Caries and obesity: A cross-sectional study of populations and microbiology

doi:10.21203/rs.3.rs-4928109/v1

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Caries and obesity: A cross-sectional study of populations and microbiology

https://doi.org/10.21203/rs.3.rs-4928109/v1

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Caries and obesity in children are public health concerns. Although the relationship between the two non-communicable diseases has been studied for many years, the results are still controversial. This study aimed to investigate the relationship between caries and obesity in children aged 7-12 years old in Jinzhou, China.1864 children were selected for cluster sampling clinical study. All the selected students completed a questionnaire, recorded their height and weight, conducted oral examinations, and collected decayed⁃missing⁃filled teeth (dmft , DMFT) information. Forty children were randomly divided into the following groups: high caries (HC) + obese, caries-free (CF) + obese, HC+non-obese (NO), CF+NO. The diagnosis of dental caries and obesity is based on the standards of the World Health Organization. Collect saliva and feces samples. Multivariate analysis of variance, chi-square test, and multiple linear regression were used to evaluate the data, and 16s rDNA V3-V4 was used to detect microorganisms in saliva and fecal samples. The prevalence rates of dental caries, overweight, and obesity were determined, with significant associations found between demographic factors and BMI. Factors such as dietary structure, frequency of specific food consumption, parents' educational level, exercise habits, and sedentary behavior were linked to the decayed-missing-filled index of teeth. Microbiota analysis revealed differences in microbial composition between caries and non-caries, obese and non-obese groups in both saliva and feces samples. Dietary factors, particularly the consumption of sugary foods, along with exercise frequency, sedentary behaviors, and parental educational levels, are recognized as common risk factors for caries and obesity. Notably, the prevalence of caries in primary teeth is inversely correlated with BMI, whereas the rate of caries in permanent teeth is directly proportional to BMI.16S rDNA sequencing results suggesting that prevotella may act as a co-pathogenic bacterium in the development of both conditions.

caries

obesity

children

saliva

feces

microorganisms

Globally, the prevalence of overweight and obesity among children has significantly increased in recent years. The World Health Organization has recognized obesity as a "global epidemic disease," making it a pressing concern for countries around the world[1]. Childhood obesity can induce both immediate and long-term health risks, such as hypertension, type 2 diabetes, metabolic syndrome, and behavioral and mental problems [2]. Dental caries is an infectious disease and is one of the most common diseases among children and teenagers in the world[3]. Multiple factors are known to be involved in its prevalence, such as high frequency of sugar intake, poor oral hygiene, presence of cariogenic bacteria, and quality and quantity of saliva[4]. Dental caries and overweight/obesity are two interrelated diseases that share numerous predisposing factors, including diet, lifestyle, genetics, socioeconomic status, and various environmental influences [5]. Given the common causative relation between dental caries and overweight/obesity, many researchers have hypothesized that overweight/obesity might be a marker for dental caries in children[6, 7].

Both the oral cavity and large intestine accommodate unique microbiomes that are relevant to human health and disease [8, 9]. Mouth and gut are linked by a constant flow of ingested food and saliva along the gastrointestinal tract (GIT), despite this connection, they host distinct microbial communities[10, 11]. Notably, alterations in the gut microbiota—specifically an increase in Firmicutes and a decrease in Bacteroidetes—have been identified as significant contributors to the pathogenesis of obesity[12].

Diet can interfere with the oral and intestinal microbiota[13, 14], which in turn affects the immune system and the development of obesity. Intestinal microflora is not the only microbiota associated with systemic diseases; alterations in oral microbiota are also linked to systemic conditions[15]; given that the oral cavity is part of the mucosal system, alterations in oral microbiota may influence the immune system and overall bodily homeostasis.

In this study, we explored the potential correlations between BMI categories and caries experience among children in the Jinzhou region of China. Furthermore, we conducted a characterization of the oral and gut microbiota in children(n = 40) by sequencing the 16S rDNA V3-V4 region.

