Abstract
Military personnel are routinely exposed to a range of occupational and environmental hazards (including chemical agents, radiation, physical stress, and psychological trauma) that may uniquely influence their long-term health outcomes. Emerging evidence suggests that such exposures could alter cancer risk profiles, yet comprehensive comparisons of tumor prevalence and distribution between military and civilian populations remain limited. Leveraging a nationally representative dataset, this study addresses this gap by systematically comparing cancer profiles between United States military veterans and the general population, thereby informing targeted prevention strategies and etiological research in occupational health. This study aims to compare cancer prevalence and profiles between military personnel and the general population to investigate the association between military service and tumor risk. This cross-sectional analysis utilized data from the National Health and Nutrition Examination Survey database. The primary outcome was self-reported cancer prevalence. Multivariate logistic regression analyses were conducted to assess the relationship between military service and cancer occurrence, adjusting for key demographic and lifestyle covariates including age, sex, race, smoking status, and socioeconomic factors. Among 12,174 participants, 1904 (15.64%) had a history of military service. Military veterans were significantly older (66.17 ± 0.43 vs 52.79 ± 0.31 years), had a higher proportion of White individuals (85.45% vs 69.74%), and higher smoking rates (66.01% vs 43.32%) compared to the nonmilitary population (all P < .001). Cancer prevalence was markedly higher in veterans (76.95% vs 46.87%, P < .001), with notably elevated rates of thyroid, dermatological, and skeletal cancers. After adjustment for confounders, nonmilitary individuals had significantly lower odds of tumor occurrence (adjusted odds ratio = 0.40, 95% confidence interval 0.31–0.53). Military service is associated with a significantly increased prevalence of tumors, particularly thyroid cancer. The findings underscore the need for further research into the underlying mechanisms and enhanced health protection strategies for military personnel.
Keywords: Cancer prevalence, Cross-sectional study, Military personnel, NHANES database, Occupational exposure
1. Introduction
Military service is a mandatory duty for citizens in many countries. During their service, military personnel may encounter various carcinogenic risk factors, including exposure to radioactivity,[1] ultraviolet radiation,[2] chemicals,[3] neurotoxicants,[4] and radioactive substances,[5] at levels higher than those experienced by the general population. Cohort studies involving male Vietnam veterans have demonstrated that exposure to Agent Orange is associated with an increased risk of bladder cancer.[6] Additionally, research indicates that military service members may have a higher propensity for smoking and alcohol abuse, further elevating their cancer risk.[7,8] Despite the availability of a specialized, free healthcare system for military personnel, existing literature suggests that United States (U.S.) military service is linked to a higher incidence of cancer, including thyroid,[9] breast, and prostate cancer,[10] melanoma,[2] colorectal cancer,[11] and mesothelioma.[12] However, a retrospective study with a 48-year follow-up period found that veterans involved in chemical agent research at Porton Down exhibited a slightly higher mortality rate, but no difference in cancer incidence.[13] In a cohort study with an 11-year follow-up period, British Gulf War veterans exhibited no increased overall cancer risk, nor any site-specific cancer risk.[14] Additionally, research has indicated that the incidence of neuroepithelial brain cancer,[15] digestive system cancers,[16] bladder and kidney cancers,[17] soft tissue sarcomas,[18] and oral cavity and oropharyngeal cancers[19] is lower among active-duty military personnel compared to the general U.S. population.
This study aims to compare cancer prevalence and profiles between military personnel and the general population using the National Health and Nutrition Examination Survey (NHANES) database, adjusting for demographic and socioeconomic factors to investigate the association between military service and tumor risk.
