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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Periodontol. Author manuscript; available in PMC 2011 December 1.
Published in final edited form as:
PMCID: PMC3187554

Association Between Chronic Periodontal Disease and Obesity: A Systematic Review and Meta-Analysis



Obesity is increasing in prevalence and is a major contributor to worldwide morbidity. One consequence of obesity might be an increased risk for periodontal disease, although periodontal inflammation might, in turn, exacerbate the metabolic syndrome, of which obesity is one component. This review aims to systematically compile the evidence of an obesity–periodontal disease relationship from epidemiologic studies and to derive a quantitative summary of the association between these disease states.


Systematic searches of the MEDLINE, SCOPUS, BIOSIS, LILACS, Cochrane Library, and Brazilian Bibliography of Dentistry databases were conducted with the results and characteristics of relevant studies abstracted to standardized forms. A meta-analysis was performed to obtain a summary measure of association.


The electronic search identified 554 unique citations, and 70 studies met a priori inclusion criteria, representing 57 independent populations. Nearly all studies matching inclusion criteria were cross-sectional in design with the results of 41 studies suggesting a positive association. The fixed-effects summary odds ratio was 1.35 (Shore-corrected 95% confidence interval: 1.23 to 1.47), with some evidence of a stronger association found among younger adults, women, and non-smokers. Additional summary estimates suggested a greater mean clinical attachment loss among obese individuals, a higher mean body mass index (BMI) among periodontal patients, and a trend of increasing odds of prevalent periodontal disease with increasing BMI. Although these results are highly unlikely to be chance findings, unmeasured confounding had a credible but unknown influence on these estimates.


This positive association was consistent and coherent with a biologically plausible role for obesity in the development of periodontal disease. However, with few quality longitudinal studies, there is an inability to distinguish the temporal ordering of events, thus limiting the evidence that obesity is a risk factor for periodontal disease or that periodontitis might increase the risk of weight gain. In clinical practice, a higher prevalence of periodontal disease should be expected among obese adults.

Keywords: Body weight, obesity, overnutrition, periodontal diseases, review

The worldwide prevalence of obesity is a considerable source of concern given its potential impact on morbidity, mortality, and the cost of health care.1 The World Health Organization (WHO)2 has recognized obesity as a predisposing factor to major chronic diseases ranging from cardiovascular disease to cancer. Successful efforts to reduce and prevent obesity will have substantial public-health benefits.

Chronic periodontal disease is an inflammatory condition characterized by a shift in the microbial ecology of subgingival plaque biofilms and the progressive host-mediated destruction of tooth-supporting structures.35 There has been considerable interest in drawing connections between periodontal inflammation and other chronic conditions, notably heart disease,6,7 diabetes,8 and preterm low birth weight delivery.9 Although observed associations suggested a causal role for periodontitis in certain systemic diseases, a consensus opinion demands further evidence.10,11

Obesity might represent a systemic condition capable of influencing the onset and progression of periodontal disease. First noted using a ligature-induced periodontitis model in the rat,12 the evidence of an obesity–periodontitis link in humans was recently addressed in several reviews.1320 Most of these publications1319 described a relationship between periodontal disease and metabolic syndrome (MetS) of which obesity, insulin resistance, dyslipidemia, and hypertension represent components,21 as extensively discussed by Bullon et al.15 In brief, all MetS components derive from a proinflammatory state characterized by insulin resistance and oxidative stress, with the latter being a common link with periodontitis in a bidirectional relationship.15 Products of oxidative damage22 and advanced glycation end products23 might promote periodontal disease. Meanwhile, periodontitis could, itself, be a source of oxidative stress,24,25 perhaps through the alteration of levels of circulating adipocytokines such as leptin,26 which, in turn, accelerate the onset of insulin resistance and MetS.

Although these reviews provided insight into the possible mechanisms of an obesity–periodontitis relationship, none of the reviews were systematic or quantitative, and none of them performed a quality assessment of included studies. There has been a tendency to highlight a relatively small pool of studies specific to obesity and periodontitis rather than to explore the broader base of anthropometric data collected during epidemiologic studies. This systematic review aims to compile the evidence for an obesity–periodontal disease association and, through a meta-analysis, to summarize individual study results into a quantitative estimate of that relationship. We hypothesized that there was a difference in the prevalence of obesity in the general adult population across groups of individuals with or without current signs of periodontal disease. As secondary aims, we sought to characterize mean differences in obesity parameters across groups with or without periodontal disease, mean differences in periodontal disease parameters across obese and non-obese groups, and any linear changes in periodontal prevalence with an increasing body mass index (BMI).


