ArticlePDF Available

Trajectory Patterns of Dental Caries Experience in the Permanent Dentition to the Fourth Decade of Life

Authors:
Jonathan M Broadbent at University of Otago
Jonathan M Broadbent
William Murray Thomson at University of Otago
William Murray Thomson
R. J. Poulton
R. J. Poulton
R. J. Poulton
  • This person is not on ResearchGate, or hasn't claimed this research yet.
Download full-text PDF
Read full-text
Download citation

Abstract and Figures

Dental caries is a chronic, cumulative disease, but no studies have investigated longitudinal patterns of caries experience. The objective of this study was to identify and describe developmental trajectories of caries experience in the permanent dentition to age 32. Longitudinal caries data for 955 participants in a longstanding birth cohort study were analyzed by trajectory analysis. Three caries experience trajectories were identified by the SAS macro PROC TRAJ; these were categorized as "high" (approximately 15%), "medium" (approximately 43%), and "low" (approximately 42%) DMFS (Decayed, Missing, and Filled Surfaces). All were relatively linear, although the higher trajectories were more "S-shaped". This effect disappeared following adjustment for the number of unaffected surfaces remaining at each age, suggesting that, among individuals following a similar caries trajectory, caries rate is relatively constant across time.
Figures - uploaded by William Murray Thomson
Author content
All figure content in this area was uploaded by William Murray Thomson
Content may be subject to copyright.
Content uploaded by William Murray Thomson
Author content
All content in this area was uploaded by William Murray Thomson
Content may be subject to copyright.
Trajectory Patterns of Dental Caries Experience in the Permanent
Dentition to the Fourth Decade of Life
J.M. Broadbent1,*, W.M. Thomson1, and R. Poulton2
1Department of Oral Sciences, Faculty of Dentistry, University of Otago, Dunedin, New Zealand 2Director,
Dunedin Multidisciplinary Health and Development Research Unit, Department of Preventive and Social
Medicine, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
Abstract
Dental caries is a chronic, cumulative disease, but no studies have investigated longitudinal patterns
of caries experience. The objective of this study was to identify and describe developmental
trajectories of caries experience in the permanent dentition to age 32. Longitudinal caries data for
955 participants in a longstanding birth cohort study were analyzed by trajectory analysis. Three
caries experience trajectories were identified by the SAS macro PROC TRAJ; these were categorized
as “high” (~ 15%), “medium” (~ 43%), and “low” (~ 42%) DMFS (Decayed, Missing, and Filled
Surfaces). All were relatively linear, although the higher trajectories were more “S-shaped”. This
effect disappeared following adjustment for the number of unaffected surfaces remaining at each
age, suggesting that, among individuals following a similar caries trajectory, caries rate is relatively
constant across time.
Keywords
longitudinal study; adult; trajectory analysis; caries
INTRODUCTION
Dental caries is a chronic, cumulative disease, and the caries status of an individual develops
over time. Caries occurs at any stage in life, provided that an individual has susceptible teeth
(and surfaces) remaining. Biological, behavioral, and environmental factors act upon the
dentition throughout life, suggesting that the life-course approach (Ben-Shlomo and Kuh,
2002) is relevant to dental caries epidemiology. However, dental caries epidemiology has rarely
been investigated from the life-course perspective (due, in part, to a paucity of appropriate
data), and statistical approaches to the analysis of such data have, correspondingly, been seldom
discussed in the dental literature. Analyzing differences in the accumulation of caries
experience over time among individuals can be challenging, and the interpretation of such data
is not always straightforward (Härkänen et al., 2002). In the past, many researchers have
defined groups to assist in data analysis on the basis of risk factors or other subjective
classifications; however, such an approach may fail to identify important developmental
patterns (Nagin, 2005).
Latent class analysis is a statistical approach used to group observations (or variables) into
strongly inter-related subgroups (or classes). Latent class analysis is relatively new in health
research, and appears to be a useful tool for evaluating complex developmental data. Thus, it
*corresponding author, jonathan.broadbent@stonebow.otago.ac.nz.
NIH Public Access
Author Manuscript
J Dent Res. Author manuscript; available in PMC 2008 February 25.
Published in final edited form as:
J Dent Res. 2008 January ; 87(1): 69–72.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
provides a new and exciting option for identifying, summarizing, and describing the complex
patterns of findings often generated by life-course studies. While numerous statistical software
applications are available for conducting latent class analysis, not all can deal with longitudinal
data.
‘Group-based trajectory modeling’ is a specialized application of finite mixture modeling, and
can simplify longitudinal data by identifying developmental trajectory groups on a likelihood
basis. It approaches a set of individual trajectories by grouping those which closely resemble
one another (using a probability function). Essentially, the methodology assumes the existence
of unobserved (latent) subpopulations. While these groups do not (necessarily) exist per se,
their identification has applications in both the interpretation and further analysis of
longitudinal data. Dealing with a small number of groups of trajectories is less complicated
than analyzing several hundred individual trajectories (Nagin, 2005). Presentation of
longitudinal findings may be in the form of easily understood graphs and tables, and
determinants of group membership can be more readily investigated. Such data may be more
accessible for clinicians and other non-researchers.
While trajectory analysis is relatively new (Nagin and Land, 1993), it has already been used
extensively in longitudinal social research (Nagin and Tremblay, 2005). In psychology, the
term ‘developmental trajectory’ is used to describe the course of a behavior or outcome over
age or time. Such a term (or one such as ‘disease trajectory’) could also be applied to the
progression over time of a cumulative disease, such as dental caries.
