menopausal hot flashes and carotid intima media thickness ... · hot flashes are the “classic”...

Menopausal Hot Flashes and Carotid Intima Media Thickness among Midlife Women

Rebecca C. Thurston, PhD*,†, Yuefang Chang, PhD‡, Emma Barinas-Mitchell, PhD†, J. Richard Jennings, PhD*, Doug P. Landsittel, PhD§, Nanette Santoro, MD‖, Roland von Känel, MD#, and Karen A. Matthews, PhD*,†

*Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA †Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA ‡Department of Neurosurgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA §Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA ‖Department of Obstetrics and Gynecology, University of Colorado School of Medicine, Denver, CO, USA #Department of Neurology, Inselspital, Bern University Hospital, and University of Bern, Switzerland

Abstract

Background and Purpose—There has been a longstanding interest in the role of menopause

and its correlates in the development of cardiovascular disease (CVD) in women. Menopausal hot

flashes are experienced by most midlife women; emerging data link hot flashes to CVD risk

indicators. We tested whether hot flashes, measured via state-of-the-art physiologic methods, were

associated with greater subclinical atherosclerosis as assessed by carotid ultrasound. We

considered the role of CVD risk factors and estradiol concentrations in these associations.

Methods—295 nonsmoking women free of clinical CVD underwent ambulatory physiologic hot

flash assessments; a blood draw; and carotid ultrasound measurement of IMT and plaque.

Associations between hot flashes and subclinical atherosclerosis were tested in regression models

controlling for CVD risk factors and estradiol.

Results—More frequent physiologic hot flashes were associated with higher carotid intima

media thickness [IMT; for each additional hot flash: beta (standard error)=.004(.001), p=.0001;

reported hot flash: beta (standard error)=.008(.002), p=.002, multivariable] and plaque [e.g., for

each additional hot flash, odds ratio (95% confidence interval) plaque index ≥2=1.07(1.003–1.14,

p=.04), relative to no plaque, multivariable] among women reporting daily hot flashes;

associations were not accounted for by CVD risk factors or by estradiol. Among women reporting

hot flashes, hot flashes accounted for more variance in IMT than most CVD risk factors.

Address for Correspondence: Rebecca C. Thurston; 3811 O’Hara St, Pittsburgh, PA 15213; 412-648-9087 (tel); 412-648-7160 (fax); [email protected].

Disclosures: Thurston: None; Chang: None; Barinas-Mitchell: None; Jennings: None; Landsittel: None; Santoro: Grant support: Bayer Healthcare, Stock options: Menogenix; von Känel: None; Matthews: None.

HHS Public AccessAuthor manuscriptStroke. Author manuscript; available in PMC 2017 December 01.

Published in final edited form as:Stroke. 2016 December ; 47(12): 2910–2915. doi:10.1161/STROKEAHA.116.014674.

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Conclusions—Among women reporting daily hot flashes, frequent hot flashes may provide

information about a woman’s vascular status beyond standard CVD risk factors and estradiol.

Frequent hot flashes may mark a vulnerable vascular phenotype among midlife women.

Keywords

women; menopause; hot flashes; atherosclerosis; cardiovascular disease

Introduction

Cardiovascular disease (CVD) is the leading cause of death among women.1 As women

typically manifest with atherosclerotic CVD postmenopausally, on average 10 years after

men, there has been a longstanding interest in the role of the menopause transition and its

correlates in the development of atherosclerotic CVD in women.2 The focus of this work has

largely been on the hormonal changes associated with menopause. Recent data has also

considered how other menopause-related factors, including menopausal symptoms, relate to

CVD risk in women.

Hot flashes are the “classic” menopausal symptom, reported by >70% of midlife women.3

For a third of women, hot flashes are frequent or severe.4 The impact of hot flashes on

quality of life is well-documented,5 and hot flashes are strong drivers of health care

utilization.6 However, hot flashes are thought to have few implications for women’s physical

health.

Newer data challenge that assumption. Posthoc analyses from large hormone therapy (HT)

trials suggested that the CVD risk with HT use was highest among older women reporting

moderate-severe hot flashes at baseline.7, 8 Later observations from cohort studies suggest

that greater hot flash reporting may be associated with a poorer CVD risk factor profile9, 10

and higher subclinical atherosclerosis11–14 beyond standard risk factors. However, studies

specifically designed to test relations among hot flashes and CVD risk are absent. The

limitations in this literature, including retrospective hot flash measures vulnerable to

multiple biases,15, 16 exclusion of highly symptomatic women,8, 17 the group most affected,

and contradictory findings17 have limited conclusions about the precise nature of hot flash-

CVD risk associations.

