Original Researchajog.org

GYNECOLOGY

Obesity, smoking, and risk of vasomotor menopausal
symptoms: a pooled analysis of eight cohort studies
Debra J. Anderson, PhD; Hsin-Fang Chung, PhD; Charrlotte A. Seib, PhD; Annette J. Dobson, PhD; Diana Kuh, PhD;
Eric J. Brunner, PhD; Sybil L. Crawford, PhD; Nancy E. Avis, PhD; Ellen B. Gold, PhD; Gail A. Greendale, MD;
Ellen S. Mitchell, PhD; Nancy F. Woods, PhD; Toyoko Yoshizawa, PhD; Gita D. Mishra, PhD

BACKGROUND: Frequent and severe vasomotor symptoms during
menopause are linked with adverse health outcomes. Understanding
modifiable lifestyle factors for the risk of vasomotor menopausal symptoms
is important to guide preventive strategies.
OBJECTIVE: We investigated the associations between body massindex and smoking, their joint effects with the risk of vasomotor symptoms,
and whether the associations differed by menopausal stage.
STUDY DESIGN: The International Collaboration for a Life Course
Approach to Reproductive Health and Chronic Disease Events pooled dataon 21,460 midlife women from 8 studies (median age, 50 years; interquartile range, 49e51 years) for the cross-sectional analysis. Four studies
provided data for the prospective analysis (n¼11,986). Multinomial logistic regression models with 4 categories of frequency/severity for theoutcome of vasomotor symptoms were used to estimate relative risk ratios
and 95% confidence intervals that were adjusted for within-study correlation and covariates.
RESULTS: At baseline, nearly 60% of the women experienced vasomotor symptoms. One-half of them were overweight (30%) or obese(21%), and 17% were current smokers. Cross-sectional analyses showedthat a higher body mass index and smoking more cigarettes with longer
duration and earlier initiation were all associated with more frequent orsevere vasomotor symptoms. Never smokers who were obese had a 1.5fold (relative risk ratio, 1.52; 95% confidence interval, 1.35e1.73) higherVasomotor menopausal symptoms(VMS), which include hot ﬂushes
and night sweats, are considered the
cardinal symptoms of menopause1 andare 1 of the main reasons formenopause-related health service use.2,3
It is estimated that up to 80% of women
will report VMS at some time during themenopausal transition,4e6 although thepercentage of women who experience
symptoms varies from as low as 20%
among some Asian populations4,5 to60‒80% in some North American4 andCite this article as: Anderson DJ, Chung H-F, Seib CA,
et al. Obesity, smoking, and risk of vasomotor menopausal symptoms: a pooled analysis of eight cohort
studies. Am J Obstet Gynecol 2020;222:478.e1-17.
0002-9378/$36.00ª 2019 Elsevier Inc. All rights reserved.
https://doi.org/10.1016/j.ajog.2019.10.103

risk of often/severe vasomotor symptoms, compared with never smokers
who were of normal-weight. Smoking strengthened the association
because the risk of often/severe vasomotor symptoms was much greater
among smokers who were obese (relative risk ratio, 3.02; 95% confidence
interval, 2.41e3.78). However, smokers who quit at <40 years of age
were at similar levels of risk as never smokers. Prospective analyses
showed a similar pattern, but the association attenuated markedly after
adjustment for baseline vasomotor symptoms. Furthermore, we found thatthe association between body mass index and vasomotor symptoms
differed by menopausal status. Higher body mass index was associatedwith increased risk of vasomotor symptoms in pre- and perimenopause butwith reduced risk in postmenopause.
CONCLUSION: High body mass index ("25 kg/m2) and cigarettesmoking substantially increased women’s risk for experiencing frequent orsevere vasomotor symptoms in a dose-response manner, and smoking
intensified the effect of obesity. However, the effect of body mass index on
the risk of vasomotor symptoms was opposite among postmenopausal
women. Maintaining a normal weight before the menopausal transitionand quitting smoking at <40 years of age may mitigate the excess risk ofvasomotor symptoms in midlife.
Key words: hot flushes, night sweats, overweight, obesity, smoking,vasomotor symptoms

European6 subgroups. VMS also vary byintensity or severity, with some womenreporting only mild transient symptoms
and others reporting intense heatspreading over the body and profuse
sweating that can disrupt sleep.3 Earlyonset VMS has been linked with endothelial dysfunction7 and is considered abiomarker for the development of cardiovascular disease in later life.8
Although menopause-related hormonal changes are associated primarily
with
VMS,9,10
evidencefrompopulation-based studies suggests thatcertain lifestyle and socio-demographic
factors are also associated with frequency and severity of VMS.11e13 For
instance, epidemiologic data haverevealed that current smokers have asigniﬁcantly higher odds of VMS
compared with nonsmokers,4 which has
been attributed to the antiestrogenic

478.e1 American Journal of Obstetrics & Gynecology MAY 2020

effects of tobacco smoking.12 Other
notable lifestyle factors that are associated with a higher risk of VMS are
overweight and obesity, where increased
subcutaneous adipose tissue is likely toprovide an insulating layer that blunts
abdominal heat transfer,14 which, during
the menopausal transition, reduces the
body’s ability to respond to changes incore temperature. In addition, smoking
and body weight are also interrelated.
Given the increased risk of VMS that isconferred by both smoking and overweight/obesity, a better understanding of
their joint associations would provide
important information for women at
midlife because weight gain is common
during the menopausal transition. Also,
it is possible that the relative contribution of body fat to the risk of VMS in
the early and late stage of menopause
may differ.15

GYNECOLOGY

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AJOG at a Glance
Why was this study conducted?
This pooled analysis provided precise estimates of the individual and joint associations between body mass index and smoking with the risk of vasomotor
menopausal symptoms.
Key ﬁndings
Higher body mass index and greater smoking were associated with more
frequent/severe vasomotor menopausal symptoms in the cross-sectional analysis;
smoking strengthened the effect of obesity. However, women who quit smoking
before age 40 years had a similar level of risk as never smokers. Prospective analyses showed similar results, but the individual and joint effects of body massindex and smoking on subsequent vasomotor menopausal symptoms at the 3year follow up attenuated markedly after adjustment for baseline vasomotor
menopausal symptoms. The effect of body mass index on vasomotor menopausal
symptoms risk differed in pre-/perimenopause and postmenopause.
What does this add to what is known?
Being both obese and a smoker conferred a much higher risk of frequent/severe
vasomotor menopausal symptoms than either alone. Maintaining a normal
weight before the menopausal transition and smoking cessation before age 40
years may mitigate the excess risk of frequent/severe vasomotor menopausal
symptoms.

Determining the modiﬁable healthbehaviors and identifying those individuals who are at an increased risk ofthe development of symptoms acrossracial/ethnic groups is essential fordeveloping preventative strategies toreduce both the individual and societal
burden that is associated with VMS.
Therefore, this study investigated thecross-sectional and prospective associations between body mass index (BMI)
and smoking and their joint effects withthe risk of VMS in a pooled sample fromthe International Collaboration for aLife Course Approach to Reproductive
Health and Chronic Disease Event(InterLACE) consortium. We further
examined whether the effects of BMI andsmoking on the risk of VMS differ bymenopausal status.

Materials and Methods
Study participants
InterLACE is an individual-level pooled
study of 20 observational studies from10 countries. Full details on the
study aims, data harmonization, andcharacteristics across the studies were
published previously.16,17 Each participating study has been undertaken withethical approval from the Institutional
Review Board or Human Research
Ethics Committee at each research
institution, and all participants provided consent for that study. For thisanalysis, 8 studies that had collected
information on BMI, smoking status,and degree of VMS (either reporting infrequency or severity) were included:
Australian Longitudinal Study on
Women’s Health (ALSWH),18 Medical
Research Council National Surveyof Health and Development (NSHD),19
National Child Development Study(NCDS),20 Study of Women’s HealthAcross the Nation (SWAN),21 Whitehall
II Study (WHITEHALL),22 Seattle
Midlife Women’s Health Study(SMWHS),23 Healthy Ageing of Women
Study (HOW),24 and Japanese Midlife
Women’s Health Study (JMWHS).24
For the longitudinal studies, data for
women around the age of 50 years wereused as an analytic baseline to make the
distribution of menopausal status and
VMS more comparable across studies.
For instance, Survey 2 (1998) was
selected as analytic baseline for ALSWH
because the median age was 50 years;
Visit 4 (2000e2002) was selected for

Original Research

SWAN and Survey 3 (1991e1994) for
WHITEHALL (Table 1). At this baseline,
21,460 women who had reported their
BMI, smoking status, and frequency orseverity of VMS and had provided
complete information on the covariates(listed later) were included for the crosssectional analyses. Four studies(ALSWH, NSHD, SWAN, and WHITEHALL) had longitudinal data to examine
the association with the risk of subsequent VMS at 3-year follow up. We
excluded 3791 women who did not return to the study or had incomplete
follow-up data on VMS, menopausal
status, or hormone therapy, which left
11,986 women for prospective analyses.
The excluded women were more likely to
be current smokers, obese, or lesseducated or to report VMS at baseline,
compared with the included women(data not shown).

