scholarly journals Exploring the Relationships Among the Inflammatory Potential of the Diet, Bone Mineral Density, and Injury Incidence in Collegiate Athletes (P23-006-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Kiley Field ◽  
John Gieng ◽  
Giselle Pignotti ◽  
Sofia Apsey
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Bone Health ◽  
Collegiate Athletes ◽  
Whole Body ◽  
Research Centre ◽  
Injury Incidence ◽  
Mineral Density ◽  
The Relationship ◽  
Prior Injury

Abstract Objectives The relationship between the inflammatory potential of the diet, estimated by the Dietary Inflammatory Index (DII) score, and bone health has been studied in older populations and suggests that the diet can influence bone mineral density (BMD) and fracture risk. These relationships have yet to be explored in other potentially vulnerable populations, such as athletes, where risk of injuries may be more common due to high physical stresses and over-use. The aims of this study were 1) to examine the correlation between DII scores, and BMD in collegiate athletes, and 2) to assess the relationship between DII score and self-reported prior injury incidence. Methods Healthy collegiate athletes (n = 43) were recruited for this study: football, n = 12; men's soccer, n = 2; women's soccer, n = 13; women's swimming, n = 12; and women's basketball, n = 4. For each athlete, three 24-hour dietary intakes were collected using a standardized multiple-pass interview methodology (Nutrition Data System for Research) and this data was used to calculate individual DII scores. Body composition, including whole-body sub-total BMD, was measured using dual-energy X-ray absorptiometry. A modified overuse injury questionnaire (Oslo Sports Trauma Research Centre) was used to assess incidence of injuries in the prior 12 months. Results The participants (n = 14 male, n = 29 female) had a mean age of 19.4 ± 1.1 yrs and BMI of 25.8 ± 4.1 kg/m2. Mean DII score was −0.43 ± 0.17 points (range: −3.94 to 4.34). Mean BMD was 1.251 ± 0.169 g/cm2. Overall, DII score and BMD was not correlated (P = 0.47). Furthermore, DII scores of athletes that reported no prior injury did not differ from those who reported 1 or more injuries. Conclusions Unlike research in postmenopausal women, it appears that bone health of young healthy athletes is less vulnerable to the influence of diets with higher inflammatory potential. Moreover, the lack of difference in DII score among athletes reporting various levels of prior injury suggests that the inflammatory potential of the diet is a poor predictor of injury risk in collegiate athletes. Funding Sources N/A.

scholarly journals Inulin supplementation reduces the negative effect of a high-fat diet rich in SFA on bone health of growing pigs

2018 ◽  
Vol 119 (10) ◽  
pp. 1111-1118 ◽  
Author(s):  
Monika Sobol ◽  
Stanisława Raj ◽  
Grzegorz Skiba
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Bone Health ◽  
High Fat Diet ◽  
Growing Pigs ◽  
Whole Body ◽  
Standard Diet ◽  
High Fat ◽  
Mineral Density ◽  
Negative Effect

AbstractConsumption of a high-fat diet, rich in SFA, causes deterioration of bone properties. Some studies suggest that feeding inulin to animals may increase mineral absorption and positively affect bone quality; however, these studies have been carried out only on rodents fed a standard diet. The primary objective of this study was to determine the effect of inulin on bone health of pigs (using it as an animal model for humans) fed a high-fat diet rich in SFA, having an unbalanced ratio of lysine:metabolisable energy. It was hypothesised that inulin reduces the negative effects of such a diet on bone health. At 50 d of age, twenty-one pigs were randomly allotted to three groups: the control (C) group fed a standard diet, and two experimental (T and TI) groups fed a high-fat diet rich in SFA. Moreover, TI pigs consumed an extra inulin supply (7 % of daily feed intake). After 10 weeks, whole-body bone mineral content (P=0·0054) and bone mineral density (P=0·0322) were higher in pigs of groups TI and C compared with those of group T. Femur bone mineral density was highest in pigs in group C, lower in group TI and lowest in group T (P=0·001). Femurs of pigs in groups TI and C had similar, but higher, maximum strength compared with femurs of pigs in group T (P=0·0082). In conclusion, consumption of a high-fat diet rich in SFA adversely affected bone health, but inulin supplementation in such a diet diminishes this negative effect.