2. Materials and methods
2.1. Study design and subjects
The cross-sectional study adhered to the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology Statement[20] and utilized NHANES data spanning from 1999 to 2018. The NHANES, conducted by the Centers for Disease Control and Prevention, is designed to evaluate the health and nutritional status of American participants through a combination of interviews, physical examinations, and laboratory analyses. Comprehensive details regarding the project’s design, data collection methodologies, sample weighting, and informed consent procedures are available through the National Center for Health Statistics, with pertinent data being publicly accessible.[21] The data, having been previously anonymized and released by National Center For Health Statistics, do not require Institutional Review Board approval. Ethical approval and consent were not required as this study was based on publicly available deidentified data.
2.2. Criteria for inclusion and exclusion
Given that military service typically commences at the age of 18, the study’s inclusion criteria were restricted to individuals aged 18 and older. The initial cohort included 119,555 participants, excluding those who either refused to disclose their military service status (N = 19), were uncertain about their service status (N = 7), had missing data regarding service status (N = 55,923), were under 18 years of age (N = 2153), refused to disclose their cancer history (N = 3), were uncertain about their cancer history (N = 57), had missing cancer history data (N = 4180), had 3 or more tumors (N = 14), refused to answer tumor type (N = 42), did not know tumor type (N = 92), had missing tumor type data (N = 44890), or had incorrect data (N = 1). In total, 12,174 participants were included in this cross-sectional analysis. The detailed flow of the participant selection process is illustrated in Figure 1.
Figure 1.
Participant censoring flowchart. N/n = number pf paticipants, NHANES = National Health and Nutrition Examination Survey.
2.3. Endpoints and exposure factors
The primary exposure variable was military service history, defined using the survey question associated with the variable DMQMILIAT (Veteran/Military Status), which inquired whether the respondent had served in the U.S. Armed Forces. Participants were categorized into 2 groups: those with a history of military service (military group) and those without (nonmilitary group). The primary endpoint of this study was self-reported cancer prevalence, assessed using the survey question linked to the variable MCQ220 (ever told you had cancer or malignancy), which asked whether the respondent had ever been informed by a doctor or other medical professional of having any form of cancer or malignancy. For participants reporting a cancer diagnosis, the specific cancer type was identified using the survey question associated with the variable MCQ230A (what kind of cancer). The cancer types were subsequently categorized according to anatomical systems. Tumors of the urinary system included bladder and kidney cancers; tumors of the hematological system encompassed hematological tumors, leukemia, and Hodgkin lymphoma; tumors of the digestive system comprised colon, esophageal, gallbladder, liver, pancreatic, rectal, and gastric cancers; tumors of the reproductive and endocrine systems included breast, cervical, testicular, uterine, prostate, thyroid, and ovarian cancers; tumors of the nervous system included brain tumors and other nervous system tumors; tumors of the skin and soft tissue encompassed melanoma, skin cancer, soft tissue tumors, as well as cancers of the mouth, tongue, and lip; tumors of the respiratory system comprised laryngeal, tracheal, and lung cancers; tumors of bone and other types were categorized as bone tumors and miscellaneous tumors.
2.4. Covariate
To strengthen the analysis of the relationship between tumors and military service, we incorporated the following variables as covariates: age, gender, race, marital status, education level,[22] poverty-to-income ratio, smoking status,[23] alcohol consumption patterns,[24,25] exercise equivalents,[26] diabetes, hypertension, and depression scores.[27,28] Diabetes mellitus was identified based on 1 or more of the following criteria: a history of diabetes mellitus, use of insulin, use of medication to lower blood glucose, hemoglobin A1c level of 6.5% or higher, fasting blood glucose level of 126 mg/dL or higher, or a 2-hour postprandial blood glucose level of 200 mg/dL or higher. Hypertension was defined as a history of hypertension or having a systolic blood pressure > 140 mm Hg or a diastolic blood pressure > 90 mm Hg.
