Open Journal of Respiratory Diseases, 2013, 3, 97-106
http://dx.doi.org/10.4236/ojrd.2013.32015 Published Online May 2013 (http://www.scirp.org/journal/ojrd)
Sleep Quality among Hispanics of Mexican Descent and
Non-Hispanic Whites: Results from the Sleep Health and
Knowledge in US Hispanics Study
Xavier Soler1*, Carolina Diaz-Piedra2, Wayne A. Bardwell1, Sonia Ancoli-Israel1,
Lawrence A. Palinkas1,3, Joel E. Dimsdale1, Jose S. Loredo1
1University of California San Diego, San Diego, USA
2University of Granada, Granada, Spain
3University of Southern California, Los Angeles, USA
Received April 1, 2013; revised May 3, 2013; accepted May 10, 2013
Copyright © 2013 Xavier Soler et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ABSTRACT
Objectives: To investigate differences in sleep quality between Hispanics of Mexican descent (HMD) and Non-His-
panic Whites (NHW) and evaluate the effect of acculturation to the US lifestyle in sleep health. We hypothesize that the
detrimental effect of acculturation on health outcomes will impact sleep quality among HMD. Design: We performed a
population-based random digit dialing telephone survey to determine sleep quality in HMD and NHW. We collected
from 3667 subjects, demographics, previous diagnosis of depression or anxiety, past treatment for sleep disorders, the
Pittsburgh Sleep Quality Index (PSQI) and the Short Acculturation Scale for Hispanics. Results: The prevalence of
poor sleep quality (PSQI > 5) was 64.4% for HMD and 64.3% for NHW (p = 0.93). A prior diagnosis of depression or
anxiety was an independent predictor of poor sleep quality in both groups (OR 3.4 and 2.7 for HMD and NHW. Ethnic-
ity was not a predictor of poor sleep quality in HMD or NHW. Acculturation was not a predictor of poor sleep quality in
HMD. However, highly acculturated young HMD males had significantly more prevalence of poor sleep quality com-
pared to NHW (64.8% vs. 49.8%, p < 0.001). Conclusion: The absence of sleep quality differences in a large sample of
HMD and NHW living in San Diego County is contrary to current data of having poorer sleep quality among Latinos.
We found that neither ethnicity nor acculturation were predictors of poor sleep quality in HMD. However, we demon-
strated a highly prevalent poor sleep quality among the two ethnic groups. The finding of significantly lower sleep qual-
ity in young highly acculturated HMD men may represent the heterogeneity of ethnicity related to sleep. Programs to
improve sleep quality in subjects with depression and/or anxiety, and in young highly-acculturated HMD seems war-
ranted.
Keywords: Sleep Quality; Race/Ethnicity; Acculturation; Hispanics; Latinos; Mexican-Americans; PSQI
1. Introduction
Sleep is restorative in daily functioning [1] and is intrin-
sically important in sustaining physical and psychosocial
well-being that theoretically is thought to be dependent
of ethnicity and culture [2,3]. Furthermore, sleep disor-
ders are linked to poor mental and physical health and
directly impact quality of life [4-8]. Prior studies have
suggested ethnic differences in sleep-related disorders
such as obstructive sleep apnea, restless legs syndrome,
insomnia, and in sleep continuity and architecture [9-19].
The majority of sleep research has been conducted in
Non-Hispanic Whites (NHW), and to a lesser extent in
African-Americans and Asians. Therefore, these results
cannot be easily generalized to other ethnic groups such
as Hispanics, the second largest ethnic group and the
fastest-growing minority in the United States [20,21]. An
understanding of the epidemiology of sleep disorders
among different ethnic groups is of key importance to
appreciate the links between sleep problems and cardio-
vascular disorders such systemic hypertension, stroke or
metabolic syndrome, quality of life, and the use of medi-
cal care among general populations [22]. As part of the
Sleep Health and Knowledge in US Hispanics project
(aimed at characterizing sleep disorders and health-re-
*Corresponding author.
C
opyright © 2013 SciRes. OJRD

X. SOLER ET AL.
98
lated knowledge of Hispanics of Mexican descent (HMD)
and NHW in San Diego County), we studied ethnic dif-
ferences on sleep quality on both groups. Because ethnic
differences in health outcomes may be attributable to
both biological and environmental factors, we also wished
to determine the role of acculturation in sleep quality in
this population, questions that are relevant for future
public health policies planning on these groups. Assum-
ing that acculturation may negatively impact health out-
comes, [23] we hypothesize that HMD will have signifi-
cantly poorer sleep quality compared to the group of
NHW measured with the PSQI.
