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Does Gender Contribute to Any Differences in Caries and Periodontal Status in UK Children?

Article Information

Sofia Papadaki1, Ioannis Pilalas2, Jing Kang3*

1Dental Core Trainee at the James Cook University Hospital, Middlesbrough, UK 2Defence Primary Healthcare, Dental Centre Catterick ITC, Catterick Garrison, UK 3School of Dentistry, University of Leeds, Leeds, UK

*Corresponding Author: Jing Kang, School of Dentistry, University of Leeds, LS2 9LU, Leeds, UK

Received: 15 July 2022; Accepted: 29 July 2022; Published: 28 September 2022

Citation: Sofia Papadaki, Ioannis Pilalas, Jing Kang. Does Gender Contribute to Any Differences in Caries and Periodontal Status in UK Children?. Archives of Internal Medicine Research 5 (2022): 463-474.

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Abstract

Background: Gender Inequalities In Dental Caries And Periodontal Diseases Have Been Reported Among Adults. However, Literature Focusing On Children Is Scarce. The Aim Was To Examine Whether Gender Affects Caries Experience And Periodontal Status In UK Children Based On The 2013 Children’s Dental Health Survey Dataset (CDHS).

Methods: CDHS Included Children Aged 5, 8, 12 And 15 Years. Dental Caries Experience And Periodontal Status Were Reported Using The Number Of Decayed, Missing And Filled Teeth (DMFT Or Dmft For Permanent Or Primary Dentition At D1 And D3 Thresholds) And The Basic Periodontal Examination (BPE) Score. To Assess Gender Inequalities On DMFT/Dmft And BPE, Zero- Inflated Negative Binomial (ZINB) And Multinomial Logistic Regression Models Were Employed Respectively.

Results: Analyses Included 9,866 Children. No Gender Inequalities In Caries Experience Were Observed For The 5 And 8-Year-Old Groups. However, In 12- And 15-Year-Old Adolescents, Females Had Higher D3MFT Scores Compared To Males (IRR: 1.28, 95% CI: 1.10-1.49 And IRR: 1.16, 95% CI: 1.00-1.35). 15-Year-Old Females Had Lower Probability To Be Caries Free (OR: 0.59, 95% CI: 0.45-0.82). With Regards To Periodontal Status, Significant Gender Inequalities Were Not Observed (P>0.05).

Conclusions: In The UK, Female Adolescents Experienced More Carious Lesions Compared To Males When Dental Caries Was Diagnosed Into Dentine (D3MFT). However, 15-Year-Old Males Matched Females In Caries Experience When Early Enamel Lesions Were Considered (D1MFT). No Gender Dissimilarity Was Identified Among British Adolescents Regarding Periodontal Status. The Increased Dental Caries Risk Of Adolescent Females May Indicate The Necessity For Bespoke Oral Health Measures.

Keywords

Caries; Periodontal; Gender Inequality; Children’s Dental Health Survey

Caries articles; Periodontal articles; Gender Inequality articles; Children?s Dental Health Survey articles

Article Details

1. Introduction

Gender inequalities in dental caries and periodontal diseases have been widely investigated for adult populations. Many studies showed that females experience a higher burden of dental caries [1], while males were found to be more susceptible to exhibiting advanced periodontal disease [2]. However, evidence in the field of paediatric dentistry remains unclear since various studies had mixed conclusions. Some studies depicted gender bias regarding caries experience for juvenile patients in which females were reported to be more susceptible [3-8], while other studies supported an opposite trend, in which males especially at the primary dentition stage, exhibited higher caries experience than females of same age [9-12]. On the other hand, certain studies reported insignificant (p>0.05) gender inequalities in caries experience between genders [13-16].

For periodontal diseases, some literature suggested that male teenagers were more likely to demonstrate suboptimal oral hygiene [17-20] and develop gingivitis. However, some studies reported absence of significant gender inequalities in the periodontal status of children [21, 22]. It is important to underline that evidence on gender inequalities is limited due to biased sampling, small sample size and methodological flaws. This study aims to investigate whether gender impacts on differences in dental caries and periodontal status of children by using the UK 2013 Children’s Dental Health Survey (CDHS) data.

2. Material and Methods

2.1 Data source

The 2013 CDHS dataset included children from England, Wales and Northern Ireland. Data were collected through clinical examinations by calibrated dental teams, questionnaires completed by 12- and 15-year-old pupils and parent questionnaires of participating children [23]. The target populations were the 5-, 8-, 12- and 15-year-old children, representing primary (5-year-old), mixed (8-year-old) and permanent dentition (12- and 15-year-old) [23]. Ethical approval for CDHS was gained by the ethics committee of University College London (Project ID 2000/003) and participants had consented in advance for data use in future research projects.

