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Validation of serum cotinine as a biomarker of environmental tobacco smoke exposure: Validation with self-report and association with subclinical atherosclerosis in non-smokers

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Validation of serum cotinine as a biomarker of environmental tobacco smoke exposure: Validation with self-report and association with subclinical atherosclerosis in non-smokers

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Content VALIDATION OF SERUM COTININE AS A BIOMARKER OF
ENVIRONMENTAL TOBACCO SMOKE EXPOSURE: VALIDATION WITH
SELF-REPORT AND ASSOCIATION WITH SUBCLINICAL
ATHEROSCLEROSIS IN NON-SMOKERS
by
Karen Chung
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(APPLIED BIOSTATISTICS AND EPIDEMIOLOGY)
May 2003
Copyright 2003 Karen Chung
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UMI Number: 1416545
UMI
UMI Microform 1416545
Copyright 2003 by ProQuest Information and Learning Company.
All rights reserved. This microform edition is protected against
unauthorized copying under Title 17, United States Code.
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UNIVERSITY OF SOUTHERN CALIFORNIA
The G raduate School
University Park
LOS ANGELES, CALIFORNIA 900894695
This thesis, w ritten b y
U nder the direction o f fyhtLt:. Thesis
C om m ittee, and approved b y a ll its members,
has been p resen ted to and accepted b y The
Graduate School, in p a rtia l fulfillm ent o f
requirem ents fo r th e degree o f
MitxttT ^ ...
Dean o f Graduate Studies
D ate
THESIS COMMITTEE
LLiiM dii iMdkL
( I Chairperson
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ACKNOWLEDGEMENTS
I would like to thank my parents for their unending love and support. I would also
like to thank Dr. Wendy Mack for her help and for her direction with this thesis.
Finally, I would like to thank committee members Dr. Stanley Azen and Dr. Howard
Hodis for their valuable time and effort with their suggestions.
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CONTENTS
ACKNOWLDEGEMENTS................................................................ ii
LIST OF TABLES.............................................................................. iv
LIST OF FIGURES............................................................................ v
LIST OF ABBREVIATIONS..................................... ........................ vi
ABSTRACT......................................................................................... vii
STRUCTURE ABSTRACT.............................................................. viii
Chapter
1. INTRODUCTION.................................................................... 1
2. METHODS .................................................................. 3
Study Population
Carotid Artery Ultrasonography and Measurement of IMT
and Arterial Diameter
Blood Pressure and Arterial Stiffness
Serum Cotinine
Other Measures
Statistical Analysis
3. RESULTS............................................................................... 7
Study Sample and Self-Reported ETS Exposure
Serum Cotinine Levels by Self-Reported ETS Exposure
Associations of Serum Cotinine with Beta Stiffness Index
and IMT
4. DISCUSSION.................. 20
REFERENCE LIST..................... 24
BIBLIOGRAPHY.......................................................... 26
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LIST OF TABLES
Table Page
1. Descriptive Statistics of Study Cohort (n=l 86)................................... 7
2. ETS Exposure by Gender (n=T 86)....................................................... 8
3. Descriptive Statistics for ETS Exposed
and Unexposed Subjects................................................................. 9
4. Mean Cotinine and Log Transformed Cotinine by Covariates 12
5. Correlation between Cotinine and Covariates..................................... 13
6. Mean Log Transformed Cotinine by Self-Reported
ETS Exposure .............................................................. 14
7. Mean Log Transformed Cotinine by Number of ETS Exposure
Sources...................... 15
8. Correlation between Number of ETS Sources with
Cotinine and Log Transformed Cotinine......................................... 16
9. Linear Correlation of Cotinine with Beta and IM T............................. 17
10. Mean Beta by Categories of Cotinine.................................................. 18
11. Mean IMT by Categories of Cotinine ............................................ 19
iv
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LIST OF FIGURES
Figure Page
1. Distribution of Serum Cotinine of 186 Nonsmokers 10
2. Distribution of Log Transformed Cotinine of 186 Nonsmokers............ 11
3. Distribution of Five Cotinine Groups.................................................. 11
v
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LIST OF ABBREVIATIONS
BMI = body mass index
ETS = environmental tobacco smoke
IMT = intima-media thickness
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ABSTRACT
The relationship between ETS and atherosclerosis either by self-report or by
cotinine has not been well studied. Among 186 nonsmokers, the mean serum
cotinine levels were higher in persons reporting ETS exposure vs. no ETS
exposure at home and at work. The log transformed mean cotinine levels
significantly increased with the number of ETS exposure sources. There was a
significant increase in the adjusted mean beta with increasing cotinine level, and
there was a statistically significant difference in median beta and median IMT
among the five cotinine groups. These data indicate that a strong correlation
exists between the number of reported ETS sources and serum cotinine, and that
ETS exposure quantified by serum cotinine level is associated with measures of
subclinical atherosclerosis.
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STRUCTURE ABSTRACT
OBJECTIVES: We used baseline data from the Vitamin E Atherosclerosis
Prevention Study to evaluate the relationship between self-reported
environmental tobacco smoke (ETS) exposure and serum cotinine levels and the
association with subclinical atherosclerosis among 186 nonsmokers.
BACKGROUND: Although self-reported ETS exposure is a common way to
measure involuntary tobacco intake, the use of serum cotinine may be a more
reliable and valid measure of ETS. The relationship between active cigarette
smoking and atherosclerosis is well established. However, the relationship
between ETS and atherosclerosis either by self-report or by cotinine has not been
well studied.
