Skip to main content

Advertisement

SpringerLink
Log in

“Non-modifiable” Risk Factors for Periodontitis and Diabetes

  • Systemic Diseases (M Bartold, Section Editor)
  • Published:
Current Oral Health Reports Aims and scope Submit manuscript

Abstract

This review describes the current evidence published from January 2013 through March 2016 for “non-modifiable” risk factors for periodontitis and diabetes mellitus. Risk factors for a disease are factors that increase the chance of developing the disease, that is, new onset or incidence. Periodontitis and diabetes are both chronic, inflammation-related diseases and often occur in the same individuals, which agrees with the two diseases having largely the same risk factors and also mutually and adversely affecting each other. “Non-modifiable” risk factors for both diseases include higher age, male sex, minority race or ethnicity, low socioeconomic status, genetic predisposition (mostly for impaired immune/inflammatory responses), a history of radiation therapy, pancreatic diseases, polycystic ovary syndrome, Alzheimer’s disease and other types of dementia, and a history of cigarette smoking. Additionally, a history of poorly controlled diabetes, rheumatoid arthritis, as well as possibly osteoporosis, increases the risk for periodontitis, whereas a personal history of antibiotics use and a family history of diabetes additionally increase the risk for diabetes. Given the similarities between the risk factors, the prevention, management, and treatment aimed to ameliorate the strength of the effects of these risk factors, the risks for both periodontitis and diabetes should be attenuated simultaneously. Interventions would probably be facilitated by being conducted in a patient-centered professional collaboration among dental and medical healthcare providers caring for their mutual patient and addressing risk factors for both periodontitis and diabetes for the best possible quality of life of their mutual patient.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Borgnakke WS. Modifiable risk factors for periodontitis and diabetes. Curr Oral Health Rep. 2016:3(3). doi:10.1007/s40496-016-0099-6. This report complements the current review as it describes risk factors that are modifiable.

  2. Bartold PM, Van Dyke TE. Periodontitis: a host-mediated disruption of microbial homeostasis; unlearning learned concepts. Periodontol 2000. 2013;62(10.1111/j.1600-0757.2012.00450.x):203–17. doi:10.1111/j.1600-0757.2012.00450.x.

  3. Lamont RJ, Hajishengallis G. Polymicrobial synergy and dysbiosis in inflammatory disease. Trends Mol Med. 2015;21(3):172–83. doi:10.1016/j.molmed.2014.11.004.

    Article  CAS  PubMed  Google Scholar 

  4. Fisher MA, Ma ZQ. Multiple chronic conditions: diabetes associated with comorbidity and shared risk factors using CDC WEAT and SAS analytic tools. J Prim Care Community Health. 2014;5(2):112–21. doi:10.1177/2150131913503347.

    Article  PubMed  Google Scholar 

  5. Genco RJ, Borgnakke WS. Risk factors for periodontal disease. Periodontol 2000. 2013;62(1):59–94. doi:10.1111/j.1600-0757.2012.00457.x.

    Article  PubMed  Google Scholar 

  6. Genco RJ, Genco FD. Common risk factors in the management of periodontal and associated systemic diseases: the dental setting and interprofessional collaboration. J Evid Based Dent Pract. 2014;14:4–16. doi:10.1016/j.jebdp.2014.03.003.

    Article  PubMed  Google Scholar 

  7. Kocher T, Schwahn C, Gesch D, Bernhardt O, John U, Meisel P, et al. Risk determinants of periodontal disease—an analysis of the study of health in Pomerania (SHIP 0). J Clin Periodontol. 2005;32(1):59–67. doi:10.1111/j.1600-051X.2004.00629.x.

    Article  CAS  PubMed  Google Scholar 

  8. Zhan Y, Holtfreter B, Meisel P, Hoffmann T, Micheelis W, Dietrich T, et al. Prediction of periodontal disease: modelling and validation in different general German populations. J Clin Periodontol. 2014;41(3):224–31. doi:10.1111/jcpe.12208.

    Article  PubMed  Google Scholar 

  9. Eke PI, Wei L, Thornton-Evans GO, Borrell LN, Borgnakke WS, Genco RJ. Risk indicators for periodontitis in US adults: NHANES 2009–2012. J Periodontol. Accepted for publication May 17, 2016.

  10. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014;37 Suppl 1:S81–90. doi:10.2337/dc14-S081.

    Article  Google Scholar 

  11. American Diabetes Association. 2. Classification and diagnosis of diabetes. Diabetes Care. 2015;38 Suppl 1:S8–16. doi:10.2337/dc15-S005.

    Article  Google Scholar 

  12. Schwartz SS, Epstein S, Corkey BE, Grant SF, Gavin 3rd JR, Aguilar RB. The time is right for a new classification system for diabetes: rationale and implications of the beta-cell-centric classification schema. Diabetes Care. 2016;39(2):179–86. doi:10.2337/dc15-1585.

    Article  PubMed  Google Scholar 

  13. Eke PI, Dye BA, Wei L, Thornton-Evans GO, Genco RJ, on behalf of the participating members of the CDC Periodontal Disease Surveillance workgroup: James Beck (University of North Carolina CH, USA), Gordon Douglass (Past President, American Academy of Periodontology), Roy Page (University of Washington, Seattle, USA), Gary Slade (University of North Carolina, Chapel Hill, USA), George W. Taylor (University of Michigan, Ann Arbor, USA), Wenche Borgnakke (University of Michigan, Ann Arbor, USA), and representatives of the American Academy of Periodontology. Prevalence of periodontitis in adults in the United States: 2009 and 2010. J Dent Res. 2012;91 Suppl 10:914–20. doi:10.1177/0022034512457373.

