Chronic Musculoskeletal Pain, Self-Reported Health and Quality of Life among Older Populations in South Africa and Uganda
Bibliographic record
Abstract
Chronic musculoskeletal pain (CMP) is a serious health concern especially among the elderly population and has significant bearing on health and quality of life. Not much is known about the relationship between chronic pain with self-reported health and quality of life among older populations in low-resource settings. Based on sub-national data from South Africa and Uganda, the present study aimed to explore whether the older population living with CMP report health and quality of life differently compared to those with no CMP complaints. This study was based on cross-sectional data on 1495 South African and Ugandan men and women collected from the SAGE Well-Being of Older People Study. Outcome variables were self-reported physical and mental health and quality of life (QoL). Mental health was assessed by self-reported depressive symptoms during the last 12 months. CMP was assessed by self-reported generalised pain as well as back pain. Multivariable logistic regression models were used to measure the association between health and QoL with CMP by adjusting for potential demographic and environmental confounders. The prevalence of poor self-rated health (61.2%, 95% CI = 51.7, 70.0), depression (37.2%, 95% CI = 34.8, 39.6) and QoL (80.5%, 95% CI = 70.8, 87.5) was considerably high in the study population. Mild/moderate and Severe/extreme generalised pain were reported respectively by 34.5% (95% CI = 28.9, 40.5) and 15.7% (95% CI = 12.2, 19.9) of the respondents, while back pain was reported by 53.3% (95% CI = 45.8, 60.4). The prevalence of both types was significantly higher among women than in men (p < 0.001). In the multivariate analysis, both generalised pain and back pain significantly predicted poor health, depression and QoL, however, it varied between the two different populations. Back pain was associated with higher odds of poor self-rated health [OR = 1.813, 95% CI = 1.308, 2.512], depression [1.640, 95% CI = 1.425, 3.964] and poor QoL [1.505, 95% CI = 1.028, 2.202] in South Africa, but not in Uganda. Compared to having no generalised pain, having Mild/Moderate [OR = 2.309, 95% CI = 1.219, 7.438] and Severe/Extreme [OR = 2.271, 95% CI = 1.447, 4.143] generalised pain was associated with significantly higher odds of poor self-rated health in South Africa. An overwhelmingly high proportion of the sample population reported poor health, quality of life and depression. Among older individuals, health interventions that address CMP may help promote subjective health and quality and life and improve psychological health.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".