Study Design, Sample Selection, and Study Population

The method of stratified random cluster sampling is adopted, that is, in designated schools, stratified according to grade and cluster random sampling with class as a unit. Taking into account missed visits and individual samples that did not meet the inclusion criteria, the sample size increased by 10%, with a total of 1864 children aged 7–12 years old. This epidemiological investigation was approved by the Ethics Committee of Stomatology Hospital Affiliated of Jinzhou Medical University (ethics permit number: JYFELL202404), which is fully in line with the Helsinki Declaration of the World Medical Association. Obtain a signed informed consent form from the child's family before the child participates in the study. The inclusion criteria are: (1) Primary school students aged 7–12 years. (2) Children who have lived in the sampling area for more than 6 months. (3) understand the details of the study and sign the consent form. The exclusion criteria are as follows: (1) Children who cannot cooperate with the examination after behavioral and psychological induction; (2) Children who are taking antibiotics or probiotics; and (3) Children who have not been examined and lack dental examinations or anthropometric data.

As part of a large study involving 1864 children, 40 children were randomly divided into the following groups after clinical examination for the diagnosis of dental caries and obesity: 1) HC + obese (n = 10), 2) CF + obese (n = 10), 3) HC + NO (n = 10), 4) CF + NO (n = 10), saliva and stool samples were collected.

Questionnaire

A questionnaire was distributed to the parents of all the subjects. The questionnaire is about diet; biscuits, cakes, candy, chocolate, carbonated drinks, fruit juice intake frequency; parents' education level; exercise frequency; and sedentary habits. After the questionnaire is collected, the quality inspection will be carried out by the auditor, and all the inspection and questionnaire results will be inputted into the computer to establish a database for data statistical processing and analysis.

Oral Examination

Caries scores (dmfs [decayed, missing, or filled surfaces]) were reported according to World Health Organization (WHO) criteria[16], teeth are cleaned and dried with gauze, and dental caries are diagnosed under head-mounted lights[17]. The examiners were calibrated to achieve a statistically significant correlation among the examiners on the diagnostic criteria of dental caries (Kappa value was 0.875, p < 0.05).

Anthropometric Measures

The height and weight of all subjects were measured and recorded using the same weight meter. These height and weight data are used to calculate BMI (BMI = weight [kg] / height [m²]). All subjects were classified according to body mass index, including underweight (mean < 18.5 kg/m²), normal weight (18.5–24.9 kg/m²), overweight (25.0-29.9 kg/m²) and obesity (≥ 30 kg/m²)[18].

Saliva Collection

Non-stimulating saliva collection should be performed at school, at least 1 hour after oral hygiene. The participants sat comfortably in a chair, tilted their heads slightly forward, allowed the saliva that had accumulated at the bottom of the mouth to drip into a previously weighed tube. The samples were transported to the laboratory on the same day and stored at -80 ° C for analysis.

Stool Sample Collection

Labeled general-purpose plastic containers for fecal sample collection in children’ own homes. Written instructions were given to their guardians to make sure the feces didn't come into contact with the inside of the toilet. The samples were refrigerated in sealed plastic bags in the domestic refrigerator for no more than 12 hours, and the fecal samples were immediately placed in the freezer after being brought to school. The samples were transported to the laboratory on the same day and stored at -80 ° C for analysis.

RNA- sequence

Saliva and feces are frozen with liquid nitrogen. The samples were stored in dry ice and shipped to GENEWIZ (Suzhou, China) for further analysis, including RNA extraction, rRNA removal, library preparation, Illumina sequencing, and data analysis. Trizol reagent was used for the extraction of total RNA, this was used to produce cDNA.Using 20-50ng DNA as a template, a series of PCR primers designed by the company were used to amplify two highly variable regions of prokaryotic 16s rDNA including V3 and V4. V3 and V4 regions were amplified by using upstream primers containing "CCTACGGRRBGCASCAGKVRVGAAT" sequence and downstream primers containing "GGACTACNVGGGTWTCTAATCC" sequence.The concentration of the library was detected by Tecan, Infinite 200Pro, and the original sequencing data (Pass Filter Data) was obtained by PE250/FE300 double-terminal sequencing according to the instructions of Illumina MiSeq/Novaseq (Illumina, San Diego, CA, USA). The forward and reverse reads obtained by double-terminal sequencing are spliced at first, filter the sequences containing N in the splicing results, and retain the sequences whose length is larger than 200bp. The 16s rRNA reference database is Silva 138. Then RDP classifier (Ribosomal Database Program) Bayesian algorithm is used to analyze the species taxonomy of the representative sequence of OTU, and the community composition of each sample is counted at different species classification levels.