Main outcome and exposure
variables
Hot ﬂushes and night sweats data werecollected at analytic baseline with the useof self-reported menopausal symptom
checklists that recalled the symptoms
over a speciﬁc period. VMS were deﬁned
as either hot ﬂushes or night sweats. In
ALSWH, women were asked how
frequently they have experienced VMS
in the last 12 months; SWAN asked frequency in the past 2 weeks. The frequency responses were categorized asnever, rarely, sometimes, and often. In
NSHD and NCDS, women were asked
how severely they have been bothered by
VMS in the last 12 months, and theseverity responses were categorized asnever, mild, moderate, and severe. In theother 4 studies, women also reported
their severity of VMS but in a recent
period (in the last 24 hours or at the
moment). For the pooled analysis, thedegree of VMS was harmonized as never,rarely, sometimes, and often (if reporting frequency) or never, mild, moderate,and severe (if reporting severity). Subsequent VMS was deﬁned based on frequency/severity of VMS reported at
3-year follow up.
Height and weight were self-reported
or measured at analytic baseline. BMI
was computed as weight divided by the

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478.e2

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TABLE 1

Characteristics of 8 studies in the International Collaboration for a Life Course Approach to Reproductive Health andChronic Disease Events consortium
Survey (year)
selected foranalytic baselinea

Survey (year)
selected for
3-year follow up

StudyCountryN

Median age atbaseline, y(interquartile range)

Australian Longitudinal Study on
Women’s Health (ALSWH)

Australia

10,32350 (48e51)

Survey 2 (1998)

Survey 3 (2001)

National Survey of Health andDevelopment (NSHD)

UK

1,068

50a

Survey 1996 (1996)

Survey 1999 (1999)

National Child Development
Study (NCDS)

UK

3,983

50a

Survey 8 (2008)

N/A

Study of Women’s HealthAcross the Nation (SWAN)

USA

2,345

50 (48e52)

Visit 4 (2000e2002)

Visit 7 (2003e2005)

Whitehall II Study (WHITEHALL)

UK

2,041

50 (45e55)

Survey 3 (1991e1994)

Survey 4 (1995e1996)

Seattle Midlife Women’s HealthStudy (SMWHS)

USA

189

50 (46e53)

Survey 2000 (2000)

N/A

Healthy Ageing of Women
Study (HOW)

Australia768

54 (52e57)

Survey 1 (2001)

N/A

Japanese Midlife Women’s
Health Study (JMWHS)b

Japan

743

N/A

Survey 1 (2002)

N/A

Overall

21,46050 (49e51)

N/A, not applicable.
a

For the longitudinal studies, data for women around the age of 50 years were used as analytic baseline to make the data more comparable across studies; the women who participated in the NSHD
(1946 British birth cohort) and NCDS (1958 British birth cohort) were at age 50 years in the 1996 and 2008 survey, respectively; b Provided age by category only (#55 and >55 years), and 48% of
women were aged >55 (age range from 45e60 years).
Anderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

square of height and categorized as underweight (<18.5 kg/m2), normal
weight (18.5e24.9 kg/m2), overweight(25e29.9 kg/m2), and obese ("30 kg/m2), according to the World Health Organization classiﬁcation.25 Because only
357 women (1.7%) were classiﬁed asunderweight, they were combined into
the normal weight group (BMI, <25 kg/m2). For the Asian population (Japanese and other Asian), we performed asensitivity analysis by using a lower BMI
cut-off of 23 and 27.5 kg/m2 for overweight and obesity.25 Smoking status
was self-reported and categorized asnever smoker, former smoker, andcurrent smoker. For the current
smokers, data on number of cigarettes
smoked per day, duration of smoking,and pack-years were collected in
ALSWH, SWAN, and WHITEHALL(n¼14,709), although these details were
not available for the former smokers at
analytic baseline. The average numberof cigarettes smoked per day was

categorised as 1e9, 10e19, and "20cigarettes/day. Smoking duration wasdeﬁned by the time between age at
initiation and age at baseline and categorized as <20, 20e29, and "30 years.
Pack-years (number of cigarettes
smoked per day divided by 20 andmultiplied by the duration of smoking)was categorized as <10, 10e19, 20e29,
30e39, and "40 pack-years. Age atsmoking initiation was collected forboth former and current smokers andcategorized as #15, 16e19, and "20years of age. In ALSWH, data on age atquitting smoking (categorized as <30,30e39, and "40 years of age) and years
since quitting smoking (categorized as
1e5, 6e14, 15e19, "20 years) werecollected for former smokers. To test thejoint effects of bodyweight and smoking
status, a new variable with 9 levels wascreated. It was made up of the combinations of BMI (underweight/normal,
overweight, and obese) and smoking
status (never, former, and current).

478.e3 American Journal of Obstetrics & Gynecology MAY 2020

Confounding factors
Participants reported on a range of demographic and reproductive factors atbaseline, including birth year, race/
ethnicity/region, education level, menopausal status, and use of menopausal
hormone therapy (MHT). Responses forbirth year were categorized as <1940,
1940e1949, and 1950e1959. Race/ethnicity/region was deﬁned based on
self-identiﬁed race/ethnicity, country ofbirth, the language spoken at home, orthe country in which the study was conducted (residency). Seven racial/ethnic
groups with regional status were deﬁned
here: white-Australian, white-European,
white-American, Japanese, other Asian(Chinese, South/Southeast Asian), African American/black/Caribbean, andOther (Hispanic, Middle Eastern,
Aboriginal, and mixed). For educationlevel, responses were categorized ascompletion of #10 years (corresponding
to less than high school or O-level in the
United Kingdom), 11e12 years (highGYNECOLOGY

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school or A-level in the United
Kingdom), and >12 years (at least morethan a high school education). Menopausal status was collapsed and categorized into 5 groups based on menstrual
bleeding patterns and gynecologic surgery: (1) unknown because of surgery(hysterectomy and/or oophorectomy,
which included bilateral oophorectomy[surgical menopause] because of insufﬁcient information to deﬁne surgicalmenopause for all studies), (2) unknown
because of hormone use (unless natural
menopause speciﬁed), (3) premenopause(regular menstrual cycles in the last 3
months and 12 months), (4) perimenopause (menses in the past 3 months andchanges/irregularity in menstrual patterns in the past 12 months or no menses
in the previous 3 months, but menses in
the preceding 11 months), and (5) natural postmenopause (amenorrhea for atleast 12 months). Women who were taking MHT (eg, estrogen) were classiﬁed as
current hormone users.

Statistical analyses
Multinomial logistic regression models
with 4 categories of outcome for VMS(never, rarely/mild, sometimes/moderate, and often/severe) were used to
examine the associations between BMI,
smoking status, and the joint effects withthe risk of VMS at baseline (crosssectional analysis) and 3-year follow up(prospective analysis). A generalized
logit model was used to estimate relativerisk ratios (RRR) and 95% conﬁdence
intervals (CIs) for each VMS category
with the use of “no symptom” as thereference category. In the cross-sectional
analysis, the associations were obtained
separately for the studies of VMS frequency and VMS severity, followed by
the overall estimates that incorporated
study design (study cluster) into theanalyses. The models were ﬁrst adjusted
for menopausal status and the use of
MHT at baseline (model 1) and additionally were adjusted for race/ethnicity/
region, education level, and included
both BMI and smoking status in thesame model (model 2). Furthermore, we
included an interaction term between
the 2 exposures in the model andanalyzed their joint associations. Because

Asian women are less likely to be overweight or obese and less likely to havefrequent or severe VMS, we performed asensitivity analysis by excluding Asian
women (996 Japanese and 488 other
Asian).
The dose-response relationships between the different aspects of smoking
and risk of VMS were examined with theuse of data from ALSWH, SWAN, and
WHITEHALL (n¼14,709). The numberof cigarettes, duration, and pack-years ofsmoking were analyzed for current
smokers; age at having initiated smoking
was analyzed for both former and current smokers. Age at quitting and years
since quitting smoking for former
smokers could be analyzed only withthe use of data from ALSWH. Neversmoker was used as the reference groupfor all smoking measures. All models
were adjusted for the confounding variables mentioned earlier, which included
BMI.
For the prospective analysis, 4 studies
provided data (n¼11,986). BMI andsmoking status at baseline and subsequent VMS at 3-year follow up were
examined in the model fully adjusted formenopausal status and the use of MHT
at 3-year follow up and baseline covariates that are mentioned in model 2 andadditionally adjusted for frequency/
severity of VMS at baseline.
We further investigated whether
menopausal status modiﬁed the association between BMI, smoking, and VMS.
The interaction term between BMI andmenopausal status and between smoking
status and menopausal status was
included in the models. If there was astatistical interaction, the association
was further stratiﬁed by concurrent
menopausal status at baseline (crosssectional analyses) and at 3-year follow
up (prospective analyses). The SURVEYLOGISTIC procedure in SAS software (version 9.4; SAS Institute Inc,
Cary, NC), which incorporated the study
cluster into the analyses, was used for themultinomial logistic regression.

