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Changes in soft tissue composition are the primary predictors of four-year bone mineral
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density changes in post-menopausal women.
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Laura A. Milliken1, Ph.D. (Corresponding Author and Reprints); Ellen Cussler2, M.S.; Richard
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A. Zeller3, Ph.D.; Ji-Eun Choi2, M.S.; Lauve Metcalfe2, M.S.; Scott B. Going4, Ph.D.; and
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Timothy G. Lohman2, Ph.D.
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Morrissey Blvd., Boston, MA 02125 Phone: 617-287-7483 Fax: 617-287-7504 Email:
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laurie.milliken@umb.edu
Department of Exercise and Health Sciences, University of Massachusetts Boston, 100
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Department of Physiology, University of Arizona, Tucson, AZ, 85721
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College of Nursing, Kent State University, Kent, Ohio 44242-0001
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Department of Nutritional Sciences, University of Arizona, Tucson, AZ, 85721
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Mini-abstract
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Changes in body weight influence bone mineral density but the role of body composition is not
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clear in postmenopausal women. Body weight and soft tissue composition predicted bone
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changes independent of calcium supplementation and exercise frequency indicating that soft
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tissue composition should be measured in clinical trials.
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Abstract
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Introduction: The purpose of this study was to examine the relationship between changes in body
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weight and composition and changes in 4-year bone mineral density (BMD) after accounting for
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age, 4-year exercise frequency (EX), and 4-year calcium supplement intake (CA) in
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postmenopausal women with and without hormone therapy (HT).
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Methods: Postmenopausal women (40-65 years) using HT (for 1 to 3.9 years) and not using HT
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(for !1 year) were recruited to the study. EX and CA was monitored throughout the study; 167
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women completed 4 years. BMD and soft-tissue composition measurements were made using
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dual-energy x-ray absorptiometry. Regression was used to predict 4-year BMD changes from
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EX, CA, age, baseline and 4-year changes in body weight and composition. HT users (n = 115,
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55.3 ± 4.3 yrs) and non-users (n = 52, 57.5 ± 4.7 yrs) were analyzed separately.
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Results: The models predicting regional BMD changes that included soft-tissue composition
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changes explained the most variation compared to those with body weight or EX and CA alone.
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Higher amounts of variation were explained in the noHT group. Conclusion: Body composition
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changes are important positive predictors of BMD changes independent of EX and CA
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supplementation, but their contribution varies by bone site and with HT use.
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Keywords: calcium, exercise, fat mass, hormone therapy, lean mass
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Introduction
Major determinants of bone loss are an inadequate calcium intake, the lack of weight-
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bearing or strengthening exercises, and the hormonal status of an individual [1]. In addition to
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these important predictors of bone loss, change in body weight is also a predictor of bone change
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in post-menopausal women [1,2,3,4]. Body weight is related to the amount and density of the
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skeleton [1] and weight loss, either intentional or unintentional, results in bone loss [3].
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However, the association between the composition of weight change and bone density change
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over several years has not been thoroughly studied. Cross-sectional evidence in females shows
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that lean mass and fat mass may have different relationships with bone density during different
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stages of life and with chronic exercise. In studies on premenopausal women, the majority show
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that lean mass is more strongly related to bone density than fat mass [5,6,7,8,9]. In one sample
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of premenopausal women stratified by habitual exercise, lean mass was associated with bone
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density in exercisers but fat mass was the stronger predictor in sedentary women [10]. In
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postmenopausal women, both lean and fat mass show associations with bone density, with fat
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mass being more consistently related [7,9,11,12,13,14,15].
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The influence of changes in fat and lean mass on changes in bone density has not been
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well documented, nor has the relative impact of soft tissue composition on bone compared to
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other factors known to affect bone. Chen (1997) found that changes in weight and fat mass, but
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not lean mass predicted one year changes in bone density or bone mineral content in a sample of
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post-menopausal women not taking HT [11]. Two-year changes in weight and fat mass, as well
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as baseline weight, predicted 2-year changes in BMD in a sample of 122 postmenopausal women
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[16]. Similar results were found in a sample of 104 postmenopausal women when predicting 10
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year changes in bone [17]. In contrast to these reports, Van Langendonck (2004) reported that
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lean mass and not fat mass significantly predicted 10 month changes in BMD in 39
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postmenopausal women taking HT [18].
