childhood stunting and caries increment in permanent teeth: a three and a half year longitudinal...

DOI: 10.1111/j.1365-263X.2012.01229.x

a three and a half year longitu
Childhood stunting and caries increment in permanent teeth:
dinal study in Peru

ELSA K. DELGADO-ANGULO1,2, MARTIN H. HOBDELL1 & EDUARDO BERNABE3

1Research Department of Epidemiology and Public Health, University College London, London, UK, 2Departamento

Academico de Odontologıa Social, Universidad Peruana Cayetano Heredia, Lima, Peru, and 3Unit of Dental Public Health,

King’s College London Dental Institute, London, UK

International Journal of Paediatric Dentistry 2012

Background. Malnutrition has been consistently

associated with caries in primary teeth, although

an effect on permanent teeth has not been estab-

lished because of the few longitudinal studies.

Aim. To explore the association between stunting

and caries increment in permanent teeth over

3.5 years.

Design. In 2003, 121 children aged 7–9 years were

randomly selected from nine underserved com-

munities in Lima (Peru). Parents provided demo-

graphic information and a food diary for their

children. Clinical examinations included assess-

ments of height, weight, oral hygiene, and dental

caries. Stunting was defined using the 2000 CDC

Correspondence to:

E. K. Delgado-Angulo, Research Department of

Epidemiology and Public Health, University College

London, 1-19 Torrington Place, London WC1E 6BT, UK.

E-mail: [email protected]

� 2012 The Authors

International Journal of Paediatric Dentistry � 2012 BSPD, IAPD and Bla

and 2007 WHO standards. In 2006, 83 children

were re-examined, and the 3.5-year net DMFS

increment was calculated. The association

between stunting and net DMFS increment was

assessed using negative binomial regression.

Results. Stunting was related to net DMFS incre-

ment after adjustment for sex and age, oral

hygiene, sugary snacks between meals, and caries

experience in primary and permanent teeth. Con-

sistent results were found when using either the

2000 CDC (incidence rate ratio: 1.61; 95%CI:

1.07, 2.44) or 2007 WHO standards (IRR: 1.79;

95%CI: 1.28, 2.51).

Conclusion. Stunting was a significant risk factor

for caries increment in permanent teeth over a

3.5-year period, independent of other well-known

risk factors for caries development.

Introduction

Under-nutrition refers to the insufficient

intake of energy and nutrients that support

growth and development as well as the main-

tenance of health1,2, resulting in stunting and

wasting together with micronutrients defi-

ciencies (essentially vitamins and minerals,

most commonly zinc)3. Stunting (defined as

inadequate height for age) is considered a

stronger indicator of long-term under-nutri-

tion than wasting (defined as inadequate

weight for height)4, especially in Latin Ameri-

can countries where populations show a low

prevalence of wasting even when other indi-

cators of poor health are evident4,5.

Under-nutrition remains a damaging condi-

tion in low- and middle-income countries4

and is linked with several negative outcomes

during childhood and adulthood. Conse-

quences of under-nutrition include less

schooling4,6, diminished intellectual function-

ing6,7, impaired child development7, increased

susceptibility to infection7,8, and increased

mortality rate4. Under-nutrition may also

affect the development and integrity of the

oral cavity as well as the progression of oral

diseases9. Dental caries, however, has tradi-

tionally been considered separately from sys-

temic diseases, and important relationships

and causal mechanisms may have been over-

looked10,11.