Results
Baseline characteristics
A total of 21,460 women with a medianage of 50 years (interquartile range,

Original Research

49e51 years) from 8 studies were
included at baseline (Table 1). HOW andJMWHS recruited women at slightly
older ages at approximately 55 years. In
the overall sample, almost one-half of
the women were premenopausal or
perimenopausal (19% and 27%,
respectively); 19% of the women had anatural menopause; 20% of the women
had had a hysterectomy or oophorectomy, and 14% of the women wereclassiﬁed as unknown menopausal statusbecause of hormone use before menopause (Table 2). Nearly 20% of thewomen were currently taking MHT,
regardless of menopausal status. Acrossstudies, one-half of the women were
either overweight (30%) or obese (21%);28% of the women were former
smokers, and 17% of the women werecurrent smokers. Overall, up to 55% of
the women experienced hot ﬂushes(rarely/mild to often/severe), and 45% of
the women reported night sweats.

Cross-sectional associations
Table 3 shows results separately forstudies of VMS frequency, VMS severity,and the overall sample. Overall, thepattern of results was similar, regardlessof whether VMS were assessed as frequency or severity. BMI and smoking
status were associated with the risk of
VMS, even when both were included in
the same model (model 2). We foundthat women who were overweight andobese and were current smokers weremore likely to report some degree of
VMS (rarely/mild to often/severe). For
instance, in the overall sample,
compared with the normal weightgroup, a dose-response relationship wasobserved between overweight and thefrequency/severity of VMS, withadjusted RRR of 1.24 (95% CI,
1.18e1.30), 1.30 (95% CI, 1.17e1.46),
and 1.53 (95% CI, 1.42e1.65) for rarely/
mild, sometimes/moderate, and often/
severe VMS, respectively. Similar trends
were seen for the obese group, withadjusted RRR of 1.15 (95% CI,
1.08e1.24), 1.32 (95% CI, 1.20e1.44),
and 1.59 (95% CI, 1.41e1.78), respectively. When we applied a lower cut-off
point of overweight (BMI, "23 kg/m2)
and obesity (BMI, "27.5 kg/m2) for the

MAY 2020 American Journal of Obstetrics & Gynecology

478.e4

54.9
41.3

1940e1949

1950e1959

478.e5 American Journal of Obstetrics & Gynecology MAY 2020
6.3
4.6
2.3
3.0
2.9

White- American

Japanese

Other Asian

African American/Black/Caribbean

Other

14.2
19.4
27.4
19.1

Unknown because of hormone use

Premenopause

Perimenopause

Natural postmenopause

19.1

Yes

Anderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

80.9

No

Current use of menopausal
hormone therapy

19.8

Unknown because of surgery

23.4

76.6

11.0

24.2

23.0

16.1

25.6

34.9

36.6

Menopausal status

17.1

17.4

>12

48.1

1.5

N/A

2.1

0.1

0.7

16.9

78.8

25.7

74.3

N/A

ALSWH
(n¼10,323)

Study, %

11e12

#10

46.0

40.1

White- European

Education level, y40.8White- Australian

Race/ethnicity/region

3.8

Overall(n¼21,460), %<1940

Birth year

Variable

Analytic baseline characteristics of study sample

TABLE 2

20.3

79.7

16.2

24.5

19.8

21.6

17.9

6.4

25.8

67.8

N/A

N/A

N/A

N/A

N/A

100

N/A

N/A

100

N/A

NSHD
(n¼1068)

9.6

90.4

21.0

30.1

18.8

13.1

16.9

27.5

10.3

62.2

0.8

0.4

0.6

N/A

N/A

98.2

N/A

100

N/A

N/A

NCDS
(n¼3983)

19.4

80.6

21.2

56.2

6.7

11.3

4.5

78.6

15.8

5.6

6.1

25.9

9.5

10.5

48.0

N/A

N/A

58.7

41.3

N/A

SWAN
(n¼2345)

15.1

84.9

31.8

18.3

22.1

12.0

15.9

29.6

16.2

54.2

12.3

N/A

N/A

N/A

N/A

87.7

N/A

12.0

48.5

39.5

WHITEHALL(n¼2041)

21.7

78.3

13.8

30.7

26.5

25.9

3.2

86.2

13.8

0

1.1

5.8

7.9

N/A

85.2

N/A

N/A

52.9

46.6

0.5

SMWHS
(n¼189)

34.9

65.1

49.1

11.6

3.4

7.6

28.4

32.7

15.6

51.7

4.2

N/A

1.0

N/A

N/A

12.5

82.3

14.6

85.4

N/A

HOW
(n¼768)(continued)

3.2

96.8

55.6

11.3

19.8

2.3

11.0

31.2

59.4

9.4

N/A

N/A

N/A

100

N/A

N/A

N/A

52.5a

47.5a

N/A

JMWHS
(n¼743)

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c

17.4

17.1
22.3
13.5

Rarely/mild

Sometimes/moderate

Often/severe

9.9

Sometimes/moderate

Often/severe

24.2
15.4

Rarely/mild

Sometimes/moderate

Often/severe

16.2

26.9

16.5

40.3

11.1

19.7

14.3

54.9

14.6

24.9

15.7

13.0

22.4

22.4

42.2

8.3

15.2

18.9

57.6

10.5

20.3

21.3

47.8

25.3

40.5

34.2

12.5

24.3

63.2

NSHD
(n¼1068)

22.4

39.1

8.4

30.1

13.7

31.2

6.9

48.3

19.4

36.5

8.6

35.5

21.9

29.3

48.8

22.5

33.0

44.5

NCDS
(n¼3983)

12.6

8.3

31.6

47.5

7.1

4.9

24.6

63.4

10.6

7.0

26.4

56.0

14.1

26.5

59.4

35.9

27.6

36.5

SWAN
(n¼2345)

10.8

12.3

17.7

59.1

7.2

8.8

15.3

68.7

8.2

10.6

17.8

63.4

16.9

30.9

52.2

15.1

32.2

52.7

WHITEHALL(n¼2041)

9.0

9.0

18.5

63.5

5.8

2.6

13.8

77.8

6.3

9.0

16.9

67.7

10.1

39.2

50.8

23.8

25.4

50.8

SMWHS
(n¼189)

5.3

12.2

32.7

49.7

3.5

8.7

25.7

62.1

4.0

11.1

28.8

56.1

9.5

27.6

62.9

24.7

32.4

42.8

HOW
(n¼768)

4.4

8.6

37.4

49.5

1.1

3.0

20.7

75.2

4.3

7.8

33.0

54.9

9.3

4.0

86.7

1.2

13.2

85.6

JMWHS
(n¼743)The Japanese Midlife Women’s Health Study provided age by category only (#55 and >55 years); thus, birth year was categorized based on age categories; b Only 357 women (1.7%) were underweight (body mass index, <18.5 kg/m2); thus, they were categorzed
into the normal weight group; c Vasomotor symptoms were defined as having either hot flushes or night sweats.
Anderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

a

GYNECOLOGYALSWH, Australian Longitudinal Study on Women’s Health; HOW, Healthy Ageing of Women Study; JMWHS, Japanese Midlife Women’s Health Study; N/A, not applicable; NCDS, National Child Development Study; NSHD, National Survey of Health and Development;
SMWHS, Seattle Midlife Women’s Health Study; SWAN, Study of Women’s Health Across the Nation; WHITEHALL, Whitehall II Study.

