Interrelationships between sociodemographic factors, oral health knowledge, behaviours, and caries experience among adults with visual impairment: A cross-sectional study

Interrelationships between sociodemographic factors, oral health knowledge, behaviours, and caries experience among adults with visual impairment: A cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Interrelationships between sociodemographic factors, oral health knowledge, behaviours, and caries experience among adults with visual impairment: A cross-sectional study Aisyah Ahmad Fisal, Seong Jin Shiu, Alias Abd Aziz, Mohamad Adam Bujang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8170573/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: Adults with visual impairment (AVI) face distinct challenges in maintaining oral health, yet evidence from Malaysia is limited. This study examined the sociodemographic factors associated with oral health knowledge, behaviours, and caries experience, and explored the interrelationships among these outcomes. Methods: A cross-sectional study was conducted at the Malaysian Association for the Blind during two outreach programmes (14 January 2023; 27 January 2024). Oral health knowledge was assessed using the 11-item Malay Health Promotion Questionnaire Index (HPQI). Oral health behaviours and sociodemographic data were self-reported. Caries experience was recorded using the Decayed, Missing, and Filled Teeth (DMFT) index. Descriptive analyses, non-parametric tests, and χ²/Fisher's tests examined associations. Logistic regression was used to model factors associated with oral health knowledge and DMFT. Results: Seventy-five unique participants (mean age 29.6 ± 10.5 years; 64% male) were included. The mean knowledge score was 8.9 ± 2.4, with 74.5% categorised as having good knowledge. Most participants brushed twice or more daily (85.3%) and used toothpaste at least twice daily (86.7%), though one-third reported never flossing. The mean DMFT was 3.48 ± 3.91, driven primarily by missing teeth (40.2%). In bivariate analyses, higher knowledge scores were associated with recent dental attendance, toothpaste use, and flossing frequency (p < 0.05). DMFT correlated strongly with age (p < 0.001). In adjusted models, age (OR = 1.06, p = 0.006), race (OR = 0.14, p < 0.05), and recent dental attendance (OR = 9.64, p = 0.01) were significantly associated with higher knowledge scores. For caries experience, age remained significantly associated with higher DMFT (OR = 1.056, p = 0.001). Conclusion: Despite moderate-to-good oral health knowledge and self-reported behaviours, caries experience remained high among Malaysian AVI. The disconnect between awareness, behaviour, and clinical outcomes underscores that education alone is insufficient. Interventions should integrate accessible, skill-based oral hygiene support and improved preventive and restorative care access. Vision Disorders Oral Health Dental Caries Health Knowledge Attitudes Practice Figures Figure 1 1. Background Vision impairment makes up one of the common global disability categories. Estimates of global vision impairment in 2020 put a figure of 43.3 million, 295 million, and 258 million of people who were blind, having moderate to severe vision impairment, and mild vision impairment respectively. Around 55% of the population with visual impairment were estimated to be female 1 . In adults with vision impairment (AVI) aged 50 years and older, the leading causes of blindness included cataract, glaucoma, undercorrected refractive error, age-related macular degeneration, and diabetic retinopathy 2 , 3 . With 160.7 million of AVI being in the working age bracket, vision impairment is associated with profound economic impact with an overall relative reduction in employment of 30.2% and annual cost of potential productivity loss between $ 408.5 billion to $ 410.7 billion 4 – 6 . Besides experiencing socioeconomic disadvantage, AVI are disproportionately affected by poor oral health. Globally, untreated dental caries remains one of the most prevalent health conditions, affecting an estimated 2.5 billion people, while severe periodontal disease affects nearly one billion adults 7 . These burdens fall disproportionately on low- and middle-income countries, where access to preventive and restorative care remains limited. Research focusing specifically on individuals with visual impairment consistently report higher rates of caries, periodontal disease, and poorer oral hygiene compared to sighted populations. For example, cross-sectional studies from Iran, Hong Kong, Ethiopia, and Jordan have shown that children, adolescents, and adults with visual impairment have significantly higher DMFT scores, greater plaque accumulation, and more dental trauma than their sighted peers 8 – 11 . Maintaining good oral health presents unique challenges for AVI. Visual impairment limits the ability to detect early signs of dental disease, monitor oral hygiene effectiveness, or identify plaque accumulation. Some individuals may rely on caregivers for daily activities, including brushing and flossing, which can lead to inconsistent oral hygiene depending on caregiver availability and skill 12 . In addition, oral health information is often delivered through visual formats (posters, leaflets, videos), making awareness campaigns less accessible to AVI unless specifically adapted into tactile, audio, or screen-reader-compatible forms 13 . These factors combined with socioeconomic barriers and reduced access to dental services may contribute to a higher oral disease burden within this population. This study aimed to describe the oral health knowledge, behaviours, and caries experience of Malaysian AVI, and to examine demographic and behavioural correlates and interrelationships among these outcomes. 2. Methods 2.1 Study design and eligibility criteria This cross-sectional study was conducted at the Malaysian Association for the Blind (MAB), a non-profit organisation providing rehabilitation and vocational training for individuals with visual impairment. Data were obtained during two community outreach programmes at the Gurney Training Centre on 14 January 2023 and 27 January 2024. Eligible participants were trainees and trainers with visual impairment classified under B1, B2, or B3 categories. Individuals were required to be enrolled at MAB, able to independently provide informed consent, and able to understand Malay. Trainers without visual impairment and individuals absent on survey days were excluded.The reporting of this study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines 14 . 2.2 Sampling strategy and sample size calculation Convenience sampling was employed, whereby all trainees and trainers present at MAB during the two survey dates were approached for participation. Across both data collection rounds, participation rates exceeded 80%. A small subset of individuals attended both sessions; to ensure independence of observations, duplicate attendees were identified and only their most recent record was retained for analysis. Given the finite population of trainees and trainers available during the outreach events, the study aimed to recruit as many eligible individuals as possible. Using finite population correction, this target sample was expected to provide approximately ± 5% precision for prevalence estimates at a 95% confidence level, which was deemed sufficient for exploratory analyses. The final number of participants included in the analysis is reported in the Results section. 2.3 Instruments Oral health knowledge was assessed using the knowledge domain (11 items) of the Health Promotion Questionnaire Index (HPQI) in Malay, which was originally validated among Malaysian schoolchildren 15 . Each statement endorsed as "agree" or "strongly agree" was scored as 1, while "disagree," "strongly disagree," or "not sure" scores were marked as 0, resulting in a total Knowledge Score ranging from 0 to 11 (higher scores indicate better knowledge). Knowledge Scores were categorised using Bloom’s cut-off criteria 16 : good (9–11 points, 80–100%), moderate (7–8 points, 60–79%), and poor (0–6 points, < 60%). For further analysis, knowledge levels were grouped into two categories: poor to moderate and good. Oral health behaviours were assessed separately using seven self-reported items: frequency of toothbrushing, toothpaste usage, flossing frequency, mouth rinsing after meals, smoking status, dental attendance, and assistance with toothbrushing. These items were analysed individually as behavioural indicators and not as part of the HPQI scale. Sociodemographic data, including age, gender, ethnicity, education level, and degree of visual impairment, were also collected. Questionnaires were administered by trained interviewers who read aloud each question in Malay, and responses were recorded with participant confirmation. 2.4 Clinical examination Clinical examinations were conducted on-site by two dental postgraduate students. The decayed, missing, and filled teeth (DMFT) index was recorded in accordance with World Health Organization (WHO) criteria 17 . Although no formal inter-examiner calibration was performed, both examiners had previously completed a caries detection workshop based on the International Caries Detection and Assessment System (ICDAS), focusing on standardised charting of caries. To minimise variability, both examiners adhered to the same examination protocol and drew upon their postgraduate clinical training. Participants received oral health education and a topical fluoride varnish application after the examination. DMFT scores were categorised into two groups: low to moderate (0–4.4) and high to very high (4.5 and above) following the WHO severity categorisation. Efforts were made to minimise potential sources of bias. Although no formal examiner calibration was conducted, both examiners had undergone ICDAS-based training and followed a standardised examination protocol to reduce measurement variability. For questionnaire items, interviewer administration was used to minimise misinterpretation, especially for participants requiring assistance. 2.5 Statistical analysis Data analysis included descriptive statistics to summarise participant characteristics and variable distributions, followed by inferential analyses examining associations between sociodemographic factors, oral health behaviours, oral health knowledge, and DMFT. As convenience sampling was used and all eligible individuals were invited, no sampling weights or cluster adjustments were applied. Normality of continuous variables (knowledge score and DMFT) was assessed using the Shapiro–Wilk test to guide the selection of appropriate statistical tests. Associations between categorical variables were evaluated using chi-square or Fisher’s exact tests, while non-parametric tests (Mann–Whitney U) were used for continuous variables. Statistical significance was set at p < 0.05. DMFT was analysed in two ways. First, it was treated as a continuous count variable for descriptive and bivariate correlation analyses. Second, for multivariable modelling, DMFT was categorised into low–moderate and high–very high severity, and entered into a logistic regression model. Factors associated with oral health knowledge and DMFT were identified using multivariable logistic regression with stepwise variable selection to remove non-significant predictors (p < 0.05). Adjusted results are reported as odds ratios (ORs) with 95% confidence intervals. Covariates considered for inclusion were age, gender, ethnicity, education level, degree of visual impairment, and dental attendance. All analyses were conducted using IBM SPSS Statistics (version 28.0; IBM Corp., Armonk, NY, USA). There were no missing data in the dataset, and no sensitivity or subgroup analyses were conducted due to the exploratory nature of the study and the limited sample size within demographic strata. 