Neuropsychiatric Presentations due to Traumatic Brain Injury in Cognitively Normal Older Adults

Abstract

Neuropsychiatric symptoms (NPS) are common sequelae of traumatic brain injuries (TBI) among adults. However, little is known about NPS associated with a history of TBI in adults relative to adults without a history of TBI and to what extent NPS may be modulated by sex and other factors. Using the National Alzheimer's Coordinating Center Uniform Data Set, we examined the association between Neuropsychiatric Inventory-Questionnaire (NPI-Q) scores in cognitively normal older adults with and without a history of TBI. A binomial logistic regression model was used to examine NPI-Q domains in adults with a history of TBI (n = 266) versus without a history of TBI (n = 1508). History of TBI, sex, age, and body mass index were used as covariates. Adults with a history of TBI had a greater probability of exhibiting agitation, anxiety, apathy, disinhibition and aberrant motor behavior relative to adults without a history of TBI. In terms of sex differences, males with and without a history of TBI had an increased likelihood of agitation, apathy, disinhibition, and apnea, whereas females had an increased likelihood of anxiety and insomnia relative to males. Our study confirms that history of TBI is associated with an increased prevalence of specific NPS, including agitation, anxiety, apathy, disinhibition, and aberrant motor behavior. Given that the aforementioned NPS are linked through different pathways, damage to any of them may cause an alteration in behavior. As well, NPS appear to be modulated by sex, with symptoms differing between males and females. Our research suggests future studies examining NPS sequelae of TBI should adjust for sex.

Introduction

A traumatic brain injury (TBI) is defined as an injury to the head causing a change in normal brain function.¹ TBIs have a large incidence across the population, being the cause of 2.87 million emergency department visits in the United States in 2014 alone, with 837,000 of them being for children.²

Some of the most important predictors of long-term outcomes of TBI are neuropsychiatric symptoms (NPS). These include cognitive and mood disorders, along with changes in motivation and behavior.^3,4 Specifically, these NPS increase the risk of psychological distress experienced by the individual and decrease the ease of their social reintegration.⁵ TBIs have been shown to increase the incidence of mood disorders, leading to increased social isolation, with changes in apathy and agitation being some of the leading contributors.⁶

Sleep disturbances such as insomnia and apnea are commonly experienced after TBIs, which can compromise recovery by increasing comorbidities.⁷ These can include depression, anxiety, irritability, cognitive defects, and functional impairments, which can overlap with NPS. Increased body mass index (BMI) is associated with increased sleep disturbances,⁷ making it an important factor to consider when looking at NPS risk after TBI.

A long-term consequence of TBI is the onset of dementia.² Experiencing a single episode of TBI from early to mid-life is associated with an increased risk of dementia.⁸ Moderate and severe TBIs have the best evidence of increasing risk of dementia (between 2-4–fold). The relative risk of dementia progression after a severe TBI is 5-15%.^8,9

The objective of this study was to explore NPS using neuropsychiatric inventory questionnaire (NPI-Q) scores in cognitively normal adults with and without a history of TBI through the use of National Alzheimer Coordination Center's Uniform Data Set (NACC-UDS). We hypothesized that participants with a history of TBI would exhibit higher levels of NPS, compared with participants without a history of TBI and predicted that sex may play a modulatory role in the appearance of NPS.

Methods

Participants

The National Alzheimer's Coordinating Center (NACC) maintains a database that pools information from approximately 31 Alzheimer's Disease Centers (ADCs).¹⁰ For the purpose of this study, data from the Uniform Data Set (UDS) was used. The UDS is a longitudinal database and is publicly accessible. More information on the contents of UDS can be referenced by Beekly and colleagues¹¹ and Besser and colleagues.¹²

Participants aged ≥50 and cognitively normal as defined by the NACC-UDS variable were included in this study. Data was extracted from this sample by filtering the NACC-UDS variable. All participants from this sample who presented with a diagnosis of stroke, transient ischemic attack, Parkinson's disease, seizures, drug abuse, schizophrenia, and bipolar disorder were excluded from the sample and all calculations. This sample was then filtered for history of TBI, leading to two groups, one with a history of TBI and one without. The final sample was 1774 participants, with 266 with a history of TBI, and 1508 participants without a history of TBI. These participants were examined for NPI-Q scores, along with sleep disturbance variables (Insomnia, Apnea). Data for insomnia and apnea was extracted from past medical history reported in NACC-UDS.

