einstein. 2016;14(4):461-7
ORIGINAL ARTICLE
This content is licensed under a Creative Commons Attribution 4.0 International License.
ABSTRACT
Objective: To analyze the levels of physical activity and sedentary
behavior in adolescents living in urban and rural areas. Methods:
An epidemiological, cross-section study with quantitative design,
carried out at the regional level. The sample comprised 6,234 students
aged 14 to 19 years, selected using random cluster sampling. The
χ² test and binary logistic regression were used in the analysis.
Results: A total of 74.5% of adolescents lived in urban areas. After
adjustment, rural residents spent less time watching television
(odds ratio – OR: 0.45; 95% confidence interval – 95%CI: 0.39-0.52),
using a computer and/or playing video games (OR: 0.30; 95%CI:
0.22-0.42), or sitting down (OR: 0.66; 95%CI: 0.54-0.80); chose
passive leisure less often (OR: 0.83; 95%IC: 0.72-0.95) and were
less likely to be classified as insufficiently active (OR: 0.88; 95%IC:
0.78-0.99) when compared to urban residents, regardless of sex or
age. The fact that adolescents living in rural areas who did not work
were more likely to be classified as insufficiently active (OR: 2.59;
95%CI: 2.07-3.24) emphasized the significant role of occupation
in physical activity levels in this group. Conclusion: Adolescents
living in rural areas were less exposed to the sedentary behaviors,
chose more active leisure, and had higher levels of physical
activity. Place of residence and occupation may play a major role in
youth lifestyle.
Keywords: Motor activity; Adolescent behavior; Sedentary lifestyle;
Urban population; Rural population
1
Universidade de Pernambuco, Recife, PE, Brazil.
2
Centro Universitário Asces-Unita, Caruaru, PE, Brazil.
3
Faculdade Boa Viagem, Recife, PE, Brazil.
4
Universidade Federal de Pernambuco, Recife, PE, Brazil.
Corresponding author: Luciano Machado Ferreira Tenório de Oliveira – Avenida Engenheiro Domingos Ferreira, 3,181, building Janaína, room 301 – Boa Viagem – Zip code: 51020-035 – Recife, PE, Brazil
Phone: (55 81) 3466-8043 – E-mail: luciano2308@hotmail.com
Received on: June 20, 2016 – Accepted on: Oct 25, 2016
Conflict of interest: none.
DOI: 10.1590/S1679-45082016AO3788
RESUMO
Objetivo: Analisar os níveis de atividade física e o comportamento
sedentário em adolescentes das áreas urbanas e rurais. Métodos:
Estudo epidemiológico, transversal, com abordagem quantitativa e
abrangência estadual, cuja amostra foi constituída por 6.234 estudantes
(14 a 19 anos), selecionados por meio de uma estratégia de amostragem
aleatória de conglomerados. As análises foram realizadas por meio
do teste χ² e da regressão logística binária. Resultados: Na amostra,
74,5% dos adolescentes eram residentes em área urbana. Após o
ajuste, constatou-se que os adolescentes oriundos da área rural usavam
menos televisão (odds ratio – OR: 0,45; intervalo de confiança de 95% –
IC95%: 0,39-0,52), computador e/ou videogame (OR: 0,30; IC95%: 0,22-
0,42), passavam menos tempo sentados (OR: 0,66; IC95%: 0,54-0,80),
optaram menos pelo lazer passivo (OR: 0,83; IC95%: 0,72-0,95) e tinham
menos chances de serem classificados como insuficientes ativos (OR:
0,88; IC95%: 0,78-0,99), quando comparados àqueles que residiam na
área urbana, independentemente do sexo e da idade. Os adolescentes
da área rural que não trabalhavam apresentaram mais chances de
serem classificados como insuficientemente ativos (OR: 2,59; IC95%:
2,07-3,24), mostrando que a ocupação tinha um papel importante
no nível de atividade física deste grupo. Conclusão: Os adolescentes
residentes na área rural estiveram menos expostos aos comportamentos
sedentários, optaram mais por um lazer ativo e apresentaram um melhor
nível de atividade física, podendo a zona de domicílio e a ocupação
influenciar no estilo de vida deles.
