Abstract
Objective:
To examine the associations between health literacy and health outcomes among individuals with TBI at least a year post-injury.
Setting:
Community following discharge from inpatient rehabilitation.
Participants:
205 individuals with complicated mild to severe TBI who completed a TBI Model Systems National Database follow-up interview and a web-based health literacy measure.
Design:
Multicenter, cross-sectional, observational study.
Main Measures:
Health Literacy Assessment Using Talking Touchscreen Technology (HealthLiTT), number of comorbid conditions (Medical and Mental Health Comorbidities Interview (MMHCI)), perceived physical and mental health (PROMIS Global Physical (PH) and Mental Health (MH) subscales), Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7).
Results:
After controlling for sociodemographic, injury, cognition, and time post injury, adequate health literacy was associated with higher odds of greater perceived physical health compared to participants with marginal/inadequate health literacy [OR=4.10 (1.52, 11.70)]. Participants with inadequate/marginal health literacy had 3.50 times greater odds of depression (PHQ-9 ≥ 10) compared to those with adequate health literacy. Participants aged 45 and older reported a greater number of MMHCI physical health conditions, but fewer MMHCI mental health conditions and GAD-7 anxiety symptoms compared to those who were younger. Non-Hispanic white participants and those with mild/moderate TBI were more likely to report a greater number of MMHCI mental health conditions compared to non-Hispanic Black participants or those with severe TBI. Greater time post injury was associated with greater number of chronic physical and mental health conditions, and less odds of good-to-excellent perceived global mental health.
Conclusions:
Inadequate health literacy is associated with worse perceived physical health and greater depressive symptoms among adults with TBI. Greater efforts are needed to explore the mechanisms by which health literacy influences chronic disease management and mental health after TBI to improve post-injury health status and outcomes, particularly among those with limited health literacy skills.
Keywords: brain injuries, traumatic, health literacy, chronic disease, quality of life, mental health, social determinants of health
INTRODUCTION
Health literacy has been conceptualized as a major public health goal to empower people to maintain physical and mental health.1,2 Healthy People 2030, from the United States (U.S.) Department of Health and Human Services, defines personal health literacy as an individual’s ability to find, understand, and use health-related information to make well-informed health decisions for themselves and others.2 It further stipulates the responsibility of organizations to achieve organizational health literacy by equitably enabling personal health literacy for all served. The National Assessment of Adult Literacy (NAAL) from 2003 assessed health literacy in a sample of 19,000 adults, age 16 or older, in the U.S. Only 12% of adults assessed demonstrated proficient health literacy, 53% demonstrated intermediate health literacy, and 14% showed below basic health literacy (i.e., no more than simple, concrete literacy skills like easily identifying information in simple charts or forms).3 Low health literacy was associated with male gender, Hispanic identity, age 65 or older, less than a high school education, income below the poverty level, and Medicare or Medicaid (vs private or military insurance).3,4 These findings from the only national health literacy survey to date suggest that many individuals do not have proficient health literacy to engage with health information and navigate health systems.
Two evidence-based reviews funded by the Agency for Healthcare Research and Quality (AHRQ) have concluded that low health literacy is associated with a variety of poor health behaviors.5,6 For example, persons with low health literacy are more likely to engage in poorer medication management, including taking prescription medications inaccurately and being unable to identify medications.7,8 Low health literacy is also associated with greater use of emergency room services among older adults.9 Researchers have found an association between low health literacy and less frequent use of preventive health services, such as mammography9,10 and influenza immunizations.10 In a mixed rehabilitation sample (stroke, hip fractures, and joint replacements), low health literacy was shown to contribute to poor decision-making when choosing rehabilitation programs.11 Low health literacy is also associated with worse health outcomes in persons with comorbid health or behavioral health conditions12and in older adults.9,10,13–16 Lastly, Hahn and colleagues found that better health literacy was associated with greater mobility, greater overall health, and lower anxiety among persons with traumatic brain injury (TBI), spinal cord injury, and stroke at one-year post-injury.17
The existing literature linking low health literacy to poor health behaviors and poor health outcomes in the general population, particularly in older persons, indicates that low health literacy is an important obstacle to management of chronic health problems. Poor health literacy has also been associated with adverse health outcomes,5,6,18 including worse physical and mental health,19 lower self-rated health status,9,10 more chronic health conditions,13,16 and greater mortality risk.14,15 Health literacy education has been shown to improve self-efficacy and reduce depressive symptoms in a small sample of adults,20 and communication skills training for physicians has been shown to improve their patients’ health literacy and health behaviors,21 suggesting that health literacy may be an effective target – through individual or institutional interventions – to improve physical and mental health outcomes.