Literature Search

Electronic searches of the MED-LINE, SCOPUS, BIOSIS, LILACS, Cochrane Library, and Brazilian Bibliography of Dentistry databases were conducted in July 2010 for publications that investigated periodontal disease and obesity. In MED-LINE, the Medical Subject Heading term periodontal disease and the Boolean connector AND were linked to the terms overweight, overnutrition, BMI, waist-hip ratio, waist circumference, body weight, and body weight changes, each joined by the connector OR with vocabulary exploding allowed to automatically query indexed subheadings under the main terms. Analogous search strategies were applied to other databases, expanding query components to include similar terms such as periodontal and periodontitis to account for less-controlled indexing vocabularies. Terms were in English, but no other language or date restrictions were placed. Two reviewers (BWC and SJW) appraised retrieved titles and abstracts. Exclusion criteria included: non-human studies, no measure of periodontal disease or obesity, case series, studies of children, reviews, abstracts, or lack of peer review. Full-text copies of the remaining potentially relevant citations were obtained, and the following inclusion criteria were applied: English or Spanish language (or translation), suitable reference group, and an obesity–periodontitis association reported or calculable from tables. Publications were further excluded if periodontal status was only assessed by tooth loss, oral hygiene, gingival appearance, or use of a dental prosthesis. Additional publications were obtained by searching the citation listings of included studies and review articles.1320 Articles meeting the inclusion criteria were combined with the articles obtained from the electronic search. Each reviewer was then unmasked to the other’s progress and a consensus was reached regarding any citations selected by only one reviewer.

Quality of Evidence

The quality of the information abstracted for the meta-analysis was assessed using a scale designed specifically for this review by the authors. Each reviewer scored studies independently using 24 criteria across six domains as follows: research questions (14 points), study design (nine points), measurement (eight points), analysis (14 points), presentation (four points), and conflict of interest (four points). A total of 16 points across the design and analysis domains were dedicated to appropriate adjustment for confounding factors. Quality-of-evidence scores were not intended to rank studies based on intrinsic quality alone but, rather, according to how well study results estimated the association between obesity and periodontal disease in the general population. There was no statistically significant difference in quality scores by reviewer (mean difference: 0.8 points; Wilcoxon matched-pairs signed rank test; P = 0.68); therefore, studies were ranked by the average score. The empirical distribution of quality scores suggested three strata, which roughly partitioned studies in tertiles. Twelve of the 13 high-quality studies and eight of the 10 low-quality studies maintained their respective designation regardless of whether average scores or the scores of either reviewer were used for classification. Two very low quality studies of the 10 were not included, and therefore did not contribute to the results of the review.


The prevalence odds ratio was the measure abstracted for the primary meta-analysis because nearly all studies were cross-sectional. When individual studies reported more than one association measure, adjusted measures were preferred over crude measures, and stratified results were pooled when possible to estimate a population-level effect. When multiple publications drew results from an identical set of participants (such as from large national surveys), only data from the study with the most inclusive study population were abstracted.

Periodontal disease status was based on the clinical parameters selected by the individual studies. If multiple measures of periodontal disease appeared in a single study, clinical attachment loss (AL) was preferred to the probing depth, which was preferred to radiographs. Presented with multiple definitions, BMI ≥30 kg/m2, concordant with guidelines of the WHO,1 was the preferred measure of obesity. The waist-to-hip ratio was considered in the case of one study that did not report BMI. Given alternate cut points, the highest reported BMI category defined obesity, and the second highest category defined overweight. Given multiple categories of periodontal disease, the most severe disease designation was preferred unless few subjects (<20) were present in that uppermost stratum.

Overall and subgroup Mantel-Haenszel fixed-effects27 summary odds ratios (sORs) were obtained using statistical software. Ninety-five percent confidence intervals (CIs) were calculated by the method of Shore et al.28 (Shore-corrected 95% CI) whenever this adjustment resulted in more conservative (wider) CIs. An overall DerSimonian-Laird random-effects29 sOR was calculated for comparison. The sensitivity of the sOR to the inclusion or exclusion of individual studies was assessed.As a secondary meta-analysis, from studies that presented a difference in mean BMI across groups with and without periodontal disease or for those presenting a difference in mean clinical AL across obese and non-obese groups, a fixed-effects summary mean difference (sMD) was calculated using the general variance inverse-weighting method.30 If not reported, SDs were calculated or estimated to obtain sMD. A Mantel-Haenszel fixed-effects linear sOR was calculated from studies that reported a change in the odds of periodontal disease per unit increase in BMI.