  14. Eke PI, Page RC, Wei L, Thornton-Evans G, Genco RJ. Update of the case definitions for population-based surveillance of periodontitis. J Periodontol. 2012;83(12):1449–54. doi:10.1902/jop.2012.110664.

    Article  PubMed  Google Scholar 

  15. Eke PI, Dye BA, Wei L, Slade GD, Thornton-Evans GO, Borgnakke WS, et al. Update on prevalence of periodontitis in adults in the United States: NHANES 2009 to 2012. J Periodontol. 2015;86(5):611–22. doi:10.1902/jop.2015.140520.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Eke PI, Wei L, Borgnakke WS, Thornton-Evans G, Zhang X, Lu H, et al. Periodontitis prevalence in United States older adults ≥65 years, NHANES 2009–2012. Periodontology 2000. Accepted for publication February 23, 2016.

  17. Pettitt DJ, Talton J, Dabelea D, Divers J, Imperatore G, Lawrence JM, et al. Prevalence of diabetes in U.S. youth in 2009: the search for diabetes in youth study. Diabetes Care. 2014;37(2):402–8. doi:10.2337/dc13-1838.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Anjana RM, Shanthi Rani CS, Deepa M, Pradeepa R, Sudha V, Divya Nair H, et al. Incidence of diabetes and prediabetes and predictors of progression among Asian Indians: 10-year follow-up of the Chennai Urban Rural Epidemiology Study (CURES). Diabetes Care. 2015;38(8):1441–8. doi:10.2337/dc14-2814.

    Article  PubMed  Google Scholar 

  19. Steffens JP, Masi S, D’Aiuto F, Spolidorio LC. Telomere length and its relationship with chronic diseases—new perspectives for periodontal research. Arch Oral Biol. 2013;58(2):111–7. doi:10.1016/j.archoralbio.2012.09.009.

    Article  CAS  PubMed  Google Scholar 

  20. Sanders AE, Divaris K, Naorungroj S, Heiss G, Risques RA. Telomere length attrition and chronic periodontitis: an ARIC study nested case–control study. J Clin Periodontol. 2015;42(1):12–20. doi:10.1111/jcpe.12337.

    Article  CAS  PubMed  Google Scholar 

  21. Masi S, Gkranias N, Li K, Salpea KD, Parkar M, Orlandi M, et al. Association between short leukocyte telomere length, endotoxemia, and severe periodontitis in people with diabetes: a cross-sectional survey. Diabetes Care. 2014;37(4):1140–7. doi:10.2337/dc13-2106.

    Article  CAS  PubMed  Google Scholar 

  22. Leung CW, Laraia BA, Needham BL, Rehkopf DH, Adler NE, Lin J, et al. Soda and cell aging: associations between sugar-sweetened beverage consumption and leukocyte telomere length in healthy adults from the National Health and Nutrition Examination Surveys. Am J Public Health. 2014;104(12):2425–31. doi:10.2105/ajph.2014.302151.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Wang Y, LaMonte MJ, Hovey KM, Mai X, Tezal M, Millen AE, et al. Association of serum 17beta-estradiol concentration, hormone therapy, and alveolar crest height in postmenopausal women. J Periodontol. 2015;86(4):595–605. doi:10.1902/jop.2015.140533.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Karvonen-Gutierrez CA, Park SK, Kim C. Diabetes and menopause. Curr Diab Rep. 2016;16(4):20. doi:10.1007/s11892-016-0714-x.

    Article  PubMed  CAS  Google Scholar 

  25. Stefanska A, Bergmann K, Sypniewska G. Metabolic syndrome and menopause: pathophysiology, clinical and diagnostic significance. Adv Clin Chem. 2015;72:1–75. doi:10.1016/bs.acc.2015.07.001.

    Article  PubMed  Google Scholar 

  26. Garcia D, Tarima S, Okunseri C. Periodontitis and glycemic control in diabetes: NHANES 2009 to 2012. J Periodontol. 2015;86(4):499–506. doi:10.1902/jop.2014.140364. This is the first paper analyzing data from the first NHANES cycles applying the full-mouth periodontal probing at six sites around all non-third-molar teeth while using the CDC/AAP periodontitis case definition and relating the periodontitis status to levels of glycemic control. Glycated hemoglobin levels were significantly associated with presence of periodontitis (mild, moderate, or severe), even in a dose–response manner.

    Article  PubMed  Google Scholar 

  27. Steffens JP, Wang X, Starr JR, Spolidorio LC, Van Dyke TE, Kantarci A. Associations between sex hormone levels and periodontitis in men: results from NHANES III. J Periodontol. 2015;86(10):1116–25. doi:10.1902/jop.2015.140530.

    Article  PubMed  Google Scholar 

  28. Meisel P, Holtfreter B, Volzke H, Kocher T. Sex differences of tooth loss and obesity on systemic markers of inflammation. J Dent Res. 2014;93(8):774–9. doi:10.1177/0022034514535604.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Kiedrowicz M, Dembowska E, Banach J, Safranow K, Pynka S. A comparison of the periodontal status in patients with type 2 diabetes based on glycated haemoglobin levels and other risk factors. Adv Med Sci. 2015;60(1):156–61. doi:10.1016/j.advms.2015.01.007.