METHODS: B-mode ultrasonograms of the common carotid artery were used to
compute the arterial wall stiffness index Beta. A structured smoking
questionnaire evaluated the number of sources of ETS exposure for each subject.
RESULTS: The mean serum cotinine levels were higher in persons reporting
ETS exposure vs. no ETS exposure at home and at work (p=0.029 and p=0.08
respectively). The log transformed mean cotinine levels significantly increased
with the number of ETS exposure sources (p=0.0016 for linear trend). There was
a significant increase in the adjusted mean beta with increasing cotinine level
(p=0.0Q7 for adjusted linear trend). There was a statistically significant
viii
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difference in median beta and median IMT among the five cotinine groups (all
p=0.001).
CONCLUSIONS: These data indicate that a structured questionnaire to assess
self-reported ETS exposure is valid among nonsmokers, that a strong correlation
exists between the number of reported ETS sources and serum cotinine, and that
ETS exposure quantified by serum cotinine level is associated with measures of
subclinical atherosclerosis.
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INTRODUCTION
Tobacco smoke has long been known to contribute to a host of diseases that
includes asthma, chronic respiratory infections, lung cancer, and cardiovascular
disease among smokers (1). Since exposure to environmental tobacco smoke (ETS)
results from tobacco smoke, it is also suspected to play a major role in causing lung
cancer and cardiovascular disease among nonsmokers. Nearly 53,000 Americans
lose their lives annually to pulmonary and cardiovascular diseases as a result of
exposure to ETS (2, 3). ETS is also known as “second-hand smoke”, which
produces a mixture of side-stream and mainstream tobacco smoke. Side-stream
smoke is the smoke from a burning cigarette, while mainstream smoke is exhaled
from the lungs of a smoker. This dangerous mixture contains more than 4,000
chemical substances, forty of which have been known to cause cancer in humans or
animals (2).
Several studies have shown that ETS may contribute to increased
atherosclerosis measured by higher levels of intima-media thickness (IMT) (4) and
reduced vasoreactivity in nonsmokers (6, 7). However, few or none have attempted
to show that ETS also contributes to arterial stiffness. The traditional and perhaps
most routine way of assessing ETS exposure in epidemiological studies is through
self-reports. However, this method may not always be reliable. Self-reported
measurements of ETS exposure (such as hours per day exposed) by non-smokers
through questionnaires rely heavily on an individual’s subjective estimate of quantity.
This often results in the under- or over-reporting of tobacco smoke intake due to
1
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variation in environmental factors such as the amount of cigarettes smoked, intensity,
duration, or size and ventilation of a location (2, 3). For these reasons, it is necessary
to provide other methods of validation to accurately reflect the amount of ETS
exposure reported by an individual.
In our study, we used the biomarker cotinine to correlate ETS exposure to
two measures of atherosclerosis. Cotinine is an indicator of smoke absorption and
the major metabolite of nicotine, a primary compound found in tobacco (8). Since
nicotine has a relatively short half-life of several hours, it is rapidly metabolized
through our system. Cotinine, however, is processed and eliminated by the body at a
much slower rate of approximately 3-4 days. Due to this chemical characteristic of
cotinine, it can be readily measured in urine, plasma, saliva or hair. In addition, the
specificity and sensitivity of cotinine as a biomarker for distinguishing smokers from
nonsmokers are in the range of 88 - 100% (9). Thus, routine radioimmunoassay
(RIA) and gas chromatography-mass spectrometry (GC-MS) can be used to assess
and quantify the amount of cotinine in the body. The objectives of this study are (1)
to establish the relationship between self-reported environmental tobacco smoke
exposure and serum cotinine levels in nonsmokers and (2) to evaluate the association
between serum cotinine and subclinical atherosclerosis measured by carotid artery
intima-media thickness (IMT) and carotid arterial stiffness.
2
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METHODS
Study Population
The study population was composed of 353 subjects who participated in a
randomized trial, the Vitamin E Atherosclerosis Prevention Study (VEAPS).
VEAPS was a clinical trial that tested the efficacy of vitamin E (400IU daily) vs.
placebo in altering the rate of progression of subclinical atherosclerosis measured
through ultrasound-assessed carotid artery intima-media thickness (IMT). The
subjects were forty years or older, had a LDL-cholesterol of at least 3.4 mmol/L (130
mg/dL), triglyceride level not more than 5.7 mmol/L (500 mg/dL), and had no
history of cardiovascular disease, diabetes mellitus, untreated thyroid problem or
uncontrolled hypertension. All subjects were required to complete a structured
questionnaire regarding their current and past active smoking and ETS exposures.
The ETS exposures were determined from three sources: at home, at work, and
places outside the home and work. For the ETS exposures at home, subjects
reported the number of smokers in the home and the hours per day they were
exposed to each smoker’s tobacco smoke. The number of years of exposure to ETS
in the home was also recorded. The ETS exposures at work and other places were
reported as average daily hours of exposure.
Carotid Artery Ultrasonography and Measurement of IMT and Arterial
Diameter
B-mode carotid artery ultrasounds were obtained on all subjects at baseline
and every 6 months using an ATL ultrasound imager equipped with a linear array
3
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7.5 MHz probe. The ultrasound images were used to measure IMT. The ECG signal
and ultrasound images were simultaneously recorded on videotape. Blood pressure
was recorded throughout the procedure using a Critikon vital signs monitor.
