INT’L. J. AGING AND HUMAN DEVELOPMENT, Vol. 65(2) 149-161, 2007

THE INFLUENCE OF SPECIFIC PHYSICAL HEALTH

CONDITIONS ON RETIREMENT DECISIONS

KENNETH S. SHULTZ

California State University, San Bernardino

MO WANG

Portland State University

ABSTRACT

Physical health has consistently been shown to strongly influence the retire-

ment decision-making process. Unfortunately, “physical health” is typically

operationalized in global terms. As a result, we know little about the specific

aspects of physical health that influence the decision to retire. Therefore, in

the present study, data from three waves of the Americans’ Changing Lives

(ACL) data set was examined to determine which specific health conditions

are associated with retirement, continued work in the same job, or continued

work but in a different job. The major health conditions most strongly related

to retirement were lung disease and cancer, while only lung disease was pre-

dictive of job change at older ages. In contrast, arthritis and diabetes were

the minor health conditions most strongly related to both changing jobs and

retiring over an eight-year period. The results are discussed in terms of the

importance of better understanding why specific health factors are associated

with retirement and job changes during one’s late career.

INTRODUCTION

Researchers have consistently shown that health and wealth factors are among the

strongest influences on retirement decisions (Barnes-Farrell, 2003). That is, those

individuals with sufficient income and poor health are more likely to retire than

149

� 2007, Baywood Publishing Co., Inc.

doi: 10.2190/AG.65.2.c

http://baywood.com

individuals with insufficient (or unstable) incomes and those in good health

(Hedge, Borman, & Lammlein, 2006). Health factors have typically been the

domain of study for sociologists, demographers, and epidemiologists, while

wealth factors have been the focus of economists (Adams & Beehr, 2003).

However, psychological factors, such as job attachment, satisfaction with career

attainment, and anxieties about separation from the workplace, have also been

shown to influence retirement decisions (Adams & Beehr, 1998, 2003; Cude &

Jablin, 1992; Hansson, DeKoekkoek, Neece, & Patterson, 1997; Taylor & Shore,

1995), but their influence appears to be much weaker and less robust than health

and wealth factors (Barnes-Farrell, 2003). However, since health is typically

operationalized via a global self-rating of current health, little is known about the

specific aspects of health which influence the retirement decision (Feldman,

1994). Therefore, in this study the concept of physical health is expanded by

providing a more detailed examination of physical health, thereby allowing

us to examine the influence of specific health conditions on the retirement

decision-making and job change processes at older ages (e.g., bridge employment;

Shultz, 2003).

Health Factors

Researchers have continued to show a strong link between a mature worker’s

health and planned retirement age (Farr & Ringseis, 2002; Taylor & Shore,

1995), actual retirement behaviors (Hardy & Quadagno, 1995; Herzog, House, &

Morgan, 1991; Muller & Boaz, 1988), and post-retirement satisfaction and adjust-

ment (Shultz, Morton, & Weckerle, 1998). In most cases though, health is

typically operationalized via global self-report measures asking about a person’s

current or past overall health status. While these global self-report health measures

tend to be highly correlated to actual observed physical health limitations

(Wegman & McGee, 2004), they tend to be very broad, providing no detailed

information on specific health problems or limitations.

Feldman (1994) has noted that, “rather than looking at health status in general,

more careful attention needs to be paid to the specific illnesses and impairments

that impel older workers to leave the workforce” (p. 307). For example, is it

chronic or acute health problems that tend to be more predictive of retirement

intentions and decisions? Clearly more detailed aspects of health need to be

delineated as we move forward to try to better understand the influence of health

on retirement decisions and outcomes.

More specifically, Feldman (1994) has suggested looking within three

categories of health related concerns. First, Feldman hypothesizes that major

health conditions (e.g., cancer) would likely cause retirement age individuals to

completely exit the labor force. Similarly, Feldman predicted that functional

impairments or minor health conditions (e.g., hearing loss) would force older

individuals to exit the workforce in the form of early retirement. Finally, Feldman

150 / SHULTZ AND WANG

predicted that psychosomatic illnesses (e.g., headaches) would be unlikely to force

people to retire, but instead would foster movement to a job or occupation with

fewer demands and so reduce the likely incidence of such illnesses.

