Inequalities in dental caries experience among 4&

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tion and dental caries experience was weakest for Asian children and was most ..... suggests a need for increased health resources to treat this increas-.
Received: 14 September 2017

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Accepted: 9 January 2018

DOI: 10.1111/cdoe.12364

ORIGINAL ARTICLE

Inequalities in dental caries experience among 4-year-old New Zealand children Nichola Shackleton1

| Jonathan M. Broadbent2 | Simon Thornley3,4,5 |

Barry J. Milne1 | Sue Crengle6 | Daniel J. Exeter3 1

Centre of Methods and Policy Application in the Social Sciences (COMPASS), University of Auckland, Auckland, New Zealand 2 Sir John Walsh Research Institute, Faculty of Dentistry, University of Otago, Dunedin, New Zealand 3

Section of Epidemiology & Biostatistics, School of Population Health, The University of Auckland, Auckland, New Zealand 4

Auckland Regional Public Health Service, Auckland, New Zealand 5 Human Potential Centre, Millennium Institute, Auckland University of Technology, Auckland, New Zealand 6

Department of Preventive and Social Medicine, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand Correspondence Nichola Shackleton, Centre of Methods and Policy Application in the Social Sciences (COMPASS), The University of Auckland, Auckland, New Zealand Email: [email protected]

Abstract Objectives: To investigate ethnic-specific deprivation gradients in early childhood dental caries experience considering different domains of deprivation. Methods: We used cross-sectional near whole population-level data on 318 321 four-year-olds attending the “B4 School check,” a national health and development check in New Zealand, across 6 fiscal years (2010/2011 to 2015/2016). The “lift the lip” screening tool was used to estimate experience of any caries and severe caries. We investigated deprivation gradients using the Index of Multiple Deprivation (IMD), which measures seven domains of deprivation across 5958 geographical areas (“data zones”). Ethnicity was categorized into five groups: (i) M aori, (ii) Pacific, (iii) Asian, (iv) Middle Eastern, Latin American and African (MELAA) and (v) European & Other (combined). We used a random intercepts model to estimate mutually adjusted associations between deprivation, ethnicity, age, fiscal year, and evidence of any dental caries experience. Results: Reports of any caries experience decreased from 15.8% (95% CI: 15.7; 15.9%) to 14.7% 95% CI: 14.4; 14.8%), while reports of severe caries experience increased from 3.0% (95% CI: 3.0; 3.1%) to 4.4% (95% CI: 4.3; 4.5%) from 2010/ 2011 to 2015/2016. This varied by ethnicity with larger increases in severe caries

Funding information The work was supported by Health Research Council of New Zealand (www.hrc.govt.nz) 13/428.

for Pacific children from 7.1% (95% CI: 6.8; 7.4%) to 14.1% (95% CI: 13.7; 14.5%). There were deprivation gradients in dental caries experience with considerable variation by ethnicity and by domain of deprivation. The association between deprivation and dental caries experience was weakest for Asian children and was most pronounced for Pacific and Maori children. Conclusion: Socioeconomic gradients in dental caries experience are evident by age 4 years, and these gradients vary by ethnicity and domain of deprivation. KEYWORDS

disparities, early childhood caries, epidemiology, trends

1 | INTRODUCTION

the 10th most prevalent condition, affecting 9% of the global population.1 Socioeconomic and ethnic inequalities in dental caries have

The Global Burden of Disease Study (2010) reported that untreated

been widely observed,2 even in countries with universal state-funded

dental caries was the most prevalent of all health conditions evalu-

dental services for children, such as in New Zealand.3 Given that oral

ated among adults and children. The global prevalence was esti-

health behaviours track from childhood to adulthood, and that

mated at 35%, and untreated caries in the deciduous dentition was

sociodemographic factors during childhood can affect oral health in

Community Dent Oral Epidemiol. 2018;1–9.

wileyonlinelibrary.com/journal/cdoe

© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd

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SHACKLETON

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adult life,4 there has been a greater focus on improving the oral

visible dental decay.13 In the B4SC, the lift the lip screening was car-

health and self-care behaviours of younger children.

ried out by registered nurses or nurse practitioners.9 Photographic

The average number of caries-affected teeth among 5-year-old

examples of each category were provided for reference, and the fol-

New Zealand children has been decreasing over time. The mean

lowing codes were assigned depending upon the appearance of the

dmft (count of decayed/carious, missing and filled/restored decidu-

teeth:13

ous teeth) in this age group was 1.9 in 2013, down from 2.2 a decade before.5 However, there are large differences in the oral health

1 = No visible caries

of children by ethnicity and by area-level socioeconomic deprivation

2 = Chalky patches (enamel demineralization) and possible initial

in New Zealand.6 A recent report from Healthy Auckland Together

enamel breakdown on anterior teeth

found substantial ethnic inequities in dental caries experience among

3 = Obvious caries between anterior teeth and/or along gum line

5-year-old children, whereby Pacific children had the highest average

4 = Partial coronal breakdown of anterior teeth (as in, teeth col-

number of teeth that were decayed, missing due to decay, or

lapsing due to caries)

restored, followed closely by Maori (the indigenous people of New

5 = Carious retained roots, whole crowns of anterior teeth are

Zealand).7 While documenting these inequities is important, under-

gone

standing the interplay between ethnicity and deprivation is vital

6 = Severe caries including posterior teeth.

given ethnicity and deprivation are so closely intertwined.

