Slide 1

Title Slide: Alterations in Body Composition and Injury Patterns with
Aging

Presenters: Stewart Wang, MD, PhD; Jonathan Rupp, PhD

Slide 2

The projected increase in the population of people over age 65 through
2050. The red line shows the percent of the US population made up of
people age 65 and older increasing from about 12% now to 21% in 2050 and
the number of people over age 65 will increase from 35 to 87 million
over the same time period. The number of occupants over age 65 in
motor-vehicle crashes is likely to increase over this same time frame
and any trends in injuries that are associated with age are likely to
become exacerbated.

Slide 3

The NASS database from calendar years 1998-2004 was analyzed: we
considered all crash types, which were defined by the first letter in
the CDC code of the most severe event. Side impacts were further split
into nearside and far side based on the seat location of the occupant
relative to the struck side of the vehicle. Occupants over age 16 in all
seating locations were considered unless otherwise specified and only
crashes and injuries involving MY 1985 or newer vehicles were
considered.

Slide 4

Shows a bar graph showing the distribution of the ages of occupants
involved in crashes. A larger number of younger occupants are involved
in crashes than older occupants and crash involvement generally
decreases with age. The bar representing occupants over age 60 is higher
than the 50-59 age groups because the 60+ age group encompasses a larger
portion of the crash population, a larger number of age groups.

Slide 5

A bar graph showing the distribution of crash types for young (20-29),
middle aged (40-49), and elderly age groups (60+) in all seating
positions. In general, the distribution of crash types for the elderly
is similar to other age groups, except that the elderly are less likely
to be involved in rollovers and rear impacts and slightly more likely to
be involved in frontal and side impacts.

Slide 6

Shows a line graph showing the distribution of crash severity in frontal
crashes by age group. A larger percentage of the frontal crashes
involving elderly occupants occur at severities less than 10 mph. Above
10 mph, the average severity of frontal crashes involving elderly
occupants is similar to, or less than, that for other, younger age
groups.

Slide 7

A line graph zooming in on the higher crash severities and more clearly
showing that the percentage of elderly occupants involved in severe
frontal crashes is similar to or less than the percentage of younger
occupants involved in severe frontal crashes.

Slide 8

A line graph showing the distribution of crash severities by age group
for near side crashes. The distribution of crash severity for elderly
occupants is not different from the distribution of crash severity for
occupants in younger age groups.

Slide 9

A line graph showing that in the higher crash severities, the
percentages of elderly occupants involved in severe crashes is not
different from the percentages of the younger age groups involved in
severe crashes.

Slide 10

A line graph showing that the percentage of elderly occupants involved
in crashes of a given severity is not different from the percentage of
occupants in younger age groups involved in crashes of similar severity.

Slide 11

A line graph showing that elderly occupants are not involved in more
severe far side crashes than occupants in younger age groups.

Slide 12

A bar graph comparing belt use rates for young, middle aged, and elderly
occupants. Rates of belt use are higher for elderly occupants and rates
of improper belt use are lower for elderly occupants across all crash
types.

Slide 13

A bar graph showing that elderly occupants make up about 10% of the
occupant population and 18% of the severely injured population.

Slide 14

A line graph showing the relationship between AIS 3+ injury risk and age
for a belted driver in a 30 mph frontal crash by NASS body region. The
numbers in parenthesis to right of the curve labels in the legend are
odds ratios which describe the size of the age effect. An odds ratio of
1 would mean no age effect and increasing odd ratios represent larger
age effects. For frontal crashes, that largest age effects were
associated with thoracic injuries and lowest were associated with
abdominal injuries. The absolute increase in injury risk with age was
greatest for thoracic injuries, which increased from less than 2% at age
20 to almost 20% at age 80. In contrast, the absolute increase in injury
risk with age was least for abdominal injuries, which increased from
0.5% at age 20 to slightly less than 1% at age 80.

Slide 15

Shows a line graph showing the effect of age on the most common
abdominal and thoracic injuries in frontal crashes. Rib fracture had the
largest increase in risk with age and the second largest age effect. The
largest age effect was associated with aortic injuries, but since aortic
injuries are rare, the increase in risk with age for aortic injuries was
small. For frontal crashes, pulmonary contusions and hemo-pneumothoraces
also had large age effects and the age effect for abdominal organs was
small.

