Skip to Content
You are currently on the new version of our website. Access the old version .
MDPIMDPI
CancersCancers
PDF
  • Article
  • Open Access

15 August 2023

Association of Metabolic Syndrome with the Risk of Head and Neck Cancer: A 10-Year Follow-Up Study of 10 Million Initially Healthy Individuals

,
and
1
Department of Otolaryngology-Head and Neck Surgery, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
2
Department of Biostatistics, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
*
Author to whom correspondence should be addressed.
Cancers2023, 15(16), 4118;https://doi.org/10.3390/cancers15164118
Version Notes
Order Reprints
Review Reports

Simple Summary

The global incidence of metabolic syndrome is on the rise, and its association with various types of cancer has been established. However, research into an association between metabolic syndrome and the incidence of head and neck cancer has been relatively limited. This population-based study aimed to report on the association of metabolic syndrome with head and neck cancer and individual subtypes of cancers. The study found that participants with metabolic syndrome exhibited a higher risk of developing head and neck cancer, particularly oral cavity and laryngeal cancers. The elevated levels of fasting glucose and blood pressure present in individuals with metabolic syndrome were independently associated with an increased risk of head and neck cancer. The results of this study could assist with etiological investigations and prevention strategies.

Abstract

The aim of this national population-based retrospective study was to analyze the relationship between MetS and the incidence of HNC. In this Korean population-based cohort study, 9,598,085 subjects above the age of 20 were monitored from 1 January 2009 to 31 December 2018. In the study population, a total of 10,732 individuals were newly diagnosed with HNC during the 10-year follow-up. The hazard ratio (HR), after adjusting for age, gender, smoking status, alcohol intake, and exercise, indicated that participants with MetS were at a 1.06-fold (95% CI: 1.01–1.10) higher risk of having HNC than those without MetS. Participants with MetS showed an increased risk of developing oral cavity cancer (HR, 1.12; 95% CI, 1.03–1.23) and laryngeal cancer (HR, 1.18; 95% CI, 1.09–1.27). Among the components of MetS, elevated fasting glucose (HR = 1.04, 95% CI: 1.00–1.08) and elevated blood pressure (HR = 1.08, 95% CI: 1.04–1.13) were significantly associated with an increased HR for HNC in an adjusted multivariable model. The association between HNC and MetS remained significant even among individuals who had never smoked or were ex-smokers (HR: 1.09; 95% CI: 1.04–1.15), as well as those who did not drink or were mild drinkers (HR: 1.07; 95% CI: 1.02–1.12). The findings of this cohort study suggest MetS was associated with an increased risk for some types of HNCs. The results of this study could assist with etiological investigations and prevention strategies.

1. Introduction

Metabolic syndrome (MetS) encompasses a combination of metabolic abnormalities such as insulin resistance, obesity, hypertension, hyperglycemia, dyslipidemia, and elevated triglyceride levels [1]. The global incidence of MetS is persistently increasing, with a notable surge in developed countries where diabetes and obesity rates are on the rise [2,3]. Head and neck cancer (HNC) was the seventh most common cancer in 2020 with 931,931 new cases globally [4], and includes oral cavity, nasopharyngeal, oropharyngeal, hypopharyngeal, laryngeal, and salivary gland cancers. In Korea, the incident cases of HNC have been steadily increasing over the past decade from around 4100 individuals in 2010 to 5600 individuals in 2020.
Smoking and alcohol consumption are major risk factors for HNC [5], but the relationship between obesity and the incidence of HNC remains controversial [6,7,8,9]. In a comprehensive analysis involving more than six million men from 203 studies, Petrelli et al. [10] found evidence indicating a higher overall cancer mortality rate among obese men. Additionally, adults classified as having metabolically healthy obesity displayed an elevated susceptibility to developing cancer [11].
MetS is associated with numerous diseases. Recent studies have demonstrated an increased risk of several cancers, including liver, colorectal, bladder, endometrial, pancreatic, and breast cancers [12,13,14,15]. Furthermore, meta-analyses indicated a strong association between MetS and thyroid cancer [16] and thyroid nodules [17]. Notably, the prevalence of MetS is progressively rising among Korean adults, emphasizing the need for population-based investigations to validate the relationship between MetS and cancer occurrence [18]. However, the association between the incidence of HNC and MetS has not been clearly determined. Thus, the objective of this study was to investigate the association between MetS and the risk of HNC and its subtypes.

