Land elevation and thyroid cancer in United States metropolitan statistical areas: an ecological study

Introduction

Thyroid cancer has become one of the most rapidly increasing malignancies globally, with environmental and genetic factors contributing to its etiology. Established risk factors include radiation exposure, excessive dietary iodine intake, genetic mutations (e.g., RET, BRAF, TP53), and autoimmune diseases such as Hashimoto’s thyroiditis (1). However, emerging evidence suggests that environmental pollutants, endocrine-disrupting chemicals (EDCs), air quality, and geographical factors such as land elevation may also influence thyroid cancer risk (2,3).

Land elevation has emerged as a potential factor influencing cancer incidence. However, investigations into this relationship have yielded divergent findings. Research by Hart suggests that higher elevations in U.S. cities correlate with reduced cancer incidence for all cancers, positing mechanisms such as natural background radiation (NBR), oxygen concentration (OC), and barometric pressure (BP) as potential protective factors (4). Other studies have corroborated this notion, suggesting that humans living at a higher altitude have reduced cancer mortality over a broader spectrum of cancer types (5,6). In contrast, findings from Garrido and Garrido underscore that living at high altitudes in Ecuador is associated with increased overall cancer risk (i.e., gastric, colorectal, hepatic/bile duct, breast, uterine/cervix, and lymphatic/hematopoietic), revealing geographical disparities and the intricate interplay of environmental variables (7). Additionally, Hussain et al. highlight the variability in overall cancer patterns at high altitudes in the Kargil Ladakh region of India, emphasizing local risk factors including extreme cold, hypoxic conditions, and heightened UV exposure (8). Pertaining to their findings, they observed that thyroid cancer was the tenth most prevalent cancer within females (8).

Several mechanisms may underlie the relationship between land elevation and thyroid cancer risk. Reduced OC at higher altitudes may create a hypoxic environment, potentially inhibiting cancer cell proliferation (9). However, hypoxia also triggers the activation of hypoxia-inducible factor-1 (HIF-1), which has been implicated in tumor progression and metastasis (10). Furthermore, NBR exposure from cosmic radiation increases with altitude, approximately doubling every 6,000 feet, potentially contributing to cancer risk (11). While previous research has linked increased ultraviolet radiation exposure with a higher incidence of thyroid cancer (12), lower BP at higher elevations has been proposed as a protective factor, though its precise impact remains unclear (13). However, it is important to note that while cosmic radiation exposure increases with altitude, the effect of this radiation on thyroid cancer risk is not necessarily proportional due to factors such as anatomical shielding from surrounding tissues and the relative magnitude of this dose compared to other well-established risk factors like radiation exposure from medical imaging or environmental pollutants.

In addition to land elevation, other environmental factors have been implicated in thyroid cancer incidence. Air pollution, particularly fine particulate matter (PM_2.5), has been associated with oxidative stress and thyroid dysfunction, increasing cancer susceptibility (14,15). Similarly, exposure to EDCs such as polychlorinated biphenyls (PCBs) and bisphenol A (BPA) may disrupt thyroid hormone regulation and promote carcinogenesis (2). Geographic disparities in thyroid cancer incidence may also be influenced by economic status and healthcare access, leading to variations in diagnostic rates and potential overdiagnosis trends (16).

The discrepancies in these findings highlight the need to clarify the role of land elevation in cancer epidemiology. Several mechanisms may underlie this relationship. Reduced OC at higher altitudes may lead to a hypoxic environment, which can inhibit cancer cell growth (17). Average human exposure to NBR from radioactive materials in the ground, soil, and water increases with altitude. In particular, cosmic radiation dose roughly doubles every 6,000 feet (18). This phenomenon may affect cancer incidence rates. Lower BP at higher elevations might also play a role, although the specific effects are not well understood (19).

