Effects of water flossing on gingival inflammation and supragingival plaque microbiota: a 12-week randomized controlled trial (2024)

Study participants

This article is reported according to CONSORT guidelines for reporting randomized clinical trials. This study was approved by the Research Ethics Committee of West China Hospital of Stomatology (WCHSIRB-D-2020-309) and was in agreement with the Declaration of Helsinki and complied with Chinese Good Clinical Practice (GCP) regulations. All participants were recruited at the West China Hospital of Stomatology, Sichuan University, and signed informed consent. The trial was registered in the Chinese Clinical Trial Registry (http://www.chictr.org.cn/showprojen.aspx?proj=61797, #ChiCTR2000038508) on September 23, 2020.

The participants were aged 18–65years with no systemic diseases. All participants had intact Ramfjord teeth (16, 21, 24, 36, 41, 44) in the oral cavity. Participants had gingivitis, with a modified gingival index ≥ 1, dental plaque index ≥ 1.5, and gingival sulcus depth < 3mm [33]. Participants were excluded if they had periodontitis, had undergone surgical/non-surgical periodontal therapy or antibacterial/hormonal drug therapy in the last 6weeks, had participated in other clinical trials within the last 3months, had an allergic constitution, or were pregnant [34].

Experimental design

This was a single-center, randomized controlled clinical trial with a duration of 14weeks (2-week washout and 12-week treatment phase) (Fig.1). The washout phase was introduced to normalize the oral hygiene habits of participants as also suggested by Sreenivasan et al. [35]. Participants who met the inclusion and exclusion criteria were recruited in the 2-week washout phase, and were instructed to brush their teeth with Bass brushing technique twice daily for 3min using Crest herbal crystal toothpaste and a Crest triple care toothbrush (P&G Technology Co., Ltd., Beijing, China). Participants were asked not to use antibiotics/hormonal drug and have periodontal therapy during the washout phase. These participants were re-screened according to the inclusion and exclusion criteria at baseline, and then were enrolled in the 12-week treatment phase.

The sample size was calculated using G*Power 3.1 software and was based on the primary data of gingival bleeding. Based on inequality and two independent groups (Fisher’s exact test), the sample size was determined to be 60, with an 0.05 alpha level (type II error) and 90% power (type I error). Considering a 15% dropout rate, 70 participants were eventually enrolled in this study.

The participants were randomly allocated to two groups (n = 35/group) using a computer-generated randomization list. The control group only brushed their teeth with Bass brushing technique twice daily for 3min using abovementioned toothbrush and toothpaste, but the experimental group was additionally instructed to use a Bixdo P50 water flosser (Bixdo SH Healthcare Technology Co., Ltd., Shanghai, China) to irrigate all the teeth in the oral cavity with water for 3min immediately after toothbrushing. Participants were recalled at 4, 8, and 12weeks, and their modified gingival index, sulcus bleeding index, bleeding on probing (BOP), dental plaque index, and oral malodor values were determined. Supragingival plaque samples were also collected. Participants were asked to refrain from brushing, flossing, eating, and drinking anything other than water for 4h prior to sample collection visits. The names and groups of the participants were covered for blinding to those collecting samples or clinical assessments. Over the experimental period, participants received weekly oral hygiene instruction and supervised plaque removal using the devices assigned for each group.

Periodontal examination and supragingival plaque collection

Periodontal examination was performed by an operator, previously trained until reaching a low intra-operator variability, using an UNC-15 periodontal probe with a controlled (ca. 0.25 N) force. The gingival sulcus depth (distance from the gingival margin to the bottom of the gingival sulcus, evaluated at each tooth surface, for all teeth), modified Loe–Silness gingival index (assessment of gingival color, texture, and bleeding tendency, evaluated at four specific sites of each tooth), sulcus bleeding index (assessment of gingival bleeding, with a score of 0–5 per site), BOP (recorded based on the presence or absence of bleeding up to 20s after probing at the experimental sites), and dental plaque index (evaluation of the presence of plaque, with a score of 0–5 per site) were measured [36]. After drying saliva off the collection site, supragingival plaque samples were collected from facial and lingual sites of all six Ramfjord teeth of each subject, by using a sterile curette. Scraped plaque was immediately transferred to and dispersed in 1 × phosphate-buffered saline in a sterile microcentrifuge tube. The plaque sample was divided into three parts after vibration and stored at − 80°C until analysis.

