Street names constitute a rich source of data for quantitative analysis in social sciences. We gather and process street-name data from OpenStreetMap to create an accessible and readily analyzable street names database for the US and a large part of Europe. We also develop a web app to visualize the spatial distribution of street names and download the underlying data from users’ queries. These tools will continue to expand its geographic coverage by including additional countries.

This paper introduces a new web app to visualize the spatial distribution of street names and download the underlying dataset. First, we motivate the relevance of street-name data for researchers in social sciences. Second, we describe the data sources employed as well as the data cleaning process. Third, we present a web search app that allows to spatially visualize and download street-name data for Spain, with a time coverage spanning from 2001 to 2022

Background: The relationship between mobility and health has multiple dimensions, and the mobility model can be considered a public health intervention. Increasingly, mobility in cities is oriented towards incorporating sustainability criteria; however, there are many very diverse measures that cities carry out in terms of mobility and urban sustainability, and in many cases, these do not receive subsequent evaluation and/or study to analyse their effectiveness or impact. Currently, the literature does not offer any updated review of the measures applied in the different communities and countries. Aim: To carry out a panoramic review of the measures implemented in the last 5 years to analyse which ones report a greater effectiveness and efficiency in health. Results: After applying the exclusion criteria of the study, a total of 16 articles were obtained for evaluation. The measures applied in terms of sustainability are grouped into four subgroups and their subsequent evaluation and possible impact on public health is analysed. Conclusions: The present study found a large heterogeneous variety of sustainability measures in local settings around the world, which seem to reflect positive impacts on population health. However, subsequent evaluation of these measures is inconclusive in most cases. Further research and sharing across macro-communities are needed to establish universal criteria.

Severe housing deprivation rates in Spain have tripled in just four years, affecting 3.4% of the population in 2020, with a higher incidence among the low-income population (9.2%). Despite the social aspect of the problem, minimal research has been carried out in Spain on the effects that the various forms of housing deprivation have on health. This study analyzes the impact of housing deprivation on health outcomes, with the objective of achieving results that facilitate the creation of improved public policies. Microdata are used from the Living Conditions Survey carried out by the National Institute of Statistics for the period 2009–2019, and several multilevel logistic regression models are presented to control for possible regional differences. The results show that the elements with the greatest effect on objective health are noise, leaks and harmful temperatures in housing. In addition, environmental factors, such as pollution, neighborhood crime and the number of units in a given apartment building, can be added to the list. As a result, we conclude that there are certain structural and environmental elements in housing and the environment in which is located that have a more intense impact on objective health and on the subjective perception of a person’s state of health.