Nov/Dec 2014
Volume 35, Issue 10

Prevalence of Periodontal Disease by Recorded Indices Among Low Income Discount Dental School Patients

Pouran Famili, DMD, MDS, MPH, PhD; and Mandana M. Shaya


Objective: The purpose of this study was to evaluate the prevalence of periodontal disease among the patient population at the University of Pittsburgh who receive the Low Income Discount (LID) financial obligation reduction based on family income in relation to federal poverty guidelines. Study Design: This was a retrospective study examining the Electronic Health Record at the University of Pittsburgh School of Dental Medicine (axiUm, Exan Group) from August 2008 to April 2013 (N = 7936). Records of the complete periodontal examination, income, age, gender, race, and other variables were collected and analyzed. Results: Logistic regressions were performed, controlling for patients’ age, ethnicity, smoking status, BMI, and diabetes. The odds of having periodontal disease for patients receiving the low income discount (LID) was higher (1.055), but the difference was not statistically significant (P = 0.35). Significance: Patients receiving the low income discount did not have a higher prevalence of periodontal disease. Factors other than income appear to be more important to predict greater prevalence of periodontal disease, but this insight requires further investigation.

The prevalence of periodontal disease increases with age and is more severe among African Americans, Hispanics, and men. Borrell et al attempted to correlate socio-economy with periodontal disease, reporting that periodontal diseases are more severe and frequent in low-income groups.1-4 The report included a 2012 comparison between National Health and Nutrition Examination Survey (NHANES) III 1988-1994 and NHANES 1999-2004.5 Analysis from the 2009-2010 NHANES cycle, the first national probability sample to use a full-mouth periodontal examination protocol,6 firmly concludes that periodontitis showed highest in men, Mexican Americans, adults with less than a high school education, adults with financial resources < 100% of federal poverty levels, and current smokers.7 It has been established that periodontal disease is the world’s leading cause of tooth loss, and poverty is a significant global social determinant for poor oral health.8 Yet, at least one systematic review of the effect of socio-economy on periodontal disease9 concludes that socioeconomics appears to bear less importance than smoking behavior.


The NHANES III data1,4,5 clearly associate race, ethnicity, education, and neighborhood characteristics with destructive periodontal disease. When assessing the effects of socioeconomics on oral health, minority communities are often associated with lower income levels and poor oral health outcomes. Individuals with less than a high-school education who live in poor neighborhoods are more likely to have destructive periodontal disease than well-educated individuals who live in wealthy neighborhoods. Borrell and colleagues’ 2006 NHANES analysis found that adult African Americans (41%) showed the highest prevalence of periodontal disease and the most loss of periodontal tissue followed by Hispanic Americans (36%). White non-Hispanics (18%) show the least disease and tissue loss. This pattern repeats for all of the periodontal disease indicators.10 That heuristic analysis was displaced somewhat by the 2009-2010 data, which showed that Mexican Americans now appear to be more affected than non-Hispanic Blacks.6,7 The Dental Atherosclerosis Risk in Communities study concluded that individual poverty and lack of education were linked to severe periodontal disease.11 Poverty and residence in a disadvantaged neighborhood are associated with higher odds of severe periodontitis even among white people, although the ethnicity is usually considered above economic disadvantage.12 In one 2009 study, disparities in oral health status among rural North Carolina senior African Americans, white, and American Indian adults skewed closer to traditional ethnic stereotypes than socioeconomics.13 In a global analysis scrutinizing income inequality and periodontal disease in rich economies, Sabbah et al14 concluded that levels of income inequality were significantly associated with increased periodontal disease than absolute income. In essence, income disadvantage relative to the general population among acknowledged first-world neighborhoods was a more significant predictor of periodontal disease than actual income.

Methods and Design

This is a retrospective study examining the prevalence of periodontal disease among low-income individuals. Data (N = 7936) were pulled from the electronic health record at the University of Pittsburgh School of Dental Medicine (axiUm, Exan Group, www.axiumdental.com) from its beginning (August 1, 2008) up to April 1, 2013 (University of Pittsburgh Institutional Review Board 1213040221 Exempt approved 04-11-2013). Based on family income in relation to federal poverty level guidelines, the University of Pittsburgh offers a 10% discount on the cost of any treatment services, flagging the patient record as low income discount. The 2013 Guidelines mark $23,550 for a family of four and $11,490 for an individual as the income level establishing poverty.15

Using the full-mouth examination protocol, periodontal probing and attachment loss were measured on six sites of each tooth. Probing depth was measured from the free gingival margin to the base of the sulcus with the use of a calibrated probe (0.5-mm-diameter Michigan-O probe, Hu-Friedy Mfg. Co., LLC, www.hu-friedy.com). Recession was measured, clinical attachment was calculated, and data on gingival bleeding was collected. Previous research by members of this investigative team has defined periodontitis as existing in the presence of at least one site with probing depth ≥ 4 mm and at least one site with clinical attachment loss ≥ 3 mm.16 In the statistical analysis, both probing depth and clinical attachment loss were examined as continuous variables, consistent with established disparity prevalence and severity reporting. Age, gender, race and ethnicity, and income level are variables chosen for comparison to documented analyses of the NHANES data.1-5 The Pittsburgh axiUm database records the date of birth, from which chronological value was calculated, gender as male/female, and race/ethnicity as black, white, or Asian without additional subtlety when the variable is recorded at all. All household income in this analysis can be construed as either falling below current federal poverty guidelines or not.