Thyroid cancer represents one of the most rapidly increasing cancers globally (20). It encompasses various histologic types, with papillary being the most prevalent (21). While the exact etiology remains elusive, risk factors include genetic predispositions, radiation exposure, and certain environmental factors such as nuclear weapon or fallout as well as organic and inorganic chemical toxicants (2). Higher altitudes might result in increased exposure to cosmic radiation, which could contribute to cancer risk (22). While studies like Hart, Hussain et al., and Di Trolio et al. suggest land elevation may influence cancer incidence, the relationship is still unsubstantiated and studies specifically investigating thyroid cancer are lacking (4,8,22).

The conflicting findings regarding land elevation’s role in thyroid cancer highlight the need for further investigation. While Hart and others suggest a protective effect of higher altitude, studies from Ecuador and China indicate that low-altitude regions may experience higher thyroid cancer rates due to environmental pollutants (1,2). Thus, this study aims to elucidate the correlation between land elevation and thyroid cancer incidence, incorporating NBR, OC, and BP as potential contributing factors. By leveraging an ecological study design across U.S. metropolitan statistical areas (MSAs), this research seeks to address the existing controversy and provide clarity on the association between altitude and thyroid cancer risk. We present this article in accordance with the STROBE reporting checklist (available at https://aot.amegroups.com/article/view/10.21037/aot-24-68/rc).

Methods

Study population

Retrospective cancer incidence data were obtained from the Centers for Disease Control and Prevention (CDC) Wonder database (23). Specifically, thyroid cancer cumulative incidence rates per 100,000 people over the time period 1999–2020 were extracted for U.S. MSAs. The data thus reflects overall incidence rather than annual or time-stratified rates, and as such time trends were not explicitly analyzed due to the nature of the dataset. Note that the CDC Wonder Database defines the cancers reported in accordance with the International Classification of Diseases for Oncology, Third Edition (ICD-to-3) (23).

An MSA is a geographical region consisting of a core city with a population of at least 50,000 and its economically and socially integrated surrounding areas (24). Ultimately, MSAs were chosen to ensure the data collected reflects larger regions with relatively high population densities, allowing for greater generalizability of thyroid cancer incidence findings. A total of 111 U.S. MSAs with thyroid cancer incidence data were available in the CDC Wonder database. Thirty-one MSAs were excluded due to incomplete thyroid cancer incidence data across the entire 21-year [1999–2020] interval, specifically thyroid cancer incidence totals, crude rate, and age-adjusted rate, resulting in 80 MSAs included for data analysis. It is important to note that county-level cancer incidence rates were age-adjusted for each MSA.

Data

In accordance with Hart, the median land elevation of MSAs were obtained via interactive Google Earth maps, with data supplied from various sources including the U.S. Geological Survey and the U.S. Department of Agriculture (4,25). Five measurements were obtained at city and county border level for each MSA, based on a cardinally oriented plus (+) sign positioned in the geographic center of the MSA, except for uninhabited areas (Figure 1) (4). Inhabited areas were identified using the following layers: populated areas, places of worship, schools, and grocery stores (4). If none of these landmarks were identified on the map, the land was considered uninhabited and excluded in the identification of the five points. Four of the five measurements were obtained at the end of the axes of the plus sign, while the fifth measurement was obtained at the center of the plus sign (4). The median of the five measurements was then used as corresponding altitude for the MSA.

Figure 1 MSA median land elevation example from Google Earth for New York-Newark-Jersey City. Edited plus sign represents the plus sign imaginarily placed within an area that connects the three cities and not extended to areas that appeared to be uninhabited. In this example, the western parts of the outlined MSA, marked with the edited “U”, were considered uninhabited and therefore not included for the MSA boundaries. The five-point altitude average for this New York-Newark-Jersey City is 4 meters. MSA, metropolitan statistical area.

The median elevation for each MSA was then entered into online calculators to calculate corresponding NBR, BP and OC values. NBR was calculated using the Environmental Protection Agency calculator, in which the region of the MSA was inputted alongside its elevation to yield the NBR value (26). Specifically, NBR calculated via the calculators is defined as the sum of terrestrial, cosmic, and internal radiation (26). BP (mmHg) and OC (% compared to sea level) were calculated using an online calculator at the Baillie Lab, which utilizes formulas to calculate BP and OC from elevation (27).

