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Journal of Transport & Health 17 (2020) 100819
Available online 9 April 2020
2214-1405/© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Nutritional and metabolic benets associated with active and
public transport: Results from the Chilean National Health Survey,
ENS 2016–2017
�
Alvaro Passi-Solar
a
,
b
, Paula Margozzini
b
,
*
, Andrea Cortinez-O’Ryan
b
,
c
,
Juan C. Mu~
noz
d
, Jennifer S. Mindell
a
a
Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London, WC1E 6BT, UK
b
Department of Public Health, School of Medicine, Ponticia Universidad Cat�
olica de Chile, Diagonal Paraguay 362, CP 88330077, Santiago, Chile
c
Department of Physical Education, Sports and Recreation, Universidad de La Frontera, Av Francisco Salazar, 01145, Temuco, Chile
d
Department of Transport Engineering and Logistics, Centre for Sustainable Urban Development (CEDEUS), Ponticia Universidad Cat�
olica de Chile,
Av. Vicu~
na Mackenna 4860, CP 7820436, Macul, Santiago, Chile
ARTICLE INFO
Keywords:
Active transport
Anthropometry
Public transport
Transport mode
Biomarkers
National Health survey
ABSTRACT
Background: Physical inactivity is one of the main risk factors for death worldwide. There is a
paucity of studies about the association between transport and objective health measures using
nationally representative samples worldwide, especially from Latin American countries. The aim
of this research is to explore the relationship between active transportation and objective health
measures in Chile.
Methods: We analysed the Chilean National Health Survey (ENS) 2016–2017, based on a na-
tionally representative sample of non-institutionalised adults aged �15 years (n ¼6,113). ENS
included anthropometric measures (weight, height, waist circumference), a specic question
about the main mode of transportation and several metabolic markers.
Results: 41%, 38% and 21% of participants used public transport, motor vehicles and active
(cycling and walking) transport respectively. Higher levels of active transport were observed in
males, younger groups, less educated and rural populations. Both active and public transport were
associated with multiple nutritional and metabolic benets such as lower BMI, lower waist
circumference, less obesity, higher vitamin D, lower cholesterol and lower hepatic inammation.
Associations persisted after adjusting for other healthy lifestyles. Stronger benets were observed
in males than in females.
Conclusions: Promoting active transportation in urban planning policies may help Chile tackle the
growing burden of chronic diseases.
RESUMEN
Antecedentes: La inactividad física es uno de los principales factores de riesgo de muerte en todo el
mundo. Hay una escasez de estudios sobre la asociaci�
on entre el transporte y las medidas obje-
tivas de salud utilizando muestras representativas a nivel nacional en todo el mundo,
* Corresponding author.
E-mail addresses: arpassi@uc.cl (�
A. Passi-Solar), pmargozz@uc.cl (P. Margozzini), andrea.cortinez@uc.cl (A. Cortinez-O’Ryan), jcm@ing.puc.cl
(J.C. Mu~
noz), j.mindell@ucl.ac.uk (J.S. Mindell).
Contents lists available at ScienceDirect
Journal of Transport & Health
journal homepage: http://www.elsevier.com/locate/jth
https://doi.org/10.1016/j.jth.2019.100819
Received 24 April 2019; Received in revised form 27 December 2019; Accepted 28 December 2019
Journal of Transport & Health 17 (2020) 100819
2
especialmente de países latinoamericanos. El objetivo de esta investigaci�
on es explorar la relaci�
on
entre el transporte activo y las medidas de salud objetivas en Chile.
M�
etodos: Analizamos la Encuesta Nacional de Salud de Chile (ENS) 2016–2017, basada en una
muestra representativa a nivel nacional de adultos no institucionalizados con edades �15 a~
nos (n
¼6.113). ENS incluy�
o medidas antropom�
etricas (peso, altura, circunferencia de la cintura), una
pregunta especíca sobre el modo principal de transporte y varios marcadores metab�
olicos.
Resultados: 41%, 38% y 21% de los participantes usaron transporte público, vehículos de motor y
transporte activo (ciclismo y caminata) respectivamente. Se observaron niveles m�
as altos de
transporte activo en hombres, grupos m�
as j�
ovenes, poblaciones menos educadas y rurales. Tanto
el transporte activo como el público se asociaron con múltiples benecios nutricionales y meta-
b�
olicos, como un IMC m�
as bajo, una circunferencia de cintura m�
as baja, menos obesidad, m�
as
vitamina D, menos colesterol y una menor inamaci�
on hep�
atica. Las asociaciones persistieron
despu�
es de ajustar por otros estilos de vida saludables. Se observaron benecios m�
as fuertes en
hombres que en mujeres.
Conclusiones: Promover el transporte activo en las políticas de planicaci�
on urbana puede ayudar
a Chile a enfrentar la creciente carga de enfermedades cr�
onicas.
ABSTRATO
Antecedentes: A inatividade física �
e um dos principais fatores de risco para a mortalidade no
mundo. H�
a uma escassez de estudos sobre a associaç~
ao entre transporte e medidas objetivas de
saúde, utilizando amostras nacionalmente representativas em todo o mundo, principalmente de
países da Am�
erica Latina. O objetivo desta pesquisa �
e explorar a relaç~
ao entre transporte ativo e
medidas objetivas de saúde no Chile.
