Socio-demographic patterns of public, private and active travel in Latin America: Cross-sectional findings from the ELANS study ☆

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Abstract
Background: Active travel such as walking or cycling has been associated with more favorable health outcomes. However, evidence on patterns of transportation in Latin America is scarce. Therefore, the aim of this study was to quantify and characterise socio-demographic patterns of public, private and active travel in Latin American countries. Methods: Data from the Latin American Study of Nutrition and Health, a population-based, cross- sectional survey conducted in eight Latin American countries including Argentina, Brazil, Chile, Colombia, Costa Rica, Ecuador, Peru and Venezuela (n 1⁄4 9218; age range: 15–65 years). Trans- portation modes include public (bus, taxi, subway and train), private (car and motorcycle) and active (walking and/or cycling). Outcomes for this study include time spent in different modes of transportation. We performed overall and country-specific descriptive analyses to examine dif- ferences by sex, age, socioeconomic and education level. Results: For the overall cohort, public transport represent 34.9% of the total travel time, whereas private, walking and cycling represent 48.2%, 10.6% and 6.3% of the total travel time. Time spent using public travel was highest in Venezuela (48.4%); Peru had the highest proportions of private travel (52.5%); Time spent walking and cycling was highest in Costa Rica (14.8% and 12.2%, respectively). The average travel time spent in public and private transport were 299.5 min/week (95% CI: 292.4307.0) and 379.6 min/week (95% CI: 368.0, 391.5) respectively; figures for walking and cycling were 186.9 min/week (95% CI: 181.8, 191.9) and 201.1 min/ week (95% CI: 187.8, 216.9). Conclusions: Public and private transport were the most common forms of travel in Latin America. Active travel (walking or cycling) represent 17% of total physical activity, therefore, promoting and providing the right infrastructure for active commuting could translate in increasing the population overall levels of physical activity in Latin America.
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Journal of Transport & Health 16 (2020) 100788
2214-1405/© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/).
Socio-demographic patterns of public, private and active travel in
Latin America: Cross-sectional ndings from the ELANS study
Gerson Luis de Moraes Ferrari
a
,
b
,
*
, Irina Kovalskys
c
, Mauro Fisberg
b
,
d
,
Georgina G
omez
e
, Attilio Rigotti
f
, Lilia Yadira Cort
es Sanabria
g
,
Martha Cecilia Y
epez García
h
, Rossina Gabriella Pareja Torres
i
,
Marianella Herrera-Cuenca
j
, Ion
a Zalcman Zimberg
k
, Viviana Guajardo
c
,
Michael Pratt
l
, Priscila Bezerra Gonçalves
m
,
n
, Jorge Rosales-Salas
o
,
Carlos Cristi-Montero
p
, Fernando Rodríguez-Rodríguez
p
, Heather Waddell
q
,
Fanny Petermann-Rocha
q
,
r
, Carlos A. Celis-Morales
a
,
q
, Jean-Philippe Chaput
s
,
Shaun Scholes
t
, Dirceu Sol
e
b
, on behalf of theELANS Study Group, Core Group
members
a
Centro de Investigaci
on en Fisiologia del Ejercicio - CIFE, Universidad Mayor, Santiago, Chile
b
Departamento de Pediatria da Universidade Federal de S~
ao Paulo, S~
ao Paulo, Brazil
c
Commitee of Nutrition and Wellbeing, International Life Science Institute (ILSI-Argentina), Buenos Aires, Argentina
d
Instituto Pensi, Fundaç~
ao Jos
e Luiz Egydio Setubal, Hospital Infantil Sabar
a, S~
ao Paulo, Brazil
e
Departamento de Bioquímica, Escuela de Medicina, Universidad de Costa Rica, San Jos
e, Costa Rica
f
Centro de Nutrici
on Molecular y Enfermedades Cr
onicas, Departamento de Nutrici
on, Diabetes y Metabolismo, Escuela de Medicina, Ponticia
Universidad Cat
olica, Santiago, Chile
g
Departamento de Nutrici
on y Bioquímica, Ponticia Universidad Javeriana, Bogot
a, Colombia
h
Col
egio de Ciencias de la Salud, Universidad San Francisco de Quito, Quito, Ecuador
i
Instituto de Investigaci
on Nutricional, La Molina, Lima, Peru
j
Centro de Estudios del Desarrollo, Universidad Central de Venezuela (CENDES-UCV)/Fundaci
on Bengoa, Caracas, Venezuela
k
Departamento de Psicobiologia, Universidade Federal de S~
ao Paulo, S~
ao Paulo, Brazil
l
Institute for Public Health, University of California San Diego, La Jolla, CA, USA
m
Programa de P
os-Graduaç~
ao em Tecnologia em Saúde, Pontifícia Universidade Cat
olica do Paran
a, Paran
a, Brazil
n
Grupo de Pesquisa em Atividade Física e Qualidade de Vida, Pontifícia Universidade Cat
olica do Paran
a, Paran
a, Brazil
o
Centro de Economía y Políticas Sociales, Universidad Mayor, Chile
p
IRyS Group, Physical Education School, Ponticia Universidad Cat
olica de Valparaíso, Valparaíso, Chile
q
British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow,
Glasgow, United Kingdom
r
Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
s
Healthy Active Living and Obesity (HALO) Research Group, Childrens Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
t
Institute of Epidemiology and Health Care, University College London, London, United Kingdom
DOI of original article: https://doi.org/10.1016/j.jth.2019.100796.
Readers of this paper are advised to read the accompanying editorial by Mindell, Buliung and Watkins concerning research funding.