    Article  PubMed  Google Scholar 

  30. Arnetz L, Ekberg NR, Alvarsson M. Sex differences in type 2 diabetes: focus on disease course and outcomes. Diabetes Metab Syndr Obes. 2014;7:409–20. doi:10.2147/dmso.s51301.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Samuelsson U, Anderzen J, Gudbjörnsdottir S, Steineck I, Åkesson K, Hanberger L. Teenage girls with type 1 diabetes have poorer metabolic control than boys and face more complications in early adulthood. J Diabet Complications. 2016;30(5):917--22. doi:10.1016/j.jdiacomp.2016.02.007.

  32. Levine ME, Kim JK, Crimmins EM. The role of physiological markers of health in the association between demographic factors and periodontal disease. J Periodontal Res. 2013;48(3):367–72. doi:10.1111/jre.12016.

    Article  CAS  PubMed  Google Scholar 

  33. Eke PI, Zhang X, Lu H, Wei L, Thornton-Evans G, Greenlund KJ, et al. Predicting periodontitis at state and local levels in the United States. J Dent Res. 2016;95(5):515–22. doi:10.1177/0022034516629112. This report is the first to apply complex statistical methods (small area estimation combined with data from the US Census) to predict periodontitis status at the state and even county level in the US. The authors used the most recent periodontal data from the NHANES 2009–2012 and applied the CDC/AAP periodontitis case definition.

    Article  CAS  PubMed  Google Scholar 

  34. Farrar D, Fairley L, Santorelli G, Tuffnell D, Sheldon TA, Wright J, et al. Association between hyperglycaemia and adverse perinatal outcomes in South Asian and White British women: analysis of data from the Born in Bradford cohort. Lancet Diabetes Endocrinol. 2015;3(10):795–804. doi:10.1016/s2213-8587(15)00255-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Geiss LS, Wang J, Cheng YJ, Thompson TJ, Barker L, Li Y, et al. Prevalence and incidence trends for diagnosed diabetes among adults aged 20 to 79 years, United States, 1980–2012. JAMA. 2014;312(12):1218–26. doi:10.1001/jama.2014.11494.

    Article  CAS  PubMed  Google Scholar 

  36. Hara K, Fujita H, Johnson TA, Yamauchi T, Yasuda K, Horikoshi M, et al. Genome-wide association study identifies three novel loci for type 2 diabetes. Hum Mol Genet. 2014;23(1):239–46. doi:10.1093/hmg/ddt399.

    Article  CAS  PubMed  Google Scholar 

  37. Kanaya AM, Herrington D, Vittinghoff E, Ewing SK, Liu K, Blaha MJ, et al. Understanding the high prevalence of diabetes in U.S. South Asians compared with four racial/ethnic groups: the MASALA and MESA studies. Diabetes Care. 2014;37(6):1621–8. doi:10.2337/dc13-2656.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Menke A, Casagrande S, Geiss L, Cowie CC. Prevalence of and trends in diabetes among adults in the United States, 1988–2012. JAMA. 2015;314(10):1021–9. doi:10.1001/jama.2015.10029.

    Article  CAS  PubMed  Google Scholar 

  39. Selvin E, Parrinello CM, Sacks DB, Coresh J. Trends in prevalence and control of diabetes in the United States, 1988–1994 and 1999–2010. Ann Intern Med. 2014;160(8):517–25. doi:10.7326/M13-2411.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Wolffenbuttel BH, Herman WH, Gross JL, Dharmalingam M, Jiang HH, Hardin DS. Ethnic differences in glycemic markers in patients with type 2 diabetes. Diabetes Care. 2013;36(10):2931–6. doi:10.2337/dc12-2711.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Mahajan A, Go MJ, Zhang W, Below JE, Gaulton KJ, Ferreira T, et al. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet. 2014;46(3):234–44. doi:10.1038/ng.2897.

    Article  CAS  PubMed  Google Scholar 

  42. Ntuk UE, Gill JM, Mackay DF, Sattar N, Pell JP. Ethnic-specific obesity cutoffs for diabetes risk: cross-sectional study of 490,288 UK biobank participants. Diabetes Care. 2014;37(9):2500–7. doi:10.2337/dc13-2966.

    Article  PubMed  Google Scholar 

  43. Borrell LN, Crawford ND. Socioeconomic position indicators and periodontitis: examining the evidence. Periodontol 2000. 2012;58(1):69–83. doi:10.1111/j.1600-0757.2011.00416.x.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Offenbacher S, Divaris K, Barros SP, Moss KL, Marchesan JT, Morelli T, et al. Genome-wide association study of biologically-informed periodontal complex traits offers novel insights into the genetic basis of periodontal disease. Hum Mol Genet. 2016. doi:10.1093/hmg/ddw069. This study combined clinical periodontal data with information on levels of 8 bacteria usually associated with periodontitis and the genome-wide association study (GWAS) in 975 American adults of European ancestry identified 6 periodontal coplex traits (PCTs) with distinct structures of microbioal community and interleukin-8-beta and tested them in two populations (US and Germany). However, the identified loci did not correspond to specific phenotypes for periodontitis, but involved genes related to immune response and function of the epithelial barriers. This could explain why existing GWAS studies fail to link specific genes to the clinical manifestation of periodontitis (See also Ref. #55 Teumer et al.) and could indicate the lack of the existence of specific genes causing specific susceptibility to periodontitis, but rather be indicative of susceptibility to general impairment of inflammatory and immune responses.

    PubMed Central  Google Scholar 

  45. Loos BG, Papantonopoulos G, Jepsen S, Laine ML. What is the contribution of genetics to periodontal risk? Dent Clin N Am. 2015;59(4):761–80. doi:10.1016/j.cden.2015.06.005.