TBI has been conceptualized as a chronic condition with consequences to health and function across the lifespan.22,23 The cognitive and behavioral impairments common after TBI can make managing health more difficult, and these same impairments can interfere with comprehension and utilization of information provided as part of patient education. Despite this, little work has been done to examine the effects of health literacy on long-term outcomes after TBI. Correa and colleagues24 found that only 6.2% of 405 available online health education materials on TBI and post-traumatic epilepsy met the recommended 6th grade reading level. Though persons with TBI may require additional supports and adaptations to ensure adequate personal health literacy to manage their long-term health. Health literacy tends to be stable over time, but even subtle cognitive decline may affect it.8 Cognitive impairments associated with TBI may therefore impact health literacy,8 making the likelihood of low health literacy among persons with TBI even higher than in other populations. Health literacy has strong associations with processing speed, working memory, and reasoning, which are commonly impaired after TBI.
Despite the known importance of health literacy in long-term management of chronic health conditions, and the potential for low health literacy to be a problem for individuals with TBI, there is little evidence for the specific effect of health literacy on rehabilitation outcomes among persons with TBI. The purpose of the current study was to examine associations between health literacy and physical and mental chronic health conditions, perceived physical and mental health and depression and anxiety symptoms in a multi-site TBI sample. We hypothesized that adequate health literacy would be associated with fewer physical and mental chronic health conditions, better perceived physical and mental health, and fewer symptoms of depression and anxiety, after adjusting for relevant covariates.
METHOD
Participants
Included participants were English- and Spanish-speaking individuals with medically documented TBI who were enrolled at one of five participating sites in the TBI Models Systems (TBIMS) National Database.25 The TBIMS National Database inclusion criteria are: age at least 16 at time of injury; sustained complicated mild, moderate, or severe TBI; received acute trauma care within 72 hours of injury; admitted to specialized brain injury inpatient rehabilitation in TBIMS facilities; and provided informed consent, either themselves or via proxy.
TBIMS participants were considered eligible for the health literacy study if they were due for a follow-up interview between 10/1/2018 and 6/30/2021 (dates of the health literacy study). TBIMS follow-ups are conducted at 1, 2, and 5 years post-injury, as well as every 5 years thereafter. The TBIMS National Database biostatistician randomly selected 61 participants from each of the five centers, based on a target sample size of 202 and estimating a 20% loss to TBIMS follow-up. To target equivalent representation of the health literacy sample education and race/ethnicity to that of the TBIMS National Database, eligible participants were stratified by years of education (less than high school diploma; high school diploma or GED; more than high school diploma) and race/ethnicity (non-Hispanic white, non-Hispanic Black, Hispanic). Eligible participants who were lost to follow-up were replaced with another eligible participant from the same center (preferred option, if available) with similar years of education, and race/ethnicity. All participants were required to be able to complete a TBIMS follow-up interview and the web-based health literacy survey. The health literacy survey data were collected and managed using REDCap electronic data capture tools hosted at the University of Texas Medical Branch (UTMB) at Galveston.26
Procedures
The larger TBIMS National Database study and health literacy study were approved by the institutional review boards of each site. TBIMS participants who were identified randomly by the national database statistician were invited to participate in the health literacy study upon completion of their TBIMS follow-up interview. Individuals who expressed interest were sent a REDCap survey link via email, which included a health literacy measure and a global health measure. Participants were asked to complete the REDCap survey within one month after completing their TBIMS follow-up interview and received $25 after survey completion. Data on sociodemographic characteristics, injury severity, chronic health conditions, cognition, depression, and anxiety were extracted from the TBIMS follow-up interview that corresponded with the REDCap survey.
Health Literacy Measure
Health Literacy Assessment With Talking Touchscreen Technology – Short Form (HealthLiTT).27,28
The Health LiTT Short-Form is a 14-item multimedia (sight, sound, and touch) self-report health literacy measure completed via computer-assisted or web-based using REDCap. The measure includes 6 prose, 6 document, and 2 quantitative items that were developed using item response theory (IRT), with multiple-choice responses. Each item is displayed on the screen and may be read aloud by touching a radio button. Relevant images or graphs are included for some questions. Prose items include a short reading passage, the document items include charts or prescription labels, and the quantitative items include either text or an image that requires some form of calculation to answer questions. The total HealthLiTT short-form score is transformed to a T-score scale, which has a mean of 50 and a standard deviation of 10. HealthLiTT meets psychometric standards with high reliability (≥ 0.90).27 The HealthLiTT short form has English- and Spanish- language versions with demonstrated equivalence.28 Participants completed either the English- or Spanish-version HealthLiTT based on their preferred language used to complete the TBIMS follow-up interview.
Health Outcomes
Medical and Mental Health Comorbidities Interview (MMHCI).
The MMHCI is based on physical and mental health comorbidities from the National Health and Nutrition Examination Survey (NHANES) and the National Comorbidity Survey Replication (NCS-R), respectively.29,30 There are 16 chronic physical health conditions (e.g., hypertension, stroke, diabetes) and 10 chronic mental health conditions (e.g., PTSD, Depression, ADD/ADHD). Each item begins with “Has a doctor ever told you that you had…”. Any affirmative response indicated the presence of the comorbidity. Previous work showed that comorbidities nearly double from pre-TBI to up to 10 years post injury.31 For this study, two separate variables were created based on the number of physical and mental health comorbidities reported.
