Linking perceived discrimination during adolescence to health during middle adulthood:
The mechanisms through self-esteem and risk behaviors
Tse-Chuan Yang, Ph.D.† I-Chien Chen, Ph.D. Candidate.‡ Seung-won Choi, Doctoral Student.‡
†
Department of Sociology, University at Albany, State University of New York
‡
Department of Sociology, Michigan State University
[Please Do Not Cite without Authors’ Consent]
Introduction
Perceived discrimination refers to an individual’s experience of receiving unfair
treatment due to his/her characteristics, such as age, gender, and race/ethnicity. In the past
decade, perceived discrimination has been found to be adversely related to mental and physical
health outcomes 1-4. However, little is known about the mechanisms through which perceived
discrimination affects health and even less is explored about how long the detrimental effect
could last. More explicitly, the existing literature on the relationship between perceived
discrimination and health has three gaps, which will be filled by this study. First, relatively few
studies used longitudinal data to examine the long-lasting impact of perceived discrimination
on health. Applying a meta-analysis to 134 published studies, Pascoe and Richman 5 concluded
that “few studies to date have been able to draw causal conclusions about the relationship
between perceived discrimination and physical or mental health because of the cross-sectional
designs of most of the research in this area” (p.545). Their conclusion highlights the importance
of investigating the causality between perceived discrimination and health outcomes. Without the
longitudinal data, it is also plausible that unhealthy people tend to be more sensitive to the
behaviors/treatments they receive than their healthy counterparts, which makes them report more
perceived discrimination.
Second, the mechanisms linking perceived discrimination and health over time are
underexplored. There is a growing interest in investigating the mechanisms between perceived
discrimination and health 3,6 but the mechanisms have not been situated into a longitudinal
research design. For example, Pavalko and colleagues 7 found that women’s functional
limitations (e.g., having problems with daily activities) were affected by the discriminatory
experience reported 7-9 years ago and this effect remained even after accounting for prior
emotional health, physical health, and other socioeconomic characteristics. Within the 7-9 years,
it is unclear whether respondents adopted any behaviors or changed their attitude to cope with
the discriminatory experience. The potential changes in behaviors or attitude may imply the
mechanisms through which perceived discrimination affects health. Third, the existing causal
evidence was not drawn from nationally representative data. Most of the studies with a
longitudinal perspective focused on specific population, such as women 7 and minority groups 810
. The generalizability of their findings is limited.
The goal of this study is to address these issues with the National Longitudinal Survey of
Youth 1979 (NLSY79), a nationally representative survey that has been administered by the
Bureau of Labor Statistics since 1979. We will examine three interrelated research hypotheses to
reach the goal: (1) The discriminatory experience during adolescence imposes an adverse impact
on one’s health during middle adulthood; (2) The perceived discrimination during adolescence
reduces one’s self-esteem during early adulthood, which in turn undermines the health during
middle adulthood; and (3) The discriminatory experience promotes risk behaviors in early
adulthood and the risk behaviors compromise the health during middle adulthood. Figure 1
shows the mechanisms linking perceived discrimination during adolescence to health during
middle adulthood. Below we discuss the data and method used in this study, followed by the
preliminary results.
Data and Method
The NLSY79 will be the major data source for this study and it was first administered in
1979 with 12,686 respondents aged 14-22 11. The respondents were followed annually through
1994 and biennially since then. The NLSY79 has maintained a very high response rate in each
wave and had considerable sample retention for such a long-term follow-up period. This study
uses the following waves: 1979, 1980, 1987, 1998, and 2010. The data in 1979 and 1980 are
defined as adolescent and the information collected in 1987 and 1998 were obtained for early
adulthood. When observed in 2010, the NLSY79 participants were between the ages of 41 and
49 and all of them took the 40-year-old health module where a range of health outcomes were
measured. Following the framework in Figure 1, we categorized the variables used in this study
into four groups: dependent variable, treatment variable, mediating variables, and control
variables. They are explained as follows.
