FOR BETTER OR FOR WORSE: THE EFFECTS OF NONSTANDARD WORK
SCHEDULES ON SELF-RATED HEALTH ACROSS MARITAL STATUS
By
Shannon Shen

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Sociology—Master of Arts
2015

ABSTRACT
FOR BETTER OR FOR WORSE: THE EFFECTS OF NONSTANDARD WORK
SCHEDULES ON SELF-RATED HEALTH ACROSS MARITAL STATUS
By
Shannon Shen
Nonstandard work schedules are increasingly common in today’s economy. Work during
these irregular hours has a negative health impact. Scholars investigating work schedule have yet
to explore how marital status, which is linked with better health, may protect the health of U.S.
nonstandard shift workers. This study analyzes pooled data from the National Study of the
Changing Workforce (N=6774) to test if marital status and gender variations occur in the
relationship between work schedule and health. The findings show that cohabiting and divorced
or separated nonstandard workers have lower odds of reporting better health than married
individuals working standard schedules. A gender difference is also present, with nonstandard
shifts being worse for the health of divorced or separated women than for married women. The
results indicate a significant interaction between gender and marital status exists and should be
considered when examining the health of the nonstandard working population.

TABLE OF CONTENTS1

LIST OF TABLES ......................................................................................................................... iv
INTRODUCTION ...........................................................................................................................1
BACKGROUND .............................................................................................................................3
Theoretical Framework ......................................................................................................3
Work Schedule and Health .................................................................................................4
Nonstandard Work Schedules and Health ..........................................................................4
Nonstandard Work and Health across Marital Status ........................................................7
Gender Differences between Work Schedule, Marital Status and Health .........................8
Other Covariates Related to Work Schedule and Health ...................................................9
METHOD ......................................................................................................................................11
Data and Sample ...............................................................................................................11
Measures ...........................................................................................................................11
Statistical Methods ...........................................................................................................12
RESULTS ......................................................................................................................................14
Descriptive Statistics of Study Sample ............................................................................14
Ordinal Logistic Regression Results ................................................................................15
DISCUSSION ................................................................................................................................19
Limitations and Future Research ......................................................................................22
REFERENCES ..............................................................................................................................24

iii1

LIST OF TABLES1

Table 1.

Descriptive Statistics of Variables (Pooled 2002 and 2008 National
Study of the Changing Workforce), N=6774 .........................................................14

Table 2.

Odds Ratios of Ordinal Logistic Regression of Nonstandard Work on
Self-Rated Health (N=6774) .................................................................................16

Table 3.

Odds Ratios of Ordinal Logistic Regression of Nonstandard Work on
Self-Rated Health by Gender .................................................................................17

iv

INTRODUCTION
The United States is now a service economy that is open 24 hours each day of the week.
This economic change contributes to nonstandard work schedules for about twenty percent of the
working population (Enchautegui 2013). While research shows that full-time employment is
beneficial to worker’s health (Ross and Mirowsky 1995), irregular shift work does not have the
same advantages (Fenwick and Tausig 2001; Gordon, Cleary, Parker, and Czeisler 1986; Kleiner
and Pavalko 2010; Mellor 1986). United States-based studies that examine the link between
nonstandard work schedule and health find that various aspects of health are jeopardized for
these workers (Chung, Wolf, and Shapiro 2009; Presser 2003). Some physical health risks
include increased smoking behavior, more work-related accidents, and interference with regular
sleep and eating schedules which results in fatigue and disrupted stomach and intestine
functioning (Finn 1981; Geiger-Brown, Lee, and Trinkoff 2012). Nonstandard shift workers’
mental health is compromised as these workers can be more stressed and suffer greater emotional
problems (Fenwick and Tausig 2001; Gordon et al. 1986; Kleiner and Pavalko 2010). Additional
studies that examined this topic used data from other countries and found similar results. In
places such as Finland or Japan employees with nonstandard schedules either reported worse
health or experienced greater health problems (Kivimaki, Kuisma, Virtanen, and Elovainio 2001;
Nakata 2012). However, previous studies do not consider how marital status moderates the
relationship between nonstandard work schedules and self-rated health in the United States.
The prevalence of nonstandard schedules varies across marital status. People who are
divorced, separated, widowed, or single are more likely to have nonstandard work arrangements
than people who are married (Presser 2003a). Several studies compare these groups in aggregate,
and they each find that individuals who are not married more frequently work outside of standard
employment hours (Enchautegui 2013; Presser 1995; Wight, Raley, and Bianchi 2008). Among
1

married couples where both spouses are working, women more often work nonstandard
schedules than men (Kalleberg et al. 1997). If both spouses do shift work, it is uncommon for a
husband and wife to work the same nonstandard shift (Presser 1995).
Health outcomes also vary across marital statuses. This link is widely documented in the
social science literature, with examinations of diverse sample sets demonstrating that married
individuals have better health than their non-married counterparts (Ross, Mirowsky, and
Goldsteen 1990). Various pathways by which married individuals report better health have been
proposed. Although some scholars argue that selection into marriage occurs for healthier
individuals, others suggest that marriage causes a healthier lifestyle which is complimented by a
decrease in health-risk behaviors (Lillard and Waite 1995; Ross et al. 1990). There is evidence in
support of each explanation, and the two relationships can exist in tandem (Lillard and Waite
1995). Still, we know little about whether and how the effect of work schedule on health varies
across different marital contexts. This is an important association to consider, given that both
nonstandard work schedule and health vary by marital status.
To address this research gap, this study explores the following research questions: does
working a nonstandard work schedule impact employees’ self-rated health, do the effects of
nonstandard work schedules on self-rated health vary by marital status, and do these
relationships differ for men and women? The importance of this topic is highlighted by the rapid
job growth in nonstandard work occupations expected to occur in future years (Enchautegui
2013).

