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. Author manuscript; available in PMC: 2026 Jan 1.
Published in final edited form as: J Head Trauma Rehabil. 2024 Sep 13;40(2):57–64. doi: 10.1097/HTR.0000000000001007

Neighborhood Deprivation and Recovery Following Traumatic Brain Injury Among Older Adults

Jennifer S Albrecht 1, Jennifer Kirk 2, Kathleen A Ryan 3, Jason R Falvey 4
PMCID: PMC11890950  NIHMSID: NIHMS2056286  PMID: 39293072

Abstract

Objective:

Understanding the extent to which neighborhood impacts recovery following traumatic brain injury (TBI) among older adults could spur targeting of rehabilitation and other services to those living in more disadvantaged areas. The objective of the present study was to determine the extent to which neighborhood disadvantage influences recovery following TBI among older adults.

Setting and Participants:

Community-dwelling Medicare beneficiaries aged ≥65 years hospitalized with TBI 2010-2018.

Design and Main Measures:

In this retrospective cohort study, the Area Deprivation Index (ADI) was used to assess neighborhood deprivation by linking it to 9-digit beneficiary zip codes. We used national-level rankings to divide the cohort into the top 10% (highest neighborhood disadvantage), middle 11-90%, and bottom 10% (lowest neighborhood disadvantage). Recovery was operationalized as days at home, calculated by subtracting days spent in a care environment or deceased from monthly follow-up over the year post-TBI.

Results:

Among 13,747 Medicare beneficiaries with TBI, 1713 (12.7%) were in the lowest decile of ADI rankings and 1030 (7.6%) were in the highest decile of ADI rankings. Following covariate adjustment, beneficiaries in neighborhoods with greatest disadvantage [rate ratio (RtR) 0.96; 95% confidence interval (CI) 0.94, 0.98] and beneficiaries in middle ADI percentiles (RtR 0.98; 95% CI 0.97, 0.99) had fewer days at home per month compared to beneficiaries in neighborhoods with lowest disadvantage.

Conclusion:

This study provides evidence that neighborhood is associated with recovery from TBI among older adults and highlights days at home as a recovery metric that is responsive to differences in neighborhood disadvantage.

OLDER ADULTS HAVE the highest rates of traumatic brain injury (TBI) related hospitalizations and deaths and these rates have been steadily increasing over the last decade.1,2 Following TBI, increased risk for psychological and sleep disorders can impede recovery among older adults, who already experience longer hospital stays, increased functional limitations, and slower cognitive recovery relative to younger adults with similar TBI severity.3-9 Yet despite this seemingly grim outlook, many older adults make full recoveries after TBI. The optimization of TBI recovery among those most susceptible to adverse outcomes might be achieved by identifying those who could benefit from targeted medical and rehabilitative care following TBI, thereby improving the efficiency of scarce resource allocation.

Neighborhoods can affect health. Higher neighborhood disadvantage is associated with increased hospital readmission, decreased use of preventative services, disability, mortality, and inadequate staffing in healthcare facilities such as nursing homes.10-15 Given the high health needs of older TBI survivors, they are particularly vulnerable to neighborhood disadvantage, which incorporates factors such as income, employment, housing quality, and transportation.16 Many of these factors have been identified as barriers to the receipt of treatment following TBI.17 For example, reliable transportation is essential following TBI as driving ability is often limited due to seizure risk and problems with attention and executive function.18,19 This issue could be compounded among older adults who have already stopped driving due to age-related conditions. Exposure to air and noise pollution and violence, more common in disadvantaged neighborhoods, could also reduce resilience to development of psychological and sleep disorders, hindering recovery from TBI.20-24

Understanding the extent to which neighborhood impacts recovery following TBI among older adults could help better tailor rehabilitation to the needs of those living in more disadvantaged areas. The objective of the present study was to determine the extent to which neighborhood disadvantage influences recovery following TBI among older adults. We hypothesized that those living in areas of greater disadvantage would have poorer recovery.

