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. 2026 Feb 3;5:1704367. doi: 10.3389/frdem.2026.1704367

Cognitive decline in U.S. military veterans: risk factors and clinical implications

Rob J MacLennan 1,2,*, Benjamin A Chapin 1,3,4, Laurence M Solberg 1,5,6, David J Clark 2,7
PMCID: PMC12909232  PMID: 41710449

Abstract

Military veterans have higher aggregate prevalence of risk factors for cognitive decline than non-veterans. This includes risk factors like diabetes, chronic pain, smoking, depression, and more. The disparity in prevalences is due in part to the unique experiences and exposures of their military service. Alzheimer's disease and other dementias are debilitating diseases with large financial and logistical burdens. These burdens are held by the patient, their family, friends, and caregivers, as well as healthcare professionals, and healthcare systems. Standardized screening for these risk factors may be helpful for understanding risk profiles that lead to cognitive decline. Additionally, screening must occur early to encourage early intervention and behavioral modifications and to reduce these burdens. This perspective presents the prevalence of risk factors for cognitive decline in the Veteran and non-veteran populations and proposes an approach to managing risk factors in Veterans.

Keywords: diabetes, hearing impairment, chronic pain, smoking, depression, social isolation, hypercholesterolemia, sleep disturbance

Introduction

US military service members have experiences and exposures that are different from those of the general population. Many perform hazardous and stressful work, work in harsh environments, and live in geographically isolated locations. As a result, US military service veterans (Veterans) have greater prevalence of many health risk factors than non-veterans. This may put Veterans at greater risk of developing diseases than non-veterans, including Alzheimer's disease and related dementias (ADRD; Powell et al., 2023). In the United States, ADRD is one of the costliest chronic disease categories (2024 Alzheimer's disease facts and figures, 2024). From disease onset to death, the estimated total cost per individual is $400 thousand, 70% of which is borne by caregivers for unpaid caregiving, medications, and home health support with the remaining being paid by Medicare and Medicaid (2024 Alzheimer's disease facts and figures, 2024; Skaria, 2022). Between the year 2018 and 2050, nationwide costs are projected to add up to $47 trillion (Nandi et al., 2022). These costs impact the individual and their family, as well as institutions that provide care such as the US Veterans Health Administration (VHA).

The search for articles was initiated by reviewing the current, comprehensive articles by The Lancet and the Alzheimer's Association (2024 Alzheimer's disease facts and figures, 2024; Livingston et al., 2024). Next, the search was expanded by database searches through Google Scholar and PubMed with the terms (veteran OR military OR “general population”) AND (Alzheimer's OR dementia OR ADRD or “cognitive decline”) AND (“risk factors”). The search was then narrowed by using terms for specific risk factors which included diabetes, hearing impairment, chronic pain, smoking, depression, social isolation, hypercholesterolemia, sleep disturbance, alcohol consumption, post-traumatic stress disorder, hypertension, obesity, physical inactivity, education level, traumatic brain injury, and air pollution. Risk factors were included based on the strength of evidence, and their interest to the military and Veteran populations (Goldstein et al., 2025; Livingston et al., 2024; Mannes et al., 2022; Veitch et al., 2013). The search was further narrowed by variations of terms for risk factors (e.g., hypertension or high blood pressure, sleep disturbance or sleep apnea or OSA). Date ranges included 2020-present, 2015-present, 2010-present, etc. with preference for more recent articles.

Evidence of elevated risk factors in Veterans and the effect on the likelihood of developing ADRD is widely dispersed in the literature. Thus, consolidating this evidence is foundational to improving the care and outcomes in Veterans.

Prevalence of risk factors in veterans and non-veterans

There are many known risk factors for the development of ADRD such as smoking, excessive alcohol consumption, hypertension, and sleep disturbance (Livingston et al., 2024). For some risk factors, there is a notable heightened prevalence in Veterans, while for other risk factors there is little or no known difference (Table 1; Littman et al., 2013; Ogden et al., 2020; Washington, 2022). Even in cases where there is little difference, the relative cost to the VHA may be higher. This is because the prevalence of some risk factors is higher in Veterans who receive care through VHA, as opposed to other sources such as private insurance (Wisco et al., 2022). The following subsections include relevant risk factors, roughly ordered by disparity of prevalence among Veterans and non-veterans. Where scientific literature is inconclusive, we have done our best to objectively present the strength of the evidence.

Table 1.

Summary of prevalence for cognitive decline risk factors in veteran and non-veteran populations.