* Corresponding author. Jos
e Toribio Medina, 29, Estacion Central, Santiago, Chile.
E-mail address: gerson.demoraes@umayor.cl (G.L.M. Ferrari).
Contents lists available at ScienceDirect
Journal of Transport & Health
journal homepage: http://www.elsevier.com/locate/jth
https://doi.org/10.1016/j.jth.2019.100788
Received 18 February 2019; Received in revised form 10 October 2019; Accepted 1 November 2019
Journal of Transport & Health 16 (2020) 100788
2
ARTICLE INFO
Keywords:
Physical activity
Active travel
Transport
Latin America
Palabras clave:
Actividad física
Transporte activo
Transporte
Am
erica Latina
Palavras-chave:
Atividade física
Transporte ativo
Transporte
Am
erica Latina
ABSTRACT
Background: Active travel such as walking or cycling has been associated with more favorable
health outcomes. However, evidence on patterns of transportation in Latin America is scarce.
Therefore, the aim of this study was to quantify and characterise socio-demographic patterns of
public, private and active travel in Latin American countries.
Methods: Data from the Latin American Study of Nutrition and Health, a population-based, cross-
sectional survey conducted in eight Latin American countries including Argentina, Brazil, Chile,
Colombia, Costa Rica, Ecuador, Peru and Venezuela (n ¼9218; age range: 1565 years). Trans-
portation modes include public (bus, taxi, subway and train), private (car and motorcycle) and
active (walking and/or cycling). Outcomes for this study include time spent in different modes of
transportation. We performed overall and country-specic descriptive analyses to examine dif-
ferences by sex, age, socioeconomic and education level.
Results: For the overall cohort, public transport represent 34.9% of the total travel time, whereas
private, walking and cycling represent 48.2%, 10.6% and 6.3% of the total travel time. Time
spent using public travel was highest in Venezuela (48.4%); Peru had the highest proportions of
private travel (52.5%); Time spent walking and cycling was highest in Costa Rica (14.8% and
12.2%, respectively). The average travel time spent in public and private transport were
299.5 min/week (95% CI: 292.4307.0) and 379.6 min/week (95% CI: 368.0, 391.5) respectively;
gures for walking and cycling were 186.9 min/week (95% CI: 181.8, 191.9) and 201.1 min/
week (95% CI: 187.8, 216.9).
Conclusions: Public and private transport were the most common forms of travel in Latin America.
Active travel (walking or cycling) represent 17% of total physical activity, therefore, promoting
and providing the right infrastructure for active commuting could translate in increasing the
population overall levels of physical activity in Latin America.
RESUMEN
Introducci
on: Transporte activo como caminada o bicicleta ha sido asociado con una salud m
as
favorable. Sin embrago, la evidencia en transporte activo en Latinoam
erica es escasa. Por lo tanto,
el objetivo de este estudio fue cuanticar y describir las características sociodemogr
acas del
transporte público, privado y activo en países de Latino Am
erica.
M
etodos: Los datos provienen del Estudio sobre Nutrici
on y Salud en Latinoam
erica, y fueron
recogidos a trav
es de encuestas nacionales en ocho países, incluyendo Argentina, Brazil, Chile,
Colombia, Costa Rica, Ecuador, Peru y Venezuela (n ¼9.218; edad: 1565 a~
nos). Los modos de
transportarse fueron, público (bus, taxi, metro y tren), privado (auto y motocicleta) y activo
(caminar y/o bicicleta). Los resultados incluyeron el tiempo dedicado a los diferentes modos de
transporte. Se realiz
o un an
alisis descriptivo de cada país para examinar las diferencias por sexo,
edad, nivel socioecon
omico y educativo.
Resultados: En general, el tiempo utilizado para transporte público represent
o el 34,9%, mientras
que para el transporte privado, caminar y desplazarse en bicicleta representaron un 48,2%, 10,6%
y 6,3%. El tiempo utilizado en viajes públicos fue m
as alto en Venezuela (48,4%); Perú tuvo la
mayor cantidad de viajes privados (52,5%); el tiempo dedicado a caminar y bicicleta fue m
as alto
en Costa Rica (14,8% y 12,2%). El tiempo de viaje en transporte público y privado fue de
299,5 min/semana (IC95%: 292,4307,0) y 379,6 min/semana (IC95%: 368,0391,5); las cifras
de caminar y bicicleta fueron 186,9 min/semana (IC95%: 181,8191,9) y 201,1 min/semana
(IC95%: 187,8216,9).
Conclusiones: El transporte público y privado fueron las formas de desplazamiento m
as comunes.
Los viajes activos (caminada o bicicleta) representan el 17% de la actividad física total, por tanto,
promover y proporcionar la infraestructura adecuada para los desplazamientos activos, podría
traducirse en un aumento de los niveles generales de actividad física en Am
erica Latina.
RESUMO
Introduç~
ao: O transporte ativo, como caminhada ou bicicleta, tem sido associado com uma saúde
mais favor
avel. No entanto, as evid^
encias do transporte ativo na Am
erica Latina s~
ao escassas.
Portanto, o objetivo deste estudo foi quanticar e descrever as características sociodemogr
acas
do transporte público, privado e ativo em países da Am
erica Latina.
