What is the cross-sectional association of geospatially derived walkability with walking for leisure and transport?

Abstract

Background

Built environments have been shown to shape active living behaviours, including walking. However, this literature is drawn predominantly from Europe and North America. This study aimed to create a geospatially derived city-wide walkability index and further investigate the association with walking in Belo Horizonte, Brazil.

Methodology

A cross-sectional analysis was conducted using data from participants in the 2014-15 MOVE-SE study in Belo Horizonte. A walkability index was created at the census tract level, which included net residential density, land use mix, and street connectivity, using ArcGIS software. Walking for leisure and transportation was self-reported via the International Physical Activity Questionnaire. Covariates such as sociodemographic characteristics, health indicators, and neighbourhood context were measured. A multilevel negative binomial regression was employed, incorporating confounders across five combined models with sequential addition of covariate groups. All statistical analyses were conducted in R software with a significance threshold of 5%.

Results

The study included 1,372 adults aged 18 years and older, with a female majority of 60.5%, a median age of 41, and 45.9% completed at most primary schooling. The family income for 63.7% ranged between one to three times the minimum wage. Self-rated health was considered good by 64.7% of participants, and the median Body Mass Index (BMI) was 26.2 kg/m2. Regarding neighbourhood context, the median length of residence was 15 years, per capita monthly income was US$175, and the average land slope was 8.2%. Participants reported a median of 180 minutes per week (interquartile range: 120 – 250) for walking for leisure and transportation. The median walkability index was -0.51 (interquartile range: -1.40 – 1.21). After adjusting for confounders, the final model indicated a positive association between the walkability index and walking for leisure (IRR: 1.33; CI_95%:1.32-1.35; p < 0.001) and transportation (IRR: 1.22; CI_95%:1.20-1.24; p < 0.001).

Discussion

The findings demonstrate a positive association between higher levels of walkability and increased walking behaviours in various contexts. It underscores the importance of urban planning, design, and policy interventions tailored to local environments to promote walkability, reduce car dependency, and facilitate healthier lifestyles as part of everyday living.

Background

Increasingly, urban spaces are recognized as important determinants of health [1]. Changing the social, natural, and physical environment in these spaces can promote healthy behaviour, especially in low-middle-income countries [2]. Even though each city has local demands and priorities [3], it is crucial to have a minimum of infrastructure, safety, and access to services so that people can insert healthy habits into their daily routines [4]. Environmental sustainability may make cities people-centred, enabling activity-friendly living [5–8], leading to a healthier population, thus, generating less cost to public health systems [9]. Nevertheless, isolated research indicators may not capture the complex health-environment interplay [10,11].

Urban attributes differently affect health outcomes [12]. Walkability, green spaces, and other amenities for health and wellbeing [13], high residential density, high density of public transport stops, presence of urban facilities, traffic safety, pedestrian infrastructure, the density of land use mix [5,6] the vicinity of parks and air quality are some of the features that have been associated with health behaviours or outcomes in urban dwellers, directly and indirectly impacting on the decrease in morbidities throughout life [14]. Physical activity opportunities are greatest in areas with connected streets and safe sidewalks [15], suggesting that walkable infrastructure promotes community health [16]. It indicates that contextual dimensions impacting physical activity must be considered in public policy promotion, incorporating people’s perceptions and features of the built, natural, and social environment where they live [17].

Geospatially derived walkability macroscale measures are utilized globally [18], affecting behaviours like sedentary lifestyles [19], mental health [20], and physical activity [21]. Frank et al. (2010) proposed a widely used walkability approach. Despite the considerable range of definitions, it can be described as how walk-friendly an urban place is, ensuring pedestrian attractiveness, comfort, and safety, with efficient access to varied, convenient, and desired destinations [22]. It harmonizes sustainable living with individual needs [23].

In addition to contributing 33-68% of total physical activity [24], active travel can benefit communities, especially in large cities, improving micro-mobility, and air quality, stimulating interaction between neighbours and access to local commerce, and reducing daily journey time [25]. However, while the prevalence of walking is 26% in the United Kingdom [26], as per the latest U.S. household travel survey data, with only 10% of all trips being done on foot, merely 14.3% of Americans achieve at least 10 minutes of walking, covering nearly 147 kilometres, in 37 hours, annually [27]. The median prevalence of walking in Latin America and the Caribbean is quite similar, with just 15% of the population undertaking any active travel [28]. For decades, city planning and management have been centred more on the automobile than pedestrians, providing a system that makes driving convenient and presents obstacles to walking, such as long distances to access destinations, poor quality sidewalks, and urban insecurity. Nevertheless, a paradigm shift is urgent, as the evidence demonstrates that people who live in the most active-friendly neighbourhoods are involved in up to 90 minutes more walking per week than those whose environments do not support active living [29].