A review of the literature published up to

2003 revealed that malnutrition was associ-

ated with caries in primary teeth, although

an effect on permanent teeth could not be

established because of the small number of

longitudinal studies12. To the best of our

knowledge, only three longitudinal studies

have explored the relationship between mal-

nutrition and caries in permanent teeth, with

ckwell Publishing Ltd 1

2 E. K. Delgado-Angulo, M. H. Hobdell & E. Bernabe

contradictory results13–15. The first study was

conducted in an underserved community in

Lima, Peru. Ninety-four of 209 children aged

6–11 months in 1986 were re-examined in

1992 (attrition rate: 55%). Stunting was

defined as a height-for-age below 95% of the

median in the 1977 National Center for

Health Statistics ⁄World Health Organisation

(NCHS ⁄WHO) standards. The authors con-

cluded that a single, moderate malnutrition

episode in infancy was associated with

increased caries in permanent teeth, although

no adjustment for confounders was

reported13. The second study was carried out

in two primary schools in Dares Salam, Tan-

zania. One hundred and forty-five of 296

children (mean age at baseline: 7.6 years)

were followed-up from 1997 to 2003 (attri-

tion rate: 51%). Malnourishment was defined

as a body mass index z-score below )1.96

standard deviations (SD) according to the

1990 British growth reference curves. The

study concluded that malnourishment at

baseline was not predictive of caries 6 years

later14. The third study was nested in a popu-

lation-based birth cohort study that started in

1993 in Pelotas, Brazil, and used data from

339 children when they were 1, 4, 6 and

12 years old. Malnutrition was defined as a

height-for-age z-score below )2 SD according

to the 1977 NCHS ⁄WHO standards. Malnutri-

tion at ages 1 and 4 was positively related to

caries prevalence and severity at age 12 in

the unadjusted models. Only a height-for-age

deficit at age 1 remained, however, as a sig-

nificant predictor of caries experience at age

12 in the fully adjusted model15.

Because of the scarcity of longitudinal stud-

ies and the inconsistency of their findings, a

study was planned to explore the association

between under-nutrition (as indicated by

stunting) and caries increment in permanent

teeth over a period of 3.5 years in a sample of

Peruvian children.

Material and methods

Study population

In summer 2003, 121 children aged 7–9 years

(28% of the total target population) were

International Journal of Pa

randomly selected from nine underserved

communities linked to the Health Centre in

Zapallal Alto (Lima, Peru), using stratified

cluster sampling method. In each community,

street blocks were considered as clusters and

chosen with a probability proportional to

their size (i.e., the number of households per

block). This selection procedure guaranteed

that each household had an equal probability

of selection. All households in the chosen

blocks were screened for eligibility, and those

with a child aged 7–9 years (i.e., they had

had their seventh birthday, but not yet

reached their tenth birthday) were invited to

participate16. In all, 121 children participated

in the baseline study (response rate: 98%). In

winter 2006 (41–44 months later, 42 months

on average), all households who took part in

the baseline study were revisited and 83 chil-

dren were clinically re-examined (follow-up

rate: 69%). The only reason for children

being lost to follow-up was change of resi-

dence.

Ethical clearance was granted from the Eth-

ics Research Committee at the Universidad

Peruana Cayetano Heredia (Lima, Peru). Only

those children who agreed to participate and

whose parents signed a consent form were

enrolled in the study.

Data collection

During home interviews at baseline, parents

provided their children’s basic demographic

information and completed a 4-day food diary

to assess the frequency of sugar intake of

their children, and the frequency of sugary

snacks between meals was measured as the

average consumption of sweets between

meals during the 4 days. Data collection was

conducted during the annual school break

(summer time), which improved the accuracy

of parental reports regarding their children’s

diet.

Anthropometric measures (weight and

height) were conducted by one calibrated

examiner following standardised procedures17.

