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. 2018 Feb;25(2):182-190.
doi: 10.1097/GME.0000000000000959.

Understanding the complex relationships underlying hot flashes: a Bayesian network approach

Rebecca L Smith  1 , Lisa M Gallicchio  2 , Jodi A Flaws  3
Affiliations

Understanding the complex relationships underlying hot flashes: a Bayesian network approach

Rebecca L Smith et al. Menopause. 2018 Feb.

Abstract

Objective: The mechanism underlying hot flashes is not well-understood, primarily because of complex relationships between and among hot flashes and their risk factors.

Methods: We explored those relationships using a Bayesian network approach based on a 2006 to 2015 cohort study of hot flashes among 776 female residents, 45 to 54 years old, in the Baltimore area. Bayesian networks were fit for each outcome (current hot flashes, hot flashes before the end of the study, hot flash severity, hot flash frequency, and age at first hot flashes) separately and together with a list of risk factors (estrogen, progesterone, testosterone, body mass index and obesity, race, income level, education level, smoking history, drinking history, and activity level). Each fitting was conducted separately on all women and only perimenopausal women, at enrollment and 4 years after enrollment.

Results: Hormone levels, almost always interrelated, were the most common variable linked to hot flashes; hormone levels were sometimes related to body mass index, but were not directly related to any other risk factors. Smoking was also frequently associated with increased likelihood of severe symptoms, but not through an antiestrogenic pathway. The age at first hot flashes was related only to race. All other factors were either not related to outcomes or were mediated entirely by race, hormone levels, or smoking.

Conclusions: These models can serve as a guide for design of studies into the causal network underlying hot flashes.

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Conflict of interest statement

The authors have no conflicts to declare.

Figures

Figure 1
Figure 1
Final model structure for presence of hot flashes, based on all women at baseline in a cohort study of midlife women in the Baltimore area. Rectangles indicate categorical variables, while ovals indicate continuous variables and hexagons indicate ordinal variables.
Figure 2
Figure 2
Final model structure for the frequency of hot flashes at baseline, based on all women in a cohort study of midlife women in the Baltimore area. Rectangles indicate categorical variables, while ovals indicate continuous variables.
Figure 3
Figure 3
Final model structure for the moderate to severe hot flashes, based on all women at baseline in a cohort study of midlife women in the Baltimore area. Rectangles indicate categorical variables, while ovals indicate continuous variables and hexagons indicate ordinal variables.
Figure 4
Figure 4
Final model structure for all outcomes at baseline, based on a cohort study of midlife women in the Baltimore area. Variables in bold were outcomes. Rectangles indicate categorical variables, while ovals indicate continuous variables and hexagons indicate ordinal variables.
See this image and copyright information in PMC

References

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