J Bone Miner Metab DOI 10.1007/s00774-014-0600-z
ORIGINAL ARTICLE
Gender- and body-site-specific factors associated with bone mineral density in a non-institutionalized Korean population aged ‡50 years Kyoung Min Lee • Soon-Sun Kwon • Chin Youb Chung • Seung Yeol Lee • Tae Gyun Kim • Young Choi • Moon Seok Park
Received: 23 December 2013 / Accepted: 8 May 2014 Ó The Japanese Society for Bone and Mineral Research and Springer Japan 2014
Abstract The aim of this study was to investigate the gender- and body-site-specific factors associated with bone mineral density (BMD) at the femoral neck and lumbar spine in a non-institutionalized population aged C50 years characterized by low average calcium intake. The comprehensive data utilized were from the 2010 Fifth Korea National Health and Nutrition Examination Survey, which included health behavior questionnaire, blood and urine tests, dual-energy X-ray absorptiometry, and nutrition intake. The factors associated with BMD at the femoral neck and lumbar spine in both genders were analyzed separately using multiple regression analysis with a stepwise selection. The average daily calcium intake in the
K. M. Lee C. Y. Chung M. S. Park (&) Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, 300 Gumi-Dong, Bundang-Gu, Sungnam, Kyungki 463-707, South Korea e-mail: [email protected] S.-S. Kwon Biomedical Research Institute, Seoul National University Bundang Hospital, 300 Gumi-Dong, Bundang-Gu, Sungnam, Kyungki 463-707, South Korea S. Y. Lee Department of Orthopaedic Surgery, Myongji Hospital, 697-24 Hwajung-Dong, Deokyang-Gu, Goyang, Kyungki 412-270, South Korea T. G. Kim Department of Orthopaedic Surgery, Konyang University Hospital, 685 Gasuwon-Dong Seo-Gu, Metropolitan City Daejon 302-718, South Korea Y. Choi Department of Orthopaedic Surgery, Gwanghye General Hospital, 96 Chungyeoldae-Ro, Dongrae-Gu, Metropolitan City Pusan 607-713, South Korea
male subjects was 565.8 mg and in the female subjects was 443.7 mg. In multiple regression analysis, age, body mass index (BMI), alkaline phosphatase (ALP), lead, daily calcium intake, and cadmium were the significant factors associated with femoral neck BMD in male subjects. BMI, creatinine (Cr), total body fat percentile, lead, ALP, and hypertension were found to be the significant factors associated with lumbar spine BMD in male subjects. In the female subjects, the significant factors associated with femoral neck BMD were age, BMI, ALP, house income, and total body fat percentile, while menopause, Cr, mercury, house income, BMI, and ALP were found to be the significant factors associated with lumbar spine BMD. In conclusion, different factors were associated with BMD depending on gender and the body site tested (femoral neck or lumbar spine). These gender- and body-site-specific factors need to be considered for the prevention and management of osteoporosis. Keywords Determinants Bone mineral density Lumbar spine Femoral neck Gender
Introduction Hip and spine fractures, known for their morbidity and mortality, both represent fractures caused by osteoporosis [1–5]. However, from a clinical perspective, these two types of fractures are different in terms of management strategies and anatomical structures involved. Hip fractures usually require surgical intervention, whereas spine fractures are managed with conservative treatment or minimally invasive surgical intervention such as vertebroplasty or kyphoplasty [6–9]. Moreover, hip fractures involve the proximal femur, which consists of a considerable amount
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of cortical bone, whereas spine fractures involve vertebral bones, the majority of which consist of cancellous bone [10]. Bone mineral density (BMD) is an important predictor of osteoporotic fractures [11–15], and the current medical treatment for osteoporosis is therefore focused on increasing BMD [16–19], although the final clinical goals of treatment are the reduction of fracture incidence and the associated morbidity. Determinants of BMD have been investigated multilaterally in previous studies in terms of several factors such as genetic, ethnic, nutritional, metabolic, and mechanical factors [20–28]. However, the results of previous studies have been inconsistent as regards the effects of smoking [22, 24, 29–31], physical activity [22, 24, 32, 33], dietary calcium intake [22, 24, 33, 34], and alcohol [22, 24, 29, 33, 35]. These results have led to confusion among clinicians with regard to the determination of treatment guidelines in the management of osteoporosis. It may be possible to resolve these uncertainties and reduce the effect of confounding variables, at least in part, by stratifying the determinants of BMD according to crucial variables (gender and body site such as hip and spine). Considering the differences between hip and spine fractures and the influence of gender, a study to investigate gender- and site-specific factors associated with BMD at the hip and spine could provide valuable clinical information regarding prevention and management of osteoporosis. In the present study, we aimed to investigate factors associated with BMD at the femoral neck and lumbar spine based on gender in a non-institutionalized population aged C50 years using data from the Korea National Health and Nutrition Examination Survey (KNHNES).
Materials and methods Subjects This study utilized a cross-sectional and nationally representative database, the Fifth Korea National Health and Nutrition Examination Survey, conducted by the Korean Centers for Disease Control and Prevention in 2010 (KNHNES V 2010). The Korean Centers for Disease Control and Prevention attempted to collect a representative sample of Korean individuals from stratified, multistage probability samples of Korean households representing the civilian, non-institutionalized population. The data were weighted according to sampling and response rates, and adjusted for gender and age group structures of the parent population. The survey comprised 4 components: health interview, health behavior, health
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Fig. 1 Flow diagram of inclusion and exclusion criteria in the Fifth Korea National Health and Nutrition Examination Survey (KNHNES V). A total of 1940 subjects were finally included
examination, and nutrition. A total of 10533 individuals (82.8 %) out of the 12722 people (aged C50 years) who were selected from the database agreed to participate in the study. Those with incomplete data for a standardized physical examination, laboratory tests (blood and urine), lifestyle questionnaire, and dual-energy X-ray absorptiometry (DXA), and those with a current diagnosis of cancer were excluded from the study. Subjects who were receiving osteoporosis medication, oral contraceptives, or hormone replacement therapy were also excluded from the data analysis (Fig. 1). A written informed consent was
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obtained from all participants by the Korean Centers for Disease Control and Prevention, and the study was exempt from approval by the institutional review board of Seoul National University Bundang Hospital, as the study utilized a publicly accessible database. Data collection This study utilized the KNHNES V 2010 database for collection of demographics including age, gender, body mass index (BMI), weight change in the past year (categories: gain [10 kg, gain between 6 and 10 kg, gain between 3 and 6 kg, gain \3 kg, no change, loss \3 kg, loss between 3 and 6 kg, loss between 6 and 10 kg, loss [10 kg), house income (below the 25th percentile, between the 25th and the 50th percentiles, between the 50th and the 75th percentiles, more than the 75th percentile), menopause, duration of menstruation (in months), amount of smoking (current and cumulative), amount of alcohol consumption in the past year, and presence of other medical conditions [hypertension (HT), coronary artery disease (CAD), cerebrovascular accident (CVA), osteoarthritis (OA) and chronic renal failure (CRF)]. The parameters of height, weight, and waist circumference were measured using standardized instruments, and BMI was calculated from the height and the weight. Weight changes in the past year were obtained from the questionnaire. The categories of house income were based on the total house income reported by the subjects. The duration of menstruation in the subjects was calculated by subtracting the age of menarche from the current age (in premenopausal women) or age of menopause in postmenopausal women, for which the ages were obtained from the questionnaire. The amount of cumulative smoking was calculated from the amount of daily smoking and the duration of smoking, which were included in the questionnaire. The amount of alcohol consumption was calculated using the data of average frequency of drinking and the average amount of drinking per session (in glasses) obtained from the questionnaire, with the assumption that 1 glass contains 10 g of alcohol. The presence of other medical conditions (HT, CAD, and CVA) was determined from the diagnoses obtained from the questionnaire, which was based on the self-reported medical conditions. The diagnosis of osteoarthritis was based on examination of radiographs of the hip and the knee (Kellgren–Lawrence grade) and the subjects’ report of arthritic symptoms. Activity level was evaluated by the short form of the International Physical Activity Questionnaire (IPAQ-SF) [36], which provided the duration of vigorous-intensity, moderate-intensity, and walking activities per week as well as the total metabolic equivalent (MET). Physical activity
