| Literature DB >> 35148740 |
Jeremiah Schmidt1, Boyen Huang2.
Abstract
BACKGROUND: Erosive tooth wear has significant impacts on oral and general health. This study aimed to measure the awareness of dental erosion to establish the relationships among sociodemographic factors, awareness and knowledge of dental erosion, and beverage consumption behaviours, in a sample of university students in Australia.Entities:
Keywords: Awareness; Beverage consumption; Dental erosion; Health literacy; Tooth erosion; Tooth wear; University students
Mesh:
Year: 2022 PMID: 35148740 PMCID: PMC8832794 DOI: 10.1186/s12903-022-02065-w
Source DB: PubMed Journal: BMC Oral Health ISSN: 1472-6831 Impact factor: 2.757
Awareness of dental erosion by age, academic field and geographic remoteness (n = 418)
| Aware [n (%)] | Not aware [n (%)] | All [n (%)] | Unadjusteda OR (95% CI) | Adjustedb OR (95% CI) | |||
|---|---|---|---|---|---|---|---|
| 18–20 | 85 (93.4) | 6 (6.6) | 91 (21.8) | 0.927 (0.897, 0.959) | < 0.001* | 0.933 (0.896, 0.971) | 0.001* |
| 21–30 | 241 (95.3) | 12 (4.7) | 253 (60.5) | ||||
| 31–40 | 39 (84.8) | 7 (15.2) | 46 (11.0) | ||||
| 41–72 | 20 (71.4) | 8 (28.6) | 28 (6.7) | ||||
| Dentistry | 104 (99.0) | 1 (1.0) | 105 (25.1) | 1 | 1 | ||
| Oral Health | 21 (100.0) | 0 (0) | 21 (5.0) | 15,533,411.95 (0, ∞) | 0.998 | 15,769,075.71 (0, ∞) | 0.998 |
| Clinical Science | 31 (96.9) | 1 (3.1) | 32 (7.7) | 0.298 (0.018, 4.905) | 0.397 | 0.338 (0.020, 5.638) | 0.450 |
| Pharmacy | 18 (90.0) | 2 (10.0) | 20 (4.8) | 0.087 (0.007, 1.005) | 0.050 | 0.080 (0.007, 0.934) | 0.044* |
| Medical Science | 48 (90.6) | 5 (9.4) | 53 (12.7) | 0.092 (0.010, 0.812) | 0.032* | 0.205 (0.021, 1.984) | 0.171 |
| Paramedicine | 29 (85.3) | 5 (14.7) | 34 (8.1) | 0.056 (0.006, 0.496) | 0.010* | 0.060 (0.007, 0.534) | 0.012* |
| Physiotherapy | 96 (90.6) | 10 (9.4) | 106 (25.4) | 0.092 (0.012, 0.735) | 0.024* | 0.098 (0.012, 0.782) | 0.028* |
| Science | 38 (80.9) | 9 (19.1) | 47 (11.2) | 0.041 (0.005, 0.331) | 0.003* | 0.087 (0.010, 0.763) | 0.028* |
| Australian major city | 152 (92.1) | 13 (7.9) | 165 (39.5) | 1 | |||
| Australian regional and remote | 223 (92.5) | 18 (7.5) | 241 (57.6) | 1.060 (0.504, 2.227) | 0.879 | 0.309 | |
| Overseas | 10 (83.3) | 2 (16.7) | 12 (2.9) | 0.428 (0.085, 2.162) | 0.304 | 0.355 | |
*p < 0.05
aOdds ratio in the univariate regression model
bOdds ratio in the multivariate regression model
cAge calculated as years in statistical analysis—age ranges presented in the table to reduce the table length
Knowledge score of dental erosion by age, academic field and geographic remoteness (n = 418)
| Knowledge score of dental erosion [n (%)] | Unadjusteda B coefficient | Adjustedb B coefficient | ||||||
|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | |||||
| 18–20 | 6 (6.6) | 68 (74.7) | 12 (13.2) | 5 (5.5) | − 0.012 (− 0.021, − 0.004) | 0.004* | 0.006 (− 0.001, 0.012) | 0.095 |
| 21–30 | 14 (5.5) | 175 (69.2) | 40 (15.8) | 24 (9.5) | ||||
| 31–40 | 7 (15.2) | 32 (69.6) | 3 (6.5) | 4 (8.7) | ||||
| 41–72 | 5 (17.9) | 22 (78.6) | 1 (3.6) | 0 (0) | ||||
| Dentistry | 1 (1.0) | 40 (38.1) | 35 (33.3) | 29 (27.6) | 0.883 (0.754, 1.011) | < 0.001* | 0.863 (0.746, 0.980) | < 0.001* |
