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Understanding reciprocal relationships between specific arenas in life and at work is critical for designing interventions to improve workplace health and safety. Most studies about the links between dimensions of well-being in life and at work have been cross-sectional and usually narrowly focused on one of the dimensions of the work-life well-being link. The issues of causality and feedback between life and work well-being have often not been addressed. We overcome these issues by measuring six aspects of well-being for both the work arena and life in general, using longitudinal data with a clear temporal sequence of cause and effect, and by explicitly accounting for feedback with potential effects in both directions. 954 Mexican apparel factory workers at a major global brand participated in two waves of the Worker Well-Being Survey. Data on life satisfaction and job satisfaction, happiness and positive affect, meaning and purpose, health, and social relationships in life and at work were used. Lagged regression controlling for confounders and prior outcomes was employed. Sensitivity analysis was used to assess the robustness of the results to potential unmeasured confounding. For the relationships between life satisfaction and job satisfaction and between happiness in life and happiness at work effects in both directions were found. Nevertheless, indication of a larger effect of life satisfaction on job satisfaction than the reverse was obtained. For depression and meaning in life, there was evidence for an effect of life well-being on work-related well-being, but not for the reverse. For social relationships and purpose, there was evidence for an effect of work-related well-being on life well-being, but not the reverse. Relationships based on the longitudinal data were considerably weaker than their respective cross-sectional associations. This study contributes to our understanding of the nature of the relationship between aspects of well-being in the arenas of life and work. Findings from this study may facilitate the development of novel workplace programs promoting working conditions that enable lifelong flourishing in life and at work.
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ORIGINAL RESEARCH
published: 09 April 2020
doi: 10.3389/fpubh.2020.00103
Frontiers in Public Health | www.frontiersin.org 1April 2020 | Volume 8 | Article 103
Edited by:
Marissa G. Baker,
University of Washington,
United States
Reviewed by:
Trevor K. Peckham,
University of Washington,
United States
Kyoung-Mu Lee,
Korea National Open University,
South Korea
*Correspondence:
Dorota Weziak-Bialowolska
doweziak@hsph.harvard.edu
Specialty section:
This article was submitted to
Occupational Health and Safety,
a section of the journal
Frontiers in Public Health
Received: 11 January 2020
Accepted: 16 March 2020
Published: 09 April 2020
Citation:
Weziak-Bialowolska D, Bialowolski P,
Sacco PL, VanderWeele TJ and
McNeely E (2020) Well-Being in Life
and Well-Being at Work: Which
Comes First? Evidence From a
Longitudinal Study.
Front. Public Health 8:103.
doi: 10.3389/fpubh.2020.00103
Well-Being in Life and Well-Being at
Work: Which Comes First? Evidence
From a Longitudinal Study
Dorota Weziak-Bialowolska 1,2
*, Piotr Bialowolski 1, Pier Luigi Sacco 3,4,5, 6,
Tyler J. VanderWeele 2,7 and Eileen McNeely 1
1Sustainability and Health Initiative (SHINE), Department of Environmental Health, Harvard T. H. Chan School of Public
Health, Boston, MA, United States, 2Human Flourishing Program, Harvard T. H. Chan School of Public Health, Institute for
Quantitative Social Science, Harvard University, Cambridge, MA, United States, 3Department of Humanities, IULM University
Milan, Milan, Italy, 4metaLAB (at) Harvard, Harvard University, Cambridge, MA, United States, 5Fondazione Bruno Kessler,
Trento, Italy, 6Berkman-Klein Center for Internet & Society, Harvard University, Cambridge, MA, United States, 7Department
of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States
Understanding reciprocal relationships between specific arenas in life and at work
is critical for designing interventions to improve workplace health and safety. Most
studies about the links between dimensions of well-being in life and at work have
been cross-sectional and usually narrowly focused on one of the dimensions of the
work-life well-being link. The issues of causality and feedback between life and work
well-being have often not been addressed. We overcome these issues by measuring
six aspects of well-being for both the work arena and life in general, using longitudinal
data with a clear temporal sequence of cause and effect, and by explicitly accounting for
feedback with potential effects in both directions. Nine hundred and fifty-four Mexican
apparel factory workers at a major global brand participated in two waves of the
Worker Well-Being Survey. Data on life satisfaction and job satisfaction, happiness and
positive affect, meaning and purpose, health, and social relationships in life and at
work were used. Lagged regression controlling for confounders and prior outcomes
was employed. Sensitivity analysis was used to assess the robustness of the results
to potential unmeasured confounding. For the relationships between life satisfaction and
job satisfaction and between happiness in life and happiness at work effects in both
directions were found. Nevertheless, indication of a larger effect of life satisfaction on job
satisfaction than the reverse was obtained. For depression and meaning in life, there was
evidence for an effect of life well-being on work-related well-being, but not for the reverse.
For social relationships and purpose, there was evidence for an effect of work-related
well-being on life well-being, but not the reverse. Relationships based on the longitudinal
data were considerably weaker than their respective cross-sectional associations. This
study contributes to our understanding of the nature of the relationship between aspects
of well-being in the arenas of life and work. Findings from this study may facilitate the
development of novel workplace programs promoting working conditions that enable
lifelong flourishing in life and at work.