    Article  PubMed  Google Scholar 

  46. Barros SP, Offenbacher S. Modifiable risk factors in periodontal disease: epigenetic regulation of gene expression in the inflammatory response. Periodontol 2000. 2014;64(1):95–110. doi:10.1111/prd.12000.

    Article  PubMed  Google Scholar 

  47. Arjunan P, El-Awady A, Dannebaum RO, Kunde-Ramamoorthy G, Cutler CW. High-throughput sequencing reveals key genes and immune homeostatic pathways activated in myeloid dendritic cells by Porphyromonas gingivalis 381 and its fimbrial mutants. Mol Oral Microbiol. 2016;31(1):78–93. doi:10.1111/omi.12131.

    Article  CAS  PubMed  Google Scholar 

  48. Zeng XT, Liu DY, Kwong JS, Leng WD, Xia LY, Mao M. Meta-analysis of association between interleukin-1beta C-511t polymorphism and chronic periodontitis susceptibility. J Periodontol. 2015;86(6):812–9. doi:10.1902/jop.2015.140698.

    Article  CAS  PubMed  Google Scholar 

  49. Wu X, Offenbacher S, Lomicronpez NJ, Chen D, Wang HY, Rogus J, et al. Association of interleukin-1 gene variations with moderate to severe chronic periodontitis in multiple ethnicities. J Periodontal Res. 2015;50(1):52–61. doi:10.1111/jre.12181.

    Article  CAS  PubMed  Google Scholar 

  50. Suma S, Naito M, Wakai K, Sasakabe T, Hattori Y, Okada R, et al. Effects of Il6 C-634G polymorphism on tooth loss and their interaction with smoking habits. Oral Dis. 2015;21(6):807–13. doi:10.1111/odi.12352.

    Article  CAS  PubMed  Google Scholar 

  51. Corbi SC, Anovazzi G, Finoti LS, Kim YJ, Capela MV, Secolin R, et al. Haplotypes of susceptibility to chronic periodontitis in the interleukin 8 gene do not influence protein level in the gingival crevicular fluid. Arch Oral Biol. 2012;57(10):1355–61. doi:10.1016/j.archoralbio.2012.07.003.

    Article  CAS  PubMed  Google Scholar 

  52. Corbi SC, Finoti LS, Anovazzi G, Tanaka MH, Kim YJ, Secolin R, et al. Clinical outcomes of periodontal therapy are not influenced by the ATC/TTC haplotype in the Il-8 gene. J Periodontal Res. 2014;49(4):489–98. doi:10.1111/jre.12128.

    Article  CAS  PubMed  Google Scholar 

  53. Scarel-Caminaga RM, Kim YJ, Viana AC, Curtis KM, Corbi SC, Sogumo PM, et al. Haplotypes in the interleukin 8 gene and their association with chronic periodontitis susceptibility. Biochem Genet. 2011;49(5):292–302. doi:10.1007/s10528-010-9407-3.

    Article  CAS  PubMed  Google Scholar 

  54. Rittling SR, Singh R. Osteopontin in immune-mediated diseases. J Dent Res. 2015;94(12):1638–45. doi:10.1177/0022034515605270.

    Article  CAS  PubMed  Google Scholar 

  55. Teumer A, Holtfreter B, Volker U, Petersmann A, Nauck M, Biffar R, et al. Genome-wide association study of chronic periodontitis in a general German population. J Clin Periodontol. 2013;40(11):977–85. doi:10.1111/jcpe.12154.

    Article  CAS  PubMed  Google Scholar 

  56. Deppe H, Mucke T, Wagenpfeil S, Kesting M, Karl J, Noe S, et al. Are selected Il-1 polymorphisms and selected subgingival microorganisms significantly associated to periodontitis in type 2 diabetes patients? A clinical study. BMC Oral Health. 2015;15(1):143. doi:10.1186/s12903-015-0132-5.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  57. Chen Z, Pereira MA, Seielstad M, Koh WP, Tai ES, Teo YY, et al. Joint effects of known type 2 diabetes susceptibility loci in genome-wide association study of Singapore Chinese: the Singapore Chinese Health Study. PLoS ONE. 2014;9(2):e87762. doi:10.1371/journal.pone.0087762.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Kondrashova A, Hyoty H. Role of viruses and other microbes in the pathogenesis of type 1 diabetes. Int Rev Immunol. 2014;33(4):284–95. doi:10.3109/08830185.2014.889130.

    Article  CAS  PubMed  Google Scholar 

  59. Petzold A, Solimena M, Knoch KP. Mechanisms of beta cell dysfunction associated with viral infection. Curr Diab Rep. 2015;15(10):654. doi:10.1007/s11892-015-0654-x.

    Article  CAS  Google Scholar 

  60. Wessel J, Chu AY, Willems SM, Wang S, Yaghootkar H, Brody JA, et al. Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility. Nat Commun. 2015;6:5897. doi:10.1038/ncomms6897.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Yu N, Barros SP, Zhang S, Moss KL, Phillips ST, Offenbacher S. Insulin response genes in different stages of periodontal disease. J Dent Res. 2015;94(9 Suppl):194S–200. doi:10.1177/0022034515584384.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Sung J, Lee K, Song YM, Lee M, Kim J. Genetic and baseline metabolic factors for incident diabetes and HbA(1c) at follow-up: the Healthy Twin Study. Diabetes Metab Res Rev. 2015;31(4):376–84. doi:10.1002/dmrr.2619. This unique twin study followed 869 initially diabetes free twins (mean age: 444 years) and 949 family members for a mean of 3.7 years during which about 5% of men and 4% of women developed diabetes. Whereas genetics explained 28% of the incident diabetes, other factors were influential as well, namely baseline fasting glucose levels, white blood cell counts, triglycerides, and waist circumference. The latter is in accord with other recent findings that point to distribution of adiposity (waist to hip ratio, for instance) being a more important risk factor than obesity measured by for instance the crude BMI. The relatively low importance of heritable risk factors was also found in the systematic review by Bao et al. [65].