2

BACKGROUND
Theoretical Framework
Employees can gain social support from their workplace, and the continuity and
coherence of a regular work schedule is favorable for an employee’s mental and physical
condition (Sorensen and Verbrugge 1987). The lack of social regulation that may accompany a
nonstandard shift leaves a worker feeling socially and institutionally isolated (Durkheim [1894]
1997; Kleiner and Pavalko 2010). The decreased amount of social support and regulation
common to nonstandard schedules predicts these workers’ lower health levels.
Marriage functions as a mechanism for social integration, and it encourages beneficial
health behaviors and deters harmful ones (House, Landis, and Umberson 1988; Umberson 1987).
Marriage increases social integration because it provides entrance into the social networks of
one’s spouse’s family and friends. This connection is beneficial, as individuals who are more
greatly integrated into society have reduced mortality rates (Seeman 1996). Given that married
individuals are in a legally-bound partnership that can keep them more socially connected, they
may enjoy better health than their unmarried peers (Waite 1995). Hence, among nonstandard
workers, married people will be healthier than all other marital status groups.
Additional theories about marriage and health further explain why various marital
statuses would have different health outcomes among nonstandard workers. Social control theory
links social integration to well-being (Umberson 1987). The social support gained in marriage is
beneficial to health because it increases the social control of health behaviors (Umberson 1992).
In general, married individuals have the lowest mortality rates of all the marital statuses and
enjoy better health (Ross et al. 1990; Waite and Gallagher 2000). The related marital protection
hypothesis argues that the institution of marriage is protective because it causes healthier

3

behavior that fosters better overall well-being (Waite and Gallagher 2000). This social causation
model is useful in explaining the relationship between work schedule and health across marital
statuses as it contends that employment improves health (Ross and Mirowsky 1995). The benefit
that social ties have on well-being is applicable to work schedule and is displayed differently
across marital status. This investigation draws upon social integration, social control theory, and
the marital causation model to predict that the integration benefits gained in marriage promote
better health for spouses than all their unmarried peers when both groups are employed in
nonstandard work schedules.
Work Schedule and Health
Paid employment is positively associated with better health for both men and women
(Bartley, Popay, and Plewis 1992; Bird and Fremont 1991; Repetti, Matthews, and Waldron
1989; Ross and Mirowsky 1995; Springer 2010). While full-time workers are healthier than part
time workers, individuals who are unemployed report the worst health (Ross and Mirowsky
1995; Kaleta, Makowiec-Dabrowska, and Jegier 2008). The health benefits that come from
employment can vary on how job demands interact with an employee’s family life and work
preferences. In particular, women’s education and employment gains over the past decades have
contributed to their work time and detracted from time they may have previously spent caring for
children. Although there are arguments about causality, as healthy workers could be more likely
to be and remain employed, there is strong evidence that being employed full-time fosters better
health than part-time employment (Ross and Mirowsky 1995).
Nonstandard Work Schedules and Health
Definitions of regular work schedules include those shifts that are recurrently scheduled
from Monday through Friday, generally between the hours of 6 a.m. and 6 p.m. (Enchautegui

4

2013; McMenamin 2007; Presser and Ward 2011). Yet economic and demographic changes in
the United States, as well as advances in technology, contribute to the increase of work schedules
that occur outside of these times (Presser 1995). Such nonstandard work schedules are those that
include night or evening shifts, rotating schedules, and weekend work (Presser 2003a; Presser
and Ward 2011). Workers employed with these schedules choose to do so for a variety of
reasons, making nonstandard workers largely a self-selected population (Davis, Goodman,
Pirretti and Almeida 2008; Harrington 2001). There are employees who primarily work part-time
and use the nonstandard shift to balance childcare responsibilities (McMenamin 2007; Presser
2003; Wight et al. 2008). Students represent a sizeable number of nonstandard workers, and
many select these shifts to accommodate their class schedule (McMenamin 2007; Presser,
Gornick, and Parashar 2008). A minority of workers indicate that they prefer shift work because
of wage benefits, although a comparison of jobs with similar characteristics shows that standard
work schedules yield better pay (Kalleberg et al. 1997; McMenamin 2007). Economic changes
demand that businesses remain open or services are available outside the standard work hours.
Therefore, workers in these industries, such as food service, entertainment, or transportation,
report that they engage in nonstandard work schedules because it is the requirement of their job
rather than being their choice (McMenamin 2007; Presser 1995).
Studies that investigate how work schedules are related to health report a variety of
results which demonstrate that working a nonstandard schedule has negative health effects
(Costa 1996; Fenwick and Tausig 2001; Geiger-Brown et al. 2012; Gordon et al. 1986; Kleiner
and Pavalko 2010; Mellor 1986; Presser 2003a). This happens in part because shift work leads to
schedules that are irregular or hours that are longer than standard schedules, and because it does
not have the same benefits of regular, full-time employment (Costa 1996; Ross and Mirowsky

