Preventing Chronic Disease最新文献

{"title":"Learning Health Systems for Chronic Disease: Embedded Artificial Intelligence Tools That Continuously Improve Care.","authors":"Anand Gourishankar, Sophia Z Shalhout","doi":"10.5888/pcd23.260103","DOIUrl":"https://doi.org/10.5888/pcd23.260103","url":null,"abstract":"","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"23 ","pages":"E49"},"PeriodicalIF":5.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13632928/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149118289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Accuracy and Completeness of OpenStreetMap Sidewalks: A Comparative Study With Google Street View.","authors":"Brianne L Nichols, Caroline Groth, Tyler D Quinn","doi":"10.5888/pcd23.260255","DOIUrl":"10.5888/pcd23.260255","url":null,"abstract":"<p><strong>Introduction: </strong>OpenStreetMap is an open-source and crowd-sourced geospatial database and one of the few available sources of sidewalk data for walkability research; however, its accuracy and completeness have not been systematically assessed. This study aimed to compare OpenStreetMap sidewalk data with Google Street View.</p><p><strong>Methods: </strong>We clipped an OpenStreetMap map of pedestrian-accessible roads in Maryland to 141 census tracts (~10.0% of census tracts in Maryland) using stratified random sampling across tertiles of population density. Fifty points within each census tract were randomly distributed across qualifying roads (n = 7,050). We determined sidewalk presence at each point in OpenStreetMap and Google Street View. We excluded points without Google Street View, resulting in a final sample of 6,103 points. In points with sidewalks in Google Street View (n = 3,674), logistic mixed effects models estimated odds of OpenStreetMap-Google Street View sidewalk agreement across population density tertiles and themes from the Centers for Disease Control and Prevention's Social Vulnerability Index (SVI).</p><p><strong>Results: </strong>Of the total points (N = 6,103), 57.8% (3,530) indicated sidewalk agreement between OpenStreetMap and Google Street View. Agreement was 30.2% among points with sidewalks present in Google Street View. Among points with sidewalks (3,674) present in Google Street View, odds of sidewalk agreement were higher in mid-density tracts (odds ratio [OR], 2.43; 95% CI, 0.63-9.40) and high-density tracts (OR, 4.50, 95% CI, 1.16-17.38) than in low-density tracts. Tracts in which a racial and ethnic minority population was larger than the non-Hispanic White population had lower sidewalk agreement (OR, 0.11; 95% CI, 0.002-0.74); no other SVI theme was associated with agreement.</p><p><strong>Conclusion: </strong>While OpenStreetMap sidewalk data were generally accurate when available, the sidewalk data were incomplete, especially in areas with low population density or areas in which a non-Hispanic racial and ethnic minority population was larger than the White population.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"23 ","pages":"E48"},"PeriodicalIF":5.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13632927/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149118230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge, Attitudes, and Perceptions of the Physician's Role in Colorectal Cancer Screening Among Primary Care Patients in Msaken, Tunisia, 2026.","authors":"Rania Bannour, Lassaad Trabelssi, Omar Khalil Ben Saad, Amani Hassine, Jihene Sahli, Amara Amel, Mariem Ghardallou, Manel Mallouli, Chekib Zedini","doi":"10.5888/pcd23.260083","DOIUrl":"10.5888/pcd23.260083","url":null,"abstract":"<p><strong>Introduction: </strong>Colorectal cancer (CRC) is a major public health concern worldwide and an emerging health issue in Tunisia. Early screening is critical for prevention and early diagnosis. Our study aimed to assess knowledge, attitudes, and behaviors related to CRC screening among primary care patients and to examine factors associated with screening acceptance, including the perceived role of physicians, as well as the barriers to discussing CRC.</p><p><strong>Methods: </strong>We conducted a cross-sectional study among adults consulting primary health care centers in Msaken, Tunisia, in January 2026. Data were collected by using a validated, structured questionnaire that assessed sociodemographic characteristics, knowledge of CRC and screening methods, sources of information, physician-patient communication, attitudes toward screening, and perceived barriers. Associations were analyzed by using univariate and multivariate logistic regression.</p><p><strong>Results: </strong>The study sample consisted of 701 participants. Among them, 72.0% had heard of CRC, but only 5.8% correctly identified the recommended age for screening. Almost one-third (32.8%) reported awareness of the hemoccult test, and 64.6% expressed willingness to undergo the test if it was free. We identified several independently associated factors with acceptance of a hemoccult test, including prior awareness of CRC (odds ratio [OR] = 2.18; P < .001), family history of CRC (OR = 2.00; P < .001), exposure to medical internet sources (OR = 2.06; P < .001), and prior discussion with a physician (OR = 2.46; P < .001).</p><p><strong>Conclusion: </strong>Although patient attitudes were generally positive, we found notable gaps in knowledge and screening practices. The strongest determinant of screening acceptance was doctor-patient communication, which shows the importance of the role primary care physicians in CRC prevention.