8

Despite the importance of monitoring oral health trends, few

For subgroup analyses, we collapsed these six categories into

population-level data sets are available. New Zealand’s B4 School

evidence of “any caries” (including categories 2-6) and “severe caries”

Check (B4SC) is a nationwide programme established in September

(including categories 4-6). This definition of severe caries is consis-

2008 to monitor child health and development at 4 years of age.9

tent with the American Association of Paediatric Dentistry definition

The B4SC aims to measure every child in New Zealand at approxi-

of severe early childhood caries in the 3-5 years age group,14 as cat-

mately 4 years of age. After merging with other data sources, the

egories 4-6 indicate that the examiner noted a cavitated carious

resultant data set enables investigation of inequities in early child-

lesion affecting one or more teeth.

hood caries experience among 4-year-old children. In this study, we aim to investigate the association between deprivation and child oral health, and how this varies by ethnicity by utilizing a new measure

2.2.2 | Demographic characteristics

of area-level deprivation: the New Zealand Index of Multiple Depri-

Child sociodemographic characteristics (gender, birth month/year

vation (IMD).10,11

and ethnicity) were derived by linking B4SC records to birth records and census records in Statistics New Zealand’s Integrated Data

2 | METHODS 2.1 | Participants

Infrastructure (IDI), a collection of de-identified administrative data sources linked at the individual level.15 Age was calculated to the nearest month. Parental-reported ethnicity was based on the “source ranked ethnicity,” which prioritizes reports from the census (the best

In the 2010/2011 fiscal year 75% of the eligible population attended

quality ethnicity information), followed by birth records and then

a B4SC, this increased to 79% in 2011/2012, 80% in 2012/2013,

administrative sources. In this sample, 85% of the ethnicity informa-

91% in 2013/2014, 92% in 2014/15 and 92% in 2015-2016.12

tion came from the census, 12% from birth records and 3% from

There was little difference between overall coverage rates and cov-

Ministry of Health. Using the Ministry of Health’s ethnicity data pro-

erage rates for those in areas of high deprivation (75% in 2010/

tocols, children were assigned into an ethnic group using the follow-

2011, 82% in 2011/2012, 80% in 2012/2013 and >90% thereafter).

ing hierarchy of prioritization: (i) Maori, (ii) Pacific, (iii) Asian, (iv)

Between 2012/2013 and 2015/2016 fiscal years, uptake rates

Middle Eastern, Latin American, and African (MELAA) and (v) Euro-

among Maori and Pacific children increased from 71% to 88% and

pean and Other combined.16 Only 1.5% of children identified as

from 68% to 89%, respectively.

“Other” ethnicity. European and Other were combined, as research

This study was given ethical approval by the Chairperson of the

indicates that there is virtually identical patterns of age, education,

Northern X Regional Ethics Committee on 24 August 2011, with

income and socioeconomic scores for the European and the Other

ongoing approval granted by the New Zealand Health and Disability

ethnic groups.17

Ethics Committees (Ref: NTX/11/EXP/190).

2.2.3 | Area deprivation 2.2 | Measures 2.2.1 | Early childhood caries

The New Zealand Index of Multiple Deprivation (IMD) uses specifically created geographical units known as “data zones” (N = 5958). Most data zones have a population ranging from 500 to 1000 (mean

As part of the B4SC children undergo oral health screening via the

population of 712).10 The IMD is explained in detail elsewhere10,11

“lift the lip” examination. This is a 2-3 minutes screen for signs of

and we include a summary diagram of the IMD in Appendix S1.

SHACKLETON

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3

Briefly the IMD represents seven domains (Employment, Income,

June) 2010/2011 to 2015/2016. The characteristics of this sample

Crime, Housing, Health, Education and Access) of deprivation mea-

are presented in Table 1. Results from the lift the lip examination are

sured at the data zone level. It can be used to measure deprivation

presented in Table 2.