Keywords: well-being in life, well-being at work, health, job and life satisfaction, happiness, meaning and purpose
in life and at work, social relationships
Weziak-Bialowolska et al. Reciprocal Benefits of Well-Being in Life and at Work
INTRODUCTION
Although the influence of work on occupational health and
safety has been long recognized (1), importance of work
for well-being has been gaining scientific attention only
recently (26). The impact of employee health on work has
been traditionally examined through the lenses of physical
and mental disabilities that limit chances for performing
certain jobs (79). Recently the topic of worker well-being
has been gaining attention in the field of occupational
health. The United States Centers for Disease Control and
Prevention’s National Institute for Occupational Safety and
Health (CDC/NIOSH) launched in 2011 the Total Worker
Health R
program that integrates protection against work-
related and health hazards with promotion of injury avoidance
and illness prevention to advance worker well-being (10
12). The World Health Organization introduced the Model
for Action, which advocates for workers’ health, safety and
well-being on and off the job (13). Similar conceptual idea,
highlighting the importance of achieving living and working
conditions that enable people to engage and thrive at work
over their lives, lies behind the concept of sustainable work
over the life course which was introduced in the European
Union to help people maintain health, develop skills and
achieve financial security, work–life balance, meaningful work,
and sense of self-fulfillment in the workplace (14). These
worker well-being promoting initiatives emerge in labor market
policies (14) and are subsequently integrated into companies’
strategies (12,15).
We argue that understanding the reciprocal relationships
between well-being aspects at work and in life is critical to
design policies to improve not only workplace health and safety
but also employee satisfaction and well-being. Unfortunately,
studies about the links between dimensions of well-being in
life and at work have been usually narrowly focused on
one of the dimensions of the work-life well-being link and
additionally—have been mostly cross-sectional making causal
inference implausible. The aim of this paper is to offer
a more holistic outlook of the relationships between well-
being at work and well-being in life by evaluating reciprocal
relationships between six dimensions of well-being (such as
life satisfaction, happiness, meaning, purpose, mental health,
and social relationships) and their work-related counterparts
while considering the bi-directional effects between work and
life for each of the dimensions over time. This perspective
contrasts with numerous well-being studies that not only limit
well-being to a single life-related measure but also conceal
the role of work as a driver for human flourishing and
disregard the value of promoting flourishing in life to enhance
flourishing at work. Consequently, in this article we hypothesize
that for each of the six dimensions, significant reciprocal
relationship between well-being in life and well-being at work
can be established. In other words, we test a hypothesis that
well-being while at work positively influences well-being in
life and well-being in life is beneficial for well-being while
at work.
LITERATURE REVIEW
One of the most examined relationships between well-being and
work has been the one between subjective well-being (SWB)1
and job satisfaction (1619). This relationship has been subject
to scrutiny over the past decades, with early contributions dating
back to the 1950’s (20). Previous studies, however, identified
only a modest to moderate association between SWB and job
satisfaction (16,19). Limited evidence, however, is available for
the relationship between other dimensions of well-being in life
and their counterparts related to well-being at work.
Many existing studies are also hardly conclusive due to
serious methodological limitations. Most of the studies have
been based on cross-sectional study designs (18,21), which
rendered it impossible to establish any causal link. Limited
longitudinal research carried out so far mainly focused on the
relationship between the broad concepts of life satisfaction and
job satisfaction without delving into its constituents [see (16) for
a review] or work-life conflict (22,23), avoiding a scrutinized
study of other aspects of well-being in the arena of life and work.
Theoretical and empirical lack of agreement on the
directionality of the relationship between well-being and
work further complicates the interpretation and assessment of
the findings (16). For instance, the part-whole theory (24,25)
posits that specific aspects of life (e.g., work) influence well-
being, whereas the dispositional approach (26,27) claims that
it is well-being that has a causal effect on specific aspects of life
(e.g., work).
Additionally, regarding the directionality of the relationship,
a heated dispute arose between proponents of the spillover
approach, advocating for a reciprocal, positive relationship
between specific aspects of life (e.g., work) and well-being (16,
28), the compensation approach, assuming that dissatisfaction in
one sphere is compensated by search for enrichment in the other
(thus envisaging a negative relationship), and the segmentalist
approach, making a case for a lack of relationships between the
two areas (29). Current evidence is thus inconclusive and thus all
hypotheses about the cause and the effect remain plausible.
The conceptual and operational definitions of well-being in
life and well-being at work have been refined more recently as
well. The definitions shifted from early characterizations in broad
affective terms to more articulate, conceptually sharper ones
(30), which provide relatively robust and consistent frameworks
necessary for a scientific analysis (16). For example, consideration
of job and life satisfaction is now combined in notions of
employee well-being (3133) and more well-being interventions
are proposed to ensure that workers are both happy (or high in
well-being) and productive (have high performance) (34,35).
However, the nature of the work-life link is still unclear.
Despite strong evidence provided by Bowling et al. (16) that
the effects are bi-directional and life satisfaction affects job
satisfaction more than job satisfaction affects life satisfaction, the
issue of the direction of causality and strength of bi-directional
1SWB is defined as either a cognitive or affective evaluation of life, and is usually
assessed for life as a whole, or for specific facets (e.g., life at work).
Frontiers in Public Health | www.frontiersin.org 2April 2020 | Volume 8 | Article 103
Weziak-Bialowolska et al. Reciprocal Benefits of Well-Being in Life and at Work
relations between dimensions of well-being at work and
well-being in life remains fundamentally open and unexplored.
Although recent research has extended our contextual knowledge
about the possible effects on the job-life satisfaction relationship
[for example the effects of: burnout (36,37), positive affect
or negative affect (19,28), job importance (38), work-family
conflict (19,28), work-life balance (39,40), workplace friendship
(41,42), job insecurity (43), and even geographical remoteness
(44)], a more comprehensive approach—as advocated also by
Neve et al. (2) is needed. However, it is worth noting that
a distinction between workplace well-being from general well-
being has been recently recognized (33). Still, limited evidence
on how particular aspects of general well-being affect their
counterparts while at work and vice versa is available.
Consequently, this paper offers the following contributions in
this relatively under-explored direction. First, by carrying out a
longitudinal analysis it provides more robust evidence on the
causal relationships between job and life satisfaction. Second,
by studying in depth other aspects of well-being in the work
and life sphere, such as happiness (45), meaning (46), purpose
(47), mental health (48) and social relationships (49), our results
provide an innovative framework for the analysis of the job vs.
life dimensions of well-being studied in the literature as well as
evidence for their causal directionality.
