Skip to main content
Download PDF
- Main
Relationship of pain and ancestry in African American women
Published Web Location
https://doi.org/10.1002/ejp.680Abstract
Background
African Americans are reported to be more sensitive to pain than European Americans. Pain sensitivity has been shown to be genetically linked in animal models and is likely to be in humans.Methods
Exactly, 11,239 self-identified African American post-menopausal women enrolled in the Women's Health Initiative had percentage African ancestry determined by ancestry informative markers, "Pain Construct" measurements and covariate information. They answered five questions about specific types and location of pain, such as joint, neck, low back, headache and urinary. They also answered two questions which were used to derive a "Pain Construct", a measure of general pain scored on a scale of 1-100. Associations were tested in linear regression models adjusting for age, self-reported medical conditions, neighbourhood socio-economic status, education and depression.Results
In the unadjusted model of the five specific types of pain measures, greater pain perception was associated with a higher proportion of African ancestry. However, some of the specific types of pain measures were no longer associated with African ancestry after adjustment for other study covariates. The Pain Construct was statistically significantly associated with African ancestry in both the unadjusted [β = -0.132, 95% confidence interval (CI) = -099 to -0.164; r = -0.075, 95% CI -0.056 to -0.093] and the adjusted models (β = -0.069 95% CI = -0.04 to -0.10).Conclusions
Greater African ancestry was associated with higher levels of self-reported pain, although this accounted for only a minor fraction of the overall variation in the Pain Construct.Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
Main Content
For improved accessibility of PDF content, download the file to your device.
Enter the password to open this PDF file:
File name:
-
File size:
-
Title:
-
Author:
-
Subject:
-
Keywords:
-
Creation Date:
-
Modification Date:
-
Creator:
-
PDF Producer:
-
PDF Version:
-
Page Count:
-
Page Size:
-
Fast Web View:
-
Preparing document for printing…
0%