Statistical methods

Due to the non-uniform distribution of the environmental factors (altitude, BP, OC, and NBR), Spearman’s rank correlation analysis was selected over Pearson’s correlation, which assumes uniform distribution of predictor variables to examine correlations between the before mentioned environmental factors on age-adjusted thyroid cancer incidence rates per MSA. The threshold for statistical significance is P≤0.05.

All statistical analyses were performed using Python. The packages pandas, numpy, seaborn, matplotlib, and scipy were used for data extraction and statistical analysis.

Results

The 80 MSAs included in the analysis were geographically diverse, representing regions across the United States. These MSAs spanned the Northeast, South, Midwest, and West, with notable representation from major metropolitan areas such as New York-Newark-Jersey City, NY-NJ-PA, Los Angeles-Long Beach-Anaheim, CA, and Houston-The Woodlands-Sugar Land, TX, as well as smaller MSAs like Akron, OH, and Rapid City, SD. The distribution of MSAs provides a comprehensive snapshot of both urban and rural areas, offering insights across various regional, demographic, and socioeconomic contexts.

Descriptive statistics of each of thyroid cancer incidence rate, altitude, BP, OC, and NBR are shown for the five highest thyroid cancer incidence rate MSAs in Table 1 as well as for the five lowest rate MSAs in Table 2. Complete data for all MSAs are included in the Table S1. Thyroid incidence rates per 100,000 people ranged from 8.5 to 20.2, OC ranged from 53% to 100%, BP from 538 to 760 mmHg, altitude from 1 meter to 1,841 meters, and NBR from 51 to 156 mRem/year.

Figure 2 shows the results of Spearman correlation of MSA thyroid cancer incidence rates compared to each of the environmental risk factors. None of the environmental factors were found to possess a statistically significant Spearman correlation with thyroid cancer incidence: OC: r=−0.154, P=0.17; BP: r=−0.083, P=0.47; Altitude: r=0.095, P=0.40; NBR: r=0.008, P=0.94.

Figure 2 Spearman correlation results of MSA thyroid cancer incidence rates (age-adjusted, per 100,000 persons) vs. environmental risk factors [oxygen concentration (% of oxygen at sea level), barometric pressure (mmHg), altitude (meter), total radiation (mRem received each year)]. MSA, metropolitan statistical area.

Discussion

The natural environment is complex and interacts with the human body in similarly intricate ways, particularly in relation to cancer development. Although this study investigating the correlation between thyroid cancer incidence and the environmental factors of altitude, BP, OC, and NBR across 80 MSAs within the U.S yielded no initial significant correlation between continuous thyroid incidence rate and the aforementioned environmental risk factors, final conclusions should be drawn with caution because of certain limitations of the design. Furthermore, the large clustering of predictor MSA values at certain ranges encourages a closer dive into complex relationships between environmental risk factors and thyroid incidence rate.

Altitude

Prior research showed that higher altitudes are correlated to increased cancer incidence. For instance, Garrido and Garrido, a study from Ecuador, corroborated that there is heightened cancer risk at higher altitudes, possibly attributable to geographical and environmental differences (7). Xiong et al. discussed land elevation’s relationship with hypoxic environments, which reduces the activity of effector immune cells such as CD4⁺ or/and CD8⁺ T cells and promote resistance to cancer therapy (28). Krain also discusses how residents of high altitude cities, such as Mexico City and Colorado, have been observed to have higher rates of cancerous conditions of the skin, testicles, bladder and even thyroid based on a comprehensive literature review and survey of governmental sources (29). However, it is important to note that there are conflicting studies like Simeonov et al., which showed that land elevation is associated with decreased lung cancer incidence (12). The variation in study findings confirms the intricacies of environmental factors affecting cancer incidence.

BP

The potential association between BP and thyroid cancer may illustrate biophysical processes related to environmental pressure variations. While the exact mechanism is unclear, low BP may influence thyroid physiology, potentially affecting thyroid hormone production or immune function (30). Increased BP could also impact the body’s metabolism or cellular oxygenation processes, which are central to cancer development (31). Deng et al. discussed how liver cancer is correlated with local climate and that there is actually a higher liver cancer mortality associated with regions with higher BP (13). However, this remains an area for future research, as there are few studies directly linking BP to overall cancer incidence and thyroid cancer, in particular.

