Race-specific associations between health-related quality of life and cellular aging among adults in the United States: evidence from the National Health and Nutrition Examination Survey
Race-specific associations between health-related quality of life and cellular aging among adults in the United States: evidence from the National Health and Nutrition Examination Survey
Rumana J. Khan 0
Samson Y. Gebreab 0
Pia R. Crespo 0
Ruihua Xu 0
Amadou Gaye 0
Sharon K. Davis 0
0 Genomics of Metabolic, Cardiovascular and Inflammatory Disease Branch, Social Epidemiology Research Unit, National Human Genome Research Institute, National Institutes of Health , 10 Center Drive, Room 7N316, MSC 1644, Bethesda, MD 20892 , USA
Purpose Poor health-related quality of life (HRQOL) could lead to higher morbidity and mortality through telomere attrition or accelerated cellular aging. We conducted a cross-sectional analysis to examine the relationship between four dimensions of HRQOL and leukocyte telomere length (LTL) among a nationally representative sample of 3547 US adults (C20 years) using the data from the 2001-2002 National Health and Nutrition Examination Survey. Method We used HRQOL survey information collected on individuals' self-rated general health, recent physical health, recent mental health, and recent activity limitation. Telomere length was assessed using quantitative polymerase chain reaction. Multiple linear regressions were used to estimate the relationship between each dimension of HRQOL and log-transformed values of LTL with adjustment for sample weights and design effects. Results HRQOL-race interactions were significant, and the results were stratified by race. After controlling for demographic factors, disease conditions, and lifestyle variables, worse general health was significantly associated with shorter LTL for Blacks (coefficient, b: -0.022, 95% Confidence Interval, 95% CI: -0.03 to -0.01), but not for
Health-related quality of life; Perceived health status; Leukocyte telomere length; Aging; Race
Whites or Mexican Americans. Unwell physical health was
associated with shorter telomere length for Whites (b:
-0.005, 95% CI: -0.01 to -0.001) only. Unwell mental
health showed no significant association with LTL in any
Conclusions Although longitudinal studies are needed to
prove causality, our findings suggest that HRQOL could be
associated with LTL shortening. We also found a possible
racial difference in this association and recommend
additional multiethnic studies to confirm this and to understand
the reasons and consequences of this difference.
Health-related quality of life (HRQOL), which is defined
as ‘‘perceived or self-rated physical and mental health
over time,’’ provides a subjective weighting of health
conditions and provides an indication of the economic and
psychosocial burden of an individual’s level of health that
are often overlooked by traditional disease measures
[1, 2]. While measures of disease and mortality are
crucial, they indicate little about other important aspects of
an individual’s level of health, including related economic
and psychosocial elements such as the impact of health
problems on quality of life, pain and suffering, social
discrimination, social and role functioning, economic
burden, health perceptions, and life satisfaction. . To
bridge this gap between traditional health measures and
overall wellbeing, the concept of HRQOL was put
forward by the World Health Organization as
comprehensive, easy, and low-burden measures to explore
healthrelated quality of life as broader measures of population
health status [2, 3].
Studies show that inferior HRQOL predicts morbidity
and mortality even after accounting for important health
risk factors [4–11]. However, the molecular or cellular
mechanisms through which HRQOL may contribute to
poorer health outcomes are not well understood. Several
studies have indicated shorter leukocyte telomere length
(LTL) to be associated with increased risk of mortality and
various disease conditions, including immune response and
infection-related diseases, diabetes, hypertension, cancer,
and atherosclerosis and other cardiometabolic disorders,
dementia, and cancers [12–18]. Therefore, LTL may
provide the biological link between economic and
psychosocial burden related to HRQOL and different health
Human telomeres are nucleoprotein structures located at
the ends of chromosomes and protect them from
degradation, fusion, and recombination in somatic cells [19, 20].
LTL generally shortens progressively with every cell
division over the lifespan and, thus, telomere shortening is
strongly associated with age in most somatic tissues and
telomere length typically declines with age [21, 22].