M�
etodos: Analisamos a Pesquisa Nacional de Saúde do Chile (ENS) 2016–2017, com base em uma
amostra nacionalmente representativa de adultos n~
ao institucionalizados com idade �15 anos (n
¼6.113). A ENS incluiu medidas antropom�
etricas (peso, altura, circunfer^
encia da cintura), uma
pergunta especíca sobre o principal meio de transporte e v�
arios marcadores metab�
olicos.
Resultados: 41%, 38% e 21% dos participantes usaram transporte público, veículos motorizados e
transporte ativo (ciclismo e caminhada), respectivamente. Níveis mais altos de transporte ativo
foram observados em homens, grupos mais jovens, populaç~
oes menos instruídas e rurais. Tanto o
transporte ativo quanto o público foram associados a múltiplos benefícios nutricionais e meta-
b�
olicos, como menor IMC, menor circunfer^
encia da cintura, menos obesidade, maior vitamina D,
menor colesterol e menor inamaç~
ao hep�
atica. As associaç~
oes persistiram ap�
os o ajuste para
outros estilos de vida saud�
aveis. Benefícios mais fortes foram observados nos homens do que nas
mulheres.
Conclus~
oes: A promoç~
ao do transporte ativo nas políticas de planejamento urbano pode ajudar o
Chile a enfrentar o crescente fardo das doenças cr^
onicas.
1. Introduction
According to the World Health Organization, physical inactivity is one of the main risk factors for death worldwide, responsible for
13.4 million DALYs worldwide and causing a higher burden among low-income and middle-income countries (75% of attributable
DALYs) (Ding et al., 2016). Motor vehicle trafc is associated with premature mortality and morbidity through trafc injuries, physical
inactivity and trafc-related environmental exposures including increases in air pollution, noise and temperature levels, as well as
reductions in green space (Khreis et al., 2016). Active modes of transport (e.g. cycling, walking) are those ways of travelling involving
physical activity during the whole trip or as a part of it. Evidence indicates that shifting from a non-active to active transport increases
physical activity, reduces obesity, noise and air pollution, trafc injuries and social isolation (Brown et al., 2017; de Nazelle et al.,
2011; Maizlish et al., 2017; Martin et al., 2015; Sugiyama et al., 2013).
Additionally, studies have shown that health benets of cycling outweigh risks of injuries and mortality (Andersen et al., 2018; de
Hartog et al., 2010; Mueller et al., 2015). Public transport is also associated with increased physical activity (Besser and Dannenberg,
2005; Voss et al., 2016) since most transit trips involve walking to/from transportation stops or between transport modes (van Soest
et al., 2019). Probably because of this, public transport use is related to other health benets such as reduced obesity, hypertension,
diabetes, and mental disorders when compared with travel by private motor vehicles modes (Tajalli and Hajbabaie, 2017). Cel-
is-Morales et al. (2017) examined a sample of 263,000 participants from the prospective UK Biobank study and found that commuting
by bicycle was associated with a lower risk of cardiovascular disease, cancer, and all-cause mortality, while walking was associated
with a lower risk of cardiovascular disease only. The authors argue that active commuting should be encouraged to reduce the risk of
death and the burden of important chronic conditions. Prior research using objective measures of health outcomes, such as BMI, waist
circumference (Tajalli and Hajbabaie, 2017), lipid prole (Xu et al., 2013) and mortality (Celis-Morales et al., 2017) are valuable since
they helped to show some health benets related to transport modes and overcome the limitations of self-reported data. Research using
metabolic biomarkers has not been extensively explored, and it would provide more strength to the evidence of the health impacts
related to transport modes. For instance, vitamin D levels are higher among those with more “outdoors” activities and active
�
A. Passi-Solar et al.
Journal of Transport & Health 17 (2020) 100819
3
commuting (Donneyong et al., 2016; Solis-Urra et al., 2019). Since vitamin D synthesis is mainly based on sunlight, both active and
public transport modes can be expected to increase vitamin D levels. Physical activity has been associated with lower levels of hepatic
inammation markers (Keating et al., 2012). It could be suggested that those using more active modes of transport could have a better
hepatic prole. To our knowledge, there is no prior research evaluating the association between public transport and active transport,
analysed separately, with Vitamin D or hepatic inammation markers.
The evidence showing the relationship between transport modes and health outcomes in Latin American is scarce and mixed,
focusing mainly on active commuting. Ramírez-V�
elez et al. (2017) found that Colombian children and adolescents who regularly
commuted to school by bicycle showed a lower incidence of metabolic syndrome and better physical tness than their non-cyclist
counterparts. Another study that analysed Colombian university students showed that those who walked to campus were less likely
to have high blood pressure, obesity and low HDL cholesterol (García-Hermoso et al., 2018). Counterintuitively, in Brazil, Treff et al.
