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10 Year Weight Gain in Smokers Who Quit, Smokers Who Continued Smoking And Never Smokers in the United States, NHANES 2003-2012

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Background/Objectives Weight gain after quitting smoking is a common concern for smokers and can discourage quit attempts. The purpose of this analysis was to describe the long term weight gain, smoking cessation attributable (SCA) weight gain and describe their relationship to cigarette consumption and body mass index (BMI) 10 years ago in a contemporary, nationally representative sample of smokers who continued to smoke and those who quit.Subjects/Methods12 204 adults ⩾ 36 years old were selected from the 2003-2012 National Health and Nutrition Examination Survey (NHANES). Ten year weight gain for never, continuing and former smokers (who quit 1-10 years ago) was calculated by body mass index (BMI) 10 years ago and cigarettes per day (CPD). SCA weight gain was calculated by taking the difference between the adjusted mean ten year weight gain of former smokers and that of continuing smokers.ResultsMean ten year weight gain among continuing smokers was 3.5 kg versus 8.4 kg among former smokers; 4.9 kg of SCA weight gain. After Bonferroni correction, there was no significant difference in overall weight gain between continuing and former smokers of 1-14 CPD and SCA weight gain was lowest in this group (2.0 kg, CI: 0.3, 3.7). SCA weight gain was highest for former smokers of ⩾25 CPD (10.3 kg, CI: 7.4, 13.2) and for those who were obese (7.1 kg, CI: 2.9, 11.3) mostly due to lower than average weight gain or weight loss among continuing smokers in these groups.Conclusions In a current, nationally representative sample, baseline BMI and CPD were important factors that contributed to the magnitude of long term weight gain following smoking cessation. Light to moderate smokers (<15 CPD) experienced little SCA weight gain while heavy smokers (⩾25 CPD) and those who were obese prior to quitting experienced the most.International Journal of Obesity accepted article preview online, 09 July 2015. doi:10.1038/ijo.2015.127.
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ORIGINAL ARTICLE
Ten-year weight gain in smokers who quit, smokers who
continued smoking and never smokers in the United States,
NHANES 20032012
S Veldheer, J Yingst, J Zhu and J Foulds
BACKGROUND/OBJECTIVES: Weight gain after quitting smoking is a common concern for smokers and can discourage quit
attempts. The purpose of this analysis was to describe the long-term weight gain, smoking cessation attributable (SCA) weight gain
and describe their relationship to cigarette consumption and body mass index (BMI) 10 years ago in a contemporary, nationally
representative sample of smokers who continued to smoke and those who quit.
SUBJECTS/METHODS: In all, 12 204 adults 36 years old were selected from the 20032012 National Health and Nutrition
Examination Survey (NHANES). Ten-year weight gain for never, continuing and former smokers (who quit 110 years ago) was
calculated by body mass index (BMI) 10 years ago and cigarettes per day (CPD). SCA weight gain was calculated by taking the
difference between the adjusted mean 10-year weight gain of former smokers and that of continuing smokers.
RESULTS: Mean 10-year weight gain among continuing smokers was 3.5 versus 8.4 kg among former smokers; the SCA weight
gain was 4.9 kg. After Bonferroni correction, there was no signicant difference in overall weight gain between continuing and
former smokers of 114 CPD, and SCA weight gain was lowest in this group (2.0 kg, condence interval (CI): 0.3, 3.7). SCA weight
gain was highest for former smokers of 25 CPD (10.3 kg, CI: 7.4, 13.2) and for those who were obese (7.1 kg, CI: 2.9, 11.3) mostly
because of lower than average weight gain or weight loss among continuing smokers in these groups.
CONCLUSIONS: In a current, nationally representative sample, baseline BMI and CPD were important factors that contributed to
the magnitude of long-term weight gain following smoking cessation. Light to moderate smokers ( o15 CPD) experienced little
SCA weight gain, whereas heavy smokers (25 CPD) and those who were obese before quitting experienced the most.
International Journal of Obesity advance online publication, 4 August 2015; doi:10.1038/ijo.2015.127
INTRODUCTION
Tobacco smoking and excess body weight are two of the leading
causes of premature death and disability in the United States.
1
It is
known that quitting smoking often leads to an increase in body
weight, although there are differing reports of the magnitude and
duration of weight gain that can be directly attributed to quitting.
For instance, the 1990 Surgeon Generals Report on The Health
Benets of Smoking Cessation concluded that 'average weight
gain after smoking cessation is only about 5 pounds [2.3 kg]'
(p 505) for smokers who had quit between 1 and 6 years and that
this 'is approximately 4 pounds [1.8 kg] greater than that expected
among continuing smokers' (p 483).
2
More recently, Aubin et al.
3
conducted a meta-analysis of smoking cessation clinical trials
published between 1989 and 2010 and found that the average
weight gain among smokers who quit was 10 pounds (4.5 kg)
1 year after quitting.
