Abstract

Introduction

Although children are the primary recipients of caries prevention programs in the Western world, dental caries is still one of the primary causes of tooth loss among adults.¹1 .Fure S. Ten-year incidence of tooth loss and dental caries in elderly Swedish individuals. Caries Res. 2003;37(6):462-9. doi:10.1159/000073401^,22 .Broadbent JM, Thomson WM, Poulton R. Progression of dental caries and tooth loss between the third and fourth decades of life: a birth cohort study. Caries Res. 2006;40(6):459-65. doi:10.1159/000095643^,33 .Vollmer WM, Papas AS, Bader JD, Maupomé G, Gullion CM, Hollis JF et al.; PACS Collaborative Research Group. Design of the Prevention of Adult Caries Study (PACS): a randomized clinical trial assessing the effect of a chlorhexidine dental coating for the prevention of adult caries. BMC Oral Health. 2010;10(1):23. doi:10.1186/1472-6831-10-23^,44 .Senna A, Campus G, Gagliani M, Strohmenger L. Socio-economic influence on caries experience and CPITN values among a group of Italian call-up soldiers and cadets. Oral Health Prev Dent. 2005;3(1):39-46. Among the clinical risk factors, mutans streptococci play an important role in the development of dental caries. However, the focus on the non-biological determinants of the disease (socio-behavioral and environmental factors) is essential.⁵5 .Holst D, Schuller AA, Aleksejuniené J, Eriksen HM. Caries in populations - a theoretical, causal approach. Eur J Oral Sci. 2001;109(3):143-8. doi:10.1034/j.1600-0722.2001.00022.x A lower educational level has been statistically associated with greater severity of dental caries in adults.⁶6 .Paulander J, Axelsson P, Lindhe J. Association between level of education and oral health status in 35-, 50-, 65- and 75-year-olds. J Clin Periodontol. 2003;30(8):697-704. doi:10.1034/j.1600-051X.2003.00357.x^,77 .Costa SM, Martins CC, Bonfim M L, Zina LG, Paiva SM, Pordeus IA et al. A systematic review of socioeconomic indicators and dental caries in adults. Int J Environ Res Public Health. 2012;9(10):3540-74. doi:10.3390/ijerph9103540 Among the prediction models available,⁸8 .Tellez M, Gomez J, Pretty I, Ellwood R, Ismail AI. Evidence on existing caries risk assessment systems: are they predictive of future caries? Community Dent Oral Epidemiol. 2013;41(1):67-78. doi:10.1111/cdoe.12003 Cariogram software has been developed and validated to illustrate graphically the chance of an individual avoiding caries in the near future.⁹9 .Petersson GH. Assessing caries risk: using the Cariogram model. Swed Dent J Suppl. 2003;(158):1-65.^,1010 .Bratthall D, Hänsel Petersson G. Cariogram - a multifactorial risk assessment model for a multifactorial disease. Community Dent Oral Epidemiol. 2005;33(4):256-64. doi:10.1111/j.1600-0528.2005.00233.x^,1111 .Campus G, Cagetti MG, Sale S, Carta G, Lingström P. Cariogram validity in schoolchildren: a two-year follow-up study. Caries Res. 2012;46(1):16-22. doi:10.1159/000334932^,1212 .Cabral RN, Hilgert LA, Faber J, Leal SC. Caries risk assessment in schoolchildren: a form based on Cariogram software. J Appl Oral Sci. 2014;22(5):397-422. doi:10.1590/1678-775720130689 Cariogram has been used to predict caries in children,¹²12 .Cabral RN, Hilgert LA, Faber J, Leal SC. Caries risk assessment in schoolchildren: a form based on Cariogram software. J Appl Oral Sci. 2014;22(5):397-422. doi:10.1590/1678-775720130689 adults¹³13 .Lee JH, Son HH, Kim HY, Chang J. Caries risk profiles of Korean dental patients using simplified Cariogram models. Acta Odontol Scand. 2013;71(3-4):899-905. doi:10.3109/00016357.2012.734416^,1414 .Sonbul H, Al-Otaibi M, Birkhed D. Risk profile of adults with severe dental restorations using the Cariogram model. Acta Odontol Scand. 2008;66(6):351-7. doi:10.1080/00016350802325853^,1515 .Aranibar Quiroz EM, Alstad T, Campus G, Birkhed D, Lingström P. Relationship between plaque pH and different caries-associated variables in a group of adolescents with varying caries prevalence. Caries Res. 2014;48(2):147-53. doi:10.1159/000355614^,1616 .Ruiz Miravet A. Montiel Company JM, Almerich Silla JM. Evaluation of caries risk in a young adult population. Med Oral Patol Oral Cir Bucal. 2007;12(5):E412-8.^,1717 .Giacaman RA, Miranda Reyes P, Bravo León V. Caries risk assessment in Chilean adolescents and adults and its association with caries experience. Braz Oral Res. 2013;27(1):7-13. doi:10.1590/S1806-83242013000100002^,1818 .Celik EU, Gokay N, Ates M. Efficiency of caries risk assessment in young adults using Cariogram. Eur J Dent. 2012;6(3):270-9.^,1919 .Petersson GH, Twetman S. Caries risk assessment in young adults: a 3 year validation of the Cariogram model. BMC Oral Health. 2015;15(1):17. doi:10.1186/1472-6831-15-17 and the elderly,²⁰20 .Alian AY, McNally ME, Fure S, Birkhed D. Assessment of caries risk in elderly patients using the cariogram model. J Can Dent Assoc. 2006;72(5):459-63. and the scientific evidence regarding its prediction efficiency is still questionable. For adults, despite some studies reporting a high predictive value for Cariogram risk levels,¹³13 .Lee JH, Son HH, Kim HY, Chang J. Caries risk profiles of Korean dental patients using simplified Cariogram models. Acta Odontol Scand. 2013;71(3-4):899-905. doi:10.3109/00016357.2012.734416^,1818 .Celik EU, Gokay N, Ates M. Efficiency of caries risk assessment in young adults using Cariogram. Eur J Dent. 2012;6(3):270-9. other studies have not found a correlation between caries experience and any single risk factor proposed by Cariogram.¹⁷17 .Giacaman RA, Miranda Reyes P, Bravo León V. Caries risk assessment in Chilean adolescents and adults and its association with caries experience. Braz Oral Res. 2013;27(1):7-13. doi:10.1590/S1806-83242013000100002^,1919 .Petersson GH, Twetman S. Caries risk assessment in young adults: a 3 year validation of the Cariogram model. BMC Oral Health. 2015;15(1):17. doi:10.1186/1472-6831-15-17 The use of Cariogram in an adult population might be useful to try to modify caries-related behaviors and increase patients’ motivation.