2.5. Statistical analysis
In this study, the interview and test weights recommended by the Centers for Disease Control and Prevention guidelines (https://wwwn.cdc.gov/nchs/nhanes/tutorials/default.aspx) were utilized.[21,29–31] Statistical analyses were conducted using R version 4.3.0 (CRAN, https://cran.r-project.org/). Normally distributed continuous data were presented as mean (standard error), and comparisons between 2 independent groups were performed using the t-test. Categorical data were expressed as frequencies and percentages (n [%]) and were compared using the chi-square test or Fisher exact test. The relationship between military service and cancer incidence was examined using logistic regression models, both univariate and multivariate logistic regression models. Multivariate logistic regression models included adjustments for sex, age, race, literacy, marital status, diabetes, hypertension, and poverty-to-income ratio. Subgroup analyses were performed stratified by age groups, sex, and smoking status to explore potential effect modification and identify whether the association between military service and cancer risk varied across these key demographic and lifestyle factors. All analyses were conducted using the R2 statistical package (R Foundation). A 2-tailed P value of < .05 was considered indicative of statistical significance.
3. Results
3.1. Baseline characteristics
The study comprised a total of 12,174 participants, of whom 1904 (15.64%) were engaged in military service, while 10,270 (84.36%) were not. The mean age for participants in military service was 66.17 ± 0.43 years, compared to 52.79 ± 0.31 years for those not in military service, indicating a statistically significant difference in mean age (t = −27.52, P < .001). Statistically significant differences were also observed between the 2 groups in terms of gender, race, and culture, as detailed in Table 1. Furthermore, significant disparities were identified in age, gender, race, culture, marital status, glance, alcohol consumption, hypertension, diabetes, and depression (P < .05), whereas no significant differences were found in education and race (P > .05).
Table 1.
A comprehensive overview of the demographic, socioeconomic, and health-related characteristics of the study population.
| Variable | Total (n = 12174) | Military service (n = 1904) | No military service (n = 10270) | Statistic | P |
|---|---|---|---|---|---|
| Age, Mean (SE) | 54.82 (0.31) | 66.17 (0.43) | 52.79 (0.31) | t = −27.52 | < .001 |
| Gender, n (%) | χ2 = 1891.84 | < .001 | |||
| Male | 5548 (45.38) | 1777 (91.76) | 3771 (37.08) | ||
| Female | 6626 (54.62) | 127 (8.24) | 6499 (62.92) | ||
| Ethnic, n (%) | χ2 = 213.29 | < .001 | |||
| Mexican American | 852 (5.03) | 53 (1.96) | 799 (5.58) | ||
| Other Hispanic | 979 (6.19) | 48 (1.82) | 931 (6.97) | ||
| Non-Hispanic White | 7664 (72.12) | 1473 (85.45) | 6191 (69.74) | ||
| Non-Hispanic Black | 1589 (8.59) | 233 (6.65) | 1356 (8.93) | ||
| Other Race: including Multiracial | 1090 (8.07) | 97 (4.12) | 993 (8.78) | ||
| Educational level, n (%) | χ2 = 15.01 | .077 | |||
| < 9th Grade | 878 (4.60) | 107 (3.88) | 771 (4.73) | ||
| 9–11th Grade | 1255 (8.50) | 170 (6.95) | 1085 (8.77) | ||
| High School Grad/GED | 2767 (24.95) | 456 (24.06) | 2311 (25.11) | ||
| Some College/AA degree | 3573 (29.82) | 606 (32.58) | 2967 (29.32) | ||
| College Graduate or above | 3685 (32.13) | 565 (32.54) | 3120 (32.06) | ||