Weight was measured on a calibrated scale

with the child wearing light clothing, and

height was measured with a wall-mounted

tape standing barefoot. A z-score (the number


ediatric Dentistry � 2012 BSPD, IAPD and Blackwell Publishing Ltd

Stunting and caries increment 3

of SD from the reference population) for

height-for-age was calculated for each child

using the 2000 CDC18 and the 2007 WHO ref-

erence standards19. Stunting was defined as

height-for-age below the fifth percentile

(equivalent to )1.645 SD) of the 2000 CDC

reference population18 and below 2 SD of the

2007 WHO reference population19.

The clinical examinations for oral hygiene

and dental caries were conducted by the same

examiner who performed the anthropometric

measures, with children seated on a portable

chair under natural light and using front-sur-

face mouth mirrors. Oral hygiene at baseline

was assessed by the Simplified Oral Hygiene

Index (OHI-S), which records the extent of

debris and calculus on six different tooth sur-

faces20. Diagnosis of tooth condition was

visual, and no radiographs were taken. Teeth

were dried with cotton pellets before examina-

tion, and a dental explorer was used to remove

debris if needed. Dental caries was diagnosed

at the caries into dentine threshold according

to the British Association for the Study of

Community Dentistry (BASCD) diagnostic cri-

teria21. To assess intra- and inter-examiner

reliability, replicate examinations were per-

formed on 20 children from the study popula-

tion by the examiner and a fully trained

assessor on the BASCD criteria. Kappa values

for intra- and inter-examiner reliability were

0.93 and 0.85, respectively, at surface level.

Caries increment between baseline and follow-

up was the outcome measure, which was com-

puted by comparing the status of each tooth

surface at baseline with that at follow-up. The

3.5-year net DMFS increment was computed

for each child by subtracting the number of

reversals from the caries increment22,23.

Statistical analysis

All analyses were carried out using STATA SE

version 11 (Stata corp. LP, College Station,

TX, USA) and incorporated the sampling

design of the baseline survey. To assess the

impact of attrition, children successfully fol-

lowed-up, and those lost to follow-up were

initially compared in terms of their baseline

demographic, behavioural, and clinical char-

acteristics.



The frequency of sugary snacks between

meals and the oral hygiene level had skewed

distributions and were therefore dichoto-

mised. The number of sugary snacks between

meals ranged between 0 and three, with 65%

of children reporting no snacking. As such,

this variable could not be analysed as contin-

uous and had to be dichotomised, with the

only possible cut-off to allow meaningful

comparison being ‘less often than daily’ ver-

sus ‘on a daily basis’24. In addition, children’s

OHI-S scores were positively skewed, with no

values above 3, and were therefore dichoto-

mised as ‘good’ if the OHI-S score was

between 0 and 1.2, or ‘regular ⁄poor’ if it was

between 1.3 and 6.025.

The association between stunting and net

DMFS increment was assessed in separate

models for each definition of stunting (2000

CDC and 2007 WHO standards) and modelled

using negative binomial regression as the out-

come was a count variable with overdisper-

sion. Negative binomial regression models

provide incidence rate ratios (IRR), which are

interpreted as a ratio of mean values26. The

association between each definition of stun-

ting and net DMFS increment was assessed

after sequential adjustment for baseline

demographic factors (sex and age) in Model

1, additionally for baseline behavioural factors

in Model 2 (sugary snacks between meals and

oral hygiene) and further for baseline levels

of caries experience (dmfs and DMFS indices)

in Model 3.

Results

This study analysed data on 83 children (46

girls and 37 boys) who were followed-up

over 3.5 years. There were no significant

differences in baseline demographic, behavio-

ural, and clinical characteristics between

children followed-up and lost to follow-up

(P > 0.10 for all variables except sex, for

which P = 0.056). Overall, 30% and 17% of

children were stunted as defined by the 2000

CDC and 2007 WHO standards, respectively.

The 2000 CDC standards classified 11 extra

children as being stunted. The mean DMFS

was 3.04 (SD: 2.53, range: 0–12) at baseline

and 5.10 (SD: 4.86, range: 0–25) at follow-up.

ckwell Publishing Ltd


The mean 3.5-year net DMFS increment was

2.47 tooth surfaces (SD: 3.33, range: 0–19).

Table 1 shows the baseline comparison of

demographic, behavioural, and clinical charac-

teristics between children with and without

stunting, as defined by the 2000 CDC stan-

dards. No differences were found between

groups, except for the proportion of children

with poor oral hygiene (P = 0.008). There

were more children with poor oral hygiene in

the stunted group compared to the non-

stunted group (96% vs 84% respectively).