Addressing the global yet diverse urban challenges requires tailored solutions [17,30]. In Brazil, unstable walking levels in cities reflect environmental and policy issues [31]. Therefore, to guide policymakers in developing strategies to promote active mobility policies, this study aimed to create a city-wide walkability index based on geospatially derived urban environment macroscale features and further investigate the association of the walkability index with walking for leisure and transportation in Belo Horizonte, Brazil.

Methods

Study design and area

This cross-sectional study was led by the Observatory for Urban Health in Belo Horizonte, from the Federal University of Minas Gerais (OSUBH/UFMG), Brazil, in collaboration with the Global Diet and Activity Research (GDAR) network. The datasets used are mixed primary and secondary sources in Belo Horizonte, the capital of the Minas Gerais state, located in the Southeast region of Brazil. The city has 2.5 million inhabitants and is Brazil’s sixth-largest urban area and the fifth-largest Gross Domestic Product among Brazilian cities [32]. The Municipal Human Development Index (MHDI) for the municipality is 0.810, placing it in the very high human development category. This is due to strong performance in longevity (0.856), income (0.841), and education (0.737). However, the municipality has notable income inequality, as indicated by a Gini index of 0.54 (IBGE 2010).

Sampling, data gathering, and ethical issues

The primary data came from a cross-sectional study conducted by OSUBH/UFMG carried out between November 2014 and March 2015, entitled MOVE-SE, Lifestyles and Health Project. The home-based health survey included as sample, resident population of ≥ 18 years old in a geographical area served by a health promotion programme. In a face-to-face interview, the data were gathered using a standardized questionnaire that assessed topics related to the individual, home-related and neighbourhood characteristics, as well as aspects related to participation in the program and health service use. The project was approved by the Research Ethics Committee of the Federal University of Minas Gerais (process number CAAE: 26152814.2.0000.5149 of May 8^th, 2014), in which all participants signed an informed written consent form. More details may be obtained in a previous publication [33,34].

Construction of a walkability index

To navigate the complex array of urban environment indicators that impact health, a macroscale index measure was employed [11]. The walkability index was built comprising three combined indicators: land use mix, intersection density, and net residential density, converted into a standard deviation unit using the Z-score, allowing for comparison on a common scale [35]. The geographical unit of analysis was the census tract – a continuous area delineated for effective data gathering, characterized by its manageability in size and population [32]. The ArcGIS software (v.10.5 for Desktop, Environment Systems Research Institute, Redlands-CA, USA) was used to harmonize and analyse data, which are publicly available on the website of different official sources, such as Municipality of Belo Horizonte (BHMap), Brazilian Institute of Geography and Statistics (IBGE), National Classification of Economic Activities (CNAE), and Open Street Map (OSM). For ease of understanding, Fig 1 illustrates the spatial distribution of the index across the city. It labels the extremities of the index spectrum as either “car-dependent” or “walkable” [14]. The “walkable” category represents areas that scored highest on the index. More detailed information is at the supplementary material C1 and F1.

[Figure omitted. See PDF.]

Exposure variable

Once the city-wide walkability index was established, individual MOVE-SE project participants were assigned an index score based on their residence’s census tract location. This index, treated as continuous data following the literature [36], was applied to 246 out of 3,933 census tracts.

Outcome variables

As part of the primary dataset, self-reported physical activity, collected using the long version of the International Physical Activity Questionnaire (IPAQ), was obtained from the MOVE-SE project [33,34]. They included frequency (days/week) and duration (minutes/day) of walking for leisure and transportation [37–39]. The questionnaire used was based on the structure and content of a Brazilian national surveillance, which has validity and reproducibility established [40]. Because the data presented a non-normal distribution, the outcomes were kept continuous for the analysis, considering minutes per week as the unit of measurement [41].

Covariates

Individual covariates were used to describe the sample and adjust the analytical models. The sociodemographic data were: a) sex, male and female; b) age, in years; c) schooling, classified as “up to primary”, “secondary”, and “university”; d) family income, based on the minimum wage (MW) in Brazilian Real (R$) set in R$ 724,00 (in 2014), and classified “up to 1 MW”, “between 2-3 MW” and “more than 3 MW”. The health indicators selected were self-rated health classified as “good”, “regular” and “poor” [42] and the nutritional status was the body mass index (BMI), the ratio between weight in kilograms and height in square meters [43]. The neighbourhood context considered the length of residence, the time the participant lives at the same address; the income per capita (R$), and the land slope percentage using geospatial data, considering the median values for the census tract where each participant’s residence is placed.

