Weathering Within War: Somatic Health Complaints Among Vietnamese Older Adults Exposed to Bombing and Violence as Adolescents in the American War

Abstract

Objective:

People living in war may experience deteriorating health via weathering (wear and tear) from long-term exposures to psychosocial and environmental stressors. Weathering embodied in somatic health complaints may illuminate the effects of war on health.

Methods:

We investigate whether wartime stress exposures occurring during adolescence and early adulthood affect weathering in late adulthood via linear regression with data from the Vietnamese Health and Aging Study (VHAS). VHAS is a cross-sectional study wherein investigators surveyed 2,447 adults aged 60+ in four districts of northern and central Vietnam in 2018. These same individuals ranged in age from seven to 52 in 1965, with most having been in adolescence or early adulthood at the peak of the American war in Vietnam (1965–1975). The sample used for this study (n = 2254) were participants in the first VHAS wave in 2018.

Results:

We find older Vietnamese adults exposed to higher-intensity provincial bombing suffer more numerous somatic health complaints (unstandardized β = 0.005, SE = 0.001, p = 0.001). Additionally, greater health complaints emerge among older adults whose most intense bombing exposures were at younger ages of adolescence (< age 15) as compared to those whose peak exposures were in older ages (19–25) (unstandardized β = 0.62 95%, SE = 0.19, p = 0.01).

Conclusion:

Our findings suggest that age of exposure to armed conflict is a critical determinant of weathering across the life course.

1. Introduction

Armed conflict exposes individuals to traumatic events and begets subtle accumulation of exposures to violence, food insecurity, familial fracturing, and unpredictability [1]. Trauma refers to events experienced or witnessed that pose threats to ones life or injury and may induce extremes of fear and psychological overwhelm [2]. Experiencing early life adversity in the form of unexpected family death, deprivation, and threat has been associated with accelerated biological aging [3] and worse overall health [4,5]. Adversities via wartime exposures in childhood and adolescence have been associated with varied effects on physical growth, like stunting [6–8], PTSD [7,9,10] and elevated subjective age relative to chronological age [11].

The gravity of war’s adverse consequences often depends on the timing, duration, and magnitude of exposures [1]. Although studies of health following traumatic exposure are typically focused upon the immediate post-conflict time frame [10], cumulative exposures to wartime stress in early life may have a lasting influence on health, shaping the biological and psychological underpinnings of late-life disease [12–14]. The “long reach of trauma” extends from early to late life through potential systemic dysregulation as well as proliferating chains of risk wherein adversity begets subsequent adversity [15,16]. While early life holds more critical periods of physical and psychosocial development, we maintain one potential pathway through which health deficits can occur is through weathering of the soma at any point of the lifespan, or effects of weathering embodied through somatic health complaints. Repeat high-impact stress exposure during armed conflict, combined with experiencing these insults during a time of heightened developmental plasticity poses a unique circumstance to investigate one potential pathway by which war exposures become embodied.

1.1. Embodiment of War and Somatic Health Complaints

Weathering is one potential framework to understand war time stress exposures that are often chronic and severe in nature [17–21]. These weathering effects may manifest as disparate functional limitations, allostatic load, and other health outcomes, but the processes of weathering and accelerated aging likely begin far earlier in the lifecourse. Compared to communities facing systemic oppression and exclusion (e.g., Black Americans or Indigenous populations) [22], weathering as a process among armed conflict-affected populations is less clear and warrants further investigation.

Traumatic war exposures and displacement have been robustly linked to development of conditions such as PTSD, depression, and anxiety [23–25]. These exposures may also “get under the skin” [26–28] or become “embodied” [29,30] and contribute to somatic health complaints that are not explained by physical comorbidities, also known as somatization or somatic distress [31,32]. Somatoform pain is pronounced in populations displaced by war and violence, often occurring alongside posttraumatic stress symptoms [33,34]. Some research suggests individuals exposed to armed conflict will present with psychosomatic symptoms that may be highly correlated with other psychological outcomes. For example in a large cross-sectional study of Syrian refugees residing in Turkey a few years following displacement, somatic distress prevalence was 53% and was associated with PTSD, depression, anxiety, and women were more likely to report somatic distress [35]. Moreover, there have been similar associations between traumatic war exposures and somatic complaints among female widows who survived the Kosovo War [36], Southern European torture victims [37], and Palestinian refugee children in the West Bank [34].