Common outcomes used in studying the epidemiology of dental caries, such as DMFT and DMFS indices, may be insufficient for investigating the risk factors that lead to specific patterns of decay.²¹21 .Shaffer JR, Polk DE, Feingold E, Wang X, Cuenco KT, Weeks DE et al. Demographic, socioeconomic, and behavioral factors affecting patterns of tooth decay in the permanent dentition: principal components and factor analyses. Community Dent Oral Epidemiol. 2013;41(4):364-73. doi:10.1111/cdoe.12016^,2222 .Iranzo-Cortés JE, Montiel-Company JM, Almerich-Silla JM. Caries diagnosis: agreement between WHO and ICDAS II criteria in epidemiological surveys. Community Dent Health. 2013;30(2):108-11. doi:10.1922/CDH_3006Silla04 The International Caries Detection Assessment System (ICDAS), based on the best available evidence for detecting early and later stage caries severity, should lead to the acquisition of better quality information to support decision-making at both individual and public health levels.²²22 .Iranzo-Cortés JE, Montiel-Company JM, Almerich-Silla JM. Caries diagnosis: agreement between WHO and ICDAS II criteria in epidemiological surveys. Community Dent Health. 2013;30(2):108-11. doi:10.1922/CDH_3006Silla04^,2323 .Ismail AI, Sohn W, Tellez M, Willem JM, Betz J, Lepkowski J. Risk indicators for dental caries using the International Caries Detection and Assessment System (ICDAS). Community Dent Oral Epidemiol. 2008;36(1):55-68. doi:10.1111/j.1600-0528.2006.00369.x^,2424 .Braga MM, Oliveira LB, Bonini GA, Bönecker M, Mendes FM. Feasibility of the International Caries Detection and Assessment System (ICDAS-II) in epidemiological surveys and comparability with standard World Health Organization criteria. Caries Res. 2009;43(4):245-9. doi:10.1159/000217855 For clinical application, the ICDAS Foundation developed an ICDAS code with merged categories called the International Caries Classification and Management System (ICCMS^TM).²⁵25 .Pitts NB, Ekstrand KR. International Caries Detection and Assessment System (ICDAS) and its International Caries Classification and Management System (ICCMS): methods for staging of the caries process and enabling dentists to manage caries. Community Dent Oral Epidemiol. 2013;41(1):e41-52. doi:10.1111/cdoe.12025