People generally gain weight over time as they age, thus a more
accurate estimate of the long-term magnitude of weight gain
because of quitting smoking is one that is able to separate age-
related weight gain from smoking cessation attributable (SCA)
weight gain. Studies with follow-ups beyond 1 year are able to
provide a more comprehensive picture of SCA weight gain by
taking the difference in weight gain between former smokers and
continuing smokers. These studies have established that smokers
who quit gain more overall weight compared with continuing
smokers,
49
although the amount of weight attributable to
quitting smoking has been varied with average SCA weight gains
between 3 and 6.6 kg, depending on the population.
59
Quitting smoking will have an immediate and positive effect on
a smokers health, but many smokers are concerned about gaining
weight after quitting, which can discourage them from making a
quit attempt.
10,11
An important clinical and public health goal is to
remove barriers to quitting, which includes addressing concerns
about weight gain by providing smokers with accurate informa-
tion on what to expect when they quit. However, accurate
information is difcult to provide as long-term studies have
observed substantial variations in weight gain among smokers
who quit,
3,6
suggesting that there are contributing factors to
gaining weight after quitting that are not well understood. Two
possible factors that have emerged as predictors of weight gain
are daily cigarette consumption before quitting and baseline body
mass index (BMI), although reports have not been entirely
consistent.
6,8,9,1214
Some studies have found that the number of
cigarettes smoked before quitting is positively associated with
weight gain,
5,6,8,13
but the majority of studies reporting on
postcessation weight gain do not discuss this effect. There have
also been signicant but inconsistent ndings regarding the
relationship between baseline BMI and postcessation weight
gain.
6,9,13,15
Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA. Correspondence: S Veldheer, Department of Public Health Sciences, Penn State College
Of Medicine, 500 University Drive, CH69, Hershey, PA 17033-0850, USA.
E-mail: sveldheer@psu.edu
Received 30 April 2015; revised 25 June 2015; accepted 2 July 2015; accepted article preview online 9 July 2015
International Journal of Obesity (2015), 16
© 2015 Macmillan Publishers Limited All rights reserved 0307-0565/15
www.nature.com/ijo
Therefore, the aim of this study was to describe the long-term
weight gain and SCA weight gain in a contemporary, nationally
representative sample of the United States population and to
describe their relationship to baseline cigarettes per day (CPD),
smoking cessation and BMI 10 years ago. This information could
provide public health professionals and clinicians with more
accurate information around which to frame discussions about
cessation-related weight gain with specic groups of smokers.
SUBJECTS AND METHODS
The National Health and Nutrition Examination Survey (NHANES) is a cross-
sectional survey conducted by the National Center for Health Statistics
(NCHS) and includes a nationally representative sample of non-institutio-
nalized, US civilians. Complete details regarding the NHANES methodology
are available elsewhere.
16
This analysis included ve survey cycles from
2003 to 2012.
The Weight History Questionnaire is asked of participants 36 years old.
In addition, selected participants had complete information for demo-
graphic, smoking status, height, current weight and weight 10 years ago.
To ensure stability of smoking cessation among former smokers and to
isolate the effect of long-term weight gain, we included only those who
had quit for at least 1 year. We did not include those who had quit 410
years ago (n= 3496), so that we had a sample of former smokers who had
not quit before the time frame for reporting weight (10 years ago). Also
excluded were continuing and former cigarette smokers who used any
other tobacco products (n= 418), women pregnant at the time of the
survey (n= 41) and underweight participants (BMI o18.5 at either time
point, n= 226). There were 2328 potentially eligible participants not
included because of missing height and current weight (n= 93), height
(n= 810), current weight (n= 879) or weight 10 years ago (n= 639).
Current height and weight were self-reported. Weight 10 years ago was
assessed by asking 'How much did you weigh 10 years ago?' BMI was
calculated using the participants height and weight with the standard
calculation (weight in kg divided by height in m
2
). BMI class was dened
according to the National Institutes of Health Clinical Guidelines,
17
as
normal weight (BMI 18.524.9), overweight (BMI 25.029.9) and obese (BMI
30.0+). The participants weight 10 years ago was subtracted from their
current weight to create a continuous 10-year weight change variable.
Never smokers were dened as individuals who smoked o100
cigarettes in their lifetime. Former smokers were dened as individuals
who smoked at least 100 cigarettes in their lifetime and who reported not
currently smoking. Continuing smokers were those who smoked at least
100 cigarettes in their lifetime and who reported smoking 'some days' or
'every day' at the time of the survey. CPD were reported by smokers as the
number of cigarettes they currently smoked per day, whereas former
smokers reported the number of cigarettes they usually smoked per day
before quitting. CPD categories were created using 114, 1524 and 25
CPD as cut-points.
Statistical analysis
All data were analyzed using SAS version 9.3 (SAS Institute, Cary, NC, USA)
and were weighted as recommended by NHANES analytical guidelines.
18
These procedures account for the complex sampling structure of NHANES
(i.e. differential weighting, clustering and stratication) when estimating
variances and condence limits. Bivariate tests of association with smoking
status (never smoker, continuing smoker, former smoker) were conducted
using RaoScott modied χ
2
tests for the categorical variables of interest
and weighted analysis of variance models for continuous variables.
Weighted analysis of covariance models were used to estimate means
and 95% condence intervals (95% CIs) for weight- and smoking-related
outcome variables, controlling for gender, race, age and education level.
