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The Profile of Bicycle Users, Their Perceived Difficulty to Cycle, and the Most Frequent Trip Origins and Destinations in Aracaju, Brazil

Department of Physical Education, Federal University of Sergipe (UFS), São Cristóvão 49100-000, Brazil
Center for Epidemiological Research in Nutrition and Health (NUPENS), University of São Paulo (USP), São Paulo 01246-904, Brazil
Non-Governmental Organization Associação Ciclo Urbano, Aracaju 49070-376, Brazil
Physical Activity, Sport and Health Sciences Laboratory, Faculty of Medical Sciences, University of Santiago, Chile (USACH), Santiago 7500618, Chile
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(21), 7983;
Submission received: 29 June 2020 / Revised: 31 July 2020 / Accepted: 3 September 2020 / Published: 30 October 2020
(This article belongs to the Special Issue Active Commuting and Active Transportation)


The objective of this study was to describe the profile of bicycle users, their perceived difficulty to cycle, and the most frequent trip origins and destinations in Aracaju, Northeast Brazil. Our cross-sectional study sampled 1001 participants and we collected information through structured interviews. Aged ≥15 years, participants were residents of all Aracaju’s neighborhoods and used a bicycle for commuting to work or for leisure. We observed that bicycle users in Aracaju are predominantly employed male subjects, aged between 18 and 40 years, and were the heads of their households. Most of the them reported “work” as the main reason for their bicycle trips and, “health” and “practicality” aspects as their main motivations for using bicycles. In general, the neighborhoods in the north and center of the city were identified as the most difficult for cycling, and the easiest trips occurred in places with cycle paths. As a conclusion of this study, we reaffirm the need for intersectoral actions that create favorable environments for active commuting and more sustainable cities.

1. Introduction

Increased physical inactivity is currently a major challenge in several countries [1], mainly due to its association with an increased risk of chronic noncommunicable diseases, such as cardiovascular diseases, different types of cancer, and mental disorders [2,3]. Most people do not comply with the minimum recommended levels of physical activity to prevent diseases and to protect health, i.e., according to the World Health Organization’s physical activity guidelines [4]. In this sense, the adoption of different strategies to provide an active lifestyle emerges as the most viable alternative for the promotion of physical activity [1,5], such as changes in the urbanized environment of cities to enable active commuting [6].
Given that commuting is seen as a daily practice among adult populations and that at least 30 min a day are spent on this activity [7], active alternatives, such as the use of bicycles, can be applied as a strategy to increase total physical activity. Commuting by bicycle provides additional benefits, such as contributing to air and noise pollution reduction, increasing social engagement, and reducing road traffic injuries [8,9,10,11,12]. Active commuting by bicycle can be considered as an accessible and relatively “easy” way to promote physical activity among different age groups (children, adults, and older adults) [13,14,15,16] and cultures/countries [17,18]. However, despite the relevance of this approach, there is limited information about the effectiveness of these strategies or even the adherence of the population to them, particularly in low- and middle-income settings [19,20,21].
Previous studies report the influence of individual and environmental variables on the use of bicycles for transport, including sex, age, economic status, and education, in addition to proximity between the point of origin and the destination [19,22,23,24]. In the Brazilian context, the accessibility of bicycle use as a means of transport is a topic of discrepancy. Reis, et al. [25] compared the prevalence of bicycle use for transportation among three cities in different states and regions of Brazil, observing differences between Recife (Pernambuco, Northeast, 16.0%), Curitiba (Paraná, South, 9.6%), and Vitória (Espírito Santo, Southeast, 8.8%). In another study conducted in Rio Claro (São Paulo, Southeast), Teixeira, et al. [26] found a much greater prevalence of bicycle use for transportation (28.3%). Although it seems clear that men, younger adults, and lower education/economic status were associated with greater use of bicycles for transportation [8,25,26,27] in both studies, some specificities should be considered in the low- and middle-income contexts. For example, Reis, et al. [25] observed a higher prevalence of bicycle use in the city with the highest crime rate (Recife), which was not expected. However, this was also the city with the lowest human development index, highest unemployment rate, and social inequalities, suggesting that bicycle use could not be an option in low-income regions. Thus, understanding the profile of bicycle users and their relations with specific characteristics of the cities is justified in order to provide better conditions for those who already use the bicycle, and to create opportunities for other population subgroups to use bicycles for transport.
Aracaju city (Sergipe, Northeast) is known as of the first Brazilian capitals to implement the proposal for mobility on bicycles in 2005 (implementing networks of cycle paths and on flat land). However, only 11.9% of the population reported active commuting (walking and cycling) in 2018 [28], and there is no available information on the use of the bicycle for transport. Given that Aracaju’s street design favors the use of bicycles for commuting, studies on bicycle flow within available structures would contribute to the development of strategies for urban planning, acting as an important way to increase health, environment, and sustainability indicators in that context. However, information about bicycle users, their perceptions about the city, and the most frequent trip origins and destinations could foster public policies in urban planning. Thus, we researched the profile of bicycle users, their perceived difficulty to cycle, and the most frequent origins and destinations of bicycle travel in Aracaju, Brazil.