scholarly journals Assessment of Total and Regional Bone Mineral Density Using Bioelectrical Impedance Vector Analysis in Elderly Population

2021 ◽  
Author(s):  
Hsueh-Kuan Lu ◽  
Chung-Liang Lai ◽  
Li-Wen Lee ◽  
Lee-Ping Chu ◽  
Kuen-Chang Hsieh
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Bioelectrical Impedance ◽  
The Elderly ◽  
Whole Body ◽  
Mineral Density ◽  
Femur Neck ◽  
Impedance Vector ◽  
The Relationship ◽  
Different Levels

Abstract This study aimed to investigate the relationship between bone mineral density (BMD) and height-adjusted resistance (R/H), reactance (Xc/H) and phase angle (PhA). A total of 61 male and 64 female subjects aged over 60 years were recruited from middle Taiwan. The R and Xc were measured using Bodystat Quadscan 4000 at a frequency of 50 kHz. BMD at the whole body, L2-L4 spine, and dual femur neck (DFN), denoted as BMDTotal, BMDL2-L4, and BMDDFN, were calculated using a Hologic DXA scanner. The R-Xc graph was used to assess vector shift among different levels of BMD. BMD was positively correlated with Xc/H and negatively correlated with R/H (p<0.001). The General Linear Model (GLM) regression results were as follows: BMDTotal = 1.473 – 0.002 R/H + 0.007 Xc/H, r = 0.684; BMDL2-L4 = 1.526 – 0.002 R/H + 0.012 Xc/H, r = 0.655; BMDDFN = 1.304 – 0.002 R/H + Xc/H, r = 0.680; p<0.0001. Distribution of vector in the R-Xc graph was significantly different for different levels of BMDTotal, BMDL2-L4 and BMDDFN. R/H and Xc/H were correlated with BMD in the elderly. The linear combination of R/H and Xc/H can effectively predict the BMD of the whole body, spine and proximal femur, indicating that BIVA may be used in clinical and home-use monitoring tool for screening BMD in the elderly in the future.

scholarly journals The Relationship between Nutrient Patterns and Bone Mineral Density in Postmenopausal Women

Nutrients ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1262 ◽  
Author(s):  
Bolaji Lilian Ilesanmi-Oyelere ◽  
Louise Brough ◽  
Jane Coad ◽  
Nicole Roy ◽  
Marlena Cathorina Kruger
Keyword(s):  
Bone Mineral Density ◽  
Fatty Acids ◽  
Vitamin E ◽  
Postmenopausal Women ◽  
Bone Mineral ◽  
Bone Health ◽  
Mineral Density ◽  
Omega 6 ◽  
Nutrient Patterns ◽  
The Relationship

In women, the menopausal transition is characterized by acid-base imbalance, estrogen deficiency and rapid bone loss. Research into nutritional factors that influence bone health is therefore necessary. In this study, the relationship between nutrient patterns and nutrients important for bone health with bone mineral density (BMD) was explored. In this cross-sectional analysis, 101 participants aged between 54 and 81 years were eligible. Body composition and BMD analyses were performed using dual-energy X-ray absorptiometry (DXA). Nutrient data were extracted from a 3-day diet diary (3-DDD) using Foodworks 9 and metabolic equivalent (MET-minutes) was calculated from a self-reported New Zealand physical activity questionnaire (NZPAQ). Significant positive correlations were found between intakes of calcium (p = 0.003, r = 0.294), protein (p = 0.013, r = 0.246), riboflavin (p = 0.020, r = 0.232), niacin equivalent (p = 0.010, r = 0.256) and spine BMD. A nutrient pattern high in riboflavin, phosphorus and calcium was significantly positively correlated with spine (p < 0.05, r = 0.197) and femoral neck BMD (p < 0.05, r = 0.213), while the nutrient pattern high in vitamin E, α-tocopherol, β-carotene and omega 6 fatty acids was negatively correlated with hip (p < 0.05, r = −0.215) and trochanter BMD (p < 0.05, r = −0.251). These findings support the hypothesis that a nutrient pattern high in the intake of vitamin E, α-tocopherol and omega 6 fatty acids appears to be detrimental for bone health in postmenopausal women.

