Question:
You are given the full text of a scientific research paper.

    Identify and summarize the **policy problem** that this research addresses. Your response should:
    - Clearly state the societal, environmental, or strategic issue motivating the study
    - Be written in accessible, policy-brief style sentences
    - Focus on the core challenge the research aims to solve
    - Avoid excessive detail or technical jargon unless necessary for clarity

    Write a short paragraph suitable for inclusion under the “Policy Problem” section of a policy brief.

    Scientific Research Paper:
    https://doi.org/10.1177/00221465231205266
Journal of Health and Social Behavior
2024, Vol. 65(2) 162–181
© American Sociological Association 2023
DOI: 10.1177/00221465231205266
journals.sagepub.com/home/hsb
Original Article
One of the most consequential changes in the
American labor market in the past half-century is
the demise of the labor movement (Farber et  al.
2018; Rosenfeld 2014). Whereas one third of pri-
vate sector workers were union members in the
1950s, today, about 6% of the private sector is
unionized. Although most research on the conse-
quences of union decline focuses on its economic
impact, a growing literature has addressed the con-
sequences of union membership for health and well-
being (Leigh and Chakalov 2021; Reynolds and
Brady 2012). Through the improvement of work-
place and occupational conditions (Donado 2015;
Hagedorn et al. 2016; Keune 2013), higher earnings
(VanHeuvelen 2018; Western and Rosenfeld 2011),
expanded access to fringe benefits (Rosenfeld
2014), and broad sociopsychological advantages
(Blanchflower and Bryson 2020; Flavin and
Shufeldt 2016), union membership has been shown
to influence multiple dimensions of physical and
mental health and well-being.
The current study uses multilevel growth curve
models applied to 39 waves of data from the Panel
Study of Income Dynamics between years 1970
and 2019 to assess how the accumulated experience
of union membership across the entirety of one’s
career, or what we term cumulative unionization,
affects disparities of general health, functional limi-
tations, and chronic conditions among adults ages
60 and older. The measure of cumulative unioniza-
tion, rather than a static measure of union status
collected at a particular point in time, captures
career-long duration of union attachment, a source
1205266 HSBXXX10.1177/00221465231205266Journal of Health and Social BehaviorHan et al.
research-article2023
1University of Minnesota, Twin Cities, Minneapolis, MN,
USA
2Bocconi University, Milano, Italy
Corresponding Author:
Tom VanHeuvelen, Department of Sociology, University
of Minnesota, Twin Cities, Social Sciences Building, 267
19th Ave S, Minneapolis, MN 55455, USA.
Email: tvanheuv@umn.edu
Cumulative Unionization and
Physical Health Disparities
among Older Adults
Xiaowen Han1
, Tom VanHeuvelen1
,
Jeylan T. Mortimer1
, and Zachary Parolin2
Abstract
Whereas previous research shows that union membership is associated with improved health, static
measurements have been used to test dynamic theories linking the two. We construct a novel measure of
cumulative unionization, tracking individuals across their entire careers, to examine health consequences
in older adulthood. We use data from the Panel Study of Income Dynamics (1970–2019) and predict
self-rated health, functional limitations, and chronic health conditions in ages 60 to 79 using cumulative
unionization measured during respondents’ careers. Results from growth models show that unionized
careers are associated with .25 SD to .30 SD improvements in health among older adults across all
measures. Analyses of life course mechanisms reveal heterogeneous effects across unionization timing, age
in older adulthood, and birth cohort. Moreover, subgroup analyses reveal unionization to partially, but not
fully, ameliorate disparities based on privileged social positions. Our findings reveal a substantial and novel
mechanism driving older adulthood health disparities.
Keywords
cumulative unionization, health disparities, heterogeneous effects, life course, older adulthood

Han et al.
163
of advantage that accumulates unequally across
social groups (Dannefer 2021; O’Rand 1996). The
unequal accumulation of union experience further
translates into health disparities in later life.
After documenting overall positive associations
between a larger proportion of one’s career spent in
unions and positive physical health outcomes at
older ages, we move on to examine key sources of
heterogeneity. First, we consider heterogeneity in
union–health associations across three temporal
dimensions of life course processes: variation in
age timing of career unionization, ages across older
adulthood, and birth cohorts. We find a significant
lag, where unionization at younger ages is more
predictive of older adulthood health, while the asso-
ciations of cumulative unionization unsurprisingly
decay as individuals move into older ages. And
associations are concentrated among earlier birth
cohorts or those who spent more years in a labor
market with strong and federally supported labor
unions (Jacobs and Myers 2014).
Second, we examine whether cumulative union
associations are heterogeneous across social cate-
gories based on structural positions of advantage:
educational attainment, sex, and race. Associations
are primarily concentrated among individuals with-
out a college degree and men, although the benefi-
cial associations are slightly more pronounced
among non-White individuals. These findings
reflect the critique of labor unions as narrowly
focused on the well-being of the midtwentieth cen-
tury’s White working class (Cowie 2010) and
labor’s tumultuous relationship with civil rights
(Frymer 2011). But they also reveal cumulative
unionization to be a distinct input into health out-
comes that cannot be fully reduced to other forms
of advantage based on social position.
The current study has significant implications
for health scholars and policymakers. It reveals that
unionization, measured at the career level, has a
meaningful input into health disparities that extend
into older adulthood. Neither cross-sectional stud-
ies nor longitudinal studies that begin in the late
career can detect these disparities. We argue that the
benefits of unionization for older adults is an under-
appreciated dimension of the positive health out-
comes recently examined by health scholars
(Hagedorn et al. 2016; Leigh and Chakalov 2021).
Results from this research build on the growing lit-
erature that extends work and occupation mecha-
nisms to the career level (Donnelly 2022; Parolin
and VanHeuvelen 2023). Finally, our findings con-
tribute to literature focusing on the policy and insti-
tutional sources of population health and well-being
(Bakhtiari, Olafsdottir, and Beckfield 2018; Montez
et al. 2020).
Background
Unions represent a critical labor market institution
promoting economic attainment, stability, and ben-
efits for ordinary and less powerful workers
(Ahlquist 2017; Farber et al. 2018; Rosenfeld 2014).
Scholars have identified the decline of private sector
unions, covering one third of workers in the 1950s
to 6% today (Eidlin 2018), as a transformational
process for the American labor market (Card,
Lemieux, and Riddell 2004; Rosenfeld 2019).
Fortin, Lemieux, and Lloyd (2021), for example,
find that the combination of minimum wage stagna-
tion and union decline accounted for two thirds of
inequality growth since the 1980s, whereas Farber
et al. (2018) show consistent union earnings premi-
ums over three quarters of a century amid union
membership compositional changes.
Yet union benefits extend beyond economic out-
comes. Health scholars have begun to focus
squarely on how labor union membership contrib-
utes to health and well-being (Leigh and Chakalov
2021; Reynolds 2021). Recent studies suggest that
union members enjoy better health outcomes than
nonunion members. In particular, union members
tend to have lower rates of workplace injuries
(Economou and Theodossiou 2015), work in firms
with higher rates of OSHA inspections (Weil 1991),
and have lower overall exposure to hazardous envi-
ronments (Ehrenberg, Smith, and Hallock 2021). In
the wake of union decline, contingent, precarious,
and unpredictable work has risen, which is shown
to have negative effects on worker health
(Schneider and Harknett 2019).
Why would unions produce positive health out-
comes for workers? Scholars point to multiple
direct and indirect mechanisms. Unions increase
wages (VanHeuvelen 2018), particularly middle
and lower incomes (Firpo, Fortin, and Lemieux
2009), and keep households out of poverty (Brady,
Baker, and Finnigan 2013; VanHeuvelen and
Brady 2022). More economic resources should
translate straightforwardly to better opportunities
to avoid and manage health problems. Unions also
compress earnings distributions (Jacobs and
Dirlam 2016; Western and Rosenfeld 2011).
Insofar as income matters not only absolutely but
relatively for individual well-being (Alderson and
Katz-Gerro 2016; Frank 2016), a compressed dis-
tribution may have wide rippling effects (Curran
and Mahutga 2018).