Utilizing group-based trajectory analysis, we investigated the natural history of dental caries
experience in a birth cohort from childhood until the middle years of life. This research will
be particularly useful in determining whether (at the population level) high-risk periods for
dental caries exist—a ‘critical period’ of risk such as, for example, the teenage years (Carlos
and Gittelsohn, 1965)—or whether a cumulative increase in caries experience over time is
relatively constant, suggesting that risk does not vary with age (Ben-Shlomo and Kuh, 2002).
METHODS
The Dunedin Multidisciplinary Health and Development Study (DMHDS) is a longitudinal
study of a birth cohort of children who were born at the Queen Mary Hospital, Dunedin, New
Zealand, between 1st April 1972 and 31st March 1973 (Silva and Stanton, 1997). Perinatal
data were obtained, and the sample for the longitudinal study was first followed up at age 3
yrs (N = 1037), and again at ages 5, 7, 9, 11, 13, 15, 18, 21, 26, and, most recently, at 32 yrs.
The current study uses data collected from dental examinations at ages 5, 9, 15, 18, 26, and 32
yrs. The Otago Ethics Committee granted ethics approval for each assessment phase. Over
90% of the cohort self-identify as being of European origin. Study participants gave informed
consent prior to inclusion.
Measurement of Dental Caries
At each age, dental examinations for caries and missing teeth were conducted by calibrated
examiners. Before each examination, recording sheets were adjusted to account for teeth that
had been missing at the previous assessment. Teeth were examined for dental caries and
restorations, with 4 surfaces (buccal, lingual, distal, and mesial) being considered for canines
and incisors, and a fifth surface (the occlusal) included for premolars and molars. In a small
number of cases where a surface could not be visualized by the examiner, the surface was
excluded from the examination (and later analyses). We obtained an estimate of accumulated
tooth loss due to caries by observing the presence or absence of each tooth, and by ascertaining
the reason for its absence at that age by asking the participant at the time of each examination.
Broadbent et al. Page 2
J Dent Res. Author manuscript; available in PMC 2008 February 25.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Repeat examinations were not possible, because of the logistical constraints imposed by the
tightly scheduled assessment that study participants underwent. Dental examiners were not
aware of study participants’ socio-economic status (SES) or questionnaire responses at the time
of the examinations. Further information on these assessments is available in previous
publications (Suckling et al., 1985; Thomson et al., 2000; Broadbent et al., 2006).
Data Analysis
We used surface-level dental examination data to compute DMFS (Decayed, Missing, and
Filled Surfaces). For the ‘M’ component of DMFS, a minimum of 3 surfaces was assigned as
having been carious for each extracted tooth (Broadbent and Thomson, 2005). Where more
than 3 surfaces (4 or 5) were known to have been carious at the most recent assessment prior
to the extraction of the tooth, this number was used. For example, DMFS scores for teeth which
were missing at age 26 due to caries were adjusted by their surface status at age 18 (if present),
while teeth which were missing due to caries at age 32 were adjusted by their surface status
only from age 26. In this study, only teeth which had been lost because of caries are included
in the estimations of tooth loss due to caries, and in the ‘M’ component of DMF scores.
Group-based trajectory analysis was performed with the PROC TRAJ macro in SAS version
9.1 (Jones et al., 2001). To enable a single measure of dental caries experience to be used for
the trajectory model, the modified DMFS was used, as described above. The modified measure
is preferable in this instance to either DFS or generally accepted DMFS (where each missing
tooth is presumed to have been completely decayed prior to extraction), since it is very likely
that those measures provide under- and overestimates of true caries experience, respectively
(Broadbent and Thomson, 2005). Data analysis was restricted to those study participants for
whom dental data were available from at least 3 assessment ages. The PROC TRAJ macro
assumes that missing data are missing completely at random, and the model is adjusted so that
missing observations do not contribute to the sample size or analytical outcome.
The parameters for the trajectory model were determined on a maximum-likelihood basis by
a general quasi-Newton method (Dennis et al., 1981; Jones and Nagin, 2005). In the interests
of parsimony, a three-group trajectory analysis model was defined (Table). The Bayesian
Information Criterion (BIC) is a tool which is often used in model selection; however, in
trajectory analysis, the BIC does not always clearly identify a preferred number of groups.
Selection of that number must balance the interests of parsimony with the objective of reporting
the distinctive developmental patterns in the data. The objective of model selection is not the
maximization of some statistic of model fit; rather, it is to summarize the distinctive features
of the data in as parsimonious a fashion as possible (Nagin, 2005).
We defined the order of the two resultant groups with the greatest experience of dental caries
over time as having cubic trajectories, while the group with the lowest disease experience was
allocated a linear trajectory. This combination was determined by visual inspection of the
shapes of the trajectory plots, and by adjustment of the parameters to maximize the BIC within
the three-group model.
Since it is not yet possible to fit models in PROC TRAJ according to the zero-inflated negative
binomial (ZINB) distribution, the zero-inflated Poisson (ZIP) model was used instead as a
reasonably acceptable alternative (Lewsey and Thomson, 2004). The degree of zero-inflation
for the ZIP model was determined with the BIC. At all ages, the analysis was restricted to the
permanent teeth, since the primary teeth constitute a discrete dentition. Age-5 dental data were
included, because 46 of the 878 participants at that age had had at least 1 permanent tooth
erupted, but none had yet experienced caries. Thus, age 5 served as a ‘zero point’ for dental
caries experience.
Broadbent et al. Page 3
J Dent Res. Author manuscript; available in PMC 2008 February 25.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Plot data were generated by means of the macro ‘TRAJPLOT’. To reinforce the model and
trajectory plots produced, we calculated 95% confidence intervals through the macro
‘TRAJPLOTNEW’. Standard errors for the mean trajectories were calculated according to a
first-order Taylor series expansion (Jones and Nagin, 2005). Plot data were exported into (and
plotted in) Intercooled Stata 8.0 (Stata Corporation, College Station, TX, USA). The percentage
of caries-affected surfaces was computed at each age within each trajectory group, and this
was also plotted.