41.9
18.4

Never

Frequency/severity of vasomotor symptoms

15.0
17.8

Rarely/mild

57.2

Never

Frequency/severity of night sweats

47.2

Never

Frequency/severity of hot flushes
44.8

17.1

27.6

Former smoker

Current smoker

26.7

54.9

56.2

20.2

31.6

48.2

ALSWH
(n¼10,323)

Study, %Never smoker

Smoking status

Obese ("30 kg/m )

2

21.0

30.4

2

Overweight (25e29.9 kg/m )48.5

Normal weight (<25 kg/m2)bBody mass index

Variable

Overall(n¼21,460), %Analytic baseline characteristics of study sample (continued)

TABLE 2

ajog.org

Original Research

MAY 2020 American Journal of Obstetrics & Gynecology

478.e6

3,9062,932

Obese ("30 kg/m2)

478.e7 American Journal of Obstetrics & Gynecology MAY 2020

2,094

2,625

1,584

Overweight(25e29.9 kg/m2)

Obese ("30 kg/m2)

2,547

1,647

Former smoker

Current skomer

32.9

41.2

46.4

36.9

39.2

15.4

15.3

18.6

14.4

16.8

18.1

18.8

18.9

19.7

20.7

19.7

18.4

Rarely/
mild

28.2

27.8

22.9

28.9

26.2

23.6

26.2

24.4

22.3

23.1

25.4

22.4

Sometimes/
moderate

23.6

15.7

12.1

19.8

17.8

12.3

21.1

15.6

13.9

18.2

17.0

13.3

Often/
severeAnderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

4,598

Never smoker

Smoking status

4,583

Normal (<25 kg/m2)

Body mass index

Severity of vasomotor
symptoms (NSHD, NCDS,
WHITEHALL, SMWHS,
HOW, JMWHS; n¼8792)
46.1

33.9

3,381

Current smoker

41.1

7,193

Former smoker

44.1

38.0

37.9

46.0

Never

Never smoker

Smoking status

5,830

Overweight(25e29.9 kg/m2)

N

Normal (<25 kg/m2)

Body mass index

Frequency of vasomotor
symptoms (ALSWH,
SWAN; n¼12668)

Variable

Vasomotor symptoms (hot flushes
and night sweats) (%)

1.17 (0.81e1.68)

0.97 (0.79e1.20)—

0.98 (0.70e1.36)

1.10 (0.90e1.34)—

1.20 (1.17e1.23)

1.02 (1.02e1.02)—

1.32 (1.08e1.61)

1.31 (1.26e1.36)—

Rarely/mild

Model 1a1.80 (1.54e2.10)

1.43 (1.07e1.91)—

1.48 (1.09e2.02)

1.31 (1.06e1.62)—

1.41 (0.99e2.01)

1.16 (1.03e1.30)—

1.17 (0.91e1.49)

1.37 (1.16e1.61)—

Sometimes/
moderate

2.70 (1.91e3.82)

1.53 (1.08e2.16)—

1.92 (1.30e2.82)

1.70 (1.30e2.23)—

1.72 (1.33e2.24)

1.17 (0.98e1.39)—

1.50 (1.49e1.50)

1.54 (1.40e1.68)—

Often/severe

Relative risk ratio (95% confidence interval)

1.33 (1.01e1.76)

1.12 (0.99e1.26)—

1.07 (0.87e1.33)

1.20 (1.08e1.33)—

1.17 (1.12e1.22)

1.01 (1.00e1.02)—

1.17 (1.15e1.18)

1.26 (1.21e1.31)—

Rarely/mild

Model 2b1.43 (1.33e1.52)

1.19 (0.95e1.48)—

1.37 (1.07e1.74)

1.20 (1.16e1.24)—

1.33 (1.11e1.61)

1.15 (1.03e1.28)—

1.30 (1.27e1.32)

1.38 (1.21e1.56)—

Sometimes/
moderate(continued)

2.11 (1.69e2.64)

1.26 (0.99e1.59)—

1.79 (1.38e2.33)

1.56 (1.31e1.85)—

1.58 (1.46e1.70)

1.12 (0.95e1.32)—

1.51 (1.50e1.51)

1.51 (1.34e1.71)—

Often/severe

Adjusted cross-sectional associations of body mass index and smoking status with the risk of vasomotor symptoms at baseline (n[21,460)

TABLE 3

Original Research GYNECOLOGY
ajog.org

6,531

4,516

Overweight(25e29.9 kg/m2)

Obese ("30 kg/m2)

3,583

1,849

1,099

2,384

1,404

728

Overweight & neversmokerOverweight & former
smokerOverweight &current smoker

Obese & never smoker

Obese & former smoker

Obese & current smoker

27.9

38.3

40.1

30.5

37.5

41.3

37.3

45.2

49.2

17.3

17.4

19.5

18.4

16.6

19.7

16.7

17.9

19.0

17.3

17.3

19.3

18.5

18.6

18.3

Rarely/
mild

29.4

24.9

24.0

27.8

28.0

23.9

25.8

24.9

21.1

27.1

25.8

22.5

25.1

25.7

22.9

Sometimes/
moderate

25.4

19.4

16.4

23.3

17.9

15.2

20.3

12.1

10.8

22.2

15.6

13.2

18.8

17.3

12.8

Often/
severe1.55 (1.20e2.02)

1.15 (0.86e1.54)

1.25 (1.03e1.50)

1.53 (1.15e2.03)

1.17 (0.97e1.41)

1.25 (1.11e1.40)

1.13 (0.96e1.33)

1.04 (0.89e1.21)—

1.17 (1.03e1.33)

0.99 (0.91e1.07)—

1.22 (1.00e1.48)

1.23 (1.11e1.36)—

Rarely/mild

Model 1a2.29 (1.73e3.03)

1.43 (1.17e1.76)

1.33 (1.07e1.66)

2.02 (1.71e2.39)

1.77 (1.41e2.22)

1.35 (1.13e1.60)

1.54 (1.20e1.99)

1.29 (1.03e1.63)—

1.55 (1.20e2.00)

1.26 (1.01e1.57)—

1.28 (1.05e1.56)

1.34 (1.17e1.55)—

Sometimes/
moderate

3.72 (2.56e5.40)

2.13 (1.38e3.28)

1.76 (1.37e2.26)

3.17 (2.38e4.23)

2.23 (1.64e3.02)

1.68 (1.37e2.06)

2.28 (1.47e3.53)

1.24 (0.96e1.61)—

2.07 (1.45e2.96)

1.30 (0.99e1.71)—

1.67 (1.37e2.05)

1.61 (1.42e1.84)—

Often/severe

Relative risk ratio (95% confidence interval)

1.50 (1.28e1.75)

1.13 (0.94e1.38)

1.21 (1.08e1.35)

1.59 (1.37e1.84)

1.23 (1.09e1.40)

1.28 (1.18e1.38)

1.18 (0.97e1.44)

1.12 (1.02e1.23)—

1.21 (1.08e1.35)

1.03 (0.97e1.09)—

1.15 (1.08e1.24)

1.24 (1.18e1.30)—

Rarely/mild

Model 2b2.14 (1.79e2.56)

1.38 (1.23e1.55)

1.30 (1.18e1.42)

1.73 (1.56e1.93)

1.56 (1.38e1.76)

1.26 (1.08e1.46)

1.31 (1.21e1.42)

1.15 (1.06e1.24)—

1.39 (1.24e1.56)

1.16 (1.05e1.27)—

1.32 (1.20e1.44)

1.30 (1.17e1.46)—

Sometimes/
moderate

MAY 2020 American Journal of Obstetrics & Gynecology

Included menopausal status and use of menopausal hormone therapy at baseline; b Additionally included race/ethnicity/region, education, and both body mass index and smoking status in the same model.
Anderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

a

ALSWH, Australian Longitudinal Study on Women’s Health; NSHD, National Survey of Health and Development; NCDS, National Child Development Study; SWAN, Study of Women’s Health Across the Nation; WHITEHALL, Whitehall II Study; SMWHS, Seattle Midlife
Women’s Health Study; HOW, Healthy Ageing of Women Study; JMWHS, Japanese Midlife Women’s Health Study

3.02 (2.41e3.78)

1.85 (1.33e2.57)

1.52 (1.35e1.73)

2.54 (2.22e2.89)

1.87 (1.59e2.19)

1.50 (1.35e1.66)

1.86 (1.37e2.52)

1.07 (0.96e1.18)—

1.83 (1.45e2.30)

1.17 (0.99e1.38)—

1.59 (1.41e1.78)

1.53 (1.42e1.65)—

Often/severe

GYNECOLOGY

Data are presented with the use of multinomial logistic regression with a generalised logit link; the SURVEYLOGISTIC procedure in SAS software (SAS Institute Inc, Cary, NC) was used to incorporate the study cluster into the analyses.

1,914

2,675

Normal weight &former smoker

Normal weight &current smoker

5,824

Normal weight &never smoker

Joint effect

41.2

5,928

3,741

Former smoker

Current smoker

33.5

45.0

37.6

38.4

46.0

Never

11,791

Never smoker

Smoking status

10,413

N

Normal (<25 kg/m2)

Body mass index

Overall sample (n¼21460)

Variable

Vasomotor symptoms (hot flushes
and night sweats) (%)

Adjusted cross-sectional associations of body mass index and smoking status with the risk of vasomotor symptoms at baseline (n[21,460) (continued)

TABLE 3

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Original Research

478.e8

Original Research GYNECOLOGY
Asian population, the estimated effects
remained unchanged. Compared withnever smoking, current smoking was
also associated with frequency/severityof VMS, with adjusted RRR of 1.21 (95%CI, 1.08e1.35), 1.39 (95% CI,
1.24e1.56), and 1.83 (95% CI,
1.45e2.30),
respectively.
Formersmokers were only at a slightly increased
risk of having often/severe VMS (RRR,
1.17; 95% CI, 0.99e1.38). By examining
the RRRs in this Table 3, it appears thatcurrent smoking conveys greater risk for
VMS than being overweight or obese.

