An Evidence-Based Comparison of Operational Criteria for the Presence of Sarcopenia

Background. Several consensus groups have previously published operational criteria for sarcopenia, incorporating lean mass with strength and/or physical performance. The purpose of this manuscript is to describe the prevalence, agreement, and discrepancies between the Foundation for the National Institutes of Health (FNIH) criteria with other operational definitions for sarcopenia. Methods. The FNIH Sarcopenia Project used data from nine studies including: Age, Gene and Environment Susceptibility-Reykjavik Study; Boston Puerto Rican Health Study; a series of six clinical trials from the University of Connecticut; Framingham Heart Study; Health, Aging, and Body Composition Study; Invecchiare in Chianti; Osteoporotic Fractures in Men Study; Rancho Bernardo Study; and Study of Osteoporotic Fractures. Participants included in these analyses were aged 65 and older and had measures of body mass index, appendicular lean mass, grip strength, and gait speed. Results. The prevalence of sarcopenia and agreement proportions was higher in women than men. The lowest prevalence was observed with the FNIH criteria (1.3% men and 2.3% women) compared with the International Working Group and the European Working Group for Sarcopenia in Older Persons (5.1% and 5.3% in men and 11.8% and 13.3% in women, respectively). The positive percent agreements between the FNIH criteria and other criteria were low, ranging from 7% to 32% in men and 5% to 19% in women. However, the negative percent agreement were high (all >95%). Conclusions. The FNIH criteria result in a more conservative operational definition of sarcopenia, and the prevalence was lower compared with other proposed criteria. Agreement for diagnosing sarcopenia was low, but agreement for ruling out sarcopenia was very high. Consensus on the operational criteria for the diagnosis of sarcopenia is much needed to characterize populations for study and to identify adults for treatment

Association of vitamin D status with arterial blood pressure and hypertension risk : a mendelian randomisation study

Peer reviewe

Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions

A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P <1 x 10(-6)) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P <5 x 10(-8) using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.Peer reviewe

The relationship between visual function and physical performance in the Study of Muscle, Mobility and Aging (SOMMA).

PurposeThe relationship of types of visual function to different aspects of physical function, especially strength and coordination, has been understudied, but delineation of these relationships could suggest potentially modifiable targets prior to the onset of disability.MethodsCross-sectional analysis of visual function (self-reported eyesight and eye disease, visual acuity, contrast sensitivity) and physical function tests in 877 older adults (mean age 76.36±5.01 years, 59.2% women, and 13.3% Black race). Separate linear regression models were constructed for short physical performance battery (SPPB), expanded SPPB (eSPPB), their components (gait speed, chair stand, balance, narrow walk), stair climb, four-square step, leg extension peak power and strength, and grip strength.ResultsIn adjusted models, worse acuity, worse contrast sensitivity, and self-reported poor vision were significantly associated with worse performance on the eSPPB and four-square step test. Worse contrast sensitivity, but not acuity, was significantly associated with shorter balance times, slower chair stand pace, longer stair climb time, and worse SPPB score. Associations of worse acuity and contrast sensitivity with weaker leg extension power, leg strength, and grip strength were attenuated by covariate adjustment. Self-reported macular degeneration, but not cataract or glaucoma, was associated with worse performance on SPPB, eSPPB, balance, stair climb, and four-square step tests in adjusted models. Worse contrast sensitivity and macular degeneration remained associated with worse SPPB and balance after controlling for visual acuity and self-reported eyesight.ConclusionsPoor contrast sensitivity was more strongly associated with worse physical performance than acuity, especially for complex tasks that dynamically challenge coordination and balance. Future studies should examine if older adults with contrast sensitivity impairment would benefit from targeted intervention to decrease their risk of disability

Strength and muscle quality in a well-functioning cohort of older adults: the Health, Aging and Body Composition Study