M
etodos: Os dados s~
ao provenientes do Estudo sobre Nutriç~
ao e Saúde na Am
erica Latinae
foram coletados por meio de pesquisas nacionais em oito países, incluindo Argentina, Brasil,
Chile, Col^
ombia, Costa Rica, Equador, Perú e Venezuela (n ¼9218; Idade: 15 a 65 anos). Os
modos de transporte foram: público (^
onibus, t
axi, metr^
o e trem), privado (carro e moto) e ativo
(caminhada e/ou bicicleta). Os resultados incluíram o tempo dedicado aos diferentes modos de
transporte. Uma an
alise descritiva de cada país foi realizada para examinar as diferenças por sexo,
idade, nível socioecon^
omico e educacional.
Result: ados: Em geral, o tempo utilizado no transporte público representou 34,9%, enquanto no
transporte privado, caminhada e ciclismo foram 48,2%, 10,6% e 6,3%. O tempo gasto em
G.L.M. Ferrari et al.
Journal of Transport & Health 16 (2020) 100788
3
transporte público foi maior na Venezuela (48,4%); O Peru teve a maior quantidade de transporte
privado (52,5%); o tempo gasto caminhando e andando de bicicleta foi maior na Costa Rica
(14,8% e 12,2%). O tempo m
edio por transporte público e privado foi de 299,5 min/semana
(IC95%: 292,4307,0) e 379,6 min/semana (IC95%: 368,0391,5); os números de caminhada e
bicicleta foram 186,9 min/semana (IC 95%: 181,8191,9) e 201,1 min/semana (IC 95%:
187,8216,9).
Conclus~
oes: O transporte público e privado foram as formas mais comuns de deslocamento. O
transporte ativo (caminhada ou ciclismo) representam 17% da atividade física total, portanto,
promover e fornecer infraestrutura adequada para o deslocamento ativo pode resultar em um
aumento nos níveis gerais de atividade física da populaç~
ao em Am
erica Latina.
1. Introduction
Strong evidence supports that physical activity (PA) has substantial health benets such as reducing premature mortality, car-
diovascular disease incidence and some types of cancer (Piercy and Troiano, 2018; Physical Activity Guidelines Advisory Committee,
2018). These benets can be obtained by performing structured PA (during leisure-time); but they can also be obtained through using
walking or cycling as forms of transportation (hereafter ‘active travel) (Celis-Morales et al., 2017; Step It Up, 2015). In fact, walking or
cycling may also be a good way for people who are inactive to become active (Andersen, 2016).
Active travel is a key component for the development of healthy sustainable environments and provides health benets as well as
ancillary benets related to greenhouse gas emissions (Dora et al., 2015; Haines et al., 2012). Moreover, increasing physical activity
related to travel is an essential population-wide strategy which aims to reverse the burden of noncommunicable diseases (NCDs), given
the substantial potential for tackling levels of physical inactivity through increasing overall PA levels (Celis-Morales et al., 2017; Pratt
et al., 2012).
Latin America is the most urbanized region in the world (80% of Latin Americans live in cities) (United Nations, 2012), and the
prevalence of obesity and chronic diseases has dramatically increased in the last 30 years (Ng et al., 2014; Rivera et al., 2014).
Furthermore, high population density, disorganized transit systems, trafc congestion, air and noise pollution, rising crime rates, and
pronounced income inequality are some of the characteristics of Latin American countries (United Nations, 2012; Barreto et al., 2012).
In terms of PA and NCDs, Latin America has a high prevalence of physical inactivity (39.1%) (Guthold et al., 2018) and NCDs in
comparison with other regions worldwide (World Health Organization, 2014). Therefore, there is an urgent need to look for different
strategies aiming to increase the overall levels of physical activity in the Latin American population.
Evidence from a comprehensive review suggested that populations with higher levels of active travel tend also to have higher
overall levels of PA than those populations who rely more on private transportation to get to and from places (Celis-Morales et al.,
2017; Saunders et al., 2013; Hamer and Chida, 2008). In addition, evidence has shown that individuals who engage in active travel
have lower risk of NCDs and all-cause mortality (Hamer and Chida, 2008; Saunders et al., 2013; Kelly et al., 2014). However, to date,
evidence on the extent of active travel and its distribution across different groups (by sex, age, and socioeconomic level) in Latin
America is limited. Filling this evidence gap could provide key information for informing national, regional and local transport and
public-health policies aiming to increase active travel and therefore overall levels of PA in the population. Therefore, the aim of this
study was to quantify and characterise socio-demographic patterns of public, private and active travel in Latin American countries.
2. Material and methods
2.1. Latin American study of nutrition and health
The Latin American Study of Nutrition and Health (Estudio Latinoamericano de Nutrici
on y Salud; ELANS) is a household-based cross-
sectional survey aimed at investigating food and nutrient intake as well as nutritional and PA statuses of nationally representative
samples from urban populations (Fisberg et al., 2016). The ELANS study includes data collected from eight Latin American countries:
Argentina, Brazil, Chile, Colombia, Costa Rica, Ecuador, Peru, and Venezuela. Thus, a total sample of 9218 participants aged between
15 and 65 years was included in this study. The sampling size required for sufcient precision was calculated with a 95% condence
level of and a maximum error of 3.5% and a survey design effect of 1.75. The study was based on complex, multistage sample design,
stratied by conglomerates, being all regions of each country represented, and random selection of main cities within each region
according to probability proportional to size method. Sample was stratied by sex, age, and socioeconomic level. Socioeconomic levels
was balanced based on national indexes used in each country (Fisberg et al., 2016) (Supplementary Table A1). For the selection of
households within each secondary sampling unit, they were selected through systematic randomization. Considering quotas for the
sex, age and socioeconomic level, the selection of the participant belonging to the domicile was made using 50% of the sample next
birthday, and 50% last birthday. The rationale and design of the study are reported in more detail elsewhere (Fisberg et al., 2016).