2.2 Outcome measures

There were two outcome measures:

  1. Dental caries experience based on DMFT/dmft scores
  2. Periodontal status using BPE scores

Dental caries experience was measured at two distinct threshold including enamel lesions (D1) and dentinal lesions (D3). Figure 1 demonstrates the differences between those thresholds. Periodontal status was measured based on BPE scores (Table 2), which were only available for 15-year-old children.

fortune-biomass-feedstock

Figure 1: Illustration of differences between D1MFT/d1mft (including enamel and dentine lesions) and D3MFT/d3mft (dentine lesions only) [47].

D1MFT/d1mft

D3MFT/d3mft

Decayed teeth including early enamel lesions along with dentinal caries

Decayed teeth, including caries lesions into dentine only

Missing teeth due to caries

Missing teeth due to caries

Filled teeth

Filled teeth

Table 1: Explanation of differences between D1MFT/d1mft (enamel lesions) and D3MFT/d3mft (dentine lesions).

Levels

BPE scores

Level 1

0

No bleeding

Level 2

1

Bleeding on probing

Level 3

2

Bleeding with retentive factors, such as calculus

Level 4

3

Bleeding with shallow pockets between 3.5-5.5mm

4

Deep pockets>5.5mm

Table 2: BPE scores and levels in multiple regression analysis.

2.3 Exposure

Gender was the main exposure measure.

2.4 Confounding factors

Those included demographic characteristics such as:

  1. Age (scale)
  2. Socio-economic status (SES; quantiles 1-5) [24]
  3. Dietary habits such as consumption of water or food and drinks containing sugar including cakes, biscuits, sweets, fruit juice, smoothies, energy and fizzy drinks (less than once a day, more than twice a day)
  4. Oral hygiene practices such as tooth brushing frequency (less than once a day, more than twice a day), tooth flossing (yes, no)
  5. Pattern of dental attendance [25] (only when problems arise, routinely)
  6. Experience of orthodontic treatment (yes, no)
  7. Dental anxiety levels (low, medium, high) [26, 27]

Further factors were examined, including children’s experience of dental prevention (fissure sealants, fluoride varnish) and use of fluoride toothpaste. However, covariates that were available for a small number of participants or did not reach the defined significance level [28] were not included in multivariate analysis for the adjustment of ZINB and MLR models.

2.5 Statistical analysis

Descriptive statistics were performed for comparisons between males and females. The zero- inflated negative binomial models (ZINB) were used to fit D1MFT/d1mft and D3MFT/d3mft scores, as indicated by the DMFT/dmft distribution. The ZINB model is a two-part model, of which the zero-inflated part estimates the chance of excessive zeros, and the count model estimates the number of DMFT/dmft. Confidence interval (CI) was set to 95% after sampling weight. Adjustments for demographic features, oral hygiene practices, dietary habits and dental anxiety were included in the models gradually. This led to three statistical models from a univariate to a multivariate analysis. The m0 model was unadjusted and compared the D1MFT/d1mft and D3MFT/d3mft differences between genders without taking into consideration other possible confounders.

The m1model was adjusted for demographic features. The m2, which applied only for the D1MFT and D3MFT variables, was adjusted for the above- mentioned covariates, including children’s SES, dental behaviour, dietary habits and dental anxiety. Subgroup statistical analysis to estimate children’s caries experience in each age group was performed. The subgroup analysis referred to 5-, 8-, 12- and 15- year-old children, respectively. With regards to periodontal status, data were analysed using the Multinomial Logistic Regression (MLR) model at four different levels [level 1, or reference level (BPE:0), level 2 (BPE:1), level 3 (BPE:2) and level 4 (BPE:3 or 4)]. The aim was to compare each group (levels 2, 3, 4) with the reference level (Table 2). The model was sequentially adjusted for SES, oral hygiene practices, including frequency of toothbrushing, flossing, dental attendance pattern, and experience of orthodontic treatment [29]. Data were weighed according to primary sampling unit (PSU) and strata, and then, analysis was performed using R studio with Survey Package and StataSE 14.