164
Journal of Health and Social Behavior 65(2)
Moreover, union members have higher rates of
various fringe benefits, such as retirement and pen-
sion plans (Rosenfeld 2014), and occupational
security (Brown 2006; Malinowski, Minkler, and
Stock 2015), which increase predictability and
opportunity to plan for the future. As a result,
unionized workers can more easily devote contem-
poraneous spending to health needs and have access
to health care to address health issues. Union mem-
bers on average have higher rates of paid sick leave,
vacation leave, and paid family leave, all of which
should increase access to health care and recovery
time away from work in the case of a negative
health event (Leigh and Chakalov 2021; Reynolds
2021; Rosenfeld 2014). Union members are also
more likely to have health insurance and higher
quality health insurance (Hagedorn et  al. 2016;
Reynolds and Brady 2012), which may enable more
immediate treatment of health problems and enable
access to preventive care, which would reduce
longer-term health problems.
Union members typically have lower rates of
excessive overtime work and less exposure to pre-
carious and contingent work, which may reduce
workplace
stress
(Hirsch,
Macpherson,
and
DuMond 1997; Morantz 2017; Trejo 1993). Unions
provide an institutionalized platform for workers to
organize collectively against unsafe conditions; the
classic work by Wallace (1987) shows that higher
union membership rate is associated with signifi-
cant declines in fatal and nonfatal injury rates
among miners. Unions also enhance social stability
and support, promoting stable marriage (Schneider
and Reich 2014), greater sociality and support at
work (Hagedorn et  al. 2016), and more frequent
community and charity engagement (Zullo 2013).
It is unlikely that any of these mechanisms would
provide positive health outcomes that can be caus-
ally determined to originate exclusively from union
membership. However, the combination of pre-
sumed indirect and peripheral benefits that are
themselves shown to be associated with improved
health and well-being suggests that unionization
makes a nontrivial contribution to better health
among workers.
Cumulative Unionization as a
Mechanism of Health
In the current study, we extend the analytic focus to
the influence of cumulative unionization that occurs
over the course of an individual’s career on health
outcomes that occur in older adulthood, which we
define as ages 60 and older. The vast majority of
studies connecting unionization to health outcomes
focus on cross-sectional associations or longitudinal
associations bounded in short time periods.
Although valuable, we argue that such a focus likely
misses key dynamics by which unionization con-
tributes to health and well-being. Above and beyond
the point-in-time measure of union status, cumula-
tive unionization contributes holistic life course
information on divergent career experiences, imply-
ing potential mechanisms underlying the accumula-
tion of union coverage.
According to mechanisms of cumulative advan-
tage (Dannefer 2003), a person with consistent
union attachment over the work career might have
entered a unionized job in early adulthood, enabling
the attainment of future benefits, greater stability,
and higher overall career earnings. These accumu-
lated advantages may bring health benefits that are
also accumulated and extended until later in life
through the aforementioned mechanisms. In addi-
tion, our argument draws on recent stratification
research that demonstrates the significance and the
nonlinearities of outcomes such as earnings mea-
sured at the career level (Kim, Tamborini, and
Sakamoto 2015; Parolin and VanHeuvelen 2023;
Sakamoto, Tamborini, and Kim 2018). Our focus
also builds on similar recent studies on cumulative
career experience and health outcomes.
For example, using Health and Retirement
Study data, Donnelly (2022) finds that precarious
work during ages 50 to 65 predicted health and
mortality at age 65 onward, suggesting that repeated
exposure to decrements in job quality produces a
unique contribution to health outcomes in subse-
quent life stages. She draws on a stress and life
course perspective (Pearlin et al. 2005), which pre-
dicts that repeated exposure to stressful life events
will accumulate across the life course to negatively
impact health. Similarly, Wahrendorf et al. (2021)
find an association between retrospectively col-
lected information on negative labor market experi-
ences, such as unemployment, involuntary job loss,
and downward mobility, and health after the age of
50. Together, these lines of research motivate the
need to extend employment mechanisms beyond
narrow point-in-time associations.
We conceptualize repeated exposure to union
membership as a protective buffer against potential
negative health events. The benefits of unionization
involve immediate support to address negative
health events, reduction of workplace and job
search stress, and an infrastructure for individuals
to accumulate resources to successfully transition
out of the labor market at traditional retirement

Han et al.
165
ages. Insofar as union membership produces higher
earnings, greater job security, and more predictable
access to fringe benefits, it is reasonable to antici-
pate that the accumulation of these benefits will be
observable in health outcomes in older age. These
mechanisms should allow for (1) more contempora-
neously available resources to address negative
health events and (2) longer-term acquisition of
resources to better address living conditions and
health concerns at older ages. Moreover, insofar as
union membership provides job security and more
predictable pathways of advancement, union mem-
bership may act as a buffer against the accumula-
tion of stress across the life course, which has been
shown to negatively impact health (Donnelly 2022;
Pearlin et al. 2005).
Life Course Dynamics of
Cumulative Unionization
Although we first consider cumulative unionization,
or the total life course duration of union member-
ship, the life course timing of union exposure
reveals another temporal dimension that could help
explain the union–health associations. According to
the life course principle of timing, the developmen-
tal consequences of life experiences depend on
when they occur in one’s life (Elder, Johnson, and
Crosnoe 2003). The very meaning of the same life
event can change significantly at different develop-
mental stages. Life course scholars have given con-
siderable attention to the formative effects of life
experiences and environments at early stages on a
number of life outcomes, including psychological
orientations, socioeconomic attainment, and health.
Therefore, they often refer to adolescence and
early adulthood as “impressionable years” in human
development (Alwin and McCammon 2003).
Similarly, across occupational career stages, the
timing of a career experience like unionization
could have strong implications for health outcomes
in later life.
We assess unionization at different career stages
to determine whether older adult health is differen-
tially affected by the timing of union membership.
Two hypotheses are plausible. On the one hand,
health outcomes in older adulthood might be more
affected by contemporaneous or recent experiences
of unionization. Union membership may thus have
more immediate influence on health outcomes later
in the career, insofar as union membership provides
access to health insurance and higher pay and sig-
nals greater probability of employment in a higher
quality job. Alternatively, union membership may
be most consequential in the early years. Budd
(2010) shows that the large majority of workers
who have ever been unionized are union members
prior to the age of 30. According to cumulative
advantage mechanisms, this initial advantage of
early unionization might either be translated into
continued union membership or provide the oppor-
tunity to develop relevant work experience and pur-
sue more advantageous job opportunities, unionized
or not, that facilitate accumulation of health bene-
fits over the following career stages. Moreover, the
benefits of unionization, including higher pay, a
more stable career, and access to fringe benefits,
may be most acutely felt at early ages, when indi-
viduals are still working to establish their careers.
At later ages, as individuals enter more stable career
stages, they may be able to collect more diverse
health benefits from sources other than unions or
work in general.
Next, we consider the dynamic nature of physi-
cal health conditions in later life. The principle of
life-span development suggests that aging is a life-
long process, dependent on circumstances and
events throughout the life course (Elder et al. 2003).
We therefore focus on growth trajectories of health
outcomes and follow workers beyond the end of
their careers. To the extent that career mechanisms
influence older adulthood health, we anticipate that
these will decay the further a respondent moves
from their working ages because any effects of
career mechanisms will mix with more immediate
life course and health issues that arise in older
adulthood. Moreover, the life course principle of
time and place argues that the life course outcomes
of individuals are embedded in and shaped by the
historical times and places they experience over
their lifetime (Elder et al. 2003). The diverse his-
torical circumstances of individuals from different
birth cohorts may matter significantly for their
career decisions, opportunities, and experiences.
Specifically, we are able to capture respondents
who entered the labor market during the golden age
of unionization (Cowie 2010) and the era of rapid
union decline, led by the Carter and Reagan admin-
istrations, which diminished the support of federal
institutions for labor (Jacobs and Myers 2014;
Rosenfeld 2014). It is reasonable to suppose that
the latter group would not be as protected by a
weakened labor movement. Guided by the two
additional life course principles of life-span devel-
opment and of time and space, we hypothesize that
the effects of cumulative unionization on health
vary across age in later life and across birth cohorts
living through shifting labor market contexts.