All the study sites are academy based (universities and other academic institutions) and each site adhered to a common study
protocol for interviewer training, implementation of eldwork, data collection and management, and quality control procedures. Data
collection for ELANS took place from September 2014 to February 2015. The ELANS protocol was approved by the Western Insti-
tutional Review Board (#20140605) and is registered at ClinicalTrials.gov (#NCT02226627). All participants of the ELANS study
provided written consent to take part in the ELANS study.
G.L.M. Ferrari et al.
Journal of Transport & Health 16 (2020) 100788
4
2.2. Exclusion criteria
Participants were excluded from the study if at recruitment they were pregnant/lactating, had a major physical/mental impairment
that impacted on food intake and PA levels, were 15 years old or 65 years old, if participants did not provide consent/consent from
a legal guardian, or if participants could not read.
2.3. Survey measures
Measurements were collected according to standardized procedures in each country. Mode of transportation, its frequency and
duration were collected using self-reported questionnaire. Participants were asked about what are the mode of transport generally used
to move from one place to another (bus, taxi, subway, train, car and motorcycle), how frequent they use this mode of transport
(number of days per week) and what is the average duration of travel (min/day). For the purpose of this study we generated two
categories for non-active travel, public travel which included those participants who reported travelling by bus, taxi, subway and train;
and private travel which include those participants reporting car and motorcycle transportation as main mode of travel. Time spent in
public and private travel was expressed as minutes per week (min/week) and calculated separately by multiplying the reported
number of days per week by the reported duration on an average day.
We refer to the measures as overall travel rather than commuting as the questions captured overall travel rather than travel
specically undertaken to/from work. For active travel the following questions were asked: (i) Do you walk or use a bicycle (pedal
cycle) for at least 10 min continuously to get to and from places?(Yes, No); (ii) In a typical week, how many days do you walk or ride a
bicycle for at least 10 min continuously to get to and from places?and (iii) How much time do you spend walking or bicycling for travel on a
typical day?These questions asked separately for walking and cycling. Time spent in active travel was expressed as min/week and
calculated in the same way as described for non-active travel.
Self-reported PA and sitting time was assessed using the International Physical Activity Questionnaire (IPAQ) long version, a
validated self-report measurement tool in Latin America (Celis-Morales et al., 2012; Hallal et al., 2010; Salvo et al., 2014). An in-
ternational group of experts developed this survey instrument to estimate PA patterns of populations from different countries and
sociocultural contexts (Craig et al., 2003; Hallal et al., 2010). A Spanish version previously validated in Mexican adults was used in
ELANS (Medina et al., 2013) and it was adapted for all eight participating ELANS countries, using culturally appropriate wording and
examples (Salvo et al., 2014).
The total time spent in PA (min/day) was assessed using six items of the IPAQ, which asked about the frequency and duration of
moderate- and vigorous-intensity PA as well as walking (Craig et al., 2003). We classed walking in this study as a moderately intensive
activity. Data were analyzed in accordance with the IPAQ scoring protocol (www.ipaq.ki.se). Adolescents and adults were categorised
physically inactive based on the WHO recommendations for moderate-to-vigorous physical activity (MVPA). For adolescents physi-
cally inactivity was dened as doing <60 min/day of MVPA. Whereas for adults, physical inactivity was dened as doing
<150 min/week of moderate-intensity PA or its equivalent 75 min/week of vigorous-intensity PA or its metabolically equivalent
<600 MET-min.week (World Health Organization, 2010).
Sitting time was used as a proxy of sedentary behaviour (Sedentary Behaviour Research Network, 2012). Participants were asked to
report time spent in sitting time over the past 7 days, separately for a weekday and a weekend day. We calculated average daily
sedentary time (min/day) as follows: [(weekday time*5 þweekend time*2)/7)] (Bauman et al., 2011).
Information about socio-demographics such as age (expressed in years), sex, socioeconomic and educational level was collected
using self-reported questionnaires. Socioeconomic data was divided into three categories (low, medium, high) based on the country-
specic indices (Fisberg et al., 2016). Age was categorised into 3 groups (1529, 3059, and 60 years) and education level was
presented as low (equivalent to non-formal education or primary school), middle (equivalent to secondary school), and high
(equivalent to technical or university degree).
2.4. Statistical analyses
We performed data analyses with IBM SPSS, version 22 for Windows (SPSS Statistics for Windows, 2013). Descriptive statistics
included the mean, frequency, percentage, and the associated 95% condence interval (95% CI). The two main outcomes were the
proportion of travel time spent by transport mode (public, private and active commuting (walking and cycling)), and the time spent in
each transport mode. We present overall and country-specic estimates by sex, age group, socioeconomic level, and educational level.
All our analyses were weighted for the survey design; with the weighting variable calculated according to the sex, socioeconomic level
and region of each participating country (Fisberg et al., 2016).
3. Results
3.1. Cohort characteristics
The main characteristics of the overall cohort and of each country are shown in Table 1. Overall, the response rate was 99.4% and
the mean age of the sample was 35.8 years. The proportion of women was slightly higher than for men (52.1% vs 47.9%), 52.0% of
participants reported a low socioeconomic level and 61.2% had a low educational level. On average, the mean amount of time spent in
total PA was 27.8 min/day. Over two-thirds of participants (68.8%; 83.1% in adolescents; 57.6% in adults, respectively) did not meet
G.L.M. Ferrari et al.
Journal of Transport & Health 16 (2020) 100788
5
Table 1
Baseline characteristics (mean or percentage and 95% condence interval) of participants for each Latin America country.