Descritores: Atividade motora; Comportamento do adolescente;
Estilo de vida sedentário; População urbana; População rural
Urban versus rural lifestyle in adolescents:
associations between environment, physical
activity levels and sedentary behavior
Estilos de vida urbano versus rural em adolescentes: associações entre
meio-ambiente, níveis de atividade física e comportamento sedentário
Manuela Ferreira Regis
1
, Luciano Machado Ferreira Tenório de Oliveira
2,3
, Ana Raquel Mendes dos Santos
1
,
Ameliane da Conceição Reubens Leonidio
1
, Paula Rejane Beserra Diniz
4
, Clara Maria Silvestre Monteiro de Freitas
1
einstein. 2016;14(4):461-7
462
Regis MF, Oliveira LM, Santos AR, Leonidio AC, Diniz PR, Freitas CM
INTRODUCTION
Adolescence is characterized by biological, physical,
psychological and social changes, with potential direct
impacts on daily activities.
(1)
The number of youth who
do not comply with the World Health Organization
recommendations on daily physical activity is on
the rise.
(2-4)
Several factors may account for this
scenario, such as time spent on electronic devices,
(5)
passive travel to school,
(6)
lack of Physical Education
in schools,
(2)
limited access to settings providing
opportunities for physical activity,
(2)
lack of maternal
physical activity
(7)
and low schooling and income
levels.
(8)
These are alarming facts, which may be
related to developing chronic degenerative disease
and mortality risks.
(9,10)
Studies with different designs suggest that both
the level of physical activity and fitness of youth and
adults are related to, or may be influenced by, the
environmental context in which they live.
(11)
Given the
environment is a determining factor of lifestyle, people
living few kilometers apart, in the same geographical
area, may have different lifestyles when it comes
to physical activity, particularly when rural and
urban areas are compared.
(12)
Greater availability of
equipment and public leisure spaces in urban areas,
such as squares, courts, pedestrian boulevards and bike
paths, may be associated with high levels of physical
activity.
(5,13)
Urban and rural areas may be associated with two
different lifestyles
(14)
and environment characteristics
may contribute to lower levels of physical activity and
fitness in adolescents.
(4,8)
However, studies addressing
physical activity levels and sedentary behavior in
adolescents living in rural areas are scarce, and few
studies control for these variables in the analysis.
Such data may be used to plan interventions aimed
to promote healthier habits among adolescents, in an
effort to reduce health problems in adulthood, given
the associations between diseases and risk behaviors at
a younger age.
(4,15)
OBJECTIVE
To analyze the levels of physical activity and sedentary
behavior in adolescents living in urban and rural areas,
in the light of socioenvironmental characteristics.
METHODS
This is a descriptive study with quantitative design
involving cross-sectional school-based epidemiological
surveys at the municipal level. The study sample
comprised male and female students aged 14 to
19 years enrolled in public high schools, in the
State of Pernambuco, Brazil. Improperly filled out
questionnaires, students who were absent at the time
of data collection or those who refused to participate
were excluded. The survey was entitled “Physical
activity practice and health risk behaviors in high
school students in the State of Pernambuco: a temporal
trend study”.
Two-stage cluster sampling was used in this study.
In the first sampling stage, schools were randomly
selected according to size and geographical location
to serve as sampling units. Groups of students were
then drawn according to school hours and grades in
the selected schools.
A pilot study was conducted to test the applicability
of the instrument prior to data collection. Data were
collected at a randomly selected reference public school
in the city of Recife (PE), from a sample comprising
86 adolescents.
Reproducibility indicators had moderate to high
intraclass correlation coefficients for variables employed
in this study. Agreement coefficients (kappa index)
were as follows: 0.78 for watching television; 0.62 for
playing videos games and/or working on a computer; 0.44
for time spent sitting down (screen time excluded); 0.67
for favorite leisure activity; 0.59 for level of physical
activity and 1.00 for place of residence.
Data were collected during the first (May and June)
and second (August through November) terms of 2011.
Adolescent classification as urban or rural residents was
based on self-reported place of residence in a previously
tested, self-administered translated version of the
Global School-Based Student Health Survey (GSHS),
proposed by the World Health Organization. The
following domains were used: “personal information”,
“physical activities” and “behavior at home and in
school”.
