The effect of ethnicity on the age-related changes of spinopelvic characteristics: a systematic review
Bibliographic record
Abstract
Spinopelvic characteristics influence the hip's biomechanical behaviour. However, to date there is little knowledge defining what 'normal' spinopelvic characteristics are. This study aims to determine how static spinopelvic characteristics change with age and ethnicity among asymptomatic, healthy individuals. This systematic review followed the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines to identify English studies, including ≥ 18-year-old participants, without evidence of hip or spine pathology or a history of previous surgery or interventional treatment, documenting lumbar lordosis (LL), sacral slope (SS), pelvic tilt (PT), and pelvic incidence (PI). From a total of 2,543 articles retrieved after the initial database search, 61 articles were eventually selected for data extraction. When all ethnicities were combined the mean values for LL, SS, PT, and PI were: 47.4° (SD 11.0°), 35.8° (SD 7.8°), 14.0° (SD 7.2°), and 48.8° (SD 10°), respectively. LL, SS, and PT had statistically significant (p < 0.001) changes per decade at: -1.5° (SD 0.3°), -1.3° (SD 0.3°), and 1.4° (SD 0.1°). Asian populations had the largest age-dependent change in LL, SS, and PT compared to any other ethnicity per decade at: -1.3° (SD 0.3°) to -0.5° (SD 1.3°), -1.2° (SD 0.2°) to -0.3° (SD 0.3°), and 1.7° (SD 0.2°) versus 1.1° (SD 0.1°), respectively. Ageing alters the orientation between the spine and pelvis, causing LL, SS, and PT to modify their orientations in a compensatory mechanism to maintain sagittal alignment for balance when standing. Asian populations have the largest degree of age-dependent change to their spinopelvic parameters compared to any other ethnicity, likely due to their lower PI.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.011 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".