RESULTS
Participation rates in the Dunedin Study have remained high, with 972 study individuals (96%)
participating at age 32 yrs, and 932 (92%) participating in the dental examination. Dental caries
data were available for 955 individuals at 3 or more of the 6 dental assessment ages, and the
following analyses are restricted to those individuals. The 82 excluded individuals included
48 males (9.0%) and 34 females (6.8%).
The individual caries trajectories were plotted (Fig. 1), and through the trajectory group
assignment based on the PROC TRAJ macro, 384 participants (40.2%) were assigned to ‘group
1’, 427 (44.7%) to ‘group 2’, and 144 (15.1%) to ‘group 3’. These were designated the ‘low’,
‘medium’, and ‘high’ trajectory groups, respectively. When DMFS data by trajectory group
were plotted against age, the mean DMFS scores of trajectory groups were seen to diverge with
increasing age (Fig. 2). By age 32, the mean DMFS was 5.4 (SD 3.7) in group 1, 18.6 (SD 6.8)
in group 2, and 42.3 (SD 12.7) in group 3. On average, 36.9% of tooth surfaces in trajectory
group 3 had been affected by caries by age 32. At the group level, the plot of the percent of
caries-affected surfaces (of those permanent teeth present in the mouth) revealed no period of
rapid increase in DMF (Fig. 3).
The prevalence of tooth loss was greatest in the two higher trajectory groups. None of the
participants had lost teeth due to caries by the age of 18 yrs. By age 26, 0.6% of participants
in the low DMFS trajectory, 13.2% in the medium DMFS trajectory, and 33.3% in the high
trajectory for DMFS had lost teeth due to caries, with a mean 0.0, 0.3, and 0.7 teeth lost,
respectively. By age 32 yrs, the prevalence of tooth loss due to caries had increased in all
groups, to 5.9% in the low trajectory, 28.4% in the medium, and 53.8% in the high trajectory,
with a mean 0.1, 0.7, and 2.2 teeth lost, respectively.
DISCUSSION
The Dunedin Study remains the only dental study to have followed a group of individuals from
birth to adulthood. Our use of group-based trajectory analysis appears to be a valid approach
to exploring developmental trajectories; the technique has the added advantage of being simple
to interpret. The trajectory groupings are a useful statistical device for capturing the essential
features of the underlying complex reality of the longitudinal caries data-set.
A possible weakness of this study is that we have chosen to limit our analyses of possible
determinants of trajectory group membership (at this stage), and have not yet considered any
potential confounding variables. From an analytical standpoint, it is important to remember
that the trajectory ‘groups’ do not exist in the real sense; they are an analytical convenience.
Furthermore, several alternative programs are available for estimation of such latent classes
(PROC TRAJ, MPlus, and LatentGold), and the outcomes of latent class analyses may differ
according to the precise estimation parameters that are specified. PROC TRAJ (which we have
used) does not consider growth factor variances within trajectory classes, while the alternative
program MPlus does. This consideration is important theoretically, since it may affect the
trajectory group membership of a few cases; however, it is unlikely that including such
Broadbent et al. Page 4
J Dent Res. Author manuscript; available in PMC 2008 February 25.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
variation would materially affect the overall outcome (and associated inferences) of the
analysis.
Trajectory analysis appears to be a useful and valid descriptive tool in the investigation of
caries experience across the life-course, and can aid in the recognition of patterns (or
trajectories) of caries experience over time. In this study, the two higher trajectory plots were
S-shaped (or cubic), while the lowest trajectory was linear. Teeth were lost at a proportionally
greater rate among participants following higher trajectories, thus decreasing the number of
surfaces available and ‘at risk’ to caries in the mouth over time. The rate of increase in %-
DMFS appeared to be linear in all trajectory groups, with no apparent drop-off in the rate of
increase in %-DMFS with increasing age. Thus, analysis of our data does not support the
commonly held belief among dentists that childhood and adolescence are periods of special
risk for dental caries, or that caries ‘immunity’ may be acquired during late adolescence or
early adulthood (Carlos and Gittelsohn, 1965). In this population at least, new caries appears
to be occurring at a relatively constant rate, implying that for greatest benefit, caries-preventive
measures are necessary at all stages of the life-course.
Acknowledgements
Jonathan Broadbent and the dental study are supported by Grant R01 DE-015260-01A1 from the National Institute
of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD 20892, USA. We thank study founder
Phil Silva, Harvey Brown, and all those involved in the administration of the Study. The Dunedin Study would not
be possible but for the ongoing participation of the Study members. The Health Research Council of New Zealand
(previously the Medical Research Council), the New Zealand Department of Education, the New Zealand Department
of Health, the National Children’s Health Research Foundation, and the Dental Research Foundation of New Zealand
provided funding for the assessments.
References
Ben-Shlomo Y, Kuh D. A life course approach to chronic disease epidemiology: conceptual models,
empirical challenges and interdisciplinary perspectives. Int J Epidemiol 2002;31:285–293. [PubMed:
11980781]
Broadbent JM, Thomson WM. For debate: problems with the DMF index pertinent to dental caries data
analysis. Community Dent Oral Epidemiol 2005;33:400–409. [PubMed: 16262607]
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;40:459–465. [PubMed: 17063015]
Carlos JP, Gittelsohn AM. Longitudinal studies of the natural history of caries - II. Arch Oral Biol
1965;10:739–751. [PubMed: 5226906]
Dennis JE, Gay DM, Welsch RE. An adaptive nonlinear least-squares algorithm. ACM Trans
Mathematical Software 1981;7:348–368.
