Evidence map›Paper›PMID 28916888›Full record

ArticleJournal of immigrant and minority health2018

HIV Testing Among Foreign-Born Men and Women in the United States: Results from a Nationally Representative Cross-Sectional Survey.

Eduardo Valverde, Elizabeth DiNenno, Emeka Oraka, Gregory Bautista, Pollyanna Chavez

Abstract read
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Article in Journal of immigrant and minority health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
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  5. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Eduardo ValverdeDivision of Global HIV & TB, Centers for Disease Control and Prevention, 1600 Clifton Road, NE, Mail Stop E-04, Atlanta, GA, 30329, USA. evalverde@cdc.gov.ORCID http://orcid.org/0000-0002-6132-9067
Elizabeth DiNennoDivision of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia.
Emeka OrakaICF International, Centers for Disease Control and Prevention, Atlanta, Georgia.
Gregory BautistaDivision of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia.
Pollyanna ChavezDivision of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

HIV disproportionately affects the foreign-born population in the United States. This analysis describes the prevalence of ever-testing for HIV among foreign-born individuals residing in the United States. Data from a national health survey of the civilian, non-institutionalized population was used to describe prevalence of ever-testing for HIV among foreign-born individuals by birth place. Multivariate logistic-regression procedures were used to determine factors associated with ever-testing for HIV among foreign-born men and women. The prevalence of ever-testing for HIV among foreign-born individuals varied by region of birth ranging from 31 to 67%. Factors related to ever-testing for HIV varied by gender. Efforts need to continue in order to improve HIV testing rates among Asian foreign-born individuals, lower educated foreign-born and foreign-born gay/bisexual men. Health care providers can play an important role by counseling new arrivals regarding the importance of testing for HIV and practicing HIV risk reduction activities.

Indexed as

AdolescentAdultAgedCross-Sectional StudiesEmigrants and ImmigrantsFemaleHealth SurveysHIV InfectionsHumansLogistic ModelsMaleMiddle AgedPrevalenceSex FactorsSocioeconomic FactorsUnited StatesForeign-bornHIVTestingUnited States

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.