that required hard physical effort and resulted in the subject breathing much harder than normal was considered a vigorous-intensity activity and that which required moderate physical effort and resulted in the subject breathing somewhat harder than normal was considered a moderateintensity activity. The total MET was calculated using the equation (8.0 9 minutes of vigorous-intensity activity/ week) ? (4.0 9 minutes of moderate-intensity activity/ week) ? (3.3 9 minutes of walking/week). Blood tests for levels of fasting blood sugar (FBS), glycosylated hemoglobin (HbAlc), insulin, total cholesterol, high-density lipoprotein (HDL) cholesterol, lowdensity lipoprotein (LDL) cholesterol, triglyceride, hemoglobin (Hb), creatinine (Cr), 25-hydroxyvitamin D [25(OH)D], alkaline phosphatase (ALP), parathyroid hormone (PTH), and heavy metals (lead, mercury, and cadmium) were performed. In addition, urine tests for urine cotinine were performed. Blood and urine samples were obtained throughout the year after an 8-h fast, and immediately processed, refrigerated, and transported in cold storage to the central testing institute (NeoDin Medical Institute, Seoul, South Korea), where they were analyzed within 24 h. The amount of daily calcium intake was calculated using the Food Composition Table developed by the National Rural Resources Development Institute (7th revision) [37, 38], based on a 24-h dietary recall questionnaire administered by a dietician. Daily energy intake was recorded, and calcium density (calcium intake per unit energy intake) was calculated. BMD (g/cm2) was measured at the femoral neck and the lumbar spine by DXA (Discovery-W fan-beam densitometer; Hologic Inc., Marlborough, MA, USA) with coefficients of variation of 1.9 and 2.5 %, respectively. The total body fat percentile was also measured. Data analysis The subjects were divided into 2 groups according to their gender. The continuous or categorical variables that had a significant correlation with the femoral neck and the lumbar spine BMDs were examined separately for each group. Moreover, the femoral neck and lumbar spine BMDs of those with other medical conditions (HT, CAD, CVA, OA, and CRF) were compared with the BMDs of those without these conditions. The variables that were significantly correlated with BMD or the conditions wherein the BMD was significantly different between cases where the condition was present and absent were selected, and included in the multiple regression analysis. The factors that influenced the BMDs of the femoral neck and the lumbar spine were evaluated using multiple regression analysis in each gender group, and were categorized as associated factors with BMDs.
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Statistical analysis A descriptive analysis of the entire dataset, including average and standard deviations (SDs) or proportions, was performed. The data were assessed for normality using the Kolmogorov–Smirnov test. Correlations between the variables and BMDs of the femoral neck and the lumbar spine were evaluated using the Pearson correlation coefficient or Spearman correlation coefficient, depending on the normality of the data. The comparison of BMDs between those with other medical conditions and those without these conditions was performed using Student’s t test. A stepwise selection of the variables was adopted in the multiple regression analysis. The variables that were significantly correlated with BMDs and the conditions wherein the BMD was significantly different between cases where the condition was present and absent were included as independent variables, whereas the BMDs of the femoral neck and the lumbar spine were the dependent variables in the multiple regression analysis in each gender. All statistical analyses were performed using SPSS 18.0 (SPSS Inc., Chicago, IL, USA), and statistical significance was set at p \ 0.05.
Results A total of 1940 subjects (1096 males, 844 females) were included in the final data analysis. The average ages of the male and female subjects were 63.2 (SD 8.7 years) and 62.9 years (SD 9.8 years), respectively. The average daily calcium intake in the male subjects was 565.8 mg and in the female subjects was 443.7 mg, and average calcium density was 0.18 and 0.16 mg/kcal in males and females, respectively. The average femoral neck BMDs of the male and female subjects were 0.7451 (SD 0.1175 g/cm2) and 0.6284 g/cm2 (SD 0.1172 g/ cm2), respectively, and the average lumbar spine BMDs were 0.9467 (SD 0.1565 g/cm2) and 0.8059 g/cm2 (SD 0.1517 g/ cm2), respectively (Table 1). In the male group, the candidate factors that were significantly associated with femoral neck BMD were age, BMI, house income, cumulative amount of smoking, total MET, FBS, total cholesterol, Hb, ALP, lead, cadmium, urine cotinine, and daily calcium intake amount. Age, BMI, house income, FBS, insulin, HDL cholesterol, Cr, ALP, lead, daily calcium intake amount, total body fat percentile, and HT were the candidate factors significantly associated with lumbar spine BMD in male subjects (Table 2). In the female group, the factors shown to have a significant association with the femoral neck BMD were age, BMI, weight change in the past year, house income, menopause, duration of menstruation, amount of alcohol consumption in
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the past year, total MET, HDL cholesterol, triglyceride, Hb, ALP, mercury, daily calcium intake amount, total body fat percentile, and the presence of HT and OA. The factors shown to have a significant association with the lumbar spine BMD in the female group were age, BMI, weight change in the past year, house income, menopause, duration of menstruation, amount of alcohol consumption in the past year, HDL cholesterol, Cr, ALP, mercury, daily calcium intake, and total body fat percentile (Table 2). In multiple regression analysis using a stepwise selection, age, BMI, ALP, lead, daily calcium intake, and cadmium were the significant factors associated with femoral neck BMD in male subjects (Table 3). BMI, Cr, total body fat percentile, lead, ALP, and HT were found to be the significant factors associated with lumbar spine BMD in male subjects (Table 4). In the female subjects, the significant factors associated with femoral neck BMD were age, BMI, ALP, house income, and total body fat percentile (Table 5), while menopause, Cr, mercury, house income, BMI, and ALP were found to be the significant associated factors with lumbar spine BMD (Table 6).
Discussion In the present study, we investigated gender-specific factors associated with BMD of the femoral neck and the lumbar spine in subjects aged C50 years. The KNHANES V 2010 database, utilized for subject selection, included comprehensive variables, and the authors endeavored to include as many clinical variables as possible to exclude or adjust the effects of potential confounding factors. BMI and ALP were associated with BMD of the femoral neck and lumbar spine in both genders. Age was associated with femoral neck BMD in both genders, and Cr was associated with lumbar spine BMD in both genders. Lead was associated with both femoral neck and lumbar spine BMD in male subjects and house income was associated with both femoral neck and lumbar spine BMD in female subjects (Fig. 2). The characteristics of the study population with regard to calcium metabolism need to be defined prior to a detailed interpretation of the results. The average daily calcium intake in the male subjects was 565.8 mg and in the female subjects was 443.7 mg. The average serum 25(OH)D level in the male subjects was 20.9 ng/mL and in the female subjects was 17.8 ng/mL. The average serum PTH level in the male subjects was 67.3 pg/mL and in the female subjects was 70.3 pg/mL. Therefore, our study population showed a low average calcium intake and a low serum 25(OH)D level, which might be compensated for by a high PTH level, to maintain the serum calcium level. Thus, we believe that a catabolic environment in terms of bone metabolism may be present in such patients.
