Abstract
Background
The association between poor oral health and diabetes is well documented. Therefore, preventive oral health is strongly indicated for individuals with diabetes. The purposes of this study were 1) to determine if there were a difference in preventive dental care utilization among older adults with diabetes from 2002 and 2011, and 2) to compare preventive dental care utilization of older adults with and without diabetes from 2002 and 2011.
Methods
The data were from the Medicare Current Beneficiary Survey. The sample included older, fee-for-service Medicare beneficiaries (ages 65 years and above). The key outcome was self-reported preventive dental care. In 2002, there were 8,725 participants; in 2011, there were 7,425 participants. Chi square and logistic regressions were conducted.
Results
In 2002, 28.8 % of participants with diabetes had preventive dental care. In 2011, this percentage increased to 36.0%. Similar results were seen among individuals without diabetes (42.9% in 2002 and 45.5% in 2011). The increase in preventive dental care was statistically significant for individuals with and without diabetes. The participants with diabetes, as compared with participants without diabetes, remained statistically less likely to have preventive dental care in adjusted logistic regression analysis with and without considering the interaction between observation year and diabetes (adjusted odds ratios= 0.73, and 0.86, respectively).
Conclusion
While the increase in preventive dental care is welcoming, older adults with diabetes continue to have significant preventive dental care need.
Practical Implication
Additional efforts are needed to encourage individuals with diabetes to obtain preventive dental care.
Keywords: Diabetes, Dental preventive care, Medicare utilization, older adults
Introduction
There is a well-documented association of periodontitis (the destruction of tissue supporting teeth) and diabetes which is a growing public health concern.1–7 Individuals with diabetes are at high risk for periodontal disease.8 Several researchers have indicated that improved oral health leads to improved diabetes control.9–11
On the tooth level, periodontal destruction is primarily due to the interaction between inflammation (the body’s response) and the microbial biofilm on the tooth/supporting tissue, as well as the biological activity of the microorganisms themselves in the biofilm. The anaerobic Gram-negative bacteria such as the red complex bacteria (for example, Porphyromonas gingivalis, Tannerella forsythia, and Treponema denticola) the orange complex bacteria (for example, Prevotella intermedia) and Aggregatibacter actinomycetemcomitans are of particular concern.12
The chronic induction of inflammatory cells (lymphocytes, macrophages, and polymorphonuclear leukocytes) and cytokines is the proposed mechanism for periodontitis influencing diabetes, while similar factors associated with diabetes influence periodontitis. Individuals with diabetes have a higher prevalence of periodontitis.13–17 As a result of the proposed feed-back loop, individuals with diabetes are encouraged to have routine preventive dental care to manage/prevent periodontal disease and its inflammatory consequences. Although one meta-analysis of periodontal maintenance (periodontal treatment and follow-up care) and glycemic control showed short-term, positive, significant results on hemoglobin A1-C,18 another meta-analysis indicated that the evidence was insufficient to support a positive association.19 The Committee on Research, Science, and Therapy of the American Academy of Periodontology (2000) in a position paper on diabetes and periodontal disease suggested that periodontal treatment has the potential to alter glycemic control. Although the relationship of periodontal treatment and glycemic control is not resolved, the relationship of diabetes and periodontitis has been established; therefore, routine preventive dental care visits are especially needed by individuals with diabetes for prevention of periodontitis, early detection of periodontitis, and treatment of periodontitis.20 This need has been widely published over the previous decade, and the oral-systemic link was addressed nationally in a Report of the Surgeon General in 2000,21 therefore an increase in preventive dental care for all individuals, particularly of older individuals with diabetes is anticipated.