5

1995). For example, nonstandard work shifts likely result in a decreased provision of health
insurance and lower wages, plus jobs demanding irregular schedules are often of lower quality
(Enchautegui 2013; Kalleberg et al. 1997).
The negative characteristics of nonstandard schedules lead to health behaviors that have
physical and mental health consequences. Nonstandard workers have variable sleep cycles which
are disruptive to the body’s circadian rhythm and contribute to gastrointestinal complications,
body temperature deregulation, and hormone imbalances (Presser 1999; Presser et al. 2008). As
for mental health, employees that have more choice over their work schedule can feel more
encouragement and pride toward their work (Harrington 2001), yet nonstandard shift workers
often lack control over their work schedule (Fenwick and Tausig 2001). Those who work only
part-time are left with less job satisfaction, displeasure from having little control over their
variable shifts, and discontentment with their changing work hours (Kleiner and Pavalko 2010).
These outcomes foster lower mental well-being which can contribute to inferior overall health
for nonstandard workers.
Different international studies report similar results for the effects of nonstandard work
schedule on health. In an examination of Japanese workers, Nakata (2012) found that employees
who worked more than eight hours a day reported poorer health, and the main association
between the extra hours and poor health was lack of sleep. A study of Finnish nurses revealed
that those who worked nonstandard shifts had higher rates of smoking and obesity than those
who worked standard shifts, and the authors reported that their findings parallel the health
behaviors of nurses in the United States (Kivimaki et al. 2001). To my knowledge, however, no
studies have been conducted using data from U.S. samples to determine the effect of nonstandard
work schedules on self-rated health. Taken together, I expect that:

6

Hypothesis 1: Individuals who work a nonstandard work schedule will report lower selfrated health than those who work a standard work schedule.
Nonstandard Work and Health across Marital Status
Studies about nonstandard work schedules often explore the descriptive characteristics of
these employees rather than focus on how the abnormal scheduling is linked to other variables
(Presser 2003a). Because of this, it is less clear whether the effect of nonstandard work on health
varies across marital status. Health can be influenced by a variety of biological and social
factors. Marital status is one of the most important social indicators that provides a variety of
health benefits, including a protection against mortality (Gove 1973; Hemstrom 1996; Umberson
1987). Marriage presumes a long-term commitment that allows partners to plan for the future, it
allows spouses to combine their resources, and it fosters integration with other social groups—all
of these promote better health (Waite 1995).
Specific outcomes found in literature on both marriage and work schedule document
health differences across marital statuses. First, workers with nonstandard schedules have higher
rates of cardiovascular disease than standard shift workers (Presser 2003a). This ailment is also
more common among divorced and widowed people, as they have higher death rates from heart
disease than married people (Ross et al. 1990). Even though nonstandard shift workers have a
greater risk of contracting cardiovascular disease, married nonstandard shift workers may be
more protected from unhealthy outcomes because of the support and control marriage provides
(Berkman, Glass, Brissette, and Seeman 2000; Waite and Gallagher 2000; Umberson 1987).
Likewise, there is more variability in the sleep schedules of nonstandard shift workers than
standard shift workers (Presser 1999; Presser et al. 2008). Married and unmarried shift workers
experience sleep irregularity, but the social control that a married shift worker receives from

7

their spouse may influence them to adopt a better sleep cycle than an unmarried shift worker who
does not have a spouse to encourage better health behaviors (Umberson 1987). Furthermore,
nonstandard workers have worse mental health with regard to stress and emotional problems
(Fenwick and Tausig 2001; Gordon et al. 1986; Kleiner and Pavalko 2010). Married shift
workers may be protected from worse psychological outcomes because marriage and living with
another person fosters emotional support (Ross et al. 1990). Given these findings, I expect that:
Hypothesis 2: The effect that work schedule has on self-rated health is stronger among
the married than the unmarried.
Gender Differences between Work Schedule, Marital Status and Health
The prevalence of nonstandard work schedules varies by gender. A disproportionate
amount of women work these schedules because they are concentrated in jobs that more greatly
require working nonstandard hours, such as nursing or home healthcare, cashier, or sales (Presser
1999). The concentration of women in service jobs that are less desirable than production sector
jobs is common across industrialized economies (Presser et al. 2008). It is additionally more
frequent for men to work full-time jobs while women work more part-time, often nonstandard,
jobs (Presser et al. 2008; Zeytinoglu and Muteshi 2000).
The relationship between marital status and health also varies by gender. While the selfassessed health of unmarried individuals has improved in recent years, married people still have
comparably better health, and this relationship is different for men and women (Liu and
Umberson 2008). The health benefit from marriage is stronger for men than women because
men’s lifestyles prior to marriage are more detrimental to their health while women’s involved
less health risks to begin with (Umberson 1987). Additionally, because women more often
engage in relationships with family or friends, married men reap benefits from this increased

8

social integration compared to unmarried men (Lillard and Waite 1995). Among women, those
who are married report a greater improvement in their health compared to those who are
widowed, separated, or divorced (Liu and Umberson 2008). This is largely due to the increased
financial reward that marriage brings (Lillard and Waite 1995).
Because gender is an essential piece in the literature on marriage and health and women
are more likely to work nonstandard schedules, I anticipate that stratifying the analysis by gender
will demonstrate that the effect marital status has on the relationship between work schedule and
health will be a particular concern for women. This leads to my third hypothesis:
Hypothesis 3. The moderating effect that marital status has for work schedule on selfrated health will be stronger for women than for men.
Other Covariates Related to Work Schedule and Health
Previous studies demonstrate the demographics of individuals who are most likely to
have a nonstandard work schedule. Age is an important factor because many of these workers are
younger, and they are often college students balancing a job outside of the standard school hours
(Wight et al. 2008). Younger people may have less age-related health problems, so accounting
for age is an important consideration. Gender and race differences are also present between
standard and nonstandard workers. Although women are more concentrated in nonstandard
shifts, male workers outnumber female workers in such jobs, and Black workers are more likely
than White workers to be employed in these shifts (McMenamin 2007; Presser 2003; Wight et al.
2008). Individuals who identify as Hispanic or of some other race are also more present in
nonstandard jobs than White workers (Presser 2003). Finally, people who are less educated are
more likely to work outside of standard hours (McMenamin 2007; Presser and Cain 1983). A
link between education and health exists, and individuals with greater educational attainment

