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. Author manuscript; available in PMC: 2023 Feb 22.
Published in final edited form as: Caries Res. 2021 Feb 3;55(2):88–98. doi: 10.1159/000511699

The Association of Dietary Fluoride Intake and Diet Variables with Dental Caries in Adolescents from the ELEMENT Cohort Study

Alejandra Cantoral a, Teresa V Muñoz-Rocha a, Lynda Luna-Villa a, Andres Mantilla-Rodriguez b, José L Ureña-Cirett c, Gina A Castiblanco b, Maritsa Solano a, Hu H Howard d,e, Karen E Peterson e, Martha M Téllez-Rojo a, Esperanza A Martínez-Mier b
PMCID: PMC9944613  NIHMSID: NIHMS1657907  PMID: 33535210

Abstract

To examine the association of dietary fluoride intake, total carbohydrate consumption and other key dietary variables with dental caries experience among adolescents, a cross-sectional analysis was conducted in a sample of 402 participants from the Early Life Exposures in Mexico to Environmental Toxicants cohort. The presence and severity of dental caries were assessed using the Caries Detection and Assessment System (ICDAS) to calculate the number of Decayed, Missing, and Filled Teeth or Surfaces (D1MFT/D4MFT). Dietary intake of fluoride, energy, carbohydrates and food groups was estimated using a validated Food Frequency Questionnaire (FFQ). Multivariate zero-inflated negative binomial regression models and negative binomial regression models were run to estimate the association of fluoride intake (mg/d) and total carbohydrate intake (g/d) with the D1MFT/D4MFT index. We found that 80% of adolescents experienced dental caries (D1MFT>0), with 30% presenting cavitated lesions (D4MFT>0). Mean scores for D1MFT and D4MFT were 6.2 (SD 5.3) and 0.67 (SD 1.3), respectively. The median intake of fluoride estimated by the FFQ was 0.015 mg/d, this intake was statistically higher in those participants with a D4MFT=0 than those with a D4MFT>0 (0.90 vs 0.82 mg/d; 0.016 mg/Kg/d vs 0.014 mg/Kg/d, p<0.05). For D1MFT, D1MFS, D4MFT and D4MFS scores, there was a statistically significant reduction in the number of lesions with higher fluoride consumption (mg/d) from foods and beverages. The reported frequency of consumption of sugary foods in a whole day was statistically higher in those with D1MFT>0 than those with D1MFT=0 (p<0.05). Total carbohydrate intake (g/d) was positively associated with dental caries experience. We conclude that higher fluoride intake through foods and beverages was associated with lower dental caries experience among adolescents; this effect was seen even when the dietary intake of fluoride was 0.015mg/kg/d, which is lower than the average intake recommendation. In contrast, a higher amount of total carbohydrate intake and the frequency of intake of sugary foods were associated with higher dental caries experience, with no apparent threshold for the effects.

Keywords: caries detection, fluoride, carbohydrates, adolescents, ICDAS

Introduction

Dental caries is a sugar-mediated, biofilm-dependent, multifactorial disease [Kidd and Fejerskov, 2004] that remains one of the major public health problems worldwide for all age groups; affecting up to 90% of children in some countries [Petersen et al., 2005]. The burden of dental caries accounts significantly for disability-adjusted life year loss [Murray et al., 2012], and in children from developing countries, is one of the main reasons for school absences [Casamassimo et al., 2009; Pongpichit et al., 2008].