18

IMD

Overall 14.6% (95% CI: 14.5; 14.7%) of 4-year-old children had

scores were ranked in ascending order (higher score = more

evidence for any caries experience. Experience of any caries was

deprived), and in this study, we categorized ranks into deciles for

greater among males [15.1% (95% CI: 15.0; 15.3)] than females

analytical purposes. The IMD is available for download from (http://

[14.1% (95% CI: 13.9; 14.3%)]. Any caries experience was lowest

(across all domains), or domain-specific scores can be used.

www.fmhs.auckland.ac.nz/imd). The IMD’s Access domain is a proxy

among children identifying as European [6.8% (95% CI: 6.8; 6.9%)],

for rurality and is based on the distance from the population

followed by MELAA [15.0% (95% CI: 14.6; 15.4%)], Asian [17.9%

weighted centroid of each data zone to the nearest three instances

(95% CI: 17.7; 18.0%)], Maori [22.3% (95% CI: 22.2; 22.4%)] and

of five key services: supermarkets, primary healthcare providers, ser-

Pacific [30.6% (95% CI: 30.4; 30.9%)].

vice stations, early childhood centres and primary and intermediate

Any caries experience decreased from 15.8% (95% CI: 15.7;

schools. Travel distances were converted to a continuous “relative

15.9%) in 2010/2011 to 14.7% (95% CI: 14.6; 14.8%) in 2015/2016.

accessibility” score as outlined in Shi et al19

Severe caries experience (categories 4-6) increased from 3.0% (95% CI: 3.0; 3.1%) in 2010/2011 to 4.4% (95% CI: 4.4; 4.5%) in 2015/

2.3 | Analysis

2016. The change in any caries experience (ie percentage2015/2016— percentage2010/2011) revealed interesting patterns. Any caries experi-

This study comprised three analytical stages, all of which were con-

ence decreased for European [ 1.8% (95% CI:

ducted in Stata version 14.20 Firstly, we considered the bivariate

[ 2.7% (95% CI:

association between lift the lip scores and gender, ethnicity, deprivation and year of measurement. This allowed us to examine differences in caries experience, as well as aggregate trends.

2.1;

1.6;

2.1%)], Maori

3.2%)] and Asian [ 2.1% (95% CI:

1.3;

2.9%)] children, but stayed the same for Pacific [0.4% (95% CI: 1.5; 0.6%)] and MELAA children [ 0.2% (95% CI:

1.8; 2.1%)].

There were increases in severe caries experience for all ethnic

Secondly, we conducted analyses within each ethnic group. We

groups [European (0.2% (95% CI: 0.1; 0.3%)), Maori (1.1% (95% CI:

considered the association between year of B4SC measurement and

0.8; 1.4%)], Asian [0.8% (95% CI: 0.4; 1.2%)] and MELAA [1.3% (95%

evidence of any caries experience and severe caries experience sepa-

CI: 0.4; 2.3%)] with the largest increases in children identifying as

rately. We also considered the association between any caries expe-

Pacific [7.0% (95% CI: 6.3; 7.7%)] (Figure 1).

rience and deprivation using deciles of the IMD and its seven

Caries and deprivation were strongly associated in all ethnic

domains individually. Analyses of severe caries experience were

groups, with the strongest association among Maori and Pacific chil-

excluded due to relatively small cell counts in areas of low depriva-

dren (Figure 2A). A weaker association between deprivation and car-

tion, reflecting the relatively low rate of severe caries in these areas,

ies experience was observed among Asian children. This association

and the differential distribution of ethnic groups across the depriva-

was greatest among the Employment, Income, Housing, Health and

tion deciles.

Education domains, which followed a similar pattern to the overall

Thirdly, as children were clustered in data zones and we were

IMD score, both overall and for each ethnicity (Figure 2B). The asso-

assessing both child-level and area-level variables, we used multilevel

ciation between Access deprivation and caries experience was the

logistic regression analysis with random intercepts to consider the

inverse of all other domains of deprivation, with lower caries preva-

adjusted association between deprivation deciles (IMD and the

lence associated with greater Access deprivation. This inverse associ-

domains individually—measured at the area level) and evidence of

ation was weaker for Asian children.

any dental caries controlling for age, sex, ethnicity and year (all mea-

The gradient of increasing caries experience with greater depri-

sured at the child level). We show the results obtained from sequen-

vation remained significant after adjustment for potential con-

tially adjusting models, adding covariates in the following blocks:

founders (Table 3). Ethnicity and deprivation were both associated

Model 1 demographics (age, sex and year), Model 2 demographics &

with any caries experience, although the association was attenuated

ethnicity, Model 3 demographics & IMD and fully adjusted Model 4

after full adjustment (Table 3, M4), such that all odds ratios were

demographics & ethnicity & IMD. Only the results from the fully

reduced relative to unadjusted estimates. Lower odds ratios were

adjusted models are presented for the domains of deprivation. The

observed for Maori and Pacific children (Model 2) after adjustment

results are presented as odds ratios. We repeated these analyses

for deprivation (Model 4) with the odds ratio for Maori falling from

using ordinal logistic regression as a sensitivity check; however,

3.11 (95% CI: 3.08; 3.15) to 2.73 (95% CI: 2.70; 2.76) and the Pacific

these results are not presented as the estimates were very similar.

falling from 4.42 (95% CI: 4.36; 4.39) to 3.72 (95% CI: 3.67; 3.78). Similarly, deprivation odds ratios were reduced after adjustment for ethnicity (Model 4).