    Article  CAS  PubMed  Google Scholar 

  63. Shungin D, Winkler TW, Croteau-Chonka DC, Ferreira T, Locke AE, Magi R, et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature. 2015;518(7538):187–96. doi:10.1038/nature14132.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Walford GA, Porneala BC, Dauriz M, Vassy JL, Cheng S, Rhee EP, et al. Metabolite traits and genetic risk provide complementary information for the prediction of future type 2 diabetes. Diabetes Care. 2014;37(9):2508–14. doi:10.2337/dc14-0560.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Bao W, Hu FB, Rong S, Rong Y, Bowers K, Schisterman EF, et al. Predicting risk of type 2 diabetes mellitus with genetic risk models on the basis of established genome-wide association markers: a systematic review. Am J Epidemiol. 2013;178(8):1197–207. doi:10.1093/aje/kwt123. The conclusion derived from 23 studies was that GWAS-identified genetic risk markers added little to traditional models of risk predication for incident T2D, regardless of the study characteristics (design, case numbers, race/ethnicity, number of variants, and mean age at T2D diagnosis).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Trombelli L, Franceschetti G, Farina R. Effect of professional mechanical plaque removal performed on a long-term, routine basis in the secondary prevention of periodontitis: a systematic review. J Clin Periodontol. 2015;42 Suppl 16:S221–36. doi:10.1111/jcpe.12339.

    Article  PubMed  Google Scholar 

  67. Raghavan S, Porneala B, McKeown N, Fox CS, Dupuis J, Meigs JB. Metabolic factors and genetic risk mediate familial type 2 diabetes risk in the Framingham Heart Study. Diabetologia. 2015;58(5):988–96. doi:10.1007/s00125-015-3498-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Dasgupta K, Ross N, Meltzer S, Da Costa D, Nakhla M, Habel Y, et al. Gestational diabetes mellitus in mothers as a diabetes predictor in fathers: a retrospective cohort analysis. Diabetes Care. 2015;38(9):e130–1. doi:10.2337/dc15-0855. This is the first study to explore any links between GDM with incident diabetes in their child’s father. Half of the 70,890 fathers had partners with GDM, and 33% more of them compared to men with non-GDM partners developed T2D during about 13 years. These results probably show the effect of their shared race/ethnicity, environment, socio-economic status, and lifestyle in general, which also casts doubt on the strength of the biologic basis for the observed effect of inherited susceptibility to T2D (See also Reference #69 by Leong et al.).

    Article  PubMed  Google Scholar 

  69. Leong A, Rahme E, Dasgupta K. Spousal diabetes as a diabetes risk factor: a systematic review and meta-analysis. BMC Med. 2014;12(1):1–12. doi:10.1186/1741-7015-12-12. A systematic review among reports encompassing 75,498 couples concluded that spousal diabetes increases risk for diabetes by 26% and spousal history of prediabetes or manifest diabetes leads to a doubling of the risk. The latter is comparable to the two-fold risk for incident T2D associated with history of diabetes in one parent. These findgins shows that the shared living circumstances probably are more important than the biologic inheritability (See also Ref. # 68 by Dasgupta et al.).

    Article  Google Scholar 

  70. Chernausek SD, Arslanian S, Caprio S, Copeland KC, El Ghormli L, Kelsey MM, et al. Relationship between parental diabetes and presentation of metabolic and glycemic function in youth with type 2 diabetes: baseline findings from the TODAY trial. Diabetes Care. 2016;39(1):110–7. doi:10.2337/dc15-1557.

    Article  PubMed  Google Scholar 

  71. Bajaj S, Prasad S, Gupta A, Singh VB. Oral manifestations in type-2 diabetes and related complications. Indian J Endocrinol Metab. 2012;16(5):777–9. doi:10.4103/2230-8210.100673.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Borgnakke WS, Anderson PF, Shannon C, Jivanescu A. Is there a relationship between oral health and diabetic neuropathy? Curr Diab Rep. 2015;15(11):93. doi:10.1007/s11892-015-0673-7. This invited review is the first of its kind. The greatest importance of this review—that applied librarian expert assisted systematic literature searches—is that it identifies a gap of a great magnitude in studies of links between periodontitis and neuropathy due to long-term poorly controlled diabetes. Only two cross-sectional studies reported on associations between periodontitis and neuropathy [71] and retinopathy [73], respectively. However, this paucity of reports does not in any way indicate there is a weak link between the diseases, only that they have not been explored and reported. The connection between periodontitis and neuropathic diabetes complications is of potentially great magnitude in the prevention and management of both diseases, so all healthcare professionals should be aware of such links.

    Article  PubMed  Google Scholar 

  73. Amiri AA, Maboudi A, Bahar A, Farokhfar A, Daneshvar F, Khoshgoeian HR, et al. Relationship between type 2 diabetic retinopathy and periodontal disease in Iranian adults. N Am J Med Sci. 2014;6(3):139–44. doi:10.4103/1947-2714.128476.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Kim C, Newton KM, Knopp RH. Gestational diabetes and the incidence of type 2 diabetes: a systematic review. Diabetes Care. 2002;25(10):1862–8.