Researchers using 2009 Medical Expenditure Panel Survey data indicated 30.7% of adults ages 65 years and above sought preventive dental care.22 Researchers using Behavioral Risk Factor Surveillance System data found a steady rise in preventive dental care utilization by older adults from 58.9% in 1995 to 63.9% in 2008,23 and researchers using the 2010 Behavioral Risk Surveillance System data, researchers indicated that 57.2%-81.7% of adults had any type of dental visit in the past year.24
The purposes of this study were 1) to determine if there was a difference in preventive dental care utilization among older adults with diabetes from 2002 (when the diabetes-periodontal disease association was not widely known) and 2011 (when the association had been widely published in peer-reviewed journals), and 2) to compare preventive dental care utilization of older adults with and without diabetes from 2002 and 2011.
Methods
Data source
The data for this study were from the 2002 and 2011 Medicare Current Beneficiary Survey (MCBS), which is a nationally representative, continuous survey of the Medicare population (both institutionalized and non-institutionalized) in the United States sponsored by the Centers for Medicare and Medicaid Services.25 The survey is designed with a multistage, stratified, random sampling design for multiple purposes and is conducted by the researchers at the Office of Enterprise Data and Analytics with a contract with the National Organization for Research at the University of Chicago.25 Representation for the samples is based on primary sampling units (a geographic unit that is a cluster representative of counties or cities), and person level.25 The researchers provide weights for the representation to be reflective of the nation’s Medicare population. Patients are surveyed 13 times over 4 years.25 There are approximately 16,000 participants, with approximately 4,000 new participants and 4,000 completed participants each year.25 The questionnaire includes demographic, socioeconomic, dwelling, income, health status, physical status and similar questions.25 The survey is linked to Medicare and Medicaid claims data. The collected files are assigned as Access to Care files or Cost and Use files (both having linked claims data).25 Details of the survey are available at http://www.cms.hhs.gov/mcbs.
West Virginia University Institutional Review Board acknowledges this study (protocol 1601969410).
Key dependent/outcome variable
The outcome variable, preventive dental care utilization was based on whether or not participants reported having an oral examination or dental prophylaxis during the calendar year (yes, no). It is a conservative measure of unmet dental needs, as for some individuals one oral examination or dental prophylaxis would not be sufficient since the American Dental Association (ADA) recommends at least one dental visit per year. It also has the strengths and weaknesses of self-reported data. We note that this is a conservative measure as some individuals may need more than one oral examination or dental prophylaxis during a calendar year.
Key independent variables
The key independent variables of interest were type 2 diabetes mellitus status and the year of observation (2002 versus 2011). Type 2 diabetes mellitus was identified from self-reports to interviewers who queried the respondents as to whether they had ever been diagnosed with diabetes using a standardized questionnaire. In data collection and use, diabetes identification from self-report is routinely used,26–29 however the severity and nature of the disease are not available from the data set.
Other variables
Other independent variables considered in the analyses as risk factors for unmet preventive dental care were determined using the Andersen model for healthcare utilization in which predisposing characteristics, enabling resources, personal health practices, and perceived health status were considered.30 These included the demographic variables of sex (male, female), race/ethnicity (White, African American, Latino, other), age in years (65–69, 70–74, 75–79, 80 and above), and metropolitan status (metropolitan, non-metropolitan). The socioeconomic variables included education (less than high school, high school, some college, college degree and above), and poverty (less than 200% of the federal poverty level, 200% and above). Chronic diseases and conditions which were considered were: heart disease (yes, no); hypertension (yes, no); and mental conditions (yes, no). Perceived health status was a self-reported response of excellent, very good, good, fair, or poor. Activities of daily living difficulties (none, 1–2, 3 or more) were used to identify functional status. Smoking (yes, no) was considered as a lifestyle choice/personal health care practice. Participants were asked specifically if they had dental insurance coverage (yes, no) as Medicare does not cover dentists’ fees.