OC

Studies have demonstrated a link between OC and cancer promotion. For instance, Burrows et al. showed HIF-1, which is a transcription factor activated by hypoxia, regulates the expression of genes that increase tumor cell survival, progression, and metastasis (9). Ristescu et al. also corroborated this notion, explaining that hypoxia promotes cancer development by activating pathways that lead to tumor growth, metastasis, resistance to therapy, and poor patient outcomes (10). However, our findings do not suggest OC is correlated to thyroid cancer.

NBR

Previous studies have evaluated the possible correlation between NBR and thyroid cancer risk. Sreekumar et al. analyzed the prevalence of thyroid nodules among women living in places with high NBR in India, originating from thorium and its decay products (32). Their team observed no significant rise in thyroid nodule prevalence, thyroiditis, or hypothyroidism associated with radiation exposure (32). Moreover, a study conducted in South Korea found that despite the increased thyroid cancer incidence rates compared to the general population, there was a non-significant association with cumulative radiation dose, demonstrating that other factors could be leading to elevated cancer risk in this population (33). These non-significant correlations align with the findings in our study, where NBR was also not linked to thyroid cancer incidence. Overall, the weak ties between NBR and thyroid cancer underscore the complexities of this relationship and highlight the need for further longitudinal studies to better understand its potential impact.

Hart showed that higher altitudes might offer protective effects against certain cancers due to reduced OC and lower BP, potentially leading to hypoxia, which could inhibit tumor growth (4). However, these protective factors may not extend to thyroid cancer, which may explain the contradictory outcomes found in this study. Ultimately, the diverse range of findings across past and present studies underscores the complexity of the relationship between altitude and thyroid cancer incidence, which may vary based on environmental factors unique to specific regions in the diverse geographic landscape of the U.S. Further factors influencing thyroid cancer incidence include genetic predispositions, local environmental exposures, and lifestyle factors.

Limitations and future directions

A few limitations should be acknowledged in the study. Firstly, the use of thyroid cancer cumulative incidence data over the time period 1999–2020 may fail to accurately capture temporal trends and variations. Future studies could benefit from a specific time-series analysis, splitting the incidence data over individual years to capture temporal dynamics more effectively. While ecological studies provide valuable insights at a population level, they are vulnerable to the ecological fallacy, where group-wise correlations may not necessarily hold true for individuals.

Furthermore, thyroid cancer incidence is influenced by several possible confounding factors, such as healthcare access, screening practices, demographics, and iodine intake. Owing to a lack of MSA-level data we were unable to access these variables in our study.

In addition, there are issues with multicollinearity given the methods of calculating BP and OC from altitude. We considered running a multiple regression model to assess independent effects of each factor on thyroid cancer incidence. However, with only 80 MSA’s, the model was prone to overfitting with unreliable coefficients. Further studies with a larger sample size could utilize multivariate analysis such as multiple regressions to account for the multicollinearity issue.

Additionally, incorporating machine learning techniques could enhance predictive modeling beyond traditional linear regression, potentially offering more robust models that can handle complex interactions between variables.

Geospatial analysis could also provide profound insights into geographical variations in cancer incidence risk. Additionally, while this study employed Spearman’s rank correlation to assess monotonic relationships, it did not explore potential non-linear associations between altitude-related environmental factors and thyroid cancer incidence. Given the limited sample size (80 MSAs), applying non-linear modeling approaches, such as polynomial regression or splines, risked overfitting and reduced generalizability. Future studies with larger datasets could employ more advanced statistical methods, including machine learning-based approaches, to better assess complex, non-linear interactions. Furthermore, analyzing mortality data in conjunction with incidence data could offer great discoveries into the progression and outcomes of thyroid cancer. Including factors that affect the likelihood of thyroid cancer leading to death would add a survival analysis dimension, enriching the knowledge of thyroid cancer’s trajectory.

