obesity and dental caries in children: a systematic review and meta-analysis

Obesity and dental caries inchildren: a systematic reviewand meta-analysis

Hayden C, Bowler JO, Chambers S, Freeman R, Humphris G, Richards D, CecilJE. Obesity and dental caries in children: a systematic review and meta-analysis. Community Dent Oral Epidemiol 2013; 41: 289–308. © 2012 JohnWiley& Sons A/S. Published by JohnWiley & Sons Ltd

Abstract – Objectives: Obesity and dental caries have become increasinglyprevalent challenges to public health. Research results into the relationshipbetween obesity and dental caries in children have been mixed andinconclusive. The aim of this review and meta-analysis was to provide evidenceto quantify the relationship between obesity and dental caries in children usinga systematic approach. Methods: A systematic search for papers between 1980and 2010 addressing childhood obesity and dental caries was conducted and arandom effects model meta-analysis applied. Results: Fourteen papers met theselection criteria. Overall, a significant relationship between childhood obesityand dental caries (effect size = 0.104, P = 0.049) was found. When analysed bydentition type (primary versus permanent), there was a nonsignificantassociation of obesity and dental caries in permanent and primary dentitions,yet on accounting only for standardized definitions for assessment of childobesity using body mass index, a strong significant relationship was evident inchildren with permanent dentitions. Moderating for study country of origin(newly ‘industrialized’ versus industrialized) showed a significant relationshipbetween obesity and dental caries in children from industrialized but not newlyindustrialized countries. Cofactors such as age and socioeconomic class weresignificant moderators. Conclusions: Future analysis should investigate theseconfounding variables, helping shape the future of obesity managementprogrammes and oral health interventions, through determining common riskfactors.

Ceara Hayden1, Jennifer O. Bowler2,

Stephanie Chambers3, Ruth Freeman3,

Gerald Humphris1, Derek Richards4 and

Joanne E. Cecil1

1School of Medicine, University of St

Andrews, Fife, Scotland, UK, 2School of

Psychology, University of East Anglia,

Norwich Research Park, Norwich, UK, 3Oral

Health and Health Research Programme,

Dental Health Services Research Unit,

University of Dundee, Dundee, UK, 4Centre

for Evidence-based Dentistry, Oxford, UK

Key words: children; dental caries; obesity;overweight

Joanne E. Cecil, School of Medicine,University of St Andrews, Medical andBiological Sciences Building, North Haugh,St Andrews KY16 9TF, UKTel.: +44 0 1334 463541Fax: +44 0 1334 467470e-mail: [email protected]

Submitted 16 November 2011;accepted 18 September 2012

Childhood obesity has become a global health

problem and is associated with precursors of adult

illnesses including cardiovascular disease (1) and

type 2 diabetes (2). Worldwide, almost 43 million

children below 5 years of age carry excess body

weight (3). In the United States, 17% of children

and adolescents are currently obese (4). The

increasing risk of obesity for young people is of

particular concern because research has suggested

that childhood obesity predicts adult obesity (5,

6). Obesity is therefore one of the primary chal-

lenges to public health, with consequences affect-

ing many different areas of life, and so the need

for immediate preventative action is warranted.

Although limited, there is evidence to suggest that

the problem extends beyond the peripheries of the

developed world into nondeveloped countries.

For example, in Mexico, classified as a newly

‘industrialized’ country (NIC; referring to coun-

tries between ‘developing’ and ‘developed’ sta-

tus), just over 10% of preschool children and 26%

of school-age children were classed as overweight

or obese in 2006 (7).

Obesity is a multifactorial disorder, influenced

by environmental and genetic risk factors (8),

where a sustained imbalance between energy

intake and energy expenditure facilitates storage of

excess energy as fat. Diet is a primary determinant

doi: 10.1111/cdoe.12014 289

Community Dent Oral Epidemiol 2013; 41; 289–308All rights reserved

� 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd

of obesity. Consumption of energy-dense low-

nutrition foods, which tend to be high in saturated

fats and sugars, and low fruit and vegetable con-

sumption have been linked with increased weight

gain and obesity (9–13). Poor diet can also impact

negatively on health through effects on immune

functioning, growth, development, ageing and oral

health. Poor oral health is typified by the onset of

dental caries, presently the most common chronic

disease found in children (14). In the United States,

27% of preschool children experience dental decay

(15). As in developed countries, dental caries is rec-

ognized as a major problem in NICs where its

prevalence in preschool age children in the devel-

oping world ranges between 27% and 46% and is

as high as 72–95% in Mexico (16).

Diet specifically through the frequent consump-

tion of monosaccharide (e.g. glucose, fructose) and

disaccharide (e.g. sucrose) sugars is the predomi-

nant cause of dental caries (17, 18). Dental caries is

the localized destruction of susceptible dental hard

tissues by acidic by-products from bacterial fer-

mentation of dietary carbohydrates (19). In recent

years, concern has been raised over the consump-

tion of sugar-sweetened beverages in contributing

towards diseases such as obesity and dental caries

(17). In the UK, soft drink consumption provides a

significant source of added sugar to the diet and

contributes around 5% to average daily total

energy intake in men and women aged 19–24 years

(20). In late adolescence and young adulthood,

sweetened beverages provided more than 50% of

total intake of sugars (20). Notably, a greater pro-

portion of children from deprived areas consume

foods high in sugar and saturated fats on a regular

basis compared with those in high socioeconomic

status (SES) areas (21), and both dental caries and

obesity have been associated with low SES (21).

Importantly, dietary behaviours such as frequency

of ingesting cariogenic foods confer risk for dental

caries (22, 23). In a survey study investigating asso-

ciations between diet and caries-associated bacteria

in young children with severe early-childhood car-

ies (ECC), Palmer et al. (22) showed that children

with severe ECC consumed food and beverages

significantly more frequently compared with car-

ies-free children. Children with severe early caries

also ingested more foods that were high in cario-

genic potential compared with caries-free children

(22). The use of fluoride toothpastes (24), fluoride

varnishes (25) and genetic susceptibility (26) are

also important contributors to development of

ECC.

Critically, a number of studies have linked con-

sumption of sweetened beverages with increased

energy intake, obesity (27–29) and dental decay (30

–32). In addition, there are reports of associations

between obesity and dental caries (16, 33–37),although the data are mixed and provide conflict-

ing evidence (38–45). A recent systematic review

(46) reported that only one of seven cross-sectional

(CS) studies with children showed an association

between obesity and dental caries. This review was

limited however, by the narrow search criteria

used in the appraisal of papers reflecting a possible

bias. Conversely, nonsignificant findings for exam-

ple within Chen et al.’s study (38) reflect a skewed

sample of very young children (aged 3 years) with

a high caries prevalence, where the proportion of

children with one or more decayed or filled teeth

(56%) was not different according to body mass

index (BMI) categories. The authors suggest that

the lack of relationship between BMI and dental

caries could be explained by the frequency of sugar

ingestion (resulting in development of dental car-

ies) rather than the amount per se and acknowledge

dietary fat as an important promoter of obesity.

Conflicting findings in the literature to date sug-

gest that the relationship between obesity and den-

tal caries in children is likely to be complex and

potentially hindered by amalgamation of multiple

age groups that differ considerably in growth rate

and expressed phenotype as well as the differential

rates of growth that are expressed in children

within an age group. However, more research

should address these important public health prob-

lems to facilitate prevention and health promotion.

The aim of this systematic review and meta-anal-

ysis was to investigate and quantify the relation-

ship between obesity and dental caries in children.

Methods

Search strategy and selection criteriaA literature search was performed using Embase,

MedLine, ScienceDirect, Ovid and PsychInfo data-

bases. As the prevalence of obesity has increased

dramatically over the past 30 years leading to more

specialized obesity studies, it was decided a priori

that the search would be restricted to studies

published between 1980 and 2010. The identified

keywords and index terms: obes*, child*, paediatric,

weight, overweight, BMI, dental caries, primary

dentition, dft, dmft, dmfs, dfs were entered. Only

studies that were in English and fully accessible

290

Hayden et al.

were included in the meta-analysis. Reference lists

for all relevant articles and review reference sec-

tions were also examined for any further relevant

articles not yet identified. Only published and

accessible papers were considered and thus

unpublished research was not considered. Papers

were filtered by title for relevance and then at

abstract and article level in accordance with inclu-

sion criteria (Table 1).

