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DRJDent Res JDental Research JournalDental Research Journal
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This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
Background:
Obesity and periodontitis are two commonly occurring disorders that affect a considerable amount of the world's population. Several studies have mentioned that there may be a link between the two. The purpose of this systematic review was to determine whether there was a difference in response to nonsurgical periodontal therapies (NSPTs) between obese and nonobese individuals.
Materials and Methods:
An online search was assembled with a combination of Medical Subject Headings terms and free-text words of the literature published up to December 2020, to identify interventional studies limited to an adult human population. Titles, abstracts, and finally full texts were scrutinized for possible inclusion by two independent investigators. Reduction in periodontal pocket depth was the primary parameter used to assess the outcome of NSPT.
Results:
The primary search yielded 639 significant titles and abstracts. After filtering, data extraction, and quality assessment, 34 full-text studies were selected. All studies matching inclusion criteria, suggest a positive association between obesity and periodontal disease.
Conclusion:
Although a possible correlation exists between periodontitis and obesity, as with other oral-systemic disease implications, some controversy exists. While some studies have reported a distinct correlation between periodontitis and obesity, other papers have suggested only moderate or no association between the two conditions at all. These results advise of a difference between response to NSPT amid obese and nonobese individuals. However, with few quality studies and variable reported findings, there is limited evidence of any significant difference in clinical practice. However, it can be a positive warning that obesity is a risk factor toward the outcome of periodontal disease treatment.
Overweightperiodontitisscaling and root planingIntroduction
Overweight and obesity are defined as abnormal or excessive fat accumulation that may impair health and as a health-care provider we must inform patients about oral health and specific periodontal health concerns.
1,
2The prevalence of obesity is increasing worldwide and the number of obese individuals has more than doubled since 1980.
3In 2014, more than 1.9 billion adults were overweight. Of these, over 600 million were obese. For adults, WHO (World Health Organization) calculates BMI by dividing the person's weight in kilograms by the square of his height in meters (kg/m
2). Based on this calculation, BMI greater than or equal to 25 is categorized as overweight and a BMI greater than or equal to 30
2,
3,
4is categorized as obesity.
Adipose tissue has been thoroughly studied in the recent years, and contrary to the assumption of it solely being a fat storage medium, it has been identified as a tissue responsible for metabolism and energy conversion.
5This endocrine tissue is also associated with significant activity related to chemical substance secretion and inflammatory responses, much like an endocrine organ. Studies have also identified other organs besides adipose tissue which act as storage media of fat, such as the liver, and this could have important implications in measuring total body fat and composition, as these are means of determining weight imbalances and obesity.
6By realizing the fact that obesity and weight imbalances stem from mechanisms which render energy intake and energy expenditure imbalances, many world health agencies have regarded obesity as a chronic disease.
7
Obesity has several negative implications on a person's systemic condition including hypertension, type II diabetes, coronary heart disease, stroke, osteoarthritis, and its presence significantly lowers a person's life expectancy.
8Several studies have shown that it is also linked to reduced periodontal health.
9The exact mechanism by which obesity predisposes to periodontitis is not fully understood; however, obese individuals have higher levels of circulating tumor necrosis factor-α (TNF-α) and interleukin (IL)-6, secreted by the adipose tissue, compared to nonobese individuals, and these have been implicated in the pathogenesis of periodontal disease.
10,
11,
12
Nonsurgical periodontal therapy (NSPT) is the first step in the clinical management of chronic periodontitis.
7,
8,
9It involves the mechanical removal of bacterial biofilm and deposits with scaling and root planing (SRP), creating a local environment favorable to better periodontal health. The efficacy of NSPT in the management of periodontitis is established, and clinical trials have shown a reduction of inflammation, pocket depth reduction, and clinical attachment gains following therapy. However, it is not clear if obesity affects the outcome of nonsurgical periodontal therapy.
10,
11,
12,
13
The purpose of this systematic review was to determine whether there was a difference in response to NSPT between obese and nonobese individuals.