Development of dental caries lesions is modified by many biological and social determinants such as sex [Martinez-Mier and Zandona, 2013], age [Bernabe and Sheiham, 2014; Hugoson et al., 2008; Kawashita et al., 2012], oral hygiene [Molina-Frechero et al., 2015], salivary flow [Lee and Brearley Messer, 2011], genetic predisposition [Wang et al., 2010], socioeconomic status [Costa et al., 2012], access to dental services [Brickhouse et al., 2008], and parent’s education [Kumar et al., 2016]. Diet is one of the most studied factors in the development and prevention of dental caries, with carbohydrate intake being a major risk factor [Armfield et al., 2013; Lingstrom et al., 2003; Marshall, 2013; Moynihan and Petersen, 2004; Sheiham and James, 2014; Skinner et al., 2015]. Total dietary carbohydrate intake is a mixture of simple and complex carbohydrates: simple carbohydrates (also known as “free sugars” e.g sucrose) represent the highest risk for caries development [Masood et al., 2012; Sreebny, 1982]; whereas complex carbohydrates (e.g starch) may play a role in the enhancement of sucrose’s cariogenicity [Ribeiro et al., 2005]. Although complex carbohydrates may also play a role in the development of dental caries lesions, there are only a few reports of total carbohydrate intake and its association with the development of dental caries [Arnadottir et al., 1998; Beighton et al., 1996; Burt et al., 1988; Moynihan, 2016; Rugg-Gunn et al., 1984]. Another dietary factor associated with dental caries development is the frequency of sugar intake (either as beverages, snacks, or candies) [Holbrook et al., 1995; Holbrook et al., 1989; Sundin et al., 1992]. Some studies have documented that with a frequency of intake >4 times per day, the odds of developing dental caries increase up to 6 times[Rodriguez et al., 1999].

In Mexican regions with low natural levels of fluoride in water (<0.7 ppm), such as Mexico City, fluoridated salt is distributed as a measure to prevent and control dental caries [Salud, 2003]. The rationale behind the salt fluoridation program is its low-cost and higher potential of providing universal access to fluoride. When delivered via salt, fluoride becomes readily available in the diet and therefore in the oral environment, where it prevents the demineralization of the dental enamel surface and promotes its remineralization [Kidd and Fejerskov, 2004]. Even though the results of some studies have described a reduction in dental caries as a result of the Mexican salt fluoridation program [Irigoyen et al., 2012; Irigoyen and Sanchez-Hinojosa, 2000], prevalence is still high and the program seems to have a limited impact with respect to reducing the caries experience in children and adults. A plausible explanation for the sustained prevalence of dental caries despite the implementation of the fluoridation program in the Mexican population may be the dramatic increase in the intake of added sugars among children (6–12 years of age) and adolescents [Afeiche et al., 2018; Sanchez-Pimienta et al., 2016]. A dose-response relationship between dietary carbohydrates and caries has been well established: the higher the dietary carbohydrate intake, the higher the dental caries experience; with fluoride reducing the prevalence of dental caries but not eliminating the association between the amount/frequency of sugars and dental caries [Bernabe et al., 2016].

Therefore, the aims of this study are 1) to describe the intake of fluoride intake and key dietary factors (added sugar, carbohydrates, sugar sweetened beverages, fruits, cereals, cereals with added sugar, candies, maize products and fast food), and the diagnosis of dental caries in a well-described cohort of Mexican adolescents; and, 2) to estimate the association of fluoride intake and total carbohydrate consumption with dental caries in this cohort.

Materials and Methods

This is a cross-sectional analysis which includes a sample of adolescent (12–18 years) participants of the Early Life Exposure in Mexico to Environmental Toxicants birth cohort project (ELEMENT). Details of the cohort are reported elsewhere [Perng et al., 2019]. During 2015–2016, a sample of 550 children and adolescents were assessed in the ABC Hospital research center as a part of a dental study [Wu et al., 2019]. We excluded from this analysis participants younger than 12 years, who have mostly primary teeth as well as, participants who refused the oral examination, resulting in a final analytical sample of 402 participants.

This research was approved by the ethical, biosafety and research committees of the National Institute of Public Health in Mexico and the Institutional Review Boards of Indiana University, the University of Michigan and the University of Washington.

Outcome Variable: Dental Caries Experience

A calibrated pediatric dentist performed all the dental exams with the assistance of a nurse who recorded the findings. Before the oral examination, participants were asked to brush their teeth. Subjects were examined on a dental chair, using an oral mirror (number 5) under optimal lighting. Each surface was air-dried and examined according to the Caries Detection and Assessment System (ICDAS) [Ismail et al., 2007]. The recorded ICDAS scores were used to calculate the D1MFT/D1MFS and D4MFT/D4MFS indices (number of Decayed, Missing, and Filled Teeth or Surfaces), which differ based on the “D” component: D1 represents both cavitated and non-cavitated lesions (ICDAS scores 1–6) and D4 represents only cavitated lesions (ICDAS scores 4–6). Also, for descriptive analyses, a dichotomous dental caries experience variable was created. Participants with caries experience were defined as those who had at least one lesion (D1) or filling score greater than zero, whereas participants with no caries experience were those who had no lesions (D1) or filling score equal to zero.