    Article  PubMed  Google Scholar 

  75. Köhler M, Ziegler AG, Beyerlein A. Development of a simple tool to predict the risk of postpartum diabetes in women with gestational diabetes mellitus. Acta Diabetol. 2016;53(3):433–7. doi:10.1007/s00592-015-0814-0.

  76. Winhofer Y, Tura A, Thomas A, Prikoszovich T, Winzer C, Pacini G, et al. Hidden metabolic disturbances in women with normal glucose tolerance five years after gestational diabetes. Int J Endocrinol. 2015;2015(No Iss):#342938. doi:10.1155/2015/342938.

  77. Xiong X, Elkind-Hirsch KE, Xie Y, Delarosa R, Maney P, Pridjian G, et al. Periodontal disease as a potential risk factor for the development of diabetes in women with a prior history of gestational diabetes mellitus. J Public Health Dent. 2013;73(1):41–9. doi:10.1111/jphd.12004.

    Article  PubMed  Google Scholar 

  78. Boursi B, Mamtani R, Haynes K, Yang YX. The effect of past antibiotic exposure on diabetes risk. Eur J Endocrinol. 2015;172(6):639–48. doi:10.1530/EJE-14-1163.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Mikkelsen KH, Knop FK, Frost M, Hallas J, Pottegard A. Use of antibiotics and risk of type 2 diabetes: a population-based case–control study. J Clin Endocrinol Metab. 2015;100(10):3633–40. doi:10.1210/jc.2015-2696. Only recently has there been focus on the role of the human microbiome in health and disease and on the unintended effects of use of antibiotics. This study is important in that it examines all diabetes cases in a small country with good records of all disease and prescriptions, combining data over a period of 13 years from three databases linked by the unique Person Registration Number that everyone living in Denmark is allocated. The results showed a clear dose–response association between antibiotics use and diabetes, with the increased antibiotics use discernable up to 15 years before the diabetes diagnosis as well as afterwards.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Silosi I, Cojocaru M, Foia L, Boldeanu MV, Petrescu F, Surlin P, et al. Significance of circulating and crevicular matrix metalloproteinase-9 in rheumatoid arthritis-chronic periodontitis association. J Immunol Res. 2015;2015(No Iss):#218060. doi:10.1155/2015/218060.

  81. Kobayashi T, Yoshie H. Host responses in the link between periodontitis and rheumatoid arthritis. Curr Oral Health Rep. 2015;2015(2):1–8. doi:10.1007/s40496-014-0039-2.

    Article  CAS  Google Scholar 

  82. de Smit MJ, Westra J, Brouwer E, Janssen KM, Vissink A, van Winkelhoff AJ. Commentary: periodontitis and rheumatoid arthritis: what do we know? J Periodontol. 2015;86(9):1013–9. doi:10.1902/jop.2015.150088.

    Article  PubMed  Google Scholar 

  83. Yokoyama T, Kobayashi T, Ito S, Yamagata A, Ishida K, Okada M, et al. Comparative analysis of serum proteins in relation to rheumatoid arthritis and chronic periodontitis. J Periodontol. 2014;85(1):103–12. doi:10.1902/jop.2013.120741.

    Article  CAS  PubMed  Google Scholar 

  84. Kobayashi T, Yokoyama T, Ito S, Kobayashi D, Yamagata A, Okada M, et al. Periodontal and serum protein profiles in patients with rheumatoid arthritis treated with tumor necrosis factor inhibitor adalimumab. J Periodontol. 2014;85(11):1480–8. doi:10.1902/jop.2014.140194.

    Article  PubMed  Google Scholar 

  85. Javed F, Ahmed HB, Mikami T, Almas K, Romanos GE, Al-Hezaimi K. Cytokine profile in the gingival crevicular fluid of rheumatoid arthritis patients with chronic periodontitis. J Investig Clin Dent. 2014;5(1):1–8. doi:10.1111/jicd.12066.

    Article  PubMed  Google Scholar 

  86. Bingham CO, Moni M. Periodontal disease and rheumatoid arthritis: the evidence accumulates for complex pathobiologic interactions. Curr Opin Rheumatol. 2013;25(3):345–53. doi:10.1097/BOR.0b013e32835fb8ec.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Zenobia C, Hajishengallis G. Basic biology and role of interleukin-17 in immunity and inflammation. Periodontol 2000. 2015;69(1):142–59. doi:10.1111/prd.12083.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Wu Z, Nakanishi H. Lessons from microglia aging for the link between inflammatory bone disorders and Alzheimer’s disease. J Immunol Res. 2015;2015(No Iss):#471342. doi:10.1155/2015/471342.

  89. Boström EA, Lundberg P. The newly discovered cytokine Il-34 is expressed in gingival fibroblasts, shows enhanced expression by pro-inflammatory cytokines, and stimulates osteoclast differentiation. PLoS ONE. 2013;8(12):10.1371/journal.pone.0081665.

    Article  CAS  Google Scholar 

  90. Monsarrat P, Vergnes JN, Blaizot A, Constantin A, de Grado GF, Ramambazafy H, et al. Oral health status in outpatients with rheumatoid arthritis: the OSARA study. Oral Health Dent Manag. 2014;13(1):113–9. doi:10.4172/2247-2452.1000553.

    PubMed  Google Scholar 

  91. Payne JB, Golub LM, Thiele GM, Mikuls TR. The link between periodontitis and rheumatoid arthritis: a periodontist’s perspective. Curr Oral Health Rep. 2015;2:20–9. doi:10.1007/s40496-014-0040-9.

    Article  PubMed  Google Scholar 

  92. Borgnakke WS. Does treatment of periodontal disease influence systemic disease? Dent Clin N Am. 2015;59(4):885–917. doi:10.1016/j.cden.2015.06.007.

