Prescription Opioid Use and Laboratory Value Derangements: A Cross-Sectional Analysis of NHANES Data
Micah Hartwell1, Benjamin Greiner2, Kelly Dunn3
1Department of Psychiatry and Behavioral Sciences, Oklahoma State University Center for Health Sciences, Tulsa, OK.
Background:
The use of opioids for the treatment of pain is a risk versus benefit analysis and metabolic disease is an often overlooked variable in the equation and may lead to increased risk of comorbidities of cardiovascular and cerebrovascular disease and diabetes.
Objectives:
Our objective was to identify and describe abnormalities among the comprehensive metabolic and lipid panels of individuals taking prescription opioids.
Study Design:
We performed a cross-sectional study of the laboratory values with 3 cycles (2011-2016) of the National Health and Nutrition Examination Survey (NHANES) in March 2020.
Setting:
NHANES sampling is conducted using a multistaged, stratified, cluster sampling technique to create a representative sample of the United States.
Methods:
We excluded patients with histories of cancer and under the age of 25 years. Our final sample size was 11,061 (n = 162,547,635), with 797 reportedly using a prescription opioid in the past 30 days-a weighted percent representing 22.95% of the US population. Our analyses identified mean differences in biomarkers between individuals taking prescription opioids and the US population.
Results:
Laboratory values from the comprehensive metabolic panel were all within reference ranges for both groups, with only bilirubin levels being statistically lower in the group currently taking prescription opioids. Values from the lipid panel of both the opioid using and comparison groups were above reference range for total cholesterol and fasting glucose. The opioid using group was also higher than the reference range for triglycerides (mean [M] = 165.4, standard deviation [SD] = 14.2) and insulin (M = 15.5, SD = 2.2), whereas the comparison group was not. The oral glucose measure was within normal ranges for both groups; however, the opioid using group was 13.7 points higher than the comparison group (M = 122.3, SD = 1.8; M = 108.6, SD = 4.0; P < 0.01).
Limitations:
While our study uses a large sample for a robust generalizable analysis it is a correlation study and a longitudinal cohort would provide better evidence linking potential disease states to prescription opioid use.
Conclusions:
Although all Americans should be alarmed at the lipid levels reported in this study, specific combinations of heightened lipid laboratory values among prescription opioid users accelerate the trajectories toward comorbidities-heart disease, cerebrovascular disease, and diabetes-leading to diminished quality of life. Therefore pain management and comprehensive drug recovery programs should include nutritional counseling and physical activity as part of their overall treatment plan.
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