Association of Depression, Poor Mental Health Status and Asthma Control Patterns in US Adults Using a Data-Reductive Latent Class Method

Association of Depression, Poor Mental Health Status and Asthma Control Patterns in US Adults Using a Data-Reductive Latent Class Method

Objectives To explore the association between depression, poor mental health status, and asthma control patterns among US adults using a latent class analysis (LCA) approach. Methods We used data from 10,337 adults aged 18 years and above from the 2016 Behavioral Risk Factor Surveillance System (BRF...

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Veröffentlicht in:Curēus (Palo Alto, CA) CA), 2023-01, Vol.15 (1), p.e33966
Hauptverfasser: Ogbu, Chukwuemeka E, Ravilla, Jayashree, Okoli, Menkeoma Laura, Ahaiwe, Onyekachi, Ogbu, Stella C, Kim, Eun Sook, Kirby, Russell S
Format: Artikel
Sprache:eng
Schlagworte:
Adults
Age
Asthma
Chronic illnesses
Datasets
Disease
Epidemiology/Public Health
Hypotheses
Latent class analysis
Medical personnel
Mental depression
Mental disorders
Mental health
Population
Preventive Medicine
Public Health
Questionnaires
Review boards
Variables
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Zusammenfassung:Objectives To explore the association between depression, poor mental health status, and asthma control patterns among US adults using a latent class analysis (LCA) approach. Methods We used data from 10,337 adults aged 18 years and above from the 2016 Behavioral Risk Factor Surveillance System (BRFSS) Asthma Call-back Survey. Data-reductive LCA was used to derive asthma control patterns in the population using class variables indicative of asthma control. Besides univariate analysis, adjusted and unadjusted logistic regression models were used to examine the association of depression and poor mental health on the derived asthma control patterns.  Results About 27.8% of adults aged
ISSN:2168-8184
2168-8184
DOI:10.7759/cureus.33966