Stunting, as defined by the 2000 CDC stan-

dards, was not related to net DMFS increment

in the unadjusted model. This association

became significant, however, after initial

adjustment for baseline demographic charac-

teristics (sex and age) and remained significant

after further adjustment for dental behaviours

(sugary snacks between meals and oral

hygiene status) and baseline caries experience

(DMFS and dmfs indices). In the fully adjusted

model (Model 1C), the net DMFS increment

over 3.5 years was 61% higher in stunted chil-

dren compared to their counterparts (Table 2).

Table 1. Comparison of baseline demographic, behavioural, andstunting (defined by the 2000 CDC standards).

Baseline characteristics

Stunting by 2000

‡ 5th percentile

Sex, nGirls 31 (53%)Boys 27 (47%)

Age, n7 years 12 (21%)8 years 22 (38%)9 years 24 (41%)

Sugary snacks between meals, nLess often than daily 37 (64%)On a daily basis 21 (36%)

Oral hygiene status, nGood 9 (16%)Regular ⁄ Poor 49 (84%)

Number of teeth, mean (SD)Primary 10.55 (2.64)Permanent 12.98 (2.63)

Caries experience, mean (SD)dmfs 9.98 (6.88)DMFS 2.93 (2.23)% D ⁄ DMFSb 98.94 (7.29)

aCategorical variables were compared using logistic regression, couvariables using linear regression.bOnly 47 non-stunted vs 19 stunted children were compared (i.e., those


Table 3 shows the baseline comparison

between children with and without stunting,

as defined by the 2007 WHO standards. There

were no differences between groups, except

for caries experience in permanent teeth

(P = 0.048). Stunted children had higher base-

line DMFS scores than non-stunted children

(4.71 vs 2.70 respectively). Stunting, as defined

by the 2007 WHO standards, was significantly

related to net DMFS increment in the unad-

justed model. Furthermore, stunting was a sig-

nificant predictor of net DMFS increment

3.5 years later even after sequential adjust-

ment for baseline demographic characteristics,

dental behaviours, and caries experience in

primary and permanent teeth. In the fully

adjusted model (Model 2C), stunted children

had a 79% higher 3.5-year net DMFS incre-

ment than their counterparts (Table 4).

Discussion

This longitudinal study provides support for

the association between growth stunting and

dental caries increment in the permanent

clinical characteristics between children with and without

CDC standards

P valuea< 5th percentile

0.48315 (60%)10 (40%)

0.5742 (8%)

14 (56%)9 (36%)

0.47417 (68%)8 (32%)

0.0081 (4%)

24 (96%)

11.20 (1.83) 0.07812.44 (1.78) 0.243

12.28 (10.25) 0.5253.28 (3.17) 0.726

99.34 (2.87) 0.736

nt variables using negative binomial regression and continuous

with DMFS > 0 to avoid division by zero).



Table 2. The association of stunting (defined by the 2000 CDC standards) with 3.5-year net DMFS increment afteradjustment for baseline demographic, behavioural, and clinical characteristics (n = 83).


Model 1Aa Model 1Ba Model 1Ca

IRRb (95% CI) IRRb (95% CI) IRRb (95% CI)

Stunting by 2000 CDC standards‡5th percentile 1.00 1.00 1.00<5th percentile 1.62 (1.09, 2.41)* 1.67 (1.18, 2.36)** 1.61 (1.07, 2.44)*

SexBoys 1.00 1.00 1.00Girls 0.88 (0.54, 1.44) 0.89 (0.54, 1.48) 0.86 (0.49, 1.50)

Age7 years 1.00 1.00 1.008 years 1.79 (1.35, 2.36)*** 1.79 (1.28, 2.52)** 1.70 (1.26, 2.30)**9 years 3.03 (2.21, 4.15)*** 2.91 (2.28, 3.71)*** 2.48 (1.51, 4.06)***

Sugary snacks between mealsLess often than daily 1.00 1.00On a daily basis 0.92 (0.74, 1.16) 0.91 (0.73, 1.13)

