Vol.3, No.6, 357-361 (2011)
doi:10.4236/health.2011.36060
C
opyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
Health
Contemporary female smokers in the US are younger
and of lower socioeconomic status
——A brief report of the 2008-2009 results from Sister to Sister: The Women’s Heart Health
Foundation Registry
Jennifer L. Jarvie1, Yun Wang2, Caitlin E. Johnson3, JoAnne M. Foody3,4*
1University of Colorado School of Medicine, Aurora, USA;
2Department of Biostatistics, Harvard School of Public Health, Boston, USA;
3Department of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, USA;
4Harvard Medical School, Boston, USA; *Corresponding Author:
Received 2 March 2011; revised 3 May 2011; accepted 10 May 2011.
ABSTRACT
Smoking is the most common cause of prema-
ture cardiovascular disease in women, but con-
temporary data is lacking. We sought to inves-
tigate the differences between female smokers
and nonsmokers in the US. Methods: Using a
registry of almost 19,000 women who attended
free public heart screenings sponsored by Sis-
ter to Sister between 2008 and 2009 in 17 large
US cities, we compared the means for lipid val-
ues, cardiometabolic measures, and differences
in sociodemographic information between smok-
ers and nonsmokers. Secondary outcomes were
age and race-adjusted odds for obesity, the
metabolic syndrome, hypertension, a non-HDL >
160 mg/dl, and a serum glucose ≥ 126 mg/dl
between smoking and nonsmoking women.
Results: The final sample included 18,892
women (49.8 ± 14.3 years, 37% black, and 32%
white, 14% Hispanic), with 1,216 (6.4%) current
smokers. Smokers were younger than non-
smokers (45.6 ± 13.0 vs 50.1 ± 14.4 years, p <
0.001), with lower HDL levels (55.5 ± 17.4 vs 58.6
± 17.4, p < 0.001), and higher triglycerides (148.8
± 103.7 vs 145.5 ± 93, p = 0.4082). There were no
significant differences in LDL between smokers
versus nonsmokers. There were more black and
white women in the smoking group. Smoking
women were more likely to meet criteria for the
metabolic syndrome (OR 1.22; 95% CI 1.00 - 1.49)
and have a non-HDL > 160 mg/dl (OR 1.19; 1.01 -
1.39). Insurance and income data showed a sig-
nificant inverse relationship between smoking
prevalence and increasing household income.
Conclusions: In this richly diverse sample of
women, female smokers were younger and of
lower socioeconomic status than nonsmokers
with significant differences in cardiometabolic
risk factors.
Keywords: Cigarette Smoking; Cardiovascular
Risk Factors; Women; Prevention
1. INTRODUCTION
Smoking is the strongest risk factor for premature
cardiovascular disease (CVD) in women [1]. While it is
well established that smoking triples CVD death, dou-
bles stroke risk, and increases peripheral vascular dis-
ease 10-fold, nearly 1 in 5 women continue to smoke [2].
While smoking rates continue to decrease in men,
rates of decline in women have plateaued [3,4]. Reasons
for the plateau are unclear and few contemporary data
exist for women. Utilizing data from a richly diverse
group of community-based women, we investigated the
characteristics of female smokers and nonsmokers.
2. METHODS
2.1. Study Sample
The study sample included women who attended free
Sister to Sister (STS) public heart screenings held annu-
ally in 17 large US cities in 2008 and 2009 (Atlanta, GA,
Baltimore, MD, Boston, MA, Chicago, IL, Dallas, TX,
Detroit, MI, Jacksonville, FL, Los Angles, CA, Miami,
FL, St. Louis, MO, Tampa, FL, and Washington, DC
held fairs in both 2008 and 2009, while Charlotte, NC,
Indianapolis, IN, New York, NY, Philadelphia, PA, and
Phoenix, AZ held fairs in 2008 only).
