









































53

Graduate Student Journal of Psychology
Spring 2024 - Vol. 22

Copyright 2024 by the Department of Counseling and Clinical Psychology
Teachers College, Columbia University

The Effects of Psychosocial and Traumatic Stressors on 
MCI Diagnosis

Katherine Goulden
Department of Psychiatry and Behavioral Sciences, Stanford University

 There is no single cause of mild cognitive im-
pairment (MCI), a neurodegenerative condition 
defined as “clinically significant memory impair-
ment that does not meet the criteria for dementia” 
(Petersen, 2011, p. 2). MCI is an amnestic disorder 
representing an intermediate stage between norma-
tive aging and Alzheimer's dementia. Though all 
MCI demonstrate neuropsychological impairment, 
diagnosis can be broken into subtypes amnestic or 
non-amnestic (Rountree et al., 2007) for more sta-
ble estimates of prevalence and rates of returning 
to normal cognitive functioning (Jak et al., 2009).
 As age increases, so does the risk of developing 
MCI. A lifetime’s worth of factors and exposures can 
affect the risk of developing this unhealthy form of 
cognitive decline. Apolipoprotein genotype (Tang et 
al., 2023), education (Tervo et al., 2004), and general 
cognitive ability during adulthood (Corbo et al., 2023) 
have been associated with an increased risk of develop-
ing MCI, but neither the exact causes of MCI nor the 
influence of a lifetime of stressors is completely un-
derstood. There is no known cure for MCI, thus the 
identification of modifiable risk factors is important 
for prevention and earlier detection of those at risk. 
Although research on MCI risk factors is extensive, 
the identification of the role of stress is incomplete 
and has never been investigated in a sample of twins.
 Exposure to stress in adulthood and midlife has 
been shown by previous studies to increase the likeli-

hood of an MCI diagnosis on the neurobiological level 
(Kritikos et al., 2023; Song et al., 2020). Stress occurs 
during a threat and when environmental demands 
exceed adaptive capacity, with threat associated  exter-
nal and internal stimuli eliciting the reactions defined 
as stressors. Potential stressors encountered during 
adulthood include a long list of adverse psychosocial 
and physical forces. A psychosocial factor is defined by 
Hemingway and Marmot (1999) as phenomena that 
are “potentially related to the social environment and 
to pathophysiologic changes…Psychosocial factors may 
act alone or combine in clusters and may exert effects 
at different stages of the life course” (p. 2). The stressor 
can be a discrete event such as the death of a spouse, or 
a prolonged exposure, such as racial discrimination ex-
perienced by minority Americans (Turner et al., 2017). 
In the Diagnostic and Statistical Manual of Mental 
Disorders (4th ed.; DSM-4), Criterion A1, traumatic 
events are defined as “an event that involves actual or 
threatened death or serious injury, or other threat to 
one’s personal integrity” and includes “learning about 
the unexpected or violent death, serious harm, or 
threat of death or injury experienced by a family mem-
ber or other close associate” (First et al., 2004, p. 14).
 Posttraumatic stress disorder (PTSD) is a disorder 
that can be present at any age. It is triggered by either 
witnessing or experiencing an event that presents a 
threat to one’s safety. Symptoms may include flash-
backs, nightmares, severe anxiety, and uncontrollable 

Background and Objective: Toxic stress exposure can have effects across the lifespan. Studies of civilians and 
veterans suggest a connection between psychosocial and traumatic stressor exposure in adulthood and a di-
agnosis of dementia later in life. The objective of this study was to investigate the impact of psychosocial and 
traumatic stressors on rates of MCI (Mild Cognitive Impairment) diagnosis in Vietnam Era Twin Study of 
Aging participants.  Methods: 1,237 twin participants from the VETSA study were aged 61.72 ± 2.44 years at 
the time of data collection. Traumatic stress was measured by clinical interviewing, with psychosocial stressors 
quantified by self-report measures. Neuropsychological assessment determined MCI diagnosis. Previously con-
ducted genotyping determined ApoE genotype. Mixed model analysis was used to determine effects on MCI 
diagnosis. Results: Our results from the mixed model analysis did not find a significant relationship between 
psychosocial and traumatic stress exposure and MCI diagnosis. PTSD diagnosis, measured by the DIS-III-R, 
collected for the Harvard Drug Study in 1996 (F = 0.249, p = 0.618) does not have a significant effect on MCI 
diagnosis. Life stress exposure, measured by Holmes and Rahe (1967), (F = 0.249, p = 0.618) does not have a 
significant effect on MCI diagnosis. Significant associations were determined using the Type III fixed effects. As-
sociations were considered statistically significant at p < 0.05, two-tailed. Implications: Few subjects in Wave 
2 of VETSA had MCI (n = 147), due in part to the age of the participants at the time (Mean 61.72 ± (2.44 
years)). This led to a lack of power in our analysis. Future studies should examine all available VETSA data.
 Keywords: veterans, mild cognitive impairment, psychosocial stress, traumatic stress



