ABSTRACT
Background and Aims:
The COVID-19 pandemic has significantly impacted various aspects of daily life, including oral health. However, limited research has explored the effects of the pandemic on oral health perceptions, hygiene behaviors, and their subsequent influence on oral health-related quality of life (OHRQoL) in underserved settings. This study aims to assess changes in oral health perceptions and behaviors during the pandemic and their impact on OHRQoL in Myanmar.
Materials and Methods:
A cross-sectional study was conducted in 2023 at a township health center in Yangon, Myanmar. A total of 158 participants were included in the study. Clinical oral assessments were performed alongside face-to-face interviews, which collected data on sociodemographic characteristics, oral health perceptions and behaviors, psychological factors, and OHRQoL. Descriptive statistics, chi-square tests, Mann–Whitney U tests, Kruskal–Wallis tests, and regression analyses were used to explore associations and predictors of OHRQoL.
Results:
Among the 158 participants, 30.4% reported a decline in oral health perception, and 27.8% reported negative changes in oral hygiene behaviors during the COVID-19 pandemic. These changes were significantly associated with a history of COVID-19 infection, depressive symptoms, and bleeding on probing during oral examinations. Regression analysis revealed that worsened oral health perception (B = −2.59; 95% confidence interval [CI] = −5.00, −0.18) and negative changes in hygiene behaviors (B = −2.27; 95% CI = −4.57, −0.02) were associated with poorer OHRQoL. However, these associations became nonsignificant after adjusting for confounding factors. Notably, a history of COVID-19 infection requiring hospitalization remained a statistically significant predictor of poorer OHRQoL in all models.
Conclusions:
A significant proportion of participants reported worsened oral health perception and negative changes in oral hygiene behaviors during the COVID-19 pandemic, which contributed to a decline in OHRQoL. However, the influence of other confounding factors, such as psychological and socioeconomic variables, needs to be carefully considered. Clinically, these findings highlight the importance of integrating psychological support and targeted oral health interventions in the post-pandemic recovery phase, particularly in underserved settings. Public health initiatives should address the long-term impacts of the pandemic on oral health behaviors and perceptions to improve OHRQoL in affected populations.
Keywords: COVID-19, Myanmar, oral health perception, oral health-related quality of life, oral hygiene behavior
INTRODUCTION
The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted global health, not only through the direct effects of viral infection but also adversely affecting psychological well-being and health-related behaviors.[1,2] Studies have shown that psychological distress, such as depression, anxiety, and stress, increased significantly during the pandemic.[3] These psychological factors may have direct and indirect consequences on individuals’ self-care practices and behaviors.[4] The relationships between these psychological factors and health-related behaviors, particularly in the COVID-19 context, have become a key area of focus in public health.[5]
Oral health has emerged as a critical concern during the pandemic, as it has negatively affected individuals’ perceptions and behaviors of oral health, potentially influencing overall quality of life and well-being.[6] The pandemic’s impact on oral health behaviors is complex and multifaceted; factors such as fear of infection, lockdowns, and restricted access to oral healthcare services have likely contributed to changes in oral hygiene practices and self-care routines.[6,7] Oral health-related quality of life (OHRQoL) is a concept that reflects the subjective effects of oral health on an individual’s daily functioning, comfort, and social interactions.[6] Understanding how the pandemic has affected OHRQoL is essential for developing targeted public health interventions, especially in low-resource settings where healthcare access is limited.[8]
Myanmar, a lower-middle-income country in Southeast Asia, has faced unique challenges during the COVID-19 pandemic.[9] Yangon, the country’s largest city with a population exceeding seven million, experienced significant disruptions in healthcare services.[9,10] The healthcare infrastructure was further strained by concurrent political and economic challenges, which likely increased the barriers to accessing essential health services.[11] Previous studies in similar settings have indicated that socioeconomic factors and psychological well-being are key determinants of oral health outcomes.[9] However, the specific impact of changes in oral health perceptions and behaviors on OHRQoL during the COVID-19 pandemic, particularly in resource-constrained settings like Myanmar, is not well understood. Therefore, this study aims to fill the gap by assessing changes in oral health perception and oral hygiene behaviors during the COVID-19 pandemic, evaluating the associations between these changes and potential factors, such as sociodemographic characteristics, psychological factors, and oral health status, and identifying whether these changes influence on OHRQoL among Myanmar adults. By exploring these relationships, the study contributes to the existing knowledge and provides evidence to guide public health strategies addressing the broader health impacts of the pandemic in low-resource settings.
