A dataset for the study of the social determinants of health.

用于研究健康的社会决定因素的数据集。

• 批准号: 7941923
• 负责人: Peter A Muennig
• 金额: $ 39.08万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-28 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7941923
• 关键词: Address; Adoption; Adult; African American; Attention; Attitude; Awareness; Back; Belief; Categories; Cause of Death; Cessation of life; Childhood; Communities; Contracts; Cross-Sectional Studies; Data; Data Set; Development; Disadvantaged; Discipline; Education; Elderly; Elements; Ensure; Epidemiologic Studies; Ethnic Origin; Etiology; Family Relationship; Feeling; Friends; Goals; Grant; Health; Health Insurance; Health Sciences; Hispanics; Income; Individual; Lead; Life; Life Cycle Stages; Life Expectancy; Link; Measures; Mediating; Medical; Methods; Minority; National Center on Minority Health and Health Disparities; Not Hispanic or Latino; Occupational; Occupations; Outcome; Persons; Plant Roots; Policies; Population; Poverty; Premature Mortality; Process; Psychological Stress; Psychosocial Deprivation; Psychosocial Factor; Race; Relative (related person); Research; Research Personnel; Resources; Risk Factors; Running; Schools; Scientific Advances and Accomplishments; Scientist; Services; Social Network; Social Sciences; Socioeconomic Status; Solutions; Stress; Student Dropouts; Surveys; System; Techniques; Time; TimeLine; Translating; Transportation; Trust; Wages; Work; base; civil society; comparison group; cost; deprivation; follow-up; health disparity; high school; improved; indexing; interdisciplinary collaboration; low socioeconomic status; markov model; mortality; novel; policy implication; prospective; psychologic; psychosocial; social; social capital; social deprivation; social health determinants; success; tool; working group

DESCRIPTION (provided by applicant): We propose a method for answering critical questions concerning the social determinants of health and health disparities by linking 30 years of comprehensive, nationally-representative sociological data to prospective mortality data containing specific causes of death. The problem: African-Americans and persons of low socio-economic status (SES) tend to have less access to social resources, such as good schools, than do whites and persons of high SES, respectively. Over time, disparities in access to such social resources translate into health disparities. For instance, disparities in access to quality education between groups results in occupational disparities that lead to income disparities. Those with less education and income have not only lower access to health insurance, but also less access to banking services, transportation, and modes of democratic engagement, as well as a host of other social systems. Researchers and thinkers dating back to Hippocrates have observed that such social deprivations lead to health disparities, but it was long thought that health disparities primarily arose from lower access to lifesaving material goods. In the twentieth century, researchers turned their attention to the association between social deprivations and psychosocial possesses as additional causes of health disparities. For instance, lower social capital (e.g., trust, group participation), social ties (e.g., friends and family relationships), and harmful psychological states (e.g., stress, pessimism) have been identified as contributors to health disparities by race, ethnicity, and SES. Despite the importance of understanding the root social causes of health disparities, however, a prospective, comprehensive sociomedical dataset has never been developed. Our proposed solution. Scientists do have access to datasets that allow for the description of health disparities. These datasets consist of a number of important medical risk factors and outcomes alongside information about the subjects' income and educational attainment. However, the datasets do not permit a deeper analysis of social and psychological causes of these disparities. Such a dataset would not only need to contain more comprehensive questions about the subjects' childhood and adult SES, they would also require questions about subjects' social networks, thought, feelings, attitudes, beliefs, and participation in civil society. In short, scientists require a dataset that allows exploration of putative social and psychological causes of health disparities. Clearly, development of an interdisciplinary, nationally-representative, prospective dataset containing robust measures in social and psychological domains would cost millions of dollars and would require many years of follow-up. Our proposal provides a rapid and highly cost-effective shortcut that will produce an extremely robust dataset with outstanding follow-up and oversampling of minority populations. Specifically, we propose to link the 1977-2007 General Social Survey (GSS), a multiple-year, cross-sectional survey rich in health and sociological variables, to National Death Index (NDI) data through 2008. This dataset will advance social epidemiologic studies of health disparities beyond mere identification and description to a deeper understanding of the underlying mechanisms. This will usher in highly targeted policies to address "health gaps" between groups. To catalyze the utility and the widespread use of this dataset, we will 1) release the dataset to the wider research community, 2) convene a group of leading transdisciplinary experts in order to troubleshoot and disseminate the GSS-NDI data, and 3) develop a set of useful research tools that will facilitate the adoption and reach of the GSS-NDI. These tools include a means for defining multi-dimensional concepts such as social capital, a means for adjusting for between group differences in the interpretation of qualitative questions (i.e., African Americans may be more likely than whites to see the question, "People treat me fairly," as having a racial component), and, finally, a means for translating mortality differences into life expectancy differences so that the policy implications of researchers' findings can be more easily understood. In short, our project will create the prospective sociomedical dataset that has been missing in the health sciences, a dataset capable of greatly advancing our understanding of the non-medical determinants of health and their relationship to health disparities. We will create this dataset in a fraction of the time and at a fraction of the cost of generating a prospective sociomedical dataset from scratch. Finally, we have done preliminary work to both ensure its success and to ensure that our project is ready for rollout. We forward this proposal under the RC2 (GO) mechanism to the National Center on Minority Health and Health Disparities' Social Determinants of Health Initiative. We propose to link over thirty years of data from the longest running social science dataset to mortality data, creating the first major prospective sociomedical dataset. This dataset will greatly advance scientific understanding of the social causation of disease and health disparities.

