Table 2.
Weighted estimates from regression (zero-inflated Poisson, logistic) to assess associations between dental insurance (no vs. yes) and dental caries indices, Grade 2 students in Calgary, 2009–10 and 2013/14
| Outcome variable | Rate ratio (RR) or odds ratio (OR) for effect of absence (vs presence) of dental insurance on dental caries outcomes (reference = 1.0) | ||
|---|---|---|---|
| 2009/10 | 2013/14 | Interaction term (Year X No dental insurance): RR or OR (95 % CI), p-value, (n) | |
| RR or OR (95 % CI), p-value, (n) | RR or OR (95 % CI), p-value, (n) | ||
| defta | RR = 1.05 (0.94 to 1.17), p = 0.40 (n = 528) | RR = 0.94 (0.86 to 1.03), p = 0.18 (n = 3164) | RR = 0.90 (0.78 to 1.04), p = .14 (n = 3692) |
| DMFTa | RR = 0.87 (0.65 to 1.16), p = 0.33 (n = 522) | RR = 1.56 (1.05 to 2.33), p = 0.03* (n = 3120) | RR = 1.80 (1.10 to 2.93), p = .02* (n = 3642) |
| 2 or more teeth (primary or permanent) with untreated decayb | OR = 1.76 (1.34 to 2.32), p < .001* (n = 522) | OR = 2.0 (1.57 to 2.53), p < .001* (n = 3120) | OR = 1.13 (0.81 to 1.58), p = .46 (n = 3642) |
deft number of decayed, missing, and filled primary teeth, DMFT number of decayed, missing, and filled permanent teeth, X multiplied by
*Statistically significant effect of no dental insurance (vs. dental insurance) on dental caries outcome
aZero-inflated Poisson regression
bLogistic regression (yes vs. no)