The variables associated with sedentary behaviors
were “time spent watching television”, determined by
calculation of the weighted mean of the answers given
to the following questions: “On school days (Monday
through Friday), how many hours do you spend watching
television per day?”, and “On weekends (Saturday
and Sunday), how many hours do you spend watching
television per day?” (question 1x5 + question 2x2)/7.
The variable “time spent on a computer and/or
playing video games” was determined by the weighted
mean of the answers given to the following questions:
463
Urban versus rural lifestyle in adolescent
einstein. 2016;14(4):461-7
“On school days (Monday through Friday), how many
hours do you spend on a computer and/or playing video
games per day?”, and “On weekends (Saturday and
Sunday), how many hours do you spend on a computer
and/or playing video games per day?”.
The variable “time spent sitting down (screen
time excluded)” was investigated by calculating the
weighted mean of the answers given to the following
questions: “On school days (Monday through Friday),
how many hours do you spend sitting down chatting
with friends, playing cards or dominoes, talking on the
telephone, commuting as driver or passenger, reading
or studying (time spent watching television or using a
computer excluded)?”, and “ On weekends (Saturday
and Sunday), how many hours do you spend sitting
down chatting with friends, playing dominoes or cards,
talking on the telephone, commuting as driver or
passenger, reading or studying (time spent watching
television or using a computer excluded)?”. Sedentary
behaviors were classified as less or more than 4 hours
of exposure.
As regards the variable “level of physical activity”,
two GSHS questions were considered: “During the last
7 days, how many days were you physically active for a
total of at least 60 minutes per day?” and “In a typical
or usual week, how many days are you physically active
for a total of at least 60 minutes per day?”. Physical
activity level assessment (questions 1 and 2) was
based on the formula suggested by Prochaska et al.
(16)
:
(question 1+ question 2)/2. Adolescents achieving
values lower than 5 days were considered insufficiently
active (i.e., non-compliant with physical activity
recommendations). The favorite leisure activity was
divided as active (sports, physical exercise, swimming
or bicycling) or passive leisure (playing dominoes or
cards, watching television, playing video games, using
computers or chatting with friends) as performed in
previous study.
(6)
Data were tabulated using EpiData (version 3.1) and
electronically controlled data entry. Double data entry
verification was used to ensure data entry consistency.
Typing errors were tracked using the VALIDADE
tool and corrected. Data analysis was performed using
software (Statistical Package for the Social Sciences,
SPSS; version 10.0 for Windows).
Inferential and descriptive statistic procedures were
used. Absolute and relative frequency distributions
were constructed in descriptive analysis. The Pearson’s
χ² test was used in inferential analysis to investigate
isolated associations between level of physical activity
and place of residence (urban or rural area), and to
investigate variables included in the model, explore
potential confounding factors and check the need for
statistical adjustment in the analyses. Multivariate
analysis was based on binary logistic regression; odds
ratio (OR) estimates and 95% confidence intervals
(95%CI) were used to express the degree of association
between dependent (level of physical activity, sedentary
behavior and favorite leisure activity) and independent
variables (place of residence), with adjustment for
potential confounding factors (sex, age, occupation
and maternal schooling). Interactions between level
of physical activity, place of residence and gender
were tested following the determination of variables
predicted in the final model.
Confounding variables were introduced simultaneously
(Enter method) and only those with significance levels
below 0.20 (p<0.20) retained. Only significant variables
were included in the final regression model. Results
were presented as crude and adjusted OR values,
and 95%CI; results were considered significant when
p<0.05.
This study was approved by the Ethics Committee
for Research Involving Humans, of the Universidade
de Pernambuco, protocol number 159/10, CAAE:
0158.0.097.000-10. An Informed Consent Form was
signed by parents of minors and by students aged over
18 years.
RESULTS
Eighty-five schools in 48 cities within the State of
Pernambuco were visited. The data collection flowchart
is presented in figure 1; the final sample comprised 6,234
adolescents aged 14-19 years, of which 59.7% were
girls. Overall, 53.4% adolescents were aged between 16
and 17 years, and 74.5% lived in urban areas. Of those
living in rural areas, 28.3% worked (Table 1).