Screenings consisted of a standardized questionnaire

J. L. Jarvie et al. / Health 3 (2011) 357-361
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
358
assessing sociodemographic information, current smok-
ing status as yes/no, and personal history of CVD. In
addition, cardiometabolic measurements were obtained
by trained healthcare professionals. Participants who
attended 2009 fairs were queried regarding annual
household income and insurance status.
2.2. Outcomes
Cardiometabolic measures included a single auto-
mated blood pressure measurement, height, weight, body
mass index (BMI) calculation, and waist circumference
(WC) measurement taken above the iliac crest and re-
ported to the nearest 0.1 inch. Plasma glucose and cho-
lesterol were measured using fingerstick technology on
the Cholestech® LDX Analyzer (Hayward, CA). Cho-
lesterol measures included total cholesterol (TC),
high-density lipoprotein (HDL) cholesterol, and triglyc-
erides (TG). Non-HDL cholesterol and low-density
lipoprotein (LDL) cholesterol were calculated.
Hypertension (HTN) was defined as a systolic blood
pressure (SBP) ≥ 140 mmHg and/or a diastolic blood
pressure (DBP) ≥ 90 mmHg. Criteria for the metabolic
syndrome (MetS) were defined using the updated NCEP
ATP III guidelines [5], which included 3 or more of the
following: WC ≥ 35 inches, TG ≥ 150 mg/dl, HDL < 50
mg/dl, SBP ≥ 130 mmHg or DBP ≥ 85 mmHg, or a fast-
ing glucose ≥ 100 mg/dl.
All forms and procedures were approved by Quorum
Institutional Review Board (Seattle, WA).
2.3. Statistical Analysis
Descriptive and bivariate analyses were conducted to
compare demographics, comorbidities, vital signs, and
lab test data between smoker and non-smoker groups.
Chi-square tests and Wilcoxen rank-sum tests were used
for categorical variables and continuous variables, re-
spectively. A hierarchical generalized linear model
(HGLM) was developed to assess the risk difference
between smoking and nonsmoking groups for each out-
come measure and adjusted for age. We calculated 95%
confidence intervals (CI) for each estimate obtained
from the model. A dummy variable was created in the
model to represent records that had missing age, and
excluded records with missing BMI, vital signs, and lab
test data for each outcome measure. All statistical testing
was 2-sided, at a significance level of 0.05, and all
analyses were conducted using SAS version 9.2 (SAS
Institute Inc., Cary, NC).
3. RESULTS
Participant characteristics are listed in Table 1. The
final sample included 18,892 women (mean age 49.8 ±
14.3 years) with 37% (7,030) non-Hispanic black
women, 32% (5,991) non-Hispanic white women, 14%
(2,665) Hispanic women, and 17% of women in the
“other” category, which included 6% of women who
Table 1. Sister to Sister heart screening participant characteristics 2008 & 2009.
Nonsmokers Smokers p-value
Number of Participants (%) 17676 (93.6) 1216 (6.7) …
Mean Age (SD) 50.1 (14.4) 45.6 (13.0) < 0.001
Sociodemographics Total % Total %
Non-Hispanic Black 6529 36.9 501 41.2 …
Non-Hispanic White 5577 31.6 414 34.1 …
Hispanic 2491 14.1 174 14.3 …
Other* 3079 17.4 127 10.5 …
Lab Values Mean SD Mean SD
Total Cholesterol (mg/dl) 194.5 42.6 192 42.6 0.0809
HDL Cholesterol (mg/dl) 58.6 17.4 55.5 17.4 < 0.001
LDL Cholesterol (mg/dl) 110.1 36.2 110.4 36.4 0.8208
Triglycerides (mg/dl) 145.5 93.0 148.8 103.7 0.4082
Non-HDL (mg/dl) 136.9 41.8 136.8 43.8 0.9626
Glucose (mg/dl) 105.5 31.8 105.9 27.9 0.7122
Cardiometabolic Measures Mean SD Mean SD
Systolic Blood Pressure (mmHg) 126.9 19.7 125.6 19.9 0.0383
Diastolic Blood Pressure (mmHg) 77.0 12.8 78.2 13.8 0.0062
BMI (kg/m2) 27.9 6.3 28.1 6.3 0.2649

J. L. Jarvie et al. / Health 3 (2011) 357-361
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
359359
Waist Circumference (in) 36.2 6.0 36.3 6.1 0.5724
*Other race/ethnicity includes 6% of women with race/ethnicity other than black, Hispanic, or white and 11% of women with unknown race/ethnicity. HDL =
igh-density lipoprotein; LDL = low-density lipoprotein; BMI = body mass index; Ellipses (…) indicate test was not performed. h
listed racial and ethnic backgrounds other than black,
white, or Hispanic and 11% of women with unknown
race/ethnicity. Of the total, 1,216 (6.4%) were current
smokers and 17,676 (93.6%) were current nonsmokers.