Oral hygiene statusGood 1.00 1.00Regular ⁄ Poor 0.80 (0.54, 1.18) 0.81 (0.53, 1.23)

Caries experience in primary teeth (dmfs)1-surface increase 0.99 (0.96, 1.03)

Caries experience in permanent teeth (DMFS)1-surface increase 1.07 (0.96, 1.19)

aModel 1A adjusted for demographic characteristics (sex and age), Model 1B additionally adjusted for dental behaviours (sugary snacksbetween meals and oral hygiene status) and Model 1C further adjusted for levels of caries experience (dmfs and DMFS) at baseline.bNegative binomial regression models were fitted and incidence rate ratios (IRR) reported.*P < 0.05, **P < 0.01, ***P < 0.001.


dentition. Overall, stunted children developed

more caries than normal children over the

3.5 years of follow-up. The magnitude of this

effect was such that the net caries increment

in permanent teeth was higher by around

61–79% in stunted children compared to

their counterparts. This is an interesting find-

ing because we controlled for a number of

well-known determinants of dental caries,

including demographic factors, sugar intake

frequency, oral hygiene level, and prior caries

experience (both in primary and in perma-

nent teeth), the latter being regarded as the

strongest predictor of future caries develop-

ment. Furthermore, this finding was robust

across the two definitions of stunting assessed

here, namely the 2000 CDC and 2007 WHO

standards.

Despite methodological differences between

studies, our findings are in-line with those

reported in the previously cited longitudinal

studies in Peru 13 and that in Pelotas in Bra-

zil15. Nevertheless, although longitudinal stud-

ies of caries are designed to assess the



progression of caries over time, the above

studies used caries at the follow-up examina-

tion as the outcome measure rather than

caries increment from baseline to follow-up.

The former approach does not provide an

indication of change over time and, more

importantly, does not account for examiners

misclassification or reversals, even when con-

trolling for baseline levels of caries. By using

caries increment, this study provided a more

stringent assessment of the association of stun-

ting with change in caries experience22,23.

Several mechanisms have been proposed to

explain the link between under-nutrition

and caries. First, under-nutrition results in

immunological deficiencies7,8 which play an

essential role in the aetiology of chronic multi-

factorial infectious diseases, including dental

caries27. Second, local effects of under-nutri-

tion include enamel hypoplasia12,28 which, in

turn, has been associated with caries develop-

ment12. Another local change associated with

under-nutrition is salivary gland hypofunction

which may increase caries risk via decreased


Table 3. Comparison of baseline demographic, behavioural, and clinical characteristics between children with and withoutstunting (defined by the 2007 WHO standards).

Characteristics

Stunting by 2007 WHO standards

P valuea‡ 2 SD < 2 SD

Sex, n 0.512Girls 37 (54%) 9 (64%)Boys 32 (46%) 5 (36%)

Age, n 0.7017 years 13 (18%) 1 (7%)8 years 28 (41%) 8 (57%)9 years 28 (41%) 5 (36%)

Sugary snacks betweenmeals, n

0.167

Less often than daily 43 (62%) 11 (79%)On a daily basis 26 (38%) 3 (21%)

Oral hygiene status, n 0.200Good 10 (14%) 0 (0%)Regular ⁄ Poor 59 (86%) 14 (100%)

Number of teeth, mean (SD)Primary 10.75 (2.52) 10.71 (1.98) 0.886Permanent 12.81 (2.50) 12.86 (1.99) 0.929

Caries experience, mean (SD)dmfs 9.80 (7.20) 15.00 (10.63) 0.257DMFS 2.70 (2.24) 4.71 (3.24) 0.048% D ⁄ DMFSb 99.06 (6.87) 99.04 (3.47) 0.990

aCategorical variables were compared using logistic regression, count variables using negative binomial regression and continuousvariables using linear regression.bOnly 53 non-stunted vs 13 stunted children were compared (i.e., with DMFS>0 to avoid division by zero).