Measures

A validated retrospective (1-month) informant-based interview/questionnaire that assesses neuropsychiatric symptoms is called the Neuropsychiatric Inventory (NPI). The more recent form of this questionnaire has an additional two fields (nighttime behaviors and appetite) to the pre-existing 10 domains and is referred to as the NPI-Q. The NPI-Q measures NPS by using questions regarding each domain (Delusions, Hallucinations, Agitation/Aggression, Dysphoria/Depression, Anxiety, Euphoria/Elation, Apathy/Indifference, Disinhibition, Irritability/Lability, Aberrant Motor Behavior, Nighttime Behavior, Appetite/Eating), and asks the informant to rank each of them in severity ranging from 1-3, where no change is 0. The validity of NPI-Q has been tested to show adequate test–retest reliability and convergent validity similar to NPI ratings, in addition to high correlation of symptom severity scales between NPI-Q and NPI.¹³ The NPI-Q was used in this study as a means of evaluating the neuropsychiatric impact of a TBI. The Montreal-Cognitive Assessment (MoCA) is a cognitive screening test for the detection of mild cognitive impairment (MCI) or Alzheimer's disease. The Geriatric Depression Scale (GDS) is a self-reported measure of depression among the elderly population.

Statistical analysis

This study consisted of a generalized linear model estimated by generalized estimating equations.¹⁴ Specifically, a binomial logistic regression model was used to examine NPI-Q domains in participants with a history of TBI versus without a history of TBI. Sex, age, and body mass index (BMI) as defined by the height and weight of a person were used as covariates.

To determine if variables differ statistically for participants with a history of TBI versus without a history of TBI, a Mann-Whitney U test¹⁵ was used due to the non-parametric nature of the variables (age, BMI, years of education, MoCA, and GDS). A chi-squared test¹⁶ was used to observe significant association between sex and TBI, as these are nominal variables.

In the logistic regression model, the binary dependent variable (having a certain NPI-Q domain) was coded as 0 (do not exhibit) or 1 (does exhibit). Exponentiation of the B coefficient (EXP(B)) can be interpreted as a probability percentage change of the outcome event for each unit increase in the predictor.¹⁷ All continuous variables (age, BMI) were checked against other curves, such as logarithm and power, and confirmed for linearity using trend analysis. Multi-collinearity was checked using linear regression for each independent variable in each model against each other. None of the predictors had a tolerance less than 0.7. A Spearman correlation¹⁸ also was run to see associations between variables. All statistical analyses were done using SPSS 26. All information regarding logistic regression procedure can be found on IBM SPSS regression 26 manual and the interpretation of the output can be found on Bors' Data Analysis for the Social Sciences: Integrating Theory and Practice. ¹⁹

Results

There was a total of 1774 subjects and 1508 had a history of TBI. There were 612 male subjects (average: age = 68.7, BMI = 27.84, years of education = 16.4, MoCA = 26.4, GDS = 1.4) and 1162 female subjects (average: age = 69.8, BMI = 27.74, years of education = 16.3, MoCA = 26.2, GDS = 1.1). All of the demographic data (age, BMI, years of education, MOCA, and GDS) can be found in Table 1. A chi-squared test was conducted between sex and TBI, and there was a significant association between the two variables (X ² (1, N = 1774) = 13.470, p < 0.005; Table 1). The strength of the association as indicated by Phi was 0.87. In our sample, females were less likely to have a TBI. A Mann–Whitney U test was conducted to compare the differences in age (U = 184760, p = 0.040), BMI (U = 182802, p = 0.886), MoCA (U = 199222.5, p = 0.076), GDS (U = 219080, p = 0.003), and years of education (U = 208617, p = 0.286) between those who had a history of TBI and those who did not.

Table 1.

Demographics

Variables	TBI		Without TBI
	Mean ± SD	Range	Mean ± SD	Range	p value
TBI (count)	1508		266
Male (count)	118 (44.4%)		494 (32.8%)		Chi-squared test X² (1, N = 1774) = 13.470, p < 0.005^***
Female(count)	148 (55.6%)		1014 (67.2%)		Chi-squared test X² (1, N = 1774) = 13.470, p < 0.005^***
Age (years)	68.7 ± 8.5	50-89	69.8 ± 7.8	50-101	Mann- Whitney U test(U = 184760, p = 0.040^*)
BMI	27.84 ± 5.73		27.74 ± 5.42		(U = 182802, p = 0.886)
Education (years)	16.4 ± 2.9		16.3 ± 2.6		(U = 208617, p = 0.286)
MoCA	26.4 ± 2.7		26.2 ± 2.7		(U = 199222.5, p = 0.076)
GDS	1.4		1.1		(U = 219080, p = 0.003^**)

Asterisk denotes a significant p value: ^*** p < 0.005, ^** p < 0.01, ^* p < 0.05.