METHODS

We conducted a retrospective cohort study using Medicare administrative claims data obtained from the Center for Medicaid and Medicare Services (CMS) Chronic Conditions Warehouse (CCW). Claims from a 5% random sample for years 2010 to 2016 and a 20% random sample for years 2017 to 2018 were available for hospitals, skilled nursing facilities, home health care agencies, and both freestanding and hospital-based outpatient facilities. This study was exempted from review by the Institutional Review Board of the University of Maryland School of Medicine.

Study population

Medicare beneficiaries aged 65 and older who were hospitalized with a primary diagnosis of TBI between 2010 and 2017 and discharged alive to skilled nursing facilities, rehabilitation hospital or home were eligible for the study. Among beneficiaries who had multiple TBI claims over the observation period, only the first occurrence was used. Included beneficiaries were community dwelling before TBI as defined by the absence of residence of more than 100 days in a long-term care facility prior to admission for TBI. We defined TBI using the Centers for Disease Control and Prevention (CDC) International Classification of Disease (ICD) version 9 (ICD-9) and version 10 (ICD-10) surveillance codes (excluding shaken baby syndrome but adding two non-specific initial encounter ICD-10 codes S098XXA and S099XXA) on inpatient claims in the primary position and the date of TBI was assigned as the index date.1,25 We excluded codes indicating TBI sequelae or subsequent encounters. Continuous Medicare Parts A and B coverage for at least 6 months before the index date and for the entirety of the 12-month follow-up period or until death was required. Individuals with Medicare Part C (Medicare Advantage) were excluded from analysis due to incomplete capture of their claims.

Neighborhood disadvantage

We defined neighborhood disadvantage using the Area Deprivation Index (ADI).12,16 The ADI is a census-based index that uses 17 indicators for poverty, education, housing and employment obtained from the American Community Survey to characterize regions defined by census-block groups.12,16 We linked Medicare beneficiaries to the ADI by nine-digit zip code using the Neighborhood Atlas and used national-level rankings to divide the cohort into the top 10% (highest neighborhood disadvantage), middle 11-90%, and bottom 10% (lowest neighborhood disadvantage)–consistent with prior work in Medicare claims finding threshold effects of neighborhood deprivation, or effects observed almost exclusively at the extremes of poverty and wealth.16,26 ADI values are not calculated for a small number of census block groups with less than 100 people or 30 housing units, or where more than 33% of the population lives in group quarters, as the underlying data for calculating the ADI is missing. Thus, beneficiaries in these block groups were excluded from this study.26

Home time

Home time is a population-based measure defined as the amount of time spent at home and not hospitalized or in a rehabilitation facility following a health-related event.27 Spending more time at home is an important patient-centered outcome for older adults and has been previously used to identify older adults vulnerable to poor recovery following TBI.28-31 For example, we recently reported that home time among older adults with Alzheimer’s disease and related dementias who were also economically vulnerable was reduced by over 30% relative to those without either condition.30

Consistent with our prior work, home time was calculated by subtracting the number of days spent in an inpatient, skilled nursing facility, nursing home, emergency department observation, or outpatient observation setting (ie, patient is in the hospital but has not been admitted), and the number of days spent deceased, from the total follow-up available for each of the 12 follow-up months (monthly level).29,30 This definition of home time extends prior work to include emergency department and outpatient observation settings but does not exclude days spent at home when home health care was received, in contrast with the healthy days at home metric.27,32,33 Beneficiaries who died did not continue to contribute to home time following the month of their death (ie, home time was set to missing for all subsequent months).

Covariates

The CCW contains annual flags and dates of first diagnosis since Medicare enrollment for 27 chronic conditions (eg, chronic pulmonary disease, diabetes, hypertension) that are identified using CMS algorithms based on specific diagnosis or procedure codes.34 Using date of first diagnosis, we determined whether CCW chronic conditions were present prior to the index date and if so, considered them baseline diagnoses. We dichotomized the original reason for entitlement code as age or disability (including end-stage renal disease). Dual eligibility for Medicaid during any point in the 6 months prior to TBI was considered as a proxy indicator of pre-TBI economic vulnerability. Community-dwelling Medicare beneficiaries are generally only eligible for Medicaid if they live near or below the poverty line, or have high medical needs and limited income or financial assets (in most states, <$3000 in assets for a couple, or $2000 for an individual).35