MATERIALS AND METHODS
STUDY SETTINGS
This research was a cross-sectional study carried out in Yangon City, Myanmar. A township health center was chosen by the Yangon Regional Public Health Department for its convenient location and resource availability. Participant recruitment was conducted between February and September 2023, with the following inclusion criteria: individuals had to be over 18 years old, ordinary residents (excluding Buddhist monks, nuns, and those living in institutional settings), physically and mentally capable of participating independently, and without any serious health conditions. Recruitment was open to all who met these criteria, and the study protocol was explained to all potential participants.
A minimum sample size of 128 was calculated using the formula: n = [Zα/2]² S²/d². This calculation was based on an estimated variance of 0.08 for Oral Health Impact Profile-14 Items (OHIP-14) scores from before research studies,[9] with a maximum margin of error set at 2% and an alpha level of 0.01. An allowance for a 20% dropout rate or missing data was also considered. Out of the 180 individuals who initially consented to participate, 10 did not attend on the assigned dates, and data for 12 participants were missed. Finally, data from 158 participants were analyzed. All participants provided written consent before participating in the study, which was conducted following the principles of the Declaration of Helsinki’s ethical standards. The study protocol received approval from the Ethics Committee of Niigata University, Japan (approval number: 2022-0248).
DATA COLLECTION
Following consent, a health assistant recorded participants’ weight and height to determine their body mass index (BMI). Subsequently, the questionnaire surveys and clinical oral assessments were administered within the same health center. The surveys collected information on sociodemographic characteristics, oral health factors, COVID-19 infection history, psychological factors, and OHRQoL. Data were gathered using a structured questionnaire in the Myanmar language through face-to-face interviews with an experienced interviewer in a private room to ensure confidentiality.
Sociodemographic information included age, sex, education (high school and above or middle school and below), and daily individual income. To calculate daily income, participants were asked to estimate their total monthly household income in Myanmar kyats. Then, this amount was divided by the number of household members, irrespective of age, to determine the per capita monthly income. Finally, daily individual income was dichotomized: >2.15 United States Dollars (USD) or ≤2.15 USD, following the World Bank’s poverty line standard.[12]
Oral health perception and behaviors were assessed with the questions: “How do you perceive your oral health condition during the COVID-19 pandemic?” with three response options (better, not changed, or worse), and “How did your oral hygiene behaviors change during the COVID-19 pandemic in terms of tooth brushing frequency, mouth cleaning with water after eating, and dental flossing?” with three response options (more care: positively changed, not changed, or less care: negatively changed). Participants were also asked about their COVID-19 infection history, categorized as: not experienced; experienced but non-hospitalized; or experienced and hospitalized. The term “hospitalized” refers to individuals who were hospitalized and received oxygen supply during infection, whereas “nonhospitalized” pertains to those who did not receive such care.
Psychological factors were evaluated using the Depression, Anxiety, and Stress Scale-21 items, a validated instrument tool in the Myanmar language,[9] that employs a 5-point Likert scale, with response options ranging from “0: not at all” to “4: applied very much.” Each subscale score was calculated by summing the relevant item responses and multiplying the total by two to obtain the final score. The resulting scores were dichotomized based on recommended cutoff values:[13] Depression (score 0–9: normal or score ≥10: depressive symptoms), anxiety (score 0–7: normal or score ≥8: anxiety symptoms), and stress (score 0–14: normal or score ≥15: stress symptoms). The OHRQoL was measured using the validated Myanmar version of the OHIP-14 questionnaire.[14] The responses were scored from “0: never” to “4: very often,” with a total possible score of 56. Higher scores indicate poorer OHRQoL.