2. Materials and Methods

2.1. Source of Data

Administered by the Ministry of Health, Welfare, and Family Affairs [19], the Korean National Health Insurance Service (KNHIS) functions as a public medical insurance system [19]. Operating as a mandatory social insurance program, the KNHIS initiative provides coverage for approximately 97% of the entire Korean population, while the remaining 3% are covered by the Medical Aid program [20]. The KNHIS database includes patient demographics and records of diagnoses, interventions, and prescriptions [21]. Diagnoses were confirmed using International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) codes, which include C02, C03, C04, C05, and C06 for oral cavity cancer; C07 and C08 for salivary gland cancer; C11 for nasopharyngeal cancer; C01, C051, C099, and C103 for oropharyngeal cancer; C12 and C13 for hypopharyngeal cancer; C10 for sinonasal cancer; and C32 for laryngeal cancer. The study’s protocol was granted approval by the Institutional Review Board of the Catholic University of Korea in Seoul.

2.2. Patient Selection

Individuals covered by the National Health Insurance Corporation are advised to undergo standardized medical assessments every two years. Those who were over 20 years old and had undergone health checkups in 2009 were enrolled in this study (n = 10,585,852). We monitored subjects until 31 December 2018. We excluded individuals with missing data (n = 746,403) and those with a history of other cancers before the health checkup (n = 153,456). We also applied a one-year lag period to minimize detection bias (n = 87,908). The remaining 9,598,085 subjects (5,220,801 males and 4,377,284 females) were included in this study from baseline to the date of diagnosis of HNC. Participants were defined as having HNC if their National Health Insurance records from 2010 to 2018 documented admissions related to HNC. The medical assessments encompassed measurements of height, weight, and blood pressure. Furthermore, measurements of fasting plasma glucose, triglyceride, total cholesterol, and high-density lipoprotein (HDL) levels were acquired. Past medical history and information on health-related behaviors such as smoking, alcohol intake, and physical activity were collected using a standardized, self-reported International Physical Activity Questionnaire. Also, the household income classification of this study was based on health insurance premiums; the National Health Insurance beneficiaries were divided into quartiles.

2.3. Definition of Metabolic Syndrome

The assessment period for MetS was determined based on the health checkup conducted in 2009. The definition of MetS was based on that of the joint interim statement of the International Diabetes Federation (IDF) Task Force on Epidemiology and Prevention [9]. According to this institution, MetS comprises three or more of these five components: abdominal obesity based on population- or country-specific definitions (waist circumference ≥ 85 cm) [22], elevated blood pressure (systolic ≥ 130 and/or diastolic ≥ 85 mmHg), hyperglycemia (fasting plasma glucose ≥ 100 mg/dL), hypertriglyceridemia (triglycerides ≥ 150 mg/dL), and low HDL-cholesterol levels (<40 mg/dL). Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters (kg/m2).

2.4. Statistical Analysis

Basic characteristics are presented using descriptive analysis. Differences in baseline characteristics between groups were determined using Student’s t-test for continuous variables and the χ2 test for categorical variables. HNC incidence was calculated by dividing the number of cases by 1000 person-years. Cox proportional hazards models were applied to estimate the hazard ratio (HR) and 95% confidence intervals (CIs) for the associations between MetS and the risk of HNC. Two linear regression models were constructed to explain the nonlinear relationship. First, segmented linear regression models were generated. The breakpoints were chosen as the values minimizing the Akaike information criteria of the Cox models. Second, multivariable regression analyses were performed using the number of metabolic components. Subtype analyses were also performed by using multivariable Cox proportional hazards models. Model 1 was unadjusted. Model 2 was adjusted for age, gender, smoking, alcohol consumption, regular exercise, and income. Model 3 was adjusted for age, gender, smoking, alcohol consumption, regular exercise, income, diabetes, and hypertension. Statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC, USA).

