1 Changes in soft tissue composition are the primary predictors of four-year bone mineral 2 density changes in post-menopausal women. 3 Laura A. Milliken1, Ph.D. (Corresponding Author and Reprints); Ellen Cussler2, M.S.; Richard 4 A. Zeller3, Ph.D.; Ji-Eun Choi2, M.S.; Lauve Metcalfe2, M.S.; Scott B. Going4, Ph.D.; and 5 Timothy G. Lohman2, Ph.D. 6 7 1 8 Morrissey Blvd., Boston, MA 02125 Phone: 617-287-7483 Fax: 617-287-7504 Email: 9 laurie.milliken@umb.edu Department of Exercise and Health Sciences, University of Massachusetts Boston, 100 10 2 Department of Physiology, University of Arizona, Tucson, AZ, 85721 11 3 College of Nursing, Kent State University, Kent, Ohio 44242-0001 12 4 Department of Nutritional Sciences, University of Arizona, Tucson, AZ, 85721 13 14 15 16 17 18 19 Mini-abstract 20 Changes in body weight influence bone mineral density but the role of body composition is not 21 clear in postmenopausal women. Body weight and soft tissue composition predicted bone 22 changes independent of calcium supplementation and exercise frequency indicating that soft 23 tissue composition should be measured in clinical trials. 24 1 25 Abstract 26 Introduction: The purpose of this study was to examine the relationship between changes in body 27 weight and composition and changes in 4-year bone mineral density (BMD) after accounting for 28 age, 4-year exercise frequency (EX), and 4-year calcium supplement intake (CA) in 29 postmenopausal women with and without hormone therapy (HT). 30 Methods: Postmenopausal women (40-65 years) using HT (for 1 to 3.9 years) and not using HT 31 (for !1 year) were recruited to the study. EX and CA was monitored throughout the study; 167 32 women completed 4 years. BMD and soft-tissue composition measurements were made using 33 dual-energy x-ray absorptiometry. Regression was used to predict 4-year BMD changes from 34 EX, CA, age, baseline and 4-year changes in body weight and composition. HT users (n = 115, 35 55.3 ± 4.3 yrs) and non-users (n = 52, 57.5 ± 4.7 yrs) were analyzed separately. 36 Results: The models predicting regional BMD changes that included soft-tissue composition 37 changes explained the most variation compared to those with body weight or EX and CA alone. 38 Higher amounts of variation were explained in the noHT group. Conclusion: Body composition 39 changes are important positive predictors of BMD changes independent of EX and CA 40 supplementation, but their contribution varies by bone site and with HT use. 41 42 43 44 Keywords: calcium, exercise, fat mass, hormone therapy, lean mass 2 45 46 Introduction Major determinants of bone loss are an inadequate calcium intake, the lack of weight- 47 bearing or strengthening exercises, and the hormonal status of an individual [1]. In addition to 48 these important predictors of bone loss, change in body weight is also a predictor of bone change 49 in post-menopausal women [1,2,3,4]. Body weight is related to the amount and density of the 50 skeleton [1] and weight loss, either intentional or unintentional, results in bone loss [3]. 51 However, the association between the composition of weight change and bone density change 52 over several years has not been thoroughly studied. Cross-sectional evidence in females shows 53 that lean mass and fat mass may have different relationships with bone density during different 54 stages of life and with chronic exercise. In studies on premenopausal women, the majority show 55 that lean mass is more strongly related to bone density than fat mass [5,6,7,8,9]. In one sample 56 of premenopausal women stratified by habitual exercise, lean mass was associated with bone 57 density in exercisers but fat mass was the stronger predictor in sedentary women [10]. In 58 postmenopausal women, both lean and fat mass show associations with bone density, with fat 59 mass being more consistently related [7,9,11,12,13,14,15]. 60 The influence of changes in fat and lean mass on changes in bone density has not been 61 well documented, nor has the relative impact of soft tissue composition on bone compared to 62 other factors known to affect bone. Chen (1997) found that changes in weight and fat mass, but 63 not lean mass predicted one year changes in bone density or bone mineral content in a sample of 64 post-menopausal women not taking HT [11]. Two-year changes in weight and fat mass, as well 65 as baseline weight, predicted 2-year changes in BMD in a sample of 122 postmenopausal women 66 [16]. Similar results were found in a sample of 104 postmenopausal women when predicting 10 67 year changes in bone [17]. In contrast to these reports, Van Langendonck (2004) reported that 3 68 lean mass and not fat mass significantly predicted 10 month changes in BMD in 39 69 postmenopausal women taking HT [18]. 