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The role of soft tissue composition (all non-bone tissue) in the regulation of bone density
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throughout the lifespan is of critical importance, especially today when weight consciousness is
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high, yet this has not been thoroughly studied. Surprisingly, little is known about how exercise,
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calcium supplementation or hormone therapy alters the effects of changes in soft tissue
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composition on bone. Therefore, the purpose of this study was to determine whether body
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weight, changes in body weight, soft tissue composition, and changes in soft tissue composition
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were significant predictors of four year regional BMD changes after accounting for age, the four
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year average hormone therapy (HT) use, exercise frequency (EX), and calcium supplement
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intake (CA) in a sample of postmenopausal women.
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Methods
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Subjects and Study Design
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The analysis presented herein were completed on longitudinal data from the Bone
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Estrogen Strength Training (BEST) study which was originally designed to determine the one
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year effects of exercise training on BMD in postmenopausal women either taking or not taking
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HT. In the original study, three hundred and twenty postmenopausal women aged 40-65 years
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were recruited and 266 women completed the one-year study (Figure 1). Women were 3 to10
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years past menopause (natural or surgical), participated in less than 120 minutes of exercise per
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week, and were willing to be randomized to an exercise or control group. Exclusion criteria
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included: smoking, a history of fractures, low BMD (Z score of –3.0 or less), body mass index
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(kg/m2) >32.9 or <19.0, or use of any bone altering medication (except HT). At the study’s start,
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subjects were either taking HT (for between 1 to 3.9 years) or not taking HT (for at least 1 year)
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and were randomized within group to either a 1-year supervised exercise training program or the
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control group (Figure 1). The main effects of exercise with and without HT on BMD have been
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published [19]. The contributions of EX and CA to four year changes in bone in both HT
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populations were also examined [20].
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After the one year clinical trial, women were invited to continue in the program; women
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randomized to the control group were allowed to self-select exercise or control. Participants
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were asked to return annually for BMD and soft tissue composition measurements and to
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complete questionnaires. The exercisers were asked to complete workout logs which were
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reviewed monthly by trained staff.
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The present study includes 167 of the 177 who had complete yearly data through 4 years.
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Ten women were excluded from the analyses for the following reasons: six women began taking
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Fosamax® (alendronate), two women began treatment for cancer, one woman was hospitalized
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for six months with a broken leg (unrelated to the training program), and one woman began
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taking steroids. Of the 167 women, 78 were originally in the no exercise; fifty-five women
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crossed over to the exercise group and 23 did not cross-over. The remaining 89 women were
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those who had been randomly assigned to the exercise group at the start of the study (Figure 1).
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All protocols were approved by the University of Arizona’s Institutional Review Board and
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informed consent was obtained from each participant.
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Dual-Energy X-Ray Absorptiometry and Anthropometry
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Lumbar spine (LS), femoral neck (FN), and greater trochanter (TR) BMDs (g/cm2) were
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measured in duplicate (within 7 days) on medium speed at baseline and yearly thereafter using a
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Lunar DPX-L (version 1.3y, Lunar Radiation Corporation, Madison, WI) dual-energy x-ray
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absorptiometer (DXA). Fat mass and lean mass were determined from total body scans using the
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same instrument. The average of the two scans at each time point was used in all analyses. Scan
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analysis was performed by one certified technician using the extended research analysis feature.
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DXA calibration was performed daily using a calibration block supplied by the manufacturer.
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The coefficient of variation for this block was 0.6%. BMD precision, expressed as a percent of
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mean BMD, was less than 2.4% for each BMD site. The coefficient of variation for repeated
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measures of percent fat was 2.8%. Body weight (kg) (WT) was measured to the nearest 0.1 kg at
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baseline and yearly thereafter using a digital scale (SECA, Model 770, Hamburg, Germany) and
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height was measured to the nearest 0.1cm with a Schorr measuring board.
