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Normal Reference for Bone Density in Healthy Chinese Children
Journal of Clinical Densitometry, vol. 10, no. 3, 266e275, 2007 Ó Copyright 2007 by The International Society for Clinical Densitometry 1094-6950/07/10:266e275/$32.00 DOI: 10.1016/j.jocd.2007.05.005
Original Article
Normal Reference for Bone Density in Healthy Chinese Children Hao Xu,* Jia-Xuan Chen, Jian Gong, Tian-Min Zhang, Qiu-Lian Wu, Zhong-Man Yuan, and Jin-Ping Wang Department of Nuclear Medicine, First Affiliated Hospital, Jinan University, Guangzhou, China
Abstract An ethnicity- and gender-specific normal reference database is necessary for the clinical dual-energy X-ray absorptiometry (DXA) assessment of skeletal status in Chinese children. We used a Lunar Prodigy DXA densitometer to measure bone mineral density (BMD), bone mineral content (BMC), and bone area (BA) at total body and subcranial skeleton for 877 healthy Chinese children (505 boys, 372 girls) aged 5e13 yr. The height-for-age, BAfor-height, and BMC-for-BA percentile curves were developed using the LMS method (L, power in Box-Cox transformation; M, median; S, coefficient of variation). We found that total body BMD and subcranial skeleton BMD were highly correlated (r 5 0.701e0.949), and that total body BMD was significantly higher than subcranial skeleton BMD for each gender and age group ( p ! 0.001). No gender differences in total body and subcranial skeleton BMD were found. Total body lean mass correlated highly with total body BMC and subcranial skeleton BMD and BMC (boys: r 5 0.888e0.953, girls: r 5 0.917e0.967) and moderately with total body BMD (boys: r 5 0.684, girls: r 5 0.777). The head region accounted for 16e52% and 16e49% of the total body BMC in boys and girls, respectively, and the percentages were negatively correlated with age (boys: r 5 0.824, girls: r 5 0.864) and height (boys: r 5 0.911, girls: r 5 0.922). Regression analyses showed that age explained more variance in subcranial skeleton BMD (boys: R2 5 0.641, girls: R2 5 0.685) than in total body BMD (boys: R2 5 0.387, girls: R2 5 0.472). In summary, we have presented an ethnicity- and gender-specific densitometric normal reference database for Chinese children aged 5e13 yr. It should allow for an appropriate clinical assessment of total body bone density in Chinese children as measured by the Lunar Prodigy DXA densitometer. Key Words: Bone mineral density; children; Chinese; DXA; normal reference.
with a low bone mass and are at increased risk of poor bone health (5). To evaluate skeletal status in children, the measurement of bone mineral density (BMD) in total body has been recommended by the International Society for Clinical Densitometry (6). Dual-energy X-ray absorptiometry (DXA) is widely considered the preferred method for assessing BMD in children because of its availability, speed, precision, and low radiation exposure (7e9). For BMD reporting, Z-scores, rather than T-scores, should be used in children, because they have not yet achieved peak bone mass (10). However, Z-scores are matched for age, sex, and ethnicity. In China, pediatric DXA utility is currently limited, due to a lack of normal reference values for Chinese children. Thus, an ethnicity-matched
Introduction Peak bone mass obtained during skeletal growth in childhood is a key factor in determining skeletal health in adult life (1). A low peak bone mass has been identified as an important risk factor for the development of osteoporosis and fractures later in life (2e4). Groups of pediatric patients with specific disorders, such as cystic fibrosis, inflammatory bowel disease, and type 1 diabetes mellitus, are associated Received 03/12/07; Revised 05/06/07; Accepted 05/22/07. *Address correspondence to: Hao Xu, MD, Department of Nuclear Medicine, First Affiliated Hospital, Jinan University, No. 613 West Huangpu Road, Guangzhou 510630, China. E-mail: txh@ jnu.edu.cn
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pediatric reference database needs to be established for use in Chinese children. One concerning problem with areal BMD measurement is that it tends to underestimate bone density in small subjects and overestimate it in larger subjects (11). The problem of size effects is particularly relevant in pediatric DXA and is now widely appreciated (5,11). For a more appropriate way of describing bone mass in children, one of the approaches to correct for size is to adjust height-for-age, bone area (BA)-for-height, and bone mineral content (BMC)-for-BA, to discriminate 3 possible clinical situations in which a low bone mass may occur as ‘‘short’’ bones, ‘‘narrow’’ bones, and ‘‘light’’ bones (12). Therefore, the aims of this study were to develop normal reference values of total body BMD and to construct percentile curves for BMC and bone size for clinical use in Chinese children.
Materials and Methods Subjects A total of 877 healthy school children (505 boys, 372 girls) were recruited from 4 local schools in Guangzhou, China.
The age range was 5.0e13.9 yr for both the participating boys and girls. All participating children were of Chinese ethnicity. Children were excluded from the study if they had (1) a history of metabolic disease or other medical disorders affecting bone growth and metabolism; (2) a history of use of medications affecting bone growth and metabolism; and (3) a history of fracture. Informed consent was obtained from all participants and their parents. The study protocol was approved by the Ethics Committee of the First Affiliated Hospital, Jinan University.
Anthropometric and DXA Measurements Anthropometric measurements were obtained for the children during the same visit for densitometry. Weight was measured using platform digital scales with a precision of 0.1 kg, and height was recorded with a stadiometer to the nearest 0.1 cm. Total body was measured with a Lunar Prodigy DXA bone densitometer (Lunar Corp., Madison, WI), and data were analyzed by specialized software Prodigy enCORE (ver. 8.80, standard-array mode). Analyzed parameters included BMD, BMC, and BA. The subcranial skeleton parameters were determined with the head region of interest removed from analysis. The precision for total body BMD
Table 1 Baseline Characteristics of the Participating Subjects by Gender and Age Group (Mean SD) Age group
n
Boys 5 6 7 8 9 10 11 12 13
41 64 34 56 68 91 68 55 28
Total
505
Girls 5 6 7 8 9 10 11 12 13
30 41 27 44 45 67 51 41 26
Total
372
Age (yr)
Height (cm)
Weight (kg)
BMI (kg/m2)
Lean mass (kg)
Body lean (%)
Fat mass (kg)
Body fat (%)
5.5 6.3 7.3 8.5 9.4 10.5 11.4 12.4 13.4
(0.3) (0.3) (0.3) (0.3) (0.3) (0.3) (0.3) (0.3) (0.3)
114.3 117.2 121.8 127.6 131.9 137.1 142.7 145.6 153.5
(5.6) (5.1) (7.1) (6.0) (5.2) (7.5) (7.3) (8.2)* (9.1)
18.2 19.5 22.0 24.5 27.3 29.7 32.7 35.3 39.5
(2.8)** (3.1) (4.0) (3.7) (6.3) (5.9) (6.9) (8.2) (7.2)
13.9 14.1 14.7 15.0 15.6 15.7 15.9 16.5 16.7
(1.3)** (1.4) (1.5) (1.6) (2.8) (2.1)** (2.2) (2.6) (2.3)
15.4 16.6 18.2 20.4 21.7 23.5 25.6 27.6 32.4
(1.8)*** (2.0)*** (2.2)** (2.0)** (2.4)** (3.1)* (3.9) (4.7) (6.1)
85.2 85.8 83.8 84.0 81.5 80.2 79.4 79.4 82.5
(4.8) (4.2)*** (5.8) (5.3)** (8.6) (7.3) (7.8) (8.0) (6.9)***
2.2 2.2 3.0 3.2 4.6 5.2 5.9 6.5 5.6
(1.4) (1.3)* (2.1) (2.0) (4.3) (3.5) (4.1) (4.7) (3.7)**
11.4 10.7 12.8 12.5 15.0 16.2 16.9 17.1 13.9
(4.9) (4.4)*** (5.9) (5.3)** (8.9) (7.5) (8.0) (8.2) (7.1)**
