Preventing Chronic Disease最新文献

{"title":"Advancing Practices to Increase Access to Diabetes Self-Management Education and Support Through State Health Departments.","authors":"Melissa Bing, Robert Montierth, Bernadine Cabansay, Pollyanna Leung, Leslie Harrison","doi":"10.5888/pcd21.240255","DOIUrl":"https://doi.org/10.5888/pcd21.240255","url":null,"abstract":"","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"21 ","pages":"E93"},"PeriodicalIF":4.4,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142734059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social Determinants of Health and Health-Related Social Needs Among Adults With Chronic Diseases in the United States, Behavioral Risk Factor Surveillance System, 2022.","authors":"Karen Hacker, Craig W Thomas, Guixiang Zhao, J'Neka S Claxton, Paul Eke, Machell Town","doi":"10.5888/pcd21.240362","DOIUrl":"https://doi.org/10.5888/pcd21.240362","url":null,"abstract":"<p><strong>Introduction: </strong>The relationship between social determinants of health (SDOH) and health-related social needs (HRSN) and some chronic diseases at the population level is not well known. We sought to determine relationships between SDOH/HRSN and major chronic diseases among US adults by using data from the 2022 Behavioral Risk Factor Surveillance System (BRFSS).</p><p><strong>Methods: </strong>We used data from the new Social Determinants and Health Equity (SD/HE) module, conducted in 39 states, the District of Columbia, and 2 territories as part of the 2022 BRFSS. These data yielded a sample of 324,631 adult participants (aged ≥18 y). We examined 12 indicators of SDOH/HRSN and 9 chronic diseases. We calculated weighted prevalence estimates for each SDOH/HRSN measure for each chronic disease and associations between each SDOH/HRSN and each chronic disease.</p><p><strong>Results: </strong>Two-thirds of participants (66.3%) had 1 or more chronic diseases, and 59.4% reported 1 or more adverse SDOH/HRSN. Prevalence estimates for individual SDOH/HRSN measures were generally higher among participants with chronic diseases (except cancer). The more chronic diseases reported, the more likely participants were to have SDOH/HRSN (P < .05 for linear trend). The leading SDOH/HRSN measures associated with each chronic disease varied; however, the most common were mental stress, receiving food stamps or participating in the Supplemental Nutrition Assistance Program, cost as a barrier for needed medical care, and life dissatisfaction.</p><p><strong>Conclusion: </strong>From a treatment and prevention perspective, health care providers should consider the influence of SDOH/HRSN on people with or at risk for chronic diseases. Additionally, human service and public health systems in communities with high rates of chronic disease should consider these findings as they plan to mitigate adverse SDOH.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"21 ","pages":"E94"},"PeriodicalIF":4.4,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142734060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trajectory of Multiple Chronic Conditions and Associated Factors Among Noninstitutionalized Adults Aged 60 Years or Older in Southern Brazil.","authors":"Samara Christ Teixeira, Thaynã Ramos Flores, Mariana Otero Xavier, Bruno Pereira Nunes, Elaine Tomasi, Andrea Dâmaso Bertoldi, Flávio Fernando Demarco, Maria Cristina Gonzalez, Renata Moraes Bielemann","doi":"10.5888/pcd21.240082","DOIUrl":"https://doi.org/10.5888/pcd21.240082","url":null,"abstract":"<p><strong>Introduction: </strong>The prevalence of chronic conditions is increasing worldwide. The objective of this study was to describe the trajectory of the occurrence of multiple chronic conditions during 6 years of follow-up and investigate their association with demographic, socioeconomic, and behavioral health characteristics of older adults in Southern Brazil.</p><p><strong>Methods: </strong>We used data from a longitudinal study (the Como Vai? study) of noninstitutionalized adults aged 60 or older living in the urban area of Pelotas, Rio Grande do Sul. We assessed the number of chronic conditions based on a list of 24 conditions in 3 interviews, conducted in 2014, 2016-2017, and 2019-2020. We used group-based semiparametric modeling to identify groups of participants based on the number of chronic conditions. For associations with participant characteristics, we performed multinomial logistic regression and considered a low, moderate, and high burden of chronic conditions.