3. Results A total of 100 individuals were invited to participate across both survey periods. Eighty-six took part (49 in 2023; 37 in 2024), and 11 attended both sessions. After removing duplicate participants and retaining the most recent record, 75 unique individuals were included in the final analysis. The participant flow is summarised in Fig. 1 . The mean age was 29.6 ± 10.5 years, with 64% male. Table 1 presents the distribution of sociodemographic characteristics across different levels of visual impairment (B1, B2, B3). The analysis revealed no statistically significant differences in age category (p = 0.208), gender (p = 0.236), race (p = 0.546), presence of comorbidities (p = 0.256), education level (p = 0.065), or monthly income (p = 0.615) across the three visual impairment groups. This suggests that the severity of visual impairment among participants was not associated with their sociodemographic background. Table 1 Sociodemographic across the level of visual impairment Variables Overall Level of Visual Impairment p-value B1 B2 B3 n (%) 75 (100.0) n (%) 37 (49.3) n (%) 22 (29.3) n (%) 16 (21.3) Age Category 18 to 30 47 (62.7) 22 (46.8) 12 (25.5) 13 (27.7) 0.208 Above 30 28 (37.3) 15 (53.6) 10 (25.7) 3 (10.7) Gender Male 48 (64.0) 27 (56.3) 13 (27.1) 8 (16.7) 0.236 Female 27 (36.0) 10 (37.0) 9 (33.3) 8 (29.6) Race Malay 53 (70.7) 24 (45.3) 17 (32.1) 12 (22.6) 0.546 Non-Malay 22 (29.3) 13 (59.1) 5 (22.7) 4 (18.2) Health Problem None 54 (72.0) 26 (48.1) 14 (25.9) 14 (25.9) 0.256 Has comorbidities 21 (28.0) 11 (52.4) 8 (38.1) 2 (9.5) Education Below Tertiary 54 (72.0) 28 (51.9) 12 (22.2) 14 (25.9) 0.065 Tertiary 21 (28.0) 9 (42.9) 10 (47.6) 2 (9.5) Monthly Income No Income 56 (74.7) 26 (46.4) 18 (32.1) 12 (21.4) 0.615 < RM 4,999 19 (25.3) 11 (57.8) 4 (21.1) 4 (21.1) Chi-square test: * indicates p-value < 0.05. The mean oral health knowledge score was 8.9 (SD 2.4; median 10; range 0–11). Table 2 explores the relationship between sociodemographic factors and oral health knowledge levels. Significant associations were observed for age and race. Participants aged above 30 years demonstrated significantly better oral health knowledge compared to those aged 18 to 30 years (p = 0.044). Additionally, Malay participants exhibited higher levels of oral health knowledge than non-Malay participants (p = 0.046). These findings indicate that older age and Malay ethnicity are positively associated with oral health knowledge. Table 2 Relationship between sociodemographic with level of knowledge on oral health Variable Overall Level of Knowledge on Oral Health p-value Poor Moderate Good n (%) 75 (100.0) n (%) 12 (16.0) n (%) 7 (9.30) n (%) 56 (74.7) Level of Visual Impairment B1 37 (49.3) 5 (13.5) 4 (10.8) 28 (75.7) 0.425 B2 22 (29.3) 6 (27.3) 1 (4.5) 15 (68.2) B3 16 (21.3) 1 (6.3) 2 (12.5) 13 (81.3) Age Category 18 to 30 47 (62.7) 9 (19.1) 7 (14.9) 31 (66.0) 0.044* Above 30 28 (37.3) 3 (10.7) 0 (0.0) 25 (89.3) Gender Male 48 (64.0) 10 (20.8) 5 (10.4) 33 (68.8) 0.254 Female 27 (36.0) 2 (7.4) 2 (7.4) 23 (85.2) Race Malay 53 (70.7) 5 (9.4) 6 (11.3) 42 (79.2) 0.046* Non Malay 22 (29.3) 7 (31.8) 1 (4.5) 14 (63.6) Education level Below Tertiary 54 (72.0) 10 (18.5) 5 (9.3) 39 (72.2) 0.631 Tertiary 21 (28.0) 2 (9.5) 2 (9.5) 17 (81.0) Monthly Income No Income 56 (74.7) 9 (16.1) 6 (10.7) 41 (73.2) 0.773 < RM 4,999 19 (25.3) 3 (15.8) 1 (5.3) 15 (78.9) Chi-square test: * indicates p-value < 0.05. The mean DMFT was 3.48 (SD 3.91; median 2.0; range 0–15). Missing teeth (M) contributed the largest share of the total DMFT burden (40.2%), followed by filled (34.9%) and decayed teeth (24.9%). While restorations (F) were the most prevalent (42.7% of participants), missing teeth contributed more heavily due to their higher average per affected participant (3.62 teeth). Based on WHO categories, 30.7% had no caries experience, and 17.3% each were classified as low or high severity. Shapiro–Wilk tests indicated that DMFT and knowledge score were not normally distributed, so non-parametric correlation and group comparison tests were used. Table 3 examines the relationship between sociodemographic variables and total DMFT scores. Age was significantly associated with DMFT scores, where participants aged above 30 years had higher mean DMFT scores (6.32 ± 4.30) compared to younger participants (1.79 ± 2.42), with a p-value of 0.001. Monthly income also showed a significant association; individuals earning less than RM 4,999 had higher DMFT scores (5.74 ± 5.38) than those with no income (2.71 ± 2.95), p = 0.041. These results suggest that older age and having income are linked to poorer dental health outcomes. Table 3 Relationship between sociodemographic with Total DMFT Variable Total DMFT p-value Mean (SD) Median (IQR) Level of Visual Impairment B1 3.41 (3.75) 2.00 (6.00) 0.916 a B2 3.59 (3.61) 3.00 (6.00) B3 3.50 (4.83) 2.00 (4.00) Age Category 18 to 30 1.79 (2.42) 1.00 (4.00) 0.001 b* Above 30 6.32 (4.30) 6.00 (7.50) Gender Male 3.73 (4.04) 2.00 (6.00) 0.536 b Female 3.04 (3.69) 2.00 (4.00) Race Malay 3.36 (3.92) 2.00 (5.00) 0.627 b Non Malay 3.77 (3.96) 2.50 (5.00) Health Problem None 3.07 (3.49) 2.00 (4.50) 0.290 b Has comorbidities 4.52 (4.77) 4.00 (8.00) Education level Below Tertiary 3.59 (4.12) 2.00 (6.00) 0.895 b Tertiary 3.19 (3.43) 2.00 (6.00) Monthly Income No Income 2.71 (2.95) 2.00 (4.00) 0.041 b < RM 4,999 5.74 (5.38) 4.00 (10.00) SD: standard deviation; IQR: interquartile range Results of a Kruskal-Wallis test and b Mann Whitney tests. * indicates p-value < 0.05. Table 4 investigates the relationship between oral health behaviours and both oral health knowledge and DMFT scores. Several behaviours were significantly associated with oral health knowledge. Participants who had visited a dentist within the past 12 months were more likely to have good oral health knowledge (p = 0.016). Similarly, frequent use of toothpaste (p = 0.011) and regular flossing (p = 0.034) were positively associated with higher knowledge levels. However, none of these behaviours showed statistically significant associations with DMFT scores, indicating that while these behaviours may enhance knowledge, they do not necessarily translate into better clinical oral health outcomes. Table 4 Relationship between oral health behaviour with level of knowledge on oral health and total DMFT Variables Overall Level of Knowledge on Oral Health Total DMFT Poor n (%) Moderate n (%) Good n (%) Mean (SD) Median (IQR) Last visit dentist > 12 Month 43 (57.3) 11 (25.6) 5 (11.6) 27 (62.8) 2.63 (3.16) 2.00 (3.00) Within 12 months 32 (42.7) 1 (3.1) 2 (6.3) 29 (90.6) 4.63 (4.54) 4.00 (7.75) p-value 0.016* 0.085 Daily toothbrushing frequency Once 11 (14.7) 1 (27.3) 1 (9.1) 7 (63.6) 1.27 (1.68) 1.00 (3.00) Twice 42 (56.0) 9 (21.4) 3 (7.1) 30 (71.4) 3.60 (3.95) 2.00 (6.00) > 2 times 22 (29.3) 0 (0.0) 3 (13.6) 19 (86.4) 4.36 (4.33) 4.00 (5.50) p-value 0.167 0.079 Daily toothpaste use Never 1 (1.3) 0 (0.0) 1 (0.0) 0 (0.0) 4.00 (N/A) 4.00 (N/A) Once 9 (12.0) 3 (33.3) 1 (11.1) 5 (55.6) 1.56 (1.74) 1.00 (3.50) Twice 45 (60.0) 9 (20.0) 3 (6.7) 33 (73.3) 3.47 (3.87) 2.00 (6.00) > 2 times 20 (26.7) 0 (0.0) 2 (10.0) 18 (90.0) 4.35 (4.59) 3.50 (5.75) p-value 0.011* 0.443 Daily floss usage Never 25 (33.3) 5 (20.0) 4 (16.0) 16 (64.0) 1.96 (2.25) 1.00 (4.00) Occasionally 8 (10.7) 0 (0.0) 0 (0.0) 8 (10.00) 5.13 (4.32) 3.50 (7.50) Once 12 (16.0) 2 (16.7) 0 (0.0) 10 (83.3) 4.33 (4.85) 3.00 (7.25) Twice 11 (14.7) 5 (45.5) 1 (9.1) 5 (45.5) 2.82 (3.55) 2.00 (4.00) > 2 times 19 (25.3) 0 (0.0) 2 (10.5) 17 (89.5) 4.63 (4.57) 4.00 (6.00) p-value 0.034* 0.148 Daily frequency of rinsing mouth with water after meal Never 19 (25.3) 4 (21.1) 2 (10.5) 13 (68.4) 3.11 (3.57) 2.00 (6.00) Occasionally 9 (12.0) 1 (11.1) 0 (0.0) 8 (88.9) 3.78 (4.32) 2.00 (7.50) Once 12 (16.0) 1 (8.3) 3 (16.7) 9 (75.0) 2.92 (2.23) 4.00 (3.75) Twice 10 (13.3) 2 (20.0) 0 (0.0) 8 (80.0) 3.90 (2.96) 4.00 (5.75) > 2 times 25 (33.3) 4 (16.0) 3 (12.0) 18 (72.0) 3.76 (5.03) 1.00 (6.00) p-value 0.851 0.905 Smoking Never 61 (81.3) 9 (14.8) 6 (9.8) 46 (75.4) 3.48 (3.99) 2.00 (6.00) Yes 14 (18.7) 3 (21.4) 1 (7.1) 10 (71.4) 3.50 (3.67) 3.00 (6.25) p-value 0.809 0.835 SD: standard deviation; IQR: interquartile range; * indicate p < 0.05. Table 5 presents the results of multivariate logistic regression analyses identifying determinant factors associated with oral health knowledge and DMFT categories. Covariates included in the multivariate models were selected based on theoretical relevance (age, gender, ethnicity, education, visual impairment, dental attendance) and significant associations identified in bivariate analyses. Age emerged as a strong predictor for both outcomes. Participants aged above 30 years were significantly more likely to have good oral health knowledge (OR = 22.21, 95% CI: 2.44–201.93, p = 0.006) and higher DMFT scores (OR = 14.47, 95% CI: 2.86–73.08, p = 0.001). Additionally, participants who had visited a dentist within the past 12 months were more likely to have good oral health knowledge (OR = 9.64, 95% CI: 1.73–53.60, p = 0.010). Race also played a role, with non-Malay participants having significantly lower odds of good oral health knowledge (OR = 0.14, 95% CI: 0.02–0.93, p = 0.042). No other sociodemographic or behavioural factors were significantly associated with DMFT in the multivariate model. Table 5 Determinant factor associate with level of oral health knowledge and DMFT category Variables Knowledge Level DMFT Category OR (95% CI) p-value OR (95% CI) p-value Level of Visual Impairment B1 Reference Reference B2 0.18 (0.03, 1.03) 0.054 2.33 (0.45, 12.03) 0.314 B3 1.99 (0.33, 11.99) 0.452 1.56 (0.20, 11.96) 0.667 Age Category 18 to 30 Reference Reference Above 30 22.21 (2.44, 201.93) 0.006* 14.47 (2.86,73.08) 0.001* Gender Male Reference Reference Female 3.85 (0.81, 18.32) 0.090 0.40 (0.09, 1.81) 0.234 Race Malay Reference Reference Non Malay 0.14 (0.02, 0.93) 0.042* 1.19 (0.24, 5.84) 0.834 Education level Below Tertiary Reference Reference Tertiary 1.87 (0.37, 9.48) 0.449 0.45 (0.09, 2.32) 0.343 Monthly Income No Income Reference Reference 12 Month Reference Reference Within 12 months 9.64 (1.73, 53.60) 0.010* 4.29 (0.95, 19.51) 0.059 Knowledge Level Low to moderate N/A High N/A 1.63 (0.23, 11.60) 0.624 OR: odds ratio; CI: confidence interval; * indicate p < 0.05. 4. Discussion This study revealed that improvements need to be made in terms of oral health knowledge among Malaysian AVI despite good self-report of oral health behaviours in terms of toothbrushing and usage of toothpaste and dental floss. The regional focus on Malaysia as one of the southeast Asian countries is essential, as the region has the third highest population of people with blindness as well as moderate and severe vision impairment 1 . As an upper-middle-income country, the socioeconomic disadvantage of the AVI in this study were evident with 28% completed tertiary education and almost 75% having no income. Others studies on AVI reported mixed socio-economic backgrounds, ranging from AVI with high education in Ethiopia 10 , low education in Jordan 11 , and various income levels for children and adolescents with visual impairment in Hong Kong 9 . Almost half of the AVI from this study were blind, although global and regional ures record a smaller ratio of people who are blind compared to those with vision impairment 1 , 3 . Other studies on oral health among people with vision impairment have recorded smaller percentages from 31.5% of the study population to 61.3% with blindness 9 , 10 . Recent dental attendance was linked to higher knowledge scores, emphasising the importance of access to dental care in improving knowledge and awareness on oral health. This has been proven to be especially true in studies on dental service utilisation and knowledge on dental diseases such as caries and periodontal disease 18 , 19 . On the other hand, age has been proven to be a significant factor influencing oral health knowledge. However, as current literature has not explored the association between age and oral health knowledge among AVI, comparisons were made with the general literature. Other studies involving dental patients, university students and schoolteachers have found that younger age groups have a better oral health knowledge 20 – 22 , contrasting with the present study where oral health knowledge improves with increasing age. This disparity highlights the need for tailored oral health education and intervention among all age groups of individuals with vision impairment. Oral health programmes need to focus more on periodontal disease as opposed to being solely focused on dental caries. Malaysian data revealed that 85.1% of the population had dental caries, whereas 94.5% had periodontal