3 | RESULTS

For the overall IMD, greater deprivation was associated with greater overall caries experience, and this was observed for all

The lift the lip screen was carried out on 318 321 children aged

domains except Access. The association between the prevalence of

between 48 and 60 months within the fiscal years (1st July to 30th

any caries experience and increasing area-level deprivation (IMD)

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SHACKLETON

2010/ 2011 (%)

2011/ 2012 (%)

2012/ 2013 (%)

2013/ 2014 (%)

2014/ 2015 (%)

2015/ 2016 (%)

Pooled sample (%)

50.9

51.3

51.7

51.4

51.2

51.2

51.3

European and Other

53.9

52.2

51.9

50.6

48.7

47.9

50.8

Maori

27.1

25.9

26.1

26.0

26.2

25.8

26.2

Pacific

9.0

9.8

9.5

9.8

10.1

9.9

9.7

Asian

8.6

10.6

11.0

11.8

13.1

14.2

11.7

MELAA

1.4

1.5

1.4

1.6

1.8

2.0

1.7

Sex Male

ET AL.

T A B L E 1 Characteristics of 4-year-old children participating in the before School Check undergoing “lift the lip” examination

Ethnicity

Deprivation (IMD Deciles)

n

a

1

8.6

9.2

8.9

8.9

8.5

8.9

8.9

2

8.3

8.5

8.8

8.9

8.7

8.9

8.7

3

8.4

8.5

8.5

8.1

8.4

8.2

8.4

4

9.0

9.1

9.0

8.7

8.8

9.0

8.9

5

9.0

9.1

9.1

9.1

9.0

9.1

9.1

6

9.4

9.0

9.4

9.2

9.6

9.5

9.4

7

9.9

9.4

9.9

10.0

9.9

9.7

9.8

8

10.4

10.2

10.2

10.4

10.6

10.4

10.4

9

11.6

11.8

11.4

11.9

11.7

11.6

11.7

10

15.4

14.8

14.5

14.5

14.7

14.4

14.7

45 582

50 574

50 517

58 182

56 754

56 709

318 321

a

Counts are randomly rounded to a base of 3, as per the confidentiality rules of Statistics New Zealand.

increased exponentially, with the odds of caries increasing substan-

were much greater (over 5 times) for Pacific children than any other

tially from decile 7 onwards (Figure 3). Relative to the least deprived

ethnic group. We found evidence for steep deprivation gradients in

decile in the Access domain, all other deciles were associated with

dental caries experience with considerable variation by ethnicity and

lower odds of any caries experience. The strongest association with

by domain of deprivation. The greatest caries experience and steep-

caries (when most deprived domains of deprivation are compared

est socioeconomic gradients were observed among Maori and Pacific

with least) was for Income [OR 3.01 (95% CI: 2.92; 3.10)], followed

children. Household income showed the strongest association with

by Housing [OR 2.97 (95% CI: 2.88; 3.06)] and Employment [OR

caries, of all the domains examined, with Access showing the weak-

2.80 (95% CI: 2.72; 2.89)]. Of all domains, Access showed the weak-

est association.

est and least consistent association with caries.

The finding of increasing severe caries among socioeconomically deprived children (especially deprived Pacific and Maori children) suggests a need for increased health resources to treat this increas-

4 | DISCUSSION

ing burden on dental services, as well as socioeconomically and culturally tailored programmes to help control this growing problem.

This is the first report of dental health among New Zealand 4-year-

The changes in experience of caries are somewhat inconsistent

old children at the national level. The analytic sample comprised

with findings from other New Zealand studies, although those stud-

84% of the 379 080 Estimated Resident Population of 4-year-olds in

ies were conducted using different methods and on children of dif-

New Zealand between July 1st 2010 and June 30th 2016.21 A new

ferent ages. Analysis of data collected from the Auckland Regional

measure of area-level deprivation was applied to investigate ethnic-

Dental Service (ARDS) showed no changes in the mean number of

specific differences in domain-specific deprivation gradients for early

5-year-old children treated in that service with teeth carious,

childhood caries. We observed evidence for a decrease in reporting

restored or missing due to caries across all ethnic groups between

of any caries experience over this time period. However, an increase

2007 and 2015.7 The ARDS data are based on treatment data

in severe caries was observed. These changes over time were not

including diagnosis and procedures recorded by a dental therapist,

consistent between ethnic groups. Decreases in overall caries experi-

rather than a dental screen, and only include children in Auckland.

