Characteristics of the sample were described by means (standard deviation) and frequency (%). At baseline, two VMS groups – any or none – were compared for group differences in, and associations among, demographics (age, race/ethnicity, education), quality of life (SF-36 score), and clinical characteristics (weight, hip and waist circumference, menopausal status, fat mass, fat free mass, skeletal mass), and VMS was estimated using chi square test (x 2 ) for categorical variables, and Kruskal-Wallis test for continuous variables. A scatter plot matrix was used to examine linear correlations among variables. For the purposes of modelling, LBM is represented by the SMI variable. Additionally, to account for the nonindependence of longitudinal observations derived from the same woman and data in which the number of observations may differ across women, longitudinal modeling using SAS PROC MIXED incorporated a random intercept term to account for the correlated errors among repeated measures of the same woman. Missing values of time-varying variables were interpolated based on prior and subsequent values for gaps of one to two visits as in previous SWAN analyses . To assess H1, incident VMS was modeled as a function of concurrent LBM using logistic regression analysis. To address H2 regarding long term change in LBM, the model was expanded to add within-woman percent change in LBM since baseline and to address H3, regarding recent change in LBM, the model was expanded to add within-woman percent change in LBM since prior visit (approximately 1 year earlier). The overall association between LBM and VMS was estimated in binary logistic regression models. Statistical analyses were one-tailed with an alpha level of 0.05 and conducted using SAS University Edition (© 2012–2018, SAS Institute Inc., Cary, NC).
Results
In the baseline (see six) there had been 2533 players residing in the new SWAN study who had been normally 52 yrs . old and the variations in the group properties receive in the Table step one. Merely feminine reporting no episodes on baseline (letter = 1179) was found in longitudinal analyses to own VMS which have LBM. In the go to ten there had been 800 female staying in the study.
At baseline, SMI showed a strong positive correlation to FFMI both for symptoms = none (r0 (864) = 0.931, p Table 2 Association of VMS to lean body mass (Odds Ratios)
Predicted odds of episodes taking place at provided quantities of SMI (adjusted getting FFMI and FMI) in females without VMS at check out 6 (baseline)
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Utilizing the data because of it highest, multiethnic try out-of middle-ages women from the SWAN research, we discovered that members having large cousin quantities of LBM was basically less inclined to generate VMS while they transitioned compliment of menopause. That it effect is seen to be separate off sociodemographic activities and you may levels of body weight bulk. At the same time, because mediocre age of the participants within our study enhanced from 52.0 so you can 56.6 age as well as the amount of women who was in fact postmenopausal enhanced out-of forty% (letter = 430) at visit six in order to 72% (letter = 733) within head to ten, the study were able to document brand new way by way of menopause changeover for almost all the cohort.
Big present research has concerned about the new relationship off human anatomy size list (BMI) and % body fat that have VMS features advised a confident relationship between growing Body mass index and presence of VMS [31, egyptisk kvinner med dating thirty-two,33,34,35,36]. not, Body mass index is considered a terrible predictor out of body mass as it merely a way of measuring additional weight and won’t identify ranging from surplus fat mass and you may fat free bulk . All of our analysis checked out the components out of human body composition and found slim mass, determined by one another fat-free mass and you will skeletal muscles, getting a life threatening effect on the chances of development VMS over time if you’re still due to the potential feeling regarding pounds mass. A current mix-sectional examination of 758 feminine found that trunk area slim bulk was a different protective factor for modest to big menopausal attacks and you will you to VMS was in fact individually associated with large Bmi and you can body weight size . The underlying elements of one’s dating between muscles structure and you may VMS aren’t totally clear due to the partial knowledge of the structure out-of VMS .
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