Evidence map›Paper›PMID 35992892›Full record

ArticleCommunications medicine2022

The demographic and socioeconomic correlates of behavior and HIV infection status across sub-Saharan Africa.

Chirag J Patel, Kajal T Claypool, Eric Chow, Ming-Kei Chung, Don Mai, Jessie Chen, Eran Bendavid

Abstract read
In one paragraph

Article in Communications medicine, 2022. 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.

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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

7 authors.

Chirag J PatelDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA USA.ORCID 0000-0002-8756-8525
Kajal T ClaypoolDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA USA.
Eric ChowRosalind Franklin University School of Medicine, Chicago, IL USA.
Ming-Kei ChungDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA USA.
Don MaiAlphabet Inc., Mountain View, CA USA.
Jessie ChenLoyola University, Chicago, IL USA.
Eran BendavidCenter for Population Health Sciences, Stanford University, Stanford, CA USA.ORCID 0000-0002-8364-4711

Funding

Making Better Decisions: Policy Modeling for AIDS and Drug AbuseR37DA015612 · NIDA · STANFORD UNIVERSITY · PI DOUGLAS K OWENS · 2019 to 2026
$6.3M
Data science tools to identify robust exposure-phenotype associations for precision medicineR01ES032470 · NIEHS · HARVARD MEDICAL SCHOOL · PI MANRAI, ARJUN KUMAR, PATEL, CHIRAG J. · 2021 to 2025
$3.5M
Big Data Analysis of HIV Risk and Epidemiology in Sub-Saharan AfricaR01AI127250 · NIAID · STANFORD UNIVERSITY · PI BENDAVID, ERAN, PATEL, CHIRAG J. · 2017 to 2020
$2.7M
Summer Research Experience for Medical Students in Inflammation and Infectious DiseasesT35AI125220 · NIAID · LOYOLA UNIVERSITY CHICAGO · PI Edward M. Campbell, Simon Kaja · 2017 to 2026
$510k
NIAID NIH HHS R01 AI127250NIAID NIH HHS T35 AI125220NIDA NIH HHS R37 DA015612NIEHS NIH HHS R01 ES032470
6 · The paper itself

Abstract

Background: Predisposition to become HIV positive (HIV + ) is influenced by a wide range of correlated economic, environmental, demographic, social, and behavioral factors. While evidence among a candidate handful have strong evidence, there is lack of a consensus among the vast array of variables measured in large surveys. Methods: We performed a comprehensive data-driven search for correlates of HIV positivity in >600,000 participants of the Demographic and Health Survey across 29 sub-Saharan African countries from 2003 to 2017. We associated a total of 7251 and of 6,288 unique variables with HIV positivity in females and males respectively in each of the 50 surveys. We performed a meta-analysis within countries to attain 29 country-specific associations. Results: Here we identify 344 (5.4% out possible) and 373 (5.1%) associations with HIV + in males and females, respectively, with robust statistical support. The associations are consistent in directionality across countries and sexes. The association sizes among individual correlates and their predictive capability were low to modest, but comparable to established factors. Among the identified associations, variables identifying being head of household among females was identified in 17 countries with a mean odds ratio (OR) of 2.5 (OR range: 1.1-3.5, R Conclusions: Our continent-wide search for variables has identified under-recognized variables associated with being HIV + that are consistent across the continent and sex. Many of the association sizes are as high as established risk factors for HIV positivity, including male circumcision.

Indexed as

EpidemiologyHIV infections

Identifiers

PMID35992892
PMCPMC9388647

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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.