Statistical Analysis

The data are compiled and input into an Excel database (Microsoft Office), and all data are processed by SPSS26.0 software. Descriptive analysis includes frequency and average (standard deviation). The chi-square test was used for multivariate analysis. The data of normal distribution were tested by the variance homogeneity test, and the data of non-normal distribution were tested by the Aspin-Welch variance heterogeneity test. Multiple linear regression was used to determine the relationship between different caries loss index and BMI. The difference was statistically significant (α = 0.05, P < 0.05). Kruskal-Wallis tests were used in comparison of relative abundance of top10 bacteria at genus level between groups.

Children with incomplete anthropometric or dental assessment data were excluded from the analysis. The missing information in the questionnaire was removed from the list. Among the 1864 children aged 7-12, 50.59% were boys (943) and 49.41% were girls (921) (Fig.1). The chi-square test was used to analyze the relationship between demographics and the prevalence of dental caries (Table 1).

There was no significant difference in the incidence of dental caries among primary teeth, permanent teeth, and mixed dentition between males and females (χ 2 were 0.58,1.21,0.14 respectively, P > 0.05). There were significant differences among different BMI groups and age groups (P < 0.05). The incidence of caries was about the same in different genders. In the BMI group, the incidence of caries of primary teeth and mixed dentition in overweight and obesity groups was lower, but that of permanent teeth was higher. The incidence of permanent teeth caries increases with age, and 21.36% of 12-year-old children have permanent teeth caries.

The relationship between related factors and the decayed-missing-filled index of primary teeth, permanent teeth, and mixed dentition is presented in Table 2. There were significant differences in dmft between groups with different dietary structures, frequency of consumption of cookies and cake, candy and chocolate, carbonated beverage and juice, parents' educational level, exercise frequency, and sedentary habit (P＜0.05). There was no significant difference in DMFT among groups with different frequencies of candy and chocolate intake (P＞0.05). Intake frequency of cookies and cakes, carbonated beverages and juice, parents' education level; exercise frequency; and sedentary habits were significantly correlated with DMFT (P＜0.05).

There were statistically significant differences in dmft and dmft+DMFT among different BMI groups (P<0.05), and dmft and dmft+DMFT decreased with the increase of BMI classification. There was no significant difference in DMFT among all groups (F=2.49, P> 0.05) (Table 3).

Multiple linear regression analysis was performed on dmft, DMFT, and dmft+DMFT (Table 4). Because of the high correlation between biscuit cake and candy chocolate intake frequency, they were not initially included in the same regression model to avoid multicollinearity.

The children with low BMI index and parents' educational level had significantly higher dmft(p=0.001, p＜0.001). Children with high cookie and cake, sugar drinks consumption frequency and high exercise frequency had significantly higher dmft (p＜0.001,p＜0.001,p=0.001). The results of Model 2 show that those with a high BMI index have significantly higher DMFT (p=0.004). The result of model 3 shows that the relationship between dmft+DMFT and each variable is the same as in model 1.

We randomly sampled 40 children and divided them into four groups:A0: high caries(HC)+obese(n=10),B1:Carries-free(CF)+obese(n=10),C2:HC+non obese(NO) (n=10), D3: CF+NO(n=10).

The results of 40 saliva samples and 40 stool samples showed that Firmicutes were more in the obese group than in the normal group, and Bacteroides were less. The relative abundance of salivary level showed that the content of Prevotella was the lowest and that of Streptococcus mutans was the highest in the obese caries group. The relative abundance of fecal genus level showed that Bacteroides was the highest in the normal group, Prevotella was the lowest in the caries group, Prevotella was the highest in the caries group, and Bacteroides were less in the obese and caries obese groups than in the normal group (Fig.2).

There was a statistically significant difference in the Simpson index of Alpha diversity in saliva samples (p=0.077), but no statistically significant difference in fecal samples (p=0.64). Anosim analysis showed no significant difference in saliva and fecal samples between groups (p=0.496, p=0.272). The five dominant bacteria in saliva and fecal samples were selected for intra-group comparison. The results showed that Prevotella was statistically different between the saliva and feces samples.

