oanoe oveer 145 - Virginia Tech

Roanoke, VA • November 12–14, 2015 145

Veteran Status and Work in Deadly Civilian JobsAre Veterans More Likely to Be Employed in High-Risk Occupations than

Nonveterans?

April L. Gunsallus ([email protected])The Pennsylvania State University

Abstract

The demand for workers in high-risk occupations is growing, as is the number of service members transitioning from military to civilian jobs. This paper will address whether veterans are more likely to hold physically hazardous occupations than nonveterans. While military jobs vary in the degree to which physical injury or death is likely, even basic entry into the military requires recruits to be mindful of risks at all times and routinely follow safety protocols. In comparison to the nonveteran workforce, veterans may experience a greater risk of holding physically hazardous jobs as a result of the jobs and skills for which they were trained in the military. This paper is part of a dissertation project which addresses fatal occupational injury. While much of the work literature on veterans has been descriptive, this study uses logistic regression to address the following questions: Are veterans overall more likely than nonveterans to hold high-risk occupations? The data come from recent pooled Veterans Supplements of the Current Population Survey. The trend toward increasing high-risk employment opportunity is substantiated by the latest employment projections from the U.S. Bureau of Labor Statistics (BLS). The occupations with the highest projected number of new jobs, in 2022, are concentrated in health care, retail service, and construction industries. The type and number of construction jobs vary among the highest growth occupations. Most in demand in 2022 will be construction laborers (259,800); laborers and freight stock, and material movers (241,900); carpenters (218,200), and heavy and tractor-trailer truck drivers (192,600). Many of these jobs are nested within industries that are well-known as dangerous—industries such as agriculture, forestry, fishing, and hunting, mining, construction, and manufacturing. None of these industries is evenly distributed across metropolitan (metro) and nonmetropolitan (nonmetro) places, with each having greater shares of total employment in nonmetro places compared to metro areas. This dissertation will explore whether nonmetro veterans are more at risk of high-risk job holding than metro or suburban veterans. One factor possibly contributing to nonmetro veterans being in high-risk work is that they have fewer alternative employment options, suggesting an increased likelihood that nonmetro veterans would be more willing to take higher-risk jobs than their nonmetropolitan counterparts.

Keywords: workforce, rural veterans, fatal occupations, gendered occupations, employment opportunities, high-risk industries

Proceedings of the Third Conference on Veterans in Society146

Veteran status and work

in deadly civilian jobs:A

re veterans m

ore likely to

be em

plo

yed

in h

igh-risk o

ccup

ation

s than

no

nveteran

s?

Ap

ril Gu

nsallu

s, Ph

.D. C

and

idate

The Pen

nsylvan

ia State Un

iversityR

ural So

ciolo

gy

3rd

An

nu

al Veteran

s in S

ociety C

on

ference

Virg

inia Tech

No

v 13, 2015


BACKGROUND –Veterans and High-Risk Occupations

Are veteran

s mo

re likely to be em

plo

yed in

high

-risk o

ccup

ations th

an n

onveteran

s?

A h

igh

-risk occu

patio

n is o

ne in

wh

ich in

juries th

at occu

r are likely to

be u

nexp

ected, su

dd

en, an

d fatal.

No

n-fatal o

r chro

nic in

juries asso

ciated w

ith rep

etitive m

ovem

ents o

r pro

lon

ged

expo

sures n

ot ad

dressed

here.


★Gulf W

ar era (1990-ongoing)

↑Vietnam

era (1964-1975)↑

Korean conflict (1950-1955)↑

World W

ar II (1941-1946)↑

World W

ar I (1917-1918)

Wartim

e PeriodsG

ulf I (P

re 9/11)

Operation D

esert ShieldO

peration Desert Storm

Gu

lf II (OE

F/O

IF)

Operation E

nduring FreedomO

peration Iraqi Freedom

Source: National Center for

Veterans Analysis and Statistics

Gulf Era Vets = 89.6%

Labor Force Participation Rate

Vietnam Vets = 64.3%

Labor Force Participation Rate


Today 22 million veterans live

among the civilian population

age 18 and older.

Gulf Era veterans represent

almost 1 in 4 of all veterans.

Gulf Era Vets = 6.1 m

illion


CFOI –The Census of Fatal Occupational Injuries by BLS

OEF total deaths: 2,220

OIF total deaths: 4,500


CFOI –Men’s & W

omen’s Fatality

Men

and

wo

men

sort in

to d

ifferent typ

es o

f occu

patio

ns.