Smokers were significantly younger (45.6 ± 13.0 years)
than nonsmokers (50.1 ± 14.4 years), with higher
triglycerides (148.8 ± 103.7 mg/dl vs 145.5 ± 93 mg/dl,
respectively), and significantly lower HDL levels (55.5 ±
17.4 mg/dl vs 58.6 ± 17.4 mg/dl, respectively). Smokers
also had a significantly lower mean systolic blood pres-
sure compared with nonsmokers (125.6 ± 19.9 mmHg vs
126.9 ± 19.7 mmHg, respectively), but a significantly
higher mean diastolic blood pressure compared with
nonsmokers (78.2 ± 13.8 mmHg vs 77.0 ± 12.8 mmHg,
respectively). Proportionally, there was a higher makeup
of non-Hispanic black and non-Hispanic white women
in the smoking group (41.2% and 34.1%, respectively)
compared with the nonsmoking group (37.0% and
31.6%, respectively).
A higher proportion of smokers were obese (35.4%)
and met criteria for the MetS (37.2%) compared with
nonsmoking women (32.6% and 34%, respectively)
(data not shown). A strong relationship between age and
smoking status was observed (Figure 1), such that there
were more smokers among the younger age groups.
Significant differences existed in insurance status be-
tween smokers and non-smokers (Figure 2a), where
only 45% of smokers had private insurance compared
with 54.8% of nonsmokers, and a higher makeup of
smokers were uninsured (40.5%) or on Medicaid (5.4%)
compared with nonsmokers (33.7% and 2.3%, respec-
tively). A significant inverse relationship was observed
between female smoking prevalence and annual house-
hold income (Figure 2b).
Risk adjusted outcomes revealed smokers had a sig-
nificantly higher risk of the MetS (OR 1.22; 95% CI 1.00
- 1.49) as well as a non-HDL > 160 mg/dl (OR 1.19; 95%
CI 1.01 - 1.39) compared with nonsmokers (Table 2).
Figure 1. Smoking prevalence was higher among younger women.

J. L. Jarvie et al. / Health 3 (2011) 357-361
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
360
Figure 2. Socioeconomic differences between smokers and nonsmokers.
Table 2. Risk adjusted outcomes in Sister to Sister women.
Obesity MetS HTN Non-HDL > 160 Glucose ≥ 126
Group
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Age-Adjusted 1.00 (1.00 - 1.01) 1.02 (1.02 - 1.03) 1.04 (1.04 - 1.05) 1.02 (1.02 - 1.03) 1.03 (1.02 - 1.03)
Nonsmoker 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Smoker 1.12 (0.98 - 1.28) 1.22 (1.00 - 1.49) 1.02 (0.87 - 1.19) 1.19 (1.01 - 1.39) 1.15 (0.94 - 1.41)
Odds ratios were drawn from a logistic model adjusted for age and race. Reference Groups: Nonsmokers reference for comparison with smokers. BMI = Body
Mass Index; MetS = Metabolic Syndrome; OR = Odds Ratio; 95% CI = 95% Confidence Interval; Obesity defined as BMI ≥30. MetS defined as any combina-
tion of 3 or more of the following: waist circumference ≥ 35 in, triglycerides ≥ 150 mg/dl, HDL < 50 mg/dl, SBP ≥ 130 mmHg or DBP ≥ 85 mmHg, and/or
fasting glucose > 100 mg/dl.