Statistical Analysis
The data were analyzed with Rao Scott Chi Square analyses and logistic regression analyses using SAS 9.3® (Cary, NC) software. MCBS has a complex survey design; therefore, data weights and strata based on the primary sampling unit (PSU) clusters (which were provided by the researchers conducting the MCBS to allow for generalizations to the national population of Medicare beneficiaries) were used in the analyses of the data. Weights refer to the number of records it represents in a population. Without proper adjustments to weights at PSU and strata level, the variance estimates are more likely to have downward bias, indicating importance of a variable, when in fact, the variable may not be important. See http-s://www.cms.gov/Research-Statistics-Data-and-Systems/Research/MCBS/downloads/2008_Appendix_A.pdf for more information of sample survey design details.
Results
Sample Description
A detailed sample description is presented in Table 1. The eligible sample in 2002 included 8,725 participants; and the eligible sample in 2011 included 7,425 participants. There were more females than males in both years (57.7%, 56.2%, respectively). In 2002 and 2011, the race/ethnicity distributions and age distributions in the samples were similar. Based upon chi-square tests, there were significantly fewer people in 2002 than in 2011 with dental insurance (5.2%, 12.2%, respectively) and diabetes (19.5%, 25.3%, respectively). Additional categories with significant differences in the sample are detailed in Table 1.
Table 1.
Overall Sample Description Medicare Current Beneficiary Survey, 2002 and 2011
| 2002 | 2011 | ||||
|---|---|---|---|---|---|
| Number | Weighted column Percent |
Number | Weighted column percent |
Significance | |
| ALL | 8,725 | 100.0 | 7,425 | 100.0 | |
| Diabetes Mellitus | *** | ||||
| Yes | 1,695 | 19.5 | 1,859 | 25.3 | |
| No | 7,030 | 80.5 | 5,566 | 74.7 | |
| Sex | |||||
| Women | 5,035 | 57.7 | 4,159 | 56.2 | |
| Men | 3,690 | 42.3 | 3,266 | 43.8 | |
| Race/Ethnicity | |||||
| White | 7,036 | 81.1 | 5,849 | 79.3 | |
| African American | 739 | 8.0 | 620 | 7.7 | |
| Latino | 617 | 7.1 | 620 | 8.3 | |
| Other | 323 | 3.8 | 318 | 4.7 | |
| Age in Years | *** | ||||
| 65–69 years | 1,561 | 20.1 | 1,410 | 23.6 | |
| 70–74 years | 2,149 | 28.2 | 1,651 | 26.6 | |
| 75–79 years | 1,886 | 23.9 | 1,526 | 20.5 | |
| 80 and above | 3,129 | 27.9 | 2,838 | 29.3 | |
| Metropolitan Status | |||||
| Metropolitan | 6,333 | 76.8 | 5,528 | 77.2 | |
| Non-Metropolitan | 2,389 | 23.2 | 1,897 | 22.8 | |
| Education | *** | ||||
| Less than High School | 2,833 | 30.8 | 1,768 | 22.1 | |
| High School | 3,097 | 36.1 | 2,588 | 34.5 | |
| Some College | 1,202 | 14.1 | 1,145 | 16.0 | |
| College | 1,560 | 19.0 | 1,903 | 27.4 | |
| Poverty | *** | ||||
| Less than 200% FPL | 4,594 | 50.8 | 3,544 | 45.2 | |
| GE 200% FPL | 4,131 | 49.2 | 3,881 | 54.8 | |
| Dental Insurance | *** | ||||
| Yes | 420 | 5.2 | 811 | 12.2 | |
| No | 8,305 | 94.8 | 6,614 | 87.8 |
Note: This study is based on older Medicare Beneficiaries, age 65 years and above, continuously enrolled in fee-for-service Medicare and alive during the observation year (that is, the participant did not drop out of Medicare coverage).
Asterisks represent significant differences in characteristics between years 2002 and 2011 based on chi-square tests.