Data extraction and quality assessmentThe two outcome measures were weight and car-

ies experience. Only participants who fell into the

highest BMI category (‘overweight/obese’

depending on assessment method) or ‘normal’

BMI were included in the analysis. Assessment of

child obesity varies worldwide and relies on dif-

ferential reference data making comparison of

trends difficult (47). BMI-for-age centiles (48), age-

and gender-related international standards recom-

mended by the International Obesity Task Force

(IOTF) (49) and Z-scores (50) are some of the most

often used methods to define a child who is over-

weight and or obese. Some studies thus assign the

term ‘obese’ to the highest BMI category, while

others assign ‘overweight’ to this group of chil-

dren. In this review, ‘obese’ will be used uni-

formly to refer to those children in the highest

BMI category. Children who were ‘underweight’

were not included. Dental caries was measured

using the decayed/missing/filled or decayed/

extracted/filled index.

Relevant abstracts and articles were indepen-

dently reviewed by three investigators (CH, JB and

JC), ensuring that validity was held across all

aspects of the studies. Review of abstracts followed

the PRISMA guidelines (51). Criteria for a valid

paper included defined outcome measures and

sample size above 200 participants. Individual

judgments from these authors were then analysed

to determine inter-rater reliability. Final decisions

on article retrieval and inclusion or exclusion were

made by consensus.

A quality assessment of the selected papers was

independently conducted by two of the authors

(CAH and SC). When assessing the quality of ran-

domized controlled trials or cohort studies, widely

recognized quality appraisal tools, such as the

Cochrane Collaboration’s tool for assessing risk of

bias (52) or the Newcastle-Ottawa scale (53) can be

used. According to a recent review by Sanderson

et al. (54), no such ‘gold standard’ tool exists for

assessing the quality and susceptibility to bias in

observational studies with CS or longitudinal

designs. However, an appraisal checklist devel-

oped by the University of Wales was selected as

Table 1. Inclusion and exclusion criteria for the studies reviewed

Inclusion criteria Exclusion criteria

Population Under 18 year olds with primary and/or secondarydentitions

Over 18s

Male and female No exclusions on genderCross-cultural No exclusions on cultureAny socio-economic class No class restrictions

Outcomes Primary outcome dental caries experience, measuredby dft, dfs, def, dmft, dmfs, DFT, DMFT, DMFS

Tooth decay or dental caries measured inother ways

Studies which did not specify or separatelyanalyse by dentition type

Use of BMI or z-scores as a measure of normal weightand obesity

BMI or z-scores not used as an indicator ofweight categorization

Sample included participants who were in one of twogroups. In the normal range or the highest BMIcategory labelled as either overweight and/orobese

Normal weight not used as control groupand/or obese group not included inanalysis

Clearly defined obesity, overweight and normal BMIcategories

Those only measuring average BMI forentire sample group

Study Design Levels I–IV; cross-sectional, quasi-experimental orcase controlled/cohort design with control groups,observational studies

Level V; qualitative designs and otherreviews

Published papers; unpublished data received directfrom author

Papers where data has not been sent afterrequest was made

Must be in English and accessible Papers in any other language andinaccessible

291

Obesity and dental caries in children

most appropriate for assessing study quality

and bias in the current systematic review and

meta-analysis (55). The checklist assesses study

quality on 12 criteria including bias, follow-up and

appropriate use of statistical methods, with a total

score of 12 indicating the highest quality score

available to each study. The quality assessment

scores for each study (Table 2) from two authors

(CAH and SC) were assessed for agreement to fur-

ther strengthen the quality assurance of this meta-

analysis.

Data extracted for meta-analysis were sample

size, outcome measures and significance. The par-

ticipant numbers for one study (43) were obtained

directly from the author. The papers included in

the analysis were those in which means and signifi-

cance, means and standard deviations, correlation

coefficient and significance or odds ratios and con-

fidence intervals (CI) were reported or calculated

from the available data. Where studies had addi-

tionally presented adjusted values for covariates,

the unadjusted values were included in the review.

Possible publication bias, which can result in the

nonpublication of small studies with negative

results, was assessed by visually evaluating a fun-

nel plot of the mean differences for asymmetry. In

addition to visual assessment of the graph, a

regression asymmetry test was performed to for-

mally determine whether such publication bias

had occurred.

Data synthesisComprehensive Meta-analysis II software (56) was

used to generate standard mean differences using

random effects meta-analysis. A random effects

approach to account for within-study and

between-study variation is more conservative than

a fixed effects model and is recommended by pres-

ence of high heterogeneity (56). Heterogeneity of

data was evaluated using the I2 statistic. Standard

mean differences were represented as a point esti-

mate and 95% CIs on a forest plot.

It was decided a priori that subgroup analyses

would be conducted on the studies according to

caries index, definition for assessment of child

obesity using BMI and the study country of origin.

Partitioning the data in this way also enabled age

and caries index to be examined in relation to

childhood obesity prevalence. The studies were

partitioned according to whether they were con-

ducted in NICs (Brazil, India, Iran, Thailand and

Mexico) or industrialized countries (France, Ger-

many, Sweden, Taiwan and USA) to assess the

impact of economic development on the relation-


Role of the funding sourceThere was no funding source for this study. The

corresponding author had full access to all the

data in the study and had final responsibility for

the decision to submit for publication.

Results

Study characteristicsTwo hundred and twelve potential studies were

identified from the initial literature search. Thirty-

eight full-text articles were accessed, and 14 stud-

ies met the criteria and were included within the

meta-analysis (Fig. 1). A systematic review of the

appraised studies was completed (Table 2). One

study was longitudinal in design (35), while 13

were CS (16, 33, 36–39, 42–45, 57–59). Eight stud-ies were conducted in industrialized countries

(33, 35, 37, 38, 42, 43, 57, 58), with six conducted

in NICs (16, 36, 39, 44, 45, 59). Six studies investi-

gated permanent dentitions only (33, 35, 36, 39,

44, 58), five studies investigated primary denti-

tions only (16, 38, 43, 57, 59) and three studies

investigated both (37, 42, 45), although data relat-

ing to permanent dentition from the Kopycka

study (42) were insufficient for inclusion in the

meta-analysis. Six studies (16, 36, 42, 43, 45, 57)

assessed child obesity using the BMI-for-age cen-

tiles from the 2000 Centers for Disease Control

and Prevention (CDC) growth charts for children

and adolescents from 2 to 20 years of age (48),

while one paper (38) used standardized centiles

derived from the First National Health and Nutri-

tion Examination Study, 1971–1974 (60). Three

studies (33, 35, 58) assessed child obesity using

age and gender appropriate international stan-

dards for child obesity (>30 kg/m2 at 18 years)

(49) recommended by the IOTF. Two studies (39,

59) used Z-scores (50), where a Z-score > 2 was

used to classify overweight. In two studies, non-

standardized measures for assessment of child

obesity were used (37, 44). Four studies analysed

decayed or filled teeth (DFT/dft) (35, 37, 38, 45),

five studies analysed decayed, missing or filled

teeth (dmft/DMFT) (39, 43, 44, 57, 58), one study

incorporated decayed, extracted or filled teeth

(deft) (16) and surfaces (defs) (16), one study

assessed decayed, missing or filled surfaces

(dmfs) (59) and two decayed or filled surfaces

292

Hayden et al.

Tab

le2.

