High prevalence and clustering of modifiable CVD risk factors among rural adolescents in southwest Nigeria: implication for grass root prevention
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease (CVD) is an immense global problem with serious economic and social consequences. Modifiable risk factors for CVD have been identified internationally in adolescents where early intervention programs have the potential to reduce CVD risk on individual and population levels. In developing countries such as Nigeria, little is known about the prevalence of modifiable CVD risk factors among adolescents especially in the rural areas. METHODS: This paper reports on a cross-sectional survey of modifiable CVD risk factors among rural adolescents in South-West Nigeria. All 15-18 years old adolescents in all the schools at Ibarapa central local government were approached and all those who assented and consented to participate in the study were involved. A total of 1500 adolescents participated in the study. Measurements of CVD risks factors taken were; smoking, physical activity, alcohol, dietary pattern using a questionnaire developed by authors. Other CVD risk factors such as waist hip ratio and BMI were taken using standardized instruments. Data were analyzed using STATA version 12. RESULTS: Data from 1079 adolescents (56.5% males and 53.5% females) were analyzed. Mean age of males was 16.4 ± 1.14 years and mean age for females was 16.29 ± 1.13 years. Adolescents showed clustering of CVD risk factors with about 72% having between two and four risk factors. A total of 102 clustering patterns were reported. The most common clustering pattern (19.6%) included high animal lipid and salt diet. CONCLUSION: There is high level and clustering of CVD risk factors among rural adolescents in Southwest Nigeria. The most common clustering pattern was biased towards dietary factors. The high prevalence of CVD risk factors among rural adolescents in Southwest Nigeria suggests that urgent primary prevention programs are required to prevent the next generation of Nigerians from suffering of CVD.
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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 | 0.000 | 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 | 0.001 | 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".