166
Journal of Health and Social Behavior 65(2)
Subgroup Advantage
We anticipate that union effects will operate differ-
ently across demographic subgroups. We consider
three key sources of subgroup heterogeneity: educa-
tional attainment, gender, and race. Unions have
historically been most consequential for raising
wages in the middle and lower portions of the earn-
ings distribution (Firpo et al. 2009, 2018). Union
protection has thus been a significant source of eco-
nomic protection and stability for a working class
that often lacks alternative mechanisms of social
closure to produce economic protection, most nota-
bly a college degree (Parolin and VanHeuvelen
2023). Particularly for the cohorts we study, which
have union membership more firmly rooted in blue
collar work (Cowie 2010), we anticipate larger
effects among those without a college degree.
We develop contradictory expectations for gen-
der and race. On the one hand, union protection
might be weaker and less consistent among margin-
alized groups. Unions have a fraught history regard-
ing discrimination and segregation along race and
gender lines (Frymer 2011; Lichtenstein 2012).
Racial integration often occurred in spite of union
wishes and under threat of litigation. Although
some unions moved to organize racial minorities,
this was not a uniform outcome (Frymer 2011).
Similarly, women often faced exclusion, discrimi-
nation, and harassment from unions in early wom-
en’s organizing efforts (Cowie 2010). Although
many dimensions of union benefits, such as the
wage premium, have similar magnitudes across
groups (Rosenfeld and Kleykamp 2012; Western
and Rosenfeld 2011), mistreatment or opportunity
hoarding among more privileged groups might
have consequences that counteract or undermine
any economic benefit.
Although we consider this argument more
likely, one could reasonably draw alternative expec-
tations. Labor unions were not the sole source of
discrimination and unfair discretion faced by
women and racial minorities among the cohorts we
study. Indeed, compared to other systems of dis-
crimination and mistreatment, unions may have
provided a more robust system of equalization
compared to other options faced by women and
people of color (Lichtenstein 2012). For example,
Wilson, Roscigno, and Huffman (2015) found that
states that enabled the public sector to operate with
more market-driven discretion resulted in greater
racial inequalities. Similarly, Biasi and Sarsons
(2022) found that changes to public sector bargain-
ing in Wisconsin, which weakened formal union
structures and increased opportunity for discretion,
resulted in substantially higher gender inequalities
among public sector teachers. Therefore, despite
the real fraught histories of discrimination and
exclusion, the equalizing effects of unions may
have overall positive effects for women and racial
minorities.
The Present Study
We anticipate that cumulative unionization will
affect physical health outcomes for older adults, the
group that would reflect the consequences of career-
long processes, with low rates of unionization pro-
ducing health disadvantages among older adults that
have hitherto gone unobserved. We assess the life
course dynamics of unionization in terms of (1) the
respondent’s union membership at different career
stages, (2) the extent to which cumulative unioniza-
tion effects extend into older ages, and (3) cohort
variation. We also consider demographic heteroge-
neity in terms of more and less advantaged sub-
groups based on educational attainment, race, and
sex. Our argument leads to the following hypothe-
ses, which we examine next.
Hypothesis 1: Respondents who spent more of
their careers as union members have better phys-
ical health in older adulthood.
Hypothesis 2: Cumulative unionization is more
consequential for physical health in older adult-
hood than contemporaneous union membership.
Hypothesis 3a: Hypothesis 1 associations are
primarily the result of early career unionization.
Hypothesis 3b: Hypothesis 1 associations are
primarily the result of late career unionization.
Hypothesis 4: Hypothesis 1 associations decline
at older ages.
Hypothesis 5: Hypothesis 1 associations are
more concentrated among earlier birth cohorts.
Hypothesis 6a: Hypothesis 1 associations are
concentrated among noncollege workers.
Hypothesis 6b: Hypothesis 1 associations are
concentrated among men.1
Hypothesis 6c: Hypothesis 1 associations are
concentrated among White individuals.
Data And Methods
Data
We used the Panel Study of Income Dynamics
(PSID), the longest running U.S. longitudinal sur-
vey, between 1970 and 2019. The PSID began with

