Impact of public housing assistance on modifiable cancer risk factors in adults

描述（由申请人提供）：尽管在过去二十年中癌症死亡率有所改善，但种族、民族和社会经济地位（SES）亚群之间仍存在显著差异。住房已被确定为一般健康差异和具体癌症相关差异的一个重要社会决定因素。公共住房援助旨在提高社会经济地位最低家庭的住房负担能力和质量。因此，PH代表了一种干预措施，以改善住房作为健康的一个社会决定因素。然而，很少有研究探讨生活在PH对健康相关结果的影响。此外，一些研究人员已经提出了PH影响健康的途径，但尚未进行经验测试。这项拟议的研究将使用1999 - 2013年收入动态小组研究（PSID）收集的数据，以估计生活在PH中对62岁以下成年人四个主要可改变的癌症风险因素（吸烟，饮酒，缺乏运动和超重/肥胖）的影响。PSID提供了一个独特的机会来研究PH的影响，因为它是一个具有全国代表性的纵向调查，涉及广泛的人口，家庭，住房，经济，就业，社会和健康变量;邻里水平的变量也将使用地理编码联系起来。治疗组将仅包括在研究期间进入PH的应答者（预期n = 550）。对照组将仅限于有收入资格获得PH的租房者（预计n = 1650）。我们将倾向评分方法应用于PSID中丰富的基线特征集，以帮助控制观察数据中固有的选择偏倚。将根据估计的倾向评分计算治疗权重的逆概率，并用于logistic回归模型，以估计基线后2、4和6年时每个风险因素的平均治疗效应。将开发多种中介模型，以检查PH通过个人水平的中介（例如，非住房收入、压力、住宅稳定性）和社区级调解员（例如，附近的SES，进入超市，步行）。研究结果将用于帮助澄清生活在PH中是否会改善或消除癌症的可改变风险因素。重要的是，通过这些影响发生的途径获得的信息可以为未来的住房和公共卫生研究，实践和政策提供信息。

DESCRIPTION (provided by applicant): Despite improvements in cancer mortality in the past two decades, significant disparities persist among racial, ethnic, and socioeconomic status (SES) subpopulations. Housing has been identified as an important social determinant for health disparities in general and cancer-related disparities specifically. Public housing (PH) assistance aims to improve housing affordability and quality for the lowest-SES households. Thus, PH represents an intervention to improve housing as a social determinant of health. However, few studies have examined the effects of living in PH on health-related outcomes. Additionally, several researchers have proposed pathways through which PH influences health but have not tested them empirically. The proposed study will use data collected from 1999-2013 in the Panel Study of Income Dynamics (PSID) to estimate the effect of living in PH on four leading modifiable risk factors for cancer (smoking, alcohol use, physical inactivity, and overweight/obesity) in adults <62 years of age. The PSID offers a unique opportunity to examine the effects of PH because it is a nationally representative, longitudinal survey with a wide range of demographic, household, housing, economic, employment, social, and health variables; neighborhood-level variables will also be linked using geocodes. The treatment group will include only respondents who move into PH during the study period (expected n=550). The comparison group will be limited to renters who are income-eligible for PH (expected n=1650). We will apply propensity score methods to the rich set of baseline characteristics available in the PSID to help control for selection bias inherent in observational data. Inverse probability of treatment weights will be calculated from estimated propensity scores and used in logistic regression models to estimate average treatment effects for each risk factor at 2, 4, and 6 years after baseline. Multiple mediation models will be developed to examine the extent to which PH influences modifiable cancer risk factors through individual-level mediators (e.g., non-housing income, stress, residential stability) and neighborhood-level mediators (e.g., neighborhood SES, access to supermarkets, walkability). Study results will be used to help clarify whether living in PH improves or worsens modifiable risk factors for cancer. Importantly, information obtained about pathways through which these effects occur can inform future housing and public health research, practice, and policy.