| Oral Health | 0 (0) | 15 (71.5) | 2 (9.5) | 4 (19.0) | 0.275 (− 0.030, 0.579) | 0.071 | 0.420 (0.196, 0.645) | < 0.001* |
| Clinical Science | 2 (6.3) | 28 (87.4) | 2 (6.3) | 0 (0) | − 0.233 (− 0.483, 0.017) | 0.068 | 0.861 | |
| Pharmacy | 2 (10.0) | 18 (90.0) | 0 (0) | 0 (0) | − 0.331 (− 0.642, − 0.020) | 0.037* | 0.634 | |
| Medical Science | 4 (7.5) | 48 (90.6) | 1 (1.9) | 0 (0) | − 0.311 (− 0.510, − 0.113) | 0.002* | 0.292 | |
| Paramedicine | 6 (17.6) | 28 (82.4) | 0 (0) | 0 (0) | − 0.426 (− 0.667, − 0.186) | 0.001* | 0.250 | |
| Physiotherapy | 8 (7.5) | 87 (82.1) | 11 (10.4) | 0 (0) | − 0.251 (− 0.402, − 0.099) | 0.001* | 0.073 | |
| Science | 9 (19.2) | 33 (70.2) | 5 (10.6) | 0 (0) | − 0.338 (− 0.547, − 0.130) | 0.002* | 0.794 | |
| Australian major city | 14 (8.5) | 104 (63.0) | 28 (17.0) | 19 (11.5) | 0.165 (0.029, 0.301) | 0.017* | 0.192 | |
| Australian regional & Remote | 15 (6.2) | 187 (77.6) | 26 (10.8) | 13 (5.4) | − 0.146 (− 0.280, − 0.012) | 0.033* | 0.192 | |
| Overseas | 3 (25.0) | 6 (50.0) | 2 (16.7) | 1 (8.3) | − 0.136 (− 0.536, 0.264) | 0.504 | − 0.420 (− 0.717, − 0.124) | 0.006* |
| Aware | 3 (0.8) | 293 (76.1) | 56 (14.5) | 33 (8.6) | 1.188 (0.968, 1.407) | < 0.001* | 0.983 (0.796, 1.170) | < 0.001* |
| Not aware | 29 (87.9) | 4 (12.1) | 0 (0) | 0 (0) | ||||
*p < 0.05
aUnstandardized B coefficient in the univariate regression model
bUnstandardized B coefficient in the multivariate regression model
cAge calculated as years in statistical analysis—age ranges presented in the table to reduce the table length
Fig. 1Beverages perceived to be acidic by the percentages of the participants (n = 418)
Frequency distribution of correctly identified acidic beverages mentioned in Fig. 1, also known as the ID score in this study (n = 418)
| Identified acidic beverages (ID) score [n (%)] | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | |
| 18–20 | 0 (0) | 5 (5.5) | 4 (4.4) | 8 (8.8) | 7 (7.7) | 7 (7.7) | 13 (14.3) | 14 (15.3) | 11 (12.1) | 9 (9.9) | 7 (7.7) | 6 (6.6) |
| 21–30 | 3 (1.2) | 7 (2.8) | 11 (4.3) | 7 (2.8) | 20 (7.9) | 33 (13.0) | 24 (9.5) | 27 (10.7) | 26 (10.3) | 29 (11.5) | 30 (11.8) | 36 (14.2) |
| 31–40 | 1 (2.2) | 3 (6.5) | 2 (4.4) | 0 (0) | 4 (8.7) | 2 (4.4) | 4 (8.7) | 6 (13.0) | 8 (17.4) | 7 (15.2) | 3 (6.5) | 6 (13.0) |
| 41–72 | 0 (0) | 3 (10.7) | 2 (7.1) | 7 (25.0) | 3 (10.7) | 2 (7.1) | 0 (0) | 2 (7.1) | 1 (3.6) | 4 (14.3) | 2 (7.2) | 2 (7.2) |
| Total | 4 (1.0) | 18 (4.3) | 19 (4.6) | 22 (5.3) | 34 (8.1) | 44 (10.5) | 41 (9.8) | 49 (11.7) | 46 (11.0) | 49 (11.7) | 42 (10.0) | 50 (12.0) |
aAge calculated as years in statistical analysis—age ranges presented in the table to reduce the table length
Frequency distribution of the number of preferred beverage types in the sample (n = 418)
| Number of preferred beverage types [n (%)] | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |
| 18–20 | 14 (15.4) | 17 (18.7) | 31 (34.0) | 16 (17.6) | 4 (4.4) | 6 (6.6) | 1 (1.1) | 2 (2.2) | 0 (0) |
| 21–30 | 33 (13.1) | 63 (24.9) | 76 (30.0) | 45 (17.8) | 15 (5.9) | 12 (4.7) | 6 (2.4) | 1 (0.4) | 2 (0.8) |