Subjects were placed supine and the head turned to the left with the use of a 45-
degree head block to ensure the optimal angle for ultrasound examination of the neck.
The common carotid artery (CCA) was imaged in cross-section, and the scanhead
moved laterally until the jugular vein was stacked above the CCA. The scanhead
was rotated around the central image line 90 degrees, while maintaining the jugular
vein stacked above the CCA in order to obtain a longitudinal view of both vessels.
The proximal portion of the carotid bulb was included in all images as an anatomical
reference point for standardization of arterial measurements. Stacking of the jugular
vein and the CCA help determine a repeatable probe angle that allows the same
portion of the arterial wall to be imaged at each examination. Minimum gain
necessary for clear visualization of structures was used. Once the transducer was
positioned, the image was recorded for a minimum of sixty seconds. Emphasis was
placed on optimizing visualization of the IMT. In order to measure CCA IMT and
arterial diameter, the videotaped images were processed off-line using a software
program that utilizes automated edge detection to locate the lumen-intima and
media-adventitia echoes at sub-pixel resolution (11,12).
Blood Pressure and Arterial Stiffness
Blood pressure (BP) was measured four times during the carotid artery
ultrasound examination and averaged. The percentage change in carotid arterial
4
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diameter on carotid ultrasonograms between maximum and minimum dilation (DD)
was measured and used to compute the Beta stiffness index, (ln[systolic BP/diastolic
BP]/DD).
Serum Cotinine
Blood samples were drawn for serum cotinine. The analytical method which
used liquid chromatography in tandem with mass spectrometry is described
elsewhere (10). Briefly, the serum samples were equilibrated with a methyl-D3
cotinine internal standard, deproteinized, basified, and extracted with methylene
chloride (13). The extraction procedure used to measure cotinine and
hydroxycotinine were modified simultaneously. The sensitivity for both analytes
was 200 pg/mL, and the coefficient of variation was 10% or less. The standard curve
ranged from 100 pg/mL to 10 ng/mL.
Other measures
Body weight and height measurements were performed in street clothes
without shoes. The BMI or body mass index was calculated as weight in kilograms
divided by the square of the height in meters.
Statistical Analysis
To evaluate self-reported ETS exposures, cotinine levels, carotid IMT and
stiffness independent of the effects of active smoking, this study included only
subjects who had reported no active cigarette smoking (current or past) and whose
serum cotinine levels were less than 20 ng/mL. Subjects were categorized as ETS-
exposed if they reported any ETS exposure at a given source (home, work, or other)
5
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and unexposed if they reported no exposure. To account for multiple sources of ETS
exposure, a summary variable determined the total number of ETS sources (ranging
from zero for no ETS exposure to three for ETS exposure reported at home, work,
and other places) for each subject. The cotinine variable was categorized into five
levels. The first group consisted of subjects with cotinine levels below the detection
limit (0.1 ng/mL) of the assay, while the remaining subjects were broken into
roughly four equal groups based on a quantile cut. Since the distribution of cotinine
concentration was skewed, a log transformation was performed, and the transformed
cotinine values were also compared between ETS exposure groups.
Several analyses were used to determine the relationship between serum
cotinine levels and self-reported ETS. A chi-square test was used to test the
association between gender and ETS exposure. To test the mean difference in serum
cotinine levels between ETS- exposed and unexposed subjects, the Student’s t-test
and ANOVA were used. To evaluate the correlation between cotinine levels and
covariates as well as number of ETS exposure sources, Spearman correlations were
used. Non-parametric ANOVA was used to test the median cotinine differences by
covariates and by self-reported ETS exposure.
To correlate cotinine levels with carotid IMT and Beta, the Spearman
correlation was used. ANOVA was used to test for differences in mean IMT and
Beta among the five cotinine groups. Non-parametric ANOVA was also used to test
the median IMT and Beta differences among the five cotinine groups. All statistical
testing was performed using SAS version 8.02 at a two-sided a - 0.05 level.
6
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RESULTS
Study Sample and Self-Reported ETS Exposure. Of 353 VEAPS subjects, 227
were self-reported nonsmokers (39 subjects had no cotinine data, and 2 had cotinine
greater than 20 ng/mL leaving 186 nonsmoking subjects with cotinine values less
than 20 ng/mL). Demographic and clinical factors such as age, weight, body mass
index (BMI), pulse rate, systolic and diastolic blood pressures, measurements of
carotid IMT and Beta index are summarized in Table 1.
Table 1: Descriptive Statistics of Study Cohort (n=186)
Variable N
Age (years)
Weight (pounds)
BMI (kg/m2 )
Pulse Rate (beats/min)
Systolic Blood Pressure (mm Hg)
Diastolic Blood Pressure (mm Hg)
Intima-Media Thickness (mm)
Beta Index (1 5 )
Gender
Female
Male
186
186
186
186
186
186
183f
183f
105(56)*
81(44)
55.7 ± 9.1 (39.5, 76.7)"
169.2 ±35.0 (99.0, 266.0)
27.1 ±4.4 (16.0,44.2)
64.6 ± 7.3 (46.0, 102.0)
127.7 ± 17.5 (90.0, 183.0)
76.1 ±9.5 (55.0,108.0)
0.740 ±0.134 (0.548,1.174)
12.3 ± 11.1 (2.7, 115.05)
*: mean ± SD (range)
f : total of 183 subjects due to 3 missing data for the Beta index.