3. Results

3.1. Basic Characteristics

The characteristics of the study population are indicated in Table 1. During the 9-year follow-up period, 10,732 subjects were diagnosed with HNC. HNC patients were significantly older than those without HNC (p < 0.001). At baseline, the percentages of male and female participants with HNC were 79.2% and 20.8%, respectively (p < 0.001). Associations with current smoking, heavy alcohol intake, diabetes, hypertension, and dyslipidemia were statistically significant in the HNC group. The study revealed that HNC patients exhibited a substantially higher average waist circumference and higher systolic and diastolic blood pressure, fasting glucose, HDL cholesterol, and triglyceride levels compared to those without HNC. The number of MetS components was a risk factor with a higher risk estimate of HNC (p < 0.001).
Table 1. General characteristics of the participants at baseline in 2009 and head and neck cancer identified 2010–2018 (n = 9,598,085).

3.2. Associations between Metabolic Syndrome and Head and Neck Cancer

The unadjusted and multivariable-adjusted HRs for having HNC according to the presence or absence of MetS are presented in Table 2. Among the data, an adjustment was performed based on factors and diseases that affected HNC. An HR adjusted for age, gender, smoking, alcohol consumption, regular exercise, income, diabetes, and hypertension indicated that participants with MetS had a 1.06-fold higher risk of having HNC than those without MetS (95% CI: 1.01–1.10). Participants with MetS showed an increased risk of developing oral cavity cancer (HR = 1.12, 95% CI: 1.03–1.23) and laryngeal cancer (HR = 1.18, 95% CI: 1.09–1.27). No significant association was observed between MetS and an incidence of salivary gland cancer, nasopharyngeal cancer, oropharyngeal cancer, hypopharyngeal cancer, and sinonasal cancer. The unadjusted and multivariable-adjusted HRs for having HNC according to the number of MetS components are presented in Table S1. Figure 1 demonstrates the adjusted HRs (Model 3) from Table S1, where the incidence of overall HNC shows a significant linear trend according to the score of metabolic syndrome components (p = 0.017). In the results by subtype, the incidence rates show a linear trend according to the score of metabolic syndrome components. However, statistically significant results were observed in the case of laryngeal cancer (p < 0.001) and oropharyngeal cancer (p = 0.032) (Table S1).
Table 2. Multivariate Cox proportional hazards model for incidence of head and neck cancer and subtypes according to the presence of metabolic syndrome.
Figure 1. Hazard ratios for incidence of head and neck cancer and subtypes according to the score of metabolic syndrome components.

3.3. Association between Individual Components of Metabolic Syndrome and Head and Neck Cancer

We performed further analyses according to the individual components of MetS (Table 3). The adjusted multivariable model shows that an increased risk of HNC was significantly associated with higher fasting glucose (HR = 1.04, 95% CI: 1.00–1.08) and elevated blood pressure (HR = 1.08, 95% CI: 1.04–1.13).
Table 3. Multivariate Cox proportional hazards model for incidence of head and neck cancer according to the presence or absence of metabolic syndrome components.
The results regarding the association between the individual components of MetS and HNC subtypes are presented in Table S2. Subtype analysis revealed that a high waist circumference was associated with sinonasal cancer (HR = 1.23, 95% CI: 1.02–1.48), nasopharyngeal cancer (HR = 1.18, 95% CI: 1.03–1.35), and salivary gland cancer (HR = 1.17, 95% CI: 1.03–1.33). Conversely, a low waist circumference was associated with hypopharyngeal cancer (HR = 0.64, 95% CI: 0.55–0.76). Elevated fasting glucose was correlated with laryngeal cancer (HR = 1.13, 95% CI: 1.05–1.21). Elevated blood pressure was associated with laryngeal cancer (HR = 1.21, 95% CI: 1.12–1.31), hypopharyngeal cancer (HR = 1.27, 95% CI: 1.10–1.47), and oral cancer (HR = 1.12, 95% CI: 1.02–1.22). An elevation in triglyceride levels was associated with laryngeal cancer (HR = 1.22, 95% CI: 1.05–1.21) and oral cancer (HR = 1.12, 95% CI: 1.03–1.22). A low HDL cholesterol level was correlated with an increased risk of oral cancer (HR = 1.14, 95% CI: 1.04–1.24).