Risk factor Age range VHA vs non-VHA Prevalence, unadjusted % (group) Prevalence, adjuste Cognitive decline effect estimate Study design Population
Diabetes
Effect estimate: HR 1.90 (<50 years; Qi et al., 2024); RR 1.43 (Xue et al., 2019)
Veterans
Liu et al. (2017) 22–65+ non-VHA 24 Not available Not available Pooled, serial, cross-sectional survey US Veterans
Jackson et al. (2015) <50–70 (μ = 53.6) VHA 20 Not available Not available Retrospective observational analysis US Veterans, BMI 30+ OR BMI 25+ with a weight-related disorder
Non-veterans
Wang et al. (2021) 18–65+ (μ = 48.2) non-VHA 14.6 14.3 (age) Not available Pooled, serial, cross-sectional survey US general population
Benoit et al. (2019) 18–79 non-VHA Not available 10.5 (age) Not available Pooled, serial, cross-sectional survey US general population
Hearing impairment
Effect estimate: HR 1.37 (Livingston et al., 2024); RR 1.90 (Livingston et al., 2020)
Veterans
Lucas and Zelaya (2020) 18+ 18–44 45–64 65–74 non-VHA 19.8 (18–44) 27.7 (45–64) 42.8 (65–74) 27.1 (age, 18+) Not available Cross-sectional survey US Veterans
Non-veterans
National Institute on Deafness and Other Communication Disorders (2024) 45–54 55–64 65–74 non-VHA 5 (45–54) 10 (55–64) 22 (65–74) Not available Not available Report US general population
Madans et al. (2021) 18+ non-VHA 14.6 Not available Not available Cross-sectional survey US general population
Lucas and Zelaya (2020) 18+ 18–44 45–64 65–74 non-VHA 5.7 (18–44) 18.6 (45–64) 37.2 (65–74) 16 (age, 18+) Not available Cross-sectional survey US general population
Chronic pain
Effect estimate: HR 1.08–1.50 (Tian et al., 2023)
Veterans
Taylor et al. (2024) Not available (18+) non-VHA Any: 49.2–64.8 Multiple: 20.8–35.5 Not available Not available Pooled, serial, cross-sectional survey US Veterans
Mannes et al. (2022) 18–65+ VHA & non-VHA 32.93 45.26 (VHA) 26.88 (non-VHA) Not available Not available Cross-sectional survey US Veterans
Zelaya et al. (2020) 20–65+ non-VHA 31.5 Not available Not available Cross-sectional survey US Veterans
Non-veterans
Taylor et al. (2024) Not available (18+) non-VHA Any: 45.9–54.8 Multiple: 21.6–28.9 Not available Not available Pooled, serial, cross-sectional survey US general population
Nahin et al. (2023) 18–50+ (μ = 49) non-VHA 20.8 Not available Not available Cohort, longitudinal US general population
Rikard et al. (2023) 18–85+ non-VHA 20.9 19.7 (age) Not available Serial, cross-sectional survey US general population
Mannes et al. (2022) 18–65+ VHA & non-VHA 20 Not available Not available Cross-sectional survey US general population
Zelaya et al. (2020) 20–65+ non-VHA 20.1 Not available Not available Cross-sectional survey US general population
Cigarette smoking and other tobacco use
Effect estimate: HR 1.88 (Tsao et al., 2023); RR 1.30 (Zhong et al., 2015)
Veterans
Nieh et al. (2021) 17–45+ non-VHA 20.1 Not available Not available Prospective cohort US Veterans
Odani et al. (2018) 18–50+ non-VHA 29.2 Not available Not available Pooled, serial, cross-sectional survey US Veterans
Brown (2010) 18+ non-VHA Not available 27 (age, men) 23 (age, women) Not available Pooled, serial, cross-sectional survey US Veterans
Non-veterans
Phillips et al. (2017) 18–65+ non-VHA Not available 25.2 (males)
15.4 (females)		 Not available Cross-sectional survey US general population
Brown (2010) 18+ non-VHA Not available 21 (age)
21 (age, men) 18 (age, women)		 Not available Pooled, serial, cross-sectional survey US general population
Depression
Effect estimate: HR 2.41 (Elser et al., 2023); RR 2.25 (Livingston et al., 2024)
Veterans
Finnegan and Randles (2023) 16–99 (μ = 62) UK NHS 17.8 22.6 (ages 28–37) 28.6 (ages 38–47) Not available Retrospective, cohort, medical records UK Veterans
Moradi et al. (2021) (μ = 13–70) VHA & non-VHA 20 Not available Not available Meta-analysis, cross-sectional studies Multi-national Veterans
Gould et al. (2015) 50+ non-VHA 11 Not available Not available Cross-sectional survey US Veterans, men
Hankin et al. (1999) (μ = 62) VHA 31 29 Not available Prospective, longitudinal cohort US Veterans, male
Non-veterans