Although genetic and epigenetic factors play important
roles to determine early life LTL, evidence suggests that
multiple environmental factors, which lead to cellular
stress, oxidation, and inflammation, may also affect LTL in
adulthood [23, 24]. For example, prolonged states of
mental stress and adverse psychological conditions, such as
depression and post-traumatic stress disorders, have been
found to be associated with shorter telomere length in
many occasions [25–30]. No studies of which we are aware
have investigated the exact association between HRQOL
with LTL. But comparable indicators such as various forms
of chronic psychosocial stressors—life stress, low
socioeconomic status, racial discrimination, social interactions,
perceived social control across different health-relevant
domains, and perceived unfair treatment—were shown to
be associated with telomere shortening in several studies
[31–40]. The underlying mechanisms by which these
factors affect LTL are not fully understood, but as stated
earlier, they may contribute to shorter LTL by increasing
oxidative stress and inflammation—two biological
mechanisms that are known to cause accelerated LTL shortening
It is often suggested that low HRQOL is indicative of
low psychosocial functioning and aggravated psychosocial
stress . Wolkowitz et al. observed that biological
derangements seen in chronic stress (e.g., inflammation,
oxidative stress, and perhaps changes in steroids) are
associated with, and may cause, telomere shortening
through greater cellular and genomic damage, and depleted
repair and protection process [42, 43]. Therefore, it is
possible that HRQOL could lead to multiple biological risk
factors, higher disease morbidity, and mortality, partly
through accelerating premature aging of cells. Since
HRQOL may impact health by altering health behaviors, it
is also possible that rather than being causally related,
HRQOL leads to telomere shortening through third factors
common to both, such as life style factors like lack of
physical activity, cigarette smoking, alcohol drinking, poor
sleep, and poor nutrition. [44–46]. Therefore,
understanding the relationships between HRQOL and LTL has the
potential to elucidate if the impact of quality of life-related
factors on life-shortening diseases could partly be
explained by telomere biology. Additionally, this can also
provide insight into if interventions targeting the
improvement of quality of life-related factors might
simultaneously be effective in aiding telomere maintenance
or lengthening. Because HRQOL has the ability to capture
important economic and psychosocial elements beyond
mere health status, this will also enable us to have an idea
about the impact of these elements on telomere shortening.
Moreover, it is also important to know whether there are
differences in this association by race, because, although
the majority of studies reported a pattern of Blacks having
longer LTL than Whites [47–49], cumulative exposure to
multiple sources of psychosocial stressors over the
lifecourse has been suggested as possible contributors to faster
LTL shortening with age in Blacks than in Whites .
In this study, we hypothesized that poorer perceptions of
quality of life were associated with greater cellular aging or
shorter LTL, and examined the cross-sectional associations
between four dimensions of HRQOL and LTL by race
among 3547 nationally representative sample of US adults
(C20 years) using the data from the 2001–2002 National
Health and Nutrition Examination Survey (NHANES) after
adjusting for individual-level risk factors.
We used the data of the 2001–2002 NHANES, which was
conducted between January 2001 and December 2002 in
5411 adult individuals (age C20 years). NHANES is a
nationally representative survey that uses a complex,
stratified, multistage probability sampling design. The
detailed description of the survey methodologies and
analytic guidelines have been reported elsewhere . In total,
our analysis included 3547 White, Black, and Mexican
American participants (flowchart: supplementary chart 1).
The NHANES datasets are de-identified and available in
the public domain. This study was exempted from human
subject review by the National Institutes of Health Office
for Human Subjects Research Protections (OHSRP13100).
The data analysis was done in 2016.
HRQOL was determined using the validated four-dimension
HRQOL-4 questionnaire, developed by the Centers for
Disease Control and Prevention . This HRQOL-4
questionnaire has demonstrated reliability and validity for
population health surveillance [52–55]. The survey asked
participants about their overall perceived general health, and
the number of unwell days in the past 30 days due to poor
physical health, mental health, or activity limitation.
Perceived or self-rated health was ascertained by response to
the question ‘‘In general, would you say your health is:
excellent, very good, good, fair, or poor?’’ Given the low
frequency of the ‘‘excellent’’ and ‘‘poor’’ responses, we
combined ‘‘excellent’’ with ‘‘very good’’ and ‘‘fair’’ with
‘‘poor.’’ Thus, the scales were re-categorized into three
groups: ‘‘excellent’’ (excellent ? very good), ‘‘good,’’ and
‘‘poor’’ (fair ? poor), with ‘‘excellent’’ being the reference
group for analysis. Physical unwell days were defined by the
question ‘‘Now thinking about your physical health, which
includes physical illness and injuries, for how many days
during the past 30 days was your physical health not
good?’’; mental unwell days by ‘‘Now thinking about your
mental health, which includes stress, depression, and
problems with emotions, for how many days during the past
30 days was your mental health not good?’’; and limited
activity days by ‘‘During the past 30 days, for about how
many days did poor physical or mental health keep you from
doing your usual activities, such as self-care, work, or
recreation?’’ The total number of unwell days (physical and
mental and limited activity) was grouped into 0, 1–15, and
16–30 days, where 0 day served as the reference group .