Exposure variables: Diet assessment

Dietary data were collected using a validated, semi-quantitative food frequency questionnaire which included 140 food and beverages classified into 14 food groups [Denova-Gutierrez et al., 2016]. FFQ is the most common way to evaluate dietary intake in epidemiological studies, especially for long-term intake [Kabagambe et al., 2001]. The data collected in this study included the number of days, times per day, serving size, and the number of servings consumed of each food and drink listed, during the seven days prior to the interview. To process the dietary information, the quantity of each food and drink was obtained by multiplying the number of days by the times per day, by the portion size (grams (g) or millimeters (mL)) and by the number of portions or pieces consumed on each occasion. Average daily intake was obtained by dividing total grams or milliliters by seven days, and this information was used to determine the seven food-groups contributing to the total carbohydrate load: sugar sweetened beverages, fruits, cereals, cereals with added sugar, candies, maize products, and fast food. The “sugar sweetened beverages” (SSB) group (ml/d) was defined as the sum of six different beverages: sodas, sugar-sweetened commercial fruit beverages, sugar-sweetened commercial tea or flavored water beverages, home-made fruit beverages with sugar (“aguas frescas” commonly consumed in Mexico), coffee with sugar, and tea with sugar. The “fruit” group (g/d) included the types most consumed in Mexico as apple, banana, pear. The “cereals” group included foods such as rice, wheat and potato products and, box cereals. The “cereals with added sugar” group included foods such as pastries, Mexican sweet breads, cake, sugary breakfast cereals. The “candy” group included all kinds of hard candies, lollipop and, chocolates. The “maize” group included all corn products as tortillas and lastly, the “fast food” group include foods like pizza and hamburgers. We did not include foods with sugar substitutes as they are low consumed in this population.

For each food consumed, energy (kcal/d), carbohydrate (g/d), and added sugar (g/d), were calculated using a nutritional composition database of foods compiled by the National Institute of Public Health of Mexico. In the case of fluoride (mg/d), we used the unique database of the fluoride content of foods and beverages in Mexico, developed by our research group [Cantoral et al., 2019]. We also estimated the proportion of calories derived from carbohydrates and sugar as percentage of total energy intake (TEI); and we estimated the daily frequency of consumption of sugary foods (containing added sugar as an ingredient) as 0=none, 1 = 1–2 times/d, 2= 3–5 times/d, 3= >6 times/d.

Covariates

A social worker collected demographic information including sex, age, and socioeconomic status (SES) through a questionnaire. Assessment of SES was done using the AMAI algorithm (Asociación Mexicana de Agencias de Investigación de Mercado), which assigns scores to the household’s characteristics and access to services and, classifies them according to six categories: A/B, C+, C, D+, D y E (with A being the highest and E, the lowest) [AMAI]. One dental hygiene behavioral variable was also included in our model, which is tooth brushing initiation age (before two years of age, 2 to 4 years or older), also collected via questionnaire. Additionally, each study participant had anthropometric measures taken (weight and height) using calibrated instruments. The Body Mass Index (BMI) Z-score was estimated and classified using the WHO reference (undernutrition BMI Z-score<−2; overweight BMI Z- score >1, and obesity BMI Z-score >2 [de Onis et al., 2007].

Statistical Analyses

Characteristics of the sample were summarized with means, standard deviations (SD) or medians (IQR) according to the distribution of the variable; given that all the continuous dietary variables were skewed, comparisons among continuous variables were made with the nonparametric test Wilcoxon Rank-sum−for two-group variables or Kruskal-Wallis −for multiple-group variables. We estimated for categorical variables percentages (n) according to the DMFT index, and compared using Fisheŕs exact test. Bivariate analyses of selected dietary variables according to lack of caries experience or caries experience (D1MFT=0 vs D1MFT>0) were also conducted.