* : frequency (%)
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The distribution of subjects self-reporting exposures to ETS stratified by
gender is shown in Table 2. Significantly more females than males reported ETS
exposure at home (pO.OOOl). There was no gender difference in reported ETS
exposure at work or in other places (p= 0.40 and p=0.14 respectively). There was
also no difference between males and females in the number of ETS sources
(p=0.19).
Table 2: ETS Exposure by Gender (n=186)
Exposure Source Females (n=105) Males (n=81) p-value§
Home 39 (37.1)" 5 (6.2) <0.001
Work 34 (32.4) 31 (38.3) 0.40
Other 38 (36.2) 38 (46.9) 0.14
Number of ETS Sources 0.19
0 40 (38.1) 33 (40.7)
1 32 (30.2) 25 (30.9)
2 20(19.1) 20 (24.7)
3 13 (12.4) 3 (3.7)
*: frequency (percentage) of subjects self-reporting ETS exposure
§: p-value from chi-square test for the association between gender and ETS exposure
Descriptive statistics for self-reported ETS exposed (n=T 13) and unexposed
subjects (n=73) are given in Table 3. There were no differences between ETS-
exposed and ETS-unexposed subjects in gender, height, weight, BMI, pulse rate, or
8
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diastolic blood pressure. ETS-exposed subjects were significantly older and had
significantly higher systolic blood pressure than ETS-unexposed subjects.
Table 3: Descriptive Statistics for ETS Exposed and Unexposed Subjectst
Variable Exposed
Mean (SD)
(n=113)
Unexposed
Mean (SD)
(n=73)
p-values§
Age (years) 57.0 (8.7) 53.7 (9.5) 0.02
Height (inches) 66.4 (4.2) 65.7 (4.2) 0.36
Weight (pounds) 170.0(35.7) 167.9 (34.0) 0.69
BMI (kg/m2 ) 27.0 (4.4) 27.2 (4.5) 0.55
Pulse Rate (beats/min) 64.6 (6.8) 64.5 (8.0) 0.89
Systolic Blood Pressure
(mm Hg)
129.9(17.0) 124.4 (17.9) 0.04
Diastolic Blood Pressure
(mm Hg)
76.4 (9.6) 75.7 (9.5) 0.62
Gender
Female
Male
65 (57)
48 (43)
40 (55)
33 (45)
p-value
0.71
f: ETS exposed = self-reported exposure at home, work, or other places;
ETS unexposed = no self-reported exposure at home, work, or other places
§: p-values from Student’s t-test to test for mean differences between ETS-exposed
and ETS-unexposed subjects
*: p-value from chi-square test to test for ETS-exposed difference between male and
female subjects
Serum Cotinine Levels by Self-Reported ETS Exposure. Plots of the distribution
of serum cotinine levels on a regular and log scale for the 186 nonsmokers are shown
in Figures 1 and 2, respectively. The distribution on a regular scale was skewed to
the right with the majority concentrating at a serum cotinine level of approximately
9
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0.1 to 2.0 ng/mL. The distribution on a log scale was also skewed to the right but in
a larger range from -3.0 to 3.0 ng/mL (the majority of the data was at -3.0 to -2.0
ng/mL). The distributions of the five cotinine groups are plotted in Figure 3 with the
majority (86%) of the subjects falling in the 0.1 ng/mL serum cotinine levels (the
assay detection limit) and approximately equal distributions in the remaining four
groups.
Figure 1: Distribution of Serum Cotinine of 186 Nonsmokers
150 -
100 -
50 -
0-------------------------- 1 ----- ! — i--- 1 ------1 ----r—T ----, ---- 1 ---- , ---- 1 ---- , ---- 1 ---- 1 ---- 1 ---- , ---- 1 -
0 2 4 6 8 10 12 14 16 18 20 22
cot
10
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Figure 2: Distribution of Log Transformed Cotinine of 186 Nonsmokers
Miiii
| S | | S i
. > ' 7 - '
— 1 1 1
B i M i
- w ,
i f c *
p i l p i i
-2.5 -1.5 -0.5 0.5 1.5 2.5
logcot
Figure 3: Distribution of Five Cotinine Groups
180 n
160 -
o
&
170
z
Ifi
3 100
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80
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3
60 - i
40 .
20 .
0
< = 0.10 0.101 - 0.107 0 . 1 0 8 - 0.153 0 . 1 5 4 - 0.744 0.745 - 18.65
Serum Cotinine (ng/mL)
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The mean log transformed cotinine levels by covariates (gender, age, and
BMI) are shown in Table 4. Non-parametric ANOVA showed significant
differences in cotinine by gender, age and BMI (all p<0.05). The Spearman
correlations between cotinine and covariates (Table 5) showed no significant
correction between cotinine and gender or age. However, cotinine was significantly
correlated with BMI (r=0.16, p=0.03).