9

report better health (Ross and Wu 1995). Thus, nonstandard shift workers are more likely to be
young, Black, and male, have low education levels, and work part-time in service sector jobs.
Furthermore, the majority of all nonstandard workers come from low-income households
(Enchauegui 2013). Low-income shift workers are often employed in low-skilled service
industry jobs that can be detrimental to health. Self-employment is another considerable factor in
this instance because many self-employed individuals work nonstandard shifts. However, as
owners of their business, they have a greater interest in performing work outside of the regular
work time because they will gain greater economic rewards (Presser 1995). Their health may not
suffer as much as an individual working a nonstandard shift for a company they do not own. The
presence of children also affects a person’s work shift, particularly because childcare options are
limited for working parents and nonstandard employment hours restrict the time parents spend
with their children (Presser et al. 2008). Childcare for single, nonstandard-scheduled parents is
especially difficult and may be more pronounced among women because of their concentration
in nonstandard jobs (Presser 1999). These variables are accounted for in the following
examination of the relationships between work schedule and health.

10

METHOD
Data and Sample
This study analyzes data from the National Study of the Changing Workforce (NSCW), a
nationally representative sample of the working population collected by the Families and Work
Institute since 1992 (Families and Work Institute 2004). A cross-sectional analysis was
conducted using pooled data from the 2002 and 2008 surveys. Only these years could be used
due to limited availability of the self-rated health variable.
This study was specifically interested in individuals who were working either standard or
nonstandard shifts. Respondents who indicated that they were working some other schedule, did
not know what their schedule was, or refused to answer were therefore excluded from the
sample. Additionally, many of the covariates were categorical variables, and some had a minimal
percent of missing cases. Missing information for these variables, which included self-rated
health, marital status, self-employment status, race, and parental status, was dropped. The age
and family income variables had larger numbers of missing cases, about 1% and 8% of the
sample, respectively. Rather than dropping these respondents, I imputed the missing value for
age based on the other covariates, and I imputed family income per year at the mean. The final
sample size was 6,774 respondents, with 3.31% of the original sample lost due to the previously
stated reasons.
Measures
Self-rated health is the dependent variable. Respondents could select from four different
categories to rank their current health, and these were recoded to reflect the worst to best ratings:
poor, fair, good, or excellent health.

11

Work schedule is the main independent variable. It is measured dichotomously, with
standard schedule workers consisting of respondents with a regular daytime schedule and
nonstandard schedule workers consisting of respondents who work any other shift. This
nonstandard schedule was composed of a number of shifts, including regular evening, night or
rotating shifts, a split shift, or having a variable on call schedule.
Marital status is the moderating variable. It is composed of five categories that reflect the
respondent’s current marital status: married, cohabiting, single and never married, divorced or
separated, and widowed. Individuals that are widowed or divorced or separated are not
cohabiting with a partner.
Additional demographic and socioeconomic variables are included to control for any
effect they may have on the main relationship. Race is categorized into three groups: White,
Black or African American, and other race. Education refers to the respondent’s highest level of
education achieved. It is broken into three categories, those with a high school diploma or below,
those with some college education, and those with a college degree or beyond (this includes an
Associate’s degree). Age is a continuous variable, ranging from 18 to 99 years. Family income is
divided into quintiles that distribute the total sample into fairly equal groups. The lowest quintile
represents families whose yearly income is $32,000 or less, the next quintile is those with
$32,001 to $54,000, the following group has incomes between $54,001 and $80,000, the
penultimate group includes incomes from $80,001 to $100,000, and the final group’s income is
$100,001 or more. Measures for self-employment and parental status are included as well. Selfemployment simply codes respondents dichotomously as being self-employed or not, and
parental status categorizes respondents as either being a parent or guardian of any person or not.
Statistical Methods

12

The relationships between self-rated health, nonstandard work schedule, and marital
status are analyzed using ordinal logistic regression. This method compares the odds of an
outcome being in a higher rather than a lower category by grouping the outcome categories
differently. The present analysis compares those with poor health to those with fair, good and
excellent health, those with poor and fair health to those with good and excellent health, and
those with poor, fair, and good health to those with excellent health. There are three nested
models used to test the hypotheses, with the final model adding interaction variables for marital
status by work schedule. The likelihood ratio test indicated that each of the new models were
significantly better than the earlier one. A separate analysis stratifies these models by gender to
test the third hypothesis.

13

RESULTS
Descriptive Statistics of Study Sample
Table 1 lists descriptive statistics which describe the sample as being majorly composed
of White, college-educated parents with an average age of about 45. There are more women than
men in the sample and a good amount of the respondents are financially well-off, with about
40% having yearly family incomes above $80,000. A minority of respondents are self-employed,
and about a quarter work nonstandard schedules. Most respondents indicate that they have good
or excellent health, and the better part of the sample is currently married.

Table 1. Descriptive Statistics of Variables (Pooled 2002 and 2008 National Study of the
Changing Workforce), N=6774
Variable
Percentage
Variable
Percentage
Self-rated health
Employment Type
Poor (ref)
1.68
Self-employed (ref)
15.63
Fair
15.85
Not self-employed
84.37
Good
49.73
Education
Excellent
32.73
College graduate (ref)
52.07
Work Schedule
Some College
22.35
Standard (ref)
72.41
HS diploma or less
25.58
Nonstandard
27.59
Parental Status
Marital Status
Not a parent (ref)
34.84
Married (ref)
59.57
Parent
65.16
Cohabiting
6.20
Family Income
Single, never married
15.63
$32,000 of less (ref)
20.74
Divorced/Separated
15.22
$32,001 - $54,000
19.40
Widowed
3.38
$54,001 - $80,000
21.69
Sex
$80,001 - $100,000
18.20
Male (ref)
45.78
$100,001 and higher
19.97
Female
54.22
Year
Race
2002 (ref)
50.00
White (ref)
82.74
2008
50.00
Black
8.70
Age
Other
8.56
Mean: 44.81 (SD: 12.89)