2. Methods

2.1. Design

We used a cross-sectional method, carried out in Aracaju, Brazil. Aracaju is the state capital of Sergipe, with about 657 thousand inhabitants (2019), and a Human Development Index of 0.770 (2010). The population’s average income in 2010 was 3.1 times the minimum wage (approximately USD 200) and 56.6% of public spaces were forested [29].

2.2. Sample and Data Procedures

The information in this study was obtained from the “Origin and Destination of Biking Trips in the City of Aracaju, Survey,” over a one-year period (June 2014 to June 2015). The survey was conducted with bicycle users that were approached personally in all 40 neighborhoods of the city, respecting the proportionality of the population of each neighborhood [29]. The structured interviews were conducted by 17 trained advisors on weekdays, from 2:00 PM to 7:00 PM. This convenience sample consisted of 1001 bicycle users. The city neighborhoods were organized into bordering zones (north, south, central, and expansion). It is important to note that the set of neighborhoods, communities, and villages that make up the Expansion Zone have been incorporated to Aracaju by legal decision. All participants were provide with information about the objectives of the study, which was conducted in accordance with the ethical standards of the institutional and/or national research committee, respecting the 1964 Helsinki Declaration and its further amendments, or comparable ethical standards. The study was approved by the Ethics Committee of the Federal University of Sergipe (CAAE: 16418619.7.0000.5546).

2.3. Instrument

The questionnaire used was prepared by the nongovernmental organization “Associação Ciclo Urbano—Aracaju,” consisting of 23 items and divided into (a) cyclist profile: sex (male and female), age (categorized into five age groups: up to 18 years, 18 to 30 years, 30 to 40 years, 40 to 50 years, and over 50 years), and family role (head of family, spouse, child, or relative); (b) socioeconomic information: work status (employed and not employed), educational level (below upper secondary,, secondary, and above secondary), activity sector (commerce, industry, construction, education, and health), monthly income (up to one minimum wage and above one minimum wage), and automotive vehicle ownership (yes or no); (c) characteristics of the origin and destination of trips made by bicycles: reason for the trip (work, school, leisure, shopping, and others), location of origin and destination (Aracaju neighborhood), region’s access conditions (easy, difficult), bicycle parking conditions (public, paid parking, and free parking), motivation to ride a bicycle (health, practicality, leisure, economic, and two options), departure and arrival period of the day (morning, afternoon, and night), time spent commuting (0 to 15 min, 15 to 30 min, 30 to 45 min, 45 to 60 min, and over 60 min), whether the destination is a different neighborhood (yes or no), and the type of trip origin and destination (nonrecreational or recreational).