ence were not observed among children of Pacific or MELAA ethnic-

Furthermore, the present study considers children prior to school

ity. Increases in the experience of severe caries over the time period

attendance. Therefore, these discrepancies may be explained by

SHACKLETON

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5

T A B L E 2 The bivariate association between lift the lip with sex, fiscal year, ethnicity, and deprivation

No visible caries (1) (%)

Chalky patches, possible initial enamel breakdown on anterior teeth (2) (%)

Obvious caries between anterior decay and/or along gum line (3) (%)

Partial coronal breakdown of anterior teeth (4) (%)

Carious retained roots, whole crowns of anterior teeth are gone (5) (%)

Severe caries including posterior teeth (6) (%)

Sex Male

84.9

8.6

2.9

1.0

0.6

2.1

Female

85.9

7.9

2.7

1.0

0.5

2.0

2010/2011

84.2

9.8

3.0

1.0

0.6

1.5

2011/2012

85.3

8.6

2.7

1.0

0.5

1.9

2012/2013

85.7

8.2

2.7

1.0

0.5

1.9

2013/2014

86.2

7.7

2.7

0.9

0.5

2.0

2014/2015

85.3

7.8

3.2

1.0

0.5

2.2

2015/2016

85.3

7.7

2.6

1.1

0.7

2.7

European and Other

93.2

4.9

1.1

0.3

0.1

0.5

Maori

77.7

12.0

4.3

1.5

0.9

3.7

Pacific

69.4

14.0

6.4

2.8

1.4

6.0

Asian

82.1

9.8

4.0

1.5

0.7

2.0

MELAA

85.0

8.1

3.4

1.3

0.7

1.6

Fiscal year

Ethnicity

Deprivation (IMD Deciles) 1

93.5

4.6

1.1

0.2

0.1

0.4

2

92.2

5.3

1.4

0.5

0.1

0.5

3

91.7

5.5

1.5

0.4

0.2

0.6

4

90.5

6.0

1.7

0.6

0.3

0.9

5

90.0

6.2

2.0

0.6

0.3

0.9

6

88.5

6.9

2.3

0.7

0.3

1.3

7

87.1

7.8

2.4

0.9

0.5

1.4

8

83.8

9.2

3.1

1.1

0.6

2.1

9

79.1

11.0

4.1

1.6

0.9

3.4

10

69.9

14.6

5.8

2.4

1.3

6.0

differences in dental service utilization prior to attending school. This

travelling to access basic services (including primary healthcare provi-

is consistent with National Health Survey6 findings that Pacific chil-

ders as well as supermarkets, schools and service stations), our results

dren are less likely than non-Pacific children to have visited dental

may suggest that the accessibility of primary healthcare professionals

health workers in the past year (adjusted R = .91), and that the per-

has limited influence on the aetiology of this disease. An alternative

centage of children visiting a dental health worker is considerably

explanation is that difficulty accessing dental services for preschoolers

lower in younger age groups (1-4 years) at 60%, compared to those

affects people across the deprivation deciles.

2

of school ages (5-9 years) at 91%.22

Indigenous children and those living in greater socioeconomic

The weak association between caries and Access is consistent

deprivation have greater risk of caries than children that are less

with research undertaken in the UK. For example, Jordan et al23 found

deprived.25,26 Early childhood caries is a sensitive marker of experi-

that the “geographical access to services” domain of the English IMD

ences of deprivation and socioeconomic stress.27 Use of dental ser-

2000 is not strongly correlated with rates of morbidity in rural areas

vices, dental self-care and dietary patterns tend to be less favourable

and in urban areas displays a negative correlation. Adams et al

24

used

the same index to establish that geographical proximity to general

among children from deprived communities, due to socioeconomic stresses.4,26

practices was greater in more deprived, compared to more affluent

The strong association between socioeconomic factors and caries

wards. As the Access domain measures the cost and inconvenience of

suggests that interventions to reduce caries should also be

6

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SHACKLETON

35

Asian

Pacific

Māori

European and Other

ET AL.

MELAA

30

Prevalence (%)

25 20 15 10

5 0

Any caries

Severe caries

F I G U R E 1 Trends in any caries experience and severe caries experience stratified by ethnicity Note: Caries experience is measured across 6 fiscal years (from July 1st to June 30th). Error bars represent 95% Confidence Intervals.

