Impact of social and built environments on health-related quality of life for cancer survivors

社会和建筑环境对癌症幸存者健康相关生活质量的影响

• 批准号: 9024189
• 负责人: Salma Shariff-Marco
• 金额: $ 7.25万
• 依托单位: CANCER PREVENTION INSTIT OF CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-02-01 至 2018-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9024189
• 关键词: Accounting; Address; Affect; Age; Area; Behavior; Behavioral; Breast; Breast Cancer Patient; Businesses; California; Cancer Patient; Cancer Survivor; Cancer Survivorship; Caring; Censuses; Characteristics; Cities; Clinical; Collaborations; Colorectal; Communities; Commuting; Comorbidity; County; Critical Care; Data; Data Set; Diet; Education; Effectiveness; Employment; Ensure; Environment; Environmental Exposure; Ethnic Origin; Evaluation; Foundations; Future; Gender; Grant; Gynecologic; Health; Health Food; Health behavior; Healthcare; Healthy Eating; Housing; Immigration; Individual; Information Systems; Intervention; Interview; Life; Linear Regressions; Link; Low income; Malignant neoplasm of prostate; Marketing; Measures; Mental Health; Meta-Analysis; Minority; Modeling; Multiple Cancer Sites; Neighborhoods; Non-Hodgkin' s Lymphoma; Obesity; Outcome; Overweight; Pathway interactions; Patients; Physical activity; Population Characteristics; Population Density; Positioning Attribute; Poverty; Prognostic Factor; Prostate; Psyche structure; Psychosocial Deprivation; Quality of life; Race; Registries; Resources; SF-12; SF-36; San Francisco; Services; Shapes; Site; Smoking; Social Environment; Social Functioning; Social Network; Social support; Socioeconomic Status; Stress; Stress and Coping; Survivors; Symptoms; Testing; Time; Translating; Transportation; Wellness Program; Work; base; built environment; cancer care; cancer diagnosis; cancer site; cohesion; cohort; contextual factors; cost; density; deprivation; design; ethnic diversity; ethnic minority population; experience; farmer; follow-up; food environment; health disparity; health related quality of life; improved; improved outcome; low socioeconomic status; malignant breast neoplasm; man; physical conditioning; population based; psychosocial; public health relevance; racial and ethnic; racial and ethnic disparities; segregation; social; socioeconomics; survivorship; trafficking; walkability

 DESCRIPTION (provided by applicant): Neighborhoods have been shown to be a critical foundation for shaping individuals' opportunities for achieving optimal health. As the number of cancer survivors continues to increase, with over 13 million in the U.S. currently, understanding factors that improve health-related quality of life (HRQOL) after cancer diagnosis is critical. Unless we identify and address the relevant contextual factors, interventions that only target individual factors are likely to have limited effectiveness. However, only three studies have considered neighborhood factors, despite that neighborhoods have been shown to influence health outcomes through a number of pathways--environmental exposures, material deprivation, psychosocial mechanisms, health behaviors, and access to resources. Therefore, we propose to leverage and pool individual-level data on sociodemographic, clinical, social, and behavioral factors from three existing cancer survivorship studies and merge them with neighborhood data. Specifically, we aim to (1) examine the associations between a comprehensive suite of social and built environment features and HRQOL, (a) adjusting for important covariates (e.g., clinical, demographic, social and behavioral factors) and (b) evaluating whether these associations vary by race/ethnicity, age, or gender, and (2) assess racial/ethnic disparities in HRQOL and evaluate whether these disparities are explained by clinical, demographic, social and behavioral factors, neighborhood factors, or a combination of them. To achieve these aims, with harmonized data across three California population-based studies (n=2,563, 46% minority)-Assessment of Patients' Experience of Cancer Care (APECC), Experiences of Care and Health Outcomes of survivors of Non-Hodgkin's Lymphoma (ECHOS-NHL), and Follow-up Care Use among Survivors (FOCUS)-we will geocode address at interview and merge the individual-level data with our social (e.g., socioeconomic, racial/ethnic composition, immigration) and built (e.g., population density, street connectivity, commuting, amenities, food environment) environment data. The main HRQOL outcomes will include physical and mental component summary scores. Linear regression models will be used to estimate unadjusted and adjusted associations between neighborhood features and the two HRQOL outcomes. Further, we will document racial/ethnic disparities in HRQOL and evaluate whether neighborhood features explain these disparities. This efficient study will be powered to detect significant neighborhoods effects across all of the cancer sites, as well as for 5 specific sites -breast, colorectal, gynecologic, NHL, and prostate. Our findings will provide the preliminary evidence for associations between the built and social environment and HRQOL and contribute significantly to our understanding of which neighborhood features influence HRQOL. Our collaboration with the Shanti Project will ensure that our study will meaningfully inform the design of multilevel interventions that not only account for individual factors that contribute to HRQOL, but also the context through which those individual factors are shaped.

 描述（由申请人提供）：事实证明，社区是塑造个人实现最佳健康机会的关键基础。随着癌症幸存者数量持续增加，目前美国癌症幸存者已超过 1300 万，了解癌症诊断后改善健康相关生活质量 (HRQOL) 的因素至关重要。除非我们识别并解决相关的背景因素，否则仅针对个体因素的干预措施可能效果有限。然而，只有三项研究考虑了邻里因素，尽管邻里已被证明可以通过多种途径影响健康结果——环境暴露、物质匮乏、心理社会机制、健康行为和资源获取。因此，我们建议利用和汇集来自三项现有癌症生存研究的社会人口学、临床、社会和行为因素的个人数据，并将其与社区数据合并。具体来说，我们的目标是 (1) 检查一套全面的社会和建筑环境特征与 HRQOL 之间的关联，(a) 调整重要的协变量（例如临床、人口统计、社会和行为因素），(b) 评估这些关联是否因种族/民族、年龄或性别而变化，以及 (2) 评估 HRQOL 中的种族/民族差异，并评估这些差异是否由以下因素解释： 临床、人口、社会和行为因素、邻里因素或它们的组合。为了实现这些目标，利用三项基于加州人口的研究（n=2,563，46%少数）的统一数据——患者癌症护理体验评估 (APECC)、非霍奇金淋巴瘤幸存者的护理体验和健康结果 (ECHOS-NHL) 以及幸存者的后续护理使用情况 (FOCUS)——我们将在访谈时对地址进行地理编码，并将个人层面的数据与我们的社交数据合并 （例如，社会经济、种族/民族构成、移民）和建筑（例如，人口密度、街道连通性、通勤、便利设施、食品环境）环境数据。主要 HRQOL 结果将包括身体和心理部分的总结分数。线性回归模型将用于估计邻域特征与两个 HRQOL 结果之间未调整和调整的关联。此外，我们将记录 HRQOL 中的种族/民族差异，并评估邻里特征是否可以解释这些差异。这项高效的研究将有助于发现重要的社区 对所有癌症部位以及 5 个特定部位（乳腺癌、结直肠癌、妇科、NHL 和前列腺）都有影响。我们的研究结果将为建筑环境和社会环境与 HRQOL 之间的关联提供初步证据，并有助于我们了解哪些社区特征影响 HRQOL。我们与 Shanti 项目的合作将确保我们的研究将为多层次干预措施的设计提供有意义的信息，这些干预措施不仅考虑有助于 HRQOL 的个人因素，而且还考虑形成这些个人因素的背景。