Obesity and Morbidity Risk in the U.S. Veteran

The Impact of Adversity on Body Mass Index as Veterans Transition to Civilian Life

INTRODUCTION

The impact of adverse childhood experiences (ACEs), warfare exposure, and mental health symptoms upon changes in body mass index (BMI) were examined in a large U.S. post-9/11 veteran sample to assess gender-specific changes in BMI within the first 2½ years after military service.

MATERIALS AND METHODS

Data were collected with institutional approval in 6 waves between 2016 and 2019 from veterans who (1) separated from active duty component service branches (i.e., Army, Navy, Air Force, and Marine Corps) or National Guard or Reserve or (2) deactivated from active duty status after serving in a National Guard or Reserve component. Veterans self-reported height and weight at separation/deactivation at wave 2, and weight was asked at each subsequent wave. Multilevel growth model analyses estimated the relationship between ACEs, warfare exposure, and mental health symptoms and BMI for males and females. Weighted wave 5 analyses were conducted to ensure the sample was calibrated for nonresponse based on wave 1 and the full sample (n = 48,965) for each cross-classification of the weighting variables of gender, rank, and branch.

RESULTS

Approximately one-third of the veterans reported a normal BMI at separation/deactivation in comparison to being overweight (51%) or obese (20%). Twenty-six percent of male veterans had a normal BMI in contrast to almost half of the female veterans. Male veterans who experienced 3-7 ACEs had a higher BMI (0.74) compared to male veterans without any ACEs, where a BMI increase of 0.08 per year was reported. Female veterans who experienced 1-2 ACEs had a higher BMI (0.89) compared to female veterans without ACEs. Male veterans who engaged in warfare (e.g., combat patrols and firing a weapon at enemy combatants) and experienced corollaries (i.e., consequences of combat) or who experienced corollaries alone (e.g., saw refugees who lost their homes/belongings) had higher BMIs (1.14 and 0.82, respectively) compared to male veterans without warfare exposure. Female veterans who experienced corollaries had a higher BMI (0.94) compared to female veterans with no warfare exposure. Female veterans who experienced warfare (i.e., corollaries and combat) had a higher BMI (0.71) compared to female veterans with no warfare exposure. Male veterans who screened positive for likely post-traumatic stress disorder (PTSD) or depressive symptoms had a higher BMI (1.01 and 0.52, respectively) compared to male veterans who did not screen positive. Male veterans who screened positive for likely PTSD increased their BMI by 0.10 per year. Male veterans who screened positive for both likely PTSD and depressive symptoms had a higher BMI (1.32) compared to male veterans who did not screen positive, and they increased their BMI by 0.21 per year. Female veterans who screened positive for likely PTSD and depressive symptoms had a higher BMI (0.78) and increased their BMI by 0.25 per year compared to female veterans who did not screen positive.

CONCLUSIONS

Boosting veterans' and service members' mental and emotional healing from childhood and warfare adversities through sound health promotion policies and increased access to evidence-informed interventions is imperative for optimal body weight and physical health.

Gender Differences in "Making Weight" Behaviors Among U.S. Iraq and Afghan War Veterans: Implications for Future Health

Objective: Failure to "make weight" carries significant consequences for military personnel including additional training burdens, stigma, possible demotion, or even separation from service. The aim of this study was to examine potential gender differences in, and investigate relationships between, military making weight behavior and obesity, eating pathology, and mental health later in life. Method: Iraq and Afghanistan war era Veterans (N = 1,126, 51.8% women) completed the Making Weight Inventory (MWI), a measure of making weight behaviors engaged in during military service, and validated measures of eating behavior and mental health. Analyses compared participants who engaged in at least one making weight behavior (MWI+) versus those who did not (MWI-). Results: Overall, 41% (n = 462) of the sample was categorized as MWI+. The most frequently endorsed making weight behavior was excessive exercise (35.7%). Among those who were MWI+, there was a significantly greater proportion of women (58.2% versus 47.3%, p < 0.001). The MWI+ group had higher rates of obesity (52.4% versus 26.2%) and had significantly higher levels of dietary restraint, emotional eating, food addiction, depression, anxiety, and posttraumatic stress disorder than the MWI- group (p's < 0.001). Conclusions: Military making weight behavior was associated with female gender, higher weight, eating pathology, and mental health later in life. Collectively, these findings suggest these factors may place female service members at a disadvantage for career advancement and salary. Efforts to better understand and address extreme making weight efforts in military populations, particularly in female service members and Veterans, are warranted.