disease 23 , further emphasising the need for programmes that focus on early intervention of periodontal disease. The finding that Malay participants demonstrated higher oral health knowledge than non-Malay participants should be interpreted in light of the sample’s demographic composition and the broader Malaysian context. Malays constituted the majority of respondents in this study, mirroring Malaysia’s population structure, where Malays make up 58.1% of the national population 24 . This larger subgroup provides greater statistical stability than the smaller non-Malay sample, which may partly explain the observed difference rather than any inherent cultural or behavioural variation. Evidence from Malaysian studies also suggests contextual factors may contribute. Among urban residents, Malays have been reported to seek dental treatment more frequently than non-Malays 25 , which aligns with the urban setting of the MAB in Kuala Lumpur and may enhance exposure to dental advice and awareness. However, another study showed that non-Malays are more likely to engage in certain healthy lifestyle behaviours, such as consuming five or more servings of fruits and vegetables daily 26 , indicating that health behaviours are not uniformly patterned by ethnicity. Additionally, national health promotion campaigns including oral health initiatives are predominantly delivered in the Malay language, which may benefit Malay speakers disproportionately in contexts where health information accessibility is language-dependent 27 , 28 . Around 30.7% of participant having caries with a mean DMFT of 3.84 in this study is an encouraging finding, particularly when contrasting it to Malaysian data where 85.1% of the population had dental caries with mean DMFT of 9.7 23 . A study on Malaysian para-athletes reported a mean DMFT of 3.49 29 , almost similar to the present study. This similarity may be because para-athletes are almost similar to AVI in terms of having physical disabilities that impact on daily functioning. However, lower DMFT scores have been recorded for children with visual impairment in Iran 8 or adults with physical disability in India 30 . This regional difference in DMFT gives the impression that oral health among Malaysians with disability is poor in general, with a need for tailored interventions featuring primary prevention of dental caries addressed to this disadvantaged cohort. The proportional increase of DMFT with increasing age in this study reflects that there is an accumulation of oral disease with aging. However, this contrasts with a study in Saudi Arabia where dental patients of younger age groups were found to have higher mean DMFT as compared to older age groups 22 . This difference may be explained through regional differences as this study had an older average population in comparison to the study by Ahmed et al. 22 where 66.5% of the population was aged between 18–28 years. As Malaysia is phasing into an aging component, the retention of natural teeth is integral. Furthermore, in this study, the component that made up majority of the DMFT was the ‘Missing’ component. The total estimated Malaysian population has a mean number of 24.4 teeth, with only 34.3% of the population aged 60 years and above retaining 20 teeth or more 23 . With older age groups in this study showing higher DMFT scores, there is a need to increase to ensure that oral health programmes are tailored towards the importance of retaining natural teeth into old age. Furthermore, as all smokers featured in this study were male, the importance of smoking cessation programmes should be specifically designed for the male population of AVI. This study has several strengths. It is among the first to examine oral health knowledge, behaviours, and caries experience in AVI in Malaysia, a population often under-represented in oral health research. The use of on-site clinical examination alongside interviewer-administered questionnaires provided both objective and subjective measures, allowing exploration of the alignment between self-reported knowledge/behaviours and clinical outcomes. Additionally, participation rates were relatively high across both survey rounds, enhancing representativeness of the study setting. Nonetheless, several limitations should be noted. First, HPQI was originally validated in schoolchildren rather than adults 15 . While this raises questions about its applicability, it is noteworthy that not all participants in our study achieved full scores, suggesting that even the most basic oral health concepts assessed by the instrument were not universally known. This supports the utility of the HPQI in highlighting knowledge gaps within this adult population. This study also had no control group unlike the study by Alshatrat et al 11 thus preventing the comparison of oral health knowledge, practice, and indices between AVI and adults without visual impairment. Second, reliance on self-reported behaviours introduces recall and social desirability bias, evident in inconsistencies between reported brushing and toothpaste use. Third, the study was conducted as part of community outreach and examiners were not formally calibrated, although both had completed ICDAS-based training. This may have led to some measurement variability in DMFT recording. Finally, the cross-sectional design precludes causal inference, and the small sample size limited the ability to detect weaker associations or fully adjust for potential confounders such as socioeconomic status as the study sample mostly had no income and only went up to secondary education. The findings highlight several important implications. The disconnect observed between knowledge, behaviours, and caries experience suggests that oral health education alone may be insufficient to reduce disease burden in AVI. Preventive and restorative services remain critical, especially given the high contribution of missing teeth to overall DMFT. The association between higher knowledge and recent dental attendance indicates that improving service accessibility could strengthen both awareness and oral health outcomes. 5. Conclusions This study examined oral health knowledge, behaviours, and caries experience among Malaysian adults with visual impairment. Although participants generally demonstrated moderate-to-good knowledge and reported positive hygiene practices, caries experience, especially tooth loss, remained substantial. The weak alignment between knowledge, behaviours, and DMFT suggests that information alone may not translate into effective oral health outcomes in this population. These findings should be interpreted cautiously given the modest sample size, convenience sampling, and reliance on self-reported behaviours, which limit generalisability beyond similar urban vocational training settings. Nonetheless, the results highlight the need for accessible, skill-based oral hygiene support and improved preventive and restorative service access. Future studies involving larger, more diverse samples are needed to confirm these patterns and to evaluate tailored oral health interventions for adults with visual impairment. Abbreviations AVI Adults with visual impairment CI Confidence interval DMFT Decayed, Missing, and Filled Teeth (DMFT) index HPQI Health Promotion Questionnaire Index ICDAS International Caries Detection and Assessment System IQR Interquartile range OR Odds ratio SD Standard deviation Declarations 7.1 Ethics approval and consent to participate Ethical approval was obtained from the Faculty of Dentistry Medical Ethics Committee (FDMEC) with the approval number of DF CD2324/0048/2405 (L). Written informed consent was obtained from all participants. This study was conducted in accordance with the principles of the Declaration of Helsinki and the General Data Protection Regulation (GDPR). 7.2 Consent for publication Not applicable. 7.4 Competing interests The authors declare that they have no competing interests. 7.5 Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author Contribution AAF and SSJ contributed to the study design and conducted the data collection. AAF, SSJ, MAB, and AAA participated in data analysis, contributed to drafting the manuscript, and read and approved the final version. Acknowledgement The authors thank all study participants, the Malaysian Association for the Blind for facilitating recruitment, and the dentists who conducted the examinations. Data Availability Data are available from the corresponding author upon reasonable request but are not publicly accessible due to privacy and ethical restrictions. References Bourne R, Steinmetz JD, Flaxman S, Briant PS, Taylor HR, Resnikoff S, et al. Trends in prevalence of blindness and distance and near vision impairment over 30 years: an analysis for the Global Burden of Disease Study. Lancet Glob Health. 2021;9(2):e130–43. Steinmetz JD, Bourne RRA, Briant PS, Flaxman SR, Taylor HRB, Jonas JB, et al. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020. Lancet Glob Health. 2021;9(2):e144–60. Nangia V, Jonas JB, George R, Lingam V, Ellwein L, Cicinelli MV, et al. Prevalence and causes of blindness and vision impairment in South and Central Asia. Br J Ophthalmol. 2019;103(7):871–7. Marques AP, Ramke J, Cairns J, Butt T, Zhang JH, Muirhead D, et al. Global economic productivity losses from vision impairment and blindness. eClinicalMedicine. 2021;35:100852. Rein DB, Wittenborn JS, Zhang P, Sublett F, Lamuda PA, Lundeen EA, et al. The economic burden of vision loss and blindness in the United States. Ophthalmology. 2022;129(4):369–78. Pezzullo L, Streatfeild J, Simkiss P, Shickle D. The economic impact of sight loss and blindness in the UK adult population. BMC Health Serv Res. 2018;18(1):63. World Health Organization. Global oral health status report: Towards universal health coverage for oral health by 2030. World Health Organization. 2022. https://iris.who.int/bitstream/handle/10665/364538/9789240061484-eng.pdf . Accessed 21 Nov 2025. Sharififard N, Sargeran K, Gholami M. Perception of oral health and medical conditions as possible predictors of oral health status in visually impaired adolescents: a cross-sectional study. BMC Oral Health. 2021;21(1):89. Lee JKY, Yuen AWT, Leung KPY, Li JTW, Bae SY, Chan YY, et al. Oral health status and oral health-related behaviours of Hong Kong students with vision impairment. Healthcare. 2024;12(3):391. Fantaye W, Nur A, Kifle G, Engida F. Oral health knowledge and oral hygiene practice among visually impaired subjects in Addis Ababa, Ethiopia. BMC Oral Health. 2022;22(1):167. Alshatrat S, Bakri IAL, Omari WAL, Tabnjh A. Oral health knowledge, behaviour, and access to dental care in visually impaired individuals in Jordan: a case-control study. Open Dent J. 2021;15:33–40. Watson EK, Moles DR, Kumar N, Porter SR. The oral health status of adults with a visual impairment, their dental care and oral health information needs. Br Dent J. 2010;208(8):E15. Bhor KB, Vinay V, Ambildhok K, Shetty V. Effectiveness of oral health educational interventions on oral health of visually impaired school children: a systematic review and meta-analysis. Spec Care Dentist. 2021;41(3):291–308. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The STROBE statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453–7. Yusof ZYM, Jaafar N. Development of a health promotion questionnaire index (HPQI) to measure Doktor Muda programme impact on schoolchildren’s oral health knowledge, attitudes and behaviour. Ann Dent Univ Malaya. 2013;20(1):13–9. Bloom BS. Learning for mastery. Eval Comment. 1968;1(2):1–12. World Health Organization. Oral health surveys: Basic methods. World Health Organization. 2013. https://iris.who.int/server/api/core/bitstreams/b00e659f-ab38-4e61-b786-0152d91b5f1b/content . Accessed 21 Nov 2025. Amarasena N, Spencer AJ, Roberts-Thomson KF, Brennan DS. Dental knowledge and dental service utilization: a 2-year follow-up study. Community Dent Oral Epidemiol. 2018;46(4):336–42. Varela-Centelles P, Diz-Iglesias P, Estany-Gestal A, Blanco-Hortas A, Bugarín-González R, Seoane-Romero JM. Regular dental attendance and periodontal health knowledge: a cross-sectional survey. Oral Dis. 2020;26(2):419–28. Kandasamy G, Almeleebia T. Assessment of oral health knowledge, attitudes, and behaviours among university students in the Asir region—Saudi Arabia: a cross-sectional study. Healthcare. 