Predictor Of Bone Mass Research Articles

Bone fragility in young people: significant anamnestic elements

Various factors are known to interfere with gain in bone density and structure during growth and development. Bone status in childhood has been shown to be a predictor of bone mass in young adulthood. This concise review aims to discuss the main factors that can influence peak bone mass during growth and development, and whether they may be predictors of future bone fragility risk, useful for physicians taking care of children and adolescents. KEY WORDS: Children and adolescent bone health, peak bone mass, predictors of bone fragility, osteoporosis prevention.

Correlation between bone density, bone metabolism markers with lipid metabolism markers and body mass index

PurposeWe aimed to explore the relationship between bone mineral density (BMD), bone metabolism markers, and blood lipid-related indicators, body mass index (BMI) in elderly individuals.MethodsA retrospective analysis was conducted on 710 patients. Patients’ gender, age, height, weight, bone density values, T-scores, bone metabolism markers (including serum N-terminal propeptide of type I collagen (s-PINP), serum C-terminal telopeptide of type I collagen (s-CTX) and 1,25-dihydroxyvitamin D3 (1,25(OH)2D3) and lipid-related indicators (including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG) and Castelli index 1 (TC/HDL-C index) and Castelli index 2 (LDL-C/HDL-C index) were recorded. Correlations between variables were analyzed, and patients were grouped according to gender and T-score for intergroup comparisons.ResultsHDL-C negatively correlates with BMD and s-CTX. TG, Castelli index, and BMI positively correlate with BMD. BMI negatively correlates with s-PINP. 1,25(OH)2D3 negatively correlates with TC, LDL-C, and Castelli index. LDL-C positively correlates with BMD in males, and TC negatively correlates with s-PINP. In females, HDL-C negatively correlates with BMD, and s-CTX positively correlates with Castelli index. 1,25(OH)2D3 negatively correlates with TC, LDL-C, and Castelli index. TG and Castelli index were higher in normal bone mass group, while HDL-C is higher in the osteoporosis group. TG and BMI positively predicted bone mass density, while HDL-C negatively predicted bone mass density.ConclusionsHDL-C may have a predictive role in osteoporosis, particularly in women. The likelihood of osteoporosis is lower in individuals with high BMI or hyperlipidemia. Some lipid metabolism markers can be used to predict osteoporosis, and further research is needed.

Sclerostin but not Dickkopf-related protein 1 predicts bone mass and markers of bone turnover in older adults

Sclerostin but not Dickkopf-related protein 1 predicts bone mass and markers of bone turnover in older adults

Correlation Between Renal Calculus Disease and Iliac Bone Thickness on a Single Non-contrast CT Scan.

Background Renal calculi remain a major economic and health burden worldwideand are considered a systemic disorder associated with multiple other diseases. Several studies have observed that patients with idiopathic calcium renal stonesshow areduction in bone mass. This study aimed to evaluate bone mass reduction on a non-contrast CT scan study in a group of idiopathic calcium-containing renal calculus disease patients in comparison with subjects without renal calculus disease. Methodology This non-interventional, cross-sectional study included a total of 300 patients with 150 cases (with renal calculi) and 150 controls (without renal calculi). Patients were divided according to age groups of 18-40, 40-60, and more than 60 years. The renal calculus size and the mean iliac bone thickness were calculated, and Spearman's correlation test was used to determine the correlation between them. Results The mean iliac bone thickness was significantly lower in the cases (3.29 mm) compared to the controls (9.73 mm with a standard deviation of 1.341 mm). There was a statistically significant negative correlation between the size of the renal calculus and the mean iliac bone thickness. Conclusions Renal calculus disease associated with hypercalciuria caused by increased bone resorption is reflected by the decreased iliac bone thickness on CT scans. Our study used the iliac bone (cancellous bone) in predicting bone mass reduction which shows changes early in the course of the disease compared to the neck of the femur and lumbar vertebrae (compact bones). It helps in predicting osteoporosis early and prevents the progression of the disease through early and appropriate clinical and urological intervention.

