Department of Pharmacy Practice & Science, University of Arizona Col-lege of Pharmacy, Tucson, Arizona. ORCID: https://orcid.org/0000-0002-9903-5996.
University of Arizona College of Pharmacy, Tucson, Arizona.
J Opioid Manag. 2022 Mar-Apr;18(2):95-105. doi: 10.5055/jom.2022.0700.
To identify the strongest predictors of opioid use among older United States' (US) adults (≥50 years) with pain.
Cross-sectional retrospective database design.
2017 Medical Expenditure Panel Survey data.
Civilian, noninstitutionalized sample of US adults aged ≥50 years alive for the calendar year with pain in the past 4 weeks.
Hierarchical logistic regression models assessed significant predictors of opioid use, which included: predisposing, enabling, need, personal health practices, and external environmental factors.
Opioid use status (opioid user vs. nonopioid user).
Among 51,372,861 civilian, noninstitutionalized US adults alive aged ≥50 years with pain in 2017, the opioid use prevalence was 27.4 percent (95 percent confidence interval = 25.8-29.0). Predictors of opioid use included: white versus other race (adjusted odds ratio, AOR = 1.430), Hispanic versus non-Hispanic ethnicity (AOR = 0.648), up to high school versus higher than high school education (AOR = 1.259), functional limitation versus no limitation (AOR = 1.580), lit-tle/moderate versus quite a bit/extreme pain (AOR = 0.422), good versus fair/poor perceived mental health status (AOR = 1.429), smokers versus nonsmokers (AOR = 1.523), and residing in the northeast versus west US (AOR = 0.646).
This study of 51 million older US adults with pain indicated that several factors including race, ethnicity, education, functional limitations, pain severity, mental health status, smoking status, and region of the country were pre-dictors of opioid use. Future research is needed in additional clinical populations and to investigate where these findings diverge from previous studies.
确定美国（≥50 岁）老年疼痛患者中阿片类药物使用的最强预测因素。
横断面回顾性数据库设计。
2017 年医疗支出面板调查数据。
在世的、非住院的、≥50 岁的美国成年人，他们在过去 4 周内有疼痛。
分层逻辑回归模型评估了阿片类药物使用的显著预测因素，包括：倾向因素、促成因素、需要因素、个人健康行为和外部环境因素。
阿片类药物使用状况（阿片类药物使用者与非阿片类药物使用者）。
在 2017 年，51372861 名在世的、非住院的、≥50 岁的、有疼痛的美国成年公民中，阿片类药物使用率为 27.4%（95%置信区间=25.8%-29.0%）。阿片类药物使用的预测因素包括：白人对其他种族（调整后优势比，AOR=1.430）、西班牙裔对非西班牙裔（AOR=0.648）、高中及以下教育对高于高中教育（AOR=1.259）、功能限制对无限制（AOR=1.580）、轻度/中度疼痛对相当多/极度疼痛（AOR=0.422）、良好对一般/较差心理健康状况（AOR=1.429）、吸烟者对非吸烟者（AOR=1.523）以及东北部对美国西部（AOR=0.646）。
本研究对 5100 万患有疼痛的美国老年患者进行了研究，结果表明，包括种族、民族、教育、功能限制、疼痛严重程度、心理健康状况、吸烟状况和所在地区在内的几个因素是阿片类药物使用的预测因素。需要在其他临床人群中进行进一步的研究，以调查这些发现与以往研究的差异。