Table 4: Log Transformed Cotinine by Covariates
Covariates N Log
Transformed
Cotinine
Mean (SD)
p-values
Gender 0.34', 0.00014
Female 105 -2.2 (0.5)
Male 81 -2.1 (0.9)
Age (years)
<47.9 47 -2.2 (0.7)
0.74', 0.007+
47.9 - 54.6 45 -2.1 (0.7)
54.7 - 62.3 48 -2.1 (0.9)
>62.4 46 -2.2 (0.4)
BMI (kg/m2 )
<24.4 46 -2.3 (0.2)
046!,0.0001i
24.4 - 26.2 47 -2.1 (0.8)
26.3-29.2 47 -2.1 (0.8)
>29.2 46 -2.1 (0.6)
^ p-values from ANOVA to test the cotinine mean differences by covariates
p-values from Wilcoxon rank sum to test the cotinine median differences by
covariates
12
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Table 5: Correlation between Serum Cotinine Levels and Covariates
Covariates Rho1 with
Cotinine
p-values1
Gender -0.006 0.93
Age -0.05 0.48
BMI 0.16 0.03
f : Spearman Correlation Coefficient
J: p-values from Spearman Correlation
The mean log transformed cotinine values by self-reported ETS exposure in
the home, work, and other places, both unadjusted and adjusted for age, gender, and
BMI are reported in Table 6. The results of non-parametric rank-based tests showed
statistically significant cotinine differences in the home, work, and other places after
adjustment for gender and BMI (all p<0.05).
13
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able 6: Log Transformed Mean Cotinine Levels by Self-Reported ETS exposure
Source ETS
Exposed
N, Median
ETS Exposed
Mean (SEM)
ETS
Unexposed
N, Median
ETS Unexposed
Mean (SEM)
p-value
Home
Adjusted for gender
Adjusted for age
Adjusted for BMI
44, -2.3 -1.9 (0.2)
-1.8 (0.1)
-1.9 (0.1)
-1.8 (0.1)
142, -2.3 -2.2 (0.04)
-2.2 (0.05)
-2.3 (0.06)
-2.2 (0.05)
0.029t
O.Oll5 , 0.0005§
0.0014*, 0.03§
0.0008*, 0.04§
Work
Adjusted for gender
Adjusted for age
Adjusted for BMI
65, -2.3 -2.0 (0.2)
-2.0 (0.08)
-2.0 (0.08)
-1.9 (0.08)
121,-2.3 -2.2 (0.04)
-2.2 (0.06)
-2.3 (0.06)
-2.2 (0.06)
0.08*
0.029*, 0.0001§
0.03*, 0.11§
0.041, G.0002§
Other
Adjusted for gender
Adjusted for age
Adjusted for BMI
76, -2.3 -2.1 (0.1)
-2.1 (0.07)
-2.1 (0.08)
-2.0 (0.08)
110,-2.3 -2.2 (0.04)
-2.2 (0.06)
-2.2 (0.06)
-2.2 (0.06)
0.15*
0.13*, 0.0001s
0.1*, 0.14§
0.13*, 0.0001§
f : p-values from Student’s t-test for log transformed mean cotinine difference between
ETS-exposed and unexposed subjects
* : p-values from ANCOVA for the log transformed mean serum cotinine difference between
ETS-exposed and unexposed subjects adjusted for age, gender and BMI
§: p-values from Wilcoxon rank sum for log transformed median serum cotinine difference between ETS-
exposed and unexposed subjects adjusted for age, gender and BMI
Log transformed mean cotinine levels significantly increased with the
number of ETS exposure sources (p-value for linear trend = 0.0016) (Table 7).
There was a statistically significant mean cotinine difference by number of ETS
exposure sources without adjustment for gender, age, and BMI (p=0.011) as well as
with adjustment for the three covariates (p=0.036). Table 8 shows that there were
significant correlations between the number of ETS sources with cotinine and with
log transformed cotinine. The Spearman correlation between the number of ETS
sources with cotinine and log transformed cotinine was 0.21 (p-0.004). After
adjustment for gender, age and BMI, the correlation became stronger (r=0.24,
p=0.0008).
Table 7: Log Transformed Mean Serum Cotinine Levels by Number of ETS
Exposure Sources
Number of
ETS Source
Mean Cotinine
(SEM)
p-value for
linear trend
Overall
p-value*
Adjusted
p-value*
0.0016 0.011 0.036
0 -2.3 (0.08)
1 -2.1 (0.09)
2 -2.0 (0.10)
3 -1.7 (0.16)
f : global p-values from ANOVA test for mean serum cotinine difference by
number of ETS exposure sources
p-value adjusted for gender, age and BMI
15
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Table 8: Correlation between Number of ETS Sources with Cotinine and Log
Transformed Cotinine
Spearman
correlation^
p-value
Serum Cotinine 0.21 0.004
Adjusted for gender 0.20 0.008
Adjusted for age 0.19 0.01
Adjusted for BMI 0.19 0.01
Adjusted for gender, age, BMI 0.24 0.0008
Log Transformed Serum Cotinine 0.21 0.004
Adjusted for gender 0.25 0.0007
Adjusted for age 0.25 0.0008
Adjusted for BMI 0.24 0.001
Adjusted for gender, age, BMI 0.24 0.001
f : Spearman correlation between number of ETS sources with and without log
transformed cotinine levels
Associations of Serum Cotinine Levels with Beta Stiffness Index and IMT.
