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. 2023 Apr 17:5:1055351.
doi: 10.3389/frsc.2023.1055351.

Bicycle use in Latin American cities: changes over time by socio-economic position

Ione Avila-Palencia  1   2 , Olga L Sarmiento  3 , Nelson Gouveia  4 , Alejandra Jáuregui  5 , Maria A Mascolli  4 , Anne D Slovic  6 , Daniel A Rodríguez  7
Affiliations

Bicycle use in Latin American cities: changes over time by socio-economic position

Ione Avila-Palencia et al. Front Sustain Cities. .

Abstract

Introduction: We aimed to examine utilitarian bicycle use among adults from 18 large Latin American cities and its association with socio-economic position (education and income) between 2008 and 2018.

Methods: Data came from yearly cross-sectional surveys collected by the Development Bank of Latin America (CAF). A total of 77,765 survey respondents with complete data were used to estimate multilevel logistic regression models with city as random intercept and year as random slope.

Results: Individuals with high education and high-income levels had lower odds of using a bicycle compared with participants with lower education and income levels. These associations, however, changed over time with the odds of bicycle use increasing for all groups, especially among individuals with the highest education and income levels.

Discussion: Our results confirm the broadening appeal of bicycling across socioeconomic positions in several Latin American cities and reinforce the importance of considering policies aimed at supporting and enhancing bicycle travel for all users.

Keywords: Latin America; bicycle; cities; education; income; socio-economic (personal) factors; survey.

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Conflict of interest statement

Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1. Predictive marginal probabilities of bike use by education and income level over time in CAF surveys of select Latin America cities.
Models after controlling for age and gender (model 1). HS, high school. (A) Education level single predictor model after controlling for age and gender (model 1). Global test interaction p-value < 0.001. 95% CIs are not displayed for clarity. (B) Income level single predictor model after controlling for age and gender (model 1). Global test interaction p-value < 0.001. 95% CIs are not displayed for clarity.
See this image and copyright information in PMC

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