J Bone Miner Metab Table 1 Data summary
Male subjects
Female subjects
No.
1096
844
Age (years)
63.2 (8.7)
62.9 (9.8)
BMI (kg/cm2)
23.7 (2.9)
24.2 (3.4)
Weight change ([10 kg gain/6–10 kg gain/3–6 kg gain/0–3 kg gain/no change/0–3 kg loss/3–6 kg loss/6–10 kg loss/[10 kg loss)
1/6/59/858/140/21/11
5/11/86/622/100/15/5
House income (0–25/25–50/50–75/75–100 percentiles)
300/285/251/260
296/213/159/176
Menopause (yes/no)
NA
771/73
Duration of menstruation (months) Cumulative amount of smoking (pack)
NA 4510.4 (7173.0)
396.6 (64.7) 69.3 (1000.3)
Amount of alcohol consumption (g/day)
14.3 (20.2)
2.5 (6.6)
HT (yes/no)
400/696
320/524
CAD (yes/no)
66/1030
38/806
CVA (yes/no)
30/1066
9/835
OA (yes/no)
72/1024
184/649
3142.5 (4463.5)
2452.7 (4175.7)
FBS (mg/dL)
105.4 (26.8)
99.7 (21.1)
HbAlc (%)
7.3 (1.4)
7.2 (1.3)
Insulin (lIU/mL)
10.2 (5.2)
10.7 (4.9)
Total cholesterol (mg/dL)
186.4 (36.2)
203.5 (36.5)
HDL cholesterol (mg/dL) LDL cholesterol (mg/dL)
48.7 (12.4) 110.7 (31.6)
53.0 (12.7) 127.4 (28.9)
Medical diseases
Activity Weekly total MET Blood test
Data are presented as mean (standard deviation) BMI body mass index, HT hypertension, CAD coronary artery disease, CVA cerebrovascular accident, OA osteoarthritis, MET metabolic equivalent, FBS fasting blood sugar, HbAlc glycosylated hemoglobin, HDL high-density lipoprotein, LDL low-density lipoprotein, Hb hemoglobin, Cr creatinine, 25(OH)D 25hydroxyvitamin D, ALP alkaline phosphatase, PTH parathyroid hormone, BMD bone mineral density, NA not applicable
Triglyceride (mg/dL)
161.8 (151.5)
134.7 (79.7)
Hb (g/dL)
14.9 (1.3)
13.1 (1.1)
Cr (mg/dL)
0.97 (0.23)
0.71 (0.13)
25(OH)D (ng/mL)
20.9 (7.3)
17.8 (6.7)
ALP (IU/L)
241.4 (67.4)
257.9 (78.6)
PTH (pg/mL)
67.3 (27.9)
70.3 (28.9)
Lead (lg/dL)
3.3 (1.5)
2.4 (0.8)
Mercury (lg/L)
6.5 (5.0)
4.3 (3.1)
Cadmium (lg/L)
1.2 (0.6)
1.6 (0.7)
Urine cotinine (lg/mL)
606.0 (971.9)
72.1 (297.2)
Daily calcium intake amount (mg)
565.8 (328.8)
443.7 (341.5)
Daily energy intake (kcal)
3391.5 (1264.5)
2887.2 (1126.2)
Calcium density (mg/kcal)
0.18 (0.10)
0.16 (0.11)
0.7451 (0.1175) 0.9467 (0.1565)
0.6284 (0.1172) 0.8059 (0.1517)
Heavy metals
2
BMD (femoral neck) (g/cm ) BMD (lumbar spine) (g/cm2)
BMI and ALP levels were the significant determinants of BMD at the femoral neck and the lumbar spine in both genders (Fig. 2). Although ALP is produced by several organs including the liver, bile duct, kidneys, and bone, it is primarily known to be associated with osteoblastic activity in bone metabolism [39]. The study results showed that the ALP level was significantly associated with BMD in the
population with low average calcium intake, with negative correlations of ALP with femoral neck and lumbar spine BMDs in both genders. These results are supported by previous studies that reported increased ALP activity in women with a more severe osteoporosis [40, 41]. BMI was another significant factor associated with BMD at the hip and the lumbar spine in both genders. This result is
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J Bone Miner Metab Table 2 Candidate factors significantly affecting BMDs of femoral neck and lumbar spine in each gender Male
Female
Femoral neck
Lumbar spine
Femoral neck
Lumbar spine
Age (r = -0.377, p \ 0.001)
Age (r = -0.078, p = 0.010)
Age (r = -0.629, p \ 0.001)
Age (r = -0.462, p \ 0.001)
BMI (r = 0.356, p \ 0.001)
BMI (r = 0.345, p \ 0.001)
BMI (r = 0.262, p \ 0.001)
BMI (r = 0.280, p \ 0.001)
House income (r = 0.258, p \ 0.001)* Cumulative amount of smoking (r = -0.079, p = 0.009)
House income (r = 0.164, p \ 0.001)* FBS (r = 0.138, p \ 0.001)
Weight change (r = 0.154, p \ 0.001)* House income (r = 0.289, p \ 0.001)*
Weight change (r = 0.119, p = 0.001)* House income (r = 0.258, p \ 0.001)*
Total MET (r = 0.073, p = 0.015)
Insulin (r = 0.113, p \ 0.001)
Menopause (p \ 0.001)
Menopause (p \ 0.001)
FBS (r = 0.090, p = 0.003)
HDL cholesterol (r = 0.103, p = 0.001)
Duration of menstruation (r = 0.268, p \ 0.001)*
Duration of menstruation (r = 0.236, p \ 0.001)*
Total cholesterol (r = 0.071, p = 0.022)
Cr (r = 0.110, p \ 0.001)
Amount of alcohol consumption (r = 0.112, p = 0.001)
Amount of alcohol consumption (r = 0.068, p = 0.048)
Hb (r = 0.158, p \ 0.001)
ALP (r = -0.153, p \ 0.001)
Total MET (r = 0.114, p = 0.001)
HDL cholesterol (r = 0.087, p = 0.015)
ALP (r = -0.216, p \ 0.001)
Lead (r = -0.130, p = 0.016)
HDL cholesterol (r = 0.151, p \ 0.001)
Cr (r = 0.074, p = 0.039)
Lead (r = -0.116, p = 0.032)
Daily calcium intake (r = 0.145, p \ 0.001)
Triglyceride (r = -0.098, p = 0.006)
ALP (r = -0.286, p \ 0.001)
Cadmium (r = -0.164, p = 0.002)
Total body fat percentile (r = 0.145, p \ 0.001)
Hb (r = 0.094, p = 0.009)
Mercury (r = 0.195, p = 0.007)
Urine cotinine (r = -0.114, p = 0.037)
HT (p = 0.001)
ALP (r = -0.235, p \ 0.001)
Daily calcium intake (r = 0.124, p \ 0.001)
Mercury (r = 0.197, p = 0.006)
Total body fat percentile (r = 0.172, p \ 0.001)
Daily calcium intake (r = 0.227, p \ 0.001)
Daily calcium intake (r = 0.172, p \ 0.001) Total body fat percentile (r = 0.113, p = 0.001) HT (p \ 0.001) OA (p = 0.001) BMI body mass index, MET metabolic equivalent, FBS fasting blood sugar, Hb hemoglobin, ALP alkaline phosphatase, HDL high-density lipoprotein, Cr creatinine, HT hypertension, OA osteoarthritis * Spearman correlation test
Table 3 Multiple regression analysis to identify significant determinants of femoral neck BMD in male subjects B
t
p value
Age
-0.005
-5.9
\0.001
BMI
0.009
4.4
\0.001
ALP
0.000
-3.3
0.001
Lead
-0.012
-2.6
0.009
0.003
2.3
0.020
-0.020
-2.1
0.039
0.950
11.8
\0.001
Daily calcium intake Cadmium Coefficient 2
R = 0.260 BMI body mass index, ALP alkaline phosphatase
concurrent with previous studies that have reported that weight or BMI is a protective factor for osteoporosis [22, 24, 25, 42].