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Hormone Therapy
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Women who were on any physician approved HT regimen for at least 1 year and up to 4
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years were accepted into the study. Most women (80%) took oral estrogen plus progesterone,
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10% took oral estrogen alone and 10% used estrogen alone or with progesterone administered
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via the patch. Though women were asked to maintain their regimen throughout their
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participation, one woman stopped HT during the second year and 25 women started taking HT
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after the first year. Of those 25 who began HT, 12 began in the first two years and 13 began in
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the third or fourth years. All subjects completed the 4 years of follow-up prior to the Women’s
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Health Initiative report documenting a relationship between HT use and an increased risk of
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certain cancers [21]. The sample was divided into those women who took HT for most of the 4
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years (HT group) and those who took little or no HT during the 4 years (NoHT group). Those
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women who took HT for four years (n = 89) plus those who took HT for at least 1 year (n = 26)
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were included in the HT group. Women who did not take HT (n = 51) or took HT for less than 1
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year (n = 1) were included in the NoHT group. The average HT use (yrs) for the HT and NoHT
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groups was 3.58 ± 0.85 yrs and 0.006 ± 0.04 yrs (p < 0.05), respectively.
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Calcium Supplement Intake
During the first and second years of the study, 800mg/day of elemental calcium was
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provided (Citrical!, Mission Pharmacal, San Antonio, TX). During subsequent years, subjects
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were asked to continue supplementation by purchasing Citrical® or another comparable
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supplement. CA (mg/day) was monitored by pill counts and quarterly written self-reports. CA
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from pill counts and self-reports were averaged over four years.
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Exercise Program
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The exercise program was a supervised 3 day per week program that lasted 60 – 75
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minutes per session. Sessions took place at 4 local fitness facilities and consisted of a warm-up,
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stretching, strength training, and weight-bearing exercises. This program is described in detail
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elsewhere [22]; briefly, six to ten repetitions at 70% of maximum for 8 exercises targeting the
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major muscle groups were performed on non-consecutive days. The 8 exercises were: seated
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leg press, lat pulldown, weighted march, seated row, one-arm overhead dumbbell press, squats,
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rotary torso machine, and back extension. The intensity was progressively increased based on
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monthly one repetition maximum strength testing. Weight-bearing exercises included activities
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such as hopping, skipping, walking/jogging and stair stepping while wearing weighted vests.
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Each participant recorded the exercises performed, the intensity/repetitions, and the amount and
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type of weight-bearing activity that was completed using workout logs. Annual exercise
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frequency was calculated by dividing the number of sessions attended by the number prescribed
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for that year, expressed as a percent. Those who were assigned to the control group in the first
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year and those who remained controls in subsequent years were assigned a 0% exercise
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frequency. The four-year average was calculated and used in the analyses.
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Statistical Analysis
All analyses were carried out using the Statistical Package for Social Sciences (SPSS, v
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13.0, Chicago, IL). The probability of making a Type I error was set at p < 0.05. Pearson
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correlation coefficients (Table 2) were calculated to estimate the relationship for the yearly
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regional BMDs between sites. Hierarchical multiple regression analysis (Table 3) was used to
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determine predictors of four year BMD changes ("BMD) for the LS, FN and TR regional sites.
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Independent variables included the age, average 4-year exercise frequency (EX), the average 4-
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year calcium supplement intake (CA), the 4-year changes in fat mass ("FAT) and lean mass
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("LEAN), baseline WT (BLWT), baseline fat (BLFAT), baseline lean (BLLEAN) and four-year
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changes in WT ("WT). Several models were constructed; model 1 included EX, CA and age for
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the prediction of "BMD for each regional site. The effects of "WT plus BLWT (Model 2) and
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"FAT, "LEAN, BLFAT, and BLLEAN (Model 3) were also calculated with both models
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controlling for EX, CA and age. All R2 values presented are adjusted R2s.
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The Measurement of Change. A change score is ordinarily defined as the post score
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minus the pre score. The problem is that the change score is negatively correlated with the pre-
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score. The higher a respondent is initially, relative to other respondents, the lower that
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respondent’s change score will be. This is called “regression toward the mean.” However, the
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residuals of the post score predicted from the pre score, by definition, are perfectly uncorrelated
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with the pre score. Therefore, when assessing “change” in this analysis, we used residuals
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(Table 3). Specifically, in this study, residuals from the fourth year regressed against baseline
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were used in place of the raw 4-year change in the regional BMD sites, WT, fat, and lean mass
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[23]. However, we have included analyses performed in a more traditional manner using raw
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changes for bone density (Table 4). These analyses resulted in higher colinearity compared to
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the residualized analyses (shared variance between independent variables as high as 43.2%
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versus 29.9% in the residualized analyses); therefore Table 4 may overestimate the relationships
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presented.