Variables Argentina Brazil Chile Colombia Costa Rica Ecuador Peru Venezuela Overall
N 1266 2000 877 1230 798 800 1113 1132 9218
Rate of response
(%)
99.7 98.9 99.6 99.1 99.5 99.8 98.5 99.8 99.4
Sex
a
Men 45.3 (42.648.1) 47.2 (44.949.4) 48.2 (45.051.7) 49.1 (46.252.0) 49.4 (46.252.6) 49.7 (46.353.1) 47.2 (44.350.1) 48.7 (45.851.4) 47.9 (46.848.9)
Women 54.7 (51.957.4) 52.8 (50.655.1) 51.8 (48.355.0) 50.9 (48.053.8) 50.6 (47.453.8) 50.3 (46.953.7) 52.8 (49.955.7) 51.3 (48.654.2) 52.1 (51.153.2)
Age (years)
b
36.7 (35.937.5) 36.5 (35.837.1) 36.4 (35.437.4) 36.9 (36.137.8) 35.2 (34.236.1) 34.3 (33.435.3) 34.1 (33.334.9) 34.9 (34.135.8) 35.8 (35.536.1)
Age group
a
15-29 38.7 (35.941.5) 38.1 (36.040.3) 40.1 (37.043.2) 41.4 (38.744.2) 44.1 (40.447.6) 45.2 (41.848.6) 46.7 (43,749.6) 44.1 (41.147.1) 41.7 (40.842.7)
30-59 55.3 (52.758.0) 56.3 (54.158.4) 54.5 (51.257.7) 52.1 (49.455.1) 52.0 (48.555.4) 49.7 (46.253.3) 49.3 (46.452.3) 55.1 (48.254.1) 53.0 (52.054.0)
60 6.0 (4.77.4) 5.6 (4.66.6) 5.4 (3.96.9) 6.5 (5.08.0) 3.9 (2.65.4) 5.1 (3.66.8) 4.0 (2.95.2) 4.8 (3.56.1) 5.3 (4.85.7)
SEL
a
Low 48.7 (45.851.5) 45.7 (43.747.9) 46.5 (42.849.8) 63.3 (60.766.0) 33.0 (29.636.3) 49.7 (46.352.9) 47.7 (44.950.7) 77.7 (75.180.4) 52.0 (51.053.0)
Medium 46.2 (43.248.9) 45.8 (43.647.9) 44.3 (41.147.8) 31.3 (28.634.0) 53.5 (50.356.9) 37.3 (34.040.7) 31.9 (29.034.4) 16.8 (14.819.1) 38.5 (37.539.5)
High 5.1 (3.96.6) 8.5 (7.49.7) 9.2 (7.211.3) 5.4 (4.26.7) 13.5 (11.115.9) 13.0 (10.815.4) 20.4 (17.922.8) 5.5 (4.26.8) 9.5 (8.910.1)
Education level
a
Low 75.5 (73.177.8) 48.4 (46.250.7) 65.1 (62.068.2) 64.9 (62.367.4) 81.6 (79.084.3) 82.9 (80.485.6) 23.0 (20.625.6) 68.7 (65.771.5) 61.2 (60.262.2)
Medium 20.3 (18.122.5) 43.1 (41.045.3) 23.5 (20.826.3) 24.0 (21.726.4) 12.7 (10.615.0) 10.5 (8.312.7) 67.2 (64.570.0) 12.5 (10.514.5) 29.2 (28.330.2)
High 4.3 (3.25.4) 8.4 (7.29.6) 11.4 (9.413.4) 11.2 (9.613.0) 5.7 (4.27.3) 6.5 (4.68.4) 9.8 (8.011.6) 18.8 (16.521.2) 9.5 (9.010.1)
Total PA (min/day)
b
28.18 (26.426.9) 23.5 (22.224.7) 29.6 (27.331.9) 28.6 (26.930.3) 32.7 (30.434.9) 42.3 (39.844.8) 31.2 (29.433.0) 19.1 (17.520.7) 27.8 (27.228.5)
PA guidelines
a
Not meeting 64.2 (61.167.5) 72.0 (69.674.5) 71.6 (68.175.0) 66.7 (63.969.7) 60.6 (56.664.4) 66.2 (62.769.9) 70.6 (67.773.5) 76.7 (73.679.7) 68.8 (67.870.0)
Meeting 35.8 (32.538.9) 28.0 (25.530.4) 28.4 (25.031.9) 33.3 (30.336.1) 39.4 (35.643.4) 33.8 (30.137.3) 29.4 (26.532.3) 23.3 (20.326.4) 31.2 (30.032.2)
Sitting time (min/
day)
b
267.8
(258.8276.2)
219.2
(212.5226.9
243.5
(233.6254.1)
241.3
(231.9250.9)
224.6
(214.2236.6)
173.7
(163.9182.8)
265.2
(256.2273.9)
197.6
(188.9205.5)
231.7
(228.5234.9)
Analyses were weighted for the survey design.
SEL: socioeconomic level; PA: physical activity.
a
Percentage and 95% condence interval.
b
Mean and 95% condence interval.
G.L.M. Ferrari et al.
Journal of Transport & Health 16 (2020) 100788
6
the WHO weekly guidelines for PA; this proportion was highest in Venezuela (76.7%) and was lowest in Costa Rica (60.6%). On
average, the mean level of sedentary behaviour was 231.7 min/day, ranging from 173.7 min/day in Chile to 265.2 min/day in Peru
(Table 1).
