Prevalence and determinants of non-communicable diseases risk factors among reproductive-aged women: Findings from a nationwide survey in Bangladesh
Bibliographic record
Abstract
INTRODUCTION: Knowing the risk factors like smoking status, overweight/obesity, and hypertension among women of reproductive age could allow the development of an effective strategy for reducing the burden of non-noncommunicable diseases. We sought to determine the prevalence and determinants of smoking status, overweight/obesity, hypertension, and cluster of these non-noncommunicable diseases risk factors among Bangladeshi women of reproductive age. METHODS: This study utilized the Bangladesh Demographic and Health Survey (BDHS) data from 2017-2018 and analyzed 5,624 women of reproductive age (age 18-49 years). This nationally representative cross-sectional survey utilized a stratified, two-stage sample of households. Poisson regression models with robust error variance were fitted to find the adjusted prevalence ratio (APR) for smoking, overweight/obesity, hypertension, and for the clustering of non-noncommunicable diseases risk factors across demographic variables. RESULTS: The average age of 5,624 participants was 31 years (SD = 9.1). The prevalence of smoking, overweight/obesity, and hypertension was 9.6%, 31.6%, and 20.3%, respectively. More than one-third of the participants (34.6%) had one non-noncommunicable diseases risk factor, and 12.5% of participants had two non-noncommunicable diseases risk factors. Age, education, wealth index, and geographic location were significantly associated with smoking status, overweight/obesity, and hypertension. Women between 40-49 years had more non-noncommunicable diseases risk factors than 18-29 years aged women (APR: 2.44; 95% CI: 2.22-2.68). Women with no education (APR: 1.15; 95% CI: 1.00-1.33), married (APR: 2.32; 95% CI: 1.78-3.04), and widowed/divorced (APR: 2.14; 95% CI: 1.59-2.89) were more likely to experience multiple non-noncommunicable diseases risk factors. Individuals in the Barishal division, a coastal region (APR: 1.44; 95% CI: 1.28-1.63) were living with a higher number of risk factors for non-noncommunicable diseases than those in the Dhaka division, the capital of the country. Women who belonged to the richest wealth quintile (APR: 1.82; 95% CI: 1.60-2.07) were more likely to have the risk factors of non-noncommunicable diseases. CONCLUSIONS: The study showed that non-noncommunicable diseases risk factors are more prevalent among women from older age group, currently married and widowed/divorced group, and the wealthiest socio-economic group. Women with higher levels of education were more likely to engage in healthy behaviors and found to have less non-noncommunicable diseases risk factors. Overall, the prevalence and determinants of non-noncommunicable diseases risk factors among reproductive women in Bangladesh highlight the need for targeted public health interventions to increase opportunities for physical activity and reduce the use of tobacco, especially the need for immediate interventions in the coastal region.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".