Full Length ArticleBody fat mass, lean body mass and associated biomarkers as determinants of bone mineral density in children 6–8 years of age – The Physical Activity and Nutrition in Children (PANIC) study
Introduction
Early childhood and puberty are the periods of rapid growth and bone accretion, and the majority of bone mass is gained during adolescence and early adulthood [1], [2], [3]. Bone mineral accrual during growth is dependent on multiple factors such as genetic background, sex, race, nutrition, physical activity, and hormone metabolism [2], [3]. Higher lean body mass (LM) has been associated with higher bone mineral density (BMD) and bone mineral content (BMC) in children and adolescents [4], [5], [6], [7], but the relationship of body fat mass (FM) with BMD or BMC remains controversial [5], [6], [8], [9], [10]. FM has been positively associated with BMD independent of LM in prepubertal children [6]. However, there is some evidence that higher FM is detrimental to bone accrual during and after puberty [5], [8], [9] and that overweight children and adolescents are at an increased risk of forearm fractures [10].
Mechanical loading increases bone formation, and weight-bearing exercise improves bone mineral accrual [11]. The classical Wolff's law and later the Frost's mechanostat theory propose that bone strength is regulated by modeling and remodeling processes which depend on the forces acting on the bones [12]. The mechanical load to bone is increased not only because of physical activity and increased muscle mass but also due to increased FM and particularly obesity [3].
In addition to the mechanical load, adipose tissue may influence bone metabolism through adipokines, other cytokines, and hormones [13], [14], [15]. Adipose tissue may stimulate bone formation by producing estrogens from steroid precursors and by increasing circulating leptin and insulin levels [13], [14], [15]. However, adipose tissue produces adiponectin and inflammation-related cytokines, such as tumor necrosis factor α (TNF-α) and interleukin 6 (IL-6), which may have deleterious effects on bone [13], [14], [15]. Vitamin D is a prohormone converted in the liver to 25-hydroxyvitamin D (25[OH]D) and then in the kidney to 1,25-dihydroxyvitamin D (1,25[OH]2D), the active metabolite which regulates calcium, phosphorus, and bone metabolism [16]. Obesity has been associated with lower serum levels of 25(OH)D [17], that could therefore be one of the links between obesity and BMD.
More recently, also skeletal muscle and bone have been recognized as endocrine organs [18], [19]. Skeletal muscle produces myokines, such as myostatin, insulin-like growth factor I (IGF-1), irisin, and IL-6, which may be important mediators in the interaction between skeletal muscle and bone [18], [19]. IGF-1 may be one of the factors that mediate the response of bone and skeletal muscle to mechanical loading [19], [20]. Osteocytes also secrete IL-6, IGF-1, and other hormone-like factors, such as osteocalcin and fibroblast growth factor 23, which have been suggested to play a role in the association between skeletal muscle and bone metabolism [18], [19].
Low BMD in childhood tends to persist until young adulthood [21], and bone mass attained during childhood and adolescence is one of the most important determinants of lifelong skeletal health [22]. Paediatric obesity is a growing global health problem [23], and it is therefore important to know how adiposity and associated increase in LM affects BMD among children. There is no consensus on the associations of FM and LM with BMD or the underlying mechanisms. We therefore studied the associations of LM, FM, and associated biomarkers, including adipokines, myokines, inflammation-related biomarkers, growth factors, and 25(OH)D, with BMD assessed by dual-energy x-ray absorptiometry (DXA) in a population sample of children 6–8 years of age.
Section snippets
Study design and participants
The present analyses are based on the baseline data of the Physical Activity and Nutrition in Children (PANIC) Study, which is an ongoing physical activity and dietary intervention study in a population sample of children 6–8 years of age from the city of Kuopio, Finland (ClinicalTrials.gov registration number NCT01803776). Altogether 736 children from the primary schools of Kuopio were invited to participate in the baseline examinations in 2007—2009. Of the invited children, 512 (70%)
Characteristics of children
The boys were heavier and taller and had higher waist circumference and LM and lower BF% and FM than the girls, but there was no difference in BMI-SDS between the genders (Table 1). The girls had higher IGF-1, insulin, leptin, and free leptin index and lower leptin receptor and IL-6 than the boys. Of the children, 38 (8.1%) had asthma, 128 (27.1%) any allergic symptom (rhinitis, conjunctivitis, atopy, food or medicine allergy), 21 (4.4%) an attention deficit hyperactivity disorder (ADHD/ADD) or
Discussion
Our study is one of the few studies on the associations of LM, FM, and various biomarkers secreted by adipose tissue, skeletal muscle, or bone with BMD in a population sample of prepubertal children. LM but also FM were strong and independent positive determinants of BMD in all children, girls, and boys. Plasma irisin was also an independent positive correlate for BMD in all children but not in girls and boys separately. The associations of other biomarkers were explained by body height, LM, or
Conclusions
Our study showed that LM is the strongest positive determinant of BMD, but also FM is positively and independently associated with BMD in a population sample of mainly normal-weight prepubertal Finnish children. Of biomarkers related to body composition, irisin had a positive association with BMD independent of LM and FM. To the best of our knowledge, this is the first study to examine the association between irisin and BMD in children, and this finding needs to be confirmed in other
Acknowledgements
The authors are grateful to all the children and their parents for participating in the PANIC study. The authors are also indebted to the members of the PANIC research team for their skillful contribution in performing the study. The authors are grateful to Ayhan Korkmaz for performing irisin measurements, Leila Antikainen for performing DHEAS and IGF-1 measurements, Tuomas Onnukka for performing leptin measurements, and Kaija Kettunen for performing leptin receptor and adiponectin
Funding sources
This work was financially supported by grants from Ministry of Social Affairs and Health of Finland (funding number 087/KTL/TE/2007), Ministry of Education and Culture of Finland (funding number 105/627/2006), Finnish Innovation Fund Sitra (funding number 545103/1), Social Insurance Institution of Finland (funding number 22/26/2008), Finnish Cultural Foundation (funding number 00090566), Juho Vainio Foundation, Foundation for Paediatric Research, Doctoral Programs in Public Health, Paavo Nurmi
Conflict of interest
The authors declare there are no conflicts of interest.
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