Mean and standard deviation was reported for each domain between the two groups. A chi-squared test was used to test for significant associations between sex and TBI. A Mann-Whitney U test was used to test for significant differences between age, BMI, years of education, MoCA, and GDS.

TBI, traumatic brain injury; SD, standard deviation; BMI, body mass index; MoCA, Montreal Cognitive Assessment; GDS, Geriatric Depression Scale.

In Model 1 (Table 2), with a history of TBI versus without a history of TBI, sex, age and BMI were used to build a logistic regression model to predict the 12 NPI-Q domains and sleep disturbance variables (apnea and insomnia). Model 1a through 1g were significant for agitation (p = 0.006), anxiety (p < 0.001), apathy (p < 0.001), disinhibition (p = 0.003), aberrant motor behavior (p = 0.004), apnea (p < 0.005), and insomnia (p < 0.005). The rest of the NPI-Q domains (delusions, hallucinations, depression/dysphoria, elation/euphoria, irritability/lability, nighttime behaviors, and appetite/eating) were not significant (p > 0.05). Participants with a history of TBI were associated with increased odds of exhibiting agitation (p = 0.011), anxiety (p = 0.049), apathy (p = 0.003), disinhibition (p = 0.025), and aberrant motor behavior (p = 0.004). Males in the combined sample (with and without history of TBI) had increased odds of exhibiting agitation (p = 0.029), apathy (p = 0.004), disinhibition (p = 0.009), and apnea (p < 0.005). In contrast, females in the combined sample had increased odds of exhibiting anxiety (p = 0.002) and insomnia (p < 0.005). Younger participants were associated with increased odds of exhibiting anxiety (p = 0.001) and insomnia (p < 0.005). Having a higher BMI was associated with increased apathy (p = 0.016) and apnea (p < 0.005). A Spearman correlation was conducted as a sub-analysis and showed significant correlations (p < 0.05) between most outcome variables (including insomnia and apnea; Table 3).

Table 2.

Statistics for Model 1: With a History of TBI vs. Without a History of TBI, Sex, Age, and BMI

		B	SE	Wald	Sig.	Exp(B)	95% CI for EXP(B)		Cox and Snell R square	Nagelkerke R square
		B	SE	Wald	Sig.	Exp(B)	Lower	Upper	Cox and Snell R square	Nagelkerke R square
Model 1a agitation	1 = with TBI; 0 = without TBI	0.773	0.306	6.391	0.011^*	2.167	1.190	3.948	0.009	0.034
	1 = Male; 0 = Female	0.592	0.270	4.785	0.029^*	1.807	1.063	3.070
	Age	0.012	0.017	0.519	0.471	1.012	0.979	1.047
	BMI	0.038	0.022	2.980	0.084	1.039	0.995	1.085
	Constant	−5.623	1.469	14.648	0.000^***	0.004

Model 1b anxiety	1 = with TBI; 0 = without TBI	0.443	0.225	3.871	0.049^*	1.557	1.002	2.421	0.016	0.036
	1 = Male; 0 = Female	−0.643	0.210	9.326	0.002^**	0.526	0.348	0.794
	Age	−0.038	0.012	10.615	0.001^**	0.963	0.941	0.985
	BMI	−0.011	0.016	0.521	0.470	0.989	0.959	1.020
	Constant	0.695	0.962	0.544	0.461	2.003

Model 1c apathy	1 = with TBI; 0 = without TBI	0.969	0.326	8.822	0.003^*	2.636	1.391	4.998	0.015	0.063
	1 = male; 0 = female	0.883	0.303	8.481	0.004^**	2.417	1.335	4.379
	Age	0.019	0.019	0.980	0.322	1.019	0.982	1.058
	BMI	0.057	0.024	5.830	0.016^*	1.059	1.011	1.109
	Constant	−7.068	1.648	18.387	0.000^***	0.001