Conclusions

In conclusion, our study demonstrates that continued research is essential to unravel the intricate web of environmental influences linked to land elevation on thyroid cancer incidence. Future research may focus on specific areas at high altitude to further explore this association.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://aot.amegroups.com/article/view/10.21037/aot-24-68/rc

Peer Review File: Available at https://aot.amegroups.com/article/view/10.21037/aot-24-68/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://aot.amegroups.com/article/view/10.21037/aot-24-68/coif). M.v.G. reports grants (paid to institution) from CDC-NIOSH (1R21OH012249-01), DOD (CA201068), CDC-NIOSH (1U01OH012621-01) and NIEHS P30 (P30ES023515). The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Our study was exempt from IRB approval as we did not have any human or animal research subjects and used publicly available information.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Huo S, Liu Y, Sun A, et al. Environmental and social determinants of thyroid cancer: A spatial analysis based on the Geographical Detector. Front Endocrinol (Lausanne) 2022;13:1052606. [Crossref] [PubMed]
2. Fiore M, Oliveri Conti G, Caltabiano R, et al. Role of Emerging Environmental Risk Factors in Thyroid Cancer: A Brief Review. Int J Environ Res Public Health 2019;16:1185. [Crossref] [PubMed]
3. Sen M, Ito R, Abe T, et al. Elevations of neutrophil-to-lymphocyte ratio and C-reactive protein over time as a precursor to anaplastic transformation of papillary thyroid carcinoma: a case report. Surg Case Rep 2024;10:190. [Crossref] [PubMed]
4. Hart J. Land elevation and cancer mortality in u.s. Cities and counties using median elevations derived from geographic information systems. Dose Response 2013;11:41-8. [Crossref] [PubMed]
5. Thiersch M, Swenson ER. High Altitude and Cancer Mortality. High Alt Med Biol 2018;19:116-23. [Crossref] [PubMed]
6. Burtscher J, Millet GP, Renner-Sattler K, et al. Moderate Altitude Residence Reduces Male Colorectal and Female Breast Cancer Mortality More Than Incidence: Therapeutic Implications? Cancers (Basel) 2021;13:4420. [Crossref] [PubMed]
7. Garrido DI, Garrido SM. Cancer risk associated with living at high altitude in Ecuadorian population from 2005 to 2014. Clujul Med 2018;91:188-96. [PubMed]
8. Hussain S, Ali M, Jeelani R, et al. Cancer burden in high altitude Kargil Ladakh: ten-year single centre descriptive study. Int J Cancer Treat 2019;2:4-10.
9. Burrows N, Babur M, Resch J, et al. Hypoxia-inducible factor in thyroid carcinoma. J Thyroid Res 2011;2011:762905. [Crossref] [PubMed]
10. Ristescu AI, Tiron CE, Tiron A, et al. Exploring Hyperoxia Effects in Cancer-From Perioperative Clinical Data to Potential Molecular Mechanisms. Biomedicines 2021;9:1213. [Crossref] [PubMed]
11. United States Nuclear Regulatory Commission. Natural background radiation sources [Internet]. Washington, DC: NRC; 2024 [cited 2024 Jul 14]. Available online: https://www.nrc.gov/about-nrc/radiation/around-us/sources/nat-bg-sources.html
12. Simeonov KP, Himmelstein DS. Lung cancer incidence decreases with elevation: evidence for oxygen as an inhaled carcinogen. PeerJ 2015;3:e705. [Crossref] [PubMed]
13. Deng W, Long L, Tang XY, et al. Anisotropic patterns of liver cancer prevalence in Guangxi in Southwest China: is local climate a contributing factor? Asian Pac J Cancer Prev 2015;16:3579-86. [Crossref] [PubMed]