Literature

review

ofpap

ersincluded

within

themeta-an

alysis

Article

characteristics

Sam

ple

characteristics

Methoddetails

Resultsdetails

Qualityscore

(Max

12)

Studydesign

Participan

tdem

ographics

andch

aracteristics

Obesityoutcomemeasu

reDen

talcaries

outcome

measu

re

Analysis

Results

Conclusion

Referen

ce:A

lmet

al.(33

)8

Cross-sectional

(CS)

Swed

enn=40

2isoBMI>25

(n=64

)isoBMI<25

(n=33

8)13

.5–16.4years

Proportional

representation

ofsocio-dem

ographics

BMI(kg/m

2),categorized

accord

ingto

IOTFcu

t-off

values

(49)

Low

isoBMI(isoBMI<25

at18

years)

Overweight

(isoBMI25–29.9

at18

years)

Obesity(isoBMI>30

at18

years)

Total

man

ifest

caries

–D

mFa

Unpaired,

two-

sample

t-test

Adolescen

tsoverweight

(incl.o

bese)

had

higher

caries

than

low

weight

participan

tsPositive

relationsh

ipbetween

obesityan

dden

talcaries

‘Overweight

andobese

adolescen

tshad

more

approxim

alcaries

than

norm

al-w

eight

individuals’

Referen

ce:C

hen

etal.(38

)6

CS

Taiwan

n=51

333yearolds

BMI;less

than

5thpercentile

(verylow

BMI)

5th–25thpercentile

(low

weight)

25th–75th(m

edium

BMI)

75th–95th(highBMI)

>95

th(obese)

First

National

Health

andNutrition

Exam

inationStudy,

1971

–197

4

dft

Chi-square

analysis

Kruskal–

Wallis

tests

Therewereno

differences

amongBMI

groupsin

regardsto

theden

tal

caries

reported

among

participan

ts(K

ruskal–

Wallis,H

=6.45

,P=0.17

)Meanscoresof

dftwithin

thisgroupof

participan

tswas

4.1+2.7for

those

obese,

4.1+3.1for

overweightan

d4.2+3.0forthose

ofnorm

alBMI

‘Wecould

notfind

theassociation

betweenden

tal

caries

indeciduousteeth

andbodymass

index

of3-year-

old

children’

‘Nev

ertheless,

since

obesity

andden

tal

caries

are,in

principle,

causedbythe

poordietary

hab

it,further

studiesincluding

themealpattern

andthe

compositionof

thedietare

needed

for

evaluatingthe

293


Tab

le2

Continued

Article

characteristics

Sam

ple

characteristics

Methoddetails

Resultsdetails

relationsh

ips

betweenthese

twomost

prevalen

thealth

problemsin

childrenan

dad

olescen

ts’

Referen

ce:G

erdin

etal.(35

)11

CSlongitudinal

Swed

enn=23

034–10

years

Clustered

by

socioeconomic

group

(I–V

;high–low)

BMI(kg/m

2),categorized

accord

ingto

IOTFcu

t-off

values

(49)

BMIforoverweight

(>25

at18

years)–

BMIforobese(>30

at18

years)

deft(6

years)

DFT(10an

d12

years)

DFSa

One-way

ANOVA

Chi-square

linear

tren

dtest

Usinggen

der

and

socioeconomic

statusas

covariates,

BMIwas

significant

inaffecting

den

talcaries

prevalen

cein

12yearolds

Positive

relationsh

ipbetween

obesity

andden

tal

caries

‘Overweight

andobese

adolescen

tshad

more

approxim

alcaries

than

norm

alweight

individuals’

Referen

ce:G

ranville-G

arcia

etal.(39

)4

CS

Brazil

n=26

51ag

e1–5years

z-scoresalongsideW

HO

criteria

andNational

Cen

treforHealth

Statisticsguidelines.

Those

withaz-score

>2forweight–

heightrelationsh

ipwereconsidered

overweight

DMFT

Descriptive

statistics

Chi-square

analysis

Man

n–

Whitney

U-tests

Obesity

appearedto

berelatedto

inflated

decayed

values

(P=0.00

7),

butnotmissing

(P=0.74

3),fi

lled

(P=0.72

1),o

roverallvalues

(P=0.09

4)Those

withlow

DMFTindexes

wereless

obese,

howev

er,this

‘Norelationsh

ipwas

found

betweenden

tal

caries

and

obesity.S

uitab

lehealthpolicies

should

be

adoptedso

asto

minim

izethe

highprevalen

ceofden

talcaries

amongthis

population’

294

Hayden et al.

Tab

le2

Continued

Article

characteristics

Sam

ple

characteristics

Methoddetails

Resultsdetails

was

confounded

bysocial

class

Referen

ce:K

opycka-Ked

zieraw

ski

etal.(42

)10

CS

USA

n=10

180(756

8completed)

2–18

years

BMI;less

than

5th

percentile

(underweight)

5th–85thpercentile

(norm

alweight)

85th–95th(riskof

overweight)

95th

(overweight)

CDC

dfs

(2–11

years)

DMFS(6–18

years)

Bivariate

analyses

with

chi-square

statistics

Logistic

regression

Nostatistically

significant

associations

betweencaries

prevalen

cean

dweightstatus

between19

99an

d20

02

Noev

iden

ceto

suggestthat

overweight

childrenareat

anincreased

risk

forden

tal

caries.A

lthough

nodifferencesin

caries

ratesby

weightwere

foundin

younger

children,

suggestions

conferthat

being

overweightmay

beassociated

withdecreased

ratesofcaries

inolder

children

Referen

ce:M

acek

andMitola

(43)

10CS

USA

n=76

17BMI-for-ag

e�

95th

percentile

=19

.8m

BMI-for-ag

e5th–85th

percentile

=83

m2–17

years

BMI-for-ag

ecentiles

(CDC20

00)

Underweight=BMI-for-ag

e<5thpercentile

Norm

al=BMI-for-ag

e5th–

<85

thpercentile

Atrisk

overweight=85

th–

<95

thpercentile

Overweight=BMI-for-ag

e�

95th

percentile

Datafrom

NHANES

1999

–200

2dft/DMFT

Multiple

linear

regression

Noassociation

foundbetween

overweightan

dden

talcaries

Overweightwas

foundto

be

associated

with

lower

geo

metric

meanDMFT

‘Althoughitwas

hypothesized

that

BMI-for-ag

ewould

be

associated

with

increasedden

tal

caries

prevalen

ce…

thisassociation

was

notfound’

‘Given

the

importan

ceof

overweightas

apublichealth

problem,

howev

er,

295


Tab

le2

Continued

Article

characteristics

Sam

ple

characteristics

Methoddetails

Resultsdetails

cliniciansare

encouraged

tocontinuegiving

healthed

ucation

anddietary

counsellingto

overweightch

ild

paren

ts’

Referen

ce:N

arksawat

etal.(44

)5

CS

Thailand

n=86

212–14years

BMICen

tiles.Nutritionstatus

calculatedaccord

ing

toThai

MinistryofPublic

HealthMan

ual

using

weightforheightin

Thai

children.S

tandard

dev

iationsfrom

themed

ian

wereusedas

the

cut-offpoints

forfivegroups

Verythin

=<median�

2SD

Thin=median�

2SDto

median�

1.5S

DNormal

=median�1

.5SDto

median+1.5SD

Overw

eigh

t=median

+1.5to

+2SD

Obese

=>median+2S

D

DMFT

Man

n–

Whitney

U-test

Multiple

logistic

regression

Aneg

ative

relationsh

ipwas

foundbetween

theobesityan

dthe

DMFTindex,such

that

asweight

decreased

caries

prevalen

ceincreased

‘Norm

alweight

childrenhad

ahigher

risk

of

den

talcaries

than

obese

childrenag

ed12

–14years

inThailand’

‘Sch

oolhealth

promotion

activitiessh

ould

emphasize

eatinghab

itim

provem

ent

toreduce

the

inciden

ceof

caries’

Referen

ce:O

liveira

etal.(59

)10

CS

Brazil

n=10

1812–59months

BMI-for-ag

e;W

HO

childgrowth

stan

dardsreference

Nutritional

status

calculatedbyZ-scores

Atrisk

underweight=

Zscore<�2

Norm

al=�2

�Z-score

�+2

Atrisk

overweight=

Zscore>+2

dmfs

Unconditional

logistic

regression

Association

foundbetween

nutritional

status,

socioeconomic

factors

andcaries

experience

‘Underweight

childrenan

dthose

with

adverse

socioeconomic

conditionswere

more

likelyto

experience

caries’

296

Hayden et al.