The detailed survey questions and their re-categorization are
presented in Supplementary chart 2. The Cronbach’s alpha
was 0.713 for the HRQOL-4 instrument .
All participants aged 20 years and older, who were
examined in 2001–2002 and who had blood collected for
DNA purification, were eligible for LTL quantification.
LTL relative to standard reference DNA (T/S ratio) was
measured using the quantitative polymerase chain reaction
method . The formula to convert T/S ratio to base pairs
(bp) was 3274 ? 2413 9 (T/S) [58, 59]. Detailed
analytical methods are documented on the NHANES website
[51, 60]. The quality control procedure is summarized in
the Supplementary section.
Self-reported race information was used. Participants were
asked what race (‘‘White,’’ ‘‘Black,’’ ‘‘Mexican American,’’
or ‘‘Other race,’’ which included mixed race, Asian, and
other Hispanic) they belonged to. For the current analysis,
the ‘‘Other race’’ category was not considered, because
respondents only formed about 6% of the total available
sample and, more importantly, their race was not as clearly
specified as other major races (flowchart: supplementary
chart 1). Age was calculated in years. Educational
attainment was dichotomized as less than high school and high
school or more. Marital status was categorized as
married/partnered and not married/partnered. Smokers were
defined as smoking C100 cigarettes during lifetime.
Participants were considered physically active if they were
involved in vigorous activity over the past 30 days (yes/no).
Alcohol consumption was defined as having at least 12
drinks in any one year. Body mass index or BMI (weight in
kg/height in meter2) was calculated using height and weight
measurements. The cut point of 30 or higher was defined as
obesity . Information on existing chronic disease
conditions (yes/no) including diabetes, high blood pressure,
congestive heart failure, and cancer or malignancy was
To account for the complex survey design (strata and
primary sampling unit indicators), we used Stata Version 12
software’s ‘‘svy’’ survey data commands (Stata Corp.,
College Station, TX) and applied NHANES sample
weights for the genetic subsample for all analysis [51, 60].
These weights additionally account for survey
non-response (note: supplementary chart 1) [51, 60]. Each
variable was assessed for outliers and normal distributions.
Weighted means with 95% confidence interval (95% CI)
and weighted proportions with 95% CI were calculated for
continuous and categorical variables, respectively, within
each racial category. Additionally, age-adjusted LTL was
derived using regression coefficient and summarized by
race. For descriptive results, non-overlapping 95% CIs
indicate statistical significance.
Multiple linear regressions were used to estimate the
relationship between LTL and each of the four dimensions
of HRQOL (perceived general health, unwell days due to
poor physical health, poor mental health, or activity
limitation). We sequentially controlled for demographic factors
(age, sex, education, marital status), disease conditions
(cancer, hypertension, diabetes, obesity, heart failure), and
lifestyle variables (smoking, physical activity, and alcohol
intake), respectively, in models 1, 2, and 3. Given prior
evidence of race/ethnic differences in perceived health
status and LTL, we estimated models stratified by race
. We also tested for the statistical interactions between
four dimensions of HRQOL and race on LTL. To examine
the variation by gender, interaction between HRQOL and
Table 1 Demographic characteristics and telomere length of US adult population by race (National Health Interview Survey, 2001–2002,
N = 3547)
White (N = 2090)
Black (N = 669)
Mexican American (N = 788)
69.57 (66.99–72.16) 47.64 (43.98–51.23) 70.49 (65.53–75.27)
5854.34 (5741.23–5967.45) 6001.31 (5858.69–6143.92) 5900.65 (5818.87–5982.42)
5864.35 (5845.96–5882.75) 5940.27 (5916.00–5964.55) 6008.86 (5984.47–6033.24)
51.68 (46.35–57.01) 43.77 (38.82–48.72) 42.00 (36.92–47.08)
76.59 (67.26–85.92) 59.65 (52.48–66.83) 67.16 (62.45–71.88)
39.38 (35.26–43.49) 30.94 (26.25–35.63) 33.75 (29.29–38.21)
29.57 (26.28–32.85) 40.56 (36.16–44.95) 29.91 (24.59–35.24)
6.82 (5.74–7.90) 10.75 (8.04–13.45) 8.72 (7.62–9.81)
25.71 (22.82–28.59) 36.88 (33.62–40.14) 11.96 (10.38–13.55)
1.98 (1.05–2.92) 2.91 (1.41–4.41) 1.09 (0.3–1.88)
9.97 (8.09–11.86) 3.24 (2.37–4.11) 1.79 (0.73–2.86)
