This study was a secondary analysis of existing data utilizing the public dataset from the SWAN study37-42. Details of the SWAN design and recruitment procedures are reported elsewhere14, however, a brief summary is provided here. Baseline eligibility criteria included being aged 42 to 52 years, having a uterus and at least one ovary, not being pregnant or lactating, not using oral contraceptives or hormone therapy in the previous three months, and having at least one menstrual cycle in the preceding months. Participants self-identified as African-American (28%), Caucasian (47%), Chinese (8%), Hispanic (8%), or Japanese (9%). Eligible women meeting the inclusion criteria were invited to join the cohort and were seen within three months of the initial survey for their baseline assessment where a written informed consent was obtained. Assessments consisted of questionnaires regarding medical history, medication, menstrual history, lifestyle, psycho-social factors, physical and psychological symptoms, and health-related quality of life, as well as blood and urine specimen collection and physical measures. Procedures specific to this study included annual examinations, questionnaires, and BIA measures. Approval for this study was granted by the Institutional Review Board at California University of Pennsylvania.
Anthropometry/body composition. Analysis was limited to the use of body composition data collected using bioelectrical impedance analysis (BIA) and included 2,533 women. BIA is based on measurement of the transmission speed of a one-quarter volt electrical pulse between electrodes attached at the feet and electrodes attached across the knuckles of the hand. Because fat-free mass is comprised of water, proteins, and electrolytes, conductivity is greater in fat-free mass than in fat mass15. Resistance and reactance are used to estimate total body water, and by extension, fat mass and lean mass, with the latter including bone16. The validity and predictive value of BIA in menopausal women has been confirmed by a recent study17. Skeletal muscle mass was calculated by the method of Janssen et al.18, who subsequently indexed skeletal muscle mass to height for a skeletal muscle index (SMI = skeletal muscle mass (kg) / height (m2)). Fat free mass, total body water, and percent body fat were all provided by RJL Systems and validated using NHANES III data19. Fat free mass (kg) and fat mass (kg) were both indexed to height to create fat mass index (FMI = kg/m2) and fat free mass index (FFMI = kg/m2). Height (m) and weight (kg) were measured in light clothing, without shoes, using a standard protocol with a stadiometer for height and a balance beam scale for weight. Hip circumference (cm) was measured at the iliac crest and waist circumference (cm) was measured at the level of the natural waist or the narrowest part of the torso from the anterior aspect 20,21.
Vasomotor symptoms. Hot flashes and night sweats were assessed via questionnaire at each SWAN visit. Women responded to two questions that separately asked them to record how often hot flashes and night sweats were experienced in the two weeks prior to the annual visit (not at all, 1-5 days, 6-8 days, 9-13 days, everyday). Accuracy of recall for VMS among the SWAN participants was previously verified22.
Covariates. Covariates were selected on the basis of previously documented associations with VMS23 and body composition21, and included age, educational level (less than high school, high school, some college, college, or post baccalaureate degree), race/ethnicity, quality of life, and menopausal transition stage. Race/ethnicity and educational level were self-reported in the SWAN screening interview. SWAN participants were assessed for menopausal status assignment based on annual reports about menstrual bleeding and its regularity. Pre-menopause was identified as no decreased regularity in menstrual bleeding during the last year. Other classifications were early perimenopause (decreased menses in previous three months), late perimenopause (no menses for 3-11 months), and postmenopause (no menses for 12+ months)24. Surgical menopause was defined by report of either hysterectomy or oophorectomy, and hormone therapy (HT) use was reported as use of HT during the year24. The Medical Outcomes Short-Form 36 (SF-36) was used to assess health related quality of life (HRQL) using the original coding algorithm in which raw scores are transformed to a 0 to 100 range.
Statistical Analysis
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 ( ) for categorical variables, and Kruskal-Wallis test for continuous variables. A scatter plot matrix was used to examine linear correlations among variables. 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 one 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).