5.5 6.4 7.4 8.5 9.4 10.5 11.4 12.4 13.5
(0.3) (0.3) (0.3) (0.2) (0.3) (0.3) (0.3) (0.3) (0.3)
112.6 116.2 118.9 127.1 131.3 138.0 144.5 149.5 155.8
(6.0) (4.6) (6.8) (5.8) (6.7) (7.4) (6.7) (6.2) (7.5)
16.2 18.6 20.2 23.9 25.7 28.0 33.1 36.2 41.7
(1.9) (2.2) (2.7) (4.8) (5.6) (6.5) (6.5) (6.2) (7.1)
12.8 13.8 14.3 14.8 14.7 14.6 15.7 16.1 17.1
(1.0) (1.0) (1.7) (2.2) (1.9) (2.2) (2.2) (2.0) (1.9)
13.8 15.2 16.6 19.0 20.1 22.1 25.3 27.6 31.4
(1.5) (1.3) (1.5) (2.3) (2.9) (3.6) (3.6) (3.5) (3.9)
84.9 82.0 82.6 80.3 79.1 79.8 77.4 76.7 76.0
(2.9) (4.8) (5.1) (6.2) (5.7) (5.5) (6.5) (5.6) (5.6)
1.9 2.8 2.9 4.1 4.7 4.9 6.6 7.3 8.7
(0.6) (1.2) (1.6) (2.8) (2.8) (3.3) (3.3) (3.4) (3.9)
11.7 14.6 13.9 16.2 17.4 16.6 18.9 19.6 20.3
(3.0) (5.0) (5.2) (6.4) (5.8) (5.7) (6.7) (5.7) (5.8)
Abbr: BMI, body mass index; SD, standard deviation. *p ! 0.05, **p ! 0.01, ***p ! 0.001 compared with girls of the same age group (unpaired-sample t-tests). Journal of Clinical Densitometry
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was 0.5% (expressed as the root-mean-square percent coefficient of variation), and it was determined by duplicate scans with repositioning between each measurement in 30 volunteer subjects. Daily quality assurance scan was conducted by scanning an aluminum spine phantom according to the manufacturer’s instructions. All DXA measurements were performed by the same well-trained technologist throughout the study.
(13). The LMS method summarized the changing distribution by 3 curves representing the median (M ), coefficient of variation (S ), and the skewness (L) expressed as a Box-Cox power. These 3 values were estimated, and the curves could be developed using the formula:
Statistical Analysis
where Z is the Z-score corresponding to a given percentile. The percentile curves were constructed using the lmsChartMaker program (ver. 2.3; Medical Research Council, UK). All the tests were 2-tailed, and a p value of less than 0.05 was considered statistically significant.
Descriptive statistics were used to analyze baseline characteristics and measurements. Paired-sample t-tests were performed to compare the BMD of the total body and the subcranial skeleton for each gender and age group. Unpairedsample t-tests were used to find possible differences in various parameters between boys and girls of the same age group. Pearson’s correlation coefficients (r) were calculated to assess correlations among different variables. After evaluations of different models, the exponential model was found best fit for the association between age and bone measurements (BMD, BMC, and BA) for both genders. The corresponding coefficients of determination (R2) were also calculated. The height-for-age, BA-for-height, and BMC-for-BA percentile curves (3rd, 25th, 50th, 75th, and 97th) were developed by using the LMS method as described by Cole and Green
Measurement percentile 5 Mð1 þ LSZÞ
1=L
;
Results Table 1 summarizes the baseline characteristics of the participating subjects. Bone measurements (i.e., BMD, BMC, and BA) of the subjects are shown in Table 2. We found that total body BMD and subcranial skeleton BMD were highly correlated (r 5 0.701e0.949, p ! 0.001), and that total body BMD was also significantly higher than subcranial skeleton BMD for each gender and age group ( p ! 0.001). No significant differences in total body and subcranial skeleton BMD were found between boys and girls of the same age
Table 2 BMD, BMC, and BA of Total Body and Subcranial Skeleton by Gender and Age Group (Mean SD) Subcranial skeletona
Total body
Age group
n
BMD (g/cm2)
Boys 5 6 7 8 9 10 11 12 13
41 64 34 56 68 91 68 55 28
0.757 0.777 0.795 0.814 0.817 0.839 0.866 0.864 0.896
(0.046) (0.046) (0.047) (0.042) (0.047) (0.048) (0.054) (0.053) (0.058)
602.67 668.82 759.03 868.16 932.71 1043.05 1184.21 1224.16 1415.66
(96.11)* (118.97)* (137.25)* (127.17) (155.85) (174.03) (206.08) (244.02)* (257.94)
793.68 856.92 951.25 1063.96 1136.91 1237.84 1361.97 1409.07 1571.98
(96.68)** (112.33)* (140.53)* (124.03) (145.94) (156.18) (178.70) (211.92) (211.91)
0.585 0.608 0.633 0.663 0.682 0.715 0.747 0.760 0.804
(0.036) (0.044) (0.044) (0.037) (0.046) (0.053) (0.056) (0.063) (0.061)
343.24 395.55 467.85 560.63 629.69 727.59 852.22 907.18 1083.43
(72.55)* (92.04) (115.36) (105.03) (136.59) (157.37) (188.91) (232.59)* (243.66)
582.28 643.74 732.54 840.93 915.29 1008.44 1130.29 1180.36 1333.85
(90.96)* (104.79)* (132.60) (119.95) (141.64) (152.05) (173.05) (208.68)* (203.14)
Girls 5 6 7 8 9 10 11 12 13
30 41 27 44 45 67 51 41 26
0.751 0.769 0.782 0.799 0.809 0.824 0.867 0.889 0.925
(0.042) (0.028) (0.034) (0.047) (0.053) (0.047) (0.054) (0.070) (0.077)
553.97 623.25 690.30 822.25 901.38 992.98 1190.22 1333.02 1538.22
(75.84) (71.04) (89.53) (143.88) (191.21) (196.86) (213.79) (250.38) (282.12)
735.48 809.68 881.51 1023.92 1105.45 1198.00 1365.95 1490.35 1653.78
(74.76) (74.84) (90.55) (132.91) (165.37) (180.79) (187.38) (185.55) (206.47)
0.575 0.604 0.624 0.659 0.680 0.707 0.765 0.786 0.824
(0.031) (0.029) (0.028) (0.044) (0.057) (0.054) (0.059) (0.069) (0.073)
309.64 367.07 424.15 538.78 615.37 702.41 886.31 1006.07 1187.68
(51.70) (57.28) (68.05) (119.11) (165.61) (183.88) (201.67) (222.30) (251.82)
535.75 605.50 677.53 810.48 893.64 982.46 1148.20 1267.71 1427.35
(66.37) (70.08) (83.22) (127.71) (158.43) (175.26) (184.05) (182.36) (202.10)
BMC (g)
BA (cm2)
BMD (g/cm2)
BMC (g)
BA (cm2)
Abbr: BMD, bone mineral density; BMC, bone mineral content; BA, bone area; SD, standard deviation; ROI, region of interest. a Total body with the head ROI removed from analysis. *p ! 0.05, **p ! 0.01 compared with girls of the same age group (unpaired-sample t-tests). Journal of Clinical Densitometry
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Fig. 1. Scatterplots showing bone mineral density (BMD), bone mineral content (BMC), and bone area (BA) at the total body and the subcranial skeleton with regression curves ( p ! 0.001) for boys (n 5 505). group. Total body lean mass correlated highly with total body BMC and subcranial skeleton BMD and BMC (r 5 0.888e0.953 in boys, r 5 0.917e0.967 in girls, p ! 0.001) and moderately with total body BMD (r 5 0.684 in boys, r 5 0.777 in girls, p ! 0.001). The head region accounted for 16e52% and 16e49% of the total body BMC in boys and girls, respectively. Furthermore, the percentages were negatively correlated with age (r 5 0.824 in boys, r 5 0.864 in girls, p ! 0.001) and height (r 5 0.911 in boys, r 5 0.922 in girls, p ! 0.001). Journal of Clinical Densitometry
Figures 1 and 2 further illustrate the association between age and bone measurements in the participating boys and girls, respectively. In both genders, BMD, BMC, and BA increased with age at both the total body and the subcranial skeleton. Regression analyses showed that the head BMD accounted for most variance of total body BMD (R2 5 0.615 in boys, R2 5 0.716 in girls, p ! 0.001) but that age only accounted for less than 50% of the variance in total body BMD (R2 5 0.387 in boys, R2 5 0.472 in girls, p ! 0.001). Compared with total body BMD, the BMD of the subcranial Volume 10, 2007
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Fig. 2. Scatterplots showing bone mineral density (BMD), bone mineral content (BMC), and bone area (BA) at the total body and the subcranial skeleton with regression curves ( p ! 0.001) for girls (n 5 372).