Analyses were done with adjustment for sample weights and design effects
Data represent percentage (95% confidence interval), except where noted
a Mean (95% confidence interval)
b Calculated using formula ‘‘3274 ? 2413 9 T/S ratio (telomere length relative to standard reference DNA)’’
c Derived using regression coefficient for age
d Defined as body mass index (weight in kg divided by height in meter square) of 30 or higher
gender was also checked. To evaluate the interactions, we
added main effects and cross-product terms to the
regression after adjusting for all the variables mentioned
previously. P value for each interaction term and F tests
comparing full and reduced models (with and without the
interaction term) were used to test the statistical
significance of the interaction terms. LTL was transformed by
natural logarithm before regression to improve normality
and stabilize the variance. Therefore, we report the
percentage change (unstandardized regression coefficient) in
the average value of LTL (the outcome variable) for each
dimension of HRQOL. Because of the exploratory nature
of all the analyses, no correction for multiple testing was
conducted [62, 63] and statistical significance was defined
as a P value \ 0.05.
We found no evidence of effect modification by sex
affecting associations between HRQOL and LTL.
Consistent with our hypothesis, HRQOL-race interaction remained
significant (findings summarized in the supplementary
section) for recent days of unwell physical health (p \ 0.05)
and perception of self-rated general health (p value \ 0.05);
hence, we present our result stratified by race. The weighted
distributions of study population characteristics from the
NHANES of 2001–2002 are shown in Table 1. Of the 3547
participants with ages ranging from 20 to 85 (mean age 49)
years, 2090 (58.92%) were White, 669 (18.86%) Black, and
788 (22.22%) Mexican Americans. Whites were older
(mean age 46.89, 95% CI: 45.71–48.08) than Blacks (mean
age 41.99, 95% CI: 40.42–43.56) or Mexican American
(37.57, 95% CI: 35.99–39.14). They were also more
educated than the other two races. About 70% of the Whites and
Mexican Americans were either partnered or married
compared to only 47% of the Blacks. Whites were more
likely to smoke, drink alcohol, and be involved in physical
activities than the participants of the other two races. Blacks
had higher prevalence of obesity, diabetes, hypertension,
and congestive cardiac failure than Whites or Mexican
Americans, but were less likely to have had cancer than
Whites. Blacks had longer LTL (mean 6001.31 bp, 95% CI:
5858.69–6143.92) than Whites (mean 5854.34 bp, 95% CI:
Table 2 Proportions of
responses to four dimensions of
health-related quality of life
(HRQOL) questions of US adult
population by race (National
Health Interview Survey,
2001–2002, N = 3547)
White (N = 2090)
Black (N = 669)
Mexican American (N = 788)
Analyses were done with adjustment for sample weights and design effects
Data represent percentage (95% confidence interval)
5741.23–5967.45) or Mexican Americans (mean
5900.65 bp, 95% CI: 5818.87–5982.42). However,
according to the age-adjusted predicted values of LTL,
Mexican Americans had longer LTL than Whites or Blacks.
Table 2 presents race-specific proportions of
participants reporting each dimension of HRQOL. Whites were
more likely to report better general health than the other
two races. Approximately 58% of whites reported having
either excellent or very good general health compared to
37.67% of Blacks and 28.39% of Mexican Americans. This
pattern, however, was not observed for measures related to
‘‘unwell days.’’ Individuals of all three races reported
similar proportions of ‘‘unwell days’’ (0, 1–15, and
16–30 days) due to physical health, mental health, and
Figure 1 portrays descriptive relationships between four
different dimensions of HRQOL and estimated mean LTL
by race. Participants reporting excellent general health had
longer LTL compared to participants reporting good or
poor general health. This pattern of decreasing LTL with
worsening of perceived general health for all Blacks and
Whites was distinct in Fig. 1. For perceived physical
health, this pattern remains true only for the Whites, where
LTL decreased with increased numbers of physically
unwell days. No evident pattern was observed for unwell
days related to mental health or activity limitation.