40

European and

35

other

Māori

Asian

Pacific

MELAA

Overall

Any caries (%)

30 25 20 15 10 5 0 1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

Any caries (%)

30 25

20 15 10 5 0

Decile of deprivation Employment

Income

Crime

Housing

Health

Education

Access

F I G U R E 2 The association between A, the IMD (deciles) and any caries by ethnicity, and B, the seven domains of deprivation (deciles) and any caries by ethnicity Note: Error bars represent 95% Confidence Intervals. Error bars not included in Figure B for visual clarity.

socioeconomic in nature. Research on the effect of the Mexican sug-

purchasing behaviour were among those from low socioeconomic

ary drink taxes suggests that purchasing of sugary drinks declined in

groups.28 Furthermore, a simulation study of the German population

tandem with the price increase, and the greatest changes in

projected that introducing a tax on sugar sweetened beverages

SHACKLETON

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ET AL.

T A B L E 3 Sequentially adjusted random intercepts logistic regression models for “any caries” compared to “no visible caries”

7

M1

M2

M3

M4

Age in months

1.06 (1.06-1.07)

1.05 (1.05-1.06)

1.05 (1.05-1.06)

1.05 (1.05-1.06)

Fiscal Year

1.00 (1.00-1.00)

0.99 (0.98-0.99)

1.00 (1.00-1.00)

0.99 (0.98-0.99)

Male

1

1

1

1

Female

0.92 (0.91-0.92)

0.91 (0.90-0.92)

0.91 (0.90-0.92)

0.91 (0.90-0.92)

Sex

Ethnicity European and Other

1

1

Maori

3.11 (3.08-3.15)

2.73 (2.70-2.76)

Pacific

4.42 (4.35-4.48)

3.72 (3.67-3.78)

Asian

2.89 (2.84-2.93)

2.76 (2.72-2.80)

MELAA

2.30 (2.22-2.37)

2.16 (2.09-2.22)

Deprivation (IMD Deciles) 1

1

1

2

1.21 (1.17-1.25)

1.14 (1.11-1.18)

3

1.30 (1.26-1.35)

1.18 (1.14-1.22)

4

1.52 (1.47-1.57)

1.34 (1.29-1.38)

5

1.59 (1.54-1.64)

1.33 (1.29-1.37)

6

1.88 (1.82-1.94)

1.50 (1.45-1.54)

7

2.17 (2.10-2.23)

1.64 (1.59-1.69)

8

2.82 (2.74-2.91)

1.94 (1.88-1.99)

9

3.85 (3.73-3.96)

2.39 (2.32-2.46)

10

6.20 (6.02-6.38)

3.30 (3.20-3.40)

Constant

0.01 (0.00-0.01)

0.01 (0.00-0.01)

0.01 (0.00-0.01)

0.01 (0.00-0.00)

Variance

0.56 (0.55-0.58)

0.28 (0.27-0.29)

0.19 (0.18-0.20)

0.15 (0.15-0.16)

ICCa

0.15 (0.14-0.15)

0.08 (0.08-0.08)

0.05 (0.05-0.06)

0.04 (0.04-0.05)

M1 adjusted for age in months and gender; M2 adjusted for age, gender and ethnicity; M3 adjusted for age, gender and deprivation; M4 adjusted for age, gender, ethnicity and deprivation. a ICC refers to the intraclass correlation coefficient.

would reduce dental caries rates, with greater reductions among

This type of bias is unavoidable in a study where the data were

low-income groups.29 Given the socioeconomic gradients in sugar

collected in a clinical setting by practitioners who were not den-

consumption, taxing sugary drinks could be an effective means to

tists or dental therapists, as these severe cases may be easier to

limit caries. However, data on the effectiveness of sugar taxes

identify.9

remain limited, especially when people can switch to cheaper brands.30

While the coverage rates for the B4SC are very high, there are still between 8 and 21% of 4-year-olds each year who do not partic-

This study has a number of strengths. For example, this is the

ipate. Information from the Ministry of Health suggests that uptake

first study to report on the dental health of an almost complete

rates were similar for those living in deprived and nondeprived areas

population of New Zealand 4-year-old children. Furthermore, we

across the years under study,12 suggesting that a selection bias by

were able to link these data to other data sources to enrich the

deprivation is unlikely to be present. However, a recent analysis

data set. A limitation is that no study has yet directly compared

found that those who did not attend B4SC in the 2015/2016 fiscal

findings of “lift the lip” screenings to a clinical examination by a

year were socioeconomically disadvantaged, and more likely to be in

dentist or dental therapist. Furthermore, we have no metric for

poor health than those who attended the B4SC.33 Furthermore,

adherence to protocols, and it is likely this varied across individual

there are ethnic differences in B4SC participation, with Maori and

practitioners and across centres. Early reports of the “lift the lip”

Pacific children less likely to participate than European children12,33,

screen suggest it can be used to identify children with caries.31,32

again suggesting that our findings underestimate the prevalence of

However, there is likely to be a bias in the estimates as “lift the

caries. A further limitation is that testing for causal mechanisms was

lip” is conducted by a health practitioner who is generally not

not possible in this study, because the study is cross-sectional, and

qualified in dental health. It is likely that the caries data presented

data on self-care and diet that could be linked to these children

here are under-estimated, as signs of early caries can be subtle.

were not available.