Table 9 shows no statistical significance for gender-, age-, and BMI-adjusted
Spearman’s partial correlation between the Beta stiffness index and cotinine levels
and between carotid IMT and cotinine levels. The mean beta index and carotid IMT
by categories of cotinine are shown in Tables 10 and 11, respectively. There was a
statistically significant difference in the mean Beta index among the five cotinine
groups after adjusting for age, gender, and BMI (p=0.02). There was a significant
increase in the adjusted mean beta index with increasing cotinine level (adjusted p-
value for linear trend = 0.007). The mean Beta index increased dramatically at the
highest level of serum cotinine. In a non-parametric test, there was a statistically
16
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significant difference in the median beta index among the five serum cotinine groups
(p=0.0001).
There was no difference in the mean carotid IMT by categories of cotinine
(adjusted overall p-value = 0.55, adjusted p-value for linear trend = 0.28) but there
was a statistically significant difference in the median carotid IMT (p=0.0001) with
nonparametric testing.
Table 9: Adjusted and Unadjusted Linear Correlation of Serum Cotinine with
the Beta Index and Carotid IMT
Spearman correlation
with Serum Cotinine
concentration
p-value
Beta 0.062 0.41
Adjusted for gender -0.009 0.90
Adjusted for age -0.025 0.72
Adjusted for BMI -0.026 0.73
Adjusted for gender, age, BMI -0.012 0.87
IMT 0.103 0.17
Adjusted for gender -0.017 0.82
Adjusted for age -0.006 0.93
Adjusted for BMI -0.008 0.91
Adjusted for gender, age, BMI -0.023 0.76
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Table 10: Mean Beta Index by Categories of Serum Cotinine
Serum
Cotinine
Category
(B)
n t Unadjusted
Mean Beta
Index
(SEM)
Overall
p-values*
(unadjusted)
Adjusted
Mean Beta
Index8
(SEM)
Overall
p-value*
(adjusted)
p-value for
linear trend
(unadjusted)
p-value for
linear trend
(adjusted)
p-value for non-
parametric test
0.028 0.02 0.0073 0.0070 0.0001
<0.1 15 11.9 (0.9) 11.9 (0.8)
0.101 -0.107 7 10.3 (4.1) 10.5 (3.9)
0.108-0.153 6 12.2 (4.4) 10.6 (4.2)
0.154-0.744 6 10.9 (4.4) 11.1 (4.2)
0.745- 18.65 7 25.7(4.1) 25.0 (3.9)
f: total of 183 subjects due to 3 missing Beta Index data
$: overall p-value from ANOVA test for mean group differences
§: Mean Beta index adjusted for gender, age and BMI
*: p-value from Wilcoxon rank sum test for median group differences
© o
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Table 11: Mean Carotid IMT by Categories of Serum Cotinine
Serum
Cotinine
Category
(mm)
nl- Unadjusted
Mean IMT
(SEM)
Overall
p-values*
(unadjusted)
Adjusted
Mean IM T§
(SEM)
Overall
p-value*
(adjusted)
p-value for
linear trend
(unadjusted)
p-value for
linear
trend
(adjusted)
p-value for
non-parametric
test*
0.65 0.55 0.22 0.28 0.0001
<0.1 15 0.736(0.011) 0.736 (0.009)
0.101 -0.107 7 0.734(0.051) 0.749 (0.046)
0.108-0.153 6 0.761 (0.055) 0.747 (0.049)
0.154-0.744 6 0.734 (0.055) 0.753 (0.049)
0.745 - 18.65 7 0.814(0.051) 0.796 (0.046)
f : total of 183 subjects due to 3 missing Beta Index data
* : overall p-value from ANOVA test for mean group differences
§: Mean IMT adjusted for gender, age and BMI
*: p-value from Wilcoxon rank sum test for median group differences
DISCUSSION
In this study, we found a positive correlation between self-reported ETS
exposure and serum cotinine levels in non-smoking individuals. The data also
showed a significant difference in the mean serum cotinine levels between persons
reporting ETS exposure vs. no ETS exposure at home and at work. More
importantly, the results reveal that there is an increase in the mean serum cotinine
level with the number of reported ETS exposure sources. These results held with
and without adjustment for covariates (gender, age and BMI), and indicate that a
structured questionnaire to assess self-reported ETS exposure is valid among
nonsmokers.
We also found a significant difference in mean carotid artery stiffness
measured by the Beta index between five ordinal categories of serum cotinine level.
The Beta index increased with respect to the serum cotinine level. More
interestingly, we noted a large surge in the mean Beta index at the highest serum
level cotinine. This clearly suggests that there is a significant association between
the level of ETS exposure measured by serum cotinine and subclinical
atherosclerosis measured by carotid arterial stiffness. Therefore, ETS exposure is
linked to atherosclerosis.
We also found a significant difference in the median carotid IMT and five
ordinal categories of serum cotinine level. Similar to the Beta index, carotid IMT
increased with respect to the serum cotinine level and there was a large increase in
carotid IMT at the highest cotinine level. However, limited sample size reduced the
20
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study power to detect associations with carotid artery IMT. This is the only known
study that has attempted to correlate cotinine to carotid IMT. Thus, more studies and
larger data pools are needed to produce a more representative and statistically
reliable conclusion.
In the cotinine assay used in this study, cotinine concentrations > 0.1 ng/mL
were detectable. For 186 nonsmokers, 84.4% had undetectable cotinine
concentration by this assay. Therefore, only a small number of nonsmokers (23 out
of 183) had a detectable level of serum cotinine. The fact that a portion of this
subgroup included subjects who reported no ETS exposure indicate a more
widespread exposure (15.6%) to cotinine than reflected by the questionnaire data.