Joint effects of BMI and smoking
Table 3 also shows the joint effect of BMI
and smoking. A signiﬁcant interaction
was observed between BMI and smoking
status for the risk of VMS (P<.001).
Never-smokers who were obese had a
1.5-fold increased risk of often/severe
VMS (RRR, 1.52; 95% CI, 1.35e1.73)
compared with never-smokers who wereof normal-weight. Smoking enhanced
the association because the risk of often/
severe VMS among smokers who wereobese was much higher (RRR, 3.02; 95%
CI, 2.41e3.78), and the joint effect was
not additive (ie, greater than the sum of
individual effects). We also observed ahigher risk of often/severe VMS amongsmokers who were overweight, but to alesser extent (RRR, 2.54; 95% CI,
2.22e2.89). Quitting smoking appeared
to mitigate excess risk because the risk ofoften/severe VMS among obese formersmokers (RRR, 1.85; 95% CI,
1.33e2.57) and overweight formersmokers (RRR, 1.87; 95% CI,
1.59e2.19) was much lower. Further
exclusion of Asian women (n¼1484) did
not change the observed associations(data not shown).

Dose-response relationshipbetween smoking and VMS
Among current smokers, dose-response
relationships were observed in all measures of smoking characteristics (ie,higher number of cigarettes smoked,
longer duration of smoking, higher
number of pack-years, and earlier age at
initiation of smoking) were associatedwith more frequent/severe VMS(Table 4). For instance, compared withnever smokers, current smokers with
"40 pack-years were at >2-foldincreased risk of often/severe VMS(RRR, 2.21; 95% CI, 2.06e2.37).
Smoking initiation at #15 years was
associated with increased risk of often/
severe VMS in both current and former
smokers, although current smokers had
a much higher risk (RRR, 2.19; 95% CI,
1.88e2.54) than former smokers (RRR,
1.29; 95% CI, 1.15e1.46). Women who
quit after the age of 40 years and those
who had quit smoking within 5 years had
a similar risk of VMS to those of current
smokers. However, smokers who quit at<40 years of age or had quit for >5 years
had similar levels of risk as neversmokers.

Prospective associations
At the 3-year follow up, 23% of thewomen reported no VMS at baseline andfollow up; 47% of the women experienced some degree of VMS (rarely/mild
to often/severe) at both times; 11% of
the women reported VMS at baseline but
no VMS at follow up, and 20% of thewomen reported VMS only at follow up(n¼11,986; data not shown). Like theresults from the cross-sectional analysis,
overweight/obesity and smoking atbaseline were associated with subsequentrisk of VMS at 3-year follow up, andsmoking strengthened the effect of BMI,
but to a much lesser extent (Table 5).
Also, former smokers had a lower risk ofoften/severe VMS at 3-year follow up
than current smokers. Similar results
were observed for studies of VMS frequency and VMS severity (data notshown). However, these associations
attenuated markedly after adjustment
for baseline VMS.

Effect modification by menopausal
statusThere was a signiﬁcant interaction between menopausal status and BMI(P<.0001) with VMS risk, but no interaction between menopausal status andsmoking (P>.05), which indicates thatthe effect of BMI may be modiﬁed bymenopausal status. After stratiﬁcation bymenopausal status, in the cross-sectional
analyses, the association between overweight, obesity, and increased risk of

478.e9 American Journal of Obstetrics & Gynecology MAY 2020

ajog.org
VMS remained in pre- and perimenopause but not in postmenopause(Figure 1). In the prospective analyses,
the association between baseline BMI
and increased risk of VMS at 3-year
follow up among pre- and perimenopausal women disappeared after adjustment for baseline VMS; however, higher
BMI was associated with reduced risk of
VMS among postmenopausal women(Figure 2).

Comment
Principal findings
This pooled analysis of >21,000 womenfrom 8 studies examined individual andjoint associations between 2 important
modiﬁable factors, BMI and smoking,with frequency/severity of VMS. Results
provided robust evidence to indicate that
overweight/obesity (BMI, "25 kg/m2)
and cigarette smoking were associatedwith the frequency and severity of VMS,
in a dose-dependent manner. Theseﬁndings are largely consistent with individual InterLACE studies (forexample, SWAN13,26) and with otherpublished research.5,27 Most notably,
this study also found that smoking
intensiﬁed the effect of obesity on VMS
risk. Smokers who were obese had aparticularly high risk of frequent or severe VMS. A signiﬁcant dose-response
was observed for the number of cigarettes, duration of smoking, pack-years,
and age at initiation of smoking on therisk of VMS in current smokers. Earlysmoking cessation before the age of 40
years may mitigate the excess risk of
VMS. Furthermore, we found thatmenopausal status modiﬁed the association between BMI and VMS. In the
cross-sectional analysis, higher BMI was
associated with VMS among pre- andperimenopausal women, but not among
postmenopause women. In the prospective analysis, baseline BMI was
associated negatively with VMS at 3-year
follow up among postmenopausal
women, even after adjustment for baseline VMS.

Results
Our results are consistent with previous
work that linked cigarette smoking andelevated BMI with increased frequency

18.7

4011 44.0

362 43.7

675 39.61135 32.2

Former smoker

Current smoker
1e9 cigarettes/dCurrent smoker
10e19 cigarettes/dCurrent smoker"20 cigarettes/d

18.74011 44.0

103 42.7

566 44.7

1745 33.5

Former smoker

Current smoker
duration <20 yCurrent smoker
duration 20e29 y

Current smoker
duration "30 y

25.6

21.4

15.4

21.4

14.9

13.4

22.2

18.7

15.2

14.9

13.4

19.9

14.9

13.4

Anderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

19.5

23.0

18.5

22.4

20.9

27.7

23.7

18.8

22.4

20.9

24.6

22.4

20.9

—

—

Often/severe—

Rarely/mild—

Sometime/moderate—

Often/severe

—

—

—

—

—

—

—

—

—

—

(continued)

1.32 (1.11e1.56) 1.52 (1.10e2.11) 1.85 (1.40e2.44) 1.30 (1.12e1.50) 1.46 (1.19e1.80) 1.74 (1.49e2.03)

0.91 (0.64e1.32) 1.15 (1.00e1.31) 1.22 (1.01e1.46) 0.92 (0.66e1.30) 1.17 (1.11e1.23) 1.22 (0.99e1.49)

0.93 (0.64e1.35) 0.90 (0.47e1.71) 1.57 (1.35e1.82) 0.93 (0.64e1.34) 0.84 (0.47e1.48) 1.45 (1.17e1.79)

1.00 (0.94e1.05) 1.11 (0.98e1.25) 1.13 (0.98e1.30) 1.01 (0.99e1.02) 1.13 (1.06e1.21) 1.12 (0.98e1.28)—

1.27 (1.05e1.52) 1.71 (1.31e2.23) 2.02 (1.65e2.47) 1.29 (1.11e1.49) 1.58 (1.47e1.70) 1.87 (1.75e1.99)

1.04 (0.76e1.43) 1.20 (0.88e1.65) 1.41 (1.00e1.97) 1.01 (0.77e1.33) 1.19 (0.93e1.52) 1.33 (1.04e1.70)

1.15 (0.96e1.38) 0.92 (0.69e1.23) 1.11 (0.76e1.63) 1.08 (1.07e1.08) 1.13 (0.77e1.67) 1.17 (0.94e1.45)

1.00 (0.94e1.05) 1.11 (0.98e1.25) 1.13 (0.98e1.30) 1.01 (0.99e1.02) 1.13 (1.06e1.21) 1.12 (0.98e1.28)—

1.19 (1.16e1.21) 1.38 (1.08e1.77) 1.66 (1.39e1.98) 1.18 (1.15e1.21) 1.35 (1.17e1.55) 1.58 (1.51e1.65)

1.00 (0.94e1.06) 1.11 (0.98e1.25) 1.13 (0.98e1.30) 1.00 (0.99e1.02) 1.13 (1.06e1.20) 1.12 (0.98e1.28)—

Sometime/moderate

Model 2c

GYNECOLOGY

17.0

17.5

19.4

18.0

18.1

22.4

18.7

19.4

8259 46.3

Never smoker

Duration of smoking(n¼14,684)

8259 46.3

Never smoker

18.9

4011 44.02439 36.6

Former smoker

Current smoker

Intensity of smoking(n¼14,442)

Model 1b

Relative risk ratio (95% confidence interval)

Rarely/ Sometime/ Often/
moderate severe Rarely/mild
Never mild

19.4

N

8259 46.3

Never smoker

Smoking status(n¼14,709)