3.4. Associations between Other Risk Factors and Head and Neck Cancer

We examined the joint effect of MetS and age, gender, smoking status, alcohol consumption, exercise frequency, and BMI on the risk of HNC (Table 4). The risk of HNC was increased due to MetS regardless of gender (HR: 1.08, 95% CI: 1.03–1.13 for men; HR: 1.17, 95% CI: 1.06–1.28). HNC was associated with MetS even when individuals were never smokers or ex-smokers (HR: 1.09; 95% CI: 1.04–1.15) and had no or mild alcohol consumption (HR: 1.07; 95% CI: 1.02–1.12). The risk of HNC was associated with MetS in participants not performing regular exercise (HR: 1.05; 95% CI: 1.00–1.10). MetS was a statistically significant risk factor with a higher risk estimate of HNC regardless of BMI.
Table 4. Analysis of factors potentially associated with head and neck cancer according to the presence or absence of metabolic syndrome.

4. Discussion

The incidence of MetS continues to rise globally, particularly in developed countries in which diabetes and obesity rates are increasing [2,3]. MetS is associated with many diseases, and recent studies have demonstrated an increased risk for several cancers, including liver, colorectal, bladder, endometrial, pancreatic, and breast cancers [12,13,14,15]. Another previous research study established an association between MetS and thyroid cancer [16], and particularly with more aggressive forms of papillary thyroid cancer [16,23]. However, the relationship between MetS and HNCs other than thyroid cancer has not been thoroughly researched. To the best of our knowledge, this is the first large population-based study to examine the association of MetS with HNC and individual subtypes of cancers rather than examining the association of HNC with individual components of MetS.
In this study, the risk for developing HNC was significantly associated with MetS after adjusting for all confounders in Model 3 (HR = 1.06, 95% CI: 1.01–1.10). Notably, oral cavity cancer (HR = 1.12) and laryngeal cancer (HR = 1.18) were significantly associated with MetS. Interestingly, the association between MetS and a risk of cancer was not observed for other types of HNCs, including salivary gland cancer, nasopharyngeal cancer, oropharyngeal cancer, hypopharyngeal cancer, and sinonasal cancer. This suggests that the relationship between MetS and HNC may be specific to certain anatomical sites within the head and neck region.
Further analysis focusing on the individual components of MetS revealed that elevated fasting glucose (HR = 1.04) and elevated blood pressure (HR = 1.08) were significantly associated with an increased risk of HNC. In the subtype analysis, elevated fasting glucose was correlated with laryngeal cancer and elevated blood pressure with laryngeal, hypopharyngeal, and oral cancer. Hyperglycemia is a critical factor in the pathophysiology of MetS. Hyperglycemia, hyperinsulinemia, and insulin resistance increase proliferation and angiogenesis and destroy DNA molecules due to oxygen-active forms caused by excess glucose, cell migration, and apoptosis [24,25,26]. Previous studies have suggested that MetS elevates the risk of cancer through an induction of changes in insulin receptors and activation of growth and transcription factors [27,28]. Several studies have evaluated the influence of diabetes on HNC risk [29,30,31]. Although numerous studies have documented an association between hypertension and cancer, not all yielded conclusive results. In a meta-analysis of ten longitudinal studies conducted in 2002, individuals with hypertension were found to have a higher risk of overall cancer mortality with an odds ratio of 1.23 (95% CI: 1.11–1.36). A further analysis based on 13 case–control studies revealed a significant positive association between hypertension and renal cell carcinoma mortality with an odds ratio of 1.75 (95% CI: 1.61–1.90) [32]. Subsequent studies have corroborated these findings by confirming the association between hypertension and an increased incidence of renal cell carcinoma [33,34]. However, hypertension has not received significant attention as a risk factor for other types of cancer. Causal relationships between hypertension and cancers are difficult to establish; reverse causality and false evidence due to biases are difficult to rule out. Nonetheless, shared risk factors and mechanisms may contribute to these conditions. One hypothesis suggests that chronic inflammation, which is associated with an increased predisposition to cancer, may also be involved in the development of hypertension through vascular inflammation [35].
HNCs are closely related to tobacco use and alcohol consumption. Our study demonstrated that participants with MetS exhibited a higher risk estimate for the development of HNC even in non- or ex-smokers (HR: 1.09). This was also true for individuals with no or mild alcohol consumption (HR: 1.07). HNC incidence increases for current smokers and heavy drinkers, regardless of the presence of MetS. Conversely, for never or ex-smokers or infrequent alcohol consumers, the risk of HNC rises with the presence of MetS. This suggests that MetS acts as an independent risk factor for HNC, which is separate from the influence of smoking and alcohol consumption.
In previous studies, the association between obesity and the incidence of HNC remained controversial [6,7,8,9]. In most studies, HNC is associated with a lower BMI compared with a normal and higher BMI [36]. Gaudet et al. suggested that a low BMI was associated with a higher risk of HNC, regardless of smoking and drinking [7]. Furthermore, a large cohort study conducted at our institution, which analyzed the correlation between BMI and HNC, also found similar results to those found in previous studies [37].
This study highlights the importance of considering MetS as a potential risk factor for HNC and emphasizes the need for comprehensive management and prevention strategies targeting the components of MetS. Further research, including well-designed case–control studies, is warranted to gain a deeper understanding of the underlying mechanisms linking MetS to specific types of HNCs and to explore potential preventive and therapeutic interventions.

