Table 4.
Parameter estimates for immigrant versus native-born populations in the individual countries and the pooled 11 country sample with age and gender controlled: model M1
| Country | Physician visits |
GP visits |
Hospital visits |
|||||
|---|---|---|---|---|---|---|---|---|
| Negative binomial |
Negative binomial |
Poisson |
Logit |
|||||
| β | SE | β | SE | β | SE | β | SE | |
| Austria | 0.07 | (0.092) | −0.07 | (0.092) | 0.06 | (0.222) | 0.68** | (0.287) |
| Belgium | 0.11* | (0.061) | 0.16** | (0.062) | −0.21 | (0.219) | −0.52* | (0.312) |
| Denmark | 0.32*** | (0.150) | 0.47*** | (0.141) | 0.65*** | (0.213) | −0.04 | (0.359) |
| France | 0.12*** | (0.045) | 0.08* | (0.044) | 0.03 | (0.191) | 0.07 | (0.249) |
| Germany | 0.10** | (0.047) | 0.14*** | (0.047) | 0.25* | (0.141) | 0.22 | (0.184) |
| Greece | 0.21 | (0.148) | 0.07 | (0.167) | −0.09 | (0.470) | −0.72 | (0.641) |
| Italy | −0.03 | (0.204) | −0.05 | (0.210) | −1.54 | (0.962) | −4.30 | (21.510) |
| Netherlands | 0.22** | (0.090) | 0.36*** | (0.083) | 1.06*** | (0.231) | 0.60** | (0.300) |
| Spain | −0.24 | (0.160) | −0.20 | (0.165) | −0.49 | (0.426) | −1.21** | (0.568) |
| Sweden | 0.35*** | (0.071) | 0.21*** | (0.072) | 0.08 | (0.238) | −0.07 | (0.281) |
| Switzerland | 0.53*** | (0.104) | 0.56*** | (0.105) | 1.55*** | (0.236) | 0.95** | (0.378) |
| Total | 0.15*** | (0.025) | 0.12*** | (0.025) | 0.18*** | (0.067) | −0.05 | (0.084) |
| Pseudo-R2 | 49.87% | 49.66% | 50.04% | |||||
M1 age and gender controlled. The model is estimated in each country and in the entire sample. For hospital visits, each column contains the results for the ZIP, the Poisson model and the logit model estimations, using the nlmixed procedure in SAS. A positive parameter in the logit equation means a higher probability of not being a hospital user
Source SHARE data, 2004 (individuals 50+)
Significance levels *** P < 0.01;
**
P < 0.05;
*
P < 0.1. Standard errors in parentheses