Similar to Feldman (1994), Colsher, Dorfman, and Wallace (1988) predicted

that “major health conditions” (e.g., stroke, myocardial infarction, cancer) would

lead individuals to retire. However, they predicted that “minor complaints”

(e.g., foot problems, arthritis, bladder problems) would not affect employment

status in the elderly (65+). Studying a large cohort of rural elderly in Iowa,

Colsher et al. found that in fact it was the major health conditions that distinguish

those elderly who had retired for health reasons, versus those who retired for

some “other” non-health reason or were still employed. While minor health

ailments were prominent in those who retired for health reasons, they were also

prominent in those who retired for other reasons, as well as those who remained

employed. Thus, using a more detailed breakdown of health (i.e., examining

more than just overall health status), we begin to get a better idea of why and how

health influences the retirement decision.

A recent summary of aging workforce issues by Hedge et al. (2006) also

discusses the influence of general health conditions on employment and retire-

ment decisions in late career. However, those authors were unable to point to

any research that examines specific physical health conditions and employment

related decisions at older ages. In addition, a recent exhaustive review of the

occupational health and safety literature specific to older workers by The National

Academies of Science (Wegman & McGee, 2004) does provide detailed infor-

mation on specific health conditions and how they differ for older versus younger

workers. Unfortunately, there is no discussion of how the specific health con-

ditions may influence job change and retirement decisions at older ages. Finally,

another recent comprehensive review of the occupational health and aging

literature by Jex, Wang, and Zarubin (2007) found a paucity of research examining

specific health conditions and employment/retirement related decisions of

older workers. Thus, the lack of available research on this topic further supports

the need of the present research.

Present Study

It is clear from recent comprehensive reviews of prior empirical research (e.g.,

Barnes-Farrell, 2003; Hedge et al., 2006; Jex et al., 2007; Wegman & McGee,

2004) that health factors have a strong influence on the work and retirement

decisions of older workers. However, it is not clear which specific aspects of

health are most prominent in predicting and understanding retirement decisions.

Colsher et al. (1988) provide some evidence for the greater importance of major

health conditions, however their study was cross-sectional, retrospective, and

restricted to the rural elderly (age 65+) in Iowa. Therefore, in the present study,

we expanded on the work of Colsher et al., and the propositions of Feldman

HEALTH AND RETIREMENT DECISIONS / 151

(1994), by examining a variety of health conditions. In addition, we used a large,

longitudinal (three waves of data), national, multistage area probability sample

examining health conditions separately for those who had continued in the same

job, those who had changed jobs, and those who had retired, between 1986

and 1994. Based on Colsher et al.’s findings, and the propositions provided by

Feldman, we propose several hypotheses below. However, given the paucity of

previous empirical research examining the influence of specific physical health

conditions on employment and retirement related decisions at older ages, our

hypotheses should be viewed as preliminary.

Hypothesis 1: Those participants who retired should report higher incidence

of major physical impairments (heart attacks, cancer, stroke, lung disease)

prior to retirement than those who changed jobs.

Hypothesis 2: Those participants who kept their same job should report the

lowest incidence rates of major physical impairments (heart attacks, cancer,

stroke, lung disease).

Hypothesis 3: Those participants who changed jobs should report higher

incidence of minor health conditions (arthritis, hypertension, foot prob-

lems, diabetes, incontinence, and broken bones) before changing jobs

than those who kept their same job.

Hypothesis 4: Those participants who kept their same job should report the

lowest incidence rates of minor health conditions (arthritis, hypertension,

foot problems, diabetes, incontinence, and broken bones).