skeleton was better predicted by age (R2 5 0.641 in boys, R2 5 0.685 in girls, p ! 0.001). Table 3 presents the percentile distribution of BMD of the total body and subcranial skeleton. The percentile distribution of total body and subcranial skeleton BMC is shown in Table 4. The gender-specific height-for-age and BA-forheight percentile curves are displayed in Figs. 3 and 4, respectively. In general, the percentile curves for the 2 genders Journal of Clinical Densitometry
were similar in shape. The BA-dependent percentile curves for BMC (Fig. 5) showed that BMC was closely associated with BA at both the total body and the subcranial skeleton.
Discussion Ethnicity difference in bone mineral acquisition for children has previously been reported (14e16), which justified Volume 10, 2007
Subcranial skeletona
Total body Age group
n
Min.
3rd
25th
50th
75th
97th
Max.
Min.
3rd
25th
50th
75th
97th
Max.
Boys 5 6 7 8 9 10 11 12 13
41 64 34 56 68 91 68 55 28
0.683 0.690 0.722 0.709 0.707 0.719 0.760 0.754 0.782
0.684 0.703 0.722 0.723 0.716 0.739 0.762 0.774 0.782
0.720 0.744 0.764 0.790 0.785 0.806 0.831 0.818 0.842
0.751 0.772 0.788 0.823 0.813 0.842 0.863 0.860 0.896
0.778 0.808 0.829 0.843 0.850 0.873 0.912 0.900 0.945
0.868 0.861 0.904 0.897 0.902 0.943 0.992 0.976 0.997
0.878 0.937 0.905 0.910 0.915 0.958 0.996 0.997 0.997
0.519 0.505 0.560 0.580 0.599 0.593 0.636 0.647 0.715
0.519 0.544 0.560 0.584 0.601 0.608 0.651 0.663 0.715
0.562 0.578 0.607 0.642 0.645 0.676 0.702 0.711 0.762
0.579 0.593 0.629 0.669 0.684 0.711 0.743 0.743 0.789
0.604 0.648 0.658 0.686 0.709 0.746 0.784 0.793 0.847
0.664 0.697 0.732 0.736 0.773 0.829 0.881 0.885 0.941
0.668 0.740 0.732 0.766 0.793 0.838 0.895 0.896 0.941
Girls 5 6 7 8 9 10 11 12 13
30 41 27 44 45 67 51 41 26
0.651 0.726 0.722 0.713 0.705 0.719 0.753 0.765 0.747
0.651 0.727 0.722 0.718 0.705 0.742 0.766 0.768 0.747
0.725 0.749 0.755 0.767 0.776 0.793 0.823 0.833 0.890
0.753 0.764 0.779 0.794 0.807 0.821 0.862 0.891 0.920
0.774 0.790 0.811 0.830 0.842 0.852 0.914 0.952 0.979
0.848 0.836 0.855 0.890 0.947 0.948 0.990 1.042 1.087
0.848 0.841 0.855 0.891 0.957 0.955 0.993 1.044 1.087
0.514 0.560 0.561 0.587 0.562 0.578 0.659 0.648 0.681
0.514 0.560 0.561 0.589 0.569 0.610 0.660 0.655 0.681
0.555 0.583 0.606 0.624 0.646 0.673 0.727 0.731 0.787
0.570 0.602 0.621 0.650 0.677 0.708 0.762 0.783 0.832
0.596 0.618 0.647 0.697 0.712 0.732 0.804 0.839 0.862
0.629 0.671 0.688 0.753 0.834 0.860 0.905 0.942 1.001
0.629 0.672 0.688 0.762 0.865 0.895 0.926 0.951 1.001
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Table 3 Percentile Distribution of BMD (g/cm2) for Total Body and Subcranial Skeleton by Gender and Age Group
Abbr: BMD, bone mineral density; ROI, region of interest. a Total body with the head ROI removed from analysis.
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Table 4 Percentile Distribution of BMC (g) for Total Body and Subcranial Skeleton by Gender and Age Group Subcranial skeletona
Total body Age group
n
Min.
3rd
25th
50th
75th
97th
Max.
Min.
3rd
25th
50th
75th
97th
Max.
Boys 5 6 7 8 9 10 11 12 13
41 64 34 56 68 91 68 55 28
390.49 443.32 556.77 596.02 624.38 641.63 752.52 819.42 1072.00
407.21 512.58 557.05 625.47 702.39 740.67 812.87 890.50 1072.00
538.37 583.29 653.89 794.84 798.97 916.81 1052.11 1049.63 1182.66
584.64 645.21 746.49 855.40 919.37 1042.47 1141.46 1157.54 1343.71
683.45 739.88 827.10 955.11 1043.06 1149.05 1274.53 1381.65 1701.16
799.99 913.99 1140.72 1179.88 1236.93 1428.17 1677.14 1820.76 1857.29
804.56 1076.47 1143.33 1282.26 1372.21 1494.27 1725.72 1887.10 1857.29
194.66 222.64 301.18 372.64 378.64 395.70 513.84 533.59 708.12
207.28 262.41 302.36 387.10 437.86 470.32 537.92 613.49 708.12
290.15 331.82 394.23 483.39 532.36 604.18 708.40 737.67 873.33
335.51 374.98 451.54 551.03 611.18 722.13 798.44 836.22 1016.91
393.19 448.53 517.23 629.86 707.88 813.50 923.45 1023.45 1319.08
523.43 624.79 794.44 829.37 946.25 1092.91 1318.60 1465.34 1537.80
529.93 675.03 796.68 904.15 1085.18 1187.05 1352.17 1541.80 1537.80
Girls 5 6 7 8 9 10 11 12 13
30 41 27 44 45 67 51 41 26
378.14 480.36 574.36 591.67 525.98 606.38 716.74 844.99 872.14
378.14 484.35 574.36 595.12 577.66 710.54 753.18 875.86 872.14
519.08 567.68 623.39 718.22 780.51 862.97 1050.65 1166.02 1375.21
550.70 619.22 677.06 784.14 867.53 976.68 1169.32 1308.12 1527.38
594.41 664.43 726.34 901.45 975.66 1049.78 1336.71 1493.62 1685.01
706.73 773.64 938.85 1206.44 1519.42 1553.72 1766.01 2045.57 2150.71
706.73 783.24 938.85 1220.33 1712.27 1852.20 1851.57 2118.49 2150.71
204.80 247.30 320.80 370.04 328.53 380.21 480.81 570.71 573.41
204.80 251.36 320.80 375.33 362.98 469.62 523.74 596.40 573.41
285.42 324.63 360.74 449.24 526.18 580.53 733.93 846.30 1042.34
307.96 366.82 414.65 512.56 597.40 672.20 898.64 993.79 1160.53
336.77 397.25 467.83 586.80 696.60 759.10 1012.87 1130.03 1333.99
420.50 483.29 613.92 853.14 1170.74 1214.85 1416.90 1634.74 1751.83
420.50 485.45 613.92 853.24 1358.19 1550.54 1525.35 1691.83 1751.83
Abbr: BMC, bone mineral content; ROI, region of interest. a Total body with the head ROI removed from analysis.