3. Results

In total, 9,866 children were included in analyses. A comparison of different covariates between genders is presented in Table 3. For dental caries, no differences were found among 5- and 8-year-old children at either caries threshold. Females were associated with higher DMFT scores, regardless of the threshold at which dental caries was diagnosed in 12-year-old children [IRR (D3): 1.28, 95%CI (1.10- 1.49), p<0.01 and IRR(D1): 1.22, 95% CI (1.10-1.35), p<0.001]. Discrepancies in caries experience between genders were evident among 15-year-old children, only at the dentinal threshold [IRR (D1): 1.16, 95% CI (1.00-1.35), p<0.05]. Also, the

possibility for 15-year-old females to be “caries-free” (DMFT:0) was lower compared to males [OR (D3):0.59, 95% CI (0.45-0.82), p<0.01 and OR

(D1):0.55, 95% (0.41-0.74), p<0.001], regardless of threshold. However, when caries experience included early enamel lesions (D1MFT), males matched females in caries experience (Table 4). The MLR model results, which compared periodontal status of 15-year-old females and males, are summarised in Table 5. There was no significant difference (p>0.05) for the examined BPE scores between genders.

Male

Female

p-value

N

4812 (48.8)

5054 (51.2)

Demographics

Age group

0.496

5-year-old

1264 (26.3)

1285 (25.4)

8-year-old

1171 (24.3)

1196 (23.7)

12-year-old

1222 (25.4)

1310 (25.9)

15-year-old

1155 (24.0)

1263 (25.0)

HMRC quintile

0.001

1 (Most deprived)

1432 (30.9)

1669 (34.5)

2

1062 (22.9)

1144 (23.7)

3

952 (20.6)

903 (18.7)

4

710 (15.3)

671 (13.9)

5 (Least deprived)

473 (10.2)

448 (9.3)

Oral hygiene practices

Frequency of brushing teeth

0.001

Twice a day or more

1652 (80.8)

1765 (85.1)

Less than twice a day

393 (19.2)

310 (14.9)

Used dental floss in the last year = No

1000 (80.6)

1013 (76.1)

0.006

Pattern of dental attendance = Only when in trouble/never

428 (18.3)

432 (17.1)

0.28

Orthodontic treatment experience

Ever had bracket fitted or adjusted = No

1493 (88.9)

1446 (83.1)

<0.001

Dietary habits

Frequency of eating cakes or biscuits

0.018

Twice or more a day

1040 (44.8)

1024 (40.5)

Once or less a day

1280 (55.2)

1506 (59.5)

Frequency of eating sweets

0.586

Twice or more a day

966 (41.6)

1074 (42.4)

Once or less a day

1355 (58.4)

1460 (57.6)

Frequency of drinking soft drinks containing sugar

<0.001

Twice or more a day

854 (37.1)

845 (33.5)

Once or less a day

1451 (62.9)

1674 (66.5)

Frequency of drinking energy drinks

<0.001

Twice or more a day

416 (18.1)

354 (14.2)

Once or less a day

1886 (81.9)

2141 (85.8)

Frequency of drinking fizzy drinks

<0.001

Twice or more a day

1103 (47.3)

1062 (41.8)

Once or less a day

1225 (52.7)

1476 (58.2)

Frequency of drinking water

0.049

Twice or more a day

1631 (70.7)

1810 (71.9)

Once or less a day

675 (29.3)

706 (28.1)

Dental anxiety

Self-rated dental anxiety score

<0.001

Low/no anxiety

935 (40.9)

576 (23.4)

Moderate anxiety

1172 (51.2)

1461 (59.5)

Extreme anxiety

181 (7.9)

420 (17.1)

Dental health outcomes

d3mft (mean (SD))

0.8 (1.8)

0.7 (1.6)

<0.001

D3MFT (mean (SD))

0.9 (1.9)

1.1 (2.2)

<0.001

d1mft (mean (SD))

1.2 (2.2)

1.0 (2.1)

0.001

D1MFT (mean (SD))

1.7 (3.0)

1.9 (3.1)

0.012

BPE (N %)

0.849

0 (N %)

530 (49.8)

581 (51.4)

>0.05

≠ 0 (N %)

534 (50.2)

550 (48.6)

>0.05

Note: Data are presented as frequency (%) unless specified. Numbers may not sum to totals due to missing values; percentage

may not sum to 100 due to rounding.

Deprivation index was grouped in quintiles as follows:

1 (most deprived, ranks 1-6496), 2 (ranks 6497-12993), 3 (ranks 12994-19489), 4 (ranks 19490-25986), 5 (least deprived, ranks

25987-32482)

P-value was for comparing characteristics between male and female. SD: standard deviation

Table 3: Comparison between male and female participants in 2013 CDHS (n=9866).