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"23 ","pages":"E45"},"PeriodicalIF":5.6,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13614343/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149041822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association Between Various Metrics of the Rural Food Environment and Diabetes and Obesity.","authors":"Jessica Gjonaj, Haeseung Yi, Tammy A Flores, Crystal So, Haley L Motola, Demba Keita, Jessie Moore, Brian Elbel, Lorna E Thorpe, David C Lee","doi":"10.5888/pcd23.260106","DOIUrl":"10.5888/pcd23.260106","url":null,"abstract":"<p><strong>Introduction: </strong>Associations between unhealthy food environments and increased risk of diabetes or obesity have been studied extensively in urban areas but less so in rural areas. To address this gap, we performed a geographically detailed study of the rural food environment, summarizing and assessing various measures and identifying their association with a higher rate of diabetes and obesity.</p><p><strong>Methods: </strong>We surveyed 1,311 residents of Sullivan County, New York, collecting data on demographic characteristics and health status in January 2021. We assessed the food environment by cataloging restaurants and retail food stores and used least absolute shrinkage and selection operator (LASSO) regression to identify metrics strongly associated with diabetes and obesity (body mass index >30.0). We compared absolute proximity, density, relative proportions, and modified retail food environment index metrics. We applied fixed distance bands and nearest-neighbor approaches for proportions.</p><p><strong>Results: </strong>Older age (LASSO = +0.276), nearest-neighbor proportion of fast food restaurants (LASSO = +0.155), and low income (LASSO = +0.150) were associated with higher diabetes rates. Nearest-neighbor proportion (LASSO = +0.269), density per square mile of groceries/supermarkets (LASSO = +0.247), and Hispanic ethnicity (LASSO = +0.181) were the strongest predictors of obesity. Nearest-neighbor metrics helped with the problem of frequent zeros: the least skewed measures were fast food restaurants with 20 nearest neighbors (P = .37 for skewness) and counter-service restaurants with 20 nearest neighbors (P = .81).</p><p><strong>Conclusion: </strong>Nearest-neighbor approaches were less skewed to other metrics based on fixed distance bands, proximity, and density. Food environment metrics must be fully described and validated, especially in rural environments, before they are applied in research on critical health outcomes.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"23 ","pages":"E46"},"PeriodicalIF":5.6,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13614342/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149041802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transportation Walking Among US Adults With and Without Transportation Insecurity, 2022 National Health Interview Survey.","authors":"Graycie Soto, Miriam E Van Dyke, Jasmine Y Nakayama, Tiffany J Chen, Heather M Devlin, Katherine Irani, Jennifer L Matjasko, Hatidza Zaganjor, Geoffrey P Whitfield","doi":"10.5888/pcd23.250436","DOIUrl":"10.5888/pcd23.250436","url":null,"abstract":"<p><strong>Introduction: </strong>How Americans get to everyday destinations has implications for health and well-being. Transportation insecurity, or the lack of safe and convenient access to reliable transportation, is a public health problem that can lead to morbidity and mortality through injuries and chronic disease. Walking can be a healthy and low-cost mode of transportation. This study describes transportation walking among US adults with and without transportation insecurity.</p><p><strong>Methods: </strong>We used 2022 National Health Interview Survey data on 25,889 US adults to estimate the prevalence of transportation walking among adults with and without transportation insecurity across sociodemographic and geographic subgroups. We tested subgroup differences using pairwise comparisons.</p><p><strong>Results: </strong>In this sample, 5.6% (95% CI, 5.1%-6.2%) of US adults reported transportation insecurity. Walking for transportation was twice as common among adults with transportation insecurity (30.9%; 95% CI, 27.9%-34.1%) than among adults without transportation insecurity (15.3%; 95% CI, 14.5%-16.1%). Among adults with transportation insecurity, the prevalence of transportation walking was higher for adults with the lowest versus the highest levels of educational attainment, adults below versus above their poverty threshold, non-Hispanic Black versus non-Hispanic White adults, younger versus older adults, adults without versus adults with disabilities, and those residing in the West versus the South.</p><p><strong>Conclusion: </strong>About 1 in 6 US adults walk for transportation, but those with transportation insecurity are twice as likely to do so as those without. Infrastructure and policies that support walking can help improve the health and well-being of Americans and may be especially important for those experiencing transportation insecurity.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"23 ","pages":"E43"},"PeriodicalIF":5.6,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13587706/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148992430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rural-Urban and Appalachian Disparities in Geographic Access to Colonoscopy and Screening Prevalence Across the Contiguous US.","authors":"Sima Namin, R Eric Heidel, Martin Whiteside, Jennifer Ferris, Jonathan S Wall, James M McLoughlin","doi":"10.5888/pcd23.260126","DOIUrl":"10.5888/pcd23.260126","url":null,"abstract":"<p><strong>Introduction: </strong>Colorectal cancer (CRC) incidence and mortality rates are disproportionately high in rural and Appalachian communities, where geographic barriers and specialist shortages may limit access to colonoscopy.