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Symptom profiles of subsyndromal depression in disease clusters of diabetes, excess weight, and progressive cerebrovascular conditions: a promising new type of finding from a reliable innovation to estimate exhaustively specified multiple indicators–multiple causes (MIMIC) models

Addressing subsyndromal depression in cerebrovascular conditions, diabetes, and obesity reduces morbidity and risk of major depression. However, depression may be masked because self-reported symptoms may not reveal dysphoric (sad) mood. In this study, the first wave (2,812 elders) from the New Have...

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Autor principal: Francoeur, Richard B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5158170/
https://www.ncbi.nlm.nih.gov/pubmed/28003768
http://dx.doi.org/10.2147/DMSO.S118432
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author Francoeur, Richard B
author_facet Francoeur, Richard B
author_sort Francoeur, Richard B
collection PubMed
description Addressing subsyndromal depression in cerebrovascular conditions, diabetes, and obesity reduces morbidity and risk of major depression. However, depression may be masked because self-reported symptoms may not reveal dysphoric (sad) mood. In this study, the first wave (2,812 elders) from the New Haven Epidemiological Study of the Elderly (EPESE) was used. These population-weighted data combined a stratified, systematic, clustered random sample from independent residences and a census of senior housing. Physical conditions included progressive cerebrovascular disease (CVD; hypertension, silent CVD, stroke, and vascular cognitive impairment [VCI]) and co-occurring excess weight and/or diabetes. These conditions and interactions (clusters) simultaneously predicted 20 depression items and a latent trait of depression in participants with subsyndromal (including subthreshold) depression (11≤ Center for Epidemiologic Studies Depression Scale [CES-D] score ≤27). The option for maximum likelihood estimation with standard errors that are robust to non-normality and non-independence in complex random samples (MLR) in Mplus and an innovation created by the author were used for estimating unbiased effects from latent trait models with exhaustive specification. Symptom profiles reveal masked depression in 1) older males, related to the metabolic syndrome (hypertension–overweight–diabetes; silent CVD–overweight; and silent CVD–diabetes) and 2) older females or the full sample, related to several diabetes and/or overweight clusters that involve stroke or VCI. Several other disease clusters are equivocal regarding masked depression; a couple do emphasize dysphoric mood. Replicating findings could identify subgroups for cost-effective screening of subsyndromal depression.
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spelling pubmed-51581702016-12-21 Symptom profiles of subsyndromal depression in disease clusters of diabetes, excess weight, and progressive cerebrovascular conditions: a promising new type of finding from a reliable innovation to estimate exhaustively specified multiple indicators–multiple causes (MIMIC) models Francoeur, Richard B Diabetes Metab Syndr Obes Original Research Addressing subsyndromal depression in cerebrovascular conditions, diabetes, and obesity reduces morbidity and risk of major depression. However, depression may be masked because self-reported symptoms may not reveal dysphoric (sad) mood. In this study, the first wave (2,812 elders) from the New Haven Epidemiological Study of the Elderly (EPESE) was used. These population-weighted data combined a stratified, systematic, clustered random sample from independent residences and a census of senior housing. Physical conditions included progressive cerebrovascular disease (CVD; hypertension, silent CVD, stroke, and vascular cognitive impairment [VCI]) and co-occurring excess weight and/or diabetes. These conditions and interactions (clusters) simultaneously predicted 20 depression items and a latent trait of depression in participants with subsyndromal (including subthreshold) depression (11≤ Center for Epidemiologic Studies Depression Scale [CES-D] score ≤27). The option for maximum likelihood estimation with standard errors that are robust to non-normality and non-independence in complex random samples (MLR) in Mplus and an innovation created by the author were used for estimating unbiased effects from latent trait models with exhaustive specification. Symptom profiles reveal masked depression in 1) older males, related to the metabolic syndrome (hypertension–overweight–diabetes; silent CVD–overweight; and silent CVD–diabetes) and 2) older females or the full sample, related to several diabetes and/or overweight clusters that involve stroke or VCI. Several other disease clusters are equivocal regarding masked depression; a couple do emphasize dysphoric mood. Replicating findings could identify subgroups for cost-effective screening of subsyndromal depression. Dove Medical Press 2016-12-08 /pmc/articles/PMC5158170/ /pubmed/28003768 http://dx.doi.org/10.2147/DMSO.S118432 Text en © 2016 Francoeur. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Francoeur, Richard B
Symptom profiles of subsyndromal depression in disease clusters of diabetes, excess weight, and progressive cerebrovascular conditions: a promising new type of finding from a reliable innovation to estimate exhaustively specified multiple indicators–multiple causes (MIMIC) models
title Symptom profiles of subsyndromal depression in disease clusters of diabetes, excess weight, and progressive cerebrovascular conditions: a promising new type of finding from a reliable innovation to estimate exhaustively specified multiple indicators–multiple causes (MIMIC) models
title_full Symptom profiles of subsyndromal depression in disease clusters of diabetes, excess weight, and progressive cerebrovascular conditions: a promising new type of finding from a reliable innovation to estimate exhaustively specified multiple indicators–multiple causes (MIMIC) models
title_fullStr Symptom profiles of subsyndromal depression in disease clusters of diabetes, excess weight, and progressive cerebrovascular conditions: a promising new type of finding from a reliable innovation to estimate exhaustively specified multiple indicators–multiple causes (MIMIC) models
title_full_unstemmed Symptom profiles of subsyndromal depression in disease clusters of diabetes, excess weight, and progressive cerebrovascular conditions: a promising new type of finding from a reliable innovation to estimate exhaustively specified multiple indicators–multiple causes (MIMIC) models
title_short Symptom profiles of subsyndromal depression in disease clusters of diabetes, excess weight, and progressive cerebrovascular conditions: a promising new type of finding from a reliable innovation to estimate exhaustively specified multiple indicators–multiple causes (MIMIC) models
title_sort symptom profiles of subsyndromal depression in disease clusters of diabetes, excess weight, and progressive cerebrovascular conditions: a promising new type of finding from a reliable innovation to estimate exhaustively specified multiple indicators–multiple causes (mimic) models
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5158170/
https://www.ncbi.nlm.nih.gov/pubmed/28003768
http://dx.doi.org/10.2147/DMSO.S118432
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