MATERIALS AND METHODS
Data Source and Sample Size
The analysis builds on the first two waves of the Worker Well-
Being Survey (WWBS), a tool designed to track workers’ well-
being, administered in the Levi Strauss & Co.’s supplier in
Mexico. The first wave of the WWBS was administered in
February 2017, and the second one in March 2018.
Workers completed surveys in a private space inside the
factory on tablets either connected directly to secure servers via
the internet or using an offline app. In this way, all information
was kept confidential. During survey administration, groups
of workers were released from their line positions (e.g., one
production line at a time) to come to the survey stations. A
communication campaign took place prior to survey activities
to invite workers to participate in the survey. The results were
reported in aggregate to workers and the factory after tabulation
and analysis. The workers’ decision to participate in the survey
was voluntary and was not disclosed to management. All workers
signed an informed consent. The study was approved by Harvard
T.H. Chan School of Public Health Institutional Review Board.
Nine hundred fifty-four apparel workers participated in both
waves of the WWBS. Descriptive statistics of the sample are
presented in Table 1. Data are available from the corresponding
author upon request.
Measures
In analyzing the relationships between life-related well-being
factors and their job-related counterparts, we distinguished six
aspects of well-being: (1) life satisfaction and job satisfaction,
(2) happiness, (3) meaning, (4) purpose, (5) social relationships,
and (6) mental health. Questions measuring the first five aspects
originated from the flourishing index (5052), while the question
TABLE 1 | Descriptive characteristics of the sample.
Characteristic Statistic
Gender (female) 53.7%
Age
Below 25 21.4%
25–34 28.6%
35–44 32.8%
45+27.3%
Marital status (married) 45.7%
Education (at least high school) 31.8%
Having children under the age 18 currently living in the household 67.9%
Being a primary caretake for a parent or an elderly currently living
in the household
47.6%
Job Tenure
Up to 1 year 25.7%
From 1 up to 3 years 28.3%
From 3 up to 5 years 13.0%
More than 5 years 33.0%
measuring health was adopted from the set of healthy days
questions of the Health-Related Quality of Life instrument (53).
For each well-being question a work-related counterpart was
used. Specifically, questions from an adapted version of the
Positive and Negative Affect Scale (PANAS) (54) referring to
work domain, i.e., from the Job-Related Affective Well-Being
Scale (55) were used, as well as a question about job satisfaction
and meaning and purpose at work (56,57).
The full set of questions used to measure specific dimensions
of well-being from both a life- and job-related perspective is
presented in Table 2.Table 3 presents descriptive statistics of
the variables in the study. Correlation matrix of the measures is
provided in Table A1 in the Appendix.
Control Variables
It has been empirically shown that relationship between
well-being and job attitudes may be different depending on
gender, age, and education (19,5865) and together with job
tenure, these variables are among the most commonly used
as control variables in the organizational research (59). There
is also evidence that marital status or having a family in
general, especially in combination with a necessity of raising
a child, is a discriminatory factor for happiness (66) and job
attitudes (6770). Similarly, caregiving to an elderly has a
detrimental effect on well-being (71,72), health (73), and job
satisfaction and other job attitudes (74). Additionally, there are
theoretical foundations and supporting empirical evidence that
job demand and job control correlate with mental health and job
attitudes (75,76).
Consequently, in the analysis, we controlled for: (1)
demographic variables: gender, age, marital status, education,
having children below 18 at home, taking care of an elderly; and
(2) job characteristics: job tenure, job demand (“I have too much
work to do, to do everything well;” yes/no), job control (“I have a
lot of say about what happens on my job;” yes/no), and work shift
(day vs. otherwise).
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Weziak-Bialowolska et al. Reciprocal Benefits of Well-Being in Life and at Work
TABLE 2 | Job-related and out-of-job variables measuring well-being in life and well-being at work.
Dimension of well-being Job-related variable Out-of-job variable
Life satisfaction Job satisfaction: all in all, how satisfied would you say you are with your
job? (0 =Not Satisfied At All, 10 =Completely Satisfied) (56)
Life satisfaction: overall, how satisfied are you with life as a
whole these days? (0 =Not Satisfied at All, 10 =Completely
Satisfied) (50)
Happiness Happiness at work: at work yesterday, or the last day I worked, I felt
happy; dichotomized: 1 =frequently or all the time, 0 =not at all or
occasionally (54,55)
Happiness in life: in general, how happy or unhappy do you
usually feel? (0 =Extremely Unhappy, 10 =Extremely Happy)
(50)
Meaning Meaningful job: my job is meaningful; originally measured on a Likert
scale; in the analysis dichotomized: 1 =agree, 0 =disagree (56,57)
Meaning in life: overall, to what extent do you feel the things
you do in your life are worthwhile? (0 =Not at All Worthwhile,
10 =Completely Worthwhile) (50)
Purpose Feeling purposeful at work: at work yesterday, or the last day I worked,
I felt that my job is purposeful; dichotomized: 1 =frequently or all the
time, 0 =not at all or occasionally (56,57)
Purpose in life: i understand my purpose in life. (0 =Strongly
Disagree, 10 =Strongly Agree) (50)
Close social relationships Friends at work: at work yesterday, or the last day I worked, I felt close
to other people; dichotomized: 1 =frequently or all the time, 0 =not at
all or occasionally
Friends in life: i am content with my friendships and
relationships (0 =Strongly Disagree, 10 =Strongly Agree)
(50)
Mental health Depressed at work: at work yesterday, or the last day I worked, I felt
depressed; dichotomized: 1 =frequently or all the time, 0 =not at all
or occasionally (54,55)
Depressed in life: During the past 30 days, for about how
many days did you feel sad or depressed? (dichotomized: 0
=none; 1 =at least 1 day) (53)
TABLE 3 | Descriptive statistics of the variables in the study.