Dependent variables: We measured one’s health during middle adulthood with the shortform 12-question (SF-12) summary scores to assess the overall physical and mental health,
respectively, when respondents first answered the 40 year-old health module. The NLSY79 40year-old health module adopted the method developed by Ware et al. 12 to calculate the SF-12
physical component and SF-12 mental component summary scores. We treated the concept of
health as a latent variable and the physical and mental component scores were the observed
indicators for health. The reliability and validity of the SF scales can be found elsewhere 13-15
Treatment variable: The treatment variable of this study is perceived discrimination. In
1979, respondents were asked whether they perceived discrimination when getting a job due to
any of following five factors: race/ethnicity, nationality, sex, age, and language. Those who
answered “yes” to this question were coded 1, otherwise 0. It should be noted that while the
measure of perceived discrimination is relatively rough, it has been commonly used by federal
agencies, such as the Centers for Disease Control and Prevention.
Mediating variables: To examine our hypotheses, respondents’ self-esteem scores in
1980 and 1987 were considered in the analysis. The NLSY79 adopted Rosenberg’s self-esteem
scale 16, which has been commonly used in the literature 17,18. Self-esteem has been found to be
associated with both discrimination and health. Specifically, discriminatory experience is
negatively related to self-esteem 19 and low self-esteem negatively affects health 20-22. Given
these relationships, we propose that self-esteem itself may mediate the relationship between
perceived discrimination and health. As self-esteem has been found to be consistent over time
23,24
, we applied the sequential mediation mechanism to 1980 and 1987 self-esteem scores,
namely the self-esteem in 1987 can be predicted by that in 1980.
The other mechanism is through risk behaviors. Specifically, in 1998, the NLSY79
respondents were asked if they have had the following four behaviors that may negatively affect
health: smoking, marijuana use, cocaine use, and the use of other sedatives. We created a
composite score ranging from 0 to 4, and the number indicated how many behaviors of these
four a respondent reported. Risk behaviors have been found to be positively associated with
discriminatory experience 25,26 and these behaviors inevitably affect one’s health in the long run.
Control variables: Beyond the key variables above, we consider the following control
variables in our analysis to better examine the mechanisms proposed in this study. One’s
baseline (1979) demographics and family background were first considered, including
respondent’s gender (females coded 1, males 0), race/ethnicity (non-Hispanic white as the
reference group, non-Hispanic black, and Hispanics), and both paternal and maternal years of
education. In addition, at different survey years, we further included a range of individual
socioeconomic and demographic variables that changed over time, such as respondent’s
educational attainment (or enrollment status), family income (natural logarithm transformed),
and marital status (married coded 1, otherwise 0).
Analytic approach: Given the nature of the longitudinal data and our research hypotheses,
we examined the framework in Figure 1 with the structural equation modeling (SEM) approach
to simultaneously estimate the relationships among these concepts/factors and to examine the
two mechanisms. To implement the SEM models, we used MPlus 7.0 27 and the full information
maximum likelihood estimation method that takes missing values into account. We first assessed
whether the variables chosen above help us to build a well-specified measurement model (for
health) and then estimated the effects of the mechanisms in Figure 1. With respect to model fit
diagnostics, since there is not agreement on which index performs best, a range of model fit
indices will be used to understand if the proposed research framework fits the NLSY79 data well,
such as comparative fit index (CFI) and root mean square error of approximation (RMSEA).
Results
Figure 2 demonstrates the estimated effects of the pathways in our framework and the
results provided preliminary support for our hypotheses. We summarized the important findings
as follows. First, after controlling for other potential covariates, as well as the two pathways, we
found that perceived discrimination during adolescence adversely affect one’s health during
middle adulthood and this effect remains statistically significant. More specifically, the
respondents experienced discrimination when they were 14-22 years old and this experience still
undermined their health when respondents were 41-49 years old. Our finding suggests that the
detrimental effect of perceived discrimination on health lasts for approximately 30 years, which
confirms our first hypothesis. To our knowledge, no study reported an effect of perceived
discrimination on health that is longer than two decades. This finding sheds new light on the
literature on discrimination and health.