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The age of the subjects was found to be a significant factor associated with BMD at the femoral neck, but not at the lumbar spine, in both genders. This result is supported by a previous study which reported that hip BMD declined and spine BMD increased with advancing age [22]. On the other hand, menopause was significantly associated with lumbar spine BMD alone. Considering that the femoral neck has a higher proportion of cortical bone than the lumbar spine and the lumbar spine has a higher proportion of cancellous bone than the femoral neck, cortical bone could be more affected by age than cancellous bone, whereas cancellous bone tended to be more affected by estrogen levels. Thus, it could be hypothesized that postmenopausal osteoporosis is likely to involve cancellous bone, whereas senile osteoporosis is likely to involve cortical bone. However, this issue needs further investigation.
J Bone Miner Metab Table 4 Multiple regression analysis to identify significant determinants of lumbar spine BMD in male subjects B BMI
t
p value
0.016
4.5
\0.001
0.162
4.2
\0.001
Total body fat percentile
-0.007
-3.7
\0.001
Lead
-0.016
-2.7
0.008
ALP
0.000
-2.6
0.009
HT
0.042
2.5
0.012
Coefficient
0.692
8.3
\0.001
Cr
2
R = 0.171 ALP alkaline phosphatase, FBS fasting blood sugar, Cr creatinine, HT hypertension
Table 5 Multiple regression analysis to identify significant determinants of femoral neck BMD in female subjects B
t
p value
Age
-0.006
-6.1
\0.001
BMI ALP
0.012 0.000
5.1 -3.7
\0.001 \0.001
House income Total body fat percentile
0.018
3.1
0.002
-0.003
-2.5
0.013
0.877
11.1
\0.001
Coefficient 2
R = 0.405 BMI body mass index, ALP alkaline phosphatase
Table 6 Multiple regression analysis to identify significant determinants of lumbar spine BMD in female subjects B Menopause
t
p value \0.001
-0.141
-4.1
Cr
0.218
2.3
0.022
Mercury
0.007
2.4
0.016
House income
0.025
2.9
0.004
BMI
0.008
2.5
0.015
ALP
0.000
-2.4
0.018
Coefficient
0.893
6.9
\0.001
R2 = 0.281 ALP alkaline phosphatase, Cr creatinine
The daily calcium intake amount was a significant factor associated with femoral neck BMD in male subjects. Male subjects showed greater average daily calcium intake than female subjects. A possible explanation for the difference in the effect of calcium intake between the genders and body sites could be the difference in hormones and proportion of cortical bones or in the different levels of calcium intake between the genders, so that the small amount of calcium intake in female subjects may be below the
threshold level triggering a positive effect on the BMD. In addition, the lower calcium intake in women than in men could be explained, at least in part, by the different dietary behaviors seen in men and women [43, 44]. The Cr level was significantly associated with lumbar spine BMD in both genders but not with femoral neck BMD. Cr is a breakdown product of creatine phosphate in muscle, and is known to be produced at a constant rate by the body and filtered out of the body by the kidney [45]. Considering that our population had a small number of subjects with impaired renal function, the serum creatinine level reflected the muscle mass of the subjects. This result could be interpreted to imply that lumbar spine BMD, but not femoral neck BMD, is significantly affected by total body muscle mass. Currently, it is uncertain whether cancellous bone is more sensitive to the mechanical load caused by muscle contraction or whether the biological effect of muscle is involved in increasing cancellous bone mass. Our study showed that lead was a significant factor associated with BMD at both the femoral neck and lumbar spine in men. Although a gender-specific association between lead and bone mineral density could not be determined, it might be partly attributed to the difference in the serum lead levels between the genders. It has been reported that lead exerts actions directly on osteoblast and osteoclast function and indirectly via kidney dysfunction on bone turnover [46, 47]. A previous study reported the adverse effect of lead and cadmium on bone mineral density, which could possibly be associated with industrial pollution [48]. Another study showed that high blood mercury level was associated with a lower risk of having osteoporosis in postmenopausal women [49], which is concurrent with our result. Further study is required to investigate the role of heavy metals and industrial pollution in bone metabolism. House income was found to be a significant factor associated with BMD at the femoral neck and lumbar spine in female subjects. This is supported by the results of previous studies on nutritional deficiencies in the underprivileged population and adherence to osteoporosis medication according to house income in women [50–52]. The effect of physical activity, as a contributing factor to BMD, has been investigated in previous studies [20, 53]. This study evaluated physical activity using the IPAQ, and the effect of physical activity on BMD was not found to be significant. Our study population showed that low average calcium intake and low serum 25(OH)D level, which made the environment unfavorable for bone metabolism and could not be overcome by physical activity, were not significant factors associated with BMD. However, we were unable to provide a detailed explanation for this occurrence with the present data. The factors significantly associated with BMD according to gender and body site tested in this study are
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J Bone Miner Metab Fig. 2 Common determinants of BMD according to body site and gender. Weight and ALP are important determinants of BMD at the femoral neck and the lumbar spine in both genders
applicable only to the Korean elderly population with low average calcium intake. We consider that the risk factors for osteoporosis reported in previous studies varied because of the different characteristics of the study population, such as ethnicity, nutrition, environment, health habit, and genetic background, and the inclusion of variables. In this case, the explanatory power of the regression model needs to be the focus. Our regression model showed an R2 of 0.405 for femoral neck BMD in female subjects, which means that the model could explain 40.5 % of the variations seen in the Korean population. An improved regression model needs to be used to better explain BMD in future studies, including more feasible variables to be generalized to other populations with different characteristics. Lastly, we need to address the limitations of this study. This was a cross-sectional study, and therefore could not establish causality. In addition, although the study data were quite comprehensive, intake of medications such as steroids was not considered in the data analysis. Another limitation of this study was that the medical conditions of the participants were self-reported. The validity of self-reported medical conditions was not established in our study cohort. In conclusion, different factors were associated with BMD according to gender and body site tested (femoral neck and lumbar spine). These gender- and body-site-specific factors need to be considered for the prevention and management of osteoporosis. Acknowledgments The authors wish to thank Mi Sun Ryu, BS, and Hyun Mi Kim, BS, for their technical support. This research was supported by the Ministry of Trade, Industry and Energy of Korea (Grant No. 10045220). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Conflict of interest declare.