70 The role of soft tissue composition (all non-bone tissue) in the regulation of bone density 71 throughout the lifespan is of critical importance, especially today when weight consciousness is 72 high, yet this has not been thoroughly studied. Surprisingly, little is known about how exercise, 73 calcium supplementation or hormone therapy alters the effects of changes in soft tissue 74 composition on bone. Therefore, the purpose of this study was to determine whether body 75 weight, changes in body weight, soft tissue composition, and changes in soft tissue composition 76 were significant predictors of four year regional BMD changes after accounting for age, the four 77 year average hormone therapy (HT) use, exercise frequency (EX), and calcium supplement 78 intake (CA) in a sample of postmenopausal women. 79 Methods 80 Subjects and Study Design 81 The analysis presented herein were completed on longitudinal data from the Bone 82 Estrogen Strength Training (BEST) study which was originally designed to determine the one 83 year effects of exercise training on BMD in postmenopausal women either taking or not taking 84 HT. In the original study, three hundred and twenty postmenopausal women aged 40-65 years 85 were recruited and 266 women completed the one-year study (Figure 1). Women were 3 to10 86 years past menopause (natural or surgical), participated in less than 120 minutes of exercise per 87 week, and were willing to be randomized to an exercise or control group. Exclusion criteria 88 included: smoking, a history of fractures, low BMD (Z score of –3.0 or less), body mass index 89 (kg/m2) >32.9 or <19.0, or use of any bone altering medication (except HT). At the study’s start, 90 subjects were either taking HT (for between 1 to 3.9 years) or not taking HT (for at least 1 year) 4 91 and were randomized within group to either a 1-year supervised exercise training program or the 92 control group (Figure 1). The main effects of exercise with and without HT on BMD have been 93 published [19]. The contributions of EX and CA to four year changes in bone in both HT 94 populations were also examined [20]. 95 After the one year clinical trial, women were invited to continue in the program; women 96 randomized to the control group were allowed to self-select exercise or control. Participants 97 were asked to return annually for BMD and soft tissue composition measurements and to 98 complete questionnaires. The exercisers were asked to complete workout logs which were 99 reviewed monthly by trained staff. 100 The present study includes 167 of the 177 who had complete yearly data through 4 years. 101 Ten women were excluded from the analyses for the following reasons: six women began taking 102 Fosamax® (alendronate), two women began treatment for cancer, one woman was hospitalized 103 for six months with a broken leg (unrelated to the training program), and one woman began 104 taking steroids. Of the 167 women, 78 were originally in the no exercise; fifty-five women 105 crossed over to the exercise group and 23 did not cross-over. The remaining 89 women were 106 those who had been randomly assigned to the exercise group at the start of the study (Figure 1). 107 All protocols were approved by the University of Arizona’s Institutional Review Board and 108 informed consent was obtained from each participant. 109 Dual-Energy X-Ray Absorptiometry and Anthropometry 110 Lumbar spine (LS), femoral neck (FN), and greater trochanter (TR) BMDs (g/cm2) were 111 measured in duplicate (within 7 days) on medium speed at baseline and yearly thereafter using a 112 Lunar DPX-L (version 1.3y, Lunar Radiation Corporation, Madison, WI) dual-energy x-ray 113 absorptiometer (DXA). Fat mass and lean mass were determined from total body scans using the 5 114 same instrument. The average of the two scans at each time point was used in all analyses. Scan 115 analysis was performed by one certified technician using the extended research analysis feature. 116 DXA calibration was performed daily using a calibration block supplied by the manufacturer. 117 The coefficient of variation for this block was 0.6%. BMD precision, expressed as a percent of 118 mean BMD, was less than 2.4% for each BMD site. The coefficient of variation for repeated 119 measures of percent fat was 2.8%. Body weight (kg) (WT) was measured to the nearest 0.1 kg at 120 baseline and yearly thereafter using a digital scale (SECA, Model 770, Hamburg, Germany) and 121 height was measured to the nearest 0.1cm with a Schorr measuring board. 