(2017) showed a protective effect of leisure-time physical activity against hypertension amongst adult women, but not for physical
activity during transportation. To our knowledge, only two studies have explored this topic in Chile. Both of them used data from the
ENS 2010, and both found associations of travel-related physical activity and cardiometabolic markers such as triglycerides, waist
circumference, BMI as well as health outcomes such as metabolic syndrome and diabetes (Sadarangani et al., 2018; Steell et al., 2018).
However, as in the aforementioned Latin American studies, the associations of public transport and health have not been individually
examined yet, therefore, we do not know if public transport by itself may also contribute to an improved cardiometabolic prole in
Latin America.
Chile is a very centralised country, with approximately 40% of its population living in its capital city, Santiago (INE, 2018). The
country is motorising quite fast; in 2002 there were 144 cars per 1,000 inhabitants (Roque and Masoumi, 2016), while now this has
risen to around 270 (INE, 2017). The modal share has also changed quite drastically in the last decades. In the case of Santiago, the
modal share of private car use increased 12% in 1977 to 46% in 2012 (SECTRA and Universidad Alberto Hurtado, 2014), despite
massive investments in an impressive Metro network and public transport subsidies. Some Chilean cities have seen a remarkable
increment in bicycle use. In the case of Santiago, according to the citywide origin-destination survey, cycling’s contribution to urban
mobility doubled between 2001 and 2012, reaching 4% of daily trips ( SECTRA and Universidad Alberto Hurtado, 2014). Since then,
most observers agree that bicycle use has kept growing in Santiago, fed by active cycling advocacy groups (Sagaris, 2015); a broader
and better bike path network; and the appearance of docked and dockless public bikes in the most afuent area of the city.
In Chile, transport investments are carefully evaluated before implementing them (OECD, 2017). This involves a quite rigorous
process, in which future ows and levels of service are predicted, to decide whether a given project should move ahead. Based on this
prediction, several direct impacts as time savings or operational costs are estimated. Although methodologies to include indirect
health-related impacts, such as pollution, crashes and injuries, have been developed, they are still waiting to be incorporated (Min-
isterio de Desarrollo Social de Chile, 2019): the impact of transport mode choice on individual health has been largely ignored.
Planners are aware that someone shifting from car to cycle for the commuting trip would receive important health benets at the
individual level. However, the current cost-benet methodology to evaluate the convenience of infrastructure projects neglects in-
dividual health impacts. Thus, if the time taken by the bike trip takes longer than by car, the methodology might treat the modal shift as
a cost, which appears as a contradiction given the personal option of the traveller and the positive health impacts. Thus, identifying an
association between mode choice and health condition is relevant to incorporate a key attribute that differentiates between different
transport modes, especially between active modes as walking and bicycling, and passive transport modes as the automobile.
There is a paucity of studies about the association between transport and objective measures of health as anthropometric and
metabolic markers using nationally representative samples worldwide, especially among Latin American countries. Given that, the
recent ENS 2016–2017 added a new, specic question about the main type of transport and added new metabolic markers (e.g. serum
vitamin D). It, therefore, provides an opportunity to further explore the relationship between active transportation and objective
measures of health in Chile. The primary aim of this study was to assess the association between demographic and socioeconomic
factors with transport mode. The secondary aim was to explore the association between anthropometric and metabolic markers with
transport mode.
2. Methods
2.1. Data source and sample
ENS 2016–2017 was a household survey with a stratied multistage probability sample of 6,233 non-institutionalised participants
aged �15 years from urban and rural Chile including the 15 Chilean geographical regions. The data collection was done between
August 2016 and March 2017. Sample size was calculated with 20% relative error for the estimation of national prevalence over 3%.
One participant per household was randomly selected using a computational Kish algorithm. Response rate was 67%; refusal rate was
9.8%, with no replacements. The study protocol and ethical consent forms were approved by the ethics committee of the Ponticia
Universidad Cat�
olica de Chile (PUC) and the Ministry of Health. A team of lay interviewers and certied nurses were trained and
supervised to apply the survey using electronic devices for data capture. In the rst home visit, a lay interviewer applied health
questionnaires, including a question on the main type of transport used at least once a week. A trained nurse applied questionnaires,
measured anthropometry (waist circumference, weight and height) and performed multiple biological sampling in a second-day visit
to 89% of the sample. Excluding the missing values on mode of transport (n ¼110), the analysed sample consisted of 6,113
participants.
�
A. Passi-Solar et al.
Journal of Transport & Health 17 (2020) 100819
4
2.2. Variables analysed
Mode of transport: self-reported main mode of transport measured with the following question: “out of the following alternatives,
what is the transportation mode you most frequently use, at least once a week?“. Three categories of transport were created based on
the original response categories 1. Motor vehicle (vehicle driver or light vehicle passenger); 2. Active modes (cycling or walking) and 3.
Public transport.
Anthropometry: nurse measurement of waist circumference (WC) in cm, body mass index (BMI) in kg/m
2
and obesity (BMI�30 kg/
m
2
).