Substance Abuse Mental Health Services Administration (2022) 18+ non-VHA 8.3 (past year) Not available Not available Cross-sectional survey US general population
Daly et al. (2021) 18–65+ (μ = 48) non-VHA 8.9 (pre-pandemic) 14.2 (April 2020) 8.7 (pre-pandemic) 14.4 (April 2020; age, sex, race/ethnicity, education, income) Not available Longitudinal, cross-sectional survey US general population
Gould et al. (2015) 50+ non-VHA 12.8 Not available Not available Cross-sectional survey US general population, men
Social isolation
Effect estimate: HR 1.38–2.34 (Saczynski et al., 2006); RR 1.41–1.57 (Kuiper et al., 2015)
Veterans
Vespa (2023) 18+, 65+ non-VHA 34.4 (18+) 42.8 (65+) Not available Not available Cross-sectional, descriptive analysis US Veterans
Non-veterans
Vespa (2023) 18+, 65+ non-VHA 26.5 (18+) 45.6 (65+) Not available Not available Cross-sectional, descriptive analysis US general population
Hypercholesterolemia
Effect estimate: HR 1.33 (Livingston et al., 2024); ES 2.01 (Wee et al., 2023)
Veterans
Nguyen et al. (2023) 18+ (μ = 62) VHA 37.8 Not available Not available Retrospective cohort, observational US Veterans
Washington (2022) 18–85+ VHA 47.3 Not available Not available Observational, cross-sectional analysis US Veterans
Non-veterans
Tsao et al. (2023) 20+ non-VHA Not available 34.7 Not available Annual systematic review US general population
Sleep disturbance
Effect estimate: HR 1.51 (Wong and Lovier, 2023); RR 1.20–1.50 (Shi et al., 2018)
Veterans
Goldstein et al. (2025) 18–75+ non-VHA 21 (sleep apnea, all) 23 (sleep apnea, men) Not available Not available Cross-sectional survey US Veterans
Faestel et al. (2013) 21–75+ non-VHA 22.4 22.4 (age, sex, race/ethnicity) Not available Cross-sectional survey US Veterans
Non-veterans
Goldstein et al. (2025) 18–75+ non-VHA 9 (sleep apnea, all) 13 (sleep apnea, men) Not available Not available Cross-sectional survey US general population
Faestel et al. (2013) 21–75+ non-VHA 27.9 20.1 (age, sex, race/ethnicity) Not available Cross-sectional survey US general population
Alcohol consumption (heavy)
Effect estimate: HR 1.08 (Jeon et al., 2023); RR 1.18 (Livingston et al., 2020)
Veterans
Teeters et al. (2017) Not specified VHA & non-VHA 7.5 (heavy) Not available Not available Review US Veterans
Wagner et al. (2007) 17–75+ non-VHA 7.5 Not available Not available Pooled analysis, repeated, cross-sectional survey US Veterans
Non-veterans
Teeters et al. (2017) Not specified VHA & non-VHA Not available 6.5 (comparable non-veterans) Not available Review US general population
Wagner et al. (2007) 17–75+ non-VHA Not available 6.5 (comparable non-veterans) Not available Pooled analysis, repeated, cross-sectional survey US general population
Post-traumatic stress disorder
Effect estimate: HR 1.61–2.11 (Günak et al., 2020); OR 2.20 (Qureshi et al., 2010)
Veterans
Eibner et al. (2016) Not available VHA & non-VHA 3.3 Not available Not available Cohort-based, modeling US Veterans
Schnurr et al. (2009) 18–65+ VHA & non-VHA 23 (VHA) 7 (non-VHA) Not available Not available Review US Veterans
Non-veterans
Schnurr et al. (2009) 18–65+ VHA & non-VHA 6 Not available Not available Review US general population
Hypertension
Effect estimate: HR 1.49–2.00 (Livingston et al., 2020; Tsao et al., 2023); RR 1.61 (Norton et al., 2014)
Veterans
Yamada et al. (2023) (μ = 66) VHA 71 (140/90) 81 (130/90) 87 (130/80) Not available Not available Retrospective cohort US Veterans
Washington (2022) Not available VHA 48.2 Not available Not available Comparative analysis, longitudinal, cross-sectional data US Veterans
Boersma et al. (2021) 25+ 25–64 65+ non-VHA Not available 32.2 (25–64, male, Veteran) 25.6 (25–64, female, Veteran) 64.9 (65+, male, Veteran) 69.8 (65+, female, Veteran) Not available Pooled report, cross-sectional survey US Veterans
Non-veterans
Centers for Disease Control and Prevention (2023) 18+ non-VHA 48.1 Not available Not available Survey, guideline application US general population
Washington (2022) Not available non-VHA 45 Not available Not available Comparative analysis, longitudinal, cross-sectional data US general population