Body composition phenotypes and bone health in young adults: A cluster analysis

Lean mass is considered the best predictor of bone mass, as it is an excellent marker of bone mechanical stimulation, and changes in lean mass are highly correlated with bone outcomes in young adults. The aim of this study was to use cluster analysis to examine phenotype categories of body composition assessed by lean and fat mass in young adults and to assess how these body composition categories are associated with bone health outcomes. Cluster cross-sectional analyses of data from 719 young adults (526 women) aged 18-30 years from Cuenca and Toledo, Spain, were conducted. Lean mass index (lean mass (kg)/height (m)2), fat mass index (fat mass (kg)/height (m)2), bone mineral content (BMC) and areal bone mineral density (aBMD) were assessed by dual-energy X-ray absorptiometry. A cluster analysis of lean mass and fat mass index z scores resulted in a classification of a five-category cluster solution that could be interpreted according to the body composition phenotypes of individuals as follows: high adiposity-high lean mass (n=98), average adiposity-high lean mass (n=113), high adiposity-average lean mass (n=213), low adiposity-average lean mass (n=142), and average adiposity-low lean mass (n=153). ANCOVA models showed that individuals in clusters with a higher lean mass had significantly better bone health (z score: 0.764, se: 0.090) than their peers in other cluster categories (z score:-0.529, se: 0.074) after controlling for sex, age, and cardiorespiratory fitness (p<0.05). Additionally, subjects belonging to the categories with a similar average lean mass index but with high or low-adiposity levels (z score: 0.289, se: 0.111; z score: 0.086, se: 0.076) showed better bone outcomes when the fat mass index was higher (p<0.05). This study confirms the validity of a body composition model using a cluster analysis to classify young adults according to their lean mass and fat mass indices. In addition, this model reinforces the main role of lean mass on bone health in this population and that in phenotypes with high-average lean mass, factors associated with fat mass may also have a positive effect on bone status.

Value of a nomogram model based on IDEAL-IQ for predicting early bone mass loss

To assess the diagnostic efficiency of a nomogram model based on iterative decomposition of water and fat with echo asymmetry and least-squares estimation- iron quantification (IDEAL- IQ) for predicting early bone loss of the lumbar vertebrae. Fifty-nine volunteers and patients with osteoporosis underwent examinations with both dual-energy X-ray absorptiometry (DXA) to determine bone mineral density (BMD) of L1-4 vertebrae and lumbar magnetic resonance imaging (MRI) with IDEAL-IQ sequence for measurement of bone marrow FF of L1-4 vertebrae. According to the results of DXA, the subjects were divided into normal bone mass group (n=23) and osteopenia group (n=36). The FF values of the two groups were compared and the diagnostic efficacy of the FF value was evaluated using ROC curve analysis. Multivariate logistic regression analysis was used to identify the independent factors for predicting bone mass loss, and a visual nomogram model was constructed and its diagnostic efficiency was assessed. The FF value of the vertebrae was significant lower in normal bone mass group than in osteopenia group [(38.84±6.75)% vs (51.96±7.65)%, P < 0.05). ROC curve analysis showed that the AUC of the FF value for differentiating normal bone mass and osteopenia was 0.797 with a cutoff value of 46.85%, a sensitivity of 73.91% and a specificity of 80.56%. Multivariate logistics regression analysis identified the FF value, age and BMI as the independent factors for predicting bone mass loss. The diagnostic AUC of the nomogram model was 0.954 (95% CI: 0.806-0.957), and the predicted probability of the model was in good agreement with the actual probability. Decision curve analysis showed that the nomogram model could provide more net benefit than the FF vale alone. FF value of MRI IDEAL- IQ sequence can reflect bone marrow fat content of the vertebral body, and the nomogram model incorporating the FF value, age, and BMI can further improve the predictive efficiency to provide a visual modality for predicting early bone mass loss.