2. Methods
2.1. Subjects
From January 2007 to September 2009, a total of 149,552
phone numbers were randomly dialed from which 14,162
households responded and showed interest in participat-
ing in the telephone survey (9.5% of response rate). Of
these, 10,495 (74%) were not qualified to participate be-
cause no one in the household was HMD or NHW or
over quota for NHW in 59 cases. To be included in the
study, subjects should have >18 years old, self-identified
as HMD or NHW ethnic group, and living in San Diego
County, California. A total of 3667 subjects were ana-
lyzed (1754 HMD and 1913 NHW). Informed consent
was obtained over the telephone. Only subjects with
complete and valid responses to the Pittsburgh Sleep
Quality Index (PSQI) were included in the analyses.
Cases were excluded when discrepancies were found in
the reports. For instance, if the subject reported habitual
sleep duration longer than the habitual sleep period (i.e.
patient reporting to sleep usually 9 hours, and in follow-
ing question answered going to bed at 11 pm and waking
up at 6 am, so time in bed is 7 hours total). Also, subjects
reporting sleeping time greater than 12 hours were ex-
cluded. Final analyzed sample was 3138 subjects. The
study was approved by the University of California San
Diego Human Research Protections Program.
2.2. Study Design
The Waksberg random digit dialing procedure was used
for recruitment [24]. This method is used for popula-
tion-based epidemiological studies. A computerized da-
tabase randomly assign and call phone numbers based in
a previously criteria of interest. It permits to accurately
select populations having certain characteristics such
gender or ethnicity. The survey was administered by
trained, bilingual, culturally competent telephone inter-
viewers (California Survey Research Services, Inc., Van
Nuys, CA) utilizing a computer assisted telephone inter-
view system. In order to adjust for the racial/ethnic dis-
tribution of the San Diego County population, zip codes
with higher concentrations of Mexican Americans were
over sampled. Once a qualifying household was identi-
fied a randomization procedure was utilized to recruit
only one adult participant per household.
The survey took approximately 40 minutes to com-
plete. We included: 1) demographics; 2) the sleep quality
questionnaire (PSQI) (25); 3) prevalence of smoking,
alcohol use, coffee use; 4) a previous diagnosis of anxi-
ety and/or depression (“have you ever been told that you
have had anxiety and/or depression?”); 5) and existence
of sleep disorder treatments (“have you ever been treated
for a sleep disorder?”). HMD subjects were also asked to
take the Short Acculturation Scale for Hispanics [25].
The telephone questionnaires were administered in Eng-
lish or Spanish based on participant’s preference.
2.3. Evaluation of Sleep
The PSQI assesses subjective sleep quality and sleep
disturbances over the previous month. It consists of 19
items evaluated over 7 domains that include subjective
sleep quality, sleep latency, sleep duration, habitual sleep
efficiency, sleep disturbances, use of sleep medication-
sand daytime dysfunction. Domains are scored on a 0 to
3 scale where 3 indicate severe impairment. The 7 sub-
scale scores are then totaled to provide a global PSQI
score, which has a range of 0 - 21, with higher scores
indicating worse sleep quality [26]. The PSQI has estab-
lished acceptable reliability (Cronbach’s alpha = 0.82 -
0.89) and validity (specificity rates to the clinical diag-
nosis of insomnia: 80% - 100%). Global scores > 5 were
interpreted as an indicator of poor sleep quality. Both
English and Spanish versions of the PSQI were available
for administration. The PSQI has been translated into
Spanish by various authors and validated in Spanish
speaking populations in Spain, [27] Colombia, [28] and
Mexico [29]. Each translation varies slightly. We made
minor changes to some of the expressions to adapt the
instrument to a telephone interview format and to the
Mexican American population. For example, question 5c,
we used “baño” instead of “servicio” to denote the bath-
room.
