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Health Disparities in Alcohol Use and Other Risk Behaviors after the Onset of Cancers and Cardiovascular Disease-Related Conditions

Health Disparities in Alcohol Use and Other Risk Behaviors after the Onset of Cancers and Cardiovascular Disease-Related Conditions
癌症和心血管疾病相关病症发病后饮酒和其他危险行为的健康差异
批准号:
10056011
负责人:
William C Kerr
金额:
$25.3万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
1981
资助国家:
美国
项目状态:
未结题
起止时间:
1981-07-01 至 2026-02-28

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中文摘要
翻译
摘要:癌症发病后饮酒和其他危险行为的健康差异 和心血管疾病相关疾病 癌症发病后饮酒和其他危险行为的拟议健康差异, 心血管疾病相关疾病是2016-2020年健康差异项目的延续 关注酒精对健康的影响。我们将注意力转移到饮酒模式和其他健康问题上, 患有糖尿病,高血压, 心脏/冠状动脉问题和癌症以及这些病症中多发病。继续进行 在这些情况下大量饮酒会增加发病率和死亡率, 当与其他健康风险行为(如肥胖、缺乏运动和吸烟)结合时, 和其他毒品使用),迫切需要采取多方面的干预措施来解决这些问题。然而,很少有研究 对特定健康状况的诊断或治疗后的健康行为的调查集中在 饮酒或危险饮酒与其他危险行为的聚集。此外,几乎没有记录 关于酒精在疾病风险中的作用的人口知识,这也可能影响关于 喝酒为了增加改进干预措施的知识基础,拟议的研究将解决三个问题: 明确的目标。首先,分析癌症、高血压、糖尿病、 使用2015年,2020年和2024年NAS的心脏问题和酒精引起的健康危害将评估 条件发作对饮酒模式的影响以及持续危险饮酒的相关性。第二、 检查当前的饮酒模式,其他生活方式风险因素(体力活动和 超重/肥胖)和物质使用(烟草、大麻和非法药物), 陈述的条件和其中的多发病率将确定这些行为之间的聚类, 注意性别、年龄、种族/族裔和社会经济地位界定的群体之间的差异。这些 分析将利用2010-2020 NAS和2015-2020全国药物使用和健康调查。第三、 关于酒精在癌症和其他健康状况中的作用的知识的预测因素的评价 利用2020年NAS和国家癌症研究所的2017年健康信息, 国家趋势调查,将确定与准确了解酒精相关的群体和特征 作为每种疾病的风险因素以及与准确知识相关的信息来源。每个目标 将评估种族/民族和社会经济地位的差异以及与性别和年龄有关的差异。 先进的流行病学模型,包括广义估计方程模型,倾向评分 加权和潜在类别分析将酌情使用。 .
英文摘要
ABSTRACT: Health Disparities in Alcohol Use and Other Risk Behaviors after the Onset of Cancers and Cardiovascular Disease-Related Condition The proposed Health Disparities in Alcohol Use and Other Risk Behaviors after the Onset of Cancers and Cardiovascular Disease-Related Condition is a continuation of the 2016-2020 Health Disparities Project focusing on alcohol's role in health outcomes. We shift our attention to patterns of drinking and other health risk behaviors among individuals with diagnosed health conditions focusing on diabetes, hypertension, heart/coronary problem, and cancer as well as multimorbidity among these conditions. As continued heavy drinking with these conditions carries risks for increased morbidity and mortality, which are likely to be further elevated when combined with other health risk behaviors (such as obesity, physical inactivity and tobacco and other drug use), there is a critical need for multifaceted interventions to address these. However, few studies investigating health behaviors following diagnosis or treatment for specific health conditions have focused on alcohol use or the clustering of risky drinking with other risk behaviors. Furthermore, little has been documented regarding population knowledge of alcohol's role in disease risk, which may also influence decisions about drinking. To increase the knowledge base for improved interventions, the proposed research will address three specific aims. First, analyses of drinking patterns after diagnosis of cancers, hypertension, diabetes, heart problems, and alcohol-attributed health harms using the 2015, 2020 and 2024 NAS will evaluate the impacts of condition onset on drinking patterns and the correlates of continued risky drinking. Second, examination of current drinking patterns, other lifestyle risk factors (physical activity and overweight/obesity), and substance use (tobacco, marijuana, and illicit drugs) in individuals with above- stated conditions and multi-morbidity among them will identify the clustering among these behaviors with attention to differences across gender, age, race/ethnicity and socioeconomic status defined groups. These analyses will utilize the 2010-2020 NAS and 2015-2020 National Surveys on Drug Use and Health. Third, evaluation of the predictors of knowledge regarding alcohol's role in cancers and other health conditions and disparities in these, utilizing the 2020 NAS and the National Cancer Institute's 2017 Health Information National Trends Survey, will identify groups and characteristics associated with accurate knowledge of alcohol as a risk factor for each condition and the sources of information associated with accurate knowledge. Each Aim will evaluate racial/ethnic and socioeconomic status disparities as well as gender and age-related differences. Advanced epidemiologic models including generalized estimating equation modeling, propensity score weighting, and latent class analysis will be utilized as appropriate. .
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  • 财政年份:
    2019
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    8918392
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海外基金