Boersma et al. (2021) 25+ 25–64 65+ non-VHA Not available 26.6 (25–64, male, non-veteran) 22.4 (25–64, female, non-veteran) 62.4 (65+, male, non-veteran) 61.9 (65+, female, non-veteran) Not available Pooled report, cross-sectional survey US general population
Obesity
Effect estimate: HR 1.34 (Ma et al., 2020); RR 1.60 (Barnes and Yaffe, 2011)
Veterans
Breland et al. (2017) Not available non-VHA 41 Not available Not available Descriptive analysis, cross-sectional US Veterans
Non-veterans
Hales et al. (2020) 20+ non-VHA 42.5 43.0 (men) 42.1 (women) 42.4 (age) Not available Pooled analysis, serial, cross-sectional survey US general population
Ogden et al. (2020) 20+ 20–74 non-VHA 42.5 42.4 (20+) 42.8 (20–74) Not available Stratified, multistage probability, cross-sectional survey US general population
Breland et al. (2017) Not available non-VHA 38 Not available Not available Descriptive analysis, cross-sectional US general population
Flegal et al. (2016) 20+ (μ ≈ 47) non-VHA 37.9 35.2 (men) 40.5 (women) 37.7 (age) Not available Pooled analysis, serial, cross-sectional survey US general population
Physical inactivity
Effect estimate: HR 1.40 (Kivimäki et al., 2019); RR 1.30–1.82 (Norton et al., 2014; Yan et al., 2020)
Veterans
Littman et al. (2013) 21–85+ non-VHA Not available 49
30.8 (inactive)
18.2 (insufficiently active)
(age, demographics)		 Not available Stratified, multistage probability, cross-sectional survey US Veterans, male
Hoerster et al. (2012) 18–65+ non-VHA 24.6 Not available Not available Population-based, cross-sectional survey US Veterans, male
Non-veterans
Littman et al. (2013) 21–85+ non-VHA Not available 56.1
32.5 (inactive)
23.6 (insufficiently active)
(age, demographics)		 Not available Stratified, multistage probability, cross-sectional survey US general population, male
Hoerster et al. (2012) 18–65+ non-VHA 21.5 Not available Not available Population-based, cross-sectional survey US general population, male
Education level
Effect estimate: HR 1.76 (Sabia et al., 2018); RR 1.59 (Barnes and Yaffe, 2011)
Veterans
Chakrabarti et al. (2023) 25–69 non-VHA Not available 27 (Bachelor's or higher) Not available Comparative analysis, survey US Veterans, male
Rolen (2017) 18+ non-VHA 30.5 (Bachelor's or higher) Not available Not available Descriptive analysis, survey US Veterans
Non-veterans
Chakrabarti et al. (2023) 25–69 non-VHA Not available 34 (Bachelor's or higher) Not available Comparative analysis, survey US general population, male
Rolen (2017) Not available non-VHA 31.1 (Bachelor's or higher) Not available Not available Descriptive analysis, survey US general population
Traumatic brain injury
Effect estimate: HR 2.36–3.77 ((Barnes et al., 2018)); RR 1.66 (Gardner et al., 2023)
Veterans
Kornblith et al. (2020) 65+ (μ = 75.2) non-VHA 7.76 Not available Not available Longitudinal cohort, survey US Veterans
Gardner et al. (2023) (μ = 49–81) VHA & non-VHA 35 36 (males) 3.5 (females) Not available RR = 2.13 (113%), 2.13 (113%, males), 2.13 (113%, females) Systematic review, meta-analysis US Veterans
Kornblith et al. (2020) 51+ non-VHA Not available 36 Not available Nationally representative survey US Veterans, male
Non-veterans
Kornblith et al. (2020) 65+ (μ = 75.2) non-VHA 8.97 Not available Not available Longitudinal cohort, survey US general population
Gardner et al. (2023) (μ = 49–81) VHA & non-VHA 31 43 (males) 22 (females) Not available RR = 1.52 (52%), 2.07 (107%, males), 1.43 (43%, females) Systematic review, meta-analysis US general population
Kornblith et al. (2020) 51+ non-VHA Not available 45 Not available Nationally representative survey US general population, male
Air pollution and toxic exposures
Effect estimate: HR 1.45 (burn pits, Wilker et al., 2023), 1.68 (Agent Orange, Martinez et al., 2021)
Veterans
Chari et al. (2024) Not available VHA & non-VHA 80 (Burn pits; OEF, OIF, & OND) Not available Not available Policy analysis and synthesis US Veterans
Martinez et al. (2021) ≈ 45–85 (μ = 62) VHA 12.2 (Agent Orange; Vietnam War) Not available HR = 1.68 (68%) Longitudinal cohort US Veterans
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Diabetes

