Bibliographic record
Abstract
The theory of social gradient in health posits that individuals with lower socioeconomic status (SES) have poorer health outcomes, compared with those in higher socioeconomic brackets. Applied to noncommunicable diseases (NCDs), this theory has largely been corroborated by studies from the West. However, evidence from sub-Saharan Africa are mixed, with those from Ghana conspicuously missing in the literature. Using data from the Study on Global Ageing and Adult Health, and applying random-effects C log-log models, this study examined the relationship between SES and the risks of living with NCDs in Ghana. Results confirmed a negative social gradient, as Ghanaians with higher SES were more likely to live with NCDs compared with those with low SES. The addition of lifestyle factors attenuated the risks of living with NCDs among Ghanaian men and women with higher SES. This study underscores the need for policies targeted at specific socioeconomic and demographic groups, such as the emerging middle and upper class Ghanaians. It is similarly important for interventions to move beyond biomedical solutions that put more emphasis on epidemiological risk factors to strategies that embrace psychosocial factors as important correlates of cardiovascular health.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".