</p><p><strong>Results: </strong>Of the 1,451 older adults in the cohort, 1,098 (75.7%) were included in analysis. Almost one-third (30.9%) had a low burden (2.3 conditions), more than half (52.0%) had a moderate burden (5.6 conditions), and 17.1% had a high burden (9.7 conditions). Men (relative risk [RR] = 6.10; 95% CI, 3.64-10.22), those aged 80 years or older (RR = 2.33; 95% CI, 1.15-4.72), those with no education (RR= 4.78; 95% CI, 2.19-10.45), and former smokers (RR = 1.53; 95% CI, 0.96-2.44) had a higher risk of being classified in the high-burden group than in the low-burden group.</p><p><strong>Conclusion: </strong>Most older adults belonged to the group with a moderate number of chronic conditions. Several sociodemographic characteristics were associated with belonging to the trajectory with a greater number of conditions.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"21 ","pages":"E91"},"PeriodicalIF":4.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuity of Care and Lifestyle Intervention Programs for Spanish-Speaking Immigrants Without Health Insurance at a Free Clinic in Rhode Island.","authors":"Chilsea Wang, Jocelyn Yang, Julia Testa, Muneet Gill, Morgan Leonard, Anne S De Groot","doi":"10.5888/pcd21.240136","DOIUrl":"https://doi.org/10.5888/pcd21.240136","url":null,"abstract":"<p><strong>Introduction: </strong>We conducted a retrospective cohort study to evaluate changes in metabolic biomarkers among participants in Bridging the [Health Equity] Gap (BTG), a free program run by Clínica Esperanza/Hope Clinic (CEHC) for Spanish-speaking immigrants without health insurance in Rhode Island.</p><p><strong>Methods: </strong>From July 2019 through June 2021, 471 people volunteered to participate in the BTG program. Participants enrolled in lifestyle change classes and visited quarterly with health care providers. We reviewed medical records to collect data on blood glucose, total cholesterol, hemoglobin A_1c (HbA_1c), and systolic and diastolic blood pressure at baseline and at 6, 12, 18, and 21 months after enrollment. We used paired t tests to identify changes in measurements and conducted a regression analysis to analyze trends in longitudinal patient outcomes.</p><p><strong>Results: </strong>From baseline to 6-month follow-up, we observed significant decreases in all participants' mean HbA_1c (-0.71%), systolic (-5 mm Hg), and diastolic blood pressure (-2 mm Hg). At 12 months, significant decreases in mean HbA_1c persisted among participants with diabetes and prediabetes (-1.07%). At 12 months, participants with mean systolic blood pressure >120 mm Hg also had significant decreases in mean systolic blood pressure (-9 mm Hg), and patients with diastolic blood pressure >80 mm Hg had significant decreases in mean diastolic blood pressure (-9 mm Hg). Local population-level surges in COVID-19 due to Delta and Omicron variants were associated with increases in HbA_1c and blood glucose measurements above trendlines.</p><p><strong>Conclusion: </strong>The BTG program demonstrated resilience in supporting improvement in the metabolic biomarkers of participants, despite disruptions caused by the COVID-19 pandemic, the continued engagement of participants in self-care despite limited health care access, and underscores the positive role of free clinics among low-income, Spanish-speaking immigrants.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"21 ","pages":"E92"},"PeriodicalIF":4.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Telemedicine Use Among Adults With and Without Diagnosed Prediabetes or Diabetes, National Health Interview Survey, United States, 2021 and 2022.","authors":"Ibrahim Zaganjor, Ryan Saelee, Stephen Onufrak, Yoshihisa Miyamoto, Alain K Koyama, Fang Xu, Kai McKeever Bullard, Meda E Pavkov","doi":"10.5888/pcd21.240229","DOIUrl":"10.5888/pcd21.240229","url":null,"abstract":"<p><p>We analyzed 2021 and 2022 National Health Interview Survey data to describe the prevalence of past 12-month telemedicine use among US adults with no prediabetes or diabetes diagnosis, diagnosed prediabetes, and diagnosed diabetes. In 2021 and 2022, telemedicine use prevalence was 34.1% and 28.2% among adults without diagnosed diabetes or prediabetes, 47.6% and 37.6% among adults with prediabetes, and 52.8% and 39.4% among adults with diabetes, respectively. Differences in telemedicine use were identified by region, urbanicity, insurance status, and education among adults with prediabetes or diabetes. Findings suggest that telemedicine use can be improved among select populations with prediabetes or diabetes.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"21 ","pages":"E90"},"PeriodicalIF":4.