Data analysis

Based on the walking for leisure and transportation high zero proportion, the most popular (log) or complex (square root) transformations for a non-normal continuous outcome were unfeasible (Supplement F2 and F3). Considering the dataset’s characteristics and the study design, the sample weight and a generalized linear mixed models (GLMM) were applied. A multilevel negative binomial regression (NBR) was selected to investigate the association between continuous walkability index and walking for leisure and transportation as the most suitable GLMM analytical model after considering mainly the Akaike Information Criterion (AIC) and the Dispersion Parameter values (Supplement T1). The application of NBR results in the Incidence Rate Ratio (IRR), which reflects in cross-sectional studies an association between exposures and outcomes at a single point in time, not allowing causality or temporal relationships. A conceptual model structured in a Directed Acyclic Graph guided the minimal sufficient adjustment sets for estimating the total effect of the exposure on outcomes, which included the confounders in five models combined, with covariates groups inputted one by one (Supplement F4). All analyses were run using R software (v.2023.03.1 build 446, PBC) for macOS, and statistical significance was set at 5%.

Results

The city-wide walkability index

Belo Horizonte has 3,933 census tracts, with a median of 0.049 km² of area, 11,651 inhabitants/km², R$743.65 Brazilian Real – representing an urban contextual income, and a land slope of 7.6%. The index comprised three indicators: land use mix (median: -0.30), intersection density (median: -0.18), and net residential density (median: 0.03). The median of walkability was -0.60 (IQR: -1.60 – 0.49), ranging between -5.37 to 175.69, where larger values represent a higher level of the index, as is shown in Table 1.

[Figure omitted. See PDF.]

The survey sampling

With 1,372 adults (≥18 years old) from Belo Horizonte, the median walkability based on the participant’s residence’s census tract (n = 246) location was -0.51 (IQR: -1.40 – 1.21) ranging from -3.30 to 11.39, where higher scores indicate greater walkability. Furthermore, the median walking for leisure and transportation was 180 min/week (IQR: 120 – 250), while the 0 min/week participants were 89% and 90%, respectively (Fig 2).

[Figure omitted. See PDF.]

(n = 1,372). Avg: Average; SD: Standard deviation; IQR: Interquartile range; Min-Max: Minimum-maximum; ‡: Developed according to Frank (2010), representing in this study the census tract (246/3,933) in which each participant’ residence is placed; *: Due to the IPAQ use, which counts undertaking from 10 minutes, the proportion of zero represents those participants who did not undertaking any physical activity.

Most of the sample was composed of women (60.5%), with a median age of 41 years old, 45.9% educated up to primary schooling, and 63.7% with family income between 1 to 3 minimum wages. The majority reported good self-rated health (64.7%), and the median BMI was 26.2 kg/m², classified as overweight. For the neighbourhood context variables, people reported living in the same place for a median of 15 years; regarding the geospatial-based macroscale measures, the median income per capita was below minimum wage at US$ 175 (for the period of participant’s data gathering, as per IPEA - Institute of Applied Economic Research of Brazil) and the land slope was 8.2%. Additionally, the crude associations were similar and in the same direction — the incidence rate ratio of both physical activity domains was higher in males, older, more educated, and wealthier participants than their counterparts. The same reading can be observed for the health indicators, with better self-rated health and higher BMI in those who perform walking for leisure and transportation. Longer residence time and higher income per capita were also associated with the outcomes, while no significant association with land slope was observed, as is shown in Table 2.

[Figure omitted. See PDF.]

All models (Supplement T2) were positively associated between the walkability index and walking outcomes, except model 1 for leisure [where the result demonstrates no statistical significance] and transportation [in which the association was inverse]. Both included only individual sociodemographic covariates. After adjusting for confounders, the final models resulted in a greater association between the walkability index and walking for leisure (IRR: 1.33; CI_95%:1.32-1.35; p < 0.001) and transportation (IRR: 1.22; CI_95%:1.20-1.24; p < 0.001), as is shown in Fig 3.

[Figure omitted. See PDF.]

(n = 1,372). IRR: Incidence rate ratio; CI95%: Confidence interval; Models: All multilevel analysis used a random intercept for census tract and regarded the sample weight; Model 0: Crude analysis; Model 1: Adjusted by individual sociodemographic; Model 2: Adjusted by health indicators; Model 3: Adjusted by neighbourhood contextual; Model 4: Adjusted by the interaction of income and land slope, geospatially derived urban macroscale measures (census tract); Model 5: Models of 1 to 4 combined.