Variable

Vasomotor symptoms (hot flushes
and night sweats), %Adjusted cross-sectional dose-response relationships between smoking and the risk of vasomotor symptoms at baseline (n[14,709)a

TABLE 4

ajog.org

Original Research

MAY 2020 American Journal of Obstetrics & Gynecology

478.e10

478.e11 American Journal of Obstetrics & Gynecology MAY 2020

285 44.2

431 40.1

436 40.1

493 32.9

516 28.5

Current smoker
10e19 pack-years

Current smoker
20e29 pack-years

Current smoker
30e39 pack-years

Current smoker"40 pack-years

17.8

670 31.6

Current smoker
initiated at #15 y

25.4

25.8

22.3

26.4

21.3

20.7

20.9

28.7

26.6

26.8

22.3

16.8

22.4

20.9

25.2

16.9

19.8

17.0

14.0

15.3

13.4

25.6

20.7

16.5

17.6

17.9

14.9

13.4

Anderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

19.81124 37.5

17.9

17.2

19.3

19.2

19.4

Current smoker
initiated at 16e19 y

605 40.0882 39.3

Former smoker
initiated at #15 yCurrent smoker
initiated at "20 y2149 45.5

854 44.7

Former smoker
initiated at "20 yFormer smoker
initiated at 16e19 y8259 46.3

Never smoker

17.3

19.9

16.5

20.0

21.1

18.7

4011 44.0

Former smoker

Current smoker<10 pack-years

Age initiated smoking(n¼14,543)

Model 1b——

Often/severe—

Rarely/mild

Model 2c—

Sometime/moderate—

Often/severe

—

—

—

—

—

(continued)

1.29 (1.17e1.42) 1.63 (1.09e2.45) 2.41 (1.81e3.20) 1.25 (1.22e1.28) 1.57 (1.14e2.17) 2.19 (1.88e2.54)

1.22 (1.12e1.32) 1.42 (1.16e1.73) 1.40 (1.21e1.62) 1.23 (1.11e1.36) 1.38 (1.27e1.50) 1.37 (1.32e1.42)

1.00 (0.80e1.26) 1.13 (0.92e1.39) 1.48 (1.35e1.61) 1.00 (0.78e1.28) 1.11 (1.00e1.22) 1.43 (1.35e1.50)

1.01 (0.81e1.26) 1.42 (1.17e1.72) 1.38 (1.19e1.60) 0.98 (0.80e1.20) 1.41 (1.21e1.64) 1.29 (1.15e1.46)

1.00 (0.93e1.08) 1.03 (0.91e1.16) 1.04 (0.87e1.25) 1.01 (0.98e1.05) 1.05 (0.96e1.15) 1.06 (0.86e1.30)

1.00 (0.78e1.28) 1.00 (0.87e1.16) 1.12 (0.91e1.37) 1.04 (0.86e1.26) 1.06 (0.98e1.15) 1.17 (1.07e1.28)—

1.36 (1.27e1.47) 1.95 (1.22e3.12) 2.55 (2.05e3.16) 1.39 (1.28e1.51) 1.68 (1.35e2.09) 2.21 (2.06e2.37)

1.35 (1.18e1.54) 1.59 (1.25e2.01) 1.77 (1.18e2.68) 1.35 (1.15e1.59) 1.54 (1.40e1.69) 1.69 (1.19e2.42)

0.96 (0.76e1.22) 1.40 (0.99e1.97) 1.30 (0.98e1.72) 0.97 (0.76e1.22) 1.39 (1.10e1.76) 1.26 (1.00e1.60)

1.11 (0.84e1.46) 1.12 (0.84e1.48) 1.31 (1.14e1.51) 1.05 (0.89e1.23) 1.13 (0.90e1.44) 1.23 (1.15e1.32)

1.10 (0.85e1.42) 0.83 (0.59e1.17) 1.35 (1.01e1.80) 1.03 (0.82e1.30) 1.01 (0.67e1.53) 1.44 (1.20e1.72)

1.00 (0.94e1.05) 1.11 (0.98e1.25) 1.13 (0.98e1.30) 1.01 (1.00e1.02) 1.13 (1.06e1.21) 1.12 (0.98e1.28)—

Sometime/moderate

Relative risk ratio (95% confidence interval)

Rarely/ Sometime/ Often/
moderate severe Rarely/mild
Never mild

19.4

N

8259 46.3

Never smoker

Cumulative dose ofsmoking (n¼14,431)

Variable

Vasomotor symptoms (hot flushes
and night sweats), %Adjusted cross-sectional dose-response relationships between smoking and the risk of vasomotor symptoms at baseline (n[14,709)a (continued)

TABLE 4

Original Research GYNECOLOGY
ajog.org

1764 33.5

807 46.1

834 40.3

829 32.7

Current smoker

Former smoker
quit at <30 yFormer smoker
quit at 30e39 yFormer smoker
quit at "40 y739 37.5

450 42.2

833 44.8

Former smoker
quit 6e14 yFormer smoker
quit 15e19 yFormer smoker
quit "20 y

15.6

15.8

18.1

14.8

16.5

16.7

16.2

17.6

15.0

16.5

16.7

25.2

29.3

28.2

33.7

28.6

26.0

31.1

28.4

25.5

28.6

26.0

14.4

12.7

16.2

20.2

21.5

14.8

20.0

13.7

13.4

21.5

14.8

—

—

Often/severe—

Rarely/mild—

Sometime/moderate

—

—

—

—

—

0.90 (0.72e1.11) 0.93 (0.77e1.12) 0.94 (0.75e1.19) 0.89 (0.72e1.10) 0.94 (0.78e1.13) 0.93 (0.74e1.17)

0.96 (0.73e1.28) 1.17 (0.92e1.48) 0.91 (0.66e1.25) 0.96 (0.72e1.28) 1.18 (0.93e1.50) 0.89 (0.65e1.23)

1.22 (0.98e1.53) 1.20 (0.99e1.46) 1.21 (0.96e1.53) 1.20 (0.96e1.50) 1.17 (0.96e1.43) 1.14 (0.90e1.45)

1.11 (0.82e1.51) 1.54 (1.21e1.97) 1.52 (1.14e2.03) 1.06 (0.78e1.44) 1.47 (1.15e1.88) 1.37 (1.03e1.83)

1.19 (1.02e1.40) 1.26 (1.10e1.45) 1.58 (1.35e1.85) 1.18 (1.01e1.39) 1.26 (1.10e1.45) 1.54 (1.31e1.81)—

1.18 (0.94e1.47) 1.40 (1.16e1.68) 1.50 (1.21e1.86) 1.14 (0.91e1.43) 1.34 (1.11e1.62) 1.37 (1.10e1.71)

1.11 (0.90e1.37) 1.14 (0.95e1.37) 0.97 (0.77e1.22) 1.10 (0.89e1.35) 1.13 (0.94e1.36) 0.94 (0.74e1.18)

0.85 (0.69e1.06) 0.95 (0.79e1.15) 0.91 (0.71e1.15) 0.85 (0.68e1.06) 0.96 (0.80e1.16) 0.90 (0.71e1.15)

Data are from the Australian Longitudinal Study on Women’s Health, the Study of Women’s Health Across the Nation, and the Whitehall II Study; b Included menopausal status and use of menopausal hormone therapy at baseline; c Additionally included race/
ethnicity/region, education, and body mass index at baseline; d The analysis was only based on data from the Australian Longitudinal Study on Women’s Health study.
Anderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

a—Often/severe

1.19 (1.02e1.40) 1.26 (1.10e1.45) 1.58 (1.35e1.85) 1.19 (1.01e1.39) 1.26 (1.10e1.45) 1.54 (1.31e1.81)—

Sometime/moderate

Model 2c

GYNECOLOGY

Data are presented with the use of multinomial logistic regression with a generalised logit link; the SURVEYLOGISTIC procedure in SAS software (SAS Institute Inc, Cary, NC) was used to incorporate the study cluster into the analyses.