Materials and Methods
The literature search was structured according to the Population, Interventions, Comparisons, and Outcomes format
Table 1. The population was composed of health subjects (>18 years old) obese and nonobese. The intervention was nonsurgical periodontal therapy. The comparator/control was nonobese subjects with nonsurgical periodontal therapy. The outcome is the response to NSPT between obese and nonobese individuals.{Table 1}
A search was conducted in the Medline, Embase, and Scopus databases using the keywords periodontal disease/periodontitis, overweight/obesity/obese, and treatment/outcome of therapy. Results in English language only up to December 31, 2020, were included. Results from all databases were combined and duplicates were removed. Studies were then subsequently excluded based on title, abstract, and finally full-text review for a final inclusion of 8 studies
Figure 1.
Search strategy studies.
Figure 1
Inclusion criteria
Interventional studies assessing the effects of periodontal therapy on obese individuals and/or comparing the effects of periodontal therapy on obese and nonobese subjects
Minimum age 18 years
Obesity/overweight assessment (e.g., body mass index, waist/hip ratio, and waist circumference)
Uncontrolled or poorly controlled systemic diseases
Observational studies, case–control, cross-sectional studies, longitudinal retrospective studies, animal studies, and in vitro studies
Letters to the editor, reviews, and conference abstracts.
Analysis and forest plots were created with Open Meta (analyst). A random effects model was employed with 95% confidence intervals. For baseline analyses, group means were summarized by subtracting the BMI+ (overweight and obese) mean from BMI− (normal) mean. For the analysis of change between baseline and 1
stfollow-up, change data were computed by subtracting the follow-up mean from the baseline mean so that higher scores indicate more improvement, such as greater reduction in pocket depth and clinical attachment loss (CAL). To compare groups on levels of improvement, the mean summary effect was then computed by subtracting the BMI+ group score from the BMI− group scores so that higher scores indicate greater treatment effects in the control group
Figure 2and
Figure 3.
Forrest plot for estimating the mean of each group and evaluation time – Probing Depth BMI: Body mass index; CI: Confidence interval.
Figure 2
Mean and 95% confidence interval, estimated by meta-analysis using the restricted maximum likelihood – Probing Depth method. BMI: Body mass index; CI: Confidence interval.
Figure 3
After a systematic review,
10,
11,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
278 articles, published between 2012 and 2020, were selected for the meta-analysis.
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24The other 9 had insufficient data for inclusion. To estimate the mean of probing depth and clinical attainment loss (CAL), random models were used using the restricted maximum likelihood method.
To identify heterogeneity between studies, the Q test was used, and to quantify heterogeneity, the I
2statistic was used. This statistic estimates the proportion of heterogeneity observed in the studies, which can vary from 0% to 100%, the higher the value, the greater the difference between the selected studies.
The presence of outliers was evaluated through externally standardized residuals. Outlier studies are not necessarily influential, that is, they significantly modify the parameter estimate. To detect influential studies, the leave-one-out technique was used. None of the studies presented itself as influential.
It was not possible to perform a bias analysis; for this analysis, at least 10 articles are required.
The significance level adopted was 5%.
Results
The selected articles present different patient follow-up times, all eight articles present an evaluation after the baseline, four articles present a second evaluation, and only two articles present a third evaluation. As there were only two articles with the third evaluation, this result was not considered in this report.
The forest plot
Figure 2and
Figure 4,
Figure 5is a graph that allows the visualization of the estimated measures and their confidence intervals. Each study is plotted on the graph and its representation has two elements, a box that represents the estimate for each study and a horizontal line, which represents the confidence interval for that estimate. Small horizontal lines indicate better accuracies of the study results.
Forrest plot for estimating the mean of each group and evaluation time – Clinical Attachment Loss. BMI: Body mass index; CI: Confidence interval.
Figure 4
Mean and 95% confidence interval, estimated by meta-analysis using the restricted maximum likelihood – Clinical Attachment Loss method. BMI: Body mass index; CI: Confidence interval.