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Fig. 3. Height percentile curves adjusted for age. Solid lines from the upper one represent the 97th, 75th, 50th, 25th, and 3rd percentiles.
Fig. 4. Bone area (BA) percentile curves adjusted for height. Solid lines from the upper one represent the 97th, 75th, 50th, 25th, and 3rd percentiles.
the necessity to establish ethnicity specific reference databases for the interpretation of pediatric DXA results. Wang et al. (14) reported significant ethnic differences in bone mass in a cross-sectional study of 423 Asian, black, Hispanic, and non-Hispanic white American youths aged 9e25 yr. A follow-up study of this cohort further confirmed the ethnic differences (15). In a longitudinal study of 773 pretubertal children, Nelson et al. (16) found that black children have significantly higher whole body BMD and BMC than white children. For both genders in our study, the BMD, BMC, and BA of the total body and the subcranial skeleton increased with age, which is consistent with previous studies of other ethnic populations (17e23). However, the variation of DXA instruments, scan modes, analysis software, and
analysis modes among different studies makes it difficult to make a direct comparison between these published data. Our study results indicated that the head region accounted for a smaller percent of the total body BMC as age and height increased for both boys and girls. Willing et al. (24) revealed that the BMC of the head comprised a greater percentage of whole body BMC in small children compared to taller children. Taylor et al. (25) suggested that in normal children, age explained more variance in subtotal BMD than in total body BMD. They also found that head BMD accounted for most of the variance in total body BMD. Our findings are consistent with these patterns and suggest that the subcranial skeleton BMD may be an important indicator in reflecting skeletal status for children.
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Fig. 5. Bone mineral content (BMC) percentile curves adjusted for bone area (BA). Solid lines from the upper one represent the 97th, 75th, 50th, 25th, and 3rd percentiles. Our literature review indicated that evidence of gender differences in total body BMD and BMC remained inconsistent for children. In the present study, no significant differences in total body and subcranial skeleton BMD have been found between boys and girls aged 5e13 yr. Significant gender differences in total body BMC were observed at age 5e7 and 12 yr but were found only at age 5 and 12 yr for subcranial skeleton BMC. In a study of Canadian children aged 8e17 yr, Faulkner et al. (18) found no gender differences until age 16 for total body BMD and age 14 for BMC. Willing et al. (24) conducted a study on 428 Iowa children aged 4.5e6.5 yr which revealed that boys in general had significantly higher total body BMD and BMC, after adjustment for age, height, and weight. No significant gender differences were observed for subcranial skeleton BMC in their study (24). In a longitudinal study of Danish children aged 6e19 yr, Molgaard et al. (19) reported that the median annual accretion rate for whole body BMC was similar for both Journal of Clinical Densitometry
genders before puberty. In general, the normal reference database for pediatric DXA should be gender-specific (5). DXA measurements are 2-dimensional. Thus, the areal BMD is the ratio of BMC to BA, rather than a true bone density. A report by Wren et al. (26) indicated that more children were diagnosed as having low bone density based on BMD measurements obtained by DXA than by quantitative computed tomography. The size effects render the interpretation of pediatric DXA results more complicated. Various approaches have been proposed to correct for bone size, and there is currently no consensus on which approach is the most appropriate (11). In our study, we adopted Molgaard et al.’s method (12) to develop percentile curves for BMC and bone size in addition to normative BMD data. It is worthwhile mentioning some limitations of the current study. First, the participating subjects in our study were primarily southern Chinese children. No previous reports have Volume 10, 2007
Bone Density of Chinese Children indicated that total body BMD is significantly different between southern and northern Chinese children. However, to be better representative of the study population, a broader range of subjects may be needed. Second, our study ended with children aged 13 yr, an age at which they have not yet achieved peak bone mass. Therefore, further investigations in adolescents are necessary for establishing a complete pediatric normal reference database. Lastly, our study design is cross-sectional. To better study the bone mineral acquisition of normal Chinese children, longitudinal data need to be obtained. In summary, we have presented an ethnicity- and genderspecific densitometric normal reference database for Chinese children aged 5e13 yr. To the best of our knowledge, these are the first total body normal reference data for Chinese children. They should allow for an appropriate clinical assessment of total body bone density in Chinese children as measured by the Lunar Prodigy DXA densitometer.
Acknowledgment We would like to express our gratitude to all participating children and their parents. We also thank Dr. William Riley, for help in preparing the manuscript; and Mr. He Huang, Mr. Jin-Qiu Xie, and Ms. Dan Wang, for their excellent technical support. This study was supported in part by the Undergraduate Science Innovation Project of Jinan University.
References 1. Cooper C, Westlake S, Harvey N, Javaid K, Dennison E, Hanson M. 2006 Review: developmental origins of osteoporotic fracture. Osteoporos Int 17:337e347. 2. Hui SL, Slemenda CW, Johnston CC. 1990 The contribution of bone loss to postmenopausal osteoporosis. Osteoporos Int 1: 30e34. 3. Riggs BL, Khosla S, Melton LJ III. 1999 The assembly of the adult skeleton during growth and maturation: implications for senile osteoporosis. J Clin Invest 104:671e672. 4. Riggs BL, Melton LJ III, Robb RA, et al. 2004 Population-based study of age and sex differences in bone volumetric density, size, geometry, and structure at different skeletal sites. J Bone Miner Res 19:1945e1954. 5. Gordon CM. 2005 Evaluation of bone density in children. Curr Opin Endocrinol Diabetes 12:444e451. 6. Khan AA, Bachrach L, Brown JP, et al. 2004 Standards and guidelines for performing central dual-energy x-ray absorptiometry in premenopausal women, men, and children. J Clin Densitom 7:51e63. 7. Bachrach LK. 2005 Osteoporosis and measurement of bone mass in children and adolescents. Endocrinol Metab Clin North Am 34:521e535. 8. Margulies L, Horlick M, Thornton JC, Wang J, Ioannidou E, Heymsfield SB. 2005 Reproducibility of pediatric whole body bone and body composition measures by dual-energy X-ray absorptiometry using the GE Lunar Prodigy. J Clin Densitom 8: 298e304.