4. COMMENTS
In this cross-sectional analysis of a richly diverse
sample of community women in the US, smokers were
younger, with lower HDL cholesterol levels, higher TG
levels, and a higher proportion of women who met crite-
ria for the MetS. The prevalence of smoking decreased
with increasing annual household income, and a higher
proportion of women who smoked were uninsured or on
Medicaid.
Our findings are consistent with US data from the
2008 National Health Interview Survey, where preva-
lence of smoking was highest among adults < 65 years
of age [1]. Further, results from the Nurses’ Health Study
showed that women who start smoking before the age of
15 have the highest risk of CVD mortality (relative risk
9.94; 95% CI 5.15 - 19.19) [6]. These findings illustrate
the importance of aggressive smoking prevention efforts
directed towards younger women given that it negates
otherwise typical cardioprotection in a premenopausal
woman.
Women smokers had an average HDL cholesterol 3
mg/dl lower than nonsmoking women—translating into
a 12% increased risk for CVD [7]. This was coupled
with increased rates of obesity and the MetS, each in-
creasing CVD risk. While we expected to see hypergly-
cemia in the smoking group given earlier reports of the
association between cigarette smoke and insulin resis-
tance [8-12], this was not the case, although increased
rates of obesity and the MetS may be earlier markers.
Our overall smoking rate was notably low (6.7%) and
may be a reflection of health-seeking persons who attend
health screenings. These women would be less likely to
smoke or continue smoking given their concern for
overall wellness, although we also captured a substantial
number of women without health coverage looking for
free services. Therefore, we feel our results are gener-
alizable and our findings are consistent with previous
investigations [1,13].
Although this study adds to the outdated body of lit-
erature on the differences between smokers and non-
smokers, this study does have limitations. First, while

J. L. Jarvie et al. / Health 3 (2011) 357-361
Copyright © 2011 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
361361
the majority of women attending the fair were fasting,
some were not. Fasting status was recorded at the time
of testing, but a non-fasting state could result in elevated
glucose, TG, and LDL. Second, a single blood pressure
measure was taken for most women, which may have
overestimated mean blood pressure measures, although
women with high readings received additional confir-
matory measures, which would increase the accuracy of
high findings. Third, former smoking status was not col-
lected and many women may have been former smokers.
However, cardiovascular risk drops precipitously after
smoking cessation and approaches that of nonsmokers
within several years [6,14,15]. Fourth, we were unable to
account for medication use, which could have resulted in
the under-estimation of HTN, hyperlipidemia, and hy-
perglycemic rates if controlled.
5. CONCLUSION
Female smokers who attended STS heart screening
fairs in 2008 and 2009 were younger than nonsmokers
and of lower socioeconomic status with significantly
lower levels of HDL cholesterol and higher risk of the
MetS. Taken together, these differences substantially
increase a female smoker’s risk of a cardiovascular event,
and signal the need for more aggressive smoking pre-
vention programs targeted at younger populations from
lower socioeconomic neighborhoods.
6. ACKNOWLEDGEMENTS
We would like to thank Mrs. Irene K Pollin MSW, founder of the
Sister to Sister Foundation, for her leadership and insights and her
continued support for events and research that promote awareness and
prevention of heart disease in women.
Dr. Foody was supported in part by a grant from the Irene and Abe
Pollin Foundation and Sister to Sister: The Women’s Heart Health
Foundation. Dr. Jarvie was supported by the Sarnoff Cardiovascular
Research Foundation, Inc.
REFERENCES
[1] Carabollo, R., Malarcher, A. and National Center for
Chronic Disease Prevention and Health Promotion. (2009)
Cigarette smoking among adults and trend in smoking
cessation—United States, 2008. Morbidity and Mortality
Weekly Report , 58, 1227-1232.
