Megan Hetherington-Rauth1, Jennifer W Bea2, Robert M Blew3, Janet L Funk4, Vinson R Lee5, Denise J Roe6, LuÍs B Sardinha7, Scott B Going8. 1. Exercise and Health Laboratory, CIPER, Faculty of Human Kinetics, University of Lisbon, Portugal. Electronic address: mchr@email.arizona.edu. 2. Department of Nutritional Sciences, University of Arizona, Tucson, AZ 85721, USA; Departments of Medicine, University of Arizona, Tucson, AZ 85721, USA; The University of Arizona Cancer Center, Tucson, AZ 85724, USA.. Electronic address: jbea@uacc.arizona.edu. 3. Department of Nutritional Sciences, University of Arizona, Tucson, AZ 85721, USA. Electronic address: rblew@email.arizona.edu. 4. Department of Nutritional Sciences, University of Arizona, Tucson, AZ 85721, USA; Departments of Medicine, University of Arizona, Tucson, AZ 85721, USA. Electronic address: jfunk@email.arizona.edu. 5. Department of Nutritional Sciences, University of Arizona, Tucson, AZ 85721, USA. Electronic address: vinsonl@email.arizona.edu. 6. The University of Arizona Cancer Center, Tucson, AZ 85724, USA.; Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ 85721, USA. Electronic address: droe@email.arizona.edu. 7. Exercise and Health Laboratory, CIPER, Faculty of Human Kinetics, University of Lisbon, Portugal. 8. Department of Nutritional Sciences, University of Arizona, Tucson, AZ 85721, USA. Electronic address: going@email.arizona.edu.
Abstract
BACKGROUND: Excess weight exerts the positive effect of mechanical loading on bone during development whereas obesity-related metabolic dysfunction may have a detrimental impact. In adults, the presence of metabolic syndrome and type 2 diabetes has been associated with compromised bone density, quality, and strength, and an increased incidence of fractures. The few studies that have investigated the role of cardio-metabolic disease risk biomarkers (CMR) on bone strength in children have given conflicting results. The aim of this study was to assess the combined and independent relationships of cardio-metabolic biomarkers with total body and regional bone parameters in young girls. METHODS: In 306, 9-12 year old girls, measures of whole body fat and lean mass, areal bone mineral density (aBMD), bone mineral content (BMC), and bone area (BA) were obtained by dual-energy x-ray absorptiometry (DXA). Bone mineral density (vBMD), geometry, and strength of metaphyseal and diaphyseal regions of the femur and tibia and a diaphyseal region of the radius were measured using peripheral quantitative computed tomography (pQCT). Fasting serum measures of CMRs included, fasting glucose, insulin, homeostatic model assessment for insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglyceride (TG), systolic and diastolic blood pressure (SBP and DBP), and C-reactive protein (CRP). Multiple linear regression was used to assess the independent associations of a single CMR with total body and peripheral measures of bone strength after controlling for the other CMRs, plus total body soft tissue, and other relevant covariates. Also, a standardized total CMR composite score, calculated by standardizing to z-scores and then summing z-scores of each CMR biomarker, was regressed with total body and regional bone measures to assess the relationship of a cluster of risk factors with bone health. RESULTS: Total CMR composite score had inverse associations (p < 0.001) with DXA total BMC and BA. Inverse associations (p < 0.05) of CMR risk score with pQCT regional bone measures occurred with total and trabecular BA at the 4% tibia. Of the individual CMRs, HOMA-IR and CRP were significant predictors of total body bone measures by DXA accounting for ~1-5% of the variance in BMC, BA, and/or aBMD. HOMA-IR was the main predictor of regional pQCT bone outcomes, accounting for the most variance in trabecular vBMD (2.6%) and BSI (3.8%) at the 4% tibia. Most markers of dyslipidemia (TG, HDL-C, LDL-C) and hypertension (SBP, DBP) were not associated (p > 0.05) with any total body or regional bone outcomes with the exception of the inverse relationship of LDL-C with total and trabecular BA and the positive relationship of DBP with cortical vBMD at the radius. CONCLUSION: Of the obesity-related metabolic impairments, insulin resistance and chronic inflammation may compromise whole body bone development in young girls. In particular, trabecular bone, such as that found at the metaphysis of long bones, may be more susceptible to the detrimental effects associated with obesity-related metabolic dysfunction.
BACKGROUND: Excess weight exerts the positive effect of mechanical loading on bone during development whereas obesity-related metabolic dysfunction may have a detrimental impact. In adults, the presence of metabolic syndrome and type 2 diabetes has been associated with compromised bone density, quality, and strength, and an increased incidence of fractures. The few studies that have investigated the role of cardio-metabolic disease risk biomarkers (CMR) on bone strength in children have given conflicting results. The aim of this study was to assess the combined and independent relationships of cardio-metabolic biomarkers with total body and regional bone parameters in young girls. METHODS: In 306, 9-12 year old girls, measures of whole body fat and lean mass, areal bone mineral density (aBMD), bone mineral content (BMC), and bone area (BA) were obtained by dual-energy x-ray absorptiometry (DXA). Bone mineral density (vBMD), geometry, and strength of metaphyseal and diaphyseal regions of the femur and tibia and a diaphyseal region of the radius were measured using peripheral quantitative computed tomography (pQCT). Fasting serum measures of CMRs included, fasting glucose, insulin, homeostatic model assessment for insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglyceride (TG), systolic and diastolic blood pressure (SBP and DBP), and C-reactive protein (CRP). Multiple linear regression was used to assess the independent associations of a single CMR with total body and peripheral measures of bone strength after controlling for the other CMRs, plus total body soft tissue, and other relevant covariates. Also, a standardized total CMR composite score, calculated by standardizing to z-scores and then summing z-scores of each CMR biomarker, was regressed with total body and regional bone measures to assess the relationship of a cluster of risk factors with bone health. RESULTS: Total CMR composite score had inverse associations (p < 0.001) with DXA total BMC and BA. Inverse associations (p < 0.05) of CMR risk score with pQCT regional bone measures occurred with total and trabecular BA at the 4% tibia. Of the individual CMRs, HOMA-IR and CRP were significant predictors of total body bone measures by DXA accounting for ~1-5% of the variance in BMC, BA, and/or aBMD. HOMA-IR was the main predictor of regional pQCT bone outcomes, accounting for the most variance in trabecular vBMD (2.6%) and BSI (3.8%) at the 4% tibia. Most markers of dyslipidemia (TG, HDL-C, LDL-C) and hypertension (SBP, DBP) were not associated (p > 0.05) with any total body or regional bone outcomes with the exception of the inverse relationship of LDL-C with total and trabecular BA and the positive relationship of DBP with cortical vBMD at the radius. CONCLUSION: Of the obesity-related metabolic impairments, insulin resistance and chronic inflammation may compromise whole body bone development in young girls. In particular, trabecular bone, such as that found at the metaphysis of long bones, may be more susceptible to the detrimental effects associated with obesity-related metabolic dysfunction.
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