54

GOULDEN

thoughts about the event (Hathaway et al., 2010). It 
is also associated with cognitive impairments unique 
to the condition in the domains of verbal learning, 
speed of information processing, attention, work-
ing memory, and verbal memory (Scott et al., 2015). 
A neurobiological pathway has been proposed to 
describe how PTSD influences dementia, with trau-
matic exposure triggering persistent over-activation 
of the hypothalamic-pituitary-adrenal (HPA) axis 
and the adrenergic system (Leister & Menke, 2020).
 The literature on the impact of psychosocial and 
traumatic stress on MCI outcomes has been mixed. 
A study by Wang et al., (2018) of non-military el-
ders of both sexes found a significant dose-depen-
dent relationship between PTSD symptom sever-
ity and developing dementia later in life. A study by 
Peavy et al., (2009) also found that chronic stress and 
stressful life events led to general memory decline in 
cognitively normal (CN) individuals as well as those 
diagnosed with MCI. As for conversion from CN to 
MCI, Peavy et al., (2012) did not find an association 
between stressful experiences and change to MCI. 
These findings could result from the variability of 
ways that stress and PTSD were operationalized.
 Although research with elderly veteran partici-
pants varies from that of elderly civilian participants, 
most VETSA participants were not exposed to combat 
(Kremen et al., 2013). However, veterans are exposed 
to factors that are unique to military service (Siben-
er, 2014). In a study of 181,093 elderly veterans by 
Yaffe et al. (2010), the 7-year cumulative incident de-
mentia rate amongst veterans with PTSD was 10.6% 
while those without PTSD had a rate of 6.6%. While 
Yaffe et al. (2010) did not specify the veterans’ era, 
in another study greater incidence of MCI was ob-
served specifically in Vietnam Era veterans who had 
also been diagnosed with PTSD (Weiner et al., 2017).
 Previous studies have indicated that psychosocial 
factors such as racism (Moon et al., 2019), workplace 
adversity (Nabe-Nielsen, et al., 2019), and divorce 
(Eriksson, 2015) are risk factors for dementia. But in a 
meta-analysis of 24 longitudinal studies examining cat-
egories of toxic psychosocial and trauma-related stress, 
Bougea et al. (2022) found suggestive, yet non-robust 
evidence that psychosocial and traumatic types of stress 
are associated with increased risk of dementia in later life.
 As VETSA participants have aged, the focus of 
the multi-institutional VETSA study has shifted from 

a focus on substance use to early identification of risk 
for MCI and Alzheimer’s disease (AD). VETSA par-
ticipants are all part of the Vietnam Era Twin Regis-
try. VETSA selection criteria were (1) being in one’s 
fifties at the time of recruitment and (2) that both 
twins in a pair had to be willing to participate in the 
baseline assessment (Kremen et al., 2013). A narrow 
subject age range of participants enhances VETSA’s 
ability to examine within-individual differences and 
change over time. Another key aspect of the study de-
sign was an extensive neuropsychological test battery. 
The study is also unique in that we have cognitive as-
sessment scores from participants when they were in-
ducted into the military at the age of 17 to 25 years 
old. The present study was designed to investigate the 
influence of psychosocial and traumatic stressors on 
MCI diagnosis. It is hypothesized that participants 
with exposure to psychosocial and traumatic stress-
ors would be more likely to have developed MCI.