Recalibrating the Genetics and Epidemiology of Colorectal Cancer Consortium Environmental Risk Score for Use in US Veterans

BACKGROUND

Risk for colorectal cancer may accumulate through multiple environmental factors. Understanding their effects, along with genetics, age, and family history, could allow improvements in clinical decisions for screening protocols. We aimed to extend the previous work by recalibrating an environmental risk score (e-Score) for colorectal cancer among a sample of US veteran participants of the Million Veteran Program.

METHODS

Demographic, lifestyle, and colorectal cancer data from 2011 to 2022 were abstracted from survey responses and health records of 227,504 male Million Veteran Program participants. Weighting for each environmental factor's effect size was recalculated using Veterans Affairs training data to create a recalibrated e-Score. This recalibrated score was compared with the original weighted e-Score in a validation sample of 113,752 (n cases = 590). Nested multiple logistic regression models tested associations between quintiles for recalibrated and original e-Scores. Likelihood ratio tests were used to compare model performance.

RESULTS

Age (P < 0.0001), education (P < 0.0001), diabetes (P < 0.0001), physical activity (P < 0.0001), smoking (P < 0.0001), NSAID use (P < 0.0001), calcium (P = 0.015), folate (P = 0.020), and fruit consumption (P = 0.019) were significantly different between colorectal cancer case and control groups. In the validation sample, the recalibrated e-Score model significantly improved the base model performance (P < 0.001), but the original e-Score model did not (P = 0.07). The recalibrated e-Score model quintile 5 was associated with significantly higher odds for colorectal cancer compared with quintile 1 (Q5 vs. Q1: 1.79; 95% CI, 1.38-2.33).

CONCLUSIONS

Multiple environmental factors and the recalibrated e-Score quintiles were significantly associated with colorectal cancer cases.

IMPACT

A recalibrated, veteran-specific e-Score could be used to help personalize colorectal cancer screening and prevention strategies.

Assessing the Relationship Between Sleep Duration and the Prevalence of Chronic Kidney Disease Among Veterans in the United States: A 2022 Behavior Risk Factor Surveillance System (BRFSS) Cross-Sectional Study

INTRODUCTION

Chronic kidney disease (CKD) is more prevalent among veterans in the United States than in the general population. Similarly, veterans also exhibit higher rates of abnormal sleep duration compared to the general population. The aim of this study was to investigate the association between self-reported length of sleep and the prevalence of CKD among veterans in the United States using responses from the 2022 Behavioral Risk Factor Surveillance System (BRFSS).

METHODS

For this cross-sectional study, a total of 53,211 veterans who responded to the 2022 BRFSS survey were analyzed. Measures include the outcome variable which is self-reported CKD diagnosis and a major independent variable sleep duration. Sleep duration was recategorized into ≤ 5 hours (short sleep duration), 6-10 hours (normal sleep duration), and >10 hours (long sleep duration). Covariates included gender, age, race, residence, insurance, alcohol consumption, diabetes comorbidity, coronary artery disease (CAD) comorbidity, and stroke comorbidity. Descriptive, bivariate, and multivariate logistic regressions were conducted using the SAS software (SAS Institute Inc., Cary, North Carolina, United States).  Results: The prevalence of CKD among veterans in the United States is 3332 (6.29%). Veterans with sleep duration of 6-10 hours had 17.5% lower odds of CKD than veterans who slept for ≤5 hours (adjusted OR (AOR)= 0.825, 95%CI= 0.821-0.830; P=<0.0001). Veterans who slept for more than 10 hours had 68.2% higher odds of having CKD (AOR=1.682, 95%CI= 1.662-1.702; P=<0.0001). Additionally, veterans diagnosed with diabetes, stroke, and coronary artery disease had 2.447-2.103, and 2.838, respectively, higher odds of developing CKD (AOR=2.447, 95%CI= 2.435-2.459; p=<0.0001). Veterans who were 65 years and older had higher odds of developing CKD compared to those aged 35-44 years (AOR= 5.743, 95%CI= 5.669-5.818; P<0.001). The odds of having CKD were also higher among veterans who identified as Black (AOR 1.397, 95%CI =1.388-1.405; P<0.01) or as Hispanic (AOR =1.318, 95%CI = 1.307-1.329; P<0.01) compared to non-Hispanic White veterans. Those who identified as Asian had lower odds of CKD (AOR= 0.87, 95%CI=0.853-0.888; P<0.01). Furthermore, veterans who consumed alcohol had 7.8% lower odds of having CKD as compared to individuals who did not consume alcohol (AOR= 0.922, 95%CI =0.918-0.927; p=<0.0001). Male veterans had 24.7% lower odds of having CKD as compared to female veterans (AOR = 0.753, 95%CI= 0.747-0.758; P<0.001).  Conclusion: This research provides evidence of a greater prevalence of CKD among veterans with short sleep duration (≤ 5 hours) and long sleep duration (> 10 hours). Sleep hygiene education and sleep optimization programs can improve sleep and boost overall kidney health among veterans.