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275 9. Njeh CF, Fuerst T, Hans D, Blake GM, Genant HK. 1999 Radiation exposure in bone mineral density assessment. Appl Radiat Isot 50:215e236. 10. Leslie WD, Adler RA, El-Hajj Fuleihan G, et al. 2006 Application of the 1994 WHO classification to populations other than postmenopausal Caucasian women: the 2005 ISCD Official Positions. J Clin Densitom 9:22e30. 11. Fewtrell MS, British Paediatric & Adolescent Bone Group 2003 Bone densitometry in children assessed by dual x ray absorptiometry: uses and pitfalls. Arch Dis Child 88:795e798. 12. Molgaard C, Thomsen BL, Prentice A, Cole TJ, Michaelsen KF. 1997 Whole body bone mineral content in healthy children and adolescents. Arch Dis Child 76:9e15. 13. Cole TJ, Green PJ. 1992 Smoothing reference centile curves: the LMS method and penalized likelihood. Stat Med 11: 1305e1319. 14. Wang MC, Aguirre M, Bhudhikanok GS, et al. 1997 Bone mass and hip axis length in healthy Asian, black, Hispanic, and white American youths. J Bone Miner Res 12:1922e1935. 15. Bachrach LK, Hastie T, Wang MC, Narasimhan B, Marcus R. 1999 Bone mineral acquisition in healthy Asian, Hispanic, black, and Caucasian youth: a longitudinal study. J Clin Endocrinol Metab 84:4702e4712. 16. Nelson DA, Simpson PM, Johnson CC, Barondess DA, Kleerekoper M. 1997 The accumulation of whole body skeletal mass in third- and fourth-grade children: effects of age, gender, ethnicity, and body composition. Bone 20:73e78. 17. Zanchetta JR, Plotkin H, Alvarez Filgueira ML. 1995 Bone mass in children: normative values for the 2e20-year-old population. Bone 16:393Se399S. 18. Faulkner RA, Bailey DA, Drinkwater DT, McKay HA, Arnold C, Wilkinson AA. 1996 Bone densitometry in Canadian children 8e17 years of age. Calcif Tissue Int 59:344e351. 19. Molgaard C, Thomsen BL, Michaelsen KF. 1999 Whole body bone mineral accretion in healthy children and adolescents. Arch Dis Child 81:10e15. 20. Lazcano-Ponce E, Tamayo J, Cruz-Valdez A, et al. 2003 Peak bone mineral area density and determinants among females aged 9 to 24 years in Mexico. Osteoporos Int 14:539e547. 21. Arabi A, Nabulsi M, Maalouf J, et al. 2004 Bone mineral density by age, gender, pubertal stages, and socioeconomic status in healthy Lebanese children and adolescents. Bone 35: 1169e1179. 22. Pludowski P, Matusik H, Olszaniecka M, Lebiedowski M, Lorenc RS. 2005 Reference values for the indicators of skeletal and muscular status of healthy Polish children. J Clin Densitom 8:164e177. 23. Goksen D, Darcan S, Coker M, Kose T. 2006 Bone mineral density of healthy Turkish children and adolescents. J Clin Densitom 9:84e90. 24. Willing MC, Torner JC, Burns TL, et al. 2005 Percentile distributions of bone measurements in Iowa children: the Iowa Bone Development Study. J Clin Densitom 8:39e47. 25. Taylor A, Konrad PT, Norman ME, Harcke T. 1997 Total body bone mineral density in young children: influence of head bone mineral density. J Bone Miner Res 12:652e655. 26. Wren TA, Liu X, Pitukcheewanont P, Gilsanz V. 2005 Bone densitometry in pediatric populations: discrepancies in the diagnosis of osteoporosis by DXA and CT. J Pediatr 146: 776e779.
Volume 10, 2007
Original Article
Normal Reference for Bone Density in Healthy Chinese Children Hao Xu,* Jia-Xuan Chen, Jian Gong, Tian-Min Zhang, Qiu-Lian Wu, Zhong-Man Yuan, and Jin-Ping Wang Department of Nuclear Medicine, First Affiliated Hospital, Jinan University, Guangzhou, China
Abstract An ethnicity- and gender-specific normal reference database is necessary for the clinical dual-energy X-ray absorptiometry (DXA) assessment of skeletal status in Chinese children. We used a Lunar Prodigy DXA densitometer to measure bone mineral density (BMD), bone mineral content (BMC), and bone area (BA) at total body and subcranial skeleton for 877 healthy Chinese children (505 boys, 372 girls) aged 5e13 yr. The height-for-age, BAfor-height, and BMC-for-BA percentile curves were developed using the LMS method (L, power in Box-Cox transformation; M, median; S, coefficient of variation). We found that total body BMD and subcranial skeleton BMD were highly correlated (r 5 0.701e0.949), and that total body BMD was significantly higher than subcranial skeleton BMD for each gender and age group ( p ! 0.001). No gender differences in total body and subcranial skeleton BMD were found. Total body lean mass correlated highly with total body BMC and subcranial skeleton BMD and BMC (boys: r 5 0.888e0.953, girls: r 5 0.917e0.967) and moderately with total body BMD (boys: r 5 0.684, girls: r 5 0.777). The head region accounted for 16e52% and 16e49% of the total body BMC in boys and girls, respectively, and the percentages were negatively correlated with age (boys: r 5 0.824, girls: r 5 0.864) and height (boys: r 5 0.911, girls: r 5 0.922). Regression analyses showed that age explained more variance in subcranial skeleton BMD (boys: R2 5 0.641, girls: R2 5 0.685) than in total body BMD (boys: R2 5 0.387, girls: R2 5 0.472). In summary, we have presented an ethnicity- and gender-specific densitometric normal reference database for Chinese children aged 5e13 yr. It should allow for an appropriate clinical assessment of total body bone density in Chinese children as measured by the Lunar Prodigy DXA densitometer. Key Words: Bone mineral density; children; Chinese; DXA; normal reference.
with a low bone mass and are at increased risk of poor bone health (5). To evaluate skeletal status in children, the measurement of bone mineral density (BMD) in total body has been recommended by the International Society for Clinical Densitometry (6). Dual-energy X-ray absorptiometry (DXA) is widely considered the preferred method for assessing BMD in children because of its availability, speed, precision, and low radiation exposure (7e9). For BMD reporting, Z-scores, rather than T-scores, should be used in children, because they have not yet achieved peak bone mass (10). However, Z-scores are matched for age, sex, and ethnicity. In China, pediatric DXA utility is currently limited, due to a lack of normal reference values for Chinese children. Thus, an ethnicity-matched
Introduction Peak bone mass obtained during skeletal growth in childhood is a key factor in determining skeletal health in adult life (1). A low peak bone mass has been identified as an important risk factor for the development of osteoporosis and fractures later in life (2e4). Groups of pediatric patients with specific disorders, such as cystic fibrosis, inflammatory bowel disease, and type 1 diabetes mellitus, are associated Received 03/12/07; Revised 05/06/07; Accepted 05/22/07. *Address correspondence to: Hao Xu, MD, Department of Nuclear Medicine, First Affiliated Hospital, Jinan University, No. 613 West Huangpu Road, Guangzhou 510630, China. E-mail: txh@ jnu.edu.cn
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pediatric reference database needs to be established for use in Chinese children. One concerning problem with areal BMD measurement is that it tends to underestimate bone density in small subjects and overestimate it in larger subjects (11). The problem of size effects is particularly relevant in pediatric DXA and is now widely appreciated (5,11). For a more appropriate way of describing bone mass in children, one of the approaches to correct for size is to adjust height-for-age, bone area (BA)-for-height, and bone mineral content (BMC)-for-BA, to discriminate 3 possible clinical situations in which a low bone mass may occur as ‘‘short’’ bones, ‘‘narrow’’ bones, and ‘‘light’’ bones (12). Therefore, the aims of this study were to develop normal reference values of total body BMD and to construct percentile curves for BMC and bone size for clinical use in Chinese children.
Materials and Methods Subjects A total of 877 healthy school children (505 boys, 372 girls) were recruited from 4 local schools in Guangzhou, China.
The age range was 5.0e13.9 yr for both the participating boys and girls. All participating children were of Chinese ethnicity. Children were excluded from the study if they had (1) a history of metabolic disease or other medical disorders affecting bone growth and metabolism; (2) a history of use of medications affecting bone growth and metabolism; and (3) a history of fracture. Informed consent was obtained from all participants and their parents. The study protocol was approved by the Ethics Committee of the First Affiliated Hospital, Jinan University.