2.4. Statistical Analysis

Descriptive information was presented using absolute and relative frequencies. To compare the profile of bicycle users with Aracaju’s population, we restricted the analysis to adult participants and used the information provided by the Brazilian 2013 National Health Survey, which is the closest survey to the reference year with representative information of the adult population of Aracaju [30] (% and 95% confidence intervals). The perception analysis of cycling difficulty in neighborhoods was determined by the relative frequency of citations used (easy or difficult). Absolute frequencies of commuting between neighborhoods were used to verify the main trip origin and destination, and the main neighborhoods cited as the origin or destination. Main trip origins and destinations were defined as those representing at least 0.9% of the total mentioned. The Aracaju Mobility Master Plan (2016) was used to identify bike lanes that were implemented until 2015. Finally, the information was presented in the form of a map with an origin and destination analysis. It was carried out using a cross-reference table to check the main neighborhoods in which there was a greater flow of bicycle users entering and leaving, in addition to identifying the main trip origin and destination of the interviewees. The maps were built using the CorelDRAW Graphics Suite 2019 software (Corel Corporation, Ottawa, ON, Canada). All analyses were performed using SPSS 22.0 software (IBM, Armonk, NY, USA).

3. Results

Table 1 shows information on bicycle user profiles. It shows that the sample was predominantly composed of men, aged 18 to 40 years, who were heads of their households and were employed. Most reported schooling at primary and secondary levels, and work in civil construction and health sectors; 66.7% reported “work” as the main reason for their travel. Most individuals reported not having their own automotive vehicle and having income of up to one minimum wage. Most participants reported “healthy” and “practicality” as their main motivation to ride a bicycle.
Figure 1 presents the perceived degree of difficulty for cycling in city neighborhoods. In general, Center (23%) and Porto Dantas (13%) were pointed out as neighborhoods in which cycling was the most difficult for cycling, while 13 de Julho (14%), Atalaia (13%), Siqueira Campos (13%), and Jabotiana (12%) were cited as the ones in which cycling was the easiest.
Figure 2 shows the most frequent trip origins and destinations among the participants. The main destination was Santa Maria neighborhood (10.9%), followed by Atalaia (5.3%), Farolândia (5.7%), and Santos Dumont (6%). Regarding the trip origin and destination, Center (6.6%), Farolândia (5.9%), and Siqueira Campos (5.6%) were the most reported. In addition, there is a greater tendency to move toward neighborhoods close to the point of departure, with 23% of the total trips occurring within the neighborhood of origin (especially the José Conrado (50%) and the Expansion Zone (77%) neighborhoods).

