{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T19:47:19Z","timestamp":1790020039850,"version":"4.0.1"},"reference-count":29,"publisher":"American Academy of Pediatrics (AAP)","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,10,1]]},"abstract":"<jats:sec>\n                  <jats:title>BACKGROUND AND OBJECTIVES:<\/jats:title>\n                  <jats:p>Despite their medical vulnerability, youth with chronic medical conditions (YCMCs) drink at levels commensurate with healthy youth. However, information about the prevalence of alcohol use among YCMCs who take alcohol-interactive (AI) medications is scant. To address gaps and inform interventions, we quantified simultaneous exposure to alcohol use and AI medications among YCMCs, hypothesizing that AI exposure would be associated with lower alcohol consumption and mediated by perceptions of alcohol-medication interference.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>METHODS:<\/jats:title>\n                  <jats:p>Adolescents with type 1 diabetes, juvenile idiopathic arthritis, moderate persistent asthma, cystic fibrosis, attention-deficit\/hyperactivity disorder, or inflammatory bowel disease completed an electronic survey. We measured the prevalence of exposure to AI medications and the associations with past-year alcohol use as well as binge drinking and total consumption volume in the past 3 months using multivariate regression to estimate the odds of alcohol use given AI medication exposure and perceptions of interference.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>RESULTS:<\/jats:title>\n                  <jats:p>Of 396 youth, 86.4% were on AI medications, of whom, 35.4% reported past-year alcohol use (46.3% among those who were not on AI medications). AI medication use was associated with 43% lower odds of past-year alcohol use (adjusted odds ratio: 0.57; 95% confidence interval: 0.39\u20130.85) and lower total consumption (\u03b2 = \u2212.43; SE = 0.11; P &amp;lt; .001). Perceptions of alcohol-medication interference partially mediated the relationship between AI medication exposure and past-year alcohol use (Sobel test P = .05).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>CONCLUSIONS:<\/jats:title>\n                  <jats:p>Many YCMCs reported using alcohol; however, drinking was less likely among those who were taking AI medications. Perceptions about alcohol-medication interference mediated the association between drinking and AI medication exposure, suggesting the potential salience of interventions that emphasize alcohol-related risks.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1542\/peds.2017-4026","type":"journal-article","created":{"date-parts":[[2018,9,18]],"date-time":"2018-09-18T07:25:10Z","timestamp":1537255510000},"source":"Crossref","is-referenced-by-count":27,"title":["Alcohol Use and Alcohol-Interactive Medications Among Medically Vulnerable Youth"],"prefix":"10.1542","volume":"142","author":[{"given":"Elissa R.","family":"Weitzman","sequence":"first","affiliation":[{"name":"Divisions of Adolescent and Young Adult Medicine and"},{"name":"Computational Health Informatics Program, Boston Children\u2019s Hospital, Boston, Massachusetts; and"},{"name":"Department of Pediatrics, Harvard Medical School, Harvard University, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kara M.","family":"Magane","sequence":"additional","affiliation":[{"name":"Divisions of Adolescent and Young Adult Medicine and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lauren E.","family":"Wisk","sequence":"additional","affiliation":[{"name":"Divisions of Adolescent and Young Adult Medicine and"},{"name":"Department of Pediatrics, Harvard Medical School, Harvard University, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph","family":"Allario","sequence":"additional","affiliation":[{"name":"Developmental Medicine, and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth","family":"Harstad","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Harvard Medical School, Harvard University, Boston, Massachusetts"},{"name":"Developmental Medicine, and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sharon","family":"Levy","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Harvard Medical School, Harvard University, Boston, Massachusetts"},{"name":"Developmental Medicine, and"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"417","published-online":{"date-parts":[[2018,10,1]]},"reference":[{"issue":"4","key":"2021121023374995500_B1","first-page":"1","article-title":"Youth risk behavior surveillance\u2013United States, 2013 [published correction appears in MMWR Morb Wkly Rep. 2014;63(26):576].","volume":"63","author":"Kann","year":"2014","journal-title":"MMWR Suppl"},{"issue":"9571","key":"2021121023374995500_B2","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1016\/S0140-6736(07)60370-5","article-title":"Adolescents with a chronic condition: challenges living, challenges 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