Objectives
To compare the relative predictive power of handgrip and leg extension strength in predicting slow walking.
Design
Report of correlative analysis from two epidemiological cohort studies.
...Setting
Foundation of the National Institutes of Health Sarcopenia Project.
Participants
Men and women aged 67 to 93 (N = 6,766).
Measurements
Leg strength, handgrip strength, and gait speed were measured. Strength cutpoints associated with slow gait speed were developed using classification and regression tree analyses and compared using ordinary least squares regression models.
Results
The cutpoints of lower extremity strength associated with slow gait speed were 154.6 N‐m in men and 89.9 N‐m in women for isometric leg extension strength and 94.5 N‐m in men and 62.3 N‐m in women for isokinetic leg extension strength. Weakness defined according to handgrip strength (odds ratios (OR) = 1.99 to 4.33, c‐statistics = 0.53 to 0.67) or leg strength (ORs = 2.52 to 5.77; c‐statistics = 0.61 to 0.66) was strongly related to odds of slow gait speed. Lower extremity strength contributed 1% to 16% of the variance and handgrip strength contributed 3% to 17% of the variance in the prediction of gait speed depending on sex and mode of strength assessment.
Conclusion
Muscle weakness of the leg extensors and forearm flexors is related to slow gait speed. Leg extension strength is only a slightly better predictor of slow gait speed. Thus, handgrip and leg extension strength appear to be suitable for screening for muscle weakness in older adults.
Body fat distribution, particularly centralized obesity, is associated with metabolic risk above and beyond total adiposity. We performed genome-wide association of abdominal adipose depots ...quantified using computed tomography (CT) to uncover novel loci for body fat distribution among participants of European ancestry. Subcutaneous and visceral fat were quantified in 5,560 women and 4,997 men from 4 population-based studies. Genome-wide genotyping was performed using standard arrays and imputed to ~2.5 million Hapmap SNPs. Each study performed a genome-wide association analysis of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), VAT adjusted for body mass index, and VAT/SAT ratio (a metric of the propensity to store fat viscerally as compared to subcutaneously) in the overall sample and in women and men separately. A weighted z-score meta-analysis was conducted. For the VAT/SAT ratio, our most significant p-value was rs11118316 at LYPLAL1 gene (p = 3.1 × 10E-09), previously identified in association with waist-hip ratio. For SAT, the most significant SNP was in the FTO gene (p = 5.9 × 10E-08). Given the known gender differences in body fat distribution, we performed sex-specific analyses. Our most significant finding was for VAT in women, rs1659258 near THNSL2 (p = 1.6 × 10-08), but not men (p = 0.75). Validation of this SNP in the GIANT consortium data demonstrated a similar sex-specific pattern, with observed significance in women (p = 0.006) but not men (p = 0.24) for BMI and waist circumference (p = 0.04 women, p = 0.49 men). Finally, we interrogated our data for the 14 recently published loci for body fat distribution (measured by waist-hip ratio adjusted for BMI); associations were observed at 7 of these loci. In contrast, we observed associations at only 7/32 loci previously identified in association with BMI; the majority of overlap was observed with SAT. Genome-wide association for visceral and subcutaneous fat revealed a SNP for VAT in women. More refined phenotypes for body composition and fat distribution can detect new loci not previously uncovered in large-scale GWAS of anthropometric traits.