Using 10-year weight change as the dependent variable, weighted
analysis of covariance models were set up to accommodate the two-way
interactions between the three main factors under investigation: BMI class,
smoking status and CPD. Gender, race, age and education level were
controlled for in all models. The estimated adjusted least-square means
and the standard errors of the mean (s.e.m.) for 10-year weight change was
obtained and plotted. The 95% CIs for the mean estimates were also
calculated and reported. SCA weight gain was calculated by taking the
difference between the adjusted mean weight gain of former smokers and
that of continuing smokers. Two tailed P-values of o0.05 were considered
signicant and Bonferroni adjustments for multiple tests were used when
necessary.
RESULTS
A general description of the overall sample is presented in Table 1.
The proportion of never smokers, continuing smokers and former
smokers was 65.2%, 25.3% and 9.5%, respectively. Former smokers
had a higher proportion of participants who were white and
currently obese compared with never smokers and continuing
smokers. Among continuing and former smokers, there were
similar proportions of obesity 10 years ago and the largest
proportion of participants in both groups smoked 114 CPD.
The overall adjusted mean weight gain for the entire population
regardless of smoking status was 4.5 kg (condence interval (CI):
4.2, 4.8), controlling for race, education level, gender and age.
Former smokers had quit an average of 5.7 years (CI: 5.5, 6.0).
Adjusted cigarette and weight-related characteristics are
Table 1. Weighted study population characteristics of participants aged 36+ in NHANES 20032012 by smoking status (n=12 204)
Never smoker (n= 7914) Continuing smoker (n= 3105) Former smoker (n= 1185) P-value
% Female 59.9 45.3 49.7 o0.001
Mean age (s.e.m.) 54.5 (0.27) 50.6 (0.23) 54.2 (0.47) o0.001
% White 71.9 72.3 76.6 0.04
% College educated 35.6 12.0 23.5 o0.001
Mean current BMI (s.e.m.) 28.7 (0.11) 27.8 (0.12) 29.6 (0.22) o0.001
Current BMI class, N(%) o0.001
Normal weight (BMI 18.5o25) 2155 (28.8) 1062 (36.0) 268 (22.1)
Overweight (BMI 25o30) 2943 (37.4) 1068 (33.5) 427 (36.5)
Obese (BMI 30) 2816 (33.9) 975 (30.4) 490 (41.3)
Mean BMI 10 years ago (s.e.m.) 27.2 (0.10) 26.3 (0.10) 26.7 (0.18) o0.001
BMI class 10 years ago, N(%) o0.001
Normal weight (BMI 18.5o25) 2987 (40.2) 1383 (47.0) 474 (42.6)
Overweight (BMI 25o30) 2896 (35.6) 1092 (33.6) 438 (35.8)
Obese (BMI 30) 2031 (24.2) 630 (19.4) 273 (21.6)
Mean CPD (s.e.m.) 17.6 (0.67) 16.6 (0.39) 0.151
CPD category, N(%) 0.007
114 1550 (43.4) 554 (44.5)
1524 1015 (38.0) 368 (32.3)
25 436 (18.6) 250 (23.2)
Abbreviations: BMI, body mass index; CPD, cigarettes per day, currently or before quitting; s.e.m., standard error of the mean.
Ten-year weight gain in smokers who quit
S Veldheer et al
2
International Journal of Obesity (2015) 1 6 © 2015 Macmillan Publishers Limited
presented in Table 2. There was no difference in CPD among
continuing and former smokers. Continuing smokers were lighter
and had lower current BMIs compared with both never smokers
and former smokers, whereas former smokers were heavier and
had a higher mean BMI compared with both continuing and never
smokers (Po0.001).
Adjusted mean 10-year weight gains and s.e.m. by smoking
status are presented in Figure 1. The overall mean SCA weight
gain was 4.9 kg (CI: 3.4, 6.4). Former smokers gained signicantly
more weight compared with continuing smokers (Po0.001) and
this difference remained signicant after Bonferroni adjustment.
Ten-year weight gains by BMI class are presented in Figure 2.
The SCA weight gain for normal weight, overweight and obese
participants was 4.4 (CI: 2.9, 5.9), 5.0 (CI: 3.3, 6.8) and 7.1 (CI: 2.9,
11.3) kg, respectively. Regardless of the smoking status, those who
were obese 10 years ago experienced less long-term weight gain
compared with those who were normal weight and overweight 10
years ago. The general pattern of the data shows that normal
weight and overweight former smokers gained about the same
amount of weight, whereas those who were obese gained the
least. However, the SCA weight gain was the highest for those
who were obese because of weight loss in obese continuing
smokers. All differences in weight gains between continuing and
former smokers were statistically signicant (Po0.002) and
remained signicant after Bonferroni adjustment.
Weight gain by CPD group among continuing and
former smokers is presented in Figure 3. The SCA weight
gain for those who smoked 114, 1524 and 25 CPD was 2.0
(CI: 0.3, 3.7), 6.0 (CI: 4.0, 7.9) and 10.3 (CI: 7.4, 13.2) kg, respectively.
