Noncommunicable Disease Profiles of Bangladeshi Immigrants Aged >55 Years Living in Toronto: Access to Health Workshop and Needed Supports for Management
Bibliographic record
Abstract
Objectives: The study explored the profiles of noncommunicable diseases (NCDs) of South Asian Bangladeshi immigrants aged > 55, access to health workshops about NCDs for self-care, and the types of support they needed to control and manage their NCDs. Methods: The study was cross-sectional. The participants were Bangladeshi immigrants aged > 55 living in Toronto. They attended an ethnic community organization for services from January to March 2020, and the study included participants from them (purposively). Pretested structured and semi-structured questionnaires were applied to collect the information. The study used chi-square and logistic regression for data analysis. Results: The study included 191 participants; among the participants, males and females were 44.0% (84) and 56.0% (107), respectively, more than half of them (53.4%, 102) were aged > 60 years, and the majority (69.6%, 133) lived in Canada for more than five years. The frequently mentioned NCDs by gender perspective were diabetes (male vs. female: 51.2% vs. 57.9%), high blood pressure (male vs. female: 48.8% vs. 54.2%), and high cholesterol (male vs. female: 33.3% vs. 36.4%). They also mentioned arthritis/chronic joint pain (22.0%, 44), anxiety and depression (16.2%, 31), and heart disease (15.2%, 29). Females, compared to males, were more likely to have multiple NCDs, AOR= 1.62, 95% CI: 0.86, 3.04. Also, the participants aged > 60 years were 2.53 times more likely to have multiple NCDs than those who were < 60 years (95% CI: 1.34, 4.77), and the participants who arrived in Canada in five years were more likely to have multiple NCDs, AOR=1.42, 95% CI: 0.72, 2.83) compared to the group more than five years. Furthermore, 51.8% (99) of participants had no access to health workshops/ health information about NCDs for self-management. Most needed caregiver support from family members (59.7%, 114) to manage NCDs. Also, they required accompaniment support to go to health care providers (40.3%, 77), needed a doctor's cooperation (34.0%, 65), prescription management support (28.3%, 54), and home support (26.7%, 51) for managing the diseases. Conclusion: The profile of NCDs of Bangladeshi immigrants aged > 55 years were high blood pressure, diabetes, and high cholesterol. Gender and sociodemographic variables changed the profile of NCDs in Bangladeshi immigrants. Participants needed better health information access and family care support to manage NCDs. Local ethnic community services can design a community-based health, home, and caregiver support approach to address the NCDs of Bangladeshi immigrants.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".