Tab

le2

Continued

Article

characteristics

Sam

ple

characteristics

Methoddetails

Resultsdetails

Referen

ce:S

adeg

hian

dAlizadeh

(45)

4CS

Iran n=10

076–11

years

BMI-for-ag

ecentiles

(CDC20

00)

Norm

al=5th–<

85th

percentile

Atrisk

Overweight=85

th–

<95th

percentile

Overweight=

�95

thpercentile

DFT/dft

Multiple

linear

regression

Therewas

no

significant

association

betweenBMI-

for-ag

ean

dDFT,andBMI-

for-ag

ean

ddft

‘Overweight

childrenhad

higher

DFT/dft

scoresthan

did

norm

alch

ildren,

buttherewas

no

association

betweenBMI-for

agean

dDFT/

dftindices’

Referen

ce:S

harmaan

dHeg

de(36)

6CS

India

n=50

08–12

years

BMI-for-ag

ecentiles

(CDC20

00)

DMFS/dfs

ANOVA

Children

whowere

overweight

andobesehad

increased

prevalen

ceofcaries

inboth

primary

andperman

ent

den

tition

Apositive

association

was

also

found

betweencaries

prevalen

cean

dsw

eetfood

preference

‘Thereishigher

prevalen

ceof

den

talcaries

inoverweightan

dobesech

ildren’

‘Theim

portan

ceofnutrition

should

notonly

beem

phasized

withresp

ectto

gen

eral

diseases

butalso

with

regardsto

cariouslesions’

Referen

ce:S

helleret

al.(57

)7

CS

USA

n=29

32–5years

BMI-for-ag

ecentiles

(CDC20

00)

dmft

Reg

ression

BMIpercentile

did

notcorrelate

withdmft

‘Inthissample

of

children,theBMI

percentile

was

notcorrelated

withdmft’

Referen

ce:T

raminiet

al.(58)

8CS

France

n=83

512

years

BMI(kg/m

2),categorized

accord

ingto

IOTFcu

t-off

values

(49)

DMFT

Kruskal–

Wallis

Test

Noassociationwas

foundbetween

DMFTan

dBMI,

‘DFMTscoreswere

notsignificantly

different

297


Tab

le2

Continued

Article

characteristics

Sam

ple

characteristics

Methoddetails

Resultsdetails

Logistic

regression

althoughan

associationwas

foundwithsu

gar

consu

mption

accord

ingto

BMIlevels,as

defi

ned

for12

yearold

children’

‘Howev

er,itis

now

well

docu

men

ted

that

obesityan

dden

talcaries

hav

ecommon

determinan

ts,so

theopportunity

ofpreven

tive

measu

res

concerning

nutrition,

especially

amongch

ildren

andad

olescen

ts,

appears

tobe

essential’

Referen

ce:V

azquez-N

avaet

al.(16)

9CS

Mexico

n=11

604–5years

BMI-for-ag

ecentiles

(CDC20

00)

Norm

al=5th–85th

percentile

Atrisk

Overweight=

�85

th–<

95th

percentile

Overweight=

�95

thpercentile

deft/defs

Logistic

regression

Therewas

asignificant

association

between

atrisk

overweight,

overweightan

dcaries

inthe

primary

den

tition

‘Childrenwith

obesityhav

emore

caries

than

childrenwith

norm

alweight’

‘Theprevalen

cedocu

men

tedfor

each

ofthese

variables

indicates

that

thereisaclear

needfor

establish

ing

community

healthprograms

toiden

tify

and

limitrisk

factors

298

Hayden et al.

Tab

le2

Continued

Article

characteristics

Sam

ple

characteristics

Methoddetails

Resultsdetails

forden

talcaries

andobesityin

children’

Referen

ce:W

illershau

senet

al.(37

)5

CS

German

yn=12

906–11

years

BMI(nutritionstatus

calculatedwith

reference

toArbeitsgem

einschaft

Adipositasim

Kindes-

undJugen

dalter,20

02)

low

weight;norm

alweight;

highweight;obese

DFT/dft

T-test

ANOVA

Logistic

regression

Therewas

asignificant

association

betweenhigh

weightan

dcaries

prevalen

cein

the

firstan

dperman

ent

den

tition

‘Theresu

ltsofthis

studyindicatea

possible

associationof

highweightan

dcaries’

‘Infuture

preven

tive

programs,the

importan

ceof

nutritionsh

ould

notonly

be

emphasized

withresp

ectto

gen

eral

details

butalso

with

regardto

carious

lesions’

IOTF,International

ObesityTaskForce.

299


(dfs) (35, 42). A single report examined total ap-

proximal caries prevalence and fillings (33).

Population characteristicsThe age of participants from the studies included

in the meta-analysis spanned from 1 to 18 years.

All studies sampled both boys and girls.

Data extraction and quality assessmentAn intraclass correlation (ICC) was calculated to

assess the inter-rater reliability of the papers that

were excluded after appraisal by three authors

(CH, JB and JC). A value of 0.63, indicating moder-

ate consensus, was found. Using the University of

Wales Quality Assessment tool for observational

studies (55), studies were assigned quality scores

ranging from 4.0 to 10.5 (Table 2). Reliability of

study quality appraisal was robust, and reliability

between raters was strong (ICC = 0.91). Four of the

14 studies scored <6.0 (half of the total possible

quality score) (37, 39, 44, 45), while seven studies

scored 8.0 or above in relation to study quality (16,

33, 35, 42, 43, 58, 59). The most frequent threats to

quality were a failure to take confounding and bias

into account and drawing conclusions not sup-

ported by the data presented. Study quality scores

assisted in the interpretation of meta-analysis

results.

A funnel plot (Fig. 2) used to assess publication

bias among the papers illustrates a symmetrical

spread of the studies with regard to the stan-

dard errors reported within each paper. The plot

Potentially relevant studies identified on literature search and screened for

retrieval n = 212

Study abstracts identified and eligibility analysed

n = 45

Studies excluded by title due to non-access or irrelevance n = 167 Elimination of duplicates n = 70

Did not satisfy inclusion criteria n = 97

Full text articles appraised n = 38

Studies included in meta-analysis n = 14

Studies excluded by abstract only n = 7No measure for caries n = 1

Review/Thesis n = 2 No direct comparison n = 3

No weight measure n = 1

Studies excluded unanimously n = 11 No comparison between BMI and caries n = 5

Wrong type of data n = 4 Inadequate measures n = 1 Inadequate statistics n = 1

Full text articles further appraised, discussed amongst investigators and

awaiting author clarification n = 27 Studies excluded n = 13

No comparison between BMI and caries n = 2 Wrong type of data n = 5

No BMI classifications n = 3 Inadequate statistics n = 3

Fig. 1. PRISMA flow diagram illus-trating the literature review process.

–2.0 –1.5 –1.0 –0.5 0.0 0.5 1.0 1.5 2.0

0.0

0.1

0.2

0.3

0.4

Stan

dard

err

or

Std diff in means

Funnel plot of standard error by std diff in means

Fig. 2. Funnel plot indicating anyelements of publication or selectionbias within the studies included inthe meta-analysis.

300

Hayden et al.

confirms a low level of publication bias, further sup-

porting the reliability of the overall findings.

Data synthesis

Relationship between BMI and dental caries. Hetero-

geneity of the included studies was present as

indicated by the significant I2 value (Q = 55.701,

P < 0.001), and therefore, a random effects model

was employed. This model provides support for

a significant relationship between obesity and

dental caries. In synthesizing the results of the

selected studies (16, 33, 35–39, 42–45, 57–59), thefirst forest plot (Fig. 3) segregates the data into

dentition type, which is correlated with age

(older children associated with DMFT, younger

with dft). Overall, a significant relationship

between childhood obesity and dental caries

(effect size = 0.104, P = 0.049) was found. When

analysed by dentition type, there was a nonsignif-

icant association of obesity and dental caries in

permanent (effect size = 0.124, 95% CI: �0.053 to

0.301, P = 0.17, ns) and primary dentitions (effect

size = 0.093, 95% CI: �0.033 to 0.220, P = 0.149,

ns). Subgroup analyses were conducted to

explore the role of caries index, definition for

assessment of child obesity using BMI, and the

study country of origin on the relationship

between obesity and dental caries.

