Endocrine DOI 10.1007/s12020-013-0160-3
ORIGINAL ARTICLE
Relationship of lean body mass with bone mass and bone mineral density in the general Korean population Seong-Su Moon
Received: 16 September 2013 / Accepted: 28 December 2013 Ó Springer Science+Business Media New York 2014
Abstract We investigated association of lean body mass with bone mass (BM) and bone mineral density (BMD) according to gender and menopausal status in the general Korean population. Participants included 4,299 males and 5,226 females who were 20 years of age or older from the fourth and fifth Korea National Health and Nutritional Examination Surveys (2009–2010). Dual-energy X-ray absorptiometry was used for measurement of BMD and body composition. BMD was measured in the femur and lumbar spine. Appendicular skeletal muscle mass (ASM) was defined as the sum of the lean soft tissue masses for the arms and legs. Analysis was performed after categorizing participants into four groups (males \50 years, males C50 years, premenopausal females, and postmenopausal females). In males, the highest ASM was observed in the 20–29-year group and then showed a gradual decrease as age increased, and BM and BMD showed similar patterns of change, while in females, ASM, BMD, and BM reached the peak level in the 40–49-year group and then decreased. In multiple regression analysis, after adjusting for confounding factors, the results showed an independent association of ASM with an increase in BM and BMD (P \ 0.05). After adjusting for confounding factors, total Electronic supplementary material The online version of this article (doi:10.1007/s12020-013-0160-3) contains supplementary material, which is available to authorized users. S.-S. Moon (&) Department of Internal Medicine, Dongguk University College of Medicine, Dongdae-ro 87, Gyeongju, Gyeongbuk Province 780-350, South Korea e-mail: [email protected] S.-S. Moon Medical Institute of Dongguk University, Gyeongju, South Korea
fat mass showed a significant association with BM (P \ 0.05). These aforementioned relationships were commonly observed on both femur and lumbar spine in every group. Lean body mass showed an independent association with increased BM and BMD, regardless of gender, age in men, and menopausal status in women. Keywords Lean body mass Bone mass Bone mineral density Korean General population
Introduction Osteoporosis, a skeletal bone disease characterized by reduced bone mass (BM) and quality with a consequent increased risk of fracture [1], is considered a major health concern in old age [2]. Similarly, sarcopenia is defined as the loss of muscle mass that commonly accompanies aging [3, 4]. Sarcopenia and osteoporosis commonly predispose individuals to frailty, falls, fractures, and disability, eventually leading to increased morbidity and mortality, and public health burden [5–8]. They are currently regarded as having common risk factors, including genetics, hormonal change, aging, physical activity, and nutrition [8–12]. In addition, several hypotheses have been suggested to explain the relationship of muscle and bone strength [12– 15]. Physiologically, muscle contractions induce tension in the bone, which in turn activates bone remodeling through osteocyte mechanoreceptors [13], and bioactive molecules produced from muscle can contribute to homeostatic regulation of bone [16]. Several studies have examined the association of lean body mass or sarcopenia with reduced BM. However, the results have been inconsistent on specific issues regarding differences of their relationships according to gender, age,
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and menopausal status. In postmenopausal women, lean mass was found to show positive correlation with whole body or regional areal bone mineral density (BMD) [17– 20], and, in European men aged 40–79 years, sarcopenia showed an association with low BMD [21]. However, some studies found no relationship between lean body mass and BMD after adjusting for body mass index (BMI) [11]. In a study examining the relationship between muscle mass and BMD among elderly people older than 60 years of age, a significant relation was observed only among males [22]. In addition, the effect of fat mass on bone density has been different between genders. Fat mass was found to have a stronger effect on BMD in women than in men [23, 24]. After menopause, fat mass, rather than lean mass, was found to be a more important factor for BMD [25–27]. Because loss of lean body mass and osteoporosis have so far been regarded as geriatric, aging, or postmenopausal diseases, they have been studied mainly among elderly people or postmenopausal women. To the best of our knowledge, few studies investigating the association between lean body mass and BM in the population, which is representative of the entire population, including young males and premenopausal females, have been reported. In order to elucidate the relationship of lean body mass with BM and BMD, in addition to the effect of fat mass on BM, according to gender, menopausal status in women, and age group in men, we investigated these relationships on femur and lumbar spine, in the general Korean population based on the Korea National Health and Nutrition Examination Survey conducted in 2009 and 2010.
Subjects and methods Study population This study was based on data acquired from the third year (2009) of the Korea National Health and Nutrition Examination Survey (KNHANES) IV (2007–2009) and the first year (2010) of KNHANES V (2010–2012). These surveys have been conducted periodically since 1998 by the Korean Ministry of Health and Welfare, using a rolling sampling design involving a complex, stratified, multistage, probability-cluster survey of a representative sample of the noninstitutionalized civilian population in order to assess the health and nutritional status of the Korean population [28, 29]. The survey consists of the health interview survey, the health examination survey, and the nutrition survey. The sampling frame was based on the 2005 national population and housing census for the 2009 survey, and on the registered market value of apartment building complexes or a registered database of the Korean government system that includes all registered citizens for the 2010 survey. Primary
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sampling units were stratified according to region, gender, population proportion by age, and average size and price of home. In the 2009 survey, there were 264,186 primary sampling units, each of which contained *60 households. Two hundred sampling frames from primary sampling units were randomly sampled, and 23 households from each sampling frame (*60 households) were sampled using a systemic sampling method. Finally, 12,722 individuals in 4,000 households were sampled, and 10,078 (79.2 % of the total target population of 12,722) of them participated in health interviews and health examination surveys. In the 2010 survey, there were 201,677 primary sampling units, each of which contained *60 households. A total of 192 sampling frames from primary sampling units were randomly sampled, and 20 households from each sampling frame (*60 households) were sampled using a systemic sampling method. Finally, 10,938 individuals in 3,840 households were sampled, and 8,473 (77.5 % of the total target population of 10.938) of these participants completed health interviews and health examination surveys. Full details of the study design, recruitment, and procedures are available from the Ministry of Health and Social Welfare and Korea Centers for Disease Control and Prevention [30]. From a total of 18,551 participants in the 2010 KNHANES, 3,588 with missing values of BMD or body composition were excluded: Exclusion criteria for DXA included pregnancy, being incapable of lying in a supine position, having received an injection of radiocontrast material or radioisotope within the previous 7 and 3 days, respectively, and unwillingness to undergo a DXA scan. Among the remaining subjects, 4,786 subjects younger than 19 years, 505 subjects who underwent osteoporosis treatment or hormone replacement, and 147 subjects with diagnosed cancer were also excluded. Therefore, a total of 9,525 participants were enrolled in the analysis (Supplemental figure 1). Information on age, smoking history, alcohol consumption, menopausal status, and physical activity was collected during the health interview. Postmenopausal females were defined as women who had not had their last menstruation for at least 1 year. Measurements of height and weight were performed with the participants wearing light clothing and no shoes. BMI was calculated as weight in kilograms divided by the square of the height in meters. Waist circumference (WC) was measured at the mid-point between the lower margin of the last palpable rib and the top of the iliac crest at the end of a normal expiration with the arms relaxed at the sides. All participants in this survey signed an informed consent form. Determination of ASM and BMD, and BM DXA (Discovery-W; Hologic, Waltham, MA, USA) was used by licensed and trained examiners for measurement of
Endocrine
body composition, including fat mass and appendicular skeletal muscle mass (ASM), BMD, and BM on the femur and lumbar spine. The system logics for BMD judgment were based on 2007 ISCD (International Society for Clinical Densitometry) Official Positions and guidelines for BMD test with quality control. Precision errors with % coefficient of variation were within acceptable ranges (lumbar 1.9 %, femoral head 2.5 %, and total femur 1.8 %) for each examiner. ASM was defined as the sum of the lean soft tissue masses for the arms and legs, after the method of Heymsfield et al. [31]. Skeletal muscle mass index (SMI) (%) was defined [32, 33] as ASM (kg) divided body weight (kg) x 100, which was modified from the study reported by Janssen et al. [34]. Statistical analyses Participants were categorized into four groups according to gender, age, or menopausal status (2,356 males \50 years, 1,943 males C50 years, 3,078 premenopausal females, and 2,148 postmenopausal females). Nominal variables are presented as the number of cases with the percentage and continuous variables as the mean ± standard deviation (SD). Student’s t test was performed in order to evaluate the significance of the mean differences between the two groups. Chi square analysis was performed for comparison of categorical variables of the groups. Multivariate regression analysis was performed for calculation of ageadjusted odd ratios (ORs) of body composition, anthropometric and demographic variables. Multivariate regression analyses were also performed for investigation of the association between ASM and BM or BMD, with ASM serving as the independent variable and BM or BMD serving as the dependent variable. These analyses were adjusted for age and BMI, which were statistically significant variables in univariate regression analyses, and wellknown important conventional factors for decreased BMD (Model 1). Additional adjustment for smoking status and alcohol consumption status, which are also known conventional risk factors for decreased BMD, was made in Model 2. In addition to Model 2, Model 3 was adjusted for total fat mass, which was also a significant variable in univariate analysis and of particular interest in this study. Multivariate regression analyses were also performed in order to investigate the association of SMI or total fat mass with BMD or BM, after adjusting for age, BMI, smoking status, alcohol consumption, SMI, and total fat mass. Among the 16 administrative districts where this survey was conducted, Seoul, Gyeonggi, and six other metropolitan cities (Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) were grouped as urban areas. The remaining regions were grouped as rural areas. Smoking status was divided into three categories: never, former, and current smoker.