Anthropometric and DXA Measurements Anthropometric measurements were obtained for the children during the same visit for densitometry. Weight was measured using platform digital scales with a precision of 0.1 kg, and height was recorded with a stadiometer to the nearest 0.1 cm. Total body was measured with a Lunar Prodigy DXA bone densitometer (Lunar Corp., Madison, WI), and data were analyzed by specialized software Prodigy enCORE (ver. 8.80, standard-array mode). Analyzed parameters included BMD, BMC, and BA. The subcranial skeleton parameters were determined with the head region of interest removed from analysis. The precision for total body BMD
Table 1 Baseline Characteristics of the Participating Subjects by Gender and Age Group (Mean SD) Age group
n
Boys 5 6 7 8 9 10 11 12 13
41 64 34 56 68 91 68 55 28
Total
505
Girls 5 6 7 8 9 10 11 12 13
30 41 27 44 45 67 51 41 26
Total
372
Age (yr)
Height (cm)
Weight (kg)
BMI (kg/m2)
Lean mass (kg)
Body lean (%)
Fat mass (kg)
Body fat (%)
5.5 6.3 7.3 8.5 9.4 10.5 11.4 12.4 13.4
(0.3) (0.3) (0.3) (0.3) (0.3) (0.3) (0.3) (0.3) (0.3)
114.3 117.2 121.8 127.6 131.9 137.1 142.7 145.6 153.5
(5.6) (5.1) (7.1) (6.0) (5.2) (7.5) (7.3) (8.2)* (9.1)
18.2 19.5 22.0 24.5 27.3 29.7 32.7 35.3 39.5
(2.8)** (3.1) (4.0) (3.7) (6.3) (5.9) (6.9) (8.2) (7.2)
13.9 14.1 14.7 15.0 15.6 15.7 15.9 16.5 16.7
(1.3)** (1.4) (1.5) (1.6) (2.8) (2.1)** (2.2) (2.6) (2.3)
15.4 16.6 18.2 20.4 21.7 23.5 25.6 27.6 32.4
(1.8)*** (2.0)*** (2.2)** (2.0)** (2.4)** (3.1)* (3.9) (4.7) (6.1)
85.2 85.8 83.8 84.0 81.5 80.2 79.4 79.4 82.5
(4.8) (4.2)*** (5.8) (5.3)** (8.6) (7.3) (7.8) (8.0) (6.9)***
2.2 2.2 3.0 3.2 4.6 5.2 5.9 6.5 5.6
(1.4) (1.3)* (2.1) (2.0) (4.3) (3.5) (4.1) (4.7) (3.7)**
11.4 10.7 12.8 12.5 15.0 16.2 16.9 17.1 13.9
(4.9) (4.4)*** (5.9) (5.3)** (8.9) (7.5) (8.0) (8.2) (7.1)**
5.5 6.4 7.4 8.5 9.4 10.5 11.4 12.4 13.5
(0.3) (0.3) (0.3) (0.2) (0.3) (0.3) (0.3) (0.3) (0.3)
112.6 116.2 118.9 127.1 131.3 138.0 144.5 149.5 155.8
(6.0) (4.6) (6.8) (5.8) (6.7) (7.4) (6.7) (6.2) (7.5)
16.2 18.6 20.2 23.9 25.7 28.0 33.1 36.2 41.7
(1.9) (2.2) (2.7) (4.8) (5.6) (6.5) (6.5) (6.2) (7.1)
12.8 13.8 14.3 14.8 14.7 14.6 15.7 16.1 17.1
(1.0) (1.0) (1.7) (2.2) (1.9) (2.2) (2.2) (2.0) (1.9)
13.8 15.2 16.6 19.0 20.1 22.1 25.3 27.6 31.4
(1.5) (1.3) (1.5) (2.3) (2.9) (3.6) (3.6) (3.5) (3.9)
84.9 82.0 82.6 80.3 79.1 79.8 77.4 76.7 76.0
(2.9) (4.8) (5.1) (6.2) (5.7) (5.5) (6.5) (5.6) (5.6)
1.9 2.8 2.9 4.1 4.7 4.9 6.6 7.3 8.7
(0.6) (1.2) (1.6) (2.8) (2.8) (3.3) (3.3) (3.4) (3.9)
11.7 14.6 13.9 16.2 17.4 16.6 18.9 19.6 20.3
(3.0) (5.0) (5.2) (6.4) (5.8) (5.7) (6.7) (5.7) (5.8)
Abbr: BMI, body mass index; SD, standard deviation. *p ! 0.05, **p ! 0.01, ***p ! 0.001 compared with girls of the same age group (unpaired-sample t-tests). Journal of Clinical Densitometry
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was 0.5% (expressed as the root-mean-square percent coefficient of variation), and it was determined by duplicate scans with repositioning between each measurement in 30 volunteer subjects. Daily quality assurance scan was conducted by scanning an aluminum spine phantom according to the manufacturer’s instructions. All DXA measurements were performed by the same well-trained technologist throughout the study.
(13). The LMS method summarized the changing distribution by 3 curves representing the median (M ), coefficient of variation (S ), and the skewness (L) expressed as a Box-Cox power. These 3 values were estimated, and the curves could be developed using the formula:
Statistical Analysis
where Z is the Z-score corresponding to a given percentile. The percentile curves were constructed using the lmsChartMaker program (ver. 2.3; Medical Research Council, UK). All the tests were 2-tailed, and a p value of less than 0.05 was considered statistically significant.
Descriptive statistics were used to analyze baseline characteristics and measurements. Paired-sample t-tests were performed to compare the BMD of the total body and the subcranial skeleton for each gender and age group. Unpairedsample t-tests were used to find possible differences in various parameters between boys and girls of the same age group. Pearson’s correlation coefficients (r) were calculated to assess correlations among different variables. After evaluations of different models, the exponential model was found best fit for the association between age and bone measurements (BMD, BMC, and BA) for both genders. The corresponding coefficients of determination (R2) were also calculated. The height-for-age, BA-for-height, and BMC-for-BA percentile curves (3rd, 25th, 50th, 75th, and 97th) were developed by using the LMS method as described by Cole and Green
Measurement percentile 5 Mð1 þ LSZÞ
1=L
;
Results Table 1 summarizes the baseline characteristics of the participating subjects. Bone measurements (i.e., BMD, BMC, and BA) of the subjects are shown in Table 2. We found that total body BMD and subcranial skeleton BMD were highly correlated (r 5 0.701e0.949, p ! 0.001), and that total body BMD was also significantly higher than subcranial skeleton BMD for each gender and age group ( p ! 0.001). No significant differences in total body and subcranial skeleton BMD were found between boys and girls of the same age
Table 2 BMD, BMC, and BA of Total Body and Subcranial Skeleton by Gender and Age Group (Mean SD) Subcranial skeletona
Total body
Age group
n
BMD (g/cm2)
Boys 5 6 7 8 9 10 11 12 13
41 64 34 56 68 91 68 55 28
0.757 0.777 0.795 0.814 0.817 0.839 0.866 0.864 0.896
(0.046) (0.046) (0.047) (0.042) (0.047) (0.048) (0.054) (0.053) (0.058)
602.67 668.82 759.03 868.16 932.71 1043.05 1184.21 1224.16 1415.66
(96.11)* (118.97)* (137.25)* (127.17) (155.85) (174.03) (206.08) (244.02)* (257.94)
793.68 856.92 951.25 1063.96 1136.91 1237.84 1361.97 1409.07 1571.98
(96.68)** (112.33)* (140.53)* (124.03) (145.94) (156.18) (178.70) (211.92) (211.91)
0.585 0.608 0.633 0.663 0.682 0.715 0.747 0.760 0.804
(0.036) (0.044) (0.044) (0.037) (0.046) (0.053) (0.056) (0.063) (0.061)
343.24 395.55 467.85 560.63 629.69 727.59 852.22 907.18 1083.43