2023;11(23):3100. Aldowah O, Assiry AA, Mujallid NF, Ashi FN, Abduljawad F, Al-Zahrani MM, et al. Assessment of oral health knowledge, literacy, and attitude among schoolteachers. BMC Oral Health. 2023;23(1):392. Ahmed MA, Jouhar R, Faheemuddin M, AlJafar A, Alabawi H, Alhumaidi B, et al. Oral health knowledge, attitude, practice and DMFT scores among dental patients at King Faisal University. Med (Kaunas). 2023;59(4):679. Oral Health Programme. National Oral Health Survey of Adults (NOHSA) 2020 Fact Sheet. Ministry of Health Malaysia. 2020. https://hq.moh.gov.my/ohp/images/pdf/4.-penyelidikan-kesihatan-pergigian/fact-sheet-nohsa-2020.pdf . Accessed 21 Nov 2025. Department of Statistics Malaysia. Demographic, Statistics FQ. 2025. Ministry of Economy Malaysia. 2025. https://www.dosm.gov.my/site/downloadrelease?id=demographic-statistics-first-quarter-2025 . Accessed 21 Nov 2025. Tan YR, Jawahir S, Doss JG. Oral healthcare seeking behaviour of Malaysian adults in urban and rural areas: findings from the National Health and Morbidity Survey 2019. BMC Oral Health. 2023;23(1):719. Khaw W-F, Nasaruddin NH, Alias N, Chan YM, Tan L, Cheong SM, et al. Sociodemographic factors and healthy lifestyle behaviours among Malaysian adults: NHMS 2019. Sci Rep. 2022;12:16569. Nurdin MF, Yusof ZYM. Facilitators and barriers to the implementation of preschool oral healthcare programme in Malaysia from the perspective of dental therapists. Children. 2020;7(12):266. Zaberi ZHS, Nor NAM, Kamarudin Y, Anuwar AHK, Hariyani N. Oral health promotion on social media: perceptions of Malaysian young adults. Maj Ked Gigi. 2025;58(3):224–30. Othman NH, Rajali A, Zulkifeli NRN, Shaharuddin IM, Hussein KH, Hassan MIA. Sports-related dental injuries and oral health status among Malaysian para-athletes: a cross-sectional study. Spec Care Dentist. 2024;44(1):221–30. Suresh S, Indiran MA, Doraikannan S, Prabakar J, Balakrishnan S. Assessment of oral health status among intellectually and physically disabled population in Chennai. J Family Med Prim Care. 2022;11(2):526–30. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 04 Feb, 2026 Reviewers agreed at journal 03 Feb, 2026 Reviewers invited by journal 23 Jan, 2026 Editor invited by journal 02 Jan, 2026 Editor assigned by journal 02 Dec, 2025 Submission checks completed at journal 01 Dec, 2025 First submitted to journal 01 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8170573","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":580206647,"identity":"7e0c3f7d-ab12-4a4f-991d-543bfa3a5cb9","order_by":0,"name":"Aisyah Ahmad Fisal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYNCCCjBpQIqWMyRrYWwjRQt/e/sziZ/zDkczsDdvk2DMOUxYi8SZM2aSvdsO5zbwHCuTYNxGhBaGGzlsErwgLRI5ZsRpkb///Jnk3zlALfJviNRicIPBTJq3AWQLD5FaDM/kGFvLHEvPbeNJK7ZI3JZOWIvc8eMPb76psc7tZz+88cbHbdaEtQABiwSIZAMRCQzNRGlh/oDEqSNKyygYBaNgFIwsAADoKzmBld5IoQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Malaya","correspondingAuthor":true,"prefix":"","firstName":"Aisyah","middleName":"Ahmad","lastName":"Fisal","suffix":""},{"id":580206649,"identity":"0e1f650a-9560-46db-9112-792c71d8b26a","order_by":1,"name":"Seong Jin Shiu","email":"","orcid":"","institution":"University of Malaya","correspondingAuthor":false,"prefix":"","firstName":"Seong","middleName":"Jin","lastName":"Shiu","suffix":""},{"id":580206650,"identity":"d4109204-cfff-4046-9528-fe348968ef09","order_by":2,"name":"Alias Abd Aziz","email":"","orcid":"","institution":"University of Malaya","correspondingAuthor":false,"prefix":"","firstName":"Alias","middleName":"Abd","lastName":"Aziz","suffix":""},{"id":580206651,"identity":"f3377cf0-c6f0-4e55-a8f9-1130d4fab474","order_by":3,"name":"Mohamad Adam Bujang","email":"","orcid":"","institution":"Sarawak General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mohamad","middleName":"Adam","lastName":"Bujang","suffix":""}],"badges":[],"createdAt":"2025-11-21 07:08:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8170573/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8170573/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101274888,"identity":"3ced521b-3faf-4b50-a7b5-ce8c19869d26","added_by":"auto","created_at":"2026-01-28 03:13:40","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":91247,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of participants\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8170573/v1/e508c581cd012e17c2e6a2f3.jpeg"},{"id":101274924,"identity":"6e606ca4-369a-42ae-b576-2e698e3f0c5d","added_by":"auto","created_at":"2026-01-28 03:13:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1323714,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8170573/v1/9525b0df-15b2-4723-931a-34add4d96657.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Interrelationships between sociodemographic factors, oral health knowledge, behaviours, and caries experience among adults with visual impairment: A cross-sectional study","fulltext":[{"header":"1. Background","content":"\u003cp\u003eVision impairment makes up one of the common global disability categories. Estimates of global vision impairment in 2020 put a figure of 43.3\u0026nbsp;million, 295\u0026nbsp;million, and 258\u0026nbsp;million of people who were blind, having moderate to severe vision impairment, and mild vision impairment respectively. Around 55% of the population with visual impairment were estimated to be female \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In adults with vision impairment (AVI) aged 50 years and older, the leading causes of blindness included cataract, glaucoma, undercorrected refractive error, age-related macular degeneration, and diabetic retinopathy \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. With 160.7\u0026nbsp;million of AVI being in the working age bracket, vision impairment is associated with profound economic impact with an overall relative reduction in employment of 30.2% and annual cost of potential productivity loss between \u003cspan\u003e$\u003c/span\u003e408.5\u0026nbsp;billion to \u003cspan\u003e$\u003c/span\u003e410.7\u0026nbsp;billion \u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBesides experiencing socioeconomic disadvantage, AVI are disproportionately affected by poor oral health. Globally, untreated dental caries remains one of the most prevalent health conditions, affecting an estimated 2.5\u0026nbsp;billion people, while severe periodontal disease affects nearly one billion adults \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. These burdens fall disproportionately on low- and middle-income countries, where access to preventive and restorative care remains limited. Research focusing specifically on individuals with visual impairment consistently report higher rates of caries, periodontal disease, and poorer oral hygiene compared to sighted populations. For example, cross-sectional studies from Iran, Hong Kong, Ethiopia, and Jordan have shown that children, adolescents, and adults with visual impairment have significantly higher DMFT scores, greater plaque accumulation, and more dental trauma than their sighted peers \u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e Maintaining good oral health presents unique challenges for AVI. Visual impairment limits the ability to detect early signs of dental disease, monitor oral hygiene effectiveness, or identify plaque accumulation. Some individuals may rely on caregivers for daily activities, including brushing and flossing, which can lead to inconsistent oral hygiene depending on caregiver availability and skill \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. In addition, oral health information is often delivered through visual formats (posters, leaflets, videos), making awareness campaigns less accessible to AVI unless specifically adapted into tactile, audio, or screen-reader-compatible forms \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. These factors combined with socioeconomic barriers and reduced access to dental services may contribute to a higher oral disease burden within this population. This study aimed to describe the oral health knowledge, behaviours, and caries experience of Malaysian AVI, and to examine demographic and behavioural correlates and interrelationships among these outcomes.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design and eligibility criteria\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted at the Malaysian Association for the Blind (MAB), a non-profit organisation providing rehabilitation and vocational training for individuals with visual impairment. Data were obtained during two community outreach programmes at the Gurney Training Centre on 14 January 2023 and 27 January 2024. Eligible participants were trainees and trainers with visual impairment classified under B1, B2, or B3 categories. Individuals were required to be enrolled at MAB, able to independently provide informed consent, and able to understand Malay. Trainers without visual impairment and individuals absent on survey days were excluded.The reporting of this study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Sampling strategy and sample size calculation\u003c/h2\u003e \u003cp\u003eConvenience sampling was employed, whereby all trainees and trainers present at MAB during the two survey dates were approached for participation. Across both data collection rounds, participation rates exceeded 80%. A small subset of individuals attended both sessions; to ensure independence of observations, duplicate attendees were identified and only their most recent record was retained for analysis. Given the finite population of trainees and trainers available during the outreach events, the study aimed to recruit as many eligible individuals as possible. Using finite population correction, this target sample was expected to provide approximately\u0026thinsp;\u0026plusmn;\u0026thinsp;5% precision for prevalence estimates at a 95% confidence level, which was deemed sufficient for exploratory analyses. The final number of participants included in the analysis is reported in the Results section.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Instruments\u003c/h2\u003e \u003cp\u003eOral health knowledge was assessed using the knowledge domain (11 items) of the Health Promotion Questionnaire Index (HPQI) in Malay, which was originally validated among Malaysian schoolchildren \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Each statement endorsed as \"agree\" or \"strongly agree\" was scored as 1, while \"disagree,\" \"strongly disagree,\" or \"not sure\" scores were marked as 0, resulting in a total Knowledge Score ranging from 0 to 11 (higher scores indicate better knowledge). Knowledge Scores were categorised using Bloom\u0026rsquo;s cut-off criteria \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e: good (9\u0026ndash;11 points, 80\u0026ndash;100%), moderate (7\u0026ndash;8 points, 60\u0026ndash;79%), and poor (0\u0026ndash;6 points, \u0026lt;\u0026thinsp;60%). For further analysis, knowledge levels were grouped into two categories: poor to moderate and good.\u003c/p\u003e \u003cp\u003eOral health behaviours were assessed separately using seven self-reported items: frequency of toothbrushing, toothpaste usage, flossing frequency, mouth rinsing after meals, smoking status, dental attendance, and assistance with toothbrushing. These items were analysed individually as behavioural indicators and not as part of the HPQI scale. Sociodemographic data, including age, gender, ethnicity, education level, and degree of visual impairment, were also collected. Questionnaires were administered by trained interviewers who read aloud each question in Malay, and responses were recorded with participant confirmation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Clinical examination\u003c/h2\u003e \u003cp\u003eClinical examinations were conducted on-site by two dental postgraduate students. The decayed, missing, and filled teeth (DMFT) index was recorded in accordance with World Health Organization (WHO) criteria \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Although no formal inter-examiner calibration was performed, both examiners had previously completed a caries detection workshop based on the International Caries Detection and Assessment System (ICDAS), focusing on standardised charting of caries. To minimise variability, both examiners adhered to the same examination protocol and drew upon their postgraduate clinical training. Participants received oral health education and a topical fluoride varnish application after the examination. DMFT scores were categorised into two groups: low to moderate (0\u0026ndash;4.4) and high to very high (4.5 and above) following the WHO severity categorisation.