3.2. Proportions of travel time by sociodemographic factors
Fig. 1 shows the proportion of travel time spent in the four modes (public transport, private transport, walking and cycling) overall
and by country. Overall, more than two thirds of travel time was spent in public and private transport (34.9% and 48.2%, respectively);
less than one-fth was spent in active travel (10.6% and 6.3% for walking and cycling respectively). The proportion of travel time spent
in public transport was highest in Venezuela (48.4%) and Colombia (45.9%); this was more than double the equivalent proportion in
Costa Rica (21.0%). The proportion of travel time spent in private transport also varied by country, ranging from 39.7% in Colombia to
52% in Costa Rica and 52.5% in Peru, respectively. Travel time varied to a lesser extent between countries. The proportions of walking
travel ranged from 8.1% (in Colombia) to 14.8% in Costa Rica; the gures for cycling ranged from 1.0% in Venezuela to 12.2% in Costa
Rica.
The overall and country-specic proportions of travel time by sex, age group, socioeconomic level, and educational level are
available in Supplementary Fig. A1-A4 respectively. The proportions of time spent walking as part of travel was higher for women than
for men overall (12.6% vs 9.8% respectively); this pattern was consistent across countries. The proportion for cycling was higher for
men than for women overall (7.1% vs 3.1% respectively); but the pattern of sex differences varied across countries. Among men, the
highest proportions of time spent walking was observed for Costa Rica (14.8% of travel time) whereas Brazil reported the higher
proportion of time spent cycling as part of travel (11.0%). Among women, the proportion time spent walking ranged from 9.2% in
Colombia to 18.9% in Costa Rica; the proportion of time spent cycling ranged from 0.1% in Venezuela to 6.8% in Chile (Supplementary
Fig. A1).
Overall, the proportions of commuting time spent in public transportation were lower among participants aged 3059 and 60
years. Costa Rica stood out in this regard: for those aged 60 years, the proportion of travel time in public transport was markedly
lower than the other countries (7.5% Costa Rica; 34.6% overall) whilst time spent in private transport was higher (82.5% Costa Rica;
48% overall). The proportions of travel time spent walking was higher among those aged 60 years, whereas those for cycling were
higher among those aged 1529 years. The patterns in active travel by age varied across countries (Supplementary Fig. A2).
Overall, the proportions of travel time spent in public transport were higher among those in the lowest socioeconomic level,
whereas the travel time in private transport was lower. With a few exceptions (e.g. public transport in Costa Rica), these patterns were
consistent across countries. The proportions of travel time in walking and in cycling were higher in the lowest socioeconomic strata
overall; however, the patterns varied across countries. Among participants in the lowest socioeconomic level, the highest proportions
of travel time in walking and in cycling were in Costa Rica (18.4% and 14.6% respectively). Differences by socioeconomic level in the
proportion of travel time spent walking were most pronounced in Brazil (11.5% and 7.8% in the lowest and highest socioeconomic
levels respectively). Differences by socioeconomic level in cycling were sharpest in Costa Rica (14.6% and 5.9% of travel time in the
lowest and highest socioeconomic levels respectively) and in Brazil (11.6% and 1.9% respectively) (Supplementary Fig. A3).
Overall, similar but smaller differences in the proportions of travel time in public- and private-transportation were observed by
educational level. The proportion of travel time associated to walking was lower (9.4%) in the medium educational level than low
(11.4%) and high level (11.6%), whereas travel time associated to cycling was higher in the lowest educational level. Patterns in active
travel by educational level varied across countries. For example, the proportion of travel time in walking was highest in the lowest
educational group in Argentina (11.4% low; 6.7% high); a reversed pattern was observed in Costa Rica (15.6% low vs 23.4% high) and
in Ecuador (12.6% low vs 17.4% high) (Supplementary Fig. A4).
3.3. Time spent in different travel modes
Fig. 2 shows the mean time per week spent in each transport mode by country. Overall, the average travel time spent in public- and
private-transportation were 299.5 min/week (95% CI: 292.4307.0) and 379.6 min/week (95% CI: 368.0, 391.5), respectively;
equivalent gures for walking and cycling were 186.9 min/week (95% CI: 181.8, 191.9) and 201.1 min/week (95% CI: 187.8, 216.9),
respectively.
Mean levels of time spent in non-active travel were lowest in Costa Rica (public transport: 241.0 min/week; 95% CI: 217.1, 266.0;
private transport: 340.2 min/week; 95% CI: 301.0, 382.2). Mean levels of time spent in public transport was highest in Colombia
(348.7 min/week; 95% CI: 320.7, 374.8); time spent in private transport was highest in Argentina (302.8 min/week; 95% CI: 281.4,
325.6). Mean levels of travel time spent walking were lowest in Brazil (168.7 min/week, 95% CI: 158.5, 178.2) and highest in Costa
Rica (227.6 min/week; 95% CI: 208.9, 246.7); time spent cycling was on average lowest in Ecuador (116.8 min/week; 95% CI: 87.3,
150.5) and highest in Colombia (262.2 min/week; 95% CI: 218.7, 314.9) (Fig. 2).
Average levels of travel time in all four modes were generally higher for men than for women in all countries, with the differences
most pronounced for private transport and for cycling. For the sex-specic, estimates (Supplementary Fig. A5), mean time spent in
public transport was lowest in Costa Rica (men: 293.3 min/week; 95% CI: 250.8, 337.6; women: 203.7 min/week; 95% CI: 175.6,
231.9) and highest in Colombia (men: 385.1 min/week; 95% CI: 344.5, 426.0; women: 320.6 min/week; 95% CI: 289.9, 354.4).
