Kumar Raj G, Delgado Andrew, Corrigan John D, Eagye C B, Whiteneck Gale G, Juengst Shannon B, Callender Librada, Bogner Jennifer A, Pinto Shanti M, Rabinowitz Amanda R, Perrin Paul B, Venkatesan Umesh M, Botticello Amanda L, Lequerica Anthony H, Taylor Shameeke, Zafonte Ross D, Dams-O'Connor Kristen
Author Affiliations: Department of Rehabilitation and Human Performance (Drs Kumar and Dams-O'Connor), Department of Population Health Science & Policy (Dr Delgado), Department of Emergency Medicine (Dr Taylor), Department of Neurology (Dr Dams-O'Connor), Icahn School of Medicine at Mount Sinai, New York, New York; Department of Physical Medicine and Rehabilitation (Drs Corrigan and Bogner), College of Medicine, The Ohio State University; Research Department, Craig Hospital, Englewood, Colorado(Drs Eagye and Whiteneck); Brain Injury Research Center, TIRR Memorial Hermann (Dr Juengst), Houston, Texas; Department of Physical Medicine and Rehabilitation (Dr Juengst), UT Health Sciences Center at Houston, Houston, Texas; Baylor Scott and White Institute for Rehabilitation (Dr Callender), Dallas, Texas; Department of Physical Medicine and Rehabilitation (Dr Pinto), University of Texas Southwestern Medical Center, Dallas, Texas; Moss Rehabilitation Research Institute (Drs Rabinowitz and Venkatesan), Elkins Park, Pennsylvania; Department of Rehabilitation Medicine (Drs Rabinowitz and Venkatesan), Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania; Central Virginia Veterans Affairs Health Care System (Dr Perrin), Richmond, Virginia; School of Data Science and Department of Psychology (Dr Perrin), University of Virginia, Charlottesville, Virginia; Kessler Foundation (Drs Botticello and Lequerica), East Hanover, New Jersey; Rutgers-New Jersey Medical School (Drs Botticello and Lequerica), Newark, New Jersey; Department of Physical Medicine and Rehabilitation (Dr Zafonte), Harvard Medical School, Boston, Massachusetts; Spaulding Rehabilitation Hospital (Dr Zafonte), Boston, Massachusetts; Massachusetts General Hospital (Dr Zafonte), Boston, Massachusetts; Brigham and Women's Hospital (Dr Zafonte), Boston, Massachusetts.
J Head Trauma Rehabil. 2025;40(2):86-96. doi: 10.1097/HTR.0000000000000968. Epub 2024 Aug 7.
To create a census-based composite neighborhood socioeconomic deprivation index (NSDI) from geocoded residential addresses and to quantify how NSDI aligns with individual-level socioeconomic factors among people with traumatic brain injury (TBI).
Community.
People enrolled in the TBI Model Systems National Database (TBIMS NDB).
Secondary analysis of a longitudinal cohort study.
The TBIMS-NSDI was calculated at the census tract level for the United States population based on a principal components analysis of eight census tract-level variables from the American Community Survey. Individual socioeconomic characteristics from the TBIMS NDB were personal household income, education (years), and unemployment status. Neighborhood:Individual NSDI residuals represent the difference between predicted neighborhood disadvantage based on individual socioeconomic characteristics versus observed neighborhood disadvantage based on the TBIMS-NSDI .
A single principal component was found to encompass the eight socioeconomic neighborhood-level variables. It was normally distributed across follow-up years 2, 5, and 10 post-injury in the TBIMS NDB. In all years, the TBIMS-NDSI was significantly associated with individual-level measures of household income and education but not unemployment status. Males, persons of Black and Hispanic background, Medicaid recipients, persons with TBI caused by violence, and those living in urban areas, as well as in the Northeast or Southern regions of the United States, were more likely to have greater neighborhood disadvantage than predicted based on their individual socioeconomic characteristics.
The TBIMS-NSDI provides a neighborhood-level indicator of socioeconomic disadvantage, an important social determinant of outcomes from TBI. The Neighborhood:Individual NSDI residual adds another dimension to the TBIMS-NSDI by summarizing how a person's socioeconomic status aligns with their neighborhood socioeconomics. Future studies should evaluate how both measures affect TBI recovery and life quality. Research studying neighborhood socioeconomic disadvantage may improve our understanding of how systemic adversity influences outcomes after TBI.
根据地理编码的居住地址创建基于人口普查的综合邻里社会经济剥夺指数（NSDI），并量化NSDI与创伤性脑损伤（TBI）患者个体层面社会经济因素的一致性。
社区。
纳入创伤性脑损伤模型系统国家数据库（TBIMS NDB）的人员。
纵向队列研究的二次分析。
基于美国社区调查的八个普查区层面变量的主成分分析，计算美国人口普查区层面的TBIMS-NSDI。TBIMS NDB中的个体社会经济特征包括个人家庭收入、教育程度（年数）和失业状况。邻里：个体NSDI残差表示基于个体社会经济特征预测的邻里劣势与基于TBIMS-NSDI观察到的邻里劣势之间的差异。
发现一个单一主成分涵盖了八个社会经济邻里层面变量。它在TBIMS NDB中受伤后随访的第2年、第5年和第10年呈正态分布。在所有年份中，TBIMS-NDSI与家庭收入和教育程度的个体层面测量指标显著相关，但与失业状况无关。男性、黑人和西班牙裔背景的人、医疗补助接受者、因暴力导致TBI的人，以及居住在城市地区以及美国东北部或南部地区的人，比根据其个体社会经济特征预测的更有可能面临更大的邻里劣势。
TBIMS-NSDI提供了一个邻里层面的社会经济劣势指标，这是TBI结局的一个重要社会决定因素。邻里：个体NSDI残差通过总结一个人的社会经济地位与其邻里社会经济状况的一致性，为TBIMS-NSDI增加了另一个维度。未来的研究应评估这两种测量指标如何影响TBI的恢复和生活质量。研究邻里社会经济劣势的研究可能会增进我们对系统性逆境如何影响TBI后结局的理解。