FPL: Federal Poverty Line; GE: Greater than or Equal
p < 0.001;
0.001 ≤ p < 0.01;
0.01 ≤ p < 0.05
Ten-year differences in preventive dental care utilization
The details of the percent changes in differences in preventive dental care utilization between 2002 and 2011 are presented in Table 2. Overall, 40.1% of participants had preventive dental care utilization in 2002 and this increased to 43.2% in 2011 (p<.001). Among individuals with diabetes, there was also a significant increase in preventive dental care utilization from 28.8% in 2002 to 36.0% in 2011, an increase of 7.2 percentage points. Among individuals without diabetes, there was an increase of 2.6 percentage points, from 42.9% in 2002 to 45.5% in 2011. Comparisons of preventive dental care utilization by observation year revealed that for many subgroups, there were not significant increases in preventive dental care utilization comparing 2002 and 2011.
Table 2.
Recipients of Preventive Dental Care and Percentage Change1 Medicare Current Beneficiary Survey, 2002 and 2011
| 2002 | 2011 | %Change | ||||
|---|---|---|---|---|---|---|
| Number | Weighted percent |
Number | Weighted percent |
2011% minus 2002% |
Significance | |
| ALL | 3392 | 40.1 | 3074 | 43.1 | 3.0 | ** |
| Diabetes Mellitus | ||||||
| Yes | 477 | 28.8 | 643 | 36.0 | 7.2 | *** |
| No | 2915 | 42.9 | 2431 | 45.4 | 2.6 | * |
| Sex | ||||||
| Women | 1956 | 40.2 | 1766 | 44.3 | 4.1 | *** |
| Men | 1436 | 40.0 | 1308 | 41.5 | 1.5 | |
| Race/Ethnicity | ||||||
| White | 3064 | 44.7 | 2687 | 47.5 | 2.8 | * |
| African American | 87 | 13.0 | 114 | 20.9 | 7.9 | *** |
| Latino | 138 | 23.1 | 173 | 29.1 | 6.0 | * |
| Other | 96 | 31.4 | 89 | 29.0 | −2.4 | |
| Age in Years | ||||||
| 65–69 years | 639 | 42.2 | 583 | 44.1 | 1.9 | |
| 70–74 years | 883 | 41.7 | 752 | 46.6 | 4.9 | ** |
| 75–79 years | 780 | 42.0 | 645 | 43.1 | 1.1 | |
| 80 and older | 1090 | 35.4 | 1094 | 39.0 | 3.6 | ** |
| Metropolitan Status | ||||||
| Metropolitan | 2639 | 42.7 | 2460 | 45.9 | 3.2 | ** |
| Non-Metropolitan | 753 | 31.7 | 614 | 33.6 | 1.9 | |
| Education | ||||||
| Less than High School | 518 | 18.6 | 280 | 16.3 | −2.3 | * |
| High School | 1240 | 40.3 | 963 | 38.2 | −2.1 | |
| Some College | 609 | 51.3 | 574 | 51.1 | −0.2 | |
| College | 1019 | 66.7 | 1250 | 66.3 | −0.4 | |
| Poverty | ||||||
| Less than 200% FPL | 1122 | 24.7 | 854 | 24.7 | 0.0 | |
| GE 200% FPL | 2270 | 56.0 | 2220 | 58.3 | 2.3 | |
| Dental Insurance | ||||||
| Yes | 382 | 76.8 | 616 | 78.1 | −0.7 | |
| No | 3070 | 38.1 | 2458 | 38.5 | 0.4 |
Note: This study is based on older Medicare Beneficiaries, aged 65 years and above, continuously enrolled in fee-for-service Medicare and alive during the observation year (that is, the participant did not drop out of Medicare coverage).
Asterisks represent significant differences in preventive dental care by observation year for each characteristic based on chi-square tests.
