Prevalence and Trends of Handgrip Strength Asymmetry in the United States
Bibliographic record
Abstract
Background: Strength asymmetries are a type of muscle function impairment that is associated with several health conditions. However, the prevalence of these asymmetries among adults from the United States remains unknown. We sought to estimate the prevalence and trends of handgrip strength (HGS) asymmetry in American adults. Methods: The unweighted analytic sample included 23,056 persons aged at least 50-years with information on HGS for both hands from the 2006-2016 waves of the Health and Retirement Study. A handgrip dynamometer measured HGS, with the highest recorded values for each hand used to calculate asymmetry. Persons were categorized into the following asymmetry severity categories: (1) >10%, (2) >20.0%, and (3) >30.0%. Survey weights were used to generate nationally-representative asymmetry estimates. Results: Overall, there were no statistically significant trends in HGS asymmetry categories over time. The prevalence of HGS asymmetry in the 2014-2016 wave was 53.4% (CI: 52.2-54.4), 26.0% (CI: 25.0-26.9), and 11.7% (CI: 10.9-12.3) for asymmetry at >10%, >20%, and >30%, respectively. HGS asymmetry was generally higher in older Americans compared to middle-aged adults at each wave. In the 2014-2016 wave, >30% asymmetry prevalence was 13.7% (CI: 12.7-14.6) in females and 9.3% (CI: 8.4-10.2) in males. Some differences in asymmetry prevalence by race and ethnicity were observed. Conclusions: The prevalence of asymmetry was generally high, especially in women and older adults. Ongoing surveillance of strength asymmetry will help monitor trends in muscle dysfunction, guide screening for disablement, identify subpopulations at risk for asymmetry, and inform relevant interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".