For the primary meta-analysis, a funnel plot served as a visual means for assessing any disproportionate representation of study results according to strength and precision.31 A Begg-adjusted rank correlation test32 formally tested for any trend of increasing association strength with reducing precision. It was suggested that such an effect could represent the preferential publication of statistically significant positive results,33 which could bias the sOR. The rank-based data-augmentation technique of Duval and Tweedie,34 commonly called the trim-and-fill method, was used to recalculate the sOR under the hypothetical scenario that association measures of similarly low precision but opposite direction had also been present. Studies were divided into subgroups based on features of study designs or characteristics of study populations to explore whether the sOR was sensitive to such variables.


The electronic search generated 864 hits, which represented 554 unique citations. A total of 142 publications were obtained as full-text copies, and 74 of these publications were later excluded on the basis of a priori criteria. Eight additional publications were identified as potentially relevant among the citation listings of included articles and review articles, and six of these articles were later excluded based on the same criteria. In total, 70 publications that represented 57 unique study populations were included for systematic review.35104 A summary flowchart is presented in accordance with a proposal for reporting meta-analysis of observational studies in epidemiology105 (Fig. 1).

Figure 1
Quality in reporting of observational studies in an epidemiology flowchart.

Articles35,36,3941,45,49,54,56,57,59,6164,67,68,72,74,77, 82,84,90,92,9597,101 listed in Table 1 represent the study results that contributed to the calculation of the sOR. Tables 2 through through44 lists those results3739,4143,4648, 5052,57,60,6366,6972,76,7880,8486,90,94,98,99,101,102 that did not define periodontal disease and obesity as binary conditions but could contribute to an sMD (Tables 2 and and3)3) or linear sOR (Table 4). Table 5 lists four studies53,73,98,103 that were unique in design and therefore their results could not be pooled. Two studies75,91 were excluded from the review because of low scores according to the quality-of-evidence criteria. Results from 12 studies39,41,52,57,63,64,72,84,90, 98,101,102 appear more than once across Tables 1 through through5,5, as do three pairs of separately published studies in which each pair was based on a single study population.36,37,58,59,72,73 Only independent results contributed to any summary measure. An additional 11 studies,44,55,58,81,83,8789,93,100,104 which otherwise matched the inclusion criteria but derived results from subsets of the populations already described in Tables 1 through through5,5, are not listed. No experimental studies were found, and just two studies73,98 were prospective. Publications were written in English, and no study published before the year 1999 met the inclusion criteria. Calculating a measure of association between periodontal disease and obesity or MetS was a principle study aim of 24 publications.35,36,43,45,4749,54,57,59,63,64,6668,72,73,82,8486, 90,101,103 Forty-one independent results reported a positive association,35,36,3943,4549,51,54,5658,60,62,63, 6670,72,74,76,78,80,82,8486,90,92,94,95,97,99,100 22 of which were statistically significant (P <0.05).36,39,41,43, 48,49,54,5658,63,66,72,74,80,82,85,86,90,94,97,99

Table 1
Descriptive Characteristics and Individual Results of Studies Meeting Criteria for Systematic Review: Results Contributing to the sOR
Table 2
Descriptive Characteristics and Individual Results of Studies Meeting Criteria for Systematic Review That Compared Mean Obesity Parameters Across Periodontal Disease Cases and Controls
Table 3
Descriptive Characteristics and Individual Results of Studies Meeting Criteria for Systematic Review That Compared Mean Periodontal Disease Parameters Across Obese and Non-Obese Groups
Table 4
Descriptive Characteristics and Individual Results of Studies Meeting Criteria for Systematic Review that Presented a Relative Increase in the Odds of Periodontal Disease With Each Unit Increase in BMI
Table 5
Descriptive Characteristics and Individual Results of Studies Meeting Criteria for Systematic Review That Had Other Study Designs

For the association between prevalent periodontal disease and obesity, the overall fixed-effects sOR and Shore-corrected 95% CI was 1.35 (1.23 to 1.47) with a χ2 statistic for heterogeneity (Q) of 81.7 with 27 degrees of freedom (P <0.005) (Fig. 2). The DerSimonian-Laird random effects sOR was 1.48 (95% CI: 1.32 to 1.66). One study97 accounted for 39% of the weight assigned in calculating the sOR; however, the exclusion of this result raised the overall estimate only slightly to 1.40 (Shore-corrected 95% CI: 1.25 to 1.57). The exclusion of no other individual result altered the sOR by >0.02 units in either direction.