Model 1d disinhibition	1 = with TBI; 0 = without TBI	0.799	0.355	5.051	0.025^*	2.223	1.108	4.461	0.010	0.047
	1 = male; 0 = female	0.845	0.322	6.887	0.009^**	2.328	1.238	4.375
	Age	−0.007	0.020	0.122	0.727	0.993	0.954	1.033
	BMI	0.044	0.026	2.925	0.087	1.045	0.994	1.099
	Constant	−4.934	1.721	8.217	0.004^**	0.007

Model 1e aberrant motor behaviour	1 = with TBI; 0 = without TBI	1.284	0.446	8.281	0.004^**	3.611	1.506	8.659	0.010	0.070
	1 = male; 0 = female	0.733	0.437	2.820	0.093	2.082	0.885	4.899
	Age	−0.034	0.028	1.556	0.212	0.966	0.916	1.020
	BMI	0.043	0.034	1.613	0.204	1.044	0.977	1.116
	Constant	−3.805	2.262	2.831	0.092	0.022

Model 1f apnea	1 = with TBI; 0 = without TBI	0.200	0.203	0.970	0.325	1.221	0.821	1.817	0.075	0.137
	1 = male; 0 = female	0.887	0.153	33.469	0.000^***	2.427	1.797	3.277
	Age	0.010	0.010	1.050	0.306	1.010	0.991	1.030
	BMI	0.118	0.012	90.549	0.000^***	1.125	1.098	1.152
	Constant	−6.398	0.854	56.177	0.000^***	0.002

Model 1g insomnia	1 = with TBI; 0 = without TBI	0.323	0.192	2.829	0.093	1.381	0.948	2.011	0.019	0.036
	1 = Male; 0 = Female	−0.668	0.170	15.406	0.000^***	0.513	0.367	0.716
	Age	−0.033	0.009	12.487	0.000^***	0.967	0.950	0.985
	BMI	−0.012	0.013	0.869	0.351	0.988	0.964	1.013
	Constant	0.882	0.769	1.317	0.251	2.415

Asterisk denotes a significant p value: ^*** p < 0.005, ^** p < 0.01, ^* p < 0.05.

All predictors were added at the baseline and all of the data were collected from the National Alzheimer Coordination Center database. The dependent variable was derived from the 12 Neuropsychiatric Inventory-Questionnaire (NPI-Q) domains. Insomnia and apnea were obtained from the reported medical history. Only the NPI-Q domains with significant results were included in the table. Degree of freedom was 1 for every model. Beta (B) coefficient reflects the degree of change to the dependent variable for every one unit of increase or decrease in the independent variable. Standard error is used to test if the parameter is significantly different from 0. Wald (Wald chi-squared test) tests the null hypothesis (H₀: the coefficient is 0) and the Sig (the p value) is used to determine if the null hypothesis should be rejected or accepted. Exponentiation of the B coefficient (Exp(B)) is the odds ratio for the predicators. A 95% CI was calculated. Cox and Snell R square and Nagelkerke R Square are two different tests that measure the amount of variability that the dependent variable can explain in the model (from minimum value of 0 to a maximum value of 1).

TBI, traumatic brain injury; CI, confidence interval; SE, standard error; BMI, body mass index.

Table 3.

