Assessment of Bias in Estimates of Sexual Network Degree using Prospective Cohort Data.


Journal

Epidemiology (Cambridge, Mass.)
ISSN: 1531-5487
Titre abrégé: Epidemiology
Pays: United States
ID NLM: 9009644

Informations de publication

Date de publication:
03 2020
Historique:
pubmed: 7 12 2019
medline: 19 3 2021
entrez: 7 12 2019
Statut: ppublish

Résumé

Sexual network degree, a count of ongoing partnerships, plays a critical role in the transmission dynamics of human immunodeficiency virus and other sexually transmitted infections. Researchers often quantify degree using self-reported cross-sectional data on the day of survey, which may result in bias because of uncertainty about future sexual activity. We evaluated the bias of a cross-sectional degree measure with a prospective cohort study of men who have sex with men (MSM). At baseline, we asked men about whether recent sexual partnerships were ongoing. We confirmed the true, ongoing status of those partnerships at baseline at follow-up. With logistic regression, we estimated the partnership-level predictors of baseline measure accuracy. With Poisson regression, we estimated the longitudinally confirmed degree as a function of baseline predicted degree. Across partnership types, the baseline ongoing status measure was 70% accurate, with higher negative predictive value (91%) than positive predictive value (39%). Partnership exclusivity and racial pairing were associated with higher accuracy. Baseline degree generally overestimated confirmed degree. Bias, or number of ongoing partners different than predicted at baseline, was -0.28 overall, ranging from -1.91 to -0.41 for MSM with any ongoing partnerships at baseline. Comparing MSM of the same baseline degree, the level of bias was stronger for black compared with white MSM, and for younger compared with older MSM. Research studies may overestimate degree when it is quantified cross-sectionally. Adjustment and structured sensitivity analyses may account for bias in studies of human immunodeficiency virus or sexually transmitted infection prevention interventions.

Sections du résumé

BACKGROUND
Sexual network degree, a count of ongoing partnerships, plays a critical role in the transmission dynamics of human immunodeficiency virus and other sexually transmitted infections. Researchers often quantify degree using self-reported cross-sectional data on the day of survey, which may result in bias because of uncertainty about future sexual activity.
METHODS
We evaluated the bias of a cross-sectional degree measure with a prospective cohort study of men who have sex with men (MSM). At baseline, we asked men about whether recent sexual partnerships were ongoing. We confirmed the true, ongoing status of those partnerships at baseline at follow-up. With logistic regression, we estimated the partnership-level predictors of baseline measure accuracy. With Poisson regression, we estimated the longitudinally confirmed degree as a function of baseline predicted degree.
RESULTS
Across partnership types, the baseline ongoing status measure was 70% accurate, with higher negative predictive value (91%) than positive predictive value (39%). Partnership exclusivity and racial pairing were associated with higher accuracy. Baseline degree generally overestimated confirmed degree. Bias, or number of ongoing partners different than predicted at baseline, was -0.28 overall, ranging from -1.91 to -0.41 for MSM with any ongoing partnerships at baseline. Comparing MSM of the same baseline degree, the level of bias was stronger for black compared with white MSM, and for younger compared with older MSM.
CONCLUSIONS
Research studies may overestimate degree when it is quantified cross-sectionally. Adjustment and structured sensitivity analyses may account for bias in studies of human immunodeficiency virus or sexually transmitted infection prevention interventions.

Identifiants

pubmed: 31809340
doi: 10.1097/EDE.0000000000001151
pmc: PMC7002246
mid: NIHMS1063200
pii: 00001648-202003000-00011
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

229-237

Subventions

Organisme : NIAID NIH HHS
ID : R01 AI138783
Pays : United States
Organisme : NIAID NIH HHS
ID : P30 AI050409
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH085600
Pays : United States
Organisme : NIMH NIH HHS
ID : R21 MH112449
Pays : United States
Organisme : NICHD NIH HHS
ID : R21 HD075662
Pays : United States

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Auteurs

Stephen Uong (S)

From the Department of Epidemiology, Emory University, Atlanta, GA, USA.

Eli S Rosenberg (ES)

Department of Epidemiology and Biostatistics, University at Albany School of Public Health, SUNY, Albany, NY, USA.

Steven M Goodreau (SM)

Department of Anthropology, University of Washington, Seattle, WA, USA.

Nicole Luisi (N)

From the Department of Epidemiology, Emory University, Atlanta, GA, USA.

Patrick Sullivan (P)

From the Department of Epidemiology, Emory University, Atlanta, GA, USA.

Samuel M Jenness (SM)

From the Department of Epidemiology, Emory University, Atlanta, GA, USA.

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