It is not surprising to find a significant gender difference in ETS exposure at
home but not at work or in other places. The reason is that few male nonsmokers are
married to female smokers but it is common for female nonsmokers to be married to
male smokers because of a higher smoking prevalence in males than females.
We found a significant difference in the mean serum cotinine levels between
individuals who self-reported ETS exposure at home and those who did not. Factors
that contribute to variability in ETS exposures include room ventilation and size (3).
In addition, our findings showed significant mean serum cotinine differences after
adjustment for gender and BMI between self-reported ETS exposure vs. no exposure
at work. This is consistent with five other studies reporting major differences in
cotinine measurements with different levels of worksite smoking restrictions (1, 3,
14,15,16). The association between self-reported ETS at work and serum cotinine
21
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indicated that ETS exposure was stable (14). In recent studies, variations in worksite
smoking policies also had a major effect on the serum cotinine concentration (15).
The variation in enforcement of such policies may contribute to different infiltration
of ETS from areas where smoking is allowed to areas where it is not allowed (3).
Further studies with a more complete questionnaire about details of workplace and
worksite smoking policies, and worksite ventilation, are needed to fully evaluate
ETS exposure at work.
The relationship between active cigarette smoking and atherosclerosis is well
established. However, there is limited literature evaluating the relationship between
ETS and atherosclerosis either by self-report or by biomarker measures such as
cotinine. Both carotid IMT and arterial stiffness are non-invasive measures of
subclinical atherosclerosis. This study is the first to evaluate the relationship
between serum cotinine concentrations and atherosclerosis. Our findings showed a
significant difference in the mean carotid arterial stiffness measured by the Beta
index between five ordinal categories of cotinine level. This indicates that there is an
association between the level of ETS exposure measured by serum cotinine levels
and subclinical atherosclerosis. Our data also confirmed the findings of previous
VEAPS investigations (16) showing that the Beta index is adversely associated with
ETS exposure in a dose-dependent manner, in which the Beta index values increased
with respect to serum cotinine level.
Limitations of this study include possible misclassification of self-reported
ETS exposures. These types of misclassification will occur in any study of ETS that
22
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uses a less than perfect measure of ETS exposure and will cause a negative bias with
underestimation of the size of ETS-disease associations. The magnitude of this
negative bias may be much greater than the positive bias induced by the
misclassification of active smokers as nonsmokers. This is because the degree of
passive smoke exposure is not only related to time or to how individuals spend their
time in each setting but also the concentration of tobacco-related air pollutants in the
environment (17). Another limitation of this study is the lack of sensitivity of the
cotinine assay to detect concentrations below 0.1 ng/mL. This left us with a small
population of individuals with concentrations above 0.1 ng/mL that greatly reduced
the study power.
In summary, our study showed a significant linear trend as well as a strong
correlation between number of ETS sources and serum cotinine levels. Our data also
suggest a positive association between serum cotinine levels at the level of ETS
exposure (i.e. well below active smoking doses) and atherosclerosis. Further studies
with much larger data pools are needed to substantiate these findings.
23
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REFERENCE
1. Pirkle JL, Flegal KM, Bemert JT, Brody DJ, Etzel RA, Maurer KR.
Exposure of the US population to environmental tobacco smoke: The
Third National Health and Nutrition Examination Survey, 1988 to 1991.
JAMA. 1996;275: 1233-1240.
2. Aubrey ET, Douglas CJ, Homayoun K. Environmental tobacco smoke
and cardiovascular disease. Circulation. 1992;86:699-702.
3. Hammond K. Exposure of U.S. workers to environmental tobacco smoke.
Environmental Health Perspectives. 1999;107:329-340.
4. Howard G, Burke GL, Szklo M, Tell GS, Exkfeldt J, Evans G, Heiss G.
Active and passive smoking are associated with increased carotid wall
thickness. Arch Intern Med. 1994;154:1277-1282.
5. Glantz SA, Parmley WW. Passive smoking and heart disease.
Circulation. 1991;83:1-12.
6. Brown RE, Nahser PJ, Rossen JD, Winniford MD. Passive exposure to
environmental tobacco smoke causes coronary vasoconstriction in
humans. Circulation. 1993;88:1-260.
7. Quillen JE, Rossen JD, Oskarsson HJ, Minor RL, Lopez AG, Winniford
MD. Acute effect of cigarette smoking on the coronary circulation:
Constriction of epicardial and resistance vessels. JACC. 1993;22:642-647.
8. Benowitz NL. Biomarkers of environmental tobacco smoke exposure.
Environmental Health Perspective. 1999;107:349-355.
9. Kemmeren JM, Poppel GV, Verhoef P, Jarvis MJ. Plasma cotinine:
Stability in smokers and validation of self-reported smoke exposure in
nonsmokers. Environmental Research. 1994;66:235-243.
10. Bemert JT. Development and validation of sensitive method for
determination of serum cotinine in smokers and non-smokers by liquid
chromatography/atmospheric pressure ionization tandem mass
spectrometry. Clinical Chemistry 1997;43:122281-122291.
24
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
11. Selzer RH, Hodis HN, Kwong-Fu H, et al. Evaluation of computerized
edge tracking for quantifying intima-media thickness of the common
carotid artery from B-mode ultrasound images. Atherosclerosis
1994;111:1-11.
12. Selzer RH, Mack WJ, Lee PL, Kwong-Fu H, Hodis HN. Improved
common carotid artery elasticity and intima-media thickness
measurements from computer analysis of sequential ultrasound frames.