Härkänen T, Larmas MA, Virtanen JI, Arjas E. Applying modern survival analysis methods to
longitudinal dental caries studies. J Dent Res 2002;81:144–148. [PubMed: 11827260]
Jones BL, Nagin DS. Advances in group-based trajectory modeling and a SAS procedure for estimating
them. Ann Am Acad Pol Soc Sci 2005;602:82–117.
Jones BL, Nagin DS, Roeder K. A SAS procedure based on mixture models for estimating developmental
trajectories. Sociol Methods Res 2001;29:374–393.
Lewsey JD, Thomson WM. The utility of the zero-inflated Poisson and zero-inflated negative binomial
models: a case study of cross-sectional and longitudinal DMF data examining the effect of
socioeconomic status. Community Dent Oral Epidemiol 2004;32:183–189. [PubMed: 15151688]
Nagin, DS. Group-based modelling of development. Cambridge, MA: Harvard University Press; 2005.
Nagin DS, Land KC. Age, criminal careers, and population heterogeneity: specification and estimation
of a nonparametric, mixed Poisson model. Criminology 1993;31:327–362.
Nagin DS, Tremblay RE. What has been learned from group-based trajectory modeling? Examples from
physical aggression and other problem behaviours. Ann Am Acad Pol Soc Sci 2005;602:82–117.
Broadbent et al. Page 5
J Dent Res. Author manuscript; available in PMC 2008 February 25.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Silva, PA.; Stanton, WR. From child to adult: the Dunedin Multidisciplinary Health and Development
Study. USA: Oxford University Press; 1997.
Suckling GW, Brown RH, Herbison GP. The prevalence of developmental defects of enamel in 696 nine-
year-old New Zealand children participating in a health and development study. Community Dent
Health 1985;2:303–313. [PubMed: 3866632]
Thomson WM, Poulton R, Kruger E, Boyd D. Socio-economic and behavioural risk factors for tooth loss
from age 18 to 26 among participants in the Dunedin Multidisciplinary Health and Development
Study. Caries Res 2000;34:361–366. [PubMed: 11014902]
Broadbent et al. Page 6
J Dent Res. Author manuscript; available in PMC 2008 February 25.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Figure 1.
Simple join of DMFS scores by age (from the Dunedin Multidisciplinary Health and
Development Study database).
Broadbent et al. Page 7
J Dent Res. Author manuscript; available in PMC 2008 February 25.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Figure 2.
Trajectory plot of mean DMFS scores for three-group caries trajectory analysis model.
Broadbent et al. Page 8
J Dent Res. Author manuscript; available in PMC 2008 February 25.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Figure 3.
Plot of mean percentage of at-risk surfaces affected by caries over time for three-group caries
trajectory analysis model.
Broadbent et al. Page 9
J Dent Res. Author manuscript; available in PMC 2008 February 25.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Broadbent et al. Page 10
Table
Trajectory Model Selection Criteria
BIC*Percent Change in BIC for +1 Group AIC
1 group −19528 −19512
2 groups −13165 −32.6 −13126
3 groups −11669 −11.4 −11607
4 groups −11026 −5.5 −10941
5 groups −10850 −1.6 −10743
6 groups −10748 − 0.9 −10618
7 groups −11401 +6.1 −11248
8 groups −11339 −0.5 −11163
9 groups −11378 +0.3 −11180
*BIC, Bayesian Information Criterion; AIC, Akaike Information Criterion.
J Dent Res. Author manuscript; available in PMC 2008 February 25.
... The longest birth cohort study of caries experience in adulthood was born in Dunedin, New Zeeland, in 1972 [14,15]. The study population was assigned to one of three caries development trajectories reflecting population differences in caries occurrence [16,17]. Using group-based trajectory analysis to investigate the natural history of dental caries experience from childhood to middle-age showed that 15% of the population had the highest caries experience, 45% had low or limited caries, and 40% had almost no caries. ...
... The three-trajectory caries model described by Broadbent et al. in the Dunedin study [16,17] was previously used to analyse two cohorts of SKaPa data (the 30-and 40-year-old groups) [20], with consistent findings regarding identifying individuals with the highest caries experience over time. ...
... The group-based trajectory modelling used in the Dunedin cohort [16], is a specialised application of finite mixture modelling. This approach simplifies analyses of longitudinal data by identifying developmental trajectory groups on a likelihood basis; this involves approaching a set of individual trajectories by grouping those that closely resemble one another using a probability function. ...
Identification of Swedish caries active individuals aged 30-90 years using a life course perspective and SKaPa longitudinal national registry data over a 10-year period
Article
Full-text available
  • Jun 2024
  • ACTA ODONTOL SCAND
Objective: To describe the occurrence of caries disease from a life course perspective using longitudinal data from the Swedish Quality Registry for Caries and Periodontal Disease (SKaPa). Material and Methods: Data from seven age cohorts (ages 30-90 years), each followed over 10 years, were retrieved from the SKaPa. Using a three-trajectory model, individuals were divided into three trajec-tories according to their caries development over time: high (15%), moderate (45%), or low (40%). Caries experience was expressed as the mean decayed, missing, and filled surfaces (DMFS) index. Results: Significant differences were found for all three trajectories and in all age groups over the 10 years. The mean DMFS index increase was significantly larger for the high trajectory group than for the moderate and low trajectory groups across all age cohorts. An increase in caries experience was observed for the older cohorts across all trajectories. Conclusions: A three-trajectory model appears useful for identifying and quantifying caries experiences in longitudinal studies. Increased caries disease occurs over time, especially in the highest trajectory group and among older cohorts. These findings emphasise the need for greater attention and more efficient caries prevention methods. ARTICLE HISTORY
View
... [6][7][8] Furthermore, a gradient in the occurrence of dental caries with increasing age has been observed. 9 Thus, there is a need to monitor the changes and trends in the prevalence of dental caries considering chronological age and different time periods. ...