Spearman Correlation between NPI-Q Domains

			DEL	HALL	AGIT	DEPD	ANX	ELAT	APA	DISN	IRR	MOT	NITE	APP	APNEA	INSOMN
Spearman's rho	Delusion(DEL)	Correlation coefficient	1.000	.407^**	.147^**	.078^**	.088^**	.200^**	.056^*	.237^**	.087^**	.081^**	-.018	.045	.037	.006
		Sig. (2-tailed)	.	.000	.000	.001	.000	.000	.023	.000	.000	.001	.480	.065	.135	.812
		N	1651	1651	1649	1649	1649	1651	1648	1650	1651	1648	1616	1646	1610	1646
	Hallucination(HALL)	Correlation coefficient	.407^**	1.000	.055^*	-.017	.071^**	.121^**	-.009	.067^**	.028	.102^**	.032	-.010	.092^**	-.019
		Sig. (2-tailed)	.000	.	.025	.495	.004	.000	.729	.006	.258	.000	.193	.685	.000	.432
		N	1651	1651	1649	1649	1649	1651	1648	1650	1651	1648	1616	1646	1610	1646
	Agitation (AGIT)	Correlation coefficient	.147^**	.055^*	1.000	.204^**	.233^**	.241^**	.212^**	.358^**	.399^**	.313^**	.090^**	.156^**	.059^*	.035
		Sig. (2-tailed)	.000	.025	.	.000	.000	.000	.000	.000	.000	.000	.000	.000	.017	.159
		N	1649	1649	1649	1647	1647	1649	1646	1648	1649	1646	1615	1644	1608	1644
	Depression(DEPD)	Correlation coefficient	.078^**	-.017	.204^**	1.000	.314^**	.108^**	.190^**	.199^**	.306^**	.116^**	.261^**	.169^**	.054^*	.083^**
		Sig. (2-tailed)	.001	.495	.000	.	.000	.000	.000	.000	.000	.000	.000	.000	.032	.001
		N	1649	1649	1647	1649	1647	1649	1646	1648	1649	1646	1615	1644	1608	1644
	Anxiety(ANX)	Correlation coefficient	.088^**	.071^**	.233^**	.314^**	1.000	.122^**	.175^**	.210^**	.309^**	.113^**	.181^**	.101^**	.031	.103^**
		Sig. (2-tailed)	.000	.004	.000	.000	.	.000	.000	.000	.000	.000	.000	.000	.211	.000
		N	1649	1649	1647	1647	1649	1649	1646	1648	1649	1646	1615	1644	1608	1644
	Elation(ELAT)	Correlation coefficient	.200^**	.121^**	.241^**	.108^**	.122^**	1.000	.093^**	.325^**	.208^**	.258^**	.029	.139^**	.073^**	-.003
		Sig. (2-tailed)	.000	.000	.000	.000	.000	.	.000	.000	.000	.000	.240	.000	.003	.919
		N	1651	1651	1649	1649	1649	1651	1648	1650	1651	1648	1616	1646	1610	1646
	Apathy(APA)	Correlation coefficient	.056^*	-.009	.212^**	.190^**	.175^**	.093^**	1.000	.192^**	.225^**	.106^**	.104^**	.173^**	.074^**	-.015
		Sig. (2-tailed)	.023	.729	.000	.000	.000	.000	.	.000	.000	.000	.000	.000	.003	.540
		N	1648	1648	1646	1646	1646	1648	1648	1647	1648	1645	1613	1644	1607	1643
	Disinhibition(DISN)	Correlation coefficient	.237^**	.067^**	.358^**	.199^**	.210^**	.325^**	.192^**	1.000	.274^**	.208^**	.099^**	.062^*	.072^**	.022
		Sig. (2-tailed)	.000	.006	.000	.000	.000	.000	.000	.	.000	.000	.000	.012	.004	.379
		N	1650	1650	1648	1648	1648	1650	1647	1650	1650	1647	1615	1645	1609	1645
	Irritability (IRR)	Correlation coefficient	.087^**	.028	.399^**	.306^**	.309^**	.208^**	.225^**	.274^**	1.000	.206^**	.140^**	.178^**	.058^*	.022
		Sig. (2-tailed)	.000	.258	.000	.000	.000	.000	.000	.000	.	.000	.000	.000	.021	.375
		N	1651	1651	1649	1649	1649	1651	1648	1650	1651	1648	1616	1646	1610	1646
	Aberrant motor behaviour (MOT)	Correlation coefficient	.081^**	.102^**	.313^**	.116^**	.113^**	.258^**	.106^**	.208^**	.206^**	1.000	.111^**	.089^**	.040	.032
		Sig. (2-tailed)	.001	.000	.000	.000	.000	.000	.000	.000	.000	.	.000	.000	.106	.188
		N	1648	1648	1646	1646	1646	1648	1645	1647	1648	1648	1615	1643	1607	1643
	Nighttime behaviour (NITE)	Correlation coefficient	-.018	.032	.090^**	.261^**	.181^**	.029	.104^**	.099^**	.140^**	.111^**	1.000	.099^**	.102^**	.155^**
		Sig. (2-tailed)	.480	.193	.000	.000	.000	.240	.000	.000	.000	.000	.	.000	.000	.000
		N	1616	1616	1615	1615	1615	1616	1613	1615	1616	1615	1616	1613	1576	1611
	Appetite(APP)	Correlation coefficient	.045	-.010	.156^**	.169^**	.101^**	.139^**	.173^**	.062^*	.178^**	.089^**	.099^**	1.000	.075^**	.030
		Sig. (2-tailed)	.065	.685	.000	.000	.000	.000	.000	.012	.000	.000	.000	.	.003	.222
		N	1646	1646	1644	1644	1644	1646	1644	1645	1646	1643	1613	1646	1605	1641
	APNEA	Correlation Coefficient	.037	.092^**	.059^*	.054^*	.031	.073^**	.074^**	.072^**	.058^*	.040	.102^**	.075^**	1.000	.010
		Sig. (2-tailed)	.135	.000	.017	.032	.211	.003	.003	.004	.021	.106	.000	.003	.	.673
		N	1610	1610	1608	1608	1608	1610	1607	1609	1610	1607	1576	1605	1722	1718
	Insomnia(INSOMN)	Correlation Coefficient	.006	-.019	.035	.083^**	.103^**	-.003	-.015	.022	.022	.032	.155^**	.030	.010	1.000
		Sig. (2-tailed)	.812	.432	.159	.001	.000	.919	.540	.379	.375	.188	.000	.222	.673	.
		N	1646	1646	1644	1644	1644	1646	1643	1645	1646	1643	1611	1641	1718	1760

