27/01/2014
The natural history of oral conditions
Recent findings from the Dunedin Study
Outline •
•
•
•
•
•
What we do
Background to the study
Scope of the study
Dental involvement
Self‐control
An overview of some findings
–
–
–
–
Caries and tooth loss
Service use – is going to the dentist good for us?
Intergenerational effects
Plaque control and oral health
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Epidemiology & public health
• Leader
– Murray Thomson
• Key researchers
– Jonathan Broadbent
Investigate the oral health of populations
and what affects it, with particular attention
to the natural history of oral diseases and health through childhood, adolescence and
adulthood. Also investigate the way in which
dental health services work, how people use
them, and what can be done to improve the
delivery of oral health care.
– Dara Shearer
– Jimmy Zeng
– Kate Morgaine
– Lyndie Foster Page
Scope of our E & PH research
Population oral health Natural history of oral conditions
Epidemiology
Health
services
research
Clinical
research
What works best to improve oral health?
What actually happens
in the health system?
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University of
Adelaide
Collaborators
Spencer, Jamieson, Mejia, Do, Peres
University of
Pelotas
Epidemiology
DeMarco, Vargas‐Ferreira
Duke
University
Caspi, Moffitt
University
of Sheffield
Baker, Gibson
Health
services
research
Clinical &
health promotion
research
DHBs:
• Taranaki
• Wanganui
• Southland
• Waikato
• Northland
• Auckland
Ministry of
Health
University of
Toronto
Lawrence
University of
Chile Espinoza, Gamonal
Oral Diagnostic &
Surgical Sciences Raukura Hauora
o Tainui
The Dunedin Multidisciplinary Health and Development Study
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Design
• Prospective observational study of a complete birth cohort born in 1972/73
– N = 1037
– Wide range of social, health & psychological data
0
3
5
7
9
11
13
15
18
21
1972/73
26
32
38
96%
96%
95%
So what?
MHDS\The Science of Us‐‐ a forthcoming documentary series about the Dunedin Longitudinal Study
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Matching research question & study type
Study design
Descriptive
Analytical
Case Surveys Cohort
reports
Interventional
CCS
RCTs
Research question
Clinical features?
How common is it?
Who gets it? Risk
markers/factors?
Natural history?
How to treat it?
Life‐course models & dental examples
Model
Dental example
Mode of action
Demarcated opacity defects of enamel
Interruption of enamel maturation by PA infection of carious predecessor tooth
Periodontitis
Low child SES and poor maternal nutrition, followed by smoking as adult
Dental caries, tooth loss
Prolonged inadequate plaque removal, low topical F exposure and frequent sugar
Orofacial trauma
Growing up deprived → exposure to family violence → aggressive behaviour → trauma
Critical period
Exposure during key developmental period leads to condition later in life
Critical period with effect modifier
Key early‐life exposures interact with later ones
Accumulation risk
Detrimental and beneficial exposures accumulate through life to affect health
Chain of risk
One exposure leads in a fairly linear way to another (etc) to influence health
Thomson WM, Paiva SM, Ardenghi TM. The life course approach. In: Moyses SM, Watt RG, Bonecker M, Sheiham A (eds)
Promoting Children’s Oral Health: Theory & Practice (2nd Ed); in press.
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Participation rates
Participation in the Dunedin Multidisciplinary Study by age
100
90
Participation rate (%)
80
General Study
70
At age 38:
95% in the wider study
92% in the dental study
60
Dental Study
50
40
30
20
10
0
0
3
5
7
9 11 13 15
18
21
26
32
38
Age in years
Location of those seen at age 38
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Current research activities include studies of:
•
SES inequalities ‐ selection v causation
•
Mental health (including substance abuse)
•
Pathways to employment
•
•
Personality continuities across the life‐
course
Intimate relationships and domestic violence
•
Oral health
•
Antisocial behaviour and criminality
•
Sexual & reproductive health
•
Long‐term consequences of childhood adversity •
Cardiovascular risk factors
•
•
Maori health/cultural identity
Retinal imaging and endothelial function
•
Cognition and neuropsychology
•
Respiratory health
•
Family health history study
•
Next generation studies (age 3 and age 15 years)
Current research activities (contd)
• Blood based studies
•
–
Chlamydia trachomatis
–
Herpes immunity
–
Cardiovascular disease risk factors
–
Inflammatory biomarkers
Genetic studies
– Mental health phenotypes
– Asthma/allergy
– Cardiovascular risk factors
– Periodontal disease
 Methodological studies
–
Comparison of Dunedin sample with national data
–
Attrition analyses
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The assessment day
• Morning (>8:30am)
– Cardiovascular health
– Cognitive function
– Respiratory health
• Afternoon (1‐5pm)
–
–
–
–
–
–
–
–
Life history
Emotional well‐being
Sexual health
Identity & health
Illegal behaviour
Partner relationships
General health
Dental health
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An example: kids and self‐control
• Children with more self‐control turn into healthier and wealthier adults
– Childhood self‐control predicts success and failure in adult life, above and beyond intelligence and family wealth
Proceedings of the National Academy of Sciences 2011; 108: 2693‐2698.
