Predictors of perceived health in adults with an intellectual disability.


Journal

Research in developmental disabilities
ISSN: 1873-3379
Titre abrégé: Res Dev Disabil
Pays: United States
ID NLM: 8709782

Informations de publication

Date de publication:
Jun 2020
Historique:
received: 11 10 2019
revised: 28 02 2020
accepted: 24 03 2020
pubmed: 25 4 2020
medline: 9 3 2021
entrez: 25 4 2020
Statut: ppublish

Résumé

The effects of Intellectual disability (ID) levels, body mass index (BMI) categories, and other factors on perceived health status of adults with ID are not well-known. We aimed to examine: (a) the relationship between perceived health and level of intellectual function; (b) the influence of different BMI categories on a perceived health; and (c) the effect of the modifiable behavioral factors on perceived health. We examined the aims using data from the 2013-2014 Adult Consumer Survey of the National Core Indicator. We extracted demographic (e.g. age, BMI) and modifiable behavior-related variables (e.g. physical activity participation, having a job) and used logistic regression models to analyze the relationships. Logistic regressions showed that more severe ID level is associated with worse perceived health, but when other variables related to personal and behavioral characteristics were accounted for, this relationship was no longer significant. Obese adults with ID had worse perceived health than those with normal weight; this effect remained significant even after considering other variables. Those in the overweight category did not differ in perceived health status from those of normal weight. The effects of all modifiable behaviors on perceived health were significant. Health promotion programs for adults with ID may benefit by consideration of modifiable behaviors.

Sections du résumé

BACKGROUND BACKGROUND
The effects of Intellectual disability (ID) levels, body mass index (BMI) categories, and other factors on perceived health status of adults with ID are not well-known.
AIMS OBJECTIVE
We aimed to examine: (a) the relationship between perceived health and level of intellectual function; (b) the influence of different BMI categories on a perceived health; and (c) the effect of the modifiable behavioral factors on perceived health.
METHODS AND PROCEDURES METHODS
We examined the aims using data from the 2013-2014 Adult Consumer Survey of the National Core Indicator. We extracted demographic (e.g. age, BMI) and modifiable behavior-related variables (e.g. physical activity participation, having a job) and used logistic regression models to analyze the relationships.
OUTCOMES AND RESULTS RESULTS
Logistic regressions showed that more severe ID level is associated with worse perceived health, but when other variables related to personal and behavioral characteristics were accounted for, this relationship was no longer significant. Obese adults with ID had worse perceived health than those with normal weight; this effect remained significant even after considering other variables. Those in the overweight category did not differ in perceived health status from those of normal weight. The effects of all modifiable behaviors on perceived health were significant.
CONCLUSIONS AND IMPLICATIONS CONCLUSIONS
Health promotion programs for adults with ID may benefit by consideration of modifiable behaviors.

Identifiants

pubmed: 32330846
pii: S0891-4222(20)30072-X
doi: 10.1016/j.ridd.2020.103642
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

103642

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Auteurs

Jooyeon Jin (J)

University of Seoul, 163 Seoulsiripdaero, Seoul 02504, Republic of Korea. Electronic address: jjin13@uos.ac.kr.

Stamatis Agiovlasitis (S)

Mississippi State University, PO Box 6186, Mississippi State, MS 39762, United States. Electronic address: sagiovlasitis@colled.msstate.edu.

Joonkoo Yun (J)

East Carolina University, M60 Minges, Mail Stop 559, Greenville, NC 27858, United States. Electronic address: yunj19@ecu.edu.

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Classifications MeSH