Figure 2
Meta-analysis forest plot. The forest plot is a graphical depiction of the individual results that contributed to meta-analysis. Sizes of the boxes are proportional to the weight assigned to each result in calculating the fixed-effects sOR, where weight ...

Combining those results37,41,42,46,5052,57,60,65,66, 69,70,72,76,7880,84,85,90,94,98,99,101,102 in Table 2 generated an sMD of 0.80 BMI units (95% CI: 0.70 to 0.95) comparing individuals with periodontal disease to those without periodontal disease (Q = 135.4; P <0.005). The studies43,47,63,64,86 that compared clinical AL across obese and non-obese groups (Table 3) yielded an sMD of 0.58 mm (95% CI: 0.40 to 0.74 mm) with greater clinical AL seen among obese individuals (Q = 5.1; P = 0.40). Eight studies3739,48, 52,71,90,102 expressed a linear change in the odds of periodontitis with each 1-unit increase in BMI (Table 4), resulting in a summary linear association ratio of 1.02 (Shore-corrected 95% CI: 0.99 to 1.04) and a Q statistic of 12.7 (P= 0.08).

Figure 3 displays the precision of the results from Table 1 as a function of the strength of association. The three largest estimates of a positive obesity–periodontitis association were also the three least precise estimates abstracted.41,74,101 The Begg test suggested a trend of increasingly positive association measures with decreasing precision (continuity corrected P = 0.08). The trim-and-fill procedure estimated the sOR if analogous low-precision measures of an inverse association had theoretically been present. This procedure added seven hypothetical study results but only slightly lowered the sOR to 1.32 (Shore-corrected 95% CI: 1.20 to 1.44).

Figure 3
Precision versus strength funnel plot. The funnel plot depicts the study precision as a function of the strength of association. The outer borders of the funnel represent the required strength of association to obtain statistical significance at any given ...

The results shown in Table 1 were divided into groups based on study characteristics, and fixed-effects sORs were recalculated by group (Fig. 4). If a particular study presented stratified results, for example among men and women, the appropriate stratum-specific result was abstracted for subgroup analyses. Among the 15 studies35,36,45,54,57,63,64,67,68,72,74,77, 84,90,96 that presented both crude and adjusted estimates, the pooled adjusted measure was lower. Similarly, a less-positive association was seen with overweight than with obesity among 14 studies36,39,45,49,57,59,63,64,68,74,92,95, 96,101 that provided both estimates. There appeared to be a stronger association between periodontal disease and obesity when results were only based on younger individuals, women, and non-smokers, as well as when a study specifically aimed to estimate an association between periodontal disease and obesity or MetS as a primary objective. No obvious pattern emerged by the quality-of-evidence levels. Summary estimates were similar whether BMI or waist circumference was used to define obesity based on the results of eight studies drawing from seven independent populations.36,49,59,63,84,89,95,97

Figure 4
Subgroup analysis of studies included in meta-analysis. The study results contributing to the meta-analysis were divided into groups based on study characteristics (left), and fixed-effects sORs were calculated accordingly.


A positive association was repeatedly demonstrated between prevalent periodontal disease and obesity across multiple studies from around the world. The meta-analysis of the systematically identified results from 57 independent study populations suggested an approximate one-third increase in the prevalence odds of obesity among subjects with periodontal disease, a greater mean clinical AL among obese individuals, a higher BMI among subjects with periodontal disease, and a slight but not statistically significant linear increase in the odds of periodontal disease with increasing BMI. In total, these findings are highly unlikely due to chance and persist over studies using a multitude of measurement strategies for assessing these two health conditions.