Type 2 diabetes is characterized by hyperglycemia due to insulin deficiency (Smushkin and Vella, 2010). Estimates in the non-veteran population find that 8%−14% have diabetes (Benoit et al., 2019; Wang et al., 2021). This contrasts with Veterans, of whom 20%−24% are affected (Jackson et al., 2015; Liu et al., 2017), suggesting Veterans are approximately twice as likely to have diabetes as non-veterans. This prevalence of diabetes is particularly concerning, as diabetes increases the risk of ADRD by up to 90% (Qi et al., 2024; Xue et al., 2019).

Hearing impairment

Hearing impairment can be diagnosed by a pure tone average of 40 decibels or more at frequencies of 500, 1000, 2000, and 4000 Hz (Taljaard et al., 2016). In ages 45–64, prevalence of hearing loss in non-veterans is estimated to be between 5 and 17% (Lucas and Zelaya, 2020; Madans et al., 2021; National Institute on Deafness and Other Communication Disorders, 2024). In Veterans between the ages of 45–64 however, hearing loss is estimated to affect 24% of the population (Lucas and Zelaya, 2020). In those 65–74 years old, the disparity remains with 22%−37.2% of non-veterans, and 48.2% of Veterans experiencing hearing loss (Lucas and Zelaya, 2020; Madans et al., 2021; National Institute on Deafness and Other Communication Disorders, 2024). Hearing loss increases the likelihood of developing dementia by approximately 37% (Livingston et al., 2024).

Chronic pain

Chronic pain is defined as pain that persists or recurs for more than 3 months (Treede et al., 2019). It is estimated that 20%−55% of non-veterans have experienced chronic pain compared to 32%−65% of Veterans (Nahin et al., 2023; Rikard et al., 2023; Taylor et al., 2024; Zelaya et al., 2020). Further, 22%−29% of non-veterans, and 21%−36% of Veterans have had multiple sites with chronic pain (Taylor et al., 2024). Within the Veteran population, 45% of Veterans who receive healthcare from the VHA had chronic pain, while only 27% of Veterans who receive their healthcare elsewhere had chronic pain (Mannes et al., 2022). This is an important consideration as the number of chronic pain sites has been found to increase risk of dementia in the range of 8%−40% (Tian et al., 2023).

Cigarette smoking and other tobacco use

A “smoker” is defined as one who currently smokes and has smoked at least 100 cigarettes in their lifetime (Agaku et al., 2014). Among non-veterans, 15%−21% are smokers (Brown, 2010; Phillips et al., 2017), while 22%−30% of Veterans are smokers (Nieh et al., 2021; Odani et al., 2018), with one study reporting up to 50% of Veterans are smokers (Odani et al., 2018). Among Veterans aged 18–25, 57% engage in some form of tobacco use (Odani et al., 2018). Additionally, 57% of non-veterans never smoked while 33% of Veterans never smoked (Nieh et al., 2021). The greater prevalence of smoking and tobacco use among Veterans is concerning because this risk factor increases the risk of developing ADRD by 30%−90% (Tsao et al., 2023; Zhong et al., 2015).

Depression

Depression is generally considered to be present when depressive symptoms last 2 weeks or more with significant social degradation (Rondón Bernard, 2018). Approaches for determining the prevalence of depression are not uniform, which results in a range of estimates. In non-veterans, the reported prevalence of depression ranges from 9 to 19% (Daly et al., 2021; Substance Abuse Mental Health Services Administration, 2022) and in Veterans it ranges from 11 to 31% (Finnegan and Randles, 2023; Gould et al., 2015; Hankin et al., 1999; Moradi et al., 2021). For major depressive disorder, the prevalence reported in the literature is 8% for non-veterans and 13% for Veterans (Gould et al., 2015; Substance Abuse Mental Health Services Administration, 2022). Those with a history of depression have a 240% increase in risk for developing ADRD, making it a highly consequential risk factor (Elser et al., 2023; Livingston et al., 2024).