\u003c/p\u003e \u003cp\u003eEfforts were made to minimise potential sources of bias. Although no formal examiner calibration was conducted, both examiners had undergone ICDAS-based training and followed a standardised examination protocol to reduce measurement variability. For questionnaire items, interviewer administration was used to minimise misinterpretation, especially for participants requiring assistance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eData analysis included descriptive statistics to summarise participant characteristics and variable distributions, followed by inferential analyses examining associations between sociodemographic factors, oral health behaviours, oral health knowledge, and DMFT. As convenience sampling was used and all eligible individuals were invited, no sampling weights or cluster adjustments were applied. Normality of continuous variables (knowledge score and DMFT) was assessed using the Shapiro\u0026ndash;Wilk test to guide the selection of appropriate statistical tests. Associations between categorical variables were evaluated using chi-square or Fisher\u0026rsquo;s exact tests, while non-parametric tests (Mann\u0026ndash;Whitney U) were used for continuous variables. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eDMFT was analysed in two ways. First, it was treated as a continuous count variable for descriptive and bivariate correlation analyses. Second, for multivariable modelling, DMFT was categorised into low\u0026ndash;moderate and high\u0026ndash;very high severity, and entered into a logistic regression model. Factors associated with oral health knowledge and DMFT were identified using multivariable logistic regression with stepwise variable selection to remove non-significant predictors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Adjusted results are reported as odds ratios (ORs) with 95% confidence intervals. Covariates considered for inclusion were age, gender, ethnicity, education level, degree of visual impairment, and dental attendance. All analyses were conducted using IBM SPSS Statistics (version 28.0; IBM Corp., Armonk, NY, USA). There were no missing data in the dataset, and no sensitivity or subgroup analyses were conducted due to the exploratory nature of the study and the limited sample size within demographic strata.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eA total of 100 individuals were invited to participate across both survey periods. Eighty-six took part (49 in 2023; 37 in 2024), and 11 attended both sessions. After removing duplicate participants and retaining the most recent record, 75 unique individuals were included in the final analysis. The participant flow is summarised in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe mean age was 29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5 years, with 64% male. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the distribution of sociodemographic characteristics across different levels of visual impairment (B1, B2, B3). The analysis revealed no statistically significant differences in age category (p\u0026thinsp;=\u0026thinsp;0.208), gender (p\u0026thinsp;=\u0026thinsp;0.236), race (p\u0026thinsp;=\u0026thinsp;0.546), presence of comorbidities (p\u0026thinsp;=\u0026thinsp;0.256), education level (p\u0026thinsp;=\u0026thinsp;0.065), or monthly income (p\u0026thinsp;=\u0026thinsp;0.615) across the three visual impairment groups. This suggests that the severity of visual impairment among participants was not associated with their sociodemographic background.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic across the level of visual impairment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eLevel of Visual Impairment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eB2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eB3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003e75 (100.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003e37 (49.3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003e22 (29.3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003e16 (21.3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge Category\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 to 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47 (62.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22 (46.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12 (25.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13 (27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbove 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15 (53.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10 (25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48 (64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.236\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27 (36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMalay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53 (70.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24 (45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-Malay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13 (59.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5 (22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHealth Problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54 (72.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26 (48.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHas comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8 (38.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelow Tertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54 (72.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28 (51.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10 (47.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMonthly Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56 (74.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26 (46.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; RM 4,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (57.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eChi-square test: * indicates p-value\u0026thinsp;\u003cem\u003e\u0026lt;\u003c/em\u003e\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eThe mean oral health knowledge score was 8.9 (SD 2.4; median 10; range 0\u0026ndash;11). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e explores the relationship between sociodemographic factors and oral health knowledge levels. Significant associations were observed for age and race. Participants aged above 30 years demonstrated significantly better oral health knowledge compared to those aged 18 to 30 years (p\u0026thinsp;=\u0026thinsp;0.044). Additionally, Malay participants exhibited higher levels of oral health knowledge than non-Malay participants (p\u0026thinsp;=\u0026thinsp;0.046). These findings indicate that older age and Malay ethnicity are positively associated with oral health knowledge.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship between sociodemographic with level of knowledge on oral health\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eLevel of Knowledge on Oral Health\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003e75 (100.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003e12 (16.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003e7 (9.30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003e56 (74.7)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLevel of Visual Impairment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37 (49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28 (75.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.425\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 (27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15 (68.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13 (81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge Category\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 to 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47 (62.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31 (66.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.044*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbove 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25 (89.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48 (64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5 (10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27 (36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23 (85.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMalay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53 (70.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e42 (79.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.046*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon Malay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14 (63.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelow Tertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54 (72.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5 (9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e39 (72.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17 (81.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMonthly Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56 (74.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e41 (73.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.773\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; RM 4,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15 (78.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eChi-square test: * indicates p-value\u0026thinsp;\u003cem\u003e\u0026lt;\u003c/em\u003e\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eThe mean DMFT was 3.48 (SD 3.91; median 2.0; range 0\u0026ndash;15). Missing teeth (M) contributed the largest share of the total DMFT burden (40.2%), followed by filled (34.9%) and decayed teeth (24.9%). While restorations (F) were the most prevalent (42.7% of participants), missing teeth contributed more heavily due to their higher average per affected participant (3.62 teeth). Based on WHO categories, 30.7% had no caries experience, and 17.3% each were classified as low or high severity.\u003c/p\u003e \u003cp\u003eShapiro\u0026ndash;Wilk tests indicated that DMFT and knowledge score were not normally distributed, so non-parametric correlation and group comparison tests were used. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e examines the relationship between sociodemographic variables and total DMFT scores. Age was significantly associated with DMFT scores, where participants aged above 30 years had higher mean DMFT scores (6.32\u0026thinsp;\u0026plusmn;\u0026thinsp;4.30) compared to younger participants (1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;2.42), with a p-value of 0.001. Monthly income also showed a significant association; individuals earning less than RM 4,999 had higher DMFT scores (5.74\u0026thinsp;\u0026plusmn;\u0026thinsp;5.38) than those with no income (2.71\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95), p\u0026thinsp;=\u0026thinsp;0.041. These results suggest that older age and having income are linked to poorer dental health outcomes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship between sociodemographic with Total DMFT\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eTotal DMFT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLevel of Visual Impairment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.41 (3.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.916\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.59 (3.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.50 (4.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.00 (4.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge Category\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 to 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.79 (2.