Reference ranges of handgrip strength from 125,462 healthy adults in 21 countries: a prospective urban rural epidemiologic (PURE) study
Bibliographic record
Abstract
Abstract Background The measurement of handgrip strength (HGS) has prognostic value with respect to all‐cause mortality, cardiovascular mortality and cardiovascular disease, and is an important part of the evaluation of frailty. Published reference ranges for HGS are mostly derived from Caucasian populations in high‐income countries. There is a paucity of information on normative HGS values in non‐Caucasian populations from low‐ or middle‐income countries. The objective of this study was to develop reference HGS ranges for healthy adults from a broad range of ethnicities and socioeconomically diverse geographic regions. Methods HGS was measured using a Jamar dynamometer in 125,462 healthy adults aged 35‐70 years from 21 countries in the Prospective Urban Rural Epidemiology (PURE) study. Results HGS values differed among individuals from different geographic regions. HGS values were highest among those from Europe/North America, lowest among those from South Asia, South East Asia and Africa, and intermediate among those from China, South America, and the Middle East. Reference ranges stratified by geographic region, age, and sex are presented. These ranges varied from a median (25 th –75 th percentile) 50 kg (43–56 kg) in men <40 years from Europe/North America to 18 kg (14–20 kg) in women >60 years from South East Asia. Reference ranges by ethnicity and body‐mass index are also reported. Conclusions Individual HGS measurements should be interpreted using region/ethnic‐specific reference ranges.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".