There was a stepwise, positive relationship between CPD and
weight gain among former smokers, a pattern that is also
reected in SCA weight gain partly because continuing
smokers in each CPD category gained signicantly less
weight over time compared with former smokers. The difference
in weight gain between continuing and former smokers
of 114 CPD (P= 0.02) did not remain signicant after Bonferroni
adjustment. Differences in weight gain between continuing
and former smokers of 1524 and 25 CPD were
signicant (Po0.001) and remained signicant after Bonferroni
adjustment.
There was a similar overall pattern of results in both genders,
except that women gained more weight compared with men in
most groups, with the exception of obese female continuing
smokers who lost more weight compared with men (data not
shown). We have not focused on gender effects as there is some
evidence from a previous study that women are more likely to
underestimate historical weight.
19
This pattern was also found
when looking at continuing and former smokers within each CPD
group by BMI (Supplementary information is available at IJO's
website).
DISCUSSION
An important nding from the analysis of this contemporary,
nationally representative sample is that there is a positive, dose
response relationship between CPD and both overall weight gain
and SCA weight gain in smokers who quit. While the average
smoker reported 4.9 kg of weight gain that could be directly
attributed to smoking, light to moderate smokers (114 CPD)
gained much less than this (2.0 kg). In addition, the amount of
Table 2. Mean (95% CI) values for cigarette and weight-related characteristics, controlling for race, education level, gender and age
Never smoker (n= 7914) Continuing smoker (n= 3105) Former smoker (n= 1185) P-value
CPD 12.5 (11.9, 13.1) 13.6 (12.4, 14.8) 0.07
Years smoked 34.9 (34.6, 35.2) 29.8 (29.2, 30.5) o0.001
Current weight (kg)
a,b,d
81.7 (81.1, 82.3) 77.7 (76.7, 78.7) 84.2 (82.7, 85.7) o0.001
Weight 10 years ago (kg)
a,c,e
77.4 (76.7, 78.0) 74.2 (73.4, 75.1) 75.9 (74.7, 77.1) o0.001
Current BMI
a,b,d
29.1 (28.9, 29.3) 27.5 (27.2, 27.9) 29.8 (29.3, 30.2) o0.001
BMI 10 years ago
a,c,d
27.5 (27.3, 27.7) 26.3 (26.0, 26.5) 26.8 (26.4, 27.2) o0.001
Abbreviations: BMI, body mass index; CI, condence interval; CPD, cigarettes per day, currently or before quitting.
a
Difference between never smoker and
continuing smoker Po0.001.
b
Difference between continuing smoker and former smoker Po0.001.
c
Difference between continuing smoker and former
smoker Po0.02.
d
Difference between never smoker and former smoker Po0.004.
e
Difference between never smoker and former smoker Po0.02.
Figure 1. Adjusted mean differences (and s.e.m.
a
) in weight
compared with 10 years ago by smoking status, controlling for
race, gender, education level and age.
a
s.e.m., standard error of the
mean;
b
P=0.03;
c
Did not remain signicant after Bonferroni
adjustment;
d
Po0.001;
e
Remained signicant after Bonferroni
adjustment.
Figure 2. Adjusted differences (and s.e.m.
a
) in weight compared
with 10 years ago by smoking status and BMI class 10 years ago,
controlling for age, gender, race and education level.
a
s.e.m.,
standard error of the mean;
b
Po0.001;
c
Po0.002;
d
Remained
signicant after Bonferroni adjustment.
Ten-year weight gain in smokers who quit
S Veldheer et al
3
© 2015 Macmillan Publishers Limited International Journal of Obesity (2015) 1 6
10-year weight gain reported by light to moderate smokers who
quit was not signicantly different (after Bonferroni adjustment)
compared with the amount of weight gain reported by those who
continued to smoke this amount.
On the other hand, heavy smokers (25 CPD) had much more
SCA weight gain (10.3 kg) compared with lighter smokers, which
was mostly because of the combined effects of lower weight gain
in continuing, heavier smokers and higher weight gain in heavier
smokers who quit (versus lighter smokers who quit). Our ndings
on heavy smokers are consistent with other studies
5,8,13
that have
identied CPD as a predictor of extreme amounts of weight gain
(413 kg) and they suggest that the average smoker of 25 CPD
will experience a 15.7% increase in body weight after they quit
smoking, 12.2% being directly attributable to quitting smoking.
When considering weight gain by BMI, we found that
participants who were obese 10 years ago gained less weight
compared with their normal or overweight counterparts regard-
less of their smoking status. While it may be counterintuitive that
those with higher BMIs gain less weight over time, this has been
observed before in both prospective studies and clinical trials.
9,20
For instance, the Prospective Studies Collaboration
20
used
measured weight for 95% of their data and found weight
change over 59 years among those who were obese at baseline
(BMI 3050) was lower compared with that of those who were
normal weight (change in BMI of 0.12 for obese versus change in
BMI of 0.62 for normal weight participants). In addition, within the
obesity category, those with higher BMIs lost weight over that
time (those with a BMI 3035 had a BMI change of 0.24 compared
with those with a BMI 4050 who had a BMI change of 0.69). This
pattern of ndings is consistent with the present report, which
found that obese former smokers experienced 2.5 kg of long-term
weight gain, which was signicantly less than that of normal
weight (10.1 kg) and overweight (9.9 kg) former smokers. How-
ever, tempering this nding is the observation that obese
continuing smokers lost weight over time, making the magnitude
of SCA weight gain higher for obese former smokers (7.1 kg)
compared with for those who were normal weight (4.4 kg) or
overweight (5.0 kg).