4. Discussion

This study aimed to describe the profile of bicycle users, their perceived difficulty to cycle, and the most frequent trip origins and destinations in the city of Aracaju. The results indicated that (1) the 60-km cycle paths distributed in the city of Aracaju serve mostly men, younger adults, and people with lower educational levels, as compared with the population of Aracaju; (2) the use of active commuting is associated with going to work, especially in the lowest income group; (3) most bicycle users move from central to peripheral areas; and (4) the majority of the participants spent an average of 15 to 30 min (per cycling trip). This information is vital to develop strategies to improve current bicycle user conditions and to create new opportunities for less represented population groups, especially in developing countries.
Bicycle user profiles differed greatly from those of Aracaju’s population in general, which reinforces the fact that some population subgroups are more inclined to use bicycles for transportation. The initial results confirm data from previous studies in Brazilian cities showing a similar bicycle user profile, including a higher proportion of adult young men [8,25,26,27]. This behavior in men is associated with a duality in terms of stimuli directed at boys and girls in childhood, with a tendency to maintain these habits in adulthood [31], culminating in less use of bicycles by women in particular and less engagement in physical activities in general. Another factor is the perception of safety, which tends to be different between sexes, making factors related to “lack of lighting during commuting,” “driver-cyclist behavior in traffic,” and “public insecurity” great obstacles, especially among women [16,32]. Some studies [8,26] also showed greater use of bicycles among workers in areas with a higher representation of men (e.g., construction and industry).
Considering that most participants who traveled by bicycle did not own automotive vehicles—a proportion higher than that observed in the population of Aracaju (78.4% vs. 49.0%)—the socioeconomic structure of the population may be a factor that explains these results. In previous studies, this factor has already been negatively associated with levels of active transport [33] and were observed more frequently in low-income regions. Bicycles tend to be a “cheaper” mode of transport due to inaccessibility of a private vehicle, high fares, and lack of quality in public transport.
Safety issues in public transport and the lack of adequate infrastructure for bicycle use tend to “disable” environments that favor walking or cycling as means to travel to work [34]. Our results indicated that, in general, the districts of the North and Central Zones were identified as the most difficult to cycle in, which may be associated with the fact that most of the Aracaju cycle system is concentrated in the South Zone [35]. In previous studies, not having bike paths, conservation of streets and avenues, car traffic, and rough surfaces were examples of variables that could impact bicycle users’ perception of neighborhoods [36,37].
The origin and destination of the trips indicated greater commuting from central areas to peripheral areas of the city. One of the possible explanations may be associated with the growth in investments in civil construction, industry, and commerce in the South Zone of the city, leading people to move to the peripheral regions of the city for work. In addition, a large part of the participants reported working in these sectors (33.9%, 20.7%, and 10.0%, for construction, commerce, and industry, respectively). Another explanation for these results could be the data collection times, which were concentrated in the afternoon and may represent the commute home from work. It was noted that the most frequently cited trip origins and destinations by respondents (Figure 2) involved commuting between adjacent or nearby neighborhoods. Previous studies identified that distances under 10 kilometers were more feasible to retain the use of the bicycle as a means of daily commuting [38,39,40]. In the present study, the most participants spent an average of 15 to 30 min (per trip) on daily commuting. This behavior shows a viability threshold for this mode of transport and can offer health benefits [41]. Other actions could improve and facilitate the use of cycle paths. The equitable distribution of schools, jobs, and sectors necessary for day-to-day activities can help people from places with longest trip origins and destinations [42,43].
The practical application of the study is to use this data as an aid in producing public policies to improve the infrastructure of cycle paths and expand cycle routes. Understanding the behavior and profile of bicycle users may also inform political decisions regarding active transport and urban planning. Although this was a nonrepresentative sample and interviews are likely to provide report bias, this study analyzes the profile and characteristics of trip origins and destinations and the perception of bicycle users in a specific social, economic, and climate context regarding active commuting.

5. Conclusions

Bicycle users are predominantly represented by men, aged between 18 and 40 years, from low income families in Aracaju, Brazil. In general, the use of active commuting is associated with going to work, mainly because this form of transport is more practical and healthier than public and private transport. The study reported a tendency of travel from central to peripheral areas, which may be associated with the workplaces. Considering that some bicycle users report the economic factor as a motivation to use bicycles and that women and adolescents are underrepresented in this scenario, the present study reaffirms the need for intersectoral actions to enable the construction of a safer city through expansion of bicycle networks with safe dimensions and accessibility.

Author Contributions

All authors contributed to the study conception and design. Material preparation and data analysis were performed by M.T., J.C.N.M., J.P.B.T., F.M.J.S., and D.R.S. The first draft of the manuscript was written by M.T. Substantial writing-review and editing were performed by E.C.M.S., A.O.W., S.D., G.F., T.H.S., and D.R.S. All authors have read and agreed to the published version of the manuscript.


This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Mabliny Thuany is supported by the Foundation for Support to Research and Technological Innovation of the State of Sergipe (FAPITEC). André Werneck is supported by the São Paulo Research Foundation (FAPESP) with a PhD scholarship (FAPESP process: 2019/24124-7). This paper presents an independent research. The views expressed in this publication are those of the authors and not necessarily those of the acknowledged institutions.

Conflicts of Interest

Authors declare no conflicts of interest.