Strengths and Limitations

Our study had several notable strengths. First, we had a substantial study population, consisting of approximately one-fourth of the adult Korean population, to provide an adequate representative sample. Moreover, the longitudinal design covered a ten-year follow-up period, enabling the collection of comprehensive data on cancer development. Second, the reliability of the data was enhanced by the accessibility of Korea’s healthcare system, which ensures universal coverage for all citizens. Third, the study’s rigorous methodology included only pathologist-diagnosed cancer cases and precise MetS diagnoses based on strict diagnostic criteria.
The study had certain limitations that should be acknowledged. First, most participants were of Korean descent, which limits the generalizability of the findings to other racial or ethnic groups. Second, the data did not include information on medications or other health conditions that could potentially increase the risk of cancer, limiting our ability to account for these factors. Third, the study did not consider the potential selection bias that could result from collecting data through self-reported questionnaires regarding prior medical history and health-related behaviors. Fourth, comprehensive data on HPV infection, which is associated with HNC, were not available for all patients. Additionally, industrial data were not available. Last, this study was conducted as a retrospective cohort study spanning a duration of 10 years; participants’ lifestyles, such as their smoking or drinking habits, may have undergone changes during this observational period. Capturing and incorporating these changes into the data analysis proved challenging. Also, exploring a causal relationship between changes in BMI, waist circumference, and the risk of HNC was not within the scope of this cohort study.

5. Conclusions

In this large cohort study, we found a significant association between MetS and the incidence of HNC. Participants with MetS had a higher risk of developing HNC, particularly oral cavity cancer and laryngeal cancer. Elevated fasting glucose and blood pressure present in MetS were independently associated with an increased HNC risk. Further research on this subject may lead to recommendations that patients diagnosed with MetS, especially diabetes and hypertension, should undergo regular screenings for HNC.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers15164118/s1. Table S1: Multivariate Cox proportional hazard model for incidence of head and neck cancer by subtype according to the score of metabolic syndrome components. Table S2: Multivariate Cox proportional hazard model for incidence of head and neck cancer by subtype according to the presence or absence of the metabolic syndrome components.

Author Contributions

Y.-H.J. designed the study. K.-D.H. collected and analyzed data. G.-J.K. wrote the main manuscript and inspected the figures and tables. Y.-H.J. reviewed the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

All data were collected in accordance with the World Medical Association Declaration of Helsinki. The study protocol was approved by the Institutional Review Board of the Catholic University of Korea (No. PC21ZISI0235).