The aim of this study was to examine the correlation among socio-behavioral factors, caries status and caries risk, calculated through Cariogram, in an adult population.

Methodology

Study design

The present study was carried out in Sassari (Sardinia, Italy) and lasted 14 months, from September 2012 to October 2013. The study design was registered (2013_01_21_a) by the Sassari local office of the National Bioethics Committee.

Data from the Italian National Institute for Statistics for 2011 showed the number of 35-45 year-olds in the town of Sassari to be 22,614. A power analysis was performed using G*Power 3.1.3 for Apple, logistic regression, an odds ratio of 1.5, and an error probability of 0.04, and the total sample size was set at 432. A letter explaining the purpose of the study and the informed consent were distributed to 5% (1131 subjects) of the age group considered living in Sassari through the collaboration of the municipal electoral registry office; 577 subjects (51.02% acceptance rate) agreed to participate, 82 did not attend the examination and 15 did not completely fill out the questionnaire (Figure 1).

Questionnaire

A simplified structured self-compiled questionnaire and an informed consent form were submitted to the participants. The questionnaire was previously used in a large sample (2908 subjects) of Italian soldiers.⁴4 .Senna A, Campus G, Gagliani M, Strohmenger L. Socio-economic influence on caries experience and CPITN values among a group of Italian call-up soldiers and cadets. Oral Health Prev Dent. 2005;3(1):39-46. It was divided into different domains: (1) personal data (i.e., age, gender, educational level, job categorization), (2) life-style behavior (i.e., smoking and dietary habits), and (3) oral health behavior (i.e., tooth brushing, use of fluoride, and frequency of dental check-ups).

Caries assessment

One calibrated examiner (GiC) performed all the dental screenings. Intra- and inter-examiner reliabilities were assessed before the beginning of the survey by examining and re-examining (after 72 h) 55 study participants. Inter-examiner reliability was evaluated using fixed-effects analysis of variance in comparison with benchmark values (GC). Intra-examiner reliability was assessed as the percentage of agreement using Cohen’s kappa statistic.²⁶26 .Castiglia P, Campus G, Solinas G, Maida C, Strohmenger L. Children’s oral health in Italy: training and clinical calibration of examiners for the National Pathfinder about caries disease. Oral Health Prev Dent. 2007;5(4):255-61. doi:10.3290/j.ohpd.a12793 Good inter-examiner reliability was found for the ICCMS^TM (merged ICDAS) score 1-2, 3-4 and 5-6, with no significant difference from benchmark values (p = 0.15) and a low mean square of error (0.47). Intra-examiner reliability was also high (Cohen’s Kappa statistic = 0.88). Subjects were examined sitting on an ordinary chair, with a mouth mirror and a Community Periodontal Index probe under optimal lighting. Subjects were categorized according to maximum ICDAS scores.

The number of missing teeth due to caries was categorized as follows: no missing teeth, 1-2 missing teeth, 3-5 missing teeth and more than 5 missing teeth. The presence of fillings was classified as: no fillings, mainly tooth-colored restorations, mainly amalgam restorations and the presence at least of one crown. Plaque index was assessed in the buccal surface using the Silness & Löe’s scale.

Microbiological evaluation

After the clinical examination, an evaluation of the mutans streptococci (MS) concentration in saliva was performed. No-stimulated whole saliva was collected over 150 seconds in sterile vials (Nunc, Kamstrup, Denmark). The samples were processed within 45 minutes after collection, and the analysis was carried out using CRT BACTERIA (Ivoclar, Vivadent AG, Schaan, Liechtenstein). The presence of mutans streptococci over 10⁵5 .Holst D, Schuller AA, Aleksejuniené J, Eriksen HM. Caries in populations - a theoretical, causal approach. Eur J Oral Sci. 2001;109(3):143-8. doi:10.1034/j.1600-0722.2001.00022.xCFU/ml suggests a high caries risk.