•d

ifferences in

men’s an

d w

om

en’s abilities

•th

eir risk/safety preferen

ces•

emp

loyer d

iscrimin

ation

•d

iffering

econ

om

ic circum

stances

Fatal work injuries &

hours worked,

by gender of worker, by year.

Source: CFOI 2012, 2013, 2014

A disproportionate share of fatal work injuries

involve men relative to their w

ork hours.


Majo

r Occu

patio

nal C

atego

ry2

01

4*

20

13

20

12

Co

un

tR

ateC

ou

nt

Rate

Co

un

tR

ate

Transp

ortatio

n an

d m

ovin

g1289

14

.71184

14

.11150

14

.0

Co

nstru

ction

and

extraction

8851

1.8

8181

1.8

8381

2.4

Service584

2.6624

2.7596

2.7

Man

agem

ent, b

usin

ess, and

finan

ce452

1.9410

1.7451

1.9

Installatio

n, m

ainten

ance,an

d rep

air391

7.8

3567

.0326

6.7

Professio

nal an

d related

2531.6

2280.8

2450.7

Farmin

g, fish

ing

, and

forestry

2342

4.1

2252

3.1

2222

3.3

Sales and

related232

0.7211

1.5216

0.7

Prod

uctio

n206

2.4210

2.6211

1.5

Office an

dad

min

istrative sup

po

rt98

0.670

0.482

2.5

Total W

orker

Fatalities/All-W

orker

Rate

46

79

3.3

44

05

3.2

43

83

3.2

CFOI –Fatality Count and Rate by Occupation by Year

* Data are preliminary for 2014.

Rates are per 100,000 full-time equivalent w

orkers

Farmin

g, fish

ing

, and

forestry

23

42

4.1

22

52

3.1

22

22

3.3


http://ww

w.startribune.com

/deadliest-workplace-the-fam

ily-farm/330403811/

October 7, 2015


“Farmin

g fits veteran

s, an

d veteran

s fit farmin

g.

Man

y veterans w

ant to

retu

rn to

small to

wn

A

merica to

raise their

families. A

nd

we

welco

me th

em h

om

e.”

WORKFORCE OPPORTUNITY –

Veterans Returning Home

http://www.cfra.org/farm

ing-fits-veterans-and-veterans-fit-farming

http://www.gijobs.com

/5-different-types-of-jobs-in-agriculture/


WORKFORCE OPPORTUNITY–

Skilled workers in demand


DATA –Current Population Survey, Veteran Supplem

entsCPS is the only m

onthly estimate of the labor force

(Does not include active duty service m

embers)

Certain months have a “focus” (a.k.a. supplem

ents)

I combined data from

2012 & 2013

Starting N ≈

300,000(rem

oved those Not in the Labor

Force) N = 124,117 (ages 18-65)

(removed w

omen)

Final N = 64,753


DATA –Dependent Variable –Binary “In a Deadly Job or Not”

Total N=64,753


DATA –Independent Variable –Binary “Nonm

etroor Not”

Total N=64,753


DATA –All W

orkers & Veteran Workers Characteristics

Variab

les2

01

2&

20

13

All ♂

& ♀

All Vets

Wo

rkin

g in

a Dead

lyJo

b2

1.7

33

.3

Ag

e (18-65)x̄

=41.4

x̄=

48.7

RaceW

hite

82.484.3

Black

9.510.2

Oth

er8.0

5.5

Hisp

anic

(any race)

12.75.7

Edu

cation

Less than

HS/H

Sd

iplo

ma

35.430.7

Som

e colleg

e30.4

39.7

Co

llege d

egree (B

S/hig

her)

34.329.5

Female

47.910.4

Everserved in

the m

ilitary5.8

100

No

nm

etrop

olitan

status

18

.82

1.7

Total W

orker

12

4,1

17

7,1

50

Variab

les2

01

2 &

20

13

All ♂

♂Vets

Wo

rkin

g in

a Dead

lyJo

b3

5.4

36

.4

Ag

e (18-65)x̄

=41.4

x̄=

49.1

RaceW

hite

83.884.8

Black

8.39.5

Oth

er8.0

5.7

Hisp

anic

(any race)

13.75.7

Edu

cation

Less than

HS/H

Sd

iplo

ma

39.632.4

Som

e colleg

e28.0

39.3

Co

llege d

egree (B

S/hig

her)

32.428.4

Female

------

Everserved in

the m

ilitary9.9

100

No

nm

etrop

olitan

status

18

.92

1.9

Total W

orker

64

,75

36

,40

8


Higher risk of holding a deadly job

for men.