Han et al.
167
a nationally representative sample of about 5,000
families and 18,000 individuals. Information from
these individuals and their descendants was col-
lected annually from 1968 to 1995 and biennially
thereafter. The PSID was ideal for our purposes. The
long-running administration of the PSID allows for
the prospective tracking of individual employment
characteristics, avoiding inaccuracies produced by
retrospective accounting of one’s career. Moreover,
the PSID began collecting extensive health informa-
tion of individuals in the 1990s. Main data came
from the WZB-PSID file, which incorporates infor-
mation from the Cross-National Equivalent File
(Brady and Kohler 2022).
We constructed a sample based on the following
conditions: respondents have been observed (1) a
minimum of 15 times between ages 18 and 60,2 (2)
a minimum of once prior to age 30, (3) a minimum
of once at or beyond age 60, and (4) employed at
least once between ages 18 and 60. The combina-
tion of these characteristics ensured that we cov-
ered respondents over a wide swath of their careers
to collect a sufficient representation of their level of
unionization.
Our sample of older adults was made up by
2,735 respondents in the PSID . We constructed a
sample of all available person-years of these 2,735
respondents when they were ages 60 or older,
resulting in a final sample of 11,354 person-years.
The PSID’s low attrition, between 92% and 98%,
suggested that unequal attrition plays a minimal
role in results (Schoeni et al. 2013).
Dependent Variables
We focused on three key dependent variables mea-
sured when respondents were ages 60 and older.
First, self-rated health was a five-category indicator
ranging from poor (1) to excellent (5). Second was
the number of reported current or former chronic
conditions. Following the logic used by Brady et al.
(2022), we focused on life-threatening conditions:
high blood pressure, cancer, diabetes, heart attack/
disease, lung disease, and stroke.3 Third, we con-
structed a scale of seven activities of daily living
(ADLs) that represent functional limitations:
whether the respondent has difficulty bathing,
dressing, eating, getting in and out of a bed/chair,
going outdoors, using the toilet, and walking.
Independent Variables
Our key variable was cumulative unionization, fol-
lowing Parolin and VanHeuvelen (2023). It was
based on prospective measurements of a respon-
dent’s employment and union membership statuses
between ages 18 and 60. We used the ratio of waves
that a respondent is a union member over waves
employed. For our respondents, cumulative union-
ization was measured as a time invariant.
Cumulative unionization has two noteworthy val-
ues: 0% and 100%. However, the health benefits of
cumulative unionization from 0% to 100% might not
be linearly additive. Some respondents who were
never unionized may have had a stable trajectory in a
nonunionized and prestigious occupation, such as
management, or may have unobserved advantages,
such as network support. Thus, they might be more
advantaged with respect to socioeconomic and health
benefits from work than someone who spent a small
proportion of their career in a union, a proportion
that might reflect employment instability. We there-
fore included a squared term for cumulative union-
ization and pay special attention to career churn that
may explain any health differences for those between
0% and 100% unionized. Appendix Tables 2a to 2c
in the online version of the article show a variety of
alternative specifications of our cumulative union-
ization measure. Although main results were sup-
ported with only a linear term, the quadratic fit
introduces some complexity that requires important
caveats against a simpler argument. We preferred to
include this complexity because it maps more closely
to the descriptive nature of our data (supplemental
analyses showed that nonlinear functional forms
improve model fit) and the complexity introduced
should motivate future research on the nature of
cumulative unionization.
We took two additional steps in the computation
of our cumulative unionization measure. First, fol-
lowing Parolin and VanHeuvelen (2023), we
imputed biennially skipped years using the mean of
two adjacent nonmissing waves for employment
and union membership.
Second, Parolin and VanHeuvelen (2023) restrict
their sample to men because of missing union infor-
mation for PSID spouses in 1970 to 1975 and 1977 to
1978 (almost entirely female in these years). We
imputed spouse membership using probabilities com-
puted from 1976 and 1979 waves that include spouse
union membership. We first estimated a logit model
predicting union membership among employed
spouses in these two waves using two-digit industry
and occupations, education, race, and state. We then
computed predicted probabilities of union member-
ship among employed spouses in 1970 to 1975 and
1977 to 1978. Nonemployed spouses received zero
values for both employment status and union

168
Journal of Health and Social Behavior 65(2)
membership. Main results without imputation are
included in the Appendix in the online version of the
article.
In addition to overall cumulative unionization
between ages 18 and 60, we constructed measures
for specific age intervals: 18 to 30, 31 to 40, 41 to
50, and 51 to 60. Each measure represented the per-
centage of employed years in the age interval in
which a respondent was covered by or a member of
a union.
To ensure that cumulative measures did not
proxy for contemporary union membership, we
included a time-varying binary indicator for current
union membership for each observation at ages 60
and older. In the Appendix in the online version of
the article, we show replicated results controlling
for year-specific union membership information
between ages 25 and 54.
Controls
We adjusted for controls, both time varying and
invariant, that may confound the association
between unionization and health.
Demographic controls included age, year of
birth, sex, race (White, Black, other), and four-cate-
gory census region of residence (Northeast, South,
Midwest, West). We included two measures of mar-
ital status: total years married and whether the
respondent is married in a particular wave.
We included an indicator of whether a respon-
dent had a college degree by the age of 40.4
We included three health-related measures: the
respondent’s retrospective self-assessment of gen-
eral health at ages 0 to 16,5 smoking status at ages
60 to 79, and the proportion of observed waves that
a respondent had health insurance from 1999
onward, the first year health insurance information
is consistently available.
We included eight measures of contemporary
and career employment. First, we included mea-
sures of a respondent’s employment status at ages
60+: working, retired, unemployed, or not in the
labor force. Second, we included the respondent’s
ages 60+ posttax and transfer total household
income, divided by the square root of the number of
household members. Third, we constructed 19
industry
categories
following
Western
and
Rosenfeld (2011) and assigned respondents the
modal category we observe at ages 18 to 60.
Appendix materials in the online version of the arti-
cle include replication with percentage waves in
industry categories. Fourth, we constructed 12 large
occupation categories and assigned the modal
observed category from ages 18 to 60. Fifth, we
assigned the respondent’s modal region of resi-
dence from ages 18 to 60. Sixth, we included a
measure of total years employed between ages 18
and 60 (percentage employed yielded the same
results). Seventh, we included the percentage of
years that a respondent was self-employed. Eighth,
we combined information from occupation and
industry, harmonized to 1990 Census Bureau clas-
sification schemes. We made all possible combina-
tions of the 200 industry categories and 275
occupation categories observed in the PSID and
counted the number of unique combinations each
respondent held between ages 18 and 60. We used
this measure to proxy labor market position
changes. Appendix materials in the online version
of the article include results with and without these
career controls.
Table 1 includes descriptive statistics for our
main analytic sample.
We observed that the average time in a union
during one’s career was around 16%. However, this
mixed those who were ever and never union mem-
bers. About 43% of the sample was never in a union
during the period observed, whereas 6% of respon-
dents age 60 or older were currently unionized.
Nearly 30% of the observed career was unionized
among the 57% who were ever union members.
Regarding the timing of unionization, we observed
slightly higher rates of unionization at ages 41 to 50
and the lowest at ages 18 to 30, but the magnitude
of differences was not great, with means varying
from 14% to 17%.6 We saw that the restrictions to
collect both contemporaneous career and older
adulthood health resulted in a sample of individuals
ages 60 to 79 born between years 1940 and 1959,
with health outcomes collected in the 2001 to 2019
survey waves.
Methods
The primary goal of the current article is to assess
the contribution of time-invariant cumulative union-
ization between ages 18 and 60 to time-varying
older adult health outcomes from ages 60 and
onward. Therefore, we used a series of growth curve
models to predict older adult health using cumula-
tive career information. We used a general setup as
follows:
health
age
cunion
cunion
it
age
it
cunion
i
cunion
i
=
+
+
+
+
+
β
β
β
β
0
2
2
xββ
it
i
age
i
β
γ
µ
β
γ
µ
0
00
0
10
1
=
+
=
+
.

Han et al.
169
Table 1.  Descriptive Statistics of Sample for Main Analysis.
Variable
Mean
Standard Deviation
Minimum
Maximum
Dependent variables
  Self-rated health
3.245
1.054
1
5
  Functional limitations scale
.401
1.081
0
7
  Total number of life-threatening
chronic health conditions
1.151
1.077
0
6
Unionization
  Cumulative unionization 18–60a
.163
.260
0
1
    Was never in a union
.431
0
1
    Cumulative unionization for
respondents ever in a unionb
.286
.289
.005
1
  Current union memberc
.059
0
1
  Cumulative unionization 18–30
.137
.243
0
1
  Cumulative unionization 31–40
.165
.306
0
1
  Cumulative unionization 41–50
.174
.335
0
1
  Cumulative unionization 51–60
.167
.337
0
1
Selection of key time-varying
independent variables
  Age
65.124
4.290
60
79
  Year of birth
1948.433
4.966
1940
1959
  Survey year
2013.558
4.627
2001
2019
  Employment status
    Currently working
.453
0
1
    Unemployed
.019
0
1
    Retired
.415
0
1
    Other
.113
0
1
  Total posttax and transfer-equivalized
income, 2021 dollars
50,416.64
55,353.41
0
1,010,548
  Years employed ages 18–60
30.460
8.605
1
43
  Percentage years self-employed ages
18–60
.090
.179
0
1
Selection of key time-invariant
independent variables
  Female
.547
0
1
  Has a college degree by age 40
.411
0
1
  Respondent race
    White
.669
0
1
    Black
.286
0
1
    Other
.045
0
1
Data Source: 1970 to 2019 Panel Study of Income Dynamics.
Note: Sample criteria for the 2,729 individuals with 11,095 person-years includes (1) 15 observations between ages 18
and 60, (2) at least one observation ages 60+, (3) minimum one observation age 30 or younger, and (4) minimum one
year observed employed.
aCumulative unionization is measured as the percentage of observed employed waves between ages 18 and 60 that a
respondent is a union member. Cumulative unionization measures are time-invariant, and so summary statistics are
collected from persons, not person-years.
bVery low values originate from imputation measures of spouses prior to 1979.
cRefers to whether respondent age 60 and older is a union member. Respondents not currently employed are coded
as 0.