Still, there are relatively few studies addressing the relationship between somatic complaints in adulthood in relation to early life armed conflict exposures. One study that followed Kuwaiti individuals 12 years after childhood armed conflict exposures during the 1990–1991 Gulf Crisis found that psychological impacts from the war continued in adulthood [38]. Another study of mid-aged Indigenous Quechua women who were exposed to political violence in Peru (1980’s-2000) found that only ~9% of participants (n =151) were likely to have PTSD despite high levels of violence, though the authors did not assess age gradients in exposure [39]. A cross-sectional study of internally displaced persons in the Republic of Georgia in the 1990’s and 2008, found heightened risks for somatic distress even after the ostensible passage of time [40]. Moreover, in a study eight years after war exposures, somatic distress was prevalent among 12.9% of Kosovar civilian war survivors in a separate study [41].

Very few if any studies examining somatic outcomes to our knowledge have investigated age at exposure. We speculate that proliferation of somatic complaints may be on a pathway through which weathering or accelerated ageing is occurring. This may be particularly applicable to the case of the American War in Vietnam, as adolescents experienced heterogeneous, but often severe stressors, across different stages in the transition to adulthood.

1.2. The American War in Vietnam

The American War in Vietnam, which began in the late 1950s, escalated in 1965 with the massive deployment of U.S. ground troops, and concluded with the April 1975 Liberation/Fall of Saigon. It was among many protracted conflicts that transformed Vietnamese society and fundamentally impacted individuals’ health and wellbeing [42]. Vietnam and its neighbors in Indochina, Laos and Cambodia, were targets of one of the most intense aerial bombing episodes in history (Khamvongsa & Russell, 2009). U.S. bombing (hundreds of kilograms of explosives per capita) resulted in loss of life, widespread destruction of infrastructure, shortages of food and other necessities, and extensive displacements, including village evacuations and the relocation of schools and other infrastructure to the countryside and mountainous areas outside of heavily targeted areas [43].

From the 1960s to 1980s, the People’s Army of Vietnam (PAVN) was one of the largest in the world [44]. Broad mobilization of young people for the war effort also extended to the Youth Shock Brigades (YSB), units of young men and women ages 15–30 who rebuilt bombed roads, dikes, bridges, and segments of the Ho Chi Minh Trail [45,46]. Enlisted for three-year commitments, the YSB members, who were disproportionately young women, were provided very modest salaries and provisions compared to the formal military. The YSB were combat units “when necessary,” working under the threat of explosion, defusing bombs, and firing at enemy planes (Van Dyke 1976: 46).

In this paper, we investigate the extent to which high-intensity bombing and wartime trauma exposures occurring during adolescence and early adulthood affect somatic health complaints. Our analyses focus upon northern Vietnamese adults who were in their teens and early twenties during the height of the American War in Vietnam (1965–75). Moreover, we discuss potential theoretical frameworks of weathering and accelerated aging in a war-affected population informed by developmental and psychoneurological perspectives.

1.3. Hypotheses

We hypothesize somatic health complaints will be greater among individuals who report more intense or numerous exposures to armed conflict (H1). Since the experience of wartime stressors was spatially heterogeneous, we hypothesize that those who resided in areas with greater bombing intensity will experience more somatic health complaints than counterparts less exposed (H2). We further hypothesize that the ill effects of both self-reported individual-level exposures and area-level exposures will be greater when experienced at younger adolescent ages (H3).

2. Method

2.1. Research Participants and Data Collection

This study uses data from the Vietnam Health and Aging Study (VHAS), developed to study the effects of armed conflict exposure during the American War in Vietnam on the long-term health of older adults [47]. Investigators surveyed 2,447 adults aged 60 and older in four districts of northern and central Vietnam in 2018. These same individuals ranged in age from seven to 52 in 1965, with most having been in adolescence or early adulthood at the peak of the American war in Vietnam.