Alcohol consumption was indicated as ‘yes’ for participants whose average weekly consumptions are more than 70 g in males and 50 g in females. Regular exercise was indicated as ‘yes’ when the participant performed moderate or strenuous exercise on a regular basis, regardless of indoor or outdoor exercise (for more than 30 min at a time and more than five times per week in the case of moderate exercise, such as swimming slowly, tennis doubles, volleyball, badminton, table tennis, and carrying light objects; for more than 20 min at a time in the case of strenuous exercise, such as running, climbing, cycling fast, swimming fast, football, basketball, jump rope, squash, tennis singles, and carrying heavy objects or when subject walked for more than 30 min at a time and more than five times per week). All tests were two-sided, and P \ 0.05 was considered statistically significant. Statistical Package for Social Science 15.0 software (SPSS, Chicago, IL, USA) was used in performance of all analyses.
Results Changes of ASM, SMI, BMD, and BM according to decade by gender In males, the highest ASM and SMI was observed in the 20–29-year group (23.79 ± 3.21 kg and 33.00 ± 2.89 %, respectively), among decade groups, and then showed a gradual decrease as age increased. In addition, the highest total femoral and lumbar BMD and total femoral BM were also observed in the 20–29-year group (1.02 ± 0.12 g/cm2, 1.00 ± 0.12 g/cm2, and 42.27 ± 7.68 g, respectively), while lumbar BM showed a peak value in the 30–39-year group (69.43 ± 10.90 g). In females, ASM, total femoral and lumbar BMD, and total femoral and lumbar BM reached the peak level in the 40–49-year group (14.62 ± 2.22 kg, 0.91 ± 0.11 g/cm2, 0.99 ± 0.13 g/cm2, 29.25 ± 4.51 g, 60.07 ± 9.77 g, respectively), and then decreased, while SMI showed a peak value in the 20–29-year group (25.89 ± 2.43 %) (Fig. 1 and Supplemental figure 2). Basal characteristics of participants The characteristics of participants in each group are shown in Table 1. Mean age of each group (males \50 years, males C50 years, premenopausal females, and postmenopausal females) was 36.4 ± 7.6, 62.6 ± 8.6, 36.2 ± 8.3, and 62.6 ± 9.8 years, respectively. Mean of BMD for every site was higher in males\50 years and premenopausal females, compared with that in males C50 years and postmenopausal females, respectively (P \ 0.001). ASM and SMI were higher in males \50 years and premenopausal females, compared with males C50 years and postmenopausal
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Endocrine Fig. 1 The means of ASM (a) and SMI (b) in women and men according to decade
females, respectively (23.2 ± 3.2 vs. 20.6 ± 2.9, 14.5 ± 2.3 vs. 13.7 ± 2.0, 32.1 ± 2.8 vs. 31.2 ± 2.7, 25.4 ± 2.3 vs. 24.3 ± 2.6, respectively, P \ 0.001). Association of BM and BMD with body composition and demographic variables in males BMI, WC, ASM, and total fat mass showed a positive association with BM and BMD on the femur and lumbar spine in both males \50 and C50 years. Fat % also showed an association with increased BMD and total femoral BM only in males C50 years. SMI did not show a significant relationship with BMD or BM, while SMI showed an association with increased BMD and lumbar spine BM in males C50 years. In males \50 years, region, smoking, and regular exercise were not significant variables for BMD or BM. In males C50 years, smokers had lower BMD on total femoral and lumbar spine and lower total femoral BM than non-smokers (Table 2). Association of BM and BMD with body composition and demographic variables in females BMI, WC, ASM, and total fat mass showed a positive association with BMD on every site in both pre- and postmenopausal females. Fat % showed an association with increased BM and BMD on every site in premenopausal females and it also showed a positive association with BMD and lumbar spine BM in postmenopausal females. In premenopausal females, participants living in urban areas showed a decreased BMD and total femoral BM, compared with those living in rural areas, while postmenopausal women did not show such a relationship. Of particular interest, only in premenopausal females, alcohol consumption showed an association with increased BM and BMD, and participants who exercised regularly showed increased BMD and lumbar spine BM. Postmenopausal females showed no such relationship (Table 3).
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Adjusted effect of ASM and total fat mass on BM and BMD In multiple regression analysis for BM and BMD with ASM as an independent variable, after adjusting for potential confounding variables in Models 1, 2, and 3, the results showed a positive association of ASM with BM and BMD on total femur and lumbar spine in every group (males \50 years, males C50 years, premenopausal females, and postmenopausal females) (Table 4). In multivariate analysis, total fat mass showed a positive association with BM in every group (Supplemental table 1). Percentages of reduced muscle mass in elderly population We calculated cutoff points of reduced muscle mass in comparison with young population. Reduced muscle mass was defined as ASM divided by body weight (ASM/Wt) (%) more than two SDs below mean value of sex-specific normal young people. The sex-specific young reference group included 3,343 healthy adults aged 20–40 year (1,449 men, 1,894 women). As cutoff points, the two SDs of sex-specific normal young people were 26.98 % in men and 21.14 % in women, respectively. Percentages of reduced muscle mass in male elderly population were 5.5, 10.9 and 17.6 % (in 60–69, 70–79, and C80-year age group, respectively) and those in female elderly population were 8.3, 11.3, and 11.7 % (in 60–69, 70–79, and C80-year age group, respectively).