Relation of bone mineral density and content to mineral content and density of the fat-free mass

2001 ◽  
Vol 91 (5) ◽  
pp. 2166-2172 ◽  
Author(s):  
Ellen M. Evans ◽  
Barry M. Prior ◽  
Sigurbjorn A. Arngrimsson ◽  
Christopher M. Modlesky ◽  
Kirk J. Cureton
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Mineral Content ◽  
Collegiate Athletes ◽  
Fat Free Mass ◽  
Whole Body ◽  
Mineral Density ◽  
Athletic Status ◽  
Four Component Model ◽  
Hydrostatic Weighing

Differences in the mineral fraction of the fat-free mass (MFFM) and in the density of the FFM (DFFM) are often inferred from measures of bone mineral content (BMC) or bone mineral density (BMD). We studied the relation of BMC and BMD to the MFFM and DFFM in a heterogeneous sample of 216 young men ( n = 115) and women ( n = 101), which included whites ( n = 155) and blacks ( n = 61) and collegiate athletes ( n = 132) and nonathletes ( n = 84). Whole body BMC and BMD were determined by dual-energy X-ray absorptiometry (DXA; Hologic QDR-1000W, enhanced whole body analysis software, version 5.71). FFM was estimated using a four-component model from measures of body density by hydrostatic weighing, body water by deuterium dilution, and bone mineral by DXA. There was no significant relation of BMD to MFFM( r = 0.01) or DFFM ( r = −0.06) or of BMC to MFFM ( r = −0.11) and a significant, weak negative relation of BMC to DFFM( r = −0.14, P = 0.04) in all subjects. Significant low to moderate relationships of BMD or BMC to MFFM or DFFM were found within some gender-race-athletic status subgroups or when the effects of gender, race, and athletic status were held constant using multiple regression, but BMD and BMC explained only 10–17% of the variance in MFFM and 0–2% of the variance in DFFM in addition to that explained by the demographic variables. We conclude that there is not a significant positive relation of BMD and BMC to MFFM or DFFM in young adults and that BMC and BMD should not be used to infer differences in MFFM or DFFM.

Bone health and multiple sclerosis

2012 ◽  
Vol 18 (11) ◽  
pp. 1522-1528 ◽  
Author(s):  
Ruth Dobson ◽  
Sreeram Ramagopalan ◽  
Gavin Giovannoni
Keyword(s):  
Multiple Sclerosis ◽  
Bone Mineral Density ◽  
Clinical Practice ◽  
General Population ◽  
Fracture Risk ◽  
Bone Mineral ◽  
Bone Health ◽  
Mineral Density ◽  
Low Bone Mineral Density ◽  
The Relationship

People with multiple sclerosis (MS) have many reasons to have low bone mineral density and an increased fracture risk. Osteoporosis is a major cause of morbidity and mortality, and is more common in people with MS than the general population. A number of studies have examined the relationship between multiple sclerosis and reduced bone mineral density. In this topical review we seek to address the risk of low bone mineral density, osteoporosis and fractures associated with MS, and make practical suggestions as to how this pertinent issue may be approached in clinical practice.

scholarly journals Assessment of total and regional bone mineral density using bioelectrical impedance vector analysis in elderly population