An important observation to note is that our overall weight gain
estimate for former smokers is higher than the 1990 Surgeon
Generals Report on The Health Benets of Smoking Cessation
2
and higher than the Clinical Practice Guideline for Treating
Tobacco Use and Dependence: 2008 Update, which stated that
'Most [quitters] will gain fewer than 10 pounds (4.5 kg)' (p 173).
21
A
possible reason for these differences is that a number of the
studies in the above reports were clinical trials, which are known
to have different sample characteristics that make them difcult to
generalize to population surveys.
22
Our average long-term weight gain among former smokers is
also higher than previously reported from older NHANES data sets
(6.9 kg (19881991)
5
absolute mean weight gain in those quitting
for o10 years). This difference may be because of the overall
increase in the prevalence of obesity across all US sub-populations
since this data was published,
23
which is supported by the
observation that even never smokers in the present study
experienced a higher 10-year weight gain (4.4 kg) compared with
data previously reported (2.6 kg in 19881991).
5
From 1960 to 2012, the prevalence of obesity in the United
States jumped from o14% to 35%.
24
At the same time, a number
of public health initiatives (e.g., health education campaigns, clean
indoor air laws and increases in cigarette taxes) converged to
successfully decrease the prevalence of smoking from a high of
42% in 1964 to its current rate of 18%.
25
Although it is not thought
that the decrease in smoking prevalence with its associated
weight gain has signicantly contributed to the overall US
prevalence of obesity,
5
our data suggest that this overall societal
weight increase may have impacted body weights among
contemporary continuing and former smokers as well.
With regard to overall SCA weight gain, although our estimate of
4.9 kg is higher than the 3.3 kg reported in the 19711984 NHANES
survey,
8
it is similar to the SCA weight gain estimate of 4.7 kg
reported for the 19881991 NHANES surveys by Flegal et al.
5
This
suggests that even though overall weight gain in smokers and
former smokers may have increased because of the general societal
increase in obesity, weight gain that can be directly attributable to
smoking cessation has remained fairly constant.
This studysndings highlight the complex relationship
between smoking and weight control
2628
and raise questions
for how to present the issue to different groups of smokers. For
smokers of 114 CPD who want to quit, the message can be fairly
simple since the weight they gain may not be much more than if
they continued to smoke. In addition, they should be reminded
that weight gain occurs naturally as people age, and that if they
quit, relatively little of the weight they will gain over the long term
may be directly attributable to quitting smoking.
However, the question remains as to what messages should be
provided to obese and heavy smokers. Fernandez and Chapman
29
have suggested that because weight gain can be barrier to
smoking cessation, 'It may be unwise to incorporate this message
into clinical or public health practice'. However, the majority of
heavy smokers have experienced weight gain on a previous quit
attempt,
30
and it is clear that they already know that signicant
weight gain after quitting is likely. In addition, obese smokers have
been shown to be the most concerned about weight gain after
quitting,
31
thus avoiding this discussion may be counterproduc-
tive. The issue may be addressed by acknowledging potential
weight gain and putting into perspective the substantially
lowered health risks for smokers who quit regardless of their
postcessation weight. For instance, Clair et al.
32
analyzed data
from the Framingham Offspring cohort and found that smoking
cessation was associated with a lower risk of cardiovascular events
regardless of the associated weight gain. In addition, for smokers
who are already obese, Freedman et al.
33
have demonstrated that
the compounded mortality risk for those who both smoke and are
obese is much greater than the mortality risk of excess weight
alone. Therefore, although former smokers gain more weight
compared with continuing smokers, the clinical signicance of
quitting outweighs the potential risks of weight gain. Heavy and
obese smokers should be encouraged to use evidence-based
tobacco dependence treatment and they should be assured that
cessation is a health priority regardless of the weight they may
gain. These patients may also benet most from weight manage-
ment interventions to help attenuate future weight gain. While
formal clinical research may be needed to identify the most
Figure 3. Adjusted differences (and s.e.m.
a
) in weight compared
with 10 years ago for continuing and former smokers by current
CPD or CPD before quitting, controlling for race, gender, education
level and age.
a
s.e.m., standard error of the mean;
b
P=0.02;
c
Did not
remain signicant after Bonferroni adjustment;
d
Po0.001 and
e
Remained signicant after Bonferroni adjustment.
Ten-year weight gain in smokers who quit
S Veldheer et al
4
International Journal of Obesity (2015) 1 6 © 2015 Macmillan Publishers Limited
efcacious interventions for these specic groups, Farley et al.
34
reviewed the topic of concurrent smoking cessation and weight
management and found modest evidence that personalized
weight management support may be effective and does not
appear to reduce abstinence.
There are some limitations to our ndings. First, smoking status
was based on self-report and was not biochemically validated.