Discussion Results of this study demonstrated a positive association of ASM with BM and BMD on the femur and lumbar spine in the general Korean population, regardless of gender, age in males, and menopausal status in females, after adjusting for confounding factors, including age, BMI, smoking status, alcohol consumption, and total fat mass. Absolute skeletal muscle mass, ASM, was a more significant factor for BM
Endocrine Table 1 Baseline characteristics of participants Male \50 years
Female C50 years
P
Premenopausal
Postmenopausal
3,078
2,148
P
No. of total participants
2,356
1,943
Age (years)
36.1 ± 7.9
62.9 ± 8.8
\0.001
36.6 ± 8.5
63.1 ± 9.9
\0.001
Height (cm)
172.4 ± 5.9
166.8 ± 5.9
\0.001
159.6 ± 5.7
153.2 ± 6.1
\0.001
Weight (kg)
72.1 ± 10.9
66.1 ± 9.6
\0.001
57.6 ± 9.3
57.0 ± 8.6
0.010
BMI (kg/cm2)
24.2 ± 3.3
23.7 ± 2.9
\0.001
22.6 ± 3.5
24.3 ± 3.3
\0.001
WC (cm)
83.5 ± 9.0
85.0 ± 8.5
\0.001
75.0 ± 9.3
82.2 ± 9.3
\0.001
ASM (kg) SMI (%)
23.2 ± 3.2 32.1 ± 2.8
20.6 ± 2.9 31.2 ± 2.7
\0.001 \0.001
14.5 ± 2.3 25.4 ± 2.3
13.7 ± 2.0 24.3 ± 2.6
\0.001 \0.001
Total fat mass (kg)
16.1 ± 5.9
14.6 ± 4.7
\0.001
18.3 ± 5.3
19.5 ± 5.4
\0.001
Fat %
23.7 ± 6.0
23.7 ± 5.4
0.724
34.4 ± 5.4
36.9 ± 5.7
\0.001
Total femoral BMD (g/cm2)
0.99 ± 0.12
0.92 ± 0.12
\0.001
0.89 ± 0.10
0.77 ± 0.12
\0.001
Lumbar spine BMD (g/cm2)
0.98 ± 0.12
0.95 ± 0.15
\0.001
0.98 ± 0.12
0.80 ± 0.14
\0.001
Total femoral BM (g)
41.0 ± 6.7
38.6 ± 6.5
\0.001
28.7 ± 4.5
25.5 ± 4.5
\0.001
Lumbar spine BM (g)
69.3 ± 11.0
66.4 ± 13.6
\0.001
59.4 ± 9.6
46.4 ± 10.1
\0.001
614 (19.9)
578 (26.9)
2,464 (80.1)
1,570 (73.1)
2,625 (85.3)
1,961 (91.3)
Regionsa
\0.001
Rural area
493 (20.9)
524 (27.0)
Urban area
1,863 (79.1)
1,419 (73.0)
Smoking statusb
\0.001
\0.001
\0.001
Never
499 (21.2)
329 (16.9)
Former
315 (13.4)
527 (27.1)
126 (4.1)
31 (1.4)
Current
1,542 (65.4)
1,087 (55.9)
327 (10.6)
156 (7.3)
948 (40.2)
59.5 (30.6)
360 (11.7)
88 (4.1)
1,408 (59.8)
1,348 (69.4)
2,718 (88.3)
2,060 (95.9)
Yes
1,272 (54.0)
1,137 (58.5)
1,517 (49.3)
1,122 (52.2)
No
1,084 (46.0)
806 (41.5)
1,561 (50.7)
1,026 (47.8)
Alcohol consumptionc Yes No Regular exercise
\0.001
d
\0.001
0.003
0.036
Values are presented as number (%) or mean (SD) BMI body mass index, WC waist circumference, ASM appendicular skeletal muscle mass, SMI ASM/body weight, BMD bone mineral density, BM; bone mass a
Region was categorized as urban (Seoul, Gyeonggi, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) and rural (eight other administrative districts) area
b
Smoking status was divided into three categories: never, former, and current smoker
c
Alcohol consumption was indicated as ‘yes’ for participants whose average weekly consumptions are more than 70 g in males and 50 g in females
d
Regular exercise was indicated as ‘yes’ when the participant performed moderate or strenuous exercise on a regular basis (for more than 30 min at a time and more than five times per week in the case of moderate exercise; for more than 20 min at a time in the case of strenuous exercise) or when the subject walked for more than 30 min at a time and more than five times per week
and BMD, rather than skeletal muscle mass adjusted for body weight, SMI, although SMI also tended to show an association with increased BMD. Total fat mass was also an independent factor for increased BM and BMD in both genders. In men, skeletal muscle, mass as well as BM, reached a peak level in the 20–29-year group, and then showed a gradual decrease together. In females, age to reach the highest level of ASM and BM was later, compared with
males. A peak level was observed in the 40–49-year group in females. After menopause, they showed an abrupt decrease. When we evaluated the prevalence of decreased lean body mass, the prevalence of subjects with SMI more than two SDs below mean value of sex-specific young normal people was 1.6, 5.2, 2.3, and 9.0 % in males \50 years, males C50 years, premenopausal females, and postmenopausal females, respectively. In the literature, the reported prevalence of sarcopenia varies widely due to
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Endocrine Table 2 Association of anthropometric, body composition, and demographic variables with BM and BMD in males Dependent variable Total femoral BM
Lumbar spine BM
Total femoral BMD
Lumbar spine BMD
\50 years BMI (kg/cm2)
0.586à
0.590à
0.012à
0.008à
WC (cm)
0.209à
0.236à
0.003à
0.003à
1.157
à
à
1.422
à
0.014
0.012à
SMI (%)
0.251
à
0.156
0.000
0.000
Total fat mass (kg)
0.176à
0.237à
0.003à
0.003à
ASM (kg)
Fat % Urban regiona
-0.039 -0.075
-0.046 -0.043
0.001 0.000
0.001 -0.011
Current smokerb
0.160
-0.243
0.003
0.001
Alcohol consumptionc
0.998
Regular exercised
0.699
0.999 -0.397
0.016
0.010
0.012
0.003
C50 years BMI (kg/cm2)
0.831à
1.445à
0.004à
0.018à
WC (cm)
0.254à
0.468à
0.002à
0.005à
à
à
à
0.019à
-0.008à
à
0.008à
à
0.004à
ASM (kg)
1.278
SMI (%) Fat % Urban regiona Current smoker
-0.793
0.352
à
0.081
-0.411 b
Alcohol consumption Regular exercised
-0.004
à
0.311
0.006
à
-0.434
0.002
0.051
-0.014
-0.004
-1.159
-0.016
-0.015
0.600
0.378
-0.001
0.001
0.691
1.177
-0.728 c
0.017
à
-0.085
Total fat mass (kg)
2.007
0.019
0.012
Results are expressed as b coefficients Adjusted for age a
Region was categorized as urban (Seoul, Gyeonggi, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) and rural (eight other administrative districts) area
b
Smoking status was divided into three categories: never, former, and current smoker
c
Alcohol consumption was indicated as ‘yes’ for participants whose average weekly consumptions are more than 70 g in males and 50 g in females
d
Regular exercise was indicated as ‘yes’ when the participant performed moderate or strenuous exercise on a regular basis (for more than 30 min at a time and more than five times per week in the case of moderate exercise; for more than 20 min at a time in the case of strenuous exercise) or when the subject walked for more than 30 min at a time and more than five times per week
P \ 0.05;
à
P \ 0.001
differences in the study population, according to the definition of sarcopenia, technique used for measurement, and the reference group. In Germans aged 60 years and older, the prevalence was 0 % [35], while the prevalence was 57 % in elderly Hispanic US Caucasian men [36]. Regarding postmenopausal women, prevalence ranging from 10 to 40 % has been reported [37]. We adopted ASM divided by body weight (%) as SMI to access the muscle mass adjusted for body mass. SMI was used because it adjusts for stature and the mass of non-skeletal muscle tissues, including fat, organ, and bone. So far, SMI used in this manuscript has been widely adopted in many studies to define sarcopenia [32, 33, 38, 39] as well as relative skeletal muscle index (RSMI), ASM/height2 (kg/m2). Because
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RSMI is highly correlated with BMI, the index primarily identified low BMI as sarcopenic could underestimate sarcopenia in overweight or obese subjects [40]. Moreover, Lim et al. [32] suggested that SMI is the more appropriate index for sarcopenic obesity in the Korean population, because RSMI was positively correlated with BMI, visceral fat area, and the homeostatic model assessment of insulin resistance (HOMA-IR). Therefore, SMI rather than RSMI is considered to be more appropriate particularly in this study population. In men, regardless of age group (\50, C50 years), ASM showed a positive association with BM and BMD on femur and lumbar spine, which is consistent with results reported in previous studies [10, 21, 41]. Of particular interest, in
Endocrine Table 3 Association of anthropometric, body composition, and demographic variables of BM and BMD in females Dependent variable Total femoral BM
Lumbar spine BM
Total femoral BMD
Lumbar spine BMD
Premenopausal BMI (kg/cm2)
0.525à
0.674à
0.014à
0.012à
WC (cm)
0.206à
0.308à
0.005à
0.005à
1.163
à
à
à
0.018à
0.107
-0.005à
0.298
à
à
0.007à
à
0.003 -0.018
0.003à -0.019
ASM (kg) SMI (%) Total fat mass (kg)
Fat % Urban regiona
0.052 -0.528
1.725
0.020
-0.156
-0.003
à
0.484
0.007
0.101 -0.934
Current smokerb
0.010
0.629
0.003
0.004
Alcohol consumptionc
0.663
1.199
0.012
0.011
Regular exercised
0.342
1.137
0.012
0.018
BMI (kg/cm2)
0.356à
0.592à
0.009à
0.011à
WC (cm)
0.133
0.234à
0.003à
0.004à
à
à
à
0.016à
-0.009à
à
0.007à
à
0.004à
Postmenopausal
ASM (kg)
1.067
SMI (%) Fat % Urban regiona Current smoker
b
0.191
0.017
à
0.045
Total fat mass (kg)
1.555 -0.423
à
-0.004
à
0.435
0.005
0.013
0.124
0.002
-0.089
0.447
-0.007
0.001
-0.283
0.815
-0.014
0.002
Alcohol consumptionc
0.388
2.138
0.009
0.025
Regular exercised
0.066
-0.466
0.006
0.002