122 Hormone Therapy 123 Women who were on any physician approved HT regimen for at least 1 year and up to 4 124 years were accepted into the study. Most women (80%) took oral estrogen plus progesterone, 125 10% took oral estrogen alone and 10% used estrogen alone or with progesterone administered 126 via the patch. Though women were asked to maintain their regimen throughout their 127 participation, one woman stopped HT during the second year and 25 women started taking HT 128 after the first year. Of those 25 who began HT, 12 began in the first two years and 13 began in 129 the third or fourth years. All subjects completed the 4 years of follow-up prior to the Women’s 130 Health Initiative report documenting a relationship between HT use and an increased risk of 131 certain cancers [21]. The sample was divided into those women who took HT for most of the 4 132 years (HT group) and those who took little or no HT during the 4 years (NoHT group). Those 133 women who took HT for four years (n = 89) plus those who took HT for at least 1 year (n = 26) 134 were included in the HT group. Women who did not take HT (n = 51) or took HT for less than 1 135 year (n = 1) were included in the NoHT group. The average HT use (yrs) for the HT and NoHT 136 groups was 3.58 ± 0.85 yrs and 0.006 ± 0.04 yrs (p < 0.05), respectively. 6 137 138 Calcium Supplement Intake During the first and second years of the study, 800mg/day of elemental calcium was 139 provided (Citrical!, Mission Pharmacal, San Antonio, TX). During subsequent years, subjects 140 were asked to continue supplementation by purchasing Citrical® or another comparable 141 supplement. CA (mg/day) was monitored by pill counts and quarterly written self-reports. CA 142 from pill counts and self-reports were averaged over four years. 143 Exercise Program 144 The exercise program was a supervised 3 day per week program that lasted 60 – 75 145 minutes per session. Sessions took place at 4 local fitness facilities and consisted of a warm-up, 146 stretching, strength training, and weight-bearing exercises. This program is described in detail 147 elsewhere [22]; briefly, six to ten repetitions at 70% of maximum for 8 exercises targeting the 148 major muscle groups were performed on non-consecutive days. The 8 exercises were: seated 149 leg press, lat pulldown, weighted march, seated row, one-arm overhead dumbbell press, squats, 150 rotary torso machine, and back extension. The intensity was progressively increased based on 151 monthly one repetition maximum strength testing. Weight-bearing exercises included activities 152 such as hopping, skipping, walking/jogging and stair stepping while wearing weighted vests. 153 Each participant recorded the exercises performed, the intensity/repetitions, and the amount and 154 type of weight-bearing activity that was completed using workout logs. Annual exercise 155 frequency was calculated by dividing the number of sessions attended by the number prescribed 156 for that year, expressed as a percent. Those who were assigned to the control group in the first 157 year and those who remained controls in subsequent years were assigned a 0% exercise 158 frequency. The four-year average was calculated and used in the analyses. 7 159 160 Statistical Analysis All analyses were carried out using the Statistical Package for Social Sciences (SPSS, v 161 13.0, Chicago, IL). The probability of making a Type I error was set at p < 0.05. Pearson 162 correlation coefficients (Table 2) were calculated to estimate the relationship for the yearly 163 regional BMDs between sites. Hierarchical multiple regression analysis (Table 3) was used to 164 determine predictors of four year BMD changes ("BMD) for the LS, FN and TR regional sites. 165 Independent variables included the age, average 4-year exercise frequency (EX), the average 4- 166 year calcium supplement intake (CA), the 4-year changes in fat mass ("FAT) and lean mass 167 ("LEAN), baseline WT (BLWT), baseline fat (BLFAT), baseline lean (BLLEAN) and four-year 168 changes in WT ("WT). Several models were constructed; model 1 included EX, CA and age for 169 the prediction of "BMD for each regional site. The effects of "WT plus BLWT (Model 2) and 170 "FAT, "LEAN, BLFAT, and BLLEAN (Model 3) were also calculated with both models 171 controlling for EX, CA and age. All R2 values presented are adjusted R2s. 172 The Measurement of Change. A change score is ordinarily defined as the post score 173 minus the pre score. The problem is that the change score is negatively correlated with the pre- 174 score. The higher a respondent is initially, relative to other respondents, the lower that 175 respondent’s