Several studies have compared self-reported smoking status with
biochemically validated smoking status in population surveys such
as NHANES and found that underreporting of smoking is minimal
(o2% misclassication).
35,36
A second limitation was that our
weight-related variables were self-reported but as NHANES
includes measured current weight for some participants, we were
able to calculate BlandAltman limits of agreement. Based on the
log-transformed self-reported weight and actual weight measures,
the BlandAltman plots
37
showed good agreement with a bias of
nearly zero and limits of agreement between 0.10 and 0.096. In
addition, the correlation between current self-reported weight
and measured weight was +0.98 overall. No group (never smokers,
continuing smokers, or former smokers and normal weight,
overweight or obese) had a mean difference in self-reported
and measured weight 4± 1.0 kg. Previous analyses of the
NHANES data compared measured weight 10 years ago with
self-reported estimates of weight 10 years ago and found these to
be more variable but still broadly accurate (correlation +0.74, with
a mean under estimation of reported body weight 10 years ago of
o0.9 kg).
19
Regardless of possible variation in the self-reported
data, our ndings provide robust evidence of a pattern of weight
gain that is unlikely to be due to minor underestimations of
historical weight.
CONCLUSION
Baseline BMI and CPD are important factors that contribute to the
magnitude of long-term weight gain following smoking cessation.
Light to moderate smokers (o15 CPD) experienced relatively little
weight gain that could be directly related to smoking cessation.
Heavy smokers (25 CPD) and those who were obese before quitting
experienced signicant SCA weight gain, partly because of lower
than average weight gain or weight loss among continuing smokers
in these groups. For smokers of more than 24 cigarettes per day,
quitting smoking resulted in a weight increase averaging 12.2% of
their body weight. Obese and heavy smokers may particularly
benet from both tobacco dependence treatment and early weight
management intervention during a quit attempt.
CONFLICT OF INTEREST
JF has done paid consulting for pharmaceutical companies involved in producing
smoking cessation medications including GSK, Pzer, Novartis, J&J and Cypress
Bioscience. The other authors have no conict of interest to declare.
ACKNOWLEDGEMENTS
This research was supported by funds from the Penn State Cancer Institute to JF.
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International Journal of Obesity (2015) 1 6 © 2015 Macmillan Publishers Limited
... Weight gain following cessation is a primary reason for relapse and a common barrier to attempting to quit [5][6][7], whereas smoking to control body weight is a frequently cited reason for taking up smoking [8]. Indeed, smokers tend to weigh less (4-5 kg) than their non-smoking counterparts [9,10], whereas smoking cessation is associated with a similar magnitude of weight gain [3,11,12]. Therefore, understanding the relationship between smoking and energy balance is crucial to prevent postcessation weight gain and to address this prominent barrier to successful quit attempts. ...
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Background and aims Smokers typically have a lower body mass index (BMI) than non‐smokers, while smoking cessation is associated with weight gain. In pre‐clinical research, nicotine in tobacco smoking suppresses appetite and influences subsequent eating behaviour; however, this relationship is unclear in humans. This study measured the associations of smoking with different eating and dietary behaviours. Design A cross‐sectional analysis of data from health assessments conducted between 2004 and 2022. Setting An independent healthcare‐based charity within the United Kingdom. Participants A total of 80 296 men and women (mean ± standard deviation [SD]: age, 43.0 ± 10.4 years; BMI, 25.7 ± 4.2 kg/m ² ; 62.5% male) stratified into two groups based on their status as a smoker ( n = 6042; 7.5%) or non‐smoker ( n = 74 254; 92.5%). Measurements Smoking status (self‐report) was the main exposure, while the primary outcomes were selected eating and dietary behaviours. Age, sex and socioeconomic status (index of multiple deprivation [IMD]) were included as covariates and interaction terms, while moderate‐to‐vigorous exercise and sleep quality were included as covariates only. Findings Smokers had lower odds of snacking between meals and eating food as a reward or out of boredom versus non‐smokers (all odds ratio [OR] ≤ 0.82; P < 0.001). Furthermore, smokers had higher odds of skipping meals, going more than 3 h without food, adding salt and sugar to their food, overeating and finding it hard to leave something on their plate versus non‐smokers (all OR ≥ 1.06; P ≤ 0.030). Additionally, compared with non‐smokers, smoking was associated with eating fried food more times per week (rate ratio [RR] = 1.08; P < 0.001), eating fewer meals per day, eating sweet foods between meals and eating dessert on fewer days per week (all RR ≤ 0.93; P < 0.001). Several of these relationships were modified by age, sex and IMD. Conclusions Smoking appears to be associated with eating and dietary behaviours consistent with inhibited food intake, low diet quality and altered food preference. Several of these relationships are moderated by age, sex and socioeconomic status.
... (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. SmCes is known to be associated with long-term weight gain [27], which can lead to white matter hyperintensities via inflammation [28]. We also observed a positive genetic correlation between CigDay and the morphology of the mean second level of the right superior longitudinal fasciculus (dMRI TBSS L2 Superior longitudinal fasciculus R, IDP 1736). ...