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00 (4.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbove 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.32 (4.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.00 (7.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.73 (4.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.536\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.04 (3.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.00 (4.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMalay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.36 (3.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.00 (5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.627\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon Malay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.77 (3.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.50 (5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHealth Problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.07 (3.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.00 (4.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.290\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHas comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.52 (4.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.00 (8.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelow Tertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.59 (4.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.895\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.19 (3.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMonthly Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.71 (2.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.00 (4.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; RM 4,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.74 (5.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.00 (10.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eSD: standard deviation; IQR: interquartile range\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eResults of\u003c/em\u003e \u003csup\u003ea\u003c/sup\u003e\u003cem\u003eKruskal-Wallis test and\u003c/em\u003e \u003csup\u003eb\u003c/sup\u003e\u003cem\u003eMann Whitney tests. * indicates p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e investigates the relationship between oral health behaviours and both oral health knowledge and DMFT scores. Several behaviours were significantly associated with oral health knowledge. Participants who had visited a dentist within the past 12 months were more likely to have good oral health knowledge (p\u0026thinsp;=\u0026thinsp;0.016). Similarly, frequent use of toothpaste (p\u0026thinsp;=\u0026thinsp;0.011) and regular flossing (p\u0026thinsp;=\u0026thinsp;0.034) were positively associated with higher knowledge levels. However, none of these behaviours showed statistically significant associations with DMFT scores, indicating that while these behaviours may enhance knowledge, they do not necessarily translate into better clinical oral health outcomes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship between oral health behaviour with level of knowledge on oral health and total DMFT\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eLevel of Knowledge on Oral Health\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eTotal DMFT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003e(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLast visit dentist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12 Month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (57.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27 (62.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.63 (3.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.00 (3.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWithin 12 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29 (90.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.63 (4.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.00 (7.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.016*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDaily toothbrushing frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnce\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (63.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.27 (1.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00 (3.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTwice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (56.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30 (71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.60 (3.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19 (86.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.36 (4.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.00 (5.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDaily toothpaste use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.00 (N/A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.00 (N/A)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnce\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.56 (1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00 (3.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTwice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33 (73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.47 (3.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (26.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.35 (4.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.50 (5.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.011*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDaily floss usage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.96 (2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00 (4.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (10.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.13 (4.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.50 (7.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnce\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.33 (4.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00 (7.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTwice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (45.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (45.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.82 (3.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.00 (4.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17 (89.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.63 (4.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.034*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDaily frequency of rinsing mouth with water after meal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (68.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.11 (3.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.78 (4.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.00 (7.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnce\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.92 (2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.00 (3.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTwice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (80.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.90 (2.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.00 (5.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 times\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18 (72.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.76 (5.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46 (75.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.48 (3.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.00 (6.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.50 (3.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00 (6.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cem\u003eSD: standard deviation; IQR: interquartile range; * indicate p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the results of multivariate logistic regression analyses identifying determinant factors associated with oral health knowledge and DMFT categories. Covariates included in the multivariate models were selected based on theoretical relevance (age, gender, ethnicity, education, visual impairment, dental attendance) and significant associations identified in bivariate analyses. Age emerged as a strong predictor for both outcomes. Participants aged above 30 years were significantly more likely to have good oral health knowledge (OR\u0026thinsp;=\u0026thinsp;22.21, 95% CI: 2.44\u0026ndash;201.93, p\u0026thinsp;=\u0026thinsp;0.006) and higher DMFT scores (OR\u0026thinsp;=\u0026thinsp;14.47, 95% CI: 2.86\u0026ndash;73.08, p\u0026thinsp;=\u0026thinsp;0.001). Additionally, participants who had visited a dentist within the past 12 months were more likely to have good oral health knowledge (OR\u0026thinsp;=\u0026thinsp;9.64, 95% CI: 1.73\u0026ndash;53.60, p\u0026thinsp;=\u0026thinsp;0.010). Race also played a role, with non-Malay participants having significantly lower odds of good oral health knowledge (OR\u0026thinsp;=\u0026thinsp;0.14, 95% CI: 0.02\u0026ndash;0.93, p\u0026thinsp;=\u0026thinsp;0.042). No other sociodemographic or behavioural factors were significantly associated with DMFT in the multivariate model.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDeterminant factor associate with level of oral health knowledge and DMFT category\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eKnowledge Level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eDMFT Category\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLevel of Visual Impairment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18 (0.03, 1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.33 (0.45, 12.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.314\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.99 (0.33, 11.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.56 (0.20, 11.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge Category\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 to 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbove 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.21 (2.44, 201.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.47 (2.86,73.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.85 (0.81, 18.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.40 (0.09, 1.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMalay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon Malay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14 (0.02, 0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.042*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.19 (0.24, 5.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelow Tertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.87 (0.37, 9.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.45 (0.09, 2.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMonthly Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; RM 4,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39 (0.07, 2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.25 (0.51, 9.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLast visit dentist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12 Month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWithin 12 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.64 (1.73, 53.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.29 (0.95, 19.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eKnowledge Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow to moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.63 (0.23, 11.