Percentage Change is the difference of the weighted percent of year 2011 minus the weighted percent of year 2002;
FPL: Federal Poverty Line; GE: Greater than or Equal.
p < 0.001;
0.001 ≤ p < 0.01;
0.01 ≤ p < 0.05
Logistic regression on Preventive Dental Care Utilization
The results of logistic regression analysis on preventive dental care utilization are presented in Table 3. With regard to diabetes and preventive dental care utilization, after adjustments for: observation year, dental insurance, sex, race/ethnicity, age, marital status, education, poverty levels, health status, smoking and obesity, participants with diabetes were significantly less likely to have preventive dental care than participants who did not have diabetes (adjusted odds ratio = 0.86). Interaction analyses between observation year and diabetes supported the significant associations.
Table 3.
Adjusted Odds Ratios (AOR) Standard Errors (SE) and and 95% Confidence Intervals (CI) from Logistic Regressions of Selected Characteristics on “Preventive Dental Care Utilization” among older Medicare Beneficiaries Medicare Current Beneficiary Survey, 2002 and 2011
| Significance | Adjusted Odds Ratio |
95% CI | |
|---|---|---|---|
| Observation Year | |||
| 2011 | reference | ||
| 2002 | * | 0.89 | [0.82, 0.97] |
| Diabetes Mellitus | |||
| Yes | ** | 0.86 | [0.78, 0.94] |
| No | reference | ||
| Dental Insurance | |||
| Yes | reference | ||
| No | *** | 0.31 | [0.26, 0.38] |
Note: This study is based on older Medicare Beneficiaries, age 65 years and above, continuously enrolled in fee-for-service Medicare and alive during the observation year (that is, the participant did not drop out of Medicare coverage).
Asterisks represent significant differences in “preventive dental care” between the comparison and the reference group based on the logistic regressions.
The adjusted model controlled for sex, race/ethnicity, age, marital status, education, poverty status, presence of dental insurance, health status (presence of heart disease, hypertension, or mental health conditions in the past year, perceived general health status and functional status), smoking, and obesity.
p < 0.001;
0.001 ≤ p < 0.01;
0.01 ≤ p < 0.05
Discussion
The foci of this study were 1) to determine if there was a difference in preventive dental care utilization among older adults with diabetes from 2002 and 2011, and 2) to compare preventive dental care utilization of older adults with and without diabetes from 2002 and 2011. For both individuals with diabetes and individuals without diabetes, preventive dental care utilization increased. For individuals with diabetes, there was an increase of 7.2 percentage points in preventive dental care utilization. For individuals without diabetes, there was an increase of 2.6 percentage points in preventive dental care utilization. However, participants with diabetes, as compared with participants without diabetes, remained statistically more less to have preventive dental care utilization in adjusted logistic regression analysis with and without considering the interaction between observation year and diabetes (adjusted odds ratios= 0.73, and 0.86, respectively).
There are few other studies in the literature with which to compare the differences of preventive dental care utilization among older adults with diabetes considering past and current preventive care utilization. In a 2009 Medical Expenditure Panel Survey study there were 30.7% of older adults who sought preventive dental care,22 a value below our 2011 value of 36.0%; and in a Behavioral Risk Factor Surveillance System study, preventive dental care in 2008 was 63.9%,23 a value above our 2011 value. Similar results to ours are from a study of adults with diabetes where researchers found that adults with diabetes had lower odds of visiting a dentist for any reason.31 Our study adds to the literature information specific to preventive dental care utilization and diabetes occurring in 2002 compared with that occurring in 2011.
Although not the focus of this study, we found that the proportion of individuals with dental insurance coverage increased between 2002 and 2011, however the percentage of preventive dental care utilization for this group remained unchanged. Individuals without dental insurance coverage were less likely to have preventive dental care as compared to individuals with dental insurance coverage (adjusted odds ratio = 0.31). Policies to provide dental insurance coverage may be beneficial. Experts have recommended a focus of including oral health care into all health policies.32 Preventive dental care is a significant need for older adults with diabetes. Unmet preventive dental care needs can lead to increased dental and potentially increased medical costs.