2.4. Evaluation of Acculturation Level
Those subjects identifying themselves as HMD were
further asked to take the Short Acculturation Scale for
Hispanics, a 12-item validated instrument, available in
both English and Spanish, which provides a global nu-
merical measure of acculturation to the American life-
style based on language familiarity and usage, language
preference in media interactions, ethnic social and per-
sonal interaction and identity. HMD participants were
classified as highly acculturated or leastacculturated based

X. SOLER ET AL. 99
Table 1. Hispanics of Mexican descent and non-Hispanic
Whites characteristics.
on whether their acculturation score fell above or below
the group median. Higher scores suggest more accultura-
tion. HMDa NHWb
n 1445 1693
p
Gender (% Male/Female) 42.5/57.5 50.6/49.4<0.001
Age (years, mean ± SD) 41.5 ± 15.8 55.4 ± 17.2<0.001
BMIc (kg/m2, mean ± SD) 28.1 ± 6.5 27.2 ± 5.7<0.001
Smokers (%) 15.2 19.1 0.005
Alcohol consumers (%) 33.1 51.2 <0.001
Caffeine consumers (%) 64.3 65.5 0.469
Sleep disorders treatment (%) 8.7 14.9 <0.001
Depression/anxiety diagnosis (%)27.6 31.4 0.061
2.5. Statistical Analysis
Statistical analyses were performed using SPSS 17.0 for
Windows (SPSS Inc., Chicago, IL). Descriptive statistics
for continuous variables were expressed as means with
standard deviations, and categorical data were described
as frequencies and percentages. “Don’t know” and “Re-
fuse to answer” responses were set to missing values and
excluded from analyses. Student t-tests were used to
compare mean values of PSQI. Pearson’s Chi-Square test
was used to compare frequency data. For each ethnic
group, anxiety, depression, gender, age and use of to-
bacco, alcohol and/or coffee scores were entered in to
logistic regression models taking PSQI score value (≤5
vs. >5) as the dependent variable. Acculturation was in-
cluded in the Hispanic model. Post hoc analyses of
prevalence of poor sleep quality were performed on
HMD data dividing the population by the median age
into young and older adults (≤47 and ≥48 years, respec-
tively). A p value < 0.05 was regarded as statistically sig-
nificant.
aHispanics of Mexican descent; bNon-Hispanic Whites; cBody mass index.
Table 2. Least and highly acculturated Hispanics of Mexi-
can descent characteristics.
Least
acculturated
HMDa
Highly
acculturated
HMDa
n 898 541
p
Gender (% Male/Female) 39.5/60.5 47.3/52.7
Age (years, mean ± SD) 42.6 ± 15.8 39.6 ± 15.6<0.001
BMIb (kg/m2, mean ± SD) 28.1 ± 6.8 28.1 ± 6.00.977
Smokers (%) 13.8 17.4 0.068
Alcohol consumers (%) 25.7 45.3 <0.001
Caffeine consumers (%) 69.3 56 <0.001
Sleep disorder treatment (%) 8.8 8.5 0.920
Depression/ anxiety diagnosis (%)27.8 27 0.692
Poor sleep quality (PSQIc > 5) 62.6 67.2 0.077
3. Results
3.1. Socio-Demographic Variables
Subject characteristics appear in Table 1. From the 3138
subjects that were analyzed (1445 HMD and 1693 NHW),
1471 were males and 1667, females. HMD were signifi-
cantly younger than NHW (41.5 ± 15.8 years old vs. 55.4
± 17.2 years old, p < 0.001). Table 2 shows the subject
characteristics of highly acculturated vs. least accultur-
ated HMD. In general, highly acculturated Hispanics
were younger, had a higher prevalence of use of alcohol
and lower prevalence of use of caffeinated beverages.
There was no difference in BMI, prevalence of smoking,
prior treatment for sleep disorders or previous diagnosis
of anxiety and/or depression between highly and least
acculturated Hispanics.
aHMD = Hispanics of Mexican descent; bBMI = Body mass index; cPitts-
burgh Sleep Quality Index.
acculturated, compared with the least acculturated was
not significantly different (67.2% vs. 62.6%, p = 0.077),
Table 2. Assessment of PSQI individual components
(subjective sleep quality, sleep latency, sleep duration,
habitual sleep efficiency, sleep disturbance, use of sleep-
ing medication and daytime dysfunction) showed sig-
nificant differences between both ethnic groups only in
the use of sleeping medication and habitual sleep effi-
ciency. HMD were less likely to use sleep medication
than NHW (17.2% vs. 28.8%, p < 0.001), and reported
significantly lower sleep efficiency (83.8% ± 14.7 vs.
85.6% ± 13.6, p = 0.001).