In a sample of nonsmoking women without clinical CVD, we used state-of-the-art

ambulatory physiologic and prospective ecological momentary reports of hot flashes to test

whether hot flashes (presence, frequency) were associated with subclinical atherosclerosis as

assessed by carotid intima media thickness (IMT) and plaque. Carotid IMT and plaque are

widely-used and well-validated indicators of subclinical atherosclerosis predictive of later

clinical CVD, including among relatively low risk samples (e.g., midlife women).18–20 They

are preferable to other widely used subclinical atherosclerosis indices (e.g., coronary artery

calcification) that show a high rate of zero readings among midlife women.21 We tested the

role of standard and novel CVD risk factors in these relations. Finally, as endogenous

estradiol has been implicated in hot flashes and atherosclerosis in women,22 we considered

estradiol concentrations in these relations.

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Methods

Study Sample

The study sample was comprised of 304 late perimenopausal (2–12 months amenorrhea) and

postmenopausal (≥12 months amenorrhea) nonsmoking women aged 40–60. By design, half

of the women reported daily hot flashes or night sweats, and half reported no hot flashes or

night sweats in the past three months. Of the 1929 women who underwent telephone

screening, 304 were interested, eligible, and enrolled and had usable physiologic hot flash

monitoring data (≥70% of 24 hours). Exclusion criteria were based upon factors having a

major impact on study measures or safety and included hysterectomy and/or bilateral

oophorectomy; history of heart disease, stroke, arrhythmia, ovarian/gynecological cancer,

pheochromocytoma, pancreatic tumor, kidney failure, seizures, Parkinson’s disease,

Raynaud’s Phenomenon; current pregnancy; or having used select medications in the past 3

months (oral/transdermal estrogen or progesterone, selective estrogen receptor modulators,

selective serotonin reuptake inhibitors, serotonin norepinephrine reuptake inhibitors,

gabapentin, insulin, beta blockers, calcium channel blockers, alpha-2 adrenergic agonists,

other antiarrhythmic agents). Women who had undergone uterine ablation, endarterectomy,

or lymph node removal or who were undergoing dialysis or chemotherapy were also

excluded.

Of the 304 women, 4 women were excluded due to missing carotid data (equipment failure

or poor image) and 5 women excluded due to missing blood marker data [Homeostatic

Model Assessment (HOMA): N=3, low density lipoprotein cholesterol (LDL-C): N=2].

Excluded women had higher triglycerides than included women (p<.05). 295 women were

included in final models.

Design and Procedures

Women were recruited from the community via advertisements, mailings, and message

boards. Participants underwent physical measurements, hot flash monitoring, a blood draw,

and a carotid artery ultrasound. Procedures were approved by the University of Pittsburgh

Institutional Review Board. Participants provided written, informed consent.

Measures

Hot Flashes—Participants completed three days of ambulatory hot flash monitoring, the

first 24 hours of which included physiologic hot flash monitoring. Women were equipped

with a hot flash monitor (VU-AMS, VU University Amsterdam, Netherlands), electronic

diary, and wrist actigraph. The VU-AMS is a wearable monitor that quantifies hot flashes

via sternal skin conductance, a validated physiologic measure of hot flashes.23 Women

reported hot flashes by completing an electronic diary (Palm Z22) and pressing event mark

buttons on the VU-AMS monitor and actigraph, providing date and time-stamped hot flash

reports. Participants wore the VU-AMS monitor for 24 hours, after which time they removed

it and stored it in a provided case. For the remaining two days, women carried the diary and

actigraph. After monitoring, hot flash data were downloaded and scored via UFI software

(DPSv3.7; Morro Bay, CA) according to validated methods that have demonstrated

reliability, including in the present laboratory (ĸ=.86).23, 24

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Carotid Ultrasound—Trained and certified sonographers at the University of Pittsburgh’s

Ultrasound Research Laboratory obtained bilateral carotid images via B-mode ultrasound

using a Sonoline Antares (Siemens, Malvern, PA) high resolution duplex scanner equipped

with a VF10-5 transducer. Digitized images were obtained from eight locations (four

locations each from the left and right carotid arteries): near and far walls of the distal

common carotid artery, far walls of the carotid bulb, and internal carotid artery. Images were

read using semi-automated reading software.25 Values were obtained by electronically

tracing the lumen-intima interface and the media-adventitia interface across a 1-cm segment

for each of these eight segments. Average and maximal values were recorded for each of the

eight locations; the mean of the average and maximal readings across the eight locations

comprised mean and maximal IMT, respectively. Reproducibility of IMT measures was

excellent [intraclass correlation coefficient between sonographers 0.87–0.94, between

readers= 0.94–0.99].