Our study has several strengths. We used a large, national database. The analyses were conducted controlling for multiple risk factors. This was possible due to the large number of participants. The analyses were completed with data weights and strata considered in the analyses.
Study limitations include the potential for misclassification bias due to the use of questionnaires for the self-report of several key variables. Diabetes self-report was not confirmed with a medical diagnosis of diabetes. Likewise there were no data available on the severity of diabetes. Preventive dental care was based upon the self-report of having an oral examination or dental prophylaxis during the calendar year. There were no data available on the clinical oral health of the participants.
The impact of overreporting or underreporting is difficult to determine. Therefore, the direction of misclassification bias in this study is unknown and a study limitation. While the design and statistical sciences behind the stability of surveys such as a long-running Medicare Current Beneficiary Survey will give reasonable confidence in the quality of reporting, the question of low quality reporting will be overcome by the significant majority of accurate reporting.
Policy recommendations
In terms of policy recommendations, there is a need for additional efforts to encourage individuals with diabetes to obtain preventive dental care. Healthcare professionals who treat patients with diabetes, such as endocrinologists, dieticians, and home healthcare workers have a role in recognizing the need to refer patients for preventive dental care. Specific professional guidelines for such referrals may be useful in addressing the need.
Conclusions
Positive inroads have been made for older adults to seek preventive dental care, but older adults with diabetes are in particular need for preventive dental care. Additional efforts are needed to encourage individuals with diabetes to obtain preventive dental care.
Acknowledgments
Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number U54GM104942. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in study design, data collection and analyses, decision to publish, or preparation of the manuscript.
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Disclosure. None of the authors reported any disclosures.
The authors report no conflicts of interest.
Contributor Information
R. Constance Wiener, Department of Dental Practice and Rural Health, School of Dentistry, 104A Health Sciences Addition, P.O. Box 9448, West Virginia University, Morgantown, WV 26506-9448, 304 581-1960 Fax 304 293-8561 rwiener2@hsc.wvu.edu.
Chan Shen, Departments of Health Services Research and Biostatistics, University of Texas MD Anderson Cancer Center, 1400 Pressler St, Houston, TX 77030 cshen@mdanderson.org.
Nethra Sambamoorthi, Master of Science in Predictive Analytics Program, 405 Church Street, Northwestern University - School of Professional Studies, Evanston, IL 60201 nethra.sambamoorthi@northwestern.edu.
Usha Sambamoorthi, Department of Pharmaceutical Systems and Policy, West Virginia University School of Pharmacy, Robert C. Byrd Health Sciences Center [North], P.O. Box 9510 Morgantown, WV 26506-9510 usambamoorthi@hsc.wvu.edu.
References
- 1.Centers for Disease Control and Prevention. Diabetes Public Health Resource: Annual Number (in Thousands) of New Cases of Diagnosed Diabetes Among Adults Aged 18–79 Years, United States, 1980–2013. 2013 http://www.cdc.gov/diabetes/statistics/incidence/fig1.htm.