PROMIS Global Health Physical (PH) and Mental Health (MH) subscales.32
The 10-item PROMIS Global Health measure, version 1.2, assesses perceived physical and mental health, producing two scores: Physical Health (4-items) and Mental Health (4-items). The measure also includes an item on fatigue and another on pain. To calculate the scores, three of the items are reverse scored so that higher scores indicate better functioning. Using a T-score conversion table, the raw sum is converted to T-scores, with a mean of 50 and a standard deviation (SD) of 10. Higher T-scores indicate greater perceived physical and mental health.
Patient Health Questionnaire-9 (PHQ-9).33
The PHQ-9 is a brief, 9-item self-report measure of depressive symptoms. Items are rated on a 4-point scale with 0 (not at all) to 3 (nearly every day) and then summed. The total score ranges from 0 to 27 with higher scores equating to greater depressive symptoms. A cut-off score of 10 (at least moderately depressed) maximizes sensitivity and specificity.34 Its psychometric properties have been deemed satisfactory.35,36
Generalized Anxiety Disorder-7 (GAD-7).37
The GAD-7 is a brief, 7-item self-report measure of anxiety symptoms, rated on a scale of 0 (not at all) to 3 (nearly every day). The items are summed, and the total score ranges from 0 to 21. A cut-off score of 10 is suggested,38 and validated for identifying anxiety disorders.39
Control Variables from the TBIMS Follow-up Interview
Sociodemographic and Injury-Related Variables.
Age, education (<high school, high school or GED, >high school), sex, race/ethnicity, language, urbanicity (rural, urban, or suburban classifications based on GreatData zip code data, which factors in population density, distance from nearest city, and size of the nearest city), and injury severity were extracted from the corresponding TBIMS follow-up Interview. Prior to 2012, the TBIMS National Database combined race and ethnicity, which included Hispanic along with several races. In 2012, the TBIMS began coding race and ethnicity separately, and ethnicity was coded as Hispanic or Non-Hispanic. Race and ethnicity were collected at the subsequent follow-up for any individual who was enrolled in the TBIMS National Database prior to 2012. If a new observation showed more than one race or included a race other than White or Black, the combined race/ethnicity data prior to 2012 were used. Any individual who was coded as Hispanic in any of the variable versions were coded as Hispanic (regardless of race). Two hundred participants had race and/or ethnicity data, while 5 participants had race/ethnicity coded based on the older combined variable. Injury severity was dichotomized as complicated mild/moderate or severe, based on information extracted from the medical records for one of the following criteria: duration of posttraumatic amnesia (PTA) in days; duration of unconsciousness in minutes; or Glasgow Coma Scale (GCS) score. Time post injury in years was based on injury date and survey completion date.
Brief Test of Adult Cognition by Telephone (BTACT).40
The BTACT is a brief telephone-based cognitive assessment that includes a variety of subtests comprising two cognitive domains of episodic memory and executive function. 41,42 The BTACT has been used with persons with TBI and has good reliability and test-retest reliability of subtests.
Statistical Analyses
Health literacy level, based on the HealthLiTT T-score, was dichotomized into marginal/inadequate (T-score <55) and adequate health literacy (T-score ≥55), which provides acceptable sensitivity and specificity to identify adequate health literacy.43 The PROMIS Global Physical Health T-scores were dichotomized into fair-to-poor physical health (T-score <42) and good-to-excellent physical health (T-score ≥ 42).44 The PROMIS Global Mental Health T-scores were also dichotomized into fair-to-poor mental health (T-score<40) and good-to-excellent mental health (≥ 40).44 Cut-off scores of 10 were used for PHQ-9 and GAD-7, respectively.34,38 T-tests or Wilcoxon tests were conducted to examine differences in outcomes (i.e., number of physical and mental health comorbidities, PHQ-9, and GAD-7). As there is no theoretical reason to anticipate that a specific number of health conditions would be more or less related to health literacy, our statisticians calculated the distribution of number of physical and mental health conditions endorsed by participants. Our investigator team (including statisticians) then reviewed this distribution and decided how to split the distribution for analyses while considering our sample size. Based on the sample distribution with more than one physical health condition diagnosed, the categorization of ≤ 1 and > 1 was selected. With a narrow distribution of mental health conditions due to fewer people having more than one condition, the number of mental health conditions was dichotomized as 0 versus ≥1.
Chi-square tests were calculated to examine health literacy level (adequate versus marginal/inadequate) by PROMIS Global Physical Health and Mental Health. Multiple logistic regression models were conducted to determine the contribution of health literacy to health outcomes, adjusting for age (<45, 45+), education (< high school (HS), HS/GED, or ≥ high school), race/ethnicity (Hispanic, non-Hispanic Black, non-Hispanic white), sex (male, female), urbanicity (suburban, urban, rural), injury severity (mild/moderate, severe), cognition, and time post injury in years. Age was dichotomized as <45 years and 45 years and older, as mid-life is often when physical and cognitive changes may occur due to normal aging.