change score will be. This is called “regression toward the mean.” However, the 176 residuals of the post score predicted from the pre score, by definition, are perfectly uncorrelated 177 with the pre score. Therefore, when assessing “change” in this analysis, we used residuals 178 (Table 3). Specifically, in this study, residuals from the fourth year regressed against baseline 179 were used in place of the raw 4-year change in the regional BMD sites, WT, fat, and lean mass 180 [23]. However, we have included analyses performed in a more traditional manner using raw 181 changes for bone density (Table 4). These analyses resulted in higher colinearity compared to 8 182 the residualized analyses (shared variance between independent variables as high as 43.2% 183 versus 29.9% in the residualized analyses); therefore Table 4 may overestimate the relationships 184 presented. 185 Results 186 Study Sample. 187 Table 1 shows the baseline and 4 year values for the regional BMD sites and mean values 188 for HT use, EX, and CA for the full sample (n = 167) and when split by HT use. Subjects 189 consumed an average of 1635 ± 367.1 mg/day of CA and attended an average of 35.7 ± 28.7% of 190 the prescribed exercise sessions over four years. As expected, the four-year HT use was 191 significantly different between HT groups (3.58 ± 0.85 years for the HT group vs 0.006 ± 0.04 192 years for the NoHT group). The HT group was 2.4 years younger and had significantly higher 193 four year TR and LS BMD. 194 BMD Associations Between Regional Sites. 195 Table 2 shows the correlations between regional BMD sites based on four separate years 196 of data. Correlations between sites showed the highest associations occurring between the FN 197 and TR (0.778 – 0.831, p < 0.05) and the lowest occurring between the TR and LS (0.571 – 198 0.630, p < 0.05). When correlations were performed for the groups split by HT use, the 199 associations among sites for the noHT group were consistently lower than the HT group (p < 200 0.05). 201 Model 1: Predicting Long-Term BMD Changes From Exercise Frequency, Calcium Supplement 202 Intake, and Age. 203 204 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) 9 205 for the FN, TR, and LS, respectively. In this group, CA was a significant predictor at the FN and 206 TR while age was significant at the FN and LS. EX was significant only at the LS (Table 3). 207 For women who used HT, much less variation in " BMD was explained by EX, CA, and 208 age, equaling 4.2% (p = 0.192), 9.7% (p = 0.010), and 8.0% (p = 0.026) at the FN, TR, and LS, 209 respectively. EX significantly predicted "BMD at all regional sites for the HT group. CA and 210 age were not significant at any site in this group (Table 3). 211 Model 2: Predicting Long-Term BMD Changes From Baseline Weight and Changes in Body 212 Weight (after accounting for age, CA and EX).. 213 The amount of variation in "BMD for the FN, TR, and LS that was explained by BLWT 214 plus "WT was 14.8% (p = 0.000), 13.9% (p = 0.000), and 7.7% (p = 0.009), respectively, for the 215 HT groups and 1% (p = 0.756), 17.1% (p = 0.006), and 3.2% (p = 0.295), respectively, for the 216 noHT group. For HT users, BLWT and "WT were both significant (p < 0.05) positive predictors 217 for the FN and TR but not LS (Table 3). For women not using HT, BLWT and "WT were not 218 significant predictors of " BMD, although they approached significance (p < 0.10) at the TR. 219 Model 3: Predicting Long-Term BMD Changes From Baseline Soft Tissue Composition and 220 Changes in Soft Tissue Composition (after accounting for age, CA and EX). 221 The amount of variation in "BMD for the FN, TR, and LS that was explained by 222 BLFAT, BLLEAN, "FAT and "LEAN was 17.8% (p = 0.000), 17.6% (p = 0.000), and 10.1% (p 223 = 0.013), respectively, for the HT groups and 6.7% (p = 0.438), 31.2% (p = 0.000), and 5.8% (p 224 = 0.356), respectively, for the noHT group. The "LEAN and "FAT were significant positive 225 predictors of FN (p < 0.05), TR (p < 0.05) and LS (p < 0.10) "BMD for the HT group. BLFAT 226 was a significant positive predictor (p < 0.05) of FN and TR "BMD but not LS. BLLEAN was 227 not a significant predictor of "BMD at any regional site for the HT group. For those using HT, 10 228 the "LEAN and "FAT were significant positive predictors of TR "BMD. BLFAT and 229 BLLEAN were not significant except BLLEAN at the TR (p < 0.10) (Table 3). 