Clinical retrospective studies have only reported limited improvements in hip fracture classification accuracy using finite element (FE) models compared to conventional areal bone mineral density ...(aBMD) measurements. A possible explanation is that state-of-the-art quasi-static models do not estimate patient-specific loads. A novel FE modeling technique was developed to improve the biofidelity of simulated impact loading from sideways falling. This included surrogate models of the pelvis, lower extremities, and soft tissue that were morphed based on subject anthropometrics. Hip fracture prediction models based on aBMD and FE measurements were compared in a retrospective study of 254 elderly female subjects from the AGES-Reykjavik study. Subject fragility ratio (FR) was defined as the ratio between the ultimate forces of paired biofidelic models, one with linear elastic and the other with non-linear stress-strain relationships in the proximal femur. The expected end-point value (EEV) was defined as the FR weighted by the probability of one sideways fall over five years, based on self-reported fall frequency at baseline. The change in maximum volumetric strain (ΔMVS) on the surface of the femoral neck was calculated between time of ultimate femur force and 90% post-ultimate force in order to assess the extent of tensile tissue damage present in non-linear models. After age-adjusted logistic regression, the area under the receiver-operator curve (AUC) was highest for ΔMVS (0.72), followed by FR (0.71), aBMD (0.70), and EEV (0.67), however the differences between FEA and aBMD based prediction models were not deemed statistically significant. When subjects with no history of falling were excluded from the analysis, thus artificially assuming that falls were known a priori with no uncertainty, a statistically significant difference in AUC was detected between ΔMVS (0.85), and aBMD (0.74). Multivariable linear regression suggested that the variance in maximum elastic femur force was best explained by femoral head radius, pelvis width, and soft tissue thickness (R2 = 0.79; RMSE = 0.46 kN; p < 0.005). Weighting the hip fracture prediction models based on self-reported fall frequency did not improve the models' sensitivity, however excluding non-fallers lead to significant differences between aBMD and FE based models. These findings suggest that an accurate assessment of fall probability is necessary for accurately identifying individuals predisposed to hip fracture.
•254 subject-specific dynamic FE models of sideways fall were generated with pelvis, lower-extremities, and soft tissue.•Hip fracture risk models based on FEA had higher AUC than aBMD models, but not statistically significant.•Excluding non-fallers provided statistically significant AUC difference between strain-based predictor and total femur aBMD.•Simulated femur impact force was predicted as a function of pelvis width, femoral head radius, and soft tissue thickness.•Force reduction between the ultimate contact forces at the femoral head and the ground correlated with soft tissue thickness.
Cerebral infarcts increase the risk for cognitive impairment. The relevance of location and number of infarcts with respect to cognitive function is less clear.
We studied the cross-sectional ...association between number and location of infarcts and cognitive performance in 4030 nondemented participants of the Age Gene/Environment Susceptibility-Reykjavik Study. Composite scores for memory, processing speed, and executive function were created from a neuropsychological battery. Subcortical, cortical, and cerebellar infarcts were identified on brain MRI. We performed linear regression analyses adjusted for demographic and vascular risk factors, depression, white matter lesions, and atrophy.
Compared to participants with no infarcts, those with infarcts in multiple locations (n=287, 7%) had slower processing speed (beta=-0.19; P<0.001) and poorer memory (beta=-0.16; P<0.001) and executive function (beta=-0.12; P=0.003). Compared to no infarcts, the presence of either subcortical infarcts only (n=275; beta=-0.12; P=0.016) or cortical infarcts only (n=215; beta=-0.17; P=0.001) was associated with poorer memory performance. Compared to no infarcts, a combination of cortical and subcortical infarcts (n=45) was associated with slower processing speed (beta=-0.38; P<0.001) and poorer executive function (beta=-0.22; P=0.02), whereas a combination of cerebellar and subcortical infarcts (n=89) was associated with slower processing speed (beta=-0.15; P=0.04). Infarcts in all 3 locations was associated with slower processing speed (beta=-0.33; P=0.002).
Having infarcts in >1 location is associated with poor performance in memory, processing speed, and executive function, independent of cardiovascular comorbidities, white matter lesions, and brain atrophy, suggesting that both the number and the distribution of infarcts jointly contribute to cognitive impairment.
We have determined the relative allele frequency and estimated linkage disequilibrium between six DNA polymorphisms of the low density lipoprotein (LDL) receptor gene. Polymorphisms were detected ...using the enzymes SfaNI, TaqI, StuI, HincII, AvaII, and NcoI after DNA amplification by the polymerase chain reaction. Strong linkage disequilibrium was detected between many of the pair wise comparisons in a sample of 60 patients heterozygous for familial hypercholesterolaemia (FH). Using the enzymes HincII, NcoI, and SfaNI, 85% of patients were heterozygous for at least one polymorphism and thus potentially informative for cosegregation studies. The polymorphisms were used to follow the inheritance of the defective allele of the LDL receptor gene in the relatives of a patient with FH. Assays of LDL receptor activity on lymphoblastoid cell lines from two members of the family was used to confirm that the proband, but not the hypercholesterolaemic brother, had a defect in the LDL receptor. In the family, none of the children had inherited the allele of the LDL receptor gene inferred to be defective. The problems associated with this cosegregation approach to identify relatives of patients with a clinical diagnosis of FH are discussed.
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