Associations between nutrition, energy expenditure and energy availability with bone mass acquisition in dance students: a 3-year longitudinal study.

To determine whether risk factors normally associated with low bone mass in athletic populations (i.e. nutrition intake, energy expenditure and energy availability) are significant predictors of bone mass changes in vocational dance students. The total of 101 vocational dancers (63 females, 12.8 ± 2.2years; 38 males, 12.7 ± 2.2years) and 115 age-matched controls (68 females, 13.0 ± 2.1years; 47 males, 13.0 ± 1.8years) were monitored for 3 consecutive years. Bone mass parameters were measured annually at impact sites (femoral neck, FN; lumber spine, LS) and non-impact site (forearm) using DXA. Nutrition (3-day record), energy expenditure (accelerometer), energy availability and IGF-1 serum concentration (immunoradiometric assays) were also assessed. Female and male vocational dancers had consistently reduced bone mass at all anatomical sites (p < 0.001) than controls. IGF-1 did not differ between male vocational dancers and controls, but female dancers showed it higher than controls. At baseline, calcium intake was significantly greater in female vocational dancers than controls (p < 0.05). Male vocational dancers' fat and carbohydrate intakes were significantly lower than matched controls (p < 0.001 and p < 0.05, respectively). Energy availability of both female and male vocational dancers was within the normal range. A significant group effect was found at the FN regarding energy intake (p < 0.05) in female dancers. No significant predictors were found to explain bone mass differences in males. Our 3-year study revealed that both female and male vocational dancers displayed lower bone mass compared to controls, at both impact and non-impact sites. The aetiology of these findings may be grounded on factors different than those usually considered in athletic populations.

Machine Learning to Predict the Progression of Bone Mass Loss Associated with Personal Characteristics and a Metabolic Syndrome Scoring Index.

A relationship exists between metabolic syndrome (MetS) and human bone health; however, whether the combination of demographic, lifestyle, and socioeconomic factors that are associated with MetS development also simultaneously affects bone density remains unclear. Using a machine learning approach, the current study aimed to estimate the usefulness of predicting bone mass loss using these potentially related factors. The present study included a sample of 23,497 adults who routinely visited a health screening center at a large health center at least once during each of three 3-year stages (i.e., 2006–2008, 2009–2011, and 2012–2014). The demographic, socioeconomic, lifestyle characteristics, body mass index (BMI), and MetS scoring index recorded during the first 3-year stage were used to predict the subsequent occurrence of osteopenia using a non-concurrence design. A concurrent prediction was also performed using the features recorded from the same 3-year stage as the predicted outcome. Machine learning algorithms, including logistic regression (LR), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost), were applied to build predictive models using a unique feature set. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, precision, and F1 score were used to evaluate the predictive performances of the models. The XGBoost model presented the best predictive performance among the non-concurrence models. This study suggests that the ensemble learning model with a MetS severity score can be used to predict the progression of osteopenia. The inclusion of an individual’s features into a predictive model over time is suggested for future studies.

Non-linear association of body composition and its components with bone density in Iranian children and adolescents.

Peak bone mass is established during childhood and adolescence. One of the important factors influencing predicted bone mass tracking in childhood and adolescence is alteration in the body composition during this growth period. This study aimed to evaluate the associations of the components of overall body mass with areal bone mineral density Z-score in children and adolescents. In this cross-sectional study, 478 healthy Iranian children and adolescents (237 girls and 241 boys) who had DXA measures participated. We evaluated the linearity of associations using generalized additive models. Children's mean age was14 years with a range of 9-18 years, and 49.6% were girls. We found an increase in aBMD Z-score with increasing overall body mass (r = 0.25, p < 0.001). We observed this association with fat-free mass and total fat mass up to the 60th (~30 Kg) and 75th percentile (~12.5 Kg) [0.051 (95% CI, 0.027-0.075) increase in aBMD Z-score per 1 Kg increase in fat-free mass and 0.079 (95% CI, 0.044-0.114) increase in aBMD Z-score per 1 Kg increase in the total fat mass]. The correlation between Z-score of overall body mass and its components with aBMD Z-score was strongly positive. (P value < 0.001 for all) CONCLUSION: The findings of this study showed that children with greater overall body mass had higher aBMD Z-score. In addition, this study adds to a growing literature, suggesting that the relationship between body composition and BMD may be influenced by the pattern of fat and fat-free mass distribution in population.