[2] Lloyd-Jones, D., Adams, R.J., Brown, T.M., et al. (2010)
Heart disease and stroke statistics—2010 update: A re-
port from the American Heart Association Statistics
Committee and Stroke Statistics Subcommittee. Circula-
tion, 121, e46-e215.
doi:10.1161/CIRCULATIONAHA.109.192667
[3] Ali, S.M., Chaix, B., Merlo, J., Rosvall, M., Wamala, S.
and Lindstrom, M. (2009) Gender differences in daily
smoking prevalence in different age strata: A popula-
tion-based study in southern Sweden. Scandinavian
Journal of Public Health, 37,146-152.
doi:10.1177/1403494808100274
[4] Tilloy, E., Cottel, D., Ruidavets, J-B., et al. (2010) char-
acteristics of current smokers, former smokers, and sec-
ondhand exposure and evolution between 1985 and 2007.
European Journal of Cardiovascular Prevention and
Rehabilitation, 17, 730-736.
doi:10.1097/HJR.0b013e32833a9a0c
[5] Grundy, S.M., Cleeman, J.I., Daniels, S.R., et al. (2005)
diagnosis and management of the metabolic syndrome:
An American Heart Association/National Heart, Lung,
and Blood Institute Scientific Statement. Circulation, 112,
e285-2390.
doi:10.1161/CIRCULATIONAHA.105.169405
[6] Kawachi, I., Colditz, G.A., Stampfer, M.J., et al. (1993)
Smoking cessation in relation to total mortality rates in
women: A prospective cohort study. Annals of Internal
Medicine, 119, 992-1000.
[7] Cooney, M.T., Dudina, A., Bacquer, D.D., et al. (2009)
HDL cholesterol protects against cardiovascular disease
in both genders, at all ages and at all levels of risk.
Atherosclerosis, 206, 611-616.
doi:10.1016/j.atherosclerosis.2009.02.041
[8] Ambrose, J.A. and Barua, R.S. (2004) The pathophysi-
ology of cigarette smoking and cardiovascular disease:
An update. Journal of the American College of Cardiol-
ogy, 43, 1731-1737.
doi:10.1016/j.jacc.2003.12.047
[9] Craig, W.Y., Palomaki, G.E., Johnson, A.M. and Haddow,
J.E. (1990) Cigarette smoking-associated changes in
blood lipid and lipoprotein levels in teh 8 - 19 year old
age group: A meta-analysis. Pediatrics, 85, 155-158.
[10] Eliasson, B., Mero, N., Taskinen, M-R. and Smith, U.
(1997) The insulin resistance syndrome and postprandial
lipid intolerance in smokers. Atherosclerosis, 129, 79-88.
doi:10.1016/S0021-9150(96)06028-5
[11] Facchini, F.S., Hollenbeck, C.B., Jeppesen, J., Chen,
Y-DI. and Reaven, G.M. (1992) Insulin resistance and
cigarette smoking. Lancet, 339, 1128-1130.
doi:10.1016/0140-6736(92)90730-Q
[12] Rafalson, L., Donahue, R.P., Dmochowski, J., et al.
(2009) Cigarette smoking is associated with conversion
from normoglycemia to impaired fasting glucose: The
western New York study. Annals of Epidemiology, 19,
365-371.
doi:10.1016/j.annepidem.2009.01.013
[13] US Department of Health and Human Services. (2004)
The health consequences of smoking: A report of the
surgeon general. CDC, Atlanta.
[14] Kenfield, S.A., Stampfer, M.J., Rosner, B.A. and Colditz,
G.A. (2008) Smoking and smoking cessation in relation
to mortality in women. The Journal of American Medical
Association, 299, 2037-2047.
doi:10.1001/jama.299.17.2037
[15] Bakhru, A. and Erlinger, T.P. (2005) Smoking cessation
and cardiovascular disease risk factors: Results from the
third national health and nutrition examination survey.
PLoS Medicine, 2, e160.
doi:10.1371/journal.pmed.0020160