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.624\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eOR: odds ratio; CI: confidence interval; * indicate p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study revealed that improvements need to be made in terms of oral health knowledge among Malaysian AVI despite good self-report of oral health behaviours in terms of toothbrushing and usage of toothpaste and dental floss. The regional focus on Malaysia as one of the southeast Asian countries is essential, as the region has the third highest population of people with blindness as well as moderate and severe vision impairment \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. As an upper-middle-income country, the socioeconomic disadvantage of the AVI in this study were evident with 28% completed tertiary education and almost 75% having no income. Others studies on AVI reported mixed socio-economic backgrounds, ranging from AVI with high education in Ethiopia \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, low education in Jordan \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, and various income levels for children and adolescents with visual impairment in Hong Kong \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Almost half of the AVI from this study were blind, although global and regional ures record a smaller ratio of people who are blind compared to those with vision impairment \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Other studies on oral health among people with vision impairment have recorded smaller percentages from 31.5% of the study population to 61.3% with blindness \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRecent dental attendance was linked to higher knowledge scores, emphasising the importance of access to dental care in improving knowledge and awareness on oral health. This has been proven to be especially true in studies on dental service utilisation and knowledge on dental diseases such as caries and periodontal disease \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. On the other hand, age has been proven to be a significant factor influencing oral health knowledge. However, as current literature has not explored the association between age and oral health knowledge among AVI, comparisons were made with the general literature. Other studies involving dental patients, university students and schoolteachers have found that younger age groups have a better oral health knowledge \u003csup\u003e\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, contrasting with the present study where oral health knowledge improves with increasing age. This disparity highlights the need for tailored oral health education and intervention among all age groups of individuals with vision impairment. Oral health programmes need to focus more on periodontal disease as opposed to being solely focused on dental caries. Malaysian data revealed that 85.1% of the population had dental caries, whereas 94.5% had periodontal disease \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, further emphasising the need for programmes that focus on early intervention of periodontal disease.\u003c/p\u003e \u003cp\u003eThe finding that Malay participants demonstrated higher oral health knowledge than non-Malay participants should be interpreted in light of the sample\u0026rsquo;s demographic composition and the broader Malaysian context. Malays constituted the majority of respondents in this study, mirroring Malaysia\u0026rsquo;s population structure, where Malays make up 58.1% of the national population \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. This larger subgroup provides greater statistical stability than the smaller non-Malay sample, which may partly explain the observed difference rather than any inherent cultural or behavioural variation. Evidence from Malaysian studies also suggests contextual factors may contribute. Among urban residents, Malays have been reported to seek dental treatment more frequently than non-Malays \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, which aligns with the urban setting of the MAB in Kuala Lumpur and may enhance exposure to dental advice and awareness. However, another study showed that non-Malays are more likely to engage in certain healthy lifestyle behaviours, such as consuming five or more servings of fruits and vegetables daily \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, indicating that health behaviours are not uniformly patterned by ethnicity. Additionally, national health promotion campaigns including oral health initiatives are predominantly delivered in the Malay language, which may benefit Malay speakers disproportionately in contexts where health information accessibility is language-dependent \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAround 30.7% of participant having caries with a mean DMFT of 3.84 in this study is an encouraging finding, particularly when contrasting it to Malaysian data where 85.1% of the population had dental caries with mean DMFT of 9.7 \u003csup\u003e23\u003c/sup\u003e. A study on Malaysian para-athletes reported a mean DMFT of 3.49 \u003csup\u003e29\u003c/sup\u003e, almost similar to the present study. This similarity may be because para-athletes are almost similar to AVI in terms of having physical disabilities that impact on daily functioning. However, lower DMFT scores have been recorded for children with visual impairment in Iran \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e or adults with physical disability in India \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. This regional difference in DMFT gives the impression that oral health among Malaysians with disability is poor in general, with a need for tailored interventions featuring primary prevention of dental caries addressed to this disadvantaged cohort.\u003c/p\u003e \u003cp\u003eThe proportional increase of DMFT with increasing age in this study reflects that there is an accumulation of oral disease with aging. However, this contrasts with a study in Saudi Arabia where dental patients of younger age groups were found to have higher mean DMFT as compared to older age groups \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. This difference may be explained through regional differences as this study had an older average population in comparison to the study by Ahmed et al. \u003csup\u003e22\u003c/sup\u003e where 66.5% of the population was aged between 18\u0026ndash;28 years. As Malaysia is phasing into an aging component, the retention of natural teeth is integral. Furthermore, in this study, the component that made up majority of the DMFT was the \u0026lsquo;Missing\u0026rsquo; component. The total estimated Malaysian population has a mean number of 24.4 teeth, with only 34.3% of the population aged 60 years and above retaining 20 teeth or more \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. With older age groups in this study showing higher DMFT scores, there is a need to increase to ensure that oral health programmes are tailored towards the importance of retaining natural teeth into old age. Furthermore, as all smokers featured in this study were male, the importance of smoking cessation programmes should be specifically designed for the male population of AVI.\u003c/p\u003e \u003cp\u003eThis study has several strengths. It is among the first to examine oral health knowledge, behaviours, and caries experience in AVI in Malaysia, a population often under-represented in oral health research. The use of on-site clinical examination alongside interviewer-administered questionnaires provided both objective and subjective measures, allowing exploration of the alignment between self-reported knowledge/behaviours and clinical outcomes. Additionally, participation rates were relatively high across both survey rounds, enhancing representativeness of the study setting.\u003c/p\u003e \u003cp\u003eNonetheless, several limitations should be noted. First, HPQI was originally validated in schoolchildren rather than adults \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. While this raises questions about its applicability, it is noteworthy that not all participants in our study achieved full scores, suggesting that even the most basic oral health concepts assessed by the instrument were not universally known. This supports the utility of the HPQI in highlighting knowledge gaps within this adult population. This study also had no control group unlike the study by Alshatrat et al \u003csup\u003e11\u003c/sup\u003e thus preventing the comparison of oral health knowledge, practice, and indices between AVI and adults without visual impairment.\u003c/p\u003e \u003cp\u003eSecond, reliance on self-reported behaviours introduces recall and social desirability bias, evident in inconsistencies between reported brushing and toothpaste use. Third, the study was conducted as part of community outreach and examiners were not formally calibrated, although both had completed ICDAS-based training. This may have led to some measurement variability in DMFT recording. Finally, the cross-sectional design precludes causal inference, and the small sample size limited the ability to detect weaker associations or fully adjust for potential confounders such as socioeconomic status as the study sample mostly had no income and only went up to secondary education.\u003c/p\u003e \u003cp\u003eThe findings highlight several important implications. The disconnect observed between knowledge, behaviours, and caries experience suggests that oral health education alone may be insufficient to reduce disease burden in AVI. Preventive and restorative services remain critical, especially given the high contribution of missing teeth to overall DMFT. The association between higher knowledge and recent dental attendance indicates that improving service accessibility could strengthen both awareness and oral health outcomes.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study examined oral health knowledge, behaviours, and caries experience among Malaysian adults with visual impairment. Although participants generally demonstrated moderate-to-good knowledge and reported positive hygiene practices, caries experience, especially tooth loss, remained substantial. The weak alignment between knowledge, behaviours, and DMFT suggests that information alone may not translate into effective oral health outcomes in this population. These findings should be interpreted cautiously given the modest sample size, convenience sampling, and reliance on self-reported behaviours, which limit generalisability beyond similar urban vocational training settings. Nonetheless, the results highlight the need for accessible, skill-based oral hygiene support and improved preventive and restorative service access. Future studies involving larger, more diverse samples are needed to confirm these patterns and to evaluate tailored oral health interventions for adults with visual impairment.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAVI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdults with visual impairment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDMFT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDecayed, Missing, and Filled Teeth (DMFT) index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHPQI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth Promotion Questionnaire Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICDAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Caries Detection and Assessment System\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003e7.1 Ethics approval and consent to participate\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eEthical approval was obtained from the Faculty of Dentistry Medical Ethics Committee (FDMEC) with the approval number of DF CD2324/0048/2405 (L). Written informed consent was obtained from all participants. This study was conducted in accordance with the principles of the Declaration of Helsinki and the General Data Protection Regulation (GDPR).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7.2 Consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003e7.4 Competing interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003e7.5 Funding\u003c/h2\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAAF and SSJ contributed to the study design and conducted the data collection. AAF, SSJ, MAB, and AAA participated in data analysis, contributed to drafting the manuscript, and read and approved the final version.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe authors thank all study participants, the Malaysian Association for the Blind for facilitating recruitment, and the dentists who conducted the examinations.