Impact of contextual factors on disparities in breast cancer risk and survival

描述(由申请人提供)：社会经济地位(SES)与乳腺癌风险和存活率的关系被很好地描述。SES较低的女性患乳腺癌的风险较低，而在这些群体中，某些种族/民族患乳腺癌后的存活率较低，特别是非裔美国人。然而，这些关联背后的原因仍然没有得到很好的理解，可能是因为之前的研究缺乏必要的多层次方法来联合检查个人和邻居(背景)特征。这项研究基于之前获得的访谈数据，建议通过将两项大型、多种族、基于人群的研究的乳腺癌病例和对照的社会经济、移民/文化适应和行为数据与有关社会经济、移民/文化适应以及社会和建筑环境的背景地理空间数据联系起来，来加强个人层面的数据。这些个体和背景变量将被用来检查它们对癌症风险和存活率的独立和联合影响，以及这些影响在多大程度上是由行为、社会和既定的乳腺癌风险或预后因素造成的。其具体目标是：1a)量化个人和背景水平的SES对种族/族裔群体内乳腺癌风险的独立和联合影响；1b)量化个人和背景水平的移民/文化因素对西班牙裔妇女乳腺癌风险的独立和联合影响；2a)量化个人和背景水平的SES对诊断阶段、乳腺癌特定存活率和种族/民族群体内的总体生存的独立和联合影响；2b)研究个人水平和背景水平的SES在多大程度上解释种族/民族的生存差异；以及2c)量化个人和背景层面的移民/文化适应因素对西班牙裔和亚裔美国妇女生存的独立和联合影响。旧金山湾区乳腺癌研究和北加州乳腺癌家庭登记处的乳腺癌病例(n=4205)和对照(n=3236)将根据确诊时的居住地(病例)或使用公共协议选择进入研究(对照)的基础进行地理编码，然后链接到基于区域人口的癌症登记处的临床数据、上下文地理空间数据以及来自医院和放射设施的数据，以便产生详细的多级数据集。这些分析结合了新的、最先进的分析方法，包括多水平回归分析、地理信息系统(GIS)和基于树的判别分析(递归划分)，将确定个人和背景措施与患乳腺癌风险最高和/或存活率最差的特定人群之间的联合影响。这些信息具有很强的转化潜力，通过告知针对特定人群的预防和干预努力，减少乳腺癌负担的差异，以减少发病率，确保早期发现，并提高存活率。公共卫生相关性：这项研究结合了新的、最先进的分析方法，应用于一个多水平的数据集，该数据集包括关于社会经济地位、移民/文化适应、行为因素的个人水平数据，并与关于社会经济地位、社区的移民/文化适应特征以及社会和建筑环境的背景水平数据相联系，这项研究将确定这些个人和背景措施与患乳腺癌风险最高和/或存活率最差的特定人群之间的联合影响。这些信息具有很强的转化潜力，通过告知针对特定人群的预防和干预努力，减少乳腺癌负担的差异，以减少发病率，确保早期发现，并提高存活率。

DESCRIPTION (provided by applicant): Associations of socioeconomic status (SES) with breast cancer risk and survival are well described. The risk of breast cancer is lower in women of lower SES, while survival after breast cancer in these groups is poorer for certain racial/ethnic groups, in particular African-Americans. However, the reasons behind these associations are still not well understood, likely because prior research lacked the necessary multilevel approach for joint examination of individual and neighborhood (contextual) characteristics. This study, based on previously obtained interview data, proposes to enhance individual-level socioeconomic, immigration/acculturation, and behavioral data on breast cancer cases and controls from two large, multiethnic, population-based studies by linking them to contextual geospatial data on SES, immigration/acculturation, and the social and built environment. These individual and contextual variables will be used to examine their independent and joint effects on cancer risk and survival, and the extent to which these effects are due to behavioral, social, and established breast cancer risk or prognostic factors. The specific aims are to: 1a) quantify the independent and joint effects of individual- and contextual-level SES on breast cancer risk within racial/ethnic groups; 1b) quantify the independent and joint effects of individual- and contextual-level immigration/acculturation factors on breast cancer risk among Hispanic women; 2a) quantify the independent and joint effects of individual- and contextual-level SES on stage at diagnosis, breast-cancer specific survival and overall survival within racial/ethnic groups; 2b) examine the extent to which individual-level and contextual-level SES explain racial/ethnic variation in survival; and 2c) quantify the independent and joint effects of individual- and contextual-level immigration/acculturation factors on survival among Hispanic and Asian-American women. Breast cancer cases (n=4205) and controls (n=3236) from the San Francisco Bay Area Breast Cancer Study and the Northern California Family Registry for Breast Cancer will be geocoded based on residence at diagnosis (cases), or selection into the study (controls) using a common protocol, and then linked to clinical data from the regional population-based cancer registry, to contextual geospatial data, and to data from hospital and radiation facilities, in order to produce a detailed, multilevel dataset. Incorporating novel, state-of-the-art analytic methods, including multilevel regression analyses, geographic information systems (GIS), and tree-based discriminant analyses (recursive partitioning), these analyses will identify joint effects among individual and contextual measures and specific populations at highest risk of developing breast cancer and/or having the worst survival. Such information has strong translational potential for reducing disparities in the burden of breast cancer by informing prevention and intervention efforts targeted toward specific populations for reducing incidence, ensuring early detection, and improving survival. PUBLIC HEALTH RELEVANCE: Incorporating novel, state-of-the art analytic methods, applied to a multilevel dataset comprising individual-level data on socioeconomic status, immigration/acculturation, behavioral factors, and linked to contextual-level data on socioeconomic status, immigration/acculturation features of neighborhoods, and social and built environment, this study will identify joint effects among these individual and contextual measures and specific populations at highest risk of developing breast cancer and/or having the worst survival. Such information has strong translational potential for reducing disparities in the burden of breast cancer by informing prevention and intervention efforts targeted toward specific populations for reducing incidence, ensuring early detection, and improving survival.