Carotid plaque was defined as a distinct focal area protruding into the vessel lumen ≥50%

thicker than the adjacent IMT.26 Sonographers evaluated the presence and extent of plaque

in each of five segments of the left and right carotid artery (distal and proximal common

carotid artery, carotid bulb, and proximal internal and external carotid arteries).26 Consistent

with the Mannheim Consensus Statement,27 plaque was defined as a focal area protruding

into the vessel lumen that was at least 50% thicker than the adjacent IMT and summarized as

the presence or absence of any plaque. Additionally, for each segment the degree of plaque

was graded using the following criteria: Grade 0=no observable plaque; grade 1=one small

plaque (<30% of the vessel diameter); grade 2=one medium plaque (30–50% of the vessel

diameter) or multiple small plaques; grade 3=one large plaque (>50% of the vessel diameter)

or multiple plaques with at least one medium plaque. The grades from all segments of the

combined left and right carotid artery were summed to create the plaque index,28 which was

categorized as 0, 1, or ≥2 for analysis. Between sonographers agreement for carotid plaque

assessment was good to excellent (kappa statistic, κ=0.78).

Covariates

Height and weight were measured via a fixed stadiometer and balance beam scale; BMI was

calculated (kg/m2). Seated blood pressure was measured via a Dinamap device after 10-min

rest. Demographics and medical history were assessed by standard instruments. Menopause

status was obtained from reported menstrual bleeding patterns.29 Depressive symptoms were

assessed by the Center for Epidemiologic Studies Depression scale.30 Sleep/wake was

assessed via actigraphy and sleep diary.31 Use of medications for blood pressure-lowering,

lipid-lowering, or diabetes were reported and considered as covariates.

Phlebotomy was performed after a 12-hr fast. Glucose, triglycerides, and high-density

lipoprotein cholesterol (HDL-C) were measured enzymatically. Total cholesterol was

determined enzymatically and LDL-C calculated.32 Insulin was measured via

radioimmunoassay. HOMA, reflecting insulin resistance, was calculated.33 C-reactive

protein was measured using a high sensitivity reagent set (Beckman Coulter, Brea, CA) and

interleukin-6 with an R&D Systems (Minneapolis, MN) high sensitivity ELISA. Estradiol

was assessed via liquid chromatography-tandem mass spectrometry, the gold standard

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method to measure estradiol at low postmenopausal levels (lower limit of

quantitation=2.5pg/mL; lower limit of detection=1.0 pg/ml).34

Data analysis

HOMA, triglycerides, estradiol, C-reactive protein, and interleukin-6 values were natural log

transformed for analysis. Hot flashes were categorized as occurring during sleep or wake

according to sleep diary and actigraph. Hot flash rates were calculated as number of hot

flashes/ monitoring time. Rates were standardized to a 7-hour and 17-hour sleep and wake

times for ease of interpretation. 24-hour, sleep, and wake hot flash rates were considered

separately. Differences between participants by hot flash status (any/none) were tested using

linear regression, Wilcoxon rank sum, and chi-square tests. Associations between hot flash

frequency and outcomes were evaluated using linear and multinomial logistic regression.

Covariates (age, race/ethnicity, BMI, education, systolic and diastolic blood pressure,

triglycerides, LDL-C, HDL-C, HOMA) were selected based upon their prior documented

associations with IMT and present associations with outcomes at p<.10, with medication

variables forced into models. Estradiol was added in a separate step. Interactions were tested

by cross product terms in multivariable models. R2 values were derived from linear

regression models. Residual analysis and diagnostic plots were conducted to verify model

assumptions. Analyses were performed with SAS v9.2 (SAS Institute, Cary, NC). Models

were 2-sided at α=0.05.

Results

Participants were on average 54 years of age, normotensive, overweight, and

postmenopausal (Table 1). Women reporting daily hot flashes (“flashers”) were younger,

less educated, more often non-White, and had a higher diastolic blood pressure than women

not reporting hot flashes (“nonflashers”) during the three months prior to enrollment. Across

the sample, 2422 hot flashes were physiologically-detected, and 2335 were reported. Among

“flashers,” median numbers of physiologically-detected and self-reported hot flashes/24

hours were 12 and 5, respectively. Among women not reporting hot flashes (“nonflashers”),

many (46%) showed evidence of physiologic hot flashes, albeit at a low frequency (24 hour:

median=0, interquartile range: 0, 5).