Slide 16

A line graph showing the over all age effects for near side impacts. The
largest increase in risk with age was for thoracic injuries. Thoracic
injuries only had the second largest age effect. The largest age effect,
as determined by odds ratios, was for spine. The large age effect
associated with spine is of lesser importance because the risk of spine
injuries relatively low across all age groups. Abdomen injuries in near
side impact had a moderate age effect, but the increase in risk of
abdominal injuries with age was relatively small.

Slide 17

Shows a line graph showing the effect of age on the most common
abdominal and thoracic injuries in near side impacts. The largest age
effect was associated with aortic injuries and the second largest age
effect was associated with rib fractures. The increase in risk with age
for rib fracture is significantly larger than the increase in the risk
of all other types of abdomen or thoracic injuries. In addition, the
risks of specific abdominal injuries did not meaningfully change with
age.

Slide 18

Trends in injury risk with age in far side crashes are similar to those
presented for near-side and frontal impacts

Slide 19

Rib fractures, hemo-pneumothoraces and pulmonary contusions are the most
common thoracic injuries. Rib fractures occur when the chest is
compressed, which places the ribs in bending. For thoracic soft tissue
injuries, rate of chest compression is also associated with the
incidence of injury. Studies in the biomechanical literature have
demonstrated that the amount of chest deflection required to cause rib
fractures decreases with age. These decreases have been associated with
changes in rib bone mineral density (BMD) and cross-sectional area.
Decreases in the force and deflection required to cause rib fracture may
also contribute to the incidence of soft tissue thoracic injuries by
allowing additional chest compression and increase rates of chest
loading. In addition, decreases in lung elasticity with age may also
contribute to the incidence of pulmonary contusions and
hemo-pneumothoraces.

Slide 20

The most commonly injury abdominal organs are the liver and spleen.
Liver and spleen injuries occur from direct compression of these organs
structures against other anatomic structures or from high rate
compression that causes over pressure within the organ resulting in a
capsular tear/rupture. The spleen and liver may also be injured by
abdominal deceleration, which would present as a tearing near the points
where the liver and spleen are tethered to other anatomic structures or
from displaced rib fractures. Consistent with the findings of the NASS
analysis, the incidence of liver, spleen and other abdominal injuries
has not been shown to increase with age in the biomechanical literature.

Slide 21

A line graph showing how much the percentage of rib fractures (red line)
increases as occupants age in severe frontal crashes with belted
drivers.

Slide 22

A line graph showing how much the percentage of rib fractures (red line)
increases as occupants age in severe near side crashes with belted
drivers.

Slide 23

A bar graph showing that the risks of thoracic injuries are much higher
for elderly occupants related to young and middle-age occupants in
frontal crashes. The risks for some abdominal injuries are also higher
for the elderly.

Slide 24

Shows a bar graph showing the annual numbers of thoracic and abdominal
injuries sustained by the 3 age groups in frontal crashes. Again, the
elderly suffer more from rib fractures that the other groups.

Slide 25

Shows a bar graph comparing the overall risk of thoracic and abdominal
injuries for the 3 age groups in near side impacts. Elderly occupants
again have a higher risk of most thoracic injuries.

Slide 26

Shows a bar graph showing the annual numbers of thoracic and abdominal
injuries for the 3 age groups in near side impacts. Elderly occupants
again have a higher risk of most thoracic injuries.

Slide 27

A bar graph showing the average crash severity for all age groups across
frontal and side impacts. The mean delta-v is lower for the elderly in
frontals. Side impacts show no clear pattern.

Slide 28

A bar graph showing that while risk is higher for the elderly in rear
and far side impacts, exposure is less. Most injuries occur in frontal
impacts.

Slide 29

Shows a text slide asking, "What is Age"?

Slide 30

Shows a text slide setting out the hypotheses of the test.

Slide 31

Scout CT scan (first image taken when a patient is put through a CT
scanner) of a CIREN patient.