Variable T=1T=2
Job related
Job satisfaction (0–10) 8.44 (2.41) 8.61 (1.99)
Happiness at work (% of yes) 68.0% 71.8%
Meaningful job (% of yes) 92.1% 90.1%
Feeling purposeful at work (% of yes) 72.5% 75.1%
Friends at work (% of yes) 70.4% 77.7%
Depressed at work (% of yes) 6.5% 9.9%
Out-of-Job
Life satisfaction (0–10) 8.12 (2.84) 8.51 (2.14)
Happiness in life (0–10) 8.69 (2.24) 8.76 (1.94)
Meaning in life (0–10) 9.04 (1.94) 9.24 (1.64)
Purpose in life (0–10) 9.36 (1.86) 9.29 (1.72)
Friends in life (0–10) 9.09 (1.86) 8.97 (1.82)
Depressed in life (% of at least 1 day in a month) 48.0% 54.0%
Means and standard deviations are reported for variables measured on 0–10
response scale.
In the longitudinal analysis, these variables were controlled at
baseline in Wave 1, in order to ensure that they were confounders
and not mediators. In the cross-sectional analysis, they were
measured simultaneously with the exposure and outcome so as
to compare results with the more rigorous longitudinal analyses.
Statistical Analysis
As the goal was to investigate a causal link between well-
being in life and job-related well-being (i.e., how well-
being in life influences job-related well-being and vice versa),
longitudinal data was used and statistical approaches for
modeling longitudinal data were employed. Contrary to analyses
conducted on cross-sectional data, this approach offered more
reliable causal evidence by virtue of the logical temporal sequence
of cause and effect. However, as most of the empirical evidence in
the field is based on cross-sectional data, we also ran secondary
analysis on such kind of data, with the aim of assessing the
level to which the relationship is inflated by the use of cross-
sectional data.
The relationship was modeled using either linear regression
model (for continuous outcomes), or logistic regression model
(for dichotomous outcomes). With respect to dichotomous
outcomes, odds ratios were reported; with respect to continuous
outcomes, standardized regression estimates were provided to
report standardized effect sizes.
The relationship between work-related well-being factors
and their out-of-work well-being counterparts for continuous
outcomes was modeled as follows:
WBWi,k(T=2) =α0+α1WBLi,k(T=1)+α2Xi(T=1) +ηi,k
(1)
WBLi,k(T=2) =β0+β1WBWi,k(T=1)+β2Xi(T=1) +εi,k
(2)
and for dichotomous outcomes as follows:
prob[WBWi,k(T=2) =1] =
1
1+e(α0+α1WBLi,k(T=1)+α2Xi(T=1)+ηi,k)(3)
prob[WBLi,k(T=2) =1] =
1
1+e(β0+β1WBWi,k(T=1)+β2Xi(T=1)+εi,k), (4)
where i=1,. . . , N,k=1,. . . ,6.
Subscript irepresents an individual, the variable WBW
indicates one out of six (k=1,. . . ,6) work-related well-being
factors, WBL is one out of six well-being in life factors. Xis
a vector of control variables including the first wave (T=1)
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Weziak-Bialowolska et al. Reciprocal Benefits of Well-Being in Life and at Work
outcomes. α1reflects effects of an out-of-work well-being factor
on a well-being at work outcome and β1shows the effects of
a well-being at work factor on a well-being in life outcome.
α2shows the association between control variables and the
well-being at work outcome, β2shows the association between
control variables and a well-being in life outcome. ηiand εiare
disturbance terms.
Robustness of the results was ensured by performing the
sensitivity analysis (77) and through the design of the study’s
procedure to account for the common method bias (78).
Sensitivity analysis was applied to assess the extent to which
an unmeasured confounder would need to be associated with
both the exposure and the outcome to explain away the
observed association (77,79). To this end, the E-value, which
is a continuous measure of how robust the association is to
potential uncontrolled confounders, was applied. The E-value
is the minimum strength of association on the risk ratio scale
that an unmeasured confounder would need to have with both
the outcome and the primary exposure or independent variable,
above and beyond the measured covariates, in order to explain
away the observed association (77).
Regarding the common method bias, we accounted for it
through the design of the study procedure (78). Specifically,
although it was not feasible to account for a common rater
and a common measurement context (as it was of crucial
importance to get data from the same persons being in the same
measurement context), we proximally and methodologically
separated predictor, and outcome variables. Specifically, these
variables were located in different sections of the questionnaire
and different response scales were used, e.g., 4-point Likert scales,
number of days, intensity scales, 0–10 Likert type scales (see
Table 2), with different scale endpoints, and different verbal
labeling. Additionally, the research team strived to ensure
anonymity of respondents and reduce evaluation apprehension
by (i) providing the choice to participate in the study
and (ii) ensuring that participation would affect neither the
employment conditions nor the employment status. Moreover,
(iii) respondent might choose to not respond to any question(s)
and (iv) withdraw without penalty at any time. Appropriate
information about (i–iv) was conveyed in the communication
campaign and also added to the invitation letter. Finally, the
follow-up visits to the factories were conducted 1, 3 and 6 months
after the survey administration and the individual interviews
with selected workers were conducted to make sure that the
workforce was not negatively affected by the participation in
the study.
Analyses were performed using Stata 15.
RESULTS
The strength of the relationships based on the longitudinal
data, controlling for prior outcome (Table 4), was found
to be in each case weaker—and in the case of purpose
and close social relationships also insignificant—than the
strength of associations revealed from the cross-sectional
analysis (Table 5). This suggests that evaluations based
TABLE 4 | Effect sizes (standardized estimates [std. est.] and odds ratios [OR])
and 95% confidence intervals (in parentheses) for the relationships between
job-related well-being factors and their out-of-job counterparts—longitudinal
results.