Data Availability Statement

Data are only available upon request due to data sharing restrictions. The data presented in this study are available upon request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Bellastella, G.; Scappaticcio, L.; Esposito, K.; Giugliano, D.; Maiorino, M.I. Metabolic syndrome and cancer: “the common soil hypothesis”. Diabetes Res. Clin. Pract. 2018, 143, 389–397. [Google Scholar] [CrossRef]
  2. Gu, D.; Reynolds, K.; Wu, X.; Chen, J.; Duan, X.; Reynolds, R.F.; Whelton, P.K.; He, J. InterASIA Collaborative Group. Prevalence of the metabolic syndrome and overweight among adults in China. Lancet 2005, 365, 1398–1405. [Google Scholar] [CrossRef]
  3. Esposito, K.; Chiodini, P.; Colao, A.; Lenzi, A.; Giugliano, D. Metabolic syndrome and risk of cancer: A systematic review and meta-analysis. Diabetes Care 2012, 35, 2402–2411. [Google Scholar] [CrossRef] [PubMed]
  4. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef] [PubMed]
  5. Hashibe, M.; Brennan, P.; Benhamou, S.; Castellsague, X.; Chen, C.; Curado, M.P.; Dal Maso, L.; Daudt, A.W.; Fabianova, E.; Fernandez, L.; et al. Alcohol drinking in never users of tobacco, cigarette smoking in never drinkers, and the risk of head and neck cancer: Pooled analysis in the International Head and Neck Cancer Epidemiology Consortium. J. Natl. Cancer Inst. 2007, 16, 777–789. [Google Scholar] [CrossRef]
  6. Lubin, J.H.; Gaudet, M.M.; Olshan, A.F.; Kelsey, K.; Boffetta, P.; Brennan, P.; Castellsague, X.; Chen, C.; Curado, M.P.; Maso, L.D.; et al. Body mass index, cigarette smoking, and alcohol consumption and cancers of the oral cavity, pharynx, and larynx: Modeling odds ratios in pooled case-control data. Am. J. Epidemiol. 2010, 171, 1250–1261. [Google Scholar] [CrossRef] [PubMed]
  7. Gaudet, M.M.; Olshan, A.F.; Chuang, S.C.; Berthiller, J.; Zhang, Z.F.; Lissowska, J.; Zaridze, D.; Winn, D.M.; Wei, Q.; Talamini, R.; et al. Body mass index and risk of head and neck cancer in a pooled analysis of case-control studies in the International Head and Neck Cancer Epidemiology (INHANCE) Consortium. Int. J. Epidemiol. 2010, 39, 1091–1102. [Google Scholar] [CrossRef] [PubMed]
  8. Maasland, D.H.E.; Brandt, P.A.V.D.; Kremer, B.; Schouten, L.J. Body mass index and risk of subtypes of head-neck cancer: The Netherlands Cohort Study. Sci. Rep. 2015, 5, 17744. [Google Scholar] [CrossRef]
  9. Gaudet, M.M.; Patel, A.V.; Sun, J.; Hildebrand, J.S.; McCullough, M.L.; Chen, A.Y.; Gapstur, S.M. Prospective studies of body mass index with head and neck cancer incidence and mortality. Cancer Epidemiol. Biomark. Prev. 2012, 21, 497–503. [Google Scholar] [CrossRef]
  10. Petrelli, F.; Cortellini, A.; Indini, A.; Tomasello, G.; Ghidini, M.; Nigro, O.; Salati, M.; Dottorini, L.; Iaculli, A.; Varricchio, A.; et al. Association of Obesity with Survival Outcomes in Patients with Cancer: A Systematic Review and Meta-analysis. JAMA Netw. Open 2021, 4, e213520. [Google Scholar] [CrossRef]
  11. Lin, C.J.; Chang, Y.C.; Cheng, T.Y.; Lo, K.; Liu, S.J.; Yeh, T.L. The association between metabolically healthy obesity and risk of cancer: A systematic review and meta-analysis of prospective cohort studies. Obes. Rev. 2020, 21, e13049. [Google Scholar] [CrossRef] [PubMed]
  12. Chiu, H.M.; Lin, J.T.; Shun, C.T.; Liang, J.T.; Lee, Y.C.; Huang, S.P.; Wu, M.S. Association of metabolic syndrome with proximal and synchronous colorectal neoplasm. Clin. Gastroenterol. Hepatol. 2007, 5, 221–229. [Google Scholar] [CrossRef] [PubMed]