METHOD

Data Source

The Americans’ Changing Lives (ACL) data set (House, 2003) was used for

the present analyses. The ACL is a multi-wave, national longitudinal panel survey

of sociological, psychological, mental, and physical health factors (see House

et al., 1992, for more details on sampling methods and procedures). Wave I data

(collected in 1986) was a multistage stratified area probability sample of 3,617

participants, with over sampling of Blacks and those 60 years of age and over

(House, 2003). As of Wave I (1986), 29.3% (N = 987) of participants were

between the ages of 47 and 64. Of this group, 569 were working when surveyed

at Wave I (1986). By Wave III (1994), 168 were still in the same job, 66 had

changed jobs, and 177 had retired. The remaining 158 participants listed their

1994 “employment” status as disabled, unemployed, keeping house, or were

“missing,” and thus were excluded from the analyses described below.

The sample was limited to ages 47 to 64 in that many company pension plans

allow individuals to retire as early as age 55, thus those age 47 in 1986 would be

152 / SHULTZ AND WANG

age 55 by 1994. In addition, much of the recent historical demographic data show

a noticeable decline in labor force participation after age 55 (Costa, 1998).

Meanwhile, by age 65 individuals were still eligible for full social security benefits

in 1994. Therefore, it was decided to limit the sample to this age group.

In addition, given that the ACL over-sampled Blacks and those over age 60

at twice the rate found in the United States, it is necessary to weight the data

when conducting multivariate analyses (cf. Schnittker, 2001). As the sample

in this study was selected based on age, we decided to only weight the current

multinomial logistic regression analyses on ethnicity using the WEIGHT function

offered by the SPSS software. It should be noted that we also conducted the

multinomial logistic regression analyses without weighting the data, which

yielded very similar results, however, only the weighted results are reported here.

Measures

A variety of physical health measures were used (see Appendix for specific

items and response scales for each measure). The physical health measures

included a list of 10 physical conditions experienced in the last 12 months at

Wave I. These were divided into “major health conditions” (heart attack, cancer,

stroke, and lung disease) and “minor health conditions” (arthritis, hypertension,

foot problems, diabetes, incontinence, and broken bones), along the lines

suggested by Colsher et al. (1988) and Feldman (1994). Unfortunately, no infor-

mation on what Feldman (1994) refers to as psychosomatic illnesses (e.g.,

headaches) were collected. While no strong rationale or theory was provided by

House (2003) as to why these specific physical conditions were included, they

are in line with previous theorizing of Feldman (1994), as well as Wegman and

McGee (2004).

RESULTS

Table 1 displays the percentage of participants, who between 1986 and 1994

kept their same job (N = 168), changed jobs (N = 66), or retired (N = 177), who

possibly suffered from 10 different chronic physical health conditions in the

previous 12 months at the time of the first survey in 1986. Looking at Table 1, we

see that 7.4% of participants suffered from cancer prior to retirement, compared

to 3.0% and 1.2% for those who changed jobs and those who kept their job,

respectively. In addition, 15.9% of participants suffered from lung disease prior to

retirement, compared to 7.6% and 1.2% for those who changed jobs and those

who kept their job, respectively. These results support hypotheses 1 and 2. The

other “major health conditions” show a somewhat similar pattern, with retirees

having the highest incidence rates among the three employment status groups.

However, due to the relatively low incidence rates in general for major health

HEALTH AND RETIREMENT DECISIONS / 153

conditions in this age group (47-64), only cancer and lung disease demonstrated

statistically significant differences via the chi-square test.

In terms of minor health conditions, we see that 51.4% of participants suffered

from arthritis prior to retirement, compared to 42.4% and 29.2% for those who

changed jobs and those who kept their job, respectively. Also, 37.9% of par-

ticipants suffered from foot problems prior to retirement, compared to 24.2%

and 26.2% for those who changed jobs and those who kept their job, respectively.

In addition, 12.4% of participants suffered from diabetes prior to retirement,

compared to 9.1% and 3.6% for those who changed jobs and those who kept their

job, respectively. Chi-square tests demonstrated significant differences on these

three kinds of minor health conditions. These results, in general, suggest that

participants who retired had the highest incidence of minor health conditions,

while those who remained in their same job had the lowest, thus supporting

hypotheses 3 and 4.