    Article  PubMed  Google Scholar 

  93. Borgnakke WS. Ch. 6. Hyperglycemia/diabetes mellitus and periodontal infection adversely affect each other. In: Genco RJ, Williams RC, editors. Periodontal disease and overall health: a clinician’s guide. 2nd ed. Yardley, PA: Professional Audience Communications; 2014. p. 99–122. Available: http://www.colgateprofessional.com/Professional/v1/en/us/locale-assets/docs/Periodontal-Disease-and-Overall-Health-A-Clinicians-Guide-2nd-Edition.pdf.

  94. Ionescu-Tirgoviste C, Gagniuc PA, Gubceac E, Mardare L, Popescu I, Dima S, et al. A 3D map of the islet routes throughout the healthy human pancreas. Sci Rep. 2015;5(No Iss):#14634. doi:10.1038/srep14634. For the first time is the organization of the islets in the human pancreas visualized in three dimensions; and it is demonstrated that there are 5,423 islets that are distributed almost evenly from the head to the tail of the pancreas, contrary to hitherto held beliefs, and they are connected by specific routes. Furthermore, the islets are found in 11 clusters consisting of small isltes surrounding large blood vessels with six clusters in the head, three in the neck, and two in the tail of the pancreas. Moreover, the authors also identified some local inflammatory processes in the fat tissue adjacent to the tail of the organ with lymphoid-like nodes and blood vessels. Finally, the authors created an index of sphericity to describe varying islet shapes.

  95. Akcali A, Bostanci N, Ozcaka O, Ozturk-Ceyhan B, Gumus P, Tervahartiala T, et al. Elevated matrix metalloproteinase-8 in saliva and serum in polycystic ovary syndrome and association with gingival inflammation. Innate Immun. 2015;21(6):619–25. doi:10.1177/1753425915572172.

    Article  CAS  PubMed  Google Scholar 

  96. Porwal S, Tewari S, Sharma RK, Singhal SR, Narula SC. Periodontal status and high-sensitivity C-reactive protein levels in polycystic ovary syndrome with and without medical treatment. J Periodontol. 2014;85(10):1380–9. doi:10.1902/jop.2014.130756.

    Article  PubMed  Google Scholar 

  97. Akcali A, Bostanci N, Özcaka O, Özturk-Ceyhan B, Gümüs P, Buduneli N, et al. Association between polycystic ovary syndrome, oral microbiota and systemic antibody responses. PLoS ONE. 2014;9(9):e108074. doi:10.1371/journal.pone.0108074.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  98. Özcaka O, Buduneli N, Ceyhan BO, Akcali A, Hannah V, Nile C, et al. Is interleukin-17 involved in the interaction between polycystic ovary syndrome and gingival inflammation? J Periodontol. 2013;84:1827–37. doi:10.1902/jop.2013.120483.

    Article  PubMed  CAS  Google Scholar 

  99. Luque-Ramirez M, Escobar-Morreale HF. Polycystic ovary syndrome as a paradigm for prehypertension, prediabetes, and preobesity. Curr Hypertens Rep. 2014;16(12):500. doi:10.1007/s11906-014-0500-6.

    Article  PubMed  Google Scholar 

  100. Ali AT. Polycystic ovary syndrome and metabolic syndrome. Ceska Gynekol. 2015;80(4):279–89.

    PubMed  Google Scholar 

  101. Glintborg D, Hass Rubin K, Nybo M, Abrahamsen B, Andersen M. Morbidity and medicine prescriptions in a nationwide Danish population of patients diagnosed with polycystic ovary syndrome. Eur J Endocrinol. 2015;172(5):627–38. doi:10.1530/eje-14-1108.

    Article  CAS  PubMed  Google Scholar 

  102. Guo R, Zheng Y, Yang J, Zheng N. Association of TNF-alpha, Il-6 and Il-1beta gene polymorphisms with polycystic ovary syndrome: a meta-analysis. BMC Genet. 2015;16:5. doi:10.1186/s12863-015-0165-4.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  103. Mayer SB, Evans WS, Nestler JE. Polycystic ovary syndrome and insulin: our understanding in the past, present and future. Womens Health (Lond Engl). 2015;11(2):137–49. doi:10.2217/whe.14.73.

    Article  CAS  Google Scholar 

  104. Naorungroj S, Slade GD, Beck JD, Mosley TH, Gottesman RF, Alonso A, et al. Cognitive decline and oral health in middle-aged adults in the ARIC study. J Dent Res. 2013;92(9):795–801. doi:10.1177/0022034513497960.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Syrjälä AM, Ylöstalo P, Ruoppi P, Komulainen K, Hartikainen S, Sulkava R, et al. Dementia and oral health among subjects aged 75 years or older. Gerodontology. 2012;29(1):36–42. doi:10.1111/j.1741-2358.2010.00396.x.

    Article  PubMed  Google Scholar 

  106. Foltyn P. Ageing, dementia and oral health. Aust Dent J. 2015;60 Suppl 1:86–94. doi:10.1111/adj.12287.

    Article  PubMed  Google Scholar 

  107. Narasimhan K, Govindasamy M, Gauthaman K, Kamal MA, Abuzenadeh AM, Al-Qahtani M, et al. Diabetes of the brain: computational approaches and interventional strategies. CNS Neurol Disord Drug Targets. 2014;13(3):408–17.

    Article  CAS  PubMed  Google Scholar 

  108. Accardi G, Virruso C, Balistreri CR, Emanuele F, Licastro F, Monastero R, et al. SHIP2: a “new” insulin pathway target for aging research. Rejuvenation Res. 2014;17(2):221–5. doi:10.1089/rej.2013.1541.