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hsueh-Kuan Lu ◽  
Chung-Liang Lai ◽  
Li-Wen Lee ◽  
Lee-Ping Chu ◽  
Kuen-Chang Hsieh
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Bioelectrical Impedance ◽  
The Elderly ◽  
Whole Body ◽  
Mineral Density ◽  
Femur Neck ◽  
Impedance Vector ◽  
The Relationship ◽  
Different Levels

AbstractThis study aimed to investigate the relationship between bone mineral density (BMD) and height-adjusted resistance (R/H), reactance (Xc/H) and phase angle (PhA). A total of 61 male and 64 female subjects aged over 60 years were recruited from middle Taiwan. The R and Xc were measured using Bodystat Quadscan 4000 at a frequency of 50 kHz. BMD at the whole body, L2–L4 spine, and dual femur neck (DFN), denoted as BMDTotal, BMDL2–L4, and BMDDFN, were calculated using a Hologic DXA scanner. The R-Xc graph was used to assess vector shift among different levels of BMD. BMD was positively correlated with Xc/H and negatively correlated with R/H (p < 0.001). The General Linear Model (GLM) regression results were as follows: BMDTotal = 1.473–0.002 R/H + 0.007 Xc/H, r = 0.684; BMDL2–L4 = 1.526–0.002 R/H + 0.012 Xc/H, r = 0.655; BMDDFN = 1.304–0.002 R/H + Xc/H, r = 0.680; p < 0.0001. Distribution of vector in the R-Xc graph was significantly different for different levels of BMDTotal, BMDL2–L4 and BMDDFN. R/H and Xc/H were correlated with BMD in the elderly. The linear combination of R/H and Xc/H can effectively predict the BMD of the whole body, spine and proximal femur, indicating that BIVA may be used in clinical and home-use monitoring tool for screening BMD in the elderly in the future.

scholarly journals SAT0485 PERCENTAGE BODY FAT HAS A STRONGER ASSOCIATION WITH BONE MINERAL DENSITY AT THE HIP AND SPINE COMPARED TO BODY MASS INDEX

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1198.1-1199
Author(s):  
C. Thurston ◽  
R. Tribbick ◽  
J. Kerns ◽  
F. Dondelinger ◽  
M. Bukhari
Keyword(s):  
Risk Factors ◽  
Bone Mineral Density ◽  
Body Mass Index ◽  
Confidence Intervals ◽  
Bone Mineral ◽  
Effect Size ◽  
Bone Health ◽  
P Value ◽  
Mineral Density ◽  
The Relationship

Background:A decreased body mass index (BMI) is associated with poorer bone health, a decreased bone mineral density (BMD), and an increased fracture risk. Cardiovascular (CVS) data has shown that the waist:hip ratio is a more robust measurement for CVS outcomes than BMI (1). Waist:hip ratio has never been evaluated as an outcome measure for bone health. Dual-energy x-ray absorptiometry (DEXA) has the capacity to measure average percentage fat in the L1-L4 region and at the hip, and directly relates to the measurement of waist:hip ratio.Objectives:To evaluate the relationship between BMD and average percent fat in a cohort referred for DEXA scanning.Methods:We analysed data routinely collected from patients referred for DEXA between 2004 and 2010 at the Royal Lancaster Infirmary in the North of England. Data collected for these patients included DEXA scans of BMD at the left and right hip, and at the lumbar spine, as well as average percent far and other risk factors for osteoporosis, including the FRAX risk factors. We used only the measures collected at baseline (time of first scan). We modelled the T scores of the BMD measurements using a linear regression model including percentage fat and BMI as explanatory variables, and adjusting for gender, age at scan, and other known risk factors for osteoporosis, including the FRAX risk factors. BMI and average percent fat were standardised.Results:The number of patients included was 33037, (82% female). Results of both regression models are shown in table 1 below. We show the standardised effect size estimates for average percent fat and BMI.Anatomical locationEffect size estimate for average percent fat (95% confidence intervals)P valueEffect size estimate for BMI (95% confidence intervals)P valueLeft neck-0.156 (-0.171, -0.141)<0.001-0.0255 (-0.0441, -0.00701)0.00692Left total-0.225 (-0.241, -0.208)<0.001-0.0680 (-0.0882, -0.0477)<0.001Left Ward’s-0.181 (-0.196, -0.166)<0.001-0.0268 (-0.0456, -0.00813)0.00493Left trochanter-0.263 (-0.281, -0.246)<0.001-0.0667 (-0.0882, -0.0451)<0.001Right neck-0.139 (-0.154, -0.124)<0.001-0.0131 (-0.0317, 0.00549)0.167Right total-0.221 (-0.237, -0.204)<0.001-0.0611 (-0.0811, -0.0411)<0.001Right Ward’s-0.180 (-0.196, -0.165)<0.001-0.0193 (-0.0381, -0.000586)0.0433Right trochanter-0.261 (-0.278, -0.243)<0.001-0.0598 (-0.0810, -0.0386)<0.001Spine (averaged L1-L4)0.219 (0.195, 0.242)<0.001-0.00846 (-0.0379, 0.0206)0.563Conclusion:The analysis shows that average percent fat is a statistically significant predictor for BMD at different anatomical locations, and a larger predictor in comparison to BMI when evaluated in the same model. In the right hip neck and the spine, BMI was not predictive of changes in BMD. Higher average percent fat increases the BMD in the spine, compared to a decline at the hip. Further research is needed to characterise the relationship more precisely and identify whether there is a causal link.References:[1]Obes Rev. 2012 Mar;13(3):275-86. doi: 10.1111/j.1467-789X.2011.00952.xDisclosure of Interests:None declared