RESULTS
There were 305 participants (61 per center) who were initially randomly selected to be contacted for the health literacy study. Of those who completed their TBIMS follow-up interview, 95 declined participation (65 due to not being comfortable using the Internet/technology, 12 too busy, 15 not interested, 3 unknown). The national database statistician replaced these cases with cases with similar race/ethnicity and education. Comparison of the health literacy study sample to the larger TBIMS sample with follow-up data showed that there were more participants aged less than 45 years (p<.05) and living in suburban areas (versus rural or urban) in the health literacy sample (p<.0001) There was no significant difference based on sex, education, racial/ethnic identification, or injury severity (complicated mild/moderate versus severe).
Most of the participants were younger than 45 years old (n=143, 70%), male (n=140, 68%), had greater than high school education (n=124, 60%), and sustained a severe TBI (n=177, 86%). Participants were non-Hispanic white (n=142, 69%), non-Hispanic Black (n=38, 19%), and Hispanic (n=25, 12%). At the time of the follow-up interview, 24% lived in a rural area, 27% lived in an urban area, and about 46% lived in a suburban area. The average time post injury was 8.11 years (SD=5.55; range=1.75–29.64].
Based on the HealthLiTT cut-off score of 55, 69% (n=141) of the sample was classified as having adequate health literacy, while 31% were classified as having marginal/inadequate health literacy. More than half of the sample (55%) had no more than one MMHCI physical condition, whereas nearly half of the sample (48%) did not have any MMHCI mental health condition. Roughly a quarter of the sample reported fair-to-poor PROMIS physical and mental global health, while most participants reported good-to-excellent health. The mean PHQ-9 score was 5.09 (SD=5.13; range=0 –24), and the mean GAD-7 score was 4.19 (SD=4.92; range=0–20).
Education, race/ethnicity, and cognition were associated with health literacy level (see Sander et al., under review). A greater proportion of individuals with less than high school education demonstrated marginal/inadequate health literacy compared to those with greater than high school education. Non-Hispanic white participants were more likely to have adequate health literacy compared to non-Hispanic Black and Hispanic participants. In addition, better scores on the BTACT were associated with adequate health literacy. Time post injury (years) was not associated with health literacy level.
As shown in Table 1, there were no differences in the number of chronic physical and mental health conditions by health literacy level. A greater proportion of individuals with good-to-excellent physical and mental health based on the PROMIS Global Physical Health (PH) and Mental Health (MH) subscales demonstrated adequate health literacy compared to those with fair-to-poor physical and mental health. A greater proportion of individuals classified as having marginal/inadequate health literacy had PHQ-9 and GAD-7 scores greater than or equal to 10 (i.e., consistent with depression or anxiety disorder) compared to those with adequate health literacy.
Table 1.
Outcome Variables Comparisons by Marginal/Inadequate and Adequate Health Literacy Groups
| Variable | Marginal/Inadequate Health Literacy | Adequate Health Literacy | p-value |
|---|---|---|---|
| Overall | 64 | 141 | |
|
| |||
| Chronic Physical Health Condition | 0.47 | ||
| ≤1 condition | 38 (59.38%) | 74 (52.48%)a | |
| >1 condition | 26 (40.63%) | 66 (46.81%) | |
| Chronic Mental Health Condition | 0.66 | ||
| 0 condition | 33 (51.56%) | 66 (46.81%) | |
| >0 condition | 31 (48.44%) | 74 (52.48%) | |
| PROMIS Global Physical Health T-scores, Mean (SD) | 42.94 (8.91) | 49.49 (9.22) | <0.01 |
| < 42 (fair to poor) | 29 (45.31%) | 28 (19.86%) | <0.01 |
| ≥ 42 (good to excellent) | 35 (54.69%) | 113 (80.14%) | |
| PROMIS Global Mental Health T-scores, Mean (SD) | 42.04 (8.71) | 47.33 (8.47) | <0.01 |
| < 40 (fair to poor) | 26 (40.63%) | 27 (19.15%) | <0.01 |
| ≥ 40 (good to excellent) | 38 (59.38%) | 114 (80.85%) | |
| PHQ-9 Total Score, Mean (SD) | 6.95 (6.31)b | 4.26 (4.27)c | <0.01 |
| < 10 | 43 (67.19%) | 118 (83.69%) | 0.03 |
| ≥ 10 | 17 (26.56%) | 16 (11.35%) | |
| GAD-7 Total Score, Mean (SD) | 5.80 (5.99)b | 3.47 (4.19)d | 0.02 |
| < 10 | 46 (71.88%) | 121 (85.82%) | 0.01 |
| ≥ 10 | 14 (21.88%) | 14 (9.93%) | |
Note.
Missing n=1
Missing n=4
Missing n=7
Missing n=6.