Relationship between BMI and dental caries by measure

of obesity assessment. As Fig. 4 confirms, different

results are derived dependent on the measure used

to assess child weight status. A significant relation-

ship between dental caries and obesity is noted in

the studies using standardized measures for

assessing child obesity such as BMI-for-age centiles

(effect size = 0.189, 95% CI: 0.060–0.318, P = 0.004)

or IOTF cut-offs (effect size = 0.104, 95% CI: 0.060–0.180, P = 0.008). Interestingly, those that used Z-

scores (effect size = �0.147, 95% CI: �0.396 to

0.102, P = 0.248) provided nonsignificant findings,

along with studies using nonstandardized scales

(effect size = �0.030, 95% CI: �0.436 to 0.375,

P = 0.884). In exploring the impact of including

both Willerhausen’s (37) and Narksawat’s (44)

studies that employed nonstandardized measures

for assessment of child overweight and obesity, it

was appropriate to run a meta-analysis by denti-

tion type on data purely based from standardized

measures (i.e. excluding the two aforementioned

papers (37, 44). Contrary to previous analysis, a

significant positive relationship between obesity

Group byDentition type

Study name Statistics for each study Std diff in means and 95% CI

Std diffin means

Lowerlimit

Upperlimit P-Value

0.0831.010–0.0620.474Alm et al., 2008Permanent

Permanent

Permanent

Permanent

Permanent

Permanent

Permanent

Permanent

Permanent

0.0170.1750.0170.096Gerdin et al., 2008

0.8360.228–0.282–0.027

0.000–0.252–0.809–0.530Narksawat et al., 2009

0.0130.6610.0780.370Sharma and Hedge, 2009

0.5990.450–0.2590.095Tramini et al., 2009

0.1700.301–0.0530.124

0.5620.148–0.0800.034Chenetal., 1998Primary

Primary

Primary

Primary

Primary

Primary

Primary

Primary

Primary

0.1240.319–0.0380.140Macek and Mitola, 2008

0.0500.000–0.563–0.282Oliveira et al., 2008

0.6810.541–0.3530.094Sheller et al., 2009

0.0000.5440.1790.362Vazquez-Nava et al., 2009

Granville-Garcia et al., 2008

Sadeghi and Alizadch, 2007 (permanent teeth) 0.394 0.176 0.612 0.000

Willerhausen et al., 2007 (permanent teeth) 0.239 0.053 0.425 0.012

Kopycka-Kedzierawski et al., 2008 (primary teeth) –0.123 –0.386 0.140 0.360

Sadeghi and Alizadch, 2007 (primary teeth) 0.227 0.010 0.445 0.040

Willerhausen et al., 2007 (primary teeth) 0.159 –0.027 0.345 0.093

0.093 –0.033 0.220 0.149

Overall 0.104 0.001 0.206 0.049

–1.00 –0.50 0.00 0.50 1.00

Favours non-caries Favours caries

Meta analysis

Fig. 3. Forest plot illustrating overall relationship between BMI and dental caries within permanent and primarydentitions.

301


and dental caries was revealed within permanent

dentitions (effect size = 0.198, 95% CI: 0.046–0.350,P = 0.011; Fig. 5).

Relationship between BMI and dental caries bycountry (industrialized versus NIC)Subgroup analyses indicated that compared with

normal weight children, obese children from

industrialized countries (effect size = 0.122,

CI = 0.047–0.197, P = 0.001) had a significant rela-

tionship between obesity and caries in contrast to

those from NIC countries (effect size = 0.079,

CI = �0.106 to 0.264, P = 0.264; Fig. 6).

Discussion

The aim of the systematic review and meta-analy-

sis was to investigate and quantify the relationship

between obesity and dental caries in children. The

principal findings indicate a small overall associa-

tion between obesity and level of caries in the

permanent dentition when standardized defini-

tions for the assessment of child obesity are used,

such that caries is more prevalent in obese children

than normal weight children. No association

between obesity and caries was found in the

primary dentition. These results reflect previous

findings indicating that different levels of obesity

exist in school-age (6–18 years) and preschool chil-

dren, where obesity tends to be more prevalent in

the older age group (42) and suggest that obesity

and childhood caries may have a joint cause. There

may be a number of candidate variables. The con-

sumption of foods high in sugar and refined carbo-

hydrates would be a strong contender. Subgroup

analyses provided a deeper understanding of this

relationship and possible explanation of previous

conflicting reports.

BMI classificationsAssessment of child weight status was subject to

nonuniformity across studies used in the meta-

analyses. Some studies used the most recent CDC

2000 centiles for children of ‘underweight’, ‘nor-

mal’, ‘at risk of overweight’ and ‘overweight’

(overweight > 95th percentile) developed for the

United States (48), to determine weight status. In

the United States, a child BMI-for-age and gender

tracking at or above the 95th centile has been rec-

ommended and related to identify obesity (61).

Other studies employed the international age and

gender appropriate data sets for assessment of

child obesity recommended by the IOTF (49),

Group byBMI scale


Std diffin means

Lowerlimit

Upperlimit P-Value

0.5620.148–0.0800.034Chen et al., 1998BMI for age centilesBMI for age centilesBMI for age centilesBMI for age centilesBMI for age centilesBMI for age centilesBMI for age centilesBMI for age centilesBMI for age centiles

0.1240.319–0.0380.140Macek and Mitola, 2008

0.0130.6610.0780.370Sharma and Hedge, 20090.6810.541–0.3530.094Sheller et al., 20090.0000.5440.1790.362Vazquez-Nava et al., 20090.0040.3180.0600.1890.0831.010–0.0620.474Alm et al., 2008IOTF cut offs

IOTF cut offsIOTF cut offsIOTF cut offs

0.0170.1750.0170.096Gerdin et al., 20080.5990.450–0.2590.095Tramini et al., 20090.0080.1800.0280.1040.000–0.252–0.809–0.530Narksawat et al., 2009Other

OtherOtherOther


Sadeghi and Alizadch, 2007 (primary teeth) 0.227 0.010 0.445 0.040Sadeghi and Alizadch, 2007 (permanent teeth) 0.394 0.176 0.612 0.000

Willerhausen et al., 2007 (primary teeth) 0.159 –0.027 0.345 0.093Willerhausen et al., 2007 (permanent teeth) 0.239 0.053 0.425 0.012

0.8840.375–0.436–0.0300.8360.228–0.282–0.027Granville-Garcia et al., 2008Z-scores

Z-scoresZ-scores

0.0500.000–0.563–0.282Oliveira et al., 20080.2480.102–0.396–0.1470.0010.1670.0420.105Overall

–1.00 –0.50 0.00 0.50 1.00


Meta analysis

Fig. 4. Forest plot illustrating overall relationship between BMI and dental caries, with measure for assessment of childobesity as a moderator.

302

Hayden et al.

based on a reference population developed from

heterogeneous CS growth studies across six

nations. Two studies used other nonstandardized

data for assessment of child obesity (37, 44) which

may be more limited in their representation of pop-

ulation variability compared with the CDC growth

charts and IOTF cut-offs. Interestingly, the effect

size varied as a function of measure to assess

Group byType of country


Std diffin means

Lowerlimit

Upperlimit P-Value

0.0831.010–0.0620.474Alm et al., 2008Industrialised

0.0170.1750.0170.096Gerdin et al., 2008

0.1240.319–0.0380.140Macek and Mitola, 2008

0.5990.450–0.2590.095Tramini et al., 2009

0.0010.1970.0470.122

0.5620.148–0.0800.034Chen et al., 1998Newly-Industrialised

Industrialised

Newly-Industrialised

Industrialised


Industrialised


Industrialised


Industrialised


Industrialised


Industrialised




0.8360.228–0.282–0.027Granville-Garcia et al., 2008

0.000–0.252–0.809–0.530Narksawat et al., 2009

0.0500.000–0.563–0.282Oliveira et al., 2008

0.0130.6610.0780.370Sharma and Hedge, 2009

0.6810.541–0.3530.094Sheller et al., 2009


0.4040.264–0.1060.079

Overall


Willerhausen et al., 2007 (primary teeth) 0.159 –0.027 0.345 0.093

Willerhausen et al., 2007 (permanent teeth) 0.239 0.053 0.425 0.012



0.116 0.046 0.185 0.001

–1.00 –0.50 0.00 0.50 1.00


Meta analysis

Fig. 6. Country type used as a moderating variable to distinguish between BMI and dental caries relationships.

