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NYU Alzheimer’s Disease Center
Silberstein Alzheimer’s Institute
Center for Cognitive Neurology

Body Fat and Muscle: Relationship to Cognitive and Physical Decline
James E. Galvin, MD, MPH
NYU Alzheimer’s Disease Center
Supported by grants from the National Institute on Aging, Morris and Alma Schapiro Fund and Michael J Fox Foundation

• Galvin Lab
– Magdalena Tolea, PhD
– Chaim Tarshish, PhD
– Arline Faustin, MD
– Stephanie Chrisphonte, MD
– Yael Zweig, MSN, ANP, GNP
– Licet Valois, LMSW, MPS
– Crystal Quinn, LMSW
– Katty Saravia, CCMA
• New York University
– Stella Karantzoulis, PhD
– Victoria Raveis, PhD
– Marie Boltz, PhD
– Ab Brody, PhD
– Els Fieremans, PhD
– Tim Shepard, MD, PhD
– Jean Bear-Lehman, PhD
• Washington University
– John Morris, MD
– Linda Larson-Prior, PhD
• University of Kansas
– David Johnson, PhD

Physical Function
• Physical Functionality: physical ability to independently carry out activities of daily living
• Frailty: geriatric syndrome with high risk of declines in health and function
– 5 dimensions: weight loss, exhaustion, weakness, slowness, and low activity
• Muscle weakness: inability to exert force with one's skeletal muscles
• Sarcopenia: degenerative loss of muscle mass, quality, and strength
• Functional dependence: disability in one or more of seven basic activities of daily living (toileting, eating, dressing, etc.)
Cognitive Function
• Healthy brain aging: little to no loss of memory or thinking abilities but tend to do things slower
• Mild Cognitive Impairment: transitional stage between healthy brain aging and dementia
• Dementia: progressive decline in memory and thinking that interferes with everyday function
• Alzheimer’s disease: most common cause of dementia

• Data support a relationship between physical function and cognition function
– Difficult to determine the causal relationship
– What comes first?
• Cognitive evaluation may be difficult for many primary care physicians, who will be the first contact for many patients but physical assessments are already part of what they do
• If physical impairment can be detected before noticeable cognitive impairment, performance-based assessments may help identify people at-risk for dementia

Cognitive Physical Impairment
Earlier Onset Faster Progression low high low high
Rajan KB et al., JGMS 67:1419-1426, 2012

Mild Physical Impairment Predicts
Future AD
HR: 1.06; 95% CI:1.01-1.12
Controlled for age, ApoE
Wilkins CH, et al JAGS 2013

Multicultural Community Dementia Screening
• Supported by grant from the National Institute on Aging
• Community-based assessment of older adults (target goal 500)
• Demographics, financial resources, preferences
• Cognitive-Behavioral Screening (memory, mood)
• Medical Screening (blood pressure, diabetes, lung disease, obesity)
• Physical assessment (balance, frailty, strength)
• Anthropometric measurements
• Social work follow-up
• Subset have Gold Standard testing and biomarkers collected
• MRI scans
• PET scans
• EEG
• Blood
• Spinal fluid
• Rich dataset with over 500,000 individual data points

Bone
Water
Lean Muscle
Fat
Body Visceral

Body Composition - Impedance
Dynamometer – Grip Strength
Tape Measure – Girth

• Changes in the Mini PPT scores correlate with disability, loss of independence, the risk of falls, and mortality.
• Cutoff scores of less than 12 imply impaired physical functioning
• Sensitivity: 86%
• Specificity: 90%
• Assessment takes ~7 minutes
• Range of Scores
• >12
• 8-11
Unimpaired
Mild
• 5-7
• 0-4
Moderate
Severe

– 30 point, 10 minute cognitive screen to detect
MCI and AD 1
• Memory, constructions, attention, executive function, language and orientation 1
• Score less than 26 suggests impairment 2
– Utility in an office setting established 1,3
– Also sensitive to PDrelated dementia 2
– Sensitivity ~90%,
Specificity ~87% 1
– http://www.mocatest.org
1. Nasreddine ZS et al, J Am Geriatr Soc . 2005;53:695-699. 2.
Zadikoff et al, Mov Disord. 2008;23:297-299. 3. Smith et al, Can J
Psych . 2007;52:329-332.