Following the World Health Organization (WHO) guidelines,[15] a trained dentist conducted clinical oral examinations using a plain mirror and a WHO-Community Periodontal Index probe under a portable light source. These examinations assessed the number of teeth present (excluding third molars), and the count of decayed, missing, and filled permanent teeth. Periodontal assessments included gingival bleeding on probing and periodontal pocket: probing depth of ≥4 mm. The saliva flow rate was measured by collecting unstimulated whole saliva volume. Participants were seated comfortably in a private, quiet room, and with their heads slightly forward and eyes open. The saliva was collected using a spitting method, where participants were instructed to spit as much saliva as feasible into a container for 5 min. The total volume of saliva was divided by five to compute the flow rate per minute. Masticatory performance was evaluated using color-changing chewing gum (Xylitol®; Lotte Co., Ltd., Saitama, Japan). Participants were instructed to chew the gum 60 times, concurrently the dentist kept count. After chewing, the gum was placed on white paper, and the color changes, which were scored from 1 to 5, based on the manufacturer’s specifications.
STATISTICAL ANALYSIS
The statistical analysis was conducted using IBM Statistical Package for Social Sciences Statistics for Windows, version 27.0 (SPSS Inc., Chicago, IL, USA). To assess the normality of the data distribution, the Kolmogorov–Smirnov test was applied. Descriptive statistics, such as the median, interquartile range, and percentages, were used to summarize demographic information and general characteristics. The chi-square test was utilized to analyze differences between categorical variables, whereas the Mann–Whitney U test or Kruskal–Wallis test was employed for continuous variables to evaluate variations in study variables and changes in oral health perceptions or oral hygiene behaviors. Following the confirmation of no multicollinearity, linear regression analyses were performed to explore the relationships between changes in oral health perceptions and behaviors, COVID-19 infection history, and OHRQoL. Multivariable regression analyses were conducted in three stages: Model 1 included sociodemographic variables; Model 2 added psychological factors to Model 1; and Model 3 further added all other oral health factors to the variables from both Model 1 and Model 2. A P value of <0.05 was set as the threshold for statistical significance. The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for reporting observational research.
RESULTS
Among 158 included participants, the median age was 58.1 years with females being 53.8% and had a BMI of 22.6 kg/m² [Table 1]. The prevalence of depressive, anxiety, and stress symptoms was 22.8%, 33.5%, and 13.3%, respectively. Nearly, one-third of participants reported worsened self-perception of oral health (30.4%), whereas 10.2% showed positive changes in oral hygiene behaviors. The median OHIP-14 score was 7.2.
Table 1.
General characteristics of the study participants
| Variables | Categories | Median (IQR) or n (%) |
|---|---|---|
| Sociodemographics | ||
| Age (years) | 58.1 (44.2, 66.5) | |
| Sex | Male | 73 (46.2) |
| Female | 85 (53.8) | |
| BMI (kg/m2) | 22.6 (20.9, 23.4) | |
| Educational level | ≥High school | 108 (68.4) |
| ≤Middle school | 50 (31.6) | |
| Daily individual income | ˃2.15 USD | 51 (32.3) |
| ≤2.15 USD | 107 (67.7) | |
| History of COVID-19 infection | Not experienced | 73 (46.2) |
| Experienced, non-hospitalized | 51 (32.3) | |
| Experienced, hospitalized | 34 (21.5) | |
| Psychological factors | ||
| Depression scale (DASS-21) | Normal | 122 (77.2) |
| Depressive symptoms | 36 (22.8) | |
| Anxiety scale (DASS-21) | Normal | 105 (66.5) |
| Anxiety symptoms | 53 (33.5) | |
| Stress scale (DASS-21) | Normal | 137 (86.7) |
| Stress symptoms | 21 (13.3) | |
| Oral health factors | ||
| Changes in self-perception on oral health | Better | – |
| No changes | 110 (69.6) | |
| Worse | 48 (30.4) | |
| Changes in oral hygiene behaviors | Positively changed | 16 (10.2) |
| Not changed | 98 (62.0) | |
| Negatively changed | 44 (27.8) | |
| Number of present teeth | 30.1 (29.2, 32.0) | |
| DMFT | 4.2 (1.1, 6.0) | |
| Bleeding on probing | 5.0 (2.0, 7.3) | |
| Periodontal pocket | 0.1 (0.0, 3.3) | |
| OHIP-14 | 7.2 (3.1, 13.4) | |
| Resting saliva, mL/min | 0.2 (0.1, 0.3) | |
| Masticatory force | 4.0 (3.0, 5.2) |
IQR = interquartile range, BMI = body mass index, DMFT = decayed, missing, filled permanent teeth, OHIP-14 = Oral Health Impact Profile-14 Items, DASS-21 = Depression, Anxiety, and Stress Scale-21 Items, USD = United States Dollars, COVID-19 = coronavirus disease 2019.