Group byDentition type


Std diffin means

Lowerlimit

Upperlimit P-Value

0.0831.010–0.0620.474Alm et al., 2008Permanent

Permanent

Permanent

Permanent

Permanent

Permanent

Permanent

0.0170.1750.0170.096Gerdin et al., 2008

0.8360.228–0.282–0.027

0.0130.6610.0780.370Sharma and Hedge, 2009

0.5990.450–0.2590.095Tramini et al., 2009

0.0110.3500.0460.198

0.5620.148–0.0800.034Chen et al., 1998Primary

Primary

Primary

Primary

Primary

Primary

Primary

Primary

0.1240.319–0.0380.140Macek and Mitola, 2008

0.0500.000–0.563–0.282Oliveira et al., 2008

Granville-Garcia et al., 2008




0.6810.541–0.3530.094Sheller et al., 2009


0.080 –0.068 0.228 0.289

Overall 0.138 0.032 0.243 0.011

–1.00 –0.50 0.00 0.50 1.00


Meta analysis

Fig. 5. A forest plot illustrating those studies using standardized definitions for assessment of child obesity, in relationto BMI and dental caries. Data moderated into permanent and primary dentitions.

303


child obesity using BMI (standardized versus

nonstandardized), and this variation in measure

may partly explain the inconclusive reports on the

relationship between dental caries and obesity in

the literature to date. In their recent investigation

into adult periodontitis and obesity, Suvan et al.

(62) have suggested that variation in BMI thresh-

olds contribute to the heterogeneity of meta-analyt-

ical data that can directly influence the resulting

effect size. The current meta-analysis was success-

ful in separating the different measures for assess-

ment of obesity to provide a more robust analysis

of the data to determine the relationship between

obesity and dental caries. It is also possible that dif-

ferential growth rates between children at similar

ages (49) and genetic susceptibility (26) may also

help to explain the mixed results into the relation-


Another confounding variable that may have influ-

enced this relationship was socio-economic class,

and thus, the investigation into industrialized and

NICs was highly relevant.

Socioeconomic statusThe differential pattern of childhood caries and

obesity observed between industrialized and NICs

might be explained by the excessive consumption

of foodstuffs, such as soft drinks (17) that contain

high quantities of refined carbohydrates, in indus-

trialized countries. Soft drink consumption has

been shown to be a risk factor for obesity and den-

tal caries (63). Previous reports have concluded an

inverse relationship to the one found within this

meta-analysis and propose that the generally

poorer eating practices in NICs are promoted by

adverse economic conditions and associated with

an increase in caries prevalence development (64).

Interestingly, Dye et al. (64) found that being Mexi-

can-American predicted increased caries preva-

lence among preschool children and associated this

with poor eating practices such as not eating suffi-

cient fruit and vegetables and missing breakfast

(64). Likewise, the growing trend of soft drink con-

sumption in NICs has been particularly associated

with hypocalcaemia among school-age children

(65), which may in turn lead to poor enamel devel-

opment or hypoplasia (66). Such conflicting results

highlight the caveats of meta-analysis to explore

multiple correlating factors. Thus, in the present

review, the moderating influence of SES to assist

explanation of the significant obesity–caries rela-

tionship may be a result of the comparative surplus

of supply of such unrefined foodstuffs in the

higher Gross Domestic Product (GDP) nations and

is likely to be a function of specific measures for

assessment of child weight status in these studies

(as above).

Dental caries in the permanent and or primary

dentition was also a moderating factor. Seen within

the context of previous research, the tentative link

between tooth development and dental caries

further highlights the notion that age may be a

significant confounding variable. One possible

explanation for this apparent age-dependent rela-

tionship could be a reflection of the increasingly

sedentary lifestyles led by children, particularly

within older children (43). Increased television

viewing habits in older children have been associ-

ated with an increasingly self-moderated and

unhealthy diet (67–69) and increased meal fre-

quency (70), particularly snack consumption (71),

which is often highly processed and high in sugar.

This specific sedentary behaviour provides an

opportunity for increased energy intake from

energy-dense poor-nutrition foods that can increase

the risk of weight gain and obesity (71) and also pro-

vides a window for increasing risk of dental decay

through an increased contact time between ferment-

able carbohydrates, in snack foods high in sugar

and dentition (72). Importantly, however, obesity

and dental caries represent multifactorial conditions

and thus, the notion that they represent a cause–effect relationship should be viewed with caution.

LimitationsThe main limitation to the present analysis is the

level of weighting of the studies included in the

meta-analysis. The study by Macek and Mitola (43)

was the most heavily weighted study based on par-

ticipant numbers, and this showed no significant

association between BMI-for-age and dental caries

in both the primary and permanent dentitions.

Thus, as there is one disproportionately strong

negative study, the true representativeness of these

results within the meta-analysis may be ques-

tioned.

Despite a stringent selection process, the quality

of the studies selected for the meta-analysis may be

subject to criticism. Many papers appeared incon-

sistent in both their definitions of dental caries as

well as assessment of child obesity; an indication

of possible measurement error across all studies.

For example, some interchanged between mea-

sures of reporting dental decay, using dft, DMFS,

DMFT or a combination of measures (16), which

could lead to variation in the levels of dental caries

304

Hayden et al.

identified. Our use of unadjusted data rather than

adjusted data should also be noted as a potential

limitation. However, not all studies gave adjusted

results and, where available, use of adjusted results

could also introduce bias through variation in

number and type of covariates adjusted for, there-

fore introducing variation of approach.

At the study level, Vazquez-Nava et al. (16)

recruited participants from a nursery school

engaged in a preventive dentistry programme.

This implies that the nursery was in an area identi-

fied as having a high incidence of tooth decay and

worthy of intervention. Thus, while the relatively

high prevalence of untreated childhood tooth

decay in Mexico has been noted (36, 37), sampling

bias might be partially responsible for the compar-

atively large effect observed in this study. Sam-

pling bias could also have occurred in the studies

by Sharma and Hegde (36) and Sheller et al. (57),

who both recruited from a single department of

paediatric dentistry.

As part of the analysis, studies were critically

appraised, and an average quality score was

attached to each. This provided some guidance as

to which papers were of better quality than others,

and the use of a scale provided a linear measure of

quality, rather than categorizing papers as ‘good’

or ‘bad’. The study by Gerdin et al. (35) was a lon-

gitudinal study and received the highest quality

score. This study found that BMI had an indepen-

dent effect on caries prevalence. There was no clear

pattern found in terms of study quality and signifi-

cant or nonsignificant relationships between obes-

ity and dental caries within the CS studies.

There were two potential sources of bias in the

studies themselves: the role of SES and the samples

used within the studies. Substantial research has

investigated the relationship of SES as a moderat-

ing variable to the onset of dental caries and BMI

(63, 73, 74). Separating papers into industrialized

and NICs attempts to account for SES, yet more

stringent assessment of SES would be advanta-

geous for future investigations. In this current

review, only two studies looked at SES directly (35,

59), and so separate analysis for this is limited.

Finally, potential sources of bias in the review

process itself can also be identified: selection bias,

validity bias and the use of meta-analysis as a pro-

cess. Primarily, papers were only selected from

online databases, and therefore, only published

and accessible papers written in English were con-

sidered, meaning unpublished studies were auto-

matically excluded. Often reports are not

published because of nonsignificance, which, in

this case, would have further confirmed the non-

significance of the results.