To further determine how major and minor health conditions influence the

retirement decision-making process, multinomial logistic regression (MLR) was

used to analyze the data. MLR allows one to control for certain variables, such

as demographic characteristics, while also allowing one to examine the unique

influence of each variable in predicting our outcomes of interest (Spicer, 2004).

154 / SHULTZ AND WANG

Table 1. Percent of Participants between 47-64 Who Experienced

10 Chronic Health Conditions in the Last 12 Months at Time 1 (1986)

by Current Job Status at Time 3 (1994)

Percent experiencing condition

Health condition �2 (df = 2)

Kept same job

(N = 168)

Changed jobs

(N = 66)

Retired

(N = 177)

Major health conditions

Heart attack

Cancer

Stroke

Lung disease

Minor health conditions

Arthritis

Hypertension

Foot problems

Diabetes

Incontinence

Broken bones

0.72

8.48*

1.28

23.80**

17.73**

2.16

7.12*

8.98*

1.51

0.04

4.8%

1.2%

1.2%

1.2%

29.2%

27.4%

26.2%

3.6%

4.2%

3.6%

3.0%

3.0%

1.5%

7.6%

42.4%

27.3%

24.2%

9.1%

1.5%

3.0%

5.6%

7.4%

2.8%

15.9%

51.4%

34.1%

37.9%

12.4%

5.1%

3.4%

Pearson Chi-Square, *p < .05, **p < .01.

MLR also has the advantage of providing odds ratios so that the likelihood of an

event occurring (e.g., retiring) can be determined based on the unique predictive

influence of a given variable (Menard, 2001). Weighted data were used in these

analyses, as African Americans were over-sampled in the ACL. To obtain the

multinomial logistic regression coefficients, participants who kept their jobs

were designated as the reference group for each model. Age, gender, ethnicity,

and income were treated as control variables in each model. Table 2 presents

the MLR analysis results.

In terms of the major health conditions, it was found that the incidence of lung

disease and cancer significantly predicted participants’ retirement decision.

Specifically, participants who suffered from lung disease were 13.14 times more

likely to retire than to keep their jobs. It was also found that participants who

suffered from cancer were 4.84 times more likely to retire than to keep their jobs.

In addition, participants who suffered from lung disease were 6.27 times more

likely to change their jobs than to keep their jobs. Another MLR analysis, which is

not presented in the table, revealed a marginal effect (B = 0.74, SE = 0.44, p < .10)

that participants who suffered from lung disease were 2.10 times more likely to

retire than to change their jobs (see Table 2).

For minor health conditions, it was found that the incidence of arthritis and

diabetes significantly predicted participants’ retirement decision. Specifically,

participants who suffered from arthritis were 1.93 times more likely to retire than

to keep their jobs. It was also found that participants who suffered from diabetes

were 3.37 times more likely to retire than to keep their jobs. In addition, par-

ticipants who suffered from arthritis were 1.97 times more likely to change their

jobs than to keep their jobs. Participants who suffered from diabetes were also

3.33 times more likely to change their jobs than to keep their jobs. Additional

MLR analyses, which are not presented in the table, did not find evidence that

minor health conditions differentiate participants in terms of the probability of

choosing retirement and the probability of changing jobs (see Table 2).

DISCUSSION

Beehr and Adams (2003) recently noted that, “There is much that we already

know and much yet to be learned about retirement decisions and retired life”

(p. 293). In the same edited text, Barnes-Farrell (2003) discusses a variety of

attitudinal and other variables (e.g., worker attitudes, job conditions, organi-

zational climate, social pressures) that may influence the retirement decision-

making process. So, while we have chosen to focus on specific health concerns

in this study, it should be made clear that there are a variety of factors, both

individual and contextual, that potentially influences the retirement decision.

Thus, the retirement process is indeed a complex process with many factors

potentially playing a role.