Out-of-job factor
(T=1)
Job-related
outcome (T=2)
Job-related
factor (T=1)
Out-of-job
outcome (T=2)
Job satisfaction
(std. est.)
Life satisfaction (std.
est.)
Life satisfaction 0.142***
(0.069; 0.216)
Job satisfaction 0.088*
(0.011; 0.164)
Happy at work
(OR)
Happiness in life
(std. est.)
Happiness in life 1.373***
(1.141; 1.653)
Happy at work 0.316***
(0.159; 0.473)
Depressed at work
(OR)
Depressed in life
(OR)
Depressed in life 2.612**
(1.427; 4.782)
Depressed at
work
0.892
(0.428; 1.860)
Meaningful job
(OR)
Meaning in life (std.
est.)
Meaning in life 1.443***
(1.177; 1.769)
Meaningful job 0.235
(0.051; 0.522)
Feeling purposeful
at work (OR)
Purpose in life (std.
est.)
Purpose in life 1.085
(0.879; 1.339)
Feeling
purposeful at
work
0.220**
(0.056; 0.384)
Friends at work
(OR)
Friends in life (std.
est.)
Friends in life 1.090
(0.893; 1.329)
Friends at work 0.168*
(0.012; 0.324)
Each regression was controlled for: job control, job demand, gender, age, education,
marital status, number of children, taking care of an elderly, job tenure, and work shift.
*p<0.05, **p<0.01, ***p<0.001.
solely on cross-sectional data could over-estimate the
actual strength of the relationships, which is consistent
with previous research about job satisfaction and subjective
well-being (16).
The effect size of the influence of life satisfaction on job
satisfaction was found to be higher (0.14) than the effect size
of the influence of job satisfaction on life satisfaction (0.09).
Happiness in life was found to influence feelings of happiness
at work and it was also the case that feelings of happiness at
work influence happiness in life (effect sizes could not be directly
compared as the former was assessed with an odds ratio scale
and the latter with a standardized difference scale). Therefore,
for both relationships—life vs. job satisfaction and happiness
in life vs. at work—there is evidence that the causal relations
are bi-directional, despite having different strength in the two
directions. Additionally, in terms of absolute strengths, causal
links in the happiness sphere turn out to be considerably stronger
than those in the satisfaction sphere.
For the remaining variables, however, the evidence suggests
that the causal relations may be unidirectional, with the actual
links emerging from the life to the job sphere or the other
way around, depending on the specific dimension. Depression
was shown to increase the probability of feeling depressed at
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Weziak-Bialowolska et al. Reciprocal Benefits of Well-Being in Life and at Work
TABLE 5 | Effect sizes (standardized estimates [std. est.] and odds ratios [OR]) and 95% confidence intervals (in parentheses) for the association between job-related
factors and their out-of-job counterparts—cross-sectional results.
Out-of-job factor Job-related outcome (cross-sectional) Job-related factor Out-of-job outcome (cross-sectional)
T=1T=2T=1T=2
Job satisfaction (std. est.) Life satisfaction (std. est.)
Life satisfaction 0.292***
(0.226; 0.357)
0.291***
(0.221; 0.360)
Job satisfaction 0.322***
(0.250; 0.395)
0.325***
(0.247; 0.402)
Happy at work (OR) Happiness in life (std. est.)
Happiness in life 1.478***
(1.139; 1.765)
2.084***
(1.696; 2.560)
Happy at work 0.339***
(0.195; 2.063)
0.731***
(0.564; 0.896)
Depressed at work (OR) Depressed in life (OR)
Depressed in life 3.776***
(1.682; 8.477)
5.730***
(2.660; 12.347)
Depressed at work 3.718***
(3.266)
5.690***
(4.203)
Meaningful job (OR) Meaning in life (std. est.)
Meaning in life 1.475***
(1.169; 1.861)
1.512***
(1.189; 1.924)
Meaningful job 0.626***
(0.359; 0.893)
0.442***
(0.186; 0.698)
Feeling purposeful at work (OR) Purpose in life (std. est.)
Purpose in life 1.364***
(1.143; 1.627)
1.290*
(1.037; 31.604)
Feeling purposeful at
work
0.286***
(0.135; 0.437)
0.185*
(0.030; 0.340)
Friends at work (OR) Friends in life (std. est.)
Friends in life 1.643***
(1.357; 1.991)
1.304**
(1.077; 1.578)
Friends at work 0.437***
(0.287; 0.588)
0.267**
(0.088; 0.448)
Each regression was controlled for: job control, job demand, gender, age, education, marital status, number of children, taking care of an elderly, job tenure, and work shift.
*p<0.05, **p<0.01, ***p<0.001.
work, but reports of feeling depressed at work were not found
to increase probability of feeling depressed in general. Similarly,
meaning in life was found to have an impact on meaning in
job, but the reverse relationship was not found to be significant.
Conversely, feeling purposeful at work was found to increase
purpose in life but not the other way around. We also found
evidence that feeling close to people at work contributes to
a sense of improved social connections in life; however, the
reverse relationship was not supported by our results. We provide
some further exploration of the potential reasons for these uni-
directional associations in the discussion.