salivary flow rate, decreased buffering capacity,

and decreased salivary constituents, particu-

larly proteins12,29. Third, altered eruption tim-

ing, which may affect age-specific exposure

time to cariogenic conditions, has also been

linked to under-nutrition12,13,29. In this regard,

previous studies have provided conflicting

results, with some authors suggesting a delayed

eruption and exfoliation of primary teeth but

an early eruption of permanent teeth13, and

others sustaining a tardy exfoliation of primary

teeth and emergence of permanent teeth,

among children with under-nutrition29. In this

study, though, there was no evidence of altered

eruption of primary or permanent teeth (nei-

ther at baseline nor at follow-up) in stunted

children as compared to non-stunted children,

which implies that a differential emergence

time may not be a major mechanism underly-

ing the link between stunting and dental caries

in the permanent teeth of this sample.

Further research should focus on the possi-

ble mechanisms underlying this association.

Longitudinal studies are of particular impor-

tance because of recent evidence suggesting a


bidirectional association, where severe dental

caries may disrupt growth mainly by affecting

food intake and sleep11,27. Only intervention

studies could provide solid evidence of a cau-

sal relationship, however, between under-

nutrition and dental caries, as suggested by

the results of a randomised trial on the effec-

tiveness of a nutritional program in reducing

early childhood caries30.

Some limitations of this study need to be

discussed. First, the sample was drawn from

underserved communities, which are charac-

terised by the lack of basic services such as

drinking water and sanitation, and poor

access to electricity, rubbish collection ser-

vices, public transport, and health care ser-

vices. As such, it is not representative of the

general child population in Peru. Restricting

the sample to underserved communities,

however, provided a control for confounders

during the study design as all children were

generally exposed to similar social and envi-

ronmental circumstances. It also allowed us

to boost the number of children experiencing

stunting for analysis. Second, our study had



Table 4. The association of stunting (defined by the 2007 WHO standards) with 3.5-year net DMFS increment afteradjustment for baseline demographic, behavioural and clinical characteristics (n = 83).


Model 2Aa Model 2Ba Model 2Ca

IRRb (95% CI) IRRb (95% CI) IRRb (95% CI)

Stunting by 2007 WHO standards‡2 SD 1.00 1.00 1.00<2 SD 1.85 (1.32, 2.58)*** 1.89 (1.46, 2.47)*** 1.79 (1.28, 2.51)**

SexBoys 1.00 1.00 1.00Girls 0.84 (0.52, 1.35) 0.85 (0.52, 1.37) 0.83 (0.49, 1.41)

Age7 years 1.00 1.00 1.008 years 1.87 (1.33, 2.63)*** 1.89 (1.25, 2.84)** 1.83 (1.28, 2.62)**9 years 3.09 (2.30, 4.16)*** 3.00 (2.39, 3.75)*** 2.72 (1.78, 4.15)***

Sugary snacks between mealsLess often than daily 1.00 1.00On a daily basis 0.91 (0.69, 1.20) 0.90 (0.70, 1.17)

Oral hygiene statusGood 1.00 1.00Regular ⁄ Poor 0.81 (0.56, 1.17) 0.82 (0.57, 1.18)

Caries experience in primary teeth (dmfs index)1-surface increase 0.99 (0.96, 1.03)

Caries experience in permanent teeth (DMFS index)1-surface increase 1.04 (0.94, 1.16)

aModel 2A adjusted for demographic characteristics (sex and age), Model 2B additionally adjusted for dental behaviours (sugarysnacks between meals and oral hygiene status) and Model 2C further adjusted for levels of caries experience (dmfs and DMFS) atbaseline.bNegative binomial regression models were fitted and incidence rate ratios (IRR) reported.*P < 0.05, **P < 0.01, ***P < 0.001