Age (years)

m0

m1

m2

5

NB, IRR (95% CI)

ZI, OR (95% CI)

NB, IRR (95% CI)

ZI, OR (95% CI)

NB

ZI

d3mft

0.89 (0.74,

1.08

(0.90,

0.90 (0.82, 1.10)

1.07 (0.82,

1.00)

1.35)

1.35)

d1mft

0.94 (0.82,

1.09

(0.90,

0.95 (0.82, 1.10)

1.07 (0.90,

1.10)

1.35)

1.35)

8

NB, IRR (95% CI)

ZI, OR (95% CI)

NB, IRR (95% CI)

ZI, OR (95% CI)

NB

ZI

d3mft

0.93 (0.82,

1.12

(0.90,

0.91 (0.82,

1.08 (0.90,

1.00)

1.35)

1.00).

1.35)

d1mft

0.96 (0.90,

1.17

(0.90,

0.95 (0.90, 1.00)

1.16 (0.90,

1.00)

1.35)

1.49)

12

NB, IRR (95% CI)

ZI, OR (95% CI)

NB, IRR (95% CI)

ZI, OR (95% CI)

NB, IRR (95% CI)

ZI, OR (95% CI)

D3MFT

1.28 (1.10,

0.95

(0.74,

1.25 (1.10, 1.49)

1.11 (0.82,

1.28 (1.10,

0.96 (0.67,

1.49) ***

1.22)

**

1.49)

1.49) **

1.35)

D1MFT

1.12 (1.00,

1.07

(0.82,

1.12 (1.10, 1.22)

1.28

1.22 (1.10,

1.32 (0.90,

1.22) *

1.49)

*

(0.90, 1.82)

1.35) ***

1.35)

15

NB, IRR (95% CI)

ZI, OR (95% CI)

NB, IRR (95% CI)

ZI, OR (95% CI)

NB, IRR (95% CI)

ZI, OR (95% CI)

D3MFT

1.13 (1.00,

0.70

(0.55,

1.13 (1.00, 1.22)

0.76

(0.55,

1.16 (1.00,

0.59 (0.45,

1.22) *

0.90) *

*

1.00) .

1.35) *

0.82) **

D1MFT

0.97 (0.90,

0.64

(0.50,

0.95 (0.90, 1.00)

0.67

(0.50,

1.01 (0.90,

0.55 (0.41,

1.10)

0.90) **

0.90) *

1.10)

0.74) ***

NB: Negative binomial part; Mean DMFT/dmft (2003/2013) difference between females and males with caries experience (females vs males); ZI: Zero-inflated part; Possibility of being caries free (females vs males); IRR: Incidence rate ratio; OR: Odds ratio; CI: Confidence interval; m0: Unadjusted model; m1: Adjusted model for demographic factors (SES); m2: Adjusted model for demographic features (SES), dental behaviour (pattern of dental attendance and toothbrushing), dietary habits (frequency of eating cakes or biscuits, drinking fizzy drinks, energy drinks, soft drinks containing sugar and water) and dental anxiety

. p value < 0.1; *p value < 0.05; **p value < 0.01; ***p value < 0.001

Table 4: Dental caries experience between females and males (females vs males).

BPE

m0RRR (95% CI)

m1RRR (95% CI)

m2RRR (95% CI)

0 (ref)

1

1

1

1

0.90 (0.74, 1.10)

0.87 (0.70, 2.07)

1.22 (0.74, 2.01)

2

0.98 (0.82, 1.22)

0.79 (0.74, 1.10)

0.62 (0.33, 1.10)

3 or 4

1.03 (0.67, 1.65)

0.90 (0.61, 1.35)

0.35 (0.12, 1.97) .

RRR: Relative risk ratio; CI: Confidence interval; m0: Unadjusted model; m1: Adjusted model for demographic factors (SES);

m2: Adjusted model for demographic features and dental behaviour including pattern of dental attendance, frequency of tooth brushing, flossing and participants’ orthodontic treatment experience.

. p value < 0.1; *p value < 0.05; **p value < 0.01; ***p value < 0.001

Table 5: Periodontal status between the 15-year-old females and males (females Vs males).