scholarly journals Relationship between anthropometric/metabolic parameters and bone mineral density in younger adults

2020 ◽  
Vol 79 (OCE2) ◽  
Author(s):  
Roberta Hack-Mendes ◽  
Lorraine Brennan
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Metabolic Parameters ◽  
Whole Body ◽  
Mineral Density ◽  
Age Related ◽  
Gender And Age ◽  
Males And Females ◽  
The Mean ◽  
The Relationship

AbstractIntroductionOsteoporosis is characterized by low bone mineral density (BMD) and increased susceptibility to low trauma fractures(1).The relationship between osteoporosis risk and general metabolic health parameters is poorly understood. The aim of this study was to investigate the relationship between anthropometric and metabolic parameters with BMD in Adults.Materials and MethodsA total of 214 (100 male and 114 female) healthy adults were recruited. The mean age was 32 ± 10 years for males and 31 ± 11 years for females. BMD was assessed by whole body dual energy X ray- absorptiometry (Dexa scan). Dexa scores were reported as total bone mineral density, T-score and Z-score. Anthropotemetric measures included body weight, height, waist circumference. Basal metabolic rate (BMR) was assessed by indirect calorimetry. Tertiles of BMD were obtained for males and females. Assessment of parameters across BMD tertiles was performed in males and females separately using ANOVA. Relationships between parameters was assessed using Spearman correlation analysis controlling for gender and age where appropriate.ResultsBMI, Weight and BMR increased significantly across the tertiles for both genders. The mean weight, BMI and BMR were significantly increased in the males at the highest tertile of BMD. Positive correlations (adjusted for gender and age) were observed between weight, BMI, BMR and BMD (R2 = 0.404; p = 0.001, R2 = 0.348, p = 0.001; R2 = 0.363; p = 0.001, respectively).ConclusionsOverall, the results confirm the relationships between BMD and BMI and weight in a healthy cohort. Furthermore, it highlights a relationship between BMR and BMD. Targeting improvement in body composition and BMR may be a strategy for the age-related decline in BMD.

