.002

β= 0.568

β= 0.007

β= 0.005

β= 0.011

Sensory NCA (mV)

β= 0.012

β= 0.003

β= 0.252

β= 0.009

β= 0.005

β= 0.006

Motor NCA (mV)

β= 0.057

β= 0.012

β= 1.374

β= 0.042

β= 0.021

β= 0.030

Finger Taps (#/10 s)

β= 0.034

β= 0.009

β= 0.627

β= 0.022

β= 0.012

β= 0.025

Graphesthesia (Able/Unable)

**∆µ= 0.218

∆µ= 0.042

∆µ= 8.046

∆µ= 0.125

∆µ= 0.051

∆µ= 0.105

Cranial Nerves (Norm/Abnorm)

∆µ= 0.178

∆µ= 0.014

∆µ= 7.647

∆µ= 0.140

∆µ= 0.042

∆µ= 0.056

Romberg Sign (Neg/Pos)

∆µ= 0.424

∆µ= 0.088

∆µ= 15.865

∆µ= 0.225

∆µ= 0.077

∆µ= 0.170

Path Reflexes (Abs/Pres)

∆µ= 0.130

∆µ= 0.028

∆µ= 4.763

∆µ= 0.068

∆µ= 0.039

∆µ= 0.059

Hypothesis

Note: Other neurological predictors did not have enough power to be analyzed or were not significant predictors of

decline in physical performance when using the fully adjusted model.

REFERENCES 1. Barry, BK, et al. The consequences of resistance training for

movement control in older adults. J Gerontol, 2009. 2. Bodwell, JA, et al. Age and features of movement influence motor

overflow. J Am Geriatr Soc, 2003. 3. Deshpande, et al. Association of lower limb cutaneous sensitivity

with gait speed in the elderly: The Health ABC Study. Am J Phys Med Rehabil, 2008.

4. Deshpande, N, et al. Physiological correlates of age-related decline in vibrotactile sensitivity. Neurobiol Aging, 2008.

5. Deshpande, N, et al. Sensorimotor and psychosocial correlates of adaptive locomotor performance in older adults. Arch Phys Med Rehabil, 2008.

6. Deshpande, N, et al. Validity of clinically derived Cumulative Somatosensory Impairment Index. Arch Phys Med Rehabil, 2010.

7. Ferrucci, L, et al. Neurological examination findings to predict limitations in mobility and falls in older persons without a history of neurological disease. Am J Med, 2004.

8. Hirsch, CH, et al. Predicting late-life disability and death by the rate of decline in physical measures. Age Ageing, 2012

9. Hong, SL, et al. A new perspective on behavioral inconsistency and neural noise in aging: compensatory speeding of neural communication. Front Aging Neurosci, 2012.

10.Hortobágyi, T, et al. Mechanisms responsible for the age-associated increase in coactivation of antagonist muscles. Exerc Sport Sci Rev, 2006.

11.Isojärvi, H, et al. Exercise and fitness are related to peripheral nervous system function in overweight adults. Med Sci Sport Exercise, 2010.

12.Leishear, K, et al. Vitamin B12 and homocysteine levels and 6-year change in peripheral nerve function and neurological signs. J Gerontol Mel Sci, 2012.

13.Missitzi, J, et al. Genetic variation of maximal velocity and EMG activity. Int J Sports Med, 2008.

14.Sachchietti, MS, et al. Neuromuscular dysfunction in diabetes: role of nerve impairment and training status. Med Sci Sports Exerc, 2012.

15.Sayers, SP. High-speed power training: a novel approach to resistance training in older men and women: a brief review and pilot study. J Strength Cond Res, 2007.

16.Schrack, JA, et al. The role of energetic cost in the age-related slowing of gait speed. J Am Geriatr Soc, 2012.

17.Simonsick, EM, et al. Measuring higher level physical function in well-functioning older adults: expanding familiar approaches in the Health ABC Study. J Gerontol, 2001.

18.Strotmeyer, ES, et al. Sensory and motor peripheral nerve function and lower-extremity quadriceps strength: The Health, Aging, and Body Composition Study. J Am Geriatr Soc, 2009.

19. Strotmeyer, ES, et al. The relationship of reduced peripheral nerve function and diabetes with physical performance in older white and black adults: The Health, Aging, and Body Composition Study. Diabetes Care, 2008.

20. Wakeling, JM. Motor unit recruitment during vertebrate locomotion. Anim Biol, 2005. 21. Wilkins, CH, et al. Mild physical impairment predicts future diagnosis

of dementia of the Alzheimer’s type. J Am Geriatr Soc, 2013.

Meaningful Decline (Longitudinal analyses):

• Usual gait speed decline ≥ 0.08 m/s/yr • Rapid gait speed decline ≥ 0.10 m/s/yr • HABCPPB score decline ≥ 0.14 points/yr • Standing balance time decline ≥ 6.00 s/yr