Methods
Participants 
 VETSA participants were recruited from the 
Harvard Drug Study (Tsuang et al., 2001). 1,237 
twins participated (349 monozygotic pairs, 265 dizy-
gotic pairs, and 9 unpaired). Attrition-replacement 
participants were included as a subset of the Wave 2 
participants. The attrition-replacement participants 
are twin pairs from the Vietnam Era Twin Registry 
in the same age range as the returning Wave 2 partic-
ipants. At Wave 2 of data collection, the mean age of 
participants was 61.72 ± (2.44 years). All VETSA par-
ticipants were in the military sometime between 1965 
and 1975. The majority did not see combat or serve 
in Vietnam. The sample was entirely male and 95.4% 
(n = 712) white. Black Americans made up 4% (n =    
30), Hispanics represented 0.3% (n = 2) and 0.3% were 
missing information on race (n = 2). The average life-
time education was 12.4 (± 1.3 years) (see Appendix).
Instrumentation
Holmes and Rahe Stress Scale
 Life stressors were measured using the Holmes 
and Rahe Social Readjustment Rating Scale. The 
Holmes and Rahe Social Readjustment Rating 
Scale is a 100-item questionnaire (α = .8458), com-
posed of 43 life events. An individual's total score 
measures the amount of stress the individual has ex-
perienced in the past year. The tool has been exten-



55

STRESSORS ON MCI DIAGNOSIS

sively studied, and its reliability and validity are well 
established. Cronbach's alpha for various populations 
ranges from 0.82 to 0.90 (Holmes & Rahe, 1967).
DIS-III-R
 Subjects were interviewed using the Diagnostic 
Interview Schedule Version III Revised (DIS-III-R), 
a structured interview employed in epidemiological 
research. Interviews were performed over the tele-
phone by the Institute for Survey Research at Temple 
University. Responses to the DIS-III-R were used to 
diagnose psychiatric disorders according to the revised 
third edition of the Diagnostic and Statistical Manu-
al of Mental Disorders (Coopers and Michels, 1988). 
PTSD Checklist (PCL-R)
 The PTSD Checklist (PCL) is a self-report rat-
ing scale for assessing posttraumatic stress disorder.  
It consists of 17 items (α = 0.87) which correspond 
to the DSM-III symptoms of PTSD.  Examinees 
are instructed to indicate how much they have been 
bothered by each symptom in the past month using 
a 5-point (1-5) scale.  The anchors for the severity rat-
ings range from "Not at all" to "Extremely." The PCL 
can be used as a continuous measure of PTSD symp-
tom severity by summing scores across the 17 items. 
AFQT
 The Armed Forces Qualification Test (AFQT) is 
a 50-minute paper-and-pencil test consisting of 100 
multiple-choice items (α = .88) that was administered 
just prior to military induction (Bayroff & Anderson, 
1963). The items equally represent the four domains 
of vocabulary, arithmetic word problems, knowledge 
of tools and mechanical or electrical equipment, and 
spatial visualization, which involves matching folded 
and unfolded box patterns (Uhlaner & Bolanovich, 
1952). Originally intended as a measure of military 
trainability, further research has found the AFQT to 
be a highly g-loaded test (Orme et al., 2001), with g be-
ing the construct of general intelligence (Humphreys, 
1979). VETSA investigators received permission from 
the United States Department of Defense to re-ad-
minister a version of the AFQT that is similar to the 
AFQT versions that had been administered to VETSA 
subjects just prior to their induction into the military 
(1965–1975). This version has been used in previous 
research (Grafman et al., 1988). Scores from the time 
of induction are also available to VETSA investigators. 
Genotyping
 ApoE genotype is integral in AD and MCI re-

search as it accounts for as much as 50% of the attrib-
utable risk for AD in many populations (Ashford, 
2004). As per Lyons et al. (2013), ApoE genotyping 
was conducted for the 1,237 VETSA participants at 
either the Boston University or University of Cal-
ifornia, San Diego site. ApoE genotype was deter-
mined using previously described conditions (Emi 
et al., 1988; Hixson & Vernier, 1990). Due to the 
low rate of participants that possessed e4 allele, ho-
mozygous and heterozygous carriers were grouped. 
Jak-Bondi MCI
 This study uses VETSA data that utilized the 
Jak-Bondi (Jak, et al., 2009) operationalization of 
MCI. Conservative criteria were used in VETSA, such 
that it requires impairment on two measures with-
in a domain, with impairment identified as 1.5 SD 
below normative data (Jak et al., 2009). According 
to these standardized criteria, individuals in VETSA 
were classified as normal if, at most, performance on 
one measure within one or two cognitive domains 
fell more than 1.5 SD below age-appropriate norms. 
Procedure
 Mixed modelling was used to test the asso-
ciation between demographic factors, psychoso-
cial and traumatic variables, and MCI diagnosis.
 All analyses were conducted in SPSS 29.0.0.0. 
All measures were assessed at the individual level. Be-
cause our sample consisted of twins, we used a linear 
mixed modelling approach to account for the clus-
tering of twins within families by including a family 
ID variable as a random effect. Separate analyses were 
performed for each measure. Standardized scores were 
used for all outcome measures and for AFQT, educa-
tion, and performance on neuropsychological tests. 
 Model 1 tested whether age at testing date for 
Wave 2 (61.72 ± 2.44 years) had an effect on MCI out-
come. Model 2 tested the association of intelligence, 
as measured by AFQT performance upon military 
induction (collected between 1965–1975) with MCI 
outcome. Model 3 tested the association of ApoE e4 
allele status on MCI outcome. Model 4 examined the 
correlation between years of education on MCI out-
come. Model 5 tested the association of race on MCI 
outcome. Model 6 tested the association of ethnicity 
(Hispanic/Non-Hispanic) on MCI outcome. Model 
7 tested the association of PTSD diagnosis at Harvard 
Drug Study (Tsuang, et al., 2001) data collection date 
(1996) as measured by the DIS-III-R on MCI out-