Students living in rural areas had healthier habits
as compared to those living in urban areas, as shown
by preference for active leisure activities (43.2% versus
39.5%), shorter sitting down time (90.1% versus 83.7%),
less computer and/or video game exposure (97.1%
versus 88.1%), less television exposure (88.7% versus
86.0%) and higher levels of physical activity (37.3%
versus 34.5%) (Table 2).
One model was constructed for each behavior.
The variables were adjusted for sex, age, occupation
and maternal schooling; only variables with p<0.20
were retained in the model. Adjustments revealed
einstein. 2016;14(4):461-7
464
Regis MF, Oliveira LM, Santos AR, Leonidio AC, Diniz PR, Freitas CM
Table 1. Characteristics of adolescents living in urban and rural areas
Variables
Urban
(n=4,646)
Rural
(n=1,588)
Total
(n=6,234)
p value
n (%) n (%) n (%)
Sex
Male 1,878 (40.4) 640 (40.3) 2,524 (40.3) 0.938
Female 2,766 (59.6) 947 (59.7) 3,737 (59.7)
Age, years
14-15 983 (21.2) 357 (22.5) 1,350 (21.6) 0.099
16-17 2,554 (55.0) 779 (49.1) 3,345 (53.4)
18-19 1,109 (23.8) 452 (28.4) 1,569 (25.0)
Occupation
Works 938 (20.2) 448 (28.3) 1,390 (22.3) <0.001
Does not work 3,697 (79.8) 1,135 (71.7) 4,857 (77.7)
Maternal schooling,
years of education
>8 1,669 (41.2) 228 (17.2) 1,903 (35.3) <0.001
≤8 2,378 (58.8) 1,100 (82.8) 3,491 (64.7)
Table 2. Level of physical activity and sedentary behaviors among adolescents
living in urban and rural areas
Variables
Urban
(n=4,646)
Rural
(n=1,588)
Total
(n=6,234)
p
value
n (%) n (%) n (%)
Level of physical activity
Active 1,596 (34.5) 591 (37.3) 2,192 (35.1) 0.041
Insufficiently active 3,031 (65.5) 992 (62.7) 4,047 (64.9)
Time spent watching
television, hours
<4 3,988 (86.0) 1,404 (88.7) 5,420 (86.5) 0.006
≥4 647 (14.0) 178 (11.3) 826 (13.2)
Time spent using a computer
and/or playing video games,
hours
<4 4,081 (88.1) 1,537 (97.1) 5,647 (90.5) <0.001
≥4 549 (11.9) 46 (2.9) 596 (9.5)
Time spent sitting down
(screen time excluded), hours
<4 3,848 (83.7) 1,412 (90.1) 5,286 (85.4) <0.001
≥4 749 (16.3) 155 (9.9) 907 (14.6)
Favorite leisure activity
Active leisure
*
1,621 (39.5) 611 (43.2) 2,241 (40.4) 0.015
Passive leisure
†
2,483 (60.5) 804 (56.8) 3,305 (59.6)
* Active leisure: sports, physical exercise, swimming or bicycling;
†
Passive leisure: playing dominoes or cards, watching
television, playing video games, using a computer or chatting with friends.
that adolescents living in rural areas had lower risks of
exposure to computer and/or video games (OR=0.30;
95%CI: 0.22-0.42), television (OR=0.45; 95%CI: 0.39-0.52)
and sitting down time excluding screen time (OR=0.66;
95%CI: 0.54-0.80).
As regards physical activity, adolescents living
in rural areas were less likely of falling within the
insufficiently active category, regardless of sex
(OR=0.88; 95%CI: 0.78-0.99). However, this association
became non-significant following adjustment for
occupation (OR=0.94; 95%CI: 0.83-1.06) (Table 3). The
investigation of associations between occupation and
level of physical activity was limited to adolescents
living in rural areas; the fact that the likelihood of being
categorized as insufficiently active was higher among
those who did not work (OR=2.59; 95%CI: 2.07-3.24)
emphasizes the significant role of work in relation to
physical activity among adolescents living in rural areas.
No interactions were found between level of physical
activity, place of residence and sex (0.21); therefore, sex
stratification was not used in the analysis.
DISCUSSION
Adolescents living in rural areas had higher levels of
physical activity, showed less preference for passive
leisure and were less exposed to sedentary behaviors
compared to adolescents living in urban areas.