8

|

SHACKLETON

ET AL.

4.0

Odds ratio (reference is least deprived decile)

3.5

3.0

2.5

2.0

1.5

1.0

2

4

5

6

7

8

9

10

Domains of deprivation

0.5

IMD FIGURE 3

3

Employment

Income

Crime

Housing

Health

Education

Access

Adjusted association between the IMD (deciles) and the seven domains of deprivation (deciles) with any caries

Note: All models were adjusted for age in months, gender, ethnicity and year. Error bars represent 95% Confidence Intervals.

Our research has identified substantial disparities in oral

Careful consideration has been given to the privacy, security and

health among New Zealand preschoolers. The strong associa-

confidentiality issues associated with using administrative and survey

tion found between caries and deprivation suggests that the IMD

data in the IDI. Further detail can be found in the Privacy impact

has the potential to identify areas in greater need of oral health

assessment for the Integrated Data Infrastructure available from

services.

www.stats.govt.nz.

ACKNOWLEDGEMENTS

ORCID

We would like to thank Caleb Moses and Stephen Challands at

Nichola Shackleton

http://orcid.org/0000-0001-5570-3617

Statistics New Zealand for their hard work in checking and releasing outputs. We would also like to thank attendees at the 2017 COMPASS Colloquium for their valuable feedback and suggestions for this project.

STATISTICS NEW ZEALAND DISCLAIMER The results in this study are not official statistics. They have been created for research purposes from the Integrated Data Infrastructure (IDI), managed by Statistics New Zealand. The

opinions,

findings,

recommendations

and

conclusions

expressed in this study are those of the author(s), not Statistics NZ or The University of Auckland. Access to the anonymized data used in this study was provided by Statistics NZ under the security and confidentiality provisions of the Statistics Act 1975. Only people authorized by the Statistics Act 1975 are allowed to see data about a particular person, household, business, or organization, and the results in this study have been confidentialized to protect these groups from identification and to keep their data safe.

REFERENCES  E, et al. Global Burden of Oral 1. Marcenes W, Kassebaum NJ, Bernabe Conditions in 1990-2010: a Systematic Analysis. J Dent Res. 2013;92:592-597. € rfer CE, Schlattmann P, Foster Page LA, Thomson 2. Schwendicke F, Do WM, Paris S. Socioeconomic inequality and caries a systematic review and meta-analysis. J Dent Res. 2015;94:10-18. 3. Thomson WM, Poulton R, Milne BJ, Caspi A, Broughton JR, Ayers KMS. Socioeconomic inequalities in oral health in childhood and adulthood in a birth cohort. Community Dent Oral Epidemiol. 2004;32:345-353. 4. Broadbent JM, Zeng J, Foster Page LA, Baker SR, Ramrakha S, Thomson WM. Oral Health–related Beliefs, Behaviors, and Outcomes through the Life Course. J Dent Res. 2016;95:808-813. 5. Schluter PJ, Lee M. Water fluoridation and ethnic inequities in dental caries profiles of New Zealand children aged 5 and 12–13 years: analysis of national cross-sectional registry databases for the decade 2004–2013. BMC Oral Health. 2016;16:21. 6. Ministry of Health. Annual Update of Key Results 2015/16: New Zealand Health Survey. New Zealand Health Survey. Wellington: Ministry of Health; 2016.

SHACKLETON

|

ET AL.