(72.55)* (92.04) (115.36) (105.03) (136.59) (157.37) (188.91) (232.59)* (243.66)
582.28 643.74 732.54 840.93 915.29 1008.44 1130.29 1180.36 1333.85
(90.96)* (104.79)* (132.60) (119.95) (141.64) (152.05) (173.05) (208.68)* (203.14)
Girls 5 6 7 8 9 10 11 12 13
30 41 27 44 45 67 51 41 26
0.751 0.769 0.782 0.799 0.809 0.824 0.867 0.889 0.925
(0.042) (0.028) (0.034) (0.047) (0.053) (0.047) (0.054) (0.070) (0.077)
553.97 623.25 690.30 822.25 901.38 992.98 1190.22 1333.02 1538.22
(75.84) (71.04) (89.53) (143.88) (191.21) (196.86) (213.79) (250.38) (282.12)
735.48 809.68 881.51 1023.92 1105.45 1198.00 1365.95 1490.35 1653.78
(74.76) (74.84) (90.55) (132.91) (165.37) (180.79) (187.38) (185.55) (206.47)
0.575 0.604 0.624 0.659 0.680 0.707 0.765 0.786 0.824
(0.031) (0.029) (0.028) (0.044) (0.057) (0.054) (0.059) (0.069) (0.073)
309.64 367.07 424.15 538.78 615.37 702.41 886.31 1006.07 1187.68
(51.70) (57.28) (68.05) (119.11) (165.61) (183.88) (201.67) (222.30) (251.82)
535.75 605.50 677.53 810.48 893.64 982.46 1148.20 1267.71 1427.35
(66.37) (70.08) (83.22) (127.71) (158.43) (175.26) (184.05) (182.36) (202.10)
BMC (g)
BA (cm2)
BMD (g/cm2)
BMC (g)
BA (cm2)
Abbr: BMD, bone mineral density; BMC, bone mineral content; BA, bone area; SD, standard deviation; ROI, region of interest. a Total body with the head ROI removed from analysis. *p ! 0.05, **p ! 0.01 compared with girls of the same age group (unpaired-sample t-tests). Journal of Clinical Densitometry
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Fig. 1. Scatterplots showing bone mineral density (BMD), bone mineral content (BMC), and bone area (BA) at the total body and the subcranial skeleton with regression curves ( p ! 0.001) for boys (n 5 505). group. Total body lean mass correlated highly with total body BMC and subcranial skeleton BMD and BMC (r 5 0.888e0.953 in boys, r 5 0.917e0.967 in girls, p ! 0.001) and moderately with total body BMD (r 5 0.684 in boys, r 5 0.777 in girls, p ! 0.001). The head region accounted for 16e52% and 16e49% of the total body BMC in boys and girls, respectively. Furthermore, the percentages were negatively correlated with age (r 5 0.824 in boys, r 5 0.864 in girls, p ! 0.001) and height (r 5 0.911 in boys, r 5 0.922 in girls, p ! 0.001). Journal of Clinical Densitometry
Figures 1 and 2 further illustrate the association between age and bone measurements in the participating boys and girls, respectively. In both genders, BMD, BMC, and BA increased with age at both the total body and the subcranial skeleton. Regression analyses showed that the head BMD accounted for most variance of total body BMD (R2 5 0.615 in boys, R2 5 0.716 in girls, p ! 0.001) but that age only accounted for less than 50% of the variance in total body BMD (R2 5 0.387 in boys, R2 5 0.472 in girls, p ! 0.001). Compared with total body BMD, the BMD of the subcranial Volume 10, 2007
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Fig. 2. Scatterplots showing bone mineral density (BMD), bone mineral content (BMC), and bone area (BA) at the total body and the subcranial skeleton with regression curves ( p ! 0.001) for girls (n 5 372).
skeleton was better predicted by age (R2 5 0.641 in boys, R2 5 0.685 in girls, p ! 0.001). Table 3 presents the percentile distribution of BMD of the total body and subcranial skeleton. The percentile distribution of total body and subcranial skeleton BMC is shown in Table 4. The gender-specific height-for-age and BA-forheight percentile curves are displayed in Figs. 3 and 4, respectively. In general, the percentile curves for the 2 genders Journal of Clinical Densitometry
were similar in shape. The BA-dependent percentile curves for BMC (Fig. 5) showed that BMC was closely associated with BA at both the total body and the subcranial skeleton.
Discussion Ethnicity difference in bone mineral acquisition for children has previously been reported (14e16), which justified Volume 10, 2007
Subcranial skeletona
Total body Age group
n
Min.
3rd
25th
50th
75th
97th
Max.
Min.
3rd
25th
50th
75th
97th
Max.
Boys 5 6 7 8 9 10 11 12 13
41 64 34 56 68 91 68 55 28
0.683 0.690 0.722 0.709 0.707 0.719 0.760 0.754 0.782
0.684 0.703 0.722 0.723 0.716 0.739 0.762 0.774 0.782
0.720 0.744 0.764 0.790 0.785 0.806 0.831 0.818 0.842
0.751 0.772 0.788 0.823 0.813 0.842 0.863 0.860 0.896
0.778 0.808 0.829 0.843 0.850 0.873 0.912 0.900 0.945
0.868 0.861 0.904 0.897 0.902 0.943 0.992 0.976 0.997
0.878 0.937 0.905 0.910 0.915 0.958 0.996 0.997 0.997
0.519 0.505 0.560 0.580 0.599 0.593 0.636 0.647 0.715
0.519 0.544 0.560 0.584 0.601 0.608 0.651 0.663 0.715
0.562 0.578 0.607 0.642 0.645 0.676 0.702 0.711 0.762
0.579 0.593 0.629 0.669 0.684 0.711 0.743 0.743 0.789
0.604 0.648 0.658 0.686 0.709 0.746 0.784 0.793 0.847
0.664 0.697 0.732 0.736 0.773 0.829 0.881 0.885 0.941
0.668 0.740 0.732 0.766 0.793 0.838 0.895 0.896 0.941
Girls 5 6 7 8 9 10 11 12 13
30 41 27 44 45 67 51 41 26
0.651 0.726 0.722 0.713 0.705 0.719 0.753 0.765 0.747
0.651 0.727 0.722 0.718 0.705 0.742 0.766 0.768 0.747
0.725 0.749 0.755 0.767 0.776 0.793 0.823 0.833 0.890
0.753 0.764 0.779 0.794 0.807 0.821 0.862 0.891 0.920
0.774 0.790 0.811 0.830 0.842 0.852 0.914 0.952 0.979
0.848 0.836 0.855 0.890 0.947 0.948 0.990 1.042 1.087
0.848 0.841 0.855 0.891 0.957 0.955 0.993 1.044 1.087
0.514 0.560 0.561 0.587 0.562 0.578 0.659 0.648 0.681
0.514 0.560 0.561 0.589 0.569 0.610 0.660 0.655 0.681
0.555 0.583 0.606 0.624 0.646 0.673 0.727 0.731 0.787
0.570 0.602 0.621 0.650 0.677 0.708 0.762 0.783 0.832
0.596 0.618 0.647 0.697 0.712 0.732 0.804 0.839 0.862
0.629 0.671 0.688 0.753 0.834 0.860 0.905 0.942 1.001
0.629 0.672 0.688 0.762 0.865 0.895 0.926 0.951 1.001
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Table 3 Percentile Distribution of BMD (g/cm2) for Total Body and Subcranial Skeleton by Gender and Age Group
Abbr: BMD, bone mineral density; ROI, region of interest. a Total body with the head ROI removed from analysis.
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Table 4 Percentile Distribution of BMC (g) for Total Body and Subcranial Skeleton by Gender and Age Group Subcranial skeletona
Total body Age group
n
Min.
