Addressing social determinants of noncommunicable diseases in primary care: a scoping review
Bibliographic record
Abstract
Abstract Background Noncommunicable diseases (NCDs) are the leading cause of global mortality, and their risk factors largely manifest at the community level. In collaboration with public health, primary care is well placed to assess and address the local social determinants of NCDs (SDONCDs). Post-Astana, many countries are reorienting their primary care systems to incorporate these traditional public health functions, but there is little evidence to guide reform. We aimed to collate examples of primary care organisations that already engage in this activity. Methods Following Cochrane guidance, PubMed, MEDLINE, Embase & HMIC were searched from inception to 28/7/2019, along with hand-searching of references for any study designs that examined international primary care organisation(s) that addressed local SDONCDs. Independent dual review was used for screening, data extraction, and quality assessment - for which we used ROBINS-i. Results Searches identified 666 studies of which 17 studies from Canada, South Africa, UK, and USA were included. All used descriptive study designs. Individual-level surveys and interviews were the most common SDONCD data collection methods reported. Fewer studies collated population-level data held by external agencies. Actions ranged from individual-level interventions to novel representation of primary care organisations on system-level policy and planning committees. Several enablers and barriers to collecting and mobilising social determinant data within well- and under-resourced primary care settings were identified. Conclusions Several models of integrated public health and primary care already exist that fulfil the Astana mandate of developing place-based preventive services, tailored to local needs. Public health input at this granular level is required to support primary care services as they extend their scope of practice, and to assist with monitoring and evaluation of new initiatives to mitigate unmet health and social needs. Key messages Primary care organisations are increasingly being encouraged to assess and address local social determinants of noncommunicable diseases but there is weak evidence to guide reform. The different approaches described in our review can help policymakers tasked with integrating public health functions into primary care.
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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 | 0.017 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.023 | 0.023 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".