Second, self-esteem seems to play an important role in transmitting the effect of
perceived discrimination during adolescence on the health during middle adulthood. Explicitly,
the SEM results indicate that experiencing discrimination in 1979 decreases one’s self-esteem in
1980, which subsequently hinders the self-esteem in 1987. The self-esteem in 1987 ultimately
contributes to the health measured when respondents turned 40s. It should be noted that in SEM
the effect of each pathway can be multiplied to get the so-called “indirect” or “mediation”
effect27. As only the effect of perceived discrimination on the 1980 self-esteem is negative (in
Figure 2, β= -0.379), the overall mediation effect from perceived discrimination to health
through self-esteem is negative. That being said, those who reported discrimination in 1979 had
lower self-esteem in 1980 and 1987 in contrast to their counterparts without such experience; the
relatively low self-esteem resulted in poor health during middle adulthood. The total impact
through this mechanism is -0.009 (-0.379*0.404*0.058). We also noted that the 1987 self-esteem
was not directly affected by perceived discrimination, which underscores the importance of the
sequence between self-esteem scores. The findings here directly bolster the second hypothesis
that the perceived discrimination during adolescence imposes a negative effect on the health
during middle adulthood through self-esteem during early adulthood.
Third, we found strong support for the mechanism through risk behaviors as individuals
who experienced discrimination in 1979 were more likely to engage in risk behaviors (β=0.174)
than those who did not have discriminatory experience. Risk behaviors, in turn, reduced one’s
health in 2010. The overall impact of perceived discrimination on the health during middle
adulthood is -0.109 (0.174*-0.628), which is more than 10 times stronger than the overall effect
through self-esteem. The finding confirms our third hypothesis and, again, highlights the longlasting effect of perceived discrimination on both risk behaviors during early adulthood and
health during middle adulthood.
It should be emphasized that the coefficients estimates in Figure 2 were obtained from the
model where control variables were included. The CFI of the model is 0.881 and the RMSEA is
0.033. Both diagnostic indicators suggest that the model fits out data appropriately. In addition to
the key findings above, we also provided the detailed coefficient estimates in Table 1. Several
findings drawn from the control variables echo the literature, indicating that our findings are
reliable. For example, family income is positively related to health and being married provides a
protective effect on health. Both paternal and maternal educational attainments affect
respondents’ self-esteem and risk behaviors in the expected direction.
Table 1. Preliminary SEM Results of the Research Framework and Hypotheses
Estimate
Self-esteem in 1980
Perceived discrimination in 1979
-0.379 *
Female (=1)
-0.616 **
Blacka
0.464 *
Hispanic
0.784 **
Maternal education
0.216 ***
Paternal education
0.052
Respondent’s educational attainment in 1980
1.068 ***
Self-esteem in 1987
Perceived discrimination in 1979
0.024
Self-esteem in 1980
0.404 ***
Maternal education
0.062
Paternal education
0.033
Respondent’s educational attainment in 1987
0.543 ***
Family income in 1987 (Ln)
0.576 ***
Risk behaviors in 1998
Perceived discrimination in 1979
0.174 ***
Female (=1)
-0.042
Blacka
-0.078
Hispanic
-0.084
Maternal education
0.001
Paternal education
0.033 ***
Respondent’s educational attainment in 1998
-0.126 ***
Marital status in 1998 (1=married)
-0.170 **
Family income in 1998 (Ln)
-0.053
Health
Perceived discrimination in 1979
-0.469 *
Risk behaviors in 1998
-0.628 ***
Self-esteem in 1980
0.088 **
Self-esteem in 1987
0.058 *
Female (=1)
-1.111 ***
Blacka
0.558 *
Hispanic
0.315
Respondent’s educational attainment turning 40
0.051
Family income when turning 40 year-old (Ln)
0.987 ***
Marital status when turning 40 year-old (1=married)
0.622 *
a
Notes. White as a reference group.
*p < 0.05; **p < 0.01; ***p < 0.001.
S.E.
(0.182)
(0.183)
(0.211)
(0.272)
(0.043)
(0.033)
(0.126)
(0.171)
(0.023)
(0.040)
(0.033)
(0.127)
(0.109)
(0.047)
(0.047)
(0.065)
(0.065)
(0.012)
(0.009)
(0.034)
(0.062)
(0.034)
(0.238)
(0.144)
(0.027)
(0.028)
(0.219)
(0.274)
(0.256)
(0.164)
(0.234)
(0.270)
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