Self‐control
• Aspects
– Delaying gratification
– Controlling impulses
– Modulating emotional expression
• The earliest and most ubiquitous demand that society places on children
• Success at many tasks depends on mastery of self‐control
• Influences health, wealth, criminal behaviour
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More necessary now than ever?
• Avoid obesity – in an era of ready food availability
• Maintain fitness – in an era of sedentariness
• Sustain marriages – in an era of easy divorce
• Prevent addiction – in an era of easy access
• Resist spending – in an era of sophisticated marketing
• Save for old age – in an era without guaranteed State support
 Impulsive, acts without thinking.
 Can’t wait his or her turn.
 Low frustration tolerance.
 Dislikes effortful tasks.
 Fleeting attention, easily distracted.
 Lacks persistence, easily forgets goals.
 Often goes for the risky thing.
 Requires constant attention and
 motivation from an adult.
[Thanks to Professor Terrie Moffitt]
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Self‐control study ‐ design
Childhood risk factors
Adolescent snares
IQ
SES
Self‐control
Early smoking
School drop‐out
Teen parenting
Adult health
Metabolic syndrome
Respiratory disease
Periodontitis
STDs
Substance dependence
Adult wealth, crime
SES, income
Single parenthood
Credit problems
Adult convictions
Composite measure:
Observations at 3, 5 yrs
Parent , teacher & self‐reports
from ages 3 to 11:
‐ impulsive aggression
‐ hyperactivity
‐ lack of persistence
‐ inattention
‐ impulsivity
0
3
5
7
9
11
13
15
18
21
26
32
Findings
• Children with poor self‐control were more likely to:
– Make mistakes as adolescents – resulting in “snares” which trapped them in poor lifestyles
• Smoking • Early school leaving
• Teenage parenthood
– The lower the self‐control, the more of these they encountered
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Health, Wealth
Health measures
Wealth measures
Single parenthood, Criminality
Single‐parent child‐rearing
Criminal convictions
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Overview of those findings
• The gradients were the same, irrespective of – Sex – IQ
– SES
• How influential were those findings?
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LET’S GET BACK TO THE MOUTH…
Dental caries and tooth loss
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The “average” caries trajectory
18
16
14
Cumulative DMFS
12
10
8
Just over 0.8
surfaces/year
6
4
2
0
9
15
18
26
32
Age (years)
What would it look like if we tracked everyone individually?
(a mess, most likely…)
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Individual trajectories of caries experience
Here’s our mess…
How to make sense of this mess?
• Trajectory analysis
– Identify distinctive developmental trajectories
• Identify trajectory ‘groups’ first, then analyse to find the determinants of group membership (eg SES)
– PROC TRAJ in SAS
– 3‐group solution the most parsimonious
Jonathan Broadbent
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DMFS trajectories
(drop‐bars represent inter‐quartile range)
“High”
144 (15.1%)
• Insert figure 2 without the droplines
The greater slope here
suggests that we
have a period of higher
susceptibility to caries…
“Medium”
429 (44.7%)
“Low”
384 (40.2%)
Group trajectories superimposed
Individual trajectories are colorised
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Tooth loss due
DMFS trajectories
to caries
53.8%
Prevalence of 1+ teeth lost
33.3%
Mean no. of teeth lost
0.7
2.2
These people are losing
more teeth and so
have fewer surfaces
left to get carious
28.4%
13.2%
0.7
0.3
0.6%
0.0
5.9%
0.1
And then to age 38…
61%
X
54%
(by 38)
33%
28%
40%
X
13%
1%
6%
15%
X
38
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WHAT HAPPENS THROUGH THE LIFE‐
COURSE?
