Co-relationships between core endurance, hip strength and balance in athletes
Bibliographic record
Abstract
Background: In Athletics, running is the most effective way to improve cardiopulmonary endurance and overall health. But simultaneously it is also associated with high-risk musculoskeletal injuries. Nearly 50 % of injuries in regular runners are because of overuse and the prevalence of lumbar spine and lower limb injuries is higher in the athletic population. Most of the common injuries are associated with poor core endurance, altered biomechanics, and lack of proper trunk and lower extremity muscle strength. Core muscle endurance, lower extremity musculature strengthening, and neuromuscular control are commonly used to enhance athletic performance. However, based on the literature review, the precise impact of back core muscle endurance, hip muscle strength, and balance is still not clear. So, the purpose of this study was to find out the relationship between core endurance, hip strength, and balance in athletes, as well as to find out the normative data for trunk core endurance, hip muscle strength, and balance in athletes. Method: After obtaining ethical approval from the institutional ethical committee and informed concern, 187 healthy long-distance runners, including 136 males and 51 females, between the age group of 18 to 35 with a Mean age is 27.07+4.52 for Males and 25.94+4.13 for females included this study. Core endurance (Anterior, posterior, and lateral) was measured using Mcgill’s endurance test, hip muscle (flexors, extensors, and abductors) strength was measured using an MMT handheld dynamometer, and balance was measured using a star excursion balance test. Data Analysis and Result: All statistical Data analysis was done using SPSS version 21.0 at an alpha level of 0.05. Pearson product correlation was used to examine the relationship between core endurance, hip strength, and balance. A linear regression analysis was used to check the influence of core endurance and hip strength on balance. Conclusion: Trunk core endurance was fairly correlated with hip flexors, extensors, and abductors muscle strength. There was a Fair positive correlation existed between anterior, posterior, left, and right lateral core endurance and SEBT com score. There was a strong correlation between hip flexor strength and balance bilaterally. This conclusion implies that when the hip flexors (e.g., the quadriceps) are stronger, an individual may reach further forward. And there was a fair correlation between hip extensors, abductors, and balance. This study also established normative data for trunk core endurance, hip muscle strength, and balance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".