170
Journal of Health and Social Behavior 65(2)
We included a random coefficient for respon-
dent age. When we estimated models to life course
timing, we replaced cumulative unionization with
four measurements of cumulative unionization,
measured in specific age intervals:

β
β
β
β
cu
i
cu
i
cu
i
cu
cu
cu
cu
cu
1830
18302
2
3140
31402
1830
1830
3140
3
+
+
+
140
4150
4150
5160
2
4150
41502
2
5160
5
i
cu
i
cu
i
cu
i
cu
cu
cu
cu
+
+
+
+
β
β
β
β
1602
2
5160
cu
i .

We first estimated models with age-specific
cumulative unionization measure between ages 50
and 60 and then added measures of earlier ages sub-
sequentially to determine the effect of a particular
era. To examine age and cohort effects, we inter-
acted our main and squared cumulative unioniza-
tion terms first with respondent age, 60 to 79, and
then with respondent birth cohort, 1940 to 1959.
When we examined subgroup heterogeneity, we
estimated growth curve models separately among
groups with and without a college degree, men and
women, and White and non-White individuals.
We used a growth curve model for three main
reasons. The first was to align with methodologies
used in recent studies of cumulative employment
on health trajectories in older adulthood (Donnelly
2022). The second was to streamline across main
and age trajectory results. Third, our growth curve
model provided several advantages for our data
structure: It handled repeated person observations,
adjusted for unobserved person-level heterogeneity
in aging, and provided a general modeling frame-
work to include both time-varying and time-invari-
ant measures. An extended discussion of the growth
curve models is included in the Appendix in the
online version of the article.
Results
Figure 1 shows local polynomial smoothed plots of
the simple bivariate association between cumulative
unionization and our three health outcomes—self-
rated health, functional limitations, and chronic
conditions—for the total sample and separately by
college degree attainment.
Several descriptive trends are notable. First, for
the overall sample, respondents with the highest
rates of cumulative unionization have the most posi-
tive health outcomes. Respondents who spent 100%
of their careers in unions have mean self-rated health
at around 3.5 compared to around 3.1 for those
spending 40% of their careers in unions and around
3.3 for those who were never unionized. Similarly,
always unionized respondents have functional
Figure 1.  Bivariate Associations between Older Adult Health Outcomes and Cumulative Unionization
Data Source: 1970 to 2019 Panel Study of Income Dynamics.
Note: Graphs depict local polynomial smoothed fits between health outcomes—self-rated health, functional limitation
scale, and the number of chronic health conditions—against the percentage of total observed employed waves
unionized between ages 18 and 60.

Han et al.
171
limitation rates of around .25 compared to between
.40 and .55 for those between 0% and 50% of their
career unionized. Always unionized respondents
similarly have around .1 to .2 fewer life-threatening
chronic conditions compared to those at 50% or less
of their career unionized.
We see significant variation of trends by educa-
tional attainment. Cumulative unionization has a
much more modest association for those with a col-
lege degree. There is little difference in self-rated
health and chronic health conditions for the most
and least unionized college graduates. Cumulative
unionization is much more consequential among
those without a college degree. Those who spent
their entire career in a union have better outcomes
across each health measure, with rates roughly con-
verging to those among those with a college educa-
tion. These descriptive findings help motivate the
examination of unionization as a career process but
also suggest the presence of significant heterogene-
ity across key subgroups in the data.
Growth Curve Models Predicting Older
Age Health Outcomes
We next turn to multilevel growth curve regression
models predicting our three health outcomes using
cumulative unionization measures and controls. We
first estimate simple associations between union
membership at ages 60+ and cumulative unioniza-
tion with our health outcomes. We then add controls
to our regression models. Results are shown in
Table 2.
Across each of our three outcomes, we observe
a similar pattern of results. Among older adults,
union membership measured at the current wave
does not predict health outcomes when controls are
added to regression models. However, cumulative
unionization operates in a similar way across each
outcome. We observe a curvilinear pattern with
more positive associations for more unionized
careers. These patterns of association for cumula-
tive unionization remain with the inclusion of both
controls and contemporaneous union membership.
Figure 2 visualizes the predicted values by cumula-
tive unionization from Models 5, 10, and 15.
Figure 2 shows a similar curvilinear pattern
across our three health outcomes. Older adults who
spent the entirety of their careers in unions have bet-
ter self-rated health, fewer functional limitations,
and fewer chronic conditions. The worst health out-
comes are found among those who spent approxi-
mately 30% of their observed waves in a union. Yet
respondents with fully unionized careers also have
better health outcomes than those who were never in
a union, with .206 higher self-rated health (p < .05),
.17 fewer functional limitations (p < .10), and .14
fewer life-threatening chronic conditions (p = .21).
Notably, these results adjust for industry, occupa-
tion, and total number of industry–occupation cate-
gories held during a respondent’s career (for
comparisons excluding career measures, see the
Appendix in the online version of the article). Effect
sizes are relatively large. Maximum differences in
predicted values range from .22 SD to .31 SD of the
specific health outcome. The overall finding is one
in which a fully unionized career corresponds with
beneficial older adulthood health.
Life Course Timing of Unionization
We next examine life course timing of cumulative
unionization. To what extent is overall cumulative
unionization’s influence dependent on the particular
career timing of union membership? To what extent
are cumulative unionization effects concentrated
among cohorts who spent a longer period of their
careers in a labor market with a strong labor pres-
ence? And to what extent does the association of
cumulative unionization and health outcomes decay
as individuals age into older adulthood?
Table 3 replicates results incorporating four age-
specific cumulative unionization measures: the per-
centage of observed waves where the respondent is
unionized between ages 18 and 30, 31 and 40, 41
and 50, and 51 and 60, in place of the career total
measure. We first include the 51 to 60 measure and
then sequentially add younger age measures. This
modeling setup assesses the extent to which con-
temporary older adulthood health reflects recent
union membership or whether earlier exposure to
union membership contributes to older adulthood
health outcomes. Descriptive information about
interage correlations are included in the Appendix
in the online version of the article.
Across each health outcome, we find a similar
general pattern: Unionization at earlier ages is more
predictive of older adulthood health than unioniza-
tion at later ages. Unionization at ages 18 to 30 is
significantly associated with more positive self-
rated health and fewer chronic conditions, and
unionization in ages 31 to 40 is significantly associ-
ated with fewer functional limitations. We do find
significant associations for ages 41 to 50 for self-
rated health, but the most consistent pattern across
health outcomes is found in earlier career stages;
any associations for older ages (e.g., Models 3, 7)
are removed when younger aged union membership