Exchange rate: 1 USD equivalent to 2102 Myanmar Kyats as of September 30, 2023.
The history of COVID-19 infection was obtained from the health center’s records. The term “hospitalized” refers to individuals who received hospitalization and oxygen supply during COVID-19 infection, and “non-hospitalized” refers to those who did not receive them. The masticatory force was assessed using Xylitol® chewing gum
Participants who reported no changes in their self-perception of oral health (n = 110) and those who reported a worsening perception (n = 48) showed no statistically significant differences in age, sex, BMI, educational level, or income [Table 2]. However, a significant difference was observed concerning the history of COVID-19 infection (P < 0.001). Additionally, participants with worsened perception had significantly more depressive symptoms (P = 0.012). Deterioration in oral health factors, such as changes in oral hygiene behaviors (P < 0.001), bleeding on probing (P = 0.010), and higher OHIP-14 scores (P = 0.037), were more common among those with a negative change in perception.
Table 2.
Differences in general characteristics based on the changes in oral health perception
| Variables | Changes in self-perception on oral health | P value | |
|---|---|---|---|
| Not changed (n = 110) | Worse (n = 48) | ||
| Age (years) | 58.0 (41.8, 66.0) | 58.0 (45.0, 67.7) | 0.635 |
| Sex | 0.527 | ||
| Male | 49 (44.5) | 24 (50.0) | |
| Female | 61 (55.5) | 24 (50.0) | |
| BMI (kg/m2) | 21.9 (21.1, 23.4) | 22.6 (20.8, 23.6) | 0.579 |
| Educational level | 0.501 | ||
| ≥High school | 77 (70.0) | 31 (64.6) | |
| ≤Middle school | 33 (30.0) | 17 (35.4) | |
| Daily individual income | 0.356 | ||
| ˃2.15 USD | 38 (34.5) | 13 (27.1) | |
| ≤2.15 USD | 72 (65.5) | 35 (72.9) | |
| History of COVID-19 infection | <0.001 | ||
| Not experienced | 64 (58.2) | 9 (18.8) | |
| Experienced, non-hospitalized | 25 (22.7) | 26 (54.2) | |
| Experienced, hospitalized | 21 (19.1) | 13 (27.1) | |
| Depression scale (DASS-21) | 0.012 | ||
| Normal | 91 (82.7) | 31 (64.6) | |
| Depressive symptoms | 19 (17.3) | 17 (35.4) | |
| Anxiety scale (DASS-21) | 0.073 | ||
| Normal | 78 (70.9) | 27 (56.2) | |
| Anxiety symptoms | 32 (29.1) | 21 (43.8) | |
| Stress scale (DASS-21) | 0.182 | ||
| Normal | 98 (89.1) | 39 (81.2) | |
| Stress symptoms | 12 (10.9) | 9 (18.8) | |
| Changes in oral hygiene behaviors | <0.001 | ||
| Positively changed | 16 (14.5) | 0 (0.0) | |
| Not changed | 93 (84.5) | 5 (10.4) | |
| Negatively changed | 1 (0.9) | 43 (89.6) | |
| Number of present teeth | 30.0 (28.8, 32.0) | 31.0 (29.0, 32.0) | 0.544 |
| DMFT | 4.0 (1.1, 6.0) | 3.5 (0.1, 5.1) | 0.435 |
| Bleeding on probing | 4.5 (1.8, 6.0) | 6.0 (2.0, 11.5) | 0.010 |
| Periodontal pocket | 0.1 (0.0, 3.0) | 1.5 (0.1, 4.7) | 0.060 |
| OHIP-14 | 7.0 (2.1, 11.0) | 10.1 (3.2, 18.0) | 0.037 |
| Resting saliva, mL/min | 0.2 (0.1, 0.3) | 0.2 (0.1, 0.3) | 0.946 |
| Masticatory force | 4.0 (3.0, 5.0) | 4.0 (3.0, 5.0) | 0.391 |
BMI = body mass index, DMFT = decayed, missing, filled permanent teeth, OHIP-14 = Oral Health Impact Profile-14 Items, DASS-21 = Depression, Anxiety, and Stress Scale-21 Items, USD = United States Dollars, COVID-19 = coronavirus disease 2019.