The authors have no conflicts of interest to
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ORIGINAL ARTICLE
Gender- and body-site-specific factors associated with bone mineral density in a non-institutionalized Korean population aged ‡50 years Kyoung Min Lee • Soon-Sun Kwon • Chin Youb Chung • Seung Yeol Lee • Tae Gyun Kim • Young Choi • Moon Seok Park
Received: 23 December 2013 / Accepted: 8 May 2014 Ó The Japanese Society for Bone and Mineral Research and Springer Japan 2014
Abstract The aim of this study was to investigate the gender- and body-site-specific factors associated with bone mineral density (BMD) at the femoral neck and lumbar spine in a non-institutionalized population aged C50 years characterized by low average calcium intake. The comprehensive data utilized were from the 2010 Fifth Korea National Health and Nutrition Examination Survey, which included health behavior questionnaire, blood and urine tests, dual-energy X-ray absorptiometry, and nutrition intake. The factors associated with BMD at the femoral neck and lumbar spine in both genders were analyzed separately using multiple regression analysis with a stepwise selection. The average daily calcium intake in the
K. M. Lee C. Y. Chung M. S. Park (&) Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, 300 Gumi-Dong, Bundang-Gu, Sungnam, Kyungki 463-707, South Korea e-mail: [email protected] S.-S. Kwon Biomedical Research Institute, Seoul National University Bundang Hospital, 300 Gumi-Dong, Bundang-Gu, Sungnam, Kyungki 463-707, South Korea S. Y. Lee Department of Orthopaedic Surgery, Myongji Hospital, 697-24 Hwajung-Dong, Deokyang-Gu, Goyang, Kyungki 412-270, South Korea T. G. Kim Department of Orthopaedic Surgery, Konyang University Hospital, 685 Gasuwon-Dong Seo-Gu, Metropolitan City Daejon 302-718, South Korea Y. Choi Department of Orthopaedic Surgery, Gwanghye General Hospital, 96 Chungyeoldae-Ro, Dongrae-Gu, Metropolitan City Pusan 607-713, South Korea
male subjects was 565.8 mg and in the female subjects was 443.7 mg. In multiple regression analysis, age, body mass index (BMI), alkaline phosphatase (ALP), lead, daily calcium intake, and cadmium were the significant factors associated with femoral neck BMD in male subjects. BMI, creatinine (Cr), total body fat percentile, lead, ALP, and hypertension were found to be the significant factors associated with lumbar spine BMD in male subjects. In the female subjects, the significant factors associated with femoral neck BMD were age, BMI, ALP, house income, and total body fat percentile, while menopause, Cr, mercury, house income, BMI, and ALP were found to be the significant factors associated with lumbar spine BMD. In conclusion, different factors were associated with BMD depending on gender and the body site tested (femoral neck or lumbar spine). These gender- and body-site-specific factors need to be considered for the prevention and management of osteoporosis. Keywords Determinants Bone mineral density Lumbar spine Femoral neck Gender
Introduction Hip and spine fractures, known for their morbidity and mortality, both represent fractures caused by osteoporosis [1–5]. However, from a clinical perspective, these two types of fractures are different in terms of management strategies and anatomical structures involved. Hip fractures usually require surgical intervention, whereas spine fractures are managed with conservative treatment or minimally invasive surgical intervention such as vertebroplasty or kyphoplasty [6–9]. Moreover, hip fractures involve the proximal femur, which consists of a considerable amount
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of cortical bone, whereas spine fractures involve vertebral bones, the majority of which consist of cancellous bone [10]. Bone mineral density (BMD) is an important predictor of osteoporotic fractures [11–15], and the current medical treatment for osteoporosis is therefore focused on increasing BMD [16–19], although the final clinical goals of treatment are the reduction of fracture incidence and the associated morbidity. Determinants of BMD have been investigated multilaterally in previous studies in terms of several factors such as genetic, ethnic, nutritional, metabolic, and mechanical factors [20–28]. However, the results of previous studies have been inconsistent as regards the effects of smoking [22, 24, 29–31], physical activity [22, 24, 32, 33], dietary calcium intake [22, 24, 33, 34], and alcohol [22, 24, 29, 33, 35]. These results have led to confusion among clinicians with regard to the determination of treatment guidelines in the management of osteoporosis. It may be possible to resolve these uncertainties and reduce the effect of confounding variables, at least in part, by stratifying the determinants of BMD according to crucial variables (gender and body site such as hip and spine). Considering the differences between hip and spine fractures and the influence of gender, a study to investigate gender- and site-specific factors associated with BMD at the hip and spine could provide valuable clinical information regarding prevention and management of osteoporosis. In the present study, we aimed to investigate factors associated with BMD at the femoral neck and lumbar spine based on gender in a non-institutionalized population aged C50 years using data from the Korea National Health and Nutrition Examination Survey (KNHNES).
Materials and methods Subjects This study utilized a cross-sectional and nationally representative database, the Fifth Korea National Health and Nutrition Examination Survey, conducted by the Korean Centers for Disease Control and Prevention in 2010 (KNHNES V 2010). The Korean Centers for Disease Control and Prevention attempted to collect a representative sample of Korean individuals from stratified, multistage probability samples of Korean households representing the civilian, non-institutionalized population. The data were weighted according to sampling and response rates, and adjusted for gender and age group structures of the parent population. The survey comprised 4 components: health interview, health behavior, health
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Fig. 1 Flow diagram of inclusion and exclusion criteria in the Fifth Korea National Health and Nutrition Examination Survey (KNHNES V). A total of 1940 subjects were finally included
examination, and nutrition. A total of 10533 individuals (82.8 %) out of the 12722 people (aged C50 years) who were selected from the database agreed to participate in the study. Those with incomplete data for a standardized physical examination, laboratory tests (blood and urine), lifestyle questionnaire, and dual-energy X-ray absorptiometry (DXA), and those with a current diagnosis of cancer were excluded from the study. Subjects who were receiving osteoporosis medication, oral contraceptives, or hormone replacement therapy were also excluded from the data analysis (Fig. 1). A written informed consent was
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obtained from all participants by the Korean Centers for Disease Control and Prevention, and the study was exempt from approval by the institutional review board of Seoul National University Bundang Hospital, as the study utilized a publicly accessible database. Data collection This study utilized the KNHNES V 2010 database for collection of demographics including age, gender, body mass index (BMI), weight change in the past year (categories: gain [10 kg, gain between 6 and 10 kg, gain between 3 and 6 kg, gain \3 kg, no change, loss \3 kg, loss between 3 and 6 kg, loss between 6 and 10 kg, loss [10 kg), house income (below the 25th percentile, between the 25th and the 50th percentiles, between the 50th and the 75th percentiles, more than the 75th percentile), menopause, duration of menstruation (in months), amount of smoking (current and cumulative), amount of alcohol consumption in the past year, and presence of other medical conditions [hypertension (HT), coronary artery disease (CAD), cerebrovascular accident (CVA), osteoarthritis (OA) and chronic renal failure (CRF)]. The parameters of height, weight, and waist circumference were measured using standardized instruments, and BMI was calculated from the height and the weight. Weight changes in the past year were obtained from the questionnaire. The categories of house income were based on the total house income reported by the subjects. The duration of menstruation in the subjects was calculated by subtracting the age of menarche from the current age (in premenopausal women) or age of menopause in postmenopausal women, for which the ages were obtained from the questionnaire. The amount of cumulative smoking was calculated from the amount of daily smoking and the duration of smoking, which were included in the questionnaire. The amount of alcohol consumption was calculated using the data of average frequency of drinking and the average amount of drinking per session (in glasses) obtained from the questionnaire, with the assumption that 1 glass contains 10 g of alcohol. The presence of other medical conditions (HT, CAD, and CVA) was determined from the diagnoses obtained from the questionnaire, which was based on the self-reported medical conditions. The diagnosis of osteoarthritis was based on examination of radiographs of the hip and the knee (Kellgren–Lawrence grade) and the subjects’ report of arthritic symptoms. Activity level was evaluated by the short form of the International Physical Activity Questionnaire (IPAQ-SF) [36], which provided the duration of vigorous-intensity, moderate-intensity, and walking activities per week as well as the total metabolic equivalent (MET). Physical activity