3.2. Subjective Sleep Quality
Table 3 depicts reported sleep quality as measured by the
PSQI in both HMD and NHW. The proportion of sub-
jects reporting poor sleep quality was not significantly
different between HMD and NHW (64.4% and 64.3% for
HMD and NHW respectively, p = 0.933). There was also
no significant difference in the mean PSQI global score
between ethnic groups (6.65 ± 4.1 for HMD vs. 6.67 ±
4.1 for NHW, p = 0.904). On average, women reported
significantly worse sleep quality than men (PSQI global
scores 7.0 ± 4.2 vs. 6.2 ± 3.8, p < 0.001). The proportion
of HMD reporting poor sleep quality among the highly
3.3. Predictors of Sleep Quality
We performed logistic regression analysis to determine
risk factors for poor sleep quality in the overall sample
and for HMD and NHW separately. When the entire
population was included, ethnicity was not a risk factor

X. SOLER ET AL.
100
Table 3. Pittsburgh sleep quality index sub-scale scores for
Hispanics of Mexican descent and Non-Hispanic Whites
(Mean ± SD).
HMDa NHWb
n 1445 1693
p
PSQIc Components
PSQI 1: Subjective sleep
quality 1.03 ± 0.82 0.99 ± 0.810.176
PSQI 2: Sleep latency 1.14 ± 0.95 1.09 ± 0.970.102
PSQI 3: Sleep duration 1.02 ± 1.08 1.13 ± 1.190.075
PSQI 4: Sleep efficiency 0.74 ± 0.99 0.63 ± 0.970.001
PSQI 5: Sleep disturbances 1.25 ± 0.68 1.26 ± 0.600.613
PSQI 6: Sleep medication use 0.39 ± 0.92 0.67 ± 1.14<0.001
PSQI 7: Daytime dysfunction 0.89 ± 0.92 0.89 ± 0.810.934
Sleep efficiency (%) 83.80 ± 14.68 85.56 ± 13.630.003
Poor sleep quality
(PSQI > 5, %) 64.4 64.3 0.933
Poor sleep quality
(PSQI > 5, %) (M/Fd) 59.9 / 67.7 61.6 / 66.90.012/ 0.002
PSQI global index 6.65 ± 4.10 6.67 ± 4.060.904
aHispanics of Mexican descent; bNon-Hispanic Whites; cPittsburgh Sleep
Quality Index; dMale/Female.
for sleep quality after controlling for age, gender, BMI,
smoking, use of alcoholic or caffeinated beverages, re-
ported presence of sleep disorders or reported diagnosis
of anxiety or depression. Ta ble 4 shows the predictors of
poor sleep quality for HMD. In HMD, a reported diagno-
sis of depression or anxiety (OR 3.444, 95% CI 2.512,
4.722, p < 0.001) and being female (OR 1.388, 95% CI
1.091, 1.766, p = 0.008) were independent predictors of
poor sleep quality. Acculturation to the US lifestyle was
not a predictor of poor sleep quality. Highly acculturated
young HMD males had a significantly higher prevalence
of poor sleep quality (64.8% vs. 49.8% p < 0.001) after
Bonferroni correction, than older HMD males, or women
regardless of acculturation status (Figure 1). Table 5
shows the predictors of poor sleep quality for NHW. In
NHW, the report of a diagnosis of depression or anxiety
was the strongest independent risk factor for poor sleep
quality (OR 2.699, 95% CI 2.093, 3.481, p < 0.001). In
addition, being female (OR 1.26, 95% CI 1.015, 1.564, p
= 0.036) and smoking (OR 1.656, 95% CI 1.240, 2.212, p
= 0.001) were independent predictors and age and BMI
were weak but statistically significant predictors of poor
sleep quality.
4. Discussion
The present study examined subjective sleep quality in a
large sample of US HMD living in San Diego County
(California, US) and compared them to NHW. We dem-
onstrated that that poor sleep quality is highly prevalent in
49.8
69
63.4
72.0
64.8 65.0
70.3 68.2
0
10
20
30
40
50
60
70
80
Least Acculturated
Highly Acculturated
p<0.05
a
Short Acculturation Scale for Hispanics
Figure 1. Sleep quality and acculturation by age and gender
in Hispanics of Mexican-descent. The results show no dif-
ferences among less and highly acculturated women. How-
ever, young highly acculturated men had significantly
poorest sleep quality compared with least acculturated
young men adults (p < 0.001).
HMD and NHW living in San Diego County, CA, but
not significantly different between these ethnic groups.