Values are presented as median (interquartile range) or number (percentage) as indicated,
Exchange rate: 1 USD equivalent to 2102 Myanmar Kyats as of September 30, 2023.
The history of COVID-19 infection was obtained from the health center’s records. The term “hospitalized” refers to individuals who received hospitalization and oxygen supply during COVID-19 infection, and “non-hospitalized” refers to those who did not receive them. The masticatory force was assessed using Xylitol® chewing gum.
Variables are analyzed by the chi-square test or the Mann–Whitney U test.
Bold values indicate for statistical significance.
Table 3 shows the differences in general characteristics according to changes in oral hygiene behaviors. A significant association was found between changes in oral hygiene behaviors and a history of COVID-19 infection (P < 0.001). The prevalence of depressive symptoms was significantly highest among those who reported positive changes in oral hygiene behaviors (P = 0.002). Furthermore, oral health factors such as bleeding on probing also differed significantly (P = 0.027), with higher bleeding scores noted among participants who reported negative changes in their oral hygiene behaviors.
Table 3.
Differences in general characteristics based on the changes in oral hygiene behaviors
| Variables | Changes in oral hygiene behaviors | P value | ||
|---|---|---|---|---|
| Positively changed (n = 16) | Not changed (n = 98) | Negatively changed (n = 44) | ||
| Age (years) | 49.5 (38.0, 64.8) | 59.0 (44.0, 67.3) | 58.0 (45.2, 67.0) | 0.160 |
| Sex | 0.173 | |||
| Male | 10 (62.5) | 40 (40.8) | 23 (52.3) | |
| Female | 6 (37.5) | 58 (59.2) | 21 (47.7) | |
| BMI (kg/m2) | 21.2 (20.6, 23.0) | 22.3 (21.1, 23.4) | 22.6 (20.8, 23.6) | 0.244 |
| Educational level | 0.491 | |||
| ≥High school | 11 (68.8) | 70 (71.4) | 27 (61.4) | |
| ≤Middle school | 5 (31.2) | 28 (28.6) | 17 (38.6) | |
| Daily individual income | 0.679 | |||
| ˃2.15 USD | 5 (31.2) | 34 (34.7) | 12 (27.3) | |
| ≤2.15 USD | 11 (68.8) | 64 (65.3) | 32 (72.7) | |
| History of COVID-19 infection | <0.001 | |||
| Not experienced | 7 (43.8) | 57 (58.2) | 9 (20.5) | |
| Experienced, non-hospitalized | 4 (25.0) | 22 (22.4) | 25 (56.8) | |
| Experienced, hospitalized | 5 (31.2) | 19 (19.4) | 10 (22.7) | |
| Depression scale (DASS-21) | 0.002 | |||
| Normal | 8 (50.0) | 84 (85.7) | 30 (68.2) | |
| Depressive symptoms | 8(50.0) | 14 (14.3) | 14 (31.8) | |
| Anxiety scale (DASS-21) | 0.393 | |||
| Normal | 10 (62.5) | 69 (70.4) | 26 (59.1) | |
| Anxiety symptoms | 6 (37.5) | 29 (29.6) | 18 (40.9) | |
| Stress scale (DASS-21) | 0.226 | |||
| Normal | 12 (75.0) | 88 (89.8) | 37 (84.1) | |
| Stress symptoms | 4 (25.0) | 10 (10.2) | 7 (15.9) | |
| Number of present teeth | 30.0 (29.0, 31.0) | 30.5 (27.8, 32.0) | 30.5 (29.0, 32.0) | 0.693 |
| DMFT | 3.5 (1.0, 5.5) | 3.0 (0.1, 5.0) | 4.0 (1.0, 6.0) | 0.550 |
| Bleeding on probing | 3.5 (0.1, 6.0) | 5.0 (2.0, 6.0) | 6.1 (2.0, 12.0) | 0.027 |
| Periodontal pocket | 1.0 (0.1, 5.8) | 0.1 (0.1, 3.0) | 1.0 (0.0, 4.0) | 0.176 |
| OHIP-14 | 7.0 (2.1, 11.0) | 8.5 (3.2, 14.5) | 11.5 (3.0, 17.1) | 0.164 |
| Resting saliva, mL/min | 0.2 (0.1, 0.3) | 0.2 (0.1, 0.3) | 0.3 (0.1, 0.3) | 0.949 |
| Masticatory force | 4.0 (3.0, 5.0) | 4.0 (3.0, 5.0) | 4.0 (3.0, 5.0) | 0.742 |
BMI = body mass index, DMFT = decayed, missing, filled permanent teeth, OHIP-14 = oral Health Impact Profile-14 Items, DASS-21 = Depression, Anxiety, and Stress Scale-21 items, USD = United States Dollars, COVID-19 = coronavirus disease 2019.