Laboratory analyses: all blood samples were run at a central laboratory (UC Christus). Serum vitamin D: Serum 25-Hydroxy
Vitamin D2 and D3 (ng/mL) were measured among females 15–49 years and males and females of 65 or older, using liquid
chromatography-tandem mass spectrometry (LC-MS/MS) (Q TRAP 4500/AB SCIEX). We used the sum of D2 and D3. Serum total
cholesterol (mg/dL) was measured using an enzymatic, colorimetric method (CHOD-PAP). Cholesterol samples with 9 h or more of
fasting were included in the analyses. Gamma-glutamyltransferase (GGT) (U/L) was measured using an enzymatic, colorimetric
method. Alanine transaminase (ALT) (U/L) was measured with UV test according to the IFCC method without pyridoxal-5-phosphate
activation. Total cholesterol, GGT and ALT were measured among a random subsample of 62% of the total sample, using the Cobas
8000-c702/Roche. Details of the laboratory methods and variation coefcients are described elsewhere (Ministerio de Salud de Chile,
2018).
Healthy lifestyles: Current smoker was dened as occasional or daily smoker. Water intake was measured with the following
question: “How many glasses of water do you drink daily?” and it was dichotomized into <6 or �6 glasses/day. Reduced-fat dairy
consumption was dened according to the question: “What kind of dairy do you preferably consume?“. Three categories were con-
structed: 1. dairy-free diet, 2. skimmed/low-fat and 3. Whole milk. Fruit and vegetable consumption, according to the number of days
per week and the number of portions per day in a typical week, was dichotomized into <5 or �5 portion/day. Alcohol use disorders
were assessed with the AUDIT score. Frequency of physical activity during leisure time was measured with the following question: “In
the last month, did you practice sports or physical activities outside of your work schedule, for 30 min or more each time?” with four
options as answers: 1. �3 times/week, 2. Once or twice/week, 3. <4 times/month and 4. No sports in the last month.
2.3. Statistical analyses
We described the sample of 6,113 participants with valid data in mode of transport, according to gender, age (mean and categories:
15–24, 25–44, 45–64, �65 years) educational level (i.e. low:<8y, medium:8-12y, high:>12y of formal education) and urban/rural
residence.
For the rst aim we analysed mode of transport as the outcome and age, gender, educational level and urban/rural residence as the
exposure variables. First, the distribution of modes of transport was described according to the exposure variables. Secondly, separate
multinomial logit regression models were performed to determine the associations between the transport mode and age, gender,
educational level and urban/rural residence. Models were adjusted for age and gender. Age was included in the models as a continuous
variable; the other independent variables were entered as categorical. From these models, we estimated Relative Risk Ratios (RRR)
with accompanying 95% condence intervals (95% CI) for active and public transport, using motor vehicle as the reference category.
For the second aim we analysed WC, BMI and obesity as the outcomes and mode of transport as the exposure variable. First, we
described mean WC, mean BMI and obesity prevalence with 95% CI according to mode of transport and gender. Secondly, associations
between WC and BMI with mode of transport were calculated by linear regression, and associations between obesity and mode of
transport using logistic regression. Three regression models were performed for each outcome (WC, BMI and obesity) and stratied by
gender: model 1, non-adjusted; model 2, adjusted by age; model 3, adjusted by age and healthy lifestyles: current smoker, water intake
�6 glasses/day, reduced-fat dairy consumption, fruit and vegetable consumption �5 portion/day, AUDIT score and frequency of
physical activity during leisure time. Age and AUDIT score were included in the models as continuous variables; the other independent
variables were entered as categorical. Thirdly, gender-specic serum vitamin D, total cholesterol, ALT and GGT levels were also
evaluated against transport mode using the three models described above. Vitamin D analyses were stratied in two age groups (15-
49y and �65y) and self-reported sunlight exposure (little or a lot in the last week) was also included in the model (3).
Analyses were based on complete-cases. We used the appropriate weights in all analyses; these account for differences in selection
probability and minimise bias from non-response. P-values <0.05 were classed as signicant (two-tailed). All analyses were conducted
in Stata V14.0 (StataCorp LP, College Station, Texas) adjusting for the complex survey design.
3. Results
3.1. Descriptive statistics of the sample
The total ENS 2016–2017 sample included 6,233 participants aged �15 years, of whom 6,113 had valid information on transport
modes and demographic variables, and 5,385 and 5,382 had valid measures of BMI and WC respectively. Demographic characteristics
of the sample with valid data on transport mode are presented in Table 1.
�
A. Passi-Solar et al.
Journal of Transport & Health 17 (2020) 100819
5
3.2. Mode of transport associated with socio-demographic variables
As seen in Fig. 1, motor vehicle was the most frequently reported transport mode (41%); followed by public transport (38%) and
active modes (21%). The use of public transport was higher among females (44% females; 31% males) while the prevalence of motor
vehicle use was lower for females (36% females; 47% males). Active travellers were: 15%, walkers (17% females; 13% males) and 6%
cyclists (3% females, 9% males). Chile, a long narrow country, has 15 geographical regions. The main type of transport varied by
geographical region, with highly populated regions (located centrally in the country) having higher rates of public transport use, as
shown in Fig. 2.