• Detect change in individuals compared to previous level of function
– No need for baseline assessment
– Patients serve as their own control
– Little bias by education, race, gender
• Brief (< 2 min), Yes/No format
– 2 or more “Yes” answers highly correlated with presence of dementia
• AUC: 0.917 (95% CI: 0.88-0.95)
• Sensitivity: 92%
• Positive PV: 93%
All participants Mean AD8 score (+ SD)
CDR
0
N
149
Informant
0.64 (1.19)
Patient
1.01 (1.52)
0.5
1
2
102
50
23
3.49 (2.32)
6.64 (1.74)
6.22 (2.66)
2.80 (2.19)
2.40 (2.51)
3.00 (2.66)
Only CDR 0 and 0.5 participants
Cohen’s d
ICC
1.66
0.98
.583 (95% CI: .47-68),p<.001

Biophysiological Markers of Health in a Multicultural Community
Variable
Health
Co-morbid conditions, #
Mean Blood Pressure
Resting Heart Rate
Lung Volume (FEV1), L
HbA1c
Strength
Mini-PPT
Grip strength
Body Composition
Body Mass Index (BMI)
Bone Mass, lb
Body Water, %
Muscle Mass, lb
Body Fat, %
Visceral Fat, lb
Abdominal Girth, cm
Hip Girth, cm
Basal Metabolic Rate, kcal
White
6.2 (3.2)
117.5 (18.8)
71.3 (15.1)
3.3 (1.4)
5.7 (0.7)
12.3 (2.6)
58.6 (24.0)
27.0 (4.5)
8.1 (13.9)
49.6 (5.7)
113.4 (27.0)
31.2 (8.2)
12.3 (4.4)
124.8 (15.8)
108.2 (9.3)
1.6 (0.4)
Black
6.0 (3.4)
117.5 (15.5)
71.3 (13.9)
2.3 (0.9)
6.4 (1.3)
9.6 (3.7)
46.6 (16.5)
30.0 (6.8)
5.0 (0.9)
43.5 (6.8)
95.9 (17.6)
39.5 (9.5)
12.8 (3.1)
98.7 (14.1)
112.7 (12.7)
1.4 (0.2)
Hispanic
5.0 (2.5)
114.7 (14.4)
71.4 (9.8)
2.5 (0.8)
6.1 (0.7)
11.8 (2.4)
46.2 (19.6)
28.2 (5.0)
4.8 (0.9)
45.5 (5.9)
90.6 (17.8)
36.1 (7.9)
13.8 (12.8)
97.7 (13.6)
106.5 (10.1)
1.3 (0.2)
P
0.058
0.530
0.893
<0.001
0.146
0.004
0.003
0.035
<0.001
<0.001
<0.001
0.004
0.307
<0.001
<0.001
<0.001
Galvin and Tolea In preparation 2014

Distribution Across Community Sample
% Body Fat
Visceral Fat

Distribution Across Community Sample
% Body Water
Lean Muscle Mass

• Categories
– No Sarcopenia: absence of both low muscle mass and grip strength
– Pre-sarcopenia: presence of low muscle mass only
– Sarcopenia: both low muscle mass and grip strength
Age
Education, yrs.
Female, %
White race, %
BMI
Muscle mass
Grip strength
Walking speed
MoCA
AD8
None
Cognitive impairment and physical impairment
Either Both P
62.9 (±9.7) 66.5 (±10.3) 74.3 (±7.6) <0.001
14.8 (±3.2) 14.2 (±3.9) 10.8 (±4.7) <0.001
62.7
60.3
55.9
39.0
81.8
25.9
0.005
0.006
27.6 (±6.2) 27.8 (±5.3) 29.2 (±5.3) 0.278
106.4 (±24.7) 105.8 (±22.9) 91.6 (±22.1) <0.001
64.3 (±26.7) 58.7 (±24.9) 42.3 (±13.6) <0.001
13.6 (±2.2) 14.8 (±3.9) 20.1 (±4.2) <0.001
27.8 (±1.3) 21.9 (±4.9) 19.4 (±4.2) <0.001
1.1 (±1.8) 1.8 (±1.9) 2.0 (±1.8) 0.012

70
60
50
40
30
20
10
0 p<0.001
% dual impairment
% single impairment
% no impairment
No sarcopenia Pre-sarcopenia Sarcopenia
Odd Ratio of having both cognitive impairment and physical impairment
Controls
Unadjusted
1.0
Adjusted 1
1.0
Adjusted 2
1.0
Pre-sarcopenia 0.94 (0.43-2.09) 1.29 (0.47-3.55) 1.89 (0.63-5.71)
Sarcopenia 5.92 (2.51-13.96) 4.21 (1.41-12.51) 3.40 (1.07-11.46)
Tolea and Galvin, In Preparation 2014

• Relationship between cognitive and physical functionality is well established at later stages of disability, however it is less clear whether association extends to the earliest stages of impairment
• Measurements included:
– upper extremity (UE) muscle strength (mean grip strength)
– lower extremity (LE) function (Mini Physical Performance Test),
– Cognition (Montreal Cognitive Assessment)
• Participants were categorized:
– no physical impairment
– UE functional impairment
– LE functional impairment
– both UE and LE impairment