172
Journal of Health and Social Behavior 65(2)
is included. As found by Budd (2010), unionization
rates by age 30 are highly predictive of unionization
prospects for one’s entire career. And Parolin and
VanHeuvelen (2023) show that career unionization
produces disproportionately high lifetime earnings
partially due to growth in union wage premiums. It
is plausible that developing higher earnings and
higher employment stability in early career and
midcareer should produce significant downstream
consequences for later career earnings and employ-
ment and, subsequently, improved health outcomes.
Notably, our results would not be found if we used
data that measured the effect of only later career
unionization on older adulthood health outcomes.
Age Timing of Health Outcomes
To what extent do cumulative unionization associa-
tions hold constant across the age range in our sam-
ple of older adults, ages 60 to 79? We address this
question by interacting both cumulative unioniza-
tion and its squared term with age. Predicted values
from these models are shown in Figure 3.
Regarding self-rated health, we see a clear
decline of the protective effects of cumulative
unionization as respondents move from ages 60 to
79. For example, among respondents who were
union members in every observed wave of their
career, self-rated health decreases from about 3.7 at
age 60 to about 3.25 at age 70 and about 2.8 at age
Table 2.  Growth Curve Models Predicting Older Age Health.
Self-Rated Health

(1)
(2)
(3)
(4)
(5)
Current union member
.1183**
(.038)
–.0237
(.039)
–.0179
(.040)
Cumulative unionization
–.7896**
(.244)
–.6929**
(.224)
–.6810**
(.226)
Cumulative unionization squared
1.1131***
(.310)
.8929**
(.278)
.8874**
(.278)
N
11,405
11,354
11,010
11,005
11,005

Functional Limitations

(6)
(7)
(8)
(9)
(10)
Current union member
–.2186***
(.042)
–.0230
(.044)
–.0331
(.045)
Cumulative unionization
.7518**
(.243)
.6257**
(.234)
.6497**
(.236)
Cumulative unionization squared
–1.1036***
(.308)
–.8052**
(.290)
–.8158**
(.290)
N
11,213
11,162
10,826
10,821
10,821

Life-Threatening Chronic Conditions

(11)
(12)
(13)
(14)
(15)
Current union member
–.1189***
(.034)
.0304
(.036)
.0263
(.037)
Cumulative unionization
.6355*
(.251)
.5320*
(.252)
.5137*
(.254)
Cumulative unionization squared
–.8591**
(.318)
–.6600*
(.313)
–.6520*
(.313)
N
11,369
11,318
10,971
10,966
10,966
Controls?
X
X
X
Data Source: 1970 to 2019 Panel Study of Income Dynamics.
Note: Standard errors are in parentheses. Controls are listed in “Data and Methods” section. Total N = 11,405.
*p < .05. **p < .01. ***p < .001 (two-tailed tests).

Han et al.
173
79. By age 79, we do not observe any significant
association.
Regarding functional limitations and chronic
conditions, we highlight an overall conclusion and
a caveat. The main effects of cumulative unioniza-
tion remain significant for both functional limita-
tions and chronic conditions, whereas interaction
terms are nonsignificant. These findings suggest no
change in cumulative unionization’s effect over
time as a respondent ages. At the same time, the lin-
ear combination of the main and interaction terms,
for cumulative unionization’s main and squared
coefficients, show insignificant associations with
functional limitations and chronic conditions by the
time respondents reach age 79. Although these do
not show up in the significance of interaction coef-
ficients, they suggest that the effect of cumulative
unionization becomes, at minimum, surrounded by
considerable uncertainty at older ages.
In total, we can conclude that although the more
lasting effects of cumulative unionization on physi-
cal health are uncertain, there is at minimum a
decade of older adulthood in which the protective
effects of career unionization extend.
Birth Cohort Timing
We next consider whether cumulative unionization
associations remain consistent across the 19 birth
cohorts in our sample. To do so, we interact year of
birth with our cumulative unionization measure. We
find overall significance of the interactions for self-
rated health and functional limitations: joint signifi-
cance Wald test, χ2(2) = 5.41 and 18.82, p < .10 and
p < .001, respectively. Figure 4 plots the predicted
effects by birth cohort. We observe that the inverted
U shape from the main results is most pronounced
among the earliest birth cohorts in our sample, or
those born in 1940. The association flattens out
across birth cohorts, until negligible associations are
found among those born in 1959.
Subgroup Heterogeneity
To what extent are results disproportionately con-
centrated among education, sex, and racial groups?
We reestimate growth curve regression models sep-
arately by subgroup and present results in Table 4.
We observe health effects of cumulative union-
ization to be primarily concentrated among indi-
viduals without college degrees and among men.
For education, the curvilinear fit for cumulative
unionization is found across all three health out-
comes for noncollege workers. Unionization has no
significant association with either physical health
or functional limitations for college-educated work-
ers. For sex, although the curvilinear fit is jointly
significant for all three outcomes for men and over-
all insignificant for women, the discrete change
between men and women is insignificant across all
Figure 2.  Predicted Health Outcomes by Cumulative Unionization.
Data Source: 1970 to 2019 Panel Study of Income Dynamics.
Note: Predicted values calculated from Models 5, 10, and 15 of Table 2. Shaded areas represent 95% confidence
intervals. SRH = self-rated health.

174
Table 3.  Age-Specific Cumulative Unionization Measures.
Self-Rated Health
Functional Limitations
Life-Threatening Chronic Conditions

(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
Cumulative unionization
  Age 51–60
–.1909
(.254)
–.2091
(.271)
–.2394
(.272)
–.2635
(.276)
–.0918
(.242)
–.0033
(.251)
.0321
(.254)
.1002
(.258)
.2847
(.283)
.2684
(.302)
.3122
(.305)
03240
(.310)
  Age 51–60 squared
.2126
(.267)
.1985
(.271)
.2309
(.273)
.2253
(.276)
.0635
(.254)
.0314
(.252)
.0003
(.255)
–.0374
(.258)
–.3521
(.297)
–.3869
(.302)
–.4446
(.306)
–.4475
(.311)
  Age 41–50
–.6017*
(.256)
–.5469*
(.261)
–.4712
(.265)
.4644
(.238)
.3715
(.243)
.3001
(.247)
.3248
(.284)
.3110
(.291)
.3209
(.297)
  Age 41–50 squared
.7148**
(.257)
.6649*
(.261)
.5917*
(.265)
–.5844*
(.238)
–.5048*
(.243)
–.4491
(.247)
–.2767
(.285)
–.2824
(.292)
–.2785
(.297)
  Age 31–40
–.3474
(.236)
–.1811
(.245)
.5438*
(.220)
.4999*
(.228)
.1027
(.264)
.0148
(.275)
  Age 31–40 squared
.4005
(.253)
.2802
(.257)
–.6180**
(.236)
–.5701*
(.239)
–.0889
(.283)
–.0896
(.288)
  Age 18–30
–.5492*
(.233)
.1782
(.216)
.6597*
(.261)
  Age 18–30 squared
.5867*
(.269)
–.2811
(.250)
–.6594*
(.302)
Data Source: 1970 to 2019 Panel Study of Income Dynamics.
Note: Standard errors are in parentheses. Models include all independent variables discussed in the “Data and Methods” section. Sample size in full models. Self-rated health n =
9,562; functional limitations n = 9,391; chronic health conditions n = 9,533.
+p < .10. *p < .05. **p < .01.