Slide 32

Shows a line drawing of a rib cage explaining the process of expansion
and contraction of the rib cage during breathing

Slide 33

CT scan of a CIREN patient explaining how the angle of the ribs changes
during expansion and contraction of the rib cage during breathing.

Slide 34

Text slide citing literature showing how bone changes with aging.

Slide 35

Shows a picture of lumbar spine #4 vertebra in a very young person (on
left) and a very old person (on right).

Slide 36

Shows a picture of lumbar spine #4 vertebra (same as slide 35) with
added measure of Hounsfield units (bone density measurement) of 244 HU
in young person and 30 HU in older person.

Slide 37

Shows a text slide citing literature on the effects of soft tissues on
chest injury tolerance.

Slide 38

Shows a transverse cut of a thoracic CT scan showing lung volume.

Slide 39

Shows a transverse cut of a thoracic CT scan showing volume of the
tissue in the thorax minus the lung volume. The 2 volumes together equal
the total tissue volume of the thorax.

Slide 40

A transverse cut of a thoracic CT scan with the internal organs sculpted
out. This shows the muscle and bone volume of the thoracic cavity.

Slide 41

A transverse cut of a thoracic CT scan with the internal organs and
bones sculpted out. This measurement gives the chest wall soft tissue
volume.

Slide 42

A transverse cut of a thoracic CT scan with the internal organs, bones,
and muscle sculpted out. This measurement gives the fat volume.

Slide 43

deleted

Slide 44

deleted

Slide 45

Picture slide. First is a scout CT showing the outside of the patient's
body. Second is a coronal cut of a chest, abdomen, pelvis CT with a 2
inch slab of the patient's body marked out at the lumbar spine, vertebra
3. Third is the actual transverse cut of the 2-inch slab from the
patient.

Slide 46

Shows a slide showing the differences between 2 patients and their
subcutaneous fat volumes (in blue).

Slide 47

Shows a slide showing the differences between 2 patients and their
visceral fat volumes (in blue).

Slide 48

Shows a slide describing the differences between age and rib angle in
Michigan CIREN patients over age 18 (n=154), split by gender. The bottom
table shows that rib angles differ between males and females (p \<.008).

Slide 49

Shows a table describing chest width and depth in the same patients as
slide 48. Tables show that chest width and depth both differ by gender
(p\<.0001 for both measurements).

Slide 50

Shows a slide describing the differences between age and rib angle in
Michigan non-CIREN, non-trauma patients over age 18 (n=229). The 2
tables show correlations separated by gender.

Slide 51

Shows scatterplots showing correlation between age and rib angles. These
data show that rib angle differs by gender in non-CIREN, non-trauma
patients (p\<.0005, t-test).

Slide 52

Tables showing the differences between age and rib angle in Michigan
trauma patients over 18, with ISS\<8 (n=34).

Slide 53

Shows a scatter plot describing the male Michigan trauma patients and
rib angle v. age. Numbers are small, but there is a slight connection
between age and rib angle in these patients.

Slide 54

Shows a table describing aging trends in 197 Michigan CIREN patients
over 18 who had chest or abdominal CT scans.

Slide 55

Shows aging trends tables broken out by gender. Age correlates with bone
density loss in both genders, chest fat gain greater in males, chest
muscle loss greater in females, visceral fat gains in both.

Slide 56

Shows three scatterplots showing the correlation between age and bone
density in the 197 Michigan CIREN adult cases with abdominal CTs. In all
groups there is a negative correlation showing that bone density
decreases as patients age (p\<.0001 for the groups together as well as
split out by gender).

Slide 57

Shows three scatterplots showing the correlation between chest fat
volume and age in 102 Michigan CIREN adult cases with thoracic CTs. The
total group is significant for chest fat volume increasing as patients
age (p=.015) and males are significant for gaining chest fat as they age
(p=.028). Additionally, the changes that occur are significantly
different between the genders (p=.0078).

Slide 58

Shows three scatterplots showing the correlation between chest muscle
volume and age in 102 Michigan CIREN adult cases with thoracic CTs. The
total group is significant for chest muscle volume decreasing as
patients age (p=.00072) and females are significant for losing chest
muscle volume as they age (p=.0005). Additionally, the changes that
occur are significantly different between the genders (p\<.0001).