Oral malodor measurement using a halimeter

Oral malodor values were measured using a halimeter (RH-17K; Interscan Co., Chatsworth, CA). Subjects refrained from any oral activity, such as food intake, for at least 2h pre-measurement. The subjects were instructed to close their mouths for 3min (using only nasal breathing) before every measurement, followed by placing a straw, connected to the halimeter, 4-cm deep into their mouth. The measurement was performed automatically, and the mean value of three consecutive measurements was used for analysis [37].

16S rRNA sequencing

Barcoded 16S rRNA amplicon (V3–V4 regions) sequencing was performed using Illumina MiSeq technology (Personalbio, Shanghai, China) and primers F (5′-ACTCCTACGGGAGGCAGCA-3′) and R (5′-TCGGACTACHVGGGTWTCTAAT-3′). A unique 12-mer tag for each DNA sample was added to the 5′-end of both primers to allow pooling of multiple samples in one run. The PCR products were visualized on a 3% agarose gel, gel purified, quantified with a Pico-Green kit, pooled in an equimolar ratio, assessed using an Agilent BioAnalyzer 2100 (Invitrogen, Carlsbad, CA), and sequenced. Sequences were trimmed using Trimmomatic 2 based on a quality score of 20, and pair-end reads were merged into longer reads using FLASH 3. Unqualified sequences were removed if they were too short or if they contained ambiguous residues. Operational taxonomic units (OTUs) were clustered using Usearch (version 7.1, http://drive5.com/uparse/) at a 97% similarity level. The final OTUs were generated based on clustering results. The raw sequencing data were deposited in the public database Sequence Read Archive (http://www.ncbi.nlm.nih.gov/Traces/sra) with accession no. PRJNA861384.

Before bioinformatic analysis, sequencing reads of all samples were standardized by rarefying OTU tables to the minimum read number. Analyses were performed using the online Majorbio Cloud Platform (www.majorbio.com) [38]. The Kruskal–Wallis H and Wilcoxon rank-sum tests were used to compare differences in taxa. Alpha diversity was calculated in terms of Chao, Shannon, and Simpson indices and was compared using the Wilcoxon rank-sum test. Beta diversity was assessed by principal coordinate analysis (PCoA) or non-metric multidimensional scaling (NMDS) analysis using weighted-unifrac distance and Adonis with 999 permutations. Analysis of similarity values and heatmaps were constructed using R (version 3.3.1; https://www.r-project.org/) “vegan” (version 2.4–3) package. Linear discriminant analysis (LDA) of the effect size (LEfSe) was performed to identify the significant taxa that most likely explained the differences between groups, with a threshold LDA score of 2. Bugbase was used for the predictions of the functional profile of a microbial community based on 16S rDNA sequence data. BugBase is able to predict seven phenotype types, including gram-positive, gram-negative, biofilm forming, pathogenic, mobile element containing, oxygen utilizing, and oxidative stress tolerant. A p value of < 0.05 was considered statistically significant in the current study.

Bacterial quantification

Quantitative polymerase chain reaction (qPCR) was used to quantify dental plaque bacteria. qPCR amplification was performed using the CFX96 system (Bio-Rad, Hercules, CA). The 25-μl reaction mixture contained the SYBR reaction mix (TaKaRa, Kusatsu, Japan), template DNA (100ng), and forward and reverse primers (500nM each). Thermal cycling conditions were as follows: initial denaturation at 95°C for 30s, followed by 40 cycles each consisting of 95°C for 15s, and 60°C for 30s. Threshold cycle (CT) values were determined, and the relative abundance was calculated based on the 2^−ΔΔCT method. Porphyromonas gingivalis, Fusobacterium nucleatum, Actinobacillus actinomycetemcomitans, and Prevotella intermedia were quantified using primers listed in Table S1. Each sample was examined in triplicate.