Age
Education
Race, %
White, non-Hispanic
Black, non-Hispanic
Hispanic
BMI
Visceral fat, %
Muscle mass
No impairment UE impairment
LE extremity impairment
UE and LE impairment
P value
62.0 (±10.9) 66.5 (±8.7) 69.5 (±7.9) 75.1 (±8.2)7 <0.001
14.8 (±3.0) 13.8 (±4.6) 13.9 (±3.2) 11.2 (±5.0) <0.001
0.015
52.8
19.4
27.8
27.9 (±5.7)
40.9
15.2
43.9
27.5 (5.6)
20.0
50.0
30.0
29.6 (±5.6)
29.0
21.0
50.0
28.7 (±5.4) 0.546
12.7 (±4.5) 10.6 (±3.7) 14.6 (±3.7) 12.1 (±3.3) 0.002
121.7 (±21.0) 91.9 (±15.5) 115.3 (±24.5) 88.4 (±17.6) <0.001
*
*

MoCA r=.02
Mini-PPT r=.14

Body Fat Visceral Fat
MoCA r=.19
MoCA r=.03
Mini-PPT r=.13
Mini-PPT r=.36
Worse Physical Performance
Worse Cognitive Performance

Abdomen/Hip Ratio as Proxy Marker
MoCA r=.23
Worse
Outcomes
Mini-PPT r=.07

Falls Risk
Cognitive vs. Physical Status
Cognitive Status
Physical Status
Impaired
Normal Impaired Normal
Normal
Impaired
P value
Age, y 64.4 (9.3) 74.5 (8.9)
Education, y 13.89 (4.4) 11.9 (5.2)
Female, %
White, %
Latino, %
44.8
66.1
46.6
71.9
69.6
47.3
Co-morbidities 4.3 (2.5)
Body Mass Index 27.5 (5.4)
Body Fat 30.2 (9.5)
Visceral Fat 12.1 (4.4)
6.5 (3.0)
28.6 (5.6)
36.6 (8.2)
12.9 (4.1)
62.4 (9.3)
15.5 (3.3)
52.9
71.1
21.2
5.4 (2.8)
27.3 (5.6)
29.8 (9.7)
10.8 (4.1)
72.6 (7.2)
15.5 (3.4)
77.8
59.3
14.8
6.7 (3.1)
28.5 (5.1)
36.6 (9.0)
12.3 (2.7)
Bone mass 5.8 (1.2) 5.0 (1.1) 5.8 (1.43) 5.3 (1.2) 0.001
Muscle mass 111.6 (23.5) 96.0 (20.6) 111.0 (24.4) 100.7 (23.3) 0.001
Grip strength 63.9 (25.2) 43.4 (15.6) 66.2 (25.2) 52.8 (36.9) <0.001
Falls, events (%) 9 (15.5) 27 (51.9) 21 (25.0) 11 (40.7) <0.001
<0.001
<0.001
0.003
0.425
<0.001
<0.001
0.543
<0.001
0.026

• Demographic Variables
– Increasing age, female, living alone, self-reported memory problems, self-reported mood problems
• Clinical/Anthropometric Variables
– Body water, fat, visceral fat, bone density, muscle mass, pulse pressure
• Cognitive Variables
– List learning, visuoconstructive, trailmaking
• Performance Variables
– Grip strength, timed walk, flexion, progressive
Romberg

• Relationship between cognitive and physical function is complex and bidirectional
– Physical impairments are strong risk factors for future cognitive impairment
– Once present, cognitive decline is stronger driver for further physical decline
• Loss of muscle mass and strength (sarcopenia) may be one of the earliest detectable warning signs of impending cognitive decline
– 3 to 6-fold increased risk
– Strength testing (via dynamometer) is easy to do
– Grip strength earlier and stronger predictor than just testing mobility
• The association between cognitive and physical functionality follows a pattern from no impairment to loss of UE muscle strength to LE functional impairment
– May explain up to 27% of variability in performance on cognitive tests
• Falls are a significant consequence of both cognitive and physical decline
– 1 st fall increases risk of 2 nd fall and may further drive cognitive and physical decline
– Our initial work developed a profile of individuals at risk for falls

• Poorly controlled medical conditions greatly increase the risk of AD
– May be multiple pathways to get to Alzheimer’s disease
– May also be multiple pathways to prevent or treat
• Interventions designed to prevent sarcopenia, increase lean muscle mass and improve strength may help reduce the burden of cognitive and physical impairments in community-dwelling older adults
• Efforts to prevent cognitive decline and development of dementia may be more successful when directed to at at-risk individuals based on their physical functional profile
• Detection of and interventions addressing physical impairments may offer novel approaches to reducing cognitive decline and falls
• Prevention measures
Stay mentally alert, physically fit and eat a heart-healthy diet
• AD is a disease of a lifetime; many ways to build a better brain as we age

New York University Resources
• Pearl I. Barlow Center for Memory Evaluation and Treatment
– Specialty Faculty Practice
– Multidisciplinary Approach
– 212-263-3210
– www.nyulmc.org/barlow
• Alzheimer Disease Center
– Longitudinal Research Project
– 212-263-8088
– www.adc.med.nyu.edu
• Clinical Trials Center
– Study New and Exciting Treatments for Dementia
– 212-263-5708