445 31.2

1764 33.5

Current smoker

Former smoker
quit 1e5 y5800 42.5

Never smoker

Years since quitting
smoking (n¼10,031)d

Model 1b

Relative risk ratio (95% confidence interval)

Rarely/ Sometime/ Often/
moderate severe Rarely/mild
Never mild

5800 42.5

N

Never smoker

Age at quitting smoking(n¼10,034)d

Variable

Vasomotor symptoms (hot flushes
and night sweats), %Adjusted cross-sectional dose-response relationships between smoking and the risk of vasomotor symptoms at baseline (n[14,709)a (continued)

TABLE 4

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Original Research

MAY 2020 American Journal of Obstetrics & Gynecology

478.e12

3638 31.0

2489 31.3

Overweight(25-29.9 kg/m2)

Obese ("30 kg/m2)

478.e13 American Journal of Obstetrics & Gynecology MAY 2020

1592 36.01016 31.02029 32.1

1053 30.0

556 28.4

1349 32.3

761 31.0

379 28.0

Normal weight &former smoker

Normal weight &current smoker

Overweight &never smoker

Overweight &former smoker

Overweight &current smoker

Obese & never smoker

Obese & former smoker

Obese & current smoker

20.3

22.3

21.6

20.0

24.0

20.8

19.3

20.5

19.5

25.6

24.3

23.9

25.4

25.6

26.0

26.9

25.1

24.9

26.2

25.0

25.0

24.3

25.8

25.3

26.1

22.3

22.2

26.3

20.4

21.0

22.8

18.4

18.6

24.5

19.9

20.1

22.8

21.7

19.3

—

—

—

Rarely/mild—

Sometimes/
moderate—

Often/severe

—

—

—

—

—

—

—

—

—

—

1.20 (1.08e1.35) 1.45 (1.23e1.71) 1.55 (1.37e1.76) 1.00 (0.88e1.14) 1.06 (0.88e1.27) 1.05 (0.99e1.11)

1.24 (1.18e1.31) 1.28 (1.11e1.47) 1.28 (1.00e1.64) 1.14 (1.05e1.24) 1.09 (0.95e1.26) 1.03 (0.80e1.31)

1.12 (0.92e1.35) 1.09 (1.02e1.17) 1.11 (0.85e1.44) 1.03 (0.87e1.22) 0.95 (0.89e1.02) 0.94 (0.74e1.20)

1.30 (1.09e1.56) 1.26 (1.17e1.34) 1.60 (1.41e1.82) 1.10 (0.92e1.31) 0.98 (0.86e1.13) 1.15 (1.04e1.27)

1.54 (1.32e1.79) 1.27 (1.11e1.45) 1.31 (1.03e1.67) 1.45 (1.26e1.67) 1.12 (1.02e1.24) 1.11 (0.88e1.40)

1.18 (1.07e1.31) 1.13 (1.05e1.21) 1.17 (1.00e1.36) 1.10 (1.01e1.21) 1.00 (0.93e1.08) 1.01 (0.89e1.14)

1.23 (1.10e1.37) 1.24 (0.91e1.70) 1.39 (1.09e1.76) 1.15 (1.04e1.27) 1.12 (0.85e1.48) 1.19 (0.95e1.50)

1.14 (1.06e1.23) 1.12 (1.06e1.19) 1.12 (1.02e1.24) 1.12 (1.02e1.24) 1.09 (1.01e1.16) 1.09 (0.96e1.24)—

1.16 (1.07e1.26) 1.22 (1.02e1.45) 1.39 (1.22e1.59) 1.07 (1.00e1.15) 1.08 (0.92e1.27) 1.17 (1.02e1.33)

1.18 (1.11e1.26) 1.13 (1.11e1.16) 1.13 (1.09e1.17) 1.18 (1.11e1.25) 1.11 (1.07e1.15) 1.09 (1.03e1.15)—

1.08 (1.00e1.17) 1.12 (1.03e1.21) 1.12 (0.92e1.37) 1.00 (0.94e1.05) 0.97 (0.91e1.03) 0.93 (0.78e1.11)

1.21 (1.12e1.31) 1.11 (1.01e1.23) 1.17 (0.99e1.38) 1.13 (1.09e1.18) 0.99 (0.94e1.05) 1.01 (0.89e1.14)—

Often/severe

Fully adjusted model þ baseline vasomotor symptoms

Data are from the Australian Longitudinal Study on Women’s Health, the National Survey of Health and Development, the Study of Women’s Health Across the Nation, and the Whitehall II Study; b Included menopausal status, use of menopausal hormone therapy at
3-year follow up, race/ethnicity/region, education, body mass index, and smoking status at baseline.
Anderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

aData are presented with the use of multinomial logistic regression with a generalized logit link; the SURVEYLOGISTIC procedure in SAS software (SAS Institute Inc, Cary, NC) was used to incorporate the study cluster into the analyses.

3251 37.1

Normal weight &never smoker

Joint effect22.0

3406 33.0

1951 29.7

former smoker

Current skomer

19.7

20.3

21.6

21.6

19.7

6629 34.6

Never smoker

Smoking status

5859 35.7

Normal (<25 kg/m2)

Body mass index

N

Sometimes/
moderate

Fully adjusted modelb

Relative risk ratio (95% confidence interval)

Rarely/ Sometimes/ Often/
moderatesevere Rarely/mild
Never mild

Vasomotor symptoms (hot flushes
and night sweats) (%)

Adjusted prospective associations of body mass index and smoking status at baseline with the risk of subsequent vasomotor symptoms
at 3-year follow up (n[11,986)a

TABLE 5

Original Research GYNECOLOGY
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GYNECOLOGY

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FIGURE 1

Adjusted cross-sectional association between body mass index and the riskof vasomotor symptoms at baseline

The adjusted cross-sectional association between body mass index and the risk of vasomotor
symptoms at baseline was stratified by menopausal status at baseline (premenopause: n¼4169;
perimenopause: n¼5881; postmenopause: n¼4109). Relative risk ratio and the 95% confidence
intervals were adjusted for use of menopausal hormone therapy, race/ethnicity/region, education,and smoking status at baseline.
BMI, body mass index; RRR, relative risk ratio; VMS, vasomotor symptoms.
Anderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

and severity of VMS,5,27-31 although themechanisms behind the relationshipbetween smoking and VMS speciﬁcallyremain unclear. Although it is widely
accepted that body fatness is associatedwith an elevated core body temperatureand delayed thermoregulation,32 studies
that have examined the results concerning pathways by which tobacco smoking
inﬂuences VMS have been inconsistent(some have suggested an antiestrogenic
effect31; others have shown the relationship is independent of estrogenlevels29,30). Alternatively, the chemicals
in cigarette smoke affect reproductivefunction and alter hormone levels andtheir ratios (for example, higher androstenedione levels, a higher total
androgen-to-total estrogen ratio, andlower progesterone levels,33,34 whichhave been associated with hot ﬂushes35).
Regardless of the exact physiologic

Original Research

who quit smoking for <5 years or quit at>40 years still had a signiﬁcantly higher
risk of frequent and severe VMS thannever smokers. These results suggest thatquitting smoking early is an importantpart of the routine counselling of women
before approaching menopause.
In line with our ﬁndings, previous
ﬁndings from SWAN showed that greater
concurrent BMI and waist circumference
were associated with increased risk ofincident VMS in early menopause butwith reduced VMS risk in late menopause, indicating the dominant mechanism of the effect of body fat on VMS
differs in pre- and postmenopause.15 A
previous NSHD study also found that
postmenopausal women with a BMI of"30 kg/m2 were less likely to have severe
VMS proﬁle.37 In the early stage of themenopausal transition, overweight andobesity may predispose to increased VMS
occurrence (potentially because of
greater heat insulation),14 whereas, inpostmenopausal women, increased
estrone production from aromatizationof androstenedione occurs withincreasing weight,38 which may be associated with less symptom reporting. Also,
the effect of weight change on VMS islikely to differ in premenopausal andpostmenopausal women.15

Clinical implications
mechanisms, however, the particularly
increased risk among women who wereboth obese and current smokers implies
that obesity and smoking intensify eachother’s effect on frequency/severity of
VMS. The mechanisms behind thepotential synergistic interaction in relation to VMS were beyond the scope of
this study.
Previously, the InterLACE study,
when examining smoking and age atmenopause, found that the toxic impactof smoking on reproductive function
appeared to be cumulative and longlasting, even former smokers had anincreased risk of earlier menopause.36
Only those women who had quit
smoking for >10 years had a similar risk
as never smokers. Findings from thisstudy also support that the reversal of
negative effects after smoking cessation
on VMS may not be immediate. WomenThis study contributes to the understanding of how unhealthy behaviors,
which often coexist, can interact andincrease risk to a greater extent than theywould if they occurred alone. Findings
also suggested that cigarette smoking
conveyed a greater risk for VMS thanbeing overweight or obese, which isconsistent with SWAN’s previous results.15 These ﬁndings support the opportunity to refer midlife women to
health promotion programs and theneed to emphasize both early smoking
cessation and weight management strategies before menopause, because waiting until the menopausal transition andpostmenopause is too late to achieve
maximum beneﬁt. Encouraging women
to stop smoking before the menopausal
transition (preferably before age 40
years) is essential. This is particularly
important for obese smokers whose risk

MAY 2020 American Journal of Obstetrics & Gynecology

478.e14

Original Research GYNECOLOGYFIGURE 2

Adjusted prospective association between body mass index at baseline andthe risk of vasomotor symptoms at 3-year follow up