</p><p><strong>Methods: </strong>We conducted a national cross-sectional geospatial analysis of all contiguous US census tracts. We identified colonoscopy providers by using National Provider Identifier specialty designations and colonoscopy procedure indicators. Geographic access was quantified by using a 4-band enhanced 2-step floating catchment area (E2SFCA) method. We used small-area estimation for colonoscopy from Centers for Disease Control and Prevention PLACES to determine CRC screening prevalence. We compared E2SFCA distributions across rural-urban and Appalachian-non-Appalachian using the Kruskal-Wallis test with Benjamini-Hochberg-adjusted Dunn post hoc pairwise comparisons; we modeled screening prevalence using a mixed-effects beta regression analysis.</p><p><strong>Results: </strong>Urban census tracts tended to rely on delivery of colonoscopies by gastroenterologists and ambulatory surgical centers, whereas rural census tracts relied more on general surgeons, particularly for screening (vs diagnostic/therapeutic colonoscopy). Geographic access to colonoscopy providers varied little across census tracts, with only modest differences by rurality and Appalachian designation. In mixed-effects beta regression, colonoscopy access was not significantly associated with screening prevalence while both rural and Appalachian census tracts had slightly lower screening prevalence compared with their counterparts (rural vs urban: Exp(β) = 0.994; P = .02; Appalachian vs non-Appalachian: Exp(β) = 0.976; P < .001).</p><p><strong>Conclusion: </strong>Better geographic access does not translate into meaningfully higher screening prevalence. Structural, socioeconomic, and referral-related barriers likely attenuate the effect of geographic proximity on screening behavior. Further integration of claims-based utilization and patient-level factors is needed to clarify pathways between access and CRC screening.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"23 ","pages":"E44"},"PeriodicalIF":5.6,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13587705/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148992444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social Determinants of Health, Depression, and Cardiovascular Health Among Veterans and Civilians: Insights From the 2013-2018 and 2021-2023 National Health and Nutrition Examination Survey.","authors":"Arum Lim, Chitchanok Benjasirisan, Marian Botchway, Ashwag Alhabodal, Diana-Lyn Baptiste, Jessica Gill, Binu Koirala","doi":"10.5888/pcd23.260097","DOIUrl":"10.5888/pcd23.260097","url":null,"abstract":"<p><strong>Introduction: </strong>Emerging evidence supports the relationship among social determinants of health, depression symptoms, and cardiovascular health. Veterans have a disproportionate prevalence of cardiovascular disease and depression, social determinants of health concerns related to socioeconomic status, and challenges with access to healthcare. This study aimed to examine associations of social determinants of health and depression symptoms with cardiovascular health among civilians and veterans and assessed whether these associations differed between the 2 groups.</p><p><strong>Methods: </strong>Our cross-sectional analysis used 2013-2018 and 2021-2023 National Health and Nutrition Examination Survey data on participants aged 20 years or older without cardiovascular disease. Social determinants of health included demographic characteristics, socioeconomic factors, and access to health care. We used the Patient Health Questionnaire-9 to assess the severity of depression and dichotomized scores as 0 to 5 symptoms (no depression) or 5 or more symptoms (mild to severe depression). We quantified cardiovascular health using Life's Essential 8 scoring metric (scored from 0 to 100, with higher scores indicating better health status). We applied sample weights in multiple linear regressions.</p><p><strong>Results: </strong>Among 11,396 participants, 10,470 were civilians (mean age, 46 y; 55% female) and 926 were veterans (mean age, 56 y; 10% female). Mean cardiovascular health score was 71 among civilians and 67 among veterans. Veterans were more likely to have some college, higher financial status, and access to health care. Among both civilians and veterans, poorer cardiovascular health was associated with older age, identifying as non-Hispanic Black or as \"other\" or multiracial, lower education, lower financial status, and depression symptoms. These associations were more pronounced among veterans who identify as members of racial and ethnic minority populations or have lower financial status.</p><p><strong>Conclusion: </strong>The magnitude of the links between cardiovascular health and some social determinants of health varied by veteran status, indicating that varied factors may influence health disparities in each group and underscoring the need for tailored strategies to address them.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"23 ","pages":"E41"},"PeriodicalIF":5.6,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13564471/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148931553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum, Volume 23, July 23 Release.","authors":"","doi":"10.5888/pcd23.250471e","DOIUrl":"10.5888/pcd23.250471e","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.5888/pcd23.250471.].