We used the R program IDCPIC-R to covert ICD-9 and -10 codes for TBI from the inpatient claim into abbreviated injury severity index (AIS) codes for the head region to provide a measure of anatomical injury associated with TBI.36 The AIS is rated on a scale from 1 to 6 for each body region, with higher scores indicating greater injury severity and mortality risk, and is combined into an overall injury severity score (ISS).37,38 AIS scores of 6/6 are designated as unsurvivable. The IDCPIC-R has been validated and shown to perform well for TBI and has been used in prior studies to estimate the head AIS score in TBI patients.39,40

Statistical analysis

We described the distribution of clinical, demographic, and injury-related characteristics in the entire sample and by ADI national ranking percentile (ie, top 10%, middle 80%, and bottom 10%) and tested differences in distributions using Chi square Goodness of Fit, ANOVA, and the Kruskal-Wallis test. We plotted mean days of home time per month pre- and post-TBI by neighborhood group status. We calculated the absolute difference in home time over the course of the year following TBI by neighborhood disadvantage group.

We modeled the monthly count of home time over the 12 months post-TBI as a function of neighborhood group percentile (bottom 10%, or least deprived, as reference) using generalized estimating equations with a negative binomial distribution to accommodate overdispersion of the monthly count of home time. To account for differing lengths of time spent alive following TBI (ie, unequal censoring due to death by group), we weighted the models by probability of survival in each month. These weights were created by modeling the probability of survival in each month post-TBI from a pooled logistic regression model fit for demographic, time-varying clinical, and injury-related characteristics. In negative binomial models, the correlation matrix was independent. Time was modeled as the inverse of its square based the quasilikelihood information criterion.

Adjusted models were built by adding variables including TBI acuity, demographics (excluding race and socioeconomic indicators which form part of the ADI) with continuous age, comorbidities and the count of days at home during the month prior to TBI to the regression model. Variables that were not statistically significant in the model were removed. Finally, we used post-estimation commands (proc plm in SAS) to estimate the adjusted mean number of days at home per month in each of the three ADI percentile groups. We exponentiated effect estimates to generate the rate ratio (RtR) and 95% confidence interval (CI) for the effect of high neighborhood disadvantage (relative to low neighborhood disadvantage) on monthly rates of home time using estimate statements in SAS Enterprise Release 3.71 (SAS Institute Inc., Cary, NC, USA).

RESULTS

Of the 20,350 Medicare beneficiaries aged 65 and older meeting study criteria, 13,747 (67.6%) were linked to the ADI. Among these beneficiaries, 1713 (12.7%) were in the lowest decile of ADI rankings, indicating the least neighborhood disadvantage, 1030 (7.6%) were in the highest decile of ADI rankings, indicated the greatest neighborhood disadvantage, and the remaining 10,731 (79.6%) were in between the two.

Beneficiaries with greatest neighborhood disadvantage were younger (79.3 (standard deviation (SD) 8.1) years vs. 80.2 (SD 8.2) years (middle) vs. 81.3 (SD 8.2) years (lowest), P < .001) and more likely to be Black (15.5% vs. 4.4% for middle ADI percentiles vs 2.5% for lowest ADI percentile, P < .001) (Table 1). They had a heavier burden of comorbidities including diabetes (50.7% vs. 43.8% (middle) vs 42.8% (lowest), P < .001), heart failure (45.5% vs. 39.1% (middle) vs. 39.4% (lowest), P < .001), and chronic lung disease (42.0% vs. 33.2% (middle) vs. 27.6%(lowest), P < .001). Individuals living in areas of highest disadvantage were more likely to have originally qualified for Medicare due to disability (19.0% vs10.6% (middle) vs. 6.3% (lowest), P < .001) and to be dually eligible for Medicaid (33.3% vs. 17.9% (middle) vs. 16.8% (lowest), P < .001).

TABLE 1.