HEALTH AND RETIREMENT DECISIONS / 155

Tab

le2

.E

stim

ate

dC

oeffic

ien

tsan

dO

dd

sR

atio

sfo

rH

ealth

Co

nd

itio

ns

inM

ultin

om

ialLo

gis

tic

Reg

ressio

n

Mo

del1

(Majo

rh

ealth

co

nd

itio

ns)

Mo

del2

(Min

or

health

co

nd

itio

ns)

Estim

ate

sS

EO

dd

sra

tio

Estim

ate

sS

EO

dd

sra

tio

Retire

dg

rou

p

Inte

rcep

t

Co

ntr

ols

Ag

e

Gen

der

Eth

nic

ity

Inco

me

Majo

rh

ealth

co

nd

itio

n

Lu

ng

dis

ease

Heart

att

ack

Can

cer

Str

oke

–1

0.8

7**

.20

**

.41

–.2

4

–.0

4

2.5

8**

–.3

3

1.5

8*

.93

1.6

9

.03

.29

.35

.06

.78

.51

.80

1.0

5

1.2

2

1.5

1

.79

.96

13

.14

.72

4.8

4

2.5

4

Retire

dg

rou

p

Inte

rcep

t

Co

ntr

ols

Ag

e

Gen

der

Eth

nic

ity

Inco

me

Min

or

health

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itio

n

Art

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tis

Hyp

ert

en

sio

n

Dia

bete

s

Fo

ot

pro

ble

ms

Bro

ken

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nes

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ntin

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ce

–1

0.8

7**

.19

**

.49

–.1

0

–.0

4

.66

*

–.3

8

1.2

1*

.49

–.2

1

–.5

7

1.6

7

.03

.29

.36

.06

.29

.32

.59

.31

.72

.62

1.2

1

1.6

3

.91

.96

1.9

3

.68

3.3

7

1.6

2

.81

.57

156 / SHULTZ AND WANG

Jo

bch

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gro

up

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�2

df

–.6

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.00

.58

.12

–.1

3

1.8

3*

–.3

5

.52

–.0

8

10

6.0

3**

16

1.8

1

.03

.34

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.07

.89

.83

1.1

0

1.3

1

1.0

0

1.7

8

1.1

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6.2

7

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1.6

7

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Jo

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ms

Bro

ken

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–.5

2

–.0

1

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.12

–.1

3

.68

*

–.2

1

1.2

0*

–.0

5

–.1

4

–1

.09

96

.94

**

20

1.8

6

.03

.35

.43

.07

.35

.41

.61

.40

.87

1.1

2

1.0

0

1.6

9

1.1

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.86

1.9

7

.81

3.3

3

.96

.87

.34

No

te:

Part

icip

an

tsw

ho

kep

tth

eir

job

sw

ere

desig

nate

das

the

refe

ren

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gro

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ata

was

weig

hed

based

on

eth

nic

ity.

*p

<.0

5.**p

<.0

1.

HEALTH AND RETIREMENT DECISIONS / 157

However, as Barnes-Farrell (2003) points out, “. . . it is clear that both health

and wealth play important roles in the decision to retire and the timing of

retirement, largely because they place important constraints on a worker’s ability

to carry out a preferred path of action . . . [in doing so they] mitigate the influence

of other individual and contextual variables that would otherwise lead workers

to remain on the job or retire from the workplace” (p. 159). Thus, we must better

understand how health status influences the retirement process before moving

on to examine other (secondary) factors.

Therefore, in the present study we extended previous research in several

important ways to better understand the health precursors to retirement and job

changes in late career in more detail. First, we evaluated specific health conditions

that older individuals (ages 47-64) suffer from, reporting these separately as

“major health conditions” and “minor health conditions.” In addition, these health

conditions were reported separately for those who subsequently retired, those

who remained employed in the same job, and those who changed jobs over an

eight-year period (1986 to 1994). The results of the present study strongly

support both Colsher et al.’s (1988) empirical findings and Feldman’s (1994)

propositions. That is, the major health conditions of lung disease and cancer are

more likely to lead to retirement, whereas minor health conditions of diabetes

and arthritis are more likely to lead to either retirement or job changes, at least for

those in the 47-64 age range. Future research should include what Feldman calls

psychosomatic illnesses to determine if they too are likely to results in job changes

versus retirement or continuing to work in the same job at older ages.