Discussion

This study derived a city-wide walkability index for Belo Horizonte, Brazil, utilizing geospatially derived macroscale features of the urban environment. It aims to inform policymakers on formulating active mobility strategies. Key strengths of the study are highlighted, as the methodology draws upon well-established techniques literature-based for evaluating walkability [35], integrates a robust study design tailored to a Latin American urban context [33,34], and employs suitable statistical modelling techniques to address dataset peculiarities [36,41].

Urban models promoting walkable cities are gaining traction globally. The initial finding of this study reveals that, based on geospatially derived metrics such as land use mix, intersection density, and net residential density, Belo Horizonte exhibits a moderate walkability index, suggesting a tendency towards car dependency rather than walkability. In part, this phenomenon can be attributed to the city’s zoning, where residential areas are segregated from hubs of daily activities like work and study, despite well-connected streets. The city’s latest master plan underscores the importance of multi-sectoral integration to address the Sustainable Development Goals (SDGs), particularly Goal 11, which pertains to sustainable cities and communities. Undoubtedly, the challenges are significant. Among the priorities is reducing reliance on the city centre and individual motorized transport. This entails improving urban infrastructure, enhancing the permeability of land, promoting densification centred around public transport, establishing facilities to encourage active urban mobility, and preserving the natural environment [44].

Despite the concentration of businesses in the central area, mixed land use or non-residential purposes have expanded, even if only modestly. This underscores the importance of diverse functions within neighbourhoods, enabling residents to access services and commerce nearby, thus reducing lengthy commutes, alleviating traffic congestion, and enhancing the daily lives of citizens. In fact, much like other major Brazilian cities, Belo Horizonte was shaped to prioritize mobility through individual motorized vehicles [45]. This leads to consequences for pedestrian movement, especially for those who use walking as a transportation mode. To address this situation, new proposals and projects have been developed to value public spaces and pedestrians. The Belo Horizonte Mobility Plan emphasizes the need for measures that promote pedestrian walking, such as actions to discourage car usage and investments in pedestrian infrastructure [46]. However, despite structural advancements, pedestrian walking is still undervalued in urban planning, even though it is the city’s most utilized mode of transportation [47]. Another pressing concern is the adverse effects of heavy rainfall. It is estimated that 144 areas in Belo Horizonte are at high risk of flooding, with a projected 32% increase in issues stemming from intense rains. These include mortality, property damage, heightened susceptibility to infectious diseases like dengue, and impacts on active travel throughout the city [48].

Broadening the geographical applicability of these findings beyond Europe and North America [49,50], this study’s findings corroborate existing literature affirming a positive association between walkability and walking. The outcome aligns with a comprehensive scoping review by Dixon et al [51], where they described a positive association between walkability and physical activity in 83% of the reviews. Such results are not surprising as it is consistent with the purpose of walkability indices, which are designed to evaluate environments conducive to walking [35]. As this study’s findings also reveal, walkability has a multi-dimensional impact as it not only influences leisure-time physical activity but also has a broader impact on transportation-related walking. Urban models promoting walkable cities are gaining traction globally. These discoveries are congruous with the international literature, which indicates that walkability and/or its components are positively associated with active transport and total physical activity [51–53]. Indeed, this is one of the most consistent findings in this field.

Urban health is a complex system in which several environmental attributes act concurrently [11,54]. This approach, besides providing a more realistic view of cities, allows a systematic contextual analysis of how walkable a place can be [12,13]. Especially when it is comprehensible that in several urban contexts, regardless of infrastructure, walking is not an individual’s choice but a necessity [17]. Walkability parallels mixed land uses [55], with access through street pedestrian-level to the diversity of destinations such as service, commerce, leisure, study, and workplace nearby. Thus, it seems a preponderant factor that a city would be compactness [56] and connectedness [15] to provide environmental benefits to the population, stimulating a walking-friendly place and reducing organically car dependency [57]. Concepts of 15 or 20-minute cities appears in the literature as great to favour urban scenario that reclaims public spaces for people [58,59].