Atherosclerosis 2001; 154:185-193.
13. Bemert JT, Sosnoff C, Turner WE, et al. Development of a rapid and
sensitive method for serum cotinine analysis as a marker of exposure to
environmental tobacco smoke. Clin Chem. 1994;40:1075.
14. Emmons KM, Abrams DB, Marshall R, et al. An evaluation of the
relationship between self-report and biochemical measures of
environmental tobacco smoke exposure. Preventive Medicine.
1994;23:26-39.
15. Hammond SK, Sorensen G, Youngstrom R, Ockene JK. Occupational
exposure to environmental tobacco smoke. JAMA. 1995;274:956-60.
16. Mack WJ, Islam T, Lee Z, Selzer RH, Hodis HN. Environmental tobacco
smoke and carotid arterial stiffness, in review.
17. Haley NJ, Colosimo SG, Axelrad CM, Harris R, Sepkovic DW.
Biochemical validation of self-reported exposure to environmental
tobacco smoke. Environmental Research. 1989;49:127-135.
25
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
BIBLIOGRAPHY
Aubrey, E.T., Douglas, C. J., & Homayoun K. (1992). Environmental tobacco
smoke and cardiovascular disease. Circulation, 86, 699-702.
Benowitz, N.L. (1999). Biomarkers of environmental tobacco smoke exposure.
Environmental Health Perspective, 107, 349-355.
Bemert, J.T. (1997). Development and validation of sensitive method for
determination of serum cotinine in smokers and non-smokers by liquid
chromatography/atmospheric pressure ionization tandem mass spectrometry.
Clinical Chemistry, 43,122281-122291.
Bemert, J. T., Sosnoff, C., & Turner, W.E., et al. (1994). Development of a
rapid and sensitive method for serum cotinine analysis as a marker of exposure to
environmental tobacco smoke. Clin Chem, 40,1075.
Brown, R. E., Nahser, P. J., Rossen, J. D., & Winniford, M. D. (1993). Passive
exposure to environmental tobacco smoke causes coronary vasoconstriction in
humans. Circulation, 88,1-260.
Emmons, K. M., Abrams, D. B., & Marshall, R, et al. (1994). An evaluation of
the relationship between self-report and biochemical measures of environmental
tobacco smoke exposure. Preventive Medicine, 23, 26-39.
Glantz, S. A., & Parmley, W. W. (1991). Passive smoking and heart disease.
Circulation, 83,1-12.
Haley, N. J., Colosimo, S. G., Axelrad, C. M., Harris, R., & Sepkovic, D.W.
(1989). Biochemical validation of self-reported exposure to environmental
tobacco smoke. Environmental Research, 49, 127-135.
Hammond, K. (1999). Exposure of U.S. workers to environmental tobacco
smoke. Environmental Health Perspectives, 107, 329-340.
Hammond, S. K., Sorensen, G., Youngstrom, R., & Ockene, J. K. (1995).
Occupational exposure to environmental tobacco smoke. JAMA, 274, 956-60.
Howard, G., Burke, G. L., Szklo, M., Tell, G. S., Exkfeldt, J., Evans, G., & Heiss,
G. (1994). Active and passive smoking are associated with increased carotid
wall thickness. Arch Intern Med, 154, 1277-1282.
26
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Kemmeren, J. M., Poppel, G. V., Verhoe, F. P., & Jarvis, M. J. (1994). Plasma
cotinine: Stability in smokers and validation of self-reported smoke exposure in
nonsmokers. Environmental Research, 66,235-243.
Mack, W. J., Islam, T., Lee, Z., Selzer, R. H., & Hodis, H.N. (n.d.).
Environmental tobacco smoke and carotid arterial stiffness.
Pirkle, J. L., Flegal, K. M., Bemert, J. T., Brody, D. J., Etzel, R. A., & Maurer,
K.R. (1996). Exposure of the US population to environmental tobacco smoke:
The Third National Health and Nutrition Examination Survey, 1988 to 1991.
JAMA, 275,1233-1240.
Quillen, J. E., Rossen, J. D., Oskarsson, H. J., Minor, R. L., Lopez, A. G., &
Winniford, M. D. (1993). Acute effect of cigarette smoking on the coronary
circulation: Constriction of epicardial and resistance vessels. JACC, 22, 642-647.
Selzer, R. H., Hodis, H. N., Kwong, F. H., et al. (1994). Evaluation of
computerized edge tracking for quantifying intima-media thickness of the
common carotid artery from B-mode ultrasound images. Atherosclerosis, 111, 1-
11.
Selzer, R. H., Mack, W. J., Lee, P. L., Kwong, F. H., & Hodis, H. N. (2001).
Improved common carotid artery elasticity and intima-media thickness
measurements from computer analysis of sequential ultrasound frames.
Atherosclerosis, 154,185-193.
27
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

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Asset Metadata

Creator Chung, Karen (author)

Core Title Validation of serum cotinine as a biomarker of environmental tobacco smoke exposure: Validation with self-report and association with subclinical atherosclerosis in non-smokers

Degree Master of Science

Degree Program Applied Biostatistics and Epidemiology

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag biology, biostatistics,health sciences, public health,OAI-PMH Harvest

Language English

Contributor Digitized by ProQuest (provenance)

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c16-304189

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