Sensitivity Analysis for Unmeasured
Confounding
The E-values calculated for the longitudinal results (Table 6)
indicate that most of the estimated associations were relatively
robust to unmeasured confounding, which provides some further
evidence of causality for those outcomes. The influence of
job satisfaction on life satisfaction, and the relationship in
the opposite direction, were moderately robust to potential
unmeasured confounding. Only an unmeasured confounder that
would be associated with both job satisfaction and life satisfaction
by a risk ratio of 1.383 (the effect of job satisfaction on life
satisfaction) and 1.536 (the effect of life satisfaction on job
satisfaction), above and beyond the measured confounders, could
explain away the observed association between life satisfaction
and job satisfaction; weaker confounding could not. Confounders
associated with both the outcome and exposure by risk ratios
of 1.5-fold to 2-fold each would be required to explain the
relationship between life and job: happiness, purpose, meaning,
and friends, also pointing to relatively strong evidence of
robustness to confounding for the link between life and job-
related outcomes. An even stronger confounder would be
necessary to explain away the relationship between depression
in life and depression at work. The strength of association
of this hypothetical confounder would have to reach at least
4.664 in terms of risk ratios, with both depression at work
and depression in life in the model; and even to reduce the
95% confidence interval to include the null would require an
unmeasured confounder association with both depression in life
and depression at work by risk ratios of 2.2-fold each having
already adjusted for all measured confounders.
DISCUSSION AND CONCLUSIONS
The results contribute to our understanding of the nature of
the relationship between job satisfaction and life satisfaction, as
well as between other dimensions of well-being in life and well-
being at work. Generally, job satisfaction and happiness, but also
purpose, and social connections while at work were found to
influence their out-of-job counterparts 1 year later. With regard
to the reverse direction, life satisfaction and happiness, but also
depression and meaning in life were found to influence the work-
related counterparts 1 year later. Thus, only for life satisfaction
and happiness was there an evidence for effects running in
both directions, confirming our research hypothesis about the
reciprocal benefits between well-being in life and well-being
at work. Other relationships were more unidirectional but not
always necessarily indicative of an impact of work on life—the
directionality more often acknowledged in the literature.
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Weziak-Bialowolska et al. Reciprocal Benefits of Well-Being in Life and at Work
TABLE 6 | E-values for significant longitudinal effect measures and for corresponding CI limits.
Out-of-job factor E-value for effect estimate E-value for CI limit Job-related factor E-value for effect estimate E-value for CI limit
Job-related outcome Out-of-job outcome
Job satisfaction Life satisfaction
Life satisfaction 1.536 1.328 Job satisfaction 1.383 1.115
Happy at work Happiness in life
Happiness in life 1.621 1.338 Happy at work 2.000 1.582
Depressed at work Depressed in life
Depressed in life 4.664 2.207 Depressed at work
Meaning job Meaning in life
Meaning in life 1.693 1.389 Meaning job
Feeling purposeful at work Purpose in life
Purpose in life Feeling purposeful at work 1.743 1.29
Friends at work Friends in life
Friends in life Friends at work 1.604 1.12
E-values are reported only for significant estimates. E-values indicate the strength of unmeasured confounding that would be necessary to invalidate the observed relationship and thus
are not of interest when the measured effect is not significant.
Our results are in some ways intuitive, but nonetheless they
call for further scrutiny. Regarding happiness and life satisfaction,
causal links in the happiness sphere in absolute terms turn out
to be significantly stronger than those in the satisfaction sphere.
This may be due to the fact that happiness, as a construct, also
includes elements of coping resources and positive emotions
(80), potentially eliciting more immediate connections between
the work and life spheres. However, the feedback loops we
found are in line with the two competing theoretical models
of well-being: the bottom-up (situational) model and top-down
(dispositional) model (27). The bottom-up model of well-being
assumes that well-being is a sum of small pleasures. This implies,
in turn, that life satisfaction and happiness may be situational
and thus influenced by job satisfaction and positive affect while
at work, respectively. Instead, according to the top-down model,
each person tends to experience things in a particular, positive
or negative way, thus well-being is dispositional (81). This is
reflected in the way in which all life experiences are perceived,
and in particular this implies that well-being is projected onto
other variables. Specifically, the impact of life satisfaction on job
satisfaction and of happiness in life on happiness while at work
are anticipated. Consequently, life satisfaction and happiness may
be both the cause (as in the top-down model) and the effect (as in
the bottom-up model) of job satisfaction and positive affect while
at work, respectively. This conclusion has been already made
by other scholars, based on empirical evidence (82,83) and on
theoretical considerations conceptualized as the spillover model
of well-being (18,84,85).
For depression, it was shown that depression in life increases
the probability of feeling depressed at work, but reports of
feeling depressed at work were not found to increase probability
of feeling depressed in general. Depression in life is likely to
manifest itself at work as its symptoms are neither temporarily
limited to the periods spent out-of-work nor spatially confined
to the non-working environment. However, depression at work
may depend on very context-specific conditions that do not
necessarily reflect a more general susceptibility to depression. In
particular, the evidence on the effects of workplace stressors [e.g.,
prolonged job strain (86,87), increased job demand (88,89) and
limited job control (90,91)] on the development of depression
is moderate but the level of exposure to stressors that seems
to be generally needed to cause depression still requires further
investigation (86,92,93).
Meaning in life was found to have an impact on meaning in
one’s job, but the reverse relationship was not corroborated. Thus,
no support was found for the assertion by Steger and Dik (94),
Duffy and Sedlacek (95), and Allan et al. (46) that meaning at
work translates into greater meaning in life. Instead, our findings
were in line with the top-down theory of subjective well-being
(27) or the dispositional approach (26,27), according to which
global well-being translates into domain-specific well-being.
Specifically, meaning refers to overall relatedness in a larger
sense, such as coherence and significance of one’s experiences,
whereas, purpose mainly refers to pursuit and aspiration of
certain ends (57,96). The one-directional causal links that we
found seem to conform to intuition—with meaning, the more
existential dimension, being driven by the life sphere, whereas
purpose, the more goal-oriented dimension, being driven by the
work sphere. This result appears to be in line with the findings of
Steger and Dik (94), who report that both experiencing a calling
and seeking life meaning are predictors of life meaning.