Association between self-reported walking speed and calcaneal stiffness index in postmenopausal Japanese women

BackgroundOsteoporosis and related fractures, a worldwide public health issue of growing concern, is characterized by compromised bone strength and an increased risk of fracture. Here we show an association between self-reported walking speed and bone mass among community-dwelling postmenopausal Japanese women aged 50 years and older.Design; cross-sectional studySetting and Participants; The survey population included 1008 postmenopausal women 50–92 years of age residing in rural communities.MethodsSelf-reported walking speed was ascertained by asking the participants: “Is your walking speed faster than others of the same age and sex?” to which participants responded “yes (faster)” or “no (moderate/slower).” Calcaneal stiffness index was measured.ResultsWomen with a faster self-reported walking speed were younger and had a lower BMI, higher stiffness index, and higher grip strength than women with a slower walking speed. Multiple linear regression analysis adjusted for age, BMI, grip strength, comorbidity, current smoking, and alcohol drinking status showed a significant association between faster self-reported walking speed and higher calcaneal stiffness index (p < 0.001).ConclusionsOur findings suggest that questionnaires of walking speed may be useful for predicting bone mass and that a fast self-reported walking may benefit bone health in postmenopausal women.

Fat and Lean Mass Predict Bone Mass During Energy Restriction in Sedentary and Exercising Rodents.

Energy restriction (ER) causes bone loss, but the impact of exercise during ER is less understood. In this study, we examined the impact of metabolic hormones and body composition on both total body bone mineral content (BMC) and local (proximal tibia) volumetric bone mineral density (vBMD) during short- (4 weeks) and long-term (12 weeks) ER with and without exercise in adult female rats. Our first goal was to balance energy between sedentary and exercising groups to determine the impact of exercise during ER. Second, we aimed to determine the strongest predictors of bone outcomes during ER with energy-matched exercising groups.Methods: Female Sprague–Dawley rats were divided into three sedentary groups (ad libitum, –20% ER, and –40% ER) and three exercising groups (ad libitum, –10% ER, and –30% ER). Approximately a 10% increase in energy expenditure was achieved via moderate treadmill running (∼60–100 min 4 days/week) in EX groups. n per group = 25–35. Data were analyzed as a 2 × 3 ANOVA with multiple linear regression to predict bone mass outcomes.Results: At 4 weeks, fat and lean mass and serum insulin-like growth factor-I (IGF-I) predicted total body BMC (R2 = 0.538). Fat mass decreased with ER at all levels, while lean mass was not altered. Serum IGF-I declined in the most severe ER groups (–40 and –30%). At 12 weeks, only fat and lean mass predicted total body BMC (R2 = 0.718). Fat mass declined with ER level regardless of exercise status and lean mass increased due to exercise (+5.6–6.7% vs. energy-matched sedentary groups). At the same time point, BMC declined with ER, but increased with exercise (+7.0–12.5% vs. energy-matched sedentary groups). None of our models predicted vBMD at the proximal tibia at either time point.Conclusion: Both fat and lean mass statistically predicted total body BMC during both short- and long-term ER. Fat and lean mass decreased with ER, while lean mass increased with EX at each energy level. Measures that predicted total body skeletal changes did not predict site-specific changes. These data highlight the importance of maintaining lean mass through exercise during periods of ER.