These results confirm a positive association

between obesity and dental caries in the permanent

dentition, although it is unclear what is the causa-

tive direction of this relationship? Future research

investigating the complexities of this relationship

is warranted and should employ experimental

designs to assess the common risk factors of obes-

ity and dental caries using more systematic and

universal measures of both obesity and permanent

dentitions. Health promotion interventions and

health education programmes promoting healthy

eating, targeting diets high in sugars and cario-

genic foods that are associated with weight gain,

within a common risk factor approach would

therefore assist in preventing obesity and dental

caries.

AcknowledgementsThere was no funding source for this study.

Author contributions

JC, RF and GH planned the study. CH and JB con-

ducted the literature search. CH, JB, JC and SC

undertook the data extraction. CH, JB and JC con-

ducted the meta-analysis. CH, JB and JC drafted

the manuscript. All authors critically revised the

manuscript.

Conflicts of interest

The authors declare that there are no conflicts of

interest.

References1. Nadeau KJ, Maahs DM, Daniels SR, Eckel RH. Child-

hood obesity and cardiovascular disease: links andprevention strategies. Nat Rev Cardiol 2011;8:513–25.

2. Alberti G, Zimmet P, Shaw J, Bloomgarden Z, Kauf-man F, Silink M. Type 2 diabetes in the young: theevolving epidemic: the international diabetes federa-tion consensus workshop. Diabetes Care2004;27:1798–811.

3. de Onis M, Blossner M, Borghi E. Global prevalenceand trends of overweight and obesity among pre-school children. Am J Clin Nutr 2010;92:1257–64.

305


4. Ogden CL, Carroll MD, Curtin LR, Lamb MM, FlegalKM. Prevalence of high body mass index in us chil-dren and adolescents, 2007–2008. JAMA 2010;303:242–9.

5. Whitaker RC, Wright JA, Pepe MS, Seidel KD, DietzWH. Predicting obesity in young adulthood fromchildhood and parental obesity. N Engl J Med1997;337:869–73.

6. Freedman DS, Khan LK, Dietz WH, Srinivasan SR,Berenson GS. Relationship of childhood obesity tocoronary heart disease risk factors in adulthood: thebogalusa heart study. Pediatrics 2001;108:712–8.

7. Olaiz-Fernandez GR-DJ, Shamah-Levy T, Rojas R,Villalpando-Hernandez S, Hernandez-Avila M, Sep-ulveda-Amor J. Encuesta nacional de salud y nutri-cion 2006. Cuernavaca, Mexico: Institute Nacional deSalud Publica, 2006; 85–103.

8. Hetherington MM, Cecil JE. Gene-environment inter-actions in obesity. Forum Nutr, 2010; 63:195–203.

9. Nicklas TA, Yang SJ, Baranowski T, Zakeri I, Beren-son G. Eating patterns and obesity in children. Thebogalusa heart study. Am J Prev Med 2003;25:9–16.

10. Vernarelli JA, Mitchell DC, Hartman TJ, Rolls BJ.Dietary energy density is associated with bodyweight status and vegetable intake in U.S. children. JNutr 2011;141:2204–10.

11. Miller P, Moore RH, Kral TV. Children’s daily fruitand vegetable intake: associations with maternalintake and child weight status. J Nutr Educ Behav2011;43:396–400.

12. Matthews VL, Wien M, Sabate J. The risk of childand adolescent overweight is related to types of foodconsumed. Nutr J 2011;10:71.

13. Muller MJ, Koertzinger I, Mast M, Langnase K,Grund A. Physical activity and diet in 5 to 7 yearsold children. Public Health Nutr 1999;2:443–4.

14. Petersen PE, Bourgeois D, Ogawa H, Estupinan-DayS, Ndiaye C. The global burden of oral diseases andrisks to oral health. Bull World Health Organ2005;83:661–9.

15. Beltran-Aguilar ED, Barker LK, Canto MT, Dye BA,Gooch BF, Griffin SO et al. Surveillance for dentalcaries, dental sealants, tooth retention, edentulism,and enamel fluorosis–united states, 1988–1994 and1999–2002. MMWR Surveill Summ 2005;54:1–43.

16. Vazquez-Nava F, Vazquez-Rodriguez EM, Saldivar-Gonzalez AH, Lin-Ochoa D, Martinez-Perales GM,Joffre-Velazquez VM. Association between obesityand dental caries in a group of preschool children inmexico. J Public Health Dent 2010;70:124–30.

17. WHO. Diet, nutrition and the prevention of chronicdiseases. World Health Organ Tech Rep Ser, 2003/05/29 edition, 2003.

18. Rugg-Gunn AJ. Nutrition, diet and dental publichealth. Community Dent Health 1993;10(Suppl 2):47–56.

19. Selwitz RH, Ismail AI, Pitts NB. Dental caries. Lancet2007;369:51–9.

20. Henderson L, Gregory J, Irving K, Swan G. Thenational diet and nutrition survey: adults aged 19–64 years, volume 2: energy, protein, carbohydrate,fat and alcohol intake. London: TSO; 2003.

21. Joint Health Surveys Unit University College Lon-don and Medical Research Council, Social and PublicHealth Sciences Unit; Scottish Health Survey, 2003

— 2009 Colchester. Essex: UK Data Archive [distri-butor].

22. Palmer CA, Kent R Jr, Loo CY, Hughes CV, StutiusE, Pradhan N et al. Diet and caries-associated bacte-ria in severe early childhood caries. J Dent Res2010;89:1224–9.

23. Arcella D, Ottolenghi L, Polimeni A, Leclercq C. Therelationship between frequency of carbohydratesintake and dental caries: a cross-sectional study inItalian teenagers. Public Health Nutr 2002;5:553–60.

24. Marinho VC, Higgins JP, Sheiham A, Logan S. Fluo-ride toothpastes for preventing dental caries in chil-dren and adolescents. Cochrane Database Syst Rev2003;1:CD002278.

25. Marinho VC, Higgins JP, Logan S, Sheiham A. Fluo-ride varnishes for preventing dental caries in chil-dren and adolescents. Cochrane Database Syst Rev2002;(3):CD002279.

26. Wang X, Willing MC, Marazita ML, Wendell S, War-ren JJ, Broffitt B et al. Genetic and environmental fac-tors associated with dental caries in children: theIowa fluoride study. Caries Res 2012;46:177–84.

27. Ludwig DS, Peterson KE, Gortmaker SL. Relationbetween consumption of sugar-sweetened drinksand childhood obesity: a prospective, observationalanalysis. Lancet 2001;357:505–8.

28. Linardakis M, Sarri K, Pateraki MS, Sbokos M, Kafa-tos A. Sugar-added beverages consumption amongkindergarten children of Crete: effects on nutritionalstatus and risk of obesity. BMC Public Health2008;8:279.

29. Schulze MB, Manson JE, Ludwig DS, Colditz GA,Stampfer MJ, Willett WC et al. Sugar-sweetened bev-erages, weight gain, and incidence of type 2 diabetesin young and middle-aged women. JAMA2004;292:927–34.

30. Al-Dlaigan YH, Shaw L, Smith A. Dental erosion in agroup of British 14-year-old school children. Part II:influence of dietary intake. Br Dent J 2001;190:258–61.

31. Marshall TA, Levy SM, Broffitt B, Warren JJ, Eichen-berger-Gilmore JM, Burns TL et al. Dental caries andbeverage consumption in young children. Pediatrics2003;112:e184–91.

32. Ismail AI, Burt BA, Eklund SA. The cariogenicity ofsoft drinks in the United States. J Am Dent Assoc1984;109:241–5.

33. Alm A, Fahraueus C, Wendt LK, Koch G, Andersson-Gare B, Birkhed D. Body adiposity status in teenagersand snacking habits in early childhood in relation toapproximal caries at 15 years of age. InternationalJournal of Paediatric Dentistry 2008;18:189–196.

34. Bailleul-Forestier I, Lopes K, Souames M, Azoguy-Levy S, Frelut ML, Boy-Lefevre ML. Caries experi-ence in a severely obese adolescent population. Int JPaediatr Dent 2007;17:358–63.

35. Gerdin EW, Angbratt M, Aronsson K, Eriksson E, Jo-hansson I. Dental caries and body mass index bysocio-economic status in Swedish children. Commu-nity Dent Oral Epidemiol 2008;36:459–65.