    Article  CAS  PubMed  Google Scholar 

  109. Desai GS, Zheng C, Geetha T, Mathews ST, White BD, Huggins KW, et al. The pancreas-brain axis: insight into disrupted mechanisms associating type 2 diabetes and Alzheimer’s disease. J Alzheimers Dis. 2014;42(2):347–56. doi:10.3233/JAD-140018.

    CAS  PubMed  Google Scholar 

  110. Michaud DS, Izard J, Rubin Z, Johansson I, Weiderpass E, Tjonneland A, et al. Lifestyle, dietary factors, and antibody levels to oral bacteria in cancer-free participants of a European cohort study. Cancer Causes Control. 2013;24(11):1901–9. doi:10.1007/s10552-013-0265-2.

    Article  PubMed  Google Scholar 

  111. Kim SJ, Jee SH, Nam JM, Cho WH, Kim JH, Park EC. Do early onset and pack-years of smoking increase risk of type II diabetes? BMC Public Health. 2014;14:178. doi:10.1186/1471-2458-14-178.

    Article  PubMed  PubMed Central  Google Scholar 

  112. Pan A, Wang Y, Talaei M, Hu FB, Wu T. Relation of active, passive, and quitting smoking with incident type 2 diabetes: a systematic review and meta-analysis. Lancet Diabetes Endocrinol. 2015;3(12):958–67. doi:10.1016/S2213-8587(15)00316-2.

    Article  PubMed  Google Scholar 

  113. Stein JH, Asthana A, Smith SS, Piper ME, Loh WY, Fiore MC, et al. Smoking cessation and the risk of diabetes mellitus and impaired fasting glucose: three-year outcomes after a quit attempt. PLoS ONE. 2014;9(6):e98278. doi:10.1371/journal.pone.0098278.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  114. Reynolds MA. Modifiable risk factors in periodontitis: at the intersection of aging and disease. Periodontol 2000. 2014;64(1):7–19. doi:10.1111/prd.12047.

    Article  PubMed  Google Scholar 

  115. Centers for Disease Control and Prevention (CDC) Framingham Heart Study: heart age predictor using BMI. Available: http://www.cdc.gov/vitalsigns/cardiovasculardisease/heartage.html. 2015.

  116. Melk A, Tegtbur U, Hilfiker-Kleiner D, Eberhard J, Saretzki G, Eulert C, et al. Improvement of biological age by physical activity. Int J Cardiol. 2014;176(3):1187–9. doi:10.1016/j.ijcard.2014.07.236.

    Article  PubMed  Google Scholar 

  117. Eke PI, Thornton-Evans GO, Wei L, Borgnakke WS, Dye BA. Accuracy of NHANES periodontal examination protocols. J Dent Res. 2010;89(11):1208–13. doi:10.1177/0022034510377793.

    Article  CAS  PubMed  Google Scholar 

  118. Kurgan S, Onder C, Altingoz SM, Bagis N, Uyanik M, Serdar MA, et al. High sensitivity detection of salivary 8-hydroxy deoxyguanosine levels in patients with chronic periodontitis. J Periodontal Res. 2015;50(6):766–74. doi:10.1111/jre.12263.

    Article  CAS  PubMed  Google Scholar 

  119. Khaw A, Liberali S, Logan R, Keefe D, Bartold PM. Influence of periodontitis on the experience of oral mucositis in cancer patients undergoing head and neck radiotherapy: a pilot study. Support Care Cancer. 2014;22:2119–25. doi:10.1007/s00520-014-2186-3.

    Article  PubMed  Google Scholar 

  120. Oeffinger KC, Sklar CA. Abdominal radiation and diabetes: one more piece in the puzzle. Lancet Oncol. 2012;13(10):961–2. doi:10.1016/s1470-2045(12)70340-6.

    Article  PubMed  PubMed Central  Google Scholar 

  121. de Vathaire F, El-Fayech C, Ben Ayed FF, Haddy N, Guibout C, Winter D, et al. Radiation dose to the pancreas and risk of diabetes mellitus in childhood cancer survivors: a retrospective cohort study. Lancet Oncol. 2012;13(10):1002–10. doi:10.1016/s1470-2045(12)70323-6.

    Article  PubMed  Google Scholar 

  122. de Pablo P, Dietrich T, McAlindon TE. Association of periodontal disease and tooth loss with rheumatoid arthritis in the US population. J Rheumatol. 2008;35(1):70–6.

    PubMed  Google Scholar 

  123. National Academies of Sciences & Engineering & Medicine. A framework for educating health professionals to address the social determinants of health. Washington, DC: The National Academies Press; 2016. 170pp. doi:10.17226/21923. Available: http://www.nap.edu/21923.

Download references

Author information

Authors and Affiliations

  1. Department of Periodontics and Oral Medicine, University of Michigan School of Dentistry, 1011 North University Avenue Rm #G049, Ann Arbor, MI, 48109-1078, USA

    Wenche S. Borgnakke

Authors
  1. Wenche S. Borgnakke
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wenche S. Borgnakke.

Ethics declarations

Conflict of Interest

Wenche Borgnakke declares that she has no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by the authors

Additional information

This article is part of the Topical Collection on Systemic Diseases

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Borgnakke, W.S. “Non-modifiable” Risk Factors for Periodontitis and Diabetes. Curr Oral Health Rep 3, 270–281 (2016). https://doi.org/10.1007/s40496-016-0098-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40496-016-0098-7

Keywords

Search

Navigation