an attrition rate of 31%, which may have

influenced the present findings. Every

attempt, however, was made to increase par-

ticipation in the follow-up examination. This

is supported by the fact that moving out of

the study’s geographical area (and not refusal

to participate) was the only reason for drop-

outs. More importantly, we found that chil-

dren lost to follow-up were not different from

those followed-up in terms of their demo-

graphic, behavioural, and clinical baseline

characteristics. Third, some readers may

regard the study sample size as relatively

small because it included 83 children. Our

findings, however, show that it provided

enough statistical power to detect the effect

of stunting on caries increment. Furthermore,

consistent findings were obtained when both

the 2000 CDC and 2007 WHO standards were

used to define stunting, which increase the

credibility of findings. By contrast, interpret-

ing other variables in the model must be car-

ried out with certain caution as sample size

may have not been large enough to detect

significant associations for those. Fourth,



because of logistic reasons, the same exam-

iner conducted both the anthropometric mea-

surements and clinical examinations, which

may raise concerns about the possibility of

bias. Complete blinding to children’s nutri-

tional status, however, may not be possible to

achieve in this situation as any sharp exam-

iner would notice anthropometric failure

while performing oral clinical examinations.

The latter would also happen if using separate

examiners for anthropometric measurements

and oral clinical examinations. Fifth, no infor-

mation on children’s exposure to fluoride was

collected in this study. Although there is no

reason to suspect a differential fluoride expo-

sure between stunted and non-stunted chil-

dren, especially when they all come from the

same underserved communities, our findings

need to be corroborated by further studies in

which other important determinants of child-

hood dental caries are also assessed.

In conclusion, this longitudinal study sug-

gests that stunting is a significant predictor of

3.5-year net caries increment among Peru-

vian children living in underserved communi-



ties. The effect of stunting was not accounted

for by other well-known risk factors for den-

tal caries, including demographic characteris-

tics, dental behaviours, and prior caries

experience. Similar conclusions were reached

when using either the 2000 CDC or 2007

WHO standards to define stunting.

Why is this paper important to paediatric dentists

• Dentists should be aware of the links between systemic

and oral diseases, which call for close collaboration

with other health professionals. Higher levels of caries

experience in children may be indicative of long-term

under-nutrition.

Conflict of interest

The authors declare no conflict of interest.

References

1 Hark L, Morrison G (eds). Medical Nutrition and

Disease: A Case-Based Approach, 4th edn. Oxford: Jon

Wiley & Sons, 2009.

2 Shetty P. Measures of nutritional status from

anthropometric survey data. In: FAO, ed. International

Scientific Symposium on Measurement and Assessment of

Food Deprivation and Undernutrition. Rome, Italy:

2002; http://www.fivims.net/EN/ISS.htm.

3 WHO, (ed). The Global Burden of Disease: 2004 Update.

Geneva, Switzerland: World Health Organization,

2008: 14–16.

4 Black RE, Allen LH, Bhutta ZA et al. Maternal and

child undernutrition: global and regional exposures

and health consequences. Lancet 2008; 371: 243–260.

5 Victora CG. The association between wasting and

stunting: an international perspective. J Nutr 1992;

122: 1105–1110.

6 Victora CG, Adair L, Fall C et al. Maternal and child

undernutrition: consequences for adult health and

human capital. Lancet 2008; 371: 340–357.

7 Rodriguez L, Cervantes E, Ortiz R. Malnutrition and

gastrointestinal and respiratory infections in

children: a public health problem. Int J Environ Res

Public Health 2011; 8: 1174–1205.

8 Cunningham-Rundles S, McNeeley DF, Moon A.

Mechanisms of nutrient modulation of the immune

response. J Allergy Clin Immunol 2005; 115: 1119–

1128.

9 Naidoo S, Myburgh N. Nutrition, oral health and the

young child. Matern Child Nutr 2007; 3: 312–321.

10 Kay EJ, Northstone K, Ness A, Duncan K, Crean SJ.

Is there a relationship between birthweight and

subsequent growth on the development of dental


caries at 5 years of age? A cohort study. Community

Dent Oral Epidemiol 2010; 38: 408–414.