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567504/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142632385","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":"Racial and Ethnic Disparities in Perceived Health Status Among Patients With Cardiovascular Disease.","authors":"Marjan Zakeri, Lincy S Lal, Susan M Abughosh, Shubhada Sansgiry, E James Essien, Sujit S Sansgiry","doi":"10.5888/pcd21.240264","DOIUrl":"10.5888/pcd21.240264","url":null,"abstract":"<p><strong>Introduction: </strong>Understanding health outcomes among people with cardiovascular disease (CVD) is crucial for improving treatment strategies and patient quality of life. This study investigated racial and ethnic disparities in perceived health status among non-Hispanic Black, Hispanic, and non-Hispanic White adults with CVD.</p><p><strong>Methods: </strong>The study had a retrospective cross-sectional design and used data from the Medical Expenditure Panel Survey spanning 8 calendar years (2014-2021). The study population consisted of adults diagnosed with various CVDs. We used ordinal logistic regression models adjusted for demographic and socioeconomic characteristics, CVD severity, comorbidities, and health care expenditures to assess racial and ethnic differences in perceived health status.</p><p><strong>Results: </strong>Among the 11,715 (weighted frequency, 15,431,283) adults with CVD, we observed significant differences in perceived health status across racial and ethnic cohorts. The unadjusted analysis showed that non-Hispanic Black adults had significantly higher odds than non-Hispanic White adults of perceiving their health as poorer (odds ratio [OR]= 1.89; 95% CI, 1.74-2.07; P < .001), with a similar observation among Hispanic adults (OR = 2.05; 95% CI, 1.85-2.26; P < .001). Although female sex, higher education, and better income had protective effects on perceived health status independent of race, we found significant racial and ethnic differences in the effect of older age, physical and cognitive limitations, and health insurance status on perceived health status.</p><p><strong>Conclusion: </strong>This study revealed substantial racial disparities in perceived health status among adults with CVD, with notable differences in the effects of predictive factors. Addressing these disparities requires targeted interventions to improve health care access and enhance socioeconomic conditions tailored to the needs and experiences of racial and ethnic populations.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"21 ","pages":"E89"},"PeriodicalIF":4.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567505/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142632384","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":"Small Area Estimation of Subdistrict Diabetes Prevalence in the US Virgin Islands, 2021-2022.","authors":"Katie Labgold, John Orr, Lyña Fredericks, David Delgado, Joseph Roth, Esther M Ellis","doi":"10.5888/pcd21.240205","DOIUrl":"10.5888/pcd21.240205","url":null,"abstract":"","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"21 ","pages":"E88"},"PeriodicalIF":4.4,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567509/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142604627","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":"Bridging Public Health Research and State-Level Policy: The Texas Research-to-Policy Collaboration Project.","authors":"Deanna M Hoelscher, Alexandra van den Berg, Amelia Roebuck, Shelby Flores-Thorpe, Kathleen Manuel, Tiffni Menendez, Christine Jovanovic, Aliya Hussaini, John T Menchaca, Elizabeth Long, D Max Crowley, J Taylor Scott","doi":"10.5888/pcd21.240171","DOIUrl":"10.5888/pcd21.240171","url":null,"abstract":"<p><strong>Purpose and objectives: </strong>Significant barriers to the implementation of evidence-based policy exist. Establishing an infrastructure and resources to support this process at the state level can accelerate the translation of research into practice. This study describes the adaptation and initial evaluation of the Texas Research-to-Policy Collaboration (TX RPC) Project, focusing on the adaptation process, legislative public health policy priorities, and baseline researcher policy knowledge and self-efficacy.</p><p><strong>Intervention approach: </strong>The federal Research-to-Policy Collaboration (RPC) method was adapted to the Texas legislative process in 2020. Policymakers and public health researchers were recruited using direct outreach and referrals. Legislators or their aides were interviewed to determine health policy needs, which directed the development of legislator resources, webinars, and recruitment of additional public health researchers with specific expertise. Researchers were trained to facilitate communication with policymakers, and TX RPC Project staff facilitated legislator and researcher meetings to provide data and policy input.