Multivariate logistic regression was then run to select among these 11 individual variables those that were associated with the individual deprivation indicator in the French EU–SILC, in which individuals are sampled all over the country. As these selected variables were also available in the census data, but at the IRIS level, we were able to build an ecological index by using these variables.
One variable was removed (‘no exclusive use of bath or shower’; OR=1.13; 95% CI 0.88 to 1.44; p=0.3376). This left 10 variables for the EDI (table 5): ‘overcrowding’, ‘no access to a system of central or electric heating’, ‘non-owner’, ‘unemployment’, ‘foreign nationality’, ‘no access to a car’, ‘unskilled worker-farm worker’, ‘household with six or more persons’, ‘low level of education (less than first stage of secondary-level education)’, ‘single-parent household’. Table 5 shows the significance of each variable and its adjusted coefficient β with 95% CI.