The summary measure of association (sOR) reported here was less strong in magnitude than those reported between periodontal disease and adverse pregnancy outcomes106 or cardiovascular events.107 However, based on a subset of included studies, there appears to be stronger obesity–periodontitis association in women, non-smokers, and younger individuals than in the general adult population. Although smoking is a well-studied predisposing factor for periodontitis,108,109 smoking and BMI share a complex relationship,110 which can appear to be inverse in certain populations.111,112 For older individuals, tooth loss and impaired masticatory function might be a path through which advanced periodontal disease could impact energy balance and nutrition.113 Studies that linked overweight or obesity to tooth loss reported positive,114116 negative,117 and equivocal results118,119 and are complicated by an association between tooth loss and underweight status.113

Though widespread, the use of meta-analysis has been controversial,120122 and any result must be interpreted cautiously. Confounding and heterogeneity more often influence observational studies than clinical trials, which is a limitation in pooling results. Although oral diseases are sometimes presented as if separate entities from systemic conditions, shared risk factors, such as behavior and genetic predisposition, frequently precede the manifestation of disease. Incomplete accounting of confounding factors has made drawing unequivocal conclusions about periodontal-systemic disease connections an elusive goal.123125 Neither the sMD reflecting pooled differences in clinical AL across obese and non-obese groups nor the sMD based on pooled differences in BMI across periodontal disease patients and healthy controls was adjusted to account for confounding and, thus, likely overstates any causal difference across groups. However, the sOR based solely on adjusted results did not differ greatly from that comprised of all studies and maintained a statistically significant positive association (Fig. 4). However, for studies that presented both adjusted and crude results, the adjusted sOR was lower and remained potentially biased by unmeasured factors such as physical inactivity,37,126 alcohol use,127 and stress.128

The preferential publication of statistically significant positive results, or those deemed important, might theoretically bias the results of any meta-analysis.129,130 Indeed, we observed a handful of results in the literature with low precision but strongly positive findings (Fig. 3). However, attempts to account for small study effects, either by exclusion or trim-and-fill techniques, did not greatly alter the sOR estimate.

The design of nearly all included studies was cross-sectional, making it impossible to determine the temporal relationship between diseased states. Whether one condition stands as a risk factor for another, or whether a measured covariable might represent a confounder or mediator on a causal pathway, could not be distinguished. Recent work73 showed that individuals with periodontal pockets at baseline were more likely to develop components of MetS, including obesity, 4 years later. Two other prospective studies131,132 appeared during the literature search but were excluded because of a lack of peer review. Hopefully, these efforts preclude the arrival of more high-quality prospective studies that are necessary to validate the proposed causal links between obesity and periodontitis.

To our knowledge, the present analysis is the first on this topic that was systematic and quantitative in approach. We estimated the magnitude of the periodontal disease–obesity association with weighting by study precision and explored differences across subgroups of similar studies. A systematic search allowed for the inclusion of studies for which the association between obesity and periodontal disease was not a primary focus but from which an effect estimate could be abstracted and greatly widened the evidence base for this review.

This review did not cover investigations into the putative causal mechanisms that underlie the observed association between periodontal disease and obesity. However, Bullon et al.15 proposed a bidirectional relationship between MetS and periodontitis mediated by circulating cytokines and oxidative stress. Alternately, Hujoel et al.133 argued that a failure to account for correlations among health-promoting behaviors could create strong but spurious associations between oral factors and systemic conditions, such as seen between obesity and a lack of flossing. Although the cross-sectional association between obesity and periodontal disease is consistent with a causal framework, deciphering the directionality of this relationship cannot be accomplished based on prevalence studies alone.


Despite the prospects of unmeasured confounding, a positive association between periodontal disease and obesity was suggested across diverse populations. Elucidating any physiologic mechanism behind this relationship will require well-designed prospective studies. For the clinician, continuing to stress the importance of maintaining a healthy weight, as recommended by the National Institutes of Health,134 stands to benefit all patients. The prevalence of periodontal disease is likely to be higher among obese patients, although there is no current evidence to recommend differences in treatment planning.


The authors thank Drs.AllanSmith, Department of Environmental Health Sciences, and Craig Steinmaus, Division of Epidemiology, School of Public Health, University of California Berkeley, Berkeley, CA, for comments on the manuscript and for recommendations regarding statistical methods. Dr. Chaffee is supported by a dental scientist training grant (DE007306) from the National Institutes of Health, Bethesda, Maryland.


Stata IC version 10.1, StataCorp, College Station, TX.

The authors report no conflicts of interest related to this review.


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