56

GOULDEN

come. Model 8 tested the association of psychosocial 
stressors over the last two years before the Wave 2 test-
ing date on MCI outcome. Model 9 tested the asso-
ciation of PTSD symptoms at Harvard Drug Study 
(Tsuang, et al., 2001) data collection date (1996), as 
measured by the DIS-III-R collection on MCI out-
come. Significant associations were determined using 
the type III fixed effects. Associations were consid-
ered statistically significant at p < 0.05, two-tailed.

Results
 Table 1 shows that Age (F = 3.879, p = 0.05) did 
not have a significant effect on MCI diagnosis, al-
though it exhibited a trend towards a predictive effect. 
Intelligence, measured by the AFQT taken between 
ages 18-25, was found to have no significant impact 
on MCI diagnosis (F = 3.523, p = 0.061). The ApoE 
e4 allele(s) status (F = .236, p = 0.628) was also found 
to have no significant impact on MCI diagnosis. Ed-
ucation, however, (F = 4.667, p = 0.031) was found 
to have a significant effect on MCI diagnosis. Nei-
ther Race (F = 2.195, p = 0.139) , nor Ethnicity (F 
= 2.252, p = 0.134) had a significant effect on MCI 
diagnosis. PTSD diagnosis, as measured by the DIS-
III-R (Coopers and Michel, 1988), collected for the 
Harvard Drug Study in 1996 (F = 0.249, p = 0.618) 
did not have a significant effect on MCI diagnosis. 
Life stress exposure, as measured by the Holmes and 
Rahe (1967), (F = 0.249, p = 0.618) also did not have 
a significant impact on MCI diagnosis. Lastly, Table 
1 shows that PTSD symptoms (F = 0.006, p = 0.936) 
did not have a significant impact on MCI diagnosis.

Discussion
 Our findings in a mixed model analysis of VETSA 
Wave 2 did not support the hypothesis. No significant 
associations between the stress factors we examined 
and MCI diagnosis in Wave 2 was observed. A signifi-
cant relationship between education and MCI was ob-
served, but is not surprising, as epidemiological studies 
consistently report that a high level of education is as-
sociated with a reduced risk of cognitive impairment 
(Anttila et al., 2002; Fratiglioni & Wang, 2007; Ngan-
du et al., 2007). The results of these studies indicate 
that education might reflect the extent of early cogni-
tive stimulation of the brain which may influence glob-
al cognitive abilities. The average lifetime education of 
the participants was 12.4 (± 1.3 years; see Appendix A).