Slide 59

Shows three scatterplots showing the correlation between chest bone
volume and age in 102 Michigan CIREN adult cases with thoracic CTs. The
table shows that the changes that occur are significantly different
between the genders (p\<.0001).

Slide 60

Shows three scatterplots showing the correlation between lung volume and
age in 102 Michigan CIREN adult cases with thoracic CTs. The table shows
that the changes that occur are significantly different between the
genders (p=.002).

Slide 61

Shows three scatterplots showing the correlation between abdominal
subcutaneous fat and age in 197 Michigan CIREN adult cases with
abdominal CTs. The table shows that the changes that occur are
significantly different between the genders (p=.02).

Slide 62

Shows three scatterplots showing the correlation between abdominal
visceral fat and age in 197 Michigan CIREN adult cases with abdominal
CTs. The group of both males and females together as well as separately
is significant for increasing abdominal visceral fat (p\<.0001).
Additionally, the changes that occur are significantly different between
the genders (p\<.0001).

Slide 63

Shows a text slide explaining that as age increase, rib angles become
more horizontal in males, bone loses density in both genders, chest fat
gain is greater in males, chest muscle loss is greater in females,
visceral fat increases in both genders.

Slide 64

Shows a text slide asking "Do changes in body composition and geometry
with aging result in altered injury tolerance"? CIREN caveat -- patients
are biased toward being significantly injured.

Slide 65

Shows a slide showing 298 Michigan CIREN adult patients and the
correlations between age and injury severity split out by gender.

Slide 66

Shows a slide showing 2 scatterplots that show bone density v. chest
injury (as measured by MAIS in the thoracic region) in 197 Michigan
CIREN adult cases split by gender. There is a correlation between lower
bone density and higher severity chest injuries for the males (p=.0031)

Slide 67

Shows a slide showing 2 scatterplots that show bone density v. chest
injury (as measured by total number of ribs fractured) in 197 Michigan
CIREN adult cases who have had abdominal CTs split by gender. Both males
(p=.0049) and females (p=.0043) are significant for decreased bone
density means an increase in total ribs fractured.

Slide 68

Slide showing 102 Michigan CIREN adult patients with thoracic CT scans
and the correlations between chest fat volume and injury severity split
out by gender.

Slide 69

Slide showing a crash test with dummies in a Volvo and a computer
simulated crash test with the dummy hitting the airbag.

Slide 70

Repeat of slide 69 with 2 pictures added of a lean person (on left) and
a fat person (on right) Subcutaneous and visceral fat is pointed out on
the fat person.

Slide 71

Shows a slide describing scatterplots showing the correlations between
abdominal injuries and bone density and subcutaneous and visceral fat.
There is significant in decreased subcutaneous fat equating with
decreased severity of abdominal injury (p=.016).

Slide 72

Shows a table describing the correlations between chest component
volumes v. injury severity.

Slide 73

Shows a table showing the correlations between chest component volumes
v. injury severity in males. The incidences that approach significant
for males are marked with a "\*M" to the right of the table. Those
categories that approach significance for females are marked with a
"\*F" to the right of the M column.

Slide 74

Shows a table describing the correlations between chest component
volumes v. injury severity in females. The incidences that approach
significant for males are marked with a "\*F" to the right of the table.
Those that approach significance for females are marked with a "\*M" to
the right of the F column.

Slide 75

A pictures of an overloaded cart with its donkey up in the air because
the cargo weighs so much more than the donkey.

Slide 76

A picture of a traffic circle in England showing vehicles traveling
every which way.

Slide 77

Text slide summarizing all the data. Males significantly differed from
females in all components measured except bone density.

Slide 78

Text slide summary 2: there appear to be trends toward altered injury
tolerance with differences in body composition (CIREN caveat -- severely
injured patients).

Slide 79

Text slide conclusions: body geometry and composition change with aging
and the changes are different according to gender. Changes are
associated with differences in injury severity. More research needs to
be done. Need a control population for CT-based body component analysis.

Slide 80

Acknowledgement slide.