We found that the strongest predictor of poor sleep qual-
ity was the prior diagnosis of depression or anxiety. In
addition, our data suggest that the level of acculturation
to the US lifestyle could play a significant role in deter-
mining an impaired sleep quality among young HMD
men.
Previous research in general population has shown a
great variability in the prevalence of poor sleep quality,
[30-32] however; it is not clear yet what causes these
heterogenic results. For example, Buysse et al. found
poor sleep quality on the PSQI in 50.8% of 187 adults in
a US community sample where 41.2% were African-
Americans, [31,32] while Ramsawh and collaborators
found poor sleep quality in 35% of 4181 German sub-
jects using the PSQI as well [31,32]. In our large sample,
we found an even higher prevalence of poor sleep quality
among subjects. For instance, sleep complaints and
prevalence of poor sleep quality may be affected by the
measuring instrument, race/ethnic, age, and gender pro-
portions, health status, socioeconomic and cultural
makeup of the study population, all of which may ex-
plain the differences among studies published comparing
ethnic groups [30,32,33]. In the recent Sleep America
Poll 2010, which focused on ethnicity, the reported
prevalence of sleeping poorly at least one day a week
was 60% regardless of ethnicity, results comparable to
our findings [34]. It is important to notice, that there have
been very few researches exploring thoroughly sleep dis-
turbances among different ethnic groups and furthermore,
studies among Hispanics are almost nonexistent. With
few exceptions, US Hispanics are only a small proportion
of epidemiologic studies, although it is the second largest
ethnic group in the United States [16]. In a study evalu-

X. SOLER ET AL.
101
Table 4. Risk factors of poor slee p quality (Pittsburgh sleep quality index global index > 5) for Hispanics of Mexican descent
(n = 1386).
95% CI for Exp(B)
Variables in the equation
B SE Wald df Sig. Exp(B) Lower Upper
Depression/ anxiety 1.237 0.161 58.994 1 <0.001 3.444 2.512 4.722
Sleep disorder 0.388 0.269 2.084 1 0.149 1.474 0.870 2.496
Gender 0.328 0.123 7.130 1 0.008 1.388 1.091 1.766
Alcohol 0.255 0.132 3.739 1 0.053 1.290 0.997 1.670
Smoking 0.214 0.169 1.599 1 0.206 1.239 0.889 1.726
Acculturation 0.184 0.124 2.205 1 0.138 1.202 0.943 1.534
BMI 0.004 0.010 0.211 1 0.646 1.004 0.986 1.023
Age 0.003 0.004 0.429 1 0.512 1.003 0.995 1.010
Caffeine −0.208 0.127 2.684 1 0.101 0.812 0.634 1.042
Constant −0.176 0.315 0.313 1 0.576 0.838
Note: Acculturation = level of acculturation to the US lifestyle; Alcohol = reported use of alcoholic beverages; BMI = body mass index; Caffeine = reported use
of caffeinated beverages; Depression/Anxiety = prior diagnosis of depression and/or anxiety; Sleep Disorder = prior treatment for a sleep disorder.
Table 5. Risk factors of poor sleep quality (Pittsburgh sleep quality index global score > 5) for non-Hispanic Whites (n =
1675).
95% CI for Exp(B)
Variables in the equation
B SE Wald df Sig. Exp(B) Lower Upper
Depression/ anxiety 0.993 0.130 58.503 1 <0.001 2.699 2.093 3.481
Smoking 0.505 0.148 11.691 1 0.001 1.656 1.240 2.212
Sleep disorder 0.321 0.167 3.686 1 0.055 1.378 0.993 1.911
Gender 0.231 0.110 4.380 1 0.036 1.260 1.015 1.564
BMI 0.029 0.010 8.182 1 0.004 1.029 1.009 1.050
Alcohol 0.014 0.110 0.016 1 0.899 1.014 0.817 1.259
Age -0.006 0.003 3.874 1 0.049 0.994 0.988 1.000
Caffeine -0.140 0.115 1.476 1 0.224 0.869 0.694 1.090
Constant -0.279 0.352 0.629 1 0.428 0.756
Note: Alcohol = reported use of alcoholic beverages; BMI = body mass index; Caffeine = reported use of caffeinated beverages; Depression/Anxiety = prior
diagnosis of depression and/or anxiety; Sleep Disorder = prior treatment for a sleep disorder.