Results are expressed as b coefficients Adjusted for age a
Region was categorized as urban (Seoul, Gyeonggi, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) and rural (eight other administrative districts) area
b
Smoking status was divided into three categories: never, former, and current smoker
c
Alcohol consumption was indicated as ‘yes’ for participants whose average weekly consumptions are more than 70 g in males and 50 g in females
d
Regular exercise was indicated as ‘yes’ when the participant performed moderate or strenuous exercise on a regular basis (for more than 30 min at a time and more than five times per week in the case of moderate exercise; for more than 20 min at a time in the case of strenuous exercise) or when the subject walked for more than 30 min at a time and more than five times per week
P \ 0.05;
à
P \ 0.001
the current study, absolute muscle mass was a more important factor for BM and BMD, rather than muscle mass ratio of body mass. Fat mass had a positive effect on BM and BMD, while fat % also tended to show an association with increased BM only in males C50 years. In contrast, in females, fat %, as well as total fat mass, showed a positive association with BM and BMD in both pre- and postmenopausal women. This result is consistent with those of previous studies showing that fat mass had a stronger effect on BMD in women than in men [23, 24]. However, except inferring the sex hormonal effect, we could not provide a precise explanation for the discrepancy between genders in this study. In this study, fat % of body weight, as well as absolute amount of lean body mass, were
independent determinants for increased BM. This result was quite interesting because we expected that, after adjusting for body size or body weight bearing effect on bone, fat mass might show a negative association with BM and BMD, possibly via inflammatory effects leading to increased bone absorption [42]. In fact, according to results of previous studies, fat mass and BMD showed either a positive [17, 43] or a negative [44] correlation. In women, regardless of menopausal status, after adjusting for confounding factors, including age, BMI, smoking status, alcohol consumption, and total fat mass, ASM showed a positive association with BM and BMD, which is consistent with results of previous studies showing positive correlation of lean mass with whole body or
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Endocrine Table 4 Multiple regression analysis for BM and BMD with ASM as an independent variable Male
Female
\50 years
C50 years
Premenopausal
Postmenopausal
Total femoral BMD (g/cm2)
0.011 (0.008–0.013)à
0.010 (0.007–0.014)à
0.011 (0.008–0.014)à
0.011 (0.008–0.015)à
Lumbar spine BMD (g/cm2)
0.010 (0.008–0.013)à
0.012 (0.017–0.016)à
0.012 (0.008–0.015)à
0.008 (0.003–0.013)
1.316 (1.182–1.450)
à
à
1.180 (1.072–1.288)
à
1.042 (0.903–1.180)à
1.772 (1.535–2.009)
à
1.721 (1.356–2.085)
1.932 (1.671–2.192)
à
1.424 (1.090–1.759)à
Model 1
Total femoral BM (g) Lumbar spine BM (g)
1.183 (1.028–1.339)
à
Model 2 Total femoral BMD (g/cm2) Lumbar spine BMD (g/cm2)
0.014 (0.012–0.016)à 0.013 (0.011–0.015)à
0.011 (0.009–0.013)à 0.010 (0.007–0.013)à
0.012 (0.010–0.014)à 0.011 (0.008–0.013)à
0.011 (0.009–0.013)à 0.009 (0.006–0.012)à
Total femoral BM (g)
1.421 (1.324–1.518)à
1.231 (1.116–1.345)à
1.144 (1.063–1.224)à
1.127 (1.025–1.228)à
Lumbar spine BM (g)
à
à
1.721 (1.435–2.007)
1.868 (1.684–2.053)
à
1.473 (1.219–1.727)à
0.010 (0.008–0.012)à
0.010 (0.007–0.012)à
0.009 (0.007–0.011)à
0.011 (0.009–0.014)à
à
à
0.010 (0.007–0.014)
0.011 (0.009–0.013)
à
0.010 (0.007–0.013)à
1.943 (1.769–2.116)
Model 3 Total femoral BMD (g/cm2) 2
Lumbar spine BMD (g/cm )
0.012 (0.010–0.014)
Total femoral BM (g)
1.399 (1.295–1.502)à
1.259 (1.139–1.379)à
1.177 (1.095–1.259)à
1.152 (1.049–1.255)à
Lumbar spine BM (g)
à
à
à
1.669 (1.416–1.921)à
2.143 (1.960–2.326)
2.030 (1.736–2.325)
2.051 (1.865–2.236)
Results are expressed as b coefficients and 95 % CI Model 1: adjusted for age and BMI Model 2: adjusted for age, BMI, smoking status, and alcohol consumption Model 3: adjusted for age, BMI, smoking status, alcohol consumption, and total fat mass P \ 0.05; à P \ 0.001
regional areal BMD in postmenopausal women [17–20, 45, 46]. The effect of fat mass on BM according to menopausal status has been controversial so far. Fat mass, rather than lean mass, was suggested as a more important factor for BMD after menopause [25, 26]. In the current study, ASM and total fat mass were independent factors for increased BMD in both pre-and postmenopausal females. So far, several studies have reported a negative association of smoking with total hip BMD in people aged 65-year old and older [17]. Results of the current study also showed a negative relationship of smoking with BMD on the femur and lumbar spine in men aged 50 years and older. However, this association was not observed in younger men and premenopausal women. Postmenopausal women who smoked showed decreased BMD on total femur. We assume that the lower prevalence of smoking among females and smoking duration may affect the difference. The role of physical activity in the association of lean mass with BMD has been inconsistent. Some studies have suggested that the relationship between lean mass and BMD was largely mediated by physical activity [11, 47]. However, in a study conducted in men aged 40 years and older, physical activity did not show an association with BMD on any site [21].The current study showed different results according to groups, reflecting that the effects of
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exercise on bone may not be simple and may be affected by potential confounders. To the best of our knowledge, although some studies examining the relationship of lean body mass with BMD in a small population, including younger men [10] or premenopausal women [47], have been reported, the strength of our study is based on a large population representative of the entire population in order to examine their relationship together. This study has several limitations. First, the cross-sectional study design prevented us from affirming the causal relationship between lean body mass and BMD or BM. Their causal relationship should be verified in future longitudinal studies. Second, although DXA is widely used for determination of lean mass, the evaluation of lean mass by DXA might underestimate the age-associated reduction in muscle mass due to change in total body water that accompanies aging [10]. Third, sarcopenia and osteoporosis are currently considered as having common risk factors, including genetics, hormonal change, and nutrition, However, because we did not measure vitamin D, testosterone, estrogen, insulin growth factor 1, or inflammatory cytokines, like tumor necrosis factor a and interleukin-1, we could not provide any mechanistic explanation for their relationship. Finally, the skeletal muscle index (%) [ASM (kg) divided body weight (kg) x 100] used in this
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manuscript has been widely adopted in many studies to define sarcopenia; however, it was recently suggested that the definition of sarcopenia be restricted to the presence of low muscle strength or poor physical performance in addition to reduced muscle [48]; therefore, because we did not measure muscle strength for determination of sarcopenia, we could not provide an exact definition of sarcopenia. Instead, we examined the relationship of lean body mass with bone mass and bone density. This might have been a limitation in this study. Despite these limitations, because the population of the current study was representative of the general Korean population, this study has powerful strength. In conclusion, results of this study showed an independent association of ASM with BM and BMD in both males and females, regardless of age or menopausal status. Of particular interest, even in pre-and postmenopausal females, lean body mass was found to be an independent correlate of BM and BMD. Therefore, reduced lean body may be an early predictor of osteoporosis in the general population. Further study is required in order to elucidate the causal relationship and pathophysiology. Acknowledgments This research was supported by a grant from the Daegu and Kyungpook local committee of the Korean Diabetes Association and by the Dongguk University research fund. I thank the Ministry of Health and Social Welfare and Korea Centers for Disease Control and Prevention for providing the invaluable data of the survey. Conflict of interest
The authors have nothing to declare.