Baseline characteristics of Medicare beneficiaries aged 65 years and older hospitalized with a traumatic brain injury (TBI) 2010-2017, by Area Deprivation Index Percentile (ADI) (higher = more disadvantage), n = 13,474

ADI 1-10,
N = 1713		 ADI 11-90,
N = 10,731		 ADI 91-100,
n = 1030		 P-value
Age, mean (SD) 81.3 (8.2) 80.2 (8.2) 79.3 (8.1) <.001
Sex .55
 Male 783 (45.7) 4764 (44.4) 453 (44.0)
 Female 930 (54.3) 5970 (55.6) 577 (56.0)
Race <.001
 White 1439 (84.0) 9601 (89.5) 809 (78.5)
 Black 42 (2.5) 470 (4.4) 160 (15.5)
 Othera 232 (13.5) 660 (6.2) 61 (5.9)
Head AISb score
 1-2 303 (17.7) 1641 (15.3) 175 (17.0) <.001
 3 578 (33.7) 3250 (30.3) 288 (28.0)
 4-5 813 (47.5) 5708 (53.2) 555 (53.9)
Length of hospital stay
 < 2 days 281 (16.4) 1683 (15.7) 137 (13.3) .04
 2-3 days 655 (38.2) 3978 (37.1) 374 (36.3)
 4-5 days 359 (21.0) 2347 (21.9) 215 (20.9)
 > 5 days 418 (24.4) 2723 (25.4) 304 (29.5)
Intensive care unit stay 643 (37.5) 3757 (35.0) 346 (33.6) .07
Discharge destination
 Home 984 (57.4) 5740 (53.5) 563 (54.7) .01
 Rehabilitation 729 (42.6) 4991 (46.5) 467 (45.3)
Death during follow-up 189 (11.0) 1234 (11.5) 136 (13.2) .20
Total days at home over year post-TBI (unadjusted), median (IQR) 343 (302, 356) 339 (288, 355) 334 (263, 353) <.001
Average monthly days at home over year post-TBI (unadjusted), median (IQR) 28.6 (25.7, 29.7) 28.3 (24.5, 29.6) 27.9 (23.3, 29.4) <.001
ADRD 519 (30.3) 2996 (27.9) 315 (30.6) .04
Anemia 1272 (74.3) 7331 (68.3) 714 (69.3) <.001
Asthma 255 (14.9) 1733 (16.2) 177 (17.2) .25
Atrial fibrillation 492 (28.7) 2952 (27.5) 252 (24.5) .05
Cancer 401 (23.4) 2161 (20.1) 195 (18.9) .004
Cataracts 1358 (79.3) 8290 (77.3) 766 (74.4) .01
Chronic kidney disease 666 (38.9) 4357 (40.6) 469 (45.5) .002
COPDc 472 (27.6) 3565 (33.2) 433 (42.0) <.001
Depression 712 (41.6) 4836 (45.1) 476 (46.2) .02
Diabetes 733 (42.8) 4699 (43.8) 522 (50.7) <.001
Heart failure 674 (39.4) 4197 (39.1) 469 (45.5) <.001
Hyperlipidemia 1494 (87.2) 9270 (86.4) 875 (85.0) .25
Hypertension 1501 (87.6) 9631 (89.8) 945 (91.8) .002
Hypothyroid 651 (38.0) 3559 (33.2) 326 (31.7) <.001
Ischemic heart disease 1113 (65.0) 6901 (64.3) 708 (68.7) .02
Osteoporosis 609 (35.6) 3184 (29.7) 274 (26.6) <.001
Rheumatoid/ osteoarthritis 1123 (65.6) 7462 (69.5) 755 (73.3) <.001
Stroke 488 (28.5) 3091 (28.8) 305 (29.6) .82
ORECd
 Age 1605 (93.7) 9597 (89.4) 834 (81.0) <.001
 Disability 108 (6.3) 1134 (10.6) 196 (19.0)
Dual 288 (16.8) 1922 (17.1) 343 (33.3) <.001
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a

Asian America, Hispanic, and Other categories compressed due to cell size restrictions.

b

Abbreviated injury scale score.

c

Chronic obstructive pulmonary disease.

d

Original reason for entitlement code.