ating sleep complaints in 88,062 people from the US Be-
havioral Risk Factor Surveillance System survey (4.7%
Hispanics), Chowdhury et al. found that African-Ameri-
cans, Hispanics and Asians were less likely to report
sleep complaints compared to Caucasians [35]. Grandner
et al. did a similar study with 159,856 subjects (17.4%
Hispanics) and found that African-American and His-
panic women and Asian men had less sleep complaints
than NHW women and men respectively [36]. We did
not find significant differences between HMD and NHW
in their global sleep quality or in their reported sleep la-
tency, sleep duration, daytime dysfunction and sleep dis-
turbances as measured by the PSQI. However, a few dif-
ferences were noted: NHW reported greater use of sleep
medications compared to HMD, which conforms to pre-
vious reports [37,38]. Potential reasons have been ad-
vanced including racial/ethnic differences in the percep-
tion of illness, safety and efficacy of medications, and
reduced access to physicians and prescription medica-
tions among minorities [39]. Another difference found in
our study was that HMD also reported significantly
lower sleep efficiency. The sleep efficiency of NHW was
85.6% (normal ≥ 85%), while that of HMD was signifi-
cantly lower and below the clinical level of normality at
83.8%. Our findings differ from the sleep efficiency ob-
served among various ethnic groups including Whites
and Hispanics reported by Redline and collaborators [40].
Redline’s study showed no ethnic differences in sleep
efficiency using polysomnography. The PSQI provides
an average of the assessment of sleep quality over the
past month while the subjects sleep in their natural envi-
ronment; the polysomnogram, however, is based on one
overnight study that by its nature changes and standard-
izes the subjects’ usual sleep conditions thus potentially

X. SOLER ET AL.
102
explaining the finding of no ethnic difference in sleep
efficiency. We did not evaluate the effect of sleep envi-
ronment on sleep quality in this study, but the sleep en-
vironment may be an important determinant of sleep
quality as noted by the Ruiter et al.’s meta-analysis
where African Americans had worse sleep continuity and
duration when sleeping at home than in the sleep labora-
tory [41]. According to the 2003 National Institute of
Health National Sleep Disorders Research Plan, racial
and ethnic minorities, and those who are socioeconomi-
cally disadvantaged are more likely to sleep in less than
optimal environments (e.g., too hot or too cold, noisy, or
crowded) and may explain our findings [42].
We evaluated potential risk factors for poor sleep
quality by multivariate analyses in HMD and NHW. A
prior diagnosis of depression or anxiety was a strong risk
factor for poor sleep quality in both ethnic groups. In
previous work studying predictors of insomnia in breast
cancer survivors, we found that of 27 potential risk fac-
tors, only depression and vasomotor symptoms were sig-
nificant [43]. Our results are also in agreement with mul-
tiple reports that found a correlation of poor sleep quality
with several factors such mood impairment, anxiety, be-
ing female and ethnic groups including NHW, Afri-
can-American, German, and Chinese populations [30-32].
[44-47] Buysse et al. reported that being a woman,
higher scores in perceived stress, anxiety, anger, hostility
and pessimism were also risk factors for poor sleep qual-
ity [32]. Ramsawh et al. reported also that being a
woman and anxiety were risk factors for poor sleep qual-
ity [31]. Baker et al. found that poor sleep quality was
associated with lifestyle, health status, and
socio-demographic factors [30]. In our current study, the
use of alcoholic beverages approached significance (OR
1.29, p = 0.05) as a predictor of poor sleep quality only in
HMD. Recently, Ehlers et al., evaluated a group of
young Hispanic men (ages 18 to 30) in San Diego
County and reported that life time diagnosis of alcohol-
use disorder, family history of alcohol dependence, ac-
culturation stress, and lifetime diagnoses of major de-
pressive disorder were all correlated with significantly
poorer sleep quality as measured by the global score on
the PSQI, [48] which appears to agree with our finding.
Similar to our findings, some published datashow that
women more frequently report poor sleep quality [49-51].
We found that both HMD and NHW women had higher
prevalence of poor sleep quality as compared to men, and
significantly higher mean PSQI global score. Hall et al.
evaluated 370 NHW, African-American, and Chinese
women and found that 66% of participants reported poor
sleep quality, with African-American women reporting
more complaints about sleep measured with the PSQI,
similar results to current study [52]. On his study, Hall
studied middle-aged women who may had been affected
by physiological changes, such as menopause, which
may have a high impact on sleep quality [53] and also
sleep complaints that may increase with aging [54].
