# Empirical Evidences for Urban Influences on Public Health in Hamburg
## Materials and Methods  
### Data Collected  
There are hardly any high-resolution data sets that link georeferenced health data with socio-demographic data in Hamburg. Thus, we conducted a household survey to collect primary data with a spatial resolution of urban blocks [77]. The variables for this data collection were derived from the UrbWellth model [30]. In addition, various health-related assessment tools were evaluated [32; 78; 79; 80; 81] to inform our questionnaire. When selecting the study areas in Hamburg (see Figure 5), small-scale differences in socio-economic burden [82], exposure to noise [83], and temperature [84] were taken into account [77]. Air quality was not considered since fine scale exposure cannot be observed without huge effort and there is no high-resolution data set available for air pollution in Hamburg. The survey areas were to cover the city's spatial extent and depict different district types derived from urban morphology, because urban morphology was used as a proxy for the structural quality of buildings, a general vulnerability assessment, and the local micro-climate [85; 86]. Questions about living conditions and assessments of the residential area (satisfaction with infrastructure and assets, future wishes), mobility behavior (transport used, duration, reasons for use), subjective health assessment [32; 87], and environmental pollution stressors were included. The final survey also included questions on socio-economic characteristics (education, income, occupation, age, etc.). The questionnaires comprised a total of 51 questions and were hand-delivered into residential mail boxes in 24 study areas. One person above 18 years old per household was asked to respond and return the survey by the postage-paid return envelope within two weeks. The questionnaires were distributed in November 2016 and April 2017; thus, a direct influence of extreme weather events (heat or cold wave) on the survey results could be avoided. The complete questionnaire is available from the authors. Each study area comprised between 150 and 400 households (6620 total). A total of 1081 surveys were returned. The participation rate of 16.24% was below the response rates for similar surveys, which can be explained by the lack of a reminder, itself resulting from a lack of resources. The differences between the survey areas are high (the response rates varied from 3.1% to 43.5%). In general, the highest response rates were achieved in areas of high socioeconomic status, and the lowest rates corresponded to those with low socioeconomic status. Most questions were answered using four- to six-point Likert scales (depending on the topic and the use of existing instruments, see Table 1). Nonetheless, some questions were answered on a binary scale or were open. Thus, not all of the survey's questions were used for the analyses in this paper. The questions pertaining to assessments of subjective health are based on the EQ-5D-5L, \"a standardized non-disease specific instrument to describe and value health-related quality of life\" [88] developed by EuroQol Group in 1987. The instrument is divided into the EQ-5D descriptive system which comprises the categories of mobility, self-care, daily activities, pain/discomfort, anxiety/depression and the EQ visual analogue scale (EQ VAS), marking self-related health on a scale (0-100). In the questionnaire, one question was assigned to each descriptive category, using EuroQol's levels ranging from \"no problems\" to \"extreme problems\" as potential answers (see Table 1). A further question refers to the EQ VAS by prompting participants to judge their current health on a scale from 0 to 100 from worst to best [89].