Han et al.
175
levels of cumulative unionization, meaning no
straightforward conclusion for gender can be
drawn. For race, we observe cumulative unioniza-
tion to operate similarly across White and non-
White groups. Cumulative unionization is jointly
significant in all cases except chronic conditions for
White respondents.
To better illustrate the subgroup heterogeneity
of cumulative unionization, Figure 5 presents pre-
dicted values of self-rated health from the six
Figure 3.  Predicted Health Outcomes, by Cumulative Unionization by Age.
Data Source: 1970 to 2019 Panel Study of Income Dynamics.
Note: Results computed from full analytic sample using growth curve models including all control variables discussed in
the “Data and Methods” section. Cumulative unionization and its squared term both interacted with age.
Figure 4.  Predicted Health Outcomes by Cumulative Unionization across Birth Cohorts.
Data Source: 1970 to 2019 Panel Study of Income Dynamics.
Note: Results are computed from the full analytic sample using growth curve models including all control variables
discussed in the “Data and Methods” section. Cumulative unionization and its squared term both interacted with
birth cohort, which ranges from 1940 to 1959. Joint significance of interactions (main and squared term) are
significant for self-rated health, χ2(2) = 11.96, p < .01, and functional limitations, χ2(2) = 19.73, p < .001, but not chronic
conditions, χ2(2) = .78 p = .68.

176
Journal of Health and Social Behavior 65(2)
Table 4.  Subgroup Analysis of Older Adulthood Health by Cumulative Unionization.
Education
Gender
Race

Noncollege
College
Men
Women
White
Non-White
Self-Rated Health
(1)
(2)
(3)
(4)
(5)
(6)
Cumulative unionization
–.7871**
(.286)
–.4022
(.366)
–.6584*
(.317)
–.5211
(.324)
–.7603**
(.276)
–.7644*
(.377)
Cumulative unionization
squared
1.0653**
(.347)
.4702
(.463)
.9340*
(.375)
.5636
(.427)
.9598**
(.341)
1.0852*
(.467)
Current union member
.0132
(.054)
–.0559
(.058)
–.0374
(.057)
.0026
(.056)
.0038
(.048)
–.0528
(.070)
Functional Limitations
(7)
(8)
(9)
(10)
(11)
(12)
Cumulative unionization
.8497**
(.298)
.3053
(.384)
.5051
(.330)
.6626+
(.338)
.8097**
(.290)
.2352
(.393)
Cumulative unionization
squared
–.9961**
(.361)
–.4913
(.484)
–.7570+
(.389)
–.7261
(.444)
–.9228**
(.358)
–.5260
(.486)
Current union member
–.0573
(.062)
–.0134
(.067)
.0403
(.064)
–.1083+
(.063)
–.0231
(.055)
–.0291
(.079)
Chronic Conditions
(13)
(14)
(15)
(16)
(17)
(18)
Cumulative unionization
.7854*
(.320)
.0260
(.410)
.5975+
(.356)
.4282
(.363)
.3754
(.311)
.6955+
(.418)
Cumulative unionization
squared
–.8906*
(.389)
–.1653
(.519)
–.6124
(.420)
–.7469
(.480)
–.4578
(.385)
–.9338+
(.520)
Current union member
–.0419
(.050)
.0955+
(.053)
–.0009
(.052)
.0644
(.051)
.0537
(.044)
–.0034
(.064)
Data Source: 1970 to 2019 Panel Study of Income Dynamics.
Note: Standard are errors in parentheses. All regression models include controls discussed in the “Data and Methods” section. Sample
sizes: Model 1 n = 6,394; Model 2 n = 4,642; Model 3 n = 5,044; Model 4 n = 5,992; Model 5 n = 8,056; Model 6 n = 2,980; Model 7 n =
6,319; Model 8 n = 4,530; Model 9 n = 4,949; Model 10 n = 5,900; Model 11 n = 7,890; Model 12 n = 2,959; Model 13 n = 6,366; Model
14 n = 4,627; Model 15 n = 5,025; Model 16 n = 5,968; Model 17 n = 8,029; Model 18 n = 2,964.
+p < .10. *p < .05. **p < .01 (two-tailed test).
subgroup regression models (top row) and group
differences at cumulative unionization levels (bot-
tom row). Beyond the conclusions drawn from
Table 4, we see that health outcomes for more vul-
nerable social categories, noncollege and non-
White individuals, converge to the more positive
health levels of the more advantaged groups, col-
lege and White individuals, at the highest levels of
cumulative unionization. We can also observe that
although the positive effect of cumulative unioniza-
tion is present for both White and non-White
groups, the magnitude of the effect of high cumula-
tive unionization is much greater for non-White
individuals in the sample.
No single and simple conclusion can be drawn
regarding unionization’s operation across privi-
leged social categories, but a few general observa-
tions can be made. We see that a unionized career
allows for certain less privileged groups, such as
workers without a college degree and non-White
workers, to attain older adulthood health outcomes
more typically found in more advantaged popula-
tions. Little can be confidently concluded from our
analyses of men and women, aside from the possi-
bility that the health consequences may be some-
what more concentrated among men than women.
Considered as a whole, cumulative unionization
represents a distinct input into the production of
older age health disparities that neither fully reflect
nor fully ameliorate disparities rooted in heteroge-
neity of social categories defined by relative advan-
tage and disadvantage.
Discussion
Labor union decline has been widely consequential
for middle and lower paid workers, resulting in
worsened job security, reduced fringe benefits,

Han et al.
177
lower earnings, social disintegration, and height-
ened inequality (Cowie 2010; Fortin et  al. 2021;
Rosenfeld 2014; Western and Rosenfeld 2011), all
consequential for health outcomes (Hagedorn et al.
2016; Leigh and Chakalov 2021; Reynolds and
Brady 2012). The present study examines how
union benefits that accrue over an entire career pre-
dict physical health among older adults. Using 39
waves of PSID data to measure both cumulative
union membership during a respondent’s career
between ages 18 and 60 and physical health at ages
60 to 79, we draw three main sets of conclusions.
First, we find that the accumulated history of
unionization contributes to older adulthood health.
Among older adults, those who spent the entirety of
their career in unions have better self-rated health,
fewer functional limitations, and fewer life-
threatening chronic conditions than those who were
partially or never union members.
Why would the health consequences of union
membership operate at the career level for older
adults? Insofar as union membership provides mate-
rial benefits to workers who may otherwise have
lower economic protection, unionized workers
should have improved capacity to pursue better
health outcomes. Moreover, insofar as union mem-
bership improves local working conditions, job secu-
rity, and fringe benefits, union membership should
provide a buffer to stressful employment events that
might accumulate to produce negative chronic health
conditions. These mechanisms imply unionization
benefits that rest on predictability and security over
long stretches of time, which contemporaneous mea-
surements of health and unionization may not detect.
These mechanisms admittedly remain speculative,
needing future empirical testing.
Second, life course dynamics produce heteroge-
neous effects. Union membership in the early career
is more predictive of older age health than member-
ship at the later stage of one’s career, potentially
due to the critical role of early career stage in real-
izing union benefits. As workers enter more stable
career stages, health benefits from sources other
than a union might emerge. Moreover, early union
experience might facilitate positive selection into
unionized jobs and related benefits in later career
stages. Yet our cumulative measures within age
intervals might not capture variations in point-in-
time health benefits of union status at each age;
such variability should be tested in future research.
Figure 5.  Predicted Self-Rated Health by Cumulative Unionization, across Education, Gender, and
Racial Subgroups.
Data Source: 1970 to 2019 Panel Study of Income Dynamics.
Note: Results are computed from the full analytic sample using growth curve models including all control variables
discussed in the “Data and Methods” section. Predicted values are collected from six separate growth curve models
estimated within each subgroup. Bottom panel shows group marginal effects with 95% confidence intervals.