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Results
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Study Sample.
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Table 1 shows the baseline and 4 year values for the regional BMD sites and mean values
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for HT use, EX, and CA for the full sample (n = 167) and when split by HT use. Subjects
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consumed an average of 1635 ± 367.1 mg/day of CA and attended an average of 35.7 ± 28.7% of
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the prescribed exercise sessions over four years. As expected, the four-year HT use was
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significantly different between HT groups (3.58 ± 0.85 years for the HT group vs 0.006 ± 0.04
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years for the NoHT group). The HT group was 2.4 years younger and had significantly higher
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four year TR and LS BMD.
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BMD Associations Between Regional Sites.
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Table 2 shows the correlations between regional BMD sites based on four separate years
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of data. Correlations between sites showed the highest associations occurring between the FN
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and TR (0.778 – 0.831, p < 0.05) and the lowest occurring between the TR and LS (0.571 –
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0.630, p < 0.05). When correlations were performed for the groups split by HT use, the
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associations among sites for the noHT group were consistently lower than the HT group (p <
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0.05).
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Model 1: Predicting Long-Term BMD Changes From Exercise Frequency, Calcium Supplement
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Intake, and Age.
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The amount of variation in 4-year "BMD that was accounted for by CA, EX and age for
women who did not use HT was 16.8% (p = 0.030), 14.1% (p = 0.062), and 37.6% (p = 0.000)
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for the FN, TR, and LS, respectively. In this group, CA was a significant predictor at the FN and
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TR while age was significant at the FN and LS. EX was significant only at the LS (Table 3).
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For women who used HT, much less variation in " BMD was explained by EX, CA, and
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age, equaling 4.2% (p = 0.192), 9.7% (p = 0.010), and 8.0% (p = 0.026) at the FN, TR, and LS,
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respectively. EX significantly predicted "BMD at all regional sites for the HT group. CA and
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age were not significant at any site in this group (Table 3).
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Model 2: Predicting Long-Term BMD Changes From Baseline Weight and Changes in Body
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Weight (after accounting for age, CA and EX)..
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The amount of variation in "BMD for the FN, TR, and LS that was explained by BLWT
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plus "WT was 14.8% (p = 0.000), 13.9% (p = 0.000), and 7.7% (p = 0.009), respectively, for the
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HT groups and 1% (p = 0.756), 17.1% (p = 0.006), and 3.2% (p = 0.295), respectively, for the
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noHT group. For HT users, BLWT and "WT were both significant (p < 0.05) positive predictors
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for the FN and TR but not LS (Table 3). For women not using HT, BLWT and "WT were not
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significant predictors of " BMD, although they approached significance (p < 0.10) at the TR.
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Model 3: Predicting Long-Term BMD Changes From Baseline Soft Tissue Composition and
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Changes in Soft Tissue Composition (after accounting for age, CA and EX).
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The amount of variation in "BMD for the FN, TR, and LS that was explained by
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BLFAT, BLLEAN, "FAT and "LEAN was 17.8% (p = 0.000), 17.6% (p = 0.000), and 10.1% (p
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= 0.013), respectively, for the HT groups and 6.7% (p = 0.438), 31.2% (p = 0.000), and 5.8% (p
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= 0.356), respectively, for the noHT group. The "LEAN and "FAT were significant positive
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predictors of FN (p < 0.05), TR (p < 0.05) and LS (p < 0.10) "BMD for the HT group. BLFAT
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was a significant positive predictor (p < 0.05) of FN and TR "BMD but not LS. BLLEAN was
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not a significant predictor of "BMD at any regional site for the HT group. For those using HT,
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the "LEAN and "FAT were significant positive predictors of TR "BMD. BLFAT and
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BLLEAN were not significant except BLLEAN at the TR (p < 0.10) (Table 3).
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Discussion
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The findings of the present study support the notion that exercise and calcium intake,
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along with the body’s hormonal milieu, are significant factors in predicting bone changes;
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however, our results also suggest that changes in fat and lean mass play a more important role in
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the regulation of bone density than current public health messages suggest. Changes in fat and
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lean mass explained an additional 6 to 32% of the variation in BMD changes in addition to that
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accounted for by EX, CA, and age. We have previously shown that EX and CA significantly
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predicts BMD changes [20].