The age-adjusted multinomial regression (Fig. 3) showed that females were more likely than males to use public transport, with a
Relative Risk Ratio (RRR) of 1.90 (95% CI 1.55, 2.32, reference: motor vehicle). Active and public transport decreased with age (RRR
¼0.56 (0.38–0.82) and RRR ¼0.35 (0.25–0.49), respectively, age �65 vs 15-24y); participants with low level of education were more
likely to use active transport than were those of high education level (RRR ¼1.73 (1.28–2.33); while participants residing in rural
areas were more likely to use active transport (RRR ¼1.27 (0.97–1.67)) and less likely to use public transport than those residing in
urban areas (RRR ¼0.71 (0.52–0.97)).
3.3. Anthropometric and metabolic markers associated with mode of transport
Descriptive statistics for WC, BMI and obesity by transport mode are shown in Fig. 4. The regression models showed gender dif-
ferences in the associations between the anthropometric measures and transport mode (Table 2). BMI was associated with transport
mode among males and females, however, WC and obesity were associated with transport mode only among males. Among males.
these associations were signicant (p <0.001) in the crude model (1), age-adjusted model (2) and in the fully adjusted model (3). Men
using active transport showed an odds ratio (OR) estimated by model (3) of 0.53 (0.35–0.81) of being obese compared with motor
vehicle users. WC was 5.20 cm (3.29–7.11) smaller and BMI was 1.90 kg/m
2
(1.14–2.65) lower among male active than motor users.
Similar signicant associations were found among males when comparing public versus motor vehicle transport in the fully adjusted
model (3). Among females, active transport was associated with signicantly lower mean BMI (β ¼ 0.84 (1.67 to 0.02)) than
motor vehicle transport in the fully adjusted model (3). Additional analyses pooling both genders showed similar associations to those
described among males (see Table 1, Supplemental Digital Content 1, which shows the regression coefcients with their 95% CI for all
persons).
Higher levels of vitamin D were found among females of both age groups using active transport compared with public transport
when the fully adjusted model (3) was used (β ¼2.71 mg/dL (0.74–4.67) for those aged <50y and β ¼2.85 mg/dL (0.56–5.15) for
those aged �65y). Higher levels of vitamin D were found among males and females aged �65y using active transport compared with
motor vehicle (β ¼3.98 mg/dL (1.46–6.50) for males; β ¼2.69 mg/dL (0.61–4.77) for females). Total cholesterol was lower among
Table 1
Sample characteristics. Chile, ENS 2016–2017.
Variable Category n
a
% or mean (95% CI)
Sociodemographic characteristics
Gender Males 2,262 48.9% (46.6–51.1)
Females 3,851 51.1% (48.9–53.4)
Age (y) x 6,113 43.0 (42.2–43.8)
15–24 831 19.1% (17.3–20.9)
25–44 1,794 37.4% (35.0–39.8)
45–64 2,028 30.5% (28.5–32.6)
�65 1,460 13.1% (11.8–14.5)
Zone Urban 5,136 88.8% (87.3–90.1)
Rural 977 11.2% (9.9–12.7)
Educational level (years of formal education) Low (<8) 1,425 16.3% (14.4–18.3)
Medium (8–12) 3,272 55.5% (52.6–58.4)
High (>12) 1,362 27.6% (24.8–30.7)
missing 54 0.5% (0.3–0.9)
Anthropometric measures
Waist (cm) x 5,382 93.2 (92.6–93.9)
BMI (kg/m
2
) x 5,385 28.5 (28.3–28.8)
Metabolic markers
Vitamin D (ng/mL, males �65y) x 447 21.3 (19.8–22.8)
Vitamin D (ng/mL, females <50y) x 1580 20.1 (19.3–20.8)
Vitamin D (ng/mL, females �65y) x 792 17.7 (16.8–18.6)
Total cholesterol (mg/dl) x 3,471 177.3 (175.0–179.6)
ALT (U/L) x 3,619 25.6 (24.5–26.7)
GGT (U/L) x 3,631 30.5 (28.6–32.5)
a
Non-weighted sample sizes. Weighted estimation with 95% condence intervals (95% CI).
�
A. Passi-Solar et al.
Journal of Transport & Health 17 (2020) 100819
6
males using active and public transport than motor vehicle (β ¼ 13.78 mg/dL (21.3 to 6.26) and β ¼ 8.58 mg/dL (16.99 to
0.18), respectively); the opposite was seen among females when comparing active transport versus motor vehicle (β ¼8.07 mg/dL
(1.10–15.04)). Among males, active and public transport users had lower levels of ALT when compared to motor vehicle users (β ¼
5.81 U/L (9.61 to 2.03) and β ¼ 5.18 (9.37 to 1.00), respectively); among males, GGT showed lower levels among public
transport than motor vehicle users (β ¼ 9.89 U/L (15.92 to 3.87)) (see detailed results in Table 2).
4. Discussion
This analysis from a large representative sample of the Chilean adult population indicates that around 41% were using public
transport, 38% motor vehicle and 21% active modes (cycling and walking) as the main modes of transport in Chile during 2016–2017.