Studies of Hispanic immigrants and their descendants
have documented higher rates of obesity [55-58], diabe-
tes [55,59,60], cardiovascular disease [60-63], and psy-
chiatric disorders [65,66] with increasing acculturation to
the US lifestyle. Little is known of the effects of accul-
turation on sleep and sleep quality. A study of middle-
aged and elderly Hispanic women examined sleeping
habits among other health habits and found that accul-
turation negatively affected the sleep habits of mid-
dle-aged but not elderly Hispanic women [67]. A study
of adolescent Hispanic men (ages 11 - 19), suggested that
higher levels of acculturation were associated with an
increased likelihood of fewer hours of sleep per night,
among other deleterious health behaviors [68]. In the
current study, in the overall sample analysis, accultura-
tion to the US lifestyle was not a significant predictor of
sleep quality on multivariate analyses, suggesting that
acculturation may be only one of many factors in the
sleep quality of Hispanics living in the US [69,70]. Our
findings are similar to those of Roberts et al. who found
that ninth-grade-Hispanic students who identified them-
selves as Mexican-Americans rather than Mexican were
at a higher risk for poor sleep quality as denoted by in-
somnia. However, it is an interesting observation that in
the current study, on post hoc analyses, highly accultur-
ated young HMD males had a significantly greater
prevalence of poor sleep quality when compared to their
least acculturated counterparts. Results consistent with
reports from Cantero [67] and Ebin [68] suggesting that
younger Latinos may be more susceptible to negative
health outcomes of acculturation including poor sleep
quality. Potential causes for acculturation-associated
poor sleep quality include reduced hours of sleep, ir-
regular sleep schedules, increased use of alcohol, tobacco,
and stimulants, and the social stress needed to keep up
with the busy American lifestyle [55,65,71-83].
4.1. Limitations
We endeavored to obtain the most representative sample
population of HMD and NHW in San Diego County by
using random digit dialing and randomization of quali-
fying household adult members, which greatly increases
confidence in the applicability of our findings. We also
utilized professional culturally competent interviewers to
conduct the study in the subject’s language of choice.
However, only land lines were called. That can introduce
a selection bias as many people don’t use land lines
anymore, or even sometimes, they may not answer in-
coming calls. It is unknown the impact to the study, fur-
thermore perhaps more stay-home subjects responded the
land line phone leading to a misrepresented cultural or

X. SOLER ET AL. 103
economic populations. Of the 3667 subjects who took the
call and agreed to participate, all completed the survey.
However, the sample population had to be reduced sig-
nificantly, potentially reducing power, due to exclusion
of cases where the subject reported logically inconsistent
information about their sleep. Another limitation was the
cross-sectional nature of the study, which did not allow
us to make causal associations. Measurement of sleep
quality using the PSQI, although subjective, may have an
advantage over objective measurements of sleep quality
such as polysomnography or actigraphy, since it repre-
sents the subjects experience over the last 30 days rather
than the sleep quality over one night or a few nights.
Quality of sleep can be influenced by many other poten-
tial factors that due to time constraints and subject bur-
den were not evaluated in the study.
4.2. Conclusion
Poor sleep quality was common and equally prevalent
between HMD and NHW in a large sample of subjects
living in San Diego County. Having been diagnosed of
depression and/or anxiety and being a woman were
strong predictors of poor sleep quality in both ethnic
groups. Post hoc analyses suggested that sleep quality of
young male HMD might be more susceptible to the dele-
terious effects of acculturation to the US lifestyle. Fur-
ther research is warranted to better understand the high
prevalence of poor sleep quality among this large popu-
lation and to study the role of acculturation in young
HMD subjects and its certain negative health effect.
5. Key Findings
 Hispanics of Mexican descent and non-Hispanic Whites
living in San Diego, CA, had a highly prevalent poor
sleep quality.
 Ethnicity was not a predictor of poor sleep quality on
those two racial groups.
 A prior diagnosis of depression or anxiety was the
best predictor of poor sleep quality regardless the
ethnic group.
 An elevated acculturation to the US lifestyle has a
negative impact on sleep health in young Hispanics of
Mexican descent males.
6. Acknowledgements
This study was supported by NIH-HL075630 grant (JSL
and XS); by AG08415 grant (SAI); and by Spanish Min-
istry of Education AP 2007-02965 fellowship grant (CDP).
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