The four sampled districts in northern and central Vietnam were purposively selected to represent an array of exposures to war, as indicated by the intensity of bombings during the 1960s and 1970s (ibid.; Miguel & Roland 2011). Within districts, stratified random sampling was used. Twelve communes were randomly selected from within the districts, and respondents were randomly selected within the communes, with oversampling to ensure adequate analytical samples in four sampling domains: male military, female military, male nonmilitary, and female nonmilitary. The military subdomains include those who served in the formal military (e.g., PAVN) as well as those who volunteered in local militias and the YSB. The VHAS sample size was determined through power calculations based upon prevalence rates for several chronic conditions observed within gender and military service subdomains in a pilot study, as well through considerations of necessary sample size within subdomains to allow for stable multivariate regression analyses across several health status outcomes (Korinek et al 2019). Sampling weights were calculated to account for the oversampling of female military and male nonmilitary respondents. In-person interviews were conducted in participants’ homes and took two hours, on average, to complete. The interview instrument assessed numerous dimensions of military service, wartime experiences including combat-linked violence and traumatic exposures, health, income and assets, family background, migration history, and social connections and support.

2.2. Measures

Dependent Variable

Somatic Health Complaints were based upon the number of affirmative responses to a question asking whether respondents had experienced the following health complaints in the past month: headache, insomnia, chest pain, joint pain, back pain, dizziness, stomachache, coughing, and difficulty breathing. The VHAS survey drew upon the Symptom Checklist 90 (SCL-90), which has been deployed in a wide variety of countries and is the recommended tool for researching somatization in population studies as long as the researchers control for diagnosed physical conditions [48–50], a recommendation we follow in this analysis. By adjusting for comorbidities that may be medically-linked to health complaints, we are better positioned to identify ‘medically unexplained’ symptoms which capture the somatization construct. Cronbach’s Alpha for Somatic Health Complaints is .7077 (unstandardized) and .7070 (standardized).

Independent Variables

War Exposure—

We assess respondents’ war exposure in several ways. First, through an index of self-reported experiences of seeing the dead and severely injured, being wounded in combat, knowing people who were injured, perceived exposure to toxic chemicals, and engagement in combat activities. Since the items that capture war exposure differ for civilians, informal military, and formal military in this population, we follow Young and colleagues (2021) in constructing separate indices for the three groups. To allow for analysis of the three groups together in a single analytical model, we standardized the index score for each respondent [51].

Second, using Department of Defense data detailing American and Allied bombing sorties from 1965–1975, we constructed a count of bombings per square kilometer for each province and year. Using respondents’ self-reported locations during this war decade through detailed migration histories, we identified the most intense bombing (annual bombs/km²) to which they were exposed during the decade. We know that most respondents were currently residing in the locations of their birth, suggesting a low level of lifetime migration.

Our third war exposure measure describes respondents’ type of military service. Because individuals who served in militias and the Youth Shock Brigades (YSB) are qualitatively different from veterans of the formal military, vis-à-vis their terms of service, potential stress exposures, and post-service status and benefits, we create a three-category variable to characterize military service. Specifically, respondents are categorized as having been civilians (i.e., no military service), informal military participants (served in militias or the YSB), or formal military veterans. Those with both formal and informal service are categorized as formal military veterans.

Age at Exposure—

In keeping with our theoretical focus upon developmental periods of exposure as they pertain to the embodiment of trauma, we include a variable specifying the respondent’s age in 1965, the beginning of the peak decade of the war. We also include a variable delineating the respondent’s age at the time they experienced their most intense exposure to bombing (based on their self-reported locations during the war decade). Both age variables are assessed in the following categories: young adolescent (< age 15), mid-late adolescent (ages 15–18), young adult (ages 19–24), and adult (age 25+).

Other covariates:

Comorbidities—

To compensate for the fact that some health complaints may be related to diagnosed or undiagnosed medical conditions, we control for those conditions with a measure of comorbidities. It is an additive index of self-reported medical conditions, both those reported as doctor-diagnosed and those perceived by the respondent but lacking formal medical diagnosis, including: hypertension, diabetes, lung diseases and cardiopulmonary disorders, cancers, liver diseases, stroke, arthritis, asthma, and heart conditions.