7. Healthy Auckland Together. Monitoring Report 2017. www.healthya ucklandtogether.org.nz. Accessed 26th July 2017. 8. Atkinson J, Salmond C, Crampton P. NZDep2013 Index of Deprivation. Dunedin: University of Otago; 2014. 9. Ministry of Health. The B4 School Check: A handbook for practitioners. Wellington: Ministry of Health; 2008. 10. Exeter DJ, Browne M, Crengle S, Lee AC, Zhao J. The New Zealand Index of Multiple Deprivation (IMD): a new suite of indictors for health and social research in New Zealand (Brief Report). Auckland: University of Auckland; 2017. 11. Exeter DJ, Zhao J, Crengle S, Lee AC, Browne M. The New Zealand Indices of Multiple Deprivation: a new suite of indicators for social and health research in Aotearoa, New Zealand. PLoS One 2017;12:e0181260. 12. Ministry of Health. B4 School Check information for the health sector 2016. http://www.health.govt.nz/our-work/life-stages/child-hea lth/b4-school-check/b4-school-check-information-health-sector. Accessed December 16, 2016. 13. New Zealand Dental Association. Healthy Smile, Healthy Child: Oral Health Guide for Well Child Providers. Auckland: New Zealand Dental Association; 2008. 14. American Academy of Pediatric Dentistry. Policy on early childhood caries (ECC): classifications, consequences, and preventive strategies. American Academy of Pediatric Dentistry Reference Manual. 2016. http://www.aapd.org/media/Policies_Guidelines/P_ECCClassifications. pdf. Accessed 29th September 2017 15. Statistics NZ. Integrated Data Infrastructure 2016. http://www.sta ts.govt.nz/idi. Accessed May 30, 2017. 16. Ministry of Health. Ethnicity Data Protocols for the Health and Disability Sector. Wellington: Ministry of Health; 2004. 17. Fahy KM, Lee A, Milne BJ. New Zealand socio-economic index 20132017. http://www.stats.govt.nz. Accessed 25th August 2017. 18. Noble M, Wright G, Smith G, Dibben C. Measuring multiple deprivation at the small-area level. Environ Plan. 2006;38:169. 19. Shi X, Alford-Teaster J, Onega T, Wang D. Spatial Access and Local Demand for Major Cancer Care Facilities in the United States. Ann Assoc Am Geogr. 2012;102:1125-1134. 20. StataCorp. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP; 2015. 21. Stats NZ. Table: Estimated Resident Population by Age and Sex (1991+) (Annual-Jun) (ref DPE056AA). In: Infoshare, ed. Population Estimates— DPE. http://www.stats.govt.nz/infoshare/ViewTable.aspx?pxID=baa4fe 99-fbad-4dfa-a97f-907e1d78320e: Statistics New Zealand; 2017. 22. Ministry of Health. Interactive Tool: Annual Update of Key Results 2015/16: New Zealand Health Survey. https://minhealthnz.shinyapps. io/nz-health-survey-2015-16-annual-update/. Accessed June 2, 2017. 23. Jordan H, Roderick P, Martin D. The Index of Multiple Deprivation 2000 and accessibility effects on health. J Epidemiol Community Health. 2004;58:250-257. 24. Adams J, White M. Socio-economic deprivation is associated with increased proximity to general practices in England: an ecological analysis. J Public Health. 2005;27:80-81.

9

25. Marshall TA, Eichenberger-Gilmore JM, Broffitt BA, Warren JJ, Levy SM. Dental caries and childhood obesity: roles of diet and socioeconomic status. Community Dent Oral Epidemiol. 2007;35:449458. 26. Irigoyen ME, Maupome G, Mejıa AM. Caries experience and treatment needs in a 6-to 12-year-old urban population in relation to socio-economic status. Community Dent Health. 1999;16: 245-249. 27. Thomson WM, Williams SM, Dennison PJ, Peacock DW. Were NZ’s structural changes to the welfare state in the early 1990s associated with a measurable increase in oral health inequalities among children? Aust N Z J Public Health. 2002;26:525-530. 28. Colchero MA, Popkin BM, Rivera JA, Ng SW. Beverage purchases from stores in Mexico under the excise tax on sugar sweetened beverages: observational study. BMJ 2016;352:h6704. 29. Schwendicke F, Thomson WM, Broadbent JM, Stolpe M. Effects of Taxing Sugar-Sweetened Beverages on Caries and Treatment Costs. J Dent Res. 2016;95:1327-1332. 30. Gibson J. The efficacy of the ‘soda tax’: Seminar. Auckland: AUT; 2017. 31. Kaste LM, Selwitz RH, Oldakowski RJ, Brunelle JA, Winn DM, Brown LJ. Coronal Caries in the Primary and Permanent Dentition of Children and Adolescents 1–17 Years of Age: United States, 1988– 1991. J Dent Res 1996;75(2 Suppl.):631-641. 32. Kaste LM, Drury TF, Horowitz AM, Beltran E. An Evaluation of NHANES III Estimates of Early Childhood Caries. J Public Health Dent. 1999;59:198-200. 33. Gibb S, Audas R, Milne BJ. Who misses out on the B4 School Check [PowerPoint Slides]. Wellington: COMPASS, The University of Auckland; COMPASS Research Colloquium; 2017. http://www.arts.auckla nd.ac.nz/en/about/our-research/research-centres-and-archives/comp ass/compass-annual-research-colloquiums.html

SUPPORTING INFORMATION Additional Supporting Information may be found online in the supporting information tab for this article.

How to cite this article: Shackleton N, Broadbent JM, Thornley S, Milne BJ, Crengle S, Exeter DJ. Inequalities in dental caries experience among 4-year-old New Zealand children. Community Dent Oral Epidemiol. 2018;00:1–9. https://doi.org/10.1111/cdoe.12364