Limitations of this study are highlighted to facilitate an adequate interpretation of the findings. Parsimony due to the study design, once the association is identified, cannot be generalized to the whole city. In fact, there is an influence on living near or even attending a health academy program centre [60]. However, the sample’s walkability index was able to capture the city-wide walkability index variability. Although the most widely used instrument in population-based studies, the physical activity tool for measuring walking has a low sensitivity over distances shorter than 10 minutes of travel [37,38]. Furthermore, the environmental indicators do not consider microscale street pedestrian level nor neighbourhoods’ citizen perception, such as sidewalk quality, presence of urban furniture, road signage, traffic, and crime safety, as they may be relevant aspects of decision-making to walk or drive [61,62]. Disregarding potential changes over time, based on a cross-sectional approach, geospatially derived macroscale measures, despite allowing a wide-ranging territorial analysis, present data from a different period than the outcomes. Additionally, the walkability index creation did not consider parsimonious methods to determine which and how many indicators would be appropriate for the contextual reality of the city [63]. However, it allows comparability with most studies worldwide related to the topic [18], which constructs the index from this set of geographical scale indicators [35]. Due to the steep slope characteristic of the city, this indicator should be part of the index, considered a local peculiarity [64,65]. Nonetheless, the slope was included in an analytical model as it is considered relevant for the finding’s interpretation.

Suggestions for future investigations are highlighted to guide new research questions. An agent-based model should be integrated into the walkability index monitoring over time [66], simulating urban scenarios to test the effectiveness of implementing or changing city features [67]. Combine mixed methods to assess the environment’s macro and microscale indicators, incorporating built, natural, and social city’ attributes beyond increased physical activity measures through accelerometery and their urban contextual using global positioning system-wearable devices to identify destinations, durations, and distances objectively-derived [68]. Finally, the longitudinal and experimental study design should be prioritized, and the population and stakeholders should be jointly considered to identify the relevant and feasible indicators to compose the walkability city index.

In conclusion, considering the city as a complex and multi-component system, our findings suggest that increasing the walkability of neighbourhoods can be an effective strategy for increasing active living behaviour. Furthermore, specific aspects of the planning, design and implementation of policies and interventions to create more walk-friendly places should be tailored to local contexts, taking people into account to decrease car-dependence and provide opportunities to improve the health of citizens as part of their daily routine.

Supporting information

Supporting Materials. Containing supporting figures 1-4 and supporting table 1-2.

https://doi.org/10.1371/journal.pone.0320202.s001

Acknowledgments

The authors acknowledge to the participants of the MOVE-SE project, from which the primary data originated, besides to the contribution of all Observatory for Urban Health in Belo Horizonte team members involved in the data gathering and project design. For more information, see https://osubh.medicina.ufmg.br. Furthermore, the authors are grateful for any contributions of all Global Diet and Activity Research Network team members involved in this work. For more information, see https://gdarnet.org.

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Citation: Lopes AAS, Lima LL, Magalhães AS, Andrade ACS, Canelas T, Foley L, et al. (2025) What is the cross-sectional association of geospatially derived walkability with walking for leisure and transport? PLoS ONE 20(3): e0320202. https://doi.org/10.1371/journal.pone.0320202

About the Authors:

Adalberto A. S. Lopes

Roles: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

E-mail: [email protected] (AASL)

Affiliation: Observatory for Urban Health in Belo Horizonte, Federal University of Minas Gerais, Brazil

ORICD: https://orcid.org/0000-0002-3001-6412

Larissa L. Lima

Roles: Conceptualization, Data curation, Methodology, Validation, Writing – original draft, Writing – review & editing

Affiliation: Center for Modeling Social Systems, Norwegian Research Centre, Kristiansand, Norway

Amanda S. Magalhães

Roles: Methodology, Validation, Visualization, Writing – review & editing

Affiliation: Observatory for Urban Health in Belo Horizonte, Federal University of Minas Gerais, Brazil

Amanda C. S. Andrade

Roles: Formal analysis, Methodology, Software, Writing – review & editing

Affiliation: Observatory for Urban Health in Belo Horizonte, Federal University of Minas Gerais, Brazil

Tiago Canelas

Roles: Methodology, Software, Validation, Visualization

Affiliation: MRC Epidemiology Unit, University of Cambridge, England, United Kingdom.

ORICD: https://orcid.org/0000-0003-2064-8456

Louise Foley

Roles: Methodology, Validation, Visualization, Writing – review & editing

Affiliation: MRC Epidemiology Unit, University of Cambridge, England, United Kingdom.

Tolu Oni

Roles: Funding acquisition, Methodology, Project administration, Supervision, Validation, Visualization, Writing – review & editing

Affiliation: MRC Epidemiology Unit, University of Cambridge, England, United Kingdom.

Waleska T. Caiaffa

Roles: Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Supervision, Validation, Writing – original draft, Writing – review & editing

Affiliation: Observatory for Urban Health in Belo Horizonte, Federal University of Minas Gerais, Brazil

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

[/RAW_REF_TEXT]

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