Genetic variation in Wnt/β-catenin and ER signalling pathways in female and male elite dancers and its associations with low bone mineral density: a cross-section and longitudinal study.

Some athletes (e.g. gymnasts, dancers, swimmers) are at increased risk for low bone mineral density (BMD) which, if untreated, can lead to osteoporosis. To investigate the association of genetic polymorphisms in the oestrogen receptor (ER) and the Wnt/β-catenin signalling pathways with low BMD in elite and pre-elite dancers (impact sport athletes). The study included three phases: (1) 151 elite and pre-elite dancers were screened for the presence of low BMD and traditional osteoporosis risk factors (low body weight, menstrual disturbances, low energy availability); (2) a genetic association study was conducted in 151 elite and pre-elite dancers and age- and sex- controls; (3) serum sclerostin was measured in 101 pre-elite dancers and age- and sex-matched controls within a 3-year period. Eighty dancers revealed low BMD: 56.3% had at least one traditional osteoporosis risk factor, whereas 28.6% did not display any risk factor (37.2% revealed traditional osteoporosis risk factors, but had normal BMD). Body weight, menstrual disturbances and energy availability did not fully predict bone mass acquisition. Instead, genetic polymorphisms in the ER and Wnt/β-catenin pathways were found to be risk factors for low BMD in elite dancers. Sclerostin was significantly increased in dancers compared to controls during the 3-year follow-up (p < 0.05). Elite and pre-elite dancers demonstrate high prevalence of low BMD, which is likely related to genetic variants at the Wnt/β-catenin and ER pathways and not to factors usually associated with BMD in athletes (body weight, menstrual disturbances, energy deficiency).

Depressive symptoms, body composition and bone mass in young adults: a prospective cohort study.

An association between depression and obesity is well recognised, but longitudinal studies of depressive symptoms in adolescents as a predictor of body composition are lacking. We examined depressive symptoms at age 14, 17 and 20 years as predictors of lean, fat and bone mass at age 20 years in a birth cohort. In 1161 participants (569 females) in the Western Australia Pregnancy Cohort (Raine) Study, depressive symptoms were assessed using the Beck Depression Inventory for Youth at age 14 and 17 years, and the Depression, Anxiety and Stress Scale 21 at age 20 years. Participants were further classified into two trajectories using latent class analysis: no/transient and persistent/recurrent depression. At age 20 years, lean body mass (LBM), fat body mass (FBM) and total body bone mass were measured by dual-energy X-ray absorptiometry. In females, accounting for age and lifestyle factors, depression scores at age 14 and 20 years were positively associated with body weight, body mass index (BMI), FBM and % FBM (r=0.110-0.184, P<0.05) but negatively correlated with % LBM (r=-0.120, P<0.05) at age 20 years. Females in the persistent/recurrent depression trajectory (n=99) had significantly higher body weight (+5.1 kg), BMI (+1.8 kg m-2), FBM (+3.9 kg) and % FBM (+2.2%) and significantly lower % LBM (-2.2%) at age 20 years than those with no/transient depression (n=470; all P<0.05). In males, depression scores at age 17 and 20 years were negatively associated with LBM but not weight or BMI, and depression trajectory was not a predictor of body composition at age 20 years. Depression scores and trajectories did not predict bone mass in either males or females. Depressive symptoms and persistent/recurrent depression in adolescence are predictors of greater adiposity at age 20 years in females, but not males, but do not predict bone mass in either gender.