Highly expressed long non-coding RNA SNHG14 activated MSU-induced inflammatory response in acute gout arthritis through targeting miR-223-3p

AIM

According to reports, long non-coding RNAs (lncRNAs) are involved in the regulation of many inflammatory diseases. Here, our main purpose was to ascertain the expression data of lncRNA SNHG14 in acute gouty arthritis (AGA) and to explore its possible mechanism in the regulation of AGA.

METHOD

Reverse transcription quantitative polymerase chain reaction technology was supplied to detect the lncRNA SNHG14 expression. A receiver operating characteristics curve was drawn to estimate the accuracy of lncRNA SNHG14 in AGA diagnosis. An in vitro AGA cell model was constructed by inducing THP-1 cells with monosodium urate (MSU). The concentrations of inflammatory factors such as interleukin-1β, interleukin-6, and tumor necrosis factor-α were measured by enzyme-linked immunosorbent assay. The luciferase reporter gene was used to verify the relationship between lncRNA SNHG14 and miR-223-3p.

RESULTS

In clinical analysis, the levels of serum lncRNA SNHG14 in AGA patients were significantly higher than those in the control group. Abnormally elevated lncRNA SNHG14 has high sensitivity and specificity for AGA diagnosis. In in vitro cell experiments, silencing lncRNA SNHG14 inhibited the inflammatory response of THP-1 cells stimulated by MSU, and the luciferase reporter gene proved that lncRNA SNHG14 could bind to miR-223-3p. In addition, the level of miR-223-3p declined in AGA patients and the AGA cell model. Overexpression of miR-223-3p is helpful to alleviate an MSU-induced inflammatory response.

CONCLUSION

In the AGA cell model, lncRNA SNHG14, as an miR-223-3p sponge, induces a cellular inflammatory response by controlling the level of miR-223-3p, so aggravating the disease progress of AGA.

The Impact of Blast Exposure-With or Without Traumatic Brain Injury-on Metabolic Abnormalities in Post-9/11 Veterans

OBJECTIVE

The primary aim included explorations of: (1) the associations between the history of blast exposure (BE), close blast exposure (CBE), and blast-related traumatic brain injury (bTBI) and metabolic abnormality; and (2) the potential mediating effect of comorbid psychological and somatic conditions on these associations. The secondary aim explored the association of dose-response impact of BE, CBE, and bTBI and metabolic abnormality.

SETTING

Data were collected by the Translational Research Center for TBI and Stress Disorders (TRACTS).

PARTICIPANTS

Post-9/11 veterans from the TRACTS baseline sample who had conflict-zone deployment experience ( N = 734).

DESIGN

Cross-sectional secondary data analysis. We computed relative risks (RRs) and 95% CI using modified Poisson regression. We quantified the impact of co-occurring psychological and somatic conditions on this association using mediation analyses.

MAIN MEASURES

Exposures included BE (<100 m), CBE (<10 m), and bTBI. Metabolic abnormality outcomes included (1) overweight/obesity (defined by abnormal waist-hip ratio [WHR] and abnormal waist circumference [WC]); (2) glucose dysregulation; and (3) meeting criteria for cardiometabolic syndrome (defined by guidelines).

RESULTS

The sample was majority male (91%) and White (68%), with a mean age of 34.6 years (SD = 8.99). Most participants had 1 or more BE (83%); 48% experienced 1 or more CBE. Overweight/obesity was highly prevalent in the sample (51% had abnormal WHR and 60% abnormal WC). There was no significant direct or indirect association between BE, CBE, and bTBI and metabolic abnormalities (RRs: 0.70-1.51; P 's > .05).

CONCLUSION

Future research is needed to investigate the association of BE with metabolic abnormalities with larger, more targeted sample selection, and longer follow-up. Effective and sustainable weight management and metabolic health prevention interventions for this veteran cohort are needed.