Table 2 shows the health literacy group was not statistically associated with the number of MMHCI chronic physical health nor mental health conditions. Participants aged 45 and older and with greater years post injury had higher odds of having more than one chronic physical health condition compared to younger participants and those who were earlier post injury, respectively. Age, race/ethnicity, injury severity, and time post injury were associated with the number of chronic mental health conditions. Participants aged less than 45, non-Hispanic white, mild/moderate injury, or were greater years post injury had higher odds of having at least one chronic mental health condition compared to participants who were older, with severe TBI, or were earlier post injury, respectively. All other covariates were not significantly associated with number of MMHCI physical nor mental conditions.
Table 2.
Logistic Regression Models of Health Literacy and Predictors of MMHCI Chronic Physical Health and Mental Health Conditions
| Chronic Physical Health
Conditions ( ≤1 vs >1) |
Chronic Mental Health
Conditions ( 0 vs >0) |
|||||
|---|---|---|---|---|---|---|
|
| ||||||
| Effect | Odds Ratio (95% CI) |
Individual p-value |
Overall p-value |
Odds Ratio (95% CI) |
Individual p-value |
Overall p-value |
|
Health Literacy
(ref: Marginal/ Inadequate) |
0.72 | 0.56 | ||||
| Adequate | 0.84 (0.33, 2.11) | 0.72 | 0.76 (0.30, 1.92) | 0.56 | ||
|
Age
(ref: <45) |
.002 | 0.018 | ||||
| 45 or above | 3.82 (1.66, 9.25) | 0.002 | 0.37 (0.15, 0.84) | 0.02 | ||
|
Sex
(ref: Male) |
||||||
| Female | 0.85 (0.39, 1.81) | 0.67 | 0.67 | 1.95 (0.90, 4.33) | 0.09 | 0.09 |
|
Education
(ref: Below HS) |
0.64 | 0.69 | ||||
| HS/GED | 0.61 (0.19, 2.01) | 0.42 | 0.99 (0.29, 3.31) | 0.98 | ||
| Above HS | 0.88 (0.29, 2.73) | 0.82 | 1.41 (0.45, 4.44) | 0.55 | ||
|
Race/Ethnicity
(ref: Non-Hispanic White) |
0.22 | 0.020 | ||||
| Non-Hispanic Black | 0.41 (0.14, 1.14) | 0.10 | 0.27 (0.09, 0.74) | 0.01 | ||
| Hispanic | 0.96 (0.31, 2.85) | 0.94 | 0.38 (0.12, 1.12) | 0.08 | ||
|
Rural/Urban
(ref: Rural) |
0.30 | 0.18 | ||||
| Suburban | 1.95 (0.84, 4.65) | 0.12 | 0.55 (0.23, 1.31) | 0.18 | ||
| Urban | 1.50 (0.58, 3.94) | 0.41 | 0.41 (0.15, 1.07) | 0.07 | ||
|
Injury Severity
(ref: Mild/ Moderate) |
0.95 | 0.038 | ||||
| Severe | 0.96 (0.32, 2.92) | 0.95 | 0.30 (0.09, 0.94) | 0.04 | ||
| BTACT Executive Function | 0.94 (0.65, 1.34) | 0.72 | 0.72 | 0.94 (0.66, 1.35) | 0.74 | 0.74 |
| BTACT Episodic Memory | 1.38 (0.92, 2.09) | 0.12 | 0.12 | 0.92 (0.62, 1.38) | 0.70 | 0.70 |
| Time Post Injury (Years) | 1.07 (1.004, 1.14) | 0.04 | 0.037 | 1.07 (1.002, 1.15) | <0.05 | 0.043 |
Note. BTACT: Brief Test of Adult Cognition by Telephone; CI: Confidence Interval; HS: High School; GED: General Educational Development; MMHCI: Medical and Mental Health Comorbidities Interview.
As shown in Table 3, participants classified as having adequate health literacy had higher odds of achieving good-to-excellent PROMIS Global PH scores compared to participants with marginal/inadequate health literacy [PH: OR=4.10 (1.52, 11.70), p<0.01]. All covariates were not significantly associated with PROMIS Global PH; however, greater time post injury was associated with decreased odd of having a PROMIS Global MH score ≥40 [OR=0.90 (0.83, 0.97), p<0.01].
Table 3.