We used the zero-inflated negative binomial (ZINB) regression model to estimate the association of fluoride intake (mg/d) and of total carbohydrate intake (g/d) with the D1Mft/D1MFS indexes and negative binomial (NB) regression model for the association with D4MFT/D4MFS indexes. These approaches allowed us to take into account the over-dispersion (variance larger than expected) and zero inflation (extra zeroes) features of the distribution of the indexes [Salinas-Rodriguez et al., 2009; Scott, 2003]. Models were adjusted by age, sex, BMI Z-scores, SES, tooth brushing initiation and energy intake.

Models fit were assessed using the Akaike information criterion (AIC), the Schwartz-Bayesian information criterion (BIC), and −2 log-likelihood statistics where for each, smaller values indicate better fit. For homogenization purposes, the models were compared in terms of marginal effects. Furthermore, to determine the presence of a “threshold” fluoride intake level, non-linear associations were estimated incorporating polynomial terms into the model. Data were analyzed using STATA software, version 14.

Results

The mean age of study participants was 14.5 (± 1.5) years of age, 50% were male, 60% were classified with a normal body mass index, 37% with overweight and only 3% with underweight. SES was mainly center in the middle, being only 4% in the E level (very low) and 3% in the A level (high). It is noteworthy that only 20% of the participants reported initiating tooth brushing before 2 years of age. Almost 80% of the participants have experienced dental caries (D1MFT >0) with 30% presenting cavitated lesions (D4MFT>0).

Table 1 presents dental caries experience including both cavitated and non-cavitated caries lesions at the tooth- and surface- levels (D1MFT/D1MFS; D4MFT/D4MFS) according to sociodemographic, anthropometric, and behavioral characteristics. The average caries experience at the tooth-level including only cavitated lesions (D4MFT) was 0.67 (SD 1.3), whereas the inclusion of non-cavitated lesions (D1MFT) increased the index to 6.2 (SD 5.3). Tooth brushing initiation was a remarkable variable on dental caries experience, those kids that initiated after 4 years of age had a significant higher score in all indices (D1MFT, D1MFS, D4MFT, and D4MFS) compared to those that started before 2 years of age. On average, girls had a higher caries experience than boys (0.78 vs 0.56; and, 1.24 vs 1.01, p<0.05), when only cavitated lesions were included in the indices (D4MFT/D4FMS).

Table 1.

Dental Caries Experience according Socio-demographic, anthropometric and behavioral characteristics of participants

D1MFT D1MFS D4MFT D4MFS
mean (SD)
Dental Caries 6.2(5.3) 8.2(7.1) 0.67(1.3) 1.1(2.4)
Tooth brushing initiation (years of age)
< 2 (70.9%) 5.8(5.1) 7.6(6.8) 0.57(1.2) 0.88(2.1)
2 −4 (25.4%) 6.6(5.5) 9.0 (7.6) 0.81(1.2) 1.6(3.0)
> 4 (3.7%) 10.1(4.7) 13.0 (5.7) 1.53(2.3) 2.0(3.2)
Amount of dental paste added to the toothbrush
Full thick (23.6%) 6.1(5.2) 7.9(6.8) 0.53(1.3) 0.85(2.2)
Full slim (53.0%) 6.2(5.1) 8.3(7.0) 0.72(1.3) 1.21(2.4)
up to 3/4 (17.2%) 5.9(5.8) 7.8(7.6) 0.63(1.2) 0.98(2.0)
up to 1/2 (4.2%) 5.1(5.6) 7.1(7.7) 0.52(1.1) 1.3(3.4)
up to 1/4(2.0%) 8.5(5.5) 11.2(7.5) 1.37(2.3) 3.0(4.7)
Child’s sex
Female (48.5%) 6.6(5.3) 8.7(7.1) 0.78(1.4) 1.24(2.4)
Male (51.5%) 5.7(5.2) 7.7(7.1) 0.56(1.2) 1.01(2.4)
Body Mass Index (kg/m2)
Underweight (<18.5) 11.8(7.4) 15.6(9.8) 1.6(1.9) 3.1(4.4)
Normal (≥18.5 & <25) 6.0(5.0) 7.9(6.8) 0.66(1.3) 1.1(2.4)
Overweight (≥25 & <30) 5.9(5.4) 7.7(7.0) 0.60(1.4) 1.1(2.6)
Obesity (≥30) 6.4(5.1) 8.8(7.1) 0.58(1.1) 0.9(1.7)
SES AMAI_13X6
E (lower) 7.3(5.4) 10.2(7.6) 0.84(1.5) 1.4(2.8)
D 4.3(3.5) 6.3(5.2) 0.53(1.1) 0.9(1.9)
D+ 6.3(5.0) 8.4(6.9) 0.73(1.4) 1.3(2.9)
C 6.1(5.4) 8.1(7.4) 0.65(1.3) 1.1(2.3)
C+ 6.3(5.7) 7.8(6.9) 0.47(1.0) 0.6(1.3)
A/B (highest) 5.4(5.0) 6.9(6.5) 0.80(1.5) 1.3(2.9)
Head of household
education
Complete secondary 6.4(5.6) 8.6(7.7) 0.82(1.5) 1.4(2.6)
Completed high school 5.9(4.7) 8.0(6.6) 0.56(1.2) 1.0(2.3)
Higher education 6.2(5.5) 7.7(6.6) 0.56(1.2) 0.8(1.9)
Age (years)
12 4.0(4.1) 5.8(6.4) 0.6(1.4) 1.1(2.7)
13 5.8(5.2) 7.9(6.8) 0.6(1.1) 1.1(2.5)
14 6.6(5.5) 8.4(6.9) 0.5(1.2) 0.8(1.6)
15 7.1(5.5) 9.3(7.4) 0.4(1.0) 0.6(1.4)
16 6.7(5.5) 8.6(7.1) 0.8(1.6) 1.2(2.5)
17 7.4(5.3) 9.9(7.6) 1.0(1.5) 1.8(3.0)
p-trend 0.00 0.01 0.07 0.19
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N = 402, Wilcoxon’s rank sum test and Kruskal-Wallis, bolds indicate p<0.05