The adjusted associations between different HRQOL
measures and log-transformed LTL, estimated from
multivariate regression models, are presented in Table 3. In
ageand demographic-adjusted model, worse perception of
general health was significantly associated with shorter LTL
for Blacks (regression coefficient, b: -0.021, 95% CI:
-0.032 to -0.010, p value 0.001), but not for White or
Mexican Americans. The association remained significant
(b: -0.022, 95% CI: -0.033 to -0.011, p value 0.001) after
adjustment for other disease and lifestyle variables. Thus,
according to the fully adjusted model, having a ‘‘good’’
perception of general health was significantly associated
with 2.2% shorter LTL compared to an ‘‘excellent’’
perception about general health for Blacks. No such association
was observed for ‘‘poor’’ perception of general health. For
Whites, recent days of unwell physical health was associated
with shorter LTL. Those having 1–15 physically unwell days
in the last 30 days were more likely to have 0.5% shorter
LTL than those reporting 0 physically unwell days (b:
-0.005, 95% CI: -0.01 to -0.001, p value 0.034). Having
1–15 physically unwell days was also marginally associated
with shorter LTL for Blacks (b: -0.009, 95% CI: -0.019 to
0.001, p value 0.061). However, those reporting 16–30
physically unwell days in last 30 days showed no association
with shorter LTL. No associations were observed with other
HRQOL measures, such as mental unwell days or days with
usual activity limitations for any of the races.
The main aim of this study was to determine the nature of
the race-specific association between perceived health
status as defined by four dimensions of HRQOL-4 and LTL
General health Limited in usual ac vi es
Fig. 1 Estimated mean
leukocyte telomere length of US
adults by race and four
dimensions of health-related
quality of life (National Health
Interview Survey, 2001–2002,
N = 3547). Base pairs (bp)
were calculated using the
formula ‘‘3274 ? 2413 9 T/S
ratio (telomere length relative to
standard reference DNA).’’
Mean calculated with
adjustment for sample weights
and design effects. Limit lines
indicate 95% confidence
Mexican Am Mexican
using a large and nationally representative sample while
adjusting for an array of potential confounders. Consistent
with the hypothesis, our results indicated that negative
perception of self-rated general health and unwell days due
to recent poor physical health were associated with greater
cellular aging as indexed by shorter LTL. One to 15 days
of unwell physical health was significantly associated with
shorter LTL in Whites, while for Blacks the association
was relatively weaker and did not reach a conventional
level of significance. The other dimension, ‘‘good’’
perception of general health, was strongly associated with
shorter LTL for Blacks compared to ‘‘excellent’’
perception. We, however, found no such relationship for ‘‘poor’’
perception of general health. No association was observed
between unwell days due to poor mental health or activity
limitations due to poor physical or mental health and LTL
for any race.
HRQOL reflects subjective perception of health-related
quality, and several community-based studies have
reported a relationship between HRQOL and mortality, defined
by chronological age at death [5–11]. Most of these studies
had participants from a selected group of sample, mainly
elderly population or hospitalized and critically ill patients.
We not only have extended these findings in a
representative general population, but also have used LTL as
outcome, which has emerged as a potential biomarker and
causative agent of aging at the cellular level . Two
dimensions of HRQOL-4, negative perception of general
health for Blacks and unwell days due to recent poor
physical health for Whites, were associated with shorter
LTL in our study. The associations remained after
adjusting for several important lifestyle variables and disease
conditions. This suggests that the links are independent and
perhaps reflect the impact of important economic and
psychosocial elements on aging that HRQOL captures
beyond objective health assessments. Such elements like
interpersonal chronic stressors, varying reaction to health
conditions, socioeconomic position, social engagement,
economic burden, poor neighborhood conditions, and lack
of resources, individually or collectively, can cause
repeated and prolonged neuroendocrine, immune, and
metabolic regulatory system disruptions causing oxidative
stress, inflammation, and inhibition of DNA repair. Since
telomeres are particularly sensitive to damage by oxidative
stress because of the high guanine content in telomere
sequences, this may accelerate leukocyte telomere
shortening by promoting cell turnover and replicative
Though perceived general and physical health had the
expected relationship with LTL, the relationship with
mental health was less consistent and not significant.