14. International Agency for Research on Cancer. Outdoor air pollution a leading environmental cause of cancer deaths [Internet]. Lyon: IARC; 2013 Oct 17 [cited 2024 Jul 14]. Available online: https://www.iarc.fr/wp-content/uploads/2018/07/pr221_E.pdf
15. Cong X. Air pollution from industrial waste gas emissions is associated with cancer incidences in Shanghai, China. Environ Sci Pollut Res Int 2018;25:13067-78. [Crossref] [PubMed]
16. AIRTUM Working Group. CCM; AIEOP Working Group. Italian cancer figures, report 2012: Cancer in children and adolescents. Epidemiol Prev 2013;37:1-225.
17. Weinberg CR, Brown KG, Hoel DG. Altitude, radiation, and mortality from cancer and heart disease. Radiat Res 1987;112:381-90. [Crossref] [PubMed]
18. Washington State Department of Health, Office of Radiation Protection. Background radiation: natural vs. man-made [Internet]. Olympia, WA: Washington State Department of Health; 2002 Jul [cited 2024 Jul 14]. Available online: https://doh.wa.gov/
19. Merrill RM, Frutos A. Reduced Lung Cancer Mortality With Lower Atmospheric Pressure. Dose Response 2018;16:1559325818769484. [Crossref] [PubMed]
20. Ross J, Parmar HA, Avram A, et al. Imaging in thyroid cancer. In: Oncologic Imaging: A Multidisciplinary Approach. Elsevier; 2023:616-29. doi: 10.1016/B978-0-323-69538-1.00036-7.10.1016/B978-0-323-69538-1.00036-7
21. Hamming JF, Van de Velde CJ, Goslings BM, et al. Prognosis and morbidity after total thyroidectomy for papillary, follicular and medullary thyroid cancer. Eur J Cancer Clin Oncol 1989;25:1317-23. [Crossref] [PubMed]
22. Di Trolio R, Di Lorenzo G, Fumo B, et al. Cosmic radiation and cancer: is there a link? Future Oncol 2015;11:1123-35. [Crossref] [PubMed]
23. Centers for Disease Control and Prevention. CDC Wonder [Internet]. Atlanta, GA: CDC; 2024 [cited 2024 Jul 6]. Available online: https://wonder.cdc.gov/
24. United States Census Bureau. data.census.gov [Internet]. Washington, DC: U.S. Census Bureau; 2024 [cited 2024 Jul 2]. Available online: https://data.census.gov/
25. United States Geological Survey. The National Map [Internet]. Reston, VA: USGS; 2024 [cited 2024 Jul 14]. Available online: https://www.usgs.gov/programs/national-geospatial-program/national-map
26. United States Environmental Protection Agency. Calculate your radiation dose [Internet]. Washington, DC: EPA; 2024 [cited 2024 Jun 19]. Available online: https://www.epa.gov/radiation/calculate-your-radiation-dose
27. Baillie Lab. Air pressure [Internet]. Baillie Lab; 2024 [cited 2024 Jul 14]. Available online: https://baillielab.net/critical_care/air_pressure/
28. Xiong Q, Liu B, Ding M, et al. Hypoxia and cancer related pathology. Cancer Lett 2020;486:1-7. [Crossref] [PubMed]
29. Krain LS. Aviation, high altitude, cumulative radiation exposure and their associations with cancer. Med Hypotheses 1991;34:33-40. [Crossref] [PubMed]
30. Sawhney RC, Malhotra AS. Thyroid function during intermittent exposure to hypobaric hypoxia. Int J Biometeorol 1990;34:161-3. [Crossref] [PubMed]
31. Schottlender N, Gottfried I, Ashery U. Hyperbaric Oxygen Treatment: Effects on Mitochondrial Function and Oxidative Stress. Biomolecules 2021;11:1827. [Crossref] [PubMed]
32. Sreekumar A, Jayalekshmi PA, Nandakumar A, et al. Thyroid nodule prevalence among women in areas of high natural background radiation, Karunagappally, Kerala, India. Endocrine 2020;67:124-30. [Crossref] [PubMed]
33. Lee WJ, Preston DL, Cha ES, et al. Thyroid cancer risks among medical radiation workers in South Korea, 1996-2015. Environ Health 2019;18:19. [Crossref] [PubMed]