14

Ordinal Logistic Regression Results
The estimated odds ratio results of ordinal logistic regression in Model 1 of Table 2
indicate that the predicted odds of reporting better health is 10.3% lower for individuals who
work nonstandard schedules than those who work standard shifts. Respondents who are
cohabiting, divorced or separated, and widowed have a significantly lower odds of reporting
good health compared to married respondents.
Model 2 of Table 2 suggests that these relationships generally remain significant when
the demographic and socioeconomic variables are added, although the relationship for widowed
respondents reporting worse health than married respondents becomes insignificant. Results
from Model 2 also suggest that men more than women and Whites more than Blacks have
significantly higher odds of reporting better health. Furthermore, as respondents get older, their
odds of reporting better health decreases. Given the link between socioeconomic status and wellbeing, it is not surprising that respondents with a college degree report better health and that
respondents in the lowest quintile of yearly family income report worse health. Finally, those
who are self-employed or parents have lower predicted odds of reporting better health than those
who are not self-employed or child free.
Model 3 tests the second hypothesis by including interaction terms between marital status
and work schedule. The significant interaction terms in Model 3 show that the relationship
between work schedule and health varies by marital status. Although the effect of nonstandard
work schedule on health is not significant among the married (indicated by the nonsignificant
main effect of work schedule), this effect tends to be negative among the cohabiting and
divorced/separated (indicated by the significant interaction effects). The odds of reporting better
health is 34.7% (i.e., (1-0.994*0.657)*100) lower for cohabiting nonstandard workers than

15

Table 2. Odds Ratios of Ordinal Logistic Regression of Nonstandard Work
on Self-Rated Health (N=6774)
Variables
Model 1
Model 2
Model 3
Nonstandard Work Schedule
0.897*
0.898*
0.994
Cohabiting
0.688*** 0.692*** 0.789
Single, never married
0.894
0.935
0.921
Divorced/Separated
0.669*** 0.848*
0.956
Widowed
0.640**
0.936
0.961
Cohabiting X NSWS
Single X NSWS
Divorced/Separated X NSWS
Widowed X NSWS

0.657*
1.018
0.640**
0.889

Female
Race: Black
Race: Other
Age
Education
Some College
HS Diploma or less
Not self-employed
Is a parent
Family Income
$32,300 - $54,000
$55,000 - $80,000
$81,000 - $100,000
$100,030 and higher
Year: 2008
Cut 1
Cut 2
Cut 3

68.74
5.49
0.56

0.878**
0.776**
0.876
0.990***

0.878**
0.775**
0.876
0.990***

0.764***
0.648***
0.849*
0.853**

0.760***
0.650***
0.859*
0.855**

1.207*
1.286**
1.576***
1.700***
0.729***

1.208*
1.295**
1.582***
1.711***
0.727***

160.74
12.52
1.20

153.39
11.92
1.14

AIC
14503.52 14295.74 14291.57
BIC
14558.09 14438.98 14462.09
2
LR Test prob>chi
0.000
0.0161
Notes: Two-tailed tests: ***p<0.001 ** p<0.01, * p<0.05
NSWS = Nonstandard work schedule; AIC = Akaike information criterion;
BIC = Bayesian information criterion

16

Table 3. Odds Ratios of Ordinal Logistic Regression of Nonstandard Work
on Self-Rated Health by Gender
Males
Females
Variables
Model 1 Model 2 Model 3 Model 1 Model 2
Nonstandard Work Schedule
0.919
0.904
0.917
0.869*
0.894
Cohabiting
0.743*
0.744
0.870
0.654** 0.667**
Single, never married
1.031
1.000
0.890
0.787** 0.895
Divorced/Separated
0.736** 0.863
0.994
0.657*** 0.842
Widowed
0.437** 0.562*
0.463*
0.731*
1.053

Model 3
1.092
0.755
0.971
0.951
1.142

Cohabiting X NSWS
Single X NSWS
Divorced/Separated X NSWS
Widowed X NSWS

0.640
0.747
0.616*
0.718

0.626
1.372
0.624
1.730

Race: Black
Race: Other
Age
Education
Some College
HS Diploma or less
Not self-employed
Is a parent
Family Income
$32,300 - $54,000
$55,000 - $80,000
$81,000 - $100,000
$100,030 and higher
Year: 2008
Cut 1
Cut 2
Cut 3

0.01
0.17
1.75

0.825
0.823
1.021
1.02
0.988*** 0.989***

0.746**
0.762*
0.992**

0.747**
0.765*
0.992**

0.689***
0.628***
0.843
0.852

0.686***
0.631***
0.853
0.849

0.819*
0.648***
0.852
0.880

0.821*
0.651***
0.868
0.880

1.19
1.244
1.461**
1.703***
0.640***

1.210
1.264
1.483**
1.728***
0.636***

1.221*
1.332**
1.689***
1.708***
0.811**

1.210
1.342**
1.696***
1.732***
0.809**

0.01
0.06
0.70

0.01
0.07
0.80

0.01
0.11
1.11

0.01
0.12
1.20

0.02
0.19
1.84

Sample Size
3101
3101
3101
3673
3673
AIC
6536.9
6435.6
6432.9
7962.7
7873.4
BIC
6585.3
6556.4
6577.9
8012.3
7997.6
LR Test prob>chi2
0.000
0.031
0.000
Notes: Two-tailed tests: ***p<0.001 ** p<0.01, * p<0.05
NSWS = Nonstandard work schedule; AIC = Akaike information criterion; BIC =
Bayesian information criterion
17