Low Testosterone Levels Are Associated With Poor Peripheral Bone Mineral Density and Quantitative Bone Ultrasound at Phalanges and Calcaneus in Healthy Elderly Men

2014 ◽  
Vol 17 (2) ◽  
pp. 169-174 ◽  
Author(s):  
Jose M. Moran ◽  
Raul Roncero Martin ◽  
Maria Pedrera-Canal ◽  
Javier Alonso-Terron ◽  
Francisco J. Rodriguez-Velasco ◽  
...  
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Bone Health ◽  
Normal Serum ◽  
Total Serum ◽  
Mineral Density ◽  
Os Calcis ◽  
Healthy Elderly ◽  
The Relationship ◽  
Peripheral Bone

Variations in sex hormones influence bone health in men. Aging in men is associated with a decrease in testosterone (T) levels. We examined the relationship between T levels and changes in bone health status as measured by quantitative ultrasound (QUS) at the phalanges and the os calcis and by peripheral bone mineral density (pBMD) at the phalanges in healthy elderly Spanish men. We examined 162 men aged 65–88 years and assessed total serum T concentrations. Total serum T < 300 ng/dL was used as the threshold for biochemical T deficiency. The sample was divided into low ( n = 66) or normal ( n = 96) T levels; both groups were matched for age, weight, height, and body mass index ( p > .05 for all the comparisons). All measured bone parameters were higher in the normal serum T group ( p < .05). Multiple regression analysis revealed that serum T was an independent predictor of both QUS at the calcaneus and phalangeal pBMD. Our data indicate that T is an independent determinant of QUS at the os calcis and pBMD at the phalanges in elderly Spanish men.

scholarly journals Machine Learning Reveals Influence of Stool pH on Bone Mineral Density in a Healthy Multi-Ethnic U.S. Population

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 8-8
Author(s):  
Elizabeth Chin ◽  
Marta Van Loan ◽  
Sarah Spearman ◽  
Ellen Bonnel ◽  
Kevin Laugero ◽  
...  
Keyword(s):  
Machine Learning ◽  
Bone Mineral Density ◽  
Bone Mineral ◽  
Bone Health ◽  
Whole Body ◽  
Fiber Intake ◽  
Learning Models ◽  
Mineral Density ◽  
Modifiable Factors ◽  
Machine Learning Models

Abstract Objectives A variety of modifiable and non-modifiable factors such as ethnicity, age, and diet have been shown to influence bone health. Previous studies are usually limited to analyses focused on the association of a few a priori variables or on a specific subset of the population. The objective of this study was to use dietary, physiological, and lifestyle data to identify directly modifiable and non-modifiable variables predictive of bone mineral content (BMC) and bone mineral density (BMD) in healthy US men and women using machine learning models. Methods Ridge, lasso, elastic net, and random forest models were used to predict whole-body, femoral neck, and spine BMC and BMD in healthy US adults (n = 313) using non-modifiable anthropometric, physiological, and demographic variables, directly modifiable lifestyle (physical activity, tobacco use) and dietary (nutrient or food groups intake via food frequency questionnaire) variables, and variables approximating directly modifiable behavior (circulating vitamin D and stool pH). Model feature importances were used to identify variables useful for predicting BMC and BMD. Results Machine learning models using non-modifiable variables explained more variation in BMC and BMD (highest R2 = 0.750) compared to when using only directly modifiable variables (highest R2 = 0.107). Machine learning models had better performance compared to multivariate linear regression, which had lower predictive value (highest R2 = 0.063) when using directly modifiable variables only. BMI, body fat %, height, and menstruation history were predictors of BMC and BMD. For the directly modifiable features, betaine, cholesterol, hydroxyproline, menaquinone-4, dihydrophylloquinone, eggs, cheese, cured meat, refined grains, fruit juice, and alcohol consumption were predictors of BMC and BMD. Low stool pH, a proxy for fermentable fiber intake, was also predictive of higher BMC and BMD. Conclusions Machine learning models can be used to identify previously unforeseen variables that may contribute to bone health. Modifiable factors explained less variation in the data compared to other features. Low stool pH, which has been shown to be associated with fermentable fiber intake, short chain fatty acid production, and enhanced calcium absorption, was associated with higher BMC and BMD in a healthy US population. Funding Sources USDA-ARS

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