  1. World Health Organization. Physical Inactivity: A Global Public Health Problem. Available online: (accessed on 25 April 2020).
  2. Firth, J.; Siddiqi, N.; Koyanagi, A.; Siskind, D.; Rosenbaum, S.; Galletly, C.; Allan, S.; Caneo, C.; Carney, R.; Carvalho, A.F.; et al. The Lancet Psychiatry Commission: A blueprint for protecting physical health in people with mental illness. Lancet Psychiatry 2019, 6, 675–712. [Google Scholar] [CrossRef] [Green Version]
  3. Lee, I.M.; Shiroma, E.J.; Lobelo, F.; Puska, P.; Blair, S.N.; Katzmarzyk, P.T. Effect of physical inactivity on major non-communicable diseases worldwide: An analysis of burden of disease and life expectancy. Lancet 2012, 380, 219–229. [Google Scholar] [CrossRef] [Green Version]
  4. World Health Organization. Global Recommendations on Physical Activity for Health; WHO Guidelines Review Committee: Geneva, Switzerland, 2010. [Google Scholar]
  5. Gomes, G.A.; Kokubun, E.; Mieke, G.I.; Ramos, L.R.; Pratt, M.; Parra, D.C.; Simoes, E.; Florindo, A.A.; Bracco, M.; Cruz, D.; et al. Characteristics of physical activity programs in the Brazilian primary health care system. Cad. Saude Publica 2014, 30, 2155–2168. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Stevenson, M.; Thompson, J.; de Sá, T.H.; Ewing, R.; Mohan, D.; McClure, R.; Roberts, I.; Tiwari, G.; Giles-Corti, B.; Sun, X.; et al. Land use, transport, and population health: Estimating the health benefits of compact cities. Lancet 2016, 388, 2925–2935. [Google Scholar] [CrossRef] [Green Version]
  7. Schantz, P. Distance, duration, and velocity in cycle commuting: Analyses of relations and determinants of velocity. Int. J. Environ. Res. Public Health 2017, 14, 1166. [Google Scholar] [CrossRef] [Green Version]
  8. Sa, T.H.; Duran, A.C.; Tainio, M.; Monteiro, C.A.; Woodcock, J. Cycling in Sao Paulo, Brazil (1997-2012): Correlates, time trends and health consequences. Prev. Med. Rep. 2016, 4, 540–545. [Google Scholar] [CrossRef] [Green Version]
  9. Saunders, L.E.; Green, J.M.; Petticrew, M.P.; Steinbach, R.; Roberts, H. What are the health benefits of active travel? A systematic review of trials and cohort studies. PLoS ONE 2013, 8, e69912. [Google Scholar] [CrossRef] [Green Version]
  10. Götschi, T.; Garrard, J.; Giles-Corti, B. Cycling as a part of daily life: A review of health perspectives. Transp. Rev. 2015, 36, 45–71. [Google Scholar] [CrossRef] [Green Version]
  11. Johansson, C.; Lovenheim, B.; Schantz, P.; Wahlgren, L.; Almstrom, P.; Markstedt, A.; Stromgren, M.; Forsberg, B.; Sommar, J.N. Impacts on air pollution and health by changing commuting from car to bicycle. Sci. Total Environ. 2017, 584–585, 55–63. [Google Scholar] [CrossRef]
  12. Savan, B.; Cohlmeyer, E.; Ledsham, T. Integrated strategies to accelerate the adoption of cycling for transportation. Transp. Res. Part. F Traffic Psychol. Behav. 2017, 46, 236–249. [Google Scholar] [CrossRef]
  13. Trapp, G.S.; Giles-Corti, B.; Christian, H.E.; Bulsara, M.; Timperio, A.F.; McCormack, G.R.; Villaneuva, K.P. On your bike! A cross-sectional study of the individual, social and environmental correlates of cycling to school. Int. J. Behav. Nutr. Phys. Act. 2011, 8, 123. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Gatersleben, B.; Appleton, K.M. Contemplating cycling to work: Attitudes and perceptions in different stages of change. Transp. Res. Part A Policy Pract. 2007, 41, 302–312. [Google Scholar] [CrossRef]
  15. Kohl, H.W.; Craig, C.L.; Lambert, E.V.; Inoue, S.; Alkandari, J.R.; Leetongin, G.; Kahlmeier, S. The pandemic of physical inactivity: Global action for public health. Lancet 2012, 380, 294–305. [Google Scholar] [CrossRef] [Green Version]
  16. Heesch, K.C.; Sahlqvist, S.; Garrard, J. Gender differences in recreational and transport cycling: A cross-sectional mixed-methods comparison of cycling patterns, motivators, and constraints. Int J. Behav. Nutr. Phys. Act. 2012, 9, 106. [Google Scholar] [CrossRef] [Green Version]
  17. Te Velde, S.J.; Haraldsen, E.; Vik, F.N.; De Bourdeaudhuij, I.; Jan, N.; Kovacs, E.; Moreno, L.A.; Dossegger, A.; Manios, Y.; Brug, J.; et al. Associations of commuting to school and work with demographic variables and with weight status in eight European countries: The ENERGY-cross sectional study. Prev. Med. 2017, 99, 305–312. [Google Scholar] [CrossRef] [PubMed]
