Periodontitis and Systemic Diseases

The expert authors of the following book chapters have taken into account the above criteria for critically appraising the existing evidence on the associations or causal relationships between periodontitis and systemic diseases. This book therefore provides comprehensive, contemporary and well- considered insights into the clinical evidence and biological plausibility of each condition. This is underpinned by the body of scientific literature published to date, which has been critically discussed throughout the book. The reader will be provided with an understanding of how periodontitis impacts on the health of other organ systems and vice versa, but also of the limitations of existing studies and how these can be overcome in the future.

References

1.Kassebaum NJ, Smith AGC, Bernabé E, et al. Global, regional, and national prevalence, incidence, and disability-adjusted life years for oral conditions for 195 countries, 1990–2015: A systematic analysis for the global burden of diseases, injuries, and risk factors. J Dent Res 2017;96:380–387.

2.Kassebaum NJ, Bernabé E, Dahiya M, Bhandari B, Murray CJL, Marcenes W. Global burden of severe periodontitis in 1990–2010: a systematic review and meta-regression. J Dent Res 2014;93:1045–1053.

3.Listl S, Galloway J, Mossey PA, Marcenes W. Global economic impact of dental diseases. J Dent Res 2015;94: 1355–1361.

4.Tonetti MS, Jepsen S, Jin L, Otomo-Corgel J. Impact of the global burden of periodontal diseases on health, nutrition and wellbeing of mankind: A call for global action. J Clin Periodontol 2017;44:456–462.

5.Genco RJ, Borgnakke WS. Risk factors for periodontal disease. Periodontology 2000 2013;62:59–94.

6.Li X, Kolltveit KM, Tronstad L, Olsen I. Systemic diseases caused by oral infection. Clin Microbiol Rev 2000;13:547–558.

7.Caton JG, Armitage G, Berglundh T, et al. A new classification scheme for periodontal and peri-implant diseases and conditions – Introduction and key changes from the 1999 classification. J Clin Periodontol 2018;45(Suppl 20):S1–S8.

8.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;83:1449–1454.

9.Network EtQaTOhRE. Reporting guidelines for main study types. Oxford: Centre for Statistics in Medicine (CSM), NDORMS, University of Oxford, 2019.

10.FAIRsharing Oe-RC, University of Oxford. Minimum Information for Biological and Biomedical Investigations. Oxford: University of Oxford, 2019.

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Chapter 1

Periodontitis, obesity and diabetes mellitus

Bruno S. Herrera and Filippo Graziani

1.1 Introduction

In the last two decades, researchers have looked more deeply into the association of periodontitis and common major systemic chronic pathologies such as atherosclerosis 1, diabetes 2, obesity 3, and preterm labour 4with adverse pregnancy outcomes 5. The rationale of the periodontal-systemic link likely involves two important mechanisms: systemic inflammation and bacteraemia. One of the most important systemic diseases in this field is diabetes mellitus (DM). DM is a group of metabolic diseases characterised by hyperglycaemia due to decrease in insulin secretion, insulin response or both. The chronic hyperglycaemia of diabetes is associated with long-term damage, dysfunction, and failure of various organs, especially the eyes, kidneys, nerves, heart and blood vessels 6. The vast majority of cases of diabetes fall into two broad aetiopathogenetic categories: type 1 (T1DM) and 2 (T2DM). T1DM is the absolute deficiency of insulin secretion due to autoimmune beta-cell destruction in the pancreas. T2DM develops when there is an abnormally increased resistance to the action of insulin and the body cannot produce enough insulin to overcome the resistance 6 , 7.

1.1.1 Obesity

Overweight and obesity involve abnormal or excessive fat accumulation that may impair health and are considered major risk factors for a number of chronic diseases, including diabetes, cardiovascular diseases and also periodontitis 8. Childhood obesity results in the same conditions, with premature onset, or with greater likelihood of developing these diseases as adults. Thus, the economic and psychosocial costs of obesity alone, as well as when coupled with these comorbidities are striking 9. According to the World Health Organization (WHO) 8, in 2016, more than 1.9 billion adults were overweight and, of these, over 650 million were obese. Worldwide obesity has nearly tripled since 1975 and most of the world’s population live in countries where overweight and obesity kills more people than underweight. This epidemic is far from its resolution, since 41 million children under the age of 5 and over 340 million children and adolescents aged 5 to 19 were overweight or obese in 2016 8.

Body mass index (BMI, calculated as weight in kg/height in metres 2) provides the most useful population-level measure of overweight and obesity. However, it should be considered a rough guide because it may not correspond to the same degree of fatness in different individuals. For adults, the WHO defines overweight as a BMI greater than or equal to 25; and obesity a BMI greater than or equal to 30 8. Another way to assess this information is to use Z-scores (also known as standard deviation scores). It is obtained by dividing the median weight of the reference person or population by the standard deviation height or age of the reference population. Z-scores are sex-independent, thus permitting the evaluation of children’s growth status by combining sex and age groups ( Table 1-1). There are several factors that increase obesity risk, such as parental diet and/or obesity, a sedentary lifestyle, famine exposure, smoking, and alcohol binge drinking and regular high consumption, especially in women 9 , 13. In addition, to date, over 60 relatively common genetic markers have been implicated in elevated susceptibility to obesity 9.

Table 1-1 Common classifications of body weight in adults and children 9

MI = body mass index; CDC = Centers for Disease Control and Prevention; SD = standard deviation of the optimum weight-for-height; WH = weight-for-height; WHO = World Health Organization; Z = Z-score.