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The role of soft tissue composition also seems to be site-specific exerting a larger impact
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at the femoral neck and greater trochanter. This effect is more pronounced in those taking HT
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despite accounting for overall less variation in BMD changes in this group. Correlations
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between spine and hip are lower than between the two hip sites, where less than 40% of the
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variance in hip BMD can be accounted for by spine BMD changes. The standardized regression
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coefficients show that soft tissue composition changes are more closely related to trochanter
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BMD than to spine and femur neck changes. Whether the differences between exercise studies in
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BMD regional outcomes can be explained, in part, by differences in the changes in soft tissue
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composition is not yet known.
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Despite exposure to similar systemic conditions, bone sites respond independently even
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after accounting for the effects of exercise and calcium. Two areas of the hip, the FN and TR
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sites, also responded differently, particularly for those not taking HT. The TR was sensitive to
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changes in weight and soft tissue composition while the FN was not; both hip sites were
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significant predictors in the HT group. This finding is supported by Stewart (2005) who found
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that, in a randomized exercise training study of 53 postmenopausal women (47% of whom took
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HT), six month changes in weight, BMI, and peak oxygen uptake were correlated with changes
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in FN but not TR (using bivariate analyses) [24].
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The significant effect of exercise also persists with the addition of soft tissue
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composition variables to the predictive models for the HT group, suggesting that the forces
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generated on bone during exercise have an effect that is independent of the effect of changes in
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lean and fat mass. In the only case where EX significantly predicted BMD changes (at the LS)
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for the NoHT group, it became nonsignificant when the soft tissue composition variables were
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added. Thus, it appears the exercise effects in the NoHT group at the spine were mediated by
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changes in soft tissue composition. This was not the case in the HT group.
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For women not taking HT, the effect of CA (at all BMD sites) and age (at the FN only)
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became nonsignificant when soft tissue composition variables were added to the models
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suggesting that these variables account for the same variation in BMD changes at these sites. At
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the LS, age remained a significant predictor of BMD changes when soft tissue composition
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variables were added. When age was removed from the analysis, the soft tissue composition
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variables were still significant (results not shown), indicating that age and soft tissue composition
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changes are independent of each other in relation to spine BMD changes.
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We conclude that soft tissue composition, both baseline and subsequent changes, are
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important in the regulation of BMD changes, especially for those taking HT. We recommend
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including the measurement of fat and lean mass when testing the effect of any new, potentially
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osteogenic, therapies. It is also important to examine the effects of the baseline fat and lean
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masses because this can affect the amount of BMD change in some populations. Also, it is
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important to study femur neck and trochanter sites separately as well as total hip when
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examining the long term effect of exercise because of the differential response of the hip sites to
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a given exercise protocol.
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Acknowledgements: Supported by the National Institute for Arthritis, and Musculoskeletal and
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Skin Diseases, National Institutes of Health (AR39559 & AR047932) and by Mission Pharmacal
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(San Antonio, TX). Conflict of interest: No Disclosures. Address correspondence to: Laura A.
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Milliken, PhD., Department of Exercise and Health Sciences, University of Massachusetts
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Boston, 100 Morrissey Blvd., Boston, MA 02125 Email: laurie.milliken@umb.edu
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Figure 1: Subject recruitment, group assignment, and long-term retention.
HT Users
54.6 ± 4.4 yrs
n = 159
No HT
55.9 ± 5.0 yrs
n = 161
Randomization
Baseline
HT
Exercise
Calcium
n = 86
HT
No Exercise
Calcium
n = 73
No HT
Exercise
Calcium
n = 91
No HT
No Exercise
Calcium
n = 70
No HT
Exercise
Calcium
n = 71
No HT
No Exercise
Calcium
n = 59
Year 1
HT
Exercise
Calcium
n = 71
HT
No Exercise
Calcium
n = 65
Year 4
Dropped (n = 99)
54.8 ± 5.0 yrs
HT (n = 46)
No HT (n = 53)
HT (n = 115)
55.3 ± 4.3 yrs
EX (n = 100)
No EX (n = 15)
No HT (n = 52)
57.5 ± 4.7 yrs
EX (n = 44)
No EX (n = 8)
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Table 1: Subject physical characteristics for the groups split by hormone therapy (HT)
use.