36. Sharma A, Hegde AM. Relationship between bodymass index, caries experience and dietary prefer-ences in children. J Clin Pediatr Dent 2009;34:49–52.

37. Willershausen B, Moschos D, Azrak B, Blettner M.Correlation between oral health and body mass

306

Hayden et al.

index (BMI) in 2071 primary school pupils. Eur JMed Res 2007;12:295–9.

38. Chen W, Chen P, Chen SC, Shih WT, Hu HC. Lack ofassociation between obesity and dental caries inthree-year-old children. Zhonghua Min Guo Xiao ErKe Yi Xue Hui Za Zhi 1998;39:109–11.

39. Granville-Garcia AF, de Menezes VA, de Lira PI,Ferreira JM, Leite-Cavalcanti A. Obesity and dentalcaries among preschool children in Brazil. Rev SaludPublica 2008;10:788–95.

40. Hilgers KK, Kinane DE, Scheetz JP. Associationbetween childhood obesity and smooth-surface car-ies in posterior teeth: a preliminary study. PediatrDent 2006;28:23–8.

41. Hong L, Ahmed A, McCunniff M, Overman P, Ma-thew M. Obesity and dental caries in children aged 2–6 years in the United States: national health andnutrition examination survey 1999–2002. J PublicHealth Dent 2008;68:227–33.

42. Kopycka-Kedzierawski DT, Auinger P, Billings RJ,Weitzman M. Caries status and overweight in 2- to 18-year-old us children: findings from national surveys.Community Dent Oral Epidemiol 2008;36:157–67.

43. Macek MD, Mitola DJ. Exploring the associationbetween overweight and dental caries among USchildren. Pediatr Dent 2006;28:375–80.

44. Narksawat K, Tonmukayakul U, Boonthum A. Asso-ciation between nutritional status and dental cariesin permanent dentition among primary schoolchil-dren aged 12–14 years, Thailand. Southeast Asian JTrop Med Public Health 2009;40:338–44.

45. Sadeghi M, Alizadeh F. Association between dentalcaries and body mass index-for-age among 6–11-year-old children in Isfahan in 2007. J Dent Res DentClin Dent Prospects 2007;1:119–24.

46. Kantovitz KR, Pascon FM, Rontani RM, Gaviao MB.Obesity and dental caries–a systematic review. OralHealth Prev Dent 2006;4:137–44.

47. Flegal KM, Ogden CL. Childhood obesity: are we allspeaking the same language? Adv Nutr 2011;2:159S–66S.

48. Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z et al. 2000 CDCgrowth charts for the united states: methods anddevelopment. Vital Health Stat 11 2002;246:1–190.

49. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Estab-lishing a standard definition for child overweightand obesity worldwide: International survey. BMJ2000;320:1240–3.

50. WHO. Who child growth standards: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: methodsand development. Geneva: World Health Organiza-tion, Department of Nutrition for Health and Devel-opment; 2006.

51. Moher D, Liberati A, Tetzlaff J, Altman DG. Pre-ferred reporting items for systematic reviews andmeta-analyses: the prisma statement. Ann InternMed 2009;151:264–9, W64.

52. Higgins J, Altman D. Assessing risk of bias inincluded studies. In: Higgins J, Green SP, editors:Cochrane handbook for systematic reviews of inter-ventions. Oxford: Wiley-Blackwell, 2008; 187–242.

53. Wells G, Shea B, O’Connell D, Peterson J, Welch V,Losos M et al. The Newcastle-Ottawa Scale (NOS)

for assessing the quality of non-randomised studiesin meta-analyses. Department of Epidemiology andCommunity Medicine, University of Ottawa,Canada, 2005. Available from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp

54. Sanderson S, Tatt ID, Higgins JP. Tools for assessingquality and susceptibility to bias in observational stud-ies in epidemiology: a systematic review and anno-tated bibliography. Int J Epidemiol 2007;36:666–76.

55. Weightman AL, Mann MK, Sander L, Turley RL.Health Evidence Bulletins Wales: A systematicapproach to identifying the evidence. Project Metho-dology 5. Cardiff: National Public Health Service forWales, 2004. Available at: http://hebw.cf.ac.uk/projectmethod/title.htm

56. Borenstein M, Hedges L, Higgins J, Rothstein H.Comprehensive meta-analysis version 2. Engelwood,NJ: Biostat; 2005.

57. Sheller B, Churchill SS, Williams BJ, Davidson B.Body mass index of children with severe early child-hood caries. Pediatr Dent 2009;31:216–21.

58. Tramini P, Molinari N, Tentscher M, Demattei C,Schulte AG. Association between caries experienceand body mass index in 12-year-old French children.Caries Res 2009;43:468–73.

59. Oliveira LB, Sheiham A, Bonecker M. Exploring theassociation of dental caries with social factors andnutritional status in Brazilian preschool children.Eur J Oral Sci 2008;116:37–43.

60. Hammer LD, Kraemer HC, Wilson DM, Ritter PL,Dornbusch SM. Standardized percentile curves ofbody-mass index for children and adolescents. Am JDis Child 1991;145:259–63.

61. Krebs NF, Himes JH, Jacobson D, Nicklas TA, Guil-day P, Styne D. Assessment of child and adolescentoverweight and obesity. Pediatrics 2007;120(Suppl4):S193–228.

62. Suvan J, D’Aiuto F, Moles DR, Petrie A, Donos N.Association between overweight/obesity and peri-odontitis in adults. A systematic review. Obes Rev2011;12:e381–404.

63. Marshall TA, Eichenberger-Gilmore JM, Broffitt BA,Warren JJ, Levy SM. Dental caries and childhoodobesity: roles of diet and socioeconomic status. Com-munity Dent Oral Epidemiol 2007;35:449–58.

64. Dye BA, Shenkin JD, Ogden CL, Marshall TA, LevySM, Kanellis MJ. The relationship between healthfuleating practices and dental caries in children aged 2–5 years in the United States, 1988–1994. J Am DentAssoc 2004;135:55–66.

65. Mazariegosramos E, Guerreroromero F, Rodri-guezmoran M, Lazcanoburciaga G, Paniagua R,Amato D. Consumption of soft drinks with phospho-ric-acid as a risk factor for the development of hypo-calcemia in children – a case–control study. J Pediatr1995;126:940–2.

66. Nikiforuk G, Fraser D. Etiology of enamel hypopla-sia and interglobular dentin – roles of hypocalcemiaand hypophosphatemia. Metab Bone Dis Relat1979;2:17–23.

67. Matheson DM, Killen JD, Wang Y, Varady A, Robin-son TN. Children’s food consumption during televi-sion viewing. Am J Clin Nutr 2004;79:1088–94.

68. Temple JL, Giacomelli AM, Kent KM, Roemmich JN,Epstein LH. Television watching increases motivated

307


responding for food and energy intake in children.Am J Clin Nutr 2007;85:355–61.

69. Sisson SB, Church TS, Martin CK, Tudor-Locke C,Smith SR, Bouchard C et al. Profiles of sedentarybehavior in children and adolescents: the USnational health and nutrition examination survey,2001–2006. Int J Pediatr Obes 2009;4:353–9.

70. Stroebele N, de Castro JM. Television viewing isassociated with an increase in meal frequency inhumans. Appetite 2004;42:111–3.

71. Campbell KJ, Crawford DA, Hesketh KD. Australianparents’ views on their 5–6-year-old children’s foodchoices. Health promot Int 2007;22:11–8.

72. Palmer CA. Dental caries and obesity in children:different problems, related causes. Quintessence Int2005;36:457–61.

73. Williams D, Croucher R, Marcenes W, O’Farrell M.The prevalence of dental erosion in the maxillaryincisors of 14-year-old school-children living intower hamlets and hackney, London, UK. Int Dent J1999;49:211–6.

74. Kazoullis S, Seow WK, Holcombe T, Newman B,Ford D. Common dental conditions associated withdental erosion in schoolchildren in Australia. PediatrDent 2007;29:33–9.

308

Hayden et al.

obesity and dental caries in children: a systematic review and meta-analysis

Documents