Muscle/Lean Mass Measurement: Comparison between Methods and Correlation with Muscle Function

Children and adolescents living with HIV have low bone mass for age. There are reliable and accurate methods for evaluation of bone mass, however, alternative methods are necessary, especially, for application in limited-resource scenarios. Anthropometry is a noninvasive and low cost method that can predict bone mass in healthy youths. The aim of the study was to develop predictive equations for bone mineral content and bone mineral density in children and adolescents living with HIV based on anthropometric variables. Forty-eight children and adolescents of both sexes (24 females) from 7 to 17 years, living in greater Florianopolis area, Santa Catarina, Brazil, who were under clinical follow-up at “Hospital Infantil Joana de Gusmão”, participated in the study. Dual-energy X-ray absorptiometry was used to evaluate whole-body bone mineral content (BMC) and areal bone mineral density (aBMD). Height, body weight, bone diameters, arm circumference, and triceps skinfold were measured and the body mass index and arm muscle area were calculated. Multiple regression models were fitted to predict BMC and aBMD, using backward selection (p ≥ 0.05). Two predictive models with high R2 values (84%–94%) were developed. Model 1 to estimate aBMD [Y = −0.1450124 + (height × 0.0033807) + (age × 0.0146381) + (body mass index × 0.0158838) + (skin color × 0.0421068)], and model 2 to estimate BMC [Y = 1095.1 + (body weight × 45.66973) + (age × 31.36516) + (arm circumference × −53.27204) + (femoral diameter × −9.594018)].The predictive models using anthropometry provided reliable estimates and can be useful to monitor aBMD and BMC in children and adolescents living with human immunodeficiency virus where limited resources are available.

Longitudinal Trajectories of Television Watching Across Childhood and Adolescence Predict Bone Mass at Age 20 Years in the Raine Study.

Sedentary behaviors such as watching television (TV) are associated with increased risk of cardiometabolic disease. The effects of TV watching during key developmental stages on skeletal health are uncertain. Hours of TV watching/week were recorded by parental or self-report at 5, 8, 10, 14, 17, and 20 years of age in 1181 members (48% female) of a pregnancy cohort (the Raine Study). Participants were classified into one of three TV-watching trajectories (using latent class analysis): low (consistently <14 h/week; 20.3%), high (consistently ≥14 h/week; 44.4%), or increasing (increased from <14 to ≥14 h/week during adolescence; 35.3%). General linear models tested associations between TV trajectory and bone mineral content (BMC) measured at age 20 years using dual-energy X-ray absorptiometry. After adjustment for height, body mass, physical activity, calcium intake, serum 25-hydroxyvitamin D levels, alcohol, and smoking (all at age 20 years), males in the low TV-watching trajectory had greater BMC for whole body (mean ± SEM, 3338 ± 59 g versus 3111 ± 31 g), legs (612 ± 12 g versus 569 ± 6 g), and arms (234 ± 5 g versus 214 ± 3 g) than those in the high TV-watching trajectory. Differences between low and high TV-watching trajectories were similar for females. BMC in the increasing TV-watching trajectory also differed for both sexes, for example males in the increasing TV-watching trajectory had greater whole-body BMC (3252 ± 38 g) than males in the high TV-watching trajectory (3111 ± 31 g) but less arm BMC (218 ± 3 g) than those in the low TV-watching trajectory (234 ± 5 g). In this community-based cohort, consistently high TV watching during childhood and adolescence independently predicted reduced peak bone mass at age 20 years. Because attainment of optimal peak bone mass is protective against osteoporosis in later life, reducing sedentary time in children may have long-term skeletal benefits. © 2016 American Society for Bone and Mineral Research.

Association between Dietary Intake and Bone Mineral Density in Japanese Postmenopausal Women: The Yokogoshi Cohort Study.