Baseline
Mean ± SD*
HT Use
No HT Use
(n = 115)
(n = 52)
Age (yrs)
55.3 ± 4.3†
57.5 ± 4.7†
Weight (kg)
67.2 ± 11.8
66.3 ± 10.3
Body Mass Index (kg/m2)
25.3 ± 3.9
24.8 ± 3.2
Fat mass (kg)
25.8 ± 8.7
25.4 ± 7.3
Lean mass (kg)
38.3 ± 4.4
38.0 ± 4.3
Femur Neck BMD (g/cm2)
0.873 ± 0.123
0.857 ± 0.115
Trochanter BMD (g/cm2)
0.753 ± 0.111
0.723 ± 0.102
Spine (L2-4) BMD (g/cm2)
1.135 ± 0.146
1.101 ± 0.134
Weight (kg)
68.5 ± 11.4
67.1 ± 11.1
Body Mass Index (kg/m2)
26.0 ± 3.8
25.0 ± 3.5
Fat mass (kg)
26.5 ± 8.5
25.2 ± 7.8
Lean mass (kg)
38.8 ± 4.3
38.2 ± 4.7
Femur Neck BMD (g/cm2)
0.874 ± 0.125
0.848 ± 0.111
Trochanter BMD (g/cm2)
0.759 ± 0.113†
0.715 ± 0.105†
Spine (L2-4) BMD (g/cm2)
1.145 ± 0.164†
1.084 ± 0.149†
Calcium Supplement Intake (mg·d-1)
715.0 ± 160.5
701.3 ± 218.4
HT use (yrs)
3.58 ± 0.85†
0.006 ± 0.04†
Exercise Attendance (%)
38.0 ± 29.5
30.5 ± 26.7
Follow-up at Four Years
Four Year Average
*SD is standard deviation; † HT groups significantly different (p < 0.05)
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Table 2: Pearson correlations* among regional BMD sites (using data for multiple years)
for the combined sample and the sample split by HT use.
Total Sample
(n = 167)
Femur Neck v. Trochanter
0.778 – 0.831
Trochanter v. Spine
0.571 – 0.630
Spine v. Femur Neck
0.609 – 0.658
* All coefficients are significant (p < 0.05)
No HT Use
(n = 52)
0.717 – 0.805
0.448 – 0.555
0.498 – 0.628
HT Use
(n = 115)
0.782 – 0.852
0.589 – 0.648
0.635 – 0.671
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Table 3: Standardized coefficients and explained variance from hierarchical regression
models predicting 4-year regional BMD residuals in postmenopausal women using (n =
115) and not using HT (n = 52).
a) Models Predicting 4-Year Neck BMD Residuals
Model 1
Model 2
Model 3
Variables
noHT
HT
noHT
HT
noHT
HT
Calcium Suppl. Intake (mg/d)
-0.062
0.259 -0.072
0.272
0.290 -0.105
Exercise Frequency (%)
-0.080 0.202
-0.074 0.246
-0.158
0.225
Age (years)
-0.085
0.264 -0.087
0.230
0.295 -0.044
Baseline Weight (kg)
0.107 0.294
" Body Weight (kg)
0.022 0.260
Baseline Fat Mass (kg)
0.042
0.261
Baseline Lean Mass (kg)
-0.018
0.060
" Lean Mass (kg)
0.273
0.178
" Fat Mass (kg)
-0.021
0.200
R2 Change†
1.0
14.8
6.7
17.8
2
Model R
16.8
4.2
17.8
19.0
23.5
22.0
b) Models Predicting 4-Year Trochanter BMD Residuals
Model 1
Model 2
Model 3
Variables
noHT
HT
noHT
HT
noHT
HT
Calcium Suppl. Intake (mg/d)
0.140 0.127
0.152
0.142
0.336 0.088
Exercise Frequency (%)
-0.030 0.255
0.057 0.299
-0.075
0.265
Age (years)
0.178 -0.128
0.113 -0.147
0.087
-0.145
Baseline Weight (kg)
0.225 0.189
" Body Weight (kg)
0.409 0.328
Baseline Fat Mass (kg)
-0.064
0.231
Baseline Lean Mass (kg)
-0.048
0.245
" Lean Mass (kg)
0.443
0.232
" Fat Mass (kg)
0.257
0.217
R2 Change†
17.1
13.9
31.2
17.6
2
Model R
14.1
9.7
31.2
23.6
45.3
27.3
c) Models Predicting 4-Year Spine BMD Residuals
Model 1
Model 2
Model 3
Variables
noHT
HT
noHT
HT
noHT
HT
Calcium Suppl. Intake (mg/d)
0.099
0.231 0.097
0.236
0.301 0.068
Exercise Frequency (%)
0.213
0.254 0.226
0.275 0.259
0.232
Age (years)
0.095
0.449 0.100
0.397 0.085
0.385
Baseline Weight (kg)
0.181 0.146
" Body Weight (kg)
0.087 0.241
Baseline Fat Mass (kg)
0.049
0.025
Baseline Lean Mass (kg)
0.137
0.147
" Lean Mass (kg)
0.177
0.187
" Fat Mass (kg)
0.020
0.165
2
R Change†
3.2
7.7
5.8
10.1
Model R2
37.6
8.0
40.8
15.7
43.4
18.1
2
Bold p < 0.05; italics p < 0.10; † R change from Model 1
17
Table 4: Standardized coefficients and explained variance from hierarchical regression
models predicting 4-year regional BMD changes in postmenopausal women using (n = 115)
and not using HT (n = 52).