Among men, average levels of cycling was highest in Argentina (283.1 min/week; 95% CI: 222.9, 349.4); among women, average
levels of cycling was lowest in Venezuela (72.4 min/week; 95% CI: 51.2, 90.3).
For the age-specic estimates (Supplementary Fig. A6), mean time spent in public transport was highest in Colombia (1529 years:
G.L.M. Ferrari et al.
Journal of Transport & Health 16 (2020) 100788
7
370.7 min/week, 95% CI: 328.3, 415.5; 3059 years: 339.7 min/week, 95% CI: 305.1, 373.9). Among those aged 60 years, the mean
time spent in walking was highest in Peru (230.0 min/week; 95% CI: 161.2, 310.2) and in Argentina (229.1 min/week; 95% CI: 164.7,
301.7). On average, levels of time spent cycling among the lowest and middle socioeconomic and educational groups were lowest in
Brazil (Supplementary Fig. A7-A8).
4. Discussion
The aim of this study was to quantify and characterise socio-demographic patterns of transport and active travel in eight Latin
American countries. Overall, four-fths of travel time was spent in transport (34.9% and 48.2% for public and private transport,
respectively); one-fth was spent in active travel (10.6% and 6.3% for walking and cycling respectively). However, there were
important differences across the countries. This multicountry study is the largest and more inclusive study to report patterns of travel
using nationally representative samples from urban populations from eight Latin American countries.
Overall, the proportions of travel time spent walking and cycling in the Latin American region are low (10.6% for walking, and
6.3% for cycling). Compare to European countries such as Germany and Sweden who reported active travel prevalence on above 20%
of the population, our estimates across Latin American countries shows a much lower prevalence (Hallal et al., 2012). In a systematic
review, de S
a et al. (2017) showed that the prevalence of walking as part of travel was 15.5%, which differ considerably by country,
ranging from 8.9% in Corrientes (Argentina) to 27.1% in Bogot
a (Colombia). In the same study, the prevalence of cycling as part of
travel was lower than the one reported in this study (3.2% vs. 6.3%), ranging from 1.3% in Argentina to 16.0% in Recife (Brazil). The
authors found that 12.0% of the studied population reported active travel (combination of walking and cycling). Moreover, the
proportion of individuals accumulating 30 min/day or more of active travel (walking and/or cycling) was 27.6% (95% CI: 26.5, 28.6)
in S~
ao Paulo, Brazil (de S
a et al., 2015). Comparisons of information from other studies, regions, countries (de S
a et al., 2015; Dinu
et al., 2018; Thern et al., 2015) and settings are challenging because there is no standardization of instruments used to report or assess
levels of physical activity associated to travel.
In relation to sex, men had a higher prevalence of cycling compared to women and women had a higher prevalence of walking than
men. These results can be explained in parts by the active commuting characteristics of these groups. Women are more likely to
perform trips accompanied and with functional objectives (e.g. taking their children to school), which are more suitable activities for
walking when compared to cycling that has a more individual and company-free prole. In addition, safety-related issues may explain
this relationship, women may feel less secure in pedaling for both heavy trafc and crime safety (de S
a et al., 2017).
Older people (60 years) do a little more walking as compared to younger ones (12.4% vs. 10.4%), which is expected to be a more
common activity among the elderly. On the other hand, the prevalence of cycling decrease with increasing age (7.8% vs 5.0%) because
older people are more vulnerable to falls and because they are exposed to less favorable environments. As probable, age group var-
iations against the 60 years were found for cycling, hypothetically reecting the effect of an environment less supportive for cycling
among susceptible groups. On the other hand, sectors of the city with well overall openness show a positive association with cycling.
Fig. 1. Prevalence of public, private, walking and cycling for each Latin America country.
*Public transport: bus, taxi, subway, and train; Private transport: car and motorcycle.
G.L.M. Ferrari et al.
Journal of Transport & Health 16 (2020) 100788
8
Also, areas with more intersections seem to encourage more cycling. This can be claried because a more permeable urban form, or
denser road network, allows elderly to nd smaller routes, making this active travel more attractive (Oliva et al., 2018).
Although, active travel differs by socio-demographics factors in Latin American countries, as presented in this study, prevalence of
active travel is relatively low compare to European countries (Hallal et al., 2012). However, there have been different initiatives
aiming to increase active travel in different Latin American countries (Gomez et al., 2015; de S
a et al., 2017). A recent study in S~
ao
Paulo city (Brazil) indicated that the presence of leisure or cycling lanes (also known as ‘cicloviasin Latin America) with less than 500
yards from home increased the participation of adults in walking (Florindo et al., 2017). Furthermore, some of the initiatives
implemented in several Latin American cities include restricted car access to main streets, which are temporarily closed to private
transport in order to create a safe environment for people to cycle, walk, run, and participate in social health promotion (Florindo et al.,
2017). These initiatives have shown to be very successful programmes in engaging the community to take part in leisure PA (Florindo
et al., 2017). For example, studies of such initiatives in Bogot
a have shown that users of cycling lanes are more likely to comply with PA
guidelines and have a higher quality of life (Sarmiento et al., 2010; Montes et al., 2012). Furthermore, the efcacy of Ciclovia pro-
grammes in Bogot
a has led to an expansion of the initiative, and it now spans across 461 cities in Latin America (Pratt et al., 2015).