Regarding the association of nutritional status and caries experience, we found that those participants in the extremes (undernutrition or obesity) presented statistically higher scores of D1MFT than those with normal weight and overweight (U-shape association, Supplementary Fig 1). We did not find any difference in dental caries experience regarding SES and education of the head of the house (mainly the mother). As expected, dental caries experience including non-cavitated lesions (D1MFT/ D1MFS) increased with age with a statistically significant p-trend (p<0.05).

The bivariate analysis that took into account all the dietary variables showed that the median intake of fluoride (mg/d) from foods and beverages reported in the FFQ was statistically higher in those participants with non cavitated lesions than in those with cavitated lesions (0.90 vs 0.82 mg/d or 0.016 mg/Kg body weight/d vs 0.014 mg/Kg body weight/d, p<0.05). These intakes of fluoride from foods and beverages correspond to 0.015 mg of fluoride per kilogram of body weight (shown in Table 2).

Table 2.

Dietary variables according to dental caries experience

Dental Caries Dental Caries
No Yes No Yes
D1MFT=0 D1MFT>0 D4MFT=0 D4MFT>0
20.3 (82) 79.9(320) 69.8(280) 30.2 (122)
median (IQR) median (IQR)
Energy and nutrients
Fluoride intake (mg/d) 0.94 (0.74, 1.12) 0.85 (0.65, 1.10) 0.90 (0.69, 1.11) 0.82 (0.61, 1.06)
Fluoride intake (mg/kg/d) 0.015 (0.012, 0.021) 0.015 (0.011, 0.020) 0.016 (0.012, 0.021) 0.014 (0.010, 0.020)
Carbohydrates(g/d) 298 (229, 409) 309 (235, 403) 308 (238, 405) 306 (216, 393)
Carbohydrates(%) 56.1 (50.9, 60.7) 57.6 (52.4, 62.7) 57.5 (52.8, 62.0) 57.3 (51.9, 62.3)
Energy (kcal/d) 2130 (1676, 2823) 2150 (1709, 2842) 2144 (1736, 2858) 2174 (1628, 2766)
Added Sugar (g/d) 35.1 (15.3, 51.9) 27.7 (12.9, 52.6) 29.1 (14.0, 53.0) 25.8 (10.4, 50.2)
Sugar of TEI (%) 5.9 (2.9, 9.0) 5.3 (2.6, 8.9) 5.2 (2.8, 9.0) 5.3 (2.4, 8.5)
Food Groups source of total
Carbohydrates
SSB (ml/d) 604 (240, 891) 570 (291, 857) 600 (300, 857) 501 (240, 857)
Fruits (g/d) 165 (78, 303) 207 (97, 371) 190 (87, 357) 207 (107, 370)
Candies (g/d) 8.5 (0, 26) 5 (0, 26) 8.5 (0, 26) 4 (0, 27)
Cereals (g/d) 131 (87, 233) 153 (95, 221) 149 (90, 234) 153 (93, 214)
Cereals with sugar (g/d) 50 (10, 88) 43 (20, 84) 49 (19, 88) 40 (18, 71)
Maize (g/d) 71 (26, 104) 75 (37, 125) 75 (32, 114) 75 (32, 125)
Fast food (g/d) 75 (45, 116) 56 (18, 111) 64 (31, 111) 56 (19, 111)
Sugary foods (times/d) *
0 7 (8.5) 13 (4.1) 13 (5) 7 (6)
[1–2] 36 (44) 107 (33.4) 98 (35) 45 (37)
2.5–5 30 (36.5) 133 (41.6) 112 (40) 51 (42)
5.5 or more 9 (11) 67 (20.9) 57 (20) 19 (15)
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N=402