We also control for PTSD and mental health conditions. Our PTSD measure is a raw score based upon the respondent’s self-reported history of experiencing PTSD symptoms. Symptoms are cataloged with nine questions drawn from the PTSD Checklist (PCL-5). The questions span each of the four diagnostic clusters for PTSD—re-experiencing, avoidance, dysphoria, and hyperarousal (Price et al. 2016). These items, scored from 0 to 3, inquired whether respondents had experienced a symptom and to what extent it bothered them— not at all, a little bit, moderately, or a lot. We generate raw PTSD scores as the sum of all possible points for the nine questions. We also assess mental health in a more general sense based on the respondent’s self-report of having or being diagnosed with a mental health condition.

Our models also control for several social and demographic covariates pertinent to health status and somatic health complaints. Specifically, we include measures for the respondent’s gender (interchangeable with sex in this context), age, education, and occupation. Due to low overall levels of education among the VHAS cohort, we measured education as a binary indicator of primary education completion. Occupation is a three-category variable capturing whether the respondent’s main lifetime occupation was in agriculture, a professional/government occupation, or other nonagricultural occupation.

2.3. Statistical Analyses

This study models somatization as the number of health complaints endorsed by respondents. We begin by examining summary statistics and the distribution of health complaints across gender, military service type, and life course timing of the war. We then evaluate the bivariate associations between health complaints and other physical and mental health conditions. Next, we use survey-adjusted ordinary least squares (OLS) regression models with sampling weights. Survey adjustments account for the stratified sampling methods and adjust error terms for error that is shared across sampling areas. We chose to use OLS rather than Poisson models for our health complaints measure since our dependent variable is approximately normally distributed, as are error terms. Further, Hausman model comparison tests found that the differences in the coefficients for the two model types are statistically significant, and the AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion) values are substantially lower in the OLS regression.

2.4. Ethics Approvals and Consent

Ethics approval for the original VHAS study was obtained from the University of Utah’s Institutional Review Board (IRB_00099861), Mount Saint Vincent University’s Research Ethics Board (2018–047), Singapore Management University’s IRB (IRB-18-031-A034(318)), Hanoi Medical University’s Independent Review Board in Bio-medical Research (IRB No. 01.18/HDDDDHYHN) and Vietnam’s Ministry of Health (No. 29/CN-HDDD). All research participants gave written informed consent for data collection.

3. Results

3.1. Participant Characteristics

From the initial sample (n = 2,447), 121 presented missing data in one or more of the health complaints, war exposure, or confounding variables and were excluded from the present analyses. Most of the missing data are from full proxy interviews (n=75), in which proxy respondents were precluded from answering subjective questions (e.g., health complaint items) for the respondent. An additional 72 participants were missing data on the PTSD and/or mental health measures and thus are excluded from the full multivariable models (n = 2254). Reflecting the sampling approach, among northern Vietnamese adults participating in the VHAS, gender is approximately evenly distributed (42% men, 58% women). With an average age of 70 years, 47% of the analytical sample were between the ages of 15 and 25 when they experienced their most intense bombing exposure. Nineteen percent of participants obtained greater than secondary education. Roughly two-thirds of individuals were employed in agriculture in their main lifetime occupation, whereas 20% held professional/government roles, and 13% were employed in manufacturing, construction, and other low-skill occupations. Fifty-seven percent of participants were considered civilians or noncombatants during wartime, whereas 40% participated in the informal military, and approximately 24% participated in the formal military (Table 1).

Table 1.

Descriptive Statistics

Full Sample (n= 2254)	Mean/Percenta	Std. Deviation	Minimum	Maximum
# Health Complaints	4.14	2.25	0	10
War Exposure
Province-level bombing intensity (per km2)	22.78	35.27	0.01	164.15
Index of individual war exposureb	−0.12	1.00	−1.43	4.10
Military service type (% shown)
Civilian	56.63
Informal military	19.74
Formal military	23.62
Life-course Factors
Current age	69.83	7.92	59	98
Age in 1965
< 15 years old	49.47
15–18 years old	16.11
19–24 years old	13.59
25+ years old	20.83
Age at most intense bombing
< 15 years old	22.45
15–18 years old	25.46
19–24 years old	21.67
25+ years old	30.42
Potential confounders
# Diagnosed health conditions	1.82	1.40	0	9
Functional limitations	2.62	2.41	0	7
Mental health problems
No	87.04
Yes, I feel I have this condition	11.65
Yes, a doctor diagnosed this	1.30
PTSD raw score	2.55	3.67	0	21
Control Variables
Sex
Male	41.97
Female	58.02
Education: more than secondary (%)	19.32
Occupation (% shown)
Agricultural	66.50
Professional	20.46
Other	13.04

^aMeans and percentages are survey-adjusted with sampling weights applied.