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eData are available from the corresponding author upon reasonable request but are not publicly accessible due to privacy and ethical restrictions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBourne R, Steinmetz JD, Flaxman S, Briant PS, Taylor HR, Resnikoff S, et al. Trends in prevalence of blindness and distance and near vision impairment over 30 years: an analysis for the Global Burden of Disease Study. Lancet Glob Health. 2021;9(2):e130\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSteinmetz JD, Bourne RRA, Briant PS, Flaxman SR, Taylor HRB, Jonas JB, et al. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020. Lancet Glob Health. 2021;9(2):e144\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNangia V, Jonas JB, George R, Lingam V, Ellwein L, Cicinelli MV, et al. Prevalence and causes of blindness and vision impairment in South and Central Asia. Br J Ophthalmol. 2019;103(7):871\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarques AP, Ramke J, Cairns J, Butt T, Zhang JH, Muirhead D, et al. Global economic productivity losses from vision impairment and blindness. eClinicalMedicine. 2021;35:100852.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRein DB, Wittenborn JS, Zhang P, Sublett F, Lamuda PA, Lundeen EA, et al. The economic burden of vision loss and blindness in the United States. Ophthalmology. 2022;129(4):369\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePezzullo L, Streatfeild J, Simkiss P, Shickle D. The economic impact of sight loss and blindness in the UK adult population. BMC Health Serv Res. 2018;18(1):63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Global oral health status report: Towards universal health coverage for oral health by 2030. World Health Organization. 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iris.who.int/bitstream/handle/10665/364538/9789240061484-eng.pdf\u003c/span\u003e\u003cspan address=\"https://iris.who.int/bitstream/handle/10665/364538/9789240061484-eng.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 21 Nov 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharififard N, Sargeran K, Gholami M. Perception of oral health and medical conditions as possible predictors of oral health status in visually impaired adolescents: a cross-sectional study. BMC Oral Health. 2021;21(1):89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee JKY, Yuen AWT, Leung KPY, Li JTW, Bae SY, Chan YY, et al. Oral health status and oral health-related behaviours of Hong Kong students with vision impairment. Healthcare. 2024;12(3):391.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFantaye W, Nur A, Kifle G, Engida F. Oral health knowledge and oral hygiene practice among visually impaired subjects in Addis Ababa, Ethiopia. BMC Oral Health. 2022;22(1):167.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlshatrat S, Bakri IAL, Omari WAL, Tabnjh A. Oral health knowledge, behaviour, and access to dental care in visually impaired individuals in Jordan: a case-control study. Open Dent J. 2021;15:33\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWatson EK, Moles DR, Kumar N, Porter SR. The oral health status of adults with a visual impairment, their dental care and oral health information needs. Br Dent J. 2010;208(8):E15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhor KB, Vinay V, Ambildhok K, Shetty V. Effectiveness of oral health educational interventions on oral health of visually impaired school children: a systematic review and meta-analysis. Spec Care Dentist. 2021;41(3):291\u0026ndash;308.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP. The STROBE statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYusof ZYM, Jaafar N. Development of a health promotion questionnaire index (HPQI) to measure Doktor Muda programme impact on schoolchildren\u0026rsquo;s oral health knowledge, attitudes and behaviour. Ann Dent Univ Malaya. 2013;20(1):13\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBloom BS. Learning for mastery. Eval Comment. 1968;1(2):1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Oral health surveys: Basic methods. World Health Organization. 2013. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iris.who.int/server/api/core/bitstreams/b00e659f-ab38-4e61-b786-0152d91b5f1b/content\u003c/span\u003e\u003cspan address=\"https://iris.who.int/server/api/core/bitstreams/b00e659f-ab38-4e61-b786-0152d91b5f1b/content\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 21 Nov 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmarasena N, Spencer AJ, Roberts-Thomson KF, Brennan DS. Dental knowledge and dental service utilization: a 2-year follow-up study. Community Dent Oral Epidemiol. 2018;46(4):336\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVarela-Centelles P, Diz-Iglesias P, Estany-Gestal A, Blanco-Hortas A, Bugar\u0026iacute;n-Gonz\u0026aacute;lez R, Seoane-Romero JM. Regular dental attendance and periodontal health knowledge: a cross-sectional survey. Oral Dis. 2020;26(2):419\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKandasamy G, Almeleebia T. Assessment of oral health knowledge, attitudes, and behaviours among university students in the Asir region\u0026mdash;Saudi Arabia: a cross-sectional study. Healthcare. 2023;11(23):3100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAldowah O, Assiry AA, Mujallid NF, Ashi FN, Abduljawad F, Al-Zahrani MM, et al. Assessment of oral health knowledge, literacy, and attitude among schoolteachers. BMC Oral Health. 2023;23(1):392.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed MA, Jouhar R, Faheemuddin M, AlJafar A, Alabawi H, Alhumaidi B, et al. Oral health knowledge, attitude, practice and DMFT scores among dental patients at King Faisal University. Med (Kaunas). 2023;59(4):679.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOral Health Programme. National Oral Health Survey of Adults (NOHSA) 2020 Fact Sheet. Ministry of Health Malaysia. 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://hq.moh.gov.my/ohp/images/pdf/4.-penyelidikan-kesihatan-pergigian/fact-sheet-nohsa-2020.pdf\u003c/span\u003e\u003cspan address=\"https://hq.moh.gov.my/ohp/images/pdf/4.-penyelidikan-kesihatan-pergigian/fact-sheet-nohsa-2020.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 21 Nov 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDepartment of Statistics Malaysia. Demographic, Statistics FQ. 2025. Ministry of Economy Malaysia. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.dosm.gov.my/site/downloadrelease?id=demographic-statistics-first-quarter-2025\u003c/span\u003e\u003cspan address=\"https://www.dosm.gov.my/site/downloadrelease?id=demographic-statistics-first-quarter-2025\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 21 Nov 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTan YR, Jawahir S, Doss JG. Oral healthcare seeking behaviour of Malaysian adults in urban and rural areas: findings from the National Health and Morbidity Survey 2019. BMC Oral Health. 2023;23(1):719.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhaw W-F, Nasaruddin NH, Alias N, Chan YM, Tan L, Cheong SM, et al. Sociodemographic factors and healthy lifestyle behaviours among Malaysian adults: NHMS 2019. Sci Rep. 2022;12:16569.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNurdin MF, Yusof ZYM. Facilitators and barriers to the implementation of preschool oral healthcare programme in Malaysia from the perspective of dental therapists. Children. 2020;7(12):266.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZaberi ZHS, Nor NAM, Kamarudin Y, Anuwar AHK, Hariyani N. Oral health promotion on social media: perceptions of Malaysian young adults. Maj Ked Gigi. 2025;58(3):224\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOthman NH, Rajali A, Zulkifeli NRN, Shaharuddin IM, Hussein KH, Hassan MIA. Sports-related dental injuries and oral health status among Malaysian para-athletes: a cross-sectional study. Spec Care Dentist. 2024;44(1):221\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuresh S, Indiran MA, Doraikannan S, Prabakar J, Balakrishnan S. Assessment of oral health status among intellectually and physically disabled population in Chennai. J Family Med Prim Care. 2022;11(2):526\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Vision Disorders, Oral Health, Dental Caries, Health Knowledge, Attitudes, Practice","lastPublishedDoi":"10.21203/rs.3.rs-8170573/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8170573/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAdults with visual impairment (AVI) face distinct challenges in maintaining oral health, yet evidence from Malaysia is limited. This study examined the sociodemographic factors associated with oral health knowledge, behaviours, and caries experience, and explored the interrelationships among these outcomes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA cross-sectional study was conducted at the Malaysian Association for the Blind during two outreach programmes (14 January 2023; 27 January 2024). Oral health knowledge was assessed using the 11-item Malay Health Promotion Questionnaire Index (HPQI). Oral health behaviours and sociodemographic data were self-reported. Caries experience was recorded using the Decayed, Missing, and Filled Teeth (DMFT) index. Descriptive analyses, non-parametric tests, and χ\u0026sup2;/Fisher's tests examined associations. Logistic regression was used to model factors associated with oral health knowledge and DMFT.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSeventy-five unique participants (mean age 29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5 years; 64% male) were included. The mean knowledge score was 8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4, with 74.5% categorised as having good knowledge. Most participants brushed twice or more daily (85.3%) and used toothpaste at least twice daily (86.7%), though one-third reported never flossing. The mean DMFT was 3.48\u0026thinsp;\u0026plusmn;\u0026thinsp;3.91, driven primarily by missing teeth (40.2%). In bivariate analyses, higher knowledge scores were associated with recent dental attendance, toothpaste use, and flossing frequency (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). DMFT correlated strongly with age (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In adjusted models, age (OR\u0026thinsp;=\u0026thinsp;1.06, p\u0026thinsp;=\u0026thinsp;0.006), race (OR\u0026thinsp;=\u0026thinsp;0.14, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and recent dental attendance (OR\u0026thinsp;=\u0026thinsp;9.64, p\u0026thinsp;=\u0026thinsp;0.01) were significantly associated with higher knowledge scores. For caries experience, age remained significantly associated with higher DMFT (OR\u0026thinsp;=\u0026thinsp;1.056, p\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDespite moderate-to-good oral health knowledge and self-reported behaviours, caries experience remained high among Malaysian AVI. The disconnect between awareness, behaviour, and clinical outcomes underscores that education alone is insufficient. Interventions should integrate accessible, skill-based oral hygiene support and improved preventive and restorative care access.\u003c/p\u003e","manuscriptTitle":"Interrelationships between sociodemographic factors, oral health knowledge, behaviours, and caries experience among adults with visual impairment: A cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-28 03:13:35","doi":"10.21203/rs.3.rs-8170573/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-04T09:30:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"220407789193852401286766650832665433640","date":"2026-02-03T08:32:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-23T06:13:37+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-02T06:14:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-02T12:21:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-02T01:43:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Oral Health","date":"2025-12-02T01:36:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5a7f5519-937d-422a-935c-42f18e4415d0","owner":[],"postedDate":"January 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-28T03:13:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-28 03:13:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8170573","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8170573","identity":"rs-8170573","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}