Electronic health records for 7,936 subjects were extracted from the database and reviewed. 34.19% of people with low income had periodontal disease and 35.01% of patients that were not considered low income had periodontal disease. Although more than 30% of people had periodontal disease, the difference of income was not significant (P = 0.35). Age was a significant predictor of periodontal disease. Ethnicity was significant for predicting an increase in periodontal disease as well (P ≤ 0.0001) (Table 1). As generally accepted in the literature, smoking was a significant risk factor in the development of periodontal disease. Smokers in this research had an increased risk of developing periodontal disease as well (P ≤ 0.0001). Findings related to body weight as a predisposing risk factor for periodontal disease, measured in computations of traditional body mass index (BMI), were in line with an emerging trend in the periodontal literature that body mass in excess of normal ranges in the computed overweight or obese categories can be linked to an increased risk for developing periodontal disease. In this research, BMI was a significant factor related to periodontal disease (P = 0.0206) (Table 2). This is only a relationship, not a cause, and this cannot predict periodontal disease.

Logistic regressions were performed to acknowledge the research question whether people with less income have more periodontal disease. Controlling for patients’ age, ethnicity, smoking status, BMI, and diabetes, the odds of having periodontal disease versus not having periodontal disease for patients receiving the low income financial obligation reduction was higher (OR 1.055 with 95% CI [0.942, 1.180]). However, the difference is not statistically significant, so there is not enough evidence by means of this analysis to support the hypothesis that people with less income have more periodontal disease.


Most literature indicates people with low income have a higher prevalence of periodontal disease. In this study, we found people with low income had periodontal disease but the difference was not significant. Although the sample size is large enough to accept this conclusion, most people that come to University of Pittsburgh have low incomes. Patients of the University of Pittsburgh School of Dental Medicine come from the city of Pittsburgh, surrounding suburban and metropolitan areas as far north as Erie, Pennsylvania, throughout southwestern Pennsylvania and areas of West Virginia and Ohio. The aggregate population for the region is mixed Rust Belt Urban and rural Appalachian. The authors did see more periodontal disease among individuals greater than 50 years of age in both groups disregard their income. The reason the prevalence of periodontal disease was not high in older patients (greater than 75 years of age) is due to the difficulty for this age group to come to the dental school by themselves. As data shows, there are fewer patients in this group. A possible reason why the authors were unable to detect any significant difference related to income is that average real income most likely varies little among dental school patients and generally skews closer to low income even among those who do not explicitly qualify for the discount. Had the authors been able to stratify the electronic health record data by zip code, identifying neighborhood as a specific variable, greater subtlety might have been likely. Prospective study with different populating may give a different conclusion.


According to this study, unlike age, ethnicity, smoking habits, and BMI, income does not play a statistically significant role as a predictor of periodontal disease (P = 0.35). Additional studies with a larger data pool would provide a more diverse population, not only in income, but also age, ethnicity, smoking status, and BMI.


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2. Borrell LN, Taylor GW, Borgnakke WS, et al. Factors influencing the effect of race on established periodontitis prevalence. J Public Health Dent. 2003;63(1):20-29.

3. Borrell LN, Papapanou PN. Analytical epidemiology of periodontitis. J Clin Periodontol. 2005;32(suppl 6):132-158.

4. Borrell LN, Burt BA, Taylor GW. Prevalence and trends in periodontitis in the USA: the [corrected] NHANES, 1988 to 2000. J Dent Res. 2005;84(10):924-930.

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11. Borrell LN, Beck JD, Heiss G. Socioeconomic disadvantage and periodontal disease: the Dental Atherosclerosis Risk in Communities study. Am J Public Health. 2006;96(2):332-339.

12. Borrell LN, Taylor GW, Borgnakke WS, et al. Perception of general and oral health in White and African American adults: assessing the effect of neighborhood socioeconomic conditions. Community Dentist Oral Epidemiol. 2004;32(5):363-373.

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14. Sabbah W, Sheiham A, Bernabé E. Income inequality and periodontal diseases in rich countries: an ecological cross-sectional study. Int Dent J. 2010;60(5):370-374.

15. Families USA. 2013 Federal Poverty Guidelines. http://www.familiesusa.org/resources/tools-for-advocates/guides/federal-poverty-guidelines.html. Accessed April 15, 2013.

16. Weyant R, Pearlstein ME, Churak P, et al. The association between osteopenia and periodontal attachment loss in older women. J Periodontol. 1999;70(9):982-991.

About the Authors

Pouran Famili, DMD, MDS, MPH, PhD
Professor and Chair
Director of Postgraduate Education and the Residency
Department of Periodontics and Preventive Dentistry
University of Pittsburgh School of Dental Medicine
Pittsburgh, Pennsylvania

Mandana M. Shaya
Student (Class of 2015)
University of Pittsburgh School of Dental Medicine
Pittsburgh, Pennsylvania

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