... This aspect is particularly important in early childhood, once caries experience at this phase is a strong predictor of dental caries throughout the life course. 9 Thus, this study aimed to verify trends in the prevalence of dental caries in preschool children and associated factors considering the age-period-cohort effects. ...
... It is well stablished in the literature that there is a notable gradient in caries occurrence as age increases. 9 Our study found similar results, indicating that 5-year-olds are about six times more likely to have caries when compared to 1-year-olds. A possible explanation for this finding is the higher number of teeth exposed to risk factors according to eruption chronology and age of such exposure. ...
Trends and age-period-cohort effect on dental caries prevalence from 2008 to 2019 among Brazilian preschoolers
Article
Full-text available
  • Jan 2024
  • Braz Oral Res
This study aimed to evaluate trends in the prevalence of dental caries in preschool children and associated factors considering different time variations. This is a time series study performed using data from three cross-sectional studies with pre-school children from southern Brazil in 2008, 2013 and 2019. This children group was born between the years of 2003 to 2018. Dental caries was evaluated by decayed, missing and filled deciduous teeth (dmft index). Demographic, socioeconomic, behavioural and psychosocial variables were also collected. Chi-square test for trends and a hierarchical age-period-cohort (HAPC) analysis using multilevel Poisson regression model for testing the associations between predictor variables and dental caries experience were used. A total of 1,644 pre-school children participated in all surveys. There was a significant difference in caries experience considering all APC effects. The prevalence of dental caries was 25.0% in 2008, 16.3% in 2013, and 19.4% in 2019 (p < 0.01) and no statistical difference was observed. An age effect showed that older children were more likely to experience dental caries. Considering the cohort effect, there is a significant difference between the generations, mainly between 2003 and 2018. Household income, use of dental services, and parent's perception of child oral health were associated with dental caries experience no matter the time variation. Despite recent declines in dental caries prevalence among preschool children, caries levels increased with age and social inequalities persisted through the years, indicating a need of reviewing the policies to reduce the burden of this oral disease.
View
... although cross-sectional as well as longitudinal studies describe caries experience among children and teenagers [3], similar studies for adults are rare, even though the disease continues to affect patients throughout adulthood. the available data indicate that individuals with active caries disease continue to be caries active for many years [4][5][6][7]. however, national oral health surveys are complex and costly to conduct, and therefore seldom performed [2]. this lack of up-to-date epidemiologic data limits the development of appropriate approaches to reduce the burden of disease imposed by dental caries [2,8]. ...
... the largest longitudinal birth cohort of caries experience among adults is the Dunedin (New Zealand) cohort, which began in 1972 [12,13]. the observed population was divided into three different caries development trajectories [4,7].the group with the greatest caries experience (15%) presented with recurring caries disease, whereas 45% presented with low or limited caries development, while 40% had almost no caries development. the obvious difference in mean DMFs index between the described trajectories provides important information about the differences in caries experience. ...
... the current study aims to identify caries-active individuals among 30-and 40-year-olds by analyzing longitudinal general population-based data from sKaPa and to compare these results divided into three different caries development trajectories as described previously for the Dunedin cohort [4,7]. Our hypothesis is that the group with the highest caries experience, expressed as mean DMFs index, will be of similar proportions in the two different sKaPa age groups using the three-trajectory model when compared with the Dunedin data. ...
Identification of caries-active individuals in longitudinal data a methodological study using a national registry
Article
Full-text available
  • Oct 2023
  • ACTA ODONTOL SCAND
Objective: The aim was to identify caries active individuals among adults by using a trajectory model of longitudinal data from the Swedish national registry (SKaPa) and comparing them with published data from the Dunedin cohort. Materials and methods: Data from two different age groups (30- and 40-year-olds) followed for 10 years were retrieved from SKaPa and were compared with published longitudinal birth-cohort data from the Dunedin study. Using the trajectory model, the subjects were divided into three different trajectories according to their caries development over time (i.e. high, 15%; moderate, 45%; low, 40%). Results: Caries experience, as measured by mean decayed, missing, and filled surfaces (DMFS) index, revealed significant differences among the three trajectories in both age groups. The patterns were similar to those observed in the Dunedin cohort. The mean increase in DMFS during the 10-year follow-up period from SKaPa was significantly higher for the high trajectories in both age groups compared with the moderate and low trajectories. Conclusions: The method using three trajectories for presentation of caries experience over time, may be a useful tool to identify subjects with different disease activities. Identification of subjects in the high caries experience trajectory may increase the possibility to explore and evaluate more effective caries prevention for this group in the future.
View
... Therefore, experimental studies assessing the effects of community-level interventions on sugar reduction, and consequent oral health improvements, are needed. Despite the anticaries effect of fluoride and its widespread availability in water and toothpaste (and in some communities, through professionally applied fluoride), caries levels increase as people age [34]. Thus, strategies to control caries without tackling sugar intake is deemed to failure. ...
... Thus, even believing that fluoride in the toothpaste is the main reason for current low caries levels [40] does not allow one to disregard sugar as the major cause of caries in the rich western countries. Millions of people exposed to fluoridated toothpaste in these countries develop caries, and the number of decayed teeth increases significantly with age [34,35]. ...