3673
7873.4
8022.4
0.090

cohabiting standard workers. Similarly, the odds of reporting better health are 36.4% (i.e., (10.994*0.640)*100) lower for nonstandard workers who are divorced or separated than their
standard working counterparts. These results also suggest that the relationship between
nonstandard work schedule and health is not significantly different between the single/widowed
and the married.
To test my third hypothesis, I separate the analysis by men and women. The results in
Table 3 suggest that among men, there are no significant interaction relationships. This means
that male, unmarried nonstandard shift workers have the same odds of reporting better health as
their married counterparts. There is also no evidence that work schedule affects men’s health.
Only the main effect for men who are widowed remained a significant predictor of reporting
worse health across all the models. This finding is supported in the literature; for men in
particular, entering widowhood also means losing the health protections marriage provides and
increases their mortality risk (Waite and Gallagher 2000). Although the link between work
schedule and health does not seem to be influenced by men’s marital status, there is a significant
impact among women. Working a nonstandard shift is worse for the health of divorced or
separated women than married women. The odds of reporting better health is 32.7% (i.e., (11.092*0.616)*100) lower for divorced or separated female nonstandard workers than divorced or
separated female standard workers.

18

DISCUSSION
Considering both theoretical perspectives and previous findings, I predicted that
nonstandard work schedules would have a negative impact on a worker’s reported health.
Because marital status influences health in a diversity of ways, I anticipated that the relationship
between work schedule and self-rated health would vary by marital status. I further predicted that
the effect of this moderating relationship would be stronger for women than for men due to the
gender differences that exist for work schedules and marital status. The results indicate support
for all of these hypotheses.
Individuals who work nonstandard schedules have lower odds of reporting good health.
This is expected given that the harm of these irregular shifts on workers’ health can manifest as
biological, psychological, and behavioral consequences. For example, nonstandard shift workers’
poor quality sleep can contribute to ill health (Chung et al. 2009; Geiger-Brown et al. 2012;
Presser 2003a). The disrupted sleep schedules that nonstandard workers experience can change
their circadian rhythm which upsets hormone levels and body temperature (Presser 2003a). Both
men and women employed in shift work have increased alcohol use and are at greater risk of
being obese (Gordon et al. 1986; Kleiner and Pavalko 2010). Nonstandard shift workers are also
at greater risk of having cardiovascular health problems (Harrington 2001; Presser 2003a).
Female shift workers have a larger chance of contracting breast cancer as well as experiencing
menstrual cycle disruptions (Chung et al. 2009). Obviously the work one does will influence
their health, but nonstandard shift workers risk a greater health disadvantage than individuals
working standard shifts.
The relationship between work schedule and health does depend on marital status. The
results indicate that nonstandard workers who are cohabiting and divorced or separated are less

19

likely to report good health than married workers. This finding was anticipated. Individuals who
are pre- or post-marriage engage in more hazardous behaviors. Divorced people have a greater
likelihood for smoking, drinking, fighting, and substance use, but for both men and women who
enter into marriage, this behavior subsides (Umberson 1987; Waite and Gallagher 2000). People
who are divorced, widowed, or single are additionally at greater risk than married people of
dying from various health problems, ranging from cardiovascular disease to cancer to murder
and suicide (Waite and Gallagher 2000).
The moderating effect of marital status is strong for divorced or separated nonstandard
workers. These respondents have lower odds than cohabiters of being unhealthy compared to
married workers which is not surprising given the adverse effect that ending a marriage can have
on health. Williams and Umberson (2004) found that the better health of married persons is more
the result of not experiencing marital dissolution rather than gaining health benefits from
marriage. Individuals who go through divorce are more likely to engage in activities that are
harmful to their health, such as alcohol or drug abuse, and, along with widows, they are less
likely to have regular daily schedules (Umberson 1987). People who are not married display
more mental ailments, worse physical health conditions, and report lower levels of self-assessed
health than their married counterparts (Ross et al. 1990).
The marital relationship is also changing as an increased amount of people cohabit either
before marriage or in place of it. Cohabiting does share some marriage benefits that minimize
detrimental health outcomes, such as sharing resources or expanding one’s social network.
However, married people still enjoy a well-being benefit over cohabiters. Although both groups
see relationship quality decrease over time, cohabiting is not as advantageous to well-being as
being married (Musick and Bumpass 2012). Similar findings are echoed in a study of

20

nonstandard working parents, where married shift workers had greater positive well-being than
their cohabiting counterparts (Liu, Wang, Keesler, and Schneider 2011). My results reflect these
findings. Cohabiters may reap more social support from living together than divorced or
separated people, but they still have lower odds of reporting better health than married people.
This study indicates that the effect that marital status has on the relationship between
work schedule and self-rated health is stronger for women than men. When stratified by gender,
the moderating effect of marital status is only present among women; there is no marital status
difference for men. The health of unmarried women is more greatly affected when working
nonstandard shifts. Specifically, having a nonstandard work schedule is more harmful for the
health of divorced or separated women than married women. Women without the combined
resources and social integration gained from marriage are less likely to be healthy when working
nonstandard schedules.
Not only do unmarried women lack this social support, but the presence of children is
potentially a key factor to explain why the health of divorced or separated nonstandard working
women is affected significantly more than other unmarried women. Children affect a parent’s
decision to engage in a nonstandard work schedule. Female nonstandard shift workers frequently
report that they do shift work due to childcare reasons, and low-income women with young
children are more likely to work a nonstandard shift (Enchautegui 2013; Presser 2003). The
ability to rely on one’s partner for childcare during a nonstandard shift is a more probable option
for married women. When a wife works a different shift from her husband, he is primarily
responsible for taking care of the children (Presser 1999; Presser et al. 2008). For nonstandard
workers, divorced or separated women’s lower odds of being healthy could be due to the

