Surveillance of Cardiovascular Risk Factors in the Fifth Military Sector Health Center, Ngaoundéré, Cameroon: Observational Study
Bibliographic record
Abstract
BACKGROUND: Noncommunicable diseases (NCDs) are the leading causes of death worldwide. They were responsible for 40 million of the 57 million deaths recorded worldwide in 2016. In Cameroon, epidemiological studies have been devoted to NCDs and their risk factors. However, none provides specific information on their extent or the distribution of their risk factors within the Cameroonian defense forces. OBJECTIVE: The objective of our study was to assess the cardiovascular risk of a Cameroonian military population compared with that of its neighboring civilian population. METHODS: We conducted a cross-sectional study that involved subjects aged 18 to 58 years, recruited from October 2017 to November 2018 at the Fifth Military Sector Health Center in Ngaoundéré, Cameroon. Data collection and assessment were done according to the World Health Organization (WHO)'s STEPS manual for surveillance of risk factors for chronic NCDs and the Alcohol Use Disorders Identification Test. Five cardiovascular risk factors were assessed: smoking, harmful alcohol consumption, obesity/overweight, hypertension, and diabetes. The risk was considered high in subjects with 3 or more of the factors. Univariate analysis and multivariate logistic regression were carried out according to their indications. RESULTS: Our study sample of 566 participants included 295 soldiers and 271 civilians of the same age group (median age 32 years versus 33 years, respectively; P=.57). The military sample consisted of 31 officers and 264 noncommissioned officers (NCOs). Soldiers were more exposed to behavioral risk factors than civilians, with a prevalence of smoking of 13.9% versus 4.4% (P<.001) and excessive alcohol consumption of 61.7% versus 14.8% (P<.001). They also presented with a higher cardiovascular risk than civilians (odds ratio 2.7, 95% CI 1.50-4.81; P<.001), and among the military participants, the cardiovascular risk was higher for officers than for NCOs (51.6% versus 14.0%, respectively; P<.001). CONCLUSIONS: Cameroonian soldiers are particularly exposed to cardiovascular behavioral risk factors and consequently are at higher risk of NCDs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04315441; https://clinicaltrials.gov/ct2/show/NCT04315441.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".