3rd
25th
50th
75th
97th
Max.
Min.
3rd
25th
50th
75th
97th
Max.
Boys 5 6 7 8 9 10 11 12 13
41 64 34 56 68 91 68 55 28
390.49 443.32 556.77 596.02 624.38 641.63 752.52 819.42 1072.00
407.21 512.58 557.05 625.47 702.39 740.67 812.87 890.50 1072.00
538.37 583.29 653.89 794.84 798.97 916.81 1052.11 1049.63 1182.66
584.64 645.21 746.49 855.40 919.37 1042.47 1141.46 1157.54 1343.71
683.45 739.88 827.10 955.11 1043.06 1149.05 1274.53 1381.65 1701.16
799.99 913.99 1140.72 1179.88 1236.93 1428.17 1677.14 1820.76 1857.29
804.56 1076.47 1143.33 1282.26 1372.21 1494.27 1725.72 1887.10 1857.29
194.66 222.64 301.18 372.64 378.64 395.70 513.84 533.59 708.12
207.28 262.41 302.36 387.10 437.86 470.32 537.92 613.49 708.12
290.15 331.82 394.23 483.39 532.36 604.18 708.40 737.67 873.33
335.51 374.98 451.54 551.03 611.18 722.13 798.44 836.22 1016.91
393.19 448.53 517.23 629.86 707.88 813.50 923.45 1023.45 1319.08
523.43 624.79 794.44 829.37 946.25 1092.91 1318.60 1465.34 1537.80
529.93 675.03 796.68 904.15 1085.18 1187.05 1352.17 1541.80 1537.80
Girls 5 6 7 8 9 10 11 12 13
30 41 27 44 45 67 51 41 26
378.14 480.36 574.36 591.67 525.98 606.38 716.74 844.99 872.14
378.14 484.35 574.36 595.12 577.66 710.54 753.18 875.86 872.14
519.08 567.68 623.39 718.22 780.51 862.97 1050.65 1166.02 1375.21
550.70 619.22 677.06 784.14 867.53 976.68 1169.32 1308.12 1527.38
594.41 664.43 726.34 901.45 975.66 1049.78 1336.71 1493.62 1685.01
706.73 773.64 938.85 1206.44 1519.42 1553.72 1766.01 2045.57 2150.71
706.73 783.24 938.85 1220.33 1712.27 1852.20 1851.57 2118.49 2150.71
204.80 247.30 320.80 370.04 328.53 380.21 480.81 570.71 573.41
204.80 251.36 320.80 375.33 362.98 469.62 523.74 596.40 573.41
285.42 324.63 360.74 449.24 526.18 580.53 733.93 846.30 1042.34
307.96 366.82 414.65 512.56 597.40 672.20 898.64 993.79 1160.53
336.77 397.25 467.83 586.80 696.60 759.10 1012.87 1130.03 1333.99
420.50 483.29 613.92 853.14 1170.74 1214.85 1416.90 1634.74 1751.83
420.50 485.45 613.92 853.24 1358.19 1550.54 1525.35 1691.83 1751.83
Abbr: BMC, bone mineral content; ROI, region of interest. a Total body with the head ROI removed from analysis.
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Fig. 3. Height percentile curves adjusted for age. Solid lines from the upper one represent the 97th, 75th, 50th, 25th, and 3rd percentiles.
Fig. 4. Bone area (BA) percentile curves adjusted for height. Solid lines from the upper one represent the 97th, 75th, 50th, 25th, and 3rd percentiles.
the necessity to establish ethnicity specific reference databases for the interpretation of pediatric DXA results. Wang et al. (14) reported significant ethnic differences in bone mass in a cross-sectional study of 423 Asian, black, Hispanic, and non-Hispanic white American youths aged 9e25 yr. A follow-up study of this cohort further confirmed the ethnic differences (15). In a longitudinal study of 773 pretubertal children, Nelson et al. (16) found that black children have significantly higher whole body BMD and BMC than white children. For both genders in our study, the BMD, BMC, and BA of the total body and the subcranial skeleton increased with age, which is consistent with previous studies of other ethnic populations (17e23). However, the variation of DXA instruments, scan modes, analysis software, and
analysis modes among different studies makes it difficult to make a direct comparison between these published data. Our study results indicated that the head region accounted for a smaller percent of the total body BMC as age and height increased for both boys and girls. Willing et al. (24) revealed that the BMC of the head comprised a greater percentage of whole body BMC in small children compared to taller children. Taylor et al. (25) suggested that in normal children, age explained more variance in subtotal BMD than in total body BMD. They also found that head BMD accounted for most of the variance in total body BMD. Our findings are consistent with these patterns and suggest that the subcranial skeleton BMD may be an important indicator in reflecting skeletal status for children.
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Fig. 5. Bone mineral content (BMC) percentile curves adjusted for bone area (BA). Solid lines from the upper one represent the 97th, 75th, 50th, 25th, and 3rd percentiles. Our literature review indicated that evidence of gender differences in total body BMD and BMC remained inconsistent for children. In the present study, no significant differences in total body and subcranial skeleton BMD have been found between boys and girls aged 5e13 yr. Significant gender differences in total body BMC were observed at age 5e7 and 12 yr but were found only at age 5 and 12 yr for subcranial skeleton BMC. In a study of Canadian children aged 8e17 yr, Faulkner et al. (18) found no gender differences until age 16 for total body BMD and age 14 for BMC. Willing et al. (24) conducted a study on 428 Iowa children aged 4.5e6.5 yr which revealed that boys in general had significantly higher total body BMD and BMC, after adjustment for age, height, and weight. No significant gender differences were observed for subcranial skeleton BMC in their study (24). In a longitudinal study of Danish children aged 6e19 yr, Molgaard et al. (19) reported that the median annual accretion rate for whole body BMC was similar for both Journal of Clinical Densitometry
genders before puberty. In general, the normal reference database for pediatric DXA should be gender-specific (5). DXA measurements are 2-dimensional. Thus, the areal BMD is the ratio of BMC to BA, rather than a true bone density. A report by Wren et al. (26) indicated that more children were diagnosed as having low bone density based on BMD measurements obtained by DXA than by quantitative computed tomography. The size effects render the interpretation of pediatric DXA results more complicated. Various approaches have been proposed to correct for bone size, and there is currently no consensus on which approach is the most appropriate (11). In our study, we adopted Molgaard et al.’s method (12) to develop percentile curves for BMC and bone size in addition to normative BMD data. It is worthwhile mentioning some limitations of the current study. First, the participating subjects in our study were primarily southern Chinese children. No previous reports have Volume 10, 2007
Bone Density of Chinese Children indicated that total body BMD is significantly different between southern and northern Chinese children. However, to be better representative of the study population, a broader range of subjects may be needed. Second, our study ended with children aged 13 yr, an age at which they have not yet achieved peak bone mass. Therefore, further investigations in adolescents are necessary for establishing a complete pediatric normal reference database. Lastly, our study design is cross-sectional. To better study the bone mineral acquisition of normal Chinese children, longitudinal data need to be obtained. In summary, we have presented an ethnicity- and genderspecific densitometric normal reference database for Chinese children aged 5e13 yr. To the best of our knowledge, these are the first total body normal reference data for Chinese children. They should allow for an appropriate clinical assessment of total body bone density in Chinese children as measured by the Lunar Prodigy DXA densitometer.
Acknowledgment We would like to express our gratitude to all participating children and their parents. We also thank Dr. William Riley, for help in preparing the manuscript; and Mr. He Huang, Mr. Jin-Qiu Xie, and Ms. Dan Wang, for their excellent technical support. This study was supported in part by the Undergraduate Science Innovation Project of Jinan University.
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