  13. Laukkanen, J.A.; Laaksonen, D.E.; Niskanen, L.; Pukkala, E.; Hakkarainen, A.; Salonen, J.T. Metabolic syndrome and the risk of prostate cancer in Finnish men: A population-based study. Cancer Epidemiol. Biomark. Prev. 2004, 13, 1646–1650. [Google Scholar] [CrossRef]
  14. Lund Håheim, L.; Wisløff, T.F.; Holme, I.; Nafstad, P. Metabolic syndrome predicts prostate cancer in a cohort of middle-aged Norwegian men followed for 27 years. Am. J. Epidemiol. 2006, 164, 769–774. [Google Scholar] [CrossRef]
  15. Pasanisi, P.; Berrino, F.; De Petris, M.; Venturelli, E.; Mastroianni, A.; Panico, S. Metabolic syndrome as a prognostic factor for breast cancer recurrences. Int. J. Cancer 2006, 119, 236–238. [Google Scholar] [CrossRef] [PubMed]
  16. Yin, D.T.; He, H.; Yu, K.; Xie, J.; Lei, M.; Ma, R.; Li, H.; Wang, Y.; Liu, Z. The association between thyroid cancer and insulin resistance, metabolic syndrome and its components: A systematic review and meta-analysis. Int. J. Surg. 2018, 57, 66–75. [Google Scholar] [CrossRef] [PubMed]
  17. Zhang, C.; Gao, X.; Han, Y.; Teng, W.; Shan, Z. Correlation Between Thyroid Nodules and Metabolic Syndrome: A Systematic Review and Meta-Analysis. Front. Endocrinol. 2021, 12, 730279. [Google Scholar] [CrossRef] [PubMed]
  18. Mendonça, F.M.; de Sousa, F.R.; Barbosa, A.L.; Martins, S.C.; Araújo, R.L.; Soares, R.; Abreu, C. Metabolic syndrome and risk of cancer: Which link? Metabolism 2015, 64, 182–189. [Google Scholar] [CrossRef]
  19. Kim, D.S. Introduction: Health of the health care system in Korea. Soc. Work Public Health 2010, 25, 127–141. [Google Scholar]
  20. Yhim, H.Y.; Jang, M.J.; Bang, S.M.; Kim, K.H.; Kim, Y.K.; Nam, S.H.; Bae, S.H.; Kim, S.H.; Mun, Y.C.; Kim, I.; et al. Incidence of venous thromboembolism following major surgery in Korea: From the Health Insurance Review and Assessment Service database. J. Thromb. Haemost. 2014, 12, 1035–1043. [Google Scholar] [CrossRef]
  21. Alberti, K.G.; Zimmet, P.; Shaw, J. Metabolic syndrome--a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabet. Med. 2006, 23, 469–480. [Google Scholar] [CrossRef] [PubMed]
  22. Renehan, A.G.; Frystyk, J.; Flyvbjerg, A. Obesity and cancer risk: The role of the insulin-IGF axis. Trends Endocrinol. Metab. 2006, 17, 328–336. [Google Scholar] [CrossRef]
  23. Park, J.H.; Choi, M.; Kim, J.H.; Kim, J.; Han, K.; Kim, B.; Kim, D.H.; Park, Y.G. Metabolic Syndrome and the Risk of Thyroid Cancer: A Nationwide Population-Based Cohort Study. Thyroid 2020, 30, 1496–1504. [Google Scholar] [CrossRef] [PubMed]
  24. Berstein, L.M. Modern approach to metabolic rehabilitation of cancer patients: Biguanides (phenformin and metformin) and beyond. Future Oncol. 2010, 6, 1313–1323. [Google Scholar] [CrossRef] [PubMed]
  25. Chia, P.P.; Fan, S.H.; Say, Y.H. Screening of peroxisome proliferator-activated receptors (PPARs) alpha, gamma and alpha Gene Polymorphisms for Obesity and Metabolic Syndrome Association in the Multi-Ethnic Malaysian Population. Ethn. Dis. 2015, 25, 383–390. [Google Scholar] [CrossRef]
  26. Yunusova, N.V.; Spirina, L.V.; Frolova, A.E.; Afanas’ev, S.G.; Kolegova, E.S.; Kondakova, I.V. Association of IGFBP-6 expression with metabolic syndrome and adiponectin and IGF-IR receptor levels in colorectal cancer. Asian Pac. J. Cancer Prev. 2016, 17, 3963–3969. [Google Scholar]