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To investigate the pleiotropic mechanisms linking brain structure and function to alcohol drinking and tobacco smoking, we integrated genome-wide data generated by the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN; up to 805,431 participants) with information related to 3,935 brain imaging-derived phenotypes (IDPs) available from UK Biobank (N=33,224). We observed global genetic correlation of smoking behaviors with white matter hyperintensities, the morphology of the superior longitudinal fasciculus, and the mean thickness of pole-occipital. With respect to the latter brain IDP, we identified a local genetic correlation with age at which the individual began smoking regularly (hg38 chr2:35,895,678-36,640,246: rho=1, p=1.01×10-5). This region has been previously associated with smoking initiation, educational attainment, chronotype, and cortical thickness. Our genetically informed causal inference analysis using both latent causal variable approach and Mendelian randomization linked the activity of prefrontal and premotor cortex and that of superior and inferior precentral sulci, and cingulate sulci to the number of alcoholic drinks per week (genetic causality proportion, gcp=0.38, p=8.9×10-4 , rho=-0.18±0.07; inverse variance weighting, IVW beta=-0.04, 95%CI=-0.07-0.01). This relationship could be related to the role of these brain regions in the modulation of reward-seeking motivation and the processing of social cues. Overall, our brain-wide investigation highlighted that different pleiotropic mechanisms likely contribute to the relationship of brain structure and function with alcohol drinking and tobacco smoking, suggesting decision-making activities and chemosensory processing as modulators of propensity towards alcohol and tobacco consumption. All rights reserved. No reuse allowed without permission.
... Hierarchical Age-Period-Cohort Analysis on Obesity contrast, findings from the National Health and NHANES showed the relationship between BMI at the time of smoking and daily cigarette use with weight changes post-cessation. 31 Additionally, the pattern of high prevalence of obesity associated with physical activity before the age of 40, shifting to a lower prevalence afterwards, supports the idea that aging promotes weight gain, while physical activity can mitigate this effect. 35, 36 Age-related increases in body fat percentage also need to be considered when examining BMI trends across different age groups. ...
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... Multiple linear regression analysis was performed to identify factors associated with changes in BW and WC during the intervention. In the models applied for analyzing BW and WC reductions, explanatory variables included sex, age, baseline BMI and WC, pre-intervention action history, smoking history, the number of subsequent guidance sessions (by videophone or messaging), and the number of days that completion was delayed, because these factors have all been shown to correlate with BW reduction [19][20][21][22][23][24] . ...
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Background High sodium intake has been linked to various health outcomes; however, its association with constipation remains unclear, particularly in adult males. This population-based study aimed to investigate the association between daily sodium intake and constipation using data from the National Health and Nutrition Examination Survey (NHANES) 2005–2010. Methods Using data from the NHANES database spanning from 2005 to 2010, a cross-sectional study including 7116 adult male participants from the United States was performed to assess the relationship between daily sodium intake and constipation. Multivariable logistic regression models were used, adjusting for various potential confounders, to evaluate this association. Restricted cubic spline (RCS) methods were applied to explore potential nonlinear trends in the association, and subgroup analyses were conducted through forest plots to examine interactions among different subgroups (P for interaction). Results The study found that an increase in daily sodium intake was significantly associated with a reduced risk of constipation. Trend analysis indicated a statistically significant trend across all models, where increased daily sodium intake was associated with lower constipation risk, with (OR: 0.78, 95% CI: 0.71 ~ 0.85; P < 0.001) in Model 1; (OR: 0.79, 95% CI: 0.73 ~ 0.87; P < 0.001) in Model 2; and (OR: 0.82, 95% CI: 0.69 ~ 0.97; P = 0.023) in Model 3 (P for trend < 0.05 in all models). On the contrary, RCS analysis did not reveal a nonlinear association between daily sodium intake and constipation risk (P = 0.528). Subgroup analysis further supported a consistent negative association between daily sodium intake and constipation risk across different subgroups, with no significant interactions found (all P values > 0.05). Conclusions This study demonstrates a negative association between daily sodium intake and constipation risk among adult males, suggesting that sodium intake might influence intestinal function.
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BACKGROUND: This follow-up study investigated the associations of smoking status and leisure-time physical activity (LTPA) with weight circumference (WC) change. METHODS: In the FinnTwin16 cohort, 3,431 twins (47% men) reported smoking status, LTPA, and WC in early adulthood and 10 years later. Regression models were conducted to investigate associations of smoking status and of LTPA change (metabolic equivalent tasks [MET]-h/week) with WC change (cm) during the follow-up. Within-pair associations were analyzed using linear mixed fixed-effect regression among 800 same-sexed (409 identical) pairs. RESULTS: During the 10-year follow-up, 40% (n=454) quit smoking. Among those who quit smoking, the mean WC increase was 7.4 cm (SD 8.2) and the mean LTPA decrease was -0.02 MET-h/week (SD 35.8). Compared to individuals continuing daily smoking, only quitters who smoked daily at baseline (β 1.87; 95% CI 0.68, 3.06) increased their WC. This association was not robust after shared familial influences were controlled for. Each additional MET-h/week lowered the risk for WC increase among individuals who smoked occasionally (β -0.054; -0,08, -0.003), quitters who smoked daily (β -0.05; -0.06, -0.02) and those who had never smoked (β -0.04; -0.05, -0.03). In the analyses among identical twin pairs, LTPA was associated with less WC increase among those who quit occasional smoking or had never smoked. For quitters from daily smoking, this association approached significance, but no association remained for those continuing smoking. CONCLUSIONS: Smoking cessation seems to be associated with WC increase, but familial confounding is involved in this process. LTPA may inhibit post-cessation WC increase.