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ORIGINAL ARTICLE
Relationship of lean body mass with bone mass and bone mineral density in the general Korean population Seong-Su Moon
Received: 16 September 2013 / Accepted: 28 December 2013 Ó Springer Science+Business Media New York 2014
Abstract We investigated association of lean body mass with bone mass (BM) and bone mineral density (BMD) according to gender and menopausal status in the general Korean population. Participants included 4,299 males and 5,226 females who were 20 years of age or older from the fourth and fifth Korea National Health and Nutritional Examination Surveys (2009–2010). Dual-energy X-ray absorptiometry was used for measurement of BMD and body composition. BMD was measured in the femur and lumbar spine. Appendicular skeletal muscle mass (ASM) was defined as the sum of the lean soft tissue masses for the arms and legs. Analysis was performed after categorizing participants into four groups (males \50 years, males C50 years, premenopausal females, and postmenopausal females). In males, the highest ASM was observed in the 20–29-year group and then showed a gradual decrease as age increased, and BM and BMD showed similar patterns of change, while in females, ASM, BMD, and BM reached the peak level in the 40–49-year group and then decreased. In multiple regression analysis, after adjusting for confounding factors, the results showed an independent association of ASM with an increase in BM and BMD (P \ 0.05). After adjusting for confounding factors, total Electronic supplementary material The online version of this article (doi:10.1007/s12020-013-0160-3) contains supplementary material, which is available to authorized users. S.-S. Moon (&) Department of Internal Medicine, Dongguk University College of Medicine, Dongdae-ro 87, Gyeongju, Gyeongbuk Province 780-350, South Korea e-mail: [email protected] S.-S. Moon Medical Institute of Dongguk University, Gyeongju, South Korea
fat mass showed a significant association with BM (P \ 0.05). These aforementioned relationships were commonly observed on both femur and lumbar spine in every group. Lean body mass showed an independent association with increased BM and BMD, regardless of gender, age in men, and menopausal status in women. Keywords Lean body mass Bone mass Bone mineral density Korean General population
Introduction Osteoporosis, a skeletal bone disease characterized by reduced bone mass (BM) and quality with a consequent increased risk of fracture [1], is considered a major health concern in old age [2]. Similarly, sarcopenia is defined as the loss of muscle mass that commonly accompanies aging [3, 4]. Sarcopenia and osteoporosis commonly predispose individuals to frailty, falls, fractures, and disability, eventually leading to increased morbidity and mortality, and public health burden [5–8]. They are currently regarded as having common risk factors, including genetics, hormonal change, aging, physical activity, and nutrition [8–12]. In addition, several hypotheses have been suggested to explain the relationship of muscle and bone strength [12– 15]. Physiologically, muscle contractions induce tension in the bone, which in turn activates bone remodeling through osteocyte mechanoreceptors [13], and bioactive molecules produced from muscle can contribute to homeostatic regulation of bone [16]. Several studies have examined the association of lean body mass or sarcopenia with reduced BM. However, the results have been inconsistent on specific issues regarding differences of their relationships according to gender, age,
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and menopausal status. In postmenopausal women, lean mass was found to show positive correlation with whole body or regional areal bone mineral density (BMD) [17– 20], and, in European men aged 40–79 years, sarcopenia showed an association with low BMD [21]. However, some studies found no relationship between lean body mass and BMD after adjusting for body mass index (BMI) [11]. In a study examining the relationship between muscle mass and BMD among elderly people older than 60 years of age, a significant relation was observed only among males [22]. In addition, the effect of fat mass on bone density has been different between genders. Fat mass was found to have a stronger effect on BMD in women than in men [23, 24]. After menopause, fat mass, rather than lean mass, was found to be a more important factor for BMD [25–27]. Because loss of lean body mass and osteoporosis have so far been regarded as geriatric, aging, or postmenopausal diseases, they have been studied mainly among elderly people or postmenopausal women. To the best of our knowledge, few studies investigating the association between lean body mass and BM in the population, which is representative of the entire population, including young males and premenopausal females, have been reported. In order to elucidate the relationship of lean body mass with BM and BMD, in addition to the effect of fat mass on BM, according to gender, menopausal status in women, and age group in men, we investigated these relationships on femur and lumbar spine, in the general Korean population based on the Korea National Health and Nutrition Examination Survey conducted in 2009 and 2010.
Subjects and methods Study population This study was based on data acquired from the third year (2009) of the Korea National Health and Nutrition Examination Survey (KNHANES) IV (2007–2009) and the first year (2010) of KNHANES V (2010–2012). These surveys have been conducted periodically since 1998 by the Korean Ministry of Health and Welfare, using a rolling sampling design involving a complex, stratified, multistage, probability-cluster survey of a representative sample of the noninstitutionalized civilian population in order to assess the health and nutritional status of the Korean population [28, 29]. The survey consists of the health interview survey, the health examination survey, and the nutrition survey. The sampling frame was based on the 2005 national population and housing census for the 2009 survey, and on the registered market value of apartment building complexes or a registered database of the Korean government system that includes all registered citizens for the 2010 survey. Primary
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sampling units were stratified according to region, gender, population proportion by age, and average size and price of home. In the 2009 survey, there were 264,186 primary sampling units, each of which contained *60 households. Two hundred sampling frames from primary sampling units were randomly sampled, and 23 households from each sampling frame (*60 households) were sampled using a systemic sampling method. Finally, 12,722 individuals in 4,000 households were sampled, and 10,078 (79.2 % of the total target population of 12,722) of them participated in health interviews and health examination surveys. In the 2010 survey, there were 201,677 primary sampling units, each of which contained *60 households. A total of 192 sampling frames from primary sampling units were randomly sampled, and 20 households from each sampling frame (*60 households) were sampled using a systemic sampling method. Finally, 10,938 individuals in 3,840 households were sampled, and 8,473 (77.5 % of the total target population of 10.938) of these participants completed health interviews and health examination surveys. Full details of the study design, recruitment, and procedures are available from the Ministry of Health and Social Welfare and Korea Centers for Disease Control and Prevention [30]. From a total of 18,551 participants in the 2010 KNHANES, 3,588 with missing values of BMD or body composition were excluded: Exclusion criteria for DXA included pregnancy, being incapable of lying in a supine position, having received an injection of radiocontrast material or radioisotope within the previous 7 and 3 days, respectively, and unwillingness to undergo a DXA scan. Among the remaining subjects, 4,786 subjects younger than 19 years, 505 subjects who underwent osteoporosis treatment or hormone replacement, and 147 subjects with diagnosed cancer were also excluded. Therefore, a total of 9,525 participants were enrolled in the analysis (Supplemental figure 1). Information on age, smoking history, alcohol consumption, menopausal status, and physical activity was collected during the health interview. Postmenopausal females were defined as women who had not had their last menstruation for at least 1 year. Measurements of height and weight were performed with the participants wearing light clothing and no shoes. BMI was calculated as weight in kilograms divided by the square of the height in meters. Waist circumference (WC) was measured at the mid-point between the lower margin of the last palpable rib and the top of the iliac crest at the end of a normal expiration with the arms relaxed at the sides. All participants in this survey signed an informed consent form. Determination of ASM and BMD, and BM DXA (Discovery-W; Hologic, Waltham, MA, USA) was used by licensed and trained examiners for measurement of
Endocrine
body composition, including fat mass and appendicular skeletal muscle mass (ASM), BMD, and BM on the femur and lumbar spine. The system logics for BMD judgment were based on 2007 ISCD (International Society for Clinical Densitometry) Official Positions and guidelines for BMD test with quality control. Precision errors with % coefficient of variation were within acceptable ranges (lumbar 1.9 %, femoral head 2.5 %, and total femur 1.8 %) for each examiner. ASM was defined as the sum of the lean soft tissue masses for the arms and legs, after the method of Heymsfield et al. [31]. Skeletal muscle mass index (SMI) (%) was defined [32, 33] as ASM (kg) divided body weight (kg) x 100, which was modified from the study reported by Janssen et al. [34]. Statistical analyses Participants were categorized into four groups according to gender, age, or menopausal status (2,356 males \50 years, 1,943 males C50 years, 3,078 premenopausal females, and 2,148 postmenopausal females). Nominal variables are presented as the number of cases with the percentage and continuous variables as the mean ± standard deviation (SD). Student’s t test was performed in order to evaluate the significance of the mean differences between the two groups. Chi square analysis was performed for comparison of categorical variables of the groups. Multivariate regression analysis was performed for calculation of ageadjusted odd ratios (ORs) of body composition, anthropometric and demographic variables. Multivariate regression analyses were also performed for investigation of the association between ASM and BM or BMD, with ASM serving as the independent variable and BM or BMD serving as the dependent variable. These analyses were adjusted for age and BMI, which were statistically significant variables in univariate regression analyses, and wellknown important conventional factors for decreased BMD (Model 1). Additional adjustment for smoking status and alcohol consumption status, which are also known conventional risk factors for decreased BMD, was made in Model 2. In addition to Model 2, Model 3 was adjusted for total fat mass, which was also a significant variable in univariate analysis and of particular interest in this study. Multivariate regression analyses were also performed in order to investigate the association of SMI or total fat mass with BMD or BM, after adjusting for age, BMI, smoking status, alcohol consumption, SMI, and total fat mass. Among the 16 administrative districts where this survey was conducted, Seoul, Gyeonggi, and six other metropolitan cities (Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) were grouped as urban areas. The remaining regions were grouped as rural areas. Smoking status was divided into three categories: never, former, and current smoker.