Diet and food intake play an important role in the development of osteoporosis. However, apart from calcium and vitamin D, how nutrients affect bone status is not fully understood. The purpose of this study was to determine cross-sectional and longitudinal associations between dietary intake and bone mineral density (BMD) in Japanese postmenopausal women. This 5-year cohort study included 600 community-dwelling women aged 55-74 years at baseline in 2005. Information on demographics, nutrition, and lifestyle was obtained through interviews, and nutritional and dietary intake was assessed using a validated food frequency questionnaire. BMD measurements were performed by dual energy X-ray absorptiometry. In 2010, 498 women underwent follow-up BMD examinations. Multiple linear regression analysis was performed to determine associations of predictor variables with BMD, adjusting for confounders. In cross-sectional analyses, coffee or black tea consumption was positively associated with lumbar spine (P = 0.004) and total hip (P = 0.003) BMD, and alcohol intake was positively associated with femoral neck (P = 0.005) and total hip (P = 0.001) BMD. In longitudinal analyses, vitamin K (P = 0.028) and natto (fermented soybeans) (P = 0.023) were positively associated with lumbar spine BMD, and meat or meat product consumption was inversely associated with total hip (P = 0.047) BMD. In conclusion, dietary factors other than calcium and vitamin D intake are predictors of bone mass and bone loss in Japanese postmenopausal women. In particular, natto intake is recommended for preventing postmenopausal bone loss on the basis of current evidence.

Lean mass predicts the size-dependent and size-adjusted BMD better than fat mass in premenopausal females: a cross-sectional analysis

Introduction: In the human body, the influence of lean and fat masses on the bone tissue is unclear. This study was conducted to examine the association of different body compartments in order to find out the major determinant of bone mass. We used both size-dependent and size adjusted bone mass measures in the analysis Methods: A group of 128 healthy premenopausal females, aged 25-50 years was selected randomly from the local community, stratified according to their BMI. Lean mass (LM), fat mass (FM), total body bone mineral density (TBBMD) and total body bone mineral content (TBBMC) were measured using a DXA scan. TBBMD was divided by the standing height to estimate height-adjusted total body BMD (TBBMD-ht). Furthermore, TBBMD was divided by the bone area and height to estimate bone mineral apparent density (BMAD). Results: Both FM and LM showed significant and positive correlations with TBBMC and corresponding r values were 0.33 and 0.73, respectively (P Conclusions: Among these premenopausal women LM predicted bone mass stronger than FM. Magnitude and directions of the correlations between bone mass and LM were different when BMC was adjusted for bone size and height of subjects. These results support the idea that lean mass has dual effects on bone tissue where it influences both linear measurements and mineral content to different extents. Journal of the Ceylon College of Physicians, 2014,45, 22-27

Impaired bone mineral accrual in prepubertal HIV-infected children: a cohort study

ObjectiveTo evaluate bone mass accrual and determine the influence of clinical, anthropometric, dietary and biochemical parameters on bone mass. MethodsA cohort study including 35 prepubertal HIV-infected children, between 7 and 12 years, attended at a referral center. At time 1 (T1) and time 2 (T2), patients were assessed according to clinical, anthropometric, dietary, biochemical parameters and bone mineral density (BMD). At T2, patients were divided into prepubertal and pubertal. ResultsDespite the increase in bone mass absolute values, there was no improvement in lumbar spine BMD (LSBMD) Z-score (p=0.512) and worsening in total body BMD (TBMD) Z-score (p=0.040). Pubertal patients (n=19) showed higher bone mineral content (BMC) (p=0.001), TBMD (p=0.006) and LSBMD (p=0.002) compared to prepubertal patients. After multivariate linear regression analysis, the predictors of bone mass in T1 were age, BMI and HA Z-scores for BMC; BMI Z-score, adequate serum magnesium concentration and dietary calcium intake for TBMD; adequate serum concentration of magnesium, BMI and HA Z-scores for LSBMD. In T2, age, total body fat and lean body mass (kg) for BMC; BMI Z-score and puberty for TBMD; dietary fat intake, BMI Z-score for BMD and puberty for LSBMD. ConclusionHIV-infected children have compromised bone mass and the presence of puberty seems to provide suitability of these parameters. Adequate intake of calcium and fat appears to be protective for proper bone mass accumulation factor, as well as monitoring nutritional status and serum magnesium concentration.