Values are presented as median (interquartile range) or number (percentage) as indicated.
Exchange rate: 1 USD equivalent to 2102 Myanmar Kyats as of September 30, 2023.
The history of COVID-19 infection was obtained from the health center’s records. The term “hospitalized” refers to individuals who received hospitalization and oxygen supply during COVID-19 infection, and “non-hospitalized” refers to those who did not receive them. The masticatory force was assessed using Xylitol® chewing gum.
Variables are analyzed by the chi-square test or the Kruskal–Wallis test.
Bold values indicate for statistical significance.
The linear regression analysis examined the associations between changes in oral health perception, changes in oral hygiene behaviors, and COVID-19 infection history with OHRQoL [Table 4]. A worsened self-perception of oral health was significantly associated with lower OHRQoL in the crude model [B = −2.59; 95% confidence interval (CI) = −5.00, −0.18]; however, this association became non-significant after adjusting for other variables. Similarly, negatively changed oral hygiene behaviors were associated with lower OHRQoL in the crude model (B = −2.27; 95% CI = −4.57, −0.02), but this relationship also became nonsignificant in the fully adjusted models. On the contrary, a history of COVID-19 infection with hospitalization was statistically significant in the univariable regression analysis and remained significant even after adjustments in all models.
Table 4.
Linear regression analysis on changes in oral health perception and oral hygiene behaviors, and COVID-19 infection history with oral health-related quality of life
| Variables | Crude | Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|---|---|
| B (95% CI) | P value | B (95% CI) | P value | B (95% CI) | P value | B (95% CI) | P value | |
| Changes in oral health perception | ||||||||
| No changes | Ref | Ref | 0.417 | Ref | Ref | |||
| Worse | −2.59 (−5.00, −0.18) |
0.036 | −0.95 (−3.25, 1.35) |
−0.49 (−2.72, 1.73) |
0.662 | −0.86 (−3.44, 1.72) |
0.511 | |
| Changes in oral hygiene behaviors | ||||||||
| Positively changed | Ref | Ref | Ref | Ref | ||||
| Not changed | 1.47 (−1.03, 3.97) |
0.246 | 0.10 (−2.23, 2.43) |
0.932 | −0.18 (−2.43, 2.07) |
0.871 | −4.00 (−9.68, 1.68) |
0.166 |
| Negatively changed | −2.27 (−4.57, −0.02) |
0.042 | −1.01 (−3.21, 1.19) |
0.368 | −0.25 (−2.41, 1.90) |
0.817 | 0.12 (−0.17, 0.41) |
0.399 |
| History of COVID-19 infection | ||||||||
| Not experienced | Ref | Ref | Ref | Ref | ||||
| Experienced, nonhospitalized | −1.56 (−4.05, 0.94) |
0.462 | −1.01 (−3.56, 1.48) |
0.760 | −1.10 (−3.56, 1.28) |
0.892 | −1.64 (−4.16, 4.26) |
0.764 |
| Experienced, hospitalized | 9.18 (6.72, 11.63) |
<0.001 | 9.34 (6.46, 11.84) |
<0.001 | 8.40 (5.68, 10.86) |
<0.001 | 7.24 (4.38, 10.64) |
<0.001 |
B = unstandardized beta coefficient, 95% CI = 95% confidence interval, BMI = body mass index, DMFT = decayed, missing, filled permanent teeth.
Multivariate models were constructed in stages. Model 1 included age, sex, BMI, educational level, and daily individual income. Model 2 additionally included psychological variables such as depression, anxiety, and stress to Model 1. Model 3 further added the number of present teeth, DMFT, bleeding on probing, periodontal pocket, resting saliva, and masticatory force to the variables from both Model 1 and Model 2.