The Health Status of the US Veterans: A Longitudinal Analysis of Surveillance Data Prior to and during the COVID-19 Pandemic

Chronic diseases affect a disproportionate number of United States (US) veterans, causing significant long-term health issues and affecting entitlement spending. This longitudinal study examined the health status of US veterans as compared to non-veterans pre- and post-COVID-19, utilizing the annual Center for Disease Control and Prevention (CDC) behavioral risk factor surveillance system (BRFSS) survey data. Age-adjusted descriptive point estimates were generated independently for 2003 through 2021, while complex weighted panel data were generated from 2011 and onward. General linear modeling revealed that the average US veteran reports a higher prevalence of disease conditions except for mental health disorders when compared to a non-veteran. These findings were consistent with both pre- and post-COVID-19; however, both groups reported a higher prevalence of mental health issues during the pandemic years. The findings suggest that there have been no improvements in reducing veteran comorbidities to non-veteran levels and that COVID-19 adversely affected the mental health of both populations.

Relationship between Body Mass Index and Diagnosis of Overweight or Obesity in Veterans Administration Population

Background: This paper examined the gap between obesity and its diagnosis for cohorts of patients with overweight, obesity, and morbid obesity in the Veterans Administration (VA) population. Using the risk adjustment models, it also identified factors associated with the underdiagnosis of obesity. Methods: Analysis was performed on a VA data set. We identified diagnosed patients and undiagnosed patients (identified through BMI but not diagnosed using ICD-10 codes). The groups' demographics were compared using nonparametric chi-square tests. We used logistic regression analysis to predict the likelihood of the omission of diagnosis. Results: Of the 2,900,067 veterans with excess weight, 46% were overweight, 46% had obesity, and 8% of them had morbid obesity. The overweight patients were the most underdiagnosed (96%), followed by the obese (75%) and morbidly obese cohorts (69%). Older, male, and White patients were more likely to be undiagnosed as overweight and obese; younger males were more likely to be undiagnosed as morbidly obese. (p < 0.05) Comorbidities significantly contributed to diagnosis. Conclusions: The underdiagnosis of obesity continues to be a significant problem despite its prevalence. Diagnosing obesity accurately is necessary to provide effective management and treatment.

PREDICTION OF THE RISKS OF THE DEVELOPMENT OF COMORBIDITY OF CORONARY HEART DISEASE AND OBESITY IN THE BACKGROUND OF MILITARY ACTIONS

OBJECTIVE

The aim: Study of prognostic possibilities of batokine complexes (fibroblast growth factor (FGF-21) and vascular endothelial growth factor A (VEGF-A)) in determining the risks of developing coronary heart disease (CHD) and obesity (especially in case of their comorbidity).

PATIENTS AND METHODS

Materials and methods: 105 patients aged 25-85 were examined: 70 (main group) -with CHD on the background of obesity and 35 - with isolated CHD (comparison group).

RESULTS

Results: Probable associations with increased risks of comorbidity of CHD and obesity were: increased systolic blood pressure (SBP) (OR = 0.844 [95.0% CI 0.735-0.970], p = 0.017), FGF-21 (OR = 1.701 [95.0 % CI 1.219-2.375], p = 0.002), VEGF-A (OR = 1.725 [95.0% CI 1.213-2.372], p = 0.005), low-density lipoprotein (LDL) (OR = 4.419 [95.0% CI 1.351-14.469], p = 0.014). Probable associations were also established for lesions of the left anterior descending artery (LADA) (OR = 1.117 [95.0% CI 0.987-1.263], p = 0.078), intermediate branch of the left coronary artery (IBLCA) (OR = 1.336 [95.0% CI 1.099-1.624], p = 0.004).

CONCLUSION

Conclusions: The values of the characteristics of batokine metabolism (FGF-21 and VEGF-A levels) can be used as a significant predictor of the development of obesity in CHD. Increased levels of FGF-21 and VEGF-A in blood serum characterize a significant relationship with the development of such comorbidity, which indicates a significant influence of batokine complexes on the pathogenesis of comorbidity of CHD and obesity.

FUNCTIONAL CHARACTERISTICS OF THE CARDIOVASCULAR SYSTEM OF PATIENTS WITH ISCHEMIC HEART DISEASE WITH OBESITY

OBJECTIVE

The aim: To determine the features of the functional characteristics of the cardiovascular system of patients with ischemic heart disease with obesity.