Reecting the potential of Ciclovías to promote PA while decreasing inequalities in access to facilities, >80% of the programs were
connected with different income areas, parks, and promote sustainable modes of active commuting, such as cycling (Sarmiento et al.,
2017). Cycle lanes are a promising way of increasing PA at the population level, and simultaneously addressing other important urban
issues such as equity, quality of life, and the health physical environments (Sarmiento et al., 2017; Díaz del Castillo et al., 2016).
Despite the important environmental (Davis et al., 2005; Dinu et al., 2018) and health benets (Garrido-M
endez et al., 2017;
Rodríguez-Rodríguez et al., 2017; Steell et al., 2018), associated with active travel (Gomez et al., 2015) little research has been carried
out in Latin America to date. To the authorsknowledge, this is among the rst studies to examine variations in active commuting
Fig. 2. Descriptive analysis (mean and 95% condence interval) of public, private, walking and cycling of participants for each Latin America
country.
*Public transport: bus, taxi, subway, and train; Private transport: car and motorcycle.
G.L.M. Ferrari et al.
Journal of Transport & Health 16 (2020) 100788
9
across Latin American countries as a whole and its patterning by socio-demographic characteristics such as sex, age, and socioeco-
nomic level. This study provides important descriptive data for the development and targeting of interventions and policies to promote
active commuting and PA generally. Surveillance of current levels and patterning of motorized- and active forms of travel could
provide key information for understanding cross-national differences in the Latin America region and, therefore, help in the design of
informed policies for health promotion efforts to tackle physical inactivity levels in the region.
4.1. Limitations and strengths
ELANS employed a cross-sectional design, precluding inferences about causality. The validity of cross-country comparisons may
have been reduced to some extent by country-level variation in the questionnaire items on socioeconomic level (due to the legislative
requirements or established local standard layouts). Latin American countries span a wide range of health, social and economic in-
dicators; therefore, our results may not be directly generalizable to other countries. It is also well recognized that self-reported
measures can overestimate PA (Celis-Morales., 2012; Sallis and Saelens, 2000), and IPAQ may do this more than other physical ac-
tivity questionnaires (Dumith et al., 2011; Hallal et al., 2010). There is also the possibility of differential measurement error using
IPAQ, with some countries or population subgroups potentially giving relatively accurate estimates of their behaviour, while other
populations may over- or under-estimate their PA. This between-country variability appeared even greater in the World Health Survey,
which was composed of mostly developing countries (Guthold et al., 2008). Among the strengths, the present study used large-scale
population samples, so these prevalence estimates can be generalized to the country level. Only urban areas were included to maintain
homogeneous populations in the research, considering that almost all countries have at least 8090% of their population living in
urban areas (Fisberg et al., 2016; Salvo et al., 2014). This study included standardized and comparable data collection protocols to
facilitate comparisons across countries. Finally, compared with many current PA surveillance systems, IPAQ is a widely used in-
strument for measuring and tracking PA levels in Latin American populations.
4.2. Conclusions
Based on the results of this study, prevalence and mean levels of public, private and active travel in Latin American countries varied
widely across sociodemographic characteristics, suggesting that active forms of travel, especially cycling, should be encouraged to
improve population and environmental health in Latin America.
Our ndings could help to inform the planning of health policies and programmes designed to reduce levels of physical inactivity,
as well as the local and cultural adaptation of these policies and programmes for successful implementation across Latin America.
Additionally, future research is required to identify other practical key elements, such as legislation, policy, barriers and facilitators for
promoting active travel in Latin America. This study and other similar future studies could help to promote active transport within
Latin American communities and act as a key component in the ght against the burden of NCDs and climate change. Moreover, the
two main health problems faced the high prevalence of NCDs and climate change, in Latin America may be ameliorated through the
promotion of active travel, but further research is needed.
Funding source
The ELANS was supported by a scientic grant from the Coca Cola Company, and support from the Ferrero, Instituto Pensi/Hospital
Infantil Sabara, International Life Science Institute of Argentina, Universidad de Costa Rica, Ponticia Universidad Cat
olica de Chile,
Ponticia Universidad Javeriana, Universidad Central de Venezuela (CENDES-UCV)/ Fundaci
on Bengoa, Universidad San Francisco de
Quito, and Instituto de Investigaci
on Nutricional de Peru. The funding sponsors had no role in study design, in the collection, analyses,
or interpretation of data, in the writing of the manuscript, and in the decision to publish the results. This study is registered at www.
clinicaltrials.gov (No. NCT02226627).
Author contributions
G.L.M.F., J.RS., and C.A.C-M., had full access to all of the data in the study and take responsibility for the integrity of the data and
the accuracy of the data analysis. The corresponding author and C.A.C.M had full access to all the data in the study and had nal
responsibility for the decision to submit for publication. Study concept and design: G.L.M.F., and C.A.C-M. Data collection: G.L.M.F, I.
K, M.F, G.G.S, A.R, L.Y.C.S, M.C.Y.G, R.G.P.T, M.HC, I.Z.Z, V.G, M.P, P.B.G, JR-S, J-PC, SS and DS. Statistical analysis: G.L.M.F., J.
RS., F.P-R and CACM. Drafting of the manuscript: G.L.M.F., J.RS., HW, FPR, and C.A.C-M. All authors have provided a critical
revision and nal approval of the manuscript.
Declaration of competing interest
None to declare.
Acknowledgments
We would like to thank the following individuals at each of the participating sites who made substantial contributions to the
G.L.M. Ferrari et al.
Journal of Transport & Health 16 (2020) 100788
10
ELANS: Luis A. Moreno, Beate Lloyd, Brenda Lynch, Mariela Jauregui, Alejandra Guidi, Luis Costa, and Regina Mara Fisberg.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.jth.2019.100788.
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