We found higher levels of active transport among males, younger groups, less educated and rural populations. This pattern has also
been reported in other countries (Nehme et al., 2016; Reis et al., 2013; S�
a et al., 2018; Titze et al., 2014). Our results on active transport
are consistent with those reported by Aguilar-Farias et al. (2019) using the Chilean National Environment Survey (CNES) 2014 and
2015, where cycling prevalence was 7%, with higher use among youth and participants of low socioeconomic status. According to the
CNES2015, females tended to walk more than males, however, the overall prevalence of active transport was similar by gender
(Ministerio del Medio Ambiente de Chile, 2018). This study broadens the evidence obtained by the transportation sector, where trips
rather than prevalence were studied. The Chilean Origin-Destination Survey (EOD) 2012 showed that around 30% of the trips in
Santiago were made by public transport, another 30% by motor vehicle and around 40% were made walking or cycling (SEC-
TRAUniversidad Alberto Hurtado, 2014). Our results showed that Santiago had higher use of public transport (around 50%) and lower
of active transport (20%). However, these differences between EOD and ENS are expected, because the questions were different. ENS
asked about the transportation mode most frequently used (at least once a week) in a sample aged �15y while EOD described total trips
in a given week-day and a weekend day with no age restrictions.
Our study showed that anthropometric benets are associated with active and public transport in males: we found lower WC, BMI
and obesity than in motor vehicle users. We also found lower BMI among females using active transport than motor vehicles, but the
magnitude of the association was 58% smaller than among males (0.9 versus 1.9 kg/m
2
for females and males, respectively). We ran
three models to analyse the associations and the effects of potential confounders. The likelihood of being obese was lower for male
active travellers compared with motor vehicle travellers. This held after adjusting for fruit-vegetable, alcohol and water consumption
as well as physical activity and smoking. Other benets were associations with decreased levels of hepatic enzymes, lower total
cholesterol and a higher level of serum vitamin D. Our study described a dose-response relationship with transport modes. Increased
health benets were seen among active transport users (cycling or walking), followed by mid benets among public transport users
when compared with motor vehicle users. According to our fully adjusted model, WC, BMI, obesity, total cholesterol and hepatic
enzymes were signicantly lower among male public transport than motor vehicle users.
Our results are in line with the benecial associations of active transport on BMI described in Chile by Steell et al. (2018) using ENS
2010. They reported that 30 min increase in active transport measured by the Global Physical Activity Questionnaire (GPAQ) was
associated with lower odds for obesity, with an OR of 0.93 (95% CI 0.88, 0.98). We found a stronger association between transport and
obesity in the fully adjusted model: OR ¼0.67 (0.52–0.86) for obesity when comparing active vs motor travel among males. Steel et al.
merged public and motor vehicle transport into a single category. We highlighted the importance of differentiating the analysis be-
tween public and motor vehicle users. For instance, we found an OR for obesity among males of 0.64 (0.43–0.96) when comparing
public with motor vehicle use. Steel et al. adjusted for gender but did not show stratied results. Our ndings showed stronger
Fig. 1. Type of transport by gender, age, educational level, urban or rural zone. Chile, ENS 2016–2017*.
*Educational level (years of formal education): Low (<8), Medium (8–12) and high (>12).
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A. Passi-Solar et al.
Journal of Transport & Health 17 (2020) 100819
7
associations between transport and anthropometry in males, pointing out the relevance of gender-specic analyses. This gender
difference has been described by others (Falconer et al., 2015). Potentially, males tend to travel longer distances and perform more
vigorous physical activity than females. This may be a plausible hypothesis for Chile, given the results obtained from the analysis of the
GPAQ transport questions included in the ENS 2016–2017 (not shown) where males and females using active transport reported 79
and 58 min of transport-based physical activity, respectively. Associations of transport with vitamin D has been described in Chile
recently by Solis-Urra et al. (2019), using ENS 2016–2017 in women, but some concern arises with the absence of complex sampling
design on their variance estimation: variances are underestimated when complex sampling design is not considered. For instance,
using the complex sample design for variance estimation we did not nd a signicant association between transport and Vitamin D
among females aged �65y after adjusting for the confounding variables described by Solis-Urra (i.e. age, menopausal status, achieved
education level, geographical region, dairy consumption and sunlight exposure). According to our fully adjusted model for females
�65y, we found an association between transport and vitamin D, but after region, BMI and menopause were included in this model,
signicance was lost (results available on request). According to a meta-analysis based on prospective cohorts, active commuting was
signicantly related to lower incidence of coronary events, stroke and heart failure (Dinu et al., 2019). This decrease in cardiovascular
risk could be partially explained by the improvement on the lipid prole. Aligned with our results, Zwald et al. (2018), using the U.S.
Fig. 2. Transportation modal share by each geographical region Chile, ENS 2016–2017*.
*The regions have been organized in the same order they are located geographically, from north to south with the densest ones located at the centre
of the territory.
Fig. 3. Multinomial regression of associations between gender, age, educational level, place of residence and transport modes. Chile, ENS
2016–2017*.
*RRR ¼Relative Risk Ratio. RRR were calculated using multinomial logistic regression. Models were gender and age-adjusted. The reference
category for the outcome was motor vehicle. Educational level (years of formal education): Low (<8), Medium (8–12) and high (>12).
�
A. Passi-Solar et al.
Journal of Transport & Health 17 (2020) 100819
8
National Health and Nutrition Examination Survey (NHANES) 2007–2016, found lower LDL cholesterol among active transport users.