Wilcoxon’s rank sum test for continuous variables (2 groups), bolds indicate p<0.05

*

n(%) Fisheŕs exact tests, bolds indicate p<0.05

In analyses of food -group sources of carbohydrates, the differences in intake were not statistically significant different among those with or with no caries experience. It is, however, remarkable that this sample had a high intake of SSB (mL/d) regardless of dental caries experience (median 505 ml/d). The reported frequency of consumption of sugary foods in a whole day was statistically higher in those with caries experience. Approximately 41.6% of participants with caries experience (D1MFT) consumed sugary foods 3–5 times per day, and 20.9% consumed 6 or more times per day. On the other hand, participants with no caries experience (D1MFT) had a lower frequency of consumption of sugary foods only when non-cavitated lesions were included in the index: 36.5% consumed 3–5 times per day; and 11% consumed 6 or more times per day. Only 8.5% of participants with no caries experience and 4.1% of participants with caries experience did not report to consume sugary foods. The reported intake of total energy (kcal/d), carbohydrates (g/d) and sugar (g/d) showed no differences between those with no caries- or caries experience.

Table 3 presents the models of the association between fluoride and carbohydrate intake and dental caries experience. For all the indices of dental caries experience (D1MFT/D1MFS, D4MFT/D4MFS), there were statistically significant inverse associations with fluoride intake (mg/d) in foods and beverages. Participants who had higher intake of fluoride had on average lower values of dental caries experience (shown in Figure 1: a (D1MFT), b (D1MFS), c (D4MFT), d (D4MFS)), and threshold levels of fluoride for the relationships were not observed. In the case of total carbohydrate intake (g/d), its consumption was positively associated with all the indices (D1MFT/D1MFS, D4MFT/D4MFS), with no evidence of a threshold for any of the relationships (shown in Figure 2: a (D1MFT), b (D1MFS), c (D4MFT), d (D4MFS)).

Table 3.

Associations of fluoride and carbohydrates intake with dental caries experience

Negative binomial regression zero-inflated
D1MFT D1MFS
Coef 95% CI e^b % Coef 95% CI e^b %
Fluoride intake (mg/d) −0.729 −1.075 −0.382 0.482 −51.76 −0.723 −1.080 −0.358 0.485 −51.47
Carbohydrate (g/d) 0.002 0.001 0.003 1.002 0.20 0.002 0.001 0.003 1.002 0.20
Negative Binomial
D4MFT D4MFS
Coef 95% CI e^b % Coef 95% CI e^b %
Fluoride intake (mg/d) −1.137 −1.920 −0.353 0.321 −67.92 −1.040 −1.523 −0.556 0.35 −64.65
Carbohydrate (g/d) 0.002 0.001 0.004 1.002 0.20 0.002 0.001 0.003 1.002 0.20
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(Models adjusted for: age, sex, BMI Z-score, SES, tooth brushing initiation and energy intake) (n=402)

Fig 1.

Fig 1.