Social isolation

Social isolation is when a person objectively lacks or has limited social contact with others (Donovan and Blazer, 2020). Among all ages, the US Census Bureau reports that 27% of non-veterans and 34% of Veterans experience social isolation (Vespa, 2023). Social isolation increases with age, but the gap closes in ages 65+ with 46% of non-veterans and 43% of Veterans being isolated (Kannan and Veazie, 2023; Vespa, 2023). Social isolation is associated with a 30%−65% increase in the risk for dementia (Kuiper et al., 2015; Penninkilampi et al., 2018; Saczynski et al., 2006).

Hypercholesterolemia

Hypercholesterolemia is defined as having total cholesterol of greater than 200 mg/dL (Civeira et al., 2022). Among all ages, 35% of non-veterans and 38% of Veterans have high cholesterol (Nguyen et al., 2023; Tsao et al., 2023). However, within the VHA, 47% of Veterans have high cholesterol (Washington, 2022). High cholesterol is associated with an estimated 30% increase in the risk of dementia (Livingston et al., 2024) and a 100% increase in the risk of mild cognitive impairment (MCI; Wee et al., 2023).

Sleep disturbance

Sleep disturbance includes insomnia, obstructive sleep apnea, sleep-related movement disorder, and more (Livingston et al., 2020; Shi et al., 2018). Veterans experience sleep disturbances more than non-veterans (Alexander et al., 2016; Fung et al., 2013; Mustafa et al., 2005). One study estimates the prevalence in non-veterans and Veterans is 20 and 23% respectively (Faestel et al., 2013). It has been reported that twice as many Veterans (21%) experience obstructive sleep apnea compared to non-veterans (9%; Goldstein et al., 2025). Sleep disturbance is associated with an increased risk of ADRD by 20%−50% (Shi et al., 2018; Wong and Lovier, 2023).

Alcohol consumption

The US National Institute on Drug Abuse reports the prevalence of alcohol use among non-veterans is 51%, while in military Veterans it is 57% (Teeters et al., 2017). Further, heavy alcohol use, defined as consuming 5 or more drinks on 5 or more days in the past month, was 6.5% among non-veterans and 7.5% among Veterans (Teeters et al., 2017; Wagner et al., 2007). The relationship between alcohol consumption and cognitive decline is complex, as mild, and moderate alcohol consumption are found to reduce the risk of dementia by 21 and 7% respectively (Jeon et al., 2023). However, heavy alcohol consumption increases risk by 8%−18% (Jeon et al., 2023; Livingston et al., 2020; Sabia et al., 2018).

Post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) results from experiencing or witnessing a traumatic event, with symptoms that interfere with one's daily life. Six percent of non-veterans and 7% of Veterans have experienced PTSD (Schnurr et al., 2009). However, PTSD in Veterans likely results in relatively greater costs to VHA because even though only 7% of Veterans experience PTSD, it is estimated that up to 23% of Veterans who receive healthcare through VHA have had PTSD (Schnurr et al., 2009). In fact, Veterans with PTSD are 13.5 times more likely to be diagnosed than non-veterans who have PTSD (Eibner et al., 2016). PTSD is associated with 50%−100% increased risk of ADRD (Bhattarai et al., 2019; Günak et al., 2020; Qureshi et al., 2010; Yaffe et al., 2010).

Hypertension

The criteria for hypertension varies depending on source, with lenient criteria being systolic blood pressure (SBP) ≥140 mmHg or diastolic blood pressure (DPB) ≥90 mmHg (Carretero and Oparil, 2000), and more strict criteria including SBP ≥130 mmHg, DPB ≥80 mmHg, or hypertensive drug prescription (Yamada et al., 2023). Some studies report that approximately 48% of non-veterans and Veterans have hypertension (Boersma et al., 2021; Centers for Disease Control and Prevention, 2023; Washington, 2022). One study that utilized the most strict criteria found that 87% of Veterans have hypertension (Yamada et al., 2023). Uncontrolled hypertension is common despite efforts to reduce it, and has been found to increase the risk of dementia by 50%−100% (Livingston et al., 2020; Norton et al., 2014; Tsao et al., 2023).

Obesity

Obesity is defined as having a body mass index of 30 kg/m2 or more (Chooi et al., 2019). In ages 20–39, 32% of non-veterans are obese and among all ages 38%−43% are obese (Breland et al., 2017; Flegal et al., 2016; Hales et al., 2020; Ogden et al., 2020). Studies of the Veteran population report that 46% of those ages 18–44 are obese and overall 41% are obese (Breland et al., 2017). Obesity increases the risk of dementia by 34% (Ma et al., 2020).