Caries risk assessment using Cariogram

Information on caries-related factors was collected and entered into Cariogram.⁹9 .Petersson GH. Assessing caries risk: using the Cariogram model. Swed Dent J Suppl. 2003;(158):1-65.^,1010 .Bratthall D, Hänsel Petersson G. Cariogram - a multifactorial risk assessment model for a multifactorial disease. Community Dent Oral Epidemiol. 2005;33(4):256-64. doi:10.1111/j.1600-0528.2005.00233.x^,1111 .Campus G, Cagetti MG, Sale S, Carta G, Lingström P. Cariogram validity in schoolchildren: a two-year follow-up study. Caries Res. 2012;46(1):16-22. doi:10.1159/000334932 The six caries-related factors listed below were included in the Cariogram software.⁹9 .Petersson GH. Assessing caries risk: using the Cariogram model. Swed Dent J Suppl. 2003;(158):1-65.^,1010 .Bratthall D, Hänsel Petersson G. Cariogram - a multifactorial risk assessment model for a multifactorial disease. Community Dent Oral Epidemiol. 2005;33(4):256-64. doi:10.1111/j.1600-0528.2005.00233.x^,1111 .Campus G, Cagetti MG, Sale S, Carta G, Lingström P. Cariogram validity in schoolchildren: a two-year follow-up study. Caries Res. 2012;46(1):16-22. doi:10.1159/000334932

Caries experience was recorded using the WHO basic report enclosed in the ICDAS evaluation, which allowed the calculation of the DMFT of the population.

1. Diet content (from questionnaires);

2. Diet frequency (from questionnaires);

3. Salivary levels of mutans streptococci (from CRT Bacteria);

4. Plaque amount and grade of oral hygiene (from clinical examination);

5. Related general diseases (from questionnaires);

6. Fluoridation program (from questionnaires).

A score of 1 in all cases was assigned for clinical judgment in order to produce a standard value.

The “chance to avoid new caries in the future” was calculated, and the subjects were divided into three groups: low risk (61-80%), medium risk (41-60%) and high risk (21-40%).

Statistical analyses

Descriptive statistics and crosstabs were calculated to investigate the relationship between dental health and different risk factors. The reference for each variable was set as follows: gender (male); caries status (ICDAS 5-6); type of dental treatment (presence of at least one crown); number of missing teeth due to caries (more than five teeth); educational level (middle school degree); occupational status (unemployed); smoking habits (yes); frequency of toothbrushing (once a day); and frequency of dental check-ups (when in pain).

A chi-square test was conducted for each variable and the level of caries risk measured by Cariogram. Multinomial logistic regression was performed using Cariogram levels as the dependent variable. The possible correlated variables were analyzed using the PCA.²⁷27 .Van Ooyen A. Theoretical aspects of pattern analysis. A simple introduction to principal component and cluster analysis. In: Dijkshoorn L, Towner KJ, Struelens M (Eds.). New approaches for the generation and analysis of microbial fingerprints. Amsterdam: Elsevier; 2001. p. 31-45.The performance of Cariogram in predicting caries in the near future was evaluated by receiver operating characteristic (ROC) analysis.²⁸28 .Koepsell TD, Connell FA. Measures of gain in certainty from a diagnostic test. Am J Epidemiol. 1985;121(5):744-53. doi:10.1093/aje/121.5.744 The p-values < 0.05 were considered statistically significant. All data were analyzed using v10.1 software for Macintosh produced by STATA^® (STATA Corporation, College Station, Texas).