11 Sheiham A. Dental caries affects body weight,

growth and quality of life in pre-school children. Br

Dent J 2006; 201: 625–626.

12 Psoter WJ, Reid BC, Katz RV. Malnutrition and

dental caries: a review of the literature. Caries Res

2005; 39: 441–447.

13 Alvarez JO. Nutrition, tooth development, and

dental caries. Am J Clin Nutr 1995; 61: 410S–416S.

14 Scheutz F, Matee MI, Poulsen S, Frydenberg M.

Caries risk factors in the permanent dentition of

Tanzanian children: a cohort study (1997–2003).

Community Dent Oral Epidemiol 2007; 35: 500–506.

15 Peres MA, Barros AJ, Peres KG, Araujo CL, Menezes

AM. Life course dental caries determinants and

predictors in children aged 12 years: a population-

based birth cohort. Community Dent Oral Epidemiol

2009; 37: 123–133.

16 Delgado-Angulo EK, Bernabe E. Influence of host-

related risk indicators on dental caries in permanent

dentition. Acta Odontol Latinoam 2006; 19: 85–92.

17 WHO. Measuring change in nutritional status.

Guidelines for Assessing the Nutritional Impact of

Supplementary feeding Programmes for Vulnerable

Groups. Geneva, Switzerland: World Health

Organization, 1983.

18 Kuczmarski RJ, Ogden CL, Guo SS et al. 2000 CDC

Growth Charts for the United States: methods and

development. Vital Health Stat 2002; 11: 1–190.

19 de Onis M, Onyango AW, Borghi E, Siyam A, Nishida

C, Siekmann J. Development of a WHO growth

reference for school-aged children and adolescents.

Bull World Health Organ 2007; 85: 660–667.

20 Greene JC, Vermillion JR. The Simplified Oral

Hygiene Index. J Am Dent Assoc 1964; 68: 7–13.

21 Pitts NB, Evans DJ, Pine CM. British Association for the

Study of Community Dentistry (BASCD) diag-

nostic criteria for caries prevalence surveys-

1996 ⁄ 97. Community Dent Health 1997; 14(Suppl. 1):

6–9.

22 Slade GD, Caplan DJ. Methodological issues in

longitudinal epidemiologic studies of dental caries.

Community Dent Oral Epidemiol 1999; 27: 236–248.

23 Slade GD, Caplan DJ. Impact of analytic

conventions on outcome measures in two

longitudinal studies of dental caries. Community Dent

Oral Epidemiol 2000; 28: 202–210.

24 Johansson I, Holgerson PL, Kressin NR, Nunn ME,

Tanner AC. Snacking habits and caries in young

children. Caries Res 2010; 44: 421–430.

25 Greene JC. The Oral Hygiene Index – development

and uses. J Periodontol 1967; 38 Suppl: 625–637.

26 Cameron AC, Trivedi PK. Regression Analysis of

Count Data. Cambridge: Cambridge University Press,

1998.

27 van Gemert-Schriks MCM, van Amerongen EW,

Aartman IHA, Wennink JMB, ten Cate JM, de Soet

JJ. The influence of dental caries on body growth in




prepubertal children. Clin Oral Invest 2011; 15: 141–

149.

28 Alvarez JO, Navia JM. Nutritional status, tooth

eruption, and dental caries: a review. Am J Clin Nutr

1989; 49: 417–426.

29 Psoter WJ, Spielman AL, Gebrian B, St Jean R, Katz

RV. Effect of childhood malnutrition on salivary

flow and pH. Arch Oral Biol 2008; 53: 231–237.



30 Feldens CA, Giugliani ER, Duncan BB, Drachler

Mde L, Vitolo MR. Long-term effectiveness of a

nutritional program in reducing early childhood

caries: a randomized trial. Community Dent Oral

Epidemiol 2010; 38: 324–332.


childhood stunting and caries increment in permanent teeth: a three and a half year longitudinal...

Documents