  27. Wang, Y.; Gao, C.; Zhang, Y.; Gao, J.; Teng, F.; Tian, W.; Yang, W.; Yan, Y.; Xue, F. Visfatin stimulates endometrial cancer cell proliferation via activation of PI3K/Akt and MAPK/ERK1/2 signalling pathways. Gynecol. Oncol. 2016, 143, 168–178. [Google Scholar] [CrossRef] [PubMed]
  28. Gao, J.; Tian, J.; Lv, Y.; Shi, F.; Kong, F.; Shi, H.; Zhao, L. Leptin induces functional activation of cyclooxygenase-2 through JAK2/STAT3, MAPK/ERK, and PI3K/AKT pathways in human endometrial cancer cells. Cancer Sci. 2009, 100, 389–395. [Google Scholar] [CrossRef]
  29. Stott-Miller, M.; Chen, C.; Chuang, S.C.; Lee, Y.C.; Boccia, S.; Brenner, H.; Cadoni, G.; Dal Maso, L.; La Vecchia, C.; Lazarus, P.; et al. History of diabetes and risk of head and neck cancer: A pooled analysis from the international head and neck cancer epidemiology consortium. Cancer Epidemiol. Biomark. Prev. 2012, 21, 294–304. [Google Scholar] [CrossRef]
  30. Wideroff, L.; Gridley, G.; Mellemkjaer, L.; Chow, W.H.; Linet, M.; Keehn, S.; Borch-Johnsen, K.; Olsen, J.H. Cancer incidence in a population-based cohort of patients hospitalized with diabetes mellitus in Denmark. J. Natl. Cancer Inst. 1997, 89, 1360–1365. [Google Scholar] [CrossRef]
  31. Suba, Z. Gender-related hormonal risk factors for oral cancer. Pathol. Oncol. Res. 2007, 13, 195–202. [Google Scholar] [CrossRef] [PubMed]
  32. Grossman, E.; Messerli, F.H.; Boyko, V.; Goldbourt, U. Is there an association between hypertension and cancer mortality? Am. J. Med. 2002, 112, 479–486. [Google Scholar] [CrossRef] [PubMed]
  33. Weikert, S.; Boeing, H.; Pischon, T.; Weikert, C.; Olsen, A.; Tjonneland, A.; Overvad, K.; Becker, N.; Linseisen, J.; Trichopoulou, A.; et al. Blood pressure and risk of renal cell carcinoma in the European prospective investigation into cancer and nutrition. Am. J. Epidemiol. 2008, 167, 438–446. [Google Scholar] [CrossRef] [PubMed]
  34. Hidayat, K.; Du, X.; Zou, S.Y.; Shi, B.M. Blood pressure and kidney cancer risk: Meta-analysis of prospective studies. J. Hypertens. 2017, 35, 1333–1344. [Google Scholar] [CrossRef] [PubMed]
  35. Dinh, Q.N.; Drummond, G.R.; Sobey, C.G.; Chrissobolis, S. Roles of inflammation, oxidative stress, and vascular dysfunction in hypertension. Biomed. Res. Int. 2014, 2014, 406960. [Google Scholar] [CrossRef] [PubMed]
  36. Radoï, L.; Paget-Bailly, S.; Cyr, D.; Papadopoulos, A.; Guida, F.; Tarnaud, C.; Menvielle, G.; Schmaus, A.; Cénée, S.; Carton, M.; et al. Body mass index, body mass change, and risk of oral cavity cancer: Results of a large population-based case-control study, the ICARE study. Cancer Causes Control 2013, 24, 1437–1448. [Google Scholar] [CrossRef] [PubMed]
  37. Kim, C.S.; Park, J.O.; Nam, I.C.; Park, S.J.; Lee, D.H.; Kim, H.B.; Han, K.D.; Joo, Y.H. Associations of Body Mass Index and Waist Circumference with the Risk of Head and Neck Cancer: A National Population-Based Study. Cancers 2022, 14, 3880. [Google Scholar] [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Journal Statistics
Multiple requests from the same IP address are counted as one view.
Evaluation of Intratumoral Response Heterogeneity in Metastatic Colorectal Cancer and Its Impact on Patient Overall Survival: Findings from 10,551 Patients in the ARCAD Database
Previous
Where to Draw the LINE—Are Retrotransposable Elements Here to Stay?
Next