| Marriage status, n (%) | χ2 = 145.15 | < .001 | |||
| Married | 6610 (61.05) | 1241 (71.83) | 5369 (59.12) | ||
| Widowed | 2868 (17.17) | 393 (15.11) | 2475 (17.54) | ||
| Divorced | 2136 (16.62) | 189 (8.42) | 1947 (18.09) | ||
| Separated | 123 (0.89) | 21 (1.32) | 102 (0.81) | ||
| Never married | 255 (2.57) | 31 (2.19) | 224 (2.64) | ||
| Living with partner | 137 (1.69) | 20 (1.13) | 117 (1.79) | ||
| Smoking stutas, n (%) | χ2 = 523.26 | < .001 | |||
| Never | 6440 (53.24) | 642 (33.99) | 5798 (56.69) | ||
| Former | 3862 (30.59) | 1016 (52.99) | 2846 (26.58) | ||
| Now | 1854 (16.17) | 246 (13.02) | 1608 (16.74) | ||
| Drinking status, n (%) | χ2 = 230.43 | < .001 | |||
| Mild drinking | 3420 (54.43) | 733 (70.11) | 2687 (51.44) | ||
| Moderate drinking | 1963 (32.64) | 183 (21.10) | 1780 (34.85) | ||
| Heavy drinking | 794 (12.92) | 77 (8.79) | 717 (13.71) | ||
| Exercise status, n (%) | χ2 = 4.67 | .391 | |||
| Low physical activity | 1643 (41.50) | 428 (39.80) | 1215 (42.05) | ||
| High physical activity | 1912 (58.50) | 568 (60.20) | 1344 (57.95) | ||
| PIR, n (%) | χ2 = 110.64 | < .001 | |||
| 0–1.36 | 3251 (24.96) | 3251 (24.96) | 3251 (24.96) | ||
| 1.36–2.48 | 2749 (24.93) | 2749 (24.93) | 2749 (24.93) | ||
| 2.48–3.86 | 2014 (21.73) | 2014 (21.73) | 2014 (21.73) | ||
| 3.86–5 | 2452 (28.37) | 2452 (28.37) | 2452 (28.37) | ||
| Hypertension, n (%) | χ2 = 135.99 | < .001 | |||
| No | 6064 (54.85) | 708 (42.42) | 5356 (57.08) | ||
| Yes | 6093 (45.15) | 1193 (57.58) | 4900 (42.92) | ||
| Diabetes, n (%) | χ2 = 68.61 | < .001 | |||
| No | 9463 (83.16) | 1375 (76.53) | 8088 (84.35) | ||
| Yes | 2459 (16.84) | 490 (23.47) | 1969 (15.65) | ||
| Depression, n (%) | χ2 = 23.14 | .006 | |||
| No | 6933 (89.12) | 1064 (92.49) | 5869 (88.57) | ||
| Yes | 933 (10.88) | 98 (7.51) | 835 (11.43) |
t: t-test, χ2: Chi-square test.
AA = Associate of Arts, GED = General Educational Development, n = number of participants, PIR = poverty-to-income ratio, SE = standard error.
3.2. Differential cancer incidence by age and military status
Figure 2 illustrates the age-stratified proportions of cancer incidence in both military and nonmilitary groups. As depicted in Figure 2, the prevalence of cancer was notably higher in the military group compared to the nonmilitary group, with all cancer types accounting for 1394 out of 1904 cases (76.95%) in the military group and 4162 out of 10,270 cases (46.87%) in the nonmilitary group. In the military cohort, reproductive endocrine tumors were the most prevalent malignant neoplasms, constituting approximately 41.9% of cases, with thyroid cancer being the most frequent at 436 out of 1394 cases (19.43%). This was followed by bone and other tumors (25.37%) and skin and soft tissue tumors (8.65%). Conversely, in the nonmilitary cohort, digestive system tumors were the most prevalent, accounting for approximately 12.32% of cases, with liver cancer being the most common within this category at 895 out of 10,270 cases (9.10%). This was followed by bone and other tumors (12.15%) and reproductive and endocrine tumors (7.94%). Detailed cancer incidence rates for each type of cancer in both cohorts are provided in Table S1, Supplemental Digital Content 1, while Table S2, Supplemental Digital Content 2 presents the incidence rates by anatomical system.
Figure 2.
The age-stratified comparison of cancer prevalence between individuals with and without a history of U.S. military service. U.S. = United States.