^bIndices are standardized for subgroups of civilians, informal and formal military; thus, means are near zero, and the minimum value is negative.

3.2. Health Complaints, Mental Illness, and War Exposures

Participants reported an average of 4.14 (standard deviation (SD): 2.25) health complaints (Table 2). They additionally report 1.82 (SD: 1.40) diagnosed health conditions and an average of 2.62 (SD: 2.41) functional limitations. An overwhelming majority of the participants disclose no mental health problems, though 13% report they have a mental health condition. Only 2% of participants report a physician-diagnosed mental health condition. Furthermore, the average PTSD raw score, based upon the modified PCL-5 checklist, is 2.55 out of a maximum possible score of 27, with a standard deviation of 3.67. For context, a raw score of three would indicate that a respondent either reported several low severity symptoms or one severe symptom. We find a relatively strong correlation between mental health conditions and somatic health complaints, as well as between somatic health complaints and PTSD raw scores (see Table 3).

Table 2.

Variable means and percentages by number of health complaints

	Full Sample n=2,254	# Health Complaints
		0	1–3	4–6	7+
# Health Complaints	4.1
War Exposure
Province-level bombing intensity (per km2)	22.8	19.2	18.3	25.0	27.7
Index of individual war exposureb	−0.1	−0.3	−0.2	−0.1	0.01
Military service type (% shown)
Civilian/Noncombatant	56.6	67.2	61.3	54.8	48.0
Informal military	19.7	15.2	18.4	25.2	33.6
Formal military	23.6	17.6	20.3	20.1	18.4
Life-course Factors
Current age	69.8	68.8	69.6	70.2	69.7
Age in 1965 (% shown)
< 15 years old	49.5	52.2	52.5	47.4	47.6
15–18 years old	16.1	14.0	12.8	17.8	19.4
19–24 years old	13.6	15.1	13.5	13.5	13.6
25+ years old	20.8	18.6	21.3	21.2	19.5
Age at most intense bombing (%)
< 15 years old	22.5	20.6	19.7	22.4	28.9
15–18 years old	25.5	29.7	27.3	24.1	23.7
19–24 years old	21.7	21.8	22.4	22.4	18.0
25+ years old	30.4	27.8	30.5	31.0	29.4
Potential confounders
# Diagnosed health conditions	1.8	0.7	1.3	2.0	2.9
Functional limitations	2.6	0.5	1.7	3.0	4.2
Mental health problems (% shown)
No	87.0	99.0	95.3	85.2	70.4
Yes, I feel I have this condition	11.7	0.6	4.0	13.4	27.0
Yes, a doctor diagnosed this	1.3	0.4	0.7	1.4	2.6
PTSD raw score	2.6	0.8	1.5	3.0	4.5
Control Variables
Sex (% shown)
Male	42.0	62.0	54.3	33.6	31.2
Female	58.0	38.0	45.7	66.4	69.0
Education: more than secondary (%)	19.3	44.1	23.7	15.7	11.3
Occupation (% shown)
Agricultural	66.5	42.1	64.7	68.2	73.9
Professional	20.5	14.7	15.4	12.9	7.9
Other	13.0	43.2	19.9	19.0	18.2

^aMeans and percentages are survey-adjusted with sampling weights applied.

^bIndices are standardized for subgroups of civilians, and informal and formal military, thus means are near zero, and the minimum value is negative.

Table 3.

Correlations between Health Complaints and Mental Health

	Health complaints	Mental health problems	PTSD raw score
Health complaints	1.00
Mental health problems	0.38*a	1.00
PTSD raw score	0.36*b	0.34*a	1.00

^aPolyserial correlation

^bPearson correlation

Concerning war exposures and their life course timing, roughly 79% of the participants were under age 24 in 1965, and 70% were under age 24 when they experienced their most intense exposure to bombing in the American War. The individual-level war-exposure index, standardized at a mean of zero, ranged among participants from 1.43 SDs below the mean to 4.10 SDs above the mean, indicating a right-skewed distribution.