Segue … dental charts
Cumulative DMFT by tooth
3 years
6 years
3 years
8 years
6 years
6 years
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Medium
High
Childhood SES:
Low
DMFS trajectories (age 9 to 32), extended to age 38
50
Proportion with 3+ teeth missing:
High 40%
Med 14%
Low 2%
40
High trajectory (15% of population) DMFS
30
20
Moderate trajectory (45% of population) 10
Low trajectory (40% of population) 0
5
9
15
18
26
Age in years
Age 38
Low trajectory
40% of people
32
38
0
1
2
3
4
5
6
Mean number of teeth lost due to caries by age 26, 32, 38
~7 DMFS by age 38
High SES more likely to be in this group
Moderate trajectory
45% of people
50+ DMFS by age 38
Low‐income people more likely to be in this group
High
5  more likely to have dental pain
trajectory
6  more likely to be embarrassed about their teeth
15% of people
20  more likely to have difficulty eating
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Implications
• Average caries increment = 1 surface/year
1.4
1.2
– Right through from adolescence to age 32
1
Mean
increment
0.8
0.6
0.4
– Similar for older people:
0.2
0
Iowa
NC (B)
NC (W)
Ontario
SA
Cohort
• Is it possible that it averages 1 surface/year right through life?
Annual caries increments – older people
1.4
Mean surfaces per year
1.2
1
The average caries increment in younger adults
0.8
0.6
0.4
0.2
0
Iowa
NC (B)
NC (W)
Ontario
Sth Aust
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Increments by setting
Mean surfaces per year
6
5
4
3
Root surface caries
Coronal caries
2
1
0
Own homes
Rest home
Rest home + dementia
South Australia
Chalmers et al Gerodontology 19: 80‐94 (2002)
IS DENTAL VISITING GOOD FOR US?
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Journal of Dental Research 89: 307‐311, 2010.
This is the first longitudinal
investigation of the effects
of dental visiting
Ways people can use dentistry
Routine attendance
Episodic attendance
• Visit regularly for check‐ups
• Visit only when a problem arises
– Usually on a recall system
– Toothache – Broken tooth
– Infection, etc
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Why do routine attenders have better oral health?
The dentists’ version
The skeptics’ version
• Preventive dental care
• Interceptive dental treatment
• The “healthy user” effect
– Routine attenders: •
•
•
•
Have better self‐care
Eat better
Are less likely to smoke
Have better health behaviours anyway
Identifying routine attenders
We looked at DMFS, DS,
missing teeth and
self-rep. oral health by 32
Enrolled for
free care?
15
Visit within
previous yr?
Prevalence:
82%
Enrolled for
free care?
18
Attend for
check-ups?
Attend for
check-ups?
26
32
Visit within
previous yr?
Visit within
previous yr?
Visit within
previous yr?
67%
31%
28%
Only 11% were RAs at all four ages…
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Routine attendance with age
100
75
%
50
25
Routine attenders at every age
15
18
26
32
Age
Routine attendance with age, by sex
100
75
%
50
25
Female routine attenders at every age
Male routine attenders at every age
15
18
26
32
Age
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Routine attendance with age, by childhood SES
SES of origin
100
High
Medium
75
Low
%
50
25
Routine attenders at every age
15
18
32
26
Age
Number of ages with routine attendance
Number of ages
Number
Percentage
of cohort
0
147
16%
1
220
24%
2
308
33%
3
155
17%
4
102
11%
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Aspects of oral health by age 32
80
70
60
Routine
attender at:
0 ages
1 age
2 ages
3 ages
4 ages
50
40
30
20
10
0
% poor self-rated
oral health
% 1+ teeth
missing
Mean DS
Mean DMFS
Outcome of multivariate models
An age-15
RA had 1.7
times the odds
(cf a nonRA) of
4
reporting good
3.5 age 32
oral h by
3
2.5
2
(Adjusted for sex, SES and plaque scores)
An age-32
RA had 3.4
times the odds
15 18
(cf a nonRA) of
reporting good
oral h by age 32
1.5
1
0.5
0
Good self-rated
oral health
1+ teeth missing
due to caries
26
32
An age-26
RA had the
lowest odds
(cf a nonRA) of
missing 1+ teeth
32 DMFS
Mean DS by ageMean
(ORs)
Age of regular attendance
An age-32
RA had the
lowest IRR
for mean DS
(IRRs)
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Intergenerational continuity in oral health
Coal miner
(edentulous)
A case study of
Scots immigrants:
Electrician
(edentulous)
Coal miner
(edentulous)
University professor
(fully dentate in
his mid‐50s)
4 generations of William Thomsons
Background
• Do the children of parents with poor health end up having poor oral health?