21

decrease of social support from severing their marriage or the presence of children that limits
their better well-being.
Overall, the results suggest that the dynamics between work and health go beyond a
biological relationship. Both physicians and employers need to adopt a biopsychosocial approach
so that when they consider the connection between employment schedule and health they include
marital status as a significant indicator of a worker’s well-being. Social interaction and support
gained from marriage provide health benefits or protection for nonstandard workers, and the
social support and connection that cohabiting and divorced or separated individuals lack when
they are not married is harmful for nonstandard workers’ health.
Additionally, a gendered understanding of this relationship is needed, as divorced or
separated women with nonstandard work schedules have particularly worse health. These
findings are problematic because more women are in the labor force and many are concentrated
in nonstandard jobs. Women without standard work schedules are at a health disadvantage
already, but those who work these shifts and are not married are doubly disadvantaged. Scholars
examining the social complexities of work schedule need to consider marital status in their
research, and more complex studies would also be attuned to gender differences.
Limitations and Future Research
The logistic regression analysis of this data demonstrated the significant role that marital
status and gender play in determining the health of nonstandard workers. Still, there are several
limitations to this dataset. Of primary importance is that this sample is only representative of the
working population. This skews some of the descriptive statistics and restricts any conclusions to
be made about the overall United States population. Additionally, the cross-sectional nature of
the NSCW limits the ability to study trends over time and investigate causation. This would be

22

an important aspect to include in related studies, particularly because certain time-sensitive
variables, such as how long an employee has worked a nonstandard schedule or if a person has
transitioned into or out of marriage, could influence one’s health. Self-rated health is a better
predictor of well-being than medical health measures (Idler and Benyamini 1997), but there are
also a variety of health behavior variables missing from the dataset that would be relevant to
include in this study, such as amount of exercise, smoking and drinking behavior, diet, and
having preexisting health conditions. Nonstandard workers are a self-selective population, and
controlling for these behaviors could help better explain shift worker’s health (Harrington 2001).
The demographic, technological, and economic changes that moved the United States
from a production to a service economy contributed to a rise in nonstandard work schedules
(Presser 1999). As companies continue to hire workers to fill these less desirable shifts, they
need to consider factors that will help protect their workers’ well-being. Furthermore, the current
tension in the United States regarding government-funded healthcare raises the importance for
employers to consider not only biological but also social factors that could compromise the
health of their employees. It is important for future studies to include marital status and gender
when examining how nonstandard work schedules influence health.

23

REFERENCES

24

REFERENCES

Bartley, Mel, Jennie Popay, and Ian Plewis. 1992. "Domestic Conditions, Paid Employment and
Women's Experience of Ill-Health." Sociology of Health & Illness 14(3):313-43.
Berkman, Lisa F., Thomas Glass, Ian Brissette, and Teresa E. Seeman. 2000. “From Social
Integration to Health: Durkheim in the New Millennium.” Social Science and Medicine
51:843-57.
Bird, Chloe E. and Allen M. Fremont. 1991. “Gender, Time Use, and Health.” Journal of Health
and Social Behavior 32(2):114-29.
Chung, Sharon A., Theresa K. Wolf, and Colin M. Shapiro. 2009. "Sleep and Health:
Consequences of Shift Work in Women." Journal of Women's Health 18(7):965-75.
Costa, Giovanni. 1996. "The Impact of Shift and Night Work on Health." Applied Ergonomics
27(1):9-16.
Davis, Kelly D., W. Benjamin Goodman, Amy E. Pirretti, and David M. Almeida. 2008.
“Nonstandard Work Schedules, Perceived Family Well-Being, and Daily Stressors.”
Journal of Marriage and Family 70(4):991-1003.
Durkheim, Émile. [1894] 1997. The Division of Labor in Society. New York: Free Press.
Enchautegui, Maria E. 2013. “Nonstandard Work Schedules and the Well-Being of Low-Income
Families.” Urban Institute, Washington, D.C.
Families and Work Institute, 2004. “National Study of the Changing Workforce Guide to Public
Use Files.” Families and Work Institute, New York, NY.
Fenwick, Rudy and Mark Tausig. 2001. "Scheduling Stress: Family and Health Outcomes of
Shift Work and Schedule Control." The American Behavioral Scientist 44(7):1179-98.
Finn, Peter. 1981. “The Effects of Shift Work on the Lives of Employees.” Monthly Labor
Review 104(10):31-35.
Geiger-Brown, Jeanne, Clark J. Lee, and Alison M. Trinkoff. 2012. “The Role of Work
Schedules in Occupational Health and Safety.” In Robert J. Gatchel and Izabela Z.
Schultz (eds.) Handbook of Occupational Health and Wellness. New York: Springer.

