Understanding the bigger picture: syndemic interactions of the immigrant and refugee context with the lived experience of diabetes and obesity
Bibliographic record
Abstract
BACKGROUND: Providing contextually appropriate care and interventions for people with diabetes and/or obesity in vulnerable situations within ethnocultural newcomer communities presents significant challenges. Because of the added complexities of the refugee and immigrant context, a deep understanding of their realities is needed. Syndemic theory sheds light on the synergistic nature of stressors, chronic diseases and environmental impact on immigrant and refugee populations living in vulnerable conditions. We used a syndemic perspective to examine how the migrant ethnocultural context impacts the experience of living with obesity and/or diabetes, to identify challenges in their experience with healthcare. METHODS: This qualitative participatory research collaborated with community health workers from the Multicultural Health Brokers Cooperative of Edmonton, Alberta. Study participants were people living with diabetes and/or obesity from diverse ethnocultural communities in Edmonton and the brokers who work with these communities. We conducted 3 focus groups (two groups of 8 and one of 13 participants) and 22 individual interviews (13 community members and 9 brokers). The majority of participants had type 2 diabetes and 4 had obesity. We conducted a thematic analysis to explore the interactions of people's living conditions with experiences of: 1) diabetes and obesity; and 2) healthcare and resources for well-being. RESULTS: The synergistic effects of pre- and post-immigration stressors, including lack of social network cultural distance, and poverty present an added burden to migrants' lived experience of diabetes/obesity. People need to first navigate the challenges of immigration and settling into a new environment in order to have capacity to manage their chronic diseases. Diabetes and obesity care is enhanced by the supportive role of the brokers, and healthcare providers who have an awareness of and consideration for the contextual influences on patients' health. CONCLUSIONS: The syndemic effects of the socio-cultural context of migrants creates an additional burden for managing the complexities of diabetes and obesity that can result in inadequate healthcare and worsened health outcomes. Consequently, care for people with diabetes and/or obesity from vulnerable immigrant and refugee situations should include a holistic approach where there is an awareness of and consideration for their context.
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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.027 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".