  18. Aparicio-Ugarriza, R.; Mielgo-Ayuso, J.; Ruiz, E.; Avila, J.M.; Aranceta-Bartrina, J.; Gil, A.; Ortega, R.M.; Serra-Majem, L.; Varela-Moreiras, G.; Gonzalez-Gross, M. Active commuting, physical activity, and sedentary behaviors in children and adolescents from Spain: Findings from the ANIBES Study. Int. J. Environ. Res. Public Health 2020, 17, 668. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Bauman, A.E.; Reis, R.S.; Sallis, J.F.; Wells, J.C.; Loos, R.J.F.; Martin, B.W. Correlates of physical activity: Why are some people physically active and others not? Lancet 2012, 380, 258–271. [Google Scholar] [CrossRef]
  20. Pollack Porter, K.M.; Prochnow, T.; Mahoney, P.; Delgado, H.; Bridges Hamilton, C.N.; Wilkins, E.; Umstattd Meyer, M.R. Transforming city streets to promote physical activity and health equity. Health Aff. 2019, 38, 1475–1483. [Google Scholar] [CrossRef]
  21. Sallis, J.F.; Cerin, E.; Conway, T.L.; Adams, M.A.; Frank, L.D.; Pratt, M.; Salvo, D.; Schipperijn, J.; Smith, G.; Cain, K.L.; et al. Physical activity in relation to urban environments in 14 cities worldwide: A cross-sectional study. Lancet 2016, 387, 2207–2217. [Google Scholar] [CrossRef] [Green Version]
  22. Pinjari, A.R.; Pendyala, R.M.; Bhat, C.R.; Waddell, P.A. Modeling the choice continuum: An integrated model of residential location, auto ownership, bicycle ownership, and commute tour mode choice decisions. Transportation 2011, 38, 933–958. [Google Scholar] [CrossRef] [Green Version]
  23. Werneck, A.O.; Baldew, S.S.; Miranda, J.J.; Díaz Arnesto, O.; Stubbs, B.; Silva, D.R. Physical activity and sedentary behavior patterns and sociodemographic correlates in 116,982 adults from six South American countries: The South American physical activity and sedentary behavior network (SAPASEN). Int. J. Behav. Nutr. Phys. Act. 2019, 16, 68. [Google Scholar] [CrossRef] [Green Version]
  24. Mitáš, J.; Cerin, E.; Reis, R.S.; Conway, T.L.; Cain, K.L.; Adams, M.A.; Schofield, G.; Sarmiento, O.L.; Christiansen, L.B.; Davey, R.; et al. Do associations of sex, age and education with transport and leisure-time physical activity differ across 17 cities in 12 countries? Int. J. Behav. Nutr. Phys. Act. 2019, 16, 121. [Google Scholar] [CrossRef] [PubMed]
  25. Reis, R.S.; Hino, A.A.; Parra, D.C.; Hallal, P.C.; Brownson, R.C. Bicycling and walking for transportation in three Brazilian cities. Am. J. Prev. Med. 2013, 44, e9–e17. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Teixeira, I.; Nakamura, P.; Smirmaul, B.; Fernandes, R.; Kokubun, E. Fatores associados ao uso de bicicleta como meio de transporte em uma cidade de médio porte. Rev. Bras. Ativ. Fis. Saúde 2013, 18, 698. [Google Scholar] [CrossRef]
  27. Kienteka, M.; Reis, R.S.; Rech, C.R. Personal and behavioral factors associated with bicycling in adults from Curitiba, Paraná State, Brazil. Cad. Saude Publica 2014, 30, 79–87. [Google Scholar] [CrossRef] [PubMed]
  28. Ministério da Saúde do Brasil. Vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico—VIGITEL; Ministério da Saúde: Brasília, Brasil, 2019, 2018.
  29. Instituto Brasileiro de Geografia e Estatística (IBGE). Sergipe. Available online: (accessed on 25 April 2020).
  30. Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa nacional de saúde 2013: Ciclos de vida. Available online: (accessed on 9 August 2020).
  31. Telama, R.; Yang, X.; Leskinen, E.; Kankaanpaa, A.; Hirvensalo, M.; Tammelin, T.; Viikari, J.S.; Raitakari, O.T. Tracking of physical activity from early childhood through youth into adulthood. Med. Sci. Sports Exerc. 2014, 46, 955–962. [Google Scholar] [CrossRef] [PubMed]
  32. Heim LaFrombois, M.E. (Re)Producing and challenging gender in and through urban space: Women bicyclists’ experiences in Chicago. Gend. Place Cult. 2019, 26, 659–679. [Google Scholar] [CrossRef]
  33. Sa, T.H.; Salvador, E.P.; Florindo, A.A. Factors associated with physical inactivity in transportation in Brazilian adults living in a low socioeconomic area. J. Phys. Act. Health 2013, 10, 856–862. [Google Scholar] [CrossRef]