3.3. Association between military status and cancer risk
Multivariate logistic regression models were employed to evaluate the association between various covariates and cancer occurrence, revealing that the odds ratio for cancer in the nonmilitary population relative to the military population was 0.4 (95% confidence interval 0.31–0.53) (P < .0001). The likelihood of developing cancer within the population exhibits a significant increase with advancing age. Furthermore, the probability of receiving a cancer diagnosis is notably higher among females compared to males, smokers compared to nonsmokers, and non-Hispanic Whites compared to Mexican Americans. For detailed results, see Table 2.
Table 2.
Univariate logistic regression and multivariate logistic regression models showing the association of various covariates with cancer occurrence.
| Variables | Univariate logistic regression | Multivariate logistic regression | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| β | SE | t | P | OR (95% CI) | β | SE | t | P | OR (95% CI) | |
| Military service | ||||||||||
| Yes | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| No | −1.33 | 0.07 | −18.36 | < .001 | 0.26 (0.23–0.30) | −0.91 | 0.14 | −6.65 | < .001 | 0.40 (0.31–0.53) |
| Gender | ||||||||||
| Male | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| Female | 0.29 | 0.05 | 6.13 | < .001 | 1.34 (1.22–1.47) | 0.73 | 0.10 | 7.34 | < .001 | 2.08 (1.71–2.53) |
| Ethnic | ||||||||||
| Mexican American | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| Other Hispanic | 0.07 | 0.25 | 0.28 | .783 | 1.07 (0.66–1.74) | −0.31 | 0.28 | −1.10 | .274 | 0.73 (0.42–1.28) |
| Non-Hispanic White | 1.76 | 0.25 | 7.14 | < .001 | 5.81 (3.58–9.41) | 1.22 | 0.31 | 3.89 | < .001 | 3.40 (1.84–6.31) |
| Non-Hispanic Black | 0.65 | 0.30 | 2.18 | .031 | 1.91 (1.07–3.43) | 0.04 | 0.43 | 0.10 | .920 | 1.04 (0.45–2.45) |
| Other Race | 0.15 | 0.31 | 0.48 | .631 | 1.16 (0.63–2.13) | 0.16 | 0.35 | 0.44 | .658 | 1.17 (0.59–2.33) |
| Educational level | ||||||||||
| < 9th Grade | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| 9–11th Grade | −0.06 | 0.14 | −0.41 | .679 | 0.94 (0.71–1.25) | −0.45 | 0.38 | −1.20 | .232 | 0.64 (0.30–1.33) |
| High School Grad/GED | −0.64 | 0.15 | −4.30 | < .001 | 0.53 (0.39–0.71) | −0.96 | 0.33 | −2.86 | .005 | 0.38 (0.20–0.74) |
| Some College/AA degree | −0.44 | 0.15 | −2.90 | .004 | 0.64 (0.48–0.87) | −0.74 | 0.34 | −2.19 | .031 | 0.48 (0.25–0.92) |
| College Graduate or above | −0.60 | 0.20 | −2.96 | .004 | 0.55 (0.37–0.82) | −0.86 | 0.35 | −2.44 | .017 | 0.42 (0.21–0.84) |
| Smoking status | ||||||||||
| Never | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| Former | 0.92 | 0.07 | 12.56 | < .001 | 2.51 (2.17–2.90) | 0.56 | 0.10 | 5.67 | < .001 | 1.75 (1.44–2.13) |
| Now | 0.48 | 0.11 | 4.33 | < .001 | 1.61 (1.30–2.00) | 0.79 | 0.14 | 5.45 | < .001 | 2.19 (1.65–2.91) |
| Drinking status | ||||||||||
| Mild drinking | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| Moderate drinking | −0.55 | 0.09 | −6.35 | < .001 | 0.57 (0.48–0.68) | −0.47 | 0.10 | −4.90 | < .001 | 0.63 (0.52–0.76) |
| Heavy drinking | −0.99 | 0.16 | −6.32 | < .001 | 0.37 (0.27–0.51) | −0.47 | 0.15 | −3.13 | .002 | 0.62 (0.46–0.84) |