</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"23 ","pages":"E40"},"PeriodicalIF":5.6,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13564470/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148931331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal Spatial Analysis of Health-Related Quality of Life in Mississippi: Clustering, Trends, and Socioeconomic Drivers.","authors":"Jae Eun Lee, JungHye Sung, Ji-Young Lee","doi":"10.5888/pcd23.260175","DOIUrl":"10.5888/pcd23.260175","url":null,"abstract":"<p><strong>Introduction: </strong>Mississippi ranks among the lowest US states in health-related quality of life (HRQoL), with disparities most severe in rural and socioeconomically disadvantaged counties, particularly the Mississippi Delta. Understanding long-term spatial and temporal patterns is critical for equity-focused public health strategies. We aimed to describe geographic disparities in HRQoL across Mississippi's 82 counties from 2015 through 2025, identify persistent hot spots of poor health, assess convergence with national averages, and inform tailored interventions.</p><p><strong>Methods: </strong>We used County Health Rankings & Roadmaps data (2015-2025) to construct an annual principal component analysis-derived composite HRQoL index from Behavioral Risk Factor Surveillance System measures (poor/fair health, physically unhealthy days, mentally unhealthy days). Local indicators of spatial association (LISA), emerging hot spot analysis (EHSA), and a spatial autoregressive lag model with year fixed effects assessed clustering, spatiotemporal trends, and predictors.</p><p><strong>Results: </strong>We found persistent disadvantage in poor/fair health in Mississippi (stable gap of 6 to 7 percentage points above national averages) but recent convergence in physically unhealthy days and reversal in mentally unhealthy days (fewer days in disadvantaged subgroups). LISA identified a persistent hot spot in the Delta and contraction of cold spots along the Gulf Coast by 2025. EHSA showed sporadic and consecutive hot spots concentrated in the Delta. The spatial autoregressive lag model confirmed significant dependence (ρ = 0.13, P < .001), with adult smoking and uninsurance as leading modifiable predictors.</p><p><strong>Conclusion: </strong>Mississippi's HRQoL trajectory shows symptom-based improvements but persistent structural inequities and geographic disparities. Expanding smoke-free policies, strengthening primary care access, and increasing health insurance coverage are high-impact strategies to reduce disparities and advance health equity in the South.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"23 ","pages":"E42"},"PeriodicalIF":5.6,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13564472/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148931511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Potential Predictors and Mediators of Marijuana Use Among US Women: A Structural Equation Modeling Approach.","authors":"Elfreda Samman, Wah Wah Myint, Gabrielle Torres-Coley, Aishatu Yusuf","doi":"10.5888/pcd23.250495","DOIUrl":"10.5888/pcd23.250495","url":null,"abstract":"<p><strong>Introduction: </strong>Despite concerns about the impact of marijuana on women's health, studies exploring factors influencing use are limited. We examined predictors and mediators of marijuana use among US women.</p><p><strong>Methods: </strong>Structural equation modeling analyzed data on women (n = 16,081) from the 2023 National Survey on Drug Use and Health, with marijuana use as dependent variable. Sociodemographic variables and covariates included age, race and ethnicity, marital status, education, poverty status, county type, criminal history, and binge drinking. Potential mediators were past-year major depressive episode (PY-MDE); past-year use of illicit drugs, tobacco, and alcohol (PY-IDTA); poverty status; and body mass index.</p><p><strong>Results: </strong>Marijuana use was frequently reported among women aged 26 to 34 years (35.6%), those who were non-Hispanic White (60.8%), never been married (62.5%), with some college-level education (38.1%), living in large metropolitan areas (56.7%), those who did not binge drink (53.8%), without a criminal history (83.7%), with no PY-MDE (74.8%), no PY-IDTA (73.4%), those who were living above the poverty threshold (58.5%), and those with obesity (37.5%). Criminal history (β = 0.188) and binge drinking (β = 0.404) had positive direct effects on marijuana use; age (β =-0.065) and race (β = -0.027) had negative direct effects on use. PY-MDE mediated the relationships between age, race and ethnicity, marital status, county, past criminal history, binge drinking, and marijuana use (indirect βs = -0.008 to 0.080). PY-IDTA mediated the relationships between race and ethnicity, marital status, education, past criminal history, binge drinking, and marijuana use (indirect βs = -0.013 to 0.378), with all P values <.05.</p><p><strong>Conclusion: </strong>Results suggest potential predictors and mediators of marijuana use, highlighting the need for multi-strategy targeted interventions among US women.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"23 ","pages":"E38"},"PeriodicalIF":5.6,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13543778/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148889335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}