Similar to other studies (41,42), we also found evidence
that feeling close to people at work contributes to improved
social connection in life. This finding corroborates Rumens’
[(97), p. 1149] assertion that “workplace friendships contribute
to human flourishing.” However, the reverse relationship was not
supported by our results. This is again a result that conforms
to intuition, as social connection at work will contribute to
one’s overall social well-being, but relationships outside of the
workplace do not necessarily make workplace friendships any
more likely. Additionally, social connection in the workplace
may call for a more demanding social adaptation compared to
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Weziak-Bialowolska et al. Reciprocal Benefits of Well-Being in Life and at Work
the life sphere since, in the work environment, people have less
control over the choice to associate with certain people or not,
compared to their own out-of-work social environment, and
the emotional control tasks in the former case are consequently
more demanding (98). Additionally, it is natural that social
relationships from work can spread (spill-over) into the life
domain, while relationships from life are confined in the life
domain. Despite recognition and effectiveness of word-of-mouth
as a recruitment source (99,100), one cannot expect to be able to
often influence the hiring decisions of one’s employer based on
non-work-related friendship.
In contrast to the majority of other studies, we used
longitudinal data thus making a substantial adjustment for
confounding and control for work and life characteristics, which
are known to correlate with aspects of both well-being at work
and well-being in life. Although cross-sectional analyses [both
ours and those of other authors; see e.g., (19)] suggest presence of
moderate to strong bidirectional relationships, our longitudinal
results provide evidence for potential effects in both directions,
with effect sizes of roughly equal magnitude only for the
relationships of life satisfaction-job satisfaction, and happiness at
work-happiness in general/life. This confirms the findings of the
meta-analysis of the relationship between job and life satisfaction
conducted by Bowling et al. (16) on 11 (eight published and three
unpublished) longitudinal studies, which may be more valid as
they account for the logical and temporal sequence of cause and
effect and for prior levels of outcomes. Moreover, our results
here also suggest that only unidirectional effects exist concerning
meaning, purpose, mental health, and social connectedness.
Although the Worker Well-Being Survey was designed to target
working adults and examine worker well-being, it must be
also noted that our sample of Mexican manufacturing workers
may reflect specific social conditions and cultural inclinations.
Different samples, covering jobs with different characteristics and
professional profiles, or taken in different geographical and socio-
cultural contexts, might yield different results. The literature
shows that cross-country variation in the dimensions, which are
the object of this study, should be expected, with a possibly
prominent role played by the local level of social capital (101
103). Likewise, work-related stress varies significantly across
occupations (104,105), and therefore—although we controlled
for job demand and job control, which are well-known correlates
of work-related stress and burnout (75,76)—one can expect this
source of variation to affect the relationship between well-being at
work and in life. Consequently, there should be caution as to the
generalizability of our results, and more research for different job
profiles and in different geographical contexts should be carried
out to gain a deeper insight. To this end, in particular, relatively
more research effort should be directed toward longitudinal
rather than cross-sectional studies, in order to improve our
understanding of the structure of the causal relations between the
work and life spheres of the other related variables of interest.
Our study made use of observational data. Most of the results
presented in this study proved to be relatively robust to potential
unmeasured confounding beyond a considerable number of
measured potential confounders already included in the analyses.
Thus, the evidence for causality was further strengthened.
However, the results may still be subject to unmeasured
confounding by personality, core self-evaluations, such as self-
esteem, self-efficacy, locus of control and emotional stability
(106,107), as well as goal self-concordance (108). However, our
sensitivity analysis indicates that, for an unmeasured confounder
to explain the effect of the observed associations, it would
have to be associated with both job-related and out-of-job well-
being factors by a risk ratio equal in magnitude to at least
1.383, while in order to explain away the relationship between
general depression and work-related depression an unmeasured
confounder related to both measures of depression by more than
four on the risk-ratio scale would be required.
We used two waves of data, which let us control for the
baseline outcomes. However, future research should consider
replicating the results using more waves of data to control also for
the baseline exposure. Such analysis will provide further evidence
for the robustness of our results.
Finally, in the analyses we relied on single item measures
of well-being dimensions. Although it is a common practice
to use multi-item measures in such a case, we argue that long
instruments—despite the advantages of conceptual richness—are
inferior to short instruments in studies focusing on a vast array of
topics. Workers’ well-being study measures well-being along with
physical and psycho-social working conditions, work safety and
occupational health, job burden, job autonomy, job resources,
work-family conflict, and others. In such a setting, a less time-
consuming instrument may be beneficial. By being short enough
for practical use in the workplace, it facilitates company’s efforts
to improve the worker well-being (32). Criticism of short
instruments—especially those with one item per domain—relates
to elevated Type 1 and Type 2 error probabilities [see (109)] for
evidence in the personality studies). Yet, such instruments can
still be found in psychology (110,111), educational psychology
(112) and organizational behavior (113), among others. In the
well-being field, it is worth noting that the United Kingdom
Office for National Statistics—to avoid excessive costs and to
enable widespread use—since 2011 includes a set of only four
well-being questions in the UK National Survey (114).
In sum, we concede that work is just one arena to enhance
well-being, however, given the amount of time spent at work
across our lifetimes, seemingly a powerful one. Therefore,
understanding the well-being ecosystem for impact areas and
reciprocal relationships in life and at work is important to finding
ways to intervene. Without this holistic view, the leverage points
for optimizing well-being may be invisible or inadequate by an
overemphasis or attribution to one sphere of influence only.
DATA AVAILABILITY STATEMENT
The datasets generated for this study are available on request to
the corresponding author.
ETHICS STATEMENT
The studies involving human participants were reviewed and
approved by Harvard T. H. Chan School of Public Health
Frontiers in Public Health | www.frontiersin.org 8April 2020 | Volume 8 | Article 103
Weziak-Bialowolska et al. Reciprocal Benefits of Well-Being in Life and at Work
Institutional Review Board. The patients/participants provided
their written informed consent to participate in this study.
