Annex Table 1.

Description of the regression models for the calculation of the adjusted proportions/mean values

Source: Own table

Independent control variables used in all estimation models: federal state (bula [Baden-Württemberg, …, Thuringia]), age (agegrp [15 to 29 years, 30 to 44 years, 45 to 64 years, 65 to 79 years, ≥ 80 years]), sex (sex [male, female]), CASMIN educational classification (edu [low, medium, high]), and the interactions between age, sex and CASMIN educational classification:

Variablen ≙ bula + agegrp + sex + edu + agegrp · sex + agegrp · edu + sex · edu

Monthly adjusted proportions or averages were calculated by adding the interview month (intmo [April 2019, …, September 2020]) as a categorical variable to the basic variables:

Model 1: health indicator = variables + intmo

The polynomial of degree four of the interview week (intwo [2019: calendar week 14 to 2020: calendar week 36]) was used to represent a smoothed temporal course:

Model 2: health indicator = variables + intwo + intwo2 + intwo3 + intwo4

A binary variable (period [period 2019, period 2020]) has been added to the model estimate for comparing the periods of the years 2019 and 2020 to distinguish the periods:

Model 3: health indicator = variables + period