描述（由申请人提供）：我们提出了一种方法，通过将 30 年全面的、具有全国代表性的社会学数据与包含特定死因的预期死亡率数据联系起来，回答有关健康和健康差异的社会决定因素的关键问题。问题是：非洲裔美国人和社会经济地位低的人往往比白人和社会经济地位高的人获得社会资源（例如好学校）的机会更少。随着时间的推移，获得此类社会资源的差异会转化为健康差异。例如，群体之间获得优质教育的机会差异导致职业差异，进而导致收入差异。受教育程度和收入较低的人不仅获得医疗保险的机会较少，而且获得银行服务、交通、民主参与方式以及许多其他社会制度的机会也较少。自希波克拉底以来的研究人员和思想家就观察到，这种社会剥夺会导致健康差距，但长期以来，人们一直认为健康差距主要是由于获得救生物质产品的机会较少造成的。二十世纪，研究人员将注意力转向社会剥夺和社会心理占有之间的关联，将其视为健康差异的其他原因。例如，较低的社会资本（例如信任、群体参与）、社会关系（例如朋友和家庭关系）和有害的心理状态（例如压力、悲观主义）已被确定为造成种族、民族和社会经济地位健康差异的因素。然而，尽管了解健康差异的根本社会原因很重要，但尚未开发出前瞻性的、全面的社会医学数据集。我们提出的解决方案。科学家确实可以访问可以描述健康差异的数据集。这些数据集包含许多重要的医疗风险因素和结果以及有关受试者收入和教育程度的信息。然而，这些数据集不允许对这些差异的社会和心理原因进行更深入的分析。这样的数据集不仅需要包含有关受试者童年和成人社会经济地位的更全面的问题，还需要有关受试者的社交网络、思想、感受、态度、信仰和公民社会参与的问题。简而言之，科学家需要一个数据集来探索健康差异的假定社会和心理原因。显然，开发一个跨学科的、具有全国代表性的前瞻性数据集，其中包含社会和心理领域的强有力的衡量标准，将花费数百万美元，并且需要多年的后续工作。我们的建议提供了一种快速且极具成本效益的捷径，将产生一个极其强大的数据集，并对少数群体进行出色的后续和过采样。具体来说，我们建议将 1977-2007 年综合社会调查 (GSS)（一项富含健康和社会学变量的多年期横断面调查）与 2008 年全国死亡指数 (NDI) 数据联系起来。该数据集将推动健康差异的社会流行病学研究，超越单纯的识别和描述，从而更深入地了解潜在机制。这将带来高度针对性的政策来解决群体之间的“健康差距”。为了促进该数据集的实用性和广泛使用，我们将 1) 向更广泛的研究界发布该数据集，2) 召集一组领先的跨学科专家来解决和传播 GSS-NDI 数据，3) 开发一套有用的研究工具，以促进 GSS-NDI 的采用和覆盖。这些工具包括定义社会资本等多维概念的方法，调整定性问题解释中群体差异的方法（即，非裔美国人可能比白人更有可能将“人们公平对待我”这个问题视为具有种族成分），最后，将死亡率差异转化为预期寿命差异的方法，以便更容易理解研究结果的政策含义。简而言之，我们的项目将创建健康科学中缺失的前瞻性社会医学数据集，该数据集能够极大地增进我们对健康的非医学决定因素及其与健康差异的关系的理解。我们将花费从头开始生成预期社会医学数据集所需的时间和成本的一小部分来创建此数据集。最后，我们已经完成了初步工作，以确保其成功并确保我们的项目已准备好推出。我们根据 RC2 (GO) 机制将此提案转发给国家少数民族健康和健康差异中心的健康社会决定因素倡议。我们建议将运行时间最长的社会科学数据集中三十多年的数据与死亡率数据联系起来，创建第一个主要的前瞻性社会医学数据集。该数据集将极大地促进对疾病和健康差异的社会原因的科学理解。