Randomized Controlled Trials in Dental Public Health
Chapter
  • Apr 2024
Dental public health (DPH) is the science and art of preventing and controlling dental diseases and promoting dental health through organized community efforts. Some themes, such as sugar, fluoride, and dental sealants, are central to DPH and were the focus of clinical, field, and community intervention trials. We selected some of them in order to illustrate the importance of the epidemiological experimental studies for DPH. Randomized controlled trials (RCTs) should focus on outcomes that are clinically relevant to patients instead of surrogate outcomes. When reporting the results of RCTs, authors should use absolute numbers, report the base rate and avoid relative measures, such as the prevented fraction. All types of RCTs play an important role in DPH; however, community intervention trials are better suited for addressing questions related to population health. The 2019 Nobel Prize in Economics was won by three economists who used RCTs to determine how best to lift people out of poverty and improve their health. This is an excellent illustration of the power of the RCT to investigate the effectiveness of public policies and should serve as an inspiration for DPH researchers.
View
... A large longitudinal study, however, the Dunedin Multidisciplinary Health and Development Study [34], has also assessed caries progression between the age of 15 and 32 years, as we did, along with other age points. In this study, different trajectories were identified where 15.1% of the participants were assigned to a high (DMFS = 42.3 ± 12.7), 44.7% to a medium (DMFS = 18.6 ± 6.8) and 40.2% to a low trajectory group (DMFS = 5.4 ± 3.7). ...
Caries and white spot lesion trajectories of orthodontic patients across an observation period of 20 years
Article
Full-text available
  • Jun 2024
  • CLIN ORAL INVEST
Objectives Fixed orthodontic appliances may increase the risk for caries and white spot lesions. The aim of this retrospective study was to determine the long-term associations between both in orthodontic patients. Materials and methods 103 patients aged 36.6 ± 6.5 years whose fixed appliance orthodontic treatment had finished at least 15 years ago were included. Current clinical data and photographs (T3), panoramic x-ray and photographs from before treatment (T0), after debonding (T1) and at 2-year follow-up (T2) were available. Parameters of interest were dentine caries, “Missing/Filled Teeth” (MFT), “White Spot Lesion” (WSL) index and “Periodontal Screening and Recording” index (PSR; T3 only). Results At T0, 30.4% had no caries experience decreasing to 25.6%, 22.4% and 6.8% at T1, T2 and T3 resp. The median MFT (95% CI) at T0, T1, T2 and T3 was 2 (1;3), 3 (2;4), 3 (2;4) and 7 (6;9) resp. increasing significantly at each time point (p < 0.001 each); 30.1% had WSL at debonding. Patients with caries experience at T0 had a 2.4-fold increased risk of WSL at debonding. Dentine caries, caries experience and WSL at T1 were significantly associated with incident caries at T2, but not at T3. PSR at T3 had a significant association with previous caries incidence and WSL. Conclusions Caries experience prior to orthodontic treatment may constitute a risk indicator for WSL, and caries experience and WSL at its end for caries incidence in the near term. Clinical Relevance Present caries and WSL may help identifying orthodontic patients with special need for prevention and counselling.
View
... and toothpaste to clean their teeth, and only about 28% brush their teeth twice a day. 3 It is well evident that dental caries is a lifetime disease and new caries appears to be occurring at a relatively constant rate, implying that for greatest benefit, caries-preventive measures are necessary at all stages of the life course. 4 Healthy behaviors, such as daily toothbrushing, should be introduced at an early age, and school is a promising setting to induce such healthy habits from childhood. 5 Supervised toothbrushing (STB) programs in school settings over 2 years can establish lifelong behavior, thus promoting oral health and reducing the dental disease burden. ...
Modeling the cost-effectiveness of school-based supervised toothbrushing program in reducing the dental caries burden in India
Article
  • May 2024
  • INT J PAEDIATR DENT
Background: Supervised toothbrushing (STB) significantly reduces the incidence and progression of dental caries. School years present a favorable age for introducing such healthy habits for a lifetime. Aim: To estimate the cost-effectiveness of implementing a STB program in India in preventing dental caries incidence. Design: An operational framework of a national STB program was devised. A mathematical model was then developed to evaluate this program's clinical effectiveness and economic impact in the Indian scenario. This study considered a hypothetical cohort of the Indian population aged from 6 to 75 years. Two groups were compared: no intervention and STB in government schools. The health outcomes assessed were a number of tooth caries incidences averted and quality-adjusted life years gained. Results: The STB program in the government schools of India would prevent at least one tooth from developing caries in an individual's lifetime. Considering the current treatment-seeking behavior, the STB program saves INR 153 (US$ 1.95) per carious tooth incidence averted and INR 22 202 (US$ 283) per QALY gained. Conclusion: In India, the school-based STB program is expected to be a cost-effective strategy for reducing the dental caries burden and its associated treatment costs.
View
... Despite being preventable, dental caries is the most common oral disease affecting millions of young children worldwide [2]. Children with caries in their primary teeth are more prone to developing oral diseases and other health problems later in life [3]. In addition to the health effects, caries may burden a young child's quality of life, leading to high costs for families and society [4]. ...