Correlation is significant at the 0.01 level (2-tailed) and ^* denotes correlation is significant at the 0.05 level (2-tailed).

Discussion

In this study of older adults extracted from the NACC-UDS, participants with a history of TBI had a significantly higher NPS burden in domains of agitation, anxiety, apathy, disinhibition and aberrant motor behavior, compared with participants without a history of TBI. Males in the combined sample had an increased likelihood of agitation, apathy, disinhibition, and apnea, whereas females had an increased likelihood of anxiety and insomnia.

It is evident from previous findings that NPS are highly prevalent post-TBI.³ The presence of NPS can affect the level of treatment, leading to longer rehabilitation stays and lower cognition scores.^20,21 Thus, it needs to be considered while planning for management of patients with TBI. Generally, apathy, and anxiety are more commonly observed, and agitated behavior, especially in the acute recovery period.³ While these behaviors can disappear after the acute stage, it has been shown that they can continue into the chronic phase of recovery, as well.³ This is in accordance with our results where we saw a link between history of TBI and NPS.

Our study showed that history of TBI was associated with increased agitation/aggression, anxiety, disinhibition/impulsivity, apathy, and aberrant motor behavior. Aggression post-TBI is common and can be associated with characteristics such as restlessness, confusion, along with physical and verbal aggression.²² Moreover, aggression has been reported in 20-41% of patients post-TBI in acute care facilities, and even up to 70% of patients in rehabilitation units.^22

–25 Disinhibition/impulsivity has been a common presentation post-TBI.²⁶ While a lot of research assesses impulsivity in the time immediately post-TBI, studies have shown that impulsivity can manifest much later and even in events such as mild TBIs.²⁷ Apathy commonly presents after TBI and can affect participation in rehabilitation along with cognitive function.⁶ According to our study, participants had higher odds of exhibiting aberrant motor behavior if they had a TBI. Our findings are consistent with previous studies that suggest aberrant motor behavior is a common sequalae of TBI.³ Anxiety was also a significant NPS among patients with a history of TBI in this study, which is a common finding in the literature, as well.^28,29

With regard to sleep disturbances, the model generated that TBI is not a significant predictor of increased likelihood of insomnia or apnea. However, a meta-analysis conducted by Matias and Alvaro indicates that 25-29% of patients experience sleep disturbances such as insomnia and apnea post-TBI.⁷ The discrepancy observed between our findings and the literature might be explained due to the limitation of the informant-based nature of NPI-Q. Another possible explanation could be due to variation in gender demographics in Matias and Alvaro's meta-analysis, which had a 71% male sample, whereas we had a 44% male sample. We did, however, find in our combined sample that males had higher odds of exhibiting apnea and females had higher odds of exhibiting insomnia.

Sex differences can play a role in the onset and presentation of several NPS post-TBI.^30,31 However, there is a lack of literature explaining these sex differences. Males are up to three times more likely to sustain TBIs than females³²; therefore, there is a mismatch on the quality and quantity of research regarding sex differences. Females are disproportionately underrepresented compared with males, leading to inequal sample sizes,^33,34 and this imbalance can skew the statistics.