3.3. Model Results

The multivariate models of somatic health complaints offer some support for our three hypotheses. Additionally, the number of somatic health complaints was attenuated by potential confounders including physical health conditions, believing one had a mental health condition (but not by a mental health condition diagnosis), and raw PTSD score (see Table 4).

Table 4.

Regression Models with Standard Errors Shown

	Base Model		Health Conditions		Functional Limit.		Mental Health		PTSD		All
	B (S.E.)	p	B (S.E.)	p	B (S.E.)	p	B (S.E.)	p	B (S.E.)	p	B (S.E.)	p
War Exposure
Province-level bombing intensity	0.007	0.01	0.006	0.01	0.006	p < 0.001	0.006	0.01	0.005	0.03	0.005	0.001
	(0.002)		(0.002)		(0.001)		(0.002)		(0.002)		(0.001)
Individual war exposure index	0.29	0.002	0.15	0.002	0.13	0.02	0.11	0.01	0.01	0.38	0.01	0.38
	(0.07)		(0.04)		(0.05)		(0.04)		(0.05)		(0.06)
Military service (ref: civilian)
Informal military	0.41	0.01	0.30	0.03	0.24	0.05	0.31	0.01	0.16	0.15	0.17	0.06
	(0.13)		(0.122		(0.12)		(0.09)		(0.12)		(0.08)
Formal military	0.72	0.002	0.50	0.004	0.49	0.002	0.51	0.002	0.29	0.06	0.36	0.01
	(0.18)		(0.14)		(0.12)		(0.12)		(0.14)		(0.11)
Life course Factors
Age in 1965
15–18 years old (ref: < 15)	0.67	0.001	0.26	0.11	0.19	0.12	0.23	0.12	0.20	0.17	0.14	0.18
	(0.13)		(0.16)		(0.13)		(0.15)		(0.15)		(0.11)
19–24 years old	0.28	0.24	−0.28	0.02	−0.36	0.01	−0.21	0.10	−0.29	0.03	−0.31	0.06
	(0.31)		(0.11)		(0.12)		(0.12)		(0.12)		(0.16)
25+ years old	0.18	0.36	−0.20	0.28	−0.60	0.02	−0.09	0.35	−0.17	0.29	−0.45	0.04
	(0.52)		(0.26)		(0.23)		(0.20)		(0.23)		(0.19)
Age at most intense bombing
15–18 years old (ref: < 15)	−0.43	0.02	−0.16	0.22	−0.13	0.26	−0.08	0.33	−0.10	0.29	−0.05	0.37
	(0.16)		(0.16)		(0.15)		(0.16)		(0.14)		(0.14)
19–24 years old	−0.84	0.02	−0.62	0.01	−0.68	0.01	−0.58	0.01	−0.57	0.01	−0.62	0.01
	(0.32)		(0.20)		(0.22)		(0.19)		(0.17)		(0.19)
25+ years old	−0.69	0.15	−0.27	0.24	−0.32	0.19	−0.32	0.18	−0.23	0.26	−0.31	0.19
	(0.50)		(0.29)		(0.28)		(0.26)		(0.27)		(0.26)
Potential confounders
# Diagnosed health conditions			0.75	p < 0.001	0.58	p < 0.001	0.71	p < 0.001	0.68	p < 0.001	0.54	p < 0.001
			(0.03)		(0.02)		(0.02)		(0.03)		(0.03)
# Functional limitations					0.29	p < 0.001					0.23	p < 0.001
					(0.03)						(0.03)
Mental health problems (ref: No)
Yes, I feel I have this condition							0.94	p < 0.001			0.50	0.03
							(0.17)				(0.20)
Yes, a doctor diagnosed this							0.56	0.05			0.28	0.19
							(0.27)				(0.24)
PTSD raw score									0.14	p < 0.001	0.10	p < 0.001
									(0.01)		(0.02)
Control Variables
Sex: Female	1.1	p < 0.001	1.01	p < 0.001	0.75	p < 0.001	0.95	p < 0.001	0.90	p < 0.001	0.70	p < 0.001
	(0.16)		(0.11)		(0.10)		(0.12)		(0.12)		(0.12)
Education: more than secondary	−0.81	0.01	−0.65	0.01	−0.48	0.06	−0.62	0.01	−0.65	0.01	−0.49	0.05
	(0.24)		(0.21)		(0.24)		(0.21)		(0.21)		(0.23)
Occupation (ref: Agricultural)
Professional	−0.09	0.36	−0.29	0.12	−0.23	0.16	−0.22	0.19	−0.20	0.22	−0.14	0.26
	(0.23)		(0.19)		(0.17)		(0.19)		(0.19)		(0.16)
Other	−0.39	0.03	−0.35	0.02	−0.33	0.02	−0.26	0.07	−0.30	0.04	−0.24	0.08
	(0.16)		(0.13)		(0.12)		(0.14)		(0.13)		(0.13)
Constant	2.59	p < 0.001	1.43	0.001	1.49	p < 0.001	1.41	0.002	1.39	p < 0.001	1.44	0.001
	(0.34)		(0.29)		(0.28)		(0.32)		(0.29)		(0.31)
N	2326		2326		2326		2260		2320		2254
R-squared	0.13		0.33		0.39		0.34		0.36		0.40