Perceived stress has been linked to oxidative DNA damage in
leukocytes and telomere shortening in [66–69].
Populationbased studies have also reported significant association of
individual-level psychological factors, such as social
stressors, greater anxiety symptoms, and depression with
shorter LTL . In contrast to this, we observed no
associations between unwell days due to poor mental and
LTL. No studies of which we are aware have exactly
investigated the association between mentally unwell days
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and LTL. The closest we found were studies which used
the same mental health measure as ours and examined its
association with mortality. Interestingly, similar to our
findings, they also reported no significant impact of
perceived mental health as measured by unwell days count on
mortality [71–73]. Taken together with these findings, our
results might indicate that as a HRQOL measure, unwell
days count past one month probably does not capture the
actual stress level or mental health of an individual. The
dilution of the strength of association could also be due to
recall bias associated with the mental health question.
Evidence suggests that one-time cross-sectional population
surveys are potentially susceptible to recall bias and may
consistently underestimate the prevalence of mental
disorders . Alternatively, the underestimation could also
be due to the influence of a substantial level of stigma that
is still linked to mental disorders .
We observed poorer perception of general health to be
strongly associated with shorter LTL in Blacks. No
association, however, was found in Whites or in Mexican
Americans. Having a ‘‘good’’ perception of general
health was significantly associated with 2.2% shorter
LTL compared to an ‘‘excellent’’ perception about
general health, which is roughly equivalent to about
3–5 years of aging on average (calculation provided in
the supplementary section) [76, 77]. Since subjective
evaluation of general health in HRQOL encompasses a
range of economic and psychosocial factors beyond mere
physical health conditions, our finding seems to indicate
toward a racial disparity in association between these
factors and LTL. Few studies have investigated the race
differences in telomere length. It is well established that
US Blacks have worse health outcomes for most major
conditions and have lower life expectancy compared to
Whites, but with regard to telomere, a majority of studies
reported the opposite direction of this hypothesis, which
is a pattern of Blacks having longer LTL than Whites
and Mexican American [31, 32, 47–50, 78]. Interestingly,
studies have also reported a steeper decline in telomere
length with age in Blacks than in Whites [50, 78].
Although LTL is influenced by genetic and epigenetic
factors, the differences in the association of age with
telomere length by race suggest that environmental
factors, which may include factors that increase
inflammation or factors that increase oxidative stress, are likely to
play an important role in race differences. Economic and
psychosocial factors have been linked to inflammation
and oxidative stress [41, 79]. Since perception of general
health may capture economic and psychosocial factors,
our results indicate that a greater exposure to a range of
economic and psychosocial factors in Blacks could play
a role for the steeper decline in LTL with age in this
It is important to note that, while we found an effect for
‘‘good’’ general health (versus ‘‘excellent’’) on LTL, those
who reported ‘‘poor’’ general health did not have shorter
LTL than those reporting ‘‘excellent’’ general health.
Several factors must be considered when interpreting this
inconsistent association between perceived general health
status and LTL. For instance, the reason behind this could
be the relatively smaller proportion of sample in the
‘‘poor’’ health category. Since the proportion was low, the
comparison in the regression analysis probably was not
efficient. Alternatively, this finding could be suggestive of
complexities of telomere dynamics. It is possible that those
with poor health adopted a healthier lifestyle and went
through different coping mechanisms, and there are several
indications that a healthy lifestyle and stress-coping
strategies might alter the rate of telomere erosion .