The adjusted prospective association between body mass index at baseline and the risk of vasomotor
symptoms at 3-year follow up was stratified by menopausal status at the 3-year follow up (data from
Australian Longitudinal Study on Women’s Health; National Survey of Health and Development; Studyof Women’s Health Across the Nation, and the Whitehall II Study; pre- or perimenopause: n¼3554;
postmenopause: n¼3966). Relative risk ratio and the 95% confidence intervals were adjusted forthe use of menopausal hormone therapy at the 3-year follow up, race/ethnicity/region, education,smoking status, and vasomotor symptoms at baseline.
BMI, body mass index; RRR, relative risk ratio; VMS, vasomotor symptoms.
Anderson et al. Obesity, smoking, and vasomotor symptoms. Am J Obstet Gynecol 2020.

of experiencing frequent and severe
VMS is notably high.
Women with frequent and severe VMS
often seek medical advice to treat their
symptoms. Hormone therapy is the mostcommon and effective treatment for
VMS. However, many women andhealthcare professionals have concerns
about the long-term risks of hormone
therapy, in particular on the risk of cardiovascular disease, based on the resultsfrom the Women’s Health Initiative trial
study.39 The beneﬁts and risks of hormone therapy vary by dosage, regimen,

and timing of initiation. According to the
National Institute for Health and Care
Excellence guidelines,40 women should
be informed that taking hormone therapy
at <60 years of age does not increase
cardiovascular disease risk and that thepresence of cardiovascular disease risk
factors (eg, blood pressure, cholesterol) is
not a contraindication to hormone therapy as long as they are treated optimally.

Strengths and limitations
To our knowledge, this is the ﬁrst study
to examine the individual and joint

478.e15 American Journal of Obstetrics & Gynecology MAY 2020

ajog.org
associations between BMI and smoking
with the risk of VMS. The InterLACE
consortium draws together individuallevel data from a number of large
studies and therefore is able to provide
precise estimates of the associations.
Additionally, the availability of race/
ethnicity/regional data, albeit based on
self-reports, provides a relatively unique
opportunity to examine differences in
VMS symptoms in women from Japan,
the United States, the United Kingdom,and Australia. Several limitations ofthese analyses should also be considered.
First, data were derived from selfreports, which could have reﬂected inrecall bias. For example, pre- or postmenopausal women or women who
experienced short-duration or mild
VMS might have been less likely toreport their symptoms than women withmoderate/severe VMS. Another signiﬁcant limitation was the differences in theassessment of menopausal symptoms(severity or frequency over different
recall periods) across studies, which
limited our ability to pool data. Therefore, it is important for future research todevelop standardized measures formenopausal symptoms (eg, theCOMMA initiative‒Core Outcome set
in Menopause; part of the CROWN
project41), which will enhance theavailability of comparable data acrossdifferent populations. Furthermore, of
the 4 studies that provided longitudinal
data on VMS, >3500 women withincomplete follow-up data were
excluded. These women were more likely
to report the exposures (obesity or current smoking), outcome (VMS), or
both, which may have led to an underestimation of the frequency/severity of
VMS. However, because we observed
sufﬁcient variation in the distribution of
exposures and outcome, we do not
expect the nature of the relationshipsthat were observed in this study tochange substantively.

Conclusions
Results from this pooled analysis provided strong evidence that both higher
body mass and smoking with higher intensity, longer duration, and earlier
initiation were associated with more

ajog.org
frequent and severe VMS. Cigarettesmoking strengthened the association
between obesity and VMS; thus, smokers
who were obese had a particularly
increased risk of VMS. Effective intervention for smoking cessation before age
40 years and maintaining a normal weight
before the menopausal transition may
have important implications for the prevention of VMS in midlife women.
nAcknowledgments
The Study of Women’s Health Across the Nation(SWAN) would like to thank the following
research centers. Clinical Centers: University ofMichigan, Ann Arbor (Siobán Harlow, PI,
2011epresent,
MaryFran
Sowers,PI,
1994e2011); Massachusetts General Hospital,
Boston, MA (Joel Finkelstein, PI, 1999epresent;
Robert Neer, PI, 1994e1999); Rush University,
Rush University Medical Center, Chicago, IL(Howard Kravitz, PI, 2009epresent; Lynda
Powell, PI, 1994e2009); University of California,
Davis/Kaiser (Ellen Gold, PI); University of California, Los Angeles (Gail Greendale, PI); Albert
Einstein College of Medicine, Bronx, NY (Carol
Derby, PI, 2011epresent; Rachel Wildman, PI,
2010e2011; Nanette Santoro, PI, 2004e2010);
University of Medicine and DentistryeNew Jersey Medical School, Newark (Gerson Weiss, PI,
1994e2004); and the University of Pittsburgh,
Pittsburgh, PA (Karen Matthews, PI). NIH Program Ofﬁce: National Institute on Aging,
Bethesda, MD (Chhanda Dutta, 2016epresent;
Winifred Rossi, 2012e2016; Sherry Sherman,
1994e2012; Marcia Ory, 1994e2001(; National
Institute of Nursing Research, Bethesda, MD(Program Ofﬁcers). Central Laboratory: University of Michigan, Ann Arbor (Daniel McConnell;
Central Ligand Assay Satellite Services). Coordinating Center: University of Pittsburgh, Pittsburgh, PA (Maria Mori Brooks, PI,
2012epresent;
Kim
Sutton-Tyrrell,PI,
2001e2012); New England Research Institutes,
Watertown, MA (Sonja McKinlay, PI,
1995e2001). Steering Committee: Susan
Johnson, Current Chair; Chris Gallagher, Former
Chair. All of the studies would like to thank theparticipants for volunteering their time to be
involved in the respective studies.

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Author and article information
From Menzies Health Institute Queensland, Griffith University, Gold Coast (Drs Anderson and Seib), and the
School of Public Health, The University of Queensland,
Brisbane (Drs Chung, Dobson, and Mishra), Queensland,
Australia; Medical Research Council Unit for Lifelong
Health and Ageing at UCL (Dr Kuh), and the Department of
Epidemiology and Public Health, University College London(Dr Brunner), London, UK; the Department of Medicine,
University of Massachusetts Medical School, Worcester,MA (Dr Crawford); the Department of Social Sciences and
Health Policy, Wake Forest School of Medicine, WinstonSalem, NC (Dr Avis); the Department of Public Health
Sciences, University of California, Davis, CA (Dr Gold); theDepartment of Medicine, Division of General Internal
Medicine and Health Services Research, University ofCalifornia, Los Angeles, David Geffen School of Medicine,Los Angeles, CA (Dr Greendale); Family and Child Nursing(Dr Mitchell), and Biobehavioral Nursing and Health Systems (Dr Woods), School of Nursing, University of Washington, Seattle, WA; the Department of Women’s HealthNursing & Midwifery, Tohoku University Graduate School of
Medicine, Sendai, Miyagi, Japan (Dr Yoshizawa).
Received Aug. 26, 2019; revised Oct. 16, 2019;
accepted Oct. 26, 2019.
Supported by the following agencies: Australian National Health and Medical Research Council project grant(APP1027196); the Australian National Health andMedical Research Council Principal Research Fellowship(APP1121844; G.D.M.). The data on which this researchis based were drawn from 8 observational studies: theAustralian Longitudinal Study on Women’s Health(ALSWH) is funded by the Australian Government
Department of Health; the Medical Research Council

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National Survey of Health Development (NSHD) has corefunding from the UK Medical Research Council (MC UU
12019/1); the National Child Development Study (NCDS)
is funded by the UK Economic and Social ResearchCouncil; the Whitehall II study is supported by grants from
the Medical Research Council (K013351), the British
Heart Foundation (BHF RG/16/11/32334) and the US
National Institutes on Aging (R01AG013196,
R01AG034454); the Seattle Midlife Women’s HealthStudy (SMWHS) was supported in part by grants from the
National Institute of Nursing Research, P50-NU02323,
P30-NR04001, and R01-NR0414; the Healthy Ageing of
Women Study (HOW) and Japanese Midlife Women’s
Health Study (JMWHS; also called Australian and Japanese Midlife Women’s Health Study) were supported by
the Queensland University of Technology Early Career
Research Grant and the JSPS Grant-in-aid for Scientific
Research; the Study of Women’s Health Across the Nation(SWAN) has grant support from the National Institutes of
Health (NIH), Department of Health and Human Services(DHHS), through the National Institute on Aging (NIA), theNational Institute of Nursing Research (NINR) and the NIH
Office of Research on Women’s Health (ORWH; Grants
U01NR004061;
U01AG012505,
U01AG012535,
U01AG012531,
U01AG012539,
U01AG012546,
U01AG012553, U01AG012554, U01AG012495).
The content of this article is solely the responsibility of
the authors and does not necessarily represent the official
views of the National Institute on Aging, National Instituteof Nursing Research, National Institutes of Health Office of
Research on Women’s Health, or the National Institutes of
Health.
The authors report no conflict of interest.
Corresponding author: Debra Anderson, PhD. debra.
anderson@griffith.edu.au