Men in deadly jobs 35%

compared

to 7% w

omen.

MEN

VETERAN w

orkers are more

likely to be in deadly jobs than w

omen veterans.

The proportions are 36% m

en and 7%

wom

en of veteran workers in

deadly jobs.

Results –Bivariate relationships –Sex


Results –Bivariate relationships –Metropolitan Status

Higher risk of holding a deadly job

in NO

NM

ETRO areas for m

en.

Nonm

etrow

orkers in deadly jobs47%

compared to 33%

metro.

NO

NM

ETRO VETERAN

men

workers are m

ore likely to be in deadly jobs than m

etro veterans.

The proportions are 34% m

etro and 46%

nonmetro

of veteran w

orkers in deadly jobs.


Results –Logistic Regression Modeling –Key IV’s

Veteran status is marginally

significant. Veterans more likely

than nonvetsto be in a deadly job.

Nonm

etrostatus is significant.

Nonm

etrom

en are more likely

than metros to be in a deadly job.


Results –Key IV’s –Veteran & Metropolitan Status

Controlling for nonmetro

status drops veteran status out of

statistical significance.

An interaction effect between

veterans and nonmetro

status is not significant in this m

odel.


Results –Interaction Effect? –Veteran x Nonm

etAn interaction effect betw

een veterans and nonm

etrostatus is

not significant in this model.


Controls –Education

Controlling for education brings veteran status back into statistical significance.


Controls –Race

Controlling for race does NO

T brings veteran status back into

statistical significance.


Controls –Education & Race

Adding controls for education &

race brings veteran status back into statistical significance.


Controls –Educ& Race & Hisp

Adding Hispanic ethnicity

strengthens the effect andstatistical significance of veteran.


CONCLUSION –Questions

April G

unsallusalg978@

psu.edu814.360.9618


About the Author

April Gunsallus, M.S., is a Graduate Research Assistant for the Clearinghouse for Military Family Readiness at The Pennsylvania State University. After earning a bachelor’s degree in Economics at Lebanon Valley College of Pennsylvania, April commissioned as a U.S. Navy officer at Pensacola, Florida, and worked for three years in naval aviation. April received her M.S. in Rural Sociology from Penn State and will receive her Ph.D. in 2016. The arc of her research explores how risk and resilience interact among the individual, family, and community levels. She is particularly fascinated by the domain of work and occupations. At the Clearinghouse, she contributes to The Veteran Metrics Initiative which seeks to better understand Service member transition from Military to civilian life. As a doctoral student, she serves on the executive board of a student Veteran fraternity and is actively engaged in philanthropic and social Veteran activities.

References

Bureau of Labor Statistics. “Fatal Occupational Injuries in 2014.” Chart Package. United States Department of Labor. 2015. http://www.bls.gov/iif/oshwc/cfoi/cfch0013.pdf.

___“Fatal Occupational Injuries in 2013.” Chart Package. United States Department of Labor, 2014. http://www.bls.gov/iif/oshwc/cfoi/cfch0012.pdf.

___“Fatal Occupational Injuries in 2012.” Chart Package. United States Department of Labor, 2013. http://www.bls.gov/iif/oshwc/cfoi/cfch0011.pdf.

National Center for Veterans Analysis and Statistics. “Profile o Veterans: 2012,” Data from the American Community Survey, United States Department of Veterans Affairs, 2014, http://www.va.gov/vetdata/docs/SpecialReports/Profile_of_Veterans_2014.pdf.

___“Characteristics of Rural Veterans: 2010,” Data from the American Community Survey. United States Department of Veterans Affairs, 2012.

http://www.va.gov/vetdata/docs/SpecialReports/Rural_Veterans_ACS2010_FINAL.pdf.

___“Labor Force Participation of Veterans: 2000 to 2009 Data from the American Community Survey.” United States Department of Veterans Affairs. 2010, http://www.va.gov/vetdata/docs/SpecialReports/LFPR_FINAL_March2.pdf.

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