Bold values indicate for statistical significance.
DISCUSSION
Previous studies have reported the impact of COVID-19 on oral health behaviors and OHRQoL in different contexts.[6,16,17,18,19,20] However, there has been limited evaluation of these effects in low-resource countries that face unique socioeconomic challenges. To our knowledge, this is the first study in Myanmar that evaluated the changes in oral health perception and behaviors during the COVID-19 pandemic, the associations between these changes and a range of potential determinants, including sociodemographic, psychological, and oral health factors, and whether these modifications have an impact on OHRQoL. Our findings reveal that the pandemic has significantly affected individuals’ self-perception and behaviors of oral health. While significant associations were found between these changes and OHRQoL in the crude model, they were not sustained in the fully adjusted models. This suggests that although behavioral changes may initially seem relevant, underlying socioeconomic and psychological factors also play a pivotal role in shaping OHRQoL during the pandemic.
Our study found that 30.4% of participants reported a worsened perception of their oral health, and 27.8% indicated negative changes in their oral hygiene behaviors during the pandemic. These findings are consistent with previous studies, suggesting that restricted access to dental care, lockdowns, and increased fear of infection during the pandemic have been linked to negative perceptions and behaviors related to oral health.[16,17] Moreover, a study in Brazil observed a decrease in the perception of oral health problems during COVID-19, highlighting the broader global impact of the pandemic on oral health.[18] Interestingly, 10.2% of participants in our study reported positive changes in their oral hygiene behaviors during the pandemic, possibly due to increased awareness of infection risks and more time spent at home. Our study adds new evidence from a low-resource setting like Myanmar, where disruptions in healthcare access may be even more pronounced due to preexisting limited healthcare infrastructure and accessibility challenges.
This study identified that worsened oral health perceptions and negatively changed oral hygiene behaviors were significantly associated with factors such as a history of COVID-19 infection, higher levels of bleeding on probing, and depressive symptoms. Participants with a history of COVID-19 infection experienced negative changes in their self-perception of oral health or oral hygiene behaviors, indicating the substantial impact of COVID-19 experiences on these outcomes.[6,18,21] Additionally, a significant increase in bleeding on probing was observed among participants who reported a worsened perception of their oral health or negative changes in oral hygiene behaviors. These findings suggest that altered oral hygiene practices during the pandemic may have contributed to worsening periodontal conditions, in line with observations from other studies.[22,23] Furthermore, participants with worsened oral health perceptions had significantly higher median OHIP-14 scores, indicating poorer OHRQoL. It is hypothesized that limited access to dental care during the pandemic may have led to reduced awareness of oral health problems, thereby worsening self-perception of oral health and decreasing the perceived impact of these conditions on OHRQoL.[18]
There was a significant association between depressive symptoms and oral health perception, consistent with previous studies linking psychological distress to poor oral health outcomes.[24,25] Although participants with anxiety or stress symptoms also reported a worsened perception of their oral health, these associations were not statistically significant. These findings suggest that psychological factors, particularly depression, may play a crucial role in influencing self-perceptions of oral health during periods of crisis. However, it is notable that those who reported positive changes in oral hygiene behaviors had a higher prevalence of depressive symptoms (50.0%). In this context, it is assumed that individuals experiencing psychological distress may adopt more rigorous self-care practices, such as enhanced oral hygiene, as a coping mechanism. Previous studies have indicated that during prolonged infectious disease outbreaks like COVID-19, individuals may strive to maintain regular daily activities, including self-care routines, to reduce adverse psychological effects.[26,27] This complex relationship between mental health and oral hygiene behaviors highlights the need for integrated public health interventions addressing both psychological well-being and oral health.
