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New Coronal Caries in Older Adults: Implications for Prevention
1 Centers for Disease Control and Prevention/Division of Oral Health/Surveillance, Investigations, and Research Branch, 4770 Buford Highway, MSF10, Chamblee, GA 30341, USA; and Correspondence: * corresponding author, sig1{at}cdc.gov
To characterize the extent and severity of coronal caries among older US adults and document their need for prevention interventions, we systematically reviewed studies on coronal caries incidence, increment, and attack rate. We abstracted six studies and calculated summary measures using a random-effects model (95% confidence interval [95%CI]). We tested for heterogeneity and identified associated factors by examining the correlation between outcome measures and baseline population risk and study characteristics. We re-calculated summary measures after adjusting outcomes that netted out examiner reversals. Incidence and increment varied significantly by study. Adjusting studies for netting out examiner reversals reduced heterogeneity significantly. Annual attack rate among adjusted North American studies was 1.4 surfaces per 100 surfaces (95%CI = 1.0–1.9), or approximately 1 new carious surface per person per year. These rates are equal to or higher than those in children and indicate a need for caries-prevention services.
Key Words: coronal caries incidence increment attack rate adults
The purpose of this research was to derive estimates of new dental disease in older adults (aged 60+ yrs) using standard tools of meta-analysis. Documenting new caries among older adults is necessary to determine both the potential impact and cost-effectiveness of caries-prevention efforts. We have good evidence that interventions to avert dental caries are effective (Truman et al., 2002; Marinho et al., 2003). Although most trials measuring effectiveness have been conducted among younger populations, the available but limited evidence for adults suggests that effects are consistent with those expected effects based on experience with children (US Department of Health and Human Services, 2000). Currently, water fluoridation is the main caries-prevention program that affects older adults. Other common primary prevention programs delivered at the community level—school-based/-linked sealant programs and delivery of fluoride via mouthrinse, supplement, or topical applications—primarily target children (ASTDD, 2002). Medicaid (a Federally funded, state-operated and -administered program that provides medical benefits to indigent or low-income persons) frequently covers only emergency dental care for adults (Oral Health America, 2003), and Medicare (a Federal health insurance program for the elderly) does not cover routine dental services. These interventions may be able to prevent significant amounts of dental caries in older adults. While national surveys provide cross-sectional data to estimate the prevalence and severity of caries, at present, we have no longitudinal estimates of new caries at the national level. However, at the state and community levels, longitudinal data for older adults suggest that they may have more new caries than children (Hand et al., 1988a). Two previous articles estimated new dental caries among older adults by averaging the findings from some of these studies (Garcia, 1989; Leake, 2001). Neither article, however, took study variance into account in deriving summary measures, or examined if outcome measures were homogenous across studies. Finally, demographic trends suggest that the number of older adults will continue to increase relative to the general population (Administration on Aging, 2000), and that these older adults are more likely to retain their teeth than were previous generations (US Department of Health and Human Services, 2000).
Search for Studies We searched MEDLINE and EMBASE for studies on new dental caries conducted after 1980 among adult populations, published in English (Appendix Table 1). We also searched bibliographies of retrieved articles; we did not, however, hand-search journals, search for unpublished studies, or contact authors of published studies for additional data. We used the following to measure new caries: (1) incidence (proportion of individuals developing caries); (2) increment (average number of tooth surfaces per person developing caries); and (3) attack rate (proportion of at-risk surfaces developing caries). We reviewed titles and abstracts and ordered articles with study populations older than 40 yrs living in established market economies (Appendix Fig.). The search strategy and data abstraction process (Appendix Table 2) have been described previously (Griffin et al., 2004).
Inclusion Criteria
Data Adjustment Some studies reported outcome measures for the same population for different time intervals (i.e., 18 and 36 mos). Because, in some of the studies, individuals who dropped out had significantly higher levels of disease at baseline (Hand et al., 1988b; Hawkins et al., 1997; Gilbert et al., 2000; Thomson et al., 2002), we reported outcome measures for the shortest study interval, to minimize potential bias resulting from the attrition of study subjects. For studies reporting caries increment or attack rate for periods greater than a year, we assumed that the outcome measure was independently and identically distributed for each year; thus, we calculated the annual measure by dividing the reported measure by the number of years in the reported interval, and estimated the annual standard error by dividing the reported standard error for the interval by the square root of the interval years. To estimate annual incidence, we assumed that the probability of experiencing caries was the same for each study year. We first calculated the probability that no disease was incurred over the study interval, and then took the nth root of this value (where n represents number of yrs in study) to calculate the probability that no disease was incurred in a given year. We then subtracted this value from 1 to obtain the annual incidence.
Some studies reported separate measures for specific groups. For these studies, we estimated the outcome measure (standard error) for the population by taking the weighted average (standard error =
We excluded studies that reported increment or attack rate but did not report a variance, standard deviation, or standard error. For studies reporting incidence but not a standard error, we calculated the standard error with the following formula: (standard error = Most studies did not include crowns in their outcome measures for disease. For studies that reported increment or attack rate including and excluding crowns, we used the outcome measure, which excluded crowns. To make the findings of studies that adjusted for examiner reversals more comparable with the results of studies that did not, we reported, when possible, crude estimates of new disease that did not net out negative reversals. Netting out negative reversals may underestimate new disease (Burt and Eklund, 1999). Two studies comparing the two methods found that the net method resulted in more biased estimates of new caries in older adults than did the crude method. One study found that using the crude instead of the net estimation method increased estimates of incidence, increment, and attack rate by 44%, 119%, and 124%, respectively (Slade and Caplan, 2000), while, similarly, the other found that crude increment estimates were 121% higher (Beck et al., 1995). We also calculated estimates of new disease adjusted for analytic convention by inflating net measures by the above percentages.
