Transition nutritionnelle et facteurs de risque de maladies cardiovasculaires chez des adultes de Cotonou, Bénin (Afrique de l'Ouest)
Bibliographic record
Abstract
There is a dearth of information on diet-related chronic diseases in West Africa.This cross-sectional study was conducted to explore the links between nutrition transition and the risk of cardiovascular diseases (CVD) in adults living in Cotonou, the largest city of Benin.A sample of 200 apparently healthy men and women aged 25-60 years was selected in 10 neighborhoods picked at random.Food intake and physical activity were assessed with three non-consecutive 24-hour recalls.Dietary patterns were examined using cluster analysis.Diet quality was assessed based on a micronutrient adequacy score and a healthfulness score.Anthropometric parameters (height, weight and waist circumference), blood pressure, fasting plasma glucose and serum lipid concentrations (triglycerides and HDL-cholesterol) were measured.WHO cut-offs were used to define CVD risk factors.Information on tobacco use and alcohol consumption was collected using a questionnaire.An overall lifestyle score (OLS) was created based on a diet quality score, an alcohol consumption score, a smoking score, and a physical activity score.A socio-economic score was computed based on education, main occupation and household amenities (a proxy measure for income).Two distinct dietary patterns emerged: a "traditional" type, and a "transitional" type.Although both patterns were still low in fat and sugar, they were also low in fruits and vegetables.The most prevalent CVD risk factors were overall obesity (18%), abdominal IV obesity (32%), hypertension (23%), and low HDL-cholesterol (13%).Diabetes and hypertriglyceridemia were uncommon.Obesity affected more women than men and increased significantly with SES, while a longer exposure to the urban environment was associated with a higher risk of hypertension.PhysicaJ activity was negatively associated with body mass index, waist circumference and blood pressure in multivariate anaJysis.Logistic regression analyses revealed that the likelihood of obesity and hypertension decreased significantly as the OLS improved, when controlling for age, sex and socioeconomic status.The resuJts of the present study cali for urgent measures to avert the rise of these dietrelated chronic diseases in Benin.Our data identify avenues for the development of public health interventions focusing on environmental risk factors that are amenable to change in this population.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".