that required hard physical effort and resulted in the subject breathing much harder than normal was considered a vigorous-intensity activity and that which required moderate physical effort and resulted in the subject breathing somewhat harder than normal was considered a moderateintensity activity. The total MET was calculated using the equation (8.0 9 minutes of vigorous-intensity activity/ week) ? (4.0 9 minutes of moderate-intensity activity/ week) ? (3.3 9 minutes of walking/week). Blood tests for levels of fasting blood sugar (FBS), glycosylated hemoglobin (HbAlc), insulin, total cholesterol, high-density lipoprotein (HDL) cholesterol, lowdensity lipoprotein (LDL) cholesterol, triglyceride, hemoglobin (Hb), creatinine (Cr), 25-hydroxyvitamin D [25(OH)D], alkaline phosphatase (ALP), parathyroid hormone (PTH), and heavy metals (lead, mercury, and cadmium) were performed. In addition, urine tests for urine cotinine were performed. Blood and urine samples were obtained throughout the year after an 8-h fast, and immediately processed, refrigerated, and transported in cold storage to the central testing institute (NeoDin Medical Institute, Seoul, South Korea), where they were analyzed within 24 h. The amount of daily calcium intake was calculated using the Food Composition Table developed by the National Rural Resources Development Institute (7th revision) [37, 38], based on a 24-h dietary recall questionnaire administered by a dietician. Daily energy intake was recorded, and calcium density (calcium intake per unit energy intake) was calculated. BMD (g/cm2) was measured at the femoral neck and the lumbar spine by DXA (Discovery-W fan-beam densitometer; Hologic Inc., Marlborough, MA, USA) with coefficients of variation of 1.9 and 2.5 %, respectively. The total body fat percentile was also measured. Data analysis The subjects were divided into 2 groups according to their gender. The continuous or categorical variables that had a significant correlation with the femoral neck and the lumbar spine BMDs were examined separately for each group. Moreover, the femoral neck and lumbar spine BMDs of those with other medical conditions (HT, CAD, CVA, OA, and CRF) were compared with the BMDs of those without these conditions. The variables that were significantly correlated with BMD or the conditions wherein the BMD was significantly different between cases where the condition was present and absent were selected, and included in the multiple regression analysis. The factors that influenced the BMDs of the femoral neck and the lumbar spine were evaluated using multiple regression analysis in each gender group, and were categorized as associated factors with BMDs.
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Statistical analysis A descriptive analysis of the entire dataset, including average and standard deviations (SDs) or proportions, was performed. The data were assessed for normality using the Kolmogorov–Smirnov test. Correlations between the variables and BMDs of the femoral neck and the lumbar spine were evaluated using the Pearson correlation coefficient or Spearman correlation coefficient, depending on the normality of the data. The comparison of BMDs between those with other medical conditions and those without these conditions was performed using Student’s t test. A stepwise selection of the variables was adopted in the multiple regression analysis. The variables that were significantly correlated with BMDs and the conditions wherein the BMD was significantly different between cases where the condition was present and absent were included as independent variables, whereas the BMDs of the femoral neck and the lumbar spine were the dependent variables in the multiple regression analysis in each gender. All statistical analyses were performed using SPSS 18.0 (SPSS Inc., Chicago, IL, USA), and statistical significance was set at p \ 0.05.
Results A total of 1940 subjects (1096 males, 844 females) were included in the final data analysis. The average ages of the male and female subjects were 63.2 (SD 8.7 years) and 62.9 years (SD 9.8 years), respectively. The average daily calcium intake in the male subjects was 565.8 mg and in the female subjects was 443.7 mg, and average calcium density was 0.18 and 0.16 mg/kcal in males and females, respectively. The average femoral neck BMDs of the male and female subjects were 0.7451 (SD 0.1175 g/cm2) and 0.6284 g/cm2 (SD 0.1172 g/ cm2), respectively, and the average lumbar spine BMDs were 0.9467 (SD 0.1565 g/cm2) and 0.8059 g/cm2 (SD 0.1517 g/ cm2), respectively (Table 1). In the male group, the candidate factors that were significantly associated with femoral neck BMD were age, BMI, house income, cumulative amount of smoking, total MET, FBS, total cholesterol, Hb, ALP, lead, cadmium, urine cotinine, and daily calcium intake amount. Age, BMI, house income, FBS, insulin, HDL cholesterol, Cr, ALP, lead, daily calcium intake amount, total body fat percentile, and HT were the candidate factors significantly associated with lumbar spine BMD in male subjects (Table 2). In the female group, the factors shown to have a significant association with the femoral neck BMD were age, BMI, weight change in the past year, house income, menopause, duration of menstruation, amount of alcohol consumption in
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the past year, total MET, HDL cholesterol, triglyceride, Hb, ALP, mercury, daily calcium intake amount, total body fat percentile, and the presence of HT and OA. The factors shown to have a significant association with the lumbar spine BMD in the female group were age, BMI, weight change in the past year, house income, menopause, duration of menstruation, amount of alcohol consumption in the past year, HDL cholesterol, Cr, ALP, mercury, daily calcium intake, and total body fat percentile (Table 2). In multiple regression analysis using a stepwise selection, age, BMI, ALP, lead, daily calcium intake, and cadmium were the significant factors associated with femoral neck BMD in male subjects (Table 3). BMI, Cr, total body fat percentile, lead, ALP, and HT were found to be the significant factors associated with lumbar spine BMD in male subjects (Table 4). In the female subjects, the significant factors associated with femoral neck BMD were age, BMI, ALP, house income, and total body fat percentile (Table 5), while menopause, Cr, mercury, house income, BMI, and ALP were found to be the significant associated factors with lumbar spine BMD (Table 6).
Discussion In the present study, we investigated gender-specific factors associated with BMD of the femoral neck and the lumbar spine in subjects aged C50 years. The KNHANES V 2010 database, utilized for subject selection, included comprehensive variables, and the authors endeavored to include as many clinical variables as possible to exclude or adjust the effects of potential confounding factors. BMI and ALP were associated with BMD of the femoral neck and lumbar spine in both genders. Age was associated with femoral neck BMD in both genders, and Cr was associated with lumbar spine BMD in both genders. Lead was associated with both femoral neck and lumbar spine BMD in male subjects and house income was associated with both femoral neck and lumbar spine BMD in female subjects (Fig. 2). The characteristics of the study population with regard to calcium metabolism need to be defined prior to a detailed interpretation of the results. The average daily calcium intake in the male subjects was 565.8 mg and in the female subjects was 443.7 mg. The average serum 25(OH)D level in the male subjects was 20.9 ng/mL and in the female subjects was 17.8 ng/mL. The average serum PTH level in the male subjects was 67.3 pg/mL and in the female subjects was 70.3 pg/mL. Therefore, our study population showed a low average calcium intake and a low serum 25(OH)D level, which might be compensated for by a high PTH level, to maintain the serum calcium level. Thus, we believe that a catabolic environment in terms of bone metabolism may be present in such patients.
