Parks are potential key urban assets for improved population health; however, their use is not equal among all social groups. Individual and contextual factors could influence residents' perceptions of parks and how they interact with and, eventually, benefit from them. The use of complementary methodologies provides a deeper understanding of the relationship between park use, physical activity (PA), and residents' perceptions. Thus, we designed a mixed-methods study to analyze differences in park use and PA, and the perceptions of parks as urban assets for PA. We selected six parks from three neighborhoods in Madrid (Spain) with different neighborhood socioeconomic status (NSES) for systematic social observation. We registered park users by age, PA level (low, medium, and high), gender, and NSES using the System for Observing Play and Recreation in Communities (SOPARC) audit tool adapted for iOS software (iSOPARC). We also conducted 37 semi-structured interviews and 29 focus groups to analyze residents' perceptions of parks as urban assets for PA in the same neighborhoods. We adopted a convergent-parallel design to analyze both quantitative and qualitative data, and to describe the convergence and divergence areas between them. Parks within the high-NSES were more visited, showing a higher proportion of people performing high PA (11.9%) as compared to residents of the middle (9.3%) and low-NSES (3.2%). Female visitors showed lower PA levels compared to men, especially for parks within high-NSES. The following issues were reported as influence urban park use and perceptions: park maintenance and area perception, works constraints, insecurity and crime, differential perceptions by age, and the availability of organized activities in the parks. Residents from high-NSES reported fewer barriers to park use compared to residents from the other areas, who reported limitations such as less leisure time due to job constrains or perceived insecurity in parks. Senior participants reported that having parks with organized activities and a design oriented towards different age-groups are valuable. Our study shows consistency between the fewer and less intense use of parks registered in the middle and low-NSES neighborhoods, and the more barriers for PA reported in this areas during the qualitative analysis. Mixed-methods provided an insight of the potential causes leading to the differences in park use and PA within cities, which is essential in terms of environmental justice and health equity. Thus, a mixed-methods comprehensive approach to public health problems can help designing public policies addressing relevant factors related to urban health inequities.

Our aim is to conduct an exploratory study to provide an in-depth characterization of a neighborhood’s social and physical environment in relation to cardiovascular health. A mixed-methods approach was used to better understand the food, alcohol, tobacco and physical activity domains of the urban environment. We conducted this study in an area of 16,000 residents in Madrid (Spain). We obtained cardiovascular health and risk factors data from all residents aged 45 and above using Electronic Health Records from the Madrid Primary Health Care System. We used several quantitative audit tools to assess: the type and location of food outlets and healthy food availability; tobacco and alcohol points of sale; walkability of all streets and use of parks and public spaces. We also conducted 11 qualitative interviews with key informants to help understanding the relationships between urban environment and cardiovascular behaviors. We integrated quantitative and qualitative data following a mixed-methods merging approach. Electronic Health Records of the entire population of the area showed similar prevalence of risk factors compared to the rest of Madrid/Spain (prevalence of diabetes: 12 %, hypertension: 34 %, dyslipidemia: 32 %, smoking: 10 %, obesity: 20 %). The food environment was very dense, with many small stores (n = 44) and a large food market with 112 stalls. Residents highlighted the importance of these small stores for buying healthy foods. Alcohol and tobacco environments were also very dense (n = 91 and 64, respectively), dominated by bars and restaurants (n = 53) that also acted as food services. Neighbors emphasized the importance of drinking as a socialization mechanism. Public open spaces were mostly used by seniors that remarked the importance of accessibility to these spaces and the availability of destinations to walk to. This experience allowed testing and refining measurement tools, drawn from epidemiology, geography, sociology and anthropology, to better understand the urban environment in relation to cardiovascular health.

Across Europe, excess body weight rates are particularly high among children and adolescents living in Southern European contexts. In Spain, current food policies appeal to voluntary self-regulation of the food industry and parents’ responsibility. However, there is no research (within Spain) assessing the food environment surrounding schools. We examined the association between neighborhood-level socioeconomic status (NSES) and the spatial access to an unhealthy food environment around schools using both counts and distance measures, across the city of Madrid. We conducted a cross-sectional study citywide (n = 2443 census tracts). In 2017, we identified all schools (n = 1321) and all food retailers offering unhealthy food and beverages surrounding them (n = 6530) using publicly available data. We examined both the counts of retailers (within 400 m) and the distance (in meters) from the schools to the closest retailer. We used multilevel regressions to model the association of neighborhood-level socioeconomic status (NSES) with both measures, adjusting both models for population density. Almost all schools (95%) were surrounded by unhealthy retailers within 400 m (median = 17 retailers; interquartile range = 8–34). After adjusting for population density, NSES remained inversely associated with unhealthy food availability. Schools located in low-NSES areas (two lowest quintiles) showed, on average, 29% (IRR (Incidence Rate Ratio) = 1.29; 95% CI (Confidence Interval) = 1.12, 1.50) and 62% (IRR = 1.62; 95% CI = 1.35, 1.95) more counts of unhealthy retailers compared with schools in middle-NSES areas (ref.). Schools in high-NSES areas were farther from unhealthy food sources than those schools located in middle-NSES areas (β = 0.35; 95% CI = 0.14, 0.47). Regulating the school food environment (within and beyond school boundaries) may be a promising direction to prevent and reduce childhood obesity.