PATIENTS AND METHODS

Materials and methods: Examined 130 persons (mostly military personnel and persons who were in the zone of active hostilities): 65 patients (the main group, 62,67±8,93 years) with coronary heart disease and obesity and 45 people of the control group (virtually healthy people, randomized by age and sex, 58,76±14,6 years).

RESULTS

Results: Coronary heart disease and obesity compared to healthy individuals probably the exceed all values of the functional state of the cardiovascular system: systolic blood pressure (152.72±14.61 and 119.03±7.94 mmHg; p<0.001); diastolic blood pressure (90.74±7.36 and 80.36±6.74 mmHg; p<0.001); end-diastolic volume (103.17±40.84 and 52.48±8.58 mm3; р<0.001); end-systolic volume (47.98±29.92 and 31.47±8.42 mm3; р=0.001); end-diastolic size (4.74±0.81 and 4.12 ± 0.27 cm; р<0.001); end-systolic size (3.34±0.76 and 3.17±0.59 cm; р=0.014).

CONCLUSION

Conclusions: The identified functional disorders of the heart in the comorbid course of coronary heart disease and obesity can be used for early diagnosis of cardiovascular complications in such patients and for the development of adequate therapeutic schemes.

Examining Predictors of Myocardial Infarction

Cardiovascular diseases are the leading cause of death in the United States. This study analyzed predictors of myocardial infarction (MI) for those aged 35 and older based on demographic, socioeconomic, geographic, behavioral, and risk factors, as well as access to healthcare variables using the Center for Disease (CDC) Control Behavioral Risk Factor Surveillance System (BRFSS) survey for the year 2019. Multiple quasibinomial models were generated on an 80% training set hierarchically and then used to forecast the 20% test set. The final training model proved somewhat capable of prediction with a weighted F1-Score = 0.898. A complete model based on statistically significant variables using the entirety of the dataset was compared to the same model built on the training set. Models demonstrated coefficient stability. Similar to previous studies, age, gender, marital status, veteran status, income, home ownership, employment status, and education level were important demographic and socioeconomic predictors. The only geographic variable that remained in the model was associated with the West North Central Census Division (in-creased risk). Statistically important behavioral and risk factors as well as comorbidities included health status, smoking, alcohol consumption frequency, cholesterol, blood pressure, diabetes, stroke, chronic obstructive pulmonary disorder (COPD), kidney disease, and arthritis. Three access to healthcare variables proved statistically significant: lack of a primary care provider (Odds Ratio, OR = 0.853, p < 0.001), cost considerations prevented some care (OR = 1.232, p < 0.001), and lack of an annual checkup (OR = 0.807, p < 0.001). The directionality of these odds ratios is congruent with a marginal effects model and implies that those without MI are more likely not to have a primary provider or annual checkup, but those with MI are more likely to have missed care due to the cost of that care. Cost of healthcare for MI patients is associated with not receiving care after accounting for all other variables.

Exploring Health Outcomes for U.S. Veterans Compared to Non-Veterans from 2003 to 2019

The physical demands on U.S. service members have increased significantly over the past several decades as the number of military operations requiring overseas deployment have expanded in frequency, duration, and intensity. These elevated demands from military operations placed upon a small subset of the population may be resulting in a group of individuals more at-risk for a variety of debilitating health conditions. To better understand how the U.S Veterans health outcomes compared to non-Veterans, this study utilized the U.S. Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System (BRFSS) dataset to examine 10 different self-reported morbidities. Yearly age-adjusted, population estimates from 2003 to 2019 were used for Veteran vs. non-Veteran. Complex weights were used to evaluate the panel series for each morbidity overweight/obesity, heart disease, stroke, skin cancer, cancer, COPD, arthritis, mental health, kidney disease, and diabetes. General linear models (GLM’s) were created using 2019 data only to investigate any possible explanatory variables associated with these morbidities. The time series analysis showed that Veterans have disproportionately higher self-reported rates of each morbidity with the exception of mental health issues and heart disease. The GLM showed that when taking into account all the variables, Veterans disproportionately self-reported a higher amount of every morbidity with the exception of mental health. These data present an overall poor state of the health of the average U.S. Veteran. Our study findings suggest that when taken as a whole, these morbidities among Veterans could prompt the U.S. Department of Veteran Affairs (VA) to help develop more effective health interventions aimed at improving the overall health of the Veterans.