</p><p><strong>Evaluation methods: </strong>Baseline surveys were completed with legislators to assess the use of health researchers in policy. Surveys were also administered before training to researchers assessing self-efficacy, knowledge, and training needs. Qualitative data from the legislator interviews were analyzed using inductive and deductive approaches. Quantitative survey data were analyzed using descriptive statistics for scales and individual survey items.</p><p><strong>Results: </strong>Legislative offices (n = 21) identified health care access, mental health, and health disparities as key health issues. Legislators reported that health data were important but did not actively involve researchers in legislation. Researchers (n = 73) reported that policy informed their work but had low engagement with legislators. Researcher training surveys indicated lower policy self-efficacy and knowledge and the need for additional training.</p><p><strong>Implications for public health: </strong>Adaptation of the RPC model for state-level health policy is feasible but necessitates logistical changes based on the unique legislative body. Researchers need training and resources to engage with policymakers.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"21 ","pages":"E87"},"PeriodicalIF":4.4,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567515/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142604327","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":"Demonstrated Progress and Future Promise of Chronic Disease Data Modernization.","authors":"Kathryn Turner, Katherine H Hohman","doi":"10.5888/pcd21.240396","DOIUrl":"10.5888/pcd21.240396","url":null,"abstract":"","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"21 ","pages":"E86"},"PeriodicalIF":4.4,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142559315","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":"Geospatial Hot Spots and Cold Spots in US Cancer Disparities and Associated Risk Factors, 2004-2008 to 2014-2018.","authors":"L Raymond Guo, M Courtney Hughes, Margaret E Wright, Alyssa H Harris, Meredith C Osias","doi":"10.5888/pcd21.240046","DOIUrl":"10.5888/pcd21.240046","url":null,"abstract":"<p><strong>Introduction: </strong>Despite declining cancer death rates in the US, cancer remains the second deadliest disease and disparities persist. Although research has focused on identifying risk factors for cancer deaths and associated disparities, few studies have examined how these relationships vary over time and space. The primary objective of this study was to identify cancer mortality hot spots and cold spots - areas where cancer death rates decreased less than or more than neighboring areas over time. A secondary objective was to identify risk factors of cancer mortality hot spots and cold spots.</p><p><strong>Methods: </strong>We analyzed county-level cancer death rates from 2004 through 2008 and 2014 through 2018, exploring disparities in changes over time for socioeconomic and demographic variables. We used hot spot analysis to identify areas with larger decreases (cold spots) and smaller decreases (hot spots) in cancer death rates and random forest machine learning analysis to assess the relative importance of risk factors associated with hot spots and cold spots. We mapped spatial clustering areas.</p><p><strong>Results: </strong>Geospatial analysis showed hot spots predominantly in the Plains states and Midwest and cold spots in the Southeast, Northeast, 2 Mountain West states (Utah and Idaho), and a portion of Texas. Factors with the strongest influence on hot spots and cold spots were unemployment, preventable hospital stays, mammography screening, and high school education.</p><p><strong>Conclusion: </strong>Geospatial disparities in changes in cancer death rates point out the critical role of access to care, socioeconomic position, and health behaviors in persistent cancer mortality disparities. Study results provide insights for interventions and policies that focus on addressing health care access and social determinants of health.</p>","PeriodicalId":51273,"journal":{"name":"Preventing Chronic Disease","volume":"21 ","pages":"E84"},"PeriodicalIF":4.4,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567514/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142559316","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}