- 2.Kim J, Amar S. Periodontal disease and systemic conditions: a bidirectional relationship. Odontology. 2006;94:10–21. doi: 10.1007/s10266-006-0060-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Nassar H, Kantarci A, VanDyke TE. Diabetic periodontitis: a model for activated innate immunity and impaired resolution of inflammation. Periodontol 2000. 2007;43:233–244. doi: 10.1111/j.1600-0757.2006.00168.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Rajhans NS, Kohad RM, Chaudhari VG, Mhaske NH. A clinical study of the relationship between diabetes mellitus and periodontal disease. J Indian Soc Periodontol. 2011;15(4):388–392. doi: 10.4103/0972-124X.92576. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Negrato CA, Tarzia O, Jovanovic L, Chinellato LEM. Periodontal disease and diabetes mellitus. J Appl Oral Sci. 2013:1–12. doi: 10.1590/1678-7757201302106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Kim E, Lee SG, Choi Y, Won K, Moon JS, Merchant AT, Lee H. Association between diabetes-related factors and clinical periodontal parameters in type-2 diabetes mellitus. BMC Oral Health. 2013;13:64. doi: 10.1186/1472-6831-13-64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Llambés F, Arias-Herrera S, Caffesse R. Relationship between diabetes and periodontal infection. World J Diabetes. 2015;6:927–935. doi: 10.4239/wjd.v6.i7.927. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Gupta N, Gupta ND, Gupta A, Goyal L, Garg S. The influence of type 2 diabetes mellitus on salivary matrix metalloproteinase-8 levels and periodontal parameters: A study in an Indian population. Eur J Dent. 2015;9:319–323. doi: 10.4103/1305-7456.163222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Merchant AT, Georgantopoulos P, Howe CJ, Virani SS, Morales DA, Haddock KS. Effect of Long-Term Periodontal Care on Hemoglobin A1c in Type 2 Diabetes. J Dent Res. 2015 Dec 23; doi: 10.1177/0022034515622197. pii: 0022034515622197. [Epub ahead of print] [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Kaur PK, Narula SC, Rajput R, K Sharma R, Tewari S. Periodontal and glycemic effects of nonsurgical periodontal therapy in patients with type 2 diabetes stratified by baseline HbA1c. J Oral Sci. 2015;57:201–211. doi: 10.2334/josnusd.57.201. [DOI] [PubMed] [Google Scholar]
- 11.Acharya AB, Thakur S, Muddapur MV. Effect of scaling and root planing on serum interleukin-10 levels and glycemic control in chronic periodontitis and type 2 diabetes mellitus. J Indian Soc Periodontol. 2015;19:188–193. doi: 10.4103/0972-124X.148644. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Salminen A, Kopra KAE, Hyvarinen K, Paju S, Mantyla P, Buhlin K, Nieminen MS, Sinisalo J, Pussinen PJ. Quantitative PCR analysis of salivary pathogen burden in periodontitis. Front Cell Infect Microbiol. 2015;5:69. doi: 10.3389/fcimb.2015.00069. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Löe H. Periodontal disease. The sixth complication of diabetes mellitus. Diabetes Care. 1993;16(1):329–334. [PubMed] [Google Scholar]
- 14.Fernandes JK, Wiegand RE, Salinas CE, Grossi SG, Sanders JJ, Lopes-Virella MF, Slate EH. Periodontal Disease Status in Gullah African Americans with Type 2 Diabetes living in South Carolina. J Periodontol. 2009;80:1062–1068. doi: 10.1902/jop.2009.080486. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Hodge PJ, Robertson D, Paterson K, Smith GLF, Creanor S, Sherriff A. Periodontitis in non-smoking type 1 diabetic adults: a cross-sectional study. J Clin Periodontol. 2012;39:20–29. doi: 10.1111/j.1600-051X.2011.01791.x. [DOI] [PubMed] [Google Scholar]
- 16.Lee KS, Kim EK, Kim JW, Choi YH, Mechant AT, Song KB, Lee HK. The relationship between metabolic conditions and prevalence of periodontal disease in rural Korean elderly. Arch Gerontol Geriatr. 2014;58:125–129. doi: 10.1016/j.archger.2013.08.011. [DOI] [PubMed] [Google Scholar]