Physical inactivity

CDC physical activity guidelines recommend 150 min of moderate intensity, or 75 min of vigorous activity per week (Littman et al., 2013). Failing to meet these guidelines is considered physical inactivity (Thivel et al., 2018). Lack of physical activity is common, with 22%−33% of non-veterans and 25%−31% of Veterans reporting being (Hoerster et al., 2012; Littman et al., 2013). Further, 24% of non-veterans and 18% of Veterans reported being active for more than 10 min per day, but less than CDC guidelines (Littman et al., 2013). The relationship between physical inactivity and cognition can vary depending on how they're quantified, but trials have reported improvements in cognition following exercise interventions (Carta et al., 2021; Sáez De Asteasu et al., 2017). Studies report that physical inactivity increases the risk of dementia by 30%−82% (Kivimäki et al., 2019; Norton et al., 2014; Yan et al., 2020).

Education level

Both the non-veteran and Veteran populations have high rates of high school graduation (Department of Defense, 2023; Heckman and LaFontaine, 2010; National Center for Education Statistics, 2024), and this acts as a ceiling effect for educational attainment as a risk factor (Sharp and Gatz, 2011). Further, evidence suggests comparable attainment of undergraduate degrees with 9% of non-veterans and 13% of Veterans having earned an associate's degree (Rolen, 2017), and 34% of non-veterans and 27% of Veterans earning a Bachelor's degree or higher (Chakrabarti et al., 2023). The effect of low educational attainment on the development of ADRD varies depending on the criteria, with studies reporting very different odds depending on variables such as years of education, demographics, student-to-teacher ratio, and more (Barnes and Yaffe, 2011; Clouston et al., 2020; Crimmins et al., 2018; Sabia et al., 2018; Soh et al., 2023).

Traumatic brain injury

Traumatic brain injury (TBI) can be categorized by a range of severities from mild to severe (Livingston et al., 2020). The prevalence of TBI is complicated due to underreporting of mild TBI and variable diagnosis (Feigin et al., 2013). Studies report that TBI prevalence in non-veterans is 31% while in Veterans it is 35% (Gardner et al., 2023). These figures include males and females together. Separated by sex, 43% of male and 22% of female non-veterans, and 36% of male and 3.5% of female Veterans have TBI (Gardner et al., 2023). The difference between sexes in the Veteran population is possibly influenced by females being ineligible for combat roles and some combat training until 2015. Thus, prevalence in male non-veterans (45%) and Veterans (36%; Gardner et al., 2023; Kornblith et al., 2020) may be the most representative figures. Evidence suggests that mild TBI may increase risk of dementia by as much as 100% (Barnes et al., 2018; Walker et al., 2022). Moderate and severe TBI have been found to increase risk of dementia by 100%−300% (Plassman et al., 2000; Walker et al., 2022).

Air pollution and toxic exposures

Military activity can result in exposure to exhaust, pesticides, and heavy metals (DeBeer et al., 2017; Skalny et al., 2021) to a greater degree than what non-veterans are exposed to (Hoisington et al. 2024). Two of the most conspicuous exposures are Agent Orange and burn pits. Agent Orange is an herbicide used by the U.S. during the Vietnam War and was not used in the US (Martinez et al., 2021). An estimated 12% of Vietnam Veterans were exposed to Agent Orange (Martinez et al., 2021). Burn pits were used during Operations Enduring Freedom, Iraqi Freedom, and New Dawn to dispose of trash and human waste, often lit using jet or diesel fuel (Trembley et al., 2024). Eighty percent of Veterans deployed in these operations report being exposed to burn pits (Chari et al., 2024). Those exposed to Agent Orange and burn pits are at greater risk of cognitive decline. Veterans exposed to Agent Orange are 68% more likely to be diagnosed with dementia (Martinez et al., 2021). The risk associated with burn pit exposure varies, with one study reporting as much as a 45% increase per 2 μg/m3 increase of PM2.5 (Wilker et al., 2023).