J Bone Miner Metab Table 1 Data summary
Male subjects
Female subjects
No.
1096
844
Age (years)
63.2 (8.7)
62.9 (9.8)
BMI (kg/cm2)
23.7 (2.9)
24.2 (3.4)
Weight change ([10 kg gain/6–10 kg gain/3–6 kg gain/0–3 kg gain/no change/0–3 kg loss/3–6 kg loss/6–10 kg loss/[10 kg loss)
1/6/59/858/140/21/11
5/11/86/622/100/15/5
House income (0–25/25–50/50–75/75–100 percentiles)
300/285/251/260
296/213/159/176
Menopause (yes/no)
NA
771/73
Duration of menstruation (months) Cumulative amount of smoking (pack)
NA 4510.4 (7173.0)
396.6 (64.7) 69.3 (1000.3)
Amount of alcohol consumption (g/day)
14.3 (20.2)
2.5 (6.6)
HT (yes/no)
400/696
320/524
CAD (yes/no)
66/1030
38/806
CVA (yes/no)
30/1066
9/835
OA (yes/no)
72/1024
184/649
3142.5 (4463.5)
2452.7 (4175.7)
FBS (mg/dL)
105.4 (26.8)
99.7 (21.1)
HbAlc (%)
7.3 (1.4)
7.2 (1.3)
Insulin (lIU/mL)
10.2 (5.2)
10.7 (4.9)
Total cholesterol (mg/dL)
186.4 (36.2)
203.5 (36.5)
HDL cholesterol (mg/dL) LDL cholesterol (mg/dL)
48.7 (12.4) 110.7 (31.6)
53.0 (12.7) 127.4 (28.9)
Medical diseases
Activity Weekly total MET Blood test
Data are presented as mean (standard deviation) BMI body mass index, HT hypertension, CAD coronary artery disease, CVA cerebrovascular accident, OA osteoarthritis, MET metabolic equivalent, FBS fasting blood sugar, HbAlc glycosylated hemoglobin, HDL high-density lipoprotein, LDL low-density lipoprotein, Hb hemoglobin, Cr creatinine, 25(OH)D 25hydroxyvitamin D, ALP alkaline phosphatase, PTH parathyroid hormone, BMD bone mineral density, NA not applicable
Triglyceride (mg/dL)
161.8 (151.5)
134.7 (79.7)
Hb (g/dL)
14.9 (1.3)
13.1 (1.1)
Cr (mg/dL)
0.97 (0.23)
0.71 (0.13)
25(OH)D (ng/mL)
20.9 (7.3)
17.8 (6.7)
ALP (IU/L)
241.4 (67.4)
257.9 (78.6)
PTH (pg/mL)
67.3 (27.9)
70.3 (28.9)
Lead (lg/dL)
3.3 (1.5)
2.4 (0.8)
Mercury (lg/L)
6.5 (5.0)
4.3 (3.1)
Cadmium (lg/L)
1.2 (0.6)
1.6 (0.7)
Urine cotinine (lg/mL)
606.0 (971.9)
72.1 (297.2)
Daily calcium intake amount (mg)
565.8 (328.8)
443.7 (341.5)
Daily energy intake (kcal)
3391.5 (1264.5)
2887.2 (1126.2)
Calcium density (mg/kcal)
0.18 (0.10)
0.16 (0.11)
0.7451 (0.1175) 0.9467 (0.1565)
0.6284 (0.1172) 0.8059 (0.1517)
Heavy metals
2
BMD (femoral neck) (g/cm ) BMD (lumbar spine) (g/cm2)
BMI and ALP levels were the significant determinants of BMD at the femoral neck and the lumbar spine in both genders (Fig. 2). Although ALP is produced by several organs including the liver, bile duct, kidneys, and bone, it is primarily known to be associated with osteoblastic activity in bone metabolism [39]. The study results showed that the ALP level was significantly associated with BMD in the
population with low average calcium intake, with negative correlations of ALP with femoral neck and lumbar spine BMDs in both genders. These results are supported by previous studies that reported increased ALP activity in women with a more severe osteoporosis [40, 41]. BMI was another significant factor associated with BMD at the hip and the lumbar spine in both genders. This result is
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J Bone Miner Metab Table 2 Candidate factors significantly affecting BMDs of femoral neck and lumbar spine in each gender Male
Female
Femoral neck
Lumbar spine
Femoral neck
Lumbar spine
Age (r = -0.377, p \ 0.001)
Age (r = -0.078, p = 0.010)
Age (r = -0.629, p \ 0.001)
Age (r = -0.462, p \ 0.001)
BMI (r = 0.356, p \ 0.001)
BMI (r = 0.345, p \ 0.001)
BMI (r = 0.262, p \ 0.001)
BMI (r = 0.280, p \ 0.001)
House income (r = 0.258, p \ 0.001)* Cumulative amount of smoking (r = -0.079, p = 0.009)
House income (r = 0.164, p \ 0.001)* FBS (r = 0.138, p \ 0.001)
Weight change (r = 0.154, p \ 0.001)* House income (r = 0.289, p \ 0.001)*
Weight change (r = 0.119, p = 0.001)* House income (r = 0.258, p \ 0.001)*
Total MET (r = 0.073, p = 0.015)
Insulin (r = 0.113, p \ 0.001)
Menopause (p \ 0.001)
Menopause (p \ 0.001)
FBS (r = 0.090, p = 0.003)
HDL cholesterol (r = 0.103, p = 0.001)
Duration of menstruation (r = 0.268, p \ 0.001)*
Duration of menstruation (r = 0.236, p \ 0.001)*
Total cholesterol (r = 0.071, p = 0.022)
Cr (r = 0.110, p \ 0.001)
Amount of alcohol consumption (r = 0.112, p = 0.001)
Amount of alcohol consumption (r = 0.068, p = 0.048)
Hb (r = 0.158, p \ 0.001)
ALP (r = -0.153, p \ 0.001)
Total MET (r = 0.114, p = 0.001)
HDL cholesterol (r = 0.087, p = 0.015)
ALP (r = -0.216, p \ 0.001)
Lead (r = -0.130, p = 0.016)
HDL cholesterol (r = 0.151, p \ 0.001)
Cr (r = 0.074, p = 0.039)
Lead (r = -0.116, p = 0.032)
Daily calcium intake (r = 0.145, p \ 0.001)
Triglyceride (r = -0.098, p = 0.006)
ALP (r = -0.286, p \ 0.001)
Cadmium (r = -0.164, p = 0.002)
Total body fat percentile (r = 0.145, p \ 0.001)
Hb (r = 0.094, p = 0.009)
Mercury (r = 0.195, p = 0.007)
Urine cotinine (r = -0.114, p = 0.037)
HT (p = 0.001)
ALP (r = -0.235, p \ 0.001)
Daily calcium intake (r = 0.124, p \ 0.001)
Mercury (r = 0.197, p = 0.006)
Total body fat percentile (r = 0.172, p \ 0.001)
Daily calcium intake (r = 0.227, p \ 0.001)
Daily calcium intake (r = 0.172, p \ 0.001) Total body fat percentile (r = 0.113, p = 0.001) HT (p \ 0.001) OA (p = 0.001) BMI body mass index, MET metabolic equivalent, FBS fasting blood sugar, Hb hemoglobin, ALP alkaline phosphatase, HDL high-density lipoprotein, Cr creatinine, HT hypertension, OA osteoarthritis * Spearman correlation test
Table 3 Multiple regression analysis to identify significant determinants of femoral neck BMD in male subjects B
t
p value
Age
-0.005
-5.9
\0.001
BMI
0.009
4.4
\0.001
ALP
0.000
-3.3
0.001
Lead
-0.012
-2.6
0.009
0.003
2.3
0.020
-0.020
-2.1
0.039
0.950
11.8
\0.001
Daily calcium intake Cadmium Coefficient 2
R = 0.260 BMI body mass index, ALP alkaline phosphatase
concurrent with previous studies that have reported that weight or BMI is a protective factor for osteoporosis [22, 24, 25, 42].
