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This study examined whether these policy changes were associated with changes in alcohol use patterns and explored age\u2010group differences.<\/jats:p><\/jats:sec><jats:sec><jats:title>Design<\/jats:title><jats:p>We examined monthly rates of positive alcohol screens in primary care patients in California from 2015 to 2019. Using an interrupted time series design and autoregressive integrated moving average (ARIMA) models, changes were evaluated in the overall sample and stratified by age groups (21\u201334, 35\u201364 and 65+) across two key intervention points for ACL: 9 November 2016 (ACL passage) and 1 January 2018 (ACL implementation). Time\u2010varying confounders of seasonality and autocorrelation were controlled for.<\/jats:p><\/jats:sec><jats:sec><jats:title>Setting<\/jats:title><jats:p>California, United States; Kaiser Permanente Northern California Healthcare System.<\/jats:p><\/jats:sec><jats:sec><jats:title>Participants<\/jats:title><jats:p>Across the study period, <jats:italic>n<\/jats:italic>\u2009=\u20098\u2009028\u2009627 screenings were completed for \u2009<jats:italic>n<\/jats:italic>=\u00a03\u2009525\u2009493 unique patients aged 21+\u2009.<\/jats:p><\/jats:sec><jats:sec><jats:title>Measurements<\/jats:title><jats:p>Aggregated monthly rates of patients exceeding daily limits, weekly limits, exceeding both daily and weekly limits and frequent heavy episodic drinking (HED), based on current US guidelines set by the National Institute on Alcohol Abuse and Alcoholism.<\/jats:p><\/jats:sec><jats:sec><jats:title>Findings<\/jats:title><jats:p>Statistically significant, gradual declines in rates of both exceeding weekly alcohol limits [estimate (95% confidence interval [CI])\u00a0of slope change\u2009=\u2009\u22120.013(\u22120.019 to\u00a0\u22120.008), <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.001] and frequent HED followed ACL passage [estimate (95% CI) of slope change\u2009=\u2009\u22120.015(\u22120.024 to \u22120.005), <jats:italic>P<\/jats:italic>\u2009=\u20090.003]. ACL implementation was generally not associated with further changes, suggesting changes after ACL passage were sustained over time. Age\u2010group patterns varied: young adults (21\u201334) demonstrated an immediate increase, followed by a statistically significant gradual decline in rates of HED post\u2010ACL passage [estimate (95% CI) of slope change\u2009=\u2009\u22120.096(\u22120.160, \u22120.033), <jats:italic>P<\/jats:italic>\u2009=\u20090.003], as well as an immediate decrease post ACL implementation; adults 35\u201349 showed consistent declines in step and slope in rates of frequent HED post ACL passage; adults 50\u201364 showed an immediate increase in rates of exceeding weekly limits [estimate (95% CI) of step change\u2009=\u20090.167(0.036\u20130.297), <jats:italic>P<\/jats:italic>\u2009=\u20090.012], with gradual declines in the other drinking limits; adults 65\u2009+\u2009had small, gradual decreases. In addition, exploratory analyses in 18\u201320\u2010year\u2010olds showed gradual increases in rates of frequent HED post ACL passage, but the <jats:italic>P<\/jats:italic> value was not significant after Bonferroni correction.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Cannabis policy changes in California, USA, appear to be linked to age\u2010specific changes in alcohol use, with moderate reductions, particularly among middle\u2010aged adults. Findings were associative in nature and causality could not be determined.<\/jats:p><\/jats:sec>","DOI":"10.1111\/add.70134","type":"journal-article","created":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T03:48:40Z","timestamp":1753415320000},"page":"2282-2294","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Are cannabis policy changes associated with alcohol use patterns? Evidence for age\u2010group differences based on primary care screening data"],"prefix":"10.1111","volume":"120","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6044-7208","authenticated-orcid":false,"given":"Natalia","family":"Van Doren","sequence":"first","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences University of California  San Francisco CA USA"},{"name":"Division of Research Kaiser Permanente Northern California  Pleasanton CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Felicia W.","family":"Chi","sequence":"additional","affiliation":[{"name":"Division of Research Kaiser Permanente Northern California  Pleasanton CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6177-534X","authenticated-orcid":false,"given":"Kelly C.","family":"Young\u2010Wolff","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences University of California  San Francisco CA USA"},{"name":"Division of Research Kaiser Permanente Northern California  Pleasanton CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4228-1504","authenticated-orcid":false,"given":"Derek D.","family":"Satre","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences University of California  San Francisco CA USA"},{"name":"Division of Research Kaiser Permanente Northern California  Pleasanton CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stacy A.","family":"Sterling","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences University of California  San Francisco CA USA"},{"name":"Division of Research Kaiser Permanente Northern California  Pleasanton CA USA"},{"name":"Department of Health Systems Science Kaiser Permanente Bernard J. 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