The regression analysis demonstrated that changes in oral health perception and behaviors were initially associated with lower OHRQoL in the crude models, consistent with findings from a previous study that reported similar associations between negative oral health behaviors and increased risk of experiencing a poorer OHRQoL.[28] However, these associations became nonsignificant after adjusting for sociodemographic, psychological, and oral health factors, suggesting that other underlying factors such as age, income, education, COVID-19 infection, mental health, and oral health status play a significant role in determining these outcomes. Notably, COVID-19 infection requiring hospitalization remained significantly associated with OHRQoL, even after adjusting for other variables, emphasizing the unique effect of severe COVID-19 experiences on OHRQoL. Hospitalization, often associated with more serious illness and longer recovery periods, likely disrupts routine oral hygiene and exacerbates psychological distress.[6,29]
Prior research has identified sociodemographic and psychological variables as key determinants of OHRQoL.[9,30] These results highlight the importance of addressing psychological and socioeconomic factors in public health interventions aimed at improving oral health in low-resource settings like Myanmar. Integrating mental health support with oral health education could enhance the effectiveness of such programs, particularly by addressing the psychological distress that seems to influence oral health behaviors and perceptions during the pandemic. Given the association between psychological distress and oral health behaviors, future public health strategies should focus on holistic approaches that combine mental health support with targeted oral health interventions. By addressing both psychological and oral health needs, such strategies could better mitigate the adverse effects of the pandemic on OHRQoL and overall well-being. Given the limited resources and ongoing challenges in Myanmar, community-based interventions that incorporate mental health support, oral health education, and accessible dental services could be particularly beneficial. Future research studies should focus on longitudinal studies to further elucidate causal relationships between psychological factors, oral health behaviors, and OHRQoL over time. Expanding research to other regions in Myanmar would also help generalize these findings across different settings.
This study has certain limitations to be considered. The cross-sectional design limits causal inferences between changes in oral health perception, hygiene behaviors, and OHRQoL. Additionally, the exclusion of certain residents, such as institutionalized personnel, introduces the potential for cohort effect, limiting the generalizability of the findings to the broader Myanmar population. The use of self-reported data is another limitation, as it may be subject to recall bias and social desirability bias, potentially affecting the accuracy of the reported oral health behaviors and perceptions. Moreover, the study did not account for all possible confounding factors, such as dietary habits, access to oral health care before and during the pandemic, and the presence of chronic conditions, which could also influence oral health outcomes. Future longitudinal studies could help establish causal relationships and explore the long-term effects of the pandemic on oral health outcomes. Expanding research to other regions in Myanmar and similar settings would also provide a more comprehensive understanding of the pandemic’s impact on oral health across diverse contexts.
CONCLUSION
Within the limitations of this study, a significant proportion of participants reported a worsened perception of their oral health or negative changes in their oral hygiene behaviors during the pandemic. These changes were found to influence OHRQoL, but the mediating effects of other potential confounding factors, such as socioeconomic and psychological variables, should be carefully considered. Additionally, experiences of COVID-19 infection with hospitalization significantly impact OHRQoL. Our finding highlights the need for integrated public health strategies that address the interconnected psychological, socioeconomic, and health-related determinants influencing oral health outcomes, particularly in low-resource settings. Targeting these factors through comprehensive approaches could help mitigate the adverse effects of the pandemic on both oral health and overall well-being.
CONFLICTS OF INTEREST
There are no conflicts of interest.
AUTHORS CONTRIBUTIONS
KMT contributed to the conceptualization and design of the study, data collection, data cleaning and verification, data analyses, data interpretation, and drafting of the manuscript. WTL contributed to data collection, data interpretation, and revision of the manuscript. NK, ST, and HO were involved in the conceptualization and design of the study, data interpretation, and revision of the manuscript. All authors approved the final manuscript as submitted and agreed to be accountable for all aspects of the work.
ETHICAL POLICY AND INSTITUTIONAL REVIEW BOARD STATEMENT
The study protocol received approval from the Ethics Committee of Niigata University, Japan (approval number 2022-0248).
PATIENT DECLARATION OF CONSENT
Not applicable.
DATA AVAILABILITY STATEMENT
The datasets generated and/or analyzed during the current study are not publicly available due to the restrictions by the Ethics Committee of Niigata University, Niigata, Japan, to protect the participants’ privacy but are available from the corresponding author on reasonable request.
ACKNOWLEDGMENT
The authors would like to thank local authorities and personnel who assisted in the study for their generous support.
Funding Statement
This study was financially supported by a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (24K20102).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during the current study are not publicly available due to the restrictions by the Ethics Committee of Niigata University, Niigata, Japan, to protect the participants’ privacy but are available from the corresponding author on reasonable request.