Logistic Regression Models of Health Literacy and Predictors of PROMIS Global Physical Health and Global Mental Health Scores
| PROMIS Global Physical
Health ( <42 vs ≥42) |
PROMIS Global Mental
Health ( <40 vs ≥40) |
|||||
|---|---|---|---|---|---|---|
|
| ||||||
| Effect | Odds Ratio (95% CI) |
Individual p-value |
Overall p-value |
Odds Ratio (95% CI) |
Individual p-value |
Overall p-value |
|
Health Literacy
(ref: Marginal/ Inadequate) |
0.005 | 0.08 | ||||
| Adequate | 4.10 (1.52, 11.70) | 0.01 | 2.52 (0.90, 7.21) | 0.08 | ||
|
Age
(ref: <45) |
0.81 | 0.43 | ||||
| 45 or above | 1.12 (0.43, 3.11) | 0.82 | 0.66 (0.24, 1.88) | 0.43 | ||
|
Sex
(ref: Male) |
0.61 | 0.39 | ||||
| Female | 0.80 (0.34, 1.94) | 0.61 | 1.53 (0.58, 4.37) | 0.40 | ||
|
Education
(ref: Below HS) |
0.27 | 0.64 | ||||
| HS/GED | 2.71 (0.77, 9.97) | 0.12 | 1.68 (0.45, 6.26) | 0.43 | ||
| Above HS | 1.53 (0.44, 5.10) | 0.49 | 1.85 (0.49, 6.68) | 0.35 | ||
|
Race/Ethnicity
(ref: Non-Hispanic White) |
0.18 | 0.21 | ||||
| Non-Hispanic Black | 1.29 (0.45, 4.12) | 0.65 | 0.60 (0.20, 1.91) | 0.38 | ||
| Hispanic | 3.62 (0.93, 19.37) | 0.09 | 2.66 (0.60, 19.12) | 0.25 | ||
|
Rural/Urban
(ref: Rural) |
0.59 | 0.31 | ||||
| Suburban | 1.60 (0.61, 4.18) | 0.34 | 1.93 (0.70, 5.36) | 0.20 | ||
| Urban | 1.61 (0.54, 4.96) | 0.40 | 2.43 (0.72, 8.89) | 0.16 | ||
|
Injury Severity
(ref: Mild/ Moderate) |
0.61 | 0.28 | ||||
| Severe | 1.38 (0.39, 4.64) | 0.61 | 0.44 (0.08, 1.91) | 0.30 | ||
| BTACT Executive Function | 1.16 (0.78, 1.75) | 0.47 | 0.47 | 1.42 (0.92, 2.23) | 0.12 | 0.11 |
| BTACT Episodic Memory | 1.06 (0.66, 1.72) | 0.81 | 0.81 | 0.90 (0.54, 1.51) | 0.69 | 0.69 |
| Time Post Injury (Years) | 1.02 (0.95, 1.10) | 0.56 | 0.56 | 0.90 (0.83, 0.97) | 0.01 | 0.006 |
Note. BTACT: Brief Test of Adult Cognition by Telephone; CI: Confidence Interval; HS: High School; GED: General Educational Development.
Health literacy was associated with PHQ-9 depression scores, but not GAD-7 anxiety scores. Participants with inadequate/marginal health literacy had 3.50 times higher odds of depression (PHQ-9 ≥ 10) in comparison to those with adequate health literacy (see Table 4). In addition, participants aged less than 45 had 4.26 higher odds of anxiety (GAD-7 ≥ 10) compared to older participants. All other covariates were not significantly associated with PHQ-9 nor GAD-7.
Table 4.
Logistic Regression Models of Health Literacy and Predictors of PHQ-9 and GAD-7 Scores
| PHQ-9 ( <10 vs ≥10) |
GAD-7 ( <10 vs ≥10) |
|||||
|---|---|---|---|---|---|---|
|
| ||||||
| Effect | Odds Ratio (95% CI) |
Individual p-value |
Overall p-value |
Odds Ratio (95% CI) |
Individual p-value |
Overall p-value |
|
Health Literacy
(ref: Marginal/ Inadequate) |
0.038 | 0.15 | ||||
| Adequate | 0.29 (0.08, 0.93) | 0.04 | 0.41 (0.12, 1.37) | 0.15 | ||
|
Age
(ref: <45) |
0.22 | 0.042 | ||||
| 45 or above | 0.45 (0.10, 1.57) | 0.24 | 0.23 (0.04, 0.95) | 0.07 | ||
|
Sex
(ref: Male) |
0.16 | 0.79 | ||||
| Female | 2.05 (0.75, 5.54) | 0.16 | 1.16 (0.39, 3.23) | 0.79 | ||
|
Education
(ref: Below HS) |
0.53 | 0.31 | ||||
| HS/GED | 1.21 (0.25, 7.05) | 0.82 | 3.51 (0.71, 26.64) | 0.16 | ||
| Above HS | 2.10 (0.49, 11.92) | 0.35 | 2.29 (0.46, 17.74) | 0.36 | ||
|
Race/Ethnicity
(ref: Non-Hispanic White) |
0.18 | 0.33 | ||||
| Non-Hispanic Black | 0.23 (0.03, 1.11) | 0.10 | 0.31 (0.04, 1.43) | 0.18 | ||
| Hispanic | 0.58 (0.10, 2.44) | 0.49 | 0.60 (0.11, 2.55) | 0.51 | ||
|
Rural/Urban
(ref: Rural) |
0.10 | 0.44 | ||||
| Suburban | 1.03 (0.36, 3.04) | 0.96 | 0.48 (0.15, 1.49) | 0.20 | ||
| Urban | 0.22 (0.03, 1.07) | 0.09 | 0.58 (0.14, 2.18) | 0.43 | ||
|
Injury Severity
(ref: Mild/ Moderate) |
0.99 | 0.69 | ||||
| Severe | 1.00 (0.19, 6.17) | 0.99 | 0.71 (0.14, 4.34) | 0.69 | ||
| BTACT Executive Function | 0.76 (0.45, 1.26) | 0.29 | 0.29 | 0.74 (0.44, 1.23) | 0.25 | 0.25 |
| BTACT Episodic Memory | 1.24 (0.70, 2.21) | 0.46 | 0.46 | 1.01 (0.56, 1.81) | 0.99 | 0.99 |
| Time Post Injury (Years) | 1.00 (0.92, 1.09) | 0.96 | 0.96 | 1.01 (0.92, 1.10) | 0.92 | 0.92 |
Note. BTACT: Brief Test of Adult Cognition by Telephone; CI: Confidence Interval; HS: High School; GED: General Educational Development.