OBJECTIVES: To determine whether lower lean mass and higher fat mass have independent effects on the loss of strength and muscle quality in older adults and might explain part of the effect of age. DESIGN: Single-episode, cross-sectional analyses of a cohort of subjects in the Health, Aging and Body Composition (Health ABC) Study. SETTING: Ambulatory clinic and research laboratory. PARTICIPANTS: Two thousand six hundred twenty-three men and women aged 70 to 79 from the Health ABC Study. MEASUREMENTS: Upper and lower extremity strength was measured using isokinetic (knee extension) and isometric (grip strength) dynamometers. Body composition (lean mass and fat mass) was determined by measuring lean mass of upper and lower extremities and the total body by dual-energy x-ray absorptiometry. Muscle quality was ascertained by taking the ratio of strength to muscle mass for both upper and lower extremities. RESULTS: Upper and lower extremity strength and muscle quality decreased as age increased. Most of the explained variance in strength was due to differences in muscle mass, but, in those at the extremes of body fat and lower leg muscle quality, the association with body fat was independent of the effect of age. Although blacks had greater muscle strength and mass than whites, leg muscle quality tended to be lower in blacks than in whites. Upper extremity strength adjusted for lean mass and muscle quality were also associated inversely and independently with age, body fat, and black race. CONCLUSION: In this older cohort, lower strength with older age was predominantly due to a lower muscle mass. Age and body fat also had significant inverse associations with strength and muscle quality. Both preservation of lean mass and prevention of gain in fat may be important in maintaining strength and muscle quality in old age

Association of individual vision variables with tests of muscle function.

Association of individual vision variables with tests of muscle function.</p

Unadjusted bivariate and adjusted bivariate models between vision variables and tests of muscle function.

Plots show Beta (95% CI) for muscle function outcomes compared at levels of discrete visual function predictors (visual acuity (TIF)</p

Unadjusted bivariate and adjusted bivariate and multivariable models between multiple vision variables and traditional measures of physical performance.

Plots show Beta (95% CI) for physical performance outcomes compared at levels of discrete visual function predictors (self-reported poor vision, macular degeneration) or for a 1-unit difference in continuous predictors (logMAR visual acuity, -Log contrast sensitivity). Panel 1: Bivariate Unadjusted presents the unadjusted association between each measure of visual function and physical performance. Panel 2: Bivariate Adjusted presents the association between each measure of visual function and physical performance, adjusted for clinical and demographic covariates (age, gender, race, education, BMI, smoking status, alcohol consumption, diabetes mellitus, hypertension, heart disease, stroke, CESD-10). Panel 3: Multivariable Adjusted presents the association between multiple measures of visual function (self-reported poor vision, logMAR visual acuity, -log contrast sensitivity) and physical performance adjusted for clinical and demographic covariates (age, gender, race, education, BMI, smoking status, alcohol consumption, diabetes mellitus, hypertension, heart disease, stroke, CESD-10). Panel 4: Multivariable Adjusted + MD presents the association between multiple measures of visual function (self-reported poor vision, logMAR visual acuity, -log contrast sensitivity, plus macular degeneration (MD)) and physical performance, adjusted for clinical and demographic covariates (age, gender, race, education, BMI, smoking status, alcohol consumption, diabetes mellitus, hypertension, heart disease, stroke, CESD-10). The physical performance outcomes are A) short physical performance battery (SPPB) B) gait speed, C) chair stand pace, and D) balance time. *-1 unit log contrast sensitivity.</p

Unadjusted bivariate and adjusted bivariate and multivariable models between multiple vision variables and more challenging tests of physical performance and tests of muscle function.

Plots show Beta (95% CI) for physical function outcomes compared at levels of discrete visual function predictors (self-reported poor vision, macular degeneration) or for a 1- unit difference in continuous predictors (logMAR visual acuity, -log contrast sensitivity). Panel 1: Bivariate Unadjusted presents the unadjusted association between each measure of visual function and physical performance or muscle function. Panel 2: Bivariate Adjusted presents the association between each measure of visual function and physical performance or muscle function, adjusted for clinical and demographic covariates (age, gender, race, education, BMI, smoking status, alcohol consumption, diabetes mellitus, hypertension, heart disease, stroke, CESD-10). Panel 3: Multivariable Adjusted presents the association between multiple measures of visual function (self-reported poor vision, logMAR visual acuity, -log contrast sensitivity) and physical performance or muscle function, adjusted for clinical and demographic covariates (age, gender, race, education, BMI, smoking status, alcohol consumption, diabetes mellitus, hypertension, heart disease, stroke, CESD-10). Panel 4: Multivariable Adjusted + MD presents the association between multiple measures of visual function (self-reported poor vision, logMAR visual acuity, -log contrast sensitivity, plus macular degeneration (MD)) and physical performance or muscle function, adjusted for clinical and demographic covariates (age, gender, race, education, BMI, smoking status, alcohol consumption, diabetes mellitus, hypertension, heart disease, stroke, CESD-10). The physical performance and muscle function outcomes are A) expanded short physical performance battery (eSPPB) B) narrow walk speed, C) stair climb time, D) four-square step test time, E) leg extension peak power, F) leg extension strength, and G) grip strength. *-1 unit log contrast sensitivity.</p