Statistical analysis

Statistical analysis of data other than 16S rRNA sequencing was performed using SPSS software (version 16.0; SPSS Inc., Chicago, IL) and GraphPad Prism 8 (GraphPad Software Inc., La Jolla, CA). Categorical variables are presented as natural frequencies, and continuous variables as mean ± standard deviation. The clinical characteristics of the participants were analyzed using Kruskal–Wallis (with Dunn–Bonferroni post hoc) or chi-squared tests. Within-group and between-group differences in gingival, sulcus bleeding, and dental plaque indices, BOP%, and oral malodor values were analyzed by repeated measure (RM) ANOVA, followed by Bonferroni post hoc tests and Student’s t tests, respectively. Other data were analyzed using one-way ANOVA, followed by Tukey’s test or the Student–Newman–Keuls test to compare all pairs of groups. Data were considered significantly different if the two-tailed p value was < 0.05.

Clinical characteristics of the study participants

This study enrolled 70 gingivitis participants, of which seven dropped out, who missed the recall time due to closed management amid COVID-19 outbreak. Thirty-three control and 30 experimental participants attended all recall visits. The baseline clinical characteristics are shown in Table ​Table1.1. Demographics, gingival, and halitosis parameters were similar between the groups (p > 0.05). No adverse reaction including gingival recession reported during the 12-week experimental period in terms of water flossing.

Effects of water flossing on clinical parameters

The effects of water flossing on periodontal parameters, dental plaque index, and oral malodor were assessed. Two-way RM-ANOVA identified time and group as statistically significant factors (p < 0.05) in the gingival index, sulcus bleeding index, and BOP% (Table ​(Table2).2). These indices improved significantly in both groups at all observation time points (weeks 4, 8, 12) compared with baseline (p < 0.05). However, the improvement in the control group slowed after 4weeks. Gingival index and sulcus bleeding index at weeks 8 and 12 were significantly better in the experimental than in the control group, and BOP% improved significantly in the experimental group at weeks 8 as compared with the control group (Table ​(Table2).2). These results suggest that water flossing had a good clinical effect on managing gingival bleeding and inflammation.

Two-way RM-ANOVA of the dental plaque index identified time as a statistically significant factor (p < 0.05), with significant differences among time points (Table ​(Table2).2). However, the control and experimental groups did not differ at any time point (Table ​(Table2).2). There was no significant difference in the oral malodor values between groups after the use of the respective oral hygiene regimens (Table ​(Table2).2). However, the value was significantly decreased after 12-week water flossing as compared with that at baseline in the experimental group (Table ​(Table22).

Effects of water flossing on dental plaque microbiota

The 16S rRNA sequencing data are detailed in the supplementary information (Fig. S1). In total, 20.71 million high-quality 16S rRNA sequences were generated from the supragingival plaque samples of 33 control and 30 experimental participants at 0, 4, 8, and 12weeks (length range 408–480bp, average length 464.36bp). After subsampling each sample to equal sequencing depth and clustering, 6442 OTUs with 97% identity were obtained. Good’s coverage for the observed OTUs was 99.72 ± 0.09%, and the rarefaction curves showed clear asymptotes, which together indicated a near-complete sampling of the community.

The α and β diversity of the baseline dental plaque samples showed no significant difference between the two groups, suggesting that the baseline dental plaque microbiota structure of the two groups was comparable (Fig. S2A and B). Although the PCoA analysis showed no significant difference in the microbiota community structure between the groups, the p value approximated 0.05 (p = 0.056). NMDS analysis revealed a significant difference between the groups (p = 0.012) (Fig. S2C). PCoA and NMDS analyses demonstrated significant differences between the control and experimental groups at week 12 (PCoA: p = 0.038, NMDS: p = 0.029), and samples could be clearly distinguished and clustered into two groups (Fig.2A). These results indicate that, after 12weeks, the dental plaque microbiota of the two groups were distinct, suggesting that water flossing changed the microbial structure.