Stacked bar plots of relative abundances at the phylum level demonstrated differences in oral and gut microbiota among four groups (Fig. 2A). Firmicutes, Bacteroidota, Proteobacteria, Actinobacteriota and Fusobacteriota were predominant

phyla in saliva, and Firmicutes and Bacteroidetes were predominant phyla in feces of all groups. At the genus level, Prevotella，Streptococcus，Haemophilus，Neisseria，Veillonella were predominant in saliva; Bacteroides，Faecalibacterium，Bifidobacterium，Agathobacter，Prevotella were predominant in feces.

Analyses of alpha (a)-diversity demonstrated that there was a statistically significant difference (p < 0.05) in the chao1 index between the CF+Obese and HC+Obese groups, and between the CF+NO and HC+Obese groups in saliva samples.

In feces samples,there was a statistically significant difference (p < 0.05) in the shannon index between the CF+Obese and HC+Obese groups,and between the HC+NO and HC+Obese groups.(Fig. 3A).

PCoA was performed to assess beta (b)- diversity of the microbiota (Fig. 3B). Bray-Curtis distance matrix demonstrated has no statistical difference (p=0.473，p=0.25) in b-diversity of oral microbiota and gut microbiota among four groups (Fig. 3C).

we selected 10 genera which ranked at the top of the total genera and analyzed the predominant members in each group. Comparing the saliva relative abundance in each group, we found that Prevotella was present at a lower level in CF+NO than HC+NO and HC+Obese group (p< 0.05; p< 0.05)，Streptococcus was at a higher level in HC+NO than CF+NO and CF+Obese (p< 0.05; p< 0.05,Figure 4A). Among gut microbiota in each groups, Faecalibacterium in CF+NO was higher than CF+NO and CF+Obese (p< 0.01; p< 0.05). Bifidobacterium in CF+NO was lower than HC+NO and CF+Obese (p< 0.05; p< 0.05). Prevotella in HC+Obese was higher than CF+Obese and CF+NO (p< 0.05; p< 0.001), that in HC+NO was higher than CF+NO (p< 0.05, Figure 4B).

Source Tracker analysis explored the ectopic colonization of oral microbiota in the gut, showing one in HC+NO (No. 32) and one in CF+Obese (No.1) had a fraction of their gut microbiota which had originated from the oral cavity in Figure 5.

The purpose of this study was to identify common risk factors that could help reduce the prevalence of dental caries and obesity among children aged 7 to 12 years in Jinzhou City, China. Our findings align with previous research indicating that dental caries is associated with dietary habits, parental education, BMI, and exercise frequency[19–22], all of which are also recognized risk factors for obesity[23, 24]. However, the relationship between dental caries and the BMI of primary and permanent teeth was inconsistent in our study. Notably, we observed that the prevalence of primary dental caries was inversely related to high BMI, a finding consistent with Alkarimi et al[25]. This inverse relationship may be attributed to untreated primary caries, which can lead to severe pain and discomfort in children, consequently reducing their food intake. Furthermore, other symptoms associated with caries, such as infection, irritability, and disrupted sleep patterns, can adversely affect children's quality of life and growth[26]. Conversely, we found that the prevalence of permanent dental caries was positively correlated with high BMI, consistent with the findings of Paisi et al[27]. This association may arise from a decrease in parental control over eating and oral health habits as children grow older, coupled with an increase in sedentary lifestyles and unhealthy dietary practices that are more prevalent among older children[28]. Additionally, our study indicated that caries experience was positively correlated with the frequency of consumption of cookies, cakes, and sugary drinks. Moreover, the consumption of sugary foods and drinks may displace the intake of nutritious options, further contributing to dental caries and undernutrition[29, 30]. It is important to note that overweight and obesity are forms of malnutrition that can coexist with micronutrient deficiencies[31].

