Prevalence and associated factors of metabolic syndrome among Bangladeshi adults: Evidence from a nation-wide survey
Bibliographic record
Abstract
Metabolic syndrome is an important risk factor for cardiovascular disease and premature mortality. This study aimed to determine the prevalence and associated factors of metabolic syndrome among Bangladeshi adults (aged 18–69 years) using a nationally representative survey: Stepwise Approach to Surveillance (STEPS). Metabolic syndrome was defined according to Adult Treatment Panel III (ATP III) and International Diabetes Federation (IDF) criteria. Design based multivariable log-binomial regression was conducted to explore the associated factors. The adjusted prevalence ratio (APR) was reported along with a 95% confidence interval (CI). In total, 6851 samples were included. Overall, 15.5% and 16.6% of the participants had metabolic syndrome according to ATP III and IDF criteria, respectively. According to ATP III criteria, the prevalence of metabolic syndrome was higher among those aged 30–49 years (APR: 2.4; 95% CI: 1.8–3.2) and 50–69 years (APR: 3.5; 95% CI: 2.5–4.5) compared to those aged 18–29 years, being educated up to college and higher (APR: 1.6; 95% CI: 1.2–2.0) compared to those who did not receive any formal education, residence in the urban area (APR: 1.2; 95% CI: 1.0–1.4) compared to rural residents, having an abnormal waist-hip ratio (APR: 2.0; 95% CI: 1.6–2.6) compared to having normal waist-hip ratio, being overweight (APR: 1.8; 95% CI: 1.4–2.3), and obese (APR: 3.5; 95% CI: 2.8–4.4) compared to those who had normal BMI/underweight. Compared to the residents in the Dhaka Rural, residents in Mymensingh, and Rangpur division had lower odds of having metabolic syndrome. Except for the place of residence, the associated factors were similar according to IDF criteria. As approximately every one in six adults are suffering from the metabolic syndrome in Bangladesh, the public health prevention and promotion programs should target the high-risk groups to curtail the high burden.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".