The models partially support H1, that self-reported exposure to war-related stressors is associated with more numerous somatic complaints net of other predictors. However, the effect size and significance of individual-level exposures decreased when all potential confounders were included in the model. When all physical and mental health confounders are included, evidence for this hypothesis weakens. In addition, military service as a proxy for combat experiences is also a key predictor. Formal military service remained a strong predictor of somatic health complaints in the full model, whereas informal military service did not. Compared to civilians, having participated in the informal military is associated with elevated health complaints; however, this positive association is largely attenuated when PTSD symptoms are included as a model covariate. On the other hand, formal military service is associated with significantly elevated health complaints.

We suspected that gendered effects may play out in types and extent of military service. When comparing the mean number of health complaints by gender and military service, we find clear distinctions (Table 4, Base Model). Women who served in the informal military report the highest average number of health complaints, followed by women who served in the formal military and civilian women (Fig 1). Civilian men report the fewest mean health complaints, followed by higher mean complaints among men who served in the informal and formal militaries.

Figure 1.

Health complaints by gender and military service type

With respect to our second hypothesis, we find that, net of other predictors, those who had greater exposure to high-intensity bombing (by province) report more somatic health complaints. In the full model containing all confounders, the effect size and significance of bombing intensity decreased but remained statistically significant (H2).

Finally, both the descriptive summaries and the multivariate models present marginal support that armed conflict’s ill effects will be more substantial when experienced at younger ages (H3) (see Figure 2, Figure 3, and Table 4). Specifically, fewer health complaints emerge among respondents whose most intense bombing exposures were at relatively older ages as compared to those whose peak exposures were younger (under age 15). While only the 19–24 year-old age range was statistically significant in the full model, the pattern of results suggests experiencing intense bombing at relatively young ages may be related to a greater weathering penalty. However, the oscillations around age categories are noted with caution.

Figure 2.

Health complaints by Age in 1965

4. Discussion

Behrouzan (2018) reminds us that every war has an afterlife: socially, economically, psychologically, and in terms of health. While each war is distinct, they are consistent in that they create an ‘environment’ with a cluster of stressors imposed upon populations that may become embodied, while varying across individual, community, and societal levels [52]. Recent research posits childhood adversity directly impacts young adult health, and may have indirect yet potent impacts on late life health [53]. Extending this further, it is plausible that weathering in the context of war is detectable as a direct, embodied effect on health if examined shortly following an armed conflict experience but may manifest indirectly as somatic health complaints later in life. However, the many possible pathways and mechanisms through which war may “get under the skin” and impact human health may be underappreciated and warrant far more attention. While research on somatic health complaints includes understanding relationships between somatic distress and traumatic exposures, our study is the first to unite developmental perspectives on adolescence, impacts of traumatic war exposures (namely aerial bombing), and somatization in a theoretical context of weathering.