Understanding parental perspectives on young children’s oral health (≤ 4 years) growing up in a disadvantaged neighbourhood of Amsterdam, the Netherlands: an exploratory study
Article
Full-text available
  • Feb 2024
  • BMC PUBLIC HEALTH
Background Families’ understanding towards oral health problems among young children is poorly studied. More insight into parents’ experiences, especially of those living in disadvantaged neighbourhoods, is needed to address persistent oral health inequalities. This qualitative study aims to explore parental perspectives on children’s oral health (≤ 4 years) and the opportunities they see to improve children’s oral health. Methods Forty-seven mothers and five fathers with different migration backgrounds from a disadvantaged neighbourhood in Amsterdam, the Netherlands, participated in our study. Semi-structured interviews (n = 27), participant observations (n = 7) and one focus group discussion were conducted. A thematic data analysis was used. Results Parents describe their daily life with young children as busy, hectic and unpredictable. Parents seem to be most concerned about parenting. Mothers, in particular, feel fully responsible for raising their children and managing daily complexities. While most parents value their children’s oral health, they all experience challenges. Parents find it hard to limit daily candy intake and to handle unwilling children during tooth brushing. They feel limited support for these issues from their household, social network and professionals. Conclusion Parental struggles in children’s oral health are complex and interrelated as they occur across family, societal, community and professional levels. Given the complex daily reality of families with young children, establishing and maintaining healthy oral health habits seems not at the top of parents’ minds. They ask for advice in the upbringing of their children backed up by social support, increased attention to children’s oral health within the community and professional assistance. Collaborating with parents as knowledgeable partners might be the first step in acting upon the endeavour to address oral health inequality among young children.
View
... It is considered an international public health problem since more than 80% of the world's population is affected. It is a pathology with a cumulative effect that develops from childhood to adulthood (Broadbent et al., 2008). Furthermore, it is the most prevalent chronic infectious disease in children. ...
View
Effect of fluoridated water on invasive NHS dental treatments for adults: the LOTUS retrospective cohort study and economic evaluation
Article
  • May 2024
Background Most water fluoridation studies were conducted on children before the widespread introduction of fluoride toothpastes. There is a lack of evidence that can be applied to contemporary populations, particularly adolescents and adults. Objective To pragmatically assess the clinical and cost effectiveness of water fluoridation for preventing dental treatment and improving oral health in a contemporary population of adults, using a natural experiment design. Design Retrospective cohort study using routinely collected National Health Service dental claims (FP17) data. Setting National Health Service primary dental care: general dental practices, prisons, community dental services, domiciliary settings, urgent/out-of-hours and specialised referral-only services. Participants Dental patients aged 12 years and over living in England ( n = 6,370,280). Intervention and comparison Individuals exposed to drinking water with a fluoride concentration ≥ 0.7 mg F/l between 2010 and 2020 were matched to non-exposed individuals on key characteristics using propensity scores. Outcome measures Primary: number of National Health Service invasive dental treatments (restorations/‘fillings’ and extractions) received per person between 2010 and 2020. Secondary: decayed, missing and filled teeth, missing teeth, inequalities, cost effectiveness and return on investment. Data sources National Health Service Business Services Authority dental claims data. Water quality monitoring data. Primary outcome Predicted mean number of invasive dental treatments was 3% lower in the optimally fluoridated group than in the sub/non-optimally fluoridated group (incidence rate ratio 0.969, 95% CI 0.967 to 0.971), a difference of −0.173 invasive dental treatments (95% CI −0.185 to −0.161). This magnitude of effect is smaller than what most stakeholders we engaged with ( n = 50/54) considered meaningful. Secondary outcomes Mean decayed, missing and filled teeth were 2% lower in the optimally fluoridated group, with a difference of −0.212 decayed, missing and filled teeth (95% CI −0.229 to −0.194). There was no statistically significant difference in the mean number of missing teeth per person (0.006, 95% CI −0.008 to 0.021). There was no compelling evidence that water fluoridation reduced social inequalities in treatments received or missing teeth; however, decayed, missing and filled teeth data did not demonstrate a typical inequalities gradient. Optimal water fluoridation in England in 2010–20 was estimated to cost £10.30 per person (excluding original setup costs). Mean National Health Service treatment costs for fluoridated patients 2010–20 were 5.5% lower per person, by £22.26 (95% CI −£23.09 to −£21.43), and patients paid £7.64 less in National Health Service dental charges per person (2020 prices). Limitations Pragmatic, observational study with potential for non-differential errors of misclassification in fluoridation assignment and outcome measurement and residual and/or unmeasured confounding. Decayed, missing and filled teeth data have not been validated. Water fluoridation cost estimates are based on existing programmes between 2010 and 2020, and therefore do not include the potentially significant capital investment required for new programmes. Conclusions Receipt of optimal water fluoridation between 2010 and 2020 resulted in very small health effects, which may not be meaningful for individuals, and we could find no evidence of a reduction in social inequalities. Existing water fluoridation programmes in England produced a positive return on investment between 2010 and 2020 due to slightly lower National Health Service treatment costs. These relatively small savings should be evaluated against the projected costs and lifespan of any proposed capital investment in water fluoridation, including new programmes. Future work National Health Service dental data are a valuable resource for research. Further validation and measures to improve quality and completeness are warranted. Trial registrations This trial is registered as ISRCTN96479279, CAG: 20/CAG/0072, IRAS: 20/NE/0144. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: NIHR128533) and is published in full in Public Health Research ; Vol. 12, No. 5. See the NIHR Funding and Awards website for further award information.
View
Role of diet and dietary habits in causing dental caries among adults reporting to a tertiary care hospital in Pakistan; a case-control study
Article
  • Nov 2023
Objective To determine the association of diet and dietary practices with dental caries among adults. Design A case-control study. Setting Operative Department, Rawal Institute of Health Sciences, Islamabad, Pakistan. Participants 300 participants of both genders, aged 25–50 years. Interventions A food frequency questionnaire and a patient proforma were used to determine the frequency and preferences of diet and dietary habits that may be associated with dental caries among adults, respectively. The diet and dietary habits of 150 adults with caries (cases) were compared with those of 150 adults without dental caries (control). An independent sample T-test was applied to determine the difference in mean age. Mann-Whitney and Chi-Square tests were applied to determine the significance of diet and dietary habits respectively. Multivariate logistic regression analysis determined the odd ratio change in significant variables. P-value ≤0.05 was considered significant. Results Refined sugar (p-value = 0.69), fruit juices (p-value = 0.45), carbonated beverages (p-value = 0.91), duration of consumption of sugary food (p-value = 0.07), and frequency of brushing (p-value = 0.15) were not found to be significantly associated with dental caries in adults. The gender (p-value = 0.02), preferred time for eating sugary foods (p-value <0.001), smoking (p-value <0.001), and tea consumption (p-value = 0.02) were found to be significantly associated with dental caries. Conclusion Adults who regularly consumed sugar as a snack other than regular mealtimes were more likely to be associated with dental caries. Men, smokers, and adults who frequently took shots of sugar with their tea were more likely to be associated with dental caries.