- 17.Aimetti M, Perotto S, Castiglione A, Mariani GM, Ferrarotti F, Romano F. Prevalence of periodontitis in an adult population from an urban area in North Italy: findings from a cross-sectional population-based epidemiological survey. J Clin Periodontol. 2015;42:622–631. doi: 10.1111/jcpe.12420. [DOI] [PubMed] [Google Scholar]
- 18.Vergnes JN. Review finds periodontal treatment has short term benefits for diabetes. Evid Based Dent. 2015;16:78–79. doi: 10.1038/sj.ebd.6401114. [DOI] [PubMed] [Google Scholar]
- 19.Wang TF, Jen IA, Chou C, Lei YP. Effects of periodontal therapy on metabolic control in patients with type 2 diabetes mellitus and periodontal disease: a meta-analysis. Medicine. 2014;93:e292. doi: 10.1097/MD.0000000000000292. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Eke PI, Thornton-Evans GO, Beckles GL. Dental Visits Among Dentate Adults with Diabetes—United States, 1999 and 2004. MMWR. 2005;54:1181–1183. [PubMed] [Google Scholar]
- 21.US Department of Health and Human Services. Oral Health in America: A Report of the Surgeon General. Rockville, MD: US Department of Health and Human Services, National Institute of Dental and Craniofacial Research, National Institutes of Health; 2000. NIH Publication no. 00-4713 (2014). [Google Scholar]
- 22.Manski RJ, Cohen LA, Brown E, Carper KV, Vargas C, Macek MD. Dental service mix among older adults aged 65 and over, United States, 1999 and 2009. J Public Health Dent. 2014;74:219–226. doi: 10.1111/jphd.12049. [DOI] [PubMed] [Google Scholar]
- 23.Akinkugbe A, Lucas-Perry E. Trends in dental visits among the us non-institutionalized civilian population: findings from brfss 1995 – 2008. J Theory Pract Dent Public Health. 2013;1:32–36. [PMC free article] [PubMed] [Google Scholar]
- 24.Xu F, Town M, Balluz LS, Bartoli WP, Murphy W, Chowdhury PP, Garvin WS, Pierannunzi C, Zhong Y, Salandy SW, Jones CK, Crawford CA Centers for Disease Control and Prevention (CDC) Surveillance for certain health behaviors among States and selected local areas - United States, 2010. MMWR Surveill Summ. 2013;6:1–247. [PubMed] [Google Scholar]
- 25.Centers for Medicaid and Medicare Centers. Medicare Current Beneficiary Survey (MCBS) http://www.cms.hhs.gov/mcbs.
- 26.Garcia D, Sergey T, Okunseri C. Periodontitis and glycemic control in diabetes: NHANES 2009 to 2012. 2015;86:499–506. doi: 10.1902/jop.2014.140364. [DOI] [PubMed] [Google Scholar]
- 27.American Diabetes Association. Economic Costs of Diabetes in the U.S. in 2007. ADA Statement. 2008;31:596–615. doi: 10.2337/dc08-9017. [DOI] [PubMed] [Google Scholar]
- 28.Persson GR. Diabetes and periodontal disease. Diabetes Spectrum. 2011;24:195–198. [Google Scholar]
- 29.Saaddine JB, Cadwell B, Gregg EW, Engelgau MM, Vinicor F, Imperatore G, Narrayan KMV. Improvements in Diabetes Processes of Care and Intermediate Outcomes: United States, 1988–2002. Ann Intern Med. 2006;144:465–474. doi: 10.7326/0003-4819-144-7-200604040-00005. [DOI] [PubMed] [Google Scholar]
- 30.Andersen RM. Revisting the Behavioral Model and Access to Medical Care: Does It Matter? Journal of Health and Social Behavior. 1995;36:1–10. [PubMed] [Google Scholar]
- 31.Chaudhari M, Hubbard R, Reid RJ, Inge R, Newton KM, Spangler L, Barlow WE. Evaluating components of dental care utilization among adults with diabetes and matched controls via hurdle models. BMC Oral Health. 2012;12:20. doi: 10.1186/1472-6831-12-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Sheiham A, Williams DM, Weyant RJ, Glick M, Naidoo S, Eisele J, Selikowitz H. Billions with oral disease. JADA. 2015;146:861–864. doi: 10.1016/j.adaj.2015.09.019. [DOI] [PubMed] [Google Scholar]