We found older Vietnamese adults who had greater exposure to high-intensity bombing earlier in life reported more somatic health complaints (H1), consistent with other research suggesting aerial bombings elevate risks of somatic health complaints [54,55] and numerous research showing exposure to aerial and atomic bombing has profound impacts on physical and psychosocial health and disability [56–60]. Weathering or accelerated biological “wear and tear” associated with stress exposure is commonly observed through biological markers of aging [17,61–63]. However, in a context wherein bodily symptoms jointly signal an amalgamation of psychological and physical harms, our findings provide preliminary insights into accelerated aging and weathering.

While we did not make a priori predictions about gender, we found that women who served in the informal military reported higher average somatic health complaints, whereas civilian men reported the fewest. Men born to more well-off parents were most likely to be adversely impacted and more likely to have died of acute causes [64], whereas others represent those who survived, carrying the long-term, accumulated impacts of war. Women, however, especially those transitioning to adulthood, may have had to bear the brunt of childcare, family caretaking, and other dynamic roles. Similar to recent findings assessing gendered impacts of the war on PTSD [65], we speculate that women serving in the informal military may have been at greater risk for higher average somatic health complaints due to balancing dual burdens of familial caretaking as well as being assigned military roles with less training and support than men. This is congruent with other studies that show somatic distress may be more commonly experienced or reported by women [66]. Further research should examine potential interactions between gendered experiences, life course timing, and war exposures on somatic health and aging.

Also salient are individual-level exposures to death, violence, and hostile conditions linked to warfare. Here we employ life course factors, including age in 1965, age at the time individuals experienced the most intense period of bombing, as well as an index of self-reported war-related experiences. We found that persons aged 19–24 at peak bombing intensity had significantly fewer health complaints than those younger than 15 years old (our referent age category, and the largest proportion of the sample) (H3), aligned with research suggesting adolescent exposures to trauma impact risks for development of psychological distress and psychopathologies [67–69]. These patterns offer some support for the proposition that experiencing intense bombing at relatively young ages may be associated with a greater aging penalty. Furthermore, the individual war exposure index was significantly associated with more health complaints in our initial regression model, but not after inclusion of confounders and controls, in particular PTSD symptoms. This potentially implies a mediating effect for physical and mental health conditions that should be explored in future research.

4.1. Limitations and Strengths

One limitation is the cross-sectional design of the VHAS taking place in Northern Vietnam only. However, future waves of the VHAS may extend the study to the former Republic of Vietnam (South), a segment of the country with arguably more intense profile of stress exposures. Recall of stress exposures may also present potential bias. While recall bias is a challenge in war-related literature, recollection of traumatic experiences from childhood and adolescence are likely to be underreported than overreported [70] and traumatic events that are highly memorable or distressing at the time (e.g., bombing) are less likely influenced by recall bias [71]. Lastly, selective mortality is also a potential limitation. A majority of deaths during the American War in Vietnam happened 1965–1975 from acute causes, therefore the current cohort is representative of individuals who survived acute exposures but may still deal with the chronic biological and psychosomatic consequences of the war. In this way, effects of war on somatic health complaints may be underestimated in the case that selective mortality influenced the current sample, especially because the impacts of war exposure experienced in adolescence may remain across the lifecourse and appear during stages of frailty later in life [72].

These limitations notwithstanding, our study contributes to understanding war as an environment by probing potential pathways through which war can contribute to weathering. We specifically focus on late adolescent and early adult exposures and attempt understand the lasting impacts of the American War in Vietnam and how those effects layer onto developmental perspectives regarding the timing of exposure in a framework of weathering. While war is certainly not the only defining feature of this population, the experiences of the research participants may interact with wartime exposures to shape susceptibilities for ill-health and accelerated aging. Our use of somatic health complaints in the context of war-driven stress, is important as somatic complaints may capture underlying weathering in a context where formal diagnoses of both physical and psychological conditions may not occur (for various reasons) and because they greatly influence older adults’ quality of life.

Highlights.

• Aerial bombardment at relatively younger ages resulted in more somatic complaints

• ‘Weathering’ should be applied to health research on armed conflict and war

• Somatic health complaints can mirror somatoform pain or somatization

• Community and individual stressors make up a biosocial environment of war

• Early adult war exposure mediated by PTSD associates with somatic complaints

Appendix A

Fig. A.1.

War Index Exposure by Age