DISCUSSION
This study examined the association between health literacy and health outcomes among a diverse sample of individuals following a complicated mild-to-severe TBI. We found that, after adjusting for sociodemographic factors, injury severity, cognition, and time post injury, inadequate health literacy level was associated with worse perceived physical health and greater likelihood of depression. Older age was significantly associated with greater number of diagnosed physical conditions, and to fewer number of diagnosed mental health conditions and GAD-7 anxiety symptoms. Greater time post injury was associated with greater number of diagnosed physical and mental health conditions and greater odds of poorer perceived global mental health. Non-Hispanic white participants and those with mild/moderate TBI were more likely to have a greater number of diagnosed mental health conditions, which is consistent with other studies.31,45 These studies suggest that ethnic minorities and those with greater deficits being less likely to receive a mental health diagnosis. Contrary to our hypotheses, health literacy was not independently associated with the number of diagnosed physical and mental health conditions, perceived global mental health nor GAD-7 anxiety symptoms, after adjusting for sociodemographic factors, injury severity, cognition and time post injury.
Our findings that marginal/inadequate health literacy was associated with fair-to-poor perceived physical health and greater likelihood of depression among individuals with TBI is consistent with findings in other populations, including older adults5 and individuals with chronic diseases.19 In a recent study of 108 individuals with stroke at 12 months following hospital discharge, health literacy was associated with fewer depressive symptoms and with better walking ability and greater perceived recovery from stroke.46 The relationship between health literacy and perceived physical health and depression may not be a direct one. Health literacy has been shown to impact health behaviors, such as medication adherence and use of preventative health services.5 These behaviors may directly impact physical health and depression, with health literacy being a moderating factor. As the current study is among the first to investigate the contribution of health literacy to perceived physical and mental health for individuals with TBI, future studies should investigate the relationship of health literacy to health behaviors and skills following TBI, as these are potentially modifiable factors.
Health literacy was not associated with the number of diagnosed physical and mental health conditions, perceived mental health, and GAD-7 anxiety symptoms. Some degree of chronic health conditions are inherent to a previous significant TBI and may be present regardless of health literacy; for example, cardiovascular disease and other medical conditions have been demonstrated to be elevated in both veteran and civilian populations.45,47 While health literacy may ameliorate the severity and improve management of a condition, it may not be directly linked to the diagnosis. Our findings are also limited due to participants’ retrospective recall of being diagnosed with specific health conditions by a doctor, which may differ if medical record documentation were available. While depression and anxiety are often considered together, studies of individuals with mild TBI suggest that depression and anxiety may have differing prevalence, with depression more frequent.48 In veteran populations, post-traumatic stress disorder is more common than depression.49 Therefore, one might expect some differences in associations between health literacy and disorders when compared to a more general population.
Limitations
Our study was exploratory and multiple analyses were conducted without correction; however, health literacy still had a significant impact on perceived physical health using a conservative Bonferroni correction. Our sample only included individuals with TBI who were admitted to acute rehabilitation, which may limit generalizability to individuals with history of uncomplicated mild TBI or those who did not attend acute inpatient rehabilitation. Issues of financial instability or lack of health insurance may prevent individuals from receiving inpatient rehabilitation care. Because economic disadvantage has been associated with low health literacy,50 future research should include information regarding socioeconomic status. This study included individuals from the three largest racial/ethnic groups in the US and can serve as a framework for research examining health literacy in racial/ethnic groups with smaller numbers where greater resources may be needed to ensure representation. Despite these limitations, there are a number of study strengths worth noting. As a collaborative study among five TBI Model Systems, this effort achieved greater geographic diversity than would result from a single site study. In addition, the sampling strategy allowed greater representation of ethnic and racial minorities, which was further enhanced by providing data collection tools in Spanish. The representation of Hispanic participants was not limited by English proficiency. This study involved only quantitative data. Qualitative studies with people with TBI with inadequate health literacy, including those from underserved groups, would provide information that could guide development of tailored interventions to meet their unique needs.
