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Record W4377138390 · doi:10.3389/fnagi.2023.1191197

Association between handgrip strength asymmetry and cognitive function across ethnicity in rural China: a cross-sectional study

2023· article· en· W4377138390 on OpenAlexaboutno aff
Wenjing Feng, Mingfeng Ma, Hanshu Gao, Wei Yuan, Ruixue Li, Hui Guo, Cuiying Gu, Zhaoqing Sun, Yao Zhang, Liqiang Zheng

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2023
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsCognitionEthnic groupConfidence intervalMedicineDemographyMontreal Cognitive AssessmentCross-sectional studyAssociation (psychology)DyslipidemiaGerontologyPsychologyInternal medicineObesityCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

Background Recently, the association between handgrip strength (HGS) asymmetry and cognition has been revealed, but evidences are still scarce. Particularly, the association between asymmetric HGS and cognitive performance in various cognitive domains is unclear and whether this association is stable across ethnic groups is unknown. Method The population was from a longitudinal study in rural areas of Fuxin, Liaoning, China. The Chinese version of Montreal Cognitive Assessment-Basic (MOCA-BC) was used to evaluate the cognitive function. The HGS ratio was calculated as maximal non-dominant HGS divided by maximal dominant HGS. HGS ratio <0.9 or >1.1 was classified as asymmetric dominant/non-dominant HGS, respectively. Generalized linear models were used to analyze the relationship between asymmetric HGS and cognitive function adjusted for HGS, handedness, wave, age, sex, education, ethnicity, smoking, drinking, physical labor level, BMI, hypertension, diabetes and dyslipidemia. Result A total of 2,969 participants ≥50 years were included in this study. Adjusted for HGS and other confunding variables, there was an inverted U-shaped association between HGS ratio and MoCA-BC scores ( P non – linear = 0.004). The association between HGS ratio and MoCA-BC scores was inconsistent among ethnic groups ( P interaction = 0.048). In Han, only asymmetric non-dominant HGS was associated with lower cognitive scores [β = −0.67, 95% confidence interval (CI): −1.26 ∼−0.08, P = 0.027]; in Mongolians, asymmetric dominant HGS(β = −0.60, 95% CI: −1.35 ∼ 0.15, P = 0.115) and asymmetric non-dominant HGS (β = −0.56, 95% CI: −1.42 ∼ 0.31, P = 0.206) were all associated with lower cognitive scores, although no statistical significance was found. Asymmetric non-dominant HGS and lower HGS, but not asymmetric dominant HGS were all independently associated with impairment of Delayed Recall (OR = 1.35, 95% CI: 1.05 ∼ 1.74; OR per 5 kg decrease = 1.10, 95% CI: 1.01 ∼ 1.21) and Fluency (OR = 1.43, 95% CI: 1.15 ∼ 1.78; OR per 5 kg decrease = 1.10, 95% CI: 1.02 ∼ 1.19). Both asymmetric dominant HGS (OR = 1.34, 95% CI: 1.07 ∼ 1.67) and lower HGS (OR per 5 kg decrease = 1.21, 95% CI: 1.10 ∼ 1.32) were associated with impairment of visuoperception. Conclusion HGS and HGS asymmetry were all independently related to lower global cognitive performance. The association between HGS asymmetry and cognitive function varies among ethnic groups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.006
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.327
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2023
Admission routes1
Has abstractyes

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