The mean and maximal IMT was .68 mm (SD=.11) and .85 (SD=.16), respectively. Mean

IMT did not vary by hot flash group (“flasher” vs. “nonflasher”) in multivariable models

[b(SE)=−.008 (.01), p=.46, flasher: raw mean (SD)=.67(.09), range: .51–.98, nonflasher: raw

mean (SD)=.69(.12) range: .50–1.28]. Maximal IMT also did not differ by hot flash group

[b(SE)=−.007(.02), p=.66]. However, significant interactions by hot flash status and hot

flash frequency in relation to IMT were observed (p=.02). Among women reporting hot

flashes (N=147), more frequent hot flashes were strongly associated with higher mean and

maximal IMT in multivariable models (Table 2; Figure 1). Associations were not accounted

for by CVD risk factors. Estradiol was not related to IMT [b(SE)=−.002 (.005), p=.75,

multivariable] and did not impact hot flash-IMT associations [e.g., waking physiologic hot

flashes and IMT: b(SE)=.004 (.001), p=.0001, multivariable models with estradiol]. Among

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women reporting hot flashes, physiologic hot flashes accounted for more variance in IMT

than any other factor except race/ethnicity (Table 3).

We also considered carotid plaque. Over half the women (54%, N=160) showed no plaque,

21% (N=63) had a plaque index of 1, and 25% (N=73) had a plaque index of ≥2. Plaque did

not differ by reported hot flash status [flasher vs. nonflasher: plaque index ≥2, OR(95%CI)=

1.06(.56–2.01), p=.85); plaque index 1, OR(95%CI)=1.08(.58–2.01), p=.82, relative to no

plaque, multivariable]. However, interactions by hot flash status (p=.02) indicated that

among women reporting hot flashes, more frequent waking physiologic hot flashes were

associated with higher carotid plaque (Table 3). Estradiol did not impact associations (data

not shown).

We conducted several additional analyses. No significant interactions by age, race,

menopause stage, time since final menstrual period, and BMI for hot flash-IMT relations

were observed. However, for plaque, significant interactions by age were observed in the

total sample (p=.04) and in flashers (p=.04), with positive relations between hot flashes and

plaque observed largely among the older (e.g., ≥54, upper median) women [e.g., for each

additional physiologic hot flash among flashers: plaque index ≥2 OR(95%CI)=1.14 (1.03–

1.26), p=.009, multivariable]. Further, we tested interactions for blood pressure, finding

significant interactions between waking physiologic hot flashes and DBP in relation to IMT

among the flashers (p=.04). Probing these interactions indicated that associations were

strongest among the women at the upper median of DBP [≥70mg/dL: b=.005 (SE=.001), p<.

001; <70mg/dL: b=.001 (SE=.001), p=.59]. To better understand factors that may account

for hot flash-IMT relations, we considered depressive symptoms, interleukin-6, C-reactive

protein as well as menopause stage as additional covariates; associations between hot flashes

and IMT or plaque persisted (data not shown). Finally, neither diary-rated hot flash severity

nor bother were associated with outcomes (data not shown).

Discussion

We present the results from the first study designed to test associations between menopausal

hot flashes and markers of carotid atherosclerosis. Among midlife women reporting daily

hot flashes, a greater frequency of hot flashes was associated with higher carotid IMT and

plaque. The associations were not accounted for by CVD risk factors nor by estradiol.

Among women reporting hot flashes, hot flashes accounted for more variance in IMT than

most CVD risk factors.

These findings contribute to the literature on hot flashes and markers of CVD risk. Initial

observations of relations between hot flashes and CVD risk arose from posthoc analysis of

large HT trials7, 8. Subsequent observations from the Study of Women’s Health Across the

Nation (SWAN) and other cohort studies indicated that reported hot flashes were positively

associated with subclinical atherosclerosis.11–14 In other work, we have found hot flashes

associated with brain white matter hyperintensities.35 Not all studies have linked hot flashes

to CVD risk.17, 36 The existing literature has been limited by the heavy reliance upon

retrospective measurements of hot flashes asking women to recall their hot flashes up to a

decade prior.36 Highly symptomatic women are typically not differentiated from their less

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symptomatic counterparts; and hot flash severity, bother, and frequency are conflated,

constructs that are not interchangeable, as evidenced here. In this most rigorous test of this

question to date, among women reporting hot flashes, more frequent hot flashes were

associated with IMT, accounting for more variance in IMT in this study than most standard

CVD risk factors.