4. Discussion

This is the first study that reported on gender inequalities using a large UK dataset which included enamel and dentine caries. Gender inequalities were not noted for primary dentition for dental caries nor for periodontal diseases. A potential explanation could be that children of such young age are not able to determine their dietary habits nor are responsible for daily oral hygiene. Therefore, the most important risk factors are influenced directly by parents or guardians, which could demarcate the absence of gender susceptibility to dental caries. Notably, most studies agree with the lack of significant gender discrepancy regarding dental caries experience in primary dentition [13, 16, 30, 31]. However, it would be prudent not to draw firm conclusions due to lack of data on eating habits and oral hygiene practices for those age groups. In the permanent dentition, the outcomes were more distinct as females in the 12- year-old group, had higher D1MFT and D3MFT scores. This susceptibility was also confirmed among 15-year-old adolescents, but only when dental caries was diagnosed into dentine (D3MFT). When early enamel lesions were included in caries diagnosis, the 15-year-old males matched females in caries experience, which highlights that caries experience for males comprised of more enamel lesions. Therefore, gender discrepancy at younger ages or when caries examined into dentine only, may be attributed to earlier tooth eruption in girls.

According to pupil questionnaires, female adolescents consumed sweets and sugary soft drinks less frequently, while they brushed their teeth more frequently. Ideally, this should have materialised in less exposure to dental caries. However, higher caries prevalence among females may be associated with erroneous assumptions on healthy and balanced diet from a dental perspective. It could be hypothesised that participants may have underestimated the daily consumption of hidden sugars with exponential cariogenic risk [32-34]. Another explanation of higher female susceptibility may be associated with earlier tooth eruption and, therefore, longer exposure to cariogenic products in the oral cavity [35]. Furthermore, some genome-wide-association-studies (GWAS) asserted that gender differences may be attributed to several gene variations influencing the oral environment, enamel formation, dietary preferences and composition of pathogenic bacteria [1, 36, 37]. Additionally, differences in saliva composition and in overall saliva flow rate could stem from hormonal changes due to puberty onset [38], pregnancy or menstruation, which in turn, renders female adolescents more prone to dental caries [10, 39]. Among physiological variations between genders, elevated oestrogen levels in females have been associated with changes in saliva composition and reduction in salivary flow. These conditions in combination with a cariogenic diet could contribute to caries incidence among female adolescents [40].

Although there is no consensus regarding the existence of specific gender inequalities in caries experience for the permanent dentition of adolescents, a few studies [3, 5, 8, 41] were in accordance with our findings. Multiple studies [21, 22, 42] agreed with the absence of gender discrepancies regarding periodontal status of the 15- year-old adolescents based on BPE scores which was also affirmed by our findings. In contrast, other studies [9, 10, 13, 14] reported that males had worse gingival or periodontal status than females. The reported susceptibility of male adolescents to poorer periodontal/gingival status may stem from suboptimal oral hygiene regime rather than genetic superiority of females. Also, notable deviations in study design, sample selection and indices do not allow direct comparisons to be made or concrete conclusions to be drawn.The high-quality 2013 CDHS dataset offers the opportunity for comprehensive analysis of children’s oral health [15]. Furthermore, the different thresholds at which dental caries was diagnosed are reflected eloquently in the present study, eliminating the risk of confusion or result deviations and allowing comparisons between different outcomes. Another strength of this study is reflected on the ΖΙΒΝ model used to investigate caries experience, which is the most reliable and appropriate statistical approach according to DMFT/dmft distribution [43].

However, there are also certain limitations. A number of factors may mean that CDHS underestimates the true population levels of oral disease. As with most surveys, CDHS was based solely on clinical examination, and epidemiological convention calibrates examiners to “underdiagnose” the presence of dental caries in case of uncertain diagnosis [15]. Also, BPE may underestimate periodontal disease [44]. Additionally, children attending special needs schools, where oral disease levels may be higher, were not included in CDHS which may have underestimated the burden of such oral diseases among British children [45, 46]. A further limitation is that self-reported dietary habits for the 12- and 15- year-old groups may have underestimated the consumption of cariogenic food and drinks. Limited availability of dietary data may mean that the ZINB model was not adjusted for those factors for 5- or 8- year-old groups. As a result, estimations of d3mft and d1mft may have been more susceptible to errors. Furthermore, BPE data were only available for the 15-year-old group, rendering comparisons between age groups impossible.

Despite our findings, more prospective studies are required to ascertain accurate conclusions before additional preventative measures can be recommended based on gender and further investigation on the impact of individual regional water fluoridation scheme may play in children’s caries experience would be useful. This investigation could reflect the need for further preventative measures, such as the implementation of water fluoridation schemes in more communities across the UK. With respect to children’s periodontal status, more prospective studies that adopt a widely agreed index, would be useful in investigating the potential for advanced periodontal treatment needs among children of different ages.

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