The relationship between literacy and multimorbidity in a primary care setting View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-12

AUTHORS

Catherine Hudon, Martin Fortin, Marie-Eve Poitras, José Almirall

ABSTRACT

BACKGROUND: Multimorbidity is now acknowledged as a research priority in primary care. The identification of risk factors and people most at risk is an important step in guiding prevention and intervention strategies. The aim of this study was to examine the relationship between literacy and multimorbidity while controlling for potential confounders. METHODS: Participants were adult patients attending the family medicine clinic of a regional health centre in Saguenay (Quebec), Canada. Literacy was measured with the Newest Vital Sign (NVS). Multimorbidity was measured with the Disease Burden Morbidity Assessment (DBMA) by self-report. Information on potential confounders (age, sex, education and family income) was also collected. The association between literacy (independent variable) and multimorbidity was examined in bivariate and multivariate analyses. Two operational definitions of multimorbidity were used successively as the dependent variable; confounding variables were introduced into the model as potential predictors. RESULTS: One hundred three patients (36 men) 19-83 years old were recruited; 41.8% had completed 12 years of school or less. Forty-seven percent of patients provided fewer than four correct answers on the NVS (possible low literacy) whereas 53% had four correct responses or more. Literacy and multimorbidity were associated in bivariate analyses (p < 0.01) but not in multivariate analyses, including age and family income. CONCLUSION: This study suggests that there is no relationship between literacy and multimorbidity when controlling for age and family income. More... »

PAGES

33

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2296-13-33

DOI

http://dx.doi.org/10.1186/1471-2296-13-33

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1011683434

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22536833


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/1471-2296-13-33'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2296-13-33'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2296-13-33'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2296-13-33'


 

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