Another important factor that should be considered is,
those with poor health could have experienced telomere
degradation to such a degree that telomere lengthening
pathways could be triggered due to increased levels of
telomerase in those undergoing stress due to ‘‘poor’’
perception of health . This inconsistency could also be due
to a relatively higher level of albumin and uric acid, two
endogenous antioxidants, which could counteract the
damaging effect of oxidative stress and attenuate the rapid
erosion of telomeres . The relationship between
perceived health status and LTL thus remains complex, and
future studies should explore other potential mediators,
such as diet, history of infection, and exposure to
environmental toxins, as well as exposure to stressful
Our findings have several implications and provide a
foundation for future exploratory research. The association
of HRQOL with mortality and disease morbidity is well
documented, yet we know relatively little about the
biological mechanisms underlying the association. The
relationship between HRQOL and LTL in the current study
persisted after adjustment for demographic, disease, and
lifestyle variables. Therefore, our results also indicate that
telomeric attrition attributable to health-related
psychosocial elements that HRQOL represents could be an
important mechanism underlying the association between
perceived health and morbidity or mortality. The
inconsistency in association between unwell days due to poor
mental health and LTL deserves reassessing this question
as an indicator of mental health. Analyses of unwell day
measures should be taken with caution however, given the
possibility of recall bias (asked about past 30 days). Thus,
there is a possibility of non-differential misclassification
which might have resulted in an underestimate of the true
strength of the association. Further research will aid in
understanding the relative contribution, potential
modification, and efficient use of HRQOL measure in assessing
precise future health risks. Our data provide evidence of a
possible stronger cross-sectional association of perceived
general health and LTL shortening in Blacks than in
Whites and Mexican Americans. The precise mechanism
and determinants of this disparity remain to be identified
but could involve greater exposure to a range of economic
and psychosocial factors over the lifecourse in Blacks
compared to other races. We recommend additional
multiethnic studies to confirm this and to understand the
reasons and consequences of this disparity.
Our results should be interpreted within the context of a
few limitations. We acknowledge that given our
crosssectional observational design, our study can only examine
the associations of the HRQOL with LTL, but precludes
drawing causal inferences. That is, rather being a direct or
indirect causal factor in telomere shortening, poor HRQOL
may occur as a result of the pathophysiological effects of
telomere shortening itself. It is also important to note that
with only one time-point telomere data, we could not
account for innate individual variation in telomere length.
Therefore, longitudinal studies with repeated measures of
LTL are needed to determine whether the observed
associations are causal and, if so, to identify the specific
mechanisms involved. Our findings may also be limited by
residual confounding due to limited accuracy in the
measures of available variables. For example, absence of
measures of lifestyle variables over the lifecourse may
have limited our ability to adjust for these factors. LTL is
strongly influenced by genetic factors. Hence, it is possible
that genetic factors could also modulate the associations of
HRQOL with LTL. Our findings may also be limited by
other unmeasured variables, such as diet, psychological
stress, neighborhood conditions, and proportion of different
leukocyte subtypes. All of these variables could contribute
to population differences in LTL. Additional studies should
consider these factors, and the role of genetic variants, and
elucidate the underlying mechanisms of the associations
between HRQOL and LTL.
In conclusion, though we did not find a gradient
relationship in the multiple regression models, negative perception
of self-rated general health and unwell days due to recent
poor physical health were associated with greater cellular
aging as indexed by shorter LTL above and beyond
individual risk factors. Thus, our findings contribute evidence
to the limited literature that HRQOL, as a source of
economic and psychosocial burden, could be associated
with LTL shortening. Although longitudinal studies are
needed to better understand and confirm this relationship,
our results, which come from a large nationally
representative sample across a wide range of age, provide
preliminary evidence that HRQOL could be associated with LTL
shortening. We also found a possible racial difference in
this association and recommend additional multiethnic
studies to confirm this and to understand the reasons and
consequences of this difference.
Acknowledgements This study is based on the data from the
National Health and Nutrition Examination Survey, conducted by the
Centers for Disease Control and Prevention, National Center for
Health Statistics. The authors acknowledge the enormous
contributions of the participants and staffs in creating and maintaining these
datasets. We thank Cindy Clark, NIH Library Editing Service, for
reviewing the manuscript.
Funding This research was funded by the Intramural Research
Program of the National Library of Medicine, National Institutes of
Compliance with ethical standards
Conflict of interest The authors declare no conflicts of interest.
Ethical approval The National Health and Nutrition Examination
Survey datasets are de-identified and available in the public domain.
This study was exempted from human subject review by the National
Institutes of Health Office for Human Subjects Research Protections.
Open Access This article is distributed under the terms of the Creative
Commons Attribution 4.0 International License (http://creative
commons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a link
to the Creative Commons license, and indicate if changes were made.
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