View
A SAS Procedure Based on Mixture Models for Estimating Developmental Trajectories
Article
Full-text available
  • Feb 2001
This article introduces a new SAS procedure written by the authors that analyzes longitudinal data (developmental trajectories) by fitting a mixture model. The TRAJ procedure fits semiparametric (discrete) mixtures of censored normal, Poisson, zero-inflated Poisson, and Bernoulli distributions to longitudinal data. Applications to psychometric scale data, offense counts, and a dichotomous prevalence measure in violence research are illustrated. In addition, the use of the Bayesian information criterion to address the problem of model selection, including the estimation of the number of components in the mixture, is demonstrated.
View
Applying Modern Survival Analysis Methods to Longitudinal Dental Caries Studies
Article
  • Feb 2002
Before the 1960s, tooth-specific caries risk was reported to be highest at 2 to 4 years after eruption. We studied the tooth-specific caries risk in three contemporary age cohorts in Finland. All together, 4072 boys and girls were followed annually from age 6 to age 18+ years in three age cohorts born in the 1960s, 1970s, and 1980s. We used a survival model and Bayesian inferential methods in the statistical analyses to establish the secular changes during this period. The analysis was based on the caries risk in individual teeth as a function of tooth age instead of summary measures, such as DMFS values. Our first finding was a marked overall decrease of caries. Moreover, analyses of the 1960 and 1970 cohorts revealed that the risk in molar teeth was highest immediately after eruption; in the youngest cohort, however, the risks of individual teeth were so low that no such dependencies on tooth age could be established.
View
View
View
Advances in Group-Based Trajectory Modeling and an SAS Procedure for Estimating Them
Article
  • May 2007
This article is a follow-up to Jones, Nagin, and Roeder (2001), which described an SAS procedure for estimating group-based trajectory models. Group-based trajectory is a specialized application of finite mixture modeling and is designed to identify clusters of individuals following similar progressions of some behavior or outcome over age or time. This article has two purposes. One is to summarize extensions of the methodology and of the SAS procedure that have been developed since Jones et al. The other is to illustrate how group-based trajectory modeling lends itself to presentation of findings in the form of easily understood graphical and tabular data summaries.
View
What Has Been Learned from Group-Based Trajectory Modeling? Examples from Physical Aggression and Other Problem Behaviors
Article
  • Nov 2005
The focus of this article is group-based trajectory modeling. Its purpose is threefold. The first is to clarify the proper statistical interpretation of a trajectory group. The second is to summarize some key findings on the developmental course of aggression and other problem behaviors that have emerged from the application of group-based trajectory models and that in the authors' judgment are important to the fields of developmental criminology and developmental psychopathology. The third is to lay out some guidelines on the types of problems for which use of group-based trajectory modeling may be particularly productive.
View
Age, Criminal Careers, and Population Heterogeneity: Specification and Estimation of a Nonparametric, Mixed Poisson Model
Article
  • Mar 2006
  • CRIMINOLOGY
This article addresses three issues that are central to the criminal career debate. First, is the life course of individual offending patterns marked by distinctive periods of quiescence? Second, at the level of the individual, do offending rates vary systematically with age? In particular, is the age-crime curve single peaked or flat? Third, are chronic offenders different from less active offenders? Do offenders themselves differ in systematic ways? Using a new approach to the analysis of individual criminal careers—based on nested, mixed Poisson models in which the mixing distribution is estimated nonparametrically—we analyze a panel data set that tracks a sample of males for more than 20 years. Our results provide empirical evidence in support of some features of criminal propensity theory and some in support of conventional criminal careers theory. In support of latent-trait criminal propensity theory, the individual-level average offense rate (per unit of time) varies as a function of observable individual-level characteristics and unobservable heterogeneity among individuals, and the age trajectory of the offense rate is generally single peaked rather than flat. On the other hand, in support of conventional criminal careers theory, models that incorporate a parameter that permits periods of active as well as inactive offending across age have greater explanatory power than those that do not. In addition, the nonparametric, discrete approximation to the population distribution of unobservable heterogeneity in the individual-level mean offense rate facilitates identification of four classes of offenders—nonoffenders as well as individual-level characteristics that are unique to each group. Problems of theoretical explanation and empirical generalizability of these results are described.
View
An Adaptive Nonlinear Least-Squares Algorithm
Article
  • Sep 1981
NL2SOL is a modular program for solving nonhnear least-squares problems that incorporates a number of novel features. It maintains a secant approximation S to the second-order part of the leastsquares Hessian and adaptively decides when to use this approximation. S is "sized" before updating, something that is similar to Oren-Luenberger scaling. The step choice algorithm is based on minimizing a local quadratic model of the sum of squares ftmctmn constrained to an elhptmal trust regmn centered at the current approximate minimizer This is accomphshed using ideas chscussed by Mor6, together with a special module for assessing the quahty of the step thus computed. These and other ideas behind NL2SOL are discussed, and its evolution and current implementation are also described briefly.
View
View
View