Alcohol consumption was indicated as ‘yes’ for participants whose average weekly consumptions are more than 70 g in males and 50 g in females. Regular exercise was indicated as ‘yes’ when the participant performed moderate or strenuous exercise on a regular basis, regardless of indoor or outdoor exercise (for more than 30 min at a time and more than five times per week in the case of moderate exercise, such as swimming slowly, tennis doubles, volleyball, badminton, table tennis, and carrying light objects; for more than 20 min at a time in the case of strenuous exercise, such as running, climbing, cycling fast, swimming fast, football, basketball, jump rope, squash, tennis singles, and carrying heavy objects or when subject walked for more than 30 min at a time and more than five times per week). All tests were two-sided, and P \ 0.05 was considered statistically significant. Statistical Package for Social Science 15.0 software (SPSS, Chicago, IL, USA) was used in performance of all analyses.
Results Changes of ASM, SMI, BMD, and BM according to decade by gender In males, the highest ASM and SMI was observed in the 20–29-year group (23.79 ± 3.21 kg and 33.00 ± 2.89 %, respectively), among decade groups, and then showed a gradual decrease as age increased. In addition, the highest total femoral and lumbar BMD and total femoral BM were also observed in the 20–29-year group (1.02 ± 0.12 g/cm2, 1.00 ± 0.12 g/cm2, and 42.27 ± 7.68 g, respectively), while lumbar BM showed a peak value in the 30–39-year group (69.43 ± 10.90 g). In females, ASM, total femoral and lumbar BMD, and total femoral and lumbar BM reached the peak level in the 40–49-year group (14.62 ± 2.22 kg, 0.91 ± 0.11 g/cm2, 0.99 ± 0.13 g/cm2, 29.25 ± 4.51 g, 60.07 ± 9.77 g, respectively), and then decreased, while SMI showed a peak value in the 20–29-year group (25.89 ± 2.43 %) (Fig. 1 and Supplemental figure 2). Basal characteristics of participants The characteristics of participants in each group are shown in Table 1. Mean age of each group (males \50 years, males C50 years, premenopausal females, and postmenopausal females) was 36.4 ± 7.6, 62.6 ± 8.6, 36.2 ± 8.3, and 62.6 ± 9.8 years, respectively. Mean of BMD for every site was higher in males\50 years and premenopausal females, compared with that in males C50 years and postmenopausal females, respectively (P \ 0.001). ASM and SMI were higher in males \50 years and premenopausal females, compared with males C50 years and postmenopausal
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Endocrine Fig. 1 The means of ASM (a) and SMI (b) in women and men according to decade
females, respectively (23.2 ± 3.2 vs. 20.6 ± 2.9, 14.5 ± 2.3 vs. 13.7 ± 2.0, 32.1 ± 2.8 vs. 31.2 ± 2.7, 25.4 ± 2.3 vs. 24.3 ± 2.6, respectively, P \ 0.001). Association of BM and BMD with body composition and demographic variables in males BMI, WC, ASM, and total fat mass showed a positive association with BM and BMD on the femur and lumbar spine in both males \50 and C50 years. Fat % also showed an association with increased BMD and total femoral BM only in males C50 years. SMI did not show a significant relationship with BMD or BM, while SMI showed an association with increased BMD and lumbar spine BM in males C50 years. In males \50 years, region, smoking, and regular exercise were not significant variables for BMD or BM. In males C50 years, smokers had lower BMD on total femoral and lumbar spine and lower total femoral BM than non-smokers (Table 2). Association of BM and BMD with body composition and demographic variables in females BMI, WC, ASM, and total fat mass showed a positive association with BMD on every site in both pre- and postmenopausal females. Fat % showed an association with increased BM and BMD on every site in premenopausal females and it also showed a positive association with BMD and lumbar spine BM in postmenopausal females. In premenopausal females, participants living in urban areas showed a decreased BMD and total femoral BM, compared with those living in rural areas, while postmenopausal women did not show such a relationship. Of particular interest, only in premenopausal females, alcohol consumption showed an association with increased BM and BMD, and participants who exercised regularly showed increased BMD and lumbar spine BM. Postmenopausal females showed no such relationship (Table 3).
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Adjusted effect of ASM and total fat mass on BM and BMD In multiple regression analysis for BM and BMD with ASM as an independent variable, after adjusting for potential confounding variables in Models 1, 2, and 3, the results showed a positive association of ASM with BM and BMD on total femur and lumbar spine in every group (males \50 years, males C50 years, premenopausal females, and postmenopausal females) (Table 4). In multivariate analysis, total fat mass showed a positive association with BM in every group (Supplemental table 1). Percentages of reduced muscle mass in elderly population We calculated cutoff points of reduced muscle mass in comparison with young population. Reduced muscle mass was defined as ASM divided by body weight (ASM/Wt) (%) more than two SDs below mean value of sex-specific normal young people. The sex-specific young reference group included 3,343 healthy adults aged 20–40 year (1,449 men, 1,894 women). As cutoff points, the two SDs of sex-specific normal young people were 26.98 % in men and 21.14 % in women, respectively. Percentages of reduced muscle mass in male elderly population were 5.5, 10.9 and 17.6 % (in 60–69, 70–79, and C80-year age group, respectively) and those in female elderly population were 8.3, 11.3, and 11.7 % (in 60–69, 70–79, and C80-year age group, respectively).
