Cross-Sectional Examination of Musculoskeletal Pain and Physical Function in a Racially and Socioeconomically Diverse Sample of Adults
Bibliographic record
Abstract
BACKGROUND: Musculoskeletal pain alters physiological function, which may be evidenced as early as middle age. Previous research has concluded that middle-aged adults are a high-risk group for musculoskeletal pain and report functional limitations similar to older adults. However, few studies have examined the relationships between musculoskeletal pain and physical function, using objective performance measures in a sample of racially and socioeconomically diverse adults. Thus, this study examined musculoskeletal pain in relation to physical function in middle-aged (30-64 years) White and Black adults and investigated whether the relationship varied by sociodemographic characteristics. METHODS: This cross-sectional examination incorporated data from the Healthy Aging in Neighborhoods of Diversity across the Life-Span Study. Participants (n = 875) completed measures of musculoskeletal pain and objective measures of physical performance (ie, lower and upper body strength, balance, and gait abnormalities). Physical performance measures were standardized to derive a global measure of physical function as the dependent variable. RESULTS: Approximately, 59% of participants identified at least 1 pain sites (n = 518). Multivariable regression analyses identified significant relationships between greater musculoskeletal pain and poorer physical function (β = -0.07, p = .031), in mid midlife (β = -0.04, p = .041; age 40-54) and late midlife (β = -0.05, p = .027; age 55-64). CONCLUSIONS: This study observed that musculoskeletal pain was associated with poorer physical function within a diverse group of middle-aged adults. Future research should longitudinally explore whether chronic musculoskeletal pain identified at younger ages is associated with greater risk for functional limitation and dependence in later life.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".