What can we learn about polytrauma typologies by comparing population-representative to trauma-exposed samples: A Nepali example.
Global mental health
Latent class analysis
Trauma
Journal
Journal of affective disorders
ISSN: 1573-2517
Titre abrégé: J Affect Disord
Pays: Netherlands
ID NLM: 7906073
Informations de publication
Date de publication:
01 10 2022
01 10 2022
Historique:
received:
30
06
2021
revised:
14
06
2022
accepted:
03
07
2022
pubmed:
11
7
2022
medline:
11
8
2022
entrez:
10
7
2022
Statut:
ppublish
Résumé
Potentially traumatic events (PTEs) are common and associated with detrimental outcomes over the life-course. Previous studies exploring the causes and consequences of PTE-exposure profiles are often from high-income settings and fail to explore the implications of sample selection (i.e., population-representative versus PTE-restricted). Among individuals in the Nepal Chitwan Valley Family Study, latent class analyses (LCA) were performed on 11 self-reported PTEs collected by the Nepali version of the World Mental Health Consortium's Composite International Diagnostic Interview 3.0 from 2016 to 2018, in a population-representative sample (N = 10,714), including a PTE-restricted subsample (N = 9183). Multinomial logistic regressions explored relationships between sociodemographic factors and class membership. Logistic regressions assessed relationships between class membership and psychiatric outcomes. On average, individuals were exposed to 2 PTEs in their lifetime. A five-class solution showed optimal fit for both samples; however, specific classes were distinct. No single sociodemographic factor was universally associated with PTE class membership in the population-representative sample; while several factors (e.g., age, age at incident PTE, education, marital status, and migration) were consistently associated with class membership in the PTE-subsample. PTE class membership differentiated psychiatric outcomes in the population-representative sample more than the PTE-subsample. Primary limitations are related to the generalizability to high-income settings, debate on LCA model fit statistic usage for final class selection, and cross-sectional nature of data collection. Although population-representative samples provide information applicable to large-scale, population-based programming and policy, PTE-subsample analyses may provide additional nuance in PTE profiles and their consequences, important for specialized prevention efforts.
Sections du résumé
BACKGROUND
Potentially traumatic events (PTEs) are common and associated with detrimental outcomes over the life-course. Previous studies exploring the causes and consequences of PTE-exposure profiles are often from high-income settings and fail to explore the implications of sample selection (i.e., population-representative versus PTE-restricted).
METHODS
Among individuals in the Nepal Chitwan Valley Family Study, latent class analyses (LCA) were performed on 11 self-reported PTEs collected by the Nepali version of the World Mental Health Consortium's Composite International Diagnostic Interview 3.0 from 2016 to 2018, in a population-representative sample (N = 10,714), including a PTE-restricted subsample (N = 9183). Multinomial logistic regressions explored relationships between sociodemographic factors and class membership. Logistic regressions assessed relationships between class membership and psychiatric outcomes.
RESULTS
On average, individuals were exposed to 2 PTEs in their lifetime. A five-class solution showed optimal fit for both samples; however, specific classes were distinct. No single sociodemographic factor was universally associated with PTE class membership in the population-representative sample; while several factors (e.g., age, age at incident PTE, education, marital status, and migration) were consistently associated with class membership in the PTE-subsample. PTE class membership differentiated psychiatric outcomes in the population-representative sample more than the PTE-subsample.
LIMITATIONS
Primary limitations are related to the generalizability to high-income settings, debate on LCA model fit statistic usage for final class selection, and cross-sectional nature of data collection.
CONCLUSIONS
Although population-representative samples provide information applicable to large-scale, population-based programming and policy, PTE-subsample analyses may provide additional nuance in PTE profiles and their consequences, important for specialized prevention efforts.
Identifiants
pubmed: 35810829
pii: S0165-0327(22)00765-0
doi: 10.1016/j.jad.2022.07.006
pmc: PMC9869468
mid: NIHMS1860295
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
201-210Subventions
Organisme : NIMH NIH HHS
ID : K08 MH127413
Pays : United States
Organisme : NIMH NIH HHS
ID : K23 MH117278
Pays : United States
Organisme : NICHD NIH HHS
ID : P2C HD041028
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH110872
Pays : United States
Informations de copyright
Copyright © 2022 Elsevier B.V. All rights reserved.
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