In our combined sample, males showed increased odds of having agitation, disinhibition apathy, and apnea compared with females. A potential explanation for the observed sex differences might relate to hormonal differences. Increased testosterone in males in both human and mice studies has been linked to aggression and disinhibition, respectively.^35,36 In addition, apathy has been observed to increase with age, especially in men.³⁷ Males are up to three times more likely to have apnea than females,³⁸ which was seen in our participants, as well.

Female participants had higher odds of exhibiting anxiety compared with males. A potential explanation for this observed finding could be that females exhibit more anxiety, as they are more likely to report emotional symptoms over men, who report more changes in motor behaviors, impulsivity, and attention.^39

–43 Our results are also consistent with literature, where anxiety is more commonly reported in women over men.⁴⁴ Females in our combined sample also had higher odds of experiencing insomnia, which is consistent with prior studies.⁴⁵

While our study revealed a number of important and interesting conclusions, there are some limitations that should be pointed out. There were approximately 11% of cases with incomplete NPI-Q data. However, there was still a sufficient sample size (over 1600 cases). Based on the Cox and Snell R Square and Nagelkerke R ², our model was unable to explain much variance. There were outliers (beyond 2 standard deviations) in our predictor variables. Many of the NPI-Q domains were significantly correlated with each other but our model did not account for this. Also, our model could not differentiate if sex differences were due to history of TBI and not just sex differences observed in the normal population. These should be addressed in future studies. There was a lack of information on the time of NPS presentation, severity, and mechanism of TBI. The NPI-Q domain severity was self-reported and not a clinician diagnosis.

Our study suggests that NPS are common sequelae of TBIs and that NPS burden differs in females versus males. Specifically, we found NPS were more attenuated in females relative to males when we analyzed a combined sample. Further research is required to replicate this finding and identify potential underlying neural mechanisms, incorporating features such as agitation, anxiety, apathy, and disinhibition. Our findings suggest that future research examining NPS in adults with TBI should be adjusted for sex.

Footnotes

Acknowledgments

We would like to thank the NACC foundation for allowing us the use of their database. The NACC database is funded by National Institute on Aging (NIA)/National Institutes of Health Grant U01 AG016976. NACC data are contributed by the NIA-funded ADCs: P30 AG019610 (PI Eric Reiman, MD), P30 AG013846 (PI Neil Kowall, MD), P30 AG062428-01 (PI James Leverenz, MD) P50 AG008702 (PI Scott Small, MD), P50 AG025688 (PI Allan Levey, MD, PhD), P50 AG047266 (PI Todd Golde, MD, PhD), P30 AG010133 (PI Andrew Saykin, PsyD), P50 AG005146 (PI Marilyn Albert, PhD), P30 AG062421-01 (PI Bradley Hyman, MD, PhD), P30 AG062422-01 (PI Ronald Petersen, MD, PhD), P50 AG005138 (PI Mary Sano, PhD), P30 AG008051 (PI Thomas Wisniewski, MD), P30 AG013854 (PI Robert Vassar, PhD), P30 AG008017 (PI Jeffrey Kaye, MD), P30 AG010161 (PI David Bennett, MD), P50 AG047366 (PI Victor Henderson, MD, MS), P30 AG010129 (PI Charles DeCarli, MD), P50 AG016573 (PI Frank LaFerla, PhD), P30 AG062429-01(PI James Brewer, MD, PhD), P50 AG023501 (PI Bruce Miller, MD), P30 AG035982 (PI Russell Swerdlow, MD), P30 AG028383 (PI Linda Van Eldik, PhD), P30 AG053760 (PI Henry Paulson, MD, PhD), P30 AG010124 (PI John Trojanowski, MD, PhD), P50 AG005133 (PI Oscar Lopez, MD), P50 AG005142 (PI Helena Chui, MD), P30 AG012300 (PI Roger Rosenberg, MD), P30 AG049638 (PI Suzanne Craft, PhD), P50 AG005136 (PI Thomas Grabowski, MD), P30 AG062715-01 (PI Sanjay Asthana, MD, FRCP), P50 AG005681 (PI John Morris, MD), P50 AG047270 (PI Stephen Strittmatter, MD, PhD).

Funding Information

We would also like to thank the St. Michael’s Hospital Foundation Heather and Eric Donnelly Endowment.

Author Disclosure Statement

No competing financial interests exist.

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