Analysis To determine if the dental health status of the study populations was similar to that of the US population as a whole, we compared the mean number of teeth present and mean number of decayed and filled coronal surfaces among the study populations at baseline (1981 to 1997) against the national estimates from the National Health and Nutrition Examination Survey (NHANES) III (1988–1991) (Winn et al., 1996) for similar age groups. Using a chi-square test (QW) (Normand, 1999), we tested for homogeneity of effect size (new disease) among studies. For effect sizes failing the heterogeneity test, we estimated the quantity I2, which describes the percentage of total variation, across studies, due to heterogeneity vs. chance (Higgins et al., 2003). Thus, if study populations at baseline had dental health status similar to that of the US population, and if new disease outcomes are homogenous across studies, our findings may be applicable to the US population. Finally, to identify potential sources of heterogeneity, we examined the correlation coefficients between each outcome measure and: (1) population baseline risk factors [measured by age and number of decayed, missing, and filled tooth surfaces (DMFS)] and (2) study design factors (measured by study length, whether the examination included 3rd molars, and whether it netted out examiner reversals) (Appendix Table 3).
Among all studies, the annual incidence estimate was 31.9% (95%CI, 23.3.0%–40.5%; heterogeneity present) (Fig. 1
Among all studies, the estimate of annual coronal caries increment was 0.86 surfaces (95%CI, 0.66–1.07; heterogeneity present) (Fig. 2
Among all studies, the annual caries attack rate equaled 1.1% (95%CI, 0.6%–1.6%; heterogeneity present; Fig. 3
It appears that, among the study populations included in this review, baseline mean DMFS was slightly lower than levels reported for similar age groups in NHANES III (Appendix Table 5). The baseline number of retained teeth among the studies included in our review, excepting Florida and perhaps Australia (because the study did not report the standard error for this value, we know only that the reported value is either the same or lower), was similar to estimates reported for the US among similar age groups. Baseline mean DFS was similar in Florida, less in Iowa and Australia, and either less than or similar in Canada and North Carolina.
Because of heterogeneity, summary effect measures should be interpreted with caution. The I2 statistic exceeded 70% for all summary effect measures, with the exception of attack rate among adjusted North American studies. For these studies, we found that, on average, 1.43% of at-risk surfaces become carious each year. The mean DMFS for these studies was 59.75; assuming no recurrent caries, the average number of new carious surfaces after one year would thus be 0.98 [= 0.0143*(128-59.75)]. These findings suggest that new decay among older adults is similar to or higher than that in children. A review of studies estimating annual caries increment among children found that children living in fluoridated and fluoride-deficient communities experienced, on average, 0.8 and 1.4 new decayed tooth surfaces per year, respectively (Garcia, 1989). The review included controls from fluoridated toothpaste clinical trials and studies from the late 1970s, and thus may not be directly comparable with our analysis of more recent data from general populations. Using published values of DMFS among children aged 12 to 18 yrs as reported in the NHANES III (Kaste et al., 1996), and assuming a constant caries increment, we imputed an annual caries increment of 0.50 surfaces (Appendix Table 6). Caries among the elderly is also more likely to remain untreated; their mean number of untreated decayed surfaces (1.6) (Winn et al., 1996) is about four times that among US schoolchildren (0.4) (Kaste et al., 1996). This may be partly attributable to the limited safety net available to provide routine dental care to adults—lower-income adults are about 6 times more likely to have untreated decay than their higher-income counterparts (Drury et al., 1999). Untreated decay reflects a need not only for treatment services, but also for preventive interventions. We found that study design characteristics were more likely to contribute to heterogeneity than were differences in baseline risk. None of the outcome measures was correlated with baseline risk variables, suggesting that risk differences did not contribute to heterogeneity among outcomes. This may be because neither baseline age nor DMFS differed greatly by study; the respective coefficients of variation were 0.07 and 0.09. Only two study design variables were correlated with outcome measures and thus may have contributed to heterogeneity—whether the study netted out examiner reversals, and the study duration (time to first follow-up). We adjusted the data to control for netting out examiner reversals; however, we could not do so completely for study duration. Study duration influences the outcome measure in at least two ways. First, subjects with higher levels of baseline disease may be more likely to drop out as study duration increases. To control for this effect, we used the shortest reported study interval. Second, the probability of recurrent caries should increase as duration increases; thus, the probability that the outcome measure is truly cumulative decreases. Incidence would be especially sensitive to increased study duration, since it is measured at the person, not the tooth, level. This may be why Sweden, where the study lasted two years longer than any of the other studies, accounted for 60% of the variation in mean incidence when the Q statistic was calculated for all adjusted studies. Our hypothesis—that confounding due to study duration will be greater for incidence than for increment—is also supported by the higher Q statistic for the adjusted summary measure for all incidence studies than for all increment studies (2.5 times higher). Our findings suggest that older adults experience caries at rates equal to or greater than those in children, the primary recipients of caries-prevention services. For quantification of the benefit of prevention among older adults, further research is needed on the effectiveness of prevention—two recent reviews found few studies conducted among adult populations (Rozier, 2001; Truman et al., 2002)—and treatment costs, which may be substantially higher if adults with more affected surfaces require procedures such as crowns to treat new decay.
We thank Brenda Mazzocchi, CDC Reference Librarian, who conducted all literature searches, Dr. Barbara Gooch for comments made during the preparation of this manuscript, and the National Science Foundation (ESS Award #0223364).
A supplemental appendix to this article is published electronically only at http://www.dentalresearch.org. Received for publication June 6, 2004. Revision received February 18, 2005. Accepted for publication April 25, 2005.
Journal of Dental Research, Vol. 84, No. 8,
715-720 (2005)
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na*sea2 + nb*seb2/na + nb) of the reported groups. 