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Although quitting smoking lowers the risk of developing chronic conditions, it usually leads to weight gain. Literature on the association between weight gain after quitting smoking and the future development of hypertension is scarce. Among 234 596 individuals who visited our health center, 856 who had quit smoking for whom data were available at least 6 years after smoking cessation were included. We evaluated changes in blood pressure and antihypertensive drug prescription rate at 1 and 6 years after smoking cessation. We also compared weight and blood pressure between the smoking cessation and continued smoking groups after 6 years. Multiple regression analyses were performed to identify predictors of changes in systolic and diastolic blood pressures using covariates affecting blood pressure. Since a median weight gain of 1.8 kg was observed at 1 year after smoking cessation, we divided the participants into high and low-weight gain groups. No significant intergroup difference in the antihypertensive drug prescription rate was observed after 6 years. The high weight gain group showed significant increases in systolic and diastolic blood pressures after 6 years. Multiple regression analyses revealed that systolic blood pressure was affected by age and high weight gain, while diastolic blood pressure was affected by high weight gain. Our findings suggest that weight gain following smoking cessation leads to blood pressure elevation: the smoking cessation group gained more weight and had higher blood pressure than the continued smoking group. Therefore, weight loss guidance may be useful for individuals who want to quit smoking. Participants in the high weight gain group showed significant increases in systolic and diastolic blood pressures at 6 years after smoking cessation that were significantly different from those observed in participants in the low weight gain group and the continued smoking group.
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The discrepancy between cigarette smoking status reported during an interview and measured level of serum cotinine, a nicotine biomarker, was investigated in a representative sample of the US population aged ≥17 years (N = 15,357). Data were collected from participants in the Third National Health and Nutrition Examination Survey (1988-1994). Among self-reported smokers, 7.5% (95% confidence interval: 6.3, 8.7) had a serum cotinine level less than or equal to 15.0 ng/ml, the selected cutoff point for identifying nonsmokers. Age (p < 0.01), race/ethnicity (p < 0.01), and average number of cigarettes smoked per day (p < 0.01) were associated with these discrepant findings. Among self-reported nonsmokers, 1.4% (95% confidence interval: 1.1, 1.7) had a serum cotinine level greater than 15.0 ng/ml, the selected cutoff point for identifying smokers. Race/ethnicity (p < 0.01), education (p < 0.01), number of household members who smoked in the home (p = 0.03), and self-reported smoking status from an earlier home interview (p < 0.01) were associated with these discrepant findings. Differences in smoking patterns, including the extent of nicotine dosing, may explain most of the discrepancy observed among self-reported smokers, whereas deception regarding smoking status may explain most of the discrepancy among self-reported nonsmokers. This study provides evidence that self-reported smoking status among adult respondents to a population-based survey conducted in a private medical setting is accurate.
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Background-Starting in 1999, the National Health and Nutrition Examination Survey (NHANES) became a continuous, ongoing annual survey of the noninstitutionalized civilian resident population of the United States. A continuous survey allowed content to change to meet emerging needs. Objective-This report describes how NHANES for 1999-2010 was designed and implemented. NHANES is a national survey designed to provide national estimates on various health-related topics. Methods-The survey used in-person face-to-face interviews and physical examinations for data collection. Approximately 5,000 people per year participated in NHANES. The 5,000 people surveyed each year are representative of the entire U.S. population.
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Concern about weight gain after quitting smoking is often cited as a barrier to smokers making a quit attempt or seeking treatment. To identify whether smokers who are non-treatment seekers (NTS) are more concerned about weight gain and have lower confidence to maintain weight after quitting smoking as compared with treatment-seeking smokers (TS). Participants were smokers recruited from Penn State Hershey Medical Center and family practice outpatient clinics. A total of 102 NTS and 186 TS, who participated in a smoking cessation trial, completed a survey regarding tobacco use, weight concern and diet. Stepwise logistic regression was used to identify variables associated with treatment seeking, overall and stratified by those who gained and did not gain weight on a previous quit attempt. Fifty three per cent of the overall sample (47.1% NTS vs. 56.5% TS, p = 0.127) had gained weight on a prior quit attempt. Among smokers who had gained weight, higher weight gain concern (WGC) and lower confidence in ability to maintain weight were significantly associated with being a NTS after adjusting for other factors. Among smokers who gained weight on a previous quit attempt, NTS had greater concern about gaining weight and less confidence in their ability to maintain their weight after quitting than treatment seekers. Clinicians can identify smokers for whom WGC may be a barrier to seeking treatment by asking if they gained weight on a previous quit attempt. These smokers should be assured that this issue will be addressed in treatment.