178
Journal of Health and Social Behavior 65(2)
Across age in later life, we find that cumulative
unionization effects decline in older ages of older
adulthood. As physical health continues to change
among adults at the older ages, it is plausible to
expect that career mechanisms would decline in
their influence.
Across birth cohorts, we find the associations
more clearly present in the earliest cohorts of our
sample, suggesting that cumulative unionization
interacts with the social context in which our
respondents came of age. It is sensible to observe a
decline in the influence of cumulative unionization
among more recent cohorts. Our earlier cohorts,
who entered the labor market during the peak of
union power, experienced the strongest effects of
unionization, whereas those entering the labor mar-
ket during the sharp decline of union membership,
power, and federal support enjoyed much weaker
longer-term benefits (Cowie 2010; Rosenfeld
2014). Previous studies show a decline in labor’s
ability to control wage setting in the private sector
in the wake of the Reagan administration’s policy
changes (Jacobs and Myers 2014) and a decline of
strike efficacy (Rosenfeld 2006). Results here sug-
gest a weakening of the health consequences as
well. This variation suggests, unsurprisingly, that
union effects vary depending on labor market insti-
tutional context.
Third, we find significant heterogeneity across
subgroups. Our findings are most pronounced
among those without a college degree and generally
larger for non-White individuals. Insofar as associ-
ations vary by gender, they are more pronounced
among men, although the strength of this contrast is
weak. Union power was most firmly rooted in
working-class men among the cohorts examined in
this study (Cowie 2010; Lichtenstein 2012), and so
it is unsurprising to find these groups to be the pri-
mary beneficiaries. As with wages and employment
security, unionization provides a source of health
protection for those with lower levels of education.
Although unions were resistant to racial integration
(Frymer 2011), Black workers quickly unionized to
gain protection against widespread risks of labor
market discrimination (Rosenfeld and Kleykamp
2012). Cumulative unionization thus provides a dis-
tinct mechanism for older age health disparities
rather than simply reinforcing or ameliorating those
of other group differences rooted in systems of
advantage and disadvantage.
Our study is the first to identify unionization as a
career-level mechanism producing health disparities
in older adulthood. Until recently, no high-quality
longitudinal data existed that allowed for the track-
ing of individuals over the entirety of their careers
and into older adulthood ages. Our study clearly
illustrates the longer-term consequences of union
membership for many individuals who would other-
wise face high risk of low pay and job insecurity. The
long-term dynamics of career attainment and oppor-
tunity will be of greater social consequence as a
larger share of the American population enters older
adulthood.
Although the mechanisms that we infer to
understand the results are established in stratifica-
tion and labor literatures, they remain speculative in
their precise connection to older adulthood health
disparities. Future research should establish the
responsible mechanisms for this study’s findings.
We assumed that union membership itself was the
driver of older adulthood health outcomes. Yet
unions have well-established influence on egalitar-
ian state-level policy outcomes. To what extent
does cumulative unionization reflect longer resi-
dence in more egalitarian policy environments? To
what extent does unionization prevent early mortal-
ity? If unions help prevent death during one’s career
and improve health outcomes, our results might be
conservative when considered alongside uneven
mortality along unionization. More research on this
topic is needed. The group with partially unionized
careers consistently and surprisingly had the worst
health outcomes. Although we control for many
career characteristics, this group may experience
significant unmeasured volatility, either life course
or economic. In Appendix Table 1 in the online ver-
sion of the article, we include descriptive informa-
tion for this group compared to never and highly
unionized groups. Although beyond the scope of
the current study, this group deserves greater atten-
tion. Although the later life health disadvantages of
partial union exposure imply longer-term conse-
quences of career instability and changes, our find-
ings do not rule out the possibility that union status
might still provide contemporaneous health bene-
fits for these workers.
ORCID iDs
Xiaowen Han
 https://orcid.org/0000-0002-9029-
5302
Tom VanHeuvelen
 https://orcid.org/0000-0002-
7504-8186
Jeylan T. Mortimer
 https://orcid.org/0000-0001-
9192-1873
Zachary Parolin
 https://orcid.org/0000-0003-4065-
3711

Han et al.
179
Supplemental Material
Appendix Tables 1 through 5, Appendix Figures 1 through
6, and the Supplementary Material are available in the
online version of the article.
Notes
1.
We argued that union effects could potentially move
in either direction for racial minorities and women.
We structure our hypotheses pointing in one direc-
tion for simplicity and because we more strongly
suspect these outcomes.
2.
No clear threshold exists for the number of measure-
ments during the occupational career. Many studies
of permanent income use 20 years of career infor-
mation (Kim et al. 2015; Parolin and VanHeuvelen
2023). We assessed variation in this decision by
choosing thresholds between 10 and 30 observa-
tions, but results did not substantively change.
3.
Unlike Brady et al. (2022), we kept our result as a
count. Sensitivity analyses showed that respondents
with multiple chronic conditions have significantly
worse health.
4.
This included an associate’s degree, bachelor’s
degree, and advanced degree.
5.
This question was asked in multiple waves. We took
the average of all available answers provided by
respondents for a single time-invariant measure.
6.
Adjacent age periods tended to have high correlations,
ranging between .63 and .77. The earliest, 18 to 30, and
oldest, 51 to 60, age ranges had a correlation of .36.
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Author Biographies
Xiaowen Han is a PhD candidate in sociology at the
University of Minnesota and affiliated with the Minnesota
Population Center and Life Course Center. Her research
interests focus on the social inequalities in multidimen-
sional job quality and its consequences on health dispari-
ties over the life course.
Tom VanHeuvelen is an associate professor in the
Department of Sociology at the University of Minnesota.
His research broadly centers around social inequality,
stratification, quantitative methodology, and historical/
comparative sociology. His work has appeared in the
American Sociological Review, American Journal of
Sociology, Social Forces, and other outlets.
Jeylan T. Mortimer is a professor emeritus in the
Department of Sociology at the University of Minnesota.
Her research focuses on the life course social psychology,
inequality, and health, particularly at the transition to
adulthood.
Zachary Parolin is an assistant professor of social policy
at Bocconi University. His research focuses on the mea-
surement, causes, and consequences of poverty and social
inequality across the United States and European Union.

    Policy Problem:

Answer: Across the United States, the sharp, decades-long decline of labor-union coverage—from one-third of private-sector workers in the 1950s to barely 6 percent today—has quietly become a public-health issue for America’s aging population. New longitudinal evidence following thousands of workers over 39 waves of the Panel Study of Income Dynamics shows that spending most or all of one’s career in a unionized job predicts markedly better health after age 60: higher self-rated health, fewer functional limitations, and fewer chronic, life-threatening conditions. Crucially, these advantages stem from early and sustained union membership, operate over the entire life course, and are strongest for non-college-educated and non-White workers—groups already at greatest risk of precarious employment and later-life disability. Yet pension, workforce-development, and healthy-aging policies rarely factor in the long-run health dividends of collective bargaining rights. As Congress and state legislatures debate labor-law reform, retirement-security supports, and workforce-participation incentives for older adults, they lack clear frameworks to weigh how weakening or strengthening unions today will shape health-care costs, disability burdens, and longevity gaps for tomorrow’s retirees.