Beneficiaries with greatest neighborhood disadvantage were more likely to have severe TBI, as defined by a head AIS score of 4 or more [53.9% vs. 53.2% (middle) vs. 47.5% (lowest), P < .001] and a hospital stay of more than 5 days [29.5% vs. 25.4% (middle) vs. 24.4% (lowest), P = .04]. Finally, beneficiaries with greatest neighborhood disadvantage were slightly more likely to die over the year post-TBI [13.2% vs. 11.5% (middle) vs. 11.0% (lowest), P = .2] but this difference was not statistically significant.

Figure 1 mean monthly home time before TBI (months 1-6) and after TBI (months 7-18). All ADI groups had a large loss of home time during the month of TBI that was mostly recovered by three months post-TBI, with clear differences in the degree of recovery by ADI ranking.

Figure 1.

Figure 1.

Open in a new tab

Average days at home per month before and after Traumatic Brain Injury (TBI) by Area Deprivation Index (ADI) Percentile, n = 13,474.

In unadjusted models, beneficiaries in neighborhoods with greatest disadvantage (RtR 0.95; 95% CI 0.92, 0.97) and beneficiaries in middle ADI percentiles (RtR 0.98; 95% CI 0.97, 0.99) had fewer days at home per month compared to beneficiaries in neighborhoods with lowest disadvantage (Table 2). The fully adjusted model was weighted for the monthly probability of survival and contained indicators for the inverse square of months post-TBI, length of hospital stay, age, days at home pre-TBI, baseline Alzheimer’s disease and related dementia, depression, hyperlipidemia, and the original reason for entitlement code (age vs. disability). Following adjustment, beneficiaries in neighborhoods with greatest disadvantage (RtR 0.96; 95% CI 0.94, 0.98) and beneficiaries in middle ADI percentiles (RtR 0.98; 95% CI 0.97, 0.99) had fewer days at home per month compared to beneficiaries in neighborhoods with lowest disadvantage.

TABLE 2.

Rate ratios and 95% confidence intervals for the effect of Area Deprivation Index (ADI) percentile on days at home over the year following hospitalization for traumatic brain injury among Medicare beneficiaries aged 65 years and older 2010-2017, n = 13,474

Unadjusted Reference
 ADI 1-10 0.98 (0.97, 0.99)
 ADI 11-90 0.95 (0.92, 0.97)
 ADI 91-100
Adjusteda Reference
 ADI 1-10 0.98 (0.97, 0.99)
 ADI 11-90 0.96 (0.94, 0.98)
 ADI 91-100
Open in a new tab
a

Adjusted for the inverse square of months post-TBI, length of hospital stay, age, days at home pre-TBI, baseline Alzheimer’s disease and related dementia, depression, hyperlipidemia, and the original reason for entitlement code (age vs. disability).

From the adjusted model, the estimated mean number of days at home per month among those who survived was 23.7 in the highest ADI percentile, 24.2 in the middle ADI percentiles, and 24.7 in the lowest ADI percentiles. Extrapolating to 12 months, beneficiaries in neighborhoods with highest disadvantage spent an average of 12 fewer days at home (284) relative to beneficiaries in neighborhoods with lowest neighborhood disadvantage (296).

DISCUSSION

Among older community-dwelling adults with TBI, residence in a neighborhood with high disadvantage was associated with spending almost two weeks fewer at home over the year following injury relative to those with the least disadvantage over the year following TBI. These disparities persisted after adjustment for an array of individual level medical factors, pre-injury disability, and days at home prior to injury. Results are consistent with prior work showing that greater neighborhood disadvantage was associated with increased disability and increased mortality among older adults with and without an acute event and more recent work reporting that greater neighborhood disadvantage was associated with longer length of hospital stay, discharge to a rehabilitation facility, and hospital readmission among mixed age adults with TBI.10,11,15