The mechanisms linking hot flashes to CVD risk are not yet clear, partly due to the limited

understanding of hot flash physiology. Hot flashes may represent thermoregulatory events.37

However, other mechanisms have been implicated. Hot flashes have been linked to a poorer

CVD risk factor profile,9, 10 yet risk factors did not explain observed associations. Lower

estradiol is permissive to hot flash occurrence and has been linked to poorer cardiovascular

health for women.22 However estradiol, measured via state-of-the-art methods that detect the

low levels of estradiol observed among postmenopausal women, did not explain

associations. Future work should consider other novel pathways (e.g., sympathetic nervous

system, hypothalamic pituitary adrenal axis) in hot flash-CVD risk relations.

Both self-reported and physiologically-monitored hot flashes were prospectively measured

here. These measures improve upon typically employed questionnaires, avoiding the

influence of memory and other limitations.16 We found that women under-reported their hot

flashes, consistent with prior work.38 Further, many “nonflashers” showed low frequency

hot flashes on physiologic monitoring; we have previously shown these hot flashes to have a

similar autonomic signature as reported hot flashes.39 Wake hot flashes showed stronger

relations to subclinical atherosclerosis than sleep hot flashes, consistent with some prior

work.11, 13 Finally, as opposed to low frequency hot flashes, the present findings underscore

the clinical significance of frequent flashing (e.g., 10+ physiologic hot flashes/day), a

frequency found in half of the women reporting hot flashes in this sample.

This work had limitations. This observational study does not allow for conclusions about

directionality or causality of relations. Use of subclinical atherosclerosis indices is necessary

given the rarity of clinical events in midlife women, but limits conclusions about clinical

disease. Estradiol concentrations, but not estradiol fluctuations, were quantified, yet most of

the women were postmenopausal, a time when estradiol typically stabilizes at low levels.

Blood pressure variability, which has been linked to CVD risk beyond blood pressure levels

alone,40 was not measured here and its role in these relations should be considered in future

work. Although the sample was 25% nonwhite, Asian and Hispanic women were under-

represented. By design, smokers, women reporting infrequent hot flashes (< daily), and

women with hysterectomy or bilateral oophorectomy were excluded. Findings cannot be

generalized to these groups; future work should consider these women. Hot flashes were

captured once over several days; yet next steps should include a longitudinal study

quantifying hot flashes over multiple time points.

Conclusions

More frequent hot flashes were associated with markers of carotid atherosclerosis among

midlife women reporting daily hot flashes. This line of work may ultimately have clinical

implications for women with frequent hot flashes. For women, midlife is typically decades

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before the emergence of clinical events and is a time in which CVD risk stratification can be

challenging; with additional replication and extension of this work, hot flashes may

ultimately assist in that effort. With further understanding of hot flash-CVD risk relations,

hot flashes may have implications for understanding the accelerated changes in the

vasculature occurring during menopause,41 changes not fully explained by reproductive

hormones or aging. This body of work begins to call into question the solely incidental

nature of this midlife symptom.

Acknowledgments

Sources of Funding

Supported by the National Institutes of Health, National Heart Lung and Blood Institute (R01HL105647, K24123565 to Thurston) and the University of Pittsburgh Clinical and Translational Science Institute (NIH Grant UL1TR000005).

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Figure 1. Adjusted means in average IMT by hot flash frequency among women in daily hot flash

group.

Quartile (Q) 1: ≤ 4 physiologic hot flashes, ≤ 1 self-reported hot flashes; Q2: 5–9

physiologic hot flashes, 2–3 self-reported hot flashes; Q3: 10–14 physiologic hot flashes, 4–

5 self-reported hot flashes; Q4: ≥ 15 physiologic hot flashes, ≥ 6 self-reported hot flashes;

waking hot flashes Adjusted for age, race, body mass index, education, high density

lipoprotein cholesterol, low density lipoprotein cholesterol, triglycerides, systolic blood

pressure, diastolic blood pressure, homeostatic model assessment, blood pressure-lowering

medications, lipid-lowering medications, diabetes medications

IMT = intima media thickness

*p<.05; **p<.01; ***p<.001 relative to Q1

Thurston et al.