Clinical implications
TBI-related impairments in cognitive and behavioral functioning may result in more difficulty managing physical health conditions as people with TBI age, and those with low health literacy may be at increased risk for difficulty managing health conditions. Based on the association of time post-injury with diagnosis of physical and mental health conditions, healthcare providers should pay special attention to monitoring physical and mental health as individuals with TBI age, and to tailoring education and recommendations to compensate for low health literacy and/or combined effects of aging and/or TBI-related cognitive and behavioral impairments. Identification of people who have inadequate health literacy early in the rehabilitation process would allow for patient and family training. Rapid assessments of functional health literacy (e.g., reading their medication label; interpreting blood sugar levels) that can be completed in the clinic are also critical if providers are to identify at risk individuals. Interventions to improve health literacy are also needed, such as educating individuals with TBI in health care maintenance and in communicating effectively with healthcare providers to get their health needs met. Findings suggest interventions are needed to address the needs of people with TBI with inadequate health literacy who are at increased risk for depression and have lower odds of achieving good-to-excellent perceived physical health.
CONCLUSION
In summary, this study reveals that health literacy skills are closely related to perceived physical health and depression as one ages with TBI, even after accounting for person- and injury-related factors. Future efforts are needed to explore how health literacy skills may play an integral role in chronic disease management and addressing mental health challenges following injury. Interventions may need to be tailored to train persons with TBI on finding, understanding, and using health-related information in a way to make appropriate decisions that will improve their overall physical and mental health after injury.
Acknowledgments
The contents of this publication were developed under grants from the National Institute on Disability, Independent Living, and Rehabilitation Research grant numbers 90DPTB0025 [PIs: Sander, Juengst], 90DPTB0016 [PIs: Sherer, Sander], 90DPTB0001 [PI: Bogner], 90DPTB0013 [PIs: Driver, Bell], 90DPTB0003 [PI: Chiaravallotti], 90DPTB0015 [PI: Novack], 90DPTB0029 [PI: Brunner], and the National Institutes of Health's National Institute on Aging (NIH/NIA) grant number K01AG065492 [PI: Pappadis], P30AG024832 [PI: Volpi], P30AG059301 [PI: Markides], National Institute on Minority Health and Health Disparities (NIMHD) contract number L60MD009326L [PI: Pappadis], and the National Center for Advancing Translational Sciences (NCATS)/NIH grant number UL1TR001439 [PI: Urban]. NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS). The contents of this publication is solely the responsibility of the authors and do not necessarily represent the policy or official views of NIDILRR, ACL, NIH/NIA, NIH/NIMHD, NIH/NCATS, HHS, and you should not assume endorsement by the Federal Government.
We certify that no party having a direct interest in the results of the research supporting this article has or will confer a benefit on us or on any organization with which we are associated.
We also certify that all financial and material support for this research and work are clearly identified in the title page of the manuscript. This study was conducted with the support of the Institute for Translational Sciences at the University of Texas Medical Branch, supported in part by a Clinical and Translational Science Award (UL1 TR001439) from the National Center for Advancing Translational Sciences, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Special thanks to Jay Bogaards, M.A. for his project coordination.
Abbreviations:
- AHRQ
Agency for Healthcare Research and Quality
- BTACT
Brief Test of Adult Cognition by Telephone
- GAD-7
Generalized Anxiety Disorder-7 item
- HealthLiTT
Health Literacy Assessment Using Talking Touchscreen Technology
- MMHCI
Medical and Mental Health Comorbidities Interview
- PHQ-9
Patient Health Questionnaire-9
- PROMIS
Patient-reported outcomes measurement information systems
- TBI
traumatic brain injury
- TBIMS
Traumatic Brain Injury Model Systems
Contributor Information
Monique R. Pappadis, Department of Population Health and Health Disparities School of Public and Population Health, The University of Texas Medical Branch (UTMB) and Sealy Center on Aging, UTMB; Brain Injury Research Center, TIRR Memorial Hermann, Houston, TX
Angelle M. Sander, Brain Injury Research Center, TIRR Memorial Hermann, Houston, TX; H. Ben Taub Department of Physical Medicine & Rehabilitation, Baylor College of Medicine and Harris Health System, Houston, TX
Shannon B. Juengst, Brain Injury Research Center, TIRR Memorial Hermann, Houston, TX; Department of Physical Medicine and Rehabilitation, UTHealth, Houston, TX
Luis Leon-Novelo, School of Public Health- Biostatistics and Data Science Department, University of Texas Health Sciences Center at Houston, Houston, TX
Esther Ngan, Department of Radiology, Baylor College of Medicine, Houston, TX
Kathleen R. Bell, Department of Physical Medicine & Rehabilitation, University of Texas Southwestern, Dallas, Texas
John D. Corrigan, Department of Physical Medicine & Rehabilitation, The Ohio State University, Columbus, OH
Simon Driver, Department of Physical Medicine and Rehabilitation, Baylor Scott and White Institute for Rehabilitation, Dallas, Texas
Laura E. Dreer, Department of Physical Medicine & Rehabilitation, University of Alabama at Birmingham, Birmingham, AL
Anthony H. Lequerica, Kessler Foundation, East Hanover, New Jersey, and Department of Physical Medicine and Rehabilitation, Rutgers-New Jersey Medical School, Newark, NJ
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