Age Trajectories of Grip Strength: Cross-Sectional and Longitudinal Data Among 8,342 Danes Aged 46 to 102

Frederiksen, Henrik; Hjelmborg, Jacob; Mortensen, Jakob; McGue, Matt; Vaupel, James W.; Christensen, Kaare

doi:10.1016/j.annepidem.2005.10.006

Cited by 248 publications

(248 citation statements)

References 42 publications

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“…The HGS results observed in our sample are considerably lower than those reported in other studies carried out with hospital patients (Klidjian et al, 1980;Klidjian et al, 1982) and healthy subjects (Luna-Heredia et al, 2005;Frederiksen et al, 2006). Grip strength distribution of our sample shows a large proportion of patients with zero or extremely low values.…”

Section: Discussioncontrasting

confidence: 89%

“…When compared with Danish reference data (Frederiksen et al, 2006), values for HGS below À1.96 Z-scores (2.5%) for standardized sex, age and height were found in all patients. It is unclear whether this could represent a high level of poor muscle function associated with undernutrition, functional impairment and disease in our sample patients or if revised standardized values are required for HGS in hospitalized patients.…”

Section: Discussionmentioning

confidence: 81%

“…Z-scores were calculated using Frederiksen et al (2006) recently published HGS reference data. For all gender-, ageand height-specific subsets of patients the estimated mean Z-score were lower than À2.00.…”

Section: Resultsmentioning

confidence: 99%

“…Grip strength distribution of our sample shows a large proportion of patients with zero or extremely low values. They were more likely to be female and older, as described previously (Luna-Heredia et al, 2005;Frederiksen et al, 2006). In this first approach to evaluate the nutritional screening value of HGS, we tried to simulate a normal screening procedure in a hospital setting.…”

Section: Discussionmentioning

confidence: 99%

“…It is unclear whether this could represent a high level of poor muscle function associated with undernutrition, functional impairment and disease in our sample patients or if revised standardized values are required for HGS in hospitalized patients. Available preliminary data suggest that mean HGS may vary across countries, regardless of height (Frederiksen et al, 2006) and therefore highlights the need for Portuguese reference data. Another possible explanation for the lower HGS values found in the present study is the choice of the non-dominant hand for grip strength measurements, as lower values were described previously for HGS measurements made with the non-dominant hand Hornby et al, 2005;Luna-Heredia et al, 2005).…”

Section: Discussionmentioning

confidence: 99%

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Handgrip strength as a hospital admission nutritional risk screening method

2007

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Objective: To investigate if handgrip strength (HGS) could be used as a single screening procedure in identifying patients who are classified as being undernourished or nutritionally-at-risk at hospital admission. Design: Cross-sectional study. In the second day of hospital admission, HGS was evaluated and results were compared with Nutritional Risk Screening (NRS-2002). Setting: Two public hospitals in Porto, Portugal, a university and a district one. Subjects: A probabilistic sample of 50% in-patients from each hospital of 314 patients (age range of 18-96) was studied. Patients were considered eligible if they were X18 years old and able to give informed consent. Hand pain, upper limb deformities, incapacity to perform muscle strength measurements and pregnancy were considered further exclusion criteria. Results: Patients identified as undernourished by NRS-2002 (37.9%) were older, shorter and lighter, with a lower functional capacity, a longer length of stay and a lower HGS (Po0.001). When comparing patients with lower HGS (first quartile) with those with the highest HGS (fourth quartile), this parameter revealed good sensitivity (86.7%) and specificity (70.2%) and a k ¼ 0.56. Multivariate analysis showed that patients with higher HGS had an independent decreased risk of being at nutritional risk (P for trend o0.001) odds ratio ¼ 0.19 (95% confidence interval ¼ 0.08-0.48). Our entire sample of hospitalized patients was À1.96 Z-score below the HGS cutoff of distribution data for healthy individuals. Conclusions: HGS identifies a high proportion of nutritionally-at-risk patients and can be a reliable first screening tool for nutritional risk in hospitals. Sponsorship: Fundação Ilídio Pinho and Reitoria of the University of Porto -Programa Investigação Científica na Pré-graduação.

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Section: Discussioncontrasting

confidence: 89%

Section: Discussionmentioning

confidence: 81%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Handgrip strength as a hospital admission nutritional risk screening method

2007

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Motor Functions and Mobility

Darling¹,

Cole²,

Ashton‐Miller³

2018

The Wiley Handbook on the Aging Mind and Brain

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Bayesian longitudinal plateau model of adult grip strength

Nahhas

Choh

Lee

et al. 2010

American J Hum Biol

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Objectives This article illustrates the use of applied Bayesian statistical methods in modeling the trajectory of adult grip strength and in evaluating potential risk factors that may influence that trajectory. Methods The data consist of from 1 to 11 repeated grip strength measurements from each of 498 men and 533 women age 18–96 years in the Fels Longitudinal Study (Roche AF. 1992. Growth, maturation and body composition: the Fels longitudinal study 1929–1991. Cambridge: Cambridge University Press). In this analysis, the Bayesian framework was particularly useful for fitting a nonlinear mixed effects plateau model with two unknown change points and for the joint modeling of a time-varying covariate. Multiple imputation (MI) was used to handle missing values with posterior inferences appropriately adjusted to account for between-imputation variability. Results On average, men and women attain peak grip strength at the same age (36 years), women begin to decline in grip strength sooner (age 50 years for women and 56 years for men), and men lose grip strength at a faster rate relative to their peak; there is an increasing secular trend in peak grip strength that is not attributable to concurrent secular trends in body size, and the grip strength trajectory varies with birth weight (men only), smoking (men only), alcohol consumption (men and women), and sports activity (women only). Conclusions Longitudinal data analysis requires handling not only serial correlation but often also time-varying covariates, missing data, and unknown change points. Bayesian methods, combined with MI, are useful in handling these issues.

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Age Trajectories of Grip Strength: Cross-Sectional and Longitudinal Data Among 8,342 Danes Aged 46 to 102

Cited by 248 publications

References 42 publications

Handgrip strength as a hospital admission nutritional risk screening method

Handgrip strength as a hospital admission nutritional risk screening method

Motor Functions and Mobility

Bayesian longitudinal plateau model of adult grip strength

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