Results

The study population consisted of 480 subjects (mean age 40.7, SE ± 0.3), 52.9% males and 47.1% females. The caries prevalence in the sample was 57.9%. The sample distribution by gender across the clinical data for ICDAS scores (initial caries ICDAS 1-2, moderate caries ICDAS 3-4, and extensive caries ICDAS 5-6) and dental treatment is displayed in Table 1. Almost half of the sample (47.9%) had at least one missing tooth due to caries. The mean number of sound teeth registered was 24.8 (SE ± 0.2). Each subject presented an average of 3.7 (SE ± 0.1) tooth-colored restorations, 3.0 (SE ± 0.1) amalgam restorations and 1.58 (SE ± 0.14) crowns. Regarding the questionnaires, 17.9% of subjects had graduated from middle school, 47.3% (most) had graduated from high school, and 34.8% (a quite high percentage) had a university degree. Additionally, 60.4% of the sample brushed their teeth three times a day. Only 26.7% of the subjects were smokers, and most of them had been smoking for more than 5 years (data not in table).

Relating to caries risk, the majority of the sample (78.1%) presented a medium caries risk (41-60% of chance to avoid new caries lesions in the future), 18.8% had a high caries risk (< 41% of chance to avoid new caries lesions in the future) and 3.1% had a low caries risk (> 60% of chance to avoid new caries lesions in the future). Table 2 shows the results of a chi-square test between the level of caries risk, calculated through Cariogram software, and background variables. A statistically significant association was evident between the caries risk and ICDAS score (p < 0.01). A statistically significant association was found between the level of caries risk and the following factors: number of missing teeth due to caries (p = 0.01), educational level (p = 0.04), smoking habit (p = 0.01), frequency of toothbrushing (p = 0.02) and frequency of dental check-ups (p < 0.01).

A multinomial logistic regression model was run for caries risk factors (Table 3), and the Cariogram score was used as a dependent variable. The presence of caries lesions at a ICDAS level 5-6 and the presence of more than 5 missing teeth were statistically associated with Cariogram scores (OR = 2.36, 95%CI = 1.83-3.03 and OR = 1.43, 95%CI = 1.13-1.82, respectively).

PCA was performed on the data set, first on the total sample and in the two main groups stratified by Cariogram scores (caries medium-risk group and high-risk group); the low caries risk group was too small, and PCA was not performed. In all PCAs, the first two eigenvalues, obtained from the distance matrix between groups, collectively accounted for more than 66.0% of the total variance (86.1%; 59.4 and 26.8%, respectively in the total sample; 52.5% and 21.1% respectively and 66.3% in the high-risk group 42.7% and 23.6% two eigenvalues respectively). Figure 2 displays the Orthogonal Rotation (Varimax) of the first two principal coordinates in the total sample and in the two main groups stratified by Cariogram scores. In the total sample, the Cariogram score, the Bacteria and the Susceptibility sectors from Cariogram tended to form a separate cluster with a high goodness of fit (63.7); also, number of missing teeth due to caries, smoking habit and circumstances from Cariogram tended to form another cluster with a high goodness of fit (61.8); however, level of education, gender and job categorization were clearly separated from the other variables. Severe caries status (ICDAS 5-6), number of missing teeth due to caries higher than 5, unemployment, smoking and male gender tended to form a cluster with a medium-high goodness of fit (0.5–0.7) in the high-risk group. In the medium-risk group, no clear cluster was identified, and all variables stood separated from each other. The sensitivity and specificity between ICDAS scores and Cariogram, measured by ROC analysis, were 0.8 and 0.9, respectively, so the gain in certainty was 1.7, while the area under the ROC curve was 0.9 (data not in table).

