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Record W2767662977 · doi:10.2196/publichealth.7741

Factors Associated With Access to HIV Testing and Primary Care Among Migrants Living in Europe: Cross-Sectional Survey

2017· article· en· W2767662977 on OpenAlexvenueno aff
Ibidun Fakoya, Débora Álvarez-del Arco, Andrew Copas, Bryan Teixeira, Koen Block, Anne-Françoise Gennotte, Alain Volny‐Anne, Janneke P. Bil, Giota Touloumi, Julia del Amo, Fiona Burns

Bibliographic record

VenueJMIR Public Health and Surveillance · 2017
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersEuropean CommissionNational Institute for Health and Care ResearchGilead SciencesSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsMedicineDemographyCross-sectional studyGerontologyOddsOdds ratioEnvironmental healthLogistic regressionSociology

Abstract

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BACKGROUND: There is a heavy and disproportionate burden of human immunodeficiency virus (HIV) infection among migrant communities living in Europe. Despite this, the published evidence related to HIV testing, prevention, and treatment needs for migrants is sparse. OBJECTIVE: The aim of this study was to identify the factors associated with access to primary care and HIV testing among migrant groups living in Europe. METHODS: A Web-based survey (available in 14 languages) was open to all people aged 18 years and older, living outside their country of birth in the World Health Organization (WHO) European area. Community organizations in 9 countries promoted the survey to migrant groups, focusing on those at a higher risk of HIV (sub-Saharan Africans, Latin Americans, gay or bisexual men, and people who inject drugs). Multivariable analysis examined factors associated with access to primary care and previous history of an HIV test. RESULTS: In total, 559 women, 395 heterosexual men, and 674 gay or bisexual men were included in the analysis, and 68.1% (359/527) of women, 59.5% (220/371) of heterosexual men, and 89.6% (596/664) of gay or bisexual men had tested for HIV. Low perceived risk was the reason given for not testing by 62.3% (43/69) of gay or bisexual men and 83.3% (140/168) of women and heterosexual men who reported never having tested for HIV. Access to primary care was >60% in all groups. Access to primary care was strongly positively associated with living in Northern Europe compared with Southern Europe (women: adjusted odds ratio, aOR 34.56 [95% CI 11.58-101]; heterosexual men: aOR 6.93 [95% CI 2.49-19.35], and gay or bisexual men: aOR 2.53 [95% CI 1.23-5.19]), whereas those with temporary residency permits were less likely to have access to primary care (women: aOR 0.41 [95% CI 0.21-0.80] and heterosexual men: aOR 0.24 [95% CI 0.10-0.54] only). Women who had experience of forced sex (aOR 3.53 [95% CI 1.39-9.00]) or postmigration antenatal care (aOR 3.07 [95% CI 1.55-6.07]) were more likely to have tested for HIV as were heterosexual men who had access to primary care (aOR 3.13 [95% CI 1.58-6.13]) or reported "Good" health status (aOR 2.94 [95% CI 1.41-5.88]). CONCLUSIONS: Access to primary care is limited by structural determinants such as immigration and health care policy, which varies across Europe. For those migrants who can access primary care and other health services, missed opportunities for HIV testing remain a barrier to earlier testing and diagnosis for migrants in Europe. Clinicians should be aware of these potential structural barriers to HIV testing as well as low perception of HIV risk in migrant groups.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.144
GPT teacher head0.408
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2017
Admission routes1
Has abstractyes

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