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Predictive margins and 95% CI of the association of Fluoride and D1MFT, D1MFS, D4MFT, D4MFS

Fig 2.

Fig 2.

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Predictive margins and 95% CI of the association of Carbohydrates and D1MFT, D1MFS, D4MFT, D4MFS

Discussion

This study further confirmed the cross-sectional negative association between fluoride intake and dental caries experience. This effect can be attributed to the fluoride content of foods and beverages only, as a quantitative estimate of fluoride from added salt was not included. The predicted decline in caries experience is higher when early caries lesions are included in the index (D1MFT/S), which was not surprising given the cross-sectional design of the study. Given that the study participants were 12–18 years old, the potential mechanism to explain the negative association found in this study and the fact that the decline in caries experience was steeper for early caries is its presence in the oral environment (topical effect) [Buzalaf et al., 2011]. It is important to note that this negative association was seen with a reported intake from foods and beverages of 0.015mg/kg/day [Castiblanco et al., 2019], which is lower than the current intake recommendation. Our findings are in agreement with previous investigations in Korean children, where a negative association between fluoride intake and dental caries experience were also found [Kim et al., 2015].

In this study, we found a prevalence of dental caries experience (D1MFT) of 80%, with cavitated lesions in 30% of the sample (D4MFT), a mean score of 6.1 for D1MFT and 0.67 for D4MFT. At national level it has been reported a prevalence of dental caries in Mexican adolescents above 60% (2014–2015) affecting an average of 2.9 to 4.5 teeth [SIVEPAB, 2015]. In this study, there were three main findings:

  1. The frequency of intake of sugary foods was higher among participants with caries experience; this finding of an association between caries experience and frequency of intake of sugary foods is in agreement with cross-sectional analyses reporting that the frequency of intake of sugary snacks is associated with dental caries even after controlling for fluoride exposure, and that this factor (frequency) accounts more than total sugar intake [Beighton et al., 1996; Holt, 1991; van Loveren, 2019].

  2. We did not find a statistically significant association between added sugar intake and dental caries experience; a potential explanation could be that in our data the median intake of added sugar as a percentage of the total energy intake (TEI) was around 5% (median 28gr/d), much lower than the current World Health Organization (WHO) recommendation of added sugars as a percentage of TEI <10% [Organization, 2003]. A daily intake of TEI <10% was reported to have a significant positive correlation between the per capita availability of sugar and dental caries, suggesting an outer limit of “safe” sugar intake of 50g per day (10% TEI) [Burt et al., 1988; Rugg-Gunn et al., 1984; Sreebny, 1982]. It is therefore, possible that the added sugar intake of this population was in the limit reported as “safe” by the WHO.

  3. After adjustment of fluoride intake and covariates, the total amount of carbohydrates was associated with increased caries experience, with no apparent threshold of carbohydrates for the relationship. The fact that we did not observe an association between added sugar intake and caries experience but between total carbohydrates intake and caries experience brings attention to an old dilemma: the role of starch in the caries process [Lingstrom et al., 2000]. As seen in the supplementary Figure 2, 47.1% of the total carbohydrate intake comes from foods with added sugars (SSB, candies and cereals with added sugars), whereas 52.9% comes from foods with the combination of intrinsic free sugars, complex sugars and added sugars (fruits, cereals, maize, fast food, other) [Sanches Castillo et al., 2000]. Most of the latter (except fruits) have in common the presence starch, meaning that its contribution may not be negligible in the caries process of this population.

It is well known that modern dietary patterns include the intake of a mix of both free- and complex sugars, and starch has been described to potentiate the cariogenic effect of free sugars like sucrose [Ribeiro et al., 2005]. The proposed mechanisms of starch in the caries process include its capacity to be retained in the dental morphology for prolonged times; its role as a sugar reservoir for prolonged times and, its role as a co-cariogenic when consumed in conjunction with free sugars [Lingstrom et al., 2000]. In fact, in-situ studies have observed greater demineralization when sucrose and starch are combined, compared to sucrose alone [Ribeiro et al., 2005]. This rationale of including total carbohydrate intake in the analysis is especially important in populations where foods rich in starch are dietary staples, as in Mexico [Nieto et al., 2017], and brings the attention to the overall composition of the diet and the frequency of intake of sugary foods more than to a particular sugar-containing food.