Figure 5
Figure 2is a summary of the graphs in
Figure 1, and it presents the means and 95% confidence intervals for each time and group, a form of descriptive comparison between times and groups.
Table 1presents the result of the meta-regression that compares the times and groups for PD. This table presents two models, one considering only the baseline and 1
stevaluation (8 articles) and another considering the baseline, 1
stevaluation, and 2
ndevaluation (4 articles). In both models, the interaction between group and time was tested and was not significant. In the first model
Table 2, it is noted that there is no significant difference between the groups (P = 0.0849) and that the 1
stevaluation is significantly lower than the baseline (P = 0.0003). In the second model, it is noted that there is no significant difference between the groups (P = 0.0653) and that the 1
stevaluation (P = 0.0001) and 2
ndevaluation (P < 0.0001) are significantly lower than the baseline
Table 3. Considering the significance level of 5%, it is concluded that the groups are not different, and both reduce the mean PD over time.{Table 2}{Table 3}
Table 2presents the result of the meta-regression that compares the times and groups for CAL. This table presents two models, one considering only the baseline and 1
stevaluation (8 articles) and another considering the baseline, 1
stevaluation, and 2
ndevaluation (4 articles). In both models, the interaction between group and time was tested and was not significant. In the first model, it is noted that there is no significant difference between the groups (P = 0.4808) and that the 1
stevaluation is significantly lower than the baseline (P = 0.0321). In the second model, it is noted that there is no significant difference between the groups (P = 0.3671) and that the 1
stevaluation (P = 0.0205) is significantly lower than the baseline; no significant difference was observed between baseline and 2
ndevaluation (P = 0.3229). Considering the significance level of 5%, it is concluded that the groups are not different, and both reduce the mean CAL from the baseline to the 1
stevaluation.
28,
29
Discussion
Despite decades of research and treatment, periodontitis remains one of the most common inflammatory conditions in humans. Often associated with systemic diseases such as cardiovascular disease and diabetes mellitus, there is mounting evidence that obesity may play a role in the immune response related to periodontal disease.
3,
9,
10,
11,
12,
13,
14Considering that obesity affected 39.8% of adults in the U. S. in 2015–2016 (CDC NCHS data brief, No. 288, October 2017), the global health implications of periodontitis in obese individuals could be significant.
4,
7
The relationship between periodontitis and obesity has been reported by several studies focusing on periodontal pathogens dissemination from epithelial through the circulation and consequently the immune system.
11
Obesity as a chronic disease has been reported by recent studies to be associated with changes in many inflammatory mediators such as IL-6, TNF-α, monocyte chemoattractant protein-1 (MCP-1), and IL receptor agonists. Obesity has also been shown to be linked to changes in some adipose-related proteins such as leptin, adiponectin, resistin, and visfatin, suggesting systemic and immunological mechanisms by which obesity may be associated with other inflammatory or immunological-related disorders.
26,
30,
31,
32,
33
Furthermore, it has been shown by experimental studies done on obese rats that periodontal disease markers, such as alveolar bone loss and periodontal inflammatory mediators linked to periodontitis, are significantly higher in these rats.
31These results point toward a possible correlation between periodontitis and obesity.
Although a possible correlation exists between periodontitis and obesity, as with other oral-systemic disease implications, some controversy exists. While some studies have reported a distinct correlation between periodontitis and obesity, other papers have suggested only moderate or no association between the two conditions at all.
Conclusion
These results advise of a difference between response to NSPT in obese and nonobese individuals. However, with few quality studies and variable reported findings, there is limited evidence of any significant difference in clinical practice. However, it can serve as a positive warning that obesity is a risk factor toward the outcome of periodontal disease treatment.
Financial support and sponsorship
Nil.
Conflicts of interest
The authors of this manuscript declare that they have no conflicts of interest, real or perceived, financial or non-financial in this article.
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