Chronic Illness and Quality of Life 5 Years After Displacement Among Rohingya Refugees in Bangladesh
Bibliographic record
Abstract
Importance: Rohingya refugees, forcibly displaced from Myanmar, face challenges adapting to Bangladesh. Examining their quality of life (QOL) is vital to identifying nuanced factors associated with their well-being, informing targeted interventions for an improved QOL. Objectives: To identify the QOL among Rohingya refugees 5 years after migration to Bangladesh, with a particular emphasis on understanding the complex interplay between sociodemographic factors and chronic illnesses. Design, Setting, and Participants: A cross-sectional study involving resettled Rohingya adults was conducted between May 18 and July 7, 2021, approximately 5 years after their resettlement in Bangladesh. Of the participants, 500 individuals were healthy, whereas 558 individuals were undergoing treatment for at least 1 chronic disease. Data were analyzed from January to February 2024. Main Outcomes and Measures: The study assessed QOL using the short version of the World Health Organization's QOL Questionnaire, covering 4 domains: physical, psychological, social, and environmental. Scores were transformed to a maximum of 100. Tobit linear regression, adjusted for potential confounders, was employed for analysis. Results: The study included a total of 1058 respondents, who were predominantly female (630 participants [59.5%]) and had a mean (SD) age of 42.5 (16.1) years. Despite being healthy, individuals without chronic illnesses had median QOL scores ranging from 44 to 56 out of 100, indicating a relatively poor QOL. A total of 260 participants (46.6%) with chronic diseases reported very poor or poor QOL, in contrast to 58 healthy individuals (11.6%) in the fifth year after displacement. Specifically, patients with cancer and those who had multimorbidity exhibited the lowest QOL scores across all domains, with significant reductions in the physical health (10.57 decrease; 95% CI, -12.97 to -8.17) and psychological domain scores (7.20 decrease; 95% CI, -9.71 to -5.93) according to Tobit regression analysis. Conclusions and Relevance: This study found that chronic illnesses were associated with all domains of QOL among Rohingya refugees, particularly those with musculoskeletal disorders, cancer, and multimorbid conditions. This heightened vulnerability may contribute to poor QOL in this population. By uncovering these disparities, the study lays the groundwork for targeted interventions and policies aligned with the United Nations' goal of leaving no one behind in sustainable development efforts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".