25

Gordon, Nancy P., Paul D. Cleary, Claire E. Parker, and Charles A. Czeisler. 1986. "The
Prevalence and Health Impact of Shiftwork." American Journal of Public Health
76(10):1225-28.
Gove, Walter R. 1973. “Sex, Marital Status, and Mortality.” American Journal of Sociology
79(1):45-67.
Harrington, J.M. 2001. “Health Effects of Shift Work and Extended Hours of Work.” Journal of
Occupational and Environmental Medicine 58:68-72.
Hemstrom, Orjan. 1996. "Is Marriage Dissolution Linked to Differences in Mortality Risks for
Men and Women?" Journal of Marriage and the Family 58(2):366-78.
House, James S., Karl R. Landis, and Debra Umberson. 1988. “Social Relationships and Health.”
Science 241(4865):540-45.
Idler, Ellen L. and Yael Benyamini. 1997. “Self-Rated Health and Mortality: A Review of
Twenty-Seven Community Studies.” Journal of Health and Social Behavior 38(1):21-37.
Kaleta, Dorota, Teresa Makowiec-Dabrowska, and Anna Jegier. 2008. "Employment Status and
Self Rated Health." International Journal of Occupational Medicine and Environmental
Health 21(3):227-36.
Kalleberg, Arne L., Edith Rasell, Naomi Cassierer, Barbara F. Reskin, Ken Hudson, David
Webster, Eileen Appelbaum, and Roberta M. Spalter-Roth. 1997. Nonstandard Work,
Substandard Jobs: Flexible Work Arrangements in the U.S. Washington, D.C.: Economic
Policy Institute.
Kivimaki, Mika, Paivi Kuisma, Marianna Virtanen, and Marko Elovainio. 2001. "Does Shift
Work Lead to Poorer Health Habits? A Comparison between Women who had Always
Done Shift Work with those who had Never Done Shift Work." Work & Stress 15(1):313.
Kleiner, Sibyl and Eliza K. Pavalko. 2010. "Clocking In: The Organization of Work Time and
Health in the United States." Social Forces 88(3):1463-86.
Lillard, Lee A., and Linda J. Waite. 1995. “’Til Death Do Us Part: Marital Disruption and
Mortality.” American Journal of Sociology 100(5):1131-56.
Liu, Hui, and Debra J. Umberson. 2008. "The Times They Are a Changin': Marital Status and
Health Differentials from 1972 to 2003." Journal of Health and Social Behavior
49(3):239-53.
Liu, Hui, Qui Wang, Venessa Keesler, and Barbara Schneider. 2011. "Non-standard Work
Schedules, Work-Family Conflict and Parental Well-Being: A Comparison of Married
and Cohabiting Unions." Social Science Research 40(2):473-84.
26

McMenamin, Terrence M. 2007. "A Time to Work: Recent Trends in Shift Work and Flexible
Schedules." Monthly Labor Review 130(12):3-15.
Mellor, Earl F. 1986. "Shift Work and Flextime: How Prevalent are They?" Monthly Labor
Review 109(11):14-21.
Musick, Kelly, and Larry Bumpass. 2012. “Reexamining the Case for Marriage: Union
Formation and Changes in Well-Being.” Journal of Marriage and Family 74(1):1-18.
Nakata, Akinori. 2012. "Investigating the Associations between Work Hours, Sleep Status, and
Self-Reported Health among Full-Time Employees." International Journal of Public
Health 57:403-11.
Presser, Harriet B. 1995. "Job, Family, and Gender: Determinants of Nonstandard Work
Schedules Among Employed Americans in 1991." Demography 32(4):577-98.
Presser, Harriet B. 1999. “Toward a 24-Hour Economy.” Science 284(5421):1778-79.
Presser, Harriet B. 2003. "Race-Ethnic and Gender Differences in Nonstandard Work Shifts."
Work and Occupations 30(4):412-39.
Presser, Harriet B. 2003a. Working in a 24/7 Economy. New York: Russell Sage Foundation.
Presser, Harriet B. and Virginia S. Cain. 1983. "Shift Work among Dual-Earner Couples with
Children." Science 219:876-78.
Presser, Harriet B., Janet C. Gornick, and Sangeeta Parashar. 2008. “Gender and Nonstandard
Work Hours in 12 European Countries.” Monthly Labor Review 131(2):83-103.
Presser, Harriet B. and Brian W. Ward. 2011. “Nonstandard Work Schedules Over the Life
Course: A First Look.” Monthly Labor Review 134(7):3-16.
Repetti, Rena L., Karen A. Matthews, and Ingrid Waldron. 1989. "Employment and Women's
Health. Effects of Paid Employment on Women's Mental and Physical Health." American
Psychologist 44:1394-1401.
Ross, Catherine E., John Mirowsky, and Karen Goldsteen. 1990. "The Impact of the Family on
Health: The Decade in Review." Journal of Marriage and the Family 52(4):1059-78.
Ross, Catherine E. and Chia-ling Wu. 1995. “The Links between Education and Health.”
American Sociological Review 60(5):719-45.
Ross, Catherine E. and John Mirowsky. 1995. “Does Employment Affect Health?” Journal of
Health and Social Behavior 36(3):230-43.

27

Seeman, Teresa E. 1996. “Social Ties and Health: The Benefits of Social Integration.” Annals of
Epidemiology 6(5):442-51.
Sorensen, Glorian and Lois M. Verbrugge. 1987. “Women, Work, and Health.” Annual Review
of Public Health 8:235-51.
Springer, Kristen W. 2010. “Do Wives’ Work Hours Hurt Husbands’ Health? Reassessing the
Care Work Deficit Thesis.” Social Science Research 39:801-13.
Umberson, Debra. 1987. "Family Status and Health Behaviors: Social Control as a Dimension of
Social Integration." Journal of Health and Social Behavior 28(3):306-19.
Umberson, Debra. 1992. “Gender, Marital Status and the Social Control of Health Behavior.”
Social Science and Medicine 34(8):907-17.
Waite, Linda J. 1995. “Does Marriage Matter?” Demography 32(4):483-507.
Waite, Linda, and Maggie Gallagher. 2000. The Case for Marriage: Why Married People are
Happier, Healthier, and Better Off Financially. New York: Doubleday.
Wight, Vanessa R., Sara B. Raley, and Suzanne M. Bianchi. 2008. "Time for Children, One's
Spouse and Oneself among Parents Who Work Nonstandard Hours." Social Forces
87(1):243-71.
Zeytinoglu, Isik Urla and Jacinta Khasiala Muteshi. 2000. “Gender, Race and Class Dimensions
of Nonstandard Work.” Industrial Relations 55(1):133-65.

28