See Also

ION Professional Cordless Water Flosser by Waterpik™

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Fig. 2

Comparison of the microbiota community structure and composition between the control and water flossing group. A Principal coordinate analysis (PCoA) and non-metric multidimensional scaling (NMDS) analysis of the dental plaque samples from control and experimental groups at week 12. B Heatmap analysis of the top 30 abundant bacterial taxa at genus level. C Linear discriminant analysis of the effect size (LEfSe) analysis at week 12. D Intergroup difference analysis of the top 15 abundant bacterial taxa at genus level at baseline. E Intergroup difference analysis of the top 15 abundant bacterial taxa at genus level at week 12. F Relative quantification of Porphyromonas gingivalis, Fusobacterium nucleatum, Actinobacillus actinomycetemcomitans, and Prevotella intermedia at weeks 4 and 12 as compared to baseline. *p < 0.05, **p < 0.01

Further analysis of the top 30 abundant bacterial taxa revealed genus-level differences between the control and water-flossing groups (Fig.2B). The abundance of Aggregatibacter, Porphyromonas, Prevotella, and Fusobacterium increased over time in the control, but not in the experimental group (Fig.2B). There was no significant difference in the top 15 most abundant bacterial taxa between groups at baseline (Fig.2D). However, after 12weeks, the water-flossing group exhibited significantly lower Prevotella and higher Corynebacterium genus as compared with the control group (Fig.2C, E). qPCR showed no difference in the relative abundance of Porphyromonas gingivalis, F. nucleatum, and A. actinomycetemcomitans between the groups at weeks 4 or 12, as compared to baseline, but the abundance of Prevotella intermedia in the experimental group was significantly lower at week 12 than week 4 or that in the control group at week 12 (Fig.2F).

The BugBase phenotype prediction showed no significant difference in the seven metabolic phenotypes between the control and experimental groups at baseline (Fig.3A). At week 4, the water-flossing group exhibited significantly higher aerobic phenotype, while the control group exhibited significantly higher anaerobic and gram-negative phenotypes (Fig.3B). At week 12, the water-flossing group still exhibited significantly higher aerobic phenotype, while the control group exhibited significantly higher anaerobic phenotype (Fig.3C). These data further suggest that water flossing may benefit periodontal health by altering the microbial composition and reducing the virulence of the dental plaque.

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Fig. 3

Phenotype prediction of the dental plaque community. A. BugBase phenotype prediction of the control and experimental groups at baseline. B. BugBase phenotype prediction of the control and experimental groups at week 4. C. BugBase phenotype prediction of the control and experimental group at week 12. *p < 0.05, **p < 0.01

Below is the link to the electronic supplementary material.

Competing interests

XX reports grants from Bixdo SH Healthcare Technology Co., Ltd., Shanghai, China, during the conduct of the study. XC reports grants from Science and Technology Bureau of Chengdu, China, during the conduct of the study. YL reports three patents licensed. The authors YZ, CL, LZ, LZ, and HL declare no conflict of interest regarding this work.

Ethics statement

This study was approved by the Research Ethics Committee of West China Hospital of Stomatology (WCHSIRB-D-2020-309). The study procedures were conducted in accordance with the principles outlined in the Declaration of Helsinki and complied with the laws and regulations covering Good Clinical Practice (GCP) in China. All participants provided written informed consent.

Conflict of interest

XX reports grants from Bixdo SH Healthcare Technology Co., Ltd., Shanghai, China, during the conduct of the study. XC reports grants from Science and Technology Bureau of Chengdu, China, during the conduct of the study. YL reports three patents licensed. The authors YZ, CL, LZ, LZ, and HL declare no conflict of interest regarding this work.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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