a) Models Predicting 4-Year Neck BMD Changes
Model 1
Variables
noHT
HT
Calcium Suppl. Intake (mg/d)
-0.102
0.287
Exercise Frequency (%)
-0.075
0.199
Age (years)
-0.040
0.291
Baseline Neck BMD
-0.340 -0.119
Baseline Weight (kg)
" Body Weight (kg)
Baseline Fat Mass (kg)
Baseline Lean Mass (kg)
" Lean Mass (kg)
" Fat Mass (kg)
R2 Change†
Model R2
26.0
5.1
b) Models Predicting 4-Year Trochanter BMD Changes
Model 1
Variables
noHT
HT
Calcium Suppl. Intake (mg/d)
0.087
0.331
Exercise Frequency (%)
-0.026
0.253
Age (years)
0.176
-0.126
Baseline Trochanter BMD
-0.062 -0.106
Baseline Weight (kg)
" Body Weight (kg)
Baseline Fat Mass (kg)
Baseline Lean Mass (kg)
" Lean Mass (kg)
" Fat Mass (kg)
R2 Change†
Model R2
14.4
11.0
c) Models Predicting 4-Year Spine BMD Changes
Model 1
Variables
noHT
HT
Calcium Suppl. Intake (mg/d)
0.063
0.309
Exercise Frequency (%)
0.246
0.233
Age (years)
0.113
0.437
Baseline Spine BMD
0.158
0.231
Baseline Weight (kg)
" Body Weight (kg)
Baseline Fat Mass (kg)
Baseline Lean Mass (kg)
" Lean Mass (kg)
" Fat Mass (kg)
R2 Change†
Model R2
39.4
11.8
Model 2
noHT
HT
-0.074
0.268
-0.060
0.248
0.221
-0.097
-0.429 -0.239
0.211
0.387
-0.008
0.270
3.2
29.2
15.0
20.1
Model 2
noHT
HT
0.140
0.123
0.066
0.295
0.081
-0.153
-0.192 -0.247
0.366
0.359
0.412
0.337
17.7
32.1
15.6
26.6
Model 2
noHT
HT
0.093
0.250
0.257
0.260
0.086
0.368
0.230
0.212
0.071
0.244
0.083
0.180
Bold p < 0.05; italics p < 0.10; † R2 change from Model 1
2.7
42.1
7.3
19.1
Model 3
noHT
HT
-0.062
0.272
-0.158
0.225
-0.085
0.230
-0.423
-0.238
0.084
0.087
0.280
-0.050
8.4
34.4
0.334
0.108
0.190
0.205
18.0
23.1
Model 3
noHT
HT
0.148
0.134
-0.070
0.264
0.056
-0.150
-0.185
-0.221
-0.034
0.322
0.441
0.266
31.9
46.3
0.338
-0.034
0.233
0.226
18.7
29.7
Model 3
noHT
HT
0.095
0.263
0.175
0.234
0.092
0.343
0.041
0.175
0.085
0.170
0.214
-0.007
6.2
45.6
0.081
0.179
0.183
0.172
9.6
21.4
18
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