| Hypertension | ||||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| Yes | 0.98 | 0.06 | 16.80 | < .001 | 2.67 (2.38–2.99) | 0.32 | 0.07 | 4.46 | < .001 | 1.38 (1.20–1.59) |
| Diabetes | ||||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| Yes | 0.46 | 0.06 | 8.01 | < .001 | 1.58 (1.42–1.77) | 0.06 | 0.11 | 0.55 | .582 | 1.06 (0.86–1.31) |
| Depression | ||||||||||
| No | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| Yes | −0.40 | 0.10 | −3.80 | < .001 | 0.67 (0.55–0.83) | −0.13 | 0.14 | −0.94 | .350 | 0.87 (0.66–1.16) |
| Age Category (yrs) | ||||||||||
| 18–40 | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| 40–57 | 1.17 | 0.11 | 10.50 | < .001 | 3.22 (2.59–4.00) | 0.97 | 0.17 | 5.60 | < .001 | 2.64 (1.88–3.71) |
| 57–70 | 1.97 | 0.11 | 18.67 | < .001 | 7.15 (5.82–8.79) | 1.56 | 0.17 | 9.18 | < .001 | 4.75 (3.41–6.63) |
| 70–85 | 2.89 | 0.10 | 27.83 | < .001 | 18.02 (14.70–22.09) | 2.34 | 0.16 | 14.40 | < .001 | 10.37 (7.54–14.26) |
| PIR quantile | ||||||||||
| 0–1.36 | 1.00 (Reference) | 1.00 (Reference) | ||||||||
| 1.36–2.48 | 0.07 | 0.10 | 0.71 | .478 | 1.07 (0.89–1.30) | −0.18 | 0.11 | −1.63 | .107 | 0.84 (0.68–1.04) |
| 2.48–3.86 | 0.14 | 0.14 | 0.98 | .327 | 1.15 (0.87–1.52) | −0.02 | 0.14 | −0.16 | .871 | 0.98 (0.74–1.29) |
| 3.86–5 | 0.14 | 0.17 | 0.83 | .406 | 1.15 (0.82–1.61) | 0.13 | 0.15 | 0.89 | .376 | 1.14 (0.85–1.52) |
CI = confidence interval, OR = odds ratio, PIR = poverty-to-income ratio, SE = standard error.
4. Discussion
In this study utilizing data from the NHANES database, approximately 15.64% of participants reported a history of military service. Individuals with military backgrounds were predominantly non-Hispanic White (85.45%), older, more educated, had higher annual household incomes, and exhibited a higher likelihood of smoking (66.01%). The military cohort demonstrated an increased propensity for cancer development within the overall population. Multivariate analysis revealed that a history of military service was significantly associated with a higher prevalence of cancers, excluding those of the digestive and respiratory systems. Furthermore, factors such as age, female gender, and smoking were found to increase the likelihood of cancer, whereas annual household income, obesity, and depression were not significantly correlated with cancer incidence across different systems.
Several plausible explanations exist for the strong association between military service history and cancer diagnosis. Firstly, individuals with military service tend to be older, which correlates with a higher cancer risk. Secondly, a higher proportion of military personnel have a history of smoking, a well-established risk factor for various cancers, including those of the lung, liver, bladder, and kidney. Thirdly, military service exposes personnel to potential carcinogens, including ultraviolet light and radiation. Additionally, the military health system, as the fourth largest in the U.S., provides military personnel with organized, accessible, and cost-free healthcare. This may result in more effective screening programs and higher adherence rates, potentially leading to increased cancer diagnoses.