Additionally, it was observed that in this population, total carbohydrate intake was more predictive of dental caries when early lesions were included compared to cavitation lesions only (Figure 1 c, d). This may be explained by differences in the caries process in both types of lesions. The development of early caries lesions (non-cavitated) locally depends mainly on the formation of the biofilm, which in turn depends on the availability of sugars. On the other hand, the development and progression of cavitated lesions also involves the degradation of the dentin’s organic matrix [Chaussain-Miller et al., 2006], which depends on the direct contact of saliva and the biofilm with the cavitation. Therefore, the biological and sociodemographic risk factors for cavitated lesions (including diet) slightly differ with those of non-cavitated lesions [Fontana et al., 2011] and this may be the reason why in this study, total carbohydrate is associated with early but not cavitation lesions.

We acknowledge that this study has some limitations. First, In Mexico, the use of radiographs for the detection of approximal caries is not part of national surveillance programs; there are no national statistics on the prevalence of this condition. Partially due to that reason, we made the decision not to include bitewing radiographs in our examination when designing the study. Two other factors influenced our decision, first we aimed at keeping the length of the visits acceptable to our participants. And finally, we were cognizant of recent evidence which has indicated that their use in children may lead to over diagnosis [Mendes et al., 2016; Moro et al., 2018; Pontes et al., 2020; Pontes et al., 2019]. Mexican adolescents have access to fluoridated toothpaste, but we were not in a position to estimate its use or frequency or the use of other caries-preventive strategies that could also contribute to the variability in dental caries experience observed in this sample.

The FFQs have limitations when calculating nutrient intakes, since recall plays a major role in their responses [Cade et al., 2002; Kipnis et al., 2002]. However, structured, interviewer-administered questionnaires were used by trained personnel to assist with portion size determination, recall, and capture of common foods not queried on standard forms by prompting for additional information in open-ended questions at the end of the survey.

Another limitation of this study is that the cohort was not originally designed to assess the relationship between fluoride intake, sugar and fluoride and we were not at the position to ask about topical fluoride use and frequency of oral hygiene, which are two known caries risk factors. However, we did include a question regarding tooth brushing before or after two years of age: interestingly, we found that those who did not start tooth brushing before two years of age had higher dental caries experience. This result was in agreement with studies that have reported that caries risk factors remain stable from early childhood to older ages [Mattila et al., 2005].

Conclusion

Dental caries is still a public health problem in Mexico and is the result of complex interactions between multiple factors, including diet, behavior, and fluoride exposure. Many reports have documented that sugar intake is the main dietś factor related to caries experience, however few studies address total carbohydrate intake as a key factor. In this cross-sectional analysis of adolescents, we estimated the association between dental caries experience and two main dietś components: fluoride intake through foods and beverages and total carbohydrate intake. After adjustment by important covariates, both components were statistically associated to all dental caries experience indices (D1MFT/D1MFS, D4MFT/D4MFS). It is crucial to develop effective interventions to prevent caries that include dietary guidelines. The development of dietary guidelines to prevent and control dental caries in Mexico should take into account not only total carbohydrate intake and frequency of consumption of sugary foods, but also total dietary fluoride intake. We recommend for future studies to evaluate total carbohydrate intake instead of free-sugar intake.

Supplementary Material

1

Acknowledgement

The authors thank the American British Cowdray Hospital provided facilities that were used for this research.

Funding Sources

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was supported by the grants R01ES021446, R01ES007821, P42-ES05947, and P30ES017885 from the US National Institute of Environmental Health Sciences (NIEHS), the grant P01ES022844/RD83543601 from NIEHS/US Environmental Protection Agency, by the National Institute of Public Health/Ministry of Health of Mexico.

Footnotes

Statement of Ethics

This research was conducted ethically in accordance with the World Medical Association Declaration of Helsinki. Participants read and signed the informed consent, Study protocol was approved by National Institute of Public Health (IRB # CI-599-8-14102014), and the Institutional Review Boards of Indiana University, the University of Michigan and the University of Washington

Disclosure Statement

The authors have no conflicts of interest to declare.

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Supplementary Materials

1
NIHMS1657907-supplement-1.pdf (176.8KB, pdf)

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