• Focus to date narrow and reductionist
– Transmission of S mutans
• Two notable exceptions
– Ringelberg et al (1974) – small study in Md
• Similar caries experience between generations
– Bedos et al (2006)
• Caries prevalence higher in children of edentulous mothers
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Family history
• A risk factor for almost all diseases of public health importance
– Neither genetics nor genomics have had much impact to date • Family history reflects consequences of:
– Genetic variation
– Shared environment
– Similar behaviours
• Can quantify risk by:
– Number of affected family
members
– Their degree of closeness
– Their age at disease onset
– The severity of their disease
• Use this to stratify the
population into:
– High risk
– Medium risk
– Low risk
Likely to be the largest group, so
interventions aimed at these families
could have a substantial public health impact
Mean dmfs score among probands
Age‐5 dmfs by maternal oral health, 1977/78
7
6
5
4
3
2
1
0
Excellent
Fairly good
Average
Fairly poor
Very poor
Mother's self-rated oral health when proband aged 5
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Age‐32 DMFS (2003/04) by maternal oral health in 1977/78
Mean DMFS score among probands
(Adjusted by sex, SES, plaque trajectory, dental visiting)
25
20
15
10
5
0
Excellent
Fairly good
Average
Fairly poor
Very poor
Mother's self-rated oral health when proband aged 5
1+ teeth missing (due to caries) in 2003/04 by maternal oral health in 1977/78
30
% with 1+ missing teeth
25
20
15
10
5
0
Excellent
Fairly good
Average
Fairly poor
Very poor
Mother's self-rated oral health when proband aged 5
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DMFS trajectories
“High”
144 (15.1%)
(drop‐bars represent inter‐quartile range)
• Insert figure 2 without the droplines
“Medium”
429 (44.7%)
“Low”
384 (40.2%)
% in highest caries trajectory by maternal oral health in 1977/78
% in high caries trajectory
30
25
20
15
10
5
0
Excellent
Fairly good
Average
Fairly poor
Very poor
Mother's self-rated oral health when proband aged 5
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Implications for dentistry • Look beyond the individual to the family
• Take a life‐course view
• Take an intergenerational view
Family history reflects the consequences of shared genetic
variations at multiple loci, shared exposures and responses
to environmental factors, and shared behaviours (Khoury et al, 2005)
PLAQUE CONTROL AND ORAL HEALTH
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Continuity in plaque levels?
• Most examinations of plaque levels and oral health have been cross‐sectional
– Only weak associations
• Similar to the coronal‐root caries association, what happens when we take a life‐course view and look longitudinally?
Measuring plaque
6 index teeth:
16, 11, 26
46, 31, 36
Greene and Vermillion (1964) – Simplified Oral Hygiene Index
[Thanks to Professor Aubrey Sheiham for this picture]
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Lifetime plaque trajectories
1.8
High trajectory
38.5%
1.6
1.4
OHI-S plaque score
1.2
Moderate trajectory
1
0.8
49.1%
0.6
Low trajectory
0.4
12.4%
0.2
0
5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Age (years)
Age‐32 caries experience by plaque trajectory
90
3.4
80
70
Adjusted odds ratios
60
1.4
50
40
30
20
4.8
Plaque trajectory
Low
Medium
Adjusted incidence
rate ratios
2.8
High
1.4
1.2
10
0
DMFT
1+DS
1+ MT
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Age‐32 periodontitis by plaque trajectory
Nonsmokers
%
Smokers
70
70
60
60
50
Plaque trajectory
40
Low
30
Medium
High
40
%
30
20
20
10
10
0
Plaque trajectory
50
Low
Medium
High
0
% BOP
1+ CAL 4+mm
% BOP
1+ CAL 4+mm
What now for the study?
• Working hard to publish latest findings
– Will have to start applying for next funds next year
• Assessments planned for ages 44 and 50
• Study then moves into gerontology territory…
– Along with the investigators…
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Acknowledgments
• Waikato DHB
• Rob Aitken, Andrea Sutton
• Our Study members
• The money people:
– NIDCR/NIH grants R01 DE015260, R03 DE018716
– NZDA Research Foundation
– The Health Research Council of NZ
• Jonathan Broadbent, Richie Poulton, Avshalom Caspi, Terrie Moffitt, Bob Hancox, Dara Shearer, Lyndie Foster Page
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