  34. Providelo, J.K.; Sanches, S.P. Percepções de indivíduos acerca do uso da bicicleta como modo de transporte. Transportes 2010, 18, 53–61. [Google Scholar] [CrossRef]
  35. Superintendência Municipal de Transporte e Trânsito (SMTT). Plano diretor de mobilidade de Aracaju. Available online: (accessed on 25 April 2020).
  36. Sivasankaran, S.K.; Balasubramanian, V. Exploring the severity of bicycle-vehicle crashes using latent class clustering approach in India. J. Saf. Res. 2020, 72, 127–138. [Google Scholar] [CrossRef]
  37. Yan, X.; Ma, M.; Huang, H.; Abdel-Aty, M.; Wu, C. Motor vehicle-bicycle crashes in Beijing: Irregular maneuvers, crash patterns, and injury severity. Accid. Anal. Prev. 2011, 43, 1751–1758. [Google Scholar] [CrossRef] [PubMed]
  38. Cervero, R.; Duncan, M. Walking, bicycling, and urban landscapes: Evidence from the San Francisco Bay Area. Am. J. Public Health. 2003, 93, 1478–1483. [Google Scholar] [CrossRef]
  39. Xing, Y.; Handy, S.L.; Mokhtarian, P.L. Factors associated with proportions and miles of bicycling for transportation and recreation in six small US cities. Transp. Res. D Transp. Environ. 2010, 15, 73–81. [Google Scholar] [CrossRef] [Green Version]
  40. Zahran, S.; Brody, S.D.; Maghelal, P.; Prelog, A.; Lacy, M. Cycling and walking: Explaining the spatial distribution of healthy modes of transportation in the United States. Transp. Res. D Transp. Environ. 2008, 13, 462–470. [Google Scholar] [CrossRef]
  41. Mueller, N.; Rojas-Rueda, D.; Salmon, M.; Martinez, D.; Ambros, A.; Brand, C.; de Nazelle, A.; Dons, E.; Gaupp-Berghausen, M.; Gerike, R.; et al. Health impact assessment of cycling network expansions in European cities. Prev. Med. 2018, 109, 62–70. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Goenka, S.; Andersen, L.B. Urban design and transport to promote healthy lives. Lancet 2016, 388, 2851–2853. [Google Scholar] [CrossRef]
  43. Krizek, K.J.; Stonebraker, E.W. Assessing options to enhance bicycle and transit integration. Transp. Res. Rec. 2011, 2217, 162–167. [Google Scholar] [CrossRef]
Figure 1. Perception of the difficulty of cycling in Aracaju/Sergipe.
Figure 1. Perception of the difficulty of cycling in Aracaju/Sergipe.
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Figure 2. Main Trajectories of Bike Riders in Aracaju/Sergipe.
Figure 2. Main Trajectories of Bike Riders in Aracaju/Sergipe.
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Table 1. Characteristics of Bicycle Users and Aracaju’s Population.
Table 1. Characteristics of Bicycle Users and Aracaju’s Population.
VariableBicycle Users
% (n)
Population *
% (CI 95%)
Female11.5 (102)55.1 (50.0 to 60.1)
Male88.5 (782)44.9 (39.9 to 50.0)
18–3034.5 (305)26.1 (21.8 to 30.8)
30–4030.8 (272)24.1 (19.9 to 28.7)
40–5020.5 (181)19.2 (15.6 to 23.4)
>5014.3 (126)30.7 (26.3 to 35.4)
Family Role
Head of Family60.9 (538)-
Spouse14.0 (124)-
Child19.5 (172)-
Relative5.7 (50)-
Work status
Employed88.9 (786)54.2 (49.3 to 59.2)
Not employed11.1 (98)45.7 (40.8 to 50.7)
Below Secondary54.3 (480)38.9 (34.1 to 43.8)
Secondary32.0 (285)39.3 (34.5 to 44.2)
Beyond Secondary13.7 (121)21.9 (17.9 to 26.5)
Activity Sector
Commerce20.7 (179)-
Industry10.0 (79)-
Construction33.9 (268)-
Education2.8 (22)-
Health30.6 (242)-
Monthly Income
Up to one minimum wage78.7 (695)-
Above one minimum wage21.3 (189)-
Automotive Vehicle Ownership
No78.4 (693)49.0 (44.0 to 54.1)
Yes21.6 (191)51.0 (45.9 to 56.0)
Reason for Trip
Work66.7 (590)-
School2.9 (26)-
Leisure12.7 (112)-
Shopping6.4 (57)-
Others11.2 (99)-
Motivation to Ride a Bicycle
Health26.4 (229)-
Practicality25.3 (219)-
Leisure7.5 (65)-
Economic19.3 (167)-
Two options21.5 (186)-
Time Spent Commuting
0 to 15 min22.7 (200)-
15 to 30 min36.4 (321)-
30 to 45 min18.1 (160)-
45 to 60 min13.9 (123)-
>60 min8.8 (78)-
Is your destination a different neighborhood?
Yes82.6 (730)-
No17.4 (154)-
Type of Trip Origin and Destination
Nonrecreational96.6 (854)-
Recreational3.4 (30)-
Note: Time spent commuting refers to the total time spent commuting from the place of departure to destination. CI = confidence interval. * Based on the Brazilian 2013 National Health Survey.
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MDPI and ACS Style