Our study also indicates that individuals with a military background are significantly more likely to develop tumors in the reproductive and endocrine systems, primarily thyroid cancer. This finding aligns with an Italian study, which reported that the standardized incidence of thyroid cancer among army servicemen is 1 to 2 times higher than expected.[32] The etiology of thyroid cancer remains poorly understood, with radiation exposure being the only major recognized risk factor. Military personnel may experience increased radiation exposure, particularly from ammunition and depleted uranium used in tanks. Furthermore, military personnel are significantly more likely to be exposed to environmental chemicals such as polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers. Extensive nested case-control studies conducted among U.S. military personnel have demonstrated significant associations and dose-response relationships between exposure to specific PCBs and their congeners and the risk of thyroid cancer.[33] Additionally, various endocrine-disrupting chemicals, including flame retardants, PCBs, phthalates, and certain pesticides, have been identified as being associated with an elevated risk of thyroid cancer.[34]
Our multivariate analysis revealed that factors not related to military service history, such as age, were associated with increased cancer prevalence.[35] Aging has been identified as the most significant risk factor for cancer, as it is associated with the accumulation of cellular damage,[36] a decline in immune system function,[37] and an increase in chronic inflammation.[38] Consequently, the incidence of most cancers rises substantially with age. The study revealed that 67.9% of veterans exhibited greater longevity compared to the average lifespan of their sex-specific birth cohort. A trend toward a significant increase in longevity over time was observed among veteran males compared to reference males (P < .002), whereas no significant trend was detected among females.[39] The average age of military service members was notably higher than that of non-service members, potentially introducing bias into the study.
Several important limitations should be acknowledged. Firstly, the retrospective nature of the data collection may have led to inaccuracies or omissions in data entry. Additionally, the cross-sectional design of the study and the absence of data on critical potential confounders precluded the attribution of causality between military service and cancer occurrence, allowing only for the examination of correlations. Furthermore, although the study accounted for numerous socioeconomic and clinical factors, it did not include established risk factors for malignancy, such as family history, personal genetic predispositions, detailed comorbidity histories, and dietary habits. Finally, the accuracy, completeness, and representativeness of the data sourced from the NHANES database underpin the generalizability and reliability of our findings; any limitations inherent to the original NHANES data collection methodology may therefore affect the validity of our conclusions. Despite these limitations, our study constitutes a substantial and distinctive real-world cohort of the American population. Utilizing self-reported data, we identified a history of military service as a potential risk factor for malignancy.
5. Conclusion
Individuals with a history of military service may exhibit an elevated prevalence of cancer, with a higher incidence of thyroid cancer, bone tumors, and skin cancer. This observed higher prevalence likely reflects a combination of factors: improved access to screening and healthcare programs leading to increased cancer detection, alongside potential occupational and environmental exposures unique to military service that may contribute to elevated biological risk. The findings of this study underscore the need for prospective research to more accurately assess cancer incidence rates, investigate risk factors for cancer development, and enhance health protection measures for military populations.
Author contributions
Conceptualization: Yizhou Luo.
Investigation: Cui Pang.
Methodology: Cui Pang.
Supervision: Kaili Zhao, Yizhou Luo.
Writing – original draft: Cui Pang.
Writing – review & editing: Kaili Zhao.
Abbreviations:
- NHANES
- National Health and Nutrition Examination Survey
- PCBs
- polychlorinated biphenyls
- U.S.
- United States
The authors have no funding or conflicts of interest to disclose.
All data generated or analyzed during this study are included in this published article [and its supplementary information files].
Supplemental Digital Content is available in the online version of this article (http://dx.doi.org/10.1097/MD.0000000000049555).
How to cite this article: Zhao K, Luo Y, Pang C. A cross-sectional study comparing tumor profiles between military personnel and the general population: Insights from the NHANES database. Medicine 2026;105:27(e49555).
Contributor Information
Kaili Zhao, Email: zhaokaili1991@163.com.
Yizhou Luo, Email: luoyizhou@gmail.com.
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