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This study uses nationally representative 2023 data (n=9,762) from the National Survey on Drug Use and Health to identify past-year risk factors among older adults via stepwise binary logistic regression, with risk associations varying across modeled domains.",{"@graph":14,"@context":76},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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regression was used, beginning with sociodemographics and then adding physical health, mental health, and other substance use factors in subsequent models.",{"name":73,"@type":60,"acceptedAnswer":74},"Which factors were associated with opioid misuse in later models?",{"text":75,"@type":63},"Poor self-rated health remained significantly associated with misuse in the final model, and a lifetime history of depression was also associated with misuse.","https://schema.org",{"og:url":32,"og:type":78,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":80,"canonical":32},"index,follow",{"doc_id":82,"site_id":7},427781,1790716692,{"code":4,"msg":85,"data":86},"success",[87,91,95,99,104,109,114,118,123,126,130],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":88,"show_sort_weight":89,"slug":90},"Story & 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annual income less than $20,000 (OR = 1.55; 95% CI: 1.01-2.39). When physical health factors were added to the model, income was no longer associated with misuse and poor self-rated health was found to be associated with opioid misuse (OR = 1 .94; 95% CI: 1.44-2. 63) . When mental health and other substance use factors were added in the final model, self-rated health remained significantly associated with misuse (OR = 1.70; 95% CI: 1.24-2.34) and a lifetime history of depression was also found to be associated with misuse (OR = 2.06; 95% CI: 1.47-2.88). Findings from this study help inform our basic knowledge on risk factors for prescription opioid misuse, which can help inform targeted screening and intervention.  \nAbstract citation ID: igaf122.2514  \nRISK FACTORS FOR PRESCRIPTION OPIOID MISUSE  \nIN OLDER ADULTS: FINDINGS FROM THE NATIONAL  \nSURVEY ON DRUG USE AND HEALTH  \nAndie MacNeil, and David Burnes, University of Toronto, Toronto, Ontario, Canada  \nPrescription opioid misuse is recognized as a significant public health concern and social problem because it significantly increases the risk of both fatal and non-fatal overdose. Although a large body of research has examined risk factors for prescription opioid misuse, this research has disproportionately focused on younger adults, even though older adults are more likely to have an opioid prescription than any other age cohort. To address this gap in the literature, this study analyzed nationally representative data from the 2023 National Survey on Drug Use and Health to identify risk factors for past-year prescription opioid misuse among older adults (n = 9,762). Stepwise binary logistic regression analyses were conducted to examine risk factors for prescription opioid misuse. In the first model, which only accounted for sociodemographics, risk factors for opioid","cbCaie9bhvdwYFz4","https://ap.wps.com/l/cbCaie9bhvdwYFz4","pdf",667219,"English","# Study purpose and background\n## Data source and sample\n## Methods: stepwise binary logistic regression\n## Main findings across model stages\n## Implications for screening and intervention","[{\"question\":\"Why focus on older adults for prescription opioid misuse risk factors?\",\"answer\":\"Older adults are more likely to have an opioid prescription than any other age cohort, yet most prior research has disproportionately examined younger adults.\"},{\"question\":\"What data and sample size were used in the study?\",\"answer\":\"The study analyzed nationally representative 2023 National Survey on Drug Use and Health data, including 9,762 older adults.\"},{\"question\":\"How were risk factors for opioid misuse analyzed?\",\"answer\":\"Stepwise binary logistic regression was used, beginning with sociodemographics and then adding physical health, mental health, and other substance use factors in subsequent models.\"},{\"question\":\"Which factors were associated with opioid misuse in later models?\",\"answer\":\"Poor self-rated health remained significantly associated with misuse in the final model, and a lifetime history of depression was also associated with misuse.\"}]","Risk Factors for Prescription Opioid Misuse in Older Adults - Findings from the National Survey on Drug Use and Health | PDF",1790644791]