Active and public modes of transport could decrease WC, BMI and obesity by mechanisms related to higher energy expenditure
(Besser and Dannenberg, 2005; Voss et al., 2016). Mechanisms by which active modes of transport could reduce hepatic inammatory
markers and improve the lipid prole are still greatly unknown, but physical activity linked to transport could decrease hepatic fat and
in this way reduce hepatic inammation (Farzanegi et al., 2019) and could also enhance the use of lipids by skeletal muscles, reducing
plasma lipid levels (Wang and Xu, 2017).
In recent decades Chile has shown a systematic drift of trips from active and public transport to the automobile. Only recently, few
cities have seen an encouraging growth of bicycle trips, most noticeably Santiago. Interventions aiming to increase more active modes
of transport are described as major opportunities for the improvement of public health (Celis-Morales et al., 2017). Our associations
suggest that incidental physical activity related to mass population transport could have a major role in public health. Our results may
contribute to the formulation of policies or investments to shift modal share towards more active modes of transport, since on the one
hand, they describe the baseline distribution of the main type of transport modes and, on the other hand, they describe the magnitude
of anthropometric and metabolic benets linked to differentiated modes of transport. This study underpins active modes promotion
policies where walking and cycling could be promoted serving as feeders for the transportation system, particularly in small and
mid-sized cities, where public transport is less available. Variations in patterns of use of active modes in Chile by geographical regions
highlight the need for appropriate local policies allowing for a range of climates and geographic features. For instance, the south-
ernmost region of Chile (XII-Magallanes) had the least use of active transportation modes, which is congruent with its cold and windy
climate and high levels of obesity compared to other Chilean regions. However, authorities from Magallanes have recently invested in
17.5 km of new bike routes and announced 60 km more to be added. In Magallanes, reinforcing public transport could also serve as a
health-enhancing local policy. Specic populations such as the less educated, females, rural and older groups would benet greatly
from cycling and pedestrian-inclusive policies which may help to tackle socioeconomic health inequalities (Gao et al., 2017). Also,
investment in infrastructure could help to increase active modes (Langlois et al., 2016).
Some of this study’s strengths are the use of a big, nationally-representative sample of the adult general population, including all
socioeconomic groups from urban and rural areas; use of objective measures of health (i.e. not self-reported); analysis of public
transport as a separate transport mode (and not included with non-active modes) and adjusting for lifestyle risk factors (i.e. current
smoker, water intake, reduced-fat dairy consumption, fruit-vegetable consumption, alcohol use disorders and physical inactivity
during leisure time). However, our study has some limitations. The cross-sectional nature of the sample limits causal inferences, as
Fig. 4. Mean waist circumference, mean BMI and obesity (%) by type of transport and gender. Chile, ENS 2016–2017.
*BMI: Body Mass Index (kg/m
2
), Obesity: BMI�30 kg/m
2
.
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A. Passi-Solar et al.
Journal of Transport & Health 17 (2020) 100819
9
reverse causality and survival bias could be affecting our results. Moreover, other unobservable variables could affect our results (e.g.
motivation or availability of time), potentially introducing a bias towards rejecting the hypothesis of no association. Health status may
also inuence transport modes (healthier people choose more active modes): we did not adjust by health status, but we did adjust by
healthy lifestyles and benets were seen both in healthy and unhealthy lifestyle populations. Nevertheless, our ndings on obesity,
BMI and WC were consistent with population-based prospective longitudinal research, as reported by Flint et al. (2016) using the UK
Biobank data and by Qin et al. (2012) using the longitudinal China Health and Nutrition Survey data.
Chile has recently implemented policies for increasing the use of active transport modes, which is positive for health. The focus has
been in adding bicycle routes mostly in capital cities of each region and afuent areas of Santiago. From 2013 to 2018 the number of
bicycle lanes in Santiago increased 20-fold, from a total of 20 km of paths to 400 km, representing 10% of the cycling lanes in Latin
America (Ríos et al., 2015). Some other big cities, noticeably Rancagua, have followed this lead. Trafc calming areas, with maximum
speeds of 30 km/h, have been implemented in a few areas of Santiago (Ministerio de Transportes y Telecomunicaciones de Chile,
2014). INE, 2018, a new law regulating the ow of different modes in a road was passed. The law reduced the maximum speed of cars
from 60 to 50 km/h and ordered cyclists to use the road unless its cycling conditions were considered unsafe (Ministerio de Transportes
y Telecomunicaciones de Chile, 2018). Finally, pedestrianised streets have increased in business districts of a few Chilean cities, but
they are still quite insignicant. Including the same transport question in the next ENS will be key for surveillance of the health impacts
of transport policies and investments in transportation infrastructure. Including this question may be a low-cost surveillance method
that could be used by other countries. Future research using longitudinal data from the Chilean population would help to clarify the
causality of the associations between transport and objective measures, particularly if examined only among participants who were
Table 2
Mode of travel associations with anthropometric and metabolic markers by gender. Chile, ENS 2016–2017.
