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dc.contributor.authorBaker, Tamara A.
dc.contributor.authorClay, Olivio J.
dc.contributor.authorJohnson-Lawrence, Vicki
dc.contributor.authorMinahan, Jacquelyn A.
dc.contributor.authorMingo, Chivon A.
dc.contributor.authorThorpe, Roland J.
dc.contributor.authorOvalle, Fernando
dc.contributor.authorCrowe, Michael
dc.date.accessioned2018-10-04T16:38:33Z
dc.date.available2018-10-04T16:38:33Z
dc.date.issued2017-10-30
dc.identifier.citationBaker T., Clay, O., Johnson-Lawrence, V., Minahan, J., Mingo, C., Thorpe, R., Ovalle, F., Crowe, M.: Association of multiple chronic conditions and pain among older black and white adults with diabetes mellitus, BMC Geriatrics, https://doi.org/10.1186/s12877-017-0652-8en_US
dc.identifier.urihttp://hdl.handle.net/1808/26776
dc.description.abstractBackground Aging is often associated with the challenge of navigating daily tasks with a painful chronic medical illness. Yet, there is concern of the number of older adults impacted with more than one chronic condition. Despite the increasing number of adults diagnosed with diabetes and comorbid chronic illnesses, there remains a lack of understanding in how multiple illnesses relate to experiences of pain. To assess the association between multiple chronic conditions and pain, this study aimed to identify clusters of chronic medical conditions and their association with pain among a sample of older Black and White adults diagnosed with diabetes.

Methods Two hundred and thirty-six participants responded to a series of questions assessing pain frequency and severity, as well as health and social characteristics. A factor analysis was used to categorize clusters of medical conditions, and multiple regression models were used to examine predictors of pain.

Results Seven of the assessed chronic medical conditions loaded on three factors, and accounted for 57.2% of the total variance, with heart disease (factor 1) accounting for 21.9%, musculoskeletal conditions (factor 2) for another 18.4%, and factor 3 (microvascular diseases) accounting for a final 16.9% of the variability among the chronic medical conditions. Covariate-adjusted models showed that fewer years of education and higher scores on the microvascular and musculoskeletal conditions factors were associated with higher pain frequency, with the musculoskeletal conditions factor being the strongest predictor.

Conclusions Findings from this study compliment existent literature underscoring the prevalence and importance of comorbid diagnoses in relation to pain. Examining health-related factors beyond a single disease diagnosis also provides an opportunity to explore underlying disease co-occurrences that may persist beyond organ system classifications.
en_US
dc.publisherBMCen_US
dc.rights© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectMultiple chronic conditionsen_US
dc.subjectPainen_US
dc.subjectOlder adultsen_US
dc.subjectDiabetesen_US
dc.subjectDeterminants of healthen_US
dc.titleAssociation of multiple chronic conditions and pain among older black and white adults with diabetes mellitusen_US
dc.typeArticleen_US
kusw.kuauthorBaker, Tamara A.
kusw.kuauthorMinahan, Jacquelyn A.
kusw.kudepartmentPsychologyen_US
dc.identifier.doihttps://doi.org/10.1186/s12877-017-0652-8en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.rights.accessrightsopenAccessen_US


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© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Except where otherwise noted, this item's license is described as: © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.