| 31–40 | 4 (8.7) | 13 (28.3) | 15 (32.6) | 8 (17.4) | 2 (4.3) | 4 (8.7) | 0 (0) | 0 (0) | 0 (0) |
| 41–72 | 1 (3.6) | 9 (32.1) | 6 (21.4) | 8 (28.6) | 4 (14.3) | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| Total | 52 (12.4) | 102 (24.4) | 128 (30.6) | 77 (18.4) | 25 (6.0) | 22 (5.3) | 7 (1.7) | 3 (0.7) | 2 (0.5) |
aAge calculated as years in statistical analysis—age ranges presented in the table to reduce the table length
Frequency distribution of the quantity of beverage consumption in the sample (n = 418)
| Cups of beverages consumed per day [n (%)] | ||||||
|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 | |
| 18–20 | 43 (47.2) | 15 (16.5) | 20 (22.0) | 10 (11.0) | 2 (2.2) | 1 (1.1) |
| 21–30 | 103 (40.7) | 45 (17.8) | 57 (22.5) | 29 (11.5) | 11 (4.3) | 8 (3.2) |
| 31–40 | 14 (30.4) | 8 (17.4) | 13 (28.3) | 6 (13.0) | 1 (2.2) | 4 (8.7) |
| 41–72 | 5 (17.8) | 4 (14.3) | 7 (25.0) | 4 (14.3) | 1 (3.6) | 7 (25.0) |
| Total | 165 (39.5) | 72 (17.2) | 97 (23.2) | 49 (11.7) | 15 (3.6) | 20 (4.8) |
aAge calculated as years in statistical analysis—age ranges presented in the table to reduce the table length
Beverage consumption patterns by age, academic fields, geographic remoteness, awareness of dental erosion, knowledge score and ID score (n = 418)
| High-risk pattern [n (%)] | Low-risk pattern [n (%)] | Unadjusteda OR (95% CI) | Adjustedb OR (95% CI) | |||
|---|---|---|---|---|---|---|
| 18–20 | 31 (34.1) | 60 (65.9) | 1.059 (1.029, 1.089) | < 0.001* | 1.035 (1.004, 1.068) | 0.029* |
| 21–30 | 111 (43.9) | 142 (56.1) | ||||
| 31–40 | 27 (58.7) | 19 (41.3) | ||||
| 41–72 | 22 (78.6) | 6 (21.4) | ||||
| Dentistry | 31 (29.5) | 74 (70.5) | 1 | 1 | ||
| Oral Health | 5 (23.8) | 16 (76.2) | 0.746 (0.251, 2.215) | 0.598 | 0.694 (0.232, 2.073) | 0.513 |
| Clinical Science | 18 (56.3) | 14 (43.7) | 3.069 (1.359, 6.931) | 0.007* | 3.376 (1.473, 7.735) | 0.004* |
| Pharmacy | 11 (55.0) | 9 (45.0) | 2.918 (1.100, 7.740) | 0.031* | 3.620 (1.337, 9.800) | 0.011* |
| Medical Science | 38 (71.7) | 15 (28.3) | 6.047 (2.914, 12.550) | < 0.001* | 5.504 (2.530, 11.973) | < 0.001* |
| Paramedicine | 17 (50.0) | 17 (50.0) | 2.387 (1.081, 5.272) | 0.031* | 2.824 (1.245, 6.409) | 0.013* |
| Physiotherapy | 40 (37.7) | 66 (62.3) | 1.447 (0.814, 2.570) | 0.208 | 1.688 (0.928, 3.071) | 0.086 |
| Science | 31 (66.0) | 16 (34.0) | 4.625 (2.218, 9.643) | < 0.001* | 3.969 (1.806, 8.722) | 0.001* |
| Australian major city | 71 (43.0) | 94 (57.0) | 1 | |||
| Australian regional and remote | 114 (47.3) | 127 (52.7) | 1.188 (0.798, 1.771) | 0.396 | 0.622 | |
| Overseas | 6 (50.0) | 6 (50.0) | 1.324 (0.410, 4.278) | 0.639 | 0.412 | |
| Aware | 176 (45.7) | 209 (54.3) | 1 | |||
| Not aware | 15 (45.5) | 18 (54.5) | 0.990 (0.485, 2.021) | 0.977 | 0.161 | |
| 1.2 ± 0.6d | 1.3 ± 0.8d | 0.814 (0.613, 1.080) | 0.153 | 0.104 | ||
| 7.0 ± 2.7d | 6.7 ± 3.1d | 1.030 (0.965, 1.100) | 0.375 | 1.091 (1.012, 1.176) | 0.022* | |
*p < 0.05
aOdds ratio in the univariate regression model
bOdds ratio in the multivariate regression model
cAge calculated as years in statistical analysis—age ranges presented in the table to reduce the table length
dMean ± standard deviation