While osteoporosis is usually considered a disease of the elderly, it could as accurately be considered a disease of childhood with manifestations in the elderly. More than 90% of peak bone mass is accrued by age 18 years. Bone mass increases in a linear manner during childhood until puberty (Figure 1). During puberty the rate of bone mass accrual increases until the late teenage years, at which time it levels off until peak bone mass is achieved (1). Once peak bone mass is achieved (in the late teens to early 20s), little can be done to further increase bone mass. Peak bone mass is thought to account for more than half the variability in adult bone mass; thus, adult fracture risk is dependent on childhood bone metabolism (2). Targeting interventions toward optimization of peak bone mass during childhood and adolescence therefore represents an important public health approach. Early intervention takes advantage of the unique window of opportunity to maximize bone mass accrual and peak bone mass, and theoretically decrease fracture risk for life.
A vertebral compression fracture, or any other pathologic fracture, in childhood is something all patients, parents, and physicians hope to avoid. The price of childhood osteoporosis is arguably greater than that of osteoporosis that develops during adulthood since it carries the potential for many more years of disability. Avoiding childhood osteoporosis is an important goal. Rushing to treat “osteoporosis” in children using adult definitions and drug protocols is, however, potentially dangerous. The report by Roth and colleagues in this issue of Arthritis & Rheumatism (3) illustrates the difficulty of diagnosing bone metabolism disorders in childhood.
The most commonly used technology for the diagnosis of osteoporosis is measurement of bone mineral density (BMD) using dual x-ray absorptiometry (DXA). DXA scanning is frequently used because it is accurate, reproducible, fast, and delivers a low radiation dose. Unfortunately, however, as noted by Roth et al, DXA scans are limited by their ability to obtain only a 2-dimensional measure of the 3-dimensional bone. Two bones of identical “true density,” but of differing size, will yield different BMD readings; the smaller bone will have a lower reading compared with the larger bone (4).
In addition, specialized software in the DXA machine is needed to make appropriate comparisons in pediatric populations. Without this software, a child's BMD result is compared with that of a normal young adult's peak bone mass. The resultant T score is an underestimate of actual bone mass accrual. With the correct software, the BMD result is compared with that of an age-appropriate reference value, with a resultant and more accurate Z score. Most physicians with expertise in childhood osteoporosis have had the experience of having a child referred for “osteoporosis” where the BMD was measured and compared with adult normative data, with the reported T score in the osteoporotic range. In fact, the child's BMD may have actually been normal when appropriately compared with age-matched pediatric normative data. There are available normative data for the lumbar spine and total body, but DXA machines do not have pediatric norms for the hip. Newer technologies, such as calcaneal ultrasound measurement, are not yet fully validated in diagnosis of adult osteoporosis and do not have large databases in order to determine normative values in children (5).
Measurement of BMD in children is further complicated by the wide variation of age at onset and progression of puberty. This leads to a wide variation in the age at attainment of peak bone mass. The presence of a chronic disease, such as juvenile arthritis, is thought to delay pubertal onset and development. It has been estimated that one-third to one-half of the total mineralization in the lumbar spine in adult women is accumulated during the 3 years around the onset of puberty (6, 7). Therefore, comparing the BMD of a well-grown 13-year-old girl who is in mid-puberty with that of a small prepubertal 13-year-old with juvenile arthritis is fraught with problems. A DXA scan is not needed to tell who has the lower BMD. The question then is, is the BMD result in this small prepubertal girl abnormal?
The World Health Organization (WHO) has defined osteoporosis in adults based on measurement of bone mass, usually BMD measurement. In 1994, the WHO defined osteoporosis as a bone mass measurement more than 2.5 standard deviations below peak bone mass and osteopenia as a bone mass between 1 and 2.5 standard deviations below peak bone mass (8, 9). These definitions are clinically relevant in adults. In epidemiologic studies of postmenopausal women, each standard deviation decrease of BMD below peak bone mass increases fracture risk 1.5–3-fold (10–12). However, since children have yet to reach peak bone mass, these definitions are meaningless in the pediatric population. Many researchers struggling with the definition of childhood osteoporosis have advocated for defining a BMD more than 2.5 SD below age mean as osteoporosis and a BMD between 1 and 2.5 SD below age mean as osteopenia. Unfortunately, there are no epidemiologic studies validating this definition.
BMD assessment does not take into account structural properties of bone. It is well known that structural properties, e.g., bone size, bone shape, and microarchitecture, are key elements affecting bone strength. For example, a recent report of bisphosphonate-induced osteopetrosis in a child who received higher-than-normal doses of intravenous pamidronate revealed normal BMD in spite of a vertebral fracture and abnormal architecture seen in a bone biopsy specimen (13). In a study of growing rats, exercise was shown to increase cortical wall thickness and mechanical strength without impacting bone mineral content measurement by DXA (14).
Recently, a strength index accounting for both bone density and bone size has been found to be predictive of fractures in postmenopausal women (15). The changes in bone size that occurred during aging in these women were found to be specific: while endocortical (inner surface) bone resorption occurred, periosteal (outer surface) bone formation compensated for this loss. In prepubertal children, linear growth of long bones is accompanied by periosteal bone formation, widening bone as endocortical resorption allows expansion of medullary space. The more rapid periosteal formation compared with endocortical resorption allows for overall thickening of the bone cortex (16). During puberty, estrogen in girls inhibits periosteal formation while stimulating endocortical bone formation, thus limiting the medullary space. In contrast, in boys androgens stimulate periosteal formation, bone diameter, and cortical thickness (17).
Most of the evidence to date suggests that among prepubertal children there is no difference in BMD between girls and boys. The action of hormones on the periosteal and endocortical surfaces accounts for some of the differences in bone strength between the sexes seen later in life (18). The finding by Roth and colleagues (3) that children with childhood arthritis have reduced cortical area and thickness of the forearm may be more significant with regard to fracture risk than is decreased BMD. A larger bone is inherently more difficult to break. In addition, their finding of decreased muscle mass associated with the decreased cortical size may indicate an important potentially modifiable risk factor for decreased bone cortical size. Childhood is the only time of life in which exercise has been shown to favorably modify skeletal mass and geometry (19, 20). It appears that the exercise must occur in the prepubertal years in order to have this beneficial effect.
As these considerations indicate, assessment of bone mineralization in children is complicated and should be performed in the context of sex, pubertal development, bone size, body size, and geometry. Bone geometry and cortical dimensions have been previously underinvestigated elements of bone health in children. Meaningful outcome variables for osteoporosis, besides actual osteoporotic fractures, are lacking in the pediatric population. With osteoporotic fractures potentially occurring decades later, defining outcome measures that are reflective of future fracture risk is an important goal. Pending the ability to more definitively predict future risk of osteoporosis in pediatric patients, and given the limitations of the current technology, clinicians should strive to optimize bone health in children with arthritis by limiting corticosteroid use, encouraging physical activity, ensuring adequate nutrition, and reducing disease activity. While these measures are useful, greater understanding of bone metabolism through studies such as the one presented by Roth et al will hopefully lead to significant improvements in the care of children with arthritis.