230 Discussion 231 The findings of the present study support the notion that exercise and calcium intake, 232 along with the body’s hormonal milieu, are significant factors in predicting bone changes; 233 however, our results also suggest that changes in fat and lean mass play a more important role in 234 the regulation of bone density than current public health messages suggest. Changes in fat and 235 lean mass explained an additional 6 to 32% of the variation in BMD changes in addition to that 236 accounted for by EX, CA, and age. We have previously shown that EX and CA significantly 237 predicts BMD changes [20]. 238 The role of soft tissue composition also seems to be site-specific exerting a larger impact 239 at the femoral neck and greater trochanter. This effect is more pronounced in those taking HT 240 despite accounting for overall less variation in BMD changes in this group. Correlations 241 between spine and hip are lower than between the two hip sites, where less than 40% of the 242 variance in hip BMD can be accounted for by spine BMD changes. The standardized regression 243 coefficients show that soft tissue composition changes are more closely related to trochanter 244 BMD than to spine and femur neck changes. Whether the differences between exercise studies in 245 BMD regional outcomes can be explained, in part, by differences in the changes in soft tissue 246 composition is not yet known. 247 Despite exposure to similar systemic conditions, bone sites respond independently even 248 after accounting for the effects of exercise and calcium. Two areas of the hip, the FN and TR 249 sites, also responded differently, particularly for those not taking HT. The TR was sensitive to 250 changes in weight and soft tissue composition while the FN was not; both hip sites were 11 251 significant predictors in the HT group. This finding is supported by Stewart (2005) who found 252 that, in a randomized exercise training study of 53 postmenopausal women (47% of whom took 253 HT), six month changes in weight, BMI, and peak oxygen uptake were correlated with changes 254 in FN but not TR (using bivariate analyses) [24]. 255 The significant effect of exercise also persists with the addition of soft tissue 256 composition variables to the predictive models for the HT group, suggesting that the forces 257 generated on bone during exercise have an effect that is independent of the effect of changes in 258 lean and fat mass. In the only case where EX significantly predicted BMD changes (at the LS) 259 for the NoHT group, it became nonsignificant when the soft tissue composition variables were 260 added. Thus, it appears the exercise effects in the NoHT group at the spine were mediated by 261 changes in soft tissue composition. This was not the case in the HT group. 262 For women not taking HT, the effect of CA (at all BMD sites) and age (at the FN only) 263 became nonsignificant when soft tissue composition variables were added to the models 264 suggesting that these variables account for the same variation in BMD changes at these sites. At 265 the LS, age remained a significant predictor of BMD changes when soft tissue composition 266 variables were added. When age was removed from the analysis, the soft tissue composition 267 variables were still significant (results not shown), indicating that age and soft tissue composition 268 changes are independent of each other in relation to spine BMD changes. 269 We conclude that soft tissue composition, both baseline and subsequent changes, are 270 important in the regulation of BMD changes, especially for those taking HT. We recommend 271 including the measurement of fat and lean mass when testing the effect of any new, potentially 272 osteogenic, therapies. It is also important to examine the effects of the baseline fat and lean 273 masses because this can affect the amount of BMD change in some populations. Also, it is 12 274 important to study femur neck and trochanter sites separately as well as total hip when 275 examining the long term effect of exercise because of the differential response of the hip sites to 276 a given exercise protocol. 277 278 Acknowledgements: Supported by the National Institute for Arthritis, and Musculoskeletal and 279 Skin Diseases, National Institutes of Health (AR39559 & AR047932) and by Mission Pharmacal 280 (San Antonio, TX). Conflict of interest: No Disclosures. Address correspondence to: Laura A. 281 Milliken, PhD., Department of Exercise and Health Sciences, University of Massachusetts 282 Boston, 100 Morrissey Blvd., Boston, MA 02125 Email: laurie.milliken@umb.edu 13 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) 14 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) 15 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 16 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 References 1. 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