This more active lifestyle may be associated with
participation in the labor market, consisting mainly
of physical labor in subsistence agriculture
(17,18)
and
common household activities performed by women
living in rural areas.
(19)
This finding differs from other
studies
(5,20)
that reported higher likelihood of being
classified as insufficiently active among adolescents
living in rural areas, due to greater availability of public
Figure 1. Flowchart representing the inclusion of students of the State of
Pernambuco in the study
465
Urban versus rural lifestyle in adolescent
einstein. 2016;14(4):461-7
leisure spaces (squares, sport centers and public courts)
in urban compared to rural areas. Hence, inclusion of
adolescents living in rural areas evaluated in this study in
the labor market was thought to be an important factor
behind the higher levels of physical activity documented
in this group.
Leisure-related physical activity is thought to be
one of the most important dimensions of physical
activity,
(17)
given 55% to 65% of moderate to vigorous
activities undertaken by children and adolescents fall
within this category.
(9)
This study revealed that youth
living in rural areas tended to have lower preference for
leisure activities involving lower energy expenditure,
such as playing dominoes or cards, watching television,
playing video games, using a computer or chatting with
friends. Similarly, recent studies have documented high
prevalence of such sedentary behaviors and low levels of
physical activity among youth living in urban areas,
(21,22)
which may reflect ease of access to technological devices,
particularly computers.
(23)
The fact that most youth who
spend excessive amounts of time on a computer do not
comply with recommended physical activity levels has
also been reported,
(24)
and suggests the replacement of
physical activity for sedentary behaviors.
(17)
Individual (motivation, self-efficacy, motor skills
and other health-related behaviors) and environmental
(access to labor or leisure spaces, costs, sociocultural
support and limited time availability) characteristics
may impact on physical activity levels and acquisition
of sedentary behaviors.
(25)
Time constraints are thought
to be a major reason underpinning insufficient physical
activity levels and/or sedentary behaviors. Still, this
factor was not significant in this study, given youth
living in rural areas were more physically active, even
though they entered the labor market sooner. Physical
Education lessons at school may also influence physical
activity levels,
(4,26)
as may parental behavior,
(27)
bearing
in mind that the family is the first learning environment
of children and adolescents.
As regards parental influences, maternal schooling
may play a role in youth lifestyle. Studies suggest
maternal schooling (low to intermediate) is significantly
associated with exposure to insufficient levels of physical
activity and acquisition of sedentary behaviors.
(28,29)
However, this study revealed that maternal schooling
was lower among adolescents living in rural compared
to those living in urban areas, even though the former
were more phsically active and less exposed to sedentary
behaviors. This may reflect the relation between low
parental schooling and lower socioeconomic status
(30)
and the resulting limited access to electronic devices
(computer, video games and television), which would
decrease the likelihood of adherence to sedentary
behaviors among adolescents living in rural areas, and
encourage higher levels of physical activity, in the form
of greater use of active transportation means in daily
Table 3. Relationship between place of residence (urban or rural area), level of physical activity and sedentary behaviors
Variables
Adolescents living in rural areas
Odds ratio
95%CI p value
Odds ratio
95%CI p value
(crude) (adjusted)
Level of physical activity
*
Active 1 1
Insufficiently active 0.88 0.78-0.99 0.041 0.94 0.83-1.06 0.29
Time spent using watching television, hours
†
<4 1 1
≥4 0.78 0.65-0.93 0.006 0.45 0.39--0.52 <0.001
Time spent using a computer and/or playing video games, hours
‡
<4 1 1
≥4 0.22 0.16-0.30 <0.001 0.30 0.22-0.42 <0.001
Time spent sitting down (screen time excluded), hours
‡
<4 1 1
≥4 0.56 0.47-0.68 <0.001 0.66 0.54-0.80 <0.001
Favorite leisure activity
§
Active leisure
¶
1 1 0.008
Passive leisure
||
0.86 0.76-0.97 0.015 0.83 0.72-0.95
* Adjusted for sex and occupation;
†
adjusted for age and occupation;
‡
adjusted for sex, age, maternal schooling and occupation;
§
adjusted for sex and occupation;
¶
active leisure: sports, physical exercise, swimming or bicycling;
||
passive leisure: playing
dominoes or cards, watching television, playing video games, using a computer or chatting with friends.