 Previous studies investigated the relationship be-
tween psychosocial and traumatic stressor activities 
with cognitive decline. We hypothesize that our results 
may vary from those obtained by Yaffe et al. (2010) be-
cause their study tracked health records over a period 
of seven years, while our analysis looked at new MCI 
diagnoses over a shorter time span between each VET-
SA data collection point. Further, their subjects were 
more racially diverse and included women. Our study 
only investigated the onset of MCI, while their study 
included all types of dementias, including end-stage 
Alzheimer’s Disease. Most importantly, the mean 
baseline age of their veteran subjects was 68.8 years.
 The study by Weiner et al. (2017) primarily aimed 
to establish the relationship between traumatic brain 
injury, PTSD, and Alzheimer’s Disease biomarkers. 
Their study’s conceptualization of PTSD may have 
been more relevant to finding the connection be-
tween traumatic exposure and cognitive impairment, 
as it accounted for current and lifetime PTSD in-
stead of PTSD status at one point in 1996. Another 
feature of their study that contributed to their find-
ing was that their subjects had a mean age of 67.8.
 As for Peavy et al. (2009), their operationalization 
of MCI was the less stringent Peterson et al. (1999) 
criteria. In one study by Oltra-Cucarella et al. (2018) 
criteria for MCI misclassified 24% of the sample com-
pared to the more conservative Jak-Bondi MCI criteria 
(Jak et al., 2009) used for the current study. Stress was 
also measured as a cortisol rating and from responses 
to the Life Events and Difficulties Schedule (Brown & 
Harris, 1978), which quantified events over the partic-
ipants’ entire adult life instead of within the last two 
years before the study visit. Stressful events were also 
self-reported every six months, at which time cortisol 
was measured. This data was collected for two to three 
years. Aside from this difference in operationalization of 
toxic stress, the mean age of participants was 78.8 years 
old, making their participants much older than ours.
 Wang et al. (2018) studied non-military elders 
and found a significant dose-dependent relation-
ship between PTSD symptom severity and devel-
oping dementia later in life. Though the average age 
of their participants was 55.44 years, PTSD severity 
was indicated by the frequency of psychiatric clin-
ic visits for PTSD. This operationalization of PTSD 
is not through clinically supported or uniform diag-
nosis criteria. As for psychosocial and trauma-related 



57

STRESSORS ON MCI DIAGNOSIS

stress, Bougea et al. (2022) may have found results 
that differed from ours because they used a wide va-
riety of conceptualizations of psychosocial stress. For 
dementia diagnosis, one included study used self-re-
port responses to quantify dementia. All partici-
pant data examined was for people 65 years or older.
 One of the main limitations of the current study 
was the small number of people that met the diagnos-
tic criteria for MCI, which in total was only 147 after 
adjusting for age, education, and practice effects. This 
small number resulted in a lack of statistical power. Ad-
ditional issues with the analysis may be from our oper-
ationalization of psychosocial and traumatic stressors. 
The measure of psychosocial stress used, the Holmes 
and Rahe (1967), only pertained to the two years of 
the participant’s life prior to test administration. A 
measure that accounts for the entirety of adulthood, 
from 18 years old onwards, would more accurately 
quantify the total adult stress burden. As for using the 
PTSD diagnosis conferred in 1996, the literature sup-
ports that just one incidence of PTSD permanently 
alters the brain (Hendrickson & Raskind, 2016). The 
mechanism is that trauma causes permanent neuronal 
changes that harm learning, habituation, and stimulus 
discrimination. Some of these neuronal changes that 
have a continuing impact do not even depend on ac-
tual exposure to reminders of the trauma for expres-
sion (Van der Kolk, 2003). Even so, a diagnosis back in 
1996 may not be as relevant to cognitive status during 
the data collection period of VETSA Wave 2, which 
occurred in the 2010’s (between 2009 and 2014).
 Our insignificant findings are still relevant to MCI 
risk factor research. Our limitations highlight the im-
portance of subject selection and support existing re-
search on the typical age of onset for MCI (Howieson 
et al., 2008). Future analyses should be conducted 
with VETSA study data that covers a longer period 
of the twins’ lives. Future analyses should also include 
data collected when the participants were older. These 
two suggestions should be followed so that a longer 
period of toxic stress exposure can be quantified and 
so that the subjects will be older, giving more time for 
MCI to develop. Higher rates of MCI can be expected 
to emerge as the participants age. The results did not 
indicate that toxic psychosocial stress exposure and/or 
traumatic stress had an impact on rates of MCI diagno-
sis within a subject pool of veterans from the VETSA 
study. Monitoring the health of veterans as they age is 

important for addressing the epidemic of cognitive im-
pairment in the general population. Even those with 
primarily non-combatant roles are at risk for adverse 
health outcomes due to their service. Veterans have 
made great sacrifices and the scientific community 
must ensure that their unique healthcare needs are met.

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Table 1

Mixed Model Tests of Fixed Effects on MCI Diagnosis

Note. Dependent Variable: MCI diagnosis at VETSA Wave 2.
*at ages 17–25 years, as measured by the AFQT upon military induction between 1965–1975, collected 
for the Harvard Drug Study
**no e4 allele vs. homo- or heterozygous for e4
*** as measured by the DIS-III-R, collected for the Harvard Drug Study in 1996
**** measured over the last two years from testing date by the Holmes and Rahe (1967).



62

GOULDEN

Appendix A

Note. Subject demographic data from Lyons et al. (2013).