Discussion

Because caries distribution is remarkably uneven, an accurate assessment of caries risk would allow a better use of limited resources.⁸8 .Tellez M, Gomez J, Pretty I, Ellwood R, Ismail AI. Evidence on existing caries risk assessment systems: are they predictive of future caries? Community Dent Oral Epidemiol. 2013;41(1):67-78. doi:10.1111/cdoe.12003 A computer caries assessment system might represent a helpful tool to assess caries risk before the development of the disease.⁹9 .Petersson GH. Assessing caries risk: using the Cariogram model. Swed Dent J Suppl. 2003;(158):1-65.^,1010 .Bratthall D, Hänsel Petersson G. Cariogram - a multifactorial risk assessment model for a multifactorial disease. Community Dent Oral Epidemiol. 2005;33(4):256-64. doi:10.1111/j.1600-0528.2005.00233.x^,1111 .Campus G, Cagetti MG, Sale S, Carta G, Lingström P. Cariogram validity in schoolchildren: a two-year follow-up study. Caries Res. 2012;46(1):16-22. doi:10.1159/000334932 A simplified computer caries assessment system, with the exclusion of two risk factors, may be used in clinical practice, when a full inclusion of risk factors is not achievable.¹³13 .Lee JH, Son HH, Kim HY, Chang J. Caries risk profiles of Korean dental patients using simplified Cariogram models. Acta Odontol Scand. 2013;71(3-4):899-905. doi:10.3109/00016357.2012.734416 Little information exists on the performance of Cariogram in adult individuals,¹⁰10 .Bratthall D, Hänsel Petersson G. Cariogram - a multifactorial risk assessment model for a multifactorial disease. Community Dent Oral Epidemiol. 2005;33(4):256-64. doi:10.1111/j.1600-0528.2005.00233.x^,1313 .Lee JH, Son HH, Kim HY, Chang J. Caries risk profiles of Korean dental patients using simplified Cariogram models. Acta Odontol Scand. 2013;71(3-4):899-905. doi:10.3109/00016357.2012.734416^,1414 .Sonbul H, Al-Otaibi M, Birkhed D. Risk profile of adults with severe dental restorations using the Cariogram model. Acta Odontol Scand. 2008;66(6):351-7. doi:10.1080/00016350802325853^,1515 .Aranibar Quiroz EM, Alstad T, Campus G, Birkhed D, Lingström P. Relationship between plaque pH and different caries-associated variables in a group of adolescents with varying caries prevalence. Caries Res. 2014;48(2):147-53. doi:10.1159/000355614^,1616 .Ruiz Miravet A. Montiel Company JM, Almerich Silla JM. Evaluation of caries risk in a young adult population. Med Oral Patol Oral Cir Bucal. 2007;12(5):E412-8.^,1717 .Giacaman RA, Miranda Reyes P, Bravo León V. Caries risk assessment in Chilean adolescents and adults and its association with caries experience. Braz Oral Res. 2013;27(1):7-13. doi:10.1590/S1806-83242013000100002^,1818 .Celik EU, Gokay N, Ates M. Efficiency of caries risk assessment in young adults using Cariogram. Eur J Dent. 2012;6(3):270-9.^,1919 .Petersson GH, Twetman S. Caries risk assessment in young adults: a 3 year validation of the Cariogram model. BMC Oral Health. 2015;15(1):17. doi:10.1186/1472-6831-15-17 so the aim of this study was to describe the relation among caries status, background variables and caries risk as calculated with Cariogram. More than two-thirds of the sample showed a medium risk, and most of the remaining sample showed a high risk of future caries development. These findings showed a statically significant association with the caries status and the number of missing teeth due to caries, measured using ICDAS criteria. Similar results were reported in Spanish young adults with a statistically significant association between the caries risk profile determined by Cariogram and past caries experience.¹⁶16 .Ruiz Miravet A. Montiel Company JM, Almerich Silla JM. Evaluation of caries risk in a young adult population. Med Oral Patol Oral Cir Bucal. 2007;12(5):E412-8. Otherwise, in a high-caries adult population, different results were found, e.g., the Cariogram risk categories did not fit with caries experience.¹⁷17 .Giacaman RA, Miranda Reyes P, Bravo León V. Caries risk assessment in Chilean adolescents and adults and its association with caries experience. Braz Oral Res. 2013;27(1):7-13. doi:10.1590/S1806-83242013000100002 Such a result was probably due to the hypothesized poor ability of the Cariogram to properly clarify the association between caries risk and caries experience in a high-caries population. Nevertheless, a direct association between the categorized outcomes of the Cariogram and caries status was found in a group of Saudi adults with several dental restorations.¹⁴14 .Sonbul H, Al-Otaibi M, Birkhed D. Risk profile of adults with severe dental restorations using the Cariogram model. Acta Odontol Scand. 2008;66(6):351-7. doi:10.1080/00016350802325853 Caries still remains an important reason for tooth loss,¹1 .Fure S. Ten-year incidence of tooth loss and dental caries in elderly Swedish individuals. Caries Res. 2003;37(6):462-9. doi:10.1159/000073401^,22 .Broadbent JM, Thomson WM, Poulton R. Progression of dental caries and tooth loss between the third and fourth decades of life: a birth cohort study. Caries Res. 2006;40(6):459-65. doi:10.1159/000095643^,2929 .Beltran-Aguilar ED, Barker LK, Canto MT, Dye BA, Gooch BF, Griffin SO et al. Surveillance for dental caries, dental sealants, tooth retention, edentulism, and enamel fluorosis: United States, 1988-1994 and 1999—2002. Surveillance Summaries. 2005;54:1-44. and the results of this paper noted the association between this variable and the caries risk profile measured by the Cariogram model. Moreover, the multinomial logistic regression outcome underlines an association between the Cariogram score and the higher ICDAS score and also the higher number of missing teeth.