Discussion

US Veterans have elevated prevalence of several risk factors for ADRD. Clinicians should implement a cognitive screening pathway for Veterans aged 55 years and older. Initial risk-tiering begins with patient health factors (e.g., hypertension, smoking) and screening assessments including the PHQ-9 (depression), AUDIT-C (alcohol), STOP-BANG (sleep), ACORN (social isolation), and PEG (pain). Veterans identified at high risk for cognitive disorders should undergo cognitive screening (e.g., Mini-Cog or Montreal Cognitive Assessment). Veterans with evidence of cognitive impairment would be referred to memory health or behavioral health programs. Further, based on the positive factors from the initial risk-tiering, patients should be referred for relevant treatment including 12-step programs (substance abuse), sleep medicine, a VA social worker, or pain management. These steps effectively close the loop, ensuring the patient's information and needs are delivered and acted upon. Also, VA providers should make increasing use of StayQuit Coach for smoking cessation, CogSMART for cognitive function and TBI, and the PTSD Coach app for managing symptoms of trauma. Additional programs could build on these models with interventions for physical activity, social engagement, and nutritional assistance. This pathway more effectively detects cognitive decline early, facilitating earlier intervention.

In addition to clinical improvements, there is a lot of opportunity to improve research in this area. First, there is significant variability in methodologies, and high reliance on observational or self-report measures to study risk factor prevalences. Second, it is difficult to establish causal links between risk factors and cognitive decline. These limitations should be addressed by future research. Large scale epidemiological studies with standardized methodologies, definitions, and reporting are needed to accurately compare risk factor prevalence between these populations. Further, established interventions like those for hearing impairment and smoking should be studied in the context of ADRD to evaluate long-term benefits. Additionally, studies are needed to assess the effectiveness of novel and emerging strategies including lifestyle, social, and cognitive interventions. These should include Veteran and non-veteran cohorts, as well as longitudinal elements.

While it is clear that Veterans have unique risk factor profiles, the subject is still emerging. It is possible that these risk factors have secondary or mitigating relationships that influence a Veteran's risk of cognitive decline. However, it is ill-advised to simply sum their effects because several risk factors cluster (e.g., depression, social isolation, sleep disturbance) and share causal pathways. Additionally, there are differences in risk factor prevalence within subgroups of the Veteran population. Female, racial and ethnic minority groups, rural communities, and Veterans from different service eras have different risk factor profiles. For example, estrogen may play a role in females developing ADRD more often than males (Kang and Grodstein, 2012; Yaffe et al., 2000) and Black and Hispanic minorities have greater prevalence of cardiovascular disease and diabetes (2024 Alzheimer's disease facts and figures, 2024; Daniel et al., 2023). Finally, care access patterns of subgroups must also be considered. For example, those living in rural communities may have transportation limitations (Syed et al., 2013; Wiese et al., 2023) and Veterans of different service eras often experience delays in eligibility related to unique exposures (e.g., Agent Orange; Chari et al., 2024). Combinations of risk factors, groups, and subgroups currently make accurate estimates of prevalence difficult, but these estimates must be pursued as this field advances.

Conclusion

This perspective highlights the importance of addressing the unique risk factor profile of Veterans for the development of ADRD. New efforts to reduce the effect of risk factors for ADRD could improve outcomes and reduce burdens to Veterans and their caregivers. While the impact of addressing these risk factors is difficult to calculate precisely, an estimated 45% of dementia cases are attributed to modifiable risk factors (Livingston et al., 2024). This suggests a significant opportunity for improving health outcomes. The Alzheimer's Association estimates $7 trillion could be saved by the year 2050 by detecting Alzheimer's Disease in the stage of MCI (Porsteinsson et al., 2021). Conducting standardized cognitive screening at an earlier age and on a regular basis may be a key to achieving these goals, because it would allow for earlier detection and intervention, as well as better understanding of risk profiles.

Acknowledgments

This material is based upon work done as part of the Advanced Fellowship in Geriatrics supported by the US Department of Veterans Affairs Office of Academic Affiliations, the Malcom Randall VA Medical Center, and the Department of Veterans Affairs North Florida/South Georgia Geriatric Research, Education, and Clinical Center (GRECC). This material is the result of work supported with resources and the use of facilities at the Malcom Randall VA Medical Center, Gainesville, Florida.

Funding Statement

The author(s) declared that financial support was not received for this work and/or its publication.

Footnotes

Edited by: Sara Palermo, University of Turin, Italy

Reviewed by: Mauro Silvestrini, Marche Polytechnic University, Italy

Che-sheng Chu, Kaohsiung Veterans General Hospital, Taiwan

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

RM: Conceptualization, Investigation, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing. BC: Conceptualization, Project administration, Writing – review & editing, Supervision. LS: Conceptualization, Project administration, Supervision, Writing – review & editing. DC: Conceptualization, Project administration, Supervision, Writing – review & editing.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

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Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

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