Discussion Results of this study demonstrated a positive association of ASM with BM and BMD on the femur and lumbar spine in the general Korean population, regardless of gender, age in males, and menopausal status in females, after adjusting for confounding factors, including age, BMI, smoking status, alcohol consumption, and total fat mass. Absolute skeletal muscle mass, ASM, was a more significant factor for BM
Endocrine Table 1 Baseline characteristics of participants Male \50 years
Female C50 years
P
Premenopausal
Postmenopausal
3,078
2,148
P
No. of total participants
2,356
1,943
Age (years)
36.1 ± 7.9
62.9 ± 8.8
\0.001
36.6 ± 8.5
63.1 ± 9.9
\0.001
Height (cm)
172.4 ± 5.9
166.8 ± 5.9
\0.001
159.6 ± 5.7
153.2 ± 6.1
\0.001
Weight (kg)
72.1 ± 10.9
66.1 ± 9.6
\0.001
57.6 ± 9.3
57.0 ± 8.6
0.010
BMI (kg/cm2)
24.2 ± 3.3
23.7 ± 2.9
\0.001
22.6 ± 3.5
24.3 ± 3.3
\0.001
WC (cm)
83.5 ± 9.0
85.0 ± 8.5
\0.001
75.0 ± 9.3
82.2 ± 9.3
\0.001
ASM (kg) SMI (%)
23.2 ± 3.2 32.1 ± 2.8
20.6 ± 2.9 31.2 ± 2.7
\0.001 \0.001
14.5 ± 2.3 25.4 ± 2.3
13.7 ± 2.0 24.3 ± 2.6
\0.001 \0.001
Total fat mass (kg)
16.1 ± 5.9
14.6 ± 4.7
\0.001
18.3 ± 5.3
19.5 ± 5.4
\0.001
Fat %
23.7 ± 6.0
23.7 ± 5.4
0.724
34.4 ± 5.4
36.9 ± 5.7
\0.001
Total femoral BMD (g/cm2)
0.99 ± 0.12
0.92 ± 0.12
\0.001
0.89 ± 0.10
0.77 ± 0.12
\0.001
Lumbar spine BMD (g/cm2)
0.98 ± 0.12
0.95 ± 0.15
\0.001
0.98 ± 0.12
0.80 ± 0.14
\0.001
Total femoral BM (g)
41.0 ± 6.7
38.6 ± 6.5
\0.001
28.7 ± 4.5
25.5 ± 4.5
\0.001
Lumbar spine BM (g)
69.3 ± 11.0
66.4 ± 13.6
\0.001
59.4 ± 9.6
46.4 ± 10.1
\0.001
614 (19.9)
578 (26.9)
2,464 (80.1)
1,570 (73.1)
2,625 (85.3)
1,961 (91.3)
Regionsa
\0.001
Rural area
493 (20.9)
524 (27.0)
Urban area
1,863 (79.1)
1,419 (73.0)
Smoking statusb
\0.001
\0.001
\0.001
Never
499 (21.2)
329 (16.9)
Former
315 (13.4)
527 (27.1)
126 (4.1)
31 (1.4)
Current
1,542 (65.4)
1,087 (55.9)
327 (10.6)
156 (7.3)
948 (40.2)
59.5 (30.6)
360 (11.7)
88 (4.1)
1,408 (59.8)
1,348 (69.4)
2,718 (88.3)
2,060 (95.9)
Yes
1,272 (54.0)
1,137 (58.5)
1,517 (49.3)
1,122 (52.2)
No
1,084 (46.0)
806 (41.5)
1,561 (50.7)
1,026 (47.8)
Alcohol consumptionc Yes No Regular exercise
\0.001
d
\0.001
0.003
0.036
Values are presented as number (%) or mean (SD) BMI body mass index, WC waist circumference, ASM appendicular skeletal muscle mass, SMI ASM/body weight, BMD bone mineral density, BM; bone mass a
Region was categorized as urban (Seoul, Gyeonggi, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) and rural (eight other administrative districts) area
b
Smoking status was divided into three categories: never, former, and current smoker
c
Alcohol consumption was indicated as ‘yes’ for participants whose average weekly consumptions are more than 70 g in males and 50 g in females
d
Regular exercise was indicated as ‘yes’ when the participant performed moderate or strenuous exercise on a regular basis (for more than 30 min at a time and more than five times per week in the case of moderate exercise; for more than 20 min at a time in the case of strenuous exercise) or when the subject walked for more than 30 min at a time and more than five times per week
and BMD, rather than skeletal muscle mass adjusted for body weight, SMI, although SMI also tended to show an association with increased BMD. Total fat mass was also an independent factor for increased BM and BMD in both genders. In men, skeletal muscle, mass as well as BM, reached a peak level in the 20–29-year group, and then showed a gradual decrease together. In females, age to reach the highest level of ASM and BM was later, compared with
males. A peak level was observed in the 40–49-year group in females. After menopause, they showed an abrupt decrease. When we evaluated the prevalence of decreased lean body mass, the prevalence of subjects with SMI more than two SDs below mean value of sex-specific young normal people was 1.6, 5.2, 2.3, and 9.0 % in males \50 years, males C50 years, premenopausal females, and postmenopausal females, respectively. In the literature, the reported prevalence of sarcopenia varies widely due to
123
Endocrine Table 2 Association of anthropometric, body composition, and demographic variables with BM and BMD in males Dependent variable Total femoral BM
Lumbar spine BM
Total femoral BMD
Lumbar spine BMD
\50 years BMI (kg/cm2)
0.586à
0.590à
0.012à
0.008à
WC (cm)
0.209à
0.236à
0.003à
0.003à
1.157
à
à
1.422
à
0.014
0.012à
SMI (%)
0.251
à
0.156
0.000
0.000
Total fat mass (kg)
0.176à
0.237à
0.003à
0.003à
ASM (kg)
Fat % Urban regiona
-0.039 -0.075
-0.046 -0.043
0.001 0.000
0.001 -0.011
Current smokerb
0.160
-0.243
0.003
0.001
Alcohol consumptionc
0.998
Regular exercised
0.699
0.999 -0.397
0.016
0.010
0.012
0.003
C50 years BMI (kg/cm2)
0.831à
1.445à
0.004à
0.018à
WC (cm)
0.254à
0.468à
0.002à
0.005à
à
à
à
0.019à
-0.008à
à
0.008à
à
0.004à
ASM (kg)
1.278
SMI (%) Fat % Urban regiona Current smoker
-0.793
0.352
à
0.081
-0.411 b
Alcohol consumption Regular exercised
-0.004
à
0.311
0.006
à
-0.434
0.002
0.051
-0.014
-0.004
-1.159
-0.016
-0.015
0.600
0.378
-0.001
0.001
0.691
1.177
-0.728 c
0.017
à
-0.085
Total fat mass (kg)
2.007
0.019
0.012
Results are expressed as b coefficients Adjusted for age a
Region was categorized as urban (Seoul, Gyeonggi, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) and rural (eight other administrative districts) area
b
Smoking status was divided into three categories: never, former, and current smoker
c
Alcohol consumption was indicated as ‘yes’ for participants whose average weekly consumptions are more than 70 g in males and 50 g in females
d
Regular exercise was indicated as ‘yes’ when the participant performed moderate or strenuous exercise on a regular basis (for more than 30 min at a time and more than five times per week in the case of moderate exercise; for more than 20 min at a time in the case of strenuous exercise) or when the subject walked for more than 30 min at a time and more than five times per week
P \ 0.05;
à
P \ 0.001
differences in the study population, according to the definition of sarcopenia, technique used for measurement, and the reference group. In Germans aged 60 years and older, the prevalence was 0 % [35], while the prevalence was 57 % in elderly Hispanic US Caucasian men [36]. Regarding postmenopausal women, prevalence ranging from 10 to 40 % has been reported [37]. We adopted ASM divided by body weight (%) as SMI to access the muscle mass adjusted for body mass. SMI was used because it adjusts for stature and the mass of non-skeletal muscle tissues, including fat, organ, and bone. So far, SMI used in this manuscript has been widely adopted in many studies to define sarcopenia [32, 33, 38, 39] as well as relative skeletal muscle index (RSMI), ASM/height2 (kg/m2). Because
123
RSMI is highly correlated with BMI, the index primarily identified low BMI as sarcopenic could underestimate sarcopenia in overweight or obese subjects [40]. Moreover, Lim et al. [32] suggested that SMI is the more appropriate index for sarcopenic obesity in the Korean population, because RSMI was positively correlated with BMI, visceral fat area, and the homeostatic model assessment of insulin resistance (HOMA-IR). Therefore, SMI rather than RSMI is considered to be more appropriate particularly in this study population. In men, regardless of age group (\50, C50 years), ASM showed a positive association with BM and BMD on femur and lumbar spine, which is consistent with results reported in previous studies [10, 21, 41]. Of particular interest, in
Endocrine Table 3 Association of anthropometric, body composition, and demographic variables of BM and BMD in females Dependent variable Total femoral BM
Lumbar spine BM
Total femoral BMD
Lumbar spine BMD
Premenopausal BMI (kg/cm2)
0.525à
0.674à
0.014à
0.012à
WC (cm)
0.206à
0.308à
0.005à
0.005à
1.163
à
à
à
0.018à
0.107
-0.005à
0.298
à
à
0.007à
à
0.003 -0.018
0.003à -0.019
ASM (kg) SMI (%) Total fat mass (kg)
Fat % Urban regiona
0.052 -0.528
1.725
0.020
-0.156
-0.003
à
0.484
0.007
0.101 -0.934
Current smokerb
0.010
0.629
0.003
0.004
Alcohol consumptionc
0.663
1.199
0.012
0.011
Regular exercised
0.342
1.137
0.012
0.018
BMI (kg/cm2)
0.356à
0.592à
0.009à
0.011à
WC (cm)
0.133
0.234à
0.003à
0.004à
à
à
à
0.016à
-0.009à
à
0.007à
à
0.004à
Postmenopausal
ASM (kg)
1.067
SMI (%) Fat % Urban regiona Current smoker
b
0.191
0.017
à
0.045
Total fat mass (kg)
1.555 -0.423
à
-0.004
à
0.435
0.005
0.013
0.124
0.002
-0.089
0.447
-0.007
0.001
-0.283
0.815
-0.014
0.002
Alcohol consumptionc
0.388
2.138
0.009
0.025
Regular exercised
0.066
-0.466
0.006
0.002