Prediction of Areal Bone Mineral Density and Bone Mineral Content in Children and Adolescents Living With HIV Based on Anthropometric Variables

Children and adolescents living with HIV have low bone mass for age. There are reliable and accurate methods for evaluation of bone mass, however, alternative methods are necessary, especially, for application in limited-resource scenarios. Anthropometry is a noninvasive and low cost method that can predict bone mass in healthy youths. The aim of the study was to develop predictive equations for bone mineral content and bone mineral density in children and adolescents living with HIV based on anthropometric variables. Forty-eight children and adolescents of both sexes (24 females) from 7 to 17 years, living in greater Florianopolis area, Santa Catarina, Brazil, who were under clinical follow-up at “Hospital Infantil Joana de Gusmão”, participated in the study. Dual-energy X-ray absorptiometry was used to evaluate whole-body bone mineral content (BMC) and areal bone mineral density (aBMD). Height, body weight, bone diameters, arm circumference, and triceps skinfold were measured and the body mass index and arm muscle area were calculated. Multiple regression models were fitted to predict BMC and aBMD, using backward selection (p ≥ 0.05). Two predictive models with high R2 values (84%–94%) were developed. Model 1 to estimate aBMD [Y = −0.1450124 + (height × 0.0033807) + (age × 0.0146381) + (body mass index × 0.0158838) + (skin color × 0.0421068)], and model 2 to estimate BMC [Y = 1095.1 + (body weight × 45.66973) + (age × 31.36516) + (arm circumference × −53.27204) + (femoral diameter × −9.594018)].The predictive models using anthropometry provided reliable estimates and can be useful to monitor aBMD and BMC in children and adolescents living with human immunodeficiency virus where limited resources are available.

Exercise capacity independently predicts bone mineral density and proximal femoral geometry in patients with acute decompensated heart failure.

Heart failure is associated with increased risk of osteoporosis. We evaluated the prevalence and predictors of osteoporosis in hospitalized patients with ADHF using quantitative computed tomography. Osteoporosis and vertebral fracture are prevalent in patients with ADHF and exercise capacity independently predicts bone mass and femoral bone geometry. Heart failure is associated with reduced bone mass and increased risk of osteoporotic fractures. However, the prevalence and predictors of osteoporosis in hospitalized patients with acute decompensated heart failure (ADHF) are not well understood. Sixty-five patients (15 postmenopausal females and 50 males) with ADHF were prospectively and consecutively enrolled. After stabilization of heart failure symptoms, quantitative computed tomography for bone mineral density (BMD) and femoral geometry as well as biochemical, echocardiographic, and cardiopulmonary exercise tests were performed. Fifteen postmenopausal female showed a high prevalence of osteoporosis (40%) and vertebral fracture (53%). Among 50 male patients, 12% had osteoporosis and 32% had osteopenia, while vertebral fracture was found in 12%. Lumbar volumetric BMD (vBMD) was significantly lower in ischemic patients than non-ischemic patients (107.9 ± 47.5 vs. 145.4 ± 40.9 mg/cm(3), p = 0.005) in male. Exercise capacity, indicated by peak oxygen consumption (VO2), was significantly associated with lumbar vBMD (r = 0.576, p < 0.001) and total hip areal BMD (aBMD) (r = 0.512, p = 0.001) and cortical thickness of the femur neck (r = 0.544, p = 0.001). When controlled for age, body mass index, N-terminal proBrain natriuretic protein (NT-proBNP), etiology of heart failure, hemoglobin, and thigh circumference, multivariate regression analysis revealed peak VO2 independently predicted lumbar vBMD (β = 0.448, p = 0.031), total hip aBMD (β = 0.547, p = 0.021), and cortical thickness of the femur neck (β = 0.590, p = 0.011). In male patients with ADHF, osteoporosis and vertebral fracture are prevalent, and exercise capacity independently predicts bone mass and geometry. Given that heart failure patients with reduced exercise capacity carry a substantial increased risk of fracture, proper osteoporosis evaluation is important in these patients.