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The age of the subjects was found to be a significant factor associated with BMD at the femoral neck, but not at the lumbar spine, in both genders. This result is supported by a previous study which reported that hip BMD declined and spine BMD increased with advancing age [22]. On the other hand, menopause was significantly associated with lumbar spine BMD alone. Considering that the femoral neck has a higher proportion of cortical bone than the lumbar spine and the lumbar spine has a higher proportion of cancellous bone than the femoral neck, cortical bone could be more affected by age than cancellous bone, whereas cancellous bone tended to be more affected by estrogen levels. Thus, it could be hypothesized that postmenopausal osteoporosis is likely to involve cancellous bone, whereas senile osteoporosis is likely to involve cortical bone. However, this issue needs further investigation.
J Bone Miner Metab Table 4 Multiple regression analysis to identify significant determinants of lumbar spine BMD in male subjects B BMI
t
p value
0.016
4.5
\0.001
0.162
4.2
\0.001
Total body fat percentile
-0.007
-3.7
\0.001
Lead
-0.016
-2.7
0.008
ALP
0.000
-2.6
0.009
HT
0.042
2.5
0.012
Coefficient
0.692
8.3
\0.001
Cr
2
R = 0.171 ALP alkaline phosphatase, FBS fasting blood sugar, Cr creatinine, HT hypertension
Table 5 Multiple regression analysis to identify significant determinants of femoral neck BMD in female subjects B
t
p value
Age
-0.006
-6.1
\0.001
BMI ALP
0.012 0.000
5.1 -3.7
\0.001 \0.001
House income Total body fat percentile
0.018
3.1
0.002
-0.003
-2.5
0.013
0.877
11.1
\0.001
Coefficient 2
R = 0.405 BMI body mass index, ALP alkaline phosphatase
Table 6 Multiple regression analysis to identify significant determinants of lumbar spine BMD in female subjects B Menopause
t
p value \0.001
-0.141
-4.1
Cr
0.218
2.3
0.022
Mercury
0.007
2.4
0.016
House income
0.025
2.9
0.004
BMI
0.008
2.5
0.015
ALP
0.000
-2.4
0.018
Coefficient
0.893
6.9
\0.001
R2 = 0.281 ALP alkaline phosphatase, Cr creatinine
The daily calcium intake amount was a significant factor associated with femoral neck BMD in male subjects. Male subjects showed greater average daily calcium intake than female subjects. A possible explanation for the difference in the effect of calcium intake between the genders and body sites could be the difference in hormones and proportion of cortical bones or in the different levels of calcium intake between the genders, so that the small amount of calcium intake in female subjects may be below the
threshold level triggering a positive effect on the BMD. In addition, the lower calcium intake in women than in men could be explained, at least in part, by the different dietary behaviors seen in men and women [43, 44]. The Cr level was significantly associated with lumbar spine BMD in both genders but not with femoral neck BMD. Cr is a breakdown product of creatine phosphate in muscle, and is known to be produced at a constant rate by the body and filtered out of the body by the kidney [45]. Considering that our population had a small number of subjects with impaired renal function, the serum creatinine level reflected the muscle mass of the subjects. This result could be interpreted to imply that lumbar spine BMD, but not femoral neck BMD, is significantly affected by total body muscle mass. Currently, it is uncertain whether cancellous bone is more sensitive to the mechanical load caused by muscle contraction or whether the biological effect of muscle is involved in increasing cancellous bone mass. Our study showed that lead was a significant factor associated with BMD at both the femoral neck and lumbar spine in men. Although a gender-specific association between lead and bone mineral density could not be determined, it might be partly attributed to the difference in the serum lead levels between the genders. It has been reported that lead exerts actions directly on osteoblast and osteoclast function and indirectly via kidney dysfunction on bone turnover [46, 47]. A previous study reported the adverse effect of lead and cadmium on bone mineral density, which could possibly be associated with industrial pollution [48]. Another study showed that high blood mercury level was associated with a lower risk of having osteoporosis in postmenopausal women [49], which is concurrent with our result. Further study is required to investigate the role of heavy metals and industrial pollution in bone metabolism. House income was found to be a significant factor associated with BMD at the femoral neck and lumbar spine in female subjects. This is supported by the results of previous studies on nutritional deficiencies in the underprivileged population and adherence to osteoporosis medication according to house income in women [50–52]. The effect of physical activity, as a contributing factor to BMD, has been investigated in previous studies [20, 53]. This study evaluated physical activity using the IPAQ, and the effect of physical activity on BMD was not found to be significant. Our study population showed that low average calcium intake and low serum 25(OH)D level, which made the environment unfavorable for bone metabolism and could not be overcome by physical activity, were not significant factors associated with BMD. However, we were unable to provide a detailed explanation for this occurrence with the present data. The factors significantly associated with BMD according to gender and body site tested in this study are
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J Bone Miner Metab Fig. 2 Common determinants of BMD according to body site and gender. Weight and ALP are important determinants of BMD at the femoral neck and the lumbar spine in both genders
applicable only to the Korean elderly population with low average calcium intake. We consider that the risk factors for osteoporosis reported in previous studies varied because of the different characteristics of the study population, such as ethnicity, nutrition, environment, health habit, and genetic background, and the inclusion of variables. In this case, the explanatory power of the regression model needs to be the focus. Our regression model showed an R2 of 0.405 for femoral neck BMD in female subjects, which means that the model could explain 40.5 % of the variations seen in the Korean population. An improved regression model needs to be used to better explain BMD in future studies, including more feasible variables to be generalized to other populations with different characteristics. Lastly, we need to address the limitations of this study. This was a cross-sectional study, and therefore could not establish causality. In addition, although the study data were quite comprehensive, intake of medications such as steroids was not considered in the data analysis. Another limitation of this study was that the medical conditions of the participants were self-reported. The validity of self-reported medical conditions was not established in our study cohort. In conclusion, different factors were associated with BMD according to gender and body site tested (femoral neck and lumbar spine). These gender- and body-site-specific factors need to be considered for the prevention and management of osteoporosis. Acknowledgments The authors wish to thank Mi Sun Ryu, BS, and Hyun Mi Kim, BS, for their technical support. This research was supported by the Ministry of Trade, Industry and Energy of Korea (Grant No. 10045220). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Conflict of interest declare.
The authors have no conflicts of interest to
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