Results are expressed as b coefficients Adjusted for age a
Region was categorized as urban (Seoul, Gyeonggi, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) and rural (eight other administrative districts) area
b
Smoking status was divided into three categories: never, former, and current smoker
c
Alcohol consumption was indicated as ‘yes’ for participants whose average weekly consumptions are more than 70 g in males and 50 g in females
d
Regular exercise was indicated as ‘yes’ when the participant performed moderate or strenuous exercise on a regular basis (for more than 30 min at a time and more than five times per week in the case of moderate exercise; for more than 20 min at a time in the case of strenuous exercise) or when the subject walked for more than 30 min at a time and more than five times per week
P \ 0.05;
à
P \ 0.001
the current study, absolute muscle mass was a more important factor for BM and BMD, rather than muscle mass ratio of body mass. Fat mass had a positive effect on BM and BMD, while fat % also tended to show an association with increased BM only in males C50 years. In contrast, in females, fat %, as well as total fat mass, showed a positive association with BM and BMD in both pre- and postmenopausal women. This result is consistent with those of previous studies showing that fat mass had a stronger effect on BMD in women than in men [23, 24]. However, except inferring the sex hormonal effect, we could not provide a precise explanation for the discrepancy between genders in this study. In this study, fat % of body weight, as well as absolute amount of lean body mass, were
independent determinants for increased BM. This result was quite interesting because we expected that, after adjusting for body size or body weight bearing effect on bone, fat mass might show a negative association with BM and BMD, possibly via inflammatory effects leading to increased bone absorption [42]. In fact, according to results of previous studies, fat mass and BMD showed either a positive [17, 43] or a negative [44] correlation. In women, regardless of menopausal status, after adjusting for confounding factors, including age, BMI, smoking status, alcohol consumption, and total fat mass, ASM showed a positive association with BM and BMD, which is consistent with results of previous studies showing positive correlation of lean mass with whole body or
123
Endocrine Table 4 Multiple regression analysis for BM and BMD with ASM as an independent variable Male
Female
\50 years
C50 years
Premenopausal
Postmenopausal
Total femoral BMD (g/cm2)
0.011 (0.008–0.013)à
0.010 (0.007–0.014)à
0.011 (0.008–0.014)à
0.011 (0.008–0.015)à
Lumbar spine BMD (g/cm2)
0.010 (0.008–0.013)à
0.012 (0.017–0.016)à
0.012 (0.008–0.015)à
0.008 (0.003–0.013)
1.316 (1.182–1.450)
à
à
1.180 (1.072–1.288)
à
1.042 (0.903–1.180)à
1.772 (1.535–2.009)
à
1.721 (1.356–2.085)
1.932 (1.671–2.192)
à
1.424 (1.090–1.759)à
Model 1
Total femoral BM (g) Lumbar spine BM (g)
1.183 (1.028–1.339)
à
Model 2 Total femoral BMD (g/cm2) Lumbar spine BMD (g/cm2)
0.014 (0.012–0.016)à 0.013 (0.011–0.015)à
0.011 (0.009–0.013)à 0.010 (0.007–0.013)à
0.012 (0.010–0.014)à 0.011 (0.008–0.013)à
0.011 (0.009–0.013)à 0.009 (0.006–0.012)à
Total femoral BM (g)
1.421 (1.324–1.518)à
1.231 (1.116–1.345)à
1.144 (1.063–1.224)à
1.127 (1.025–1.228)à
Lumbar spine BM (g)
à
à
1.721 (1.435–2.007)
1.868 (1.684–2.053)
à
1.473 (1.219–1.727)à
0.010 (0.008–0.012)à
0.010 (0.007–0.012)à
0.009 (0.007–0.011)à
0.011 (0.009–0.014)à
à
à
0.010 (0.007–0.014)
0.011 (0.009–0.013)
à
0.010 (0.007–0.013)à
1.943 (1.769–2.116)
Model 3 Total femoral BMD (g/cm2) 2
Lumbar spine BMD (g/cm )
0.012 (0.010–0.014)
Total femoral BM (g)
1.399 (1.295–1.502)à
1.259 (1.139–1.379)à
1.177 (1.095–1.259)à
1.152 (1.049–1.255)à
Lumbar spine BM (g)
à
à
à
1.669 (1.416–1.921)à
2.143 (1.960–2.326)
2.030 (1.736–2.325)
2.051 (1.865–2.236)
Results are expressed as b coefficients and 95 % CI Model 1: adjusted for age and BMI Model 2: adjusted for age, BMI, smoking status, and alcohol consumption Model 3: adjusted for age, BMI, smoking status, alcohol consumption, and total fat mass P \ 0.05; à P \ 0.001
regional areal BMD in postmenopausal women [17–20, 45, 46]. The effect of fat mass on BM according to menopausal status has been controversial so far. Fat mass, rather than lean mass, was suggested as a more important factor for BMD after menopause [25, 26]. In the current study, ASM and total fat mass were independent factors for increased BMD in both pre-and postmenopausal females. So far, several studies have reported a negative association of smoking with total hip BMD in people aged 65-year old and older [17]. Results of the current study also showed a negative relationship of smoking with BMD on the femur and lumbar spine in men aged 50 years and older. However, this association was not observed in younger men and premenopausal women. Postmenopausal women who smoked showed decreased BMD on total femur. We assume that the lower prevalence of smoking among females and smoking duration may affect the difference. The role of physical activity in the association of lean mass with BMD has been inconsistent. Some studies have suggested that the relationship between lean mass and BMD was largely mediated by physical activity [11, 47]. However, in a study conducted in men aged 40 years and older, physical activity did not show an association with BMD on any site [21].The current study showed different results according to groups, reflecting that the effects of
123
exercise on bone may not be simple and may be affected by potential confounders. To the best of our knowledge, although some studies examining the relationship of lean body mass with BMD in a small population, including younger men [10] or premenopausal women [47], have been reported, the strength of our study is based on a large population representative of the entire population in order to examine their relationship together. This study has several limitations. First, the cross-sectional study design prevented us from affirming the causal relationship between lean body mass and BMD or BM. Their causal relationship should be verified in future longitudinal studies. Second, although DXA is widely used for determination of lean mass, the evaluation of lean mass by DXA might underestimate the age-associated reduction in muscle mass due to change in total body water that accompanies aging [10]. Third, sarcopenia and osteoporosis are currently considered as having common risk factors, including genetics, hormonal change, and nutrition, However, because we did not measure vitamin D, testosterone, estrogen, insulin growth factor 1, or inflammatory cytokines, like tumor necrosis factor a and interleukin-1, we could not provide any mechanistic explanation for their relationship. Finally, the skeletal muscle index (%) [ASM (kg) divided body weight (kg) x 100] used in this
Endocrine
manuscript has been widely adopted in many studies to define sarcopenia; however, it was recently suggested that the definition of sarcopenia be restricted to the presence of low muscle strength or poor physical performance in addition to reduced muscle [48]; therefore, because we did not measure muscle strength for determination of sarcopenia, we could not provide an exact definition of sarcopenia. Instead, we examined the relationship of lean body mass with bone mass and bone density. This might have been a limitation in this study. Despite these limitations, because the population of the current study was representative of the general Korean population, this study has powerful strength. In conclusion, results of this study showed an independent association of ASM with BM and BMD in both males and females, regardless of age or menopausal status. Of particular interest, even in pre-and postmenopausal females, lean body mass was found to be an independent correlate of BM and BMD. Therefore, reduced lean body may be an early predictor of osteoporosis in the general population. Further study is required in order to elucidate the causal relationship and pathophysiology. Acknowledgments This research was supported by a grant from the Daegu and Kyungpook local committee of the Korean Diabetes Association and by the Dongguk University research fund. I thank the Ministry of Health and Social Welfare and Korea Centers for Disease Control and Prevention for providing the invaluable data of the survey. Conflict of interest
The authors have nothing to declare.
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