AUTHOR CONTRIBUTIONS
DW-B developed the study concept, contributed to data analysis
and interpretation of the result, drafted the manuscript and
approved the final version of the manuscript. PB contributed
to data analysis and interpretation of the result, drafted the
manuscript and approved the final version of the manuscript.
PS contributed to interpretation of the results, drafted the
manuscript and approved the final version of the manuscript.
TV contributed to interpretation of the results, revised the
manuscript and approved the final version of the manuscript. EM
developed the study design, revised the manuscript and approved
the final version of the manuscript.
FUNDING
This study was supported by the Robert Wood Johnson
Foundation under the grant No. 74275 Building a Culture of
Health: A Business Leadership Imperative and by the Levi Strauss
Foundation under the grant Follow up of Well-being measures in
Mexico, China, Cambodia, and Sri Lanka.
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Conflict of Interest: The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be construed as a
potential conflict of interest.
Copyright © 2020 Weziak-Bialowolska, Bialowolski, Sacco, VanderWeele and
McNeely. This is an open-access article distributed under the terms of the Creative
Commons Attribution License (CC BY). The use, distribution or reproduction in
other forums is permitted, provided the original author(s) and the copyright owner(s)
are credited and that the original publication in this journal is cited, in accordance
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APPENDIX
TABLE A1 | Zero-order correlation matrix of the variables in the study (at T=1).
Variable (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
Job satisfaction (1)
Happiness at work (2) 0.273***
Meaningful job (3) 0.222*** 0.198***
Feeling purposeful at work (4) 0.212*** 0.289*** 0.203***
Friends at work (5) 0.182*** 0.240*** 0.169*** 0.307***
Depressed at work (6) –0.165*** –0.189*** –0.076* –0.047 –0.128***
Life satisfaction (7) 0.384*** 0.202*** 0.204*** 0.224*** 0.106** –0.207***
Happiness in life (8) 0.293*** 0.207*** 0.169*** 0.203*** 0.164*** –0.182*** 0.403***
Meaning in life (9) 0.302*** 0.194*** 0.231*** 0.219*** 0.145*** –0.235*** 0.531*** 0.486***
Purpose in life (10) 0.270*** 0.190*** 0.184*** 0.168*** 0.136*** –0.145*** –0.289*** 0.386*** 0.590***
Friends in life (11) 0.303*** 0.184*** 0.081* 0.185*** 0.225*** –0.119*** 0.249*** 0.323*** 0.293*** 0.193***
Depressed in life (12) –0.193*** –0.177*** –0.097** –0.106** –0.080* 0.169*** –0.162*** –0.234*** –0.168*** –0.087** –0.155***
***p<0.001, **p<0.01, *p<0.05.
Frontiers in Public Health | www.frontiersin.org 12 April 2020 | Volume 8 | Article 103
... Although the experiences of meaning in life and sense of purpose in life have been found to be prospectively associated with some health conditions, health behaviours, as well as well-being and quality of life, empirical research documenting its antecedents remains scarce (VanderWeele, Chen, et al., 2020). The five longitudinal studies, in which the determinants of either a meaningful or a purposeful life have been found, have indicated that positive affect, social connections, orientation to promote good, feeling purposeful at work, wealth and income are all favorably associated with subsequent purpose in life, whereas psychological distress is associated negatively King et al., 2006;Steptoe & Fancourt, 2020;Weziak-Bialowolska et al., 2020;Weziak-Bialowolska et al., 2021). The reported results on health conditions are ambiguous, with health behaviours and physical health reported as not being associated with subsequent purpose in life and the number of chronic diseases and lack of pain being prospectively associated with the experience of meaning in life (Steptoe & Fancourt, 2020). ...
... In this study, we focus on the concept of sense of meaning in life, following the theoretical arguments and preliminary empirical evidence suggesting that the concept is distinct from purpose in life (George & Park, 2013;Martela & Steger, 2016;Weziak-Bialowolska et al., 2020). We address two research questions: (1) What changes in health, emotional ill-being and daily life functioning outcomes might be observed within a 6-year time horizon (6-year follow-up), if people feel a sense of meaning in life? ...
... Ambiguity in the results might result from differences in the concepts measured [i.e., purpose in life vs. broader construct of meaning in life, which, despite being correlated, are still distinct concepts (George & Park, 2013;Weziak-Bialowolska et al., 2020)], instruments [purpose in life scale from the Ryff and Keyes (1995)'s Psychological Well-Being vs. a single item from the CASP-12 measure of quality of life in early old age (Mehrbrodt et al., 2019); self-reported data on stroke vs. data derived from the autopsy results], as well as the observation period [up to four-year follow-up in the study by Kim et al. (2013) vs. up to 6-year follow-up in our study]. These differences preclude drawing definite conclusions based on the direct comparison of results. ...
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... Studies have indicated that EWB improves job performance (Medina-Garrido et al., 2017), decreases turnover intentions (DiPietro et al., 2020) and increases work engagement (Koon and Ho, 2021). On top of this, one longitudinal study by Weziak-Bialowolska et al. (2020) found evidence that in the domains of social relationships and purpose, work-related well-being affects overall life well-being (LWB), but not the reverse, pointing to how work well-being can impact other areas of life. ...
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... Its findings can bring a novelty into the HRM and leadership-related subjects as well as courses aiming at increasing students awareness in the area of sustainable development. Considering the amount of time spent at work across individuals' lifetimes, employees' WB is a powerful factor of general quality of life of a society (Weziak-Bialowolska et al., 2020). ...
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... With respect to the nature of occupation, new urbanites were basically engaged in physical or flexible work, employed by either themselves or private enterprises and lack of professional skills, but had a relatively high satisfaction with their current work. Of theses factors, the types of workplaces were evaluated to significantly affect life satisfaction, as reported in Weziak-Bialowolska's research [45]. Employment in formal sectors or informal sectors is expected to have a direct or indirect effect on the level of life satisfaction [46]. ...
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