Interestingly, another important extension of the present research, the use of

longitudinal data, may have contributed to the fact that only half (5 of 10) of the

health conditions showed statistically significant differences (see Table 1). This

lack of statistical significance may be due in part to the low number of participants

(i.e., low power) in the “changed jobs” (N = 66) category. Future studies should

use longer time intervals and/or larger initial samples to examine these issues.

In addition, the low prevalence rate for major health conditions such as stroke

also likely contributed to the lack of power to detect significant differences.

In addition, the difficulty in defining and measuring retirement should be noted.

Feldman (1994), for example, pointed out that retirement can be defined in

self-report, labor force participation, pension receipt, and several other forms. In

the present study we used self-report of current employment status at Wave III

(1994). Thus, the same individuals currently working part-time who have “retired”

from career jobs may well report different employment statuses (Shultz, 2003). In

a similar vein, we used self-report measures of illness as well. Thus, future

researchers should try to confirm self-reported health conditions with actual

medical records. Given the increased use of electronic medical records, this may

be practical in just a few years.

Better understanding of the specific physical health related factors that

influence employment decisions at older ages would help both researchers and

158 / SHULTZ AND WANG

organizations to better predict and understand the retirement process. In particular,

specific health conditions, which put individuals at risk for premature retirement,

can be identified, as well as identifying which conditions play the greatest role in

the decision to retire (Colsher et al., 1988). However, recent preventive strategies

may already be reducing major illnesses such as heart disease (via reduced fat

diets, increased exercise, and cholesterol lowering drugs) and lung disease (via

reduced tobacco use), thus reducing the risks of the need to change jobs late in

ones career or retire early altogether. Still, retirement and employment counselors

who are aware of the health conditions associated with the need to change jobs or

retire early at later ages can provide targeted counseling to individuals deemed

to be “at risk” for such conditions.

In addition, future research should incorporate organizational factors that

might impact the relationship between health and retirement decisions. For

example, given an older employee might be experiencing a chronic major health

condition or minor health condition, what would be the impact of the loss of

health insurance upon her retirement decision? In terms of job changes, what

options exist within her organization for reduced work schedules or for light duty

assignments? What job redesign processes could be implemented to assist older

workers to remain employed versus having to retire or change jobs (Jex et al.,

2007)? What types of social supports exist in the employee’s work and home

environments that might help her to deal with her physical condition(s)? Other

psychosocial variables (e.g., job satisfaction or organizational commitment), no

doubt, interact with current health conditions to impact one’s retirement and late

career job decisions as well, and so should be examined in future research

(Barnes-Farrell, 2003).

In conclusion, although this study served as an important first step in better under-

standing how specific physical health conditions influence later life employment

decisions, it was just a first step. Additional, primary research with larger samples

and psychometrically stronger, well-established scales is clearly warranted. In

doing so, we will gain a better understanding of the specific health precursors to job

changes and early retirements at older ages, as well as eventually determine how

these specific health factors interact with other known predictors of retirement

(e.g., wealth, job commitment) in the complex retirement decision making process.

ACKNOWLEDGMENTS

This research was begun while the first author was on sabbatical and serving

as a post-doctoral fellow at the Ethel Percy Andrus Gerontology Center at

the University of Southern California. He thanks the University of Southern

California for providing financial support through a National Institute on Aging

training grant (No. T32-AG00037). The authors also thank Deborah Olson,

Elizabeth Klonoff, and two anonymous reviewers for their comments on earlier

versions of this article.

HEALTH AND RETIREMENT DECISIONS / 159

APPENDIX

Physical Health Measures

Chronic conditions experienced in the last 12 months (scored: 0 = not experi-

enced, 1 = experienced).

• arthritis/rheumatism

• lung disease

• hypertension

• heart attacks or heart trouble

• diabetes

• cancer/malignant tumor

• foot problems

• stroke

• fracture or broken bones

• incontinence

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Direct reprint requests to:

Kenneth S. Shultz

Department of Psychology

5500 University Parkway

California State University, San Bernardino

San Bernardino, CA 92407

e-mail: kshultz@csusb.edu

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