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Table 1

Sample characteristics

Flasher (N=147) Non-Flasher (N=148)

Age, years, M (SD)* 53.34 (3.60) 54.73 (4.28)

Race/ethnicity, N (%)*

White 96 (65.31) 116 (78.38)

African American 45 (30.61) 21 (14.19)

Other 6 (4.08) 11 (7.43)

Education*

High school, some college, vocational 72 (48.98) 54 (36.49)

College graduate 47 (31.97) 41 (27.70)

>College 28 (19.05) 53 (35.81)

Body mass index, M (SD) 29.10 (6.55) 28.97 (6.94)

Systolic blood pressure, mmHg, M (SD) 120.16 (14.15) 119.64 (14.79)

Diastolic blood pressure, mmHg, M (SD)* 71.47 (8.74) 68.98 (9.33)

Menopause stage

Perimenopausal 30 (20.41) 18 (12.16)

Postmenopausal 117 (79.59) 130 (87.84)

High density lipoprotein cholesterol, mg/dL, M (SD) 62.60 (15.18) 63.20 (14.44)

Low density lipoprotein cholesterol, mg/dL, M (SD) 130.19 (30.88) 130.70 (35.72)

Triglycerides, mg/dL, Median (IQR) 95.00 (72, 124) 94.50 (70, 130)

Homeostatic model assessment, Median (IQR) 2.16 (1.58, 3.18) 2.19 (1.69, 3.12)

Estradiol, pg/mL, Median (IQR) 4.30 (2.00, 9.00) 5.00 (2.00, 12.35)

Medications, N (%)

Lipid-lowering 17 (11.56) 19 (12.84)

Blood pressure-lowering 25 (17.01) 22 (14.86)

Diabetes medication 4 (2.72) 5 (3.38)

Physiologically detected hot flashes, Median (IQR)†

24-hour 12 (7, 19) 0 (0, 5)

Wake 10 (4, 15) 0 (0, 3)

Sleep 3 (1, 5) 0 (0, 2)

Self-reported hot flashes, Median (IQR)†

24-hour 5 (3, 7) 0 (0, 0)

Wake 4 (2, 6) 0 (0, 0)

Sleep 1 (0, 2) 0 (0, 0)

*p<0.05 differs by hot flash group (daily hot flashes versus no hot flashes, past three months prior to enrollment);

†Sleep and wake values standardized to 7-hour and 17-hour sleep and wake durations for interpretation


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Table 2

Relation between hot flashes and carotid intima media thickness (IMT) and plaque among women reporting

daily hot flashes

Mean IMT Max IMT Plaque index

1 ≥2

beta (standarderror)§

beta (standarderror)§

Odds ratio(confidenceinterval)‖

Odds ratio(confidenceinterval)‖

Physiologic Hot Flashes

24-hour .003 (.001)† .004 (.001)† 1.00 (.94–1.06) 1.06 (1.001–1.12)*

Wake .004 (.001)‡ .005 (.001)‡ 0.99 (.92–1.06) 1.07 (1.003–1.14)*

Sleep .003 (.003) .004 (.005) 0.96 (.77–1.21) 1.17 (.96–1.42)

Self-Reported Hot Flashes

24-hour .006 (.002)† .007 (.003)* 1.06 (.92–1.21) 1.06 (.93–1.21)

Wake .008 (.002)† .009 (.004)* 1.09 (.92–1.30) 1.12 (.95–1.32)

Sleep .008 (.006) .01 (.009) .98 (.65–1.48) 1.00 (.70–1.42)

Covariates: age, race, body mass index, education, high density lipoprotein cholesterol, low density lipoprotein cholesterol, triglycerides, systolic blood pressure, diastolic blood pressure, homeostatic model assessment, blood pressure-lowering medications, diabetes medications, and lipid-lowering medications

*p<.05;

†p<.01,

‡p<.001

N=147; IMT measured in mm

§beta coefficients indicate mm increase in IMT for each additional hot flash

‖Odds ratio associated with each additional hot flash, relative to no plaque


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Table 3

Percent of variance (R2) in mean intima media thickness (IMT) explained by each variable among women

reporting daily hot flashes (N=147)

Variable R2

Age 4.72

Race 8.75

Education 0.98

Body mass index 1.50

Systolic blood pressure 0.19

Diastolic blood pressure 0.01

High-density lipoprotein cholesterol 0.31

Low-density lipoprotein cholesterol 2.71

Triglycerides 0.91

Homeostatic model assessment 0.13

Lipid-lowering medication 0.99

Blood pressure-lowering medication 0.67

Diabetes medication 0.19

Physiologic waking hot flashes 7.86


menopausal hot flashes and carotid intima media thickness ... · hot flashes are the “classic”...

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