| Literature DB >> 16817952 |
Jamil David1, Anne N Astrøm, Nina J Wang.
Abstract
BACKGROUND: Oral health status in India is traditionally evaluated using clinical indices. There is growing interest to know how subjective measures relate to outcomes of oral health. The aims of the study were to assess the prevalence and correlates of self-reported state of teeth in 12-year-old schoolchildren in Kerala, India.Entities:
Year: 2006 PMID: 16817952 PMCID: PMC1559687 DOI: 10.1186/1472-6831-6-10
Source DB: PubMed Journal: BMC Oral Health ISSN: 1472-6831 Impact factor: 2.757
Distribution of 12-year-old schoolchildren according to dependent and independent variables.
| Dependent variable | Categories | Number (%) |
| State of teeth | Good | 644 (77) |
| Bad | 194 (23) | |
| Independent variables | ||
| Gender | Girls | 359 (43) |
| Boys | 479 (57) | |
| Place of residence | Rural | 616 (74) |
| Urban | 222 (26) | |
| Socio-economic status | Poor | 212 (25)* |
| Middle class | 585 (70) | |
| High class | 40 (5) | |
| School performance | Good | 681 (81) |
| Poor | 157 (19) | |
| Bleeding gums | No | 143(17) |
| Yes | 695 (83) | |
| Bad breath | No | 547 (65) |
| Yes | 291 (35) | |
| Toothache | No | 266 (32)* |
| Yes | 571 (68) | |
| Food impaction | No | 239 (29) |
| Yes | 599 (71) | |
| Dental visits | Never | 504 (60) |
| Yes | 334 (40) | |
| Satisfied with appearance of teeth | Satisfied | 526 (63) |
| Dissatisfied | 312 (37) | |
| Oral health knowledge | Good | 487 (59)* |
| Poor | 344 (41) | |
| Caries experience | DMFT = 0 | 612 (73) |
| DMFT > 0 | 226 (27) | |
| Oral hygiene index | Good | 681 (81) |
| Fair | 157 (19) | |
| Anterior teeth fracture | No | 787 (94) |
| Yes | 51 (6) | |
* The totals of the numbers in the categories do not add up to 838 because of missing data
Number (%) of 12-year-old schoolchildren with caries experience and self-reported bad state of teeth according to area of residence and gender.
| DMFT > 0 n (%) | Bad state of teeth n (%) | |
| Urban | ||
| all | 74 (33)* | 63 (28)* |
| girls | 34 (38) | 35 (27) |
| boys | 40 (30) | 28 (31) |
| Rural | ||
| all | 152 (25) | 131 (21) |
| girls | 66 (25) | 86 (25)† |
| boys | 86 (25) | 45 (17) |
* Chi-square test, p < 0.05 (comparison between urban and rural)
† Chi-square test, p < 0.05 (comparison between girls and boys in rural area)
Number (%) of schoolchildren who reported the state of teeth to be bad by socio-behavioural factors, non-clinical and clinical oral health indicators. Cross-tabulation analysis (chi-square) and multiple logistic regression with odds ratios (OR) and 95% confidence interval (CI).
| Unadjusted | Adjusted | |||
| Independent variables | Bad state of teeth n (%) | OR | 95% CI | R2 |
| Girls | 73 (20) | 1 | ||
| Boys | 121 (25) | 1.1 | 0.8–1.6 | |
| Rural | 131 (21)* | 1 | ||
| Urban | 63 (28) | 1.3 | 0.9–2.0 | |
| Socio-economic status – Poor | 52 (25) | 1 | ||
| Socio-economic status – Middle class | 133 (23) | 0.8 | 0.5–1.2 | |
| Socio-economic status – High class | 9 (22.5) | 0.3 | 0.4–2.4 | |
| School performance – Good | 130 (19)* | 1 | ||
| School performance – Poor | 64 (41) | |||
| Bleeding gums – No | 135 (21)* | 1 | ||
| Bleeding gums – Yes | 59 (29) | 1.1 | 0.7–1.7 | |
| Bad breath – No | 87 (16)* | 1 | ||
| Bad breath – Yes | 107 (37) | |||
| Toothache – No | 55 (21) | |||
| Toothache – Yes | 139 (24) | |||
| Food impaction – No | 34 (14)* | 1 | ||
| Food impaction – Yes | 160 (27) | |||
| Dental visits – Never | 97 (19)* | 1 | ||
| Dental visits – Yes | 97 (29) | |||
| Oral health knowledge – Good | 102 (21) | |||
| Oral health knowledge – Poor | 90 (26) | |||
| Satisfied with appearance of teeth | 68 (13)* | 1 | ||
| Dissatisfied with appearance of teeth | 126 (40) | |||
| DMFT = 0 | 120 (20)* | 1 | ||
| DMFT > 0 | 74 (32) | |||
| Oral hygiene – Good | 147 (22)* | 1 | ||
| Oral hygiene – Fair | 47 (30) | 1.4 | 0.9–2.3 | |
| Anterior trauma – no | 182 (23) | |||
| Anterior trauma – yes | 12 (24) | |||
* p < 0.05
All variables in Step 1 and other statistically significant bivariate variables were entered into the multiple logistic regression analysis