The prevalence of dental caries is inversely related to the educational attainment of parents. This relationship may be attributed to the Chinese government's initiatives promoting oral health education among children in preschool, primary, and middle schools, as well as the implementation of effective measures such as topical fluoridation and pit and fissure sealing [32]. Increased awareness of oral health care among parents has contributed to a decline in the incidence of caries in children. Furthermore, there exists a macro-level correlation between caries and obesity [6, 7, 33]. However, there is a paucity of studies investigating the relationship between oral cariogenic bacteria and gut microbiota at the microscopic level. In this study, we present a comprehensive analysis of the oral and gut microbiota associated with caries and obesity, utilizing 16S rDNA sequencing. Our findings indicate differences in the diversity and composition of oral and gut microbiota between the two conditions. Notably, among the oral species transmitted to the gut, prevotella appears to play a crucial role in both diseases. The microbial composition of saliva samples from the four study groups exhibited similarities; however, statistical differences (p < 0.05) were observed with respect to prevotella and streptococcus. Previous research has established a strong association between streptococcus and prevotella with caries, these taxa are considered core components of the oral microbiome [34]. Our findings align with earlier studies, which demonstrated that alpha diversity is higher in caries-free individuals compared to those with active caries[35].

Our findings indicate that the fecal microbiota of obese individuals exhibits lower alpha diversity, as measured by the Shannon index, compared to non-obese individuals. This observation aligns with previous research, which also demonstrated that, at the genus level, a higher relative abundance of gut prevotella is present in obese individuals compared to their non-obese counterparts [36]. However, we observed that the relative abundance of prevotella in the gut of the high caries + obese group was greater than that in the caries-free + obese group. Several potential explanations for this discrepancy can be proposed: prevotella-rich microbiomes in obese individuals are linked to insulin resistance through the production of branched-chain amino acids[37]; and obesity is characterized as a chronic low-grade inflammatory condition, marked by elevated circulating pro-inflammatory cytokines, which may be sustained by microbiomes dominated by pro-inflammatory prevotella bacteria[38]. Furthermore, prevotella from the oral cavity of the high caries + obese group may migrate to the intestine during the digestive process, potentially exacerbating the already disrupted intestinal microenvironment.

We acknowledge several limitations in our study, we did not trace the Prevotella bacteria from the oral cavity to the intestine, making it insufficient to conclude that there is ectopic colonization of gut prevotella originating from the oral microbiome. Therefore, further experimental verification is warranted.

Dietary factors, particularly the consumption of sugary foods, along with exercise frequency, sedentary behaviors, and parental educational levels, are recognized as common risk factors for caries and obesity. Notably, the prevalence of caries in primary teeth is inversely correlated with BMI, whereas the rate of caries in permanent teeth is directly proportional to BMI.16s rDNA sequencing results revealed differences in the oral and gut microbiota associated with caries and obesity, suggesting that prevotella may act as a co-pathogenic bacterium in the development of both conditions.

Author Contributions

CYW and BRC contributed to conception and design, analysis and interpretation, drafted and critically revised the manuscript. XPY, WY, NM, MW, YML and MHB contributed to data acquisition and critically revised the manuscript. All authors gave their final approval and agree to be accountable for all aspects of the work.

Acknowledgments

We appreciate the students who participated in the surveys for their cooperation and the examination equipment provided by the Stomatology Hospital Affiliated of Jinzhou Medical University.

Funding

This work was funded by the Collaborative Innovation Center for Health Promotion of Children and Adolescents of Jinzhou Medical University；National Natural Science Foundation of China (U21A2074)；the National Natural Science Foundation of China (62375115)；Applied Basic Research Program of Liaoning Province (2022JH2/101300033)；the Applied Basic Research Program of Liaoning Province (2023JH2/101700071).

Ethical approval and consent to participate

The study approval was provided by the Ethics Committee of Stomatology Hospital Affiliated of Jinzhou Medical University (JYFELL202404), which was fully in line with the Helsinki Declaration of the World Medical Association. Written informed consent was obtained from adolescent’s legal guardians.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

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Table 1 to 4 are available in the Supplementary Files section.

No competing interests reported.

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Caries and obesity: A cross-sectional study of populations and microbiology

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Version 1

Abstract

Figures

Introduction

Methods

Study Design, Sample Selection, and Study Population

Questionnaire

Oral Examination

Anthropometric Measures

Saliva Collection

Stool Sample Collection

RNA- sequence

Statistical Analysis

Results

Discussion

Conclusions

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1