Males Females
Outcome Travel mode Sample
size
#
β Model 1 β Model 2 β Model 3 Sample
size
#
β Model 1 β Model 2 β Model 3
Anthropometry
Waist (cm) Active vs MV 1,958 5.76*** 5.33*** 5.20*** 3,418 1.73* 1.13 1.14
Public vs MV 5.72*** 4.02*** 3.91*** 1.41 0.79 0.96
Public vs
active
0.04 1.31 1.29 0.32 0.34 0.18
BMI (km/m
2
) Active vs MV 1,956 1.99*** 1.91*** 1.90*** 3,423 0.97** 0.82* 0.84**
Public vs MV 1.57*** 1.25*** 1.22*** 0.59 0.44 0.51
Public vs
active
0.42 0.67 0.67 0.37 0.38 0.34
Obesity (OR) Active vs MV 1,956 0.53*** 0.54*** 0.53*** 3,423 0.80 0.81 0.80
Public vs MV 0.60*** 0.64** 0.63** 0.82 0.84 0.82
Public vs
active
1.13 1.20 1.20 1.03 1.04 1.03
Metabolic markers
Vitamin D (ng/m)
[<50y]
Active vs MV N/A N/A N/A N/A 1,577 1.99** 2.00** 2.00**
Public vs MV N/A N/A N/A 0.85 0.85 0.75
Public vs
active
N/A N/A N/A 2.85*** 2.85*** 2.75**
Vitamin D (ng/m)
[�65y]
Active vs MV 446 2.10 2.02 3.99*** 792 2.42** 2.33* 2.56**
Public vs MV 2.17 2.22 2.07 0.05 0.14 0.26
Public vs
active
0.07 0.20 1.92 2.46** 2.47** 2.82**
Total Cholesterol (mg/
dL)
Active vs MV 1,256 16.45*** 15.26*** 13.78*** 2,210 4.75 7.24** 8.07**
Public vs MV 13.35*** 9.44** 8.58** 1.65 0.93 1.77
Public vs
active
3.09 5.83 5.20 6.40* 6.31* 6.30*
ALT (U/L) Active vs MV 1,321 6.31*** 6.37*** 5.82*** 2,293 2.06 1.76 2.08
Public vs MV 5.33** 5.54** 5.18** 1.01 0.71 0.98
Public vs
active
0.98 0.83 0.64 1.06 1.05 1.09
GGT (U/L) Active vs MV 1,325 4.52 3.54 2.57 2,301 3.88 2.52 2.06
Public vs MV 13.63*** 10.44*** 9.89*** 4.85** 3.48 3.86*
Public vs
active
9.11** 6.90* 7.32* 0.98 0.96 1.80
Note: *p<0.1, **p<0.05, ***p<0.01. Linear regression coefcients (β) for the association between transport mode and waist circumference, Body
Mass Index (BMI), vitamin D, total cholesterol, Alanine transaminase (ALT) and Gamma-Glutamyl transferase (GGT). Logistic regression Odds Ratio
(OR) for the association between transport mode and obesity (BMI �30 kg/m
2
). Model 1: non-adjusted; Model 2 adjusted for age and gender; Model 3:
adjusted for age, gender, smoking, water intake �6 glasses/day, reduced-fat dairy consumption, fruit and vegetable consumption �5 portion/day,
alcohol (AUDIT score) and frequency of physical activity during leisure time sedentarism. Vitamin D model 3 results were also adjusted for sunlight
exposure (self-reported as “little” or “a lot” in the last week). MV: Motor Vehicle; N/A: non-available data. #Model 1, 2 and 3 used the sample with
valid data in model 3.
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A. Passi-Solar et al.
Journal of Transport & Health 17 (2020) 100819
10
healthy at baseline, and thus did not base their mode choice on pre-existing impairments, and to understand the gender inequities we
found.
The evidence to support transport planning decisions in local communities is growing in Latin America, as part of the broader
spectrum of planning decisions that lead to healthy communities. There is no doubt that health is strongly related to the built envi-
ronment people live in (Koehler et al., 2018) and transport is a very important component of this environment and vice versa.
5. Conclusions
In Chile, both active transport (cycling and walking) and public transport use were associated with multiple nutritional and
metabolic benets such as lower BMI, lower waist circumference, less obesity, higher vitamin D, lower cholesterol and lower hepatic
inammation. Stronger benets were seen in males than in females. These ndings are important evidence for transport planning
policies and a great opportunity for the local design of population-wide preventive strategies to tackle chronic diseases, decrease
gender, regional and socioeconomic inequities and to improve the quality of life of the population.
Financial disclosure
ENS 2016–2017 was funded by the Chilean Ministry of Health. Vitamin D laboratory analyses were funded by the Ponticia
Universidad Cat�
olica de Chile’s School of Medicine. The authors did not receive any specic funding for this work.
CRediT authorship contribution statement
�
Alvaro Passi-Solar: Methodology, Formal analysis, Investigation, Data curation, Writing - original draft. Paula Margozzini:
Methodology, Investigation, Writing - original draft, Supervision. Andrea Cortinez-O’Ryan: Writing - original draft, Writing - review
& editing. Juan C. Mu~
noz: Methodology, Writing - original draft. Jennifer S. Mindell: Conceptualization, Methodology, Writing -
review & editing, Supervision.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.jth.2019.100819.
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