Thuany, M.; N. Melo, J.C.; B. Tavares, J.P.; M. J. Santos, F.; C. M. Silva, E.; O. Werneck, A.; Dantas, S.; Ferrari, G.; Sá, T.H.; R. Silva, D. The Profile of Bicycle Users, Their Perceived Difficulty to Cycle, and the Most Frequent Trip Origins and Destinations in Aracaju, Brazil. Int. J. Environ. Res. Public Health 2020, 17, 7983.

AMA Style

Thuany M, N. Melo JC, B. Tavares JP, M. J. Santos F, C. M. Silva E, O. Werneck A, Dantas S, Ferrari G, Sá TH, R. Silva D. The Profile of Bicycle Users, Their Perceived Difficulty to Cycle, and the Most Frequent Trip Origins and Destinations in Aracaju, Brazil. International Journal of Environmental Research and Public Health. 2020; 17(21):7983.

Chicago/Turabian Style

Thuany, Mabliny, João Carlos N. Melo, João Pedro B. Tavares, Filipe M. J. Santos, Ellen C. M. Silva, André O. Werneck, Sayuri Dantas, Gerson Ferrari, Thiago H. Sá, and Danilo R. Silva. 2020. "The Profile of Bicycle Users, Their Perceived Difficulty to Cycle, and the Most Frequent Trip Origins and Destinations in Aracaju, Brazil" International Journal of Environmental Research and Public Health 17, no. 21: 7983.

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