Among background variables, educational level, smoking habit, frequency of toothbrushing and frequency of dental check-ups showed a statistically significant association with Cariogram risk groups. In particular, the educational level is one of the most frequently used socioeconomic indicator: a lower educational level has been statistically associated with a greater prevalence of dental caries.⁶6 .Paulander J, Axelsson P, Lindhe J. Association between level of education and oral health status in 35-, 50-, 65- and 75-year-olds. J Clin Periodontol. 2003;30(8):697-704. doi:10.1034/j.1600-051X.2003.00357.x^,77 .Costa SM, Martins CC, Bonfim M L, Zina LG, Paiva SM, Pordeus IA et al. A systematic review of socioeconomic indicators and dental caries in adults. Int J Environ Res Public Health. 2012;9(10):3540-74. doi:10.3390/ijerph9103540 The finding of a statistically significant association among the Cariogram score and socioeconomic and behavioral variables is quite new and interesting because it highlights that even if the Cariogram model includes proximal risk factors for caries almost exclusively, distal risk factors, such as smoking and educational level, are strongly correlated with the risk assessed through the Cariogram.

PCA supports the concept that caries risk is divisible into patterns attributable to distinct risk factors that work in accord. In the total sample, two different clusters might be noted: the first centered on a Cariogram score with two Cariogram sectors, Susceptibility (fluoride program, saliva secretion and buffer capacity) and Bacteria (plaque amount and MS), while the second is the association of a high number of missing teeth due to caries, smoking habit and circumstances (caries experience and related diseases), which further supports the involvement of environmental risk factors on the caries pattern. The interpretation of the PCA on the Cariogram high-risk group is that those with a severe caries status (ICDAS 5-6), with a high number of missing teeth due to caries, who are unemployed, smoke and are male tend to be strictly associated with a distinct disease pattern. Socioeconomic indicators often have a heavy impact on biological factors, influencing variables such as diet or oral hygiene habits.⁵5 .Holst D, Schuller AA, Aleksejuniené J, Eriksen HM. Caries in populations - a theoretical, causal approach. Eur J Oral Sci. 2001;109(3):143-8. doi:10.1034/j.1600-0722.2001.00022.x^,77 .Costa SM, Martins CC, Bonfim M L, Zina LG, Paiva SM, Pordeus IA et al. A systematic review of socioeconomic indicators and dental caries in adults. Int J Environ Res Public Health. 2012;9(10):3540-74. doi:10.3390/ijerph9103540^,2929 .Beltran-Aguilar ED, Barker LK, Canto MT, Dye BA, Gooch BF, Griffin SO et al. Surveillance for dental caries, dental sealants, tooth retention, edentulism, and enamel fluorosis: United States, 1988-1994 and 1999—2002. Surveillance Summaries. 2005;54:1-44. Therefore, it is possible to suggest that those who have no job are more likely to have more caries, lose more teeth due to caries, and have no economic resources to receive dental treatment because, in Italy, public dental services for adults are very limited and dental care has to be paid directly by the patient.

This study benefited from several strengths, as a large sample and the surface-level caries assessment that made the different modeling of caries patterns possible. A limitation would be the non-generalizability of the results. The studied population belonged to a medium-low socio-economic group living in an area with a low mean income per capita. It is possible that, in a population with different socio-economic and behavioral variables, distinct risk factors may have an influence on caries disease.

Conclusion

In conclusion, the Cariogram model was able to identify caries-related factors in an adult population. A direct association among the risk categories from Cariogram, the caries status and some socio-behavioral variables was verified.

Acknowledgments

The authors would like to thank everyone who helped carry out this study, including the personnel of the municipal electoral registry office of the town of Sassari.

References

Publication Dates

History