Mechanisms of this disparity in recovery from TBI are likely multifaceted. First, neighborhoods can impact resilience to functional decline for older adults. Participation in important health behaviors such as physical activity is often hampered by factors such as poor-quality sidewalks (increasing risk for falls), air pollution, and exposures to violent crime more common in disadvantaged neighborhoods.41-43 In our study, baseline disability was significantly higher among those in neighborhoods with greater disadvantage, which may contribute to lower resilience to decline after even mild TBI, resulting in increased time spent hospitalized and, in a rehabilitation, or nursing facility. After TBI, living in a deprived neighborhood may also impact access to high-quality healthcare.18,19 Availability of healthcare providers, and the quality ratings of facilities, are lower in high deprivation areas while at the same time alternative transportation options may also be limited, impeding the ability to seek care elsewhere.13,44 Prior studies also suggest that neighborhood disadvantage may influence early provider follow-up, negatively impacting care coordination and creating inequities in care that could impact recovery from TBI.14 Neighborhood disadvantage has also been shown to negatively impact disease self-management, possibly through decreased access to high quality medical care, social support, or transportation.45,46

Unfortunately, as a result of discriminatory local, state, and federal level policies that led to segregation in these communities, residents of disinvested neighborhoods are also more likely to identify as racially minoritized populations. This means that racism, both overt and structural, may be one potential mechanisms for our findings. Racial segregation often leads to unequal access to resources, healthcare, and quality living environments. At the same time, colorism can result in differential treatment within racial groups, affecting the level of care and support individuals receive. Both factors contribute to the complexity of health inequities experienced by marginalized communities. In our study, beneficiaries in neighborhoods with greater disadvantage were more likely to identify as Black. Racial and ethnic disparities in outcomes following TBI have been described in mixed age populations, with those who identify as Black or Hispanic often experiencing poorer recovery compared with White individuals.47-50 Prior studies have suggested that this difference may stem from limited use of rehabilitation services, with Black older adults more likely to be discharged home rather than to rehabilitation after TBI, but we did not observe that in these data, possibly because all participants were insured through Medicare.51,52 We previously noted that among older Medicare beneficiaries hospitalized with TBI, older adults identified as Black were less likely to participate in outpatient rehabilitation after returning to the community compared to White older adults, suggesting a potential mechanism for poorer recovery.53

Limitations of this study should be noted. Primary among these was that this study did not include beneficiaries residing in areas with missing ADIs (notably, those living in congregate settings) who may have different outcomes than included beneficiaries. Results of this study, therefore, may not generalize to those in these facilities, including older adults in assisted living settings. Additionally, this study focused on older adults hospitalized with TBI, implying that individuals with milder injury may have been excluded. Finally, this study included Medicare Fee for Service beneficiaries; thus, individuals with Medicare Advantage plans are not represented.

In conclusion, our study provides additional evidence that neighborhood is associated with recovery from injury among older adults and highlights days at home as a recovery metric that is responsive to differences in neighborhood disadvantage. The association between neighborhood disadvantage and days at home following TBI was independent of age, TBI severity, and comorbid conditions yet likely represents the additive effects of these and other factors that remain unmeasured in these data including baseline cognition, social support, distance to quality care, and health literacy. Future work should explore these factors and their interactions with neighborhood disadvantage to identify modifiable targets for intervention to improve recovery from TBI among older adults.

Acknowledgments

Drs Albrecht and Kirk were supported by National Institute on Aging (grant number R01AG076441). Dr Falvey was supported during the work by the National Institute on Aging and the Maryland Claude D. Pepper Center (grant numbers K76AG074926 and P30AG028747). We acknowledge the support of the University of Maryland, Baltimore, Institute for Clinical & Translational Research and the National Center for Advancing Translational Sciences Clinical Translational Science Award (grant number 1UL1TR003098) in helping secure Medicare data and providing support for analysis. No competing financial interests exist.

Contributor Information

Jennifer S. Albrecht, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland.

Jennifer Kirk, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland.

Kathleen A. Ryan, Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland.

Jason R. Falvey, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland; Department of Physical Therapy and Rehabilitation Science, University of Maryland School of Medicine, Baltimore, Maryland.

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