Characteristics of all respondents (n=4020), and prevalence estimates on the interest in GP advice on health protection (=yes) relative to the respondents’ characteristics; including results of regression models on associations between these characteristics and an interest in receiving GP advice (yes vs no)
| Total sample, n=4020 unweighted data % (n) | Interested in GP advice on health protection against heat=yes (vs no) | ||
| Weighted data, n=892 % (n, 95% CI) | Unweighted data OR* (95% CI) | ||
| Sex† | |||
| Male (reference) | 47.2 (1899) | 19.9 (368, 18.1 to 21.8) | 1 |
| Female | 52.8 (2121) | 26.6 (524, 24.7 to 28.6) | 1.39 (1.21 to 1.60) |
| Age in years† | |||
| 14–24 | 8.4 (337) | 14.1 (64, 11.1 to 17.7) | Continuous, per year 1.01 (1.01 to 1.01) |
| 25–39 | 21.9 (881) | 22.0 (183, 19.20 to 24.9) | |
| 40–59 | 32.3 (1300) | 20.1 (257, 17.9 to 22.4) | |
| 60–74 | 25.7 (1033) | 28.0 (243, 25.0 to 31.1) | |
| 75+ | 11.7 (469) | 38.2 (146, 33.3 to 43.2) | |
| Educational attainment‡ | |||
| High (reference) | 30.8 (1237) | 19.4 (231, 17.2 to 21.8) | 1 |
| Medium | 37.5 (1506) | 22.8 (326, 20.7 to 25.1) | 1.07 (0.89 to 1.28) |
| Low | 29.5 (1185) | 30.0 (314, 27.2 to 32.9) | 1.26 (1.04 to 1.51) |
| Household income/ۤ | |||
| High | 26.3 (1056) | 21.3 (213, 18.8 to 23.9) | Continuous, see¶ 0.91 (0.83 to 0.99) |
| Medium | 60.8 (2446) | 23.6 (556, 21.9 to 25.4) | |
| Low | 12.8 (513) | 27.1 (124, 23.1 to 31.4) | |
| Migration background† | |||
| No (reference) | 82.0 (3298) | 22.1 (663, 20.7 to 23.7) | 1 |
| Yes | 14.2 (570) | 25.9 (179, 22.7 to 29.3) | 1.62 (1.34 to 2.00) |
| Region of residence** | |||
| Rural area (reference) | 38.2 (1535) | 17.7 (279, 15.9 to 19.7) | 1 |
| Urban area | 41.9 (1686) | 28.4 (464, 26.2 to 30.7) | 2.17 (1.82 to 2.59) |
| Metropolitan area | 19.9 (799) | 24.7 (150, 21.3 to 28.3) | 2.07 (1.67 to 2.57) |
| Cohabitation†† | |||
| Other household (reference) | 62.0 (2494) | 21.6 (631, 20.1 to 23.1) | 1 |
| Single-person household | 38.0 (1526) | 29.4 (262, 26.4 to 23.5) | 1.20 (1.02 to 1.40) |
Data are presented as column percentages (number), row percentages (number, 95% CI), and as OR together with 95% CI around OR, statically significant results are highlighted in bold.
*Adjustment sets for regression analyses were derived by application of directed acyclic graphs (more details—including the graphs—have been published together with the analysis protocol https://osf.io/ycz7n).
†Univariate logistic regression model: no adjustment is necessary or possible—as it would produce a collider bias—to estimate the total effect of the independent variable on the outcome.
‡Multivariable logistic regression model adjusted for the variable: migration background.
§Multivariable logistic regression model adjusted for the variables: sex, age, educational attainment, migration background.
¶Entered as a continuous variable in regression analyses (range from 0 (€0 income) to 7 (€7000 or more).
**Multivariable logistic regression model for the variables: age, educational attainment, income per person, migration background, cohabitation.
††Multivariable logistic regression model for the variables: age, educational attainment, income per person, migration background, region of residence.
GP, general practitioner.